Contributions of spatial point process modelling to biodiversity theory

Janine Illian; David Burslem

Journal de la société française de statistique (2007)

  • Volume: 148, Issue: 1, page 9-29
  • ISSN: 1962-5197

Abstract

top
Recent decades have seen an unprecedented decline in biodiversity that has led to a growing concern about the consequences of biodiversity loss for the functioning of ecosystems. Key research in plant community ecology seeks to reveal the mechanisms that allow a large number of species to coexist and sustain biodiversity. Processes in plant communities are predominantly local and interactions take place in a spatial context. They thus need to be modelled from the individual plants’ perspective. Several ecological theories of plant species coexistence have been proposed with niche theory and neutral theory being the most prominent. They differ mainly in the extent to which functional differences between species are considered necessary for preventing competitive exclusion. This results in different predictions about interactions among the plants and between the plants and the environment. Extensive spatially explicit data sets of plant communities have become available. This paper outlines how the theories’ predictions may be assessed using spatial point process modelling and how this approach may be suitably applied to these data sets to contribute to the discussion.

How to cite

top

Illian, Janine, and Burslem, David. "Contributions of spatial point process modelling to biodiversity theory." Journal de la société française de statistique 148.1 (2007): 9-29. <http://eudml.org/doc/93459>.

@article{Illian2007,
abstract = {Recent decades have seen an unprecedented decline in biodiversity that has led to a growing concern about the consequences of biodiversity loss for the functioning of ecosystems. Key research in plant community ecology seeks to reveal the mechanisms that allow a large number of species to coexist and sustain biodiversity. Processes in plant communities are predominantly local and interactions take place in a spatial context. They thus need to be modelled from the individual plants’ perspective. Several ecological theories of plant species coexistence have been proposed with niche theory and neutral theory being the most prominent. They differ mainly in the extent to which functional differences between species are considered necessary for preventing competitive exclusion. This results in different predictions about interactions among the plants and between the plants and the environment. Extensive spatially explicit data sets of plant communities have become available. This paper outlines how the theories’ predictions may be assessed using spatial point process modelling and how this approach may be suitably applied to these data sets to contribute to the discussion.},
author = {Illian, Janine, Burslem, David},
journal = {Journal de la société française de statistique},
keywords = {spatial point processes; multivariate spatial point patterns; biodiversity; plant communities; tropical rainforest},
language = {eng},
number = {1},
pages = {9-29},
publisher = {Société française de statistique},
title = {Contributions of spatial point process modelling to biodiversity theory},
url = {http://eudml.org/doc/93459},
volume = {148},
year = {2007},
}

TY - JOUR
AU - Illian, Janine
AU - Burslem, David
TI - Contributions of spatial point process modelling to biodiversity theory
JO - Journal de la société française de statistique
PY - 2007
PB - Société française de statistique
VL - 148
IS - 1
SP - 9
EP - 29
AB - Recent decades have seen an unprecedented decline in biodiversity that has led to a growing concern about the consequences of biodiversity loss for the functioning of ecosystems. Key research in plant community ecology seeks to reveal the mechanisms that allow a large number of species to coexist and sustain biodiversity. Processes in plant communities are predominantly local and interactions take place in a spatial context. They thus need to be modelled from the individual plants’ perspective. Several ecological theories of plant species coexistence have been proposed with niche theory and neutral theory being the most prominent. They differ mainly in the extent to which functional differences between species are considered necessary for preventing competitive exclusion. This results in different predictions about interactions among the plants and between the plants and the environment. Extensive spatially explicit data sets of plant communities have become available. This paper outlines how the theories’ predictions may be assessed using spatial point process modelling and how this approach may be suitably applied to these data sets to contribute to the discussion.
LA - eng
KW - spatial point processes; multivariate spatial point patterns; biodiversity; plant communities; tropical rainforest
UR - http://eudml.org/doc/93459
ER -

