Clinton T. Moore’s research while affiliated with University of Georgia and other places

The U.S. Fish and Wildlife Service (Service) is a primary manager of federal public lands in the northern Great Plains region, with over 400,000 hectares (ha) of mostly grassland and wetland administered under the National Wildlife Refuge System (NWRS). More specifically, the Service manages > 100,000 ha of mixed-grass and tallgrass prairie in northern Great Plains states. Prairies range from small, isolated < 16-ha tracts embedded in agricultural landscapes to > 10,000-ha contiguous tracts embedded within grassland-dominated landscapes. The mission of the NWRS is uniquely wildlife/wildland oriented, with human uses secondary in importance. As such, the expectation is that natural plant communities occur as relatively high-quality habitats. Grant et al. (2009) explored this expectation, concluding that “Despite 40–70 years of protection, the integrity of many prairies held in public trust continues to decline, primarily because of invasion by cool-season, introduced plants and woody vegetation.” To address this concern, the Service proposed a program to evaluate restoration of Service-owned prairies following principles of adaptive management, including a decision support function. Our purpose in this paper is to update 14 years of development and implementation of the Native Prairie Adaptive Management (NPAM) program. We confirmed that Service-owned prairies continue to be degraded by invasive plants, especially Bromus inermis (smooth brome) and Poa pratensis (Kentucky bluegrass). However, NPAM has facilitated a significant gain in our understanding of ecological restoration and management of prairies in the region, increasing hope that restoration successes can occur when viewed over the long-term (i.e., many decades).

Wildlife conservation involves making management decisions with incomplete knowledge of ecological relationships. Efforts to augment foraging resources for the endangered Mexican long‐nosed bat ( Leptonycteris nivalis ) are progressing despite limited knowledge about the species' foraging behavior and requirements. This study aimed to understand L. nivalis responses to floral resource availability, focusing on individual agave‐ and local‐scale characteristics influencing visitation rates to flowering agaves. We observed bat visitation at 62 flowering agaves around two roosts in northeast Mexico on 46 nights in the summers of 2017 and 2018. We found visitation rate had positive relationships with two agave‐scale characteristics: the number of umbels with open flowers and the lower vertical position on the stalk of those umbels (i.e., earlier phenological stages of flowering). However, these factors exhibited strong negative interaction: with few umbels with open flowers, the position of flowering umbels had little effect on visitation rate, but when umbels with open flowers were abundant, visitation rate was more strongly related to the lower flowering umbel position. We also found relationships between visitation rate and two local‐scale characteristics: negative for the density of flowering conspecifics within 30 m of the focal agave and positive for the density of dead standing agave stalks within 30 m. Our findings suggest opportunities to augment foraging resources for L. nivalis in ways that are consistent with their foraging behavior, including: increasing the supply of simultaneously blooming flowers by planting agave species that tend to have more umbels with simultaneously open flowers; planting multiple species of agaves with different flowering times to increase the availability of agaves with open flowers on lower‐positioned umbels throughout the period when bats are present in the region; planting agaves in clusters; and keeping dead standing agave stalks on the landscape. Our study points to useful management strategies that can be implemented and monitored as part of an adaptive management approach to aid in conservation efforts.

Wildlife conservation involves making management decisions with incomplete knowledge of biological and ecological relationships. Efforts to augment foraging resources for the endangered Mexican long-nosed bat (Leptonycteris nivalis) are progressing despite limited knowledge about the species’ foraging behavior and requirements. This study sought to fill knowledge gaps about L. nivalis responses to floral resource availability by addressing individual plant and local-scale (30 m) characteristics that influence visitation rates to flowering agaves. We observed bat visitation at 62 flowering agaves around two roosting caves in northeast Mexico on 46 nights in summers 2017 and 2018. We found visitation rate had positive relationships with two agave-scale characteristics: the number of umbels (flower clusters) with open flowers and earlier phenological stages of plants. A negative interaction between the significant predictors indicated that direction of the relationship between visitation and either characteristic depended on the level of the other characteristic. We also found relationships between visitation rate and two local-scale characteristics: negative for the density of flowering conspecifics within 30 m of the focal plant and positive for the density of dead standing stalks within 30 m. Our findings suggest opportunities to augment foraging resources for L. nivalis in ways that are consistent with the bats’ foraging behavior, including: planting larger agave species with more flowers, planting multiple species of agaves with different flowering times to ensure nectar availability when L. nivalis is present in northeast Mexico, planting agaves in clusters, and keeping dead standing stalks on the landscape. Our study highlights important considerations for management actions, which will ultimately aid the development of ongoing conservation efforts.

