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Estimations can be biased when occurrences do not fully represent the environmental requirement of a species. We tested to what extent species\u2019 physiological knowledge might influence SDM estimations. Focusing on the Japanese sea cucumber <jats:italic>Apostichopus japonicus<\/jats:italic> within the coastal ocean of East Asia, we compiled a comprehensive dataset of occurrence records. We then explored the importance of incorporating physiological knowledge into SDMs by calibrating two types of correlative SDMs: a na\u00efve model that solely depends on environmental correlates, and a physiologically informed model that further incorporates physiological information as priors. We further tested the models\u2019 sensitivity to calibration area choices by fitting them with different buffered areas around known presences. Compared with na\u00efve models, the physiologically informed models successfully captured the negative influence of high temperature on <jats:italic>A. japonicus<\/jats:italic> and were less sensitive to the choice of calibration area. The na\u00efve models resulted in more optimistic prediction of the changes of potential distributions under climate change (i.e., larger range expansion and less contraction) than the physiologically informed models. Our findings highlight benefits from incorporating physiological information into correlative SDMs, namely mitigating the uncertainties associated with the choice of calibration area. Given these promising features, we encourage future SDM studies to consider species physiological information where available.<\/jats:p>","DOI":"10.1007\/s42995-024-00226-0","type":"journal-article","created":{"date-parts":[[2024,5,13]],"date-time":"2024-05-13T10:01:30Z","timestamp":1715594490000},"page":"349-362","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Incorporating physiological knowledge into correlative species distribution models minimizes bias introduced by the choice of calibration area"],"prefix":"10.1007","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3457-2934","authenticated-orcid":false,"given":"Zhixin","family":"Zhang","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1806-944X","authenticated-orcid":false,"given":"Jinxin","family":"Zhou","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7516-1835","authenticated-orcid":false,"given":"Jorge","family":"Garc\u00eda Molinos","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4471-9055","authenticated-orcid":false,"given":"Stefano","family":"Mammola","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2905-338X","authenticated-orcid":false,"given":"\u00c1kos","family":"Bede-Fazekas","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4638-3927","authenticated-orcid":false,"given":"Xiao","family":"Feng","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7246-3210","authenticated-orcid":false,"given":"Daisuke","family":"Kitazawa","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6624-4820","authenticated-orcid":false,"given":"Jorge","family":"Assis","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3037-3767","authenticated-orcid":false,"given":"Tianlong","family":"Qiu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9916-7761","authenticated-orcid":false,"given":"Qiang","family":"Lin","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,5,13]]},"reference":[{"key":"226_CR1","doi-asserted-by":"publisher","first-page":"541","DOI":"10.1111\/ecog.01132","volume":"38","author":"ME Aiello-Lammens","year":"2015","unstructured":"Aiello-Lammens ME, Boria RA, Radosavljevic A, Vilela B, Anderson RP (2015) spThin: an R package for spatial thinning of species occurrence records for use in ecological niche models. 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