scholarly journals Spatial extinction date estimation: a novel method for reconstructing spatiotemporal patterns of extinction and identifying potential zones of rediscovery

2018 ◽  
Author(s):  
Colin J. Carlson ◽  
Kevin R. Burgio ◽  
Tad A. Dallas ◽  
Alexander L. Bond
Keyword(s):  
Historical Ecology ◽  
R Package ◽  
Spatiotemporal Patterns ◽  
Population Persistence ◽  
Spatially Explicit ◽  
List Type ◽  
Explicit Method ◽  
Improve Accuracy ◽  
Novel Method ◽  
Sighting Data

AbstractThe estimation of extinction dates from limited and incomplete sighting records is a key challenge in conservation (when experts are uncertain whether a species has gone extinct) and historical ecology (when the date and mechanism of extinction is controversial).We introduce a spatially-explicit method of interpolating extinction date estimators, allowing users to estimate spatiotemporal surfaces of population persistence from georeferenced sighting data of variable quality.We present the R package spatExtinct, which produces spatially-explicit extinction date surfaces from geolocated sightings, including options for custom randomization schemes to improve accuracy with limited datasets. We use simulations to illustrate the sensitivity of the method to parameterization, and apply the method to identify potential areas where Bachman’s warbler (Vermivora bachmanii) might be rediscovered.Our method, and the spatExtinct package, has the potential to help describe and differentiate different drivers of extinction for historical datasets, and could be used to identify possible regions of population persistence for species with an uncertain extinction status, improving on non-spatial or imprecise methods that are currently in use.

scholarly journals FIREcaller: Detecting Frequently Interacting Regions from Hi-C Data

2019 ◽  
Author(s):  
Cheynna Crowley ◽  
Yuchen Yang ◽  
Yunjiang Qiu ◽  
Benxia Hu ◽  
Armen Abnousi ◽  
...  
Keyword(s):  
Gene Regulation ◽  
Spatial Organization ◽  
R Package ◽  
Specific Gene ◽  
List Type ◽  
Cell Type ◽  
R Software ◽  
Computational Tools ◽  
Cell Type Specific ◽  
User Friendly

AbstractHi-C experiments have been widely adopted to study chromatin spatial organization, which plays an essential role in genome function. We have recently identified frequently interacting regions (FIREs) and found that they are closely associated with cell-type-specific gene regulation. However, computational tools for detecting FIREs from Hi-C data are still lacking. In this work, we present FIREcaller, a stand-alone, user-friendly R package for detecting FIREs from Hi-C data. FIREcaller takes raw Hi-C contact matrices as input, performs within-sample and cross-sample normalization, and outputs continuous FIRE scores, dichotomous FIREs, and super-FIREs. Applying FIREcaller to Hi-C data from various human tissues, we demonstrate that FIREs and super-FIREs identified, in a tissue-specific manner, are closely related to gene regulation, are enriched for enhancer-promoter (E-P) interactions, tend to overlap with regions exhibiting epigenomic signatures of cis-regulatory roles, and aid the interpretation or GWAS variants. The FIREcaller package is implemented in R and freely available at https://yunliweb.its.unc.edu/FIREcaller.Highlights– Frequently Interacting Regions (FIREs) can be used to identify tissue and cell-type-specific cis-regulatory regions.– An R software, FIREcaller, has been developed to identify FIREs and clustered FIREs into super-FIREs.

CIRCLES AND SPIRALS: POPULATION PERSISTENCE IN A SPATIALLY EXPLICIT PREDATOR–PREY MODEL

Ecology ◽  
1998 ◽  
Vol 79 (7) ◽  
pp. 2516-2530 ◽  
Author(s):  
W. S. C. Gurney ◽  
A. R. Veitch ◽  
I. Cruickshank ◽  
G. McGeachin
Keyword(s):  
Population Persistence ◽  
Spatially Explicit ◽  
Predator Prey ◽  
Predator Prey Model ◽  
Prey Model

scholarly journals blockCV: an R package for generating spatially or environmentally separated folds for k-fold cross-validation of species distribution models

2018 ◽  
Author(s):  
Roozbeh Valavi ◽  
Jane Elith ◽  
José J. Lahoz-Monfort ◽  
Gurutzeta Guillera-Arroita
Keyword(s):  
Species Distribution ◽  
Cross Validation ◽  
Species Distribution Models ◽  
Predictive Performance ◽  
R Package ◽  
Species Distribution Modelling ◽  
List Type ◽  
Distribution Models ◽  
Distribution Modelling ◽  
Evaluation Approaches

SummaryWhen applied to structured data, conventional random cross-validation techniques can lead to underestimation of prediction error, and may result in inappropriate model selection.We present the R package blockCV, a new toolbox for cross-validation of species distribution modelling.The package can generate spatially or environmentally separated folds. It includes tools to measure spatial autocorrelation ranges in candidate covariates, providing the user with insights into the spatial structure in these data. It also offers interactive graphical capabilities for creating spatial blocks and exploring data folds.Package blockCV enables modellers to more easily implement a range of evaluation approaches. It will help the modelling community learn more about the impacts of evaluation approaches on our understanding of predictive performance of species distribution models.

