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182 results for “state dependence”
Data from: Charge state-dependent ion condensation near conjugated polymer backbones
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Data from: Brain-state mediated modulation of inter-laminar dependencies in visual cortex
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Dataset:Female state and condition-dependent chemical signalling revealed by male choice of silk trails
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Sex- and state-dependent covariation of risk-averse and escape behavior in a widespread lizard
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Fish resist temptation from junk food: State-dependent diet choice in reproductive Atlantic cod (Gadus morhua) facing seasonal fluxes of lipid-rich prey
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Data from: Whole-organism behavioral profiling reveals a role for dopamine in state-dependent motor program coupling in C. elegans.
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Datasets used for the publication: State-dependence explains individual variation in nest defence behaviour in a long-lived bird
<p>The uploaded datasets were used to test if variation in states predicts nest defence behaviour (a 'risky' behaviour) in a long-lived species, the barnacle goose (<em>Branta leucopsis</em>). Repeated measures of nest defence towards a human intruder (flight initiation distance or FID) of females of known age were collected during 15 breeding seasons. Increasing values of FID represent increasing shyness. Adaptive models have predicted that an individual's residual reproductive value or 'asset' is an important state variable underlying variation in such risk-taking behaviour. Hence, we used this data to investigate how nest defence varies as a function of time of the season and individual age, two state variables that can vary between and within individuals and determine asset.<br> <br> </p>
Data from: When should I be aggressive? A state-dependent foraging game between competitors
More often than not, animals forage with other foragers present. A foraging game may take place when the outcome of a forager's actions depends on both its own and other foragers' strategies. Previous studies on predator–prey systems have verified that complex state-dependent foraging games exist between predators and prey. In this study, we looked for evidence of such a state-dependent foraging game between intra-guild competitors. We studied a desert rodent system featuring 2 coexisting species known to compete with each other: midday gerbils (Meriones meridianus, the dominant competitor) and 3-toed jerboas (Dipus sagitta, the subordinate competitor). We simultaneously manipulated the energetic states of both species and allowed them to forage and interact in arenas with artificial food patches. We found that both species responded to their own energetic states, whereas hungry jerboas also significantly responded to gerbils' energetic state in terms of food harvest. Gerbils preferred to carry food items away when foraging alone but switched to on-tray consumption when jerboas were present. Jerboas harvested more food when gerbils were hungry and the most intensive interference occurred when hungry jerboas encountered well-fed gerbils. A plausible explanation for these results is that the future rather than current value of cacheable food is more important to well-fed gerbils. In contrast, hungry gerbils prefer immediate consumption to completely excluding jerboas from resource patches.
Data from: State-dependent decision-making by predators and its consequences for mimicry
The mimicry of one species by another provides one of the most celebrated examples of evolution by natural selection. Edible Batesian mimics deceive predators into believing they may be defended, whereas defended Müllerian mimics have evolved a shared warning signal, more rapidly educating predators to avoid them. However, it may benefit hungry predators to attack defended prey, while the benefits of learning about unfamiliar prey depends on the future value of this information. Previous energetic state-dependent models of predator foraging behaviour have assumed complete knowledge, while informational state-dependent models have assumed fixed levels of hunger. Here, we identify the optimal decision rules of predators accounting for both energetic and informational states. We show that the nature of mimicry is qualitatively and quantitatively affected by both sources of state dependence. Associative learning weakens the extent of parasitic mimicry by edible prey because naive predators often attack defended models. More importantly, mimicry among equally highly defended prey may be parasitic or mutualistic depending on the ecological context. Finally, mimicry by prey with intermediate defences corresponds to Batesian or Müllerian mimicry depending on whether the mimic is profitable to attack by hungry predators, but it is not a special case of mimicry.
Data from: State-dependent behavior alters endocrine-energy relationship: implications for conservation and management
Glucocorticoids (GC) and triiodothyronine (T3) are two endocrine markers commonly used to quantify resource limitation, yet the relationships between these markers and the energetic state of animals has been studied primarily in small-bodied species in captivity. Free-ranging animals, however, adjust energy intake in accordance with their energy reserves, a behavior known as state-dependent foraging. Further, links between life-history strategies and metabolic allometries cause energy intake and energy reserves to be more strongly coupled in small animals relative to large animals. Because GC and T3 may reflect energy intake or energy reserves, state-dependent foraging and body size may cause endocrine-energy relationships to vary among taxa and environments. To extend the utility of endocrine markers to large-bodied, free-ranging animals, we evaluated how state-dependent foraging, energy reserves, and energy intake influenced fecal GC and fecal T3 concentrations in free-ranging moose (Alces alces). Compared with individuals possessing abundant energy reserves, individuals with few energy reserves had higher energy intake and high fecal T3 concentrations, thereby supporting state-dependent foraging. Although fecal GC did not vary strongly with energy reserves, individuals with higher fecal GC tended to have fewer energy reserves and substantially greater energy intake than those with low fecal GC. Consequently, individuals with greater energy intake had both high fecal T3 and high fecal GC concentrations, a pattern inconsistent with previous documentation from captive animal studies. We posit that a positive relationship between GC and T3 may be expected in animals exhibiting state-dependent foraging if GC is associated with increased foraging and energy intake. Thus, we recommend that additional investigations of GC- and T3-energy relationships be conducted in free-ranging animals across a diversity of body size and life-history strategies before these endocrine markers are applied broadly to wildlife conservation and management.
