Predicting the distribution of endangered species from habitat data is frequently perceived to be a useful technique. Models that predict the presence or absence of a species are normally judged by the number of prediction errors. These may be of two types: false positives and false negatives. Many of the prediction errors can be traced to ecological processes such as unsaturated habitat and species interactions. Consequently, if prediction errors are not placed in an ecological context the results of the model may be misleading. The simplest, and most widely used, measure of prediction accuracy is the number of correctly classified cases. There are other measures of prediction success that may be more appropriate. Strategies for assessing the causes and costs of these errors are discussed. A range of techniques for measuring error in presence/absence models, including some that are seldom used by ecologists (e.g. ROC plots and cost matrices), are described. A new approach to estimating prediction error, which is based on the spatial characteristics of the errors, is proposed. Thirteen recommendations are made to enable the objective selection of an error assessment technique for ecological presence/absence models.

https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0376892997000088

A review of methods for the assessment of prediction errors in conservation presence/absence models

There is disagreement in the literature about the exact nature of the phenomenon of empathy. There are emotional, cogni- tive, and conditioning views, applying in varying degrees across species. An adequate description of the ultimate and proximate mecha- nism can integrate these views. Proximately, the perception of an object's state activates the subject's corresponding representations, which in turn activate somatic and autonomic responses. This mechanism supports basic behaviors (e.g., alarm, social facilitation, vicar- iousness of emotions, mother-infant responsiveness, and the modeling of competitors and predators) that are crucial for the reproduc- tive success of animals living in groups. The Perception-Action Model (PAM), together with an understanding of how representations change with experience, can explain the major empirical effects in the literature (similarity, familiarity, past experience, explicit teach- ing, and salience). It can also predict a variety of empathy disorders. The interaction between the PAM and prefrontal functioning can also explain different levels of empathy across species and age groups. This view can advance our evolutionary understanding of empa- thy beyond inclusive fitness and reciprocal altruism and can explain different levels of empathy across individuals, species, stages of de- velopment, and situations.

/pdf/empathy-its-ultimate-and-proximate-bases-3gnr9okjki.pdf

Empathy: Its ultimate and proximate bases.

The package “adehabitat” for the R software: A tool for the analysis of space and habitat use by animals

Beginning with Emlen (1966) and MacArthur and Pianka (1966) and extending through the last ten years, several authors have sought to predict the foraging behavior of animals by means of mathematical models. These models are very similar,in that they all assume that the fitness of a foraging animal is a function of the efficiency of foraging measured in terms of some "currency" (Schoener, 1971) -usually energy- and that natural selection has resulted in animals that forage so as to maximize this fitness. As a result of these similarities, the models have become known as "optimal foraging models"; and the theory that embodies them, "optimal foraging theory." The situations to which optimal foraging theory has been applied, with the exception of a few recent studies, can be divided into the following four categories: (1) choice by an animal of which food types to eat (i.e., optimal diet); (2) choice of which patch type to feed in (i.e., optimal patch choice); (3) optimal allocation of time to different patches; and (4) optimal patterns and speed of movements. In this review we discuss each of these categories separately, dealing with both the theoretical developments and the data that permit tests of the predictions. The review is selective in the sense that we emphasize studies that either develop testable predictions or that attempt to test predictions in a precise quantitative manner. We also discuss what we see to be some of the future developments in the area of optimal foraging theory and how this theory can be related to other areas of biology. Our general conclusion is that the simple models so far formulated are supported are supported reasonably well by available data and that we are optimistic about the value both now and in the future of optimal foraging theory. We argue, however, that these simple models will requre much modification, espicially to deal with situations that either cannot easily be put into one or another of the above four categories or entail currencies more complicated that just energy.

Citation classic - optimal foraging - a selective review of theory and tests

Since the Age of Exploration began, there has been a drastic breaching of biogeographic barriers that previously had isolated the continental biotas for millions of years. We explore the nature of these recent biotic exchanges and their consequences on evolutionary processes. The direct evidence of evolutionary consequences of the biotic rearrangements is of variable quality, but the results of trajectories are becoming clear as the number of studies increases. There are examples of invasive species altering the evolutionary pathway of native species by competitive exclusion, niche displacement, hybridization, introgression, predation, and ultimately extinction. Invaders themselves evolve in response to their interactions with natives, as well as in response to the new abiotic environment. Flexibility in behavior, and mutualistic interactions, can aid in the success of invaders in their new environment.

