Next Article in Journal
Sustainable Biochar and/or Melatonin Improve Salinity Tolerance in Borage Plants by Modulating Osmotic Adjustment, Antioxidants, and Ion Homeostasis
Next Article in Special Issue
Mowing Facilitated Shoot and Root Litter Decomposition Compared with Grazing
Previous Article in Journal
Triterpenes and Phenolic Compounds from Euphorbia deightonii with Antiviral Activity against Herpes Simplex Virus Type-2
Previous Article in Special Issue
Dwarfing and the Underlying Morphological Changes of Poa alpigena Plants in Response to Overgrazing Conditions
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Plants
Volume 11
Issue 6
10.3390/plants11060763
plants-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Vegetation Dynamics in a Loess Grassland: Plant Traits Indicate Stability Based on Species Presence, but Directional Change When Cover Is Considered

by
Péter Csontos
1,*,
Júlia Tamás
2,
Zsófia Kovács
3,4,
Judit Schellenberger
1,
Károly Penksza
5,
Tibor Szili-Kovács
1,* and
Tibor Kalapos
6
1
Institute for Soil Sciences, Centre for Agricultural Research, Herman O. út 15, 1022 Budapest, Hungary
2
Department of Botany, Hungarian Natural History Museum, Könyves K. krt. 40, 1087 Budapest, Hungary
3
Doctoral School of Horticultural Sciences, Hungarian University of Agriculture and Life Sciences, Villányi út 29-43, 1118 Budapest, Hungary
4
Plant Protection Institute, Centre for Agricultural Research, Nagykovácsi út 26-30, 1029 Budapest, Hungary
5
Department of Botany, Hungarian University of Agriculture and Life Sciences, Páter Károly u. 1, 2100 Gödöllő, Hungary
6
Department of Plant Systematics, Ecology and Theoretical Biology, Loránd Eötvös University, Pázmány P. sétány 1/C, 1117 Budapest, Hungary
*
Authors to whom correspondence should be addressed.
Plants 2022, 11(6), 763; https://doi.org/10.3390/plants11060763
Submission received: 26 February 2022 / Revised: 10 March 2022 / Accepted: 11 March 2022 / Published: 13 March 2022
(This article belongs to the Special Issue Grassland Diversity and Ecological Restoration)
Browse Figures
Versions Notes

Abstract

:
This article evaluates the three-year vegetation dynamics of a species rich, protected steppe grassland on loess where no grazing occurred for decades at Bicske, Central Hungary. A detailed coenological survey of vascular vegetation was conducted in four permanent plots of 16 m2 each from 2018 to 2020. Raunkiaer’s life-forms, distribution range, and thousand-seed weight of species were evaluated. Shannon diversity and turnover rates for the species and the vegetation were also determined for each plot. In total, 108 vascular plant species were detected. The results indicate grassland stability when plant traits spectra were based on species presence data, but directional change if species cover values were used to weight trait categories. During the three years of the study, chamaephytes decreased and woody species increased their contribution for the Raunkiaer’s life-forms, while the cosmopolitan group has steadily lost its significance for distribution range types. Shannon diversity varied between 2.46 and 3.18 among plots (based on natural logarithm) and remained statistically unchanged through time. Average species turnover rates were 14.18% for 2018/19 and 17.52% for 2019/20, whereas corresponding values for vegetation turnover rates were 25.83% and 23.28%. Vegetation turnover rate was significantly higher than the species turnover rate.

1. Introduction

Steppe grasslands on loess are among the most species rich vegetation types of Hungary, harbouring several rare and endangered species. Before the advent of industrial agriculture, these grasslands covered large areas on the Hungarian Plain and the surrounding foothills [1]. By now, this vegetation type had shrunk to a fraction of its former territory, surviving in isolated fragments mostly on terrain unsuitable for mechanized agriculture, like steep slopes and narrow land stripes along motorways or railway lines, whereas some other patches were spared on prehistoric earthworks (kurgans, mottes, ramparts) considered as cultural heritage sites [2,3]. Therefore, each still existing steppe grassland patch on loess is of high botanical and nature conservation values today [4,5].
These grasslands understandably attracted the interest of botanical researchers. The relic patches of loess grassland vegetation played an important role in the reconstruction of the potential vegetation map of Hungary [6,7]. Due to their textural and structural complexity as well as historical importance, plant communities on loess soils were also frequent subjects of archaeobotanical and vegetation dynamical studies abroad [8,9,10,11,12]. In Hungary, loess vegetation was also intensively studied, led by professorFekete, a prominent plant ecologist, in the second half of the 20th century [13,14,15,16]. Further research focused on soil respiration and soil water content in connection with vegetation cover [17], as well as on the effect of indigenous fossorial mammals on the species composition of loess grasslands [18].
In general, biodiversity has long been shown to be influenced by environmental factors [19]. Besides studies on the effects of abiotic factors on biodiversity [20,21,22], the biotic environment has significant effects on biodiversity as well [23]. Interaction of biotic impact in combination with environmental conditions on biodiversity was also reported [24]. Documented examples prove that high diversity of one biotic component has supportive effect in increasing the diversity of another biotic component of the environment. In a review of 320 case studies, Castagneyrol and Jactel [25] convincingly demonstrated that the diversity of arthropods, birds, and mammals significantly increased with plant diversity regardless of species’ habitats. Multiple pieces of evidence also support the interaction between aboveground and belowground diversity via grazing the standing vegetation, individual plant species effects, plant species and functional type diversity, mixing of plant litter types, and other reasons [26,27]. However, there are difficulties in detecting these interactions mainly because soil organisms are much lesser known than aboveground biota; therefore, species-level comparisons are practically impossible in most cases [28]. Novel molecular genetic techniques like metagenomics provide a solution for this problem.
Our work is part of a multidisciplinary research on loess substrate that aims at uncovering the diversity of the soil microbiome and the coexisting macroscopic biota with particular interest in how various ways of farming influence diversity relative to that of a reference natural grassland.
Although the reference grassland can be considered as a stable vegetation, changes in its structure and diversity may occur due to the abandonment of past grazing, climate change, nitrogen deposition and other causes may also affect grasslands [29]. Tilman’s resource–ratio hypothesis model is among others the most likely to operate in this case [30,31].
This paper reports on the phytocoenological survey of the reference natural steppe grassland on loess conducted through three years. We give a detailed description of the plant community with special attention to vascular plant diversity, and also evaluate its change during the three years by using a plant functional trait approach.

