Shadiness in the global leaf economics spectrum

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(Above is an image assembled in the Inkscape and GIMP programs — it shows the silhouette of an unidentified Piper sp. from Peru superimposed with a map generated in R. Below are some thoughts that Ken and I had on a 2016 Nature Plants paper  entitled, “Global plant traits estimates biased due to plasticity in the shade,” by Keenan and Niinemets.)

Much of the variance observed in the functional niche-space of plants can be explained by light. Despite the long-established and well-studied roles of light in plant ecology, Keenan and Niinemets1 highlight potential biases in studies of the global spectrum of leaf form and function that may arise through neglect of standardized light measurements. To correct for these biases, the authors advocate several important modifications in the procedures for sampling and reporting leaf functional data. Below, we expand upon some of these recommendations and highlight other sources of error in estimates of the leaf economics spectrum. 
 
We agree with Keenan and Niinemets (1) that studies investigating functional plant ecology should report some level of light exposure associated with trait data. While photon-flux density or canopy density estimates (e.g., from hemispherical photography) is ideal, these measurements may be prohibitive at times due to cost and/or feasibility (e.g. it can be extremely difficult to take measurements over mature canopy trees). However, crown illumination indices (CIIs) require no special equipment and are reasonably correlated with estimates of light exposure derived from hemispherical photography (2). Future meta-analyses amalgamating CII and trait data would inevitably suffer from inter-observer error, and additional error would be introduced through different methods of CII estimation (namely the number illumination categories[3]).  Therefore, we propose that ecologists use the 7 categorical light classes used by Clark and Clark (4) as the standard for quantifying light exposure when more sophisticated quantifications are unavailable.  
 
Standard protocol for measurements of leaf traits generally calls for sampling of fully sun-exposed leaves.  Sampling sun leaves from tall canopies can be difficult and the failure to properly sample fully-exposed canopy leaves has potentially introduced considerable error in estimates of leaf form and function, particularly for tropical forests (1). Canopy sampling techniques have traditionally relied on shotguns, which often require hard-to-obtain ammunition and permits. Until terrestrial laser technology and radiative transfer modeling become more accessible, some sampling constraints may be removed through the use of low-tech methods. Although infrequently reported in the literature, slingshots are commonly used in arboriculture for canopy-ascension and provide a less-invasive and more precise method for sampling canopies compared to shotguns.  More specifically, slingshots can be used to position weighted lines over small branches with fully sun-exposed leaves, which can then be harvested with the aid of serrated wires or modified chainsaw chains. Since slingshots can reliably reach heights up to approximately 50m, they are suitable for sampling all but the very tallest forest canopies.  
 
Standard sampling protocol also calls for recently matured leaves. As leaves age, they can undergo marked changes in traits such as leaf mass area and photosynthetic rate (5). It is also common for old leaves to develop epiphylls, which influence host leaf physiology through light preemption (6) and nutrient leaching (7). However, without previous information regarding phenology, determining which leaves are newly matured is inherently subjective. Assuming that studies have accurately sampled leaves with the same relative development, measurements of leaf traits are still likely to misrepresent the majority of leaves in a given canopy because newly matured leaves may be proportionally rare compared to all leaves in the canopy.  
 
When scaled up from individuals, unrepresentative measurements in leaf traits due to shading and age may result in gross stoichiometric miscalculations at the global level. For now, the implications of Keenan and Niinemets’ findings suggest that studies based on the reported global spectrum of leaf form and function may require some re-evaluation. We propose that increased use of CIIs, improved sampling techniques, and more detailed study of the within-canopy and age-related trait variation are effective ways to correct the observed bias in the leaf economics spectrum.  

References: 
1.Keenan, T. F. & Niinemets, Ü. Nat. Plants 16201, 1020–1029 (2016). 
2.Keeling, H. C. & Phillips, O. L.. For. Ecol. Manage. 242, 431–437 (2007). 
3.Jennings, S. B., Brown, N. D. & Sheil, D.  Forestry 72, 59–73 (1999). 
4.Clark, D. A. & Clark, D. B. Ecol. Monogr. 62, 315–344 (1992). 
5.Kitajima, K., Mulkey, S. S. Am. J. Bot. 89, 1925–1932 (2002). 
6.Anthony, P. A., Holtum, J. A. M. & Jackes, B. R. Funct. Ecol. 16, 808–816 (2002). 
7.Wanek, W. & Pörtl, K. New Phytol. 166, 577–588 (2005). 

Cross-posted on http://www.timothymperez.com/blog/shadiness-in-the-global-leaf-economic-spectrum-databases. 

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