Developing Earth Observation (EO)-based Ecosystem Modelling Tools for the Assessment of Climate Change Impacts

Activity Rationale

This activity focuses on developing ecosystem models and a satellite data assimilation system in order to:

• Better understand how ecosystems respond to climate changes.
• Quantify the current state of Canada’s key ecosystems and how ecosystems have changed over the recent past.
• Predict future climate change impacts on ecosystems including water, carbon, nitrogen, and energy cycles.
• Provide decision-makers with useful information for the sustainable management of Canada’s natural resources.

Activity Leader: Shusen Wang

The Topic

Ecosystems are dynamic, complex systems in which living organisms interact with each other and their environment. Ecosystems are influenced largely by climate variables, affecting processes such as energy and water balance, carbon and nutrient cycling, and ecosystem integrity and services. On the other hand, ecosystems affect the climate system by regulating water, energy, and carbon dioxide fluctuations.

To improve our capability in climate change impact assessment, a comprehensive ecosystem model is required to address the many interactions between climate change and ecosystems. In addition, different ecosystems can have very different responses to the climate change and its variation. To provide more scientific support for ecosystem impact assessment at a national scale, it is imperative that ecosystem models have the capability of assimilating large scale geospatial information from satellite observations, GIS datasets, and climate model outputs or reanalysis. The EALCO model (Ecological Assimilation of Land and Climate Observations) is developed for such purposes.

The EALCO model simulates the comprehensive interactions among ecosystem processes and climate, and assimilates a variety of remote sensing products and GIS databases. It provides both national and local scale model outputs of how ecosystems respond to climate change including plant and overall ecosystem productivity, water conditions and hydrological cycles, carbon sequestration and greenhouse gas exchange, energy states, radiation budgets, and nutrient (nitrogen) cycling. The results form the foundation for the assessment of climate change impacts on ecosystem functioning and the invaluable services that ecosystems provide.

Results

The following summarizes some of the advances and outputs in ecosystem performance and change monitoring, modelling, and mapping. If you would like more detailed information, please contact Shusen Wang

Ecosystem water cycles

Ecosystem water cycles involve a number of water fluxes, including:

• Water inputs through precipitation (either rain or snow) and dew and frost formation.
• Water outputs through surface runoff, drainage or groundwater recharge, and evapotranspiration (ET). Surface water runoff and drainage link terrestrial ecosystems with aquatic ecosystems and groundwater systems. ET includes evaporation from soil or from intercepted precipitation on the tree canopy, sublimation from snow, and transpiration from plant leaves. ET is important to ecologists because it is highly related to plant productivity and carbon sequestration. ET is also important to hydrologists and hydrogeologists because it represents a considerable amount of water lost from a watershed, and to climatologists and meteorologists because it affects atmospheric processes such as cloud development.
• Soil water content and change. Soil water is the major source of plant water uptake and it largely determines the plant growing conditions.

The EALCO model simulates the dynamics of the water cycles stated above. Important outputs from the water cycle modelling include evapotranspiration, surface runoff, groundwater recharge or uptake, soil water content, and snow water equivalent.

 

Ecosystem carbon cycles

Ecosystem carbon cycles involve a number of carbon fluxes, including:

• Carbon fixation, mainly through photosynthesis by plant leaves.
• Carbon release through respiration, which includes autotrophic respiration by plants and heterotrophic respiration by soil microorganisms through organic matter decomposition.
• Carbon exchange induced by ecosystem disturbances such as forest fires and harvesting.
• Ecosystem carbon changes due to plant biomass and soil organic matter changes.

The ecosystem carbon cycle modelling and mapping research was conducted by using the EALCO model, remote sensing products, and other geospatial datasets. Outputs include gross primary production (GPP), net primary production (NPP), net ecosystem production (NEP), plant biomass, soil carbon content, and others.

 

Drought impact monitoring, modelling, and mapping

The Canadian Prairies have highly variable precipitation patterns, both in location and through time. The years 2001 and 2002 were associated with the worst drought in a hundred years in many parts of the Canadian Prairies. Abnormally dry meteorological conditions persisted in the west-central Prairie region for eight consecutive seasons from autumn 2000 to summer 2002 (see Drought Watch for precipitation distribution at   http://www.agr.gc.ca/pfra/drought/index_e.htm). The longevity of the dry weather led to severe agricultural, hydrologic, and socio-economic impacts over various time and space scales on many sectors of the Canadian Prairies.

In the maps below we compared Net Primary Productivity (NPP) simulated by EALCO in the dry year of 2002 with those in 2005, which had normal or above normal precipitation over most parts of the region. The models clearly show lower NPP (indicated by the blue end of the spectrum) in 2002 compared to 2005, particularly in the west-central region.

Ecosystem radiation and energy balance

Radiation absorbed by plants, soil, and snow provides energy for the ecosystem to function. All ecological processes such as water and carbon cycles are powered by the ecosystem net radiation. Therefore, ecosystem radiation simulation and its accuracy provide the foundation for modelling other ecological processes. EALCO outputs include surface albedo, forest canopy, soil/snow surface radiation absorption, and longwave radiation fluxes and balances.

Soil and snow

Soil freeze and thaw has profound significance in high latitude ecosystems. Soil thermal and water conditions affect plant phenology and the plant root and soil microbial activities. Snow cover is typical in northern ecosystems, and due to its low thermal conductivity and high albedo, it has large impacts on the soil thermal regime and microclimate. Accurate simulations of snow accumulation and melt and soil thermal and water conditions are critical to the assessment of climate change impacts on ecosystems. In the EALCO model, a detailed snow and soil scheme is developed to improve the simulations of snow and soil thermal and water regimes.

