Introduction
============

Atmospheric CO~2~ concentration has varied tremendously over geological time, from as high as 3000 ppm in the lower Devonian (Royer [@b42]) to as low as 180--280 ppm during the past 2.1 Ma of the Pleistocene (Honisch et al. [@b22]). About 17.5 Ka ago, atmospheric CO~2~ concentration started to rise from 180 ppm, levelled off at 280 ppm around 15 Ka ago and broadly remained at 280 ppm until the Industrial Revolution. Since the start of the Industrial Revolution, CO~2~ levels have risen to 390 ppm today, levels not experienced by plants for over 25 Ma (Royer [@b42]) and are expected to increase even further; common model estimates go up to 700 ppm by 2100 (IPCC [@b23]). A CO~2~ atmosphere of 700 ppm has not been observed since 42 million years ago (Royer [@b42]). The atmosphere today and as predicted for the end of the century is thus increasingly different from that experienced by plants during a large part of the recent past.

CO~2~ plays a pivotal role in a number of important ecophysiological processes: it is an essential ingredient for photosynthesis and plant growth, and it is highly likely that plants\' morphological and physiological traits and their plastic responses to the CO~2~ concentrations are more tuned to the range of CO~2~ concentrations they have experienced recently. Because adjustment to changing CO~2~ involves changes in photosynthetic rates, nitrogen allocation, and other physiological properties (Curtis and Wang [@b13]; Korner [@b26]; Cowling [@b11]; Poorter and Navas [@b37]; Ainsworth and Long [@b1]), this trait adjustment has the potential to create a feedback that could affect the global carbon cycle (Beerling et al. [@b4]). Connecting the performance of plants of different species at low, ambient and future high CO~2~ is thus an important part of understanding the links between the atmospheric CO~2~ concentrations and the terrestrial biosphere in the past, present, and future.

At low CO~2,~ photosynthesis is limited by the amount of available carbon by limiting carboxylase activity of the enzyme RuBisCO. Conversely, at higher CO~2~ concentrations, the rate at which CO~2~ can be taken up (photosynthetic capacity) becomes limiting (Sage [@b43]). CO~2~ levels in the past could thus have selected for RuBisCO carboxylase activity or efficiency. At current and future CO~2~ concentrations, other factors such as water and nutrient uptake will become more limiting than CO~2~ (Ward et al. [@b51]; Campbell and Sage [@b8]; Reich et al. [@b40]). This implies that trait states useful in a low CO~2~ atmosphere can be redundant or suboptimal in a high CO~2~ atmosphere. For example, high investment in RuBisCO, useful at low CO~2~, in a high CO~2~ environment requires a high N investment, which could otherwise be used in other N-limited steps. High activity of enzymes facilitating transport and binding of CO~2~ is a lower priority at high CO~2~ compared with the need for more sink capacity of photosynthates to take advantage of increased photosynthetic rates (Sage and Coleman [@b45]). Favorable traits in low CO~2~ thus do not necessarily mirror those in high CO~2~.

For obvious reasons, considerable scientific effort has gone into examining the response of plants to high levels of CO~2~ as projected for the latter half of this century. Several recent meta-analyses have found that, despite methodological differences among studies, a few main results are apparent: at high (500+ ppm) CO~2,~ there is an increase in carbon assimilation and growth and decrease in stomatal conductance, nitrogen content and specific leaf area (Poorter [@b36]; Curtis and Wang [@b13]; Poorter and Navas [@b37]). The increase in biomass is about +45% for C~3~ species and +12% for C~4~ species at a 50% increase in CO~2~ concentration (Poorter and Navas [@b37]). The response of C~4~ species to increased CO~2~ is smaller than that of C~3~ species, probably because the carbon concentrating mechanism of C~4~ plants already concentrates CO~2~ around RuBisCO leaving less room for increased photosynthetic rate (Bowes [@b7]; Ghannoum et al. [@b20]). Overall, woody species showed a greater response to elevated CO~2~ than herbaceous species (Curtis and Wang [@b13]; Poorter and Navas [@b37]; Ainsworth and Long [@b1]; Lee et al. [@b28]).

In contrast to the large amount of studies on plant responses to elevated CO~2~, less research has been carried out on the response of plants to subambient, Pleistocene levels of CO~2.~ Several individual experiments reveal that the influence of low CO~2~ acts on multiple biotic levels, ranging from leaf level to plant level and ecosystem level (Gerhart and Ward [@b18]). The emergence of agriculture has even been linked to the increase in CO~2~ to 280 ppm 17.5 Ka ago, as higher levels of CO~2~ lead to higher yields (Sage [@b44]). Understanding how plants have adapted to the low CO~2~ of their recent evolutionary history can aid us in understanding plants response to future high CO~2~ (Gerhart and Ward [@b18]; Beerling [@b3]; Leakey and Lau [@b27]). Recent research has shown CO~2~ uptake and water use are highly consistent across CO~2~, from low to high (Franks et al. [@b17]) Thus, there is clearly a need to integrate the knowledge available so far on low CO~2~ responses to determine whether more traits follow a predictable pattern.

