Effects of fertilisation on grass and forb gamic reproduction in semi-natural grasslands

Site, meadow, and fertilisation

The grassland utilized in this study was located in Sedico (BL: 420 m a.s.l., eastern Italian Pre-Alps), where the annual mean temperature is 10.6 °C and the annual rainfall is approximately 1366 mm (389, 326, 401, and 250 mm in spring, summer, autumn, and winter, respectively). The site was level and had an alluvial calcareous substratum. The soil was sandy-loam textured with 12.2% gravel content, 14.6% total carbonate content, and a pH of 7.5. Since 1977, a section of the meadow has been used for a fertilisation trial organised as three completely randomized blocks with 24 m2 plots and twenty-seven treatments obtained by combining three levels of yearly N, P, and K applications per ha: 0, 96, and 192 kg N as ammonium nitrate; 0, 54, and 108 kg P2O5 as triple superphosphate; and 0, 108, and 216 kg K2O as K sulphate. Since 2010, the grassland has been cut twice per year and surveyed for seed production in three treatments: no fertilisation (000), fertilization with no N and intermediate levels of P and K (011), and fertilisation with the highest nutrient rates (222).

The vegetation of the three treatments (Annex 1) corresponded to the following meadow types: type 000, vegetation intermediate between a poor-soil form of the Arrhenatherum elatius meadow (Ar0) and a Bromus erectus meadow (Br), with high species richness and low legume abundance; type 011, an Ar0 meadow with high species richness and legume abundance; and type 222, a grass-rich form of the Arrhenatherum elatius meadow with low species richness and legume abundance.

Plant sampling and laboratory analysis

During the two growth periods within each of the years from 2012 to 2017, fertile shoots were sampled from the three fertilization treatments. 15–30 shoots (5–10 in each plot) from each flowering species were collected at the optimal seed maturation stage (most fruits/inflorescences still intact, i.e., no seed shedding). At the sub-plot level, all fertile shoots were collected at the time of meadow mowing on one 1-m2 sub-plot per plot. Collected shoots were put separately per species into porous paper bags, dried, and preserved in a refrigerator until laboratory analysis.

During the autumn and winter after collection, the 15–30 shoots of each species were analysed for the number of compound and/or simple inflorescences and the flowers per simple inflorescence or shoot. For species with flowers or inflorescences too numerous to be rapidly counted, an inflorescence length or diameter which could be related to the number of flowers was also measured (e.g., the panicle length in grasses). In sample flowers, intact fruits, or simple inflorescences, the number of ovules per flower and the number of ovules transformed to seed were observed under a binocular microscope. Mature seeds were weighed and tested for germinability and viability according to ISTA19. Germination trials were performed with three seed samples per species, which were placed on filter paper in petri-dishes and moved to a germinator for 4 weeks (8 h light/25 °C and 16 h darkness/15 °C) with weekly observation and extraction of germinated seeds. At the end of the germination test, seeds that had not germinated were checked for viability with the tetrazolium test. Total viability was calculated as the sum of germinability and viability of non-germinated seeds.

All shoots collected on the sub-plots were counted and measured for the number of inflorescences and flowers. When inflorescences and flowers were too numerous to be counted rapidly (e.g., in all grasses), only the same length/diameter measured on the 15–30 shoot samples was recorded.

A more detailed description of the laboratory analyses is available in Scotton20.

Data analysis

The value of each reproductive trait was calculated for each year and growth period at the plot level for each species. The values of the traits describing the size of the reproductive system were obtained from the shoots collected on the sub-plots. However, for species with too many flowers per shoot, a relation was calculated between the flowers per shoot and the length/diameter of the inflorescences measured on the 15–30 shoot samples. This relationship was then used to calculate the flower number for each shoot. The number of ovules per flower, the portion of ovules transformed to seed (ovule site utilisation, i.e. the filled seed/ovule ratio), the 1000-seed weight, germinability, and viability were calculated from the results of lab analyses of the 15–30 shoot samples.

Because all the species collected were not always present in the six study years, only the thirty-two species (fifteen grasses and seventeen forbs: Table 1) found in at least three of the study years were considered in this paper to obtain enough reliable results. For all grasses, data were available only for the first growth period. For four forbs (see Annex 3) data were available for the first and second growth periods: in these cases, the average values of the two periods were used in the analyses.

Table 1 Species studied for reproductive traits in a grassland fertilisation trial in the Italian eastern Alps.
Full size table

The statistical analyses were performed at the levels of individual species and the two grassland functional groups (grasses and forbs). Nine main reproductive traits describing the whole process of gamic reproduction were considered: number of simple inflorescences per shoot, flowers per simple inflorescence, ovules per flower, ovules and viable seeds per shoot, OSU (ovule site utilization), percent viability, germinability, and seed weight. Percent dormancy (the difference between percent viability and germinability) and the shoot density recorded in the subplots were also considered in some analyses.

