Introduction

Considerable research has been devoted to understanding the effects of elevated atmospheric CO2 and climate warming on physiological responses of plants and the resulting effects on growth and survival (e.g., Drake et al. 1997; Ward and Strain 1999; Anderson et al. 2001; Ainsworth and Rogers 2007; Reich et al. 2018). Experiments investigating the impact of elevated CO2 (eCO2) have shown enhanced photosynthetic rates (A), reductions in stomatal conductance (gs), and increased water use efficiency (WUE) in a variety of species (Knapp 1993; Owensby et al. 1993; Jackson et al. 1994; Garcia et al. 1998; Ainsworth and Rogers 2007; Xu et al. 2013), which generally leads to an increase in plant productivity (Drake and Leadley 1991; Jacob et al. 1995; Drake et al. 1996). In cold climates limited by growing season temperatures, experimental warming of air and soil can positively affect gas-exchange rates and plant productivity due to enhanced metabolic rates early in spring and an increase in the length of the growing season (Ibáñez et al. 2010; Reich et al. 2018; May et al. 2020). However, during droughts or dry periods of the growing season, any positive effects of warming can be dampened or even eliminated by soil water limitation due to low precipitation and/or high rates of evapotranspiration (Reich et al. 2018; Wilschut et al. 2022). While the individual effects of warming and eCO2 are relatively well-understood, few manipulative studies have directly assessed their interactive effects on plant communities, despite model analyses suggesting that these factors will interact and affect species in ways that are not necessarily predictable given the results of single-factor experiments (e.g., Luo et al. 2008).

The magnitude and direction of plant physiological responses to variation in environmental conditions are species-specific and often differ significantly depending on whether a species uses the C3 or C4 photosynthetic pathway. Warmer conditions tend to favor C4 species over C3 species since C4 species concentrate CO2 around Rubisco and diminish O2 competition around its active site, thus largely eliminating photorespiration (Long 1999; Sage et al. 1999). When well-watered, C4 plants have lower gs, and higher A and WUE than C3 plants (Ripley et al. 2010; Taylor et al. 2011), and have been shown to maintain high photosynthetic rates even under conditions of low resource availability such as limited water or soil nitrogen (Knapp and Medina 1999). In both temperate climates and the tropics, C4 grasses dominate in permanent and seasonally waterlogged environments where woody plant establishment and maintenance cannot occur (Piedade et al. 1994; Long 1999). However, plants growing in tidal wetlands often deal with salinity stress, as well as periods of both flooded and relatively dry conditions depending on the time of year. Stomata tend to exhibit similar responses to drought and salinity, with declines in gs occurring with both higher aridity and salt stress making it difficult to predict how plants growing in salt marshes will respond physiologically to inundation under brackish conditions (Chaves 1991; Wang et al. 2003).

Elevated atmospheric CO2 conditions tend to stimulate photosynthetic rates (Sage 1994; Jacob et al. 1995; Sage and Cowling 1999). However, this stimulation of A tends to be limited when plants are in suboptimal conditions such low nutrient status (Sage 1994). WUE of both C3 and C4 species increases under eCO2 conditions through reduced gs, but the effects are much more pronounced for C3 plants (Wand et al. 2001). Previous work in Free-Air CO2 Enrichment (FACE) experiments saw a decrease in gs of 22% on average, while declines of approximately 40% were found greenhouse and chamber experiments (Curtis and Wang 1998; Morison and Lawlor 1999; Ainsworth and Rogers 2007). This reduction in gs is common in response to eCO2 (Medlyn et al. 2001) and may impact photosynthetic rates by increasing the barrier to CO2 diffusion into the leaf (Bernacchi et al. 2003). Additionally, because of the decline in gs under eCO2 there is also a decline in transpiration and heat loss, causing leaf temperatures to rise (Kim et al. 2008; Šigut et al. 2015). Because of this, the combination of high temperatures and eCO2 may have an antagonistic effect and exaggerate heat damage to the photosynthetic apparatus due to the decline in latent heat lost as water vapor in response the decline in gs (Jiahong et al. 2009; Warren et al. 2011).

This study took place in a brackish marsh that is dominated by the C3 sedge Schoenoplectus americanus and two C4 grasses, Spartina patens and Distichlis spicata. A well-established limitation of working with the dominant plant species in many salt marsh habitats, in particular sedges such as S. americanus, is that gas exchange is not easily measured with commonly-used physiological instruments (more details in Materials and Methods section). Due to this limitation, we chose to focus our efforts on making relatively simple in situ measurements of stomatal conductance and chlorophyll fluorescence variables (e.g., electron transport rate, quantum efficiency of PSII photochemistry) which can be used make indirect inferences about plant photosynthetic productivity and water use efficiency. For example, stomata adjust their rates of conductance in response to changes in atmospheric CO2 concentrations, soil water availability, temperature, and light (Lu and Zeiger 1994; Hetherington and Woodward 2003; Perez-Martin et al. 2009; Hubbard et al 2013; Šigut et al. 2015), and many studies have found positive correlations between gs, A, and accumulation of biomass (Cornish et al. 1991; Franks 2006; Kattge et al. 2009; Cernusak et al. 2011; Drake et al. 2013). Likewise, when plants experience environmental stress (e.g., salinity, heat stress), they often exhibit reduced photosynthesis and electron transport rates (ETR) to avoid damage caused by excess absorbed energy (Kato et al. 2003; Adams et al. 2004), while the quantum efficiency of PSII photochemistry (Fv/Fm) tends to decline (Björkman and Demmig 1987; Posch and Bennett 2009), leading to positive correlations between these traits (Wong et al. 2014; Yang et al. 2017).

