Economic-based projections of future land use in the conterminous United States under alternative policy scenarios

Land-use change significantly contributes to biodiversity loss, invasive species spread, changes in biogeochemical cycles, and the loss of ecosystem services. Planning for a sustainable future requires a thorough understanding of expected land use at the fine spatial scales relevant for modeling many ecological processes and at dimensions appropriate for regional or national-level policy making. Our goal was to construct and parameterize an econometric model of land-use change to project future land use to the year 2051 at a fine spatial scale across the conterminous United States under several alternative land-use policy scenarios. We parameterized the econometric model of land-use change with the National Resource Inventory (NRI) 1992 and 1997 land-use data for 844 000 sample points. Land-use transitions were estimated for five land-use classes (cropland, pasture, range, forest, and urban). We predicted land-use change under four scenarios: business-as-usual, afforestation, removal of agricultural subsidies, and increased urban rents. Our results for the business-as-usual scenario showed widespread changes in land use, affecting 36% of the land area of the conterminous United States, with large increases in urban land (79%) and forest (7%), and declines in cropland (-16%) and pasture (-13%). Areas with particularly high rates of land-use change included the larger Chicago area, parts of the Pacific Northwest, and the Central Valley of California. However, while land-use change was substantial, differences in results among the four scenarios were relatively minor. The only scenario that was markedly different was the afforestation scenario, which resulted in an increase of forest area that was twice as high as the business-as-usual scenario. Land-use policies can affect trends, but only so much. The basic economic and demographic factors shaping land-use changes in the United States are powerful, and even fairly dramatic policy changes, showed only moderate deviations from the business-as-usual scenario. Given the magnitude of predicted land-use change, any attempts to identify a sustainable future or to predict the effects of climate change will have to take likely land-use changes into account. Econometric models that can simulate land-use change for broad areas with fine resolution are necessary to predict trends in ecosystem service provision and biodiversity persistence.     

Mapping shifts in spatial synchrony in grassland birds to inform conservation planning

Spatial synchrony, defined as the correlated fluctuations in abundance of spatially separated populations, can be caused by regional fluctuations in natural and anthropogenic environmental population drivers. Investigations into the geography of synchrony can provide useful insight to inform conservation planning efforts by revealing regions of common population drivers and metapopulation extinction vulnerability. We examined the geography of spatial synchrony and decadal changes in these patterns for grassland birds in the United States and Canada, which are experiencing widespread and persistent population declines. We used Bayesian hierarchical models and over 50 years of abundance data from the North American Breeding Bird Survey to generate population indices within a 2° latitude by 2° longitude grid. We computed and mapped mean local spatial synchrony for each cell (mean detrended correlation of the index among neighboring cells), along with associated uncertainty, for 19 species in 2, 26-year periods, 1968–1993 and 1994–2019. Grassland birds were predicted to increase in spatial synchrony where agricultural intensification, climate change, or interactions between the 2 increased. We found no evidence of an overall increase in synchrony among grassland bird species. However, based on the geography of these changes, there was considerable spatial heterogeneity within species. Averaging across species, we identified clusters of increasing spatial synchrony in the Prairie Pothole and Shortgrass Prairie regions and a region of decreasing spatial synchrony in the eastern United States. Our approach has the potential to inform continental-scale conservation planning by adding an additional layer of relevant information to species status assessments and spatial prioritization of policy and management actions. Our work adds to a growing literature suggesting that global change may result in shifting patterns of spatial synchrony in population dynamics across taxa with broad implications for biodiversity conservation.     

Revisiting Kappa to account for change in the accuracy assessment of land-use change models

Land-use change models are typically calibrated to reproduce known historic changes. Calibration results can then be assessed by comparing two datasets: the simulated land-use map and the actual land-use map at the same time. A common method for this is the Kappa statistic, which expresses the agreement between two categorical datasets corrected for the expected agreement. This expected agreement is based on a stochastic model of random allocation given the distribution of class sizes. However, when a model starts from an initial land-use map and makes changes to it, that stochastic model does not pose a meaningful reference level. This paper introduces K_Simulation, a statistic that is identical in form to the Kappa statistic but instead applies a more appropriate stochastic model of random allocation of class transitions relative to the initial map. The new method is illustrated on a simple example and then the results of the Kappa statistic and K_Simulation are compared using the results of a land-use model. It is found that only K_Simulation truly tests models in their capacity to explain land-use changes over time, and unlike Kappa it does not inflate results for simulations where little change takes place over time.     

