Quantifying the impact of vegetation-based metrics on species persistence when choosing offsets for habitat destruction

Developers are often required by law to offset environmental impacts through targeted conservation actions. Most offset policies specify metrics for calculating offset requirements, usually by assessing vegetation condition. Despite widespread use, there is little evidence to support the effectiveness of vegetation-based metrics for ensuring biodiversity persistence. We compared long-term impacts of biodiversity offsetting based on area only; vegetation condition only; area × habitat suitability; and condition × habitat suitability in development and restoration simulations for the Hunter Region of New South Wales, Australia. We simulated development and subsequent offsetting through restoration within a virtual landscape, linking simulations to population viability models for 3 species. Habitat gains did not ensure species persistence. No net loss was achieved when performance of offsetting was assessed in terms of amount of habitat restored, but not when outcomes were assessed in terms of persistence. Maintenance of persistence occurred more often when impacts were avoided, giving further support to better enforce the avoidance stage of the mitigation hierarchy. When development affected areas of high habitat quality for species, persistence could not be guaranteed. Therefore, species must be more explicitly accounted for in offsets, rather than just vegetation or habitat alone. Declines due to a failure to account directly for species population dynamics and connectivity overshadowed the benefits delivered by producing large areas of high-quality habitat. Our modeling framework showed that the benefits delivered by offsets are species specific and that simple vegetation-based metrics can give misguided impressions on how well biodiversity offsets achieve no net loss.     

Consequences of ignoring dispersal variation in network models for landscape connectivity

Habitat loss and fragmentation can negatively influence population persistence and biodiversity, but the effects can be mitigated if species successfully disperse between isolated habitat patches. Network models are the primary tool for quantifying landscape connectivity, yet in practice, an overly simplistic view of species dispersal is applied. These models often ignore individual variation in dispersal ability under the assumption that all individuals move the same fixed distance with equal probability. We developed a modeling approach to address this problem. We incorporated dispersal kernels into network models to determine how individual variation in dispersal alters understanding of landscape-level connectivity and implemented our approach on a fragmented grassland landscape in Minnesota. Ignoring dispersal variation consistently overestimated a population's robustness to local extinctions and underestimated its robustness to local habitat loss. Furthermore, a simplified view of dispersal underestimated the amount of habitat substructure for small populations but overestimated habitat substructure for large populations. Our results demonstrate that considering biologically realistic dispersal alters understanding of landscape connectivity in ecological theory and conservation practice.     

Fire and forest landscapes in the Georgia Piedmont: an assessment of spatial modeling assumptions

Landscape simulation models are widely used to study the behavior of ecological systems. As computing power has increased, these models have become more complex and incorporated more realistic spatial representations of landscape patterns and ecological processes. The goal of this research was to examine the sensitivity of simulated landscape patterns to fundamental spatial modeling assumptions. The LANDIS simulator was parameterized for forests of the Georgia Piedmont and used to model landscape-scale community dynamics at fire return intervals from 20 to 100 years. A base scenario incorporating localized seed dispersal along with landform-related variation in species establishment rates and disturbance regimes was contrasted with three alternative scenarios. The uniform habitat scenario applied the same set of species establishment coefficients across all landforms. The uniform dispersal scenario removed the effects of seed source abundance and pattern on species establishment. The uniform disturbance scenario assumed identical disturbance regimes on all landforms.At the shortest fire return intervals, fire severities were low and the stand age distribution was dominated by older forests. At longer fire return intervals, fire severities were high and the stand age distribution was skewed toward younger forests. Species composition generally followed a gradient from fire-resistant species at short fire return intervals to fire-sensitive species at longer fire return intervals. However, some species exhibited bimodal distributions with high abundances at both short and long fire return intervals. Landscape responses to fire were similar in the uniform habitat scenario and the base scenario. Communities were less sensitive to fire return interval and had more fire-sensitive species in the uniform dispersal scenario than in the base scenario. Species composition in the uniform disturbance scenario was similar to the base scenario for the longest fire-intervals, but was more sensitive to changes in the fire regime at shorter fire return intervals. In models of Piedmont forest landscapes, accurate spatial representations of dispersal and fire regime heterogeneity are essential for predicting landscape-scale species composition under changing fire regimes. In contrast, the precise spatial representation of species–habitat relationships may be considerably less important.     

