4.1. Genetic analysis
The genetic composition of the experimental site of common reed did not change considerably after 24 years, and the difference in clonal variation between mono- and polyclonal plots remained. The number of genotypes in the plots established by monoclonal planting increased from nine to 13, but the new four genotypes were found in only five out of 397 samples in the plots with free succession or planting density of 1 plant per m2 (Fig. 1). These four genotypes most likely occurred by seed recruitment; their genetic similarity to the most of the monoclonally planted genotypes (Fig. 3) points towards the local formation of these seeds. As such, established monodominant stands of P. australis seem to be extremely persistent.
The plots established by polyclonal planting lost some genetic diversity due to vegetative growth, but not significantly. The monoclonally planted plots did certainly not always receive the genotype adapted best to local conditions, but the establishment advantage of the planted genotype outweighs by far a possible competitive advantage of a newcomer. We assume that reeds in the monoclonally planted plots have not yet reached the “stationary” stage, and are still undergoing the stage of “propagation and establishment”. Whereas the plots established by polyclonal planting are in the very early phase of the “propagation and establishment” stage with only a few genotypes starting to grow vegetatively.
Apart from the difference in the original number of genotypes between plots with different establishment techniques, the variation in gene diversity could be influenced by the mostly higher water level at the polyclonally planted plots in comparison to the monoclonal plots (85% of samples from polyclonal plots are collected from the flooded area). However, two polyclonal plots from the driest area also stayed polyclonal. And for the monoclonal plots, no clear tendency towards an increase in genetic diversity with lower water level was detected. Perhaps, not sufficient difference in water level along the site together with high plasticity of reeds resulted in no influence of water regime on genetic structure. Another explanation of the higher gene diversity in the polyclonally planted plots can be the genetic and/or epigenetic similarity of genotypes propagated from seeds with the same origin, which may lead to similar ecological preferences and, therefore allows coexistence. However, the result of PCoA did not show genetic clustering of genotypes collected from plots established with the same ecotype (but did not exclude a possible epigenetic similarity). It also did not indicate the clustering of monoclonally planted genotypes according to their geographical origin, proving again the presence of a large interbreeding metapopulation of common reed in NE Germany (Lambertini et al. 2008; Kuprina et al. 2022). Therefore, we can conclude that the source of a higher genetic diversity detected for the polyclonally planted plots most likely was the originally higher number of genotypes, but not different environmental conditions or similar origin of ecotypes.
There is no available information about the “window of opportunity” allowing the establishment of different genotypes in a natural population of P. australis. Lambertini et al. (2008) compared the clonal variability of eight natural reed stands in the Po Plain, Italy. They described one monoclonal population with a low disturbance level which was at least 50 years old and seven polyclonal populations with a high level of disturbance and estimated age of about 30 years. It is not yet clear which of two factors, population age or level of disturbance, has a greater impact on the genetic structure of a reed population, and it can probably vary. In addition, many other factors, like effective population size, mutation rate, and linked selection (Ellegren and Galtier 2016), can contribute to this impact, which greatly complicates their unravelling in the case of the natural reed stands. Although disturbance is suggested to be a driver of seed recruitment and genetic diversity for reeds (e.g., Lambertini et al 2008b; Kettenring et al 2011), most of the studies comparing levels of genetic diversity of natural reed populations did not find the expected influence of moderate disturbance on population genetic structure (Fant et al. 2016; Kuprina et al. 2022). We thus can only assume that an undisturbed population, like the one in our study site, will reach the “stationary” stage not earlier than 50 years, and most likely even in a century. That gives an expectation for paludiculture farmers to be able to either maintain favourable genotype(s) for many years or to keep a high genetic diversity in case of no preferences in genotypes. However, the effect of disturbance by regular mowing on the population genetic structure of a recently established reed stand still has to be addressed in future studies.
