Data from: 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 average pairwise differences (site-specific comparisons throughout each species’ range) among climate and instream models. Second, ‘congruence’ tests determined how often the same stream segments were assigned high habitat suitability by climate and instream models. Third, Schoener’s <i>D</i> and Warren’s <i>I</i> niche overlap statistics quantified range-wide similarity in predicted habitat suitability values from climate vs. instream models. Equivalence tests revealed small, pairwise differences in habitat suitability between climate and instream models (mean pairwise differences in MaxEnt raw scores for all species < 3×10^-4). Congruence tests showed a strong tendency for climate and instream models to predict high habitat suitability at the same stream segments (median congruence = 68%). <i>D</i> and <i>I</i> statistics reflected a high margin of overlap among climate and instream models (median <i>D</i> = 0.78, median <i>I</i> = 0.96). Overall, we found little support for the hypothesis that SDM predictions are fundamentally different when climate versus instream covariates are used to model fish species’ distributions at the scale of the Columbia Basin.

河流生态系统中的物种分布模型（Species distribution models, SDMs）可通过两种方式纳入气候信息：一是将气温与降水作为河流内环境的替代指标，二是构建独立的水温与水文模型以关联气候与河流内栖息地。后者的建模思路更为优选，但受限于开发水温与水文模型的实操负担。为此，本研究评估了以气候数据为协变量，与以河流内水温、水文数据为协变量时，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：其一为结合物理栖息地变量的气温与降水（气候变量）；其二为水温、水文（河流内变量）与物理栖息地变量。随后采用三种方法对比两类模型的结果：其一，通过等效性检验评估两类模型间的平均成对差异，即在每个物种的分布范围内开展特定点位对比；其二，借助一致性检验判断气候协变量模型与河流内协变量模型将相同河段判定为高栖息地适宜区的频次；其三，通过舍克纳D（Schoener’s D）指数与沃伦I（Warren’s I）生态位重叠统计量，量化两类模型在全分布范围内预测的栖息地适宜度值的相似性。等效性检验结果显示，两类模型的栖息地适宜度得分仅存在微小的成对差异：所有物种的MaxEnt原始得分平均成对差异均小于3×10⁻⁴。一致性检验表明，两类模型在相同河段预测高栖息地适宜度的倾向极强，中位一致性达68%。舍克纳D与沃伦I统计量也反映出两类模型间存在较高的重叠度：中位D值为0.78，中位I值为0.96。总体而言，在哥伦比亚流域尺度下，以气候协变量或河流内协变量建模鱼类物种分布时，"物种分布模型预测结果存在本质差异"的假说几乎未得到本研究的支持。