{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,29]],"date-time":"2025-10-29T03:47:22Z","timestamp":1761709642648,"version":"build-2065373602"},"reference-count":35,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2019,12,3]],"date-time":"2019-12-03T00:00:00Z","timestamp":1575331200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Different livestock behaviors have distinct effects on grassland degradation. However, because direct observation of livestock behavior is time- and labor-intensive, an automated methodology to classify livestock behavior according to animal position and posture is necessary. We applied the Random Forest algorithm to predict livestock behaviors in the Horqin Sand Land by using Global Positioning System (GPS) and tri-axis accelerometer data and then confirmed the results through field observations. The overall accuracy of GPS models was 85% to 90% when the time interval was greater than 300\u2013800 s, which was approximated to the tri-axis model (96%) and GPS-tri models (96%). In the GPS model, the linear backward or forward distance were the most important determinants of behavior classification, and nongrazing was less than 30% when livestock travelled more than 30\u201350 m over a 5-min interval. For the tri-axis accelerometer model, the anteroposterior acceleration (\u20133 m\/s2) of neck movement was the most accurate determinant of livestock behavior classification. Using instantaneous acceleration of livestock body movement more precisely classified livestock behaviors than did GPS location-based distance metrics. When a tri-axis model is unavailable, GPS models will yield sufficiently reliable classification accuracy when an appropriate time interval is defined.<\/jats:p>","DOI":"10.3390\/s19235334","type":"journal-article","created":{"date-parts":[[2019,12,4]],"date-time":"2019-12-04T04:30:35Z","timestamp":1575433835000},"page":"5334","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Method for Classifying Behavior of Livestock on Fenced Temperate Rangeland in Northern China"],"prefix":"10.3390","volume":"19","author":[{"given":"Xiaowei","family":"Gou","sequence":"first","affiliation":[{"name":"The United Graduate School of Agricultural Sciences, Tottori University, 4-101 Koyama-Minami, Tottori 680-8553, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7690-0633","authenticated-orcid":false,"given":"Atsushi","family":"Tsunekawa","sequence":"additional","affiliation":[{"name":"Arid Land Research Center, Tottori University, 1390 Hamasaka, Tottori 680-0001, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5816-4898","authenticated-orcid":false,"given":"Fei","family":"Peng","sequence":"additional","affiliation":[{"name":"International Platform for Dryland Research and Education, Tottori University, 1390 Hamasaka, Tottori 680-0001, Japan"},{"name":"Key Laboratory of Desert and Desertification, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 73000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xueyong","family":"Zhao","sequence":"additional","affiliation":[{"name":"Naiman Desertification Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Tongliao 028300, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yulin","family":"Li","sequence":"additional","affiliation":[{"name":"Naiman Desertification Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Tongliao 028300, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jie","family":"Lian","sequence":"additional","affiliation":[{"name":"Naiman Desertification Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Tongliao 028300, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,12,3]]},"reference":[{"key":"ref_1","unstructured":"Assessment, Millennium Ecosystem (2005). Ecosystems and Human Well-Being, Island Press."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1016\/j.quascirev.2011.11.014","article-title":"A 2500 year record of natural and anthropogenic soil erosion in South Greenland","volume":"32","author":"Massa","year":"2012","journal-title":"Quat. Sci. Rev."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"248","DOI":"10.1002\/ldr.972","article-title":"Impact of the spatial and temporal arrangement of pastoral use on land degradation around animal concentration points","volume":"21","author":"Okayasu","year":"2010","journal-title":"Land Degrad. Dev."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1351","DOI":"10.1016\/j.jaridenv.2010.05.007","article-title":"Estimation of grazing intensity along grazing gradients\u2013the bias of nonlinearity","volume":"74","author":"Manthey","year":"2010","journal-title":"J. Arid Environ."