Geology topics

Graziella V. DiRenzo

Publications and source records attributed to Graziella V. DiRenzo.

9 recordsLinked to original sources

USGS2026

Small cumulative survival costs of enzootic disease could suppress long-term population size

Fungal pathogens can cause epizootics that result in widespread mortality and rapid population declines in some species. However, even in the absence of high disease-induced mortality, enzootic mycoses could have large-scale impacts on host population dynamics. Here, we examined the effects of ophidiomycosis, an enzootic fungal disease, on a Louisiana snake community over a 3-year period using a multi-state Jolly–Seber model with disease-state misclassification. We did not detect a difference between the average weekly apparent survival probability of uninfected and infected hosts for either Nerodia species or Thamnophis proximus . We also found a strong positive association between snout-to-vent length and weekly apparent survival probability across all species. We found that recruitment of infected hosts was slightly higher than recruitment of uninfected hosts for two of the three species. Population projections suggested divergent trajectories between disease-present and disease-absent scenarios, where disease-absent populations had higher abundance than disease-present populations. Our results highlight that small differences in survival can accumulate over time, as well as the challenges of quantifying population-level impacts of enzootic diseases when survival differences are not readily detected, underscoring the importance of continued long-term monitoring to assess whether ophidiomycosis affects snake population dynamics.

Louisiana↗

USGS2025

An analysis of the linked decisions in the confiscation of illegally traded turtles

Over the last few decades, freshwater turtles have become more common in the illegal wildlife trade because of growing global demand. Illegally traded turtles may be intercepted by several different agencies with separate jurisdictions. When turtles are confiscated, uncertainties may make releasing them back to the wild difficult. We used tools from decision analysis to achieve the following three objectives: (1) map elements of the decision process and their relationships in the illegal turtle trade using conceptual models, (2) outline the linked decisions for turtle confiscation and repatriation using decision trees, and (3) evaluate the decision trees for two example scenarios, one with moderate uncertainty and one with high uncertainty. We used the wood turtle ( Glyptemys insculpta ) as a case study, which is a species of conservation concern in part due to illegal wildlife trafficking. We conducted 23 semi-structured interviews of decision makers in law enforcement, biologists, land managers, and zoo staff. Interviews revealed that decisions regarding the disposition of confiscated turtles are complicated by uncertainty in disease status and origin. Decision makers that handle confiscated turtles also recognize that their decisions are often made in sequence and dependent on the outcome of antecedent decisions. In evaluating our decision trees, we found that the optimal decisions for example scenarios were similar and insensitive to uncertainty. Future applications of the decision trees by decision makers would involve a decision analyst to parameterize and interpret the choices and consequences involved in working through these decision trees. Collectively, our work shows how the use of decision trees can help structure and evaluate risky decisions for repatriating confiscated wildlife.

Conservation Science and Practice↗

USGS2025

Pan-amphibia distribution of the fungal parasite Batrachochytrium dendrobatidis varies with species and temperature

Batrachochytrium dendrobatidis (Bd) is a globally distributed fungal pathogen of amphibians that has contributed to one of the largest disease-related biodiversity losses in wildlife. Bd is regularly viewed through the lens of a global wildlife epizootic because the spread of highly virulent genetic lineages has resulted in well-documented declines and extinctions of multiple amphibian species. However, the current state of Bd occurrence, host range, host impacts, and ecological drivers remains poorly understood outside of the most negatively affected amphibian species and regions. Our objective was to describe the macroecology of Bd occurrence and infection intensity on caudates (salamanders) across the United States and to compare these patterns with better-studied anurans (frogs and toads). We collected swabs from 11,183 amphibians at 609 sites from 54 species across the United States from 2015 to 2017. We analyzed the prevalence and intensity of Bd infection jointly using a Bayesian hurdle model with covariates of site-level temperature and precipitation, as well as individual characteristics and species identification. Bd was distributed widely across sites and species sampled across the spatial extent of the conterminous United States. We found that Bd prevalence and intensity were most strongly influenced by temperature in the month preceding sampling and by differences among taxon groups. We estimated that temperature had a strong and nonlinear influence on both Bd prevalence and intensity with peak infection at intermediate temperatures and lower infection at low and high temperatures. We found Caudate hosts tended to have higher prevalence than Anuran hosts and Anuran hosts tended to have higher intensity at optimal temperatures for Bd infection. Our findings suggest that Bd has an amphibian-wide host range, temperature gradients exert a strong influence on Bd, and enzootic transmission likely encompasses a much larger spatial and species distribution than previously recognized across North America.

conterminous United States↗

USGS2020

Dermal denticle assemblages in coral reef sediments correlate with conventional shark surveys

