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19,493 results for “Populism”
Critical thermal maxima of freshwater larvae (Serratella ignita and Baetis Rhodani), Scotland, from 10 populations at different times
<p>The dataset includes a collection of Critical Thermal maxima values (CTmax) for 676 <em>Serratella ignita </em>and 155 <em>Baetis rhodani</em> specimens, sampled in 4 Scottish lakes in 2016 and 2017. The dataset indicates date of collection for each specimen, location, and body size. </p>
Figures 4–5. Phylogenetic tree for Aedes vexans populations constructed from 395 in Global phylogeography of the flood mosquito, Aedes vexans (Diptera: Culicidae), from mitochondrial DNA
Figures 4–5. Phylogenetic tree for Aedes vexans populations constructed from 395 haplotypes from the COI gene by using Bayesian Inference, BI (4) and Maximum Likelihood, ML (5). The evolutionary history for both analyses was inferred by using the GTR + G model, as suggested by jModelTest version 2.1.10. The BI tree was obtained by using 2-million generations, while the ML used 1,000 replicas. For BI, the support of the branches is indicated by the subsequent probability values, while for ML the bootstrap values are shown. Numbers in blue represent sequences from the A. nipponii subspecies. In both figures the colors below denote the continents and their respective countries: (z) America (Canada and USA) + Europe (Turkey); (z) Asia (China, India, Japan, Singapore and South Korea); (z) Europe (Sweden and Belgium) + Asia (China); (z) Eurasia (Romania, Sweden, Belgium, Russia, Kosovo, the Netherlands, China, Spain, Germany, Iran, Austria and Hungary); (z) Africa (South Africa); (z) America (USA) + Africa (South Africa).
Population genomic evidence that stream networks structure genetic diversity in the narrowly endemic patch-nosed salamander (Urspelerpes brucei)
<p>Described in 2009, the Patch-nosed Salamander (<em>Urspelerpes brucei</em>) is a miniature species of lungless salamander with a geographic range of only ~45 km<sup>2</sup>. This species is endemic to the foothills of the Appalachian Mountains in extreme northeastern Georgia and northwestern South Carolina. The Tugaloo River—a waterway of some 50 m in width that forms the political boundary between the two states—bisects the tiny range of <em>U. brucei</em> and likely acts as a barrier to gene flow. Using RADcap data and a suite of complementary population genomic analyses, we evaluated the role that this river and its tributaries may play in enabling and/or interrupting gene flow among populations of <em>U. brucei</em>, and we investigated patterns of within-population and between-population genetic variation. Our results revealed a general pattern of isolation-by-stream distance and indicated that a population separated by the Tugaloo River is moderately more differentiated than what is explainable by stream distance alone. Unique in both its physiography and geologic history, this region in which <em>U. brucei</em> lives also harbors more than a dozen other species of lungless salamanders. Therefore, the genetic patterns that we have elucidated may have larger implications for differentiation among populations of other species with similar dispersal abilities.</p>
Associated Dataset for Genome-wide DNA methylation patterns in bumble bee (Bombus vosnesenskii) populations from spatial-environmental range extremes
<p>The dataset contains the final methylation call set (n=14,627,533), variant calling file for population genomics analyses, analysis codes/scripts, and other associated files related to the research (Constitutive and variable patterns of genome-wide DNA methylation in populations from spatial-environmental range extremes of the bumble bee <em>Bombus vosnesenskii)</em>. Raw WGBS reads generated in this study have been deposited and are currently available at the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) under NCBI BioProject PRJNA956115.</p>
Data from: Species-specific ecological traits, phylogeny, and geography underpin vulnerability to population declines for North American birds
