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230 results for “phylogenetic scale”
Environmental and biotic drivers of soil microbial β‐diversity across spatial and phylogenetic scales
<p>Soil microbial communities play a key role in ecosystem functioning but still little is known about the processes that determine their turnover (β-diversity) along ecological gradients. Here, we characterize soil microbial β-diversity at two spatial scales and at multiple phylogenetic grains to ask how archaeal, bacterial and fungal communities are shaped by abiotic processes and biotic interactions with plants. We characterized microbial and plant communities using DNA metabarcoding of soil samples distributed across and within eighteen plots along an elevation gradient in the French Alps. The recovered taxa were placed onto phylogenies to estimate microbial and plant β-diversity at different phylogenetic grains (i.e. resolution). We then modeled microbial β-diversities with respect to plant β-diversities and environmental dissimilarities across plots (landscape scale) and with respect to plant β-diversities and spatial distances within plots (plot scale). At the landscape scale, fungal and archaeal β-diversities were mostly related to plant β-diversity, while bacterial β-diversities were mostly related to environmental dissimilarities. At the plot scale, we detected a modest covariation of bacterial and fungal β-diversities with plant β-diversity; as well as a distance–decay relationship that suggested the influence of ecological drift on microbial communities. In addition, the covariation between fungal and plant β-diversity at the plot scale was highest at fine or intermediate phylogenetic grains hinting that biotic interactions between those clades depends on early-evolved traits. Altogether, we show how multiple ecological processes determine soil microbial community assembly at different spatial scales and how the strength of these processes change among microbial clades. In addition, we emphasized the imprint of microbial and plant evolutionary history on today's microbial community structure.</p>
Data from: The early elasmobranch Phoebodus: phylogenetic relationships, ecomorphology, and a new time-scale for shark evolution
Anatomical knowledge of early chondrichthyans and estimates of their phylogeny are improving, but many taxa are still known only from microremains. The nearly cosmopolitan and regionally abundant Devonian genus Phoebodus has long been known solely from isolated teeth and fin spines. Here, we report the first skeletal remains of Phoebodus from the Famennian (Late Devonian) of the Maïder region of Morocco, revealing an anguilliform body, specialized braincase, hyoid arch, elongate jaws and rostrum, complementing its characteristic dentition and ctenacanth fin spines preceding both dorsal fins. Several of these features corroborate a likely close relationship with the Carboniferous species Thrinacodus gracia, and phylogenetic analysis places both taxa securely as members of the elasmobranch stem lineage. Identified as such, phoebodont teeth provide a plausible marker for range extension of the elasmobranchs into the Middle Devonian, thus providing a new minimum date for the origin of the chondrichthyan crown-group. Among pre-Carboniferous jawed vertebrates, the anguilliform body shape of Phoebodus is unprecedented, and its specialized anatomy is, in several respects, most easily compared with the modern frilled shark Chlamydoselachus. These results add greatly to the morphological, and by implication ecological, disparity of the earliest elasmobranchs.
Scaling between macro- to microscale climatic data reveals strong phylogenetic inertia in niche evolution in plethodontid salamanders
<p>Macroclimatic niches are indirect and potentially inadequate predictors of the realized environmental conditions that many species experience. Consequently, analyses of niche evolution based on macroclimatic data alone may incompletely represent the evolutionary dynamics of species niches. Yet, understanding how an organisms' climatic (Grinnellian) niche responds to changing macroclimatic conditions is of vital importance for predicting their potential response to global change. In this study, we integrate microclimatic and macroclimatic data across 26 species of plethodontid salamanders to portray the relationship between microclimatic niche evolution in response to changing macroclimate. We demonstrate stronger phylogenetic signal in microclimatic niche variables than at the macroclimatic scale. Even so, we find that the microclimatic niche tracks climatic changes at the macroscale, but with a phylogenetic lag at million-year timescales. We hypothesize that behavioral tracking of the microclimatic niche over space and phenology generates the lag: salamanders preferentially select microclimates similar to their ancestral conditions rather than adapting with changes in physiology. We demonstrate that macroclimatic variables are weak predictors of niche evolution and that incorporating spatial scale into analyses of niche evolution is critical for predicting responses to climate change.</p>
Figure 2. - Phylogenetic relationships among Dicronocephalus species reconstructed with Bayesian inference using COI sequences. Numbers above branches indicate ML bootstrap values and Bayesian posterior probabilities. Numbers below branches are bootstrap, symmetric resampling, and jacknife support from parsimony searches, respectively. Scale bar represents 10% nucleotide mutation rate.