Data from: Inferring state-dependent diversification rates using approximate Bayesian computation (ABC)
<p><span>State-dependent speciation and extinction (SSE) models provide a framework for quantifying whether species traits have an impact on evolutionary rates and how this shapes the variation in species richness among clades in a phylogeny. However, SSE models are becoming increasingly complex, limiting the application of likelihood-based inference methods. Approximate Bayesian computation (ABC), a likelihood-free approach, is a potentially powerful alternative for estimating parameters. One of the key challenges in using ABC is the selection of efficient summary statistics, which can greatly affect the accuracy and precision of the parameter estimates. In state-dependent diversification models, summary statistics need to capture the complex relationships between rates of diversification and species traits. Here, we develop an ABC framework to estimate state-dependent speciation, extinction and transition rates in the BiSSE (binary state dependent speciation and extinction) model. Using different sets of candidate summary statistics, we then compare the inference ability of ABC with that of using likelihood-based maximum likelihood (ML) and Markov chain Monte Carlo (MCMC) methods. Our results show the ABC algorithm can accurately estimate state-dependent diversification rates for most of the model parameter sets we explored. The inference error of the parameters associated with the species-poor state is larger with ABC than in the likelihood estimations only when the speciation rate is highly asymmetric between the two states (</span><em><span>λ</span></em><sub><span>1</span></sub><span> / <em>λ</em><sub>0 </sub></span><span>= 5). Furthermore, we find that the combination of normalized lineage-through-time (nLTT) statistics and phylogenetic signal in binary traits (Fitz and Purvis’s <em>D</em>) constitute efficient summary statistics for the ABC method. By providing insights into the selection of suitable summary statistics, our work aims to contribute to the use of the ABC approach in the development of complex state-dependent diversification models, for which a likelihood is not available.</span></p>
Data from: Inferring state-dependent diversification rates using approximate Bayesian computation (ABC)
<p>State-dependent speciation and extinction (SSE) models provide a framework for quantifying whether species traits have an impact on evolutionary rates and how this shapes the variation in species richness among clades in a phylogeny. However, SSE models are becoming increasingly complex, limiting the application of likelihood-based inference methods. Approximate Bayesian computation (ABC), a likelihood-free approach, is a potentially powerful alternative for estimating parameters. One of the key challenges in using ABC is the selection of efficient summary statistics, which can greatly affect the accuracy and precision of the parameter estimates. In state-dependent diversification models, summary statistics need to capture the complex relationships between rates of diversification and species traits. Here, we develop an ABC framework to estimate state-dependent speciation, extinction and transition rates in the BiSSE (binary state dependent speciation and extinction) model. Using different sets of candidate summary statistics, we then compare the inference ability of ABC with that of using likelihood-based maximum likelihood (ML) and Markov chain Monte Carlo (MCMC) methods. Our results show the ABC algorithm can accurately estimate state-dependent diversification rates for most of the model parameter sets we explored. The inference error of the parameters associated with the species-poor state is larger with ABC than in the likelihood estimations only when the speciation rate is highly asymmetric between the two states (<em>λ</em><sub>1</sub> / <em>λ</em><sub>0 </sub>= 5). Furthermore, we find that the combination of normalized lineage-through-time (nLTT) statistics and phylogenetic signal in binary traits (Fitz and Purvis’s <em>D</em>) constitute efficient summary statistics for the ABC method. By providing insights into the selection of suitable summary statistics, our work aims to contribute to the use of the ABC approach in the development of complex state-dependent diversification models, for which a likelihood is not available.</p>
Data and scripts used to produce the figures for state-dependent CO2 forcing paper
<p>Data and scripts used to produce the figures for state-dependent CO2 forcing paper (He et al., 2023)</p>
State-dependent mortality, not behavior, fragments population distribution of a long-lived mammal after ecological disturbance
<p>Data and code used to produce figures and analyses for the peer-reviewed paper "State-dependent mortality, not behavior, fragments population distribution of a long-lived mammal after ecological disturbance". All demographic and GPS data were collected by the authors as part of the Wyoming Range Mule Deer Project, and spatial data were derived from publicly available GIS platforms. </p> <p>Questions about data and code can be directed to rraffer1@uwyo.edu and tlasharr@uwyo.edu.</p> <p> </p>
Feeding-state dependent neuropeptidergic modulation of reciprocally interconnected inhibitory neurons biases sensorimotor decisions in Drosophila
<p>Raw and source data related to the study "Feeding-state dependent neuropeptidergic modulation of reciprocally interconnected inhibitory neurons biases sensorimotor decisions in Drosophila"</p> <p>Please not that protein-deprived (pd) and sucrose annotation are used interchangeabley in the dataset</p> <p> </p>
Data for behavioral state-dependent habitat selection analysis of translocated female greater sage-grouse, North Dakota 2018-2020
