Climate change is exerting unprecedented effects on the habitats of marine mammals. Common minke whales (Balaenoptera acutorostrata) have suffered immense harm from commercial whaling, and the recovery of this species is likely threatened by climate change. To better manage and conserve this species, it is important to predict its current habitat distribution and the potential change under future climate change scenarios. Such predictions are typically generated by species distribution models (SDMs), which construct a correlation between species occurrence data and its habitat environmental variables. SDMs are commonly constructed at the species level, assuming a homogenous response of the species to climatic variables across their entire geographic range. Spatially segregated populations from the same species inhabit distinct environments and gradually adapt to the local conditions, resulting in niche differentiation among populations. Species-level SDMs that ignore the effects of local adaptation mask differences in population responses to climate change and might present an unrealistic picture of potential species distributions. Based on morphological and genetic evidence, the common minke whale was divided into three populations: the North Atlantic population (NAP), Southern Hemisphere population (SHP) and North Pacific population (NPP); these populations inhabit isolated geographic areas with distinct environmental conditions. We quantified the realized niches of these populations and found evidence of significant ecological niche differentiation. We then constructed SDMs at the species and population levels and compared the predictions from these two types of models under different climate change scenarios. Both types of models projected similar change trends in species range, with a contraction of future suitable habitats for the NAP and SHP and an expansion for the NPP. However, the magnitudes of this change differed; the population-level model projected more optimistic results for the SHP and NAP, indicating less habitat loss. This study highlighted the importance of considering local adaptation when estimating the impact of climate change on species habitat suitability. These spatiotemporal predictions provide essential knowledge for designing climate-adaptive conservation and management strategies, such as the delimitation of mobile marine protected areas (MPAs).

气候变化正在对海洋哺乳动物的栖息地产生前所未有的影响。常见的小须鲸 (尖吻蝾螈) 遭受了商业捕鲸的巨大伤害，该物种的恢复可能受到气候变化的威胁。为了更好地管理和保护该物种，预测其当前栖息地分布和未来气候变化情景下的潜在变化非常重要。这种预测通常由物种分布模型 (SDM) 生成，该模型构建了物种发生数据与其栖息地环境变量之间的相关性。SDM 通常在物种层面构建，假设物种在其整个地理范围内对气候变量的反应是同质的。来自同一物种的空间隔离种群居住在不同的环境中，并逐渐适应当地条件，导致种群之间的生态位分化。忽略局部适应影响的物种级 SDM 掩盖了种群对气候变化的反应差异，并可能呈现出潜在物种分布的不切实际图景。根据形态和遗传证据，将普通小须鲸分为三个种群：北大西洋种群（NAP）、南半球种群（SHP）和北太平洋种群（NPP）；这些人口居住在具有不同环境条件的孤立地理区域。我们量化了这些种群的已实现生态位，并发现了显着生态位分化的证据。然后，我们在物种和种群水平上构建了 SDM，并比较了这两种模型在不同气候变化情景下的预测。两种类型的模型都预测了物种范围的相似变化趋势，未来适合 NAP 和 SHP 的栖息地收缩，而 NPP 则扩大。但是，这种变化的幅度不同。种群水平模型对 SHP 和 NAP 的预测结果更为乐观，表明栖息地丧失较少。这项研究强调了在评估气候变化对物种栖息地适宜性的影响时考虑当地适应的重要性。这些时空预测为设计适应气候的保护和管理战略提供了必要的知识，例如移动海洋保护区 (MPA) 的划界。种群水平模型对 SHP 和 NAP 的预测结果更为乐观，表明栖息地丧失较少。这项研究强调了在估计气候变化对物种栖息地适宜性的影响时考虑当地适应的重要性。这些时空预测为设计适应气候的保护和管理战略提供了必要的知识，例如移动海洋保护区 (MPA) 的划界。种群水平模型对 SHP 和 NAP 的预测结果更为乐观，表明栖息地丧失较少。这项研究强调了在估计气候变化对物种栖息地适宜性的影响时考虑当地适应的重要性。这些时空预测为设计适应气候的保护和管理战略提供了必要的知识，例如移动海洋保护区 (MPA) 的划界。