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Data from: Functional traits, not productivity, predict openness to seedling recruitment in alpine plant communities under climatic warming
Understanding the degree to which plant communities are open to seedling recruitment is key to predicting how they will be impacted by climate change. We experimentally assessed whether communities assembled under colder climates were inherently more open to recruitment than warmer-climate communities, after controlling for differences in the current climate under which the communities were growing. We then tested whether variation in openness to recruitment could be explained by community biomass or by the plant functional traits of the community. The study was conducted in a climate grid of twelve grassland sites across southern Norway, differing systematically in temperature and precipitation. Along a 2000 mm precipitation gradient, we transplanted turfs with intact plant communities from alpine and sub-alpine sites into 2℃ warmer sites, and measured natural seedling emergence in these transplanted turfs vs. locally replanted control turfs at the transplant destination sites. Mixed effect models were used to assess the effect of origin (cold vs warm climate), biomass, and functional trait composition of the communities on seedling emergence. We further assessed variation in these effects across different climatic contexts (the temperature and precipitation gradients). Communities originating from colder climates were consistently more open to recruitment, with on average 44% more seedlings emerging, than the locally replanted control communities. The higher rates of seedling emergence in colder-climate communities were attributable to systematic differences in plant functional traits, but not in biomass. The colder-climate communities were composed of species with smaller leaves and lower maximum plant heights; traits that may make these communities less effective at excluding new recruits. These trait-related responses were not significant in the warmest sites and did not very across the precipitation gradient. Our results suggest that alpine species lack the competitive effect traits required to make their communities resistant to invasion by novel competitors under climate change.
Data from: Achromatic plumage brightness predicts stress resilience and social interactions in tree swallows (Tachycineta bicolor)
Theory suggests that signal honesty may be maintained by differential costs for high and low quality individuals. For signals that mediate social interactions, costs can arise from the way that a signal changes the subsequent social environment via receiver responses. These receiver-dependent costs may be linked with individual quality through variation in resilience to environmental and social stress. Here, we imposed stressful conditions on female tree swallows (Tachycineta bicolor) by attaching groups of feathers during incubation to decrease flight efficiency and maneuverability. We simultaneously monitored social interactions using an RFID network that allowed us to track the identity of every individual that visited each nest for the entire season. Prior to treatments, plumage coloration was correlated with baseline and stress-induced corticosterone. Relative to controls, experimentally challenged females were more likely to abandon their nest during incubation. Overall, females with brighter white breasts were less likely to abandon, but this pattern was only significant under stressful conditions. In addition to being more resilient, brighter females received more unique visitors at their nest box and tended to make more visits to other active nests. In contrast, dorsal coloration did not reliably predict abandonment or social interactions. Taken together, our results suggest that females differ in their resilience to stress and that these differences are signaled by plumage brightness, which is in turn correlated with the frequency of social interactions. While we do not document direct costs of social interaction, our results are consistent with models of signal honesty based on receiver-dependent costs.
Data from: Genomic signals of selection predict climate-driven population declines in a migratory bird
The ongoing loss of biodiversity caused by rapid climatic shifts requires accurate models for predicting species' responses. Despite evidence that evolutionary adaptation could mitigate climate change impacts, evolution is rarely integrated into predictive models. Integrating population genomics and environmental data, we identified genomic variation associated with climate across the breeding range of the migratory songbird, yellow warbler (Setophaga petechia). Populations requiring the greatest shifts in allele frequencies to keep pace with future climate change have experienced the largest population declines, suggesting that failure to adapt may have already negatively affected populations. Broadly, our study suggests that the integration of genomic adaptation can increase the accuracy of future species distribution models and ultimately guide more effective mitigation efforts.
