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The Endangered Species Act (ESA) has succeeded in shielding hundreds of species from extinction and improving species recovery over time. However, recovery for most species officially protected by the ESA - i.e., listed species-has been harder to achieve than initially envisioned. Threats to species are persistent and pervasive, funding has been insufficient, the distribution of money among listed species is highly uneven, and at least 10 times more species than are actually listed probably qualify for listing. Moreover, many listed species will require ongoing management for the foreseeable future to protect them from persistent threats. Climate change will exacerbate this problem and increase both species risk and management uncertainty, requiring more intensive and controversial management strategies to prevent species from going extinct.

High numbers of threatened species might be expected to occur where overall species richness is also high; however, this explains only a proportion of the global variation in threatened species richness. Understanding why many areas have more or fewer threatened species than would be expected given their species richness, and whether that is consistent across taxa, is essential for identifying global conservation priorities. Here, we show that, after controlling for species richness, environmental factors, such as temperature and insularity, are typically more important than human impacts for explaining spatial variation in global threatened species richness. Human impacts, nevertheless, have an important role, with relationships varying between vertebrate groups and zoogeographic regions. Understanding this variation provides a framework for establishing global conservation priorities, identifying those regions where species are inherently more vulnerable to the effects of threatening human processes, and forecasting how threatened species might be distributed in a changing world.

Public lands provide many ecosystem services and support diverse plant and animal communities. In order to provide these benefits in the future, land managers and policy makers need information about future climate change and its potential effects. In particular, weather extremes are key drivers of wildfires, droughts, and false springs, which in turn can have large impacts on ecosystems. However, information on future changes in weather extremes on public lands is lacking. Our goal was to compare historical (1950-2005) and projected mid-century (2041-2070) changes in weather extremes (fire weather, spring droughts, and false springs) on public lands. This case study looked at the lands managed by the U.S. Forest Service across the conterminous United States including 501 ranger district units. We analyzed downscaled projections of daily records from 19 Coupled Model Intercomparison Project 5 General Circulation Models for two climate scenarios, with either medium-low or high CO 2 - equivalent concentration (RCPs 4.5 and 8.5). For each ranger district, we estimated: (1) fire potential, using the Keetch-Byram Drought Index; (2) frequency of spring droughts, using the Standardized Precipitation Index; and (3) frequency of false springs, using the extended Spring Indices. We found that future climates could substantially alter weather conditions across Forest Service lands. Under the two climate scenarios, increases in wildfire potential, spring droughts, and false springs were projected in 32-72%, 28-29%, and 13-16% of all ranger districts, respectively. Moreover, a substantial number of ranger districts (17-30%), especially in the Southwestern, Pacific Southwest, and Rocky Mountain regions, were projected to see increases in more than one type of weather extreme, which may require special management attention. We suggest that future changes in weather extremes could threaten the ability of public lands to provide ecosystem services and ecological benefits to society. Overall, our results highlight the value of spatially-explicit weather projections to assess future changes in key weather extremes for land managers and policy makers., (© 2019 by the Ecological Society of America.)

The concept of ecological integrity has been applied widely to management of aquatic systems, but still is considered by many to be too vague and difficult to quantify to be useful for managing terrestrial systems, particularly across broad areas. Extensive public lands in the western United States are managed for diverse uses such as timber harvest, livestock grazing, energy development, and wildlife conservation, some of which may degrade ecological integrity. We propose a method for assessing ecological integrity on multiple-use lands that identifies the components of integrity and levels in the ecological hierarchy where the assessment will focus, and considers existing policies and management objectives. Both natural reference and societally desired environmental conditions are relevant comparison points. We applied the method to evaluate the ecological integrity of shrublands in Nevada, yielding an assessment based on six indicators of ecosystem structure, function, and composition, including resource- and stressor-based indicators measured at multiple scales. Results varied spatially and among indicators. Invasive plant cover and surface development were highest in shrublands in northwest and southeast Nevada. Departure from reference conditions of shrubland area, composition, patch size, and connectivity was highest in central and northern Nevada. Results may inform efforts to control invasive species and restore shrublands on federal lands in Nevada. We suggest that ecological integrity assessments for multiple-use lands be grounded in existing policies and monitoring programs, incorporate resource- and stressor-based metrics, rely on publicly available data collected at multiple spatial scales, and quantify both natural reference and societally desired resource conditions.

