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We describe a case of a unique antipredator behavior sequence in response to rattlesnakes in a population of black-tailed prairie dogs in Fort Collins, Colorado. Our analysis revealed individuals across multiple social groups within the population engaged in novel behavioral responses to prairie rattlesnakes, including 'escorting' behavior, where a prairie dog would walk alongside the snake. Using Markov chain analysis, we also found that prairie dogs engaged in non-random behavioral transitions and that specific pairs of behaviors were contributing to this pattern. Digital video images related to the article are available at http://www.momo-p.com/showdetail-e.php?movieid=momo230929cl01a). [ABSTRACT FROM AUTHOR]

Nonbreeding raptors are vulnerable to many anthropogenic changes such as habitat fragmentation and increasing risk of collision (e.g., with wind turbines, powerlines, or vehicles). One aspect of habitat quality for raptors during winter has received comparably less attention: the role of colonial burrowing rodents such as prairie dogs (Cynomys spp.) as a reliable food source, and the effects of widespread reduction in prairie dog abundance and availability to nonbreeding raptors. We used a historical dataset (1998–2002) of roadside surveys for raptors and prairie dogs in the Southern and Central Great Plains, including Arizona, Colorado, New Mexico, and Texas, USA, and the Mexican state of Chihuahua, to provide the most spatially and temporally expansive analysis to date of the potential role of prairie dogs in influencing presence and abundance of raptors. We assessed patterns of co-occurrence among raptors and prairie dogs and modeled the response of selected species to weather, latitude, grassland cover, and prairie dog presence and abundance at multiple spatial scales. During the study period, we detected 19 species of raptors and identified nine raptor species that co-occurred with prairie dogs more than expected by chance. We also found evidence that occurrence of prairie dogs was related to presence and/or abundance of Ferruginous Hawks (Buteo regalis), Golden Eagles (Aquila chrysaetos), Bald Eagles (Haliaeetus leucocephalus), and Rough-legged Hawks (B. lagopus). Our work underscores the association of prairie dogs with many wintering raptor species, especially Ferruginous Hawks and Golden Eagles, and indicates that prairie dogs may also be an important resource for Rough-legged Hawks and Bald Eagles during the nonbreeding season. Las rapaces no reproductoras son vulnerables a muchos cambios antropogénicos, como la fragmentación del hábitat y el aumento del riesgo de colisión (por ejemplo, con aerogeneradores, líneas eléctricas o vehículos). Un aspecto de la calidad del hábitat para las rapaces durante el invierno ha recibido comparativamente menos atención: el papel de roedores coloniales que excavan madrigueras, como los perritos de las praderas (Cynomys spp.), como una fuente confiable de alimento, y los efectos de la reducción generalizada en la abundancia y disponibilidad de perritos de las praderas para las rapaces no reproductoras. Utilizamos una serie de datos histórica (1998–2002) de censos en carreteras de rapaces y perritos de las praderas en las Grandes Llanuras del sur, que incluyen Arizona, Colorado, Nuevo México y Texas, EEUU, y el estado mexicano de Chihuahua, para proporcionar el análisis espacial y temporal más amplio hasta la fecha sobre el papel potencial de los perritos de las praderas en la influencia de la presencia y abundancia de rapaces. Evaluamos patrones de coocurrencia entre rapaces y perritos de las praderas y modelamos la respuesta de especies seleccionadas a factores como el clima, la latitud, la cobertura de pastizales y la presencia y abundancia de perritos de las praderas considerando múltiples escalas espaciales. Durante el período de estudio, detectamos 19 especies de rapaces e identificamos nueve especies de rapaces que coocurrieron con perritos de las praderas más de lo esperado por azar. También encontramos evidencia de que la presencia de perritos de las praderas estaba relacionada con la presencia y/o abundancia de Buteo regalis, Aquila chrysaetos, Haliaeetus leucocephalus, y B. lagopus. Nuestro trabajo destaca la asociación de los perritos de las praderas con muchas especies de rapaces invernantes, especialmente con B. regalis y A. chrysaetos, e indica que los perritos de las praderas también pueden ser un recurso importante para B. lagopus y H. leucocephalus durante la temporada no reproductiva. [Traducción del equipo editorial] [ABSTRACT FROM AUTHOR]

Lesser prairie-chicken (Tympanuchus pallidicinctus) populations of in the Sand Sagebrush Prairie Ecoregion of southwest Kansas and southeast Colorado, USA, have declined sharply since the mid-1980s. Decreased quality and availability of habitat are believed to be the main drivers of declines. Our objective was to reconstruct broad-scale change in the ecoregion since 1985 as a potential factor in population declines. We assessed temporal change from 1985–2015 in landcover types and calculated landscape metrics using Land Change Monitoring, Assessment, and Projection imagery layers. We also documented presence of anthropogenic structures including oil wells and electrical transmission lines. Landcover type composition changed little since 1990 across the Sand Sagebrush Prairie Ecoregion. However, anthropogenic structures (i.e., oil/gas wells, cell towers, wind farms, and transmission lines) notably increased, potentially causing functional habitat loss at a broad scale. Increased anthropogenic structures may have decreased habitat availability as well as the quality of existing habitat for lesser prairie-chickens, possibly contributing to recent population declines throughout the Sand Sagebrush Prairie Ecoregion. [ABSTRACT FROM AUTHOR]

Habitat fragmentation is the process where large complex habitats are divided and separated into smaller "patches" with little transitional habitat between one habitat type to the next. Fragmentation is largely an anthropogenic issue caused by development, spread of agriculture, and improper management of land. Prairies and grasslands are particularly at risk and these habitats are home to species of plants, mammals and other wildlife groups that rely on large unfragmented grasslands to thrive. The historic prairies of Missouri have been heavily fragmented and isolated from one another and many of the prairie patches are surrounded by agriculture and other less than ideal landcover types. Here, I aim to understand the effects of agriculture on the native plant communities within prairie patches of southern Missouri. Using the Quantum Geographic Information System (QGIS) and the statistical programing language R, we show that increased agriculture surrounding a prairie decreases native plant richness within the plant community of the prairie patches in our study. Missouri's landscape is dominated by agriculture and the remnants of prairie are likely becoming both encroached upon and isolated from one another by agricultural land use. [ABSTRACT FROM AUTHOR]

