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32 results for “Species relative abundance”
Modelled relative abundance of bird species in Britain and Ireland 2007-2011
<p>This data package describes the modelled relative (not absolute) abundance of Carrion Crow (<em>Corvus corone</em>), Magpie (<em>Pica pica</em>), Buzzard (<em>Buteo buteo</em>), Kestrel (<em>Falco tinnunculus</em>) and Red Kite (<em>Milvus milvus</em>) in Britain and Ireland.</p> <p>This was used to produce Bird Atlas 2007-2011 <a href="https://app.bto.org/mapstore/StoreServlet" target="_blank" rel="noopener">maps</a> of relative abundance at a tetrad (2x2km) resolution. </p> <p>Acknowledgement: These data originate from the Bird Atlas 2007–11 project which was run by the BTO in partnership with BirdWatch Ireland and the Scottish Ornithologists’ Club. We are grateful to the thousands of volunteers who undertook and organised the fieldwork for the atlas.</p> <p>Please refer to the metadata for a more detailed description, and for information on dataset usage.</p> <p>v1.3 update: added Red Kite (<em>Milvus milvus</em>) and put the species lookup back in.</p> <p><em>If you would like access to this data for another species, please get in touch with BTO via email: datarequests@bto.org</em></p> <p>........................................................................................</p> <p>BTO would also greatly appreciate if you could fill out <a href="https://forms.gle/DCc58VXpdmqnTmTk8" target="_blank" rel="noopener">this very short form</a> to tell us how you intend to use these data. Thanks in advance!</p>
Data for: Assortative mating in an ecological context: Effects of mate choice errors and relative species abundance on the frequency and asymmetry of hybridization
<p><span>The frequency and asymmetry of mixed-species mating set the initial stage for the ecological and evolutionary implications of hybridization. How such patterns of mixed-species mating, in turn, are influenced by the combination of mate choice errors and relative species abundance remain largely unknown. We develop a mathematical model that generates predictions for how relative species abundances and mate choice errors affect hybridization patterns. When mate choice errors are small (<5%) the highest frequency of hybridization occurs when one of the hybridizing species is at low abundance, but when mate choice errors are high (>5%) the highest hybridization frequency occurs when species occur in equal proportions. Furthermore, females of the less abundant species are overrepresented in mixed-species matings. We compare our theoretical predictions with empirical data on naturally hybridizing Ficedula flycatchers and find that hybridization is highest when the two species occur in equal abundance, implying rather high mate choice errors. We discuss ecological and evolutionary implications of our findings and encourage future work on hybrid zone dynamics that take demographic aspects, such as relative species abundance, into account.</span></p>
Fig. 1. Photographs taken with a in Diptilomiopus floridanus (Acari: Eriophyoidea: Diptilomiopidae): its distribution and relative abundance with other eriophyoid species on dooryard, varietal block, and commercial citrus in Florida
Fig. 1. Photographs taken with a scanning electron microscope of the new species of Diptilomiopus floridanus Craemer & Amrine on Florida citrus. (A) Dorsal view of prodorsum, legs, and well developed chelicerae. (B) Dorsal view of the mite. (C) Lateral view of the mite. (D) Dorso–lateral view of the mite with extended, downward gnathosome.
Data for: Assortative mating in an ecological context: Effects of mate choice errors and relative species abundance on the frequency and asymmetry of hybridization
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Congeneric predators fill discrete niches created by the relative abundances of their prey species
To what degree is niche partitioning driven by underlying patterns in resources such as food, rather than by competition itself? Do discrete niches exist? We address these questions in the context of Cooper's and Sharp-shinned Hawks, two broadly sympatric, North American, bird-eating raptors in the genus Accipiter. We find that the resource base, as quantified by body masses of birds at bird feeders, is approximately lognormal (smallest birds are most abundant), with lesser modes (peaks) in abundance at larger body mass. The predators appear to exploit peaks in the resource base, with Sharp-shinned Hawks focusing on small prey items (median of 26.5 g), and Cooper's Hawks taking prey from the two most abundant peaks (both the small body mass peak and a lesser peak at medium body mass ~90g). We tested the ability of citizen scientists to distinguish these notoriously similar species, and we determined the influence of potential false positive detections on our conclusions. We find that citizen scientists struggle to distinguish these predators from one another, and 18% of Cooper's Hawks were identified as Sharp-shinned Hawks, while 27% of Sharp-shinned Hawks were identified as Cooper's Hawks. Yet, simulations show that this uncertainty did not jeopardize our qualitative conclusions.
