• Energy Research

Abstract Climate change is one of the most serious global environmental problems and it is of great importance to understand how species respond to climate change. Species distribution models (SDMs) have been regarded as an effective tool to examine the impacts of climate change on species’ potential distribution. In this study, we developed a SDM for a marine fish, the Japanese whiting Sillago japonica by using records of its occurrence and five predictor variables (ocean depth, distance to shore, mean sea surface temperature, salinity, and currents velocity) and predicted its habitat suitability for current conditions and under scenarios of future climates. The SDM suggests that ocean depth, distance to shore, and temperature are the three most important predictor variables determining the distribution of S. japonica. Our SDM accurately predicted the current distribution of the species, with values of true skill statistics and area under the receiver operating characteristic curve above 0.95. Under future climate scenarios, the suitable habitat of S. japonica is predicted to become smaller in size and to shift northward. Differences between climate change scenarios for 2040–2050 and 2090–2100 showed that this species will lose more suitable habitat as climate change progresses over time. Future fisheries management strategies should take this range contraction and associated northward shift into account.

Abstract Climate change is one of the most serious global environmental problems and it is of great importance to understand how species respond to climate change. Species distribution models (SDMs) have been regarded as an effective tool to examine the impacts of climate change on species’ potential distribution. In this study, we developed a SDM for a marine fish, the Japanese whiting Sillago japonica by using records of its occurrence and five predictor variables (ocean depth, distance to shore, mean sea surface temperature, salinity, and currents velocity) and predicted its habitat suitability for current conditions and under scenarios of future climates. The SDM suggests that ocean depth, distance to shore, and temperature are the three most important predictor variables determining the distribution of S. japonica. Our SDM accurately predicted the current distribution of the species, with values of true skill statistics and area under the receiver operating characteristic curve above 0.95. Under future climate scenarios, the suitable habitat of S. japonica is predicted to become smaller in size and to shift northward. Differences between climate change scenarios for 2040–2050 and 2090–2100 showed that this species will lose more suitable habitat as climate change progresses over time. Future fisheries management strategies should take this range contraction and associated northward shift into account.