Some qualitative expectations can be made as to how plants are likely to respond to low CO~2~. A lowering of CO~2~ will likely lead to a reduction in photosynthetic rates (Farquhar et al. [@b16]) and plant biomass (Overdieck et al. [@b35]; Cunniff et al. [@b12]). Next, an increase in leaf nitrogen concentration as RuBisCO may ameliorate some of the reduction in total C assimilation rate (Sage and Coleman [@b45]). Differences in response among different plant types can also be expected. C~4~ metabolism, which concentrates CO~2~ around RuBisCO, could partly compensate the potential reduction in growth as experienced by C~3~ plants. At lower atmospheric CO~2~ concentration, one of the mechanisms to maintain a high enough internal CO~2~ concentration is to open stomata wider, allowing water to escape at a faster rate (Farquhar and Sharkey [@b15]). Because of the carbon concentrating mechanism in C~4~ species, the diffusion gradient of CO~2~ across the stomata can be much steeper. At reduced CO~2,~ this should allow C~4~ plants to maintain a smaller stomatal aperture than C~3~ plants, giving a smaller increase in stomatal conductance and a smaller decrease in water use efficiency (Farquhar and Sharkey [@b15]). As woody plants invest more biomass in stems than herbaceous plants (Poorter et al. [@b39]) and as stems usually do not contribute substantially to photosynthesis, it is possible that this constrains the ability to adjust carbon allocation at low atmospheric CO~2~. In response to a reduction in growth, a complex suite of trait adjustments, with differences among plant types, is expected at all physiological levels, varying from photosynthesis to biomass allocation. While the directions of all these responses to low CO~2~ have empirical support (Gerhart and Ward [@b18]), they have not yet been quantified in general terms across studies and species.

Here, we present the results of a global meta-analysis synthesizing data from currently available low CO~2~ experiments to quantify general patterns of morphological and ecophysiological trait responses to subambient CO~2~. In particular, together with the body of work on high CO~2~, we aim to build toward a general, quantitative understanding of the response of plant traits to a range of CO~2~.

Thus, we address the following research questions and hypotheses:

1.  How much do plant traits vary with decreased CO~2~ concentration?

    We hypothesize that lower photosynthetic rates will lead to reduced growth at low CO~2~. To acclimate to a low CO~2~ environment and keep up photosynthetic rates, plants will have higher leaf nitrogen and larger stomatal conductance.

2.  How much do plant functional groups differ in their response to low CO~2~?

    Because of the carbon concentrating mechanism of C~4~ plants, we hypothesize (a) that the negative effects of low CO~2~ on their photosynthesis and growth will be reduced as compared to those in C~3~ plants; and (b) that woody species will invest more of their biomass in nonphotosynthetic tissue leading to a greater reduction in biomass accumulation than herbaceous species.

3.  Is plant trait response to low CO~2~ similar in magnitude to the response to elevated CO~2~?

    Atmospheric CO~2~ is on a trajectory from low during glacial times to very high CO~2~ in the future. We aim to shed light on whether plant traits adjust similarly from low to ambient as from ambient to high. Given the saturating nature of the photosynthetic response to CO~2,~ we expect photosynthetic traits to respond to low CO~2~ through a greater magnitude shift compared with the high CO~2~ response. For other traits, we are curious if they follow the saturating response of photosynthesis or if they respond more proportional to CO~2~ changes.

Methods
=======

We performed a literature review on plant science journals searching Web of Science using keywords "subambient CO~2~," "low CO~2~," "reduced CO~2~" and "glacial CO~2~." This resulted in 33 papers that reported on studies with experimentally lowered atmospheric CO~2~ concentration for 54 species in total. In these experiments, plants were grown in greenhouses, climate chambers, or outdoor tubes after Mayeux et al. ([@b301]). For the climate chambers and greenhouses, CO~2~ concentrations were reduced by passing air through some kind of filter or adsorbent (e.g., Soda lime) or through a reactive solution (e.g., NaOH).

For each study, we recorded sample size, duration, growing conditions, low CO~2~ treatment type, and germination conditions along with measures of plant physiological traits at the CO~2~ concentrations used ([Table S1, Data S1 and S2](#SD1){ref-type="supplementary-material"}). A full list of the studies found with which species and trait data they reported can be found in [Table S1, Data S1 and S2](#SD1){ref-type="supplementary-material"}. When data and errors were not present in tabular form, they were extracted from graphs using Datathief 3 (Tummers [@b48]). All papers reported trait means in response to CO~2~ concentration and most reported a measure of error (standard deviation, standard error, or confidence interval) for the trait in each CO~2~ treatment. Three of the published papers dealt with response to low CO~2~ at varying resource conditions (P limitation: Campbell and Sage [@b8]; Lewis et al. [@b29]; Drought: Ward et al. [@b51]). In order to exclude confounding factors, only those results at high nutrients and well-watered conditions were included. C~3~--C~4~ intermediates were grouped together with C~4~ species.

