INSTITUTO NACIONAL DE PESQUISAS DA AMAZÔNIA … · na Amazônia e uma na transição da Amazônia...

INSTITUTO NACIONAL DE PESQUISAS DA AMAZÔNIA

PROGRAMA DE PÓS-GRADUAÇÃO EM ECOLOGIA

VULNERABILIDADE DO LAGARTO KENTROPYX CALCARATA ÀS MUDANÇAS

CLIMÁTICAS: EFEITOS DAS VARIACÕES NA BIOLOGIA TÉRMICA EM NÍVEL

INTRAESPECÍFICO

EMERSON PONTES DA SILVA

Manaus, Amazonas

Junho 2016

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EMERSON PONTES DA SILVA

VULNERABILIDADE DO LAGARTO KENTROPYX CALCARATA ÀS MUDANÇAS

CLIMÁTICAS: EFEITOS DAS VARIACÕES NA BIOLOGIA TÉRMICA EM NÍVEL

INTRAESPECÍFICO

DRA. FERNANDA DE PINHO WERNECK

Orientadora

DR. WILLIAM ERNEST MAGNUSSON

Coorientador

Dissertação apresentada ao Instituto

Nacional de Pesquisas da Amazônia

como parte dos requisitos para obtenção

do título de Mestre em Biologia

(Ecologia).

Manaus, Amazonas

Junho 2016

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BANCA EXAMINADORA DA DEFESA ORAL PÚBLICA

Jaydione Luiz Marcon

(Universidade Ferderal do Amazonas)

Albertina Pimentel Lima

(Instituto Nacional de Pesquisas da Amazônia)

George Henrique Rebêlo

(Instituto Nacional de Pesquisas da Amazônia)

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AGRADECIMENTOS

À minha mãe Josenira Pontes, mulher guerreira que inspira a cada chão que pisa. Agradeço à

ela e à minha família pela força e compreensão em todos momentos.

À Dra. Fernanda Werneck pela orientação e confiança em cada etapa deste trabalho. Ao Dr.

William Magnusson pelo ânimo sempre explícíto e disposição em colaborar durante a

coorientação.

À Elizabeth Franklin, Pedro Ivo, Cinara Calvin, Lúcia Tinoco e Jason Telêmaco

(eterno!) pela orientação durante as Iniciações Científicas e demais projetos. Sou um pedaço

de vocês.

A cada amiga e amigo por sua presença, sorrisos e pelos “vai dar certo!”.

Às amigas e amigos da turma ECO 2014, eu definitivamente não consigo imaginar como

poderia ter sido a caminhada nessa estrada sem vocês.

Ao Dr. Guarino Colli e Dra. Teresa Avila Pires pelo apoio na orientação da coleta de dados

e companhia profissional inspiradora em Tocantins e no Pará, respectivamente.

Ao Gabriel Caetano e Juan Santos, pela força fundamental com a modelagem e

intermináveis trocas de idéias.

À todas as pessoas que colaboraram com a coleta de dados em cada local: Carla, Jessica,

Derek, Ana, Luisa, Liriann, Gueviston, Janet, Orsolya, Kate, Dona Maria, Jesus, Seu

Compensa, Dorinha, Seu Móh, Madinson, Sarah e Carlos. Nada seria possível sem a essencial

ajuda que deram (o que inclui os sorrisos, banhos de igarapé e conversas descontraídas pós-

rango).

À Val (nossa futura presidente da república!), à Cida, ao Seu Valdir, ao Rubenildo e a todo

o pessoal do INPA pelo apoio incondicional ao desenvolvimento das atividades de pesquisa

mas, principalmente, pelo apoio à contrução de profissionais humanos por meio da ajuda

mútua.

Ao pessoal do Centro de Pesquisas Canguçú (TO) e ao pessoal da Estação Ferreira Pena

(PA), lugares que por si só são incríveis, mas que com a presença de vocês se tornam lugares

inesquecíveis na vida de quem estuda biologia.

Ao CNPq pela bolsa de pesquisa e ao Programa de Pós-Graduação em Ecologia do INPA,

por proporcionar oportunidades e vivências fascinantes na Amazônia. Ao Partnerships for

Enhanced Engagement in Research da US National Academy of Sciences and US Agency

of International Development pelo financiamento ao projeto.

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Dois anos de mestrado, aprox. 670 dias de múltiplas vivências nos mais variados lugares e

companhias de pessoas. Da calmaria ao desespero, da pele seca no conforto à enxarcada de

suor com mais quilômetros à frente. Momentos instáveis que exigiram força e fé. Meu último

agradecimento, portanto, é para àquelas/àqueles que também me motivam a seguir e resistir:

mulheres e LGBT’s de todos os corpos, cores, crenças e lugares.

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B743 Pontes-da-Silva, Emerson

Vulnerabilidade do lagarto Kentropyx calcarata às mudanças climáticas: efeitos

das variacões na biologia térmica em nível intraespecífico / Emerson Pontes da

Silva. --- Manaus: [s.n.], 2016.

69 f. : il. color.

Dissertação (Mestrado) --- INPA, Manaus, 2016.

Orientadora : Fernanda de Pinho Werneck.

Coorientador : William Ernest Magnusson.

Área de concentração : Ecologia

1. Aquecimento global. 2. Ecologia termica. 3. Lagartos amazônicos I.

Título.

CDD 631.4

Sinopse:

Investigamos os riscos de extinção e a variação dos traços da biologia térmica de

lagartos entre localidades na Amazônia e no ecótono Amazônia-Cerrado.

Combinamos os traços térmicos do ambiente e dos lagartos para estimar sua

vulnerabilidade aos aumentos globais de temperatura. Para tanto, foram avaliados

aspectos como preferência térmica, limites térmicos críticos, desempenho

locomotor e temperaturas operacionais.

Palavras chaves: Aquecimento global, lagartos, extincão local, biologia térmica,

Amazônia,variação intraespecífica

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RESUMO

Aumentos de temperatura podem gerar impactos sobre os organismos e a predição destes

efeitos sobre a biodiversidade é um dos maiores desafios atuais da ciência. Ectotérmicos são

sensíveis a alterações de temperatura. Ainda que predições indiquem que as linhagens

tropicais possuem alta vulnerabilidade ao aquecimento global, elas permanecem como as

menos estudadas com relação à sua vulnerabilidade aos aumentos de temperatura e à extensão

pela qual traços da fisiologia térmica variam dentro de espécies. Aqui, usando uma versão

modificada do modelo de Sinervo et al. (2010) parametrizado com estimativas fisiológicas

feitas em campo, estimamos a vulnerabilidade de um lagarto tropical (Kentropyx calcarata) e

a extensão da variação geográfica intraespecífica dos traços de sua biologia térmica entre

diferentes locais. Nós quantificamos as horas de restrição de atividade e calculamos os riscos

de extinção previstos para K. calcarata para os anos de 2050 e 2070 com base na

adequabilidade térmica prevista para cada ambiente e em um amplo conjunto de dados

geográficos da espécie. Adicionalmente, mensuramos e comparamos a temperatura

preferencial, os limites críticos, as temperaturas operacionais e a sensibilidade do desempenho

locomotor de indivíduos de K. calcarata entre quatro localidades amostrais, três localizadas

na Amazônia e uma na transição da Amazônia com o Cerrado. Os riscos de extinção previstos

para K. calcarata variaram de 2.6% a 52.4% para o ano de 2050 com moderado aumento para

2070, variando de 8.0% a 66.8% de risco entre as grandes regiões investigadas. Mostramos

que existem diferenças do nicho térmico e que ambientes térmicos distintos favorecem a

variação da tolerância térmica máxima de K. calcarata. Nossos resultados mostram que

temperaturas ambientais operacionais mais elevadas impõem a seleção de limites térmicos

máximos. Nossos resultados sugerem que os aumentos de temperatura reduzirão a

favorabilidade da ocorrência de K. calcarata em regiões florestais na Amazônia. Nossos

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resultados apontam que lagartos tropicais estão sob risco de extinção local e que esses riscos

podem ser geograficamente estruturados, pois parte da variação no nicho térmico de K.

calcarata ocorre por diferenças ambientais locais. Concluímos que as diferenças em

características fisiológicas entre indivíduos de uma mesma localidade e entre diferentes

localidades poderão ser a base de adaptação local e permitir maior persistência para este

ectotérmico tropical em um cenário de aquecimento global.

