Geology topics

Graziella Vittoria DiRenzo

Publications and source records attributed to Graziella Vittoria DiRenzo.

At least 19 recordsLinked to original sources

USGS2026

Leveraging local species data, a global database, and an occupancy model to explore bee–plant interactions

Global declines in bee populations are threatening the ecosystem services they provide, including pollination. Many bee–plant interactions are understudied, producing an incomplete understanding of resulting ecosystem-level vulnerabilities. The last decade has generated a wealth of opportunistic data originating from natural history collection records, published ecological datasets, and citizen/community science initiatives in online databases such as Global Biotic Interactions (GloBI). Here, we explore hypotheses related to bee–plant interactions and detection processes using the GloBI database, curated checklists of bee and flowering plant species, and an occupancy model. We hypothesized that larger, social bees would visit a larger number of plant species, while smaller, solitary bees would visit fewer. We also predicted that flowers with open, bowl-like shapes would attract a greater diversity of bee visitors compared to closed shapes. Further, we hypothesized that both floral and bee traits, such as bright colors and conspicuous patterns, would increase detectability, and that different data collection methods would vary in their ability to capture bee–plant interactions. Lastly, we hypothesized that the interaction network generated by the output of the occupancy model, which accounted for imperfect bee–plant detection, would yield more interactions, thereby increasing measures of evenness and decreasing nestedness and specialization, as compared to the network generated from recorded interaction data. We found that smaller bees exhibited higher probabilities of plant interactions than larger bees, but we did not find evidence that bee sociality influenced the probability of interacting with plants. We found that blue flowers and closed (not-bowl-shaped) flowers had higher probabilities of bee-plant interaction than other flower colors or bowl-shaped flowers, respectively. We also found that larger bee size, blue flowers, bowl shapes, and community science sources were associated with higher detection probabilities of bee–plant interactions. Lastly, the interaction network generated by the occupancy model output showed higher levels of evenness, nestedness, and connectance than the network generated by the GloBI data. Our study is among the first to utilize occupancy modeling to directly model species' interactions, leverage aggregated, open-source databases and expert checklists, and highlight the influence of detection and collection biases on our understanding of ecological interactions.

California↗

USGS2026

Chronic wasting disease (CWD) knowledge, risk perception, and management acceptance are influenced by media engagement and trust among deer hunters in Massachusetts

Prior to wildlife disease emergence, public outreach campaigns can improve disease-related knowledge and increase the likelihood that stakeholders accept potential management actions. One wildlife disease of particular interest is chronic wasting disease (CWD), which is spreading across the United States but has not been detected in Massachusetts. We conducted a survey of deer hunters ( n = 7,419) in Massachusetts to: (1) explore media channel usage and source trust, and (2) assess the relationship among CWD knowledge, risk perception, management acceptability, and state wildlife agency trust. We found that channel usage and source trust varied by socio-demographic factors. We also found that engagement with popular channels and trust in accurate sources were positively correlated with CWD knowledge. CWD risk perception mediated the relationship between knowledge and management acceptance, and trust was positively associated with management acceptance. Collectively, our results indicate a mixed-media campaign by state wildlife agencies could improve CWD management acceptance.

Massachusetts↗

USGS2025

Watershed forest cover and habitat restoration can offset some negative impacts of climate change on freshwater fishes and mussels

