Bibliography - E. Shevliakova

1. Gerber, S., L.O. Hedin, Michael Oppenheimer, Stephen W. Pacala, and E. Shevliakova, 2009: Nitrogen Cycling and Feedbacks in a Global Dynamic Land Model. Global Biogeochemical Cycles, http://www.agu.org/journals/pip/gb/2008GB003336-pip.pdf, doi:10.1029/2008GB003336
   [ Abstract ]

   Global anthropogenic changes in carbon (C) and nitrogen (N) cycles call for modeling tools that are able to address and quantify essential interactions between N, C, and climate in terrestrial ecosystems. Here, we introduce a prognostic N cycle within the Princeton-GFDL LM3V land model. The model captures mechanisms essential for N cycling and their feedbacks on C cycling: N limitation of plant productivity, the N dependence of C decomposition and stabilization in soils, removal of available N by competing sinks, ecosystem losses that include dissolved organic and volatile N, and ecosystem inputs through biological N fixation.
   Our model captures many essential characteristics of C-N interactions, and is capable of broadly recreating spatial and temporal variations in N and C dynamics. The introduced N dynamics improves the model’s short term NPP response to step changes in CO₂. Consistent with theories of successional dynamics, we find that physical disturbance induces strong C-N feedbacks, caused by intermittent N loss and subsequent N limitation. In contrast, C-N interactions are weak when the coupled model system approaches equilibrium. Thus, at steady state many simulated features of the carbon cycle, such as primary productivity and carbon inventories are similar to simulations that do not include C-N feedbacks.

2. Shevliakova, E., Stephen W. Pacala, S. Malyshev, G. C. Hurtt, P.C.D. Milly, J. P. Caspersen, L. T. Sentman, J. P. Fisk, C. Wirth, and C. Crevoisier, 2009: Carbon Cycling Under 300 Years of Land-Use Change: The Importance of the Secondary Vegetation Sink. Global Biogeochemical Cycles, doi:10.1029/2007GB003176
   [ Abstract ]

   We have developed a dynamic land model (LM3V) able to simulate ecosystem dynamics and exchanges of water, energy, and CO₂ between land and atmosphere. LM3V is specifically designed to address the consequences of land use and land management changes including cropland and pasture dynamics, shifting cultivation, logging, fire, and resulting patterns of secondary regrowth. Here we analyze the behavior of LM3V, forced with the output from the Geophysical Fluid Dynamics Laboratory (GFDL) atmospheric model AM2, observed precipitation data, and four historic scenarios of land use change for 1700–2000. Our analysis suggests a net terrestrial carbon source due to land use activities from 1.1 to 1.3 GtC/a during the 1990s, where the range is due to the difference in the historic cropland distribution. This magnitude is substantially smaller than previous estimates from other models, largely due to our estimates of a secondary vegetation sink of 0.35 to 0.6 GtC/a in the 1990s and decelerating agricultural land clearing since the 1960s. For the 1990s, our estimates for the pastures’ carbon flux vary from a source of 0.37 to a sink of 0.15 GtC/a, and for the croplands our model shows a carbon source of 0.6 to 0.9 GtC/a. Our process-based model suggests a smaller net deforestation source than earlier bookkeeping models because it accounts for decelerated net conversion of primary forest to agriculture and for stronger secondary vegetation regrowth in tropical regions. The overall uncertainty is likely to be higher than the range reported here because of uncertainty in the biomass recovery under changing ambient conditions, including atmospheric CO₂ concentration, nutrients availability, and climate.

3. Crevoisier, C., E. Shevliakova, M. N. Gloor, C. Wirth, and Stephen W. Pacala, 2007: Drivers of fires in the boreal forests: data constrained design of a prognostic model for burned area for use in dynamic global vegetation models. Journal of Geophysical Research, 112(D24112), doi:10.1029/2006JD008372
   [ Abstract ]

   Boreal regions are an important component of the global carbon cycle because they host large stocks of aboveground and belowground carbon. Since boreal forest evolution is closely related to fire regimes, shifts in climate are likely to induce changes in ecosystems, potentially leading to a large release of carbon and other trace gases to the atmosphere. Prediction of the effect of this potential climate feedback on the Earth system is therefore important and requires the modeling of fire as a climate driven process in dynamic global vegetation models (DGVMs). Here, we develop a new data-based prognostic model, for use in DGVMs, to estimate monthly burned area from four climate (precipitation, temperature, soil water content and relative humidity) and one humanrelated (road density) predictors for boreal forest. The burned area model is a function of current climatic conditions and is thus responsive to climate change. Model parameters are estimated using a Markov Chain Monte Carlo method applied to on ground observations from the Canadian Large Fire Database. The model is validated against independent observations from three boreal regions: Canada, Alaska and Siberia. Provided realistic climate predictors, the model is able to reproduce the seasonality, intensity and interannual variability of burned area, as well as the location of fire events. In particular, the model simulates well the timing of burning events, with two thirds of the events predicted for the correct month and almost all the rest being predicted 1 month before or after the observed event. The predicted annual burned area is in the range of various current estimates. The estimated annual relative error (standard deviation) is twelve percent in a grid cell, which makes the model suitable to study quantitatively the evolution of burned area with climate.

