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40 results for “foraging decisions”
EJR01 Foraging decisions underlying restricted space-use: effects of fire and forage maturation on large herbivore nutrient uptake on Konza Prairie
Recent models suggest that herbivores optimize nutrient intake by selecting patches of low to intermediate vegetation biomass. We assessed the application of this hypothesis to plains bison (Bison bison) in an experimental grassland managed with fire by estimating daily rates of nutrient intake in relation to grass biomass and by measuring patch selection in experimental watersheds in which grass biomass was manipulated by prescribed burning. Digestible crude protein content of grass declined linearly with increasing biomass, and the mean digestible protein content relative to grass biomass was greater in burned watersheds than watersheds not burned that spring (intercept; F1,251 = 50.57, P < 0.0001). Linking these values to published functional response parameters, ad libitum protein intake, and protein expenditure parameters, Fryxell's (Am. Nat., 1991, 138, 478) model predicted that the daily rate of protein intake should be highest when bison feed in grasslands with 400 - 600 kg/ha. In burned grassland sites, where bison spend most of their time, availability of grass biomass ranged between 40 and 3650 kg/ha, bison selected foraging areas of roughly 690 kg/ha, close to the value for protein intake maximization predicted by the model. The seasonal net protein intake predicted for large grazers in this study suggest feeding in burned grassland can be more beneficial for nutrient uptake relative to unburned grassland as long as grass regrowth is possible. Foraging site selection for grass patches of low to intermediate biomass help explain patterns of uniform space use reported previously for large grazers in fire-prone systems. This data set was used to test the forage maturation hypothesis in the Konza Prairie bison enclosure from 2012-2013. Our objectives were to quantify foraging site selection of Plains bison in order to determine if bison in a fire-prone grassland selected sites of low-to-intermediate forage biomass as posited by Fryxell’s (1991) forage mat
Inference based decisions in a hidden state foraging task: differential contributions of prefrontal cortical areas
<p>Tabular dataset of behavioral data in the hidden state foraging task. The data is stored as a unique table, with one row per "attempt", i.e. a poke for mice and a tap for humans.</p> <p>The table includes four distinct experiments, encoded in the Experiment column. Experiment "Learning" refers to Fig. 2, experiment "VaryingParameters" refers to Fig. 2h and Fig.3. Experiment "LearningAndVaryingParameters" refers to Fig. 4. Experiment "OptogeneticInactivation" refers to Fig. 5.</p> <p>The column "TestingSession" defines whether those sessions were used for the analysis. It is used to exclude adaptation sessions to a new protocol for rodents in the "VaryingParameters" and "OptogeneticInactivation" experiments.</p> <p>In the human case, after an incorrect transition the subject receives an error cue and does not tap. This is considered a "trial" (and also a "streak") but not an attempt. This causes the StreakNumber and PokeNumber columns to increase by 2 after an error cue.</p>
Altitudinal differences in foraging decisions under predation risk in great tits
<p>Foraging decisions under risk of predation are crucial for survival as predation risk can contribute to a reduction of food intake over time leading to a trade-off between starvation and predation. Environmental variation can provoke changes in food accessibility or predation risk that will in turn affect foraging decisions. Specifically, less predictable or harsher environments, such as those found at high elevation, should lead to more risk-prone foraging in order to prevent risk of starvation, but empirical confirmation of this hypothesis is lacking. In the current study, we used video playbacks combined with an automatic feeder to measure continuous foraging choices between control and predator videos by wild great tits originating from high and low elevations and tested under controlled conditions. Great tits discriminated between two conditions representing differences in predation risk and visited the feeder less frequently when a predator was shown. Moreover, we found that birds from low elevation populations were more risk-averse and visited the feeder significantly less when a predator video playback was broadcasted compared to high elevation individuals. This elevation related contrast was also dependent on the season, body mass and fat reserves of individuals, and was more marked in females. Furthermore, adults visited the feeder less in the presence of a predator compared to yearlings. These results are consistent with predictions from life history theory and starvation-predation trade-off hypotheses and could have implications for individual movements and population dynamics in changing environments.</p>
Fig. 2 in Hierarchical establishment of information sources during foraging decision-making process involving Acromyrmex subterraneus (Forel, 1893) (Hymenoptera, Formicidae)
Fig. 2. Decision time (s) spent by the A. subterraneus target worker according to number of trips (n) made by the respective target worker and the concentration of pheromone manipulated on the branch that does not lead to the food, estimated by total flow of foragers.
Fig. 1. Y in Hierarchical establishment of information sources during foraging decision-making process involving Acromyrmex subterraneus (Forel, 1893) (Hymenoptera, Formicidae)
Fig. 1. Y-trail system with branches of equal length (225 mm). Branches arranged at an angle of 60◦ connected to a bifurcation. Decision lines (LD) established at fixed points 140 mm far from the bifurcation center on the right and left branches, and 25 mm from the base branch to calculate the A. subterraneus workers' frequency of passage when half of their bodies had crossed each LD.