<p>Species declines and extinctions characterize the Anthropocene. Determining species vulnerability to decline, and where and how to mitigate threats, are paramount for effective conservation. We hypothesized that species with shared ecological traits also share threats, and therefore may experience similar population trends. Here, we used a Bayesian modeling framework to test whether phylogeny, geography, and 22 ecological traits predict regional population trends for 380 North American bird species. Groups like blackbirds, warblers, and shorebirds, as well as species occupying Bird Conservation Regions at more extreme latitudes in North America, exhibited negative population trends, while groups such as ducks, raptors, and waders, as well as species occupying more inland Bird Conservation Regions, exhibited positive trends. Specifically, we found that in addition to phylogeny and breeding geography, multiple ecological traits contributed to explaining variation in regional population trends for North American birds. Furthermore, we found that regional trends and the relative effects of migration distance, phylogeny, and geography differ between shorebirds, songbirds, and waterbirds. Our work provides evidence that multiple ecological traits correlate with North American bird population trends, but that the individual effects of these ecological traits in predicting population trends often vary between different groups of birds. Moreover, our results reinforce the notion that variation in avian population trends is controlled by more than phylogeny and geography, where closely-related species within one region can show unique population trends due to differences in their ecological traits. We recommend that regional conservation plans, i.e. one-size-fits-all plans, be implemented only for bird groups with population trends under strong phylogenetic or geographic controls. We underscore the need to develop species-specific research and management strategies for other groups, like songbirds, that exhibit high variation in their population trends and are influenced by multiple ecological traits.</p>
Fig. 1 in Morphometric characterization of adult Artemia (Crustacea: Branchiopoda) populations from costal and inland Tunisian salt lakes
Fig. 1. Scatterplot of the first two canonical discriminant functions (group centroids) resulting from the discriminant analysis applied to morphological traits and morphometric data for the studied populations, using the origin of each population as a separation factor. Abbreviations for populations are explained in Table 1.
Effects of local density dependence and temperature on the spatial synchrony of marine fish populations
<ol> <li><span>Disentangling empirically the many processes affecting spatial population synchrony is a challenge in population ecology. Two processes that could have major effects on the spatial synchrony of wild population dynamics are density dependence and variation in environmental conditions like temperature. Understanding these effects is crucial for predicting the effects of climate change on local and regional population dynamics.</span></li> <li><span>We quantified the direct contribution of local temperature and density dependence to spatial synchrony in the population dynamics of nine fish species inhabiting the Barents Sea. First, we estimated the degree to which the annual spatial autocorrelations in density are influenced by temperature. Second, we estimated and mapped the local effects of temperature and strength of density dependence on annual changes in density. Finally, we measured the relative effects of temperature and density dependence on the spatial synchrony in changes in density. </span></li> <li><span>Temperature influenced the annual spatial autocorrelation in density more in species with greater affinities to the benthos and to warmer waters. Temperature correlated positively with changes in density in the eastern Barents Sea for most species. Temperature had a weak synchronising effect on density dynamics, while increasing strength of density dependence consistently desynchronised the dynamics. </span></li> <li><span>Quantifying the relative effects of different processes affecting population synchrony is important to better predict how population dynamics might change when environmental conditions change. Here, high degrees of spatial synchrony in the population dynamics remained unexplained by local temperature and density dependence, confirming the presence of additional synchronizing drivers, such as trophic interactions or harvesting. </span></li> </ol>
figure 1 in Spatial genetic structure in the Eurasian otter (Lutra lutra) meta-population from its core range in Italy
figure 1 The area surveyed for collection of otter samples (40° 40' N, 39° 37' N). Red spots indicate the location of the collected samples. The blue lines highlight the main rivers (order 1) and their tributaries (order 2, 3 and 4 according to waterway hierarchy). The continuous red lines represent regional boundaries. In the inset, the current otter distribution (inferred from Balestrieri et al., 2016, modified) is reported in orange and the study area is defined by the black bold square.
