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UNIVERSIDADE ESTADUAL DE CAMPINAS

INSTITUTO DE BIOLOGIA

IVAN JEFERSON SAMPAIO DIOGO

BIOGEOGRAPHY AND DIVERSITY OF HUMID MOUTAIN

FORESTS IN NORTHEASTERN, BRAZIL

BIOGEOGRAFIA E DIVERSIDADE DE FLORESTAS

SERRANAS ÚMIDAS DO NORDESTE DO BRASIL

CAMPINAS

2017


IVAN JEFERSON SAMPAIO DIOGO

BIOGEOGRAPHY AND DIVERSITY OF HUMID MOUTAIN FORESTS IN NORTHEASTERN, BRAZIL

BIOGEOGRAFIA E DIVERSIDADE DE FLORESTAS SERRANAS ÚMIDAS DO NORDESTE DO BRASIL

Thesis presented to the Institute of Biology of the University of Campinas in partial fulfillment of the requirements for the degree of Doctor in Plant Biology.

Tese apresentada ao Instituto de Biologia da Universidade Estadual de Campinas como parte dos requisitos exigidos para a obtenção do Título de Doutor em Biologia Vegetal.

Orientador: FLAVIO ANTONIO MAËS DOS SANTOS Co-Orientador: ITAYGUARA RIBEIRO DA COSTA

CAMPINAS

2017

ESTE ARQUIVO DIGITAL CORRESPONDE À

VERSÃO FINAL DA TESE DEFENDIDA PELO

ALUNO IVAN JEFERSON SAMPAIO DIOGO E

ORIENTADA PELO PROF. DR. FLAVIO

ANTONIO MAËS DOS SANTOS


Agência(s) de fomento e nº(s) de processo(s): CNPq, 140822/2013-5; CNPq, 234983/2014-0 ORCID: http://orcid.org/0000-0002-5440-9851

Ficha catalográfica Universidade Estadual de Campinas

Biblioteca do Instituto de Biologia Mara Janaina de Oliveira - CRB 8/6972

Diogo, Ivan Jeferson Sampaio, 1988- D621b DioBiogeography and diversity of humid mountain forests in Northeastern,

Brazil / Ivan Jeferson Sampaio Diogo. – Campinas, SP : [s.n.], 2017.

DioOrientador: Flavio Antonio Maës dos Santos. DioCoorientador: Itayguara Ribeiro da Costa. DioTese (doutorado) – Universidade Estadual de Campinas, Instituto de

Biologia.

Dio1. Topografia. 2. Carbono. 3. Zoocoria. 4. Pólen. 5. Biodiversidade -

Brasil, Nordeste. I. Santos, Flavio Antonio Maës dos, 1958-. II. Costa,

Itayguara Ribeiro. III. Universidade Estadual de Campinas. Instituto de

Biologia. IV. Título.

Informações para Biblioteca Digital

Título em outro idioma: Biogeografia e diversidade de florestas serranas úmidas

do Nordeste do Brasil Palavras-chave em inglês: Topography Carbon Zoochory Pollen Biodiversity - Brazil, Northeast Área de concentração: Biologia Vegetal Titulação: Doutor em Biologia Vegetal Banca examinadora: Flavio Antonio Maës dos Santos [Orientador] Leonardo Dias Meireles Pedro Vasconcellos Eisenlohr Ingrid Koch Gustavo Hiroaki Shimizu Data de defesa: 22-11-2017 Programa de Pós-Graduação: Biologia Vegetal

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Campinas, 22 de novembro de 2017.

COMISSÃO EXAMINADORA

Prof. Dr. Flavio Antonio Maës dos Santos

Prof. Dr. Leonardo Dias Meireles

Prof. Dr. Pedro Vasconcelos Eisenlohr

Prof.(a). Dr.(a). Ingrid Koch

Dr. Gustavo Hiroaki Shimizu Os membros da Comissão Examinadora acima assinaram a Ata de defesa, que se encontra no processo de vida acadêmica do aluno.

5


AGRADECIMENTOS

Não é nada fácil começar, cursar e (principalmente!) terminar um doutorado. A gente encontra um bilhão

de percalços nessa estrada. No entanto, conhecemos e reconhecemos pessoas maravilhosas que nos dão

força e carinho na trajetória (e que trajetória!). Tentei estabelecer uma regra cronológica de

agradecimento, embora as lembranças tenham me feito choramingar um pouco.

Aos meus pais, Sr. Diogo e Sra. Cristina, por todos os ensinamentos, dedicação e apoio

que me deram durante toda a minha vida acadêmica. Sem vocês não seria a pessoa que

sou hoje, suas virtudes me fizeram um homem melhor. Obrigado, pois mesmo sem

acreditar, vocês me permitiram voar. Ainda aqui, a minha irmã, pela companhia, força

e desejos de sucesso.

Sem dúvida, uma das pessoas que mais me estimulou durante todo o processo de

doutorado, foi o meu eterno orientador, Itayguara Ribeiro. A você, pela força,

compreensão, discussões, trabalhos, tabelas, exsicatas, campos, estufas, identificações,

envio de folhas, aquelas cervejinhas e conversas aleatórias, muitíssimo obrigado por

manter viva essa chama em mim.

Ao meu orientador de doutorado, Flavio Mäes, por ter me recebido de braços abertos na

UNICAMP. Por aceitar um novo desafio científico e estar sempre disponível para

conversas e questionamentos.

À Karin Santos, porque sem seu apoio de campo e amizade, eu não conseguiria ter feito

esse doutorado. Além do abrigo em Estocolmo. Muito obrigado!

Ao CNPq, pela bolsa de doutorado e doutorado sanduíche concedidas.

Aos docentes e pesquisadores afiliados à UNICAMP, Jorge Tamashiro, Fernando

Roberto Martins, Simone Aparecida Vieira, Ricardo Ribeiro Rodrigues, Luciana

Alves, Valéria Martins, pelas contribuições e ensinamentos durante o curso.

Aos meus colegas de curso e laboratório, Carol Signori, Ana Liboni, Cris Yuri, Raquel

Mourura, Fernanda Barros, Lu, Anninha, Cinthia, Júnior, Isa, Azul, Gus, João,

Nathi, Rafa Guimarães, Caio, Thaís, Magda, pela companhia, ajudas acadêmicas,

farras, cervejas, churras e IFCH. Em especial à Fernanda Cabral, por sempre me apoiar

e acreditar em mim, me ajudando sempre que possível, pelos vinhos, conversas e o amor

(até na Suécia); e à Gigi, por me auxiliar nas identificações, sempre dizer palavras lindas

de carinho e cozinhar aquele maravilhoso cheesecake.

Aos meus companheiros da rep nuvem, em especial Ruan Mariano e Rafhael Parintins,

por me acolherem super bem, darem as melhores festas, compartilhar todas as refeições,

conversar besteira e me fazerem me sentir em casa. Às minhas companheiras da melhor

casinha, Mônica, Thaís pelas pizzas, festinhas, composteira, e melhor uso do quintal de

casa; em especial, à Carol Potas, pelas lindas lembranças morando juntos, os vinhos

tomados, os apoios dados, tristezas e alegrias compartilhas, os papos cabeça e a grande

amizade.

Aos meus amigos de Campinas, Pira e Rafael, por me apresentar aos locais bonitos da

cidade e sempre me levarem pra beber com o objetivo de esquecer um pouco do

doutorado. Magnum, Rafa Guimarães e Neto, pelas lindas sexta-feiras pelas quais eu

6


esperava ansiosamente. Vizinho e Antonielle pela companhia maravilhosa, festinhas

usuais e conversas mais loucas. Abel, pela amizade inesperada e acolhida tão boa.

Ao prof. Dr. Alexandre Antonelli, por me fazer se sentir tão bem acolhido em uma

instituição como a Universidade de Gotemburgo. Agradeço a oportunidade, o empenho,

a ajuda e, principalmente, o fato de acreditar em mim.

To the AntonelliLab team, for being so lovely and kind with me in the new life abroad.

In special, to Anna and Ylva, who helped me a lot in different ways. To Alex Zizka,

Tobi, Eric, Romina, Fernanda, Thaís, Bruno, Angela, Kemal, Victor and Josué for

receive me in a such a nice group (with discussion and parties). To Božo, for being more

than a lab mate, but a friend for the entire life. To my special Swedish friends, Mia, Juan

and Nicklas, for the support out of the university and the great birthday celebration. In

special to Camila, Victor Gonçalez and Daniela to show me the meaning of partnership,

friendship and happiness in other country.

Aos meus amigos cearenses que sempre me deram apoio nessa conquista, Lilian, por

sempre me encorajar com palavras de carinho e positividade quando eu mais precisava.

Fernando, por estar sempre ao meu lado e não largar essa amizade ao ouvir as lamúrias

da vida acadêmica. Ao Alexandre Holanda, por compartilhar as amarguras do

doutorado, mas também as alegrias e os artigos. Ao Hilton Galvão, por sempre me

colocar pra cima e ajudar com piadinhas infames e por Copenhagen. Ao Luiz Filho, por

ser essa fonte de doçura e força. Ao Vinícius Bonjerbar, por ser mais do que

companheiro nos meus momentos tensos quando estive distante. Ao paraibano mais fofo,

Marcelo Ramos, por me dar força e alegria quando mais precisei, pelas horas de

conversas afáveis e pelo inigualável sentimento desenvolvido.

Muito obrigado, de coração!

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RESUMO

Os eventos de glaciação e deglaciação durante o Pleistoceno aceleraram a disjunção das

florestas úmidas da América do Sul, ocasionando retração e expansão de formações

vegetais e alta diversidade biológica dos Neotrópicos. As florestas serranas localizadas

no semiárido nordestino são consideradas um dos ambientes mais sensíveis às variações

climáticas e uma das melhores áreas para estudar a dinâmica e os efeitos da (de)glaciação

mundial. As perguntas norteadoras desse trabalho foram: 1) Qual a composição florística,

diversidade e como se estrutura a Serra de Maranguape?, 2) Como a flora da Serra de

Maranguape se relaciona com as outras fitofisionomias do estado do Ceará?, 3) Qual a

composição palinológica das Serras de Maranguape, Baturité e Pacatuba?, 4) Como a

distribuição da vegetação está relacionada com a chuva polínica atual?, 5) Qual a relação

entre as florestas serranas úmidas do Noredeste brasileiro, 6) Quais são e como as

variáveis ambientais explicam a distribuição de espécies em escalas local e regional?, 7)

Como essas florestas estão relacionadas com os outros domínios brasileiros? e 8) Estas

florestas podem ser classificadas como uma única unidade florística? A Serra de

Maranguape possui uma clara distinção florística entre barlavento, sotavento e topo, com

a prevalência de Myrtaceae em locais mais úmidos e Fabaceae nos mais secos. Diferença

que também foi encontrada nas florestas de Baturité e Pacatuba, tanto na vegetação

quanto na chuva polínica. Ao compararmos a chuva polínica com a vegetação atual, o

predomínio de Myrtaceae é característico dessas áreas, no entanto, observamos pólens

que não estão presentes na vegetação atual e vice-versa. As áreas próximas do topo

apresentam características de florestas nebulares e condições edáficas distintas. Sotavento

é a área mais rica e diversa, com uma flora distinta e compartilhada com as diversas

fitofisionomias locais, entretanto, sua composição varia significativamente de uma serra

pra outra. Analisando as 17 florestas serranas úmidas nordestinas, verificamos uma

distinção clara entre as florestas mais ao norte (Ceará) e as mais ao sul (Pernambuco,

Paraíba e Sergipe). Temperatura e pluviosidade inluenciam a distribuição local de

espécies e pólen nas florestas serranas. Por outro lado, quando consideramos a escala

regional, verificamos que fatores edáficos (carbono orgânico) e ecológicos (zoocoria) são

responsáveis pela distribuição de espécies nas florestas serranas nordestinas. As florestas

serranas nordestinas são uma bioregião única e distinta com características próprias e

espécies indicadoras, como Guettarda angelica e Manilkara rufula.

Palavras-chave: temperatura, precipitação, sotavento, carbono orgânico, zoocoria,

pólen, bioregião.

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ABSTRACT

The events of glaciation and deglaciation during the Pleistocene accelerated the the South

American rainforest disjunction, leading to the retraction and expansion of plant

formations and Neotropics’ high biological diversity. The semi-arid montane forests are

greatly affected by climatic variations, thus, one of the best areas to study the dynamics

and effects of the (de)glaciation. As guiding questions of this study: 1) What is the

floristic composition, diversity, and structure of Serra de Maranguape? 2) How is the flora

of Serra de Maranguape related to other phytophysiognomies in the Ceará state? 3) What

is the palynological composition of the Serra de Maranguape, Baturité and Pacatuba? 4)

How is the distribution of vegetation related to the current pollen rain? 5) What is the

relationship between the humid mountain forests of the Brazilian Northeast? 6) Which

are an how the environmental variables explain the distribution of species at local and

regional scales? 7) How those mountain forests are related to the other domains? and 8)

Do they represent a single floristic unit? The Serra de Maranguape has a clear floristic

distinction among windward, leeward and top, with a prevalence of Myrtaceae in humid

places and Fabaceae in the driest. This difference was also found in Baturité and Pacatuba

forests, both in the vegetation and in the pollen rain. When we compared the pollen rain

with current vegetation, the predominance of Myrtaceae is a clear characteristic of these

areas, however, we observe pollen that is not present in the current vegetation and vice

versa. The areas near to the top have nebular forests characteristics and different edaphic

conditions, with pollen and species of heliophilous and pioneer plants (Alchornea,

Miconia and Clusia). Leeward is the richest and most diverse area with a distinct flora,

which is shared with the various local phytophysiognomies, however, its composition

varies significantly from one mountain range to another. Analyzing the 18 northeastern

mountain forests, we found a clear distinction between the northernmost forests (Ceará)

and the southern (Pernambuco, Paraíba e Sergipe). Temperature and rainfall affect the

species and pollen local distribution in the mountain forests of Ceará. On the other hand,

when we consider the regional scale, we verified that edaphic (organic carbon) and

ecological factors (zoochory) are responsible for the distribution of species in the

northeastern mountain forests. The Brazilian Northeastern Mountain Forests are a distinct

and unique bioregion with its own chacteristic and indicator species, such Guettarda

angelica and Manilkara rufula.

Key words: temperature, precipitation, leeward, organic carbon, zoochory, pollen rain,

bioregion.

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SUMÁRIO

INTRODUÇÃO GERAL..……......................................................................................10

CHAPTER I - VEGETATION STRUCTURE, SPECIES COMPOSITION AND

DISTRIBUTION IN A TOPOGRAPHIC GRADIENT OF A MOUNTAIN FOREST,

NORTHEASTERN BRAZIL ……………......................................................................18

CHAPTER II- POLLEN-BASED CHARACTERIZATION OF MONTANE FOREST

TYPES IN NORTH-EASTERN BRAZIL.......................................................................47

CHAPTER III- DISPERSAL AND EDAPHIC FACTORS DRIVING PLANT SPECIES

COMPOSITION IN MOUNTAIN FORESTS IN A SEMIARID REGION

OF BRAZIL.....................................................................................................................77

CHAPTER IV- ELEVATIONAL GRADIENTS OF MOIST FOREST IN BRAZILIAN

SEMIARID: A DISTINCT BIOREGION……………………..…………………….....97

CONSIDERAÇÕES FINAIS ........................................................................................116

RFERÊNCIAS...............................................................................................................118

ANEXOS.......................................................................................................................163

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INTRODUÇÃO GERAL

Períodos glaciais e interglaciais e o surgimento de zonas de refúgio

A distribuição da vegetação por paisagens ecológicas depende em grande parte da

variação no clima, demonstrada pela translocação de espécies por diferentes gradientes

topográficos e geográficos, um processo consolidado durante o último evento de

deglaciação (Betancourt et al., 1990). Os períodos glaciais e interglaciais que se

alternaram sobre todas as regiões da Terra durante o Terciário (desde o Eoceno, há 23

milhões de ano) e Quaternário (Pleistoceno Tardio e Holoceno, há 1,6 milhão de anos)

causaram modificações no nível dos oceanos, na temperatura e na quantidade de gelo das

calotas polares (Bigarella et al., 1975; Bigarella & Andrade-Lima, 1982; Allen &

Breshears, 1998).

Os eventos de acréscimo de precipitação foram intensos e sincrônicos por

apresentarem um padrão de longas fases áridas intercaladas por fases úmidas (Hoorn et

al., 2010) e retração e expansão de formações vegetais (Whitmore & Prance, 1987; Prado

& Gibbs, 1993; Oliveira-Filho & Ratter, 1995). Esses eventos paleoclimáticos e

geomorfológicos foram responsáveis pela geração de alta diversidade biológica e

endemismos nos Neotrópicos (Antonelli & Sanmartín, 2011).

Estudos que buscam explicar a diversidade biológica neotropical ainda estão em

fase inicial (Mello-Martins, 2011). Historicamente, muito mais atenção tem sido dedicada

à diversificação da região amazônica por meio da teoria dos refúgios (Haffer, 1969), que

sugere que as flutuações climáticas do Pleistoceno fizeram com que as formações

florestais tenham sido fragmentadas por formações secas e abertas, como as savanas.

Dessa forma, os fragmentos florestais remanescentes seriam isolados e, nesses refúgios,

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novas espécies surgiriam pelo isolamento de espécies ancestrais amplamente distribuídas

(especiação por vicariância).

Embora a teoria dos refúgios tenha recebido um amplo apoio inicialmente

(Vanzolini & Williams, 1981), ela não foi corroborada por dados empíricos na área da

Amazônia, com evidências congruentes e diferentes hipóteses de diversificação (da Silva

& Patton, 1998; Marks et al., 2002; Aleixo, 2004; Zink, Klicka & Barber, 2004; Rull,

2008). Por outro lado, estudos paleoecológicos, de modelagem e filogeográficos sugerem

a ocorrência de refúgios florestais do Pleistoceno para outras áreas tropicais (Hugall et

al., 2002), como a Floresta Atlântica, que foi fragmentada por áreas abertas, gerando

manchas florestais isoladas em toda sua extensão (Behling & Lichte, 1997; Ledru et al.,

1998; Behling & Negrelle, 2001; Behling, 2002).

Diferentemente da disposição interiorana dos refúgios amazônicos, as áreas de

refúgio na Mata Atlântica geralmente ocorrem próximas do litoral (Ab’sáber, 1977;

Brown, 1982; Prance, 1982; Haffer, 1987; Sant'Anna-Neto & Nery, 2005; Carnaval &

Moritz, 2008; Mello-Martins, 2011), relacionadas às encostas das serras, onde existiram

condições para a permanência de florestas pelas massas de ar úmidas vindas do Oceano

Atlântico.

Carnaval & Moritz (2008) sugerem um modelo, baseado em estudos de fauna, que

mostra que houve uma grande mancha florestal contínua entre o Rio Doce e o Rio São

Francisco, que foi fragmentada em diversas manchas de refúgio, correspondendo aos

centros atuais de endemismo de vários táxons e de padrões de diversidade do DNA

mitocondrial de algumas espécies. Em diversos grupos taxonômicos, têm sido

encontrados padrões filogeográficos que corroboram a hipótese de refúgios do

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Pleistoceno na Floresta Atlântica (Cabanne et al., 2008; Carnaval et al., 2009; D’Horta et

al., 2011; Pavan et al., 2011).

Zonas ecotonais e o Nordeste Brasileiro

As respostas da vegetação às variações climáticas são mais rápidas e extremas nos

limites entre diferentes ecossistemas, denominadas ecótonos (Gosz, 1992; Risser, 1995).

Nas últimas décadas, diversos estudos abordaram eventos de glaciação e deglaciação

durante o Terciário e Quaternário em ambientes ecotonais no mundo: em regiões

semiáridas mexicanas (Allen & Breshears, 1998), regiões alpinas nos EUA (Walsh et al.,

1994), chaco boliviano (Latrubesse et al., 2013), sudeste da Tasmânia (Macphail, 1979),

bacias montanhosas na Suíça (Köplin et al., 2013) e montanhas subalpinas bulgarianas

(Tonkov et al., 2012).

No Brasil, os estudos de ecótonos são mais recentes e estão em constante processo

de desenvolvimento (Behling, 2001; Behling & Costa, 2001; Behling et al., 2001;

Latrubesse & Franzinelli, 2002; Vidotto et al., 2007; Santos et al., 2007; Diogo et al.,

2013). Os ecótonos localizados no semiárido são considerados um dos mais sensíveis às

variações climáticas (Allen & Breshears, 1998). Desse modo, uma das melhores áreas

para estudar a dinâmica e efeitos da glaciação é o Nordeste brasileiro. A cobertura vegetal

dessa região é modulada pelo clima (Juaréz & Liu, 2001; Ferreira et al., 2001), sendo a

caatinga seu tipo de vegetação predominante.

A configuração atual do relevo do Nordeste brasileiro deriva das forças de

distensão oriundas da separação das placas tectônicas da América do Sul e da África, que

provocaram o soerguimento de bacias sedimentares e de maciços cristalinos residuais

durante o período Cretáceo (Claudino-Sales; Peulvast, 2007). Devido à presença de

fósseis característicos (mamíferos pleistocênicos associados a climas úmidos e registros

13


polínicos de plantas ombrófilas), rochas calcárias e datações de recifes marinhos,

diferentes autores afirmam a existência de períodos de alta umidade no Terciário e

Quaternário em regiões que atualmente são consideradas semiáridas (Arz et al., 1999;

DeOliveira et al., 1999; Behling et al., 2000; Auler et al., 2004; Wang et al., 2004;

Ximenes, 2008).

Floresta Amazônica, Floresta Atlântica e as Florestas Serranas Nordestinas

As flutuações no clima foram supostamente suficientes para promover a retração

e expansão da Floresta Amazônica e da Mata Atlântica, gerando a hipótese de que elas

podem ter sido conectadas, permitindo o intercâmbio de espécies (Cole, 1960; Andrade-

Lima, 1966, 1982; Ab’saber, 1977; Behling et al., 2000; Auler et al., 2004, Wang et al.,

2004). Após intervalos entre períodos glaciais e interglaciais, as florestas tropicais

atlântica e amazônica retornaram a sua distribuição original, gerando ilhas vegetacionais

(Andrade-Lima, 1982) que permaneceram em locais de mesoclima favorável.