Palavras-chave: Lagartos amazônicos, fisiologia térmica, aquecimento global, variação

intraespecífica

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ABSTRACT

Vulnerability forced by climatic change and intraspecific variation on the thermal

physiology in a tropical lizard

Temperature increases can have impacts on organisms and predicting these effects is one of

the main challenges for climate change research. Ectothermics are sensitive to temperature

change. However, although predictions indicate that tropical ectotherms are highly vulnerable

to global warming, they remain poorly studied with respect to vunerability and the extent that

thermal physiological traits vary within species. Here, we predicted the consequences of

thermal variation forced by increasing temperatures using a modified version of Sinervo et al.

(2010) model parameterized with field physiological estimates and investigated how thermal

biology traits of a tropical lizard species (Kentropyx calcarata) vary intraespecifically

between different locations. We quantified the restriction hours suitable for activity and

calculated the extinction risk for K. calcarata for the years 2050 and 2070 based on the

environmental thermal suitability and a large geographic database. We also measured and

compared preferred temperatures, thermal critical limits, operative temperatures, and

locomotor-performance sensitivity of K. calcarata in three locations in the Amazon rainforest

and one in the transition between the Amazon and the Cerrado biome. Extinction risks

estimated for K.calcarata ranged from 2.6% to 52.4% for the year 2050 with a moderate

increase for 2070, ranging from 8.0% to 66.8% among the major regions investigated. We

show thermal niche differences and that different thermal environments favor variation in K.

calcarata upper thermal limits. Our results show that higher operative environmental

temperatures determine the selection of higher thermal limits. Our results show that tropical

lizards are under local extinction risks and that these risks can be geographically structured,

because part of the variation in K. calcarata thermal niche is by local environmental

differences. We conclude that differences in physiological characteristics between individuals

of the same locality and between different locations may be the local adaptation base and

allow greater persistence to this tropical ectothermic in a global warming scenario.

Key-Words: Amazonian lizards, themal physiology, global warming, intraespecific variation

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SUMÁRIO

RESUMO ........................................................................................................................................ IV

ABSTRACT.................................................................................................................................... VI

LISTA DE TABELAS ..................................................................................................................IX

LISTA DE FIGURAS ....................................................................................................................X

LISTA DE APÊNDICES .............................................................................................................XI

INTRODUÇÃO GERAL ........................................................................................................... 12

OBJETIVO GERAL.................................................................................................................... 16

OBJETIVOS ESPECÍFICOS. .................................................................................................. 16

CAPÍTULO 1: VULNERABILITY FORCED BY CLIMATIC CHANGE AND INTRASPECIFIC VARIATION ON THE

THERMAL PHYSIOLOGY IN A TROPICAL LIZARD ................................................................................... 18

SUMMARY .................................................................................................................................... 20

INTRODUCTION ........................................................................................................................ 22

MATERIAL E METHODS ....................................................................................................... 26

RESULTS ........................................................................................................................................ 36

DISCUSSION................................................................................................................................. 39

ACKNOWLEDGEMENTS ................................................................................................................ 44

REFERENCES ................................................................................................................................... 46

REFERENCIAS ADICIONAIS ............................................................................................... 53

TABLES .......................................................................................................................................... 53

FIGURES ........................................................................................................................................ 59

APÊNDICES .................................................................................................................................. 64

CONCLUSÃO ............................................................................................................................... 67

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LISTA DE TABELAS

Tabela 01: Fisiologia térmica (temperatura preferida - Tpref, e limites térmicos críticos - CTmin

e CTmax) e temperaturas operacionais (Top) de Kentropyx calcarata das quatro localidades

amostradas. São apresentados o tamanho de cada amostra (n) e as estimativas da

média/variância (var) e entre parênteses os valores mínimo e máximo para cada

localidade..................................................................................................................................54

Tabela 02: Coeficientes obtidos com Generalized Linear Model (GLM). São apresentados os

parâmetros do modelo: horas de restrição acumuladas (Total_hr), horas de atividade

(Total_ha) e precipitação (Total_prec). Também são apresentados os termos quadráticos:

precipitação -sqprec (Total_prec^2), horas de restrição -sqhr (Total_hr^2) e as interações

entre precipitação e horas de restrição -Prechr (Total_prec x Total_hr) e precipitação e horas

de atividade -Precha (Total_prec x Total_ha). ........................................................................55

Tabela 03: Coeficientes obtidos com Generalized Linear Model (GLM). São apresentados os

parâmetros do modelo: horas de restrição acumuladas (Total_hr), horas de atividade

(Total_ha) e precipitação (Total_prec). São apresentados os termos quadráticos: precipitação -

sqprec (Total_prec^2), horas de restrição -sqhr (Total_hr^2) e as interações entre precipitação

e horas de restrição -Prechr (Total_prec x Total_hr), precipitação e horas de atividade -Precha

(Total_prec x Total_ha) e índice de vegetação (Forest Layer). Também são apresentados os

valores de graus de liberdade (edf / Ref.df) e qui-quadrado (Chi.sq)................................56

Tabela 04: Estimativas de riscos de extinção de Kentropyx calcarata para Unidades de

Conservação e Terras Indígenas da Amazônia (TI’s). Os valores para cada ano representam as

probabilidades de não ocorrência da espécie devido a redução de áreas favoráveis, baseados

no cálculo de Hr usando a amplitude térmica de atividade registrada em

campo........................................................................................................................................57

Tabela 05: Resultados das modelagens de curvas de desempenho térmico para indivíduos de

Kentropyx calcarata de quatro localidades. São mostradas as estatísticas do efeito da

temperatura e do CRC no desempenho (Temperatura-Temp e comprimento rostro-cloacal-

CRC, respectivamente) e valor de r2 do modelo, além das estimativas de temperatura ótima

para o desempenho (Totima) e da amplitude térmica na qual é possível pelo menos 80% do

desempenho máximo do indivíduo..........................................................................................58

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LISTA DE FIGURAS

Figura 01: Kentropyx calcarata fotografado em Ribeirão Cascalheira, Mato Grosso, Brasil.

Foto de G. R. Colli. …………………................ .....................................................................59

Figura 02: Áreas estudadas e pontos de distribuição geográfica de Kentropyx calcarata

usados para a modelagem de riscos de extinção entre quatro sub-regiões. Os limites

geográficos usados para sub-selecionar pontos de amostragem foram baseadas na distribuição

de linhagens intra-específicas de Kentropyx calcarata inferidas a partir de Cronemberger

(2015) como segue: círculos verdes referem-se à sub-região do Amazonas, que corresponde

ao Estado Amazonas (AM) ao norte do Rio Amazonas estendendo-se até Roraima (RR);

círculos amarelos referem-se à sub-região do Amapá que corresponde ao Estado Amapá (AP);

círculos brancos referem-se à sub-região do Tocantins, que corresponde a pontos de

amostragem no Estado do Tocantins (TO) e se estende até Maranhão (MA) e leste do Pará

(PA); círculos azuis referem-se à sub-região do Pará que corresponde a pontos de amostragem

no Estado do Pará, interflúvio dos Rios Xingu (oeste), Araguaia (leste) e Rio Amazonas

(norte). Estrelas vermelhas representam os pontos de amostragem de dados ecofisiológicos

para K. calcarata, como segue: 1 - Florestal Nacional do Amapá, Amapá; 2 - Floresta

Nacional de Caxiuanã, Pará; 3 - Reserva Florestal Adolpho Ducke, Amazonas; e 4 - Estação

de Pesquisa Canguçu, Tocantins...............................................................................................60

Figura 03: Estimativas de ocorrência de Kentropyx calcarata para as sub-regiões estudadas,

baseadas na adequabilidade do hábitat à espécie para o presente e anos de 2050 e 2070 . A

escala de cor indica um gradiente de áreas favoráveis a ocorrência da espécie, que varia de

azul (1.0): áreas adequadas a vermelho (0.0) áreas inadequadas. Os pontos pretos referem-se a

ocorrência atual de K. calcarata na região...............................................................................61

Figura 04: Frequência absoluta de sítios com riscos de extinção de Kentropyx calcarata para

cada período na região Amazônica............................................................................................62

Figura 07: Relação entre máxima temperatura operacional (TEMAX) e limite térmico máximo

(CTMAX) de K. calcarata estimado em laboratório para as quatro localidades

amostradas.................................................................................................................................63

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LISTA DE APÊNDICES

APÊNDICE I: Mapa de altitude da região estudada e pontos de distribuição geográfica de

Kentropyx calcarata usados para a modelagem de riscos de extinção. As siglas se referem aos

estados do Amazonas (AM), Roraima (RR), Amapá (AP), Tocantins (TO), Maranhão (MA) e

Pará (PA). Estrelas vermelhas representam os sítios de amostragem de dados ecofisiológicos

para K. calcarata e as setas verdes indicam as áreas de maior altitude com ocorrência atual de

