基于生态位模型的秦岭山系林麝生境预测

生境评价和预测是对物种进行有效保护的基础。利用林麝痕迹点、自然环境及人类干扰空间数据,分别用两种生态位模型MAXENT和ENFA,预测了秦岭山系林麝的生境分布,并对结果进行了阈值依赖和非阈值依赖比较。探讨了林麝生境选择与环境因子的关系。结果表明,两种生态位模型预测效果都较好,但MAXNET模型预测效果更为优秀。秦岭山系林麝生境主要集中在主峰太白山及周边地区中高海拔的森林中,共有生境面积10764.4km²,现有的保护区保护了 3500.9km²的林麝生境,还有67.5%的林麝生境处于保护空缺状态。交通干道、农田和居民点是影响林麝生境选择的主要人类干扰因子。为更有效地保护该地区的林麝及其生境,有必要对现有保护区进行规划调整,使林麝生境集中分布区都得到有效保护,并恢复隔离的林麝生境之间的迁徙廊道。

Habitat prediction for forest musk deer (Moschus berezovskii) in Qinling mountain range based on niche model

Habitat assessment and prediction is the base for protection of endangered species. In this paper, MAXENT and ENFA were applied to predict habitat for forest musk deer in Qinling mountain range, with evidence data of this species, and other environment factors. Prediction results were evaluated by both of threshold-dependent and threshold-independent methods. And the environmental factors and habitat selection of forest musk deer were then analyzed. Results showed that both models showed good prediction ability, and MAXENT gave a better prediction than that of ENFA. The habitat of forest musk deer was mainly distributed in Taibai Mountain and surrounding areas in Qinling mountain range, with the total area of 10764.4km². The current nature reserves protected only 3500.9km² of the habitat of this species, and 67.5% of the habitat was in conservation gap. For effective protection of forest musk deer in this area, it is necessary to adjust the current nature reserves for covering most of the concentration habitat, and to restore the corridors among habitat patches.