2017 ESA Annual Meeting (August 6 -- 11)

COS 6-8 - Remotely sensing forest functional traits to assess scale-dependent functional diversity

Monday, August 7, 2017: 4:00 PM
C125-126, Oregon Convention Center
Fabian D. Schneider1, Bernhard Schmid2, Owen L. Petchey2, Felix Morsdorf1 and Michael E. Schaepman3, (1)Department of Geography, University of Zurich, Zurich, Switzerland, (2)Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland, (3)RSL, Department of Geography, University of Zurich, Zurich, Switzerland
Background/Question/Methods

Forest functional traits build the foundation to describe diversity patterns and offer a mechanistic link between ecological processes and community structure. However, it remains difficult to assess functional diversity at global scale, in part due to the limitations of in-situ measurements and geo-referencing in forest ecosystems. We present a novel methodological approach using data from remote sensing and relating these to field measurements in a test region. Based on the results of this study, the developed methodology can be used to assess functional diversity and diversity-area relationships on broad spatial scales.

We retrieved three physiological (leaf chlorophylls, carotenoids and water concentration) and three morphological traits (canopy height, layering and density) using airborne imaging spectroscopy and airborne laser scanning, respectively, over the 900 ha of temperate mixed forest covering the test region. We then assessed functional richness, divergence and evenness, representing three different aspects of functional diversity, at spatial scales from 0.05-327 ha and tested for trait convergence or divergence at the different scales.

Results/Conclusions

Remotely sensed functional traits correlated with field measurements (r2of 0.5 to 0.9) and were in agreement with community-weighted means of the functional trait database TRY. Our results show similar patterns of physiological and morphological diversity, underlining the stability of two independent measurement techniques to assess functional diversity. Among functional richness, divergence and evenness, we found functional richness to best represent scale-dependent functional diversity. Communities were predominantly structured by trait convergence at all observed scales. Most pronounced trait convergence could be observed on a mountain ridge, where low functional richness coincided with significantly different abiotic conditions regarding topography, radiation and soil. High functional richness was related to the occurrence of disturbed areas and mixtures of tree functional groups.

With the emergence of the concept of ecosystem services, urgent need arises from conservation requirements and stakeholders to better quantify and map functional diversity over entire landscapes. By combining imaging spectroscopy and laser guided diversity mapping with dynamic vegetation models, we will be able to establish the link from functional traits and diversity to ecosystem functioning and services. Ultimately, this will considerably improve predictive ecology.