
==== Front
Sci Rep
Sci Rep
Scientific Reports
2045-2322
Nature Publishing Group UK London

39294249
72526
10.1038/s41598-024-72526-5
Article
Diagnostic species are crucial for the functioning of plant associations in inland salt marshes
http://orcid.org/0000-0001-5969-0067
Lubińska-Mielińska Sandra slm@umk.pl

http://orcid.org/0000-0003-4083-5822
Rajabi Dehnavi Ahmad
http://orcid.org/0000-0003-3919-3498
Cárdenas Pérez Stefany
http://orcid.org/0000-0001-7842-6704
Kamiński Dariusz
http://orcid.org/0000-0002-0800-5266
Piernik Agnieszka piernik@umk.pl

https://ror.org/0102mm775 grid.5374.5 0000 0001 0943 6490 Department of Geobotany and Landscape Planning, Faculty of Biological and Veterinary Sciences, Nicolaus Copernicus University in Toruń, Lwowska 1, 87-100 Toruń, Poland
18 9 2024
18 9 2024
2024
14 2178728 2 2024
9 9 2024
© The Author(s) 2024
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
Salt marsh vegetation is considered unique and valuable and has been legally protected in Europe for years but is still declining. Its protection is related to vegetation syntaxonomical units. The characteristic combination of diagnostic species is used to create this syntaxonomical system. The aim of our novel study was to assess whether diagnostic species are sufficient for characterising vegetation functioning. Moreover, we included biochemical traits not considered to date in vegetation ecology. We hypothesised that (1) diagnostic species are crucial for the functioning of inland salt marsh vegetation and (2) their morphological and biochemical traits define the functioning of typical salt marsh associations. We chose three typical inland associations to test our hypotheses and measured the morphological and biochemical functional traits of their diagnostic plant species. Our research has shown that diagnostic species play a crucial role not only in distinguishing typical inland salt marsh associations but also in determining their functioning. Among the analysed associations, Salicornietum ramosissimae was the most adaptable to osmotic and oxidative stress under soil salinity. Triglochino maritimae-Glaucetum maritimae showed the lowest salt resistance, as indicated by the highest osmotic and oxidative stress and stress responses. Our findings may facilitate the practical application of new approaches and protection strategies for inland salt marsh habitats.

Subject terms

Salt
Plant ecology
Plant sciences
issue-copyright-statement© Springer Nature Limited 2024
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pmcIntroduction

The plant species that most effectively exhibit specific ecological relationships within a given community are used as indicators in vegetation classification and are called diagnostic species (Dg)1. According to the phytosociological concept, Dg species prefer a single or few vegetation units, allowing for the delimitation of plant communities2. Dgs create specific and repeatable co-occurring species composition associated with historical background and environmental and geographical conditions under which plant communities develop3. The characteristic combination of Dg species is used to create a hierarchical classification system of plant communities. This system has been consistently developed and expanded based on maximal floristic and ecological similarity principle, with the association serving as the fundamental unit4. In fact, identifying individual communities is contingent upon the presence or absence of Dg plant species5. Within this selection framework, phytosociological fidelity, cover percentage, and frequency are crucial indicators1. Currently, phytosociologists determine Dg species based on fidelity measured by the Phi coefficient as a statistical measure of the concentration and occurrence of species in phytosociological units3,6–8. Positive Phi values indicate that the species and the vegetation unit co-occur more frequently than would be expected by chance. Larger values indicate a greater degree of joint fidelity with the maximum value at 1. Phi determination is supported by relevant software, e.g. JUICE9.

The most recent classification of European vegetation grouped inland salt marshes into two classes10. The class Therosalicornietea Tx. in Tx. et Oberd. 1958, order Therosalicornietalia Pignatti 1952, and alliance Salicornion ramosissimae Tx. 1974 includes pioneer vegetation of annual succulent halophytes. The class Festuco-Puccinellietea Soó ex Vicherek 1973, order Scorzonero-Juncetalia gerardi Vicherek 1973, and alliance Juncion gerardi Wendelberger 1943 include inland salt meadows of temperate salt marshes. The main environmental drivers of this vegetation have already been identified, such as a high-salt groundwater level, flooding, and management by moving and grazing, which are recommended for their conservation11–15. Although inland salt marshes in Europe have been protected for years and included in 1992 in the Natura 2000 network16, they are still declining and are considered endangered17. Natural salt marsh habitats are critically important in the face of increasing salinity problems in agriculture worldwide18. They can serve as a source of natural, unique plant species adapted to high soil salinity that can be applied in future saline agriculture19,20. Hence, it is imperative to explore novel approaches to address the question of which additional factors should be considered to prevent the depletion of salt marshes.

Recent investigations have demonstrated that syntaxonomical units and their functioning may be related to specific plant functional traits21–23. Our recent research also showed link between syntaxonomical and functional approaches to the vegetation, i.e. that the syntaxonomical system also reflects functional differences between classes and associations24. Persistence traits, such as specific leaf area, canopy height, clonal index, leaf dry matter content, leaf mass, and clonality, are the most important for separating classes and associations. Additionally, regeneration traits, including seed number, play a significant role. We observed that the classes Therosalicornietea and Festuco-Puccinelietea, and association Salicornietum ramosissimae are the most sensitive to environmental changes due to their low persistence and regeneration potentials. Therefore, special attention should be given to these units in the protection process.

Typically, such research on the functional traits of vegetation is based on all species and data from large databases, which include many measurements or average values and a limited set of functional traits, e.g., by Kleyer et al.25 or Lubińska-Mielińska et al.24. Biochemical traits related to salt stress responses were not included. Moreover, there is still poor link between concept of Dg species for syntaxonomical units and their indicative functional traits concept. Some research shows that it is possible to identify Dg species for particular habitat subtypes due to their functional traits26. Few research look for ways to take functional species traits into account in assessing their diagnostic value for group of vegetation sites27. Therefore, we decided to concentrate in the current research only on measured traits for Dg species already determined for inland salt marsh associations and compare results based on the LEDA Traitbase25. The aim of this novel study was to ascertain whether including all species in inland salt marsh associations trait analyses is essential or whether focusing solely on Dg species is sufficient for assessment of their functional characteristics. We hypothesised that (1) Dg species are crucial for the functioning of inland salt marsh vegetation and that (2) their morphological and biochemical traits define the functioning of typical salt marsh associations. To test our hypotheses, we chose three inland associations, the most common in Poland, and measured the functional traits of their Dg species. We used field-collected data from a single location with consistent high salinity levels to include both morphological and biochemical traits, which are unavailable in functional trait databases. This site was chosen because the three selected associations were present in this relatively small area, forming a mosaic of small patches. Moreover, extremely strong soil salinity (> 16 dS·m−1) has been stable in this area for several years28–30. This approach allows for a detailed characterisation of traits specific to individual associations and provides a partial validation of the relationships by leveraging morphological data from the LEDA Traitbase25.

