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Abstract: Forest dynamics after timber harvesting is a major issue for tropical forest managers and communities. Timber harvesting provides income to communities and governments and resources to industry but it has also been identified as a potential contributor to deforestation and degradation of tropical forests. In Papua New Guinea (PNG) harvesting is primarily occurring in accessible primary forests however, the fate of these forests under current harvesting practices is poorly understood. In this study we investigated the impacts of selective harvesting on stand structure, growth and dynamics, recovery and degradation, and species diversity. We also assessed the impacts of forest fire after the 1997–98 El Nino on basal area (BA) growth and mortality rates of natural tropical forests in PNG. For this study we used data from 118 (105 in selectively harvested and 13 in un-harvested forest), one-hectare permanent sample plots distributed across the country and measured for over 15years by the PNG Forest Research Institute (PNGFRI). We analysed data from 84 of these plots in harvested forest to examine temporal trends in stand condition following harvesting. Mortality rates were investigated in 10 of the 21 plots in harvested forest that were burned during the 1997–98 El Nino drought with sufficient data for analyses. We tested a model developed in Queensland tropical forests to determine whether or not a critical threshold residual BA existed for the recovery of harvested tropical forests in PNG. Results from a logarithmic regression analysis of the relationship between starting BA (BA at first census) and stand BA increment after selective harvesting showed a positive increase in BA growth (r 2 =0.74, p <0.05). However, there was no critical threshold in residual BA that determined whether a harvested forest was likely to degrade or recover BA growth after harvesting. Our analyses suggested that the response to harvesting was variable, with the majority of un-burned plots (75%) showing an increase in BA and remainder a decrease. Average BA of selectively-harvested tropical forests was about 17m2 ha−1 ±4.17 (SD). Average annual increment in BA across the 84 un-burned plots was 0.17m2 ha−1 year−1 ±0.62 (SD). Thus these forests generally show capacity to recover after selective harvesting even when the residual BA is low. A proportion of the BA increment is made up of non-commercial pioneer species that originate in significant gaps after harvesting. On burned plots, BA is affected by high mortality rates. The fate of these forests will depend on the degree of future harvesting, potential conversion to agriculture and the impact of fire and other disturbances. [Copyright &y& Elsevier]

Abstract: This paper details predictive models of tree-level hollow incidence for State forests in central and eastern Victoria. Models are based on the hollows component of the Statewide Forest Resource Inventory (SFRI), the most comprehensive database of hollow incidence in Australia. A two-stage methodology was used at the individual tree-level that in its first-stage generated a statement of the probability of hollows presence, and in its second-stage estimated the size of hollows. The hierarchical nature of SFRI data prompted the search for statistical methodology capable of explicitly modelling a complicated error structure. Subsequently, generalised linear mixed models (GLMMs) were used to estimate first-stage, tree-level models in the presence of spatial and nested dependence. The developed models were statistically and biologically plausible and performed well when validated using independent data. By overcoming the limitations facing previous research associated with insufficient data and inappropriate statistical methodology viable predictive models were developed. Tree-level models will help us understand patterns of hollow incidence, can be used for predictive purposes when individual-tree information is available, and can improve habitat tree retention guidelines. [Copyright &y& Elsevier]

Abstract: An individual-tree growth modelling methodology capable of explicitly modelling observed spatial dependence was sought using growth data for even-aged Eucalyptus pilularis (Smith.) in New South Wales, Australia. Candidate methodologies included the moving average autoregression, the directly specified Gaussian covariance function, and the Papadakis method. The directly specified Gaussian covariance function and the Papadakis method adequately modelled positive spatial dependence attributable to micro-site influences, but failed to model the negative spatial dependence attributable to competitive influences. The moving average autoregression was the only model which facilitated the simultaneous modelling of spatial dependence attributable to confounded competitive and micro-site influences. Consequently, the moving average autoregression was identified as the best methodology for explicitly modelling the spatial dependence prevalent among the individual trees of forests. Benefits from this new methodology for estimating individual-tree growth models include valid parameter estimates and inferences, improved estimation efficiency and a strengthened theoretical basis for the model. Furthermore, the moving average autoregression provides a definition of the dispersion matrix which can be used to generate more realistic stochastic predictions of individual-tree growth. The results detailed here apply to an even-aged eucalypt stand, and their generality need to be explored further in different forest structures, particularly irregular natural forests. Practical application of the methodology is discussed. [Copyright &y& Elsevier]

