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Infectious diseases pose a significant threat to global health and biodiversity. Yet, predicting the spatiotemporal dynamics of wildlife epizootics remains challenging. Disease outbreaks result from complex nonlinear interactions among a large collection of variables that rarely adhere to the assumptions of parametric regression modeling. We adopted a nonparametric machine learning approach to model wildlife epizootics and population recovery, using the disease system of colonial black-tailed prairie dogs (BTPD, Cynomys ludovicianus) and sylvatic plague as an example. We synthesized colony data between 2001 and 2020 from eight USDA Forest Service National Grasslands across the range of BTPDs in central North America. We then modeled extinctions due to plague and colony recovery of BTPDs in relation to complex interactions among climate, topoedaphic variables, colony characteristics, and disease history. Extinctions due to plague occurred more frequently when BTPD colonies were spatially clustered, in closer proximity to colonies decimated by plague during the previous year, following cooler than average temperatures the previous summer, and when wetter winter/springs were preceded by drier summers/falls. Rigorous cross-validations and spatial predictions indicated that our final models predicted plague outbreaks and colony recovery in BTPD with high accuracy (e.g., AUC generally > 0.80). Thus, these spatially explicit models can reliably predict the spatial and temporal dynamics of wildlife epizootics and subsequent population recovery in a highly complex host-pathogen system. Our models can be used to support strategic management planning (e.g., plague mitigation) to optimize benefits of this keystone species to associated wildlife communities and ecosystem functioning. This optimization can reduce conflicts among different landowners and resource managers, as well as economic losses to the ranching industry. More broadly, our big data-model integration approach pr

Potential carbon mineralization (Cmin) is a commonly used indicator of soil health, with greater Cmin values interpreted as healthier soil. While Cmin values are typically greater in agricultural soils managed with minimal physical disturbance, the mechanisms driving the increases remain poorly understood. This study assessed bacterial and archaeal community structure and potential microbial drivers of Cmin in soils maintained under various degrees of physical disturbance. Potential carbon mineralization, 16S rRNA sequences, and soil characterization data were collected as part of the North American Project to Evaluate Soil Health Measurements (NAPESHM). Results showed that type of cropping system, intensity of physical disturbance, and soil pH influenced microbial sensitivity to physical disturbance. Furthermore, 28% of amplicon sequence variants (ASVs), which were important in modeling Cmin, were enriched under soils managed with minimal physical disturbance. Sequences identified as enriched under minimal disturbance and important for modeling Cmin, were linked to organisms which could produce extracellular polymeric substances and contained metabolic strategies suited for tolerating environmental stressors. Understanding how physical disturbance shapes microbial communities across climates and inherent soil properties and drives changes in Cmin provides the context necessary to evaluate management impacts on standardized measures of soil microbial activity.

Potential carbon mineralization (Cmin) is a commonly used indicator of soil health, with greater Cmin values interpreted as healthier soil. While Cmin values are typically greater in agricultural soils managed with minimal physical disturbance, the mechanisms driving the increases remain poorly understood. This study assessed bacterial and archaeal community structure and potential microbial drivers of Cmin in soils maintained under various degrees of physical disturbance. Potential carbon mineralization, 16S rRNA sequences, and soil characterization data were collected as part of the North American Project to Evaluate Soil Health Measurements (NAPESHM). Results showed that type of cropping system, intensity of physical disturbance, and soil pH influenced microbial sensitivity to physical disturbance. Furthermore, 28% of amplicon sequence variants (ASVs), which were important in modeling Cmin, were enriched under soils managed with minimal physical disturbance. Sequences identified as enriched under minimal disturbance and important for modeling Cmin, were linked to organisms which could produce extracellular polymeric substances and contained metabolic strategies suited for tolerating environmental stressors. Understanding how physical disturbance shapes microbial communities across climates and inherent soil properties and drives changes in Cmin provides the context necessary to evaluate management impacts on standardized measures of soil microbial activity.