Use of stochastic patch occupancy models in the California red-legged frog for Bayesian inference regarding past events and future persistence

Assessing causes of population decline is critically important to management of threatened species. Stochastic patch occupancy models (SPOMs) are popular tools for examining spatial and temporal dynamics of populations when presence–absence data in multiple habitat patches are available. We developed a Bayesian Markov chain method that extends existing SPOMs by focusing on past environmental changes that may have altered occupancy patterns prior to the beginning of data collection. Using occupancy data from 3 creeks, we applied the method to assess 2 hypothesized causes of population decline—in situ die-off and residual impact of past source population loss—in the California red-legged frog. Despite having no data for the 20–30 years between the hypothetical event leading to population decline and the first data collected, we were able to discriminate among hypotheses, finding evidence that in situ die-off increased in 2 of the creeks. Although the creeks had comparable numbers of occupied segments, owing to different extinction–colonization dynamics, our model predicted an 8-fold difference in persistence probabilities of their populations to 2030. Adding a source population led to a greater predicted persistence probability than did decreasing the in situ die-off, emphasizing that reversing the deleterious impacts of a disturbance may not be the most efficient management strategy. We expect our method will be useful for studying dynamics and evaluating management strategies of many species.     

Meta‐Analysis of the Effects of Forest Fragmentation on Interspecific Interactions

Forest fragmentation dramatically alters species persistence and distribution and affects many ecological interactions among species. Recent studies suggest that mutualisms, such as pollination and seed dispersal, are more sensitive to the negative effects of forest fragmentation than antagonisms, such as predation or herbivory. We applied meta‐analytical techniques to evaluate this hypothesis and quantified the relative contributions of different components of the fragmentation process (decreases in fragment size, edge effects, increased isolation, and habitat degradation) to the overall effect. The effects of fragmentation on mutualisms were primarily driven by habitat degradation, edge effects, and fragment isolation, and, as predicted, they were consistently more negative on mutualisms than on antagonisms. For the most studied interaction type, seed dispersal, only certain components of fragmentation had significant (edge effects) or marginally significant (fragment size) effects. Seed size modulated the effect of fragmentation: species with large seeds showed stronger negative impacts of fragmentation via reduced dispersal rates. Our results reveal that different components of the habitat fragmentation process have varying impacts on key mutualisms. We also conclude that antagonistic interactions have been understudied in fragmented landscapes, most of the research has concentrated on particular types of mutualistic interactions such as seed dispersal, and that available studies of interspecific interactions have a strong geographical bias (arising mostly from studies carried out in Brazil, Chile, and the United States). Meta‐Análisis de los Efectos de la Fragmentación del Bosque sobre las Interacciones Interespecíficas     

Use of linkage mapping and centrality analysis across habitat gradients to conserve connectivity of gray wolf populations in western North America

Centrality metrics evaluate paths between all possible pairwise combinations of sites on a landscape to rank the contribution of each site to facilitating ecological flows across the network of sites. Computational advances now allow application of centrality metrics to landscapes represented as continuous gradients of habitat quality. This avoids the binary classification of landscapes into patch and matrix required by patch-based graph analyses of connectivity. It also avoids the focus on delineating paths between individual pairs of core areas characteristic of most corridor- or linkage-mapping methods of connectivity analysis. Conservation of regional habitat connectivity has the potential to facilitate recovery of the gray wolf (Canis lupus), a species currently recolonizing portions of its historic range in the western United States. We applied 3 contrasting linkage-mapping methods (shortest path, current flow, and minimum-cost-maximum-flow) to spatial data representing wolf habitat to analyze connectivity between wolf populations in central Idaho and Yellowstone National Park (Wyoming). We then applied 3 analogous betweenness centrality metrics to analyze connectivity of wolf habitat throughout the northwestern United States and southwestern Canada to determine where it might be possible to facilitate range expansion and interpopulation dispersal. We developed software to facilitate application of centrality metrics. Shortest-path betweenness centrality identified a minimal network of linkages analogous to those identified by least-cost-path corridor mapping. Current flow and minimum-cost-maximum-flow betweenness centrality identified diffuse networks that included alternative linkages, which will allow greater flexibility in planning. Minimum-cost-maximum-flow betweenness centrality, by integrating both land cost and habitat capacity, allows connectivity to be considered within planning processes that seek to maximize species protection at minimum cost. Centrality analysis is relevant to conservation and landscape genetics at a range of spatial extents, but it may be most broadly applicable within single- and multispecies planning efforts to conserve regional habitat connectivity.     