Consideration of the full annual cycle population dynamics can provide useful insight for conservation efforts, but collecting data needed to estimate demographic parameters is often logistically difficult. For species that breed in remote areas, monitoring is often conducted during migratory stopover or at nonbreeding sites, and the recruitment rate of new breeding adults can be difficult to estimate directly. Here, we present an integrated population model that uses mark‐resight and count data to estimate survival probability, population growth rate, and recruitment rate for an Arctic‐breeding shorebird of conservation concern, the red knot (Calidris canutus rufa), from data collected during spring stopover in Delaware Bay, USA, from 2005 to 2018. At this site, red knots feed primarily on the eggs of spawning horseshoe crabs (Limulus polyphemus), a legally harvested species. We used this model to estimate the relationship between horseshoe crab abundance and red knot demographics, which informed a recent revision to the framework used to establish horseshoe crab harvest regulations. Our analysis indicates that the red knot population was most likely stable from 2005 to 2018 (average λ = 1.03, 95% credible interval [CRI]: 0.961, 1.15) despite low recruitment rates (average ρ = 0.088, 95% CRI: 0.012, 0.18). Adult survival probability was positively associated with horseshoe crab abundance in the same year (β = 0.35, 95% CRI: 0.09, 0.63), but we found no effect of horseshoe crab abundance two years previously on recruitment of new adults (β = −0.08, 95% CRI: −0.41, 0.38). Our approach demonstrates the utility of integrated population models for understanding population dynamics, even when data are only available from migratory stopover monitoring.

Population models often require detailed information on sex-, age-, or size-specific abundances, but population monitoring programs cannot always acquire data at the desired resolution. Thus, state uncertainty in monitoring data can potentially limit the demographic resolution of management decisions, which may be particularly problematic for stage-or size-structured species subject to consumptive use. American alligators (Alligator mississippiensis; hereafter alligator) have a complex life history characterized by delayed maturity and slow somatic growth, which makes the species particularly sensitive to overharvest. Though alligator populations are subject to recreational harvest throughout their range, the most widely used monitoring method (nightlight surveys) is often unable to obtain size class-specific counts, which limits the ability of managers to evaluate the effects of harvest policies. We constructed a Bayesian integrated population model (IPM) for alligators in Georgetown County, SC, USA, using records of mark-recapture-recovery, clutch size, harvest, and nightlight survey counts collected locally, and auxiliary information on fecundity, sex ratio, and somatic growth from other studies. We created a multistate mark-recapture-recovery model with six size classes to estimate survival probability, and we linked it to a state-space count model to derive estimates of size class-specific detection probability and abundance. Because we worked from a count dataset in which 60% of the original observations were of unknown size, we treated size class as a latent property of detections and developed a novel observation model to make use of information where size could be partly observed. Detection probability was positively associated with alligator size and water temperature, and negatively influenced by water level. Survival probability was lowest in the smallest size class but was relatively similar among the other five size classes (>0.

Line‐transect distance sampling (LTDS) surveys are commonly used to estimate abundance of animals or objects. In terrestrial LTDS surveys of gopher tortoise ( Gopherus polyphemus ) burrows, the presence of ground‐level vegetation substantially decreases detection of burrows of all sizes, but no field or analytical methods exist to control for spatially heterogeneous vegetation obstruction as a source of variation in detection. We propose the addition of a simple measurement of ground‐level vegetation that serves as a covariate for the detection function. We present a Bayesian hierarchical model in which covariates burrow width and nearby vegetation height help to account for detection bias and improve precision of estimated density. We investigate the performance of this covariate by simulation and by using real LTDS data collected before and after application of prescribed fire. We collected data in 2018 at the Jones Center at Ichauway in Newton, Georgia, USA. Across all simulations, our model including both covariates produced the most accurate density point estimates of any of the models tested. For our case study, our Bayesian model with vegetation covariates tended to produce similar estimates of density before and after burns. Our study indicates that any level of spatial variation in vegetation obstruction decreases detection of burrows and may lead to underestimation in population size (≤68%) and proportion of individuals with small burrow sizes (≤32%) when not considered during analysis. Our work is extensible to other terrestrial sampling efforts where systematic measurement of a spatially distributed obstructing feature is feasible during the LTDS survey.

