Abstract

Predictions of the magnitude and timing of leaf phenology in Amazonian forests remain highly controversial. Here, we use terrestrial LiDAR surveys every two weeks spanning wet and dry seasons in Central Amazonia to show that plant phenology varies strongly across vertical strata in old-growth forests, but is sensitive to disturbances arising from forest fragmentation. In combination with continuous microclimate measurements, we find that when maximum daily temperatures reached 35 °C in the latter part of the dry season, the upper canopy of large trees in undisturbed forests lost plant material. In contrast, the understory greened up with increased light availability driven by the upper canopy loss, alongside increases in solar radiation, even during periods of drier soil and atmospheric conditions. However, persistently high temperatures in forest edges exacerbated the upper canopy losses of large trees throughout the dry season, whereas the understory in these light-rich environments was less dependent on the altered upper canopy structure. Our findings reveal a strong influence of edge effects on phenological controls in wet forests of Central Amazonia.

Highlights

  • Predictions of the magnitude and timing of leaf phenology in Amazonian forests remain highly controversial

  • Precipitation estimates indicate the occurrence of a 4-month period of accumulated rainfall below 200 mm month−1, and significant reductions in soil moisture between July and September in Central Amazonia

  • Repeat high density terrestrial LiDAR combined with microclimate measurements of a Central Amazonian forest provided a unique perspective on the seasonal dynamics of vegetation and the interaction with fragmentation

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Summary

Introduction

Predictions of the magnitude and timing of leaf phenology in Amazonian forests remain highly controversial. Persistently high temperatures in forest edges exacerbated the upper canopy losses of large trees throughout the dry season, whereas the understory in these light-rich environments was less dependent on the altered upper canopy structure. Seasonal variations in leaf quantity and leaf area across evergreen Amazonian forests have frequently been considered negligible or small[4,12,21,34] These studies are based on passive optical remote sensing approaches, which cannot detect potential differences between canopy strata. These approaches tend to detect only upper canopy trees with deeper roots and water access[30], and that are likely adapted to more stressful conditions such as high solar radiation, high temperatures and low air humidity[35].

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