Figure 2. - Phylogenetic relationships among Dicronocephalus species reconstructed with Bayesian inference using COI sequences. Numbers above branches indicate ML bootstrap values and Bayesian posterior probabilities. Numbers below branches are bootstrap, symmetric resampling, and jacknife support from parsimony searches, respectively. Scale bar represents 10% nucleotide mutation rate.
Figure 4. - Phylogenetic relationships among Dicronocephalus species reconstructed with Bayesian inference using COI and 16S rRNA sequences. Numbers above branches indicate ML bootstrap values and Bayesian posterior probabilities. Numbers below branches are bootstrap, symmetric resampling, and jacknife support from parsimony searches, respectively. Scale bar represents 10% nucleotide mutation rate.
Figure 4. - Phylogenetic relationships among Dicronocephalus species reconstructed with Bayesian inference using COI and 16S rRNA sequences. Numbers above branches indicate ML bootstrap values and Bayesian posterior probabilities. Numbers below branches are bootstrap, symmetric resampling, and jacknife support from parsimony searches, respectively. Scale bar represents 10% nucleotide mutation rate.
Figure 3. - Phylogenetic relationships among Dicronocephalus species reconstructed with Bayesian inference using 16S rRNA sequences. Numbers above branches indicate ML bootstrap values and Bayesian posterior probabilities. Numbers below branches are bootstrap, symmetric resampling, and jacknife support from parsimony searches, respectively. Scale bar represents 10% nucleotide mutation rate.
Figure 3. - Phylogenetic relationships among Dicronocephalus species reconstructed with Bayesian inference using 16S rRNA sequences. Numbers above branches indicate ML bootstrap values and Bayesian posterior probabilities. Numbers below branches are bootstrap, symmetric resampling, and jacknife support from parsimony searches, respectively. Scale bar represents 10% nucleotide mutation rate.
Long-term nitrogen fertilization alters arbuscular mycorrhizal fungi community phylogenetic structure in plant roots across fine spatial scales
<p><span>Purpose:</span><span> Nitrogen deposition due to human activities is known to have a substantial impact on arbuscular mycorrhizal fungi (AMF) community in plant roots. However, the influence of elevated nitrogen on the phylogenetic structure of AMF across fine spatial scales, as well as the mechanisms behind such alterations, are remained poorly understood. </span></p> <p><span>Results:</span><span> Nitrogen addition significantly increased the phylogenetic alpha diversity (diversity within a plot) and the 'within-treatment' phylogenetic beta diversity (dissimilarity among replicate plots) of AMF communities, which resulted in an increased 'within-treatment' phylogenetic gamma diversity (overall diversity among all the replicate plots within a treatment). These changes were caused by the relative abundance decline of a dominant genus (</span><span>Glomus</span><span>) and an increase in non-dominant genera. Mechanically, nitrogen addition affected phylogenetic alpha diversity mainly by influencing soil properties. Likewise, the increased 'within-treatment' dissimilarity of plant community composition and changes in soil properties caused by nitrogen addition and plot distance contributed to an increase in within-treatment phylogenetic beta diversity. </span></p> <p><span>Conclusions:</span><span> We conclude that deterministic environmental filtering (both abiotic and biotic) and dispersal limitation effect played critical roles in AMF community assembly under global change scenarios. Insightfully, this study provides a mechanistic understanding of the response of AMF to nitrogen addition across fine scales.</span></p>
Biodiversity scale-dependence and opposing multi-level correlations underlie differences among taxonomic, phylogenetic, and functional diversity