This light-induced inhibition of photosynthetic machinery occurs whenever light exceeds the amount of energy needed to drive photosynthetic processes (Murata et al. 2007; Guidi et al. 2019). Salinity, high temperatures, low soil nutrient status, and other abiotic plant stressors can affect the point at which light becomes excessive, causing accelerated PSII photoinhibition compared to unstressed plants (Adir et al. 2003; Melis 1999). A decline in the Fv /Fm ratio is considered to be a good indicator of photoinhibition, which may result from damage to the PSII reaction centers or an increase in the rate of energy dissipation (Öquist et al. 1992). PSII photoinhibition has been shown to slow down ETR and prevent reactive oxygen species (ROS) from forming, preventing damage to the PSII reaction centers (Tikkanen et al. 2014). Recent research also suggests that abiotic stress directly inhibits the repair of PSII reaction centers after light-induced damage occurs (Kangasjärvi et al. 2012; Nishiyama and Murata 2014). Thus, the extent of damage depends on the balance between photodamage caused by the generation of ROS and PSII repair mechanisms (Demmig-Adams et al. 2012).

The goal of this study was to directly assess the interactive effects of warming and eCO2 on the plasticity of leaf physiological traits related to A and WUE, and thus plant growth and survival. We compared physiological responses of dominant salt marsh species exposed to ambient air and soil temperatures or heated to 1.7, 3.4, and 5.1 °C above ambient, as well as the response of the C3 sedge to ambient and elevated carbon dioxide levels. We tested the following hypotheses:

  1. (1)

    Rates of gs will be positively correlated with Fv /Fm, ETRmax, and saturating light (PPFDsat), with higher values attributable to increased CO2 availability when stomata are open and lower values related to photoinhibition and oxidative stress caused by a reduction in evaporative heat loss when stomata are closed.

  2. (2)

    C3 sedges growing under eCO2 will have reduced rates of gs, which will reduce evapotranspiration and lead to heat stress, consequently affecting the point at which light becomes excessive and leading to reduced ETR and Fv /Fm.

  3. (3)

    Both C3 and C4 plant communities will experience reductions in gs, ETR, and Fv /Fm in response to warming, but the response of the C3 sedge will be more pronounced due to the need for C3 plants to close stomata to minimize water loss under high temperatures.

  4. (4)

    The most significant declines in gs, ETR, and Fv /Fm will occur in sedges grown under 5.1 °C above ambient + eCO2 conditions.

Materials and Methods

Site and species descriptions

Our experiment was located in the Smithsonian’s Global Change Research Wetland (GCReW), which is part of the tidal, brackish Kirkpatrick Marsh that runs along the western shore of the Chesapeake Bay, United States (38°53’ N, 76°33’ W). Flood frequency varies across the high marsh site, but the soils are typically saturated to within 5 to 15 cm of the soil surface. Two plant communities largely dominate the site: the first is a C3 sedge community that consists primarily of Schoenoplectus americanus (Pers.) Volkart ex Schinz & R. Keller, while the second is primarily comprised of two C4 grasses, Spartina patens (Aiton) Muhl and Distichlis spicata (L.) Greene. The higher elevation areas of the marsh that flood during 10 to 20% of high tides are dominated by the C4 grass community, whereas the lower elevation areas that flood during 30 to 60% of high tides are dominated by the C3 sedge community. These species are rhizomatous perennials that reproduce sexually by seed and via vegetative sprouting from rhizomes. Aboveground biomass dies back each winter and is replaced by new growth each spring.

Experimental design

The Salt Marsh Accretion Response to Temperature eXperiment (SMARTX) was established within the GCReW site in 2016 (Noyce at el. 2019). The experiment consists of six replicate transects, three located in the C3 sedge community and three located in the C4 grass community. Each transect consists of four 2 × 2 m plots: an unheated ambient plot, and plots that are heated to 1.7, 3.4, and 5.1 °C above ambient. Each plot is surrounded by a 0.2 m buffer to minimize edge effects and transects were positioned in the marsh to have similar plant composition along their length. Experimental warming of soil and plant-surface temperatures is carried out using vertical resistance cables belowground (which warm to a soil depth of 1.5 m) and infrared heaters aboveground. Four to six 1,000-W heaters (FTW-1000, Mor Electric Heating Assoc. Inc., Comstock Park, MI) are installed within each heated plot. Concurrent above- and belowground warming provides a more realistic treatment than does either in isolation since growing season soil temperatures are likely to mirror changes in air temperature. To maintain the temperature gradient across plots, we used integrated microprocessor-based feedback control to generate a fixed temperature differential from ambient for each plot. We began warming on June 1, 2016 and have continued 365 days per year since the initial start date.

