Global impacts of future urban expansion on terrestrial vertebrate diversity

Nature Communications, Journal Year: 2022, Volume and Issue: 13(1)

Published: March 25, 2022

Abstract Rapid urban expansion has profound impacts on global biodiversity through habitat conversion, degradation, fragmentation, and species extinction. However, how future will affect needs to be better understood. We contribute filling this knowledge gap by combining spatially explicit projections of under shared socioeconomic pathways (SSPs) with datasets terrestrial (amphibians, mammals, birds). Overall, lead 11–33 million hectares natural loss 2100 the SSP scenarios disproportionately cause large fragmentation. The within current key priority areas is projected higher (e.g., 37–44% in WWF’s Global 200) than average. Moreover, land conversion reduce local within-site richness 34% abundance 52% per 1 km grid cell, 7–9 may lost 10 cell. Our study suggests an urgent need develop a sustainable development pathway balance conservation.

Language: Английский

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The spatial association of ecosystem services with land use and land cover change at the county level in China, 1995–2015

The Science of The Total Environment, Journal Year: 2019, Volume and Issue: 669, P. 459 - 470

Published: March 11, 2019

Language: Английский

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Considering landscape-level processes in ecosystem service assessments

The Science of The Total Environment, Journal Year: 2021, Volume and Issue: 796, P. 149028 - 149028

Published: July 13, 2021

Language: Английский

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Simulating land use change for sustainable land management in China's coal resource-based cities under different scenarios

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 916, P. 170126 - 170126

Published: Jan. 20, 2024

Language: Английский

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Examining effects of climate change and land use dynamic on biophysical and economic values of ecosystem services of a natural reserve region

Journal of Cleaner Production, Journal Year: 2020, Volume and Issue: 257, P. 120424 - 120424

Published: Feb. 14, 2020

Ecosystem Service Valuation (ESV) is a process of evaluating and quantifying the monetary values ESs their functions. Using both biophysical spatially explicit integrated models, key Services (ESs) were estimated in Sundarbans Biosphere Region (SBR), India. Quantification was made time series (1982–2017) individual years (1973, 1988, 2003, 2013, 2018, 2025, 2035, 2045) to understand impact climate change land-use dynamics on long-term ecological status region. The then obtained from Net Primary Productivity (NPP) Integrated Trade-offs (InVEST), Cellular Automata Markov Chain Model (CA-Markov). NPP increased significantly during first half period (1982–1999), but declined second (2000–2017). highest ESVs (US$ ha−1) found for habitat service (30780), nutrient cycling (12626), gas regulation (7224.81), whereas, lower approximated water (347.81), raw material production (777.82) waste treatment (13.57) services. Among nine evaluated, regulation, disturbance most important regulating services SBR. combined effects are much stringent vulnerable region like Most closely associated with fluctuation land use cover input. Thus, management policies reform strategies that will encourage conversion productive land, especially highly mangrove forest, development or any other financial benefits, would disturb ideal human-nature balance this ecosystem. outcomes study also provide an reference administrators, researchers, decision-makers comprehend expected social-ecological juxtaposition protected natural reserve Sundarbans.

Language: Английский

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Modeling land cover change based on an artificial neural network for a semiarid river basin in northeastern Brazil

Global Ecology and Conservation, Journal Year: 2019, Volume and Issue: 21, P. e00811 - e00811

Published: Oct. 11, 2019

Accelerated changes in land cover cause environmental dynamics and may degradation. The goals of the present paper were to analyze estimate a future scenario for 2035 using an artificial neural network Taperoá River basin, located northeastern Brazil. classification was carried out years t1 (1990), t2 (1999) t3 (2002), with latter being used validate prediction obtain year t4 (2035). classes identified basin (a) water bodies, (b) tree-shrub vegetation, (c) shrub (d) herbaceous-shrub (e) herbaceous vegetation. results classifications analyzed kappa coefficient, total operating characteristic (TOC), area under curve (AUC). dynamic modeling based on multilayer perceptron (MLP) network, which presented very good results, accuracy = 89.69% after 10,000 iterations, 0.61 AUC 0.67. change analysis showed decrease class increase vegetation between analyzed. predicted occupied by

Language: Английский

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Water-energy nexus within urban agglomeration: An assessment framework combining the multiregional input-output model, virtual water, and embodied energy

Resources Conservation and Recycling, Journal Year: 2020, Volume and Issue: 164, P. 105113 - 105113

Published: Aug. 27, 2020

Language: Английский

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China's energy-related carbon emissions projections for the shared socioeconomic pathways

Resources Conservation and Recycling, Journal Year: 2021, Volume and Issue: 168, P. 105456 - 105456

Published: Feb. 6, 2021

Language: Английский

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Characterizing the spatial pattern of annual urban growth by using time series Landsat imagery

The Science of The Total Environment, Journal Year: 2019, Volume and Issue: 666, P. 274 - 284

Published: Feb. 12, 2019

Language: Английский

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Spatio-temporal changes in water-related ecosystem services provision and trade-offs with food production

Journal of Cleaner Production, Journal Year: 2020, Volume and Issue: 286, P. 125316 - 125316

Published: Nov. 30, 2020

Language: Английский

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