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Assessing multitemporal calibration for species distribution models
Institution:1. Laboratory of Integrative Research in Biodiversity (PIBiLab), Centro de Ciências Biológicas e da Saúde, Universidade Federal de Sergipe, São Cristóvão-SE 49100-000, Brazil;2. Departamento de Sistemática e Ecologia, Centro de Ciências Exatas e da Natureza, Universidade Federal da Paraíba, João Pessoa, PB 58059-900, Brazil;1. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;2. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China;1. Department of Information Science and Technology, Dalian Maritime University, 116026 Dalian, China;2. Center of Microfluidic and Optoelectronic Sensing, Dalian Maritime University, 116026 Dalian, China
Abstract:Species distribution models (SDMs), the most prominent tool in modern biogeography, rely on the assumptions that (i) species distribution is in equilibrium with the environment and (ii) that climatic niche has been conserved throughout recent geological time. These issues affect the spatial and temporal transferability of SDMs, limiting their reliability for applications such as when studying effects of past climate change on species distribution and extinctions. The integration of paleontological and neontological data for a multitemporal calibration and validation of SDMs has been suggested for improving SDMs flexibility. Here, we provide an empirical test for a multitemporal calibration, employing virtual species (i.e., with perfectly-known distributions) and comparing them directly with monotemporal SDMs (i.e., SDM calibrated in a single time layer). We used 1kyr-interval scenarios throughout the last 22 kyr BP for two ecologically different species in South America (a “hot and wet” species and a “cold and dry” species). Models with multitemporal calibration performed similarly to models with monotemporal calibration, regardless of species, sample sizes, and time frame. However, multitemporal calibration performed better when dealing with non-analogous climates among time layers. By improving the temporal SDMs transferability, multitemporal calibration opens new avenues for integrating fossil and recent occurrence data, which may substantially benefit biogeography and paleoecology.
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