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For: Xue P, Liu H, Zhang M, Gong H, Cao L. Nonlinear Characteristics of NPP Based on Ensemble Empirical Mode Decomposition from 1982 to 2015—A Case Study of Six Coastal Provinces in Southeast China. Remote Sensing 2022;14:15. [DOI: 10.3390/rs14010015] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]

For:	Xue P, Liu H, Zhang M, Gong H, Cao L. Nonlinear Characteristics of NPP Based on Ensemble Empirical Mode Decomposition from 1982 to 2015—A Case Study of Six Coastal Provinces in Southeast China. Remote Sensing 2022;14:15. [DOI: 10.3390/rs14010015] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]

Number

Cited by Other Article(s)

Liu J, Yan Q, Zhang M. Ecosystem carbon storage considering combined environmental and land-use changes in the future and pathways to carbon neutrality in developed regions. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023;903:166204. [PMID: 37567287 DOI: 10.1016/j.scitotenv.2023.166204] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Revised: 08/08/2023] [Accepted: 08/08/2023] [Indexed: 08/13/2023]

Abstract

Assessing the carbon storage capacity of terrestrial ecosystems is crucial for land management and carbon reduction policymaking. There is still a knowledge gap regarding how ecosystem carbon storage will be impacted by combined environmental and land-use factors and their spatial-temporal changes, especially in developed regions where urbanization has slowed down. This study investigated how developed regions in subtropical and tropical areas might increase carbon storage and achieve carbon neutrality, using Guangdong Province in South China as an example. Based on the sustainable development assumption, three land-management scenarios were developed and simulated for 2020-2060 using the Patch-generating Land Use Simulation model. Without considering disturbance and natural losses, carbon storage was estimated by net ecosystem productivity (NEP)-the difference between net primary productivity (NPP) and heterotrophic respiration (HR). NPP was predicted using an artificial neural network model trained by historical NPP data and 16 environmental and land-use variables. HR was predicted using soil respiration models from previous research. Based on the balance between carbon storage and emissions, we predicted the allowable fossil fuel consumption to achieve net-zero CO2 emissions in 2060. The results show that Guangdong's total carbon storage changes from 73.7 MtC in 2020 to 70.6-74.8 MtC in 2060 under different scenarios. Nonlinear relationships exist between the carbon stored and the areas of different land-use types. Topography, temperatures, and land-use configurations jointly lead to significantly varied carbon storage between croplands and between forests in space and time. Protecting and regenerating forests in subtropical areas and forest edges is more effective than afforestation in lowland tropical areas for storing carbon. Net-zero CO2 emissions rely more on reducing emissions than land management. To achieve this, the proportion of fossil energy in total energy consumption should be lowered from 75.5 % in 2020 to ~25 % in 2060.

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Zhang X, Nian L, Liu X, Li X, Adingo S, Liu X, Wang Q, Yang Y, Zhang M, Hui C, Yu W, Zhang X, Ma W, Zhang Y. Spatial-Temporal Correlations between Soil pH and NPP of Grassland Ecosystems in the Yellow River Source Area, China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022;19:ijerph19148852. [PMID: 35886703 PMCID: PMC9323939 DOI: 10.3390/ijerph19148852] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 07/16/2022] [Accepted: 07/19/2022] [Indexed: 11/16/2022]

Abstract

In recent years, ecological concerns such as vegetation destruction, permafrost deterioration, and river drying have been paid much more attention to on the Yellow River Basin in China. Soil pH is regarded to be the fundamental variable among soil properties for vegetation growth, while net primary productivity (NPP) is also an essential indicator to reflect the healthy growth of vegetation. Due to the limitation of on-site samples, the spatial−temporal variations in soil pH and NPP, as well as their intrinsic mechanisms, remain unknown, especially in the Yellow River source area, China. Therefore, it is imperative to investigate the coupling relationship between soil pH and NPP of the area. The study coupled MODIS reflectance data (MOD09A1) with on-site soil pH to estimate spatial−temporal variations in soil pH, explore the response of NPP to soil pH, and assess the extent to which they contribute to grassland ecosystems, thus helping to fill knowledge gaps. Results indicated that the surface spectral reflectance for seven bands could express the geographic pattern of soil pH by applying a multiple linear regression equation; NPP exhibited an increasing trend while soil pH was the contrary in summer from 2000 to 2021. In summer, NPP was negatively correlated with soil pH and there was a lag effect in the response of NPP to soil pH, revealing a correlation between temperate steppes > montane meadows > alpine meadows > swamps in different grassland ecosystems. In addition, contribution indices for temperate steppes and montane meadows were positive whereas they were negative for swamps and alpine meadows, which are apparent findings. The contribution index of montane and alpine meadows was greater than that of temperate steppes and swamps. The approach of the study can enable managers to easily identify and rehabilitate alkaline soil and provides an important reference and practical value for ecological restoration and sustainable development of grassland ecosystems in alpine regions.

