Linear and non-linear dynamics of ecosystem services supply, demand, and mismatches across a rapidly urbanizing region
Achieving the sustainability of coupled human-nature systems requires matching the ecosystem services (ES) provided by nature to the needs of society. However, most of the current studies on ES supply–demand relationships focus on spatial mismatches and rarely consider their temporal dynamics. In th...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-01-01
|
| Series: | Ecological Indicators |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X24000712 |
| _version_ | 1827378258727927808 |
|---|---|
| author | Zhen Zhong Xuening Fang Jingwei Li Qun Ma Rui Zhou Yina Hu Shiqiang Du |
| author_facet | Zhen Zhong Xuening Fang Jingwei Li Qun Ma Rui Zhou Yina Hu Shiqiang Du |
| author_sort | Zhen Zhong |
| collection | DOAJ |
| description | Achieving the sustainability of coupled human-nature systems requires matching the ecosystem services (ES) provided by nature to the needs of society. However, most of the current studies on ES supply–demand relationships focus on spatial mismatches and rarely consider their temporal dynamics. In this study, the year-by-year dynamics (2001–2020) of 12 ESs at multiple spatial scales were investigated by using space–time interaction (STI) analysis, fuzzy C-mean clustering, and emerging hotspot analysis. We found that (1) three forms of temporal dynamics of ES indicators can be identified, including linear dynamics, fluctuating dynamics, and regime shift dynamics. (2) Temporal dynamic patterns of the same ES were not consistent across all counties, showing great spatial heterogeneity. The temporal dynamics of each ES type at each county were spatially explicitly clustered into linear dynamics, fluctuating dynamics, and regime shift dynamics with different means. (3) The ES supply–demand relationships can shift between supply–demand balance, excess supply, and excess demand when the temporal dynamics of ES supply do not match with that of ES demand. Our results suggest that temporal dynamic analysis in ecological restoration effectiveness assessment can help to avoid erroneous results compared to considering only pre- and post-policy ES changes. The identified emerging hotspots of excess supply and excess demand can help decision-makers more accurately identify priority locations for management. |
| first_indexed | 2024-03-08T12:52:25Z |
| format | Article |
| id | doaj.art-751c9920f0574464abde9dd141345626 |
| institution | Directory Open Access Journal |
| issn | 1470-160X |
| language | English |
| last_indexed | 2024-03-08T12:52:25Z |
| publishDate | 2024-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecological Indicators |
| spelling | doaj.art-751c9920f0574464abde9dd1413456262024-01-20T04:44:44ZengElsevierEcological Indicators1470-160X2024-01-01158111614Linear and non-linear dynamics of ecosystem services supply, demand, and mismatches across a rapidly urbanizing regionZhen Zhong0Xuening Fang1Jingwei Li2Qun Ma3Rui Zhou4Yina Hu5Shiqiang Du6School of Environmental and Geographical Sciences, Shanghai Normal University, Shanghai 200234, ChinaSchool of Environmental and Geographical Sciences, Shanghai Normal University, Shanghai 200234, China; Yangtze River Delta Urban Wetland Ecosystem National Field Scientific Observation and Research Station, Shanghai 200234, China; Corresponding author at: School of Environmental and Geographical Sciences, Shanghai Normal University, Shanghai 200234, China.School of Environmental and Geographical Sciences, Shanghai Normal University, Shanghai 200234, China; Yangtze River Delta Urban Wetland Ecosystem National Field Scientific Observation and Research Station, Shanghai 200234, ChinaSchool of Environmental and Geographical Sciences, Shanghai Normal University, Shanghai 200234, China; Yangtze River Delta Urban Wetland Ecosystem National Field Scientific Observation and Research Station, Shanghai 200234, ChinaSchool of Environmental and Geographical Sciences, Shanghai Normal University, Shanghai 200234, China; Yangtze River Delta Urban Wetland Ecosystem National Field Scientific Observation and Research Station, Shanghai 200234, ChinaSchool of Environmental and Geographical Sciences, Shanghai Normal