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Methods for assessing the effects of environmental parameters on biological communities in long-term ecological studies - A literature review

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  • Verniest, Fabien
  • Greulich, Sabine

Abstract

Many ecological processes that play important roles in ecosystems occur over long time periods and can therefore not always be properly studied with short-term studies. However, researchers have to face many challenges while setting up long-term ecological studies, including the choice of relevant data analysis methods and the design of the study (i.e. sampling frequency, number of sites, etc.). This literature review, based on 99 original studies, provides an overview of methodological choices used to analyse the effects of abiotic parameters on biological communities on a long-term scale. To this end, the main characteristics of study design were recorded (e.g. sampling frequency, duration, taxa, variables) and the different data analysis tools summarised and analysed. We found that long-term ecological studies focusing on the effects of environmental factors on biotic parameters mostly concerned aquatic habitats. Studies substantially varied in their design, although many of them had similar aims. Univariate methods, almost entirely performed by means of linear modelling and correlation tests, were used more often than multivariate methods. Finally, constrained and unconstrained ordination methods were used equally, and other data analysis tools were rare. Finally, we created a decision key to help researchers choose the appropriate analysis tools for their specific long-term study.

Suggested Citation

  • Verniest, Fabien & Greulich, Sabine, 2019. "Methods for assessing the effects of environmental parameters on biological communities in long-term ecological studies - A literature review," Ecological Modelling, Elsevier, vol. 414(C).
    • Handle: RePEc:eee:ecomod:v:414:y:2019:i:c:s0304380019302327
    DOI: 10.1016/j.ecolmodel.2019.108732
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    References listed on IDEAS

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    1. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    2. J. Kruskal, 1964. "Nonmetric multidimensional scaling: A numerical method," Psychometrika, Springer;The Psychometric Society, vol. 29(2), pages 115-129, June.
    3. Blanchet, F. Guillaume & Legendre, Pierre & Borcard, Daniel, 2008. "Modelling directional spatial processes in ecological data," Ecological Modelling, Elsevier, vol. 215(4), pages 325-336.
    4. J. Kruskal, 1964. "Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis," Psychometrika, Springer;The Psychometric Society, vol. 29(1), pages 1-27, March.
    5. David R. Larsen & Paul L. Speckman, 2004. "Multivariate Regression Trees for Analysis of Abundance Data," Biometrics, The International Biometric Society, vol. 60(2), pages 543-549, June.
    6. Michael D. Jennions & Anders Pape Møller, 2003. "A survey of the statistical power of research in behavioral ecology and animal behavior," Behavioral Ecology, International Society for Behavioral Ecology, vol. 14(3), pages 438-445, May.
    7. J. Andrew Royle, 2004. "N-Mixture Models for Estimating Population Size from Spatially Replicated Counts," Biometrics, The International Biometric Society, vol. 60(1), pages 108-115, March.
    8. Roger Shepard, 1962. "The analysis of proximities: Multidimensional scaling with an unknown distance function. I," Psychometrika, Springer;The Psychometric Society, vol. 27(2), pages 125-140, June.
    9. P. T. Davies & M. K‐S. Tso, 1982. "Procedures for Reduced‐Rank Regression," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 31(3), pages 244-255, November.
    10. Roger Shepard, 1962. "The analysis of proximities: Multidimensional scaling with an unknown distance function. II," Psychometrika, Springer;The Psychometric Society, vol. 27(3), pages 219-246, September.
    11. Ledyard Tucker, 1966. "Some mathematical notes on three-mode factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 31(3), pages 279-311, September.
    12. Penczak, Tadeusz, 2011. "Fish assemblages composition in a natural, then regulated, stream: A quantitative long-term study," Ecological Modelling, Elsevier, vol. 222(13), pages 2103-2118.
    Full references (including those not matched with items on IDEAS)

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