},{"key":"ref_5","first-page":"386","article-title":"Mechanisms that result in large herbivore grazing distribution patterns","volume":"49","author":"Bailey","year":"1996","journal-title":"Rangel. Ecol. Manag. J. Range Manag. Arch."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1071\/RJ11062","article-title":"Characterising the spatial and temporal activities of free-ranging cows from GPS data","volume":"34","author":"Anderson","year":"2012","journal-title":"Rangel. J."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1016\/j.agee.2008.05.008","article-title":"Influence of historic sheep grazing on vegetation and soil properties of a Desert Steppe in Inner Mongolia","volume":"128","author":"Li","year":"2008","journal-title":"Agric. Ecosyst. Environ."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1023\/A:1014519206041","article-title":"Vegetation change along gradients from water sources in three grazed Mongolian ecosystems","volume":"157","year":"2001","journal-title":"Plant Ecol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"172","DOI":"10.1111\/j.1365-2494.2007.00579.x","article-title":"Effects of livestock breed and grazing intensity on grazing systems: 3. Effects on diversity of vegetation","volume":"62","author":"Scimone","year":"2007","journal-title":"Grass Forage Sci."},{"key":"ref_10","first-page":"491","article-title":"The influence of livestock trampling under intensive rotation grazing on soil hydrologic characteristics","volume":"39","author":"Warren","year":"1986","journal-title":"Rangel. Ecol. Manag. J. Range Manag. Arch."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"319","DOI":"10.1016\/j.anbehav.2007.01.010","article-title":"Slowness and acceleration: A new method to quantify the activity budget of chelonians","volume":"75","author":"Lagarde","year":"2008","journal-title":"Anim. Behav."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"262","DOI":"10.1016\/j.applanim.2007.06.021","article-title":"Classifying sows\u2019 activity types from acceleration patterns: An application of the multi-process Kalman filter","volume":"111","author":"Cornou","year":"2008","journal-title":"Appl. Anim. Behav. Sci."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1016\/j.applanim.2009.03.005","article-title":"Cow behaviour pattern recognition using a three-dimensional accelerometer and support vector machines","volume":"119","author":"Martiskainen","year":"2009","journal-title":"Appl. Anim. Behav. Sci."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1016\/j.compag.2014.10.018","article-title":"Behavioral classification of data from collars containing motion sensors in grazing cattle","volume":"110","author":"Handcock","year":"2015","journal-title":"Comput. Electron. Agric."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"75","DOI":"10.3354\/ab00039","article-title":"Activity and diving metabolism correlate in Steller sea lion Eumetopias jubatus","volume":"2","author":"Fahlman","year":"2008","journal-title":"Aquat. Biol."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1016\/j.jembe.2010.01.012","article-title":"Accelerating estimates of activity-specific metabolic rate in fishes: Testing the applicability of acceleration data-loggers","volume":"385","author":"Gleiss","year":"2010","journal-title":"J. Exp. Mar. Biol. Ecol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"471","DOI":"10.1242\/jeb.026377","article-title":"Estimating energy expenditure of animals using the accelerometry technique: Activity, inactivity and comparison with the heart-rate technique","volume":"212","author":"Green","year":"2009","journal-title":"J. Exp. Biol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1016\/j.zool.2007.07.011","article-title":"Acceleration versus heart rate for estimating energy expenditure and speed during locomotion in animals: Tests with an easy model species, Homo sapiens","volume":"111","author":"Halsey","year":"2008","journal-title":"Zoology"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Homburger, H., Schneider, M.K., Hilfiker, S., and L\u00fcscher, A. (2014). Inferring behavioral states of grazing livestock from high-frequency position data alone. PLoS ONE, 9.","DOI":"10.1371\/journal.pone.0114522"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/j.applanim.2003.11.003","article-title":"The use of differentially corrected global positioning system to monitor activities of cattle at pasture","volume":"85","author":"Schlecht","year":"2004","journal-title":"Appl. Anim. Behav. Sci."