Remote sensing tools to improve species distribution models for birds in Alberta

Remote sensing tools to improve species distribution models for birds in Alberta

Evaluating the benefits of using finer-scale LiDAR-derived vegetation metrics in species distribution models

Project Summary

Brendan Casey (PhD Student with Erin Bayne at the University of Alberta) is evaluating the use of finer-scale LiDAR-derived vegetation metrics in species distribution models, compared to the more common remotely sensed forest attributes included in Forest Resource Inventories. He is also evaluating how the time lag between LiDAR acquisition and survey date effects model robustness for songbirds belonging to different forested habitat guilds. LiDAR metrics related to canopy closure, vegetation height, and vertical vegetation density, were combined with data from the Common Attribute Schema for Forest Resource Inventories (CASFRI) and wet areas mapping products to build preliminary species distribution models for Canada Warbler. 

Project Partners

This project is a collaboration with the Alberta Department of Agriculture and Forestry. For more information please contact us. 

Functional response models to quantify habitat selection

Explanatory models of differential habitat selection

Functional response models to quantify habitat selection while accounting for habitat availability in the surrounding region

© Benoît Audet

Project Summary

BAM is developing explanatory models of differential habitat selection (DHS) to better predict changes to bird populations in changing landscapes. These models account for the way differences in habitat availability and species density interact to affect population size and distribution, known as a functional response. In 2019-2020, we summarized habitat distribution at the landscape scale using the Common Attribute Schema for Forest Resource Inventories (CASFRI) database. CASFRI is a standardized compilation of spatially explicit forest resource inventory data from across Canada. We then developed preliminary functional response models that explain a portion of DHS in Black-throated Green Warbler. To accurately predict future distributions and population sizes in response to changing landscapes, it is essential that models account for the effect of habitat availability on the habitat selection process. These models show promise for making better density predictions outside the spatial and temporal bounds of the data to which they were fit.  The next step is to fully develop these models for integration with TARDIS, a forest landscape simulation model, to estimate the effects of different forest harvest strategies on bird populations at a national extent.

Contact us for more information about this project.

Differential habitat selection in boreal songbirds

Differential habitat selection in boreal songbirds influences estimates of population size and distribution

Evidence for differential habitat selection among regions for six boreal songbird species across Canada

Project Summary

Understanding habitat selection across a species range is an important step in estimating population size and distribution. BAM has undertaken efforts to test for and quantify differential habitat selection (DHS) in birds among regions of the Canadian boreal forest. In 2018-19, we developed models to test for differential selection of forest compositional and structural attributes among three boreal forest regions for six landbird species. We found strong evidence for DHS among regions for all six species. Species distribution models that did not account for DHS overestimated density. This work was published in October 2019 as a manuscript in Diversity & Distributions (Crosby et al. 2019).

For more information about this project please contact us

Publications

Crosby, A.D., Bayne, E.M., Cumming, S.G., Schmiegelow, F.K.A., Dénes, F.V., Tremblay, J.A., 2019. Differential habitat selection in boreal songbirds influences estimates of population size and distribution. Divers Distrib 25, 1941–1953. https://doi.org/10.1111/ddi.12991