University, Shanghai 200234, China; Yangtze River Delta Urban Wetland Ecosystem National Field Scientific Observation and Research Station, Shanghai 200234, ChinaSchool of Environmental and Geographical Sciences, Shanghai Normal University, Shanghai 200234, China; Yangtze River Delta Urban Wetland Ecosystem National Field Scientific Observation and Research Station, Shanghai 200234, ChinaAchieving the sustainability of coupled human-nature systems requires matching the ecosystem services (ES) provided by nature to the needs of society. However, most of the current studies on ES supply–demand relationships focus on spatial mismatches and rarely consider their temporal dynamics. In this study, the year-by-year dynamics (2001–2020) of 12 ESs at multiple spatial scales were investigated by using space–time interaction (STI) analysis, fuzzy C-mean clustering, and emerging hotspot analysis. We found that (1) three forms of temporal dynamics of ES indicators can be identified, including linear dynamics, fluctuating dynamics, and regime shift dynamics. (2) Temporal dynamic patterns of the same ES were not consistent across all counties, showing great spatial heterogeneity. The temporal dynamics of each ES type at each county were spatially explicitly clustered into linear dynamics, fluctuating dynamics, and regime shift dynamics with different means. (3) The ES supply–demand relationships can shift between supply–demand balance, excess supply, and excess demand when the temporal dynamics of ES supply do not match with that of ES demand. Our results suggest that temporal dynamic analysis in ecological restoration effectiveness assessment can help to avoid erroneous results compared to considering only pre- and post-policy ES changes. The identified emerging hotspots of excess supply and excess demand can help decision-makers more accurately identify priority locations for management.http://www.sciencedirect.com/science/article/pii/S1470160X24000712Ecosystem servicesTemporal dynamicsSupply–demandUrban sustainabilityLandscape sustainabilityYangtze River Delta |
| spellingShingle | Zhen Zhong Xuening Fang Jingwei Li Qun Ma Rui Zhou Yina Hu Shiqiang Du Linear and non-linear dynamics of ecosystem services supply, demand, and mismatches across a rapidly urbanizing region Ecological Indicators Ecosystem services Temporal dynamics Supply–demand Urban sustainability Landscape sustainability Yangtze River Delta |
| title | Linear and non-linear dynamics of ecosystem services supply, demand, and mismatches across a rapidly urbanizing region |
| title_full | Linear and non-linear dynamics of ecosystem services supply, demand, and mismatches across a rapidly urbanizing region |
| title_fullStr | Linear and non-linear dynamics of ecosystem services supply, demand, and mismatches across a rapidly urbanizing region |
| title_full_unstemmed | Linear and non-linear dynamics of ecosystem services supply, demand, and mismatches across a rapidly urbanizing region |
| title_short | Linear and non-linear dynamics of ecosystem services supply, demand, and mismatches across a rapidly urbanizing region |
| title_sort | linear and non linear dynamics of ecosystem services supply demand and mismatches across a rapidly urbanizing region |
| topic | Ecosystem services Temporal dynamics Supply–demand Urban sustainability Landscape sustainability Yangtze River Delta |
| url | http://www.sciencedirect.com/science/article/pii/S1470160X24000712 |
| work_keys_str_mv | AT zhenzhong linearandnonlineardynamicsofecosystemservicessupplydemandandmismatchesacrossarapidlyurbanizingregion AT xueningfang linearandnonlineardynamicsofecosystemservicessupplydemandandmismatchesacrossarapidlyurbanizingregion AT jingweili linearandnonlineardynamicsofecosystemservicessupplydemandandmismatchesacrossarapidlyurbanizingregion AT qunma linearandnonlineardynamicsofecosystemservicessupplydemandandmismatchesacrossarapidlyurbanizingregion AT ruizhou linearandnonlineardynamicsofecosystemservicessupplydemandandmismatchesacrossarapidlyurbanizingregion AT yinahu linearandnonlineardynamicsofecosystemservicessupplydemandandmismatchesacrossarapidlyurbanizingregion AT shiqiangdu linearandnonlineardynamicsofecosystemservicessupplydemandandmismatchesacrossarapidlyurbanizingregion |