School of Ecology and Environment Science, Yunnan University, Kunming, 650031, Yunnan Province, People's Republic of China.
Research Institute of Forestry Policy and Information, Chinese Academy of Forestry, Beijing, 100091, People's Republic of China.
Sci Rep. 2023 Aug 22;13(1):13673. doi: 10.1038/s41598-023-40678-5.
Microclimate ecology is attracting renewed attention because of its fundamental importance in understanding how organisms respond to climate change. Many hot issues can be investigated in desert ecosystems, including the relationship between species distribution and environmental gradients (e.g., elevation, slope, topographic convergence index, and solar insolation). Species Distribution Models (SDMs) can be used to understand these relationships. We used data acquired from the important desert plant Nitraria tangutorum Bobr. communities and desert topographic factors extracted from LiDAR (Light Detection and Ranging) data of one square kilometer in the inner Mongolia region of China to develop SDMs. We evaluated the performance of SDMs developed with a variety of both the parametric and nonparametric algorithms (Bioclimatic Modelling (BIOCLIM), Domain, Mahalanobi, Generalized Linear Model, Generalized Additive Model, Random Forest (RF), and Support Vector Machine). The area under the receiver operating characteristic curve was used to evaluate these algorithms. The SDMs developed with RF showed the best performance based on the area under curve (0.7733). We also produced the Nitraria tangutorum Bobr. distribution maps with the best SDM and suitable habitat area of the Domain model. Based on the suitability map, we conclude that Nitraria tangutorum Bobr. is more suited to southern part with 0-20 degree slopes at an elevation of approximately 1010 m. This is the first attempt of modelling the effects of topographic heterogeneity on the desert species distribution on a small scale. The presented SDMs can have important applications for predicting species distribution and will be useful for preparing conservation and management strategies for desert ecosystems on a small scale.
微气候生态学因其在理解生物如何应对气候变化方面的基本重要性而重新引起关注。在沙漠生态系统中可以研究许多热点问题,包括物种分布与环境梯度(例如海拔、坡度、地形汇聚指数和太阳辐射)之间的关系。物种分布模型(SDM)可用于理解这些关系。我们使用了从中国内蒙古地区一个平方公里的 LiDAR(光探测和测距)数据中提取的重要沙漠植物白刺 Nitraria tangutorum Bobr. 群落数据和沙漠地形因子来开发 SDM。我们评估了使用多种参数和非参数算法(生物气候建模(BIOCLIM)、域、马氏距离、广义线性模型、广义加性模型、随机森林(RF)和支持向量机)开发的 SDM 的性能。我们使用接收者操作特征曲线下的面积来评估这些算法。基于曲线下面积(0.7733),RF 开发的 SDM 表现出最佳性能。我们还使用最佳 SDM 和域模型的适宜生境面积生成了白刺 Nitraria tangutorum Bobr. 分布图。根据适宜性图,我们得出结论,白刺 Nitraria tangutorum Bobr. 更适合坡度在 0-20 度、海拔约 1010 米的南部地区。这是首次尝试在小尺度上模拟地形异质性对沙漠物种分布的影响。所提出的 SDM 可用于预测物种分布,对于制定小尺度沙漠生态系统的保护和管理策略将非常有用。