Foraging behavior and spatial grazing distribution of free-ranging cattle 2014-2018 on the Central Plains Experimental Range
공공데이터포털
,Data were collected on the Central Plains Experimental Range (CPER) from 2014-2018, near Nunn, Colorado as part of the common experiments in grazinglands for the Long-Term Agroecosystem Research network. LTAR scientists seek to create new knowledge regarding sustainable management of grazinglands. This dataset on cattle foraging behavior and distribution provides new information towards understanding how management practices influence grazing livestock movements in space and time. The common experiment at CPER is called Collaborative Adaptive Rangeland Management (CARM) and is a ten-year ranch-scale (2,600-ha) social-ecological experiment designed to examine how adaptive rotations of a single large cattle herd among paddocks within a heterogeneous landscape during the growing season (collaborative, adaptive rangeland management; CARM) contrasts with continuous, season-long grazing of paddocks by small non-rotational herds (traditional rangeland management; TRM). Differences in movement patterns between the two treatments were examined with data collected from global positioning system tracking collars (Lotek 3300LR GPS) combined with activity sensors. These data were used to determine daily metrics of foraging behavior by steers in both treatments at five-minute intervals and include (1) location, (2) distance moved within 5 minutes, and (3) and grazing activity. These data are from the first half of the CARM experiment to support the publication, "Adaptive, multi-paddock, rotational grazing management alters foraging behavior and spatial grazing distribution of free-ranging cattle.",Resources in this dataset:,,
Broad-scale analysis of greater sage-grouse population trends in response to grazing in Wyoming, USA (2004-2014), at 3.25 km scale
공공데이터포털
The file 'ssm_data_3.25.csv' contains data necessary for analyzing state-space models for male greater sage-grouse (Centrocercus urophasianus) populations in response to grazing level (relative grazing index), timing, and NDVI (Normalized Difference Vegetation Index) in Wyoming, USA. In this case, all covariates were measured within 3.25 km of lek sites.
Broad-scale analysis of greater sage-grouse population trends in response to grazing in Wyoming, USA (2004-2014), at 3.25 km scale
공공데이터포털
The file 'ssm_data_3.25.csv' contains data necessary for analyzing state-space models for male greater sage-grouse (Centrocercus urophasianus) populations in response to grazing level (relative grazing index), timing, and NDVI (Normalized Difference Vegetation Index) in Wyoming, USA. In this case, all covariates were measured within 3.25 km of lek sites.
Bird, Ground Dwelling Vertebrate and Invertebrate Data
공공데이터포털
These data were collected as part of the NSW Grazing Study. Surveys were conducted at a subset (108 sites) of the 451 NSW Grazing Study sites to determine the abundance and diversity of fauna. The following methods were employed; Small mammals and reptiles were surveyed using dry pit-fall traps, funnel traps, Elliott traps and timed searches. Vertebrate trap lines consisted of two 20 L buckets (150 mm deep), two 150 mm diameter PVC pipes (500-600 mm deep), and four double-ended funnel traps placed under or along a 20 m drift-fence. Pit-fall traps were placed flush with the ground under the drift fence. Captured specimens were provided with sarking sheets, shade cloth sheets, PVC tubes, Styrofoam blocks, litter and some soil in each trap to prevent over-heating or drowning in the event of rain. Ant rid powder and sprays were used at sites where ants were abundant. Funnel traps were located at either side of the drift fence, between the end pairs of pit-fall traps. A sarking or 90% shade-cloth cover was placed over the top of the funnel traps to buffer temperatures inside the traps. Captured specimens were provided with a cardboard roll and/or a sheet of sarking for shelter. All fauna surveys were conducted with approval from the Animal Ethics Committee (approval number: 140602/02). Four Elliot traps were also positioned near each trap line in appropriate habitat patches such as under shrubs, or near logs or rocks to enhance capture rates. Each trap was baited with a mixture of rolled oats and peanut butter. Traps were covered with shade cloth or sarking cover to buffer temperature extremes for captured specimens. All trap-lines were checked and cleared early each morning and late each afternoon over a 4 day period (8 times). The species name of each specimen captured was recorded and the specimen marked to obtain an assessment of the number of recaptures. Two 30 minute habitat searches were undertaken at each 100 m x 200m site on different afternoons. Searches were targeted towards potential reptile habitat (e.g. open patches, leaf litter, logs, rocks, bark) by experienced personnel. Species were generally identified without the need for capture, although some species did need to be captured with a noose or by hand for identification. Bird surveys were conducted during two springs to early summers over two consecutive years. Each year, all sites were sampled twice for 20 minutes, on different days at different times, by a single observer. Surveys commenced from dawn and concluded by 12 noon or if the ambient temperature reached 30 degrees C or if it became excessively windy (>39 km/hr). In addition, we collected data on the cover and density of trees, shrubs, groundcover, bare soil, litter and coarse woody debris along a 200 m belt transect that formed the central line of the 2 ha bird sampling plot. For each sampling site we derived a habitat complexity score. Six habitat attributes were rated on a scale of 0 to 3 and the scores for all six attributes totalled to give an overall score for a site. Thus sites with a larger score have greater habitat complexity. Ground dwelling invertebrates were sampled using both wet and dry pitfall traps. Wet pitfall traps were 250 ml plastic screw-top containers half filled with ethylene glycol, installed at each corner of a 5 m x 5 m plot, plus one trap located centrally within the plot. Each pitfall trap was placed flush with the ground with a cover to prevent damage or loss of material due to rainfall. Traps were left open for five consecutive nights at each site. Incidental captures of large invertebrates (i.e. scorpions, spiders, centipedes, beetles, etc. > 1 cm, but not ants) were also collected from the vertebrate fauna pitfall traps each morning.