Figure. Relative abundance of species in the Phyllonorycter parasitoid complex. in Hymenopterous parasitoids associated with Phyllonorycter coryli (Nic.) and Phyllonorycter nicellii (Stt.) on hazel in Poland
Figure. Relative abundance of species in the Phyllonorycter parasitoid complex.
Bayesian species distribution models integrate presence-only and presence-absence data to predict deer distribution and relative abundance
<p>Using geospatial data of wildlife presence to predict a species distribution across a geographic area is among the most common tools in management and conservation. The collection of high-quality presence-absence data through structured surveys is, however, expensive, and managers usually have access to larger amounts of low-quality presence-only data collected by citizen scientists, opportunistic observations, and culling returns for game species. Integrated Species Distribution Models (ISDMs) have been developed to make the most of the data available by combining the higher-quality, but usually scarcer and more spatially restricted presence-absence data, with the lower quality, unstructured, but usually more extensive presence-only datasets. Joint-likelihood ISDMs can be run in a Bayesian context using INLA (Integrated Nested Laplace Approximation) methods that allow the addition of a spatially structured random effect to account for data spatial autocorrelation. Here, we apply this innovative approach to fit ISDMs to empirical data, using presence-absence and presence-only data for the three prevalent deer species in Ireland: red, fallow and sika deer. We collated all deer data available for the past 15 years and fitted models predicting distribution and relative abundance at a 25 km<sup>2</sup> resolution across the island. Models' predictions were associated to spatial estimates of uncertainty, allowing us to assess the quality of the model and the effect that data scarcity has on the certainty of predictions. Furthermore, we checked the performance of the three species-specific models using two datasets, independent deer hunting returns and deer densities based on faecal pellet counts. Our work clearly demonstrates the applicability of spatially-explicit ISDMs to empirical data in a Bayesian context, providing a blueprint for managers to exploit unexplored and seemingly unusable data that can, when modelled with the proper tools, serve to inform management and conservation policies.</p>
Bayesian species distribution models integrate presence-only and presence-absence data to predict deer distribution and relative abundance
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Congeneric predators fill discrete niches created by the relative abundances of their prey species
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Data from msGBS: A new high-throughput approach to quantify the relative species abundance in root samples of multi-species plant communities
<p>Plant interactions are as important belowground as aboveground. Belowground plant interactions are however inherently difficult to quantify, as roots of different species are difficult to disentangle. Although for a couple of decades molecular techniques have been successfully applied to quantify root abundance, root identification and quantification in multi-species plant communities remains particularly challenging.</p> <p><span><span><span><span><span><span><span><span><span><span><span>Here we present a novel methodology, multi-species Genotyping By Sequencing (msGBS), as a next step to tackle this challenge. First, a multi-species meta-reference database containing thousands of gDNA clusters per species is created from GBS derived High Throughput Sequencing (HTS) reads. Second, GBS derived HTS reads from multi-species root samples are mapped to this meta-reference which, after a filter procedure to increase the taxonomic resolution, allows the parallel quantification of multiple species. </span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span>The msGBS signal of 111 mock-mixture root samples, with up to 8 plant species per sample, was used to calculate the within-species abundance. Optional subsequent calibration yielded the across-species abundance. The within- and across-species abundances highly correlated (R<sup>2 </sup>range 0.72-0.94 and 0.85-0.98, respectively) to the biomass-based species abundance. Compared to a qPCR based method which was previously used to analyze the same set of samples, msGBS provided similar results. Additional data on 11 congener species groups within 105 natural field root samples showed high taxonomic resolution of the method. </span></span></span></span></span></span></span></span></span></span></span><span><span><span><span><span><span><span><span><span><span><span></span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span><a>msGBS is highly scalable in terms of sensitivity and species numbers within samples, which is a major advantage compared to the qPCR method and advances our tools to reveal hidden belowground interactions.