The effect of pollution on crime: Evidence from data on particulate matter and ozone

We estimate the effect of short-term air pollution exposure (PM_2.5 and ozone) on several categories of crime, with a particular emphasis on aggressive behavior. To identify this relationship, we combine detailed daily data on crime, air pollution, and weather for an eight-year period across the United States. Our primary identification strategy employs extremely high dimensional fixed effects and we perform a series of robustness checks to address confounding variation between temperature and air pollution. We find a robust positive effect of increased air pollution on violent crimes, and specifically assaults, but no relationship between increases in air pollution and property crimes. The effects are present in and out of the home, at levels well below Ambient Air Pollution Standards, and PM_2.5 effects are strongest at lower temperatures. The results suggest that a 10% reduction in daily PM_2.5 and ozone could save $1.4 billion in crime costs per year, a previously overlooked cost associated with pollution.     

Fecundity as a Basis for Risk Assessment of Nonindigenous Freshwater Molluscs

Abstract:  The most efficient way to reduce future damages from nonindigenous species is to prevent the introduction of harmful species. Although ecologists have long sought to predict the identity of such species, recent methodological advances promise success where previous attempts failed. We applied recently developed risk assessment approaches to nonindigenous freshwater molluscs at two geographic scales: the Laurentian Great Lakes basin and the 48 contiguous states of the United States. We used data on natural history and biogeography to discriminate between established freshwater molluscs that are benign and those that constitute nuisances (i.e., cause environmental and/or economic damage). Two statistical techniques, logistic regression and categorical tree analysis, showed that nuisance status was positively associated with fecundity. Other aspects of natural history and biogeography did not significantly affect likelihood of becoming a nuisance. We then used the derived statistical models to predict the chance that 15 mollusc species not yet in natural ecosystems would cause damage if they become established. We also tested whether time since establishment is related to the likelihood that nonindigenous mollusc species in the Great Lakes and United States would cause negative impacts. No significant relationship was evident at the U.S. scale, but recently established molluscs within the Great Lakes were more likely to cause negative impacts. This may reflect changing environmental conditions, changing patterns of trade, or may be an indication of "invasional meltdown." Our quantitative analyses could be extended to other taxa and ecosystems and offer a number of improvements over the qualitative risk assessments currently used by U.S. (and other) government agencies.     

Complementary habitat use by wild bees in agro-natural landscapes

Human activity causes abrupt changes in resource availability across the landscape. In order to persist in human-altered landscapes organisms need to shift their habitat use accordingly. Little is known about the mechanisms by which whole communities persist in human-altered landscapes, including the role of complementary habitat use. We define complementary habitat use as the use of different habitats at different times by the same group of species during the course of their activity period. We hypothesize that complementary habitat use is a mechanism through which native bee species persist in human-altered landscapes. To test this idea, we studied wild bee communities in agro-natural landscapes and explored their community-level patterns of habitat and resource use over space and time. The study was conducted in six agro-natural landscapes in the eastern United States, each containing three main bee habitat types (natural habitat, agricultural fields, and old fields). Each of the three habitats exhibited a unique seasonal pattern in amount, diversity, and composition of floral resources, and together they created phenological complementarity in foraging resources for bees. Individual bee species as well as the bee community responded to these spatiotemporal patterns in floral availability and exhibited a parallel pattern of complementary habitat use. The majority of wild bee species, including all the main crop visitors, used fallow areas within crops early in the season, shifted to crops in mid-season, and used old-field habitats later in the season. The natural-forest habitat supported very limited number of bees, mostly visitors of non-crop plants. Old fields are thus an important feature in these arable landscapes for maintaining crop pollination services. Our study provides a detailed examination of how shifts in habitat and resource use may enable bees to persist in highly dynamic agro-natural landscapes, and points to the need for a broad cross-habitat perspective in managing these landscapes.     

Modeling patterns of nonlinearity in ecosystem responses to temperature, CO2, and precipitation changes.

