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As the human footprint upon the landscape expands, wildlife seeking to avoid human contact are losing the option of altering their spatial distribution and instead are shifting their daily activity patterns to be active at different times than humans. In this study, we used game cameras to evaluate how human development and activity were related to the daily activity patterns of the nine‐banded armadillo (Dasypus novemcinctus) along an urban to rural gradient in Arkansas, USA during the winter of 2020–2021. We found that armadillos had substantial behavioral plasticity in regard to the timing of their activity patterns; >95% of armadillo activity was nocturnal at six of the study sites, whereas between 30% and 60% of activity occurred during the day at three other sites. The likelihood of diurnal armadillo activity was best explained by the distance to downtown Fayetteville (the nearest population center) and estimated ambient sound level (both indices of human activity) with armadillos being most active during the day at quiet sites far from Fayetteville. Furthermore, armadillo activity occurred later during the night period (minutes after sunset) at sites near downtown and with higher anthropogenic sound. Anecdotal evidence suggests that the observed activity shift may be in response to not only human activity but also the presence of domestic dogs. Our results provide further evidence that human activity has subtle nonlethal impacts on even common, widespread wildlife species. Because armadillos have low body temperatures and basal metabolism, being active during cold winter nights likely has measurable fitness costs. Nature reserves near human population centers may not serve as safe harbors for wildlife as we intend, and managers could benefit from considering these nonlethal responses in how they manage recreation and visitation in these natural areas., The nine‐banded armadillo (Daspyus novemcinctus) is a widespread mammal capable of being active during the day or night. Here, we present evidence that armadillos living in proximity to humans shift their activity to be nocturnal despite likely thermal fitness costs to avoid human contact.

Patterns in disturbance severity and time since fire can drive landscape heterogeneity that is critical to conservation; however, there is limited understanding of how wildlife interact with the spatial–temporal complexities of disturbance outcomes and at what scales. We conducted multiscale modeling of habitat selection for male and female Rocky Mountain bighorn sheep (Ovis canadensis canadensis) over an 8-year period. We aimed to identify the spatial scales at which bighorn sheep responded to various habitat features and determine how fire severity and time since fire can shape habitat selection by bighorn sheep over different seasons and between sexes. With the exception of litter cover, spatial scales that extended beyond the finest spatial grain (i.e., a 30-m pixel) to include the surrounding landscape were better at predicting habitat selection. Escape terrain, elevation, fire severity, year, perennial and annual forb and grass cover, and shrub cover occurred in every best-supported model. Associations with escape terrain, elevation, and perennial and annual forb and grass cover varied by sex and season. In contrast, bighorn sheep were consistently positively associated with low- and high-severity fire. Females increased use of low- and high-severity burned areas with greater time since fire, while males tended to decrease use of areas that burned at high severity with greater time since fire. Our results support the importance of landscape heterogeneity created by fire severity and time since fire for Rocky Mountain bighorn sheep and reinforces calls to integrate disturbance-driven heterogeneity into our assessments and management of wildlife.

Historically, relying on plot-level inventories impeded our ability to quantify large-scale change in plant biomass, a key indicator of conservation practice outcomes in rangeland systems. Recent technological advances enable assessment at scales appropriate to inform management by providing spatially comprehensive estimates of productivity that are partitioned by plant functional group across all contiguous US rangelands. We partnered with the Sage Grouse and Lesser Prairie-Chicken Initiatives and the Nebraska Natural Legacy Project to demonstrate the ability of these new datasets to quantify multi-scale changes and heterogeneity in plant biomass following mechanical tree removal, prescribed fire, and prescribed grazing. In Oregon's sagebrush steppe, for example, juniper tree removal resulted in a 21% increase in one pasture's productivity and an 18% decline in another. In Nebraska's Loess Canyons, perennial grass productivity initially declined 80% at sites invaded by trees that were prescriptively burned, but then fully recovered post-fire, representing a 492% increase from nadir. In Kansas' Shortgrass Prairie, plant biomass increased 4-fold (966,809 kg/ha) in pastures that were prescriptively grazed, with gains highly dependent upon precipitation as evidenced by sensitivity of remotely sensed estimates (SD ± 951,308 kg/ha). Our results emphasize that next-generation remote sensing datasets empower land managers to move beyond simplistic control versus treatment study designs to explore nuances in plant biomass in unprecedented ways. The products of new remote sensing technologies also accelerate adaptive management and help communicate wildlife and livestock forage benefits from management to diverse stakeholders.