Validating graph-based connectivity models with independent presence–absence and genetic data sets

Habitat connectivity is a key objective of current conservation policies and is commonly modeled by landscape graphs (i.e., sets of habitat patches [nodes] connected by potential dispersal paths [links]). These graphs are often built based on expert opinion or species distribution models (SDMs) and therefore lack empirical validation from data more closely reflecting functional connectivity. Accordingly, we tested whether landscape graphs reflect how habitat connectivity influences gene flow, which is one of the main ecoevolutionary processes. To that purpose, we modeled the habitat network of a forest bird (plumbeous warbler [Setophaga plumbea]) on Guadeloupe with graphs based on expert opinion, Jacobs’ specialization indices, and an SDM. We used genetic data (712 birds from 27 populations) to compute local genetic indices and pairwise genetic distances. Finally, we assessed the relationships between genetic distances or indices and cost distances or connectivity metrics with maximum-likelihood population-effects distance models and Spearman correlations between metrics. Overall, the landscape graphs reliably reflected the influence of connectivity on population genetic structure; validation R² was up to 0.30 and correlation coefficients were up to 0.71. Yet, the relationship among graph ecological relevance, data requirements, and construction and analysis methods was not straightforward because the graph based on the most complex construction method (species distribution modeling) sometimes had less ecological relevance than the others. Cross-validation methods and sensitivity analyzes allowed us to make the advantages and limitations of each construction method spatially explicit. We confirmed the relevance of landscape graphs for conservation modeling but recommend a case-specific consideration of the cost-effectiveness of their construction methods. We hope the replication of independent validation approaches across species and landscapes will strengthen the ecological relevance of connectivity models.     

The effects of habitat loss, fragmentation, and community homogenization on resilience in estuaries.

When changes in the frequency and extent of disturbance outstrip the recovery potential of resident communities, the selective removal of species contributes to habitat loss and fragmentation across landscapes. The degree to which habitat change is likely to influence community resilience will depend on metacommunity structure and connectivity. Thus ecological connectivity is central to understanding the potential for cumulative effects to impact upon diversity. The importance of these issues to coastal marine communities, where the prevailing concept of open communities composed of highly dispersive species is being challenged, indicates that these systems may be more sensitive to cumulative impacts than previously thought. We conducted a disturbance-recovery experiment across gradients of community type and environmental conditions to assess the roles of ecological connectivity and regional variations in community structure on the recovery of species richness, total abundance, and community composition in Mahurangi Harbour, New Zealand. After 394 days, significant differences in recovery between sites were apparent. Statistical models explaining a high proportion of the variability (R2 > 0.92) suggested that community recovery rates were controlled by a combination of physical and ecological features operating across spatial scales, affecting successional processes. The dynamic and complex interplay of ecological and environmental processes we observed driving patch recovery across the estuarine landscape are integral to recovery from disturbances in heterogeneous environments. This link between succession/recovery, disturbance, and heterogeneity confirms the utility of disturbance-recovery experiments as assays for cumulative change due to fragmentation and habitat change in estuaries.     

Comparing spatial conservation prioritization methods with site- versus spatial dependency-based connectivity

Larval dispersal is an important component of marine reserve networks. Two conceptually different approaches to incorporate dispersal connectivity into spatial planning of these networks exist, and it is an open question as to when either is most appropriate. Candidate reserve sites can be selected individually based on local properties of connectivity or on a spatial dependency-based approach of selecting clusters of strongly connected habitat patches. The first acts on individual sites, whereas the second acts on linked pairs of sites. We used a combination of larval dispersal simulations representing different seascapes and case studies of biophysical larval dispersal models in the Coral Triangle region and the province of Southeast Sulawesi, Indonesia, to compare the performance of these 2 methods in the spatial planning software Marxan. We explored the reserve design performance implications of different dispersal distances and patterns based on the equilibrium settlement of larvae in protected and unprotected areas. We further assessed different assumptions about metapopulation contributions from unprotected areas, including the case of 100% depletion and more moderate scenarios. The spatial dependency method was suitable when dispersal was limited, a high proportion of the area of interest was substantially degraded, or the target amount of habitat protected was low. Conversely, when subpopulations were well connected, the 100% depletion was relaxed, or more habitat was protected, protecting individual sites with high scores in metrics of connectivity was a better strategy. Spatial dependency methods generally produced more spatially clustered solutions with more benefits inside than outside reserves compared with site-based methods. Therefore, spatial dependency methods potentially provide better results for ecological persistence objectives over enhancing fisheries objectives, and vice versa. Different spatial prioritization methods of using connectivity are appropriate for different contexts, depending on dispersal characteristics, unprotected area contributions, habitat protection targets, and specific management objectives. Comparación entre los métodos de priorización de la conservación espacial con sitio y la conectividad espacial basada en la dependencia     

