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885 results for “data strategy”
Data from: Smaller islands, bigger appetites: Evolutionary strategies of insular endemic skinks
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Data from: Multiple introductions, polyploidy and mixed reproductive strategies are linked to genetic diversity and structure in the most widespread invasive plant across Southern Ocean archipelagos
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Data from: Using multiple scales of movement to highlight risk-reward strategies of coyotes (Canis latrans) in mixed-use landscapes
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Data from: Sampling strategy optimization to increase statistical power in landscape genomics: a simulation-based approach
An increasing number of studies are using landscape genomics to investigate local adaptation in wild and domestic populations. The implementation of this approach requires the sampling phase to consider the complexity of environmental settings and the burden of logistic constraints. These important aspects are often underestimated in the literature dedicated to sampling strategies. In this study, we computed simulated genomic datasets to run against actual environmental data in order to trial landscape genomics experiments under distinct sampling strategies. These strategies differed by design approach (to enhance environmental and/or geographic representativeness at study sites), number of sampling locations and sample sizes. We then evaluated how these elements affected statistical performances (power and false discoveries) under two antithetical demographic scenarios. Our results highlight the importance of selecting an appropriate sample size, which should be modified based on the demographic characteristics of the studied population. For species with limited dispersal, sample sizes above 200 units are generally sufficient to detect most adaptive signals, while in random mating populations this threshold should be increased to 400 units. Furthermore, we describe a design approach that maximizes both environmental and geographical representativeness of sampling sites and show how it systematically outperforms random or regular sampling schemes. Finally, we show that although having more sampling locations (between 40 and 50 sites) increase statistical power and reduce false discovery rate, similar results can be achieved with a moderate number of sites (20 sites). Overall, this study provides valuable guidelines for optimizing sampling strategies for landscape genomics experiments.
Data from: The microbiota influences the Drosophila melanogaster life history strategy
<p class="CxSpFirst">Organisms are locally adapted when members of a population have a fitness advantage in one location relative to conspecifics in other geographies. For example, across latitudinal gradients, some organisms may trade off between traits that maximize fitness components in one, but not both, of somatic maintenance or reproductive output. Latitudinal gradients in life history strategies are traditionally attributed to environmental selection on an animal's genotype, without any consideration of the possible impact of associated microorganisms ("microbiota") on life history traits. Here, we show in Drosophila melanogaster, a key model for studying local adaptation and life history strategy, that excluding the microbiota from definitions of local adaptation is a major shortfall. First, we reveal that an isogenic fly line reared with different bacteria varies the investment in early reproduction versus somatic maintenance. Next, we show that in wild fruit flies, the abundance of these same bacteria was correlated with the latitude and life history strategy of the flies, suggesting geographic specificity of the microbiota composition. Variation in microbiota composition of locally adapted D. melanogaster could be attributed to both the wild environment and host genetic selection. Finally, by eliminating or manipulating the microbiota of fly lines collected across a latitudinal gradient, we reveal that host genotype contributes to latitude-specific life history traits independent of the microbiota and that variation in the microbiota can suppress or reverse the differences between locally adapted fly lines. Together, these findings establish the microbiota composition of a model animal as an essential consideration in local adaptation.</p>
Data from: Brain size does not predict learning strategies in a serial reversal learning test
<p><span><span><span><span><span><span><span><span><span><span><span>Reversal learning assays are commonly used across a wide range of taxa to investigate associative learning and behavioural flexibility. In serial reversal learning, the reward contingency in a binary discrimination is reversed multiple times. Performance during serial reversal learning varies greatly at the interspecific level, as some animals adapt a rule-based strategy that enables them to switch quickly between reward contingencies. Enhanced learning ability and increased behavioural flexibility generated by a larger relative brain size has been proposed to be an important factor underlying this variation. Here we experimentally test this hypothesis at the intraspecific level. We use guppies (<i>Poecilia reticulata</i>) artificially selected for small and large relative brain size, with matching differences in neuron number, in a serial reversal learning assay. We tested 96 individuals over ten serial reversals and found that learning performance and memory were predicted by brain size, whereas differences in efficient learning strategies were not. We conclude that variation in brain size and neuron number is important for variation in learning performance and memory, but these differences are not great enough to cause the larger differences in efficient learning strategies observed at higher taxonomic levels. </span></span></span></span></span></span></span></span></span></span></span></p>
Data from: Depth dependent dive kinematics suggest cost-efficient foraging strategies by tiger sharks
Tiger sharks Galeocerdo cuvier are a keystone, top-order predator that are assumed to engage in cost-efficient movement and foraging patterns. To investigate the extent to which patterns of oscillatory diving by these animals conform to these patterns, we used a biologging approach to model their cost of transport. High-resolution biologging tags with tri-axial sensors were deployed on 21 tiger sharks at Ningaloo Reef for durations of 5-48 hours. Using overall dynamic body acceleration (ODBA) as a proxy for energy expenditure, we modelled the cost of transport of oscillatory movements of varying geometries in both horizontal and vertical planes for tiger sharks. The cost of horizontal transport was minimized by descending at the lowest possible angle and ascending at an angle of 5-14°, meaning that vertical oscillations conserved energy compared to swimming at a level depth. Reduction of vertical travel costs occurred at steeper angles. The absolute dive angles of tiger sharks increased between inshore and offshore zones, presumably to reduce the cost of transport while continuously hunting for prey in both benthic and surface habitats. Oscillatory movements of tiger sharks conform to strategies of cost-efficient foraging, and shallow inshore habitats appear to be an important habitat for both hunting prey and conserving energy while travelling.
