Leafing Patterns and Drivers across Seasonally Dry Tropical Communities

Abstract

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.

Peer Review #3 of "Seasonal and successional dynamics of size-dependent plant demographic rates in a tropical dry forest (v0.2)"

“…Our results clearly matched these predictions (Figures 2 a-f -4 a-f) and indicate that large-plant density and species density recover to old-growth forest values quickly, in line with previous findings in other SDTF (Aide et al, 2000;Lebrija-Trejos et al, 2008;Chazdon et al, 2011;Maza-Villalobos et al, 2011). Moreover, early successional recruitment and species gain rates were higher in the rainy than the dry season (Figure 3 a, d), which is in line with findings of previous studies in SDTF indicating that seasonal water availability enhances plant growth and establishment (Holbrook et al, 1995;Dirzo et al, 2011;Gaviria & Engelbrecht, 2015;Alberton et al, 2019;Campos et al, 2019). In SDTF, temperature, solar radiation and water vapor-pressure deficit are higher while soil water content is lower at the early successional stage compared to subsequent stages (Lebrija-Trejos et al, 2011;Pineda-García et al, 2013).…”

“…Manuscript to be reviewed 2001; Ceccon et al, 2006;Becknell et al, 2012;Alberton et al, 2019;Campos et al, 2019) especially early in succession. Although seasonality affects SDTF regeneration and secondary succession processes, few studies have examined effects of seasonality on plant community dynamics during SDTF succession (Lebrija-Trejos et al, 2011;Maza-Villalobos et al, 2013).…”

Environmental Drivers of Water Use for Caatinga Woody Plant Species: Combining Remote Sensing Phenology and Sap Flow Measurements

“…Plant species have their own specific adaptive mechanisms to cope with droughts [3,4], which are particularly important in water-limited ecosystems such as seasonally dry tropical forests (SDTFs).…”

“…The vegetation ranges from tall forests with closed canopies to scrublands rich in succulents and thorn-bearing plants [7,8]. The long water-limited period has been shown to be selective for deciduous, thorny, and succulent plant species that show a marked leaf senescence during the dry season followed by synchronous leaf flushing at the beginning of the rainy season [3,4,[7][8][9]. The deciduity and absence of a grassy layer are important characteristics that distinguish SDTFs from other mild seasonally dry tropical biomes such as the savannas [8].…”

“…An alternative approach to monitor vegetation phenology is near-surface RS, which uses in-situ automated cameras (phenocams) [26]. This technique, in combination with EC measurements and remote sensing, has been applied in Brazilian SDTFs [4] to investigate the drivers that regulate phenological patterns and vegetation responses to seasonal and severe droughts.…”