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
Secretaria da Educação da Paraíba Examinadora externa à instituição
______________________________
Dra. Maria Cristina Oddone
Universidade Federal do Rio GrandeExaminadora externa à instituição
______________________________
Dr. Sergio Maia Queiroz Lima
Universidade Federal do Rio Grande do NorteOrientador/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
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.
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.
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.
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
What explains the modelled increase in environmental suitability? ... 58
Beyond distribution ... 59
CONCLUSION AND FUTURE PERSPECTIVES ... 61
REFERENCES ... 62
CONCLUSÃO GERAL ... 68
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
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
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.
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
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: jess.fernandd@gmail.com
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.
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
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
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
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 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
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 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.
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
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).
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.
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
Figure 3: Ecological niche models of Atlantoraja castelnaui (A), A. cyclophora (B), A. platana (C), and Rioraja agassizii (D).
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 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.
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
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 (~
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.
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.
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.
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.
