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Instituto Nacional de Pesquisas da Amazônia – INPA
PROGRAMA DE PÓS-GRADUAÇÃO EM ECOLOGIA
OS EFEITOS DA FRAGMENTAÇÃO FLORESTAL NO FENÓTÍPO DE
UM PÁSSARO DE SUB-BOSQUE NEOTROPICAL
STEFANO SPITERI AVILLA
Manaus, Amazonas
Setembro, 2020
STEFANO SPITERI AVILLA
OS EFEITOS DA FRAGMENTAÇÃO FLORESTAL NO FENOTÍPO DE
UM PÁSSARO DE SUB-BOSQUE NEOTROPICAL
Orientadora:
DRA. CINTIA CORNELIUS FRISCHE
Co-orientadoras:
Dra. Marina Anciães
Dra. Kathryn Sieving
Dissertação apresentada ao
Instituto Nacional de Pesquisas da
Amazônia como parte dos
requisitos para obtenção do título
de Mestre em Biologia (Ecologia).
Manaus, Amazonas
Setembro, 2020
RELAÇÃO DA BANCA EXAMINADORA
Profa. Dra. Juliana Menger
Instituto Nacional de Pesquisas da Amazônia - (INPA):
APROVADO
Prof. Dr. Pedro Pequeno
Instituto Nacional de Pesquisas da Amazônia - (INPA):
APROVADO
Prof. Dr. Charles Duca
Universidade de Vila Velha - (UVV):
APROVADO
FICHA CATALOGRÁFICA
A958e Avilla, Stefano Spiteri
Os efeitos da fragmentação florestal no fenótipo de um pássaro de sub-bosque
neotropical / Stefano Spiteri Avilla; orientadora Cintia Cornelius; coorientadora
Marina Anciães e Kathryn Sieving. -- Manaus:[s.l], 2020.
56 f.
Dissertação (Mestrado - Programa de Pós Graduação em Ecologia) --
Coordenação do Programa de Pós-Graduação, INPA, 2020.
1. Fragmentação Florestal. 2. comportamento exploratório. 3. novo ambiente.
I. Cornelius, Cintia, orient. II. Anciães, Marina, coorient. III.Título.
CDD: 598
Sinopse:
Estudou-se os efeitos da fragmentação florestal no fenótipo de uma espécie de
pássaro de sub-bosque na Amazônia Central no município de Manaus. Em especial
investigou-se aspectos comportamentais e morfológicos.
Palavras-chave: Fragmentação florestal, comportamento exploratório, novo
ambiente, adaptação fenotípica.
DEDICATÓRIA
Dedico este trabalho à Ciência e todos aqueles que a exercem como profissão. Passamos
por tempos difíceis em que nosso trabalho tem sido desvalorizado, mas não devemos perder as
esperanças. Devemos continuar a fazer aquilo que amamos e com a mesma dedicação de sempre,
e lembrar que o que fazemos é de todxs, para todxs. Não há nada de errado em sentir medo e
chorar. Respeitem seus limites e os de outros, permitam-se sentir suas emoções. Dias melhores
virão!
AGRADECIMENTOS
Ao Programa da Ecologia do Instituto Nacional de Pesquisas da Amazônia (INPA) pela
infraestrutura física e administrativa que me permitiram desenvolver meu projeto. À Coordenação
de Aperfeiçoamento Pessoal de Nível Superior (CAPES) e a Fundação de Amparo à Pesquisa do
Estado do Amazonas (FAPEAM) por financiarem o programa de pós graduação e as atividades de
campo deste projeto, respectivamente.
Às seguintes instituições e às pessoas por facilitarem e permitirem acesso aos sítios de
amostragem desse projeto: a Universidade Federal do Amazonas (UFAM) e sua Fazenda
Experimental (FAEXP); a Empresa Brasileira de Infraestrutura Aeroportuária (INFRAERO) e a
gestão do Aeroporto Internacional Eduardo Gomes, em especial, aos funcionários Ednei e Alírio;
ao Museu na Floresta e os professores, monitores, alunos e assistentes de campo, do II Curso de
História Natural do Rio Cuieiras. Em especial, neste último, agradeço à Mario Cohn-Haft e Ramiro
Melinsk pelos ensinamentos em ornitologia de campo.
Às pessoas que de alguma forma me auxiliaram nas expedições de campo: Anaís Prestes,
Alex Latorre, Beatriz Barreto dos Santos Modesto, Flávia Líbia, Francielen Paiva, Gisiane
Rodrigues, Iamile Brandão de Oliveira, Jessica Andrade de Oliveira, José Raulino, Lucas Carvalho
de Jesus, Juliana de Oliveira Pinheiro, Marcos Pimentel Abbade, Max Queiroz, Natasha Helena,
Natasha Raíssa, Pedro Paulo, Phamela Barbosa, Priscilla Diniz e Riomar Queiroz. Em especial, à
Carla Ivanilde pela confecção dos materiais utilizados no desenho experimental desse projeto.
Aos colegas do Laboratório de Biologia da Conservação (LABICO) e do Laboratório de
Biologia Evolutiva e Comportamento Animal (LABECA) pelas conversas, cafés, ensinamentos,
discussões, risadas, aprendizados, apoios morais e psicológicos. Em especial, às minhas
orientadoras, Cintia Cornelius (LABICO), Marina Anciães (LABECA) e Kathryn Sievieng, pelo
apoio, ensinamentos e puxões de orelha, que foram essenciais durante essa jornada. Foi uma honra
de trabalhar com vocês, tive um grande crescimento profissional e vou levar seus ensinamentos
para toda a vida.
Quero deixar um agradecimento especial ao Martín, um grande guerreiro que venceu uma
grande luta e me mostrou quais são as verdadeiras prioridades na vida. Não importa os imprevistos,
a família, os amigos e nossa saúde vem em primeiro lugar.
Aos meus amigos de turma Gabriela Ushida, Pedro Paulo e muitos outros, por estarem
comigo nos momentos de alegrias e dificuldades. Aos amigos passarinheiros Izaias Miranda e
Priscilla Diniz pelas incríveis passarinhadas na Amazônia. Aos amigos que já faziam parte da
minha vida antes desse período e que, mesmo à distância, a presença no meu dia a dia foi essencial.
Sem essas amizades minha experiência nessa jornada teria sido muito mais difícil.
À minha família, em especial, minha mãe Maria Carolina Passos, meu pai Giovanni Avilla,
meu irmão Gianluca Avilla e meu primo Gustavo Avilla. Mais uma vez minhas escolhas nos
afastaram fisicamente e não pude dividir presencialmente as perdas, as conquistas e sentir o calor
do abraço da família. Saibam que, mesmo de longe, o apoio e confiança de vocês sempre me deu
muita força e foi um grande estímulo para seguir adiante.
Ao meu cachorro, o Negão, a família que adotei em Manaus, por estar do meu lado durante
todo esse processo. Me acompanhar nos dias de escrita e nas noites de análise. Por ser a minha
fonte de conforto, amor, carinho (às vezes, preocupação e frustração) e por me lembrar, apenas
com um olhar, que tudo vai ficar bem. Aos meus vizinhos Taís, Mateus, André, Alany e Fabio por
cuidarem do Negão nos mais de 60 dias em que tive que ficar fora de casa durante minhas
expedições de campo. Agradeço também às pessoas que me ajudaram nos dias em que o Negão
adoeceu e tive que colocar tudo de lado para cuidar dele.
Por fim, é essencial lembrar que, mesmo para biólogos, nossa presença em campo gera
impactos nos ecossistemas naturais, mesmo que de baixa magnitude. Por isso, quero agradeço em
especial à todas as aves que foram capturadas, medidas, anilhadas e testadas durante a coleta de
dados deste projeto.
