Volume 41 Issue 3
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WANG Xiangfu, LI Yuanhui, WANG Weifeng, SUN Jiejie, WANG Qian, DONG Wenting, WANG Rongnü, YANG Yaqi. Impact of land use and climate change on potential suitable habitats of snow leopards (Panthera uncia) in Qinghai Province[J]. Journal of Zhejiang A&F University, 2024, 41(3): 526-534. doi: 10.11833/j.issn.2095-0756.20230259
Citation: WANG Xiangfu, LI Yuanhui, WANG Weifeng, SUN Jiejie, WANG Qian, DONG Wenting, WANG Rongnü, YANG Yaqi. Impact of land use and climate change on potential suitable habitats of snow leopards (Panthera uncia) in Qinghai Province[J]. Journal of Zhejiang A&F University, 2024, 41(3): 526-534. doi: 10.11833/j.issn.2095-0756.20230259
shu

Impact of land use and climate change on potential suitable habitats of snow leopards (Panthera uncia) in Qinghai Province

doi: 10.11833/j.issn.2095-0756.20230259
  • 1.

    Key Laboratory of National Forestry and Grassland Administration on Ecological Hydrology and Disaster Prevention in Arid Regions, Northwest Surveying and Planning Institute, National Forestry and Grassland Administration, Xi’an 710048, Shaanxi, China

  • 2.

    Co-innovation Center for Sustainable Forestry in Southern China, College of Ecology and Environment , Nanjing Forestry University, Nanjing 210037, Jiangsu, China

  • Received Date: 2023-04-18
  • Accepted Date: 2024-02-27
  • Rev Recd Date: 2024-02-24
    • Available Online: 2024-05-22
  • Publish Date: 2024-05-22
  •   Objective  The aim of this study is to simulate suitable habitat changes of snow leopards (Panthera uncia) under land use change before and after Natural Forest Protection Project (NFPP) and different climate scenarios, which has practical significance for rare animal conservation in alpine mountains.  Method  Total 22 environmental variables that might have an impact on the distribution of snow leopards were selected and the land use data in 2000 and 2020 were used to represent the changes in land use type before and after the implementation of NFPP. The maximum entropy model (MaxEnt) was used to simulate the distribution change of suitable habitats for snow leopards, and the potential suitable habitats for snow leopards in 2050 under two climate scenarios, namely RCP 4.5 and RCP 8.5, were simulated.   Result  Before the implementation of NFPP, the high suitable area of snow leopards in Qinghai Province was 117 900 km2, the medium suitable area was 119 600 km2, and the low suitable area was 229 600 km2. The total suitability distribution area was 467 100 km2 (accounting for 64.7% of the study area). After the implementation of NFPP, the high, medium, and low suitable areas of snow leopards were 117 800, 117 700 and 241 400 km2, respectively, and the total suitable area increased to 476 900 km2 (accounting for 66.0% of the study area). The simulation results of future scenarios showed that by 2050, the suitable habitat of snow leopards in Qinghai Province would generally show a trend of contraction and agglomeration, with a certain degree of decrease in the areas of high, medium and low suitable habitats compared with 2020. Among them, the medium suitable habitats would decrease by 1 400 and 7 200 km2 under RCP 4.5 and RCP 8.5 scenarios, respectively, while the high and medium suitable habitat area would decrease by 3 200 and 4 900 km2, respectively.   Conclusion  The land use changed from 2000 to 2020, with a slight increase in the suitable habitat for snow leopards, inferring that NFPP has not led to the expansion of sirable habitat for snow leopards. A future warming climate will have a negative impact on the suitable habitat for snow leopards. Therefore, forestry management departments should strengthen monitoring of snow leopard activities and develop conservation strategies in advance for endangered wildlife such as snow leopards under climate change. [Ch, 3 tab. 42 ref.]
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Impact of land use and climate change on potential suitable habitats of snow leopards (Panthera uncia) in Qinghai Province

doi: 10.11833/j.issn.2095-0756.20230259
  • 1. Key Laboratory of National Forestry and Grassland Administration on Ecological Hydrology and Disaster Prevention in Arid Regions, Northwest Surveying and Planning Institute, National Forestry and Grassland Administration, Xi’an 710048, Shaanxi, China
  • 2. Co-innovation Center for Sustainable Forestry in Southern China, College of Ecology and Environment , Nanjing Forestry University, Nanjing 210037, Jiangsu, China
  • Received Date: 2023-04-18
  • Accepted Date: 2024-02-27
  • Rev Recd Date: 2024-02-24
  • Available Online: 2024-05-22
  • Publish Date: 2024-05-22