In the C3 sedge community, there are six additional 2-m-diameter plots, each consisting of an open-top, elevated carbon dioxide (eCO2) chamber. Three chambers are at ambient temperatures and three are warmed to 5.1 °C above ambient, using the vertical resistance cables and infrared heaters described above. Target atmospheric CO2 concentrations of 750 to 800 ppm are maintained within each chamber using K30 sensors (CO2Meter Inc., Ormond Beach, FL) with continuous feedback control. CO2 concentrations are manipulated only during daylight hours of each growing season: 2017 from April 11-November 30, 2018 from April 26-December 6, 2019 from April 23-November 18, 2020 from April 14-December 11, 2021 from April 20-Novermber 27, and 2022 from April 26-November 28.

Across the duration of the experiment, the species composition in one of the C4-dominated transects transitioned into a mix of both C3 S. americanus and C4 S. patens and D. spicata as the C3 sedge encroached into the plots. Thus, in 2019 and later, we measured both plant types in these four plots.

Stomatal Conductance

A well-established limitation of working with the dominant plant species in the GCReW site is that they do not lend themselves to leaf-level gas-exchange measurements with commonly-used physiological equipment such as the LI-6400 (LI-COR, Lincoln, NE). This is particularly true of the C3 sedge, which typically reacts to being enclosed in the LI-6400 leaf chamber with complete stomatal closure, and therefore it can take upward of 60 min to make a single measurement. Due to these limitations, we chose to focus our efforts on making relatively simple, in situ measurements of instantaneous stomatal conductance (gs) with a non-destructive, hand-held SC-1 leaf porometer (Decagon Devices, Pullman, WA). From these measurements, we can make indirect assumptions about plant photosynthetic productivity and water use efficiency since these traits are linked to the dynamic range of stomatal conductance (Drake et al. 2013). For example, the upper limit of rates of CO2 assimilation for plants growing in high light and under low evaporative demand conditions is most often determined by maximum rates of stomatal conductance.

Similar to most leaf physiological equipment, the SC-1 porometer is designed for use with broadleaved plants, so it was necessary to flatten a portion of the triangular cross-section of each C3 sedge shoot prior to measuring. To determine if this minor shoot damage, or repeated measurements of the same shoot over subsequent days of measuring, had any effect on gs, a set of preliminary measurements were made over a two-week period in 2017. We found no significant differences between measurements made immediately following the flattening of shoots and shoots that were sampled repeatedly over the preliminary testing period (p > 0.05).

Rates of gs were measured between the hours of 08:00 and 14:00 on warm, sunny days across the growing seasons of 2017–2019 and 2021–22 (the COVID-19 pandemic prevented measurements from being made in 2020). Measurement dates varied from year to year, but generally they spanned a period of eight weeks per summer. Only 2017 measurements occurred over a shorter time period of three weeks. Prior to the start of measurements each year, we systematically designated three physiological sampling areas per plot (hereafter referred to as clusters), so as to minimize the number of shoots subjected to this minimal shoot damage, as well as to avoid portions of the plant biomass being used by other researchers. Each daily set of measurements utilized plants growing in one of the three clusters, and we alternated to the next cluster on the subsequent measurement date. In C3 plots, three shoots per cluster were randomly chosen for measurement each day, with gs measured on the top third of the shoot while avoiding any insect damage or sections that were senescing. In C4 plots, three measurements per cluster were made by selecting 3–5 blades of grass and laying them side-by-side to fill the chamber of the porometer. We varied the plant community and transect where measurements began each day to ensure that different plants were measured in the late morning/early afternoon to account for any mid-day depression or other factors that could affect physiological traits.

Chlorophyll Fluorescence

Maximum Quantum Efficiency of PSII Photochemistry

In 2018, we used a FluoroPen FP 110 (Photon System Instruments, Drásov, Czech Republic) to make rapid, nondestructive measurements of chlorophyll fluorescence. Measurements were made between the pre-dawn hours of 01:00 and 05:00, typically following warm, sunny days. Following similar sampling protocols as above, we randomly chose three C3 shoots per cluster each measurement day, or made three C4 measurements by selecting 3–5 blades to lay side-by-side to fill the leaf clip of the FluoroPen, to measure the maximum quantum efficiency of PSII photochemistry (Fv/Fm).

$${F}_{v}/{F}_{m}=\frac{{F}_{m}-{F}_{o}}{{F}_{m}}$$
(1)

where Fo is the minimum fluorescence yield of dark-adapted leaves and Fm is the maximum dark-adapted fluorescence yield when a saturating light pulse of 3000 µmol m−2 s−1 is applied to the leaf (Schreiber and Bilger 1993). The difference between Fo and Fm is the variable fluorescence, Fv. The value of Fv/Fm is highly consistent for unstressed C3 leaves, with values of approximately 0.83, and has been shown to correlate well with the maximum quantum yield of photosynthesis (Demmig and Bjӧrkman 1987). Several studies have observed Fv/Fm values of 0.80–0.81 for C4 plants under typical growth conditions where plants may be under minimal light or water stress (Jiang et al. 2011; Romanowska et al. 2017), so we assume that C4 plants also have an optimum Fv/Fm of approximately 0.83. Plants growing under limiting conditions such as heat stress, salinity stress, or drought stress, tend to exhibit lower values of Fv/Fm due to photoinhibition, or inactivation damage of PSII (Long et al. 1994).