2. Results

In total, 108 vascular plant species were detected in the plots. The highest number of species (71) was found in Plot-1 in 2018, whereas the lowest (39) was recorded in Plot-2 in 2019. Average and median number of species were 54.9 (SD = 10.3) and 52.5, respectively. The most abundant species were in decreasing order: Brachypodium pinnatum, Festuca rupicola, Filipendula vulgaris, Euphorbia pannonica, Teucrium chamaedrys, Galium verum, Carex michelii and Salvia pratensis. The complete list of species with their cover values are shown in the Appendix A, Table A1.
Distribution of species according to Raunkiaer’s life-form categories in the three study years is shown in Figure 1. The groups of hemicryptophytes and geophytes (H+G) are dominant, followed by the group of annual and biennial species (Th+TH), whereas phanerophytes (M) has subordinate contribution throughout the three years. Chamaephytes and nanophanerophytes are practically negligible as they are represented by only 1–3 species.
Considering the life-form spectra based on cover values, the H+G group maintained its overwhelming dominance in every year. At the same time, the least competitive species has lost some of their importance (Th+TH group), whereas chamaephytes decreased and woody species (N and M) increased their contribution in the vegetation of the grassland (Figure 2). Based on the chi-squared test performed on the merged cover data of the four plots, a significant shift appears in the life-form distribution over the three years (Chi2 = 16.183, p = 0.03983, d.f. = 8). According to the residuals, changes in the cover of chamaephytes (Ch) and phanerophytes (M) are mainly responsible for the shift in the spectrum.
According to chorological type of species, the European species are dominant followed by those of continental species (Figure 3). The ratio of species among the distribution range types remained basically similar during the study.
When the distribution among range types was based on species cover values, the homogeneity test which was performed on the merged cover data of the four plots revealed highly significant differences among years (Chi2 = 34.251, p < 0.0001, d.f. = 8). The significant differences are mainly due to the annual fluctuations of some chorological groups. This can be observed even in the dominant European (EUR) group. The only significant one-way change was shown by the cosmopolitan (COS) group, which has steadily lost its significance during the years of observation (Figure 4).
The species pool in each of the four plots of the loess grassland was also analyzed by their thousand-seed weight. Relative representation of the eight seed weight classes was depicted based on yearly vegetation surveys from 2018 to 2020 (Figure 5). The seed weight spectra of the three study years proved to be statistically identical in a homogeneity test (Chi-square: 17.923; p = 0.9848). However, the loess grassland’s seed weight spectra differed significantly from that of the Hungarian flora (Chi-square: 120.03; p < 0.0001). The most striking difference was the over-representation of the intermediate seed weight categories (3, 4 and 5) in the loess grassland.
Species-abundance diversity values are summarized in Table 1. During the three years, the diversity of the grassland remained statistically unchanged (p = 0.6528 according to Friedman’s nonparametric repeated measures ANOVA). Average diversity (n = 12) was 2.857 (±0.20); however, the values fluctuated slightly, the highest value was 3.18 in Plot-4 and the lowest was 2.46 in Plot-2, observed in 2018 and 2019, respectively.
Turnover rates in consecutive years and in two years term for species and vegetation of the plots are shown in Figure 6. Regarding species turnover rates, the values calculated for adjacent years did not differ statistically. Average species turnover rates of plots (n = 4) were 14.18% and 17.52% for 2018/2019 and 2019/2020, respectively. However, two-year turnover rates of plots (19.23% in average) proved to be significantly higher (p < 0.05) than the one-year rates of 2018/2019, whereas they were identical with that of 2019/2020, according to Friedman’s nonparametric repeated measures ANOVA (Table 2).
Considering vegetation turnover rates, the values calculated for the consecutive years again did not differ statistically. Average vegetation turnover rates of plots (n = 4) were 25.83% and 23.28% for 2018/2019 and 2019/2020, respectively. However, two-year turnover rates (2018/2020) of plots (30.35% in average) were significantly higher (p < 0.05) than that of 2019/2020, whereas they did not differ from that of 2018/2019, according to the same statistical test used for species turnover rate data (Table 2).
Finally, the species turnover rates of plots calculated between the adjacent years were compared with the corresponding vegetation turnover rates. In the paired t-test, vegetation turnover rates proved to be significantly higher (p = 0.0067, t = 3.799, d.f. = 7).

3. Discussion

Some of the analyses which were performed in this study referred to the stability of the loess grassland in Pócalja, while others referred to its slow successional change. The results indicating stability were obtained mainly from the analyses based on the species data, while changes were observed when vegetation data were taken into consideration.
The share of species among Raunkiaer’s life-form classes and distribution range classes remained practically unchanged during the three years of observation. These indicate that no remarkable textural change of the grassland took place during the study period. The same could be read from the distribution of the species pools of the four plots among the thousand-seed weight classes, which also did not show a significant shift during the three years. As far as the distribution of thousand-seed weight is concerned, it is also necessary to point out that the distribution of the studied loess grassland differed significantly from the distribution observed in the species pool of the entire Hungarian flora [32]. It is known from Salisbury’s studies that the average thousand-seed weight of species coexisting in a habitat is expected to increase as the habitat closes [33,34]. Later, the phenomenon was also demonstrated for the Hungarian flora [35]. In line with this, the maximum values observed for the medium seed weight categories, which characterized the studied grassland, can be assessed as the vegetation in Pócalja being a perfectly developed, considerably closed typical loess steppe grassland. The dominance of species with intermediate thousand-seed weight was also reported for other closed grasslands of north facing slopes [36].
A further sign of maturity of the studied loess grassland is its relatively high Shannon diversity that was, on average, 2.949, 2.809 and 2.812 for 2018, 2019 and 2020, respectively. In comparison, long time uncultivated linear-shaped habitats in verges covered by dry grassland fragments in the Great Hungarian Plain maintained an average diversity of 2.2 [37]. In Transylvania (Romania), for grazed grasslands and hand mowed grasslands, Shannon diversity values were around 2.7–3.2 [38], whereas, for mountainous semi-natural grasslands, diversity values of 2.36–2.68 were reported, depending on various conservation treatments [39]. Beyond local geographical regions, like in Sweden, grazed semi-dry grasslands’ diversity ranged from 2.4 to 3.3 [40], whereas grasslands developed on limestone bedrock maintained diversity of 2.2–3.1 [41]. A slightly higher diversity was reported from the Himalayas, near the border between Pakistan and India, where grazed mountain meadows were characterised by Shannon diversity values of 2.9–3.3 [42].
Besides the signs of stability, some of the analyses indicated gradual change of the studied grassland. The Raunkiaer’s life-form distribution based on species cover values has changed significantly during the three years. The change could be attributed to the gradual decrease in a cover of therophyte (Th+TH) and chamaephyte (Ch) groups, with the simultaneous increase of phanerophytes’ (M) cover. These changes can collectively be explained by the growing prevalence of woody species, as their cover increases competition with therophytes, increasing shading conditions, affecting at the same time both chamaephytes and therophytes. Shrub encroachment is a worldwide phenomenon on mesic or moderately dry grasslands [43,44], and its restrictive effect on annual and biennial species as well as the most light demanding group of perennials has also been documented [45].
Another plant trait which indicates changes among years is the geographical distribution type when species cover data were used. There were fluctuating changes in most of the categories, but a continuous decline was observed in the cosmopolitan (COS) group over the three years. The fluctuations can be explained as the adaptive response of the vegetation to the different climatic years, with which the plant community keeps the grassland closed by increasing or decreasing the cover of individual species according to changes in the prevailing precipitation, irradiance or other regimes [46,47,48]. Similar buffering effect to compensate environmental changes was reported for other grasslands and the phenomenon generally discussed as “the insurance hypothesis” [49,50]. However, the continuous and considerable decrease in the cover of cosmopolitan species can probably be linked with the increased cover of woody species. Most of the species in the cosmopolitan group have more or less ruderal character [51], and are therefore sensitive to increased competition caused by shrub encroachment [52].
In summary, plant trait frequency analyses based on species pool referred more to the stability of the grassland, whereas analyses taking into account the cover of the species indicated a change in the grassland. This result can be interpreted as meaning that the relatively short period of observation did not allow for detecting significant change in species composition, but unidirectional successional change has already occurred in species cover.
Comparing the sensitivity of the examined turnover rates to indicate changes, it is again shown that vegetation turnover rate indicates a larger percentage change than species turnover rate, and the difference between the two types of turnover rates was statistically significant. The study of the exchange rates also provided an additional opportunity to explore the vegetation dynamics processes in the studied loess grassland. According to this, if there is indeed a directional change, the values of the two-year turnover rates should be significantly higher than the values calculated for any of the two cases of one-year turnover rates. However, this was only partially achieved, as for both types of turnover rates the values calculated for the two-year period behaved ambivalently to the one-year rates: in one case, the two-year rate was significantly higher, but not in the other. In this context, it is worth mentioning that considerable differences were also reported among species turnover rates calculated for different pairs of consecutive years in a South Bohemian heathland [53]. Ambiguous results may also be due to climatic fluctuations between years [54]. Mixed signs of fluctuation and slight directional change have also been observed in other grassland studies [55].
In conclusion, the plant trait approach used here proved to be applicable in studying dynamic changes of a species rich loess grassland. Plant traits based on species cover values were more sensitive to changes than traits based on species pool data, at least in the relatively short observation period applied in the present study. Species turnover rates and vegetation turnover rates are also suitable for quantifying dynamic processes in grasslands, but, for detecting directional successional changes, a study longer than three years is advised.

