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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 />

534<br />

across space <strong>and</strong> time. To monitor changes in the composition of the forecasts, BAP tracks the<br />

proportion of habitat types <strong>and</strong> diversity of the forest using the following metrics. 1) Areaweighted<br />

age is a single value at each time step during the simulation, indicating the average<br />

age of the entire forest. 2) Tree species distribution separates the forest into hardwood st<strong>and</strong>s,<br />

hardwood-dominated mixedwood st<strong>and</strong>s, softwood st<strong>and</strong>s <strong>and</strong> softwood-dominated mixedwood<br />

st<strong>and</strong>s. It provides an indication of the proportion of the FM area expected to support each<br />

habitat type at each time step. 3) Species presence indicates the extent of coverage of each tree<br />

species over the l<strong>and</strong>scape. 4) Species dominance takes into account both tree species presence<br />

<strong>and</strong> relative dominance. 5) Habitat diversity was computed using a matrix showing similarity<br />

between habitat types as a weighting factor. The habitat diversity index considers the relative<br />

position of broad habitat types using a rating of similarity between the habitat types as a<br />

weighting factor. The diversity equation generates a single unitless value between 0 <strong>and</strong> 1 at<br />

each time step; 0 represents a very uniform l<strong>and</strong>scape <strong>and</strong> 1 indicates the most diverse<br />

l<strong>and</strong>scape possible. Incorporated into the index are both the number of habitat types present<br />

within the FM area <strong>and</strong> the proportion of the l<strong>and</strong>scape covered by each habitat type.<br />

<strong>L<strong>and</strong>scapes</strong> containing many habitat types distributed evenly across the area are considered<br />

more diverse than those dominated by one habitat type, yet containing small portions of others.<br />

Within the l<strong>and</strong>scape configuration analysis, habitat types were used as class attributes because<br />

they can be weighted by contrast. As well, different levels of distinction among habitats can be<br />

used following the classification hierarchy. The l<strong>and</strong>scape configuration analysis was comprised<br />

of several types of biostatistical analyses:<br />

• Patch – areas of similar characteristics based on age <strong>and</strong> species composition.<br />

• Edge – mean edge contrast index <strong>and</strong> contrast weighted edge length.<br />

• Core area – The impact of edge on wildlife was expected to be linearly related to the<br />

abruptness of the habitat structure change at the edge <strong>and</strong> therefore the buffer width would<br />

change with contrast between adjacent habitat patches.<br />

• Adjacency – It was expected that the spatial distribution of habitat types would differ in a<br />

managed scenario relative to a natural scenario. Consequently the proportion of adjacencies<br />

might be different. Many species use a combination of different habitats to fulfill their<br />

needs; therefore the adjacency of these habitats is important.<br />

• Nearest neighbor – It was understood that a population using an isolated habitat is highly<br />

prone to local extinction. In addition, an organism using dispersed habitat patches may not<br />

be able to defend a sufficiently large territory from which to extract its needed resources.<br />

The nearest neighbor metric gives an indication of the dispersion of similar habitat types.<br />

Fine filter analysis was undertaken by developing species-specific habitat supply models. It was<br />

recognized that the species selected would comprise an imperfect representation of the large<br />

array of species that occupy the FM area. The selection process was based on the following<br />

premises. 1) It is not possible to create models for all species. 2) Coarse filter analysis can<br />

account for habitat requirements for many species. 3) Models created for a carefully selected list<br />

of species will adequately represent the habitat needs of many other species. 4) Terrestrial<br />

vertebrates will be selected because: they use a large range of forest features; are good<br />

indicators of change; are the subjects of concern by the public <strong>and</strong>; approaches for analyzing<br />

forests in terms of vertebrate habitat potential are relatively well developed. Species were<br />

selected that represented the following classes: large terrestrial carnivorous mammals, large<br />

ungulates, medium-sized herbivores/omnivorous mammals, medium-sized carnivorous<br />

mammals, small mammals, raptors, birds in the order Gallinaceae <strong>and</strong> passerines (perching<br />

birds). The following criteria were used, with the numbers relating to the weighting scheme for<br />

each element: sensitivity to disturbance – 4; species status – 3; ability to monitor the species – 3;<br />

habitat specificity – 2; special habitat elements – 2; functionally essential species – 2; l<strong>and</strong>scape<br />

configuration – 2; socioeconomic value – 2 <strong>and</strong>; available information – 1.<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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