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Disturbance Effects on Soil Carbon and Greenhouse Gas Emissions in Forest Ecosystems

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ISBN: 9783039286669 / 9783039286676 Year: Pages: 232 DOI: 10.3390/books978-3-03928-667-6 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Biology --- Forestry
Added to DOAB on : 2020-06-09 16:38:57
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Abstract

Forest ecosystems are often disturbed by agents such as harvesting, fire, wind, insects and diseases, and acid deposition, with differing intensities and frequencies. Such disturbances can markedly affect the amount, form, and stability of soil organic carbon in, and the emission of greenhouse gases, including CO2, CH4, and N2O from, forest ecosystems. It is vitally important that we improve our understanding of the impact of different disturbance regimes on forest soil carbon dynamics and greenhouse gas emissions to guide our future research, forest management practices, and policy development. This Special Issue provides an important update on the disturbance effects on soil carbon and greenhouse gas emissions in forest ecosystems in different climate regions.

Keywords

carbon stock changes --- forest --- greenhouse gas inventory --- IPCC --- South Korea --- greenhouse gas emission --- soil respiration --- coastal wetlands --- anthropogenic effect --- CO2 production and diffusion --- soil properties --- CO2 emission --- surface soil layer --- forest soils --- autotrophic respiration --- heterotrophic respiration --- CO2 effluxes --- decomposition --- forest disturbance --- tree mortality --- storm damage --- insect outbreak --- land use types --- soil organic carbon --- soil total nitrogen --- N addition --- soil respiration --- microbe --- subtropical forest --- soil organic carbon --- soil microbial residue --- forest conversion --- natural forest --- assisted natural regeneration --- plantation --- CO2 --- CH4 --- N2O --- soil --- biochar --- sensitivity --- temperature --- stoichiometric ratios --- landform --- rocky desertification --- karst graben basin --- warming --- nitrogen --- greenhouse gas --- soil characteristics --- microbial properties --- soil quality --- successive planting --- generation --- stand age --- clear-cutting --- Larix principis-rupprechtii Mayr --- biochar --- Camellia oleifera --- DCD --- nitrification inhibitor --- nitrous oxide --- calcareous soil --- plum plantation ages --- organic carbon mineralization --- fitting parameters --- organic carbon accumulation --- karst graben basin --- land use pattern --- bacterial community --- next-generation sequencing --- subtropical forest --- calcareous soils --- red soils --- soil CO2 --- carbon source–sink --- CH4 emissions --- CO2 emissions --- climate change mitigation --- global change --- land-use change --- N2O emissions --- soil carbon sequestration

Remote Sensing Technology Applications in Forestry and REDD+

Authors: --- --- ---
ISBN: 9783039284702 9783039284719 Year: Pages: 244 DOI: 10.3390/books978-3-03928-471-9 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- Environmental Technology
Added to DOAB on : 2020-04-07 23:07:09
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Advances in close-range and remote sensing technologies are driving innovations in forest resource assessments and monitoring on varying scales. Data acquired with airborne and spaceborne platforms provide high(er) spatial resolution, more frequent coverage, and more spectral information. Recent developments in ground-based sensors have advanced 3D measurements, low-cost permanent systems, and community-based monitoring of forests. The UNFCCC REDD+ mechanism has advanced the remote sensing community and the development of forest geospatial products that can be used by countries for the international reporting and national forest monitoring. However, an urgent need remains to better understand the options and limitations of remote and close-range sensing techniques in the field of forest degradation and forest change. Therefore, we invite scientists working on remote sensing technologies, close-range sensing, and field data to contribute to this Special Issue. Topics of interest include: (1) novel remote sensing applications that can meet the needs of forest resource information and REDD+ MRV, (2) case studies of applying remote sensing data for REDD+ MRV, (3) timeseries algorithms and methodologies for forest resource assessment on different spatial scales varying from the tree to the national level, and (4) novel close-range sensing applications that can support sustainable forestry and REDD+ MRV. We particularly welcome submissions on data fusion.

Keywords

sentinel imagery --- above-ground biomass --- predictive mapping --- machine learning --- geographically weighted regression --- canopy cover (CC) --- spectral --- texture --- digital hemispherical photograph (DHP) --- random forest (RF) --- gray level co-occurrence matrix (GLCM) --- forest inventory --- LiDAR --- tall trees --- overstory trees --- tree mapping --- crown delineation --- aboveground biomass --- Landsat --- random forest --- topography --- human activity --- aboveground biomass estimation --- remote sensing --- crown density --- low-accuracy estimation --- model comparison --- old-growth forest --- multispectral satellite imagery --- random forest --- forest classification --- remote sensing --- forestry --- phenology --- silviculture --- forest growing stock volume (GSV) --- full polarimetric SAR --- subtropical forest --- topographic effects --- environment effects --- geographic information system --- support vector machine --- random forest --- ensemble model --- hazard mapping --- 3D tree modelling --- aboveground biomass estimation --- destructive sampling --- Guyana --- LiDAR --- local tree allometry --- model evaluation --- quantitative structural model --- Pinus massoniana --- specific leaf area --- leaf area --- terrestrial laser scanning --- voxelization --- forest canopy --- REDD+ --- Cameroon --- reference level --- deforestation --- agriculture --- forest baseline --- airborne laser scanning --- terrestrial laser scanning --- remote sensing --- REDD+ --- forestry

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2020 (2)