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21 results for “vegetation shift”
Dataset from: Spatially heterogeneous shifts in vegetation phenology induced by climate change threaten the integrity of the avian migration network
<p>Original data and code for the study:</p> <p>Wei, J., Xu, F., Cole, E. F., Sheldon, B. C., de Boer, W. F., Wielstra, B., Fu, H., Gong, P., & Si, Y. (2024, Accepted). Spatially heterogeneous shifts in vegetation phenology induced by climate change threaten the integrity of the avian migration network. Global Change Biology.</p> <p>The dataset mainly contains data showing the climate change-induced heterogeneous shifts in vegetation phenology and the migration integrity change from 2000 to 2020 for 16 Asian herbivorous waterfowl species. These data were derived from the following resources available in the public domain.</p> <p>The Global Lakes and Wetlands Database is available from “https://www.worldwildlife.org/pages/global-lakes-and-wetlands-database”. The global land cover datasets are available from European Space Agency (ESA) Climate Change Initiative (CCI) products, “https://maps.elie.ucl.ac.be/CCI/viewer/download.php”. The Global Multi-resolution Terrain Elevation Data are available from “https://www.usgs.gov/centers/eros/science/terrain-monitoring-and-modeling”. The Moderate Resolution Imaging Spectroradiometer (MODIS) Terra surface reflectance product is available from “https://modis.gsfc.nasa.gov/data/dataprod/mod09.php”. The bird distribution maps are available from Birdlife International, “https://www.birdlife.org/”. The bird foraging attribute data are available from EltonTraits 1.0, “https://figshare.com”. The bird occurrence data are available from eBird Basic Dataset (EBD), “https://science.ebird.org/en/use-ebird-data/download-ebird-data-products”. The Hackett backbone phylogenetic trees are available from “https://birdtree.org/”.</p> <p>The code contains the R scripts and MATLAB scripts that we used for this study.</p> <p>For details please see the file “Readme.txt”, and the research paper.</p>
Empirical evidence for recent global shifts in vegetation resilience
<p>Data and codes for the publication:</p> <p>Smith, T., Traxl, D. & Boers, N. Empirical evidence for recent global shifts in vegetation resilience. <em>Nat. Clim. Chang.</em> (2022). https://doi.org/10.1038/s41558-022-01352-2</p> <p>Data is described in 'README.txt'.</p>
Infauna shift trait-productivity relationships in submerged aquatic vegetation communities
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Data from: Spatiotemporal dynamics of Nektonic biodiversity and vegetation shifts during the Smithian–Spathian Transition: Conodont and Palynomorph insights from Svalbard
<p>The dataset includes an Excel file with sporomorph counting of samples from the Stensiöfjellet section, Svalbard. Furthermore, it includes additional taxonomic notes on conodonts from the Stensiöfjellet section, Svalbard.</p>
Data from: Spatiotemporal dynamics of Nektonic biodiversity and vegetation shifts during the Smithian–Spathian Transition: Conodont and Palynomorph insights from Svalbard
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Continuous abrupt vegetation shifts in the global terrestrial ecosystem
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Data from: Climate change, wildfire, and vegetation shifts in a high-inertia forest landscape: Western Washington, U.S.A.