scholarly journals SPARSEMODr: Rapid simulations of spatially explicit and stochastic models of infectious disease

2021 ◽  
Author(s):  
Joseph R Mihaljevic ◽  
Seth Borkovec ◽  
Saikanth Ratnavale ◽  
Toby D Hocking ◽  
Kelsey E Banister ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Stochastic Models ◽  
Disease Modeling ◽  
R Package ◽  
Work Flow ◽  
Spatially Explicit ◽  
Universal Functions ◽  
Spatially Explicit Models ◽  
Complex Models ◽  
The Common

1. Simulating the dynamics of realistically complex models of infectious disease is conceptually challenging and computationally expensive. This results in a heavy reliance on customized software and, correspondingly, lower reproducibility across disease modeling studies. 2. SPARSEMOD stands for SPAtial Resolution-SEnsitive Models of Outbreak Dynamics. The goal of our project, encapsulated by the SPARSEMODr R package, is to offer a framework for rapidly simulating the dynamics of stochastic and spatially-explicit models of infectious disease for use in pedagogical and applied contexts. 3. We outline the universal functions of our package that allow for user-customization while demonstrating the common work flow. 4. SPARSEMODr offers an extendable framework that should allow the open-source community of disease modelers to add new model types and functionalities in future releases.

scholarly journals Transcriptome Deconvolution of Heterogeneous Tumor Samples with Immune Infiltration

2017 ◽  
Author(s):  
Zeya Wang ◽  
Shaolong Cao ◽  
Jeffrey S. Morris ◽  
Jaeil Ahn ◽  
Rongjie Liu ◽  
...  
Keyword(s):  
Experimental Validation ◽  
Expression Profiles ◽  
R Package ◽  
High Accuracy ◽  
High Dimensional ◽  
Transcriptomic Data ◽  
Conditional Mode ◽  
Improve Accuracy ◽  
Heterogeneous Tissues ◽  
Heterogeneous Tumor

AbstractTranscriptomic deconvolution in cancer and other heterogeneous tissues remains challenging. Available methods lack the ability to estimate both component-specific proportions and expression profiles for individual samples. We present DeMixT, a new tool to deconvolve high dimensional data from mixtures of more than two components. DeMixT implements an iterated conditional mode algorithm and a novel gene-set-based component merging approach to improve accuracy. In a series of experimental validation studies and application to TCGA data, DeMixT showed high accuracy. Improved deconvolution is an important step towards linking tumor transcriptomic data with clinical outcomes. An R package, scripts and data are available: https://github.com/wwylab/DeMixT/.

scholarly journals Trailing-edge zombie forests can increase population persistence in the face of climate change

2021 ◽  
Author(s):  
Robin R. Decker ◽  
Marissa L. Baskett ◽  
Alan Hastings
Keyword(s):  
Climate Change ◽  
Maximum Rate ◽  
Population Persistence ◽  
Spatially Explicit ◽  
Suitable Habitat ◽  
Trailing Edge ◽  
Left Behind ◽  
Range Edge ◽  
The Face ◽  
Range Core

Climate-driven habitat shifts pose challenges for dispersal-limited, late-maturing taxa such as trees. Older trees are often the most reproductive individuals in the population, but as habitats shift, these individuals can be left behind in the trailing range edge, generating "zombie forests" that may persist long after the suitable habitat has shifted. Are these zombie forests vestiges of ecosystems past or do they play an ecological role? To understand how zombie forests affect population persistence, we developed a spatially explicit, stage-structured model of tree populations occupying a shifting habitat. Our model shows that seed dispersal from zombie forests to the range core can considerably increase the maximum rate of climate change that a population can withstand. Moreover, the entire core population can ultimately descend from recruitment-limited zombie forests, highlighting their demographic value. Our results suggest that preserving trailing-edge zombie forests can greatly increase population persistence in the face of climate change.

scholarly journals ShapeRotator: an R tool for standardised rigid rotations of articulated Three-Dimensional structures with application for geometric morphometrics

2017 ◽  
Author(s):  
Marta Vidal-García ◽  
Lashi Bandara ◽  
J. Scott Keogh
Keyword(s):  
Geometric Morphometrics ◽  
Phenotypic Diversity ◽  
Three Dimensional ◽  
R Package ◽  
Morphological Data ◽  
List Type ◽  
Shape Variation ◽  
Data Set ◽  
Articulated Structures ◽  
Shape And Size

SummaryThe quantification of complex morphological patterns typically involves comprehensive shape and size analyses, usually obtained by gathering morphological data from all the structures that capture the phenotypic diversity of an organism or object. Articulated structures are a critical component of overall phenotypic diversity, but data gathered from these structures are difficult to incorporate in to modern analyses because of the complexities associated with jointly quantifying 3D shape in multiple structures.While there are existing methods for analysing shape variation in articulated structures in Two-Dimensional (2D) space, these methods do not work in 3D, a rapidly growing area of capability and research.Here we describe a simple geometric rigid rotation approach that removes the effect of random translation and rotation, enabling the morphological analysis of 3D articulated structures. Our method is based on Cartesian coordinates in 3D space so it can be applied to any morphometric problem that also uses 3D coordinates (e.g. spherical harmonics). We demonstrate the method by applying it to a landmark-based data set for analysing shape variation using geometric morphometrics.We have developed an R tool (ShapeRotator) so that the method can be easily implemented in the commonly used R package geomorph and MorphoJ software. This method will be a valuable tool for 3D morphological analyses in articulated structures by allowing an exhaustive examination of shape and size diversity.

