基于InVEST与倾向评分匹配模型评估秦岭国家级自然保护区水源涵养服务保护成效

doi:10.17520/biods.2020271

生物多样性 ›› 2021, Vol. 29 ›› Issue (5): 617-628. DOI: 10.17520/biods.2020271

• 研究报告: 生态系统多样性 • 上一篇下一篇

基于InVEST与倾向评分匹配模型评估秦岭国家级自然保护区水源涵养服务保护成效

曹明¹^,², 李俊生¹^,², 王伟¹^,²^,^*(), 夏聚一¹^,²^,³, 冯春婷¹^,², 付刚¹^,², 黄文婕¹^,², 刘方正¹^,²

1.中国环境科学研究院国家环境保护区域生态过程与功能评估重点实验室, 北京 100012
2.中国环境科学研究院生物多样性研究中心, 北京 100012
3.中国人民大学环境学院, 北京 100872

收稿日期:2020-07-07 接受日期:2020-11-04 出版日期:2021-05-20 发布日期:2020-12-31
通讯作者: 王伟
作者简介:* E-mail: wang.wei@craes.org.cn
基金资助:
国家重点研发计划(2016YFC0503304)

Assessing the effectiveness of water retention ecosystem service in Qinling National Nature Reserve based on InVEST and propensity score matching model

Ming Cao¹^,², Junsheng Li¹^,², Wei Wang¹^,²^,^*(), Juyi Xia¹^,²^,³, Chunting Feng¹^,², Gang Fu¹^,², Wenjie Huang¹^,², Fangzheng Liu¹^,²

1 State Environmental Protection Key Laboratory of Regional Eco-process and Function Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012
2 Biodiversity Research Center, Chinese Research Academy of Environmental Sciences, Beijing 100012
3 School of Environment & Natural Resources, Renmin University of China, Beijing 100872

Received:2020-07-07 Accepted:2020-11-04 Online:2021-05-20 Published:2020-12-31
Contact: Wei Wang

摘要/Abstract

摘要：

自然保护区在保障水源涵养等生态系统服务方面发挥了重要作用, 对区域水资源的可持续利用具有重要意义。然而, 自然保护区水源涵养服务保护成效的主要影响因素仍然不清, 不利于自然保护区的有效管理和区域可持续发展目标的实现。本文拟探讨: (1)秦岭区域水源涵养服务的总体情况; (2)自然保护区对水源涵养服务的保护成效; (3)自然保护区水源涵养服务保护成效的主要影响因素是什么。本文采用InVEST模型计算秦岭区域19个国家级自然保护区2010-2015年的水源涵养量, 基于倾向评分配比法研究了自然保护区水源涵养服务保护成效, 并通过随机森林回归判断自然保护区水源涵养服务保护成效的主要影响因素。研究结果表明, 虽然在2010-2015年秦岭区域水源涵养服务整体降低, 但与自然保护区外的配对样本相比, 大多数自然保护区(63.16%)水源涵养服务保护成效显著(N = 12, P < 0.05); 少数保护区(26.32%)在减缓水源涵养服务降低的作用不如自然保护区外(N = 5, P < 0.05); 也有个别自然保护区(10.52%)对水源涵养服务保护成效不明显(N = 2, P > 0.05)。从主要影响因素来看, 自然保护区水源涵养服务保护成效主要受降水量变化和自然保护区资金投入的影响。结果显示: (1) 2010-2015年间秦岭区域水源涵养量减少较为明显, 但总体来看自然保护区在减缓水源涵养服务降低方面取得了积极成效。(2)降水量变化对水源涵养服务保护成效起到主导作用; (3)管理因素也对保护区水源涵养服务保护成效有一定影响, 在管理因素中资金投入的大小对水源涵养服务保护效果影响最大。因此, 建议进一步增加资金投入, 以提升自然保护区水源涵养服务的保护成效。

