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Dirac Twidwell

Publications and source records attributed to Dirac Twidwell.

At least 19 recordsLinked to original sources

Biome-scale spatial patterns of avian abundance reveal proactive conservation opportunities in North American grasslands

North American grassland birds have experienced steeper population declines than any other avian guild, yet conservation efforts remain largely reactive and fragmented. We used nearly four decades of North American Breeding Bird Survey data to identify biome-scale spatial patterns (clustering) of grassland bird abundance for the Great Plains. Our results reveal an ecological core in the north-central Plains where community-level abundance is either increasing by >100% or remains high and stable, providing a strategic roadmap for a “Defend the Core” conservation approach. This approach flips the script from reactive triage centered on isolated population fragments to a proactive strategy of maintaining large-scale ecosystem integrity. Conversely, we found that population losses are more spatially clustered than wins, reflecting the relentless, one-way movement of woody encroachment and agricultural conversion. This asymmetry supports prioritizing intact landscapes, as current restoration rates are often outpaced by the scale of habitat loss. Notably, we found that community-level spatial clustering is a more robust indicator of biome condition than trends of individual flagship species, suggesting that managing for ecosystem integrity provides a more effective multi-species umbrella. Given our results, there is an opportunity for operationalizing a Great Plains Conservation Design that is ecosystem-centric and rooted in the sustainability of the private-land cattle production that maintains these open spaces. By leveraging avian abundance as a biological sensor, managers and producers can deploy a shared vision that matches the spatial scale of the threats, moving from reactive triage to proactive defense of core working grasslands in North America.

Great Plains biome↗

Sentinel-2 based estimates of rangeland fractional cover and canopy gap class for the western United States

Rangelands are extensive ecosystems, providing important ecosystem services while undergoing continuous change. As a result, improved monitoring technologies can help better characterize vegetation change. Satellite remote sensing has proven effective in this regard, tracking vegetation dynamics at broad and fine scales. We leveraged the spatial, spectral, and temporal resolution of Sentinel-2 satellites to estimate fractional cover and canopy gap across rangelands of the western United States. We produced annual, 10 m spatial resolution estimates of fractional cover and canopy gap size class for years 2018 to 2024. Fractional cover estimates include that of common plant functional types (annual forb and grass, bareground, littler, perennial forb and grass, shrub, tree) and select genera (including invasive annual grass species, pinyon-juniper species, and sagebrush species); canopy gap size classes include gap sizes 25 to 50, 51 to 100, 101 to 200, and greater than 200 cm. We make these data available as Cloud Optimized GeoTIFFs, organized as 75 × 75 km tiles covering the 17 western states of the United States.

western United States↗

Reconciling scale using the Resist-Accept-Direct (RAD) Framework to improve management of woody encroachment in grasslands

Implementing strategies to navigate large-scale ecological transitions in grasslands is one of this century's greatest conservation challenges. In the US Great Plains, managing areas impacted by woody transitions have been reactive, short-lived, costly, and ineffective. Along with current technological innovation in rangeland monitoring, the promise of early warning science is to provide managers with sufficient time to be better prepared for novel signals of ecological change. Combining the science of early warning signals and frameworks such as the Resist – Accept – Direct (RAD) can provide land managers with guidelines to identify proactive strategies when facing ecological change. Using this approach, we found that opportunities to resist woody transitions decreased from 84 % to 60 % between 1990 and 2020 over the entire biome but remained highest in the northern and western Great Plains, which contributes to large scale conservation targets. These are key areas to prioritize resist opportunities. In contrast, 11 % of the biome exhibited early warning transition signals across all hierarchical scales by 2020, a fourfold increase since 1990. Lastly by 2020, 30 % of the biome exhibited early warning signals across multiple but not all scales. Here, efforts may be more effective when management is directed to conserve fragmented grassland legacies within a woody-dominated matrix and avoid large-scale monocultures of problematic encroaching woody species. Our multi-scale study indicates that 1) anchoring to the last remaining grassland core areas with no early warning of transitions and 2) strategically investing in these intact grasslands may provide the best results for grassland conservation.

