Nicho Abiótico E Efeitos Do Aquecimento Global Em Riorajini (Rajiformes, Arhynchobatidae), Raias Do Atlântico Sudoeste

Nicho abiótico e efeitos do aquecimento global em Riorajini (Rajiformes, Arhynchobatidae), raias do Atlântico Sudoeste

JÉSSICA FERNANDA RAMOS COELHO ______Dissertação de Mestrado Natal/RN, Fevereiro de 2020

JÉSSICA FERNANDA RAMOS COELHO

Nicho abiótico e efeitos do aquecimento global em Riorajini

(Rajiformes, Arhynchobatidae), raias do Atlântico Sudoeste

Dissertação de Mestrado apresentada ao Programa de Pós-

Graduação em Sistemática e Evolução da Universidade

Federal do Rio Grande do Norte como requisito parcial

para obtenção de título de mestre.

Orientador: Dr. Sergio Maia Queiroz Lima Coorientadora: Dra. Flávia de Figueiredo Petean

Fevereiro, 2020 Natal–RN

Nicho abiótico e efeitos do aquecimento global em Riorajini

(Rajiformes, Arhynchobatidae), raias do Atlântico Sudoeste

BANCA EXAMINADORA:

______Dra. Françoise Dantas de Lima Dra. Maria Cristina Oddone Secretaria da Educação da Paraíba Universidade Federal do Rio Grande Examinadora externa à instituição Examinadora externa à instituição

______Dr. Sergio Maia Queiroz Lima Universidade Federal do Rio Grande do Norte Orientador/Presidente

Fevereiro, 2020 Natal–RN

Universidade Federal do Rio Grande do Norte - UFRN Sistema de Bibliotecas - SISBI Catalogação de Publicação na Fonte. UFRN - Biblioteca Setorial Prof. Leopoldo Nelson - •Centro de Biociências - CB

Coelho, Jéssica Fernanda Ramos. Nicho abiótico e efeitos do aquecimento global em Riorajini (Rajiformes, Arhynchobatidae), raias do Atlântico Sudoeste / Jéssica Fernanda Ramos Coelho. - Natal, 2020. 73 f.: il.

Dissertação (Mestrado) - Universidade Federal do Rio Grande do Norte. Centro de Biociências. Programa de Pós-Graduação em Sistemática e Evolução. Orientador: Prof. Dr. Sergio Maia Queiroz Lima.

1. Conservatismo filogenético de nicho - Dissertação. 2. Modelagem de nicho ecológico - Dissertação. 3. Mudanças climáticas - Dissertação. 4. Simpatria - Dissertação. 5. Sobreposição de nicho - Dissertação. I. Lima, Sergio Maia Queiroz. II. Universidade Federal do Rio Grande do Norte. III. Título.

RN/UF/BSE-CB CDU 575.8

Elaborado por KATIA REJANE DA SILVA - CRB-15/351

AGRADECIMENTOS

Primeiramente agradeço a UFRN, onde realizei graduação e agora o mestrado; instituição pública da mais alta qualidade, sinônimo de resistência em meio ao caos atual; me orgulho de ser daqui e de ter alguns dos meus maiores sonhos sendo realizados aqui. Também agradeço ao Programa de Pós-Graduação em Sistemática e Evolução, em especial ao Bruno Bellini e a Gilmara, pela atenção e competência; e a Capes, pela bolsa de estudos, sem a qual esse trabalho não seria possível.

Agradeço demais ao meu orientador Sergio, por ter me aceitado de braços abertos no laboratório; pelo espaço, apoio e confiança na minha independência; espero poder carregar essa parceria científica pro resto da vida.

Um obrigada muito especial à minha coorientadora Flávia, pela oportunidade (lá atrás) de me deixar ajudar no doutorado e me apoiar no mestrado. Foi um grande privilégio ser sua primeira orientanda; obrigada pela confiança, pela ajuda e por me lembrar de “respirar” nos (incontáveis) momentos de surto. No mesmo balaio agradeço a parceria da sereia de água doce do Nerds, Yasmin, por ser a fofa que é, minha parceira de forró e cachaça. Vocês duas são exemplos inspiradores do que é ser cientista, embora, às vezes, talvez nem percebam que são. Eu tenho muita sorte em chamá-las amigas.

A toda a galera do LISE e do GEEFAA – Thais, Germano, Valéria, Sávio, Luciano, Carol, Aninha, Matheus Arthur, Salu, Lai, Geni, Ori, Diego, Lucas, Roney, demais componentes e agregados do laboratório mais zuero do DBZ. Vocês são profissionais em fazer qualquer um rir, em quebrar qualquer clima que ouse ficar sério; assim fica fácil (ou impossível) trabalhar. Um obrigada especial a Sávio e Salu, pela ajuda estatística e com os mapas desse trabalho. Vocês (todos) são massa demais!

A alguns amigos de vida que fizeram muita diferença nesses dois anos, em especial Mari, Higo e Viktor; às esposas que a Austrália me deu, Marina e Luiza; and Jamie, for being ‘so close, no matter how far; it couldn’t be much more from the heart’. Meus amores, a cabeça não teria aguentado sem a leveza, a amizade e o amor de vocês.

Um grandíssimo obrigada ao Filipe Serrano (Giro), pela ajuda na discussão dos resultados, mas também pelas músicas e os papos sincronizados.

Aos queridos com os quais dividi moradia nesse período de perrengues e cheio de mudanças, em especial a Ellen, amiga-irmã de longa data. E o Camurugi, por ser o melhor parceiro de casa que eu poderia ter; obrigada demais pelas conversas regadas a muito café (e cerveja) e pelo carinho de sempre; “um brinde à porr* da amizade”.

Por fim, sou muito grata à minha família: meu pai, minha mãe, minhas duas irmãs e Nina; obrigada pela liberdade, pela educação de base, pela confiança e pela força. Dedico esses anos todos de estudo, e os próximos que virão, a vocês, meus maiores exemplos de perseverança e amor.

Não sei se um dia conseguirei retribuir o apoio que recebi ao longo dessa jornada. Obrigada demais a todos que cruzaram meu caminho, que me ajudaram nesse período e a tantos outros que me permitiram ajudar de algum modo. Foram dois anos de intenso aprendizado e da certeza de que ainda há muito a ser aprendido.

I was hoping we’d make real progress But it seems we have lost the power Any tiny step of advancement Is like a raindrop falling into the ocean We’re running on the spot; always have, always will? We’re just the next generation of the emotionally crippled Though we keep piling up the building blocks The structure never seems to get any higher Because we keep kicking out the foundations And stand useless while our lives fall down I believe in life and I believe in love But the world in which I live in keeps trying to prove wrong Out the pastures we call society You can’t see further than the bottom of your glass Only you but easily shocked You get all violent when the boat gets rocked Just like sheep little lambs into the slaughter Don't fully grasp what exactly is wrong Truth is you never cared still You get all violent when the boat gets rocked Intelligence should be our first weapon And stop reveling in rejection Follow yourselves, not some ageing drain brain Whose quite content to go on feeding your garbage We’re running on the spot; always have, always will? We’re just the next generation of the emotionally crippled

Running on the spot Paul Weller Paralamas do Sucesso

RESUMO

O nicho abiótico de espécies conta parte de sua história ecológica e evolutiva, bem como seu estudo pode ajudar a identificar grupos mais susceptíveis à extinção em um contexto de rápidas mudanças climáticas. Espécies marinhas de ambientes temperados estão entre as mais vulneráveis, pois o estresse térmico e demais impactos em cascata do aquecimento global podem resultar em perda de habitat e deslocamento de distribuição geográfica para maiores latitudes. A tribo Riorajini é composta por quatro espécies de raias marinhas – classificadas pela IUCN como vulneráveis ou em perigo de extinção – que coocorrem no sudoeste Neotropical do Atlântico: Atlantoraja castelnaui, A. cyclophora, A. platana e Rioraja agassizii. A presente dissertação, dividida em dois capítulos, usa esse agrupamento como modelo de estudos ecológico-evolutivos. No primeiro capítulo, questiona-se o conservatismo filogenético de nicho para um clado de espécies potencialmente competidoras em simpatria. Tratando-se de espécies filogeneticamente próximas, espera-se que uma baixa sobreposição de nicho reduza competição interespecífica. No segundo capítulo, estimaram-se os impactos das mudanças climáticas sobre a atual distribuição geográfica da tribo Riorajini. Primeiro, reconstruiu-se a filogenia desse grupo. Posteriormente, modelos de nicho ecológico para cada espécie do grupo foram desenvolvidos sob condições geofísicas e climáticas atuais e futuras (2100, sob cenário climático extremo) do ambiente marinho. Dados ambientais e de ocorrência das espécies foram compilados de bancos de dados públicos e literatura. Análises de sobreposição e deslocamento de nicho foram conduzidas a níveis inter- e intraespecíficos. Os resultados indicam conservatismo filogenético de nicho no qual águas rasas, proximidade da costa e baixa concentração de nitrato são as variáveis mais importantes para a ocorrência das espécies. Em um cenário climático futuro projetado, as áreas de maior adequabilidade ambiental à ocorrência de cada espécie analisada aumentam em até 20% em direção a áreas de maior profundidade, sugerindo que esse clado resistirá ao estresse térmico decorrente do aquecimento global. Apesar disso, estudos futuros devem considerar efeitos combinados do aumento da temperatura a aspectos biológicos desses animais, como o tempo de eclosão das cápsulas ovígeras e o desenvolvimento dos juvenis, bem como o impacto a outros fatores potencialmente determinantes à coexistência dessas espécies, como a disponibilidade de presas.

Palavras-chave: Conservatismo filogenético de nicho; modelagem de nicho ecológico; mudanças climáticas; simpatria; sobreposição de nicho.

ABSTRACT

The abiotic niche of species tells part of their ecological and evolutionary history, as well as helps to identify groups that are more susceptible to extinction in a context of a rapidly changing climate. Marine species from temperate regions are among the most vulnerable taxa because habitat loss as a consequence of thermal stress and other cascading impacts can constrain the availability of suitable area of occurrence, or result in distribution shift towards higher latitudes. The tribe Riorajini comprises four species of neotropical skates that are evaluated by IUCN as vulnerable or endangered, and cooccur in the subtropical Atlantic Ocean: Atlantoraja castelnaui, A. cyclophora, A. platana and Rioraja agassizii. The present dissertation is divided into two chapters and uses this group as a model for eco-evolutionary studies. In the first chapter, phylogenetic niche conservatism is questioned for a clade of sympatric and competitive sister-species. Low niche overlap was expected to reduce interspecific competition between closely-related species. The second chapter assessed the impacts of climate change on the current geographical distribution of the tribe Riorajini. First, the phylogeny of the tribe was reconstructed. Then, ecological niche models for each species of the group were developed under current and future (2100, for the most extreme scenario) geophysical and climatic conditions of the marine environment. Environmental data and species occurrence data were compiled from public databases and literature. Niche shift and overlap were measured within and between species. Results indicate phylogenetic niche conservatism in which shallow waters, proximity to the coast, and low nitrate concentration are the most important variables for the occurrence of these species. Under the future climatic scenario projected, the areas of higher environmental suitability for the occurrence of each species analysed increases up to 20% towards deeper areas, suggesting that this clade will resist the thermal stress resulting from global warming. Nevertheless, future studies should consider the combined effects of an increase in temperature in the time of hatching of egg-capsules and the early development of juveniles, as well as the impact of other factors potentially determining the coexistence of these species, such as prey availability.

