Abstract
Calibrating land surface phenology (LSP) with tree rings is important to model spatio-temporal variations in forest productivity. We used MODIS (resolution: 250 m) NDVI, WDRVI and EVI series 2000–2014 to derive LSP metrics quantifying phenophase timing and canopy photosynthetic rates of 26 European beech forests covering a large thermal gradient (5–16 °C) in Italy. Average phenophase timing changed greatly with site temperature (e.g. growing season 70 days longer at low- than high-elevation); average VI values were affected by precipitation. An annual temperature about 12 °C (c. 1100 m asl) represented a bioclimatic threshold dividing warm from cold beech forests, distinguished by different phenology-BAI (basal area increment) relationships and LSP trends. Cold forests showed decreasing VI values (browning) and delayed phenophases and had negative BAI slopes. Warmer forests tended to increase VI (greening), and positive BAI slopes. NDVI peak, commonly used in global trend assessments, changed with elevation in agreement with changes in wood production. A cross-validation modelling approach demonstrated the ability of LSP to predict average BAI and its interannual variability. Merging sites into bioclimatic groups improved models by amplifying the signal in growth or LSP. NDVI had highest performances when informing on BAI trends; WDRVI and EVI were mostly selected for modelling mean and interannual BAI. WDRVI association with tree rings, tested in this study for the first time, showed that this VI is highly promising for studying forest dynamics. MODIS LSP can quantify forest functioning changes across landscapes and model interannual spatial variations and trends in productivity dynamics under climate change.
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Acknowledgements
We thank two anonymous reviewers for constructive comments on previous versions of the manuscript. We thank Tobias Gränzig for advice. Research partially supported by the Ministry of Instruction, University and Research (MIUR) “Department of excellence” (Law 232/2016) and FISR-MIUR project “Italian Mountain Lab”.
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Di Fiore, L., Brunetti, M., Baliva, M. et al. Modelling Fagus sylvatica stem growth along a wide thermal gradient in Italy by incorporating dendroclimatic classification and land surface phenology metrics. Int J Biometeorol 66, 2433–2448 (2022). https://doi.org/10.1007/s00484-022-02367-2
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DOI: https://doi.org/10.1007/s00484-022-02367-2