Abstract:   Objective  The aim of this study is to simulate suitable habitat changes of snow leopards (Panthera uncia) under land use change before and after Natural Forest Protection Project (NFPP) and different climate scenarios, which has practical significance for rare animal conservation in alpine mountains.  Method  Total 22 environmental variables that might have an impact on the distribution of snow leopards were selected and the land use data in 2000 and 2020 were used to represent the changes in land use type before and after the implementation of NFPP. The maximum entropy model (MaxEnt) was used to simulate the distribution change of suitable habitats for snow leopards, and the potential suitable habitats for snow leopards in 2050 under two climate scenarios, namely RCP 4.5 and RCP 8.5, were simulated.   Result  Before the implementation of NFPP, the high suitable area of snow leopards in Qinghai Province was 117 900 km2, the medium suitable area was 119 600 km2, and the low suitable area was 229 600 km2. The total suitability distribution area was 467 100 km2 (accounting for 64.7% of the study area). After the implementation of NFPP, the high, medium, and low suitable areas of snow leopards were 117 800, 117 700 and 241 400 km2, respectively, and the total suitable area increased to 476 900 km2 (accounting for 66.0% of the study area). The simulation results of future scenarios showed that by 2050, the suitable habitat of snow leopards in Qinghai Province would generally show a trend of contraction and agglomeration, with a certain degree of decrease in the areas of high, medium and low suitable habitats compared with 2020. Among them, the medium suitable habitats would decrease by 1 400 and 7 200 km2 under RCP 4.5 and RCP 8.5 scenarios, respectively, while the high and medium suitable habitat area would decrease by 3 200 and 4 900 km2, respectively.   Conclusion  The land use changed from 2000 to 2020, with a slight increase in the suitable habitat for snow leopards, inferring that NFPP has not led to the expansion of sirable habitat for snow leopards. A future warming climate will have a negative impact on the suitable habitat for snow leopards. Therefore, forestry management departments should strengthen monitoring of snow leopard activities and develop conservation strategies in advance for endangered wildlife such as snow leopards under climate change. [Ch, 3 tab. 42 ref.]

WANG Xiangfu, LI Yuanhui, WANG Weifeng, SUN Jiejie, WANG Qian, DONG Wenting, WANG Rongnü, YANG Yaqi. Impact of land use and climate change on potential suitable habitats of snow leopards (Panthera uncia) in Qinghai Province[J]. Journal of Zhejiang A&F University, 2024, 41(3): 526-534. doi: 10.11833/j.issn.2095-0756.20230259
Citation: WANG Xiangfu, LI Yuanhui, WANG Weifeng, SUN Jiejie, WANG Qian, DONG Wenting, WANG Rongnü, YANG Yaqi. Impact of land use and climate change on potential suitable habitats of snow leopards (Panthera uncia) in Qinghai Province[J]. Journal of Zhejiang A&F University, 2024, 41(3): 526-534. doi: 10.11833/j.issn.2095-0756.20230259
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  • 不合理的土地利用会影响生态环境的稳定性，同时对生物多样性造成巨大影响，严重威胁物种的生存与繁衍。天然林资源保护工程实施20多年以来，森林资源得到了很好的保护和恢复，森林面积和蓄积实现了双增长，动植物资源也变得丰富，生物多样性得到有效保护[1−2]。天然林资源保护工程实施前后，土地利用类型发生了重大转变。这种转变主要表现为乔灌林地面积的扩张以及裸地面积的削减，其中灌木林地增加了近1.3万 km2 [3]，极大丰富了动植物栖息地，为野生动物提供了更多可能的适生区。甘肃省对林业资源的保护增加了当地野生动物数量[4]，这表明天然林资源保护工程实施引起的乔灌草等土地利用类型面积的扩张有利于野生动物的栖息和繁衍。近年来全球气候变化问题日趋严重，造成部分动植物栖息地丧失，同时也破坏了生态系统中物种间关系的平衡，显著降低了生态系统的生物多样性[4]。青海省地处青藏高原东北部，生态系统脆弱，在很大程度上受到气候变化的影响[5]。

