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Landscapes Forest and Global Change - ESA - Escola Superior ...

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J. Russell et al. 2010. Developing models <strong>and</strong> processes to aid decision support for integrated l<strong>and</strong> management<br />

535<br />

Habitat supply models were developed for each of 17 species selected to evaluate the potential<br />

of the FM area to provide suitable habitat (Van Damme et al. 2003). The models define habitat<br />

suitability based on the provision of habitat elements required for survival <strong>and</strong> reproduction.<br />

Within the models, special habitat element models were developed to characterize changes in<br />

condition (i.e. abundance, density) of habitat elements through forest succession <strong>and</strong> disturbance.<br />

Specific (i.e. canopy closure, tree height), general (i.e. perches, hiding cover) <strong>and</strong> habitat uses<br />

(i.e. food) were included in the analysis. Habitat supply models projected suitability based on<br />

home range size for each species <strong>and</strong> were used to assess each forest harvest scenario at 5-year<br />

time steps. Additionally, the special habitat elements were analyzed within the habitat supply<br />

model to determine a subset of elements that were most critical for the 17 species. These were<br />

then associated with silvicultural practices, seral stages <strong>and</strong> dominant species groups <strong>and</strong><br />

embedded within the timber supply model as constraints.<br />

2.3 Water<br />

The <strong>Forest</strong> Watershed <strong>and</strong> Riparian Disturbance (FORWARD) project developed hydrologic<br />

models at two spatial scales (first- <strong>and</strong> third-order watershed) to predict how forest harvesting<br />

would change precipitation-normalized stream runoff at the watershed outlet (i.e. corrected for<br />

both watershed area <strong>and</strong> precipitation inputs). This variable, termed a runoff coefficient, was<br />

predicted for a given set of watershed attributes under forested conditions using a variant of the<br />

Soil <strong>and</strong> Water Assessment Tool (SWAT) (Arnold et al. 1998). The data to populate these<br />

runoff coefficient models were collected before <strong>and</strong> after experimental harvest from treatment<br />

<strong>and</strong> reference watersheds. Data included streamflow at a high temporal resolution, as well as<br />

improved digital elevation model, slope, soil <strong>and</strong> wetl<strong>and</strong> coverage, <strong>and</strong> watershed boundaries.<br />

SWAT simulations are still underway to compare measured to predicted runoff coefficients with<br />

time after harvest <strong>and</strong> to calibrate the model for future FM planning cycles (Watson et al. 2008).<br />

Water quality is being incorporated into SWAT modelling, as well as artificial neural network<br />

modelling (Nour et al. 2006). The FORWARD project established indicators <strong>and</strong> ranges of<br />

acceptability in changes in streamflow based upon changes in runoff coefficients (Prepas et al.<br />

2008). Thus, potential changes to streamflow could be given equal or varying weight as<br />

compared to other forest values during the development of a FM plan.<br />

3. Results <strong>and</strong> Discussion<br />

The structure of the FM planning analysis is hierarchical. The first task was to set the future<br />

l<strong>and</strong>base condition that included climate <strong>and</strong> vegetation change, human population change,<br />

wildfire response to these two conditions <strong>and</strong> oil <strong>and</strong> gas activities (Fig. 2). This produced a<br />

l<strong>and</strong>scape change outside the normal projection (i.e. these issues are not included in a st<strong>and</strong>ard<br />

timber supply model). These conditions act as forest l<strong>and</strong>base constraints: over the st<strong>and</strong>ard<br />

planning period of approximately 200 years these conditions enact significant changes in the<br />

forest l<strong>and</strong> base <strong>and</strong> forest growth patterns. This then produced future l<strong>and</strong> base series on which<br />

we could overlay a timber supply analysis. This analysis includes the constraints of biodiversity<br />

(BAP) <strong>and</strong> water (FORWARD) (Fig 2). This was conducted for multiple future scenarios at two<br />

basic levels of projection: multiple scenarios of each component part (e.g., different oil <strong>and</strong> gas<br />

scenarios could be incorporated into the model leaving all other components static) <strong>and</strong><br />

projections with various elements turned on or off, dependent upon what multiple effects needed<br />

to be focused upon for analysis. In this manner any number of iterations could be undertaken to<br />

arrive at an underst<strong>and</strong>ing of how each element affects the system at certain levels or how<br />

various combinations of elements can affect the system based on projected future scenarios.<br />

The system described above is a logical evolution from the st<strong>and</strong>ard timber supply analysis<br />

employed in much of Canada to a more holistic model concept that looks at all issues facing a<br />

forest state. It is critical to model elements of varying forest values outside of traditional<br />

<strong>Forest</strong> <strong>L<strong>and</strong>scapes</strong> <strong>and</strong> <strong>Global</strong> <strong>Change</strong>-New Frontiers in Management, Conservation <strong>and</strong> Restoration. Proceedings of the IUFRO L<strong>and</strong>scape Ecology<br />

Working Group International Conference, September 21-27, 2010, Bragança, Portugal. J.C. Azevedo, M. Feliciano, J. Castro & M.A. Pinto (eds.)<br />

2010, Instituto Politécnico de Bragança, Bragança, Portugal.

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