It is commonly acknowledged that ecosystem responses to global climate change are nonlinear. However, patterns of the nonlinearity have not been well characterized on ecosystem carbon and water processes. We used a terrestrial ecosystem (TECO) model to examine nonlinear patterns of ecosystem responses to changes in temperature, CO2, and precipitation individually or in combination. The TECO model was calibrated against experimental data obtained from a grassland ecosystem in the central United States and ran for 100 years with gradual change at 252 different scenarios. We primarily used the 100th-year results to explore nonlinearity of ecosystem responses. Variables examined in this study are net primary production (NPP), heterotrophic respiration (R(h)), net ecosystem carbon exchange (NEE), runoff, and evapotranspiration (ET). Our modeling results show that nonlinear patterns were parabolic, asymptotic, and threshold-like in response to temperature, CO2, and precipitation anomalies, respectively, for NPP, NEE, and R(h). Runoff and ET exhibited threshold-like pattern in response to both temperature and precipitation anomalies but were less sensitive to CO2 changes. Ecosystem responses to combined temperature, CO2, and precipitation anomalies differed considerably from the responses to individual factors in terms of response patterns and/or critical points of nonlinearity. Our results suggest that nonlinear patterns in response to multiple global-change factors were diverse and were considerably affected by combined climate anomalies on ecosystem carbon and water processes. The diverse response patterns in nonlinearity have profound implications for both experimental design and theoretical development.     

Social comfort zones for transformative conservation decisions in a changing climate

Novel management interventions intended to mitigate the impacts of climate change on biodiversity are increasingly being considered by scientists and practitioners. However, resistance to more transformative interventions remains common across both specialist and lay communities and is generally assumed to be strongly entrenched. We used a decision-pathways survey of the public in Canada and the United States (n = 1490) to test two propositions relating to climate-motivated interventions for conservation: most public groups are uncomfortable with interventionist options for conserving biodiversity and given the strong values basis for preferences regarding biodiversity and natural systems more broadly, people are unlikely to change their minds. Our pathways design tested and retested levels of comfort with interventions for forest ecosystems at three different points in the survey. Comfort was reexamined given different nudges (including new information from trusted experts) and in reference to a particular species (bristlecone pine [Pinus longaeva]). In contrast with expectations of public unease, baseline levels of public comfort with climate interventions in forests was moderately high (46% comfortable) and increased further when respondents were given new information and the opportunity to change their choice after consideration of a particular species. People who were initially comfortable with interventions tended to remain so (79%), whereas 42% of those who were initially uncomfortable and 40% of those who were uncertain shifted to comfortable by the end of the survey. In short and across questions, comfort levels with interventions were high, and where discomfort or uncertainty existed, such positions did not appear to be strongly held. We argue that a new decision logic, one based on anthropogenic responsibility, is beginning to replace a default reluctance to intervene with nature.     

Mapping Change in Human Pressure Globally on Land and within Protected Areas

It is widely accepted that the main driver of the observed decline in biological diversity is increasing human pressure on Earth's ecosystems. However, the spatial patterns of change in human pressure and their relation to conservation efforts are less well known. We developed a spatially and temporally explicit map of global change in human pressure over 2 decades between 1990 and 2010 at a resolution of 10 km². We evaluated 22 spatial data sets representing different components of human pressure and used them to compile a temporal human pressure index (THPI) based on 3 data sets: human population density, land transformation, and electrical power infrastructure. We investigated how the THPI within protected areas was correlated to International Union for Conservation of Nature (IUCN) management categories and the human development index (HDI) and how the THPI was correlated to cumulative pressure on the basis of the original human footprint index. Since the early 1990s, human pressure increased 64% of the terrestrial areas; the largest increases were in Southeast Asia. Protected areas also exhibited overall increases in human pressure, the degree of which varied with location and IUCN management category. Only wilderness areas and natural monuments (management categories Ib and III) exhibited decreases in pressure. Protected areas not assigned any category exhibited the greatest increases. High HDI values correlated with greater reductions in pressure across protected areas, while increasing age of the protected area correlated with increases in pressure. Our analysis is an initial step toward mapping changes in human pressure on the natural world over time. That only 3 data sets could be included in our spatio‐temporal global pressure map highlights the challenge to measuring pressure changes over time. Mapeo del Cambio en la Presión Humana Global en Tierra y Dentro de Áreas Protegidas     