Potential carbon mineralization (Cmin) is a commonly used indicator of soil health, with greater Cmin values interpreted as healthier soil. While Cmin values are typically greater in agricultural soils managed with minimal physical disturbance, the mechanisms driving the increases remain poorly understood. This study assessed bacterial and archaeal community structure and potential microbial drivers of Cmin in soils maintained under various degrees of physical disturbance. Potential carbon mineralization, 16S rRNA sequences, and soil characterization data were collected as part of the North American Project to Evaluate Soil Health Measurements (NAPESHM). Results showed that type of cropping system, intensity of physical disturbance, and soil pH influenced microbial sensitivity to physical disturbance. Furthermore, 28% of amplicon sequence variants (ASVs), which were important in modeling Cmin, were enriched under soils managed with minimal physical disturbance. Sequences identified as enriched under minimal disturbance and important for modeling Cmin, were linked to organisms which could produce extracellular polymeric substances and contained metabolic strategies suited for tolerating environmental stressors. Understanding how physical disturbance shapes microbial communities across climates and inherent soil properties and drives changes in Cmin provides the context necessary to evaluate management impacts on standardized measures of soil microbial activity.

Adaptive management of large herbivores requires an understanding of how spatial-temporal fluctuations in forage biomass and quality influence animal performance. Advances in remote sensing have yielded information about the spatial-temporal dynamics of forage biomass, which in turn have informed rangeland management decisions such as stocking rate and paddock selection for free-ranging cattle. However, less is known about the spatial-temporal patterns of diet quality and their influence on large herbivore performance. This is due to infrequent concurrent ground observations of forage conditions with performance (e.g., mass gain), and previously limited satellite data at fine spatial and temporal scales. We combined multi-temporal field observations of diet quality (weekly) and mass gain (monthly) with satellite-derived phenological metrics (pseudo-daily, using data fusion and interpolation) to model daily mass gains of free-ranging yearling cattle in shortgrass steppe. We used this model to predict grazing season (mid-May to October) mass gains, a key management indicator, across 40 different paddocks grazed over a 10-year period (n = 138). We found strong relationships between diet quality and the satellite-derived phenological metrics, especially metrics related to the timing and rate of green-up and senescence. Satellite-derived diet quality estimates were strong predictors of monthly mass gains (R2 = 0.68) across a wide range of aboveground net herbaceous production. Season-long predictions of average daily gain and cattle off-mass had mean absolute errors of 8.9% and 2.9%, respectively. The model performed better temporally (across repeated observations in the same paddock) than spatially (across all paddocks within a given year), highlighting the need for accurate vegetation maps and robust field data collection across both space and time. This study demonstrates that freeranging cattle performance in rangelands is strongly affected by diet quality, which is

Ranchers and pastoralists worldwide manage and depend upon resources from rangelands (which support indigenous vegetation with the potential for grazing) across Earth's terrestrial surface. In the Great Plains of North America rangeland ecology has increasingly recognized the importance of managing rangeland vegetation heterogeneity to address conservation and production goals. This paradigm, however, has limited application for ranchers as they manage extensive beef production operations under high levels of social-ecological complexity and uncertainty. We draw on the ethics of care theoretical framework to explore how ranchers choose management actions. We used modified grounded theory analysis of repeated interviews with ranchers to (1) compare rancher decision-making under relatively certain and uncertain conditions and (2) describe a typology of practices used to prioritize and choose management actions that maintain effective stewardship of these often multi-generational ranches. We contrast traditional decision-making frameworks with those described by interviewees when high levels of environmental and market uncertainty or ecological complexity led ranchers toward use of care-based, flexible and relational frameworks for decision-making. Ranchers facing complexity and uncertainty often sought "middle-ground" strategies to balance multiple, conflicting responsibilities in rangeland social-ecological systems. For example, ranchers' care-based decision-making leads to conservative stocking approaches to "manage for the middle," e.g. to limit risk under uncertain weather and forage availability conditions. Efforts to promote heterogeneity-based rangeland management for biodiversity conservation through the restoration of patch burn grazing and prairie dog conservation will require increased valuation of ranchers' care work.

