Incorporating physiological knowledge into correlative species distribution models minimizes bias introduced by the choice of calibration area

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外文摘要：Correlative species distribution models(SDMs)are important tools to estimate species'geographic distribution across space and time,but their reliability heavily relies on the availability and quality of occurrence data.Estimations can be biased when occurrences do not fully represent the environmental requirement of a species.We tested to what extent species'physiological knowledge might influence SDM estimations.Focusing on the Japanese sea cucumber Apostichopus japonicus 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 naïve model that solely depends on environmental correlates,and a physiologically informed model that further incorporates physiological information as priors.We further tested the models'sensitivity to calibration area choices by fitting them with different buffered areas around known presences.Compared with naïve models,the physiologically informed models successfully captured the negative influence of high temperature on A.japonicus and were less sensitive to the choice of calibration area.The naïve 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 physi-ological information where available.

外文关键词：

Bayesian approachClimate changeHabitat suitabilityPhysiological knowledgeSpecies distribution model

作者：

Zhixin Zhang、Jinxin Zhou、Jorge García Molinos、Stefano Mammola、Ákos Bede-Fazekas、Xiao Feng、Daisuke Kitazawa、Jorge Assis、Tianlong Qiu、Qiang Lin

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作者单位：

CAS Key Laboratory of Tropical Marine Bio-resources and Ecology,South China Sea Institute of Oceanology,Chinese Academy of Sciences,Guangzhou 510301,China

Guangdong Provincial Key Laboratory of Applied Marine Biology,South China Sea Institute of Oceanology,Chinese Academy of Sciences,Guangzhou 510301,China

Marine Biodiversity and Ecological Evolution Research Center,South China Sea Institute of Oceanology,Guangzhou 510301,China

Global Ocean and Climate Research Center,South China Sea Institute of Oceanology

Institute of Industrial Science,The University of Tokyo,5-1-5 Kashiwanoha,Kashiwa,Chiba,277-8574,Japan

Arctic Research Center,Hokkaido University,Sapporo,Hokkaido 001-0021,Japan

Finnish Museum of Natural History,University of Helsinki,Helsinki,Finland

Molecular Ecology Group(MEG),Water Research Institute(IRSA),National Research Council of Italy(CNR),28922 Verbania Pallanza,Italy

National Biodiversity Future Center(NBFC),Palermo,Italy

Institute of Ecology and Botany,HUN-REN Centre for Ecological Research,Vácrátót,Hungary

Department of Environmental and Landscape Geography,ELTE Eötvös Loránd University,Budapest,Hungary

Department of Biology,University of North Carolina,Chapel Hill,NC 27599,USA

Centre of Marine Sciences,University of Algarve,Campus de Gambelas,Faro,Portugal

CAS Key Laboratory of Experimental Marine Biology,Institute of Oceanology,Chinese Academy of Sciences,Qingdao 266071,China

University of Chinese Academy of Sciences,Beijing 100049,China

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出版年：

2024

DOI：

10.1007/s42995-024-00226-0

海洋生命科学与技术(英文)

ISSN：

年,卷(期)：2024.6(2)