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81 results for “Behavioral strategies”
Data from: "Landscape context and behavioral clustering contribute to flexible habitat selection strategies in a large mammal"
<p>Processed datasets used for analysis in "Landscape context and behavioral clustering contribute to flexible habitat selection strategies in a large mammal" by Hooven et al. published in <em>Mammal Research</em>. R scripts used to process and analyze these data are available from: <a href="https://github.com/nhooven/elk-individual-habitat">https://github.com/nhooven/elk-individual-habitat</a></p> <p>WS_sampled.csv, SU_sampled.csv, UA_sampled.csv, AW_sampled.csv - Processed telemetry datasets (with relocation data removed), resultant files from script "01 - Pre-processing.R".</p> <p>WS_HRs.csv, SU_HRs.csv, UA_HRs.csv, AW_HRs.csv - Home range areas (derived from autocorrelated kernel density estimators) and associated variables, by individual. </p> <p>WS_groups.csv, UA_groups.csv, AW_groups.csv - Home range areas (derived from autocorrelated kernel density estimators) and associated variables, by groups. </p> <p>Note: Raw telemetry data and home range polygons are not available due to the sensitive nature of providing animal locations publicly. Please direct any questions or concerns to the corresponding author (nathan.d.hooven@gmail.com). </p>
Data and Analysis Scripts for "Drift in Individual Behavioral Phenotype as a Strategy for Unpredictable Worlds"
<p>This document contains the raw data and analysis scripts for the paper "Drift in Individual Behavioral Phenotype as a Strategy for Unpredictable Worlds", including <em>Drosophila melanogaster</em> circling and handedness behavior at multiple timepoints and across genotypes and experimental conditions manipulating serotonin. It also contains code used to run ecological simulations in the paper and the results of those simulations, as well as code to generate figures for the paper.</p>
Behavioral strategies and the spatial pattern formation of nesting
<p>This dataset contains data from a combined field and simulation study regarding spatial pattern formation of nesting, described in the paper: "Batsleer, F., Maes, D., Bonte, D. (2021) Behavioral strategies and the spatial pattern formation of nesting. The American Naturalist".</p> <p>The study investigates the relative importance of environmental and behavioral mechanisms in nest aggregations of the ground-nesting digger wasp <em>Bembix rostrata</em>. A field study was combined with an individual-based model that simulated the possible behaviors of spatial organisation of nesting.</p> <p>In the first analysis, a microhabitat model was built based on the location of the nests from a capture-mark-recapture study (CMR) and environmental variables NDVI (vegetation) and insolation (sun irradiance), derived from detailed remote sensing data from a drone flight.</p> <p>In the second analysis, an IBM was built that combined three possible mechanisms of nest choice to simulate the emerging spatial and network patterns found in the field. This was done by combining an environmental cue (based on the microhabitat model) and two relevant behavioral mechanisms related to local site fidelity and conspecific attraction. Strengths and combinations of the mechanisms could vary. Simulations were compared to the field data to find which combinations and strengths of mechanisms can best explain the emerging spatial and network patterns.</p> <p>The main results are that 1) the observed pattern in nature is best predicted by the simultaneous effect of a weak environmental cue and strong behavioral mechanisms. 2) individuals differ in their combination of mechanisms used and will either use local site fidelity (personal information) or conspecific attraction (inadvertent social information), but not both simultaneously. 3) We demonstrate that the nest pattern formation of a central place foraging insect cannot be considered as the sum of environmental and behavioral mechanisms.</p>
Behavioral strategies and the spatial pattern formation of nesting
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Data from: Variation in season length and development time is sufficient to drive the emergence and coexistence of social and solitary behavioral strategies
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Data from: The influence of wind selectivity on migratory behavioral strategies
Air and water currents affect the timing and energy expenditure of many migratory animals, and therefore selection of favorable currents is important for optimal migratory performance. However, waiting for favorable currents also incurs costs. Here we conduct an optimality analysis to determine how wind selectivity affects three migratory currencies: time, energy, and risk. To describe variation in these metrics under varying degrees of selectivity, we constructed an individual-based model to simulate fall migration of passerines across eastern North America, allowing birds to use different thresholds of wind profit as the criterion for daily departure. A gradient of thresholds were tested across a range of realistic wind currents, from initiating flights only on nights when winds were directed in their preferred migratory direction (highly selective), to flying under most wind conditions (low selectivity). Our analysis indicated that relative mortality risk was lowest at intermediate selectivity; energy expended during flight was least for the most selective individuals; and of those that successfully completed migration, time spent on migration was lowest for the least selective birds. We solved for the optimal range of wind selectivity and show that this departure criterion alone can produce a tradeoff between time and energy that has been seen in many other behavioral contexts. While we solved for optima using some conditions specific to eastern North America, we show that variation in wind selectivity at departure can produce migratory behaviors that mimic the classic "time-minimizer" and "energy-minimizer" strategies developed from measurements of wild birds across multiple continents.
