Forest Productivity and Diversity: Using Ecological Theory and Landscape Models to Guide Sustainable Forest Management
Sustainable forest management requires maintaining or increasing ecosystem productivity, while preserving or restoring natural levels of biodiversity. Application of general concepts from ecological theory, along with use of mechanistic, landscape-based computer models, can contribute to the successful achievement of both of these objectives. Ecological theories based on the energetics and dynamics of populations can be used to predict the general distribution of individual species, the diversity of different types of species, ecosystem process rates and pool sizes, and patterns of spatial and temporal heterogeneity over a broad range of environmental conditions. This approach requires subdivision of total biodiversity into functional types of organisms, primarily because different types of organisms respond very differently to the spatial and temporal variation of environmental conditions on landscapes. The diversity of species of the same functional type (particularly among plants) tends to be highest at relatively low levels of net primary productivity, while the total number of different functional types (particularly among animals) tends to be highest at high levels of productivity (e.g., site index or potential net primary productivity). In general, the diversity of animals at higher trophic levels (e.g., predators) reaches its maximum at much higher levels of productivity than the diversity of lower trophic levels (e.g., plants). This means that a single environment cannot support high diversity of all types of organisms. Within the framework of the general patterns described above, the distributions, population dynamics, and diversity of organisms in specific regions can be predicted more precisely using a combination of computer simulation models and GIS data based on satellite information and ground surveys. Biophysical models that use information on soil properties, climate, and hydrology have been developed to predict how the abundance and spatial distribution of various plants and animals. These models can be, used to predict the patterns of forest type and structure that develop in response to variation in productivity and disturbance across complex landscapes, as well as species diversity and the distribution and population fluctuations of threatened species in specific regions.
- Research Organization:
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- Sponsoring Organization:
- USDOE Office of Science (US)
- DOE Contract Number:
- AC05-00OR22725
- OSTI ID:
- 772471
- Report Number(s):
- P00-108426; TRN: AH200101%%56
- Resource Relation:
- Conference: North American Science Symposium, Guadalajara (MX), 11/01/1998--11/06/1998; Other Information: PBD: 1 Nov 1998
- Country of Publication:
- United States
- Language:
- English
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