GEOG 801 Earth System Sciences/Physical Geography Research Seminar

Department of Geography

University of North Carolina at Chapel Hill

Fall, 2007

Instructor: Dr. Conghe Song

Meeting Time: 3:00-5:30pm Monday

Location of Meeting: 204 Saunders Hall

 Instructor’s Office Hours: 2-3pm MWF

 

Prerequisite: Students enroll in the class must have working knowledge with remote sensing and geographic information systems. Students are also expected to have taken introductory calculus and statistics courses.

 

Course Description: This is a research oriented course with ideas originate from my current research projects funded by NSF and NASA. The goal is to hone your research skills in Earth System Sciences with a focus on terrestrial ecosystem carbon and water exchanges with the atmosphere on a regional scale. Specifically, I wish to achieve the following objectives after you take the course:

 

(1) to improve your understanding of ecosystem processes that control ecosystem carbon and water exchanges with the atmosphere.

(2) to help you acquire the ability to integrate remote sensing and ecosystem models to understand ecosystem functions over a significantly large area.

(3) to enhance your ability in using remote sensing and geographic information systems in your research.

 

 To achieve these objectives, each of you in the class will undertake a semester long research project using a local watershed as your study area. There is a diverse array of watersheds in the triangle area ranging from highly urbanized to mostly agricultural or forested watersheds. We will take advantage of the most current remotely sensed data from Landsat and MODIS to characterize landscape structure, and stream flow records for the watershed collected by USGS. We will use an ecosystem process model developed by the instructor to simulate carbon and water exchange between the land surface and the atmosphere. In the meantime, we will read the relevant papers ranging from the classical ones to the most current in the literature. Toward the end of the semester, we will pool our research results from everyone, and we hope for a synergistic understanding on how landscape structure regulates ecosystem functions on carbon and water fluxes.  Everyone will present their research findings during the final week of the class.

 

Grading Policy: There will be no final exam for the course. Your performance will be evaluated based on your weekly homework (40%), progress on your project (40%), final presentation (10%) and your instructor’s evaluation of the level of creativity you demonstrate during the process (10%).

 

Project Description

 

Reading Schedule

PART I Basic Theories

  1. Bloom et al., 1985. Resources Limitation in Plants—An Economic Analogy. Annual Review of Ecology and Systematics, 16:363-392.
  2. Field, C. 1983. Allocating leaf nitrogen for the maximization of carbon gain - leaf age as a control on the allocation program. Oecologia, 56 (2-3): 341-347.
  3. Penman, H. L. 1945. Natural evaporation from open water, bare soil and grass.
  4. Monteith, J. L., 1965. Evaporation and environment. Symposium of the Society for Experimental Biology, 19:205-234.
  5. Farquhar and Sharkey, 1982. Stomatal conductance and photosynthesis. Annual Review of Plant Physiology, 33:317-345.
  6. Jarvis, P. G. 1976. The interpretation of the variations in leaf water potential and stomatal conductance found in canopies in the field. Philosophical Transactons of the Royal Society of London, Series B, Biological Sciences, 273(927):593-610.
  7. Leuning, R. 1995. A critical appraisal of a combined stomatal-photosynthesis model for C3 plants. Plant, Cell and Environment, 18:339-355.
  8. Monteith, J. L., 1972. Solar radiation and productivity in tropical ecosystems. The Journal of Applied Ecology, 9(3): 747-766.
  9. Law et al., 2002. Environmental controls over carbon dioxide and water vapor exchange of terrestrial vegetation. Agricultural and Forest Meteorology, 113: 97-120.

PART II Carbon Models

  1. Running and Coughlan, 1988. A general model for forest ecosystem processes for regional application: 1. Hydrological balance, canopy gas exchange and primary production processes. Ecological Modelling, 42: 125-154.
  2. Wang, Y. P. and Jarvis, P. G.  1990. Description and validation of an array model – MAESTRO. Agricultural And Forest Meteorology 51 (3-4): 257-280 JUL 1990 Maestro
  3. Biome-BGC, 2002. see data/ directory
  4. Portter et al., 1993. Terrestrial ecosystem production: a process model based on global satellite and surface data. Global Biogeochemical Cycles, 7(4): 811-841.
  5. Landsberg and Waring, 1997. A generalize model of forest productivity using simplified concepts of radiation-use efficiency, carbon balance and partitioning. Forest Ecology and Management, 95: 209-228.
  6. Running et al., 2004. A continuous satellite-derived measure of global terrestrial primary production. Bioscience, 54(6): 547-560.