Data from: Plant-soil feedback contributes to predicting plant invasiveness of 68 alien plant species differing in invasive status
<p>Understanding what species characteristics allow some alien plants to become invasive while others fail is critical to our understanding of community assembly processes. While many characteristics have been shown to predict plant invasiveness, the importance of plant-soil feedback (PSF) in invasions has been difficult to assess since individual studies include only a few species and use disparate methodology. We studied PSF of 68 invasive and non-invasive alien species in a single two-phase common garden experiment, and compared the relative importance of PSF, residence time, phylogenetic novelty and plant traits for plant invasiveness. Additionally, we explored relationships between PSF, residence time and phylogenetic novelty. PSF for seedling establishment, but not for biomass, was a significant predictor of invasive status, with invasive species having more positive PSF than non-invasive species. Its explanatory power was, however, much lower than that of specific leaf area, height, and residence time. Phylogenetically novel species experienced less negative PSF than species with native congeners, suggesting they benefit more from enemy release. PSF of non-invasive species, contrary to that of invasive species, was becoming more negative with increasing residence time. We demonstrated that PSF for seedling establishment plays a role in predicting plant invasiveness and is a better predictor than more commonly studied PSF for plant biomass. Other species traits, such as specific leaf area, however, predict plant invasiveness much better than the PSF.</p>
Data from: Flight of the bumble bee: buzzes predict pollination services
Multiple interacting factors drive recent declines in wild and managed bees, threatening their pollination services. Widespread and intensive monitoring could lead to more effective management of wild and managed bees. However, tracking their dynamic populations is costly. We tested the effectiveness of an inexpensive, noninvasive and passive acoustic survey technique for monitoring bumble bee behavior and pollination services. First, we assessed the relationship between the first harmonic of the flight buzz (characteristic frequency) and pollinator functional traits that influence pollination success using flight cage experiments and a literature search. We analyzed passive acoustic survey data from three locations on Pennsylvania Mountain, Colorado to estimate bumble bee activity. We developed an algorithm based on Computational Auditory Scene Analysis that identified and quantified the number of buzzes recorded in each location. We then compared visual and acoustic estimates of bumble bee activity. Using pollinator exclusion experiments, we tested the power of buzz density to predict pollination services at the landscape scale for two bumble bee pollinated alpine forbs (Trifolium dasyphyllum and T. parryi). We found that the characteristic frequency was correlated with traits known to affect pollination efficacy, explaining 30-52% of variation in body size and tongue length. Buzz density was highly correlated with visual estimates of bumble bee density (r = 0.97), indicating that acoustic signals are predictive of bumble bee activity. Buzz density predicted seed set in two alpine forbs when bumble bees were permitted access to the flowers, but not when they were excluded from visiting. Our results indicate that acoustic signatures of flight can be deciphered to monitor bee activity and pollination services to bumble bee pollinated plants. We propose that applications of this technique could assist scientists and farmers in rapidly detecting and responding to bee population declines.
Data from: Climate variability predicts thermal limits of aquatic insects across elevation and latitude
Janzen's extension of the climate variability hypothesis posits that increased seasonal variation at high latitudes should result in greater temperature overlap across elevations, and favor wider thermal breadths in temperate organisms compared to their tropical counterparts. We tested these predictions by measuring stream temperatures and thermal breadths (i.e. the difference between the critical thermal maximum and minimum) of 62 aquatic insect species from temperate (Colorado, USA) and tropical (Papallacta, Ecuador) streams spanning an elevation gradient of ca. 2000m. Temperate streams exhibited greater seasonal temperature variation and overlap across elevations than tropical streams, and as predicted, temperate aquatic insects exhibited broader thermal breadths than tropical insects. However, elevation had contrasting effects on patterns of thermal breadth. In temperate species, thermal breadth decreased with increasing elevation because CTMAX declined with elevation while CTMIN was similar across elevations. In tropical insects, by contrast, CTMAX declined less sharply than CTMIN with elevation, causing thermal breadth to increase with elevation. These macrophysiological patterns are consistent with the narrower elevation ranges found in other tropical organisms, and they extend Janzen's climate variability hypothesis to freshwater streams. Furthermore, because lowland tropical aquatic insects have the narrowest thermal breadths of any region, they may be particularly vulnerable to short-term extreme changes in stream temperature.
