scholarly journals Investigation and analysis of operational conditions for pilot project villages of Forest Carbon Cycle Community

2012 ◽  
Vol 16 (3) ◽  
pp. 41-52
Author(s):  
서정원
Keyword(s):  
Carbon Cycle ◽  
Pilot Project ◽  
Forest Carbon ◽  
Operational Conditions

scholarly journals Approaches for inclusion of forest carbon cycle in life cycle assessment - a review

GCB Bioenergy ◽  
2012 ◽  
Vol 5 (5) ◽  
pp. 475-486 ◽  
Author(s):  
Tuomas Helin ◽  
Laura Sokka ◽  
Sampo Soimakallio ◽  
Kim Pingoud ◽  
Tiina Pajula
Keyword(s):  
Life Cycle Assessment ◽  
Life Cycle ◽  
Carbon Cycle ◽  
Forest Carbon

Aligning ecology and markets in the forest carbon cycle

2013 ◽  
Vol 11 (1) ◽  
pp. 37-42 ◽  
Author(s):  
Matthew D Hurteau ◽  
Bruce A Hungate ◽  
George W Koch ◽  
Malcolm P North ◽  
Gordon R Smith
Keyword(s):  
Carbon Cycle ◽  
Forest Carbon

scholarly journals Modeling forest carbon cycle response to tree mortality: Effects of plant functional type and disturbance intensity

2015 ◽  
Vol 120 (11) ◽  
pp. 2178-2193 ◽  
Author(s):  
Renato Prata de Moraes Frasson ◽  
Gil Bohrer ◽  
David Medvigy ◽  
Ashley M. Matheny ◽  
Timothy H. Morin ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Tree Mortality ◽  
Forest Carbon ◽  
Plant Functional Type ◽  
Functional Type ◽  
Disturbance Intensity

scholarly journals Constraining modelled global vegetation dynamics and carbon turnover using multiple satellite observations

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Matthias Forkel ◽  
Markus Drüke ◽  
Martin Thurner ◽  
Wouter Dorigo ◽  
Sibyll Schaphoff ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Vegetation Dynamics ◽  
Climate Impacts ◽  
Forest Carbon ◽  
Satellite Observations ◽  
Future Climate Change ◽  
Carbon Turnover ◽  
Bioclimatic Variables ◽  
Optimized Model ◽  
Global Vegetation

AbstractThe response of land ecosystems to future climate change is among the largest unknowns in the global climate-carbon cycle feedback. This uncertainty originates from how dynamic global vegetation models (DGVMs) simulate climate impacts on changes in vegetation distribution, productivity, biomass allocation, and carbon turnover. The present-day availability of a multitude of satellite observations can potentially help to constrain DGVM simulations within model-data integration frameworks. Here, we use satellite-derived datasets of the fraction of absorbed photosynthetic active radiation (FAPAR), sun-induced fluorescence (SIF), above-ground biomass of trees (AGB), land cover, and burned area to constrain parameters for phenology, productivity, and vegetation dynamics in the LPJmL4 DGVM. Both the prior and the optimized model accurately reproduce present-day estimates of the land carbon cycle and of temporal dynamics in FAPAR, SIF and gross primary production. However, the optimized model reproduces better the observed spatial patterns of biomass, tree cover, and regional forest carbon turnover. Using a machine learning approach, we found that remaining errors in simulated forest carbon turnover can be explained with bioclimatic variables. This demonstrates the need to improve model formulations for climate effects on vegetation turnover and mortality despite the apparent successful constraint of simulated vegetation dynamics with multiple satellite observations.

scholarly journals Multi‐element regulation of the tropical forest carbon cycle

2011 ◽  
Vol 9 (1) ◽  
pp. 9-17 ◽  
Author(s):  
Alan R Townsend ◽  
Cory C Cleveland ◽  
Benjamin Z Houlton ◽  
Caroline B Alden ◽  
James WC White
Keyword(s):  
Carbon Cycle ◽  
Tropical Forest ◽  
Forest Carbon

Quantifying forest growth and uncertainty across Brazil under potential future climates: combing models and Earth Observation

2020 ◽  
Author(s):  
Thomas Smallman ◽  
David Milodowski ◽  
Mathew Williams
Keyword(s):  
Climate Change ◽  
Carbon Cycle ◽  
Carbon Cycling ◽  
Earth Observation ◽  
Forest Growth ◽  
Forest Carbon ◽  
Carbon Accumulation ◽  
Terrestrial Ecosystem Model ◽  
New Forest ◽  
The Impact