Light-Response Curves

In 2019 and 2021–22, we measured light-response curves using a light curve program of the FluoroPen FP 110. We randomly chose one C3 shoot per cluster each measurement day, or made one C4 measurements by selecting 3–5 blades to lay side-by-side to fill the leaf clip of the FluoroPen. Leaves were dark-adapted for 20–40 min, then exposed to actinic light intensities of 0, 100, 200, 300, 500, and 1000 µmol m−2 s−1 in successive 30 s steps. The initial measurement of the dark-adapted leaf at 0 µmol m−2 s−1 photosynthetic active radiation (PPFD) is the equivalent of the pre-dawn Fv/Fm measurements described in the previous section. At each stepwise increase in light intensity, the effective quantum yield of PSII (ΔF/Fm′) was measured.

$$\Delta F/{F}_{m}^{\prime}= \frac{{F}_{m}^{\prime}- F}{{F}_{m}^{\prime}}$$
(2)

where F is the fluorescence yield of the light-adapted sample, Fm′ is the maximum light-adapted fluorescence yield when a saturating light pulse of 3000 µmol m−2 s−1 is superimposed on the current light intensity level of the light curve program.

The apparent rate of photosynthetic electron transport of PSII (ETR) was calculated as:

$$ETR= \Delta F/{F}_{m}^{\prime}*PPFD*0.5*0.84$$
(3)

where the 0.5 value assumes equal excitation of both PSII and PSI photosystems and the 0.84 value is the ETR correction factor, which accounts for the proportion of incident light that is absorbed by the photosystems. We chose to use the empirical mean reflection factor of 0.84 (Ehrlinger 1981) because no specific reflection factors were known for the species in this study, and no anatomical structures that would affect this value such as trichomes or waxy cuticles were present.

The \(\Delta F/F_m^{\prime}\) versus PPFD curves were mathematically fitted using a double exponential decay function, as provided by SigmaPlot (SPSS Inc., San Rafael, CA):

$$f\left(x\right)=m+ {ae}^{-bx}+{ce}^{-dx}$$
(4)

where a, b, c, d, and m are independent parameters. To determine the cardinal points of the light response curves, ETR versus PPFD data were fit using a single exponential function in SigmaPlot:

$$f\left(x\right)=a\left(1- {e}^{-bx}\right).$$
(5)

From the results of Eq. 5, cardinal points can be determined with a = ETRmax and PPFDsat is reached at 0.9ETRmax (Rascher et al. 2000).

Statistical Analyses

Mixed effects analyses of variance (ANOVAs) were used to determine the treatment effects on stomatal conductance and chlorophyll fluorescence traits. Models included the following independent variables: year, plant community, warming treatment, CO2 treatment, and all 2- and 3-way interactions among variables. Plot was added to each model as a random effect with each plot having a unique identifying number. We ran multiple models for each measured trait because not all plant types were measured in all growing seasons; C3 sedges were measured in 2017–19 and 2021, C4 grasses were measured in 2018–19 and 2021–22, and C3 sedges encroaching into the C4 plots were measured in 2019 and 2021–22. Additionally, the eCO2 treatment is only present in the C3 sedge community, so a separate model was used to look at the interactive effects of warming and CO2 on the sedge community. In all cases, we used the fullest model possible, meaning some measurements were used in more than one analysis. For example, S. americanus measurements made in the warming treatment (under ambient CO2 conditions) were included in analyses comparing C3 and C4 plants responses to warming, as well as in analyses comparing C3 plant responses under ambient and elevated CO2. ANOVA tables and fixed effect results for each model are provided. Bivariate relationships among traits were analyzed using linear regressions with all analyses conducted in JMP statistical analysis software (JMP 15.0, SAS Institute, Cary, NC, USA).

Results

Environmental Conditions

Since the experiment began in 2016, mean growing season air temperature has not differed dramatically among years, though 2018 and 2019 averaged approximately 0.5 °C higher than other years (Table 1). Precipitation regime, however, has varied from year to year, with 2018 and 2022 being wetter and other years receiving 35% less rain on average (Table 1). Water depth and salinity also differed by year, but neither measure was significantly related to the total amount of precipitation that fell.

