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376 results for “local scales”
Text-fig. 13. Paramblypterus sp. Locality Otovice "Chmelnice", P 64668, scale bar 10 mm. in Actinopterygians Of The Broumov Formation (Permian) In The Czech Part Of The Intra-Sudetic Basin (The Czech Republic)
Text-fig. 13. Paramblypterus sp. Locality Otovice "Chmelnice", P 64668, scale bar 10 mm.
IMPREX - TUC - Local scale seasonal hydrological and drought indices forecasts
<p>The compressed files are seasonal forecasts of discharge based on ECMWF System4 (1981-2003) and GLOSEA5 (1996-2003) for the Koutsoulidis catchment, Crete, Greece. The location of the Koutsoulidis catchment as well as the methodology of data development and validation are described in the open access publication by Grillakis et al., 2018 (<a href="https://www.mdpi.com/2073-4441/10/11/1593">https://www.mdpi.com/2073-4441/10/11/1593</a>). Seasonal forecasts of Standardized Precipitation Index (SPI) based on ECMWF System4 (1981-2009) and GLOSEA5 (1996-2009) for the Messara catchment are also included. A description of the study site and methodology is included in the poster attached in the compressed file (EGU201712072-Koutroulis).</p>
Data used in manuscript Spatial modelling of local-scale biogenic and anthropogenic carbon dioxide emissions in Helsinki
<p>This data set includes data used to develop and evaluate carbon dioxide emission modelling component in the Surface Urban Energy and Water balance Scheme (SUEWS). The data files are:</p> <ol> <li>CO2_Model_Parameter_Fitting.zip contains m-files (Matlab) used to calculate parameters for photosynthesis modelling <ul> <li>F_pho_data.mat includes meteorological and EC data used to fit photosynthesis model parameters in Kumpula</li> <li>FitKumpulaData.m calculates the model parameters in Kumpula</li> <li>FitViikkiData.m calculates the model parameters in Viikki</li> <li>Other m-files needed by the above two codes</li> </ul> </li> <li>Data.zip contains measured data used to develop and evaluate SUEWS <ul> <li>KumpulaData2012.txt and TorniData2012.txt include eddy covariance data measured at the two sites in Helsinki</li> <li>SMEARIII_meteorology_2016MM_30.m meteorological data used to fit model parameters in Viikki street trees (see 00 ReadMe_SMEARIII_Meteorology.TXT for details)</li> <li>Viikki_SWC_2016.txt measured soil moisture from Viikki in 2016</li> <li>Kumpula_2016_HH_RLAI6_Output.out is SPP output used to fit model parameters in Viikki street trees</li> </ul> </li> <li>SUEWS_EC_Site_Model_runs: SUEWS input and output files for Kumpula and Torni model runs</li> <li>SpatialRun_input.zip: SUEWS input files for the spatial model run</li> <li>spatmatHel_final.mat: SUEWS output files for spatial model run in mat-format</li> </ol>
Locality-sensitive hashing enables signal classification in high-throughput mass spectrometry raw data at scale
<p>Raw data of nanoLC-IMS-MS/MS (DDA-PASEF) from HeLa whole proteome digest. </p> <p>HeLa cells were lysed in a urea-based lysis buffer (7 M urea, 2 M thiourea, 5 mM dithiothreitol (DTT), 2% (w/v) CHAPS) assisted by sonication for 15 min at 4°C in high potency using a Bioruptor instrument (Diagenode). Proteins were digested with Trypsin using a filter-aided sample preparation (FASP) [Wisniewski <em>et al</em>., 2009] as previously detailed [Distler <em>et al</em>., 2016]. 200 ng of peptide digest were analyzed using a nanoElute UPLC coupled to a TimsTOF PRO MS (Bruker). Peptides injected directly in an Aurora 25 cm x 75 µm ID, 1.6 µm C18 column (Ionopticks) and separated using a 120 min. gradient method at 400 nL/min. Phase A consisted on water with 0.1% formic acid and phase B on acetonitrile with 0.1% formic acid. Sample was injected at 2% B, lineally increasing to 20% B at 90 min., 35% B at 105 min., 95% at 115 min. and hold at 95% until 120 min. before re-equilibrating the column at 2%B. The MS was operated in DDA-PASEF mode [Meier <em>et al</em>., 2018], scanning from 100 to 1700 m/z at the MS dimension and 0.60 to 1.60 1/k0 at the IMS dimension with a 100 ms TIMS ramp. Each 1.17 sec MS cycle comprised one MS1 and 10 MS2 PASEF ramps (frames). The source was operated at 1600 V, with dry gas at 3 L/min and 200°C, without nanoBooster gas. The instrument was operated using Compass Hystar version 5.1 and timsControl version 1.1.15 (Bruker).</p>
Landscape-scale dynamics of a threatened species respond to local-scale conservation management
