东北地区水獭分布格局与保护优先区识别

doi:10.17520/biods.2021157

生物多样性 ›› 2022, Vol. 30 ›› Issue (1): 21157. DOI: 10.17520/biods.2021157

• 研究报告: 动物多样性 • 下一篇

东北地区水獭分布格局与保护优先区识别

张超¹, 陈敏豪¹, 杨立², 庄鸿飞¹, 武曙红¹, 湛振杰¹, 王嘉栋¹, 栾晓峰¹^,^*()

1.北京林业大学生态与自然保护学院, 北京 100083
2.中山大学生命与科学学院, 广州 510275

收稿日期:2021-04-24 接受日期:2021-08-26 出版日期:2022-01-20 发布日期:2022-01-29
通讯作者: 栾晓峰
作者简介:* E-mail: luanxiaofeng@bjfu.edu.cn
基金资助:
国家自然科学基金(31972944);国家自然科学基金(32000352)

Distribution pattern and identification of conservation priority areas of the otter in Northeast China

Chao Zhang¹, Minhao Chen¹, Li Yang², Hongfei Zhuang¹, Shuhong Wu¹, Zhenjie Zhan¹, Jiadong Wang¹, Xiaofeng Luan¹^,^*()

1 School of Ecology and Nature Conservation, Beijing Forestry University, Beijing 100083
2 School of Life Sciences, Sun Yat-sen University, Guangzhou 510275

Received:2021-04-24 Accepted:2021-08-26 Online:2022-01-20 Published:2022-01-29
Contact: Xiaofeng Luan

摘要/Abstract

摘要：

水獭是水生生态系统重要的指示种和旗舰种, 由于强烈的人为干扰, 中国的水獭种群数量大幅下降, 部分区域已局部灭绝。然而目前国内对水獭的调查和研究非常有限, 本底不清的状况已经严重影响到水獭的野外保育工作。本文以东北地区的欧亚水獭指名亚种(Lutra lutra lutra)为研究对象, 基于2016-2020年的调查数据, 使用组合建模的方法评估了水獭的潜在分布区; 利用地理信息系统和系统保护规划软件分析了水獭的保护优先区并计算了各省级行政区内水獭潜在分布区和保护优先区面临的人类压力; 结合国家级自然保护区的空间布局分析了水獭的保护现状, 并以内蒙古森工集团、大兴安岭林业集团、伊春森工集团三大国有林区为例分析了重点国有林区在水獭保护中的作用。结果表明: (1)水獭潜在分布区和保护优先区面积分别为104,515.04 km²和45,448.99 km², 其中大兴安岭的水獭保护优先区集中连片, 并与小兴安岭的保护优先区相连, 栖息地之间没有明显地理隔离, 是维持东北地区水獭种群稳定的重中之重; (2)水獭面临的人类压力大小依次为: 辽宁 > 吉林 > 黑龙江 > 内蒙古; (3)研究区内110个国家级自然保护区中有63个包含水獭潜在分布区, 覆盖面积为12,168.93 km², 仅占水獭潜在分布区面积的11.64%, 其中32个国家级自然保护区包含水獭保护优先区, 占水獭保护优先区面积的10.88%; (4)三大国有林区涵盖了71.18%的水獭潜在分布区和79.26%的保护优先区(面积分别为74,390.89 km²和36,022.22 km²)。由此可见, 尽管水獭潜在分布区中国家级自然保护区占比较低, 但是在天然林全面禁伐的背景下, 重点国有林区可能在未来东北地区的生物多样性保护中发挥更大作用, 因此我们建议将重点国有林区中具有重要保护价值的区域逐步纳入以国家公园为主体的自然保护地体系中, 以实现生物多样性的系统性和完整性保护。最后, 本文结合研究结果和实地调研提出以下保护建议: (1)加强对河流污染物的管理; (2)控制渔民捕鱼强度; (3)开展全面的水獭专项调查并建立长期的监测体系; (4)加大对水獭的科研投入; (5)加强宣传力度, 提升公众保护意识。

关键词: 欧亚水獭, 组合模型, 分布, 保护优先区, 国有林区

Abstract

Aims: The otter is an indicator and flagship species of aquatic ecosystems. Its populations have undergone a drastic decline in China, and have become locally extinct in some regions due to anthropogenic disturbance. However, the current literature on otters in China is inadequate, which has subsequently affected conservation of the species. We aim to assess the potential distribution and conservation priority areas of the Eurasian otter (Lutra lutra) in Northeast China.

Methods: In this study, we integrated species distribution models with otter survey data from 2016 to 2020 to assess Eurasian otter distribution. Then, we used the geographic information system and core-area zonation algorithm in Zonation 4.00 to identify conservation priority areas for otter protection. Using the anthropogenic pressures layer, we also evaluated anthropogenic stressors in each province. Then, we analyzed the conservation status of the otter based on the spatial distribution of national nature reserves. Furthermore, we used Inner Mongolia Forest Industry Group, Daxing’anling Forestry Group and Yichun Forest Industry Group as case studies to analyze the role of state-owned forest areas for otter conservation.

Results: The results demonstrate that potential distribution and conservation priority areas cover 104,515.04 km²and 45,448.99 km², respectively. Large swathes of conservation priority areas remain for the otter in Daxing’anling which are connected with conservation priority areas in Xiaoxing’anling and there is no obvious geographical boundary between them. Therefore, these regions are mandatory to conserve to maintain the stability of otter populations in Northeast China. Otters in the Liaoning Province faced the greatest anthropogenic pressures, followed by the Jilin Province and Heilongjiang Province. Otters in the Inner Mongolia Autonomous Region faced the lowest amount of pressure. There is potential distribution for the otter in 63 nature reserves and conservation priority areas in 32 nature reserves out of the 110 reserves in the region. The study area includes 11.64% of the otter’s potential distribution and 10.88% of conservation priority areas. Three state-owned forest industry groups cover 71.18% of the potential distribution of the otter (74,390.89 km²) and 79.26% of the conservation priority areas (36,022.22 km²).