Table 1 Growing season (May–September) environmental conditions of measurement years calculated using SERC Meteorological Data (Chitra-Tarak et al. 2019). Temperature means ± SE were calculated using the daily average of ambient plots from 08:00 to 08:00 so we could investigate the effects of temperature for the 24-h period prior to measurements beginning. Precipitation is the total rainfall received from May through September. Water depth and salinity means ± SE were calculated using the daily average of ambient plots in each plant community
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Stomatal Conductance

Rates of gs varied significantly across year and plant community (C3, C4, and C3 encroaching into C4 plots) in all statistical models (P < 0.001, Table 2 and Fig. 1). Interestingly, rates of gs were 15–20% higher on average for S. americanus sedges encroaching into the higher elevation C4 plots compared to sedges in the lower elevation C3 plots in 2019 and 2021, but rates were similar across elevations in 2022. Rates of gs of C3 sedges encroaching into the C4 plots were negatively affected by warming, (P < 0.01, Table 2 and Fig. 1), with a generally similar negative effect across all years of the experiment as indicated by the weak Year x Warming treatment interaction terms in models including those measurements. Stomatal conductance in the C4 grasses were affected least by the warming treatment, and in some cases seemed to exhibit a modest positive response to the + 1.7 and + 3.4 °C treatments (Fig. 1).

Table 2 Mixed effect ANOVA results for stomatal conductance measurements made from 2017–2022 in the Salt Marsh Accretion Response to Temperature eXperiment (SMARTX). Four analyses were run since not all plant communities were measured in all four years. P < 0.05 are indicated in bold
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Fig. 1
figure 1

Changes in stomatal conductance in response to warming and CO2 measured in 2017–2019 and 2021–2022 (n = 273, 1756, 1733, 2443, and 2058, respectively). Open circles represent plants growing under ambient CO2, closed circles represent plants growing under elevated CO2, open triangles represent C3 sedges that began encroaching into C4 plots beginning in 2019, and error bars represent ± 1SE. Note the difference in y-axis scale between the C3 and C4 plant communities. Letters show results of Tukey–Kramer HSD tests looking for warming and CO2 effects within each measurement year; capital letters in the top row show results for C3 sedges growing in C4 plots and lowercase letters show results for C3 sedges in C3 plots. ANOVA results are provided in Table 2

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Warming also had a significant negative effect on gs of S. americanus growing in the C3 plots, whether the sedges were growing under ambient or elevated CO2 (eCO2) conditions (P < 0.05, Table 2 and Fig. 1). However, the eCO2 treatment caused a significant reduction in gs of 15% on average for C3 S. americanus, with a similar decline regardless of whether they were growing under ambient or + 5.1 °C warming in 2018, 2019, and 2021 (P < 0.001, Table 2 and Fig. 1). It was only in 2022 that the most significant reduction in gs was observed in sedges growing in the warmed x eCO2 interaction plots (Fig. 1).

Chlorophyll Fluorescence

Fv/Fm measured during pre-dawn hours in 2018 was unaffected by both warming and eCO2 (Appendix Table 5 and 6). Values of Fv/Fm for C3 sedges were similar to values reported for unstressed leaves (approximately 0.83; Demmig and Bjӧrkman 1987), while values for C4 grasses were slightly lower, indicating very mild stress. However, it appears that if plants were under any type of heat, light, salinity, or inundation stress during the day in these plots, they were able to successfully recover overnight.

In 2019–2022, when Fv/Fm was measured on dark-adapted leaves during daylight hours, we found that the C3 sedges showed the least amount of stress on average (Fv/Fm values were closest to the 0.83 known value for unstressed leaves; Fv/Fm growing season average = 0.79), followed by the C3 sedges encroaching into C4 plots (Fv/Fm average = 0.77), and the C4 grasses showed the highest degree of stress (Fv/Fm average = 0.67). We observed a significant decline in Fv/Fm with warming in all plant communities in aCO2, indicating higher levels of plant stress under warmer growing conditions (P < 0.05, Table 3 and Fig. 2). The eCO2 treatment had no effect on C3 sedges in 2019 and 2021, and did not appear to cause any form of additional plant stress (Table 3 and Fig. 2). However, in 2022, Fv/Fm was significantly reduced in the eCO2 treatment indicating a higher level of stress in these plants (Year x CO2 interaction P < 0.01).

Table 3 Mixed effect ANOVA results for maximum quantum efficiency of PSII photochemistry (Fv/Fm) measurements made from 2019–2022 on dark-adapted leaves in the Salt Marsh Accretion Response to Temperature eXperiment (SMARTX). Two analyses were run since the elevated CO2 treatment is only in the C3 community. P < 0.05 are indicated in bold, P < 0.10 are italicized
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Fig. 2
figure 2

Changes in maximum quantum efficiency of PSII photochemistry (Fv /Fm) in response to warming and CO2 measured in 2019, 2021, and 2022 on dark-adapted leaves (n = 328, 580, and 664, respectively). Open circles represent plants growing under ambient CO2, closed circles represent plants growing under elevated CO2, open triangles represent C3 sedges that began encroaching into C4 plots beginning in 2019, and error bars represent ± 1SE. Note the difference in y-axis scale between the C3 and C4 plant communities. Letters show results of Tukey–Kramer HSD tests looking for warming and CO2 effects within each measurement year; capital letters in the top row show results for C3 sedges growing in C4 plots and lowercase letters show results for C3 sedges in C3 plots. ANOVA results are provided in Table 3