Model output data for "Negative density-dependent dispersal emerges from the joint evolution of density- and body condition-dependent dispersal strategies"
<p>Empirical studies have documented both positive and negative density-dependent dispersal, yet most theoretical models predict positive density dependence as a mechanism to avoid competition. Several hypotheses have been proposed to explain the occurrence of negative density-dependent dispersal, but few of these have been formally modeled. Here, we developed an individual based model of the evolution of density-dependent dispersal. This model is novel in that it considers the effects of density on dispersal directly, and indirectly through effects on individual condition. Body condition is determined mechanistically, by having juveniles compete for resources in their natal patch. We found that the evolved dispersal strategy was a steep, increasing function of both density and condition. Interestingly, although populations evolved a positive density-dependent dispersal strategy, the simulated metapopulations exhibited negative density-dependent dispersal. This occurred because of the negative relationship between density and body condition: high density sites produced low condition individuals that lacked the resources required for dispersal. Our model therefore generates the novel hypothesis that observed negative density-dependent dispersal can occur when high density limits the ability of organisms to disperse. We suggest that future studies consider how phenotype is linked to the environment when investigating the evolution of dispersal.</p>
Data from: Identification of top-priority areas to achieve EU Biodiversity Strategy for 2030 key commitments
<p>Data from: Identification of top-priority areas to achieve EU Biodiversity Strategy for 2030 key commitments. The dataset includes all files to run prioritization analyses included in Iulia V. Miu, Laurentiu Rozylowicz, Viorel D. Popescu, Paulina Anastasiu (2020) Identification of areas of very high biodiversity value to achieve the EU Biodiversity Strategy for 2030 key commitments. </p> <p>To run analyses, unzip the files in your computer (drive C) and use Zonation v4 developed by CBIG - CONSERVATION BIOLOGY INFORMATICS GROUP, Department of Biosciences of the University of Helsinki (<a href="https://www.helsinki.fi/en/researchgroups/digital-geography-lab/software-developed-in-cbig#section-52992">https://www.helsinki.fi/en/researchgroups/digital-geography-lab/software-developed-in-cbig#section-52992</a>). Files are available for nationwide prioritization of terrestrial Natural 2000 in Romania, taxa specific prioritization of terrestrial Natural 2000 in Romania (amphibians, mammals, plants, reptiles, invertebrates, and fish), and at biogeographical level prioritization of terrestrial Natural 2000 in Romania (Alpine, Continental, Pannonian, Steppic & Black Sea).</p>
Data from: Physician champions' perspectives and practices on electronic health records implementation: challenges and strategies
<p><span><span><span><b>Objective: </b>Physician champions are "boots on the ground" physician leaders who facilitate the implementation of, and transition to, new health information technology (HIT) systems within an organization. They are commonly cited as key personnel in HIT implementations, yet little research has focused on their practices and perspectives. </span></span></span></p> <p><span><span><span><b>Methods: </b>We addressed this research gap through a qualitative study of physician champions that aimed to capture their challenges and strategies during a large-scale HIT implementation. Email interviews were conducted with 45 physician champions from diverse clinical areas five months after a new electronic health record (EHR) system went live in a large academic medical center. We adopted a grounded theory approach to analyze the data.</span></span></span></p> <p><span><span><span><b>Results: </b>Our physician champion participants reported multiple challenges, including insufficient training, limited at-the-elbow support, unreliable communication with leadership and the EHR vendor, as well as flawed system design. To overcome these challenges, physician champions developed their own personalized training programs in a simulated context or in the live environment, sought and obtained more at-the-elbow support both internally and externally, and adapted their departmental sociotechnical context to make the system work better.</span></span></span></p> <p><b>Discussion and Conclusion: </b>This study identified the challenges physician champions faced and the strategies they developed to overcome these challenges. Our findings suggest<b> </b>factors that are crucial to the successful involvement of physician champions in HIT implementations, including the availability of instrumental (e.g., reward for efforts), emotional (e.g., mechanisms for expressing frustrations), and peer support; ongoing engagement with the champions; and appropriate training and customization planning.</p>
Data from: Changes in soil pH and their dependence on the species of cereals and strategies for sustainable agriculture