Key-words: Phylogenetic niche conservatism; ecological niche modelling; climate change; sympatry; niche overlap.

Sumário

RESUMO ...... ABSTRACT ...... CAPÍTULO 1 – LISTA DE FIGURAS ...... CAPÍTULO 1 – LISTA DE TABELAS ...... CAPÍTULO 2 – LISTA DE FIGURAS ...... CAPÍTULO 2 – LISTA DE TABELAS ...... INTRODUÇÃO GERAL ...... 14 Dividindo o ambiente ...... 14 Grupo de estudo ...... 14 O futuro não demora – o problema do aquecimento global ...... 15 OBJETIVOS ...... 17 Geral ...... 18 Específicos ...... 18 CAPÍTULO 1: Phylogenetic conservatism of abiotic niche in neotropical skates ...... 19 ABSTRACT ...... 19 INTRODUCTION ...... 20 MATERIALS AND METHODS ...... 23 Phylogenetic analysis ...... 23 Ecological Niche Models (ENMs) ...... 24 Comparing niches – testing niche conservatism ...... 26 RESULTS ...... 27 DISCUSSION ...... 33 Evolutionary perspective ...... 33 Environmental drivers of occurrence ...... 35 FINAL CONSIDERATIONS ...... 38 REFERENCES ...... 39 CAPÍTULO 2: Temperate skates’ shift ranges as an outcome of global warming ...... 47 ABSTRACT ...... 47 INTRODUCTION ...... 48 MATERIALS AND METHODS ...... 50 Models of present and future climatic scenarios ...... 50 Statistical Analysis – Measuring differences ...... 51 RESULTS ...... 51

DISCUSSION ...... 58 Minding the caveats ...... 58 What explains the modelled increase in environmental suitability? ...... 58 Beyond distribution ...... 59 CONCLUSION AND FUTURE PERSPECTIVES ...... 61 REFERENCES ...... 62 CONCLUSÃO GERAL ...... 68 REFERÊNCIAS BIBLIOGRÁFICAS ...... 70

CAPÍTULO 1 – LISTA DE FIGURAS

Figure 1: Phylogeny of Riorajini based on a Bayesian inference using gene NADH dehydrogenase 2 (ND2), including Sympterygia acuta as outgroup. Node values as posterior probabilities. Photos of A. cyclophora and A. castelnaui by Bianca de Sousa Rangel ©. Photo of A. platana by Pablo D. Meneses. Photo of R. agassizii by Itamar A. Martins. Photo of S. acuta by Marcelo Vianna...... 27 Figure 2: Occurrence records of preserved specimens used for the ecological niche models of Atlantoraja castelnaui, A. cyclophora, A. platana, and Rioraja agassizii along the marine provinces (Spalding et al., 2007) in Southwestern Atlantic Ocean...... 28 Figure 3: Ecological niche models of Atlantoraja castelnaui (A), A. cyclophora (B), A. platana (C), and Rioraja agassizii (D)...... 30 Figure 4: Principal Component Analysis (PCA) illustrating the influence of environmental variables for Atlantoraja castelnaui (Acas), Atlantoraja cyclophora (Acyc), Atlantoraja platana (Apla), and Rioraja agassizii (Raga). Largest circles are the centroids of distribution of the scattered points. Contrib: contribution of environmental variables (vectors), with darker shades indicating stronger contribution...... 31 Figure 5: PCA-env results of niche overlap and niche similarity tests for each pair of Riorajini species. The gridded niche of the first species in a pair is green; the second, in red; overlap between the two niches is in blue. Arrows point to the direction of shift for the centroids of distribution. Acas: Atlantoraja castelnaui; Acyc: Atlantoraja cyclophora; Apla: Atlantoraja platana; and Raga: Rioraja agassizii...... 32 Figure 6: Scheme illustrating phylogenetic relationship in Riorajini and the main abiotic niche features shared...... 34 Figure 7: Nitrate and phosphate concentrations along the coast of South America. Images retrieved from Bio-ORACLE (available at: bio-oracle.org). Black arrows point to San Matías Gulf in Argentina, where nitrate and phosphate concentrations are higher than surrounding areas...... 37

CAPÍTULO 1 – LISTA DE TABELAS

Table 1: List of environmental variables selected after Pearson’s Correlation Test (|r| ≥ 0.8) for running ecological niche models of Atlantoraja castelnaui, A. cyclophora, A. platana, and Rioraja agassizii...... 29 Table 2: Summary of the best combination (ΔAICc = 0) of parameters established by ENMeval package (Muscarella et al., 2014), and performance evaluation. n – number of occurrence points in the dataset; FC – Feature Classes allowed in the model (L – linear; Q – quadratic; H – hinge); RM – Regularization multiplier; AUC – Area Under ROC curve; sd – AUC standard deviation...... 29 Table 3: Permutation importance (%) per variable (lines) per species (columns). Acas: Atlantoraja castelnaui; Acyc: A. cyclophora; Apla: A. platana; Raga: Rioraja agassizii. Bold highlights the variables of higher contribution (Σ > 70%) to the models of each species.31

CAPÍTULO 2 – LISTA DE FIGURAS

Figure 1: Ecological niche models of present (left) and future (right) climatic scenarios, showing degrees of environmental suitability for the occurrence of Atlantoraja castelnaui (Acas)...... 54 Figure 2: Niche dynamics of Atlantoraja castelnaui. Red arrow in the bottom left graph indicates direction of shift of the distribution’ centroid between the two climatic scenarios. Green: present climatic conditions; red: projected future climatic scenario (2100, RCP 8.5); purple: overlap between scenarios...... 54 Figure 3: Ecological niche models of present (left) and future (right) climatic scenarios, showing degrees of environmental suitability for the occurrence of Atlantoraja cyclophora (Acyc)...... 55 Figure 4: Niche dynamics of Atlantoraja cyclophora. Red arrow in the bottom left graph indicates direction of shift of the distribution’ centroid between the two climatic scenarios. Green: present climatic conditions; red: projected future climatic scenario (2100, RCP 8.5); purple: overlap between scenarios...... 55 Figure 5: Ecological niche models of present (left) and future (right) climatic scenarios, showing degrees of environmental suitability for the occurrence of Atlantoraja platana (Apla)...... 56 Figure 6: Niche dynamics of Atlantoraja platana. Red arrow in the bottom left graph indicates direction of shift of the distribution’ centroid between the two climatic scenarios. Green: present climatic conditions; red: projected future climatic scenario (2100, RCP 8.5); purple: overlap between scenarios...... 56 Figure 7: Ecological niche models of present (left) and future (right) climatic scenarios, showing degrees of environmental suitability for the occurrence of Rioraja agassizii (Raga)...... 57 Figure 8: Niche dynamics of Rioraja agassizii. Red arrow in the bottom left graph indicates direction of shift of the distribution’ centroid between the two climatic scenarios. Green: present climatic conditions; red: projected future climatic scenario (2100, RCP 8.5); purple: overlap between scenarios...... 57

CAPÍTULO 2 – LISTA DE TABELAS

Table 1: Summary of the best combination (ΔAICc = 0) of parameters established by ENMeval package (Muscarella et al., 2014) per species and climatic scenario: P – present; F – future. n: number of occurrence points in the dataset; FC: Feature Classes allowed in the model (L – linear; Q – quadratic; H – hinge); RM: Regularization Multiplier; AUC: Area Under ROC curve per model; sd: standard deviation of AUC...... 52 Table 2: Permutation importance (%) per variable per species for present (P) and future (F) climatic scenarios. Acas – Atlantoraja castelnaui; Acyc – A. cyclophora; Apla – A. platana; Raga – Rioraja agassizii. Bold highlights the variables of higher contribution (Σ > 80%) to models...... 53

Table 3: Minimum and maximum values of the three main variables to the ENMs of Riorajini species in present (P, grey shaded) and future (F, white) climatic scenarios modelled. Acas: Atlantoraja castelnaui; Acyc: A. cyclophora; Apla: A. platana; Raga: Rioraja agassizii.53 Table 4: Niche overlap, expansion, stability, and unfilling measured between present and future climatic scenarios for each Riorajini' species. All values range from 0 (none) to 1 (identical). Acas – Atlantoraja castelnaui; Acyc – A. cyclophora; Apla – A. platana; Raga – Rioraja agassizii...... 58

INTRODUÇÃO GERAL

Dividindo o ambiente

Desde os trabalhos clássicos de Darwin (1859), Wallace (1876) e Grinnell (1917) naturalistas buscam compreender como uma alta biodiversidade compartilha o ambiente. O princípio da exclusão competitiva, atribuído a Gause (1934), é uma maneira de explicar tal padrão. Esse princípio estipula que, quando em simpatria, duas espécies competidoras particionam os recursos do ambiente de modo que ambas possam coexistir sem tendência à exclusão de uma por competição. Tal particionamento ocorre em algum nível do nicho das espécies, que, de modo geral, pode ser biótico (trófico ou reprodutivo, por exemplo; também chamado de nicho Eltoniano (Elton, 1927)) ou abiótico (ambiental; ou nicho Grinnelliano (Grinnell, 1917)).

A tendência de linhagens em manter características de nicho no decorrer do tempo é denominada conservatismo filogenético de nicho (Harvey & Pagel, 1991; Wiens et al., 2010). Como uma possível consequência desse processo, espécies mais próximas filogeneticamente tendem a compartilhar mais aspectos de nicho entre si do que o esperado ao acaso, reflexo de sinal filogenético (Losos, 2008). Esse padrão, porém, é pouco provável entre espécies-irmãs simpátricas, dado que uma alta sobreposição de nicho pode significar maior competição interespecífica. Ainda assim, contrariando parte da lógica ecológica teórica, é possível encontrar exemplos de espécies-irmãs ocorrendo em simpatria na natureza (Kocher, 2004). A tribo de raias neotropicais marinhas Riorajini, grupo de estudo do presente trabalho, é um desses exemplos.

Grupo de estudo

Riorajini (sensu McEachran & Dunn, 1998) é um clado formado por quatro espécies de raias marinhas da família Arhynchobatidae (Chondricthyes: Rajiformes): Atlantoraja castelnaui (Miranda Ribeiro, 1907), A. cyclophora (Regan, 1903), A. platana (Gunther, 1880), e Rioraja agassizii (Müller & Henle, 1841). Atualmente, a avaliação global da União Internacional pela Conservação da Natureza (UICN) classifica A. cyclophora, A. platana e R. agassizii como ‘Vulneráveis’ (VU), e A. castelnaui como ‘Em perigo’ de extinção (EN) (Hozbor et al., 2004; Massa et al., 2006; Kyne et al., 2007; San Martín et al., 2007). A sobrepesca é um dos principais contribuintes ao alarmante status de ameaça dessas espécies, que no Brasil são alvo da pesca, bem como são frequentemente capturadas acidentalmente (by-

catch) (Lessa et al., 1999). Decorrente desta pressão, uma estimativa para A. castelnaui aponta para um declínio de 75% na biomassa dessa espécie entre 1994 e 1999 na Argentina e Uruguai (Hozbor & Massa, dados não publicados; Hozbor et al., 2004).