Intrusion detection datasets are highly likely to contain numerous redundant, irrelevant, and noisy features that slow the performance of the machine learning techniques and classifiers that may be applied to them. The feature selection approach is used for reducing the number of features in intrusion detection datasets and eliminating those that are not important. One of the most powerful structured population approaches is the Cellular Automata approach, which is used to enhance the diversity and convergence of population-based optimization algorithms. In this work, the Cellular Automata approach, Mixed opposition-based learning, and the K-Nearest Neighbor classifier are incorporated with the Prairie dog optimization algorithm (PDO) in a new intrusion detection framework called Binary Opposition Cellular Prairie dog optimization algorithm (BOC-PDO). The proposed framework contains four key features. First, the Cellular Automata model is utilized to enhance the population of feasible solutions in the PDO. Second, four S-shaped and four V-shaped Binary Transfer Functions are used to convert the continuous solutions in BOC-PDO to binary ones. Third, the Mixed opposition-based learning approach is used at the end of the optimization loop of BOC-PDO to improve capacity for exploration. Fourth, the K-Nearest Neighbor classifier is used as the main learning model in BOC-PDO. Eleven famous intrusion detection datasets were employed in the evaluation of the effectiveness of BOC-PDO compared to eight popular binary optimization algorithms and four machine learning approaches. According to the overall simulation results, BOC-PDO scored the highest accuracy, best objective value, and fewest selected features for each of the eleven intrusion detection datasets. Besides, the reliability and consistency of the simulation results of BOC-PDO compared to the other tested algorithms were established using Friedman and Wilcoxon statistical tests. [ABSTRACT FROM AUTHOR]

The consequences of intraguild predation on vulnerable subordinate species are an important consideration in the recovery of endangered species. In prairie ecosystems, coyotes (Canis latrans) are the primary predator of endangered black-footed ferrets (Mustela nigripes ; hereafter, ferrets) and presumably compete for prairie dog (Cynomys spp.) prey. Coyote predation of ferrets is thought to occur at night when ferrets are active aboveground; however, the apparent source of competition, diurnal prairie dogs, are belowground and inaccessible to coyotes at this time, presenting a perplexing temporal mismatch between actual and expected times that coyotes and ferrets come into conflict. Our study used remote wildlife cameras, occupancy models, and overlap of circadian activity patterns to investigate how landscape features, prairie dog colony attributes, and attraction to sympatric species, i.e. American badgers (Taxidea taxus ; hereafter, badgers) and lagomorphs (cottontail rabbits and jackrabbits) influence Coyote use of prairie dog colonies and potential Coyote–ferret interactions. We first evaluated Coyote use (i.e. occupancy) between prairie dog colonies and surrounding available grasslands, finding that coyotes whose home ranges include prairie dog colonies used colonies nearly twice as much as surrounding grasslands. Next, we investigated biotic and abiotic factors that may influence Coyote use and frequency of use (i.e. detection probability) on prairie dog colonies. We found high Coyote use across all areas on prairie dog colonies; however, their frequency of use increased in areas that were also used by badgers. High overlap between Coyote and badger activity patterns (81%) further supports the spatial use patterns revealed by our occupancy analysis, and badgers and coyotes are known to form hunting associations. Interspecific competition and overlapping patterns of resource use between badgers and ferrets have been documented in previous studies; our study supports these findings and suggests that Coyote attraction to badger activity may influence Coyote–ferret interactions. [ABSTRACT FROM AUTHOR]

Less than 1% of native prairie lands remain in the United States. Located in eastern Washington, the rare habitat called Palouse prairie was largely converted to wheat monocropping. With this conversion came numerous physical, chemical, and biological changes to the soil that may ultimately contribute to reduced wheat yields. Here, we explored how wheat (Tritcum aestivum L.) seedling establishment, plant size, and heading, signifying the developmental transition to flowering, were affected by being planted in prairie soil versus agricultural soils. We then sought to understand whether the observed effects were the result of changes to the soil microbiota due to agricultural intensification. We found that prairie soil enhanced both the probability of wheat seedling survival and heading compared to agricultural soil; however, wheat growth was largely unaffected by soil source. We did not detect effects on wheat developmental transitions or phenotype when inoculated with prairie microbes compared with agricultural microbes, but we did observe general antagonistic effects of microbes on plant size, regardless of soil source. This work indicates that agricultural intensification has affected soils in a way that changes early seedling establishment and the timing of heading for wheat, but these effects may not be caused by microbes, and instead may be caused by soil nutrient conditions. [ABSTRACT FROM AUTHOR]

Wireless Sensor Networks (WSNs) consist of small, multifunctional nodes distributed across various locations to monitor and record parameters. These nodes store data and transmit signals for further processing, forming a crucial topic of study. Monitoring the network's status in WSN applications using clustering systems is essential. Collaboration among sensors from various domains enhances the precision of localised information reporting. However, nodes closer to the data sink consume more energy, leading to hotspot challenges. To address these challenges, this research employs clustering and optimised routing techniques. The aggregation of information involves creating clusters, further divided into sub-clusters. Each cluster includes a Cluster Head (CH) or Sensor Nodes (SN) without a CH. Clustering inherently optimises CHs' capabilities, enhances network activity, and establishes a systematic network topology. This model accommodates both multi-hop and single-hop systems. This research focuses on selecting CHs using a Genetic Algorithm (GA), considering various factors. While GA possesses strong exploration capabilities, it requires effective management. This research uses Prairie Dog Optimization (PDO) to overcome this challenge. The proposed Hotspot Mitigated Prairie with Genetic Algorithm (HM-PGA) significantly improves WSN performance, particularly in hotspot avoidance. With HM-PGA, it achieves a network lifetime of 20913 milliseconds and 310 joules of remaining energy. Comparative analysis with existing techniques demonstrates the superiority of the proposed approach. [ABSTRACT FROM AUTHOR]