scholarly journals fluxweb: a R package to easily estimate energy fluxes in food webs

2017 ◽  
Author(s):  
Benoit Gauzens ◽  
Andrew Barnes ◽  
Darren Giling ◽  
Jes Hines ◽  
Malte Jochum ◽  
...  
Keyword(s):  
Steady State ◽  
Food Web ◽  
Food Webs ◽  
Ecosystem Functioning ◽  
R Package ◽  
Estimation Methods ◽  
List Type ◽  
Energy Fluxes ◽  
Flux System ◽  
Primary Output

AbstractUnderstanding how changes in biodiversity will impact the stability and functioning of ecosystems is a central challenge in ecology. Food-web approaches have been advocated to link community composition with ecosystem functioning by describing the fluxes of energy among species or trophic groups. However, estimating such fluxes remains problematic because current methods become unmanageable as network complexity increases.We developed a generalisation of previous indirect estimation methods assuming a steady state system [1, 2, 3]: the model estimates energy fluxes in a top-down manner assuming system equilibrium; each node’s losses (consumption and physiological) balances its consumptive gains. Jointly, we provide theoretical and practical guidelines to use the fluxweb R package (available on CRAN at https://bit.ly/2OC0uKF).We also present how the framework can merge with the allometric theory of ecology [4] to calculate fluxes based on easily obtainable organism-level data (i.e. body masses and species groups -eg, plants animals), opening its use to food webs of all complexities. Physiological losses (metabolic losses or losses due to death other than from predation within the food web) may be directly measured or estimated using allometric relationships based on the metabolic theory of ecology, and losses and gains due to predation are a function of ecological efficiencies that describe the proportion of energy that is used for biomass production.The primary output is a matrix of fluxes among the nodes of the food web. These fluxes can be used to describe the role of a species, a function of interest (e.g. predation; total fluxes to predators), multiple functions, or total energy flux (system throughflow or multitrophic functioning). Additionally, the package includes functions to calculate network stability based on the Jacobian matrix, providing insight into how resilient the network is to small perturbations at steady state.Overall, fluxweb provides a flexible set of functions that greatly increase the feasibility of implementing food-web energetic approaches to more complex systems. As such, the package facilitates novel opportunities for mechanistically linking quantitative food webs and ecosystem functioning in real and dynamic natural landscapes.

scholarly journals Generation and application of river network analogues for use in ecology and evolution

2020 ◽  
Author(s):  
Luca Carraro ◽  
Enrico Bertuzzo ◽  
Emanuel A. Fronhofer ◽  
Reinhard Furrer ◽  
Isabelle Gounand ◽  
...  
Keyword(s):  
Spatial Ecology ◽  
Spanning Trees ◽  
Random Search ◽  
Three Dimensional ◽  
R Package ◽  
River Network ◽  
River Networks ◽  
List Type ◽  
Freshwater Ecology ◽  
Scaling Features

AbstractSeveral key processes in freshwater ecology and evolution are governed by the connectivity inherent to dendritic river networks. These networks have extensively been analyzed from a geomorphological and hydrological viewpoint, yet network structures classically used in modelling have only been partially representative of the structure of real river basins, and have often failed to capture well known scaling features of real river networks. Pioneering work has identified optimal channel networks (OCNs) as spanning trees that reproduce all scaling features characteristic of real, natural stream networks worldwide. While these networks have been used to generate landscapes for studies on metapopulations, biodiversity and epidemiology, their generation has not been generally accessible.Given the increasing interest in dendritic riverine networks by ecologists and evolutionary biologists, we here present a method to generate OCNs and, to facilitate its application, we also provide the R-package OCNet. Owing to the random search process that generates OCNs, multiple network replicas spanning the same surface can be built, allowing one to perform computational experiments whose results do not depend on the particular shape of a single river network. The OCN construct also enables the generation of elevational gradients derived from the optimal network configuration, which can constitute three-dimensional landscapes for spatial studies in both terrestrial and freshwater realms. Moreover, the OCNet package provides functions that aggregate the OCN into an arbitrary number of nodes, calculate several metrics and descriptors of river networks, and draw relevant features of the network.We describe the main functionalities of the package and present how it can be integrated into other R-packages commonly used in spatial ecology. Moreover, we exemplify the generation of OCNs and discuss an application to a metapopulation model for an invasive riverine species.In conclusion, OCNet provides a powerful tool to generate and use realistic river network analogues for various applications. It thereby allows the design of spatially realistic studies in increasingly impacted ecosystems, and enhances our knowledge on spatial processes in freshwater ecology in general.

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