摘要:在动物生境研究中，移动生境和卧息生境是生境研究的焦点。开展移动生境和卧息生境选择，并在此基础上进行生境评价，有利于深入了解动物对移动和卧息生境条件的需求，制定科学合理的栖息地保护计划。以东北虎（Panthera tigris altaica）的主要猎物物种之一-狍（Capreolus pygargus）为研究对象，于2017-2019年冬季积雪覆盖期在老爷岭南部通过随机布设28个大样方和84条用于足迹链跟踪的样线收集狍的移动点和卧息点信息，再结合近年来收集的东北虎出现点，利用广义可加模型（GAM）和最大熵模型（MaxEnt）进行狍移动、卧息生境选择及评价研究。移动生境选择研究表明，狍在移动的过程中偏好选择坡度小、距农田距离>500 m、远离道路、居民点和低海拔或较高海拔的区域；移动生境评价分析表明，移动适宜和次适宜生境面积之和为1318.16 km²，占研究区域面积的51.28%，当加入虎活动点影响因子后，狍移动适宜和次适宜生境面积之和为901.52 km²，适宜和次适宜生境面积之和减少了31.61%。狍卧息生境选择研究表明，水源、农田、道路和雪深是影响狍卧息的关键因素，其中雪深对狍卧息生境选择的贡献率达到70.13%；卧息生境评价表明，卧息适宜和次适宜生境面积之和为1243.77 km²，占研究区域面积的48.39%，当加入虎出现点因子后，适宜生境和次适宜生境面积之和减少了61.00%，仅为485.02 km²。研究认为，虎的出现对狍移动和卧息生境选择均产生影响，虎的活动及捕食行为可能会减少狍的活动范围和频次，狍远离虎活动区域卧息休息，压缩了狍适宜卧息的空间。



Abstract:The conservation of wide-ranging species presents challenges in a world of increasingly human-dominated landscapes, which forces animals to occupy human-modified landscapes. Although analyzing habitat selection and identifying suitable habitats are important in supporting natural recolonization, these actions are rarely validated owing to difficulties in monitoring animal colonization events. Habitat studies are, however, fundamentally important for species conservation policies and management decisions. Analyses of habitat selection and evaluation for animal conservation, especially moving and bedding behaviors, are often in short supply. We conducted a study on habitat selection and evaluation in roe deer (Capreolus pygargus), which is one of the main prey species of the Amur tiger (Panthera tigris altaica) in southern Laoyeling, Heilongjiang Province. A large part of southern Laoyeling is inhabited by the Amur tiger and the Leopard National Park and is a key habitat for tigers and ungulates. It is one of the main distribution regions of the Amur tiger and its prey. Systematic studies are required to thoroughly investigate the effects of landscape factors and tiger occurrences on the selection of suitable habitats by roe deer, which are necessary for wildlife conservation. Such data were collected by conducting 28 plot surveys and 84 lines for footprint chain tracking during the winters from 2017 to 2019 in southern Laoyeling of Heilongjiang Province. Furthermore, data of tiger occurrences were recently collected and integrated with roe deer data into a habitat analysis. Generalized additive model (GAM) and Maximum Entropy (MaxEnt), based on ecological niche theory, were used to assess the response of roe deer to different landscape factors and to evaluate the suitability of habitats for roe deer during the snow season. From our investigation of roe deer movement between habitats, we found that roe deer preferred habitats including flat with small slopes, less than 500 m from farmland, at low or high-elevation areas, and in areas without roads and settlements. The results of our habitat evaluation for movement without tiger occurrence data showed that the combined area of suitable large and medium-sized habitats was 1318.16 km² (51.28% of the study area), but was only 901.52 km² (a decline of 31.61%) if tiger occurrence data were used as a factor in the habitat selection model for roe deer. For bedding habitats, our results demonstrate that factors including river, farmland, road and snow depth affect the habitat selection of roe deer. Among them, snow depth contributed 70.13% to the bedding habitat selection of roe deer. The results of bedding habitat evaluation, without tiger occurrence data, showed that the combined area of suitable large and medium-sized habitats was 1243.77 km² (48.39% of the study area), but was only 485.02 km² (decline of 61.00%) if tiger occurrence data were included as a factor in the roe deer habitat selection model. Our results suggest that predator-prey interactions may result in strong spatial patterns of avoidance. We suggest that the occurrence of tigers has an ecological effect on the habitat selection of roe deer and makes habitats less suitable for roe deer. Roe deer may, in fact, be more likely to avoid specific habitats or landscape features that increase their vulnerability to predation.





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