Projecting Wildlife Responses to Alternative Future Landscapes in Oregon's Willamette Basin

Abstract

Increasingly, environmental quality is becoming recognized as a critical factor that should constrain land use planning. One important measure of a landscape's quality is its capacity to support viable populations of wildlife species. But the ability of land managers to balance conservation with other competing objectives is limited by a shortage of methodologies for assessing landscape quality. In response to this shortage, the research community has begun developing a variety of multispecies, landscape‐level, assessment models. Useful models must strike a balance between parsimony and biological realism and must be designed to make the most of limited life history data. This paper applies two such assessments to an examination of wildlife responses to scenarios of landscape change within Oregon's Willamette River Basin. The study uses GIS maps of pre‐European settlement and circa 1990 habitat conditions, and three possible realizations of how the Basin might appear in the year 2050. Our simpler assessment generated statistics of landscape change from the GIS imagery and species–habitat relationships for all 279 amphibian, reptile, bird, and mammal species in the basin. Our more complex assessment used an individual‐based life history simulator to estimate population sizes for a small subset of this fauna. These two assessments offer complementary kinds of information about wildlife responses to landscape change: estimates of habitat changes for a large number of species representing a region's biodiversity, and estimates of changes in the persistence of populations of key species. We found both good and poor correlations between our two assessments, depending upon the species and landscape. Both assessments agreed in their overall ranking of the landscapes' quality for wildlife. In most cases, the percentage change in habitat quality underestimated the percentage change in population size. In a few cases, small gains in habitat quality were accompanied by very large increases in wildlife populations. We attribute discrepancies in our two assessments to the influence habitat fragmentation had on our individual‐based model. As such, our study provides a methodology for separating the influences of habitat quality and quantity from those of habitat pattern.

Emerging Opportunities for Landscape Ecological Modelling

“…They have been used to address questions at a range of spatial and temporal scales varying from models of home range dynamics and daily movements [200,201] to multi-decadal models of species range shifting [19]. IBMs have also been used extensively to study landscape connectivity: identifying threats to populations [202] and testing the impacts of future scenarios [203,204]. Notably a stochastic IBM approach has recently been demonstrated to provide better estimates of inter-patch connectivity (in terms of correlation with genetic estimates) than least-cost path and circuit theory approaches [205].…”

The role of ecological models in linking ecological risk assessment to ecosystem services in agroecosystems

“…Nalle et al (2004) developed a simpler spatially explicit model for finding cost-effective strategies in timber production and endangered species conservation in a forested landscape. The ecological model here is based on the PATCH model (Schumaker et al, 2004) and consists of a matrix model for the great horned owl, Bubo virginianus, and the great porcupine, Erethizon dorsatum that includes life-history parameters such as survival and reproduction rates. Dispersal of individuals is modeled with maximum dispersal distances in a stochastic search procedure.…”

Environmental screening tools for assessment of infrastructure plans based on biodiversity preservation and global warming (PEIT, Spain)

“…The criteria applied in this evaluation matrix were the optimization of the máximum protection of the pixels in the territory (1 ha) with the greatest biodiversity and environmental quality and the lowest incidence in Spanish territory; as opposed to the lower protection of the pixels with less biodiversity and environmental quality and greater frequency. These criteria are connected to those of Treweek et al (1998), Brown (2003) and Schumaker et al (2004). This evaluation matrix allowed us to propose as a final result four potential impact classes of the PEIT 2000-2007 on biodiversity and environment (1 = compatible; 2 = modérate; 3 = severe; 4 = critical) (Table 4) within these 12-km bands.…”

“…Treweek et al (1998) indícate that infrastructure developments, when considered collectively, can be compatible with safeguarding important and protected wildlife habitats and their associated protected species. Norris and Farrar (2001), Brown (2003) and Schumaker et al (2004) indícate that environmental quality is becoming recognized as a critical factor that should constrain land-use planning, and they also recommend that specialists should adopt approaches in which environmental quality information assists those involved in the development plans.…”