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

Assessing how environmental changes affect the distribution and dynamics of vegetation and animal populations is becoming increasingly important for terrestrial ecologists to enable better predictions of the effects of global warming, biodiversity reduction or habitat degradation. The ability to predict ecological responses has often been hampered by our rather limited understanding of trophic interactions. Indeed, it has proven difficult to discern direct and indirect effects of environmental change on animal populations owing to limited information about vegetation at large temporal and spatial scales. The rapidly increasing use of the Normalized Difference Vegetation Index (NDVI) in ecological studies has recently changed this situation. Here, we review the use of the NDVI in recent ecological studies and outline its possible key role in future research of environmental change in an ecosystem context.

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Using the satellite-derived NDVI to assess ecological responses to environmental change

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

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

There is growing recognition of the important roles played by predators in regulating ecosystems and sustaining biodiversity. Much attention has focused on the consequences of predator-regulation of herbivore populations, and associated trophic cascades. However apex predators may also control smaller 'mesopredators' through intraguild interactions. Removal of apex predators can result in changes to intraguild interactions and outbreaks of mesopredators ('mesopredator release'), leading in turn to increased predation on smaller prey. Here we provide a review and synthesis of studies of predator interactions, mesopredator release and their impacts on biodiversity. Mesopredator suppression by apex predators is widespread geographically and taxonomically. Apex predators suppress mesopredators both by killing them, or instilling fear, which motivates changes in behaviour and habitat use that limit mesopredator distribution and abundance. Changes in the abundance of apex predators may have disproportionate (up to fourfold) effects on mesopredator abundance. Outcomes of interactions between predators may however vary with resource availability, habitat complexity and the complexity of predator communities. There is potential for the restoration of apex predators to have benefits for biodiversity conservation through moderation of the impacts of mesopredators on their prey, but this requires a whole-ecosystem view to avoid unforeseen negative effects. 'Nothing has changed since I began. My eye has permitted no change. I am going to keep things like this.' From 'Hawk Roosting', by Ted Hughes.

https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1461-0248.2009.01347.x

Predator interactions, mesopredator release and biodiversity conservation

The elk or wapiti (Cervus elaphus) and bison (Bison bison) of Yellowstone National Park have lived in an environment free of wolves (Canis lupus) for the last 50 years. In the winter of 1994-1995, wolves were reintroduced into parts of Yellowstone National Park. Foraging theory predicts that elk and bison would respond to this threat by increasing their vigilance levels. We tested this prediction by comparing vigilance levels of elk and bison in areas with wolves with those of elk still in "wolf-free" zones of the Park. Male elk and bison showed no response to the reintroduction of wolves, maintaining the lowest levels of vigilance throughout the study (12 and 7% of the time was spent vigilant, respectively). Female elk and bison showed significantly higher vigilance levels in areas with wolves than in areas without wolves. The highest vigilance level (47.5 ± 4.1%; mean ± SE) was seen by the second year for female elk with calves in the areas with wolves and was maintained during the subsequent 3 years of...

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Wolves, elk, and bison: reestablishing the "landscape of fear" in Yellowstone National Park, U.S.A.

Predation risk\" and \"fear\" are concepts well established in animal behavior literature. We expand these concepts to develop the model of the \"landscape of fear\". The landscape of fear represents relative levels of predation risk as peaks and valleys that reflect the level of fear of predation a prey experiences in different parts of its area of use. We provide observations in support of this model regarding changes in predation risk with respect to habitat types, and terrain characteristics. We postulate that animals have the ability to learn and can respond to differing levels of predation risk. We propose that the landscape of fear can be quantified with the use of well documented existing methods such as giving- up densities, vigilance observations, and foraging surveys of plants. We conclude that the landscape of fear is a useful visual model and has the potential to become a unifying ecological concept.

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The Landscape of Fear: Ecological Implications of Being Afraid~!2009-09-09~!2009-11-16~!2010-02-02~!

We applied optimal foraging theory to test effects of habitat and predation risk on foraging behavior of mule deer (Odocoileus hemionus) subject to predation by mountain lions (Puma concolor). We predicted that deer would spend less time foraging, have higher giving-up densities of food (GUDs), and have higher vigilance behavior when occupying patch edges than when in open and forest interiors. We also measured GUDs in 3 microhabitats within 3 forest types. We used pellet-group surveys to estimate habitat and microhabitat use, and we assessed vigilance behavior with automatic camera systems. The GUDs (perceived predation risk) were greater in forests of Douglas fir (Pseudostuga menziensii) than mountain mahogany (Cercocarpus ledifolius). In forests of Douglas fir, GUDs were greatest in the forest interior, declined at the forest edge, and were lowest in the open microhabitat. Microhabitat features did not influence GUDs in the mountain mahogany forest. Pelletgroup data indicated more activity in the open than in the edge or forest. Based on photographs, deer were more vigilant at forest edges than in open and forest areas. We concluded that deer are responding to predation risk by biasing their feeding efforts at the scale of habitats and microhabitats and altering their habitat-specific patterns of vigilance behavior. words: GUDs, Idaho, mule deer, Odocoileus hemionus, optimal foraging, predation risk

/pdf/assessing-effects-of-predation-risk-on-foraging-behavior-of-rionlomeg6.pdf

Assessing effects of predation risk on foraging behavior of mule deer

Predation risk" and "fear" are concepts well established in animal behavior literature. We expand these concepts to develop the model of the "landscape of fear". The landscape of fear represents relative levels of predation risk as peaks and valleys that reflect the level of fear of predation a prey experiences in different parts of its area of use. We provide observations in support of this model regarding changes in predation risk with respect to habitat types, and terrain characteristics. We postulate that animals have the ability to learn and can respond to differing levels of predation risk. We propose that the landscape of fear can be quantified with the use of well documented existing methods such as giving- up densities, vigilance observations, and foraging surveys of plants. We conclude that the landscape of fear is a useful visual model and has the potential to become a unifying ecological concept.

The Landscape of Fear: Ecological Implications of Being Afraid

In 1995, wolves Canis lupus were reintroduced into Yellowstone National Park, USA, where they began to prey on ungulate species. In response to this new predation risk by wolves, we predicted that the two main ungulate species, elk Cervus elaphus and bison Bison bison, should compensate by reducing their use of riskier open meadows and increasing their use of safer forest. Additionally we predicted that this shift in habitat use would result in reduced diet quality. We tested the first prediction by regressing the number of faecal groups in 10-m2 sampling plots against distance from forest edges. To test the second prediction, we compared percent faecal nitrogen in elk and bison faeces between areas with and without wolves. We found a significant negative relationship between number of elk faecal groups and distance from forest edge in areas with wolves (r2 = 0.65, P = 0.001), but we did not find a relationship between these two factors in areas without wolves. Mean percent faecal nitrogen in elk...

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John W. Laundré

Papers

Wolves, elk, and bison: reestablishing the "landscape of fear" in Yellowstone National Park, U.S.A.

The Landscape of Fear: Ecological Implications of Being Afraid~!2009-09-09~!2009-11-16~!2010-02-02~!

Assessing effects of predation risk on foraging behavior of mule deer

The Landscape of Fear: Ecological Implications of Being Afraid

Foraging in the ‘landscape of fear’ and its implications for habitat use and diet quality of elk Cervus elaphus and bison Bison bison