Hidden shift of the ionome of plants exposed to elevated CO2 depletes minerals at the base of human nutrition
Identifieur interne : 000279 ( Pmc/Corpus ); précédent : 000278; suivant : 000280Hidden shift of the ionome of plants exposed to elevated CO2 depletes minerals at the base of human nutrition
Auteurs : Irakli LoladzeSource :
- eLife [ 2050-084X ] ; 2014.
Abstract
Mineral malnutrition stemming from undiversified plant-based diets is a top global challenge. In C3 plants (e.g., rice, wheat), elevated concentrations of atmospheric carbon dioxide (eCO2) reduce protein and nitrogen concentrations, and can increase the total non-structural carbohydrates (TNC; mainly starch, sugars). However, contradictory findings have obscured the effect of eCO2 on the ionome—the mineral and trace-element composition—of plants. Consequently, CO2-induced shifts in plant quality have been ignored in the estimation of the impact of global change on humans. This study shows that eCO2 reduces the overall mineral concentrations (−8%, 95% confidence interval: −9.1 to −6.9, p<0.00001) and increases TNC:minerals > carbon:minerals in C3 plants. The meta-analysis of 7761 observations, including 2264 observations at state of the art FACE centers, covers 130 species/cultivars. The attained statistical power reveals that the shift is systemic and global. Its potential to exacerbate the prevalence of ‘hidden hunger’ and obesity is discussed.
Url:
DOI: 10.7554/eLife.02245
PubMed: 24867639
PubMed Central: 4034684
Links to Exploration step
PMC:4034684Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Hidden shift of the ionome of plants exposed to elevated CO<sub>2</sub> depletes minerals at the base of human nutrition</title><author><name sortKey="Loladze, Irakli" sort="Loladze, Irakli" uniqKey="Loladze I" first="Irakli" last="Loladze">Irakli Loladze</name></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">24867639</idno><idno type="pmc">4034684</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4034684</idno><idno type="RBID">PMC:4034684</idno><idno type="doi">10.7554/eLife.02245</idno><date when="2014">2014</date><idno type="wicri:Area/Pmc/Corpus">000279</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000279</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Hidden shift of the ionome of plants exposed to elevated CO<sub>2</sub> depletes minerals at the base of human nutrition</title><author><name sortKey="Loladze, Irakli" sort="Loladze, Irakli" uniqKey="Loladze I" first="Irakli" last="Loladze">Irakli Loladze</name></author></analytic><series><title level="j">eLife</title><idno type="eISSN">2050-084X</idno><imprint><date when="2014">2014</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>Mineral malnutrition stemming from undiversified plant-based diets is a top global challenge. In C<sub>3</sub> plants (e.g., rice, wheat), elevated concentrations of atmospheric carbon dioxide (eCO<sub>2</sub>) reduce protein and nitrogen concentrations, and can increase the total non-structural carbohydrates (TNC; mainly starch, sugars). However, contradictory findings have obscured the effect of eCO<sub>2</sub> on the ionome—the mineral and trace-element composition—of plants. Consequently, CO<sub>2</sub>-induced shifts in plant quality have been ignored in the estimation of the impact of global change on humans. This study shows that eCO<sub>2</sub> reduces the overall mineral concentrations (−8%, 95% confidence interval: −9.1 to −6.9, p<0.00001) and increases TNC:minerals > carbon:minerals in C<sub>3</sub> plants. The meta-analysis of 7761 observations, including 2264 observations at state of the art FACE centers, covers 130 species/cultivars. The attained statistical power reveals that the shift is systemic and global. Its potential to exacerbate the prevalence of ‘hidden hunger’ and obesity is discussed.</p><p><bold>DOI:</bold><ext-link ext-link-type="doi" xlink:href="10.7554/eLife.02245.001">http://dx.doi.org/10.7554/eLife.02245.001</ext-link></p></div></front><back><div1 type="bibliography"><listBibl><biblStruct></biblStruct><biblStruct><analytic><author><name sortKey="Al Rawahy, Sh" uniqKey="Al Rawahy S">SH Al-Rawahy</name></author><author><name sortKey="Sulaiman, H" uniqKey="Sulaiman H">H Sulaiman</name></author><author><name sortKey="Farooq, Sa" uniqKey="Farooq S">Sa Farooq</name></author><author><name sortKey="Karam, Mf" uniqKey="Karam M">MF Karam</name></author><author><name sortKey="Sherwani, N" uniqKey="Sherwani N">N Sherwani</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Arnaud, J" uniqKey="Arnaud J">J Arnaud</name></author><author><name sortKey="Bertrais, S" uniqKey="Bertrais S">S Bertrais</name></author><author><name sortKey="Roussel, Am" 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<front><journal-meta><journal-id journal-id-type="nlm-ta">eLife</journal-id><journal-id journal-id-type="iso-abbrev">Elife</journal-id><journal-id journal-id-type="hwp">eLife</journal-id><journal-id journal-id-type="publisher-id">eLife</journal-id><journal-title-group><journal-title>eLife</journal-title></journal-title-group><issn pub-type="epub">2050-084X</issn><publisher><publisher-name>eLife Sciences Publications, Ltd</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">24867639</article-id><article-id pub-id-type="pmc">4034684</article-id><article-id pub-id-type="publisher-id">02245</article-id><article-id pub-id-type="doi">10.7554/eLife.02245</article-id><article-categories><subj-group subj-group-type="display-channel"><subject>Research Article</subject></subj-group><subj-group subj-group-type="heading"><subject>Ecology</subject></subj-group><subj-group subj-group-type="heading"><subject>Epidemiology and Global Health</subject></subj-group></article-categories><title-group><article-title>Hidden shift of the ionome of plants exposed to elevated CO<sub>2</sub> depletes minerals at the base of human nutrition</article-title></title-group><contrib-group><contrib id="author-7223" contrib-type="author"><name><surname>Loladze</surname><given-names>Irakli</given-names></name><xref ref-type="aff" rid="aff1">1</xref><xref ref-type="corresp" rid="cor1">*</xref><xref ref-type="fn" rid="con1"></xref><xref ref-type="fn" rid="conf1"></xref><xref ref-type="other" rid="dataro1"></xref><aff id="aff1"><label>1</label><addr-line>Department of Mathematics Education</addr-line>,<institution>The Catholic University of Daegu</institution>,<addr-line>Gyeongsan</addr-line>,<country>Republic of Korea</country></aff></contrib></contrib-group><contrib-group><contrib contrib-type="editor"><name><surname>Baldwin</surname><given-names>Ian T</given-names></name><role>Reviewing editor</role><aff><institution>Max Planck Institute for Chemical Ecology</institution>,<country>Germany</country></aff></contrib></contrib-group><author-notes><corresp id="cor1"><label>*</label>For correspondence: <email>loladze@asu.edu</email></corresp></author-notes><pub-date pub-type="epub"><day>07</day><month>5</month><year>2014</year></pub-date><pub-date pub-type="collection"><year>2014</year></pub-date><volume>3</volume><elocation-id>e02245</elocation-id><history><date date-type="received"><day>08</day><month>1</month><year>2014</year></date><date date-type="accepted"><day>25</day><month>4</month><year>2014</year></date></history><permissions><copyright-statement>Copyright © 2014, Loladze</copyright-statement><copyright-year>2014</copyright-year><copyright-holder>Loladze</copyright-holder><license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/3.0/"><license-p>This article is distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/3.0/">Creative Commons Attribution License</ext-link>, which permits unrestricted use and redistribution provided that the original author and source are credited.</license-p></license></permissions><self-uri content-type="pdf" xlink:type="simple" xlink:href="elife02245.pdf"></self-uri><related-article id="d35e135" related-article-type="commentary" ext-link-type="doi" xlink:href="10.7554/eLife.03233"></related-article><abstract><p>Mineral malnutrition stemming from undiversified plant-based diets is a top global challenge. In C<sub>3</sub> plants (e.g., rice, wheat), elevated concentrations of atmospheric carbon dioxide (eCO<sub>2</sub>) reduce protein and nitrogen concentrations, and can increase the total non-structural carbohydrates (TNC; mainly starch, sugars). However, contradictory findings have obscured the effect of eCO<sub>2</sub> on the ionome—the mineral and trace-element composition—of plants. Consequently, CO<sub>2</sub>-induced shifts in plant quality have been ignored in the estimation of the impact of global change on humans. This study shows that eCO<sub>2</sub> reduces the overall mineral concentrations (−8%, 95% confidence interval: −9.1 to −6.9, p<0.00001) and increases TNC:minerals > carbon:minerals in C<sub>3</sub> plants. The meta-analysis of 7761 observations, including 2264 observations at state of the art FACE centers, covers 130 species/cultivars. The attained statistical power reveals that the shift is systemic and global. Its potential to exacerbate the prevalence of ‘hidden hunger’ and obesity is discussed.</p><p><bold>DOI:</bold><ext-link ext-link-type="doi" xlink:href="10.7554/eLife.02245.001">http://dx.doi.org/10.7554/eLife.02245.001</ext-link></p></abstract><abstract abstract-type="executive-summary"><title>eLife digest</title><p>Rice and wheat provide two out every five calories that humans consume. Like other plants, crop plants convert carbon dioxide (or CO<sub>2</sub>) from the air into sugars and other carbohydrates. They also take up minerals and other nutrients from the soil.</p><p>The increase in CO<sub>2</sub> in the atmosphere that has happened since the Industrial Revolution is thought to have increased the production of sugars and other carbohydrates in plants by up to 46%. CO<sub>2</sub> levels are expected to rise even further in the coming decades; and higher levels of CO<sub>2</sub> are known to lead to lower levels of proteins in plants. But less is known about the effects of CO<sub>2</sub> levels on the concentrations of minerals and other nutrients in plants.</p><p>Loladze has investigated the effect of rising CO<sub>2</sub> levels on the nutrient levels in food plants by analyzing data on 130 varieties of plants: his dataset includes the results of 7761 observations made over the last 30 years, by researchers around the world. Elevated CO<sub>2</sub> levels were found to reduce the overall concentration of 25 important minerals—including calcium, potassium, zinc, and iron—in plants by 8% on average. Furthermore, Loladze found that an increased exposure to CO<sub>2</sub> also increased the ratio of carbohydrates to minerals in these plants.</p><p>This reduction in the nutritional value of plants could have profound impacts on human health: a diet that is deficient in minerals and other nutrients can cause malnutrition, even if a person consumes enough calories. This type of malnutrition is common around the world because many people eat only a limited number of staple crops, and do not eat enough foods that are rich in minerals, such as fruits, vegetables, dairy and meats. Diets that are poor in minerals (in particular, zinc and iron) lead to reduced growth in childhood, to a reduced ability to fight off infections, and to higher rates of maternal and child deaths.</p><p>Loladze argues that these changes might contribute to the rise in obesity, as people eat increasingly starchy plant-based foods, and eat more to compensate for the lower mineral levels found in crops. Looking to the future, these findings highlight the importance of breeding food crops to be more nutritious as the world's CO<sub>2</sub> levels continue to rise.</p><p><bold>DOI:</bold><ext-link ext-link-type="doi" xlink:href="10.7554/eLife.02245.002">http://dx.doi.org/10.7554/eLife.02245.002</ext-link></p></abstract><kwd-group kwd-group-type="author-keywords"><title>Author keywords</title><kwd>elevated CO<sub>2</sub></kwd><kwd>zinc</kwd><kwd>iron</kwd><kwd>ionome</kwd><kwd>crops</kwd><kwd>human nutrition</kwd></kwd-group><kwd-group kwd-group-type="research-organism"><title>Research organism</title><kwd>none</kwd></kwd-group><funding-group><funding-statement>The author declares that there was no external funding for this work.</funding-statement></funding-group><custom-meta-group><custom-meta><meta-name>elife-xml-version</meta-name><meta-value>0.7</meta-value></custom-meta><custom-meta specific-use="meta-only"><meta-name>Author impact statement</meta-name><meta-value>Increasing levels of atmospheric carbon dioxide reduce the mineral content but increase the levels of starch and sugars found in crop plants; which could exacerbate both obesity and malnutrition in some human populations.</meta-value></custom-meta></custom-meta-group></article-meta></front><body><sec sec-type="intro" id="s1"><title>Introduction</title><p>Mankind's ultimate source of carbohydrates is atmospheric carbon dioxide (CO<sub>2</sub>) converted by photosynthesis to sugars. The bulk of the terrestrial conversion of CO<sub>2</sub>-to-carbohydrates is done by C<sub>3</sub> plants, which account for over three quarters of global primary production and for over 90% of Earth's plant species (<xref rid="bib151" ref-type="bibr">Still and Berry, 2003</xref>). (<italic>If not stated otherwise, hereafter, terms ‘plant(s)’ and ‘crop(s)’ refer to C<sub>3</sub> species</italic>). When exposed to CO<sub>2</sub> concentrations twice the preindustrial level of ∼280 ppm, plants increase the synthesis of carbohydrates by 19–46% (<xref rid="bib87" ref-type="bibr">Leakey et al., 2009</xref>). Currently, CO<sub>2</sub> concentrations are reaching 400 ppm—the highest level since the dawn of agriculture and likely to be the highest since the rise of modern humans (<xref rid="bib143" ref-type="bibr">Siegenthaler et al., 2005</xref>). Within a single human lifespan, CO<sub>2</sub> levels are projected to reach 421–936 ppm (<xref rid="bib65" ref-type="bibr">IPCC, 2013</xref>). Will rising CO<sub>2</sub> concentrations—one of the most certain and pervasive aspects of global climate change—alter the quality of crops and wild plants? Will the CO<sub>2</sub>-induced stimulation of carbohydrate synthesis increase the carbohydrates-to-minerals ratio in crops? Can such shifts in crop quality affect human nutrition and health?</p><p>Elevated CO<sub>2</sub> effects on plant <italic>quantity</italic> (productivity and total biomass) have been extensively studied and show higher agricultural yields for crops, including wheat, rice, barley, and potato. But eCO<sub>2</sub> effects on plant <italic>quality</italic>, and possible cascading effects on human nutrition, have been largely ignored in the estimation of the impact of eCO<sub>2</sub> on humans. Notably, <xref rid="bib64" ref-type="bibr">IPCC (2007</xref>, <xref rid="bib65" ref-type="bibr">2013)</xref> and <xref rid="bib1" ref-type="bibr">AAAC Climate Science Panel (2014)</xref> include direct CO<sub>2</sub> effects (e.g., ocean acidification) in their climate change assessments but do not mention any CO<sub>2</sub> effects on crop or wild plant quality. However, it is unwarranted to assume that plants will balance the increased carbohydrate synthesis with other adjustments to their physiology to maintain the nutritional quality for their consumers in a state of unperturbed homeostasis. The stoichiometry—the relative ratios of chemical elements—in plants is plastic and, to a considerable degree, reflects their environment (<xref rid="bib149" ref-type="bibr">Sterner and Elser, 2002</xref>). However, detecting CO<sub>2</sub>-induced shifts in plant quality is challenging for several reasons. First, plant quality involves multiple nutritional currencies, for example macronutrients (carbohydrates, protein, and fat) and micronutrients (minerals, vitamins and phytonutrients). Assessing relative changes within and among multiple currencies requires significantly more effort and funding than measuring only plant quantity (e.g., yield). Second, plant quality, including the plant ionome—all the minerals and trace-elements found in a plant (<xref rid="bib86" ref-type="bibr">Lahner et al., 2003</xref>; <xref rid="bib136" ref-type="bibr">Salt et al., 2008</xref>)—is inherently variable; and measurement imprecisions further amplify the variability. For example, <xref rid="bib147" ref-type="bibr">Stefan et al. (1997)</xref> report the accuracy test for 39 facilities that analyzed samples of the same plant tissues: the inter-laboratory variance was 6.5% for N, but twice as large for phosphorus (P) and calcium (Ca), and reached 130% for sodium (Na). Therefore, CO<sub>2</sub>-induced changes in the plant ionome (the signal) can be easily lost amid highly variable data (the noise), especially when such data are limited and sample sizes are small. However, it is important to bear in mind that a low signal-to-noise ratio <italic>does not</italic> imply that the signal is practically insignificant, especially if it is global and sustained—a point revisited in the ‘Discussion’.</p><sec id="s1-1"><title>Elusive CO<sub>2</sub> effect on the plant ionome: contradictory findings</title><p>The first empirical evidence of lower mineral content in plants exposed to eCO<sub>2</sub> appeared at least over a quarter century ago (e.g., <xref rid="bib125" ref-type="bibr">Porter and Grodzinski, 1984</xref>; <xref rid="bib113" ref-type="bibr">Peet et al., 1986</xref>; <xref rid="bib106" ref-type="bibr">O’Neill et al., 1987</xref>). Physiological mechanisms responsible for the overall decline of plant mineral content—with expected changes being <italic>non-uniform</italic> across minerals—have been proposed: the increased carbohydrate production combined with other eCO<sub>2</sub> effects such as reduced transpiration (<xref rid="bib91" ref-type="bibr">Loladze, 2002</xref>; <xref rid="bib97" ref-type="bibr">McGrath and Lobell, 2013</xref>). However, most of the experimental evidence showing CO<sub>2</sub>-induced mineral declines came from artificial facilities, mainly closed chambers and glasshouses, and many results were statistically non-significant. This led some research groups to challenge altogether the notion of lower mineral content in plants exposed to eCO<sub>2</sub> in field conditions. Such conditions are most accurately represented in Free-Air Carbon dioxide Enrichment (FACE) centers, which have been established in at least 11 countries.</p><p>In the grains of rice harvested at four FACE paddies in Japan, <xref rid="bib90" ref-type="bibr">Lieffering et al. (2004)</xref> found no decline in any of the minerals but lower N content. The result disagreed with <xref rid="bib140" ref-type="bibr">Seneweera and Conroy (1997)</xref>, who were the first to report lower iron (Fe) and zinc (Zn) in grains of rice grown at eCO<sub>2</sub> and warned that altered rice quality can negatively affect developing countries. <xref rid="bib90" ref-type="bibr">Lieffering et al. (2004)</xref>, however, argued that the result of <xref rid="bib140" ref-type="bibr">Seneweera and Conroy (1997)</xref> could be an artifact of growing rice in pots, which restrict rooting volumes. They hypothesized that in FACE studies, which provide unrestricted rooting volumes, plants would increase uptake of all minerals to balance the increased carbohydrate production. This hypothesis, however, found no support in the FACE studies of <xref rid="bib111" ref-type="bibr">Pang et al. (2005)</xref> and <xref rid="bib174" ref-type="bibr">Yang et al. (2007)</xref> (carried out in China and latitudinally not very far from the study in Japan), who found that eCO<sub>2</sub> significantly altered the content of several minerals in rice grains.