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Affiliation(s)

Xiaoning Zhang College of Forestry, Gansu Agricultural University, Lanzhou 730070, China; (X.Z.); (L.N.); (X.L.); (X.L.); (S.A.); (W.M.); (Y.Z.) College of Resources and Environmental Sciences, Gansu Agricultural University, Lanzhou 730070, China; (Y.Y.); (C.H.); (W.Y.); (X.Z.)
Lili Nian College of Forestry, Gansu Agricultural University, Lanzhou 730070, China; (X.Z.); (L.N.); (X.L.); (X.L.); (S.A.); (W.M.); (Y.Z.) College of Resources and Environmental Sciences, Gansu Agricultural University, Lanzhou 730070, China; (Y.Y.); (C.H.); (W.Y.); (X.Z.)
Xingyu Liu College of Forestry, Gansu Agricultural University, Lanzhou 730070, China; (X.Z.); (L.N.); (X.L.); (X.L.); (S.A.); (W.M.); (Y.Z.) College of Resources and Environmental Sciences, Gansu Agricultural University, Lanzhou 730070, China; (Y.Y.); (C.H.); (W.Y.); (X.Z.)
Xiaodan Li College of Forestry, Gansu Agricultural University, Lanzhou 730070, China; (X.Z.); (L.N.); (X.L.); (X.L.); (S.A.); (W.M.); (Y.Z.) College of Management, Gansu Agricultural University, Lanzhou 730070, China;
Samuel Adingo College of Forestry, Gansu Agricultural University, Lanzhou 730070, China; (X.Z.); (L.N.); (X.L.); (X.L.); (S.A.); (W.M.); (Y.Z.)
Xuelu Liu College of Forestry, Gansu Agricultural University, Lanzhou 730070, China; (X.Z.); (L.N.); (X.L.); (X.L.); (S.A.); (W.M.); (Y.Z.) College of Resources and Environmental Sciences, Gansu Agricultural University, Lanzhou 730070, China; (Y.Y.); (C.H.); (W.Y.); (X.Z.) Correspondence:
Quanxi Wang College of Humanities and Law, Northeastern University, Shenyang 110169, China;
Yingbo Yang College of Resources and Environmental Sciences, Gansu Agricultural University, Lanzhou 730070, China; (Y.Y.); (C.H.); (W.Y.); (X.Z.)
Miaomiao Zhang College of Management, Gansu Agricultural University, Lanzhou 730070, China;
Caihong Hui College of Resources and Environmental Sciences, Gansu Agricultural University, Lanzhou 730070, China; (Y.Y.); (C.H.); (W.Y.); (X.Z.)
Wenting Yu College of Resources and Environmental Sciences, Gansu Agricultural University, Lanzhou 730070, China; (Y.Y.); (C.H.); (W.Y.); (X.Z.)
Xinyu Zhang College of Resources and Environmental Sciences, Gansu Agricultural University, Lanzhou 730070, China; (Y.Y.); (C.H.); (W.Y.); (X.Z.)
Wenjun Ma College of Forestry, Gansu Agricultural University, Lanzhou 730070, China; (X.Z.); (L.N.); (X.L.); (X.L.); (S.A.); (W.M.); (Y.Z.) College of Resources and Environmental Sciences, Gansu Agricultural University, Lanzhou 730070, China; (Y.Y.); (C.H.); (W.Y.); (X.Z.)
Yaoquan Zhang College of Forestry, Gansu Agricultural University, Lanzhou 730070, China; (X.Z.); (L.N.); (X.L.); (X.L.); (S.A.); (W.M.); (Y.Z.) College of Resources and Environmental Sciences, Gansu Agricultural University, Lanzhou 730070, China; (Y.Y.); (C.H.); (W.Y.); (X.Z.)

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