Results

Diagnostic species functional traits

The results concerning Dg species show that they differ significantly in measured persistence traits (see Tables 1 and S1). The highest values were found for Dg species of the Triglochino maritimae-Glaucetum maritimae (Tm-Gm) association, i.e., Phragmites australis—shoot length (SL), shoots dry weight (SDW), leaves area (LA), leaves fresh and dry weight (LFW and LDW), and the leaf dry matter content (LDMC) of Juncus compressus. Glaux maritima had the highest specific leaf area index (SLA), while Potentilla anserina had the highest leaf mass (LM) and leaf weight ratio (LWR). In terms of the roots parameters, P. australis also had the greatest root length (RL) and roots fresh and dry weight (RFW and RDW), while J. compressus had the greatest root weight ratio (RWR). Salicornia europaea, a Dg species of the Salicornietum ramosissimae (Sr) association, had the highest shoots fresh weight (SFW), shoot weight ratio (SWR), and assimilation area (AA) after P. australis. Atriplex prostrata, Puccinellia distans, and G. maritima were characterised by the greatest number of leaves (NoL). The morphological traits of Spergularia marina and Triglochin maritima were intermediate. Table 1 Diagnostic species within three typical inland salt-marsh associations in temperate Europe according to Lubińska-Mielińska et al. 11.

Associations	Abbreviations	Diagnostic species	
Class: Therosalicornietea Tx. in Tx. et Oberd. 1958	THE	(see association ↓)	
Salicornietum ramosissimae Christiansen 1955	Sr	Salicornia europaea L.	
Class: Festuco-Puccinellietea Soó ex Vicherek 1973	FEP	(see associations ↓)	
Triglochino maritimae-Glaucetum maritimae

Wilkoń-Michalska 1963 ex Dítě et al. ass. nov. 2022

	Tm-Gm	Triglochin maritima L.

Glaux maritima L. (= Lysimachia maritima (L.) Galasso, Banfi & Soldano)

Phragmites australis (Cav.) Steud

Juncus compressus Jacq

Potentilla anserina L.

	
Puccinellio-Spergularietum salinae (Feekes 1936) R.Tx. at Volk 1937	P-Ss	Spergularia marina (L.) Besser

Puccinellia distans (Jacq.) Parl

Atriplex prostrata Boucher ex DC

	
Classes to which individual associations belong are marked in bold.

For biochemical parameters, the highest contents of the photosynthetic pigments chlorophyll a (chla), b (chlb), total (chlt), and carotenoids (car), were found in P. anserina, P. australis, and G. maritima, which are the Dg species for the Tm-Gm association; P. distans and A. prostrata, which are the Dg species for the Puccinellio-Spergularietum salinae (P-Ss) association (Table S2). Among the substances involved in osmoregulation, proline (prol) was most abundant in T. maritima and P. distans, and carbohydrates (carbo) were most abundant in G. maritima, J. compressus, and A. prostrata. Substances acting as oxidative stress markers were also the most abundant in the Dg species of both associations. The highest hydrogen peroxide (H2O2) levels were detected in G. maritima and A. prostrata, while the highest malondialdehyde (MDA) levels were detected in P. australis, J. compressus, P. anserina, and P. distans. The highest antioxidant enzyme activities were observed in Dg species of the Tm-Gm association, i.e., catalase (CAT) activity in G. maritima and P. anserina and peroxidase (APX) activity in T. maritima, P. australis, and P. anserina.

Plant associations morphological traits

The results of trait comparisons weighted by Dg species cover averages for associations demonstrated that the highest canopy (SL) was typical for Tm-Gm and the shortest for Sr (see Fig. 1). The Tm-Gm association was also characterised by the highest RL and belowground biomass (RFW and RDW), while the Sr association had the highest aboveground biomass (SFW and SDW). The P-Ss association had the shortest RL and the lowest RFW.Fig. 1 Comparison of morphological traits related to shoots, roots, and leaves parameters for vegetation associations. Significantly different groups (at p ≤ 0.05), according to the Kruskal‒Wallis test with Dunn post hoc comparisons, are denoted by different letters. Abbreviations of associations: Sr—Salicornietum ramosissimae (n = 133), P-Ss—Puccinellio-Spergularietum salinae (n = 134), Tm-Gm—Triglochino maritimae-Glaucetum maritimae (n = 56).

Among the parameters related to leaves (see Fig. 1), the Tm-Gm association had the highest LFW, LDW, single LM and LA. The highest NoL was recorded for the P-Ss association. Thus far, the lowest leaves parameter values were observed for the Sr association. However, the AA of this association was the highest. As mentioned, the Dg species of the Sr association is S. europaea, the entire shoots of which have assimilation functions.

Figure 2 compares individual association indices calculated based on morphological parameters. The Sr association was characterised by the highest SWR, while the Tm-Gm association had the highest RWR, LWR, SLA, and LDMC. The P-Ss association had intermediate values in all cases except LDMC, which was similar to that of the Tm-Gm association.Fig. 2 Comparison of indices calculated based on morphological traits for vegetation associations. Significantly different groups (at p ≤ 0.05), according to the Kruskal‒Wallis test with Dunn post hoc comparisons, are denoted by different letters. Abbreviations of associations: Sr—Salicornietum ramosissimae (n = 133), P-Ss—Puccinellio-Spergularietum salinae (n = 134), Tm-Gm—Triglochino maritimae-Glaucetum maritimae (n = 56).

