Corrigendum

Abstract

Functional EcologyVolume 34, Issue 2 p. 545-545 CorrigendumFree Access Corrigendum This article corrects the following: Does plant biomass partitioning reflect energetic investments in carbon and nutrient foraging? Deliang Kong, Jason D. Fridley, Julia Cooke, Volume 33Issue 9Functional Ecology pages: 1627-1637 First Published online: July 12, 2019 First published: 24 January 2020 https://doi.org/10.1111/1365-2435.13518AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Kong, D, Fridley, JD. Does plant biomass partitioning reflect energetic investments in carbon, nutrient foraging? Functional Ecology, 2019, 33, 1627–1637. https://doi.org/10.1111/1365-2435.13392 In the paper by Kong and Fridley (2019), the authors have determined that three of the 311 values of root mass fraction (RMF) are erroneous. Upon further examination, it was determined that the shoot mass values of the rows in question were summed incorrectly in Excel, leading to three spuriously low RMF values. The authors regret this error. Subsequently, the authors re-ran all analyses with the three revised RMF values. Because they are a small proportion of the dataset, no statistical tests or study interpretations are affected by the error. In one regression analysis conducted on a subset of the data (Figure 2a, N = 131), the slope coefficient decreases from 0.61 to 0.54, due to the high leverage of the three points in question, lowering the R2 from 0.22 to 0.20. An updated figure is provided. Figure 2Open in figure viewerPowerPoint Relationships between total below-ground energy allocation and root mass fraction in carbon allocation studies of individual plants. Whole-plant energy budgets in studies shown in (a) include night-time shoot respiration (N = 131); those in (b) ignore above-ground respiratory costs (N = 270; note some studies are used in both figures). Observations are distinguished by whether plants were inoculated with fungal (AMF, ECM) or bacterial (Rhizobium spp.) mutualist microbes (purple), and triangles represent grasses. Dashed lines are ordinary least squares regressions, and solid lines are 1:1 In the first paragraph of the Results section, it currently reads: We found a positive correlation of RMF and TBCA across studies, regardless of whether TBCA was calculated in reference to plant GPP (R2 = 0.22, p < .001, Figure 2a) or GPP-Rshoot (R2 = 0.32, p < .001, Figure 2b). Because Rshoot was often the smallest component of plant energy budgets, our statistical tests did not depend on which metric of TBCA was used. Slopes of the simple linear relationships of TBCA and RMF (0.61, 0.74) were both significantly lower than 1 (p < .01 in Wald tests), and the intercepts (0.18, 0.19) were both higher than zero (all p < .01), indicating greater underestimation of TBCA at low RMF values (Figure 2). It should read: We found a positive correlation of RMF and TBCA across studies, regardless of whether TBCA was calculated in reference to plant GPP (R2 = 0.20, p < .001, Figure 2a) or GPP-Rshoot (R2 = 0.33, p < .001, Figure 2b). Because Rshoot was often the smallest component of plant energy budgets, our statistical tests did not depend on which metric of TBCA was used. Slopes of the simple linear relationships of TBCA and RMF (0.54, 0.73) were both significantly lower than 1 (p < .01 in Wald tests), and the intercepts (0.19, 0.18) were both higher than zero (all p < .01), indicating greater underestimation of TBCA at low RMF values (Figure 2). REFERENCE Kong, D., & Fridley, J. D. (2019). Does plant biomass partitioning reflect energetic investments in carbon and nutrient foraging? Functional Ecology, 33, 1627– 1637. https://doi.org/10.1111/1365-2435.13392Wiley Online LibraryWeb of Science®Google Scholar Volume34, Issue2Special Features: Sensory ecology and cognition in social decisions Guest Editors: Karin Schneeberger and Michael Taborsky & Epigenetics in ecology and evolution Guest Editors: Anthony Herrel, Dominique Joly and Etienne DanchinFebruary 2020Pages 545-545 FiguresReferencesRelatedInformation