    模拟濒危物种的适生区分布对确定濒危物种保护区并制定相关保护措施具有重要意义[6]。洪洋等[7]分析了卧龙自然保护区的雪豹Panthera uncia生境选择偏好与食源结构特征。李欣海等[8]利用物种分布模型和距离抽样评估了三江源藏野驴Equus kiang、藏原羚Procapra picticaudata和藏羚羊Pantholops hodgsonii的数量[5]。宓春荣等[9]发现：物种分布模型预测的高适宜分布区有利于提高发现稀有种的概率，从而增强调查的针对性。李芳菲等[10]利用最大熵模型(Maximum Entropy，MaxEnt)结合气候、地形和人为干扰等关键环境变量对雪豹在祁连山山区的生境适宜性进行了评估和分析。杨子文等[11]利用MaxEnt模型对当前和未来全球不同发展模式引起的气候变化对雪豹适宜生境的影响进行了模拟预测和分析评估。然而，上述研究未能考虑灌丛、草地和雪山等土地利用类型的变化情况，且未考虑土地利用的影响。

    雪豹是猫科Felidae豹属Panthera哺乳动物，被人们称为“高海拔生态系统健康与否的气压计”。中国是雪豹重点分布的国家之一，拥有60%的雪豹栖息地，天山、青海等高海拔陡峭偏远地区是雪豹的主要分布地。20世纪过度的人为捕杀以及植被退化，导致雪豹种群数量逐年下降。2008年，雪豹被世界自然保护联盟(IUCN)评定为濒危物种[12]，是中国一级重点保护野生动物[13]。近年来，随着一系列生态工程和相关保护工作的实施，雪豹保护取得了一定的成效[13]，但是日益加剧的气候变化仍然对雪豹未来的生存和发展构成较大的威胁。因此，本研究利用物种分布模型，模拟雪豹在天然林资源保护工程实施前后以及未来2种气候情境下雪豹的适宜生境，探究天然林资源保护工程实施前后土地利用类型的转变和气候变化对雪豹适生区的影响，以期揭示天然林资源保护工程实施后土地利用类型的转变对濒危野生动物保护的积极作用，并为气候变化下制定雪豹的保护策略提供一定的理论参考。

    • 1.   材料与方法

      1.1.   研究区概况

    • 青海省地处青藏高原东北部，全省80%以上的区域为高原，地理坐标为31°36′~39°19′N，89°35′~103°04′E，总面积为72.23 万km2，全省平均海拔为3 000 m以上，其中海拔4 000~5 000 m地区占全省总面积的54%。地势总体呈西高东低，南北高中部低，地貌复杂多样，是雪豹的重要集中分布区。青海省属典型的高原大陆性气候，年平均气温为−5.1~9.0 ℃，最冷月1月平均气温为−17.4~−4.7 ℃，最热月7月平均气温为5.8~20.2 ℃。全省降水量呈由东南向西北逐渐减少的分布趋势，境内绝大部分地区年降水量小于400.0 mm。青海有高等植物2 700多种，占全国维管束植物种数的9.6%，其中有许多是中国特有或青海特有的植物。目前，青海有14种珍稀、濒危植物列入国家级重点保护范围，57种野生植物列入省级重点保护范围。青海野生动物资源较丰富。根据最新普查资料，青海有陆栖脊椎动物约1 100种，鸟类294种，占全国已知鸟类种数的1/4；兽类103种，占全国已知兽类种数的1/3，其中受国家重点保护的珍稀鸟兽达74种。青藏高原特有的10余种珍禽异兽总量超过30万头(只)。