<p><span>Landscape-scale approaches are increasingly advocated for species conservation but ensuring landscape level persistence by enlarging the size of patches or increasing their physical connectivity is often impractical. Here, we test how such barriers can be overcome by management of habitat at the local (site-based) level, using a rare butterfly as an exemplar. We used four surveys of the entire UK distribution of the Lulworth Skipper (<em>Thymelicus</em> <em>acteon</em>) over 40 years to test how local habitat influences population density and colonization / extinction dynamics, and parameterized, validated and applied a metapopulation model to simulate effects of varying local habitat quality on regional persistence. We found the total number of populations in four distribution snapshots between 1978 and 2017 varied between 59–84, and from 1997 to 2017, 34% of local populations showed turnover (colonization or extinction). Population density was closely linked to vegetation characteristics indicative of management, namely height and food plant frequency, both of which changed through time. Simulating effects of habitat quality on metapopulation dynamics 40 years into the future suggests coordinated changes to two key components of quality (vegetation height and food plant frequency) would increase patch occupancy above the range observed in the past 40 years (50–80%). In contrast, deterioration of either component below threshold levels leads to metapopulation retraction to core sub-networks of patches, or eventual extirpation. Our results indicate that changes to habitat quality can overcome constraints imposed by habitat patch area and spatial location on relative rates of colonization and local extinction, demonstrating the sensitivity of regional dynamics to targeted in situ management. Local habitat management therefore plays a key role in landscape-scale conservation. Monitoring of population density, and the monitoring and management of local (site-level) habitat quality, therefore represent effective and important components of conservation strategies in fragmented landscapes.</span></p>
Dataset for: Indirect nitrous oxide emission factors of fluvial networks can be predicted by dissolved organic carbon and nitrate from local to global scales
<p>Streams and rivers are important sources of nitrous oxide (N<sub>2</sub>O), a powerful greenhouse gas. Estimating global riverine N<sub>2</sub>O emissions is critical for the assessment of anthropogenic N<sub>2</sub>O emission inventories. The indirect N<sub>2</sub>O emission factor (EF<sub>5r</sub>) model, one of the bottom-up approaches, adopts a fixed EF<sub>5r</sub> value to estimate riverine N<sub>2</sub>O emissions based on IPCC methodology. However, the estimates have considerable uncertainty due to the large spatiotemporal variations in EF<sub>5r</sub> values. Factors regulating EF<sub>5r</sub> are poorly understood at the global scale. Here, we combine 4-year in situ observations across rivers of different land use types in China, with a global meta-analysis over six continents, to explore the spatiotemporal variations and controls on EF<sub>5r</sub> values. Our results show that the EF<sub>5r</sub> values in China and other regions with high N loads are lower than those for regions with lower N loads. Although the global mean EF<sub>5r</sub> value is comparable to the IPCC default value, the global EF<sub>5r</sub> values are highly skewed with large variations, indicating that adopting region-specific EF<sub>5r</sub> values rather than revising the fixed default value is more appropriate for the estimation of regional and global riverine N<sub>2</sub>O emissions. The ratio of dissolved organic carbon to nitrate (DOC/NO<sub>3</sub><sup>-</sup>) and NO<sub>3</sub><sup>-</sup> concentration are identified as the dominant predictors of region-specific EF<sub>5r</sub> values at both regional and global scales because stoichiometry and nutrients strictly regulate denitrification and N<sub>2</sub>O production efficiency in rivers. A multiple linear regression model using DOC/NO<sub>3</sub><sup>-</sup> and NO<sub>3</sub><sup>-</sup> is proposed to predict region-specific EF<sub>5r</sub> values. The good fit of the model associated with easily obtained water quality variables allows its widespread application. This study fills a key knowledge gap in predicting region-specific EF<sub>5r</sub> values at the global scale and provides a pathway to estimate global riverine N<sub>2</sub>O emissions more accurately based on IPCC methodology.</p> <p>This dataset is a global integrated N<sub>2</sub>O dataset including data from 4-year (2017-2020) in situ measurements of six large rivers in China, 3-year (2018-2020) in situ measurements of urban river networks in Beijing of China, and 825 measurements from 70 published papers over six continents. The data includes dissolved N<sub>2</sub>O concentration, biogeochemical (DOC, NO<sub>3</sub><sup>-</sup>, NH<sub>4</sub><sup>+</sup>, temperature, and DO), climatological (climate zones), and geographic (region, location, and land cover) information.</p>
