# Modelling Net CO2 Assimilation of Two Sphagnum Species From Temperature and Water Content Response

Alicia V Perera-castro, Miquel Nadal

► To cite this version:

Alicia V Perera-castro, Miquel Nadal. Modelling Net CO2 Assimilation of Two Sphagnum Species From Temperature and Water Content Response. Physiologia Plantarum, 2025, 177 (3), pp.e70325. 10.1111/ppl.70325. hal-05219069

HAL Id: hal-05219069

https://hal.inrae.fr/hal-05219069v1

Submitted on 22 Aug 2025

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
<figure><img src="image_2.png" /></figure>

ORIGINAL RESEARCH OPEN ACCESS

# Modelling Net CO₂ Assimilation of Two *Sphagnum* Species From Temperature and Water Content Response

Alicia V. Perera-Castro<fnref n="1" />,² | Miquel Nadal³,⁴

**Correspondence:** Alicia V. Perera-Castro (pereraalicia11@gmail.com)

**Received:** 8 November 2024 | **Revised:** 2 May 2025 | **Accepted:** 15 May 2025

**Handling Editor:** S. Bokhorst

**Funding:** This work was supported by the European Union H2020 through INTERACT Transnational Access [Grant Agreement No. 871120, RESPIRA]. MN was supported by the postdoctoral fellowship Juan de la Cierva-Formación (FJC2020-043902-I), funded by MCIN/AEI/10.13039/501100011033 and the European Union ('Next Generation EU/PRTR).

**Keywords:** carbon balance | photoperiod | primary productivity | respiration | *Sphagnum*

## ABSTRACT

Photosynthesis and respiration respond differently to the combined effects of temperature and water status. Quantifying their responses is crucial to predict the carbon balance of *Sphagnum* peatlands in different scenarios of climate change. A first approach was done for two *Sphagnum* species inhabiting a boreal peatland in Finland. Gas exchange at different temperatures and moss hydration were measured to model net assimilation using simultaneous measurements of photosynthesis and dark respiration. In addition, measurements of moss surface temperature at different water content were performed in the field, covering natural conditions of sun exposure and air temperature. We also accounted for the interaction effect between moss canopy temperature and air temperature, radiation, and water content. Our model accurately predicted net assimilation and was used to estimate net primary productivity based on meteorological inputs and moss water content. The two *Sphagnum* species presented optimum temperatures for net CO₂ assimilation around 25°C, with minimum changes at other temperatures. In contrast, dark respiration increased exponentially with temperature, which makes losses of carbon during the night and the duration of dark conditions key determinants in the carbon balance of *Sphagnum*. The modeled net primary productivity revealed an enhancement of CO₂ fixation under warming conditions (averaged +10°C), concomitant to the expected transformation of peatlands from sink to source of CO₂. Our model highlighted the importance of respiration restriction in ensuring positive assimilation in *Sphagnum*. Therefore, day and night temperature oscillation and short night photoperiods are more important than the optimum temperature of photosynthesis for carbon balance.

## 1 | Introduction

Boreal peatlands are valuable ecosystems dominated by the moss *Sphagnum*, characterized by a low decomposition rate of dead plant material that results in the accumulation of 20%-30% of the global terrestrial carbon, despite occupying

only a 3% of the Earth's surface (Vile et al. 2011). The net carbon budget in peatlands depends on the balance between two processes: (1) photosynthesis-driven CO₂ fixation and (2) decomposition-driven CO₂ and CH₄ emissions (Limpens et al. 2008). Thanks to cool temperatures and waterlogged conditions that decrease oxygen availability, the decomposition

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

© 2025 The Author(s). Physiologia Plantarum published by John Wiley & Sons Ltd on behalf of Scandinavian Plant Physiology Society.

<footnote n="1">¹Department of Botany, Ecology and Plant Physiology, Universidad de La Laguna, La Laguna, Canary Islands, Spain | ²Institute of Biology, University of Hohenheim, Stuttgart, Germany | ³AgroParisTech, INRAE, UMR Silva, Université de Lorraine, Nancy, France | ⁴Departamento de Sistemas Agrícolas, Forestales y Medio Ambiente, Centro de Investigación y Tecnología Agroalimentaria de Aragón (CITA), Zaragoza, Spain</footnote>
rates are normally reduced, and carbon is accumulated in the soil. However, changes in temperature and hydrological processes under climate change may drive enhanced decomposition and changes in fungal communities, favoring the activity of decomposers (Dieleman et al. 2016; Asemaninejad et al. 2018; but see also Flanagan and Syed 2011; Nakanishi and Tsuyuzaki 2024). These new conditions could lead peatlands to behave as net carbon sources instead of sinks, depending on the new balance between carbon gain and decomposition rates. In addition to studying the drivers of decomposition rates, many efforts have been made in modeling past and future net ecosystem productivity in peatlands (Wu and Roulet 2014; Beyer and Höper 2015; Lunt et al. 2019; Chaudhary et al. 2020; Qiu et al. 2020; Zhao and Zhuang 2023) and establishing a relationship between ecosystem photosynthesis, respiration, and/or net ecosystem production with variation in temperature, water table depth, and radiation in temperate and tropical peatlands (Flanagan and Syed 2011; Charman et al. 2013; Kurnianto et al. 2015; Walker et al. 2017; Karki et al. 2019; Bengtsson et al. 2021; Hanson et al. 2020). However, the specific response of CO₂ assimilation to changing temperature conditions and to the water content of the moss tissue remains underexplored in *Sphagnum*. Precise knowledge of how temperature, radiation, and water content- and their interplay-affect both photosynthesis and respiration is required to accurately predict the response of net CO₂ assimilation and hence provide a more detailed understanding of the dynamics of carbon balance in peatlands.

Gametophytes of mosses are poikilohydric organisms, that is, their water content is equilibrated with atmospheric water potential (Walter 1931). The absence of stomata and, in most cases, the absence of a hydrophobic cuticle and endohydric conducting apparatus contribute to this poikilohydry (Raven 2002; Proctor and Tuba 2002; Raven and Edwards 2004; Vitt et al. 2014; Duckett and Pressel 2022). Delayed dehydration can only be achieved in some species thanks to a set of tiny, compact shoots that confer canopies the ability to retain high amounts of external capillary water and thick boundary layers (Dilks and Proctor 1979; Proctor et al. 1998; Proctor et al. 2007). This capacity to buffer water availability in the environment is most prominent in species with hyaline cells (organelle-free, porous cells), including *Sphagnum* (Thompson and Waddington 2008). Mosses are frequently considered inherently better adapted to cold conditions than angiosperms (Glime 2007). Furness and Grime (1982a) and Furness and Grime (1982b) reported an average optimum temperature for the relative growth rate of 19°C, with long-term temperatures of 30°C being lethal for all studied mosses. However, these previous studies confound the processes of photosynthesis and respiration. A comprehensive review of optimum temperatures for maximum net carbon assimilation in mosses recently found that most species have optimal temperatures around 25°C–30°C (temperature at moss surface) with no significant latitude effect (Perera-Castro, González-Rodríguez, and Fernández-Marín 2022). Notably, species which grow in environments where the average maximum air temperature does not exceed 5°C (for instance, mosses inhabiting Antarctica) do not significantly differ from the 25°C–30°C optimum. This discrepancy between the growth and assimilation rates at elevated

temperatures may have a methodological explanation related to the experimental procedures used for growing mosses under controlled conditions. Furness and Grime (1982a) and Furness and Grime (1982b) used an unrealistic photoperiod of 12 h and no thermal oscillation between day and night, as in some other studies culturing mosses (Bates 1994; Duckett et al. 2004; Melosik and Såstad 2005; Cove et al. 2009; Graham et al. 2010), being a 12/12 h photoperiod less frequent (Grime et al. 1990; Gerdol and Vicentini 2011; Horsley et al. 2011). This would result in excessively high respiration rates at high temperatures, thus lowering the capacity for carbon assimilation (Perera-Castro, González-Rodríguez, and Fernández-Marín 2022). The reduction of night respiration by shortening night length or by experiencing low night temperatures could be crucial for positive carbon balance in mosses. For instance, moss survival in Antarctica may be more related to their reduced respiration at low temperatures during short nights instead of having lower optimum temperatures for photosynthesis (Perera-Castro et al. 2020; Yin et al. 2023). The response of moss respiration to rising temperatures is relevant for modelling the effect of different climate change scenarios on the long-term net CO₂ assimilation and carbon balance of mosses, including *Sphagnum* species, separately from the response of peat decomposition and heterotrophic CO₂ and CH₄ release.

