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

Kernel methods for estimating home range are being used increasingly in wildlife research, but the effect of sample size on their accuracy is not known. We used computer simulations of 10-200 points/ home range and compared accuracy of home range estimates produced by fixed and adaptive kernels with the reference (REF) and least-squares cross-validation (LSCV) methods for determining the amount of smoothing. Simulated home ranges varied from simple to complex shapes created by mixing bivariate normal distributions. We used the size of the 95% home range area and the relative mean squared error of the surface fit to assess the accuracy of the kernel home range estimates. For both measures, the bias and variance approached an asymptote at about 50 observations/home range. The fixed kernel with smoothing selected by LSCV provided the least-biased estimates of the 95% home range area. All kernel methods produced similar surface fit for most simulations, but the fixed kernel with LSCV had the lowest frequency and magnitude of very poor estimates. We reviewed 101 papers published in The Journal of Wildlife Management (JWM) between 1980 and 1997 that estimated animal home ranges. A minority of these papers used nonparametric utilization distribution (UD) estimators, and most did not adequately report sample sizes. We recommend that home range studies using kernel estimates use LSCV to determine the amount of smoothing, obtain a minimum of 30 observations per animal (but preferably >50), and report sample sizes in published results.

Effects of sample size on kernel home range estimates

Long-distance movements of animals are an important driver of population spatial dynamics and determine the extent of overlap with area-focused human activities, such as fishing. Despite global concerns of declining shark populations, a major limitation in assessments of population trends or spatial management options is the lack of information on their long-term migratory behaviour. For a large marine predator, the tiger shark Galeocerdo cuvier, we show from individuals satellitetracked for multiple years (up to 1101 days) that adult males undertake annually repeated, roundtrip migrations of over 7,500 km in the northwest Atlantic. Notably, these migrations occurred between the highly disparate ecosystems of Caribbean coral reef regions in winter and high latitude oceanic areas in summer, with strong, repeated philopatry to specific overwintering insular habitat. Partial migration also occurred, with smaller, immature individuals displaying reduced migration propensity. Foraging may be a putative motivation for these oceanic migrations, with summer behaviour showing higher path tortuosity at the oceanic range extremes. The predictable migratory patterns and use of highly divergent ecosystems shown by male tiger sharks appear broadly similar to migrations seen in birds, reptiles and mammals, and highlight opportunities for dynamic spatial management and conservation measures of highly mobile sharks.

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Repeated, Long-Distance Migrations by a Philopatric Predator Targeting Highly Contrasting Ecosystems

By studying animal movements, researchers can gain insight into many of the ecological characteristics and processes important for understanding population-level dynamics. We developed a Brownian bridge movement model (BBMM) for estimating the expected movement path of an animal, using discrete location data obtained at relatively short time intervals. The BBMM is based on the properties of a conditional random walk between successive pairs of locations, dependent on the time between locations, the distance between locations, and the Brownian motion variance that is related to the animal's mobility. We describe two critical developments that enable widespread use of the BBMM, including a derivation of the model when location data are measured with error and a maximum likelihood approach for estimating the Brownian motion variance. After the BBMM is fitted to location data, an estimate of the animal's probability of occurrence can be generated for an area during the time of observation. To illustrate potential applications, we provide three examples: estimating animal home ranges, estimating animal migration routes, and evaluating the influence of fine-scale resource selection on animal movement patterns.

https://www.webpages.uidaho.edu/population_ecology/Horne,%20Garton,%20Krone%20&%20Lewis%202007%20Ecology%20-%20BrownianBridge.pdf

Analyzing animal movements using Brownian bridges.