4. Materials and Methods

Study site. Surrounded by intensive agricultural fields (maize, wheat, sunflower), a 14-hectare loess grassland has escaped conversion to arable land at “Pócalja” near the town Bicske (Central Hungary) owing to its relief with steep slopes between 30–50 degrees, facing north, which prevented the use of agricultural machinery (Figure 7 and Figure 8). The grassland is 2 km away from the residential area and is avoided by traffic routes, so human disturbance and trampling practically do not affect the study site. The slope is covered with Haplic Chernozem (loamic) soil according to IUSS Working Group WRB [56], which is characterised by the following physico-chemical properties: pHH2O = 7.1 ± 0.1, pHKCl = 6.8 ± 0.1, Corg = 4.00% ± 0.18, Ntot = 0.48% ± 0.02, CaCO3 content by Scheibler calcimeter = 5.07% ± 2.69, plant available P2O5 = 104 ± 46.7 and K2O = 260 ± 11.0 mg/kg (ammonium-lactate soluble), NH4+-N = 8.57 ± 0.42 mg/kg, nitrate-N = 1.82 ± 0.56 [57].
The local climatic conditions are characterized by yearly average temperature 9.7–10.0 °C, average temperature in the summer semester 16.0–16.5 °C, yearly average precipitation 550 mm, average precipitation in the summer semester 330 mm. Frosty days can occur from November to April, the average wind speed is around 3 m/s [58].
The protected Natura 2000 area is covered by Pannonic loess steppic grasslands where Festuca rupicola and Brachypodium pinnatum are the dominant species. Among dicotyledonous species, Filipendula vulgaris, Salvia pratensis, Galium verum, Chamaecytisus austriacus, Euphorbia pannonica and Teucrium chamaedrys attain greater cover values, whereas notable protected, rare herbs are Echium russicum, Adonis vernalis, Dianthus pontederae, Linum flavum and Taraxacum serotinum.
Sampling. Four 4 m by 4 m permanent plots were established in 2018. GPS coordinates of the four plots (P1–P4) are: P1, 47°28.187′ N, 18°39.374′ E; P2, 47°28.193′ N, 18°39.381′ E; P3, 47°28.201′ N, 18°39.386′ E; P4, 47°28.208′ N, 18°39.388′ E, each located at an altitude of about 160 m above sea level. For each plot, vascular plant species and their cover values were recorded by using a percentage scale. Since species asynchrony is a characteristic feature of species rich grasslands [59], surveys of plots were conducted in three occasions (May, July and September) during the growing seasons of years 2018–2020. On every occasion, the species cover was estimated visually by three trained botanists, then their individually estimated values were averaged, thus forming the raw data of the surveys. Plant specimens were identified according to the Hungarian flora [60], plant nomenclature follows [61].
For further analyses, raw data of the three surveys of a certain plot in a year were summarized so that each species was considered with its highest recorded cover value in the growing season, thus forming the phytosociological relevé of the plot. Phytosociological relevés are presented in the Appendix A, Table A1.
Data analyses. For each phytosociological relevé, share of species according to Raunkiaer’s life-form categories and distribution range types (chorological types) were calculated [61]. The representativeness of the eight seed weight categories in the species pool of the four plots was also analyzed, based on the thousand-seed weight (TSM) of species [32,36]. (Hereafter, seed denotes all kinds of seed-like disseminules: seed, achene, caryopsis, etc). The following TSM classes were used: 1: ≤0.2 g, 2: 0.21–0.50 g, 3: 0.51–1 g, 4: 1.01–2 g, 5: 2.01–4 g, 6: 4.01–10 g, 7: 10.1–50 g, 8: >50 g. Where appropriate, the plant trait spectra were subjected to homogeneity tests among the three studied years.
Species-abundance diversity of the plots was calculated based on the Shannon–Wiener formula, with natural base of logarithm.
For each permanent plot, species turnover rate (Tsp) was calculated between years 2018 and 2019, as well as years 2019 and 2020, according to the formula:
Tsp = (I + D)/(I + D + 2U) ∗ 100
where I is the “increases”: the number of species occurred in the second year of the comparison but were absent in the first year; D is the “decreases”: the number of species occurred in the first year of the comparison but disappeared to the second year; U is “unaltered”: the number of common species of the two years. In this way, the results are given in a percentage form [19,62].
Vegetation turnover rate (Tveg) between two subsequent years were also calculated for each permanent plot according to the formula:
T Veg ( y 1 ) ( y 2 ) = ∑ i = 1 n | x i ( y 1 ) − x i ( y 2 ) | ∑ i = 1 n ( x i ( y 1 ) + x i ( y 2 ) ) ∗ 100
where xi(y1) and xi(y2) is the percentage cover of species i in the first year and in the subsequent year, respectively, and n is the cumulative number of species registered in the given permanent plot during year 1 and year 2. Thus, for a given species, whether its cover increases or decreases compared to the previous year, it contributes to increasing the value of the vegetation turnover rate.
Additionally, a two-year turnover rate (2018/2020) was also calculated to detect changes in the flora and in the vegetation.
A paired sample t-test was used to compare species- and vegetation turnover rates between 2018/2019 and 2019/2020. Friedman’s nonparametric repeated measures ANOVA followed by Dunn’s multiple comparison post hoc test was used for comparisons for more than two data sets.
PAST-3.25 and InStat-3.06 packages were used to perform statistical tests [63,64].

Author Contributions

Conceptualization, P.C., T.S.-K. and T.K.; methodology, P.C., J.T. and T.K.; field work, P.C., J.T., Z.K., T.K. and J.S.; validation, Z.K. and T.K.; formal analysis, J.T., P.C. and T.K.; investigation, T.S.-K.; resources, K.P. and T.S.-K.; data curation, J.T. and J.S.; writing—original draft preparation, P.C. and T.K.; writing—review and editing, P.C. and T.K.; visualization, P.C. and J.T.; supervision, T.K. and T.S.-K.; project administration, J.S. and T.S.-K.; funding acquisition, T.S.-K. and K.P. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Széchenyi 2020 programme, the European Regional Development Fund and the Hungarian Government (Grant No: GINOP-2.3.2-15-2016-00056), and also received support from National Scientific Research Fund (Grant No.: OTKA K-125423.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data are contained within the article and its Appendix A.

