Summary
For the description of patterns in data from quadrats arranged in a belt or grid, a new ‘paired-quadrat variance’ (PQV) method is introduced. This and other published methods were applied to artificial data with known patterns and to two sets of field data. Hypotheses formed by other methods about patterns shown in the field data are tested by Goodall's method involving ‘random pairing of quadrats to obtain variances’ (RPQV). The advantages of using the PQV method and Hill's new ‘two-term local quadrat variance’ (TTLQV) method over the earlier ‘blocked-quadrat variance’ (BQV) methods are discussed. It is recommended that quadrat data be divided into two subsets, and then the PQV method be applied to one and the RPQV method to the other. This new procedure for spatial pattern analysis would permit the separation of hypothesis formation (by the PQV method) from hypothesis testing (by the RPQV method), and would permit unambiguous significance tests.
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Nomenclature of Australian species follows Black, J.M. 1957–1964 Flora of South Australia (2nd edition). Government Printer, Adelaide.
This research was performed while on sabbatical leave from The Biology Department, New Mexico State University, Las Cruces, New Mexico 88003, USA.
We are indebted to our colleagues in the Division of Land Resources Management for their stimulating support, to Helen Warrener for secretarial assistance, and to Drs Mike Austin, Jonathan Majer, Imanuel Noy-Neir, David Jupp and Jim Watson for comments on the paper in draft.
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Ludwig, J.A., Goodall, D.W. A comparison of paired- with blocked-quadrat variance methods for the analysis of spatial pattern. Vegetatio 38, 49–59 (1978). https://doi.org/10.1007/BF00141298
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DOI: https://doi.org/10.1007/BF00141298