Similar photosynthetic but different yield responses of C3 and C4 crops to elevated O3
Edited by Krishna Niyogi, University of California, Berkeley, CA; received August 21, 2023; accepted October 6, 2023
Significance
Current ground-level ozone (O3) pollution significantly reduces global crop productivity. Understanding how different crops respond to elevated O3 concentration ([O3]) is critical to improve crop production and resilience under atmospheric change. Here, we synthesize available literature and unpublished data from five C3 crops and four C4 crops grown with increased O3 pollution in open-air field experiments over the past 20 y. We quantitatively show that C3 crops are more sensitive to elevated [O3] than C4 crops. Our results provide key insights into O3 response in crops with different photosynthetic pathways and could help guide future efforts to improve crop O3 tolerance.
Abstract
The deleterious effects of ozone (O3) pollution on crop physiology, yield, and productivity are widely acknowledged. It has also been assumed that C4 crops with a carbon concentrating mechanism and greater water use efficiency are less sensitive to O3 pollution than C3 crops. This assumption has not been widely tested. Therefore, we compiled 46 journal articles and unpublished datasets that reported leaf photosynthetic and biochemical traits, plant biomass, and yield in five C3 crops (chickpea, rice, snap bean, soybean, and wheat) and four C4 crops (sorghum, maize, Miscanthus × giganteus, and switchgrass) grown under ambient and elevated O3 concentration ([O3]) in the field at free-air O3 concentration enrichment (O3-FACE) facilities over the past 20 y. When normalized by O3 exposure, C3 and C4 crops showed a similar response of leaf photosynthesis, but the reduction in chlorophyll content, fluorescence, and yield was greater in C3 crops compared with C4 crops. Additionally, inbred and hybrid lines of rice and maize showed different sensitivities to O3 exposure. This study quantitatively demonstrates that C4 crops respond less to elevated [O3] than C3 crops. This understanding could help maintain cropland productivity in an increasingly polluted atmosphere.
Sign up for PNAS alerts.
Get alerts for new articles, or get an alert when an article is cited.
Tropospheric ozone (O3) is a damaging airborne pollutant and an important greenhouse trace gas that is produced by photochemical oxidation of carbon monoxide (CO), methane (CH4), and nonmethane volatile organic compounds in the presence of nitrogen oxides (NOx) (1, 2). The harmful effects of O3 on vegetation have been recognized since the 1940 s (3). The pollutant diffuses into leaves through stomata and generates reactive oxygen species (ROS) within the apoplast, thereby damaging cellular metabolism and triggering the process of programmed cell death above threshold concentrations (4–7). Atmospheric O3 concentrations ([O3]) currently range from 30 to 50 ppb (parts per billion) and negatively impact crop growth and development, leading to significant crop yield loss worldwide (8–13).
Over the past 50 y, the impacts of current and future [O3] on major food crops and emerging bioenergy feedstocks have been extensively studied using controlled enclosure systems such as open-top chambers (OTC) and more recently free-air O3 concentration enrichment (O3-FACE) technology (14–17). Plant performance and response to environmental factors under controlled conditions can be very different from those in the open field (18–22). FACE experiments enable growing crops under elevated [O3] in fully -open conditions, but without modifying the soil–plant–atmosphere continuum, hence providing more realistic simulations of elevated atmospheric [O3] compared to other experimental approaches (20, 23–26). Previous FACE studies have found that elevated [O3] reduced leaf photosynthesis and accelerated the process of senescence in many C3 crops, including rice (Oryza sativa L.) (27), soybean (Glycine max L.) (15, 28, 29) and wheat (Triticum aestivum L.) (30, 31), and in a C4 crop, maize (Zea mays L.) (32, 33). It is estimated that 8 to 37% of soybean yields (28) and 15 to 17.5% of rice yields in two sensitive cultivars (34) would be lost to a 50% increase in background [O3]. Elevated [O3] at 25% above ambient decreased wheat yields by 10 to 35% in four Chinese cultivars (35). In maize, exposure to 100 ppb [O3] reduced yields by 5 to 39% in hybrids but had no effect on two inbred lines (32, 36). Recent FACE experiments further revealed that many C4 crops, including sorghum (Sorghum bicolor L.) (37), switchgrass (Panicum virgatum L.) (38), and miscanthus (Miscanthus × giganteus) (17), maintained photosynthetic capacity and biomass when exposed to 100 ppb [O3]. These various experiments suggest that wheat is the most O3-sensitive major staple crop and C3 crops are generally more sensitive to O3 than C4 crops. However, these studies have been done in different locations with different backgrounds and target concentrations for O3 fumigation and a quantitative synthesis that normalizes O3 exposure and response is lacking.
In C3 plants, ROS from O3 degradation can cause direct damage to both spongy and palisade mesophyll cells where photosynthesis occurs, leading to rapid downstream responses, hormone changes, and signaling (4, 5, 26). However, C4 plants initially assimilate atmospheric CO2 in mesophyll cells via phosphoenolpyruvate (PEP) carboxylase and concentrate CO2 around Rubisco in separate bundle sheath cells where the initial reactions of the Calvin cycle occur (39, 40). Thus, the outer layer of mesophyll cells in C4 leaves could protect the inner layer bundle sheath cells from ROS damage and act as a barrier against ROS diffusion from the apoplastic space to the bundle sheath cells (41). Moreover, C4 crops, such as switchgrass and sorghum, have lower stomatal conductance than C3 crops including wheat and rice, potentially resulting in less O3 uptake in C4 crops (42, 43). Taken together, this suggests that C4 crops are less sensitive to O3 than C3 crops. Previous analysis of the global effects of surface O3 on crop yield showed that the O3 sensitivity of staple food crops declined in the order of soybean > wheat > maize > rice (10, 13, 44). A recent modeling study of historical crop yield and O3 data showed a 10% decrease in yield in maize and 5% in soybean in the United States, indicating maize was potentially more sensitive to O3 than soybean (12). However, these estimations come with inevitable uncertainties. For example, many other environmental factors, such as drought and/or heat stress, can be correlated with O3 concentrations and also directly impact crop yields (45–49). These interactions cannot be entirely excluded because of a lack of control in large-scale observations. Controlled enclosure facilities including OTC can substantially modify microenvironments, including water availability, air turbulence, temperature, and light quality and intensity, and thereby alter O3 uptake by leaves and subsequent plant performance (20, 23, 25, 50). In addition, the considerable variation in O3 sensitivity among genotypes and between inbred and hybrid lines in both C3 and C4 crops has been rarely considered in previous studies. This emphasizes the importance of quantifying the response of plant variables to O3 to obtain a more accurate comparison of O3 response between C3 and C4 crops.
