Strategic land use planning beyond the scale of individual projects must integrate diverse human activities and ecological interactions at a variety of space and time scales. Individual land use decisions made today often do not display their full ecological effects until some years later. This in effect, leads to a decoupling of the two processes with the result being the “cumulative effects” problem whereby small incremental activities lead to slow but steady deterioration of ecological condition and function. The slow but steady expansion of deer, coyotes, and cowbirds through human-created habitat change is one possible example. In order to reduce the likelihood of this happening we need to assess the long-term implications of individual land use decisions by integrating and projecting them over ecologically meaningful space and time (long time and broad spatial scales). This is only possible through some form of simulation modeling. Building on concepts pioneered by C.S. Holling and with the advent of extensive databases in GIS format, there have been exciting advances in land use and resource planning model development. Forest landscape models, Integrated Assessment, Alternative Futures Analysis, and the Integrated Landscape Management Models Policy Research Initiative are models and approaches designed to assist in the land use planning arena. These tools explore, to varying degrees, the economic, ecological, and social implications of strategic land use decisions.
The basic logic of the ecological component of these models is similar. They begin with a current landscape condition as defined by spatially explicit vegetation and land use GIS layers. This “current condition” is then modified according to change rules that might be driven by natural disturbances, vegetation succession, and human activities (examples include LANDIS, SELES, PATCHWORKS, TELSA, FORECAST). The changes in habitats can then be linked to wildlife species through habitat association, resource selection functions or spatially explicit population viability analysis. These sorts of models have their roots in forest growth and harvest planning. Others focus on watershed planning or agricultural systems. The development and use of these sorts of models is fundamental to the land use planning exercise. Among other things they serve to focus attention on important relationships and key uncertainties, allow stakeholders to explore creative scenarios and foster learning.
During the first term of the ILM Chair, the primary modeling platform used to organize ecological knowledge, simulate alternative land use scenarios, and represent the ecological effects of multiple land uses, was ALCES (A Landscape Cumulative Effects Simulator). For example we explored the implications of a growing energy, forestry, and agricultural sector in northeastern Alberta. ALCES is a spatially stratified model that generates graphic output (figures, tables) on a series of economic, social, and environmental indicators for each “what-if” development scenario. Its strength as a strategic-level tool lies in its ability to simulate the effects of multiple natural and anthropogenic disturbances on environmental and economic indicators over large regions and long time periods. Disturbances simulated include forestry, oil and gas development, mining, agriculture, human settlements, transportation networks, fire, and insect outbreaks. The model also has the capability of projecting human activities and landscape change under various climate change scenarios. ALCES has enjoyed significant funding support from the Government of Canada, Government of Alberta and industrial sectors during its development. It is now being extensively deployed on regional landscape assessments throughout Alberta, Yukon, Northwest Territories, and Alaska.
The use and sophistication of ALCES has grown considerably over Phase I of the Chair. The ILM lab has supplied important empirical relationships, added relevant ecosystem indicators, beta-tested new versions of the model, revealed and resolved key uncertainties, and explored new management scenarios. ALCES has been parameterized for various regions of Alberta as well as for the entire province. The model has been used to run numerous best practices scenarios and as part of caribou range planning exercises. Model results have been presented at a wide range of forums and this has served to educate stakeholders as to what they can expect their future to look like given the level of planned development in Alberta.
Proposed research: In Phase II we wish to focus on the use of ILMMs to explore alternative scenarios that might provide viable alternatives to better manage future risks to economic and ecological sustainability. We will develop and apply ILMMs at three spatial scales ranging from Forest Management Areas (up to 50,000 km2), to regional plans (100,000 km2) to province-wide strategies. At the smallest scale, we will apply modeling approaches to improve the linkages between operational and strategic land use planning. Recent examples in the forestry and oil and gas sectors in Alberta have demonstrated that long-term ecological and economic outcomes can be improved by coordinating activities such as road construction. While these examples are encouraging, most operational and strategic planning done by the forestry and other sectors in the boreal do not consider other sectors in a meaningful way. We will apply ILMMs in a series of case studies to explore the constraints behind more effective planning, and develop approaches that accelerate progress towards true integration.
At the regional scale, we will explore land use zoning scenarios that have historically not been considered in detail by the multi-stakeholder consultation processes frequently used to try and balance competing resource objectives. All provinces and territories apply some form of zoning, but most of Canada’s boreal is covered by land use zones in which managers attempt to accommodate multiple land uses simultaneously. Outcomes of this “try-to-please-everyone” approach include negative cumulative ecological effects and frequent conflicts among land uses. We see an opportunity to use ILMMs to help stakeholders more clearly understand what is being lost by this approach, and to demonstrate how approaches that may seem “radical” could, in fact, produce better outcomes than the status quo. Ultimately, we plan to combine regional strategies into a province-wide scenario analysis. In essence, this is a quest for workable solutions at province-wide scales that are not feasible at regional or smaller scales. We will use ALCES to look for combinations of regional solutions that could be implemented over the entire province of Alberta.
Finally, we need to link our studies of key uncertainties back to the modeling work. We will do this by incorporation both woodland caribou and forest birds into ILMM models and scenarios. The emphasis in this case will be on exploring how the different causes and the spatial scales over which they operate, affect model structure and outcomes.
We have and continue to use a multi-faceted approach to developing ILMMs. ALCES, which removes a lot of the inherent complexity through spatial stratification, is an excellent tool for rapidly assessing alternative policies with respect to a variety of indicators under strong simplifying assumptions. Even so, ALCES is able to provide valuable guidance for ranking which policies should be explored using more complex and computationally demanding simulation models. This interplay between modeling approaches of differing complexity provides key insights into when simple or more complex ILMMs are needed to assess alternative policy options. The ILMM projects will be organized and directed by a modeling team consisting of Research Associates and graduate students. The intention is to provide the graduate student with hands-on training in ILMM development and application that becomes the basis for addressing new questions formulated in their thesis.