Predicting the strength of urban-rural clines in a Mendelian polymorphism along a latitudinal gradient
Cities are emerging as models for addressing the fundamental question of whether populations evolve in parallel to similar environments. Here, we examine the environmental factors that drive the evolution of parallel urban-rural clines in a Mendelian trait—the cyanogenic antiherbivore defense of white clover (Trifolium repens). Previous work suggested urban-rural gradients in frost and snow depth could drive the evolution of reduced hydrogen cyanide (HCN) frequencies in urban populations. Here, we sampled over 700 urban and rural clover populations across 16 cities along a latitudinal transect in eastern North America. In each population, we quantified changes in the frequency of genotypes that produce HCN, and in a subset of the cities we estimated the frequency of the alleles at the two genes (CYP79D15 and Li) that epistatically interact to produce HCN. We then tested the hypothesis that cold climatic conditions are necessary for the evolution of cyanogenesis clines by comparing the strength of clines among cities located along a gradient of winter temperatures and frost exposure. Overall, half of the cities exhibited urban-rural clines in the frequency of HCN, whereby urban populations evolved lower HCN frequencies. Clines did not evolve in cities with the lowest temperatures and greatest snowfall, supporting the hypothesis that snow buffers plants against winter frost and constrains the formation of clines. By contrast, the strongest clines occurred in the warmest cities where snow and frost are rare, suggesting that alternative selective agents are maintaining clines in warmer cities. Some clines were driven by evolution at only CYP79D15, consistent with stronger and more consistent selection on this locus than on Li. Together, our results demonstrate that urban environments often select for similar phenotypes, but different selective agents and targets underlie the evolutionary response in different cities.
Data from: Cross-biome patterns in soil microbial respiration predictable from evolutionary theory on thermal adaptation
Climate warming may stimulate microbial metabolism of soil carbon, causing a carbon cycle-climate feedback whereby carbon is redistributed from soil to atmospheric CO2. The magnitude of this feedback is uncertain, in part because warming-induced shifts in microbial physiology and/or community composition could retard or accelerate soil carbon losses. Here, we measure microbial respiration rates for soils collected from 22 sites in each of three years, at locations spanning boreal to tropical climates. Respiration was measured in the laboratory with standard temperatures, moisture and excess carbon substrate, to allow physiological and community effects to be detected independent from the influence of these abiotic controls. Patterns in respiration for soils collected across the climate gradient are consistent with evolutionary theory on physiological responses that compensate for positive effects of temperature on metabolism. Respiration rates per unit microbial biomass were as much as 2.6-times higher for soils sampled from sites with a mean annual temperature (MAT) of -2.0 versus 21.7ºC. Subsequent 100-day incubations suggested differences in the plasticity of the thermal response among microbial communities, with communities sampled from sites with higher MAT having a more plastic response. Our findings are consistent with adaptive metabolic responses to contrasting thermal regimes that are also observed in plants and animals. These results may help build confidence in soil carbon-climate feedback projections by improving understanding of microbial processes represented in biogeochemical models.
Data from: Personality predicts foraging site fidelity and trip repeatability in a marine predator
1. Animal populations are often comprised of both foraging specialists and generalists. For instance, some individuals show higher foraging site fidelity (spatial specialisation) than others. Such individual differences in degree of specialisation can persist over timescales of months or even years in long-lived animals, but the mechanisms leading to these different individual strategies are not fully understood. 2. There is accumulating evidence that individual variation in foraging behaviour is shaped by animal personality traits, such as boldness. Despite this, the potential for boldness to drive differences in the degree of specialisation is unknown. 3. In this study, we used novel object tests to measure boldness in black-legged kittiwakes (Rissa tridactyla) breeding at four colonies in Svalbard, and deployed GPS loggers to examine their at-sea foraging behaviour. We estimated the repeatability of foraging trips, and used a hidden Markov model to identify locations of foraging sites in order to quantify individual foraging site fidelity. 4. Across the breeding season, bolder birds were more repeatable than shy individuals in the distance and range of their foraging trips, and during the incubation period (but not chick rearing), bolder individuals were more site faithful. Birds exhibited these differences while showing high spatial similarity in foraging areas, indicating that site selection was not driven by personality-dependent spatial partitioning. 5. We instead suggest that a relationship between boldness and site fidelity may be driven by differences in behavioural flexibility between bold and shy individuals. Together, these results provide a potential mechanism by which widely reported individual differences in foraging specialisation may emerge.