Only sixteen species were present in all of the fertilisation treatments, presenting a challenge in the tests that included all of the species together because a balanced among-treatments comparison was only possible by discarding the data from species not present in all of the treatments. To overcome this issue, we assumed that due to symbiotic N-fixation, the high presence of legumes in the 011 treatment (fertilization with P and K) was equivalent to a yearly N fertilisation of about 3.5 kg/ha per percent point of legume abundance in the species composition21,22. Therefore, treatment 011 (30% more legume abundance than in treatment 222: Annex 1) was regarded as an intermediate N addition of 105 kg per ha per year (from 3.5 kg N × 30% legume abundance). The values of the reproductive traits were then calculated for two fertilisation levels, low (LowFert) and high (HighFert). For species present in 000 and 011, LowFert was 000 and HighFert was 011. For species present in 011 and 222, LowFert was 011 and HighFert was 222. For species present in three fertilisation treatments, LowFert was 000 and HighFert was the average between 011 and 222. Statistical analysis considering only the species present in all fertilisation treatments yielded a similar pattern of fertilisation effects to those found in analysis of the two separate fertilisation levels. The analysis of the two fertilisation levels was therefore utilized because it was representative of a larger number of species.

Statistical analyses (see summary in Annex 2) were conducted with three main aims: 1. studying the fertilisation effect on the reproductive behaviour of individual species and the two species groups of grasses and forbs; 2. finding species biological and ecological traits explaining their response to fertilisation; and 3. identifying multispecies correlations among reproductive traits and the possible effects of fertilisation on their patterns.

For the first aim, the fertilisation effect was tested for the reproductive traits of each individual species through application of a mixed linear model under a repeated measure approach. In the model, fertilisation treatment, year, and block were input as class factors, and a plot identifier was used as a random factor. In case of significant fertilisation effects, the among-treatment differences were tested using the Tukey multiple comparison adjustment. Prior to performing the mixed model, data were checked for homoscedasticity and normality and, if necessary, log-transformed.

From the individual species mixed models, a table was calculated containing the frequency of cases with fertilisation effects (three levels: no, positive, or negative) for each reproductive trait and species group. To check if grasses and forbs differed for the obtained frequencies, for each trait a chi-square test on the frequency table “fertilisation effect x species group” was performed.

In a following set of analyses, the effect of the grassland functional group (grasses or forbs) on the multi-year means of each reproductive trait was tested with general linear models (GLM). Prior to the analysis, the data were sometimes log-transformed to mitigate homoscedasticity and normality problems. In these analyses, species were considered as replicates within the species group (therefore not included as a class factor) and the fertilisation level was input as a class factor. The effect of the fertilisation level on each reproductive trait was tested separately for the two species groups. In this case, the GLM included both fertilisation level and species as class factors.

For the second aim, possible biological and ecological traits explaining the species response to fertilisation were investigated by relating the percent variation due to fertilisation in two important size traits (ovule and viable seed number per shoot: variables Y) to the following explanatory (X) variables: average values of the nine reproductive traits, the seven Ellenberg bioindicator values23, and the percent variation of shoot density. The relationships were fitted according to a linear regression approach for grasses and forbs together or separately and checked for the parametric assumptions of residual normality and homoscedasticity. For the percent variation due to fertilisation of individual species of OSU, seed germinability, viability and weight, one-way analyses of variance were performed where three traits of the species reproductive biology (type of reproduction, breeding system and pollen vector4: Annex 1) were used as categorical factors. A GLM approach was also used in this case.

For the third aim, multispecies correlations were analysed by in-pairs relating the reproductive trait values of individual species averaged across fertilisation treatments and years. Fertile shoot density recorded in the subplots. was used as a supplementary characteristic. Nonlinear relationships were made linear with a log-transformation. Because the purpose of the analysis was not to predict one trait from the other but to efficiently summarise the relationships between traits, the standardised major axis (SMA) approach was used instead of the linear regression method24. The analyses were performed for grasses and forbs both together and separately. In order to verify if fertilisation could affect the characteristics of the evaluated relationships, a second set of SMA analyses were performed by separating the two fertilisation levels and the lines obtained were tested for common slope and elevation according to Warton et al.24.

The year effect will be reported in a forthcoming paper and is therefore not discussed here, despite its inclusion in the statistical analyses.

We used SAS/STAT software 12.325 with procedures MIXED, GLM, REG, and UNIVARIATE, and R 3.0.026 with package SMATR.

Additional statements

The experimental research and the collection of plant material was done according to relevant institutional, national, and international guidelines and legislation. No grassland species considered in the research is included in the list of endangered species according to the IUCN, European Union, Italian national and regional classifications. The collection of plant specimen was done with permission of the grassland owner during the hay-making operations for forage production which do not need a special permission from the concerned local authorities. The plant species were identified by the first author, Michele Scotton. A voucher specimen of each plant species considered in the research was stored in the laboratory of the authors’ Department (DAFNAE) and the authors have provided an ID number for each voucher specimen.

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