From the studies found, only 6 traits emerged with 10 or more species analyzed and only 20 traits with 3 or more species. Of these 20 traits, 12 were related to growth and development. These traits included specific leaf area (as SLA or leaf mass per area, which was recalculated to SLA, m^2^·g^−1^) and (components of) plant biomass (DW, g dry weight). In some cases, plant biomass was divided into above- and belowground mass. Aboveground mass was divided into leaf and stem mass. All of these masses can be expressed either in absolute terms or as allocation, that is, relative to plant mass. Number of stomata and stomatal pore size (μm) were infrequently reported. Five traits related to photosynthesis included photosynthetic rate either as maximum, at saturating light levels (*A*~max~, μmol·m^−2^·s^−1^), and/or net, at growth conditions, photosynthesis (*A*~net~, μmol·m^−2^·s^−1^), stomatal conductance (*g*~*s*~*,* mol·m^−2^·s^−1^), the ratio of internal to external CO~2~ concentration (*C*~*i*~/*C*~*a*~) and water use efficiency (WUE; *A*~net~/*g*~*s*~, mmol·mol^−1^). Lastly, four traits were related to chemical composition, namely nitrogen content either area-based (g·m^−2^) or mass-based (g·g^−1^), chlorophyll content (μmol·g^−1^) and RuBisCO content (g·m^−2^).

To examine the effect of CO~2~ among all species in the study, we performed a weighted ANCOVA for each trait with CO~2~ concentration as covariate, species as a factor, and a potential interaction between the two. To determine the overall effect of CO~2~ on a plant trait, a model without differing slopes between species was fitted when species by CO~2~ interaction was not significant or the average slope from all species was calculated when species by CO~2~ interactions were significant. We used the inverse of the square root of the standard error from the original study as the weighting factor for uncertainty, as is standard in meta-analyses (Hedges and Olkin [@b21]; Sokal and Rohlf [@b47]) For trait values reported without an error term, the average standard deviation in the trait was used to calculate the weighting factor. All traits and CO~2~ concentrations were log-transformed, which improved the normality of the residuals and allowed the output to be considered as scaling slopes (Renton and Poorter [@b41]). We investigated both which traits responded to low CO~2~ and, for those traits that did, what the effect size of that adjustment was.

In the ANCOVA framework, the scaling slope of the trait-CO~2~ relationship then indicates the proportional change in trait value in the following way:

where CO~2~ change is the proportional change in CO~2~ concentration and β is the slope in the log--log plot. For example, if β were 1 then a 50% reduction in CO~2~ concentration would result in a 50% reduction in trait amount. When β is less or \>1, a 50% reduction in CO~2~ will result in a less or more than 50% reduction in trait amount, respectively. A negative slope indicates an increase in trait value with a decrease in CO~2~ concentration. Subsequent to the ANCOVA analysis, differences in slope between C~3~ and C~4~ herbs and woody and herbaceous C~3~ plants were assessed by 2 sample t-tests weighted by 1/SE of the species. All statistics were performed using R, version 2.14.0 (R Foundation for Statistical Computing, Vienna, Austria). Due to the limited number of species for many traits, statistical power tended to be low; however, we judge it important enough to report those results as they reflect the current state of knowledge and to show the lack of data in important traits.

Rather than performing a meta-analysis on the available high CO~2~ experiments ourselves, we searched the literature for highly cited large-scale meta-analyses on plant traits in experimentally elevated CO~2~. From our survey, 5 large meta-analyses emerged involving tens to hundreds of plant species reporting various traits including the 6 traits that were reported for 10 or more species at reduced CO~2~ (Curtis and Wang [@b13]; Poorter and Navas [@b37]; Ainsworth and Long [@b1]; Ainsworth and Rogers [@b2]; Wang et al. [@b50]). From the meta-analyses, we extracted the shift in trait value at nonlimiting resources when available. We then compared this to the projected trait shift when assuming the same proportional response as to low CO~2~.

Results
=======

Of the 21 traits that were reported for 3 or more species, 14 showed either significant variation with CO~2~ or species response to CO~2~. Percentage values in the text below show the proportional change in trait value ± SE upon a 50% reduction in growth CO~2~ concentration (eqn 1). For each trait, species could respond to CO~2~ (adjust their trait value), show consistent variation in trait value between species over a CO~2~ gradient (species intercept or elevation of species line in trait vs. CO~2~ plot) and show significant variation in how species responded to CO~2~ (CO~2~\*species interaction; Table [1](#tbl1){ref-type="table"}). A nonsignificant interaction of species\*CO~2~ for a given trait indicates that different species adjust the trait by the same proportional amount.