Data from: Impacts of rainfall extremes predicted by climate-change models on major trophic groups in the leaf-litter arthropod community
1. Arthropods in the leaf-litter layer of forest soils influence ecosystem processes such as decomposition. Climate-change models predict both increases and decreases in average rainfall. Increased drought may have greater impacts on the litter arthropod community. In addition to affecting survival or behavior of desiccation-sensitive species, lower rainfall may indirectly lower abundances of consumers that graze drought-stressed fungi, with repercussions for higher trophic levels. 2. We tested the hypothesis that trophic structure will differ between the two rainfall scenarios. In particular, we hypothesized that densities of several broadly defined trophic groupings of arthropods would be lower under reduced rainfall. 3. To test this hypothesis we used sprinklers to impose two rainfall treatments during three growing seasons in roofed, fenced 14-m2 plots; and documented changes in abundance from initial, pre-treatment densities of 39 arthropod taxa. Experimental plots were subjected to either LOW (fortnightly) or HIGH (weekly) average rainfall based upon climate models and the previous 100 years of regional weekly averages. Unroofed open plots, our reference treatment (REF), experienced higher-than-average rainfall during the experiment. 4. The two rainfall extremes produced clear negative effects of lowered rainfall on major trophic groups. Broad categories of fungivores, detritivores and predators were more abundant in HIGH than LOW plots by the final year. Springtails (Collembola), which graze fungal hyphae, were 3x more abundant in the HIGH-rainfall treatment. Taxa of larger-bodied fungivores and detritivores, spiders (Araneae), and non-spider predators were 2x more abundant under HIGH rainfall. Densities of mites (Acari), which include fungivores, detritivores and predators, were 1.5x greater in HIGH rainfall plots. Abundances and community structure of arthropods were similar in REF and experimental plots, showing that effects of rainfall uncovered in the experiment are applicable to nature. 5. This pattern suggests that changes in rainfall will alter bottom-up control processes in a critical detritus-based food web of deciduous forests. Our results, in conjunction with other findings on the impact of desiccation on arthropods and fungal growth, suggest that drier conditions will depress densities of fungal consumers, causing declines in higher trophic levels, with possible impacts on soil processes and the larger forest food web.
Female mate preferences do not predict male sexual signals across populations
<p>New species can arise when female preferences and male sexual signals diverge across populations and thereby reduce mating between populations. Under this hypothesized mechanism for speciation, mate preferences and male signals should be correlated, but divergent, across populations. We evaluated this prediction using spadefoot toads (Spea multiplicata). We measured a sexually-selected male signal (call rate) for which female preferences are known to vary across populations in response to hybridization risk. Contrary to expectation, we found no correlation between male call rate and female preferences across populations. We discuss possible mechanisms of this pattern, including the effect of gene flow from heterospecifics on male call rate. Our results suggest that, even when populations vary in mating traits, the independent evolution of female preferences and male sexual signals might impede reproductive isolation between populations. </p>
Dynamic inferential NOx emission prediction model with delay estimation for SCR de-NOx process in coal-fired power plants