</a></span></span></span></span></span></span></span></span></span></span></span></p> <p>This dataset belongs to the article "<span><span><span><span><span><span><span><span><span><span><span><b>msGBS: A new high-throughput approach to quantify the relative species abundance in root samples of multi-species plant communities</b>". </span></span></span></span></span></span></span></span></span></span></span>msGBS is a technique that uses Genotyping By Sequencing on mixed plant species root samples which, after a filtering step to increase the taxonomic resolution and calibration, is able to estimate plant species abundances. </p> <p>The article uses data of two different experiment:</p> <ol> <li>the Jena field survay (13 plant species) and</li> <li>the Dutch field survay (120 plant species).</li> </ol>
Estimation of the relative abundance of species in artificial mixtures of insects using low-coverage shotgun metagenomics
<p>Amplicon metabarcoding is an established technique to analyse the taxonomic composition of communities of organisms using high-throughput DNA sequencing, but there are doubts about its ability to quantify the relative proportions of the species, as opposed to the species list. Here, we bypass the enrichment step and avoid the PCR-bias, by directly sequencing the extracted DNA using shotgun metagenomics. This approach is common practice in prokaryotes, but not in eukaryotes, because of the low number of sequenced genomes of eukaryotic species. We tested the metagenomics approach using insect species whose genome is already sequenced and assembled to an advanced degree. We shotgun-sequenced, at low-coverage DNA, 18 species of insects in 22 single-species and 6 mixed-species libraries and mapped the reads against 110 reference genomes of insects. We used the single-species libraries to calibrate the process of assignation of reads to species and the libraries created from species mixtures to evaluate the ability of the method to quantify the relative species abundance. Our results showed that the shotgun metagenomic method is easily able to set apart closely-related insect species, like four species of <i>Drosophila</i> included in the artificial libraries. However, to avoid the counting of rare misclassified reads in samples, it was necessary to use a rather stringent detection limit of 0.001, so species with a lower relative abundance are ignored. We also identified that approximately half the raw reads were informative for taxonomic purposes. Finally, using the mixed-species libraries, we showed that it was feasible to quantify with confidence the relative abundance of individual species in the mixtures.</p>
Using species distribution modeling to generate relative abundance information in unstable territories: conservation of Felidae in Mexico
<p>Raw data used in the abovementioned manuscript</p>
Relative species abundance successfully predicts nestedness and interaction frequency of monthly pollination networks in an alpine meadow
<p>Plant-pollinator networks have been repeatedly reported as cumulative ones that are described with >1 years observations. However, such cumulative networks are composed of pairwise interactions recorded at different periods, and thus may not be able to reflect the reality of species interactions in nature (e.g., early-flowering plants typically do not compete for shared pollinators with late-flowering plants, but they are assumed to do so in accumulated networks). Here, we examine the monthly sampling structure of an alpine plant-pollinator bipartite network over a two-year period to determine whether relative species abundance and species traits better explain the network structure of monthly networks than yearly ones. Although community composition and species abundance varied from one month to another, the monthly networks (as well as the yearly networks described with annual pooled data) had a highly nested structure, in which specialists directly interact with generalist partners. Moreover, relative species abundance predicted the nestedness in both the monthly and yearly networks and accounted for a statistically significant percentage of the variation (i.e., 20%-44%) in the pairwise interactions of monthly networks, but not yearly networks. The combination of relative species abundance and species traits (but not species traits only) showed a similar prediction power in terms of both network nestedness and pairwise interaction frequencies. Considering the previously recognized structural pattern and associated mechanisms of plant-pollinator networks, we propose that relative species abundance may be an important factor influencing both nestedness and interaction frequency of pollination networks.</p>
How does variation in total and relative abundance contribute to gradients of species diversity?
