Expecting and planning for adjustment: Using vegetation maps and climate data to model the distribution of novel bird habitat with climate change

Background/Question/Methods

Landscape predictions of suitable habitat for wildlife can be improved when fine-scale maps of existing vegetation are included as covariates in the models. The resulting models help inform managers by directing where to work and contribute to our understanding about how vegetation management can support wildlife conservation.

There are several challenges associated with using vegetation maps in habitat suitability models for wildlife. Fine scale maps of vegetation have often been generated using inconsistent vegetation classifications, limiting their usefulness in habitat suitability models for widely distributed species. Also, natural resource managers that use vegetation maps and models that incorporate them often demand the inclusion of fine vegetation classes that they directly manage. Wildlife habitat suitability models can be only be improved by including these fine scale vegetation types if all of the vegetation types have been surveyed for the fauna being modeled. Finally, with climate change we expect the composition of present-day plant communities to change, resulting in the emergence of novel associations of both plant species and wildlife that are difficult to model.

Thus a tension emerges for habitat suitability modelers: managers would like the models to incorporate very fine vegetation classes but data gaps and the challenges of dealing with novel species associations encourage models to use coarser vegetation classes. We demonstrate the use of different vegetation classifications for modeling the breeding distribution and abundance of birds across the western United States. We will highlight the choices made when using vegetation maps for modeling changes in bird distributions in response to climate change and demonstrate the value of using the uniform and hierarchical levels of natural vegetation classifications in the National Vegetation Classification (NVC).     

 Results/Conclusions

The uniform classification standards of the NVC facilitate the inclusion of vegetation data in habitat suitability models by providing a consistent classification across large spatial scales. Additionally, the NVC hierarchy allows modelers and managers to be flexible in selecting the finest level of vegetation classification that available data will support. Climate change will result in the formation of novel associations of species that will force habitat suitability models to extrapolate predictions into the future. However, the models can be used to develop hypotheses and guide future monitoring to support the adaptive management of the impacts to wildlife from changing environmental conditions. The monitoring can then support the update of the NVC and resulting suitability models to perpetuate the adaptive management cycle.