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Invasive Plant Species in the Accompanying Vegetation of the Nitra River

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Invasive Plant Species in the Accompanying Vegetation of the Nitra River MENDELNET 2016 INVASIVE PLANT SPECIES IN THE ACCOMPANYING VEGETATION OF THE NITRA RIVER MICHAELA BENCOVA, JANA NOZDROVICKA, VERONIKA SELECKA, JOZEF TAZKY Department of Ecology and Environmental Sciences Constantine the Philosopher University in Nitra Tr. A. Hlinku 1, 949 01, Nitra SLOVAK REPUBLIC [email protected] Abstract: This paper focuses on the evaluation of the species composition of accompanying vegetation adjacent to water flow in the of the Upper Nitra region and species diversity among communities attacked by invasive species and non-invasive communities. The research was carried out in the vegetation period during the years 2015 and 2016 on the 10 km long section with 48 phytocenological relevés. The results indicate that there is a high concentration of researched species in the area, which progressively push out the original, natural vegetation. A total of 133 plant species were recorded 111 species in non-invasive vegetation and 104 species in invasive vegetation, 78 species were the same in both types of relevés. The species with the highest average coverage were the following invasive taxa: Helianthus tuberosus, Solidago canadensis and Amaranthus retroflexus. The non-invasive species were: Solanum nigrum, Urtica dioica, Rubus caesius and Humulus lupulus. KeyWords: invasive plant species, the Nitra river, the Slovak Republic INTRODUCTION Invasive plant species cause problems and have negative impact on flora and fauna almost all over the world. They are one of the reasons for the change in the abiotic environment, and they affect human health and national economies (Křivánek 2006). The term "negative impact" conceals the suppression of native species in competition for resources (Melgoza et al. 1990), reduction of habitats, increased groundwater extraction and its subsequent lack for other species. There are also other changes in the hydrological regime, increased sedimentation and a subsequent change of rhythm to the whole ecosystem, e.g. riparian vegetation (Zavaleta 2000). Each non-native species changes the composition of natural diversity in a certain way. On the one hand, the introduction of non-native species can increase the overall number of species occurring in a particular place – at least in the short term. On the other hand, in the long term it will lead to a reduction in species diversity (the number and abundance of species). Another possibility is that it also leads to the displacement of native species from habitats or regions and to a total change in natural ecosystems (Shine et al. 2000, Nentwig 2014). On a municipal level, the crowding out of native plant species is a phenomenon resulting from the dominance of invasive plants, which prevail in contaminated locations. In general, the plant invasion causes homogenization of flora in which the originally different phytogeographic units become similar due to the massive invasion (Hejda and Pyšek 2006). In his study of invasive species of the Czech flora, Pyšek et al. (1998) indicates that after settlements, the habitats connected with still standing and running water are places with the highest representation of non-native species. Some authors consider habitats along rivers are more prone to invasion. It is justified by the disturbance occurring in these areas. Because of this disturbance, these communities are receiving higher quantities of available resources (Stohlgren et al. 1998). 369 | Page MENDELNET 2016 The aim of this paper is to assess the impact of invasive plant species on the composition and nature of the infested habitats, and to ascertain what the subsequent changes are to the composition of the community. MATERIAL AND METHODS Study area The Nitra river rises on the southern slopes of the Malá Fatra Mts. After passing the Podunajská pahorkatina Upland it flows into the Váh river in the area of the Podunajská rovina Plain to the north of the city of Komárno. The flow length is 196.7 km and the total area of the river basin is about 5 144 km2 (Mazúr and Lukniš 1980, Porubský 1991).The area belongs to the basin of the Nitra river with a left tributary of the Handlovka river and to the upland-lowland regions with a rain-snow runoff regime (Šimo and Zaťko 2002). The defined part of the river is 10 river kilometres in length, and passes through cadastral territory of Bojnice town and the villages Opatovce nad Nitrou, Diviacka Nová Ves and Zemianske Kostoľany (Figure 1). Figure 1 Location of the study area in the Slovak Republic (Bencová 2016) Methodology of work The area of interest chosen was a 10 km long section from the confluence of the Nitra river with the Handlovka river (48° 44' 47.14" N, 18° 33' 32.70" E), up to the trigger point of the Zemianske Kostoľany village cadastre (48° 40' 42.27" N, 18° 30' 56.28" E). In this area a part of the river had transferred to a new river bed due to lignite mining. Also, settlements and a large number of cultivated areas occur in the area, where