###### 

Overview of ANCOVA results on log(trait data) versus log(CO~2~) concentration with species as covariate and as weighting factor. Traits are ordered by number of species analyzed. Slope indicates the average slope of log(trait) versus log(CO~2~) including SE. −50% CO~2~ gives the proportional change in trait given a 50% reduction in CO~2~ concentration as per *Trait change* = *CO*~*2*~ *change*^*β*^*-1* where β is the slope. Values are calculated by slope ± SE

  Trait                           \#Species   \#Studies   Slope           −50% CO~2~        p(CO~2~)   p(species)   p(CO~2~\*species)
  ------------------------------- ----------- ----------- --------------- ----------------- ---------- ------------ -------------------
  WUE (mmol mol^−1^)              26          8           0.95 ± (0.1)    −48.3% ± (3.5)    \*\*\*     \*\*\*       \*\*\*
  *A*~*net*~ (μmol·m^−2^·s^−1^)   25          15          0.7 ± (0.11)    −38.3% ± (4.5)    \*\*\*     \*\*\*       \*\*\*
  DW (g)                          25          14          0.91 ± (0.16)   −46.9% ± (5.8)    \*\*\*     \*\*\*       ns
  SLA (m^2^·g^−1^)                22          17          −0.2 ± (0.08)   +17.2% ± (6.4)    \*\*\*     \*\*\*       ns
  *g*~*s*~ (mol·m^−2^·s^−1^)      17          11          −0.7 ± (0.13)   +59.8% ± (13.9)   \*\*       \*\*\*       \*\*
  *A*~max~ (μmol·m^−2^·s^−1^)     15          9           0.58 ± (0.09)   −33.1% ± (4.3)    \*         \*\*\*       ns
  \% Leaf *N* (g·g^−1^)           10          9           −0.2 ± (0.1)    +17.8% ± (8)      \*\*\*     \*\*\*       ns
  PNUE (μmol·mmol·N^−1^·s^−1^)    10          2           0.22 ± (0.36)   −14.2% ± (21.6)   †          \*           ns
  r/s ratio                       9           3           0.34 ± (0.11)   −21% ± (6.1)      \*\*\*     \*\*\*       \*\*
  Shoot DW (g)                    7           4           0.62 ± (0.14)   −35.1% ± (6.5)    \*\*\*     \*\*\*       ns
  \% Leaf mass                    5           4           −0.1 ± (0.2)    +9% ± (15)        \*         \*\*\*       \*\*\*
  Root DW (g)                     5           4           1.34 ± (0.27)   −60.6% ± (7.5)    \*\*\*     \*\*\*       ns
  Leaf DW (g)                     5           4           0.83 ± (0.54)   −43.9% ± (21.5)   \*\*\*     \*\*\*       \*\*
  *C*~*i*~*/C*~*a*~               4           4           −0.1 ± (0.12)   +6% ± (8.8)       ns         ns           ns
  Chlorophyll (μmol·g^−1^)        4           4           0.19 ± (0.09)   −12.4% ± (5.4)    ns         \*\*\*       ns
  Leaf *N* (g·m^−2^)              4           4           0.23 ± (0.11)   −14.8% ± (6.3)    \*         ns           ns
  \% Stem mass                    4           3           0.08 ± (0.08)   −5.4% ± (5)       ns         \*           ns
  Stem DW (g)                     4           3           1.72 ± (0.83)   −69.7% ± (18.5)   \*\*\*     \*\*\*       \*\*\*
  \# Stomata                      4           2           0.08 ± (0.11)   −5.7% ± (7.3)     ns         \*\*\*       ns
  RuBisCO (g·m^−2^)               3           3           0.37 ± (0.14)   −22.7% ± (7.3)    ns         \*\*         ns
  Pore size (μm)                  3           1           0.12 ± (0.13)   −7.8% ± (8.2)     ns         \*\*\*       ns

*P*-values are ns: not significant; †\<0.1, \*\<0.05, \*\*\<0.01, \*\*\*\<0.001.

Photosynthesis-related traits
-----------------------------

Across the species studied, a 50% reduction in CO~2~ did on average reduce maximum photosynthesis (*A*~max~, μmol·m^−2^·s^−1^) by 33 ± 4% (*P* \< 0.05, 15 species; Fig. [1](#fig01){ref-type="fig"}A) and net photosynthesis (*A*~net~, μmol·m^−2^·s^−1^) comparably by 38 ± 5% (*P* \< 0.001, 25 species; Fig [1](#fig01){ref-type="fig"}B). Next to this, stomatal conductance (*g*~*s,*~ mol·m^−2^·s^−1^) increased by 60 ± 14% (*P* \< 0.01, 17 species; Fig. [1](#fig01){ref-type="fig"}C). The ratio of water loss to carbon gain, intrinsic water use efficiency (*A*~net~ over *g*~*s*~, WUE), decreased by 48 ± 4% (*P* \< 0.001, 26 species; Fig. [1](#fig01){ref-type="fig"}D). For *A*~net~, WUE and *g*~s~ species showed significant variation in trait elevation (*P* \< 0.001) and response to CO~2~ (interaction, *P* \< 0.01). *A*~max~ however showed only significant variation in species trait elevation (*P* \< 0.001).

