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Graziella Vittoria DiRenzo

Publications and source records attributed to Graziella Vittoria DiRenzo.

27 records · Page 2Linked to original sources

Structured decision-making workshop: Chronic wasting disease management in free-ranging cervids in Massachusetts

This document describes the results of a 2.5-day rapid decision prototype workshop that evaluated management activities for chronic wasting disease (CWD) in Massachusetts (MA) that were either proactive (i.e., actions taken prior to CWD arrival/detection) or reactive (i.e., actions taken after CWD arrival/detection). The workshop was led by members of the Wildlife Section of the MA Division of Fisheries and Wildlife (hereafter referred to as MassWildlife) and included a group of agency communications specialists and district managers. U. S. Geological Survey staff and a volunteer acted as decision facilitators and led the analysis of the decision. Chronic wasting disease is an always fatal neurological disease that has spread across much of North America and threatens the health of deer populations in locations where it occurs (reviewed by Escobar et al. 2020). CWD can spread into new areas via two general mechanisms: (1) natural spread (e.g., dispersal of CWD-infected male white-tailed deer [Odocoileus virginianus]), and (2) anthropogenic spread (e.g., CWD spread facilitated by human intervention; Leiss et al. 2017, Escobar et al. 2020). Once CWD arrives in a state, natural resources agencies spend eight times more on CWD than agencies with no known cases; to cover these new CWD-related management activities, the natural resources agencies are typically forced to reallocate money from existing conservation priorities (Chiavacci, 2022). As of May 2024, there were 34 U.S. states and five Canadian provinces that had detected CWD positive free-ranging and/or captive animals in the family Cervidae (collectively referred to as ‘cervid’ hereafter), and the number of new states/provinces that are detecting CWD for the first time continues to grow (U. S. Geological Survey, May 2024). As of February 2024, the closest CWD positive state to MA with CWD detected in free-ranging white-tailed deer is Pennsylvania. To date, there have been no detections of CWD in MA, but testing has been limited in MA since 2012. The growing number of CWD positive states suggests that there may be increasing risk of CWD entering and establishing in MA as the number of CWD cases increases across North America. According to a 2023 survey of hunters in MA conducted by MassWildlife, 68% of hunters were concerned about CWD entering MA, and 88% of respondents said that it was at least moderately important to keep CWD out of MA; these survey results indicate that most hunters may support CWD risk reduction actions (Martin Feehan, Massachusetts Division of Fisheries and Wildlife, oral communication, 12 Feb 2024). In addition, 23.1% of responding deer hunters in MA have hunted for cervids in CWD-positive states/provinces in the last five years (not including states/provinces that have been able to successfully eradicate CWD following a positive detection). Participants of the survey were also asked, “how many deer have you harvested that tested positive for CWD?”. A total of three respondents said that they had one deer test positive for CWD, which, when extended to the whole population of MA deer hunters, results in an estimated 32 CWD positive deer harvested in CWD-positive states and imported into MA in the last five years. When asked about how they transport harvested deer from out of state into MA, the three participants indicated either “already processed & packaged” or “not applicable.” Note, that in MA, it is a violation of regulation to import whole carcasses or high-risk parts (e.g., head, brain, spinal tissues, bones) of any member of the Cervidae family (wild or captive) from a state/province that has detected CWD; it is legal to bring in deboned meat, cleaned skull caps, hides without the head, or a fixed taxidermy mount (Massachusetts Division of Fisheries and Wildlife, 2024a). To date, testing for CWD has been limited in MA since 2012. However, the data collected from the 2023 MA hunter survey suggests that there is a real risk of CWD being imported by a MA resident who has hunted in a CWD positive state. Therefore, given the higher costs of CWD management post arrival, the potential natural spread of CWD from nearby states, and the risk of CWD introduction via humanmediated cervid movement, MassWildlife is motivated to take actions that minimize the risk of CWD introduction and spread in MA with the ultimate goal of managing thriving wildlife populations and maximizing hunter and general public satisfaction, which are both parts of the MassWildlife mission. A 