Climate conditions, such as temperature or precipitation, averaged over several decades strongly affect species distributions, as evidenced by experimental results and a plethora of models demonstrating statistical relations between species occurrences and long-term climate averages. However, long-term averages can conceal climate changes that have occurred in recent decades and may not capture actual species occurrence well because the distributions of species, especially at the edges of their range, are typically dynamic and may respond strongly to short-term climate variability. Our goal here was to test whether bird occurrence models can be predicted by either covariates based on short-term climate variability or on long-term climate averages. We parameterized species distribution models (SDMs) based on either short-term variability or long-term average climate covariates for 320 bird species in the conterminous USA and tested whether any life-history trait-based guilds were particularly sensitive to short-term conditions. Models including short-term climate variability performed well based on their cross-validated area-under-the-curve AUC score (0.85), as did models based on long-term climate averages (0.84). Similarly, both models performed well compared to independent presence/absence data from the North American Breeding Bird Survey (independent AUC of 0.89 and 0.90, respectively). However, models based on short-term variability covariates more accurately classified true absences for most species (73% of true absences classified within the lowest quarter of environmental suitability vs. 68%). In addition, they have the advantage that they can reveal the dynamic relationship between species and their environment because they capture the spatial fluctuations of species potential breeding distributions. With this information, we can identify which species and guilds are sensitive to climate variability, identify sites of high conservation value where climate variability is low, and assess how species' potential distributions may have already shifted due recent climate change. However, long-term climate averages require less data and processing time and may be more readily available for some areas of interest. Where data on short-term climate variability are not available, long-term climate information is a sufficient predictor of species distributions in many cases. However, short-term climate variability data may provide information not captured with long-term climate data for use in SDMs., (© 2016 by the Ecological Society of America.)

Understanding the forces shaping ecological communities is of crucial importance for basic science and conservation. After 50 years in which ecological theory has focused on either stable communities driven by niche-based forces or nonstable "neutral" communities driven by demographic stochasticity, contemporary theories suggest that ecological communities are driven by the simultaneous effects of both types of mechanisms. Here we examine this paradigm using the longest available records for the dynamics of tropical trees and breeding birds. Applying a macroecological approach and fluctuation analysis techniques borrowed from statistical physics, we show that both stabilizing mechanisms and demographic stochasticity fail to play a dominant role in shaping assemblages over time. Rather, community dynamics in these two very different systems is predominantly driven by environmental stochasticity. Clearly, the current melding of niche and neutral theories cannot account for such dynamics. Our results highlight the need for a new theory of community dynamics integrating environmental stochasticity with weak stabilizing forces and suggest that such theory may better describe the dynamics of ecological communities than current neutral theories, deterministic niche-based theories, or recent hybrids.

As people encroach increasingly on natural areas, one question is how this affects avian biodiversity. The answer to this is partly scale-dependent. At broad scales, human populations and biodiversity concentrate in the same areas and are positively associated, but at local scales people and biodiversity are negatively associated with biodiversity. We investigated whether there is also a systematic temporal trend in the relationship between bird biodiversity and housing development. We used linear regression to examine associations between forest bird species richness and housing growth in the conterminous United States over 30 years. Our data sources were the North American Breeding Bird Survey and the 2000 decennial U.S. Census. In the 9 largest forested ecoregions, housing density increased continually over time. Across the conterminous United States, the association between bird species richness and housing density was positive for virtually all guilds except ground nesting birds. We found a systematic trajectory of declining bird species richness as housing increased through time. In more recently developed ecoregions, where housing density was still low, the association with bird species richness was neutral or positive. In ecoregions that were developed earlier and where housing density was highest, the association of housing density with bird species richness for most guilds was negative and grew stronger with advancing decades. We propose that in general the relationship between human settlement and biodiversity over time unfolds as a 2-phase process. The first phase is apparently innocuous; associations are positive due to coincidence of low-density housing with high biodiversity. The second phase is highly detrimental to biodiversity, and increases in housing density are associated with biodiversity losses. The long-term effect on biodiversity depends on the final housing density. This general pattern can help unify our understanding of the relationship of human encroachment and biodiversity response., (© 2014 Society for Conservation Biology.)