EPÍGRAFO
“So far away we wait for the day
For the lives all so wasted and gone
We feel the pain of a lifetime lost in a thousand days
Through the fire and the flames we carry on”
“Tão longe esperamos pelo dia
Pelas vidas perdidas que se foram
Sentimos a dor de uma vida perdida em mil dias
Através do fogo e das chamas nós continuamos” (tradução livre)
-Through the fire and the flames, Dragonforce
RESUMO
A fragmentação de habitat tem levado a perdas de biodiversidade nos Neotropicos em um ritmo
alarmante. Contudo, indivíduos de algumas espécies confinados em fragmentos desenvolvem
mudanças fenotípicas que permitem que populações persistam, mesmo em paisagens alteradas pela
ação humana e a urbanização. Adaptações, tanto morfológicas como comportamentais, podem
melhorar a habilidade de uma população em lidar com os perigos impostos pelas mudanças
antropogênicas. Nós investigamos se uma população urbana de arapaçu-bico-de-cunha
(Glyphorynchus spirurus), uma ave neotropical insetívora de sobosque neotropical desenvolveu
diferenças em seu fenótipo em resposta à fragmentação florestal, comparando com populações de
florestas contínuas e preservadas. Nós avaliamos o comportamento exploratório e a morfologia
usando modelos lineares generalizados (GLM) e análise linear discriminante (LDA) para
quantificar diferenças fenotípicas entre populações, e análise de tempo de falha (FTA) para
comparar a latência de exploração e movimentação em teste de novo ambiente (NET). Nossas
analises detectaram diferenças na morfologia (comprimento da cauda e do tarso) e em certos
comportamentos (latências para se mover durante NET), sugerindo que a fragmentação em nosso
sistema pode ter causado a seleção de traços que influenciem movimentos de rotina. A variação
populacional observada pode ser um processo evolucionário em curso mas não podemos descartar
ajustes comportamentais por parte dos indivíduos, mas sugerimos que essas diferenças podem estar
permitindo a sobrevivência dessa pequena ave em fragmentos florestais.
ABSTRACT
Habitat fragmentation drives biodiversity loss in the Neotropics at an alarming rate. However,
some individuals and species confined to fragments develop phenotypic adaptations that allow
populations to persist, even in landscapes made harsh by human activities and urbanization.
Adaptations in both morphology and behavior may enhance a population’s ability to cope with
changing anthropogenic hazards. We investigated if urban populations of Wedge-billed
Woodcreeper (Glyphorynchus spirurus), an understory insectivorous neotropical bird, developed
phenotypic differences in response to fragmentation, by comparing it with populations from
continuous preserved forests. We evaluated the exploratory behavior and morphological traits
using generalized linear models (GLM) and linear discriminant analysis (LDA) to quantify
phenotypical differences among populations, and used failure time analysis (FTA) to compare
latency to explore and move during exploration in a novel environment test (NET). Our analyses
detected differences in morphology (tarsus and tail length) and certain movement behaviors
(latencies to move during NET), suggesting that fragmentation in our system may be causing
selection on traits influencing routine movements. Observed differences were not associated with
environmental variables. We do not ascribe population variation to evolutionary processes yet,
given the short timeline since fragment formation, but we suggest these differences may currently
be aiding fragmentation persistence in this small forest bird.
SUMÁRIO DEDICATÓRIA 6
AGRADECIMENTOS 7
EPÍGRAFO 9
RESUMO 10
ABSTRACT 11
LISTA DE FIGURAS 13
1. Introdução Geral 14
2. Objetivos 17
2.1. 17
2.2. 17
3. Capítulo único 17
Phenotypic differences in a neotropical understory bird driven by habitat fragmentation in an
urban landscape 18
3.1. Introduction 18
3.2. Methods 21
3.2.1. Study site and experimental design 21
3.2.2. Novel Environment Test 23
3.2.3. Morphological traits 25
3.2.4. Statistical analyses 25
3.3. Results 27
3.3.1. Exploratory behavior and morphology 27
3.3.2. Latency times 30
3.4. Discussion 32
3.4.1. Morphological differences 33
3.4.2. Behavioral differences 34
3.4.3. Limitations and sampling bias 35
3.5. Conclusion 36
3.6. Conflict of interest 36
3.7. Animal Rights 36
3.8. Acknowledgements 37
3.9. Literature cited 37
4. Síntese geral 44
5. Referências bibliográficas 45
LISTA DE FIGURAS
Figura 1 – Sítios de amostragem ....................................................................................................22
Figura 2 – Espécie modelo: arapaçu-bico-de-cunha (Glyphorynchus spirurus) ............................23
Figura 3 – Configuração para teste de novo ambiente ....................................................................24
Figura 4 – Boxplots dos traços comportamentais ...........................................................................27
Figura 5 – Boxplots dos traços morfológicos .................................................................................28
Figura 6 – Scores de LDA para traços morfológicos e comportamentais .......................................30
Figura 7 – Curvas de Kaplan-Meier ...............................................................................................33
1. Introdução Geral
Fragmentação por atividade humana representa uma grande ameaça à biodiversidade.
Como consequência da perda de habitat, a fragmentação isola manchas de habitat em uma matriz,
às vezes agressiva (Fahrig 2003, Haddad et al., 2015). Espécies de animais que habitam fragmentos
são forçadas a se mover por paisagens alteradas, levando à movimentos não-ótimos (Fahrig 2007)
e vórtices de extinção (Fagan e Holmes 2006). Em sistemas neotropicais, fragmentação aumenta
a temperatura, penetração de luz e perturbações de vento no sobosque até 500m da borda do
fragmento, levando a alta mortalidade de árvores (Laurance et al., 2018). Tais perturbações
impõem fortes pressões seletivas nas populações que a maioria das espécies florestais não
conseguem suportar (Harris e Reed 2002; Bélisle 2005; Baguette e Van Dyck 2007). Por outro
lado, essa mesma pressão pode levar a rápidas adaptações fenotípicas que melhoram o fitness das
populações (Cheptou et al., 2017).
Adaptações comportamentais são, em geral, ajustes às condições do ambiente, por
exemplo, aves que modificam seu período de vocalização para evitar a poluição sonora (Fuller et
al., 2007), ou ainda, mudanças em sinais acústicos após processos que levaram a uma liberação de
carácter (Bicudo et al., 2016). Contudo, eventos estocásticos também podem levar à ajustes de
comportamento (Dingemanse et al., 2004). Adaptações menos discutidas, mas que pode prever
como indivíduos reagirão às novidades impostas pela ação humana, são as que dizem respeito o
comportamento exploratório. A exploração é um conjunto variável de comportamentos expressos
quando indivíduos se deparam com uma novidade, exercendo um importante papel na
identificação de recursos e perigos (Dingemanse et al., 2002; Mettke-Hoffmann et al., 2004).
Veerbeck et al. (1994) descreveram pela primeira vez tal variação em populações naturais de aves,
baseado na resposta individual ao desconhecido e as respectivas pontuações de exploração.
Quando apresentados a um ambiente novo, indivíduos com altas pontuações exploratórias
moveram-se rapidamente pelo ambiente, encarando a novidade com pouca neofobia (Verbeeck et
al., 1994). Outros indivíduos com pontuações exploratórias mais baixas moveram-se mais
lentamente pelo ambiente e levaram mais tempo para explorar todos os atributos oferecidos
(Verbeeck et al., 1994). Esses perfis de exploração foram nomeados de acordo com o ritmo de
exploração em novo ambiente, os exploradores “rápidos” e “lentos” (Verbeeck et al., 1994). A
diferença entre esses perfis é como cada indivíduo perceberá, assimilará e reagirá à informação
nova (Dingemanse et al., 2002). Exploradores rápidos exploram a novidade de forma superficial,
são mais propensos a não repararem em potenciais perigos e, consequentemente, de tomarem
decisões de alto risco (Van Oers et al., 2003), mas são normalmente mais agressivos e exercem
maior dominância sobre recursos (Verbeeck et al., 1996). Cornelius et al. (2017) reportaram
diferenças de comportamentos exploratórios em aves especialistas de florestas, onde indivíduos
que viviam em fragmentos florestais tinham perfis exploratórios mais lentos quando comparados
à indivíduos de populações de paisagens integras. Essa diferença foi atribuída a um ajuste
comportamental para melhor lidar com as mudanças impostas pela fragmentação antropogênica e
travessias de áreas abertas (Cornelius et al., 2017). Um padrão similar também foi observado em
borboletas florestais (Merckx et al., 2003). Indivíduos de paisagens contínuas reagem menos à
fontes de riscos e são muito mais propensas à se arriscarem, por exemplo, em atravessar áreas
abertas, onde são muito mais suscetíveis à predação, enquanto que indivíduos de fragmentos
evitam transições entre ambientes florestais, raramente atravessando áreas abertas (Merckx et al.
