Modeling the spatial distribution of grazing intensity in Kazakhstan.

dc.contributor.authorHankerson, Brett R
dc.contributor.authorSchierhorn, Florian
dc.contributor.authorPrishchepov, Alexander V
dc.contributor.authorDong, Changxing
dc.contributor.authorEisfelder, Christina
dc.contributor.authorMüller, Daniel
dc.coverage.spatialLATITUDE: 52.000000 * LONGITUDE: 64.000000
dc.date.accessioned2019-11-23T11:23:57Z
dc.date.available2019-11-23T11:23:57Z
dc.date.issued2018-12-20
dc.description.abstractWe developed a spatial model that combines fine-scale livestock numbers with their associated energy requirements to distribute livestock grazing demand onto a map of energy supply, with the aim of estimating where and to what degree pasture is being utilized. We applied our model to Kazakhstan, which contains large grassland areas that historically have been used for extensive livestock production but for which the current extent, and thus the potential for increasing livestock production, is unknown. We measured the grazing demand of Kazakh livestock in 2015 at 286 Petajoules, which was 25% of the estimated maximum sustainable energy supply that is available to livestock for grazing. The model resulted in a grazed area of 1.22 million km2, or 48% of the area theoretically available for grazing in Kazakhstan, with most utilized land grazed at low intensities (average off-take rate was 13% of total biomass energy production). Under a conservative scenario, our estimations showed a production potential of 0.13 million tons of beef additional to 2015 production (31% increase), and much more with utilization of distant pastures. This model is an important step forward in evaluating pasture use and available land resources, and can be adapted at any spatial scale for any region in the world.
dc.formatimage/tiff, 3142.0 kBytes
dc.identifierhttps://doi.pangaea.de/10.1594/PANGAEA.896908
dc.identifierhttps://doi.org/10.1594/PANGAEA.896908
dc.identifier.citationHankerson, Brett R; Schierhorn, Florian; Prishchepov, Alexander V; Dong, Changxing; Eisfelder, Christina; Müller, Daniel (in press): Modeling the spatial distribution of grazing intensity in Kazakhstan. PLoS ONE, https://doi.org/10.1371/journal.pone.0210051
dc.identifier.urihttps://repository.geologyscience.ru/handle/123456789/7321
dc.language.isoen
dc.publisherPANGAEA
dc.relationCoordinate reference system (URI: http://store.pangaea.de/Publications/HankersonB-etal_2018/CRS.zip)
dc.relationLayer definition file to color the map in QGIS (URI: http://store.pangaea.de/Publications/HankersonB-etal_2018/OffTakeRate.qml)
dc.relationRead me - Livestock grazing intensity in Kazakhstan from 2015 based on NPP and spatial allocation model (URI: http://store.pangaea.de/Publications/HankersonB-etal_2018/FurtherDetails.docx)
dc.rightsCC-BY-4.0: Creative Commons Attribution 4.0 International
dc.rightsAccess constraints: unrestricted
dc.sourceSupplement to: Hankerson, Brett R; Schierhorn, Florian; Prishchepov, Alexander V; Dong, Changxing; Eisfelder, Christina; Müller, Daniel (in press): Modeling the spatial distribution of grazing intensity in Kazakhstan. PLoS ONE, https://doi.org/10.1371/journal.pone.0210051
dc.subjectKazakhstan
dc.titleModeling the spatial distribution of grazing intensity in Kazakhstan.
dc.title.alternativeLivestock grazing intensity in Kazakhstan from 2015 based on NPP and spatial allocation model
dc.typeDataset

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