Convergence in relationships between leaf traits, spectra and age across diverse canopy environments and two contrasting tropical forests

• Leaf age structures the phenology and development of plants, as well as the evolution of leaf traits over life histories. However, a general method for efficiently estimating leaf age across forests and canopy environments is lacking. • Here, we explored the potential for a statistical model, previously developed for Peruvian sunlit leaves, to consistently predict leaf ages from leaf reflectance spectra across two contrasting forests in Peru and Brazil and across diverse canopy environments. • The model performed well for independent Brazilian sunlit and shade canopy leaves (R2 = 0.75–0.78), suggesting that canopy leaves (and their associated spectra) follow constrained developmental trajectories even in contrasting forests. The model did not perform as well for mid-canopy and understory leaves (R2 = 0.27–0.29), because leaves in different environments have distinct traits and trait developmental trajectories. When we accounted for distinct environment–trait linkages – either by explicitly including traits and environments in the model, or, even better, by re-parameterizing the spectra-only model to implicitly capture distinct trait-trajectories in different environments – we achieved a more general model that well-predicted leaf age across forests and environments (R2 = 0.79). • Fundamental rules, linked to leaf environments, constrain the development of leaf traits and allow for general prediction of leaf age from spectra across species, sites and canopy environments

Can Permafrost Soil Thaw be Characterized by Hyperspectral Reflectance and Plant Community Structure?

I investigated (1) whether stages of permafrost thaw were consistently associated with plant community composition and other land surface characteristics; (2) whether those different land surface characteristics could be consistently distinguished with remote sensing tools in a sub-arctic mire. I utilized plant area cover and topography to identify five distinct site-types as being characteristic of different stages of permafrost thaw, and 50 one square-meter plots were measured for species-specific area cover and pole-based hyperspectral reflectance. A Tukey-HSD comparison test showed that plant functional group richness decreased with permafrost thaw, and could readily be used to differentiate between stages of thaw. A discrete, stepwise canonical classification function with bootstrap cross validation showed a mean classification error rate of 7.3% +/- 7.3% (6.8%-9.65% 95% Confidence Interval). These results showed successful ground-truthing methods for regional-scale landscape classification, allowing for high temporal and spatial resolution of circumpolar permafrost thaw monitoring

Establishing the Role of Digital Repeat Photography in Understanding Phenology and Carbon Cycling in a Subarctic Peatland

In this thesis, I establish and explore the role of phenology in understanding the rapidly changing environment of a subarctic peatland. First, I demonstrate how digital repeat photography can be used to characterize and differentiate distinct plant communities using two years of images. Each habitat is composed of different plant functional groups, promoting the individualistic approach to characterization that near-earth remote sensing tools can provide. The camera-product Relative Greenness successfully characterized interannual variability in seasonal growth for each habitat type. Across habitats, there was a direct relationship between advancement of spring onset and active season growth though this overall pattern showed habitat-specific variance. The camera images were also useful in characterizing the flowering phenology of an ​eriophorum​-rich fen habitat, for which a metric named Intensity was created. These results suggest that employment of phenology cameras in highly heterogeneous subarctic environments is a robust method to characterize phenology on a habitat to species scale. Next, I explored the role that this phenology product has in modeling Net Ecosystem Exchange (NEE) also measured at the field site. I hypothesized that the explanatory power of the phenology index, which is conceptually tied to a measure of photosynthetic capacity, would be tightly linked to the timescale it was used for: At sub-daily timescales, environmental forces would dominate, though when averaged over days to weekly scales, the biology represented through the camera index would be more influential. I show that at multiple time scales the environmental factors outperform the camera index when modeling NEE. Together, these studies begin to explore the applicability of phenology camera systems in subarctic environments

Unmanned Aerial Imagery over Stordalen Mire, Northern Sweden, 2014

RGB composite mosaic from over 600 images captured with a Panasonic Lumix-GM1 flown at solar noon aboard a fixed wing Robota Triton unmanned aircraft at approximately 70m above ground. Spatial resolution is 3 cm. For more information on methodology, see related publication. (2014-07-11) Data part of long-term research and collected in conjunction with nearby Abisko Scientific Research Station (Abisko Naturvetenskapliga Station, ANS

Unmanned Aerial Imagery over Stordalen Mire, Northern Sweden, 2014

RGB composite mosaic from over 600 images captured with a Panasonic Lumix-GM1 flown at solar noon aboard a fixed wing Robota Triton unmanned aircraft at approximately 70m above ground. Spatial resolution is 3 cm. For more information on methodology, see related publication

Convergence in relationships between leaf traits, spectra and age across diverse canopy environments and two contrasting tropical forests.

Leaf age structures the phenology and development of plants, as well as the evolution of leaf traits over life histories. However, a general method for efficiently estimating leaf age across forests and canopy environments is lacking. Here, we explored the potential for a statistical model, previously developed for Peruvian sunlit leaves, to consistently predict leaf ages from leaf reflectance spectra across two contrasting forests in Peru and Brazil and across diverse canopy environments. The model performed well for independent Brazilian sunlit and shade canopy leaves (R2  = 0.75-0.78), suggesting that canopy leaves (and their associated spectra) follow constrained developmental trajectories even in contrasting forests. The model did not perform as well for mid-canopy and understory leaves (R2  = 0.27-0.29), because leaves in different environments have distinct traits and trait developmental trajectories. When we accounted for distinct environment-trait linkages - either by explicitly including traits and environments in the model, or, even better, by re-parameterizing the spectra-only model to implicitly capture distinct trait-trajectories in different environments - we achieved a more general model that well-predicted leaf age across forests and environments (R2  = 0.79). Fundamental rules, linked to leaf environments, constrain the development of leaf traits and allow for general prediction of leaf age from spectra across species, sites and canopy environments