In this era of global environmental change and rapid regime shifts, managing core areas that species require to survive and persist is a grand challenge for conservation. Wildlife monitoring data are often limited or local in scale. The emerging ability to map and track spatial regimes (i.e., the spatial manifestation of state transitions) using advanced geospatial vegetation data has the potential to provide earlier warnings of habitat loss because many species of conservation concern strongly avoid spatial regime boundaries. Using 23 yr of data for the lek locations of Greater Prairie-Chicken (Tympanuchus cupido; GPC) in a remnant grassland ecosystem, we demonstrate how mapping changes in the boundaries between grassland and woodland spatial regimes provide a spatially explicit early warning signal for habitat loss for an iconic and vulnerable grassland-obligate known to be highly sensitive to woody plant encroachment. We tested whether a newly proposed metric for the quantification of spatial regimes captured well-known responses of GPC to woody plant expansion into grasslands. Resource selection functions showed that the grass:woody spatial regime boundary strength explained the probability of 80% of relative lek occurrence, and GPC strongly avoided grass:woody spatial regime boundaries at broad scales. Both findings are consistent with well-known expectations derived from GPC ecology. These results provide strong evidence for vegetation-derived delineations of spatial regimes to serve as generalized signals of early warning for state transitions that have major consequences to biodiversity conservation. Mapping spatial regime boundaries over time provided interpretable early warnings of habitat loss. Woody plant regimes displaced grassland regimes starting from the edges of the study area and constricting inward. Correspondingly, the relative probability of lek occurrence constricted in space. Similarly, the temporal trajectory of spatial regime boundary strength increased over time and moved closer to the observed limit of GPC lek site usage relative to grass:woody boundary strength. These novel spatial metrics allow managers to rapidly screen for early warning signals of spatial regime shifts and adapt management practices to defend and grow habitat cores at broad scales.

In the present era of rapid global change, development of early warnings of ecological regime shifts is a major focus in ecology. Identifying and tracking shifts in spatial regimes is a new approach with potential to enhance understanding of ecological responses to global change. Here, we show strong directional non-stationarity of spatial regimes identified by avian community body mass data. We do this by tracking 46 years of avian spatial regime movement in the North American Great Plains. The northernmost spatial regime boundary moved >590 km northward, and the southernmost boundary moved >260 km northward. Tracking spatial regimes affords decadal planning horizons and moves beyond the predominately temporal early warnings of the past by providing spatiotemporally explicit detection of regime shifts in systems without fixed boundaries. Highly mobile taxa, like birds, occupy ecosystems that lack fixed boundaries, and tracking how these spatial regimes respond to environmental change is difficult. Avian route data show the spatial regimes of Great Plains bird communities have shifted poleward and reorganized over the past 46 years.

Rangelands of the United States provide ecosystem services that benefit society and rural economies. Native tree encroachment is often overlooked as a primary threat to rangelands due to the slow pace of tree cover expansion and the positive public perception of trees. Still, tree encroachment fragments these landscapes and reduces herbaceous production, thereby threatening habitat quality for grassland wildlife and the economic sustainability of animal agriculture.Recent innovations in satellite remote sensing permit the tracking of tree encroachment and the corresponding impact on herbaceous production. We analyzed tree cover change and herbaceous production across the western United States from 1990 to 2019.We show that tree encroachment is widespread in U.S. rangelands; absolute tree cover has increased by 50% (77,323 km2) over 30 years, with more than 25% (684,852 km2) of U.S. rangeland area experiencing tree cover expansion. Since 1990, 302 ± 30 Tg of herbaceous biomass have been lost. Accounting for variability in livestock biomass utilization and forage value reveals that this lost production is valued at between $4.1 - $5.6 billion U.S. dollars.Synthesis and applications: The magnitude of impact of tree encroachment on rangeland loss is similar to conversion to cropland, another well-known and primary mechanism of rangeland loss in the U.S. Prioritizing conservation efforts to prevent tree encroachment can bolster ecosystem and economic sustainability, particularly among privately-owned lands threatened by land-use conversion.

