Assessment and monitoring of decline and dieback of forest eucalypts in relation to ecologically sustainable forest management: a review with a case study

Techniques for assessing and monitoring the decline and dieback of forest eucalypts are reviewed in relation to ecologically sustainable forest management.

Abstract

Summary In this paper techniques for assessing and monitoring the decline and dieback of forest eucalypts are reviewed in relation to ecologically sustainable forest management. The concept of ecologically sustainable management is a guiding philosophy being adopted for the management of all Australian native forests. An integral component of this strategy will be the ability to monitor forest health. This requires assessment of both the appearance of trees (canopy condition) and their underlying physiological status. However, visual assessment of eucalypt canopies can be misleading because of their opportunistic leafing phenology and epicormic regrowth characteristics. Several forest health assessment programs outside Australia now use multispectral imagery obtained by remote sensing. Such programs depend on relating spectral features with plant physiological properties such as chlorophyll content of the foliage. More recently chlorophyll fluorescence spectra have been related to the functioning of the photosynthetic apparatus and have been shown to be highly sensitive indicators of plant stress. Both reflectance and fluorescence spectral properties should be included in the development of future health monitoring programs for eucalypt forests. A form of forest eucalypt dieback associated with bell miners (Manorina melanophrys) was selected to test the correlation between canopy dieback and leaf-based chlorophyll fluorescence measurements. In addition, a conceptual model of this form of eucalypt dieback is presented in order to demonstrate the complex interrelationships between the poor health of individual tree canopies and overall declining health of the forest ecosystem. Such a model is critical to the correct interpretation of remote sensing imagery.