Title: For everything there is a season: Analysing periodic mortality patterns with the cyclomort r package
Abstract Many important demographic processes are seasonal, including survival. For many species, mortality risk is significantly higher at certain times of the year than at others, whether because resources are scarce, susceptibility to predators or disease is high, or both. Despite the importance of survival modelling in wildlife sciences, no tools are available to estimate the peak, duration and relative importance of these ‘seasons of mortality’.We presentcyclomort, anrpackage that estimates the timing, duration and intensity of any number of mortality seasons with reliable confidence intervals. The package includes a model selection approach to determine the number of mortality seasons and to test whether seasons of mortality vary across discrete grouping factors.We illustrate the periodic hazard function model and workflow of cyclomort with simulated data. We then estimate mortality seasons of two caribouRangifer taranduspopulations that have strikingly different mortality patterns, including different numbers and timing of mortality peaks, and a marked change in one population over time.Thecyclomortpackage was developed to estimate mortality seasons for wildlife, but the package can model any time‐to‐event processes with a periodic component. more »« less
Abstract ThePCMBase Rpackage is a powerful computational tool that enables efficient calculations of likelihoods for a wide range of phylogenetic Gaussian models.Taking advantage of it, we redesigned theRpackagemvSLOUCH.Here, we demonstrate how the new version of the package can be used to thoroughly examine the evolution and adaptation of traits in a large dataset of 1252 vascular plants through the use of multivariate Ornstein–Uhlenbeck processes.The results of our analysis demonstrate the ability of the modelling framework to distinguish between various alternative hypotheses regarding the evolution of functional traits in angiosperms.
Doser, Jeffrey_W; Finley, Andrew_O; Kéry, Marc; Zipkin, Elise_F
(, Methods in Ecology and Evolution)
Abstract Numerous modelling techniques exist to estimate abundance of plant and animal populations. The most accurate methods account for multiple complexities found in ecological data, such as observational biases, spatial autocorrelation, and species correlations. There is, however, a lack of user‐friendly and computationally efficient software to implement the various models, particularly for large data sets.We developed thespAbundance Rpackage for fitting spatially explicit Bayesian single‐species and multi‐species hierarchical distance sampling models, N‐mixture models, and generalized linear mixed models. The models within the package can account for spatial autocorrelation using Nearest Neighbour Gaussian Processes and accommodate species correlations in multi‐species models using a latent factor approach, which enables model fitting for data sets with large numbers of sites and/or species.We provide three vignettes and three case studies that highlightspAbundancefunctionality. We used spatially explicit multi‐species distance sampling models to estimate density of 16 bird species in Florida, USA, an N‐mixture model to estimate black‐throated blue warbler (Setophaga caerulescens) abundance in New Hampshire, USA, and a spatial linear mixed model to estimate forest above‐ground biomass across the continental USA.spAbundanceprovides a user‐friendly, formula‐based interface to fit a variety of univariate and multivariate spatially explicit abundance models. The package serves as a useful tool for ecologists and conservation practitioners to generate improved inference and predictions on the spatial drivers of abundance in populations and communities.
Justison, Joshua A.; Solis‐Lemus, Claudia; Heath, Tracy A.
(, Methods in Ecology and Evolution)
Abstract Gene flow is increasingly recognized as an important macroevolutionary process. The many mechanisms that contribute to gene flow (e.g. introgression, hybridization, lateral gene transfer) uniquely affect the diversification of dynamics of species, making it important to be able to account for these idiosyncrasies when constructing phylogenetic models. Existing phylogenetic‐network simulators for macroevolution are limited in the ways they model gene flow.We presentSiPhyNetwork, an R package for simulating phylogenetic networks under a birth–death‐hybridization process.Our package unifies the existing birth–death‐hybridization models while also extending the toolkit for modelling gene flow. This tool can create patterns of reticulation such as hybridization, lateral gene transfer, and introgression.Specifically, we model different reticulate events by allowing events to either add, remove or keep constant the number of lineages. Additionally, we allow reticulation events to be trait dependent, creating the ability to model the expanse of isolating mechanisms that prevent gene flow. This tool makes it possible for researchers to model many of the complex biological factors associated with gene flow in a phylogenetic context.
Steadmon, Maria; Ngiraklang, Kebang; Nagata, Macy; Masga, Keanu; Frank, Kiana L.
(, Water Environment Research)
Abstract Staphylococcus aureusis an opportunistic pathogen frequently detected in environmental waters and commonly causes skin infections to water users.S. aureusconcentrations in fresh, brackish, and marine waters are positively correlated with water turbidity. To reduce the risk ofS. aureusinfections from environmental waters,S. aureussurvival (stability and multiplication) in turbid waters needs to be investigated. The aim of this study was to measureS. aureusin turbid fresh and brackish water samples and compare the concentrations over time to determine which conditions are associated with enhancedS. aureussurvival. Eighteen samples were collected from fresh and brackish water sources from two different sites on the east side of Oʻahu, Hawaiʻi.S. aureuswas detected in microcosms for up to 71 days with standard microbial culturing techniques. On average, the greatest environmental concentrations ofS. aureuswere in high turbidity fresh waters followed by high turbidity brackish waters. Models demonstrate that salinity and turbidity significantly predict environmentalS. aureusconcentrations.S. aureuspersistence over the extent of the experiment was the greatest in high turbidity microcosms with T90's of 147.8 days in brackish waters and 80.8 days in freshwaters. This study indicates that saline, turbid waters, in the absence of sunlight, provides suitable conditions for enhanced persistence ofS. aureuscommunities that may increase the risk of exposure in environmental waters. Practitioner PointsStaphylococcus aureusconcentrations, survival, and persistence were assessed in environmental fresh and brackish waters.Experimental design preserved in situ conditions to measureS. aureussurvival.Higher initialS. aureusconcentrations were observed in fresh waters with elevated turbidity, while sustained persistence was greater in brackish waters.Water turbidity and salinity were both positively associated withS. aureusconcentrations and persistence.Climate change leads to more intense rainfall events which increase water turbidity and pathogen loading, heightening the exposure risk toS. aureus.