K. calcarata...............................................................................................................................64

APÊNDICE II: Temperaturas preferidas (Tpref) por indivíduos de Kentropyx calcarata das

quatro localidades amostradas. As linhas horizontais grossas representam medianas, as caixas

contém 50% dos valores dos dados e as linha horizontais finas indicam os valores máximos e

mínimos de temperatura preferida pelos indivíduos........ ........................................................65

APÊNDICE III: Curvas de desempenho térmico mostrando os efeitos da temperatura

corporal (oC) no desempenho locomotor (m/s - metros/segundo) de indivíduos de Kentropyx

calcarata de quatro locais……................... .............................................................................66

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INTRODUÇÃO GERAL

A temperatura afeta muitos aspectos da ecologia, fisiologia e evolução animal

(Adolph & Porter, 1993). Organismos ectotérmicos, tais como lagartos, frequentemente

experimentam variações na temperatura corpórea durante a atividade que influenciam o

metabolismo e a fisiologia e, consequentemente, o sucesso das atividades de forrageio e

reprodução. Temperaturas ambientais podem, portanto, afetar muitos parâmetros

fisiológicos (Huey & Berrigan, 2001), de desempenho ecológico e reprodutivo em

ectotérmicos, tais como a velocidade de corrida, taxa metabólica, fecundidade e

sobrevivência (Angilletta, 2009).

O desempenho de qualquer atividade em ectotérmicos aumenta com a elevação

da temperatura até estabilizar-se em uma faixa de temperatura ótima para o

desempenho, na qual ele pode decair até o limite térmico mínimo-CTmin ou aumentar até

o denominado limite térmico máximo-CTmax (Angilletta, 2009). Com base nestas

características fisiológicas os lagartos podem ser classificados dentro de uma faixa

contínua de sensibilidade térmica para determinadas atividades, onde espécies cujo

desempenho ocorre apenas em uma estreita faixa de temperaturas são consideradas

termoespecialistas (muitas dessas são termoconformadoras), enquanto aquelas que

possuem desempenho adequado em um intervalo maior de temperaturas são

consideradas termogeneralistas (muitas dessas são heliotérmicas) (Angilletta, 2009).

Em ambientes onde existe variação térmica espacial qualquer organismo está

sujeito a processos biofísicos de troca de calor com o ambiente, como absorção de

radiação solar, transferência de calor com o fluido à sua volta por convecção e

transferência de calor por condução com o substrato (Pough et al., 2003). Os lagartos

podem regular a taxa dessas trocas energéticas por meio de estratégias comportamentais

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(Bauwens, 1996; Díaz & Cabezas-Díaz, 2004) ou fisiológicas (Seebacher & Franklin,

2005) e, como consequência, podem responder às variações ambientais e obter certo

controle sobre suas temperaturas corporais. A termorregulação pode ser um processo

relativamente preciso, dependendo dos custos e benefícios associados a outras

atividades ecológicas, como fuga de predadores, forrageamento e comportamento

reprodutivo (Huey & Slatkin, 1976).

Indivíduos podem responder às pressões seletivas locais, como o aumento da

temperatura, por meio de plasticidade fenotípica ou adaptação evolutiva (Hoffman &

Sgro, 2011). Mudanças climáticas estão ocorrendo em diferentes escalas espaciais

(IPCC 2014) e diversos efeitos sobre os organismos e a biodiversidade causados por

incrementos da temperatura têm sido registrados (Colwell et al., 2008; Both et al., 2009;

Sinervo et al., 2010). A vulnerabilidade das espécies depende de três fatores-chave: sua

sensibilidade metabólica, que pode ser medida através de estimativas de desempenho

locomotor ou digestivo, por exemplo (Angilletta, 2009); sua exposição à mudança de

temperatura, que pode ser medida através de estimativas do CTmax e CTmin; e de sua

resiliência às perturbações, para a qual a variabilidade de traços térmicos representa um

indicador do potencial de adaptação (Williams et al., 2008).

Ectotérmicos tropicais possuem a preferência térmica próxima do limite de

tolerância máxima (Sunday et al., 2010), de forma que sua amplitude de

termorregulação tende a ser mais estreita quando comparada aos ectotérmicos de

regiões temperadas (Huey et al., 2012) e o limite térmico máximo tende a ser mais

conservado entre espécies e linhagens de uma mesma espécie (Addo-Bediako et al.,

2000). Tais características, são apontadas por conferirem alta vulnerabilidade ao

aumento da temperatura, independente da escala avaliada (Parmesan 2006; Deutsch et

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al., 2008; Dillon et al., 2010; Huey et al., 2012). Assim, considera-se que as mudanças

climáticas em regiões tropicais poderão ter profundas consequências locais e globais,

uma vez que estas regiões concentram altos níveis da biodiversidade e produtividade

primária (Dillon et al., 2010).

A intensidade na qual o aumento de temperatura afetará os riscos de extinção

dos organismos dependerá da capacidade de migração, das estratégias comportamentais

e fisiológicas de aclimatização e da evolução das tolerâncias fisiológicas (Hoffmann &

Sgro 2011). Considerando a magnitude das mudanças climáticas e a fisiologia dos

organismos, o aquecimento pode ter impactos diferentes entre táxons, podendo

beneficiar algumas linhagens (Chamaille-Jammes et al., 2006; Gunderson & Leal, 2012;

Logan et al., 2014) e levar outras à extinção (Sinervo et al., 2010). Portanto, predizer os

impactos do aumento de temperatura depende de estimativas da flexibilidade de

características térmicas, que podem variar de acordo com a especialização da linhagem

e características ambientais (Hoffmann & Sgro, 2011).

Para entender a resposta de ectotérmicos a aumentos de temperatura local, é

essencial estimar a variação geografíca de traços da fisiologia dentro de espécies para

acessar como a vulnerabilidade está espacialmente estruturada (Paranjpe et al., 2013).

No entanto, ectotérmicos tropicais permanecem como os organismos menos estudados

com relação aos traços fisiológicos (Huey et al. 2009) e os resultados encontrados

geralmente são conflitantes, sem que a estrutura espacial da variação de traços que

conferem vulnerabilidade possa ser definida com confiança.

Abordagens correlacionistas de modelagem descrevem o nicho das espécies

através de correlações entre dados climáticos macroespaciais e dados atuais de

distribuição, mas sem a possibilidade de extrapolação para microambientes devido à

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limitação do uso de estimativas de traços não diretamente tomadas das espécies e do seu

ambiente (Kearney & Porter, 2009). Abordagens mecanísticas mais modernas superam

tais limitações usando dados coletados a partir dos organismos para acessar a complexa

rede de inter-relações entre a fisiologia, o ambiente térmico, o comportamento e as

distribuições do organismo (Gunderson & Leal, 2012; Kearney & Porter, 2009). No

entanto a quantidade de estudos mecanísticos em escala refinada ainda é incipiente

(Lara-Rezendiz et al., 2013, Kubisch et al., 2016).

Nesse contexto, a compreensão da fisiologia térmica ao longo da distribuição

das espécies em escalas locais é essencial para determinar se as atuais mudanças

climáticas globais possuem o potencial de selecionar diferencialmente populações

adaptadas a temperaturas mais elevadas (Corlett, 2011), o que pode ser de particular

relevância dentro de uma região com organismos potencialmente mais vulneráveis ao

aumento de temperatura.

Sinervo e colaboradores (2010) reuniram dados de diversas espécies de lagartos

do mundo e mostraram que o aquecimento global pode reduzir as horas de atividade das

espécies, comprometendo sua busca por alimento e reprodução e, potencialmente,

causar extinções locais ou regionais. O principal fator limitante da abordagem utilizada

por Sinervo et al., (2010) foi a macroescala térmica ambiental utilizada para prever os

impactos do aumentos de temperatura sobre as espécies, pois tal abordagem não foi

refinada para acessar diferenças térmicas micrambientais que utilizam estimativas

diretamente tomadas das espécies e do ambiente no qual vivem.

Sinervo et al. (2010) acessaram a vulnerabilidade de 34 famílias de lagartos do

mundo utilizando as médias de temperatura corporal durante a atividade. Para muitas

espécies termonconformadoras, que possuem temperaturas corporais baixas e mais

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próximas da ambiental (Huey et al 2012), o valor médio como limitante da atividade

deve ser mais adequado do que para espécies heliotérmicas, pois estas geralmente

mantêm sua temperatua corporal bem acima da temperatura do ar e do substrato e

movimentam-se entre o sol e a sombra para evitar o aquecimento corporal. Lagartos

heliotérmicos possuem o potencial para evitar o superaquecimento através da

termorregulação comportamental (Kearney et al. 2009) e a temperatura máxima de

atividade registrada em campo, ao invés da média, deve refletir melhor o início da

restrição da atividade, representando um melhor preditor para acessar a vulnerabilidade

de heliotérmicos frente aos aumentos de temperatura.