The principal component analysis (PCA) and the correlation of traits with the ordination axes (Fig. 3a and Table 2) revealed differences between the analysed associations due to morphological traits. The first ordination axis (PC1) explained 54.3% of the trait variability. It was positively correlated with most leaves parameters, such as LM, LFW, LDW, LA, LDMC, SLA, LWR, and the SL and RWR characteristics of the Tm-Gm association. PC1 was also strongly negatively correlated with SFW and SWR, with the highest correlation occurring for the Sr association. The second axis (PC2) explained 29.7% of the variance and was positively correlated with AA, SDW, and RL. The correlations were stronger in the Sr and Tm-Gm associations than in the P-Ss association. PC2 was most strongly negatively correlated with NoL in the P-Ss association, for which the centroid was located in the lower part of the PCA graph.Fig. 3 Results of principal component analysis (PCA) showing the relationships between the analysed associations and (a) morphological functional traits and (b) biochemical functional traits. The red star marks the centroid of each group. Abbreviations of associations: Sr—Salicornietum ramosissimae (n = 133), P-Ss—Puccinellio-Spergularietum salinae (n = 134), Tm-Gm—Triglochino maritimae-Glaucetum maritimae (n = 56).

Table 2 Results of Spearman’s correlation (rs) of morphological functional traits with the principal component analysis (PCA) ordination axes.

	PC 1	PC 2	SL	RL	SFW	SDW	RFW	RDW	NoL	LM	LFW	LDW	LA	AA	LDMC	SLA	SWR	RWR	LWR	
PC 1		− 0.07	0.79****	0.21***	− 0.73****	− 0.54****	0.51****	0.54****	0.39****	0.84****	0.86****	0.84****	0.83****	− 0.45****	0.83****	0.83****	− 0.94****	0.87****	0.92****	
PC 2	− 0.07		0.36****	0.71****	0.66****	0.82****	0.69****	0.59****	− 0.74****	0.16**	0.07	0.13*	0.10	0.87****	− 0.35****	− 0.45****	0.27****	− 0.16**	− 0.33****	
Correlation coefficients greater than 0.7 are marked in bold.

Abbreviations of morphological functional traits: SL shoot length, RL root length, SFW shoots fresh weight, SDW shoots dry weight, RFW roots fresh weight, RDW roots dry weight, NoL number of leaves, LM leaf mass, LFW leaves fresh weight, LDW leaves dry weight, LA leaves area, AA assimilation area, LDMC leaf dry matter content, SLA specific leaf area, SWR shoot weight ratio, RWR root weight ratio, LWR leaf weight ratio.

Statistically significant values are marked by asterisks: * p ≤ 0.05, ** p ≤ 0.01, *** p ≤ 0.001, **** p ≤ 0.0001.

Plant associations biochemical traits

Figure 4 summarises biochemical traits related to photosynthetic pigment contents—chla, chlb, chlt, and car; osmoregulation—prol and carbo; stress indicators—H2O2 and MDA; and antioxidant enzyme activities—CAT and APX. The parameters related to photosynthetic pigment content were the lowest for Sr, intermediate for P-Ss, and the highest for the Tm-Gm association. The other parameters, except for MDA and prol, were highest for the Tm-Gm association. MDA was the highest for the P-Ss association, while prol was the highest for both of these associations. The lowest value for prol was obtained for the Sr association, and that for carbo was obtained for the P-Ss association. The lowest values of stress indicators and antioxidant enzyme activity were recorded for the Sr association. CAT activity was also low in the P-Ss association.Fig. 4 Comparison of biochemical functional traits for vegetation associations. Significantly different groups (at p ≤ 0.05), according to the ANOVA with Tukey’s post hoc comparisons, are denoted by different letters. Abbreviations of associations: Sr—Salicornietum ramosissimae (n = 133), P-Ss—Puccinellio-Spergularietum salinae (n = 134), Tm-Gm—Triglochino maritimae-Glaucetum maritimae (n = 56).

PCA (Fig. 3b) and the correlation of traits with the ordination axes (Table 3) revealed differences in the analysed associations due to biochemical traits. The first ordination axis (PC1) explained 70.5% of the variability. It was positively correlated with the prol, MDA, and car contents, which were highest in the P-Ss and Tm-Gm associations and lowest in the Sr association. The second axis (PC2) explained 24.0% of the variance. It was positively correlated with H2O2 content, APX activity, and chla, chlb, and chlt contents. The highest correlation was observed in the Tm-Gm association, for which the centroid was located in the upper right part of the graph, and the lowest was observed for the Sr association. Table 3 Results of Spearman’s correlation (rs) of biochemical functional traits with the principal component analysis (PCA) ordination axes.

	PC 1	PC 2	chla	chlb	chlt	car	prol	carbo	H2O2	MDA	CAT	APX	
PC 1		0.02	0.40****	0.48****	0.43****	0.54****	0.99****	− 0.48****	− 0.23****	0.70****	0.02	0.37****	
PC 2	0.02		0.59****	0.62****	0.60****	0.50****	0.09	0.46****	0.96****	0.00	0.16**	0.62****	
Correlation coefficients greater than 0.5 are marked in bold.

Abbreviations of biochemical functional traits: chla chlorophyll a, chlb chlorophyll b, chlt total chlorophyll, car carotenoids, prol proline, carbo carbohydrates, H2O2 hydrogen peroxide, MDA malondialdehyde, CAT catalase, APX ascorbate peroxidase.

Statistically significant values are marked by asterisks: * p ≤ 0.05, ** p ≤ 0.01, *** p ≤ 0.001, **** p ≤ 0.0001.

Key role of diagnostic species

To test the key role of Dg species, we compared data from the LEDA Traitbase25 based on weighted means of nine Dg species with weighted means of all species recorded in the plots. We compared the five functional traits of the Sr, P-Ss, and Tm-Gm associations: canopy height (CH), leaf size (LS), leaf mass (LM), leaf dry matter content (LDMC), and specific leaf area (SLA). In all cases, except those involving LM, the results for the analysed associations were identical (see Fig. 5). The results for the Sr and P-Ss associations calculated using data for only Dg species showed no difference in LM, but when using data for all species, LM was clearly lower for the Sr association. Despite these small differences, the results indicate a key role for Dg species in plant communities functioning in salt marshes. Given the greater sensitivity of LM, future studies are needed to identify such labile traits.Fig. 5 Comparison of functional traits based on LEDA Traitbase data 25 for vegetation associations. Significantly different groups (at p ≤ 0.05), according to the Kruskal‒Wallis test with Dunn post hoc comparisons, are denoted by different letters. Abbreviations of associations: Sr—Salicornietum ramosissimae (n = 133), P-Ss—Puccinellio-Spergularietum salinae (n = 134), Tm-Gm—Triglochino maritimae-Glaucetum maritimae (n = 56).

