B43H-06:
Spatio-Temporal Canopy Complexity and Leaf Acclimation to Variable Canopy Microhabitats.

Thursday, 18 December 2014: 2:55 PM
Alex Theodore Fotis, Ohio State University Main Campus, Columbus, OH, United States
Abstract:
The theory that forests become carbon (C) neutral with maturity has recently been challenged. While a growing body of evidence shows that net C accumulation continues in forests that are centuries old, the reasons remain poorly known. Increasing canopy structural complexity, quantified by high variability in leaf distribution, has been proposed as a mechanism for sustained rates of C assimilation in mature forests. The goal of our research was to expand on these findings and explore a new idea of spatio-temporal canopy structural complexity as a mechanism linking canopy structure to function (C assimilation).

Our work takes place at the UMBS AmeriFlux core facility (US-UMB) in northern Michigan, USA. Canopy structure was quantified over 6 seasons with portable canopy LiDAR (PCL) and canopy spatial microhabitat variability was studied using hemispherical photographs from different heights within the canopy. We found a more even distribution of irradiance in more structurally complex canopies within a single year, and furthermore, that between-year variability of spatial leaf arrangement decreased with increasing canopy complexity. We suggest that in complex canopies less redistribution of leaf material over time may lead to more similar light microhabitats within and among years. Conversely, in less complex canopies this relationship can lead to a year-to-year time lag in morphological leaf acclimation since the effects of the previous-year’s light environment are reflected in the morphological characteristics of current-year leaves.

Our study harnesses unique spatio-temporal resolution measurements of canopy structure and microhabitat that can inform better management strategies seeking to maximize forest C uptake. Future research quantifying the relationship between canopy structure and light distribution will improve performance of ecosystem models that currently lack spatially explicit canopy structure information.