Classification of Climate‐Change‐Induced Stresses on Biological Diversity

Abstract: Conservation actions need to account for and be adapted to address changes that will occur under global climate change. The identification of stresses on biological diversity (as defined in the Convention on Biological Diversity) is key in the process of adaptive conservation management. We considered any impact of climate change on biological diversity a stress because such an effect represents a change (negative or positive) in key ecological attributes of an ecosystem or parts of it. We applied a systemic approach and a hierarchical framework in a comprehensive classification of stresses to biological diversity that are caused directly by global climate change. Through analyses of 20 conservation sites in 7 countries and a review of the literature, we identified climate‐change‐induced stresses. We grouped the identified stresses according to 3 levels of biological diversity: stresses that affect individuals and populations, stresses that affect biological communities, and stresses that affect ecosystem structure and function. For each stress category, we differentiated 3 hierarchical levels of stress: stress class (thematic grouping with the coarsest resolution, 8); general stresses (thematic groups of specific stresses, 21); and specific stresses (most detailed definition of stresses, 90). We also compiled an overview of effects of climate change on ecosystem services using the categories of the Millennium Ecosystem Assessment and 2 additional categories. Our classification may be used to identify key climate‐change‐related stresses to biological diversity and may assist in the development of appropriate conservation strategies. The classification is in list format, but it accounts for relations among climate‐change‐induced stresses.     

Selecting a binary Markov model for a precipitation process

This paper uses rth-order categorical Markov chains to model the probability of precipitation. Several stationary and non-stationary high-order Markov models are proposed and compared using BIC. The number of parameters increases exponentially by adding the Markov order. Several classes of high-order Markov models are proposed which their increase of number of parameters are modest. For example models that use the number of precipitation days in a period prior to date, temperature of the previous day and sines/cosines periodic functions (to model the seasonality) are considered. The theory of partial likelihood is used to estimate the parameters. Parsimonious non-stationary first order Markov models with few seasonal terms are found optimal using BIC and temperature does not turn out to be a useful covariate. However BIC seems to underestimate the number of seasonal terms. We have also compared the results with AIC in some cases which tends to pick parsimonious models with more seasonal terms and higher order. We also show that ignoring seasonal terms result in picking higher order Markov chains. Finally we apply the methods to build confidence intervals for the probability of periods with no precipitation or low number of precipitation days in Calgary using historical data from 1980 to 2000.     

Gradient forests: calculating importance gradients on physical predictors

In ecological analyses of species and community distributions there is interest in the nature of their responses to environmental gradients and in identifying the most important environmental variables, which may be used for predicting patterns of biodiversity. Methods such as random forests already exist to assess predictor importance for individual species and to indicate where along gradients abundance changes. However, there is a need to extend these methods to whole assemblages, to establish where along the range of these gradients the important compositional changes occur, and to identify any important thresholds or change points. We develop such a method, called "gradient forest," which is an extension of the random forest approach. By synthesizing the cross-validated R2 and accuracy importance measures from univariate random forest analyses across multiple species, sampling devices, and surveys, gradient forest obtains a monotonic function of each predictor that represents the compositional turnover along the gradient of the predictor. When applied to a synthetic data set, the method correctly identified the important predictors and delineated where the compositional change points occurred along these gradients. Application of gradient forest to a real data set from part of the Great Barrier Reef identified mud fraction of the sediment as the most important predictor, with highest compositional turnover occurring at mud fraction values around 25%, and provided similar information for other predictors. Such refined information allows for more accurate capturing of biodiversity patterns for the purposes of bioregionalization, delineation of protected areas, or designing of biodiversity surveys.     

Associations of forest bird species richness with housing and landscape patterns across the USA.

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.     

Trends over time in tree and seedling phylogenetic diversity indicate regional differences in forest biodiversity change

Changing climate conditions may impact the short-term ability of forest tree species to regenerate in many locations. In the longer term, tree species may be unable to persist in some locations while they become established in new places. Over both time frames, forest tree biodiversity may change in unexpected ways. Using repeated inventory measurements five years apart from more than 7000 forested plots in the eastern United States, we tested three hypotheses: phylogenetic diversity is substantially different from species richness as a measure of biodiversity; forest communities have undergone recent changes in phylogenetic diversity that differ by size class, region, and seed dispersal strategy; and these patterns are consistent with expected early effects of climate change. Specifically, the magnitude of diversity change across broad regions should be greater among seedlings than in trees, should be associated with latitude and elevation, and should be greater among species with high dispersal capacity. Our analyses demonstrated that phylogenetic diversity and species richness are decoupled at small and medium scales and are imperfectly associated at large scales. This suggests that it is appropriate to apply indicators of biodiversity change based on phylogenetic diversity, which account for evolutionary relationships among species and may better represent community functional diversity. Our results also detected broadscale patterns of forest biodiversity change that are consistent with expected early effects of climate change. First, the statistically significant increase over time in seedling diversity in the South suggests that conditions there have become more favorable for the reproduction and dispersal of a wider variety of species, whereas the significant decrease in northern seedling diversity indicates that northern conditions have become less favorable. Second, we found weak correlations between seedling diversity change and latitude in both zones, with stronger relationships apparent in some ecoregions. Finally, we detected broadscale seedling diversity increases among species with longer-distance dispersal capacity, even in the northern zone, where overall seedling diversity declined. The statistical power and geographic extent of such analyses will increase as data become available over larger areas and as plot measurements are repeated at regular intervals over a longer period of time.     

