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52 results for “Warning signal”
Data and code of the article: "Early Warning Signals of the Termination of the African Humid Period(s)"
<p>Data and MATLAB Code of the article Trauth, M.H., Asrat, A., Fischer, M.L., Hopcroft, P.O., Foerster, V., Kaboth-Bahr, S., Kindermann, K., Lamb, H.F., Marwan, N., Maslin, M.A., Schaebitz, F., Valdes, P.J. (2024) Early Warning Signals of the Termination of the African Humid Period(s), Nature Communications, https://doi.org/10.1038/s41467-024-47921-1. The individual directories contain the data and the MATLAB code used to generate Fig. 1 and 2 and Supplementary Fig. 1 to 7 published with the article.</p>
Eco-evolutionary processes underlying early warning signals of population declines
<p>Datasets for the paper appearing in Journal of Animal ecology : "Eco-evolutionary processes underlying early warning signals of population declines". Also GitHub repository link :<a href="https://github.com/GauravKBaruah/ECO-EVO-EWS-DATA">https://github.com/GauravKBaruah/ECO-EVO-EWS-DATA</a></p>
A computational neuroscience framework for quantifying warning signals
<p>Animal warning signals show remarkable diversity, yet subjectively appear to share certain visual features that make defended prey stand out and look different from more cryptic palatable species. For example, many (but far from all) warning signals involve high contrast elements, such as stripes and spots, and often involve the colours yellow and red. How exactly do aposematic species differ from non-aposematic ones in the eyes (and brains) of their predators?</p> <p>Here we develop a novel computational modelling approach, to quantify prey warning signals and establish what visual features they share. First, we develop a model visual system, made of artificial neurons with realistic receptive fields, to provide a quantitative estimate of the neural activity in the first stages of the visual system of a predator in response to a pattern. The system can be tailored to specific species. Second, we build a novel model that defines a 'neural signature', comprising quantitative metrics that measure the strength of stimulation of the population of neurons in response to patterns. This framework allows us to test how individual patterns stimulate the model predator visual system.</p> <p>For the predator-prey system of birds foraging on lepidopteran prey, we compared the strength of stimulation of a modelled avian visual system in response to a novel database of hyperspectral images of aposematic and undefended butterflies and moths. Warning signals generate significantly stronger activity in the model visual system, setting them apart from the patterns of undefended species. The activity was also very different from that seen in response to natural scenes. Therefore, to their predators, lepidopteran warning patterns are distinct from their non-defended counterparts, and stand out against a range of natural backgrounds.</p> <p>For the first time, we present an objective and quantitative definition of warning signals based on how the pattern generates population activity in a neural model of the brain of the receiver. This opens new perspectives for understanding and testing how warning signals have evolved, and, more generally, how sensory systems constrain signal design.</p>
Predator selection on multicomponent warning signals in an aposematic moth
<p>Aposematic prey advertise their unprofitability with conspicuous warning signals that are often composed of multiple color patterns. Many species show intraspecific variation in these patterns even though selection is expected to favor invariable warning signals that enhance predator learning. However, if predators acquire avoidance to specific signal components, this might relax selection on other aposematic traits and explain variability. Here we investigated this idea in the aposematic moth <em>Amata</em> <em>nigriceps</em> that has conspicuous black and orange coloration. The size of the orange spots in the wings is highly variable between individuals, whereas the number and width of orange abdominal stripes remain consistent. We produced artificial moths that varied in the proportion of orange in the wings or the presence of abdominal stripes. We presented these to a natural avian predator, the noisy miner (<em>Manorina</em> <em>melanocephala</em>), and recorded how different warning signal components influenced their attack decisions. When moth models had orange stripes on the abdomen, birds did not discriminate between different wing signals. However, when the stripes on the abdomen were removed, birds chose the model with smaller wing spots. In addition, we found that birds were more likely to attack moths with a smaller number of abdominal stripes. Together, our results suggest that bird predators primarily pay attention to the abdominal stripes of <em>A. nigriceps,</em> and this could relax selection on wing coloration. Our study highlights the importance of considering individual warning signal components if we are to understand how predation shapes selection on prey warning coloration.</p>
Selfish herd effects in aggregated caterpillars and their interaction with warning signals
