scholarly journals Carbon Stocks and Fluxes in Kenyan Forests and Wooded Grasslands Derived from Earth Observation and Model-Data Fusion

2020 ◽  
Vol 12 (15) ◽  
pp. 2380
Author(s):  
Pedro Rodríguez-Veiga ◽  
Joao Carreiras ◽  
Thomas Luke Smallman ◽  
Jean-François Exbrayat ◽  
Jamleck Ndambiri ◽  
...  
Keyword(s):  
Data Fusion ◽  
Forest Inventory ◽  
National Level ◽  
Woody Biomass ◽  
Carbon Stocks ◽  
Earth Observation ◽  
Climate Mitigation ◽  
Biomass Carbon ◽  
Model Data ◽  
Essential Information

The characterization of carbon stocks and dynamics at the national level is critical for countries engaging in climate change mitigation and adaptation strategies. However, several tropical countries, including Kenya, lack the essential information typically provided by a complete national forest inventory. Here we present the most detailed and rigorous national-scale assessment of aboveground woody biomass carbon stocks and dynamics for Kenya to date. A non-parametric random forest algorithm was trained to retrieve aboveground woody biomass carbon (AGBC) for the year 2014 ± 1 and forest disturbances for the 2014–2017 period using in situ forest inventory plot data and satellite Earth Observation (EO) data. The ecosystem carbon cycling of Kenya’s forests and wooded grassland were assessed using a model-data fusion framework, CARDAMOM, constrained by the woody biomass datasets from this study as well as time series information on leaf area, fire events and soil organic carbon. Our EO-derived AGBC stocks were estimated as 140 Mt C for forests and 199 Mt C for wooded grasslands. The total AGBC loss during the study period was estimated as 1.89 Mt C with a dispersion below 1%. The CARDAMOM analysis estimated woody productivity to be three times larger in forests (mean = 1.9 t C ha−1 yr−1) than wooded grasslands (0.6 t C ha−1 yr−1), and the mean residence time of woody C in forests (16 years) to be greater than in wooded grasslands (10 years). This study stresses the importance of carbon sequestration by forests in the international climate mitigation efforts under the Paris Agreement, but emphasizes the need to include non-forest ecosystems such as wooded grasslands in international greenhouse gas accounting frameworks.

scholarly journals Brazilian Mangroves: Blue Carbon Hotspots of National and Global Relevance to Natural Climate Solutions

2022 ◽  
Vol 4 ◽  
Author(s):  
Andre S. Rovai ◽  
Robert R. Twilley ◽  
Thomas A. Worthington ◽  
Pablo Riul
Keyword(s):  
Carbon Sequestration ◽  
National Level ◽  
Cost Effective ◽  
Woody Biomass ◽  
Carbon Stocks ◽  
Blue Carbon ◽  
Carbon Accumulation ◽  
Amazon Forest ◽  
Nationally Determined Contributions ◽  
Natural Climate

Mangroves are known for large carbon stocks and high sequestration rates in biomass and soils, making these intertidal wetlands a cost-effective strategy for some nations to compensate for a portion of their carbon dioxide (CO2) emissions. However, few countries have the national-level inventories required to support the inclusion of mangroves into national carbon credit markets. This is the case for Brazil, home of the second largest mangrove area in the world but lacking an integrated mangrove carbon inventory that captures the diversity of coastline types and climatic zones in which mangroves are present. Here we reviewed published datasets to derive the first integrated assessment of carbon stocks, carbon sequestration rates and potential CO2eq emissions across Brazilian mangroves. We found that Brazilian mangroves hold 8.5% of the global mangrove carbon stocks (biomass and soils combined). When compared to other Brazilian vegetated biomes, mangroves store up to 4.3 times more carbon in the top meter of soil and are second in biomass carbon stocks only to the Amazon forest. Moreover, organic carbon sequestration rates in Brazilian mangroves soils are 15–30% higher than recent global estimates; and integrated over the country’s area, they account for 13.5% of the carbon buried in world’s mangroves annually. Carbon sequestration in Brazilian mangroves woody biomass is 10% of carbon accumulation in mangrove woody biomass globally. Our study identifies Brazilian mangroves as a major global blue carbon hotspot and suggest that their loss could potentially release substantial amounts of CO2. This research provides a robust baseline for the consideration of mangroves into strategies to meet Brazil’s intended Nationally Determined Contributions.

scholarly journals Increases in soil and woody biomass carbon stocks as a result of rangeland riparian restoration

2020 ◽  
Vol 15 (1) ◽  
Author(s):  
Virginia Matzek ◽  
David Lewis ◽  
Anthony O’Geen ◽  
Michael Lennox ◽  
Sean D. Hogan ◽  
...  
Keyword(s):  
Woody Biomass ◽  
Carbon Stocks ◽  
Biomass Carbon ◽  
Riparian Restoration

scholarly journals The landscape of soil carbon data: Emerging questions, synergies and databases

2019 ◽  
Vol 43 (5) ◽  
pp. 707-719 ◽  
Author(s):  
Avni Malhotra ◽  
Katherine Todd-Brown ◽  
Lucas E Nave ◽  
Niels H Batjes ◽  
James R Holmquist ◽  
...  
Keyword(s):  
Soil Carbon ◽  
Agricultural Practices ◽  
Carbon Stocks ◽  
Progress Report ◽  
Climate Mitigation ◽  
Biogeochemical Processes ◽  
Model Data ◽  
Natural Ecosystems ◽  
Carbon Network

Soil carbon has been measured for over a century in applications ranging from understanding biogeochemical processes in natural ecosystems to quantifying the productivity and health of managed systems. Consolidating diverse soil carbon datasets is increasingly important to maximize their value, particularly with growing anthropogenic and climate change pressures. In this progress report, we describe recent advances in soil carbon data led by the International Soil Carbon Network and other networks. We highlight priority areas of research requiring soil carbon data, including (a) quantifying boreal, arctic and wetland carbon stocks, (b) understanding the timescales of soil carbon persistence using radiocarbon and chronosequence studies, (c) synthesizing long-term and experimental data to inform carbon stock vulnerability to global change, (d) quantifying root influences on soil carbon and (e) identifying gaps in model–data integration. We also describe the landscape of soil datasets currently available, highlighting their strengths, weaknesses and synergies. Now more than ever, integrated soil data are needed to inform climate mitigation, land management and agricultural practices. This report will aid new data users in navigating various soil databases and encourage scientists to make their measurements publicly available and to join forces to find soil-related solutions.

