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136 results for “rangeland”

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zenodo28/100

Supplementary material 5 from: Lee T, Alemseged Y, Mitchell A (2018) Dropping Hints: Estimating the diets of livestock in rangelands using DNA metabarcoding of faeces. Metabarcoding and Metagenomics 2: e22467. https://doi.org/10.3897/mbmg.2.22467

Family level taxa (BOLD Data) ('*' indicates that the column contains no taxa).

opencc-zeroApr 2018View details →
zenodo28/100

Supplementary material 4 from: Lee T, Alemseged Y, Mitchell A (2018) Dropping Hints: Estimating the diets of livestock in rangelands using DNA metabarcoding of faeces. Metabarcoding and Metagenomics 2: e22467. https://doi.org/10.3897/mbmg.2.22467

Number of paired-end reads for each sample resulting from Illumina Miseq Nano run.

opencc-zeroApr 2018View details →
zenodo28/100

Supplementary material 8 from: Lee T, Alemseged Y, Mitchell A (2018) Dropping Hints: Estimating the diets of livestock in rangelands using DNA metabarcoding of faeces. Metabarcoding and Metagenomics 2: e22467. https://doi.org/10.3897/mbmg.2.22467

Taxon accumulation curves for Merino specimens.

opencc-zeroApr 2018View details →
zenodo28/100

Supplementary material 9 from: Lee T, Alemseged Y, Mitchell A (2018) Dropping Hints: Estimating the diets of livestock in rangelands using DNA metabarcoding of faeces. Metabarcoding and Metagenomics 2: e22467. https://doi.org/10.3897/mbmg.2.22467

Taxon accumulation curves for goat samples.

opencc-zeroApr 2018View details →
dryad28/100

Species co-occurrence shapes spatial variability in plant diversity–biomass relationships in natural rangelands under different grazing intensities

<p>Grazing can alter plant species interactions in natural rangelands, which in turn might influence the productivity of the ecosystem but we do not fully understand how spatial variability in plant diversity-biomass relationships are modulated by grazing intensity. Here, we hypothesized that plant species co-occurrence in rangelands is mainly driven by niche segregation due to grazing and heterogeneity in local resources, and that grazing therefore modulates diversity–biomass relationships.<b> </b>We tested our hypothesis across 35 rangeland sites in Iran, using a species co-occurrence index to assess plant spatial aggregation within each site. At each site, we measured aboveground biomass, plant diversity, topography, soil nutrients and three levels of grazing intensity. High spatial segregation of plant communities (low species co-occurrence) was found at heavily grazed sites, whereas greater spatial aggregation (high species co-occurrence) was found on low and moderate grazed sites, showing varied associational patterns of species with grazing intensity. Soil nutrients increased with grazing intensity and spatial segregation of plant communities was greater at sites with high soil nutrient concentrations, indicating that grazing intensity influences the spatial heterogeneity of plant communities via nutrients deposited in urine and faeces. Declining plant biomass with grazing intensity was related to a strong decline in graminoid species diversity, which suggests that the diversity-biomass relationship is influenced by selective grazing of palatable species. The relationships between species co-occurrence and biomass or plant diversity suggest non-random patterns in species co-occurrences with grazing intensity, which could be the result of competition driven by high livestock grazing intensity. We therefore suggest that rangeland stocking rates should be managed properly to maintain rangeland production while promoting plant diversity.</p>

opencc-zeroJul 2021View details →
dryad28/100

Tradeoffs with utility-scale solar development and ungulates on western rangelands

<p>Utility scale solar energy (USSE) has become an efficient and cost-effective form of renewable energy, with an expanding footprint into rangelands that provide important habitat for many ungulate populations. Using GPS data collected before and after construction, we documented the potential impacts of USSE on pronghorn, including direct habitat loss, indirect habitat loss, and barrier effects to both resident and migratory population segments. Our case study highlights the challenges that USSE poses to ungulate conservation, including 1) impermeable security fencing that removes habitat and reduces connectivity, and 2) the lack of guidelines for minimizing solar impacts to ungulates. We encourage agencies and industry to work towards a unified siting process and develop ungulate-specific best management practices to minimize habitat loss and retain landscape connectivity. Ungulate biodiversity and ecosystem services (e.g., long-distance migrations) in arid rangelands are important considerations when balancing the global benefits of renewable energy with local wildlife impacts.</p>

opencc-zeroJul 2021View details →
zenodo28/100

Supplementary material 1 from: Gaskin JF, Chapagain N, Schwarzländer M, Tancos MA, West NM (2023) Genetic diversity and structure of Crupina vulgaris (common crupina): a noxious rangeland weed of the western United States. NeoBiota 82: 57-66. https://doi.org/10.3897/neobiota.82.90229