Prairie dogs have declined by 98% throughout their range in the grasslands of North America. Translocations have been used as a conservation tool to reestablish colonies of this keystone species and to mitigate human–wildlife conflict. Understanding the behavioral responses of prairie dogs to translocation is of utmost importance to enhance the persistence of the species and for species that depend on them, including the critically endangered black‐footed ferret. In 2017 and 2018, we translocated 658 black‐tailed prairie dogs on the Lower Brule Indian Reservation in central South Dakota, USA, a black‐footed ferret recovery site. Here, we describe and evaluate the effectiveness of translocating prairie dogs into augered burrows and soft‐released within presumed coteries to reestablish colonies in previously occupied habitat. We released prairie dogs implanted with passive integrated transponders (PIT tags) and conducted recapture events approximately 1‐month and 1‐year post‐release. We hypothesized that these methods would result in a successful translocation and that prairie dogs released as coteries would remain close to where they were released because of their highly social structure. In support of these methods leading to a successful translocation, 69% of marked individuals was captured 1‐month post‐release, and 39% was captured 1‐year post‐release. Furthermore, considerable recruitment was observed with 495 unmarked juveniles captured during the 1‐year post‐release trapping event, and the reestablished colony had more than doubled in the area by 2021. Contrary to our hypothesis, yet to our knowledge a novel finding, there was greater initial movement within the colony 1‐month post‐release than expected based on recapture locations compared with the published average territory size; however, 1 year after release, most recaptured individuals were captured within the expected territory size when compared to capture locations 1‐month post‐release. This research demonstrates that while translocating prairie dogs may be socially disruptive initially, it is an important conservation tool. [ABSTRACT FROM AUTHOR]

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This study proposes a new prairie dog optimization algorithm version called EPDO. This new version aims to address the issues of premature convergence and slow convergence that were observed in the original PDO algorithm. To improve performance, several modifications are introduced in EPDO. First, a dynamic opposite learning strategy is employed to increase the diversity of the population and prevent premature convergence. This strategy helps the algorithm avoid falling into local optima and promotes global optimization. Additionally, the Lévy dynamic random walk technique is utilized in EPDO. This modified Lévy flight with random walk reduces the algorithm's running time for the test function's ideal value, accelerating its convergence. The proposed approach is evaluated using 33 benchmark problems from CEC 2017 and compared against seven other comparative techniques: GWO, MFO, ALO, WOA, DA, SCA, and RSA. Numerical results demonstrate that EPDO produces good outcomes and performs well in solving benchmark problems. To further validate the results and assess reliability, the authors employ average rank tests, the measurement of alternatives, and ranking according to the compromise solution (MARCOS) method, as well as a convergence report of EPDO and other algorithms. Furthermore, the effectiveness of the EPDO algorithm is demonstrated by applying it to five design problems. The results indicate that EPDO achieves impressive outcomes and proves its capability to address practical issues. The algorithm performs well in solving benchmark and practical design problems, as supported by the numerical results and validation methods used in the study. [ABSTRACT FROM AUTHOR]

Butterfly abundances are declining globally, with meta‐analysis showing a rate of −2% per year. Agriculture contributes to butterfly decline through habitat loss and degradation. Prairie strips—strips of farmland actively restored to native perennial vegetation—are a conservation practice with the potential to mitigate biodiversity loss, but their impact on butterfly biodiversity is not known.Working within a 30‐year‐old experiment that varied land use intensity, from natural areas to croplands (maize–soy–wheat rotation), we introduced prairie strips to less intensely managed crop treatments. Treatments included conservation land, biologically based (organic) row crops with prairie strips, reduced input row crops with prairie strips, no‐till row crops and conventional row crops. We measured butterfly abundance and richness: (1) within prairie strips and (2) across the gradient of land use intensity at the plot level.Butterfly abundance was higher within prairie strips than in all other treatments. Across the land use intensity gradient at the plot level, the conservation land treatment had the highest abundance, treatments with prairie strips had intermediate levels and no‐till and conventional treatments had the lowest abundances. Also across entire plots, butterfly richness increased as land use intensity decreased. Treatments with prairie strips, which also had reduced land use intensity, had distinct butterfly communities as they harboured several butterfly species that were not found in other row crop treatments.In addition to the known effects of prairie strips on ecosystem services including erosion control and increased water quality, prairie strips can increase biodiversity in multifunctional landscapes. [ABSTRACT FROM AUTHOR]

Deploying distributed generators (DGs) supplied by renewable energy resources poses a significant challenge for efficient power grid operation. The proper sizing and placement of DGs, specifically photovoltaics (PVs) and wind turbines (WTs), remain crucial due to the uncertain characteristics of renewable energy. To overcome these challenges, this study explores an enhanced version of a meta-heuristic technique called the prairie dog optimizer (PDO). The modified prairie dogs optimizer (mPDO) incorporates a novel exploration phase inspired by the slime mold algorithm (SMA) food approach. The mPDO algorithm is proposed to analyze the substantial effects of different dynamic load characteristics on the performance of the distribution networks and the designing of the PV-based and WT-based DGs. The optimization problem incorporates various operational constraints to mitigate energy loss in the distribution networks. Further, the study addresses uncertainties related to the random characteristics of PV and WT power outputs by employing appropriate probability distributions. The mPDO algorithm is evaluated using cec2020 benchmark suit test functions and rigorous statistical analysis to mathematically measure its success rate and efficacy while considering different type of optimization problems. The developed mPDO algorithm is applied to incorporate both PV and WT units, individually and simultaneously, into the IEEE 69-bus distribution network. This is achieved considering residential, commercial, industrial, and mixed time-varying voltage-dependent load demands. The efficacy of the modified algorithm is demonstrated using the standard benchmark functions, and a comparative analysis is conducted with the original PDO and other well-known algorithms, utilizing various statistical metrics. The numerical findings emphasize the significant influence of load type and time-varying generation in DG planning. Moreover, the mPDO algorithm beats the alternatives and improves distributed generators' technical advantages across all examined scenarios. [ABSTRACT FROM AUTHOR]

The growing demand for solar energy conversion underscores the need for precise parameter extraction methods in photovoltaic (PV) plants. This study focuses on enhancing accuracy in PV system parameter extraction, essential for optimizing PV models under diverse environmental conditions. Utilizing primary PV models (single diode, double diode, and three diode) and PV module models, the research emphasizes the importance of accurate parameter identification. In response to the limitations of existing metaheuristic algorithms, the study introduces the enhanced prairie dog optimizer (En-PDO). This novel algorithm integrates the strengths of the prairie dog optimizer (PDO) with random learning and logarithmic spiral search mechanisms. Evaluation against the PDO, and a comprehensive comparison with eighteen recent algorithms, spanning diverse optimization techniques, highlight En-PDO's exceptional performance across different solar cell models and CEC2020 functions. Application of En-PDO to single diode, double diode, three diode, and PV module models, using experimental datasets (R.T.C. France silicon and Photowatt-PWP201 solar cells) and CEC2020 test functions, demonstrates its consistent superiority. En-PDO achieves competitive or superior root mean square error values, showcasing its efficacy in accurately modeling the behavior of diverse solar cells and performing optimally on CEC2020 test functions. These findings position En-PDO as a robust and reliable approach for precise parameter estimation in solar cell models, emphasizing its potential and advancements compared to existing algorithms. [ABSTRACT FROM AUTHOR]