In the present work, we synthesized published data together with unpublished datasets that reported photosynthesis and photosynthetic capacity, chlorophyll content and fluorescence, leaf biochemical traits, crop biomass, and seed yield in C3 and C4 crops grown under ambient and elevated [O3] in the field using FACE technology to 1) examine the extent of leaf trait variation in C3 and C4 crops, 2) analyze how elevated [O3] affects crop performance in C3 and C4 crops, and 3) explore whether inbred and hybrid lines of rice and maize exhibit a similar O3 response. Because previous FACE studies have suggested that antioxidant capacity in leaf tissue may determine O3 sensitivity in wheat, soybean, and maize (28, 32, 34, 36), we tested the association between antioxidant metabolites (phenolics) and O3 response in these crops. To compare across diverse experiments and different growing seasons, we used a common metric AOT40 (ppm h), a measure of hourly accumulated exposure over a threshold [O3] of 40 ppb during daylight hours, to quantify and normalize the response of plant traits to O3 pollution.
Results
Global Crop O3-FACE Facilities.
Our analysis used data compiled from 46 published studies (SI Appendix, Fig. S1) and unpublished data from three O3-FACE facilities (China, India, and the United States) over 20 y from 2002 to 2021 (Table 1 and SI Appendix, Tables S1 and S2). Nine crop species, including five C3 crops (chickpea, rice, snap bean, soybean, and wheat) and four C4 crops (sorghum, maize, Miscanthus × giganteus, and switchgrass) which represent major staple crops and emerging bioenergy feedstocks were included (Table 1 and SI Appendix, Tables S1 and S2). Soybean, snap bean, maize, and C4 bioenergy grasses were investigated at the SoyFACE research facility near Champaign, Illinois, located in one of the most productive soybean and maize growing regions in the world (Table 1). The target fumigation concentration varied over the two decades of experimentation at SoyFACE (Table 1). The effects of elevated [O3] on crop physiology and yield in rice and wheat were studied at Jiangdu, China, where FACE facilities were operated from 2007 to 2013 and elevated O3 treatments were set at 1.5 to 1.6 × ambient [O3] (Table 1 and SI Appendix, Table S1). Rice and wheat cultivation has been practiced for more than 1,000 y in this region. Diverse inbred and F1 hybrid maize and rice lines were studied in the United States and China (SI Appendix, Table S3). From 2016 to 2018, chickpea, rice, wheat, and maize were investigated at a FACE experiment in New Delhi, India (Table 1 and SI Appendix, Table S1). The elevated [O3] ranged from 60 to 70 ppb in the experiments in India (Table 1 and SI Appendix, Table S1).
Table 1.
| Crop | Scientific name | Photosynthetic pathway | Site | Years of experiment | Target O3 concentration | References* |
|---|---|---|---|---|---|---|
| Chickpea | Cicer arietinum L. | C3 | New Delhi, India | 2017 to 2018 | 60 to 70 ppb | (50) |
| Rice | Oryza sativa L. | C3 | Jiangdu, Jiangsu, China | 2007 to 2012 | 1.5 to 1.6 × ambient [O3] | (34, 51) |
| Rice | Oryza sativa L. | C3 | New Delhi, India | 2016 to 2017 | 60 ± 10 ppb | (52) |
| Snap bean | Phaseolus vulgaris L. | C3 | Champaign, IL | 2006 | 1.4 × ambient [O3] | (53) |
| Soybean | Glycine max L. | C3 | Champaign, IL | 2002 to 2013 2020 to 2021 | 1.2 to 2 × ambient [O3]; 40 to 200 ppb; 100 ppb | (15, 28, 54, 55) |
| Wheat | Triticum aestivum L. | C3 | Jiangdu, Jiangsu, China | 2007 to 2013 | 1.5 × ambient [O3] | (35) |
| Wheat | Triticum aestivum L. | C3 | New Delhi, India | 2017 to 2018 | 70 ppb | (31) |
| Maize | Zea mays L. | C4 | Champaign, IL | 2013 to 2019 | 100 ppb | (32, 33, 56) |
| Maize | Zea mays L. | C4 | New Delhi, India | 2016 to 2017 | 70 ppb | (57) |
| Miscanthus | Miscanthus × giganteus | C4 | Champaign, IL | 2019 to 2020 | 100 ppb | (17) |
| Sorghum | Sorghum bicolor L. | C4 | Champaign, IL | 2018 to 2019 | 100 ppb | (17, 37) |
| Switchgrass | Panicum virgatum L. | C4 | Champaign, IL | 2018 to 2019 | 100 ppb | (17, 38) |
*A full list of references used in this study can be found in SI Appendix, Table S1 and details of unpublished data are in SI Appendix, Table S2.
C3 vs. C4.
At ambient [O3] conditions, C3 crops, including chickpea, rice and wheat, showed lower net CO2 assimilation rates (A) but greater stomatal conductance (gs) compared to C4 crops (SI Appendix, Fig. S2). C3 crops had significantly lower mean A (24.7 vs. 29.3 µmol m−2 s−1) and instantaneous water use efficiency (iWUE, 50.6 vs. 126.5 µmol mol−1), and greater gs (0.53 vs. 0.26 mol m−2 s−1) and intercellular CO2 concentration (Ci, 267.7 vs. 172.9 µmol mol−1) compared to C4 crops (SI Appendix, Fig. S3). Meta-analysis revealed consistent impacts of elevated [O3] on leaf gas exchange in C3 and C4 crops (Fig. 1). The reduction in A by elevated [O3] was approximately 15% for both C3 and C4 plants (Fig. 1). Although elevated [O3] decreased gs in both C3 and C4 crops, the magnitude of the response was two times greater in C3 compared to C4 crops and the reduction was not significant in C4 crops (Fig. 1). Ci was increased by elevated [O3] in C4 crops but was not significantly affected in C3 crops (Fig. 1).
Fig. 1.
Meta-analyses are useful for identifying general trends in response, but the approach does not evaluate the sensitivity of different crops to a given change in O3 concentration. To quantitatively evaluate O3 sensitivity in each crop or photosynthetic group, we used AOT40 (accumulated hourly exposure over a threshold of 40 ppb, ppm h) to normalize the changes in each trait caused by a given increase in [O3] (Materials and Methods). We found that C3 crops showed similar decreases in A (ΔA) and gs ( ) per unit AOT40 compared to C4 crops (Fig. 2 A and B). At a given unit O3 exposure, A was reduced on average by 1.38% and 1.10%, and gs was reduced by 1.14% and 0.84% in C3 and C4 crop groups, respectively (Fig. 2 A and B). A small increase in AOT40 weighted Ci ( ) and no changes in iWUE (ΔiWUE) per unit AOT40 were observed in both C3 and C4 crop groups (Fig. 2C).
