Christopher S. Potter

TL;DR: In this paper, the authors present a modeling approach aimed at seasonal resolution of global climatic and edaphic controls on patterns of terrestrial ecosystem production and soil microbial respiration using satellite imagery (Advanced Very High Resolution Radiometer and International Satellite Cloud Climatology Project solar radiation), along with historical climate (monthly temperature and precipitation) and soil attributes (texture, C and N contents) from global (1°) data sets as model inputs.

TL;DR: In this article, the authors used semi-mechanistic, empirically based statistical models to predict the spatial and temporal patterns of global carbon dioxide emissions from terrestrial soils and found that CO 2 emissions from soils follow a seasonal pattern with maximum emissions coinciding with periods of active plant growth.

TL;DR: In this paper, the spatial and temporal patterns of global carbon emissions form terrestrial soils were predicted using semi-chanistic, empirically based statistical models, and it was found that, at the global scale, the rates of soil CO{sub 2} efflux correlate significantly with temperature and precipitation, have a pronounced seasonal pattern in most locations, and contribute to observed wintertime increases in atmospheric CO[sub 2}.

TL;DR: The authors used a climate-driven regression model to develop spatially resolved estimates of soil-CO2 emissions from the terrestrial land surface for each month from January 1980 to December 1994, to evaluate the effects of interannual variations in climate on global soil-to-atmosphere CO2 fluxes.

TL;DR: In this paper, an ecosystem modeling approach that integrates global satellite, climate, vegetation, and soil data sets to examine conceptual controls on nitrogen trace gas (NO, N2O, and N2) emissions from soils and identify weaknesses in our bases of knowledge and data for these fluxes is presented.