<p><span><span>The selective catalytic reduction (SCR) de</span><span>-</span><span>NO<sub>x</sub> </span><span>process in coal-fired power plants not only displays nonlinearity, large inertia, and time variation but also a lag in NO<sub>x</sub> analysis; </span><span>hence,</span><span> it is difficult to obtain an accurate model </span><span>that </span><span>can be used to control NH<sub>3</sub> injection </span><span>during changes in the </span><span>operating state. </span><span>In this work,</span><span> a novel dynamic inferential model with delay estimation was proposed for NO<sub>x</sub> emission prediction. First, k-nearest neighbour mutual information (knnMI) was used to estimate the time-delay of the descriptor variables, followed by reconstruction of the phase space of the model data. Second, multi-scale wavelet kernel partial least square (mwKPLS) was</span><span> used</span><span> to improve the prediction ability, </span><span>and this was followed by verification using </span><span>benchmark dataset experiments. Finally, the delay-time difference (DTD) method and feedback correction strategy </span><span>were </span><span>proposed to deal with the time variation of the SCR de</span><span>-</span><span>NO<sub>x</sub> process.</span> <span>Through the analysis of the </span><span>experimental field data </span><span>in the</span> <span>steady state, </span><span>the variable</span><span> state and </span><span>the </span>NO<sub>x</sub> analyser blowback process<span>, the results proved that</span><span> this dynamic model has </span><span>high prediction accuracy</span><span> during</span><span> state changes and can </span><span>realize</span><span> advance prediction of the NO<sub>x</sub> emission. </span></span></p>
Data from: Genotyping by sequencing and genome–environment associations in wild common bean predict widespread divergent adaptation to drought
Drought will reduce global crop production by >10% in 2050 substantially worsening global malnutrition. Breeding for resistance to drought will require accessing crop genetic diversity found in the wild accessions from the driest high stress ecosystems. Genome–environment associations in crop wild relatives reveal natural adaptation, and therefore can be used to identify adaptive variation. We explored this approach in the food crop Phaseolus vulgaris L., characterizing 86 geo-referenced wild accessions using Genotyping by Sequencing (GBS) to discover single-nucleotide-polymorphisms (SNPs). The wild beans represented Mesoamerica, Guatemala, Colombia, Ecuador/Northern Peru and Andean groupings. We found high polymorphism with a total of 22,845 SNPs across the 86 accessions loci that confirmed genetic relationships for the groups. As a second objective, we quantified allelic associations with a bioclimatic-based drought index using 10 different statistical models that accounted for population structure. Based on the optimum model, 115 SNPs in 90 regions, widespread in all 11 common bean chromosomes, were associated with the bioclimatic-based drought index. A gene coding for an Ankyrin repeat-containing protein and a phototropic-responsive NPH3 gene were identified as potential candidates. Genomic windows of 1Mb containing associated SNPs had more positive Tajima's D scores than windows without associated markers. This indicates that adaptation to drought, as estimated by bioclimatic variables, has been under natural divergent selection, suggesting that drought tolerance may be favorable under dry conditions but harmful in humid conditions. Our work exemplifies that genomic signatures of adaptation are useful for germplasm characterization, potentially enhancing future marker-assisted selection and crop improvement.
Data from: Integrating life history traits into predictive phylogeography
Predictive phylogeography seeks to aggregate genetic, environmental and taxonomic data from multiple species in order to make predictions about unsampled taxa using machine-learning techniques such as Random Forests. To date, organismal trait data have infrequently been incorporated into predictive frameworks due to difficulties inherent to the scoring of trait data across a taxonomically broad set of taxa. We refine predictive frameworks from two North American systems, the inland temperate rainforests of the Pacific Northwest (PNW) and the Southwestern Aridlands (SWAL), by incorporating a number of organismal trait variables. Our results indicate that incorporating life history traits as predictor variables improves the performance of the supervised machine-learning approach to predictive phylogeography, especially for the SWAL system, in which predictions made from only taxonomic and climate variables meets only moderate success. In particular, traits related to reproduction (e.g., reproductive mode; clutch size) and trophic level appear to be particularly informative to the predictive framework. Predictive frameworks offer an important mechanism for integration of organismal trait, environmental data, and genetic data in phylogeographic studies.