<p><b>Aim:</b> Biodiversity is a multi-dimensional property of biological communities that represents different information depending on how it is measured, but how dimensions relate to one another and under what conditions is not well understood. We explore how taxonomic, phylogenetic, and functional diversity can differ in scale-of-effect dependence and habitat-biodiversity relationships, and subsequently how spatial differences among biodiversity dimensions may arise.</p> <p><b>Location:</b> Nebraska, United States</p> <p><b>Time period:</b> May-July 2016, 2017</p> <p><b>Major taxa studied:</b> Birds</p> <p><b>Methods:</b> Across 2016 and 2017, we conducted 2,641 point counts at 781 sites. We modeled the occupancy of 141 species using Bayesian Bernoulli-Bernoulli hierarchical logistic regressions. We calculated species richness (SR), phylogenetic diversity (PD), and functional diversity (FD) for each site and year based on predicted occupancy, accounting for imperfect detection. Using Bayesian latent indicator scale selection and multivariate modeling, we quantified the spatial scales-of-effect that best explained the relationships between environmental characteristics and SR, PD, and FD. Additionally, we decomposed the residual between- and within-site biodiversity correlations using our repeated measures design.</p> <p><b>Results:</b> We demonstrate spatial differences among biodiversity predictions, arising from scale-dependence in habitat-biodiversity relationships and variation in correlation structure among biodiversity dimensions. Although relationships between specific land cover types and SR, PD and FD were qualitatively similar, the spatial scales at which these variables were important in explaining biodiversity differed among dimensions. Between-site residual biodiversity correlations were negative, yet within-site biodiversity residual correlations were positive.</p> <p><b>Main conclusions:</b> Our results demonstrate how spatial differences among biodiversity dimensions may arise from biodiversity-specific scale-dependent habitat relationships, low shared environmental correlations and opposing residual correlations between dimensions, which suggest that single-scale and single-dimension analyses are not entirely appropriate for quantifying habitat-biodiversity relationships. After accounting for shared habitat relationships, we found positive within-site residual correlations between taxonomic, phylogenetic, and functional diversity, suggesting that habitat change over time influenced all biodiversity dimensions relatively similarly. However, negative between-site residual correlation among biodiversity dimensions may indicate trade-offs in achieving maximum biodiversity across multiple biodiversity dimensions at any given location. Although habitat management can to a limited degree improve biodiversity relatively across all metrics, other environmental effects may ensure that not all facets of biodiversity can be maximized at once. If maximizing a specific biodiversity dimension is the goal, then care should be taken to consider these within-site residual correlations.</p>
Data from: Chilean bee diversity: Contrasting patterns of species and phylogenetic turnover along a large-scale ecological gradient
<p>Title of dataset</p> <p>Data from: Chilean bee diversity: Contrasting patterns of species and phylogenetic turnover along a large-scale ecological gradient</p> <p>Authors of dataset</p> <p>Leon Marshall<sup>1,2</sup>, John S. Ascher<sup>3</sup>, Cristian Villagra<sup>4</sup>, Amaury Beaugendre<sup>1</sup>, Valentina Herrera<sup>4</sup>, Patricia Henríquez-Piskulich<sup>4</sup>, Alejandro Vera<sup>5</sup>, Nicolas J. Vereecken<sup>1</sup></p> <ol> <li>Agroecology Lab, Université libre de Bruxelles (ULB), Boulevard du Triomphe CP 264/2, B 1050 Brussels, Belgium</li> <li>Naturalis Biodiversity Center, Darwinweg 2, 2333 CR Leiden, The Netherlands</li> <li>Department of Biological Sciences, National University of Singapore, 14 Science Drive 4, Singapore 117543, Singapore</li> <li>Instituto de Entomología, Universidad Metropolitana de Ciencias de la Educación, Santiago, Región Metropolitana, Chile</li> <li>Departamento de Biología, Universidad Metropolitana de Ciencias de la Educación, Santiago, Región Metropolitana, Chile</li> </ol> <p>Abstract</p> <p>Chile's isolation and varied climates have driven the evolution of a unique biodiversity with a high degree of endemism. As a result, Chile encompasses diverse environments, including the Mediterranean-type ecosystem, a global biodiversity hotspot. These environments are currently threatened by anthropogenic land