A Floresta Amazônica abrange as bacias amazônicas desde o Alto Orinoco,

situado no estado do Amazonas, até o Baixo Tocantins, no Pará, extrapolando as

fronteiras brasileiras para atingir os países vizinhos como: Peru, Bolívia, Equador,

Venezuela, Colômbia, Suriname, Guiana e Guiana Francesa (Pires, 1953; Terborgh &

Andresen, 1998), além de regiões pré-amazônicas (extremo oriental), como o estado do

Maranhão (Muniz, 1996). A floresta Atlântica estendia-se do Rio Grande do Sul até o

nordeste brasileiro (Rio Grande do Norte), tendo como região nuclear entre o rio São

Francisco e o Rio Doce (no Estado da Bahia) e São Paulo, ocupando 1 milhão de km²

(Joly et al., 1991; Veloso et al., 1991; Rizzini, 1997; Scudeller et al., 2001).

Dentro do domínio Atlântico e Amazônico são encontradas diversas

fitofisionomias florestais e formações associadas ora adentrando no continente, ora se

14


restringindo a uma estreita faixa litorânea de planície, ocorrendo também os encraves

florestais no Nordeste (Schäffer & Prochnow, 2002), conhecidos como brejos de altitude

ou florestas serranas. A origem da vegetação encontrada nas florestas serranas é baseada

na teoria de refúgios, onde esses encraves florestais úmidos localizados no semiárido

teriam funcionado como refúgios ecológicos (Haffer, 1969; Bigarella et al., 1975;

Andrade-Lima, 1982; Prance, 1982) para diferentes espécies vegetais e animais,

constituindo abrigo natural de diversas espécies ameaçadas de extinção e de espécies

novas ainda não descritas (Schneider et al., 1999).

As florestas serranas são ilhas de floresta úmida estabelecidas na região semi-

árida, sendo cercadas por uma vegetação de caatinga (Andrade-Lima 1982), classificadas

como “áreas de exceção” dentro do domínio do nordeste semi-árido (Lins 1989). A

existência dessas ilhas de floresta em uma região onde a precipitação média anual varia

entre 240 - 900 mm (Lins 1989) está associada à ocorrência de planaltos e chapadas entre

500 - 1.100 m altitude (por exemplo, Borborema, Chapada do Araripe, Chapada de

Ibiapaba), onde as chuvas orográficas garantem níveis de precipitação superiores a 1.200

mm/ano (Andrade-Lima 1960, 1961). Quando comparados às regiões semiáridas, os

brejos possuem condições privilegiadas quanto à umidade do solo e do ar, temperatura e

cobertura vegetal (Andrade-Lima 1966).

As florestas serranas são caracterizadas por apresentar plantas com distribuição

amazônica e algumas espécies típicas das florestas serranas do sul e sudeste do Brasil

(Tabarelli, 2001). Santos (2002) reforçou essa hipótese ao encontrar um padrão de

distribuição disjunta da flora lenhosa na Amazônia e em 12 localidades de floresta serrana

nordestina de Pernambuco que se enquadra em um modelo de separação sequencial e

gradativa de uma condição preexistente (retração da floresta úmida). Dessa forma, o

15


processo de separação continuou até que essas florestas atingissem o número e a

conformação espacial atual (Tabela 1).

Tabela 1. Número e área florestal das florestas serranas ocorrentes no Nordeste (sensu Andrade-Lima,

1982).

Estados No de florestas serranas Área florestal (km2) %

Ceará 11 6.596,50 34,2

Rio Grande do Norte 5 1.147,50 6

Paraíba 8 6.760 35,1

Pernambuco 23 4.850 25,2

Sergipe 2 670 3,5

Total 49 19.259 100

No estado do Ceará, as serras úmidas são encontradas nos topos das serras e

chapadas e nas vertentes a barlavento (que recebem as chuvas orográficas), como é o caso

das serras de Aratanha, Maranguape, Meruoca, Uruburetama, Planalto da Ibiapaba do

Norte, Chapada do Araripe e Baturité (Figueiredo & Barbosa, 1990). Tais serras

representam apenas 3,71% da superfície do Estado (Xavier, 2007, Figura 1) e, dentre

estas, a Serra de Baturité merece destaque por ser a mais extensa, uma das mais altas e

mais úmidas do Ceará (Araújo et al., 2007).

As melhores condições climáticas das florestas serranas atraíram e continuam

atraindo pecuaristas e agricultores, que, através da criação de bovinos e do plantio de

lavouras permanentes (banana, café e citros) e temporárias (hortaliças, mandioca, milho

e feijão) constituem a base da estrutura sócio-econômica nessas áreas (Lins 1989). Silva

& Tabarelli (2000) demonstraram que as florestas serranas nordestinas necessitam de

ações conservacionistas mais intensas, já que estas são muito ameaçadas, tanto pela

grande distância existente entre elas, como pela exploração antrópica. Considerando que

esses encraves florestais constituem abrigo natural de diversas espécies ameaçadas de

extinção e que a maior parte da biodiversidade encontra-se hoje localizada em pequenos

fragmentos florestais pouco estudados e marginalizados por iniciativas conservacionistas,

16


o conhecimento da estrutura e da composição das comunidades vegetais e animais e de

suas interações com o ambiente é de suma importância para a implementação de ações

visando à diminuição da perda de biodiversidade e à conservação ambiental dessas

florestas.

Poucos estudos nas florestas úmidas serranas no Nordeste brasileiro enfocam

biogeografia por meio de composição taxonômica. As análises fitogeográficas abordam

relações entre o Centro Pernambucano de Endemismo e outras fitofisionomias florestais

(Santos et al., 2007), relações de florestas serranas com florestas de terras baixas em

Pernambuco (Cavalcanti & Tabarelli, 2004) e comparações florísticas e estruturais entre

florestas estacionais e úmidas em Pernambuco (Lopes et al., 2008).

Uma vez que os táxons ombrófilos provenientes das florestas tropicais geralmente

não toleram condições de aridez, a hipótese principal desse estudo é de que as florestas

serranas configuram-se como áreas únicas e distintas de tensão ecológica com grande

diferença da caatinga circundante, já que os sucessivos ciclos climáticos no Nordeste

durante o Pleistoceno foram responsáveis pelo isolamento de populações de espécies

vegetais nessas florestas. Dentro deste contexto, conhecer a vegetação das florestas

serranas é de suma importância para entender a origem desses encraves de vegetação

úmida. A segunda hipótese é de que a distribuição de espécies nessas florestas é

dependente da altitude e das condições edáficas, diferenciando-se portanto entre as

vertentes das serras e entre os diversos tipos vegetacionais localizados no semiárido.

Admitindo-se que as florestas serranas são áreas ecotonais ilhadas no semiárido,

a pergunta geral que norteia o trabalho é: Qual a relação entre as florestas serranas úmidas

e os diferentes domínios brasileiros, e como se dá a distribuição de espécies nessas áreas?

Desse modo, estudamos uma serra específica, comparamos com os estudos já existentes,

elaboraramos listas das espécies ocorrentes nas florestas serranas e verificamos suas

17


características principais que as delimitam enquanto áreas de refúgio. A partir daí,

denominamos perguntas específicas: A) Qual a composição florística, diversidade e como

se estrutura a Serra de Maranguape, Ceará, comparando vertentes e topo? B) Quais são e

como as variáveis ambientais explicam a distribuição de espécies na Serra de

Maranguape? C) Como a flora da Serra de Maranguape se relaciona com as outras

fitofisionomias do estado do Ceará? (Capítulo 1, onde a Serra de Maranguape foi

escolhida como um objeto de estudo das florestas serranas úmidas em escala local). D)

Qual a composição palinológica das Serras de Maranguape, Baturité e Pacatuba,

comparando vertentes e topo? E) Como a distribuição da vegetação está relacionada com

a atual chuva polínica? F) Qual e como as variáveis ambientais explicam a distribuição

da chuva polínica nessas serras? (Capítulo 2, que mostra a importância da chuva polínica

das florestas serranas cearenses para entender a distribuição atual da vegetação). G) Qual

a relação entre as serras úmidas do Nordeste brasileiro? H) Qual as variáveis bióticas e

abióticas (processos ecológicos) e como elas explicam a atual distribuição de espécies

nessas serras nordestinas? (Capítulo 3, que acrescenta uma visão regional das florestas

serranas úmidas nordestinas) I) Qual a relação das florestas serranas úmidas com

Amazônia, Floresta Atlântica, Cerrado e Caatinga? J) As florestas serranas do Nordeste

brasileiro podem ser classificadas com uma única unidade florística? (Capítulo 4, que

relaciona os domínios brasileiros com as florestas serranas nordestinas e traz uma nova

classificação dessas áreas).

18


CHAPTER I

VEGETATION STRUCTURE, SPECIES COMPOSITION AND DISTRIBUTION

IN A TOPOGRAPHIC GRADIENT OF A MOUNTAIN FOREST, NORTHEASTERN

BRAZIL *

SPECIES DISTRIBUTION IN A TOPOGRAPHIC GRADIENT

*MANUSCRIPT SUBMITTED TO JOURNAL OF SYSTEMATICS AND EVOLUTION

IVAN JEFERSON SAMPAIO DIOGO1*, KARIN DOS SANTOS2, ITAYGUARA RIBEIRO

DA COSTA 3 & FLAVIO MÄES DOS SANTOS 1

¹University of Campinas - UNICAMP, Institute of Biology, Department of Plant Biology, 13083-970.

Campinas, SP, Brazil *[email protected]

²Swedish Museum of Natural History, Botany Department, P.O. Box 50007 SE-104 05 Stockholm, Sweden

³Federal University of Ceará - UFC, Departament of Biology, Sciences Center, 60455-760. Fortaleza,

CE, Brazil

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Abstract

The humid mountain forests located in Brazilian semiarid region are diverse and

endangered areas located in the semiarid region. We aimed to examine the

phytosociological structure, richness, diversity and species distribution of woody plant of

the mountain forest at Serra de Maranguape, Brazil. Data collection went from 2013 to

2015 and we divided the whole area into three topographic categories: windward (600-

800 m, WMA), leeward (600-800 m, LMA) and top (above 800 m, TMA). We calculated

different phytosociological parameters and floristic diversity of each category. A

correspondence analysis was performed to analyze the indirect ordination of forest sites

by species abundance. A canonical correspondence analysis was conducted to verify

which variables were driving species distribution. We used non-metric multidimensional

scaling distance and average linkage method to investigate the similarity among mountain

forests and thorny woodlands. A total of 1536 individuals belonging to 144 tree species

distributed in 44 families and 93 genera were recorded. Myrtaceae, Fabaceae and

Rubiaceae were the most species rich families. Myrcia splendens had the highest IV

followed by Guapira nitida and Mollinedia ovata. The leeward slope showed the highest

richness and diversity index, the windward showed the highest density and the top showed

the highest basal area. The PCA ordination indicated a greater similarity between TMA

and WMA than LMA. Temperature and precipitation are the climatic factors driving

species distribution in Maranguape. Crystalline origin mountains are closer than

sedimentary ones, but the leeward slope from Baturité was close to thorny woodland

areas. Our results will be useful for conservation or restoration purposes on the poor

known mountain forests of Northeast, Brazil.

Key words: Myrtaceae, Fabaceae, temperature, precipitation, leeward, windward and

top.

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1 Introduction

The Brazilian Atlantic Forest (BAF) represents the second largest tropical forest

in the world and may contain between one and eight percent of the world’s species (Silva

and Casteleti, 2003). However, BAF has been explored and degraded for more than 500

years, one of the most threatened and fragmented ecosystem in the world. Nowadays,

only around 11.4% to 16% of its original cover remains (Ribeiro et al., 2009, 2011).

Forzza et al. (2012) estimated that approximately 20,000 species (40% endemics) of

vascular plants are found in the BAF, which make it one of the most distinctive

biogeographical units in the entire Neotropical region.

Through the last century, the Atlantic forest has been extensively deforested

because of coffee and sugarcane monocultures to the economic development of Brazil

(Gibbs et al., 2010). Nevertheless, BAF is recognized as one of the 35 biodiveristy

hotspots for conservation priorities (Myers et al., 2000; Mittermeier et al., 2004; Zachos

and Habel, 2011). Some forest fragments still exist and are concentrated on the top of

mountains and steep slopes, where is difficult to access and the anthropogenic activities

is unfeasible.

The northernmost BAF stretches 1,500 km along the atlantic coast from Bahia to

Rio Grande do Norte states. In Ceará state, the original Atlantic Forest is distributed in

small and isolated fragments, the mountain forests, such as Baturité (Araújo et al., 2007).

These fragments may play an important role as stepping stones for diversity, dispersal

and conservation of species (Anderson and Jenkins, 2006). Due to their history, these

small enclaves on mountain tops are considered as interglacial microrefugia, i.e., relics

of a past expansion of the Atlantic forest (Ledru et al., 2007; Montade et al., 2014).

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These humid forest enclaves located in the semiarid region have functioned as

ecological refuges for flora and fauna, providing natural shelter of several endangered

species and new species not yet described (Andrade-Lima, 1982). They are characterized

by having plants with Amazon, Atlantic and Caatinga distribution (Santos et al., 2007).

There are 49 mountain forests, distributed in the states of Ceará, Rio Grande do Norte,

Paraiba and Pernambuco, which cover 19 259 km2; however, this number is actually

reduced by half. (Vasconcelos Sobrinho, 1971). In Ceará state, these humid forests are

found on the tops of mountains and plateaus and on the windward side (receiving

orographic rainfall), which cover 3.71% of the state surface (Xavier, 2007).

Few studies and inventories are located on these areas and it demands further

attention especially given the extensive loss of habitat. We aimed to examine the floristic

composition, diversity and phytosociological structure of woody plant of the mountain

forest at Serra de Maranguape, Ceará state, at different topographic areas: leeward,

windward and top. We conducted statistical comparisons between Serra de Maranguape

and other mountain forests from Ceará State in order to verify if they differ in terms of

topographical, horizontal and vertical phytosociological structure.

2 Material & Methods

2.1 Study area

The study took place in the mountainous rainforest of the protected area of Serra

de Maranguape (Área de Proteção Ambiental da Serra de Maranguape; SEMA). The

SEMA is one of the high elevation areas of Ceará State, reaching 980 m a.s.l. (3°53′40.32″

S, 38°43′13.56″ W), covers an area of 71 km2 and is located 30 km from the Atlantic

Ocean (Fig. 1). The SEMA has a very steep crystalline relief and different types of plant

physionomies and is a protected área (APA).The local climate is characterized by a hot

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semiarid, with rainy summer (December to May) and dry winter (mainly from September

to November), BSh in Köppen-Geiger system (Peel et al., 2007). In opposite to the

semiarid climate, the SEMA has a tropical and sub-humid climate (Aw), with avarage

rainfall above 1300 mm year-1 and average temperature between 23°C and 26°C. The soil

classes vary between Alisol, Luvisol and Neosol (Arruda, 2001).

While the lower areas of the mountain forests are dominated by deciduous thorny

woodland (caatinga), upper areas are dominated by semideciduous and ombrophilous

forests. The position of the massif in relation to the wind exposure provides a higher

humidity on the windward slopes due to the rain-forced convection. This fact results in

different gradients among the slopes and, in general, higher precipitation than the

surrounding semi-arid region, where the average precipitation rate is 700 mm per year

(Funceme, 2005).

2.2 Data collection

Data collection started in July 2013 and completed in January 2015 and was based

on the point-centered quarter method (Cottam & Curtis, 1956). This procedure consists

of dividing each sampling point into four quarters by a pair of perpendicular lines. We

divided the SEMA into three topographic categories: top (TMA) from 880 m to 934 m

(3o53'48''S; 38o43'15"W), leeward (LMA) from 654 m to 702 m (3°54'30.9''S;

38°43'57.0''W) and windward (WMA) from 678 m to 796 m (3o54'31''S; 38o43'01"W).

We established two areas of 0.5ha in each one (separated by a minimum distance

of 200m and a maximum of 1km; Fig. 2A). In each area, we sampled five parallel

transects with 100m length, 10 points quadrats and 50m between them (Fig. 2B), totaling

3ha, 30 transects and 300 point quadrats. We attempted to sample a standardized area of

each category, in order to isolate the effect of area from other variables, such as edge and

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anthropogenic effects. In each quarter, we recorded the nearest tree of 15 cm perimeter at

breast height (PBH) or larger and measured their circumference (cm), height (m) and

distance from the point to the tree (m). Multi-stemmed individuals at breast height were

sampled if at least one stem showed this minimal PBH criterion. When these individuals

had a PBH < 30cm, we sampled another individual in the same quadrat with PBH ≥ 30

cm (Fig. 2C).

We identified specimens by consulting the literature and specialists and by

comparison in herbaria. The plant families were listed according to the Angiosperm

Phylogeny Group IV guidelines (APG IV, 2016). Vouchers of specimens were deposited

in the EAC (Federal University of Ceará, Brazil), (University of Campinas, Brazil) and S

(Swedish Museum of Natural History, Stockholm, Sweden) herbaria.

2.3 Data analysis

We analyzed the following phytosociological parameters: absolute and relative

density (based on the distance from the point to the tree), frequency and dominance; cover

value, importance value (IV) and basal area of each topographic category and of whole

SEMA (Mueller-Dombois & Ellenberg, 1974). We calculated floristic diversity by

Shannon-Wiener (H’), Pielou’s evenness (J’) and Simpson index (D). A non-parametric

Kruskal-Wallis test was applied to verify statistical differences among forest sites on

average tree height and diameter. A Chi-square test was performed to verify differences

in the proportion of multi-stemmed individuals at breast height. These analyzes were

performed using the software Fitopac 2.1 (Shepherd, 2009) and PC-ORD 6.0 (McCune

& Mefford, 2011).

A correspondence analysis (CA) (Hill, 1973) was performed to analyze the

indirect ordination of forest sites by species abundance in order to verify the horizontal

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structure similarities among the different sites. Those species observed at only one site

were eliminated in this analysis because the CA is very sensitive to their presence

(McCune & Grace, 2002).

To test for differences in horizontal and vertical structure between leeward,

windward and top, the structural parameters of species richness (S), Shannon-Wiener

index (H'), total density per hectare (DE), total dominance per hectare (DO) were listed

for Baturité and Maranguape mountains and compared. Furthermore, in order to

determine correlations between the spatial distribution of vegetation groups and

environmental data from each area, Canonical Correspondence Analysis (CCA) was

carried out. Environmental parameters such as slope angle and elevation were calculated

using QGIS software (QGIS Development Team, 2015) running the ASTER Global

Digital Elevation Model (from METI and NASA). Mean annual precipitation and

temperature values for the period 1950–2000 were obtained using the WorldClim

database for each location of the surface samples with a spatial resolution of 1 km2 (Fick

and Hijmans, 2017). To test the correlation among the environmental variables, we did a

Pearson correlation test (r).

We used non-metric multidimensional scaling (nMDS) with Jaccard index and

average linkage method (UPGMA) using the Jaccard index to test for floristic similarities

among Cearás’s mountain forests and caatinga (Table 1). These analyses were performed

in PC-ORD 6.0 (McCune & Mefford, 2011).

3 Results

A total of 1536 individuals belonging to 144 tree species distributed in 44 families

and 93 genera were recorded in the 6 samples (Table 2). Myrtaceae (21 spp.), Fabaceae

(17 spp.), Rubiaceae (15 spp.), Lauraceae and Sapotaceae (6 spp.), and Malpighiaceae

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and Euphorbiaceae (5 spp.) were the most species rich families, which accounted for

52,1% of the species observed at the study site. Eugenia and Myrcia (07 spp.), and Inga,

Senna, Ocotea and Byrsonima (4 spp.) were the richest genera. Many families and genera

were represented by only one species each. Myrtaceae, Nyctaginaceae, Fabaceae,

Lauraceae, Sapindaceae and Rubiaceae showed the highest IV and represented almost

50% of the total IV.

Although Myrcia splendens had the highest IV (7.5% of the total IV), number of

individuals, relative density and relative frequency, its relative dominance was lower than

that of Guapira nitida and Mollinedia ovata, which together represented 12.1% of the

total IV (Table 2). Myrcia splendens, G. nitida, M. ovata, Cupania impressinervia,

Handroanthus serratifolius, Nectandra cuspidata, Inga bollandii, G. opposita,

Pilocarpus spicatus, C. oblongifolia, Margaritaria nobilis, Cinnamomum triplinerve had

more than 30 individuals and were the species with highest IV (43% of the total, Table

2). However, Neea floribunda had 19 individuals and presented a big IV value (5.47).

The standing dead biomass was represented by 52 individuals and 3.5% of the total IV.

The total density for the three forest sites was 1,275 individuals.ha−1, the total

dominance was 27.39 m2.ha−1, the total basal area was 26.53 m2.ha−1. The Shannon-

Wiener index was 4.182, evenness was 0.841 and Simpson index was 0.027. The LMA

site showed the highest species-level richness (95 spp.) and the WMA showed the highest

density (522 individuals.ha−1). However, the WMA site showed the lowest dominance

(29.15 m2.ha−1) and the TMA showed the highest basal area (28.374 m2.ha−1), while the

LMA presented the highest Shannon-Wiener and evenness index (Table 3).

From the 144 species sampled, 20 (13.9%) were present in the three sample areas,

16 (11.1%) between TMA and WMA, 5 (3.47%) between TMA and LMA, and 13

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(9.03%) between WMA and LMA slopes. Thus, 12 (8.33%) species were found only in

TMA, 17 (11.8%) only in WMA and 41 (28.5%) only in LMA. The CA ordination of

forest sites by species abundance indicated a greater similarity between TMA and WMA.

The inertia explained by the first two axes was 70.8% (Fig. 3). M. splendens was abundant

in all sample areas, but was strongly associated with TMA and WMA, as well as G. nitida.

M. ovata. and I. bolandii were more associated with TMA areas, while C. impressinervia

and Neoraputia magnifica with WMA areas. On the other hand, P. spicatus, H.

serratifolius and Senegalia poliphilla were more associated with LMA areas (Table 3 and

Fig. 3).

The tree stems in SEMA had an average height of 11.45m ± 4.58 and an average

diameter of 58.67cm ± 43.59. The average height had no significant difference among the

sites, although the diameter (H = 187.4521, P < 0.001) in TMA were significantly higher

than WMA and LMA. The WMA and LMA sites were similar in terms of the proportion

of multi-stemmed individuals at breast height, 13.36% and 12.34% respectively, whereas

in TMA showed a higher proportion (23.75%) of stems per individual than the other sites

(χ2 = 18.766, P = 0.0005, DF = 2). The Shannon–Wiener (H’) and evenness (J) were

higher in LMA, followed by WMA and TMA respectively, whereas the Simpson index

(D) was higher in TMA (Table 3).