Great Plains↗

High-intensity fire supports restoration of grassland species richness and community composition following woody encroachment

Woody encroachment has driven drastic declines in grassland biodiversity and productivity. In the U.S. Great Plains, high-intensity prescribed fire is increasingly being used to shift encroaching redcedar woodlands to a grassland state. High-intensity fire treatments drive redcedar mortality and increase herbaceous biomass. However, it is unclear how grassland community composition recovers following stand-consuming fire. We contrast herbaceous community composition, basal cover, and species richness in woodlands treated with stand-consuming high-intensity fire to reference grassland and woodland sites to examine whether high-intensity fires facilitate restoration of grassland communities. To determine the long-term outcomes of high-intensity fire treatments, we use a space-for-time substitute to measure changes to herbaceous community and species richness over a time-since-fire gradient of 17 years. We found that herbaceous cover and species richness increased substantially in woodlands treated with stand-consuming high-intensity fire compared to unburned woodlands, and that these values were similar to those observed in both burned and unburned grasslands. Herbaceous community composition in woodlands treated with high-intensity fire also shifted towards grasslands, though some legacies of woodland communities persisted. Time-since-fire generally did not have a large influence on total herbaceous cover or species richness through time, though grass cover decreased in woodlands treated with high-intensity fire a decade post-treatment. Our findings suggest that a single high-intensity fire can support the restoration of herbaceous plant species richness and cover, and shift community composition to a grassland regime, though additional low-intensity fire treatments may be necessary to erode legacies from the encroached state.

Nebraska↗

Sentinel-2 based estimates of rangeland fractional cover and canopy gap class for the western United States

Rangelands are extensive ecosystems, providing important ecosystem services while undergoing continuous change. As a result, improved monitoring technologies can help better characterize vegetation change. Satellite remote sensing has proven effective in this regard, tracking vegetation dynamics at broad and fine scales. We leveraged the spatial, spectral, and temporal resolution of Sentinel-2 satellites to estimate fractional cover and canopy gap across rangelands of the western United States. We produced annual, 10 m spatial resolution estimates of fractional cover and canopy gap size class for years 2018 to 2024. Fractional cover estimates include that of common plant functional types (annual forb and grass, bareground, littler, perennial forb and grass, shrub, tree) and select genera (including invasive annual grass species, pinyon-juniper species, and sagebrush species); canopy gap size classes include gap sizes 25 to 50, 51 to 100, 101 to 200, and greater than 200 cm. We make these data available as Cloud Optimized GeoTIFFs, organized as 75×75 km tiles covering the 17 western states of the United States.

BioRxiv↗

Population increases of the threatened American burying beetle (Nicrophorus americanus) linked to large-scale collaborations in a working lands ecoregion

Woody plant encroachment and row-crop agricultural land conversion are existential threats to species that rely on grassland ecosystems. The American Burying Beetle ( Nicrophorus americanus ) is a threatened species whose largest remnant populations are predominantly located in grassland ecoregions comprised of privately-owned ranching lands. Here, we seek to determine functional scaling patterns and population trends of the American Burying Beetle in the face of conservation threats and grassland restoration. We used 13 years (2007–2019) of American Burying Beetle abundance data collected from permanent sampling locations across the Loess Canyons ecoregion (Nebraska, USA), where a network of ranchers have been restoring large-scale grasslands. To estimate beetle abundance relative to land cover variables, we developed a Bayesian N-mixture model, incorporating the Bayesian latent indicator scale selection (BLISS) method to probabilistically determine at which scales land cover variables best explained beetle abundance. American Burying Beetle abundance exhibited high interannual variation but overall significantly increased across the ecoregion. Increases in beetle abundance were associated with large-scale (1149 ha extent) grassland cover. Decreases in abundance were associated with large-scale crop conversion (590 ha extent) and large-scale increases in woody cover (1149 ha extent). This study provides the first evidence of ecoregion-scale population increases of the American Burying Beetle. These increases are tied to landscape variables that are managed in a large-scale, coordinated private lands grassland restoration effort. Our results suggest that successful grassland restoration will depend on coordinating across property boundaries to implement conservation at scales necessary to conserve species that require large-scale, unfragmented grasslands.

Nebraska↗

Declining pronghorn (Antilocapra americana) population productivity caused by woody encroachment and oil and gas development

Conservation is increasingly focused on preventing losses in species’ populations before they occur. Tracking changes in demographic parameters that can impact a population’s resilience in response to drivers of global change can support early conservation efforts. We assessed trends in population productivity (late summer juveniles per 100 females) relative to drivers of global change in 40 pronghorn ( Antilocapra americana ) herds across sagebrush ( Artemisia spp.) steppe in Wyoming. Pronghorn are an iconic rangeland species that have been exposed to increasing levels of anthropogenic, climatic, and land-use change. Using data collected across the state of Wyoming, we (1) assessed long-term trends in population productivity, (2) identified patterns in large-scale drivers of global change (i.e., climate, land cover change) across pronghorn habitat, and (3) determined the relationship between drivers of global change and population productivity over a 35-year (1984–2019) period. While Wyoming hosts some of the most abundant populations of pronghorn in North America that have been largely stable in recent years, we found many herds are experiencing long-term declines in productivity. Long-term declines in productivity were associated with increases in oil and gas development and woody encroachment. Although increasing across almost all herd units, woody vegetation cover remains at low levels, suggesting that pre-emptive management may help to prevent losses in pronghorn populations.