We also validated the data from the LEDA Traitbase25 by comparing the results with those based on field measurements. The LEDA CH can be considered equivalent to our SL, and the LEDA LS is comparable to our 1LA. The other three parameters, LM, LDMC, and SLA, are the same. The comparison showed that the weighted means of species traits, in general, reflect differences in CH, LA, and LM between associations. The greatest differences between the results were found for LDMC and SLA (Fig. S1). For LDMC, the highest value was obtained for the P-Ss association based on measurements instead of the lowest, and for SLA, the P-Ss and Tm-Gm associations switched places.

Discussion

Adaptive strategies

Our previous results24 showed that persistence traits are the most important for separating classes and associations among the vegetation of inland salt marshes in temperate Europe. Therefore, we decided to take a closer look at the functional strategies of associations representing both typical salt marsh classes Therosalicornietea and Festuco-Puccinelietea, including measuring the most important morphological traits responsible for persistence and previously unaccounted-for biochemical parameters. The results of the morphological trait analysis revealed significant differences among the three considered associations. These differences were particularly notable for various leaves’ parameters. Remarkably, the Tm-Gm association exhibited the highest values for these traits. The high dry and fresh weight values revealed relatively high biomass production in this association. That is why, habitats occupied by Tm-Gm are frequently reported as pastures or hay meadows31,32. The relatively high leaf dry matter content in the Tm-Gm association confirms, on the one hand, the higher productivity of this association33 but, on the other hand, the lower acquisitive strategy34. The results also prove the role of roots in association productivity. The highest root weight ratio in the Tm-Gm association was related to the greatest ability to acquire water and nutrients from the soil35. An increase in roots parameters such as length and weight indicates the plasticity of the plant species, which is adapted to salinity stress36,37. A high leaves area directly influences the highest specific leaf area38. Plants grown in resource-rich environments can increase their photosynthetic capacity and productivity via higher SLAs39. Therefore, Tm-Gm can be considered as growing in resource richer places than Sr and P-Ss. Specific leaf area is also linked to water use or survival strategies40. Plants adopt the strategy of smaller SLAs to improve stress resistance and competitive ability in stressful environments41 because large leaves tend to require greater biomass investments per unit of leaves area than small leaves42. The relatively high SLA of Tm-Gm informs about its relatively lower adaptation and competitive ability compared to Sr and P-Ss under salinity conditions.

The highest values of assimilation area, shoots fresh weight, shoots dry weight, and shoot weight ratio were characteristic of the Sr association. This association is dominated by the extreme halophyte S. europaea, whose reduced leaves and succulent shoots take over during the assimilation process43. The high fresh weight can be affected by water accumulation, and a greater dry weight can be affected by ionic accumulation44. The leaf reduction of this Dg species affects the low specific leaf area and proves its stress resistance and high competitive ability under high soil salinity41. A low leaf dry matter content in the Sr association indicates a rapid acquisition strategy in leaves34. The P-Ss association was characterised by the greatest number of leaves related to the physiognomy of the Dg species P. distans and S. marina45,46. This association had a leaf dry matter content similar to that of the Tm-Gm association, and in this way similar low acquisitive strategy in leaves34.

All differences in morphological traits between associations could be related to the impact of salinity. It is well documented that an increase in salinity, depending on the species and even variety, negatively correlates with all morphological traits of leaves, shoots, roots, and even flowers47. For example, Mohammadi and Kardan48 reported a noticeable response to increasing salinity, manifested by a reduction in the dry mass of shoots and roots of selected halophytes.

The results of the biochemical trait analysis highlighted notable differences among the considered associations, particularly in the proline and malondialdehyde contents, which were greater in the P-Ss and Tm-Gm associations than in the Sr association. High proline accumulation is a physiological response of plants to abiotic stress factors, which may be due to its synthesis, reduced degradation, lower utilization, or protein hydrolysis49. A relatively high proline content can be due to plant defence against high osmotic pressure in the soil solution, which allows water absorption under high soil salinity. However, as shown in the example of S. europaea, the level of proline in halophytes may be stable even with increasing salinity43. For glycophytic species, an increasing level of proline is observed with increasing salinity50. Malondialdehyde is used to evaluate lipid peroxidation in cell membranes induced by salt stress51–53. A high malondialdehyde level can indicate greater oxidative stress under saline conditions54, which can be comparable for both the Tm-Gm and P-Ss associations in terms of lipid peroxidation and lower for the Sr association.

Another marker of oxidative stress is hydrogen peroxide, a reactive oxygen species (ROS) produced in cells during normal aerobic metabolism. During the action of unfavourable external factors (such as salinity), hydrogen peroxide is overproduced in plants, which can damage cell components and lead to cell death55–57. A greater increase is observed in salt-sensitive plants than in salt-tolerant plants under salt stress52. Our results demonstrated that the lowest oxidative stress caused by hydrogen peroxide was present in the Sr, more remarkable in the P-Ss, and the greatest in the Tm-Gm association. One of the elements involved in the response to oxidative stress is the induction of catalase and ascorbate peroxidase, which are hydrogen peroxide-metabolizing enzymes55,56. The enzymes’ highest activity in the Tm-Gm association indicates the highest defence against oxidative stress under salinity. Interestingly, ascorbate peroxidase activity was greater than catalase activity, demonstrating its greater role in salt marsh vegetation. Cárdenas Pérez et al.43 reported similar results for the halophyte S. europaea.

