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Demand for Ecosystem Services Drive Large-Scale Shifts in Land-Use in Tropical Mountainous Watersheds Prone to Landslides. REMOTE SENSING 2022. [DOI: 10.3390/rs14133097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
An increasing frequency of extreme atmospheric events is challenging our basic knowledge about the resilience mechanisms that mediate the response of small mountainous watersheds (SMW) to landslides, including production of water-derived ecosystem services (WES). We hypothesized that the demand for WES increases the connectivity between lowland and upland regions, and decreases the heterogeneity of SMW. Focusing on four watersheds in the Central Andes of Colombia and combining “site-specific knowledge”, historic land cover maps (1970s and 1980s), and open, analysis-ready remotely sensed data (GLAD Landsat ARD; 1990–2000), we addressed three questions. Over roughly 120 years, the site-specific data revealed an increasing demand for diverse WES, as well as variation among the watersheds in the supply of WES. At watershed-scales, variation in the water balances—a surrogate for water-derived ES flows—exhibited complex relationships with forest cover. Fractional forest cover (pi) and forest aggregation (AIi) varied between the historic and current data sets, but in general showed non-linear relationships with elevation and slope. In the current data set (1990–2000), differences in the number of significant, linear models explaining variation in pi with time, suggest that slope may play a more important role than elevation in land cover change. We found ample evidence for a combined effect of slope and elevation on the two land cover metrics, which would be consistent with strategies directed to mitigate site-specific landslide-associated risks. Overall, our work shows strong feedbacks between lowland and upland areas, raising questions about the sustainable production of WES.
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Warm–Wet Climate Trend Enhances Net Primary Production of the Main Ecosystems in China during 2000–2021. ATMOSPHERE 2022. [DOI: 10.3390/atmos13050738] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
A significant greening trend has been reported globally in recent decades. The greening indicates the improvement in net primary production (NPP) in vegetation. Adopting statistics-based regression models, we investigated the dynamics of NPP and its climatic drivers in main ecosystems (forest land, grass land, and unused land) over China during the period 2000–2021. The results confirmed an increasing NPP covering approximately 86% area in the main ecosystems. NPP exhibited an increase rate of 6.11 g C m−2 yr−1 in forest land, 4.77 g C m−2 yr−1 in grass land, and 1.25 g C m−2 yr−1 in unused land, respectively. Over the same period, warm–wet climate trend was observed covering approximately 90% of the main ecosystems. The warm–wet climate has had a positive effect rather than negative effect on NPP in the main ecosystems, judging by their significant positive correlation. Our results suggested that the increase in annual precipitation exerted much more important effect on the increasing NPP. The warm–wet climate trend contributes to the upward trend in NPP, even if variability in NPP might involve the influence of solar radiation, atmospheric aerosols, CO2 fertilization, nitrogen deposition, human intervention, etc.
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Naeem S, Zhang Y, Zhang X, Tian J, Abbas S, Luo L, Meresa HK. Both climate and socioeconomic drivers contribute to vegetation greening of the Loess Plateau. Sci Bull (Beijing) 2021; 66:1160-1163. [PMID: 36654352 DOI: 10.1016/j.scib.2021.03.007] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Revised: 01/20/2021] [Accepted: 01/21/2021] [Indexed: 01/20/2023]
Affiliation(s)
- Shahid Naeem
- Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Yongqiang Zhang
- Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
| | - Xuanze Zhang
- Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Jing Tian
- Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Sawaid Abbas
- Department of Land Surveying and Geo-Informatics, the Hong Kong Polytechnic University, Hong Kong, China
| | - Lili Luo
- Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Hadush Kidane Meresa
- Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
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Zhang Q, Wang Y, Tao S, Bilsborrow RE, Qiu T, Liu C, Sannigrahi S, Li Q, Song C. Divergent socioeconomic-ecological outcomes of China's Conversion of Cropland to Forest Program in the subtropical mountainous area and the semi-arid Loess Plateau. ECOSYSTEM SERVICES 2020; 45:101167. [PMID: 32953433 PMCID: PMC7494128 DOI: 10.1016/j.ecoser.2020.101167] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
China's Conversion of Cropland to Forest Program (CCFP) is one of the world's largest Payments for Ecosystem Services (PES) programs. Its socioeconomic-ecological effects are of great interest to both scholars and policy-makers. However, little is known about how the socioeconomic-ecological outcomes of CCFP differ across geographic regions. This study integrates household survey data, satellite imagery, and statistical models to examine labor migration and forest dynamics under CCFP. The investigation is carried out at two mountainous sites with distinct biophysical and socioeconomic conditions, one in a subtropical mountainous region (Anhui) and the other in the semi-arid Loess Plateau (Shanxi). We found divergent CCFP outcomes on migration behavior, stimulating both local- and distant-migration in the Anhui site while discouraging distant-migration in the Shanxi site, after controlling for factors at the individual, household, community and regional levels. Forest recovery is positively associated with distant-migration in Anhui but with local-migration in Shanxi. Contextual factors interact with demographic-socioeconomic factors to influence household livelihoods in both areas, leading to various socio-ecological pathways from CCFP participation to enhanced forest sustainability. Regional differences should therefore be taken into account in the design of future large-scale PES programs.
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Affiliation(s)
- Qi Zhang
- Frederick S. Pardee Center for the Study of the Longer-Range Future, Frederick S. Pardee School of Global Studies, Boston University, Boston, MA 02215, USA
| | - Ying Wang
- School of Public Administration, China University of Geosciences, Wuhan, Hubei 430074, China
| | - Shiqi Tao
- Graduate School of Geography, Clark University, Worcester, MA 01610, USA
| | - Richard E. Bilsborrow
- Department of Geography, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27516, USA
| | - Tong Qiu
- Department of Geography, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Chong Liu
- School of Geospatial Engineering and Science, Sun Yat-Sen University, Guangzhou 510275, China
| | - Srikanta Sannigrahi
- School of Architecture, Planning, and Environmental Policy, University College Dublin, Belfield, Dublin 4, Ireland
| | - Qirui Li
- Climatology Research Group, University of Bayreuth, 95447 Bayreuth, Germany
| | - Conghe Song
- Department of Geography, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27516, USA
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