Towards quantitative acousto-optic imaging in tissue

We have investigated the possibilities and limitations of the application of ultrasound modulated coherent light to obtain quantitative information of local absorbers in light-scattering objects, among which tissue. For all objects studied, the combined use of microsecond ultrasound and light pulses enabled us to construct a 3D map of local absorbers with a spatial resolution of ∼2 mm. Moreover, in relatively homogeneous model systems, mimicking a blood vessel embedded in tissue, the use of a calibration procedure allowed for a determination of the local absorbance. Speckle decorrelation times for real tissue containing blood vessels, in which appreciable motion of scatterers can exist, were found to be smaller than 1ms. These relatively short times present a major challenge for acousto-optics to be applied in living tissue systems

Using Australian Virtual Herbarium data to find all the woody rain forest plants in Australia

Data bases that provide continental and global scale information about species distributions provide a valuable resource for environmental, ecological and evolutionary research. However to bring a large dataset to a standard that is suitable for quantitative analysis, data quality needed to be checked. Here we provide a worked example using a large dataset (c. 320,000 records) from Australia’s Virtual Herbarium (AVH) database, based on an initial data request for full distribution data for c. 2600 woody rain forest species known to occur in Australia. To reconcile inconsistencies around taxonomic identity prior to merging with our trait data-base, and resolve issues around spatial resolution and accuracy, we implemented extensive data filtering using a ‘cloud-based’ solution (Google Refine). This systematic process resulted in 1) the removal of close to 45% of the records originally downloaded, and 2) a clean and powerful data set based on herbarium backed distribution records for Australia’s woody rain forest species. Such resources can contribute significantly to improving research outcomes related to understanding Australia’s vegetation

Modelling growth, recruitment and mortality to describe and simulate dynamics of subtropical rainforests following different levels of disturbance

The capacity of rainforests to recover from logging disturbance is difficult to model due to the compounding interactions between long-term disturbance effects, natural dynamics, site characteristics and tree species regeneration strategies. The aim of this study was to develop a quantitative model using over three decades of data from stands subjected to various levels of disturbance ranging from natural, through increasing intensities of tree removal to intensive logging. Data for trees >10 cm diameter at 1.3 m above the ground (dbh) in subtropical rainforest of north-east New South Wales, Australia were used. Botanical identity of trees at species level, species-specific shade tolerance and size at maturity were used to classify 117 species into five groups. These groups include the emergent and shade tolerant main canopy species, shade tolerant mid canopy species, shade tolerant understorey species, moderate shade tolerant species, and shade intolerant tree species. Multilevel nonlinear regression was used to estimate growth, recruitment and mortality parameters, based on the assumption of variations in tree species performance at both the plot and tree levels. The species group, tree size and competition from larger trees accounted for most variation at the tree level. Significant stand level variables included topography (elevation, slope and aspect), stand basal area, and time since the disturbance. The final model is a classical matrix management-oriented model with an ecological basis and maximum size-dependent parameters of ingrowth and outgrowth. The model provides a tool to simulate stand performance after logging and to assess silvicultural prescriptions before they are applied. Simulations with estimated parameters indicate that moderate harvesting (47% overstorey basal area (BA) removal) in a checkerboard of logged and unlogged patches (group selection) on a 120-year cycle could enable sustainable timber production without compromising the ecological integrity in these rainforests. This is due to reduced logging damage in group selection, which also released retained stems and facilitated recruitment of both shade tolerant and intolerant trees. Single-tree selection (35% BA removal) created small canopy gaps that resulted in low recruitment, a slight increase in the growth of retained stems and recovery time of 150 years. Intensive single-tree selection (50% BA removal) resulted in high logging damage that increased recovery time to 180 years. Intensive logging (65-80% BA removal) decreased the stem density and created larger canopy gaps allowing for high growth rates and recruitment of both shade tolerant and intolerant trees. However, few retained stems and high mortality of recruits, increased the recovery time to 180-220 years. Pre-harvest climber cutting coupled with poisoning of nontimber species followed by logging could allow harvesting on a 300-year cycle. Shorter logging cycles may lead to changes in species composition as well as in the forest structure

Patterns and drivers of plant diversity across Australia

Biodiversity analyses across continental extents are important in providing comprehensive information on patterns and likely drivers of diversity. For vascular plants in Australia, community-level diversity analyses have been restricted by the lack of a consistent plot-based survey dataset across the continent. To overcome these challenges, we collated and harmonised plot-based vegetation survey data from the major data sources across Australia and used them as the basis for modelling species richness (α-diversity) and community compositional dissimilarity (β-diversity), standardised to 400 m2, with the aim of mapping diversity patterns and identifying potential environmental drivers. The harmonised Australian vegetation plot (HAVPlot) dataset includes 219 552 plots, of which we used 115 083 to analyse plant diversity. Models of species richness and compositional dissimilarity both explained approximately one-third of the variation in plant diversity across Australia (D2 = 33.0% and 32.7%, respectively). The strongest environmental predictors for both aspects of diversity were a combination of temperature and precipitation, with soil texture and topographic heterogeneity also important. The fine-resolution (≈ 90 m) spatial predictions of species richness and compositional dissimilarity identify areas expected to be of particular importance for plant diversity, including south-western Australia, rainforests of eastern Australia and the Australian Alps. Arid areas of central and western Australia are predicted to support assemblages that are less speciose or unique; however, these areas are most in need of additional survey data to fill the spatial, environmental and taxonomic gaps in the HAVPlot dataset. The harmonised data and model predictions presented here provide new insight into plant diversity patterns across Australia, enabling a wide variety of future research, such as exploring changes in species abundances, linking compositional patterns to functional traits or undertaking conservation assessments for selected components of the flora

Regeneration Changes in Tree Species Abundance, Diversity and Structure in Logged and Unlogged Subtropical Rainforest over a Thirty-Six-Year Period

The long-term effects of logging treatments on rainforest regeneration are difficult to quantify due to compounding interactions between natural dynamics, site characteristics and tree species. The aim of this study was to compare regeneration differences over a 36 year period in stands subjected to various levels of disturbance ranging from natural, through an increasing intensity of individual tree removal to intensive logging. Data for tree