The LMA showed distinct horizontal structure when compared to WMA and

TMA, whereas these two are quite similar. LMA had higher richness (S) (T = 4.679, P =

0.0003, GL = 9), and higher diversity according to the Shannon-Wiener index (H') (U =

0.00, Z(U) = 3.607, P = 0.002); however, the total density per hectare was significantly

lower (T = −3.478, P = 0.0017, GL = 9). TMA had a significantly higher total dominance

per hectare (T = 1.067, P = 0.00012, GL = 9). WMA had higher total density per hectare

(T = 2.149, P = 0.0023, GL = 9). On the other hand, the leeward slope of Baturité

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mountain had the lower richness and diversity per hectare, whereas the top presented

higher density, richness and diversity per hectare (see Araújo et al., 2007). However,

Baturité and Maranguape mountains have one similarity: the both leeward slopes have

the lowest density.

The distribution of samples in the CCA diagram clearly separates four groups,

which displays windward and top of each mountain in two different groups and each

leeward as a unique group, which reflects the vegetation variation from the seasonal semi-

deciduous montane forest to the dense ombrophilous forest. Temperature and

precipitation were the main ecological parameters driving the species distribution in these

mountains. TMA and WMA had greater values for temperature and precipitation,

whereas TB and WB had the same greater values for precipitation, but lower for

temperature. LMA had greater values for temperature, but lower for precipitation, and LB

had lower values for both variables (Fig. 4).

The environmental parameters are mainly correlated with axis 2. The main

correlation concerning axis 1 is with the temperature (-0.715), followed by precipitation

(-0.580). The closest environmental parameters related to axis 2 are precipitation (0.802),

temperature (0.415) and slope (0.190) (Table 4).

The cluster dendrogram showed two different groups: one with TB, WB, TMA,

WMA, LMA, MF1, MF2 and MF3, and another one with LB and CA 1, CA2, CA3 and

CA4 (17.5% of information remaining, Fig. 5). In a higher resolution, the leeward slope

of Baturité was grouped with all Caatinga areas, except for CA2. Maranguape, MF1, TB

and WB were grouped together. MF2 and MF3 formed the last group (Fig. 5). The

correlations between the cophenetic similarities and the Jaccard original similarities were

strong (0.78), confirming the reliability of the UPGMA analyses.

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The NMDS ordination provided a two-dimensional solution, with both axes being

significant (P = 0.01), and explained 79% of the correlations between the distances in the

original space and the ordination distances. After 38 iterations, the final stress value was

13.71, which is a satisfactory result (McCune and Grace, 2002). The NMDS diagram

showed a clear separation among all the mountains and caatinga areas with three groups

formed (Fig. 6). The nMDS analysis ordered the same groups from the UPGMA,

revealing a great correspondence between them.

There was no correlation between the geographical distance and the floristic

among topographical sides (r = 0.12; p = 0.32). On the other hand, there was a strong

correlation between the geographical distance and the floristic among mountain forests (r

= 0,63; p < 0,01).

4 Discussion

The results of our study were largely inconsistent with those of several other

floristics studies in Ceará state, mainly because of the Caatinga areas, where the species

richness is lower and Fabaceae is the richest family (Queiroz, 2006; Lima et al., 2012a;

Moro et al. 2014). On the other hand, we found some similarities among the mountain

forest areas of Ceará, such as the higher number of species, Myrtaceae as the richest

family and Myrcia splendens as the most common species (Araújo et al., 2007; Ribeiro-

Silva et al., 2012). Maranguape and Baturité mountains share many species, including

similar richness, H’, IV, density, frequency and dominance because of their geographical

proximity and same crystalline origin. Moreover, those similarities also occur with

mountain forests located in other states from Northeast, Brazil (Diogo et al., In press).

Considering the slopes, it is worth noting that, although they are geographically

close, each one has a distinctive flora with some exclusive species. This result

corroborates the hypothesis that the plant distribution is more strongly associated with the

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forest type and environmental heterogeneity than with the geographical distance (Lima et

al., 2012a; Gonzalez-Caro et al., 2014; Sabatini et al., 2014). The greater richness and

diversity of species in the leeward slope of SEMA do not agree with Gentry (1982, 1988),

who pointed that a greater diversity would be expected in wetter areas. Araújo et al.

(2006) and Fernández-Palacios et al. (1995) also found a positive correlation between

precipitation and species richness and diversity, with the windward areas being the most

diverse. On the other hand, our findings agree with some studies with Fabaceae in

Baturité, Brazil (Lima et al., 2012b), with floristic composition in a rain forest in Taiwan

(Chen et al., 1997) and with altitudinal pattern of vegetation on Tenerife (Fernández-

Palacios and Nicolás, 1995).

Although we found a greater richness and diversity for total flora in the drier areas

of the Maranguape Mountain Range, this result was not observed when the analysis was

carried out at the family level. For instance, Myrtaceae has higher richness and diversity

in wetter areas as the Atlantic rainforest (Murray-Smith et al., 2009; Lucas & Bünger,

2015), Amazonia (Nigel et al., 2002) and the windward slope, whereas Fabaceae has the

opposite pattern, with higher richness and diversity in the drier areas as the Caatinga

(Moro et al., 2014) and the leeward slope. The richness and diversity of species vary

according to the taxonomic group analyzed and its evolutionary history (Murray-Smith

et al., 2008; Schouten et al., 2009), each family responds differently according to the

climate and topography. For instance, temperature is the most important climatic variable

for Fabaceae, but for other families, such as Myrtaceae and Bignoniaceae it is

precipitation (Punyasena et al., 2008). The forest composition change found when

comparing windward and leeward was also observed in the corresponding pollen

assemblages of those slopes (Montade et al., 2016). The windward slope is an area which

is under the influence of orographic rainfalls and has features of ombrophilous forest as

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its dominant type of vegetation, as we see an increase of Myrtaceae, Lauraceae and

Nyctaginaceae families. The leeward slope is an area with lower precipitation and higher

temperatures and has semideciduous seasonal forest as vegetation type with an increase

of Fabaceae, Bignoniaceae and Rutaceae families.

The type of forest located closer to the mountain top differs partly in their structure

and composition from the forests located just below, which demonstrates typical features

of forests under influence of clouds, such as low canopy height, low species richness,

high proportion of multi-stemmed individuals at breast height, high tree diameter and

high dominance (Hamilton et al., 1995; Falkenberg and Voltolini, 1995; Meireles et al.,

2008). Among the sampled species, an increase of pioneer and heliophilous trees is

observed, such as Alchornea glandulosa, Pourouma guianensis and Miconia mirabilis

(Souza et al., 2006; Pessoa et al., 2012), as well as an increase of narrow geographical

distribution species, which occurred only in forest formations of high-altitude mountain

ranges, such as Clusia melchiorii and Clusia paralicola (Araujo & Scarano, 2007). The

representativeness increase of those taxa in both vegetation and pollen rain (Montade et

al., 2016), may be consequence of the existence of specific environmental conditions on

the mountain tops or areas located close to it, such as different soil conditions related to

the rocks. Those local conditions can explain the difference in plant community, which is

more dependent on atmospheric moisture under the influence of fogs and/or clouds and

is dominated by species ecologically adapted (Kitayama, 1992). Moreover, although

rainfalls would reach their maxima close to the mountain tops, local environmental

conditions induce lower diversity and richness and higher density when compared to

forests located a few tens of meters below. The higher Simpson index for top surveys

suggests a higher concentration of individuals within a few species as altitude increases

(Martins & Santos, 1999).

http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0102-33062015000100058&lng=en&nrm=iso&tlng=en#B68

31


The lower richness, diversity index and density in leeward slope of Baturité are

related with more restrictive environmental conditions, such as high temperatures and

small amount of rainfall (Mantovani, 2006). Furthermore, LB is greatly influenced by

caatinga flora (Cereus jamacaru, Croton blanchetianus, Jatropha mollissima and

Mimosa caesalpiniifolia), which suggests that those areas share some characteristics, such

as shallow depth soils with high pH, maximum and minimum temperatures above the

average for mountain forests, and annual rainfall concentrated in a few months of the year

and below the average for mountain forests (Araújo et al., 2007). Although the leeward

slope of Maranguape has the lower density, it presents a greater mix of species with some

Caatinga species (Anadenanthera colubrina and Poincianella bracteosa), Amazon

rainforest (Abarema jupunba and Coccoloba latifolia) and Atlantic rainforest (Alseis

floribunda and Celtis spinosa). Besides sharing species with windward and top areas,

more than 20% of the species of Maranguape mountain occurs only in LMA.

This study indicates that many of these species seem to prefer a given area, and

those divergences might be a response to climate conditions: temperature and

precipitation changes induced by the altitudinal gradient. Both faces have different mean

annual temperature and precipitation forming specific communities growing on distincts

environments (Chen et al., 1997; Mantovani, 2006; Punyasena, 2008). Those climate

variables are the chief factors determining the distribution of the vegetation around the

world and are usually associated with rapid transition among ombrophilous forest and

semideciduous seasonal forests (Oliveira-Filho et al., 2006). Tree species diversity is

highly correlated with water consumption and energy uptake, resources that are

partitioned among species, and could limit their number in forest communities (Hugget,

1995). The precipitation changes are controlled by the elevation of air masses on the

windward side, which act as a barrier generating orographic precipitation. The leeward

32


side is not reached by many of the air masses, which decrease rainfalls and increase

evaporation. This mechanism is called rain shadow effect and is commonly observed in

tropical mountainous islands (Giambelluca et al., 2013; Duarte et al. 2005). The variation

in the floristic composition among different plant formations in Maranguape mountain

range is also observed in a larger scale, as in the southeastern and northeastern regions of

Brazil (Oliveira-Filho & Fontes, 2000; Ferraz et al. 2004) and even in South America

(Oliveira-Filho et al., 2006). Furthermore, biogeographical studies show that both

temperature and rainfall regime suffered dramatic shifts during the Quaternary (Ledru,

1993, Ledru et al., 1998).

Slope angle could also influence vegetation distribution, because leads to a

gradual removal of dissolved materials from linear slope and the accumulation of these

materials near the creek site. However, it is a relevant factor only at values over than 40o.

(Fernández-Palacios and Nicolás, 1995; Montade et al., 2016). Significant progress has

also been made in analysing consequences of plant–soil feedbacks for biodiversity-

functioning relationships and plant distribution in mountain forests (Liu et al., 2003; John

et al. 2007; Diogo et al., In Press). Nevertheless, the distribution of individuals in a given

environment is not only determined by abiotic factors, but may also result from biological

interactions such as competition, mutualisms herbivorism, dispersal and pollination

(Wisz et al., 2013; Diogo et al., 2016).

When the flora of SEMA was compared to the main plant formations of Ceará

state, there was a grouping varying from drier to wetter areas. It is worth noting that the

leeward of Baturité is clearly more similar to thorny woodland areas and deciduous forests

(Santos et al., 2007 and Araújo et al., 2007 found similar results). For instance, 34% and

32% of its Fabaceae exclusive species can be found in seasonal forests areas and thorny

woodland (Bauhinia cheilanta and Libidibia ferrea), respectively, but only 4% occur in

33


ombrophilous areas (Copaifera duckei) (Lima et al., 2012b). Whereas the leeward of

Maranguape is more similar to semideciduous and ombrophilous forest, with species that

can be found in both forest formations, including the other mountain forests, such as

Anadenanthera colubrina, Ixora brevifolia and Randia armata, it still has thorny

woodland species, Poincianella bracteosa for example. This difference between leeward

slopes can be explained by the distance from the coast, while Maranguape is only 30 km

far, Baturité is 80 km. The precipitation generated by maritime trade winds is distributed

along a gradient: decrease from the coast to the interior, thus, leeward slope of

Maranguape receives a greater amount of rainfall and, consequentely, has better

conditions to different species grow.

On the contrary, windward and top areas of Baturité and Maranguape are more

related to Pacatuba, Araripe and Ubajara, sharing some species, such as Eugenia florida,

Inga bolandii, I. ingoides, Miconia prasina, Myrcia splendens, Ocotea longifolia,

Psychotria carthagenensis and Vismia guianensis. Those forests have similar climatic

conditions and are clearly more humid and receive higher precipitation amount, which

contribute positively to species distribution there. In addition, Maranguape, Baturité and

Pacatuba are closer because of the same crystalline origin and the geographical

approximation. Whereas, Araripe and Ubajara are closer because of the sedimentary

origin. During the Quaternary, the semi-arid region of Brazil experienced episodes of

climatic fluctuations (Behling et al., 2000) and the forested vegetation could have

established in mountain forests as a humid refugia on the most dry periods (Auler et al.,

2004), which could explain the similarity among these mountains.

5 Conclusion

The huge environmental and climatic heterogeneity (temperature and

precipitation) observed in the Maranguape mountain can explain the high diversity and

34


variation in floristic composition among slopes and top because it enables the coexistence

of different species, and such pattern are also observed on a regional scale. Our study

provides a better knowledge of flora, species distribution, forest relationships of the

mountainous massifs in northeastern Brazil. However, there are still areas in northeastern

mountain forests where no floristic or quantitative surveys have been conducted. As these

areas can be considered as a refugia of tropical rainforest in the middle of semiarid, our

results will be useful for conservation or restoration purposes. The knowledge of the flora

in these regions can bring new insights to the species distribution of forests under the

influence of temperature and precipitation in altitudinal gradients.

6 Acknowledgements

Financial support was provided by Royal Swedish Academy of Sciences, KS was

benefited. IJSD was benefited from PhD position funded by CNPq (Brazil). FAMS was

benefited by CNPq (number 306595/2014-1). We thank the Swedish Museum of Natural

History for host IJSD during the taxonomy process. We thank Fernanda Cabral and

Nállarett Dávila for the help on the identifications.

7 Conflict of interest

No potential conflict of interest was reported by the authors.

35


Table 1. Floristic surveys of 6 areas of mountain forests and 4 areas of caatinga located

in Ceará State used in this study.

Locality Code Geographic coordinates

(S;W)

References

Baturité windward

Baturité leeward

Baturité top

Pacatuba

Ubajara

Araripe

Crateús

Aiuaba

Iguatu

Quixadá

WB

LB

TB

MF1

MF2

MF3

CA1

CA2

CA3

CA4

4º17’54”; 38º56’10’’

4º15’32”; 39º00’04’’

4º12’22”; 38º55’55’’

3°59'04"; 38°37'12"

3º51’16”; 40º55’16”

7º16’32”; 39º27’13”

5°7’; 40°2’22.79”

6°36’01”; 40°19’19”

6°19’46”; 39°22’38’’

4°49′34″, 38°59′09″

Araújo et al. (2007)



Not published

Not published

Ribeiro-Silva et al. (2012)

Costa & Araújo (2012)

Sousa et al. (2007)

Lima et al. (2012)

Costa et al. (2007)

36


Table 2. Phytosociological parameters of species sampled in the three topographic areas

of the Serra of Maranguape, northeastern Brazil. NInd: number of individuals, RelDe:

relative density, NOQ: number of occurrences per quadrant, AbsFr: absolute frequency,

RelFr: relative frequency, RelDo: relative dominance, MaxH: maximum height, MaxD:

maximum diameter, IV: importance value, CV: coverage value.