Fig. 2.
Large variation among the photosynthetic CO2 response curve (A/Ci curve) parameters was also detected in both C3 and C4 crops (SI Appendix, Fig. S4). A/Ci curve parameters were significantly reduced by elevated [O3] in soybean and maize but less so in other crops (SI Appendix, Fig. S4). Additionally, there was an overall reduction of A/Ci curve parameters per unit AOT40 in both C3 and C4 crop groups (Fig. 2C).
Elevated [O3] negatively impacted chlorophyll content and fluorescence and C3 crops showed a significantly greater decrease in AOT40 weighted chlorophyll content (ΔChl content), Fv′/Fm′ ( ), ΦPSII ( ), and qP (ΔqP) than C4 crops (Fig. 3A). In addition, there were significant differences in the response of fructose and phenolics per unit AOT40 (ΔFructose and ΔPhenolics, respectively) in C3 and C4 crop groups (Fig. 3B). The percentage change in yield or biomass per unit AOT40 (Δyield/biomass) varied from −3.44 in snap bean to −1.10 in chickpea in C3 crops and from −0.41 in maize to 0.36 in switchgrass in C4 crops (Fig. 4). Thus, the productivity of C4 crops was significantly less responsive to elevated [O3] compared to C3 crops (−0.31% ppm−1 h−1 vs. −1.44% ppm−1 h−1, P < 0.001) (Fig. 4).
Fig. 3.
Fig. 4.
Our analysis further showed that ΔA, , ΔChl content, and Δyield/biomass were positively correlated, while ΔPhenolics was negatively correlated with ΔA, , ΔChl content, and Δyield/biomass in C3 crops (SI Appendix, Fig. S5 and Table S4). In C4 crops, however, significant relationships were found only between ΔA and Δyield/biomass (SI Appendix, Fig. S5A) and between and ΔA (SI Appendix, Fig. S5E), indicating that sensitivity of leaf biochemical traits to O3 rarely limited crop productivity. C4 crops also showed highly significant correlations among ΔA, , and percentage changes in chlorophyll fluorescence per unit AOT40 (SI Appendix, Table S5).
Inbred vs. Hybrid.
We further analyzed leaf traits and grain yield in rice and maize to test whether their responses to O3 enrichment varied between inbred and hybrid lines. We did not observe any significant difference in A (20.2 vs. 18.7), gs (0.47 vs. 0.53), and grain yield (817.5 vs. 821.9) between inbred and hybrid lines of rice at ambient [O3] (SI Appendix, Fig. S6 A–C). Hybrids showed significant reductions in gs and grain yield under elevated [O3] (SI Appendix, Fig. S6 A–C), which agreed with the results from the meta-analysis showing that elevated [O3] significantly decreased A, gs, and grain yield in rice hybrids (Fig. 5A). However, there was no significant difference in the quantitative effect of elevated [O3] on rice leaf traits between inbred and hybrid lines (Fig. 5B). For grain yield, the percentage reduction per unit AOT40 was more than double in hybrid lines compared with inbred lines (2.56% vs. 1.15%) (Fig. 5B).
Fig. 5.
In maize, hybrids had greater A (29.1 vs. 23.0), gs (0.29 vs. 0.15), and grain yield (122.6 vs. 39.5) than inbred lines in ambient [O3] conditions (SI Appendix, Fig. S6 D–F). Elevated [O3] significantly reduced A and grain yield in hybrids but did not affect any trait values in inbred lines (SI Appendix, Fig. S6 D–F). The meta-analysis indicated that A, gs, and grain yield were significantly reduced in both inbred and hybrid lines (Fig. 5C). Quantitatively, maize inbred lines did not differ from hybrids in O3 response of most traits but had significantly less reduction in A per unit AOT40 than hybrid lines (Fig. 5D).
Discussion
Although previous manipulative experiments and modelling efforts reported significant variation in O3 sensitivity across crop species, variation in O3 treatment concentrations across open-air field facilities adds uncertainty to comparative analysis of O3 response (10, 12, 13, 44, 59, 60). In addition, differences in crop size and growing season length particularly between C3 and C4 crops, inbreds, and hybrids limit the ability to do accurate side-by-side comparisons within a FACE facility. Meta-analytic approaches have been widely used to estimate the general effects of elevated [O3] on crop physiology and production (18, 60–62), but quantitatively, they have not estimated crop responses to a given change in [O3], rather all concentrations higher than ambient are typically binned. Here, we performed a comprehensive analysis of the impact of O3 on crop physiology and production across nine crop species from three FACE facilities in the United States, China, and India (Table 1 and SI Appendix, Tables S1 and S2) to test for differences in how C3 and C4 crops respond to elevated [O3], when normalized to a common AOT40 dose. Our analysis unequivocally demonstrated that C3 crops are more vulnerable to elevated [O3] compared to C4 crops with O3 sensitivity ranking in the order of snap bean > rice ≥ wheat > chickpea > soybean > maize > miscanthus > sorghum > switchgrass (Fig. 4), which is consistent with a previous meta-analysis (60) but not with modeling studies suggesting that soybean is the most sensitive crop and rice is the most tolerant (13, 44).
It should be noted that the O3 sensitivity of crops may differ among continents or regions. For instance, North American crops, such as wheat and soybean, were reported to be more tolerant to O3 than their Asian and European counterparts (4, 21, 63–66). Growing environments, physiological traits, and genetic backgrounds associated with sensitivity may be responsible for continent-wide variation in O3 response in crops, but the mechanisms are still unknown. In our analysis, most of the C3 crops except snap bean and soybean were studied in Asian O3-FACE experiments, whereas all the C4 crops except two genotypes of maize from India were studied at SoyFACE in North America (Table 1). However, C3 and C4 crops were grown in the same year at SoyFACE. That experiment suggests that C4 crops (maize, miscanthus, sorghum, and switchgrass) are more O3 tolerant than C3 crops (snap bean and soybean) (Fig. 4). While our analysis represented worldwide data sources for major staple crops and emerging bioenergy crops from a broad range of climates, it could be strengthened by additional side-by-side comparisons of C3 and C4 crops exposed to elevated [O3] in the same climatic conditions.