Ranchers and pastoralists worldwide manage and depend upon resources from rangelands (which support indigenous vegetation with the potential for grazing) across Earth's terrestrial surface. In the Great Plains of North America rangeland ecology has increasingly recognized the importance of managing rangeland vegetation heterogeneity to address conservation and production goals. This paradigm, however, has limited application for ranchers as they manage extensive beef production operations under high levels of social-ecological complexity and uncertainty. We draw on the ethics of care theoretical framework to explore how ranchers choose management actions. We used modified grounded theory analysis of repeated interviews with ranchers to (1) compare rancher decision-making under relatively certain and uncertain conditions and (2) describe a typology of practices used to prioritize and choose management actions that maintain effective stewardship of these often multi-generational ranches. We contrast traditional decision-making frameworks with those described by interviewees when high levels of environmental and market uncertainty or ecological complexity led ranchers toward use of care-based, flexible and relational frameworks for decision-making. Ranchers facing complexity and uncertainty often sought "middle-ground" strategies to balance multiple, conflicting responsibilities in rangeland social-ecological systems. For example, ranchers' care-based decision-making leads to conservative stocking approaches to "manage for the middle," e.g. to limit risk under uncertain weather and forage availability conditions. Efforts to promote heterogeneity-based rangeland management for biodiversity conservation through the restoration of patch burn grazing and prairie dog conservation will require increased valuation of ranchers' care work.

The Northern Great Plains (NGP) region of the USA—which comprises Montana, Wyoming, Colorado, North Dakota, South Dakota, and Nebraska—is a largely rural area that provides numerous ecosystem services, including livestock products, cultural services, and conservation of biological diversity. The region contains 25% of the Nation’s beef cattle and approximately one-third of the confined beef cattle, as well as the largest remaining native prairie in the US—the Northern Mixedgrass Prairie. With rising atmospheric CO2, the NGP is projected to experience warmer and longer growing seasons, greater climatic variability, and more extreme events (e.g., increased occurrence of large precipitation events). These climatic changes may affect livestock production both directly via physiological impacts on animals and indirectly via modifications to forage, invasion of undesirable plants, and increased exposure to parasites. This raises concerns about the vulnerability of grazing livestock operations and confined livestock operations to projected changes in mid- (2050) and late- (2085) twenty-first century climate. Our objectives are to (1) describe the NGP’s exposure to temperature and precipitation trends, inter-annual variability, and extreme events; (2) evaluate the sensitivity of beef cattle production to direct and indirect effects imposed by these projected climatic changes; and (3) provide a typology of adaptation strategies to minimize adverse consequences of projected changes and maximize beneficial consequences. Agricultural managers have developed considerable adaptive capacity to contend with environmental and economic variability. However, projected climatic changes, especially the increased frequency and magnitude of weather extremes, will require even greater adaptive capacity to maintain viable production systems. Consequently, regional vulnerability to projected climatic changes will be determined not only by ecological responses but also by the adaptive capacit

The Northern Great Plains (NGP) region of the USA—which comprises Montana, Wyoming, Colorado, North Dakota, South Dakota, and Nebraska—is a largely rural area that provides numerous ecosystem services, including livestock products, cultural services, and conservation of biological diversity. The region contains 25% of the Nation’s beef cattle and approximately one-third of the confined beef cattle, as well as the largest remaining native prairie in the US—the Northern Mixed grass Prairie. With rising atmospheric CO2, the NGP is projected to experience warmer and longer growing seasons, greater climatic variability, and more extreme events (e.g., increased occurrence of large precipitation events). These climatic changes may affect livestock production both directly via physiological impacts on animals and indirectly via modifications to forage, invasion of undesirable plants, and increased exposure to parasites. This raises concerns about the vulnerability of grazing livestock operations and confined livestock operations to projected changes in mid- (2050) and late- (2085) twenty-first century climate. Our objectives are to (1) describe the NGP’s exposure to temperature and precipitation trends, inter-annual variability, and extreme events; (2) evaluate the sensitivity of beef cattle production to direct and indirect effects imposed by these projected climatic changes; and (3) provide a typology of adaptation strategies to minimize adverse consequences of projected changes and maximize beneficial consequences. Agricultural managers have developed considerable adaptive capacity to contend with environmental and economic variability. However, projected climatic changes, especially the increased frequency and magnitude of weather extremes, will require even greater adaptive capacity to maintain viable production systems. Consequently, regional vulnerability to projected climatic changes will be determined not only by ecological responses but also by the adaptive capaci