 

PART III Transpiration Models

  1. Thornthwhite, C. W. An Approach toward a Rational Classification of Climate. Geographical Review, 38(1):55-94.
  2. Priestley and Taylor, 1972. Assessment of surface heat-flux and evaporation using large-scale parameters. Monthly Weather Review, 100(2):81-
  3. Choudhury and DiGirolamo, 1998. A biophysical process-based estimate of global land surface evaporation using satellite and ancillary data. Journal of Hydrology, 205:164-185.
  4. Shuttleworth, W. J. 2007. Putting the “Vap” into Evaporation. Hydrology and Earth System Sciences, 11(1): 210-244.
  5. Venturini et al., 2007. Estimation of evaporative fraction and evapotranspiration from MODIS products using a complementary based model. Remote Sensing of Environment, In Press.
  6. Mu, Q. et al., 2007. Development of a global evapotranspiration algorithm based on MODIS and global meteorology data. Remote Sensing of Environment, In Press.

 

PART IV Critical Issues

  1. Wessman, C. A. 1992. Spatial scales and global change: bridging the gap from plots to GCM grid cells. Annual Review of Ecology and Systematics,  23:175-200.
  2. Pierce and Running, 1995. The effects of aggregating sub-grid land surface variation on large-scale estimates of net primary production. Landscape Ecology, 10(4): 239-253.
  3. Schulze, E.-D., et al., 1994. Relationships among maximum stomatal conductance, ecosystem surface conductance, carbon assimilation rate, and plant nitrogen nutrition: A global ecology scaling exercise. Annual Review of Ecology and Systematics, 25: 629-660.
  4. Friend, A. D. 2001. Modelling canopy CO2 fluxes: are 'big-leaf' simplifications justified? Global ecology and biogeography, 10(6):603-619.
  5. Friend, A. D. 2007. FLUXNET and modelling the global carbon cycle. Global Change Biology, 13(3):610-633.
  6. Niyogi and Raman, 1997. Comparison of four different stomatal resistance schemes using FIFE observations. Journal of Applied Meteorology, 36: 903-917.
  7. Churkina, et al., 1999. Comparing global models of terrestrial net primary productivity (NPP): the importance of water availability. Global Change Biology
  8. Choudhury and Monteith, 1988. A four-layer model for the heat budget of homogeneous land surfaces, Q. J. Royal Meterol. Soc., 114:373-398.
  9. Wilson, et al., 2000. Factors controlling evaporation and energy partitioning beneath a deciduous forest over an annual cycle. Agricultural and Forest Meteorology, 102:83-103.
  10. Liu, et al., 2003. Mapping evapotranspiration based on remote sensing: An application to Canada’s landmass. Water Resources Research, 39(7):doi:10.1029/2002WR001680.
  11. Olioso et al., 1999. Estimation of Evapotranspiration and photosyntehsis by assimilation of remote sensing data iinto SVAT models. Remote Sensing of Environment, 69: 341-356.
  12. Niyogi and Raman, 1997. Comparison of four different stomatal resistance schemes using FIFE observations. Journal of Applied Meteorology, 36: 903-917.

 

  1. Wullschleger et al., 2002. Sensitivity of stomatal and canopy conductance to elevated CO2 concentration – Interacting variables and perspective of scale. New Phytologist. 153: 485-496
  2. Eamus, D. 1991. The interaction of rising CO2 and temperature with water use efficiency. Plant, Cell and Environment. 14: 843-852.
  3. Boulain et al., 2007. Changing scale in ecological modeling: a bottom up approach with an individual based vegetation model. Ecological Modelling, 203: 257-269.