References

top
  1. [1] Adler R. (1981). The Geometry of Random Fields. Wiley, New York. Zbl0478.60059MR611857
  2. [2] Armstrong P. (1991). Species patterning in the heath vegetation of the Northern Sandplain. Honours thesis, University of Western Australia. 
  3. [3] Baddeley A., J. Møller and R. Waagepetersen (2000). Non- and semiparametric estimation of interaction in inhomogenous point patterns. Statistica Neerlandica 54, 329-350. Zbl1018.62027MR1804002
  4. [4] Bell G. (2001). Neutral macroecology. Science 293, 2413-2418. 
  5. [5] Cardinale B. J., A. Ives and P. Inchausti (2004). Effects of species diversity on the primary productivity of ecosystems: extending our spatial and temporal scales of inference. Oikos 104, 437-450. 
  6. [6] Chave J. (2004). Neutral theory and community ecology. Ecology Letters 7, 241-253. 
  7. [7] Chesson P. L. (2000). Mechanisms of maintenance of species diversity. Annual Review of Ecology and Systematics 31, 343-366. 
  8. [8] Condit R., P. S. Ashton, P. Baker, S. Bunyavejchewin, S. Gunatilleke, N. Gunatilleke, S. Hubbell, R. Foster, A. Itoh, J. LaFrankie, H. Lee, E. Losos, N. Manokaran, R. Sukumar, and T. Yamakura (2000). Spatial patterns in the distribution of tropical tree species. Science 288, 1414-1418. 
  9. [9] Condit, R., N. Pitman, E. G. Leigh Jr., J. Chave, J. Terborgh, R. B. Foster, P. Nunez, S. Aguilar, R. Valencia, G. Villa, H. C. Müller-Landau, E. Losos, and S. P. Hubbell (2002). Beta diversity in tropical forest trees. Science 295, 666-669. 
  10. [10] Connell J. (1971). On the role of natural enemies in preventing competitive exclusion in some marine animals and in rainforest trees. In P. den Boer and G. Gradwell (Eds.), Dynamics of Populations, pp. 298-313. Centre for Agricultural Publishing and Documentation, Wageningen, The Netherlands. 
  11. [11] Coomes D. A., M. Rees and L. Turnbull (1999). Identifying aggregation and association in fully mapped spatial data. Ecology 80, 554-565. 
  12. [12] Cox D. R. (1955). Some statistical models related with series of events. Journal of the Royal Statistical Society Series B 17, 883-904. MR92301
  13. [13] Crawley M. (1997). The structure of plant communities. In M. Crawley (Ed.), Plant Ecology, pp. 475-531. Blackwell Publishing, Oxford. 
  14. [14] Daley D. J. and D. Vere-Jones (1988). An Introduction to the theory of point patterns. Springer-Verlag, New York. Zbl0657.60069MR950166
  15. [15] De Mazancourt C. (2001). Consequences of community drift. Science 293, 1772. 
  16. [16] DeAngelis D. L. and L. J. Gross (1992). Individual based Models and Approaches in Ecology: Populations, Communities and Ecosystems. Chapman & Hall, London. 
  17. [17] Dieckmann U., R. Law and J. Metz (2000). The Geometry of Ecological Interactions – Simplifying spatial complexity. Cambridge University Press, Cambridge. Zbl1170.92339
  18. [18] Diggle P. (1983). Statistical Analysis of Spatial Point Patterns. Academic Press, London. Zbl0559.62088MR743593
  19. [19] Diggle P. (2003). Statistical Analysis of Spatial Point Patterns, 2nd ed. Hodder Arnold, London. Zbl1021.62076
  20. [20] Diggle P. J., V. Gómez-Rubio, P. E. Brown, and A. G. Chetwynd (2006). Second-order analysis of inhomogeneous spatial point processes using case-control data. Biometrics. Zbl1134.62081
  21. [21] Dixon K. (2005). Personal communication. 
  22. [22] Duivenvoorden J. F., J. C. Svenning and S. J. Wright (2002). Beta diversity in tropical forests. Science 295, 636-637. 
  23. [23] Durrett R. and S. Levin (1998). Spatial aspects of interspecific competition. Theoretical Population Biology 53, 30-43. Zbl0908.92031
  24. [24] Elton C. (1927). Animal Ecology. Sidgwick and Jackson, London. 
  25. [25] Gaston K. J. and S. L. Crown (2005). Editorial: Neutrality and the niche. Functional Ecology 19, 1-6. 
