Mark J. Twery

Neighborhood Analyses Of Canopy Tree Competition Along Environmental Gradients In New England Forests

We use permanent-plot data from the USDA Forest Services Forest Inventory and Analysis (FIA) program for an analysis of the effects of competition on tree growth along environmental gradients for the 14 most abundant tree species in forests of northern New England, USA. Our analysis estimates actual growth for each individual tree of a given species as a function of average potential diameter growth modified by three sets of scalars that quantify the effects on growth of (1) initial target tree size (dbh), (2) local environmental conditions, and (3) crowding by neighboring trees. Potential growth of seven of the 14 species varied along at least one of the two environmental axes identified by an ordination of relative abundance of species in plots. The relative abundances of a number of species were significantly displaced from sites where they showed maximum potential growth. In all of these cases, abundance was displaced to the more resource-poor end of the environmental gradient (either low fertility or low moisture). The pattern was most pronounced among early successional species, whereas late-successional species reached their greatest abundance on sites where they also showed the highest growth in the absence of competition. The analysis also provides empirical estimates of the strength of intraspecific and interspecific competitive effects of neighbors. For all but one of the species, our results led us to reject the hypothesis that all species of competitors have equivalent effects on a target species. Most of the individual pairwise interactions were strongly asymmetric. There was a clear competitive hierarchy among the four most shade-tolerant species, and a separate competitive hierarchy among the shade-intolerant species. Our results suggest that timber yield following selective logging will vary dramatically depending on the configuration of the residual canopy, because of interspecific variation in the magnitude of both the competitive effects of different species of neighbors and the competitive responses of different species of target trees to neighbors. The matrix of competition coefficients suggests that there may be clear benefits in managing for specific mixtures of species within local neighborhoods within stands.

A Practical Decision-Analysis Process for Forest Ecosystem Management

Abstract 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.

Decision support systems for ecosystem management: An evaluation of existing systems

This report evaluated 24 computer-aided decision support systems (DSS) that can support management decision-making in forest ecosystems. It compares the scope of each system, spatial capabilities, computational methods, development status, input and output requirements, user support availability, and system performance. Questionnaire responses from the DSS developers (who have sole responsibility for their content) provide the basis for four summary tables comparing system capabilities. The responses are also presented verbatim for reference. This evaluation aids potential users of decision support systems in determining which system most closely fulfills their needs.

UNDERSTORY PLANT RESPONSES TO UNEVEN-AGED FORESTRY ALTERNATIVES IN NORTHERN HARDWOOD-CONIFER FORESTS

The understory layer encompasses the majority of plant species diversity in forested ecosystems and may be sen- sitive to timber harvest disturbance. We hypothesize that (i) uneven-aged, low-intensity silvicultural systems can maintain understory plant diversity and support late-successional species following harvest disturbance; (ii) retaining and enhancing stand structural complexity can increase understory plant diversity in northern hardwood-conifer forests; and (iii) plant re- sponses are influenced by interactions among canopy structure, soils, and climate processes. Experimental treatments in- clude single-tree selection and group selection, both modified to increase structural retention, and a third technique designed to promote late-successional forest structure and function, structural complexity enhancement. Four replications of each treatment were applied to 2 ha units in Vermont and New York, USA. Understory vegetation was monitored 2 years pre- and 4 years post-treatment. Results show that over time, understory responses were strongly affected by overstory treatment and less influenced by soils and drought. All treatments succeeded at maintaining overall composition and diver- sity. However, late-successional diversity increased significantly in structural complexity enhancement units compared with group selection units. These results indicate that while conventional uneven-aged systems can maintain understory plant di- versity, variations that retain or enhance structural complexity may be more effective at retaining late-successional species.

NED-2: an agent-based decision support system for forest ecosystem management

Abstract Decision making for forest ecosystem management can include the use of a wide variety of modeling tools. These tools include vegetation growth models, wildlife models, silvicultural models, GIS, and visualization tools. NED-2 is a robust, intelligent, goal-driven decision support system that integrates tools in each of these categories. NED-2 uses a blackboard architecture and a set of semi-autonomous agents to manage these tools for the user. The blackboard integrates a Microsoft Access database and Prolog clauses, and the agents are implemented in Prolog. A graphical user interface written in Visual C++ provides powerful inventory analysis tools, dialogs for selecting timber, water, ecological, wildlife, and visual goals, and dialogs for defining treatments and building prescriptive management plans. Users can simulate management plans and perform goal analysis on different views of the management unit, where a view is determined by a management plan and a point in time. Prolog agents use growth and yield models to simulate management plans, perform goal analyses on user-specified views of the management unit, display results of plan simulation using GIS tools, and generate hypertext documents containing the results of such analysis. Individual agents use metaknowledge to set up and run external simulation models, to load rule-based models and perform inference, to set up and execute external GIS and visualization systems, and to generate hypertext reports as needed, relieving the user from performing all these tasks.

