On the use of climate covariates in aquatic species distribution models: are we at risk of throwing the baby out?

Species distribution models (SDMs) in river ecosystems can incorporate climate information by using air temperature and precipitation as surrogate measures of instream conditions or by using independent models of water temperature and hydrology to link climate to instream habitat. The latter approach is preferable but constrained by the logistical burden of developing water temperature and hydrology models. We therefore assessed whether regional scale, freshwater SDM predictions are fundamentally different when climate data versus instream temperature and hydrology are used as covariates. Maximum Entropy (MaxEnt) SDMs were built for 15 freshwater fishes using one of two covariate sets: (1) air temperature and precipitation (climate variables) in combination with physical habitat variables; or (2) water temperature, hydrology (instream variables) and physical habitat. Three procedures were then used to compare results from climate vs. instream models. First, equivalence tests assessed av...

河流生态系统中的物种分布模型（Species Distribution Models, SDMs）可通过两种途径纳入气候因子：一是将气温与降水作为河流生境状态的替代指标，二是构建独立的水温和水文模型以建立气候与河流生境的关联。其中后者的方法更具优势，但受限于开发水温和水文模型的后勤实施负担。为此本研究评估了以气候数据作为协变量，与以河流水温、水文数据作为协变量时，区域尺度淡水物种分布模型的预测结果是否存在本质差异。研究针对15种淡水鱼类构建了最大熵（Maximum Entropy, MaxEnt）物种分布模型，协变量集分为两类：（1）结合物理生境变量的气温与降水（气候变量）；（2）结合物理生境变量的水温与水文（河流生境变量）。随后采用三种流程对比气候驱动模型与河流生境驱动模型的结果：首先，等价性检验用于评估……