</p><p>The contradictory results coming from these studies on rice seem perplexing, especially in light of the very robust effect that eCO<sub>2</sub> has on N in non-leguminous plants. Elevated CO<sub>2</sub> reduces N concentrations by 10–18% systemically throughout various tissues: leaves, stems, roots, tubers, reproductive and edible parts, including seeds and grains (<xref rid="bib23" ref-type="bibr">Cotrufo et al., 1998</xref>; <xref rid="bib66" ref-type="bibr">Jablonski et al., 2002</xref>; <xref rid="bib152" ref-type="bibr">Taub et al., 2008</xref>). If the increased carbohydrate production dilutes the nutrient content in plants, why does the dichotomy seem to exist between the responses of N and minerals to eCO<sub>2</sub>? In addition to the carbohydrate dilution and reduced transpiration, eCO<sub>2</sub> can further lower N concentrations in plants by: (1) reducing concentrations of Rubisco—one of the most abundant proteins on Earth that comprises a sizable N-pool in plants (<xref rid="bib27" ref-type="bibr">Drake et al., 1997</xref>), and (2) inhibiting nitrate assimilation (<xref rid="bib12" ref-type="bibr">Bloom et al., 2010</xref>). Hence, it is reasonable to expect the effect of eCO<sub>2</sub> on N to be larger and, thus, easier to discern than its effect on most minerals. The stronger signal for N, combined with the plentiful and less noisy data on this element, can help explain why by the end of last century the effect of eCO<sub>2</sub> on N had been already elucidated (<xref rid="bib23" ref-type="bibr">Cotrufo et al., 1998</xref>), but its effect on minerals has remained elusive.</p><p>The obscure nature of the effect of eCO<sub>2</sub> on minerals becomes particularly apparent in the largest to date meta-analysis on the issue by <xref rid="bib29" ref-type="bibr">Duval et al. (2011)</xref>, who fragmented data from 56 eCO<sub>2</sub> studies into 67 cases. In 47 of the cases, the effect of eCO<sub>2</sub> on minerals was statistically non-significant, that is the 95% Confidence Interval (CI) for the effect size overlapped with 0. The remaining 20 cases were statistically significant but showed no pattern: for example, Fe increased in grasses but decreased in trees, Zn increased in roots but decreased in stems, while in grains only sulfur (S) decreased. <xref rid="bib29" ref-type="bibr">Duval et al. (2011)</xref> concluded: “A major finding of this synthesis is the lack of effect of CO<sub>2</sub> on crop grains nutrient concentration”. This would imply laying to rest the hypothesis that eCO<sub>2</sub> consistently alters the plant ionome and would render mitigation efforts to combat declining crop mineral concentrations in the rising CO<sub>2</sub> world unnecessary. However, a closer examination of the results of <xref rid="bib29" ref-type="bibr">Duval et al. (2011)</xref> reveals that every statistically significant increase in mineral concentrations was obtained by bootstrapping a sample of size 2, 4 or 5—a recipe for generating invalid 95% CIs. <xref rid="bib63" ref-type="bibr">Ioannidis (2005)</xref> showed that false research findings, stemming from small sample sizes and associated low statistical power, are a persistent problem in biomedical sciences.</p></sec><sec id="s1-2"><title>‘Power failure’ and the plant ionome</title><p>Calling the problem as ‘power failure’, <xref rid="bib15" ref-type="bibr">Button et al. (2013)</xref> emphasized that the probability of a research finding to reflect a true effect drops drastically if the statistical power is reduced from 0.80 (considered as appropriate) to low levels, for example <0.30. Since the power of a statistical test drops non-linearly with the effect size, a sample size that is sufficient for detecting a 15% effect, for example a decline in N content, can be inadequate for detecting a 5% effect, for example a decline in a mineral content. Considering that the standard deviation of mineral concentrations in a plant tissue can reach 25% (<xref rid="bib28" ref-type="bibr">Duquesnay et al., 2000</xref>; <xref rid="bib86" ref-type="bibr">Lahner et al., 2003</xref>), the 5% effect size standardized as Cohen's <italic>d</italic> is <italic>d</italic> = 5/25 = 0.2. A <italic>t</italic> test applied for <italic>d</italic> = 0.2 to a sample size of 3–5—a typical size used in eCO<sub>2</sub> studies—yields the power of 0.06–0.10 (<xref rid="bib39" ref-type="bibr">Faul et al., 2007</xref>). (Unfortunately, <italic>MetaWin</italic> (<xref rid="bib134" ref-type="bibr">Rosenberg et al., 2000</xref>), a statistical package routinely used in meta-analytic and other CO<sub>2</sub> studies in ecology, provides neither a priori nor <italic>post-hoc</italic> power estimates.) Such a small power not only raises the probability of obtaining a false negative to 90–94% but also increases the likelihood that a statistically significant result does not reflect a true effect (<xref rid="bib15" ref-type="bibr">Button et al., 2013</xref>).</p></sec><sec id="s1-3"><title>Answering questions with adequate power</title><p>As of this writing, researchers on four continents have generated data sufficient for answering with an adequate statistical power, the following questions:<list list-type="order"><list-item><p>Does eCO<sub>2</sub> shift the plant ionome? If yes, what are the direction and magnitude of shifts for individual chemical elements? How does the effect of eCO<sub>2</sub> on N compares to its effect on minerals?</p></list-item><list-item><p>Do FACE studies differ principally from non-FACE studies in their effect on the plant ionome?</p></list-item><list-item><p>Do the plant ionomes in temperate and subtropical/tropical regions differ in their response to eCO<sub>2</sub>?</p></list-item><list-item><p>Do the ionomes of photosynthetic tissues and edible parts differ in their response to eCO<sub>2</sub>? How does eCO<sub>2</sub> affect the ionomes of various plant groups (woody/herbaceous, wild/crops, C<sub>3</sub>/C<sub>4</sub>) and grains of the world's top C<sub>3</sub> cereals—wheat, rice, and barley?</p></list-item></list></p></sec></sec><sec sec-type="results" id="s2"><title>Results</title><p>For brevity, hereafter ‘minerals’ refer to all elements except C, hydrogen (H), oxygen (O), and N. All results are for C<sub>3</sub> plants except when noted otherwise.</p><sec id="s2-1"><title>Power analysis</title><p>Plotting the effect sizes (with 95% CIs) for the 25 minerals against their respective statistical power reveals a clear pattern (<xref ref-type="fig" rid="fig1">Figure 1</xref>). In the very low power (<0.20) region, the noise completely hides the CO<sub>2</sub>-induced shift of the plant ionome. In the low power region (<0.40), the shift still remains obscure. As the statistical power increases, so does the likelihood that a statistically significant result reflects true effect and, consequently, the direction and the magnitude of the CO<sub>2</sub> effect on minerals become increasingly visible in the higher power regions of the plot.<fig id="fig1" orientation="portrait" position="float"><object-id pub-id-type="doi">10.7554/eLife.02245.003</object-id><label>Figure 1.</label><caption><title>Statistical power and the effect of CO<sub>2</sub> on the plant ionome.</title><p>The effect of elevated atmospheric CO<sub>2</sub> concentrations (eCO<sub>2</sub>) on the mean concentration of minerals in plants plotted (with the respective 95% confidence intervals [CI]) against the power of statistical analysis. The figure reflects data on 25 minerals in edible and foliar tissues of 125 C<sub>3</sub> plant species and cultivars. The true CO<sub>2</sub> effect is hidden in the very low and the low power regions. As the statistical power increases, the true effect becomes progressively clearer: the systemic shift of the plant ionome.</p><p><bold>DOI:</bold><ext-link ext-link-type="doi" xlink:href="10.7554/eLife.02245.003">http://dx.doi.org/10.7554/eLife.02245.003</ext-link></p><p><supplementary-material content-type="local-data" id="SD1-data"><object-id pub-id-type="doi">10.7554/eLife.02245.015</object-id><label>Figure 1—source data 1.</label><caption><title>Supportive data for <xref ref-type="fig" rid="fig1 fig2 fig3 fig4 fig5 fig6 fig7 fig8">Figures 1–8</xref>.</title><p><bold>DOI:</bold><ext-link ext-link-type="doi" xlink:href="10.7554/eLife.02245.015">http://dx.doi.org/10.7554/eLife.02245.015</ext-link></p></caption><media xlink:href="elife02245s001.xlsx" mimetype="application" mime-subtype="xlsx" orientation="portrait" xlink:type="simple" id="d35e656" position="anchor"></media></supplementary-material></p></caption><graphic xlink:href="elife02245f001"></graphic></fig></p><p>To increase the likelihood of reporting true effects, only results with the statistical power >0.40 are reported in this section. However, <xref ref-type="supplementary-material" rid="SD1-data">Figure 1–source data 1</xref> lists all the results together with their p-values irrespective of the statistical power (e.g., results for chromium (Cr) or the bean ionome are not shown here due to low power, but are listed in <xref ref-type="supplementary-material" rid="SD1-data">Figure 1–source data 1</xref>).</p></sec><sec id="s2-2"><title>CO<sub>2</sub> effect on individual elements</title><p>Across all the data, eCO<sub>2</sub> reduced concentrations of P, potassium (K), Ca, S, magnesium (Mg), Fe, Zn, and copper (Cu) by 6.5–10% (p<0.0001) as shown on <xref ref-type="fig" rid="fig2">Figure 2</xref>. Across all the 25 minerals, the mean change was (−8%, −9.1 to −6.9, p<0.00001). Only manganese (Mn) showed no significant change. It is not clear whether the oxygen-evolving complex (OEC) demands for Mn separate this mineral from the pattern of declines exhibited by other minerals. Among all the measured elements, only C increased (6%, 2.6 to 10.4, p<0.01). The sharp difference between the responses of C and minerals to eCO<sub>2</sub> is expected if a higher carbohydrate content drives the change in the plant ionome: for most plant tissues, the dilution by carbohydrates lowers the content of minerals while having little effect on C (<xref rid="bib91" ref-type="bibr">Loladze, 2002</xref>). (This also suggests that the increase in C concentrations found here could be a result of a higher content of lipids or lignin—the two sizable plant compounds that are very C-rich [∼60–75% C].)<fig id="fig2" orientation="portrait" position="float"><object-id pub-id-type="doi">10.7554/eLife.02245.004</object-id><label>Figure 2.</label><caption><title>The effect of CO<sub>2</sub> on individual chemical elements in plants.</title><p>Change (%) in the mean concentration of chemical elements in plants grown in eCO<sub>2</sub> relative to those grown at ambient levels. Unless noted otherwise, all results in this and subsequent figures are for C<sub>3</sub> plants. Average ambient and elevated CO<sub>2</sub> levels across all the studies are 368 ppm and 689 ppm respectively. The results reflect the plant data (foliar and edible tissues, FACE and non-FACE studies) from four continents. Error bars represent the standard error of the mean (calculated using the number of <italic>mean</italic> observations for each element). The number of mean and total (with all the replicates) observations for each element is as follows: C(35/169), N(140/696), P(152/836), K(128/605), Ca(139/739), S(67/373), Mg(123/650), Fe(125/639), Zn(123/702), Cu(124/612), and Mn(101/493). An element is shown individually if the statistical power for a 5% effect size for the element is >0.40. The ‘ionome’ bar reflects all the data on 25 minerals (all the elements in the dataset except of C and N). All the data are available at Dryad depository and at GitHub. Copies of all the original sources for the data are available upon request.</p><p><bold>DOI:</bold><ext-link ext-link-type="doi" xlink:href="10.7554/eLife.02245.004">http://dx.doi.org/10.7554/eLife.02245.004</ext-link></p></caption><graphic xlink:href="elife02245f002"></graphic></fig></p><p>The patterns of change within edible and foliar tissues are similar: N, P, Ca, Mg, Zn, and Cu declined significantly in both tissues (<xref ref-type="fig" rid="fig3 fig4">Figures 3, 4</xref>). Aside from Mn, only K showed no significant decline in the edible tissues (on <xref ref-type="fig" rid="fig1">Figure 1</xref>, it is visible as one of the only two black 95% CI in the ‘High Power’ region). In the foliar tissues, Mg declined the most (−12.3%, −16 to −8.7), which is congruent with the hypothesis of <xref rid="bib97" ref-type="bibr">McGrath and Lobell (2013)</xref> that Mg should exhibit a larger decline in photosynthetic tissues because ‘chlorophyll requires a large fraction of total plant Mg, and chlorophyll concentration is reduced by growth in elevated CO<sub>2</sub>’. However, the 95% CIs for Mg and for most other minerals overlap. A richer dataset would shed more light on the issue of Mg in photosynthetic tissues.<fig id="fig3" orientation="portrait" position="float"><object-id pub-id-type="doi">10.7554/eLife.02245.005</object-id><label>Figure 3.</label><caption><title>The effect of CO<sub>2</sub> on foliar tissues.</title><p>Change (%) in the mean concentration of chemical elements in foliar tissues grown in eCO<sub>2</sub> relative to those grown at ambient levels. Average ambient and eCO<sub>2</sub> levels across all the foliar studies are 364 ppm and 699 ppm respectively. Error bars represent 95% CI. For each element, the number of independent mean observations, <italic>m</italic>, is shown with the respective statistical power. For each plant group, <italic>m</italic> equals the sum of mean observations over all the minerals (not including C and N) for that group. Elements and plant groups for which the statistical power is >0.40 (for a 5% effect size) are shown.</p><p><bold>DOI:</bold><ext-link ext-link-type="doi" xlink:href="10.7554/eLife.02245.005">http://dx.doi.org/10.7554/eLife.02245.005</ext-link></p></caption><graphic xlink:href="elife02245f003"></graphic></fig><fig id="fig4" orientation="portrait" position="float"><object-id pub-id-type="doi">10.7554/eLife.02245.006</object-id><label>Figure 4.</label><caption><title>The effect of CO<sub>2</sub> on edible tissues.</title><p>Change (%) in the mean concentration of chemical elements in edible parts of crops grown in eCO<sub>2</sub> relative to those grown at ambient levels. Average ambient and elevated CO<sub>2</sub> levels across all the crop edible studies are 373 ppm and 674 ppm respectively. Other details are in the legends for <xref ref-type="fig" rid="fig2 fig3">Figures 2 and 3</xref>.</p><p><bold>DOI:</bold><ext-link ext-link-type="doi" xlink:href="10.7554/eLife.02245.006">http://dx.doi.org/10.7554/eLife.02245.006</ext-link></p></caption><graphic xlink:href="elife02245f004"></graphic></fig></p><p>As expected, among all elements N declined the most (−15%, −17.8 to −13.1, p<0.00001) (<xref ref-type="fig" rid="fig2">Figure 2</xref>), matching very closely previous findings (<xref ref-type="fig" rid="fig3 fig4 fig5 fig6">Figures 3–6</xref>): the 17–19% decline in leaves found by <xref rid="bib23" ref-type="bibr">Cotrufo et al. (1998)</xref> and the 14% decline in seeds found by <xref rid="bib66" ref-type="bibr">Jablonski et al. (2002)</xref>. Since the contents of N and protein correlate strongly in plant tissues, the lower N in edible tissues (<xref ref-type="fig" rid="fig4">Figure 4</xref>) corroborates the protein declines in crops found by <xref rid="bib152" ref-type="bibr">Taub et al. (2008)</xref>.<fig id="fig5" orientation="portrait" position="float"><object-id pub-id-type="doi">10.7554/eLife.02245.007</object-id><label>Figure 5.</label><caption><title>The effect of CO<sub>2</sub> in artificial enclosures.</title><p>Change (%) in the mean concentration of chemical elements of plants grown in chambers, greenhouses, and other artificial enclosures under eCO<sub>2</sub> relative to those grown at ambient levels. Average ambient and eCO<sub>2</sub> levels across all the non-FACE studies are 365 ppm and 732 ppm respectively. Other details are in the legends for <xref ref-type="fig" rid="fig2 fig3">Figures 2 and 3</xref>.</p><p><bold>DOI:</bold><ext-link ext-link-type="doi" xlink:href="10.7554/eLife.02245.007">http://dx.doi.org/10.7554/eLife.02245.007</ext-link></p></caption><graphic xlink:href="elife02245f005"></graphic></fig><fig id="fig6" orientation="portrait" position="float"><object-id pub-id-type="doi">10.7554/eLife.02245.008</object-id><label>Figure 6.</label><caption><title>The effect of CO<sub>2</sub> at FACE centers.</title><p>Change (%) in the mean concentration of chemical elements of plants grown in Free-Air Carbon dioxide Enrichments (FACE) centers relative to those grown at ambient levels. Average ambient and eCO<sub>2</sub> levels across all the FACE studies are 376 ppm and 560 ppm respectively. Other details are in the legends for <xref ref-type="fig" rid="fig2 fig3">Figures 2 and 3</xref>.</p><p><bold>DOI:</bold><ext-link ext-link-type="doi" xlink:href="10.7554/eLife.02245.008">http://dx.doi.org/10.7554/eLife.02245.008</ext-link></p></caption><graphic xlink:href="elife02245f006"></graphic></fig></p></sec><sec id="s2-3"><title>FACE vs non-FACE studies</title><p>With respect to the types of experiments, the CO<sub>2</sub> effect on the plant ionome is surprisingly robust: in both the FACE and the non-FACE studies eCO<sub>2</sub> significantly reduced N, P, K, Ca, S, Mg, and Zn (<xref ref-type="fig" rid="fig5 fig6">Figures 5, 6</xref>). The high cost of CO<sub>2</sub> required for running free-air experiments led to a much lower average level of eCO<sub>2</sub> in the FACE studies (560 ppm) cf. 732 ppm in the non-FACE studies. It is plausible that the lower levels of CO<sub>2</sub> in the FACE studies contributed to a smaller overall mineral decline (−6.1%, −7.8 to −4.4) cf. (−8.7%, −10.1 to −7.4) for the non-FACE studies. In both the FACE and the non-FACE studies, the overall mineral concentrations declined significantly in herbaceous plants and crops, foliar and edible tissues, including wheat and rice (<xref ref-type="fig" rid="fig5 fig6">Figures 5, 6</xref>).</p></sec><sec id="s2-4"><title>Geographical analysis</title><p>The CO<sub>2</sub> effect on the plant ionome appears to be pervasive throughout latitudes (<xref ref-type="fig" rid="fig7 fig8">Figures 7, 8</xref>). With the exception of three small centers (in Bangladesh, Japan, and the UK), the mean mineral concentrations declined in every FACE and open top chamber (OTC) center on four continents. The mineral decline in the tropics and subtropics (−7.2%, −10.4 to −4.0, p<0.0001) is comparable to the decline in the temperate region (−6.4%, −7.9 to −5.0, p<0.00001). A finer regional fragmentation currently is not possible due to lack of data for Africa, South America, Russia, and Canada. For many existing centers the data are limited and yield a low statistical power.<fig id="fig7" orientation="portrait" position="float"><object-id pub-id-type="doi">10.7554/eLife.02245.009</object-id><label>Figure 7.</label><caption><title>The effect of CO<sub>2</sub> at various locations and latitudes.</title><p>Locations of the FACE and Open Top Chamber (OTC) centers, which report concentrations of minerals in foliar or edible tissues, are shown as white dots inside colored circles. The area of a circle is proportional to the total number of observations (counting replicates) generated by the center. If the mean change is negative (decline in mineral content), the respective circle is blue; otherwise, it is red. The figure reflects data on 21 minerals in 57 plant species and cultivars. The shaded region (between 35 N and S latitudes) represents tropics and subtropics.</p><p><bold>DOI:</bold><ext-link ext-link-type="doi" xlink:href="10.7554/eLife.02245.009">http://dx.doi.org/10.7554/eLife.02245.009</ext-link></p></caption><graphic xlink:href="elife02245f007"></graphic></fig><fig id="fig8" orientation="portrait" position="float"><object-id pub-id-type="doi">10.7554/eLife.02245.010</object-id><label>Figure 8.</label><caption><title>The systemic aspect of the CO<sub>2</sub> effect.</title><p>Change (%) in the mean concentration of minerals in plants grown in eCO<sub>2</sub> relative to those grown at ambient levels. All the results in the figure reflect the combined data for the foliar and the edible tissues. The number of total <italic>mean</italic> observations (<italic>m</italic>) for all the measured minerals across all the studies for each crop/plant group, experiment type, country, or region is shown with the respective statistical power. Country specific and regional results reflect all the FACE and Open Top Chamber (OTC) studies carried in any given country/region. The number of total observations (with replicates) for all the minerals (not counting C and N) for each country is as follows: Australia (926), China (193), Finland (144), Germany (908), and USA (1156). Other details are in the legends for <xref ref-type="fig" rid="fig2 fig3">Figures 2 and 3</xref>.