![Plant trait versus growth CO~2~ concentration (note the double-log scale) of the 6 traits with the highest number of species. (A) Maximum photosynthesis (*A*~max~), (B) Net photosynthesis (*A*~net~), (C) Stomatal conductance (*g*~*s*~), (D) Intrinsic water use efficiency (net photosynthesis over *g*~*s*~, WUE), (E) Plant dry weight, (F) Specific leaf area (SLA). Each line represents the response of a single species. Open symbols: C~3~ metabolism, solid symbols: C~4~ metabolism. Error bars give SE. Different colors represent the different families the species belong to.](ece30003-4525-f1){#fig01}

Growth and allocation
---------------------

A halving of growth CO~2~ concentration resulted in a corresponding reduction in plant dry weight (DW) by 47 ± 6% (*P* \< 0.001, 25 species; Fig. [1](#fig01){ref-type="fig"}E). Aboveground biomass was less reduced than belowground biomass as Shoot DW was reduced by 35 ± 7% (*P* \< 0.01, 7 species) and Root DW by 61 ± 8% (*P* \< 0.001, 5 species). This pattern was reflected in a reduced root/shoot dry matter ratio (r/s ratio) of 21 ± 6% (*P* \< 0.001, 9 species). In contrast, specific leaf area (SLA, m^2^·g^−1^) increased by 17 ± 6% (*P* \< 0.001, 22 species; Fig. [1](#fig01){ref-type="fig"}f) at reduced CO~2~. For root/shoot ratio, there was both significant variation in species trait elevation (*P* \< 0.001) and response to CO~2~ (*P* \< 0.01). For SLA and plant biomass, species showed significant variation in trait elevation but did not respond differently to reduced CO~2~.

Chemical composition
--------------------

Only few data on chemical composition were available, strongly limiting statistical power of our test. The concentration of chlorophyll (μmol·g^−1^, 4 species) and amount of RuBisCO (g·m^−2^, 3 species) were not significantly affected by CO~2~. Nitrogen levels in the leaf showed a contrasting response to halving CO~2~ where leaf nitrogen percent (g·g^−1^) increased by 18 ± 8 (*P* \< 0.001, 10 species) whereas nitrogen content per area (g·m^−2^) decreased by 15 ± 6% (*P* \< 0.05, 4 species). Neither for nitrogen per unit mass nor per unit leaf area did species have significantly different responses to reduced CO~2~.

Differential responses of plant types
-------------------------------------

Due to the small number of available species, the statistical power of the comparison between plant types was limited. Thus, in a few cases, there was only a trend of differential response among C~3~, C~4~ and woody and herbaceous species. Nevertheless, interesting contrasts and similarities emerged. Figure [2](#fig02){ref-type="fig"} shows the contrasting slopes between plant types for the eight plant traits with nine or more species. Between C~3~ and C~4~ herbs, only the greater increase in SLA for C~3~ herbs at reduced CO~2~ was significant (*P* \< 0.01). C~4~ plants showed on average a negligible SLA response to CO~2~. Net photosynthesis and dry weight seemed to be less reduced for C~4~ herbs although with small sample size and large variation this was not significant. Interestingly, plant dry weight of woody species was reduced less by 16% than that of herbaceous C~3~ plants (*P* \< 0.05). Overall, for the traits shown in Figure [2](#fig02){ref-type="fig"}, different plant types appear to show rather similar responses to reduced CO~2~.

![Slope of log(trait) versus log(CO~2~ concentration) for different plant types, C~3~/C~4~ and woody/herbaceous. Open circles, C~3~ herbaceous type; solid circles, C~4~ herbaceous type; open square, C~3~ woody type. ±1 indicates a 1:1 change in a trait for a change in CO~2~ concentration with a negative slope indicating an increase in trait value and a positive slope indicating a decrease in trait value. *A*~max~, maximum photosynthesis (μmol·m^−2^·s^−1^); *A*~net~, net photosynthesis (μmol·m^−2^·s^−1^); *g*~*s*~, stomatal conductance (mol·m^−2^·s^−1^); WUE, water use efficiency (mmol·mol^−1^); DW, plant dry weight (g); SLA, specific leaf area (m^2^·g^−1^); r/s ratio, root DW to shoot DW (g·g^−1^). Numbers between brackets gives the number of species for each plant type. *P*-values between plant types are \*\< 0.05, \*\*\< 0.01.](ece30003-4525-f2){#fig02}

Comparison with elevated CO~2~ experiments
------------------------------------------

Table [2](#tbl2){ref-type="table"} highlights the comparison between trait responses at low CO~2~ to the response at elevated CO~2~ of the six traits that had the most data. When comparing the trait shifts found in five large meta-analyses (Curtis and Wang [@b13]; Poorter and Navas [@b37]; Ainsworth and Long [@b1]; Ainsworth and Rogers [@b2]; Wang et al. [@b50]) to trait shifts extrapolated from the response to low CO~2,~ a few interesting contrasts and similarities emerged. With increasing CO~2,~ the magnitude of shift in *A*~net~ deviated more from the response to low CO~2~; for *g*~*s*~, the shift was similar in magnitude to results found in FACE studies and one growth chamber meta-analysis but not another. While we found no differences between C~3~ and C~4~ plants in water use efficiency at low CO~2~, at high CO~2~ large differences are found. The increase in WUE at high CO~2~ found for C~3~ plants at FACE sites is comparable to our extrapolated response. Whole plant dry weight (DW) appears to increase much less at high CO~2~ then expected based on the low CO~2~ response. SLA, however, seems to be adjusted in a similar magnitude as expected from the response to low CO~2~.