C4 crops are characterized by Kranz anatomy, in which vascular bundles are surrounded by bundle sheath cells and bundle sheath cells are further surrounded by mesophyll cells (39, 40). Kranz anatomy in C4 crops enables bundle sheath cells to concentrate CO2 around Rubisco, improving the efficiency of photosynthesis compared to C3 crops (40, 42). The C4 crops studied in O3-FACE experiments have significantly lower gs and higher A and iWUE than C3 crops (SI Appendix, Figs. S2 and S3). Lower gs in C4 crops limits O3 uptake and O3-induced damage. C3 crops showed greater grain yield loss per increased [O3] than C4 crops, yet there were no significant differences in AOT40 weighted responses of leaf photosynthesis, stomatal conductance, photosynthetic capacity, or leaf sugar content between C3 and C4 crops (Figs. 2 and 3). This may be because leaf-level measurements were taken throughout the growing season and on leaves of various ages, which were not always clearly reported. Previous studies have demonstrated that O3 damage to photosynthesis is greater in aging leaves and later in the growing season (15), which may not have been captured accurately in our analysis. O3 effects on photosynthesis and metabolites also vary with position in the canopy (32, 33, 67). Still, it is interesting that C4 crops could clearly better tolerate O3-induced reductions in photosynthesis without significant impacts on yield, which was not the case for C3 crops.
Elevated O3 exposure often changes the levels of hormones and biochemicals such as apoplastic antioxidants, including ascorbate, phenolics, and glutathione. These antioxidants directly react with O3 and scavenge ROS within the leaf and therefore contribute to O3 tolerance (4, 36, 68, 69). Because energy or products for detoxification and antioxidant biosynthesis are supplied by photosynthesis, O3 tolerance in C4 crops may be attributable to greater photosynthetic efficiency. Here, we show that the concentration of phenolics, the only antioxidant molecules studied widely in both C3 and C4 crops in FACE experiments, was increased under elevated [O3] and were negatively correlated with AOT40 weighted changes in chlorophyll content, A and yield in C3 crops (Fig. 3 and SI Appendix, Fig. S5). This indicates a trade-off between carbon assimilation and antioxidant biosynthesis. Although phenolics were measured in maize hybrids (32), the small number of genotypes studied was not sufficient to determine a protective role of the molecules in O3 stress resistance in C4 crops. Indeed, antioxidant metabolism and response under O3 stress is complex in C4 crops where antioxidative enzymes are not uniformly distributed in mesophyll and bundle sheath cells and compound concentrations change within cellular compartments (70, 71). Future research in C4 crops is needed to clarify the temporal and spatial antioxidant response under elevated [O3].
Our results also suggest that O3-induced reduction in A and grain yield in hybrids are greater than in inbred lines in rice and maize (Fig. 5 and SI Appendix, Fig. S6). In rice, gs is unlikely to be a major factor determining different O3 sensitivity between inbreds and hybrids because both lines showed a similar range of gs (SI Appendix, Fig. S6B) while the inbreds showed relatively small changes in A and grain yield under elevated [O3] (Fig. 5 A and B). The greater impacts of elevated [O3] on hybrid rice lines could be attributed in part to greater reductions in tiller and spikelet numbers and less efficient antioxidant metabolism (34, 72–76). In contrast, gs may play a crucial role in responding to elevated [O3] in maize where hybrids with greater gs showed a larger decrease in A and more grain yield loss (Fig. 5 C and D and SI Appendix, Fig. S6 D–F). Recent studies have additionally shown that variation in O3 sensitivity between maize inbred and hybrid lines is potentially associated with antioxidant content and capacity (32, 36). Furthermore, developmental differences between hybrids and inbreds could also result in differences in O3 response in both rice and maize (33, 34). These studies illustrate the complexity in O3 response mechanisms in inbreds and hybrids with profound implications for improving O3 tolerance in hybrid crops, where tolerance to O3 in hybrids is not always predicable from tolerance in inbreds.
Conclusions and Implications
Accurately quantifying the response of C3 and C4 crops to elevated [O3] is critical to improving predictions of crop yield losses due to O3 at the global scale. Here, we show that O3-induced reductions in leaf traits and crop production are larger in C3 crops than that in C4 crops at a given O3 exposure, likely underpinned by biochemical differences in O3 response. It is important to note that hybrids were more sensitive to O3 than inbred lines in rice and maize, which has implications for breeding for O3 tolerance in hybrid crops. At the landscape scale, agricultural lands can be managed to have improved overall performance in polluted environments. C4 crops, in particular bioenergy feedstocks, could provide sustainable biomass yields and energy in high O3-polluted regions.
Materials and Methods
Data Compilation.
To gather data on how elevated O3 concentrations affect crop physiology and productivity in C3 and C4 crops, we searched ISI Web of Science, Google Scholar, and China Wanfang database for published literature using the following combinations of keywords: FACE (or free-air O3 concentration enrichment) OR elevated O3 (or elevated ozone) OR crop. The literature search was performed in accordance with guidelines from the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA; 77) (see SI Appendix, Fig. S1 for full details). To be included in this analysis, the study had to meet the following criteria: 1) Experiments must include control and O3 treatment groups; 2) plants must be rooted in natural soils in the field; 3) studies must provide one or more of the following traits: leaf gas exchange, photosynthetic CO2 response curve (A/Ci curve) parameters, chlorophyll content (or SPAD values) and fluorescence, leaf carbohydrate content, leaf total soluble protein, Rubisco content, leaf phenolic content, and seed yield or above-ground biomass; and 4) data from control and elevated O3 treatments must be clearly provided independently from other stresses if applied. In total 46 published articles, with five C3 crops (chickpea, rice, snap bean, soybean, and wheat) and four C4 crops (sorghum, maize, Miscanthus × giganteus, and switchgrass), were compiled from FACE studies in China, India, and the United States from 2002 to 2019 (Table 1 and SI Appendix, Table S1). Data from tables or text of the original articles were used directly, while data presented in graphical form were extracted using Engauge Digitizer (http://markummitchell.github.io/engauge-digitizer/).
In addition to datasets from published sources, we also included unpublished data from our previous and current research projects that investigated O3 response in soybean and C4 crops at SoyFACE (SI Appendix, Table S2). Both inbred and F1 hybrid cultivars of rice in China and maize in the United States (SI Appendix, Table S3) were included in our analysis.
Meta-Analysis.
We calculated the logarithm-transformed response ratios [ln(RR)] as a measure for effect sizes (78) to assess the effect of elevated [O3] on leaf gas exchange in C3 and C4 crops and on leaf traits and grain yield in inbred and hybrid lines of rice and maize. For each type of comparison, ln(RR) was calculated as follows:
[1]
where and are the means of target trait values obtained from elevated and ambient [O3], respectively.
The variance of ln(RR), υ, was calculated as:
[2]
where SDe and SDa are the SDs of the target trait obtained from elevated and ambient [O3], respectively; ne and na are the samples sizes of the target trait obtained from elevated and ambient [O3], respectively. As some <5% of studies did not report SDs, we used the impute_SD function of the R package metagear (79) to estimate SDs using Rubin and Schenker’s resampling approach (80). Instantaneous water use efficiency (iWUE) was calculated from reported means of net CO2 assimilation rate (A) and stomatal conductance (gs), and thus was omitted from the meta-analysis.
