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：一是以气温与降水作为河道内环境的替代指标，二是构建独立的水温与水文模型以联结气候与河道内生境。其中后一种方法更为合理，但受限于开发水温与水文模型所需的后勤工作量。因此，本研究旨在评估：当以气候数据作为协变量，与以河道内水温、水文作为协变量时，区域尺度淡水SDMs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）气温、降水（气候变量）与物理生境变量的组合；（2）河道内水温、水文（河道内环境变量）与物理生境变量的组合。

随后采用三种方法对比两类模型的结果：其一为等价性检验，评估所有物种分布范围内逐位点比对下，两类模型间的平均成对差异；其二为“一致性”检验，统计气候模型与河道内环境模型将相同河段判定为高生境适宜性的频率；其三为Schoener’s D与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生境适宜性值的相似性。

等价性检验结果显示，两类模型的生境适宜性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，气候模型与河道内环境模型在相同河段预测高生境适宜性的倾向极强（中位一致性率为68%）。Schoener’s D与Warren’s I统计量反映出两类模型的重叠度较高（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模拟鱼类物种分布时，本研究未发现足够证据支持“使用气候协变量与河道内环境协变量的SDM预测结果存在本质差异”这一假说。