A performance comparison of sampling methods in the assessment of species composition patterns and environment–vegetation relationships in species-rich grasslands

Grzegorz Swacha, Zoltán Botta-Dukát, Zygmunt Kącki, Daniel Pruchniewicz, Ludwik Żołnierz

Abstract


The influence that different sampling methods have on the results and the interpretation of vegetation analysis has been much debated, but little is yet known about how the spatial arrangement of samples affect patterns of species composition and environment–vegetation relationships within the same vegetation type. We compared three data sets of the same sample size obtained by three standard sampling methods: preferential, random, and systematic. These different sampling methods were applied to a study area comprising of 36 ha of intermittently wet Molinia meadows. We compared the performance of the three methods under two management categories: managed (extensively mown) and unmanaged (abandoned for 10 years). A total of 285 vegetation-plots were sampled, with 95 plots recorded per sampling method. In preferential sampling, we sampled only patches of vegetation with an abundance of indicator species of the habitat type, while random and systematic plots were positioned independently from the researcher by using GIS. The effect of each sampling method on the patterns of species composition and species–environment relationships was explored by redundancy analysis and the significance of effects was tested by the randomization test. Preferential sampling revealed different patterns of species composition than random and systematic sampling methods. Random and systematic sampling methods have resulted in broader vegetation variability than with preferential sampling method. Preferential sampling revealed different relationship between soil parameters and species composition in contrast to random and systematic sampling methods. Although we have not found significant differences in vegetation–environment relationships between random and systematic sampling methods, random sampling revealed a more robust correlation of species data to soil factors than preferential and systematic sampling methods. Intentional restriction of vegetation variation sampled preferentially may be detrimental to statistical inference in studies of species composition patterns and vegetation–environment relationships.

Keywords


preferential; random; systematic; soil properties; Molinion meadows

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References


Bourdeau PF. A test of random versus systematic ecological sampling. Ecology. 1953;34:499–512. https://doi.org/10.2307/1929722

Greig-Smith P. Quantitative plant ecology. Berkley, CA: University of California Press; 1983. https://doi.org/10.1126/science.144.3626.1562-b

Kenkel NC, Juhász-Nagy P, Podani J. On sampling procedures in population and community ecology. Vegetatio. 1989;83(1):195–207. https://doi.org/10.1007/BF00031692

Braun-Blanquet J. Pflanzensoziologie. Grundzüge der Vegetationskunde. Wien: Springer-Verlag; 1964. https://doi.org/10.1007/978-3-7091-8110-2

Ewald J. A critique for phytosociology. J Veg Sci. 2003;14(2):291–296. https://doi.org/10.1111/j.1654-1103.2003.tb02154.x

Dengler J, Chytrý M, Ewald J. Phytosociology. In: Jørgensen SE, Fath BD, editors. Encyclopedia of ecology. Vol. 4. Oxford: Elsevier; 2008. p. 2767–2779.

Holeksa J, Woźniak G. Biased vegetation patterns and detection of vegetation changes using phytosociological databases. A case study in the forests of the Babia Góra National Park (the West Carpathians, Poland). Phytocoenologia. 2005;35(1):1–18. https://doi.org/10.1127/0340-269X/2005/0035-0001

Roleček J, Chytrý M, Hájek M, Lvončík S, Tichý L. Sampling design in large-scale vegetation studies: do not sacrifice ecological thinking to statistical purism! Folia Geobot. 2007;42(2):199–208. https://doi.org/10.1007/BF02893886

Schaffers A. Soil, biomass, and management of semi-natural vegetation – part II. Factors controlling species diversity. Plant Ecol. 2002;158(2):247–268. https://doi.org/10.1023/A:1015545821845

Hájek M, Hájková P. Environmental determinants of variation in Czech Calthion wet meadows: a synthesis of phytosociological data. Phytocoenologia. 2004;34(1):33–54. https://doi.org/10.1127/0340-269X/2004/0034-0033

Zelnik I, Čarni A. Wet meadows of the alliance Molinion and their environmental gradients in Slovenia. Biologia. 2008;63(2):187–196. https://doi.org/10.2478/s11756-008-0042-y

Zelnik I, Čarni A. Plant species diversity and composition of wet grasslands in relation to environmental factors. Biodivers Conserv. 2013;22(10):2179–2192. https://doi.org/10.1007/s10531-013-0448-x

Chiarucci A. To sample or not to sample? That is the question … for the vegetation scientist. Folia Geobot. 2007;42(2):209–216. https://doi.org/10.1007/BF02893887

Rédei T, Botta-Dukát Z, Csiky J, Kun A, Tóth T. On the possible role of local effects on the species richness of acidic and calcareous rock grasslands in northern Hungary. Folia Geobot. 2003;38(4):453–467. https://doi.org/10.1007/BF02803252

