Biogeosciences [B]

B23A  ACC:03   Tuesday

The Fellows Speak: Perspectives on the Science From the New Biogeosciences Section


Presiding: W Reeburgh, Univ. of California, Irvine; K Hibbard, NCAR

B23A-01  

Fire, drought, and feedbacks between the carbon cycle and the climate system

* Randerson, J T (jranders@uci.edu), Department of Earth System Science, University of California, Croul Hall, Irvine, CA 92697, United States
Tosca, M (mtosca@uci.edu), Department of Earth System Science, University of California, Croul Hall, Irvine, CA 92697, United States
Flanner, M G (mflanner@uci.edu), Department of Earth System Science, University of California, Croul Hall, Irvine, CA 92697, United States
van der Werf, G (guido.van.der.werf@falw.vu.nl), Faculty of Earth and Life Sciences Vrije Universiteit, De Boelelaan 1085, Amsterdam, 1081 HV, Netherlands
Lin, H (hwlin@uci.edu), Department of Earth System Science, University of California, Croul Hall, Irvine, CA 92697, United States
Collatz, G J (jcollatz@biome2.gsfc.nasa.gov), NASA Goddard Space Flight Center, Biospheric Sciences Branch Code 614.4, Greenbelt, MD 20771, United States
Kasibhatla, P (psk9@aerosol.env.duke.edu), Nicholas School of the Environment, Duke University, Room A355, Levine Science Research Center, Durham, NC 27708, United States
Zender, C S (zender@uci.edu), Department of Earth System Science, University of California, Croul Hall, Irvine, CA 92697, United States
Giglio, L (louis_giglio@ssaihq.com), Science Systems Applications, Inc., 10210 Greenbelt Road, Suite 600, Lanham, MD 20706, United States

We assess how humans have changed the magnitude (and possibly the sign) of interannual variability of atmospheric carbon dioxide. Remote sensing and trace gas observations from the last decade show that humans take advantage of El Nino-induced drought to clear tropical forests for agriculture at a faster rate. During El Nino events of 1997/1998, 2002, and 2006 fire emissions increased substantially in equatorial Asia. In parallel, fire-emitted aerosols may have reduced light levels and gross primary production at a regional scale. Both of these mechanisms contribute to a strong negative correlation between the Southern Oscillation Index and the CO2 growth rate observed in the Mauna Loa CO2 time series. In the absence of widespread changes in the fire regime caused by humans, two mechanisms linked with El Nino probably have the opposite effect on atmospheric carbon dioxide levels. In intact forests, moderate drought may enhance net ecosystem carbon uptake by causing microbial respiration to shutdown more rapidly than net primary production. Relaxation of the trade winds during El Nino suppresses upwelling and reduces outgassing of CO2 from the eastern equatorial Pacific - strengthening the ocean sink. Based on the differences between the anthropogenic and background terrestrial ecosystem and ocean responses to El Nino, we hypothesize that the sensitivity of terrestrial carbon loss to El Nino events will strengthen in the future with increasing demand for agriculture in tropical regions. More generally, the direct effect of climate on deforestation processes and agricultural productivity represents an important class of feedbacks between the carbon cycle and the climate system that is not yet represented in contemporary models.


B23A-02  

Role of Flux Networks in Biogeosciences

* Baldocchi, D (baldocchi@nature.berkeley.edu), University of California, Berkeley, 137 Mulford Hall Depart of Environmental Science, Policy and Management, Berkeley, ca 94720, United States
Papale, D (darpap@unitus.it), Universita' de Tuscia, Department of Forest Science and Environment (DISAFRI) Via S. Camillo de Lellis, Viterbo, 01100, Italy
Reichstein, M (mreichstein@bgc-jena.mpg.de), Max Planck Institute for Biogeochemistry, Hans-Knöll-Str. 10, Jena, D-07745, Germany

A decade ago, a global network of sites measuring carbon dioxide, water vapor and energy fluxes between vegetation and the atmosphere was initiated. At present over 400 sites exist and together, with over 600 site years of data, they are producing a new view on the breathing of the terrestrial biosphere. In this presentation we will give an overview of the network and a survey of key findings. Among the topics discussed will be the range of annual carbon fluxes measured across a spectrum of climate space and plant functional types, quantification of interannual variability of fluxes, links between gross primary productivity and ecosystem respiration, detection of flux phenology and a presentation of new emergent processes like the role of diffuse light on canopy photosynthesis, the acclimation of canopy photosynthesis with temperature and the detection of pulses and lags in the temporal flux record.


B23A-03  

Using Radiocarbon to Test Models of Ecosystem Carbon Cycling

* Trumbore, S (setrumbo@uci.edu), University of California Irvine, Department of Earth System Science, Irvine, CA 92697-3100, United States
Lin, H (hwlin@uci.edu), University of California Irvine, Department of Earth System Science, Irvine, CA 92697-3100, United States
Randerson, J (jranders@uci.edu), University of California Irvine, Department of Earth System Science, Irvine, CA 92697-3100, United States

The radiocarbon content of carbon stored in and respired by ecosystems provides a direct measure of ecosystem carbon dynamics that can be directly compared to model predictions. Because carbon cycles through ecosystems on a variety of timescales, the mean age of C in standing biomass and soil organic matter pools is older than the mean age of microbially respired carbon. In turn, each pathway for C transit through ecosystems my respond differently to edaphic conditions; for example, soil organic matter mean age is controlled by factors affecting stabilization of C on very long timescales, such as mineralogy, while a factor like litter quality that effects decomposition rates reflects vegetation and climate characteristics. We compare the radiocarbon signature of heterotrophically respired CO2 across a number of ecosystems with models predicted using the CASA ecosystem model. The major controls of microbially respired CO2 from ecosystems include the residence time of C in living plant pools (i.e. the age of C in litter inputs to soil) and factors that control decomposition rates (litter quality and climate). Major differences between model and measured values at low latitudes are related to how woody debris pools are treated differently in models and measurements. The time lag between photosynthesis and respiration is a key ecosystem property that defines its potential to store or release carbon given variations in annual net primary production. Radiocarbon provides a rare case where models can be directly compared with measurements to provide a test of this parameter.


B23A-04 INVITED  

Recent Progress in Biogeochemistry Model Development: Simple vs. Complex Models

* Parton, W (billp@nrel.colostate.edu), Natural Resource Ecology Laboratory, Colorado State University Campus Delivery 1499, Ft. Collins, CO 80523-1499, United States

Biogeochemical models are now used extensively to simulate ecosystem level carbon, nitrogen, and phosphorus dynamics at the site, regional and global scales. These models are widely used to simulate the impact of current agricultural and forestry management practices on nitrogen trace gas fluxes (N2O, NOx, and N2), net carbon exchange, soil NO3 leaching, nutrient cycling (N and P), and plant production. These models are the major tools we have to project the potential impact of future environmental changes on ecosystem dynamics for natural and managed ecosystems. This presentation will discuss the progress we have made in developing ecosystem models, testing models using observed data sets, comparing the performance of the different models, and applying the models at site regional and global scales. Results from using biogeochemical models at different scales will be presented along with an evaluation of how well the models work and potential problems we have with existing models. I will suggest how we might use newly developed fairly simple ecosystem models when we are modeling carbon exchange and nitrogen dynamics at large scales.