Population Data and AFLP Data

opencc-zeroFeb 2023View details →
dryad28/100

Data from: Root traits are related to plant water-use among rangeland Mediterranean species

Open the record for dataset details and reuse information.

publicApr 2017View details →
dryad28/100

Identifying relationships between multi-scale social-ecological factors to explore ungulate health in a Western Kazakhstan rangeland

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publicNov 2021View details →
dryad28/100

Tradeoffs with utility-scale solar development and ungulates on western rangelands

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publicJul 2021View details →
dryad28/100

Data from: Experimentally simulating warmer and wetter climate additively improves rangeland quality on the Tibetan Plateau

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publicNov 2018View details →
dryad28/100

Species co-occurrence shapes spatial variability in plant diversity–biomass relationships in natural rangelands under different grazing intensities

Open the record for dataset details and reuse information.

publicJul 2021View details →
zenodo24/100

Rangeland Analysis Platform - vegetation cover 1984

<p>Rangeland Analysis Platform vegetation cover 1984</p> <p>These data represent rangeland cover estimates determined by Jones et al. (2018)<br> and as accessible on the Rangeland Analysis Platform (https://rangelands.app).<br> Values are percent aerial cover of the following rangeland functional groups:</p> <p>Band 1 - annual forbs and grasses<br> Band 2 - bare ground<br> Band 3 - litter<br> Band 4 - perennial forbs and grasses<br> Band 5 - shrubs<br> Band 6 - trees<br> No Data value = 255</p> <p>Although these data were produced across a broad region, they are primarily<br> intended for rangeland ecosystems. Cover estimates may not be suitable in other<br> ecosystems, e.g., forests, agricultural lands.</p> <p>Data are in WGS84 Geographic Coordinate System (EPSG:4326); spatial resolution<br> is approximately 30m.</p> <p>Please attribute these data to:<br> Jones, M. O., B. W. Allred, D. E. Naugle, J. D. Maestas, P. Donnelly, L. J.<br> Metz, J. Karl, R. Smith, B. Bestelmeyer, C. Boyd, J. D. Kerby, and J. D. McIver.<br> 2018. Innovation in rangeland monitoring: annual, 30 m, plant functional type<br> percent cover maps for U.S. rangelands, 1984-2017. Ecosphere 9:e02430.<br> http://dx.doi.org/10.1002/ecs2.2430</p>

opencc-by-nc-4.0Jun 2019View details →
zenodo24/100

Rangeland Analysis Platform - vegetation cover 1987

<p>Rangeland Analysis Platform vegetation cover 1987</p> <p>These data represent rangeland cover estimates determined by Jones et al. (2018)<br> and as accessible on the Rangeland Analysis Platform (https://rangelands.app).<br> Values are percent aerial cover of the following rangeland functional groups:</p> <p>Band 1 - annual forbs and grasses<br> Band 2 - bare ground<br> Band 3 - litter<br> Band 4 - perennial forbs and grasses<br> Band 5 - shrubs<br> Band 6 - trees<br> No Data value = 255</p> <p>Although these data were produced across a broad region, they are primarily<br> intended for rangeland ecosystems. Cover estimates may not be suitable in other<br> ecosystems, e.g., forests, agricultural lands.</p> <p>Data are in WGS84 Geographic Coordinate System (EPSG:4326); spatial resolution<br> is approximately 30m.</p> <p>Please attribute these data to:<br> Jones, M. O., B. W. Allred, D. E. Naugle, J. D. Maestas, P. Donnelly, L. J.<br> Metz, J. Karl, R. Smith, B. Bestelmeyer, C. Boyd, J. D. Kerby, and J. D. McIver.<br> 2018. Innovation in rangeland monitoring: annual, 30 m, plant functional type<br> percent cover maps for U.S. rangelands, 1984-2017. Ecosphere 9:e02430.<br> http://dx.doi.org/10.1002/ecs2.2430</p>

