A5044706713- Wildlife Ecology and Conservation
- Genetic and phenotypic traits in livestock
- COVID-19 epidemiological studies
- Ecology and Vegetation Dynamics Studies
- Insect and Arachnid Ecology and Behavior
- Spatial and Panel Data Analysis
- Plant and animal studies
- Species Distribution and Climate Change
- Animal Behavior and Reproduction
- Wildlife-Road Interactions and Conservation
- Animal Behavior and Welfare Studies
- Genetic Mapping and Diversity in Plants and Animals
- Statistical Methods and Bayesian Inference
- Soil Geostatistics and Mapping
- Data-Driven Disease Surveillance
- Groundwater and Isotope Geochemistry
- Economic and Environmental Valuation
- SARS-CoV-2 and COVID-19 Research
- Genetic diversity and population structure
- Fish Ecology and Management Studies
- Rangeland and Wildlife Management
- Marine animal studies overview
- Diffusion and Search Dynamics
- Animal Vocal Communication and Behavior
- Bayesian Methods and Mixture Models
Pennsylvania State University
2016-2025
Center for Disease Dynamics, Economics & Policy
2014-2025
Ecological Society of America
2018-2019
John Wiley & Sons (United States)
2018-2019
Millennium Engineering and Integration (United States)
2018
Muhlenberg College
2018
United States Geological Survey
2015
Colorado Parks and Wildlife
2015
Colorado State University
2010-2015
Utah State University
2010
Abstract Ecological data often exhibit spatial pattern, which can be modeled as autocorrelation. Conditional autoregressive (CAR) and simultaneous (SAR) models are network‐based (also known graphical models) specifically designed to model spatially autocorrelated based on neighborhood relationships. We identify discuss six different types of practical ecological inference using CAR SAR models, including: (1) selection, (2) regression, (3) estimation autocorrelation, (4) other connectivity...
In spatial generalized linear mixed models (SGLMMs), covariates that are spatially smooth often collinear with random effects. This phenomenon is known as confounding and has been studied primarily in the case where support of process being discrete (e.g., areal data). this case, most common approach suggested restricted regression (RSR) which effects constrained to be orthogonal fixed We consider RSR geostatistical (continuous support) setting. show provides computational benefits relative...
The processes influencing animal movement and resource selection are complex varied. Past efforts to model behavioral changes over time used Bayesian statistical models with variable parameter space, such as reversible-jump Markov chain Monte Carlo approaches, which computationally demanding inaccessible many practitioners. We present a continuous-time discrete-space (CTDS) of that can be fit using standard generalized linear modeling (GLM) methods. This CTDS approach allows for the joint...
Circuit theory has seen extensive recent use in the field of ecology, where it is often applied to study functional connectivity. The landscape typically represented by a network nodes and resistors, with resistance between function characteristics. effective distance two locations on network. been many other scientific fields for exploratory analyses, but parametric models circuits are not common literature. To model explicitly, we demonstrate link Gaussian Markov random contemporary...
Summary Analyses based on utilization distributions (UDs) have been ubiquitous in animal space use studies, largely because they are computationally straightforward and relatively easy to employ. Conventional applications of resource functions (RUFs) suggest that estimates UDs can be used as response variables a regression involving spatial covariates interest. It has claimed contemporary implementations RUFs yield inference about selection, although our knowledge, an explicit connection not...
New methods for modeling animal movement based on telemetry data are developed regularly. With advances in capabilities, models becoming increasingly sophisticated. Despite a need population‐level inference, still predominantly individual‐level inference. Most efforts to upscale the inference population level either post hoc or complicated enough that only developer can implement model. Hierarchical Bayesian provide an ideal platform development of but be challenging fit due computational...
Abstract 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 likelihood‐based packages lme4 ) machine learning methods. These software programs afford user greater control flexibility in tailoring hierarchical models. However, this level places a higher degree responsibility on evaluate robustness their inference. To determine how often...