A multispecies test of source–sink indicators to prioritize habitat for declining populations

For species at risk of decline or extinction in source–sink systems, sources are an obvious target for habitat protection actions. However, the way in which source habitats are identified and prioritized can reduce the effectiveness of conservation actions. Although sources and sinks are conceptually defined using both demographic and movement criteria, simplifications are often required in systems with limited data. To assess the conservation outcomes of alternative source metrics and resulting prioritizations, we simulated population dynamics and extinction risk for 3 endangered species. Using empirically based habitat population models, we linked habitat maps with measured site‐ or habitat‐specific demographic conditions, movement abilities, and behaviors. We calculated source–sink metrics over a range of periods of data collection and prioritized consistently high‐output sources for conservation. We then tested whether prioritized patches identified the habitats that most affected persistence by removing them and measuring the population response. Conservation decisions based on different source–sink metrics and durations of data collection affected species persistence. Shorter time series obscured the ability of metrics to identify influential habitats, particularly in temporally variable and slowly declining populations. Data‐rich source–sink metrics that included both demography and movement information did not always identify the habitats with the greatest influence on extinction risk. In some declining populations, patch abundance better predicted influential habitats for short‐term regional persistence. Because source–sink metrics (i.e., births minus deaths; births and immigrations minus deaths and emigration) describe net population conditions and cancel out gross population counts, they may not adequately identify influential habitats in declining populations. For many nonequilibrium populations, new metrics that maintain the counts of individual births, deaths, and movement may provide additional insight into habitats that most influence persistence.     

Developing Metapopulation Connectivity Criteria from Genetic and Habitat Data to Recover the Endangered Mexican Wolf

Restoring connectivity between fragmented populations is an important tool for alleviating genetic threats to endangered species. Yet recovery plans typically lack quantitative criteria for ensuring such population connectivity. We demonstrate how models that integrate habitat, genetic, and demographic data can be used to develop connectivity criteria for the endangered Mexican wolf (Canis lupus baileyi), which is currently being restored to the wild from a captive population descended from 7 founders. We used population viability analysis that incorporated pedigree data to evaluate the relation between connectivity and persistence for a restored Mexican wolf metapopulation of 3 populations of equal size. Decreasing dispersal rates greatly increased extinction risk for small populations (<150–200), especially as dispersal rates dropped below 0.5 genetically effective migrants per generation. We compared observed migration rates in the Northern Rocky Mountains (NRM) wolf metapopulation to 2 habitat‐based effective distance metrics, least‐cost and resistance distance. We then used effective distance between potential primary core populations in a restored Mexican wolf metapopulation to evaluate potential dispersal rates. Although potential connectivity was lower in the Mexican wolf versus the NRM wolf metapopulation, a connectivity rate of >0.5 genetically effective migrants per generation may be achievable via natural dispersal under current landscape conditions. When sufficient data are available, these methods allow planners to move beyond general aspirational connectivity goals or rules of thumb to develop objective and measurable connectivity criteria that more effectively support species recovery. The shift from simple connectivity rules of thumb to species‐specific analyses parallels the previous shift from general minimum‐viable‐population thresholds to detailed viability modeling in endangered species recovery planning. Desarrollo de Criterios de Conectividad Metapoblacional a Partir de Datos Genéticos y de Hábitat para Recuperar al Lobo Mexicano en Peligro de Extinción     

The Sensitivity of Population Viability Analysis to Uncertainty about Habitat Requirements: Implications for the Management of the Endangered Southern Brown Bandicoot