Many species of freshwater fishes and freshwater mussels have experienced population declines over the past century due to threats including habitat degradation, overexploitation, species invasion, and climate change. Management actions may offset climate-related changes to biodiversity, although identifying appropriate strategies is challenging. Our goal was to identify the impacts of climate change on freshwater biota (i.e., fish and mussel) distribution and management actions that may offset the climate change impacts across the northeastern United States. We used land use, geography, stream temperature, and streamflow variables to predict species distribution in a baseline scenario, climate change scenario, and several climate change plus land use management scenarios. We found climate change negatively impacted (i.e., reduced the probability of occurrence of) coldwater fishes and reduced the relative occurrence probability of fluvial specialist and coolwater fishes compared to other species. Increasing watershed forest cover best offset these negative impacts and minimized the predicted transition from coldwater fish dominance to warmwater fish dominance in coldwater habitats; however, no intervention fully offset the negative impacts of climate change on vulnerable fish groups (i.e., coldwater and fluvial specialist fishes). Climate change negatively impacted all vulnerable groups of mussels (e.g., lotic species, drying intolerant) and mussel species richness. Combining multiple management interventions (e.g., increase forest cover, dam removal, etc.) had the greatest potential to offset the negative impacts of climate change for freshwater mussels and fishes. This study provides managers a comparison of management interventions across a landscape to combat the impacts of climate change on biota in streams and rivers.

Connecticut, Maine, Massachusetts, New Hampshire, ↗

USGS2025

Similar population dynamics before and after a chytridiomycosis outbreak in a tropical riparian amphibian species

Emerging infectious diseases can cause rapid, widespread host mortality, and the lack of demographic data before and after pathogen emergence complicates understanding mechanisms of host persistence. This challenge is further compounded by environmental conditions that influence host behavior, while driving pathogen growth and virulence. These interactions create complex disease outcomes that hinder predictions of when and how hosts endure pathogen outbreaks. Here, we analyzed 10 years of capture-mark-recapture data (2000–2014) spanning wet and dry seasons for male Espadarana prosoblepon in El Copé, Panama, encompassing a period before (2000–2004) and after (2010–2014) a Batrachochytrium dendrobatidis ( Bd ) outbreak using Jolly-Seber models. We found that post- Bd male E. prosoblepon population size (range in mean population size among primary periods = 136–225 individuals) was similar to pre- Bd population size (range in mean population size among primary periods = 201–242 individuals). Pre- Bd , average monthly survival probability in the wet season was 0.93 (95% credible interval [CI] = 0.90–0.96). Post- Bd , uninfected individuals had survival probability higher in the wet season (mean = 0.97; [95% CI = 0.95–0.98]) than the dry season (mean = 0.90 [95% CI = 0.84–0.94]), while survival probability for infected individuals decreased as a function of Bd infection intensity. Pre- Bd , mean monthly per-capita entry probability was 0.07 (95% CI = 0.05–0.10), and post- Bd , mean monthly per-capita entry probability was 0.06 (95% CI = 0.00–0.10). Lastly, infection probability during the wet season was lower (mean = 0.04 [95% CI = 0.03–0.05]) than the dry season (mean = 0.10 [95% CI = 0.05–0.15]), and recovery probability during the wet season was lower (mean = 0.19 [95% CI = 0.11–0.28]) than the dry season (mean = 0.54 [95% CI = 0.20–0.88]). Our findings suggest that survival probabilities of uninfected individuals, as well as per-capita entry probabilities, are similar pre- and post- Bd , leading to a stable and similar sized pre- Bd population. These results contribute to understanding disease dynamics and tropical amphibian ecology.

Ecosphere↗

USGS2025

Catchment prioritization for freshwater mussel conservation in the Northeastern United States based on distribution modelling

Freshwater mussels are critical to the health of freshwater systems, but their populations are declining dramatically throughout the world. The limited resources available for freshwater mussel conservation necessitates the geographic prioritization of conservation-related actions. However, lack of knowledge about freshwater mussel spatial distributions hinders decision making in this context. In this study, we assessed the distribution of twelve native freshwater mussel species across six Northeastern states (Connecticut, Rhode Island, Massachusetts, Vermont, New Hampshire, and Maine) in the United States using data collected from lentic and lotic environments by eight state agencies. We first modeled individual distributions using a maximum entropy (MaxEnt) model and then compiled distribution models to assess the distribution of freshwater mussel species richness. We also determined geographic prioritization for three conservation-related actions: species surveys, land protection, and population restoration of species of high conservation concern. We found that the percent of catchments predicted to have species occurrence (based on a probability threshold) varied across species, with Elliptio complanata (Eastern elliptio) predicted to occur in the greatest percent of available catchments (33.92%) and Alasmidonta heterodon (Dwarf wedgemussel) expected in the smallest percent (5.30%). The predicted overall species richness within our modeled catchments ranged from zero to all twelve species, with an average of two species per catchment. Although conservation priorities vary depending on the conservation action of interest, we found some areas of consistent importance including much of Maine and the southern reaches of the Connecticut River. An improved understanding of freshwater mussel distribution in a landscape framework will enable managers to implement more precise and efficient conservation interventions for these essential aquatic species.