figure 4 in Spatial genetic structure in the Eurasian otter (Lutra lutra) meta-population from its core range in Italy
figure 4 Principal Component Analysis (pca) performed on microsatellite genotypes (dots). Circles show the well-defined spatial groups. A) pca according to the belonging of genotypes to the six river basins: the Cilento basin (green dots); the Agri basin (pink dots); the Sinni basin (blue dots); the Lao basin (red dots); the Basento basin (orange dots); the Abatemarco basin (violet dots); black dots indicate the samples outside of the main river basins. Dashed line indicates geographically contiguous but genetically different genotypes. B) pca according to clusters inferred by STRUCTURE: genotypes assigned unambiguously to K2 (green dots), to K3 (yellow dots), to K5 (violet dots). Grey dots represent samples with mixed genotypes assignable to K1 and K4.
figure 3 in Spatial genetic structure in the Eurasian otter (Lutra lutra) meta-population from its core range in Italy
figure 3 Genetic structure and distribution of the Italian otter genotypes in the study area. A) Estimated population structure based on the analysis of 11 microsatellite loci according to STRUCTURE (K = 5). Each bar represents a sample analysed. B) Geographic visualisation of genotypes in the study area performed using QGIS 3.4.1 software with base layers acquired from http://www.pnc.miniambiente. it/. Each circle represents a sample analysed. The colours indicate the percentage of assignment of an individual to each cluster: in blue, K1; in green, K2; in orange, K3; in red, K4; in violet, K5. The bold blue lines highlight the main rivers, while the tiny blue lines show all other waterways.
figure 6 Mantel test for A in Spatial genetic structure in the Eurasian otter (Lutra lutra) meta-population from its core range in Italy
figure 6 Mantel test for A) the correlation between geographic distance (GGDsq) and genetic distance (LinGD) (Rxy = 0.264, P = 0.0001) and for B) the correlation between resistance distance (a measure of ecological distance) (ECO500) and LinGD (Rxy = 0.217, P = 0.0001).
Acclimation capacity of critical thermal maximum varies among populations: Consequences for estimates of vulnerability
<p>Adaptive plasticity in thermal tolerance traits may buffer organisms against changing temperatures, making such responses of particular interest in the face of global climate change. Although population variation is integral to the evolvability of this trait, many studies inferring proxies of physiological vulnerability from thermal tolerance traits extrapolate data from one or few populations to represent the species. Estimates of physiological vulnerability can be further complicated by methodological effects associated with experimental design. We evaluated how populations varied in their acclimation capacity (i.e., the magnitude of plasticity) for critical thermal maximum (CT<sub>max</sub>) in two species of tailed frogs (Ascaphidae), cold-stream specialists. We used the estimates of acclimation capacity to infer physiological vulnerability to future warming. We performed CT<sub>max</sub> experiments on tadpoles from 14 populations using a fully factorial experimental design of two holding temperatures (8℃, 15℃) and two experimental starting temperatures (8℃, 15℃). This design allowed us to investigate the acute effects of transferring organisms from one holding temperature to a different experimental starting temperature, as well as fully acclimated responses by using the same holding and starting temperature. We found that most populations exhibited beneficial acclimation, where CT<sub>max</sub> was higher in tadpoles held at a warmer temperature, but populations varied markedly in magnitude of the response and the inferred physiological vulnerability to future warming. We also found that the response of transferring organisms to different starting temperatures varied substantially among populations, although accounting for acute effects did not greatly alter estimates of physiological vulnerability at the species-level or for most populations. These results underscore the importance of sampling widely among populations when inferring physiological vulnerability, as population variation in acclimation capacity and thermal sensitivity may be critical when assessing vulnerability to future warming. </p>
Numerical response of predator to prey: Dynamic interactions and population cycles in Eurasian lynx and roe deer