Abstract: Spatial dependence in individual-tree diameter, and growth model residuals was characterised for an even-aged Eucalyptus pilularis (Smith) experiment in New South Wales, Australia. The magnitude of spatial dependence changed as the dominance of competitive mechanisms and micro-site influences changed through stand development. Examination of spatial dependence at several spatial scales revealed a consistent structure of initially significant positive spatial dependence declining over larger inter-tree distances. This structure was attributed to the influence of micro-site variation, whereby neighbours are subject to similar environmental conditions, but the confounding influence of competition was also observed over small inter-tree distances. This structure was prevalent among individual-tree diameters, and residuals from an individual-tree growth model. The finding of a significant and consistent spatial dependence in growth model residuals violates the assumption of independent residuals thus threatening estimation efficiency and model inference. Improved individual-tree growth modelling methodologies need to be developed capable of incorporating this observed spatial dependence. [Copyright &y& Elsevier]

Hollow-bearing trees are an important ecological resource for many forest-dwelling species throughout the world. Assessments of the abundance and characteristics of tree hollows usually involve ground-based surveys. These are likely to be biased because of the distance over which the assessments are made. We demonstrate the use of double-sampling theory to correct this bias in order to provide the most efficient estimate of hollow abundance. A sample of 40 Eucalyptus leucoxylon (yellow gum) trees located at Yarra Bend Park, Melbourne, were climbed and assessed for hollows through close-up inspection. The results were compared to ground-based surveys conducted by individuals with varying levels of experience in assessing tree hollows. Strong correlations (r=0.57−0.83) were found between climbing and ground surveys and amongst ground surveys. Those ground surveyors who took more time with their surveys generally identified a higher proportion of hollows (Spearman’s r2=0.72), although all ground surveys underestimated hollow frequency. The proportion of hollows identified by each observer (range 0.09–0.44) remained approximately constant across all tree diameter size classes, indicating systematic underestimation of hollow frequency. The relative efficiency of ground surveys in comparison to climbing surveys is dependent on the time taken for each survey method and the strength of the relationship between them. Although climbing surveys provided the standard for hollow detection, in all cases, the quicker ground surveys were found to increase the efficiency of hollow assessments. Therefore, it was determined that efficient surveys of hollow occurrence could be undertaken by inexperienced surveyors with periodic climbing surveys to measure and correct for bias. [Copyright &y& Elsevier]

The majority of past and current individual-tree growth modelling methodologies have failed to characterise and incorporate structured stochastic components. Rather, they have relied on deterministic predictions or have added an unstructured random component to predictions. In particular, spatial stochastic structure has been neglected, despite being present in most applications of individual-tree growth models. Spatial stochastic structure (also called spatial dependence or spatial autocorrelation) eventuates when spatial influences such as competition and micro-site effects are not fully captured in models. Temporal stochastic structure (also called temporal dependence or temporal autocorrelation) eventuates when a sequence of measurements is taken on an individual-tree over time, and variables explaining temporal variation in these measurements are not included in the model. Nested stochastic structure eventuates when measurements are combined across sampling units and differences among the sampling units are not fully captured in the model. This review examines spatial, temporal, and nested stochastic structure and instances where each has been characterised in the forest biometry and statistical literature. Methodologies for incorporating stochastic structure in growth model estimation and prediction are described. Benefits from incorporation of stochastic structure include valid statistical inference, improved estimation efficiency, and more realistic and theoretically sound predictions. It is proposed in this review that individual-tree modelling methodologies need to characterise and include structured stochasticity. Possibilities for future research are discussed. [ABSTRACT FROM AUTHOR]