Indicators of biodiversity have been proposed as a potential tool for selecting areas for conservation when information about species distributions is scarce. Although tests of the concept have produced varied results, sites selected to address indicator groups can include a high proportion of other species. We tested the hypothesis that species at risk of extinction are not likely to be included in sites selected to protect indicator groups. Using a reserve-selection approach, we compared the ability of seven indicator groups-freshwater fish, birds, mammals, freshwater mussels, reptiles, amphibians, and at-risk species of those six taxa-to provide protection for other species in general and at-risk species in particular in the Middle Atlantic region of the United States. Although sites selected with single taxonomic indicator groups provided protection for between 61% and 82% of all other species, no taxonomic group provided protection for more than 58% of all other at-risk species. The failure to cover at-risk species is likely linked to their rarity. By examining the relationship between a species' probability of coverage by each indicator group and the extent of its geographic range within the study area, we found that species with more restricted ranges were less likely to be protected than more widespread species. Furthermore, we found that although sites selected with indicator groups composed primarily of terrestrial species (birds and mammals) included relatively high percentages of those species (82-85%) they included smaller percentages of strictly aquatic species (27-55%). Finally, of both importance and possible utility, we found that at-risk species themselves performed well as an indicator group, covering an average of 84% of all other species. §

We examined the impacts of possible future land development patterns on the biodiversity of a landscape. Our landscape data included a remote sensing derived map of the current habitat of the study area and six maps of future habitat distributions resulting from different land development scenarios. Our species data included lists of all bird, mammal, reptile, and amphibian species in the study area, their habitat associations, and area requirements for each. We estimated the area requirements using home ranges, sampled population densities, or genetic area requirements that incorporate dispersal distances. Our measures of biodiversity were species richness and habitat abundance. We calculated habitat abundance in two ways. First, we computed the total habitat area for each species in each landscape. Second, we calculated the number of habitat units for each species in each landscape by dividing the size of each habitat patch in the landscape by the area requirement and summing over all patches. Species richness was based on presence of habitat. Species became extinct in the landscape if they had no habitat area or no habitat units, respectively. We then computed ratios of habitat abundance in each future landscape to habitat abundance in the present for each species. We also computed the ratio of future to present species richness. We then calculated summary statistics across all species. Species richness changed little from present to future. There were distinctly greater risks to habitat abundance in landscapes that extrapolated from present trends or zoning patterns, however, as opposed to landscapes in which land development activities followed more constrained patterns. These results were stable when tested using Monte Carlo simulations and sensitivity tests on the area requirements. We conclude that this methodology can begin to discriminate the effects of potential changes in land development on vertebrate biodiversity.

The contributions of current agricultural practices to environmental degradation and the social problems facing agricultural regions are well known. However, landscape-scale alternatives to current trends have not been fully explored nor their potential impacts quantified. To address this research need, our interdisciplinary team designed three alternative future scenarios for two watersheds in Iowa, USA, and used spatially-explicit models to evaluate the potential consequences of changes in farmland management. This paper summarizes and integrates the results of this interdisciplinary research project into an assessment of the designed alternatives intended to improve our understanding of landscape ecology in agricultural ecosystems and to inform agricultural policy. Scenario futures were digitized into a Geographic Information System ͑GIS͒, visualized with maps and simulated images, and evaluated for multiple endpoints to assess impacts of land use change on water quality, social and economic goals, and native flora and fauna. The Biodiversity scenario, targeting restoration of indigenous biodiversity, ranked higher than the current landscape for all endpoints ͑biodiversity, water quality, farmer preference, and profitability͒. The Biodiversity scenario ranked higher than the Production scenario ͑which focused on profitable agricultural production͒ in all endpoints but profitability, for which the two scenarios scored similarly, and also ranked higher than the Water Quality scenario in all endpoints except water quality. The Water Quality scenario, which targeted improvement in water quality, ranked highest of all landscapes in potential water quality and higher than the current landscape and the Production scenario in all but profitability. Our results indicate that innovative agricultural practices targeting environmental improvements may be acceptable to farmers and could substantially reduce the environmental impacts of agriculture in this region.

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