<p>The acidity of the environment is one of the key elements determining proper conditions for crop cultivation. Inappropriate environmental conditions may contribute to numerous changes in plant raw materials. New strategies introduced in agriculture bring with them some uncertainties associated with the adaptation of plants to the soil. Currently, in the EU market, a gradual replacement of conventional strategies in favour of organic ones is observed. The change in fertilization strategy may lead to the emergence of new soil conditions in cultivation. Soil pH and humus content determine the phenomenon of soil fertility as well as soil physical, chemical, and biological properties. Rational and effective management of nutrients is related to the assessment of the content of available nutrients in the soil, as well as to the agronomic assessment of the soil class. This type of treatment is key in the planning of crops rotation. The study aimed to evaluate soil pH after combine harvesting, in wheat, rye, and barley crops cultivation according to two agricultural strategies, viz. ecological and conventional. In the course of the study mature soil was sampled. The research was carried out on pH meter CP 411 combined with an EPS-1 pH electrode. The obtained soil pH results varied according to the type of cereal grown. Statistical analysis of variance with the significance level of 0.05 showed no significant difference regardless of the implemented agricultural strategy. It is recommended once every 4 years to perform laboratory examination of soil pH for fertilization advice.</p>
Learning strategies and long-term memory in Asian short-clawed otters (Aonyx cinereus) data
<p>Data submitted here, are those used in the writing of our manuscript entitled "Learning strategies and long-term memory in Asian short-clawed otters (<i>Aonyx cinereus</i>)" which has been submitted to Royal Society Open Science for publication. Abstract for that manuscript is below</p> <p>Social learning, namely learning from information acquired from others or their products, is widespread throughout the animal kingdom. There is growing evidence that animals selectively employ 'social learning strategies', which for example, determine when<i> </i>they should copy others instead of learning asocially, and whom they should copy. Furthermore, once animals have acquired new information, it is beneficial for them to commit it to long-term memory, especially when it concerns the discovery of profitable resources. Research into social learning strategies and long-term memory has covered a wide range of taxa. However, otters (subfamily Lutrinae), popular in zoos due to their sociability and playfulness, remained neglected until a recent study provided evidence of social learning in captive smooth-coated otters (<i>Lutrogale perspicillata</i>), but not in Asian short-clawed otters (<i>Aonyx cinereus</i>). We investigated Asian short-clawed otters' learning strategies and long-term memory performance in a foraging context. We presented novel extractive foraging tasks twice to captive family groups and used network-based diffusion analysis to provide evidence of social learning and long-term memory in this species. A major cause of wild Asian short-clawed otter declines is prey scarcity. Furthering our understanding of how they learn about and remember novel food sources could inform key conservation strategies.</p>
Elements of Data Strategy
<p>The diagram represents the fundamental components of a data strategy. It is separated into three abstraction levels:</p> <ol> <li>Phases</li> <li>Tracks</li> <li>Tasks, activities, and deliverables</li> </ol> <p> </p>
Data set for study '"Optimal intervention strategies to mitigate the COVID-19 pandemic effects"
<p>Data associated with the findings presented in the study '"Optimal intervention strategies to mitigate the COVID-19 pandemic effects"</p>
Data from: A hidden Markov model to identify and adjust for selection bias: an example involving mixed migration strategies
An important assumption in observational studies is that sampled individuals are representative of some larger study population. Yet, this assumption is often unrealistic. Notable examples include online public-opinion polls, publication biases associated with statistically significant results, and in ecology, telemetry studies with significant habitat-induced probabilities of missed locations. This problem can be overcome by modeling selection probabilities simultaneously with other predictor–response relationships or by weighting observations by inverse selection probabilities. We illustrate the problem and a solution when modeling mixed migration strategies of northern white-tailed deer (Odocoileus virginianus). Captures occur on winter yards where deer migrate in response to changing environmental conditions. Yet, not all deer migrate in all years, and captures during mild years are more likely to target deer that migrate every year (i.e., obligate migrators). Characterizing deer as conditional or obligate migrators is also challenging unless deer are observed for many years and under a variety of winter conditions. We developed a hidden Markov model where the probability of capture depends on each individual's migration strategy (conditional versus obligate migrator), a partially latent variable that depends on winter severity in the year of capture. In a 15-year study, involving 168 white-tailed deer, the estimated probability of migrating for conditional migrators increased nonlinearly with an index of winter severity. We estimated a higher proportion of obligates in the study cohort than in the population, except during a span of 3 years surrounding back-to-back severe winters. These results support the hypothesis that selection biases occur as a result of capturing deer on winter yards, with the magnitude of bias depending on the severity of winter weather. Hidden Markov models offer an attractive framework for addressing selection biases due to their ability to incorporate latent variables and model direct and indirect links between state variables and capture probabilities.
