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Tree Hollow Incidence in Victorian State Forests

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Tree Hollow Incidence in Victorian State Forests Julian C. Fox, Fiona Hamilton and Sharon Occhipinti 39 Tree hollow incidence in Victorian state forests Julian C. Fox1,2, Fiona Hamilton3 and Sharon Occhipinti4 1Department of Forest and Ecosystem Science, Melbourne School of Land and Environment, The University of Melbourne, Burnley Campus, 500 Yarra Blvd, Richmond, Victoria 3121, Australia 2Email: [email protected] 3Department of Sustainability and Environment, 3/8 Nicholson Street, East Melbourne, Victoria 3002, Australia 4URS Australia Pty Ltd, Level 6, 1 Southbank Boulevard, Southbank, Victoria 3006, Australia Revised manuscript received 4 December 2008 Summary species (Ambrose 1982; Smith and Lindenmayer 1988; Loyn 1993). These include species listed as threatened under the The availability of tree hollows in timber production forests is a Environment Protection and Biodiversity Conservation Act 1999 contentious issue facing forest and wildlife managers in Australia. (EPBC Act), and for this reason loss of hollow­bearing trees has To integrate conservation priorities for hollow­dependent fauna recently been listed as a ‘Key Threatening Process’ under the in forest stewardship, public land managers need information EPBC Act. In Victoria, much of the hollow­based habitat for on the quantity and spatial distribution of hollow­bearing trees. these species may occur within state forests (Attiwill 1995), but This information has previously been lacking, but an extensive little is known of the availability and distribution of tree hollows hollows database exists in the Victorian Statewide Forest Resource in these forests. Inventory (SFRI). We use the SFRI to estimate simple stand­level models for the density of hollow­bearing trees, and the density Tree hollows form as a result of stochastic, episodic events such of hollow size classes. Models were of borderline predictive as fire, decay by fungal or insect attack, and mechanical damage ability but were statistically significant. This is consistent with from other trees, wind or lightning. Given the stochastic nature previous models of hollow incidence that have found hollow of hollow development and a paucity of information from which formation to be intrinsically stochastic. We then applied these to develop and parameterise predictive models (Gibbons and models in a geographic information system (GIS) to generate Lindenmayer 1996), previous modelling attempts have had spatial predictions of hollow availability in Victorian state forests. modest success. Models previously developed in Victoria are The resulting GIS layers are available from the Department of those of Lindenmayer et al. (1993), who examined 2315 trees in Sustainability and Environment (DSE) and are a valuable resource the central highlands of Victoria, and Bennett et al. (1994), who for forest and wildlife managers, researchers and the interested studied 1120 trees on the northern plains of Victoria. Although public. We also created tables describing hollow abundance for both studies identified useful relationships between the incidence different forest types, and important stand­level trends in hollow of hollows and individual­tree attributes, the developed models availability emerged. We found that hollow density in ash forests had limited predictive ability. In a small number of studies trees (Eucalyptus regnans, Eucalyptus delegatensis) was consistently have been felled for a more detailed examination of hollow size low and strongly influenced by the presence of non­ash species and abundance. The extent of such work has been limited because that are more susceptible to hollow formation. Hollows occurred of the expense of tree felling and dissection and restrictions on in E. regnans forest at particularly low density, with less than this practice in national parks and state forests (Lindenmayer 37% of trees having hollows until diameter exceeded 125 cm. et al. 2000), but the studies of Mackowski (1987), Gibbons The density of hollows in non­ash forests was comparatively (1999), Whitford and Williams (2002) and Koch et al. (2008) greater, with more than 49% of trees containing hollows when are notable. Unfortunately the limited size of the samples in their diameter exceeded 75 cm. these studies hindered the usefulness of the models developed (Gibbons 1999). Keywords: forest management; wildlife; cavities in trees; habitats; models; state forests; Victoria Several studies have attempted to build predictive models for the incidence of tree hollows, using biotic and abiotic factors to Introduction explain the variation. Studies have used generalised linear models and have assumed either that counts of hollow incidence follow Managing state forests for net social benefit