Connecticut, Maine, Massachusetts, New Hampshire, ↗

USGS2025

Climate and land use drivers of freshwater fish biodiversity in the northeastern United States

Freshwater habitats can sustain high biodiversity, but habitat degradation, species invasion, and overexploitation have imperiled freshwater species. The multiple threats to freshwater habitats and changing stream characteristics due to climate change make it challenging to identify the drivers of fish vulnerability, especially given that the importance of drivers may vary by the biodiversity endpoint. The goals of this study were to 1) describe freshwater (lotic) fish biodiversity across northeastern states in the United States, and 2) identify geographic, climate, and land use drivers of fish biodiversity, toward improving freshwater fish conservation. We predicted habitat suitability for 53 fish species using survey data and corresponding geographic, climate, and land use data. After model fitting, we grouped species using a traditional approach based on traits and a new approach using modeled streamflow and stream temperature to create clusters. We found that climate and land use vulnerable groups did not always have similar geographic patterns or relationships to the climate or land use variables, suggesting that biota vulnerable to changing conditions may be overlooked by reliance on predefined guilds to set conservation goals. Biodiversity groups that were vulnerable to climate variables were also related to land use variables that can be used to identify restoration opportunities. This approach may be useful for managers interested in holistic freshwater management under changing stream conditions.

Connecticut, Maine, Massachusetts, New Hampshire, ↗

USGS2025

Experimental drought suppresses amphibian pathogen yet intensifies transmission and disrupts protective skin microbiome

Shifting precipitation regimes driven by global climate change can alter vertebrate behavior and host-symbiont relationships, potentially compromising host resistance to pathogen invasion. In Brazil's Atlantic Forest, a biodiversity hotspot, prior research identified drought as a key factor disrupting the skin microbiome, contributing to a die-off of pumpkin toadlets due to the invasive waterborne fungal pathogen Batrachochytrium dendrobatidis (Bd). However, observational studies cannot disentangle the direct effect of moisture on Bd growth from increased amphibian activity during wet breeding seasons. Using field enclosures, we experimentally tested the influence of drought conditions on host microhabitat use, Bd disease dynamics, and the composition and predicted Bd-inhibitory function of cutaneous bacterial communities. Each enclosure housed ecologically realistic densities of Brachycephalus pitanga , a micro-endemic pumpkin toadlet. We simulated a short-term drought in half of the enclosures using translucent tarp coverings. To track individual toadlets, we identified their unique markings and collected skin swabs biweekly over 3 months. We then implemented molecular techniques to quantify Bd loads and characterize skin bacterial diversity and composition over time. Our findings indicate that while drought may reduce overall Bd loads on hosts, this effect is partially offset by an increase in the use of water-filled areas of the enclosures and by a disruption of the protective host skin microbiome. This study provides valuable insights into the cascading impacts of climate change on animal behavior, host-symbiont interactions, and disease dynamics.