Neste trabalho utilizei a amplitude térmica de atividade de Kentropyx calcarata

para modelar seus riscos de extinção e avaliei como a a variação da fisiologia térmica

entre distintas localidades na Amazônia e no ecótono Amazonia-Cerrado se relaciona à

persistência da espécie nos diferentes cenários de aumento de temperatura.

OBJETIVO GERAL

Avaliar como a fisiologia térmica de uma espécie de lagarto de ampla

distribuição em formações florestais da América do Sul (Kentropyx calcarata) é afetada

por diferentes ambientes térmicos onde ela está presente e como a combinação de traços

fisiológicos em cada local pode gerar vulnerabilidade e afetar os riscos de extinção que

estimamos para a maior parte da Amazônia e transição Amazônia-Cerrado.

OBJETIVOS ESPECÍFICOS

17

1 – Mensurar traços ecofisiológicos termais (preferência térmica, limites da tolerância

térmica, sensibilidade térmica do desempenho locomotor) de indivíduos de Kentropyx

calcarata e temperaturas ambientais operacionais e a extensão em que estes variam

entre quatro localidades na Amazônia e no ecótono Cerrado-Amazônia.

2 – Estimar os riscos de extinção de Kentropyx calcarata em cenários de mudanças

climáticas globais

18

Capítulo 1

Pontes-da-Silva E, Magnusson WE, Sinervo BR, Oliveira GC, Miles DV, Colli GR,

Antunes JF, Santos JC & Werneck FP. Extinction risks forced by climatic change and

intraspecific variation in the thermal physiology of a tropical lizard. Manuscrito

formatado para a revista Functional Ecology.

19

Extinction risks forced by climatic change and intraspecific 1

variation in the thermal physiology of a tropical lizard 2

3

Emerson Pontes-da-Silva*a

, William E. Magnussona, Barry R. Sinervo

b, 4

Gabriel C. de Oliveirab, Donald B. Miles

c, Guarino R. Colli

d, Jessica 5

Fenkere, Juan C. Santos

f and Fernanda P. Werneck

a 6

7

a Coordenação de Biodiversidade, Instituto Nacional de Pesquisas da Amazônia, 8

Manaus, Brazil 9

b Department of Ecology & Evolutionary Biology, University of California, Santa Cruz, 10

United States 11

c Department of Biological Sciences, Ohio University, Athens, Ohio, United States 12

d Department of Zoology, University of Brasília, Brasília, Brazil 13

e Division of Evolution, Ecology and Genetics, Australian National University, 14

Canberra, Australia 15

f Biology Department, Brigham Young University, Utah, United States 16

17

Running headline: extinction risks of a tropical lizard 18

19

* Corresponding author: [email protected] 20

21

22

mailto:[email protected]

20

23

Summary 24

1. Temperature increases can impact biodiversity and predicting their effects is one 25

of the main challenges facing global climate change research. Ectotherms are 26

sensitive to temperature change and, although predictions indicate that tropical 27

species are highly vulnerable to global warming, they remain one of the groups 28

least studied with respect to local extinction risk and the extent of physiological 29

variation. 30

2. Here, we model the extinction risks of a tropical heliothermic teiid lizard 31

(Kentropyx calcarata) based on eco-physiological traits and contemporary 32

species distributions (occupancy) for specific intraspecific evolutionary lineages. 33

Our model represents an update of methods used in the recent physiological-34

behavioral models of lizard vulnerability to extinction. We also investigated how 35

thermal biology traits vary throughout the species geographic ranges and the 36

consequences of such variation for lineage vulnerability. 37

3. We investigated the thermo-physiological profile of K. calcarata by measuring 38

preferred temperatures, critical limits, operative model temperatures, and 39

locomotor performance sensitivity for the species in four sites in the Amazon 40

rainforest and in the ecotone between the Amazon and savannah in the Cerrado 41

biome. We forecast the relative extinction risk for K. calcarata in four regions 42

for the years 2050 and 2070, based on thermal adequacy predicted for each 43

region and a dense geographic database of the species known occurrences. 44

4. We show substantial variation in thermal tolerance of individuals among 45

thermally distinct sites, such as in the Amazon and in the Amazon-Cerrado 46

21

ecotone. Thermal critical limits were highly correlated with operative 47

environmental temperatures. As individuals from different localities show 48

distinct degrees of variability in the thermal tolerance, the strength of natural 49

selection in response to climate change is likely to vary geographically. 50

5. Our physiological model predicted 2.6% to 52.4% relative extinction risks for 51

clades of K. calcarata for 2050, while for 2070, extinction risks ranged from 52

8.0% to 66.8%. Individuals from forested Amazon areas are anticipated to 53

experience a reduction in suitable habitat. However, our laboratory studies 54

revealed large thermophysiological differences among individuals from the same 55

site and from different sites that suggest local adaptation and may allow greater 56

persistence for tropical ectotherm in a global warming scenario. 57

58

Key-words Ecophysiology, local extinction, global warming, Amazon, lizard 59

60

22

Introduction 61

Climate change is occurring at different spatial scales (IPCC 2014), and various 62

effects on organisms caused by rising temperature have been recorded (Colwell et al. 63

2008; Both et al 2009; Sinervo et al. 2010).Several studies suggest that tropical 64

ectotherms are more vulnerable to rising temperatures than species further from the 65

equator (e.g., Parmesan 2006; Deutsch et al. 2008; Dillon, Wang & Huey 2010; Sinervo 66

et al. 2010; Huey et al. 2012). Thus, climate change in tropical regions is expected to 67

induce a decrease in biodiversity, because these regions support the highest levels of 68

biodiversity (Dillon et al. 2010). 69

Current species distribution models (SDMs) largely describe the environmental 70

niches of the focal species through correlations between climatic factors and 71

distributional data, without incorporating species-specific ecophysiological predictors 72

(e.g., body and operative environmental temperatures) in the modeling (Kearney & 73

Porter 2009). However, such SDMs may be limited because they are not based on traits 74

measured directly from the physiology of species. In contrast, mechanistic SDMs might 75

overcome these drawbacks by using physiological data to portrait the complexity of 76

interrelationships between organismal physiology, microclimate, behavior and 77

geographic distribution (Gunderson & Leal 2012). 78

Local declines in lizard diversity associated with global temperature increases 79

were reported by Sinervo et al. (2010) and these were associated with global 80

temperature increases. These environmental disturbances likely caused changes in 81

thermal niches by reducing hours of activity (Ha) and increasing restriction (i.e., Hr or 82

the total number of daylight hours in which environmental temperatures above or below 83

critical limits restrict lizard activity). Models estimating extinction risks on a global 84

23

scale indicated that by 2070, >39% of local populations of ~20% of lizard species could 85

become extinct. These predictions are especially alarming for large and biodiverse 86

areas, such as the Amazon, the Cerrado and their ecotone in South America; which are 87

expected to become high extinction risk regions for lizards (Sinervo et al. 2010). 88

Until recently, SDMs based on ecophysiology were premised on extinction risk 89

across lizards families, i.e., not individual species, and need further refinement and 90

validation with field data obtained in situ (Sinervo et al. 2010). Recent studies on lizards 91

have refined the estimation of extinction risk rates at local scales, considering the 92

interrelations between physiology and microclimate (e.g., Ceia-Hasse et al. 2014; Lara-93

Resendiz et al. 2015; Kubisch et al. 2015). However, few such analyses exist for lizard 94

species inhabiting tropical rainforests, which are vulnerable to the effects of global 95

warning (Huey et al. 2009). 96

Organisms of the same species at distinct locations are subject to variation in local 97

environmental conditions, which is particularly true for species widely distributed 98

across areas under different climatic regimes and selective pressures (Hoffmann & Sgro 99

2011). Geographic variation in physiological traits can reveal the spatial structure of 100

adaptive potential throughout species distributions (Moritz et al. 2012). For example, 101

differences in physiological traits can confer differences in vulnerability of populations 102

according to local habitat structure (Piantoni, Navas & Ibargüengoytía 2016). 103

Differences in physiological traits have been revealed between organisms from 104

temperate and tropical regions. For example, differences in locomotor performance at 105

different body temperatures between different populations within a clade were detected 106

in skinks in Australia (Moritz et al. 2012) and Anoles populations in the Bahamas 107

(Logan, Cox & Calsbeek 2014). However, differences in performance were not found in 108

