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1,104 results for “aridity”
Plant richness of the terrestrial ecoregions of the world with a mean aridity index lower than 0.65
<p>Data used to compose the <strong>Figure 1</strong> and the <strong>Table S1</strong> of the paper <strong>Biogeography of Global Drylands</strong>, by Maestre <em>et al</em>. (2021).</p>
Data for Table S10 of the article "Source-to-sink aeolian fluxes from arid landscape dynamics in the Lut Desert"
<p>Exhaustive list of the 227 individual denudation rates in arid areas compiled to estimate median denudation rate and sediment discharge for the internal river system of the Lut watershed.</p>
Vegetation survey (BACI and Paired-plots) from arid central Australia for impacts of buffel grass on resident native plant communities
<p>The data set accompanies the accepted paper in Ecosphere. The data set includes two experimental appraoches to assess the spread and impacts of buffel grass, Cenchrus cilairis, in the Aṉangu Pitjantjatjara Yankunytjatjara (APY) Lands of arid central Australia: a Before-After-Control-Impact (BACI) experiment over 25 years at 15 sites (surveyed in 1994-95 and 2018-19), and a spatially paired-plot (randomised-block) experiment at 18 sites (surveyed in 2018-19). Both experiments spanned two geographic regions (~ 300 km apart) and multiple vegetation communities amongst flat plains and rocky hills landforms. Each experimental design has a plant species data set, and a data set that includes site variables and summed relative cover of plant functional groups. Data collection methodology is described in the accompanying paper, and summarised here.</p> <p>Each site was one hectare in size. The ecological data was collected in accordance with standard biological survey methods in South Australia (Heard and Channon 1997), including recording of plant species and cover abundance, life form, height class and habitat variables including percent bare earth, litter, rock/strew and soil type (clay percent). Fire history for the previous 25 years was also available from fire scar mapping. Species cover-abundance was estimated in the field using a modified Braun-Blanquet scale and later converted to a raw continuous variable based on the mid-point of the cover class: 1% (1-10 plants, <5% cover); 2% (sparsely present, <5% cover; 3% (plentiful but <5% cover); 15% (5 to 25% cover class); 37% (25 to 50% cover class); 63% (50 to 75% cover class). Buffel grass was recorded on the same scale. Plant species were vouchered and identification checked post-field by the South Australian Hebarium. Plant taxonomy reflects current names (as of 2015) in the Biological Databases of South Australia and taxonomy was aligned between the 1990s and 2020s decades. Recently some species have been split into multiple species (e.g. <em>Acacia aneura</em>, Mulga) but this latest taxonomy was not adopted to retain taxonomic alignment within the dataset. The raw mid-point percent cover was converted to relative percent cover by dividing each species’ (or groups’) raw cover by the summed cover of all species at that site (including buffel grass + understorey + overstorey species). Classification of plants into functional groups was based on field assessed (1) height class + (2) life form, and literature-derived (3) life strategy (perennial or annual) + (4) Native status to South Australia. Height classes were grouped into overstorey (>1m in height) and understorey (≤1m). Summed relative cover for each functional group per site is included in the site and cover data sets to facilitate modelling of cover with site variables. The plant species data sets is the full list of species and cover abundance recorded at each site which can be used for analysis of community composition, diversity, turnover or individual species change. Sensitive species (one species in this dataset) has had the coordinates denatured by 10km due according to the requirements of the Biological Database of South Australia for sensitive species. All coordinates provided in MGA 52 Eastings and Northings (UTM, Australian National Grid). </p> <p>The authors wish to acknowledge Traditional Owners and Aṉangu Pitjantjatjara Yankunytjatjara (APY) Lands Organisation who gave permission for collaboration, data collection, photographs and reporting on and about their Traditional Lands. Data is jointly the Intellectual Property of Aṉangu as the Traditional Owners and the author team, and approval has been granted for research and publication use with appropriate acknowledgment of Aṉangu and the author team. The 1990s baseline data is also the Intellectual Property of the South Australian Government and is made publicly available under a licencing agreement with the Biological Databases of South Australia (licence number 2412). Many people assisted in the field during the 1990s and 2020s vegetation surveys and are wholly acknowledged. APY Land Management, Alinytjara Wilurara Landscape Board, Central Land Council, Ten Deserts Project, Charles Darwin University, South Australian Department for Environment and Water, State Herbarium of South Australia, Holsworth Wildlife Research Endowment, Jill Landsberg Trust and Ecological Society of Australia all provided either funding and/or in-kind support of the project. Study conducted with APY Executive Board approval, South Australian Scientific Permit Q26782 and Northern Territory Wildlife Permit 63104. </p> <p> </p> <p> </p>