The states of Colorado, Montana, Nebraska, North Dakota, South Dakota, and Wyoming comprise the Northern Great Plains region of the USA. The soil and water resources contained in this region have historically supported highly diverse and productive agriculture enterprises that provide a significant proportion of the food, feed, and oilseed for the nation. The region also provides ecological services that influence air, water, and soil quality along with biological diversity. Combined with livestock production and a biofuel industry, crop production forms an integrated system that can offer producers flexibility in management decisions. Projected climatic changes for this region include increasing atmospheric CO2, a longer, warmer growing season, and increased precipitation, likely received in more frequent extreme events. These changes will impact soil and water resources in the region and create opportunities and challenges for land managers. The objectives of this paper are to describe anticipated impacts of projected mid-(2050) and late-(2085) climatic changes on crop production systems in the Northern Great Plains and provide adaptation strategies that should be developed to take advantage of positive and mitigate negative changes. Projected climatic changes will influence agricultural productivity directly as well as indirectly due to changes in weed pressure, insect populations, and diseases. A warmer, longer growing season will change the crops and distribution of those crops grown within the region. An increase in the number of extreme temperature events (high daytime highs or nighttime lows) will decrease crop yields due to increased plant stress during critical pollination and grain fill periods. Adaptation strategies to reduce vulnerability of soil and water resources to projected climatic changes include increasing cropping intensity, reducing tillage intensity, and use of cover crops to provide surface cover to reduce erosion potential and improve nutri

Predicted increases in atmospheric CO2 and temperature may benefit some invasive plants, increasing the need for effective invasive plant management. Biological control can be an effective means of managing invasive plants, but the anticipated range in responses of plant–insect interactions to climate change make it difficult to predict how effective biological control will be in the future. Field experiments that manipulate climate within biological control systems could improve predictive power, but are challenging to implement and therefore rare to date. Here, we show that free air CO2 enrichment in the field increased the fitness of Centaurea diffusa Lam., a problematic invader in much of the western United States. However, CO2 enrichment also increased the impact of the biological control agent Larinus minutus (Coleoptera: Curculionidae) on C. diffusa fitness. C. diffusa plants flowered earlier and seed heads developed faster with both elevated CO2 and increased temperature. Natural dispersal of L. minutus into the experimental plots provided a unique opportunity to examine weevil preference for and effects on C. diffusa grown under the different climate change treatments. Elevated CO2 increased both the proportion of seed heads infested by L. minutus and, correspondingly, the amount of seed removed by weevils. Warming had no detectable effect on weevil utilization of plants. Higher weevil densities on elevated CO2 plants reduced, but did not eliminate, the positive effects of CO2 on C. diffusa fitness. Correlations between plant development time and weevil infestation suggest that climate change increased weevil infestation by hastening plant phenology. Phenological mismatches are anticipated with climate change in many plant–insect systems, but in the case of L. minutus and C. diffusa in mixed-grass prairie, a better phenological match may make the biological control agent more effective as CO2 levels rise.

The Undergraduate Range Management Exam (URME) has been administered to undergraduate students at the Annual Meeting of the Society for Range Management since 1983, with students demonstrating their higher order learning skills and synthesis knowledge of the art and science of rangeland management. • The multiple-choice exam is composed of six subject categories:1) Range Ecology; 2) Grazing Management; 3) Range Improvements; 4) Range Regions; 5) Range Inventory and Analysis; and 6) Multiple-use Relationships on Rangelands. • Topics of changing climate and weather variability (including extreme events), and the associated adaptive management strategies employed by land managers to reduce risk and increase resilience will be highlighted in future years. Increasing emphasis on ecosystem restoration (including mechanisms, processes and pathways), animal grazing behavior, pyric herbivory (patch burn grazing), soil microorganisms, greenhouse gases, and human dimensions should be expected as well.

