Item

Abstract

Concern about how climate change affects marine ecosystems is growing, despite international commitments to reduce CO2 emissions. Predicting amphipod species' responses to ocean warming is critical given their high abundance and key ecological roles in marine ecosystems. We selected 35 widespread benthic amphipod species with at least 30 unique occurrence records after thinning from two or more biogeographical regions and classified them according to depth and feeding strategy. Following spatial thinning, 17 species retained sufficient occurrence records for Maximum Entropy (MaxEnt) modeling; of which 15 met the model evaluation criteria by having a Partial ROC value below 1 or a 5% omission rate exceeding 0.2. We projected species distributions under the low-emission RCP 2.6 and high-emission RCP 8.5 scenarios for 2050 and 2100. To compare species responses among feeding groups, we used linear mixed-effects models with feeding type, scenario_time combination, and their interaction as fixed effects and species identity as a random effect. Species were also classified by depth, but statistical comparisons among depth groups were not performed because of limited species representation. Projected distributions showed substantial species-specific distribution shifts, including both gains and losses of suitable habitat and changes in areas of high species richness. Linear mixed-effects models showed that potential future changes in suitable habitat area did not differ significantly among feeding groups, whereas centroid shifts were significantly influenced by the interaction between feeding type and scenario–time combinations. This indicates that trophic strategy influences the spatial response of amphipods to future climate change. These findings highlight that climate change may dramatically alter the functional composition of benthic communities and their ecological roles, beyond simple changes in species distributions. Incorporating trophic identity and functional roles into climate impact assessments will be essential for predicting ecosystem responses and informing conservation strategies that safeguard marine ecosystems functioning under future climate change. This approach will improve predictions of ecosystem responses and strengthen conservation and management strategies aimed at maintaining ecosystem functioning in a rapidly changing ocean.