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The ecology of peace: preparing Colombia for new political and planetary climates.
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- Frontiers in Ecology & the Environment, 2018, v. 16, n. 9, p. 525, doi. 10.1002/fee.1950
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- Article
Cryostratigraphy and Permafrost Evolution in the Lacustrine Lowlands of West-Central Alaska.
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- Permafrost & Periglacial Processes, 2014, v. 25, n. 1, p. 14, doi. 10.1002/ppp.1800
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- Article
Phenology shift from 1989 to 2008 on the Tibetan Plateau: an analysis with a process-based soil physical model and remote sensing data.
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- Climatic Change, 2013, v. 119, n. 2, p. 435, doi. 10.1007/s10584-013-0722-7
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- Article
Sensitivity of carbon budget to historical climate variability and atmospheric CO concentration in temperate grassland ecosystems in China.
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- Climatic Change, 2013, v. 117, n. 1/2, p. 259, doi. 10.1007/s10584-012-0533-2
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Modeling soil thermal and hydrological dynamics and changes of growing season in Alaskan terrestrial ecosystems.
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- Climatic Change, 2011, v. 107, n. 3/4, p. 481, doi. 10.1007/s10584-010-9988-1
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- Article
Spatial-temporal variations and driving factors of soil organic carbon in forest ecosystems of Northeast China.
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- Forest Ecosystems (KeAi Communications Co.), 2023, v. 10, p. 1, doi. 10.1016/j.fecs.2023.100101
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A fine spatial resolution modeling of urban carbon emissions: a case study of Shanghai, China.
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- Scientific Reports, 2022, v. 12, n. 1, p. 1, doi. 10.1038/s41598-022-13487-5
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Tundra landscape heterogeneity, not interannual variability, controls the decadal regional carbon balance in the Western Russian Arctic.
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- Global Change Biology, 2018, v. 24, n. 11, p. 5188, doi. 10.1111/gcb.14421
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- Article
The important but weakening maize yield benefit of grain filling prolongation in the US Midwest.
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- Global Change Biology, 2018, v. 24, n. 10, p. 4718, doi. 10.1111/gcb.14356
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The combined and separate impacts of climate extremes on the current and future US rainfed maize and soybean production under elevated CO<sub>2</sub>.
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- Global Change Biology, 2017, v. 23, n. 7, p. 2687, doi. 10.1111/gcb.13617
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Do maize models capture the impacts of heat and drought stresses on yield? Using algorithm ensembles to identify successful approaches.
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- Global Change Biology, 2016, v. 22, n. 9, p. 3112, doi. 10.1111/gcb.13376
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Global patterns and predictors of stem CO<sub>2</sub> efflux in forest ecosystems.
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- Global Change Biology, 2016, v. 22, n. 4, p. 1433, doi. 10.1111/gcb.13188
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Methane emissions from wetlands: biogeochemical, microbial, and modeling perspectives from local to global scales.
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- Global Change Biology, 2013, v. 19, n. 5, p. 1325, doi. 10.1111/gcb.12131
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- Article
Quantifying the Role of Snowmelt in Stream Discharge in an Alaskan Watershed: An Analysis Using a Spatially Distributed Surface Hydrology Model.
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- Journal of Geophysical Research. Earth Surface, 2017, v. 122, n. 11, p. 2183, doi. 10.1002/2017JF004214
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Contrasting soil thermal responses to fire in Alaskan tundra and boreal forest.
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- Journal of Geophysical Research. Earth Surface, 2015, v. 120, n. 2, p. 363, doi. 10.1002/2014JF003180
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- Article
Methane emissions from Arctic landscapes during 2000-2015: An analysis with land and lake biogeochemistry models.
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- Biogeosciences Discussions, 2022, p. 1, doi. 10.5194/bg-2022-220
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- Article
Global soil consumption of atmospheric carbon monoxide: an analysis using a process-based biogeochemistry model.
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- Atmospheric Chemistry & Physics, 2018, v. 18, n. 11, p. 7913, doi. 10.5194/acp-18-7913-2018
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Detectability of Arctic methane sources at six sites performing continuous atmospheric measurements.