Conclusions: This study indicates that state-owned forest areas may play a greater role in the protection of biodiversity following a comprehensive ban on logging in natural forests. Therefore, we propose that areas with important conservation value in state-owned forest land should be gradually included under the protections of national parks in order to achieve systematic and complete protection of biodiversity. Finally, we suggest: (1) strengthening the management of river pollutions; (2) reducing fishing intensity; (3) a long-term field monitoring network be established to study population changes in otters; (4) increasing the investment in scientific research on otters; and (5) raising awareness of otter conservation through public education.

Key words: Eurasian otter, ensemble models, distribution, conservation priority areas, state-owned forest areas

张超, 陈敏豪, 杨立, 庄鸿飞, 武曙红, 湛振杰, 王嘉栋, 栾晓峰 (2022) 东北地区水獭分布格局与保护优先区识别. 生物多样性, 30, 21157. DOI: 10.17520/biods.2021157.

Chao Zhang, Minhao Chen, Li Yang, Hongfei Zhuang, Shuhong Wu, Zhenjie Zhan, Jiadong Wang, Xiaofeng Luan (2022) Distribution pattern and identification of conservation priority areas of the otter in Northeast China. Biodiversity Science, 30, 21157. DOI: 10.17520/biods.2021157.

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链接本文: https://www.biodiversity-science.net/CN/10.17520/biods.2021157

https://www.biodiversity-science.net/CN/Y2022/V30/I1/21157

图/表 7

图1 中国东北地区稀疏化后水獭的231个分布位点

Fig. 1 A total of 231 occurrence points of otter after spatial thinning in Northeast China

表1 环境变量的方差膨胀因子(VIF)及重要性

Table 1 Variance inflation factor (VIF) value and importance of environmental variables

环境变量 Environmental variables	第一次方差膨胀因子评估 VIF evaluation for the first time	第二次方差膨胀因子评估 VIF evaluation for the second time	重要性 Importance
年降水量 Annual precipitation	14.246	-	-
最湿季降水量 Precipitation of wettest quarter	6.432	2.815	0.017
最干季降水量 Precipitation of driest quarter	4.322	2.870	0.018
距河流距离 Distance from river	1.361	1.357	0.521
湿润指数 Moisture index	3.120	2.946	0.051
海拔 Elevation	7.402	7.078	0.006
地表起伏度 Relief degree of land surface	6.491	6.416	0.002
有林地密度 Forest density	2.732	2.429	0.02
距道路距离 Distance from road	1.389	1.376	0.003
人口密度 Human density	1.070	1.067	0.117
人类压力 Anthropogenic pressures	2.590	2.500	0.048

图2 模型选择标准(TSS: 真实技巧统计值; AUC: 受试者操作特征曲线下的面积值)。GLM: 广义线性模型; GBM: 广义推进模型; GAM: 广义加法模型; CTA: 分类树模型; ANN: 人工神经网络模型; SRE: 表面分布区分室模型; FDA: 柔性判别分析; MARS: 多元适应回归样条函数; RF: 随机森林; MaxEnt: 最大熵模型。

Fig. 2 Models selection (TSS, True skill statistics; AUC, Area under the receiver operating characteristic curve). GLM, Generalized linear model; GBM, Generalized boosted regression model; GAM: Generalized additive model; CTA, Classification tree analysis; ANN, Artificial neural network; SRE, Surface range envelope; FDA, Flexible discriminant analysis; MARS, Multiple adaptive regression splines; RF: Random forest; MaxEnt, Maximum entropy.

表2 东北各省/自治区水獭潜在分布区和保护优先区面积及平均人类压力

Table 2 Potential distribution and conservation priority areas of the otter and mean anthropogenic pressures in each provinces/ autonomous region

	潜在分布区面积 Potential distribution (km²)	保护优先区面积 Conservation priority areas (km²)	潜在分布区平均人类压力 Mean anthropogenic pressures of potential distribution (0-1)	保护优先区平均人类压力 Mean anthropogenic pressures of conservation priority areas (0-1)
内蒙古 Inner Mongolia	50,503.58	30,613.58	0.063	0.045
黑龙江 Heilongjiang	48,533.40	10,269.55	0.078	0.065
吉林 Jilin	5,250.36	4,338.16	0.148	0.135
辽宁 Liaoning	227.7	227.7	0.223	0.223

图3 东北地区水獭潜在分布区和保护现状

Fig. 3 Potential distribution and conservation status of the otter in Northeast China

图4 水獭保护优先度排序和保护优先区保护现状

Fig. 4 Conservation priority ranking and conservation status in conservation priority areas of the otter

图5 水獭潜在分布区(a)和保护优先区(b)面临的人类压力。NMG: 内蒙古; HLJ: 黑龙江; JL: 吉林; LN: 辽宁。

Fig. 5 Anthropogenic pressures in potential distribution (a) and conservation priority areas (b) of the otter. NMG: Inner Mongolia; HLJ: Heilongjiang; JL: Jilin; LN: Liaoning.

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	[ 庄鸿飞, 张殷波, 王伟, 任月恒, 刘方正, 杜金鸿, 周越 (2018) 基于最大熵模型的不同尺度物种分布概率优化热点分析: 以红色木莲为例. 生物多样性, 26, 931-940.] DOI

东北地区水獭分布格局与保护优先区识别

Distribution pattern and identification of conservation priority areas of the otter in Northeast China

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