Acknowledgments

We are grateful to the anonymous Reviewers for valuable suggestions.

Conflicts of Interest

The authors declare no conflict of interest.

Abbreviations

RLFRaunkiaer’s life forms
Ththerophyte
THhemitherophyte
Hhemicryptophyte
Ggeophyte
Chchamaephyte
Nnanophanerophyte
Mmicrophanerophyte
FLEfloristic element (chorological type)
SWseed weight category
nanot available

Appendix A

Table
Table A1. List of species with their cover values in the Natura-2000 loess grassland at “Pócalja”, Central Hungary, in the years 2018–2020.
Table A1. List of species with their cover values in the Natura-2000 loess grassland at “Pócalja”, Central Hungary, in the years 2018–2020.
PlotsPlot-1Plot-2Plot-3Plot-4RLFFLESW
Years201820192020201820192020201820192020201820192020
Species Name
Achillea collina J. Becker 2.0 0.1 1.0 1.0HCON1
A. pannonica Scheele2.01.00.10.51.00.12.05.01.03.01.00.5HPON1
Adonis vernalis L.2.01.02.04.01.03.04.03.04.03.02.02.0HCON7
Agrimonia eupatoria L. 0.1 1.01.02.02.03.03.0HEUR7
Agropyron intermedium Host 0.19.0 0.110.02.015.014.0GPoM6
A. repens (L.) P. B. 0.1 1.05.00.13.010.0 GCIR5
Ailanthus altissima (Mill.) Swingle 0.1 MMADV7
Ajuga reptans L. 0.1 H-ChEUR4
Anthericum ramosum L.1.0 GCEU6
Arabis hirsuta (L.) Scop.0.10.10.1 0.10.50.1TH-HCIR1
Arrhenatherum elatius (L.) J. et C. Presl0.1 1.0 0.1 0.5 HEUA5
Asperula cynanchica L. 0.1 0.51.01.0HPoM3
Astragalus austriacus Jacq. 1.00.50.5HCON3
A. onobrychis L.1.01.00.1 1.00.50.5 HCON4
Betonica officinalis L.0.10.50.1 HEUA4
Bothriochloa ischaemum (L.) Keng 0.5 0.50.10.11.0HPoM2
Brachypodium pinnatum (L.) P. B.19.030.030.040.045.030.09.020.025.025.025.013.0H(Ch)EUA6
Brassica elongata Ehrh. 0.1 TH-HCON2
Briza media L.2.02.00.50.1 3.00.11.0HKOZ3
Bromus erectus Huds. 0.1 0.1 HPaB6
B. inermis Leyss. 0.15.01.08.0HCIR5
Campanula bononiensis L.0.1 0.12.00.50.1 HEUA1
C. glomerata L. 2.00.1 0.1HEUA1
Carduus acanthoides L. 0.1 THEUR4
Carex humilis Leyss.5.03.02.00.10.1 0.1 0.51.00.5HCON4
C. michelii Host1.01.00.52.05.03.038.015.013.00.10.11.0HSMO5
C. tomentosa L.0.10.10.10.10.1 0.1 0.10.10.1GEUA4
Carlina vulgaris L.0.10.50.1 0.1TH-HEUA4
Centaurea micranthos S.G. Gmel. 0.1 0.1 TH-HPON4
C. pannonica (Heuff.) Simk.1.00.51.02.04.04.00.51.02.03.02.05.0HPoP4
C. sadlerana Janka3.05.07.0 HPAN6
Chamaecytisus austriacus (L.) Link10.010.013.08.06.05.02.05.03.00.10.10.5NPoP6
Chrysanthemum leucanthemum L. 0.1 0.1HEUA2
Cirsium arvense (L.) Scop.1.02.00.1 GEUA4
Clinopodium vulgare L. 9.03.01.0HCIR2
Cornus sanguinea L.0.10.10.10.1 0.10.10.10.1MSME8
Coronilla varia L. 0.10.1 HPoM5
Crataegus monogyna Jacq.0.11.00.52.02.03.02.02.03.01.01.03.0MEUR7
Dactylis glomerata L.1.02.00.52.01.0 0.1 0.18.02.00.5HKOZ3
Daucus carota L. 0.1 0.10.5 1.0 0.1Th-THKOZ5
Dianthus pontederae Kern.0.10.50.10.10.50.10.10.10.10.1 0.1HPAN3
Dorycnium germanicum (Gremli) Rikli 3.01.02.0 ChALB5
Eryngium campestre L.2.00.51.04.03.03.01.02.02.01.01.01.0HPoM5
Euphorbia pannonica Host10.014.015.08.04.07.015.020.014.06.05.05.0HPaB4
Falcaria vulgaris Bernh. 1.00.50.11.00.10.1Th-THEUA4
Festuca rupicola Heuff.25.035.025.020.025.025.010.020.025.020.030.035.0HEUA3
Filipendula vulgaris Mönch15.010.08.08.011.05.015.012.012.015.012.010.0HEUA3
Fragaria viridis Duch.0.10.50.11.01.00.52.03.02.03.03.03.0HCON2
Galium aparine L.0.1 ThKOZ6
G. glaucum L.1.01.00.11.01.01.00.10.10.10.10.51.0HPoM4
G. verum L.7.08.05.06.015.05.05.015.06.05.010.02.0HEUA3
Helictotrichon praeustum (Rchb.) Tzvelev1.01.00.5 0.52.06.05.010.03.0 2.0HEURna
Helictotrichon pubescens (Huds.) Pilger1.01.00.11.02.01.01.00.10.55.00.11.0HEUA5
Hieracium cymosum L.0.10.50.1 0.1HEUAna
H. sabaudum L. 0.1 0.1HCEU2
Inula sp. 0.1 0.1 HCONna
Knautia arvensis (L.) Coult.1.02.02.01.01.01.02.01.00.51.01.01.0HEUA5
Koeleria cristata (L.) Pers.1.01.00.1 0.10.1 HKOZ2
Lathyrus tuberosus L. 0.1 0.1 H-GEUA7
Leontodon hispidus L.0.10.10.1 0.1 HEUR4
Ligustrum vulgare L. 0.1 MAsM7
Linum catharticum L.0.10.10.1 Th(H)EUR1
L. flavum L.0.10.51.0 0.1 0.5HPoP3
Lotus corniculatus L.1.00.10.11.00.50.5 1.00.10.1HEUA4
Luzula campestris (L.) Lam. et DC.0.10.1 HKOZ3
Medicago falcata L.3.00.10.55.02.02.05.02.03.03.05.02.0HEUA4
M. lupulina L.0.1 Th-THEUA4
Melilotus officinalis (L.) Pall. 0.10.1 0.1 0.1 0.1Th-THEUA4
Muscari comosum (L.) Mill. 0.1 0.1 GSME6
M. racemosum (L.) Mill.0.1 GSME5
Ononis spinosa L. 1.01.51.00.50.50.5 H-ChEUR5
Ornithogalum kochii Parl.0.10.5 0.1 0.1 GPoMna
Orobanche teucrii Holandre0.10.1 GCEU1
Phleum phleoides (L.) Karsten0.10.10.1 0.1 0.1 HCON1
Picris hieracioides L.0.10.52.00.10.10.10.11.0 0.12.01.0TH-HEUA3
Pimpinella saxifraga L.0.1 0.10.10.50.10.50.50.50.50.12.0HEUA3
Plantago media L.1.00.50.5 0.50.10.1HEUA2
Poa pratensis L.1.01.00.18.00.50.52.0 1.00.11.0 HKOZ2
Prunella grandiflora (L.) Scholler0.10.10.5 0.10.1 HEUR3
P. laciniata (L.) Nath.0.10.50.1 0.1 HSME4
P. x bicolor Beck0.1 0.1 1.00.51.00.1 HSMEna
Prunus cerasifera Ehrh. 0.1 0.1 0.1MADV8
P. spinosa L.0.10.10.50.10.10.50.10.50.54.08.013.0MEUR8
Ranunculus polyanthemos L.1.00.50.10.10.10.1 2.01.00.5HPON5
Rhamnus catharticus L.0.10.10.10.10.10.1 0.10.10.1MEUA7
Salvia nemorosa L. 0.10.50.5 HEUR3
S. pratensis L.3.08.07.04.05.03.05.010.06.04.07.06.0HEUR4
Sanguisorba minor Scop. 0.1 HEUR6
Scabiosa ochroleuca L.1.00.10.1 0.1 1.00.11.0HCON4
Senecio jacobaea L. 0.1 0.10.10.1HEUA2
Seseli annuum L.1.00.10.10.10.10.10.50.10.10.10.10.5Th-TH-HCON2
Setaria viridis (L.) P. B. 3.0 0.1 ThEUA3
Stachys recta L.0.1 0.1 0.1 HPoM4
Taraxacum officinale Weber 0.10.10.1 0.1HEUA2
T. serotinum (W. et K.) Poir.0.50.50.5 1.02.02.0HPoP3
Teucrium chamaedrys L.8.08.08.03.03.02.015.015.06.010.08.05.0ChSME4
Thesium linophyllon L.0.10.10.10.1 0.1 0.10.10.1G-HCEU5
Thlaspi perfoliatum L.0.10.1 ThSME2
Thymus pannonicus All.1.05.00.10.1 1.01.0 2.03.00.5ChCEUna
Tragopogon orientalis L.1.02.00.1 0.10.50.1 TH-HEUA6
Trifolium alpestre L.0.1 0.13.01.00.10.1 HCEU5
Trifolium montanum L.1.03.01.03.01.01.02.05.01.01.02.01.0HCON3
Verbascum phoeniceum L.0.51.00.5 0.11.00.5HPON1
Veronica austriaca L.0.10.10.1 0.1 HPON1
Veronica spicata L.0.50.10.10.1 0.10.1 0.50.50.1H-ChEUA1
Viola canina L. 0.1 0.1 HEUA3
indet. dicot. 1 0.1
indet. dicot. 2 0.1
Number of species716269513945524448625363
Total cover (%)140.8169.0141.9141.0144.6120.4160.9178.5161.5162.8172.8155.1