Species NInd RelDe NOQ AbsFr RelFr RelDo MaxH MaxD IV CV

Myrcia splendens 165 10,74 28 93,33 4,15 7,59 33,00 69,07 22,48 18,33

Guapira nitida 87 5,66 25 83,33 3,70 12,78 25,00 75,76 22,15 18,44

Mollinedia ovata 40 2,60 9 30,00 1,33 10,09 27,00 208,81 14,03 12,69

Cupania impressinervia 80 5,21 27 90,00 4,00 2,11 20,00 32,15 11,32 7,32

Handroanthus serratifolius 47 3,06 19 63,33 2,81 3,96 20,00 97,40 9,83 7,02

Nectandra cuspidata 33 2,15 15 50,00 2,22 3,64 25,00 85,94 8,01 5,79

Inga bollandii 30 1,95 11 36,67 1,63 3,78 26,00 127,32 7,36 5,73

Guapira opposita 34 2,21 15 50,00 2,22 2,85 30,00 49,97 7,29 5,06

Pilocarpus spicatus 42 2,73 8 26,67 1,19 1,92 19,00 72,89 5,84 4,65

Cupania oblongifolia 38 2,47 15 50,00 2,22 1,08 18,00 32,79 5,78 3,55

Neea floribunda 19 1,24 8 26,67 1,19 3,05 19,00 102,81 5,47 4,29

Margaritaria nobilis 34 2,21 11 36,67 1,63 1,60 21,00 51,57 5,45 3,82

Cinnamomum triplinerve 31 2,02 11 36,67 1,63 1,78 20,00 60,16 5,43 3,80

Campomanesia dichotoma 25 1,63 12 40,00 1,78 1,74 20,00 54,11 5,15 3,37

Roupala montana 25 1,63 15 50,00 2,22 0,85 20,00 35,33 4,70 2,47

Miconia mirabilis 30 1,95 10 33,33 1,48 1,11 18,00 53,16 4,54 3,06

Psychotria carthagenensis 28 1,82 15 50,00 2,22 0,46 16,00 21,96 4,50 2,28

Maytenus obtusifolia 21 1,37 8 26,67 1,19 1,77 20,00 65,89 4,32 3,14

Eugenia flavescens 23 1,50 10 33,33 1,48 1,23 18,00 63,66 4,21 2,72

Ixora cf. brevifolia 26 1,69 10 33,33 1,48 0,94 18,00 32,79 4,12 2,64

Neoraputia magnifica 23 1,50 6 20,00 0,89 1,73 20,00 62,39 4,11 3,22

Eugenia florida 23 1,50 10 33,33 1,48 0,79 18,00 45,84 3,77 2,29

Banara guianensis 20 1,30 11 36,67 1,63 0,80 23,00 38,20 3,73 2,10

Zanthoxylum rhoifolium 17 1,11 7 23,33 1,04 1,10 30,00 39,15 3,25 2,21

Senegalia polyphylla 18 1,17 9 30,00 1,33 0,58 12,00 35,65 3,09 1,75

Inga marginata 18 1,17 8 26,67 1,19 0,73 20,00 33,74 3,08 1,90

Guatteria pogonopus 18 1,17 8 26,67 1,19 0,65 18,00 34,06 3,00 1,82

Ficus arpazusa 14 0,91 9 30,00 1,33 0,74 21,00 34,06 2,98 1,65

Manilkara rufula 13 0,85 6 20,00 0,89 1,22 22,00 56,66 2,96 2,07

Ocotea puberula 10 0,65 9 30,00 1,33 0,89 18,00 52,84 2,87 1,54

Casearia sylvestris 15 0,98 11 36,67 1,63 0,23 15,00 19,42 2,84 1,21

Inga laurina 14 0,91 7 23,33 1,04 0,84 22,00 36,61 2,79 1,75

Myrciaria tenella 15 0,98 8 26,67 1,19 0,59 30,00 37,56 2,75 1,57

Miconia prasina 17 1,11 9 30,00 1,33 0,30 12,00 22,60 2,74 1,41

Alchornea glandulosa 12 0,78 7 23,33 1,04 0,81 22,00 41,38 2,63 1,59

Pourouma mollis 12 0,78 7 23,33 1,04 0,78 22,00 40,74 2,60 1,56

Eugenia ligustrina 18 1,17 8 26,67 1,19 0,22 14,00 20,37 2,58 1,40

Geonoma pohliana 13 0,85 9 30,00 1,33 0,40 13,00 26,10 2,58 1,24

Astronium fraxinifolium 9 0,59 7 23,33 1,04 0,91 22,00 79,58 2,54 1,50

Byrsonima nitidifolia 18 1,17 5 16,67 0,74 0,61 19,00 39,79 2,52 1,78

Hyeronima oblonga 13 0,85 6 20,00 0,89 0,73 15,00 33,42 2,47 1,58

Eugenia aff. florida 11 0,72 4 13,33 0,59 0,86 16,00 63,66 2,17 1,57

Coccoloba latifolia 11 0,72 5 16,67 0,74 0,70 11,00 51,25 2,15 1,41

37


Faramea sp. 14 0,91 5 16,67 0,74 0,43 11,00 29,60 2,08 1,34

Randia armata 9 0,59 7 23,33 1,04 0,38 15,00 31,83 2,00 0,96

Ilex sapotifolia 9 0,59 6 20,00 0,89 0,49 20,00 37,88 1,97 1,08

Coutarea hexandra 11 0,72 7 23,33 1,04 0,14 15,00 15,92 1,89 0,86

Campomanesia sp. 7 0,46 5 16,67 0,74 0,66 15,00 44,88 1,85 1,11

Eugenia sp. 11 0,72 5 16,67 0,74 0,37 14,00 34,06 1,83 1,09

Clusia panapanari 5 0,33 2 6,67 0,30 1,10 14,00 70,66 1,73 1,43

Vismia guianensis 10 0,65 4 13,33 0,59 0,45 21,00 36,61 1,69 1,10

Myrcia cf. fenestrata 7 0,46 5 16,67 0,74 0,44 14,00 32,79 1,64 0,90

Solanum maranguapense 8 0,52 5 16,67 0,74 0,37 18,00 28,65 1,63 0,89

Esenbeckia grandiflora 8 0,52 5 16,67 0,74 0,34 18,00 36,61 1,60 0,86

Artocarpus heterophyllus 4 0,26 3 10,00 0,44 0,77 18,00 50,93 1,48 1,03

Pourouma guianensis 7 0,46 3 10,00 0,44 0,42 18,00 31,19 1,32 0,88

Chrysophyllum gonocarpum 6 0,39 5 16,67 0,74 0,16 17,00 22,92 1,29 0,55

Ocotea longifolia 5 0,33 4 13,33 0,59 0,26 17,00 34,06 1,17 0,58

Manihot carthaginensis 7 0,46 3 10,00 0,44 0,27 19,00 24,51 1,17 0,73

Symplocos nitens 5 0,33 4 13,33 0,59 0,24 18,00 27,37 1,16 0,57

Handroanthus impetiginosus 9 0,59 2 6,67 0,30 0,28 16,00 24,83 1,16 0,87

Clusia melchiorii 6 0,39 3 10,00 0,44 0,30 10,00 31,19 1,13 0,69

Clusia paralicola 4 0,26 4 13,33 0,59 0,25 12,00 31,83 1,10 0,51

Myrciaria glazioviana 5 0,33 5 16,67 0,74 0,03 7,00 7,96 1,10 0,36

Sapium glandulosum 4 0,26 2 6,67 0,30 0,53 22,00 42,97 1,09 0,79

Bunchosia cf. acuminata 6 0,39 4 13,33 0,59 0,10 12,00 15,92 1,08 0,49

Ardisia guianensis 4 0,26 4 13,33 0,59 0,21 13,00 38,83 1,06 0,47

Byrsonima crispa 5 0,33 3 10,00 0,44 0,25 18,00 31,51 1,02 0,58

Ficus americana subsp. guianensis 6 0,39 3 10,00 0,44 0,17 20,00 29,28 1,00 0,56

Miconia amacurensis 5 0,33 4 13,33 0,59 0,08 14,00 14,64 1,00 0,40

Inga ingoides 4 0,26 3 10,00 0,44 0,28 10,00 37,56 0,98 0,54

Aspidosperma subincanum 6 0,39 3 10,00 0,44 0,12 12,00 20,05 0,95 0,51

Ocotea cf. indecora 3 0,20 3 10,00 0,44 0,30 8,00 47,75 0,94 0,49

Pseudobombax marginatum 4 0,26 3 10,00 0,44 0,23 16,00 30,56 0,93 0,49

Ficus calyptroceras 2 0,13 2 6,67 0,30 0,50 22,00 63,66 0,92 0,63

Myrsine guianensis 4 0,26 4 13,33 0,59 0,06 11,00 15,28 0,92 0,32

Chrysophyllum rufum 3 0,20 2 6,67 0,30 0,41 20,00 40,11 0,90 0,60

Senna macranthera 2 0,13 2 6,67 0,30 0,47 13,00 60,48 0,89 0,60

Triplaris gardneriana 4 0,26 2 6,67 0,30 0,30 16,00 41,06 0,85 0,56

Senna quinquangulata 3 0,20 2 6,67 0,30 0,35 18,00 40,43 0,85 0,55

Myrcia decorticans 3 0,20 3 10,00 0,44 0,20 12,00 32,47 0,84 0,39

Mangifera indica 1 0,07 1 3,33 0,15 0,60 15,00 70,35 0,81 0,66

Myrcia multiflora 1 0,07 1 3,33 0,15 0,57 20,00 69,07 0,79 0,64

Cordia trichotoma 3 0,20 2 6,67 0,30 0,29 19,00 39,79 0,78 0,48

Cordia cf. taguahyensis 3 0,20 2 6,67 0,30 0,26 18,00 33,74 0,75 0,45

Pouteria cf. reticulata 3 0,20 3 10,00 0,44 0,11 16,00 26,10 0,75 0,30

Trischidium molle 5 0,33 2 6,67 0,30 0,08 12,00 17,83 0,70 0,41

Ocotea cf. notata 4 0,26 2 6,67 0,30 0,15 18,00 23,55 0,70 0,41

Senna pendula 3 0,20 3 10,00 0,44 0,06 13,00 14,01 0,70 0,26

Schweiggeria floribunda 2 0,13 2 6,67 0,30 0,24 15,00 41,38 0,67 0,37

Styrax camporum 3 0,20 1 3,33 0,15 0,27 12,00 41,38 0,61 0,46

Anadenanthera colubrina 2 0,13 2 6,67 0,30 0,15 17,00 31,83 0,58 0,28

Oreopanax capitatus 2 0,13 2 6,67 0,30 0,13 10,00 28,01 0,56 0,26

Thysordium spruceanum 2 0,13 2 6,67 0,30 0,11 20,00 26,10 0,53 0,24

Dulacia guianensis 4 0,26 1 3,33 0,15 0,11 8,00 24,83 0,52 0,37

Alseis floribunda 1 0,07 1 3,33 0,15 0,29 10,00 49,02 0,50 0,35

38


Syagrus cearensis 2 0,13 2 6,67 0,30 0,08 16,00 18,78 0,50 0,21

Apeiba tibourbou 2 0,13 2 6,67 0,30 0,07 11,00 22,92 0,50 0,20

Ouratea cuspidata 2 0,13 2 6,67 0,30 0,06 12,00 16,87 0,49 0,19

Coccoloba obtusifolia 4 0,26 1 3,33 0,15 0,07 9,00 18,46 0,48 0,33

Matayba guianensis 2 0,13 2 6,67 0,30 0,04 10,00 17,51 0,47 0,17

Cabralea canjerana 2 0,13 1 3,33 0,15 0,18 15,00 31,51 0,46 0,31

Heisteria blanchetiana 2 0,13 2 6,67 0,30 0,01 7,00 7,00 0,44 0,14

Abarema jupunba 3 0,20 1 3,33 0,15 0,09 14,00 18,78 0,44 0,29

Byrsonima stipulacea 2 0,13 1 3,33 0,15 0,16 22,00 29,28 0,43 0,29

Jacaratia spinosa 1 0,07 1 3,33 0,15 0,21 11,00 42,02 0,43 0,28

Psychotria sp. 2 0,13 1 3,33 0,15 0,14 17,00 32,47 0,41 0,27

Celtis spinosa 3 0,20 1 3,33 0,15 0,04 9,00 11,46 0,38 0,24

Clusia melchioriii 1 0,07 1 3,33 0,15 0,15 8,00 35,65 0,37 0,22

Poincianella bracteosa 2 0,13 1 3,33 0,15 0,08 16,00 24,83 0,36 0,21

Myrtaceae sp. 2 0,13 1 3,33 0,15 0,06 15,00 18,46 0,34 0,19

Acnistus arborescens 1 0,07 1 3,33 0,15 0,11 17,00 29,60 0,32 0,17

Andira inermis 1 0,07 1 3,33 0,15 0,09 18,00 27,06 0,30 0,15

Faramea multiflora 2 0,13 1 3,33 0,15 0,02 8,00 10,19 0,30 0,15

Cassia grandis 1 0,07 1 3,33 0,15 0,08 14,00 26,42 0,30 0,15

Prunus myrtifolia 1 0,07 1 3,33 0,15 0,06 10,00 21,96 0,27 0,12

Eugenia aff. culicina 1 0,07 1 3,33 0,15 0,06 20,00 21,65 0,27 0,12

Ficus americana 1 0,07 1 3,33 0,15 0,06 15,00 21,65 0,27 0,12

Guarea macrophylla subsp.

tuberculata

1 0,07 1 3,33 0,15 0,05 10,50 20,05 0,26 0,11

Byrsonima gardneriana 1 0,07 1 3,33 0,15 0,05 13,00 19,74 0,26 0,11

Pereskia grandifolia 1 0,07 1 3,33 0,15 0,04 7,00 19,10 0,26 0,11

Luetzelburgia auriculata 1 0,07 1 3,33 0,15 0,04 9,00 18,46 0,25 0,11

Pouteria sp. 1 0,07 1 3,33 0,15 0,04 8,00 18,46 0,25 0,11

Myrcia spectabilis 1 0,07 1 3,33 0,15 0,04 8,00 17,51 0,25 0,10

Myrcia sp. 1 0,07 1 3,33 0,15 0,03 9,00 16,55 0,25 0,10

Brosimum gaudichaudii 1 0,07 1 3,33 0,15 0,02 13,00 14,32 0,24 0,09

Mimosa arenosa 1 0,07 1 3,33 0,15 0,02 12,00 14,01 0,24 0,09

Eugenia sp.2 1 0,07 1 3,33 0,15 0,02 15,00 12,73 0,23 0,08

Posoqueria longiflora 1 0,07 1 3,33 0,15 0,02 8,00 12,73 0,23 0,08

Guettarda viburnoides 1 0,07 1 3,33 0,15 0,01 10,00 11,14 0,23 0,08

Simaba guianensis 1 0,07 1 3,33 0,15 0,01 9,00 11,14 0,23 0,08

Eugenia acutata 1 0,07 1 3,33 0,15 0,01 11,00 10,82 0,23 0,08

Palicourea rudgeoides 1 0,07 1 3,33 0,15 0,01 2,00 9,55 0,22 0,08

Micropholis guianensis 1 0,07 1 3,33 0,15 0,01 9,00 8,59 0,22 0,07

Acalypha villosa 1 0,07 1 3,33 0,15 0,01 7,50 7,96 0,22 0,07

Garcinia gardeneriana 1 0,07 1 3,33 0,15 0,01 7,00 7,32 0,22 0,07

Gustavia augusta 1 0,07 1 3,33 0,15 0,00 6,50 6,05 0,22 0,07

Myrcia aff. racemosa 1 0,07 1 3,33 0,15 0,00 6,00 5,41 0,22 0,07

Myrciaria sp. 1 0,07 1 3,33 0,15 0,00 5,00 4,77 0,22 0,07

Senna hirsuta 1 0,07 1 3,33 0,15 0,00 4,00 4,77 0,22 0,07

39


Table 3. Richness, Shannon-Wiener (H’), Simpson index (D), Pielou’s evenness (J’),

species and families with highest IV (importance value) among each topographic

category and the whole mountain.

Richness

Species/Families

H’ D J’ Species highest IV Families highest IV

Top

(TMA)

54/25 3.233 0.062 0.810 Mollinedia ovata

Myrcia splendens

Guapira nitida

Nyctaginaceae

Myrtaceae

Monimiaceae

Windward

(WMA)

78/35 3.859 0.031 0.886 Myrcia splendens

Guapira nitida

Cupania impressinervia

Myrtaceae

Nyctaginaceae

Rubiaceae

Leeward

(LMA)

95/34 4.033 0.024 0.887 Handroanthus serratifolius

Pilocarpus spicatus

Senegalia poliphylla

Bignoniaceae

Rutaceae

Fabaceae

SEMA 144/44 4.182 0.027 0.841 Myrcia splendens

Guapira nitida

Mollinedia ovata

Myrtaceae

Nyctaginaceae

Fabaceae

40


Table 4. Pearson correlation test (r) of passive ecological variables with axes 1 and 2 of

correspondence analysis. *significant at the 0.01 level.

Ecological variables Axis 1 Axis 2

Temperature - 0.715* 0.415*

Precipitation - 0.580* 0.802*

Elevation - 0.086 - 0.058

Slope - 0.095 0.190*

41


Figure legends

Figure 1. Map of Ceará state, Brazil showing the mountain forests locations (in gray) and

detail of the studied area with altitudinal scale, where the delimited region comprises the

protected area of the Maranguape Mountain (SEMA). Datum, SAD 69, Date, March

2017.

Figure 2. Sample design: A the distribution of the areas with transects in each topographic

category, B an example area with transects and its distances measurements and C the

method of sampling trees in each point-centered quarter, until two tree by quarter. *If the

first sampling individual has less than 30cm of PBH (perimeter at breast height), we

sampled another one with more than 30cm.

Figure 3. Correspondence analysis by the abundance of species for the three sample areas

at Serra de Maranguape, northeastern Brazil. Eigenvalues: Axis 1 = 50.5%, and Axis 2 =

20.3%. P value = 0.001 in both axes.

Figure 4. Canonical correspondece analysis between environmental parameters and

species distribution of leeward, windward and top sides from Baturité and Maranguape

mountains. Eigenvalues: Axis 1 = 68.8% , and Axis 2 = 60% . P value = 0.025 in both

axes.

Figure 5. Unweighted pair group method with arithmetic mean with Jaccard coefficient

as distance measure, illustrating the similarity in floristic patterns at the species level

among Mountain Forests and Caatingas of Ceará state. Cophenetic coefficient = 0.78

See table 1 for locality names.

Figure 6. Non-metric multidimensional scaling yielded by the species data showing the

floristic connections among Mountain Forests and Caatingas of Ceará state. Eigenvalues:

Axis 1 = 55.7%, and Axis 2 = 23.3%. P value (proportion of randomized runs with

stress ≤ observed stress) = 0.01 in both axes. Final stress = 13.71. See table 1 for locality

names.

42


Figures

Figure 1

43


Figure 2

44


Figure 3

45


Figure 4

46


Figure 5

Figure 6

47


CHAPTER II

POLLEN-BASED CHARACTERIZATION OF MONTANE FOREST TYPES IN

NORTH-EASTERN BRAZIL *

*MANUSCRIPT PUBLISHED IN REVIEW OF PALAEOBOTANY AND PALYNOLOGY

(https://doi.org/10.1016/j.revpalbo.2016.07.003)

Vincent Montade1,2*, Ivan Jeferson Sampaio Diogo3, Laurent Bremond1,2, Charly Favier1,

Itayguara Ribeiro da Costa4, Marie-Pierre Ledru1, Laure Paradis1, Eduardo Sávio Passos

Rodrigues Martins5, Julien Burte6, Francisco Hilder Magalhães e Silva7, Christiano Franco

Verola4

1Institut des Sciences de l’Evolution de Montpellier, Université de Montpellier, CNRS, IRD,

EPHE, Place Eugène Bataillon, 34095 Montpellier, Cedex, France

2Ecole Pratique des Hautes Etudes, 4-14 rue Ferrus, 75014 Paris, France

3Institute of Biology, Department of Plant Biology, State University of Campinas, UNICAMP,

13083-970, Campinas, SP, Brazil

4Departamento de Biologia, Centro de Ciências, Universidade Federal do Ceará, Pici, CEP

60455-760 Fortaleza, CE, Brazil

5Fundação Cearense de Meteorologia e Recursos Hídricos, Aldeota, Fortaleza CEP 60115-221,

CE, Brazil

6Centre de Coopéeration Internationale en Recherche Agronomique pour le Développement,

Tunis 1080, Tunisia

7Departamento de Educação, Universidade do Estado da Bahia, CEP 48970-000 Senhor do

Bonfim, BA, Brazil

48


ABSTRACT

Surface soil samples were collected in three mountainous massifs in north-eastern Brazil

to characterize the different vegetation types according to their respective pollen assemblages.

Complementary approach between pollen and vegetation data shows that the pollen rain

accurately reflects the following three main forest types: i) a dense ombrophilous forest (or

tropical moist broadleaf forest) characterized by Myrtaceae associated with high percentages of

Miconia, Guapira, Ilex, Moraceae-Urticaceae undif. or Byrsonima, ii) a seasonal semi-deciduous

montane forest characterized by an increase of Arecaceae associated with Fabaceae-Mimosideae,

Myrtaceae, Piper, Cecropia, Urera and Mitracarpus, and iii) a seasonal deciduous forest

dominated by Fabaceae-Mimosideae and Arecaceae tree taxa associated with Alternanthera,

Cyperaceae and Mitracarpus. Using of botanical data from several plots of ombrophilous forest,

in which several surface soil samples have been collected, allows to roughly estimate the over-

and underrepresentation of pollen taxa relative to their floristic abundance. Furthermore,

distribution of surface soil samples at different altitude and mountain sides also allows to

characterize vegetation variation according to several environmental parameters. The

precipitation increase with altitude is confirmed as the main environmental factor controlling

vegetation distribution. However, the forests located close to the crest with a proportion increase

of pollen taxa characteristic of heliophilous and pioneer trees (Alchornea, Miconia, Clusia), are

also influenced by changes of edaphic conditions. In addition to provide useful information in

understanding of fossil pollen records, this approach improves our understanding of the

ecosystem functioning in mountainous massifs in north-eastern Brazil, an useful knowledge for

conservation or restoration purposes.

Keywords: South America, North-eastern Brazil, Montane rainforest, Tropical forest,

Vegetation distribution, Modern pollen spectra

49


1. INTRODUCTION

Tropical mountains which harbor a high species diversity are considered as the

world's most important diversity hotspots (Barthlott et al., 2005). Indeed, interactions of

an extraordinary variety of wet and dry habitats in close proximity due to local altitudinal

climate gradients allows the coexistence of different vegetation types, contributing to the

high species richness in tropical mountains (Richter, 2008). In particular, these complex

landscapes generate climatically suitable habitats, that can shelter animals and plants from

hostile climates, which is especially important for species conservation in periods of

climate change (Shoo et al., 2011;Williams et al., 2003). In north-eastern Brazil,

mountainous massifs (or “brejo de altitude”), which form islands of moisture, where

tropical rainforests contrast with the dry forest (Caatinga) of the surrounding plain, could

be considered as such a type of habitat. Closely related to the Caatinga in terms of floristic

composition (Rizzini, 1963), these montane rainforests could be result of the evolution

from this dry to a wet forest. On the other hand, these montane rainforests harbor endemic

species of Atlantic and Amazonian forests showing a past connection between these two

biomes (Andrade-Lima, 1982), which thus illustrates the capacity of such areas to shelter

species from long-term climate changes. Several botanical surveys performed in

mountainous massifs in north-eastern Brazil allowed describing composition, density and

diversity of different forest types (e.g., Andrade et al., 2006; Araújo et al., 2007; Costa-

Junior et al., 2008; Ferraz et al., 2004). The development of these forests is related to

altitude increase, generating high orographic precipitation.However, no studies focused

on the specific impact of environmental parameters (such as precipitation) on the

distribution of these forests. Although botanical data from this region provide a

representative set of different vegetation types, they arise from discontinuous sampling,

and consequently they do not allow to link the observed vegetation changes to the closely

50


altitude-related climatic gradient. In comparison to extratropical mountains, vegetation

boundaries in tropical mountains are generally discrete (e.g., Ashton, 2003; Duarte et al.,

2005; Fernández-Palacios and de Nicolás, 1995; Hemp, 2005; Martin et al., 2007).

Discontinuities in vegetation composition may offer insights into the factors controlling

the assembly of plant communities and thus may have significance for management and

nature conservation. The present study aims to fill this gap by using pollen samples from

different plant communities along an altitudinal gradient with discontinuous botanical

data from several mountainous massifs in north-eastern Brazil. Studying modern pollen

samples in the tropics allows an accurate characterization of the different vegetation types

(e.g., Burn et al., 2010; Gosling et al., 2009; Jones et al., 2011). In addition, variations in

the pollen assemblages along altitudinal gradients are sensitive to altitudinal climate

changes (Cárdenas et al., 2014; Schüler et al., 2014; Urrego et al., 2011; Weng et al.,

2004). Here we focus on several mountainous massifs from northeastern Brazil to try to

answer the following questions: Does the modern pollen rain represent the composition

of different forest types? Using modern pollen data, do the present-day environmental

conditions explain the spatial distribution of different vegetation types? By providing a

better understanding of ecosystem functioning, the present study will be helpful in

defining conservations strategies for the rainforest of north-eastern Brazil with growing

human activities.

2. ENVIRONMENTAL SETTINGS AND METHODS

2.1 Study location

Our study was conducted in the state of Ceará of north-eastern Brazil (“Nordeste”)

in three isolated mountainous massifs named Pacatuba, Maranguape and Baturité, that

reach respectively up to 735 m, 920 m and 1115 m asl (Fig. 1). Located between 80 km

(Baturité) and 30 km (Pacatuba and Maranguape) from the coast, mineralogy of basement

51


rocks mainly consists in gneissic facies interpreted as the erosional remnants of an Early

Cretaceous rift shoulder (Peulvast and de Claudino Sales, 2004). Characterized by steep

slopes and sinuous scarps, these mountainous massifs are contrasted with the topography

and climate of the surrounding plains. Climate is defined as hot and humid in mountainous

massifs, semi-arid in lowlands and sub-humid close to coast (FUNCEME;

http://www.funceme.br/). While the temperature with annual mean of c. 27 °C in the

lowlands shows no seasonal variations, rainfalls, mainly from February to May, show a

strong seasonality. Precipitation generated by maritime trade winds is distributed along

two main gradients: (1) a precipitation decrease with the distance from the coast, and (2)

a precipitation increase with the elevation. Annual precipitation ranges from c. 1400 mm

in the coastal area to 700 mm in the interior and reach values higher than 1600 mm in the

mountainous massifs. High evapotranspiration (generally between 2000 and 3000 mm yr

−1) causes an important water deficit resulting in a semi-arid climate. In mountainous

massifs, altitude increase that lowers temperature, results in cloud formation and

precipitation, enabling the development of a highly diversified tropical forest. From the

mountain top downwards, the following vegetation types are observed: a tropical moist

broadleaf forest corresponding to dense ombrophilous forest (sub-montane) according to

Veloso (2012), a seasonal semi-deciduous montane forest, and a seasonal deciduous

forest (Caatinga).

2.2 Field collection and data processing

Fieldwork was carried out in 2013 and 2014 and the modern pollen samples were

collected from surface soils. Each pollen sample consists of 10 sub-samples collected in

the upper 2 cm layer of surface soil and distributed on a plot between 1/2 and 1 ha under

homogeneous vegetation cover. In order to simultaneously obtain a representative set of

each vegetation type and a representative sampling of the climatic gradient, surface

52


samples were located at different altitudes and mountainsides (Fig. 1 and Table 1). A

complete altitudinal transect on the lee- and windward sides was sampled in the Pacatuba

Massif with an altitude interval between each sample of c. 100 m (Fig. 1c). As the Baturité

and Maranguape massifs are more disturbed by human activity, surface soil samples were

collected above 600 m asl (Fig. 1b and d). To study the pollen-vegetation relationships,

samples were collected close to the locations of the botanical surveys performed by

Araújo et al. (2007) in Baturité Massif. In Maranguape Massif four surface soil samples

(MB9, MB7, MS7a and MS7b) were collected in botanical plots performed at the same

time. Each botanical plot consists of ten parallel transects of 100 m length. Following the

point-centered quarter method (Cottam and Curtis, 1956), the nearest trees with at least

15 cm perimeter at breast height were identified along these transects. Surface samples

were collected between two or three transects depending on the topography. For MS7,

because of slight difference in altitude, species composition and vegetation structure, the

plot was split in two sub-groups: a group of eight transects below 700 m asl corresponding

to the surface sample MS7a and a group of two transects above 700 m asl corresponding

to the surface samples MS7b.

After sampling, surface soil samples were transported to the laboratory and stored

in a cold room at 5 °C. To extract pollen grains, an aliquot of 2 cm3 for each sample was

chemically treated, adapting the method of Faegri and Iversen (1975). Surface samples

were processed by five successive KOH (10%) at 70 °C to remove humic acids followed

by HF (70%) to eliminate silicates and by the standard acetolysis method. Prior to

chemical treatment, a calibrated Lycopodium tablet was added to each sample in order to

calculate the pollen concentrations (Stockmarr, 1972). Palynomorphs were counted and

identified using a light microscope (Leica) at 1000×magnification after mounting slides

with residues and glycerine. At least 300 pollen grains were counted for each sample and

53


119 pollen and spore taxa were identified using the reference collection of M.-P. Ledru

(IRD pollen collection) and several specialized publication on pollen morphology

(Colinvaux et al., 1999; Leal et al., 2011; Roubick and Moreno, 1991; Rull, 2003).

Fig. 1. General locationmaps of (a)mountainousmassifs in north-eastern Brazilwith the locations of their

respectivemodern pollen samples (b, c and d). (e) and (f) represent the transect location performed on

themean annual precipitation values based onWorldClimdatabase (Hijmans et al., 2005). Satellite image

romBingmaps) and elevation maps (fromASTER Global Digital Elevation Model from METI and NASA)

were plotted using QGIS software (QGIS Development Team, 2015).

