Exploring the complex relationships and drivers of ecosystem services across different geomorphological types in the Beijing-Tianjin-Hebei region, China (2000–2018)

Ecosystem services (ESs), as important indicators for ecosystem conditions, are always interacted complexly, however, the underlying mechanisms remain not fully understood. The Beijing-Tianjin-Hebei (BTH) region is a typical example of this complexity and is one of the most populous regions globally...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Huan Wang, Laibao Liu, Le Yin, Jiashu Shen, Shuangcheng Li
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Ecosystem services Temporal variability Trade-offs Synergies Drivers Spatial heterogeneity Ecology QH540-549.5
Acceso en línea:	https://doaj.org/article/ac2155cdb7904f11ab1da3d1f1a9ca91
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:ac2155cdb7904f11ab1da3d1f1a9ca91
record_format	dspace
spelling	oai:doaj.org-article:ac2155cdb7904f11ab1da3d1f1a9ca912021-12-01T04:35:35ZExploring the complex relationships and drivers of ecosystem services across different geomorphological types in the Beijing-Tianjin-Hebei region, China (2000–2018)1470-160X10.1016/j.ecolind.2020.107116https://doaj.org/article/ac2155cdb7904f11ab1da3d1f1a9ca912021-02-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1470160X20310554https://doaj.org/toc/1470-160XEcosystem services (ESs), as important indicators for ecosystem conditions, are always interacted complexly, however, the underlying mechanisms remain not fully understood. The Beijing-Tianjin-Hebei (BTH) region is a typical example of this complexity and is one of the most populous regions globally. In this study, we take the BTH region as the study area and try to identify the spatiotemporally complex relationships and dominant drivers of ESs, by utilizing multiple methods: Pearson correlation analysis, partial correlation analysis and the GeoDetector method. Three critically important ESs: soil erosion, water yield, and net primary production (NPP) are simulated for the period of 2000 to 2018. The results show that the Pearson correlation coefficient indicated a synergistic relationship between soil erosion and water yield and between water yield and NPP and a trade-off relationship between soil erosion and NPP, while the partial correlation analysis using the normalized difference vegetation index (NDVI) and precipitation as controlling factors showed that the relationships between soil erosion and water yield and between water yield and NPP were transformed to trade-offs. We confirmed that the drivers (especially the shared drivers and dominant drivers of each ecosystem service) played important roles in the direction of complex relationships; when different factors were involved in the relationships, the direction of positive or negative relationships may be diverse. Furthermore, the slope (q = 0.32), precipitation (q = 0.42) and NDVI (q = 0.72) were the dominant factors for soil erosion, water yield and NPP, respectively. The power of determinants for ESs showed high spatial heterogeneity in different geomorphological types due to differences in each type of inner characteristic; for example, the q value of slope for soil erosion decreased with increasing mountain relief, but the q value of NDVI increased. In addition, the trade-off degree among the three ESs was spatially heterogeneous; in mountainous areas the trade-off scores were much higher than those in relatively flat areas. Our general approaches and results provide useful references for researchers and policy makers to understand the mechanisms governing complex relationships among ESs and to manage ESs by manipulating these drivers to enhance synergies or weaken trade-offs.Huan WangLaibao LiuLe YinJiashu ShenShuangcheng LiElsevierarticleEcosystem servicesTemporal variabilityTrade-offsSynergiesDriversSpatial heterogeneityEcologyQH540-549.5ENEcological Indicators, Vol 121, Iss , Pp 107116- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Ecosystem services Temporal variability Trade-offs Synergies Drivers Spatial heterogeneity Ecology QH540-549.5
spellingShingle	Ecosystem services Temporal variability Trade-offs Synergies Drivers Spatial heterogeneity Ecology QH540-549.5 Huan Wang Laibao Liu Le Yin Jiashu Shen Shuangcheng Li Exploring the complex relationships and drivers of ecosystem services across different geomorphological types in the Beijing-Tianjin-Hebei region, China (2000–2018)