关键词: 保护成效评估, 倾向评分配比, 生态系统服务, 随机森林, 资金投入

Abstract

Aims: Nature reserves (NRs) play an important role in ensuring ecosystem services such as water retention, which are of great significance for the sustainable use of regional water resources. However, the main factors influencing the effectiveness of water retention in NRs are still unclear, which is not conducive to the effective management of NRs and the achievement of regional sustainable development goals. Therefore, the aims of this research are to explore: (1) the overall situation of water retention services in Qinling Mountains; (2) the conservation effectiveness of water retention services in NRs; and (3) the key influencing factors of the conservation effectiveness of water retention services in NRs.
Methods: Here, we used the InVEST model to calculate the water retention between 2010 and 2015 in Qinling Mountains related to 19 national nature reserves. Based on the propensity score matching approach, we assessed the conservation effectiveness of these nature reserves in ensuring the ecosystem service of water retention. We then used the random forest regression model to identify the factors that mainly affect the conservation effectiveness.
Results: The results showed that the water retention ecosystem service in Qinling Mountains generally reduced between 2010 and 2015. Compared with the matched samples outside the NRs, most reserves (63.16%) showed significant positive effects on water retention (N = 12, P < 0.05), while some reserves (26.32%) showed significant negative effects (N = 5, P < 0.05). There were also two reserves (10.52%) that had no significant effects on water retention (N = 2, P > 0.05). In addition, the conservation effectiveness of reserves in ensuring water retention was mainly affected by changes in precipitation and funding investment.
Conclusions: (1) Between 2010 and 2015, the water retention rate was reduced remarkably in Qinling Mountains, but the NRs had achieved positive effectiveness in mitigating the reduction of water retention in general; (2) Changes in precipitation play a dominant role in sustaining the ecosystem service of water retention; and (3) The management factors also affect the conservation effectiveness to certain extent, in which the amount of investment is the most important. Therefore, we suggest increasing capital investment in the future to improve the conservation effectiveness of water retention service of NRs.

Key words: conservation effectiveness assessment, propensity score matching, ecosystem services, random forest model, funding investment

曹明, 李俊生, 王伟, 夏聚一, 冯春婷, 付刚, 黄文婕, 刘方正 (2021) 基于InVEST与倾向评分匹配模型评估秦岭国家级自然保护区水源涵养服务保护成效. 生物多样性, 29, 617-628. DOI: 10.17520/biods.2020271.

Ming Cao, Junsheng Li, Wei Wang, Juyi Xia, Chunting Feng, Gang Fu, Wenjie Huang, Fangzheng Liu (2021) Assessing the effectiveness of water retention ecosystem service in Qinling National Nature Reserve based on InVEST and propensity score matching model. Biodiversity Science, 29, 617-628. DOI: 10.17520/biods.2020271.

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链接本文: https://www.biodiversity-science.net/CN/10.17520/biods.2020271