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"De Weerd, N., van Langevelde, F., van Oeveren, H., Nolet, B.A., K\u00f6lzsch, A., Prins, H.H., and de Boer, W.F. (2015). Deriving animal behaviour from high-frequency GPS: Tracking cows in open and forested habitat. PLoS ONE, 10.","DOI":"10.1371\/journal.pone.0129030"},{"key":"ref_22","first-page":"88","article-title":"Carbon accumulation in the bulk soil and different soil fractions during the rehabilitation of desertified grassland in Horqin Sandy Land (Northern China)","volume":"63","author":"Li","year":"2015","journal-title":"Pol. J. Ecol."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1007\/s11104-008-9826-7","article-title":"Spatial heterogeneity of soil properties and vegetation\u2013soil relationships following vegetation restoration of mobile dunes in Horqin Sandy Land, Northern China","volume":"318","author":"Zuo","year":"2009","journal-title":"Plant Soil"},{"key":"ref_24","first-page":"346","article-title":"The animal-unit and animal-unit-equivalent concepts in range science","volume":"38","author":"Scarnecchia","year":"1985","journal-title":"Rangel. Ecol. Manag. J. Range Manag. Arch."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1277","DOI":"10.5194\/bg-9-1277-2012","article-title":"Indirect drivers of plant diversity-productivity relationship in semiarid sandy grasslands","volume":"9","author":"Zuo","year":"2012","journal-title":"Biogeosciences"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1081","DOI":"10.1111\/j.1365-2656.2006.01127.x","article-title":"Moving towards acceleration for estimates of activity-specific metabolic rate in free-living animals: The case of the cormorant","volume":"75","author":"Wilson","year":"2006","journal-title":"J. Anim. Ecol."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"47","DOI":"10.3354\/esr00084","article-title":"Identification of animal movement patterns using tri-axial accelerometry","volume":"10","author":"Shepard","year":"2008","journal-title":"Endanger. Species Res."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"673","DOI":"10.1007\/s10980-009-9341-0","article-title":"Gradient modeling of conifer species using random forests","volume":"24","author":"Evans","year":"2009","journal-title":"Landsc. Ecol."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1995","DOI":"10.1016\/j.ecolmodel.2010.04.017","article-title":"Ecological relevance of performance criteria for species distribution models","volume":"221","author":"Mouton","year":"2010","journal-title":"Ecol. Model."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"2783","DOI":"10.1890\/07-0539.1","article-title":"Random forests for classification in ecology","volume":"88","author":"Cutler","year":"2007","journal-title":"Ecology"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"751","DOI":"10.1002\/sim.4780110606","article-title":"Estimating the number of clusters for the analysis of correlated binary response variables from unbalanced data","volume":"11","author":"Shoukri","year":"1992","journal-title":"Stat. Med."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"3711","DOI":"10.3390\/s130303711","article-title":"Assessing herbivore foraging behavior with GPS collars in a semiarid grassland","volume":"13","author":"Augustine","year":"2013","journal-title":"Sensors"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"427","DOI":"10.3758\/BF03192796","article-title":"Application testing of a new three-dimensional acceleration measuring system with wireless data transfer (WAS) for behavior analysis","volume":"38","author":"Scheibe","year":"2006","journal-title":"Behav. Res. Methods"},{"key":"ref_35","first-page":"259","article-title":"Grazing systems, stocking rates, and cattle behavior in southeastern Wyoming","volume":"44","author":"Hepworth","year":"1991","journal-title":"Rangel. Ecol. Manag. J. Range Manag. Arch."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/23\/5334\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:39:52Z","timestamp":1760189992000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/23\/5334"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,12,3]]},"references-count":35,"journal-issue":{"issue":"23","published-online":{"date-parts":[[2019,12]]}},"alternative-id":["s19235334"],"URL":"https:\/\/doi.org\/10.3390\/s19235334","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2019,12,3]]}}}