Appendix of Large-Scale Evaluation of Method-Level Bug Localization with FinerBench4BL
<p>Appendix of "Large-Scale Evaluation of Method-Level Bug Localization with FinerBench4BL"</p> <p> </p> <p>FinerBench4BL is available at the following URL</p> <p><a href="https://github.com/salab/FinerBench4BL">https://github.com/salab/FinerBench4BL</a></p>
Datasets from: Local- and landscape-scale drivers of terrestrial herbaceous plant diversity along a tropical rainfall gradient in Western Ghats, India
<p>This data set contains information on local- and landscape-level terrestrial herbaceous plant diversity and critical abiotic factors along a 36-km East-West transect in Mudumalai Tiger Reserve, Tamil Nadu India. Understory angiosperms with no above-ground wood (secondary cambial growth) were considered as herbaceous plants.</p>
Convergent genomic signatures of local adaptation across a continental-scale environmental gradient
<p><span>Convergent local adaptation offers a glimpse into the role of constraint and stochasticity in adaptive evolution, in particular the extent to which similar genetic mechanisms drive adaptation to common selective forces. Here, we investigated the genomics of local adaptation in two non-sister woodpeckers that are co-distributed across an entire continent and exhibit remarkably convergent patterns of geographic variation. We sequenced the genomes of 140 individuals of Downy (<em>Dryobates</em> <em>pubescens</em>) and Hairy (<em>D</em>. <em>villosus</em>) woodpeckers and employed a suite of genomic approaches to identify loci under selection. We showed evidence that convergent genes have been targeted by selection in response to shared environmental pressures, such as temperature and precipitation. Among candidates, we found multiple genes putatively linked to key phenotypic adaptations to climate, including differences in body size (e.g., <em>IGFPB</em>) and plumage (e.g., <em>MREG</em>). These results are consistent with genetic constraints limiting the pathways of adaptation to broad climatic gradients, even after genetic backgrounds diverge.</span></p>
Data from: Local and landscape scale woodland cover and diversification of agroecological practices shape butterfly communities in tropical smallholder landscapes
<p>The conversion of biodiversity-rich woodland to farmland and subsequent management has strong, often negative, impacts on biodiversity. In tropical smallholder agricultural landscapes, the impacts of agriculture on insect communities, both through habitat change and subsequent farmland management, is understudied. The use of agroecological practices has social and agronomic benefits for smallholders. Although ecological co-benefits of agroecological practices are assumed, systematic empirical assessments of biodiversity effects of agroecological practices are missing, particularly in Africa.</p> <p>In Malawi, we assessed butterfly abundance, species richness, species assemblages and community life-history traits on 24 paired woodland and smallholder-managed farmland sites located across a gradient of woodland cover within a 1 km radius. We tested whether habitat type (woodland vs. farmland) and woodland cover at the landscape scale interactively shaped butterfly communities. Farms varied in the implementation of agroecological pest and soil management practices and flowering plant species richness.</p> <p>Farmland had lower butterfly abundances and approximately half the species richness than woodland. Farmland butterfly communities had, on average, a larger wingspan than woodland site communities. Surprisingly, higher woodland cover in the landscape had no effect on butterfly abundance in both habitats. In contrast, species richness was higher with higher woodland cover. Butterfly species assemblages were distinct between wood- and farmland and shifted across the woodland cover gradient.