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Data from: Changing climate may drive large shifts in vegetation zones of Oregon, USA
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Data from: Structural complexity and large-sized trees explain shifting species richness and carbon relationship across vegetation types
<p>1. It is prominently claimed that enhancing forest diversity would play a dual role of nature conservation and climate regulation. While the idea is intuitively appealing, studies show that species richness effects on aboveground carbon (AGC) are not always positive, but instead unpredictable especially across scales and complex terrestrial systems having large-diameter and tall-stature trees. Previous studies have further considered structural complexity and larger trees as determinants of AGC. Yet it remains unclear what drives differential diversity-AGC relationships across vegetation types.</p> <p>2. Here, we test whether structural complexity and large-sized trees play an influential role in explaining shifting diversity-AGC relationships across vegetation types, using a 22.3 ha sampled dataset of 124 inventory plots in woodlands, gallery forests, tree/shrub savannahs and mixed plantations in West Africa.</p> <p>3. Natural vegetation had greater species richness and structural complexity than mixed plantations, as expected. In addition, AGC was highest in gallery forests and mixed plantations, which is consistent with favorable environmental conditions in the former and high stocking densities and presence of fast-growing species in the latter. Significant interaction effects of species richness and vegetation on AGC revealed a vegetation-dependent species richness-AGC relationship: consistently, we found positive species richness-AGC relationship in both mixed plantations and woodlands, and nonsignificant patterns in gallery forests and tree/shrub savannah. Further, there was a vegetation-dependent mediation of structural complexity in linking species richness to AGC, with stronger positive structural complexity effects where species richness-AGC relationships were positive, and stronger positive large-sized trees' effect where species richness-AGC relationships were neutral.</p> <p>4. Our study provides strong evidence of vegetation-dependent species richness-AGC relationships, which operated through differential mediation by structural complexity of the species richness and large trees' effects. We conclude that even higher species richness in diversified ecosystems may not always relate positively with AGC, and that neutral pattern may arise possibly as a result of larger dominant individual trees imposing a slow stand dynamic flux and overruling species richness effects.</p>
Data from: The role of plant-soil feedbacks in stabilizing a reindeer-induced vegetation shift in subarctic tundra
1.Herbivory can drive vegetation into different states of productivity and community composition, and these changes may be stable over time due to historical contingency effects. Interactions with abiotic and biotic soil components can contribute to such long‐term legacies in plant communities through stabilizing positive feedbacks. 2.We studied the role of plant‐soil feedbacks in maintaining vegetation changes caused by historical (~1350‐1900 AD) reindeer herding in northern Sweden. These historical milking grounds (HMGs) consist of meadow plant communities formed in naturally nutrient poor heath or naturally nutrient rich shrub‐dominated vegetation, and are still clearly visible in the landscape, a century after active use ceased. 3.We selected two phytometer species: the forb Potentilla crantzii as representative of HMG vegetation, and the dwarf shrub Betula nana, as representative of control vegetation. We grew both species under glasshouse conditions on soils derived from replicated HMG and paired control plots, using live soils and sterilized (γ‐radiation)‐inoculated soils, to separate between biotic and abiotic soil effects. 4.A net negative plant‐soil feedback for B. nana biomass in its home (i.e., control) soil and a net positive feedback for P. crantzii in its home (i.e., HMG) soil in heath habitat was partly driven by the soil biotic community. However, abiotic differences in mineral nitrogen (N) concentrations between control and HMG soils were a stronger driver of differences in plant growth. Positive feedbacks maintaining a high mineral nutrient availability are thus important, especially in nutrient poor habitats. 5.The positive plant responses to higher soil mineral N concentrations, combined with positive biotic plant‐soil feedbacks, might shift the competitive balance in favour of typical HMG plant species, thereby contributing to stability of HMG plant communities. Our data indicate that herbivore‐driven changes in the interactions between plants and both biotic and abiotic components of the soil persist over long temporal scales.
Data and code for "Topography and climate drive recent shifts in vegetation productivity dynamics"
<p>This zip file includes data and code for manuscript "<span><span>Topography and climate drive recent shifts in vegetation productivity dynamics</span></span>".</p>
Data for 'Post-disturbance recovery drives 21st century vegetation shifts in the Boreal forest in a dynamic vegetation model'
<p>This is the database containing all the LPJ-GUESS output data used in the paper. For LPJ-GUESS model code, refer to https://zenodo.org/record/8065737. For data processing refer to https://github.com/lucialayr/borealRecovery </p> <p> </p> <p>If you are interested in the raw data, please contact me. </p>
Data from: Vegetation structure mediates a shift in predator avoidance behavior in a range-edge population
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Data from: Structural complexity and large-sized trees explain shifting species richness and carbon relationship across vegetation types
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Data from: The role of plant-soil feedbacks in stabilizing a reindeer-induced vegetation shift in subarctic tundra
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Data from: Pervasive early 21st-century vegetation changes across Danish semi-natural ecosystems – more losers than winners and a shift towards competitive, tall-growing species
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Dataset: Species presence, trait and philogeny database. Data from: Shift from trait convergence to divergence along old field succession. Journal of Vegetation Science.