Global Change and Ecology↗

Herbaceous production lost to tree encroachment in United States rangelands

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 analysed tree cover change and herbaceous production across the western United States from 1990 to 2019. We show that tree encroachment is widespread in US rangelands; absolute tree cover has increased by 50% (77,323 km 2 ) over 30 years, with more than 25% (684,852 km 2 ) of US 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 US 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 US Prioritizing conservation efforts to prevent tree encroachment can bolster ecosystem and economic sustainability, particularly among privately-owned lands threatened by land-use conversion.

Journal of Applied Ecology↗

Tracking spatial regimes in animal communities: Implications for resilience-based management

Spatial regimes (the spatial extents of ecological states) exhibit strong spatiotemporal order as they expand or contract in response to retreating or encroaching adjacent spatial regimes (e.g., woody plant invasion of grasslands) and human management (e.g., fire treatments). New methods enable tracking spatial regime boundaries via vegetation landcover data, and this approach is being used for strategic management across biomes. A clear advancement would be incorporating animal community data to track spatial regime boundaries alongside vegetation data. In a 41,170-hectare grassland experiencing woody plant encroachment, we test the utility of using animal community data to track spatial regimes via two hypotheses. (H1) Spatial regime boundaries identified via independent vegetation and animal datasets will exhibit spatial synchrony; specifically, grassland:woodland bird community boundaries will synchronize with grass:woody vegetation boundaries. (H2) Negative feedbacks will stabilize spatial regimes identified via animal data; specifically, frequent fire treatments will stabilize grassland bird community boundaries. We used 26 years of bird community and vegetation data alongside 32 years of fire history data. We identified spatial regime boundaries with bird community data via a wombling approach. We identified spatial regime boundaries with vegetation data by calculating spatial covariance between remotely-sensed grass and woody plant cover per pixel. For fire history data, we calculated the cumulative number of fires per pixel. Setting bird boundary strength (wombling R 2 values) as the response variable, we tested our hypotheses with a hierarchical generalized additive model (HGAM). Both hypotheses were supported: animal boundaries synchronized with vegetation boundaries in space and time, and grassland bird communities stabilized as fire frequency increased (HGAM explained 38% of deviance). We can now track spatial regimes via animal community data pixel-by-pixel and year-by-year. Alongside vegetation boundary tracking, tracking animal community boundaries can inform the scale of management necessary to maintain animal communities endemic to desirable ecological states. Our approach will be especially useful for conserving animal communities requiring large-scale, unfragmented landscapes—like grasslands and steppes.

Kansas↗

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.

Kansas, Nebraska, Oregon↗

Guiding principles for using satellite-derived maps in rangeland management

On the Ground Rangeland management has entered a new era with the accessibility and advancement of satellite-derived maps. Maps provide a comprehensive view of rangelands in space and time, and challenge us to think critically about natural variability. Here, we advance the practice of using satellite-derived maps with four guiding principles designed to increase end user confidence and thereby accessibility of these data for decision-making.

Idaho↗

Improving Landsat predictions of rangeland fractional cover with multitask learning and uncertainty

Operational satellite remote sensing products are transforming rangeland management and science. Advancements in computation, data storage and processing have removed barriers that previously blocked or hindered the development and use of remote sensing products. When combined with local data and knowledge, remote sensing products can inform decision‐making at multiple scales. We used temporal convolutional networks to produce a fractional cover product that spans western United States rangelands. We trained the model with 52,012 on‐the‐ground vegetation plots to simultaneously predict fractional cover for annual forbs and grasses, perennial forbs and grasses, shrubs, trees, litter and bare ground. To assist interpretation and to provide a measure of prediction confidence, we also produced spatiotemporal‐explicit, pixel‐level estimates of uncertainty. We evaluated the model with 5,780 on‐the‐ground vegetation plots removed from the training data. Model evaluation averaged 6.3% mean absolute error and 9.6% root mean squared error. Evaluation with additional datasets that were not part of the training dataset, and that varied in geographic range, method of collection, scope and size, revealed similar metrics. Model performance increased across all functional groups compared to the previously produced fractional product. The advancements achieved with the new rangeland fractional cover product expand the management toolbox with improved predictions of fractional cover and pixel‐level uncertainty. The new product is available on the Rangeland Analysis Platform (https://rangelands.app/), an interactive web application that tracks rangeland vegetation through time. This product is intended to be used alongside local on‐the‐ground data, expert knowledge, land use history, scientific literature and other sources of information when making interpretations. When being used to inform decision‐making, remotely sensed products should be evaluated and utilized according to the context of the decision and not be used in isolation.