use change impacting the integrity of local biomes and associated species. This area is the most intensively sampled of the country with high endemicity of native bee species. Characterising habitat requirements of bees is a pressing priority to safeguard these insects and the ecosystem services they provide. We investigated broad-scale patterns of bee (Hymenoptera: Apoidea: Anthophila) diversity using newly accessible expert-validated datasets comprising digitized specimen records from Chilean and US collections, and novel expert-validated type specimen data for the bees of Chile. We used a generalised dissimilarity modelling (GDM) approach to explore both compositional and phylogenetic β-diversity patterns across latitudinal, altitudinal, climate and habitat gradients in well-sampled bee assemblages in Central Chile. Using the GDM measures of increasing compositional and environmental dissimilarity we categorised and compared the most important drivers of these patterns and used them to classify 'wild bee ecoregions' (WBE) representing unique assemblages. Turnover of bee assemblages was explained primarily by latitudinal variation (proxy for climate) from south to north in Chile. However, temperature variations, precipitation and the presence of bare soil also significantly explained turnover in bee assemblages. In comparison, we observed less turnover in phylogenetic biodiversity corresponding to spatial gradients. We identified six de novo ecoregions (WBE), all with distinct taxa, endemic lineages, and representative species. The WBE represent distinct spatial classifications but have similarities to existing biogeographical classifications, ecosystems and bioclimatic zones. This approach establishes the baseline needed to prioritise bee species conservation efforts across this global biodiversity hotspot. We discuss the novelty of this classification considering previous biogeographical characterisations and their relevance in assessing conservation priorities for bee conservation. We argue that Chile's WBE highlight areas in need of funding for bee species surveys and description, distribution mapping and strengthening of conservation policies.</p> <p>Usage notes</p> <p>The dataset contains species occurrence data of chilean bees aggregated to a 5 x 5 km grid shapefile. The shapefile of the grid and the raster mask of the Central Chilean study area are also included. Finally, a database of type specimen data used to supplement the dataset is included here. The code for the analysis can be found at: <a href="https://github.com/lmar116/ChileanBeeDiversity">https://github.com/lmar116/ChileanBeeDiversity</a>.</p> <p>Shapefiles, rasters, CSV files and code were all loaded and analyzed using R statistics software. </p> <p>Four files are included:</p> <ol> <li>Marshall-et-al-2023_Ecosphere_DataTable_bee_grid: contains all species occurrence data used in GDM analysis, Grid column refers to cl.5km.shp.</li> <li>cl.5km.shp (and associated files): 5 x 5 km grid shapefile of the Central Chilean study area</li> <li>chile.mask.tif: raster outline of the Central Chilean study area</li> <li>Marshall-et-al-2023_Ecosphere_CentralChileTypeSpecimens.xlsx: contains type specimen data used to supplement species occurrence dataset.</li> </ol>
Data from: Context- and taxon-dependent small-scale taxonomic and phylogenetic nestedness of bryophytes on insular rocks in a karst natural reserve and its implication for their conservation
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Data from: The early elasmobranch Phoebodus: phylogenetic relationships, ecomorphology, and a new time-scale for shark evolution
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Evolutionary trajectories of multiple defense traits across phylogenetic and geographic scales in Vitis
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Biodiversity scale-dependence and opposing multi-level correlations underlie differences among taxonomic, phylogenetic, and functional diversity
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Lineage-specific phylogenetic structure of boreal habitats suggests different assembly processes across phylogenetic and spatial scales
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Environmental and biotic drivers of soil microbial β‐diversity across spatial and phylogenetic scales