</p><p><bold>DOI:</bold><ext-link ext-link-type="doi" xlink:href="10.7554/eLife.02245.010">http://dx.doi.org/10.7554/eLife.02245.010</ext-link></p></caption><graphic xlink:href="elife02245f008"></graphic></fig></p><p>Germany leads the world in the FACE and OTC data generation with the largest number of <italic>mean</italic> observations of mineral concentrations (285), followed by the USA (218) (<xref ref-type="fig" rid="fig8">Figure 8</xref>). Though Australia generated only 30 mean observations, it stands out in the exceptional precision of some of its studies: the wheat experiments of <xref rid="bib43" ref-type="bibr">Fernando et al. (2014)</xref> employed an unprecedented for FACE studies 48 replicates (for this reason, the study is easily identifiable on <xref ref-type="fig" rid="fig9">Figure 9</xref>).<fig id="fig9" orientation="portrait" position="float"><object-id pub-id-type="doi">10.7554/eLife.02245.011</object-id><label>Figure 9.</label><caption><title>Testing for publication bias.</title><p>A funnel plot of the effect size (the natural log of the response ratio) plotted against the number of replicates/sample sizes (<italic>n</italic>) for each study and each mineral in the dataset for C<sub>3</sub> plants. The plot provides a simple visual evaluation of the distribution of effect sizes. The blue line represents the mean effect size of eCO<sub>2</sub> on mineral concentrations: the decline of 8.39% (yielding the decline of 8.04% when back transferred from the log-form). The symmetrical funnel shape of the plot around the mean effect size indicates the publication bias in the dataset is insignificant (<xref rid="bib31" ref-type="bibr">Egger et al., 1997</xref>).</p><p><bold>DOI:</bold><ext-link ext-link-type="doi" xlink:href="10.7554/eLife.02245.011">http://dx.doi.org/10.7554/eLife.02245.011</ext-link></p></caption><graphic xlink:href="elife02245f009"></graphic></fig></p></sec><sec id="s2-5"><title>CO<sub>2</sub> effect on various plant groups and tissues</title><p>Since eCO<sub>2</sub> does not stimulate carbohydrate production in C<sub>4</sub> plants to a degree that it does in C<sub>3</sub> plants, one would expect a milder CO<sub>2</sub> effect on minerals for C<sub>4</sub> plants. Indeed, no statistically significant effect was found on the ionome of C4 plants (<xref ref-type="fig" rid="fig8">Figure 8</xref>). Note, however, that the very limited data on this plant group are insufficient for deducing the absence of the effect; rather, it is likely that the effect size <5% for C<sub>4</sub> plants.</p><p>The CO<sub>2</sub> effect on the C<sub>3</sub> plant ionome shows its systemic character through the analysis of various plant groups and tissues (<xref ref-type="fig" rid="fig3 fig4 fig8">Figures 3, 4 and 8</xref>). Elevated CO<sub>2</sub> reduced the overall mineral concentrations in crops (−7.2%, −8.6 to −5.6); wild (−9.7%, −11.6 to −7.8), herbaceous (−7.5%, −8.7 to −5.6), and woody (−9.6%, −12.1 to −7.6) plants; foliar (−9.2%, −10.8 to −7.6) and edible (−6.4%, −7.8 to −5.1) tissues, including grains (−7.2%, −8.6 to −5.6). The cereal specific declines in <italic>grains</italic> are as follows: wheat (−7.6%, −9.3 to −5.9), rice (−7.2%, −11.3 to −3.1), and barley (−6.9%, −10.5 to −3.2) (<xref ref-type="fig" rid="fig8">Figure 8</xref>). This is notable because wheat and rice alone provide over 40% of calories to humans.</p></sec></sec><sec sec-type="discussion" id="s3"><title>Discussion</title><p>The analysis of all the data shows that eCO<sub>2</sub> shifts the plant ionome toward lower mineral content; the mean change across all the 25 measured minerals is (−8%, −9.1 to −6.9) (<xref ref-type="fig" rid="fig2">Figure 2</xref>). This shift, however, is hidden from low-powered statistical tests (<xref ref-type="fig" rid="fig1">Figure 1</xref>). Attaining adequate meta-analytic power reveals that the shift is:<list list-type="order"><list-item><p>Empirically robust—evident in both artificial (chambers, greenhouses) and field (FACE) conditions (<xref ref-type="fig" rid="fig5 fig6">Figures 5 and 6</xref>).</p></list-item><list-item><p>Geographically pervasive—found in temperate and subtropical/tropical regions (<xref ref-type="fig" rid="fig7 fig8">Figures 7 and 8</xref>).</p></list-item><list-item><p>Systemic—affecting herbaceous and woody plants, crops, and wild plants, photosynthetic and edible tissues, including wheat, rice, and barley grains (<xref ref-type="fig" rid="fig3 fig4 fig8">Figures 3, 4 and 8</xref>).</p></list-item></list></p><sec id="s3-1"><title>Elevated CO<sub>2</sub> alters plant C:N:P:S stoichiometry</title><p>Not only does eCO<sub>2</sub> reduce the plant mineral content, but it also alters plant stoichiometry. Specifically, the effect of eCO<sub>2</sub> on N is nearly twice as large as its mean effect on minerals. The differential effect of eCO<sub>2</sub> on N (15%), and P (9%) and S (9%) translates into a ∼7% reduction in the plant N:P and N:S. In contrast to the lower N and mineral content, eCO<sub>2</sub> increased C content by 6% (<xref ref-type="fig" rid="fig2 fig3 fig5">Figures 2, 3 and 5</xref>). It follows then that eCO<sub>2</sub> increases C:P and C:S by 16%, and C:N by 25% confirming the previous findings of 19–27% higher C:N in plants grown in eCO<sub>2</sub> (<xref rid="bib122" ref-type="bibr">Poorter et al., 1997</xref>; <xref rid="bib150" ref-type="bibr">Stiling and Cornelissen, 2007</xref>; <xref rid="bib130" ref-type="bibr">Robinson et al., 2012</xref>).</p></sec><sec id="s3-2"><title>Data scarcity</title><p>The current dataset (available at Dryad depository) suffices to show the overall shift in the plant ionome. However, it would require much richer datasets to quantify differences among the shifts of various minerals and to assess shifts in the ionomes of individual species. Unfortunately, funding hurdles for analyzing fresh and archived samples harvested at FACE centers have significantly delayed progress in this area. Only two CO<sub>2</sub> studies report selenium (Se) content (<xref rid="bib59" ref-type="bibr">Högy et al., 2009</xref>, <xref rid="bib55" ref-type="bibr">2013</xref>), and none report data on tin (Sn), lithium (Li), and most other trace-elements. For many of the world's popular crops, pertinent data are non-existent or very limited, including (in the descending order of calories provided to the world's population, <xref rid="bib38" ref-type="bibr">FAO, 2013</xref>): maize (the top C<sub>4</sub> crop), soybeans (including oil), cassava, millet, beans, sweet potatoes, bananas, nuts, apples, yams, plantains, peas, grapes, rye, and oats.</p><p>The current data scarcity, however, should not detract our attention from what is likely to be the overarching physiological driver behind the shift in the plant ionome—the CO<sub>2</sub>-induced increase in carbohydrate production and the resulting dilution by carbohydrates. Let us take a closer look at this nutritionally important issue.</p></sec><sec id="s3-3"><title>TNC:protein and TNC:minerals respond strongly to elevated CO<sub>2</sub></title><p>Carbohydrates in plants can be divided into two types: total structural carbohydrates (TSC; e.g., cellulose or fiber) that human body cannot digest, and total non-structural carbohydrates (TNC), most of which—including starch and several sugars (fructose, glucose, sucrose, and maltose)—is readily digestible and absorbed in the human gut. Hence, for humans, TNC carries the most of caloric and metabolic load of carbohydrates. Out of the two types of carbohydrates, eCO<sub>2</sub> affects stronger the latter, boosting TNC concentration by 10–45% (<xref rid="bib150" ref-type="bibr">Stiling and Cornelissen, 2007</xref>; <xref rid="bib130" ref-type="bibr">Robinson et al., 2012</xref>). Furthermore, eCO<sub>2</sub> tends to lower protein in plant tissues (<xref rid="bib152" ref-type="bibr">Taub et al., 2008</xref>). Hence, we can reason that eCO<sub>2</sub> should exacerbate the inverse relationship found between TNC and protein (<xref rid="bib123" ref-type="bibr">Poorter and Villar, 1997</xref>). Considering that TNC and protein are two out of the three primary macronutrients (with fats/lipids being the third), it becomes imperative to quantify changes in TNC:protein, when estimating the impact of altered plant quality on human nutrition in the rising CO<sub>2</sub> world.</p><p>Regrettably, TNC:protein is rarely reported by CO<sub>2</sub> studies; instead C:N is used as a yardstick for accessing changes in the plant quality. However, C:N poorly correlates with TNC:protein because protein is more C-rich than carbohydrates (C content in protein is 52–55% cf. 40–45% in carbohydrates). Thus, a <italic>higher</italic> carbohydrate:protein results in a <italic>lower</italic> C content. This means that CO<sub>2</sub>-induced changes in nutritionally and metabolically important ratios—TNC:protein and TNC:minerals—can substantially exceed the respective changes in C:N. We can calculate changes in TNC:protein using reported changes in TNC and protein (see ‘Formula for calculating percentage changes in TNC:protein and TNC:minerals’ in ‘Materials and methods’). <xref ref-type="table" rid="tbl1">Table 1</xref> compares CO<sub>2</sub>-induced changes in C:N with respective changes in TNC:protein. It shows that eCO<sub>2</sub> can elevate TNC:protein up to fivefold higher than it does C:N.<table-wrap id="tbl1" orientation="portrait" position="float"><object-id pub-id-type="doi">10.7554/eLife.02245.012</object-id><label>Table 1.</label><caption><p>Comparing the effects of CO<sub>2</sub> on two plant quality indicators.</p><p><bold>DOI:</bold><ext-link ext-link-type="doi" xlink:href="10.7554/eLife.02245.012">http://dx.doi.org/10.7554/eLife.02245.012</ext-link></p></caption><table frame="hsides" rules="groups"><thead><tr><th rowspan="1" colspan="1">Study/species</th><th rowspan="1" colspan="1">C:N (%)</th><th rowspan="1" colspan="1">TNC:protein (%)</th><th rowspan="1" colspan="1">Reference</th></tr></thead><tbody><tr><td rowspan="1" colspan="1"><italic>Arabidopsis thaliana</italic></td><td align="char" char="." rowspan="1" colspan="1">25</td><td align="char" char="." rowspan="1" colspan="1">125</td><td rowspan="1" colspan="1"><xref rid="bib155" ref-type="bibr">Teng et al. (2006)</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Bromus erectus</italic></td><td align="char" char="." rowspan="1" colspan="1">6</td><td align="char" char="." rowspan="1" colspan="1">26</td><td rowspan="1" colspan="1"><xref rid="bib135" ref-type="bibr">Roumet et al. (1999)</xref><xref ref-type="table-fn" rid="tblfn1">*</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Dactylis glomerata</italic></td><td align="char" char="." rowspan="1" colspan="1">17</td><td align="char" char="." rowspan="1" colspan="1">53</td><td rowspan="1" colspan="1"><xref rid="bib135" ref-type="bibr">Roumet et al. (1999)</xref><xref ref-type="table-fn" rid="tblfn1">*</xref></td></tr><tr><td rowspan="1" colspan="1">wheat grain (low N)</td><td align="char" char="." rowspan="1" colspan="1">−10</td><td align="char" char="." rowspan="1" colspan="1">47</td><td rowspan="1" colspan="1"><xref rid="bib124" ref-type="bibr">Porteaus et al. (2009)</xref></td></tr><tr><td rowspan="1" colspan="1">wheat grain (high N)</td><td align="char" char="." rowspan="1" colspan="1">−18</td><td align="char" char="." rowspan="1" colspan="1">7</td><td rowspan="1" colspan="1"><xref rid="bib124" ref-type="bibr">Porteaus et al. (2009)</xref></td></tr><tr><td rowspan="1" colspan="1">wheat grain</td><td align="char" char="." rowspan="1" colspan="1">9</td><td align="char" char="." rowspan="1" colspan="1">6</td><td rowspan="1" colspan="1"><xref rid="bib59" ref-type="bibr">Högy et al. (2009)</xref></td></tr><tr><td rowspan="1" colspan="1">27 C<sub>3</sub> species</td><td align="char" char="." rowspan="1" colspan="1">28</td><td align="char" char="." rowspan="1" colspan="1">90</td><td rowspan="1" colspan="1"><xref rid="bib122" ref-type="bibr">Poorter et al. (1997)</xref></td></tr><tr><td rowspan="1" colspan="1">meta-analysis</td><td align="char" char="." rowspan="1" colspan="1">25</td><td align="char" char="." rowspan="1" colspan="1">54</td><td rowspan="1" colspan="1"><xref rid="bib130" ref-type="bibr">Robinson et al. (2012)</xref></td></tr><tr><td rowspan="1" colspan="1">meta-analysis</td><td align="char" char="." rowspan="1" colspan="1">27</td><td align="char" char="." rowspan="1" colspan="1">39</td><td rowspan="1" colspan="1"><xref rid="bib150" ref-type="bibr">Stiling and Cornelissen (2007)</xref></td></tr></tbody></table><table-wrap-foot><fn><p>CO<sub>2</sub>-induced changes (%) in C:N (a quality indicator often used in CO<sub>2</sub> studies) and in TNC:protein (a rarely used but nutritionally important indicator) for wheat grains and for foliar tissues of various plants. The results shows that in the same plant tissue, eCO<sub>2</sub> can increase TNC:protein up to several-fold > C:N. Significant CO<sub>2</sub>-induced shifts in the ratio of major macronutrients are probable. Hence, it is important for CO<sub>2</sub> studies to start accessing and reporting changes in TNC:protein.</p></fn><fn id="tblfn1"><label>*</label><p>in lieu of protein, N content is used.</p></fn></table-wrap-foot></table-wrap></p><p>How shifts in TNC:protein affect human nutrition is still unknown. New evidence, however, challenges “the notion that a calorie is a calorie from a metabolic perspective” by showing that changes in dietary carbohydrate:protein:fat ratios affect metabolism and weight gain in humans (<xref rid="bib30" ref-type="bibr">Ebbeling et al., 2012</xref>). The new evidence supports an emerging view that while obesity is quantified as an imbalance between energy inputs and expenditures (<xref rid="bib49" ref-type="bibr">Hall et al., 2011</xref>), it could also be a form of malnutrition (<xref rid="bib164" ref-type="bibr">Wells, 2013</xref>), where increased carbohydrate:protein (<xref rid="bib144" ref-type="bibr">Simpson and Raubenheimer, 2005</xref>) and excessive carbohydrate consumption (<xref rid="bib153" ref-type="bibr">Taubes, 2013</xref>) could be possible culprits.</p></sec><sec id="s3-4"><title>Absolute CO<sub>2</sub> effect on TNC. Spoonful of sugars for everyone?</title><p>The baseline TNC content in plant tissues varies widely. In grains and tubers, it is very high, 50–85% of dry mass (DM). Therefore, in these tissues a percentage increase in TNC is arithmetically limited (e.g., a 60% increase is impossible). However, even a modest percentage increase in TNC-rich tissues can be nutritionally meaningful in absolute terms. For example, the FACE study of <xref rid="bib124" ref-type="bibr">Porteaus et al. (2009)</xref> reports a 7–8% increase in starch concentrations in wheat grains, which translates to ∼4 g of additional starch per 100 g DM. In contrast to grains and tubers, the baseline TNC level in photosynthetic tissues is small (usually <25%), which makes large TNC increases possible. For example, <xref rid="bib155" ref-type="bibr">Teng et al. (2006)</xref> reports that eCO<sub>2</sub> increased TNC by 76% in leaves of <italic>Arabidopsis thaliana</italic>. What is interesting here is that in <italic>absolute</italic> terms (per 100 g DM) the ∼5 g TNC increase in <italic>Arabidopsis thaliana</italic> is comparable to the ∼4 g TNC increase in wheat grains.</p><p>More generally, CO<sub>2</sub> studies show that—irrespective of the baseline TNC content—eCO<sub>2</sub> tends to boost TNC by a few grams (1–8 g) per 100 g DM of plant tissue (<xref rid="bib122" ref-type="bibr">Poorter et al., 1997</xref>; <xref rid="bib79" ref-type="bibr">Keutgen and Chen, 2001</xref>; <xref rid="bib75" ref-type="bibr">Katny et al., 2005</xref>; <xref rid="bib33" ref-type="bibr">Erbs et al., 2010</xref>; <xref rid="bib4" ref-type="bibr">Azam et al., 2013</xref>). Note that such an infusion of carbohydrates into plant tissues, all else being equal, dilutes the content of other nutrients by ∼1–7.4%. Let us compare the dilution with its pragmatic and easily graspable analog—adding a spoonful of sugar-and-starch mixture. <xref ref-type="table" rid="tbl2">Table 2</xref> shows that the CO<sub>2</sub> effect on TNC:protein and TNC:minerals is stoichiometrically similar to the effect of adding a spoonful of carbohydrates to every 100 g DM of plant tissue.<table-wrap id="tbl2" orientation="portrait" position="float"><object-id pub-id-type="doi">10.7554/eLife.02245.013</object-id><label>Table 2.</label><caption><p>Comparing the effect of CO<sub>2</sub> to the effect of adding ‘a spoonful of sugars.’</p><p><bold>DOI:</bold><ext-link ext-link-type="doi" xlink:href="10.7554/eLife.02245.013">http://dx.doi.org/10.7554/eLife.02245.013</ext-link></p></caption><table frame="hsides" rules="groups"><thead><tr><th rowspan="1" colspan="1">Plant quality indicator</th><th rowspan="1" colspan="1">Effect of adding 5g of TNC (%)</th><th rowspan="1" colspan="1">Effect of elevated CO<sub>2</sub> (%)</th></tr></thead><tbody><tr><td rowspan="1" colspan="1"><bold>Grains and tubers:</bold></td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"></td></tr><tr><td rowspan="1" colspan="1">TNC</td><td align="char" char="." rowspan="1" colspan="1">2.6</td><td rowspan="1" colspan="1">1 to 15</td></tr><tr><td rowspan="1" colspan="1">TNC:protein</td><td align="char" char="." rowspan="1" colspan="1">7</td><td rowspan="1" colspan="1">6 to 47</td></tr><tr><td rowspan="1" colspan="1">TNC:minerals</td><td align="char" char="." rowspan="1" colspan="1">7</td><td rowspan="1" colspan="1">6 to 28</td></tr><tr><td rowspan="1" colspan="1">protein</td><td align="char" char="." rowspan="1" colspan="1">−4.8</td><td rowspan="1" colspan="1">−14 to −9</td></tr><tr><td rowspan="1" colspan="1">minerals</td><td align="char" char="." rowspan="1" colspan="1">−4.8</td><td rowspan="1" colspan="1">−10 to −5</td></tr><tr><td rowspan="1" colspan="1"><bold>Foliar tissues:</bold></td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"></td></tr><tr><td rowspan="1" colspan="1">TNC</td><td align="char" char="." rowspan="1" colspan="1">27</td><td rowspan="1" colspan="1">15 to 75</td></tr><tr><td rowspan="1" colspan="1">TNC:protein</td><td align="char" char="." rowspan="1" colspan="1">33</td><td rowspan="1" colspan="1">26 to 125</td></tr><tr><td rowspan="1" colspan="1">TNC:minerals</td><td align="char" char="." rowspan="1" colspan="1">33</td><td rowspan="1" colspan="1">24 to 98</td></tr><tr><td rowspan="1" colspan="1">protein</td><td align="char" char="." rowspan="1" colspan="1">−4.8</td><td rowspan="1" colspan="1">−19 to −14</td></tr><tr><td rowspan="1" colspan="1">minerals</td><td align="char" char="." rowspan="1" colspan="1">−4.8</td><td rowspan="1" colspan="1">−12 to −5</td></tr></tbody></table><table-wrap-foot><fn><p>Changes (%) in various plant quality indicators caused by: (1) Adding a teaspoon of TNC (∼5g of starch-and-sugars mixture) per 100g of dry mass (DM) of plant tissue, an<bold>:</bold>d (2) growing plants in twice-ambient CO<sub>2</sub> atmosphere. Changes due to the addition of TNC are calculated assuming<bold>:</bold>the baseline TNC content of 65% for grains and tubers, and 15% for foliar tissues. The C content is assumed to be ∼42% for plant tissues and TNC.</p></fn></table-wrap-foot></table-wrap></p><p>Clearly, adding a spoonful of sugar sporadically to one's diet is not a cause for concern. However, the inescapable pervasiveness of globally rising atmospheric CO<sub>2</sub> concentrations raises new questions: What are health consequences, if any, of diluting every 100 g DM of raw plant products with a spoonful of starch-and-sugar mixture? What are the consequences if the dilution is not sporadic but unavoidable and lifelong? These questions are better left for nutritionists, but it is worth noting that <xref rid="bib167" ref-type="bibr">WHO (2014)</xref> conditionally recommends that intake of free sugars not exceed 5% of total energy, which is equivalent to 5–8 teaspoons of sugar for a typical 2000–3000 kcal/day diet.