<p>Larval Lepidoptera gains survival advantages by aggregating, especially when combined with aposematic warning signals, yet reductions in predation risk may not be experienced equally across all group members. Hamilton's selfish herd theory predicts that larvae that surround themselves with their group mates should be at lower risk of predation, and those on the periphery of aggregations experience the greatest risk, yet this has rarely been tested. Here, we expose aggregations of artificial 'caterpillar' targets to predation from free-flying, wild birds to test for marginal predation when all prey are equally accessible, and for interaction between warning colouration and marginal predation. We find that targets nearer the centre of the aggregation survived better than peripheral targets and nearby targets isolated from the group. However, there was no difference in survival between peripheral and isolated targets. We also find that grouped targets survived better than isolated targets when both are aposematic, but not when they are non-signalling. To our knowledge, our data provide the first evidence to suggest that avian predators preferentially target peripheral larvae from aggregations, and that prey warning signals enhance predator avoidance of groups.</p>
Additive genetic variation, but not temperature, influences warning signal expression in Amata nigriceps moths (Lepidoptera: Arctiinae)
<p>Many aposematic species show variation in their colour patterns even though selection by predators is expected to stabilise warning signals towards a common phenotype. Warning signal variability can be explained by trade-offs with other functions of colouration, such as thermoregulation, that may constrain warning signal expression by favouring darker individuals. Here, we investigated the effect of temperature on warning signal expression in aposematic <em>Amata nigriceps</em> moths that vary in their black and orange wing patterns. We sampled moths from two flight seasons that differed in the environmental temperatures and also reared different families under controlled conditions at three different temperatures. Against our prediction that lower developmental temperatures would reduce the warning signal size of the adult moths, we found no effect of temperature on warning signal expression in either wild or laboratory-reared moths. Instead, we found sex- and population-level differences in wing patterns. Our rearing experiment indicated that ~70% of the variability in the trait is genetic but understanding what signalling and non-signalling functions of wing colouration maintain the genetic variation requires further work. Our results emphasise the importance of considering both genetic and plastic components of warning signal expression when studying intraspecific variation in aposematic species.</p>
Selfish herd effects in aggregated caterpillars and their interaction with warning signals
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Additive genetic variation, but not temperature, influences warning signal expression in Amata nigriceps moths (Lepidoptera: Arctiinae)
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A computational neuroscience framework for quantifying warning signals
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Predator selection on multicomponent warning signals in an aposematic moth
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The impact of life stage and pigment source on the evolution of novel warning signal traits
<p><span><span><span><span><span><span><span><span><span><span><span>Our understanding of how novel warning color traits evolve in natural populations is largely based on studies of reproductive stages and organisms with endogenously produced pigmentation. In these systems, genetic drift is often required for novel alleles to overcome strong purifying selection stemming from frequency-dependent predation and positive assortative mating. Here, we integrate data from field surveys, predation experiments, population genomics, and phenotypic correlations to explain the origin and maintenance of geographic variation in a diet-based larval pigmentation trait in the redheaded pine sawfly (<i>Neodiprion lecontei</i>), a pine-feeding hymenopteran. Although our experiments confirm that <i>N. lecontei</i><i> </i>larvae are indeed aposematic—and therefore likely to experience frequency-dependent predation—our genomic data do not support a historical demographic scenario that would have facilitated the spread of an initially deleterious allele via drift. Additionally, significantly elevated differentiation at a known color locus suggests that geographic variation in larval color is currently maintained by selection. Together, these data suggest that the novel white morph likely spread via selection. However, white body color does not enhance aposematic displays, nor is it correlated with enhanced chemical defense or immune function. Instead, the derived white-bodied morph is disproportionately abundant on a pine species with a reduced carotenoid content relative to other pine hosts, suggesting that bottom-up selection via host plants may have driven divergence among populations. Overall, our results suggest that life stage and pigment source can have a substantial impact the evolution of novel warning signals, highlighting the need to investigate diverse aposematic taxa to develop a comprehensive understanding of color variation in nature.</span></span></span></span></span></span></span></span></span></span></span></p>
Codes and data for the article 'Early warning signal for river-borne diseases with almost no data'
<p>Codes and data for the paper "Early warning signal for river-borne diseases with almost no data".</p> <p>This collection includes data on the prevalence of river-borne diseases and related environmental variables.<br>The codes are for extracting the tree structure of the river from the map and using the extended HMM model to predict the presence of contaminated samples in each part of the river.</p>
Early warning signal reliability varies with COVID-19 waves
