Future land use and land cover in Southern Amazonia and resulting greenhouse gas emissions from agricultural soils

Göpel, Jan; Schüngel, Jan; Schaldach, Rüdiger; Meurer, Katharina; Jungkunst, Hermann F.; Franko, Uwe; Boy, Jens; Strey, Robert; Strey, Simone; Guggenberger, Georg; Hampf, Anna; Parker, Phillip S.

doi:10.1007/s10113-017-1235-0

Cited by 18 publications

(8 citation statements)

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“…LULCC scenarios (section 2.3) were generated with the spatially explicit LandSHIFT model. The model is fully described in [54] and has been tested and validated in different case studies for Brazil [26,55,56]. It is based on the concept of land-use systems [57] and couples components that represent the respective anthropogenic and environmental sub-systems.…”

Section: Modeling and Assessment Protocolmentioning

confidence: 99%

“…The following paragraphs briefly describe the central assumptions of the scenarios. For a comprehensive overview of the quantitative scenario assumptions (crop production, crop yield, population, and livestock) see [56]. An elaborate description and discussion of the translation process from qualitative to quantitative information and the respective results for all scenario assumptions is described in Schönenberg et al [62].…”

Section: Plos Onementioning

confidence: 99%

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Assessing the effects of agricultural intensification on natural habitats and biodiversity in Southern Amazonia

et al. 2020

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The ongoing trend toward agricultural intensification in Southern Amazonia makes it essential to explore the future impacts of this development on the extent of natural habitats and biodiversity. This type of analysis requires information on future pathways of land-use and land-cover change (LULCC) under different socio-economic conditions and policy settings. For this purpose, the spatially explicit land-use change model LandSHIFT was applied to calculate a set of high-resolution land-use change scenarios for the Brazilian states Para and Mato Grosso. The period of the analysis were the years 2010–2030. The resulting land-use maps were combined with maps depicting vertebrate species diversity in order to examine the impact of natural habitat loss on species ranges as well as the overall LULCC-induced effect on vertebrate diversity as expressed by the Biodiversity Intactness Index (BII). The results of this study indicate a general decrease in biodiversity intactness in all investigated scenarios. However, agricultural intensification combined with diversified environmental protection policies show least impact of LULCC on vertebrate species richness and conservation of natural habitats compared to scenarios with low agricultural intensification or scenarios with less effective conservation policies.

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Section: Modeling and Assessment Protocolmentioning

confidence: 99%

Section: Plos Onementioning

confidence: 99%

Assessing the effects of agricultural intensification on natural habitats and biodiversity in Southern Amazonia

et al. 2020

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“…The predicted land-use data from these models were used to effectively evaluate the impacts of land-use changes on cropland-N 2 O emissions on small scales (smaller than the national scale). , However, large-scale evaluations are limited because of the weakness of land-use change prediction models. First, land-use prediction is commonly performed in a holistic way in a specific study area. , However, socioeconomic development and land-use change regulations have significant spatial heterogeneity, such as population growth, gross domestic product (GDP) growth rate, and land-use change costs. − Certain researchers have noticed this phenomenon and have improved the land-use prediction model using regional division .…”

Section: Introductionmentioning

confidence: 99%

“…18,19 The predicted land-use data from these models were used to effectively evaluate the impacts of land-use changes on cropland-N 2 O emissions on small scales (smaller than the national scale). 20,21 However, large-scale evaluations are limited because of the weakness of land-use change prediction models. First, land-use prediction is commonly performed in a holistic way in a specific study area.…”

Section: Introductionmentioning

confidence: 99%

A Declining Trend in China’s Future Cropland-N₂O Emissions Due to Reduced Cropland Area

Liu

Zhou

Huang

et al. 2021

Environ. Sci. Technol.