      • 1.2.   物种分布模型的选择

    • 物种分布模型(species distribution models，SDMs)是利用物种分布数据(出现数据)和环境数据，评估物种在环境中的生态位，可以反映物种对生境的偏好程度，解释推测物种在区域内的出现概率、对生境适宜度的要求和物种丰富度等重要的生态评估指标[14]。 物种分布模型的发展始于BIOCLIM模型，此后的30多年内，越来越多的物种分布模型相继出现，如生态位因子分析模型(ecological niche factor analysis, ENFA) 、最大熵模型(MaxEnt)以及基于统计的和基于规则集的遗传算法 (genetic algorithm for rule-setprediction, GARP)等[15]，其中MaxEnt模型是目前公认表现最好、应用最广的生态位模型[16−17]。近年来，MaxEnt模型应用于物种分布预测、入侵物种分布预测、自然保护区设计和全球气候变暖对物种适生区域的影响等热点生态学问题，取得了较好结果[18−21]。但MaxEnt模型也有一定的缺陷，如模型的时空外推能力仅在低阈值情况下较好，在较小的样本量情况下得出的结论可能对物种生态位模拟不完整，导致模拟结果失真[22]。

      • 1.3.   数据收集

      1.3.1.   雪豹分布点数据

    • 根据中国知网文献资料和媒体的报道，确定102个雪豹分布点。

      • 1.3.2.   气候数据

    • 政府间气候变化专门委员会(IPCC)第5次报告明确以2100年总辐射强迫为指标，确定了4个典型温室气体浓度路径(representative concentration pathway, RCP)排放情景，分别对应的情景是2100年总辐射强迫相对于1750年达到2.6、4.5、6.0和8.5 W·m−2。RCP 4.5情景是到2100年，温室气体浓度对应辐射强迫稳定在4.5 W·m−2，大气中二氧化碳(CO2)质量分数增至538 mg·kg−1[23]；RCP 8.5情景代表世界各国未采取任何温室气体减排措施，是温室气体排放量最高的情景，到2100年辐射强度超8.5 W·m−2，即CO2质量分数大于1 370 mg·kg−1。本研究选取了目前接受度较高的RCP 4.5和RCP 8.5情景。

      从WorldClim (https://www.worldclim.org/)下载并转换了当代(1970—2000年30 a气候观测数据的平均值)及未来(2050年)等2种不同强度气候变化场景(RCP 4.5和RCP 8.5)下的气候数据，所需的气候数据均来自全球气候模型[Community Climate System Model (version 4)，CCSM 4]，包括19个气候因子。选用的19个气候因子主要反映了降水量和温度的特点以及季节性的变化特征[24]。这些气候因子具有较强的生物学意义，已被广泛用于物种适宜分布区的预测中[16]。

      • 1.3.3.   人类活动数据

    • 人类活动数据(代表人类活动产生的干扰)来自于国际地球科学中心信息网络(CIESIN, http://www.ciesin.org/)，它可以综合反映人类活动的强度。该数据来自对以下因素的综合评估：建成环境、人口密度、电力基础设施、农作物土地、牧场、道路、铁路、可用航道，从中提取青海地区的部分用于模型模拟。

      • 1.3.4.   土地利用数据

    • 青海省 2000和 2020 年的土地利用数据来自 MODIS 图像(https://search.earthdata.nasa.gov/search)。在解译之前，利用地面样本对遥感数据进行了地理参照，2014年土地利用判读结果与《青海省森林资源规划设计调查成果(2014年)》进行了对比验证，表明总体分类准确率超过 85%。根据判读标准，土地利用被判读为 11 种类型，即农业用地、森林用地、灌木林地、疏林地、草地、水体、永久积雪和冰川、建筑用地、裸地、荒漠和沙化土地、湿地[3]。利用ArcGIS对各分类进行统计(表1)，结果显示：灌木林地和裸地面积是变化最大的2种土地利用类型，灌木林地面积扩大了1.29 万km2，裸地面积减少了2.52 万km2。森林用地、草地、永久积雪和冰川、水体、湿地均有所增加，分别增加了0.21、0.77、0.06 、0.33和0.53 万km2。农业用地、疏林地、建筑用地、荒漠和沙化土地有所减少，分别减少了0.05、0.01、 0.11和0.49 万km2。

      年份
      		土地利用面积/万km2
      农业用地森林用地灌木林地疏林地草地水体永久积雪和冰川建筑用地裸地荒漠和沙化土地湿地
      20000.900.383.350.0341.661.380.660.3113.694.352.49
      20200.850.594.640.0242.431.710.720.2011.173.863.02

      Table 1.  Areas of main land use type in Qinghai Province in 2000 and 2020

      • 1.3.5.   距水系距离数据

    • 青海水系数据来源于国家科技基础条件平台——国家地球系统科学数据中心(http://www.geodata.cn)。在此基础上，利用ArcGIS计算出青海省范围内距水系距离的栅格数据。