Data from: Human movement, cooperation, and the effectiveness of coordinated vector control strategies
Vector-borne disease transmission is often typified by highly focal transmission and influenced by movement of hosts and vectors across different scales. The ecological and environmental conditions (including those created by humans through vector control programmes) that result in metapopulation dynamics remain poorly understood. The development of control strategies that would most effectively limit outbreaks given such dynamics is particularly urgent given the recent epidemics of dengue, chikungunya and Zika viruses. We developed a stochastic, spatial model of vector-borne disease transmission, allowing for movement of hosts between patches. Our model is applicable to arbovirus transmission by Aedes aegypti in urban settings and was parametrized to capture Zika virus transmission in particular. Using simulations, we investigated the extent to which two aspects of vector control strategies are affected by human commuting patterns: the extent of coordination and cooperation between neighbouring communities. We find that transmission intensity is highest at intermediate levels of host movement. The extent to which coordination of control activities among neighbouring patches decreases the prevalence of infection is affected by both how frequently humans commute and the proportion of neighbouring patches that commits to vector surveillance and control activities. At high levels of host movement, patches that do not contribute to vector control may act as sources of infection in the landscape, yet have comparable levels of prevalence as patches that do cooperate. This result suggests that real cooperation among neighbours will be critical to the development of effective pro-active strategies for vector-borne disease control in today's commuter-linked communities.
Data from: Invasion strategies in round goby (Neogobius melanostomus): is bigger really better?
Few studies have systematically investigated mid- or long-term temporal changes of biological characteristics in invasive alien species considering the different phases of an invasion. We studied the invasion performance of one of the most invasive species worldwide, the round goby Neogobius melanostomus, from total absence over first occurrence until establishment from 2010 to 2015 in the upper Danube River. After an upstream movement of the invasion front of about 30 river km within four years, the pattern that round goby pioneering populations significantly differ from longer established ones has been confirmed: Pioneering populations at the invasion front comprised more females than males, and adult specimens with a larger body size compared to those at longer inhabited areas. On the population-level, the proportion of juveniles increased with time since invasion. The results of this study provide support for the previously postulated ´bigger is better´ and ´individual trait utility´ hypotheses explaining invasion success in round goby. Pioneering invaders with their greater exploratory behavior, highly adaptive phenotypic plasticity and increased competitive ability seem to act as prime emperors of new habitats, strongly following and benefiting from man-made river-bank structures.
Data from: A long-term evaluation of applied nucleation as a strategy to facilitate forest restoration
Applied nucleation is a restoration technique that seeks to facilitate woody plant establishment by attracting birds or other animals that may introduce seeds of dispersal-limited species. In 1991, an experimental test of applied nucleation was initiated in an abandoned landfill in New Jersey, USA. Trees and shrubs were planted into 16 10 × 10-m plots, covering less than 3% of the 6 ha site. In 2010-2011, we sampled the plant community to test the impact of the treatments on forest cover and plant biodiversity. Site-wide forest cover increased substantially in the 19 years since planting from none to 59%. The original planted plots had significantly higher stem density, particularly of bird-dispersed species, than unplanted areas. Species composition outside the planted plots was dominated by the wind-dispersed Fraxinus americana and several small-seeded bird-dispersed species, but there were few species indicative of later successional stages. The expected model of successional development via the nucleation model - that rates of colonization would be highest near plantings and that forest cover would spread outward from established clusters - was not supported after this time span. Given the site's isolation from potential sources of woody propagules, the experimental treatments may not have been enough to overcome many species' dispersal limitation. Regardless of the mechanism, however, the treatments transformed the once essentially treeless site into a densely wooded habitat, and did so at a rate faster than other descriptions of reforestation following disturbances or land-use changes in the region. Despite the relatively low species richness of the community, this experiment demonstrated that reforestation of even severely degraded habitat can be achieved with minimal management after site preparation and cluster plantings.