Methods in Ecology and Evolution↗

Resilience in environmental risk and impact assessment: Concepts and measurement

Different resilience concepts have different assumptions about system dynamics, which has implications for resilience-based environmental risk and impact assessment. Engineering resilience (recovery) dominates in the risk assessment literature but this definition does not account for the possibility of ecosystems to exist in multiple regimes. In this paper we discuss resilience concepts and quantification methods. Specifically, we discuss when a system fails to show engineering resilience after disturbances, indicating a shift to a potentially undesired regime. We show quantification methods that can assess the stability of this new regime to inform managers about possibilities to transform the system to a more desired regime. We point out the usefulness of an adaptive inference, modelling and management approach that is based on reiterative testing of hypothesis. This process facilitates learning about, and reduces uncertainty arising from risk and impact.

Bulletin of Environmental Contamination and Toxico↗

Quantifying variance across spatial scales as part of fire regime classifications

The emergence of large‐scale fire classifications and products informed by remote sensing data has enabled opportunities to include variability or heterogeneity as part of modern fire regime classifications. Currently, basic fire metrics such as mean fire return intervals are calculated without considering spatial variance in a management context. Fire return intervals are also only applicable at a particular grain size (defined as the spatial unit of interest) even though they are typically applied homogeneously. In this study, we utilized a 29‐yr fire occurrence database to show how spatial variance changes with respect to grain as postulated by Wiens ( 1989 ) when reporting fire patterns within the Great Plains, USA. We utilized data from the Monitoring Trends in Burn Severity database of fire occurrence for the years 1984–2012. We analyzed median numbers of fire along with their variance at four spatial grains ranging from small units (e.g., plots at 3 × 3 km resolution) to large units (e.g., landscapes at 1500 × 2700 km resolution). Median number of fire occurrences was consistently low, irrespective of grain. Despite the consistency in low median numbers of fires across grain, variance in the numbers of fires between units decreased. Variance within units, however, did not change as grain increased indicating fire‐pattern‐scale inconsistencies. Fire pattern interpretations depended entirely on the scale at which it is calculated. Given that the Great Plains region has a large disparity in fire patterns (i.e., some regions burn often, while others may never burn), fire regime classifications will benefit from including scale‐specific variance estimates as a foundation for understanding changes in fire regimes and corresponding social–ecological and policy responses.

Ecosphere↗

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. Here, we conduct a scenario impact assessment to determine the potential impact of climate change scenarios on the rates at which lands enrolled in the Conservation Reserve Program (CRP) lands are authorized for emergency biomass removal. Grassland biomass on CRP lands is authorized for ‘emergency’ harvesting for agricultural use when precipitation for the last four months falls below 40 percent of the normal, or ‘historical’ mean, precipitation for that four-month period. We develop and analyze 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 show the historical likelihood of authorizing emergency biomass harvesting in any given year in the northern Great Plains was 33.28 ± 0.96%, according to long-term weather records. Emergency biomass harvesting became the norm (>50% of years) in the scenario reflecting 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 experienced a greater increase in emergency biomass removal. Emergency biomass harvesting decreased only in the scenario reflecting rapid reductions in emissions. Our scenario impact analysis indicates that biomass from lands enrolled in the CRP will 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.

Montana, Nebraska, North Dakota, South Dakota, Wyo↗

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.

Nebraska↗

Enhancing quantitative approaches for assessing community resilience

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.

Journal of Environmental Management↗

Regeneration and invasion of cottonwood riparian forest following wildfire

Populus deltoides is considered to be a weak resprouter and highly susceptible to wildfire, but few post-wildfire studies have tracked P. deltoides response and resprouting within the Great Plains of North America. Following a wildfire in southwestern Kansas, U.S.A., we surveyed burned and unburned areas of a cottonwood riparian forest along the Cimarron River that included a major understory invader, tamarisk ( Tamarix ramosissima Ledeb.). We tested the following hypotheses, which are consistent with the current understanding of P. deltoides response to wildfire in the Great Plains: (1) regeneration of P. deltoides will be low in areas burned by the wildfire; (2) the number of dead P. deltoides individuals will be greater in the wildfire than unburned areas; and (3) tamarisk regeneration will be higher than P. deltoides regeneration in the wildfire areas because tamarisk is considered a stronger resprouter. We found evidence contrary to two of our hypotheses 3 years following the wildfire. (1) P. deltoides regeneration was high following the wildfire, averaging 692 individuals/ha. (2) The number of dead mature cottonwood trees was greater in wildfire plots than in unburned plots. (3) There was more P. deltoides regeneration than tamarisk regeneration following wildfire. These findings, which diverge from the majority of studies examining P. deltoides regeneration in the Great Plains, suggest that differing local environmental and forest stand conditions, coupled with the timing and intensity of the fire, could be important determinants of riparian forest species' responses to wildfire.

Kansas↗