Phenological responses to climate warming in temperate moths and butterflies: species traits predict future changes in voltinism
Changes in the number of generations per year (voltinism) have been among the most common phenological responses to climate warming in insects inhabiting seasonal environments. Nevertheless, numerous species have maintained univoltine (one generation per year) phenology with increasing temperatures, indicating the involvement of phylogenetic, ecological or some other constraints on phenological change. I examined geographic variation in voltinism in moths and butterflies of Northern Europe to identify species traits that might predispose species to univoltine/multivoltine phenology. I focused on species with a wide latitudinal distribution range (15 degrees as a minimum) which makes it unlikely that constraints imposed by season length could preclude multivoltinism across their distribution. Almost half of the 731 moth and butterfly species considered appear to have a single generation throughout their entire European range. A univoltine life-cycle across a wide latitudinal gradient suggests the presence of some constraint that makes additional generations either impossible or at least strongly disadvantageous, which will unlikely change with future climate warming. The scattered distribution of univoltine and multivoltine species across the lepidopteran phylogeny indicates that phylogenetic constraints are not strongly limiting changes in voltinism, and the trait is open to ecologically-driven adaptive evolution. My data show that species with one generation per year are generally larger than multivoltine species, but size forms no absolute constraint to having multiple generations per year. Obligately univoltine species dominate among egg and adult overwinterers (life-histories typical of so-called spring-feeders), whereas species with capacity for multiple generations prevail among pupal overwinterers. Multivoltinism is also infrequent among species feeding on grasses, particularly in endophagous grass-feeders. Larval diet breadth has no discernible effect on voltinism. Given the diverse ecological consequences of voltinism and its changes, accounting for the species' capacity for multivoltinism may be a key to address future challenges in biodiversity conservation and pest management.
Strong species differences in life-history do not predict oxidative stress physiology or sensitivity to an environmental oxidant
1. Species typically align along a fast-slow life-history continuum, yet it is not clear to what extent oxidative stress physiology can be integrated with this continuum to form a 'pace-of-life syndrome', especially so in invertebrates. This is important, given the assumed role of oxidative stress in mediating life-history trade-offs, and the prediction that species with a faster pace should be more vulnerable to oxidative stress. 2. We tested whether a species' life-history pace, here represented by its growth rate, can predict species-level differentiation in physiology and sensitivity to oxidative stress. Therefore, we exposed four species of Ischnura damselflies that strongly align along a fast-slow life-history continuum to different levels of ultraviolet (UV) radiation. We measured an extended set of physiological traits linked to the pace-of-life: standard metabolic rate (SMR), oxidative stress physiology (antioxidant enzymes and oxidative damage), and defence/condition traits (investment in immune function, energy storage, and structural defence). 3. Despite strong species differences in growth rate and physiology, growth rate did not predict species-level differentiation in physiology. Hence there was no support for the integration of metabolic rate, oxidative stress physiology or defence/condition traits into a species-level syndrome. 4. UV exposure affected nearly all traits: it reduced growth rate and increased metabolic rate, affected all oxidative stress physiology traits and increased the two defence traits (immune function, and melanin content). Nevertheless, the pace-of-life based on growth rate did not predict sensitivity to UV. Instead, the observed pattern of investment in structural UV defence (melanin) might have reduced the need for enzymatic antioxidant defence, this way potentially decoupling the covariation between the life-history pace and oxidative stress physiology. 5. The absence of an integrated axis of life-history and physiological variation indicates no major constraints for the evolution of these traits among the studied damselfly species. Our study highlights that ecological differences between species may decouple covariation between species' life-history pace and their physiology, as well as their sensitivity to environmental stressors. 30-Mar-2020
Data from: Can avian functional traits predict cultural ecosystem services?