https://www.biodiversity-science.net/CN/Y2021/V29/I5/617

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数据类型 Data type	来源与获取方法 Data sources
土地利用数据(2010, 2015年) Land use data (2010, 2015)	2010-2015年全国生态状况变化遥感调查与评估项目 2010-2015 Remote Sensing Investigation and Assessment Project of Ecological Status Change in China
数字高程模型数据 Digital elevation model (DEM) data	地理空间数据云GDEMV2数据(30 m分辨率) GDEMV2 data from Geospatial data cloud with 30 m resolution
子流域数据 Sub-watersheds data	根据数字高程模型数据进行水文提取 Hydrological information extraction based on DEM data
降雨数据 Precipitation data	数据来源于资源环境数据云平台(分辨率1 km) Precipitation data with 1 km resolution obtained from the website of www.resdc.cn
蒸散数据 Evapotranspiration	数据来源于谷歌地球引擎平台, MOD16A2产品(500 m分辨率) Data were extracted from the MOD16A2 products (500 m resolution), which were obtained from the Google Earth Engine.
土壤数据 Soil data	数据来源于第二次土壤普查, 国家青藏高原数据科学中心(上官微和戴永久, 2013) Data were obtained from the second soil census of National Tibetan Plateau Data Center (Shangguan & Dai, 2013)
植物有效含水量 Plant available water capacity (PAWC)	根据土壤普查数据采用土壤质地数据进行计算得到 The data were calculated from the soil texture data based on the soil census.
根系深度 Root depth	第二次土壤普查土壤剖层, 结合研究区文献校正得到(刘兆谦, 1983; 游松财等, 2009; 上官微和戴永久, 2013) Adjusted from the soil profile in the second soil census combined with related literature in the study area (Liu, 1983; You et al, 2009; Shangguan & Dai, 2013)
Zhang系数 Zhang coefficient	根据自然径流反复计算, 结合研究区文献(范亚宁, 2017^①(① 范亚宁 (2017) 秦岭北麓及周边生态系统水源涵养与水质净化功能评估. 硕士学位论文, 西北大学, 西安.); 魏星涛, 2018^②(② 魏星涛 (2018) 基于InVEST模型的祁连山南坡水源涵养功能研究. 硕士学位论文, 青海师范大学, 西宁.))反复校验得到, 估算数值为4.35 According to the repeated calculation of natural runoff, combined with repeated verification of the literature in the study area^①②, the estimated value was 4.35.
流速系数 Velocity coefficient	查阅相关文献(包玉斌等, 2016) Extracted from related literature (Bao et al, 2016)
地形指数 Terrain index	根据数字高程模型数据计算 Calculated from DEM
土壤饱和导水率 Soil saturated hydraulic conductivity	根据Vereecken模型计算(Vereecken et al, 1992) Calculated according to Vereecken model (Vereecken et al, 1992)
自然保护区边界 Nature reserves’ boundaries	生态环境部 Ministry of Ecology and Environment of the People’s Republic of China
自然保护区相关管理数据 Management data of nature reserves	现场调查, 查阅资料 On-site investigation and archives searching
路网数据 Roads data	Open Street Map (www.openstreetmap.org)

数据类型 Data type	来源与获取方法 Data sources
土地利用数据(2010, 2015年) Land use data (2010, 2015)	2010-2015年全国生态状况变化遥感调查与评估项目 2010-2015 Remote Sensing Investigation and Assessment Project of Ecological Status Change in China
数字高程模型数据 Digital elevation model (DEM) data	地理空间数据云GDEMV2数据(30 m分辨率) GDEMV2 data from Geospatial data cloud with 30 m resolution
子流域数据 Sub-watersheds data	根据数字高程模型数据进行水文提取 Hydrological information extraction based on DEM data
降雨数据 Precipitation data	数据来源于资源环境数据云平台(分辨率1 km) Precipitation data with 1 km resolution obtained from the website of www.resdc.cn
蒸散数据 Evapotranspiration	数据来源于谷歌地球引擎平台, MOD16A2产品(500 m分辨率) Data were extracted from the MOD16A2 products (500 m resolution), which were obtained from the Google Earth Engine.
土壤数据 Soil data	数据来源于第二次土壤普查, 国家青藏高原数据科学中心(上官微和戴永久, 2013) Data were obtained from the second soil census of National Tibetan Plateau Data Center (Shangguan & Dai, 2013)
植物有效含水量 Plant available water capacity (PAWC)	根据土壤普查数据采用土壤质地数据进行计算得到 The data were calculated from the soil texture data based on the soil census.
根系深度 Root depth	第二次土壤普查土壤剖层, 结合研究区文献校正得到(刘兆谦, 1983; 游松财等, 2009; 上官微和戴永久, 2013) Adjusted from the soil profile in the second soil census combined with related literature in the study area (Liu, 1983; You et al, 2009; Shangguan & Dai, 2013)
Zhang系数 Zhang coefficient	根据自然径流反复计算, 结合研究区文献(范亚宁, 2017^①(① 范亚宁 (2017) 秦岭北麓及周边生态系统水源涵养与水质净化功能评估. 硕士学位论文, 西北大学, 西安.); 魏星涛, 2018^②(② 魏星涛 (2018) 基于InVEST模型的祁连山南坡水源涵养功能研究. 硕士学位论文, 青海师范大学, 西宁.))反复校验得到, 估算数值为4.35 According to the repeated calculation of natural runoff, combined with repeated verification of the literature in the study area^①②, the estimated value was 4.35.
流速系数 Velocity coefficient	查阅相关文献(包玉斌等, 2016) Extracted from related literature (Bao et al, 2016)
地形指数 Terrain index	根据数字高程模型数据计算 Calculated from DEM
土壤饱和导水率 Soil saturated hydraulic conductivity	根据Vereecken模型计算(Vereecken et al, 1992) Calculated according to Vereecken model (Vereecken et al, 1992)
自然保护区边界 Nature reserves’ boundaries	生态环境部 Ministry of Ecology and Environment of the People’s Republic of China
自然保护区相关管理数据 Management data of nature reserves	现场调查, 查阅资料 On-site investigation and archives searching
路网数据 Roads data	Open Street Map (www.openstreetmap.org)