</p><p>Below, I shift focus on a direct consequence of the CO<sub>2</sub>-induced increase in carbohydrate production—the mineral decline in plant tissues, and explore its potential effect on human nutrition.</p></sec><sec id="s3-5"><title>Plant minerals and ‘hidden hunger’</title><p>‘Hidden hunger’—stems from poorly diversified plant-based diets meeting caloric but not nutritional needs. It is currently the world's most widespread nutritional disorder (<xref rid="bib78" ref-type="bibr">Kennedy et al., 2003</xref>; <xref rid="bib163" ref-type="bibr">Welch and Graham, 2005</xref>). It lowers the GDP of the most afflicted countries by 2–5% and is partly responsible for their Third World status (<xref rid="bib166" ref-type="bibr">WHO, 2002</xref>; <xref rid="bib148" ref-type="bibr">Stein, 2009</xref>). A paradoxical aspect of ‘hidden hunger’ is that the minuscule amount of minerals, which a human body requires, could be provided easily and inexpensively—at least in theory—to all people in need by fortifying foods with minerals. However, in practice, such required mineral levels do not reach large parts of the world's community. The case of iodine is illustrative: although iodized table salt nearly wiped out iodine deficiency in the industrialized world, a billion people still have no regular access to it, making iodine deficiency the leading cause of preventable brain damage, cretinism, and lower IQ in children (<xref rid="bib162" ref-type="bibr">Welch and Graham, 1999</xref>; <xref rid="bib166" ref-type="bibr">WHO, 2002</xref>). Hence, the reality of logistic, economic, and cultural hurdles for fortification leaves the natural and bioavailable mineral content in food, and in plants in particular, to be the major, and sometimes the only, consistent mineral supply for a large part of mankind (<xref rid="bib165" ref-type="bibr">White and Broadley, 2009</xref>; <xref rid="bib13" ref-type="bibr">Bouis and Welch, 2010</xref>). This supply, unfortunately, is suboptimal for human nutrition with some of the consequences outlined below.</p><p>Every third person in the world is at risk of inadequate Zn intake with its deficiency substantially contributing to stunting, compromised immunity, and child mortality (<xref rid="bib14" ref-type="bibr">Brown et al., 2001</xref>; <xref rid="bib158" ref-type="bibr">UNICEF, 2009</xref>). Iron deficiency affects at least 2 billion people and is the leading cause of anemia that increases maternal mortality (<xref rid="bib166" ref-type="bibr">WHO, 2002</xref>; <xref rid="bib158" ref-type="bibr">UNICEF, 2009</xref>). Millions are Ca, Mg, and Se deficient (<xref rid="bib148" ref-type="bibr">Stein, 2009</xref>; <xref rid="bib165" ref-type="bibr">White and Broadley, 2009</xref>), including some population segments of developed countries (<xref rid="bib128" ref-type="bibr">Rayman, 2007</xref>; <xref rid="bib82" ref-type="bibr">Khokhar et al., 2012</xref>). Ironically, a person can be obese <italic>and</italic> mineral undernourished—the so called ‘hunger-obesity paradox’ (<xref rid="bib138" ref-type="bibr">Scheier, 2005</xref>), for example the many homeless in the US who rely on “cheap and energy-dense but low-nutrient” foods (<xref rid="bib84" ref-type="bibr">Koh et al., 2012</xref>). With every third adult in the world being overweight or obese (<xref rid="bib76" ref-type="bibr">Keats and Wiggins, 2014</xref>), WHO ranks both mineral undernutrition and obesity among the top 20 global health risks (<xref rid="bib166" ref-type="bibr">WHO, 2002</xref>; <xref rid="bib54" ref-type="bibr">Hill et al., 2003</xref>; <xref rid="bib148" ref-type="bibr">Stein, 2009</xref>). While the role of mineral deficiency in obesity is still unclear, intriguing links have been found between the lower blood serum concentrations of Ca, Cr, Fe, Mg, Mn, Se, Zn, and increased body mass index (BMI), with most of the findings appearing in the last decade (<xref rid="bib145" ref-type="bibr">Singh et al., 1998</xref>; <xref rid="bib96" ref-type="bibr">Martin et al., 2006</xref>; <xref rid="bib3" ref-type="bibr">Arnaud et al., 2007</xref>; <xref rid="bib46" ref-type="bibr">García et al., 2009</xref>; <xref rid="bib112" ref-type="bibr">Payahoo et al., 2013</xref>; <xref rid="bib175" ref-type="bibr">Yerlikaya et al., 2013</xref>).</p><p>How can the CO<sub>2</sub>-induced depletion of minerals in crops affect humans? I emphasize that the impact of CO<sub>2</sub>-induced shifts in the quality of crops on human health is far from settled. The purpose of what follows is not to make definitive claims but to stimulate research into this important but unresolved issue.</p></sec><sec id="s3-6"><title>Stoichiometric thought experiment</title><p>A randomized controlled trial for a human diet based exclusively (directly or indirectly) on plants grown in eCO<sub>2</sub> is unlikely and ethically questionable; and even if feasible, the trial might take years to generate results. In lieu of relevant data, we can employ a thought experiment. While such ‘experiments’ are usually reserved for physical sciences, any living system, notwithstanding its complexity, adheres to simple but irrefutable elemental mass balance, which can help us to elucidate plausible scenarios.</p><p>For simplicity, let us focus on one question: how can a 5% reduction in the plant mineral content affect human nutrition? Thus, we ignore other potential or likely CO<sub>2</sub> effects: for example higher agricultural yields; altered concentrations of lipids, vitamins, and polyphenols; substantially higher TNC:protein and TNC:minerals; differential C<sub>3</sub> and C<sub>4</sub> plant responses; changes in the phytate content that affects mineral bioavailability (<xref rid="bib95" ref-type="bibr">Manoj-Kumar, 2011</xref>); and multiplicative health effects of the concomitant declines of many minerals in the same tissue.</p><p>Suppose that starting tomorrow and without our knowledge, the baseline mineral content of all plants on Earth drops by 5%. A self-evident but easily overlooked mass-balance law tells us that neither thermal nor mechanical processing of raw plants enriches them with minerals (i.e., transmutations are impossible). Thus, the mineral decline in raw crops will follow into plant-based foods (except for a few food items that are fortified with certain minerals in some countries).</p><p>We can safely assume that the individuals, whose dietary intake of each essential mineral has exceeded the recommended dietary intake (RDI) by >5%, will be unaffected by the depletion. This leaves us with the majority of the human population, whose diet is either at risk of deficiency or already deficient in atleast one mineral (<xref rid="bib166" ref-type="bibr">WHO, 2002</xref>; <xref rid="bib78" ref-type="bibr">Kennedy et al., 2003</xref>; <xref rid="bib148" ref-type="bibr">Stein, 2009</xref>). Though a human body can synthesize complex compounds (e.g., vitamins K and D, non-essential amino acids), the mass balance low implies that <italic>no organism can synthesize any amount of any mineral</italic>. Therefore, to compensate for the mineral deficit, an organism has to increase mineral intake (or, otherwise, endure the consequences of the deficit). Taking supplements or intentionally shifting one's diet toward mineral-rich foods, for example animal products, can eliminate the deficit. Such dietary changes, however, presuppose behavioral adjustments on the part of the individuals who are aware of their mineral deficiency and have both the means and motivation to address it. A simpler way to compensate for the mineral deficit is to <italic>increase food intake</italic>, whether consciously or not. (The notion of compensatory feeding is not entirely alien—herbivores <italic>do</italic> increase consumption by 14–16%, when consuming plants grown in eCO<sub>2</sub>; <xref rid="bib150" ref-type="bibr">Stiling and Cornelissen, 2007</xref>; <xref rid="bib130" ref-type="bibr">Robinson et al., 2012</xref>).</p><p>For a calorie deficient person, eating 5% more (to be exact 5.26%, because 1.0526*.95 ≈ 1) is likely to be beneficial. However, for a calorie sufficient but mineral deficient person, eating 5% more could be detrimental. The dynamic mathematical model of human metabolism, which links weight changes to dietary and behavioral changes (<xref rid="bib49" ref-type="bibr">Hall et al., 2011</xref>), can help to quantify the effect of a prolonged 5% increase in food intake. When parameterized with anthropometric data for an average moderately active American female (age 38, height 163 cm, weight 76 kg, BMI 28.6, energy intake 2431 kcal/day [10171 kJ]) (<xref rid="bib45" ref-type="bibr">Fryar et al., 2012</xref>; <xref rid="bib21" ref-type="bibr">CIA, 2013</xref>), the model outputs a weight gain of 4.8 kg over a 3-year period, provided all other aspects of behavior and diet remain unchanged. For a male, the respective weight gain is 5.8 kg. The results are congruent with <xref rid="bib54" ref-type="bibr">Hill et al. (2003)</xref>, who argued that a 4–5% difference in total daily energy intake, a mere 100 kcal/day, could be responsible for most weight gain in the population.</p><p>The above ‘experiment’ suggests that a systemic and sustained 5% mineral depletion in plants can be nutritionally significant. While the rise in the atmospheric CO<sub>2</sub> concentration is expected to be nearly uniform around the globe, its impact on crop quality might unequally affect the human population: from no detrimental effects for the well-nourished to potential weight gain for the calorie-sufficient but mineral-undernourished.</p></sec><sec id="s3-7"><title>Has rising CO<sub>2</sub> already altered the plant ionome?</title><p>The rise in CO<sub>2</sub> levels over the last 18–30 years has already been implicated in the two effects that can influence the plant ionome: higher C assimilation and plant growth (<xref rid="bib26" ref-type="bibr">Donohue et al., 2013</xref>), and lower transpiration (<xref rid="bib77" ref-type="bibr">Keenan et al., 2013</xref>). Considering that over the last 250 years, the atmospheric CO<sub>2</sub> concentration has increased by 120 ppm—an increase that is not far from the mean 184 ppm enrichment in the FACE studies—it is plausible that plant quality has changed. Indeed, declines in mineral concentrations have been found in wild plants and in crop fruits, vegetables, and grains over 22–250 years (<xref rid="bib116" ref-type="bibr">Penuelas and Matamala, 1993</xref>; <xref rid="bib28" ref-type="bibr">Duquesnay et al., 2000</xref>; <xref rid="bib24" ref-type="bibr">Davis et al., 2004</xref>; <xref rid="bib32" ref-type="bibr">Ekholm et al., 2007</xref>; <xref rid="bib34" ref-type="bibr">Fan et al., 2008</xref>; <xref rid="bib73" ref-type="bibr">Jonard et al., 2009</xref>). While the mineral declines in crops can be an unintended consequence of the Green Revolution that produced high-yield cultivars with altered mineral content (<xref rid="bib24" ref-type="bibr">Davis et al., 2004</xref>; <xref rid="bib34" ref-type="bibr">Fan et al., 2008</xref>), the reason for the mineral declines in wild plants cannot be attributed to it.</p><p>Can eCO<sub>2</sub> directly affect human health? <xref rid="bib53" ref-type="bibr">Hersoug et al. (2012)</xref> proposed that rising CO<sub>2</sub> promotes weight gains and obesity in the human population directly (via breathing) by reducing the pH of blood and, consequently, increasing appetite and energy intake. Weight gain has been observed in wild mammals, lab animals, and humans over the last several decades (<xref rid="bib83" ref-type="bibr">Klimentidis et al., 2011</xref>). However, it is not clear what role, if any, the rising CO<sub>2</sub> could have played either directly (breathing) or indirectly (altered plant quality). And disentangling the rising CO<sub>2</sub> effect from other plausible factors currently does not seem feasible due to scarce data. This brings us to the broader issue of detecting—amid high local noise—signals that are small in their magnitude but global in their scope.</p></sec><sec id="s3-8"><title>Hidden shifts of global change</title><p>While some scientific areas (e.g., genomics, bioinformatics) have experienced a data deluge, many areas of global change, including the issue of shifting plant quality, have been hindered by chronic data scarcity. Fortunately, researchers worldwide have been steadily generating data on the effects of eCO<sub>2</sub> on the chemical composition of plants. It is their collective efforts that have made it possible to reveal the CO<sub>2</sub>-induced shift in the plant ionome.</p><p>Human activities profoundly alter the biogeochemical cycle not only of C but also of N, P, and S, which are central to all known life forms. It is plausible that other subtle global shifts in the physiology and functioning of organisms lurk amid highly noisy data. The small magnitude of such shifts makes them hard to detect and easy to dismiss. But by virtue of being global and sustained, the shifts can be biologically potent. Revealing hidden shifts requires plentiful data to attain sufficient statistical power. (For example, <xref rid="bib133" ref-type="bibr">Rohde et al. (2013)</xref> analyzed 14 million <italic>mean</italic> monthly local temperature records to uncover the 1.5°C rise in the global average temperature since 1753—undoubtedly a potent but a very small change relative to the variations of tens of degrees in local temperature.)</p><p>New data on the effects of eCO<sub>2</sub> on plant quality (e.g., minerals, TNC: protein, TNC:minerals, lipids, bioavailability of nutrients) can be generated very cost-efficiently by analyzing fresh and archived plant samples collected at FACE centers worldwide (the project leaders of many centers are keen to share such samples; PS Curtis, BA Kimball, R Oren, PB Reich, C Stokes; IL personal communication, July, 2006). With regard to minerals, the application of the high-throughput techniques of ionomics (<xref rid="bib136" ref-type="bibr">Salt et al., 2008</xref>) can generate rich phenotypic data that can be linked with functional genomics. Such analyses will shed more light on changes in plant quality in the rising CO<sub>2</sub> world. Anticipating and assessing such changes will help not only in mitigating their effects but also in steering efforts to breed nutritionally richer crops for the improvement of human health worldwide.</p></sec></sec><sec sec-type="materials|methods" id="s4"><title>Materials and methods</title><sec id="s4-1"><title>Search for data</title><p>I searched Google Scholar, Google, PubMed, the ISI Web of Science, AGRICOLA, and Scopus to find relevant articles with sensible combinations of two or more of the following search-words: elevated, rising, CO<sub>2</sub>, carbon dioxide, ppm, FACE, effects, content, concentration, %, mg, dry matter, micronutrients, plant(s), crop(s), tree(s), C<sub>3</sub>, C<sub>4</sub>, foliar, leaves, grains, seeds, tubers, fruits, minerals, chemical elements, and names/symbols of various chemical elements (e.g., zinc/Zn). I found additional studies from references in the articles identified in the initial searches.</p></sec><sec id="s4-2"><title>Study suitability and data selection criteria</title><p>Among all plant tissues for which mineral concentrations are reported in the literature, the most abundant data are on foliar tissues (leaves, needles, shoots), and—for herbaceous plants—on above ground parts. Hence, focusing on the foliar tissues and above ground parts allows one to maximize the number of <italic>independent</italic> observations of the effect of eCO<sub>2</sub> on each mineral. Although the data on edible parts of crops are scarcer, a dataset on crop edible tissues was compiled due to their direct relevance for human nutrition.</p><p>The following objective and uniform criteria were applied for deciding which studies to include into the dataset: (1) a study grew plants at two or more CO<sub>2</sub> levels, (2) a study directly measured the content of one or more minerals in foliar or edible plant tissues at low (ambient) and high (elevated) CO<sub>2</sub> levels, and (3) a study reported either absolute concentrations at each treatment or relative change/lack thereof in the concentrations for each mineral between treatments. Studies that indirectly deduced mineral concentrations, reported data on N but not on any mineral, exposed only a part (e.g., a branch) of the plant, used super-elevated or uncontrolled CO<sub>2</sub> levels were not included. <xref ref-type="table" rid="tbl3">Table 3</xref> lists all the studies together with their respective species/cultivars and CO<sub>2</sub> enrichment levels (the dataset with all the details is deposited at Dryad and GitHub). When a study reported the low CO<sub>2</sub> level as ‘ambient’ with no specific numerical values, then I used the Keeling curve to approximate the ambient CO<sub>2</sub> level for the year the study was carried out.<table-wrap id="tbl3" orientation="portrait" position="float"><object-id pub-id-type="doi">10.7554/eLife.02245.014</object-id><label>Table 3.</label><caption><p>Studies covered in the meta-analysis of CO<sub>2</sub> effects on the plant ionome.