References

  1. Zólyomi, B. Természetes növénytakaró (Natural vegetation). In Magyarország Nemzeti Atlasza (National Atlas of Hungary); Pécsi, M., Ed.; Kartográfiai Vállalat: Budapest, Hungary, 1989; p. 89. [Google Scholar]
  2. Penksza, K.; Kiss, T.; Herczeg, E.; Nagy, A.; Malatinszky, Á. Anthropogenic impacts and management of natural grasslands on kurgans. In Kurgan Studies: An Environmental and Archaeological Multiproxy Study of Burial Mounds in the Eurasian Steppe Zone; Pető, Á., Barczi, A., Eds.; BAR International Series: Oxford, UK, 2011; pp. 329–338. [Google Scholar]
  3. Tóth, A.C.; Deák, B.; Nyilas, I.; Bertalan, L.; Valkó, O.; Novák, T. Iron age burial mounds as refugia for steppe specialist plants and invertebrates—Case study from the Zsolca mounds (NE Hungary). Hacquetia 2019, 18, 189–200. [Google Scholar] [CrossRef] [Green Version]
  4. Szerényi, J. Adatok az Észak-Mezőföld löszflórájához. Kitaibelia 2000, 5, 249–270. [Google Scholar]
  5. Molnár, Z.; Biró, M.; Bartha, S.; Fekete, G. Past Trends, Present State and Future Prospects of Hungarian Forest-Steppes. In Eurasian Steppes. Ecological Problems and Livelihoods in a Changing World. Plant and Vegetation; Werger, M.J.A., van Staalduinen, M.A., Eds.; Springer: Dordrecht, The Netherlands, 2012; Volume 6, pp. 209–252. [Google Scholar] [CrossRef]
  6. Zólyomi, B. Rekonstruált növénytakaró. [Reconstructed vegetation.] 1:1500000. In Magyarország Nemzeti Atlasza; Radó, S., Ed.; Kartográfiai Vállalat: Budapest, Hungary, 1967; pp. 21–31. [Google Scholar]
  7. Zólyomi, B.; Fekete, G. The Pannonian loess steppe: Differentiation in space and time. Abstr. Bot. 1994, 18, 29–41. [Google Scholar]
  8. Liu, T.S.; Guo, Z.T.; Wu, N.Q.; Lu, H.Y. Prehistoric vegetation on the Loess Plateau: Steppe or forest? J. Southeast Asian Earth Sci. 1996, 13, 341–346. [Google Scholar] [CrossRef]
  9. Li, X.; Sun, N.; Dodson, J.; Zhou, X.; Zhao, K. Vegetation characteristics in the western Loess plateau between 5200 and 4300 cal. B.P. based on fossil charcoal records. Veget. Hist. Archaeobot. 2013, 22, 61–70. [Google Scholar] [CrossRef]
  10. Wu, G.-L.; Zhang, Z.-N.; Wang, D.; Shi, Z.-H.; Zhu, Y.-J. Interactions of soil water content heterogeneity and species diversity patterns in semi-arid steppes on the Loess Plateau of China. J. Hydrol. 2014, 519, 1362–1367. [Google Scholar] [CrossRef]
  11. Miñarro, F.; Martinez, U.; Bilenca, D.; Olmos, F. Río de la Plata Grasslands or Pampas & Campos (Argentina, Uruguay and Brazil)—Temperate grasslands of South America. In Proceedings of the World Temperate Grasslands Conservation Initiative Workshop, Hohhot, China, 28–29 June 2008; pp. 24–33. [Google Scholar]
  12. Paruelo, J.M.; Jobbágy, E.G.; Oesterheld, M.; Golluscio, R.A.; Aguiar, M.R. The Grasslands and Steppes of Patagonia and the Rio de la Plata Plains. In The Physical Geography of South America; Veblen, T., Young, K., Orme, A., Eds.; Oxford University Press: Oxford, UK, 2007; Chapter 14; pp. 232–248. [Google Scholar] [CrossRef]
  13. Virágh, K.; Fekete, G. Degradation stages in a xeroseries: Composition, similarity, grouping, coordination. Acta Bot. Acad. Sci. Hung. 1984, 30, 427–459. Available online: https://www.webofscience.com/wos/woscc/full-record/WOS:A1984ATM0900014 (accessed on 26 February 2022).
  14. Fekete, G.; Tóthmérész, B. Vegetation science in Hungary. J. Veg. Sci. 1993, 4, 279–282. [Google Scholar] [CrossRef]
  15. Nagy, Z.; Tuba, Z.; Szente, K.; Úzvölgyi, J.; Fekete, G. Photosynthesis and water-use efficiency during degradation of a semiarid loess steppe. Photosynthetica 1994, 30, 307–311. Available online: https://www.webofscience.com/wos/woscc/full-record/WOS:A1994PT73600018 (accessed on 26 February 2022).
  16. Fekete, G.; Virágh, K.; Aszalós, R.; Précsényi, I. Static and dynamic approaches to landscape heterogeneity in the Hungarian forest-steppe zone. J. Veg. Sci. 2000, 11, 375–382. [Google Scholar] [CrossRef]
  17. Fóti, S.; Balogh, J.; Nagy, Z.; Ürmös, Z.; Bartha, S.; Tuba, Z. Temporal and spatial variability and pattern of soil respiration in loess grassland. Community Ecol. 2008, 9, 57–64. [Google Scholar] [CrossRef]
  18. Zimmermann, Z.; Szabó, G.; Csathó, A.I.; Kapocsi, J.S.; Szentes, S.; Juhász, M.; Házi, J.; Komoly, C.; Virágh, K.; Harkányiné Székely, Z.; et al. The impact of the lesser blind mole rat [Nannospalax (superspecies leucodon)] on the species composition and diversity of a loess steppe in Hungary. Appl. Ecol. Env. Res. 2014, 12, 577–588. [Google Scholar] [CrossRef]
  19. MacArthur, R.H.; Wilson, E.O. The Theory of Island Biogeography; Princeton University Press: Princeton, NJ, USA, 1967; pp. 1–203. [Google Scholar]
  20. Johnson, M.P.; Frost, N.J.; Mosley, M.W.J.; Roberts, M.F.; Hawkins, S.J. The area-independent effects of habitat complexity on biodiversity vary between regions. Ecol. Lett. 2003, 6, 126–132. [Google Scholar] [CrossRef]
  21. Hjort, J.; Heikkinen, R.K.; Luoto, M. Inclusion of explicit measures of geodiversity improve biodiversity models in a boreal landscape. Biodivers. Conserv. 2012, 21, 3487–3506. [Google Scholar] [CrossRef]
  22. Carballeira, R.; Pontevedra-Pombal, X. Diversity of testate Amoebae as an indicator of the conservation status of peatlands in Southwest Europe. Diversity 2021, 13, 269. [Google Scholar] [CrossRef]