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- Atmospheric Chemistry & Physics, 2017, v. 17, n. 13, p. 8371, doi. 10.5194/acp-17-8371-2017
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- Article
Inverse modeling of pan-Arctic methane emissions at high spatial resolution: what can we learn from assimilating satellite retrievals and using different process-based wetland and lake biogeochemical models?
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- Atmospheric Chemistry & Physics, 2016, v. 16, n. 19, p. 12649, doi. 10.5194/acp-16-12649-2016
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CO<sub>2</sub> and CH<sub>4</sub> exchanges between land ecosystems and the atmosphere in northern high latitudes over the 21st century.
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- Geophysical Research Letters, 2006, v. 33, n. 17, p. n/a, doi. 10.1029/2006GL026972
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Crop model- and satellite imagery-based recommendation tool for variable rate N fertilizer application for the US Corn system.
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- Precision Agriculture, 2017, v. 18, n. 5, p. 779, doi. 10.1007/s11119-016-9488-z
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Optimal Sample Size for SOC Content Prediction for Mapping Using the Random Forest in Cropland in Northern Jiangsu, China.
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- Eurasian Soil Science, 2022, v. 55, n. 12, p. 1689, doi. 10.1134/S1064229322600816
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Modeling methane emissions from the Alaskan Yukon River basin, 1986-2005, by coupling a large-scale hydrological model and a process-based methane model.
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- Journal of Geophysical Research. Biogeosciences, 2012, v. 117, n. G2, p. n/a, doi. 10.1029/2011JG001843
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Equifinality in parameterization of process-based biogeochemistry models: A significant uncertainty source to the estimation of regional carbon dynamics.
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- Journal of Geophysical Research. Biogeosciences, 2008, v. 113, n. G4, p. n/a, doi. 10.1029/2008JG000757
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Leaf <sup>13</sup>C data constrain the uncertainty of the carbon dynamics of temperate forest ecosystems.
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- Ecosphere, 2021, v. 12, n. 10, p. 1, doi. 10.1002/ecs2.3741
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Modeling leaf area index in North America using a process‐based terrestrial ecosystem model.
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- Ecosphere, 2018, v. 9, n. 1, p. 1, doi. 10.1002/ecs2.2046
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Quantifying spatially and temporally explicit CO<sub>2</sub> fertilization effects on global terrestrial ecosystem carbon dynamics.
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- Ecosphere, 2016, v. 7, n. 7, p. 1, doi. 10.1002/ecs2.1391
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- Article
Importance of biophysical effects on climate warming mitigation potential of biofuel crops over the conterminous United States.
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- GCB Bioenergy, 2017, v. 9, n. 3, p. 577, doi. 10.1111/gcbb.12370
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Bioenergy crop productivity and potential climate change mitigation from marginal lands in the United States: An ecosystem modeling perspective.
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- GCB Bioenergy, 2015, v. 7, n. 6, p. 1211, doi. 10.1111/gcbb.12212
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Carbon and nitrogen dynamics in bioenergy ecosystems: 2. Potential greenhouse gas emissions and global warming intensity in the conterminous United States.
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- GCB Bioenergy, 2015, v. 7, n. 1, p. 25, doi. 10.1111/gcbb.12106
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Carbon and nitrogen dynamics in bioenergy ecosystems: 1. Model development, validation and sensitivity analysis.
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- GCB Bioenergy, 2014, v. 6, n. 6, p. 740, doi. 10.1111/gcbb.12107
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Impacts of land use change due to biofuel crops on carbon balance, bioenergy production, and agricultural yield, in the conterminous United States.
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- GCB Bioenergy, 2012, v. 4, n. 3, p. 277, doi. 10.1111/j.1757-1707.2011.01129.x
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- Article
Consumption of atmospheric methane by the Qinghai-Tibet Plateau alpine steppe ecosystem.
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- Cryosphere, 2018, v. 12, n. 9, p. 2803, doi. 10.5194/tc-12-2803-2018
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Multimodel simulation of vertical gas transfer in a temperate lake.