In the face of an increasingly variable climate, long-term cattle weight gain datasets are rare, yet invalu-able, for determining site-specific influences of seasonal weather patterns on cattle production. Here,we present a long-term (1936–2005) yearling Hereford steer dataset collected at the Northern GreatPlains Research Laboratory (NPGRL) near Mandan, ND, USA. Data were analyzed using weighted AICcmodel averaging to examine the effects of spring (April–June) and summer (July–September) temper-ature and precipitation, as well as prior growing season (prior April–September) and prior fall/winter(prior October–March) precipitation on cattle production (kg/ha) under light (37.4 ± 5.3 SD Animal UnitDays [AUD]/ha across all study years) and heavy (91.6 ± 22.2 SD AUD/ha) stocking rates. Because Ken-tucky bluegrass (Poa pratensis L.) invaded the grassland at NPGRL in the early 1980s, we modeled cattleproduction separately for pre- (1936–1983) and post-invasion (1986–2005) years to determine if theplant community shift influenced sensitivity to seasonal weather patterns. Cattle production under heavystocking was more sensitive to seasonal weather variability than under light stocking during both pre-and post-invasion years. Interestingly, the magnitude and robustness of coefficients changed between thepre- and post-invasion years, with seasonal weather patterns explaining more cattle production variationduring the post-invasion years. Though cattle sensitivity to seasonal weather patterns differed betweenlight and heavy stocking for both pre- and post-invasion years, invasion status did change cattle responseto weather. For example, cattle production in P. pratensis invaded pastures was more heavily influencedby cool, wet springs and wet prior grazing seasons than was production in un-invaded pastures. Forcattle stocked heavily in native pastures, wet winters more strongly increased cattle production than ininvaded pastures.

Quantifying the effects of seasonal temperature and precipitation on cow–calf production on rangelands is challenging, as few long-term (420 yrs) studies have been reported. However, an understanding of how seasonal weather inconsistency affects beef production is needed for beef producers to better manage their herds on native rangelands to minimize enterprise risk with respect to climatic variability. Cow–calf beef production data collected at the USDA-ARS High Plains Grasslands Research Station near Cheyenne, WY, USA from 1975 to 2012 were tested using model averaging for effects of spring (April–June) and summer (July–September) temperature and precipitation, as well as prior winter (October–March) and prior growing season (April–September) precipitation on beef production. Two breeds were used at different times during the study period (Herefords from 1975 to 2001 and a Red Angus x Charolais x Salers cross from 2003 to 2012; there was no grazing in 2002) and examined separately to test for differential effects of seasonal weather by breed. Herefords were more sensitive to seasonal weather patterns than the crossbreds, with Hereford pair total beef production showing the largest effect sizes and Hereford cows showing the highest R2 value (0.66) among models.Wet springs and wet winters particularly increased Hereford beef production in this northern mixed-grass prairie, where as beef production from the crossbreds did not show any weather effect patterns. The model structure used maximizes utility of these data to be built into decision support tools to help ranchers optimize stocking rates and minimize enterprise risk in advance of the grazing season.

