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The ECOPHYS model is an ecophysiological growth process model of juvenile poplar clones growing under near optimal conditions. The theoretical basis for the ECOPHYS model is that (1) individual leaves drive and control growth; (2) the microenvironment at the leaf exerts primary control of photosynthetic rates; (3) leaf orientation is a major determinant of that microenvironment, (4) photosynthates produced by leaves are allocated among meristematic and respiratory sinks: and (5) the plant's genome and microenvironment regulate photosynthate allocation. The major driving variables are solar radiation, temperature, and clonal morphological and physiological factors. The user can interact or override any or all of the input variables to examine the effects of such changes on photosynthetic production and growth. Verification and sensitivity analyses of ECOPHYS are presented and discussed. The use of ECOPHYS as a research tool is illustrated with several examples. Model potential and limitations are discussed.

Many authors have pointed out the need to firm up the 'fuzzy' ecosystem management paradigm and develop operationally practical processes to allow forest managers to accommodate more effectively the continuing rapid change in societal perspectives and goals. There are three spatial scales where clear, precise, practical ecosystem management processes are needed: the regional assessment scale, the forest-level scale, and the project-level scale. This paper proposes a practical decision analysis process for ecosystem management at the project-level scale. Goals are the focal point of management. To achieve them requires a formal, structured goal hierarchy, desired future conditions, several interesting alternatives, scenario analysis, and monitoring and evaluation of the results. The proposed process is firmly grounded in the body of theory and practice organized in the scientific literature under the heading of multi-objective decision analysis. An illustrative example of this decision analysis process is presented using the Bent Creek Experimental Forest of the Pisgah National Forest near Asheville, NC as a test case. Published by Elsevier Science B.V.

NED-2 is a Windows-based system designed to improve project-level planning and decision making by providing useful and scientifically sound information to natural resource managers. Resources currently addressed include visual quality, ecology, forest health, timber, water, and wildlife. NED-2 expands on previous versions of NED applications by integrating treatment prescriptions, growth simulation, and alternative comparisons with evaluations of multiple resources across a management unit. The NED-2 system is adaptable for small private holdings, large public properties, or cooperative managernent across multiple ownerships. NED-2 implements a goal-driven decision process that ensures that all relevant goals are considered; the character and current condition of forestland are known; alternatives to manage the land are designed and tested; the future forest under each alternative is simulated; and the alternative selected achieves the owner's goals. NED-2 is designed to link with ' The computer programs described in this document are available with the understanding that the U.S. Department of Agriculture cannot assure their accuracy, completeness, reliability, or suitability for any purposes other than that reported. The use of trade, firm, or corporation names in this publication is for the infomation and convenience of the reader. Such use does not constitute an official endorsement or approval by the U.

Al_tract. Models that address the impacts to forests of climate change are reviewed by four levels of biological organization: global, regional or landscape, community, and tree. The models are compared as to their ability to assess changes in greenhouse gas flux, land use, maps of forest type or species composition, forest resource productivity, forest health, biodiversity, and wildlife habitat. No one model can address ali of these impacts, but landscape transition models and regional vegetation and land-use models consider the largest number of impacts. Developing landscape vegetation dynamics models of functional groups is suggested as a means to integrate the theory of both landscape ecology and individual tree responses to climate change. Risk assessment methodologies can be adapted to deal with the impacts of climate change at various spatial and temporal scales. Four areas of research development are identified: (1) linking socioeconomic and ecologic models, (2) interfacing forest models at different scales, (3) obtaining data on susceptibility of trees and forest to changes in climate and disturbance regimes, and (4) relating information from different scales.