We calculated mean effect sizes of elevated [O3] and their CIs using the rma.mv function of the R package metafor (version 3.8-1) (81) with studies nested in species or cultivars as random effects. The mean effect sizes of elevated [O3] were considered significant if a 95% CI did not overlap with zero. For all variables in the meta-analysis, we also evaluated publication bias with funnel plots and Egger’s regression test (81–83). We found little evidence for publications bias. Only A in the whole dataset, chlorophyll content in rice, and A and Ci in maize showed evidence of bias (SI Appendix, Figs. S7–S9). Furthermore, trim-and-fill analysis (84) revealed that no missing values were found, suggesting the direction and the significance of the overall effects in the models were stable. All meta-analyses were performed on the R platform (version 4.2.2).
Quantitative Analysis.
Although meta-analytical approach allowed us to evaluate the general effects of elevated [O3], the approach does not normalize ozone responses to a given unit of exposure. To further quantitatively estimate the changes in a target trait caused by O3 and to compare studies with different target concentrations, we calculated the plant trait response per unit O3 exposure (Δ, O3 exposure weighted response) using the following:
[3]
where x represents the target trait, δx is the percentage change in the target trait in elevated O3, and AOT40e and AOT40a are trait-associated AOT40 values measured at the elevated and ambient [O3] treatments, respectively. δx is derived from the mean values of target trait obtained from elevated and ambient [O3] and estimated as ( / − 1) × 100% (see Eq. 1 for definition). Considering that different ambient and elevated [O3] were used in different years and sites (28, 35, 55, 56), we used the increase in AOT40 (AOT40e – AOT40a) to estimate trait response to elevated [O3].
AOT40 (ppm h), a measure of hourly accumulated O3 exposure above a threshold of 40 ppb during daylight hours, is a widely used metric for assessing O3 effects on crops and forests (85, 86). In the present study, the AOT40 data were i) extracted directly from the published articles; ii) estimated from i) for studies not reporting AOT40 but presenting measurement dates when experiments were conducted at the same site on the same year as i); iii) calculated based on hourly or daily average [O3] according to the equations provided by Osborne et al. (21) when season-long mean [O3] was reported; and iv) calculated from the raw fumigation data for experiments conducted at SoyFACE, but not reporting AOT40 (87). We calculated AOT40 from ambient and elevated [O3] using the following:
[4]
where [O3]i is hourly O3 concentration (ppb) during daytime (8:00 to 18:00) fumigation hours and n is the number of hours within target fumigation period. Cumulative AOT40 from the entire fumigation period was used to normalize the changes of crop yield or biomass, while AOT40 for the leaf level measurement was summed from the beginning of the fumigation up to the date of the measurement. However, the AOT40 values were not available for leaf gas exchange of five studies (SI Appendix, Tables S1 and S2), and those data were only presented in SI Appendix, Figs. S2, S3, and S6. It should be noted that an AOT40 of 9 ppm h was considered to be the critical level at which a significant decrease in plant traits due to O3 could be observed for soybean (29), and thus, we included only soybean trait data collected at AOT40 >9 ppm h for calculations.
In addition to analyzing all the traits together in each crop or crop group, we made separate analyses of inbred and hybrid cultivars/genotypes for rice and maize. We performed ANOVA to compare leaf trait or crop production means between C3 and C4 crop groups and between inbred and hybrid lines of rice and maize under ambient conditions. The O3 effects on leaf trait and crop production in each crop or crop group were estimated by one-way ANOVA followed by Tukey’s test. We also performed one-way ANOVA to examine differences in plant response per unit AOT40 between C3 and C4 crop groups and between inbreds and hybrids. We calculated the correlations between plant response per unit AOT40 in each crop group using simple linear regression.
Data, Materials, and Software Availability
Sources of previously published data used in this paper are provided in SI Appendix, Table S1. The dataset is publicly available at the Illinois Data Bank at https://doi.org/10.13012/B2IDB-9446886_V1 (88). The SoyFACE O3 fumigation database is publicly available at https://doi.org/10.13012/B2IDB-3496460_V3 (89). All other data are included in the manuscript and/or SI Appendix.
Acknowledgments
We are grateful to Jesse McGrath, Noah Mitchell, Anthony Digrado, Hannah Demler, Yanqun Zhang, Duncan Martin, Nicole Choquette, Aidan McMahon, John Ferguson, Renan Umburanas, Seldon Kwafo, and many other students and researchers for soybean, snap bean and C4 crop measurements and maintenance of the experimental plots at the SoyFACE. This work was funded by the DOE Center for Advanced Bioenergy and Bioproducts Innovation (U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research under Award Number DE-SC0018420). Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the views of the U.S. Department of Energy (DOE) or the US Department of Agriculture (USDA). Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the USDA. USDA is an equal opportunity provider and employer.
Author contributions
S.L. and E.A.A. designed research; S.L., A.D.B.L., C.A.M., C.M.M., E.J.S., D.L., and E.A.A. performed research; S.L. analyzed data; and S.L. and E.A.A. wrote the paper.
Competing interests
The authors declare no competing interest.
Supporting Information
Appendix 01 (PDF)
- Download
- 2.85 MB
References
1
P. S. Monks et al., Tropospheric ozone and its precursors from the urban to the global scale from air quality to short-lived climate forcer. Atmos. Chem. Phys. 15, 8889–8973 (2015).
2
J. M. Wedow, E. A. Ainsworth, S. Li, Plant biochemistry influences tropospheric ozone formation, destruction, deposition, and response. Trends Biochem. Sci. 46, 992–1002 (2021).
3
J. T. Middleton, J. B. Kendrek, H. W. Schwalm, Injury to herbaceous plants by smog or air pollution. Plant Dis. Rep. 34, 245–252 (1950).
4
E. A. Ainsworth, Understanding and improving global crop response to ozone pollution. Plant J. 90, 886–897 (2017).
5
J. Kangasjärvi, P. Jaspers, H. Kollist, Signalling and cell death in ozone-exposed plants. Plant Cell Environ. 28, 1021–1036 (2005).
6
S. Li, P. C. Harley, Ü. Niinemets, Ozone-induced foliar damage and release of stress volatiles is highly dependent on stomatal openness and priming by low-level ozone exposure in Phaseolus vulgaris. Plant Cell Environ. 40, 1984–2003 (2017).
7
S. P. Long, S. L. Naidu, "Effect of oxidants at the biochemical, cell and physiological levels, with particular reference to ozone" in Air Pollution and Plant Life, J. N. B. Bell, M. Treshow, Eds. (John Wiley & Sons Ltd., 2002), pp. 69–88.