All statistical analyses were performed on the pollen taxa with percentages ≥1%

and percentages were calculated on a pollen sum excluding fern spores. Pollen spectra

(Fig. 2) were plotted using PSIMPOLL 4.10 software (Bennett, 1994). Pollen-vegetation

54


representativeness ratios were calculated for the four surface samples collected in the

botanical plot of the Maranguape Massif by calculating the p/v values (% of arboreal

pollen/%of total stems of all taxa inplot). Only for p/v values, pollen percentages were

calculated on the arboreal pollen sum(Appendix A). As described by Gosling et al. (2009)

this ratio is intended to assess the relative pollen productivity and dispersal of different

pollen taxa (Fig. 3). In order to determine correlations between the spatial distribution of

vegetation groups and environmental data from pollen assemblages, Correspondence

Analysis (CA) was carried out (Figs. 4, 5 and Appendix B). Correspondence Analysis is

a classically used ordination method to summarize the patterns of variations among a

collection of pollen assemblages, as it is well suited to contingency tables. Different or

more refined commonly used ordination methods were also tested (Principal

Correspondence Analysis, square-root transform of percentages, Detrended

Correspondence Analysis) but they lead to similar results. Environmental parameters

such as slope angle and distance to the crest were calculated using QGIS software (QGIS

Development Team, 2015) running the ASTER Global Digital Elevation Model (from

METI and NASA). Mean annual precipitation (MAP) values for the period 1950–2000

were obtained using the WorldClim database for each location of the surface samples.

As the Maranguape and Pacatuba massifs occupy relatively small areas, without

any meteorological stations, the climatic altitudinal gradient is not well resolved at

WorldClim resolutions. Contrariwise, from the Baturité Massif, being larger than the

Maranguape and Pacatuba massifs, more precise meteorological data are available, which

allow obtaining a realistic pattern of precipitation changes according to elevation. A

second estimation of MAP (hereafter MAP2) was then obtained by assuming that

altitude/precipitation patterns are the same over the three massifs. Altitude and MAP were

related along an altitudinal transect between thewind- and leeward side of the Baturité

55


Massif and two non-linear regression fits were performed to model altitudinal variations

of MAP wind- and leeward (Fig. 1e and f).The obtained equations were applied to all

surface sample locations. Then, an increase of 200 mm was added for all samples of

Pacatuba and Maranguape in order to take into account the observed difference in MAP

recorded in rainfall stations located in the lowland at a greater proximity to the seashore.

(Hijmans et al., 2005). The first estimates of MAP is denoted hereafter MAP1 (Table 1).

3. RESULTS

3.1 Modern pollen assemblages

According to their respective altitudinal ranges and their main pollen taxa based

on percentage values, the different vegetation types can be characterized by the following

pollen assemblages (Fig. 2 and Table 2).

Table 1

Names and locations of surface samples with their ecological and environmental parameters. Lat S and

LonW: latitude south and west;MAP: Mean Annual Precipitation; Veg: vegetation type; DF: Deciduous

Forest; SDF: Semi-Deciduous Forest; OF: Ombrophilous Forest (*close to the crest).

Site Massif Lat

S

Lon

W

Altitude

m asl

Side Distance to

the crest m

Slope

°

MAP 1

mm

MAP 2

mm

Veg Human

disturbance

PS11 Pacatuba -3.98 -38.62 130 Windward 2529 10 1296 1228 DF Low

PS9 Pacatuba -3.98 -38.63 158 Windward 2514 26 1272 1269 DF Low

PS8 Pacatuba -3.99 -38.63 263 Windward 2350 16 1272 1401 SDF High

PS10 Pacatuba -3.97 -38.62 312 Windward 2056 32 1320 1451 SDF Low

PS7 Pacatuba -3.99 -38.63 383 Windward 2079 27 1272 1514 SDF Moderate

PS1 Pacatuba -3.97 -38.63 411 Windward 1720 17 1440 1536 SDF Moderate

PS6 Pacatuba -3.98 -38.63 569 Windward 1633 18 1416 1635 OF Low



PS4 Pacatuba -3.98 -38.64 724 Windward 446 19 1428 1700 OF Undisturbed


PC2* Pacatuba -3.97 -38.64 765 Windward 34 14 1464 1713 OF* Undisturbed

PS12 Pacatuba -3.98 -38.66 575 Leeward 414 18 1428 1544 SDF Moderate

PS13 Pacatuba -3.99 -38.66 489 Leeward 657 32 1296 1459 SDF Moderate

PS14 Pacatuba -3.99 -38.67 395 Leeward 986 23 1296 1353 DF Moderate



Bsal Baturité -4.26 -38.98 735 Leeward 580 14 1548 1476 DF Low

Bjar Baturité -4.29 -39.00 760 Leeward 1411 3 1512 1494 SDF Low

56


Btav Baturité -4.30 -38.92 600 Windward 433 15 1500 1450 OF Low

Bsin Baturité -4.29 -38.93 647 Windward 840 17 1524 1470 OF Low

Barv Baturité -4.24 -38.93 816 Windward 350 12 1560 1528 OF Low

Blag* Baturité -4.21 -38.97 940 Windward 0 31 1584 1557 OF* Low

MB7 Maranguape -3.91 -38.72 730 Windward 800 16 1464 1702 OF Low

MS4* Maranguape -3.90 -38.72 850 Windward 37 21 1524 1737 OF* High

MB9* Maranguape -3.90 -38.72 934 Windward 30 17 1524 1756 OF* Undisturbed

MS5* Maranguape -3.89 -38.72 950 Windward 8 19 1524 1759 OF* Undisturbed

MS7a Maranguape -3.91 -38.73 700 Leeward 1260 6 1476 1650 OF Low

MS7b Maranguape -3.91 -38.73 659 Leeward 1500 12 1392 1617 OF Low

The dense ombrophilous forest (sub-montane): in this forest type, Myrtaceae

remains among the most frequent tree pollen taxa associated with high percentages of

Miconia (Melastomataceae), Guapira (Nyctaginaceae), Ilex (Aquifoliaceae), Moraceae-

Urticaceae undif. or Byrsonima (Malpighiaceae). The dominance of these pollen taxa is

generally observed from the upper limit of the semi-deciduous montane forest upwards.

However, pollen assemblages of ombrophilous forests located close to the crest or to the

mountain top reveal some differences. Indeed, in these samples we recorded a percentage

increase of Miconia, Alchornea (Euphorbiaceae) or Mitracarpus (Rubiaceae) and a slight

increase of Clusia (Clusiaceae). The altitude in which such assemblages are observed,

changes according to the maximum elevation of mountainous massifs, ~900 m asl at

Baturité and Maranguape and ~700 m asl at Pacatuba.

57


Fig. 2. Percentage pollen diagram of surface soil samples of the three mountainous massifs studied in the

north-eastern Brazil. Pollen taxa in bold represent arboreal elements and the other correspond to shrubs or

herbs. Samples located on the mountain top are indicated by “*”.

The seasonal semi-deciduous montane forest: in this forest type, Arecaceae, the

most frequent tree pollen taxon, is associated with Fabaceae-Mimosideae, Myrtaceae,

Piper (Piperaceae), Cecropia (Urticaceae), Urera (Urticaceae) and Mitracarpus. These

assemblages are recorded up to ~500 m asl on the windward side and up to ~600 m asl

on the leeward side. The seasonal deciduous forest: the tree pollen signature is mainly

characterized by Fabaceae-Mimosideae and Arecaceae and the percentages of herbaceous

pollen taxa, such as Alternanthera (Amaranthaceae), Cyperaceae and Mitracarpus,

increase. This pollen assemblage is observed from the base up to ~200 m asl on the

windward side and up to ~400 m asl on the leeward side. In Baturité Massif, located more

58


inland than massifs of Pacatuba and Maranguape, this pollen assemblage is observed up

to ~700 m asl on the leeward side.

Table 2

Main pollen taxa ordered by their respective percentage values for each surface soil samples. Arboreal

pollen taxa are represented in bold. Surface soil samples are ordered according to axis 1 values of the

correspondence analysis (CA) except for the five underlined samples removed from the CA. Color scale of

surface samples from black to light gray represents the three main vegetation types, fromthe ombrophilous,

semi-deciduous to deciduous forest (samples with “*” indicate ombrophilous forest located close to the

crest).

Names Main pollen taxa

MS5* Miconia 50, Guapira 15, Serjania-Cupania type 4, Myrsine 4, Myrtaceae 3, Alchornea 2

MS4* Alchornea 63, Miconia 11, Piper 5, Poaceae 3, Mitracarpus 2

MB9* Moraceae-Urticaceae undif. 21, Miconia 13, Asteraceae tubuliflorae 8, Myrtaceae 5, Guapira 4, Alchornea 4, Solanum

3

MB7 Myrtaceae 26, Guapira 19, Miconia 7, Mitracarpus 5, Borreria 5, Tetrapteris 4, Ilex 3, Moraceae-Urticaceae undif. 2

PS4 Myrtaceae 40, Guapira 24, Mitracarpus 4, Cyperaceae 3, Poaceae 3

PS3 Guapira 29, Mitracarpus 12, Myrtaceae 9, Protium 7, Piper 4, Clusia 4, Moraceae-Urticaceae undif. 4, Miconia 3

PS2 Guapira 16, Zanthoxylum type 14, Anthurium type tetragonum 14, Mitracarpus 7, Cyperaceae 6, Myrtaceae 4,

Arecaceae 4, Miconia 3

Blag* Guapira 17, Mitracarpus 16, Zanthoxylum type 7, Myrsine 6, Myrtaceae 6, Clusia 5, Ilex 5

PS5 Ilex 40, Mitracarpus 12, Myrtaceae 9, Arecaceae 5, Cyperaceae 4, Moraceae-Urticaceae undif. 3

MS7a Myrtaceae 16, Ilex 9, Fabaceae-Mimosideae 7, Mitracarpus 6, Piper 5, Miconia 4, Cyperaceae 4, Gallesia 4, Byrsonima

4

MS7b Myrtaceae 22, Mitracarpus 13, Guapira 9, Zanthoxylum type 6, Tetrapteris 5, Moraceae-Urticaceae undif. 4,

Fabaceae-Mimosideae 3, Piper 3

PC2* Mitracarpus 35, Ilex 10, Guapira 9, Myrtaceae 7, Zanthoxylum type 3, Asteraceae tubuliflorae 3, Clusia 3

PS6 Arecaceae 19, Mitracarpus 16, Borreria 6, Protium 6, Piper 4, Myrtaceae 4, Coutarea 4, Guapira 4

Barv Byrsonima 81, Mitracarpus 6, Myrtaceae 3, Miconia 2

Bsin Byrsonima 53, Mitracarpus 8, Miconia 7, Myrtaceae 3

Btav Byrsonima 23, Miconia 21, Mitracarpus 14, Poaceae 10, Sida 2, Moraceae-Urticaceae undif. 2

PS1 Mitracarpus 14, Borreria 10, Arecaceae 8, Piper 7, Tetrapteris 6, Cecropia 4, Moraceae-Urticaceae undif. 4, Guapira 4,

Fabaceae-Mimosideae 4

PS12 Cecropia 31, Arecaceae 9, Piper 8, Mitracarpus 8, Moraceae-Urticaceae undif. 6, Myrtaceae 5, Astronium 4,

Fabaceae-Mimosideae 4, Miconia 3

PS7 Arecaceae 29, Cecropia 20, Piper 7, Miconia 7, Fabaceae-Mimosideae 4, Zanthoxylum type 3

PS13 Arecaceae 28, Protium 12, Tetrapteris 11, Piper 6, Cecropia 4, Zanthoxylum type 4, Mitracarpus 4, Fabaceae-

Mimosideae 3

PS8 Urera 43, Arecaceae 17, Cecropia 7, Mitracarpus 5, Myrtaceae 4, Fabaceae-Mimosideae 3, Poaceae 2

PS10 Arecaceae 31, Myrtaceae 14, Fabaceae-Mimosideae 8, Mitracarpus 5, Zanthoxylum type 5, Moraceae-Urticaceae

undif. 4

Bsal Mitracarpus 34, Piper 14, Alternanthera 12, Fabaceae-Mimosideae 7, Moraceae-Urticaceae undif. 5, Arecaceae 4,

Myrtaceae 3, Cecropia 2

PS11 Fabaceae-Mimosideae 25, Mitracarpus 20, Cyperaceae 17, Althernanthera 11, Myrtaceae 8, Arecaceae 4, Poaceae 3

Bjar Mitracarpus 32, Alternanthera 24, Fabaceae-Mimosideae 8, Arecaceae 8, Sapium 4, Myrtaceae 3

PS16 Clidemia 22, Mitracarpus 20, Alternanthera 13, Fabaceae-Mimosideae 12, Cecropia 6, Arecaceae 5, Cyperaceae 3

PS14 Fabaceae-Mimosideae 36, Arecaceae 24, Senna 5, Cecropia 4, Piper 3, Moraceae-Urticaceae undif. 3

PS15 Fabaceae-Mimosideae 50, Alternanthera 12, Mitracarpus 9, Arecaceae 8, Cecropia 4

PS9 Fabaceae-Mimosideae 68, Arecaceae 8, Cyperaceae 7, Mitracarpus 3, Poaceae 2

59


3.2. Representativeness of pollen taxa in the ombrophilous forest

Within the botanical plots of the ombrophilous forest studied in the Maranguape

Massif, in which surface soil samples have been collected (MB9, MB7, MS7a, MS7b),

between thirteen and seventeen woody taxa are present in both the vegetation and pollen

rain (see Appendix A). Principal among them is Myrtaceae, which is the most common

taxon (~20% stems) in all the plots. In order to compare the relative representativeness of

the pollen rain to the vegetation, we selected the p/v values for the twelve taxa that are

most significant in the vegetation and pollen rain (Fig. 3). Although the p/v values can

vary between plots for a same taxon, we recognized three main groups of important taxa.

The taxa of the first group, characterized by Moraceae-Urticaceae undif. (mean p/v = 5.1),

Miconia (3.9), Alchornea (2.3) and Areaceae (2), are highly overrepresented in the pollen

rain relative to their abundance in the vegetation. Except for Arecaceae, the p/v values for

all the plots are higher than 2. The second group, that is also overrepresented, is

characterized by taxa with mean p/v values between 1 and 2: Guapira (mean p/v= 1.6),

Myrtaceae (1.3) and Byrsonima (1.2). The taxa Rubiaceae undif. (mean p/v= 0.9), Clusia

(0.8), Fabaceae-Mimosideae (0.8), Zanthoxylum (Rutaceae) type (0.7) and Serjania-

Cupania type (0.2) that correspond to the third group, are generally underrepresented in

the pollen rain relative to their abundance in the vegetation. Several taxa, Bignoniaceae,

Lauraceae, Monimiaceae and Phyllanthaceae, including significant woody species such

as, Handroanthus serratifolius, Nectandra cuspidata, Cinnamomum triplinerve,

Mollinedia ovata, Margaritaria nobilis, are completely absent in the pollen rain.

60


Fig. 3. p/v values according to arboreal taxa present in both the pollen rain and vegetation of the botanical

plots from Maranguape Massif (in black). The p/v ratio corresponds to “% of arboreal pollen / % of total

stems of all taxa in plot”. Values higher and lower than 1 respectively characterize the pollen taxa over-

and underrepresented. Taxa in gray are absent in the pollen rain.

3.3. Multivariate data analysis

Among the 91 different pollen taxa identified, 64 pollen taxa occurring with a

frequency higher than 1% have been used to perform the CA. A first CA analysis clearly

separates a group that includes all samples except five outlier samples (see Appendix B).

These samples characterize the ombrophilous forest of the Baturité Massif with high

frequencies of Byrsonima (Btav, Bsin and Barv) or highly disturbed vegetation (PS8 and

MS4). In order to improve ordination results and provide a better understanding of the

relationships between pollen assemblages and natural vegetation distribution, the outlier

samples were removed and a new CA was performed (Fig. 4). Eigenvalues for the first

and second axes represent respectively 17.8% and 11.7% of the total variation. The

distribution of samples in the CA diagram (Fig. 4a) displays a continuous pattern along

axis 1 which reflects the vegetation variation from the seasonal deciduous forest, the

seasonal semi-deciduous montane forest to the dense ombrophilous forest (sub-montane).

61


Along this gradient we observe a clear distinction between these three main vegetation

types. Ombrophilous forests located close to the crest or to the mountain top are not well

defined by the CA except for two samples from the Maranguape Massif (MS5 and MB9).

Several passive environmental parameters (Altitude, MAP1, MAP2, Slope and Distance

to the crest) have been projected in the axes 1–2 bi-plot of the CA. As shown in Fig. 4b

and by the correlation coefficient (Table 3), the environmental parameters are mainly

correlated with axis 1. The closest environmental parameters related to axis 1 are MAP2

(0.87), altitude (0.81), MAP1 (0.67) and distance to the crest (−0.66). The main

correlation concerning axis 2 is with the Slope (0.19).

Table 3

Pearson correlation test (r) of passive ecological variables with axes 1 and 2 of correspondence analysis.

Fig. 4. Bi-plot of correspondence analysis for axes 1 and 2 with (a) distribution of surface soil samples and

(b) projection of passive environmental parameters. Empty circles represent samples of ombrophilous forest

located close to the crest.

Ordination of the pollen taxa according to axis 1 values reveals a distribution

pattern similar to the pollen taxa distribution observed in our synthetic pollen diagram

according to the altitudinal gradient (Fig. 5a). Altitude and precipitation values of surface

62


samples plotted according to axis 1 values reflect the general structure of the three main

vegetation types (Fig. 5b and c). We observe that the samples of the seasonal deciduous

forest remain below 400 m asl with an annual precipitation lower than 1400 mm and the

samples of the seasonal semi-deciduous montane forest remain below 600 m asl with an

annual precipitation of 1400–1600 mm. Two samples of the Baturité Massif (Bjar and

Bsal) differ from this general pattern showing altitude values higher for their respective

forest type than at the Pacatuba Massif. For the ombrophilous forest, all samples (except

PS6), are located above 600 m asl with an annual precipitation higher than 1600 mm.

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Fig. 5. (a) The distribution of main pollen taxa percentages discussed in the text, (b) the altitude values of

surface soil samples and (c) the mean annual precipitation of surface soil samples according to axis 1 values

of the correspondence analysis.

4. Discussion

4.1. Pollen-vegetation relationship and characteristic pollen taxa

One of the most typical features of the dense ombrophilous forests (sub-montane)

of the mountainous massifs from north-eastern Brazil, is the dominance of Myrtaceae

which represents the most diversified tree family (Lima et al., 2009; Siqueira et al., 2001).

A dominance of Myrtaceae is evident in the massifs of Baturité and Maranguape, for

instance, only in Baturité more than forty species of Myrtaceae have been identified

(Araújo et al., 2007). In the pollen rain, although Myrtaceae is not always the most

abundant pollen taxon, it remains among the main arboreal pollen percentages in the

ombrophilous forest in all mountainous massifs (Fig. 2 and Table 2). However, in both

the vegetation and pollen rain, the association of Myrtaceae with other dominant taxa

allows to characterize different communities within the ombrophilous forests. In the

Baturité Massif, among the most dominant trees, species of Myrtaceae such as Myrcia

splendens are frequently associated with Byrsonima sericea, Clusia nemorosa, Miconia

cecidophora or Ilex sapotifolia (Araújo et al., 2007; Cavalcante et al., 2000). Pollen

contents of this vegetation type (Barv, Bsin and Btav) from surface soil samples collected

in Baturité are characterized by a high amount of Byrsonima in the pollen rain associated

with Miconia and Myrtaceae (Fig. 2).

In the Pacatuba and Maranguape massifs, Byrsonima is no longer among the main

pollen taxa and Myrtaceae is frequently associated with Guapira, Miconia and Moraceae-

Urticaceae undif. in surface soil samples from the ombrophilous forest (Fig. 2 and Table

2). This difference in pollen contents observed between the Baturité and Pacatuba/

Maranguape massifs is also supported by botanical data. Indeed, at Maranguape, while

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species of Myrtaceae remain the most abundant and diversified tree family (see Appendix

A), the most common trees identified are M. splendens, Guapira nitida and Cupania

impressinervia. On the leeward side (MS7a and MS7b), the forest composition changes

slightly and the latter trees are frequently associated with Pilocarpus spicatus, H.

serratifolius and several species of Fabaceae-Mimosideae such as Senegalia polyphylla.

These forest composition changes are also partly observed in the corresponding pollen

assemblages of the leeward side with a slight increase of Fabaceae-Mimosideae and

Zanthoxylum type (including Pilocarpus) (Fig. 2).

The forests located closer to the crest or on the mountain top differ partly in their

structure and composition from the ombrophilous forest located just below. This forest

type is generally characterized by a lower canopy and a high proportion of epiphytic

plants. Among the trees, an increase of Alchornea glandulosa, Miconia mirabilis, C.

nemorosa and C. melchiorii is observed in the Baturité and Maranguape massifs (Araújo

et al., 2007 and Appendix A). In the tropical rainforest, these species are considered as

pioneer and heliophilous trees (Pessoa et al., 2012; Souza et al., 2006). In addition, several

species of Clusia (e.g., C. nemorosa) can facultatively apply crassulacean acid

metabolism (CAM) or C3 metabolism according to water availability (Lüttge, 2006;

Vaasen et al., 2006). Species characterized by this a useful adaptation have the ability to

adjust to dry conditions by switching to the CAM mode, but also back to the C3 mode

under humid conditions. The pollen rain from surface soil samples located close to the

crest also reveals these changes in composition of trees with high frequencies of

Alchornea, Miconia (MS5, MS4) or a slight percentage increase of Clusia (Blag).

Representativeness increase of such taxa in both the pollen rain and vegetation, probably

highlights specific environmental conditions prevailing on the mountain tops or areas

located close to the crest.

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The forest composition of seasonal semi-deciduous and deciduous montane

forests was studied in two plots on the leeward side of the Baturité Massif (Bjar and Bsal,

Araújo et al., 2007). In this zone, the Myrtaceae, which is no longer the structural family,

is replaced in abundance and diversity by the Euphorbiaceae (i.e. Sebastiania

macrocarpa, Manihot carthaginensis, Croton blanchetianus, Croton argyrophylloides,

Sapium obovatum), Fabaceae-Mimosideae (i.e. Mimosa caesalpiniifolia, Mimosa

arenosa) and Fabaceae-Caesalpinioideae (i.e. Bauhinia cheilantha). Species of Fabaceae-

Mimosideae and Euphorbiaceae are frequent components of the Caatinga growing

generally under low humidity conditions prevailing in the lowlands of northeastern Brazil

(Ferraz et al., 1998). Their associated pollen assemblages are characterized by a decrease

of Myrtaceae at the expense of Fabaceae-Mimosideae and by high frequencies of

herbaceous pollen taxa (Mitracarpus or Alternanthera). This change in pollen signature

highlights an opening of the forest canopy, as shown in other semi-arid regions in north-

eastern Brazil (dos Santos et al., 2015; Gomes et al., 2014). Most of the surface soil

samples of the semi-deciduous montane forest were collected at Pacatuba. They differ

from the deciduous forest samples by an increase in Arecaceae pollen frequencies (Fig.

