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ObjectivesJust as people with the same weight can have different body builds, woods with the same wood density can have different anatomies. Here, our aim was to assess the magnitude of anatomical variation within a restricted range of wood density and explore its potential ecological implications.MethodsTwig wood of 69 angiosperm tree and shrub species was analyzed. Species were selected so that wood density varied within a relatively narrow range (0.38–0.62 g cm-3). Anatomical traits quantified included wood tissue fractions (fibres, axial parenchyma, ray parenchyma, vessels, and conduits with maximum lumen diameter below 15 μm), vessel properties, and pith area. To search for potential ecological correlates of anatomical variation the species were sampled across rainfall and temperature contrasts, and several other ecologically-relevant traits were measured (plant height, leaf area to sapwood area ratio, and modulus of elasticity).ResultsDespite the limited range in wood density, substantial anatomical variation was observed. Total parenchyma fraction varied from 0.12 to 0.66 and fibre fraction from 0.20 to 0.74, and these two traits were strongly inversely correlated (r = -0.86, P < 0.001). Parenchyma was weakly (0.24 ≤|r|≤ 0.35, P < 0.05) or not associated with vessel properties nor with height, leaf area to sapwood area ratio, and modulus of elasticity (0.24 ≤|r|≤ 0.41, P < 0.05). However, vessel traits were fairly well correlated with height and leaf area to sapwood area ratio (0.47 ≤|r|≤ 0.65, all P < 0.001). Modulus of elasticity was mainly driven by fibre wall plus vessel wall fraction rather than by the parenchyma component.ConclusionsOverall, there seem to be at least three axes of variation in xylem, substantially independent of each other: a wood density spectrum, a fibre-parenchyma spectrum, and a vessel area spectrum. The fibre-parenchyma spectrum does not yet have any clear or convincing ecological interpretation. 相似文献
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Data-Driven Method to Estimate Nonlinear Chemical Equivalence 总被引:1,自引:0,他引:1
There is great need to express the impacts of chemicals found in the environment in terms of effects from alternative chemicals of interest. Methods currently employed in fields such as life-cycle assessment, risk assessment, mixtures toxicology, and pharmacology rely mostly on heuristic arguments to justify the use of linear relationships in the construction of “equivalency factors,” which aim to model these concentration-concentration correlations. However, the use of linear models, even at low concentrations, oversimplifies the nonlinear nature of the concentration-response curve, therefore introducing error into calculations involving these factors. We address this problem by reporting a method to determine a concentration-concentration relationship between two chemicals based on the full extent of experimentally derived concentration-response curves. Although this method can be easily generalized, we develop and illustrate it from the perspective of toxicology, in which we provide equations relating the sigmoid and non-monotone, or “biphasic,” responses typical of the field. The resulting concentration-concentration relationships are manifestly nonlinear for nearly any chemical level, even at the very low concentrations common to environmental measurements. We demonstrate the method using real-world examples of toxicological data which may exhibit sigmoid and biphasic mortality curves. Finally, we use our models to calculate equivalency factors, and show that traditional results are recovered only when the concentration-response curves are “parallel,” which has been noted before, but we make formal here by providing mathematical conditions on the validity of this approach. 相似文献
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Janne Alahuhta Sarian Kosten Munemitsu Akasaka Dominique Auderset Mattia M. Azzella Rossano Bolpagni Claudia P. Bove Patricia A. Chambers Eglantine Chappuis John Clayton Mary de Winton Frauke Ecke Esperança Gacia Gana Gecheva Patrick Grillas Jennifer Hauxwell Seppo Hellsten Jan Hjort Mark V. Hoyer Christiane Ilg Agnieszka Kolada Minna Kuoppala Torben Lauridsen En Hua Li Balázs A. Lukács Marit Mjelde Alison Mikulyuk Roger P. Mormul Jun Nishihiro Beat Oertli Laila Rhazi Mouhssine Rhazi Laura Sass Christine Schranz Martin Søndergaard Takashi Yamanouchi Qing Yu Haijun Wang Nigel Willby Xiao Ke Zhang Jani Heino 《Journal of Biogeography》2017,44(8):1758-1769
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