Woody encroachment is a global driver of grassland loss and management to counteract encroachment represents one of the most expensive conservation practices implemented in grasslands. Yet, outcomes of these practices are often unknown at large scales and this constrains practitioner&rsquo, s ability to advance conservation. Here, we use new monitoring data to evaluate outcomes of grassland conservation on woody encroachment for Nebraska&rsquo, s State Wildlife Action Plan, a statewide effort that targets management in Biologically Unique Landscapes (BULs) to conserve the state&rsquo, s natural communities. We tracked woody cover trajectories for BULs and compared BUL trajectories with those in non-priority landscapes (non-BULs) to evaluate statewide and BUL-scale conservation outcomes more than a decade after BUL establishment. Statewide, woody cover increased by 256,653 ha (2.3%) from 2000&ndash, 2017. Most BULs (71%) experienced unsustainable trends of grassland loss to woody encroachment, however, management appeared to significantly reduce BUL encroachment rates compared to non-BULs. Most BULs with early signs of encroachment lacked control strategies, while only one BUL with moderate levels of encroachment (Loess Canyons) showed evidence of a management-driven stabilization of encroachment. These results identify strategic opportunities for proactive management in grassland conservation and demonstrate how new monitoring technology can support large-scale adaptive management pursuits.

Natural disasters, such as hurricanes and forest fires, could trigger collapse and reorganization of social-ecological systems. In the face of external perturbations, a resilient system would have capacity to absorb impacts, adapt to change, learn, and if needed, reorganize within the same regime. Within this context, we asked how human and natural systems in Louisiana responded to Hurricane Katrina, and how the natural disaster altered the status of these systems. This paper discusses community resilience to natural hazards and addresses the limitations for assessing disaster resilience. Furthermore, we assessed social and environmental change in New Orleans and southern Louisiana through both a spatial and temporal lens (i.e., pre- and post-Katrina). By analyzing changes in system condition using social, economic and environmental factors, we identified some of the characteristics of the system's reorganization trajectories. Our results suggest that although the ongoing population recovery may be a sign of revitalization, the city and metropolitan area continue to face socioeconomic inequalities and environmental vulnerability to natural disasters. Further, the spatial distribution of social-ecological condition over time reveals certain levels of change and reorganization after Katrina, but the reorganization did not translate into greater equity. This effort presents an enhanced approach to assessing social-ecological change pre and post disturbance and provides a way forward for characterizing pertinent aspects of disaster resilience.

Human activity causes biome shifts that alter biodiversity and spatial resilience patterns, ultimately challenging conservation. Rare species, often considered vulnerable to change and endangered, can be a critical element of resilience by providing adaptive capacity in response to disturbances. However, little is known about changes in rarity and dominance patterns of communities once a biome transitions into a novel spatial regime, and how this affects conservation. We used time series modeling to identify species rarity and dominance patterns in an expanding terrestrial (southern) spatial regime in the North American Great Plains and another (northern) regime that will become encroached by the southern regime in the near future. In this approach, presumably rare and abundant species show stochastic and deterministic dynamics, respectively. We specifically assessed how stochastic species of the northern spatial regime influence the resilience and adaptive capacity of a novel spatial regime once it has been encroached by the southern regime by either becoming deterministic or staying stochastic. Using 47 years (1968 – 2014) of breeding bird survey data and a space-for-time substitution, we found half of the stochastic species from the northern regime to be either deterministic or stochastic in the southern regime. However, the overall contribution of these species to the community of the southern regime was low, manifested in marginal contributions to resilience and adaptive capacity of this regime. Also, none of these species were of conservation concern, suggesting limited need for revised species conservation action in the novel spatial regime. From a systemic perspective our result suggest that while stochastic species can potentially compensate for the loss of dominant species after disturbances and maintain the system in its current regime, they may only marginally contribute to resilience and adaptive capacity in a new spatial regime after fundamental ecological changes have occurred.