Cachovanová L, Hájek M, Fajmonová Z, Marrs R. Species richness, community specialization and soil–vegetation relationships of managed grasslands in a geologically heterogeneous landscape. Folia Geobot. 2012;47(4):349–371. https://doi.org/10.1007/s12224-012-9131-3

Merunková K, Chytrý M. Environmental control of species richness and composition in upland grasslands of the southern Czech Republic. Plant Ecol. 2012;213(4):591–602. https://doi.org/10.1007/s11258-012-0024-6

Turtureanu PD, Palpurina S, Becker T, Dolnik C, Ruprecht E, Sutcliffe LME, et al. Scale- and taxon-dependent biodiversity patterns of dry grassland vegetation in Transylvania. Agric Ecosyst Environ. 2014;182:15–24. http://doi.org/10.1016/j.agee.2013.10.028

Palpurina S, Chytrý M, Tzonev R, Danihelka J, Axmanová I, Merunková K, et al. Patterns of fine-scale plant species richness in dry grasslands across the eastern Balkan Peninsula. Acta Oecol. 2015;63:36–46. http://doi.org/10.1016/j.actao.2015.02.001

Chytrý M, Hennekens SM, Jiménez-Alfaro B, Knollová I, Dengler J, Jansen F, et al. European Vegetation Archive (EVA): an integrated database of European vegetation plots. Appl Veg Sci. 2016;19(1):173–180. https://doi.org/10.1111/avsc.12191

Chytrý M. Phytosociological data give biased estimates of species richness. J Veg Sci. 2001;12(3):439–444. https://doi.org/10.1111/j.1654-1103.2001.tb00190.x

Diekmann M, Kühne A, Isermann M. Random vs non-random sampling: effects on patterns of species abundance, species richness and vegetation–environment relationships. Folia Geobot. 2007;42(2):179–190. https://doi.org/10.1007/BF02893884

Michalcová D, Lvončík S, Chytrý M, Hájek O. Bias in vegetation databases? A comparison of stratified-random and preferential sampling. J Veg Sci. 2011;22(2):281–291. https://doi.org/10.1111/j.1654-1103.2010.01249.x

Mörsdorf MA, Ravolainen VT, Støvern LE, Yoccoz NG, Jónsdóttir IS, Bråthen KA. Definition of sampling units begets conclusions in ecology: the case of habitats for plant communities. PeerJ. 2015;3:e815. https://doi.org/10.7717/peerj.815

Lájer K. Statistical tests as inappropriate tools for data analysis performed on non-random samples of plant communities. Folia Geobot. 2007;42(2):115–122. https://doi.org/10.1007/BF02893878

Botta-Dukát Z, Kovács-Láng E, Rédei T, Kertész M, Garadnai J. Statistical and biological consequences of preferential sampling in phytosociology: theoretical considerations and a case study. Folia Geobot. 2007;42(2):141–152. https://doi.org/10.1007/BF02893880

Lepš J, Šmilauer P. Subjectively sampled vegetation data: don’t throw out the baby with the bath water. Folia Geobot. 2007;42(2):169–178. https://doi.org/10.1007/BF02893883

Økland RH. Wise use of statistical tools in ecological field studies. Folia Geobot. 2007;42(2):130–140. https://doi.org/10.1007/BF02893879

Rudmann-Maurer K, Weyand A, Fischer M, Stöcklin J. The role of land use and natural determinants for grassland vegetation composition in the Swiss Alps. Basic Appl Ecol. 2008;9(5):494–503. http://doi.org/10.1016/j.baae.2007.08.005

Wellstein C, Otte A, Waldhardt R. Impact of site and management on the diversity of Central European grasslands. Agric Ecosyst Environ. 2007;122(2):203–210. https://doi.org/10.1016/j.agee.2006.12.033

Pruchniewicz D, Żołnierz L. The influence of environmental factors and management methods on the vegetation of mesic grasslands in a central European mountain range. Flora. 2014;209(12):687–692. http://doi.org/10.1016/j.flora.2014.09.001

Virtanen R, Oksanen J, Oksanen L, Razzhivin VY. Broad-scale vegetation–environment relationships in Eurasian high-latitude areas. J Veg Sci. 2006;17(4):519–528. https://doi.org/10.1111/j.1654-1103.2006.tb02473.x

Hettenbergerova E, Hájek M, Zelený D, Jiroušková J, Mikulášková E. Changes in species richness and species composition of vascular plants and bryophytes along a moisture gradient. Preslia. 2013;85(3):369–388.

Cochran WG. Sampling techniques. New York, NY: Wiley; 1977.

