SPATIAL MODELS OF ENERGY FLOW AND

NUTRIENT DYNAMICS

ROQUE MERRICK A. DACULLO, BSBIO-3; BOTANY

VISAYAS STATE UNIVERSITY

ECOSYSTEM SCIENCE

SIMULATION MODELING

LANDSCAPE DYNAMICS

ECOSYSTEM PROCESSES

MODELS OF ENERGY FLOW & NUTRIENT DYNAMICS

CENTURY FOREST-BGC FIRE-BGC

CENTURY

• A widely used model developed to simulate grassland ecosystems (Parton et al.,1987, 1988).

CENTURY COMBINED WITH GIS DATA (BURKE, ET AL. 1990)

• Inputs- spatial data for climate and soils

• Outputs- spatial patterns of NPP, soil organic carbon, net nitrogen mineralization, and oxidized nitrogen emissions

• Their study aimed to simulate spatial variability in storage and flux of carbon and nitrogen for the northeastern quarter of Colorado in the U.S. Central Grasslands

CENTURY COMBINED WITH GIS DATA (BURKE, ET AL. 1990)

• Scale-dependent effects identified in their study

• Climate data aggregated at coarse-scale yet still produce reasonable estimates of NPP

• Soil texture must be represented at finer scale due to nonlinear relationships between soil texture and soil organic matter (SOM)

• Costanza et al. (1990) developed another model for the Atchafalaya Basin to evaluate a variety of alternative management strategies to reduce coastal erosion.

• 2479 1-km2 grid cells connected to one another by simulated fluxes of water, nutrients, and sediments

FOREST-BGC MODEL

• Started as a single-tree water balance model for a year and developed into an integrated carbon, nitrogen, and water cycle model (Running and Hunt, 1993)

• Predicts photosynthesis, respiration, evapotranspiration, decomposition, and nitrogen mineralization over broad landscapes

• Used to calibrate simple models for implementation at the global scale (Hunt et al, 1991; Running, 1994)

• Calibration of simple models offers a powerful approach for scaling (Running and Hunt, 1993).

• Overton (1975) suggested to use multiscale models that contain submodels operating at different scales and degrees of complexity.

• This promises new insight into simulating ecosystem pattern and processes (DeAngelis et al.)

FIRE-BGC MODEL

• Forest gap model linked with BGC and effects of fire disturbances and succession were incorporated (Keane et al., 1996)

IMPORTANT POINTS DEMONSTRATED BY MODELING STUDIES• Spatial variations in abiotic variables often produce

substantial variation, themselves, in ecosystem processes.

• Abiotic template is a powerful constraint on ecosystem function.

• Abiotic factors vary over multiple spatial scales; appropriate scales must be determined for developing predictive relationships.

• Furthest limit of knowledge in landscape ecology is the implications of the dynamic landscape mosaic for ecosystem processes.

• Absence of a spatially explicit, well-developed theory of ecosystem function

• Lack of empirical studies as sources of general conclusions

REFERENCES:

1. Picket, S.T.A., Cadenasso, M.L. (2004). Landscape Ecology: Spatial Heterogeneity in Ecological Systems. Science. Retrieved from http://links.jstor.org/sici?sici=0036-8075%2819950721%293%3A269%3A269%3A5222%3C331%3ALESHIE%3E2.0.CO%3B2-Z

2. Turner et al. (2001). Landscape Ecology in Theory and Practice. New York, USA: Springer.

3. http://www.ncgia.ucsb.edu/conf/SANTA_FE_CD-ROM/sf_papers/mckeown_rebecca/figure1.gif

4. http://firelab.org/sites/default/files/images/projects/fbgc-clime_fire.jpg

THANK YOU!