Multiple factors complicate the analysis of animal telemetry location data. Recent advancements address issues such as temporal autocorrelation and measurement error, but additional challenges remain. Difficulties introduced by complicated error structures or barriers to movement can weaken inference. We propose an approach for obtaining resource selection inference from data that accounts structures, constraints, temporally autocorrelated observations. specify a model observed with...
Abstract High-density living is often associated with high disease risk due to density-dependent epidemic spread. Despite being paragons of high-density living, the social insects have largely decoupled association epidemics. It hypothesized that this accomplished through prophylactic and inducible defenses termed ‘collective immunity’. Here we characterise segregation carpenter ants would be most likely encounter infectious agents (i.e. foragers) using integrated social, spatial temporal...
Animal movement drives important ecological processes such as migration and the spread of infectious disease. Current approaches to modeling animal tracking data focus on parametric models used understand environmental effects behavior fill in missing data. Machine Learning Deep learning algorithms are powerful flexible predictive tools but have rarely been applied In this study we present a general framework for predicting that is combination two steps: first behavioral states second...
Abstract Background When three SARS-CoV-2 vaccines came to market in Europe and North America the winter of 2020–2021, distribution networks were a race against major epidemiological wave that began autumn 2020. Rapid optimized vaccine allocation was critical during this time. With 95% efficacy reported for two vaccines, near-term public health needs likely require is prioritized elderly, care workers, teachers, essential individuals with comorbidities putting them at risk severe clinical...
Understanding animal movement and resource selection provides important information about the ecology of animal, but an animal's behavior are not typically constant in time. We present a velocity-based approach for modeling space time that allows temporal heterogeneity response to environment, irregularity telemetry data, accounts uncertainty location information. Population-level inference on patterns can then be made through cluster analysis parameters related behavior. illustrate this...
Intraspecific trait variation is caused by genetic and plastic responses to environment. This intraspecific diversity captured in immense natural history collections, giving us a window into across continents through centuries of environmental shifts. Here we tested if hypotheses based on life the leaf economics spectrum explain changes global spatiotemporal gradients. We measured phenotypes 216-year time series Arabidopsis thaliana accessions from its native range applied spatially varying...
Cholera is a bacterial water-borne diarrheal disease transmitted via the fecal-oral route that causes high morbidity in sub-Saharan Africa and Asia. It preventable with vaccination, Water, Sanitation, Hygiene (WASH) improvements. However, impact of vaccination endemic settings remains unclear. city Kalemie, on shore Lake Tanganyika, Democratic Republic Congo, where both seasonal mobility lake, potential environmental reservoir, may promote transmission. Kalemie received campaign WASH...
Abstract A basic understanding of how the landscape impedes, or creates resistance to, dispersal organisms and hence gene flow is paramount for successful conservation science management. Spatially structured ecological networks are often used to represent spatial landscape‐genetic relationships, where nodes individuals populations movement represented using non‐binary edge weights. Weights typically assigned estimated by user, rather than observed, validating such weights challenging. We...
Ecological spatial data often come from multiple sources, varying in extent and accuracy. We describe a general approach to reconciling such sets through the use of Bayesian hierarchical framework. This provides way for borrow strength one another while allowing inference on underlying ecological process. apply this study incidence eastern spruce dwarf mistletoe (Arceuthobium pusillum) Minnesota black (Picea mariana). A Department Natural Resources operational inventory stands northern found...
State-level reopenings in late spring 2020 facilitated the resurgence of severe acute respiratory syndrome coronavirus 2 transmission. Here, we analyze age-structured case, hospitalization, and death time series from three states—Rhode Island, Massachusetts, Pennsylvania—that had successful May without summer waves infection. Using 11 daily data streams, show that to summer, epidemic shifted an older a younger age profile elderly individuals were less able reduce contacts during lockdown...
While many species have suffered from the detrimental impacts of increasing human population growth, some species, such as cougars (Puma concolor), been observed using human-modified landscapes. However, habitat can be a source both increased risk and food availability, particularly for large carnivores. Assessing preferential use landscape is important managing wildlife useful in transitional habitats, at wildland-urban interface. Preferential often evaluated resource selection functions...