2003).
Na mesma perspectiva que as adaptações comportamentais, adaptações morfológicas
também são reportadas em paisagens alteradas pela ação humana. Essas adaptações estão
associadas com o desafio de lidar com novas pressões impostas pela ação humana (Perry 2020).
Brown e Brown (2013) relataram adaptações no formato de asa em populações de andorinhas-de-
dorso-acanelado (Petrochelidon pyrrhonota) que melhoraram a manobrabilidade individual e a
habilidade de evitar colisões com veículos em uma estrada construída próxima a uma área de
ninhos. Martin et al. (2017) encontraram adaptações semelhantes em espécies da família Paridae
em resposta a 100 anos de fragmentação da paisagem. Os autores descreveram uma tendência de
diferenças no formato de asas: espécies com asas mais pontudas e com maior capacidade
dispersiva, começaram a assumir formas de asas mais arredondadas e com menor poder dispersivo
(Martin et al., 2017). O contrário foi encontrado em espécies com menor poder dispersivo, uma
vez que essas passaram a ter formas de asas mais pontudas e com maior poder de dispersão (Martin
et al., 2017). Essa tendência foi sugerida como uma resposta a mudança de riscos da movimentação
pela paisagem. Espécies que tinham maior contato com a matriz, logo, maior poder dispersivo,
passaram a sofre com alta taxas de mortalidade, logo, permanecer dentro dos fragmentos foi mais
benéfico (Martin et al., 2017). Por outro lado, as espécies que permaneciam em fragmentos e
tinham menor poder de dispersão estavam sujeitas à escassez de recursos, endogamia e eventos
estocásticos, logo, deixar os fragmentos tornou-se mais benéfico (Martin et al. 2017). Entretanto,
adaptações morfológicas podem não ser tão evidente, como em formatos de bicos que permitem
acessar alimentos oferecidos em comedouros (Bosse et al., 2017). Com isso, outros traços
poderiam estar sob pressões seletivas, em especial, para ambientes urbanos. Para espécies que não
visitam comedouros, traços relacionados à movimentos de curta distância e rotineiros (e.g.,
forrageio), podem ser selecionados. Por exemplo, em aves trepadoras de árvores, cauda e tarso
merecem atenção uma vez que tem forte relação com a habilidade de escalar troncos (Norberg
1979, Zeffer e Norberg 2003) e assim podem estar sujeitos à seleção.
Dada a constante expansão de áreas antropizadas, é de alta importância entender como
populações de animais podem responder a novas condições impostas pela atividade humana.
Ambientes urbanos impõem condições extremas para a vida selvagem, e mesmo que espécies
nativas sejam capazes de persistir em fragmentos florestais em cidades (Aronson et al., 2015),
pouco se sabe sobre adaptações que as permitem ainda ocupar tais espaços. Nesse trabalho,
avaliamos o efeito da fragmentação de habitat em uma paisagem urbana no fenótipo de uma
espécie de ave de sobosque na cidade mais populosa da Amazônia Central. Espécies de sobosque
são especialmente sensíveis à fragmentação (Sekersioglu et al., 2002; Lee e Peres 2007) e são
normalmente o primeiro grupo de aves a desaparecer em um cenário de fragmentação florestal
(Van Houtan et al., 2007). Nosso objetivo foi identificar divergências fenotípicas em populações
urbanas de arapaçu-bico-de-cunha (Glyphorynchus spirurus, Dendrocolaptidae) usando um
desenho experimental de paisagens “fragmentada versus contínua”, comparando indivíduos de
fragmentos florestais em uma paisagem urbana com indivíduos de florestas contínuas e
preservadas. Nossa hipótese é que espécies de fragmentos florestais diferem tanto no
comportamento como na morfologia quando comparados a populações de florestas contínuas. Nós
esperamos que indivíduos de fragmentos florestais tenham menor ritmo de exploração quando
comparados à indivíduos de paisagens contínuas. Também esperamos que tenham adaptações
relacionadas à movimentos de longa distância (e.g., dispersão) e de curta distância (e.g., forrageio
e exploração). Em especial, prevemos que 1) indivíduos de paisagens fragmentadas terão menores
pontuações em traços exploratórios, levando mais tempo para explorar todos os atributos de um
novo ambiente e 2) terão asas mais pontudas (longa distância) e tarsos e caudas (curta distância)
com tamanhos diferentes, como consequência da pressão seletiva imposta pela paisagem.
2. Objetivos
2.1. Geral
Investigar a existência de divergência fenotípica entre populações de Glyphorynchus spirurus que
persistem em fragmentos florestais urbanos e florestas continuas e preservadas.
2.2.Específicos
-Investigar e comparar o comportamento exploratório de Glyphorynchus spirurus em um
conjunto de indivíduos de fragmentos florestais e de floresta contínua.
-Investigar e comparar a morfologia de Glyphorynchus spirurus de fragmentos florestais e
de floresta contínua.
3. Capítulo único
Este trabalho foi submetido à revista Oecologia (A1 – Classificação de Periódicos Quadriênio
2013-2016 da CAPES)
Phenotypic differences in a neotropical understory bird driven by habitat
fragmentation in an urban landscape
Stefano Spiteri Avilla¹, Kathryn Sieving², Marina Anciães¹, Cintia Cornelius³
¹Instituto Nacional de Pesquisas da Amazônia (INPA)
²University of Florida – Wildlife Ecology and Conservation Department (UFL)
³Universidade Federal do Amazonas – Instituto de Ciências Biológicas (UFAM)
3.1.Introduction
Fragmentation by human activity imposes a great threat to biodiversity. As a consequence
of habitat loss, fragmentation often isolates habitat patches in an aggressive matrix (Fahrig, 2003;
Haddad et al., 2015). Animal species that inhabit fragments are forced to move through human
altered areas, leading to non-optimal movements (Fahrig, 2007) and extinction vortexes (Fagan &
Holmes, 2006). In neotropical systems, fragmentation increases temperature, light penetration in
the understory and wind disturbances, over 500m from forest edge, leading to a high tree mortality
(Laurance et al., 2018). Such disturbances may create a strong selective pressure on populations,
which most of individuals of forest species are unable to endure (Baguette & Van Dyck, 2007;
Bélisle, 2005; Harris & Reed, 2002). On the other hand, this same pressure may lead to rapid
phenotypic adaptations to improve general fitness (Cheptou et al., 2017).
Behavioral adaptations are usually adjustments to environmental conditions imposed by
fragmentation, e.g., birds that change their vocalizing period to avoid urban noise (Fuller et al.,
2007) or even change their acoustic signal after character release process (Bicudo et al., 2016). A
less discussed adaptation that can predict how individuals will react to novelty created by human
activity is in the exploratory behavior. Exploration is a variable set of behaviors where individuals
gather environmental information, playing an important role on identifying potential resources and
hazards (Dingemanse et al., 2002a; Mettke-Hofmann et al., 2006). Veerbeck et al (1994) first
described exploratory variation in avian natural populations, based on individual reaction to
novelty, measuring it with exploration scores and pace. When presented to an unfamiliar
environment, individuals with high exploration scores moved quickly through it, facing novelty
with little neophobia (Veerbeck et al. 1994). While individuals with low scores moved slowly
through the environment and took longer to explore all its attributes (Verbeek et al., 1994). These
sets of behaviors and its variations were named in profiles after individual exploration pace while
presented to a novel environment, as “fast” and “slow” explorers (Verbeek et al., 1994). Given the
time invested on exploration, these profiles differ in how individuals perceive and acquire new
environmental information and how they will react to novelty (Dingemanse et al., 2002b). Fast
individuals usually explore novelty superficially, are less likely to notice hazards and thus more
prone to take high risk decisions while exploring (Van Oers et al., 2004), but are usually more
aggressive and dominate resources more efficiently. On the other hand, slow individuals are highly
reactive to novelty – i.e., usually by being neophobic –, but are more efficient while identifying
inconspicuous environmental cues or hazards (Veerbeck et al. 1996). Cornelius et al. (2017)
reported exploratory behavior differences in a forest specialist avian species, where a slower
exploration pace prevailed in populations living in forest fragments, when compared to populations
from non-fragmented landscapes. This difference was related to a behavioral adjustment to better
cope with hazards imposed by human modified landscapes and to successfully traverse open areas
(Cornelius et al. 2017). Woodland butterflies from different landscapes also showed a similar
pattern (Merckx et al. 2003). Butterflies from continuous landscapes are less reactive to hazard
sources and much more prone to risk, i.g., traverse open areas – where they are much more
susceptible to predation -, while individuals from fragments avoid boundaries and usually not dare
to cross them (Merckx et al., 2003).
