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Redressing the paucity of tree hollows is essential for conservation of hollow‐dependent fauna in many landscapes around the world. We describe a method of accelerating availability of natural hollows in regenerating landscapes by mechanically creating entrances in tree stems that have existing voids or internal decay but have not yet developed entrances. We trialed this method in woodland and forest of south‐eastern Australia in 39 stems in the closely related tree genera Eucalyptus and Angophora. Exploratory drilling of 10‐mm diameter holes was used to detect the presence of internal decay or voids. We then drilled 40‐, 65‐, or 90‐mm diameter entrance holes, depending on the size of the potential cavity, 2.4–4.8 m above ground level. Camera traps showed that drilled entrances were investigated or used within hours of creation. A diverse suite of invertebrates, reptiles, mammals, and birds were recorded entering or leaving entrances, including threatened species. All 39 holes were used by animals with up to six vertebrate taxa using some entrances. Two bird species excavated material from within cavities, and three species of marsupial were recorded taking nesting material into the cavities. This trial provides evidence that adding entrances to currently inaccessible internal cavities in trees has potential to accelerate development of habitat for hollow‐dependent fauna, particularly in regenerating vegetation. [ABSTRACT FROM AUTHOR]

Hollows, also known as tree cavities, are critical to the survival of many animal species but are too poorly mapped across landscapes to allow for their adequate consideration in regional planning. Managing cost is important, so we tested whether freely available satellite-derived foliage projective cover and field-measured stand attributes could be used separately or combined to predict tree hollow abundance in relictual Australian temperate woodlands. Satellite-derived foliage projective cover revealed variation in woody vegetation densities both within mapped woodland remnants and cleared areas of the agricultural matrix. Plot-based field assessment of the actual number of hollows in each one-hectare site ( n = 110 sites) revealed a relationship with foliage cover. Improvement of the model was achieved if site-based estimates of the proportion of the canopy due to Eucalyptus species and the number of mature trees per hectare were included. Remotely sensed foliage cover can improve on traditional vegetation mapping for predicting hollow-bearing tree and hollow abundances at landscape scales when managing hollow-dependent fauna habitat across relictual woodlands in temperate Australian agricultural landscapes. At finer scales, the addition of other predictors is necessary to raise the accuracy of the predicted hollow densities. [ABSTRACT FROM AUTHOR]

Abstract: Offset schemes are advocated as a way that continued development and environmental restoration can be achieved concurrently. We used a simple modelling approach to evaluate proposed offsets schemes, with scenarios that required offsetting the impacts of clearing woodlands either by revegetation of cleared land or by improving the habitat value of degraded woodland. Each simulation used the attribute table of a single GIS polygon layer to obtain data and record results. We investigated the likely consequences of these schemes for three groups of species with different foraging resource requirements: shrub-dependent; canopy-dependent and old tree-dependent. Only the shrub-dependent group, whose requirements could be rapidly grown, saw increases in suitable habitat in the landscape within our 30year simulations. The habitat of the canopy-dependent group initially declined but began to increase towards the end of some simulations, while the old tree-dependent group’s habitat declined. When a simple measure of spatial configuration was considered further differences between the schemes were highlighted. The simulation results demonstrate that assessing only the eventual benefit score of a scheme can hide the losses sustained by some elements of biodiversity. We recommend this type of simple modelling approach as the first step in determining whether a proposed offsets scheme is worth investigating further. In particular, the ability to represent the scheme’s predicted consequences as maps and graphs assists decision makers in judging whether the scheme has sufficient merit to warrant a full assessment and subsequent implementation; or needs some adjustments to achieve its aims, or is seriously flawed. [Copyright &y& Elsevier]