###### 

Comparison of trait shift at high CO~2~ extrapolated from low CO~2~ response (bold values) to actual changes found in three meta-analyses. If the trait adjustments are proportional from past low to future high CO~2~, the predictions from the low CO~2~ experiments should match the measured values from the high CO~2~ experiments. The measured trait shifts are from chamber studies, GC1: Curtis and Wang [@b13] (700 ppm), GC2: Poorter and Navas [@b37] (690 ppm), GC 3: Wang et al. [@b50] (700 ppm) and FACE experiments, FACE: Ainsworth and Long [@b1]; Ainsworth and Rogers [@b2] (560 ppm). Percentage values indicate magnitude of trait shift as compared to current, levels of CO~2~

             GC1 (700 ppm)   GC2 (690 ppm)     GC3 (700 ppm)           FACE (560 ppm)                                                                    
  ---------- --------------- ----------------- ----------------------- ----------------- ---------------------- ----------------- ---------------------- ----------------
  *A*~max~                                                                                                                        +31%                   **+27% ± (5)**
  *A*~net~   +28%            **+63% ± (12)**   +28%                    **+61% ± (12)**   +14%                   **+63% ± (12)**   +26%                   **+34% ± (6)**
  *g*~*s*~   −11%            −**38% ± (6)**                                              −32%                   −**38% ± (6)**    −21%                   −**25% ± (4)**
  WUE                                                                                                                             +68%(C~3~) +6%(C~4~)   **+48% ± (6)**
  DW         +28%            **+88% ± (21)**   +48%(C~3~) +12%(C~4~)   **+86% ± (20)**   +25%(C~3~) −3%(C~4~)   **+88% ± (21)**                          
  SLA                                          −13%                    −**15% ± (5)**    −10%                   −**15% ± (5)**    −6%                    −**9% ± (3)**

Discussion
==========

This meta-analysis seeks to quantify and aggregate current knowledge on plant traits in low CO~2~. Few traits were measured for many species, and data were found for a limited number, 45, of species (Table [1](#tbl1){ref-type="table"}). Due to the limited number of species and trait measurements, comparison between plant types, woody--herbaceous, C~3~--C~4~, was difficult. This limited data set should be taken into account when reviewing the results. Interesting results do however emerge. In response to reduced CO~2,~ plants adjusted both physiological and morphological traits (Figure [1](#fig01){ref-type="fig"}, Table [1](#tbl1){ref-type="table"}). The magnitude of trait adjustment varied among species for 6 of 20 traits examined (Table [1](#tbl1){ref-type="table"}). This suggests that on order to cope with low CO~2~ different species adjust different traits. This species-level heterogeneity in response though was not clearly based on simple functional groups (Figure [2](#fig02){ref-type="fig"}).

Below, we discuss trait shifts at low CO~2~ moving from leaf to ecosystem scales, keeping in mind that all the results discussed below are all short-time scale, plastic responses (Gerhart and Ward [@b18]). Plant plastic response to changing conditions occurs at different levels of organization after different periods of time (Nicotra et al. [@b34]).

Leaf-level responses to low CO~2~
---------------------------------

We found support for our hypotheses at the leaf level. We hypothesized that low CO~2~ would lead to lower photosynthetic rates (*A*), which leads to reduced growth, and that in order to partially ameliorate the photosynthetic rate reduction, plants would have higher leaf nitrogen and larger stomatal conductance (*g*~*s*~) (Sage and Reid [@b46]; Medlyn et al. [@b33]). Focussing first on *A* and *g*~s~, *A*~net~ substantially decreased at a 50% decrease in CO~2~ and *g*~*s*~ increased considerably, indicating that the increase in stomatal conductance is not enough to keep up with lower atmospheric carbon concentration.

Water use efficiency (WUE) decreased proportionally with CO~2~ (following Franks et al. [@b17]) but did show significant variation between species. Such a strong increase in water demand suggests great consequences for plants experiencing drought stress. However, recovery from drought at low CO~2~ was found to be similar between C~3~ (*Abutilon theophrasti*) and C~4~ (*Amaranthus retroflexus*) plants at low CO~2,~ due to less leaf loss and stomatal closure than expected for C~3~ species (Ward et al. [@b51]). Suggesting that there are trait shifts that mitigate some ill effects.

When comparing the magnitude of the response of *A*, *g*~*s*~ and WUE at high CO~2~ to the responses, we found at low CO~2~ a contrasting picture emerges. At low CO~2,~ no difference in WUE was found between plant types, although at high CO~2,~ C~4~ plants increase their WUE less than C~3~ plants (Poorter and Navas [@b37]). For C~3~ plants, the response to high CO~2~ seems similar in magnitude as to low CO~2~ for WUE. For the components of WUE, at high CO~2,~ the adjustment of *A*~net~ was greater in magnitude as to low CO~2,~ whereas the effect on *g*~*s*~ was comparable to low CO~2~, although one meta-analysis reported a far lower decrease in *g*~s~ at high CO~2~ (Table [2](#tbl2){ref-type="table"}). The extent to which *g*~*s*~ can be reduced might be limited though. Leaf thermal regulation, which is impaired at very low stomatal conductance, could put a limit on the possible decrease. Paleo-evidence suggests this may have been relevant during a previous "rapid" transition to a high CO~2~ atmosphere at the Triassic--Jurassic boundary (Mcelwain et al. [@b31]).

