基于土地利用情景模拟的喀斯特关键带生态系统服务权衡与协同分析

陈金珂; 蒲俊兵; 李建鸿; 张陶

doi:10.11932/karst20230108

基于土地利用情景模拟的喀斯特关键带生态系统服务权衡与协同分析——以蒙自喀斯特断陷盆地为例

doi: 10.11932/karst20230108

陈金珂^{1, 3,},
蒲俊兵^2, ,,
李建鸿¹,
张陶²

1.
中国地质科学院岩溶地质研究所/自然资源部、广西岩溶动力学重点实验室, 广西桂林 541004
2.
重庆师范大学地理与旅游学院长江上游湿地科学研究重庆市重点实验室/三峡库区地表过程与环境遥感重庆市重点实验室, 重庆 401331
3.
西南大学地理科学学院重庆市岩溶环境学重点实验室, 重庆 400715

基金项目: 国家重点研发计划项目“不同气候区喀斯特关键带水文—生态耦合过程对比研究”（2021YFE0107100）；重庆师范大学基金项目（21XRC002）

详细信息

作者简介:
陈金珂（1994－），女，博士研究生，主要从事喀斯特环境与全球变化研究。E-mail：17839164069@163.com

通讯作者:
蒲俊兵（1982－），男，博士，研究员，主要从事喀斯特环境学、喀斯特水文地球化学研究。E-mail：junbingpu@163.com

中图分类号: F301.2；X171.1
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出版历程
- 收稿日期: 2022-03-08
- 刊出日期: 2023-02-25

Trade-off and synergy of ecosystem services of a karst critical zone based on land use scenario simulation: Take Mengzi karst graben basin as a study case

CHEN Jinke^{1, 3
,},
PU Junbing^{2
, ,},
LI Jianhong¹,
ZHANG Tao²

1.
Key Laboratory of Karst Dynamics, MNR & GZAR/Institute of Karst Geology, CAGS, Guilin, Guangxi 541004, China
2.
Chongqing Key Laboratory of Wetland Science Research of the Upper Reaches of the Yangtze River /Chongqing Key Laboratory of Surface Process and Environment Remote Sensing in the Three Gorges Reservoir Area, School of Geography and Tourism, Chongqing Normal University, Chongqing 401331, China
3.
Southwest University School of Geographical Sciences, Chongqing Key Laboratory of Karst Environmental Science, Chongqing 400715, China

摘要

摘要: 以蒙自喀斯特断陷盆地为例，利用CLUE-S模型设置自然演化、微度、适度、强力生态治理情景并探究2030年不同情景对生态系统服务的影响及权衡与协同特征。结果表明：（1）2018年蒙自喀斯特断陷盆地植被净初级生产力（NPP）、产水量、覆盖型喀斯特区土壤保持量、裸露型喀斯特区土壤保持量、食物供给量分别增加了13.98%、38.97%、23.04%、25%、105.43%，且各种服务变化存在一定的空间差异性；（2）随着生态治理力度加大，2030年NPP和土壤保持量不断增加，产水量不断减少，食物供给量在强力生态治理情景下减少，在其他三种情景下增加；（3）NPP与产水量、食物供给量为权衡关系，与土壤保持量为协同关系；产水量与土壤保持量为权衡关系，与食物供给量为协同关系；土壤保持量与食物供给量为权衡关系；（4）相较于2018年，适度生态治理情景下四种生态系统服务之间的协调性最好，是较为合理的生态治理模式。
- 石漠化 /
- 生态系统 /
- CLUE-S模型 /
- 权衡与协同 /
- 喀斯特断陷盆地
Abstract: The karst critical zone is the near-surface layer of the Earth including vegetation, soil, water, and rocks in the karst area. It is sensitive to the changes of external environment due to the karst power provided by the Five Circles. And the karst critical zone has been regarded as one of the important ecological barrier areas in China. It is very necessary to study the ecological environment in the zone. Therefore, taking the Mengzi karst graben basin (MKGB) as a case, this study hopes to provide some suggestions for ecological governance in the karst critical zone.MKGB is located in the southeast of Honghe Hani-Yi Autonomous Prefecture in Yunnan Province. Its boundary is almost consistent with the third-largest karst underground river system (the Nandong underground river watershed) in South China. With the influence of natural and human activities, karst rocky desertification is severe in this area. The forest is mainly composed of artificial forest, secondary forest and shrub forest. The ecosystem is imbalanced and the capability of ecosystem services has been reducing. At present, China has launched the project to control rocky desertification, and the main way is to return farmland to forest or grassland. Previous studies have also shown that optimizing land use mode can achieve win-win results between ecological environment and human benefits. However, the pattern and intensity of land use change is unclear in the control of rock desertification. It will be difficult to make reasonable policies for ecological protection if the problem is not paid more attention to. Ecosystem services and the relationship (trade-off and synergy) are important indicators to measure the structure of ecosystem. Therefore, we quantitatively analyzed the current status of ecosystem services and simulated the land use change to maximize ecosystem services in MKGB. In this study, we evaluated regional Net Primary Productivity (NPP), water yield, soil retention of covered and bare karst areas and food supply by respectively using Carnegie-Ames Stanford Approach (CASA model), Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST model), the Revised Universal Soil Loss Equation (RUSLE model) and food supply model. Besides, in order to find the optimal land use mode, we also set up four scenarios—natural scenario, mild ecological governance scenario, moderate ecological governance scenario and strong ecological governance scenario—by the Conversion of Land Use and its Effects at Small Region Extent (CLUE-S model). Then we explored the impacts of different ecological governance scenarios on ecosystem services and their tradeoff or synergistic characteristics.Results show that ecological land use experienced an increasing trend from 2006 to 2018, which reflected that the land conversion was reasonable in the process of rock desertification control, and the effect of rock desertification control was obvious. In 2030, the continuous strengthening of ecological governance will contribute to the increase of forest land and the decrease of cultivated land. Secondly, NPP, water yield, soil retention of covered and bare karst areas and food supply increased by 13.98%, 38.97%, 23.04%, 25% and 105.43%, respectively in MKGB, and there were certain spatial differences in the changes of various services in 2018. Thirdly, with the implementation of ecological governance measures, NPP and soil retention will show an increasing trend, but water yield will decrease continuously in 2030. The food supply will decrease in the strong ecological governance scenario, but increase in the other three scenarios. This result demonstrates that ecological governance measures can promote NPP and soil retention, but they will also limit the growth of water yield and food supply to some extent. Fourthly, NPP presents a trade-off relationship with water yield and food supply, and a synergic relationship with soil retention. Water yield shows a trade-off relationship with soil retention, and a synergic relationship with food supply. Soil retention and food supply are in a trade-off relationship. Finally, compared with the situation in 2018, the degree of trade-off in the moderate ecological governance scenario is acceptable, implying that it will be a reasonable ecological governance.Therefore, we should pay close attention to the control of rocky desertification in the areas with the slope > 20° in the future. We believe the conclusions of this study can provide a clear direction for the control of rocky desertification. However, there still exist limitations. For example, the accuracy of basic data should be continuously improved, and more factors affecting the ecosystem services should also be taken into account in future studies.
- rocky desertification /
- ecosystem /
- CLUE-S model /
- trade-off and synergy /
- karst graben basin

