Spatially-explicit habitat characterization and population-response modeling are important elements of conservation planning that inform efficient and effective on-the-ground conservation efforts. Habitat assessments determine the amount and configuration of habitat types across a landscape of conservation interest, while bird-habitat or bird population-response models quantify the relationship between habitat amount and configuration, and bird distribution and abundance. Used together, they help conservationists decide where on-the-ground conservation projects are most likely to result in a positive population response of target bird species, making conservation more effective and cost-efficient.

The choice of an assessment or modelling approach is affected by the availability and quality of information linking bird abundance with habitat quality, configuration, and quantity. Habitat Suitability Index (HSI) models, for example, can be more conceptual and based on hypothesized relationships formulated from the literature, empirical data, expert opinion, or some combination thereof. Statistical models are data-dependent, and the majority employ some form of statistical regression analysis to characterize and quantify the relationship between species and their habitats. Statistical models can be used to predict a population’s distribution and abundance across large landscapes and also to evaluate a population’s response to conservation efforts. For more on the pros and cons of statistical and habitat suitability index models, see a model comparison. HSI and statistical models used in conservation planning by the CHJV operate in a geographic information system (GIS) which enables us to generate maps from models. These “GIS Models” are preliminary explorations of bird-habitat relationships using a combination of existing spatial products and species occurrence data. Models designed to assess the effects of climate change on bird populations incorporate information derived from climate models as well as habitat and bird population attributes, and tend to be very complex.