description	Ecosystem services (ESs), as important indicators for ecosystem conditions, are always interacted complexly, however, the underlying mechanisms remain not fully understood. The Beijing-Tianjin-Hebei (BTH) region is a typical example of this complexity and is one of the most populous regions globally. In this study, we take the BTH region as the study area and try to identify the spatiotemporally complex relationships and dominant drivers of ESs, by utilizing multiple methods: Pearson correlation analysis, partial correlation analysis and the GeoDetector method. Three critically important ESs: soil erosion, water yield, and net primary production (NPP) are simulated for the period of 2000 to 2018. The results show that the Pearson correlation coefficient indicated a synergistic relationship between soil erosion and water yield and between water yield and NPP and a trade-off relationship between soil erosion and NPP, while the partial correlation analysis using the normalized difference vegetation index (NDVI) and precipitation as controlling factors showed that the relationships between soil erosion and water yield and between water yield and NPP were transformed to trade-offs. We confirmed that the drivers (especially the shared drivers and dominant drivers of each ecosystem service) played important roles in the direction of complex relationships; when different factors were involved in the relationships, the direction of positive or negative relationships may be diverse. Furthermore, the slope (q = 0.32), precipitation (q = 0.42) and NDVI (q = 0.72) were the dominant factors for soil erosion, water yield and NPP, respectively. The power of determinants for ESs showed high spatial heterogeneity in different geomorphological types due to differences in each type of inner characteristic; for example, the q value of slope for soil erosion decreased with increasing mountain relief, but the q value of NDVI increased. In addition, the trade-off degree among the three ESs was spatially heterogeneous; in mountainous areas the trade-off scores were much higher than those in relatively flat areas. Our general approaches and results provide useful references for researchers and policy makers to understand the mechanisms governing complex relationships among ESs and to manage ESs by manipulating these drivers to enhance synergies or weaken trade-offs.
format	article
author	Huan Wang Laibao Liu Le Yin Jiashu Shen Shuangcheng Li
author_facet	Huan Wang Laibao Liu Le Yin Jiashu Shen Shuangcheng Li
author_sort	Huan Wang
title	Exploring the complex relationships and drivers of ecosystem services across different geomorphological types in the Beijing-Tianjin-Hebei region, China (2000–2018)
title_short	Exploring the complex relationships and drivers of ecosystem services across different geomorphological types in the Beijing-Tianjin-Hebei region, China (2000–2018)
title_full	Exploring the complex relationships and drivers of ecosystem services across different geomorphological types in the Beijing-Tianjin-Hebei region, China (2000–2018)
title_fullStr	Exploring the complex relationships and drivers of ecosystem services across different geomorphological types in the Beijing-Tianjin-Hebei region, China (2000–2018)
title_full_unstemmed	Exploring the complex relationships and drivers of ecosystem services across different geomorphological types in the Beijing-Tianjin-Hebei region, China (2000–2018)
title_sort	exploring the complex relationships and drivers of ecosystem services across different geomorphological types in the beijing-tianjin-hebei region, china (2000–2018)
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/ac2155cdb7904f11ab1da3d1f1a9ca91
work_keys_str_mv	AT huanwang exploringthecomplexrelationshipsanddriversofecosystemservicesacrossdifferentgeomorphologicaltypesinthebeijingtianjinhebeiregionchina20002018 AT laibaoliu exploringthecomplexrelationshipsanddriversofecosystemservicesacrossdifferentgeomorphologicaltypesinthebeijingtianjinhebeiregionchina20002018 AT leyin exploringthecomplexrelationshipsanddriversofecosystemservicesacrossdifferentgeomorphologicaltypesinthebeijingtianjinhebeiregionchina20002018 AT jiashushen exploringthecomplexrelationshipsanddriversofecosystemservicesacrossdifferentgeomorphologicaltypesinthebeijingtianjinhebeiregionchina20002018 AT shuangchengli exploringthecomplexrelationshipsanddriversofecosystemservicesacrossdifferentgeomorphologicaltypesinthebeijingtianjinhebeiregionchina20002018
_version_	1718405863455064064

Exploring the complex relationships and drivers of ecosystem services across different geomorphological types in the Beijing-Tianjin-Hebei region, China (2000–2018)

Ejemplares similares