Bhatta KP, Chaudhary RP, Vetaas OR. A comparison of systematic versus stratified-random sampling design for gradient analyses: a case study in subalpine Himalaya, Nepal. Phytocoenologia. 2012;42(3–4):191–202. https://doi.org/10.1127/0340-269X/2012/0042-0519

Goedickemeier I, Wildi O, Kienast F. Sampling for vegetation survey: some properties of a GIS-based stratification compared to other statistical sampling methods. Coenoses. 1997;12(1):43–50.

Hédl R. Is sampling subjectivity a distorting factor in surveys for vegetation diversity? Folia Geobot. 2007;42(2):191–198. https://doi.org/10.1007/BF02893885

Hu X, Wu Z, Wu C, Ye L, Lan C, Tang K, et al. Effects of road network on diversiform forest cover changes in the highest coverage region in China: an analysis of sampling strategies. Sci Total Environ. 2016;565:28–39. https://doi.org/10.1016/j.scitotenv.2016.04.009

Mohler CL. Effect of sampling pattern on estimation of species distributions along gradients. Vegetatio. 1983;54(2):97–102. https://doi.org/10.1007/BF00035144

Podani J. Analysis of mapped and simulated vegetation patterns by means of computerized sampling techniques. Acta Bot Hung. 1984;30(3):419–441.

Goslee SC. Behaviour of vegetation sampling methods in the presence of spatial autocorrelation. Plant Ecol. 2006;187(2):203–212. https://doi.org/10.1007/s11258-005-3495-x

Lengyel S, Déri E, Magura T. Species richness responses to structural or compositional habitat diversity between and within grassland patches: a multi-taxon approach. PLoS One. 2016;11(2):e0149662. https://doi.org/10.1371/journal.pone.0149662

Pawlak W. Atlas of Lower and Opole Silesia. Wrocław: University of Wrocław; 2008.

Sykes JM, Horrill AD, Mountford MD. Use of visual cover assessments as quantitative estimators of some British woodland taxa. J Ecol. 1983;71(2):437–450. https://doi.org/10.2307/2259726

Kennedy KA, Addison PA. Some consideration for the use of visual estimates of plant cover in biomonitoring. J Ecol. 1987;75(1):151–157. https://doi.org/10.2307/2260541

Westhoff V, van der Maarel E. The Braun-Blanquet approach. In: Whittaker RH, editor. Classification of plant communities. The Hague: W. Junk; 1978. p. 289–399. https://doi.org/10.1007/978-94-009-9183-5_9

Kącki Z. Comprehensive syntaxonomy of Molinion meadows in southwestern Poland. Acta Botaniczne Silesiaca, Monografie. 2007;2:1–134.

Matuszkiewicz W. Przewodnik do oznaczania zbiorowisk roślinnych Polski. Warszawa: Wydawnictwo Naukowe PWN; 2001.

Allen SE, editor. Chemical analysis of ecological materials. Oxford: Blackwell Scientific Publications; 1989.

Radojević M, Bashkin VN. Practical environmental analysis. 2nd ed. Cambridge: Royal Society of Chemistry; 2006. https://doi.org/10.1039/9781847552662

Swacha G, Kącki Z, Załuski T. Classification of Molinia meadows in Poland using a hierarchical expert system. Phytocoenologia. 2016;46(1):33–47. https://doi.org/10.1127/phyto/2016/0094

Kočí M, Chytrý M, Tichý L. Formalized reproduction of an expert‐based phytosociological classification: a case study of subalpine tall‐forb vegetation. J Veg Sci. 2003;14(4):601–610. https://doi.org/10.1111/j.1654-1103.2003.tb02187.x

Janišová M, Dúbravková D. Formalized classification of rocky Pannonian grasslands and dealpine Sesleria-dominated grasslands in Slovakia using a hierarchical expert system. Phytocoenologia. 2010;40(4):267–291. https://doi.org/10.1127/0340-269X/2010/0040-0444

Anderson MJ, Ellingsen KE, McArdle BH. Multivariate dispersion as a measure of beta diversity. Ecol Lett. 2006;9(6):683–693. https://doi.org/10.1111/j.1461-0248.2006.00926.x

Whittaker RH. Vegetation of the Siskiyou Mountains, Oregon and California. Ecol Monogr. 1960;30(3):279–338. https://doi.org/10.2307/1943563

Legendre P, Gallagher ED. Ecologically meaningful transformations for ordination of species data. Oecologia. 2001;129(2):271–280. https://doi.org/10.1007/s004420100716

ter Braak CJF, Šmilauer P. Canoco reference manual and CanoDraw for Windows user’s guide: software for canonical community ordination (version 4.5). Ithaca, NY: Microcomputer Power; 2002.

Legendre P, Legendre L. Numerical ecology. Amsterdam: Elsevier; 1998.

