Grace V. DiRenzo, PhD
Assistant Unit Leader - Massachusetts Cooperative Fish and Wildlife Research Units
Dr. DiRenzo joined the MA Cooperative Research Unit in Nov 2020, where she is the Assistant Unit Leader of Wildlife and adjunct faculty in the department of Environmental Conservation at the University of Massachusetts, Amherst. Dr. DiRenzo received her PhD at the University of Maryland, College Park, and her Bachelor’s degree from the University of Connecticut, Storrs. Her research emphasizes disease dynamics, community and population ecology, and species conservation. To mimic natural hierarchical systems, she develops hierarchical Bayesian models, and she uses data collected over space and time to separate ecological and observational processes to answer ecological questions.
Dr. DiRenzo's research program focuses on unifying ecological and evolutionary theory to address fundamental questions in ecology using field, experimental, and quantitative approaches.
She enjoys teaching graduate courses related to quantitative ecology, disease ecology, and population/community ecology.
Professional Experience
Assistant Unit Leader, Massachusetts Cooperative Fish and Wildlife Research Unit, 2020-
Education and Certifications
PhD, University of Maryland, College Park, 2011
BS, University of Connecticut, 2007
Science and Products
Framework for Protecting Aquatic Biodiversity in the Northeast Under Changing Climates
Aquatic ecosystems provide habitat and migration corridors to a myriad of species, including plants, fishes, amphibians, birds, mammals, and insects. These ecosystems typically contain relatively higher biodiversity than their terrestrial counterparts; yet, aquatic biodiversity loss in North America is occurring at a rate five times faster than in terrestrial ecosystems. One of the major causes of
Abiotic and biotic factors reduce viability of a high-elevation salamander in its native range
Includes data used 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.
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 crit
Authors
Molly Bletz, Evan H. Campbell Grant, Graziella Vittoria DiRenzo
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 wer
Authors
Andrew B. Gordon Jr., Donovan Drummey, Anthony Tur, Annie E. Curtis, Jacob C. McCumber, Michael T. Jones, Jeremy C. Andersen, Graziella Vittoria DiRenzo
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 d
Authors
Elias Rosenblatt, Jonathan D. Cook, Graziella Vittoria DiRenzo, Evan H. Campbell Grant, Fernando Arce, Kimberly M Pepin, F. Javiera Rudolph, Michael C. Runge, Susan A. Shriner, Daniel P. Walsh, Brittany A. Mosher
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 fa
Authors
William G. Pfadenhauer, Graziella Vittoria DiRenzo, Bethany A. Bradley
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.
Authors
Margaret McEachran, Johanna A. Harvey, Riley Olivia Mummah, Molly Bletz, Claire S. Teitelbaum, Elias Rosenblatt, F. Javiera Rudolph, Fernando Arce, Shanglai Yin, Diann Prosser, Brittany A. Mosher, Jennifer M. Mullinax, Graziella Vittoria DiRenzo, Jannelle Couret, Michael C. Runge, Evan H. Campbell Grant, Jonathan D. Cook
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. detecti
Authors
Evan H. Campbell Grant, Riley O. Mummah, Brittany A. Mosher, Jonah Evans, Graziella Vittoria DiRenzo
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 mod
Authors
Graziella Vittoria DiRenzo, Ephraim Hanks, David A. W. Miller
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 knowle
Authors
Brian J. Halstead, Patrick M. Kleeman, Graziella Vittoria DiRenzo, Jonathan P. Rose
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 p
Authors
Graziella Vittoria DiRenzo, David A. W. Miller, Evan H. Campbell Grant
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 covari
Authors
Graziella Vittoria DiRenzo, David A. W. Miller, Blake R. Hossack, Brent H. Sigafus, Paige E. Howell, Erin L. Muths, Evan H. Campbell Grant
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 princi
Authors
Robin E. Russell, Graziella Vittoria DiRenzo, J. Szymanski, Katrina E. Alger, Evan H. Campbell Grant
Code for quantitative support for the benefits of proactive management for wildlife disease control
This software release contains the input data, R scripts, and Rmarkdown visualization scripts. This includes (i) aggregation code of expert elicited parameter estimates, (ii) simulation code using our develop dynamic multi-state occupancy model for no management, proactive management, and reactive management, (iii) code for probabilistic decision trees, and (iv) Rmarkdown scripts visualize the sim
Code for the effect of myiasis on Eastern Box Turtle (Terrapene carolina carolina) body condition, movement, and habitat use at Camp Edwards
This software release contains one R script that reproduces all of the statistical analysis with objectives to (2) determine if myiasis affects Eastern Box Turtle body condition, (3) determine if myiasis affects Eastern Box Turtle shell temperature, (4) determine if myiasis affects Eastern Box Turtle habitat use, and (5) determine if myiasis affected turtles move shorter distances than noninfected
Code for Human activity drives establishment, but not invasion, of non-native plants on islands
This software release contains 7 R markdown files, the contents of which are described below. The raw data analyzed in these files is available at the following DOI: https://scholarworks.umass.edu/data/175/
1. SEMs_Native.Rmd
- Code for the piecewise structural equation model (pSEM) that predicts native plant richness on islands using the covariates described in the manuscript.