<p><strong>Abstract</strong></p> <p>Early warning signals (EWSs) aim to predict changes in complex systems from phenomenological signals in time series data. These signals have recently been shown to precede the emergence of disease outbreaks, offering hope that policy makers can make predictive rather than reactive management decisions. Here, using a novel, sequential analysis in combination with daily COVID-19 case data across 24 countries, we suggest that composite EWSs consisting of variance, autocorrelation, and skewness can predict non-linear case increases, but that the predictive ability of these tools varies between waves based upon the degree of critical slowing down present. Our work suggests that in highly monitored disease time series such as COVID-19, EWSs offer the opportunity for policy makers to improve the accuracy of urgent intervention decisions but best characterise hypothesised critical transitions.</p> <p><strong>Dataset</strong></p> <p>The deposited dataset contains scripts used in the early warning signal and generalised additive model analysis, the generation of figures, and the custom R functions underpinning the work. Raw COVID-19 case data is also provided if users prefer to access files directly rather than sourcing from the host repositories (all credit is provided to the original publishers).</p>
Unexpected colour pattern variation in mimetic frogs: implication for the diversification of warning signals in the genus Ranitomeya
<p>Predation is expected to promote uniformity in the warning colouration of defended prey, but also mimicry convergence between aposematic species. Despite selection constraining both colour-pattern and population divergence, many aposematic animals display numerous geographically structured populations with distinct warning signals. Here, we explore the extent of phenotypic variation of sympatric species of <em>Ranitomeya</em> poison frogs and test for theoretical expectations on variation and convergence in mimetic signals. We demonstrate that both warning signal and mimetic convergence are highly variable and are negatively correlated: some localities display high variability and no mimicry while in others the phenotype is fixed and mimicry is perfect. Moreover, variation in warning signals is always present within localities, and in many cases, this variation overlaps between populations, such that variation is continuous. Finally, we show that coloration is consistently the least variable element and is likely of greater importance for predator avoidance compared to patterning. We discuss the implications of our results in the context of warning signal diversification and suggest that, like many other locally adapted traits, a combination of standing genetic variation and founding effect might be sufficient to enable divergence in colour pattern.</p>
Data from: Temperature as an early warning signal of honeybee colony failure
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The impact of life stage and pigment source on the evolution of novel warning signal traits
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Data from: Early warning signals of malaria resurgence in Kericho, Kenya
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Data from: I remember you! Multicomponent warning signals and predator memory
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Unexpected colour pattern variation in mimetic frogs: implication for the diversification of warning signals in the genus Ranitomeya
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Long-term empirical evidence, early warning signals, and multiple drivers of regime shifts in a lake ecosystem
<p>1. Catastrophic regime shifts in various ecosystems are increasing with the intensification of anthropogenic pressures. Understanding and predicting critical transitions are thus a key challenge in ecology. Previous studies have mainly focused on single environmental drivers (e.g., eutrophication) and early warning signals (EWSs) prior to population collapse. However, how multiple environmental stressors interact to shape ecological behaviour and whether EWSs were detectable prior to the recovery process in lake ecosystems are largely unknown.</p> <p>2. We present long-term empirical evidence of the critical transition and hysteresis with the combined pressures of climate warming, eutrophication and trophic cascade effects by fish stocking in a subtropical Chinese lake in the Yangtze floodplain. The catastrophic regime shifts are cross-validated by 64-year multi-trophic level monitoring data and paleo-diatom records.</p> <p>3. We show that EWSs are detectable in both the collapse and recovery trajectories and that including body size information in composite EWSs requires shorter time series data and can improve the predictive ability of regime shifts. Although full recovery has not yet been observed, EWSs prior to recovery provide us with the opportunity to take measures for a clear-water regime.</p> <p>4. Climate warming and top-down cascade effects have a negative influence on water clarity by altering lower trophic level abundance and body size, which in turn have a negative effect on macrophyte abundance. Furthermore, we identify a shift in the dominant driving forces from bottom-up to top-down after regime shifts, decoupling the relationships between nutrients and biological components and thus decreasing the efficiency of nutrient reduction.</p> <p>5. Synthesis This study provides new insights into ecological hysteresis under multiple external stressors and improves our understanding of trait-based EWSs in both the collapse and recovery processes in natural freshwater ecosystems. For management practice, our work suggests that slowing down climate warming and weakening the fish predation pressure on food webs are necessary to increase the effectiveness of nutrient reduction in the restoration of lakes.</p>
ScienceDex guides
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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.