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6 results for “interacting land use effects”
Datasets from Ganuza et al. 2022: Interactive effects of climate and land use on pollinator diversity differ among taxa and scales
<p>Datasets used in Ganuza et al. 2022: Interactive effects of climate and land use on pollinator diversity differ among taxa and scales. Local and regional data are provided in separate files for the environmental variables, plant species composition and the composition of the different pollinator taxa.</p>
Dataset of pollinator functional traits and interaction networks in neotropical mangroves: effects of patch size and surrounding land use
<p>This is the dataset of the manuscript entitled "Pollinator functional traits and interaction networks in neotropical mangroves: effects of patch size and surrounding land use", which was submitted for publication. The dataset include the functional traits of 162 insect pollinator species and 315 interactions with the mangrove species <em>Avicennia germinans, Conocarpus erectus, Laguncularia racemosa,</em> and <em>Rhizophora</em> <em>mangle</em>. The manuscript evaluates the effects of mangrove patch size and surrounding land use on pollinator functional diversity and plant-pollinator interactions in seven mangrove patches from the Colombian Caribbean region. Data variables are pollinator order, family, species, functional traits (pollinator guilds, body size, feeding preference, sociality, and nesting site) and frequency, interacting mangrove species, mangrove patch name, coordinates and size (ha), surrounding land use areas (urban areas, croplands, conserved dry forest, degraded vegetation areas, beach and water) and landscape diversity (Shannon H').</p>
Data from: Ontogenetic responses of four plant species to additive and interactive effects of land-use history, canopy structure and herbivory
The strength of interactions among species is often highly variable in space and time, and a major challenge in understanding context-dependent effects of herbivores lies in disentangling habitat-mediated from herbivore-mediated effects on plant performance. We conducted a landscape-scale experiment that manipulated light availability in woodlands with either a history of agricultural use or no history of agricultural use and coupled this with performance measurements of three life stages on four perennial herbaceous species exposed to varying levels of herbivory. We found that the context-dependent effects of herbivory on plant performance changed as plants grew: juvenile plant survival was reduced by herbivores in low-light habitats whereas biomass of adult plants was reduced by a more diverse insect fauna in high-light environments. A history of agricultural land use also had negative effects on seedling establishment and adult performance, independent of herbivory. Synthesis. This work experimentally separates the habitat-mediated effects on plant performance from the herbivore-mediated effects on plant performance and highlights how context-dependent interactions depend on plant ontogenetic stages.
Data from: Ontogenetic responses of four plant species to additive and interactive effects of land-use history, canopy structure and herbivory
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Data supporting "Modeling and evaluating the effects of irrigation on land-atmosphere interaction in southwestern Europe with the regional climate model REMO2020-iMOVE using a newly developed parameterization"
<p>This data supports the analysis of the manuscript Asmus et al. 2023 "Modeling and evaluating the effects of irrigation on land-atmosphere interaction in southwestern Europe with the regional climate model REMO2020-iMOVE using a newly developed parameterization".</p><p><strong>Simulation data</strong></p><p>The simulation data is created with REMO2020-iMOVE using the new irrigation parameterization. The results are saved as NetCDF files with monthly mean values and/or time series (hourly) of single variables for the analysis period. A list of the simulations can be found below.</p><p><strong>Observation data </strong></p><p>The observation data is published with the kind permission of ISPRA which hosts the SCIA database (www.scia.isprambiente.it). If you use this data, please make sure to include the following data source:<br>SCIA by ISPRA - Area Climatologia operativa - Via V. Brancati 48 00144 Roma. <br>We downloaded monthly mean values for the variables T2Max, T2Min and T2Mean from <a href="http://193.206.192.214/servertsutm/serietemporali100.php">http://193.206.192.214/servertsutm/serietemporali100.php </a>(last accessed on 14/10/2022) to verify the model results with and without irrigation parameterization. </p><p>By untarring the tarballs, the data structure is created that is necessary to execute the analysis scripts.