The photosynthetic pigment concentration related to productivity was greatest in the Tm-Gm, lower in the P-Ss, and lowest in the Sr association. The different responses of photosynthetic pigments to soil salinity levels have been reported in the literature. In some species, a decrease in the level of chlorophyll or carotenoid was recorded under salt stress, e.g., by Taïbi et al.58. In others, an increase was observed but was not related to increased productivity59,60. A decrease in chlorophyll content is considered a symptom of oxidative stress61. The results for S. europaea, the Dg species of the Sr association, confirmed a decrease in chlorophyll content together with increasing salinity but not related to a decrease in biomass production43. Carotenoid not only acts as a pigment but also as an antioxidant, and its high content may indicate that its production is one of the most important protective mechanisms against salinity stress in the Tm-Gm vegetation type58. Total soluble carbohydrate acts together with proline as an osmolyte responsible for the greater biochemical stability of cells. Research on various species shows that an increase in the level of carbohydrate is associated with greater plant resistance to salinity62,63. Our results demonstrate that both proline and carbohydrate play similar roles in the Sr and Tm-Gm associations, while carbohydrate plays a minor role compared to proline in the P-Ss association.

PCA allowed us to compare the functioning of the associations based on all analysed traits together. However, to make this comparison clearer, we separated morphological and biochemical traits. The first PCA axis of the morphological trait analysis can be interpreted as a negative salinity gradient with Sr at the most saline sites and P-Ss and Tm-Gm at the least saline sites, which has already been discussed. Such a sequence along the salinity gradient of these associations has already been reported11,12,46. The second PCA gradient separating the P-Ss association from the other two associations can be interpreted as a different strategy of receiving resources—related to high root length and assimilation area—resulting in relatively high shoots dry weight in the Sr and Tm-Gm associations and, at the opposite axis end, the P-Ss association investing in higher number of leaves. Taking into account biochemical parameters, the main differences between the considered associations along the first PCA axis can be interpreted as a response to osmotic stress, the latter expressed in the Sr association, where dominant species are adapted to extreme salinity43,64 and the most highly expressed in the P-Ss and Tm-Gm associations, where the Dg species are less adapted to salinity and demonstrate more intensive defences. This osmotic stress is most strongly related to the accumulation of proline but also to the oxidative damage of lipids in cell membranes (malondialdehyde content) and the protective response of carotenoids. The biochemical factor related to the second PCA axis can be interpreted as a response to the oxidative stress marked by hydrogen peroxide, and the defence by ascorbate peroxidase. They were the highest in the Tm-Gm association, where the Dg species are less adapted to salinity. A greater increase in hydrogen peroxide content and ascorbate peroxidase activity in salt-sensitive plants than in salt-tolerant plants under salt stress has already been reported52.

Validity of the databases

Our research indicated that results based on directly measured functional traits may differ from those obtained based on average values from the databases. According to Kattge et al.65, plant traits are heterogeneous, have a low degree of standardization, and often require auxiliary data to interpret the results, particularly in the context of biotic and abiotic environmental stress. For salt marshes, environmental factors such as substrate parameters (e.g., salinity level) can be crucial43,66,67. Cárdenas Pérez et al.43 showed that changing only the substrate salinity concentration may influence fluctuations in both the morphological and biochemical traits of S. europaea. Such factors may result in differences even within plants of the same age and within the same research area, which may result in a mosaic of environmental parameters. Moreover, Cárdenas Pérez et al.64 demonstrated that the local environment, i.e., maternal salinity, can determine trait responses in the same species. Additionally, trait values may depend on the genotype or ecotype of the plant species18,68. In the results based on our own measurements and data from the LEDA Traitbase25 we found the greatest differences referring to leaf dry matter content and specific leaf area. Both parameters can be related to the site of species collection33,34. Májeková et al.69 showed that higher leaf dry matter content values might be related to greater population stability. As it has been already mentioned the specific leaf area may strongly depend on the salinity level. Therefore results should be interpreted with caution independently of the trait data source. For large datasets, average trait values from databases can be even better, reflecting general differences and trends.

Syntaxonomical integrity

Our results indicate the syntaxonomical integrity of inland salt marsh vegetation in temperate Europe, i.e., its associations also reflect functional differences. For the first time, linking phytosociological and functional vegetation approaches, we demonstrated that Dg species may play a key role in the typical inland salt marsh associations’ functioning. Our results demonstrated that functional differences between typical inland salt marsh associations are directly related to Dg species rather than the whole species composition. This can progress research focusing on association functioning by limiting measurements and calculations to a few Dg species instead of all species. Additionally, our concept of phytosociological units as functional units can be applied as a tool for the validation of existing phytosociological systems. As research on selected types of vegetation shows, functional-based indicators of Dg species work just as well as abundance-based indicators used so far in phytosociology [e.g., by Ricotta et al.27]. However, determining this requires future research, which should be preceded by checking if the relationships revealed by us apply to other vegetation types due to the possible smaller role of Dg species.

Conservation and protection implications

Our results highlight the need and importance of the legal protection of Dg species, which may be key functional components of inland salt marsh associations. Inland salt marshes are legally protected in Europe under the Natura 2000 network as two habitat types: 1310—Salicornia and other annuals colonizing mud and sand and *1340—Inland salt meadows Glauco-Puccinellietalia32,70. However, the protection of these two habitats and their key species should be integrated, which, unfortunately, is not always practised. An example is the protection of vegetation in inland salt marshes in Poland, where habitats are protected under the Natura 2000 network and as nature reserves15,71, but not all Dg species are legally protected. Only three Dg salt-adapted halophytes, S. europaea., T. maritima, and G. maritima (Lysimachia maritima) are protected by the law72. The other key halophytes in salt marsh associations, such as S. marina, are unprotected. Of course, only rare specialists should be considered. Although P. australis is included in a set of Dg species for the Tm-Gm association11, it is a common and expansive species and does not require protection. In addition, its expansion may adversely affect more valuable and light-requiring species of typical halophytes, which has been widely reported in the literature14,73. With many advantages of new methods used to distinguish phytosociological units, which allow obtaining repeatable results while maintaining statistical rigour6, this example shows some limitations of the concept of computed Dg species, which are context-dependent. This means that the chosen methodology may influence the set of distinguished Dg species74. It should be carefully tested every time to ensure it is appropriate for the analysed case. P. australis may meet the criteria for Dg species in a particular vegetation context, but it is not a suitable indicator species. This is evidenced by its broad habitat niche and the fact that it is considered a model invasive species [e.g., by Meyerson et al.75].