  26. [26] Grinnell J. (1917). The niche relationships of the Californian thrasher. Auk 34, 427-433. 
  27. [27] Grubb P. J. (1977). The maintenance of species-richness in plant communities: the importance of the regeneration niche. Biological Reviews 52, 107-145. 
  28. [28] Harms K. E., R. Condit, S. P. Hubbell and R. B. Foster (2001). Habitat associations of trees and shrubs in a 50-ha neotropical forest plot. Journal of Ecology 89, 947-959. 
  29. [29] Hector A., B. Schmid, C. Beierkuhnlein, M. Caldeira, M. Diemer, P. Dimitrakopoulos, J. Finn, H. Freitas, P. Giller, J. Good, R. Harris, P. Hogberg, K. H. Danell, J. Joshi, A. Jumpponen, C. Krner, P. Leadley, M. Loreau, A. Minns, C. Mulder, G. O. G, S. Otway, J. Pereira, A. Prinz, D. Read, M. S. Lorenzen, E. Schulze, A. Siamantziouras, E. Spehn, A. Terry, A. Troumbis, F. Woodward, S. Yachi, and J. Lawton (1999). Plant diversity and productivity experiments in European grasslands. Science 286, 1123-1127. 
  30. [30] Hubbell S. (2001). The Unified Neutral Theory of Biodiversity and Biogeography. Monographs in Population Biology 32, Princeton University Press. 
  31. [31] Hubbell S. P. (1979). Tree dispersion, abundance and diversity in a tropical dry forest. Science 203, 1299-1309. 
  32. [32] Huston M., D. L. DeAngelis, and W. M. Post (1988). New computer model unify ecologcal theory. BioScience 38, 682-691. 
  33. [33] Hutchinson G. E. (1957). Concluding remarks. Cold Spring Habor Symposium on Quantitative Biology 22, 415-457. 
  34. [34] Hutchinson G. E. (1959). Homage to santa rosalia, or why are there so many kinds of animals? American Naturalist 93, 145-159. 
  35. [35] Illian J. B. (2006). Spatial point process modelling of a biodiverse plant community. PhD thesis, University of Abertay Dundee. 
  36. [36] Illian J. B., E. Benson, J. Crawford, and H. J. Staines (2004). Multivariate methods for spatial point processes – a simulation study. In A. Baddeley, P. Gregori, J. Mateu, R. Stoica, and D. Stoyan (Eds.), Spatial point process modelling and its applications, pp. 125-130. Castelló de la Plana: Publicacions de la Universitat Jaume I. 
  37. [37] Illian J. B., E. Benson, J. Crawford, and H. Staines (2006). Principal component analysis for spatial point patterns. In A. Baddeley, P. Gregori, J. Mateu, R. Stoica, and D. Stoyan (Eds.), Case studies in spatial point process modelling. Springer, New York. Zbl05243458MR2232127
  38. [38] Illian J. B., J. Møller, and R. P. Waagepetersen (2007). Spatial point process models for a complex plant community. To appear in Journal of Ecological and Environmental Statistics. MR2396935
  39. [39] Janzen D. H. (1970). Herbivores and the number of tree species in tropical forests. American Naturalist 104, 501-528. 
  40. [40] Judson O. (1994). The rise of the individual-based model in ecology. TREE 9, 9-14. 
  41. [41] Law R., D. Murrell and U. Dieckmann (2003). Population growth in space and time: spatial logistic equations. Ecology 84, 252-262. 
  42. [42] Loreau M. (2000). Biodiversity and ecosystem functioning: recent theoretical advances. Oikos 91, 3-17. 
  43. [43] Loreau M., S. Naeem, P. Inchausti, J. Bengtsson, J. P. Grime, A. Hector, D. U. Hooper, M. A. Huston, D. Raffaelli, B. Schmid, D. Tilman, and D. A. Wardle (2001). Biodiversity and ecosystem functioning: current knowledge and future challenges. Science 294, 804-808. 
  44. [44] Mateu J., J. L. Us’o, and F. Montes (1998). The spatial pattern of a forest ecosystem. Ecological Modelling 108, 163-174. 
  45. [45] Møller J. and R. Waagepetersen (2003a). An introduction to simulation-based inference for spatial point processes. In J. Møller (Ed.), Lecture Notes in Statistics 137, pp. 143-198. Springer-Verlag, New York. Zbl1039.62089MR2001387
