Tracking spatial regimes as an early warning for a species of conservation concern.

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.

Next-generation technologies unlock new possibilities to track rangeland productivity and quantify multi-scale conservation outcomes.

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.

The perpetual state of emergency that sacrifices protected areas in a changing climate.

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.

Nine-banded armadillo (Dasypus novemcinctus) activity patterns are influenced by human activity.

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.

Fire legacies in eastern ponderosa pine forests.

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 < 0.05). Bird communities differed between high- and moderate-severity patches, low-severity patches, and unburned patches (all p < 0.05). Bird species richness varied across burn severities: low-severity patches had the highest (5.29 ± 1.44) and high-severity patches had the lowest (2.87 ± 0.72). Understory woody plant richness was highest in unburned (5.93 ± 1.10) and high-severity (5.07 ± 1.17) patches, and it was lower in moderate- (3.43 ± 1.17) and low-severity (3.43 ± 1.06) patches. We show material fire legacies persisted decades after the mixed-severity wildfire in eastern ponderosa forest, fostering distinct structures, communities, and species in burned versus unburned patches and across fire severities. At a patch scale, eastern and western ponderosa system responses to mixed-severity fires were consistent.

Doublethink and scale mismatch polarize policies for an invasive tree.

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.

Early Warnings for State Transitions.

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.