Endêmicas da região subtropical do Oceano Atlântico, essas quatro espécies coocorrem do litoral do sudeste brasileiro, a partir do Espírito Santo (20°S), ao litoral da Argentina (45°S) (Figueiredo, 1977). Essa faixa latitudinal apresenta a maior concentração de elasmobrânquios classificados sob algum nível de ameaça de extinção da região Neotropical (vulnerável, ameaçada ou criticamente ameaçada – VU, EN e CR) (Field et al., 2009). Dados recentes da literatura expandem a área de distribuição de algumas dessas espécies em até cinco graus ao sul (Menni et al., 2010; Bovcon et al; 2011), indicando que os mapas de distribuição atualmente disponíveis estão desatualizados (e.g. mapas da UICN e FishBase) – um típico déficit Wallacean (incertezas acerca da distribuição geográfica de espécies) para o grupo (Hortal et al., 2015). Mapas defasados limitam o entendimento de aspectos ecológicos desse grupo, como: até onde esses táxons coexistem? Existem diferenças latitudinais e/ou longitudinais significativas entre eles? Quais características ambientais limitam a distribuição geográfica de uma espécie em relação à outra? Além disso, conhecer a distribuição geográfica de uma espécie é importante para avaliar seu estado de conservação. Assim, atualizar os mapas de distribuição dessas espécies com dados mais recentes da literatura é essencial para compreender não somente implicações ecológicas desses padrões de distribuição, mas para planejar medidas efetivas de conservação do grupo e propor estudos futuros.

O futuro não demora1 – o problema do aquecimento global

O ritmo acelerado de mudanças ambientais desafia a capacidade adaptativa dos organismos. Alterações fenológicas, metabólicas e de distribuição geográfica de espécies já têm sido atribuídas às mudanças climáticas (Edwards & Richardson, 2004; Pistevos et al., 2015). No tocante às mudanças de distribuição geográfica, de modo geral, o padrão observado é um deslocamento para altas latitudes e maior elevação de altitude para táxons terrestres (Hickling et al., 2006; Chen et al., 2011). No ambiente aquático, além do latitudinal, há o deslocamento batimétrico, em direção a áreas de maior profundidade (Perry et al., 2005; Nicolas et al., 2011). Em ambos os ambientes, as mudanças latitudinais ocorrem em direção oposta à linha do Equador, região de maior incidência solar do planeta e, consequentemente, mais exposta aos efeitos do estresse térmico imediato do aquecimento global.

1 Álbum da banda BaianaSystem (2019).

O ambiente marinho provê bens e serviços cruciais à manutenção da vida na Terra. Mais da metade do oxigênio do planeta é produzido nos oceanos, bem como a maior parte do dióxido de carbono – um dos gases estufa mais abundantes – é absorvido por sistemas marinhos (Field et al., 1998; Falkowski, 2012). Além disso, correntes marítimas transportam calor do Equador aos polos, regulando padrões climáticos (Chahine, 1992). Em escala local, zonas costeiras são uma área econômica importante, contribuindo com quase 80% do valor dos serviços ecossistêmicos globais (Costanza et al., 1997), os quais incluem armazenamento e ciclagem de nutrientes, disponibilidade de água e comida (Martínez et al., 2007). Por este motivo, certamente, há alta densidade populacional humana nas zonas costeiras, embora essas regiões estejam também mais vulneráveis a desastres naturais (Nicholls & Small, 2002). Portanto, não somente o bom funcionamento de ecossistemas terrestres, mas também o estilo de vida humano atual, dependem intimamente de oceanos saudáveis.

O problema

Algumas características biológicas e ecológicas tornam algumas espécies mais susceptíveis às consequências negativas do aquecimento global. Por exemplo, para raias da família Arhynchobatidae, o hábito bentônico e a filopatria tornam esse grupo particularmente vulnerável às mudanças climáticas se comparado a outros elasmobrânquios de hábitos pelágicos (Dulvy & Reynolds, 2002). Isso acontece porque uma área de ocorrência restrita e dependência de habitats específicos limitam a capacidade dispersiva das espécies do grupo (Di Santo, 2015). Ademais, crescimento lento e maturidade sexual tardia, além da deposição de cápsulas ovígeras sésseis, também podem limitar a capacidade dispersiva e adaptativa do grupo frente às rápidas mudanças climáticas, bem como dificultar a reposição de indivíduos em uma população (population replenishment), o que aumenta a vulnerabilidade das espécies aos impactos da sobrepesca, por exemplo (Stevens et al., 2000; Iglésias et al., 2009).

As diferenças de nicho influenciando a simpatria desse clado ainda são pouco exploradas. Tratando-se de uma tribo de espécies potencialmente competidoras simpátricas, de dieta generalista e reprodução anual (Barbini & Lucifora, 2011; 2012; 2016; Viana & Vianna, 2014; Viana et al., 2017), o primeiro capítulo dessa dissertação testa a hipótese de que espécies mais aparentadas filogeneticamente apresentarão nichos mais dissimilares. Ou seja, espera-se que diferenças de nicho abiótico, potencialmente refletidas em diferenças ecológicas, explicam como tais espécies coexistem temporal e espacialmente. O segundo capítulo usa cenários climáticos projetados (até 2100) para testar a hipótese de que, em decorrência das mudanças climáticas, haverá diminuição e/ou deslocamento ao sul das áreas de maior adequabilidade

ambiental para distribuição das espécies de raias da tribo Riorajini. Um contexto de mudanças climáticas globais destaca a importância de avaliar diferenças de nicho ecológico entre espécies, pois tais características podem indicar grupos mais tolerantes ou vulneráveis à mudança termal, auxiliando a tomada de decisões relativas aos planos de manejo e conservação (Gallagher et al., 2012).

Resumo gráfico dos dados da literatura sobre tamanho corpóreo máximo, amplitude batimétrica de ocorrência e principais itens de dieta das quatro espécies da tribo Riorajini (do topo a baixo): Rioraja agassizii (vermelho), Atlantoraja castelnaui (azul), A. cyclophora (verde) e A. platana (amarelo).

OBJETIVOS

Geral

Os objetivos principais desta dissertação são (i) identificar o padrão de particionamento de nicho abiótico da tribo Riorajini: Rioraja agassizii (Müller & Henle, 1841), Atlantoraja platana (Günther, 1880), A. cyclophora (Regan, 1903) e A. castelnaui (Miranda Ribeiro, 1907), raias neotropicais simpátricas, endêmicas do Atlântico subtropical ocidental (Capítulo 1), e (ii) estimar os impactos das mudanças climáticas sobre a atual distribuição geográfica dessas espécies (Capítulo 2).

Específicos

• Atualizar os mapas de distribuição geográfica das quatro espécies da tribo Riorajini, indicando as províncias biogeográficas segundo Spalding et al. (2007) nas quais cada uma ocorre; • Modelar o nicho ecológico dessas espécies sob o cenário climático atual e futuro (2100) de maior concentração de gases estufa (Representative Concentration Pathway – RCP 8.5); • Identificar as variáveis abióticas de maior influência ao nicho ecológico atual de cada uma dessas espécies; • Relacionar o grau de sobreposição de nicho ecológico par-a-par entre essas espécies ao grau de parentesco (proximidade filogenética); • Medir as diferenças entre os modelos de nicho ecológico atual e futuro para cada espécie da tribo Riorajini, identificando as espécies mais e menos vulneráveis quanto à potencial disponibilidade de habitat em um cenário climático futuro.

CAPÍTULO 1: Phylogenetic conservatism of abiotic niche in neotropical skates

Jéssica Fernanda Ramos Coelho¹, Sergio Maia Queiroz Lima¹, Flávia de Figueiredo Petean¹

1Departamento de Botânica e Zoologia, Centro de Biociências, Universidade Federal do Rio Grande do Norte, Campus Universitário, BR 101 s/n, 59078-900, Lagoa Nova, Natal, RN, Brazil.

E-mail: [email protected]

ABSTRACT

From the perspective of phylogenetic niche conservatism (PNC), we expect that closely related species share more aspects of niche among them than expected randomly. However, considering the competitive exclusion principle, PNC is questionable for closely related species occurring in sympatry. The present research aims to test niche conservatism in Riorajini, a tribe of four Neotropical sympatric skates endemic to the subtropical western Atlantic Ocean: Atlantoraja castelnaui, A. cyclophora, A. platana and Rioraja agassizii. We hypothesized that an abiotic niche differentiation supports the coexistence of this clade, questioning niche conservation in a sympatric clade of potentially competitive species. We used R as an interface to conduct Ecological Niche Models (ENMs) to map the set of conditions that characterize the abiotic niche for each species under current marine geophysical and climatic conditions. We compiled presence records for each species from public online databases and literature, and nine uncorrelated (Pearson Correlation Test < 0.8) environmental variables from MARSPEC and Bio-ORACLE databases considering biological and ecological relevance for the group. We calculated niche overlap, equivalency, and similarity using a variation of a principal component analysis (PCA-env) for all pairwise combination of Riorajini’ species. Results indicate niche conservatism in this tribe, suggesting that a differentiation in an aspect of niche, other than the abiotic niche, allows the coexistence of these species.

Key-words: Competitive Exclusion principle; Ecological Niche Model; Grinnellian Niche.

INTRODUCTION

The term “niche” can assume multiple meanings. Grinnell (1917) was the first to denote the idea of niche when referring to the set of abiotic/climatic conditions in a species habitat allowing survival and reproduction. Later, Elton (1927) and Gause (1934) introduced the functional role of organisms and other biotic interactions to the niche concept, such as competition. A further thorough concept presented by Hutchinson (1957) refers to niche as an n-dimensional hypervolume of characteristics required for a species to exist in an area, called fundamental niche. Where the species in fact occur, however, must consider biotic interactions and other limiting factors (e.g.: the ability to reach an area), called realized niche (Soberón & Nakamura, 2009). Although the realized niche is logically smaller than the fundamental niche, mathematical proof was only recently presented (Soberón & Arroyo-Peña, 2017).

Phylogenetic niche conservatism is a lineage’s likelihood to maintain ancestral niche features through time (Harvey & Pagel, 1991). Since this first definition, numerous studies exploring this idea have been published typically testing whether species closer in a phylogeny share more aspects of niche than expected randomly (Prinzing et al., 2001; Ahmadzadeh et al., 2013; Peixoto et al., 2017). Pyron et al. (2015) argued phylogenetic niche conservatism as a process from which three patterns of niche may arise: niche conservation, niche divergence, and niche constrain. The first is intuitive. The second, although contradictory at first glance, states that niches are considered divergent when they are less similar than expected given phylogenetic proximity of lineages (Pyron et al., 2015). When such pattern is attributed to ecological speciation (Wiens, 2004; Gorel et al., 2019), then selective forces other than stasis in current niche are acting, and phylogenetic niche conservatism does not occur (Pyron et al., 2014). Finally, niches of species are considered constrained when they vary within a limited subset of the niches available in the environment (Pyron et al., 2015).