Most of the functional traits we analysed concerned growth parameters and leaves dimensions, including these biochemical parameters, which are responsible for plant persistence, especially in the context of salt stress25. Therefore, our results show that the greatest attention when selecting protective treatments should be focused on sensitive associations, i.e., Sr, followed by P-Ss and Tm-Gm. This confirms our previous findings reported by Lubińska-Mielińska et al.24 but additionally underlines the role of osmotic and oxidative stress, and resource acquisition in shaping differences between associations functioning. In this way, an approach based on functional traits may facilitate the practical application of our research results to new protection strategies for endangered habitats.

Materials and methods

Plant material

We included three of the most common associations: Salicornietum ramosissimae (Sr), Puccinellio-Spergularietum salinae (P-Ss), and Triglochino maritimae-Glaucetum maritimae (Tm-Gm), which belong to two syntaxonomical classes typical of inland salt marshes. The list of their Dg species, according to Lubińska-Mielińska et al.11, is presented in Table 1 and includes nine species in total, i.e., S. europaea, T. maritima, G. maritima (L. maritima), P. australis, J. compressus, P. anserina, S. marina, P. distans, and A. prostrata. Plant samples were collected on August 10, 2023, from the inland salt marsh in Inowrocław, located in north-central Poland (52°45′N, 18°13′E; Central Europe). This site was chosen because the three selected associations are present in this relatively small area, forming a mosaic of small patches. Moreover, strong soil salinity (> 16 dS·m1) has been stable in this area for several years28–30. We dug out 15 individuals of each species together with a large layer of soil around the roots and transported them to the laboratory in plastic bags to prevent moisture loss. In the laboratory, leaves samples were immediately prepared for further biochemical analyses, frozen in liquid nitrogen, and placed in a freezer at − 80 °C. Morphometric analyses were then carried out. Together with plants, soil samples (0–25 cm) were also collected, and parameters were analysed by external services (see supplementary materials Table S3). Because of the low saline groundwater table depth close to the surface, we reported the mean values of the soil properties at this site. During the sampling period, the salinity was approximately 36 dS·m-1. Three of the nine analysed species are legally protected in Poland: S. europaea., T. maritima, and G. maritima (L. maritima). Therefore, permission to collect and work with the plants was provided by the Regional Director of Environmental Protection in Bydgoszcz, Poland (number WOP.6400.9.2023.MWK). The voucher specimen of the plant material has been deposited in a publicly available herbarium of the Nicolaus Copernicus University in Toruń (Index Herbarium code TRN); the deposition number is not available (dr Dariusz Kamiński undertook the formal identification of plant species). The collection of plant material complies with relevant institutional, national, and international guidelines and legislation. All methods were carried out in accordance with relevant guidelines.

Vegetation data

We used data from a database by Lubińska-Mielińska et al.11 with vegetation plots (relevés) for the three abovementioned syntaxonomical associations: Sr—133 plots, P-Ss—134 plots, and Tm-Gm—56 plots, for a total of 323 plots. These data were used to calculate weighted averages of the functional traits (community weighted means, CWMs)76 for each association based on the cover/abundance and measured parameters. To perform the calculations, we transformed the phytosociological data from the Braun-Blanquet1 scale into the van der Maarel77 ordinal scale as follows: r → 1, +  → 2, 1 → 3, 2 → 5, 3 → 7, 4 → 8, 5 → 9. The full characteristics of species composition has been presented in publication by Lubińska-Mielińska et al.11. The species cover/abundance in the considered associations presents average non-zero cover synoptic table (Table S5). Only nine Dg species11, as mentioned above, were considered (see Table 1). Data on the other species have been omitted. All species were considered only in comparisons based on data from the LEDA Traitbase25.

Morphological analyses

To evaluate morphological characteristics, 10 plants were randomly selected from each species. Subsequently, measurements were taken for shoot length (SL) and root length (RL) in centimetres (cm). Additionally, the number of leaves (NoL) was counted. Shoots fresh weight (SFW), roots fresh weight (RFW), and leaves fresh weight (LFW) were assessed in grams (g). Leaf mass (LM) was expressed in milligrams (mg). The dry weights of the shoots (SDW), roots (RDW), and leaves (LDW) were determined after the samples were oven-dried at 80 °C for 72 h, and reported in g. Leaves area (LA) and assimilation area (AA) were scanned and measured using digiShape 1.9 software78, and the results are reported in square centimetres (cm2). In the case of AA for S. europaea, the entire area of shoots was considered to be affected by the assimilation functions. For T. maritima, the AA value is the LA multiplied by two due to the double-sided structure of its leaves. A single ramet was measured as an individual plant for ramet-producing species such as P. distans, T. maritima, P. australis, and J. compressus. More details about the measurement methods are provided in Table S4.

Based on the measured parameters, five growth indices were calculated: shoot weight ratio (SWR), root weight ratio (RWR), leaf weight ratio (LWR), leaf dry matter content (LDMC) [mg/g], and specific leaf area (SLA) [cm2/g] according to the following formulas:1 SWR=SDWDW

where SDW is the shoots dry weight [g], and DW is the total dry weight [g].2 RWR=RDWDW

where RDW is the roots dry weight [g], and DW is the total dry weight [g].3 LWR=LDWDW

where LDW is the leaves dry weight [g], and DW is the total dry weight [g].4 LDMC=LDWLFW

where LDW is the leaves dry weight [mg], LFW is the leaves fresh weight [g],5 SLA=LALDW

where LA is the leaves area [cm2], and LDW is the leaves dry weight [g].

Additionally, to compare the results based on our measurements with those based on the LEDA Traitbase data25, we recalculated our data to obtain the single leaf area (1LA) expressed in cm2 and the single leaf dry mass (1LDM) as the dry weight of one leaf according to the LEDA protocol expressed in mg.