2.5-day rapid prototyping structured decision making workshop was held with MassWildlife staff to develop a decision framework for CWD management in MA. During the workshop, we defined the context and extent of CWD management activities in MA. Next, we identified four fundamental objectives that help achieve the mission of MassWildlife and that address stakeholder concerns. The fundamental objectives included: (1) maximizing hunter satisfaction and participation, (2) maximizing public satisfaction (non-consumptive), (3) maximizing health and sustainability of cervids, and (4) maximizing the efficiency of CWD management. Then, we generated a list of five alternatives (i.e., strategies) that varied the intensity of proactive and reactive actions. The five strategies were: (1) minimal proactive and minimal reactive actions, (2) intermediate proactive and intermediate reactive actions, (3) intensive proactive and intermediate reactive actions, (4) minimal proactive and intensive reactive actions, and (5) intensive proactive and intensive reactive actions. Lastly, we estimated the performance of each strategy on the fundamental objectives and assessed the overall performance of strategies relative to one another. We did so by first estimating the consequences of each alternative strategy on fundamental objectives using expert elicitation, and then, we elicited objective weights from MassWildlife staff to incorporate the relative importance of different fundamental objectives. Given that it is unknown when CWD will arrive in MA, we evaluated the performance of alternative strategies against fundamental objectives given three distinct scenarios for time to arrival of CWD: introduction in 2.5, 7.5, or 10+ years. The preliminary results of the rapid prototype indicate that the performance of the CWD management strategies that we evaluated depends on when CWD first arrives in MA. If CWD were to arrive in 2.5 or 7.5 years from now (February, 2024), then the ‘minimal proactive and minimal reactive’ strategy performs the best on both the deer population and cost fundamental objectives (fundamental objectives 3 & 4), but the ‘intensive proactive and intensive reactive’ strategy performs best on both of the human dimensions fundamental objectives (fundamental objectives 1 & 2) as well as the minimize CWD prevalence objective (also related to fundamental objective 3). We also found that public trust is likely to remain high across all five alternative strategies if CWD arrives after year 10, but public trust decreases if CWD arrives in year 2.5 or 7.5. After incorporating objective weights, we found that in scenarios where CWD arrives in the near-term (in years 2.5 or 7.5), an intermediate strategy (e.g., ‘intermediate proactive and intermediate reactive’ or ‘intensive proactive and intermediate reactive’) performed best, and the ‘minimal proactive and intensive reactive’ strategy performed worst. Conversely, if CWD were to arrive after 10 years, then the ‘minimal proactive and minimal reactive’ and ‘minimal proactive and intensive reactive’ strategies performed best. Collectively, these results suggest that the decision on which alternative strategy to employ is sensitive to when CWD arrives in MA. Following the discussion of the preliminary results, we identified the following four next steps. First, we discussed how a more detailed communications plan is needed and would likely alter the performance estimates of the alternative strategies on fundamental objectives 1 & 2, which were hunter and public satisfaction, respectively. The development of the communication plan would likely be easier once the alternative actions have been identified along with the audience and message. Second, a surveillance plan could be a useful tool to inform CWD management. Surveillance for CWD was performed in MA annually from 2002 to 2012 (n = 4,356 wild white-tailed deer and moose [Alces alces] samples). Limited surveillance was conducted from 2013 to 2022; and in 2023, 242 wild samples were collected. It is not clear whether MA needs a robust or minimal surveillance plan (e.g., is a minimal surveillance plan enough to detect the pathogen at the threshold that would trigger action?), or what type of invasion event the surveillance plan should target (e.g., natural vs anthropogenic spread events). The use of decision trees and a formal risk assessment may help answer these questions. Third, some of the elicited estimates from experts during this rapid prototype could be replaced with empirical data. Lastly, given that the decision was sensitive to when CWD arrived in MA and a surveillance plan would rely on the mode of introduction, forecasting and predicting the CWD invasion front and/or the likelihood of different incursion events across MA would provide valuable insights.