Review of: Prairie Interlace: Weaving, Modernisms, and the Expanded Frame, 1960–2000, Michele Hardy, Timothy Long and Julia Krueger (eds) (2023) Calgary: University of Calgary Press, 248 pp., ISBN 978-1-77385-486-1, h/bk, $99.99 ISBN 978-1-77385-487-8, p/bk, $59.99 ISBN 978-1-77385-489-2, e-book (institutional PDF) ISBN 978-1-77385-490-8, e-book (ePub) [ABSTRACT FROM AUTHOR]

Inventories of the flora and insect fauna of the Black Belt Prairie of Mississippi and Alabama have documented disjunct populations of species broadly distributed in the Great Plains, including two grasshopper species. During a recent survey of a large privately-owned prairie remnant in Sumter Co., Alabama, we documented a disjunct population of a third grasshopper species — Hesperotettix speciosus, extending the known distribution of this species significantly eastwards. The discovery of this population is surprising due to the number of previous survey efforts of the Black Belt, Alabama and Mississippi overall and exemplifies the importance of conservation on private lands. [ABSTRACT FROM AUTHOR]

Context. Prairie dogs (Cynomys spp.) are rodents enjoyed by some humans; yet, they cause crop and property damage, and carry zoonotic disease. Non-lethal control of prairie dogs is of interest in urban/suburban settings. The injectable immunocontraceptive vaccine GonaCon (active ingredient is gonadotropin-releasing hormone [GnRH]) has been shown to be effective at reducing fertility in equine and deer, and is a US EPA-registered vaccine for use in these ungulate species. Aims. To conduct a replicated field study to test efficacy of GonaCon in black-tailed prairie dogs(C. ludovicianus), and if found to be efficacious, to help facilitate the EPA registration of this product for prairie dog management in urban/suburban areas. Methods. Prairie dogs were live-trapped in October–December 2018 in three treatment and three controlsites. Every captured female ≥660 g wasinjected with 0.4 mL of either GonaCon (0.032% w/w GnRH) at treatment sites or a sham vaccine (absent of GnRH) at control sites. Juveniles and adults were counted at all six sites to establish juvenile:adult (ratio) and juvenile density in May–June 2019 (determining initial GonaCon effectiveness) and 2020 (determining persistence of contraception). Key results. In 2019, the juvenile:adult ratio was significantly reduced (P = 0.0022) in GonaCon (mean ± s.e.: 0.23 ± 0.01) relative to the sham (1.10 ± 0.58) sites. Juvenile density was three times greater in sham than GonaCon sites. In 2020, GonaCon sites produced equal offspring to nearby sham sites. Conclusions. GonaCon is highly effective during the first year(2019) but not in the second year(2020) if only a small area (0.6–2.8 ha) orsmall proportion of females in a colony is treated, such as was undertaken in this study. Implications. In 2022, GonaCon− Prairie Dogs was EPA-registered. Treating whole colonies of prairie dogs at once is favoured; yet, if small or partial colony treatment is desired, then annual GonaCon treatment may be needed. [ABSTRACT FROM AUTHOR]

Social isolation affects the brain and behavior in a variety of animals, including humans. Studies in traditional laboratory rodents, including mice and rats, have supported the idea that short-term social isolation promotes affiliative social behaviors, while long-term isolation promotes anti-social behaviors, including increased aggression. Whether the effects of isolation on the social behaviors of mice and rats generalize to other rodents remains understudied. In the current study, we characterized the effects of short-term (3-days) social isolation on the social behaviors of adult prairie voles (Microtus ochrogaster) during same-sex and opposite-sex social interactions. Our experiments revealed that short-term isolation did not affect rates of ultrasonic vocalizations or time spent in non-aggressive social behaviors and huddling during same-sex and opposite-sex interactions. Unexpectedly, although short-term isolation also did not affect time spent in resident-initiated and mutually-initiated aggressive behavior, we found that short-term isolation increased time spent in visitor-initiated aggression during male-male interactions. Our findings highlight the importance of comparative work across species and the consideration of social context to understand the diverse ways in which social isolation can impact social behavior. [ABSTRACT FROM AUTHOR]

Conservation translocations are frequently inhibited by extensive dispersal after release, which can expose animals to dispersal‐related mortality or Allee effects due to a lack of nearby conspecifics. However, translocation‐induced dispersals also provide opportunities to study how animals move across a novel landscape, and how their movements are influenced by landscape configuration and anthropogenic features. Translocation among populations is considered a potential conservation strategy for lesser prairie‐chickens (Tympanuchus pallidicinctus). We determined the influence of release area on dispersal frequency by translocated lesser prairie‐chickens and measured how lesser prairie‐chickens move through grassland landscapes through avoidance of anthropogenic features during their dispersal movements. We translocated 411 lesser prairie‐chickens from northwest Kansas to southeastern Colorado and southwestern Kansas in 2016–2019. We used satellite GPS transmitters to track 115 lesser prairie‐chickens throughout their post‐release dispersal movements. We found that almost all lesser prairie‐chickens that survived from their spring release date until June undergo post‐translocation dispersal, and there was little variation in dispersal frequency by release area (96% of all tracked birds, 100% in Baca County, Colorado, 94% in Morton County, Kansas, n = 55). Dispersal movements (male: 103 ± 73 km, female: 175 ± 108 km, n = 62) led to diffusion across landscapes, with 69% of birds settling >5 km from their release site. During dispersal movements, translocated lesser prairie‐chickens usually travel by a single 3.75 ± 4.95 km dispersal flight per day, selecting for steps that end far from roads and in Conservation Reserve Program (CRP) grasslands. Due to this "stepping stone" method of transit, landscape connectivity is optimized when <5 km separates grassland patches on the landscape. Future persistence of lesser prairie‐chicken populations can be aided through conservation of habitat and strategic placement of CRP to maximize habitat connectivity. Dispersal rates suggest that translocation is better suited to objectives for regional, rather than site‐specific, population augmentation for this species. [ABSTRACT FROM AUTHOR]