Biochemical analyses

The biochemical traits related to photosynthetic activity (photosynthetic pigments content), osmotic adjustment (proline and carbohydrates content), oxidative stress (hydrogen peroxide and malondialdehyde), and antioxidative enzymatic activities (catalase and ascorbate peroxidase activities) under environmental salt stress were measured. All biochemical analyses were performed with three replicates of 0.5 g fresh green leaves samples. In the case of S. europaea, instead of leaves that are reduced in this species, the assimilation tissue of shoots was used for measurements. Fresh plant material was frozen using liquid nitrogen and stored at − 80 °C except for carbo, where 0.1 g of dried sample was used.

Photosynthetic pigment content

The content of photosynthetic pigments, i.e., chlorophyll a (chla), b (chlb), total (chlt), and carotenoid (car), was measured according to Lichtenthaler and Wellburn79. A total of 0.5 g of each fresh green leaves sample was ground in a liquid nitrogen mortar. Next, 10 ml of 80% acetone was added to the mortar with the ground sample and triturated until a green liquid was obtained. Then, the sample was transferred to a test tube and adjusted to a 10 ml volume with 80% acetone. All the samples were centrifuged for 15 min at 5,000 RPM. Absorption was measured at wavelengths of 663 nm, 646 nm, and 470 nm using a spectrophotometer and 80% acetone as a blank. The pigment contents were calculated using the following equations:6 Chla=12.21·Abs663-2.81·Abs646·ml Acetonemg plant samplemg/g FW

7 Chlb=20.13·Abs646-5.03·Abs663·ml Acetonemg plant samplemg/g FW

8 Car=1000·Abs470-3.27·Chl a-104·Chl b/227·ml Acetonemg plant samplemg/g FW

The sum of chla and chlb was taken as the chlt content. The results are reported as milligrams per gram of fresh weight [mg/g FW].

Proline content

The proline (prol) content was determined according to Bates et al.80. Each sample (0.5 g) was ground in a liquid nitrogen mortar. Then, 10 ml of 3% sulfosalicylic acid was added to the mortar with the crushed sample and further ground. Next, the sample was transferred to a test tube. All the samples were centrifuged for 10 min at 13,000 RPM at 4 °C. Later, 2 ml of supernatant from each sample was transferred to a new tube, and 2 ml of ninhydrin and 2 ml of glacial acetic acid were added. All the samples were placed in a water bath for one hour at 100 °C. After cooling on ice, 4 ml of toluene was added to the test tubes, and the samples were mixed. The absorbances of the samples were measured at 520 nm. Toluene was used as a blank. The prol content was determined using the standard curve in the 0.5–4 mg/l prol concentration range and equation y = 0.1964x + 0.0143, R2 = 0.9748. The results are reported as milligrams per gram of fresh weight [mg/g FW].

Total soluble carbohydrate content

To determine the total soluble carbohydrate (carbo) content in our samples, we used the Sheligl method81. Plant materials were used after oven-drying for 72 h at 80 °C (0.1 g of each sample). Each sample was ground into powder using an electric grinder and mortar. The crushed samples were transferred to Falcon tubes, and 15 ml of warm 80% ethyl alcohol was added. After mixing the samples, they were placed in a centrifuge for 10 min at 3000 RPM. The solution was poured into Petri dish lids (5 cm in diameter) and placed for 60/90 min (until the alcohol evaporated completely) in a dryer at 50–70 °C. Next, each sample was rinsed from the bottom of the dish lid into a Falcon tube and 40 ml of distilled water. Next, 5 ml of 5% ZnSO4 and 5 ml of 3% Ba(OH)2 were added to the test tubes. The samples were centrifuged for 10 min at 3000 RPM. Then, 2 ml of the supernatant was transferred to another Falcon tube, and 1 ml of 5% phenol and 5 ml of 96–98% H2SO4 were added. After 45 min of reaction, the absorbance was measured at 485 nm and mixture of 1 ml of phenol and 5 ml of H2SO4 was used as a blank. To obtain the results, a standard curve for glucose was used in the range of 0–90 mg, with the following equation y = 0.0091x + 0.0212, R2 = 0.9808. The results are reported in milligrams per 100 g fresh weight [mg/100 g FW].

Hydrogen peroxide (H2O2) content

The hydrogen peroxide (H2O2) content was determined according to the method of Velikova et al.82. The samples were ground in a mortar in liquid nitrogen. Next, 2 ml of 1% TCA was added to each sample, and then ground further. Later, the samples were poured into Eppendorf tubes and centrifuged for 10 min at 4 °C at 10,000 RPM. After that, 0.5 ml of supernatant, 0.5 ml of 0.1 M potassium phosphate buffer, and 1 ml of 1 M potassium iodide were added to new tubes. Potassium iodide was added in the dark. The samples were placed in the dark on ice for one hour. The absorbance of the samples was measured at a wavelength of 390 nm. We used 0.5 ml of 1% TCA, 0.5 ml of buffer, and 1 ml of potassium iodide as a blank. We used a standard curve in the 0–40 nM H2O2 concentration range and the equation y = 0.0615x + 0.0287, R2 = 0.9954 to obtain the results. The results are reported as nanomoles per gram of fresh weight [nmol/g FW].

Malondialdehyde (MDA) content

The malondialdehyde (MDA) content was measured according to Velikova et al.82. After grinding the sample in a mortar in liquid nitrogen, 2 ml of 1% trichloroacetic acid (TCA) was added, followed by further grinding. Each sample was poured into Eppendorf tubes and centrifuged for 5 min at 4 °C at 10,000 RPM. Next, 0.5 ml of the supernatant was transferred to a new tube, and 1 ml of a mixture of 20% TCA and 0.5% thiobarbituric acid (TBA) was added. The samples were placed in a water bath for 30 min at 95 °C. After that, the samples were cooled on ice and placed in a centrifuge at 4 °C for 15 min at 10,000 RPM. The absorbance of the supernatants was measured with a spectrophotometer at two wavelengths—532 nm for MDA and 600 nm—to determine changes caused by infection. A 1 ml mixture of 20% TCA, 0.5% TBA and 0.5 ml of 0.1% TCA was used as a blank. The MDA content was calculated according to the following formula:9 MDA=Abs532-Abs600155·samplevolumesamplefreshweight·1000mmol/g FW

where the sample volume was 1.5 ml, and the sample fresh weight was 0.5 g. The results are given as millimoles per gram of fresh weight [mmol/g FW].