Semi-Arid Grassland Nitrogen Addition Experiment: New Mexico, 2018-2021
This dataset contains field and laboratory incubation measurements from a four-year nutrient addition experiment (2018–2021) conducted in three adjacent (<5 km apart) Chihuahuan Desert grasslands near Carlsbad Caverns National Park, New Mexico, USA (32°10′31″N, 104°26′38″W). The three replicate grassland sites were dominated by different grass species: Bouteloua gracilis (“Native Grama” site), Muhlenbergia setifolia (“Native Muhly” site), and Eragrostis lehmanniana (“Invasive Lovegrass” site). The Native Grama and Invasive Lovegrass sites were located on recently deposited alluvial soils classified as Entisols (Ustic Torrifluvents), formed from gravelly alluvium derived from limestone. Soils at the Native Muhly site were classified as shallow Aridisols formed from colluvium and residuum weathered from limestone and dolomite. Plot soils at the Native Grama and Invasive Lovegrass sites were sandy loam, while soils at the Native Muhly site were loam. Pre-treatment soil chemistry (collected May 2018 at 0–5 cm depth) was relatively consistent across sites, with pH ranging from 7.6 to 7.8 and similar inorganic N concentrations. Experimental field plots at each site received annual additions of nitrogen (+2 or +4 kg N ha⁻¹ yr⁻¹ as ammonium nitrate), carbon (+6 g m⁻² as sucrose), or no additions (ambient control). In 2020, a supplemental water treatment was applied only at the Native Grama site to simulate an additional 55 mm of rainfall during the monsoon season. Field data include measurements of soil chemistry (pH, inorganic nutrients, extractable organic C, total N), microbial biomass (C, N, P), extracellular enzyme activities, vegetation cover by functional group, species richness, Shannon diversity indices, and foliar chemistry (%C, %N, C:N ratios). Measurements were collected seasonally (pre-monsoon, monsoon, winter) or annually at peak biomass from 2018 through 2021. Laboratory incubations were conducted to complement field measurements. In 2019, a 30-day nitrogen t
Belowground responses to altered precipitation regimes in two semi-arid grasslands
Predicted climate change extremes, such as severe and prolonged drought, may profoundly impact biogeochemical processes like carbon and nitrogen cycling in water-limited ecosystems. To increase our understanding of how extreme climate events impact belowground ecosystem processes, we investigated the effects of five years of severe growing season drought and two-month delay in monsoon precipitation on belowground productivity and biogeochemical processes in two semi-arid grasslands. This experiment takes place during the fifth year of the Extreme Drought in Grassland Experiment (EDGE) at the Sevilleta National Wildlife Refuge (SNWR), a Long-Term Ecological Research in central New Mexico, USA. The two grassland sites a Chihuahuan Desert grassland dominated by Bouteloua eriopoda and Great Plains grassland dominated by B. gracilis are ~5km apart in the SWNR. The EDGE platform was established in the spring of 2012 (pre-treatment). Each site contains three treatments (ten replicates): ambient rainfall, extreme growing season drought, and delayed monsoon. The extreme drought treatment reduces growing season rainfall (April through September) each year by 66%, which equates to a 50% reduction of annual precipitation while maintaining natural precipitation patterns. There are 10 replicates per treatment within each site. All plots are 3 x 4 m in size and are paired spatially into blocks with treatments assigned randomly within a block. We measured an array of belowground and biogeochemical variables. Each variable was measured either once, twice, or three times (specific information on sampling scheme for each measured variable in methods section). Belowground net primary productivity, standing crop root biomass, total organic carbon, and total nitrogen were measured once. Extractable organic carbon, extractable total nitrogen, microbial biomass carbon, microbial biomass nitrogen and extracellular enzymes were measured twice. Available soil nitrate, available soil ammonium,
Dataset to manuscript: Soil organic carbon stocks and quality in small-scale tropical, sub-humid and semi-arid watersheds under shrubland and dry deciduous forest in southwestern India