2). Moreover, the pollen rain of the semi-deciduous forests shows a significant increase

of Cecropia, a pioneer tree taxon (Santo-Silva et al., 2013), and Piper indicating

secondary successional shrubs (Pearson et al., 2002). Recurrent droughts could favor the

development of these two taxa in comparison with the ombrophilous forest where higher

altitude and moisture could limit drought impact on vegetation. In addition, more frequent

human disturbance through this altitudinal range (e.g., banana crop) could also explain

the development of these taxa characteristic of forest fragmentation and regeneration.

4.2. Over- and underrepresented pollen taxa in the ombrophilous forest

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In order to compare directly the botanical with pollen data for the dense

ombrophilous forest, four surface soils samples have been collected in the same locations

as the botanical plots (MB7, MB9, MS7a and MS7b). In particular, calculating of p/v

values allowed us to obtain a rough assessment of the over- and underrepresentation of

each pollen taxon relative to their floristic abundance (Fig. 3 and see Appendix A).

Among the most significant tree taxa represented in the vegetation and pollen rain,

anemophilous taxa such as Moraceae-Urticaceae undif. and Alchornea are highly

overrepresented in all the plots. Characterized by a high pollen productivity and

dispersion, such anemophilous taxa are frequently among the most overrepresented in the

pollen rain (Burn and Mayle, 2008; Bush and Rivera, 2001; Gosling et al., 2005). Miconia

and Arecaceae which are not typical anemophilous taxa are also overrepresented in all

the plots. Generally pollinated by bees (Ishara and Maimoni-Rodella, 2011), species of

Miconia as M. mirabilis frequently identified in the Maranguape Massif are characterized

by flowers with a large number of well exposed anthers. This could favor the pollen

representation increase and can be attributed to a ‘messy pollination’ (Bush and Rivera,

2001; Horn and B, 1990).Well represented in pollen spectra, Guapira, Myrtaceae and

Byrsonima indicate mean p/v values N1 showing probably messy pollination syndromes.

Although taxa such as Myrtaceae have already been reported as overrepresented (Gosling

et al., 2009; Grabandt, 1980), the p/v values for these taxa are also variable and can reach

values b1 in several plots. The floristic composition changes between each plot, which

could partly explain the observed variability of p/v values. Other significant tree taxa

represented in the vegetation, Rubiaceae undif., Clusia, Fabaceae-Mimosideae, the

Zanthoxylum type and the Serjania-Cupania type, are rather underrepresented;

Bignoniaceae, Lauraceae, Monimiaceae and Phyllanthaceae are completely absent in the

pollen rain. Several of these taxa have already been reported as underrepresented or silent

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taxa, e.g., Clusia (Grabandt, 1980), Rubiaceae, Bignoniaceae, and the Serjania-Cupania

type (Gosling et al., 2009). Otherwise, our p/v values are also not always consistent with

previous trends observed in other regions. Among the most striking, the Zanthoxylum

type has been reported as overrepresented, while Miconia, generally included in

Melastomataceae, has been reported as underrepresented (Bush and Rivera, 2001;

Gosling et al., 2009). Apart from the fact that species included in pollen taxa are not

necessarily the same between the different regions, which certainly generates differences

in terms of pollen representation, our study focused on surface soil samples which also

could generate differences in terms of pollen preservation and representation in

comparison with studies focused on pollen traps. Although this approach based on p/v

values, including different biases, is not perfect, values for some taxa are in accordance

with predictions associated with their pollination strategy (e.g., Moraceae-Urticaceae

undif. and Alchornea) as it has been shown in different tropical regions (Bush, 1995; Bush

and Rivera, 2001; Gosling et al., 2005).

4.3. Impact of environmental factors on forest distribution

Modern pollen samples from the Maranguape, Pacatuba and Baturité massifs

closely reflect the different vegetation types along the altitudinal gradient. On the

windward side of Maranguape and Pacatuba, close to the coast, the lowland seasonal

deciduous forest is replaced by a seasonal semi-deciduous montane forest at 200m asl,

which in turn is replaced by a dense ombrophilous forest (sub-montane) at 500 m asl. The

same pattern is observed on the leeward side although each ecotone is located between

100 and 200 m higher than on the windward side. The spatial distribution of the vegetation

in mountainous areas is commonly related to precipitation and temperature changes

induced by the altitudinal gradient. The studied massifs from north-eastern Brazil are not

high enough to result in temperatures that could be considered as a direct limiting factor

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on the vegetation, as was already described from other tropical areas (Duarte et al., 2005;

Sarthou et al., 2009). Consequently, precipitation (MAP2) highly correlated with the

distribution of modern pollen samples on axis 1 of the CA represents the main factor

controlling the distribution of the different forest types (Table 3 and Fig. 4). Such a pattern

of precipitation changes is controlled by the elevation of air masses on the windward side

generating orographic precipitation. On the leeward side, the altitude decrease, warms up

and dries the air masses, which dissipate fogs, decrease rainfalls and increase evaporation.

This mechanism, the “foehn effect”, is frequently observed in tropical mountainous

islands like Hawaii (Giambelluca et al., 2013) and Cape Verde (Duarte et al., 2005). A

high correlation coefficient (r=0.82) between altitude and precipitation (MAP2) changes

of surface soil samples shows the influence of the altitude gradient on precipitation

increase and vegetation distribution.

While altitude increase represents one of the main factors influencing

precipitation, the distance from the coast is also an important factor for explaining

changes in precipitation rates. In particular, rainfall decrease is observed when the

distance from the coast increases. For example, at Baturité (80 km inland) the deciduous

forest grows up to 700 m asl on the leeward side (Bsal), while it remains below 400 m asl

on the same side at Pacatuba Massif (30 km from the coast). Slope angle could also

influence vegetation distribution. However, the slope angle has been generally shown as

a relevant factor at values N40° (Fernández-Palacios and de Nicolás, 1995). None of our

surface samples reaches such values, which could explain that no correlation is observed

between the slope angle values and the vegetation distribution revealed by the CA axes

(Table 3). Distance to the crest is inversely correlated with axis 1 of the CA, because

when this distance increases, altitude generally decreases, thus reflecting the decreasing

precipitation.

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In areas located close to the crest or on the mountain top, pollen assemblages from

surface soil samples reflect a different community of the ombrophilous forest, with

abundant heliophilous and pioneer tree taxa such as Alchornea, Clusia or Miconia.

Different edaphic conditions related to the rocky soil of the summit reduce the water-

holding capacities. Such local conditions could explain the development of plant

communities that are more dependent on atmospheric moisture and thus more strongly

correlate with changes therein. This is particularly well illustrated by a greater abundance

of epiphytic plants near the crest. In addition, associated with strong winds, the drying

effect and falling trees are more important in these areas. The strong development of

pioneer trees in these forests confirms strong dynamics and probably a high resilience

related to frequent natural disturbances. Consequently, this different forest community is

more disturbed and affected by the frequent droughts of this region than the dense

ombrophilous forest (Hastenrath and Heller, 1977). Moreover, although rainfalls would

reach their maxima close to the mountain tops, local environmental conditions induce

drier moisture conditions than in the dense ombrophilous forest, only located a few tens

of meters below. At this point, additional and exhaustive botanical surveys would be

essential to better describe such a forest community, preferably focusing on epiphytic

plant or liana diversity, which seems tobe important structural plant components at higher

elevation.

5. Conclusions

Our complementary approach between pollen analysis of surface soil samples and

present-day vegetation in mountainous massifs in north-eastern Brazil shows that the

pollen rain accurately reflects the different vegetation types. Based on the different pollen

assemblages, the following tropical forest types can be recognized: i) a dense

ombrophilous forest (or tropical moist broadleaf forest) characterized by Myrtaceae

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associated with high percentages of Miconia, Guapira, Ilex, Moraceae-Urticaceae undif.

or Byrsonima, ii) a seasonal semi-deciduousmontane forest characterized by an increase

of Arecaceae associated with Fabaceae-Mimosideae, Myrtaceae, Piper, Cecropia, Urera

and Mitracarpus, and iii) a seasonal deciduous forest dominated by Fabaceae-

Mimosideae and Arecaceae tree taxa associated with Alternanthera, Cyperaceae and

Mitracarpus. In areas located close to the crest, a different ombrophilous forest

community has been identified by the increase of Alchornea, Miconia or Clusia. Being

typical heliophilous and pioneer trees, these taxa indicate drier moisture conditions,

related to local environmental factors than in the dense ombrophilous forest just located

a few tens of meters below. Concerning the dense ombrophilous forest, pollen rain has

also been directly compared with data from several botanical plots. Although we observed

some differences with previous studies performed in tropical regions, pollen

representativeness for several taxa are conform to the predictions inferred from their

pollination strategies. In particular, anemophilous pollen taxa are always overrepresented

relative to their floristic abundance.

In addition to characterize each vegetation type, our ordination of pollen data,

based on surface soil samples distributed at different altitudes and mountain sides, allows

the reconstruction of the spatial distribution of different vegetation types. Unlike previous

studies, this approach combining vegetation and pollen data also allows studying the

influence of environmental factors on vegetation distribution. In particular, we

characterize the high importance of precipitation changes (associated with increasing

altitude) that represents the main environmental factor controlling vegetation distribution,

except for the forest located close to the crest in which changes of edaphic conditions also

seem to be important. Our study provides a better understanding of the ecosystem

functioning in mountainous massifs in north-eastern Brazil. As these areas can be

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considered as “islands” of tropical rainforest, this knowledge will be useful for

conservation or restoration purposes. Furthermore, development of this type of

comparison between pollen and vegetation data will be helpful, to improve our

understanding of fossil pollen records for reconstructing past vegetation dynamics,

climate changes and diversity processes of tropical rainforest in a semi-arid environment.

Acknowledgements

Financial support was provided by FUNCAP (CI1-0080-000170100/ 13),

FAPESP (BIOTA 2013/50297-0), NSF (DOB 1343578) and NASA and IRD. V.M.

benefited from a postdoctoral position funded by FUNCAP at FUNCEME (Brazil) and

EPHE at ISEM (France) I.J.S.D benefited from PhD position funded by CNPq (Brazil).

We thank William D. Gosling and the Editor of RPP for their very constructive and

helpful comments which have greatly contributed to improve this article. We also thank

Daniel Sabatier for the stimulating discussions and Claire-Line Montade for the help

during the fieldwork. This is Institut des Sciences de l’Evolution de Montpellier

publication n°2016-138 SUD.

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Appendix A. List of pollen taxa present in both the pollen rain and vegetation of the

botanical plots from Maranguape Massif including botanical and pollen data. Taxa

in gray represent plant families absent in the pollen rain. pbh: perimeter at breast

height

MB9

Pollen taxa Vegetation data Pollen data

No. of stems ≥ 10

cm dbh

% of total stems

(v) No. of

pollen % of pollen

(p) p/v

Myrtaceae 114 23.8 15 6.5 0.3

Guapira 62 12.9 13 5.7 0.4

Serjania-Cupania type 54 11.3 8 3.5 0.3

Miconia 28 5.8 39 17.0 2.9

Rubiaceae undif. 15 3.1 10 4.3 1.4

Clusia 13 2.7 3 1.3 0.5

Moraceae-Urticaceae undif. 13 2.7 64 27.8 10.3

Roupala 12 2.5 8 3.5 1.4

Alchornea 10 2.1 11 4.8 2.3

Ficus 6 1.3 2 0.9 0.7

Byrsonima 5 1.0 2 0.9 0.8

Solanum 3 0.6 9 3.9 6.2

Symplocos 3 0.6 4 1.7 2.8

Ilex 2 0.4 1 0.4 1.0

Senna 1 0.2 3 1.3 6.2

Pouteria 1 0.2 1 0.4 2.1

Acalypha 1 0.2 1 0.4 2.1

Total 343 71.6 194 84.3

Lauraceae 44 9.2

Monimiaceae 38 7.9

Fabaceae-Mimosideae 28 5.8

Bignoniaceae 2 0.4

Total 112 23.4

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MB7


No. of stems ≥ 10

cm dbh

% of total stems

(v) No. of

pollen % of pollen

(p) p/v

Myrtaceae 100 18.7 86 37.9 2.0


Guapira 46 8.6 62 27.3 3.2


Fabaceae-Mimosideae 28 5.2 2 0.9 0.2

Zanthoxylum type 24 4.5 7 3.1 0.7

Miconia 20 3.7 24 10.6 2.8

Ficus 14 2.6 1 0.4 0.2


Ilex 7 1.3 10 4.4 3.4

Solanum 5 0.9 1 0.4 0.5

Arecaceae 4 0.7 3 1.3 1.8

Clusia 4 0.7 2 0.9 1.2

Sapium 4 0.7 1 0.4 0.6

Myrsine 3 0.6 2 0.9 1.6

Alchornea 2 0.4 2 0.9 2.4

Gallesia 1 0.2 2 0.9 4.7

Total 367 68.6 223 98.2

Bignoniaceae 21 3.9

Lauraceae 30 5.6

Phyllanthaceae 20 3.7

Monimiaceae 2 0.4

Total 73 13.6

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MS7a_L1to7


No. of stems ≥ 10 cm dbh

% of total stems

(v) No. of

pollen % of pollen

(p) p/v

Myrtaceae 76 21.2 48 23.1 1.1



Guapira 22 6.1 8 3.8 0.6



Byrsonima 9 2.5 12 5.8 2.3

Arecaceae 8 2.2 5 2.4 1.1

Astronium 5 1.4 4 1.9 1.4

Aspidosperma 5 1.4 1 0.5 0.3


Miconia 3 0.8 12 5.8 6.9

Myrsine 1 0.3 3 1.4 5.2

Senna 1 0.3 2 1.0 3.5

Total 208 57.9 143 68.8

Bignoniaceae 21 5.8

Lauraceae 8 2.2


Total 37 10.3

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MS7bL8to10


No. of stems ≥ 10

cm dbh

% of total stems

(v) No. of

pollen % of pollen

(p) p/v

Myrtaceae 33 20.2 68 33.0 1.6



Byrsonima 11 6.7 8 3.9 0.6

Guapira 10 6.1 28 13.6 2.2



Roupala 4 2.5 7 3.4 1.4

Astronium 4 2.5 2 1.0 0.4

Senna 3 1.8 1 0.5 0.3

Arecaceae 2 1.2 8 3.9 3.2

Ficus 2 1.2 1 0.5 0.4

Miconia 1 0.6 4 1.9 3.2

Total 125 76.7 163 79.1

Bignoniaceae 12 7.4


Lauraceae 4 2.5

Total 22 13.5

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Appendix B. Bi-plot of correspondence analysis with all modern pollen samples for

axes 1 and 2 (a) and for axes 1 and 3 (b). Only the names of outlier samples have

been indicated

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CHAPTER III

DISPERSAL AND EDAPHIC FACTORS DRIVING PLANT SPECIES COMPOSITION

IN MOUNTAIN FORESTS IN A SEMIARID REGION OF BRAZIL *

*MANUSCRIPT ACCEPTED BY PLANT ECOLOGY AND DIVERSITY

Ivan Jeferson Sampaio Diogoa*, Fernando Roberto Martinsa, Itayguara Ribeiro da

Costab and Flavio Antonio Maës dos Santosa

a Department of Plant Biology, University of Campinas – UNICAMP, Campinas, Brazil

b Department of Biology, Federal University of Ceará– UFC, Fortaleza, Brazil

* [email protected]

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Abstract

Background: Species distribution may result from several factors, including the ability

to disperse, biotic and abiotic factors.

Aims: To understand the patterns of abiotic and biotic influence on species distribution

in the Brazilian northeastern mountain forests.

Methods: We related topography, climate, soil and biotic predictors to species

composition in 17 forest stands in northeastern Brazil, using non-metric multidimensional

scaling and cluster analysis. We built minimum adequate models to select the variables,

and a canonical correspondence analysis to relate environmental and biotic variables to

species composition.

Results: The NMDS showed a clear but gradual discrimination gradient from southern to

northern sites in the distribution and abundance of the surveyed 1427 species, belonging

to 216 genera of woody plants at 17 locations. The Zoochory and Soil Organic Carbon

model explained 43% of the correlation between the response variables and explanatory

variables. The CCA analysis indicated four different groups based on zoochory and SOM.

Conclusions: The zoochory and soil organic carbon predictors, with their associated

ecological processes, determine the niche of mountain forests’ woody species and may

be the decisive factors for the distribution of tropical trees in Brazilian Northeastern

mountain forests.

Keywords: model selection, soil organic carbon, zoochoric dispersion.

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Introduction

A fundamental issue in ecology is the understanding of the mechanisms that

generate the spatial distributions of species and their abundances at different spatial

scales. Disturbance processes and local site factors interact to regulate patterns and

processes in biological communities that lead to species coexistence and maintenance of

species diversity (Chesson 2000).

Much research has discussed the role of historical processes and environmental

factors in shaping community vegetation in tropical forests (Boulangeat et al. 2012; Chust

et al. 2006; Phillips et al. 2003). However, factors posited as the most important have

varied widely across studies, especially when considering different spatial scales and

areas of study (Normand et al. 2006; Tuomisto and Ruokolainen 2008).

Three main drivers could interact independently or simultaneously and influence

the observed spatial distribution of a given species: the abiotic environment, dispersal

limitation and biotic interactions (Austin 2007; Götzenberger et al. 2011; Soberon 2007).

The abiotic constraints may delimit the niche of a species, given its physiological limits

(Chase & Leibold 2003). Dispersal limitations may influence the distribution range of a

species by allowing or prevent it from reaching a suitable site; dispersal limitation is

linked to dispersal capability (Vellend et al. 2007). Finally, biotic interactions may affect

resource availability, with consequences for abundance (e.g. competition,

Lortie et al. 2004, Pons and Pausas 2006).

Climate and soil variables have been shown to be the most relevant variables

when predicting plant species distributions at regional to continental scales

(Thuiller et al. 2004). Biotic interactions are assumed to limit distribution at local scales

(Soberon 2007; Wiens 2011; Godsoe et al. 2017). Dispersal limitations act at larger

extents (Boulangeat et al. 2012). The mechanisms involved in the changes in species

http://onlinelibrary.wiley.com/doi/10.1111/j.1461-0248.2012.01772.x/full#b11





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distribution by dispersal are still unknown for montane areas. So far, species distribution

has been modelled using species distribution models (SDMs), which ignore the effects of

dispersal and biotic interactions (VanDerWal ET AL. 2009).

Although these drivers of species distributions could act at different spatial scales,

we aimed to quantify how dispersal limitation and/or abiotic factors are related to the

floristic composition of mountain forests in north-eastern, Brazil. These humid forest

enclaves located in the semiarid region have functioned as ecological refuges for flora

and fauna since the Pleistocene, providing natural shelter of several endangered species

and new species not yet described and therefore should be priorities for conservation

(Andrade-Lima, 1982). Few studies and inventories are located on these areas and it

demands further attention especially given the extensive loss of habitat.

To understand the species composition and distribution in those endangered and

unique areas, we addressed the following questions: Is the distribution of species in the

northeastern mountain forests follow a gradient? Which variables are most important to

species distribution in those forests? Which is the relative role of the variables in shaping

floristic distribution? and How this influence vary among different sites? We

hypothesized that (1) geographically nearby areas are most correlated, (2) elevation and

rainfall are the environmental factors that have more influence, (3) dispersal limitation is

extremely important to shape the mountain forests community.

Material and methods

Study sites

Montane forests in north-eastern Brazil are defined as those forests that occur

between 600 and 1100 m a.s.l. Bordering or completely surrounded by caatinga, those

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3999639/#R45

81


mountain forests are locally named as brejo forests and have 1200 mm of average annual

rainfall due to an orographic effect (Tabarelli and Santos 2004, Silva and Casteletti,

2003). Steep slopes and sinuous scarps, contrasting with the topography of the

surrounding plains, characterize the mountainous massifs. Climate is defined as hot and

humid, with privileged conditions regarding soil and air humidity and temperature when

compared to the surrounding semiarid region (Tabarelli and Santos 2004).

We made a presence/absence matrix of woody plant species from all checklist

published for 17 montane forests sites in north-eastern Brazil, (Figure 1, Table 1).

Selection of abiotic and biotic variables

Environmental predictors were selected with the understanding of known

ecological, ecophysiological and biophysical processes, and were used as our explanatory

variables. Based on literature (Meier et al. 2010, Boulangeat et al. 2012), we selected 10

types of predictors and divided them into four classes: topographic (elevation and slope),

climatic (rainfall and average temperature), edaphic (pH, cation exchange capacity, total

clay, organic carbon and nitrogen) and biotic (dispersal syndrome). We used dispersal

syndrome as a proxy for dispersal limitation. The response variable was the species

ocurrence data that were available from the surveys. We then constructed a matrix using

the geographic data (the plot coordinates), response variable selected and explanatory

variables.

The climate data were compiled from WorldClim (Hijmans et al. 2005) and the

topography data was downloaded from SoilGrids (http://soilgrids.org) at a spatial

resolution of ca. 1 km. When available, we used the variables data from the paper itself.

Dispersion syndrome according to Pijl (1982) was classified as (1) anemochory, (2)

zoochory, (3) autochory or barochory, and (4) hydrochory, using literature reviews and

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analysis of herbarium specimens. The proportion of dispersion syndromes per community

was based on species richness.

Data analysis

In order to compare the relationships of species composition among the sites, we

carried out an unweighted pair group method with arithmetic mean (UPGMA)

agglomerative cluster analysis with Jaccard coefficient as measure of distance. To assess

how accurately the cluster dendrograms preserved the information from the original

matrices, we calculated the cophenetic correlation coefficient.

To reduce the dimensionality of the community data, we carried out a non-metric

multidimensional scaling (NMDS), also using the Jaccard coefficient. NMDS allows

floristic patterns to be captured without being constrained by a set of predictors (McCune

and Grace 2002). Each NMDS axis has a coefficient of determination (r²) resulting from

the correlation between the distances in the original space and the distances in the

ordination and tested its significance (P) after 999 Monte Carlo permutations. Those

distances were compared, and by iterative procedure, the differences between these arrays

were minimized by using the statistical stress (S) (Clarke and Warwick 2001).

To answer the question as to which variables were most strongly related to species

distribution, we built minimum adequate models (MAMs). Since autocorrelation in

explanatory and response variables violate the assumption of data independence, we first

tested the spatial autocorrelation of the variables before beginning to select the MAMs.

We calculated Moran’s I coefficient, which varies between +1 and -1, where positive

values indicate spatial aggregation (Legendre and Legendre 1998).