/pdf/the-evolutionary-impact-of-invasive-species-3jya0wftzs.pdf

The evolutionary impact of invasive species.

Analysis of habitat use based on radio-tagged animals presents difficulties inadequately addressed by current methods. Areas of concern are sampling level, data pooling across individuals, non-independence of habitat proportions, differential habitat use by groups of animals, and arbitrary definition of habitat availability. We advocate proportional habitat use by individual animals as a basis for analysis. Hypothesis testing of such nonstandard multivariate data is done by compositional analysis, which encom- passes all MANOVA/MANCOVA-type linear models. The applications to habitat use range from testing for age class effects or seasonal differences, to examining relationships with food abundance or home range size. We take as an example the comparison of habitat use and availability. The concepts are explained and demonstrated on two data sets, illustrating different methods of treating missing values. We compare utilized with available habitats in two stages, examining home range selection within the overall study area first, then habitat use within the home range. At each stage, assuming that use differs from random, habitats can be ranked according to relative use, and significant between-rank differences located. Compositional analysis is also suited to the analysis of time budgets or diets.

Compositional Analysis of Habitat Use From Animal Radio-Tracking Data

Preface. First Questions: Biological questions. Planning. Training. Basic Equipment: Frequency. Receivers. Receiving antennas. Transmitters. Tag Designs. Tags as Capture Aids. Automated Systems: Satellite Tracking. GPS Tags. Location by Ground-Based Stations. Choosing Location Systems. Data Logging. Making Preparations: Buying Equipment. Software Preparations. Maps and GIS. Making Tags: Tag Components. Tag Construction. Tag Designs. Tag Attachment: Effects on Animals. Minimal Tagging, Soft Tagging. Attachment Techniques. Tag Adjustment and Detachment. Radio Tracking: First Principles. Making a Start. Practice Tracking. Signals from Tagged Animals. Motorised Tracking. Collecting Data: Radio Surveillance. Recording Locations. Accuracy. Survival Data. Continuous Refinement. Behaviour and Home Ranges: Activity and Event Records. Movement Records. Home-Range Analysis. Demography and Interactions: Density Estimations. Survival Analyses. Interaction with Resources. Social Interactions. References. Glossary. Appendix I: Sources of Equipment. Appendix II: Sources of Software. Index.

A manual for wildlife radio tagging

(1) A trained male goshawk was used to arrange attacks on single pigeons and flocks, at brassica feeding sites and elsewhere. Captured pigeons were compared with shot samples from the same sites, using dry weight of the pectoralis minor muscle as an index of condition. Attacks on pigeon flocks at brassica sites were more successful than when the birds were feeding on grasslands and stubbles, possibly because of variation in pigeon condition.

http://www.jstor.org/stable/pdfplus/3793.pdf

Hawks and doves: factors affecting success and selection in goshawk attacks on woodpigeons.

Wildlife radio tagging : equipment, field techniques and data analysis

1. Kernel-density estimation (KDE) is one of the most widely used home-range estimators in ecology. The recommended implementation uses least squares cross-validation (LSCV) to calculate the smoothing factor (h) which has a considerable influence on the home-range estimate. 2. We tested the performance of least squares cross-validated kernel-density estimation (LSCV KDE) using data from global positioning system (GPS)-collared lions subsampled to simulate the effects of hypothetical radio-tracking strategies. 3. LSCV produced variable results and a 7% failure rate for fewer than 100 locations (H = 2069) and a 61% failure rate above 100 points (n = 1220). Patterns of failure and variation were not consistent among lions, reflecting different individual space use patterns. 4. Intensive use of core areas and site fidelity by animals caused LSCV to fail more often than anticipated from studies that used computer-simulated data. 5. LSCV failures at large sample sizes and variation at small sample sizes, limits the applicability of LSCV KDE to fewer situations than the literature suggests, and casts doubts over the method's reliability and comparability as a home-range estimator. © 2005 British Ecological Society.

Are kernels the mustard? Data from global positioning system (GPS) collars suggests problems for kernel home- range analyses with least-squares cross-validation

Robert E. Kenward

Papers

Compositional Analysis of Habitat Use From Animal Radio-Tracking Data

A manual for wildlife radio tagging

Hawks and doves: factors affecting success and selection in goshawk attacks on woodpigeons.

Wildlife radio tagging : equipment, field techniques and data analysis

Are kernels the mustard? Data from global positioning system (GPS) collars suggests problems for kernel home- range analyses with least-squares cross-validation