Altitudinal differences in foraging decisions under predation risk in great tits
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Data from: Statistically testing the role of individual learning and decision-making in trapline foraging
Trapline foraging, a behavior consisting of repeated visitation to spatially fixed resources in a predictable sequence, has been observed over diverse taxa and is important ecologically for efficient resource gathering. Despite this, few null models exist to test the significance of suspected traplines, particularly for studies interested in the role of individual decision-making in the formation of traplines versus the role of resource layouts and random movement patterns. Here we present a spatially explicit, individual-based null model, which may be used to test whether resource layout and realistic forager movement may account for sequence repeats in suspected traplines. In our model, we generate resource visitation sequences by modeling a forager without spatial memory using a random walk to discover and visit spatially-fixed resources. We quantify traplining using Determinism, a metric derived from recurrence quantification analysis. Using both simulated and empirical bee foraging data, we compared our model with two existing null models—a completely random model and a sample randomization model. The former creates null sequences by randomly selecting available resources, while the latter randomizes the order of visits in observed sequences. We found that our model has a higher propensity of being (correctly) rejected than a sample randomization model for trapliners, and a lower propensity of being (incorrectly) rejected for non-trapliners compared to a completely random model. The use of a spatially explicit individual-based null model to test the statistical significance of patterns in empirical data is a novel approach that may be useful for other spatial and individual-based processes.
The effect of competitor presence on the foraging decisions of small mammals
<p>Competitive interactions between species can have marked effects on the diets and foraging behaviours of the interactants. Dominant competitors may constrain the foraging decisions of subordinate competitors, reducing the individual fitness of subordinates, and potentially driving their populations to low levels. Following a sustained population decline of the bush rat (<em>Rattus fuscipes</em>) in the presence of the competitively dominant common brushtail possum (<em>Trichosurus vulpecula</em>) at Booderee National Park in south-eastern Australia, we investigated whether possums affected the foraging decisions of bush rats. Using a modified giving-up density experiment, we predicted that bush rats would: (a) increase visits to baited sites where possums had restricted access, and (b) restrict visits to baited sites where possums had free access. We used camera traps to investigate visitation patterns and foraging bout lengths at 40 baited sites with two treatments, one that allowed full access by both species (full access), and the other that attempted to prevent possum access (restricted access). We also measured additional covariate factors that may influence visitation. Bush rats visited both treatments less when there were more possum visits. We also found that bush rats spent less time eating bait at regularly visited sites, regardless of possums' access level. Our results suggest a negative, potentially competitive interaction between the two species that is detrimental to bush rat foraging and is a potential factor contributing to bush rat's decline at Booderee National Park.</p>
Social interactions differ in their impact on foraging decisions
<p>Data and code for the manuscript: Social interactions differ in their impact on foraging decisions</p>
Sensory neurons couple arousal and foraging decisions in C. elegans
<p>Foraging animals optimize feeding decisions by adjusting both common and rare behavioral patterns. Here, we characterize the relationship between an animal's arousal state and a rare decision to leave a patch of bacterial food. Using long-term tracking and behavioral state classification, we find that food leaving decisions in <em>C. elegans</em> are coupled to arousal states across multiple timescales. Leaving emerges probabilistically over minutes from the high arousal roaming state, but is suppressed during the low arousal dwelling state. Immediately before leaving, animals have a brief acceleration in speed that appears as a characteristic signature of this behavioral motif. Neuromodulatory mutants and optogenetic manipulations that increase roaming have a coupled increase in leaving rates, and similarly acute manipulations that inhibit feeding induce both roaming and leaving. By contrast, inactivating a set of chemosensory neurons that depend on the cGMP-gated transduction channel TAX-4 uncouples roaming and leaving dynamics. In addition, <em>tax-4-</em>expressing sensory neurons promote lawn-leaving behaviors that are elicited by feeding inhibition. Our results indicate that sensory neurons responsive to both internal and external cues play an integrative role in arousal and foraging decisions.</p>
Data from: Interannual variation in foraging decisions in chick-rearing black-legged kittiwakes
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Sensory neurons couple arousal and foraging decisions in C. elegans
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The effect of competitor presence on the foraging decisions of small mammals
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Local dominance predicts foraging decisions in a changing environment
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Data from: Statistically testing the role of individual learning and decision-making in trapline foraging
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Data from: Moving on with foraging theory: incorporating movement decisions into the functional response of a gregarious shorebird
1. Models relating intake rate to food abundance and competitor densities (generalized functional response models) can predict forager distributions and movements between patches, but we lack understanding of how distributions and small-scale movements by the foragers themselves affect intake rates. 2. Using a state-of-the-art approach based on continuous-time Markov chain dynamics, we add realism to classic functional response models by acknowledging that the chances to encounter food and competitors are influenced by movement decisions, and, vice versa, that movement decisions are influenced by these encounters. 3. We used a multi-state modelling framework to construct a stochastic functional response model in which foragers alternate between three behavioural states: searching, handling and moving. 4. Using behavioural observations on a molluscivore migrant shorebird (red knot, Calidris canutus canutus), at its main wintering area (Banc d'Arguin, Mauritania), we estimated transition rates between foraging states as a function of conspecific densities and densities of the two main bivalve prey. 5. Intake rate decreased with conspecific density. This interference effect was not due to decreased searching efficiency, but resulted from time lost to avoidance movements. 6. Red knots showed a strong functional response to one prey (Dosinia isocardia), but a weak response to the other prey (Loripes lucinalis). This corroborates predictions from a recently developed optimal diet model that accounts for the mildly toxic effects due to consuming Loripes. 7. Using model-averaging across the most plausible multi-state models, the fully parameterized functional response model was then used to predict intake rate for an independent dataset on habitat choice by red knot. 8. Comparison of the sites selected by red knots with random sampling sites showed that the birds fed at sites with higher than average Loripes and Dosinia densities, i.e. sites for which we predicted higher than average intake rates. 9. We discuss the limitations of Holling's classical functional response model that ignores movement and the limitations of contemporary movement ecological theory ignoring consumer-resource interactions. With the rapid advancement of technologies to track movements of individual foragers at fine spatial scales, the time seems ripe to integrate descriptive tracking studies with stochastic movement-based functional response models.