Massachusetts

Abiotic and biotic factors reduce the viability of a high-elevation salamander in its native range

Amphibian populations are undergoing worldwide declines, and high-elevation, range-restricted amphibian species may be particularly vulnerable to environmental stressors. In particular, future climate change may have disproportional impacts to these ecosystems. Evaluating the combined effects of abiotic changes and biotic interactions simultaneously is important for forecasting the range of future outcomes. This information is necessary to aid conservation decision-making. We use field data to estimate population demographic parameters for an exemplary high-elevation amphibian species, the federally endangered Shenandoah salamander Plethodon shenandoah . These parameters were entered into a Markov projection model which we used to forecast the future population status of the Shenandoah salamander. We found that if the population maintains its current site colonization and persistence rates, it is at the risk of extinction that could be exacerbated by both climate and interspecific competition. Synthesis and applications. Managers have a fundamental objective directed by official policy of maintaining the species ‘for the foreseeable future’. Our evaluation of multiple hypotheses about population drivers reveals that extinction is projected for this species. Our analysis suggests that considering active management need not depend on resolving the uncertainty.

Virginia

Inferring pathogen presence when sample misclassification and partial observation occur

Surveillance programmes are essential for detecting emerging pathogens and often rely on molecular methods to make inference about the presence of a target disease agent. However, molecular methods rarely detect target DNA perfectly. For example, molecular pathogen detection methods can result in misclassification (i.e. false positives and false negatives) or partial detection errors (i.e. detections with ‘ambiguous’, ‘uncertain’ or ‘equivocal’ results). Then, when data are to be analysed, these partial observations are either discarded or censored; this, however, disregards information that could be used to make inference about the true state of the system. There is a critical need for more direction and guidance related to how many samples are enough to declare a unit of interest ‘pathogen free’. Here, we develop a Bayesian hierarchal framework that accommodates false negative, false positive and uncertain detections to improve inference related to the occupancy of a pathogen. We apply our modelling framework to a case study of the fungal pathogen Pseudogymnoascus destructans (Pd) identified in Texas bats at the invasion front of white-nose syndrome. To improve future surveillance programmes, we provide guidance on sample sizes required to be 95% certain a target organism is absent from a site. We found that the presence of uncertain detections increased the variability of resulting posterior probability distributions of pathogen occurrence, and that our estimates of required sample size were very sensitive to prior information about pathogen occupancy, pathogen prevalence and diagnostic test specificity. In the Pd case study, we found that the posterior probability of occupancy was very low in 2018, but occupancy probability approached 1 in 2020, reflecting increasing prior probabilities of occupancy and prevalence elicited from the site manager. Our modelling framework provides the user a posterior probability distribution of pathogen occurrence, which allows for subjective interpretation by the decision-maker. To help readers apply and use the methods we developed, we provide an interactive RShiny app that generates target species occupancy estimation and sample size estimates to make these methods more accessible to the scientific community ( https://rmummah.shinyapps.io/ambigDetect_sampleSize ). This modelling framework and sample size guide may be useful for improving inferences from molecular surveillance data about emerging pathogens, non-native invasive species and endangered species where misclassifications and ambiguous detections occur.

Methods in Ecology and Evolution

A practical guide to understanding and validating complex models using data simulations

Biologists routinely fit novel and complex statistical models to push the limits of our understanding. Examples include, but are not limited to, flexible Bayesian approaches (e.g. BUGS, stan), frequentist and likelihood-based approaches (e.g. packages lme4 ) and machine learning methods. These software and programs afford the user greater control and flexibility in tailoring complex hierarchical models. However, this level of control and flexibility places a higher degree of responsibility on the user to evaluate the robustness of their statistical inference. To determine how often biologists are running model diagnostics on hierarchical models, we reviewed 50 recently published papers in 2021 in the journal Nature Ecology & Evolution , and we found that the majority of published papers did not report any validation of their hierarchical models, making it difficult for the reader to assess the robustness of their inference. This lack of reporting likely stems from a lack of standardized guidance for best practices and standard methods. Here, we provide a guide to understanding and validating complex models using data simulations. To determine how often biologists use data simulation techniques, we also reviewed 50 recently published papers in 2021 in the journal Methods Ecology & Evolution . We found that 78% of the papers that proposed a new estimation technique, package or model used simulations or generated data in some capacity (18 of 23 papers); but very few of those papers (5 of 23 papers) included either a demonstration that the code could recover realistic estimates for a dataset with known parameters or a demonstration of the statistical properties of the approach. To distil the variety of simulations techniques and their uses, we provide a taxonomy of simulation studies based on the intended inference. We also encourage authors to include a basic validation study whenever novel statistical models are used, which in general, is easy to implement. Simulating data helps a researcher gain a deeper understanding of the models and their assumptions and establish the reliability of their estimation approaches. Wider adoption of data simulations by biologists can improve statistical inference, reliability and open science practices.