Water availability and temperature are the most relevant indicators of *Sphagnum* distribution (Campbell et al. 2021). However, a wide range of optimum temperatures for net CO₂ assimilation has been reported for *Sphagnum* species in boreal ecosystems, from 6.5°C to 30°C (Stålfelt 1937; Rudolph 1968; Grace and Marks 1978; Silvola and Heikkinen 1979; Silvola and Hanski 1979; Titus and Wagner 1984; Lösch et al. 1994; Oechel and Van Cleve 1986; Gaberščik and Martinčič 1987; Goulden and Crill 1997; Bergeron et al. 2009), although in most studies the response of net CO₂ assimilation to temperature was measured repeatedly using the same samples with no control of water content. For instance, this is the case for the only report (to the best of our knowledge) of the optimum temperature for *Sphagnum* in Finland 43 years ago (Silvola and Heikkinen 1979). By using air temperature instead of moss surface temperature, the authors predicted that an increase of 2°C would result in a null net change in the carbon content of the peatland (Silvola and Hanski 1979). However, ecologists have recently pointed out the importance of a detailed description of microclimate in understanding and modelling ecosystem functioning, especially in small-stature species (Convey et al. 2018; Lembrechts et al. 2019; Lembrechts and Lenoir 2020). Surface temperature is especially dependent on incident irradiance, so mosses can experience high temperatures even in Antarctic ecosystems where air temperature can be 10°C–27°C lower (Matsuda 1968; Schenker and Block 1986; Smith 1996; Perera-Castro et al. 2020). Therefore, a subsequent decrease in cloud cover (Mendoza et al. 2021) may have a warming effect on mosses. In addition, the water content of the live tissue also influences the heating of mosses so that excess water also buffers against extreme temperatures due to the high specific heat capacity of water (Pannewitz et al. 2005; Block et al. 2009; Perera-Castro et al. 2020). The effect of the water content has scarcely been considered in the temperature response of CO₂ assimilation in mosses, despite its critical role in the response of photosynthesis to air temperature
and vapour pressure deficit in vascular plants (Li et al. 2020; Márquez and Busch 2024). In this sense, we hypothesize that the effects of high air temperature and high irradiance on photosynthesis and respiration will be exacerbated under lower water contents, resulting in a potential synergic effect of the temperature and water content, further limiting net assimilation under these ‘dry conditions’. In our study, we also consider the irradiance and water effects on the *Sphagnum* surface to estimate the present and future carbon balance of *Sphagnum*. Hence, we aim to estimate the carbon balance of *Sphagnum* by combining three driving factors and their interactions: temperature, irradiance and water content. Using this combined approach, we provide a much more accurate description of the temperature effect on *Sphagnum* carbon balance, including the environmental requirements (night and day air temperature, irradiance regime, etc.) that enhance net primary productivity in the ecosystem. Although applied to Finland peatlands, this new approach for assessing environmental responses can be readily extensible to other *Sphagnum* communities worldwide.

The objectives of the present study were three-fold: (1) to quantify the response of respiration and photosynthesis of *Sphagnum* species to independent changes in temperature and water content, (2) to measure the effect of water content on the warm-up of irradiated *Sphagnum* at the surface level in comparison with air temperature, and (3) to estimate the carbon balance of *Sphagnum* under different scenarios of temperature, water content, radiation, and photoperiod, considering optimum and suboptimum conditions for CO₂ assimilation and the combined effects of these factors. All measurements were conducted in situ (Hyytiälä, Finland) with *Sphagnum* shoots collected during the growing season (3rd–17th July). While the measurements were conducted during a relatively

short period in the peak growing season, this timeframe coincides with the period of highest physiological activity for *Sphagnum*. As such, our data capture the species' photosynthetic response under optimal conditions. Nonetheless, we acknowledge that *Sphagnum*-dominated peatlands can remain active year-round and thus experience different environmental conditions from those evaluated in the present study. Although our results do not necessarily provide a complete annual picture of carbon dynamics, they are valuable representatives of peak-season dynamics.

## 2 | Materials and Methods

### 2.1 | Study Site and Plant Material

Two *Sphagnum* species were considered in this study: *Sphagnum squarrosum* Crome (Figure 1A) and *Sphagnum angustifolium* (Russow) C.E.O. Jensen (Figure 1B), growing at the fen border near Lake Kuivajärvi (61°50′ 21.7″ N, 24°17′13″ E), close to Hyytiälä Forestry Research Station (SMEAR II, Finland) (Figure 1C). For gas exchange analysis, apical capitula were daily collected and stored in semi-sealed bags until their measurement within the next 4h at the SMEAR II lab facilities. Adjacent samples were used for in situ measurements of moss temperature, radiation, and water content (Figure 1D,E). The collection dates comprised from 3rd July to 17th July 2023, from 9:00 to 10:00 h (local time). During this period, air temperatures oscillated from 20°C–25°C during the day to 10°C–15°C during the night, and maximum radiation was 500–800 W m⁻² during the midday (SMEAR II meteorological station). In all cases, samples were collected randomly without considering their position with respect to hummocks or hollows and therefore their distance to the water table.

<figure><img src="image_3.png" /><figcaption>**FIGURE 1** | Study site and measured species. (A) *Sphagnum squarrosum*, (B) *Sphagnum angustifolium*. (C) General aspect of the peatland where mosses were collected for gas exchange analysis. (D) Set for in situ measurement of the effect on moss temperature of water content and irradiance. (E) Extraction of moss canopy in its original structure.</figcaption></figure>
## 2.2 | Gas Exchange Analysis

Measurements of net CO₂ assimilation rate ($A_N$), dark respiration rate ($R_D$) and chlorophyll fluorescence in response to variations in water content ('dehydration' or 'water loss' curve; Perera-Castro et al. 2020) at different temperatures were done with a Li-6800 system (Multiphase Flash Fluorometer chamber, LiCOR Biosciences). Each dehydration curve was performed in samples that were oversaturated with distilled water prior to the measurements; then, they were placed over a custom-made cuvette consisting of a 6 cm² gasket fixed to a piece of thin polyester stocking fabric (Figure S1, Perera-Castro et al. 2020) and introduced in the Li-6800 chamber, placed between the two gaskets of the chamber. The water concentration of the incoming air (reference water) was set to 0 mmol mol⁻¹ air to enhance the dehydration of samples inside the chamber during the measurements and to avoid the risk of condensation in the air pathway. The flow rate within the chamber was maintained at 400 µmol s⁻¹, and the CO₂ concentration in the incoming air was set at 420 µmol mol⁻¹ air. Irradiance was set at a saturation level of 800 µmol m⁻² s⁻¹ (tested previously with light-response curves) for $A_N$ measurement or switched off for at least 5–10 min for determination of $R_D$. Gas exchange and chlorophyll fluorescence recordings were alternated with weighing of the sample each 5–10 min to obtain the fresh weight (FW) of the sample to complete the dehydration curve. An entire cycle of dehydration lasted for approximately 2 h with a similar dehydration rate between species that ranged from 97 to 250 mL H₂O g⁻¹ DW min⁻¹ for the full range of the measured temperatures (15°C–35°C). Water content (WC) at any given time during dehydration was calculated as: $WC = (FW-DW)/DW$, where DW is the dry weight obtained after keeping the samples at 70°C for 48 h. This procedure was repeated for different samples at several temperatures of the measuring chamber (15°C, 20°C, 25°C, 30°C and 35°C, 5 biological replicates each for $A_N$ and $R_D$) to obtain complete dehydration curves at each temperature. $A_N$ and $R_D$ were expressed per projected capitula area. In addition, the response of the maximum yield of PSII ($F_v/F_m$) to dehydration was also monitored for additional air-dried samples at 25°C, following the same procedure described above under dark conditions.

Due to low gas exchange rates, especially $R_D$, measurements of CO₂ leakages (Flexas et al. 2007) were done regularly (each 15–30 min). Since relative humidity in the chamber varied depending on the hydration state of the sample (RH of 10%–80%), an additional correction was applied to avoid artefacts in the assimilation rate. A wet piece of paper was introduced in an empty moss cuvette, and CO₂ of reference (CO₂R) and sample (CO₂S) were monitored during the dehydration curve using the same settings as for the measurements described above. The correction factor (F) used for correcting the CO₂S was calculated as the ratio CO₂R/CO₂S, and its relationship with water vapour difference between sample and reference IRGAs (H₂OS and H₂OR, respectively) was obtained by linear regression ($R^2 = 0.998$, Figure S2):

$$F = 9.73 \cdot 10^{-4} \cdot (\text{H}_2\text{OS} - \text{H}_2\text{OR}) + 1 \quad (1)$$

The final formula for $A_N$ was:

$$A_N = \frac{\text{Flow}(\text{CO}_2\text{R} - \text{CO}_2\text{S} \cdot F)}{\text{Area}} \quad (2)$$

Notice that the formula of $A_N$ provided by LICOR already contains its own F for correcting the effect of air dilution by evaporated and/or transpired water. However, it was not enough for the high humidity levels of our chamber and the sensitivity requirements of our analysis.

## 2.3 | In Situ Measurement of the Effect of Water Content and Irradiance on Moss Temperature

Temperature ($T_{moss}$), WC, and irradiance (considering photosynthetic active radiation, PAR) were monitored in moss capitula during 3 days of diverse environmental conditions in the field. Moss canopy samples of 7 cm² ($n=12$) were extracted in their original structure using a 1 cm deep cylinder (Figure 1E). Moss and the cylinder were placed over a plastic plate near (< 5 m) their original population (Figure 1D). Both the cylinder and plate were weighted previously and accompanied the same sample during all measurements. $T_{moss}$ was measured with an infra-red thermometer (DT-8666, CEM Instruments) and a K-type thermocouple thermometer (TM-902C UXCell) by pointing to or touching the surface of the central moss capitula. Temperatures obtained from the two instruments were very similar (Figure S3); therefore, $T_{moss}$ was calculated as the average of both values. Immediately after $T_{moss}$ determination, samples were weighed for calculating WC, as explained above, using a field portable balance (ML203E, Mettler Toledo International Inc.). PAR flux was measured with a QSPAR Quantum sensor (Hansatech Ltd.) before and after $T_{moss}$ and WC determination. Both values of PAR (Figure S4) were averaged for subsequent analysis.