Increased spatial variance accompanies reorganization of two continental shelf ecosystems

Phase transitions between alternate stable states in marine ecosystems lead to disruptive changes in ecosystem services, especially fisheries productivity. We used trawl survey data spanning phase transitions in the North Pacific (Gulf of Alaska) and the North Atlantic (Scotian Shelf) to test for increases in ecosystem variability that might provide early warning of such transitions. In both time series, elevated spatial variability in a measure of community composition (ratio of cod [Gadus sp.] abundance to prey abundance) accompanied transitions between ecosystem states, and variability was negatively correlated with distance from the ecosystem transition point. In the Gulf of Alaska, where the phase transition was apparently the result of a sudden perturbation (climate regime shift), variance increased one year before the transition in mean state occurred. On the Scotian Shelf, where ecosystem reorganization was the result of persistent overfishing, a significant increase in variance occurred three years before the transition in mean state was detected. However, we could not reject the alternate explanation that increased variance may also have simply been inherent to the final stable state in that ecosystem. Increased variance has been previously observed around transition points in models, but rarely in real ecosystems, and our results demonstrate the possible management value in tracking the variance of key parameters in exploited ecosystems.     

Using the past to contextualize anthropogenic impacts on the present and future distribution of an endemic Caribbean mammal

Island species are difficult to conserve because they face the synergy of climate change, invasive species, deforestation, and increasing human population densities in areas where land mass is shrinking. The Caribbean island of Hispaniola presents particular challenges because of geopolitical complexities that span 2 countries and hinder coordinated management of species across the island. We employed species distribution modeling to evaluate the impacts of climatic change and anthropogenic activities on the distribution of an endemic mammal of conservation concern, the Hispaniolan solenodon (Solenodon paradoxus). We aggregated occurrence points for this poorly known species for the Last Glacial Maximum (LGM) and the present (1975–2016) based on museum collections, online biodiversity databases, and new field surveys. We quantified degree of overlap between periods and scenarios with Schoener's D. Through a conservation paleobiology lens, we found that over time humans played an increasing role in shaping the distribution of S. paradoxus, thus, providing a foundation for developing conservation strategies on appropriate spatiotemporal scales. Human population density was the single most important predictor of S. paradoxus occurrence. Densities >166 people/km² corresponded to a near-zero probability of occurrence. Models that accounted for climate but not anthropogenic variables falsely identified suitable habitat in Haiti, where on-the-ground surveys confirm habitat is unavailable. Climate-only models also significantly overestimated the potential for habitat connectivity between isolated populations. Our work highlights that alternative fates for S. paradoxus in the Anthropocene exist across the political border between the Dominican Republic and Haiti due to the fundamentally different economic and political realities of each country. Relationships in the fossil record confirm that Hispaniola's sociopolitical boundary is not biologically significant but instead represents one imposed on the island's fauna in the past 500 years by colonial activity. Our approach reveals how a paleontological perspective can contribute to concrete management insights.     

Multimethod,multistate Bayesian hierarchical modeling approach for use in regional monitoring of wolves

In many cases, the first step in large‐carnivore management is to obtain objective, reliable, and cost‐effective estimates of population parameters through procedures that are reproducible over time. However, monitoring predators over large areas is difficult, and the data have a high level of uncertainty. We devised a practical multimethod and multistate modeling approach based on Bayesian hierarchical‐site‐occupancy models that combined multiple survey methods to estimate different population states for use in monitoring large predators at a regional scale. We used wolves (Canis lupus) as our model species and generated reliable estimates of the number of sites with wolf reproduction (presence of pups). We used 2 wolf data sets from Spain (Western Galicia in 2013 and Asturias in 2004) to test the approach. Based on howling surveys, the naïve estimation (i.e., estimate based only on observations) of the number of sites with reproduction was 9 and 25 sites in Western Galicia and Asturias, respectively. Our model showed 33.4 (SD 9.6) and 34.4 (3.9) sites with wolf reproduction, respectively. The number of occupied sites with wolf reproduction was 0.67 (SD 0.19) and 0.76 (0.11), respectively. This approach can be used to design more cost‐effective monitoring programs (i.e., to define the sampling effort needed per site). Our approach should inspire well‐coordinated surveys across multiple administrative borders and populations and lead to improved decision making for management of large carnivores on a landscape level. The use of this Bayesian framework provides a simple way to visualize the degree of uncertainty around population‐parameter estimates and thus provides managers and stakeholders an intuitive approach to interpreting monitoring results. Our approach can be widely applied to large spatial scales in wildlife monitoring where detection probabilities differ between population states and where several methods are being used to estimate different population parameters.     