24

A. cristatellus, which is a close relative of A. sagrei, on Puerto Rican islands 109

(Gunderson & Leal 2012). Body temperature can vary with sex, ontogeny, and climate 110

seasonality, as well as between individuals at distinct locations (e.g.,Van Damme, 111

Bauwens & Verheyen 1986; Van Damme, Bauwens & Verheyen 1987; Gunderson & 112

Leal 2012). Clusella-Trullas, Blackburn & Chown (2011) suggested that differences in 113

preferred temperature (measured in the laboratory as a proxy for body temperature in 114

nature) may be more related to other climatic variables, such as variation in 115

environmental temperature and precipitation, than to mean temperature. 116

Critical thermal limits (CTmin and CTmax) are considered key predictors of 117

ectotherm physiological sensitivity, and differences in both traits have been used to 118

investigate physiological patterns relative to temperature and precipitation (e.g., 119

Clusella-Trullas et al. 2011), latitude (e.g., Addo-Bediako, Chown & Gaston 2000; 120

Araujo et al. 2013), and habitat (e.g., terrestrial versus marine; Sunday et al. 2011). 121

Likewise, critical thermal limits may vary intraspecifically (e.g., Moritz et al. 2012; 122

Logan et al. 2014), but the extent of their variation remains underexplored (Losos 123

2008). Uncovering intraspecific differences may help clarify whether critical thermal 124

limits are evolutionarily conserved or are evolutionarily labile (Pearman et al. 2008). 125

The upper temperature limit is known to vary little and tends to be conserved among 126

populations (Moritz et al. 2012), and among ectotherm species (Addo-Bediako et al. 127

2000; Araujo et al. 2013). Thus, it is assumed that temperature increases will impose a 128

seletive pressure over a wide range of species and populations (Sunday et al. 2011). 129

The regional phylogenetic diversification of some tropical lineages has been 130

described and can be integrated with evolutionary-physiological studies (Moritz et al. 131

2012). Here, we aim to explore this using Kentropyx calcarata (Spix 1825), a whiptail 132

25

lizard (Squamata: Teiidae) widely distributed species in Brazil and the Guiana. 133

Individuals are found in forest environments near streams, natural clearings or forest 134

edges with open areas (Vitt1991; Avila-Pires 1995). The species has a relatively well 135

known phylogeographic history (Werneck et al. 2009; Avila-Pires et al. 2012; 136

Cronenberg 2015). Given this species distribution and the conservative nature of 137

thermal traits typical of tropical ectotherms (Deutsch et al. 2008; Huey et al. 2009) , K. 138

calcarata is assumed to be more sensitive to climate change. However, narrower critical 139

limits for thermal traits may be more typical of K. calcarata (a forest heliotherm) and 140

tropical thermoconforming species than for open-habitat heliotherms. Most open-habitat 141

heliotherms may be thermal generalists and experience a wide variety of thermal 142

environments, and this may explain their wide geographic distributions (Bonino et al. 143

2015). The use of Kentropyx calcarata thermal microhabitat contrasts with those of 144

heliotherms of open areas and thermoconformers (Vitt et al. 1991; Vitt et al. 1997). 145

Thus, K. calcarata belongs to an under-explored group in relation to its thermal 146

biology. 147

Most teiid lizards are heliotherms that maintain body temperature above 148

environmental temperature during activity and avoid heat stress by shuttling between 149

the sun and shade (e.g., Sartorius et al. 1999). Behavioral thermoregulationmay buffer 150

lizards from thermal-warming impacts (Kearney & Porter 2009), and estimates of mean 151

field or laboratory body temperatures may not be suitable to estimate restriction in 152

activity times for heliothermic lizards. For these species, the the voluntary thermal 153

maximum (VTM) for activity is probably a better threshold to indicate activity 154

limitation. 155

26

Here we estimate relative extinction risks for K. calcarata in large sub-regions 156

within the Brazilian Amazon and the Cerrado-Amazon ecotone occupied by four major 157

clades recognized by Cronemberg (2015), based on the calculation of thermally 158

imposed hours of restriction, alone and in interaction with rainfall and vegetation cover. 159

We also investigate how the thermal biology of K. calcarata is affected by different 160

thermal environments to predict how differences in thermal biology might affect 161

differences in vulnerability of populations from different regions. 162

163

Materials and methods 164

Study area 165

We sampled four localities within the wide distribution of K. calcarata (Fig 1), 166

which are in regions occupied by different clades, based on a recent phylogeographic 167

studies of the species (Avila-Pires et al. 2012; Cronenberg 2015). Specimen collection 168

and experiments were done in September 2014 and between July and October 2015. 169

These months correspond to the dry season in all collection and experiment locations in 170

the Brazilian Amazon:1 – Floresta Nacional (FLONA) de Caxiuanã (1°44’.199” S; 171

51°27’.207” W; elevation 28m), Melgaço/Portel, Pará State, where the mean annual 172

temperature is 25.7 °C; 2 – Área de Proteção Ambiental (APA) Adolpho Ducke 173

(2°55’.458” S; 59°58’

.23” W; elevation 68m), Manaus, Amazonas State, where the 174

mean annual temperature is 26.0 °C; 3 – Floresta Nacional (FLONA) do Amapá 175

(0.05°51’.42” S; 51°11’ W; elevation 14.4m), Amapá State, with a mean annual 176

temperature of 25.5 °C; and the Cerrado-Amazon ecotone: 4 – Centro de Pesquisas 177

Canguçu (9°97’.721” S; -50°03’

.325”; elevation 150m), Pium, Tocantins State, with an 178

annual mean temperature of 26.9 °C (Fig. 2). 179

27

At each sampling site, individuals were captured by active search, nooses, pitfall-180

traps and funnel-traps. Each lizard was housed individually in containers measuring 181

22.5 cm x 15.0 cm x 8.0 cm (L x W x H) at room temperature (approximately 25-30°C) 182

and provided with water ad libitum until the experiments were performed on the same 183

day of collection in a nearby field lab. 184

We restricted extinction-risk modeling to distribution records from areas adjacent 185

to where physiological data were collected and within areas occupied by four structured 186

intraspecific clades defined on mitochondrial and nuclear data (Cronenberg 2015). For 187

the Tocantins sub-region, we considered geographic points east of the Araguaia River, 188

except for disjunct records on the east coast; for the Amazonas sub-region we 189

considered geographic records in the area around Manaus extending to Boa Vista 190

(Roraima) and south of Pantepui; for the Pará sub-region we considered geographic 191

records in the interfluves of the Xingu River (west), Araguaia (east) and Amazonas 192

(north) Rivers; and for the sub-region of Amapá we considered geographic records of 193

the entire Amapá State (Fig. 2). 194

Geographic (SDM-input) data were assembled that included a total of 2,013 195

points distributed as follows between sub-regions: Pará (416), Amazonas (82), Amapá 196

(449) and Tocantins (1066).When points were separated by 1 km or less from the next 197

point (defined as one locality; Sinervo et al. 2010), only one was used. Geographic 198

records were made available by various sources such as online databases (American 199

Museum of Natural History (USA) - http://www.amnh.org), Scientific Collections and 200

Museums records, and other references listed in the acknowledgments. 201

Although localities had similar mean annual temperatures, the three Amazon 202

sampling localities are covered by rainforests, have high mean annual precipitation 203

28

(2.200 mm, 2.272 mm and 2.300 mm for AM, PA and AP, respectively) and low annual 204

temperature range (approx. 2 °C difference between the coldest and hottest months). 205

The Cerrado-Amazon ecotone sampling locality is characterized by transitional forest, 206

where many trees are seasonally deciduous (Marimon et al. 2006; Mews, Marimon & 207

Ratter. 2012), with mean annual rainfall of 1.760 mm and a more variable climate, with 208

an annual temperature range of approximately 6 °C (INMET 2016). 209

Collected individuals and tissue samples were deposited at the following 210

institutions: Coleção Herpetológica da Universidade de Brasília (Tocantins samples), 211

Coleção de Anfíbios e Répteis do Instituto Nacional de Pesquisas da Amazônia 212

(Amazonas and Pará samples), and Coleção Herpetológica do Museu Paraense Emílio 213

Goeldi (Pará and Amapá samples). All protocols involving live animals were approved 214

by the Comissão de Ética no Uso de Animais na Pesquisa of the Instituto Nacional de 215

Pesquisas da Amazônia (INPA) (Code: 029/2014). 216

217

Operative temperatures and extinction-risk modeling 218

To explore the natural thermal environment (i.e., microclimate) of K. calcarata 219

individuals in each location, we recorded local operative (Te) and air (Tair) temperatures. 220