On the same perspective, morphological adaptations are also reported on animal
populations living in human altered areas. These adaptations follow the same pattern as behavioral
adaptations and are associated with the challenge to cope with new pressures created by human
activity (Perry, 2020). Brown & Brown (2013) reported wing shape adaptation in a swallow
population that predicted improved individual maneuverability to avoid vehicle collision in a road
built next to a nesting site. Martin et al. (2017) have found similar adaptations in the wing shape
of Paridae populations as a response to a 100 years landscape fragmentation. Authors described a
tendency of homogenization of wing shape on different species of a same family: species with
pointier wings had a higher dispersal ability and became less dispersive, with a rounder shape
wings (Martin et al., 2017). The opposite was true for species with less dispersal ability, with round
shape wings, which became more dispersive with pointier wing shapes (Martin et al., 2017). Some
adaptive changes may be less evident. Bill shape adaptations, e.g., have also been correlated to the
use of feeders in urban environment and the offer of new sources of food (Bosse et al., 2017).
Given that other traits may be under selective pressure, especially in urban environments, one must
also consider traits that might be related to routine activities, such as small movements and
foraging. For birds that are bark explorers, e.g., tarsus and tail length might be relevant traits to be
examined as these traits are directly related to trunk climbing performance (Norberg, 1979; Zeffer
& Norberg, 2003) and thus to environment exploration while foraging.
Given the constant expansion of human settlements, it is of high importance to understand
how animal populations may respond to new conditions imposed by human activity. Urban
environments impose extreme conditions on wildlife, and even so some native species are able to
persist in natural remnants within cities (Aronson et al., 2014); little is known about adaptations
that allow them to do so. In this research, we evaluated the effect of habitat fragmentation in an
urban landscape on the phenotype of an understory forest specialist bird species in the most
populated city in Central Amazonia. Understory birds are especially sensitive to forest
fragmentation (Lees & Peres, 2008; Sekercioğlu et al., 2002) and are usually the first group of
birds to be locally extinct in a forest fragmentation scenario (Van Houtan et al., 2007). Our
objective was to identify phenotypic divergence on urban populations of the Wedge-billed
Woodcreeper (Glyphorynchus spirurus, Dendrocolpatidae) by using an experimental design of
“fragmented versus continuous” landscapes and comparing individuals from forest fragments in
an urban landscape with individuals from continuous preserved forests. Our hypothesis is that
populations from forest fragments differ in both behavior and morphology when compared to
populations from continuous forests. We expect that individuals from forest fragments have a
slower exploration pace than those from continuous forests. Given the constant challenge of
traversing highly modified open areas and the environmental conditions of forest fragments
described above, we also expect morphological differences of traits related to dispersal (long
distance movement) and environment exploration (short distance movement) between individuals
from the fragmented and continuous forest landscape. Specifically, we predict that 1) individuals
from the fragmented landscape score lower for exploratory behavior traits, taking longer to explore
attributes in novel environment, than individuals form the continuous forests, and 2) individuals
form forest fragments should have more pointed wings and tarsus and tail length should differ as
a consequence of selective pressures imposed by the environment in fragmented landscapes.
3.2.Methods
3.2.1. Study site and experimental design
Most of central and western Brazilian Amazonia is still highly preserved with large
continuous areas that retain natural vegetation cover. On most of Amazonas State’s (Brazil) we
can sample and study natural systems with little or none human disturbance. Our samples were
made in Amazonas State in two groups of landscapes: (1) fragmented forests surrounded by urban
matrix in the capital city (Manaus) and (2) continuous and preserved forest sites (Fig. 1). In order
to guarantee discrepant sampling between preserved and disturbed environments, continuous
forest sites were set at more than 30km north of Manaus’s urban periphery, as in shorter distances
forests are fragmented by secondary roads and small settlements of country houses. Samples in
continuous forests were made in two different sites: the Experimental Farm of the Amazonas
Federal University (FAEXP) and the “Cuieiras” research base of the National Institute of
Amazonian Research’s (INPA). Both continuous sites are represented by primary “terra firme”
forest. FAEXP has a RAPELD plot system (Magnusson et al., 2005) that we used as sample sites
and on INPA’s base we established sampling sites along trails opened for research purpose in the
interior of the continuous forest.
Samples were conducted between July of 2019 and February of 2020. Samples from forest
fragments were made inside the urban perimeter of Manaus, a ca. 2 million people city (available
at: https://www.ibge.gov.br/, accessed in September 2020). Two large fragments were selected
because known occurrence of the sampled species: a 600 ha forest fragment in which the
Amazonas Federal University campus (UFAM) is located and a 180 ha forest fragment in which
the “Eduardo Gomes” International Airport is located (Fig. 1). Both fragments are mostly formed
by old secondary forest, with small patches of primary, “terra firme” forest, with a few buildings,
roads and other human made structures. The UFAM fragment has 10 pairs of permanent
monitoring plots in riparian and non-riparian habitats, at various distances from forest edges, which
we used for sampling. On the airport fragment, we gave preference to core areas, sampling no less
100m from forest edges.
Subjects were captured with mist nets (Ecotone© 12m, 36mm mesh). Sampling effort was
described in hours-net, where each hour a single net was open, one hour of effort was accounted.
Depending on field conditions, we used six to 10 nets in continuous forests and eight to 20 nets in
forest fragments. We sampled 19 subjects from forest fragments, 10 from the UFAM fragment and
9 from the “Eduardo Gomes” international airport fragment, and 19 subjects from continuous
forest sites, five from the INPA’s Cuieras base and 14 from the FAEXP. Accumulated sampling
effort in the continuous forest sites was 575 net-hours and 2611 net-hours in forest fragments.
Figure 1 – Sampling sites. Sites in the urban area of Manaus, arrows F1 and F2 indicates the UFAM campus
site and the international airport fragment site, respectively. Sites in the continuous forests area, C1 indicates
the INPA’s base site and C2 the FAEXP site.
The species selected for this research was the Wedge-billed Woodcreeper (Glyphorynchus
spirurus; Fig. 2), a small (10.5 – 21g) insectivorous understory forest bird and bark forager,
abundant in primary and secondary forest (Marantz et al. 2020) and one of the few species of
understory forest specialists that inhabits forest fragments in Manaus (Conceição et al. 2013).
Although considered solitary, it is commonly seen in mixed flocks with other understory birds,
and may even join bird flocks associated with army ants (Marantz et al. 2020). Adults, both male
and females, are sedentary with movements restricted to its small territories (5 ha), with no
migration or seasonal movements (Marantz et al. 2020), but it has been shown that G. spirurus has
little genetic structure on populations within a continuous forest area of 10.000 ha, suggesting
periodically long-distance movements within the forest (Menger et al. 2018). Reproductive season
is not consistent through its distribution, but based on incubation plate in central Amazonia, nesting
period is between October and March, during the flooding season (Stouffer et al., 2013). It is
widely distributed in the Amazon Basin, with taxonomic divergence among populations that occur
on different sides of major rivers (Fernandes et al., 2013). Sampling sites were all in the same
interfluve, north of Rio Negro, therefore we had no bias of sampling different subspecies.
Figure 2 – Study species, the Wedge-billed Woodcreeper (Glyphorynchus spirurus; Credits: Priscilla Diniz).
3.2.2. Novel Environment Test
We tested exploratory behavior based on the Novel Environment Test method proposed by
Verbeek et al. (1994). Each bird was presented to an unfamiliar environment: a cage (3.0 m x 3.0
m x 2.0 m) of aluminum structure, covered with a 2mm mesh and a plastic sheet, to prevent
escaping behavior (Huang et al., 2015; Fig. 3). After capture, subjects were measured, banded and
then transported in cloth bags to a testing site where the novel environment test cage was set up.