Atlantic Forest↗

USGS2025

Fomites could determine severity of SARS-CoV-2 outbreaks in low-density white-tailed deer (Odocoileus virginianus) populations

The establishment of a reservoir species for zoonotic diseases is concerning for both animal and human health. Severe acute respiratory syndrome coronavirus (SARS-CoV)-2, the coronavirus responsible for the COVID-19 pandemic, has been detected in white-tailed deer ( Odocoileus virginianus ) in the United States. Since its initial detection, various studies have documented circulation and evolution of SARS-CoV-2 in deer, with human cases suspected of spill-back from infectious deer. A priority for mitigating SARS-CoV-2 outbreaks in deer populations is determining the contribution of direct (via aerosols and physical contact) and indirect (via contaminated objects and media) transmission pathways. We expanded existing epidemiological models founded on direct transmission pathways to include three indirect transmission pathways of infection for simulated deer populations, including contaminated water, food waste, and feed piles. Despite lower infection probabilities and transmission hazards (measured by force-of-infection (FOI)) posed solely by these indirect pathways compared to direct transmission pathways, the addition of indirect transmission pathways increased FOI, which had ramifications for the severity of SARS-CoV-2 outbreaks in simulated deer populations, particularly in populations with low degrees of spread between deer (measured by basic reproductive number; R 0 ). We used contact rate models to estimate SARS-CoV-2 spread across deer range in the United States and identified widespread potential for indirect transmission to increase the severity of outbreaks in low-density deer populations. These results indicate that indirect transmission pathways need to be considered in the management of white-tailed deer as a reservoir species for SARS-CoV-2.

Transboundary and Emerging Diseases↗

USGS2025

Idiosyncratic spatial scaling of biodiversity–disease relationships

High host biodiversity is hypothesized to dilute the risk of vector-borne diseases if many host species are ‘dead ends' that cannot effectively transmit the disease and low-diversity areas tend to be dominated by competent host species. However, many studies on biodiversity–disease relationships characterize host biodiversity at single, local spatial scales, which complicates efforts to forecast disease risk if associations between host biodiversity and disease change with spatial scale. Here, our objective is to evaluate the spatial scaling of relationships between host biodiversity and Borrelia (the bacterial taxon which causes Lyme disease) infection prevalence in small mammals. We compared the associations between infection prevalence and small mammal host diversity for local communities (individual plots) and metacommunities (multiple plots aggregated within a landscape) sampled by the National Ecological Observatory Network (NEON), an emerging continental-scale environmental monitoring program with a hierarchical sampling design. We applied a multispecies, spatially-stratified capture–recapture model to a trapping dataset to estimate five small mammal biodiversity metrics, which we used to predict infection status for a subset of trapped individuals. We found that relationships between Borrelia infection prevalence and biodiversity did indeed vary when biodiversity was quantified at different spatial scales but that these scaling behaviors were idiosyncratic among the five biodiversity metrics. For example, species richness of local communities showed a negative (dilution) effect on infection prevalence, while species richness of the small mammal metacommunity showed a positive (amplification) effect on infection prevalence. Our modeling approach can inform future analyses as data from similar monitoring programs accumulate and become increasingly available through time. Our results indicate that a focus on single spatial scales when assessing the influence of biodiversity on disease risk provides an incomplete picture of the complexity of disease dynamics in ecosystems.

Ecography↗

USGS2025

Reproductive habitat mismatch influences chytrid infection dynamics in a tropical amphibian community

Batrachochytrium dendrobatidis ( Bd ) has been decimating amphibian populations globally; previous work indicates that infection risk increases with moisture and thermal mismatch from a host’s optimum. We hypothesized that, in addition to these abiotic influences, mismatch of hosts from their reproductive habitat heightens infection risk via exposure and/or susceptibility mechanisms. We evaluated this “reproductive habitat mismatch hypothesis” by quantifying the interplay of host breeding mode, habitat, and rainfall on Bd infection dynamics using two years of frog survey data—including swab data for 3427 captures representing 44 species—from Brazil’s Atlantic Forest. We modeled infection prevalence, infection intensity, and the number of frogs captured as a function of rainfall, reproductive mode (aquatic or terrestrial), and habitat (aquatic or terrestrial) using hierarchical models. High rainfall was associated with increases in infection prevalence and infection intensity; however, these increases were particularly apparent for species in habitats that were mismatched from the species’ reproductive habitat. Tropical regions experiencing increases in precipitation will likely see higher Bd risk, and our results indicate that such increases in rainfall will be particularly problematic for species that are forced to move from their reproductive habitats by factors such as habitat loss or thermal stress.