Taylor's law, one of the most widely accepted generalizations in ecology, states that the variance of a population abundance time series scales as a power law of its mean. Here we reexamine this law and the empirical evidence presented in support of it. Specifically, we show that the exponent generally depends on the length of the time series, and its value reflects the combined effect of many underlying mechanisms. Moreover, sampling errors alone, when presented on a double logarithmic scale, are sufficient to produce an apparent power law. This raises questions regarding the usefulness of Taylor's law for understanding ecological processes. As an alternative approach, we focus on short-term fluctuations and derive a generic null model for the variance-to-mean ratio in population time series from a demographic model that incorporates the combined effects of demographic and environmental stochasticity. After comparing the predictions of the proposed null model with the fluctuations observed in empirical data sets, we suggest an alternative expression for fluctuation scaling in population time series. Analyzing population fluctuations as we have proposed here may provide new applied (e.g., estimation of species persistence times) and theoretical (e.g., the neutral theory of biodiversity) insights that can be derived from more generally available short-term monitoring data.

Protected areas are a cornerstone for biodiversity conservation, but they also provide amenities that attract housing development on inholdings and adjacent private lands. We explored how this development affects biodiversity within and near protected areas among six ecological regions throughout the United States. We quantified the effect of housing density within, at the boundary, and outside protected areas, and natural land cover within protected areas, on the proportional abundance and proportional richness of three avian guilds within protected areas. We developed three guilds from the North American Breeding Bird Survey, which included Species of Greatest Conservation Need, land cover affiliates (e.g., forest breeders), and synanthropic species associated with urban environments. We gathered housing density data for the year 2000 from the U.S. Census Bureau, and centered the bird data on this year. We obtained land cover data from the 2001 National Land Cover Database, and we used single- and multiple-variable analyses to address our research question. In all regions, housing density within protected areas was positively associated with the proportional abundance or proportional richness of synanthropes, and negatively associated with the proportional abundance or proportional richness of Species of Greatest Conservation Need. These relationships were strongest in the eastern forested regions and the central grasslands, where more than 70% and 45%, respectively, of the variation in the proportional abundance of synanthropes and Species of Greatest Conservation Need were explained by housing within protected areas. Furthermore, in most regions, housing density outside protected areas was positively associated with the proportional abundance or proportional richness of synanthropes and negatively associated with the proportional abundance of land cover affiliates and Species of Greatest Conservation Need within protected areas. However, these effects were weaker than housing within protected areas. Natural land cover was high with little variability within protected areas, and consequently, was less influential than housing density within or outside protected areas explaining the proportional abundance or proportional richness of the avian guilds. Our results indicate that housing development within, at the boundary, and outside protected areas impacts avian community structure within protected areas throughout the United States.

Changes in land use and land cover have affected and will continue to affect biological diversity worldwide. Yet, understanding the spatially extensive effects of land-cover change has been challenging because data that are consistent over space and time are lacking. We used the U.S. National Land Cover Dataset Land Cover Change Retrofit Product and North American Breeding Bird Survey data to examine land-cover change and its associations with diversity of birds with principally terrestrial life cycles (landbirds) in the conterminous United States. We used mixed-effects models and model selection to rank associations by ecoregion. Land cover in 3.22% of the area considered in our analyses changed from 1992 to 2001, and changes in species richness and abundance of birds were strongly associated with land-cover changes. Changes in species richness and abundance were primarily associated with changes in nondominant types of land cover, yet in many ecoregions different types of land cover were associated with species richness than were associated with abundance. Conversion of natural land cover to anthropogenic land cover was more strongly associated with changes in bird species richness and abundance than persistence of natural land cover in nearly all ecoregions and different covariates were most strongly associated with species richness than with abundance in 11 of 17 ecoregions. Loss of grassland and shrubland affected bird species richness and abundance in forested ecoregions. Loss of wetland was associated with bird abundance in forested ecoregions. Our findings highlight the value of understanding changes in nondominant land cover types and their association with bird diversity in the United States., (Conservation Biology©2012 Society for Conservation Biology  No claim to original US government works.)

