Funding From: Sources of Variability in Canopy Reflectance and the Convergent Properties of Plants: Integrating Remote Sensing and Ecological Theory toward Improved Model Parameterization and Validation S.V. Ollinger, A.E. Richardson, M.E. Martin, H.F. Wicklein, L.C. Lepine, M.C. Day, University of New Hampshire, Durham, NH D.Y. Hollinger, USDA Forest Service, Northern Research Station, Durham, NH P.B. Reich, University of Minnesota, St. Paul, MN CARBON–NITROGEN–ALBEDO LINKAGES IN PLANTS ABSTRACT In a recent study involving Ameriflux data, field measurements and remote sensing, we showed that the well-known relationship between leaf-level photosynthesis and foliar %N also scales to whole canopies over continental scales (Ollinger et al. 2008). We also found that both C assimilation and canopy %N were strongly and positively related to shortwave surface albedo in temperate and boreal forests. This pattern has since been demonstrated using independent sources of data that include grasslands and crops as well as forests (e.g., Hollinger et al. 2010). These results have potentially important implications for climate modeling because they suggests a greater coupling between carbon, nitrogen and energy fluxes than has previously been recognized. However, resolving underlying mechanisms of the relationship is important because different potential mechanisms carry different implications for responses under future scenarios of change. Here, we (1) explore the C-N-albedo relationship across a broader range of ecosystems and spatial scales, (2) examine their implications across gradients of disturbance and recovery, and (3) examine sources of variability in canopy reflectance related to leaf and canopy level traits. We also consider the role of convergence in plant functioning and the difficulty of identifying individual drivers of spectral properties among a suite of interrelated traits. A pattern that emerges suggests a synergy among the scattering effects of leaf-, stem- and canopy-level traits that becomes accentuated in the near-infrared (NIR) region. This poses a serious challenge for remote detection of specific plant properties, but suggests an emergent property of ecosystems that results from optimization of plant form and function across multiple scales. Remote detection of canopy %N with NIR reflectance – Potential for broadband global-scale sensors The leaf-level relationship between photosynthetic capacity and foliar %N scales directly to whole forest canopies NIR reflectance (%) Canopy %N 450 950 1525 2225 2500 Wavelength (nm) Reflectance (%) MODIS albedo 0 20 40 60 R2 = 0.64 (a) Figure 3. AVIRIS reflectance spectra for more than 200 plots across U.S. and Canadian temperate & boreal forests and croplands grouped into classes of canopy %N (a). The feature that emerged as the dominant source of variability with canopy %N was the height of the NIR reflectance plateau. This variation was further demonstrated through the strong relationship between canopy %N and a single NIR reflectance value derived from an average of all AVIRIS bands in the 840-880nm range (b). These observations suggest that reflectance data from global-scale satellite sensors could be used to predict canopy %N, thereby extending our ability to predict canopy %N from small landscapes to continental scales. (a) Figure 2. Relationships among canopy-level CAmax and canopy %N for 10 eddy covariance towers across the conterminous U.S.. Area-based CAmax (a) was derived through inversion of a simple C flux model on tower net CO2 exchange data. Mass-based CAmax (b) was derived by combining area-based values with canopy mass estimates for each site. (Ollinger et al. 2008) Dashed line in (b): Leaf-level trend from Wright et al. 2004 global leaf traits data set. While variability in reflectance with canopy %N is most pronounced in the NIR region, the pattern of increasing reflectance with increasing canopy %N spans a wide enough range of the solar energy spectrum to drive an overall trend between canopy %N and shortwave albedo. This is demonstrated in the relationship between canopy %N for forested and cropland plots in relation to growing season albedo from MODIS (c). (b) (b) Figure 4. Using trends demonstrated for forest canopies (e.g., Fig. 3c above) that compared growing season MODIS albedo with canopy %N and CAmax for flux tower footprints, MODIS albedo data were converted to estimates of canopy %N and CAmax . While the estimates shown here are for forested areas only, we demonstrate the potential for mapping forest %N and C assimilation at continental scales using existing remote sensing observations. (c) BACKGROUND The work presented here is based on an integration of field sampling, high-resolution imaging spectroscopy, broad-band remote sensing, and tower-based CO2 flux measurements from