Translocation, the intentional movement of animals from one location to another, is a common management practice for the gopher tortoise (Gopherus polyphemus). Although the inadvertent spread of pathogens is a concern with any translocation effort, waif tortoises—individuals that have been collected illegally, injured and rehabilitated or have unknown origins—are generally excluded from translocation efforts due to heightened concerns of introducing pathogens and subsequent disease to naïve populations. However, repurposing these long-lived animals for species recovery is desirable when feasible, and introducing waif tortoises may bolster small populations facing extirpation. The objective of this study was to assess the health of waif tortoises experimentally released at an isolated preserve in Aiken County, SC, USA. Our assessments included visual examination, screening for 14 pathogens using conventional or quantitative polymerase chain reaction (qPCR) and haematological evaluation. Of the 143 individuals assessed in 2017 and 2018, most individuals (76%; n = 109 of 143) had no overt clinical evidence of disease and, when observed, clinical findings were mild. In both years, we detected two known tortoise pathogens, Mycoplasma agassizii and Mycoplasma testudineum, at a prevalence of 10.2–13.9% and 0.0–0.8%, respectively. Additionally, we found emydid Mycoplasma, a bacterium commonly found in box turtles (Terrapene spp.), in a single tortoise that showed no clinical evidence of infection. The presence of nasal discharge was an important, but imperfect, predictor of Mycoplasma spp. infection in translocated tortoises. Hemogram data were comparable with wild populations. Our study is the first comprehensive effort to assess pathogen prevalence and hemogram data of waif gopher tortoises following translocation. Although caution is warranted and pathogen screening necessary, waif tortoises may be an important resource for establishing or augmenting isolated populations when potential health risks can be managed.

Populations of amphibians that breed in isolated, ephemeral wetlands may be particularly sensitive to breeding and recruitment rates, which can be influenced by dynamic and difficult-to-predict extrinsic factors. The gopher frog Rana capito is a declining species currently proposed for listing under the U.S. Endangered Species Act, as well as one of many pond-breeding amphibians of conservation concern in the southeastern United States. To represent gopher frog breeding dynamics, we applied an occupancy modeling framework that integrated multiple datasets collected across the species’ range to (i) estimate the influence of climate, habitat, and other factors on wetland-specific seasonal breeding probabilities, and (ii) use those estimates to characterize seasonal, annual, and regional breeding patterns over a 10-yr period. Breeding probability at a wetland was positively influenced by seasonal precipitation (Standardized Precipitation Index) and negatively influenced by fish presence. We found some evidence that the amount of suitable habitat surrounding a wetland was positively correlated with breeding probability during drought conditions. The percentage of sampled wetlands (N = 192) predicted to have breeding varied seasonally, annually, and regionally across the study. Within-year temporal patterns of breeding differed across the range: in most locations north of Florida, peaks of breeding occurred in winter and spring months; whereas breeding was more dispersed throughout the year in Florida. Peaks of breeding across the 10-yr period often occurred during or in the season following high rainfall events (e.g., hurricanes). These results have direct applications for site-level management that aims to increase successful breeding opportunities of gopher frogs and other associated pond-breeding amphibians, including monitoring protocol and intensity, removal of fish, and improving terrestrial habitat conditions surrounding wetlands (e.g., via tree/shrub removal and prescribed fire). The results also have implications for better-informed management through the closer alignment of breeding activity monitoring with predicted seasonal peaks. Furthermore, estimates of breeding frequency can be incorporated into population viability analyses to inform forthcoming assessments of extinction risk and designation of the species’ conservation status by the U.S. Fish and Wildlife Service.

Climate change effects are contributing to widespread declines of amphibians, and pond-breeding species may be particularly sensitive to future drought conditions that restrict wetland hydroperiods and decrease opportunities for successful breeding and recruitment. Pond-breeding amphibian populations can compensate for periodic droughts via episodic booms in recruitment, but studies predict that increased future drought conditions will negatively impact long-term persistence for several species. The southeastern United States is a global hotspot of amphibian biodiversity where future trends in drought conditions are uncertain. This study applied a population viability analysis (PVA) framework for an at-risk amphibian, the gopher frog (Lithobates [Rana] capito), to (i) explore population sensitivity to the frequency of droughts that restrict reproductive events, relative to changes in other demographic rates, and (ii) forecast future population viability over 30 years, given plausible scenarios varying in the frequency and duration of droughts adapted from recent historical patterns in the southeastern United States. Population persistence was highly sensitive to frequency of reproductive success. Persistence was fairly insensitive to all demographic parameters when reproductive success was ≥ 0.7 (i.e., ≤ 3 drought years per decade, on average), but sensitivity to survival of terrestrial stages (juvenile, adults) and initial abundance increased as reproductive success decreased. Persistence probabilities were relatively high (0.63–0.99) across a range of plausible future drought scenarios, with higher persistence probabilities (> 0.89) for all scenarios where drought years did not increase from recent historical conditions. Our results indicate gopher frog populations are likely resilient to periodic droughts that occur in 4 or fewer years per decade, but extirpation of some populations is possible if recent drought patterns repeat or increase during the next 30 years. Estimates of future risk to gopher frog populations can inform forthcoming status assessments and designation decisions of the U.S. Fish and Wildlife Service. More broadly, PVAs incorporating drought dynamics can identify climate thresholds that at-risk, pond-breeding amphibian populations can tolerate, which can inform management actions (e.g., maintaining a range of hydroperiods across proximate wetlands) that provide sufficient frequent breeding opportunities for long-term persistence even under drought conditions.