Dou Hongliang, Gao Ruiqi, Wu Fei, Gao Haiyang
Guangdong Provincial Key Laboratory of Silviculture, Protection and Utilization, Guangdong Academy of Forestry, Guangzhou 510520, China.
Biology (Basel). 2025 Aug 1;14(8):976. doi: 10.3390/biology14080976.
Identifying habitat characteristics is essential for conserving critically endangered species. When quantifying species habitat characteristics, ignoring data types may lead to misunderstandings about species' specific habitat requirements. This study focused on the critically endangered Chinese pangolin in Guangdong Province, China, and divided the study area into 600 m × 600 m grids based on its average home range. The burrow number within each grid was obtained through line transect surveys, with burrow numbers/line transect lengths used as direct indicators of habitat utilization intensity. The relationships with sixteen environmental variables, which could be divided into three categories, including topographic, human disturbance and land cover composition, were quantified using the GAM method. We also converted continuous data into binary data (0, 1), constructed GAMs and compared them with habitat utilization intensity models. Our results indicate that the habitat utilization intensity model identified profile curvature and slope as primary factors, showing a nonlinear response to profile curvature ( = 5.610, = 0.014) and a positive relationship with slope ( = 1.000, = 0.006). The presence-absence model emphasized distance to water ( = 1.000, = 0.014), slope ( = 1.709, = 0.043) and aspect ( = 2.000, = 0.026). The intensity model explained significantly more deviance, captured complex nonlinear relationships and supported higher model complexity without overfitting. This study demonstrates that habitat utilization intensity data provides a more ecologically informative basis for in situ conservation (e.g., identifying core habitats), and the process from habitat selection to habitat utilization should be integrated to reveal species' habitat characteristics.
识别栖息地特征对于保护极度濒危物种至关重要。在量化物种栖息地特征时,忽略数据类型可能会导致对物种特定栖息地需求的误解。本研究聚焦于中国广东省极度濒危的中华穿山甲,并根据其平均活动范围将研究区域划分为600米×600米的网格。通过样线调查获取每个网格内的洞穴数量,将洞穴数量/样线长度用作栖息地利用强度的直接指标。使用广义相加模型(GAM)方法量化了与16个环境变量的关系,这些变量可分为三类,包括地形、人为干扰和土地覆盖组成。我们还将连续数据转换为二元数据(0, 1),构建了广义相加模型,并将其与栖息地利用强度模型进行比较。我们的结果表明,栖息地利用强度模型确定剖面曲率和坡度为主要因素,对剖面曲率呈现非线性响应(= 5.610,= 0.014),与坡度呈正相关(= 1.000,= 0.006)。存在-缺失模型强调距水距离(= 1.000,= 0.014)、坡度(= 1.709,= 0.043)和坡向(= 2.000,= 0.026)。强度模型解释的偏差显著更多,捕捉到复杂的非线性关系,并支持更高的模型复杂度而不过度拟合。本研究表明,栖息地利用强度数据为就地保护(例如识别核心栖息地)提供了更具生态信息的基础,并且应整合从栖息地选择到栖息地利用的过程以揭示物种的栖息地特征。