000120064 001__ 120064
000120064 005__ 20240319081012.0
000120064 0247_ $$2doi$$a10.1038/s41598-022-22391-x
000120064 0248_ $$2sideral$$a130937
000120064 037__ $$aART-2022-130937
000120064 041__ $$aeng
000120064 100__ $$aRevuelto, J.
000120064 245__ $$aIntermediate snowpack melt-out dates guarantee the highest seasonal grasslands greening in the Pyrenees
000120064 260__ $$c2022
000120064 5060_ $$aAccess copy available to the general public$$fUnrestricted
000120064 5203_ $$aIn mountain areas, the phenology and productivity of grassland are closely related to snow dynamics. However, the influence that snow melt timing has on grassland growing still needs further attention for a full understanding, particularly at high spatial resolution. Aiming to reduce this knowledge gap, this work exploits 1 m resolution snow depth and Normalized Difference Vegetation Index observations acquired with an Unmanned Aerial Vehicle at a sub-alpine site in the Pyrenees. During two snow seasons (2019–2020 and 2020–2021), 14 NDVI and 17 snow depth distributions were acquired over 48 ha. Despite the snow dynamics being different in the two seasons, the response of grasslands greening to snow melt-out exhibited a very similar pattern in both. The NDVI temporal evolution in areas with distinct melt-out dates reveals that sectors where the melt-out date occurs in late April or early May (optimum melt-out) reach the maximum vegetation productivity. Zones with an earlier or a later melt-out rarely reach peak NDVI values. The results obtained in this study area, suggest that knowledge about snow depth distribution is not needed to understand NDVI grassland dynamics. The analysis did not reveal a clear link between the spatial variability in snow duration and the diversity and richness of grassland communities within the study area.
000120064 536__ $$9info:eu-repo/grantAgreement/ES/MICINN/IJC-2018-036260-I$$9info:eu-repo/grantAgreement/ES/MINECO/CGL2017-82216-R
000120064 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000120064 590__ $$a4.6$$b2022
000120064 592__ $$a0.973$$b2022
000120064 591__ $$aMULTIDISCIPLINARY SCIENCES$$b22 / 73 = 0.301$$c2022$$dQ2$$eT1
000120064 593__ $$aMultidisciplinary$$c2022$$dQ1
000120064 594__ $$a7.5$$b2022
000120064 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000120064 700__ $$aGómez, D.
000120064 700__ $$aAlonso González, E.
000120064 700__ $$aVidaller, I.
000120064 700__ $$aRojas Heredia, F.
000120064 700__ $$aDeschamps Berger, C.
000120064 700__ $$aGarcía Jiménez, J.
000120064 700__ $$aRodríguez López, G.$$uUniversidad de Zaragoza
000120064 700__ $$aSobrino, J.
000120064 700__ $$0(orcid)0000-0001-7403-1764$$aMontorio, R.$$uUniversidad de Zaragoza
000120064 700__ $$aPerez Cabello, F.
000120064 700__ $$aLópez Moreno, J. I.
000120064 7102_ $$14000$$2415$$aUniversidad de Zaragoza$$bDpto. Análisis Económico$$cÁrea Fund. Análisis Económico
000120064 7102_ $$13006$$2010$$aUniversidad de Zaragoza$$bDpto. Geograf. Ordenac.Territ.$$cÁrea Análisis Geográfico Regi.
000120064 773__ $$g12, 1 (2022), 18328 [11 pp.]$$pSci. rep. (Nat. Publ. Group)$$tScientific reports (Nature Publishing Group)$$x2045-2322
000120064 8564_ $$s3886506$$uhttps://zaguan.unizar.es/record/120064/files/texto_completo.pdf$$yVersión publicada
000120064 8564_ $$s2491367$$uhttps://zaguan.unizar.es/record/120064/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000120064 909CO $$ooai:zaguan.unizar.es:120064$$particulos$$pdriver
000120064 951__ $$a2024-03-18-15:15:23
000120064 980__ $$aARTICLE