Plant phenology is a commonly used and suitable indicator of the impact of climate change on vegetation. In mountainous areas, phenology is governed by environmental drivers such as air temperature, photoperiod and the presence of snow. In this study, digital images collected over 3 years (2009, 2010 and 2011) in a subalpine grassland site were used to investigate the relationship between the timing of snowmelt and the beginning of the growing season in both the spatial and the temporal dimension.The image analysis was conducted for a wide area corresponding to approximately 150m2 to characterize the spatial heterogeneity of grassland phenology. The investigated area was divided into 855 10×10 pixel cells, and for each cell annual time series of green chromatic coordinates (gcc) were computed from hourly images. To analyse the spatial pattern of phenology, the beginning of the season for each cell was extracted from the gcc time series. Based on the same grid dimension, three maps of yearly snowmelt date corresponding to the day of the year in which the snow in each cell disappeared from the ground were obtained.Although complete snowmelt in the area occurred rapidly, within a maximum of six days, several distinct spatial patterns were identified with snowmelt occurring earlier in convex compared to concave areas. Differences in snowmelt dates were quite unexpectedly negatively related to the beginning of the growing season. The negative correlation was explained considering that areas characterized by different microtopography have also a different species composition: the growing season began earlier in concave areas preferred by opportunistic species with a fast development after snowmelt while phenological development of grass typical of convex areas can take longer. This behaviour was especially evident in 2011 characterized by an extremely anticipated snowmelt. On the contrary, the analysis of the relationship between the timing of snowmelt and the beginning of the season between the three years analysed in this study, highlighted an advancement of the beginning of the growing season in 2011. However, this is valid only in areas characterized by the abundance of opportunistic species such as forbs for which the snow cover plays a major role in determining the beginning of phenological development. The results presented in this study support the possibility of using repeat digital photography to analyse the role of plant species composition on phenology in complex ecosystems such as subalpine and alpine grasslands. © 2014 Elsevier B.V.

Using digital camera images to analyse snowmelt and phenology of a subalpine grassland

SINISCALCO, Maria Consolata;
2014

Abstract

Plant phenology is a commonly used and suitable indicator of the impact of climate change on vegetation. In mountainous areas, phenology is governed by environmental drivers such as air temperature, photoperiod and the presence of snow. In this study, digital images collected over 3 years (2009, 2010 and 2011) in a subalpine grassland site were used to investigate the relationship between the timing of snowmelt and the beginning of the growing season in both the spatial and the temporal dimension.The image analysis was conducted for a wide area corresponding to approximately 150m2 to characterize the spatial heterogeneity of grassland phenology. The investigated area was divided into 855 10×10 pixel cells, and for each cell annual time series of green chromatic coordinates (gcc) were computed from hourly images. To analyse the spatial pattern of phenology, the beginning of the season for each cell was extracted from the gcc time series. Based on the same grid dimension, three maps of yearly snowmelt date corresponding to the day of the year in which the snow in each cell disappeared from the ground were obtained.Although complete snowmelt in the area occurred rapidly, within a maximum of six days, several distinct spatial patterns were identified with snowmelt occurring earlier in convex compared to concave areas. Differences in snowmelt dates were quite unexpectedly negatively related to the beginning of the growing season. The negative correlation was explained considering that areas characterized by different microtopography have also a different species composition: the growing season began earlier in concave areas preferred by opportunistic species with a fast development after snowmelt while phenological development of grass typical of convex areas can take longer. This behaviour was especially evident in 2011 characterized by an extremely anticipated snowmelt. On the contrary, the analysis of the relationship between the timing of snowmelt and the beginning of the season between the three years analysed in this study, highlighted an advancement of the beginning of the growing season in 2011. However, this is valid only in areas characterized by the abundance of opportunistic species such as forbs for which the snow cover plays a major role in determining the beginning of phenological development. The results presented in this study support the possibility of using repeat digital photography to analyse the role of plant species composition on phenology in complex ecosystems such as subalpine and alpine grasslands. © 2014 Elsevier B.V.
198-199
116
125
http://scopus
Tommaso Julitta;Edoardo Cremonese;Mirco Migliavacca;Roberto Colombo;Marta Galvagno;Consolata Siniscalco;Micol Rossini;Francesco Fava;Sergio Cogliati;Umberto Morra di Cella;Annette Menzel
File in questo prodotto:
File Dimensione Formato  
julitta.pdf

Accesso riservato

Tipo di file: PDF EDITORIALE
Dimensione 3.04 MB
Formato Adobe PDF
3.04 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
Julitta post print CS.pdf

Accesso aperto

Tipo di file: POSTPRINT (VERSIONE FINALE DELL’AUTORE)
Dimensione 1.16 MB
Formato Adobe PDF
1.16 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/150402
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 61
  • ???jsp.display-item.citation.isi??? 61
social impact