A patch use model to separate effects of foraging costs on giving-up densities: an experiment with white-tailed deer (Odocoileus virginianus)

Rieucau, Guillaume; Vickery, William L.; Doucet, G. Jean

doi:10.1007/s00265-009-0732-7

Cited by 22 publications

(42 citation statements)

References 23 publications

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“…This has been empirically demonstrated for wolf (Canis lupus)-moose (Alces alces) (Kunkel and Pletscher 2000) and wolf-elk interactions (Kauffman et al 2007). For the prey, some habitat characteristics, such as openness, can be positive with regard to foraging while negative with regard to predation risk (Brown 1999;Creel et al 2005;Hernández and Laundré 2005;Hebblewhite and Merrill 2009;Rieucau et al 2009). For the predator, the same traits may imply the abundance of prey as well as its low accessibility or catchability (Hopcraft et al 2005).…”

Section: Introductionmentioning

confidence: 99%

A “death trap” in the landscape of fear

Schmidt

Kuijper

2015

Mamm Res

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A crucial element in the Bthe landscape of fearĉ oncept is that prey animals are aware of varying levels of predation risk at a spatial scale. This often leads to a negative spatial relationship between prey and predator in which prey avoid the most risky sites in the landscape. In this paper, we argue that our understanding of large carnivore-ungulate interactions is biased by studies from highly heterogeneous landscapes (e.g. the Yellowstone National Park). Due to a high availability of refuges and foraging sites in such landscapes, prey are able to reduce predation risk by showing habitat shifts. Besides the spatial heterogeneity at the landscape scale, the ungulate response to predation risk can be affected by the hunting mode (stalking vs. cursorial) of the predator. We propose that prey cannot easily avoid predation risk by moving to less risky habitats in more homogenous landscapes with concentrated food resources, especially where the large carnivores' assemblage includes both stalking and cursorial species. No distinct refuges for prey may occur in such landscapes due to equally high accessibility to predators in all habitats, while concentrated resources make prey distribution more predictable. We discuss a model of a densely forested landscape based on a case study of the Białowieża Primeval Forest, Poland. Within this landscape, ungulates focus their foraging activity on small food-rich forest gaps, which turn out to be Bdeath traps^as the gaps are primarily targeted by predators (stalking lynx and cursorial wolf) while hunting. No alternative of moving to low predation risk areas exist for prey due to risk from wolves in surrounding closed-canopy forest. As a result, the prey is exposed to constant high predation pressure in contrast to heterogeneous landscapes with less concentrated resources and more refuge areas. Future research should focus on explaining how ungulates are coping with predation risk in these landscapes that offer little choice of escaping predation by considering behavioural and physiological (e.g. metabolic, hormonal) responses.

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Section: Introductionmentioning

confidence: 99%

A “death trap” in the landscape of fear

Schmidt

Kuijper

2015

Mamm Res

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“…Thus, habitat structure may play an important mediating role in predator-prey interactions either facilitating or hampering both the survival of the prey and the hunting success of the predator. Some habitat characteristics, such as openness, may have opposite effects for the prey, being positive with regard to foraging while negative with regard to predation risk [5–9]. Habitat structure may affect in different ways a recognizable ‘landscape of fear’ for prey species, as animals could alter the use of an area in trying to reduce vulnerability to predation [10].…”

Section: Introductionmentioning

confidence: 99%

The Seagrass Effect Turned Upside Down Changes the Prospective of Sea Urchin Survival and Landscape Implications

