Abstract
Long term vegetation monitoring provides valuable information on spatio-temporal patterns in plant communities that could be analysed to detect spatial relationship changes among species and to interpret dynamic tendencies and assembly rules in non-equilibrium phytocoenoses. In studies of this kind, one should take into account recent ecological theories emphasizing the scale dependence of vegetation; in particular, fine-scale spatial patterns of vegetation are important constraints in the genesis and maintenance of diversity. The information theory models of Juhász-Nagy offer an appropriate tool for describing the relationship between diversity and multispecies spatial dependence in vegetation. Diversity (florula diversity) and spatial dependence (associatum) are calculated for a series of increasing plot sizes (spatial scaling). The plot sizes at which the two coenostate descriptors reach the maximum information represent the characteristic scales that should be considered as optimal plot sizes in monitoring data collection. Moreover, this methodology enables us to study non-equilibrium dynamics and assembly rules in a more effective way. Diversity and spatial dependence are related, but the power and direction of this relationship change according to environmental characteristics, vegetation type and successional context. The demonstrated correspondence between dominant pattern-generating mechanisms and the related trajectories in abstract coenostate spaces (florula diversity and associatum maximum values), obtained by exploratory simulation studies, can improve interpretation of dynamic state and vegetation tendencies and can support a better inference about the relative role of different background mechanisms. We present some results obtained using this methodology with field data from the forest of Białowieza National Park (Poland). In particular, we compared the herb layer spatial patterns of dynamically contiguous regeneration phases of the same phytocoenosis. Sampling was performed by recording the presence of plant species in 10 cm x 10cm contiguous microquadrats arranged in 150 m long circular transects. Field data were analysed with the same information theory methods as the ones applied to simulated data. Results show that assemblages of plant individuals are less diverse and more associated in primary than in regenerating stands, suggesting, in both situations, competitive dominance and disturbance as the main ecological mechanisms. Thus, the method was proven effective in distinguishing slightly different dynamical processes.
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References
Bartha, S., T. Czárán and J. Podani. 1998. Exploring plant community dynamics in abstract coenostate spaces. Abstracta Botanica 22: 49–66.
Bartha, S. and M. Kertész. 1998. The importance of neutral-models in detecting interspecific spatial associations from ‘trainsect’ data. Tiscia 31: 85–98.
Bobiec, A. 1994. The mosaic diversity of ground vegetation along the transect through the transition zone from the pure coniferous to the mixed coniferous site in the Białowieza Primeval Forest in the north-eastern Poland. Fragm. Flor. Geobot. 39: 605–617.
Campetella, G. and R. Canullo. 2001. Structure and spatial scale in woodland vegetation studies in permanet plots: a determinant feature of monitoring. ISAFA, Comunicazioni di Ricerca 2001/02: 101–111 (in Italian, with English abstract).
Campetella, G., R. Canullo and S. Bartha. 1999. Fine-scale spatial pattern analysis of the herb layer of woodland vegetation using information theory. Plant Biosystems 133: 277–288.
Czárán, T. 1998. Spatiotemporal Models of Population and Community Dynamics, Chapman and Hall, New York.
Dale, M.R.T. and M.W. Zbigniewicz. 1995. The evaluation of multi-species pattern. J.Veg. Sci. 6: 391–398.
Faliński, J.B. 1986. Vegetation Dynamics in Temperate Lowland Primeval Forest (Ecological Studies in Białowieza Forest), Geobotany 8. Junk, Dordrecht.
Faliński, J.B. 1988. Succession, regeneration and fluctuation in the Białowieza forest (NE Poland). Vegetatio 77: 115–128.
Faliñski, J.B. and W. Matuszkiewicz. 1963. La Grande Forêt de Białowieza. Der Urwald von Białowieza (2). Excursion internationale phytosociologique en Pologne N-E. Mat. Zakl. Fitosoc. Stos. UW 2: 31–60.
Faliński, J.B., R. Canullo and K. Bialy. 1988. Changes in herb layer, litter fall and soil properties under primary and secondary tree stands in a deciduous forest ecosystem. Phytocoenosis (N.S.) 1: 1–49.
Fotheringham, A.S. and D.W.S. Wong. 1991. The modifiable areal unit problem in statistical analysis. Environment and Planning A 23: 1025–1044.
Greig-Smith, P. 1964. Quantitative Plant Ecology, 2nd ed. Butterworths, London.
Greig-Smith, P. 1979. Pattern in vegetation. J. Ecol. 67: 755–779.