Cattle weight gain responses to seasonal weather variability are difficult to predict for rangelands because few long-term (>20 yr) studies have been conducted. However, an increased understanding of temperature and precipitation influences on cattle weight gains is needed to optimize stocking rates and reduce enterprise risk associated with climatic variability. Yearling steer weight gain data collected at the USDA-ARS High Plains Grasslands Research Station at light, moderate, and heavy stocking rates for 30 years (1982–2011) were used to examine the effects of spring (April–June) and summer (July–September) temperature and precipitation, as well as prior-growing-season (prior April–September) and fall/winter (October–March) precipitation, on beef production (kg ha-1). At heavier stocking rates, steer production was more sensitive to seasonal weather variations. A novel finding was that temperature (relatively cool springs and warm summers) played a large predictive role on beef production. At heavier stocking rates, beef production was highest during years with cool, wet springs and warm, wet summers, corresponding to optimum growth conditions for this mixed C3–C4 plant community. The novelty and utility of these findings may increase the efficacy of stocking rate decision support tools. The parsimonious model structure presented here includes three-month seasonal clusters that are forecasted and freely available from the US National Oceanic and Atmospheric Administration up to a year in advance. These seasonal weather forecasts can provide ranchers with an increased predictive capacity to adjust stocking rates (in advance of the grazing season) according to predicted seasonal weather conditions, thereby reducing enterprise risk.

PR, IFPRI4, EPTD

PR, IFPRI4, EPTD

Species diversity is thought to stabilize functioning of plant communities. An alternative view is that stability depends more on dynamics of dominant species than on diversity. We compared inter-annual variability (inverse of stability) of aboveground biomass in paired restored and remnant tallgrass prairies at two locations in central Texas, USA. Data from these two locations were used to test the hypothesis that greater richness and evenness in remnant than restored prairies would reduce variability in aboveground biomass in response to natural variation in rainfall. Restored prairies were chosen to be similar to paired remnant prairies in characteristics other than species diversity that affect temporal variability in biomass. Variability was measured as the coefficient of variation among years (square root of variance/mean; CV), where variance in community biomass equals the sum of variances of individual plant species plus the summed covariances between species pairs.

Grime’s (1998) ‘‘mass-ratio’’ hypothesis holds that ecosystem processes depend in the short term on functional properties of dominant plants and in the longer term on how resident species influence the recruitment of dominants. The latter of these effects may be especially important among early-successional species in disturbed ecosystems, but experimental tests are few. We removed two groups of early-successional species, an annual forb Gutierrezia dracunculoides (DC.) S. F. Blake and annual species (mostly grasses) that complete growth early in the growing season [early-season (ES) species], from a heavily-grazed grassland in central Texas, USA dominated by a C4 perennial grass. We sought to determine effects of annuals on grassland functioning [productivity, water balance, soil and plant nitrogen (N)] and composition.

To restore diversity of native vegetation, we must understand factors responsible for diversity in targeted communities. These factors operate at different spatial scales and may affect the number and relative abundances of species differently. We measured diversity of plant species and functional groups of species in replicated plots within paired restored and remnant (relic) tallgrass prairies at three locations in central Texas, U.S.A.

Structural attributes of the C4, perennial bunchgrass Schizachyrium scoparium in restored prairies may be affected by the time since restoration. One hundred plants each in 8-, 17-, and 23-year-old restored prairies and a native Texas Blackland prairie were assessed for the presence/absence and diameter of a hollow crown (i.e., dead center portion), degree of fragmentation, plant height, and tiller density.

We evaluated the influences of CO2 and soil water on above- and below-ground responses of C3 and C4 plants in monocultures and two density mixtures.

The glacial-to-present increase in atmospheric CO2 concentration is likely to have stimulated plant production, but experimental tests in natural ecosystems are lacking.

Plant species richness influences primary productivity via mechanisms that (1) favour species with particular traits (selection effect) and (2) promote niche differentiation between species (complementarity). Influences of species evenness, plant density and other properties of plant communities on productivity are poorly defined, but may depend on whether selection or complementarity prevails in species mixtures. We predicted that selection effects are insensitive to species evenness but increase with plant density, and that the converse is true for complementarity. To test predictions, we grew three species of annuals in monocultures and in three-species mixtures in which evenness of established plants was varied at each of three plant densities in a cultivated field in Texas, USA. Above-ground biomass was smaller in mixtures than expected from monocultures because of negative 'complementarity' and a negative selection effect. Neither selection nor complementarity varied with species evenness, but selection effects increased at the greatest plant density as predicted.