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Long-term nitrogen fertilization alters arbuscular mycorrhizal fungi community phylogenetic structure in plant roots across fine spatial scales
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Scaling between macro- to microscale climatic data reveals strong phylogenetic inertia in niche evolution in plethodontid salamanders
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Detecting phylogenetic signal and adaptation in papionin cranial shape by decomposing variation at different spatial scales
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Pairwise distance demarcation of species in the family Coronaviridae. a, Diagonal matrix of PPDs of 2,505 viruses clustered according to 49 coronavirus species, 39 established and 10 pending or tentative, and ordered from the most to least populous species, from left to right; green and white, PPDs smaller and larger than the inter-species threshold, respectively. Areas of the green squares along the diagonal are proportional to the virus sampling of the respective species, and virus prototypes of the five most sampled species are specified to the left; asterisks indicate species that include viruses whose intra-species PPDs crossed the inter-species threshold (threshold 'violators'). b, Maximal intra-species PPDs (x axis, linear scale) plotted against virus sampling (y axis, log scale) for 49 species (green dots) of the Coronaviridae. Indicated are the acronyms of virus prototypes of the seven most sampled species. Green and blue plot sections represent intra-species and intra-subgenera PPD ranges. The vertical black line indicates the inter-species threshold. c, Shown are the PDs of non-identical residues (y axis) for four viruses representing three major phylogenetic lineages (clades) of the species Severe acute respiratorysyndrome-related coronavirus (panel b) and all pairs of the 256 viruses of this species ('all pairs'). The PD values were derived from pairwise distances in the MSA that were calculated using an identity matrix. Panels a and b were adopted from the DEmARC v.1.4 output. in The species Severe acute respiratory syndromerelated coronavirus: classifying 2019-nCoV and naming it SARS-CoV-2
Pairwise distance demarcation of species in the family Coronaviridae. a, Diagonal matrix of PPDs of 2,505 viruses clustered according to 49 coronavirus species, 39 established and 10 pending or tentative, and ordered from the most to least populous species, from left to right; green and white, PPDs smaller and larger than the inter-species threshold, respectively. Areas of the green squares along the diagonal are proportional to the virus sampling of the respective species, and virus prototypes of the five most sampled species are specified to the left; asterisks indicate species that include viruses whose intra-species PPDs crossed the inter-species threshold (threshold 'violators'). b, Maximal intra-species PPDs (x axis, linear scale) plotted against virus sampling (y axis, log scale) for 49 species (green dots) of the Coronaviridae. Indicated are the acronyms of virus prototypes of the seven most sampled species. Green and blue plot sections represent intra-species and intra-subgenera PPD ranges. The vertical black line indicates the inter-species threshold. c, Shown are the PDs of non-identical residues (y axis) for four viruses representing three major phylogenetic lineages (clades) of the species Severe acute respiratorysyndrome-related coronavirus (panel b) and all pairs of the 256 viruses of this species ('all pairs'). The PD values were derived from pairwise distances in the MSA that were calculated using an identity matrix. Panels a and b were adopted from the DEmARC v.1.4 output.
Supplementary material 2 from: Hatch AS, Liew H, Hourdez S, Rouse GW (2020) Hungry scale worms: Phylogenetics of Peinaleopolynoe (Polynoidae, Annelida), with four new species. ZooKeys 932: 27-74. https://doi.org/10.3897/zookeys.932.48532
In situ fighting behavior of Peinaleopolynoe orphanae sp. nov. observed in the Pescadero Basin, Gulf of California, Mexico
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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.