We consider the history of woodland clearing in central western New South Wales, Australia, which has led to the present highly cleared and fragmented landscape. A combined approach is used examining available historical land-use data and using regression analysis to relate the pattern of cleared and wooded areas in the recent landscape to environmental variables, taking into account the contagious nature of clearing. We also ask whether it would be possible to apply a simple simulation modelling approach to reconstruct a credible historical sequence of clearing in the study area. The historical data indicate that annual clearing rates have varied substantially in the study area and selective tree removal (ringbarking and thinning) has been common. These findings make it unlikely that a simple simulation approach would replicate the spatial and temporal sequence of woodland loss. Our regression results show that clearing patterns can be related to environmental variables, particularly annual rainfall and estimated pre-European vegetation type, but that patterns are dominated by contagion. [ABSTRACT FROM AUTHOR]

White cypress pine Callitris glaucophylla is an important native tree widespread in heavily cleared savanna woodlands of the south-east Australian wheat-sheep belt. C. glaucophylla woodlands have been the focus of vigorous debate regarding their structure and dynamics during Aboriginal times and following European settlement, and the causes of structural changes are poorly understood. Management of contemporary woodland remnants is therefore controversial, and has so far lacked a predictive, process-based approach. We sought to determine whether a simple process model with recruitment, growth and survival mediated by rainfall and competition, could accurately simulate medium-term dynamics of C. glaucophylla woodlands in which fire has typically been excluded. Model parameters were optimised using reference data from 6- to 36-year silvicultural trials in central-western New South Wales (NSW). Predictions of the calibrated model compared favourably to actual growth, survival and recruitment of C. glaucophylla in the reference data, as well as in an independent dataset not used in optimisation. We tested whether remaining differences between predictions and actual data were related to variation in site productivity (a function of moisture availability as influenced by soil and landscape factors not modelled). Growth was overestimated in low-productivity sites and underestimated in high-productivity sites. Growth predictions were improved by using site-specific expected maximum heights to reflect site productivity. We also tested whether the model and parameter set produce dynamics consistent with those observed over the last half century. Modelled growth, survival, recruitment and competition processes were consistent with data and observations in previous studies on historical dynamics and stand behaviour of C. glaucophylla. The model has a wide range of potential applications for understanding past and predicting future stand dynamics. To illustrate an application of the model to thinning, a strategy currently being implemented to manage tree densities in inland NSW, we compared predicted stand structures in simulations of different thinning treatments. The simulations showed that without careful manipulation of existing canopy cover, stands can re-fill to pre-thinning densities within relatively short periods of time. [Copyright &y& Elsevier]

Abstract: Many ecological indices convert raw estimates of a variable into a score, and combine scores for multiple variables into a total score. Biodiversity valuation indices, for example, convert raw estimates of variables thought to be surrogates for habitat attributes into a quantitative expression of biodiversity value for use in market-based conservation policies. This study evaluated two potential sources of inaccuracy in total scores: quantitative or model uncertainty; and input data uncertainty or measurement error. Simulated scenarios were run to explore the effects of measurement error and bias on hypothetical sites in a grassy woodland, using two indices of biodiversity value commonly used in Australia. Parameterisation of measurement error was informed by published information on empirical measurement error, as well as results of a field trial using 10 independent observers. As expected, larger observer errors led to less precision in valuations, although coefficients of variation in total scores were often smaller than those of the input variables due to compensatory errors. Unexpectedly, unbiased observer errors in the input variables generated biased valuations of biodiversity. This bias was almost always in one direction – the indices underestimated the true biodiversity value of most sites, high-value sites in particular. Underestimation primarily occurred where raw true values were within benchmark scoring categories but observer error caused a majority of observer estimates to fall into lower scoring categories. The size of benchmark scoring intervals and parameter weightings were the two factors that most influenced the degree of bias. Depending on the index used to calculate biodiversity value, the underestimation effect was more significant for sites with intact woody or herbaceous features, due to scoring intervals and weightings of these features. For market-based biodiversity policies, significant implications include increasing the risk of worse than expected outcomes. This research highlights the imperative to minimise observer error hitherto poorly dealt with, to design and construct quantitative ecological indices in ways that do not exacerbate uncertainty, and to explicitly address uncertainty in decision making. [Copyright &y& Elsevier]