Data from: Strategies for a successful plant invasion: the reproduction of Phragmites australis in northeastern North America
1. Knowing the relative contribution of vegetative propagation and sexual reproduction to the dispersal and establishment of exotic plants is crucial for devising efficient control strategies. This is particularly true for the common reed (Phragmites australis), one of the most invasive species in North America. 2. For the first time we combined in situ field observations and genetic evidence, based on two genotyping techniques, i.e., microsatellite markers (SSR) and genotyping-by-sequencing (GBS), to determine the propagation strategies of this invader at its northern distribution limit in North America, and especially in roadside ditches. 3. Field observations revealed that, in a region where the common reed is already abundant, both seeds and plant fragments contributed to the establishment of new populations. Newly established individuals originated mostly (84%) from seeds rather than fragments, but a larger proportion of individuals originating from fragments survived the second year compared to seedlings. 4. High genetic diversity among marsh and roadside common reed stands indicated the prime role of sexual reproduction for dispersal. The vast majority of genotypes were found in only one stand; such high genetic variability can only be explained by sexual reproduction. Half the surveyed stands comprised a single clone, suggesting that local expansion mainly occurred vegetatively. As the small proportion of SSR genotypes initially thought to be common between distant stands proved to be distinct (as revealed by GBS data), it is likely that all the stands examined were initially founded by genetically distinct individuals. 5. Synthesis. Our study suggests that long-distance dispersal by seeds is important for the common reed, in marshes and roadsides, while both seeds and plant fragments contribute to short-distance dispersal along roads, at least in regions where the species is already abundant. The success of this invader in North America seems to be attributable to a reproduction strategy combining the advantages of sexuality with those of vegetative propagation. Moreover, this study shows that the GBS approach strongly reduces uncertainties associated with the use of a limited number of markers. This approach is especially valuable for ecologists dealing with an ever increasing number of invaders, of which few have identified microsatellite markers.
Data from: Exploiting mycorrhizas in broad daylight: partial mycoheterotrophy is a common nutritional strategy in meadow orchids.
Partial mycoheterotrophy (PMH) is a nutritional mode in which plants utilize organic matter, i.e. carbon, both from photosynthesis and a fungal source. The latter reverses the direction of plant-to-fungus carbon flow as usually assumed in mycorrhizal mutualisms. Based on significant enrichment in the heavy isotope 13C, a growing number of PMH orchid species have been identified. These PMH orchids are mostly associated with fungi simultaneously forming ectomycorrhizas with forest trees. In contrast, the much more common orchids that associate with rhizoctonia fungi, which are decomposers, have stable isotope profiles most often characterized by high 15N enrichment and high nitrogen concentrations but either an insignificant 13C enrichment or depletion relative to autotrophic plants. Using hydrogen stable isotope abundances recent investigations showed PMH in rhizoctonia-associated orchids growing under light-limited conditions. Hydrogen isotope abundances can be used as substitute for carbon isotope abundances in cases where autotrophic and heterotrophic carbon sources are insufficiently distinctive to indicate PMH. To determine whether rhizoctonia-associated orchids growing in habitats with high irradiance feature PMH as a nutritional mode, we sampled 13 orchid species growing in montane meadows, four forest orchid species and 34 autotrophic reference species. We analysed δ2H, δ13C, δ15N and δ18O and determined nitrogen concentrations. Orchid mycorrhizal fungi were identified by DNA sequencing. As expected, we found high enrichments in 2H, 13C, 15N and nitrogen concentrations in the ectomycorrhiza-associated forest orchids, and the rhizoctonia-associated Neottia cordata from a forest site was identified as PMH. Most orchids inhabiting sunny meadows lacked 13C enrichment or were even significantly depleted in 13C relative to autotrophic references. However, we infer PMH for the majority of these meadow orchids due to both significant 2H and 15N enrichment and high nitrogen concentrations. Pseudorchis albida was the sole autotrophic orchid in this study as it exhibited neither enrichment in any isotope nor a distinctive leaf nitrogen concentration. Synthesis. Our findings demonstrate that partial mycoheterotrophy is a trophic continuum between the extreme endpoints of autotrophy and full mycoheterotrophy, ranging from marginal to pronounced. In rhizoctonia-associated orchids, partial mycoheterotrophy plays a far greater role than previously assumed, even in full light conditions.
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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.