- Related Research Areas
- Carbon Cycle & Ecosystems
Globally, wetland soils contain a significant proportion of the terrestrial soil carbon (C) (20 - 25%), despite occupying a small proportion of the total land area (2-3%), and a majority of that C is in high northern latitude soils. Northern hydric soils are particularly susceptible to climatic changes because hydrology (e.g., precipitation) and temperature (especially with permafrost soils) strongly influence the soil C balance. We suggest that changes in the soil temperature regime will drastically alter permafrost soils, and interactions with alterations with the water regime will alter the anaerobic conditions that regulate C storage, transformations and fluxes. We propose to develop a process-based modeling framework, driven with remotely sensed data, to assess changes in the terrestrial C cycle resulting from changes in ecosystem structure and function in response to altered climatic regimes. The model framework will integrate three robust models to address the high northern latitude conditions.(1) Wetland-DNDC was developed with a focus on water, C and nitrogen (N) biogeochemistry in wetlands, it incorporates hydrologic drivers (e.g., water table, vertical and horizontal water flux) that regulate the C cycle to dynamically divide the soil profile into saturated and unsaturated zones and hence to simultaneously simulate the aerobic and anaerobic biogeochemical processes occurring in the wetland ecosystems; (2) NEST predicts long-term impacts of climate change on the soil temperature and moisture regimes in permafrost zones; and (3) ArcVeg is a nutrient-based, plant community and ecosystem model designed to simulate the transient effects of temperature change on the biomass and community composition of a variety of arctic ecosystems This proposal is to (1) develop a DNDC-based modeling framework for simulating permafrost/wetland hydroclimate, arctic plant growth and C biogeochemistry in northern high latitudes; (2) calibrate and validate the modeling framework against observations from both field measurements (e.g., eddy tower data, chamber fluxes, forest inventories etc.) and remote sensing analysis (e.g., biomass production, soil moisture etc.) at five selected sites across northern high latitude regions; (3) utilize PASLSAR, MODIS, and Landsat data to parameterize vegetation, soil, water/moisture and disturbance (e.g., large-scale forest fires, peat fires) at landscape scale surrounding the selected sites, (4) develop GIS databases to link the climate, soil, vegetation and hydrology information generated from statistic and remotely sensed data as input drivers to the modeling framework; and (5) predict impacts on C dynamics and non-CO2 greenhouse emissions of climate change scenarios produced by RCMs with a time span of 100 years for the selected landscapes. We will develop and test a computer simulation tool by integrating field data, remote sensing images and biogeochemical models through the proposed project. If successful, the modeling framework could be applied as an operational platform for assessing C dynamics in northern high latitudes at large regional scales.
Project PI: Changsheng Li/University of New Hampshire
Institute for the Study of Earth, Oceans, and Space Morse Hall University of New Hampshire 8 College Road Durham, NH 03824-3525
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