## 2.4 | Modeling Net CO₂ Assimilation

The response of $A_N$ to radiation, water content, and temperature was fitted to a non-linear model using the R statistical software (1.4.2.3 version) (R Core Team 2023). The semi-empirical model was based on using the light response of photosynthesis and the exponential response of respiration as a base for net assimilation (Street et al. 2012; Calama et al. 2013; Günther et al. 2017; Silvan et al. 2017; Gong et al. 2020), with some modifications. Our model was based on a light response equation (E. L. Smith 1936) fitted to data:

$$A_N = \frac{(A_{sat} + R_D) \cdot PAR \cdot AQE}{\sqrt{(AQE \cdot PAR)^2 + (A_{sat} + R_D)^2}} - R_D \quad (3)$$

where $A_{sat}$ is the light-saturated $A_N$ and AQE is the apparent quantum efficiency (initial slope of the light curve). Averaged AQE was considered as 0.0144 obtained from the light curves performed at 25°C, assumed to remain constant for 15°C–35°C, as reported in other moss species (Perera-Castro et al. 2020, data available upon request). $A_{sat}$ was expressed as a non-symmetric polynomial function of $T_{moss}$ and WC:

$$A_{sat} = aT_{moss}^2 + bT_{moss} + c - (dWC^2 + eWC) \quad (4)$$

where a, b, c, d, and e are fitted parameters. $R_D$ was also expressed as a function of $T_{moss}$ and WC following the empirical model of Heskel et al. (2016):
$$R_D = e^{f+0.1012T_{moss}-0.0005T_{moss}^2} - gWC + h + i \cdot \log(WC) \cdot T_{moss} \quad (5)$$

where f, g, h, and i are fitted parameters.

The procedure to solve Equation (3) consisted of two independent steps. First, parameters f, g, h, and i were fitted from the temperature and water content response of the dataset obtained under dark conditions using Equation (5). Once these parameters were obtained, the measured A_N, PAR, T_moss, and WC were used to obtain model fittings for a, b, c, d, and e by combining Equations (3–5). Modelled A_N was thus calculated from PAR, T_moss, WC, and the fitted parameters (a–i). This two-step procedure avoided the undesirable effect of the different sizes of datasets (R_D vs. A_N under irradiated conditions) on the quality of the fitting.

A second model was developed to obtain T_moss from in situ WC, PAR, and air temperature (T-air). T-air was obtained from meteorological data of the SMEAR II Hyytiälä forest meteorological station, available at the data portal of SMEAR (https://smear.avaa.csc.fi/download) (Figure S5). T_moss can be considered close to T-air, plus the warming-up resulted from PAR, which is mitigated by WC. Therefore:

$$T_{moss} = T_{air} + jPAR^2 + kPAR + l + m \cdot \log(WC) \quad (6)$$

where j, k, l and m are fitted parameters.

Both A_N and T_moss model fits were carried out through ordinary nonlinear least squares regression techniques using the nlme package (Pinheiro et al., 2023). Additional R packages used for data analysis were plyr (Wickham 2011), ggplot2 (Wickham 2016), and agricolae (de Mendiburu 2021).

## 2.5 | Net Assimilation of Sphagnum Under Different Scenarios

Both A_N and T_moss models were combined to calculate the A_N of S. squarrosum and S. angustifolium for the natural environmental conditions and photoperiod of the studied period (from 3rd to 17th July 2023; SMEAR II Hyytiälä forest meteorological station) (Figure S5). Meteorological T-air and PAR were used for Equations (3 and 6) with some modifications to produce different scenarios: (1) variable water content (using WC values across the measured range, from 4.5 to 17 g H₂O g⁻¹ DW), reflecting variation in the water table from both flooding and drought situations, (2) variations of meteorological T-air of ±10°C under optimal WC, which corresponds to a 2-fold change of the maximum predicted increase of mean T-air for Finland (Venäläinen et al. 2020), and (3) PAR flux variation under optimal WC. Since it is unknown how the reduction of total cloud cover (predicted to be -1.4% for the next 20 years, Mendoza et al. 2021) will affect integrated PAR flux, a reasonable ample range of variation of PAR was tested instead (variation factors of 0.6–1.6). Furthermore, A_N and T_moss models were used for calculating A_N of both studied species under two additional scenarios that may affect respiration losses: (4) variations in photoperiod (12/12, 18/6 or 20/4 h day/night photoperiods), and (5) changes in night temperatures (25°C/15°C, 25°C/20°C, or 25°C/25°C day/night

temperatures). Scenarios 4 and 5 were modelled under optimum water content conditions and saturating light conditions (800 µmol m⁻² s⁻¹).

Since the meteorological station provided meteorological data (T-air and PAR) with a frequency of 30 min, daily net primary productivity of the studied period (NPP-day; g CO₂ m⁻²) was estimated from averaged meteorological conditions as:

$$NPP_{day} = \sum_{23:59}^{00:00} \frac{\text{modelled } A_N \cdot 1800 \cdot MW_{CO2}}{10^6} \quad (7)$$

where MW-CO₂ is the molecular weight of CO₂ (44.01 g mol⁻¹). Notice that NPP-day refers to projected area of the capitula and not to the ground area. Since photosynthetic tissues are localized in the tips of the shoots, capitula are the main drivers of most CO₂ assimilation of the plant and the primary productivity. Errors of the calculated NPP-day were obtained for the different scenarios by creating a bootstrapping dataset: the function rnorm() of the stats package (R Core Team 2023) was used for creating an artificial data frame of 1000 observations per fitted parameter from parameter a to m; Equations (4–6) with mean and standard deviation identical to the mean and standard deviation of each parameter. The combination of this bootstrapping data frame with the meteorological dataset allowed the calculation of 1000 values of A_N per any observation of T-air and PAR in the meteorological data (each 30 min). The average of those 1000 values of A_N allowed the calculation of the total standard deviation of the obtained A_N value per meteorological data. Then, as done for modelled A_N, the obtained standard deviation was added for the summer period and transformed into g CO₂ m⁻². This procedure was repeated for all scenarios and the two species. Notice that for scenarios 4 and 5 the meteorological data was not used, and set values of PAR and temperature were used instead.

# 3 | Results

## 3.1 | A_N and R_D Response to WC and Temperature

For all temperatures, A_N increased during the initial dehydration of the moss inside the chamber until a WC of 7.2 ± 0.3 and 8.6 ± 0.1 (mean ± SE) g H₂O g⁻¹ DW for S. angustifolium and S. squarrosum, respectively (Figures 2 and S6A,B for details at 25°C). On the contrary, R_D was not inhibited at high WC values (Figures 3 and S6C,D). Furthermore, both parameters differed in their x-intercept. A_N was zero at WC, close to those at which F_v/F_m remained at 50% of its non-stressed value after a dehydration/rehydration cycle (Figures S6 and S7). At this point, R_D was reduced by 50% of the hydrated value and only reached zero at WC close to 0 g g⁻¹ (Figure S6C,D).

Under optimum water content conditions (when A_N reached its maximum values in the dehydration curve), both species presented similar optimum temperatures for assimilation (Figure 4A,B). At 25°C, Sphagnum squarrosum presented a higher maximum A_N than S. angustifolium
<figure><img src="image_4.png" /><figcaption>**FIGURE 2** | Net CO₂ assimilation ($A_N$) under saturated light conditions in response to water content (WC) of *S. angustifolium* (top panels) and *S. squarrosum* (bottom panels) during dehydration curves at 15°C, 20°C, 25°C, 30°C and 35°C (see Figure S6 for detailed response at 25°C).</figcaption></figure>

<figure><img src="image_5.png" /><figcaption>**FIGURE 3** | Dark respiration rates ($R_D$) in response to water content (WC) of *S. angustifolium* (top panels) and *S. squarrosum* (bottom panels) during dehydration curves at 15°C, 20°C, 25°C, 30°C, and 35°C (see Figure S6 for detailed response at 25°C).</figcaption></figure>

$(2.8 \pm 0.3 \mu\text{mol m}^{-2}\text{s}^{-1}) \text{ vs. } (1.8 \pm 0.2 \mu\text{mol m}^{-2}\text{s}^{-1}, p < 0.001, \text{t-test)}.$
$A_N$ at 30°C and 3°C did not significantly differ from those at 25°C in both species. Regarding respiration, $R_D$ increased exponentially with temperature ($R^2 = 0.846$ and 0.763 for *S. angustifolium* and *S. squarrosum*, respectively, with all fitted parameters significantly different to zero, Figure 4C,D). $R_D$ above 27°C was significantly higher in *S. angustifolium* than in *S. squarrosum* ($p < 0.001$, t-test, Figure 4C,D).

When all data (WC curves at 5 temperatures) were fitted to the described $A_N$ model, good fits were obtained for *S. angustifolium* ($R^2 = 0.928$, Figure 5A,B) and *S. squarrosum* ($R^2 = 0.913$, Figure 5C,D). The values of the parameters fitted for the $A_N$ model of both species are shown in Table S1.

## 3.2 | Drivers of Moss Canopy Temperature

A wide range of $T_{\text{moss}}$ values was measured in the field ($T_{\text{moss}}$ between 12°C-37°C), greater than the $T_{\text{air}}$ range registered by the meteorological station for the same measuring time (13°C-26°C) (Figure 6A,B). For all WC values, the highest differences between $T_{\text{moss}}$ and $T_{\text{air}}$ (15°C maximum) were registered at the highest PAR values and the lowest WC in both species (Figure 6B). The effect of WC in buffering the warming of the moss canopy was only relevant at WC > 5 g H₂O g⁻¹ DW (Figure 6C,D), when the corresponding $A_N$ of both species had already decreased more than 50% of optimum values, and $F_v/F_m$ started decreasing in an irreversible way (Figures S6 and S7). When data of both species were combined and fitted to the $T_{\text{moss}}$ model (Table S2), a
<figure><img src="image_6.png" /><figcaption>**FIGURE 4** | Maximum net CO₂ assimilation ($A_N$, A, B) under saturated light conditions and maximum dark respiration rates ($R_D$, C, D) in response to temperature ($T_{moss}$) of *S. angustifolium* (A, C) and *S. squarrosum* (B, D). Maximum $A_N$ of each dehydration curve was obtained for a water content of 7.2±0.3 and 8.6±0.1 g H₂O g⁻¹ DW for *S. angustifolium* and *S. squarrosum*, respectively. Maximum $R_D$ correspond to a water content of 11±1.5 and 9.6±1.9 g H₂O g⁻¹ DW for *S. angustifolium* and *S. squarrosum*, respectively. Dashed black lines represent a polynomial function for A and B, and the exponential function of Heskel et al. (2016) for C and D ($n=5$).</figcaption></figure>

good fit was obtained when comparing observed and modelled temperatures ($R^2=0.778$, Figure 7), although 22.2% of total variance remained unexplained. In contrast, for modelled $A_N$, only 7.2%–8.7% of variance remained unexplained (Figure 5A,C).