Parque Estadual da Serra do Mar–Núcleo Santa Virgí↗

USGS2024

Reducing uncertainty with iterative model updating parses effects of competition and environment on salamander occupancy

Making timely management decisions is often hindered by uncertainty. Monitoring reduces two key types of uncertainty. First, it serves to reduce structural uncertainty of how the system works and provides support for expectations of how a system works. Second, it serves to reduce parametric uncertainty of the drivers of system dynamics. By combining monitoring data and quantitative models, we can reduce structural and parametric uncertainty. To demonstrate this, we focus on the Shenandoah salamander ( Plethodon shenandoah ), a United States Federally Endangered Species. Early work suggested that P. shenandoah extinction risk results from competition with a conspecific ( Plethodon cinereus ). However, more recent work has found equivocal support for this claim, instead suggesting that abiotic factors, such as moisture and temperature, drive P. shenandoah persistence. Using long-term monitoring data, we find that while competition may play a part in P. shenandoah extinction risk, measures of surface moisture are better predictors of occupancy dynamics. Further, we find decreased detection rates of P. shenandoah when P. cinereus is present, suggesting a conflation of detection probability with actual competition, which cautions against making inference from unadjusted observations of occurrence. Using multiple lines of inquiry allows for more robust understanding of system drivers in the face of high uncertainty, increasing opportunities to manage extinction risk.

Virginia↗

USGS2024

One Health collaboration is more effective than single-sector actions at mitigating SARS-CoV-2 in deer

One Health aims to achieve optimal health outcomes for people, animals, plants, and shared environments. We describe a multisector effort to understand and mitigate SARS-CoV-2 transmission risk to humans via the spread among and between captive and wild white-tailed deer. We first framed a One Health problem with three governance sectors that manage captive deer, wild deer populations, and public health. The problem framing included identifying fundamental objectives, causal chains for transmission, and management actions. We then developed a dynamic model that linked deer herds and simulated SARS-CoV-2. Next, we evaluated management alternatives for their ability to reduce SARS-CoV-2 spread in white-tailed deer. We found that single-sector alternatives reduced transmission, but that the best-performing alternative required collaborative actions among wildlife management, agricultural management, and public health agencies. Here, we show quantitative support that One Health actions outperform single-sector responses, but may depend on coordination to track changes in this evolving system.

Nature Communications↗

USGS2024

Quantitative support for the benefits of proactive management for wildlife disease control

Finding effective pathogen mitigation strategies is one of the biggest challenges humans face today. In the context of wildlife, emerging infectious diseases have repeatedly caused widespread host morbidity and population declines of numerous taxa. In areas yet unaffected by a pathogen, a proactive management approach has the potential to minimize or prevent host mortality. However, typically critical information on disease dynamics in a novel host system is lacking, empirical evidence on efficacy of management interventions is limited, and there is a lack of validated predictive models. As such, quantitative support for identifying effective management interventions is largely absent, and the opportunity for proactive management is often missed. We considered the potential invasion of the chytrid fungus, Batrachochytrium salamandrivorans (Bsal), whose expected emergence in North America poses a severe threat to hundreds of salamander species in this global salamander biodiversity hotspot. We developed and parameterized a dynamic multistate occupancy model to forecast host and pathogen occurrence, following expected emergence of the pathogen, and evaluated the response of salamander populations to different management scenarios. Our model forecasted that taking no action is expected to be catastrophic to salamander populations. Proactive action was predicted to maximize host occupancy outcomes relative to wait-and-see reactive management, thus providing quantitative support for proactive management opportunities. The eradication of Bsal was unlikely under all the evaluated management options. Contrary to our expectations, even early pathogen detection had little effect on Bsal or host occupancy outcomes. Our results provide quantitative support that proactive management is the optimal strategy for promoting persistence of disease-threatened salamander populations. Our approach fills a critical gap by defining a framework for evaluating management options prior to pathogen invasion and can thus serve as a template for addressing novel disease threats that jeopardize wildlife and human health.