Patterns of biodiversity provide insights into the processes that shape biological communities around the world. Variation in species diversity along biogeographical or ecological gradients, such as latitude or precipitation, can be attributed to variation in different components of biodiversity: changes in the total abundance (i.e. more-individual effects) and changes in the regional species abundance distribution (SAD). Rarefaction curves can provide a tool to partition these sources of variation on diversity, but first must be converted to a common unit of measurement. Here, we partition species diversity gradients into components of the SAD and abundance using the effective number of species (ENS) transformation of the individual-based rarefaction curve. Because the ENS curve is unconstrained by sample size, it can act as a standardized unit of measurement when comparing effect sizes among different components of biodiversity change. We illustrate the utility of the approach using two datasets spanning latitudinal diversity gradients in trees and marine reef fish, and find contrasting results. Whereas the diversity gradient of fish was mostly associated with variation in abundance (86%), the tree diversity gradient was mostly associated with variation in the SAD (59%). These results suggest that local fish diversity may be limited by energy through the more-individuals effect, while species pool effects are the larger determinant of tree diversity. We suggest that the framework of the ENS-curve has the potential to quantify the underlying factors influencing most aspects of diversity change. --
Relative abundance tables for bacterial species, pathways, ARGs, and VFGs in "Gut Microbial Community Structure, Metabolic Signature, and Resistome in Dyslipidemia: Insights from Metagenomic Sequencing"
<p>Dyslipidemia, characterized by abnormal blood lipid levels, is a significant risk factor for cardiovascular disease. Emerging evidence suggests that the gut microbiota plays a role in lipid metabolism, although findings across studies have varied. In this study, we analyzed the gut microbiota, metabolic pathways, predicted gut metabolites, and resistome in 1384 participants (895 with dyslipidemia cases and 489 controls) using shotgun metagenomic sequencing. Our results revealed that Bacteroides caccae was enriched in dyslipidemia cases, potentially contributing to inflammation and altered lipid metabolism, while Coprococcus eutactus and Coprococcus catus, known producers of short-chain fatty acids (SCFAs) in lipid regulation, and Blautia obeum, known to be positively impacted by SCFAs, were more abundant in controls. We also identified an enrichment of the dTDP-beta-D-fucofuranose biosynthesis pathway gene family, which is linked to bacterial pathogenicity, in dyslipidemia cases, with Bacteroides stercoris contributing strongly. Dyslipidemia cases exhibited depleted glycogen and peptidoglycan biosynthesis pathways, potentially impairing energy storage and immune function, alongside distinct metabolic profiles, including decreased pseudouridine, which may affect RNA metabolism. Furthermore, we observed a higher abundance of antibiotic-resistance genes, particularly tetQ, in dyslipidemia cases, suggesting a link between gut resistome and metabolic disorders. These findings provide new insights into how dysbiosis of the gut microbiota may contribute to the pathophysiology of dyslipidemia, offering potential avenues for microbiome-based interventions in personalized medicine.</p>
Long-term changes in occurrence, relative abundance, and reproductive fitness of bat species in relation to arrival of White-nose Syndrome in West Virginia, USA
<p>White-nose syndrome (WNS) is a disease caused by the fungus Pseudogymnoascus destructans which has resulted in the deaths of millions of bats across eastern North America. To date, hibernacula counts have been the predominant means of tracking the spread and impact of this disease on bat populations. However, an understanding of the impacts of WNS on demographic parameters outside the winter season is critical to conservation and recovery of bat populations impacted by this disease. We used long-term monitoring data to examine WNS-related impacts to summer populations in West Virginia, where WNS has been documented since 2009. Using capture data from 290 mist-net sites surveyed from 2003–2019 on the Monongahela National Forest, we estimated temporal patterns in presence and relative abundance for each bat species. For species that exhibited a population-level response to WNS, we investigated post-WNS changes in adult female reproductive state and body mass. Myotis lucifugus (little brown bat), M. septentrionalis (northern long-eared bat), and Perimyotis subflavus (tri-colored bat) all showed significant decreases in presence and relative abundance during and following the introduction of WNS, while Eptesicus fuscus (big brown bat) and Lasiurus borealis (eastern red bat) responded positively during the WNS invasion. Probability of being reproductively active was not significantly different for any species, though a shift to earlier reproduction was estimated for E. fuscus and M. septentrionalis. For some species, body mass appeared to be influenced by the WNS invasion, but the response differed by species and reproductive state. Results suggest that continued long-term monitoring studies, additional research into impacts of this disease on the fitness of WNS survivors, and a focus on providing optimal non-wintering habitat may be valuable strategies for assessing and promoting recovery of WNS-affected bat populations.</p>
Data from: Wide prevalence of hybridization in two sympatric grasshopper species may be shaped by their relative abundances
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Data from: The devil is in the detail: estimating species richness, density, and relative abundance of tropical island herpetofauna
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Relative species abundance successfully predicts nestedness and interaction frequency of monthly pollination networks in an alpine meadow
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Data from: Disentangling the relative importance of species occurrence, abundance and intraspecific variability in community assembly: a trait-based approach at the whole-plant level in Mediterranean forests
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Allen Brain Atlas
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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.
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