Haveman, R. and R. van der Wijngaart. 2003. Multi-scale vegetation monitoring for conservation practice on military ranges in the Netherlands. In: E. Feldmeyer-Christe (ed.), State of the Art in Vegetation Monitoring Approaches. International Symposium, March 24–26, 2003. Birmensdorf, Swiss Federal Research Institute WSL. p. 20.
Hogeweg, P. 2002. Computing an organism: on the interface between informatic and dynamic processes. BioSystems 64: 97–109.
Huston, M.A. and D.L. DeAngelis. 1994. Competition and coexistence: the effects of resource trasport and supply rates. Am. Nat. 144: 954–977.
Jelinski, D.E. and J.-G. Wu. 1996. The modifiable areal unit problem and implications for landscape ecology. Landscape Ecology 11: 129–140.
Juhász-Nagy, P. 1976. Spatial dependence of plant populations. Part I. A family of new models. Acta Bot. Acad. Sci. Hung. 22: 61–68.
Juhász-Nagy, P. 1984. Spatial dependence of plant populations. Part II. A family of new models. Acta Bot. Acad. Sci. Hung. 30: 363–402.
Juhász-Nagy, P. 1993. Notes on compositional diversity. Hydrobiologia 249:173–182.
Juhász-Nagy, P. and J. Podani. 1983. Information theory methods for the study of spatial processes in succession. Vegetatio 51: 129–140.
Kershaw, K.A. 1964. Quantitative and Dynamic Plant Ecology, E. Arnold, London.
Lande, R. 1996. Statistics and partitioning of species diversity, and similarity among multiple communities. Oikos 76: 5–13.
Lepš, J. 1990. Comparison on transect methods for the analysis of spatial pattern. In: F. Krahulec, A.D.Q. Agnew, S. Agnew and H.J. Willems (eds.), Spatial Processes in Plant Communities. Academia, Praha. pp. 71–82.
Magurran, A.E. 1988. Ecological Diversity and its Measurement, Princeton Univ. Press, Princeton.
Moreno-Casasola, P. and G. Vásquez. 1999. The relationship between vegetation dynamics and water table in tropical dune slacks. J. Veg. Sci. 10: 515–524.
Newbery, D.M. and J. Proctor. 1984. Ecological studies in four contrasting lowland rain forests in Gunung Mulu National Park, Sarawak. IV. Association between tree distribution and soil factors. J. Ecol. 72: 475–493.
Olszewski, J.L. 1986. The role of forest ecosystems in modifying local climate of the Białowieza Primeval Forest, as revealed by air temperature characteristics. Wydawnictwo Polskiej Akademii Nauk, Wroclaw (in Polish with English summary).
Openshaw, S. 1984. The Modifiable Areal Unit Problem, CATMOG 38. GeoBooks, Norwich, England.
Pélissier, R. and F. Goreaud. 2001. A practical approach to the study of spatial structure in simple cases of heterogeneous vegetation. J. Veg. Sci. 12: 99–108.
Peterson, C.J. and S.T.A. Pickett. 1990. Microsite and elevation influences on early forest regeneration after catastrophic wind-throw. J. Veg. Sci. 1: 657–662.
Pielou, E.C. 1975. Ecological Diversity, Wiley, New York.
Podani, J. 1984. Spatial processes in the analysis of vegetation: theory and review. Acta Bot. Hung. 30: 75–118.
Podani, J., T. Czárán and S. Bartha. 1993. Pattern, area and diversity: the importance of spatial scale in species assemblages. Abstracta Botanica 17:289–302.
Tilman, D. 1993. Species richness of experimental productivity gradients: how important is colonization limitation? Ecology 74: 2179–2191.
Tutin, T.G. (ed.) et al. 1993. Flora Europea. 2nd edition, Cambridge University Press, Cambridge
van der Maarel, E. 1996. Pattern and processin the plant community: fifty years after A.S. Watt. J. Veg. Sci. 7: 19–28.
Wagner, H.H. 2003. Spatial covariance in plant communities: integrating ordination, geostatistics, and variance testing. Ecology 84: 1045–1057.
Watkins, A.J. and J.B. Wilson. 1992. Fine scale community structure of lawns. J. Ecol. 80: 15–24.
Wilson, J.B. 1994. Who makes assembly rules? J. Veg. Sci. 5: 275–278.
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Campetella, G., Canullo, R. & Bartha, S. Coenostate descriptors and spatial dependence in vegetation — derived variables in monitoring forest dynamics and assembly rules. COMMUNITY ECOLOGY 5, 105–114 (2004). https://doi.org/10.1556/ComEc.5.2004.1.10
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DOI: https://doi.org/10.1556/ComEc.5.2004.1.10