Stressors activate the hypothalamic-pituitary-adrenal axis which produces glucocorticoid (GC) hormones. Social buffering, the lowering of glucocorticoid secretion with increased social ties, commonly mitigates the stress response following exposure to a stressor. Black-tailed prairie dogs (Cynomys ludovicianus) are ground-dwelling sciurids that vary their social behaviour over time, and provide an exciting opportunity to investigate social buffering and GC production. We observed social behaviours and measured GC hormones in prairie dogs during the spring (reproduction) and summer. We expected social buffering would reduce GC production in the summer, following the stressors experienced during the spring. However, we found social integration and GC deposition were inversely correlated during the spring, which suggests social buffering occurs during the highly stressful period of reproduction, instead of after. Our study shows that the relationship between social behaviour and GC production is context-dependent, and social buffering may be an adaptive strategy in this colonially-living species. [ABSTRACT FROM AUTHOR]

This paper presents a novel hybrid optimization method to solve the resource allocation problem for multi-target multi-sensor tracking of drones. This hybrid approach, the Improved Prairie Dog Optimization Algorithm (IPDOA) with the Genetic Algorithm (GA), utilizes the strengths of both algorithms to improve the overall optimization performance. The goal is to select a set of sensors based on norms of weighted distances cost function. The norms are the Euclidean distance and the Mahalanobis distance between the drone location and the sensors. The second one depends on the predicted covariance of the tracker. The Extended Kalman Filter (EKF) is used for state estimation with proper clutter and detection models. Since we use Multi-objects to track, the Joint Probability Distribution Function (JPDA) estimates the best measurement values with a preset gating threshold. The goal is to find a sensor or minimum set of sensors that would be enough to generate high-quality tracking based on optimum resource allocation. In the experimentation simulated with Stone Soup, one radar among five radars is selected at every time step of 50-time steps for 200 tracks distributed over 20 different ground truths. The proposed IPDOA provided optimum solutions for this complex problem. The obtained solution is an optimum offline solution that is used to select one or more sensors for any future flights within the vicinity of the 5 radars. Environment and conditions are assumed to be similar in future drone flights within the radars' defined zone. The IPDOA performance was compared with the other 8 metaheuristic optimization algorithms and the testing showed its superiority over those techniques for solving this complex problem. The proposed simulated model can find the most relevant sensor(s) capable of generating the best quality tracks based on weighted distance criteria (Euclidean and Mahalanobis). That would cut down the cost of operating extra sensors and then it would be possible to move them to other vicinity. [ABSTRACT FROM AUTHOR]

Introduction: The mesolimbic reward system is associated with the promotion and rewarding benefits of social relationships. In the socially monogamous prairie vole (Microtus ochrogaster), the establishment of a pair bond can be displayed by a robust preference for a breeding partner and aggressive rejection of unfamiliar conspecifics. Mesolimbic dopamine signaling influences bondrelated behaviors within the vole through dopamine transmission and receptor activity in the nucleus accumbens. However, only one experiment has examined how the ventral tegmental area (VTA), a region that produces much of the foreand mid-brain dopamine, regulates these social behaviors. Specifically, inhibition of either glutamate or GABA neurons in the VTA during a brief courtship promoted a partner preference formation in male prairie voles. The VTA is a heterogeneous structure that contains dopamine, GABA, and glutamate neurons as well as receives a variety of projections including corticotropin-releasing factor (CRF) suggested to modulate dopamine release. Methods: We used pharmacological manipulation to examine how GABA and CRF signaling in the VTA modulate partner preference formation in male and female prairie voles. Specifically, we used a 3 h partner preference test, a social choice test, to assess the formation of a partner preference following an infused bicuculline and CRF during a 1 h cohabitation and muscimol and CP154526, a CRFR1 antagonist, during a 24 h cohabitation with an opposite-sex conspecific. Results: Our study demonstrated that bicuculline, a GABAA receptor antagonist, and CRF in the VTA promoted a partner preference, whereas low-dose muscimol, a GABAA receptor agonist, and CP154526, a CRFR1 antagonist, inhibited a partner preference in both male and female prairie voles. Conclusion: This study demonstrated that GABA and CRF inputs into the VTA is necessary for the formation of a partner preference in male and female prairie voles. [ABSTRACT FROM AUTHOR]

Simple Summary: Prairie dogs are native to the United States, Canada, and Mexico. They have been brought to Thailand and become popular as exotic pets and providing humans with exotic pets in close-contact environments. Prairie dogs have been known to carry several waterborne protozoan pathogens. One of those pathogens is known as Giardia, a flagellate protozoan parasite which can cause gastrointestinal illness in humans and other animals. This study has identified the Giardia parasite in the feces of prairie dogs. There were 13% of prairie dogs pets in Bangkok, Thailand that carried the Giardia parasite. We also found that the parasite was categorized as a human parasite. Therefore, there was potential risk that prairie dogs could contract a Giardia infection from humans as a source, and that humans could receive the parasite from their exotic pets via the fecal-oral route in shared environments. We suggest that exotic pet owners should pay more attention to effective sanitation and provide clean food and water for their exotic pets. Owners should bring their exotic pets for veterinary services and screening of zoonotic pathogens using fecal examination regularly. Treatment can successfully cure the infected pets as well as prevent the spreading of pathogen to the environment. Giardia is a flagellate protozoa that can be transmitted via direct contact and by consuming contaminated water. It is pathogenic in humans and various other animals, including exotic pets. Pet prairie dogs are popular in Thailand, but they have not been investigated regarding giardiasis. Giardia infection was measured, and genetic characterization was performed to investigate the zoonotic potential of Giardia carried by pet prairie dogs. In total, 79 fecal samples were examined from prairie dogs visiting the Kasetsart University Veterinary Teaching Hospital during 2017–2021. Simple floatation was conducted. Two Giardia-positive samples were submitted for DNA extraction, PCR targeting the Giardiassu rRNA, tpi and gdh genes was performed, and genetic characterization using sequencing analysis was conducted. Risk factors associated with Giardia infection were analyzed. Giardia infection was found in 11 out of the 79 pet prairie dogs (13.9%). Giardia infection was significantly higher in male prairie dogs (p = 0.0345). Coccidia cysts (12.7%), the eggs of nematodes (6.3%), and amoeba cysts (2.5%) were also detected. Genetic characterization of the two Giardia-positive samples revealed that they were G. duodenalis assemblage A, sub-genotypes AI and assemblage B, and sub-genotype BIV, the zoonotic assemblages. This was the first report of Giardia infection in pet prairie dogs in Bangkok, Thailand. The results revealed that these pet prairie dogs in Thailand were infected with zoonotic assemblages of G. duodenalis sub-genotype AI, which might have been derived from animal contaminants, whereas sub-genotype BIV might have been derived from human contaminants. Owners of prairie dogs might be at risk of giardiasis or be the source of infection to their exotic pets. [ABSTRACT FROM AUTHOR]

The conservation and management of black‐tailed prairie dogs (Cynomys ludovicianus) have been contentious issues in grasslands of central North America for much of the past century, primarily because of the perception that they compete with livestock for forage. Studies quantifying the magnitude of competition between prairie dogs and cattle are difficult to conduct because of the large spatial and long temporal scales needed to quantify how competition varies in response to interannual variation in precipitation and prairie dog abundance. We examined variation in mass gains of yearling steers in shortgrass steppe of northeastern Colorado, USA, with and without prairie dogs from 2008–2019, a period that encompassed a full cycle in prairie dog abundance from a nadir following plague‐induced population collapse, to peak abundance following population recovery, to plague‐induced population lows again. Analyses of cattle grazing distribution with global positioning system (GPS)‐collars revealed preferential grazing on colonies following a period of unusually high vegetation production, and preferential grazing off colonies following a period of rapid vegetation senescence, but these patterns were not clearly related to cattle mass gains. Across all 12 years of the study, average daily mass gain (ADG) during the growing season was 0.97 kg/steer/day in pastures where prairie dogs were controlled annually, and 0.95 kg/steer/day in pastures where they were not. Average daily mass gain was a quadradic function of precipitation and a linear function of prairie dog occupancy within a pasture, with a generalized linear mixed model predicting an 8.0% decrease in ADG as prairie dog occupancy increased from 0 to 60% of a pasture with average growing‐season precipitation. We did not detect a significant interaction between precipitation and prairie dog occupancy, but one limitation of our study is that the only drought year (2012) occurred when prairie dogs occupied low percentages (10–25%) of the study pastures. Prairie dogs had a small but detectable negative effect on cattle mass gains during the growing season in shortgrass steppe. The magnitude of this effect can be used by managers in combination with market conditions and the spatial extent of prairie dog colonies to estimate economic effects of prairie dogs on livestock operations. © 2021 The Wildlife Society. This article is a U.S. Government work and is in the public domain in the USA. : Mass gain of cattle during the growing season declined linearly by 8% as prairie dog occupancy of shortgrass pastures increased from 0 to 60%. Decisions on the need to manage prairie dog populations could be based on the magnitude of the effect documented in our study, market values of cattle, and the costs of prairie dog control, but managers should also consider the potential for drought to coincide with peak prairie dog abundance, the frequency and timing of plague epizootics in the prairie dog population, and costs of alternative forage sources during drought. [ABSTRACT FROM AUTHOR]

Contamination of soil by spills of crude oil and oilfield brine is known to affect the species composition and functioning of soil microbial communities. However, the effect of such contamination on nitrogen cycling, an important biogeochemical cycle in tallgrass prairie soil, is less well known. Detecting nitrate-reducing (NR) and denitrifying (DN) bacteria via PCR amplification of the genes essential for these processes depends on how well PCR primers match the sequences of these bacteria. In this study, we enriched for NR and DN bacteria from oil/brine tallgrass prairie soil contaminated 5–10 years previously versus those cultured from uncontaminated soil, confirmed the capacity of 75 strains isolated from the enrichments to reduce nitrate and/nitrite, then screened the strains with primers specific to seven nitrogen cycle functional genes. The strains comprised a phylogenetically diverse group of NR and DN bacteria, with proportionately more γ-Proteobacteria in oil-contaminated sites and more Bacilli in brine-contaminated sites, suggesting some residual effect of the contaminants on the NR and DN species distribution. Around 82% of the strains shown to reduce nitrate/nitrite would not be identified as NR and DN bacteria by the battery of NR and DN primers used. Our results indicate an urgent need to expand the NR/DN functional gene primer database by first identifying novel NR/DN strains through their capacity to reduce nitrate/nitrite. [ABSTRACT FROM AUTHOR]

Yersinia pestis, causative agent of plague, occurs throughout the western United States in rodent populations and periodically causes epizootics in susceptible species, including black‐tailed prairie dogs (Cynomys ludovicianus). How Y. pestis persists long‐term in the environment between these epizootics is poorly understood but multiple mechanisms have been proposed, including, among others, a separate enzootic transmission cycle that maintains Y. pestis without involvement of epizootic hosts and persistence of Y. pestis within epizootic host populations without causing high mortality within those populations. We live‐trapped and collected fleas from black‐tailed prairie dogs and other mammal species from sites with and without black‐tailed prairie dogs in 2004 and 2005 and tested all fleas for presence of Y. pestis. Y. pestis was not detected in 2126 fleas collected in 2004 but was detected in 294 fleas collected from multiple sites in 2005, before and during a widespread epizootic that drastically reduced black‐tailed prairie dog populations in the affected colonies. Temporal and spatial patterns of Y. pestis occurrence in fleas and genotyping of Y. pestis present in some infected fleas suggest Y. pestis was introduced multiple times from sources outside the study area and once introduced, was dispersed between several sites. We conclude Y. pestis likely was not present in these black‐tailed prairie dog colonies prior to epizootic activity in these colonies. Although we did not identify likely enzootic hosts, we found evidence that deer mice (Peromyscus maniculatus) may serve as bridging hosts for Y. pestis between unknown enzootic hosts and black‐tailed prairie dogs. [ABSTRACT FROM AUTHOR]

The quality of romantic relationships can predict health consequences related to aging. DNA methylation-based biomarkers of aging accurately estimate chronological age. We developed several highly accurate epigenetic aging clocks, based on highly conserved mammalian CpGs, for the socially monogamous prairie vole (Microtus ochrogaster). In addition, our dual-species human-vole clock accurately measured relative age and illustrates high species conservation of epigenetic aging effects. Next, we assessed how pair bonding impacts epigenetic aging. We did not find evidence that pair-bonded voles exhibit accelerated or decelerated epigenetic aging effects in blood, ear, liver, or brain tissue. Our epigenome wide association study identified CpGs in five genes strongly associated with pair bonding: Foxp4, Phf2, Mms22l, Foxb1, and Eif1ad. Overall, we present accurate DNA methylation-based estimators of age for a species of great interest to researchers studying monogamy in animals. We did not find any evidence that sex-naive animals age differently from pair-bonded animals. [ABSTRACT FROM AUTHOR]

The management of the new North American prairie at Wakehurst Place is described, including the difficulties faced when some species threaten to become dominant. [ABSTRACT FROM AUTHOR]

The prairie dog optimization (PDO) algorithm is a metaheuristic optimization algorithm that simulates the daily behavior of prairie dogs. The prairie dog groups have a unique mode of information exchange. They divide into several small groups to search for food based on special signals and build caves around the food sources. When encountering natural enemies, they emit different sound signals to remind their companions of the dangers. According to this unique information exchange mode, we propose a randomized audio signal factor to simulate the specific sounds of prairie dogs when encountering different foods or natural enemies. This strategy restores the prairie dog habitat and improves the algorithm's merit-seeking ability. In the initial stage of the algorithm, chaotic tent mapping is also added to initialize the population of prairie dogs and increase population diversity, even use lens opposition-based learning strategy to enhance the algorithm's global exploration ability. To verify the optimization performance of the modified prairie dog optimization algorithm, we applied it to 23 benchmark test functions, IEEE CEC2014 test functions, and six engineering design problems for testing. The experimental results illustrated that the modified prairie dog optimization algorithm has good optimization performance. [ABSTRACT FROM AUTHOR]

Grasshoppers are major consumers of plant biomass in grassland and shrubland ecosystems. While often considered generalists, grasshopper species have differing habitat preferences and interactions with other consumers in grasslands. There are conflicting accounts of how prairie dog colonies and differences in vegetation impact grasshopper abundance and composition. We conducted a landscape-scale survey of grasshopper communities, plant communities, and prairie dogs in a grassland/shrubland ecosystem in eastern Wyoming. Over the study landscape, spurthroat grasshoppers (Melanoplinae) were associated with lower sagebrush cover and lower cover of C3 perennial graminoids, bandwing grasshoppers (Oedipodinae) were associated with low-lying areas with a high cover of C4 grasses and a low cover of cheatgrass, and slantface grasshoppers (Gomphocerinae) were associated with low vegetation height. Prairie dogs, presumably because of their effects on vegetation, had different impacts on different groups of grasshoppers. Melanoplinae grasshoppers, the Wyoming toothpick grasshopper (Paropomala wyomingensis Thomas), and grasshoppers with early-season phenology were associated with prairie dog colonies. However, because some species of grasshoppers were positively and others negatively associated with prairie dogs, the net effect of prairie dogs on total grasshopper biomass was neutral. Thus, to determine the role of grasshoppers in prairie ecosystems, it will be important to determine whether there is functional equivalence of grasshopper species in consuming plant biomass and as food for vertebrates. [ABSTRACT FROM AUTHOR]

An efficient task scheduling plays an important role in facilitating the virtual resource in a cloud computing environment by minimalizing make span and enhancing the allocation of resources. Requests for resources are treated as tasks, and appropriate resources are allocated based on user requirements. But, due to high demand and requests, the cloud has difficulty allocating resources. To overcome the issues, this research introduced an optimization-based task scheduling approach. The Multi-Objective Prairie Dog Optimization (MOPDO) algorithm is introduced which considers the makespan time and the execution time as the major objective while allocating resources in IoT. The proposed MOPDOA effectively allocates the resource to the Virtual Machines (VMs) by choosing the host with maximized resources. The search mechanism with the help of MOPDO helps to detect a suitable VM for resource allocation will be continued. After the process of allotting the resources to VMs, the load balancing process must be initiated to schedule the tasks for VMs. When the task count is assigned as 100, the makespan time of MOPDOA is 12s while Particle Swarm Gray Wolf Optimization (PSGWO) obtains a makespan time of the 20s. Similarly, for different VMs, the proposed approach is 175.45s for execution whereas the existing Improved Multi-Objective Multi-Verse Optimizer obtains 186.33s to execute for 10 VMs. [ABSTRACT FROM AUTHOR]

Background. Wildfire on rangelands in the mixed grassland can severely disrupt livestock operations. Understanding how fire severity impacts post-fire production recovery is important for grazing management. Aims. We examined how topography and other environmental factors influence wildfire severity, or the consumption of biomass and exposure of soil, under extreme (>120 km h-1) wind conditions in native mixed grass prairie in western Canada. We also examined how variation in fire severity impacts grassland production recovery. Methods. Fire severity and production recovery were measured using the bare soil index (BSI) and normalised difference vegetation index (NDVI). Impacts of topography, wind exposure, and site capability on fire severity and production recovery were assessed using generalised additive models. Key results. Fire severity varied as a function of slope, wind exposure and fuel load. Severity peaked at NDVI between 0 and 0.4, values associated with high litter content and minimal green vegetation. Interactions between slope and aspect with respect to dominant wind direction generated very high fire severity on slopes greater than 15° that faced into the wind. Production recovery increased moderately with higher fire severity and recovery was generally higher on sites with lower potential productivity. Implications. Post-fire production recovery was rapid; fire severity and site capability had only modest impacts on recovery rates demonstrating the resilience of grassland ecosystems to even severe wildfire. [ABSTRACT FROM AUTHOR]

Introduction: The social defeat paradigm is the most representative animal model to study social anxiety disorder (SAD) and its underlying neuronal mechanisms. We have previously reported that defeat progressively reduces oxytocin receptors (OXTR) in limbic regions of the brain over an eight-week period in female prairie voles (Microtus ochrogaster). Oxytocin receptors activate the mitogen-activated protein kinase (MAPK) pathway, which has been previously associated with the anxiolytic effects of oxytocin. Here, we assessed the functional significance of OXTR in stress-induced social avoidance and the response of the MAPK signaling pathway in the nucleus accumbens (NAc), anterior cingulate cortex (ACC), and basolateral amygdala (BLA) of female prairie voles. Methods: In experiment 1, Sexually naïve adult female prairie voles were defeated for three consecutive days and tested a week after for social preference/avoidance (SPA) test. Control subjects were similarly handled without defeat conditioning. In experiment 2, sexually and stress naïve adult female prairie voles were bilaterally injected into the NAc, ACC, or the BLA with a CRISPR/Cas9 virus targeting the Oxtr coding sequence to induce OXTR knockdown. Two weeks post-surgery, subjects were tested for SPA behavior. Viral control groups were similarly handled but injected with a control virus. A subgroup of animals from each condition in both experiments were similarly treated and euthanized without being tested for SPA behavior. Brains were harvested for OXTR autoradiography, western blot analysis of MAPK proteins and quantification of local oxytocin content in the NAc, BLA, ACC, and PVN through ELISA. Results: Social defeat reduced OXTR binding in the NAc and affected MAPK pathway activity and oxytocin availability. These results were region-specific and sensitive to exposure to the SPA test. Additionally, OXTR knockdown in the NAc, ACC, and BLA induced social avoidance and decreased basal MAPK activity in the NAc. Finally, we found that OXTR knockdown in these regions was associated with less availability of oxytocin in the PVN. Conclusion: Dysregulation of the oxytocin system and MAPK signaling pathway in the NAc, ACC, and BLA are important in social behavior disruptions in female voles. This dysregulation could, therefore, play an important role in the etiology of SAD in women. [ABSTRACT FROM AUTHOR]

Context: Prairies historically covered much of inland North America, and many species have adapted to the unique conditions found in prairie ecosystems. Less than 1% of prairies remain in Arkansas, with much historic prairie having been converted for urban and agricultural development, resulting in steep population declines for many prairie-associated species. Objectives: Because many reptile and amphibian species are difficult to detect, the current distributions and habitat requirements of prairie-associated herpetofauna in fragmented landscapes are poorly understood. Thus, we assessed the state of prairie-associated herpetofauna communities in intact prairie, as well in degraded and developed historic prairie throughout Western Arkansas. Methods: Using repeated field surveys, remote sensing data, and hierarchical community occupancy models, we examined the influence of vegetation conditions, land use, and landscape characteristics on an assemblage of nine species of prairie-associated herpetofauna. Results: Prairie mound density, representing prairie that has not been subject to intense anthropogenic disturbance, was the strongest positive predictor of occupancy by prairie-associated species. Historic prairie area also exhibited a positive relationship with occupancy for several species but not at the assemblage level. Current vegetation conditions did not strongly influence occupancy patterns. Conclusions: Our results suggest that long-term land use filters, rather than present site-level conditions, are the driving forces dictating current distributions of prairie-associate herpetofauna in Western Arkansas. Our findings provide insight into the present state of understudied populations in an increasingly fragmented region and present accessible tools for directing exploratory conservation and research efforts. [ABSTRACT FROM AUTHOR]

Understanding dispersal potential, or the probability a species will move a given distance, under different environmental conditions is essential to predicting species' ability to move across the landscape and track shifting ecological niches. Two important drivers of dispersal ability are climatic differences and variations in local habitat type. Despite the likelihood these global drivers act simultaneously on plant populations, and thus dispersal potential is likely to change as a result, their combined effects on dispersal are rarely examined. To understand the effect of climate and varying habitat types on dispersal potential, we studied Geum triflorum—a perennial grassland species that spans a wide range of environments, including both prairie and alvar habitats. We explored how the climate of the growing season and habitat type (prairie vs. alvar) interact to alter dispersal potential. We found a consistent interactive effect of climate and habitat type on dispersal potential. Across prairie populations, an increased number of growing degree days favored traits that increase dispersal potential or the probability of dispersing farther distances. However, for alvar populations, dispersal potential tended to decrease as the number of growing degree days increased. Our findings suggest that under continued warming, populations in prairie habitats will benefit from increased gene flow, while alvar populations will become increasingly segregated, with reduced potential to track shifting fitness optima. [ABSTRACT FROM AUTHOR]

Monoculture switchgrass and restored prairie are promising perennial feedstock sources for bioenergy production on the lands unsuitable for conventional agriculture. Such lands often display contrasting topography that influences soil characteristics and interactions between plant growth and soil C gains. This study aimed at elucidating the influences of topography and plant systems on the fate of C originated from switchgrass plants and on its relationships with soil pore characteristics. For that, switchgrass plants were grown in intact soil cores collected from two contrasting topographies, namely steep slopes and topographical depressions, in the fields in multi-year monoculture switchgrass and restored prairie vegetation. The 13C pulse labeling allowed tracing the C of switchgrass origin, which X-ray computed micro-tomography enabled in-detail characterization of soil pore structure. In eroded slopes, the differences between the monoculture switchgrass and prairie in terms of total and microbial biomass C were greater than those in topographical depressions. While new switchgrass increased the CO2 emission in depressions, it did not significantly affect the CO2 emission in slopes. Pores of 18–90 µm Ø facilitated the accumulation of new C in soil, while > 150 µm Ø pores enhanced the mineralization of the new C. These findings suggest that polyculture prairie located in slopes can be particularly beneficial in facilitating soil C accrual and reduce C losses as CO2. [ABSTRACT FROM AUTHOR]

Understanding dispersal potential, or the probability a species will move a given distance, under different environmental conditions is essential to predicting species' ability to move across the landscape and track shifting ecological niches. Two important drivers of dispersal ability are climatic differences and variations in local habitat type. Despite the likelihood these global drivers act simultaneously on plant populations, and thus dispersal potential is likely to change as a result, their combined effects on dispersal are rarely examined. To understand the effect of climate and varying habitat types on dispersal potential, we studied Geum triflorum—a perennial grassland species that spans a wide range of environments, including both prairie and alvar habitats. We explored how the climate of the growing season and habitat type (prairie vs. alvar) interact to alter dispersal potential. We found a consistent interactive effect of climate and habitat type on dispersal potential. Across prairie populations, an increased number of growing degree days favored traits that increase dispersal potential or the probability of dispersing farther distances. However, for alvar populations, dispersal potential tended to decrease as the number of growing degree days increased. Our findings suggest that under continued warming, populations in prairie habitats will benefit from increased gene flow, while alvar populations will become increasingly segregated, with reduced potential to track shifting fitness optima. [ABSTRACT FROM AUTHOR]