## 3.3 | Scenarios of Carbon Balance

Combining the $A_N$ and $T_{moss}$ models (Equations 3–6), $A_N$ was estimated from meteorological data of SMEAR II Hyytiälä forest station, and $NPP_{day}$ was approximated from the integration of modelled $A_N$ during the summer period (3rd to 17th July). $T_{air}$ values registered for the studied period at SMEAR II Hyytiälä forest station oscillated between averaged daily minimum $T_{air}$ of 12.4°C ± 1.1°C during the night at 03:00 h to averaged maximum $T_{air}$ of 19.4°C ± 3.5°C during midday (14:00 h) (Figure S5). The average daily maximum PAR at midday was 750 µmol m⁻² s⁻¹ (Figure S5) during a day length of 20.5 h. Under these conditions, maximum $NPP_{day}$ at the optimum values of WC were estimated as 12.0 ± 4.0 and 11.3 ± 2.4 g CO₂ m⁻² for *S. angustifolium* and *S. squarrosum*, respectively (Figure 8A). Under optimum WC conditions, an increase of 5°C above the $T_{air}$ (and therefore $T_{moss}$’ depending on PAR) resulted in an enhancement of mean $NPP_{day}$ of only 1.1 and 0.7 g CO₂ m⁻² for *S. angustifolium* and *S. squarrosum*, respectively (Figure 8B), without a decrease of $NPP_{day}$ with +10°C of the reported temperatures. Something similar was observed for the estimation of $NPP_{day}$ under different reduction factors of PAR (and, therefore, subsequent effects on $T_{moss}$). A PAR variation factor of 1.3 (PAR increase by 30%) only resulted in increases of average $NPP_{day}$ by 0.7 and 0.5 g CO₂ m⁻² for *S.*

*angustifolium* and *S. squarrosum*, respectively, under optimum WC (Figure 8C).

Our model also revealed a slight variation of averaged $NPP_{day}$ with decreases of night temperature from 25°C to 5°C at optimum WC (1.6 and 0.8 g CO₂ m⁻² for *S. angustifolium* and *S. squarrosum*) (Figure 9A). On the contrary, this averaged $NPP_{day}$ increased by 8 and 7.2 g CO₂ m⁻² in *S. angustifolium* and *S. squarrosum*, respectively, if a short-night photoperiod of 20/4 (day/night = 83% of hours of light per day) is modelled instead of 12/12 h (50% of hours of light) (Figure 9B).

# 4 | Discussion

## 4.1 | Source of Errors and Reliability of the Estimated NPP

The presented models calculated net CO₂ assimilation in two *Sphagnum* species in response to radiation, temperature and water content, also considering the interaction between these variables in the determination of moss canopy temperature. Using a bootstrapping dataset of each fitting parameter, the total SD was calculated for the estimated $NPP_{day}$ (3rd–17th July) for the two studied *Sphagnum* species. Most of the deviation originated in the estimation of $T_{moss}$ from $T_{air}$, radiation and WC, which was not as accurate as the estimation of $A_N$ (Figures 4 and 6). Other factors may also affect $T_{moss}$ and its interactions with radiation and WC, such as the wind speed (Bilgili 2010; Perera-Castro et al. 2020), canopy structure (Rice
<figure><img src="image_7.png" /><figcaption>**FIGURE 5** | Relationship between modelled net CO₂ assimilation rate (A_N) and measured A_N of S. angustifolium (A, B) and S. squarrosum (C, D) considering dehydration curves for all temperatures and light conditions. Circles denote data under saturating light conditions (PAR of 800 µmol m⁻² s⁻¹) and triangles under dark conditions. Red dashed line indicates linear regression, which remains very close to the 1:1 relationship (black dashed line). Parameters fitted to both species are detailed in Table S1. In B and D panels, red datapoints indicate measured A_N and blue points indicate the estimated A_N under 800 µmol m⁻² s⁻¹ or dark conditions (equivalent to negative respiration: -R_D) and blue points indicate the estimated A_N for the same conditions according to the model (Equations 3–5). The final total number of recordings used in the model were 431 and 498 for S. angustifolium and S. squarrosum, respectively.</figcaption></figure>

et al. 2018), light angle (Fuchs 1990, for leaf temperature) or water temperature surrounding mosses, some of which are not easily accessible from meteorological stations. The measurement of water content in capitula in the field or under lab conditions necessarily requires the use of detached samples excised from the underlying tissue. Although this hinders direct comparison of intact *Sphagnum* shoots, continuously 'watered' by the lower layers of moss canopy, our main intent was to induce sample dehydration to measure temperature, A_N and R_D under the whole range of water content. Since the density of shoots and structure of the canopy was maintained for the detached 1 cm deep samples, we consider that the response of T_moss is comparable to that of the intact moss canopy, which

is expected to experience fewer WC variations (Silvola and Aaltonen 1984; Gaberščik and Martinčič 1987; Kellner and Halldin 2002; Fukuta et al. 2012).

In the modelling of net assimilation, 7.2% and 8.7% of variance remained unexplained when compared to measured A_N in S. angustifolium and S. squarrosum, respectively, which may reflect the variability of plant material in the field, similar to other studies that modelled gas exchange fluxes in *Sphagnum* (Beyer and Höper 2015). The factors that explain this intraspecific variation in a single location remain unknown, possibly related to genetic variation, phenology, or stressful conditions prior to our measurements. The heterogeneity of ground level observed in
<figure><img src="image_8.png" /><figcaption>**FIGURE 6** | (A) Relationship between measured moss canopy temperature ($T_{moss}$) and air temperature of the meteorological station SMEAR II Hyytiälä forest, Finland ($T_{air}$) in relation to photosynthetic active radiation (PAR). (B) Warming of moss canopy ($T_{moss} - T_{air}$) in relation to PAR and water content (WC). Data for both species are presented together in (A, B). Variation of moss canopy temperature in relation to moss water content (WC) and photosynthetic active radiation (PAR) of *S. angustifolium* (C) and *S. squarrosum* (D).</figcaption></figure>

the field is an indicator of different distances to the water table, which also can affect both biomass density and moss growth (Serk et al. 2021). Serk et al. (2021) also reported a growth increase due to short-term exposure to high CO₂ concentration (8–10 weeks under 280 vs. 400 ppm CO₂), although the increase of CO₂ exchange at enhanced CO₂ is expected to be dissipated after long-term exposure (> 17 weeks, Jauhiainen and Silvola 1999). The effect of long-term exposure to other factors, such as stressful temperatures or unfavourable WC, may explain seasonal decreases in the photosynthetic capacity of *Sphagnum* (Gaberščik and Martinčič 1987; Fukuta et al. 2012). Heat waves can also compromise the photosynthetic capacity and yield of *Sphagnum* (Gerdol and Vicentini 2011), probably followed by a delayed recovery. Fukuta et al. (2012) also reported that the relative response of $A_N$ to water content and temperature did not change seasonally, although possible acclimation in other *Sphagnum* species could still play a role throughout the year. Our models were not conceived to estimate annual NPP. However, their good fit to the measured $A_N$ data makes them suitable for estimating changes in the maximum optimum $NPP_{day}$ of the growing season and estimating the average balances between CO₂ uptake and respiration in the different tested scenarios.

## 4.2 | Water Content as a Double-Edged Sword

In the field, *Sphagnum* tissues are often far from their optimal water content for assimilation, being either overhydrated or desiccated—a dynamic state typical of poikilohydric plants (Proctor et al. 2007). Dehydration below optimum WC can lead to irreversible damage to the photosynthetic apparatus, reflected by the decrease in $F_v/F_m$ (Figure S7), although some authors have reported recovery after extreme water loss (i.e., desiccation tolerance) in *Sphagnum* (Schipperges and Rydin 1998; Hájek and Beckett 2008), probably associated with dehydration rate and ABA signalling (Marschall and Borbély 2011; Hájek and Vicherová 2014). *Sphagnum* tissues and canopy structure allow for a desiccation avoidance strategy, enhancing the retention of a considerable reservoir of water (the highest among bryophytes; Wang and Bader 2018) inside porous, hyaline, non-photosynthetic cells and capillary spaces formed by overlapping pendent branches that hang down against the stem (Van Breemen 1995; McCarter and Price 2014). Since CO₂ diffuses about 10,000 times more slowly in water than in air (Griffiths et al. 2004), this high capacity of *Sphagnum* for storage water constrains CO₂ internal conductance and photosynthetic capacity under WC higher than optimum (Dilks and Proctor 1979;
Proctor 2000; Rice et al. 2011; Perera-Castro, Waterman, et al. 2022). Furthermore, the *Sphagnum* structure also allows water movement by capillary action from the water table to *Sphagnum* capitula at higher levels (Van Breemen 1995), something that varies between species, as well as their preferred height above the water table (Laing et al. 2014; Bengtsson et al. 2016; Piatkowski and Shaw 2019).

