Browsing by Author "Hunter, Elizabeth A."

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    A big data-model integration approach for predicting epizootics and population recovery in a keystone species
    Barrile, Gabriel M.; Augustine, David J.; Porensky, Lauren M.; Duchardt, Courtney J.; Shoemaker, Kevin T.; Hartway, Cynthia R.; Derner, Justin D.; Hunter, Elizabeth A.; Davidson, Ana D. (Wiley, 2023-02)
    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 provides a general framework for spatially explicit forecasting of disease-induced population fluctuations for use in natural resource management decision-making.
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    A comparison of non-surgical methods for sexing young gopher tortoises (Gopherus polyphemus)
    Loope, Kevin J.; Rostal, David C.; Walden, M. A.; Shoemaker, Kevin T.; Hunter, Elizabeth A. (PeerJ, 2022-06-14)
    Many turtle species have temperature-dependent sex determination (TSD), raising the prospect that climate change could impact population dynamics by altering sex ratios. Understanding how climate change will affect populations of animals with TSD requires a reliable and minimally invasive method of identifying the sexes of young individuals. This determination is challenging in many turtles, which often lack conspicuous external sexual dimorphism until years after hatching. Here, we explore four alternatives for sexing three age classes of captive-reared young gopher tortoises (Gopherus polyphemus), a terrestrial turtle of conservation concern native to the southeastern United States: (1) naive testosterone levels, (2) testosterone levels following a follicle stimulating hormone (FSH) challenge, (3) linear morphological measurements, and (4) geometric morphometrics. Unlike some other turtle species, male and female neonatal gopher tortoises have overlapping naive testosterone concentration distributions, justifying more complicated methods. We found that sex of neonates (<7 days old) is best predicted by a "random forest" machine learning model with naive testosterone levels and morphological measurements (8% out-of-bag error). Sex of hatchlings (4-8 months old) was predicted with 11% error using a simple threshold on naive testosterone levels, or with 4% error using a simple threshold on post-FSH testosterone levels. Sex of juveniles (approximately 3.5 years old) was perfectly predicted using a simple threshold on naive testosterone levels. Sexing hatchlings at >4 months of age is the easiest and most reliable non-surgical method for sex identification. Given access to a rearing facility and equipment to perform hormone assays, these methods have the potential to supplant laparoscopic surgery as the method of choice for sexing young gopher tortoises.
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    Demography and site fidelity of a grassland bird, the Henslow's Sparrow, in powerline right-of-way habitat
    Hunter, Elizabeth A.; Dwire, Abigail; Schneider, Todd M. (Resilience Alliance, 2022)
    Grassland birds are among the fastest declining avian species in North America, primarily due to habitat loss. In the southeastern United States, much grassland and open savanna habitat has been converted to timber production or agriculture, neither of which typically provides habitat for breeding or wintering grassland birds. Powerline right-of-ways could provide suitable habitat for many grassland species because these areas are maintained to be treeless. We studied the population dynamics of Henslow's Sparrows (Centronyx henslowii) wintering in powerline right-of-ways in southeastern Georgia through an 11-year mark-recapture study. We used a robust design Cormack-Jolly-Seber model to estimate probability of detection and apparent survival. Abundance varied substantially among years at each site, with density varying from 1.7 to 8.5 birds/ha. Within-year detection probability was moderately high at 28% (24-33%, 95% credible interval [CI]), but apparent survival was very low at 13% (9-17%, 95% CI). This low apparent survival was likely due to low return rates (and not necessarily low survival). However, birds that did return to the study sites had extremely high site fidelity, with 82% of across-year recaptures < 200 m apart. This apparent incongruity between low apparent survival rates (likely due to emigration from the study sites) and high site fidelity for returning individuals could be explained by the dependability of the rightof-way habitat, which differs from typically patchy and temporally variable grassland and savanna wintering habitats. Dependable habitat may allow for higher site fidelity than this species would otherwise have, potentially resulting in the high densities we observed. Thousands of miles of right-of-ways in Georgia, and other southeastern states, could be managed to maximize potential habitat for declining grassland bird species.
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    Direct and indirect pathways for environmental drivers of hatching success in the loggerhead sea turtle
    Whitesell, Mattie J.; Hunter, Elizabeth A.; Rostal, David C.; Carroll, John M. (Inter-Research, 2022-11)
    Nest site selection has consequences for hatching success by mediating the temperature and moisture conditions that eggs experience during the incubation period. Understanding the potentially complex pathways by which nest placement influences these abiotic mediators, and therefore hatching success, is important for predicting which nests will be successful and which may require management action. We studied the effects of loggerhead sea turtle (Caretta caretta) nest site selection on hatching success by linking nest placement characteristics to hatching success through a structural equation model. We monitored 170 nests on Ossabaw Island, Georgia, during the summers of 2017 and 2018 and tracked nest conditions throughout the incubation period. Temperature had a complex effect on hatching success-nests had higher hatching rates if they were exposed to higher mean temperatures but also if they experienced both extremely high (>34 degrees C) and extremely low (<26.5 degrees C) temperatures, suggesting that temperature variability plays a role in determining nest outcomes beyond the mean temperature. Likewise, hatching success declined with a higher incidence of nests being inundated by tides. We found that nests placed at the highest elevations had the highest hatching success rates, likely because those nests had a much lower chance of being washed over by high tides and had higher mean temperatures. Nests were also more successful when placed in greater amounts of vegetation, again because vegetated nests were generally warmer and were associated with fewer washover events. These results shed light on the mechanisms behind selection for certain nest site characteristics and can guide the relocation of nests as a conservation action.