Establishing species conservation priorities and recovery goals is often enhanced by extinction risk estimates. The need to set goals, even in data-deficient situations, has prompted researchers to ask whether general guidelines could replace individual estimates of extinction risk. To inform conservation policy, recent studies have revived the concept of the minimum viable population (MVP), the population size required to provide some specified probability of persistence for a given period of time. These studies conclude that long-term persistence requires ≥5000 adult individuals, an MVP threshold that is unaffected by taxonomy, life history or environmental conditions. Here, we re-evaluate this suggestion. We find that neither data nor theory supports its general applicability, raising questions about the utility of MVPs for conservation planning., (Copyright © 2011 Elsevier Ltd. All rights reserved.)

Wetlands generally provide significant ecosystem services and function as important harbors of biodiversity. To ensure that these habitats are conserved, an efficient means of identifying wetlands at risk of conversion is needed, especially in the southern United States where the rate of wetland loss has been highest in recent decades. We used multivariate adaptive regression splines to develop a model to predict the risk of wetland habitat loss as a function of wetland features and landscape context. Fates of wetland habitats from 1992 to 1997 were obtained from the National Resources Inventory for the U.S. Forest Service's Southern Region, and land-cover data were obtained from the National Land Cover Data. We randomly selected 70% of our 40 617 observations to build the model (n = 28 432), and randomly divided the remaining 30% of the data into five Test data sets (n = 2437 each). The wetland and landscape variables that were important in the model, and their relative contributions to the model's predictive ability (100 = largest, 0 = smallest), were land-cover/ land-use of the surrounding landscape (100.0), size and proximity of development patches within 570 m (39.5), land ownership (39.1), road density within 570 m (37.5), percent woody and herbaceous wetland cover within 570 m (27.8), size and proximity of development patches within 5130 m (25.7), percent grasslands/herbaceous plants and pasture/hay cover within 5130 m (21.7), wetland type (21.2), and percent woody and herbaceous wetland cover within 1710 m (16.6). For the five Test data sets, Kappa statistics (0.40, 0.50, 0.52, 0.55, 0.56; P < 0.0001), area-under-the-receiver-operating-curve (AUC) statistics (0.78, 0.82, 0.83, 0.83, 0.84; P < 0.0001), and percent correct prediction of wetland habitat loss (69.1, 80.4, 81.7, 82.3, 83.1) indicated the model generally had substantial predictive ability across the South. Policy analysts and land-use planners can use the model and associated maps to prioritize at-risk wetlands for protection, evaluate wetland habitat connectivity, predict future conversion of wetland habitat based on projected land-use trends, and assess the effectiveness of wetland conservation programs.

Ecosystem energy is now recognized as a primary correlate and potential driver of global patterns of species richness. The increasingly well-tested species-energy relationship is now ripe for application to conservation, and recent advances in satellite technology make this more feasible. While the correlates for the species-energy relationship have been addressed many times previously, this study is among the first to apply species-energy theory to conservation. Our objectives were to: (1) determine the strongest model of bird richness across North America; (2) determine whether the slope of the best species-energy model varied with varying energy levels; and (3) identify the spatial patterns with similar or dissimilar slopes to draw inference for conservation. Model selection techniques were used to evaluate relationships between Moderate Resolution Imaging Spectroradiometer (MODIS) measures of ecosystem energy and species richness of native land birds using the USGS Breeding Bird Survey (BBS) data. Linear, polynomial, and break point regression techniques were used to evaluate the shape of the relationships with correction for spatial autocorrelation. Spatial analyses were used to determine regions where slopes of the relationship differed. We found that annual gross primary production (GPP) was the strongest correlate of richness (adjusted R2 = 0.55), with a quadratic model being the strongest model. The negative slope of the model was confirmed significantly negative at the highest energy levels. This finding demonstrates that there are three different slopes to the species-energy relationship across the energy gradient of North America: positive, flat, and negative. If energy has a causal relationship with richness, then species-energy theory implies that energy causes richness to increase in low-energy areas, energy has little effect in intermediate-energy areas, and energy depresses richness in the highest-energy areas. This information provides a basis for potential applications for more effective conservation. For example, in low-energy areas, increased nutrients could improve vegetation productivity and increase species richness. In high-energy areas where competitive dominance of vegetation might reduce species richness, vegetation manipulation could increase species richness. These strategies will likely be most effective if tailored to the local energy gradient.

