• Title of article

    A conceptual model of tree behaviour improves the visual assessment of tree condition

  • Author/Authors

    Souter، نويسنده , , Nicholas J. and Watts، نويسنده , , Richard A. and White، نويسنده , , Melissa G. and George، نويسنده , , Amy K. and McNicol، نويسنده , , Kate J.، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2010
  • Pages
    4
  • From page
    1064
  • To page
    1067
  • Abstract
    A conceptual model describing the response of two Australian floodplain eucalypts, river red gum (Eucalyptus camaldulensis) and black box (Eucalyptus largiflorens), to changes in water availability was developed based on field observations. This model was incorporated into a percentage based visual method estimating two tree crown parameters, crown extent and density. Extent is the amount of foliage at the periphery of the assessable crown; density is the density of assessable crown foliage. Polychoric correlation was used to determine the level of agreement between two experienced observers assessing river red gum and black box trees using a simple percentage scale and a percentage scale supported by the conceptual model. Trees were evaluated using the model by determining their position on a trajectory of water stress related decline and response. In both cases observer estimates of crown extent and density were significantly correlated. With the exception of red gum crown density the correlation coefficients were higher for the model supported scale. Using a conceptual model of tree response to water availability improved observer agreement. Supporting subjective assessment systems with a conceptual model is recommended to improve observer agreement in cases where a distinct model of the dominant stressor can be defined.
  • Keywords
    Tree condition , Crown density , Observer agreement , Visual assessment , Eucalyptus largiflorens , Crown extent , Eucalyptus camaldulensis
  • Journal title
    Ecological Indicators
  • Serial Year
    2010
  • Journal title
    Ecological Indicators
  • Record number

    2091765