Leafing Patterns and Drivers across Seasonally Dry Tropical Communities

Autor: Bruna Alberton, Ricardo da Silva Torres, Thiago Sanna Freire Silva, Humberto R. da Rocha, Magna S. B. Moura, Leonor Patricia Cerdeira Morellato
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: Remote Sensing, Vol 11, Iss 19, p 2267 (2019)
Druh dokumentu: article
ISSN: 2072-4292
11192267
DOI: 10.3390/rs11192267
Popis: Investigating the timing of key phenological events across environments with variable seasonality is crucial to understand the drivers of ecosystem dynamics. Leaf production in the tropics is mainly constrained by water and light availability. Identifying the factors regulating leaf phenology patterns allows efficiently forecasting of climate change impacts. We conducted a novel phenological monitoring study across four Neotropical vegetation sites using leaf phenology time series obtained from digital repeated photographs (phenocameras). Seasonality differed among sites, from very seasonally dry climate in the caatinga dry scrubland with an eight-month long dry season to the less restrictive Cerrado vegetation with a six-month dry season. To unravel the main drivers of leaf phenology and understand how they influence seasonal dynamics (represented by the green color channel (Gcc) vegetation index), we applied Generalized Additive Mixed Models (GAMMs) to estimate the growing seasons, using water deficit and day length as covariates. Our results indicated that plant-water relationships are more important in the caatinga, while light (measured as day-length) was more relevant in explaining leafing patterns in Cerrado communities. Leafing behaviors and predictor-response relationships (distinct smooth functions) were more variable at the less seasonal Cerrado sites, suggesting that different life-forms (grasses, herbs, shrubs, and trees) are capable of overcoming drought through specific phenological strategies and associated functional traits, such as deep root systems in trees.
Databáze: Directory of Open Access Journals
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