A web-based expert system for gypsy moth risk assessment

The gypsy moth is one of North Americas most devastating exotic forest pests because it can cause the loss of valuable oak species, degraded aesthetics, loss of wildlife habitat, and detrimental effects on watersheds. Due to the increasingly wide infestation of the gypsy moth, it is important to develop decision aids that help assess the risks of this pest to our forests. Expert systems are a type of decision aid that could be applied to the area of risk assessment. We have developed the Gypsy Moth Expert System to estimate the risk that a forest stand faces from the gypsy moth based on the composition, structure, and management objectives of a particular forest. Risk assessment in this context is developed from forest susceptibility to infestation, vulnerability to damage caused by an infestation, and the hazard that management objectives for a forest may be affected if damage occurs. The system uses a straightforward set of if-then rules to classify risk. The development of a web-based expert system presented significant challenges to maintaining remote user processing integrity.

Beech Bark Disease: Proceedings of the Beech Bark Disease Symposium

Contains invited papers, short contributions, abstracts, and working group summaries from the Beech Bark Disease Symposium in Saranac Lake, NY, June 16-18, 2004.

NED-1: integrated analyses for forest stewardship decisions

NED is a collective term for a set of software intended to help resource managers develop goals, assess current and potential conditions, and produce sustainable management plans for forest properties. The software tools are being developed by the USDA Forest Service, Northeastern and Southern Research Stations, in cooperation with many other collaborators. NED-1 is a Windows-based program that helps analyze forest inventory data from the perspective of various resources on management areas as large as several thousand hectares. Resources addressed include visual quality, ecology, forest health, timber, water, and wildlife. NED-1 evaluates the degree to which an individual stand or an entire management unit may provide the conditions required to accomplish specific goals. NED-1 users select from a variety of reports, including tabular data summaries, general narratives, and goal-specific analyses. An extensive hypertext system provides information about the resource goals, the desired conditions that support achieving those goals, and related data used to analyze the actual condition of the forest, as well as detailed information about the program itself and the rules and formulas used to produce the analyses. The software is constructed in C++ using an application framework; the inferencing component that handles the rule bases uses Prolog.

Goals and Goal Orientation in Decision Support Systems for Ecosystem Management

We explore a goal-oriented as opposed to a problem-oriented approach to DSS development for ecosystem management. Ecosystem management ordinarily is guided by a set of goals that may conflict in various ways. Problems are perceived obstacles to realizing goals. Identifying and resolving conflicts between goals, testing current or projected situations for goal satisfaction, and problem identification all require a robust model of the goal structure for the intended domain. The lowest level of this goal structure must be represented as desirable future conditions consisting of proposed values for observable indicators. A model of the causal, legal, and other institutional relations between these desirable future conditions is also needed. Two projects based on a goal-oriented approach to DSS development are described. The first project has produced an initial prototype that incorporates goals for forest management in rules representing three tiers: management unit goals, stand-level goals, and desirable future conditions. The second, at an initial knowledge acquisition stage, is an attempt to develop a participatory decision-making methodology for socially and environmentally sensitive economic development in Central America.

Woody understory response to changes in overstory density: thinning in Allegheny hardwoods

Understanding the effects of silvicultural treatments on understory vegetation is important in predicting the consequences of such treatments, not only on regeneration but also on wildlife habitat, visual qualities, and recreation. We sought to develop an empirical model of understory response that could be generalized to other forest types. We analyzed understory populations of tree species for 15 years following thinning to different residual relative densities in 50- to 55-year-old Allegheny hardwoods. The average number of stems 1 ft (0.3 m) tall to 1 in (2.5 cm) dbh increased for 3 to 5 years after thinning and then leveled-off or decreased after 10 or 15 years. The greatest density of understory stems developed at low residual density. In stems 1 to 3 ft (0.3 to 0.9 m) tall, the densities of shade-tolerant species were unresponsive to thinning while the shade-intolerant were most responsive. The shade-intolerant and -intermediate species increased in importance over time in the more heavily thinned treatments. In the 3 ft (0.9 m) tall to 1 in (2.5 cm) dbh size class, shade-intolerant and -intermediate species were more responsive to thinning than tolerant species, but shade-tolerant species remained more important numerically throughout the study. Ingrowth to > 1 in diameter classes was greatest by shade-tolerant stems, increased over time, and was enhanced by thinning. We used repeated measures analysis of variance to model the number of stems in these three size classes and three shade-tolerance classes as a function of residual relative density at thinning and time since treatment. These models explained 0.08 to 0.80 of the variation in stem numbers, depending on the size and tolerance class. These descriptions might be improved by reference to prior conditions of the regeneration or interfering herbaceous competition, but a model that required this information would not be capable of predicting responses to future treatments.