1. It is challenging to assess long-term trends in mobile, long-lived, and relatively rare species such as sharks. Despite ongoing declines in many coastal shark populations, conventional surveys might be too fleeting and too recent to describe population trends over decades to millennia. Placing recent shark declines into historical context should improve management efforts as well as our understanding of past ecosystem dynamics. 2. A new paleoecological approach for surveying shark abundance on coral reefs is to quantify dermal denticle assemblages preserved in sediments. This approach assumes that denticle accumulation rates correlate with shark abundances. Here, we test this assumption by comparing the denticle record in surface sediments to three conventional shark survey methods at Palmyra Atoll, Line Islands, central Pacific Ocean, where shark density is high and spatially heterogeneous. 3. We generally found a significant positive correlation between denticle accumulation rates and shark abundances derived from underwater visual census, baited remote underwater video, and hook and line surveys. 4. Denticle accumulation rates reflected shark abundances, suggesting that denticle assemblages can preserve a signal of time-averaged shark abundance in low-energy coral reef environments. We offer suggestions for applying this tool to measure shark abundance over long timescales in other contexts.

Methods in Ecology and Evolution↗

USGS2020

Moving from decision to action in conservation science

Biodiversity loss is a major threat to the integrity of ecosystems and is projected to worsen, yet the path to successful conservation remains elusive. Decision support frameworks (DSFs) are increasingly applied by resource managers to navigate the complexity, uncertainty, and differing socio-ecological objectives inherent to conservation problems. Most published conservation research that uses DSFs focuses on analytical stages (e.g., identifying an optimal decision), making it difficult to assess and learn from previous examples in a conservation practice context. Here, we (1) evaluate the relationship between the application of decision science and the resulting conservation outcomes, and (2) identify and address existing barriers to the application of DSFs to conservation practice. To do this, we develop a framework for evaluating conservation initiatives using decision science that emphasizes setting attainable goals, building momentum, and obtaining partner buy-in. We apply this framework to a systematic review of amphibian conservation decision support projects, including a follow-up survey of the pertinent conservation practitioners, stakeholders, and scientists. We found that all projects identified optimal solutions to reach stated objectives, but positive conservation outcomes were limited when implementation challenges arose. Further, we identified multiple barriers (e.g., dynamic and hierarchical leadership, scale complexity, limited resource availability) that can inhibit the progression from decision identification to action implementation (i.e., ‘decision-implementation gap’), and to successful conservation outcomes. Based on these results, we provide potential actionable steps and avenues for future development of DSFs to facilitate the transition from decision to action and the realization of conservation successes.

Biological Conservation↗

USGS2019

Disease‐structured N‐mixture models: A practical guide to model disease dynamics using count data

Obtaining inferences on disease dynamics (e.g., host population size, pathogen prevalence, transmission rate, host survival probability) typically requires marking and tracking individuals over time. While multistate mark–recapture models can produce high‐quality inference, these techniques are difficult to employ at large spatial and long temporal scales or in small remnant host populations decimated by virulent pathogens, where low recapture rates may preclude the use of mark–recapture techniques. Recently developed N ‐mixture models offer a statistical framework for estimating wildlife disease dynamics from count data. N ‐mixture models are a type of state‐space model in which observation error is attributed to failing to detect some individuals when they are present (i.e., false negatives). The analysis approach uses repeated surveys of sites over a period of population closure to estimate detection probability. We review the challenges of modeling disease dynamics and describe how N ‐mixture models can be used to estimate common metrics, including pathogen prevalence, transmission, and recovery rates while accounting for imperfect host and pathogen detection. We also offer a perspective on future research directions at the intersection of quantitative and disease ecology, including the estimation of false positives in pathogen presence, spatially explicit disease‐structured N ‐mixture models, and the integration of other data types with count data to inform disease dynamics. Managers rely on accurate and precise estimates of disease dynamics to develop strategies to mitigate pathogen impacts on host populations. At a time when pathogens pose one of the greatest threats to biodiversity, statistical methods that lead to robust inferences on host populations are critically needed for rapid, rather than incremental, assessments of the impacts of emerging infectious diseases.

Ecology and Evolution↗

USGS2018

Eco‐evolutionary rescue promotes host–pathogen coexistence

Emerging infectious pathogens are responsible for some of the most severe host mass mortality events in wild populations. Yet, effective pathogen control strategies are notoriously difficult to identify, in part because quantifying and forecasting pathogen spread and disease dynamics is challenging. Following an outbreak, hosts must cope with the presence of the pathogen, leading to host–pathogen coexistence or extirpation. Despite decades of research, little is known about host–pathogen coexistence post‐outbreak when low host abundances and cryptic species make these interactions difficult to study. Using a novel disease‐structured N‐mixture model, we evaluate empirical support for three host–pathogen coexistence hypotheses (source–sink, eco‐evolutionary rescue, and spatial variation in pathogen transmission) in a Neotropical amphibian community decimated by Batrachochytrium dendrobatidis ( Bd ) in 2004. During 2010–2014, we surveyed amphibians in Parque Nacional G. D. Omar Torríjos Herrera, Coclé Province, El Copé, Panama. We found that the primary driver of host–pathogen coexistence was eco‐evolutionary rescue, as evidenced by similar amphibian survival and recruitment rates between infected and uninfected hosts. Average apparent monthly survival rates of uninfected and infected hosts were both close to 96%, and the expected number of uninfected and infected hosts recruited (via immigration/reproduction) was less than one host per disease state per 20‐m site. The secondary driver of host–pathogen coexistence was spatial variation in pathogen transmission as we found that transmission was highest in areas of low abundance but there was no support for the source–sink hypothesis. Our results indicate that changes in the host community (i.e., through genetic or species composition) can reduce the impacts of emerging infectious disease post‐outbreak. Our disease‐structured N‐mixture model represents a valuable advancement for conservation managers trying to understand underlying host–pathogen interactions and provides new opportunities to study disease dynamics in remnant host populations decimated by virulent pathogens.