Conservation Biology↗

USGS2024

Epidemiological modeling of SARS-CoV-2 in white-tailed deer (Odocoileus virginianus) reveals conditions for introduction and widespread transmission

Emerging infectious diseases with zoonotic potential often have complex socioecological dynamics and limited ecological data, requiring integration of epidemiological modeling with surveillance. Although our understanding of SARS-CoV-2 has advanced considerably since its detection in late 2019, the factors influencing its introduction and transmission in wildlife hosts, particularly white-tailed deer ( Odocoileus virginianus ), remain poorly understood. We use a Susceptible-Infected-Recovered-Susceptible epidemiological model to investigate the spillover risk and transmission dynamics of SARS-CoV-2 in wild and captive white-tailed deer populations across various simulated scenarios. We found that captive scenarios pose a higher risk of SARS-CoV-2 introduction from humans into deer herds and subsequent transmission among deer, compared to wild herds. However, even in wild herds, the transmission risk is often substantial enough to sustain infections. Furthermore, we demonstrate that the strength of introduction from humans influences outbreak characteristics only to a certain extent. Transmission among deer was frequently sufficient for widespread outbreaks in deer populations, regardless of the initial level of introduction. We also explore the potential for fence line interactions between captive and wild deer to elevate outbreak metrics in wild herds that have the lowest risk of introduction and sustained transmission. Our results indicate that SARS-CoV-2 could be introduced and maintained in deer herds across a range of circumstances based on testing a range of introduction and transmission risks in various captive and wild scenarios. Our approach and findings will aid One Health strategies that mitigate persistent SARS-CoV-2 outbreaks in white-tailed deer populations and potential spillback to humans.

PLOS Computational Biology↗

USGS2024

Reframing wildlife disease management problems with decision analysis

Contemporary wildlife disease management is complex because managers need to respond to a wide range of stakeholders, multiple uncertainties, and difficult trade-offs that characterize the interconnected challenges of today. Despite general acknowledgment of these complexities, managing wildlife disease tends to be framed as a scientific problem, in which the major challenge is lack of knowledge. The complex and multifactorial process of decision-making is collapsed into a scientific endeavor to reduce uncertainty. As a result, contemporary decision-making may be oversimplified, rely on simple heuristics, and fail to account for the broader legal, social, and economic context in which the decisions are made. Concurrently, scientific research on wildlife disease may be distant from this decision context, resulting in information that may not be directly relevant to the pertinent management questions. We propose reframing wildlife disease management challenges as decision problems and addressing them with decision analytical tools to divide the complex problems into more cognitively manageable elements. In particular, structured decision-making has the potential to improve the quality, rigor, and transparency of decisions about wildlife disease in a variety of systems. Examples of management of severe acute respiratory syndrome coronavirus 2, white-nose syndrome, avian influenza, and chytridiomycosis illustrate the most common impediments to decision-making, including competing objectives, risks, prediction uncertainty, and limited resources.