      • 1.3.6.   海拔数据

    • 数字高程(DEM)数据来源于WorldClim (https://www.worldclim.org/)，通过ArcGIS裁剪出青海地区的DEM作为模型的输入数据。

      • 1.4.   环境因子的选择

    • 将搜集到的全部环境数据输入建立初始模型。为了降低环境因子之间的高度相关性和共线性而导致模型过度拟合，本研究采用Pearson相关分析选择环境变量。在Pearson相关系数绝对值大于0.8的2个因子中，只保留生态意义较大和初始模型中贡献率较大的一个环境变量。最终选择11个环境变量，包含7个气候变量(最热季度降水量、降水季节性变化系数、最干月降水量、最湿季度平均气温、气温日较差、等温性、最冷月最低温度)、海拔、人类活动、距水系距离以及土地利用变化。

      • 1.5.   MaxEnt模型的运行

    • 将收集的栅格数据在ArcGIS里统一边界和分辨率，并转为ASCII 格式，作为输入 MaxEnt 模型的环境变量，同时将收集到的青海地区雪豹分布点数据在 Excel中记录并转化为 CSV 格式也输入MaxEnt 模型。将 75%的数据作为训练数据，25%作为测试数据[25]。设置软件重复运算 15 次(即产生 15 个随机的预测模型)[26] ，输出分布值为逻辑斯蒂值(logistic)。

      MaxEnt提供了结果精度计算功能，可以生成受试者工作特征曲线(receiver operating characteristic curve, ROC)进行模型的模拟预测自检，并且在对动物生境进行评价与预测时，只需动物“出现点”的数据，且具有较高的精度[11, 20, 25]。曲线下面积(area under curve, AUC)值越大说明环境因子与雪豹分布模型之间相关性越大，预测效果也越好。其评价标准为：AUC值为0.5~0.6时，模型预测失败；AUC值为0.6~0.7时，模型预测效果较差；AUC值为0.7~0.8时，模型预测效果一般；AUC值为0.8~0.9时，模型预测效果好；AUC值为0.9~1.0，模型预测效果非常好[27]。由于不同区域气候存在不同程度的相关性，最终需结合刀切法和贡献率结果，筛选出影响雪豹分布的主要气候因子。

      本研究按照MaxEnt模型输出的每个地理单元生境适宜性值，对该地理单元进行分级。将雪豹适宜生境(区域)划分为4个等级：0~0.1为非适生区，0.1~0.3为低适生区，0.3~0.5为中适生区，0.5~1.0为高适生[28−29]。

    2.   结果与分析

      2.1.   模型准确性及因子贡献率

    • MaxEnt模型15次重复运算结果显示：平均AUC值达0.838，说明模型模拟效果较好，结果的可信度较高。基于2020年土地利用数据和当前气候条件进行建模的结果显示：贡献率前5位的环境变量依次为最热季度降水量(43.5%)、降水季节性变化系数(29.8%)、人类活动(6.3%)、最干月降水量(5.3%)和海拔(4.6%)，以上环境因子对于模型的累计贡献率达到89.5%。可见，这5个环境因素主导了雪豹的分布(表2)。

      环境因子贡献率/% 环境因子贡献率/% 环境因子贡献率/%
      最热季度降水量(bio18) 43.5 海拔 4.6 等温性(温度日较差/气温年较差，bio3) 1.8
      降水季节性变化系数(bio15) 29.8 距水系距离 2.7 土地利用变化(2020年) 1.0
      人类活动 6.3 气温日较差(bio2) 2.3 最冷月最低气温(bio6) 0.5
      最干月降水量 (bio14) 5.3 最湿季度平均气温(bio8) 2.0

