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Spatial pattern analysis of line-segment data in ecology
journal contribution
posted on 2023-05-21, 04:51 authored by Luke YatesLuke Yates, Barry BrookBarry Brook, Jessie BuettelJessie BuettelThe spatial analysis of linear features (lines and curves) is a challenging and rarely attempted problem in ecology. Existing methods are typically expressed in abstract mathematical formalism, making it difficult to assess their relevance and transfer ability into an ecological setting. We introduce a set of concrete and accessible methods to analyse the spatial patterning of line-segment data. The methods include Monte Carlo techniques based on a new generalisation of Ripley's K-function and a class of line-segment processes which can be used to specify parametric models - parameters are estimated using maximum likelihood and models compared using information-theoretic principles. We apply the new methods to fallen tree (dead log) data collected from two one-hectare Australian tall eucalypt forest plots. Our results show that spatial pattern of the fallen logs is best explained by plot-level spatial heterogeneity in combination with a slope-dependent non-uniform distribution of fallen-log orientations. These methods are of a general nature and are applicable to any line-segment data. In the context of forest ecology, the integration of fallen logs as linear structural features in a landscape with the point locations of living trees, and a quantification of their interactions, can yield new insights into the functional and structural role of tree fall in forest communities and their enduring post-mortem ecological legacy as spatially distributed decomposing logs.
History
Publication title
EcologyArticle number
3597Number
3597Pagination
1-36ISSN
0012-9658Department/School
School of Natural SciencesPublisher
John Wiley & Sons, Inc.Place of publication
1707 H St Nw, Ste 400, Washington, USA, Dc, 20006-3915Rights statement
© 2022 Ecological Society of America. All rights reserved.Repository Status
- Restricted