  23. Wehnert, A.; Wagner, S.; Huth, F. Effects of pure and mixed pine and oak forest stands on carabid beetles. Diversity 2021, 13, 127. [Google Scholar] [CrossRef]
  24. Mod, H.K.; Heikkinen, R.K.; le Roux, P.C.; Wisz, M.S.; Luoto, M. Impact of biotic interactions on biodiversity varies across a landscape. J. Biogeogr. 2016, 43, 2412–2423. [Google Scholar] [CrossRef]
  25. Castagneyrol, B.; Jactel, H. Unraveling plant–animal diversity relationships: A meta-regression analysis. Ecology 2012, 93, 2115–2124. [Google Scholar] [CrossRef] [PubMed]
  26. Wardle, D.A. The influence of biotic interactions on soil biodiversity. Ecol. Lett. 2006, 9, 870–886. [Google Scholar] [CrossRef] [PubMed]
  27. Millard, P.; Singh, B.K. Does grassland vegetation drive soil microbial diversity? Nutr. Cycl. Agroecosyst. 2010, 88, 147–158. [Google Scholar] [CrossRef]
  28. Hooper, D.U.; Bignell, D.E.; Brown, V.K.; Brussaard, L.; Dangerfield, J.M.; Wall, D.H.; Wardle, D.A.; Coleman, D.C.; Giller, K.E.; Lavelle, P.; et al. Interactions between aboveground and belowground biodiversity in terrestrial ecosystems: Patterns, mechanisms, and feedbacks. Bioscience 2000, 50, 1049–1061. [Google Scholar] [CrossRef]
  29. Liu, J.-J.; Xu, Y.; Shan, Y.-X.; Burgess, K.S.; Ge, X.J. Biotic and abiotic factors determine species diversity–productivity relationships in mountain meadows. J. Plant Ecol. 2021, 14, 1175–1188. [Google Scholar] [CrossRef]
  30. Begon, M.; Harper, J.L.; Townsend, C.R. Ecology: Individuals, Populations and Communities; Blackwell Scientific Publication: Oxford, UK, 1986; pp. 1–876. [Google Scholar]
  31. Tilman, D. The resource-ratio hypothesis of plant succession. Am. Nat. 1985, 125, 827–852. Available online: https://www.jstor.org/stable/2461449 (accessed on 12 March 2022). [CrossRef]
  32. Csontos, P. A Természetes Magbank Kutatásának Módszerei; Scientia Kiadó: Budapest, Hungary, 2001; pp. 1–155. Available online: https://www.researchgate.net/publication/351241955_A_termeszetes_magbank_kutatasanak_modszerei (accessed on 12 March 2022).
  33. Salisbury, E.J. The Reproductive Capacity of Plants; G. Bell and Sons: London, UK, 1942; pp. 1–244. [Google Scholar]
  34. Salisbury, E.J. Seed size and mass in relation to environment. Proc. R. Soc. Ser. B-Biol. 1974, 186, 83–88. [Google Scholar] [CrossRef]
  35. Csontos, P. The applicability of a seed ecological database (SEED) in botanical research. Seed Sci. Res. 1998, 8, 47–51. [Google Scholar] [CrossRef]
  36. Csontos, P.; Tamás, J.; Podani, J. Slope aspect affects the seed mass spectrum of grassland vegetation. Seed Sci. Res. 2004, 14, 379–385. [Google Scholar] [CrossRef]
  37. Deák, B.; Radai, Z.; Lukács, K.; Kelemen, A.; Kiss, R.; Bátori, Z.; Kiss, P.J.; Valkó, O. Fragmented dry grasslands preserve unique components of plant species and phylogenetic diversity in agricultural landscapes. Biodivers. Conserv. 2020, 29, 4091–4110. [Google Scholar] [CrossRef]
  38. Kuhn, T.; Domokos, P.; Kiss, R.; Ruprecht, E. Grassland management and land use history shape species composition and diversity in Transylvanian semi-natural grasslands. Appl. Veg. Sci. 2021, 24, e12585. [Google Scholar] [CrossRef]
  39. Păcurar, F.; Balázsi, Á.; Rotar, I.; Vaida, I.; Reif, A.; Vidican, R.; Rușdea, E.; Stoian, V.; Sângeorzan, D. Technologies used for maintaining oligotrophic grasslands and their biodiversity in a mountain landscape. Rom. Biotechnol. Lett. 2020, 25, 1128–1135. [Google Scholar] [CrossRef]
  40. Reitalu, T.; Johansson, L.J.; Sykes, M.T.; Hall, K.; Prentice, H.C. History matters: Village distances, grazing and grassland species diversity. J. Appl. Ecol. 2010, 47, 1216–1224. [Google Scholar] [CrossRef]
  41. Reitalu, T.; Sykes, M.T.; Johansson, L.J.; Lönn, M.; Hall, K.; Vandewalle, M.; Prentice, H.C. Small-scale plant species richness and evenness in semi-natural grasslands respond differently to habitat fragmentation. Biol. Conserv. 2009, 142, 899–908. [Google Scholar] [CrossRef]
  42. Shaheen, H.; Khan, S.M.; Harper, D.M.; Ullah, Z.; Qureshi, R.A. Species diversity, community structure, and distribution patterns in Western Himalayan alpine pastures of Kashmir, Pakistan. Mt. Res. Dev. 2011, 3, 153–159. [Google Scholar] [CrossRef] [Green Version]
  43. Briggs, J.M.; Knapp, A.K.; Blair, J.M.; Heisler, J.L.; Hoch, G.A.; Lett, M.S.; McCarron, J.K. An ecosystem in transition: Causes and consequences of the conversion of mesic grassland to shrubland. BioScience 2005, 55, 243–254. [Google Scholar] [CrossRef]
  44. Knapp, A.K.; Briggs, J.M.; Collins, S.L.; Archer, S.R.; Bret-Harte, M.S.; Ewers, B.E.; Peters, D.P.; Young, D.R.; Shaver, G.R.; Pendall, E.; et al. Shrub encroachment in North American grasslands: Shifts in growth form dominance rapidly alters control of ecosystem carbon inputs. Glob. Chang. Biol. 2008, 14, 615–623. [Google Scholar] [CrossRef]
  45. Kesting, S. Shrub Encroachment of Temperate Grasslands: Effects on Plant Biodiversity and Herbage Production. Ph.D. Thesis, Georg-August-Universität Göttingen, Göttingen, Germany, 2009; pp. 1–63. [Google Scholar]
  46. Debreczy, Z. Fluctuating-dynamic equilibrium of photophil, xerophil rupicolous plant communities and scrub woods at the lower arid woodland limit. Ann. Hist.-Nat. Musei Natl. Hung. 1987, 79, 89–112. Available online: http://publication.nhmus.hu/annales/cikkreszletes.php?idhoz=2467 (accessed on 12 March 2022).
