North American carbon dioxide sources and sinks: magnitude, attribution, and uncertainty

North America is both a source and sink of atmospheric carbon dioxide (CO2). Continental sources - such as fossil-fuel combustion in the US and deforestation in Mexico - and sinks - including most ecosystems, and particularly secondary forests - add and remove CO2 from the atmosphere, respectively. Photosynthesis converts CO2 into carbon as biomass, which is stored in vegetation, soils, and wood products. However, ecosystem sinks compensate for only similar to 35% of the continent's fossil-fuel-based CO2 emissions; North America therefore represents a net CO2 source. Estimating the magnitude of ecosystem sinks, even though the calculation is confounded by uncertainty as a result of individual inventory- and model-based alternatives, has improved through the use of a combined approach. Front Ecol Environ 2012; 10(10): 512-519, doi:10.1890/12006

An estimate of carbon emissions from 2004 wildfires across Alaskan Yukon River Basin

© 2007 Tan et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

Estimates of CO2 from fires in the United States: implications for carbon management

<p>Abstract</p> <p>Background</p> <p>Fires emit significant amounts of CO₂to the atmosphere. These emissions, however, are highly variable in both space and time. Additionally, CO₂emissions estimates from fires are very uncertain. The combination of high spatial and temporal variability and substantial uncertainty associated with fire CO₂emissions can be problematic to efforts to develop remote sensing, monitoring, and inverse modeling techniques to quantify carbon fluxes at the continental scale. Policy and carbon management decisions based on atmospheric sampling/modeling techniques must account for the impact of fire CO₂emissions; a task that may prove very difficult for the foreseeable future. This paper addresses the variability of CO₂emissions from fires across the US, how these emissions compare to anthropogenic emissions of CO₂and Net Primary Productivity, and the potential implications for monitoring programs and policy development.</p> <p>Results</p> <p>Average annual CO₂emissions from fires in the lower 48 (LOWER48) states from 2002–2006 are estimated to be 213 (± 50 std. dev.) Tg CO₂yr^-1and 80 (± 89 std. dev.) Tg CO₂yr^-1in Alaska. These estimates have significant interannual and spatial variability. Needleleaf forests in the Southeastern US and the Western US are the dominant source regions for US fire CO₂emissions. Very high emission years typically coincide with droughts, and climatic variability is a major driver of the high interannual and spatial variation in fire emissions. The amount of CO₂emitted from fires in the US is equivalent to 4–6% of anthropogenic emissions at the continental scale and, at the state-level, fire emissions of CO₂can, in some cases, exceed annual emissions of CO₂from fossil fuel usage.</p> <p>Conclusion</p> <p>The CO₂released from fires, overall, is a small fraction of the estimated average annual Net Primary Productivity and, unlike fossil fuel CO₂emissions, the pulsed emissions of CO₂during fires are partially counterbalanced by uptake of CO₂by regrowing vegetation in the decades following fire. Changes in fire severity and frequency can, however, lead to net changes in atmospheric CO₂and the short-term impacts of fire emissions on monitoring, modeling, and carbon management policy are substantial.</p

Response of Soil Respiration to Soil Temperature and Moisture in a 50-Year-Old Oriental Arborvitae Plantation in China

China possesses large areas of plantation forests which take up great quantities of carbon. However, studies on soil respiration in these plantation forests are rather scarce and their soil carbon flux remains an uncertainty. In this study, we used an automatic chamber system to measure soil surface flux of a 50-year-old mature plantation of Platycladus orientalis at Jiufeng Mountain, Beijing, China. Mean daily soil respiration rates (Rs) ranged from 0.09 to 4.87 µmol CO2 m−2s−1, with the highest values observed in August and the lowest in the winter months. A logistic model gave the best fit to the relationship between hourly Rs and soil temperature (Ts), explaining 82% of the variation in Rs over the annual cycle. The annual total of soil respiration estimated from the logistic model was 645±5 g C m−2 year−1. The performance of the logistic model was poorest during periods of high soil temperature or low soil volumetric water content (VWC), which limits the model's ability to predict the seasonal dynamics of Rs. The logistic model will potentially overestimate Rs at high Ts and low VWC. Seasonally, Rs increased significantly and linearly with increasing VWC in May and July, in which VWC was low. In the months from August to November, inclusive, in which VWC was not limiting, Rs showed a positively exponential relationship with Ts. The seasonal sensitivity of soil respiration to Ts (Q10) ranged from 0.76 in May to 4.38 in October. It was suggested that soil temperature was the main determinant of soil respiration when soil water was not limiting

Is the water footprint an appropriate tool for forestry and forest products: The Fennoscandian case

The water footprint by the Water Footprint Network (WF) is an ambitious tool for measuring human appropriation and promoting sustainable use of fresh water. Using recent case studies and examples from water-abundant Fennoscandia, we consider whether it is an appropriate tool for evaluating the water use of forestry and forest-based products. We show that aggregating catchment level water consumption over a product life cycle does not consider fresh water as a renewable resource and is inconsistent with the principles of the hydrologic cycle. Currently, the WF assumes that all evapotranspiration (ET) from forests is a human appropriation of water although ET from managed forests in Fennoscandia is indistinguishable from that of unmanaged forests. We suggest that ET should not be included in the water footprint of rain-fed forestry and forest-based products. Tools for sustainable water management should always contextualize water use and water impacts with local water availability and environmental sensitivity

Author Correction: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

The following authors were omitted from the original version of this Data Descriptor: Markus Reichstein and Nicolas Vuichard. Both contributed to the code development and N. Vuichard contributed to the processing of the ERA-Interim data downscaling. Furthermore, the contribution of the co-author Frank Tiedemann was re-evaluated relative to the colleague Corinna Rebmann, both working at the same sites, and based on this re-evaluation a substitution in the co-author list is implemented (with Rebmann replacing Tiedemann). Finally, two affiliations were listed incorrectly and are corrected here (entries 190 and 193). The author list and affiliations have been amended to address these omissions in both the HTML and PDF versions

The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data.

The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible