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Abstract In the mid-continental grasslands of North America, climate change is increasing the intensity and frequency of extreme weather events. Increasingly severe storms and prolonged periods of elevated temperatures can impose challenges that adversely affect an individual's condition and, ultimately, survival. However, despite mounting evidence that extreme weather events, such as heavy rain storms, can impose short-term physiological challenges, we know little regarding the putative costs of such weather events. To determine the consequences of extreme weather for small endotherms, we tested predictions of the relationships between both severe precipitation events and wet bulb temperatures (an index that combines temperature and humidity) prior to capture with body composition and hematocrit of grasshopper sparrows (Ammodramus savannarum) caught during the breeding season at the Konza Prairie Biological Station, Kansas, USA, between 2014 and 2016. We measured each individual's fat mass, lean mass and total body water using quantitative magnetic resonance in addition to their hematocrit. Individuals exposed to storms in the 24 hours prior to capture had less fat reserves, more lean mass, more water and higher hematocrit than those exposed to moderate weather conditions. Furthermore, individuals stored more fat if they experienced high wet bulb temperatures in the week prior to capture. Overall, the analysis of these data indicate that extreme weather events take a physiological toll on small endotherms, and individuals may be forced to deplete fat stores and increase erythropoiesis to meet the physiological demands associated with surviving a storm. Elucidating the potential strategies used to cope with severe weather may enable us to understand the energetic consequences of increasingly severe weather in a changing world. 

Abstract Many exogenous factors may influence demographic rates (i.e., births, deaths, immigration, emigration), particularly for migratory birds that must cope with variable weather and habitat throughout their range and annual cycle. In midcontinental grasslands, disturbance (e.g., fire and grazing) and precipitation influence variation in grassland structure and function, but we know little about when and why precipitation is associated with grassland species' vital rates. We related estimates of detection, survival, and emigration toa priorisets of precipitation metrics to test the putative alternative factors influencing movement and mortality in grasshopper sparrows (Ammodramus savannarum). This species is a migratory songbird that exhibits exceptionally high rates of within‐season and between‐season dispersal. Between 2013 and 2020, we captured and resighted grasshopper sparrows in northeastern Kansas, USA, compiling capture histories for 1,332 adult males. We tested predictions of climatic hypotheses explaining variation in survival and emigration throughout a grasshopper sparrow's annual cycle; both survival and emigration were associated with the El Niño‐Southern Oscillation precipitation index (ESPI). Survival was positively related with ESPI during winter, and temporary emigration was curvilinearly related to breeding season ESPI lagged 2 years, with the highest site fidelity associated with intermediate rainfall values. The relationship between rainfall and temporary emigration likely reflects the influence of weather over multiple years on vegetation structure with consequent effects on local demography. This study provides compelling support for the idea that grassland species respond to high interannual variability by adopting dispersal strategies unlike those of many well‐studied migrant birds. Furthermore, the results imply that the consequences of increasing climatic extremes may not be immediately apparent, with demographic consequences lasting for at least a few years. 

Abstract Spatial models for occupancy data are used to estimate and map the true presence of a species, which may depend on biotic and abiotic factors as well as spatial autocorrelation. Traditionally researchers have accounted for spatial autocorrelation in occupancy data by using a correlated normally distributed site‐level random effect, which might be incapable of modeling nontraditional spatial dependence such as discontinuities and abrupt transitions. Machine learning approaches have the potential to model nontraditional spatial dependence, but these approaches do not account for observer errors such as false absences. By combining the flexibility of Bayesian hierarchal modeling and machine learning approaches, we present a general framework to model occupancy data that accounts for both traditional and nontraditional spatial dependence as well as false absences. We demonstrate our framework using six synthetic occupancy data sets and two real data sets. Our results demonstrate how to model both traditional and nontraditional spatial dependence in occupancy data, which enables a broader class of spatial occupancy models that can be used to improve predictive accuracy and model adequacy. 

Abstract Intensification of livestock production has reduced heterogeneity in vegetative structure in managed grasslands, which has been linked to widespread declines in grassland songbird populations throughout North America. Patch-burn grazing management aims to restore some of that heterogeneity in vegetative structure by burning discrete pasture sections, so that cattle preferentially graze in recently burned areas. Although patch-burn grazing can increase reproductive success of grassland songbirds, we know little about possible interactions with regional variation in predator communities or brood parasite abundance, or annual variation in weather conditions. Using six years of data from two tallgrass prairie sites in eastern Kansas, USA, we tested effects of patch-burn grazing on the rates of brood parasitism, clutch size, nest survival, and fledging success of three common grassland songbirds, Dickcissels (Spiza americana), Eastern Meadowlarks (Sturnella magna), and Grasshopper Sparrows (Ammodramus savannarum), among pastures managed with patch-burn grazing versus pastures that were annually burned and either grazed or ungrazed. Dickcissel nests experienced lower parasitism (72.8 ± 4.6% SE vs. 89.1 ± 2.2%) and Eastern Meadowlarks had higher nest survival (63.2 ± 20.5% vs. 16.5 ± 3.5%) in annually burned and ungrazed pastures than pastures managed with patch-burn grazing. However, average number of host fledglings per nesting attempt did not differ among management treatments for any species. Annual variation in weather conditions had a large effect on vegetation structure, but not on reproductive success. Probability of brood parasitism was consistently high (25.5‒84.7%) and nest survival was consistently low (9.9–16.9%) for all species pooled across treatments, sites, and years, indicating that combined effects of predation, parasitism and drought can offset potential benefits of patch-burn grazing management previously found in tallgrass prairies. Although differences in reproductive success among management treatments were minimal, patch-burn grazing management could still benefit population dynamics of grassland songbirds in areas where nest predators and brood parasites are locally abundant by providing suitable nesting habitat for bird species that require greater amounts of vegetation cover and litter, generally not present in burned pastures. 

Abstract Human induced climate and land‐use change are severely impacting global biodiversity, but how community composition and richness of multiple taxonomic groups change in response to local drivers and whether these responses are synchronous remains unclear. We used long‐term community‐level data from an experimentally manipulated grassland to assess the relative influence of climate and land use as drivers of community structure of four taxonomic groups: birds, mammals, grasshoppers, and plants. We also quantified the synchrony of responses among taxonomic groups across land‐use gradients and compared climatic drivers of community structure across groups. All four taxonomic groups responded strongly to land use (fire frequency and grazing), while responses to climate variability were more pronounced in grasshoppers and small mammals. Animal groups exhibited asynchronous responses across all land‐use treatments, but plant and animal groups, especially birds, exhibited synchronous responses in composition. Asynchrony was attributed to taxonomic groups responding to different components of climate variability, including both current climate conditions and lagged effects from the previous year. Data‐driven land management strategies are crucial for sustaining native biodiversity in grassland systems, but asynchronous responses of taxonomic groups to climate variability across land‐use gradients highlight a need to incorporate response heterogeneity into management planning. 

North America’s grassland birds remain in crisis despite decades of conservation effort s. This review pro- vides an overview of factors contributing to these declines, as well as strategies and resources available to a diversity of stakeholders to help conserve grassland bird communities with an emphasis on the Great Plains—a grassland region of global ecological significance and a habitat stronghold for grassland birds. Grassland bird declines are driven by historical and continuing threats across the full annual cycle including grassland habitat loss, agriculture intensification, woody encroachment, and disruption of fire and grazing regimes. More recently, energy development activities, the use of neonicotinoid pesticides, and anthropogenic climate change have emerged as additional threats. While threats to grassland birds are numerous and often synergistic, possibilities for conservation are also diverse and multifaceted. Land set-aside programs, incentives and voluntary practices for producers, improved environmental manage- ment by energy and utility companies, and policy and regulation can all contribute to the conservation of these unique species. We suggest that future grassland bird research should focus on poorly studied aspects of the annual cycle, such as overwinter survival and habitat use, and the migratory period, which remains completely unexplored for many species. Filling these knowledge gaps may facilitate more so- phisticated population modeling that can identify limiting factors and more effectively guide investment in conservation.