et al. 2016

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Habitat structure plays an important mediating role in predator-prey interactions. However the effects are strongly dependent on regional predator pools, which can drive predation risk in habitats with very similar structure in opposite directions. In the Mediterranean Sea predation on juvenile sea urchins is commonly known to be regulated by seagrass structure. In this study we test whether the possibility for juvenile Paracentrotus lividus to be predated changes in relation to the fragmentation of the seagrass Posidonia oceanica (four habitat classes: continuous, low-fragmentation, high-fragmentation and rocks), and to the spatial arrangement of such habitat classes at a landscape scale. Sea urchin predation risk was measured in a 20-day field experiment on tethered individuals placed in three square areas 35×35 m2 in size. Variability of both landscape and habitat structural attributes was assessed at the sampling grain 5×5 m2. Predation risk changed among landscapes, as it was lower where more ‘rocks’, and thus less seagrass, were present. The higher risk was found in the ‘continuous’ P. oceanica rather than in the low-fragmentation, high-fragmentation and rock habitats (p-values = 0.0149, 0.00008, and 0.0001, respectively). Therefore, the expectation that juvenile P. lividus survival would have been higher in the ‘continuous’ seagrass habitat, which would have served as shelter from high fish predation pressure, was not met. Predation risk changed across habitats due to different success between attack types: benthic attacks (mostly from whelks) were overall much more effective than those due to fish activity, the former type being associated with the ‘continuous’ seagrass habitat. Fish predation on juvenile sea urchins on rocks and ‘high-fragmentation’ habitat was less likely than benthic predation in the ‘continuous’ seagrass, with the low seagrass patch complexity increasing benthic activity. Future research should be aimed at investigating, derived from the complex indirect interactions among species, how top-down control in marine reserves can modify seagrass habitat effects.

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“…As two different habitats may also have different predation risk, natural experiments capable of separating both effects at habitat scale may be difficult to design. A method was developed which is capable of separating both effects (Rieucau et al 2009). Using this method, one may test not only hypothesis regarding metabolic costs, but also several hypotheses shown in Formula 6, such as missing opportunity and metabolic costs having an additive effect on predation risk.…”

Section: Predictions and Discussionmentioning

confidence: 99%

“…This relation was reported in the beginning of foraging ecology (Charnov 1976) and has been used in several modern methods (Rieucau et al 2009). In our model, opportunity costs are represented by predation risk, in the missed opportunity cost.…”

Section: Appendixmentioning

confidence: 96%

“…In heterogeneous (nonuniform) predation risk, experimental designs might compare pairs of patches in different habitats (Brown et al 1992b;Orrock and Danielson 2004;Stapp and Lindquist 2007;Rieucau et al 2009), in a way that only predation risk varies between these (Brown 1988). These habitats are chosen with certain types of risk in mind, and the design ensures that other habitat features do not vary; therefore, any other source of risk uncorrelated with the predation risk in focus can be considered uniform across the experiment.…”

Section: Introductionmentioning

confidence: 99%

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Uniform predation risk in nature: common, inconspicuous, and a source of error to predation risk experiments

Menezes

Kotler

Mourão³

2014

Behav Ecol Sociobiol

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Previous studies indicate that when predation risk is uniform across habitats, foragers concentrate their exploitation in fewer patches. Although uniform predation risk may seem rare in nature, some scenarios might cause it. Testing all scenarios in a single experiment is unfeasible; therefore, we developed a model that points whether concentration of exploitation in specific habitats due to uniform risk requires parameter values similar to what is found in literature. This model was based on Brown's (Behav Ecol Sociobiol 22:37-47, 1988) fitness function but rescaled to multiple habitats and predators, including uniform risk predators. Deriving function's maximum allowed comparisons with giving-up density studies. Results showed that uniform predation risk had a ushaped effect in habitat exploitation, causing a concentration of habitat exploitation at probabilities of survival from 0.2 to 0.8. However, the length of this interval and degree of concentration depended on the value of safety to forager fitness. Heterogeneous, nonuniform, predation risk decreases habitat exploitation where it was higher, therefore suppressing the effect of uniform risk on prey behavior. Time spent in the focal habitat and metabolic costs reduced the detectability of habitat concentration, while total time did not. We also found that uniform risk reduced accuracy of heterogeneous risk measurements. Future studies should aim to control all possible predators, as even the mild ones can induce complex behavior.

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A patch use model to separate effects of foraging costs on giving-up densities: an experiment with white-tailed deer (Odocoileus virginianus)

Cited by 22 publications

References 23 publications

A “death trap” in the landscape of fear

A “death trap” in the landscape of fear

The Seagrass Effect Turned Upside Down Changes the Prospective of Sea Urchin Survival and Landscape Implications

Uniform predation risk in nature: common, inconspicuous, and a source of error to predation risk experiments

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