<p>Forest play a major role in the global carbon cycle storing large amounts of carbon in both living and dead organic matter. Forests can be either a sink or source of carbon depending on the net of far larger fluxes of carbon into (photosynthesis) and out of (mortality, decomposition and disturbance) forest ecosystems. Due to the potential for substantial accumulation of carbon in forests, has led to nationally determined commitments (NDCs) by Governments across the world to protect existing and plant large areas of new forest. However, significant uncertainty remains in our understanding of current forest carbon cycling, especially mortality and decomposition processes, and how carbon cycling will change under climate change. These uncertainties present two connected challenges to effective forest protection and new planting; (i) which existing forests are under the greatest risk to climate change and (ii) where are the most climate safe locations for new forest planting to maximise carbon accumulation.</p><p>Here we combine a terrestrial ecosystem model of intermediate complexity (DALEC) with Earth observation (e.g. leaf area, biomass, disturbance) and databased information (soil texture and carbon stocks) within a Bayesian model-data fusion framework (CARDAMOM) to retrieve location specific carbon cycle analyse (i.e. parameter retrievals) across Brazil at 0.5 x 0.5 degree spatial resolution between 2001 and 2015. CARDAMOM allows us to retrieve, independently for each location analysed, an ensemble of parameters for DALEC which are consistent with the location specific observational constraints and their uncertainties. These ensembles give us multiple potential, but observation consistent, realisations of forest carbon cycling and ecosystem traits. We directly quantify our uncertainty in forest carbon cycling and ecosystem traits from these ensembles. The DALEC parameterisations are then simulated into the future under a range of climate scenarios from the CMIP6 model dataset. From these simulations we will, with defined uncertainty, quantify the impact on forest carbon accumulation of existing forest and the potential accumulation of new planting. This information can feed into national planning identifying locations which have the greatest confidence of being a net sink of carbon under climate change highlighting forest areas which are most important to protect and suitable for new planting.</p>

scholarly journals Modeling forest carbon cycle using long-term carbon stock field measurement in the Delaware River Basin

Ecosphere ◽  
2017 ◽  
Vol 8 (5) ◽  
pp. e01802 ◽  
Author(s):  
Bing Xu ◽  
Yude Pan ◽  
Alain F. Plante ◽  
Kevin McCullough ◽  
Richard Birdsey
Keyword(s):  
Carbon Cycle ◽  
River Basin ◽  
Field Measurement ◽  
Carbon Stock ◽  
Forest Carbon ◽  
Delaware River

scholarly journals Carbon Dynamics in a Human-Modified Tropical Forest: A Case Study Using Multi-Temporal LiDAR Data

2020 ◽  
Vol 12 (3) ◽  
pp. 430 ◽  
Author(s):  
Yhasmin Mendes de Moura ◽  
Heiko Balzter ◽  
Lênio S. Galvão ◽  
Ricardo Dalagnol ◽  
Fernando Espírito-Santo ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Tropical Forests ◽  
Carbon Dynamics ◽  
Carbon Stocks ◽  
Forest Carbon ◽  
Selective Logging ◽  
Carbon Accounting ◽  
Lidar Data ◽  
Multi Temporal ◽  
The Tropics

Tropical forests hold significant amounts of carbon and play a critical role on Earth´s climate system. To date, carbon dynamics over tropical forests have been poorly assessed, especially over vast areas of the tropics that have been affected by some type of disturbance (e.g., selective logging, understory fires, and fragmentation). Understanding the multi-temporal dynamics of carbon stocks over human-modified tropical forests (HMTF) is crucial to close the carbon cycle balance in the tropics. Here, we used multi-temporal and high-spatial resolution airborne LiDAR data to quantify rates of carbon dynamics over a large patch of HMTF in eastern Amazon, Brazil. We described a robust approach to monitor changes in aboveground forest carbon stocks between 2012 and 2018. Our results showed that this particular HMTF lost 0.57 m·yr−1 in mean forest canopy height and 1.38 Mg·C·ha−1·yr−1 of forest carbon between 2012 and 2018. LiDAR-based estimates of Aboveground Carbon Density (ACD) showed progressive loss through the years, from 77.9 Mg·C·ha−1 in 2012 to 53.1 Mg·C·ha−1 in 2018, thus a decrease of 31.8%. Rates of carbon stock changes were negative for all time intervals analyzed, yielding average annual carbon loss rates of −1.34 Mg·C·ha−1·yr−1. This suggests that this HMTF is acting more as a source of carbon than a sink, having great negative implications for carbon emission scenarios in tropical forests. Although more studies of forest dynamics in HMTFs are necessary to reduce the current remaining uncertainties in the carbon cycle, our results highlight the persistent effects of carbon losses for the study area. HMTFs are likely to expand across the Amazon in the near future. The resultant carbon source conditions, directly associated with disturbances, may be essential when considering climate projections and carbon accounting methods.

Sign in / Sign up

Export Citation Format

Share Document