Clonal variability on this experimental site was also explored in 2001, 4–5 years after establishment using RAPD-PCR with primers M13 and (GACA)4 (Koppitz and Buddrus 2004). The growth parameters, biomass and C/N content of stems were measured for monoclonal plots established in 1997 with the density of 4 plant/m2. Additionally, the clone composition of mono- and polyclonal plots was studied: 10 randomly selected samples were genotyped for one plot of each genotype and ecotype; for three ecotypes, three water levels were also compared (dry, wet and flooded). The observed patterns of genetic diversity were similar to those found in 2020–2021. In 2001, for polyclonally planted plots, nearly all analysed samples were genetically different, despite the difference in planted ecotypes and water level. Monoclonally planted plots, however, already showed different levels of genetic diversity: plots contained from one (genotypes “3”, “4” and “6”) to four (genotype “8”) different genotypes. In our study, genotypes “3” and “4” also showed the highest levels of persistence, but genotype “10” - the lowest (Fig. 4b). Further, genetically distant genotypes did not show a higher or lower relative persistence or invasiveness. Genotype “3” which was genetically most distant from all others showed an average value for relative persistence and a moderate one for invasiveness. The comparison of these indices with haplotypes also did not reveal a tendency. We expected that genotypes “3”, “9”, and “10”, which have haplotype T4b (widely known as M when combined with haplotype R4b of chloroplast marker rbcL – psaI), will have the highest values of invasiveness. Studies describing invasive lineages of P. australis in North America, China and Australia revealed haplotype M as the most common for these lineages (Saltonstall 2002; An et al. 2012; Hurry et al. 2013); Haplotype M was even introduced to China for restoration because of its robust clonal growth. Moreover, M is also the most common haplotype in Europe (Lambertini et al. 2012) and northeast Germany (Kuprina et al. 2022). However, genotype “10” had the lowest values of both indices, which is not surprising, since it originated from a mesotrophic clear water lake (Parsteiner See) where it already displayed low productivity and short culms. The Biesenbrow experimental site can be categorised as a nutrient rich area. It was intensively used as arable land for growing maize and fodder grasses with high fertilizer input since the mid-1970’s and even with reduced intensity of grassland use since 1992 (Timmermann 1999). The nutrient availability due to peat degradation was high. All the other genotypes originated from eutrophic lakes or meadows that were temporarily or permanently flooded, especially genotype “1”, which originated from another extreme habitat, floodable fields (Rieselfeldern bei Blankenfelde) with high pollution with heavy metals and nutrients. Therefore, the origin of the genotypes is essential for the establishment and persistence of success and the initial local adaptation might also persist over a couple of years.
Planting density did not influence the genetic diversity after 24 years for both establishment techniques (Fig. 4a). Under proper conditions, common reed can display impressively rapid expansion right after planting (Kühl 1999; Timmerman 1999). Already three years after the establishment with a density of 1 plant per m2, the species can create a monodominant stand (Timmermann 1999) and reach its maximum productivity after three to five years. It has also been shown that there is no relationship between planting density and subsequent density of stems already in the following years after establishment (Timmermann 1999). After reaching a maximum in the second or third season, stem density tends to increase gradually for at least the next five seasons (Vymazal and Krőpfelová 2005), perhaps as a result of competition between shoots. For natural populations, mature reedbeds (older than 50 years) were found to have about six times lower stem density than young populations perhaps because of the litter accumulation and decrease of the light availability (Packer et al. 2017). In spite of different planting densities assessed by Koppitz and Buddrus (2004), the number of stems per m2 (taken as the average per genotype) was comparable (2001: 54–114 stems per m2, 4 pl/m2; 2022: 46–156 stems per m2, 1 pl/m2; Table 1).
4.2. Morphological and biomass analysis
The five genotypes analysed performed differently after 24 years. Stem width, height, dry above-ground biomass per stem but as well the absolute and relative number of panicles were found to be rather variable. Interestingly, genotypes “3” and “9” (both showing haplotype T4b) have the smallest, but most dense stems (however, the values are not significantly different from those of other genotypes). These genotypes may follow a different physiological strategy, producing more but smaller shoots, but finally leading to figures for aboveground biomass comparable to that of other genotypes. The morphological comparison of these genotypes in 2001 (Koppitz and Buddrus 2004) also revealed differences, but with different patterns for some parameters: in 2001, genotypes “3”, “6”, “8”, “9” had higher stems than genotype “1”, however, in 2021, genotypes “6” and “9” have the highest values of stem height, than “3” and “9”. We did not find significant differences in dry above-ground biomass and stem density among genotypes, although in 2001 genotype “3” had the highest stem density and genotype “6” produced more biomass, than genotype “9”. The measurements of stem length and density made in 1998 (Koppitz et al. 2000) do not correspond to the data from 2001 and 2022. It is reasonable to assume that the phenotypic manifestation of the genotype may have dynamics and change over time and under different climatic conditions. We can conclude that only long-term experiments under controlled conditions (mesocosms) can be used to select a genotype with favourable performance.
In accordance to these results several studies describe a very high level of phenotypic plasticity of P. australis (Hansen et al. 2007; Achenbach et al. 2012; Eller and Brix 2012). It was also shown that in changing environments, common reed has a strategy to primarily change its morphology, but not phenological and reproductive traits (Ren et al. 2020). For example, in the first years after the establishment of our experimental site, the same genotypes in the dry parts of the site produced less than half of the biomass, then on the flooded parts (Koppitz et al. 2000). Some experiments also showed that different genotypes can vary in morphology and biomass production after transplanting into similar environments (Hansen et al. 2007; Achenbach et al. 2012; Haldan et al. 2023), and explained this phenomenon by differences in genetics. However, it is not yet known how large the contribution of epigenetics to the phenotypic plasticity of common reed is. For example, Song et al. (2022) showed in the common garden experiment that demethylation of P. australis originating in freshwater, but not in saltwater populations, can improve the growth of these plants under salt stress. It allows to assume that not only genetics, but also epigenetics, may have a great impact on local pre-adaptation and phenotypic traits.