Background: Quantifying changes in forest bird diversity is an essential task for developing effective conservation actions. When subtle changes in diversity accumulate over time, annual comparisons may offer an incomplete perspective of changes in diversity. In this case, progressive change, the comparison of changes in diversity from a baseline condition, may offer greater insight because changes in diversity are assessed over longer periods of times. Our objectives were to determine how forest bird diversity has changed over time and whether those changes were associated with forest disturbance., Methodology/principal Findings: We used North American Breeding Bird Survey data, a time series of Landsat images classified with respect to land cover change, and mixed-effects models to associate changes in forest bird community structure with forest disturbance, latitude, and longitude in the conterminous United States for the years 1985 to 2006. We document a significant divergence from the baseline structure for all birds of similar migratory habit and nest location, and all forest birds as a group from 1985 to 2006. Unexpectedly, decreases in progressive similarity resulted from small changes in richness (<1 species per route for the 22-year study period) and modest losses in abundance (-28.7 - -10.2 individuals per route) that varied by migratory habit and nest location. Forest disturbance increased progressive similarity for Neotropical migrants, permanent residents, ground nesting, and cavity nesting species. We also documented highest progressive similarity in the eastern United States., Conclusions/significance: Contemporary forest bird community structure is changing rapidly over a relatively short period of time (e.g., approximately 22 years). Forest disturbance and forest regeneration are primary factors associated with contemporary forest bird community structure, longitude and latitude are secondary factors, and forest loss is a tertiary factor. Importantly, these findings suggest some regions of the United States may already fall below the habitat amount threshold where fragmentation effects become important predictors of forest bird community structure.

Protected areas are crucial for biodiversity conservation because they provide safe havens for species threatened by land-use change and resulting habitat loss. However, protected areas are only effective when they stop habitat loss within their boundaries, and are connected via corridors to other wild areas. The effectiveness of protected areas is threatened by development; however, the extent of this threat is unknown. We compiled spatially-detailed housing growth data from 1940 to 2030, and quantified growth for each wilderness area, national park, and national forest in the conterminous United States. Our findings show that housing development in the United States may severely limit the ability of protected areas to function as a modern "Noah's Ark." Between 1940 and 2000, 28 million housing units were built within 50 km of protected areas, and 940,000 were built within national forests. Housing growth rates during the 1990s within 1 km of protected areas (20% per decade) outpaced the national average (13%). If long-term trends continue, another 17 million housing units will be built within 50 km of protected areas by 2030 (1 million within 1 km), greatly diminishing their conservation value. US protected areas are increasingly isolated, housing development in their surroundings is decreasing their effective size, and national forests are even threatened by habitat loss within their administrative boundaries. Protected areas in the United States are thus threatened similarly to those in developing countries. However, housing growth poses the main threat to protected areas in the United States whereas deforestation is the main threat in developing countries.

Landscape-scale disturbance events, including ecological restoration and fuel reduction activities, can modify habitat and affect relationships between species and their environment. To reduce the risk of uncharacteristic stand-replacing fires in the southwestern United States, land managers are implementing restoration and fuels treatments (e.g., mechanical thinning, prescribed fire) in progressively larger stands of dry, lower elevation ponderosa pine (Pinus ponderosa) forest. We used a Before-After/Control-Impact experimental design to quantify the multi-scale response of avifauna to large (approximately 250-400 ha) prescribed fire treatments on four sites in Arizona and New Mexico dominated by ponderosa pine. Using distance sampling and an information-theoretic approach, we estimated changes in density for 14 bird species detected before (May-June 2002-2003) and after (May-June 2004-2005) prescribed fire treatments. We observed few site-level differences in pre- and posttreatment density, and no species responded strongly to treatment on all four sites. Point-level spatial models of individual species response to treatment, habitat variables, and fire severity revealed ecological relationships that were more easily interpreted. At this scale, pretreatment forest structure and patch characteristics were important predictors of posttreatment differences in bird species density. Five species (Pygmy Nuthatch [Sitta pygmaea], Western Bluebird [Sialia mexicana], Steller's Jay [Cyanocitta stelleri], American Robin [Turdus migratorius], and Hairy Woodpecker [Picoides villosus]) exhibited a strong treatment response, and two of these species (American Robin and Hairy Woodpecker) could be associated with meaningful fire severity response functions. The avifaunal response patterns that we observed were not always consistent with those reported by more common studies of wildland fire events. Our results suggest that, in the short-term, the distribution and abundance of common members of the breeding bird community in Southwestern ponderosa pine forests appear to be tolerant of low- to moderate-intensity prescribed fire treatments at multiple spatial scales and across multiple geographic locations.

