Rintz Cam Ly, Koubbi Philippe, Ramiro-Sánchez Berta, Azarian Clara, Caccavo Jilda Alicia, Cotté Cédric, Goberville Eric, Godet Claire, Hulley Percy Alexander, Le Goff Rémy, Leprieur Fabien, Robuchon Marine, Serandour Baptiste, Leroy Boris
Laboratoire de Biologie Des Organismes et Des Écosystèmes Aquatiques-BOREA, Muséum National d'Histoire Naturelle (MNHN), SU, CNRS, IRD, UA, Paris, France.
Laboratoire D'océanographie et du Climat: Expérimentations et Approches Numériques (LOCEAN/IPSL), UPMC, CNRS, IRD, Muséum National D'histoire Naturelle, Sorbonne Université, Paris, France.
Glob Chang Biol. 2025 Jun;31(6):e70256. doi: 10.1111/gcb.70256.
To predict the spatial responses of biodiversity to climate change, studies typically rely on species-specific approaches, such as species distribution models. In this study, we propose an alternative methodology that investigates the collective response of species groups by modelling biogeographical regions. Biogeographical regions are areas defined by homogeneous species compositions and separated by barriers to dispersal. When climate acts as such a barrier, species within the same region are expected to respond similar to changing climatic conditions, enabling the prediction of entire region shifts in response to future climate scenarios. We applied this approach to the Southern Ocean, which exhibits sharp climatic transitions known as oceanic fronts, focusing on the mesopelagic lanternfishes (family Myctophidae). We compiled occurrence data for 115 lanternfish species from 1950 onwards and employed a network-based analysis to identify two major biogeographical regions: a southern and a subtropical region. These regions were found to be distinct, with minimal overlap in species distributions along the temperature gradient and a separation around 8°C, indicating that temperature likely acts as a climatic barrier. Using an ensemble modelling approach, we projected the response of these regions to future temperature changes under various climate scenarios. Our results suggest a circumpolar expansion of the subtropical region and a contraction of the southern region, with the Southern Ocean becoming a cul-de-sac for southern species. Ultimately, our results suggest that when support is found for the climatic barrier hypothesis, community-level models from a 'group first, then predict' strategy may effectively predict future shifts in species assemblages.
为了预测生物多样性对气候变化的空间响应,研究通常依赖于特定物种的方法,如物种分布模型。在本研究中,我们提出了一种替代方法,即通过对生物地理区域进行建模来研究物种群体的集体响应。生物地理区域是由同质物种组成定义的区域,并由扩散障碍分隔。当气候充当这样的障碍时,同一区域内的物种预计会对不断变化的气候条件做出相似的反应,从而能够预测整个区域对未来气候情景的响应变化。我们将这种方法应用于南大洋,该区域呈现出被称为海洋锋面的急剧气候转变,重点关注中层灯笼鱼(灯笼鱼科)。我们收集了自1950年以来115种灯笼鱼的出现数据,并采用基于网络的分析来确定两个主要的生物地理区域:一个南部区域和一个亚热带区域。发现这些区域是不同的,沿着温度梯度的物种分布重叠最小,且在约8°C处分离,这表明温度可能充当了气候障碍。使用集合建模方法,我们预测了这些区域在各种气候情景下对未来温度变化的响应。我们的结果表明亚热带区域将进行环极扩张,而南部区域将收缩,南大洋将成为南部物种的死胡同。最终,我们的结果表明,当气候障碍假说得到支持时,来自“先群体,后预测”策略的群落水平模型可能有效地预测物种组合的未来变化。