      Table 2.  Contribution rates of input factors

      • 2.2.   土地利用对雪豹适生区的影响

    • MaxEnt模拟结果显示：天然林资源保护工程实施后(2020年)雪豹在青海省的适宜生境面积相较于天然林资源保护工程实施之前(2000年)有所增加但增加幅度不大(增加了0.98 万km2)。2000和2020年，雪豹在青海省的地理分布范围基本一致，主要集中在青海省南部的玉树州(杂多县、囊谦县、玉树市和治多县)，青海省东北部的海北州(祁连县、刚察县、海晏县)，以及天峻县、玛沁县、同仁县等地。2000和2020年雪豹在青海省的高适生区面积分别为11.79和11.78 万km2，中适生区面积分别为11.90和11.77 万km2，低适生区面积分别为22.96和24.14 万km2。由此可以看出：土地利用的改变使得雪豹在青海省的低适生区变大，而对中高适生区无明显影响。

      • 2.3.   雪豹适生区在未来气候变化情景下的变化趋势

    • 在假设土地利用类型不变的情况下，本研究模拟了2050年2种气候场景(RCP 4.5和RCP 8.5)下的青海省雪豹的适宜生境。结果显示：2050年，雪豹在青海省的适宜生境面积相较于2020年总体上是减少的，但适生区减少的面积并不大。在RCP 4.5的气候场景下减少0.14 万km2，在RCP 8.5的气候场景下减少0.72 万km2。ArcGIS分区统计结果显示：雪豹在2050年的中高适宜生境面积相较于2020年都出现了一定程度的下降，其中，高适生区在RCP 4.5和RCP 8.5情景下分别减少0.25和0.03 万km2；中适生区在RCP 4.5和RCP 8.5情景下分别减少0.07和0.46 万km2。低适生区在2050年RCP 4.5气候情景下增加0.18 万km2，在RCP 8.5气候情景下减少0.23 万km2。

      将中高适宜生境视作整体统计，得到其主要适宜生境(适宜指数＞0.3的区域)，在2050年RCP 4.5和RCP 8.5情景下分别丧失1.44和1.46 万km2；扩张的适宜生境分别为1.12和0.96 万km2，总体上丧失的适宜生境多于扩张的适宜生境(表3)。在未来，青海省雪豹分布区总体稳定，但局部地区(如称多县、曲麻莱县、格尔木市南、德令哈市、天峻县、乌兰县、达日县等)会缩减，局部地区(如班玛县、久治县、共和县、兴海县、同德县、泽库县、河南县等)会扩张。在RCP 4.5和RCP 8.5气候变化情境下均呈现这种趋势，只是在各地区的变化程度不一定，如在RCP 4.5的气候变化情境下，青海省东部地区的扩张程度大于西部地区，而在RCP 8.5的气候变化情境下青海省西部地区的扩张程度大于东部地区。

      气候情景2050年变化区面积/万km2
      丧失区稳定区扩张区
      RCP 4.51.4422.111.12
      RCP 8.51.4622.090.96

      Table 3.  Areas of suitable habitat loss, expansion and stabilization in current and future climate change scenarios

    3.   讨论

      3.1.   土地利用变化对雪豹适生区的影响

    • 本研究的遥感解译和判读结果是通过森林资源二类调查结果验证的，土地利用分类数据与青海省第3次全国国土调查数据存在一些差异。本研究中的建筑用地和冰川面积并没有进行实际验证，因此存在误差，然而这种差异只体现在面积占比较小且对雪豹分布影响不大的土地类型上。

      本研究发现：2020年雪豹的适生区比2000年有所增加但增幅较小，说明土地利用对雪豹分布有积极影响，但这种影响并未完全驱动雪豹适生区面积的扩展。土地利用类型对雪豹分布的贡献率只占1.0%也证实了土地利用类型变化并不会对雪豹分布产生显著的直接影响。主要原因是雪豹主要的栖息环境多在常年冰雪覆盖的高山裸岩及寒漠带，而在这20 a间实施的天然林资源保护工程造成了草地、疏林地、灌木林及乔木林地这些土地利用类型的改变，对雪豹栖息地的直接影响较小。以往有研究表明：天然林资源保护工程增加了雪豹的种群数量[30−31]，但没有过多关注天然林资源保护工程后土地利用的变化对于雪豹适生区面积的影响。关于雪豹分布的研究主要集中于气候因子对雪豹适生区的影响[11]。近年来的相关研究逐渐加入了人类活动、地形、水文、其他动植物分布及土地利用等因素[10]。有研究指出：土地利用对于雪豹分布的影响较小(贡献率只占5.3%)[32] ，但龚健辉等[33]研究发现：土地利用对于雪豹分布的影响巨大(贡献率达53.8%)，与本研究结果不同。产生不同结果的原因可能是由于研究区域和范围不同。

