Evaluating population responses of Greater sage-grouse to variation in public grazing records at broad scales
Dates
Publication Date
2017-03-21
Start Date
2001-03-01
End Date
2014-12-31
Citation
Monroe, A.P., 2017, Evaluating population responses of Greater sage-grouse to variation in public grazing records at broad scales: U.S. Geological Survey data release, https://doi.org/10.5066/F70K26RK.
Summary
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 [...]
Summary
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.
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Type: Related Primary Publication
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.
The state-space analysis estimates effects of grazing level, timing, and NDVI on the rate of population for lek counts of male greater sage-grouse in Wyoming, USA (2004-2014). Covariates for grazing level, timing, and NDVI could be lagged by 1-2 years. Additional covariates include mean sagebrush cover and cumulative burned area over the previous 10 years. We also include indicator variables for Department of the Interior Bureau of Land Management allotment and field office (management unit). The Land Health Standard analysis evaluates whether grazing timings and levels (relative grazing index) varied the year after an allotment failed one or more Land Health Standard, which could indicate adjustments in livestock management in response to land health evaluations. Finally, 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%).