Ecological Applications↗

USGS2017

Imperfect pathogen detection from non-invasive skin swabs biases disease inference

1. Conservation managers rely on accurate estimates of disease parameters, such as pathogen prevalence and infection intensity, to assess disease status of a host population. However, these disease metrics may be biased if low-level infection intensities are missed by sampling methods or laboratory diagnostic tests. These false negatives underestimate pathogen prevalence and overestimate mean infection intensity of infected individuals. 2. Our objectives were two-fold. First, we quantified false negative error rates of Batrachochytrium dendrobatidis on non-invasive skin swabs collected from an amphibian community in El Copé, Panama. We swabbed amphibians twice in sequence, and we used a recently developed hierarchical Bayesian estimator to assess disease status of the population. Second, we developed a novel hierarchical Bayesian model to simultaneously account for imperfect pathogen detection from field sampling and laboratory diagnostic testing. We evaluated the performance of the model using simulations and varying sampling design to quantify the magnitude of bias in estimates of pathogen prevalence and infection intensity. 3. We show that Bd detection probability from skin swabs was related to host infection intensity, where Bd infections < 10 zoospores have < 95% probability of being detected. If imperfect Bd detection was not considered, then Bd prevalence was underestimated by as much as 16%. In the Bd-amphibian system, this indicates a need to correct for imperfect pathogen detection caused by skin swabs in persisting host communities with low-level infections. More generally, our results have implications for study designs in other disease systems, particularly those with similar objectives, biology, and sampling decisions. 4. Uncertainty in pathogen detection is an inherent property of most sampling protocols and diagnostic tests, where the magnitude of bias depends on the study system, type of infection, and false negative error rates. Given that it may be difficult to know this information in advance, we advocate that the most cautious approach is to assume all errors are possible and to accommodate them by adjusting sampling designs. The modeling framework presented here improves the accuracy in estimating pathogen prevalence and infection intensity.

Methods in Ecology and Evolution↗

USGS2017

Antifungal bacteria on woodland salamander skin exhibit high taxonomic diversity and geographic variability

Diverse bacteria inhabit amphibian skin; some of those bacteria inhibit growth of the fungal pathogen Batrachochytrium dendrobatidis . Yet there has been no systematic survey of anti- B. dendrobatidis bacteria across localities, species, and elevations. This is important given geographic and taxonomic variations in amphibian susceptibility to B. dendrobatidis . Our collection sites were at locations within the Appalachian Mountains where previous sampling had indicated low B. dendrobatidis prevalence. We determined the numbers and identities of anti- B. dendrobatidis bacteria on 61 Plethodon salamanders (37 P. cinereus , 15 P. glutinosus , 9 P. cylindraceus ) via culturing methods and 16S rRNA gene sequencing. We sampled co-occurring species at three localities and sampled P. cinereus along an elevational gradient (700 to 1,000 meters above sea level [masl]) at one locality. We identified 50 anti- B. dendrobatidis bacterial operational taxonomic units (OTUs) and found that the degree of B. dendrobatidis inhibition was not correlated with relatedness. Five anti- B. dendrobatidis bacterial strains occurred on multiple amphibian species at multiple localities, but none were shared among all species and localities. The prevalence of anti- B. dendrobatidis bacteria was higher at Shenandoah National Park (NP), VA, with 96% (25/26) of salamanders hosting at least one anti- B. dendrobatidis bacterial species compared to 50% (7/14) at Catoctin Mountain Park (MP), MD, and 38% (8/21) at Mt. Rogers National Recreation Area (NRA), VA. At the individual level, salamanders at Shenandoah NP had more anti- B. dendrobatidis bacteria per individual (μ = 3.3) than those at Catoctin MP (μ = 0.8) and at Mt. Rogers NRA (μ = 0.4). All salamanders tested negative for B. dendrobatidis . Anti- B. dendrobatidis bacterial species are diverse in central Appalachian Plethodon salamanders, and their distribution varied geographically. The antifungal bacterial species that we identified may play a protective role for these salamanders.

Applied and Environmental Microbiology↗