Understanding the capacity of ecosystems to adapt and to cope (i.e. adaptive capacity) with change is crucial to their management. However, definitions of adaptive capacity are often unclear and confusing, making application of this concept difficult. In this paper, we revisit definitions of adaptive capacity and operationalize the concept. We define adaptive capacity as the latent potential of an ecosystem to alter resilience in response to change. We present testable hypotheses to evaluate complementary attributes of adaptive capacity that may help further clarify the components and relevance of the concept. We suggest how sampling, inference and modelling can reduce key uncertainties incrementally over time and increase learning about adaptive capacity. Improved quantitative assessments of adaptive capacity are needed because of the high uncertainty about global change and its potential effect on the capacity of ecosystems to adapt to social and ecological change. An improved understanding of adaptive capacity might ultimately allow for more efficient and targeted management.

New concepts have emerged in theoretical ecology with the intent to quantify complexities in ecological change that are unaccounted for in state-and-transition models and to provide applied ecologists with statistical early warning metrics able to predict and prevent state transitions. With its rich history of furthering ecological theory and its robust and broad-scale monitoring frameworks, the rangeland discipline is poised to empirically assess these newly proposed ideas while also serving as early adopters of novel statistical metrics that provide advanced warning of a pending shift to an alternative ecological regime. Were view multivariate early warning and regime shift detection metrics, identify situations where various metrics will be most useful for rangeland science, and then highlight known shortcomings. Our review of a suite of multivariate-based regime shift/early warning indicators provides a broad range of metrics applicable to a wide variety of data types or contexts, from situations where a great deal is known about the key system drivers and a regime shift is hypothesized a priori, to situations where the key drivers and the possibility of a regime shift are both unknown. These metrics can be used to answer ecological state-and-transition questions, inform policymakers, and provide quantitative decision-making tools for managers.

A modern challenge for conservation biology is to assess the consequences of policies that adhere to assumptions of stationarity (e.g., historic norms) in an era of global environmental change. Such policies may result in unexpected and surprising levels of mitigation given future climate-change trajectories, especially as agriculture looks to protected areas to buffer against production losses during periods of environmental extremes. We assessed the potential impact of climate-change scenarios on the rates at which grasslands enrolled in the Conservation Reserve Program (CRP) are authorized for emergency harvesting (i.e., biomass removal) for agricultural use, which can occur when precipitation for the previous 4 months is below 40% of the normal or historical mean precipitation for that 4-month period. We developed and analyzed scenarios under the condition that policy will continue to operate under assumptions of stationarity, thereby authorizing emergency biomass harvesting solely as a function of precipitation departure from historic norms. Model projections showed the historical likelihood of authorizing emergency biomass harvesting in any given year in the northern Great Plains was 33.28% based on long-term weather records. Emergency biomass harvesting became the norm (>50% of years) in the scenario that reflected continued increases in emissions and a decrease in growing-season precipitation, and areas in the Great Plains with higher historical mean annual rainfall were disproportionately affected and were subject to a greater increase in emergency biomass removal. Emergency biomass harvesting decreased only in the scenario with rapid reductions in emissions. Our scenario-impact analysis indicated that biomass from lands enrolled in the CRP would be used primarily as a buffer for agriculture in an era of climatic change unless policy guidelines are adapted or climate-change projections significantly depart from the current consensus.

Scholars from many different intellectual disciplines have attempted to measure, estimate, or quantify resilience. However, there is growing concern that lack of clarity on the operationalization of the concept will limit its application. In this paper, we discuss the theory, research development and quantitative approaches in ecological and community resilience. Upon noting the lack of methods that quantify the complexities of the linked human and natural aspects of community resilience, we identify several promising approaches within the ecological resilience tradition that may be useful in filling these gaps. Further, we discuss the challenges for consolidating these approaches into a more integrated perspective for managing social-ecological systems.