Short-finned pilot whales exhibit behavioral plasticity in foraging strategies mediated by their environment
<p>Predators adapt their foraging behavior to exploit a variety of prey in a range of environments. Short-finned pilot whales are wide-ranging predators in tropical and sub-tropical oceans, but most previous studies of their foraging ecology have been conducted near oceanic islands. We deployed sound and movement recording tags on 43 short-finned pilot whales off Cape Hatteras, North Carolina, USA, to measure their foraging behavior in a continental shelf-break ecosystem and investigate how variation in the environment shapes their behavior. Overall, the foraging behavior of pilot whales off Cape Hatteras was similar to that of their counterparts from island-associated habitats. Off Cape Hatteras, pilot whales made foraging dives as deep as 1077 m (mean: 445 m), lasting up to 23 min (mean: 12.8 min), with sprints (pursuit at speeds over 3 m/s and up to 6.9 m/s) in more than half of foraging dives. However, tagged whales off Cape Hatteras produced higher buzz rates (11.3 buzzes/dive), foraged more extensively in daytime hours, and engaged in more frequent benthic foraging than island-associated ecotypes. By parsing the echoic scene generated by the animal's own echolocation clicks, we show that pilot whales off Cape Hatteras frequently exploit bathymetric features for foraging, with benthic dives resulting in higher prey capture attempts than pelagic dives. The ability of these predators to strategically adapt foraging strategies to local habitat features likely contributes to their ecological success and may allow them to adjust to shifts in prey distributions in a rapidly changing Anthropocene ocean.</p>
Head-motion and eye-gaze behavior reveal audio-visual target search strategies - dataset
<p>Participants were tasked with finding a target stimulus in the presence of a number of auditory distractors. </p> <p>The target stimulus (audio-only, audio-visual or visual-only) was presented at the central position for 3 seconds, after which the stimulus was moved to one of 24 positions around the participant. The other 23 positions all contained a visual distractor and 0, 1, 2, 3, 5, 7 or 11 auditory distractors (evenly spaced). </p> <p>Based on the eye and headtracking data, we calculated the FOV and target localization time and the maximum headrotation into the wrong direction. </p> <p>FOV localization time: time it took to bring target within FOV. <br>Target localization time: From FOV to response.</p> <p>These datasets contain both the tracking data and the summarized data. </p> <p>Columns "av_stim_x_y" list for each of the 24 AV stimuli (which both served as the targets and distractors), the id, the angle at which it was present during the trial and the visual and audio status.</p> <p>FUNDING: </p> <p>The research was supported by the Centre for Applied Hearing<br>research (CAHR) through a research consortium agreement with<br>GN Resound, Oticon, and Widex. The funders had no role in<br>study design, data collection and analysis, decision to publish, or<br>preparation of the article.</p>
Publication data of Examining holistic processing strategies in dogs and humans through gaze behavior
<p>This version, compared to the version 1, further includes the figures and tables used in the publication. </p> <p>There is an error in the Table 3 file uploaded. The locations of the column names 'else upper half' and 'else lower half' or the images in the two column cells are switched.</p> <p>Please check the Figure 4 of PloS one version of the paper for correct information. <a href="https://doi.org/10.1371/journal.pone.0317455">https://doi.org/10.1371/journal.pone.0317455</a></p> <p> </p> <p>bioRXiv version: Data of Holistic Processing Strategy in Cross-Species Face Perception between Dogs and Humans </p> <p><a href="https://doi.org/10.1101/2024.06.21.599532">https://doi.org/10.1101/2024.06.21.599532</a></p> <p>&</p> <p>PloS one version: Data of Examining holistic processing strategies in dogs and humans through gaze behavior </p> <p><a href="https://doi.org/10.1371/journal.pone.0317455">https://doi.org/10.1371/journal.pone.0317455</a></p>
