SS5_stats_mean.csv from The influence of scale-dependent geodiversity on species distribution models in a biodiversity hotspot

Improving models of species' distributions is essential for conservation, especially in light of global change. Species distribution models (SDMs) often rely on mean environmental conditions, yet species distributions are also a function of environmental heterogeneity and filtering acting at multiple spatial scales. Geodiversity, which we define as the variation of abiotic features and processes of Earth's entire geosphere (inclusive of climate), has potential to improve SDMs and conservation assessments, as they capture multiple abiotic dimensions of species niches, however they have not been sufficiently tested in SDMs. We tested a range of geodiversity variables computed at varying scales using climate and elevation data. We compared predictive performance of MaxEnt SDMs generated using CHELSA bioclimatic variables to those also including geodiversity variables for 31 mammalian species in Colombia. Results show the spatial grain of geodiversity variables affects SDM performance. Some variables consistently exhibited an increasing or decreasing trend in variable importance with spatial grain, showing slight scale-dependence and indicating that some geodiversity variables are more relevant at particular scales for some species. Incorporating geodiversity variables into SDMs, and doing so at the appropriate spatial scales, enhances the ability to model species-environment relationships, thereby contributing to the conservation and management of biodiversity.This article is part of the Theo Murphy meeting issue ‘Geodiversity science for society’.

优化物种分布模型对生物多样性保护至关重要，在全球变化的背景下尤为如此。物种分布模型（Species Distribution Models，SDMs）通常依赖平均环境条件，但物种分布同时也是多空间尺度下环境异质性与环境过滤过程共同塑造的结果。地质多样性（Geodiversity）指地球全圈层（涵盖气候）的非生物特征与过程的变异程度，其具备优化物种分布模型与保护评估的潜力——因其能够捕捉物种生态位的多个非生物维度，但目前其在物种分布模型中的应用尚未得到充分验证。本研究利用气候与高程数据，构建了多空间尺度下的一系列地质多样性变量并开展测试。针对哥伦比亚境内的31种哺乳动物，本研究对比了仅使用CHELSA生物气候变量构建的最大熵（MaxEnt）物种分布模型，与同时纳入地质多样性变量的模型的预测性能。结果表明，地质多样性变量的空间粒度会影响物种分布模型的预测性能。部分变量的重要性随空间粒度变化呈现持续上升或下降的趋势，表现出轻微的尺度依赖性，这表明部分地质多样性变量在特定空间尺度下对特定物种的模型构建更具相关性。将地质多样性变量纳入物种分布模型，并选择合适的空间尺度开展建模，能够提升物种-环境关系的模拟能力，进而为生物多样性保护与管理提供支撑。本文属于《面向社会的地质多样性科学》Theo Murphy会议专题特刊的一部分。