</p> <p>Farmland butterfly abundance, but not species richness, was higher with higher flowering plant species richness on farms. Farms with a higher number of agroecological pest management practices had a lower abundance of the dominant butterfly species, but not of rarer species. However, a larger number of agroecological soil management practices was associated with a higher abundance of rarer species. </p> <p><em>Synthesis and applications</em>: We show that diversified agroecological soil practices and flowering plant richness enhanced butterfly abundance on farms. However, our results suggest that on-farm measures cannot compensate for the negative effects of continued woodland conversion. Therefore, we call for more active protection of remaining African woodlands in tandem with promoting agroecological soil management practices and on-farm flowering plant richness to conserve butterflies whilst benefiting smallholders.</p>
Agroforestry-based community forestry as a large-scale strategy to reforest agricultural encroachment areas in Myanmar: ambition vs. local reality
<p>Abstract: <br> Context: <br> The high rate of deforestation in Myanmar is mainly due to agricultural expansion. One task of the Forest Department is to increase tree cover in the encroaching farmland by establishing large-scale agroforestry-based community forests (ACFs).<br> Aim: <br> The objectives of this study were to analyze the adoption and performance of the ACFs in the agricultural encroachment areas in the Bago-Yoma region, Myanmar; and to provide recommendations to enhance the adoption of ACFs by farmers.<br> Methods: <br> We inventoried 42 sample plots and surveyed 291 farmers. Survey responses were analyzed by binary logistic regression, one-way ANOVA, and non-parametric correlation tests to evaluate factors influencing the adoption of ACFs. Stand characteristics were calculated from the inventory data to evaluate the performance of ACFs.<br> Results: <br> Our results show that farmer participation in ACFs was lower than stated in the registry of the Forest Department. Farmers practiced four different agroforestry designs in ACFs with different outcomes. The Forest Department strongly determined tree species and planting designs, farmers’ perception and participation in ACFs. Farmland size, unclear and insufficient information on ACFs, and a negative perception of raising trees in crop fields were the major factors limiting the adoption rates of ACFs. <br> Conclusion: <br> We recommend capacity building for farmers and Forest Department staff and raising awareness about the benefits of planting designs and trees on farmland. A stronger consideration of farmers’ preferences for design and species selection could increase their motivation to adopt ACFs and improve the long-term sustainability of ACFs.</p> <p> </p>
Genomic data for Tracing SARS-CoV-2 clusters across local scales: Greater Houston, January–October 2021
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Environmental drivers of local abundance-mass scaling in soil animal communities
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Data from: multidimensional beta-diversity across local and regional scales in a Chinese subtropical forest: the role of forest structure
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Data from: Local and landscape scale woodland cover and diversification of agroecological practices shape butterfly communities in tropical smallholder landscapes
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Data from: Local-scale tree and shrub diversity improves pollination services to shea trees in tropical West African parklands
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Data from: Associations with landscape and local-scale wetland habitat conditions vary among migratory shorebird species during stopovers
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Convergent genomic signatures of local adaptation across a continental-scale environmental gradient
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Tree mycorrhizal associations regulate relationships between plant and microbial communities and soil organic carbon stocks at local scales in a temperate forest
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Counterintuitive scaling between population abundance and local density: implications for modelling transmission of infectious diseases in bat populations
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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.