Climate, hydrologic disturbance, and succession: drivers of floodplain pattern

Floodplains are among the world's most threatened ecosystems due to the pervasiveness of dams, levee systems, and other modifications to rivers. Few unaltered floodplains remain where we may examine their dynamics over decadal time scales. Our study provides a detailed examination of landscape change over a 60-year period (1945-2004) on the Nyack floodplain of the Middle Fork of the Flathead River, a free-flowing, gravel-bed river in northwest Montana, USA. We used historical aerial photographs and airborne and satellite imagery to delineate habitats (i.e., mature forest, regenerative forest, water, cobble) within the floodplain. We related changes in the distribution and size of these habitats to hydrologic disturbance and regional climate. Results show a relationship between changes in floodplain habitats and annual flood magnitude, as well as between hydrology and the cooling and warming phases of the Pacific Decadal Oscillation (PDO). Large magnitude floods and greater frequency of moderate floods were associated with the cooling phases of the PDO, resulting in a floodplain environment dominated by extensive restructuring and regeneration of floodplain habitats. Conversely, warming phases of the PDO corresponded with decreases in magnitude, duration, and frequency of critical flows, creating a floodplain environment dominated by late successional vegetation and low levels of physical restructuring. Over the 60-year time series, habitat change was widespread throughout the floodplain, though the relative abundances of the habitats did not change greatly. We conclude that the long- and short-term interactions of climate, floods, and plant succession produce a shifting habitat mosaic that is a fundamental attribute of natural floodplain ecosystems.     

Toward a Management Framework for Networks of Protected Areas in the Face of Climate Change

Abstract: Networks of sites of high importance for conservation of biological diversity are a cornerstone of current conservation strategies but are fixed in space and time. As climate change progresses, substantial shifts in species’ ranges may transform the ecological community that can be supported at a given site. Thus, some species in an existing network may not be protected in the future or may be protected only if they can move to sites that in future provide suitable conditions. We developed an approach to determine appropriate climate‐change adaptation strategies for individual sites within a network that was based on projections of future changes in the relative proportions of emigrants (species for which a site becomes climatically unsuitable), colonists (species for which a site becomes climatically suitable), and persistent species (species able to remain within a site despite the climatic change). Our approach also identifies key regions where additions to a network could enhance its future effectiveness. Using the sub‐Saharan African Important Bird Area (IBA) network as a case study, we found that appropriate conservation strategies for individual sites varied widely across sub‐Saharan Africa, and key regions where new sites could help increase network robustness varied in space and time. Although these results highlight the potential difficulties within any planning framework that seeks to address climate‐change adaptation needs, they demonstrate that such planning frameworks are necessary, if current conservation strategies are to be adapted effectively, and feasible, if applied judiciously.     

A Multispecies Framework for Landscape Conservation Planning

Abstract: Rapidly changing landscapes have spurred the need for quantitative methods for conservation assessment and planning that encompass large spatial extents. We devised and tested a multispecies framework for conservation planning to complement single‐species assessments and ecosystem‐level approaches. Our framework consisted of 4 elements: sampling to effectively estimate population parameters, measuring how human activity affects landscapes at multiple scales, analyzing the relation between landscape characteristics and individual species occurrences, and evaluating and comparing the responses of multiple species to landscape modification. We applied the approach to a community of terrestrial birds across 25,000 km² with a range of intensities of human development. Human modification of land cover, road density, and other elements of the landscape, measured at multiple spatial extents, had large effects on occupancy of the 67 species studied. Forest composition within 1 km of points had a strong effect on occupancy of many species and a range of negative, intermediate, and positive associations. Road density within 1 km of points, percent evergreen forest within 300 m, and distance from patch edge were also strongly associated with occupancy for many species. We used the occupancy results to group species into 11 guilds that shared patterns of association with landscape characteristics. Our multispecies approach to conservation planning allowed us to quantify the trade‐offs of different scenarios of land‐cover change in terms of species occupancy.