</p><p><bold>DOI:</bold><ext-link ext-link-type="doi" xlink:href="10.7554/eLife.02245.014">http://dx.doi.org/10.7554/eLife.02245.014</ext-link></p></caption><table frame="hsides" rules="groups"><thead><tr><th rowspan="1" colspan="1">Species</th><th rowspan="1" colspan="1">Common name</th><th rowspan="1" colspan="1">Crop</th><th rowspan="1" colspan="1">+CO2</th><th rowspan="1" colspan="1">Country</th><th rowspan="1" colspan="1">Reference</th></tr></thead><tbody><tr><td rowspan="1" colspan="1"><italic>Acer pseudoplatanus</italic></td><td rowspan="1" colspan="1">maple tree</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">260</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib108" ref-type="bibr">Overdieck, 1993</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Acer rubrum</italic></td><td rowspan="1" colspan="1">red maple tree</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">200</td><td rowspan="1" colspan="1">USA</td><td rowspan="1" colspan="1"><xref rid="bib44" ref-type="bibr">Finzi et al., 2001</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Agrostis capillaris</italic></td><td rowspan="1" colspan="1">grass</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">340</td><td rowspan="1" colspan="1">UK</td><td rowspan="1" colspan="1"><xref rid="bib8" ref-type="bibr">Baxter et al., 1994</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Agrostis capillaris</italic></td><td rowspan="1" colspan="1">grass</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">250</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib102" ref-type="bibr">Newbery et al., 1995</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Alnus glutinosa</italic></td><td rowspan="1" colspan="1">alder tree</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">350</td><td rowspan="1" colspan="1">UK</td><td rowspan="1" colspan="1"><xref rid="bib154" ref-type="bibr">Temperton et al., 2003</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Alphitonia petriei</italic></td><td rowspan="1" colspan="1">rainforest tree</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">440</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib74" ref-type="bibr">Kanowski, 2001</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Ambrosia dumosa</italic></td><td rowspan="1" colspan="1">shrub</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">180</td><td rowspan="1" colspan="1">USA</td><td rowspan="1" colspan="1"><xref rid="bib60" ref-type="bibr">Housman et al., 2012</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Arabidopsis thaliana</italic></td><td rowspan="1" colspan="1">thale cress</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">450</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib104" ref-type="bibr">Niu et al., 2013</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Arabidopsis thaliana</italic></td><td rowspan="1" colspan="1">thale cress</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">330</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib155" ref-type="bibr">Teng et al., 2006</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Betula pendula</italic> 'Roth'</td><td rowspan="1" colspan="1">birch tree</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">349</td><td rowspan="1" colspan="1">Finland</td><td rowspan="1" colspan="1"><xref rid="bib107" ref-type="bibr">Oksanen et al., 2005</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Bouteloua curtipendula</italic></td><td rowspan="1" colspan="1">grass</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">230</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib121" ref-type="bibr">Polley et al., 2011</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Bromus tectorum</italic></td><td rowspan="1" colspan="1">cheatgrass</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">150</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib11" ref-type="bibr">Blank et al., 2006</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Bromus tectorum</italic></td><td rowspan="1" colspan="1">cheatgrass</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">150</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib9" ref-type="bibr">Blank et al., 2011</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Calluna vulgaris</italic></td><td rowspan="1" colspan="1">heather shrub</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">200</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib169" ref-type="bibr">Woodin et al., 1992</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Cercis canadensis</italic></td><td rowspan="1" colspan="1">red bud tree</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">200</td><td rowspan="1" colspan="1">USA</td><td rowspan="1" colspan="1"><xref rid="bib44" ref-type="bibr">Finzi et al., 2001</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Chrysanthemum morifolium</italic></td><td rowspan="1" colspan="1">chrysanth</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">325</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib85" ref-type="bibr">Kuehny et al., 1991</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Cornus florida</italic></td><td rowspan="1" colspan="1">dogwood tree</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">200</td><td rowspan="1" colspan="1">USA</td><td rowspan="1" colspan="1"><xref rid="bib44" ref-type="bibr">Finzi et al., 2001</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Fagus sylvatica</italic></td><td rowspan="1" colspan="1">beech tree</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">260</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib108" ref-type="bibr">Overdieck, 1993</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Fagus sylvatica</italic></td><td rowspan="1" colspan="1">beech tree</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">300</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib131" ref-type="bibr">Rodenkirchen et al., 2009</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Festuca pratensis</italic></td><td rowspan="1" colspan="1">meadow fescue</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">320</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib108" ref-type="bibr">Overdieck, 1993</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Festuca vivipara</italic></td><td rowspan="1" colspan="1">grass</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">340</td><td rowspan="1" colspan="1">UK</td><td rowspan="1" colspan="1"><xref rid="bib8" ref-type="bibr">Baxter et al., 1994</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Flindersia brayleyana</italic></td><td rowspan="1" colspan="1">rainforest tree</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">440</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib74" ref-type="bibr">Kanowski, 2001</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Galactia elliottii</italic></td><td rowspan="1" colspan="1">Elliott's milkpea</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">325</td><td rowspan="1" colspan="1">USA</td><td rowspan="1" colspan="1"><xref rid="bib62" ref-type="bibr">Hungate et al., 2004</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Larix kaempferi</italic></td><td rowspan="1" colspan="1">larch tree</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">335</td><td rowspan="1" colspan="1">Japan</td><td rowspan="1" colspan="1"><xref rid="bib141" ref-type="bibr">Shinano et al., 2007</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Lepidium latifolium</italic></td><td rowspan="1" colspan="1">peppergrass</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">339</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib10" ref-type="bibr">Blank and Derner, 2004</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Liquidambar styraciflua</italic></td><td rowspan="1" colspan="1">sweetgum tree</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">200</td><td rowspan="1" colspan="1">USA</td><td rowspan="1" colspan="1"><xref rid="bib44" ref-type="bibr">Finzi et al., 2001</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Liquidambar styraciflua</italic></td><td rowspan="1" colspan="1">sweetgum tree</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">167</td><td rowspan="1" colspan="1">USA</td><td rowspan="1" colspan="1"><xref rid="bib71" ref-type="bibr">Johnson et al., 2004</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Liquidambar styraciflua</italic></td><td rowspan="1" colspan="1">sweetgum tree</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">156–200</td><td rowspan="1" colspan="1">USA</td><td rowspan="1" colspan="1"><xref rid="bib101" ref-type="bibr">Natali et al., 2009</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Liriodendron tulipifera</italic></td><td rowspan="1" colspan="1">tulip tree</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">325</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib106" ref-type="bibr">O’Neill et al., 1987</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Lolium perenne</italic></td><td rowspan="1" colspan="1">grass</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">320</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib108" ref-type="bibr">Overdieck, 1993</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Lolium perenne</italic></td><td rowspan="1" colspan="1">grass</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">290</td><td rowspan="1" colspan="1">Germany</td><td rowspan="1" colspan="1"><xref rid="bib139" ref-type="bibr">Schenk et al., 1997</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Lupinus albus</italic></td><td rowspan="1" colspan="1">white lupin</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">550</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib16" ref-type="bibr">Campbell and Sage, 2002</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Lycium pallidum</italic></td><td rowspan="1" colspan="1">shrub</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">180</td><td rowspan="1" colspan="1">USA</td><td rowspan="1" colspan="1"><xref rid="bib60" ref-type="bibr">Housman et al., 2012</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Nephrolepis exaltata</italic></td><td rowspan="1" colspan="1">fern</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">650</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib105" ref-type="bibr">Nowak et al., 2002</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Pelargonium x hortorum</italic> 'Maverick White'</td><td rowspan="1" colspan="1">geranium</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">330</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib99" ref-type="bibr">Mishra et al., 2011</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Picea abies</italic> 'Karst.'</td><td rowspan="1" colspan="1">spruce tree</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">350</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib118" ref-type="bibr">Pfirrmann et al., 1996</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Picea abies</italic> 'Karst.'</td><td rowspan="1" colspan="1">spruce tree</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">300</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib131" ref-type="bibr">Rodenkirchen et al., 2009</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Picea abies</italic> 'Karst.'</td><td rowspan="1" colspan="1">spruce tree</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">300</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib161" ref-type="bibr">Weigt et al., 2011</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Picea rubens</italic></td><td rowspan="1" colspan="1">spruce tree</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">350</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib142" ref-type="bibr">Shipley et al., 1992</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Pinus ponderosa</italic></td><td rowspan="1" colspan="1">pine tree</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">346</td><td rowspan="1" colspan="1">USA</td><td rowspan="1" colspan="1"><xref rid="bib160" ref-type="bibr">Walker et al., 2000</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Pinus ponderosa</italic> 'Laws.'</td><td rowspan="1" colspan="1">pine tree</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">350</td><td rowspan="1" colspan="1">USA</td><td rowspan="1" colspan="1"><xref rid="bib70" ref-type="bibr">Johnson et al., 1997</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Pinus sylvestris</italic></td><td rowspan="1" colspan="1">pine tree</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">331</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib92" ref-type="bibr">Luomala et al., 2005</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Pinus sylvestris</italic></td><td rowspan="1" colspan="1">pine tree</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">225</td><td rowspan="1" colspan="1">Finland</td><td rowspan="1" colspan="1"><xref rid="bib159" ref-type="bibr">Utriainen et al., 2000</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Pinus taeda</italic></td><td rowspan="1" colspan="1">loblolly pine tree</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">200</td><td rowspan="1" colspan="1">USA</td><td rowspan="1" colspan="1"><xref rid="bib44" ref-type="bibr">Finzi et al., 2001</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Pinus taeda</italic></td><td rowspan="1" colspan="1">pine tree</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">200</td><td rowspan="1" colspan="1">USA</td><td rowspan="1" colspan="1"><xref rid="bib101" ref-type="bibr">Natali et al., 2009</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Poa alpina</italic></td><td rowspan="1" colspan="1">grass</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">340</td><td rowspan="1" colspan="1">UK</td><td rowspan="1" colspan="1"><xref rid="bib8" ref-type="bibr">Baxter et al., 1994</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Poa alpina</italic></td><td rowspan="1" colspan="1">grass</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">340</td><td rowspan="1" colspan="1">UK</td><td rowspan="1" colspan="1"><xref rid="bib7" ref-type="bibr">Baxter et al., 1997</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Pteridium aquilinum</italic></td><td rowspan="1" colspan="1">fern</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">320</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib176" ref-type="bibr">Zheng et al., 2008</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Pteridium revolutum</italic></td><td rowspan="1" colspan="1">fern</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">320</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib176" ref-type="bibr">Zheng et al., 2008</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Pteris vittata</italic></td><td rowspan="1" colspan="1">fern</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">320</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib176" ref-type="bibr">Zheng et al., 2008</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Quercus chapmanii</italic></td><td rowspan="1" colspan="1">oak tree</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">350</td><td rowspan="1" colspan="1">USA</td><td rowspan="1" colspan="1"><xref rid="bib101" ref-type="bibr">Natali et al., 2009</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Quercus geminata</italic></td><td rowspan="1" colspan="1">oak tree</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">350</td><td rowspan="1" colspan="1">USA</td><td rowspan="1" colspan="1"><xref rid="bib72" ref-type="bibr">Johnson et al., 2003</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Quercus geminata</italic></td><td rowspan="1" colspan="1">oak tree</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">350</td><td rowspan="1" colspan="1">USA</td><td rowspan="1" colspan="1"><xref rid="bib101" ref-type="bibr">Natali et al., 2009</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Quercus myrtifolia</italic></td><td rowspan="1" colspan="1">oak tree</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">350</td><td rowspan="1" colspan="1">USA</td><td rowspan="1" colspan="1"><xref rid="bib72" ref-type="bibr">Johnson et al., 2003</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Quercus myrtifolia</italic></td><td rowspan="1" colspan="1">oak tree</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">350</td><td rowspan="1" colspan="1">USA</td><td rowspan="1" colspan="1"><xref rid="bib101" ref-type="bibr">Natali et al., 2009</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Quercus suber</italic></td><td rowspan="1" colspan="1">cork oak tree</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">350</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib103" ref-type="bibr">Niinemets et al., 1999</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Schizachyrium scoparium</italic></td><td rowspan="1" colspan="1">grass</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">230</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib121" ref-type="bibr">Polley et al., 2011</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Sorghastrum nutans</italic></td><td rowspan="1" colspan="1">grass</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">230</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib121" ref-type="bibr">Polley et al., 2011</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Sporobolus kentrophyllus</italic></td><td rowspan="1" colspan="1">grass</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">330</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib168" ref-type="bibr">Wilsey et al., 1994</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Trifolium alexandrinum</italic> 'Pusa Jayant'</td><td rowspan="1" colspan="1">berseem clover</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">250</td><td rowspan="1" colspan="1">India</td><td rowspan="1" colspan="1"><xref rid="bib109" ref-type="bibr">Pal et al., 2004</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Trifolium pratense</italic></td><td rowspan="1" colspan="1">red clover</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">320</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib108" ref-type="bibr">Overdieck, 1993</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Trifolium repens</italic></td><td rowspan="1" colspan="1">white clover</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">320</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib108" ref-type="bibr">Overdieck, 1993</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Trifolium repens</italic></td><td rowspan="1" colspan="1">white clover</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">290</td><td rowspan="1" colspan="1">Germany</td><td rowspan="1" colspan="1"><xref rid="bib139" ref-type="bibr">Schenk et al., 1997</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Trifolium repens</italic></td><td rowspan="1" colspan="1">white clover</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">615</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib156" ref-type="bibr">Tian et al., 2014</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Trifolium repens</italic> 'Regal'</td><td rowspan="1" colspan="1">white clover</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">330</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib51" ref-type="bibr">Heagle et al., 1993</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Vallisneria spinulosa</italic></td><td rowspan="1" colspan="1">macrophyte</td><td rowspan="1" colspan="1">No</td><td align="char" char="." rowspan="1" colspan="1">610</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib173" ref-type="bibr">Yan et al., 2006</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Apium graveolens</italic></td><td rowspan="1" colspan="1">celery</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">670</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib157" ref-type="bibr">Tremblay et al., 1988</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Brassica juncea</italic> 'Czern'</td><td rowspan="1" colspan="1">mustard</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">500</td><td rowspan="1" colspan="1">India</td><td rowspan="1" colspan="1"><xref rid="bib146" ref-type="bibr">Singh et al., 2013</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Brassica napus</italic> 'Qinyou 8'</td><td rowspan="1" colspan="1">rapeseed</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">615</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib156" ref-type="bibr">Tian et al., 2014</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Brassica napus</italic> 'Rongyou 10'</td><td rowspan="1" colspan="1">rapeseed</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">615</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib156" ref-type="bibr">Tian et al., 2014</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Brassica napus</italic> 'Zhongyouza 12'</td><td rowspan="1" colspan="1">rapeseed</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">615</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib156" ref-type="bibr">Tian et al., 2014</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Brassica napus</italic> 'Campino'</td><td rowspan="1" colspan="1">oilseed rape</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">106</td><td rowspan="1" colspan="1">Germany</td><td rowspan="1" colspan="1"><xref rid="bib57" ref-type="bibr">Högy et al., 2010</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Brassica rapa</italic> 'Grabe'</td><td rowspan="1" colspan="1">turnip</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">600</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib4" ref-type="bibr">Azam et al., 2013</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Citrus aurantium</italic></td><td rowspan="1" colspan="1">orange tree</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">300</td><td rowspan="1" colspan="1">USA</td><td rowspan="1" colspan="1"><xref rid="bib115" ref-type="bibr">Penuelas et al., 1997</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Citrus madurensis</italic></td><td rowspan="1" colspan="1">citrus tree</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">600</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib79" ref-type="bibr">Keutgen and Chen, 2001</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Cucumis sativus</italic></td><td rowspan="1" colspan="1">cucumber</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">650</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib113" ref-type="bibr">Peet et al., 1986</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Daucus carota</italic> 'T-1-111'</td><td rowspan="1" colspan="1">carrot</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">600</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib4" ref-type="bibr">Azam et al., 2013</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Fragaria x ananassa</italic></td><td rowspan="1" colspan="1">strawberry</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">600</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib80" ref-type="bibr">Keutgen et al., 1997</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Glycine max</italic> 'Merr.'