Furthermore, laboratory data collection occurred simultaneously with operative 221

temperature recording in all locations (Tocantins: August 31-16 September 2014, Pará: 222

14-30 June 2015, Amazonas:14-29 July 2015, Amapá:05-17 September 2015). For this 223

purpose, we used automatic temperature dataloggers (HOBO ™ Onset Pro V2) 224

connected to a polyvinyl chloride (PVC) tube simulating adult K. calcarata in size and 225

shape (3 cm in diameter, 14 cm long). We also used dataloggers unconnected to models 226

to record air temperatures. Each temperature datalogger had two probes, each inserted in 227

29

at different ends of each model tube. We placed temperature recorders in microhabitats 228

most likely occupied by lizards (natural clearings, edges of the forest and stream 229

borders), always with a probe in the shade covered with leaves and the other placed in a 230

position exposed to sunlight (Sinervo et al.2010). Temperature was recorded every two 231

minutes throughout the field period. We also considered the temperature recorded by 232

the probes to represent the operative temperature (Te) of K. calcarata in each sampling 233

locality. We selected only temperature records within the time period when the species 234

is active, based on the time of the first and the last sighting in the field (07:00 h and 235

16:00 h). 236

We estimated the activity hours (Ha) as the time that lizards are outside their 237

shelters in activity and the restriction hours (Hr) as time that lizard activity would be 238

limited due to temperatures above or below their thermal limits (Sinervo et al. 2010). 239

For field data, the lower thermal limit (Tlower), i.e., the lowest air temperature at which 240

the species was found active, was used to calculate Ha. We considered the estimated 241

Tlower as the lowest body temperature for individual seen active. Therefore, air 242

temperature can only be a surrogate for insolation at the beginning of the activity 243

period. The upper limit (Tupper) was the highest body temperature at which the species 244

was found voluntarily active and it was used to calculate Ha. As lizards usually do not 245

use evaporative cooling to any large degree, we assume that they would not be able to 246

maintain body temperatures within their preferred range when air temperatures are 247

higher than the upper limit (Tupper). 248

We used the lowest air temperature at which activity was recorded in the field and 249

the highest body temperature recorded in the field as the upper and lower temperature 250

bounds. Considering that this thermal activity breadth is similar for several Amazonian 251

30

locations where K. calcarata occurs, we calculated the activity hours based on mean 252

temperature breadth: 26.9 - 40.2 °C for all the locations studied (collected data from 253

Gasnier et al. 1994; Vitt 1991; Vitt et al. 1997). Therefore, the daily activity hours were 254

considered as those when Tair was higher than 26.9 °C and lower than 40.2 °C for the all 255

sub-regions. 256

We model the interaction of biophysical variables and traits through a function for 257

hours of restriction, Hr, during the peak breeding season and hours of potential activity, 258

Ha, during the entire year. For ectotherms, hours of restriction (Hr) is a crucial constraint 259

during the breeding season, as it limits reproductive output (Sinervo et al. 2010). 260

Outside of the breeding period, ectotherms use behavioral and physiological 261

mechanisms to escape excessive cold (brumation in winter), heat, or drought (estivation 262

during warm or dry periods), so ignoring Hr during these times, accounts for such 263

strategies. 264

265

(Eq. 1) – adapted from Sinervo et al. 2010 266

267

Net hours of activity is thus the difference between Ha (h,t) and Hr (h,t) across the 268

same seasonal time period. However, as noted above, Hr may be most relevant during 269

the breeding season, while Ha is most important across the entire activity season. 270

Accordingly, we keep Ha and Hr as separate functions in our models. 271

For many ectotherms specialized for shaded environments, referred to as 272

thermoconformers, Te can be estimated from daily excursions in Tair,m (lowest air 273

temperature) into Tair,max (highest air temperature) with a sinusoidal function. However, 274

Kentropyx calcarata is often found concentrated around forests clearings where a tree-275

31

fall event has opened up the habitat and it can be seen basking to raise its temperature in 276

the clearings during the day but then moving into the forest and slowly cooling down to 277

ambient temperatures, only to return to bask. Sinervo et al. (2010) considered the 278

dichotomy between heliothermy and thermoconforming modes of regulation to be strict. 279

Here we illustrate a model that considers a forest heliothermic, which can have its 280

frequency of shuttling to the sun reduced when air temperatures are higher, thus 281

effectively giving the species less activity restriction as it spends a smaller proportion of 282

the time basking. 283

The equations for Hr and Ha of a heliotherm can be estimated from the measured 284

Te data according to a Richard’s Growth equation, which well captures the interaction 285

of T(air,max)–Tupper on Hr and Ha. These values must be computed from deployed 286

operative environmental temperature models designed to mimic the thermal properties 287

of the studied species (Bakken 1992). 288

To quantify how reptile activity relates empirically to local environmental 289

temperatures, we used sigmoidal curves (Richard's four parameter growth curve) to map 290

Ha or Hr onto daily maximum air temperature (Tair,max –Tupper) from a nearby 291

meteorological station. The calculations were computed on a daily basis. Following 292

Sinervo et al. (2010), we use this relationship to predict Ha and Hr at any site from 293

Ti,air,max (i=month) at a nearby weather station, or from a single cell in a climate surface, 294

even where Te data are unavailable. Specifically, we used the sigmoidal curve to 295

compute the cumulative hours of activity during the entire adult activity season, over 296

months, [N.B. the integration of Te models to compute Ha and Hr is built into data 297

analysis step]: 298

299

32


301

We used the same approach to compute cumulative “hours of restriction,” Hr, 302

during each month and then averaged across the number of months of the breeding 303

season (NBreed), given T(i,max) for each sample period: 304

305


307

Here, we develop a modified model of the two thermoregulatory modes in the 308

case where a species evolves to local conditions across a wide geographic region. In the 309

southern part of the range, K. calcarata is found in the Cerrado–Amazon ecotone, with 310

more openings in the forest than in the northern parts of its range. While it is still only 311

abundant in true Amazonian forest ecosystems, it has more thermoregulatory 312

opportunities in the south, compared to the Amazonian forest environments to the north. 313

Accordingly, we used another structural habitat feature, the presence or absence of 314

Amazonian forest, as an index of the macroscale habitat structure, which K. calcarata 315

might evolve, to become locally adapted. We also computed Hr and Ha, using a 316

combination of equations for thermoconforming modes (based on simple sinusoidal 317

relationships) and the equations derived from operative environmental temperature 318

models deployed in various thermal habitats in which the various clades of K. calcarata 319

are found. 320

The modified Hr and Ha equations can be computed across the landscape of sites 321

as a simple proportion of the mixture of Amazonian versus non-Amazonian forest 322

environments, in which the distribution of species occurrences is found. 323

33

To forecast future favorable areas for the occurrence of Kentropyx calcarata, we 324

used RCP 4.5 from the Representative Concentration Pathways (RCP) database. We 325

used the temperature values (Tair,max and Tair,min) to assess how Ha and Hr will be 326

affected. RCPs are the different scenarios of emission and concentration of greenhouse 327

gases by 2100, which are based on the set of all available information on climate 328

predictions in the literature (reviewed by van Vuuren et al. 2011).The RPCs are 329

categorized into four different scenarios in an optimistic scale of emissions mitigation 330

(RCP 2.6) to a less optimistic scenario with higher emissions (RCP 8.5). We selected 331

RCP 4.5 which represents an intermediate stage of relative stabilization of emissions by 332

2100. 333

Using the R Programming Environment, we calculated the relative proportion of 334

the current species distribution where Ha and Hr values were favorable to the occurrence 335

of K. calcarata for the years 2050 and 2070. The favorability for occurrence in an area 336

(proxy of habitat suitability) is represented by the occupancy index, and the percentage 337

of extinction risk is calculated by comparing the present with future occupancy 338

index.(Sinervo et al. 2010). In each of the four sub-regions, we compared occupancy 339

index based on K. calcarata distribution points from three data sets of interest: 1 – 340

points within the sub-region where physiological data was collected (physiological 341

populations); 2 - points within the largest integral protection conservation units and 342

indigenous lands in each major sub-region (protected areas), which under a scenario of 343

temperature rise may be useful as future potential refuges for the species; and 3 – points 344

randomly selected from all the sub-regions together (n = 150). 345

346

Estimation of thermal traits 347

34

Preferred temperature (Tpref) 348

The preferred temperature of individual lizards was estimated in a thermal 349

gradient that measured 2.0 m x 0.3 m x 0.65 m (L x W x H).The gradient was divided 350

into lanes, where an individual was placed. A heat lamp was placed at one end of the 351

lane to maintain a substrate temperature of 48 °C simulating direct daylight, while gel 352

ice packs and a fan kept the other end of the lane at an approximate temperature of 21 353