Water levels in peatlands can vary seasonally and annually (Kurnianto et al. 2015; Swindles et al. 2015; Silvan et al. 2017; Karki

<figure><img src="image_9.png" /><figcaption>**FIGURE 7** | Relationship between measured and modelled moss canopy temperature ($T_{moss}$). Data for *S. angustifolium* and *S. squarrosum* were considered together for this analysis. Red dashed line indicates linear regression, which corresponds to the 1:1 relationship (black dashed line). The fitted model is: $T_{moss} = T_{air} + 0.017 \cdot PAR - 8.2 \cdot 10^{-6} \cdot PAR^2 - 1.624 \cdot log(WC) - 0.734$, where WC is the water content of the sample, PAR is the photosynthetic active radiation measured in the field, and $T_{air}$ the air temperature registered by the SMEAR II Hyytiälä forest meteorological station. SD and significance of fitted parameters are detailed in Table S2.</figcaption></figure>

et al. 2019; Sim et al. 2021). Several studies have revealed a relationship between water level and NPP (Gunnarsson 2005; Walker et al. 2017; but also Street et al. 2012). However, due to the complex regulation of CO₂ and CH₄ release by heterotrophic respiration, the response of net ecosystem productivity to water level seems elusive (Updegraff et al. 2001; Flanagan and Syed 2011), with possible enhanced methane emissions if the water level reaches the ground level (Beyer and Höper 2015). Cases of success in farming *Sphagnum* are based on tight control of irrigation for enhancing moss growth (examples in Cris et al. 2011, 2014; Günther et al. 2017; Gaudig et al. 2018; Grobe et al. 2021). Our results show that NPP could be enhanced considerably if the water table is controlled to allow optimum water content for gas exchange and follows the increase in height of moss shoots to avoid chlorosis and dehydration for the highest shoots (Hoshi 2017). That may avoid overhydration and problems with CO₂ diffusion and methane production (Beyer and Höper 2015). Monitoring evapotranspiration (Moore et al. 2013) and the water table–WC and NPP–height relationship of the different *Sphagnum* species will be of great interest.

## 4.3 | There Are Different Temperature Thresholds for Sink Capacity of Peatlands and *Sphagnum*

Mean annual temperature is frequently considered an important factor determining productivity on a global scale in *Sphagnum*-dominated wetlands (Gunnarsson 2005). Most studies that estimate the effects of global warming on the carbon balance of peatlands agree that their sink capacity could be substantially reduced by 2050 under the high-warming scenario (RCP8.5) due to increases in mineralization rates (Chaudhary et al. 2020), becoming even a source of CO₂ (Qiu et al. 2020; Hanson et al. 2020). In addition, a risk of shifting wetlands from a wet system dominated by cryptogams to a drier system with increased cover of vascular plants has also been predicted (Bao, Jia, and Xu 2022). However, Charman et al. (2013) predicted an increase in the carbon sequestration rate of peatlands in a climate warming scenario, but only if water availability is maintained. In their approach, PAR dose (daily radiation level on days when the temperature is above 0°C) had a positive effect

<figure><img src="image_10.png" /><figcaption>**FIGURE 8** | Daily net primary productivity of summer (3rd–17th July, 2023) ($NPP_{day}$) estimated from the combination of the $A_N$ and $T_{moss}$ models and different scenarios: (A) complete range of measured WC (scenario 1), (B) variations of each recorded meteorological $T_{air}$ from –10°C to +10°C under optimal WC (scenario 2), and (C) PAR variation factors projected for the next decades, including those modelled by Mendoza et al. (2021) in the 0.6–1.6 range, under optimal WC (scenario 3). Datapoints are mean ± SD. Standard deviation was calculated by generating a bootstrapping dataset of mean ± SD of each fitting parameter.</figcaption></figure>
<figure><img src="image_11.png" /><figcaption>**FIGURE 9** | Estimated average daily net primary productivity (NPP<sub>day</sub>) under optimum conditions of water content for: (A) different air temperatures (T<sub>air</sub>) during night, considering a photoperiod of 20/4h (day/night), optimum T<sub>air</sub> (25°C) during day and saturating light conditions (800 µmol m<sup>-2</sup>s<sup>-1</sup>) (scenario 4); and (B) different photoperiods represented as a percentage of hours per day considering an oscillation of T<sub>air</sub> of 25°C/15°C (the natural one for the study site during summer) and saturating light conditions during day (scenario 5). Datapoints are mean ± SD. Standard deviation was calculated by generating a bootstrapping dataset of mean ± SD of each fitting parameter.</figcaption></figure>

on carbon accumulation. Lunt et al. (2019) reported the same past and contemporary high rates of carbon accumulation for a peatland in South West England, suggesting that recent climate changes appeared to have had no impact on their role as carbon sinks. In agreement with these studies, our estimations of NPP<sub>day</sub> from the modeled A<sub>N</sub> using meteorological data for the summer (and, therefore, not considering heterotrophic respiration), reflect a potential suboptimal carbon sink capacity that can be slightly enhanced (by 1.1 and 0.7 g CO<sub>2</sub>m<sup>-2</sup> for S. angustifolium and S. squarrosum, respectively) if each registered T<sub>air</sub> value increases by 5°C (Figure 8B). Notice that this change in T<sub>air</sub> has an amplified effect in T<sub>moss</sub>, which would increase by 6.1°C and 5.7°C in S. angustifolium (WC = 9.5) and S. squarrosum (WC = 10.75) during the midday in sunny days, according to the T<sub>moss</sub> model. S. angustifolium and S. squarrosum presented optimum temperatures for the highest A<sub>N</sub>, around 25°C, with a wide plateau. Meanwhile, the average diurnal T<sub>air</sub> for the 2023 summer period at SMEAR II Hyytiälä forest station was 19.4°C ± 3.5°C, and 12.4°C ± 1.1°C during the night. Our data reflect that, under this context, an increase in temperature can enhance daily carbon fixation in photosynthesis more than carbon release in night respiration, at least for the first averaged 5° of increase.

Different predictions between studies of peatland sink capacity in warming scenarios may be related to different sink-source thresholds for the components of net ecosystem productivity (NPP and heterotrophic respiration and mineralization). Hanson et al. (2020) estimated that an increase in mean annual temperature of 4°C will result in a negative net carbon balance due to an enhanced heterotrophic release of CO₂ and CH₄. However, our estimated *Sphagnum NPP*<sub>day</sub> will not become negative even after a *T*<sub>air</sub> increase of 10°C (Figure 8B). This suggests that the change of peatlands from sink to source of CO₂ under warming scenarios may precede the *Sphagnum* optimum temperatures for NPP. Thus, optimum environmental conditions for maximizing *Sphagnum* CO₂ fixation may at the same time be detrimental due to a concomitant increase in heterotrophic release of CO₂ and CH₄, transforming the ecosystem into a source

of carbon even when its principal primary producers perform at their highest capacity.

## 4.4 | Photoperiod Could Be the Main Limiting Factor for NPP

Although low night temperatures can reduce carbon losses due to respiration (with possibly some non-temperature dependent changes in respiration rate, Bruhn et al. 2022), the model shows that an increased carbon gain results from shorter night periods (Figure 9). The relevance of respiration in determining NPP could explain the lack of correlation between CO₂ assimilation and growth reported for *Sphagnum* (Gaberščik and Martinčič 1987). This result, together with the described suboptimal growth of *Sphagnum* in the study site (enhanced by warming), suggests photoperiod as a relevant driver of *Sphagnum* productivity and the global distribution of *Sphagnum*-dominated mires, although intercorrelated with low temperatures (Campbell et al. 2021) and latitude (Tanneberger et al. 2017). If true, this new idea will involve that the affinity of mosses for high latitudes would be more related to shorter nights during the growing season –and, therefore, enhancing carbon balance–than with an intrinsic cold-adapted physiology, as their relatively high optimum temperature for maximum A<sub>N</sub> evidence (Figure 4, Perera-Castro, González-Rodríguez, and Fernández-Marín 2022). *Sphagnum* is a widespread genus with an ample world distribution (Daniels and Eddy 1990). However, *Sphagnum*-dominated bogs are more frequent in the northern hemisphere, while *Sphagnum*-dominated peatlands of the tropics are less extensive and have a lower pool of C (Page and Baird 2016). Since most predictions of the spatial–temporal variation of *Sphagnum* (Ma et al. 2022) and mosses in general (He et al. 2016) are based on their cold affinity, considering the “phoperiod” hypothesis would be essential for understanding the response of the peatland ecosystem to global warming and also improve harvesting protocols.

Continuous light is sometimes used for in vitro cultivation of *Physcomitrella patens* (Calcutt et al. 2024). However, at least in
some vascular plants, long-term continuous light can be dam-
aging (Velez-Ramirez et al. 2011). Furthermore, the warming
effect of sun radiation in enhancing NPP day for scenarios with
higher PAR, even in light-saturated Sphagnum (Figure 8C),
contradicts the observed enhancement of photosynthesis and
yield when Sphagnum grows under shaded conditions (Murray
et al. 1993; Hájek et al. 2009). Long-term high light exposure, al-
though positive in its warming effect and carbon balance, could
have a negative effect on Sphagnum photosynthesis if photoin-
hibition is triggered. Future studies about the importance of the
night period in the daily cycle of Sphagnum will shed light on
the best settings for optimizing the culturing of this important
moss and provide useful tools to monitor the future of peatlands.

5 | Conclusions

The present study establishes the photosynthesis and respira-
tion responses of S. angustifolium and S. squarrosum to tissue
water content and temperature in a short period of the growth
season (3rd–17th July). Net assimilation was quite sensitive to
water content in both species. Notably, A_N presented an opti-
mum around 25°C, while R_D increased significantly over the
same temperature range. When A_N is integrated to calculate
net primary productivity, our assimilation model reflects how
the carbon fixation of Sphagnum can potentially be affected
under certain scenarios. The simulation accounting for higher
temperatures enhanced the estimated NPP of the two studied
species if water content remained near optimum. In addition to
water availability, the reduction of carbon losses by respiration
during the night was also important for obtaining a positive
daily carbon balance in our model. Thus, even when consid-
ering optimum temperatures of 25°C, when maximum assim-
ilation rates were recorded, big variations in the NPP of both
Sphagnum species were estimated in response to variations of
the photoperiod due to reduced or enhanced carbon losses by
respiration.