8
E. A. Ainsworth, C. R. Yendrek, S. Sitch, W. J. Collins, L. D. Emberson, The effects of tropospheric ozone on net primary productivity and implications for climate change. Annu. Rev. Plant Biol. 63, 637–661 (2012).
9
A. T. Archibald et al., On the changes in surface ozone over the twenty-first century: Sensitivity to changes in surface temperature and chemical mechanisms. Phil. Trans. R. Soc. A 378, 20190329 (2020).
10
S. Avnery, D. L. Mauzerall, J. Liu, L. W. Horowitz, Global crop yield reductions due to surface ozone exposure: 1. Year 2000 crop production losses and economic damage. Atmos. Environ. 45, 2284–2296 (2011).
11
I. Bourgeois et al., Large contribution of biomass burning emissions to ozone through the global remote troposphere. Proc. Natl. Acad. Sci. U.S.A. 118, e2109628118 (2021).
12
J. M. McGrath et al., An analysis of ozone damage to historical maize and soybean yields in the United States. Proc. Natl. Acad. Sci. U.S.A. 112, 14390–14395 (2015).
13
G. Mills et al., Closing the global ozone yield gap: Quantification and cobenefits for multistress tolerance. Global Change Biol. 24, 4869–4893 (2018).
14
D. T. Tingey, R. A. Reinert, H. B. Carter, Soybean cultivars: Acute foliar response to ozone. Crop Sci. 12, 268–270 (1972).
15
P. B. Morgan, C. J. Bernacchi, D. R. Ort, S. P. Long, An in vivo analysis of the effect of season-long open-air elevation of ozone to anticipated 2050 levels on photosynthesis in soybean. Plant Physiol. 235, 2348–2357 (2004).
16
H. Tang, G. Liu, Y. Han, J. Zhu, K. Kobayashi, A system for free-air ozone concentration elevation with rice and wheat: Control performance and ozone exposure regime. Atmos. Environ. 45, 6272–6282 (2011).
17
S. Li et al., Testing unified theories for ozone response in C4 species. Global Change Biol. 28, 3379–3393 (2022).
18
E. A. Ainsworth, Rice production in a changing climate: A meta-analysis of responses to elevated carbon dioxide and elevated ozone concentration. Global Change Biol. 14, 1642–1650 (2008).
19
M. A. De Graaf, K. J. Van Groenigen, J. Six, B. Hungate, C. Van Kessel, Interaction between plant growth and soil nutrient cycling under elevated CO2: A meta-analysis. Global Change Biol. 12, 2077–2091 (2006).
20
Z. Feng, J. Uddling, H. Tang, J. Zhu, K. Kobayashi, Comparison of crop yield sensitivity to ozone between open-top chamber and free-air experiment. Global Change Biol. 24, 2231–2238 (2018).
21
S. A. Osborne et al., Has the sensitivity of soybean cultivars to ozone pollution increased with time? An analysis of published dose-response data. Global Change Biol. 22, 3097–3111 (2016).
22
H. Poorter et al., Pampered inside, pestered outside? Differences and similarities between plants growing in controlled conditions and in the field. New Phytol. 212, 838–855 (2016).
23
E. A. Ainsworth, S. P. Long, What have we learned from 15 years of free-air CO2 enrichment (FACE)? A meta-analytic review of the responses of photosynthesis, canopy properties and plant production to rising CO2. New Phytol. 165, 351–372 (2005).
24
E. A. Ainsworth, S. P. Long, 30 years of free-air carbon dioxide enrichment (FACE): What have we learned about future crop productivity and its potential for adaptation? Global Change Biol. 27, 27–49 (2021).
25
S. P. Long, E. A. Ainsworth, A. Rogers, D. R. Ort, Rising atmospheric carbon dioxide: Plants FACE the future. Annu. Rev. Plant Biol. 55, 591–628 (2004).
26
C. M. Montes, H. J. Demler, S. Li, D. G. Martin, E. A. Ainsworth, Approaches to investigate crop responses to ozone pollution: From O3-FACE to satellite-enabled modeling. Plant J. 109, 432–446 (2022).
27
J. Pang, K. Kobayashi, J. Zhu, Yield and photosynthetic characteristics of flag leaves in Chinese rice (Oryza sativa L.) varieties subjected to free-air release of ozone. Agric. Ecosyst. Environ. 132, 203–211 (2009).
28
A. M. Betzelberger et al., Effects of chronic elevated ozone concentration on antioxidant capacity, photosynthesis and seed yield of 10 soybean cultivars. Plant Cell Environ. 33, 1569–1581 (2010).
29
J. Sun, Z. Feng, D. R. Ort, Impacts of rising tropospheric ozone on photosynthesis and metabolite levels on field grown soybean. Plant Sci. 226, 147–161 (2014).
30
Z. Feng, J. Pang, K. Kobayashi, J. Zhu, D. R. Ort, Differential responses in two varieties of winter wheat to elevated ozone concentration under fully open-air field conditions. Global Change Biol. 17, 580–591 (2011).
31
A. Yadav, A. Bhatia, S. Yadav, V. Kumar, B. Singh, The effects of elevated CO2 and elevated O3 exposure on plant growth, yield and quality of grains of two wheat cultivars grown in north India. Heliyon 5, e02317 (2019).
32
N. E. Choquette, E. A. Ainsworth, W. Bezodis, A. P. Cavanagh, Ozone tolerant maize hybrids maintain Rubisco content and activity during long-term exposure in the field. Plant Cell Environ. 43, 3033–3047 (2020).
33
C. R. Yendrek et al., Elevated ozone reduces photosynthetic carbon gain by accelerating leaf senescence of inbred and hybrid maize in a genotype-specific manner. Plant Cell Environ. 40, 3088–3100 (2017).
34
G. Shi et al., Impact of elevated ozone concentration on yield of four Chinese rice cultivars under fully open-air field conditions. Agric. Ecosyst. Environ. 131, 178–184 (2009).
35
X. Zhu et al., Effects of elevated ozone concentration on yield of four Chinese cultivars of winter wheat under fully open-air field conditions. Global Change Biol. 17, 2697–2706 (2011).
36
J. M. Wedow, C. H. Burroughs, L. R. Acosta, A. D. B. Leakey, E. A. Ainsworth, Age-dependent increase in α-tocopherol and phytosterols in maize leaves exposed to elevated ozone pollution. Plant Direct 5, e00307 (2021).
37
S. Li, C. A. Moller, N. G. Mitchell, D. Lee, E. A. Ainsworth, Bioenergy sorghum maintains photosynthetic capacity in elevated ozone concentrations. Plant Cell Environ. 44, 729–746 (2021).
