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Abstract. As one samples species from a particular landscapes which retained a greater proportion of natural habitats (r=−0.64, P<0.001). This finding supports assemblage, the initial rapid rate with which new species are predictions of ecosystem behavior under human land use. encountered declines with increasing effort. Nine candidate There was no evidence that intermediate levels of land models to characterize species-accumulation functions were use intensity maximized accumulation rates. The approach compared in a search for a model that consistently fit reviewed in this paper makes no assumptions about the geographically extensive avian survey data from a wide form of the species-abundance distribution or how species range of environmental conditions. Landscape-specific are distributed in space, thereby offering some advantages species-accumulation curves generated under a bootstrap over more conventional diversity indices for characterizing resampling plan were best described by a generalized Weibull how species assemblages respond to anthropogenic cumulative distribution function. Traditional species-area disturbance. Investigation of how species accumulation models of cumulative species richness as a function of varies over time in a given geographic area is needed to accumulated sample had notable functional bias. The evaluate fully the potential application of this approach to Weibull model fitted species-accumulation data equally well regional land use planning. among sixty-six forested landscapes in the eastern U.S. Landscapes with a greater proportion of agricultural and

The hypothesis that Neotropical migrant birds may be undergoing widespread declines due to land use activities on the breeding grounds has been examined primarily by synthesizing results from local studies. Growing concern for the cumulative influence of land use activities on ecological systems has heightened the need for largescale studies to complement what has been observed at local scales. We investigated possible landscape effects on Neotropical migrant bird populations for the eastern United States by linking two large-scale inventories designed to monitor breeding-bird abundances and land use patterns. The null hypothesis of no relation between landscape structure and Neotropical migrant abundance was tested by correlating measures of landscape structure with bird abundance, while controlling for the geographic distance among samples.Neotropical migrants as a group were more "sensitive" to landscape structure than either temperate migrants or permanent residents. Neotropical migrants tended to be more abundant in landscapes with a greater proportion of forest and wetland habitats, fewer edge habitats, larger forest patches, and with forest habitats well dispersed throughout the scene. Permanent residents showed few correlations with landscape structure and temperate migrants were associated with habitat diversity and edge attributes rather than with the amount, size, and dispersion of forest habitats. The association between Neotropical migrant abundance and forest fragmentation differed among physiographic strata, suggesting that landscape context affects observed relations between bird abundance and landscape structure. Finally, associations between landscape structure and temporal trends in Neotropical migrant abundance were counter to those observed in space. Trends in Neotropical migrant abundance were negatively correlated with forest habitats. These results suggest that extrapolation of patterns observed in some landscapes is not likely to hold regionally, and that conservation policies must consider the variation in landscape structure associations observed among different types of bird species and in physiographic strata with varying land use histories.

We simulated the effects of missing information on statistical distributions of animal response that covaried with measured predictors of habitat to evaluate the utility and performance of quantile regression for providing more useful intervals of uncertainty in habitat relationships. These procedures were evaulated for conditions in which heterogeneity and hidden bias were induced by confounding with missing variables associated with other improtant processes, a problem common in statistical modeling of ecological phenomena. Simulations for a large (N ϭ 10 000) finite population representing grid locations on a landscape demonstrated various forms of hidden bias that might occur when the effect of a measured habitat variable on some animal was confounded with the effect of another unmeasured variable. Quantile (0 Յ Յ 1) regression parameters for linear models that excluded the important, unmeasured variable revealed bias relative to parameters from the generating model. Depending on whether interactions of the measured and unmeasured variables were negative (interference interactions) or positive (facilitation interactions) in simulations without spatial structuring, either upper ( Ͼ 0.5) or lower ( Ͻ 0.5) quantile regression parameters were less biased than mean rate parameters. Heterogeneous, nonlinear response patterns occurred with correlations between the measured and unmeasured variables. When the unmeasured variable was spatially structured, variation in parameters across quantiles associated with heterogeneous effects of the habitat variable was reduced by modeling the spatial trend surface as a cubic polynomial of location coordinates, but substantial hidden bias remained. Sampling (n ϭ 20-300) simulations demonstrated that regression quantile estimates and confidence intervals constructed by inverting weighted rank score tests provided valid coverage of these parameters. Local forms of quantile weighting were required for obtaining correct Type I error rates and confidence interval coverage. Quantile regression was used to estimate effects of physical habitat resources on a bivalve (Macomona liliana) in the spatially structured landscape on a sandflat in a New Zealand harbor. Confidence intervals around predicted 0.10 and 0.90 quantiles were used to estimate sampling intervals containing 80% of the variation in densities in relation to bed elevation. Spatially structured variation in bivalve counts estimated by a cubic polynomial trend surface remained after accounting for the nonlinear effects of bed elevation, indicating the existence of important spatially structured processes that were not adequately represented by the measured habitat variables.