Leaf dry matter content is better at predicting above-ground net primary production than specific leaf area



Smart, Simon Mark, Glanville, Helen Catherine, Blanes, Maria del Carmen, Mercado, Lina Maria, Emmett, Bridget Anne, Jones, David Leonard, Cosby, Bernard Jackson, Marrs, Robert Hunter ORCID: 0000-0002-0664-9420, Butler, Adam, Marshall, Miles Ramsvik
et al (show 3 more authors) (2017) Leaf dry matter content is better at predicting above-ground net primary production than specific leaf area. FUNCTIONAL ECOLOGY, 31 (6). pp. 1336-1344.

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Abstract

<jats:title>Summary</jats:title><jats:p> <jats:list> <jats:list-item><jats:p>Reliable modelling of above‐ground net primary production (<jats:styled-content style="fixed-case">aNPP</jats:styled-content>) at fine resolution is a significant challenge. A promising avenue for improving process models is to include response and effect trait relationships. However, uncertainties remain over which leaf traits are correlated most strongly with <jats:styled-content style="fixed-case">aNPP</jats:styled-content>.</jats:p></jats:list-item> <jats:list-item><jats:p>We compared abundance‐weighted values of two of the most widely used traits from the leaf economics spectrum (specific leaf area and leaf dry matter content) with measured <jats:styled-content style="fixed-case">aNPP</jats:styled-content> across a temperate ecosystem gradient.</jats:p></jats:list-item> <jats:list-item><jats:p>We found that leaf dry matter content (<jats:styled-content style="fixed-case">LDMC</jats:styled-content>) as opposed to specific leaf area (<jats:styled-content style="fixed-case">SLA</jats:styled-content>) was the superior predictor of <jats:styled-content style="fixed-case">aNPP</jats:styled-content> (<jats:italic>R</jats:italic><jats:sup>2</jats:sup> = 0·55).</jats:p></jats:list-item> <jats:list-item><jats:p>Directly measured <jats:italic>in situ</jats:italic> trait values for the dominant species improved estimation of <jats:styled-content style="fixed-case">aNPP</jats:styled-content> significantly. Introducing intraspecific trait variation by including the effect of replicated trait values from published databases did not improve the estimation of <jats:styled-content style="fixed-case">aNPP</jats:styled-content>.</jats:p></jats:list-item> <jats:list-item><jats:p>Our results support the prospect of greater scientific understanding for less cost because <jats:styled-content style="fixed-case">LDMC</jats:styled-content> is much easier to measure than <jats:styled-content style="fixed-case">SLA</jats:styled-content>.</jats:p></jats:list-item> </jats:list> </jats:p><jats:p>A <jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="http://onlinelibrary.wiley.com/doi/10.1111/1365-2435.12832/suppinfo">lay summary</jats:ext-link> is available for this article.</jats:p>

Item Type: Article
Uncontrolled Keywords: Bayesian modelling, ecosystem function, global change, intraspecific variation, measurement error
Depositing User: Symplectic Admin
Date Deposited: 19 Jan 2017 11:34
Last Modified: 18 Sep 2023 18:38
DOI: 10.1111/1365-2435.12832
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3005289