At the level of enzymes and leaf chemical composition, we found no evidence that RuBisCO content and chlorophyll content were affected by reduced CO~2;~ the power of our test was limited because few studies measured those traits (Table [1](#tbl1){ref-type="table"}). Leaf nitrogen (N) content per mass did increase but N content per area decreased in response to low CO~2~; this contrasting response might be explained by the higher specific leaf area (SLA) in low CO~2~. A higher SLA indicates lower nitrogen containing mass per area. Whether or not the nitrogen increase per mass is the result of an increase in certain nitrogen-rich chemical compounds or a decrease in carbon-rich compounds, as carbon is a limiting resource, is unclear. Clearly more work is needed on the enzymatic and chemical response of plants to low CO~2~.

Plants adjust their leaf morphology in order to cope with low concentrations of atmospheric CO~2~. At half of ambient CO~2,~ leaf SLA increased by 15%. This increase has two potential advantages to the plant: first, when CO~2~ is limiting, more leaf area per unit C invested in leaves allows for lower carbon costs per unit carbon capture; second, at the leaf level, higher SLA leaves may improve mesophyll conductance (Vitousek et al. [@b49]). While increased *g*~*s*~ at low CO~2~ can maintain internal CO~2~ concentration up to a point, at low CO~2~ concentrations the diffusion of CO~2~ inside the leaf can become limiting to photosynthesis as well (Keenan et al. [@b24]). Higher SLA indicates either thinner or less dense leaves with more internal air space, which in many cases leads to greater mesophyll conductance to CO~2~ (Loreto et al. [@b30]). However, a higher SLA could also be a result of less starch or less other nonstructural carbohydrate present in the leaf at low CO~2~ concentrations (Poorter et al. [@b38]). It is interesting to find that at high CO~2,~ SLA follows the same trend as at low CO~2~. The relative contributions of the above factors to reducing and increasing SLA are an interesting avenue to pursue further.

Plant-level responses to low CO~2~
----------------------------------

While plants adjust their gas exchange and leaf morphology in response to reduced CO~2,~ photosynthetic rates are nevertheless reduced, resulting in less biomass but also shifts in allocation between root and shoot. Plant biomass (g dry weight) decreases proportionally at a 50% CO~2~ reduction, which is more pronounced in belowground biomass as is illustrated by a reduction in root-to-shoot ratio. This could be the result of plants balancing their nutrient gain and their carbon gain to the now more limiting carbon resource (Bloom et al. [@b5]; Chapin et al. [@b9]) or some specific source-sink relationship between root and shoot, that is, fixed in the plant\'s metabolism, similar to the idea of a fixed *c*~*i*~*/c*~*a*~ ratio for species across time (Ehleringer and Cerling [@b14]; Gerhart et al. [@b19]; Franks et al. [@b17]). At low CO~2,~ photosynthesis per area is lower, so the amount of sugars available for the roots is less per unit of shoot biomass. This shift in allocation at low CO~2~ may have important implications for species interactions, particularly in tree--savanna grass interactions (Bond and Midgley [@b6]): at low CO~2,~ the regrowth capacity following disturbance of tree species is much diminished, adding weight to the importance of fire and herbivory as ecosystem shaping factors (Kgope et al. [@b25]; Bond and Midgley [@b6]). Next to allocation, the increased SLA at low CO~2~ might lead to greater food availability and thus pressure from herbivores as high SLA leaves are eaten more readily (Poorter et al. [@b38]). Faster decomposition rates and nutrient cycling of high SLA leaves would also have large ecosystem effects by allowing faster nutrient cycling (Cornelissen et al. [@b10]).

Plant types, growth environments, and low CO~2~ response
--------------------------------------------------------

Differences between C~3~, C~4~, woody, and herbaceous species were not as pronounced as hypothesized. Results suggested differences between plant types although the responses of only few traits were significantly different. C~3~ herbs had a significantly greater increase in SLA than C~4~ herbs, which on average showed no response. Decreases in biomass diminished starting from herbaceous C~3~, woody C~3~ to herbaceous C~4~. However, only the difference between woody and herbaceous C~3~ was significant with woody plants having a smaller reduction in biomass at low CO~2~. This result mirrors that at high CO~2~ experiments where increased CO~2~ generally leads to a greater relative growth rate (RGR) increase for fast growing, herbaceous, plants than slow growing, woody, plants (Poorter and Navas [@b37]). As fast growers "win" more at high CO~2~ they "lose" more at low CO~2~. While the smaller decrease in biomass for herbaceous C~4~ than for C~3~ is not significant, it should be noted that the average reduction in *A*~net~ and *A*~max~ is also lower than in C~3~ herbs. This may point to a smaller reduction in biomass accumulation for C~4~ herbs via a smaller reduction in photosynthesis. With more data on woody and C~4~ species, such differences between plant types and their underlying mechanism may become more apparent.