38
S. Li, G. Courbet, A. Ourry, E. A. Ainsworth, Elevated ozone concentration reduces photosynthetic carbon gain but does not alter leaf structural traits, nutrient composition or biomass in switchgrass. Plants 8, 85 (2019).
39
M. D. Hatch, C4 photosynthesis: A unique blend of modified biochemistry, anatomy and ultrastructure. Biochim. Biophys. Acta 895, 81–106 (1987).
40
R. F. Sage, The evolution of C4 photosynthesis. New Phytol. 161, 341–370 (2004).
41
D. A. Grantz, H.-B. Vu, T. L. Tew, J. C. Veremis, Sensitivity of gas exchange parameters to ozone in diverse C4 sugarcane hybrids. Crop Sci. 52, 1270–1280 (2012).
42
A. D. B. Leakey et al., Water use efficiency as a constraint and target for improving the resilience and productivity of C3 and C4 crops. Annu. Rev. Plant Biol. 70, 781–808 (2019).
43
S. Li et al., The leaf economics spectrum of triploid and tetraploid C4 grass Miscanthus x giganteus. Plant Cell Environ. 45, 3462–3475 (2022).
44
R. Van Dingenen et al., The global impact of ozone on agricultural crop yields under current and future air quality legislation. Atmos. Environ. 43, 604–618 (2009).
45
B. Barnabás, K. Jäger, A. Fehér, The effect of drought and heat stress on reproductive processes in cereals. Plant Cell Environ. 31, 11–38 (2008).
46
S. Fahad et al., Crop production under drought and heat stress: Plant responses and management options. Front. Plant Sci. 8, 1147 (2017).
47
S. P. Long, D. R. Ort, More than taking the heat: Crops and global change. Curr Opin Plant Biol. 13, 241–248 (2010).
48
X. Pu et al., Enhanced surface ozone during the heat wave of 2013 in Yangtze River Delta region, China. Sci. Tot. Environ. 603, 807–816 (2017).
49
E. Stathopoulou, G. Mihalakakou, M. Santamouris, H. S. Bagiorgas, On the impact of temperature on tropospheric ozone concentration levels in urban environments. J. Earth Syst. Sci. 117, 227–236 (2008).
50
A. R. McLeod, S. P. Long, Free-air carbon dioxide enrichment (FACE) in global change research: A review. Adv. Ecol. Res. 28, 1–56 (1999).
51
A. Bhatia et al., Effect of elevated ozone and carbon dioxide interaction on growth, yield, nutrient content and wilt disease severity in chickpea grown in Northern India. Heliyon 7, e06049 (2021).
52
J. S. Zhang, H. Y. Tang, G. Liu, J. G. Zhu, Stomatal ozone flux-response relationships of rice (Oryza sativa L.) in subtropical area. J. Agro-Environ. Sci. 35, 1857–1866 (2016). (In Chinese with English abstract).
53
R. Kumar et al., Effect of elevated ozone and carbon dioxide on growth and yield of rice (Oryza sativa). Indian J. Agr. Sci. 91, 1607–1611 (2021).
54
K. O. Burkey, F. L. Booker, E. A. Ainsworth, R. L. Nelson, Field assessment of a snap bean ozone bioindicator system under elevated ozone and carbon dioxide in a free air system. Environ. Pollut. 166, 167–171 (2012).
55
A. M. Betzelberger et al., Ozone exposure response for U.S. soybean cultivars: Linear reductions in photosynthesis potential, biomass and yield. Plant Physiol. 160, 1827–1839 (2012).
56
P. B. Morgan, T. A. Mies, G. A. Bollero, R. L. Nelson, S. P. Long, Season-long elevation of ozone concentration to projected 2050 levels under fully open-air conditions substantially decreases the growth and production of soybean. New Phytol. 170, 333–343 (2006).
57
N. E. Choquette et al., Uncovering hidden genetic variation in photosynthesis of field-grown maize under ozone pollution. Global Change Biol. 25, 4327–4338 (2019).
58
A. Yadav et al., Growth, yield and quality of maize under ozone and carbon dioxide interaction in North West India. Aerosol Air Qual. Res. 21, 200194 (2021).
59
D. A. Grantz, S. Gunn, H.-B. Vu, O3 impacts on plant development: A meta-analysis of root/shoot allocation and growth. Plant Cell Environ. 29, 1193–1209 (2006).
60
Z. Feng, K. Kobayashi, Assessing the impacts of current and future concentrations of surface ozone on crop yield with meta-analysis. Atmos. Environ. 32, 1510–1519 (2009).
61
P. B. Morgan, E. A. Ainsworth, S. P. Long, How does elevated ozone impact soybean? A meta-analysis of photosynthesis, growth and yield. Plant Cell Environ. 26, 1317–1328 (2003).
62
Z. Feng, K. Kobayashi, E. A. Ainsworth, Impact of elevated ozone concentration on growth, physiology and yield of wheat (Triticum aestivum L.): A meta-analysis. Global Change Biol. 14, 2696–2708 (2008).
63
L. D. Emberson et al., A comparison of North American and Asian exposure-response data for ozone effects on crop yields. Atmos. Environ. 43, 1945–1953 (2009).
64
H. Pleijel, M. C. Broberg, J. Uddling, Ozone impact on wheat in Europe, Asia and North America - a comparison. Sci. Tot. Environ. 664, 908–914 (2019).
65
H. Pleijel, M. C. Broberg, J. Uddling, K. Kobayashi, Letter to the editor regarding Pleijel et al. 2019: Ozone sensitivity of wheat in different continents - an addendum. Sci. Tot. Environ. 773, 146335 (2021).
66
Z. Feng et al., Ozone pollution threatens the production of major staple crops in East Asia. Nat. Food 3, 47–56 (2022).
67
A. L. Burton, K. O. Burkey, T. E. Carter Jr., J. Orf, P. B. Cregan, Phenotypic variation and identification of quantitative trait loci for ozone tolerance in a Fiskeby III x Mandarin (Ottawa) soybean population. Theor. Appl. Genet. 129, 1113–1125 (2016).
68
Z. Feng, L. Wang, H. Pleijel, J. Zhu, K. Kobayashi, Differential effects of ozone on photosynthesis of winter wheat among cultivars depend on antioxidative enzymes rather than stomatal conductance. Sci. Tot. Environ. 572, 404–411 (2016).
69
C. H. Foyer, G. Noctor, Oxidant and antioxidant signalling in plants: A re-evaluation of the concept of oxidative stress in a physiological context. Plant Cell Environ. 28, 1056–1071 (2005).
