Predicting Spatial Distribution of Foragers over Large Resource Landscapes: A Modeling Analysis of the Ideal Free Distribution

Tyler, Jeffrey A.; Hargrove, William W.

doi:10.2307/3546022

Cited by 48 publications

(61 citation statements)

References 64 publications

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“…To summarize the relative effects of experimental factors on the bias and imprecision, we conducted an analysis of variance (ANOVA) on the bias or the imprecision of each replication and viewed the four factors in our simulation design as treatments (n site , n visit , l r , l b 0 ), with all interactions included. Following White et al (2014), we evaluated sums of squares (SS) and mean SS rather than the statistical significance of the ANOVA to assess the importance of the effects (Tyler and Hargrove 1997;Fahrig 2001;Fletcher 2006).…”

Section: Submodel Of the Detection Processmentioning

confidence: 99%

Study of biological communities subject to imperfect detection: bias and precision of communityN‐mixture abundance models in small‐sample situations

Yamaura

Kéry

Royle

2016

Ecological Research

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Community N-mixture abundance models for replicated counts provide a powerful and novel framework for drawing inferences related to species abundance within communities subject to imperfect detection. To assess the performance of these models, and to compare them to related community occupancy models in situations with marginal information, we used simulation to examine the effects of mean abundance ð k: 0.1, 0.5, 1, 5), detection probability ðp: 0.1, 0.2, 0.5), and number of sampling sites (n site : 10, 20, 40) and visits (n visit : 2, 3, 4) on the bias and precision of species-level parameters (mean abundance and covariate effect) and a community-level parameter (species richness). Bias and imprecision of estimates decreased when any of the four variables ð k, p, n site , n visit ) increased. Detection probability p was most important for the estimates of mean abundance, while k was most influential for covariate effect and species richness estimates. For all parameters, increasing n site was more beneficial than increasing n visit . Minimal conditions for obtaining adequate performance of community abundance models were n site ‡ 20, p ‡ 0.2, and k ‡ 0.5. At lower abundance, the performance of community abundance and community occupancy models as species richness estimators were comparable. We then used additive partitioning analysis to reveal that raw species counts can overestimate b diversity both of species richness and the Shannon index, while community abundance models yielded better estimates. Community N-mixture abundance models thus have great potential for use with community ecology or conservation applications provided that replicated counts are available.

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Section: Submodel Of the Detection Processmentioning

confidence: 99%

Study of biological communities subject to imperfect detection: bias and precision of communityN‐mixture abundance models in small‐sample situations

Yamaura

Kéry

Royle

2016

Ecological Research

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“…However, the results of such a smaller-scale study would have limited power as the conclusions would only be applicable to a very restricted area. To date, it is unclear at what scale the mechanisms of habitat selection operate (Tyler and Hargrove, 1997). This demonstrates one of the inherent difficulties in the identification of essential fish habitats and habitat requirements of fish in the field and needs further scientific attention.…”

Section: Accepted M Manuscriptmentioning

confidence: 99%

Evaluation of habitat use by adult plaice (Pleuronectes platessa L.) using underwater video survey techniques

Shucksmith

Hinz

Bergmann

et al. 2006

Journal of Sea Research

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Large-scale spatial surveys of fish species in relation to habitat have tended to focus on depth, sediment type and temperature as descriptors of fish habitats. At a smaller scale, habitat parameters such as the relief of the sea floor, the presence of structuring fauna and prey availability may have a large influence on fish distribution, but often are not considered. In the present study we used video survey techniques to study habitat components in areas of the English Channel that were known to support consistently high densities of adult plaice. Habitat features were quantified and related to the density of adult plaice caught within the same study areas. To focus the study on habitat components other than sediment type all sites chosen had sandy substrata. The scale and spatial distribution and heterogeneity of physical and biological structures were quantified for each site and correlated to plaice densities. Plaice densities correlated with the abundance of benthic fauna recorded. In particular the emergent tube-dwelling polychaetes Lanice conchilega and Cheatopterus spp., which are a valuable food source for plaice, dominated some sites. Abiotic habitat features and habitat heterogeneity showed no clear relationships with respect to plaice densities at the scale of our surveys. This indicated that prey availability might be the driving force for habitat selection of adult plaice within sandy habitats and that other habitat descriptors assume less importance at smaller spatial scales.