</td><td rowspan="1" colspan="1">soybean</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">360</td><td rowspan="1" colspan="1">USA</td><td rowspan="1" colspan="1"><xref rid="bib126" ref-type="bibr">Prior et al., 2008</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Glycine max</italic> 'Merr.'</td><td rowspan="1" colspan="1">soybean</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">200</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib132" ref-type="bibr">Rodriguez et al., 2011</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Gossypium hirsutum</italic> 'Deltapine 77'</td><td rowspan="1" colspan="1">cotton</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">180</td><td rowspan="1" colspan="1">USA</td><td rowspan="1" colspan="1"><xref rid="bib61" ref-type="bibr">Huluka et al., 1994</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Hordeum vulgare</italic></td><td rowspan="1" colspan="1">barley</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">175</td><td rowspan="1" colspan="1">Germany</td><td rowspan="1" colspan="1"><xref rid="bib33" ref-type="bibr">Erbs et al., 2010</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Hordeum vulgare</italic> 'Alexis'</td><td rowspan="1" colspan="1">barley</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">334</td><td rowspan="1" colspan="1">Germany</td><td rowspan="1" colspan="1"><xref rid="bib94" ref-type="bibr">Manderscheid et al., 1995</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Hordeum vulgare</italic> 'Arena'</td><td rowspan="1" colspan="1">barley</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">334</td><td rowspan="1" colspan="1">Germany</td><td rowspan="1" colspan="1"><xref rid="bib94" ref-type="bibr">Manderscheid et al., 1995</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Hordeum vulgare</italic> 'Europa'</td><td rowspan="1" colspan="1">barley</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">400</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib48" ref-type="bibr">Haase et al., 2008</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Hordeum vulgare</italic> 'Iranis'</td><td rowspan="1" colspan="1">barley</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">350</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib117" ref-type="bibr">Pérez-López et al., 2014</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Hordeum vulgare</italic> 'Theresa'</td><td rowspan="1" colspan="1">barley</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">170</td><td rowspan="1" colspan="1">Germany</td><td rowspan="1" colspan="1"><xref rid="bib170" ref-type="bibr">Wroblewitz et al., 2013</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Lactuca sativa</italic> 'BRM'</td><td rowspan="1" colspan="1">lettuce</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">308</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib6" ref-type="bibr">Baslam et al., 2012</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Lactuca sativa</italic> 'Mantilla'</td><td rowspan="1" colspan="1">lettuce</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">350</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib20" ref-type="bibr">Chagvardieff et al., 1994</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Lactuca sativa</italic> 'MV'</td><td rowspan="1" colspan="1">lettuce</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">308</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib6" ref-type="bibr">Baslam et al., 2012</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Lactuca sativa</italic> 'Waldmann's Green'</td><td rowspan="1" colspan="1">lettuce</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">600</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib98" ref-type="bibr">McKeehen et al., 1996</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Lycopersicon esculentum</italic> 'Astra'</td><td rowspan="1" colspan="1">tomato</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">600</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib81" ref-type="bibr">Khan et al., 2013</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Lycopersicon esculentum</italic> 'Eureka'</td><td rowspan="1" colspan="1">tomato</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">600</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib81" ref-type="bibr">Khan et al., 2013</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Lycopersicon esculentum</italic> 'Mill.'</td><td rowspan="1" colspan="1">tomato</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">360</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib88" ref-type="bibr">Li et al., 2007</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Lycopersicon esculentum</italic> 'Zheza 809'</td><td rowspan="1" colspan="1">tomato</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">450</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib69" ref-type="bibr">Jin et al., 2009</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Mangifera indica</italic> 'Kensington'</td><td rowspan="1" colspan="1">mango tree</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">350</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib137" ref-type="bibr">Schaffer and Whiley, 1997</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Mangifera indica</italic> 'Tommy Atkins'</td><td rowspan="1" colspan="1">mango tree</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">350</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib137" ref-type="bibr">Schaffer and Whiley, 1997</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Medicago sativa</italic></td><td rowspan="1" colspan="1">alfalfa</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">615</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib156" ref-type="bibr">Tian et al., 2014</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Medicago sativa</italic> 'Victor'</td><td rowspan="1" colspan="1">alfalfa</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">100</td><td rowspan="1" colspan="1">UK</td><td rowspan="1" colspan="1"><xref rid="bib2" ref-type="bibr">Al-Rawahy et al., 2013</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Oryza sativa</italic></td><td rowspan="1" colspan="1">rice</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">200</td><td rowspan="1" colspan="1">China</td><td rowspan="1" colspan="1"><xref rid="bib111" ref-type="bibr">Pang et al., 2005</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Oryza sativa</italic> 'Akitakomachi'</td><td rowspan="1" colspan="1">rice</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">205–260</td><td rowspan="1" colspan="1">Japan</td><td rowspan="1" colspan="1"><xref rid="bib90" ref-type="bibr">Lieffering et al., 2004</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Oryza sativa</italic> 'Akitakomachi'</td><td rowspan="1" colspan="1">rice</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">250</td><td rowspan="1" colspan="1">Japan</td><td rowspan="1" colspan="1"><xref rid="bib172" ref-type="bibr">Yamakawa et al., 2004</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Oryza sativa</italic> 'BRRIdhan 39'</td><td rowspan="1" colspan="1">rice</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">210</td><td rowspan="1" colspan="1">Bangladesh</td><td rowspan="1" colspan="1"><xref rid="bib129" ref-type="bibr">Razzaque et al., 2009</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Oryza sativa</italic> 'Gui Nnong Zhan'</td><td rowspan="1" colspan="1">rice</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">500</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib89" ref-type="bibr">Li et al., 2010</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Oryza sativa</italic> 'IR 72'</td><td rowspan="1" colspan="1">rice</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">296</td><td rowspan="1" colspan="1">Philippines</td><td rowspan="1" colspan="1"><xref rid="bib177" ref-type="bibr">Ziska et al., 1997</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Oryza sativa</italic> 'Japonica'</td><td rowspan="1" colspan="1">rice</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">200</td><td rowspan="1" colspan="1">China</td><td rowspan="1" colspan="1"><xref rid="bib68" ref-type="bibr">Jia et al., 2007</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Oryza sativa</italic> 'Jarrah'</td><td rowspan="1" colspan="1">rice</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">350</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib140" ref-type="bibr">Seneweera and Conroy, 1997</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Oryza sativa</italic> 'Khaskani'</td><td rowspan="1" colspan="1">rice</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">210</td><td rowspan="1" colspan="1">Bangladesh</td><td rowspan="1" colspan="1"><xref rid="bib129" ref-type="bibr">Razzaque et al., 2009</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Oryza sativa</italic> 'Rong You 398'</td><td rowspan="1" colspan="1">rice</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">500</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib89" ref-type="bibr">Li et al., 2010</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Oryza sativa</italic> 'Shakkorkhora'</td><td rowspan="1" colspan="1">rice</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">210</td><td rowspan="1" colspan="1">Bangladesh</td><td rowspan="1" colspan="1"><xref rid="bib129" ref-type="bibr">Razzaque et al., 2009</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Oryza sativa</italic> 'Shan You 428'</td><td rowspan="1" colspan="1">rice</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">500</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib89" ref-type="bibr">Li et al., 2010</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Oryza sativa</italic> 'Tian You 390'</td><td rowspan="1" colspan="1">rice</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">500</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib89" ref-type="bibr">Li et al., 2010</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Oryza sativa</italic> 'Wu Xiang jing'</td><td rowspan="1" colspan="1">rice</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">200</td><td rowspan="1" colspan="1">China</td><td rowspan="1" colspan="1"><xref rid="bib47" ref-type="bibr">Guo et al., 2011</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Oryza sativa</italic> 'Wuxiangjing 14'</td><td rowspan="1" colspan="1">rice</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">200</td><td rowspan="1" colspan="1">China</td><td rowspan="1" colspan="1"><xref rid="bib93" ref-type="bibr">Ma et al., 2007</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Oryza sativa</italic> 'Wuxiangjing 14'</td><td rowspan="1" colspan="1">rice</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">200</td><td rowspan="1" colspan="1">China</td><td rowspan="1" colspan="1"><xref rid="bib174" ref-type="bibr">Yang et al., 2007</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Oryza sativa</italic> 'Yin Jing Ruan Zhan'</td><td rowspan="1" colspan="1">rice</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">500</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib89" ref-type="bibr">Li et al., 2010</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Oryza sativa</italic> 'Yue Za 889'</td><td rowspan="1" colspan="1">rice</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">500</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib89" ref-type="bibr">Li et al., 2010</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Phaseolus vulgaris</italic> 'Contender'</td><td rowspan="1" colspan="1">bean</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">340</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib100" ref-type="bibr">Mjwara et al., 1996</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Phaseolus vulgaris</italic> 'Seafarer'</td><td rowspan="1" colspan="1">bean</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">870</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib125" ref-type="bibr">Porter and Grodzinski, 1984</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Raphanus sativus</italic> 'Mino'</td><td rowspan="1" colspan="1">radish</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">600</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib4" ref-type="bibr">Azam et al., 2013</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Raphanus sativus</italic> 'Cherry Belle'</td><td rowspan="1" colspan="1">radish</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">380</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib5" ref-type="bibr">Barnes and Pfirrmann, 1992</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Raphanus sativus</italic> 'Giant White Globe'</td><td rowspan="1" colspan="1">radish</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">600</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib98" ref-type="bibr">McKeehen et al., 1996</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Rumex patientia x R. Tianschanicus</italic> 'Rumex K-1'</td><td rowspan="1" colspan="1">buckwheat</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">615</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib156" ref-type="bibr">Tian et al., 2014</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Secale cereale</italic> 'Wintergrazer-70'</td><td rowspan="1" colspan="1">rye</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">615</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib156" ref-type="bibr">Tian et al., 2014</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Solanum lycopersicum</italic> '76R MYC+'</td><td rowspan="1" colspan="1">tomato</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">590</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib19" ref-type="bibr">Cavagnaro et al., 2007</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Solanum lycopersicum</italic> 'rmc'</td><td rowspan="1" colspan="1">tomato</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">590</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib19" ref-type="bibr">Cavagnaro et al., 2007</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Solanum tuberosum</italic></td><td rowspan="1" colspan="1">potato</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">500</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib17" ref-type="bibr">Cao and Tibbitts, 1997</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Solanum tuberosum</italic> 'Bintje'</td><td rowspan="1" colspan="1">potato</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">170</td><td rowspan="1" colspan="1">Germany</td><td rowspan="1" colspan="1"><xref rid="bib56" ref-type="bibr">Högy and Fangmeier, 2009</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Solanum tuberosum</italic> 'Bintje'</td><td rowspan="1" colspan="1">potato</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">278-281</td><td rowspan="1" colspan="1">Sweden</td><td rowspan="1" colspan="1"><xref rid="bib119" ref-type="bibr">Piikki et al., 2007</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Solanum tuberosum</italic> 'Bintje'</td><td rowspan="1" colspan="1">potato</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">305-320</td><td rowspan="1" colspan="1">Europe</td><td rowspan="1" colspan="1"><xref rid="bib35" ref-type="bibr">Fangmeier et al., 2002</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Solanum tuberosum</italic> 'Dark Red Norland'</td><td rowspan="1" colspan="1">potato</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">345</td><td rowspan="1" colspan="1">USA</td><td rowspan="1" colspan="1"><xref rid="bib50" ref-type="bibr">Heagle et al., 2003</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Solanum tuberosum</italic> 'Superior'</td><td rowspan="1" colspan="1">potato</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">345</td><td rowspan="1" colspan="1">USA</td><td rowspan="1" colspan="1"><xref rid="bib50" ref-type="bibr">Heagle et al., 2003</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Sorghum bicolor</italic></td><td rowspan="1" colspan="1">sorghum</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">360</td><td rowspan="1" colspan="1">USA</td><td rowspan="1" colspan="1"><xref rid="bib126" ref-type="bibr">Prior et al., 2008</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Spinacia oleracea</italic></td><td rowspan="1" colspan="1">spinach</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">250</td><td rowspan="1" colspan="1">India</td><td rowspan="1" colspan="1"><xref rid="bib67" ref-type="bibr">Jain et al., 2007</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Trigonella foenum-graecum</italic></td><td rowspan="1" colspan="1">fenugreek</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">250</td><td rowspan="1" colspan="1">India</td><td rowspan="1" colspan="1"><xref rid="bib67" ref-type="bibr">Jain et al., 2007</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Triticum aestivum</italic></td><td rowspan="1" colspan="1">wheat</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">175</td><td rowspan="1" colspan="1">Germany</td><td rowspan="1" colspan="1"><xref rid="bib33" ref-type="bibr">Erbs et al., 2010</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Triticum aestivum</italic> 'Ningmai 9'</td><td rowspan="1" colspan="1">wheat</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">200</td><td rowspan="1" colspan="1">China</td><td rowspan="1" colspan="1"><xref rid="bib93" ref-type="bibr">Ma et al., 2007</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Triticum aestivum</italic> 'Triso'</td><td rowspan="1" colspan="1">wheat</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">150</td><td rowspan="1" colspan="1">Germany</td><td rowspan="1" colspan="1"><xref rid="bib59" ref-type="bibr">Högy et al., 2009</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Triticum aestivum</italic> 'Triso'</td><td rowspan="1" colspan="1">wheat</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">150</td><td rowspan="1" colspan="1">Germany</td><td rowspan="1" colspan="1"><xref rid="bib55" ref-type="bibr">Högy et al., 2013</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Triticum aestivum</italic> 'Alcazar'</td><td rowspan="1" colspan="1">wheat</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">350</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib25" ref-type="bibr">de la Puente et al., 2000</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Triticum aestivum</italic> 'Batis'</td><td rowspan="1" colspan="1">wheat</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">170</td><td rowspan="1" colspan="1">Germany</td><td rowspan="1" colspan="1"><xref rid="bib170" ref-type="bibr">Wroblewitz et al., 2013</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Triticum aestivum</italic> 'Dragon'</td><td rowspan="1" colspan="1">wheat</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">305-320</td><td rowspan="1" colspan="1">Sweden</td><td rowspan="1" colspan="1"><xref rid="bib120" ref-type="bibr">Pleijel and Danielsson, 2009</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Triticum aestivum</italic> 'HD-2285'</td><td rowspan="1" colspan="1">wheat</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">250</td><td rowspan="1" colspan="1">India</td><td rowspan="1" colspan="1"><xref rid="bib110" ref-type="bibr">Pal et al., 2003</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Triticum aestivum</italic> 'Janz'</td><td rowspan="1" colspan="1">wheat</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">166</td><td rowspan="1" colspan="1">Australia</td><td rowspan="1" colspan="1"><xref rid="bib43" ref-type="bibr">Fernando et al., 2014</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Triticum aestivum</italic> 'Jinnong 4'</td><td rowspan="1" colspan="1">wheat</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">615</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib156" ref-type="bibr">Tian et al., 2014</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Triticum aestivum</italic> 'Minaret'</td><td