<p>Raw data to the manuscript entitled "Soil organic carbon stocks and quality in small-scale tropical, sub-humid and semi-arid watersheds under shrubland and dry deciduous forest in southwestern India" by Severin-Luca Bellè, Jean Riotte, Muddu Sekhar, Laurent Ruiz, Marcus Schiedung and Samuel Abiven.</p> <p>Data files include all raw data of soil cores (20211111_Raw_data.zip), data measured on composited samples (20211111_Composite_data.zip) and DRIFT spectra (20211111_DRIFT_data.zip).</p> <p>Files ending with var_names are the README files.</p>
Modern aridity in the Altai-Sayan Mountain Range derived from multiple millennial proxies
<p><em>1500-year stable carbon and oxygen isotopes in larch tree-ring cellulose from the Altai-Sayan Mountain Range region </em>(49-51N, 87-89 E)</p> <p><em>Regional summer (June-July-August) precipitation reconstruction for the Altai-Sayan Mountain Range region based on d<sup>13</sup>C in tree-ring cellulose (d<sup>13</sup>C<sub>cell </sub>) combined with Co/Inc and Rb/Sr from Teletskoe Lake core sediments (TLs).</em></p> <p><em>Regional summer air temperature (June-July-August) reconstruction based on d<sup>18</sup>O<sub> </sub>in tree-ring cellulose (d<sup>18</sup>O<sub>cell</sub>), tree-ring width (TRW), latewood density (MXD) and elemental concentrations (Ca, Ti, Br/Sr) in the Teletskoe Lake core sediments (TLs).</em></p>
Datasets for paper 'Cabello, V., Renner, A., Giampietro, M. 2019. Relational analysis of the resource nexus in arid land crop production. Advances in Water Resources 130:258-629'
<p>Datasets produced for the paper Cabello, V., Renner, A., Giampietro, M. 2019.<em> </em>Relational analysis of the resource nexus in arid land crop production. <em>Advances in Water Resources </em>130:258-269</p>
Indicative distribution map for Ecosystem Functional Group F1.6 Episodic arid rivers
<p>This archive contains indicative distribution maps and profiles for <strong>F1.6 Episodic arid rivers</strong>, a ecosystem functional group (EFG, level 3) of the <a href="https://global-ecosystems.org/">IUCN Global Ecosystem Typology</a> (v2.0). Please refer to Keith <em>et al.</em> (2020) for details.</p> <p>The descriptive profiles provide brief summaries of key ecological traits and processes, maps are indicative of global distribution patterns, and are not intended to represent fine-scale patterns. The maps show areas of the world containing major (value of 1, coloured red) or minor occurrences (value of 2, coloured yellow) of each ecosystem functional group. Minor occurrences are areas where an ecosystem functional group is scattered in patches within matrices of other ecosystem functional groups or where they occur in substantial areas, but only within a segment of a larger region. Given bounds of resolution and accuracy of source data, the maps should be used to query which EFG are likely to occur within areas, rather than which occur at particular point locations. Detailed methods and references for the maps are included in the profile (xml format).</p>
Indicative distribution map for Ecosystem Functional Group TF1.5 Episodic arid floodplains
<p>This archive contains indicative distribution maps and profiles for <strong>TF1.5 Episodic arid floodplains</strong>, a ecosystem functional group (EFG, level 3) of the <a href="https://global-ecosystems.org/">IUCN Global Ecosystem Typology</a> (v2.0). Please refer to Keith <em>et al.</em> (2020) for details.</p> <p>The descriptive profiles provide brief summaries of key ecological traits and processes, maps are indicative of global distribution patterns, and are not intended to represent fine-scale patterns. The maps show areas of the world containing major (value of 1, coloured red) or minor occurrences (value of 2, coloured yellow) of each ecosystem functional group. Minor occurrences are areas where an ecosystem functional group is scattered in patches within matrices of other ecosystem functional groups or where they occur in substantial areas, but only within a segment of a larger region. Given bounds of resolution and accuracy of source data, the maps should be used to query which EFG are likely to occur within areas, rather than which occur at particular point locations. Detailed methods and references for the maps are included in the profile (xml format).</p>
Indicative distribution map for Ecosystem Functional Group T5.5 Hyper-arid deserts
