AUTHOR=Ramos Desirée M. , Andrade João M. , Alberton Bruna C. , Moura Magna S. B. , Domingues Tomas F. , Neves Nattália , Lima José R. S. , Souza Rodolfo , Souza Eduardo , Silva José R. , Espírito-Santo Mário M. , Morellato Leonor Patrícia Cerdeira , Cunha John 

TITLE=Multiscale phenology of seasonally dry tropical forests in an aridity gradient

JOURNAL=Frontiers in Environmental Science

VOLUME=Volume 11 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/environmental-science/articles/10.3389/fenvs.2023.1275844

DOI=10.3389/fenvs.2023.1275844

ISSN=2296-665X

ABSTRACT=The leaf phenology of Seasonally Dry Tropical Forests is highly seasonal, marked by synchronized flushing of new leaves triggered by the first rains of the wet season. Leafout, however, varies among species during the dry season. Such phenological transitions may not be accurately detected by remote sensed vegetation indices (VIs) and the derived transition dates (TDs), due to the coarse spatial and temporal resolution of satellite data. Commonly used methods for transition date calculation involve curve fitting models and predefined thresholds of vegetation indices' seasonal amplitude. Yet, these model results are influenced by chosen thresholds. We compared TDs from PhenoCam and Satellite Remote Sensing (RS) methods and used the TDs calculated from PhenoCams to select the best thresholds for the RS timeseries and calculate the TDs. PhenoCam-derived TDs helped determine optimal thresholds for RS timeseries and calculating TDs. The ideal thresholds were 5% for start of the season (SOS) and 20% for end of the season (EOS) vegetation index amplitudes. Using calibrated phenocamera thresholds reduced Mean Absolute Error by 5 days for SOS and 34 days for EOS, compared to common thresholds in land surface phenology studies. Using MODIS data and calibrated thresholds, we studied how leafing TDs differ across a gradient of aridity and which environmental factors are the main triggers of phenological responses (TDs) of those plant communities. On average, growing season length (LOS) didn't differ significantly among vegetation type, but driest sites showed highest interannual variation. This pattern applied to leaf flushing (SOS) and leaf fall (EOS) as well. We found a positive relationship between the accumulated precipitation and the LOS, and between the accumulated precipitation and maximum and minimum temperatures and the vegetation productivity (Peak and Accumulated NDVI). Our results demonstrated that: (A) The fine temporal resolution of phenocameras phenology time series improved the definitions of TDs and Thresholds for RS landscape phenology; (b) Long-term RS greening responded to the variability in rainfall, adjusting their timing of green up and down, and (C) the amount of rainfall, although not determinant for the length of the growing season, is related to the estimates of vegetation productivity.