Soluble protein content

The protein content was measured according to the Bradford method83. The samples were crushed in a mortar with liquid nitrogen and transferred to Eppendorf tubes. Next, 1 ml of extraction buffer (consisting of a buffer and Tris, EDTA, Triton, and DDT) was added. The samples were subsequently centrifuged for 30 min at 12,000 RPM at 4 °C. The protein content was measured after adding 3 ml of Bradford’s reagent to new tubes and adding 100 μl of the supernatant. They were allowed to complete the reaction for 30–60 min. The absorbance was measured at a wavelength of 595 nm. Bradford’s reagent was used as a blank. The results were used to express the enzyme activity (ascorbate peroxidase and catalase) in the samples. For this purpose, a standard curve was determined for protein concentrations in the range of 0–120 µg/ml, using the equation y = 0.0088x + 0.0387, R2 = 0.9906. The protein content is expressed in milligrams of protein per millilitre [protein mg/ml].

Specific catalase (CAT) activity

For measurements of catalase (CAT), we used the same samples used for the protein measurements. The method of Aebi84 was used. The absorbance was measured at 240 nm in 1.5 ml of phosphate buffer supplemented with 4.51 μl of H2O2 and 50 μl of the supernatant. The mixture of phosphate buffer and 30% H2O2 was used as a blank. The following formula was used to calculate the enzyme content in ml of the sample:10 Enzyme=ΔAbs·Tv·Dε·Evu/ml

where: ΔAbs—difference in absorbance (240 nm for CAT/290 nm for APX) of the sample after 30 s. Tv—the volume of the spectrophotometer cuvette used for the measurement (2 ml). D—possible dilutions of the measured sample.

ε—extinction coefficient (39, 4 for CAT/2,8 for APX). Ev—sample volume used for measurement (0.05 ml). The results of the protein content were used to report the results of CAT expressed in units per milligram of protein [u/mg protein].

Specific ascorbate peroxidase (APX) activity

The same samples prepared for protein and catalase activity measurements were used to measure ascorbate peroxidase (APX) activity according to the method of Nakano and Asada85. Absorbance measurements were performed at 290 nm by mixing 2 ml of phosphate buffer, 100 μl of ascorbic acid, 4.51 μl of 30% H2O2, and 50 μl of supernatant. As a blank, 2 ml of phosphate buffer, 100 μl of ascorbic acid, and 4.51 μl of 30% H2O2 were used. The same formula as for CAT (above) was used to calculate the enzyme content per ml of the sample [u/ml]. The results of the protein content were used to report the results of APX expressed in units per milligram of protein [u/mg protein].

Statistical and multivariate analyses

All nine Dg species based on individual morphological and biochemical functional traits were compared by one-way analysis of variance (ANOVA) with Tukey’s post hoc comparisons due to the normal data distribution according to the Shapiro‒Wilk test.

We compared trait weighted averages of three analysed associations using the nonparametric Kruskal‒Wallis test with Dunn post hoc comparisons for morphological data and the parametric ANOVA for equal means with Tukey’s post hoc comparisons for biochemical traits, depending on the distribution of the data with the proven Shapiro‒Wilk test. We used the unconstrained ordination method to explore and visualise relationships between these analysed associations regarding functional traits. Due to the high value of the stress index (> 0.5) for biochemical data in the nonmetric multidimensional scaling (NMDS) analysis, we decided to use principal component analysis (PCA) separately for morphological and biochemical traits. We also correlated traits with the first two ordination axes using Spearman’s correlation coefficient (rs) to determine the pattern of the main differences. Due to the large variability in the morphological trait values resulting from the use of many specific units, the data had to be standardised before ordination analysis, which was carried out using MVSP 3.1 software86.

To determine the role of Dg species in association functioning, we compared the results of the CWMs calculated based on Dg species with the CWMs calculated based on all species in the plots. We included canopy height (CH), leaf size (LS), leaf mass (LM), leaf dry matter content (LDMC), and specific leaf area (SLA) from the LEDA Traitbase25 and made comparisons via Kruskal‒Wallis tests with Dunn’s post hoc test.

To validate the results obtained from field measurements with the results based on the LEDA Traitbase data25, we compared three associations for nine Dg species using the Kruskal‒Wallis test with Dunn’s post hoc comparisons. For all analyses, we used PAST 4.12 software87.

Conclusions

Based on the morphological and biochemical functional trait analyses, we demonstrated the different salinity resistance strategies of associations typical of inland salt marshes in temperate Europe. The Tm-Gm association had the highest values of most measured morphological parameters related to biomass production but also had the lowest salt resistance, as indicated by the highest osmotic and oxidative stress and oxidative stress responses. The Sr association was the best adapted to both osmotic and oxidative stress. The P-Ss association had the smallest biomass production. This association was similar to the Tm-Gm in managing osmotic stress but more adaptable to oxidative stress under soil salinity. The Dg species of the investigated associations play critical roles in their functioning because including all species does not change the main research findings. Therefore, an approach based on functional traits may facilitate the practical application of our research results to new protection approaches and strategies for endangered habitats.

Supplementary Information

Supplementary Information.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-024-72526-5.

Author contributions

S.L.M., A.R.D., and D.K. collected plant material samples. S.L.M. and A.R.D. performed morphometrical measurements and biochemical analyses of the plant’s functional traits. S.L.M. organised and managed data including from the LEDA Traitbase, performed statistical and multivariate analyses, and prepared the first draft of the publication. A.R.D. and S.C.P. contributed to the interpretation of the results and critical revision of the manuscript for important intellectual content. A.P. conceived the ideas, designed statistical and multivariate methodology, substantially contributed to the manuscript’s final version, and supervised the project. All authors have read and approved the final version of the manuscript.

Funding

This study was financially supported by the Excellence Initiative—Research University Emerging Field Ecology and Biodiversity and publication in Open Access was funded within the Excellence Initiative—Research University programme from the budget for science by Nicolaus Copernicus University in Toruń, Poland.

Data availability

Data used during the research will be made available upon request from the corresponding authors: S.L.M. (slm@umk.pl) or A.P. (piernik@umk.pl).

Competing interests

The authors declare no competing interests.

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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