Increasing wildfires in western North American conifer forests have led to debates surrounding the application of post-fire management practices. There is a lack of consensus on whether (and to what extent) post-fire management assists or hinders managers in achieving goals, particularly in under-studied regions like eastern ponderosa pine forests. This makes it difficult for forest managers to balance among competing interests. We contrast structural and community characteristics across unburned ponderosa pine forest, severely burned ponderosa pine forest, and severely burned ponderosa pine forest treated with post-fire management with respect to three management objectives: ponderosa pine regeneration, wildland fuels control, and habitat conservation. Ponderosa pine saplings were more abundant in treated burned sites than untreated burned sites, suggesting increases in tree regeneration following tree planting, however, natural regeneration was evident in both unburned and untreated burned sites. Wildland fuels management greatly reduced snags and coarse woody debris in treated burned sites. Understory cover measurements revealed bare ground and fine woody debris were more strongly associated with untreated burned sites, and greater levels of forbs and grass were more strongly associated with treated burned sites. Wildlife habitat was greatly reduced following post-fire treatments. There were no tree cavities in treated burned sites, whereas untreated burned sites had an average of 27 &plusmn, 7.68 cavities per hectare. Correspondingly, we found almost double the avian species richness in untreated burned sites compared to treated burned sites (22 species versus 12 species). Unburned forests and untreated burned areas had the same species richness, but hosted unique avian communities. Our results indicate conflicting outcomes with respect to management objectives, most evident in the clear costs to habitat conservation following post-fire management application.

Globally, savanna ecosystems are shifting outside of “safe operating spaces” due to removal of their primary self-reinforcing feedback—fire—and subsequent erosion of disturbance legacies. Restoring savannas will require reinstating fire feedbacks. But knowledge gaps in the nature of historic fire regimes and how mechanisms such as time-since-fire and fire severity interact to produce disturbance legacies hinders development of ecologically relevant restoration targets. A theory-based approach for determining restoration targets is to compare structures produced by time-since-fire/fire severity interactions to structures that fostered animal communities that historically inhabited savannas. Here, we use a space-for-time substitution to quantify interactive effects of time-since-fire and fire severity on vegetation structures related to known animal community habitat preferences by surveying sites in 10-year-old and 27-year-old mixed-severity fires that occurred in an eastern ponderosa pine (Pinus ponderosa) savanna where fire was excluded since European settlement. Our specific objectives are to 1), quantify the relative strengths and interactive effects of time-since-fire and a full fire severity gradient on multivariate vegetation structure across landscape patches and 2), assess relationships between multivariate vegetation structures and time-since-fire/fire severity classes across landscape patches. We used a stratified random design to distribute 112 sampling plots by fire severity (unburned, low, moderate, and high) and time-since-fire (10 years and 27 years) and measured stand structure, tree cavity characteristics, and coarse woody debris. The interaction of time-since-fire and fire severity drove structure complexity for 27 years post-fire, but fire severity explained > 14 times the amount of variation in structure than time-since-fire alone. A full fire severity gradient (low-, moderate-, and high-severities) and structural changes within patches that experienced different fire severities generated sufficient patch-level heterogeneity to foster animal communities historically native to eastern ponderosa pine savannas. Structures generated by low fire severity alone, which is a common goal of fire management in easternmost ponderosa pine savannas, did not reflect sufficient structural complexity to support the diversity of endemic animal species. This indicates information legacies (i.e., represented by the distribution of species traits in a community) were shaped by mixed severity fire regimes, which provides further support for the scientific premise that management goals seeking to minimize variation in fire regimes (e.g., low intensity and low-severity fires only) is less able to support a full array of biodiversity. Rather, mixed-severity fire is an important driver of structural heterogeneity, fosters diverse information legacies, and enhances ponderosa pine savanna resilience to extreme fire.

The concept of ecological resilience (the amount of disturbance a system can absorb before collapsing and reorganizing) holds potential for predicting community change and collapse—increasingly common issues in the Anthropocene. Yet neither the predictions nor metrics of resilience have received rigorous testing. The cross-scale resilience model, a leading operationalization of resilience, proposes resilience can be quantified by the combination of diversity and redundancy of functions performed by species operating at different scales. Here, we use 48 years of sub-continental avian community data aggregated at multiple spatial scales to calculate resilience metrics derived from the cross-scale resilience model (i.e., cross-scale diversity, cross-scale redundancy, within-scale redundancy, and number of body mass aggregations) and test core predictions inherent to community persistence and change. Specifically, we ask how cross-scale resilience metrics relate community stability and collapse. We found low mean cross-correlation between species richness and cross-scale resilience metrics. Resilience metrics constrained the magnitude of community fluctuations over time (mean species turnover), but resilience metrics but did not influence variability of community fluctuations (variance in turnover). We show shifts in resilience metrics closely predict community collapse: shifts in cross-scale redundancy preceded abrupt changes in community composition, and shifts in cross-scale diversity synchronized with abrupt changes in community composition. However, we found resilience metrics only weakly relate to maintenance of particular species assemblages over time. Our results distinguish ecological resilience from ecological stability and allied concepts such as elasticity and resistance: we show communities may fluctuate widely yet still be resilient. Our findings also differentiate the roles of functional redundancy and diversity as metrics of resilience and reemphasize the importance of considering resilience metrics from a multivariate perspective. Finally, we support the contention that ecological stability is nested within ecological resilience: stability predicts the behavior of systems within an ecological regime, and resilience predicts the maintenance of regimes and behavior of systems collapsing into alternative regimes.

