Introduction: About 50% of the Amazon basin comprises forests growing on shallow water tables (WT). These regions are severely undersampled in forest plot networks as compared to deep WT forests and yet may exhibit distinct responses to drought. Specifically, droughts have been shown to have deleterious effects on deep WT forests while shallow WT areas may benefit from some level of drying, which reduces anoxia and extends the growing season.
Here, we explore the influence of water table depth (a proxy for local soil water availability) on spatial and seasonal patterns of forest structure in the Amazon including through case studies by our group. Forest structure is the physical manifestation of tree demographic processes and is mechanistically linked to key ecosystem functions. Therefore, understanding spatial and temporal patterns and drivers of forest structural variation may provide valuable insights into mechanisms of forest responses to climatic changes.
Hypotheses: We examine the hypothesis that shallow rooting depths and (unstable) waterlogged soils of shallow WT regions give rise to higher tree turnover rates and forest structures characterised by higher stem densities, lower canopy heights, and higher gap fractions. We hypothesise that the seasonality of vertical leaf area distributions in deep WT forests opposes that of shallow WT forests since the period most favourable for growth (growth window) is during the rainy and dry seasons for deep and shallow WT forests, respectively.
Methods: We measured the canopy structure of ~300 Amazon forest plots distributed across large-scale climate and WT gradients using tree inventories and ground-based profiling canopy lidar (PCL). We made seasonal forest structure PCL measurements at deep and shallow WT sites.
Results: Stem density and leaf area index (LAI) increased and canopy height decreased with increasing soil water availability (decreasing WT). The seasonality of forest structure at a deep WT forest was dependent on canopy height as well as light environments. Specifically, lower canopy leaf area in the sun and shade exhibited opposite seasonal patterns, likely due to differential air and soil water availabilities.
Implications / Conclusions: We review the implications of these case studies for Amazon forest function and drought responses, and present a research agenda for furthering understanding of the influence of soil water on forest structure and function. This includes unprecedented opportunities offered by linking a new shallow WT forest plot network, led by members of our group, to existing and recently launched lidar and spectral remote sensing platforms.
water table depth; forest structure; remote sensing; lidar