TELSA: the Tool for Exploratory Landscape Scenario Analyses

The Tool for Exploratory Landscape Scenario Analyses (TELSA) is a spatially explicit model of vegetation succession, natural disturbances, and forest management activities. TELSA is a strategic planning tool designed to support adaptive management by projecting the consequences of alternative scenarios at the scale of landscape units (i.e. 10000¯200000 ha) over time frames of decades to centuries. Scenario combine user-specified assumptions about natural disturbances and management activities, and can include `no actionʹ or historic disturbance scenarios. The simulation model is at the core of a set of tools that also includes a geographic information system, databases, and several user interfaces for scenario definition, data analysis, spatial analysis and the display of results. Spatial characteristics of landscapes, such as fragmentation, patch-size distribution and connectivity are largely determined by management actions and their interaction with natural disturbances. The TELSA toolbox includes a tool for the automated design of management units (i.e. harvest cutblocks), based on user-defined criteria and scenario objectives. TELSA easily evaluates strategic alternatives regarding the size range of management units, their spatial aggregation, the use of adjacency constraints, and the application of different silvicultural systems. TELSA represents vegetation succession as changes in species composition and structural stages of stands, thus projecting landscape conditions in a format that is relevant for the analysis of wildlife habitat and many other resource indicators. Succession pathway diagrams define the transition times between successional classes and, for each class, the probabilities and impacts of disturbance by insects, fire or other agents. These diagrams also define the impacts of management actions on stand structure and vegetation composition. Diagrams can be defined for forests and other vegetation types such as shrub and rangelands. Wildfires and other natural disturbance events that affect vegetation dynamics are inherently unpredictable. The model can use multiple stochastic simulations of each scenario to provide estimates of the mean, range and variability of selected performance indicators.