Understanding species abiotic preferences is an important aspect to comprehend why these occur in some areas and not in others, despite geographic closeness. Besides, characterizing the abiotic niche (also called Grinnellian niche) of species is of paramount importance to understand physiological aspects and tolerances, as well as to predict the role of a lineage in an ecosystem (Dumbrell et al., 2010). For example, higher biomasses of phytoplankton are present in areas of high concentration of chlorophyll-a and nutrients (Panda et al., 2012), which reflects the photosynthetic role of this group in the ecosystem. Such characterizations are important to understand evolutionary dynamics, interactions among

groups of organisms, and the impacts of environmental changes on species (Harmon et al., 2009; Rinnan & Lawler, 2019).

Competitive species in sympatry must agree on a co-occurrence strategy. Even though usually attributed to Gause (1934), the competitive exclusion principle has its roots in works as early as Grinnell (1917) and Darwin’s (1859) (Kneitel, 2008). This principle states that two species cannot coexist if they occupy the exact same niche. Therefore, without a tendency to competitive exclusion as a consequence of high niche overlap, we expect niche conservatism to be unlikely between sympatric sister-species (Pigot & Tobias, 2012; Scriven et al., 2016). In other words, between two closely related species coexisting in space and time, niche divergence is probable to be the rule for the stable occurrence of both lineages. Yet, contrary to theoretical ecological expectation, sister-species co-occur in nature (Kocher, 2004). The tribe of neotropical skates Riorajini is one of these examples (Last et al., 2016).

The tribe Riorajini (sensu McEachran & Dunn, 1998) is a clade of four skates: Rioraja agassizii (Muller & Henle, 1841), Atlantoraja platana (Günther, 1880), A. cyclophora (Regan, 1903), and A. castelnaui (Miranda Ribeiro, 1907). Originally, Menni (1972) described Atlantoraja as a subgenus in Raja Linnaeus, 1768 based on the shape of the dorsal terminal 1 cartilage. Later, McEachran and Dunn (1998) elevated Atlantoraja and Rioraja to the genus level based on morphological characteristics. Using sequences of NADH dehydrogenase subunit 2 (ND2), a mitochondrial gene, Naylor et al. (2012) presented a distance analysis depicting the genetic similarity of the tribe as R. agassizii(A. castelnaui (A. platana A. cyclophora))2. However, no phylogenetic analysis has been conducted to the moment, which limits evolutionary discussions on the group.

As other elasmobranchs, skates are oviparous and egg-laying occurs all year (Oddone & Vooren, 2005; Oddone et al., 2007; Oddone & Capapé, 2011), however these are species of slow growth, slow metabolism, late maturity age, and high investment of energy in offspring (Stevens et al., 2000; Helfman et al., 2009). The latter particularly increases new-borns survival rate. The downside of slow growth and late maturation is a decrease in overall population resilience, making species vulnerable to immediate anthropogenic impacts, such as commercial exploitation (Shepherd & Myers, 2005; Helfman et al., 2009). Additionally, skates are the most diverse group within batoids, yet presents highly conserved morphological and ecological characters (Ebert & Compagno, 2007; Ball et al., 2016). Some morphological characters in

2 Newick format.

Riorajini, such as reduction of rostral cartilage and extension of pectoral radials – the former considered a paedomorphism – reflects adaptation to benthic habitats (McEachran & Dunn, 1998).

Despite differences in mean body size and ontogenetic diet shift, Riorajini species converge to the consumption of similar prey items, mostly crustaceans (amphipods, shrimps, brachyurans), teleosts, and to a lesser extent, A. castelnaui also feeds on cephalopods and other elasmobranchs (Paesch, 2000; Viana & Vianna, 2014; Barbini & Lucifora, 2011; 2012; 2016; Viana et al., 2017). Changes in diet have been noticed seasonally, although this is more likely to be a consequence of prey availability and behaviour rather than a change in preferences by these skates (Barbini & Lucifora, 2012). High dietary overlap between these species suggests they compete for prey.

Abiotic conditions rapidly change with increasing depth of seafloor, influencing community composition and population dynamics along the environmental gradient (Smith & Brown, 2002). Temperature, salinity, and bathymetry likewise affect elasmobranchs’ distribution, and shifts from a species’ optimum set of environmental conditions can impact behaviour, physiology, and metabolic functioning (Green & Jutfelt, 2014; Pistevos et al., 2015). Understanding species-specific requirements of environmental conditions tells part of the evolutionary’ history of a group, as well as helps identifying taxa more vulnerable to extinction in face of climatic changes. The influence of the environmental heterogeneity on Riorajini’ distribution, however, remains poorly explored.

The southwestern portion of the Atlantic Ocean (SWA) hosts the highest number of threatened chondrichthyan species in the Neotropical region (Field et al., 2009). Due to its high richness, endemism, and number of threatened species, Stein et al. (2018) classified the SWA as a priority area for conservation of Chondrichthyes. The four Riorajini species are endemic to this area and present occurrence records, as for the IUCN maps, from Espírito Santo in Brazil, to Patagonia in Argentina (Hozbor et al., 2004; Massa et al., 2006; Kyne et al., 2007; San Martín et al., 2007; Moreira et al., 2017), although some of this maps do not consider data from more recent literature (e.g. Bovcon et al., 2011) and are, therefore, outdated. Such obsolete maps can over- or underestimate the area of occurrence of these species, making it more difficult to conduct management. Besides, failing to include new data of species occurrence into maps of distribution limits our ability to visualize the degree of sympatric occurrence in this tribe, and, consequently, to understand the dynamics of the coastal community they occupy.

Anthropogenic activities are one of the main sources of disturbance to the dynamics of coastal communities. For example, overfishing has led skates to local extinction, such as Dipturus batis in the Irish sea (Brander, 1981). This is of particular concern given that as a consequence of a high fishing pressure, all Riorajini species are threatened with extinction, according to the classification of the International Union for Conservation of Nature (IUCN): Atlantoraja cyclophora, A. platana, and Rioraja agassizii are classified as vulnerable (Massa et al., 2006; Kyne et al., 2007; San Martín et al., 2007), and A. castelnaui as endangered (Hozbor et al., 2004). This, combined with a limited geographic distribution and life-history traits previously exposed, makes skates one of the most vulnerable taxa of all marine species (Stevens et al., 2000; Dulvy et al., 2014). The problem of outdated maps of geographic distribution also jeopardize identification of conservation statuses. Thus, one objective of the present research is to incorporate data available in the literature to provide updated maps of geographic distribution for these species, which can aid future evaluation of their degree of threat.

Biological characteristics suggest Riorajini species explore resources similarly, thus they are likely to play similar ecologic roles in the environment (Rosenfeld et al., 2002). These same characteristics, however, combined with sympatry in a limited geographic range raises the question on which aspect of their niche allows co-occurrence. We hypothesize species- specific responses to environmental factors. In other words, abiotic niche differentiation might play an important role in species sympatry, guiding species to different strata in the environment (Scriven et al., 2016). We first built the phylogeny of the tribe to then test niche conservatism, as the former is a must to understand and discuss results. For the purposes of the present research, we consider the Grinnellian niche concept, which focus on abiotic and climatic conditions necessary for a species to survive (Soberón, 2007).

MATERIALS AND METHODS

Phylogenetic analysis

We used sequences of NADH dehydrogenase 2 (ND2) available on GenBank to infer the phylogenetic relationships in Riorajini. ND2 is a mitochondrial gene considered barcode for chondrichthyans for its bigger length and faster evolution rates (more variation) in comparison with cytochrome oxidase 1 (CO1), commonly used in other taxa (Moore et al., 2011; Naylor et al., 2012). We chose Sympterygia acuta Garman, 1877 as an outgroup for the phylogenetic

analysis, a skate of the same family as the tribe Riorajini occurring in sympatry with these species, for which ND2 sequence is also available on GenBank (Massa et al., 2004; Naylor et al., 2012). Sequences were retrieved under the following accession numbers: A. castelnaui: JQ519082.1; A. cyclophora: JQ519084.1; A. platana: JQ519083.1; R. agassizii: JQ519080.1; and S. acuta: JQ519081.1.

We used Mega version 7.0.26 (Tamura et al., 2007) to align the five sequences using the ClustalW method (Larkin et al., 2007). The same software was used to select the molecular evolution model under the Bayesian Inference Criteria (BIC), which indicated Hasegawa- Kishino-Yano+Gamma (HKY+G) as the best model. To infer phylogenetic relationship under a Bayesian analysis, we used BEAST version 1.10.4 (Suchard et al., 2018), set the molecular clock to a relaxed log normal distribution, and ran 107 generations sampled every 1000, with a burn-in of 10%.

Ecological Niche Models (ENMs)

The R program version 3.5.1 (R Core Team, 2018) was used as an interface to perform a machine-learning algorithm of maximum entropy (maxent) models. ENMs were conducted using species’ records of occurrence (presence) and data characterizing the environment it occupies, following a correlative approach (Pearson, 2007).

Following Muscarella et al. (2014), we tested six combinations of maxent’s feature classes (FC): L, H, LQ, LQH, LQHP, LQHPT (L: linear; H: hinge; Q: quadratic; P: product; T: threshold). Feature classes represent raw or modified values of environmental variables. For each FC combination, we tested eight values of regularization multiplier (varying from 0.5 to 4.0, with a 0.5 increment). Regularization multiplier (RM or β) decreases overfitting of models (Merow et al., 2013). ENMeval package was used to choose the best combination of parameters (FC and RM) per model (Muscarella et al., 2014); the combination to generate the most parsimonious model (deltaAICc = 0) was considered the best. Models’ training and testing points were partitioned applying the ‘block’ method. Models were run with a 10-5 convergence threshold, 10,000 maximum iterations, and 10,000 maximum background points. Each model is a mean of 15 bootstrap replicates. Maps were edited with QGIS 2.8.9 software (QGIS Development Team, 2019).

Occurrence records

Occurrence data for each species derived from online databases, such as Global Biodiversity Information Facility (GBIF, 2019; http://gbif.org), speciesLink (CRIA, 2019; http://splink.cria.org.br/) and FishNet2 (http://www.fishnet2.net/) (full set of compiled records: Supplementary Material – Table 1). We conducted an exploratory analysis to remove discrepant values (outliers) using vegan package version 2.5.2 in R (Oksanen et al., 2013). In an attempt to increase data accuracy, only georeferenced preserved specimens in each species’ known occurrence area were accounted (Brazilian, Uruguayan and Argentinean coasts; coordinates from other regions – e.g. one specimen at coast of Panama – were considered misidentifications and therefore eliminated from the analysis). Remarkable morphological differences between the species of this group – evidenced by well-defined species diagnoses, as well as notably different patterns of dorsal coloration (e.g. Figueiredo, 1977; Gomes et al., 2010) – aggregates trustworthiness to the identification of the specimens used as reference in this research.