°C, which simulated a natural shaded microenvironment. 354

We measured the initial body temperature of individuals before placing them in 355

the lane for the performance experiment. Body temperature was measured with an 356

infrared laser thermometer (Digitech QM7221) at a distance of

35

intervals the loss of motor motion and individual body temperature with a cloacal 371

thermometer (Miller & Weber 4K8893). 372

To estimate CTmin, lizards were isolated in styrofoam boxes with gel ice packs. To 373

estimate CTmax, lizards were directly exposed to sunlight or to bottles containing heated 374

water placed in styrofoam boxes. To represent the critical thermal limit, we used the 375

body temperature at which the individual did not move after being turned belly 376

up(Clobert et al 2000). 377

378

Sensitivity of Thermal Performance 379

We measured individuals’ ability to sustain physical activity to simulate natural 380

activity conditions where mobility is required for territorial defense, escape from 381

predators or foraging (Miles 1994; Robson & Miles 2000). Lizards were manually 382

stimulated to run in a circular track (Clobert et al. 2000) made of metal with an inner 383

compartment diameter of 60 cm and an external compartment diameter of 150 cm and 384

25 cm width, which was placed on a substrate with soil from each collection site in 385

order to mimic natural conditions. The time (s) and distance (m) of individual 386

locomotion until fatigue and motor-response loss were used as performance estimates 387

(Clobert et al. 2000). 388

Each individual was acclimated to run at seven different body temperatures (15 389

°C, 20 °C, 25 °C, 30 °C, 35 °C, 40 °C and 43 °C) in a randomized sequence. The test 390

started when the individual’s body temperature was within 0.5 °C of the target 391

temperature. Lizards had a rest interval of 4 h between each race at a new temperature. 392

Within individuals, running temperatures were given in a random sequence. The 393

substrate temperature of the track was adjusted to each running body temperature 394

36

through intercalation of track site in shadow or sun. The optimum performance 395

temperature (Topt) was estimated based on the body temperature at which each 396

individual ran fastest (Huey & Stevenson 1979). 397

398

Data analysis 399

We compared the thermal biology among localities using either an analysis of 400

variance (ANOVA) or Kruskal-Wallis tests. When significant (P < 0.05) differences 401

were found in mean trait values among sites, we used the Tukey post hoc test to identify 402

pairwise differences. The shapes of thermal performance curves (TPC's) of individuals 403

from each site were estimated and plotted using generalized additive mixed models 404

(GAMM) (Zajitschek et al. 2012), using the function "gamm" in the package mgcv 405

(Woods 2006) and ggplot2 (Wickham 2009). Because size may influence locomotor 406

performance, we included snout-to-vent length (SVL) as a covariate.To compute the 407

curve, mean CTmax and CTmin values of individuals from each location were given a 408

performance value of 0. The breadth of optimum performance was estimated asthe 409

range of body temperatures at which lizards attained 80% (B80) of maximum 410

performance, by multiplying the maximum performance speed at the best temperature 411

(Topt) by 0.8 (Huey & Stevenson 1979). Statistical analyses were performed with R (R 412

Development Core Team 2014). 413

414

Results 415

Operative temperature, occupancy index and extinction risks 416

The estimated operative temperatures for K. calcarata differed significantly between 417

sampling sites (F(3,13) = 91, P = 0.0001).At the Tocantins site, lizards had higher mean 418

37

Te and an amplitude 93% higher than in other locations (Table 1). At Amapá and 419

Amazonas sites, lizards had the lowest Te (7.5 ° C lower than TO) and were more 420

thermally homogeneous. Te at Pará was higher and also had greater variability than in 421

other Amazonian sites (Table 1). 422

While all ecophysiological traits (Hr, Ha and precipitation) were significant 423

explanatory variables in our SDM, along with most of their interaction effects and 424

quadratic terms, historical Amazon forest cover did not contribute significantly, nor did 425

its interactions (Tables 2 and 3). 426

The occupancy index in the present (Fig.3a) for the Tocantins sub-region was of 427

42.3 %, 63.8% for the Amapá sub-region, 69.4%for the Amazonas sub-region 428

and65.6%for the Pará sub-region. The extinction risk for 2050 (Fig. 3b) for the Pará 429

sub-region was 5.2%, 16.7% for the Tocantins sub-region, 22.3%for the Amazonas sub-430

region and 37.2%for the Amapá sub-region. The extinction risk for 2070 (Fig. 3c) for 431

the Pará sub-region was of 8.0%, 19.4% for the Tocantins sub-region, 21.2%for the 432

Amazonas sub-region and 45.6% for the Amapá sub-region. 433

Similar extinction risk values to those for the sub-regions were estimated for K. 434

calcarata in larger conservation units in each sub-region (Table 4). Also, similar 435

extinction risk values to those for the sub-regions were observed for the 150 sites in 436

which the species is known to occur across all four sub-regions (Fig. 4 and Appendix I). 437

438

Preferred temperatures and thermal tolerances 439

Individuals of K. calcarata from different sampling locations exhibited significant 440

differences in Tpref (F(3,94) = 123 , P

38

(AM: 31.3 ± 2.8 °C; PA: 30.4 ± 2.6 °C and AP: 29.9 ± 2.2 °C). The remaining three 443

populations exhibited no significant differeince in Tpref (Table 1). 444

No significant differences were found in mean thermal tolerance range among the 445

sampling locations, although there was a trend for differences in minimum temperature 446

(CTmin) among locations (CTmin, P = 0.08; CTmax, P = 0.3; Amptol, P = 0.5). Amapá 447

individuals had the lowest CTmin (6.2 °C difference from PA individuals, which 448

presented the highest CTmin). Variances of minimum and maximum critical limits were 449

significantly different between locations (Levene test, CTmin, F(3,26) = 3.2, P = 0.03; 450

CTmax, F(3,27) = 3.6, P = 0.02). Pará (CTmin,14.0 ± 6.4 °C; CTmax, 41.4 ± 3.3 °C), 451

Amazonas (CTmin,11.1 ± 3.0 °C; CTmax, 40.7 ± 6.1 °C), and Amapá (CTmin, 8 ± 5.2 °C; 452

CTmax, 39.8 ± 3.5 °C) individuals were similar to each other, showing greater variability 453

in thermal tolerance estimates than Tocantins individuals (CTmin,12.8 ± 1.1 °C; CTmax, 454

43.1 ± 0.8 °C) which were 99.96% and 99.97% less variable than other populations in 455

CTmax and CTmin, respectively(Table 1). 456

There was no significant relationship between mean operative temperature or 457

maximum operative temperature (Te,max) and Tpref, Topt, or the upper temperature limit 458

for 80% of maximum performance measured in the laboratory (P ≥ 0.3 in all cases). 459

However, there was a strong positive relationship (Fig.5) between maximum operative 460

temperatures (Te,max) and critical thermal maximum (CTmax) measured in the laboratory 461

(CTmax = 37± 0.1*Te,max, F(3,45) = 37.1, P = 0.02). 462

463

Thermal sensitivity of locomotor performance 464

Body temperatures significantly affected individual performance at all sampling 465

locations (AM: F value = 31.6, P =

39

0.2; AP: F value = 5.2, P = 0.0003, r2 = 0 .08 and TO: F value = 34.2, P = 0.0001, r

2= 467

0.5) with reduced performance at higher temperatures. We detected a significant effect 468

(P =

40

change in a mega-diverse region. We also present an updated model to calculate 491

extinction risks based on highest body temperatures recorded in the field instead of 492

preferred body temperatures estimated in laboratory, which can serve as a baseline for 493

future studies with forest helioterms. 494

While Sinervo et al. (2010) predicted an extinction risk for teiids of 13.6% by 495

2050 and 21% by 2080, our geographically and taxonomically more 496

refinedphysiological models that included more habitat variables in the SDMfor K. 497

calcarata predictedhigher relative extinction risks, with 29.1% for 2050 and 32.4% for 498

2070. A possible reason for the difference between the studies is that 30 out of the 36 499

heliotermic species Sinervo et al. (2010) considered for their predictions live in open 500

vegetation areas and deserts, and experience higher activity temperatures (mean body 501

activity temperatures = 38.6oC) than the few living in forest or aquatic environments 502