opencc-by-nc-4.0Jun 2019View details →
zenodo24/100

Rangeland Analysis Platform - vegetation cover 1992

<p>Rangeland Analysis Platform vegetation cover 1992</p> <p>These data represent rangeland cover estimates determined by Jones et al. (2018)<br> and as accessible on the Rangeland Analysis Platform (https://rangelands.app).<br> Values are percent aerial cover of the following rangeland functional groups:</p> <p>Band 1 - annual forbs and grasses<br> Band 2 - bare ground<br> Band 3 - litter<br> Band 4 - perennial forbs and grasses<br> Band 5 - shrubs<br> Band 6 - trees<br> No Data value = 255</p> <p>Although these data were produced across a broad region, they are primarily<br> intended for rangeland ecosystems. Cover estimates may not be suitable in other<br> ecosystems, e.g., forests, agricultural lands.</p> <p>Data are in WGS84 Geographic Coordinate System (EPSG:4326); spatial resolution<br> is approximately 30m.</p> <p>Please attribute these data to:<br> Jones, M. O., B. W. Allred, D. E. Naugle, J. D. Maestas, P. Donnelly, L. J.<br> Metz, J. Karl, R. Smith, B. Bestelmeyer, C. Boyd, J. D. Kerby, and J. D. McIver.<br> 2018. Innovation in rangeland monitoring: annual, 30 m, plant functional type<br> percent cover maps for U.S. rangelands, 1984-2017. Ecosphere 9:e02430.<br> http://dx.doi.org/10.1002/ecs2.2430</p>

opencc-by-nc-4.0Jun 2019View details →
zenodo24/100

Rangeland Analysis Platform - vegetation cover 1989

<p>Rangeland Analysis Platform vegetation cover 1989</p> <p>These data represent rangeland cover estimates determined by Jones et al. (2018)<br> and as accessible on the Rangeland Analysis Platform (https://rangelands.app).<br> Values are percent aerial cover of the following rangeland functional groups:</p> <p>Band 1 - annual forbs and grasses<br> Band 2 - bare ground<br> Band 3 - litter<br> Band 4 - perennial forbs and grasses<br> Band 5 - shrubs<br> Band 6 - trees<br> No Data value = 255</p> <p>Although these data were produced across a broad region, they are primarily<br> intended for rangeland ecosystems. Cover estimates may not be suitable in other<br> ecosystems, e.g., forests, agricultural lands.</p> <p>Data are in WGS84 Geographic Coordinate System (EPSG:4326); spatial resolution<br> is approximately 30m.</p> <p>Please attribute these data to:<br> Jones, M. O., B. W. Allred, D. E. Naugle, J. D. Maestas, P. Donnelly, L. J.<br> Metz, J. Karl, R. Smith, B. Bestelmeyer, C. Boyd, J. D. Kerby, and J. D. McIver.<br> 2018. Innovation in rangeland monitoring: annual, 30 m, plant functional type<br> percent cover maps for U.S. rangelands, 1984-2017. Ecosphere 9:e02430.<br> http://dx.doi.org/10.1002/ecs2.2430</p>

opencc-by-nc-4.0Jun 2019View details →
zenodo24/100

Rangeland Analysis Platform - vegetation cover 1993

<p>Rangeland Analysis Platform vegetation cover 1993</p> <p>These data represent rangeland cover estimates determined by Jones et al. (2018)<br> and as accessible on the Rangeland Analysis Platform (https://rangelands.app).<br> Values are percent aerial cover of the following rangeland functional groups:</p> <p>Band 1 - annual forbs and grasses<br> Band 2 - bare ground<br> Band 3 - litter<br> Band 4 - perennial forbs and grasses<br> Band 5 - shrubs<br> Band 6 - trees<br> No Data value = 255</p> <p>Although these data were produced across a broad region, they are primarily<br> intended for rangeland ecosystems. Cover estimates may not be suitable in other<br> ecosystems, e.g., forests, agricultural lands.</p> <p>Data are in WGS84 Geographic Coordinate System (EPSG:4326); spatial resolution<br> is approximately 30m.</p> <p>Please attribute these data to:<br> Jones, M. O., B. W. Allred, D. E. Naugle, J. D. Maestas, P. Donnelly, L. J.<br> Metz, J. Karl, R. Smith, B. Bestelmeyer, C. Boyd, J. D. Kerby, and J. D. McIver.<br> 2018. Innovation in rangeland monitoring: annual, 30 m, plant functional type<br> percent cover maps for U.S. rangelands, 1984-2017. Ecosphere 9:e02430.<br> http://dx.doi.org/10.1002/ecs2.2430</p>

