• Energy Research

AbstractCorrelative species distribution models (SDMs) are important tools to estimate species’ geographic distribution across space and time, but their reliability heavily relies on the availability and quality of occurrence data. Estimations can be biased when occurrences do not fully represent the environmental requirement of a species. We tested to what extent species’ physiological knowledge might influence SDM estimations. Focusing on the Japanese sea cucumber Apostichopus japonicus within the coastal ocean of East Asia, we compiled a comprehensive dataset of occurrence records. We then explored the importance of incorporating physiological knowledge into SDMs by calibrating two types of correlative SDMs: a naïve model that solely depends on environmental correlates, and a physiologically informed model that further incorporates physiological information as priors. We further tested the models’ sensitivity to calibration area choices by fitting them with different buffered areas around known presences. Compared with naïve models, the physiologically informed models successfully captured the negative influence of high temperature on A. japonicus and were less sensitive to the choice of calibration area. The naïve models resulted in more optimistic prediction of the changes of potential distributions under climate change (i.e., larger range expansion and less contraction) than the physiologically informed models. Our findings highlight benefits from incorporating physiological information into correlative SDMs, namely mitigating the uncertainties associated with the choice of calibration area. Given these promising features, we encourage future SDM studies to consider species physiological information where available.

AbstractCorrelative species distribution models (SDMs) are important tools to estimate species’ geographic distribution across space and time, but their reliability heavily relies on the availability and quality of occurrence data. Estimations can be biased when occurrences do not fully represent the environmental requirement of a species. We tested to what extent species’ physiological knowledge might influence SDM estimations. Focusing on the Japanese sea cucumber Apostichopus japonicus within the coastal ocean of East Asia, we compiled a comprehensive dataset of occurrence records. We then explored the importance of incorporating physiological knowledge into SDMs by calibrating two types of correlative SDMs: a naïve model that solely depends on environmental correlates, and a physiologically informed model that further incorporates physiological information as priors. We further tested the models’ sensitivity to calibration area choices by fitting them with different buffered areas around known presences. Compared with naïve models, the physiologically informed models successfully captured the negative influence of high temperature on A. japonicus and were less sensitive to the choice of calibration area. The naïve models resulted in more optimistic prediction of the changes of potential distributions under climate change (i.e., larger range expansion and less contraction) than the physiologically informed models. Our findings highlight benefits from incorporating physiological information into correlative SDMs, namely mitigating the uncertainties associated with the choice of calibration area. Given these promising features, we encourage future SDM studies to consider species physiological information where available.

AbstractAimClimate change is affecting the geographic distributions of many species and researchers are increasingly relying on species distribution models (SDMs) to forecast species' redistributions under climate change. Such modelling studies, however, often ignore biotic interactions that shape species' geographic ranges. This is especially problematic for coral reefs, which host a high diversity of species and interactions. We tested how biotic interactions affect the distribution patterns of obligate coral‐dwelling Trapezia crabs.LocationGlobal coastal ocean.Time Period2000–2014, 2040–2050, 2090–2100.Major Taxa StudiedCorals and coral‐dwelling Trapezia crabs.MethodsWe determined the symbiotic relationships between 22 crab species in the genus Trapezia and corals via field survey and extensive literature review. We first developed SDMs for coral and crab species using exclusively abiotic variables (abiotic‐only models for corals and crabs). Then we constructed a second set of models where we accounted for coral distributions into crab predictions by combining model predictions for the two taxa a posteriori (abiotic‐plus‐biotic models for crabs only).ResultsWe obtained 30 commonly accepted coral‐crab symbiotic relationships from nine Trapezia crab and six stony coral species. The abiotic‐only model predictions showed that six corals may lose approximately one‐sixth of suitable ranges under RCP 8.5 in 2040–2050. The two types of models for crabs yielded largely different habitat suitability predictions and accounting for biotic interactions into SDM predictions exacerbates the predicted impacts of climate change on coral‐dwelling crabs.Main ConclusionsOur results show large discrepancies in crab spatial distribution patterns with and without accounting for symbiotic interactions. Our findings highlight the important role of modeller's decision on accounting for biotic interactions when predicting the geographical ranges of coral‐dwelling species, with important implications for designing future conservation and management strategies for marine species.

AbstractAimClimate change is affecting the geographic distributions of many species and researchers are increasingly relying on species distribution models (SDMs) to forecast species' redistributions under climate change. Such modelling studies, however, often ignore biotic interactions that shape species' geographic ranges. This is especially problematic for coral reefs, which host a high diversity of species and interactions. We tested how biotic interactions affect the distribution patterns of obligate coral‐dwelling Trapezia crabs.LocationGlobal coastal ocean.Time Period2000–2014, 2040–2050, 2090–2100.Major Taxa StudiedCorals and coral‐dwelling Trapezia crabs.MethodsWe determined the symbiotic relationships between 22 crab species in the genus Trapezia and corals via field survey and extensive literature review. We first developed SDMs for coral and crab species using exclusively abiotic variables (abiotic‐only models for corals and crabs). Then we constructed a second set of models where we accounted for coral distributions into crab predictions by combining model predictions for the two taxa a posteriori (abiotic‐plus‐biotic models for crabs only).ResultsWe obtained 30 commonly accepted coral‐crab symbiotic relationships from nine Trapezia crab and six stony coral species. The abiotic‐only model predictions showed that six corals may lose approximately one‐sixth of suitable ranges under RCP 8.5 in 2040–2050. The two types of models for crabs yielded largely different habitat suitability predictions and accounting for biotic interactions into SDM predictions exacerbates the predicted impacts of climate change on coral‐dwelling crabs.Main ConclusionsOur results show large discrepancies in crab spatial distribution patterns with and without accounting for symbiotic interactions. Our findings highlight the important role of modeller's decision on accounting for biotic interactions when predicting the geographical ranges of coral‐dwelling species, with important implications for designing future conservation and management strategies for marine species.