Disturbance legacies structure communities and ecological memory, but due to increasing changes in disturbance regimes, it is becoming more difficult to characterize disturbance legacies or determine how long they persist. We sought to quantify the characteristics and persistence of material legacies (e.g., biotic residuals of disturbance) that arise from variation in fire severity in an eastern ponderosa pine forest in North America. We compared forest stand structure and understory woody plant and bird community composition and species richness across unburned, low‐, moderate‐, and high‐severity burn patches in a 27‐year‐old mixed‐severity wildfire that had received minimal post‐fire management. We identified distinct tree densities (high: 14.3 ± 7.4 trees per ha, moderate: 22.3 ± 12.6, low: 135.3 ± 57.1, unburned: 907.9 ± 246.2) and coarse woody debris cover (high: 8.5 ± 1.6% cover per 30 m transect, moderate: 4.3 ± 0.7, low: 2.3 ± 0.6, unburned: 1.0 ± 0.4) among burn severities. Understory woody plant communities differed between high‐severity patches, moderate‐ and low‐severity patches, and unburned patches (all p

Although organisms make resource selection decisions at multiple spatiotemporal scales, not all scales are ecologically relevant to any given organism. Ecological patterns and rhythms such as behavioral and climatic patterns may provide a consistent method for identifying ecologically relevant scales of habitat selection. Using elk (Cervus canadensis) as an example species, we sought to test the ability of behavioral patterns to empirically partition diel scales for modeling habitat selection. We used model selection to partition diel scales by shifts in dominant behavior and then used resource selection probability functions to model elk habitat selection hierarchically at diel scales within seasons. Model selection distinguished four diel temporal partitions following elk crepuscular behavioral patterns: dawn, midday, dusk, and night. Across seasons, model-averaged coefficients indicated that elk shifted from selecting grassland cover at dawn/dusk, to selecting for greater canopy and forest cover at midday, and then to areas with greater herbaceous biomass at night. Top models changed between diel intervals in spring and fall but stayed the same across diel intervals in winter and summer. In winter, elk selected for southern aspects during midday, for unburned areas at dawn/dusk, and for areas burned within 1–3 yr at dawn/dusk and night. In spring, elk selected for northern aspects and for areas burned within 1–3 yr at midday, for areas farther from roads at dawn/dusk and midday, and for areas farther from water at midday. In summer, elk changed diel preferences for fewer covariates: At dawn/dusk and midday, elk selected for areas farther from water and avoided forest cover, and at night, elk selected for areas burned within 1–3 yr. In fall, elk selected for areas burned the previous year at dawn/dusk and night, for higher elevations at midday, and for areas closer water at night. Using behavioral patterns to identify ecologically relevant scales can help identify overlooked habitat requirements such as diel changes in preference for fire history, forage availability, and cover. We show that the ecological relevancy of a given scale (e.g., a diel temporal scale) can change throughout a given extent (e.g., across seasons).