Abstract:  Whenever population viability analysis (PVA) models are built to help guide decisions about the management of rare and threatened species, an important component of model building is the specification of a habitat model describing how a species is related to landscape or bioclimatic variables. Model-selection uncertainty may arise because there is often a great deal of ambiguity about which habitat model structure best approximates the true underlying biological processes. The standard approach to incorporate habitat models into PVA is to assume the best habitat model is correct, ignoring habitat-model uncertainty and alternative model structures that may lead to quantitatively different conclusions and management recommendations. Here we provide the first detailed examination of the influence of habitat-model uncertainty on the ranking of management scenarios from a PVA model. We evaluated and ranked 6 management scenarios for the endangered southern brown bandicoot ( Isoodon obesulus ) with PVA models, each derived from plausible competing habitat models developed with logistic regression. The ranking of management scenarios was sensitive to the choice of the habitat model used in PVA predictions. Our results demonstrate the need to incorporate methods into PVA that better account for model uncertainty and highlight the sensitivity of PVA to decisions made during model building. We recommend that researchers search for and consider a range of habitat models when undertaking model-based decision making and suggest that routine sensitivity analyses should be expanded to include an analysis of the impact of habitat-model uncertainty and assumptions.     

Effects of crowding due to habitat loss on species assemblage patterns

Terrestrial animals are negatively affected by habitat loss, which is assessed on a landscape scale, whereas secondary effects of habitat loss, such as crowding, are usually disregarded. Such impacts are inherently hard to address and poorly understood, and there is a growing concern that they could have dire consequences. We sampled birds throughout a deforestation process to assess crowding stress in an adjacent habitat remnant in the southern Brazilian Atlantic Forest. Crowding is expected of highly mobile taxa, especially given the microhabitat heterogeneity of Neotropical forests, and we hypothesized that the arrival of new individuals or species in refuges shifts assemblage patterns. We used point counts to obtain bird abundances in a before-after-control-impact design sampling of a deforestation event. Temporal changes in taxonomic and functional diversity were examined with metrics used to assess alpha and beta diversity, turnover of taxonomic and functional similarity, and taxonomic and functional composition. Over time increased abundance of some species altered the Simpson index and affected the abundance-distribution of traits in the habitat remnant. Taxonomic composition and functional composition changed in the remnant, and thus bird assemblages changed over time. Taxonomic and functional metrics indicated that fugitives affected resident assemblages in refuges, and effects endured >2 years after the deforestation processes had ceased. Dissimilarity of taxonomic composition between pre- and postdeforestation assemblages increased, whereas functional composition reverted to preimpact conditions. We found that ecological disruptions resulted from crowding and escalated into disruptions of species’ assemblages and potentially compromising ecosystem functioning. It is important to consider crowding effects of highly mobile taxa during impact assessments, especially in large-scale infrastructure projects that may affect larger areas than is assumed.     

Defining and Evaluating the Umbrella Species Concept for Conserving and Restoring Landscape Connectivity

Conserving or restoring landscape connectivity between patches of breeding habitat is a common strategy to protect threatened species from habitat fragmentation. By managing connectivity for some species, usually charismatic vertebrates, it is often assumed that these species will serve as conservation umbrellas for other species. We tested this assumption by developing a quantitative method to measure overlap in dispersal habitat of 3 threatened species—a bird (the umbrella), a butterfly, and a frog—inhabiting the same fragmented landscape. Dispersal habitat was determined with Circuitscape, which was parameterized with movement data collected for each species. Despite differences in natural history and breeding habitat, we found substantial overlap in the spatial distributions of areas important for dispersal of this suite of taxa. However, the intuitive umbrella species (the bird) did not have the highest overlap with other species in terms of the areas that supported connectivity. Nevertheless, we contend that when there are no irreconcilable differences between the dispersal habitats of species that cohabitate on the landscape, managing for umbrella species can help conserve or restore connectivity simultaneously for multiple threatened species with different habitat requirements. Definición y Evaluación del Concepto de Especie Paraguas para Conservar y Restaurar la Conectividad de Paisajes     

Testing the robustness of management decisions to uncertainty: Everglades restoration scenarios.