Zobitz, John; Ayres, Edward; Werbin, Zoey; Abdi, Ridwan; Ashburner‐Wright, Natalie; Brown, Lillian; Frink‐Sobierajski, Ryan; Lee, Lajntxiag; Mehmeti, Dijonë; Tran, Christina; et al
(, Methods in Ecology and Evolution)
Abstract Accurate quantification of soil carbon fluxes is essential to reduce uncertainty in estimates of the terrestrial carbon sink. However, these fluxes vary over time and across ecosystem types and so, it can be difficult to estimate them accurately across large scales. The flux‐gradient method estimates soil carbon fluxes using co‐located measurements of soil CO2concentration, soil temperature, soil moisture and other soil properties. The National Ecological Observatory Network (NEON) provides such data across 20 ecoclimatic domains spanning the continental U.S., Puerto Rico, Alaska and Hawai‘i.We present an R software package (neonSoilFlux) that acquires soil environmental data to compute half‐hourly soil carbon fluxes for each soil replicate plot at a given terrestrial NEON site. To assess the computed fluxes, we visited six focal NEON sites and measured soil carbon fluxes using a closed‐dynamic chamber approach.Outputs from theneonSoilFluxshowed agreement with measured fluxes (R2between measured andneonSoilFluxoutputs ranging from 0.12 to 0.77 depending on calculation method used); measured outputs generally fell within the range of calculated uncertainties from the gradient method. Calculated fluxes fromneonSoilFluxaggregated to the daily scale exhibited expected site‐specific seasonal patterns.While the flux‐gradient method is broadly effective, its accuracy is highly sensitive to site‐specific inputs, including the extent to which gap‐filing techniques are used to interpolate missing sensor data and to estimates of soil diffusivity and moisture content. Future refinement and validation ofneonSoilFluxoutputs can contribute to existing databases of soil carbon flux measurements, providing near real‐time estimates of a critical component of the terrestrial carbon cycle.
Gurarie, Eliezer, Thompson, Peter R., Kelly, Allicia P., Larter, Nicholas C., Fagan, William F., Joly, Kyle, and Graham, ed., Laura. For everything there is a season: Analysing periodic mortality patterns with the cyclomort r package. Methods in Ecology and Evolution 11.1 Web. doi:10.1111/2041-210X.13305.
Gurarie, Eliezer, Thompson, Peter R., Kelly, Allicia P., Larter, Nicholas C., Fagan, William F., Joly, Kyle, & Graham, ed., Laura. For everything there is a season: Analysing periodic mortality patterns with the cyclomort r package. Methods in Ecology and Evolution, 11 (1). https://doi.org/10.1111/2041-210X.13305
Gurarie, Eliezer, Thompson, Peter R., Kelly, Allicia P., Larter, Nicholas C., Fagan, William F., Joly, Kyle, and Graham, ed., Laura.
"For everything there is a season: Analysing periodic mortality patterns with the cyclomort r package". Methods in Ecology and Evolution 11 (1). Country unknown/Code not available: Wiley-Blackwell. https://doi.org/10.1111/2041-210X.13305.https://par.nsf.gov/biblio/10455477.
@article{osti_10455477,
place = {Country unknown/Code not available},
title = {For everything there is a season: Analysing periodic mortality patterns with the cyclomort r package},
url = {https://par.nsf.gov/biblio/10455477},
DOI = {10.1111/2041-210X.13305},
abstractNote = {Abstract Many important demographic processes are seasonal, including survival. For many species, mortality risk is significantly higher at certain times of the year than at others, whether because resources are scarce, susceptibility to predators or disease is high, or both. Despite the importance of survival modelling in wildlife sciences, no tools are available to estimate the peak, duration and relative importance of these ‘seasons of mortality’.We presentcyclomort, anrpackage that estimates the timing, duration and intensity of any number of mortality seasons with reliable confidence intervals. The package includes a model selection approach to determine the number of mortality seasons and to test whether seasons of mortality vary across discrete grouping factors.We illustrate the periodic hazard function model and workflow of cyclomort with simulated data. We then estimate mortality seasons of two caribouRangifer taranduspopulations that have strikingly different mortality patterns, including different numbers and timing of mortality peaks, and a marked change in one population over time.Thecyclomortpackage was developed to estimate mortality seasons for wildlife, but the package can model any time‐to‐event processes with a periodic component.},
journal = {Methods in Ecology and Evolution},
volume = {11},
number = {1},
publisher = {Wiley-Blackwell},
author = {Gurarie, Eliezer and Thompson, Peter R. and Kelly, Allicia P. and Larter, Nicholas C. and Fagan, William F. and Joly, Kyle and Graham, ed., Laura},
}
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