The results presented here summarize the effects of low CO~2~ at high water and high nutrients. One important caveat to consider, however, is that that there are many potential interactions between CO~2~, water, and nutrients as is shown by some studies. Low nutrients in the form of low P limited photosynthetic rates even further at low CO~2~ in *Lupinus albus* (Campbell and Sage [@b8]) and *Populus deltoides* (Lewis et al. [@b29]). C~3~ (*Abutilon theophrasti*) and C~4~ (*Amaranthus retroflexus*) plants recovered similarly from drougth at low CO~2~ (Ward et al. [@b51]). This shows that other environmental factors strongly influence the effect of CO~2~ on plant traits. However, most data were available for well-watered, high-nutrient growth experiments. The interactions between CO~2~, light, nutrients and water are clearly important when extrapolating from growth chamber experiments to glacial environments, but a full understanding of the interactions would require many more or more extensive studies.

Experimental results presented here on plastic responses need to be put into context with other sources of information on plant traits in the past including measurements on paleomaterials. In the past, CO~2~ has proven to be a strong selective agent altering worldwide floristic composition (McElwain et al. [@b32]). Thus, evolution and selection have likely occurred with increasing CO~2,~ and it is therefore important to determine whether the traits of modern plants grown under low CO~2~ compare to the traits of plants that lived in a low CO~2~ atmosphere. The regeneration of *Silene stenophylla* buried in Siberian permafrost for over 30 ka (Yashina et al. [@b52]) provides an interesting opportunity for testing the response of modern plants and ancient plants to low CO~2~ and how similar they are. It is also likely that in the period since the low CO~2~ in the Last Glacial Maximum (LGM), species with short generation turnover have evolved more compared with long generation turnover species, although the drastic increase from 280 to 700 pmm within 250 years (1850--2100) will likely constrain the values to which traits have been adjusted. A full understanding of plant response to the transition from the LGM to current and future CO~2~ levels must include both evolutionary adaptation and plastic responses.

Conclusion
==========

In conclusion, we found that, despite the more limited set of low CO~2~ studies compared with high CO~2~ studies, a general response is emerging. Plant response to reduced atmospheric CO~2~ involves a complex suite of trait adjustments. In order to diminish the effects of reduced CO~2~ plants open their stomata wider, invest more in aboveground biomass and increase their SLA. Despite these adjustments, photosynthetic rate is nevertheless reduced, leading to a proportional reduction in biomass accumulation. Both trait adjustment and growth effect varies among species, but this variation does not appear to be a function of simple plant functional groups. Trait adjustments at low CO~2~ as compared to high CO~2~ were proportionally similar for *g*~*s*~, WUE and SLA but responses at low CO~2~ were greater than proportional for *A*~*net*~ and biomass. In other words, the data suggest that in terms of water relations and leaf morphology, the responses to low and high CO~2~ are proportional and opposite. Carbon gain and whole plant growth rate are more complex---responses to low CO~2~ in these cases are more extreme. At high CO~2,~ other factors such as nutrient and light availability could control these traits. To understand the response of plants to future high CO~2,~ it is important to understand how and when other factors become drivers for certain traits. Our understanding of plant response to CO~2~ benefits from data from both low and high CO~2~ conditions. The shape of that response will become increasingly relevant in a high CO~2~ future.

This study was financially supported by Grant 142.16.3032 of the Darwin Center for Biogeosciences to R. Aerts. This is publication number DW-2013-1005 of the Darwin Center for Biogeosciences, which partially funded this project.

Conflict of Interest
====================

None declared.

Supporting Information
======================

Additional Supporting Information may be found in the online version of this article:

**Table S1.** Overview of trait measurements reported for three or more species. **V**: Traits reported with error value, **X**: Traits reported without SE. Traits are ordered from most to least measured in low CO~2~ studies. SLA/LMA, specific leaf area or recalculated leaf mass per area (g·m^−2^); *g*~*s*~, stomatal conductance (mol·m^−2^·s^−1^); DW, plant dry weight (g); *A*~max~, maximum photosynthesis (μmol·m^−2^·s^−1^); *A*~net~, net photosynthesis (μmol·m^−2^·s^−1^); WUE, water use efficiency (mmol·mol^−1^); PNUE, photosynthetic nitrogen use efficiency (μmol·mmol·N^−1^·s^−1^); r/s ratio, root-to-shoot ratio DW; C~i~/C~a~, ratio intercellular to atmospheric CO~2~; % Leaf *N*, percentage *N* per weight; % Leaf mass, percentage leaf DW of total DW; Root DW, root dry weight (g); Leaf DW, leaf dry weight (g); Chlorophyll, chlorophyll content (μmol·g^−1^); Leaf *N*, N per area (g·m^−2^); %Stem mass, percentage stem mass of total weight; RuBisCO, RuBisCO content (g·m^−2^); Shoot DW, shoot dry weight (g); %Root DW, percentage root DW of total DW; Pore size, diameter of stomatal pore (μm).

**Data S1.** Meta-analysis data sheet compiled and used for this paper.

**Data S2.** Column headers used in the meta-data file with their description and meaning.

[^1]: **Funding Information** This study was financially supported by grant 142.16.3032 of the Darwin Center for Biogeosciences to RA.