forest, agricultural, peatland and grassland sites distributed across the United States and Canada. Howland, ME Hubbard Brook, NH Harvard Forest, MA Duke Forest, NC Austin Cary Memorial Forest, FL Albedo and canopy %N following disturbance from harvesting and fire (a) (b) Figure 5. The patterns in (a) and (b) are influenced by surface reflectance properties that change with disturbance (e.g., biomass, stand density, canopy structure, species composition), but biochemical variability in needles from stands in different stages of recovery since disturbance may also play a role in the pattern. E.g., needles from trees in the oldest stands generally had the lowest mean %N (c). (c) Quebec BERMS Campbell River Comparison of needle %N within species at each of the three Canadian sites. Albedo (a) and %N (b) in relation to stand age in chronosequences following harvesting and fire. UNDERPINNINGS OF THE CARBON–NITROGEN–ALBEDO RELATIONSHIPS Leaf and canopy albedo under elevated CO2 and N fertilization Factors affecting leaf and canopy reflectance Functional convergence among spectrally important plant traits ORNL: Elevated CO2 (a) (b) (c) Leaf-level associations can influence stem- and canopy-level architecture in ways that accentuate canopy properties. For instance, though their effect on canopy reflectance is unclear, differences observed in (a-c) are consistent with the notion that leaf-level %N correlates with anatomical leaf properties that influence scattering. Figure 1. Location of study sites incorporated in our previous and current synthetic studies that have examined CO2 uptake, canopy N and albedo at local, landscape and regional scales. Examples of our estimates of canopy nitrogen concentration are shown for several eastern U.S. sites within the AmeriFlux network. These nitrogen maps were derived using PLS regression of field-measured canopy N (% by foliar mass) against spectral reflectance data from NASA’s AVIRIS and Hyperion sensors. Data for forested sites here have been integrated to develop generalizeable methods for N detection using broad-band sensors as well as to derive a continental-scale relationship between canopy N and maximum carbon assimilation capacity (CAmax). (a) (b) Figure 8. Cell anatomy of black oak leaves from trees in the control (a), low N-fertilization (b) and high N-fertilized (c) plots at Harvard Forest. (b) (a) CONCLUSIONS Figure 6. ANOVA results (means ± standard error) for leaf-level albedo (αsw), %N and LMA by treatment from sweetgum at ORNL (a) were not observed at the canopy level (b). While little difference was observed in leaf-level reflectance between treatments, reflectance data obtained from the AVIRIS sensor showed that whole-canopy NIR reflectance was higher for the N fertilized sweetgum treatment than the ambient CO2 sweetgum treatment (b). Potential importance of interrelated plant traits that affect radiation scattering over scales ranging from cells to canopies. Although measuring canopy structural properties is challenging, future work should consider variables such as leaf arrangement and foliage clumping, leaf angle distribution and crown geometry in conjunction with leaf traits and canopy spectral properties. Citations Hollinger, D.Y. et al. (2010). Albedo estimates for land surface models and support for a new paradigm based on foliage nitrogen concentration. Global Change Biology 16, 696–710. Ollinger, S.V., et al. (2008). Canopy nitrogen, carbon assimilation, and albedo in temperate and boreal forests: Functional relations and potential climate feedbacks. PNAS 105(49), 19335-19340. Ollinger, S.V. (2011). Sources of variability in canopy reflectance and the convergent properties of plants. New Phytologist 189, 375-394. Wright, I.J. (2004). The worldwide leaf economics spectrum. Nature 428, 821-827. Harvard Forest: N Fertilization ANOVA results of leaf-level analyses for black oak from Harvard Forest (c) demonstrated that %N was higher in the high N-fertilization treatment than in the low N and control treatments, which were not significantly different from each other. There were no differences in leaf-level albedo nor LMA between nitrogen treatments at HF. (c) Figure 9. Examples of known associations that illustrate convergence of spectrally important plant traits are shown (a); idealized relationships among other variables that exhibit some degree of convergence and that are known to be related to NIR reflectance are (b) (Ollinger 2011). Figure 7. Leaf (a) and canopy (b) reflectance spectra predicted by the PROSPECT and SAIL models, generated using a range of values for Chl concentration, dry matter content, EWT, and the structure parameter N; and LAI and leaf angle distribution (LAD) for whole-canopy reflectance (Ollinger 2011). The factors that most affect reflectance are those that are most difficult to measure or estimate.