Duplicates and redundant points (i.e.: points in the same grid cell) were removed to increase data uniformity of distribution and avoid spatial autocorrelation (Shcheglovitova & Anderson, 2013). Additionally, we used spThin package version 0.1 in R to return the best dataset of occurrence records per species (Aiello-Lammens et al., 2015). These procedures avoid biasing the model towards areas of easier access and higher sampling effort by removing aggregations of one species’ occurrence records. These data per species were then plotted in the marine biogeographic provinces as in Spalding et al. (2007).

Environmental data

The environmental layers used in ENMs are variables, also called predictors, that characterize the abiotic conditions of the region to be modelled. Each layer is a raster file derived from satellite data. Bio-ORACLE (Tyberghein et al., 2012; Assis et al., 2017) and MARSPEC (Sbrocco & Barber, 2013) offer high resolution (5-arc-min and 30-arc-sec, respectively) environmental layers for the present climatic and geophysical marine conditions. There is no consensual guideline regarding the ideal number of predictors for ENMs. However, the selection of environmental layers must consider aspects of the species’ biology and ecology (Fourcade et al., 2017), and the question to be answered (Merow et al., 2013). Besides, from a model-performance point-of-view, the selection of predictors must be conducted in a way to avoid model overfitting and multicollinearity – which can happen when the number of predictors is much higher than the number of occurrence points in a dataset (Parolo et al., 2008) or when variables are correlated (Warren et al., 2014), respectively. Thus, a Pearson correlation

test was performed with 36 layers available (18 from MARSPEC and 18 from Bio-ORACLE) for current geo-climatic conditions to remove highly correlated layers (|r| ≥ 0.8).

Even without strong correlation with remaining variables, layers with immediate appearance of no relevance for the clade (e.g. plan curvature) were manually removed. The removal of one from a pair of highly correlated variables considered ecological and biological knowledge of the clade. Likewise, chosen environmental layers correspond to benthic maximum depth. Before running the models, predictors were scaled to equal dimension and resolution (0.833°, ~9 km). We used boxplots to visualize and remove occurrence records outliers for each environmental variable selected after the Pearson correlation test.

Comparing niches – testing niche conservatism

We conducted a principal component analysis (PCA) to reduce dataset dimensions (Jollife & Cadima, 2016), and visualize the degree of divergence between centroids of distribution of each species and the set of environmental layers selected. The first principal components explaining more than 70% of the proportion of variance (PV) of the data were kept in the analysis (Zuur et al., 2010). Eigenvectors showing |PV| ≥ 0.4 in at least one principal component were kept. Data homoscedasticity was confirmed using biotools package version 3.1 in R (da Silva et al., 2017), thus we used a permutational multivariate analysis of variance (PERMANOVA) to test multivariate significance of niche overlap.

The Schoener’s D index was calculated to measure the degree of niche overlap between models of pairs of species (Warren et al., 2008). Schoener’s D values vary from 0 (no overlap) to 1 (identical models). Then, following Boennimann’s et al. (2012) framework, we conducted a variation of a principal component analysis (PCA-env) to compare niches of Riorajini’ species. This approach allows to test niche equivalency and niche similarity between pairs of species. The first, tests the null hypothesis of niche equivalency (the two niches are identical/equivalent) by comparing the true equivalency calculated to a null distribution of niche equivalency scores based on the pooling of occurrence records of the two species. The second tests if the niche occupied by one species in its range is more similar than what would be expected at random to the niche occupied in the other range. A null distribution to which the true overlap is compared is created by measuring niche overlap between one species and the background space of the other species. Both niche equivalency and similarity tests are based on 100 repetitions and null hypotheses cannot be rejected if the measured value falls within 95%

of simulated values (Broennimann et al., 2012). Tests were conducted using ecospat package version 3.0 in R (Broennimann et al., 2018).

RESULTS

The Bayesian phylogenetic inference recovered the same topology of relationships among Riorajini species (Figure 1) as the neighbour-joining analysis by Naylor et al. (2012). Besides, all nodes have high posterior probabilities (> 0.97). Coupling data from online biodiversity databases and literature (Supplementary Material – Table 1), occurrence records for Riorajini species expanded in up to five degrees southward (Figure 2) in comparison with distribution maps currently available (e.g. IUCN maps).

3 Images available at: A. cyclophora: shark-references.com/species/view/Atlantoraja-cyclophora A. castelnaui: https://shark-references.com/species/view/Atlantoraja-castelnaui A. platana: https://www.fishbase.se/summary/Atlantoraja-platana.html R. agassizii: https://www.fishbase.se/summary/50857 S. acuta: https://www.fishbase.se/summary/Sympterygia-acuta.html

Figure 2: Occurrence records of preserved specimens used for the ecological niche models of Atlantoraja castelnaui, A. cyclophora, A. platana, and Rioraja agassizii along the marine provinces (Spalding et al., 2007) in Southwestern Atlantic Ocean.

Nine uncorrelated (|r| ≤ 0.8) environmental layers were selected for modelling the ecological niche of Atlantoraja castelnaui, A. cyclophora, A. platana and Rioraja agassizii (Table 1; Figure 3). The best model (ΔAICc = 0) of each species presented a different combination of parameters (Table 2). When models are created with presence-only data, AUC reflects the model ability to differentiate occurrence from background points (Phillips et al., 2006). The ENM of each species (Figure 3) presented a different set of environmental variables with higher contribution to the model (> 70%, measured as the permutation importance) (Table 3), although the niches in bidimensional, gridded space showed high overlap and similarity (Figures 4 and 5).

Variable Code Unit Scaling Reference Temperature mean SST_mean °C 100x MARSPEC Temperature range SST_range °C 100x MARSPEC Salinity mean SSS_mean psu 100x MARSPEC Salinity range SSS_range psu 100x MARSPEC Distance to shore dist_shore km 1x MARSPEC Depth of seafloor bathy_5m m 1x MARSPEC Nitrate concentration nitrate_mean mol.m-3 1x Bio-ORACLE Iron concentration iron_mean mol.m-3 1x Bio-ORACLE Currents velocity current_vel m-1 1x Bio-ORACLE

Table 2: Summary of the best combination (ΔAICc = 0) of parameters established by ENMeval package (Muscarella et al., 2014), and performance evaluation. n – number of occurrence points in the dataset; FC – Feature Classes allowed in the model (L – linear; Q – quadratic; H – hinge); RM – Regularization multiplier; AUC – Area Under ROC curve; sd – AUC standard deviation.

Species Code n FC RM AUC sd Atlantoraja castelnaui Acas 31 LQ 2.5 0.984 0.003 Atlantoraja cyclophora Acyc 60 LQH 1.0 0.994 0.001 Atlantoraja platana Apla 30 LQH 2.0 0.988 0.002 Rioraja agassizii Raga 43 LQ 0.5 0.989 0.002

Figure 3: Ecological niche models of Atlantoraja castelnaui (A), A. cyclophora (B), A. platana (C), and Rioraja agassizii (D).

Figure 4: Principal Component Analysis (PCA) illustrating the influence of environmental variables for Atlantoraja castelnaui (Acas), Atlantoraja cyclophora (Acyc), Atlantoraja platana (Apla), and Rioraja agassizii (Raga). Largest circles are the centroids of distribution of the scattered points. Contrib: contribution of environmental variables (vectors), with darker shades indicating stronger contribution.

Table 3: Permutation importance (%) per variable (lines) per species (columns). Acas: Atlantoraja castelnaui; Acyc: A. cyclophora; Apla: A. platana; Raga: Rioraja agassizii. Bold highlights the variables of higher contribution (Σ > 70%) to the models of each species.

Acas Acyc Apla Raga Temperature mean 1.6 4.5 8.9 2.6 Temperature range 18.2 3.2 1.7 0.1 Salinity mean 0.2 0.5 0.4 0.3 Salinity range 0.1 1.4 1.2 11.7 Distance to shore 12.2 2 26.5 30.6 Depth of seafloor 19.6 3.8 53.6 33.7 Nitrate mean 37.1 80.1 0.1 20.2 Iron mean 10.9 3.1 7.5 0.5 Currents velocity 0.1 1.4 0.1 0.2

Figure 5: PCA-env results of niche overlap and niche similarity tests for each pair of Riorajini species. The gridded niche of the first species in a pair is green; the second, in red; overlap between the two niches is in blue. Arrows point to the direction of shift for the centroids of distribution. Acas: Atlantoraja castelnaui; Acyc: Atlantoraja cyclophora; Apla: Atlantoraja platana; and Raga: Rioraja agassizii.

Niche equivalency results indicate Riorajini species present equivalent niches, and niche similarity results indicate they are more similar than expected by chance, although the former did not always find a significant value for the results (Supplementary material – PCA-env results). Statistically non-significant results (p > 0.05) will not be discussed despite being available in all graphs/figures depicting PCA-env results. Phylogeny results coupled with PCA analysis suggest niche conservatism in this tribe.

DISCUSSION

As the term “niche” can assume multiple meanings, when testing for conservatism it is important to highlight the concept and the taxonomic level at which it is discussed (Peixoto et al., 2017). In the present research we applied a test of niche conservatism coupled with a phylogenetic reconstruction to test the hypothesis that a differentiation in abiotic niche at the tribe level allows the co-occurrence of four species of skates. Our results, however, show that niche conservatism is the overall pattern within Riorajini, though no linear relationship between phylogenetic proximity and niche similarity is clear, as some pairs of species more phylogenetically distant show highly similar niches, whereas congeners display more divergent niches.

Evolutionary perspective

The highest value of niche similarity was found between A. castelnaui and R. agassizii (~72%) and the lowest value was found between A. castelnaui and A. platana (~43%). From a phylogenetic perspective, it is more parsimonious to assume that an ancestral lineage had a niche “A”, which could be a feature at the node of the tribe shared by R. agassizii and its sister- clade. Within this clade, the niche “A” is also present in A. castelnaui as a conserved characteristic. The sister-clade to A. castelnaui evolved a distinct feature, “B”, which is shared by A. cyclophora and A. platana (Figure 5). These two groups of species differ in preferable habitats, with R. agassizii and A. castelnaui occurring in shallower waters, closer to the shoreline in comparison to A. cyclophora and A. platana, which explore the continental shelf farther.

Figure 6: Scheme illustrating phylogenetic relationship in Riorajini and the main abiotic niche features shared in the southwest Atlantic Ocean.

In each group separated by depth, species partition food resources. Atlantoraja castelnaui and R. agassizii feed mainly on teleosts, however, the former attains up to 1470 mm in total length (TL) (Weigmann, 2016), being the largest body-sized species of Riorajini, which allows it to also explore larger preys, such as cephalopods and other chondrichthyans (Barbini & Lucifora, 2012). Rioraja agassizii, the smallest species in the group, feeds on smaller preys such as crustaceans and polychaetes (Barbini & Lucifora, 2011). Atlantoraja platana and A. cyclophora have diets based on crustaceans decapods, although teleosts are also an important item for the latter (Schwingel & Assunção, 2009; Barbini & Lucifora, 2016). Differences in depth of occurrence have been mentioned for these four species in the literature (Menni et al., 2010) and, as a general pattern for elasmobranchs, Smith and Brown (2002) found a negative relationship between bathymetry and body size with larger elasmobranchs’ species occurring in shallower waters – a pattern to some extent present in our results.