Patterns of association between humans and biodiversity typically show positive, negative, or negative quadratic relationships and can be described by 3 hypotheses: biologically rich areas that support high human population densities co-occur with areas of high biodiversity (productivity); biodiversity decreases monotonically with increasing human activities (ecosystem stress); and biodiversity peaks at intermediate levels of human influence (intermediate disturbance). To test these hypotheses, we compared anthropogenic land cover and housing units, as indices of human influence, with bird species richness and abundance across the Midwestern United States. We modeled richness of native birds with 12 candidate models of land cover and housing to evaluate the empirical evidence. To assess which species were responsible for observed variation in richness, we repeated our model-selection analysis with relative abundance of each native species as the response and then asked whether natural-history traits were associated with positive, negative, or mixed responses. Native avian richness was highest where anthropogenic land cover was lowest and housing units were intermediate based on model-averaged predictions among a confidence set of candidate models. Eighty-three of 132 species showed some pattern of association with our measures of human influence. Of these species approximately 40% were negatively associated, approximately 6% were positively associated, and approximately 7% showed evidence of an intermediate relationship with human influence measures. Natural-history traits were not closely related to the direction of the relationship between abundance and human influence. Nevertheless, pooling species that exhibited any relationship with human influence and comparing them with unrelated species indicated they were significantly smaller, nested closer to the ground, had shorter incubation and fledging times, and tended to be altricial. Our results support the ecosystem-stress hypothesis for the majority of individual species and for overall species diversity when focusing on anthropogenic land cover. Nevertheless, the great variability in housing units across the land-cover gradient indicates that an intermediate-disturbance relationship is also supported. Our findings suggest preemptive conservation action should be taken, whereby areas with little anthropogenic land cover are given conservation priority. Nevertheless, conservation action should not be limited to pristine landscapes because our results showed that native avian richness and the relative abundance of many species peaked at intermediate housing densities and levels of anthropogenic land cover.

In the United States, housing density has substantially increased in and adjacent to forests. Our goal in this study was to identify how housing density and human populations are associated with avian diversity. We compared these associations to those between landscape pattern and avian diversity, and we examined how these associations vary across the conterminous forested United States. Using data from the North American Breeding Bird Survey, the U.S. Census, and the National Land Cover Database, we focused on forest and woodland bird communities and conducted our analysis at multiple levels of model specificity, first using a coarse-thematic resolution (basic models), then using a larger number of fine-thematic resolution variables (refined models). We found that housing development was associated with forest bird species richness in all forested ecoregions of the conterminous United States. However, there were important differences among ecoregions. In the basic models, housing density accounted for < 5% of variance in avian species richness. In refined models, 85% of models included housing density and/or residential land cover as significant variables. The strongest guild response was demonstrated in the Adirondack-New England ecoregion, where 29% of variation in richness of the permanent resident guild was associated with housing density. Model improvements due to regional stratification were most pronounced for cavity nesters and short-distance migrants, suggesting that these guilds may be especially sensitive to regional processes. The varying patterns of association between avian richness and attributes associated with landscape structure suggested that landscape context was an important mediating factor affecting how biodiversity responds to landscape changes. Our analysis suggested that simple, broadly applicable, land use recommendations cannot be derived from our results. Rather, anticipating future avian response to land use intensification (or reversion to native vegetation) has to be conditioned on the current landscape context and the species group of interest. Our results show that housing density and residential land cover were significant predictors of forest bird species richness, and their prediction strengths are likely to increase as development continues.