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ETRmax and PPFDsat varied significantly across year and plant community (C3, C4, and C3 encroaching into C4 plots) in all statistical models (P < 0.001, Table 4, Appendix Table 7). Rates of ETRmax and PPFDsat were 20–30% higher in 2019 than in 2021 and 2022, and were also 20–30% higher in the C3 sedges than in the C4 grasses in all years (Fig. 3). In the ETRmax model that included all three plant communities, we found a significant negative effect of warming (P < 0.05), and in the model solely for the C3 sedge community, we found that both + 5.1 °C warming and eCO2 caused significant declines in electron transport of PSII (P < 0.01, Figs. 2, 3 and 4). PPFDsat was unaffected by warming in all plant communities, but did decline significantly in C3 sedges grown under eCO2 conditions (P < 0.001, Fig. 4, Appendix Table 7). Across all years and plant communities, we found significant positive relationships between gs and Fv/Fm, ETRmax, and PPFDsat (Figs. 5 and 6).

Table 4 Mixed effect ANOVA results for the apparent rate of maximum photosynthetic electron transport of PSII (ETRmax) measurements made in 2019 and 2021–22 in the Salt Marsh Accretion Response to Temperature eXperiment (SMARTX). Two analyses were run since the elevated CO2 treatment is only in the C3 community. P < 0.05 are indicated in bold
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Fig. 3
figure 3

Light response curves of C3 S. americanus and C4 grasses measured in 2019, 2021, and 2022. Plants were dark-adapted for 30 + minutes prior to measurements. The top row of panels represents C3 plants, the middle row of panels show C3 plants encroaching into C4 plots, and the bottom row of panels is C4 plants. Open circles/solid lines represent ambient temperatures, closed triangles/long dashed lines are + 1.7 °C above ambient, open triangles/short dashed lines are + 3.4 °C above ambient, and closed circles/dotted lines are + 5.1 °C above ambient. The numbers to the right of the fitted curves give the maximum rate of electron transport (ETRmax ± SE) for each warming treatment and the dashed vertical lines show PPFDsat ± SE (i.e., PPFD at 90% of ETRmax). Only one PPFDsat value (left of vertical dashed line) is shown for each plant community in a given year because there was no significant effect of warming; ANOVA results are provided in Table 4 and Appendix Table 7. Letters show results of Tukey–Kramer HSD tests looking for warming effects for each community within a measurement year

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Fig. 4
figure 4

Light response curves of C3 S. americanus growing under warming and eCO2 treatments in 2019, 2021 and 2022. Plants were dark-adapted for at least 30 min prior to the start of measurements. The top row of panels represents plants growing under ambient temperatures and the bottom row of panels represents plants growing in + 5.1 °C above ambient. Symbols refer to the CO2 treatment: open circles/solid line fits represent ambient CO2 (aCO2) and closed circles/dashed line fits are elevated CO2 (eCO2). The numbers at the dotted horizontal lines give the maximum rate of electron transport (ETRmax ± SD) of aCO2 plants and the numbers at the dashed horizontal lines give ETRmax (± SD) of eCO2 plants. The dotted vertical lines show PPFDsat (i.e., PPFD at 90% of ETRmax) of aCO2 plants and the numbers at the dashed horizontal lines give PPFDsat of eCO2 plants. ANOVA results are provided in Table 4 and Appendix Table 7. Letters show results of Tukey–Kramer HSD tests looking for warming and CO2 effects within each measurement year

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Fig. 5
figure 5

Relationships between stomatal conductance and (A) maximum photosynthetic electron transport of PSII (ETRmax) and (B) saturating photosynthetically active radiation (PPFDsat). Measurements were made in 2019, 2021, and 2022 (n = 1544)

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Fig. 6
figure 6

Quantum efficiency of PSII photosynthesis (Fv /Fm) in relation to stomatal conductance. Pre-dawn measurements (panel A) were made in 2018 between the hours of 01:00 and 05:00 (n = 566) and dark-adapted measurements (panel B) were made in 2019–2022 between the hours of 08:00 and 14:00 (n = 1434)

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Discussion

In support of our hypotheses we found that both experimental warming and eCO2 caused reductions in stomatal conductance (gs), maximum electron transport rates (ETRmax), the light level at which ETR saturates (PPFDsat), and the maximum quantum efficiency of PSII photochemistry (Fv/Fm; Table 2, 3, 4 and Figs. 1, 2, 3 and 4), and that these traits were positively correlated with one another (Figs. 5 and 6). These declines were not always significant when post hoc Tukey–Kramer HSD analyses were run within a given year, but the trends in data were consistent. The hypothesis that the sedge would experience more severe declines in these traits than the grasses (hypothesis 3) was supported at the start of the experiment as the C3 sedge showed a strong negative stomatal response to warming in 2017 and 2018 (28% and 17% reduction, respectively in + 5.1 °C). However, in 2019, 2021, and 2022, the negative response to warming was dampened to < 7% reduction in all years, indicating that S. americanus was able to partially acclimate to the warming treatments over time (Fig. 7). These plant responses suggest that future climate conditions have the potential to negatively affect gas-exchange rates in both C3 and C4 salt marsh communities, but the long-term negative impacts on plant growth and survival have may be mitigated through physiological adjustments or genetic selection (Vahsen et al. 2023).