We used the first axis scores obtained by the NMDS as response variables to carry

out a multiple regression. Then, we tested the autocorrelation of the residuals obtained by

constructing a spatial correlogram with the Moran’s I coefficient for 10 variables classes


83


and 999 permutations. We tested the correlogram significance with Bonferroni

corrections (Legendre and Legendre 1998).

If the residuals were not autocorrelated, we tested whether or not the explanatory

variables predicted the species abundance and distribution by fitting ordinary least

squares (OLS). The best models are generally those with the lowest Akaike information

criterion (AIC) values. However, for the MAMs, the best models are considered when the

difference between the AIC value of the model and the minimum AIC value of all models

(∆i) is lower than 2 (Diniz-Filho et al. 2008).

After fitting OLS, we tested the collinearity of the variables in the models with

the variance inflation factor (VIF). We also tested for autocorrelation in the residuals of

these models by constructing correlograms with Moran’s I coefficient, and then selected

the MAM that best adjusted to the assumptions of spatial independence and lack of

collinearity among the explanatory variables.

To see the correlation between the sites and the environmental variables selected

by the MAM, we made two canonical correspondence analyses (CCA, the first with the

variables selected by all models with ∆i <2, and the second with the variables of the model

selected). We made 999 permutations and used a Monte Carlo test to evaluate whether

the correlation between the biotic and abiotic matrices was different from that expected

by random chance. We carried out the analyses using the PC-ORD 6.0 software (McCune

and Mefford 2011), and the spatial correlograms and model selection using the SAM 4.0

software (Rangel et al. 2010).

Results

A total of 1427 species in 216 genera of woody plants were compiled for the

species data. The cluster dendrogram showed two different groups: A with all BNMFs

from Ceará and Paraíba and two from Pernambuco, and B with six BNMFs from

84


Pernambuco and one from Sergipe (Figure 2, 87.5% of information remaining).

Moreover, in a finer resolution, group A was separated into three sub-groups: one with a

single site (BNMF 16), another formed by the CE samples (BNMFs 6, 9, 13 and 17) and

the third one formed by two PB samples (BNMF 1 and 3) and three PE samples (BNMF

5, 8 and 10). The correlations between the cophenetic similarities and the Jaccard original

similarities were strong (0.94), confirming the reliability of the UPGMA analyses.


significant (P = 0.01), and explained 60% of the correlations between the distances in the

original space and the ordination distances (Figure 3). After 49 iterations, the final stress

value was 13.74, which is a satisfactory result (McCune and Grace 2002). There was a

clear but gradual discrimination gradient from southern to northern BNMFs (Figure 3).

Furthermore, we found four different groups within both axis, in which the closest areas

had more similarity. The NMDS ordination identified the same groups as the UPGMA.

We found no autocorrelation for the explanatory and response variables, or for the

residuals. The AIC sorted a total of 4023 OLS models, from which four had ∆i < 2, with

four explanatory variables: zoochory, organic carbon, precipitation and nitrogen (Table

2).

In the first CCA (Figure 4, axis 1 = 48% and axis 2 = 31%, P > 0.05), two pairs

of variables were formed: zoochory and precipitation had a similar influence on the

species distribution inside the sites (Pearson R between variables = 0.87), and nitrogen

and organic carbon have the same behaviour (Pearson R = 0.92). This can be clearly

observed in the ordination diagram (Figure 4), in which a strong pattern of correlation

among the variables can be observed along the diagonals from the first and fourth

quadrants.

http://onlinelibrary.wiley.com/doi/10.1111/btp.12254/full#btp12254-fig-0004



85


The final model was selected because of the independence among data (smallest

VIF) among variables, the smallest ∆i and P < 0.05, included the explanatory variables

zoochory and organic carbon (Table 3), resulting in the following OLS final equation 1:

Y = 1.934 – 1.301zoochory + 0.753organic carbon (1)

The model Zoochory-OC explained 44% of the correlation between the response

variables and explanatory variables (∆i = 1.813). The other models (2, 3 and 4) presented

VIF greater than the zoochory-OC model.

The second CCA was based on the Zoochory-OC model (Figure 5A, axis 1 = 52%

and axis 2 = 27%). The eigenvalues indicated that the probability that is explained by the

environmental or explanatory variables is larger than would expected by random chance

(P = 0.003 to Monte Carlo randomisation test).

The CCA scatterplot indicated the formation of four distinct groups of sites

(Figure 5B). Group 1 – BNMFs 1-5 was found to be directly correlated with OC and

indirectly correlated with zoochory. Group 2 – BNMFs 7, 8 and 14 was directly correlated

with both variables. Group 3 – BNMFs 6, 9, 13 and 17 was directly correlated with

zoochory and indirectly correlated with OC. Group 4 – BNMFs 10, 11, 12, 15 and 16 was

wispy correlated to both variables. The first axis separated the effect of zoochory and OC

into two sides, while the second one highlighted the negative and positive effect of both

variables.

There was a remarkable transition among the groups, suggesting a gradual overlap

of the species. The similarity between CCA and nMDS showed a correlation between the

floristic composition and environmental-dependent distribution of species.

Discussion

Distribution of species across the Brazilian Northeastern Mountain Forests

86


The variation in species composition across the BNMFs can be significantly

predicted by environmental factors and the connections among these forest types indicate

that they are quite divided accordingly to the geographical location. The existence of

certain differences between groups (Figures 2 and 3) does not exclude the possibility of

connections among them. This is demonstrated by the difference between the northern

and southern part of the BNMFs that were shown to be connected in terms of species

composition by the cluster dendrogram, despite the consistent identity of each group (the

same pattern is found in Oliveira-Filho et al. 2005, 2006, Eisenlohr and Oliveira-Filho

2015).

Furthermore, these floristic connections were strongly supported by the ordination

analysis. The transition between these groups is gradual, however it is possible to detect

some changes in species composition between the groups along the gradients. These

findings disagree with the validity about the northern part of Atlantic Forest (see Oliveira-

Filho et al. 2006; Carnaval et al. 2008), showing that even those north-eastern mountain

forests are quite different among them. Andrade et al. (2007) have shown this difference

in genetic level for populations of Monstera adansonii var. klotschiana from these areas.

Although we agree with the conservation implications suggested by Santos and

Tabarelli (2004) and Santos et al. (2007) to the BNMFs, our study sheds light on a number

of additional interesting phytogeographic patterns. We establish a new viewpoint from

which the Brazilian Northeastern Mountain Forests should no longer be considered as a

single group. In fact, we still have a lot to explore and to address from this

phytogeographic region.

Variables and their role in shaping floristic distribution

In most studies of Neotropical region, a large portion of the floristic variance is

not explained by the variables under consideration, the variables can show redundancy in

87


explain species distribution and there are a lot of indirect effects of variables (Ter Braak

1987, Austin 2007, Meier et al. 2010). We found that both soil and dispersal syndrome

were related to the distribution of tree species. Climate, topography, and spatial forces,

among other factors have been well-established for the Atlantic Forest (Oliveira-Filho &

Fontes 2000, Scudeller et al. 2001, Oliveira-Filho et al. 2005, Marques et al. 2011,

Eisenhlor and Oliveira-Filho 2015). However, our study is the first to analyse them in the

north-eastern mountain forests context and to test dispersal limitation.

Conversely to our expectation that elevation and rainfall would be the main factors

to explain differences in species composition (see Eisenlohr and Oliveira-Filho 2015), we

found that zoochory and organic soil carbon content were the most important variables

related to differences in species composition. The fact that these predictors passed a

statistical selection process, through which the relationships between the candidate

predictors and the species distributions were evaluated and all collinearities were

discarded, supports the interpretation of them as a factor that affect floristic patterns. It

has been studied that soils components are very important to plant distribution throughout

the world (Jobbágy and Jackson 2000, John et al. 2007, Coudon et al. 2006, Vicent and

Meguro 2008, Nieto-Lugilde 2014, Horn et al. 2015). However there are still few studies

concerning dispersal limitation as a driver in floristic distribution (Primack and Miao

1992, Pearson and Dawson 2003, Boulangeat et al. 2012).

The soil organic carbon influencing plant distribution has been substantiated by

other studies (Jobbágy and Jackson 2000, Motta et al. 2002, Freschet et al. 2013, Roy et

al. 2013). The main content of OC is the organic matter, located at the litterfall or in the

top 20 or 30 cm of soil, which has a great contribution to the plant allocation (carbon

cycle). Furthermore, we observed that the different groups formed by the CCA (Figure 5)

have similar type of soils and similar amount of soil components, which indicate the

88


grouping. Most of the BNMFs located in PE, PB and SE has eutrophic soils where the

organic matter produced is accumulated, and they belong to groups 1 and 2 (higher

amounts of OC). The opposite is found for CE’s mountain forests, which have distrophic

soils.

On the other hand, few studies have used functional traits such as dispersion

syndrome as a proxy for dispersal limitation (Calba et al. 2014, Mair et al. 2014).

However, it is already known that the dispersion mode has an influence on the

establishment of species (Guisan and Zimmermann 2000; Seidler and Plotkin 2006).

Zoochory is the most common dispersion category in different ecosystems (Howe and

Smallwood 1982). The differential prevalence of this category is most probably the result

of ecological adaptations to successional niches (Kupfer and Malanson 1993). Most of

CE’s mountain forests and three from PE are less disturbed areas and consequently have

greater amount of zoochoric species when compared to the others (Brown Jr. and Brown

1992, Drezner 2001, Diogo et al. 2016).

Conclusions

The patterns described here suggest that the BNMFs species not only withstand

soil constraints but also exhibit variations in their dispersion strategies across the

mountain forests, resulting in a highly species-rich flora. Furthermore, a considerable

number of Atlantic forest tree species are known to be flexible with respect to habitat

(Linares- Palomino et al. 2010).

As part of the variance remains unexplained (what is common in plant ecology,

Ter Braak 1986), the main challenge in the future is to explain floristic patterns with

additional variables (spatials, for instance) and to assess the role of stochastic event in

space and time. This study is among the first to apply selection model to the region,

89


providing an idea for the use of this tool in biodiversity and conservation of restricted and

endangered areas.

Acknowledgements

We thank Luciana C. Franci for the help with statistical analysis.

Disclosure statement

No potential conflict of interest was reported by the authors.

Funding

This work was supported by the Conselho Nacional de Desenvolvimento

Científico e Tecnológico [grant number #479263/2011-6 and #563537/2010-8) and by

the Fundação Cearense de Apoio ao Desenvolvimento Científico e Tecnológico [grant

number #PP1-0033-00025.01.00/10]. The research missions between UFC and

UNICAMP was supported by Coordenação de Aperfeiçoamento de Pessoal de Nível

Superior [grant number 552213/2011-0].

Notes on contributors

Ivan J. S. Diogo is a Ph.D. student whose research interests include the biogeography,

diversity and composition of mountain forests

Itayguara R. da Costa is a professor with interest in the evolution and systematics of

plants..

Fernando R. Martins is a professor with research interests in community ecology

Flavio A. M. dos Santos is a professor with interests in plant population ecology.

90


Tables

Table 1. Floristic surveys of 17 mountain forests used in this study. Code: BNMF –

Brazilian northeastern mountain forests.

Municipality/State Code Geographic

coordinates (S;W)

References

Areia/PB BNMF1 6º57’48”; 35º41’29” Andrade et al. (2006)

São Vicente Férrer/PE BNMF2 7º34’60”; 35º30’00” Ferraz and Rodal (2008)

Maturéia/PB BNMF3 7º10’07”; 37º23’04” Cunha (2010)

Bonito/PE BNMF4 8º29’40’’; 35º41’45’' Rodal et al. (1998)

Catende/PE BNMF5 8º40’01’’; 35º43’00” Costa-Junior et al. (2008)

Guaramiranga/CE

Caruaru/PE

Triunfo/PE

Baturité/CE

Araripe/CE

Pesqueira/PE

Itaparica/PE

Maranguape/CE

Madre de Deus/PE

Serra da Guia/SE

Ubajara/CE

Pacatuba/CE

BNMF6

BNMF7

BNMF8

BNMF9

BNMF10

BNMF11

BNMF12

BNMF13

BNMF14

BNMF15

BNMF16

BNMF17

4º15’48”; 38º55’59”

8º16’60’’; 35º57’59”

7º50’18”; 38º06’05”

4º19’43”; 38º53’05”

7º16’32”; 39º27’13”

8º20’27”; 36º46’59”

9º04’60”; 38º17’59”

4º00’33”; 38º48’49”

8º11’14”; 36º24’60”

9°58’55”; 37°52’06”

3º51’16”; 40º55’16”

3°59'04"; 38°37'12"

Cavalcante et al. (2000)

Tavares et al. (2000)

Ferraz et al. (2003)



Pereira et al. (2010), Pinto et al. (2012)

Rodal & Nascimento (2002)

Diogo et al. In press


Machado et al. (2012)

Not published

Not published

91


Table 2. Ordinary least squares (OLS) model selection, sorted by Akaike information

criterion (AIC), coefficient of determination (r²) and minimum AIC value (∆i) of

variables.

OLS Models Variables r² AIC ∆i

Model 1 Zoochory, Organic Carbon 0.440 38.564 1.673

Model 2 Precipitation, Organic Carbon 0.399 39.359 1.695

Model 3 Zoochory, Nitrogen 0.371 39.412 1.813

Model 4 Precipitation, Nitrogen 0.359 39.498 1.867

Table 3. Non-standard coefficients of the explanatory variables selected by ordinary least

squares model selection, sorted by Akaike information criterion and the respective

variance inflation factors (VIF). (T test, P < 0.05)

Explanatory

variable

Coefficient

VIF

Standard

error

T

P

Zoochory -1.301 1.094 0.087 -1.667 0.126

Organic carbon 0.753 1.094 0.016 1.491 0.167

92


Figures

Figure 1. Geographic distribution of Brazilian Northeastern Mountain Forests, with the

location of the floristic and phytosociological checklists used in this study in black

squares: six in Ceara (CE), eigth in Pernambuco (PE), three in Paraiba (PB) and one in

Sergipe (SE).

93


Figure 2. Unweighted pair group method with arithmetic mean with Jaccard coefficient

as distance measure, illustrating the similarity in floristic patterns at the species level

among Brazilian Northeastern Mountain Forests. Cophenetic coefficient = 0.94. See table

1 for locality names.

94



floristic connections among the Brazilian Northeastern Mountain Forests. R² values: Axis

1 = 44.17%, and Axis 2 = 16.36%. P value (proportion of randomized runs with

stress ≤ observed stress) = 0.02 in both axes. Final stress = 13.74. BNMF16 is a unitary

group. See table 1 for locality names.

95


Figure 4. Ordination diagram produced by Canonical Correspondence Analysis for sites

are represented by circles with their identifications, and environmental variables by

vectors. OC = Organic Carbon, Precipit = Precipitation. See table 1 for locality names.

96


Figure 5. A. Ordination diagram produced by Canonical Correspondence Analysis for

sites vs. the explanatory variables selected by MAM. OC = Organic Carbon. B. CCA

Scatterplot, where the explanatory variables are the axis of the analysis, showing four

different groups. See table 1 for locality names.

97


CHAPTER IV

ELEVATIONAL GRADIENTS OF MOIST FOREST IN BRAZILIAN SEMIARID: A

DISTINCT BIOREGION

*MANUSCRIPT FORMATED TO APPLIED VEGETATION SCIENCE

IVAN DIOGO1*, KARIN SANTOS2, ITAYGUARA COSTA 3, ALEXANDRE ANTONELLI4

& FLAVIO SANTOS 1

¹University of Campinas - UNICAMP, Institute of Biology, Department of Plant Biology, 13083-970.

Campinas, SP, Brazil *[email protected]

²Swedish Museum of Natural History, Botany Department, P.O. Box 50007 SE-104 05 Stockholm, Sweden

³Federal University of Ceará - UFC, Departament of Biology, Sciences Center, 60455-760. Fortaleza,

CE, Brazil

4University of Gothenburg - Department of Biological and Environmental Sciences, Carl Skottsbergs

gata 22B - P.O. Box 461 - SE 405 30 - Göteborg - Sweden

98


Abstract

There is a general agreement that the history of the Neotropical forests is complex, as

they have passed for several changes over evolutionary time. The separation of Amazon

and Atlantic Forest and the increasing number of isolated forest patches occurred during

the last Terciary and Quaternary. Assuming that the Brazilian Northeastern Mountain

Forests (BNMF) are considered microrefugia we tested three hypotheses: 1) Amazon and

Atlantic forests share the larger number of species with BNMF, 2) Caatinga has a great

influence on BNMF flora and 3) BNMF are an unique and interconnected bioregion. We

extracted all floristic dataset of Amazon, Atlantic forest, Cerrado and Caatinga from

NeoTropTree and summed with 17 studies of BNMF. To test the relationship among all

domains, we used Venn Diagrams, WPGMA, MRPP and NMDS analysis. To test if the

BNMF is a distinct bioregion, we performed the Infomap Bioregion Analysis. Amazon

presented more than half (5798 spp., 50.23%) of exclusive species, followed by Atlantic

(2089spp., 18,1%), Cerrado (183 spp., 1,59%), BNMF (168 spp., 1,46%) and Caatinga

(64 spp., 0.55%). The other amount of species (3240 spp., 28.77%) is shared by two,

three, four or five domains, for instance 185 species were accounted for occurring in all

domains. The cluster dendogram and NMDS grouped Cerrado, Atlantic Forest and

Caatinga together and Amazon and BNMF separately. We identified 26 bioregions of

woody plants in South America region and BNMF as a distinct one. The most common

species in BNMF were Manilkara rufula, Wedelia villosa and Guettarda angelica. The

most indicative species were Guettarda angelica and Manilkara rufula. Our results

indicates that past connections between the Neotropical rainforests resulted from specific

climatic conditions and support BNMF as an unique biogeographical region as they were

shaped by different climate conditions.

Key words: Neotropical, Amazon, Atlantic forest, Caatinga, biogeography.

99


Introduction

During the last Terciary/Quaternary, successive climate cyles and

Pleistocene/Holocene glacial and interglacial fluctuations have played an important role

in determining the origin and distribution of living organisms in the world (Hewitt 2000).

The temperature descent through Last Glacial Maximum (LGM, 23~18 kyr BP), and the

warmer climate on the Last Interglacial (LIG, 130~116 kyr BP) had a great impact on

retraction and expansion of vegetation and accounted for the high biological diversity and

biogeographical history of plant formations (Ledru et al. 1996). These climatic

fluctuations would cause the forest formations to be fragmented by open dry formations,

such as savannahs, and the forest fragments would be isolated in refugia areas, where

species accumulate new mutations and new species would arise from the widely

distributed ancestral species (Refuge theory, Haffer 1969). Throughout the years, the most

discussed mechanism of diversification and endemism in the Neotropics is the existence

and effects of forest refugia, mainly in South America Neotropical area (Prance 1982,

Colinvaux et al. 2000, Ledru 2002, Bush & de Oliveira 2006, Graham et al. 2006, Carnal

& Moritz 2008, Rull 2008, Mello-Martins 2011, Bueno et al. 2016).

The Brazilian region was covered by Amazon and Atlantic rainforests, which

together formed a big interconnected and continuous forest (Morley 2000). However, this

continuum was historically compressed and fragmented by an open area (semi-arid

formations) due to LGM and LIG climatic fluctuations, which was responsible by the

separation of Amazon and Atlantic and the increasing number of isolated forest patches

(Bigarella et al. 1975, Ledru et al. 1998, Behling & Negrelle 2001, Behling 2002, Hoorn

et al. 2010, Mello-Martins 2011). Paleovegetation, pollen data and biogeographical

studies have shown evidences of past connections between northern Atlantic and eastern

Amazon (Cole 1960, Andrade-Lima 1966, 1982, Behling et al. 2000, Auler & Smart 2001,

100


Auler et al. 2004, Wang et al. 2004, Santos 2007, Pellegrino et al. 2011, Fouquet et al.

2012). The open and drier area is delimited by Caatinga, Cerrado and Chaco (Ab’Saber

1977).

Despite the expansion of drier physiognomies in lowland areas, the tropical

rainforest persists in historically stable areas (Carnaval & Moritz 2008), for instance:

gallery forests across Cerrado in the center region of Brazil and humid patches of

Caatinga in Northeast (Rizzini 1963, Bigarella et al. 1975, Redford & Fonseca 1986,

Oliveira-Filho & Ratter 1995, Coimbra-Filho & Câmara 1996, Ledru et al. 2002). Many

rainforest tree taxa are supposed to have occurred across Caatinga during the wet phases

of LGM and LIG cycles, suggesting the existence of ecological corridors connecting

Amazon and Atlantic, which is also reinforced by the disjunct distribution of several taxa

in both rainforests (Martini et al. 2007, Turchetto-Zolet et al. 2013, Fouquet et al. 2014).

Specifically, the mountainous regions in the middle of Brazilian semiarid have

been considered as exceptionally rich centers of biodiversity and endemism (Tabarelli

2001, Pôrto et al. 2004). Given their complex topography and habitat heterogeneity, there

is likely to be a high genetic diversity within most montane species and signals of the

genetic and evolutionary process that occurred as a consequence of the Pleistocene glacial

cycles (Haffer 1969, Gentry 1982), and therefore should be priorities for conservation.

There have been studies to verify the effects of LGM and LIG on the diversity of

Neotropical montane species (e.g., Aguirre-Planter et al. 2000, Santos et al. 2007,

Jaramillo-Correa et al. 2008, Koscinski et al. 2008, Carnaval et al. 2009, Hensen et al.

2011). However, only a few of them focused in northern part of Northeast region,

revealing lowland expansion of the tropical rainforest in this subregion that lasted for

4000 years during the last deglaciation (Behling et al. 2000, Ledru et al. 2002, 2007,

Montade et al. 2014).

101


Assuming that the Brazilian Northeastern Mountain Forests (hereafter called by

BNMF) are considered microrefugia areas for showing climatic conditions to support

rainforest species, that bioregion is a geographically distinct assemblages of species and

communities (Vilhena & Antonelli, 2015) and that domain is an area which share the

same phytogeographical, morfoclimatic and geomorphological characteristics

(Ab’Saber, 2003), the aim of our research is to check changes in plant communities along

five domains in order to test three hypotheses: 1) Amazon and Atlantic forests share a

higher number of species with BNMF, 2) Caatinga has a great influence on BNMF flora

and 3) BNMF are an unique and interconnected bioregion.

Material & Methods

Study area

Throughout the semiarid (caatinga) region, the annual rainfall ranges from 240 to

900 mm and falls within 3–7 months (IBGE, 1985; Lins, 1989). On the other hand, there

are “islands” of rainforest vegetation in the middle of the semiarid associated with the

occurrence of plateaus and mountains between 600 and 1100 m (for instance, Borborema,

Araripe, Baturité and Ibiapaba). Bordering or completely surrounded by caatinga, those

mountain forests are locally named as brejo forests, where the annual rainfall exceeds

1200 mm (Andrade-Lima, 1982). They have privileged conditions regarding soil and air

humidity, temperature and vegetation cover when compared to caatinga and present

species with Amazon and Atlantic distribution (Tabarelli and Santos 2004).