(mean body activity temperatures = 34.8oC). However, even using other species, the 503

model of Sinervo et al. (2010) should have had a greater relative extinction rate because 504

they used a narrower thermal tolerance. Our modeling suggests that heliothermic 505

lineages of Kentropyx calcarata living in densely forested environments (PA, AM, AP) 506

have lower thermal preferences than the lineage living in the Amazon-Cerrado ecotone, 507

and this elevates the risk of extinction. 508

In a similar approach, Kubisch et al. (2015) calculate the restriction hours for a 509

thermoconformer and predicted that 20% of Homonota darwinii populations could 510

become extinct by 2080, while Sinervo et al. (2010) predicted that the Phyllodactylidae 511

family as a whole would not suffer impacts due to climate change. Extinction risk 512

modeling by Kubisch et al. (2015) was conducted at the species level on a high latitude 513

species of Phyllodactylidae gecko, and thus, may represent a finer scale risk assessment. 514

41

Our SDM results suggest that the ecophysiological traits, as the thermal breadth 515

for activity, provide a useful explanation of the occurrence of K. calcarata in certain 516

locations of the Amazon. In addition, the significant effect of precipitation (alone and in 517

interaction with hours of restriction) suggests that a study of egg development and/or 518

adult water loss (Muth 1980), and the potential for climate change induced drought 519

(Westphal et al. 2016), might prove to be a fruitful avenue of research at a deeper 520

mechanistic level than we have done with our study of thermal ecophysiological traits 521

across the four clades of K. calcarata. 522

There was little relationship between mean or maximum operative temperatures 523

and most of the thermal traits we measured. This might be expected, because the cost 524

associated with different environments is mainly related to behavioral modifications 525

that might not strongly impact fitness. However, passing the critical thermal maximum 526

has a very strong immediate cost (death), so it is not surprising that it is related to the 527

maximum environmental temperature of the site. 528

Thermal traits appear to be, at least in part, determined by the environmental 529

temperatures at each site, as evidenced by the strong relationship between critical 530

thermal maximum and maximum operative temperatures. This indicates selection for 531

different thermal traits at different sites (Gunderson & Leal 2012; Moritz et al. 2012;, 532

Piantoni, Navas & Ibargüengoytía 2016). The variance in laboratory measures of 533

thermal critical limits was greater in some sites than others, especially those sites that 534

had low mean preferred temperatures. Therefore, adaptation to forested environments 535

with lower environmental temperatures does not appear to have resulted in narrow 536

amplitudes of thermal traits and loss of adaptive potential to climate changes. Huey et 537

al. (2012) and Deutsch et al. (2008) predicted that presumed narrow amplitudes of 538

42

thermal traits of tropical ectotherms would increase their vulnerability to climate 539

change, but we show that individuals of Kentropyx calcarata, although living in 540

thermally homogeneous environments, exhibit high variability in critical limits, which 541

may favor individuals with increased tolerance to changes in temperature under a 542

global-warming scenario. 543

Intrapopulational polymorphism tends to increase the niche amplitude (Weaver & 544

Hedrick 1991) in a way that thermal traits with greater variability may be favored by 545

natural selection caused by climate change (Logan et al. 2014). Thus, we suggest that 546

the potential adaptive amplitude will be greater in populations or areas whose 547

individuals exhibit greater variation in thermal tolerance. Populations of K. calcarata in 548

the Amazonian sites clearly show high flexibility in the thermal critical limits and, 549

therefore, may have higher potential adaptive amplitude. On the other hand, critical 550

limits were less variable in the population at the ecotone. This could be a result of 551

higher selection pressure at the ecotone, resulting in reduced variance in this phenotype. 552

Despite the lower variablility, under a scenario of climate warming, this could favor 553

these populations as Tpref was higher at the ecotone. 554

Most studies evaluating thermal biology considered the mean values of those 555

traits to evaluate differences between species, populations or locations. We found 556

geographic differences in thermal traits, such as critical limits and in variability values. 557

We suggest that future studies should pay closer attention to the variability of thermal 558

traits. Variability in responses to environmental conditions can be considered as a proxy 559

for the adaptive potential of natural populations (e.g., Logan et al. 2014) and, therefore, 560

of persistence in response to climate change (Hoffman & Sgro 2011). 561

43

Large areas of tropical forest have been predicted as potential refuges for 562

biodiversity with increasing temperatures (Kearney et al. 2009, Clusella-Trullas et al. 563

2011). Our estimates are of increased extinction risks in most regions, mainly with the 564

reduction of favorable areas for occurrence in lower altitude Amazon forest regions that 565

could contribute to local declines. However, even if the species goes extinct in some 566

areas, colonization processes facilitated by the large land connection that exists in the 567

Amazon region may lead to species persistence in the long term. 568

As it is a forest heliotherm, persistence of Kentropyx calcarata also depends on 569

forest preservation. However, the Amazon rainforest is currently under high 570

deforestation rates and some sub-regions are even more impacted, such southern Pará 571

State that has the second highest absolute deforestation rate of the Amazon (Fonseca et 572

al. 2015). It is also important to note that, in addition to extinction risks estimated for 573

the Tocantins sub-region, the Cerrado-Amazon ecotone is under intense anthropogenic 574

change characterized by intense change of natural landscapes for cattle ranching and 575

agriculture (Costa & Pires 2010; Coe et al. 2013). Combined effects of temperature 576

increases on a global scale and on a local scale as a result of landscape conversion are 577

factors that may further increase extinction risks of K. calcarata in these regions. 578

Our results show that Kentropyx calcarata thermal physiology varies 579

geographically and thermal maxima appear to be conditional on the thermal 580

environment of each populations of this species. We used an novel approach to model 581

extinctions risks for intraespecific lineages of a tropical heliothermic lizard that takes 582

into account activity body temperatures measured in the field and vegetation cover ande 583

preciptation as environmental variables. The results reinforce that tropical lizard species 584

are under local extinction risks and that these risks can be geographically structured, 585

44

with some regions within its range predicted to become more favorable and some 586

becoming less favorable for the species. Also, our laboratory studies indicate large 587

differences among individuals from the same site and from different sites in thermal 588

traits. We propose that this variability in thermal traits is the basis of local adaptation 589

and might buffer some populations from extinction as the climate warms. Large areas of 590

dense forest vegetation, thermal-tolerance variability and natural selection for heat 591

tolerance are factors with considerable capacity to absorb the impacts of temperature 592

increase on tropical ectotherms during climate change, and they should be included in 593

future models of extinction risk. 594

595

Acknowledgements 596

We would like to thank Conselho Nacional de Desenvolvimento Científico e 597

Tecnológico (CNPq) and Partnerships for Enhanced Engagement in Research from the 598

US National Academy of Sciences and US Agency for International Development 599

(PEER NAS/USAID PGA-2000005316) for funding this research. We thank the 600

institutions that provided spatial data of K. calcarata: University of Kansas (KU), 601

Coleção Herpetológica da Universidade Federal da Paraíba (CHUFPB), Coleção de 602

Tecido Animal da Universidade Federal do Espírito Santo (CTAUFES), Coleção 603

Herpetológica do Museu Paraense Emílio Goeldi (CH-MPEG), Coleção Herpetológica 604

da Universidade de Brasília (CHUNB), Coleção Herpetológica do Instituto de Pesquisas 605

Científica e Tecnológica do Amapá (CH-IPCTA), Museu de Zoologia da Universidade 606

de São Paulo (MZUSP), and Coleção de Anfíbios e Répteis do Instituto Nacional de 607

Pesquisas da Amazônia (INPA-H). We thank Dra. Teresa Avila-Pires for support in 608

data collection in Pará, the staff of INPA reserves for support in data collection in AM 609

45

(Valdecira, Valdir and Rubenildo), and to all people who gave direct assistance for data 610

collection in all locations: AM = G. Lima, L. Chrisley, L. M. Viegas, J. Buckner, K. 611

Bajer, O. R. Molnar, Sr. Compensa and Jesus; PA = C. Sette, A. Paula, Sr. Mór and 612

Dorinha; and TO = C. Morais, S. Balbino, D. Tucker, M. Kucinick and S. Bee. FPW 613

thanks financial support from CNPq (CNPq: 475559/2013-4) and PEER 614

NAS/USAID.B.S. and D. B. M. were supported by NSF EF-1241848. JCS thanks Jack 615

W. Sites, Jr. (BYU) for his support. GRC thanks Coordenação de Aperfeiçoamento de 616

Pessoal de Nível Superior (CAPES), CNPq,Fundação de Apoio à Pesquisa do Distrito 617

Federal (FAPDF) and PEER for financial support. WEM was supported by the PPBio 618

and CENBAM, and both contributed to the availability of a data repository. 619

620

Data Accessibility: data deposited in the KNB Data Repository. Identifier 621

knb.1111.4 (https://knb.ecoinformatics.org/#view/knb.1111.4) 622

623

46

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