rowspan="1" colspan="1">wheat</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">278</td><td rowspan="1" colspan="1">Germany</td><td rowspan="1" colspan="1"><xref rid="bib37" ref-type="bibr">Fangmeier et al., 1997</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Triticum aestivum</italic> 'Minaret'</td><td rowspan="1" colspan="1">wheat</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">300</td><td rowspan="1" colspan="1">Europe</td><td rowspan="1" colspan="1"><xref rid="bib36" ref-type="bibr">Fangmeier et al., 1999</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Triticum aestivum</italic> 'Rinconada'</td><td rowspan="1" colspan="1">wheat</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">350</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib25" ref-type="bibr">de la Puente et al., 2000</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Triticum aestivum</italic> 'Star'</td><td rowspan="1" colspan="1">wheat</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">334</td><td rowspan="1" colspan="1">Germany</td><td rowspan="1" colspan="1"><xref rid="bib94" ref-type="bibr">Manderscheid et al., 1995</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Triticum aestivum</italic> 'Turbo'</td><td rowspan="1" colspan="1">wheat</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">334</td><td rowspan="1" colspan="1">Germany</td><td rowspan="1" colspan="1"><xref rid="bib94" ref-type="bibr">Manderscheid et al., 1995</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Triticum aestivum</italic> 'Turbo'</td><td rowspan="1" colspan="1">wheat</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">350</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib171" ref-type="bibr">Wu et al., 2004</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Triticum aestivum</italic> 'Veery 10'</td><td rowspan="1" colspan="1">wheat</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">410</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"><xref rid="bib18" ref-type="bibr">Carlisle et al., 2012</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Triticum aestivum</italic> 'Yangmai'</td><td rowspan="1" colspan="1">wheat</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">200</td><td rowspan="1" colspan="1">China</td><td rowspan="1" colspan="1"><xref rid="bib47" ref-type="bibr">Guo et al., 2011</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Triticum aestivum</italic> 'Yitpi'</td><td rowspan="1" colspan="1">wheat</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">166</td><td rowspan="1" colspan="1">Australia</td><td rowspan="1" colspan="1"><xref rid="bib41" ref-type="bibr">Fernando et al., 2012a</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Triticum aestivum</italic> 'Yitpi'</td><td rowspan="1" colspan="1">wheat</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">166</td><td rowspan="1" colspan="1">Australia</td><td rowspan="1" colspan="1"><xref rid="bib42" ref-type="bibr">Fernando et al., 2012b</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Triticum aestivum</italic> 'Yitpi'</td><td rowspan="1" colspan="1">wheat</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">166</td><td rowspan="1" colspan="1">Australia</td><td rowspan="1" colspan="1"><xref rid="bib40" ref-type="bibr">Fernando et al., 2012c</xref></td></tr><tr><td rowspan="1" colspan="1"><italic>Triticum aestivum</italic> 'Yitpi'</td><td rowspan="1" colspan="1">wheat</td><td rowspan="1" colspan="1">Yes</td><td align="char" char="." rowspan="1" colspan="1">166</td><td rowspan="1" colspan="1">Australia</td><td rowspan="1" colspan="1"><xref rid="bib43" ref-type="bibr">Fernando et al., 2014</xref></td></tr></tbody></table><table-wrap-foot><fn><p>The table provides species name, common name, the type of experimental set up, the level of CO<sub>2</sub> enrichment, and indicates whether the species is a crop. Countries are listed only for FACE and OTC type experiments with ‘Europe’ accounting for combined data from Belgium, Denmark, Finland, Germany, Sweden, and the UK.</p></fn></table-wrap-foot></table-wrap></p><p>The following data-inclusion rules were applied to the studies with multiple co-dependent datasets for the foliar dataset: (1) the lowest and the highest CO<sub>2</sub> levels for studies with multiple CO<sub>2</sub> levels, (2) the control and single-factor CO<sub>2</sub> for studies with environmental co-factors (e.g., observations from combined eCO<sub>2</sub> and ozone experiments were excluded), (3) the highest nutrient regime when the control could not be identified in a study with multiple nutrient co-factors, (4) the last point, that is the longest exposure to ambient/eCO<sub>2</sub> for studies with time series, (5) the most mature needles/leaves for studies reporting foliar tissues of various ages. If, in rare instances, a publication reported three or more separate datasets for the same species or cultivar, the data were averaged prior to the inclusion into the foliar dataset. For the edible tissue dataset, the study inclusion rules were the same as for the foliar dataset with the following exception: due to relative scarcity of data for edible tissues, the data with co-factors were included in the dataset (e.g., observations from combined eCO<sub>2</sub> and ozone experiments were included). The ‘Additional info’ column in the dataset specifies exactly what datasets were extracted from each study with multiple datasets.</p><p>The above publication-inclusion and data-inclusion rules allow treating each study as independent in the dataset. At no instance, potentially co-dependent observations (e.g., multiple observations of the same plant throughout a growing season or observations of various parts of the same plant) were included in either the foliar or the edible dataset as separate studies. I used GraphClick v.3.0 and PixelStick v.2.5 to digitize data presented in a graphical form, for example bar charts.</p><p>The foliar dataset covers 4733 observations of 25 chemical elements in 110 species and cultivars. The edible tissues dataset covers 3028 observations of 23 elements in 41 species and cultivars. The FACE studies cover 2264 observations of 24 elements in 25 species and cultivars. The two datasets reflect data on 125 C<sub>3</sub> and 5 C<sub>4</sub> species/cultivars.</p></sec><sec id="s4-3"><title>Effect size measure</title><p>While the amount of statistical details provided in each study varies considerably, the following data were extractable from each study: (1) the relative change (or lack thereof) in the mean concentration between the low and the high CO<sub>2</sub> treatments: <italic>(E-A)/A</italic>, where <italic>A</italic> and <italic>E</italic> are the mean concentrations of an element at the low and the high CO<sub>2</sub> treatments respectively, (2) the sample size or the number of replicates (<italic>n</italic>).</p><p>Since a decrease in the concentration of a mineral is limited to 100%, but an increase in its concentration is theoretically unlimited, a standard technique was applied to reduce biases towards increases. Specifically, the natural log of the response ratio, that is <italic>ln(E/A)</italic>, was used as the effect size metric (e.g., <xref rid="bib52" ref-type="bibr">Hedges et al., 1999</xref>; <xref rid="bib66" ref-type="bibr">Jablonski et al., 2002</xref>; <xref rid="bib152" ref-type="bibr">Taub et al., 2008</xref>). The response ratio, <italic>r = E/A,</italic> was calculated from the relative change as follows: <italic>r = 1+(E-A)/A</italic>. After performing statistical analyses, I converted all the results back from the log form to report them as ordinary percent changes.</p></sec><sec id="s4-4"><title>Making results replicable</title><p>Published meta-analytic and biostatistical results need to be replicable and reproducible, and the process of replication needs to be made as easy as possible and clearly traceable to the original sources (<xref rid="bib114" ref-type="bibr">Peng, 2009</xref>). In this regard, I have made the following efforts to ease the replication (from the original sources) of each and every result presented here:<list list-type="order"><list-item><p>While copyright restrictions do not permit posting the original published data sources online, I will share, upon request, all the data sources in PDF form, where all the pertinent data are clearly marked for easy identification, thus removing any potential ambiguity about what data were extracted from each study.</p></list-item><list-item><p>The entire dataset for the foliar and the edible tissues is available at Dryad digital depository, <ext-link ext-link-type="uri" xlink:href="http://www.datadryad.org/">www.datadryad.org</ext-link>, under <ext-link ext-link-type="uri" xlink:href="http://dx.doi.org/10.5061/dryad.6356f">10.5061/dryad.6356f</ext-link>. The dataset is available as an Excel file (formatted for easy viewing) and as a ‘CSV’ file; the latter is made-ready (tidy) for analysis with open-source (<xref rid="bib127" ref-type="bibr">R Core Team, 2014</xref>) and commercial statistical packages (e.g., SPSS).</p></list-item><list-item><p>An executable R code to generate individual results is available with the dataset at the above-mentioned depository and at GitHub: <ext-link ext-link-type="uri" xlink:href="https://github.com/loladze/co2">https://github.com/loladze/co2</ext-link>. Assistance for replicating any result and figure presented in this study will be provided to any interested party.</p></list-item></list></p></sec><sec id="s4-5"><title>Statistical analysis</title><p>I performed all the analyses using R (<xref rid="bib127" ref-type="bibr">R Core Team, 2014</xref>), SPSS v. 21 (IBM, Armonk, NY, USA) and G*Power 3 (<xref rid="bib39" ref-type="bibr">Faul et al., 2007</xref>). Meta-analytic studies often weight effect sizes by the reciprocal of their variance, which tends to give a greater weight to studies with greater precision. However, many eCO<sub>2</sub> studies do not report measures of variation in the data (standard error, standard deviation, or variance). In lieu of the measures of variance, studies can be weighted by the number of replicates (<italic>n</italic>) or, alternatively, each study can be assigned equal weight, that is, unweighted method (<xref rid="bib66" ref-type="bibr">Jablonski et al., 2002</xref>). I used both methods (weighted and unweighted) to calculate the means of effect sizes with 95% CIs and compared the results of both methods. Nearly in all instances, the difference between the weighted and the unweighted means was small and lesser than the standard error of the unweighted mean. For example, across all the FACE studies, the overall mineral change was −6.1% (−7.8 to −4.4) when unweighted cf. the −6.5% (−8.0 to −5.1) when weighted. For the reason of close similarity between weighted and unweighted approaches, I used the simpler out of the two methods, that is the unweighted one, when reporting the results.</p><p>Since the distribution of effect sizes is not necessarily normal, I applied both parametric (<italic>t</italic> test) and non-parametric (bootstrapping with 10,000 replacements) tests for calculating the 95% CI for the mean effect size and the statistical power. The latter was calculated for: (1) an absolute effect size of 5%, and (2) the probability of Type I error, <italic>α</italic> = 0.05. If the variance of a small sample << the true population variance, then this leads to substantial overestimations of Cohen's <italic>d</italic> and the statistical power. To be conservative when estimating power for small samples (m <20), I used the <italic>larger</italic> of the sample standard deviation or 0.21, which is the standard deviation for the entire mineral dataset.</p><p>The results from the parametric and non-parametric tests were very close. For example, for Zn in edible tissues (sample size = 65), <italic>t</italic> test yields (−11.4%, −14.0 to −8.7) and 0.91 power cf. (−11.4%, −13.9 to −8.7) and 0.92 power for the bootstrapping procedure. A close similarity between the results of <italic>t</italic> test and non-parametric test is expected when sample size (<italic>m</italic>, the number of independent observations for each mineral) is >30, which often was the case in this study. For reporting purposes, I used the 95% CI and the power generated by the non-parametric method, that is, the bootstrapping procedure.</p></sec><sec id="s4-6"><title>Testing for publication bias</title><p>To test for publication bias or ‘the file drawer effect’ in the dataset, I plotted effect sizes against corresponding sample sizes/replicates, <italic>n</italic>, to provide a simple visual evaluation of the distribution of effect sizes (<xref ref-type="fig" rid="fig9">Figure 9</xref>). The resulting cloud of points is funnel-shaped, narrowing toward larger sample sizes, and overall is symmetrical along the mean effect size. This indicates the absence of any significant publication bias (<xref rid="bib31" ref-type="bibr">Egger et al., 1997</xref>).</p></sec><sec id="s4-7"><title>Fragmenting the dataset into categories</title><p>Meta-analytic CO<sub>2</sub> studies often partition their datasets into various categories (e.g., plant group, plant tissue, fertilization, or water regime) to estimate effect sizes for each category. Such data fragmentation, however, is warranted only if the statistical power of the resulting test for each category is adequate. Otherwise, low power can lead to non-significant outcomes and Type II errors. As tempting as it can be to partition the current dataset into many categories and cases (e.g., Zn in fruits, Fe in tuber, Cu in annuals, multiple CO<sub>2</sub> levels), only by fragmenting the data into sufficiently large categories an adequate statistical power can be retained. Such categories include: foliar tissues, edible tissues, woody plants (trees and shrubs), herbaceous plants, FACE studies, non-FACE studies, crops, wild plants (all non-crops, including ornamental plants), C<sub>3</sub> plants, C<sub>4</sub> plants, rice, wheat, barley, and potato. Furthermore, I fragmented the data for C<sub>3</sub> plants, the foliar and the edible tissues, the non-FACE and the FACE studies into individual chemical elements and into individual common plant names (e.g., all rice cultivars grouped under ‘rice’). For the regional analysis, I used only OTC and FACE studies because they reflect local environment much more accurately than studies using complete-enclosures (e.g., closed chamber, glasshouse). If an OTC or FACE study did not report precise geographic coordinates, then the latitude and longitude of a nearby research facility or city was used (all coordinates in the dataset are in decimal units). <xref ref-type="fig" rid="fig1 fig2 fig3 fig4 fig5 fig6 fig7">Figures 1–7</xref> include results with the statistical power >0.40 for each element, country, region, plant tissue or category. Generally, power >0.80 is considered acceptable (<xref rid="bib22" ref-type="bibr">Cohen, 1988</xref>). Unfortunately, such a level was achievable only for elements for which the data are most abundant and for the ionomes of some plant groups and species. Note that the power was calculated for a 5% effect size, while the true effect size is likely to be larger (∼8%); therefore, the true power is likely to be higher than the calculated power for most results. All the results, irrespective of the statistical power, can be found in <xref ref-type="supplementary-material" rid="SD1-data">Figure 1–source data 1</xref>. Furthermore, <xref ref-type="fig" rid="fig1">Figure 1</xref> shows the mean effect sizes (with their 95% CI) plotted against their respective statistical powers for all the minerals and all the plant groups/tissues.</p></sec><sec id="s4-8"><title>Formula for calculating percentage changes in TNC:protein and TNC:minerals</title><p>If the concentration of substance X in a plant increases by <inline-formula><mml:math id="inf1"><mml:mrow><mml:mi>x</mml:mi><mml:mo>%</mml:mo></mml:mrow></mml:math></inline-formula> and concomitantly the concentration of substance Y decreases by <inline-formula><mml:math id="inf2"><mml:mrow><mml:mi>y</mml:mi><mml:mo>%</mml:mo></mml:mrow></mml:math></inline-formula> in the plant, then the X-to-Y ratio of the plant (X:Y) increases by:<disp-formula id="equ1"><label>(1)</label><mml:math id="m1"><mml:mrow><mml:mfrac><mml:mrow><mml:mi>x</mml:mi><mml:mo>+</mml:mo><mml:mi>y</mml:mi></mml:mrow><mml:mrow><mml:mn>100</mml:mn><mml:mo>−</mml:mo><mml:mi>y</mml:mi></mml:mrow></mml:mfrac><mml:mo>·</mml:mo><mml:mn>100</mml:mn><mml:mo>%</mml:mo></mml:mrow></mml:math></disp-formula></p><sec id="s4-8-1"><title>Proof</title><p>Let us denote the initial concentrations of substances <italic>X</italic> and <italic>Y</italic> in a plant as <italic>x</italic><sub><italic>A</italic></sub> and <italic>y</italic><sub><italic>A</italic></sub>, respectively. Suppose the <italic>X</italic> and <italic>Y</italic> contents in the plant changed by <italic>x</italic>% and −<italic>y</italic>%, respectively. Then the new <italic>X</italic> content in the plant, <italic>x</italic><sub><italic>E</italic></sub>, is<disp-formula id="equ2"><mml:math id="m2"><mml:mrow><mml:msub><mml:mi>x</mml:mi><mml:mi>E</mml:mi></mml:msub><mml:mo>=</mml:mo><mml:msub><mml:mi>x</mml:mi><mml:mi>A</mml:mi></mml:msub><mml:mo>·</mml:mo><mml:mrow><mml:mo>(</mml:mo><mml:mn>100</mml:mn><mml:mo>+</mml:mo><mml:mi>x</mml:mi><mml:mo>)</mml:mo></mml:mrow><mml:mo>%</mml:mo><mml:mo>,</mml:mo></mml:mrow></mml:math></disp-formula>and the new <italic>Y</italic> content in the plant,<italic>y</italic><sub><italic>E</italic></sub>, is<disp-formula id="equ3"><mml:math id="m3"><mml:mrow><mml:msub><mml:mi>y</mml:mi><mml:mi>E</mml:mi></mml:msub><mml:mo>=</mml:mo><mml:msub><mml:mi>y</mml:mi><mml:mi>A</mml:mi></mml:msub><mml:mo>·</mml:mo><mml:mrow><mml:mo>(</mml:mo><mml:mn>100</mml:mn><mml:mo>−</mml:mo><mml:mi>y</mml:mi><mml:mo>)</mml:mo></mml:mrow><mml:mo>%</mml:mo><mml:mo>.