The events that resulted in or contributed to the speciation of the tribe Riorajini are still unknown. The southwestern Atlantic region where these species occur is under the influence of the freshwater outflow of the La Plata river, between Uruguay and Argentina. This impacts environmental heterogeneity and provides a plethora of new niches to explore, which is reflected in species’ niches when they present different tolerances to environmental characteristics. We would expect, however, a stronger signal of niche divergence to argue that

these differences played an important role triggering cladogenesis within the group in a scenario of sympatric speciation – in fact, Riorajini species co-occurring nowadays do not necessarily imply the clade underwent sympatric speciation since secondary contact of previously isolated lineages is commonly seen in nature (Petit et al., 2003; Chevolot et al., 2006). As the species in this tribe show niches that are more similar than expected by chance, however still differing within a subset of conditions, it is likely that an ancestral lineage of this monophyletic group accumulated differences along an environmental gradient. Reviews on the topic [of speciation] highlight this scenario of parapatry as an important driver of diversification in the marine environment, preventing the need of strong vicariant barriers and large geographic scales to occur (Rocha & Bowen, 2008; Bowen et al., 2013).

Environmental drivers of occurrence

For the nine variables included in the ENMs, five were the most significant for all species: nitrate concentration, temperature range, salinity range, depth of seafloor (bathymetry), and distance to shore. Our study indicates these variables characterize the fundamental abiotic niche of the group. It is worth noting that the two latter variables are likely to experience drastic changes in a global warming scenario, as the rise of sea level is expected to be one of the main consequences of higher temperatures in the near future (Zhang et al., 2004). However, how these changes will translate into an impact to the niche of this group remains to be tested (Chapter 2). The importance of each of these predictors varied between species and up to three variables were necessary to characterize the niche of each species in more than 70 per cent, which we consider to be the abiotic conditions to exert higher influence in the realized abiotic niche of each species.

Species differed in response to nitrate concentrations. Response curves for this variable shows that A. cyclophora presents a peak in probability of occurrence when the concentration reached approximately 5 mol.m-3 (Supplementary Material – Maxent figures, Figure 2) and the jackknife test indicates nitrate as the variable that, alone, is the most useful as well as has the most unique information (i.e.: information that is not present in other variables) for developing the model (Supplementary Material – Maxent figures, Figure 1). Therefore, nitrate mean is the environmental variable to better characterize the ecological niche of this species. Rioraja agassizii shows a peak in probability of occurrence for even lower concentrations of nitrate (~ 1.0 mol.m-3). Only for A. platana, nitrate was not an important predictor for the model.

The Pearson’s correlation test revealed that the concentrations of phosphate, silicate, and nitrate are highly correlated (|r| ≥ 0.8), indicating these variables represent similar environmental information. To avoid biasing the model towards this redundancy, we excluded one from a pair of highly-correlated variables, leading the removal of phosphate and silicate from the analyses. Other studies with Chondrichthyes have disregarded information of these variables (Lucifora et al., 2012), so there is a gap in literature on models revealing and exploring the link between nitrate concentration and the distribution of skates in general.

Low concentrations of nitrate in Southwestern Atlantic near the shoreline reflects the influence of the Brazilian current flowing southward along a shallow continental shelf. Tropical waters in the Brazilian current are oligotrophic and present low concentrations of suspended particles, which also indicate that the influx of organic matter from land does not affect the water in this current (Seeliger et al., 1998). On the other hand, the Falkland current, reaching the south of Warm Temperate Southwestern Atlantic province and flowing northward, is rich in dissolved nutrients and, therefore, sustain primary productivity and a vast food chain in the region (Seeliger et al., 1998). As illustrated in Figure 2, Riorajini species occurrence is constrained to the continental shelf, where nitrate concentration is low. For A. platana, for example, it is important to notice the isolated population at the San Matías Gulf in Argentina. In this region, nitrate and phosphate concentrations tend to be higher in comparison with its surroundings (Figure 5). Mean nitrate concentration is probably not influencing the ENM of A. platana because this species occurs in areas of either low (e.g. south coast of Brazil) or high values of this variable. This can translate into an ecological resilience of this species, or, at least, of the population at San Matías Gulf.

Figure 7: Nitrate and phosphate concentrations along the coast of South America. Images retrieved from Bio-ORACLE (available at: bio-oracle.org). Black arrows point to San Matías Gulf in Argentina, where nitrate and phosphate concentrations are higher than surrounding areas.

Oddone and Vooren (2004) did not find a correlation between the frequency of occurrence and abundance of A. cyclophora with temperature, salinity, or depth for specimens collected off the coast of Rio Grande do Sul, Brazil. Accordingly, these variables were not significantly relevant for modelling the ecological niche of this species. Combined, mean temperature, salinity, and depth of seafloor contributed with less than 10% to the model of A. cyclophora (Table 3). Similarly, nitrate concentration is the variable of higher influence (37.1%) to the niche model (Table 3; Figure 3) of A. castelnaui. However, depth of seafloor and temperature range also played important roles in increasing model gain for this species (19.6 and 18.2% permutation importance, respectively). The graph showing the response curve for temperature range suggests this species tolerates high variations in this variable (Supplementary Material – Maxent figures, Figure 4), which could be considered an advantage in a global warming scenario.

FINAL CONSIDERATIONS

Phylogenetic niche conservatism is the overall pattern in Riorajini. However, no linear relationship between phylogenetic proximity and niche similarity is clear since some pairs of species that are more phylogenetically distant show highly similar niches. The environmental features to characterize the abiotic niche of the group are bathymetry, distance to shore, nitrate concentration, temperature range, and salinity range. Species-specific responses to these variables characterize the abiotic niche of each species.

Despite imperative importance to understand ecosystems’ dynamics and species’ biology, data registering the occurrence of elasmobranchs are often a by-product of other researches, such as studies of species diet, or fisheries statistics. Perhaps for this reason, the process of mapping the distribution of species is yet not entirely automated, evidenced by outdated maps for some species in renowned, popular websites of biological information (e.g. IUCN and FishBase). Previous maps of distribution mostly failed to illustrate the southern limit of distribution of all Riorajini species, either underestimating distribution, which was the case for A. castelnaui (Hozbor et al., 2004), or disregarding distribution gaps, such as for A. platana (San Martín et al., 2007). The maps of geographic distribution here presented considered data of georeferenced preserved specimens and literature, and the niche models offer a simple bidimensional overview of the probability of occurrence of each species as for the abiotic conditions. Additionally, these maps can aid future assessment of conservation status for this tribe as they comprise the data available so far on the occurrence of the four species and indicate a general set of ecological tolerances for each of them.

An extensive body of research is available on diet, morphology, and reproductive biology of Riorajini species (e.g., Oddone & Vooren, 2004, 2005, 2008; Colonello et al., 2007; Oddone & Amorim, 2007; Oddone et al., 2007, 2008; Barbini & Lucifora, 2011, 2012, 2016; Oddone & Capapé, 2011) although studies focusing on other physiological and ecological aspects such as behaviour, for example, are lacking in the literature, perhaps for the high cost and logistic difficulties to conduct such. Low cost, non-invasive methodologies are an alternative way to explore some of these areas. Our research is the first to apply a modelling approach to identify and discuss signals of abiotic niche conservatism in Riorajini skates. These provide insights into possible triggers to the isolation of ancestral lineages, telling part of the evolutionary history of the clade, even though numerous strands, as abovementioned, remain to be explored in the group.

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CAPÍTULO 2: Temperate skates’ shift ranges as an outcome of global warming

Jéssica Fernanda Ramos Coelho¹, Sergio Maia Queiroz Lima¹, Flávia de Figueiredo Petean¹

1Departamento de Botânica e Zoologia, Centro de Biociências, Universidade Federal do Rio Grande do Norte, Campus Universitário, BR 101 s/n, 59078-900, Lagoa Nova, Natal, RN, Brazil.

E-mail: [email protected]

ABSTRACT

Climate change is a growing global-scale issue with an increasing body of evidence revealing its potential to impact patterns of distribution of living organisms. Some biological and ecological traits make some organisms more vulnerable than others to climate-related abiotic stress, with species of slow growth, late maturation, and limited geographic distribution being of particular concern. Riorajini is a tribe of four sympatric skates’ species occurring in the temperate southwestern Atlantic falling into this category. Considering skates’ life-history traits, coupled with species’ ecological requirements, we hypothesize a poleward geographic shift with potential shrink in overall distribution range of these species as a response to climate change impacts at the coastal zones this clade occupies. We compiled satellite-derived raster imagery and data on species occurrence from public online databases to model the ecological niche of Riorajini species under present and future (2100, RCP 8.5) climatic scenarios. Between the two climatic scenarios modelled per species, we calculated metrics of niche overlap, stability, expansion, and unfilling, as well as niche similarity and equivalency. All analyses were conducted in R. Our results show high overlap between the two climatic scenarios and reveal an expansion in up to 20% in future environmental suitability for the occurrence of the tribe. The expansion occurred to deeper zones (longitudinal shift), however still within the bathymetric limit of the continental shelf. Although positive at first glance, future research focusing on ontogenetically different responses (adults versus eggs capsules) to cascade events resulting from global warming are needed to address the physiological resilience of this group. Also, consequences of such shift can be detrimental to the local biota in newly invaded areas, as the introduction of new predatory species can affect negatively the dynamics of the community.

Key-words: climate change; distribution shift; Riorajini; RCP 8.5.

INTRODUCTION

Evidence for both terrestrial and marine biotas shifting ranges as a response to impacts of climate change are growing in the literature. Terrestrial organisms are changing distributions in latitude and elevation to cope with thermal stress (Root et al., 2003; Hickling et al., 2006; Chen et al., 2011). In the oceans, these differences are in latitudinal range and depth (Perry et al., 2005; Nicolas et al., 2011). Perry et al. (2005) showed that two-thirds of the fish species analysed from the North Sea respond to warming waters shifting in mean latitude, depth, or both, as well as a distribution boundary shift poleward. These changes are a reflection of a climate-related disequilibrium.

Long-term analyses show a global scale warming resulting from the continuous increase in the emission of greenhouse gases, likely an effect of anthropogenic activities (Houghton, 1996; Mann et al., 1999; Barnett et al., 2001; Rosenzweig et al., 2008). Such changes are occurring faster than most organisms can adapt to (Quintero & Wiens, 2013), and, besides the difficulty to attribute an impact as a consequence of anthropic global warming, studies are consistently finding rather compelling evidence of theoretical predictions for climate change- related impacts on biodiversity distribution (Hughes, 2000; Walther et al., 2002; Parmesan & Yohe, 2003). The accumulation and synergistic effect of these changes on ecosystems can alter abiotic conditions of the planet to the extent that living organisms will be pressured towards the maxim “move, adapt or die”.

Climate change is not likely to impact species or habitats in the same way. For example, for elasmobranchs, animals with long life cycles, slow growth, and late maturation, the “move” option seems more feasible in face of environmental stress (Stevens et al., 2000; Helfman et al., 2009). Fewer physical barriers in comparison with terrestrial habitats makes it easier to move and disperse in the marine environment, however, some biological and ecological characteristics, along with a lack of connectivity between some populations, makes this group more susceptible than others to adverse events (Somero, 2010). In skates, for example, sessile eggs capsules and philopatry imply in a restricted area of occurrence and strong reliance on particular habitats, which adds to the vulnerability of this group to climatic changes in comparison with other pelagic elasmobranchs (Dulvy & Reynolds, 2002; Parmesan, 2006; Dulvy et al., 2014; Di Santo, 2015).

