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 Rangeland Resources & Systems Research: Fort Collins, CO
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ARS Home Plains Area Fort Collins, Colorado Center for Agricultural Resources Research Rangeland Resources & Systems Research People & Locations







Sean  Kearney
                        Rangeland Resources & Systems Research

                        




                        
                        Non-Federal Affiliate
                        Phone: (970) 492-7139
                        
                        
                        Fax: (Employee information on this page comes from the REE Directory. Please contact your front office staff to update the REE Directory.)
                            **Publications**
                                                (Clicking on the reprint icon
                                                    Reprint Icon
                                                    will take you to the publication reprint.)Toward broad-scale mapping and characterization of prairie dog colonies from airborne imagery using deep learning
                                                        

- (Peer Reviewed Journal)Kearney, S.P., Porensky, L.M., Augustine, D.J., Pellatz, D.W. 2023. Toward broad-scale mapping and characterization of prairie dog colonies from airborne imagery using deep learning. Ecological Indicators. 154. Article 110684. https://doi.org/10.1016/j.ecolind.2023.110684.Adaptive, multi-paddock, rotational grazing management alters foraging behavior and spatial grazing distribution of free-ranging cattle
                                                        

- (Peer Reviewed Journal)Augustine, D.J., Kearney, S.P., Raynor, E.J., Porensky, L.M., Derner, J.D. 2023. Adaptive, multi-paddock, rotational grazing management alters foraging behavior and spatial grazing distribution of free-ranging cattle. Agriculture, Ecosystems and Environment. 352. Article 108521. https://doi.org/10.1016/j.agee.2023.108521.Indicators of water use efficiency across diverse agroecosystems and spatiotemporal scales
                                                        

- (Peer Reviewed Journal)Hoover, D.L., Abendroth, L.J., Browning, D.M., Saha, A., Snyder, K.A., Wagle, P., Witthaus, L.M., Baffaut, C., Biederman, J.A., Bosch, D.D., Bracho, R., Busch, D., Clark, P., Ellsworth, P.Z., Fay, P.A., Flerchinger, G.N., Kearney, S.P., Levers, L.R., Saliendra, N.Z., Schmer, M.R., Schomberg, H.H., Scott, R.L. 2022. Indicators of water use efficiency across diverse agroecosystems and spatiotemporal scales. Science of the Total Environment. 864. Article e160992. https://doi.org/10.1016/j.scitotenv.2022.160992.Can measurements of foraging behaviour predict variation in weight gains of free-ranging cattle?
                                                        

- (Peer Reviewed Journal)Augustine, D.J., Raynor, E.J., Kearney, S.P., Derner, J.D. 2022. Can measurements of foraging behaviour predict variation in weight gains of free-ranging cattle? Animal Production Science. Special Issue: AAAS|Stobbs Lecture. https://doi.org/10.1071/AN21560.Monitoring standing herbaceous biomass and thresholds in semiarid rangelands from harmonized Landsat 8 and Sentinel-2 imagery to support within-season adaptive management
                                                        

- (Peer Reviewed Journal)Kearney, S.P., Porensky, L.M., Augustine, D.J., Gaffney, R.M., Derner, J.D. 2022. Monitoring standing herbaceous biomass and thresholds in semiarid rangelands from harmonized Landsat 8 and Sentinel-2 imagery to support within-season adaptive management. Remote Sensing of Environment. 271. Article e112907. https://doi.org/10.1016/j.rse.2022.112907.Using hyperspectral imagery to characterize rangeland vegetation composition at process-relevant scales
                                                        

- (Peer Reviewed Journal)Gaffney, R.M., Augustine, D.J., Kearney, S.P., Porensky, L.M. 2021. Using hyperspectral imagery to characterize rangeland vegetation composition at process-relevant scales. Remote Sensing. 13. Article 4603. https//doi.org/10.3390/rs13224603.Predicting spatial-temporal patterns of diet quality and large herbivore performance using satellite time series
                                                        

- (Peer Reviewed Journal)Kearney, S.P., Porensky, L.M., Augustine, D.J., Derner, J.D., Gao, F.N. 2022. Predicting spatial-temporal patterns of diet quality and large herbivore performance using satellite time series. Ecological Applications. 32. Article e2503. https://doi.org/10.1002/eap.2503.Big data reveals drivers of vegetation phenology and cattle productivity in semi-arid rangelands

- (Abstract Only)
                    ARS News Articles
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                                                New Research Reveals How Grazing Management Practices Affect Cattle Weight Gain by Altering Foraging Behavioritem
                                                A New Way to Predict Grazing Cattle Weight Gain on Rangelands From Satellite Imagery


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