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Croplands are the largest anthropogenic source of nitrous oxide (N2O), a powerful greenhouse gas that contributes to the growing atmospheric N2O burden. However, few studies provide a comprehensive depiction of future cropland-N2O emissions on a national scale due to a lack of accurate cropland prediction data. Herein, we present a newly developed distributed land-use change prediction model for the high-precision prediction of national-scale land-use change. The high-precision land-use data provide an opportunity to elucidate how the changes in cropland area will affect the magnitude and spatial distribution of N2O emissions from China’s croplands during 2020–2070. The results showed a declining trend in China’s total cropland-N2O emissions from 0.44 ± 0.03 Tg N/year in 2020 to 0.39 ± 0.07 Tg N/year in 2070, consistent with a cropland area reduction from (1.78 ± 0.02) × 108 ha to (1.40 ± 0.15) × 108 ha. However, approximately 31% of all calculated cities in China would emit more than the present level. Furthermore, different land use and climate change scenarios would have important impacts on cropland-N2O emissions. The Grain for Green Plan implemented in China would effectively control emissions by approximately 12%.

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“…Land cover is a focal point for mapping and assessing carbon stocks [1][2][3][4] because land cover is a major driver of the distribution and function of carbon stocks, such as Gross Primary Production (GPP) and Net Primary Production (NPP). In addition, habitat fragmentation and species loss are caused by land cover and land use changes [5].…”

Section: Introductionmentioning

confidence: 99%

Effects of spatial–temporal land cover distribution on gross primary production and net primary production in Schleswig-Holstein, northern Germany

2020

Carbon Balance Manage

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Background: Annual total Gross Primary Production (GPP) and Net Primary Production (NPP) and the annual total stored GPP and NPP are tightly coupled to land cover distributions because the distinct vegetation conditions of different land cover classes strongly affect GPP and NPP. Spatial and statistical analysis tools using Geographic Information Systems (GIS) were used to investigate the spatial distribution of each land cover class and the GPP and NPP based on the CORINE land cover classification in the federal state, Schleswig-Holstein, Germany for the years 2000, 2006 and 2012.Results: "Non-irrigated arable land" and "pastures" were the dominant land cover classes. Because of their large area, "non-irrigated arable land" and "pastures" had higher annual total stored GPP and NPP values than the other land cover classes. Annual total GPP and NPP hotspots were concentrated in the central-western part of Schleswig-Holstein. Cold spots were mainly located in the western and eastern Schleswig-Holstein. The distributions of the annual total GPP and NPP hotspots and cold spots were primarily determined by land cover and land cover changes among the investigated years. The average annual total NPP/GPP ratios were 0.5647, 0.5350 and 0.5573 in the years 2000, 2006 and 2012, respectively. The calculated respiration in 2006 was the highest, followed by those in 2012 and 2000. Conclusions:The land cover classes with high-ability of carbon stocks in 2000, 2006 and 2012 in Schleswig-Holstein were identified in this study. Furthermore, it is recommendable to enhance the annual total GPP and NPP and the annual total stored GPP and NPP in Schleswig-Holstein by replacing the land cover classes showing low carbon stock capabilities with the classes showing high abilities for the purpose of increasing greenhouse gas fixation.

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Future land use and land cover in Southern Amazonia and resulting greenhouse gas emissions from agricultural soils

Cited by 18 publications

References 61 publications

Assessing the effects of agricultural intensification on natural habitats and biodiversity in Southern Amazonia

Assessing the effects of agricultural intensification on natural habitats and biodiversity in Southern Amazonia

A Declining Trend in China’s Future Cropland-N₂O Emissions Due to Reduced Cropland Area

Effects of spatial–temporal land cover distribution on gross primary production and net primary production in Schleswig-Holstein, northern Germany

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Future land use and land cover in Southern Amazonia and resulting greenhouse gas emissions from agricultural soils

Cited by 18 publications

References 61 publications

Assessing the effects of agricultural intensification on natural habitats and biodiversity in Southern Amazonia

Assessing the effects of agricultural intensification on natural habitats and biodiversity in Southern Amazonia

A Declining Trend in China’s Future Cropland-N2O Emissions Due to Reduced Cropland Area

Effects of spatial–temporal land cover distribution on gross primary production and net primary production in Schleswig-Holstein, northern Germany

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A Declining Trend in China’s Future Cropland-N₂O Emissions Due to Reduced Cropland Area