Tests were always conducted near the capture site and inside forested areas, in order to avoid stress
from long handling time. Before tests were run, the individual was placed inside the testing cage
in a card paper box for acclimatization. The box had a string tied to the cover, which allowed to
release the bird from a distance outside the testing cage. Five perches (trunks 1.5 m tall and 0.3 m
wide) were placed inside the cage to induce exploration (Fig. 3). Since G. spirurus is a bark
forager, we used tree trunks as perches during our tests. After five minutes of acclimatization, the
box was opened and access to the cage was allowed for 20 minutes (1200 s). At the end of the test,
we used a small net with a handling to recapture and immediately release individuals. From the
moment that subjects were placed in the boxes until the end of tests, no more than 20 minutes
passed and all disturbances from human presence were avoided. Only one bird was tested at a time.
Figure 3 – Novel environment test design for Glyphorynchus spirurus. (A) Cage (3,0 m x 3,0m x 2,0 m) with
plastic sheet cover and (B) without it, showing the mesh underneath. (C) Cage interior overview with five
vertical perches (circles) to stimulate exploration, cameras positioned in corners (small boxes) and the
acclimatization box next to the entry (large box).
Activity inside the cage was recorded with three cameras for later analyses. Exploratory
behavior was defined by four traits: 1) time spent outside the acclimatization box (Test time), 2)
visiting events (each time a subject changed from an object to another), 3) number of objects
visited (perches, walls or ceiling), and 4) the number of hops and flights during the entire test
duration (adapted from Verbeek et al., 1994; Dingemanse et al., 2003, 2004). We also registered
the latency times from the start of the test (t = 0 s) until 1) subjects left the acclimatization box and
2) subjects visited each of the five perches. Perches were numbered according to the order in which
each subject visited them. The quantification of these metrics and behavioral analyses were
conducted in BORIS (Behavioral Observation Research Interactive Software; Friard & Gamba,
2016) and were made by the same observer (SSA).
3m
3m
A B
C
Because subjects left the acclimatization box at different times after the lid was open, and
therefore had different time exploring the cage, we standardized values for hops and flights, objects
visited, and visiting events to the number per minute to facilitate unbiased comparisons among
subjects. We first standardized the units of test time to 5 min (300s; t standardized = t test/300) periods,
because the shortest test time for a subject was five minutes. We then divided the value of each
exploratory trait by the standardized test time (its 5min rate) and multiplied by 100, rendering to
the trait score (scoretrait = trait value/t standarized * 100). After examining normality of these variables,
we log transformed them due to high dispersion of values from a normal distribution.
3.2.3. Morphological traits
As proposed by (Cheptou et al., 2017), adaptations are expected in movement traits in
animal populations living in fragmented landscapes, as strong selective pressures should exist for
animals moving between fragments. We chose two categories of movement traits: long distance
movements (dispersal) and short distance movement (foraging and routine movements). For long
distance movements, we measured two traits to get an index of dispersal ability in birds (Dawideit
et al., 2009), the length of the longest primary and secondary feathers. Dispersal ability is then
measured with the hand-wing index (HWI), as a proxy for avian morphological suitability to
traverse open areas (Claramunt et al. 2012; Sheard et al. 2020), and is calculated using the distance
from the carpal joint and the tip of the longest primary (PD) and secondary (SD) feather:
100*(PD/PD-SD; adapted from Claramunt et al., 2012). For short distance movements, we
measured tarsus and tail length. Body mass (weight) of the birds was measured as it is used both
for long and short distance movements. All measures were made according to Baldwin et al. (1931)
and were made by the same observer (SSA).
3.2.4. Statistical analyses
Variation of morphological and behavioral traits
Variation of morphological and behavioral traits among individuals from the fragmented
and continuous landscapes was analyzed with generalized linear models (GLM). We used a
negative binomial distribution for behavioral traits and Gaussian distribution for morphological
traits and conducted univariate tests for population differences on each metric. However, we relied
on GLMs with multiple response variables to investigate a multivariate shift in behavioral and/or
morphological traits among landscapes of origin. Models were adjusted based on the median of
residual deviance and were accepted if medians lay between +1 and -1. Analyses were conducted
with the MASS package in R version 3.6.2 software (R-Core-Team, 2019). Finally, we used a linear
discriminant analysis (LDA) with pooled morphological and behavioral metrics to determine if
variation in morphological and behavioral traits was enough to clearly separate individuals in two
groups, fragmented and continuous forest. LDA describes the distinctiveness of groupings using
misclassification matrices. We chose this method over other ordination methods, e.g., Principal
Component Analysis (PCA), as LDA uses less scores to classify samples and it is more efficient
with low sample sizes. This analysis was conducted with the stats package using R version 3.6.2
software (R-Core-Team, 2019).
Variation in latency times
We chose a failure analysis approach (Fox 2001) for analyzing the latency times for
subjects to leave the acclimatization box and to reach each perch, registering observations at every
second for 20min (1200s). This approach considers time until a certain event occurs in an
observation period, thus scoring as survival the time before the event and as failure once the event
has occurred (Fox 2001). As such, every one-second observation in which the acclimatization box
was still occupied or when a perch was not yet visited was considered a survival event. A failure
event was considered when the individual left the box or reached a perch. Failure could happen
once for the acclimatization box and multiple times for perches, but only the first failure (visit) for
each perch was considered. Because subjects could not visit more than one perch at the same time,
only one perch could fail at each observation. A hazard rate was given by the chance that a failure
event would occur in a given time. To evaluate how time may affect the hazard rate, we tested a
survival model with a distribution defined by a shape (ρ) parameter. When ρ < 1, hazard chance
decreases over time, i.e., the longer a subject remains in the box, lower is the chance to leave it,
but if ρ > 1, the opposite is true. When ρ ≠ 1, the distribution is called Weibull. If ρ = 1 the hazard
rate is constant, that is, the chance for a certain event to happen is the same at any given observation
time (exponential distribution). If a certain event was never observed during our observation time
(e.g., a subject that never left the box or a certain number of perches that were never visited), it
was considered as censored data.
Latency times for each response variable (time to leave the box and time to reach each
perch) was modeled using the survreg function in R version 3.6.2 software (R-Core-Team, 2019)
and with the population of origin (continuous or fragmented) as response variable. We modeled
the hazard rate with Weibull and Exponential distributions, which lead to four models for each
response variable: (1) latency time ~ origin (Weibull), (2) latency time ~ origin (Exponential), (3)
latency time ~ 1 (Weibull) and (4) latency time ~ 1 (Exponential); for each latency time: (1) time
to leave acclimatization box, (2) time to reach the first (3) second, (4) third, (5) fourth and (6) fifth
perch. Model selection followed the approach by Burnham & Anderson (2002) using Akaike
Information Criterion (AICc) values. Models with ΔAICc < 2 were considered as equally plausible
and model weight values (wi) were compared among selected models. Latency time was
graphically represented as Kaplan-Meier survival curves (Kaplan & Meier, 1958). All analyses
were conducted with the package survival in R version 3.6.2 software (R-Core-Team, 2019).
During analyses of traits variation and latency times, subjects were grouped in landscape
times and sites were not analyses separately.
3.3.Results
3.3.1. Exploratory behavior and morphology
Analyses for behavioral traits were conducted with 17 subjects from forest fragments and
18 from continuous forests, as two and one subject, respectively, never left the acclimatization
box. Results for exploratory behavior traits are shown in Fig. 4. No difference was found among
individuals from forest fragments (f) and the continuous forest (c) for the number of hops and
flights (meanc = 43.48 ± 37.69, meanf = 45.94 ± 31.34, p = 0.842), events of changes among objects
(meanc = 4.5 ± 0.46, meanf = 4.5 ± 0.53, p = 0.99,), test time (meanc = 2.95 ± 0.87, meanf = 2.56 ±
0.85, p = 0.485) and objects visited (meanc = 201.4 ± 108.85, meanf = 186.48 ± 104.67, p = 0.693,).
The multivariate model combining all behavioral variables returned no difference between
populations (R2 = - 0.05 p = 0.78)
Figure 4 – Exploratory traits: time spent exploring the testing cage – normalized to 5 min intervals -, score of
visiting events, score of objects visited – including perches, walls and ceiling -, score of hops and flights during
the whole test time (see methods).