Data from: Can measurements of foraging behaviour predict variation in weight gains of free-ranging cattle?
공공데이터포털
,Technologies are now available to continuously monitor livestock foraging behaviours, but it remains unclear whether such measurements can meaningfully inform livestock grazing management decisions. Empirical studies in extensive rangelands are needed to quantify relationships between short-term foraging behaviours (e.g. minutes to days) and longer-term measures of animal performance. The objective of this study was to examine whether four different ways of measuring daily foraging behaviour (grazing-bout duration, grazing time per day, velocity while grazing, and turn angle while grazing) were related to weight gain by free-ranging yearling steers grazing semiarid rangeland. These data include measurements interpreted from yearling steer outfitted with neck collars supporting a solar-powered device that measured GPS locations at 5 minute intervals and used an accelerometer to predict grazing activity at 4 second intervals. Average daily weight gains of steers are included as well as an estimate of standing forage biomass derived from the Harmonized Landsat-Sentinel remote-sensing product. These data support research to advance knowledge regarding the use of on-animal sensors that monitor foraging behaviour, which have the potential to transmit indicators to livestock managers in real time (e.g. daily). This approach can help inform decisions such as when to move animals among paddocks, or when to sell or transition animals from rangeland to confined feeding operations.,,
Broad-scale analysis of greater sage-grouse population trends in response to grazing records in Wyoming, USA (2004-2014)
공공데이터포털
The file 'ssm_data.csv' contains data necessary for analyzing state-space models for male greater sage-grouse (Centrocercus urophasianus) populations in response to grazing level (relative grazing index), timing, and NDVI (Normalized Difference Vegetation Index) in Wyoming, USA, and then to compare models with 10-fold cross validation scores (Monroe et al. 2017). Literature Cited: Monroe, A. P., C. L. Aldridge, T. J. Assal, K. E. Veblen, D. A. Pyke, and M. L. Casazza. 2017. Patterns in Greater Sage-grouse Population Dynamics Correspond with Public Grazing Records at Broad Scales. Ecological Applications. doi: 10.1002/eap.1512.
Broad-scale analysis of greater sage-grouse population trends in response to grazing records in Wyoming, USA (2004-2014)
공공데이터포털
The file 'ssm_data.csv' contains data necessary for analyzing state-space models for male greater sage-grouse (Centrocercus urophasianus) populations in response to grazing level (relative grazing index), timing, and NDVI (Normalized Difference Vegetation Index) in Wyoming, USA, and then to compare models with 10-fold cross validation scores (Monroe et al. 2017). Literature Cited: Monroe, A. P., C. L. Aldridge, T. J. Assal, K. E. Veblen, D. A. Pyke, and M. L. Casazza. 2017. Patterns in Greater Sage-grouse Population Dynamics Correspond with Public Grazing Records at Broad Scales. Ecological Applications. doi: 10.1002/eap.1512.
Evaluating population responses of Greater sage-grouse to variation in public grazing records at broad scales
공공데이터포털
In 'Broad-scale analysis of greater sage-grouse population trends in response to grazing records in Wyoming, USA (2004-2014)', we provide data and R code necessary for analyzing state-space models for male greater sage-grouse (Centrocercus urophasianus) populations in response to grazing level, timing, and NDVI in Wyoming, USA, and then to compare models with 10-fold cross validation scores (Monroe et al. 2017). In 'Analysis of Land Health Standard failure among allotments in Wyoming, USA (2001-2009)', we provide data and R code necessary for logistic regression analyzing effects of grazing level and timing on the probability of an allotment failing one or more Land Health Standard (LHS) the previous year (Monroe et al. 2017). Relative predictive ability of models are then compared with a 10-fold cross-validation score. In 'Data to evaluate sensitivity of model results to scale and allotment overlap threshold', we provide data used to evaluate the sensitivity of our results to our choice of scale (6.44 km around lek sites) and the overlap threshold for allotments with grazing data (>75%). Literature Cited: Monroe, A. P., C. L. Aldridge, T. J. Assal, K. E. Veblen, D. A. Pyke, and M. L. Casazza. 2017. Patterns in Greater Sage-grouse Population Dynamics Correspond with Public Grazing Records at Broad Scales. Ecological Applications. doi: 10.1002/eap.1512.
Jornada Experimental Range (USDA-ARS) monthly stocking data and pasture shape files from 1915 to 1952
공공데이터포털
This data package contains two types of data for the Jornada Experimental Range (JER) from 1915 to 1952: 1) shape files containing polygons and attribute tables that represent the pasture configurations on the Jornada Experimental Range and 2) monthly stocking data from these pastures. The livestock represented in the stocking data comprise cattle, horse, sheep, and goats. Grazing goats were infrequent and are grouped with sheep in the source data. As such for this data set, they are included in the sheep category. Stocking data are expressed in animal unit months (AUM), which is based on metabolic weight.This data package provides finer resolution AUM data than knb-lter-jrn.210412001, which presents the annual stocking data for the entire JER from 1916 to 2001. The stocking data in this package begins in June of 1915 and continues through December of 1952, the last year for which the researchers on this project have verified and digitized historical pasture configurations on the JER.https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-jrn&identifier=210412001