Riorajini (sensu McEachran & Dunn, 1998) is a tribe of four skates of the Arhynchobatidae family occurring in sympatry in the southwest Atlantic Ocean, a region that

harbours the highest number of threatened chondrichthyan species in the Neotropics (Field et al., 2009). According to the IUCN latest global assessment, the species in this group are evaluated as “endangered” (EN): Atlantoraja castelnaui (Hozbor et al., 2004), and “vulnerable” (VU): A. cyclophora, A. platana, and Rioraja agassizii (Massa et al., 2006; Kyne et al., 2007; San Martín et al., 2007). These species occur mainly at the Warm Temperate Province, as defined by Spalding et al. (2007), influenced at north by the Cabo Frio upwelling system, and at south by the effects of cold-water masses from Falkland current (Peterson & Stramma, 1990; Coelho-Souza et al., 2012). A range of occurrence limited to the shore makes these taxa more vulnerable as coastal zones are considered to be more exposed to natural climate-related hazards (Nicholls & Small, 2002; Nicholls & Cazenave, 2010).

Frameworks on how to answer climate change-related questions (e.g.: Broennimann et al., 2012, and Guisan et al., 2014) coupled with the improvement of computational models able to address biological issues boosted our capacity to test eco-biological-based hypothesis, and to visualize theoretical scenarios more efficiently. For example, Representative Concentration Pathways (RCPs) represents data from the literature on possible paths for the main driving agents of climate change. There are currently four RCPs available, from mild to more extreme scenarios, varying from 2.6 to 8.5 W/m² (ranging from ~490 to ~1370 ppm CO2, respectively) by the end of the century, predicted as for the trends in emission of greenhouse gases and land use (Van Vuuren et al., 2011). These emissions translate into an increase of up to 1.7 °C in mean temperature in the 2.6 RCP scenario, and up to 4.8°C in the 8.5 RCP scenario, both compared to pre-industrial levels (Stocker et al., 2013). Studies on the distribution of species under different geographic and temporal scenarios benefited from these advances and became more popular (Guisan & Zimmermann, 2000), however, studies focusing on the impacts of climate change in distribution patterns in the marine environment are yet scarce in comparison with terrestrial ones (Dambach & Rödder, 2011).

In a context of rapid climatic changes in a global scale, these are of particular interest given that the patterns of biodiversity distribution may interfere in ecosystems’ goods for human populations, such as fisheries (Blanchet et al., 2019). Besides, with an increasing number of species threatened with extinction detrimental to such changes (Thomas et al., 2004; Maclean & Wilson, 2011), the use of non-invasive methodologies to aid addressing such urgent matters has been necessary. There is an increasing body of literature in this regard, using models to identify ecological barriers to the distribution of species (Costa et al., 2017). Yet, perhaps because of sampling difficulties and costly logistics, studies focusing on elasmobranchs are to

some degree neglected compared to bony fish, molluscs, and marine mammals, for example, for which studies applying ENMs correspond to over half of the studies published so far considering marine taxa (Melo-Merino et al., 2020). Such studies are of paramount importance to provide the basis from which conservation efforts can be planned and implemented.

In this study, we compiled information from public biodiversity databases and RCP data to model current and projected (2100) distributions of Riorajini, a Neotropical tribe of four skates’ species. Considering life-history traits (e.g. slow growth, late maturation, and philopatry), ecological features (benthic, sedentary habit, coastal habitats, temperate waters) and putative future climate change impacts on coastal zones, we hypothesize Riorajini species will present a southward shift in their current geographic distribution and a reduction in the range of areas where these species are likely to occur in a future scenario of climate change (considering the extreme scenario of global warming impacts, RCP 8.5).

MATERIALS AND METHODS

Models of present and future climatic scenarios

We ran maximum entropy (maxent) ecological niche models (ENMs) for each one of the four species in the tribe following a correlative approach, which requires georeferenced sites of occurrence of a given species, and data characterizing abiotic, climatic conditions where such species is present (also called abiotic predictors, or layers) (Phillips et al., 2006; Robinson et al., 2011).

Occurrence sites were derived from published literature and public online databases filtered by preserved specimens georeferenced in the area of known occurrence, to increase data reliability. Localities were partitioned into model training and testing points applying the ‘block’ method, suitable when spatial and temporal transferability is required (Muscarella et al., 2014). Layers for future (2100) environmental conditions considered the worst-climatic- scenario (RCP 8.5) for which 18 variations (e.g. minimum, maximum, mean) of three variables (salinity, temperature and currents velocity) for benthic maximum depth were available in Bio- ORACLE (Tyberghein et al., 2012; Assis et al., 2017). A Pearson’s correlation test was conducted to remove highly-correlated variables (|r| ≥ 0.8) from the analysis aiming to avoid multicollinearity (Warren et al., 2014) and model overfitting (Parolo et al., 2008). For comparative purposes, the ENM for the current climatic scenario, including only the variables

selected after the Pearson correlation test for future modelling, was also performed for each species, following the same procedure.

Environmental variables were scaled to equal dimension and resolution (0.833°, ~9km). ENMeval package was used to select the combination of maxent parameters to output the parsimonious model (ΔAICc = 0), which are considered the best models (Muscarella et al., 2014). ENMs were conducted in R program version 3.5.1 (R Core Team, 2018).

Statistical Analysis – Measuring differences

We followed the methodological framework proposed by Guisan et al. (2014) to map and measure the degree of change between niches of present and future climatic scenarios for each species. Niche expansion, stability and unfilling were measured by comparing intra- specific models for both climatic scenarios. Niche expansion refers to the portion of niche available in a future climatic scenario, but not occupied in the current scenario; niche stability reflects the proportion of climatic conditions available in both temporal scenarios; and niche unfilling refers to conditions of current climatic scenario that are not available in the projected future climatic scenario (Guisan et al., 2014). The Schoener’s D index was calculated to measure niche overlap between present and future models per species (Warren et al., 2008). Finally, niche similarity and equivalency were measured to test if present and future niches will be more similar or equivalent than expected at random (Broennimann et al., 2012). All niche metrics were calculated using ade4 package version 1.7.13 and ecospat package version 3.0 in R (Chessel et al., 2004; Dray & Dufour, 2007; Dray et al., 2007; Bougeard & Dray, 2018; Broennimann et al., 2018).

RESULTS

Six uncorrelated environmental variables were selected for the ENMs of current and future climatic scenarios: temperature mean (°C), salinity mean and range (psu), current velocity mean, minimum, and maximum (m-1). The most parsimonious models included different feature classes and values of regularization multiplier compared with default maxent models (Table 1).

Species Code n FC RM AUC sd Atlantoraja castelnaui Acas 31 P LQ 0.5 0.986 0.003 F LQ 1.5 0.982 0.003 Atlantoraja cyclophora Acyc 60 P LQ 0.5 0.991 0.001 F H 2.5 0.991 0.001 Atlantoraja platana Apla 30 P H 2.5 0.977 0.004 F H 4.0 0.977 0.005 Rioraja agassizii Raga 36 P LQH 2.5 0.978 0.003 F H 2.0 0.981 0.003

The importance of each of the six abiotic predictors included in the models varied in each climatic scenario modelled per species (Table 2), as well as the range of values of the three main environmental variables for the models (Table 3). Within species, niche overlap and stability were overall high (> 80%), and values of niche expansion and unfilling were low (< 22%), suggesting the abiotic conditions currently required for the existence of these species in that area will be available in a future of warmer climatic conditions (Table 4). Both climatic scenarios are also significantly more similar than expected by chance (Figures 2, 4, 6, and 8).

Table 2: Permutation importance (%) per variable per species for present (P) and future (F) climatic scenarios. Acas – Atlantoraja castelnaui; Acyc – A. cyclophora; Apla – A. platana; Raga – Rioraja agassizii. Bold highlights the variables of higher contribution (Σ > 80%) to models.

Acas Acyc Apla Raga P F P F P F P F Temperature mean 94.7 89.1 96.9 51.1 17.1 2.4 48.3 73 Salinity range 0.5 5.5 0.1 23.4 39.8 72 44.6 20.7 Salinity mean 0.7 0.9 1.3 17.7 2.4 0.3 2 2.7 Current velocity minimum 0.1 0.2 0.5 5.8 36.5 18.2 0.8 2 Current velocity mean 1.5 2.5 0.3 1.9 3.3 6.2 1.5 0.1 Current velocity maximum 2.6 1.7 0.9 0.1 0.9 0.9 2.8 1.4

Salinity Salinity Temperature

mean (psu) range (psu) mean (°C) Acas P 33.20–36.72 0.35–1.25 9.34–21.84 F 33.26–37.21 0.38–1.42 11.53–23.99 Acyc P 33.60–36.61 0.43–1.20 10.59–19.67 F 33.83–37.04 0.38–1.34 12.36–21.77 Apla P 34.05–37.12 0.13–1.40 3.53–25.47 F 33.94–37.79 0.18–1.53 4.37–28.09 Raga P 33.64–37.11 0.47–1.59 10.59–25.63 F 33.85–37.77 0.37–1.81 12.36–28.34

ENMs show an increase in habitat suitability for the occurrence of A. castelnaui (Figure 1) and R. agassizii (Figure 7) along the latitudinal gradient they occupy, and in La Plata river mouth. For A. cyclophora, such increase occurs more expressively at the Brazilian coast (Figure 3). There is a slight loss in environmental adequacy for the occurrence of A. platana near the coastline of Rio de Janeiro (23°S) but an overall increase in habitat suitability in deeper areas, still constrained to the continental shelf (Figure 5); besides, occurrence sites plotted into the future modelled climatic scenario fall into areas of up to 2°C warmer than the present scenario.

Figure 1: Ecological niche models of present (left) and future (right) climatic scenarios, showing degrees of environmental suitability for the occurrence of Atlantoraja castelnaui (Acas).

Figure 2: Niche dynamics of Atlantoraja castelnaui. Red arrow in the bottom left graph indicates direction of shift of the distribution’ centroid between the two climatic scenarios. Green: present climatic conditions; red: projected future climatic scenario (2100, RCP 8.5); purple: overlap between scenarios.

Figure 3: Ecological niche models of present (left) and future (right) climatic scenarios, showing degrees of environmental suitability for the occurrence of Atlantoraja cyclophora (Acyc).

Figure 4: Niche dynamics of Atlantoraja cyclophora. Red arrow in the bottom left graph indicates direction of shift of the distribution’ centroid between the two climatic scenarios. Green: present climatic conditions; red: projected future climatic scenario (2100, RCP 8.5); purple: overlap between scenarios.

Figure 5: Ecological niche models of present (left) and future (right) climatic scenarios, showing degrees of environmental suitability for the occurrence of Atlantoraja platana (Apla).