Nonaggressive behavior: A strategy employed by an obligate nest invader to avoid conflict with its host species
<p>In addition to its builders, termite nests are known to house a variety of secondary opportunistic termite species so‐called inquilines, but little is known about the mechanisms governing the maintenance of these symbioses. In a single nest, host and inquiline colonies are likely to engage in conflict due to nestmate discrimination, and an intriguing question is how both species cope with each other in the long term. Evasive behaviour has been suggested as one of the mechanisms reducing the frequency of host‐inquiline encounters, yet, the confinement imposed by the nests' physical boundaries suggests that cohabiting species would eventually come across each other. Under these circumstances, it is plausible that inquilines would be required to behave accordingly to secure their housing. Here, we show that once inevitably exposed to hosts individuals, inquilines exhibit nonthreatening behaviours, displaying hence a less threatening profile and preventing conflict escalation with their hosts. By exploring the behavioural dynamics of the encounter between both cohabitants, we find empirical evidence for a lack of aggressiveness by inquilines towards their hosts. Such a nonaggressive behaviour, somewhat uncommon among termites, is characterised by evasive manoeuvres that include reversing direction, bypassing and a defensive mechanism using defecation to repel the host. The behavioural adaptations we describe may play an important role in the stability of cohabitations between host and inquiline termite species: by preventing conflict escalation, inquilines may improve considerably their chances of establishing a stable cohabitation with their hosts.</p>
A Hybrid Type 2 Trial of Trauma-Focused Cognitive Behavioral Therapy and a Pragmatic Individual-Level Implementation Strategy
ClinicalTrials.gov study NCT04451161. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Behavioral Economic Strategies to Improve PRO Adherence
ClinicalTrials.gov study NCT06013176. IPD Sharing: NO. Countries: 1. Publications: 2.
Rapid Evaluation of Innovative Intervention Components to Maximize the Health Benefits of Behavioral Obesity Treatment Delivered Online: An Application of Multiphase Optimization Strategy
ClinicalTrials.gov study NCT04520256. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Sativex and Behavioral-relapse Prevention Strategy in Cannabis Dependence
ClinicalTrials.gov study NCT01747850. IPD Sharing: NO. Countries: 1. Publications: 1.
Impact of Behavioral Economic Strategies on Low-Income Older Adults' Food Choices in Online Retail Settings
ClinicalTrials.gov study NCT04766034. IPD Sharing: YES. Countries: 1. Publications: 1.
Testing Multiple Behavioral Science Strategies to Increase Flu-Shot Rates
ClinicalTrials.gov study NCT04565353. IPD Sharing: YES. Countries: 1. Publications: 5.
Implementation Strategy Resource Package for Behavioral Classroom Interventions: Pilot Test
ClinicalTrials.gov study NCT05489081. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Gait Training Combined With Behavioral Strategies for People With Stroke
ClinicalTrials.gov study NCT04546217. IPD Sharing: NO. Countries: 1. Publications: 15.
Data from: The influence of wind selectivity on migratory behavioral strategies
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Asymmetries-induced nonlinear dynamic behaviors enable a versatile modulation strategy for insect-scale robotics
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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.