GIScience & Remote Sensing (Oct 2021)

Recent trends in the timing of the growing season in New Zealand’s natural and semi-natural grasslands

  • Xiaobin Hua,
  • Pascal Sirguey,
  • Ralf Ohlemüller

DOI
https://doi.org/10.1080/15481603.2021.1969629
Journal volume & issue
Vol. 58, no. 7
pp. 1090 – 1111

Abstract

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We investigate the temporal dynamics of shifts in phenological responses of a range of key stages of the growing season in New Zealand’s three indigenous grassland types over the last 16 years (2001–2016). A near-daily Normalized Difference Vegetation Index (NDVI) time series from MODerate Resolution Imaging Spectroradiometer (MODIS) was used to extract five annual growth phenology indices, namely the Start, End, Length, Peak and Peak NDVI of a growing season. The start of the growing season advanced (i.e. happened earlier) by a median of 7.2, 6.0 and 8.8 days per decade in Alpine, Tall Tussock and Low Producing grassland, whereas the end of the season advanced by a median of 4.5, 0.4 and 0.4 days in the three types respectively. The length of growing season was extended by 3.2, 5.2 and 7.1 days per decade in these three grassland types. Over 86% of the investigated grassland areas showed an advancing (earlier) start of the growing season, and 74% of Alpine grassland showed a trend toward an earlier end of season. Over 63% of all grassland types showed an increase in growing season length. A trend toward earlier growing season peak and overall increasing NDVI in the three grassland types indicate a tendency for increasing vegetation vitality in grassland ecosystems in recent years. The start of growing season was correlated with atmospheric pressure (negatively) and precipitation (positively) changes in winter–spring months, while the timing of the season end is positively correlated with air temperature and solar radiation in summer–autumn months. Our study shows that different grassland types differ in magnitude – but not in direction – of their recent shifts in timing of key growing season stages with high-alpine grasslands showing the strongest response. This study highlights the usefulness of remote sensing for monitoring ecosystem-level phenological shifts over large areas and long time periods.

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