  46. [46] Møller J. and R. Waagepetersen (2003b). Statistical Inference and Simulation for Spatial Point Processes. Chapman & Hall/CRC, Boca Raton. Zbl1044.62101
  47. [47] Mouquet N., J. L. Moore, and M. Loreau (2002). Plant species richness and community productivity: why the mechanism that promotes coexistence matters. Ecology Letters 5, 56-65. 
  48. [48] Murrell D. J., D. W. Purves, and R. Law (2001). Uniting pattern and process in plant ecology. Trends in Ecology and Evolution 16, 529-530. 
  49. [49] Purves D. and R. Law (2003). Heteromyopia and the spatial coexistence of similar competitors. Ecology letters 6, 48-59. 
  50. [50] Purves D. W. and S. W. Pacala (2005). Ecological drift in niche-strucured communities: neutral pattern does not imply neutral process. In D. Burslem, M. Pinard, and S. Hartley (Eds.), Biotic Interactions in the Tropics, pp. 107-138. Cambridge University Press, Cambridge. 
  51. [51] Ramsay J. and B. Silverman (1997). Functional data analysis. Springer, New York. Zbl0882.62002MR2168993
  52. [52] Ramsay J. and B. Silverman (2002). Applied functional data analysis. Springer, New York. Zbl1011.62002MR1910407
  53. [53] Regan H., R. Lupia, and M. Burgmann (2001). The currency and tempo of extinction. American Naturalist 157, 1-10. 
  54. [54] Ripley B. (1976). The second-order analysis of stationary point processes. Journal of Applied Probability 13, 255-266. Zbl0364.60087MR402918
  55. [55] Schlather M. (2001). On the second-order characteristics of marked point patterns. Bernoulli 7, 99-117. Zbl0978.60045MR1811746
  56. [56] Schoener T. W. (1989). The ecological niche. In J. Cherrett (Ed.), Ecological Concepts, pp. 79-113. Blackwell Scientific Publications, Oxford. 
  57. [57] Stoll P. and J. Weiner (2000). A neighbourhood view of interactions among individual plants. In U. Dieckmann, R. Law, and J. Metz (Eds.), The Geometry of Ecological Interactions: Simplifying Spatial Complexity, pp. 11-27. Cambridge University Press, Cambridge. 
  58. [58] Stoyan D., W. Kendall, and J. Mecke (1995). Stochastic Geometry and its Applications (2nd ed.). John Wiley & Sons, London. Zbl0838.60002MR895588
  59. [59] Stoyan D. and A. Penttinen (2000). Recent applications of point process methods in forestry statistics. Statistical Science 1, 61-78. MR1842237
  60. [60] Stoyan D. and H. Stoyan (1994). Fractals, random Shapes and Point Fields. John Wiley & Sons, London. Zbl0828.62085MR1297125
  61. [61] Tilman D. (1994). Competition and biodiversity in spatially structured habitats. Ecology 75, 2-16. 
  62. [62] Tilman D., P. B. Reich, J. Knops, D. Wedin, T. Mielke, and C. Lehman (2001). Diversity and productivity in a long-term grassland experiment. Science 294, 843-845. 
  63. [63] Tilman D., D. Wedin, and J. Knops (1996). Productivity and sustainability influenced by biodiversity in grassland ecostystems. Nature 379, 718-720. 
  64. [64] Turkington R. A. and J. L. Harper (1979). The growth, distribution and neighbour relationships of Trifolium repens in a permanent pasture. I ordination, pattern and contact. Journal of Ecology 67, 201-208. 
  65. [65] Van Lieshout M. (2000). Markov point processes and their applications. Imperial College Press, London. Zbl0968.60005MR1789230

NotesEmbed ?

top

You must be logged in to post comments.

To embed these notes on your page include the following JavaScript code on your page where you want the notes to appear.

Only the controls for the widget will be shown in your chosen language. Notes will be shown in their authored language.

Tells the widget how many notes to show per page. You can cycle through additional notes using the next and previous controls.

    
                

Note: Best practice suggests putting the JavaScript code just before the closing </body> tag.