<p>This dataset was use in the manuscript "Shift from trait convergence to divergence along old field succession" publish at Journal of Vegetation Science. It contains the data of species presence at three different plots and species trait values (SLA, LDMC, height, seed weight and Phylogeny). We show that at the initial stage of succession, there is a scale-invariant pattern of trait convergence. On the contrary, in the late and intermediate stages of succession we observed that trait divergence became frequent at smaller grains and extents. The trend along the chronosequence is consistent with the theoretical hypothesis that predicts a shift from convergence to divergence along succession.</p>
SHIFT: Vegetation Plot Characterization, Santa Barbara County, CA, 2022
This dataset contains vegetation plot locations, descriptions, fractional cover, and sample identifier information from surveys conducted as part of the 2022 NASA Surface Biology Geology (SBG) High Frequency Time series (SHIFT) campaign. Surveys took place from 2022-02-23 to 2022-09-27 at the Jack and Laura Dangermond Preserve, Sedgwick Reserve, and Carpinteria Salt Marsh Reserve, which are located in Santa Barbara County, California, USA. This project collected field data contemporaneously with weekly flights of the NASA Airborne Visible-Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) facility instrument over the study areas. Plot information includes: plot tree subform, species lists, plot description, plot samples characterization, and plot location and contextual information. Related data packages contain additional biogeochemical, reflectance, and foliar data. Survey data and metadata are presented in comma-separated values (*.csv) format along with survey plot polygons in GeoJSON (*.geojson) format.
SHIFT: Vegetation Plot Photos, Santa Barbara, CA, USA, 2022
This dataset contains photographs of the plots where field vegetation sampling was conducted during the 2022 NASA Surface Biology Geology (SBG) High Frequency Time series (SHIFT) campaign. Sampling occurred at the Jack and Laura Dangermond Preserve, Sedgwick Reserve, and Carpinteria Salt Marsh Reserve, which are located in Santa Barbara County, California, USA. Photographs were taken from 2022-02-23 to 2022-09-18. This project collected field data contemporaneously with weekly flights of Airborne Visible-Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) over the study areas. Related SHIFT data packages contain additional biogeochemical, reflectance, and foliar data.
Data from: Discrepancies in vegetation phenology trends and shift patterns in different climatic zones in middle and eastern Eurasia between 1982 and 2015
Changes in vegetation phenology directly reflect the response of vegetation growth to climate change. In this study, using the Normalized Difference Vegetation Index (NDVI) dataset from 1982 to 2015, we extracted start date of vegetation growing season (SOS), end date of vegetation growing season (EOS) and length of vegetation growing season (LOS) in the middle and eastern Eurasia region and evaluated linear trends in SOS, EOS and LOS for the entire study area, as well as for four climatic zones. The results show that the LOS has significantly increased by 0.27 d/yr (days per year), mostly due to a significantly advanced SOS (-0.20 d/yr) and a slightly delayed EOS (0.07 d/yr) over the entire study area from 1982 to 2015. The vegetation phenology trends in the four climatic zones are not continuous throughout the 34 year period. Furthermore, discrepancies in the shifting patterns of vegetation phenology trend existed among different climatic zones. Turning points (TP) of SOS trends in the Cold zone, Temperate zone and Tibetan Plateau zone occurred in the mid or late 1990s. The advanced trends of SOS in the Cold zone, Temperate zone and Tibetan Plateau zone exhibited accelerated, stalled and reversed patterns after the corresponding TP, respectively. The TP did not occurred in Cold-Temperate zone, where the SOS showed a consistent and continuous advance. TPs of EOS trends in the Cold zone, Cold-Temperate zone, Temperate zone and Tibetan Plateau zone occurred in the late 1980s or mid-1990s. The EOS in the Cold zone, Cold-Temperate zone, Temperate zone and Tibetan Plateau zone showed weak advanced or delayed trends after the corresponding TP, which were comparable with the delayed trends before the corresponding TP. The shift patterns of LOS trends were primarily influenced by the shift patterns of SOS trends and were also heterogeneous within climatic zones.
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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)
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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.