Fig. 7
figure 7

Stomatal conductance of S. americanus in + 1.7, + 3.4, and + 5.1 °C above ambient conditions as a percentage of stomatal conductance in the ambient warming treatment. All data are from ambient CO2 growth conditions. Data are averaged from measurements made in 2017 (white circles, n = 273), 2018 (gray circles, n = 1756), 2019 (black circles, n = 1733), 2021 (white triangles, n = 2443), and 2022 (gray triangles, n = 2058). ANOVA results are provided in Table 2. Symbols represent the mean response to each warming treatment (shown as a percentage of ambient) averaged across transects (n = 3); error bars represent ± 1SE

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Elevated CO2 caused declines in the physiological traits of S. americanus as hypothesized (hypothesis 2). However, in contrast to hypothesis 4, the declines under eCO2 conditions were similar for plants in 2018–2021 regardless of whether they were growing in the ambient or + 5.1 °C temperature treatment (Figs. 1, 2, and 4). It was only in 2022 that sedges growing in the combined + 5.1 °C x eCO2 plots exhibited more significant declines in gs, Fv/Fm, and ETRmax than in either treatment individually (Figs. 1, 2, and 4). In this case, it seems that long-term responses can also exacerbate the negative impacts of warming and eCO2 on the processes we measured.

We were surprised to discover that mean annual variation in plant traits and species-specific responses to warming and eCO2 treatments across years were not dependent on growing season average environmental conditions (Table 1). For example, prior research has shown that plants adjust rates of stomatal conductance in response to annual average changes in environmental conditions such as soil water availability and temperature (Perez-Martin et al. 2009; Šigut et al. 2015), and long-term records from our study site suggest that plant productivity is positively correlated to precipitation (Drake et al. 2013). As such, we expected years with relatively low precipitation to be associated with overall declines in physiological traits and more significant drops in gs and other traits in response to warming. While plants that experience prolonged exposure to extreme growth conditions may acclimate or adapt to those conditions, as suggested by the decline in the negative response of S. americanus gs to warming over time (Fig. 7), plants also exhibit short-term sensitivity to changes in their environment on the scale of hours to weeks. For example, grassland species have been shown to increase rates of gs and photosynthesis in response to increased soil water content over a 3-month period (Volk et al. 2000), and sedge species showed patterns of gs and photosynthesis that were related to diurnal and seasonal variability in leaf temperature and vapor pressure deficit (Koch and Rawlik 1993; Gebauer et al. 1998). We suspect that environmental factors occurring over short periods early in the growing season set the development of the plant traits we measured, a topic that is beyond the scope of the current study.

While our statistical model that included both plant communities found a reduction in gs response to the warming treatment (P < 0.001, Table 2), the C3 sedges showed a more consistent negative response to warming than the C4 grasses when Tukey–Kramer HSD tests were run within year (Fig. 1). This result is not surprising given that warmer growing conditions tend to favor C4 species over C3 species due to the elimination of photorespiration in C4 species which concentrate CO2 around Rubisco, eliminating O2 competition for its active site (Osmond et al. 1982; Long 1999; Taylor et al. 2014). Since many prior studies have found a positive correlation between gs and photosynthesis (Franks 2006; Kattge et al. 2009; Cernusak et al. 2011), it is likely that the C3 sedges in this habitat would exhibit stronger negative gas exchange and growth responses to future climate warming compared to the C4 grasses, but could eventually acclimate and become more similar to the C4 response. Furthermore, a study of four tropical tree species exposed to higher than optimal temperatures showed that photosynthetic rates were limited by gs, rather than traits associated with enzymatic control of photosynthetic capacity (maximum carboxylation rate Vcmax; maximum electron transport rate Jmax) (Slot and Winter 2017). However, while we observed a large decline in gs associated with warming during the first two years of the experiment, the C3 sedges seemed to acclimate to the warming treatment in later years and declines in gs were greatly reduced (Fig. 7). This could alleviate potential reductions in gas-exchange rates and plant growth associated with higher growth temperatures (Kattge and Knorr 2007; Gunderson et al. 2010), allowing both C3 sedges and C4 grasses to remain successful under future climate warming.

Despite the relatively minimal decline of gs of C4 grasses and the acclimation of C3 sedges in response to warming after 2019, we observed a negative effect of warming on ETRmax and Fv/Fm in 2022 for C3 sedges, and in both 2021 and 2022 for C4 grasses (Figs. 2 and 3). We expected gs and ETRmax to follow similar patterns because stomatal closure prevents water loss via transpiration, but yields excess light energy that can damage photosynthetic machinery via the generation of reactive oxygen species (Cruz de Carvalho 2008). Thus, we assumed that during years when the warming treatments caused the most severe declines in gs, we would also observe significant declines in ETRmax. Similarly, we assumed that gs and Fv/Fm would follow similar patterns because as transpiration declines with stomatal closure, plants cannot release heat and therefore suffer increased leaf temperatures (Kim et al. 2006; Šigut et al. 2015). Since reductions in Fv/Fm are indicative of higher levels of plant stress (Demmig and Bjorkman 1987), we thought that heat damage and/or damage to the photosynthetic machinery caused by reactive oxygen species would lead to reductions in this leaf trait. Nonetheless, while we did not observe expected similarities in plant responses to warming when averaged over growing seasons, we did find that that these traits were positively correlated when data were pooled across years and plant communities (Figs. 5 and 6), and that lower gs was observed in plants that had lower ETRmax and were under a higher degree of stress (e.g., lower Fv/Fm).