disturbance provides appropriate conditions for the occurrence of invasive species. During the years 2015 and 2016, 24 pairs of phytocenological relevés were recorded on an area of 4 x 4 metres. Each pair had one relevé per locality with a minimum of 60% coverage of invasive species and in the nearby non-invasive vegetation. Non-invasive areas were selected to represent the same habitat conditions as the habitat conditions of invasive areas (Hejda and Pyšek 2006). Individual invasive plant species have also appeared in the relevés of non-invasive areas because it was difficult to find areas with the total absence of their occurrence. The areas of comparison were selected on the basis of the following criteria: (a) locations are strongly attacked with invasive species, while populations are homogeneous (b) non-invasive cover is linked as far as possible on the attacked localities in order to maintain the same habitat conditions of the environment (altitude, orientation, ... etc.). The presence of the species was evaluated on the basis of the Braun-Blanquet scale coverage (van der Maarel 2005): 370 | Page MENDELNET 2016 r – rare species, + – occasional species, coverage is negligible, coverage ˂ 1%, 1 – coverage from 1 up to 5%, 2 – coverage from 5 up to 25%, 3 – coverage from 25 up to 50%, 4 – coverage from 50 up to 75%, 5 – coverage more than 75%. Invasive taxa were selected and mapped according to Gojdičová et al. (2002): category 1 – invasive taxa and category 2 – potential (regional) invasive taxa. Invasive relevés were realized in the vegetation of the following species: Helianthus tuberosus, Solidago canadensis, Impatiens parviflora, Tanacetum vulgare, Fallopia japonica, Fallopia x bohemica and Robinia pseudoacacia. The key for determination of plants was used for verifying the taxa of vascular plants (Dostál and Červenka 1991, 1992). The nomenclature of taxa has been unified according to the work of Marhold and Hindák (1998). The relevés were processed in Excel and subsequently in JUICE 7.0 (Tichý 2002), with which we calculated the average coverage of species and Shannon diversity index H´. Subsequently we calculated the evenness index by using the formula: Hʹ/In S, where S represents the number of species (Hejda and Pyšek 2006). The obtained data was processed in the CANOCO 4.0 program (Ter Braak and Šmilauer 2002), where DCCA (Detrended Canonical Correspondence Analysis) and RDA (Redundancy Analysis) analyses were carried out. A total number of 499 permutations were calculated in the Monte-Carlo test. Visualization was carried out using the CanoDraw program. The relation between invasive and non-invasive relevés was tested using the STATISTICA program (StatSoft Inc. 2007). RESULT AND DISCUSSION In the study area through the 48 phytocenological relevés we discovered the presence of 133 plant species. Data about species abundance and value indexes was processed by DCCA analysis. On the basis of DCCA analysis, we found that the length of gradient was 2.534 therefore in the next step we used RDA analysis (Redundancy Analysis). The resulting values were visualized through CanoDraw (see Figure 2). The diagram shows only species with more than 10% variability in the data. Figure 2 RDA ordination diagram expressing relation between data and environmental variables Legend: Agri eup – Agrimonia eupatoria, Achil mil – Achillea millefolium, Cent jac – Centaurea jacea, Cich int – Cichorium intybus, Clem vit – Clematis vitalba, Euph cyp – Euphorbia cyparissias, Gali apa – Galium aparine, Heli tub – Helianthus tuberosus, Lotu cor – Lotus corniculatus, Odon vul – Odontites vulgaris, Past sat – Pastinaca sativa, Phra aus – Phragmites australis, Plan lan – Plantago lanceolata, Poa pra – Poa pratensis, Poly avi – Polygonum aviculare, Rubu cae – Rubus caesius, Sali alb – Salix alba, Samb ebu – Sambucus ebulus, Tara sec – Taraxacum sect. Ruderalia, Trif rep – Trifolium repens, Urti dio – Urtica dioica. 371 | Page MENDELNET 2016 For better differentiation, invasive relevés are represented by a blue triangle and non-invasive relevés are represented by a red triangle. The diagram shows the dependence between species, relevés and environmental variables. Relevés realized in areas of invasive vegetation were displayed in the opposite direction to the growing diversity of the relevés, while Helianthus tuberosus, Sambucus ebulus and Rubus caesius had the largest variability. The relevés located in the negative part of the diagram showed the greatest diversity and species richness. Ruderal and field species prevailed here as Trifolium repens, Plantago lanceolata and Clematis vitalba. We used the Monte-Carlo permutation test for evaluating environmental factors. We found following values of Shannon-Wiener Index: P-value = 0.002, F-ratio = 2.29; evenness Index: P-value = 0.004, F-ratio = 1.71. This means that both variables have a significant impact on the variability of displayed data, while both of the factors according to RDA analysis explain 8% of the overall variability. In the invasive relevés, the average occurrence of species was 14.41 species per relevé and in non- invasive it was 16.45.
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