</mml:mo></mml:mrow></mml:math></disp-formula></p><p>The original <inline-formula><mml:math id="inf3"><mml:mrow><mml:mi>X</mml:mi><mml:mo>:</mml:mo><mml:mi>Y</mml:mi><mml:mo>=</mml:mo><mml:mrow><mml:mrow><mml:msub><mml:mi>x</mml:mi><mml:mi>A</mml:mi></mml:msub></mml:mrow><mml:mo>/</mml:mo><mml:mrow><mml:msub><mml:mi>y</mml:mi><mml:mi>A</mml:mi></mml:msub></mml:mrow></mml:mrow></mml:mrow></mml:math></inline-formula>, while the new <inline-formula><mml:math id="inf4"><mml:mrow><mml:mi>X</mml:mi><mml:mo>:</mml:mo><mml:mi>Y</mml:mi><mml:mo>=</mml:mo><mml:mrow><mml:mrow><mml:msub><mml:mi>x</mml:mi><mml:mi>E</mml:mi></mml:msub></mml:mrow><mml:mo>/</mml:mo><mml:mrow><mml:msub><mml:mi>y</mml:mi><mml:mi>E</mml:mi></mml:msub></mml:mrow></mml:mrow></mml:mrow></mml:math></inline-formula>. Since the percentage change in the <italic>X:Y</italic> equals to:<disp-formula id="equ4"><mml:math id="m4"><mml:mrow><mml:mfrac><mml:mrow><mml:mi>n</mml:mi><mml:mi>e</mml:mi><mml:mi>w</mml:mi><mml:mo>−</mml:mo><mml:mi>o</mml:mi><mml:mi>r</mml:mi><mml:mi>i</mml:mi><mml:mi>g</mml:mi><mml:mi>i</mml:mi><mml:mi>n</mml:mi><mml:mi>a</mml:mi><mml:mi>l</mml:mi></mml:mrow><mml:mrow><mml:mi>o</mml:mi><mml:mi>r</mml:mi><mml:mi>i</mml:mi><mml:mi>g</mml:mi><mml:mi>i</mml:mi><mml:mi>n</mml:mi><mml:mi>a</mml:mi><mml:mi>l</mml:mi></mml:mrow></mml:mfrac><mml:mo>·</mml:mo><mml:mn>100</mml:mn><mml:mo>%</mml:mo><mml:mo>=</mml:mo><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mfrac><mml:mrow><mml:mi>n</mml:mi><mml:mi>e</mml:mi><mml:mi>w</mml:mi></mml:mrow><mml:mrow><mml:mi>o</mml:mi><mml:mi>r</mml:mi><mml:mi>i</mml:mi><mml:mi>g</mml:mi><mml:mi>i</mml:mi><mml:mi>n</mml:mi><mml:mi>a</mml:mi><mml:mi>l</mml:mi></mml:mrow></mml:mfrac><mml:mo>−</mml:mo><mml:mn>1</mml:mn></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mo>·</mml:mo><mml:mn>100</mml:mn><mml:mo>%</mml:mo><mml:mo>,</mml:mo></mml:mrow></mml:math></disp-formula>substituting <inline-formula><mml:math id="inf5"><mml:mrow><mml:mrow><mml:mrow><mml:msub><mml:mi>x</mml:mi><mml:mi>A</mml:mi></mml:msub></mml:mrow><mml:mo>/</mml:mo><mml:mrow><mml:msub><mml:mi>y</mml:mi><mml:mi>A</mml:mi></mml:msub></mml:mrow></mml:mrow></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="inf6"><mml:mrow><mml:mrow><mml:mrow><mml:msub><mml:mi>x</mml:mi><mml:mi>E</mml:mi></mml:msub></mml:mrow><mml:mo>/</mml:mo><mml:mrow><mml:msub><mml:mi>y</mml:mi><mml:mi>E</mml:mi></mml:msub></mml:mrow></mml:mrow></mml:mrow></mml:math></inline-formula> for the original and the new, respectively, yields: <disp-formula id="equ5"><mml:math id="m5"><mml:mrow><mml:mfrac><mml:mrow><mml:mrow><mml:mrow><mml:msub><mml:mi>x</mml:mi><mml:mi>E</mml:mi></mml:msub></mml:mrow><mml:mo>/</mml:mo><mml:mrow><mml:msub><mml:mi>y</mml:mi><mml:mi>E</mml:mi></mml:msub></mml:mrow></mml:mrow></mml:mrow><mml:mrow><mml:mrow><mml:mrow><mml:msub><mml:mi>x</mml:mi><mml:mi>A</mml:mi></mml:msub></mml:mrow><mml:mo>/</mml:mo><mml:mrow><mml:msub><mml:mi>y</mml:mi><mml:mi>A</mml:mi></mml:msub></mml:mrow></mml:mrow></mml:mrow></mml:mfrac><mml:mo>−</mml:mo><mml:mn>1</mml:mn><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:msub><mml:mi>x</mml:mi><mml:mi>E</mml:mi></mml:msub><mml:mo>·</mml:mo><mml:msub><mml:mi>y</mml:mi><mml:mi>E</mml:mi></mml:msub></mml:mrow><mml:mrow><mml:msub><mml:mi>x</mml:mi><mml:mi>A</mml:mi></mml:msub><mml:mo>·</mml:mo><mml:msub><mml:mi>y</mml:mi><mml:mi>A</mml:mi></mml:msub></mml:mrow></mml:mfrac><mml:mo>−</mml:mo><mml:mn>1</mml:mn><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mi>x</mml:mi><mml:mi>A</mml:mi></mml:msub><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mn>100</mml:mn><mml:mo>+</mml:mo><mml:mi>x</mml:mi></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mo>%</mml:mo></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mo>·</mml:mo><mml:msub><mml:mi>y</mml:mi><mml:mi>A</mml:mi></mml:msub></mml:mrow><mml:mrow><mml:msub><mml:mi>x</mml:mi><mml:mi>A</mml:mi></mml:msub><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mi>y</mml:mi><mml:mi>A</mml:mi></mml:msub><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mn>100</mml:mn><mml:mo>−</mml:mo><mml:mi>y</mml:mi></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mo>%</mml:mo></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:mrow></mml:mfrac><mml:mo>−</mml:mo><mml:mn>1</mml:mn><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:mn>100</mml:mn><mml:mo>+</mml:mo><mml:mi>x</mml:mi></mml:mrow><mml:mrow><mml:mn>100</mml:mn><mml:mo>−</mml:mo><mml:mi>y</mml:mi></mml:mrow></mml:mfrac><mml:mo>−</mml:mo><mml:mn>1</mml:mn><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:mi>x</mml:mi><mml:mo>+</mml:mo><mml:mi>y</mml:mi></mml:mrow><mml:mrow><mml:mn>100</mml:mn><mml:mo>−</mml:mo><mml:mi>y</mml:mi></mml:mrow></mml:mfrac><mml:mo>.</mml:mo></mml:mrow></mml:math></disp-formula></p><p>An advantage of <xref ref-type="disp-formula" rid="equ1">Equation 1</xref> is that it holds true irrespective of whether the decrease in <italic>Y</italic> is driven by some reason applicable only to <italic>Y</italic> or by the increase in <italic>X</italic>, that is the dilution by <italic>X</italic>.</p></sec></sec></sec></body><back><ack id="ack"><title>Acknowledgements</title><p>The author thanks George Kordzakhia, Nik Loladze and Marina Van for discussions, David Salt and four anonymous referees for comments, and Dmitri Logvinenko for providing access to library resources. The author acknowledges NSF rejections to support this research (proposals Nos. 0548181, 0644300, 0746795).</p></ack><sec sec-type="additional-information"><title>Additional information</title><fn-group content-type="competing-interest"><title><bold>Competing interests</bold></title><fn fn-type="conflict" id="conf1"><p>The author declares that no competing interests exist.</p></fn></fn-group><fn-group content-type="author-contribution"><title><bold>Author contributions</bold></title><fn fn-type="con" id="con1"><p>IL, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article.</p></fn></fn-group></sec><sec sec-type="supplementary-material"><title>Additional files</title><sec sec-type="datasets"><title>Major dataset</title><p>The following dataset was generated:</p><p><related-object content-type="generated-dataset" id="dataro1" document-id="Dataset ID and/or url" document-type="data" document-id-type="dataset"><name><surname>Loladze</surname><given-names>I</given-names></name>, <year>2014</year><x xml:space="preserve">, </x><source>CO<sub>2</sub> Dataset (CSV format); CO<sub>2</sub> Dataset (XLSX format); R Code for the CO<sub>2</sub> dataset</source><x xml:space="preserve">, </x><ext-link ext-link-type="uri" xlink:href="http://dx.doi.org/10.5061/dryad.6356f">http://dx.doi.org/10.5061/dryad.6356f</ext-link><x xml:space="preserve">, </x><comment>Available at Dryad Digital Repository under a CC0 Public Domain Dedication.</comment></related-object></p></sec></sec><ref-list><title>References</title><ref id="bib1"><mixed-citation publication-type="web"><person-group person-group-type="author"><collab>AAAC Climate Science Panel</collab></person-group><year>2014</year><article-title>What we know: the reality, risks and response to climate change</article-title>. <comment>URL <ext-link ext-link-type="uri" 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person-group-type="author"><name><surname>Ziska</surname><given-names>L</given-names></name><name><surname>Namuco</surname><given-names>O</given-names></name><name><surname>Moya</surname><given-names>T</given-names></name><name><surname>Quilang</surname><given-names>J</given-names></name></person-group><year>1997</year><article-title>Growth and yield response of field-grown tropical rice to increasing carbon dioxide and air temperature</article-title>. <source>Agronomy Journal</source><volume>89</volume>:<fpage>45</fpage>–<lpage>53</lpage>. doi: <pub-id pub-id-type="doi">10.2134/agronj1997.00021962008900010007x</pub-id></mixed-citation></ref></ref-list></back><sub-article id="SA1" article-type="article-commentary"><front-stub><article-id pub-id-type="doi">10.7554/eLife.02245.016</article-id><title-group><article-title>Decision letter</article-title></title-group><contrib-group><contrib contrib-type="editor"><name><surname>Baldwin</surname><given-names>Ian T</given-names></name><role>Reviewing editor</role><aff><institution>Max Planck Institute for Chemical Ecology</institution>,<country>Germany</country></aff></contrib></contrib-group></front-stub><body><boxed-text position="float" orientation="portrait"><p>eLife posts the editorial decision letter and author response on a selection of the published articles (subject to the approval of the authors). An edited version of the letter sent to the author after peer review is shown, indicating the substantive concerns or comments; minor concerns are not usually shown. Reviewers have the opportunity to discuss the decision before the letter is sent (see <ext-link ext-link-type="uri" xlink:href="http://elifesciences.org/review-process">review process</ext-link>). Similarly, the author response typically shows only responses to the major concerns raised by the reviewers.</p></boxed-text><p>[Editors’ note: a previous version of this study was rejected after peer review, but the author submitted for reconsideration. The two decision letters after peer review are shown below.]</p><p>Thank you for choosing to send your work entitled “Hidden shift: elevated CO<sub>2</sub> alters the plant ionome depleting minerals at the base of human and herbivore nutrition” for consideration at <italic>eLife</italic>. Your full submission has been evaluated by a Senior editor and 3 peer reviewers, and the decision was reached after discussions between the reviewers. We regret to inform you that your work will not be considered further for publication at this time.</p><p>The following peer reviewers have agreed to reveal their identity: David Salt and Lisa Ainsworth.</p><p>This is not an easy call, as all reviewers agreed that it was a solid analysis that builds significantly on the previously published work in Trends in Ecology and Evolution in 2002 and that the power analysis was a particularly noteworthy advance. The reason for decision to reject lay in the concerns about the “scaleability” the results from the FACE trails to human nutrition. The conclusions were based on analogies to human obesity studies and were simply too strongly drawn to be supported by the data. It also wasn't clear to the reviewers that the FACE results could extrapolate to tropical agricultural systems given that tropical agricultural productivity is limited by other factors (water, nitrogen, pests etc).</p><p><italic>Reviewer</italic><italic>#1:</italic></p><p>This manuscript details a meta analysis based on published data on the concentration of elements (aka ionome) in various plant tissues and species from studies in which atmospheric CO<sub>2</sub> has been varied. Analysis of the data in an appropriate statistical framework revealed significant chances in the plant ionome after growth of plants in atmospheres with elevated CO<sub>2</sub> (in both laboratory and field-based experiments). Many of these changes were not observed as significant changes in the original studies due to low sample sizes. Further analyses by integration of published data on carbohydrate content of plant tissues reveals that these changes in the plant ionome are likely due to dilution by the enhanced accumulation of carbohydrates observed when plants are grown in elevated CO<sub>2</sub>. An interesting discussion is then presented on the potential significance of this dilution of essential mineral nutrients in our global food supply.</p><p>I enjoyed reading this manuscript and liked the discursive style (something that is now quite rare in the scientific literature). However, I felt the manuscript was too long and both the Introduction and Discussion could be significantly shortened after careful editing without significant loss of readability or information content. For example, the long discussion on sample size being important to detect significant differences between treatments when the effect is expected to be small could be significantly reduced.</p><p><italic>Reviewer</italic><italic>#2:</italic></p><p>This is an interesting review of the effects of rising CO<sub>2</sub> on the mineral content of plants. This author previously published a study on this topic, alerting the community to the detrimental impact that rising CO<sub>2</sub> concentrations were having on mineral content of plants and edible parts of plants. In the current manuscript, a much larger data set is compiled and statistically analyzed to report that elevated CO<sub>2</sub> significantly decreases mineral content in leaves and other edible parts of plants. Much thought and discussion is given to the power of the meta-dataset and I think that this is an important aspect of the paper. Finally, a thought experiment is done to discuss the potential impact of the increase in C and decrease in mineral nutrients on human health.</p><p>I think that the biggest question from this analysis is the impact on human health. In regions of the world where people are most dependent on bioavailable calories and nutrients from plants, few elevated CO<sub>2</sub> experiments have been done. For example, there are no published data from FACE experiments in the tropics. In tropical regions, drought, extreme temperatures and/or very poor nutrient supply likely limit agricultural production and in these areas elevated CO<sub>2</sub> may have substantially less impact on plant growth or plant quality. Therefore, it is very uncertain what effect elevated CO<sub>2</sub> will have on human nutrition there, and I think this needs to be acknowledged as a gap in the data and in the potential inferences made in this paper.</p><p><italic>Reviewer</italic><italic>#3:</italic></p><p>I very much enjoyed reading this paper. It takes a clever approach to the highly significant issue of how climate change might impact on the human food chain via its influence of plant composition, and in so doing does an excellent job of discussing the results in a broad integrative context. Usually a critical reviewer, I could find little to complain about here: the story is important, convincing, and nicely told.</p><p>[Editors’ note: what now follows is the decision letter after the authors submitted for further consideration.]</p><p>Thank you for sending your work entitled “Hidden shift: elevated CO<sub>2</sub> alters the plant ionome and depletes minerals at the base of human nutrition” for further consideration at <italic>eLife</italic>. Your article has been favorably evaluated by Ian Baldwin and 3 new peer reviewers.</p><p>The Reviewing editor and the reviewers discussed their comments before we reached this decision, and the Reviewing editor has assembled the following comments to help you prepare a revised submission.</p><p>This manuscript presents a unique collection of data on CO<sub>2</sub>-induced changes of the plant ionome, which clearly show that the majority of plants investigated so far showed a remarkably similar tendency in their response to CO<sub>2</sub> (albeit with variation). This is clearly an under-appreciated component of the undeniable rise in global CO<sub>2</sub> levels, which deserves more attention. The reviewers also recognized that the core of the argument that relates to the impact of changes in nutrient content of the edible portion of food crops on human health has simply not been settled, and were (again) split as to whether this problem was sufficient to reject the manuscript for <italic>eLife</italic>. After discussion, a consensus agreement was reached that the manuscript could be accepted if it was substantially revised so that it was clear that impact of changes in nutrient content of the edible portion of food crops on human health has not been settled. We hope that in revising the manuscript, this uncertainty is explicitly addressed and that you could highlight the need for more research to address this very important but festering issue. In addition, it was felt that the Introduction should be shortened, downplaying the thought experiment, and significantly tempering the conclusions drawn in the Discussion.</p></body></sub-article><sub-article id="SA2" article-type="reply"><front-stub><article-id pub-id-type="doi">10.7554/eLife.02245.017</article-id><title-group><article-title>Author response</article-title></title-group></front-stub><body><p>[Editors’ note: the author responses to the first round of peer review follow.]</p><p>Reviewer 2 claims that there is “no published data from FACE experiments in the tropics.” Her opinion is that “elevated CO<sub>2</sub> may have substantially less impact” on plant quality in the tropics and, “therefore, it is very uncertain what effect elevated CO2 will have on human nutrition there.”</p><p>This argument is flawed. There <italic>are</italic> published FACE, open-top chamber and greenhouse experiments carried out between the 35<bold>°</bold> N & S latitudes – the tropical and subtropical regions, where large parts of malnourished population reside (e.g., <xref rid="bib93" ref-type="bibr">Ma <italic>et al.</italic> 2007</xref>; <xref rid="bib68" ref-type="bibr">Jia <italic>et al.</italic> 2007</xref>, <xref rid="bib110" ref-type="bibr">Pal <italic>et al.</italic> 2003</xref>, <xref rid="bib109" ref-type="bibr">2004</xref>; <xref rid="bib146" ref-type="bibr">Singh <italic>et al.</italic> 2013</xref>; Khan <italic>et al.</italic> 2012; Azam <italic>et al.</italic> 2012), and they do show declines in the plant mineral content. Prompted by the <italic>eLife</italic> review, I made the regional analysis of all the CO<sub>2</sub> studies carried out between the 35<bold>°</bold> N & S parallels: it shows that the plant mineral content declines by 5% in the region. Furthermore, many countries in the tropics rely on imports of wheat, maize and soybeans, most of which are grown north of the N 35<bold>°</bold>parallel, where FACE and other experiments also reveal declines in the crop mineral content.</p><p>No reviewer found any logical flaws in my human-nutrition thought experiment, which relies on the rigor of mass balance laws. However, I understand that such “experiments” are not conventional even if their conclusions are valid. For this reason, I can tone down and shorten the health and obesity discussion. The revised paper will focus on firmly establishing a novel and important aspect of global change – the shift in the plant ionome induced by the rising CO<sub>2</sub>.</p><p>I emphasize that this is a novel result because the last definitive word on the issue was <xref rid="bib29" ref-type="bibr">Duval <italic>et al.</italic> (2011)</xref> meta-analysis claiming the absence of any prevailing effect of elevated CO<sub>2</sub> on the plant minerals and, specifically, the lack of response of grain minerals to high-CO<sub>2</sub> – claims that are opposite to my results.</p><p>The power is in your hands to give my revised and stronger paper further consideration at e<italic>Life</italic> and to advance the progress on this important issue.</p><p>[Editors’ note: the author responses to the re-review follow.]</p><p><italic>After discussion, a consensus agreement was reached that the manuscript could be accepted if it was substantially revised so that it was clear that impact of changes in nutrient content of the edible portion of food crops on human health has not been settled. We hope that in revising the manuscript, this uncertainty is explicitly addressed and that you could highlight the need for more research to address this very important but festering issue</italic>.</p><p>I revised the manuscript accordingly. Specifically:</p><p>I have added the following statement to the Discussion: “I emphasize that the impact of CO<sub>2</sub>-induced shifts in the quality of crops on human health is far from settled. The purpose of what follows is not to make definitive claims but to stimulate research into this important but festering issue.”</p><p>I have added a new subsection to the Discussion, titled “Data Scarcity,” noting that for many crops, the pertinent data are limited or non-existent.</p><p>The wording about the effects of the mineral decline on human nutrition was toned down from “will” to “can”/“might/potential”. (Furthermore, the abstract was changed to stress that the effects on human health are discussed (and, thus, are not parts of results.)</p><p><italic>In addition, it was felt that the Introduction should be shortened, downplaying the thought experiment..</italic>.</p><p>I deleted the passage referring to my 2002 ‘thought experiment’ from the Introduction and do not mention it anywhere else in the manuscript.</p><p>I deleted the reference to Loladze & Elser (2011) together with the sentence stating that the cellular stoichiometric homeostasis is sensitive to the environment.</p><p>I have shortened and simplified the passage about the dichotomy between CO<sub>2</sub> effects on N and minerals.</p><p>I have shortened and improved readability of the list of questions at the end of the Introduction. The new Introduction is shorter by ∼200 words.</p><p><italic>...and significantly tempering the conclusions drawn in the Discussion</italic>.</p><p>Aside from changes indicated above, I have made the following changes to the Discussion:</p><p>1) Deleted <xref ref-type="fig" rid="fig9">Figure 9</xref> showing the graphical output of <xref rid="bib49" ref-type="bibr">Hall et al. (2011)</xref> dynamic model of weight gains in a female and a male.</p><p>2) Tempered and shortened conclusions about the impact on human health. Now the statements are reduced to: “The above ‘experiment’ suggests that a systemic and sustained 5% mineral depletion in plants can be nutritionally significant. While the rise in the atmospheric CO<sub>2</sub> concentration is expected to be nearly uniform around the globe, its impact on crop quality might unequally affect the human population: from no detrimental effects for the well-nourished people to potential weight gain for the calorie-sufficient but mineral-undernourished.”</p><p>In addition, to the above changes I revamped the Results by separating them into clear subsections. Furthermore, the readability throughout the paper was improved.</p></body></sub-article></pmc></record>Pour manipuler ce document sous Unix (Dilib)
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