<p>The dynamic interactions between predators and their prey have two fundamental processes; numerical and functional responses. Numerical response is defined as predator growth rate as a function of prey density or both prey and predator densities [dP/dt = f(N, P)]. Functional response is defined as the kill rate by an individual predator being a function of prey density or prey and predator densities combined. Although there are relatively many studies on the functional response in mammalian predators, numerical response remains poorly documented. We studied numerical response of Eurasian lynx (<em>Lynx lynx</em>) to various densities of its primary prey species, roe deer (<em>Capreolus</em> <em>capreolus</em>), and to itself (lynx). We exploited an unusual natural situation, spanning three decades where lynx, after a period of absence in central and southern Sweden, during which roe deer populations had grown to high densities, subsequently recolonized region after region, from north to south. We divided the study area into seven regions, with increasing productivity from north to south. We found strong effects of both roe deer density and lynx density on lynx numerical response. Thus, both resources and intraspecific competition for these resources are important to understand the lynx population dynamic. We built a series of deterministic lynx–roe deer models and applied them to the seven regions. We found a very good fit between these Lotka-Volterra-type models and the data. The deterministic models produced almost cyclic dynamics or dampened cycles in five of the seven regions. Thus, we documented population cycles in this large-predator-large-herbivore system, which is rarely done. The amplitudes in the dampened cycles decreased towards the south. Thus, the dynamics between lynx and roe deer became more stable with increasing carrying capacity for roe deer, which is related to higher productivity in the environment. This increased stability could be explained by variation in predation risk, where human presence can act as prey refugia, and by a more diverse prey guild that will weaken the direct interaction between lynx and roe deer.</p>
African elephant rumbles differ between populations and sympatric social groups: possible consequences of vocal learning?
<p>Vocal production learning, the ability to modify vocalizations in response to sounds made by others, was a critical prerequisite for the evolution of human speech but is rare among mammals. Elephants have exhibited this ability in captivity, yet its function in wild elephants remains unknown. Female African savannah elephants (<em>Loxodonta</em> <em>africana</em>) live in large societies with nested tiers of association in which vocal signatures of group identity could facilitate recognition of distant social affiliates. Vocal production learning allows the formation of such group signatures in many species and can also cause vocal differentiation between populations. However, the existence of vocal signatures of social group or population in elephants was unexplored. We recorded multiple social groups of wild elephants in two Kenyan populations (Samburu and Amboseli) and used random forest models to determine if calls could be assigned to individual callers, family groups, bond groups (collections of family groups), or populations based on acoustic structure. Calls were assigned by a random forest model to individual callers and populations with better-than-chance accuracy, demonstrating population-level divergence in vocalization structure. While random forest models failed to accurately assign calls to family or bond group, calls from the same family or bond group were significantly more similar (higher proximity scores) than calls from different groups, suggesting the existence of group signatures as well. We discuss possible drivers of this differentiation and argue that vocal learning is the most likely explanation for population- and group-level variation in elephants. The existence of group signatures suggests recognition of large numbers of individuals as a possible adaptive function for vocal production learning in elephants.</p>
Leveraging the strengths of citizen science and structured surveys to achieve scalable inference on population size
<ol> <li>Population size is a key metric for management and policy decisions, yet wildlife monitoring programs are often limited by the spatial and temporal scope of surveys. In these cases, citizen science data may provide complementary information at higher resolution and greater extent.</li> <li>We present a case study demonstrating how data from the eBird citizen science program can be combined with regional monitoring efforts by the U.S. Fish and Wildlife Service to produce high-resolution estimates of golden eagle abundance. We developed a model that uses aerial survey data from the western United States to calibrate high-resolution annual estimates of relative abundance from eBird. Using this model, we compared regional population size estimates based on the calibrated eBird information to those based on aerial survey data alone.</li> <li>Population size estimates based on the calibrated eBird information had strong correspondence to estimates from aerial survey data in two out of four regions, and population trajectories based on the two approaches showed high correlations.