It is commonly accepted that C4 plants have higher photosynthetic rates than C3 species, which is attributable to different mechanisms of carbon fixation connected to biochemical and anatomical differences that exist between these groups. Because of this, we were surprised to find that the C4 grasses in our experiment exhibited lower values of Fv /Fm, ETRmax, and PPFDsat compared to the C3 sedges. However, while the CO2 concentrating mechanism in C4 species increases their water use efficiency, studies have shown that stomatal limitation posed by abiotic stressors (e.g., high temperatures or drought) potentially induces a larger reduction in CO2 uptake in these species (Wand et al. 2001). Comparisons of C3 and C4 grass subspecies of Alloteropsis semialata showed that the C4 plants had a lower CO2 assimilation rate under drought conditions (Ripley et al. 2007). Additionally, Killi et al. (2017) found that drought- and heat-induced declines in Fv /Fm and PSII efficiency were more severe in C4 species, suggesting that they perform more poorly under stressful conditions, even at temperatures that should favor C4 species over C3. Thus, our results support the premise that C4 species may be inferior competitors under abiotic stress due to a higher susceptibility for photoinhibition (Guidi et al. 2019).

Similar to plant responses to the warming treatment, we found that gs declined significantly for the C3 sedge in response to eCO2 treatment, which again was expected given results of prior studies (Fig. 1; Morison and Lawlor 1999; Medlyn et al. 2001; Ainsworth and Rogers 2007). We also observed significant declines in ETRmax in the eCO2 treatments (Fig. 4). This may seem counterintuitive given the significant increase in net primary production of S. americanus to eCO2 observed in our experiment in 2017 and 2018 (Noyce et al. 2019), as well as prior findings from the same coastal wetland site (Curtis et al. 1989; Drake and Leadley 1991; Jacob et al. 1995; Drake et al. 1996). However, because of the increase in CO2 supply in eCO2 treatments, plants tend to have enhanced photosynthetic rates in spite of the limitation of lower gs (Sage 1994; Kaiser et al. 2017), leading to increased photosynthesis in C3 plants regardless of whether ETRmax is limiting (Stitt 1991; Long and Drake 1992). We found no significant effect of eCO2 on Fv/Fm in 2019, 2021, and under ambient temperatures in 2022 (Table 4). This may be due to the alleviation of oxidative stress that would typically be induced by excess light under aCO2, as higher photosynthetic rates caused by enhanced CO2 levels would make use of that extra light energy input.

We predicted that the combined + 5.1 °C x eCO2 treatment would have the largest effects on plant physiological traits, particularly for the C3 sedges, but we only saw evidence for this in 2022 (Figs. 1, 2, and 4). Mean growing season air temperature was not atypical in 2022, while the amount of precipitation that fell indicates that plants would not have been drought-stressed any more than prior years (Table 1). However, we observed significant declines in gs, ETRmax, and Fv/Fm in the combined + 5.1 °C x eCO2 treatment compared to the individual + 5.1 °C or eCO2 treatments. It could be that some of the initial stimulation of plants under eCO2 is becoming offset by changes in the development of photosynthetic organs as they acclimate (Long and Drake 1992). For example, Jacob et al. (1995) found that eCO2 led to a 30–58% reduction in Rubisco content and lower carboxylation efficiency in S. americanus grown under eCO2 over eight years of treatment. It is possible that these types of developmental changes could, over time, have led to additive effects of warming and eCO2 for this species, but more research is required to test this interpretation.

More studies evaluating the interaction of climate stressors are needed to better understand mechanisms driving gas-exchange and growth responses of plant communities. For example, this study is helping to fill in some gaps regarding plant responses to warming and eCO2, but a recent publication investigating the effects of rising temperatures and CO2 levels found that most ecosystems are becoming deficient in nutrients such as nitrogen (Mason et al. 2022), which further complicates making predictions about the health of future ecosystems. The GCReW site where this experiment took place is the longest continually running investigation on the effects of eCO2 on an ecosystem, and research found reduced tissue nitrogen concentrations in eCO2 treatments over a 28-year period, but particularly in years when precipitation rates were high (Drake et al. 2013). Drake et al. (2013) posits that any decline in nitrogen was driven by a combination of the higher nitrogen demand for growth and transpiration rates (Polley et al. 1999; McDonald et al. 2002). Thus, independent from any changes in photosynthesis or growth, changes in stomatal conductance with warming, eCO2, or environmental factors such as precipitation will affect broader ecosystem processes such as nutrient availability and recycling.