  47. Stroh, C.L.; De Steven, D.; Guntenspergen, G.R. Effect of climate fluctuations on long-term vegetation dynamics in Carolina bay wetlands. Wetlands 2008, 28, 17–27. [Google Scholar] [CrossRef]
  48. Lloret, F.; Escudero, A.; Iriondo, J.M.; Vilalta, J.M.; Valladares, F. Extreme climatic events and vegetation: The role of stabilizing processes. Glob. Chang. Biol. 2012, 18, 797–805. [Google Scholar] [CrossRef]
  49. Hobbs, R.J.; Yates, S.; Mooney, H.A. Long-term data reveal complex dynamics in grassland in relation to climate and disturbance. Ecol. Monogr. 2007, 77, 545–568. [Google Scholar] [CrossRef]
  50. Yachi, S.; Loreau, M. Biodiversity and ecosystem productivity in a fluctuating environment: The insurance hypothesis. Proc. Natl. Acad. Sci. USA 1999, 96, 1463–1468. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  51. Grime, J.P. Evidence for the existence of three primary strategies in plants and its relevance to ecological and evolutionary theory. Am. Nat. 1977, 111, 1169–1194. [Google Scholar] [CrossRef]
  52. Teleki, B.; Sonkoly, J.; Erdős, L.; Tóthmérész, B.; Prommer, M.; Török, P. High resistance of plant biodiversity to moderate native woody encroachment in loess steppe grassland fragments. Appl. Veg. Sci. 2020, 23, 175–184. [Google Scholar] [CrossRef]
  53. Chytrý, M.; Sedláková, I.; Tichý, L. Species richness and species turnover in a successional heathland. Appl. Veg. Sci. 2001, 4, 89–96. [Google Scholar] [CrossRef]
  54. Mészáros, T.; Józan, Z. Az évjárat hatása az Adonis vernalis L. Aculeata megporzóira. Bot. Közlem. 2020, 107, 45–55. [Google Scholar] [CrossRef]
  55. Păcurar, F.; Rotar, I.; Reif, A.; Vidican, R.; Stoian, V.; Gärtner, S.M.; Allen, R.B. Impact of climate on vegetation change in a mountain grassland—Succession and fluctuation. Not. Bot. Horti Agrobot. 2014, 42, 347–356. [Google Scholar] [CrossRef] [Green Version]
  56. IUSS Working Group WRB. World Reference Base for Soil Resources 2014, Update 2015. International Soil Classification System for Naming Soils and Creating Legends for Soil Maps; World Soil Resources Reports No. 106; FAO: Rome, Italy, 2015; pp. 1–192. Available online: https://www.fao.org/3/i3794en/I3794en.pdf (accessed on 12 March 2022).
  57. Ujvári, G.; Borsodi, A.K.; Megyes, M.; Mucsi, M.; Szili-Kovács, T.; Szabó, A.; Szalai, Z.; Jakab, G.; Márialigeti, K. Comparison of soil bacterial communities from juvenile maize plants of a long-term monoculture and a natural grassland. Agronomy 2020, 10, 341. [Google Scholar] [CrossRef] [Green Version]
  58. Dövényi, Z. Magyarország Kistájainak Katasztere, 2nd ed.; MTA Földrajztudományi Kutatóintézet: Budapest, Hungary, 2010; p. 876. [Google Scholar]
  59. Muraina, T.O.; Xu, C.; Yu, Q.; Yang, Y.; Jing, M.; Jia, X.; Jaman, M.S.; Dam, Q.; Knapp, A.K.; Collins, S.L.; et al. Species asynchrony stabilises productivity under extreme drought across Northern China grasslands. J. Ecol. 2021, 109, 1665–1675. [Google Scholar] [CrossRef]
  60. Simon, T. A Magyarországi Edényes Flóra Határozója. Harasztok—Virágos Növények, 4th ed.; Nemzeti Tankönyvkiadó: Budapest, Hungary, 2000; p. 976. [Google Scholar]
  61. Horváth, F.; Dobolyi, Z.K.; Morschhauser, T.; Lőkös, L.; Karas, L.; Szerdahelyi, T. FLÓRA Adatbázis 1.2—Taxonlista és Attribútum-Állomány; FLÓRA Munkacsoport, MTA-ÖBKI, MTM Növénytára: Vácrátót, Hungary, 1995; pp. 1–267. [Google Scholar]
  62. Tworek, S. Factors affecting temporal dynamics of avian assemblages in a heterogeneous landscape. Acta Ornithol. 2004, 39, 155–163. [Google Scholar] [CrossRef] [Green Version]
  63. Hammer, Ø.; Harper, D.A.T.; Ryan, P.D. PAST: Paleontological statistics software package for education and data analysis. Palaeontol. Electron. 2001, 4, 9. Available online: http://palaeo-electronica.org/2001_1/past/issue1_01.htm (accessed on 12 March 2022).
  64. InStat. GraphPad InStat, Version 3.06, for Windows; GraphPad Software, Inc.: San Diego, CA, USA, 2003. [Google Scholar]
Plants 11 00763 g001 550
Figure 1. Life-form spectra of species in the four plots (P1–P4) of “Pócalja” Natura 2000 loess grassland (Central Hungary), in years 2018, 2019 and 2020. Th = therophytes, TH = hemitherophytes, H = hemicryptophytes, G = geophytes, Ch = chamaephytes, N = nanophanerophytes, M = phanerophytes.
Figure 1. Life-form spectra of species in the four plots (P1–P4) of “Pócalja” Natura 2000 loess grassland (Central Hungary), in years 2018, 2019 and 2020. Th = therophytes, TH = hemitherophytes, H = hemicryptophytes, G = geophytes, Ch = chamaephytes, N = nanophanerophytes, M = phanerophytes.
Plants 11 00763 g001
Plants 11 00763 g002 550
Figure 2. Life-form spectra based on species’ cumulative percentage cover values in the four plots (P1–P4) of “Pócalja” Natura 2000 loess grassland (Central Hungary), in years 2018, 2019 and 2020. Th = therophytes, TH = hemitherophytes, H = hemicryptophytes, G = geophytes, Ch = chamaephytes, N = nanophanerophytes, M = phanerophytes.
Figure 2. Life-form spectra based on species’ cumulative percentage cover values in the four plots (P1–P4) of “Pócalja” Natura 2000 loess grassland (Central Hungary), in years 2018, 2019 and 2020. Th = therophytes, TH = hemitherophytes, H = hemicryptophytes, G = geophytes, Ch = chamaephytes, N = nanophanerophytes, M = phanerophytes.
Plants 11 00763 g002
Plants 11 00763 g003 550