Analyses for morphological traits were conducted with 19 subjects from forest fragments
and 19 from continuous forests and results are presented in Fig 5. No difference among subjects
from the forest fragments (f) and the continuous forest (c) was observed for long distance
movement traits: HWI (meanc = 18.62 ± 3.26, meanf = 18.46 ± 2.8, p = 0.93), primary feather
length (meanc = 68.11 ± 2.56, meanf = 67.42 ± 2.48, p = 0.405), secondary feather length (meanc =
55.46 ± 2.73, meanf = 54.99 ± 3.06, p = 0.617) and weight (meanc = 13.44 ± 1.09, meanf= 12.77 ±
1.56, p = 0.13; Fig. 5). But short distance movement traits, tarsus and tail length, were significantly
different between populations, with subjects from forest fragments having shorter tarsi (meanc =
16.54 ± 1.29, meanf = 15.44±1.91, p = 0.04) and shorter tails (meanc = 68.94 ± 3.39, meanf = 66.12
± 4.46, p = 0.03) than subjects from the continuous forest (Fig. 5). The multivariate model
combining all morphological variables returned a significant variance between populations (R2 =
- 6.66, p = 0.01).
Figure 5 Morphological traits: hand-wing index (Claramunt et al. 2012, Sheard et al. 2020), weight, longest
primary and secondary feathers, tarsus and tail length, according to Baldwin et al. (1931).
Linear discriminant analysis (LDA) was conducted with 18 and 17 subjects for continuous
and fragmented forest, respectively. Because three subjects did not have values for behavioral
traits, their morphological measurements were excluded from this analysis. LDA presented 94.5%
accuracy (17 out of 18) in classifying subjects from continuous forests and 82.3% (14 out of 17)
from forest fragments, given a total of 88.5% of accuracy (31 out of 35). Considering
morphological and behavioral traits together yielded the highest accuracy (Table 1). Probabilities
for discriminant scores using behavioral and morphological traits has the best separation between
groups, although with some overlapping (Fig. 6). Subjects with same scores may be grouped in
the same origin (fragmented and continuous groups), e.g. subjects with approximately -1 score
have about 50% chance of being from continuous group and about 30% chance of being from
fragmented group (Fig. 6).
Table 1 – Misclassification matrix using LDA’s accuracy for origin estimative are presented for each run of the
analysis with behavioral and morphological variables separately and with all variables combined. Estimative
values represent LDA attempt while classifying subjects using measured traits. Observed values represent the
real origin of each subject. Note that all lines have the same values as the number of subjects used in this
analysis for continuous and fragmented origins, 18 and 17, respectively.
Estimative
Observed Continuous Fragmented Accuracy (%)
Behavior
Continuous 13 5 72.2
Fragmented 8 9 52.9
Morpholog
y
Continuous 14 4 77.8
Fragmented 6 11 64.7
Behavior +
Morpholog
y
Continuous 17 1 94.5
Fragmented 3 14 82.3
Figure 6 – Discriminant scores for LDA with morphological and behavioral traits. In the x axis are represented
the interval of scores for LDA, while the y axis represents the probability of an individual with that score to
belong to a certain group. Continuous group represents probabilities for scores of subjects from continuous
forest, while fragmented group represents probabilities for subjects from forest fragments.
3.3.2. Latency times
Failure analyses for the latency times were made with 19 subjects from forest fragments
and 19 from continuous forests. Two subjects from forest fragments and one from continuous
forest never left the acclimatization box. Fifteen subjects from the continuous forest explored at
least one perch, with four subjects never reaching the first perch and preferred to use the cage walls
and ceiling. Only, five subjects from forest fragments explored at least one perch. Ten subjects
from continuous forest and four from forest fragments explored at least two perches. Three subjects
from continuous forests and one from forest fragments explored all five perches.
For time until subjects left the acclimation box (Box latency time), the constant model was
selected as the best model suggesting no difference related to population of origin (w = 0.46) for
this variable. The model fitted to the Weibull distribution (ρ = 1.34) suggesting an influence of
time spent in the box, meaning that the longer a subject remained in the box, the greater the chances
of leaving it (Table 2). For time to reach the first and second perch the best model was the model
considering population of origin as predictor variable (w = 0.711 and w = 0.539, respectively;
Table 2). In both cases, the Exponential distribution (ρ = 1) model was selected over the Weibull
model indicating that time spent inside the cage had no influence in the chance of reaching a perch
(Table 2). For time to reach the second perch the constant model was also selected within the
plausible models (with ΔAICc < 2) indicating weaker evidence for an effect of population of origin.
For the time to reach the third, fourth and fifth perch, the constant model was always the best
model, and there was high uncertainty associated to all selected models, indicating no evidence for
an effect of population of origin as a factor that influenced time until reaching these perches (Table
2).
Table 2 – Model selection results based on ΔAIC for latency times tested using survival analyses. Distribution
represents the Failure Analysis type of distribution with a ρ value that represents the influence of time in the
observed event (see Methods). AICc is the information score of the model, ΔAICc is the difference between the
best model and the model being compared with, df is the number of parameters in the model and wi is the
predictive power of the model.
Rank Model Distribution ρ AICc ΔAICc df wi
Box lantency time
1 constant Weibull 1.34 501.5 0.0 2 0.46
2 origin Weibull 1.49 502.7 1.2 3 0.25
3 constant Exponential 1 503.4 2.0 1 0.17
4 origin Exponential 1 504.2 2.7 2 0.12
First perch
1 origin Exponential 1 325.8 0.0 2 0.71
2 origin Weibull 1.5 327.6 1.9 3 0.28
3 constant Exponential 1 335.2 9.5 1 0.00
4 constant Weibull 1.25 336.2 10.4 2 0.00
Second perch
1 origin Exponential 1 248.3 0.0 2 0.54
2 constant Exponential 1 250.1 1.8 1 0.22
3 origin Weibull 0.93 250.6 2.3 3 0.17
4 constant Weibull 0.96 252.3 4.0 2 0.07
Third perch
1 constant Weibull 0.55 171.2 0.0 2 0.35
2 constant Exponential 1 171.8 0.6 1 0.26
3 origin Weibull 0.54 172.1 0.9 3 0.23
4 origin Exponential 1 172.8 1.6 2 0.16
Fourth perch
1 constant Exponential 1 102.8 0.0 1 0.27
2 constant Weibull 0.49 102.9 0.1 2 0.26
3 origin Exponential 1 103.0 0.2 2 0.24
4 origin Weibull 0.48 103.2 0.4 3 0.22
Fifth perch
1 constant Exponential 1 84.5 0.0 1 0.37
2 constant Weibull 0.49 85.1 0.5 2 0.28
3 origin Exponential 1 85.7 1.2 2 0.20
4 origin Weibull 0.48 86.3 1.8 3 0.15
Kaplan-Meier survival curves (Fig. 7) illustrates the differences between populations for
latency times indicated by model selection. Each step on the survival slope represents a failure,
i.e. a subject leaving the box or reaching a perch. Curves for time until leaving the box show no
difference between populations (forest fragments versus continuous forest). In the other hand, time
to reach the first and second perch were different between populations, with individuals from the
continuous forest reaching the first and second perch in a shorter time than individuals form forest
fragments. Curves become similar again for time to reach the third, fourth and fifth perch.
Figure 7 – Kaplan-Meier survival curves representing the time for subjects from continuous (solid lines) and
fragmented (dotted lines) landscapes to leave the acclimatization box and to reach the first, second, third, fourth
and fifth perches, respectively (panels from upper left to bottom right).
3.4.Discussion
Our study revealed phenotypic differences among traits related to movement ability and
exploration of environments, between G. spirurus populations from forest fragments in an urban
context and from continuous forest. Although, some differences were not as expected – as
morphological traits related to long distance movements - we found differences for traits related
to short distance movements. Morphological traits had a stronger divergence than behavioral traits,
but when analyzed together this strengthened evidence for phenotypic variation among
populations. Most behavioral traits associated with exploration provided little evidence for
differences between populations, but latency to move to perches while exploring an unfamiliar
environment confirm growing tendency that individuals persisting in forest fragments are slower
explorers when compared to individuals from continuous forest (Cornelius et al., 2017).