1. Although the home range is a fundamental ecological concept, there is considerable debate over how it is best measured. There is a substantial literature concerning the precision and accuracy of all commonly used home range estimation methods; however, there has been considerably less work concerning how estimates vary with sampling regime, and how this affects statistical inferences. 2. We propose a new procedure, based on a variance components analysis using generalized mixed effects models to examine how estimates vary with sampling regime. 3. To demonstrate the method we analyse data from one study of 32 individually marked roe deer and another study of 21 individually marked kestrels. We subsampled these data to simulate increasingly less intense sampling regimes, and compared the performance of two kernel density estimation (KDE) methods, of the minimum convex polygon (MCP) and of the bivariate ellipse methods. 4. Variation between individuals and study areas contributed most to the total variance in home range size. Contrary to recent concerns over reliability, both KDE methods were remarkably efficient, robust and unbiased: 10 fixes per month, if collected over a standardized number of days, were sufficient for accurate estimates of home range size. However, the commonly used 95% isopleth should be avoided; we recommend using isopleths between 90 and 50%. 5. Using the same number of fixes does not guarantee unbiased home range estimates: statistical inferences differ with the number of days sampled, even if using KDE methods. 6. The MCP method was highly inefficient and results were subject to considerable and unpredictable biases. The bivariate ellipse was not the most reliable method at low sample sizes. 7. We conclude that effort should be directed at marking more individuals monitored over long periods at the expense of the sampling rate per individual. Statistical results are reliable only if the whole sampling regime is standardized. We derive practical guidelines for field studies and data analysis.

https://besjournals.onlinelibrary.wiley.com/doi/epdf/10.1111/j.1365-2656.2006.01164.x

Effects of sampling regime on the mean and variance of home range size estimates

Ninety-three papers on home-range analysis using radio-tracking data were reviewed; these papers were found in a literature search of 18 of the major journals likely to include such papers, published in the 5-year period to the end of 1988. The review showed that even 25 years after the first radio-tracking studies, in the majority of papers there was still insufficient attention given to accurate and sufficient data collection, and to using appropriate and sophisticated analytical techniques to assess home-range size and configuration. This paper is designed to help people undertaking a radio-tracking study to avoid some of the most common pitfalls. It is based on some of the problems we have experienced studying several species of larger mammals. We use our collective experience to produce a guide on how to plan a radio-tracking study, to highlight some of the potential problems in designing the study and collecting the data, and to identify some of the difficulties that may be encountered during the analytical stages. The advantages and disadvantages of the most frequently used methods of home-range analysis are discussed and methods for determining the minimum number of radio-fixes and techniques for adjusting inadequate sample sizes are described, as are the problems that may be caused by autocorrelated data.

Home‐range analysis using radio‐tracking data–a review of problems and techniques particularly as applied to the study of mammals

Wildlife telemetry - remote monitoring and tracking of animals

Over the last few decades, there have been significant declines in Brown Hare Lepus europaeus numbers throughout Europe, leading to concern for their status in many countries. In Britain, there were no quantified data on the extent of this decline, on current population levels, or any baseline against which to monitor future population changes. The need for a quantified national hare survey led to this evaluation of the techniques available to assess hare numbers. Published information on counting hares is reviewed, and various techniques compared by applying them to a number of sites in southern England.



Three basic approaches are available: counts of inactive hares, counts of active hares and indirect methods. Counts of inactive hares include total clearance, wide belt and line transect counts. Total clearance counts give an absolute figure, but are labour intensive and can only be applied to restricted areas. Wide-belt assessments are difficult to apply in certain habitats and even in open areas tend to produce a substantial over-estimate. Line transect counts are easy to undertake and are not labour intensive but should only be applied to large areas, or data from several small areas combined. Counts based on active hares are more problematical, because it is difficult to determine what proportion of the population is inactive at any one time. Spotlight counts based on variable circular plots are the most accurate but difficult to apply widely, and twilight counts are very subjective in their interpretation, especially when surveying small areas or areas with a large proportion of concealing habitats. Of the indirect methods, dung pellet counts can be valuable in specific areas but are difficult to apply across a range of habitats.



We concluded that, of the various techniques considered, line transect counts have the greatest potential for a national survey, but need to be stratified so that enough transects are undertaken within each habitat stratum to obtain a reliable mean population estimate for each stratum.

Techniques for assessing the abundance of brown hares Lepus europaeus

What, if anything, is a core area? An analysis of the problems of describing internal range configurations

Summary - Biodiversity is declining and that decline must be addressed urgently - The UK is among the countries that have seen the greatest decline - Sustainability is about more than carbon and net zero - Business needs a good structure of legislation, policy and regulation within which to operate - It is important to view everything in terms of how the activity affects the natural environment.

S. Wray

Papers

Home‐range analysis using radio‐tracking data–a review of problems and techniques particularly as applied to the study of mammals

Wildlife telemetry - remote monitoring and tracking of animals

Techniques for assessing the abundance of brown hares Lepus europaeus

What, if anything, is a core area? An analysis of the problems of describing internal range configurations

Rethinking the way society operates