<p>This dataset is associated with the article, "Behavioral state-dependent habitat selection and implications for animal translocations" (Picardi et al., 2021, Journal of Applied Ecology).</p> <p>Post-release monitoring of translocated animals can be used to inform future translocation protocols. In particular, quantifying habitat selection of translocated individuals may help identify features that characterize suitable settlement habitat and inform the choice of future release sites; however, because translocated animals undergo post-release behavioral modification, the underlying behavioral state needs to be taken into account.</p> <p>We analyzed behavioral state-dependent habitat selection in female greater sage-grouse (<i>Centrocercus urophasianus</i>) translocated from Wyoming to North Dakota, USA, using Hidden Markov Models in combination with Integrated Step Selection Analysis. This dataset includes GPS tracks (resampled at a 6-hour resolution using a Continuous Time Movement Model) for 48 individuals translocated between 2018 and 2020, along with environmental variables associated with each location. We segmented each track into behavioral phases corresponding to an exploratory state, characterized by broad and directed movements, and a restricted state, characterized by short and tortuous movements. Then, we quantified habitat selection in each state while also accounting for seasonality and individual reproductive status.</p> <p>Habitat selection of translocated sage-grouse differed between the post-release exploration and the settlement phase. While in the exploratory state, sage-grouse exhibited natal habitat preference induction by selecting for high sagebrush cover, typical of their natal area but not of the release area. In the restricted state, sage-grouse selected for gentle topography and also adjusted their habitat selection based on the season and their reproductive needs.</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>
Input files and structures for article "Carbon dioxide fixation in RuBisCO is protonation state dependent and irreversible"
<p>Pdb file and amber topology of the initial RuBisCO model together with parameter files for the MD simulations with AMBER to equilibrate the system.</p> <p>Structures of reactant, transition state and products in the enzyme RuBisCo used to correct the activation and reaction free energies. Molpro input files used in the projector-based embedding calculations are provided. The same holds for the calculations involving the Zn cation. </p> <p>Optimized structures used to calculate descriptors with conceptual DFT. </p>
Mechanisms of individual variation in large herbivore diets: Roles of spatial heterogeneity and state-dependent foraging
<p>Many populations of consumers consist of relatively specialized individuals that eat only a subset of the foods consumed by the population at large. Although the ecological significance of individual specialization is recognized, it is difficult to document and its underlying mechanisms are poorly understood. Optimal foraging theory provides a useful framework for predicting how individuals might select different diets, positing that animals balance the 'opportunity cost' of stopping to eat an available food item against the cost of searching for something more nutritious; diet composition should be contingent on the distribution of food, and foragers should be more specialized when individuals have high energy reserves to spend searching for high-quality foods. We tested these predicted mechanisms of individual niche differences by quantifying environmental (resource heterogeneity) and organismal (nutritional condition) determinants of diet in a widespread browsing antelope (bushbuck, <em>Tragelaphus sylvaticus</em>) in an African floodplain-savanna ecosystem. We quantified individual diet breadth and composition using DNA metabarcoding of fecal samples collected repeatedly from 15 GPS-collared animals (6–14 samples per individual, median 12). Bushbuck diets were structured by spatial heterogeneity and constrained by individual conditions. We observed significant individual-level partitioning of food plants by bushbuck both within and between two adjacent habitat types (floodplain and woodland). Individuals with home ranges that were closer together and/or had similar vegetation structures (measured using LiDAR) ate more similar diets, supporting the prediction that heterogeneous resource distribution promotes individual differentiation. Individuals in good nutritional condition had significantly narrower diets (fewer plant taxa), searched their home ranges more intensively (intensity-of-use index), and had higher-quality diets (percent digestible protein) than those in poor condition, supporting the prediction that animals with greater endogenous reserves are more specialized because they can invest time in searching for nutritious foods. Our results support predictions from optimal foraging theory about the energetic basis of individual specialization and provide a potentially generalizable framework for understanding how individual niche width is governed by animal behavior and physiology in heterogeneous landscapes.</p>
Data from: Protocol dependence and state variables in the force-moment ensemble
Stress-based ensembles incorporating temperature-like variables have been proposed as a route to an equation of state for granular materials. To test the efficacy of this approach, we perform experiments on a two-dimensional photoelastic granular system under three loading conditions: uniaxial compression, biaxial compression, and simple shear. From the interparticle forces, we find that the distributions of the normal component of the coarse-grained force-moment tensor are exponential-tailed, while the deviatoric component is Gaussian-distributed. This implies that the correct stress-based statistical mechanics conserves both the force-moment tensor and the Maxwell-Cremona force-tiling area. As such, two variables of state arise: the tensorial angoricity and a new temperature-like quantity associated with the force-tile area which we name keramicity. Each quantity is observed to be inversely proportional to the global confining pressure; however only keramicity exhibits the protocol-independence expected of a state variable, while tensorial angoricity behaves as a variable of process.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.