There are 49 mountain forests, distributed in the states of Ceará, Rio Grande do

Norte, Paraiba, Sergipe and Pernambuco, which cover 19 259 km2, however, this number

is actually reduced by half due to the anthropization and loss of habitat (Vasconcelos-

Sobrinho, 1971). However, only 17 (concerning plants) were studied until now: two in

102


Paraíba state (PB), eight in Pernambuco state (PE), six in Ceará state (CE) and one in

Sergipe state (SE) (Table 1).

Table 1. Floristic surveys of 17 mountain forests located in Northeast, Brazil.

City/State Geographic

coordinates (S;W)

References

Areia/PB 6º57’48”; 35º41’29” Andrade et al. (2006)

São Vicente Férrer/PE 7º34’60”; 35º30’00” Ferraz & Rodal (2008)

Maturéia/PB 7º10’07”; 37º23’04” Cunha (2010)

Bonito/PE 8º29’40’’; 35º41’45’' Rodal et al. (1998)

Catende/PE 8º40’01’’; 35º43’00” Costa-Junior et al. (2008)

Guaramiranga/CE

Caruaru/PE

Triunfo/PE

Baturité/CE

Araripe/CE

Pesqueira/PE

Itaparica/PE

Maranguape/CE

Madre de Deus/PE

Serra da Guia/SE

Ubajara/CE

Pacatuba/CE

4º15’48”; 38º55’59”

8º16’60’’; 35º57’59”

7º50’18”; 38º06’05”

4º19’43”; 38º53’05”

7º16’32”; 39º27’13”

8º20’27”; 36º46’59”

9º04’60”; 38º17’59”

4º00’33”; 38º48’49”

8º11’14”; 36º24’60”

9°58’55”; 37°52’06”

3º51’16”; 40º55’16”

3°59'04"; 38°37'12"

Cavalcante et al. (2000)

Tavares et al. (2000)

Ferraz et al. (2003)



Pereira et al. (2010), Pinto et al. (2012)


Diogo et al. In press


Machado et al. (2012)

Not published

Not published

These plant surveys represented the best-published information available on

woody plant species composition at the local level and they yet covered a small part of

the area occupied by mountain forests. Plant surveys were conducted based on different

methods, some of them used plant sample criteria (from 5 cm DBH to all woody plant

species) and another part used only trees and shrubs over 3 m in height.

Dataset

103


The floristic dataset of Amazon, Atlantic forest, Cerrado and Caatinga was

extracted from NeoTropTree (Oliveira-Filho, 2014), a database that consists of tree

(defined as free-standing woody plants > 3 m in height) species checklists for > 2000 geo-

referenced sites compiled from the literature and herbarium specimen records. In addition

to that, we updated the list with recent studies available from the literature. A

NeoTropTree site is defined by a single vegetation type founded in a circular area with a

5-km radius. If there are two or more vegetation types occurring in one area, we

considered this as overlapping sites and excluded from the dataset. The NeoTropTree only

includes occurrence records with an indication or evidence of vegetation type and with

complete species lists, which is important to avoid bias caused by different sampling

efforts across the same sites. The species were checked regarding their taxonomy and

synonymies by using two different databases (available

at http://floradobrasil.jbrj.gov.br/ and http://tropicos.org/).

We extracted species from all domains: 7907 of Amazon, 4298 of Atlantic forest,

2916 of Cerrado and 1078 of Caatinga. Those species were summed to 733 species

recorded to BNMF (Fig. 1) to build a presence/absence matrix. The plant families and

species were listed according to the Angiosperm Phylogeny Group IV guidelines (APG

IV, 2016).

Data analysis

Both the numbers of shared and exclusive species at the five domains were

demonstrated using Venn diagrams, in which we compared dry domains (Cerrado and

Caatinga) and wet domains (Amazon and Atlantic) with BNMF. In order to evaluate the

floristic relationships among the domains, a dendrogram displaying the hierarchical

clustering was employed with the Jaccard coefficient as a measure of distance, and the

WPGMA linking method as the cluster algorithm. To assess how accurately the cluster

http://tropicos.org/

104


dendrograms preserved the information from the original similarity matrix, we calculated

the cophenetic correlation coefficient.

We tested the hypothesis that all five domains are heterogeneous in terms of

community composition (distance and similarity) by multiresponse permutation

procedure (MRPP). In order to determine the floristic patterns among the domains

resulting from the correlation between the distances in the original space and the floristic

distances, we performed non-metric multidimensional scaling (NMDS, two dimensions

multivariate analysis), with Jaccard coefficient as a measure of similarity. Although a

common practice, we did not exclude rare species from these analyses as they have little

influence in NMDS (Muotka et al. 2002). The adequacy of the ordination for

interpretation was evaluated by using a coefficient of determination (r²), a statistical stress

(S), which its significance (P) was tested after 1,000 Monte Carlo permutations (Clarke

& Warwick 2001).

105


Figure 1. Geographic Distribution of the sites recorded in this study with the location and domain.

Note that BNMF sites are located in the middle of Caatinga domain.

All analyses were performed using the R (R Development Core Team 2013). The

VennDiagram package (Chen & Boutros 2011) was used to create the Venn diagram and

the Vegan (Oksanen et al. 2009) and Cluster (Maechler et al. 2013) packages were used

for multivariate analyses.

In order to test if the BNMF can be classified as a bioregion, we downloaded geo-

referenced ocurrences of the recorded species from the global biodiversity information

facility (GBIF) by the speciesgeocodeR package (Töpel et al. 2017). We only included

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collections without known coordinate issues, based on observations and specimens, and

used the ‘CleanCoordinateLarge’ function of the sampbias package (<

https://github.com/azizka/sampbias_beta/tree/master>) in R to remove potentially

erroneous coordinates.

We cleaned this dataset using the R functions of the same package, checking for

empty coordinates, species reported in the sea and coordinates assigned to country or

province centroids, and then we uploaded on the Infomap Bioregion software (Edler et

al. 2017). The software displays different bioregions on maps and provides a list of the

most common and indicative species for each bioregion. We used the following

parameters: maximum cell capacity = 500; minimum cell capacity = 100; maximum cell

size = 8°; minimum cell size = 2°. See < http://bioregions.mapequation.org/ > for an

explanation of these settings and further software documentation.

Results

A total of 11 542 species, 1 141 genera and 159 plant families were encountered

in the five domains studied (Appendix 1). Amazon presented more than half (5798 spp.,

50.23%) of exclusive species, followed by Atlantic (2089spp., 18,1%), Cerrado (183 spp.,

1,59%), BNMF (168 spp., 1,46%) and Caatinga (64 spp., 0.55%). The other amount of

species (3240 spp., 28.77%) is shared by two, three, four or five domains, for instance

185 species were accounted for occurring in all domains (Fig. 2). From them, we can

name Casearia grandiflora Cambess., Inga ingoides (Rich.) Willd. and Tapirira

guianensis Aubl., which are spread all over Brazil. A great amount of species is

distributed only between Amazon and Cerrado (898 spp.); Atlantic and Cerrado (455

spp.) Amazon, Atlantic and Cerrado (419 spp.); Atlantic, Cerrado and Caatinga (236

spp.). On the other hand, few species are shared only by Amazon, Cerrado and Caatinga

(9 spp.); Amazon, Atlantic, Caatinga and BNMF (7 spp.); Caatinga and BNMF (4 spp.,

http://bioregions.mapequation.org/

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for example Cordia oncocalyx Allemão); Cerrado and BNMF (3 spp., for example

Senegalia monacantha (Willd.) Seigler & Ebinger); and Amazon, Cerrado, Caatinga and

BNMF (only Commiphora leptophloeos (Mart.) J.B.Gillett). Whereas, no species are

shared only by Amazon and Caatinga nor by Amazon, BNMF and Caatinga (Fig. 2,

Appendix 1).

Figure 2. Venn Diagram with species distribution in five domains. AM = Amazon, AT =

Atlantic, BNMF = Brazilian Northeastern Mountain Forests, CA = Caatinga, CE =

Cerrado.

When we analysed the singular contribution of each domain on BNMF flora, we

found that Atlantic and Amazon were the domains that shared more species (61 and 34

spp., respectively), followed by Caatinga (4 spp.) and Cerrado (3 spp.). A different view,

considering the relationships among dry and wet domains separately, showed that the

savannas shared a lower number of species with BNMF when compared to the forests

(Figure 3). Although Cerrado and Caatinga shared together 255 species with BNMF, the

contribution of each one was very discrepant, with Cerrado being the main contributor

(Figure 3a). The same was found for wet domains, with Atlantic being the best contributor

(Figure 3b).

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Comparing the Venn diagrams, we found that when we considered all domains

sharing species, the number of species shared by a single domain was decreased. For

instance, Cerrado, Caatinga and Atlantic had a greater number of shared species when

were evaluated into dry and wet domains (50, 10 and 2 times more). However, Amazon

and BNMF shared 34 species in both analyses, which showed that those species were

shared exclusively by the two domains.

Figure 3. Venn Diagram with species distributions in a) dry domains and b) wet domains.

AM = Amazon, AT = Atlantic, BNMF = Brazilian Northeastern Mountain Forests, CA =

Caatinga, CE = Cerrado.

The cluster dendrogram grouped BNMF, Atlantic, Cerrado and Caatinga together,

but Amazon alone (Fig. 4). In a bigger resolution, BNMF formed a single group (33% of

information remaining), same as Caatinga (73%). Atlantic and Cerrado are very similar

in flora. The correlations between the cophenetic similarities and the Jaccard original

similarities were strong (0.91), showing the reliability of the WPGMA analyses.

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Figure 4. Weighted pair group method with arithmetic mean with Jaccard coefficient as

distance measure, illustrating the similarity in floristic patterns at the species level among

BNMF, Amazon, Atlantic, Cerrado and Caatinga. Cophenetic coefficient = 0.91.

The MRPP method proved that the five domains presented a heterogeneity of

species, with a significant variation in floristic composition in the different sites (A =

0.53, p <0.001). This result gives support to employ comparisons and ordinations with

the domains, since the species composition differs among the groups as expected

stochastically.


significant (P = 0.01), and explained almost 50% of the correlations between the

distances in the original space and the ordination distances. After 15 iterations, the final

stress value was 14.49, which is satisfactory according to McCune and Grace (2002). The

NMDS diagram showed a clear separation of all domains with some connections among

Atlantic, Cerrado and Caatinga (Figure 5). The NMDS analysis ordered the same groups

from the WPGMA, revealing a great correspondence between them. It is worth noting

that BNMF was found to be isolated in both analyses.



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floristic connections among the five domains. R² values: Axis 1 = 25.34%, and Axis

2 = 23.27%. P value (proportion of randomized runs with stress ≤ observed stress) <

0.0001 in both axes. Final stress = 14.49.

We identified 26 bioregions of woody plants in South America region as

illustrated in Figure 6. Most of the species belong to the larger bioregions, however we

verified smaller bioregions, such as in the western Amazon where species turnover is high

and there are many species in just a few cells. We identified clearly the eastern Amazon,

a mix between Cerrado and Caatinga, two bioregions (northern and southern portion) of

Atlantic forest and the BNMF as an unique bioregion (Fig. 6). Besides that, we also

identified Pantanal, Chaco, Pampas and other South American bioregions, although they

are not the focus of this study. The most common and exclusive species in BNMF were

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Solanum rhytidoandrum, Manilkara rufula, Wedelia villosa and Guettarda angelica. The

most indicative species were Guettarda angelica and Manilkara rufula (Score = 16.0).

Figure 6. Bioregion map of the woody plants occurring in South America generated with

Infomap Bioregions, using the GBIF species range distribution. Different coloured areas

represent a bioregion. Amazon in different colors, mainly blue, Cerrado and Caatinga in

dark gray, Atlantic in brown and pink, Pantanal in dark purple and BNMF in light purple

are the bioregions identified in Brazil.

Discussion

Our findings provided clues about the species dynamics of Neotropical rainforests

through the LGM and LGI, corroborating past links and indicating spatial displacements

that may have affected species distribution around BNMF areas. Furthermore, we found

evidences of great connections among different domains that give ideas about

biogeographical islands, isolated fragments and bioregions.

Paleoclimate models for those domains suggest at least three pathways for the

connections between Amazon and Atlantic forests: the central Brazil bridge, based on

species interchange between eastern Amazon and south-eastern Atlantic Forest.

112


(Oliveira-Filho & Ratter 1995); the Northeast one that would have crossed the Caatinga

at certain periods since the late Tertiary (Andrade-Lima 1964); and the major southern

route through the Paraná River basin (Por 1992). The high number of species shared by

Cerrado with Amazon and Atlantic forests support the hypothesis of the first pathway

with interchange during the Quaternary, and those species are currently restricted to

multiple interglacial refugia (Collevatti et al. 2009, Barbosa et al. 2012, Bonatelli et al.

2014). Méio et al. (2003) also found a great number of plant species (58.9%) that occur

in Cerrado are also occurring in Atlantic and Amazon or both. For instance, the tree

Plathymenia reticulata shows a pattern of recent expansion from the central Cerrado to

northeastern Brazil via eastern (Atlantic coast) and western (inland) colonization routes

(Novaes et al., 2010). In addition, the species shared by Caatinga and Cerrado are part of

the coalescence of dry forests in peripheral depressions during the dry periods of

Quaternary (Ab'Saber 1983, Pennington et al. 2000).

The second pathway is related to the interchange along Caatinga domain.

Although the Caatinga domain is one of the less studied and vegetation shifts during the

Pleistocene are unclear, the evidence suggests that Atlantic forest have been shaping the

Caatinga diversity (Thomé et al., 2016). For instance, the extensive haplotype of the

orchid Epidendrum cinnabarinum indicates connections between populations of the

Atlantic Forest and Caatinga inselbergs (Pinheiro et al., 2014). This pattern is the

opposite found for Amazon and Caatinga, they shared no species, and there is no

connections addressed on literature (Leal et al. 2016). On the other hand, the mountain

forests (BNFM) that presently exists with the Caatinga domain are actual relicts of an

ancient and wider rainforest.

Studies on endemism and inventories of the BNMF are still scarce, however, we

found a great number of exclusive trees and shrubs in these areas (almost the same as


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Cerrado, see appendix 1). They have been functioned as ecological refuges and stepping

stones providing natural shelter of several endangered species and new species not yet

described (Andrade-Lima 1982, Carnaval & Bates 2007, Sobral-Souza et al. 2015) and,

consequently, often present endemic taxas (Loebmann & Haddad, 2010; Camardelli &

Napoli, 2012; Guedes et al., 2014). Furthermore, we accept our first hypothesis, the

lineages diversity of Atlantic and Amazon had been shaped along recurrent connections

between them during LGM, what contributed to the main BNMF diversity. Although

Amazon has less contribution when compared to the Atlantic forest, it has the same

amount of exclusive species when compared among all domais and only among humid

domains, which indicates that connections between Amazon and BNMF are better

explained by vicariance events. Oppositely, the long-distance dispersal events are more

common between Atlantic forest and BNMF because of the geographic proximity.

We reject our second hypothesis, the geographic proximity does not influence on

the interchange between Caatinga and BNMF, where we accounted only four species

shared. The same occurs between Cerrado and BNMF, with three species shared. The

reason for such few number is probably the difference in environmental conditions, as

soil properties, temperature and humidity, that is related to the species niche. We can see

this pattern, when we compare analyses along all domain and only between dry and wet

domains, both Cerrado and Caatinga have more species shared when analyzed separately

because they are sharing species with other domains rather than BNFM (Figs. 2 and 3).

In terms of the affinities, we can see a slight trend towards a closer association

between Cerrado, Atlantic forest and Caatinga as revealed by the analyses of WPGMA

and NMDS. The same pattern is described by Costa (2003) for small mammals and by

Leal et al. (2016) in a review for phylogeographic studies on plants. The analyses also

indicate a clear separation of Amazon and BNMF from the other domains, mainly because

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of their exclusive species. This separation is also confirmed by the bioregion analysis,

where we accept our third hypothesis: the BNMF constitute a new biogeographical

region.

The portioning of Amazon into several highly divergent phylogeographical areas

was already found by Cracraft & Prum, (1988) and Patton et al. (2000). The northern and

southern portion of Atlantic forest was described by Carnaval & Moritz (2008) and

confirmed by phylogeographical studies (Sobral-Souza et al. 2015, Peres et al. 2017). The

Caatinga and Cerrado are together part of the dry South American diagonal (Werneck et

al. 2011). The bioregions identified are consistent with those found by Vilhena and

Antonelli (2015) for amphibian species, except for some smaller bioregions. Considering

the Neotropics, our results are in accordance to the regionalization proposed by Morrone

(2006; 2014), for instance the Amazonian, the Paraná, the Colombian and the Chaco

provinces. We also compared our data with the World Wildlife Fund (WWF) ecoregions

(Olson et al. 2001), which is very similar. Furthermore, our results announces the

Brazilian Northeast Mountain Forests as a new bioregion never described before with its

exclusive species and characteristics.

Nevertheless, bioregionalization based on species distribution needs to deal with

the quantity and quality of occurrence data because they clearly contain spatial,

taxonomic and temporal biases. For instance, Amazon has the biggest remaining area and

consequently the major exclusive species proportion when compared to the other

domains. On the contrary, despite of the smaller remaining area, Atlantic has more

exclusive species than Cerrado. Additionally, the NeoTropTree has surveys from

different times (decades) and concentrated in some areas (around the state capital, for

example). So, the detection of bioregions is impacted by how we treat and revise the data

available.



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Conclusion

To understand better the emergence of those new bioregions or even accept their

existence, it is necessary to develop phylogeographical studies focuse on species or

groups of species sampled in different domains. Our results indicates that past

connections between the Neotropical rainforests resulted from specific climatic

conditions in this area and support that subregions of Amazon and Atlantic Forest, such

as Brazilian Northeastern Mountain Forest, should be considered as distinct and unique

biogeographical regions as they were shaped by different climate conditions.

Appendix 1 – List of species of all domains studied. Available online:

https://docs.google.com/spreadsheets/d/1g2lfhKGII_p-SMG_aPM0XKC_j-ZsrDKw-

az4DtMofRg/edit?ts=59847e39#gid=0

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CONSIDERAÇÕES FINAIS

Apresentamos uma síntese de estudos para as Florestas Serranas do Nordeste

Brasileiro, explorando características físicas, climáticas e bióticas, padrões gerais de

similaridade florística, relações com os diferentes domínios brasileiros, distribuição de

espécies e composição palinológica. É patente que a história das florestas serranas

nordestinas vem sendo modificada, embora ainda haja grande lacunas, os resultados aqui

encontrados facilitam a compreensão do funcionamento ecossistêmico em gradientes

altitudinais de florestas serranas do Nordeste brasileiro.

Chamamos atenção para cinco destaques da tese. O primeiro destaque é o fato da

vertente à sotavento da Serra de Maranguape apresentar maior diversidade e riqueza de

espécies e flora bem diferente das áreas de Caatinga. O segundo é que as áreas de topo

das florestas serranas cearenses ostentam características de florestas nebulares. O terceiro

é a reestruturação constante das florestas serranas, uma vez que há espécies da chuva

polínica não encontradas na vegetação e vice-versa. O quarto é a incidência de zoocoria

como processo chave na distribuição de espécies nas florestas serranas nordestinas (escala

regional). O quinto e mais importante é a classificação das florestas serranas como uma

bioregião única e distinta do Brasil.

Desse modo, econtramos resultados novos e significativos para a biodiversidade,

biogeografia e distribuição de espécies nas florestas serranas do Nordeste brasileiro.

Como essas florestas são restritas e constantemente ameaçadas, os resultados serão

bastante úteis para conservação e restauração ambiental. Esse estudo foi o primeiro a

utilizar a ferramenta de seleção de modelos e análises de bioregião em florestas do

semiárido, fornecendo dados e ideias para pesquisas vindouras.

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Além disso, nosso estudo traz dados que colaboram para a conservação e

preservação das florestas serranas nordestina, fornecendo listas de espécies, espécies

indicativas e ameaçadas de extinção, critérios para elaborar planos de manejo e novas

Unidades de Conservação. Os próximos passos e pesquisas futuras irão focar nas origens

e centros de dispersão de espécies-chaves destas florestas (filogeografia) e respostas da

distribuição destas espécies frente às mudanças climáticas (modelagem ecológica). Esses

dados, quando levados em conta por novos estudos, potencialmente maximizarão

resultados, metodologias e conhecimento para o semiárido brasileiro, na medida em que

permitem direcionar novos esforços para onde há mais carência de dados.

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ANEXOS

DECLARAÇÃO

Em observância ao §5º do Artigo 1º da Informação CCPG-

UNICAMP/001/15, referente a Bioética e Biossegurança, declaro que o

conteúdo de minha Tese de Doutorado, intitulada “BIOGEOGRAPHY AND

DIVERSITY OF HUMID MOUTAIN FORESTS IN NORTHEASTERN,

BRAZIL”, desenvolvida no Programa de Pós-Graduação em Biologia Vegetal

do Instituto de Biologia da Unicamp, não versa sobre pesquisa envolvendo

seres humanos, animais ou temas afetos a Biossegurança.

Assinatura:

Nome do(a) aluno(a): Ivan Jeferson Sampaio Diogo

Assinatura:

Nome do(a) orientador(a): Flavio Antonio Mäes dos Santos

Data: 30 de novembro de 2017.

COORDENADORIA DE PÓS-GRADUAÇÃO INSTITUTO DE BIOLOGIA Universidade Estadual de Campinas Caixa Postal 6109. 13083-970, Campinas, SP, Brasil Fone (19) 3521-6378. email: [email protected]

mailto:[email protected]

164


Declaração

As cópias de artigos de minha autoria ou de minha co-autoria, já publicados ou

submetidos para publicação em revistas científicas ou anais de congressos

sujeitos a arbitragem, que constam da minha Dissertação/Tese de

Mestrado/Doutorado, intitulada BIOGEOGRAPHY AND DIVERSITY OF

HUMID MOUTAIN FORESTS IN NORTHEASTERN, BRAZIL, não infringem

os dispositivos da Lei n.° 9.610/98, nem o direito autoral de qualquer editora.

Campinas, 30 de novembro de 2017

Assinatura:

Nome do(a) aluno(a): Ivan Jeferson Sampaio Diogo

Assinatura:

Nome do(a) orientador(a): Flavio Antonio Mäes dos Santos

universidade estadual de campinas instituto de...

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