opencc-by-nc-4.0Jun 2019View details →
zenodo24/100

Rangeland Analysis Platform - vegetation cover 1996

<p>Rangeland Analysis Platform vegetation cover 1996</p> <p>These data represent rangeland cover estimates determined by Jones et al. (2018)<br> and as accessible on the Rangeland Analysis Platform (https://rangelands.app).<br> Values are percent aerial cover of the following rangeland functional groups:</p> <p>Band 1 - annual forbs and grasses<br> Band 2 - bare ground<br> Band 3 - litter<br> Band 4 - perennial forbs and grasses<br> Band 5 - shrubs<br> Band 6 - trees<br> No Data value = 255</p> <p>Although these data were produced across a broad region, they are primarily<br> intended for rangeland ecosystems. Cover estimates may not be suitable in other<br> ecosystems, e.g., forests, agricultural lands.</p> <p>Data are in WGS84 Geographic Coordinate System (EPSG:4326); spatial resolution<br> is approximately 30m.</p> <p>Please attribute these data to:<br> Jones, M. O., B. W. Allred, D. E. Naugle, J. D. Maestas, P. Donnelly, L. J.<br> Metz, J. Karl, R. Smith, B. Bestelmeyer, C. Boyd, J. D. Kerby, and J. D. McIver.<br> 2018. Innovation in rangeland monitoring: annual, 30 m, plant functional type<br> percent cover maps for U.S. rangelands, 1984-2017. Ecosphere 9:e02430.<br> http://dx.doi.org/10.1002/ecs2.2430</p>

opencc-by-nc-4.0Jun 2019View details →
zenodo24/100

Rangeland Analysis Platform - vegetation cover 1997

<p>Rangeland Analysis Platform vegetation cover 1997</p> <p>These data represent rangeland cover estimates determined by Jones et al. (2018)<br> and as accessible on the Rangeland Analysis Platform (https://rangelands.app).<br> Values are percent aerial cover of the following rangeland functional groups:</p> <p>Band 1 - annual forbs and grasses<br> Band 2 - bare ground<br> Band 3 - litter<br> Band 4 - perennial forbs and grasses<br> Band 5 - shrubs<br> Band 6 - trees<br> No Data value = 255</p> <p>Although these data were produced across a broad region, they are primarily<br> intended for rangeland ecosystems. Cover estimates may not be suitable in other<br> ecosystems, e.g., forests, agricultural lands.</p> <p>Data are in WGS84 Geographic Coordinate System (EPSG:4326); spatial resolution<br> is approximately 30m.</p> <p>Please attribute these data to:<br> Jones, M. O., B. W. Allred, D. E. Naugle, J. D. Maestas, P. Donnelly, L. J.<br> Metz, J. Karl, R. Smith, B. Bestelmeyer, C. Boyd, J. D. Kerby, and J. D. McIver.<br> 2018. Innovation in rangeland monitoring: annual, 30 m, plant functional type<br> percent cover maps for U.S. rangelands, 1984-2017. Ecosphere 9:e02430.<br> http://dx.doi.org/10.1002/ecs2.2430</p>

opencc-by-nc-4.0Jun 2019View details →
zenodo24/100

Rangeland Analysis Platform - vegetation cover 1985

<p>Rangeland Analysis Platform vegetation cover 1985</p> <p>These data represent rangeland cover estimates determined by Jones et al. (2018)<br> and as accessible on the Rangeland Analysis Platform (https://rangelands.app).<br> Values are percent aerial cover of the following rangeland functional groups:</p> <p>Band 1 - annual forbs and grasses<br> Band 2 - bare ground<br> Band 3 - litter<br> Band 4 - perennial forbs and grasses<br> Band 5 - shrubs<br> Band 6 - trees<br> No Data value = 255</p> <p>Although these data were produced across a broad region, they are primarily<br> intended for rangeland ecosystems. Cover estimates may not be suitable in other<br> ecosystems, e.g., forests, agricultural lands.</p> <p>Data are in WGS84 Geographic Coordinate System (EPSG:4326); spatial resolution<br> is approximately 30m.</p> <p>Please attribute these data to:<br> Jones, M. O., B. W. Allred, D. E. Naugle, J. D. Maestas, P. Donnelly, L. J.<br> Metz, J. Karl, R. Smith, B. Bestelmeyer, C. Boyd, J. D. Kerby, and J. D. McIver.<br> 2018. Innovation in rangeland monitoring: annual, 30 m, plant functional type<br> percent cover maps for U.S. rangelands, 1984-2017. Ecosphere 9:e02430.<br> http://dx.doi.org/10.1002/ecs2.2430</p>

opencc-by-nc-4.0Jun 2019View details →

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