Conservation Biology↗

USGS2024

Human activity drives establishment, but not invasion, of non-native plants on islands

Island ecosystems are particularly susceptible to the impacts of invasive species. Many rare and endangered species that are endemic to islands are negatively affected by invasions. Past studies have shown that the establishment of non-native species on islands is related to native plant richness, habitat heterogeneity, island age, human activity, and climate. However, it is unclear whether the factors promoting establishment (i.e. the formation of self-sustaining populations) also promote subsequent invasion (i.e. spread and negative impacts). Using data from 4308 non-native plant species across 46 islands and archipelagos globally, we examined which biogeographic characteristics influence established and invasive plant richness using generalized linear models nested within piecewise structural equation models. Our results indicate that anthropogenic land use (i.e. human modification) is strongly associated with establishment but not invasion, that climate (maximum monthly temperature) is strongly associated with invasion but not establishment, and that habitat heterogeneity (represented by maximum elevation and island area) is strongly associated with both establishment and invasion. Island isolation explains native plant richness well, but is not associated with established and invasive plant richness, likely due to anthropogenic introductions. We conclude that anthropogenic land use on islands is likely to be a proxy for the number of introductions (i.e. propagule pressure), which is more important for establishment than invasion. Conversely, islands with more diverse habitats and favorable (warm) climate conditions are likely to contain more available niche space (i.e. ‘vacant niches’) which create opportunities for both establishment and invasion. By evaluating multiple stages of the invasion process, we differentiate between the biogeographic characteristics that influence plant establishment (which does not necessarily lead to ecological impacts) versus those that influence subsequent plant invasion (which does lead to negative impacts).

Ecography↗

USGS2024

Long-term monitoring reveals management effects on Prairie Warbler colonization, local extinction, and detection in a Massachusetts pine barren

Habitat management can directly impact Setophaga discolor (Prairie Warbler) abundance and distribution. Despite regional declines, Prairie Warbler populations at Camp Edwards (Bourne, MA) have increased. To investigate habitat-management effects on Prairie Warbler populations at Camp Edwards, we used a dynamic-occupancy model to analyze a long-term monitoring dataset collected across 84 point-count sites from 2013 to 2022. The model results indicated that Prairie Warbler colonization and extinction probabilities were impacted by management (measured in years since disturbance). Colonization probability was highest initially after disturbance, then subsequently decreased for ∼50 years, and extinction probability also decreased for ∼25 years. Both probabilities remained low before increasing at ∼75 years since disturbance. The increase in colonization probability >75 years since disturbance may have been an artifact of our study design and incomplete disturbance records. We also found that latitude and longitude significantly affected colonization probability, likely a result of how habitat types are distributed across the base. These results inform how Prairie Warblers respond to long-term management, suggesting that habitat management could improve colonization rates and sustain Prairie Warbler populations.

Massachusetts↗

USGS2024

The effect of myiasis on Eastern Box Turtle (Terrapene carolina carolina) body condition, movement, and habitat use at Camp Edwards in Massachusetts

In 2020, natural resource managers at Camp Edwards, Barnstable County, MA, observed Terrapene carolina carolina (Eastern Box Turtle) individuals infected by myiasis, where parasitic flesh flies larviposit into the living tissue of a host. The hypothesized parasite was Dexosarcophaga cistudinis, but its impacts on the host's body condition, movement, and habitat use were unknown. Our objectives were to identify the parasite at Camp Edwards and to compare the body condition, movement, and habitat characteristics at capture locations of Eastern Box Turtles for infected and noninfected individuals. We radio-tracked turtles weekly and encountered 48 individuals from May to August 2022 at Camp Edwards, MA. Upon capture, we recorded turtle infection status, mass, carapace length, shell surface temperature, GPS location, and habitat characteristics of the capture location. We confirmed D. cistudinis as the parasite and found that myiasis-infected turtles had a significantly higher shell temperature (27.92 ± 5.28 °C) than noninfected turtles (26.77 ± 5.64 °C). However, we did not find an effect of myiasis on body condition, habitat use, or average daily distance moved. Collectively, our results suggest that infected turtles may exhibit behavioral fever, a mechanism by which ectotherms move to warmer microclimates to raise their body temperature in response to infections. Eastern Box Turtles at Camp Edwards may be able to use behavioral fever in response to myiasis infection because of the habitat mosaic made available through detailed habitat-management regimes.

Massachusetts↗