To effectively manage large natural reserves, resource managers must prepare for future contingencies while balancing the often conflicting priorities of different stakeholders. To deal with these issues, managers routinely employ models to project the response of ecosystems to different scenarios that represent alternative management plans or environmental forecasts. Scenario analysis is often used to rank such alternatives to aid the decision making process. However, model projections are subject to uncertainty in assumptions about model structure, parameter values, environmental inputs, and subcomponent interactions. We introduce an approach for testing the robustness of model-based management decisions to the uncertainty inherent in complex ecological models and their inputs. We use relative assessment to quantify the relative impacts of uncertainty on scenario ranking. To illustrate our approach we consider uncertainty in parameter values and uncertainty in input data, with specific examples drawn from the Florida Everglades restoration project. Our examples focus on two alternative 30-year hydrologic management plans that were ranked according to their overall impacts on wildlife habitat potential. We tested the assumption that varying the parameter settings and inputs of habitat index models does not change the rank order of the hydrologic plans. We compared the average projected index of habitat potential for four endemic species and two wading-bird guilds to rank the plans, accounting for variations in parameter settings and water level inputs associated with hypothetical future climates. Indices of habitat potential were based on projections from spatially explicit models that are closely tied to hydrology. For the American alligator, the rank order of the hydrologic plans was unaffected by substantial variation in model parameters. By contrast, simulated major shifts in water levels led to reversals in the ranks of the hydrologic plans in 24.1-30.6% of the projections for the wading bird guilds and several individual species. By exposing the differential effects of uncertainty, relative assessment can help resource managers assess the robustness of scenario choice in model-based policy decisions.     

Ranking individual habitat patches as connectivity providers: Integrating network analysis and patch removal experiments

Here we propose an integrated framework for modeling connectivity that can help ecologists, conservation planners and managers to identify patches that, more than others, contribute to uphold species dispersal and other ecological flows in a landscape context. We elaborate, extend and partly integrate recent network-based approaches for modeling and supporting the management of fragmented landscapes. In doing so, experimental patch removal techniques and network analytical approaches are merged into one integrated modeling framework for assessing the role of individual patches as connectivity providers. In particular, we focus the analyses on the habitat availability metrics PC and IIC and on the network metric Betweenness Centrality. The combination and extension of these metrics jointly assess both the immediate connectivity impacts of the loss of a particular patch and the resulting increased vulnerability of the network to subsequent disruptions. In using the framework to analyze the connectivity of two real landscapes in Madagascar and Catalonia (NE Spain), we suggest a procedure that can be used to rank individual habitat patches and show that the combined metrics reveal relevant and non-redundant information valuable to assert and quantify distinctive connectivity aspects of any given patch in the landscape. Hence, we argue that the proposed framework could facilitate more ecologically informed decision-making in managing fragmented landscapes. Finally, we discuss and highlight some of the advantages, limitations and key differences between the considered metrics.     

Patch Size and Connectivity Thresholds for Butterfly Habitat Restoration

Abstract:  Recovery of endangered species in highly fragmented habitats often requires habitat restoration. Selection of restoration sites typically involves too many options and too much uncertainty to reach a decision based on existing reserve design methods. The Fender's blue butterfly (  Icaricia icarioides fenderi ) survives in small, isolated patches of remnant prairie in Oregon's Willamette Valley—a habitat for which <0.5% of the original remains. Recovery of this species will require considerable habitat restoration. We investigated the potential of biologically based rules of thumb and more complex models to serve as tools in making land acquisitions. Based on Fender's blue dispersal behavior and demography, we have estimated that restored patches should be <1 km from existing habitat and at least 2 ha. We compared these rules to the results of two modeling approaches: an incidence function model and a spatially explicit simulation of demography and dispersal behavior. Not surprisingly, the simple rules and complex models all conclude that large (>2 ha) connected (<1 km) patches have the highest restoration value. The dispersal model, however, suggests that small, connected patches have more restoration value than large, isolated patches, whereas the incidence function model suggests that size and connectivity are equally important. These differences stem from model assumptions. We used incidence functions to predict long-term, stochastic, steady-state conditions and dispersal simulations to predict short-term (25-year) colonization dynamics. To apply our results in the context of selecting restoration sites on the ground, we recommend selecting nearby sites when short-term colonization dynamics are expected to be an important aspect of a species' biology.     

Predicted Climate‐Driven Bird Distribution Changes and Forecasted Conservation Conflicts in a Neotropical Savanna

Abstract: Climate‐change scenarios project significant temperature changes for most of South America. We studied the potential impacts of predicted climate‐driven change on the distribution and conservation of 26 broad‐range birds from South America Cerrado biome (a savanna that also encompass tracts of grasslands and forests). We used 12 temperature or precipitation‐related bioclimatic variables, nine niche modeling techniques, three general circulation models, and two climate scenarios (for 2030, 2065, 2099) for each species to model distribution ranges. To reach a consensus scenario, we used an ensemble‐forecasting approach to obtain an average distribution for each species at each time interval. We estimated the range extent and shift of each species. Changes in range size varied across species and according to habitat dependency; future predicted range extent was negatively correlated with current predicted range extent in all scenarios. Evolution of range size under full or null dispersal scenarios varied among species from a 5% increase to an 80% decrease. The mean expected range shifts under null and full‐dispersal scenarios were 175 and 200 km, respectively (range 15–399 km), and the shift was usually toward southeastern Brazil. We predicted larger range contractions and longer range shifts for forest‐ and grassland‐dependent species than for savanna‐dependent birds. A negative correlation between current range extent and predicted range loss revealed that geographically restricted species may face stronger threat and become even rarer. The predicted southeasterly direction of range changes is cause for concern because ranges are predicted to shift to the most developed and populated region of Brazil. Also, southeastern Brazil is the least likely region to contain significant dispersal corridors, to allow expansion of Cerrado vegetation types, or to accommodate creation of new reserves.     