4. Hurtt, G. C., S. Frolking, M. G. Fearon, B. Moore III, E. Shevliakova, S. Malyshev, Stephen W. Pacala, and R. A. Houghton, 2006: The underpinnings of land-use history: three centuries of global gridded landuse transitions, wood-harvest activity, and resulting secondary lands. Global Change Biology, 12(7), doi:10.1111/j.1365-2486.2006.01150.x 1208-1299
   [ Abstract ]

   To accurately assess the impacts of human land use on the Earth system, information is needed on the current and historical patterns of land-use activities. Previous global studies have focused on developing reconstructions of the spatial patterns of agriculture. Here, we provide the first global gridded estimates of the underlying land conversions (land-use transitions), wood harvesting, and resulting secondary lands annually, for the period 1700–2000. Using data-based historical cases, our results suggest that 42–68% of the land surface was impacted by land-use activities (crop, pasture, wood harvest) during this period, some multiple times. Secondary land area increased 10–44 X 10⁶km²; about half of this was forested. Wood harvest and shifting cultivation generated 70–90% of the secondary land by 2000; permanent abandonment and relocation of agricultural land accounted for the rest. This study provides important new estimates of globally gridded land-use activities for studies attempting to assess the consequences of anthropogenic changes to the Earth’s surface over time.

5. Pacala, Stephen W., G. C. Hurtt, D. Baker, P. Peylin, R. A. Houghton, R. A. Birdsey, L. Heath, E. T. Sundquist, R. F. Stallard, P. Ciais, P. R. Moorcroft, J. P. Caspersen, and E. Shevliakova, et al., 2001: Consistent Land- and Atmosphere-Based U.S. Carbon Sink Estimates. Science, 292, doi:10.1126/science.1057320 2316-2320
   [ Abstract ]

   For the period 1980-89, we estimate a carbon sink in the coterminous United States between 0.30 and 0.58 petagrams of carbon per year (petagrams of carbon = 10¹⁵ grams of carbon). The net carbon ßux from the atmosphere to the land was higher, 0.37 to 0.71 petagrams of carbon per year, because a net ßux of 0.07 to 0.13 petagrams of carbon per year was exported by rivers and commerce and returned to the atmosphere elsewhere. These land-based estimates are larger than those from previous studies (0.08 to 0.35 petagrams of carbon per year) because of the inclusion of additional processes and revised estimates of some component fluxes. Although component estimates are uncertain, about one-half of the total is outside the forest sector. We also estimated the sink using atmospheric models and the atmospheric concentration of carbon dioxide (the tracer-transport inversion method). The range of results from the atmosphere-based inversions contains the land-based estimates. Atmosphere- and land-based estimates are thus consistent, within the large ranges of uncertainty for both methods. Atmosphere-based results for 1980-89 are similar to those for 1985-89 and 1990-94, indicating a relatively stable U.S. sink throughout the period.

6. Hurtt, G. C., Stephen W. Pacala, P. R. Moorcroft, J. P. Caspersen, E. Shevliakova, R. A. Houghton, and B. Moore III, 0000: Projecting the Future of the U.S. Carbon Sink. Proceedings of the National Academy of Sciences of the United States of America, 99(3), doi:10.1073/pnas.012249999 1389-1394
   [ Abstract ]

   Atmospheric and ground-based methods agree on the presence of a carbon sink in the coterminous United States (the United States minus Alaska and Hawaii), and the primary causes for the sink recently have been identified. Projecting the future behavior of the sink is necessary for projecting future net emissions. Here we use two models, the Ecosystem Demography model and a second simpler empirically based model (Miami Land Use History), to estimate the spatio-temporal patterns of ecosystem carbon stocks and fluxes resulting from land-use changes and fire suppression from 1700 to 2100. Our results are compared with other historical reconstructions of ecosystem carbon fluxes and to a detailed carbon budget for the 1980s. Our projections indicate that the ecosystem recovery processes that are primarily responsible for the contemporary U.S. carbon sink will slow over the next century, resulting in a significant reduction of the sink. The projected rate of decrease depends strongly on scenarios of future land use and the long-term effectiveness of fire suppression.

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