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图 1 研究区位置及范围

Figure 1. Location map of the study area

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图 2 2006-2018年蒙自喀斯特断陷盆地土地利用变化

A.2006-2018年土地利用状况 B.2006-2018年土地利用变化率

Figure 2. Change of land use in MKGB from 2000 to 2018

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图 3 2030年不同情景下蒙自喀斯特断陷盆地土地利用状况

a.自然演化情景 b.微度生态治理情景 c.适度生态治理情景 d.强力生态治理情景

Figure 3. Land use of MKGB in different scenarios

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图 4 2006-2018年蒙自喀斯特断陷盆地生态系统服务变化

Figure 4. Change of ecosystem services from 2006 to 2018 in MKGB

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图 5 不同情景下蒙自喀斯特断陷盆地生态系统服务评价

a.自然演化情景 b.微度生态治理情景 c.适度生态治理情景 d.强力生态治理情景

Figure 5. Ecosystem services of MKGB in different scenarios

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图 6 生态系统服务权衡关系变化

Figure 6. Trade-off changes of ecosystem services

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表 1 蒙自喀斯特断陷盆地未来土地利用情景设置规则

Table 1. Rules for setting future land use scenarios in MKGB

情景	描述
自然情景	按照2012-2018年土地演化趋势确定。
微度生态治理情景	坡度＞25°的耕地转化为林地；15°~25°坡度范围内轻度石漠化区的耕地转化为果园； 15°~25°坡度范围内中重度石漠化区的耕地转化为林地。
适度生态治理情景	坡度＞20°的耕地转化为林地；15°~20°坡度范围内轻度石漠化区的耕地转化为果园； 15°~20°坡度范围内中重度石漠化区的耕地转化为林地。
强力生态治理情景	坡度＞15°的耕地转化为林地。

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表 2 2030年蒙自喀斯特断陷盆地耕地、果园和林地面积相较于2018年的变化状况(km²)

Table 2. Projected changes of cultivated land, orchard land and forest land in Mengzi karst graben basin in 2030 compared with the changes in 2018 (km²)

	自然情景	微度生态治理情景	适度生态治理情景	强力生态治理情景
耕地减少面积	154.50	202.31	208.72	215.82
果园增加面积	32.53	34.24	34.26	28.52
林地增加面积	24.66	126.39	138.81	152.74

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表 3 不同情景下生态系统服务权衡与协同关系

Table 3. Relationship between trade-off and synergy of ecosystem services in different scenarios

	NPP—产水量	NPP—土壤保持	NPP—食物供给	产水量—土壤保持	产水量—食物供给	土壤保持-食物供给
自然情景	−0.473**	0.362**	−0.377**	−0.122**	0.307**	−0.134**
微度生态治理情景	−0.524**	0.444**	−0.414**	−0.261**	0.403**	−0.074**
适度生态治理情景	−0.508**	0.451**	−0.412**	−0.252**	0.358**	−0.170**
强力生态治理情景	−0.515**	0.453**	−0.417**	−0.260**	0.360**	−0.175**
注：**表示通过了显著性检验。

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