Occurrence–habitat mismatching and niche truncation when modelling distributions affected by anthropogenic range contractions

作者：Sean E. H. Pang, Yiwen Zeng, Jose Don T. De Alban, Edward L. Webb · 发表于：Diversity and Distributions · 年份：2022 · DOI：10.1111/ddi.13544 · 被引用次数：28 · 研究领域：Species Distribution and Climate Change、Wildlife Ecology and Conservation、Ecology and Vegetation Dynamics Studies

Abstract Aims Human‐induced pressures such as deforestation cause anthropogenic range contractions (ARCs). Such contractions present dynamic distributions that may engender data misrepresentations within species distribution models. The temporal bias of occurrence data—where occurrences represent distributions before ( past bias) or after ( recent bias) ARCs—underpins these data misrepresentations. Occurrence–habitat mismatching results when occurrences sampled before contractions are modelled with contemporary anthropogenic variables; niche truncation results when occurrences sampled after contractions are modelled without anthropogenic variables. Our understanding of their independent and interactive effects on model performance remains incomplete but is vital for developing good modelling protocols. Through a virtual ecologist approach, we demonstrate how these data misrepresentations manifest and investigate their effects on model performance. Location Virtual Southeast Asia. Methods Using 100 virtual species, we simulated ARCs with 100‐year land‐use data and generated temporally biased ( past and recent ) occurrence datasets. We modelled datasets with and without a contemporary land‐use variable (conventional modelling protocols) and with a temporally dynamic land‐use variable. We evaluated each model's ability to predict historical and contemporary distributions. Results Greater ARC resulted in greater occurrence–habitat mismatching for datasets with past bias and great...