Using Ecological‐Niche Modeling to Predict Barred Owl Invasions with Implications for Spotted Owl Conservation

Abstract

The Spotted Owl ( Strix occidentalis ) is the focus of intense concern as a species threatened by the destruction and fragmentation of primary forest in the Pacific Northwest ( U.S.A. ). Aside from habitat concerns, an additional peril exists for the species: the larger and more aggressive Barred Owl ( S. varia ) is invading the Pacific Northwest and has the potential to overrun much of the range of the endangered species. We evaluated the dimensions of this potential invasion by using ecological niche models based on point‐occurrence data. With these tools, we developed models with significant predictions for the native distributions of both Spotted and Barred owls ( tested via independent occurrence data ) and for the invasive range of Barred Owls. Overlap between the models for the two species suggests that most of the northern portion of the Spotted Owl's distribution ( south to about lat. 38°N ) is vulnerable to Barred Owl invasion. We present an example of the potential effects of species invasions on endangered species conservation.

Uses and Requirements of Ecological Niche Models and Related Distributional Models

“…Finally, additional evidence comes from studies of invasive species, in which species are transplanted to a distinct geographic and community context. Although it has been suggested based on theoretical musing and limited laboratory experiments that shifting species' interactions would confound any possible predictivity (in this case in the context of anticipating climate change effects on species' distributions) (Davis et al 1998), numerous studies have successfully predicted the invasive distributional potential of species based on native-range ecological characteristics (Beerling et al 1995;Higgins et al 1999;Honig et al 1992;Iguchi et al 2004;Panetta and Dodd 1987;Papes and Peterson 2003;Peterson 2003a;Peterson et al 2003a;Peterson and Robins 2003;Peterson et al 2003b;Peterson and Vieglais 2001;Richardson and McMahon 1992;Scott and Panetta 1993;Skov 2000;Sutherst et al 1999;Zalba et al 2000).…”

“…Here, the idea is that-given apparently widespread evolutionary conservatism in ecological niche characteristics-species will often 'obey' the same set of ecological rules on invaded distributional areas as they do on their native distributional areas. As such, the geographic potential of invasive species is often quite predictable, based on their geographic and ecological distributions on their native distributional areas (Beerling et al 1995;Higgins et al 1999;Hinojosa-Díaz et al 2005;Hoffmann 2001;Honig et al 1992;Iguchi et al 2004;Panetta and Dodd 1987;Papes and Peterson 2003;Peterson 2003a;Peterson et al 2003a;Peterson and Robins 2003;Peterson et al 2003b;Peterson and Vieglais 2001;Podger et al 1990;Richardson and McMahon 1992;Robertson et al 2004;Sindel and Michael 1992;Skov 2000;Sutherst et al 1999;Welk et al 2002;Zalba et al 2000), although the factors that make a species invasive are clearly more complex than just niche considerations ).…”

Lizard species richness patterns in China and its environmental associations

“…The map used an Albers Equal-Area Conic projection (at the standard parallels of 25°and 47°of N, central meridian of 105°). The solid lines identify the biogeographical limits of Zhang (1999) used in our analyses and GARP is a very useful technique to estimate richness and composition of unsampled areas and have been tested to correctly predict the most of the species' distributional potential (Pearson et al 2007, for example in applications to invasive species (e.g., Peterson and Robins 2003), tree species (e.g., Ferreira de Siqueira et al 2009;Menon et al 2010), squamate species (e.g., Raxworthy et al 2003;Costa et al 2007;Peterson et al 2007), and so on.…”

The Relative Importance of Biotic and Abiotic Controls on Young Conifer Growth After Fire in the Klamath-Siskiyou Region

“…Rule-based methods (including GARP, Genetic Algorithm for Rule-set Prediction; Peterson 2001, Peterson et al 2002, Peterson & Robins 2003Scachetti-Pereira 2002) seek combinations of habitatbased rules to optimize prediction of species presence-absence. These methods can also incorporate traditional statistical models, such as logistic regression.…”