A modern challenge for conservation biology is to assess the consequences of policies that adhere to assumptions of stationarity (e.g., historic norms) in an era of global environmental change. Such policies may result in unexpected and surprising levels of mitigation given future climate-change trajectories, especially as agriculture looks to protected areas to buffer against production losses during periods of environmental extremes. We assessed the potential impact of climate-change scenarios on the rates at which grasslands enrolled in the Conservation Reserve Program (CRP) are authorized for emergency harvesting (i.e., biomass removal) for agricultural use, which can occur when precipitation for the previous 4 months is below 40% of the normal or historical mean precipitation for that 4-month period. We developed and analyzed scenarios under the condition that policy will continue to operate under assumptions of stationarity, thereby authorizing emergency biomass harvesting solely as a function of precipitation departure from historic norms. Model projections showed the historical likelihood of authorizing emergency biomass harvesting in any given year in the northern Great Plains was 33.28% based on long-term weather records. Emergency biomass harvesting became the norm (50% of years) in the scenario that reflected continued increases in emissions and a decrease in growing-season precipitation, and areas in the Great Plains with higher historical mean annual rainfall were disproportionately affected and were subject to a greater increase in emergency biomass removal. Emergency biomass harvesting decreased only in the scenario with rapid reductions in emissions. Our scenario-impact analysis indicated that biomass from lands enrolled in the CRP would be used primarily as a buffer for agriculture in an era of climatic change unless policy guidelines are adapted or climate-change projections significantly depart from the current consensus.

Mismatches between invasive species management policies and ecological knowledge can lead to profound societal consequences. For this reason, natural resource agencies have adopted the scientifically-based density-impact invasive species curve to guide invasive species management. We use the density-impact model to evaluate how well management policies for a native invader (Juniperus virginiana) match scientific guidelines. Juniperus virginiana invasion is causing a sub-continental regime shift from grasslands to woodlands in central North America, and its impacts span collapses in endemic diversity, heightened wildfire risk, and crashes in grazing land profitability. We (1) use land cover data to identify the stage of Juniperus virginiana invasion for three ecoregions within Nebraska, USA, (2) determine the range of invasion stages at individual land parcel extents within each ecoregion based on the density-impact model, and (3) determine policy alignment and mismatches relative to the density-impact model in order to assess their potential to meet sustainability targets and avoid societal impacts as Juniperus virginiana abundance increases. We found that nearly all policies evidenced doublethink and policy-ecology mismatches, for instance, promoting spread of Juniperus virginiana regardless of invasion stage while simultaneously managing it as a native invader in the same ecoregion. Like other invasive species, theory and literature for this native invader indicate that the consequences of invasion are unlikely to be prevented if policies fail to prioritize management at incipient invasion stages. Theory suggests a more realistic approach would be to align policy with the stage of invasion at local and ecoregion management scales. There is a need for scientists, policy makers, and ecosystem managers to move past ideologies governing native versus non-native invader classification and toward a framework that accounts for the uniqueness of native species invasions, their anthropogenic drivers, and their impacts on ecosystem services.

Historically, eastern ponderosa pine (Pinus ponderosa) forests were described as sparse patches of old-growth trees maintained by frequent, low-severity fires; however, in recent decades, there have been a number of large mixed-severity wildfires throughout the range of these forests. Wildlife responses to severe fire disturbance in eastern ponderosa pine forests are not well understood. Our study investigates how cavity-nesting bird species in an eastern ponderosa pine forest are impacted by burn severity. The objectives of our study were to: (1) identify the community composition of cavity-nesting birds in a 27 y old burn of mixed severity, (2) assess how habitat variables important to cavity-nesting birds differ in the mixed-severity fire, and (3) determine what habitat variables best predict bird occurrence 27 y after mixed-severity fire. We surveyed 56 sites across four burn severity classes, ranging from unburned to severely burned forest, in the Pine Ridge region of Nebraska. We measured multiple habitat characteristics (tree and snag diameter at breast height (DBH), coarse woody debris (CWD), tree and snag density, shrub height, and shrub cover) in May–August 2016 and conducted bird count surveys between 25 May and 8 June 2016. Cavity-nesting bird species' occurrence varied among the burn severity variables. Burn severity class (unburned, low severity, moderate severity, high severity) was a significant predictor of habitat characteristics for cavity-nesting birds, including tree density, snag density, mean snag DBH, variance in DBH, and CWD, which also was the best indicator of cavity-nesting bird community composition. We report evidence that mixed-severity wildfires in eastern ponderosa pine forests create variation in habitat characteristics and cavity-nesting bird occurrence.