Source‐Sink Models and the Problem of Habitat Degradation: General Models and Applications to the Yellowstone Grizzly

• Published in: Conservation Biology
• Main Author: Doak, Daniel F.
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 1995
• Subjects: Ursus arctos
• Online Access: https://doi.org/10.1046/j.1523-1739.1995.09061370.x; https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1046%2Fj.1523-1739.1995.09061370.x; http://onlinelibrary.wiley.com/wol1/doi/10.1046/j.1523-1739.1995.09061370.x/fullpdf

I used source‐sink population models to explore the consequences of habitat degradation for populations living on good and degraded habitats linked by movement. In particular, I modeled the conversion of land from good habitat quality supporting positive population growth to a degraded condition in which there was population decline. I found that with high rates of movement between good and bad quality areas populations require relatively large amounts of good habitat to remain stable. However, low movement rates resulted in greater sensitivity of population growth to habitat loss. Even small amounts of habitat degradation could result in rapid changes in overall population growth rates depending upon the rates of population increase and decline in the two habitat types. I also developed and simulated an age‐structured model for grizzly bears ( Ursus arctos horribilis ) existing in good and degraded habitats and fit this model to data from the Yellowstone grizzly population. I used this model to predict the ability to detect crucial amounts of habitat degradation from census data and found that when degradation is slow (e.g., 1% conversion of good to poor habitat per year), more than a decade may pass between crucial amounts of degradation—beyond which populations begin long‐term decline—and its detection, even if census data were unrealistically good. Thus these simple models indicate that, at least in some circumstances, habitat degradation can have rapid and severe impacts on population dynamics and traditional monitoring programs may not be adequate to detect the consequences of degradation.