-
Code for: Small enzootic survival costs mask the potential for long-term population size suppression
This repository contains all of the scripts to reproduce the analyses, figures, and tables associated with the manuscript Glorioso et al. in review. The scripts are organized into folders, and the folders are numbered in the order in which they should be executed. Briefly, there are six folders that do the following: (1) format the data, (2) fit the model, (3) run the population projections, (4) r
whitetailedSIRS: A package to project SARS-CoV-2 outbreak dynamics in white-tailed deer
This software release contains several R scripts that generate epidemic projections of SARS-CoV-2 in white tailed deer populations using a Susceptible-Infected-Recovered-Susceptible (SIRS) modeling framework. We provide a workflow of vignettes used in Rosenblatt et al. In Prep and Cook et al. In Prep. Users are able to specify transmission parameters for human-deer and deer-deer transmission to qu
Code for: Leveraging local efforts to solve regional-scale ecological questions: using multiple sources of data and a multi-species occupancy model to explore bee-plant interactions
This repository contains all of the scripts to reproduce the analyses, figures, and tables associated with the manuscript Lee et al. in prep. The scripts are organized in the order in which they should be run. Briefly, the files do the following: format the data, fit the model, create the figures, and create the tables.
Inferring pathogen presence when sample misclassification and partial observation occur
This software contains four separate R scripts and one Matlab script that comprise an analysis to estimate the posterior probability of pathogen presence when sample misclassification and partial observations occur. We develop a Bayesian hierarchal framework that accommodates false negative, false positive, and uncertain detections and apply this framework to a case study of the fungal pathogen Ps
Simulations to understand and validate models
This software release contains one R script file that allows the user to download data and reproduce all of the figures and analyses associated with DiRenzo et al. In the R script, we provide a guide to understanding and validating complex models using data simulations. In an effort to facilitate the implementation of these methods, we provide a running example throughout DiRenzo et al. 2022 with
Science and Products
Framework for Protecting Aquatic Biodiversity in the Northeast Under Changing Climates
Aquatic ecosystems provide habitat and migration corridors to a myriad of species, including plants, fishes, amphibians, birds, mammals, and insects. These ecosystems typically contain relatively higher biodiversity than their terrestrial counterparts; yet, aquatic biodiversity loss in North America is occurring at a rate five times faster than in terrestrial ecosystems. One of the major causes of
Abiotic and biotic factors reduce viability of a high-elevation salamander in its native range
Includes data used 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.
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 crit
Authors
Molly Bletz, Evan H. Campbell Grant, Graziella Vittoria DiRenzo
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 wer
Authors
Andrew B. Gordon Jr., Donovan Drummey, Anthony Tur, Annie E. Curtis, Jacob C. McCumber, Michael T. Jones, Jeremy C. Andersen, Graziella Vittoria DiRenzo
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 d
Authors
Elias Rosenblatt, Jonathan D. Cook, Graziella Vittoria DiRenzo, Evan H. Campbell Grant, Fernando Arce, Kimberly M Pepin, F. Javiera Rudolph, Michael C. Runge, Susan A. Shriner, Daniel P. Walsh, Brittany A. Mosher
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 fa
Authors
William G. Pfadenhauer, Graziella Vittoria DiRenzo, Bethany A. Bradley
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.