</li> <li>We demonstrate how the combination of citizen science data and targeted surveys can be used to (a) increase the spatial resolution of population size estimates, (b) extend the spatial extent of inference, and (c) predict population size beyond the temporal period of surveys. Findings based on this case study can be used to refine policy metrics used by the U.S. Fish and Wildlife Service and inform permitting regulations (e.g., mortality/harm associated with wind energy development).</li> <li> <em>Policy implications</em>. Our results demonstrate the ability of citizen science data to complement targeted monitoring programs and improve the efficacy of decision frameworks that require information on population size or trajectory. After validating citizen science data against survey-based benchmarks, agencies can harness strengths of citizen science data to supplement information needs and increase the resolution and extent of population size predictions.</li> </ol>
Capacity for recovery in Bornean orangutan populations if both forest fragmentation and offtake are limited
<p>Spatial layers to run RangeShifter for orangutan populations across Borneo for the three subspecies (<em>Pongo pygmaeus pygmaeus, P. p. wurmbii </em>and <em>P. p. morio</em>).</p> <p>Each subspecies has four associated layers, defined for two fragmentation scenarios Status quo (current levels of fragmentation) and Extreme fragmentation (fragments less than 5,000 ha removed). 1). Habitat, defines the 1/b values for populations intersecting the specific habitat types. 2). Patches, delineates discrete areas of suitable orangutan habitat, each with a unique ID. 3). Resistance, accumulative cost to an orangutan of moving across that landscape and 4). Start_patches, specifies which patches should be initialised with orangutans present at year 0 of the model run. </p>
Supporting information for "Few-Shot Learning Enables Population-Scale Analysis of Leaf Traits in Populus trichocarpa"
<p>Raw VCF file for <em>Populus trichocarpa</em> V4 SNPs - Biallelic SNP variants were called for 1492 Populus trichocarpa genotypes using GATK Version 4.0 software.</p>
Monitoring wildlife population trends with sample counts: A case study on the Alpine ibex (Capra ibex)
<p><span>Monitoring population dynamics is of fundamental importance in conservation but assessing trends in abundance can be costly, especially in large and rough areas. Obtaining trend estimations from counts performed in only a portion of the total area (sample counts) can be a cost-effective method to improve the monitoring and conservation of species difficult to count. </span></p> <p><span>We tested the effectiveness of sample counts in monitoring population trends of wild animals, using as a model population the Alpine ibex (<em>Capra ibex</em>) in the Gran Paradiso National Park (Italy), both with computer simulations and using historical count data collected over the last 65 years. Despite sample counts failed to correctly estimate the true population abundance, sampling half of the target area could reliably monitor the trend of the target population. In case of strong changes in abundance, an even lower proportion of the total area could be sufficient to identify the direction of the population trend. However, when there is a high yearly trend variability, the required number of samples increases and even counting in the entire area can be ineffective to detect population trends. The effect of other parameters, such as which portion of the area is sampled and detectability, was lower, but these should be tested case by case. </span></p> <p><span>Sample counts could therefore constitute a viable alternative to assess population trends, allowing for important, cost-effective improvements in the monitoring of wild animals of conservation interest. </span></p>
Fig. 5 in Calling songs of sympatric and allopatric populations of Cicada barbara and C. orni (Hemiptera: Cicadidae) on the Iberian Peninsula
Fig. 5. Scores of the first two PCA components extracted from a data matrix, which was composed of 9 acoustic variables measured for 158 individuals of Cicada barbara (Cb) and C. orni (Co) occurring allopatrically (allop) and sympatrically (symp).
Fig. 7 in Patterns of acoustic and morphometric variation in species of genus Tettigettalna (Hemiptera: Cicadidae): Sympatric populations show unexpected differences
Fig. 7. Box plot of the morphometric traits that differed statistically (Mann-Whitney, p <0.0039) between allopatric (Allo) and sympatric (Sym) populations of A – Tettigettalna argentata and B – Tettigettalna mariae. All measurements are in millimetres. See Table 2 for description of the morphometric traits.
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.