Invasive Species Compendium

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Abstract

Landscape modeling of the potential natural vegetation of Santa Catalina Island, California.

Abstract

The vegetation of Santa Catalina Island has been significantly transformed through a history of introduction of exotic plant species and disturbance by large introduced herbivores. Many of these disturbances have been reduced in recent decades, using measures such as carefully controlling the number of bison and removing cattle, sheep, feral pigs, and goats. The success of subsequent vegetation restoration actions depends on the choice of the right plant community for a location, which may not be obvious for an island with extensive areas dominated by exotic species. Environmental niche modeling is an approach to re-create the spatial distribution of habitat types for such a purpose. Such models, however, often require both presence and absence data to be meaningful, while in this scenario absence is misleading because it may reflect a long history of disturbance. Maximum entropy modeling is a technique to model species distributions with presence-only data that has been shown to produce accurate results. We used this modeling tool to model the environmental niche for distinct vegetation types, conceptualized as potential natural vegetation, on Catalina Island as a means to predict locations where restoration actions would be most successful and to predict potential natural vegetation prior to anthropogenic disturbance. Using an existing vegetation map, we extracted random points from within the polygons defining each native vegetation type. We then modeled the habitat suitability for each habitat using high-resolution environmental data that included elevation, aspect, hillshade, northeastness, slope, solar radiation, and topographic wetness index. The resulting models were combined to produce a map of potential natural vegetation. A 1977 map of potential natural vegetation included 4 vegetation types (woodland, chaparral, scrub, and grassland) to which we compared our results. Our new model of potential natural vegetation has high spatial complexity and high resolution. It also shows naturalistic responses to topography that are consistent with the broad patterns mapped in 1977 while providing fine-scale resolution to inform restoration efforts.