Abstract
From a strictly statistical perspective, most of the commonly used statistical tests cannot be performed on vegetation data obtained using a non-random sampling design. Despite this, non-randomly sampled plots such as phytosociological relevés still make sense: because they may focus on objectives not appropriately addressed by random sampling, such as the study of rare plant communities or species; and because random sampling is often more time-demanding and expensive. Considering the huge body of phytosociological data available, an interesting question arises: if we compare randomly and non-randomly sampled data sets, to what extent do the results of our analyses differ with respect to various species and vegetation parameters?
We present an attempt to tackle this question by comparing two data sets collected in a 25 km2 area close to the city of Bremen, northwestern Germany: the first data set consisted of 30 subjectively (non-randomly) placed, homogeneous plots across different plant communities, each of which was laid out in a nested design including 9 sizes from 0.5 m2 to 1,000 m2. The second data set consisted of 30 (again nested) plots randomly selected and located with a GPS device; plots were rejected only if they for some reason were inaccessible. The data collection was the same for both data sets: presence-absence of all vascular plants was recorded for the different plot sizes, and soil samples were collected for the determination of the values of some important environmental variables. For the comparison of the two data sets, we used either the complete data sets or sub-sets of those plots located in woodlands.
The main results included the following: (1) Species abundance patterns: Random sampling resulted in a larger number of common and a smaller number of rare species than non-random sampling. (2) Species richness at different spatial scales: For the small plot sizes, the number of species in the non-randomly placed plots was higher than in the randomly placed plots, while the differences were less pronounced at larger spatial scales. As a consequence, also the parameters of species-area curves differed between the data sets, especially in the sub-set including woodland plots. (3) Vegetation differentiation: In random sampling, there was considerable redundancy, i.e., there were several plots with high floristic similarity. (4) Vegetation-environment relationships: The ordination scores of the non-randomly placed plots showed a larger number of significant correlations to soil parameters than the scores of randomly placed plots. The results suggest that conclusions drawn from the analysis of non-randomly placed plots such as phytosociological relevés may be biased, especially regarding estimates of species abundance and species richness patterns.
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References
Arrhenius O. (1921): Species and area.J. Ecol. 9: 95–99.
Berg C., Dengler J. &Abdank A. (eds.) (2001):Die Pflanzengesellschaften Mecklenburg-Vorpommerns und ihre Gefährdung. Tabellenband. Landesmat für Umwelt, Naturschutz und Geologie Mecklenburg-Vorpommern. Weissdorn-Verlag, Jena.
Berg C., Dengler J., Abdank A. &Isermann M. (eds.) (2004):Die Pflanzengesellschaften Mecklenburg-Vorpommerns und ihre Gefährdung. Textband. Landesamt für Umwelt, Naturschutz und Geologie Mecklenburg-Vorpommern. Weissdorn-Verlag, Jena.
Chytrý M., Tichý L. &Roleček J. (2003): Local and regional patterns of species richness in Central European vegetation types along the pH/calcium gradient.Folia Geobot. 38: 429–442.
Colwell R.K. &Coddington J.A. (1994): Estimating terrestrial biodiversity through extrapolation.Philos. Trans., Ser. B 345: 101–118.
Dupré C., Wessberg C. &Diekmann M. (2002): Species richness in deciduous forests: effects of species pools and environmental variables.J. Veg. Sci. 13: 505–516.
Gimaret-Carpentier C., Pélissier R., Pascal J.-P. &Houllier F. (1998): Sampling strategies for the assessment of tree species diversity.J. Veg. Sci. 9: 161–172.
Grabherr G., Reiter K. &Willner W. (2003): Towards objectivity in vegetation classification: the example of the Austrian forests.Pl. Ecol. 169: 21–34.
Greig-Smith P. (1964):Quantitative plant ecology. Ed. 2. Butterworth, London.
Hédl R. (2007): Vegetation diversity of beechwoods in a forested area: eligibility and properties of randomized versus subjective sampling.Folia Geobot. 27: 191–198.
Hobohm C. (2005): Die Erforschung der Artenvielfalt in Pflanzengesellschaften — eine Zwischenbilanz.Tuexenia 25: 7–28.
Kenkel N.C., Juhász-Nagy P. &Podani J. (1989): On sampling procedures in population and community ecology.Vegetatio 83: 195–207.
Kühne A. (2006):Untersuchungen zur Abschätzung der Phytodiversität auf Landschaftsebene. Unpubl. Diploma Thesis, Bremen.
Lájer K. (2007): Statistical tests as inappropriate tools for data analysis performed on non-random samples of plant communities.Folia Geobot. 27: 115–122.
Lepš J. &Šmilauer P. (2007): Subjectively sampled vegetation data: don’t throw out the baby with the bath water.Folia Geobot. 27: 169–178.
Magurran A. (2004):Measuring biological diversity. Blackwell Publishing, Oxford.
McCune B. &Mefford M.J. (1999):PC-ORD. Multivariate analysis of ecological data. Version 4. MjM Software Design, Gleneden Beach, Oregon, USA.
Mucina L., Grabherr G. &Ellmauer T. (1993):Die Pflanzengesellschaften Österreichs — Teil I: Anthropogene Vegetation. Fischer-Verlag, Jena.
Økland R.H. (1990): Vegetation ecology: theory, methods and applications with reference to Fennoscandia.Sommerfeltia, Suppl. 1: 1–233.
Økland R.H. (2007): Statistical inference in ecological field studies.Folia Geobot. 27: 123–140.
Rédei T., Botta-Dukát Z., Csiky J., Kun A. &Tóth T. (2003): On the possible role of local effects on the species richness of acidic and calcareous rock grasslands in northern Hungary.Folia Geobot. 38: 453–467.
Rosenzweig M.L. (1995):Species diversity in space and time. Cambridge University Press, Cambridge.
Schaminée J.H.J., Stortelder A.H.F. &Westhoff V. (1995):De Vegetatie von Nederland — Deel 1. Inleiding tot de plantensociologie — grondslagen, methoden en toepassingen (The vegetation of the Netherlands — Part. 1. Introduction to phytosociology — basic approach, methods and applications). Opulus Press, Uppsala.
Schuster B. &Diekmann M. (2003): Changes in species density along the soil pH gradient — evidence from German plant communities.Folia Geobot. 38: 367–379.
von Drachenfels O. (2004):Kartierschlüssel für Biotoptypen in Niedersachsen unter besonderer Berücksichtigung der nach § 28a und § 28b NNatG geschützten Biotope sowie der Lebensraumtypen von Anhang I der FFH-Richtlinie, Stand März 2004. Naturschutz Landschaftspfl. Niedersachsen A/4:1–240.
Wilson J.B. (2007): Priorities in statistics, the sensitive feet of elephants, and don’t transform data.Folia Geobot. 27: 161–167.
Wisskirchen R. &Haeupler H. (1998):Standardliste der Gefäß-und Blütenpflanzen Deutschlands. Ulmer Verlag, Stuttgart.
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Diekmann, M., Kühne, A. & Isermann, M. Randomvs non-random sampling: Effects on patterns of species abundance, species richness and vegetation-environment relationships. Folia Geobot 42, 179–190 (2007). https://doi.org/10.1007/BF02893884
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DOI: https://doi.org/10.1007/BF02893884