While the importance of spatial scale in ecology is well established, few studies have investigated the impact of data grain on conservation planning outcomes. In this study, we compared species richness hotspot and representation networks developed at five grain sizes. We used species distribution maps for mammals and birds developed by the Arizona and New Mexico Gap Analysis Programs (GAP) to produce 1-km2, 100-kmn2, 625-km2, 2500-km2, and 10,000-km2 grid cell resolution distribution maps. We used these distribution maps to generate species richness and hotspot (95th quantile) maps for each taxon in each state. Species composition information at each grain size was used to develop two types of representation networks using the reserve selection software MARXAN. Reserve selection analyses were restricted to Arizona birds due to considerable computation requirements. We used MARXAN to create best reserve networks based on the minimum area required to represent each species at least once and equal area networks based on irreplaceability values. We also measured the median area of each species' distribution included in hotspot (mammals and birds of Arizona and New Mexico) and irreplaceability (Arizona birds) networks across all species. Mean area overlap between richness hotspot reserves identified at the five grain sizes was 29% (grand mean for four within-taxon/state comparisons), mean overlap for irreplaceability reserve networks was 32%, and mean overlap for best reserve networks was 53%. Hotspots for mammals and birds showed low overlap with a mean of 30%. Comparison of hotspots and irreplaceability networks showed very low overlap with a mean of 13%. For hotspots, median species distribution area protected within reserves declined monotonically from a high of 11% for 1-km2 networks down to 6% for 10,000-km2 networks. Irreplaceability networks showed a similar, but more variable, pattern of decline. This work clearly shows that map resolution has a profound effect on conservation planning outcomes and that hotspot and representation outcomes may be strikingly dissimilar. Thus, conservation planning is scale dependent, such that reserves developed using coarse-grained data do not subsume fine-grained reserves. Moreover, preserving both full species representation and species rich areas may require combined reserve design strategies.

A discrete reaction-diffusion model was used to estimate long-term equilibrium populations of a hypothetical species inhabiting patchy landscapes to examine the relative importance of habitat amount and arrangement in explaining population size. When examined over a broad range of habitat amounts and arrangements, population size was largely determined by a pure amount effect (proportion of habitat in the landscape accounted for >96% of the total variation compared to <1% for the arrangement main effect). However, population response deviated from a pure amount effect as coverage was reduced below 30%-50%. That deviation coincided with a persistence threshold as indicated by a rapid decline in the probability of landscapes supporting viable populations. When we partitioned experimental landscapes into sets of "above" and "below" persistence threshold, habitat arrangement became an important factor in explaining population size below threshold conditions. Regression analysis on below-threshold landscapes using explicit measures of landscape structure (after removing the covariation with habitat amount) indicated that arrangement variables accounted for 33%-39% of the variation in population size, compared to 27%-49% for habitat amount. Thus, habitat arrangement effects became important when species persistence became uncertain due to dispersal mortality.

We examine habitat size, shape, and arrangement effects on populations using a discrete reaction-diffusion model. Diffusion is modeled passively and applied to a cellular grid of territories forming a coupled map lattice. Dispersal mortality is proportional to the amount of nonhabitat and fully occupied habitat surrounding a given cell, with distance decay. After verifying that our model produces the results expected for single patches of uniform habitat, we investigate heterogeneous and fragmented model landscapes. In heterogeneous single-patch systems near critical patch size, populations approach Gaussian spatial distributions with total population constrained by the capacity of the most limiting cell. In fragmented habitat landscapes, threshold effects are more complex and parametrically sensitive. The results from our experiments suggest the following: the ability to achieve persistence in hyperdispersed patchy habitats by adding similarly fragmented patches requires meeting threshold reproduction rates; persistent metapopulations in which no local population is individually persistent appear when dispersal distances and reproduction rates are both high, but only within narrow parameter ranges that are close to extinction thresholds; successful use of stepping-stone patches to support metapopulation systems appears unlikely for passively diffusing species; elongated patches offer early colonization advantages, but blocky patches offer greater population resilience near extinction thresholds. A common theme running through our findings is that population viability estimates may depend on our ability to determine when population and habitat systems are approaching extinction threshold conditions., (Copyright 1999 Academic Press.)

Understanding the relationship between animal community dynamics and landscape structure has become a priority for biodiversity conservation. In particular, predicting the effects of habitat destruction that confine species to networks of small patches is an important prerequisite to conservation plan development. Theoretical models that predict the occurrence of species in fragmented landscapes, and relationships between stability and diversity do exist. However, reliable empirical investigations of the dynamics of biodiversity have been prevented by differences in species detection probabilities among landscapes. Using long-term data sampled at a large spatial scale in conjunction with a capture-recapture approach, we developed estimates of parameters of community changes over a 22-year period for forest breeding birds in selected areas of the eastern United States. We show that forest fragmentation was associated not only with a reduced number of forest bird species, but also with increased temporal variability in the number of species. This higher temporal variability was associated with higher local extinction and turnover rates. These results have major conservation implications. Moreover, the approach used provides a practical tool for the study of the dynamics of biodiversity.