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    Habitat edges influence the distribution of nest predators for Seaside Sparrows, but not nest placement or success
    Newsome, Corina D.; Hunter, Elizabeth A. (Oxford University Press, 2022-08-02)
    Nest failure for coastal marsh bird species is primarily caused by predation and nest flooding. As sea level rise makes nest flooding more likely, the threat of nest predation will constrain the potential adaptive responses of marsh nesting species. Thus, understanding the predictors of nest predation is important for the conservation of salt marsh-dwelling bird species, such as the Seaside Sparrow (Ammospiza maritima). Predator activity may be influenced by landscape features (particularly habitat edges), potentially making nest predation predictable. We aimed to understand the predictability of Seaside Sparrow nest predation relative to two major landscape features: roads and tidal rivers, as both of these edges may be entryways or attractants for predators in marshes. In coastal Georgia, USA, we assessed mammalian predator activity relative to the two features of interest, and hypothesized that mammalian predator activity would be greater close to roads and tidal rivers. We also recorded Seaside Sparrow nest locations and nest predation events and hypothesized that nest predation events would increase with increasing predator activity. Consistent with our first hypothesis, mammalian predator activity increased close to roads and tidal rivers, but mammalian predator distribution did not explain the spatial variation in Seaside Sparrow nest predation thus not supporting our second hypothesis. Seaside Sparrows also placed their nests in locations with high mammalian predator activity, indicating that the ability to avoid nesting in high-risk areas may be constrained by habitat or resource limitations. Additionally, mammals may not be the primary nest predators, as we found that one bird species-Marsh Wren (Cistothorus palustris)-contributed substantially to nest predation rates. Understanding the predictability of mammalian predator distribution can allow for focused predator management efforts, such as exclusion, to habitat edges where we found the highest mammalian predator activity, which could relax the constraint of nest predation on Seaside Sparrow's ability to respond to the intensifying threat of sea level rise. Lay Summary center dot Seaside Sparrows (Ammospiza maritima) nest in salt marsh grasses. If a nest fails from flooding, they elevate their next nest. However, nests higher from the ground experience increased predation risk. center dot Understanding the spatial pattern of nest predation across Seaside Sparrow habitat is critical in the face of increased nest flooding from sea level rise. center dot We predicted that mammalian predator activity would increase along habitat edges adjacent to roads and rivers in Glynn County, Georgia, and that Seaside Sparrow nests would experience increased predation in these areas. Mammalian predator activity increased near road and water edges, but Seaside Sparrows placed their nests in locations with high predator activity, and nest predation was not correlated with mammalian predator activity. Marsh Wrens depredated Seaside Sparrow nests and may have had an important impact on nest predation patterns. center dot Our results suggest that future predator management be focused on habitat edges along roads and waterways.
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    Within-marsh and Landscape Features Structure Ribbed Mussel Distribution in Georgia, USA, Marshes
    Annis, William K.; Hunter, Elizabeth A.; Carroll, John M. (Springer, 2022-12)
    Ribbed mussels, Geukensia demissa, are marsh fauna that are used in coastal management and restoration due to the ecosystem services they provide. Ribbed mussel restoration efforts may be improved with a greater understanding of the environmental drivers of ribbed mussel distribution at multiple spatial scales to predict areas where restoration could be successful. This study sought to estimate the effects of within-marsh (4 m) and landscape (500 m) factors on ribbed mussel distribution. Ribbed mussel densities were surveyed at 11 sites along the coast of Georgia, USA, and overlaid with spatial data for within-marsh factors (elevation, distance to marsh features, slope) as well as landscape factors (percent cover by subtidal creek, forest, and development within a 500-m radius). The distribution model was then validated using three previously unsurveyed marshes and explained 55% of the variance in ribbed mussel abundance. Ribbed mussel abundances and occupancy were most sensitive to changes in within-marsh factors (elevation and distance to subtidal creeks, bodies of water inundated during the full tidal cycle) but were also sensitive to landscape features (percent landcover of forests and development). The highest ribbed mussel densities were found in mid-elevation areas (similar to 0.7 m NAVD88), far from subtidal creeks, and in marshes surrounded with forest and development. These results contrast with distributions in the northeastern USA, where ribbed mussels are distributed along subtidal creek banks. This work suggests that restoration may be most effective when focused on appropriate elevations and at locations away from the marsh-creek ecotone.