Analysis of Land Use Land Cover in Annapurna Conservation Area in Gandaki Province, Nepal using Vegetation Index and Land Use Land Cover Datasets

2019 ◽  
Vol 2 (2) ◽  
pp. 87-99
Author(s):  
Shiva Pokhrel ◽  
Chungla Sherpa
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Vegetation Index ◽  
National Level ◽  
Climate Mitigation ◽  
Land Use Land Cover ◽  
Conservation Area ◽  
Barren Land ◽  
Wide Range ◽  
Annapurna Conservation Area

Conservation areas are originally well-known for protecting landscape features and wildlife. They are playing key role in conserving and providing a wide range of ecosystem services, social, economic and cultural benefits as well as vital places for climate mitigation and adaptation. We have analyzed decadal changes in land cover and status of vegetation cover in the conservation area using both national level available data on land use land cover (LULC) changes (1990-2010) and normalized difference vegetation index (NDVI) (2010-2018) in Annapurna conservation area. LULC showed the barren land as the most dominant land cover types in all three different time series 1990, 2000 and 2010 with followed by snow cover, grassland, forest, agriculture and water body. The highest NDVI values were observed at Southern, Southwestern and Southeastern part of conservation area consisting of forest area, shrub land and grassland while toward low to negative in the upper middle to the Northern part of the conservation area.

scholarly journals Biomass and Soil Carbon Stocks in Wet Montane Forest, Monteverde Region, Costa Rica: Assessments and Challenges for Quantifying Accumulation Rates

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Lawrence H. Tanner ◽  
Megan T. Wilckens ◽  
Morgan A. Nivison ◽  
Katherine M. Johnson
Keyword(s):  
Costa Rica ◽  
Soil Carbon ◽  
Secondary Forest ◽  
Cloud Forest ◽  
Montane Forest ◽  
Carbon Stocks ◽  
Age Difference ◽  
Biomass Carbon ◽  
Mature Forest ◽  
Large Trees

We measured carbon stocks at two forest reserves in the cloud forest region of Monteverde, comparing cleared land, experimental secondary forest plots, and mature forest at each location to assess the effectiveness of reforestation in sequestering biomass and soil carbon. The biomass carbon stock measured in the mature forest at the Monteverde Institute is similar to other measurements of mature tropical montane forest biomass carbon in Costa Rica. Local historical records and the distribution of large trees suggest a mature forest age of greater than 80 years. The forest at La Calandria lacks historical documentation, and dendrochronological dating is not applicable. However, based on the differences in tree size, above-ground biomass carbon, and soil carbon between the Monteverde Institute and La Calandria sites, we estimate an age difference of at least 30 years of the mature forests. Experimental secondary forest plots at both sites have accumulated biomass at lower than expected rates, suggesting local limiting factors, such as nutrient limitation. We find that soil carbon content is primarily a function of time and that altitudinal differences between the study sites do not play a role.

scholarly journals Constraining a complex biogeochemical model for CO<sub>2</sub> and N<sub>2</sub>O emission simulations from various land uses by model–data fusion

2017 ◽  
Vol 14 (14) ◽  
pp. 3487-3508 ◽  
Author(s):  
Tobias Houska ◽  
David Kraus ◽  
Ralf Kiese ◽  
Lutz Breuer
Keyword(s):  
Data Fusion ◽  
Arable Land ◽  
Shallow Groundwater ◽  
Scale Model ◽  
Biogeochemical Model ◽  
N2o Emissions ◽  
Model Errors ◽  
Model Data ◽  
Validation Data ◽  
Fusion Concept

Abstract. This study presents the results of a combined measurement and modelling strategy to analyse N2O and CO2 emissions from adjacent arable land, forest and grassland sites in Hesse, Germany. The measured emissions reveal seasonal patterns and management effects, including fertilizer application, tillage, harvest and grazing. The measured annual N2O fluxes are 4.5, 0.4 and 0.1 kg N ha−1 a−1, and the CO2 fluxes are 20.0, 12.2 and 3.0 t C ha−1 a−1 for the arable land, grassland and forest sites, respectively. An innovative model–data fusion concept based on a multicriteria evaluation (soil moisture at different depths, yield, CO2 and N2O emissions) is used to rigorously test the LandscapeDNDC biogeochemical model. The model is run in a Latin-hypercube-based uncertainty analysis framework to constrain model parameter uncertainty and derive behavioural model runs. The results indicate that the model is generally capable of predicting trace gas emissions, as evaluated with RMSE as the objective function. The model shows a reasonable performance in simulating the ecosystem C and N balances. The model–data fusion concept helps to detect remaining model errors, such as missing (e.g. freeze–thaw cycling) or incomplete model processes (e.g. respiration rates after harvest). This concept further elucidates the identification of missing model input sources (e.g. the uptake of N through shallow groundwater on grassland during the vegetation period) and uncertainty in the measured validation data (e.g. forest N2O emissions in winter months). Guidance is provided to improve the model structure and field measurements to further advance landscape-scale model predictions.

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