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- Hydrology & Earth System Sciences Discussions, 2019, p. 1, doi. 10.5194/hess-2019-146
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Elevated atmospheric CO<sub>2</sub> negatively impacts photosynthesis through radiative forcing and physiology‐mediated climate feedback.
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- Geophysical Research Letters, 2017, v. 44, n. 4, p. 1956, doi. 10.1002/2016GL071733
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Rising methane emissions from northern wetlands associated with sea ice decline.
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- Geophysical Research Letters, 2015, v. 42, n. 17, p. 7214, doi. 10.1002/2015GL065013
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Aerosol effects on global land surface energy fluxes during 2003-2010.
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- Geophysical Research Letters, 2014, v. 41, n. 22, p. 7875, doi. 10.1002/2014GL061640
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Reduced net methane emissions due to microbial methane oxidation in a warmer Arctic.
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- Nature Climate Change, 2020, v. 10, n. 4, p. 317, doi. 10.1038/s41558-020-0734-z
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Soil organic carbon is a key determinant of CH<sub>4</sub> sink in global forest soils.
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- Nature Communications, 2023, v. 14, n. 1, p. 1, doi. 10.1038/s41467-023-38905-8
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Evaluating the Variability of Surface Soil Moisture Simulated Within CMIP5 Using SMAP Data.
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- Journal of Geophysical Research. Atmospheres, 2022, v. 127, n. 5, p. 1, doi. 10.1029/2021JD035363
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Validation and Sensitivity Analysis of a 1‐D Lake Model Across Global Lakes.
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- Journal of Geophysical Research. Atmospheres, 2021, v. 126, n. 4, p. 1, doi. 10.1029/2020JD033417
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Evapotranspiration in Northern Eurasia: Impact of forcing uncertainties on terrestrial ecosystem model estimates.
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- Journal of Geophysical Research. Atmospheres, 2015, v. 120, n. 7, p. 2647, doi. 10.1002/2014JD022531
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Modeling thermal dynamics of active layer soils and near-surface permafrost using a fully coupled water and heat transport model.
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- Journal of Geophysical Research. Atmospheres, 2012, v. 117, n. D11, p. n/a, doi. 10.1029/2012JD017512
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Mid-upper tropospheric methane in the high Northern Hemisphere: Spaceborne observations by AIRS, aircraft measurements, and model simulations.
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- Journal of Geophysical Research. Atmospheres, 2010, v. 115, n. D19, p. n/a, doi. 10.1029/2009JD013796
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Linking Biogeochemical and Hydrodynamic Processes to Model Methane Fluxes in Shallow, Tropical Floodplain Lakes.
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- Journal of Advances in Modeling Earth Systems, 2023, v. 15, n. 12, p. 1, doi. 10.1029/2022MS003385
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Quantifying Dissolved Organic Carbon Dynamics Using a Three‐Dimensional Terrestrial Ecosystem Model at High Spatial‐Temporal Resolutions.
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- Journal of Advances in Modeling Earth Systems, 2019, v. 11, n. 12, p. 4489, doi. 10.1029/2019MS001792
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Modeling CO<sub>2</sub> emissions from Arctic lakes: Model development and site-level study.
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- Journal of Advances in Modeling Earth Systems, 2017, v. 9, n. 5, p. 2190, doi. 10.1002/2017MS001028
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- Article
Modeling methane emissions from arctic lakes: Model development and site-level study.
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- Journal of Advances in Modeling Earth Systems, 2015, v. 7, n. 2, p. 459, doi. 10.1002/2014MS000344
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Parameterization and sensitivity analysis of a process-based terrestrial ecosystem model using adjoint method.
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- Journal of Advances in Modeling Earth Systems, 2014, v. 6, n. 2, p. 315, doi. 10.1002/2013MS000241
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- Article
Consumption of atmospheric methane by the Qinghai-Tibetan Plateau alpine steppe ecosystem.
- Published in:
- Cryosphere Discussions, 2017, p. 1, doi. 10.5194/tc-2017-264
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- Publication type:
- Article