3.4.1. Morphological differences
Tail and tarsus were the most discrepant morphological traits between populations, as
individuals from forest fragments had shorter tarsi and tails than individuals from the continuous
forest population. Long tarsi have been observed in G. spirurus populations living in forests with
high moss density, which was explained as an adaptation to reduce friction between birds and
moss, allowing a better performance while clinging trees (Milá et al., 2009). In turn, shorter tarsi
reduce distance between the bird center of mass and used surfaces, allowing vertical climbers to
spent less energy while moving upwards (Zeffer & Norberg, 2003). Tarsus was also independent
from body mass (Zeffer & Norberg, 2003), which explains the observed difference in tarsus length
but not in body masses. It is possible that populations from forest fragments might be experiencing
less resistance while climbing trunks, allowing tarsi to be shorter without a friction penalty. We
cannot directly relate this to reduced moss density in fragments, as it would require a specific
sampling approach to this variable. Although, given the increased temperature and light
penetration in forest fragments (Laurance et al., 2018), lower moss diversity and biomass would
be expected. Tail, on the other hand, is correlated with body mass (Norberg, 1979). Heavier bird
species have longer tails that are used both for movement and keeping stationary while in vertical
position (Norberg, 1979). Shorter tails in forest fragments populations implies that more energy is
being spent while birds are stationary and moving.
Wing measures, longest primaries, secondaries and HWI, were not different between
populations. These traits represent a proxy for morphological ability to traverse non-forest areas
(Dawideit et al., 2009). We expected that subjects would be trying to access other fragments, thus
facing the matrix or using small connections between fragments. Based on the lack of discrepancy
in these morphological traits, however, it is possible that individuals might not be dispersing at all
between fragments and thus dispersal patterns within fragments in the urban landscape are the
same as in continuous forests, with short distance dispersal events restricted to early life stages
(Paradis et al., 1998). This would imply that subjects are either perishing in the matrix while trying
to reach other fragments, or that fragmentation per se is inhibiting dispersal movements. Dispersal
events can also happen in later life stages (Clobert et al., 2012), and food availability is what mostly
influences dispersal in different taxa (Fronhofer et al., 2018). G. spirurus feeds mostly on small
arthropods, specially ants of the Pheidole genus (Marantz et al. 2020) a very abundant ant taxa in
the neotropics (Vicente et al., 2018). Given that body mass was not different between populations,
it is possible that subjects from forest fragments are not experiencing food scarcity, decreasing
their need to disperse in search for food. Nevertheless, given the five-fold higher capture rates of
G. spirurus in continuous forests in comparison to fragments, it is possible to infer that the species
occurs at lower densities in the fragmented landscape. Bierregaard & Lovejoy (1989) detected
initially an abundance increase of G. spirurus during the initial years after fragmentation, followed
by a decrease in later years. Moreover, G. spirurus is only found in very large forest fragments (>
100 ha) within the urban landscape indicating that populations are not able to persist in small and
isolated fragments (Conceição et al. 2013).
3.4.2. Behavioral differences
Exploration profiles have been related to trade-offs between risk exposure and resource
reward (Van Oers et al., 2004), among other things. We did not find significant differences in most
individual behavioral traits tested between populations. But we only studied one species and it is
highly specialized on tree creeping. As far as we know, this is the first time that a species from this
functional guild has been assessed regarding its exploratory behavior and, also, we only measured
a small number of traits (Carter et al., 2013). Exploration features for avian populations were
designed with species from temperate regions (Verbeek et al., 1996, 1994). It is possible that other
traits could better express exploration for G. spirurus, e.g. handling aggressiveness and breath rate
(Charmantier et al., 2017; Senar et al., 2017). For instance, our results from linear discriminant
analyses showed that correct classification of subjects to their populations was higher with all traits
combined than when traits were compared separately. This suggests significant differences
between populations from fragmented and continuous forests in a broader scale, despite not being
so for individual traits, which highlights the relevance of investigating additional morphological
and behavioral traits potentially associated to exploratory behavior.
Latency times are considered an efficient way to predict exploratory behaviors (Groothuis
& Carere, 2005), and our results agree with this idea. Testing subjects from forest fragments took
longer to explore perches from an unfamiliar environment, a feature that represents slow
exploration (Verbeek et al., 1994), in agreement with our hypothesis that fragmentation may have
selected a suite of slow exploratory behaviors. This same pattern has already been described with
other neotropical bird species from the forest understory (Cornelius et al., 2017) and woodland
butterflies (Merckx et al., 2003), suggesting that individuals with a fast exploratory profile, usually
more prone to take risks, are being eliminated from fragmented landscapes.
While examining the recordings from our tests, we noticed that in late phases of the
experiment, most subjects reached to higher areas of the cage, which was not possible to present
analytically. Individuals from forest fragments preferred to use ceiling and walls over perches,
when compared to continuous forest subjects, and when they did decide to visit a perch, they took
longer to reach it. Also, individuals from forest fragments commonly flew through the cage
directly to walls and ceiling, ignoring the perches, while most subjects from continuous forests
used at least two perches before reaching to higher areas, which agrees with a more risk-taking of
fast explorer (Dingemanse & Réale, 2005). We can also see that the number of subjects that
reached the second perch was smaller than those reaching the first perch, a pattern that applies
throughout the fifth perch. This suggests individual decision to either keep exploring the perches
or, alternatively, to reach for higher areas of the cage, ceiling and walls, or yet the decision to keep
in the same object until the end of the test.
3.4.3. Limitations and sampling bias
We also would like to discuss some limitations of our study. We cannot imply that
differences observed were actually adaptations, phenotypic plasticity or a result of genetic drift, as
it would require a genetic approach with common garden experiment (Merckx et al., 2003, Kaiser
et al 2019) and direct measures of fitness. Personalities can fit different situations (Dingemanse &
Réale, 2005), fluctuating with spatial and temporal changes (Dingemanse & Wolf, 2010) and our
work only represents a small frame of a long-time fragmentation process. Additionally, captures
with mist nets could bias sampling, as slow explores tend to identify and avoid passive capture
methods (Stuber et al., 2013). Given our five times higher sampling effort in forest fragments than
in continuous forest to attain the same number of captured individuals, slow exploration could be
underestimated. Nevertheless, if we sampled mostly faster explorers in forest fragments, those are
still slower than what we found in continuous forest. Also, observed behavioral difference could
potentially be related to sex related different among sampled populations, as would be expected
for species in which males and females present different behaviors (Awade et al., 2017;
Dingemanse & Wolf, 2010). Although G. spirurus has no sexual dimorphism, we have no reasons
to believe that males and females have significant differences in exploratory behavior, as this
species is mostly observed in pairs, usually male and female, while foraging, defending their
territories and in parental care (Marantz et al. 2020, Darrah & Smith, 2013). Furthermore, it is
unlikely that sex related variation in exploratory behavior would be greater than that observed
between the studied populations, given the consistency of our trait values within populations. On
the other hand, young dispersing birds may corroborate to an unexplained variation. Young
dispersing individuals may travel long distances before settling its own territory and it is expected
that age differences may imply on different exploratory behaviors (Dingemanse & Wolf 2010).
We did not had a safe method to differentiate an dispersing and young individual from an adult
with an stablished territory, so we cannot argue that all subjects tested were fully adults.
3.5.Conclusion
Finally, it was not our goal to relate observed differences to environmental variables, but
to highlight that populations are accumulating phenotypic differences in response to landscape
fragmentation, specifically in a very harsh condition as in urban settings. As such, our results
should not be interpreted as a resilience to fragmentation per se, but rather as a possible adjustment
to habitats in forest fragments with specific conditions that can support populations. It still remains
a challenge to understand if these populations will be viable in the long-term, as well as which
landscape configuration features may guarantee the viability of populations in forest fragments
located in urban settings. An examination of traits in demonstrably older fragments compared to
newer ones, and larger versus smaller isolates of the same or different ages, would help illuminate
the development and function of intra-specific trait shifts we observed (Liu et al., 2019; Warzecha
et al., 2016). Our work, and future work on this topic underscores the importance of species traits
in determining fragmentation response both among (Valente & Betts, 2018) and within species
(Cornelius et al., 2017). Particularly considering the high current rates of deforestation in
Amazonia, these forest remnants could disappear fast and adaptation to altered habitats would not
save forest species from being extinct.