<p>This archive contains indicative distribution maps and profiles for <strong>T5.5 Hyper-arid deserts</strong>, a ecosystem functional group (EFG, level 3) of the <a href="https://global-ecosystems.org/">IUCN Global Ecosystem Typology</a> (v2.0). Please refer to Keith <em>et al.</em> (2020) for details.</p> <p>The descriptive profiles provide brief summaries of key ecological traits and processes, maps are indicative of global distribution patterns, and are not intended to represent fine-scale patterns. The maps show areas of the world containing major (value of 1, coloured red) or minor occurrences (value of 2, coloured yellow) of each ecosystem functional group. Minor occurrences are areas where an ecosystem functional group is scattered in patches within matrices of other ecosystem functional groups or where they occur in substantial areas, but only within a segment of a larger region. Given bounds of resolution and accuracy of source data, the maps should be used to query which EFG are likely to occur within areas, rather than which occur at particular point locations. Detailed methods and references for the maps are included in the profile (xml format).</p>
Evenness response to aridity gradients: Data required for Smith et al. 2022 Oecologia
These are the required data to do all analyses in Smith et al. 2022 in Oecologia using the assembled database across gradients. Included are the richness, evenness, and site level abiotic data. Paper abstract: We sought to understand the role that water availability (expressed as an aridity index) plays in determining regional and global patterns of richness and evenness, and in turn how these water availability-diversity relationships may result in different richness-evenness relationships at regional and global scales. We examined relationships between water availability, richness and evenness for eight grassy biomes spanning broad water availability gradients on five continents. Our study found that relationships between richness and water availability switched from positive for drier (South Africa, Tibet and USA) vs. negative for wetter (India) biomes, though were not significant for the remaining biomes. In contrast, only the India biome showed a significant relationship between water availability and evenness, which was negative. Globally, the richness-water availability relationship was hump-shaped, however, not significant for evenness. At the regional scale, a positive richness-evenness relationship was found for grassy biomes in India and Inner Mongolia, China. In contrast, this relationship was weakly concave-up globally. These results suggest that different, independent factors are determining patterns of species richness and evenness in grassy biomes, resulting in differing richness-evenness relationships at regional and global scales. As a consequence, richness and evenness may respond very differently across spatial gradients to anthropogenic changes, such as climate change.
CDRRC growing season aridity and grazing season vegetation biomass data
Growing season aridity and livestock grazing seasonality can influence biomass production of perennial grasses in dryland systems. For this study, we used a long-term dataset (1967-2004) to investigate the independent and joint effects of growing season aridity (De Martonne aridity index calculated for the months of June through September) and grazing season (yearlong continuous, fall, winter/spring, or summer season grazing) on the mean annual biomass (kg per hectare) of the perennial grasses Bouteloua eriopoda (black grama), Aristida spp. (threeawn), and Sporobolus spp. (dropseed) in a southwestern United States Chihuahuan Desert rangeland system. Biomass data were collected from 78 permanent sampling transects that were within one mile (1609.34 m) distance to water. Over the 37-year study period, total perennial grass biomass decreased as growing season aridity increased, but the extent of this relationship depended upon season of grazing and specific grass taxon. Aridity-related decreases in total perennial grass biomass were most severe in the summer and fall summer seasonal grazing pastures, primarily due to inherently low black grama levels. Our findings indicate that over time, summer and fall grazing can potentially exacerbate the negative effects of increasing aridity on perennial grass biomass.
Aggregate mesquite litter chemistry following soil-mixing and decomposition in a semi-arid grassland at the Jornada Basin LTER, 2010-2012
This dataset contains litter carbon content, nitrogen content, and associated chemistry data from a litter decomposition experiment at the Jornada Basin LTER in 2010 to 2012. To assess the role of soil-litter mixing (SLM) in aridland litter decomposition, litterbags were deployed in the Chihuahuan Desert and interrelationships between vegetation structure, SLM, and rates of decomposition were quantified. To assess the role of vegetation structure, litterbags were deployed in contrasting vegetation microsites, including grass, shrub, and bare ground microsites. This dataset contains litter chemistry data from the experiment including percent carbon, percent nitrogen, ash corrections, and the carbon to nitrogen ratio of litter in recovered bags. This study is complete.