Data from: Predation risk perception, food density and conspecific cues shape foraging decisions in a tropical lizard
When foraging, animals can maximize their fitness if they are able to tailor their foraging decisions to current environmental conditions. When making foraging decisions, individuals need to assess the benefits of foraging while accounting for the potential risks of being captured by a predator. However, whether and how different factors interact to shape these decisions is not yet well understood, especially in individual foragers. Here we present a standardized set of manipulative field experiments in the form of foraging assays in the tropical lizard Anolis cristatellus in Puerto Rico. We presented male lizards with foraging opportunities to test how the presence of conspecifics, predation-risk perception, the abundance of food, and interactions among these factors determines the outcome of foraging decisions. In Experiment 1, anoles foraged faster when food was scarce and other conspecifics were present near the feeding tray, while they took longer to feed when food was abundant and when no conspecifics were present. These results suggest that foraging decisions in anoles are the result of a complex process in which individuals assess predation risk by using information from conspecific individuals while taking into account food abundance. In Experiment 2, a simulated increase in predation risk (i.e., distance to the feeding tray) confirmed the relevance of risk perception by showing that the use of available perches is strongly correlated with the latency to feed. We found Puerto Rican crested anoles integrate instantaneous ecological information about food abundance, conspecific activity and predation risk, and adjust their foraging behavior accordingly.
Data from: Exploring foraging decisions in a social primate using discrete choice models
There is a growing appreciation of the multiple social and nonsocial factors influencing the foraging behavior of social animals, but little understanding of how these factors depend on habitat characteristics or individual traits. This partly reflects the difficulties inherent in using conventional statistical techniques to analyze multi-factor, multi-context foraging decisions. Discrete choice models provide a way to do so, and we demonstrate this by using them to investigate patch preference in a wild population of social foragers (chacma baboons, Papio ursinus). Data were collected from 29 adults across two social groups encompassing 683 foraging decisions over a six-month period, and the results interpreted using an information theoretic approach. Baboon foraging decisions were influenced by multiple nonsocial and social factors, and were often contingent on the characteristics of the habitat or individual. Differences in decision-making between habitats were consistent with changes in interference competition costs but not changes in social foraging benefits. Individual differences in decision-making were suggestive of a trade-off between dominance rank and social capital. Our findings emphasize that taking a multi-factor, multi-context approach is important to fully understand animal decision-making. We also demonstrate how discrete choice models can be used to achieve this.
Foraging through multiple nest holes: an impediment to collective decision-making in ants
<p>Raw Data: study investigating the impact of nest structure (number of nest entrances) on the ability of ant colonies to collectively exploit food resources and to select the most rewarding food source.</p>
Beaked whales and state-dependent decision-making: how does body condition affect the trade-off between foraging and predator avoidance?
<p>Body condition is central to how animals balance foraging with predator-avoidance – a trade-off that fundamentally affects animal fitness. Animals in poor condition may accept greater predation risk to satisfy current foraging "needs", whilst those in good condition may be more risk averse to protect future "assets". These state-dependent behavioural predictions can help interpret responses to human activities, but are little explored in marine animals. This study investigates the influence of body condition on how beaked whales trade off foraging and predator-avoidance. Body density (indicating lipid-energy stores) was estimated for 15 foraging northern bottlenose whales tagged near Jan Mayen, Norway. Composite indices of foraging (diving and echolocation clicks) and anti-predation (long ascents, non-foraging dives and silent periods reducing predator eavesdropping) were negatively related. Experimental sonar exposures led to decreased foraging and increased risk aversion, confirming a foraging/perceived safety trade-off. However, lower lipid stores were not related to a decrease in predator-avoidance versus foraging, i.e. worse condition animals did not prioritise foraging. Individual differences ('personalities') or reproductive context could offer alternative explanations for the observed state-behaviour relationships. This study provides evidence of foraging/predator-avoidance trade-offs in a marine top predator and demonstrates that animals in worse condition might not always take more risks.</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.