Dispersal, competition, and shifting patterns of diversity in a degraded oak savanna

Diversity is a balance between processes that add and limit species (e.g., dispersal vs. competition), but reconciling their contributions remains a challenge. Recruit-ment-based models predict that dispersal barriers are most limiting for diversity, while competition-based models predict that dispersal matters only when competition is minimized. Testing these models is difficult because their influence varies with scale and site productivity. In a degraded oak savanna, we used plot-level (seed additions, burning) and site-level (proportions of regional functional groups found locally) analyses in areas with variable soil depth to examine how dispersal and competition influence diversity. At the plot level, added species persisted where they were formerly absent, but few established naturally despite fire-induced resource enrichment and nearby populations, revealing the importance of dispersal limitation for diversity. This result did not vary with soil depth or standing crop. Although competition could not prevent establishment in unburned plots, it significantly lowered survival, indicating that resource limitations exacerbate dispersal inefficiencies. At the site level, the concordance between regional and local diversity for native species was associated with soil depth heterogeneity, not dispersal or competition. This suggests that persistence is determined primarily by the influence of the environment on population demographics. Given that the formation of new populations is unlikely, those remaining appear to be confined to optimal habitat where they resist competitive or stochastic displacement, possibly explaining why species loss is rare despite substantial habitat loss and invasion. For exotics, there was no relationship between diversity and soil depth heterogeneity. Annuals with presumed dispersal capabilities were significantly overrepresented in all sites while perennial forbs, the largest regional functional group, were significantly underrepresented. We interpret the native-exotic discrepancies as reflecting the recent arrival of exotics (150 years ago), suggesting that local establishment occurs slowly even for species with regional prevalence. The accumulation lag may be explained by the need for founder populations to be demographically stable; otherwise persistence requires continual immigration favoring overrepresentation by dispersers. Our findings support the view that dispersal limitation restricts diversity within plant communities, but suggests that the impacts of environment on demographic performance ultimately determine the pattern and rate of community assembly.     

Effects of life history and reproduction on recruitment time lags in reintroductions of rare plants

Reintroductions are important components of conservation and recovery programs for rare plant species, but their long-term success rates are poorly understood. Previous reviews of plant reintroductions focused on short-term (e.g., ≤3 years) survival and flowering of founder individuals rather than on benchmarks of intergenerational persistence, such as seedling recruitment. However, short-term metrics may obscure outcomes because the unique demographic properties of reintroductions, including small size and unstable stage structure, could create lags in population growth. We used time-to-event analysis on a database of unusually well-monitored and long-term (4–28 years) reintroductions of 27 rare plant species to test whether life-history traits and population characteristics of reintroductions create time-lagged responses in seedling recruitment (i.e., recruitment time lags [RTLs]), an important benchmark of success and indicator of persistence in reintroduced populations. Recruitment time lags were highly variable among reintroductions, ranging from <1 to 17 years after installation. Recruitment patterns matched predictions from life-history theory with short-lived species (fast species) exhibiting consistently shorter and less variable RTLs than long-lived species (slow species). Long RTLs occurred in long-lived herbs, especially in grasslands, whereas short RTLs occurred in short-lived subtropical woody plants and annual herbs. Across plant life histories, as reproductive adult abundance increased, RTLs decreased. Highly variable RTLs were observed in species with multiple reintroduction events, suggesting local processes are just as important as life-history strategy in determining reintroduction outcomes. Time lags in restoration outcomes highlight the need to scale success benchmarks in reintroduction monitoring programs with plant life-history strategies and the unique demographic properties of restored populations. Drawing conclusions on the long-term success of plant reintroduction programs is premature given that demographic processes in species with slow life-histories take decades to unfold.