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Five years of phenological monitoring in a mountain grassland: inter-annual patterns and evaluation of the sampling protocol

International Journal of Biometeorology volume 59, pages 1927–1937 (2015)Cite this article

Abstract

The increasingly important effect of climate change and extremes on alpine phenology highlights the need to establish accurate monitoring methods to track inter-annual variation (IAV) and long-term trends in plant phenology. We evaluated four different indices of phenological development (two for plant productivity, i.e., green biomass and leaf area index; two for plant greenness, i.e., greenness from visual inspection and from digital images) from a 5-year monitoring of ecosystem phenology, here defined as the seasonal development of the grassland canopy, in a subalpine grassland site (NW Alps). Our aim was to establish an effective observation strategy that enables the detection of shifts in grassland phenology in response to climate trends and meteorological extremes. The seasonal development of the vegetation at this site appears strongly controlled by snowmelt mostly in its first stages and to a lesser extent in the overall development trajectory. All indices were able to detect an anomalous beginning of the growing season in 2011 due to an exceptionally early snowmelt, whereas only some of them revealed a later beginning of the growing season in 2013 due to a late snowmelt. A method is developed to derive the number of samples that maximise the trade-off between sampling effort and accuracy in IAV detection in the context of long-term phenology monitoring programmes. Results show that spring phenology requires a smaller number of samples than autumn phenology to track a given target of IAV. Additionally, productivity indices (leaf area index and green biomass) have a higher sampling requirement than greenness derived from visual estimation and from the analysis of digital images. Of the latter two, the analysis of digital images stands out as the more effective, rapid and objective method to detect IAV in vegetation development.

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Acknowledgments

This study was conducted in the framework of PHENOALP and e-PHENO projects, two INTERREG projects co-funded by the European Regional Development Fund under the operational program for territorial cooperation ItalyFrance (ALCOTRA) 2007-13. We acknowledge the Centro Funzionale della Regione Autonoma Valle d’Aosta for providing access to the Cignana long-term weather data and the people who contributed to collect them.

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Affiliations

  1. Environmental Protection Agency of Aosta Valley, ARPA VdA, Climate Change Unit, Aosta, Italy

    Gianluca Filippa, Edoardo Cremonese, Marta Galvagno, Umberto Morra di Cella & Martina Petey

  2. Biogeochemical Integration Department, Max Planck Institute for Biogeochemistry, Jena, Germany

    Mirco Migliavacca

  3. Remote Sensing of Environmental Dynamics Lab, DISAT, University of Milano-Bicocca, Milano, Italy

    Mirco Migliavacca

  4. Dipartimento di Scienze della Vita e Biologia dei Sistemi - University of Torino, Torino, Italy

    Consolata Siniscalco

Authors
  1. Gianluca Filippa
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  2. Edoardo Cremonese
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  3. Marta Galvagno
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  4. Mirco Migliavacca
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  5. Umberto Morra di Cella
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  6. Martina Petey
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  7. Consolata Siniscalco
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Correspondence to Gianluca Filippa.

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Filippa, G., Cremonese, E., Galvagno, M. et al. Five years of phenological monitoring in a mountain grassland: inter-annual patterns and evaluation of the sampling protocol. Int J Biometeorol 59, 1927–1937 (2015). https://doi.org/10.1007/s00484-015-0999-5

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  • DOI: https://doi.org/10.1007/s00484-015-0999-5

Keywords

  • Ecosystem phenology
  • Subalpine belt
  • Greenness
  • Leaf area index
  • Biomass
  • Digital camera
  • Grassland