Links

Ecosystem productivity map used in Biodiversity Atlas by BC Ministry of Environment

Canadian Centre for Remote Sensing

Publications

Please note that subscriptions may be required for access to some articles. To request a copy of publications, or for any more information, please contact Shusen Wang

Check for more recent publications in GEOSCAN, the publications database of the Geological Survey of Canada and the Canada Centre for Remote Sensing.

Wang, S., Yang, Y., Trishchenko, A. P., Barr, A. G., Black, T.A., McCaughey, H., 2008, Modelling the response of canopy stomatal conductance to humidity. Journal of Hydrometeorology , (in press).

Wang, S., 2008, Simulation of evapotranspiration and its response to plant water and CO2 transfer dynamics. Journal of Hydrometeorology, 9: 426-443, DOI: 10.1175/2007JHM918.1.

Trishchenko A. P., Yi Luo, Konstantin V. Khlopenkov, William M. Park, Shusen Wang, 2008, Arctic Circumpolar Mosaic at 250-m Spatial Resolution for IPY by Fusion of MODIS/TERRA Land Bands B1-B7. International Journal of Remote Sensing(in print).

Trishchenko A. P., Luo, Y., Khlopenkov, K. V., and Wang, S., 2008, A method to derive the multi-spectral surface albedo consistent with MODIS from historical AVHRR and VGT satellite data. Journal of Applied Meteorology and Climatology, 47, 1199–1221, DOI: 10.1175/2007JAMC1724.1

Zhang, Y., Wang, S., Barr, A.G., Black, T.A., 2008. Impact of snow cover on soil temperature and its simulation in the EALCO model. Cold Regions Science and Technology, 52, 355-370, doi:10.1016/j.coldregions.2007.07.001.

Wang, S., Trishchenko, A. P., Sun, X., 2007, Simulation of canopy radiation transfer and surface albedo in the EALCO model. Climate Dynamics 29:615–632, DOI: 10.1007/s00382-007-0252-y.

Wang, S., and Davidson, A., 2007, Impact of climate variations on surface albedo of a temperate grassland. Agricultural and Forest Meteorology 142, 133-142.

Fernandes, R., Korolevich, V., Wang, S., 2007, Trends in land evapotranspiration over Canada for the period 1960-2000 based on in-situ climate observations and a land surface model. Journal of Hydrometeorology, 8, 1016-1030.

Mi, N., Yu Gui-Rui, Wang Pan-Xing,Wen Xue-Fa, Sun Xiao-Min, Zhang Lei-Ming, Song Xia, and Wang S., 2007, Modeling seasonal variation of CO2 flux in a subtropical coniferous forest using the EALCO model, Journal of Plant Ecology , 31, 1119-1131.

Wang, S., Trishchenko, A. P., Khlopenkov, K. V. and Davidson, A. (2006), Comparison of International Panel on Climate Change Fourth Assessment Report climate model simulations of surface albedo with satellite products over northern latitudes, Journal of Geophysical Research, 111, D21108, doi:10.1029/2005JD006728.

Davidson, A., Wang, S., and Wilmshurst, J., 2006, Remote sensing of grassland-shrubland vegetation water content in the shortwave domain. International Journal of Applied Earth Observation and Geoinformation, 8, 225-236.

Grant R.F., Zhang Y., Yuan F., Wang S., Hanson P.J., Gaumont-Guay D., Chen J., Black T.A., Barr A., Baldocchi D.D., Arain A., 2006, Intercomparison of techniques to model water stress effects on CO2 and energy exchange in temperate and boreal deciduous forests. Ecological Modelling, 196, 289–312.

Wang, S., 2005, Dynamics of land surface albedo for a boreal forest and its simulation. Ecological Modelling, 183, 477–494, doi:10.1016/j.ecolmodel.2004.10.001.

Zhang, Y., Grant, R.F., Flanagan, L.B., Wang, S., Verseghy, D.L., 2005, Modelling CO2 and energy exchanges in a northern semiarid grassland using the carbon- and nitrogen-coupled Canadian Land Surface Scheme (C-CLASS). Ecological Modelling, 181, 591–614.

Grant R.F., Arain A., Arora V., Barr A., Black T.A. Chen J., Wang, S., Yuan F., Zhang Y., 2005, Intercomparison of techniques to model high temperature effects on CO2 and energy exchange in temperate and boreal coniferous forests. Ecological Modelling, 188, 217–252.

Davidson, A. and Wang, S., 2005, Spatio-temporal variations in land surface albedo across Canada from MODIS observations, Canadian Journal for Remote Sensing 31(5), 377–390.

Latifovic, R., Trishchenko, A. P., Chen, J., Park, W. B., Khlopenkov, K. V., Fernandes, R., Pouliot, D., Ungureanu, C., Luo, Y., Wang, S., Davidson, A., and Cihlar, J., 2005, Generating historical AVHRR 1-km baseline satellite data records over Canada suitable for climate change studies. Canadian Journal for Remote Sensing 31(5), 324–346.

Hanson, P.J., et al., 2004, Oak forest carbon and water simulations: model intercomparisons and evaluations against independent data. Ecological Monographs 74(3), 443–489.