Aggregate mesquite litter mass-loss following soil-mixing and decomposition in a semi-arid grassland at the Jornada Basin LTER, 2010-2012
This package contains litter mass loss data from a litter decomposition experiment at the Jornada Basin LTER. To assess the role of soil-litter mixing (SLM) in aridland litter decomposition, litterbags were deployed in the Chihuahuan Desert and interrelationships between vegetation structure, SLM, and rates of decomposition were quantified. To assess the role of vegetation structure, litterbags were deployed in contrasting vegetation microsites, including grass, shrub, and bare ground microsites. This dataset contains the mass-loss data (including ash-corrections) from the experiment. This study is complete.
Intra-urban variations in land surface phenology in a semi-arid environment
<p>Data repository for 'Intra-urban variations in land surface phenology in a semi-arid environment', ERL</p> <p>Contact: Ben Crawford, University of Colorado Denver (benjamin.crawford@ucdenver.edu)</p> <p>Data description:</p> <ul> <li>NDVI.zip: <ul> <li>MODIS NDVI geotif rasters for Denver study area</li> <li>Additional metadata provided in subdirectories</li> </ul> </li> <li>LST.zip: <ul> <li>Landsat LST geotif rasters for Denver study area</li> </ul> </li> <li>Tair.zip <ul> <li>Seasonal modeled air temperatures for Denver study area (as described in the manuscript and supplemental information)</li> </ul> </li> <li>Den470_LandCover_250m_WGS.tif <ul> <li>Denver study area 2018 land cover fractions, derived from 1 m data at https://data.drcog.org/</li> </ul> </li> </ul> <p> </p>
Thirty-eight years of CO 2 fertilization have outpaced growing aridity to drive greening of Australian woody ecosystems
<p>Data and code for "Thirty-eight years of CO 2 fertilization have outpaced growing aridity to drive greening of Australian woody ecosystems"</p>
Morpho-sedimentary outlines displayed in Figures 1, S1, and S6-S15 of the article "Source-to-sink aeolian fluxes from arid landscape dynamics in the Lut Desert"
<p>Morpho-sedimentary outlines of the aeolian landforms in the Lut Desert.</p>
Topoedaphic constraints on woody plant cover in a semi-arid grassland
<p>Provided is an excel spreadsheet which contains data used to estimate maximum potential shrub cover across a semi-arid grassland in Southern Arizona. Data was obtained using a classified shrub cover (mesquite) map of Las Cienegas National Conservation Area in Southeastern Arizona which was derived using 2017 NAIP imagery which is free available on EarthExplorer. Classified shrub cover map was created using an unsupervised ISO classification technique within ArcGIS. This shrub cover map was upscaled to 100m and a number of topoedaphic spatial layers were overlaid onto this shrub cover layer and their layers extracted per pixel. This data was then analyized within R using a segmented quantile regression approach to identify maximum shrub cover by topoedaphic characteristics at the 95th percent quantile. For sample of quantile code please contact the corresponding author.</p> <p>Topoedaphic variables analyzed in this data set are: <br> Shrub Cover (%)<br> Elevation (m)<br> Slope Inclination (°)<br> Slope Aspect (Cardinal Direction)<br> Value 2 = North<br> Value 3 = East<br> Value 4 = South<br> Value 5 = West<br> Percent Clay between 0 to 5cm (%)<br> Depth to bedrock (cm)<br> Topographic Wetness index (TWI) (unitless with higher values representing more run-on/wetter conditions)</p> <p>Shrub cover was analyzed at the study site level and at the ecological site level. </p>
Simulated climate change reduced the capacity of lichen-dominated biocrusts to act as carbon sinks in two semi-arid Mediterranean ecosystems
<p> Biocrust gas exchange measurements used as input data for this study. The methods are described in detail in the related identifier paper.</p>
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