Figure 6: Niche dynamics of Atlantoraja platana. Red arrow in the bottom left graph indicates direction of shift of the distribution’ centroid between the two climatic scenarios. Green: present climatic conditions; red: projected future climatic scenario (2100, RCP 8.5); purple: overlap between scenarios.

Figure 7: Ecological niche models of present (left) and future (right) climatic scenarios, showing degrees of environmental suitability for the occurrence of Rioraja agassizii (Raga).

Figure 8: Niche dynamics of Rioraja agassizii. Red arrow in the bottom left graph indicates direction of shift of the distribution’ centroid between the two climatic scenarios. Green: present climatic conditions; red: projected future climatic scenario (2100, RCP 8.5); purple: overlap between scenarios.

Table 4: Niche overlap, expansion, stability, and unfilling measured between present and future climatic scenarios for each Riorajini' species. All values range from 0 (none) to 1 (identical). Acas – Atlantoraja castelnaui; Acyc – A. cyclophora; Apla – A. platana; Raga – Rioraja agassizii.

Acas Acyc Apla Raga Niche overlap 0.8953927 0.9241363 0.9520403 0.8097972 Niche expansion 0.1947291 0.10116894 0.05615735 0.10056594 Niche stability 0.8052709 0.89883106 0.94384265 0.89943406 Niche unfilling 0.2116576 0.07294093 0 0.1013457

DISCUSSION

Minding the caveats

Models for current climatic conditions developed in Chapter 1, including nine environmental predictors, showed temperature mean, salinity mean and range, and current velocity as variables of low importance for characterizing the abiotic niche of Riorajini (permutation importance < 12% for these variables, for all species). However, as explained in the Methods’ section, these are the only predictors available in Bio-ORACLE for modelling benthic habitats in an RCP 8.5 scenario. Nevertheless, we assume that this lack of data does not constrain our understanding on the shifts of the realised niche of these species. Bearing in mind this limitation, a variety of questions worth of debate arise from these results, and some of which will be briefly discussed in the next sections.

What explains the modelled increase in environmental suitability?

The abiotic niche of Riorajini did not markedly expand southward as hypothesized, but in longitude, towards deeper areas; however, still within the limits of the continental shelf, reinforcing the barrier that depth poses to the distribution of this group (Chapter 1). The environment is expected to change as climate changes. Tracking suitable environmental conditions leads Riorajini species to occupy deeper zones, and such range expansion in response to global warming is seemingly the pattern for many other marine organisms, from invertebrates to teleosts, elasmobranchs, and mammals, for example (Parmesan & Yohe, 2003; Perry et al., 2005; Parmesan, 2006; Molinos et al., 2015). Marine taxa exhibiting niche conservatism are even faster tracking these conditions, as for their tendency to maintain ancestral lineages’ characteristics of niche (Chivers et al., 2017), and fewer physical barriers constraining distribution (Pinsky et al., 2013). Such eastward shift in abiotic conditions necessary for the occurrence of these species is likely to push their distribution towards the limits of the

continental shelf. However, these species are not likely to surpass the barrier imposed by the continental shelf, since the abiotic conditions beyond this boundary are not suitable for their occurrence – high depth and high concentration of nitrate, for example (Chapter 1). Besides, a geographic expansion beyond the shelf requires physiological adaptations, for example, changes in osmoregulatory strategies (Treberg & Speers-Roesch, 2016), not feasible in 100- years scale.

Niches of A. castelnaui and R. agassizii are more at risk because these species presented the lowest values of niche overlap and highest values of niche unfilling between climatic scenarios modelled. This result was expected considering the shallower waters these species occur are likely to be more exposed to climate change impacts (Nicholls & Cazenave, 2010). Abiotic niches of these species are also likely to expand more drastically towards deeper areas, in ~20 and ~10%, respectively. Atlantoraja cyclophora and A. platana, on the other hand, presented the highest values of niche overlap between the two climatic scenarios (> 90% for both species), suggesting that the areas where these species currently occur will not face severe changes.

Overall for the group, low values of niche unfilling indicate that most of the current abiotic conditions required by the species will be available in the future. Similarly, high values of niche overlap and stability (>80% in both metrics) suggest stasis between the two modelled scenarios. Nevertheless, it is important to consider that an increase in environmental adequacy does not necessarily translates into the organisms’ ability to occupy new climatically available areas, as other local forces might interact compromising dispersion (Vaz & Nabout, 2016). VanDerWal et al. (2013) draw attention to the complexity of the combined climate change impacts and other uncountable factors influencing species distribution in a way so that simply looking at the expected poleward shift in biodiversity geographic distribution detrimental to climate change underestimates the real effects of this phenomenon. To shed light on an often overlooked pattern arising from a phenomenon it is important to assess issues from different angles and be able to discuss beyond the obvious (or expected).

Beyond distribution

Temperature mean was the variable of higher contribution to the models of present and future climatic conditions for all analysed species except A. platana, which showed salinity range as the variable of higher contribution for both climatic scenarios (Table 2). While higher temperatures might be tolerable for adults, it is likely to be harmful for young and eggs (Pörtner

& Peck, 2010), as seen for skates Leucoraja erinacea (Di Santo et al., 2015) and Raja microocelata Montagu, 1818 (Hume, 2019), for example.

Changes in biological and physiological aspects of elasmobranchs have been documented with probable link to global warming. Laboratory experiments simulating future concentrations of atmospheric carbon dioxide indicate behavioural alterations in sharks detrimental to water acidification (Green & Jutfelt, 2014), as well as a decrease in metabolic and hunting efficiency of these predators (Pistevos et al., 2015). Negative impacts in young bony fishes have also been documented, with Pistevos et al. (2017) study’s showing that ocean acidification modifies the perception of physiochemical cues by fish larvae with potential to jeopardize dispersal of young and, later, population replenishment. In embryos of Leucoraja erinacea, there is evidence of decrease in metabolic efficiency caused by both thermal stress and ocean acidification (Di Santo et al., 2015). The role of temperature on the timing of hatching egg capsules of elasmobranchs is well documented in the literature (e.g., Clark, 1922) and recent lab experiments have illustrated such effect. For example, embryos of Raja microocellata showed that increasing temperatures leads eggs capsules to hatch faster and produce young of smaller body size (Hume, 2019). In such study, a temperature increase of 2 °C produced skates 3.5% smaller (Hume, 2019). Such metabolic impacts in early developmental stages can reduce an organisms’ fitness and later compromise survival, development and reproduction. More empirical tests and estimates of climate change effects on benthic predators such as skates are clearly lacking in the literature.

The problem of going locally extinct in some areas, and/or expanding distribution to others not occupied before, is exacerbated by the short time period in which these changes occur and has potential to affect the dynamics of the community. Elasmobranchs are typical predators and, as such, play a crucial role in structuring marine communities, either directly through predation and influences in prey-behaviour (e.g. changes in preys’ response to the presence of predators) (Creel & Christianson, 2008; Heithaus et al., 2008), or indirectly, by keeping other predators out of the local community system (Cailliet et al., 2005). Current abiotic conditions act like filters delimiting boundaries to the distribution of these skates in their native area. Climate change effects weaken such filters for aquatic invasive species (Rahel & Olden, 2008). For Riorajini species, it is the case of expansion of habitat suitability that, if translated into real occupation by one or more of these species, can alter the dynamics of the new occupied area.

CONCLUSION AND FUTURE PERSPECTIVES

Our study shows mainly a longitudinal increase in environmental suitability for the occurrence of four neotropical skates’ species in a scenario of global warming. In favourable biotic conditions, these species are, therefore, likely to explore deeper areas. The shift in niche centroid for these species will push them towards the limits of ecological tolerances and geographic space. Consequences of such shift can be detrimental both (i) to local biota, as the introduction of a new predatory species has potential to negatively affect the dynamics of this community, as well as (ii) to the species themselves, likely to face a reduction of geographic range considering a longer period of time.

Future studies should take advantage of the increasing amount of biodiversity data available online (e.g. GBIF) and the numerous modelling and ordination approaches (e.g. Broennimann et al., 2012; Guisan et al., 2014) to assess aspects of species’ biology and ecology in a relatively easy-to-follow, low-cost framework.

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CONCLUSÃO GERAL

O modo como uma alta biodiversidade particiona recursos limitados e compartilha o ambiente depende de inúmeros fatores e, portanto, nem sempre é refletido em diferenças claras em algum aspecto do nicho das espécies. Da faixa latitudinal do litoral sudeste do Brasil à Patagônia, dentro dos limites longitudinais da plataforma continental, as quatro espécies de raias da tribo Riorajini coexistem com alto grau de similaridade de nicho abiótico. Esse conservatismo filogenético de nicho está refletido no monofiletismo do grupo, cuja topologia filogenética é concordante tanto com dados morfológicos (McEachran & Dunn, 1998) quanto genéticos (Capítulo 1). No entanto, uma sutil diferença existe entre essas espécies quanto à probabilidade de ocorrência em função da batimetria, da distância da costa e da baixa concentração de nitrato. Essas três variáveis podem desempenhar um papel crucial na ocupação do ambiente por esse grupo, sendo que Atlantoraja castelnaui e Rioraja agassizii apresentam maior probabilidade de ocorrência em águas rasas mais próximas à costa, e A. platana e A. cyclophora ocorrem em maior profundidade e distância da costa.

Através de modelos computacionais, dados de biodiversidade e informações de satélites, é possível simular diferentes cenários climáticos e estimar a probabilidade de ocorrência de uma espécie em determinada área, permitindo o teste de hipóteses eco-evolutivas em direção ao passado ou ao futuro. Em um contexto climático projetado ao ano de 2100, considerando o cenário mais drástico de mudanças climáticas, há um aumento de áreas adequadas à ocorrência das quatro espécies da tribo Riorajini. Na prática, a ocupação dessas novas áreas por essas espécies pode não ser possível considerando (i) interações com outras espécies, (ii) efeitos combinados decorrentes das mudanças climáticas, como mudanças na composição iônica e pH da água, e (iii) impactos na época de reprodução e de eclosão dos ovos. Estudos futuros devem, em especial, considerar este último ponto, já que a temperatura é um fator importante à eclosão do ovo em raias (Salinas-de-León et al., 2018). O aumento da temperatura atrelado a outros efeitos do aquecimento global pode ser prejudicial ao desenvolvimento de juvenis em águas rasas de zonas costeiras, já que essa variável acelera o desenvolvimento embrionário, encurtando períodos de incubação; tal estresse térmico pode se refletir numa diminuição de fitness ao longo das gerações (Di Santo et al., 2015). Ainda, a disponibilidade de presas pode ser um fator determinante à coocorrência dessas espécies no ambiente, e esta também pode mudar em um cenário de aquecimento global.

Por fim, os resultados dos dois capítulos contribuem ao entendimento de aspectos ecológicos e evolutivos dessa tribo, bem como apresenta caminhos a explorar aspectos práticos,

como exemplo em estudos aplicados à fisiologia (ex.: efeitos do aumento da temperatura da água nesses animais em diferentes estágios ontogenéticos). Além disso, através da atualização dos mapas de distribuição geográfica apresentados, pode-se apontar áreas de possível falha amostral com informações para subsidiar mais estudos, planos de manejo e conservação das espécies desse grupo.

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