To evaluate this we developed predictive habitat suitability models.
Habitat suitability models were evaluated using data from 7 years of breeding site surveys.
The habitat suitability models for individual animals have the form of classification trees.
Various habitat suitability models based on expert knowledge have been used to evaluate the suitability of spawning habitat.
Habitat suitability models are thus theoretical concepts that can be used for planning in fragmented landscapes and habitat conservation.
Examples of correlative habitat suitability models include BRT (Boosted Regression Tree), MaxEnt (Maximum Entropy), and CART (Classification and Regression Tree) models, which rely on occurrence data.
Focal species, selected by an expert-based approach, provide a practical way of extending the scope of habitat suitability models to the conservation of biodiversity at landscape scale.
The two final habitat suitability models explained the observed presence absence pattern moderately well (AUC of 0.71 and 0.77) with horizontal structure explaining better than vertical structure.
Assessments of habitat connectivity are typically based on the output of habitat suitability models to first map potential habitat, and then identify where corridors exist.
Spatially explicit suitability models based on these data allowed us to predict the status quo of hedge suitability for these species groups.
Here, we propose a hybrid approach based on network analysis tools and empirical habitat suitability models to integrate connectivity on decision-making.