requires an appro­ a Poisson distribution (e.g., Lindenmayer et al. 1993; Bennett priate balance of timber production and conservation priorities et al. 1994; Gibbons 1999) or that the presence or absence of (Ferguson 1996). Forest managers trying to strike this balance hollows follows a binomial distribution (Lindenmayer et al. 1991; face many challenges, and amongst the most contentious is the Gibbons 1999; Fox et al. 2008). These studies indicated that biotic availability of tree hollows, with previous studies indicating that factors including tree diameter, crown form, age, species and a limited availability constrains populations of forest­dwelling understorey composition (Lindenmayer et al. 1993; Bennett et Australian Forestry 2009 Vol. 72 No. 1 pp. 39–48 40 Tree hollows in Victorian forests al. 1994; Gibbons 1999), as well as abiotic factors including site 25 361 ground­based assessments of hollow presence or absence characteristics such as slope, latitude and rainfall (Lindenmayer et across 2683 variable­radius plots. In the second stage the size and al. 1993; Bennett et al. 1994) influence the incidence of hollows. quantity of hollows was measured in three randomly­sampled The models developed had limited predictive ability, however, trees that were felled for a subset of randomly­selected plots and researchers resigned themselves to identifying simple rules (Department of Natural Resource and Environment 1999; Fox et of thumb that can be coarsely applied (Lindenmayer et al. 2000). al. 2008). In total 1326 trees were felled for 423 randomly­selected Researchers have speculated that the poor precision of previous plots. The dimensions of entries to hollows in felled trees were predictive models indicates a need to collect further data at several categorised into four size classes: 2–5 cm, 5–10 cm, 10–20 cm spatial scales and to ensure that variables are measured at the and > 20 cm. Dead trees were included in the modelling, as appropriate level of resolution (Lindenmayer et al. 1993). they often contain hollows: this is particularly the case for ash forests where pre­1939 stags are an important source of hollows Victoria’s Statewide Forest Resource Inventory (SFRI) provides (Lindenmayer et al. 1990). Therefore we have a large dataset of an opportunity to overcome the limitations facing previous first­stage hollow presence or absence, and a smaller subset of modelling (Fox et al. 2008). As part of SFRI, information on the second­stage hollow size and quantity. We used SFRI ground incidence of tree hollows was collected in state forests across plots from state forests in Central, Dandenong, Tambo, Central Victoria. This information on the distribution and abundance of Gippsland and East Gippsland Forest Management Areas. State tree hollows is critical given the aims of forest management to forest in western Victoria and in North­East and Benalla/Mansfield balance timber extraction with wildlife conservation (Department FMAs was not included due to problems with data consistency of Natural Resource and Environment 1999). SFRI sampling was and quality. restricted to state forest that is available for timber production. National park, reserves and areas within state forest that are Associated with each SFRI ground plot are the attributes of the unavailable for timber production due to low productivity, steep aerial photograph interpretation (API) polygon within which the slope or proximity to water courses were not sampled in the SFRI. plot falls. The entire state forest area sampled in the SFRI has Despite the sample being restricted to productive and available been divided into uniform API polygons that were classified for state forest, information on tree hollows collected in the SFRI species composition, tree height and crown cover (Department represents the most extensive database of hollow incidence in of Natural Resource and Environment 1997), and for which a Australian forests. number of derived BIOCLIM environmental (McMahon et al. 1995) and radiometric variables (DPI 2005) were generated. A methodology for modelling tree­level hollow incidence has Therefore models relating the number of hollows on SFRI plots been developed and applied to SFRI data (Fox et al. 2008). to API polygon and other derived predictors can be applied to the The developed tree­level models can be used to estimate the entire forest estate for spatial predictions of hollow incidence in probability that any individual tree will have a hollow and can state forests. be used for creating guidelines for tree retention strategies or for assessing the habitat potential of particular retained trees. However, the models of Fox et al. (2008) cannot be applied for Modelling hollow-bearing trees per hectare stand­level predictions of hollow incidence, and cannot generate Several alternative statistical methodologies
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