1,721,026 research outputs found
Animal movement tools (amt): R package for managing tracking data and conducting habitat selection analyses
No full textAdvances in tracking technology have led to an exponential increase in animal location data, greatly enhancing our ability to address interesting questions in movement ecology, but also presenting new challenges related to data management and analysis. Step-selection functions (SSFs) are commonly used to link environmental covariates to animal location data collected at fine temporal resolution. SSFs are estimated by comparing observed steps connecting successive animal locations to random steps, using a likelihood equivalent of a Cox proportional hazards model. By using common statistical distributions to model step length and turn angle distributions, and including habitat- and movement-related covariates (functions of distances between points, angular deviations), it is possible to make inference regarding habitat selection and movement processes or to control one process while investigating the other. The fitted model can also be used to estimate utilization distributions and mechanistic home ranges. Here, we present the R package amt (animal movement tools) that allows users to fit SSFs to data and to simulate space use of animals from fitted models. The amt package also provides tools for managing telemetry data. Using fisher (Pekania pennanti) data as a case study, we illustrate a four-step approach to the analysis of animal movement data, consisting of data management, exploratory data analysis, fitting of models, and simulating from fitted models
Estimating Utilization Distributions From Fitted Step-SelectionFunctions
Get PDFHabitat-selection analyses are often used to link environmental covariates, measured within some spatial domain of assumed availability, to animal location data that are assumed to be independent. Step-selection functions (SSFs) relax this independence assumption, by using a conditional model that explicitly acknowledges the spatiotemporal dynamics of the availability domain and hence the temporal dependence among successive locations. However, it is not clear how to produce an SSF-based map of the expected utilization distribution. Here, we used SSFs to analyze virtual animal movement data generated at a fine spatiotemporal scale and then rarefied to emulate realistic telemetry data. We then compared two different approaches for generating maps from the estimated regression coefficients. First, we considered a naïve approach that used the coefficients as if they were obtained by fitting an unconditional model. Second, we explored a simulation-based approach, where maps were generated using stochastic simulations of the parameterized step-selection process. We found that the simulation-based approach always outperformed the naïve mapping approach and that the latter overestimated home-range size and underestimated local space-use variability. Differences between the approaches were greatest for complex landscapes and high sampling rates, suggesting that the simulation-based approach, despite its added complexity, is likely to offer significant advantages when applying SSFs to real data. (PDF) Estimating utilization distributions from fitted step-selection functions. Available from: https://www.researchgate.net/publication/316010730_Estimating_utilization_distributions_from_fitted_step-selection_functions [accessed Oct 22 2018]
R Code and Output Supporting: A 'How-to' Guide for Interpreting Parameters in Habitat-Selection Analyses
No full textSee uploaded readme file.This repository contains data and R code (along with associated output from running the code) supporting all results reported in: Fieberg, J., Signer, J. 2021. A 'How-to' Guide for Interpreting Parameters in Habitat-Selection Analyses. Journal of Animal Ecology. The code demonstrates how to correctly interpret parameters in habitat- and step-selection functions and methods for implementing integrated step-selection analyses using the amt package.Fieberg, John R; Signer, Johannes; Smith, Brian; Avgar, Tal. (2021). R Code and Output Supporting: A 'How-to' Guide for Interpreting Parameters in Habitat-Selection Analyses. Retrieved from the University Digital Conservancy, https://doi.org/10.13020/2q0q-yq05
A ‘How to’ guide for interpreting parameters in habitat‐selection analyses
Get PDFHabitat-selection analyses allow researchers to link animals to their environment via habitat-selection or step-selection functions, and are commonly used to address questions related to wildlife management and conservation efforts. Habitat-selection analyses that incorporate movement characteristics, referred to as integrated step-selection analyses, are particularly appealing because they allow modelling of both movement and habitat-selection processes. Despite their popularity, many users struggle with interpreting parameters in habitat-selection and step-selection functions. Integrated step-selection analyses also require several additional steps to translate model parameters into a full-fledged movement model, and the mathematics supporting this approach can be challenging for many to understand. Using simple examples, we demonstrate how weighted distribution theory and the inhomogeneous Poisson point process can facilitate parameter interpretation in habitat-selection analyses. Furthermore, we provide a ‘how to’ guide illustrating the steps required to implement integrated step-selection analyses using the AMT package By providing clear examples with open-source code, we hope to make habitat-selection analyses more understandable and accessible to end users
From Diffusion to Cognition: Analytical, Statistical and Mechanistic Approaches to the Study of Animal Movement
No full textEcology is the scientific study of processes that determine the distribution and abundance of organisms in space and time. Animal movement plays a crucial role in determining the fates of individuals, populations, communities, and ecosystems. Hence, understanding how and why animals change their spatial location through time is fundamental to ecological research. Animal movement patterns reflect behavioral, physiological and physical interactions between individuals and their environment. Coupling movement and environmental data may thus provide a rich source of information regarding many aspects of animal ecology. In my PhD thesis, I develop and demonstrate different approaches to understanding and predicting animal movement patterns in relation to their environment. In the first chapter, I merge two fundamental ecological models, the functional response and random walk, to formally derive diffusion rates of consumers as function of their handling time and the abundance, distribution and mobility of their resources. This mechanistic null model provides a simple behavior-free explanation to commonly observed negative associations between movement rates and resource abundance, often attributed to area-restricted search behavior. In the second chapter, I use positional data of woodland caribou in Ontario to calculate random walk-based movement expectations for each individual during each month. I then statistically link these expectations to ecologically significant environmental conditions. I show that landscape correlates of forage abundance and habitat permeability explain much of the observed variation in caribou movement characteristics and that residual variability may be attributed to spatial population structure. In the third chapter, I develop a novel state-space approach, enabling simultaneous consideration of resource preference, cognitive capacities and movement limitations, within a simulation model of animal movement across heterogeneous landscapes. The model is designed to enable direct parameterization based on empirical movement and landscape data. This approach allows one to both theoretically explore the consequences of different cognitive abilities and to predict animal space-use patterns across novel or altered landscapes. Overall, my thesis contributes to the rapidly developing field of movement ecology by formulating mechanistically defendable linkages between animal movement and landscape characteristics
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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