Huanhuan Pan , Ziqiang Du , Zhitao Wu , Hong Zhang , Keming Ma
{"title":"在能源和化学工业领域建立基于生态系统服务的生态网络","authors":"Huanhuan Pan , Ziqiang Du , Zhitao Wu , Hong Zhang , Keming Ma","doi":"10.1016/j.ecolmodel.2024.110897","DOIUrl":null,"url":null,"abstract":"<div><div>The massive utilization of fossil energy by humans has promoted socio-economic development. However, it has also generated severe regional eco-environmental problems, including water shortage, soil erosion, and land desertification. An optimal ecological-network-based regulation of eco-environmentally damaged areas is necessary to balance economic development with rigid eco-environmental constraints in pursuit of sustainable regional development. Using remote-sensing, meteorology, land use, and soil data of energy and chemical industrial areas in the mid-upper reaches of the Yellow River, we quantitatively evaluated the related ecosystem services (ESs) by applying InVEST, CASA, and RWEQ models. Additionally, we constructed ecological conservation networks comprising ecological source areas, resistance surface, corridors, and nodes. The results are as follows. First, from 2000 to 2020, the areas of cultivated and unused land decreased, but those of forest, grassland, water bodies, and construction land increased. Regarding spatial distribution, the proportion of grassland was the highest, followed by unused land, and other types of land accounting for a relatively low proportion. Second, from 2000 to 2020, all ESs and the overall ecosystem improved. However, ESs demonstrated a clear spatial heterogeneity (i.e., better in the southeast than in the northwest). Third, comparing the two ecological networks constructed by minimum cumulative resistance (MCR) and circuit models, the MCR-based ecological network was considered better because of its higher ε, θ, and σ values. Robustness analysis also showed that the MCR-based ecological network was more stable. Finally, ecological source areas of 110,300 km<sup>2</sup> were obtained, accounting for 21.69 % of the study region. Ecological resistance was relatively high in desert areas, which are to the northwest of the study region, and relatively low in the southeast. Fifty-nine ecological corridors (including 31 important ones) and 22 ecological nodes were extracted. The finalized ecological network was diamond-shaped, with the ecological source areas in four directions (i.e., east, south, west, and north) of the study region being closely connected. To promote the spatial optimization of the study region, appropriate measures (e.g., afforestation and soil improvement) must be taken to reduce regional imbalance in ecological condition, improve ecosystem functions and landscape connectivity, reduce various resistance, and ultimately promote conservation outcomes.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":null,"pages":null},"PeriodicalIF":2.6000,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Building ecosystem services-based ecological networks in energy and chemical industry areas\",\"authors\":\"Huanhuan Pan , Ziqiang Du , Zhitao Wu , Hong Zhang , Keming Ma\",\"doi\":\"10.1016/j.ecolmodel.2024.110897\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The massive utilization of fossil energy by humans has promoted socio-economic development. However, it has also generated severe regional eco-environmental problems, including water shortage, soil erosion, and land desertification. An optimal ecological-network-based regulation of eco-environmentally damaged areas is necessary to balance economic development with rigid eco-environmental constraints in pursuit of sustainable regional development. Using remote-sensing, meteorology, land use, and soil data of energy and chemical industrial areas in the mid-upper reaches of the Yellow River, we quantitatively evaluated the related ecosystem services (ESs) by applying InVEST, CASA, and RWEQ models. Additionally, we constructed ecological conservation networks comprising ecological source areas, resistance surface, corridors, and nodes. The results are as follows. First, from 2000 to 2020, the areas of cultivated and unused land decreased, but those of forest, grassland, water bodies, and construction land increased. Regarding spatial distribution, the proportion of grassland was the highest, followed by unused land, and other types of land accounting for a relatively low proportion. Second, from 2000 to 2020, all ESs and the overall ecosystem improved. However, ESs demonstrated a clear spatial heterogeneity (i.e., better in the southeast than in the northwest). Third, comparing the two ecological networks constructed by minimum cumulative resistance (MCR) and circuit models, the MCR-based ecological network was considered better because of its higher ε, θ, and σ values. Robustness analysis also showed that the MCR-based ecological network was more stable. Finally, ecological source areas of 110,300 km<sup>2</sup> were obtained, accounting for 21.69 % of the study region. Ecological resistance was relatively high in desert areas, which are to the northwest of the study region, and relatively low in the southeast. Fifty-nine ecological corridors (including 31 important ones) and 22 ecological nodes were extracted. The finalized ecological network was diamond-shaped, with the ecological source areas in four directions (i.e., east, south, west, and north) of the study region being closely connected. To promote the spatial optimization of the study region, appropriate measures (e.g., afforestation and soil improvement) must be taken to reduce regional imbalance in ecological condition, improve ecosystem functions and landscape connectivity, reduce various resistance, and ultimately promote conservation outcomes.