Author Contributions

A.V.P.-C. and M.N. designed the experiment, applied for the funding, and conducted the experiments; A.V.P.-C. performed the analysis and wrote the first draft; both authors contributed to the final version of the manuscript.

Acknowledgments

Thanks to SMEAR II staff for their technical support and maintenance of facilities, including open data of SMEAR II Hyytiälä forest meteorological station. M.N. was supported by the postdoctoral fellowship Juan de la Cierva-Formación (FJC2020-043902-1), funded by MCIN/AEI/10.13039/501100011033 and the European Union (Next Generation EU/PRTR). Open Access funding enabled and organized by Projekt DEAL.

Data Availability Statement

The datasets used and/or analyzed during the current study are avail-
able at Zenodo (https://doi.org/10.5281/zenodo.15463352; Perera-
Castro and Nadal 2025) and from the corresponding author, Alicia V.
Perera-Castro, on reasonable request.

**References**

Asemaninejad, A., R. G. Thorn, B. A. Branfireun, and Z. Lindo. 2018. "Climate Change Favours Specific Fungal Communities in Boreal Peatlands." *Soil Biology and Biochemistry* 120: 28-36.

Bao, T., G. Jia, and X. Xu. 2022. "Warming Enhances Dominance of Vascular Plants Over Cryptogams Across Northern Wetlands." *Global Change Biology* 28: 4097-4109.

Bates, J. W. 1994. "Responses of the Mosses *Brachythecium Rutabulum* and *Pseudoscleropodium Purum* to a Mineral Nutrient Pulse." *Functional Ecology* 8: 686-693.

Bengtsson, F., G. Granath, and H. Rydin. 2016. "Photosynthesis, Growth, and Decay Traits in Sphagnum-a Multispecies Comparison." *Ecology and Evolution* 6: 3325-3341.

Bengtsson, F., H. Rydin, J. L. Baltzer, et al. 2021. "Environmental Drivers of Sphagnum Growth in Peatlands Across the Holarctic Region." *Journal of Ecology* 109: 417-431.

Bergeron, O., H. A. Margolis, and C. Coursolle. 2009. "Forest Floor Carbon Exchange of a Boreal Black Spruce Forest in Eastern North America." *Biogeosciences* 6: 1849-1864.

Beyer, C., and H. Höper. 2015. "Greenhouse Gas Exchange of Rewetted Bog Peat Extraction Sites and a *Sphagnum* Cultivation Site in Northwest Germany." *Biogeosciences* 12: 2101-2117.

Bilgili, M. 2010. "Prediction of Soil Temperature Using Regression and Artificial Neural Network Models." *Meteorology and Atmospheric Physics* 110: 59-70.

Block, W., R. I. Lewis Smith, and A. D. Kennedy. 2009. "Strategies of Survival and Resource Exploitation in the Antarctic Fellfield Ecosystem." *Biological Reviews* 84: 449-484.

Bruhn, D., F. Newman, M. Hancock, et al. 2022. "Nocturnal Plant Respiration Is Under Strong Non-Temperature Control." *Nature Communications* 13: 5650.

Calama, R., J. Puértolas, G. Madrigal, and M. Pardos. 2013. "Modeling the Environmental Response of Leaf Net Photosynthesis in *Pinus pinea* L. Natural Regeneration." *Ecological Modelling* 251: 9-21.

Calcutt, R., Y. Aghli, T. Arinzeh, and R. Dixit. 2024. "A Fibrous Scaffold for In Vitro Culture and Experimental Studies of *Physcomitrium Patens*." *Plant Direct* 8: e570.

Campbell, C., G. Granath, and H. Rydin. 2021. "Climatic Drivers of Sphagnum Species Distributions." *Frontiers of Biogeography* 13: e511.

Charman, D. J., D. W. Beilman, M. Blaauw, et al. 2013. "Climate-Related Changes in Peatland Carbon Accumulation During the Last Millennium." *Biogeosciences* 10: 929-944.

Chaudhary, N., S. Westermann, S. Lamba, et al. 2020. "Modelling Past and Future Peatland Carbon Dynamics Across the Pan-Arctic." *Global Change Biology* 26: 4119-4133.

Convey, P., S. J. Coulson, M. R. Worland, and A. Sjöblom. 2018. "The Importance of Understanding Annual and Shorter-Term Temperature Patterns and Variation in the Surface Levels of Polar Soils for Terrestrial Biota." *Polar Biology* 41: 1587-1605.

Cove, D. J., P. F. Perroud, A. J. Charron, S. F. McDaniel, A. Khandelwal, and R. S. Quatrano. 2009. "Culturing the Moss *Physcomitrella Patens*." *Cold Spring Harbor Protocols* 4: 1-7. https://doi.org/10.1101/pdb.prot5136.

Cris, R., S. Buckmaster, C. Bain, and A. Bonn. 2011. "UK Peatland Restoration—Demonstrating Success." IUCN UK National Committee Peatland Programme. Edinburgh.

Cris, R., S. Buckmaster, C. Bain, and M. Reed. 2014. "*Global Peatland Restoration Demonstrating Success.*" Edinburgh: IUCN UK National Committee Peatland Programme.
Daniels, R. E., and A. Eddy. 1990. "Handbook of European Sphagna. Institute of Terrestrial Ecology." In *Natural Environment Research Council*. London: HMSO.

de Mendiburu, F. 2021. "Agricolae: Statistical Procedures for Agricultural Research. R Package Version 1, 3–5." https://CRAN.R-project.org/package=agricolae.

Dieleman, C. M., Z. Lindo, J. W. McLaughlin, A. E. Craig, and B. A. Branfireun. 2016. "Climate Change Effects on Peatland Decomposition and Porewater Dissolved Organic Carbon Biogeochemistry." *Biogeochemistry* 128: 385–396.

Dilks, T. J. K., and M. C. F. Proctor. 1979. "Photosynthesis, Respiration and Water Content in Bryophytes." *New Phytologist* 82: 97–114.

Duckett, J. G., and S. Pressel. 2022. "Do Moss Sporophytes Maintain Water Balance? New Insights From Sporophyte Water Relations and the Wild Maturation Cycle in *Funaria Hygrometrica* Hedw." *Journal of Bryology* 44: 187–198.

Duckett, J. G., J. Burch, P. W. Fletcher, et al. 2004. "*In Vitro* Cultivation of Bryophytes: A Review of Practicalities, Problems, Progress and Promise." *Journal of Bryology* 26: 3–20.

Flanagan, L. B., and K. H. Syed. 2011. "Stimulation of Both Photosynthesis and Respiration in Response to Warmer and Drier Conditions in a Boreal Peatland Ecosystem." *Global Change Biology* 17: 2271–2287.

Flexas, J., A. Díaz-Espejo, J. A. Berry, et al. 2007. "Analysis of Leakage in IRGA'S Leaf Chambers of Open Gas Exchange Systems: Quantification and Its Effects in Photosynthesis Parameterization." *Journal of Experimental Botany* 58: 1533–1543.

Fuchs, M. 1990. "Infrared Measurement of Canopy Temperature and Detection of Plant Water Stress." *Theoretical and Applied Climatology* 42: 253–261.

Fukuta, E., A. Sasaki, and T. Nakatsubo. 2012. "Microclimate and Production of Peat Moss *Sphagnum Palustre* L. in the Warm-Temperate Zone." *Plant Species Biology* 27, no. 1: 110–118.

Furness, S. B., and J. P. Grime. 1982a. "Growth Rate and Temperature Responses in Bryophytes: I. An Investigation of *Brachythecium Rutabulum*." *Journal of Ecology* 70: 513–523.

Furness, S. B., and J. P. Grime. 1982b. "Growth Rate and Temperature Responses in Bryophytes: II. A Comparative Study of Species of Contrasted Ecology." *Journal of Ecology* 70: 525–536.

Gaberščik, A., and A. Martinčič. 1987. "Seasonal Dynamics of Net Photosynthesis and Productivity of *Sphagnum Papillosum*." *Lindbergia* 13: 105–110.

Gaudig, G., M. Krebs, A. Prager, et al. 2018. "*Sphagnum* Farming From Species Selection to the Production of Growing Media: A Review." *Mires and Peat* 20: 1–30.

Gerdol, R., and R. Vicentini. 2011. "Response to Heat Stress of Populations of Two *Sphagnum* Species From Alpine Bogs at Different Altitudes." *Environmental and Experimental Botany* 74: 22–30.

Glime, J. M. 2007. "Bryophyte Ecology." In *Michigan Technological University, Botanical Society of America & International Association of Bryologists*. Chapman and Hall.

Gong, J., N. Roulet, S. Frolking, H. Peltola, A. M. Laine, N. Kokkonen, and ES. Tuittila. 2020. "Modelling the Habitat Preference of Two Key *Sphagnum* Species in a Poor Fen as Controlled by Capitulum Water Content." *Biogeosciences* 17: 5693–5719.

Goulden, M. L., and P. M. Crill. 1997. "Automated Measurements of CO₂ Exchange at the Moss Surface of a Black Spruce Forest." *Tree Physiology* 17: 537–542.