      • 3.2.   气候变化对雪豹适生区的影响

    • 本研究结果显示：雪豹的高适生区主要分布在青海省南部雪山和冰川较多的玉树州以及青海东北部的祁连山区域(海北州)，这与雪豹本身的习性较为吻合[34]。最热季度降水量对雪豹分布的贡献率最高，其次是降水季节性变化系数，对雪豹分布占主导的影响因素都是与降水相关的环境变量，这与过去研究结果较为接近[8]。降水一方面会影响灌木丛[35]和草地[36]的初级生产力，从而间接影响以此为栖息地的动物种群数量，最终影响雪豹的食物供给[8, 37]；另一方面，降水也影响河流径流，从而影响雪豹的水源供应[22]。人类活动对雪豹分布的贡献率占6.3%，因此对雪豹生境的保护应该尽量避免人类活动的干扰。本研究结果还显示：海拔对雪豹分布的影响相对较小(占4.6%)，这与部分研究有所不同[31, 33]，但也有研究显示：海拔与雪豹分布并无显著相关性[32] 。造成这些研究结果差异的原因一方面可能是研究区的空间尺度和位置不同，另一方面可能是本研究采用的其他环境变量相较于海拔对雪豹分布有强影响作用。本研究区海拔普遍较高，雪豹分布点都集中在较高海拔地区，

      气候变化会直接或间接影响动植物生境区域的温度、降水等气候因子及其相关的生态因子[23]，从而影响生物的养分获取、生存和繁殖等行为，因此模拟气候变化对雪豹适宜生境的影响对提前制定响应的保护策略具有重要的意义。本研究模拟结果显示：2050年雪豹在青海省的适宜生境相较于2020年总体上呈现减少的趋势，尤其青海省南部的玉树州、果洛州以及海西州东北部(天峻县和乌兰县)的适宜生境减少较为明显。这一结果与杨子文等[11]的研究在一定程度上相近。玉树州、果洛州以及海西州的东北部雪山较多，在未来气候变暖的情况下，雪山和冰川面积可能会减少[38]，导致雪豹栖息地减少。随着全球气候变暖，雪豹这类喜爱寒冷环境的濒危动物的适生区面积会出现缩减的情况[39]。这除了对雪豹的生境面积带来直接的影响外，可能会通过雪豹的食性偏好间接影响雪豹的生境适宜性[40]。也有研究表明：在冬季雪豹会偏向栖息于温度较高的环境，但该现象是否直接源于雪豹对于栖息地温度的选择仍不明确[41]。另外，基于岛屿生物地理学理论，适宜生境破碎化还会产生额外的消极影响[42]。气候变化所导致的雪豹适宜生境的破碎化将导致雪豹的活动范围受限，对于体型和习性上均不占优势的雪豹而言，其在适生区范围内的捕食等种内或种间竞争可能更加激烈，最终将进一步对其种群数量产生负作用。

    4.   结论

    • 本研究将19个生物气候因子和其他4个与雪豹分布相关的环境因子(海拔、人类活动、距水系距离及土地利用变化)作为驱动物种分布模型的环境变量，结合雪豹分布点的经纬度数据，比较了天然林资源保护工程实施引起的土地利用变化对雪豹潜在适生区的影响，并使用未来的气候数据，预测了未来2050年2种不同强度气候变化场景(RCP 4.5和RCP 8.5)下雪豹的适宜生境情况。最热季度降水量、降水季节性变化系数、人类活动、最干月降水量、海拔等环境因素主导了雪豹的分布。天然林资源保护工程实施后土地利用的变化在一定程度上增加了雪豹适宜生境的面积，但由于天然林资源保护工程并没有使雪豹栖息环境，如常年冰雪覆被的高山裸岩及寒漠带等土地利用类型增加，因此这20 a间土地利用变化对于雪豹适生区影响较小。本研究还发现：气候变化主要通过水分因子的改变影响雪豹的分布。预测2050年青海省的雪豹适生面积将会出现一定程度的缩减。因此，在气候变化背景下，林业管理部门应当加强对雪豹活动的监测，提前制定气候变化下雪豹等濒危野生动物的保护策略。

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