</div></div>\",\"PeriodicalId\":51043,\"journal\":{\"name\":\"Ecological Modelling\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2024-10-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Ecological Modelling\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0304380024002850\",\"RegionNum\":3,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ECOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ecological Modelling","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0304380024002850","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECOLOGY","Score":null,"Total":0}
Building ecosystem services-based ecological networks in energy and chemical industry areas
The massive utilization of fossil energy by humans has promoted socio-economic development. However, it has also generated severe regional eco-environmental problems, including water shortage, soil erosion, and land desertification. An optimal ecological-network-based regulation of eco-environmentally damaged areas is necessary to balance economic development with rigid eco-environmental constraints in pursuit of sustainable regional development. Using remote-sensing, meteorology, land use, and soil data of energy and chemical industrial areas in the mid-upper reaches of the Yellow River, we quantitatively evaluated the related ecosystem services (ESs) by applying InVEST, CASA, and RWEQ models. Additionally, we constructed ecological conservation networks comprising ecological source areas, resistance surface, corridors, and nodes. The results are as follows. First, from 2000 to 2020, the areas of cultivated and unused land decreased, but those of forest, grassland, water bodies, and construction land increased. Regarding spatial distribution, the proportion of grassland was the highest, followed by unused land, and other types of land accounting for a relatively low proportion. Second, from 2000 to 2020, all ESs and the overall ecosystem improved. However, ESs demonstrated a clear spatial heterogeneity (i.e., better in the southeast than in the northwest). Third, comparing the two ecological networks constructed by minimum cumulative resistance (MCR) and circuit models, the MCR-based ecological network was considered better because of its higher ε, θ, and σ values. Robustness analysis also showed that the MCR-based ecological network was more stable. Finally, ecological source areas of 110,300 km2 were obtained, accounting for 21.69 % of the study region. Ecological resistance was relatively high in desert areas, which are to the northwest of the study region, and relatively low in the southeast. Fifty-nine ecological corridors (including 31 important ones) and 22 ecological nodes were extracted. The finalized ecological network was diamond-shaped, with the ecological source areas in four directions (i.e., east, south, west, and north) of the study region being closely connected. To promote the spatial optimization of the study region, appropriate measures (e.g., afforestation and soil improvement) must be taken to reduce regional imbalance in ecological condition, improve ecosystem functions and landscape connectivity, reduce various resistance, and ultimately promote conservation outcomes.
期刊介绍:
The journal is concerned with the use of mathematical models and systems analysis for the description of ecological processes and for the sustainable management of resources. Human activity and well-being are dependent on and integrated with the functioning of ecosystems and the services they provide. We aim to understand these basic ecosystem functions using mathematical and conceptual modelling, systems analysis, thermodynamics, computer simulations, and ecological theory. This leads to a preference for process-based models embedded in theory with explicit causative agents as opposed to strictly statistical or correlative descriptions. These modelling methods can be applied to a wide spectrum of issues ranging from basic ecology to human ecology to socio-ecological systems. The journal welcomes research articles, short communications, review articles, letters to the editor, book reviews, and other communications. The journal also supports the activities of the [International Society of Ecological Modelling (ISEM)](http://www.isemna.org/).