Grace, J., and T. C. Marks. 1978. "Physiological Aspects of Bog Production at Moor House." In *Production Ecology of British Moors and*

*Montane Grasslands*, edited by D. A. Wardle, J. G. Canadell, S. Díaz, G. Heldmaier, R. B. Jackson, D. F. Levia, E. D. Schulze, and U. Sommer, 38–51. Springer.

Graham, L. E., E. Kim, P. Arancibia-Avila, J. M. Graham, and L. W. Wilcox. 2010. "Evolutionary and Ecophysiological Significance of Sugar Utilization by the Peat Moss *Sphagnum Compactum* (Sphagnaceae) and the Common Charophycean Associates *Cylindrocystis Brebissonii* and *Mougeotia* sp. (Zygnemataceae)." *American Journal of Botany* 97: 1485–1491.

Griffiths, H., K. Maxwell, D. Richardson, and W. Robe. 2004. "Turning the Land Green: Inferring Photosynthetic Physiology and Diffusive Limitations in Early Bryophytes." In *The Evolution of Plant Physiology*, edited by A. Hemsley and I. Poole, 3–16. Elsevier Academic Press.

Grime, J. P., E. R. Rincon, and B. E. Wickerson. 1990. "Bryophytes and Plant Strategy Theory." *Botanical Journal of the Linnean Society* 104: 175–186.

Grobe, A., B. Tiemeyer, and M. Graf. 2021. "Recommendations for Successful Establishment of Sphagnum Farming on Shallow Highly Decomposed Peat." *Mires and Peat* 27: 1–18.

Gunnarsson, U. 2005. "Global Patterns of *Sphagnum* Productivity." *Journal of Bryology* 27: 269–279.

Günther, A., G. Jurasinski, K. Albrecht, G. Gaudig, M. Krebs, and S. Glatzel. 2017. "Greenhouse Gas Balance of an Establishing *Sphagnum* Culture on a Former Bog Grassland in Germany." *Mires and Peat* 20: 1–16.

Hájek, T., and E. Vicherová. 2014. "Desiccation Tolerance of *Sphagnum* Revisited: A Puzzle Resolved." *Plant Biology* 16: 765–773.

Hájek, T., and R. P. Beckett. 2008. "Effect of Water Content Components on Desiccation and Recovery in *Sphagnum* Mosses." *Annals of Botany* 101: 165–173.

Hájek, T., E. S. Tuittila, M. Ilomets, and R. Laiho. 2009. "Light Responses of Mire Mosses-a Key to Survival After Water-Level Drawdown?" *Oikos* 118: 240–250.

Hanson, P. J., N. A. Griffiths, C. M. Iversen, et al. 2020. "Rapid Net Carbon Loss From a Whole-Ecosystem Warmed Peatland." *AGU Advances* 1: e2020AV000163.

He, X., K. S. He, and J. Hyvonen. 2016. "Will Bryophytes Survive in a Warming World?" *Perspectives in Plant Ecology, Evolution and Systematics* 19: 49–60.

Heskel, M. A., O. S. O'sullivan, and P. B. Reich. 2016. "Convergence in the Temperature Response of Leaf Respiration Across Biomes and Plant Functional Types." *Proceedings of the National Academy of Sciences of the United States of America* 113: 3832–3837.

Horsley, K., L. R. Stark, and D. N. McLetchie. 2011. "Does the Silver Moss *Bryum argenteum* Exhibit Sex-Specific Patterns in Vegetative Growth Rate, Asexual Fitness or Prezygotic Reproductive Investment?" *Annals of Botany* 107: 897–907.

Hoshi, Y. 2017. "*Sphagnum* Growth in Floating Cultures: Effect of Planting Design." *Mires and Peat* 20: 1–10.

Jauhiainen, J., and J. Silvola. 1999. "Photosynthesis of *Sphagnum Fuscum* at Long-Term Raised CO₂ Concentrations." *Annales Botanici Fennici* 36: 11–19.

Karki, S., T. P. Kandel, L. Elsgaard, R. Labouriau, and P. E. Lærke. 2019. "Annual CO₂ Fluxes From a Cultivated Fen With Perennial Grasses During Two Initial Years of Rewetting." *Mires and Peat* 25: 1–22.

Kellner, E., and S. Halldin. 2002. "Water Budget and Surface-Layer Water Storage in a *Sphagnum* Bog in Central Sweden." *Hydrological Processes* 16: 87–103.

Kurnianto, S., M. Warren, J. Talbot, B. Kauffman, D. Murdiyarso, and S. Frolking. 2015. "Carbon Accumulation of Tropical Peatlands Over Millennia: A Modeling Approach." *Global Change Biology* 21: 431–444.
Laing, C., G. Granath, L. R. Belyea, K. E. Allton, and H. Rydin. 2014. "Tradeoffs and Scaling of Functional Traits in *Sphagnum* as Drivers of Carbon Cycling in Peatlands." *Oikos* 123: 817-828.

Lembrechts, J. J., and J. Lenoir. 2020. "Microclimatic Conditions Anywhere at any Time!" *Global Change Biology* 26: 337-339.

Lembrechts, J. J., J. Lenoir, N. Roth, et al. 2019. "Comparing Temperature Data Sources for Use in Species Distribution Models: From In-Situ Logging to Remote Sensing." *Global Ecology and Biogeography* 28: 1578-1596.

Li, Y., X. Song, S. Li, W. T. Salter, and M. M. Barbour. 2020. "The Role of Leaf Water Potential in the Temperature Response of Mesophyll Conductance." *New Phytologist* 225: 1193-1205.

Limpens, J., F. Berendse, C. Blodau, et al. 2008. "Peatlands and the Carbon Cycle: From Local Processes to Global Implications-a Synthesis." *Biogeosciences* 5: 1475-1491.

Lösch, R., P. Mülders, E. Fischer, and J. P. Frahm. 1994. "Scientific Results of the BRYOTROP Expedition to Zaire and Rwanda. 3. Photosynthetic Gas Exchange of Bryophytes From Different Forest Types in Eastern Central Africa." *Tropical Bryology* 9: 169-185.

Lunt, P. H., R. M. Fyfe, and A. D. Tappin. 2019. "Role of Recent Climate Change on Carbon Sequestration in Peatland Systems." *Science of the Total Environment* 667: 348-358.

Ma, X., H. Xu, Z. Cao, L. Shu, and R. Zhu. 2022. "Will Climate Change Cause the Global Peatland to Expand or Contract? Evidence From the Habitat Shift Pattern of *Sphagnum* Mosses." *Global Change Biology* 28: 6419-6432.

Márquez, D. A., and F. A. Busch. 2024. "The Interplay of Short-Term Mesophyll and Stomatal Conductance Responses Under Variable Environmental Conditions." *Plant, Cell & Environment* 47: 3393-3410.

Marschall, M., and P. Borbély. 2011. "Photosynthetic Responses of the Desiccation Intolerant *Sphagnum Angustifolium* in Relation to Increasing Its Desiccation Tolerance by Exogenous ABA." *Acta Biologica Szegediensis* 55: 119-121.

Matsuda, T. 1968. "Ecological Study of the Moss Community and Microorganisms in the Vicinity of Syowa Station, Antarctica." *JARE Scientific Reports. Ser. E, Biology* 29: 1-58.

McCarter, C. P., and J. S. Price. 2014. "Ecohydrology of *Sphagnum* Moss Hummocks: Mechanisms of Capitula Water Supply and Simulated Effects of Evaporation." *Ecohydrology* 7: 33-44.

Melosik, I., and S. M. Såstad. 2005. "In Vitro Propagation of Selected *Sphagnum* Species (Section Subsecunda)." *Lindbergia* 30: 21-31.

Mendoza, V., M. Pazos, R. Garduño, and B. Mendoza. 2021. "Thermodynamics of Climate Change Between Cloud Cover, Atmospheric Temperature and Humidity." *Scientific Reports* 11: 21244.

Moore, P. A., T. G. Pypker, and J. M. Waddington. 2013. "Effect of Long-Term Water Table Manipulation on Peatland Evapotranspiration." *Agricultural and Forest Meteorology* 178: 106-119.

Murray, K. J., J. D. Tenhunen, and R. S. Nowak. 1993. "Photoinhibition as a Control on Photosynthesis and Production of *Sphagnum* Mosses." *Oecologia* 96: 200-207.

Nakanishi, R., and S. Tsuyuzaki. 2024. "Litter Decomposition Rates in a Post-Mined Peatland: Determining Factors Studied in Litterbag Experiments." *Environmental Processes* 11, no. 1: 2.

Oechel, W. C., and K. Van Cleve. 1986. "The Role of Bryophytes in Nutrient Cycling in the Taiga." In *Forest Ecosystems in the Alaskan Taiga: A Synthesis of Structure and Function*, edited by K. Cleve, F. S. Chapin, P. W. Flanagan, L. A. Viereck, and C. T. Dyrness, 121-137. Springer New York.

Page, S. E., and A. J. Baird. 2016. "Peatlands and Global Change: Response and Resilience." *Annual Review of Environment and Resources* 41: 35-57.

Pannewitz, S., T. A. Green, K. Maysek, et al. 2005. "Photosynthetic Responses of Three Common Mosses From Continental Antarctica." *Antarctic Science* 17: 341-352.

Perera-Castro, A. V., Á. M. González-Rodríguez, and B. Fernández-Marin. 2022. "When Time Is Not of the Essence: Constraints to the Carbon Balance of Bryophytes." *Journal of Experimental Botany* 73: 4562-4575.

Perera-Castro, A. V., and M. Nadal. 2025. "Data From: Modelling Net CO₂ Assimilation of Two Sphagnum Species From Temperature and Water Content Response. Zenodo." https://doi.org/10.5281/zenodo.15463352.