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“…Mechanistic optimal foraging models of large herbivores have been applied to understand the determinants of aggregation (Fryxell 1991) and to predict habitat selection (Wilmshurst et al 1999(Wilmshurst et al , 2000. Models based on the ideal free distribution, IFD (see Fretwell andLucas 1970, Fretwell 1972), however, have not been successful at predicting animal distributions (Kennedy and Gray 1993), particularly when applied to large spatial areas (Tyler and Hargrove 1997). This failure may be caused by vio- 3 E-mail: jredfern@nature.berkeley.edu lations of IFD assumptions, specifically that individuals are free to move to any patch and that movement costs are negligible (Kennedy andGray 1993, Tyler andHargrove 1997).…”

Section: Introductionmentioning

confidence: 99%

“…Models based on the ideal free distribution, IFD (see Fretwell andLucas 1970, Fretwell 1972), however, have not been successful at predicting animal distributions (Kennedy and Gray 1993), particularly when applied to large spatial areas (Tyler and Hargrove 1997). This failure may be caused by vio- 3 E-mail: jredfern@nature.berkeley.edu lations of IFD assumptions, specifically that individuals are free to move to any patch and that movement costs are negligible (Kennedy andGray 1993, Tyler andHargrove 1997). Additionally, the utility of many landscape-scale models of herbivore distributions may be limited because they focus primarily on the role of biotic factors.…”

Section: Introductionmentioning

confidence: 99%

Surface-Water Constraints on Herbivore Foraging in the Kruger National Park, South Africa

Redfern

Grant

Biggs

et al. 2003

Ecology

265

249

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Abstract. At a landscape scale, the combined influence of biotic and abiotic factors may determine the distribution patterns of large herbivores in African savanna ecosystems. Herbivores foraging in these ecosystems may become nutritionally stressed during an annual dry season when both forage quality and quantity are reduced. Additionally, the locations of water sources may impose a landscape-scale constraint on dry-season herbivore distributions. We used logistic regression to analyze 13 years of aerial census data collected in the Kruger National Park (KNP), South Africa, and evaluated hypotheses regarding the relative influences that surface water, forage quality, and forage quantity exert on the dryseason, landscape-scale distribution patterns of eight herbivore species. Hypotheses regarding the degree of correlation between species' distributions and distance to water were developed using previous observations of species' relative water dependence. We also developed hypotheses regarding species' responses to the trade-off that may occur between surface-water constraints and nutritional requirements when either forage quality or quantity is reduced. In general, we expect an increase in species' mean distance to water as a result of individuals mitigating limitations in nutritional requirements (i.e., intake quality or quantity) by foraging farther from water. Our analyses suggest that the trade-off between nutritional requirements and surface-water constraints that species face varies according to the species' water dependence, size, and gut morphology. Of the four grazers considered in our analyses, waterbuck distributions appear to be constrained primarily by surfacewater availability. Distributions of buffalo, a large ruminant grazer, suggest that individuals face a trade-off between nutritional requirements and surface-water constraints when forage quantity is reduced. Alternatively, distributions of wildebeest, a smaller ruminant grazer, suggest that individuals face this trade-off when access to high-quality forage is limited. In comparison to buffalo and wildebeest, the strength of this trade-off is moderate for zebra, a nonruminant similar in size to wildebeest, when either forage quality or quantity is reduced. Distribution patterns for browsers are characterized by a weak relationship with distance to water, as expected for these relatively water-independent species. Population densities relative to forage quality confound exploration of this trade-off for mixed feeders.

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Predicting Spatial Distribution of Foragers over Large Resource Landscapes: A Modeling Analysis of the Ideal Free Distribution

Cited by 48 publications

References 64 publications

Study of biological communities subject to imperfect detection: bias and precision of communityN‐mixture abundance models in small‐sample situations

Study of biological communities subject to imperfect detection: bias and precision of communityN‐mixture abundance models in small‐sample situations

Evaluation of habitat use by adult plaice (Pleuronectes platessa L.) using underwater video survey techniques

Surface-Water Constraints on Herbivore Foraging in the Kruger National Park, South Africa

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