自然保护区 Nature reserve	对比结果Comparison results (E)	N	P	自然保护区 Nature reserve	对比结果 Comparison results (E)	N	P
周至 Zhouzhi	+	358	0.000**	太白山 Taibaishan	+	185	0.006**
汉中朱鹮 Hanzhong crested Ibis	+	349	0.000**	天华山 Tianhuashan	+	170	0.000**
观音山 Guanyinshan	+	97	0.000**	小陇山 Xiaolongshan	?	199	0.000**
佛坪 Foping	+	223	0.000**	紫柏山 Zibaishan	?	110	0.009**
黄柏塬 Huangbaiyuan	+	108	0.000**	宝天曼 Baotianman	?	53	0.000**
老县城 Laoxiancheng	+	67	0.020*	伏牛山 Funiushan	?	471	0.000**
长青 Changqing	+	178	0.000**	南阳恐龙蛋化石群 Nanyang Dinosaur Egg Fossil	?	650	0.000**
牛背梁 Niubeiliang	+	81	0.000**	摩天岭 Motianling	不显著 Nonsignificant	49	0.689
平河梁 Pingheliang	+	140	0.000**	小秦岭 Xiaoqinling	不显著 Nonsignificant	132	0.213
桑园 Sangyuan	+	82	0.000**	总体 Overall	+	3,721	0.018**

自然保护区 Nature reserve	对比结果Comparison results (E)	N	P	自然保护区 Nature reserve	对比结果 Comparison results (E)	N	P
周至 Zhouzhi	+	358	0.000**	太白山 Taibaishan	+	185	0.006**
汉中朱鹮 Hanzhong crested Ibis	+	349	0.000**	天华山 Tianhuashan	+	170	0.000**
观音山 Guanyinshan	+	97	0.000**	小陇山 Xiaolongshan	?	199	0.000**
佛坪 Foping	+	223	0.000**	紫柏山 Zibaishan	?	110	0.009**
黄柏塬 Huangbaiyuan	+	108	0.000**	宝天曼 Baotianman	?	53	0.000**
老县城 Laoxiancheng	+	67	0.020*	伏牛山 Funiushan	?	471	0.000**
长青 Changqing	+	178	0.000**	南阳恐龙蛋化石群 Nanyang Dinosaur Egg Fossil	?	650	0.000**
牛背梁 Niubeiliang	+	81	0.000**	摩天岭 Motianling	不显著 Nonsignificant	49	0.689
平河梁 Pingheliang	+	140	0.000**	小秦岭 Xiaoqinling	不显著 Nonsignificant	132	0.213
桑园 Sangyuan	+	82	0.000**	总体 Overall	+	3,721	0.018**

影响因素 Influencing factor	Spearman相关系数 Spearman correlation coefficient	P
降水变化率 Precipitation change rate	0.926	0.000**
平均高程 Average elevation	0.235	0.363
形状指数 Landscape shape index	?0.260	0.314
资金投入 Funding investment	0.542	0.025*
路网密度 Road density	0.047	0.859
单位面积工作人员数量 Number of staff per km²	?0.056	0.83
单位面积巡护人员数量 Number of patrolling personnel per km²	?0.105	0.687
保护区建立时长 Period from the establishment of nature reserves	?0.205	0.430

基于InVEST与倾向评分匹配模型评估秦岭国家级自然保护区水源涵养服务保护成效

Assessing the effectiveness of water retention ecosystem service in Qinling National Nature Reserve based on InVEST and propensity score matching model

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