Oksanen J, Blanchet FG, Kindt R, Legendre P, Minchin PR, O’Hara RB, et al. Package “vegan”: Community Ecology Package. R package version 2.0-10 [Internet]. 2013 [cited 2017 Nov 20]. Available from: https://cran.r-project.org/web/packages/vegan/vegan.pdf

Hothorn T, Hornik K, van de Wiel MA, Zeileis A. Coin: a computational framework for conditional inference [Internet]. 2013 [cited 2017 Nov 20]. Available from: https://cran.r-project.org/web/packages/coin/vignettes/coin.pdf

ter Braak CJF, Šmilauer P. Canoco reference manual and user’s guide: software for ordination (version 5.0). Ithaca, NY: Microcomputer Power; 2012.

Mirek Z, Piękoś-Mirkowa H, Zając A, Zając M, editors. Flowering plants and pteridophytes of Poland – a checklist. Cracow: W. Szafer Institute of Botany, Polish Academy of Sciences; 2002.

Hanski I. Dynamics of regional distribution: the core and satellite species hypothesis. Oikos. 1982;38(2):210–221. https://doi.org/10.2307/3544021

Shmida A, Ellner S. Coexistence of plant species with similar niches. Plant Ecol. 1984;58(1):29–55. https://doi.org/10.1007/BF00044894

Økland RH. Vegetation ecology: theory, methods and applications with reference to Fennoscandia. Oslo: Botanical Garden and Museum; 1990. (Sommerfeltia, Supplement; vol 1).

Smartt PFM, Grainger EA. Sampling for vegetation survey: some aspects of the behaviour of unrestricted, restricted, and stratified techniques. J Biogeogr. 1974;1(3):193–206. https://doi.org/10.2307/3037969

Lepš J. Scale- and time-dependent effects of fertilization, mowing and dominant removal on a grassland community during a 15-year experiment. J Appl Ecol. 2014;51(4):978–987. https://doi.org/10.1111/1365-2664.12255

Pavlů L, Pavlů V, Gaisler J, Hejcman M, Mikulka J. Effect of long-term cutting versus abandonment on the vegetation of a mountain hay meadow (Polygono-Trisetion) in Central Europe. Flora. 2011;206(12):1020–1029. http://doi.org/10.1016/j.flora.2011.07.008

Házi J, Bartha S, Szentes S, Wichmann B, Penksza K. Seminatural grassland management by mowing of Calamagrostis epigejos in Hungary. Plant Biosyst. 2011;145(3):699–707. https://doi.org/10.1080/11263504.2011.601339

Rebele F, Lehmann C. Biological flora of Central Europe: Calamagrostis epigejos (L.) Roth. Flora. 2001;196(5):325–344. https://doi.org/10.1016/S0367-2530(17)30069-5

Szymura M, Szymura TH. Soil preferences and morphological diversity of goldenrods (Solidago L.) from south-western Poland. Acta Soc Bot Pol. 2013;82(2):107–115. https://doi.org/10.5586/asbp.2013.005

Weber E, Jakobs G. Biological flora of Central Europe: Solidago gigantea Aiton. Flora. 2005;200(2):109–118. http://doi.org/10.1016/j.flora.2004.09.001

Kącki Z, Michalska-Hejduk D. Assessment of biodiversity in Molinia meadows in Kampinoski National Park based on biocenotic indicators. Pol J Environ Stud. 2010;19(2):351–362.

Sardans J, Peñuelas J. Potassium: a neglected nutrient in global change. Global Ecology and Biogeography. 2015;24(3):261–275. https://doi.org/10.1111/geb.12259

Smart SM, Clarke RT, van de Poll HM, Robertson EJ, Shield ER, Bunce RGH, et al. National-scale vegetation change across Britain: an analysis of sample-based surveillance data from the countryside surveys of 1990 and 1998. J Environ Manage. 2003;67(3):239–254. https://doi.org/10.1016/S0301-4797(02)00177-9

Grabherr G, Reiter K, Willner W. Towards objectivity in vegetation classification: the example of the Austrian forests. Plant Ecol. 2003;169(1):21–34. https://doi.org/10.1023/A:1026280428467

Ruskule A, Nikodemus O, Kasparinskis R, Prižavoite D, Bojāre D, Brūmelis G. Soil–vegetation interactions in abandoned farmland within the temperate region of Europe. New Forests. 2016;47(4):587–605. https://doi.org/10.1007/s11056-016-9532-x

Vandvik V, Birks HJB. Partitioning floristic variance in Norwegian upland grasslands into within-site and between-site components: are the patterns determined by environment or by land-use? Plant Ecol. 2002;162(2):233–245. https://doi.org/10.1023/A:1020322205469

Sebastiá MT. Role of topography and soils in grassland structuring at the landscape and community scales. Basic Appl Ecol. 2004;5(4):331–346. https://doi.org/10.1016/j.baae.2003.10.001