Given the vast damage of fragmentation to biodiversity globally, and its persistent spread,
protection of every fragment of suitable habitat is a priority. In part because any species are worth
protecting no matter they occur, and especially in urban habitats where people benefit from the
aesthetics and ecosystem functions they provide. But also because, as our work clearly shows,
fragments in urban settings are hotbeds of rapid evolutionary changes that may, ultimately, lessen
the severity or extinction debts incurred by human activities.
3.6.Conflict of interest
Authors declare no conflict of interest.
3.7.Animal Rights
All applicable institutional and/or national guidelines for the care and use of animals were
followed.
3.8.Acknowledgements
We would like to thank all volunteers who helped during our field expeditions: Anaís Prestes,
Beatriz Barreto dos Santos Modesto, Francielen Paiva, Gisiane Rodrigues, Iamile Brandão de
Oliveira, Jessica Andrade de Oliveira, José Raulino, Lucas Carvalho de Jesus, Juliana de Oliveira
Pinheiro, Marcos Pimentel Abbade, Max Queiroz, Natasha Helena, Natasha Raíssa, Pedro Paulo,
Phamela Barbosa, Priscilla Diniz and Riomar Queiroz. We also thank the INFRAERO for allowing
us to access the “Eduardo Gomes” International airport for sampling and the “Museu na Floresta”
for providing logistical support during one of our field expeditions. This study was financially
supported by FAPEAM (Universal Amazonas - 002/2018). Field work and avian captures were
performed under the license granted by the Brazilian Government (ICMBio/SISBio 66065-1).
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4. Síntese geral
Nosso estudo revelou diferenças fenotípicas nos traços relacionados à capacidade de
movimentação e exploração entre populações de G. spirurus de fragmentos florestais em contexto
urbano e de floresta contínua. Apesar de algumas diferenças não serem como esperadas – como
em traços morfológicos relacionados à movimentação em longa distância – nós encontramos
diferenças em traços relacionados a movimentações em curta distância. Traços morfológicos
tiveram maior divergência do que os traços comportamentais, porém, quando analisados em
conjunto (morfologia + comportamento) oferecem maior força de evidência, ressaltando a
diferença entre as populações amostradas. A maior parte dos traços comportamentais medidos
ofereceram pouca evidência de diferença entre as populações, mas os tempos de latência até os
poleiros, enquanto explorando um ambiente desconhecido, confirmam que indivíduos de
fragmentos florestais são exploradores mais lentos do que os de paisagens contínuas (Cornelius et
al., 2017).
Não foi nosso objetivo correlacionar as diferenças observadas com variáveis ambientais,
mas de ressaltar que populações estão acumulando diferenças fenotípicas em resposta à
fragmentação florestal, especificamente em condições drásticas de ambientes urbanos. Assim,
nossos resultados não devem ser representados como um sinal de resiliência à fragmentação, mas
sim como possíveis ajustes à habitat em fragmentos florestais com condições que ainda podem
suportar populações. É ainda um desafio entender se essas populações serão viáveis a longo prazo,
assim como que tipo de configurações espaciais de paisagem podem garantir a viabilidade das
populações em fragmentos urbanos. Examinar os traços fenotípicos em fragmentos com tamanhos
e tempos de isolamento distintos, pode ajudar a entender o desenvolvimento e a função
intraespecífica das diferenças observadas (Liu et al., 2019; Warzecha et al., 2016). Nosso trabalho
e trabalhos futuros mostram a importância em se determinar a resposta de traços fenotípicos intra
(Valente & Betts, 2018) e interespecíficos (Cornelius et al., 2017). Particularmente considerando
as altas taxas de desmatamento na Amazônia, esses remanescentes florestais podem desaparecer
depressa e nenhuma adaptação a áreas alteradas salvaria espécies florestais de seguir o mesmo
destino.
Dado ainda o vasto dano que a fragmentação florestal tem causado em nível global, a
proteção de cada fragmento de habitat viável deve ser uma prioridade. Em parte por que todas as
espécies são dignas de proteção, mas em especial por que em áreas urbanizadas a população
humana pode se beneficiar dos serviços ambientais estéticos e funcionais que esses fragmentos
provêm. Nosso trabalho claramente mostra que fragmentos florestais urbanos podem ainda ser
catalisadores de rápidas mudanças evolutivas que podem diminuir a gravidade ou a as taxas de
extinção consequentes da ação humana.
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PROGRAMA DE PÓS-GRADUAÇÃO EM ECOLOGIA
INSTITUTO NACIONAL DE PESQUISAS DA AMAZÔNIA - INPA
PROGRAMA DE PÓS-GRADUAÇÃO EM ECOLOGIA – PPG ECO Av. André Araújo, nº 2936, Bairro – Petrópolis, Manaus-AM, CEP: 69.067-375
Site: http://pg.inpa.gov.br e-mail: ppg.ecologia@posgrad.inpa.gov.br
ATA DA DEFESA PÚBLICA DA DISSERTAÇÃO DE MESTRADO DO PROGRAMA DE PÓS-GRADUAÇÃO EM ECOLOGIA DO INSTITUTO NACIONAL DE PESQUISAS DA AMAZÔNIA.
Aos 24 dias do mês de Setembro do ano de 2020, às 14h00min, por videoconferência. Reuniu-se a Comissão Examinadora de Defesa Pública, composta pelos seguintes membros: o (a) Prof (a). Dr (a). Juliana Menger, do Instituto Nacional de Pesquisas da Amazonia - INPA, o (a) Prof (a). Dr (a). Pedro Pequeno, do Instituto Nacional de Pesquisas da Amazonia (INPA Roraima), e o(a) Prof(a). Dr(a). Charles Duca, da Universidade Vila Velha - UVV, tendo como suplentes o(a) Prof(a). Dr(a). Mario Cohn-Haft, do Instituto Nacional de Pesquisas da Amazônia – INPA, e o(a) Prof(a). Dr(a). Sérgio Borges, da Universidade Federal do Amazonas – UFAM, sob a presidência do (a) primeiro (a), a fim de proceder a argüição pública do trabalho de DISSERTAÇÃO DE MESTRADO do STEFANO SPITERI AVILLA, intitulado: “OS EFEITOS DA FRAGMENTAÇÃO FLORESTAL NO FENÓTIPO DE UM PÁSSARO DE SUBOSQUE NEOTROPICAL”, orientado(a) pelo(a) Prof(a). Dr. (a) Cintia Cornelius Frische, da Universidade Federal do Amazonas – UFAM e Co-orientado (a) pelo (a) Prof. (a) Dr. (a). Marina Anciães, do Instituto Nacional de Pesquisas da Amazonia – INPA.
Após a exposição, o(a) discente foi arguido(a) oralmente pelos membros da Comissão Examinadora, tendo recebido o conceito final:
x APROVADO (A) REPROVADO (A)
x POR UNANIMIDADE POR MAIORIA
Nada mais havendo, foi lavrada a presente ata, que, após lida e aprovada, foi assinada pelos membros da Comissão Examinadora. Prof(a).Dr(a). JULIANA MENGER Prof(a).Dr(a). PEDRO PEQUENO Prof(a).Dr(a). CHARLES DUCA
(Coordenação PPG-ECO/INPA)
PROGRAMA DE PÓS-GRADUAÇÃO EM ECOLOGIA
INSTITUTO NACIONAL DE PESQUISAS DA AMAZÔNIA - INPA
PROGRAMA DE PÓS-GRADUAÇÃO EM ECOLOGIA – PPG ECO Av. André Araújo, nº 2936, Bairro – Petrópolis, Manaus-AM, CEP: 69.067-375
Site: http://pg.inpa.gov.br e-mail: ppg.ecologia@posgrad.inpa.gov.br
DEFESA PÚBLICA DA DISSERTAÇÃO DE MESTRADO
Aluno(a): STEFANO SPITERI AVILLA
Curso: Ecologia Nível: (X) Mestrado (_) Doutorado
Dia: 24/09/2020 – Hora: 14h00min
Local: Por Videoconferência.
Orientador(a): Dr(a) Cintia Cornelius Frische
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