Figure 3. Share among distribution range types of species in the four plots (P1–P4) of “Pócalja” Natura 2000 loess grassland (Central Hungary), in years 2018, 2019 and 2020. COS = cosmopolitan, EUR = European, CON = continental, MED = Mediterranean, END = endemic.
Figure 3. Share among distribution range types of species in the four plots (P1–P4) of “Pócalja” Natura 2000 loess grassland (Central Hungary), in years 2018, 2019 and 2020. COS = cosmopolitan, EUR = European, CON = continental, MED = Mediterranean, END = endemic.
Plants 11 00763 g003
Plants 11 00763 g004 550
Figure 4. Share among distribution range types based on species’ cover values in the four plots (P1–P4) of “Pócalja” Natura 2000 loess grassland (Central Hungary), in years 2018, 2019 and 2020. COS = cosmopolitan, EUR = European, CON = continental, MED = Mediterranean, END = endemic.
Figure 4. Share among distribution range types based on species’ cover values in the four plots (P1–P4) of “Pócalja” Natura 2000 loess grassland (Central Hungary), in years 2018, 2019 and 2020. COS = cosmopolitan, EUR = European, CON = continental, MED = Mediterranean, END = endemic.
Plants 11 00763 g004
Plants 11 00763 g005 550
Figure 5. Distribution of species along seed weight categories in the four plots (P1–P4) of “Pócalja” Natura 2000 loess grassland (Central Hungary), in years 2018, 2019 and 2020.
Figure 5. Distribution of species along seed weight categories in the four plots (P1–P4) of “Pócalja” Natura 2000 loess grassland (Central Hungary), in years 2018, 2019 and 2020.
Plants 11 00763 g005
Plants 11 00763 g006 550
Figure 6. Species and vegetation turnover rates in four permanent plots (P1–P4) of the Natura 2000 loess grassland at “Pócalja”, Central Hungary.
Figure 6. Species and vegetation turnover rates in four permanent plots (P1–P4) of the Natura 2000 loess grassland at “Pócalja”, Central Hungary.
Plants 11 00763 g006
Plants 11 00763 g007 550
Figure 7. View of the high diversity steppe grassland on loess with Euphorbia pannonica and Chamaecytisus austriacus in the foreground on 8 July 2019. (Photo: T. Kalapos).
Figure 7. View of the high diversity steppe grassland on loess with Euphorbia pannonica and Chamaecytisus austriacus in the foreground on 8 July 2019. (Photo: T. Kalapos).
Plants 11 00763 g007
Plants 11 00763 g008 550
Figure 8. View of the studied steppe grassland on loess with Salvia austriaca in the foreground and S. pratensis in the upper right corner on 11 May 2020. (Photo: P. Csontos).
Figure 8. View of the studied steppe grassland on loess with Salvia austriaca in the foreground and S. pratensis in the upper right corner on 11 May 2020. (Photo: P. Csontos).
Plants 11 00763 g008
Table
Table 1. The Shannon–Wiener diversity of the four permanent plots (P1–P4) in the “Pócalja” Nature-2000 loess grassland (Central Hungary), during three consecutive years.
Table 1. The Shannon–Wiener diversity of the four permanent plots (P1–P4) in the “Pócalja” Nature-2000 loess grassland (Central Hungary), during three consecutive years.
201820192020
P13.04262.88412.7083
P22.70152.46052.6303
P32.87292.92512.8833
P43.18032.96493.0256
Table
Table 2. Results of statistical tests on species- and vegetation turnover rates according to Friedman’s nonparametric repeated measures ANOVA followed by Dunn’s multiple comparisons test. (* = indicates significant differences, ns = not significant).
Table 2. Results of statistical tests on species- and vegetation turnover rates according to Friedman’s nonparametric repeated measures ANOVA followed by Dunn’s multiple comparisons test. (* = indicates significant differences, ns = not significant).
Compared Turnover RatesRank Sum Differencep-ValueSignificance
species turnover
2018/19 vs. 2019/20−5.0p > 0.05ns
2018/19 vs. 2018/20−7.0p < 0.05*
2019/20 vs. 2018/20−2.0p > 0.05ns
vegetation turnover
2018/19 vs. 2019/20+2.0p > 0.05ns
2018/19 vs. 2018/20−5.0p > 0.05ns
2019/20 vs. 2018/20−7.0p < 0.05*
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Csontos, P.; Tamás, J.; Kovács, Z.; Schellenberger, J.; Penksza, K.; Szili-Kovács, T.; Kalapos, T. Vegetation Dynamics in a Loess Grassland: Plant Traits Indicate Stability Based on Species Presence, but Directional Change When Cover Is Considered. Plants 2022, 11, 763. https://doi.org/10.3390/plants11060763

AMA Style

Csontos P, Tamás J, Kovács Z, Schellenberger J, Penksza K, Szili-Kovács T, Kalapos T. Vegetation Dynamics in a Loess Grassland: Plant Traits Indicate Stability Based on Species Presence, but Directional Change When Cover Is Considered. Plants. 2022; 11(6):763. https://doi.org/10.3390/plants11060763

Chicago/Turabian Style

Csontos, Péter, Júlia Tamás, Zsófia Kovács, Judit Schellenberger, Károly Penksza, Tibor Szili-Kovács, and Tibor Kalapos. 2022. "Vegetation Dynamics in a Loess Grassland: Plant Traits Indicate Stability Based on Species Presence, but Directional Change When Cover Is Considered" Plants 11, no. 6: 763. https://doi.org/10.3390/plants11060763

APA Style

Csontos, P., Tamás, J., Kovács, Z., Schellenberger, J., Penksza, K., Szili-Kovács, T., & Kalapos, T. (2022). Vegetation Dynamics in a Loess Grassland: Plant Traits Indicate Stability Based on Species Presence, but Directional Change When Cover Is Considered. Plants, 11(6), 763. https://doi.org/10.3390/plants11060763

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop