Search Results

You are looking at 1 - 10 of 3,903 items for :

  • Ecosystem model x
  • All content x
Clear All
Min Chen and Qianlai Zhuang

biological, physical, and chemical processes of ecosystems and use mathematical equations to represent these processes. These mathematical equations are usually parameterized for representative vegetation types and then extrapolated to regional scales. For example, the Terrestrial Ecosystem Model (TEM) has been widely used to study ecosystem carbon and nitrogen dynamics at different scales since the early 1990s ( Kicklighter et al. 1999 ; McGuire et al. 1992 ; McGuire et al. 2001 ; Melillo et al. 1993

Full access
Gregory R. Quetin and Abigail L. S. Swann

there is no analog ecological community to base predictions on, in order to project vegetation response to novel environments, process-based models must correctly reproduce ecosystem functioning: the sensitivity of vegetation to the physical environment. Observational constraints are critical for testing the fidelity of our ability to simulate ecosystem functioning in the present-day climate and to provide confidence in simulations under a changing climate. Here we evaluate the ecosystem functioning

Open access
Z. M. Subin, W. J. Riley, J. Jin, D. S. Christianson, M. S. Torn, and L. M. Kueppers

for Atmospheric Research Mesoscale Model (MM5) predicted that early harvesting of Midwest crops raised surface air and soil temperature by 1°–2°C ( Cooley et al. 2005 ). Finally, the Simple Biosphere Model (SiB) and the Regional Atmospheric Modeling System (RAMS) were coupled to investigate ecosystem CO 2 fluxes in Wisconsin ( Denning et al. 2003 ). Ecosystems and climate form a feedback cycle because changes in climate can affect the distribution and properties of land cover and because land

Full access
Mônica Carneiro Alves Senna, Marcos Heil Costa, Lucía Iracema Chipponelli Pinto, Hewlley Maria Acioli Imbuzeiro, Luciana Mara Freitas Diniz, and Gabrielle Ferreira Pires

structure may alter the fluxes of energy, water, momentum, CO 2 , and other atmospheric gases, consequently affecting climate ( Pielke et al. 1998 ; Bonan 2002 ; Foley et al. 2003 ). The interactive coupling of terrestrial ecosystems and climate has been examined by fully integrated dynamic global vegetation models within global climate models ( Betts et al. 1997 ; Foley et al. 1998 ; Foley et al. 2000 ; Bonan et al. 2003 ; Krinner et al. 2005 ). In these coupled models, vegetation growth and

Full access
Joy Clein, A. David McGuire, Eugenie S. Euskirchen, and Monika Calef

), were just one of several alternative climate datasets that could have been used in the study. Because there is much uncertainty among the alternative climate datasets in the western Arctic ( Drobot et al. 2006 ; Rawlins et al. 2006 ; Rupp et al. 2007 ), it is not clear the degree to which the findings of Kimball et al. ( Kimball et al. 2007 ) depend on the alternative climate datasets. In this study, we assessed the sensitivity of carbon dynamics by the Terrestrial Ecosystem Model (TEM

Full access
Christopher Potter, Steven Klooster, Alfredo Huete, and Vanessa Genovese

implications for carbon cycle research. Direct input of satellite vegetation index “greenness” data from the MODIS sensor into ecosystem simulation models is now used to estimate spatial variability in monthly net primary production (NPP), biomass accumulation, and litter fall inputs to soil carbon pools. Global NPP of vegetation can be predicted using the relationship between leaf reflectance properties and the absorption of photosynthetically active radiation (PAR), assuming that net conversion

Full access
Akihiko Ito and Motoko Inatomi

ecosystem using a process-based model including major ecohydrological and biogeochemical processes. Although several model studies have explored the interaction between water and carbon cycles (e.g., Kucharik et al. 2000 ; Sitch et al. 2003 ; Krinner et al. 2005 ; Alton et al. 2009 ), few global-scale analyses have examined WUE in relation to natural and human factors. Therefore, we investigated WUE on the basis of global simulations in conjunction with ancillary inventory data on human impacts. 2

Full access
Gretchen Keppel-Aleks, Samantha J. Basile, and Forrest M. Hoffman

evaluate models against observations. When evaluating coupled ESMs, simulated ecosystem properties may disagree with observational metrics due either to misparameterization of the relevant biogeochemical or biogeophysical processes or to biases in the physical climate drivers thereof. Model development and improvement, therefore, requires evaluating simulations using metrics that constrain functional responses—in other words, the relationships between driver and response variables—rather than simply

Full access
Michael A. White, Peter E. Thornton, Steven W. Running, and Ramakrishna R. Nemani

carbon dynamics ( Motovalli et al. 1994 ), effects of nitrogen saturation ( Aber et al. 1997 ), and the location of global carbon sources and sinks ( Houghton et al. 1998 ; Randerson et al. 1997 ). Models can also be used to develop basic theoretical understandings of ecosystem function that cannot be tested with field methods ( Churkina and Running 1998 ; Schimel et al. 1996 ). Perhaps most importantly, models are used to address the political and management need for estimates of ecosystem

Full access
Peter J. Lawrence, Johannes J. Feddema, Gordon B. Bonan, Gerald A. Meehl, Brian C. O’Neill, Keith W. Oleson, Samuel Levis, David M. Lawrence, Erik Kluzek, Keith Lindsay, and Peter E. Thornton

carbon, and soil carbon. Fig . 7. CCSM4 full transient simulation average annual land use carbon flux and total change in all of ecosystem carbon for the CMIP5 historical and RCP periods. Fig . 8. CMIP5 global historical and RCP carbon fluxes of land use, net ecosystem exchange, and wood harvest and all of ecosystem carbon from CCSM4 full transient simulations. The historical global annual carbon fluxes of CCSM4 ( Table 4 ) show that the model had an average global land use carbon flux of 0.76 PgC yr

Full access