Perera-Castro, A. V., M. J. Waterman, J. D. Turnbull, et al. 2020. "It Is Hot in the Sun: Antarctic Mosses Have High Temperature Optima for Photosynthesis Despite Cold Climate." *Frontiers in Plant Science* 11: 1178.

Perera-Castro, A. V., M. J. Waterman, S. A. Robinson, and J. Flexas. 2022. "Limitations to Photosynthesis in Bryophytes: Certainties and Uncertainties Regarding Methodology." *Journal of Experimental Botany* 73: 4592-4604.

Piatkowski, B. T., and A. J. Shaw. 2019. "Functional Trait Evolution in *Sphagnum* Peat Mosses and Its Relationship to Niche Construction." *New Phytologist* 223: 939-949.

Pinheiro, J., D. Bates, and R Core Team. 2023. "nlme: Linear and Nonlinear Mixed Effects Models. R Package Version 3: 1-162." https://CRAN.R-project.org/package=nlme.

Proctor, M. C. 2000. "The Bryophyte Paradox: Tolerance of Desiccation, Evasion of Drought." *Plant Ecology* 151: 41-49.

Proctor, M. C. F., and Z. Tuba. 2002. "Poikilohydry and Homoiohydry: Antithesis or Spectrum of Possibilities?" *New Phytologist* 156: 327-349.

Proctor, M. C. F., M. J. Oliver, A. J. Wood, et al. 2007. "Desiccation-Tolerance in Bryophytes: A Review." *Bryologist* 110: 595-621.

Proctor, M. C. F., Z. Nagy, Z. Csintalan, and Z. Takács. 1998. "Water Content Components in Bryophytes: Analysis of Pressure Volume Relationships." *Journal of Experimental Botany* 49: 1845-1854.

Qiu, C., D. Zhu, P. Ciais, B. Guenet, and S. Peng. 2020. "The Role of Northern Peatlands in the Global Carbon Cycle for the 21st Century." *Global Ecology and Biogeography* 29: 956-973.

R Core Team. 2023. *R: A Language and Environment for Statistical Computing*. R Foundation for Statistical Computing. https://www.R-project.org/.

Raven, J. A. 2002. "Putting the Fight in Bryophytes." *New Phytologist* 156: 321-323.

Raven, J. A., and D. Edwards. 2004. "Physiological Evolution of Lower Embryophytes: Adaptations to the Terrestrial Environment." In *The Evolution of Plant Physiology*, edited by A. R. Hemsley and I. Poole, 17-41. Elsevier Academic Press.

Rice, S. K., N. Neal, J. Mango, and K. Black. 2011. "Modeling Bryophyte Productivity Across Gradients of Water Availability Using Canopy Form Function Relationships." In *Tuba Z, Stack NG, Stark LR, Bryophyte Ecology and Climate Change, 441-457*. University Press, Cambridge.

Rice, S. K., T. A. Gagliardi, and R. A. Krasa. 2018. "Canopy Structure Affects Temperature Distributions and Free Convection in Moss Shoot Systems." *American Journal of Botany* 105: 1499-1511.

Rudolph, H. 1968. "Gas Exchange Determinations of *Sphagnum magellanicum*: A Contribution to the Problem of Membrane Pigments in *Sphagna* (III)." *Planta* 79: 35-43.

Schenker, R., and W. Block. 1986. "Micro-Arthropod Activity in Three Contrasting Terrestrial Habitats on Signy Island, Maritime Antarctic." *British Antarctic Survey Bulletin* 71: 31-43.
Schipperges, B., and H. Rydin. 1998. "Response of Photosynthesis of Sphagnum Species From Contrasting Microhabitats to Tissue Water Content and Repeated Desiccation." *New Phytologist* 140: 677–684.

Serk, H., M. B. Nilsson, J. Figueira, T. Wieloch, and J. Schleucher. 2021. "CO₂ Fertilization of *Sphagnum* Peat Mosses Is Modulated by Water Table Level and Other Environmental Factors." *Plant, Cell & Environment* 44: 1756–1768.

Silvan, N., K. Jokinen, J. Näkkilä, and R. Tahvonen. 2017. "Swift Recovery of *Sphagnum* Carpet and Carbon Sequestration After Shallow *Sphagnum* Biomass Harvesting." *Mires and Peat* 20: 1–11.

Silvola, J., and H. Aaltonen. 1984. "Water Content and Photosynthesis in the Peat Mosses *Shagnum Fuscum* and *S. Angustifolium*." *Annales Botanici Fennici* 21: 1–6.

Silvola, J., and I. Hanski. 1979. "Carbon Accumulation in a Raised Bog. Simulation on the Basis of Laboratory Measurements of CO₂ Exchange." *Oecologia* 37: 285–295.

Silvola, J., and S. Heikkinen. 1979. "CO₂ Exchange in the *Empetrum nigrum-Sphagnum fuscum* Community." *Oecologia* 37: 273–283.

Sim, T. G., G. T. Swindles, P. J. Morris, et al. 2021. "Divergent Responses of Permafrost Peatlands to Recent Climate Change." *Environmental Research Letters* 16: 034001.

Smith, E. L. 1936. "Photosynthesis in Relation to Light and Carbon Dioxide." *Proceedings of the National Academy of Sciences of the United States of America* 22: 504–511.

Smith, R. I. L. 1996. "Terrestrial and Freshwater Biotic Components of the Western Antarctic Peninsula." In *Foundations for Ecological Research West of the Antarctic Peninsula*, edited by R. M. Ross, I. I. E. Hoffmann, and L. B. Quetin, 15–59. American Geophysical Union.

Stålfelt, M. G. 1937. "Der Gasaustausch der Moose." *Planta* 27: 30–60.

Street, L. E., P. C. Stoy, M. Sommerkorn, et al. 2012. "Seasonal Bryophyte Productivity in the Sub-Arctic: A Comparison With Vascular Plants." *Functional Ecology* 26: 365–378.

Swindles, G. T., J. Holden, C. L. Raby, et al. 2015. "Testing Peatland Water-Table Depth Transfer Functions Using High-Resolution Hydrological Monitoring Data." *Quaternary Science Reviews* 120: 107–117.

Tanneberger, F., C. Tegetmeyer, S. Busse, et al. 2017. "The Peatland Map of Europe." *Mires and Peat* 19: 1–17.

Thompson, D. K., and J. M. Waddington. 2008. "*Sphagnum* Under Pressure: Towards an Ecohydrological Approach to Examining *Sphagnum* Productivity." *Ecohydrology* 1: 299–308.

Titus, J. E., and D. J. Wagner. 1984. "Carbon Balance for Two *Sphagnum* Mosses: Water Balance Resolves a Physiological Paradox." *Ecology* 65: 1765–1774.

Updegraff, K., S. D. Bridgham, J. Pastor, P. Weishampel, and C. Harth. 2001. "Response of CO₂ and CH₄ Emissions From Peatlands to Warming and Water Table Manipulation." *Ecological Applications* 11: 311–326.

Van Breemen, N. 1995. "How *Sphagnum* Bogs Down Other Plants." *Trends in Ecology & Evolution* 10: 270–275.

Velez-Ramirez, A. I., W. van Ieperen, D. Vreugdenhil, and F. F. Millenaar. 2011. "Plants Under Continuous Light." *Trends in Plant Science* 16: 310–318.

Venäläinen, A., I. Lehtonen, M. Laapas, et al. 2020. "Climate Change Induces Multiple Risks to Boreal Forests and Forestry in Finland: A Literature Review." *Global Change Biology* 26: 4178–4196.

Vile, M. A., K. D. Scott, E. Brault, R. K. Wieder, and D. H. Vitt. 2011. "Living on the Edge: The Effects of Drought on Canada's Western Boreal Peatlands." In *Bryophyte Ecology and Climate Change*, edited by Z. Tuba, N. G. Slack, and L. R. Stark, 277–298. Cambridge University Press.

Vitt, D. H., B. Crandall-Stotler, and A. Wood. 2014. "Bryophytes: Survival in a Dry World Through Tolerance and Avoidance." In *Plant Ecology and Evolution in Harsh Environments*, edited by N. Rajakaruna, R. Boyd, and T. Harris, 267–295. Nova Publishers.

Walker, A. P., K. R. Carter, L. Gu, et al. 2017. "Biophysical Drivers of Seasonal Variability in *Sphagnum* Gross Primary Production in a Northern Temperate Bog." *Journal of Geophysical Research: Biogeosciences* 122: 1078–1097.

Walter, H. 1931. *Die Hydratur der Pflanze und ihre physiologisch-ökologische Bedeutung*. Fischer.

Wang, Z., and M. Y. Bader. 2018. "Associations Between Shoot-Level Water Relations and Photosynthetic Responses to Water and Light in 12 Moss Species." *AoB Plants* 10: ply034.

Wickham, H. 2011. "The Split-Apply-Combine Strategy for Data Analysis." *Journal of Statistical Software* 40: 1–29.

Wickham, H. 2016. *ggplot2: Elegant Graphics for Data Analysis*. Springer-Verlag.

Wu, J., and N. T. Roulet. 2014. "Climate Change Reduces the Capacity of Northern Peatlands to Absorb the Atmospheric Carbon Dioxide: The Different Responses of Bogs and Fens." *Global Biogeochemical Cycles* 28: 1005–1024.

Yin, H., A. V. Perera-Castro, K. L. Randall, et al. 2023. "Basking in the Sun: How Mosses Photosynthesise and Survive in Antarctica." *Photosynthesis Research* 158: 151–169.

Zhao, B., and Q. Zhuang. 2023. "Peatlands and Their Carbon Dynamics in Northern High Latitudes From 1990 to 2300: A Process-Based Biogeochemistry Model Analysis." *Biogeosciences* 20: 251–270.

## Supporting Information

Additional supporting information can be found online in the Supporting Information section.