{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T08:30:47Z","timestamp":1774945847746,"version":"3.50.1"},"reference-count":44,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2020,1,29]],"date-time":"2020-01-29T00:00:00Z","timestamp":1580256000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Premium Funding Project for Academic Human Resources Development in Beijing Union University","award":["BPHR2019DZ01"],"award-info":[{"award-number":["BPHR2019DZ01"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41771049 and 41471033"],"award-info":[{"award-number":["41771049 and 41471033"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Autumn phenology is a crucial indicator for identifying the alpine grassland growing season\u2019s end date on the Qinghai-Tibet Plateau (QTP), which intensely controls biogeochemical cycles in this ecosystem. Although autumn phenology is thought to be mainly influenced by the preseason temperature, precipitation, and insolation in alpine grasslands, the relative contributions of these climatic factors on the QTP remain uncertain. To quantify the impacts of climatic factors on autumn phenology, we built stepwise linear regression models for 91 meteorological stations on the QTP using in situ herb brown-off dates, remotely sensed autumn phenological metrics, and a multi-factor climate dataset during an optimum length period. The results show that autumn precipitation has the most extensive influence on interannual variation in alpine grassland autumn phenology. On average, a 10 mm increase in autumn precipitation during the optimum length period may lead to a delay of 0.2 to 4 days in the middle senescence date (P &lt; 0.05) across the alpine grasslands. The daily minimum air temperature is the second most important controlling factor, namely, a 1 \u00b0C increase in the mean autumn minimum temperature during the optimum length period may induce a delay of 1.6 to 9.3 days in the middle senescence date (P &lt; 0.05) across the alpine grasslands. Sunshine duration is the third extensive controlling factor. However, its influence is spatially limited. Moreover, the relative humidity and wind speed also have strong influences at a few stations. Further analysis indicates that the autumn phenology at stations with less autumn precipitation is more sensitive to precipitation variation than at stations with more autumn precipitation. This implies that autumn drought in arid regions would intensely accelerate the leaf senescence of alpine grasslands. This study suggests that precipitation should be considered for improving process-based autumn phenology models in QTP alpine grasslands.<\/jats:p>","DOI":"10.3390\/rs12030431","type":"journal-article","created":{"date-parts":[[2020,1,29]],"date-time":"2020-01-29T10:51:07Z","timestamp":1580295067000},"page":"431","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":61,"title":["Precipitation and Minimum Temperature are Primary Climatic Controls of Alpine Grassland Autumn Phenology on the Qinghai-Tibet Plateau"],"prefix":"10.3390","volume":"12","author":[{"given":"Shuai","family":"An","sequence":"first","affiliation":[{"name":"College of Applied Arts and Science, Beijing Union University, Beijing 100191, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3012-7091","authenticated-orcid":false,"given":"Xiaoqiu","family":"Chen","sequence":"additional","affiliation":[{"name":"Laboratory for Earth Surface Processes of the Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8456-0547","authenticated-orcid":false,"given":"Xiaoyang","family":"Zhang","sequence":"additional","affiliation":[{"name":"Geospatial Sciences Center of Excellence (GSCE), South Dakota State University, Brookings, SD 57007, USA"},{"name":"Department of Geography &amp; Geospatial Sciences, South Dakota State University, Brookings, SD 57007, USA"}]},{"given":"Weiguang","family":"Lang","sequence":"additional","affiliation":[{"name":"Laboratory for Earth Surface Processes of the Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China"}]},{"given":"Shilong","family":"Ren","sequence":"additional","affiliation":[{"name":"Environment Research Institute, Shandong University, Qingdao 266237, China"}]},{"given":"Lin","family":"Xu","sequence":"additional","affiliation":[{"name":"College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193, China"}]}],"member":"1968","published-online":{"date-parts":[[2020,1,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2940","DOI":"10.1111\/gcb.12277","article-title":"The impacts of climate change and human activities on biogeochemical cycles on the Qinghai-Tibetan Plateau","volume":"19","author":"Chen","year":"2013","journal-title":"Glob. 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