</p><p>For more information or additional data please contact the author.</p><p> </p><p><strong>tarball | exp_number | description </strong></p><p>067015.tar.gz | 067015 | not irrigated</p><p>067016.tar.gz | 067016 | irrigated with "adaptive water application scheme"</p><p>067017.tar.gz | 067017 | irrigated with "adaptive water application scheme"</p><p>067019.tar.gz | 067019 | irrigated with "flexible time water application scheme"</p><p>067020.tar.gz | 067020 | irrigated with "prescribed water application scheme"</p><p>observation_scia.tar | - | observation data from SCIA </p><p> </p><p><strong>Data structure for simulation data</strong></p><p>\<exp_number><br> \monthly<br> \hourly<br> \var_series<br> \<variable><br><br>Note:<br>\067015 includes static variables<br> \irrifrac (irrigated fraction)<br> \bla (land-sea-mask)</p>
Data supporting the publication of "Interactive effects of climate change and land-use change on mammal range retraction in Great Britain"
<p><strong>Table S1 (Species records) provided as a separate .xlsx file in Supporting Information. </strong>List of species included in the sample with corresponding attributes, number of records and rates of change over time.</p> <p>Column A (Scientific name): species’ accepted scientific name (n = 43 species).</p> <p>Column B (Common name): species’ common name in Great Britain (n = 43 names).</p> <p>Column C (Order): species’ taxonomical Order (n = 6 Orders).</p> <p>Column D (Family): species’ taxonomical Family (n = 14 Families).</p> <p>Column E (Guild): species’ sampling guild (n = 3 Guilds, either Bats, Midlarge, or Small</p> <p>Column F (Distribution): species’ distribution status in Great Britain (n = 3 Statuses, either Native, Naturalised, or Non-Native).</p> <p>Column G (Habitat): species’ habitat preference (n = 2 Habitats, either Terrestrial or Freshwater).</p> <p>Column H (Records): total number of records per species from 1960 to 2016 (average = 10,931).</p> <p>Column I (1960s): total number of records per species from 1960 to 1969 (average = 420).</p> <p>Column J (1970s): total number of records per species from 1970 to 1979 (average = 457).</p> <p>Column K (1980s): total number of records per species from 1980 to 1989 (average = 423).</p> <p>Column L (1990s): total number of records per species from 1990 to 1999 (average = 641).</p> <p>Column M (2000s): total number of records per species from 2000 to 2010 (average = 943).</p> <p>Column N (2010s): total number of records per species from 2011 to 2016 (average = 870).</p> <p>Column O (Hectads TP1): number of hectads where the species has been recorded in Time Period 1, from 1960 to 1992 (average = 892).</p> <p>Column P (Hectads TP2): number of hectads where the species has been recorded in Time Period 2, from 2000 to 2016 (average = 1,117).</p> <p>Column Q (Hectads Total): number of hectads where the species has been recorder from 1960 to 2016 (average = 1,315).</p> <p>Column R (Extirpation rate): species’ extirpation rate, calculated as the ratio of extirpations over the sum of extirpations and persistences (average = 0.24). The sum of extirpation and persistence rates is always equal to 1.</p> <p>Column S (Persistence rate): species’ persistence rate, calculated as the ratio of persistences over the sum of extirpations and persistences (average = 0.76). The sum of persistence and extirpation rates is always equal to 1.</p> <p>Column T (Occupancy TP1): species’ occupancy estimate in Time Period 1, from 1960 to 1992, as calculated in Frescalo (average = 0.395).</p> <p>Column U (Occupancy TP2): species’ occupancy estimate in Time Period 2, from 2000 to 2016, as calculated in Frescalo (average = 0.403).</p> <p>Column V (Occupancy change): change in the species’ occupancy estimates between Time Periods 1 and 2, as calculated in Frescalo (average = 0.076).</p> <p>Column W (Occupancy change slope): average yearly change in the species’ occupancy estimates from 1960 to 2016, as calculated in Frescalo (average = -0.001).</p> <p>Column X (Frequency TP1): adjusted frequency of occurrence in Time Period 1, from 1960 to 1992, as calculated in Frescalo (average = 0.527).</p> <p>Column Y (Frequency TP2): adjusted frequency of occurrence in Time Period 2, from 2000 to 2016, as calculated in Frescalo (average = 0.461).</p> <p>Column Z (Frequency change): change in the adjusted frequency of occurrence between Time Periods 1 and 2, as calculated in Frescalo (average = -0.066).</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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DANDI Archive for NWB datasets
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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.