Methods in Ecology and Evolution

Ignoring species availability biases occupancy estimates in single-scale occupancy models

Most applications of single-scale occupancy models do not differentiate between availability and detectability, even though species availability is rarely equal to one. Species availability can be estimated using multi-scale occupancy models; however, for the practical application of multi-scale occupancy models, it can be unclear what a robust sampling design looks like and what the statistical properties of the multi-scale and single-scale occupancy models are when availability is less than one. Using simulations, we explore the following common questions asked by ecologists during the design phase of a field study: (Q1) what is a robust sampling design for the multi-scale occupancy model when there are a priori expectations of parameter estimates? (Q2) what is a robust sampling design when we have no expectations of parameter estimates? and (Q3) can a single-scale occupancy model with a random effects term adequately absorb the extra heterogeneity produced when availability is less than one and provide reliable estimates of occupancy probability? Our results show that there is a tradeoff between the number of sites and surveys needed to achieve a specified level of acceptable error for occupancy estimates using the multi-scale occupancy model. We also document that when species availability is low (<0.40 on the probability scale), then single-scale occupancy models underestimate occupancy by as much as 0.40 on the probability scale, produce overly precise estimates, and provide poor parameter coverage. This pattern was observed when a random effects term was and was not included in the single-scale occupancy model, suggesting that adding a random-effects term does not adequately absorb the extra heterogeneity produced by the availability process. In contrast, when species availability was high (>0.60), single-scale occupancy models performed similarly to the multi-scale occupancy model. Users can further explore our results and sampling designs across a number of different scenarios using the RShiny app https://gdirenzo.shinyapps.io/multi-scale-occ/ . Our results suggest that unaccounted for availability can lead to underestimating species distributions when using single-scale occupancy models, which can have large implications on inference and prediction, especially for those working in the fields of invasion ecology, disease emergence, and species conservation.

Methods in Ecology and Evolution

Optimizing survey design for shasta salamanders (Hydromantes spp.) to estimate occurrence in little-studied portions of their range

Shasta salamanders (collectively, Hydromantes samweli, H. shastae, and H. wintu; hereafter, Shasta salamander) are endemic to northern California in the general vicinity of Shasta Lake reservoir. Although generally associated with limestone, they have repeatedly been found in association with other habitats, calling into question the distribution of the species complex. Further limiting our knowledge of the species' distributions is that they are only active or available for sampling on the soil surface for a small portion of the year, and detection probabilities for the species have never been estimated. We developed and implemented a survey protocol designed to estimate detection, availability, and occurrence probabilities from December 2019 through March 2020. We provide inference on Shasta salamander occurrence in portions of their range that have received little survey effort. We found that Shasta salamander occurrence was positively associated with the percent cover of embedded rock, and the species' availability (i.e., probability of being active on the soil surface during sampling) was positively related to relative humidity. The probability of occurrence of Shasta salamanders in our study area was low, and our winter-to-spring survey protocol was effective for estimating detection, availability, and occurrence probabilities in the study area and at specific sites. We suggest that conducting replicate surveys that quantify animal availability and detection probabilities will facilitate a better understanding of the habitat associations of Shasta salamanders and other rare species that might often be unavailable for detection.

California

Accommodating the role of site memory in dynamic species distribution models

First-order dynamic occupancy models (FODOMs) are a class of state-space model in which the true state (occurrence) is observed imperfectly. An important assumption of FODOMs is that site dynamics only depend on the current state and that variations in dynamic processes are adequately captured with covariates or random effects. However, it is often difficult to understand and/or measure the covariates that generate ecological data, which are typically spatiotemporally correlated. Consequently, the non-independent error structure of correlated data causes underestimation of parameter uncertainty and poor ecological inference. Here, we extend the FODOM framework with a second-order Markov process to accommodate site memory when covariates are not available. Our modeling framework can be used to make reliable inference about site occupancy, colonization, extinction, turnover, and detection probabilities. We present a series of simulations to illustrate the data requirements and model performance. We then applied our modeling framework to 13 yr of data from an amphibian community in southern Arizona, USA. In this analysis, we found residual temporal autocorrelation of population processes for most species, even after accounting for long-term drought dynamics. Our approach represents a valuable advance in obtaining inference on population dynamics, especially as they relate to metapopulations.

Arizona

Principles and mechanisms of wildlife population persistence in the face of disease

Emerging infectious diseases can result in species declines and hamper recovery efforts for at-risk populations. Generalizing considerations for reducing the risk of pathogen introduction and mitigating the effects of disease remains challenging and inhibits our ability to provide guidance for species recovery planning. Given the growing rates of emerging pathogens globally, we identify key principles and mechanisms for maintaining sustainable populations in the face of emerging diseases (including minimizing the risk of pathogen introductions and their future effects on hosts). Our synthesis serves as a reference for minimizing the risk of future disease outbreaks, mitigating the deleterious effects of future disease outbreaks on species extinction risk, and a review of the theoretical and/or empirical examples supporting these considerations.

Frontiers in Ecology and Environment