Suchergebnisse

An extensive survey was conducted to locate sap trees used by the yellow-bellied glider (Petaurus australis) throughout the forests and woodlands of southern Queensland, across an area of 43.7 million hectares. We recorded the characteristics of 478 sap trees located at 109 of 297 sites surveyed. Only 13 tree species were selected by gliders for sap feeding throughout the study region, with the grey gum species Eucalyptus longirostrata and E. biturbinata most likely to be incised for sap. Of the tree species used for sap feeding by gliders, trees >40 cm in diameter at breast height (dbh) were used more than would be expected on the basis of their abundance in the forest. The number of sap trees with active and recently active feed scars at a site ranged from 0 to 12. Factors that appear to influence the abundance of active and recently active sap trees at a site include intensity of disturbance (basal area of cut stumps and dead trees), the number of stems in the 41–60 and 61–80 cm dbh classes, and number of Myrtaceae species. The response to these variables could be indicative of habitat quality, and the availability of alternative foraging substrates such as flower cover and decorticating bark. Intensification of selective logging in south-east Queensland, as an outcome of the Southeast Queensland Regional Forest Agreement, could potentially marginalise glider habitat. This would necessitate the retention of potential, or 'recruit', sap trees to maintain yellow-bellied glider habitat in these areas.

Identifying the tree species used in sap feeding by the yellow-bellied glider (Petaurus australis) and describing the pattern of use of these trees is fundamental to forest management in eastern and southern Australia. We conducted surveys at 74 sites across 17�000 ha in St Mary State Forest near Maryborough in south-east Queensland, during five visits over a 2-year period. We identified sap-feeding incisions of gliders on 194 trees (2% of all trees) at 47 of our survey sites, including five trees recruited as sap trees during our monitoring period. Five tree species were involved: Corymbia citriodora (100 trees at 26 sites), Eucalyptus longirostrata (73 trees at 19 sites), Eucalyptus moluccana (17 trees at 6 sites), Eucalyptus tereticornis (3 trees at 3 sites), and Angophora leiocarpa (1 tree). Of these trees, E. longirostrata was used much more than expected on the basis of its abundance in the forest. Active glider incisions were observed on 95 of the sap trees (49% of total) during the monitoring period. During our first visit, 66 sap trees showed no evidence of current or recent use (within the previous month). By the fifth visit, there were still 44 sap trees (23% of all sap trees) that showed no evidence of recent use during any visit. Approximately 40% of sap tree observations were of trees with fewer than five recently active incisions, which is currently the threshold number of incisions for tree retention during logging operations in Queensland. We used Poisson regression to assess the influence of climatic and habitat variables on the abundance of active incisions at sites with sap trees. Three variables had a significant influence on the abundance of active incisions at a site: flowering, site index (a measure of productivity) and density of ringbarked trees. Our results confirm the importance of a small number of forest trees in sap feeding and recommendations are provided to enhance prescriptions for effective management of sap food resources of yellow-bellied gliders in south-east Queensland.

Terrestrial laser scanning (TLS) can be used to characterize a woodland site by measuring structural attributes of the vegetation community. In Australia, government funded programs monitor vegetation structure using manual field surveys to assess change and ecological condition. In this study, we examined whether structural attributes commonly assessed in woodland ecology surveys can be extracted from a single TLS scan. Attributes of the ground, shrub and overstory vegetation layers were evaluated at nine open woodland sites in central Western Queensland. We used 0.1 m voxels to aggregate returns. Our results show that, compared with field assessment by highly experienced ecologists, TLS can rapidly characterize structural attributes for tree canopy cover, maximum tree height, average tree height (R² > 0.9) and average diameter at breast height (R² = 0.77). However, we could not accurately determine shrub height, shrub canopy cover, shrub average height, ground cover (grass, litter and coarse woody debris) or the number of trees per hectare (R² 0.9) and average diameter at breast height (R² = 0.77). However, we could not accurately determine shrub height, shrub canopy cover, shrub average height, ground cover (grass, litter and coarse woody debris) or the number of trees per hectare (R²