Forest Productivity and Diversity: Using Ecological Theory and Landscape Models211 to Guide Sustainable Forest Management

摘要

Sustainable forest management requires maintaining or increasing ecosystem211u001eproductivity, while preserving or restoring natural levels of biodiversity. 211u001eApplication of general concepts from ecological theory, along with use of 211u001emechanistic, landscape-based computer models, can contribute to the successful 211u001eachievement of both of these objectives. Ecological theories based on the 211u001eenergetics and dynamics of populations can be used to predict the general 211u001edistribution of individual species, the diversity of different types of species, 211u001eecosystem process rates and pool sizes, and patterns of spatial and temporal 211u001eheterogeneity over a broad range of environmental conditions. This approach 211u001erequires subdivision of total biodiversity into functional types of organisms, 211u001eprimarily because different types of organisms respond very differently to the 211u001espatial and temporal variation of environmental conditions on landscapes. The 211u001ediversity of species of the same functional type (particularly among plants) 211u001etends to be highest at relatively low levels of net primary productivity, while 211u001ethe total number of different functional types (particularly among animals) tends 211u001eto be highest at high levels of productivity (e.g., site index or potential net 211u001eprimary productivity). In general, the diversity of animals at higher trophic 211u001elevels (e.g., predators) reaches its maximum at much higher levels of 211u001eproductivity than the diversity of lower trophic levels (e.g., plants). This 211u001emeans that a single environment cannot support high diversity of all types of 211u001eorganisms. Within the framework of the general patterns described above, the 211u001edistributions, population dynamics, and diversity of organisms in specific 211u001eregions can be predicted more precisely using a combination of computer 211u001esimulation models and GIS data based on satellite information and ground surveys. 211u001eBiophysical models that use information on soil properties, climate, and 211u001ehydrology have been developed to predict how the abundance and spatial 211u001edistribution of various plants and animals. These models can be, used to predict 211u001ethe patterns of forest type and structure that develop in response to variation 211u001ein productivity and disturbance across complex landscapes, as well as species 211u001ediversity and the distribution and population fluctuations of threatened species 211u001ein specific regions.