70
A. G. Doulis, N. Debian, A. H. Kingston-Smith, C. H. Foyer, Differential localization of antioxidants in maize leaves. Plant Physiol. 114, 1031–1037 (1997).
71
D. Sundar, B. Perianayaguy, A. Ramachandra Reddy, Localization of antioxidant enzymes in the cellular compartments of sorghum leaves. Plant Growth Regul. 44, 157–163 (2004).
72
Y. Wang et al., Investigations on spikelet formation in hybrid rice as affected by elevated tropospheric ozone concentration in China. Agric. Ecosyst. Environ. 150, 63–71 (2012).
73
J. Wang, Q. Zeng, J. Zhu, G. Liu, H. Tang, Dissimilarity of ascorbate-glutathione (AsA-GSH) cycle mechanism in two rice (Oryza sativa L.) cultivars under experimental free-air ozone exposure. Agric. Ecosyst. Environ. 165, 39–49 (2013).
74
H. Tang, G. Liu, J. Zhu, K. Kobayshi, Effects of elevated ozone concentration on CH4 and N2O emission from paddy soil under fully open-air field conditions. Global Change Biol. 21, 1727–1736 (2015).
75
J. Wang, G. Liu, F. Liu, J. Zhu, Responses of antioxidant enzymes to chronic free-air ozone stress in rice (Oryza sativa L.) cultivars with different ozone-sensitivities. Bull. Environ. Contam. Toxicol. 103, 428–434 (2019).
76
G. Zhang et al., Ethylenediurea (EDU)protects inbred but not hybrid cultivars of rice from yield losses due to surface ozone. Environ. Sci. Pollut. Res. 28, 68946–68956 (2021).
77
D. Moher, A. Liberati, J. Tetzlaff, D. G. Altman; PRISMA Group, Preferred reporting items for systematic reviews and meta-analyses: The PRISMA Statement. PLoS Med. 6, e1000097 (2009).
78
L. V. Hedges, J. Gurevitch, P. S. Curtis, The meta-analysis of response ratios in experimental ecology. Ecology 80, 1150–1156 (1999).
79
M. J. Lajeunesse, Facilitating systematic reviews, data extraction and meta-analysis with the METAGEAR package for R. Methods Ecol. Evol. 7, 323–330 (2016).
80
D. B. Rubin, N. Schenker, Multiple imputation in health-are databases: An overview and some applications. Stat. Med. 10, 585–598 (1991).
81
W. Viechtbauer, Conducting meta-analyses in R with the metafor Package. J. Stat. Softw. 36, 1–48 (2010).
82
M. Egger, G. D. Smith, M. Schneider, C. Minder, Bias in meta-analysis detected by a simple, graphical test. Brit. Med. J. 315, 629–634 (1997).
83
S. Nakagawa, E. S. A. Santos, Methodological issues and advances in biological meta-analysis. Evol. Ecol. 26, 1253–1274 (2012).
84
S. Duval, R. Tweedie, Trim and fill: A simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis. Biometrics. 56, 455–463 (2000).
85
J. Fuhrer, L. Skärby, M. R. Ashmore, Critical levels for ozone effects on vegetation in Europe. Environ. Pollut. 97, 91–106 (1997).
86
G. Mills et al., A synthesis of AOT40-based response functions and critical levels of ozone for agricultural and horticultural crops. Atmos. Environ. 41, 2630–2643 (2007).
87
E. K. Aspray et al., Two decades of fumigation data from the soybean free air concentration enrichment facility. Sci. Data 10, 226 (2023).
88
S. Li et al., Similar photosynthetic, but different yield responses of C3 and C4 crops to elevated O3. Illinois Data Bank. https://doi.org/10.13012/B2IDB-9446886_V1. Deposited 11 August 2023.
89
E. K. Aspray et al., SoyFACE Fumigation Data Files. Illinois Data Bank. https://doi.org/10.13012/B2IDB-3496460_V3. Deposited 26 January 2023.
Information & Authors
Information
Published in
Cover image: Pictured are Adélie penguins poised to dive off an ice floe near Cape Crozier, Antarctica. Annie E. Schmidt et al. analyzed data from geolocating dive recorders on 195 adult Adélie penguins at two colonies in the Ross Sea. The data pertained to the timing and location of the penguins’ annual molting, in which they replace all their feathers. Annual return rates of adult penguins to breeding colonies were positively correlated with sea ice concentrations in molting areas. The findings suggest that declining sea ice in the molting areas may constrain the survival of adult penguins. See the article by Schmidt et al. e2306840120. Image credit: Annie Schmidt/Point Blue.
Classifications
Copyright
Copyright © 2023 the Author(s). Published by PNAS. This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).
Data, Materials, and Software Availability
Sources of previously published data used in this paper are provided in SI Appendix, Table S1. The dataset is publicly available at the Illinois Data Bank at https://doi.org/10.13012/B2IDB-9446886_V1 (88). The SoyFACE O3 fumigation database is publicly available at https://doi.org/10.13012/B2IDB-3496460_V3 (89). All other data are included in the manuscript and/or SI Appendix.
Submission history
Received: August 21, 2023
Accepted: October 6, 2023
Published online: November 10, 2023
Published in issue: November 14, 2023
Keywords
Acknowledgments
We are grateful to Jesse McGrath, Noah Mitchell, Anthony Digrado, Hannah Demler, Yanqun Zhang, Duncan Martin, Nicole Choquette, Aidan McMahon, John Ferguson, Renan Umburanas, Seldon Kwafo, and many other students and researchers for soybean, snap bean and C4 crop measurements and maintenance of the experimental plots at the SoyFACE. This work was funded by the DOE Center for Advanced Bioenergy and Bioproducts Innovation (U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research under Award Number DE-SC0018420). Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the views of the U.S. Department of Energy (DOE) or the US Department of Agriculture (USDA). Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the USDA. USDA is an equal opportunity provider and employer.
Author contributions
S.L. and E.A.A. designed research; S.L., A.D.B.L., C.A.M., C.M.M., E.J.S., D.L., and E.A.A. performed research; S.L. analyzed data; and S.L. and E.A.A. wrote the paper.
Competing interests
The authors declare no competing interest.
Notes
This article is a PNAS Direct Submission.
Authors
Metrics & Citations
Metrics
Citation statements
Altmetrics
Citations
Cite this article
120 (46) e2313591120,
Export the article citation data by selecting a format from the list below and clicking Export.
Cited by
Loading...
View Options
View options
PDF format
Download this article as a PDF file
DOWNLOAD PDFLogin options
Check if you have access through your login credentials or your institution to get full access on this article.
Personal login Institutional LoginRecommend to a librarian
Recommend PNAS to a LibrarianPurchase options
Purchase this article to access the full text.