Authors
Margaret McEachran, Johanna A. Harvey, Riley Olivia Mummah, Molly Bletz, Claire S. Teitelbaum, Elias Rosenblatt, F. Javiera Rudolph, Fernando Arce, Shanglai Yin, Diann Prosser, Brittany A. Mosher, Jennifer M. Mullinax, Graziella Vittoria DiRenzo, Jannelle Couret, Michael C. Runge, Evan H. Campbell Grant, Jonathan D. Cook
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. detecti
Authors
Evan H. Campbell Grant, Riley O. Mummah, Brittany A. Mosher, Jonah Evans, Graziella Vittoria DiRenzo
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 mod
Authors
Graziella Vittoria DiRenzo, Ephraim Hanks, David A. W. Miller
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 knowle
Authors
Brian J. Halstead, Patrick M. Kleeman, Graziella Vittoria DiRenzo, Jonathan P. Rose
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 p
Authors
Graziella Vittoria DiRenzo, David A. W. Miller, Evan H. Campbell Grant
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 covari
Authors
Graziella Vittoria DiRenzo, David A. W. Miller, Blake R. Hossack, Brent H. Sigafus, Paige E. Howell, Erin L. Muths, Evan H. Campbell Grant
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 princi
Authors
Robin E. Russell, Graziella Vittoria DiRenzo, J. Szymanski, Katrina E. Alger, Evan H. Campbell Grant
Code for quantitative support for the benefits of proactive management for wildlife disease control
This software release contains the input data, R scripts, and Rmarkdown visualization scripts. This includes (i) aggregation code of expert elicited parameter estimates, (ii) simulation code using our develop dynamic multi-state occupancy model for no management, proactive management, and reactive management, (iii) code for probabilistic decision trees, and (iv) Rmarkdown scripts visualize the sim
Code for the effect of myiasis on Eastern Box Turtle (Terrapene carolina carolina) body condition, movement, and habitat use at Camp Edwards
This software release contains one R script that reproduces all of the statistical analysis with objectives to (2) determine if myiasis affects Eastern Box Turtle body condition, (3) determine if myiasis affects Eastern Box Turtle shell temperature, (4) determine if myiasis affects Eastern Box Turtle habitat use, and (5) determine if myiasis affected turtles move shorter distances than noninfected
Code for Human activity drives establishment, but not invasion, of non-native plants on islands
This software release contains 7 R markdown files, the contents of which are described below. The raw data analyzed in these files is available at the following DOI: https://scholarworks.umass.edu/data/175/
1. SEMs_Native.Rmd
- Code for the piecewise structural equation model (pSEM) that predicts native plant richness on islands using the covariates described in the manuscript.
-
Code for: Small enzootic survival costs mask the potential for long-term population size suppression
This repository contains all of the scripts to reproduce the analyses, figures, and tables associated with the manuscript Glorioso et al. in review. The scripts are organized into folders, and the folders are numbered in the order in which they should be executed. Briefly, there are six folders that do the following: (1) format the data, (2) fit the model, (3) run the population projections, (4) r
whitetailedSIRS: A package to project SARS-CoV-2 outbreak dynamics in white-tailed deer
This software release contains several R scripts that generate epidemic projections of SARS-CoV-2 in white tailed deer populations using a Susceptible-Infected-Recovered-Susceptible (SIRS) modeling framework. We provide a workflow of vignettes used in Rosenblatt et al. In Prep and Cook et al. In Prep. Users are able to specify transmission parameters for human-deer and deer-deer transmission to qu
Code for: Leveraging local efforts to solve regional-scale ecological questions: using multiple sources of data and a multi-species occupancy model to explore bee-plant interactions
This repository contains all of the scripts to reproduce the analyses, figures, and tables associated with the manuscript Lee et al. in prep. The scripts are organized in the order in which they should be run. Briefly, the files do the following: format the data, fit the model, create the figures, and create the tables.
Inferring pathogen presence when sample misclassification and partial observation occur
This software contains four separate R scripts and one Matlab script that comprise an analysis to estimate the posterior probability of pathogen presence when sample misclassification and partial observations occur. We develop a Bayesian hierarchal framework that accommodates false negative, false positive, and uncertain detections and apply this framework to a case study of the fungal pathogen Ps
Simulations to understand and validate models
This software release contains one R script file that allows the user to download data and reproduce all of the figures and analyses associated with DiRenzo et al. In the R script, we provide a guide to understanding and validating complex models using data simulations. In an effort to facilitate the implementation of these methods, we provide a running example throughout DiRenzo et al. 2022 with