<ol> <li><span>The functional trait diversity of species assemblages can predict the provision of ecosystem services such as pollination and carbon sequestration, but it is unclear whether the same trait-based framework can be applied to identify the factors that underpin cultural ecosystem services and disservices. </span></li> <li><span>To explore the relationship between traits and the contribution of species to cultural ecosystem services and disservices, we conducted 404 questionnaire surveys with birdwatchers and local residents in Guanacaste, Costa Rica.</span></li> <li><span>We used an information-theoretic approach to identify which of 20 functional traits for 199 Costa Rican bird species best predicted their cultural ecosystem service scores related to birdwatching, acoustic aesthetics, education and local identity, as well as disservices (e.g., harm to crops). </span></li> <li><span>We found that diet was the most important variable explaining perceptions of cultural ecosystem service and disservice providers. Aesthetic traits such as plumage colour and pattern were important in explaining birdwatching scores. We also found people have a high affinity for forest-affiliated birds. </span></li> <li><span>The insight that functional traits can explain variation among cultural perspectives on values derived from birds offers a first step towards a trait-based system for understanding the species attributes that underpin cultural ecosystem services and disservices.</span></li> </ol>
Data from: Microclimate predicts within-season distribution dynamics of montane forest birds
Aim Climate changes are anticipated to have pervasive negative effects on biodiversity and are expected to necessitate widespread range shifts or contractions. Such projections are based upon the assumptions that (1) species respond primarily to broad-scale climatic regimes, or (2) that variation in climate at fine spatial scales is less relevant at coarse spatial scales. However, in montane forest landscapes, high degrees of microclimate variability could influence occupancy dynamics and distributions of forest species. Using high-resolution bird survey and under-canopy air temperature data, we tested the hypothesis that the high vagility of most forest bird species combined with the heterogeneous thermal regime of mountain landscapes would enable them to adjust initial settlement decisions to track their thermal niches. Location Western Cascade Mountains, Oregon, USA. Methods We used dynamic occupancy models to test the degree to which microclimate affects the distribution patterns of forest birds in a heterogeneous mountain environment. In all models we statistically accounted for vegetation structure, vegetation composition and potential biases due to imperfect detection of birds. We generated spatial predictions of forest bird distributions in relation to microclimate and vegetation structure. Results Fine-scale temperature metrics were strong predictors of bird distributions; effects of temperature on within-season occupancy dynamics were as large or larger (1–1.7 times) than vegetation effects. Most species (86.7%) exhibited apparent within-season occupancy dynamics. However, species were almost as likely to be warm associated (i.e., apparent settlement at warmer sites and/or vacancy at cooler sites; 53.3% of species) as cool associated (i.e., apparent settlement at cooler sites and/or vacancy at warmer sites; 46.7% of species), suggesting that microclimate preferences are species specific. Main conclusions High-resolution temperature data increase the quality of predictions about avian distribution dynamics and should be included in efforts to project future distributions. We hypothesize that microclimate-associated distribution patterns may reflect species' potential for behavioural buffering from climate change in montane forest environments.
Predicted lake dissolved organic carbon at a global scale
<p>The pool of dissolved organic carbon (DOC), is one of the main regulators of the ecology and biogeochemistry of inland water ecosystems, and an important loss term in the carbon budgets of land ecosystems. We used a novel machine learning technique and global databases to test if and how different environmental factors contribute to the variability of <em>in situ</em> DOC concentrations in lakes. In order to estimate DOC in lakes globally we predicted DOC in each lake with a surface area larger than 0.1 km<sup>2</sup>. Catchment properties and meteorological and hydrological features explained most of the variability of the lake DOC concentration, whereas lake morphometry played only a marginal role. The predicted average of the global DOC concentration in lake water was 3.88 mg L<sup>-1</sup>. The global predicted pool of DOC in lake water was 729 Tg from which 421 Tg was the share of the Caspian Sea. The results provide global-scale evidence for ecological, climate and carbon cycle models of lake ecosystems and related future prognoses.</p>
Prediction items
Orenburg region. Excavations in 2022. Fragment of the MMK1B1 object. Researcher S.V. Sirotin. Fortune-telling stones and a fossil shell from the burial of a fortune teller girl. Early Iron Age. Chronology: IV century BC. Sarmatian culture. Оренбургский район. Раскопки 2022 года. Фрагмент объекта ММК1Б1. Исследователь С.В. Сиротин. Камни для гадания и ископаемая раковина из захоронения девушки-гадалки. Ранний железный век. Хронология: IV в. до н.э. Сарматская культура. Source: Objaverse 1.0 / Sketchfab
ScienceDex guides
Understand access before you commit
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.