Areas Of South-eastern Australia Research Articles

A crustal Pb isotope map of southeastern Australia.

Lead isotopes are a powerful geochemical tracer and a popular tool applied across a broad range of scientific fields, e.g., earth sciences, archaeology, and forensic sciences. Here we present a Pb isotope dataset collected from 232 igneous samples, spanning a ca. 2.3 million km2 area in southeastern Australia, and over 3 billion years of Earth history. This contribution provides a range of isotopic maps showing the spatial variability of Pb isotopes (206Pb/204Pb, 207Pb/204Pb, and 208Pb/204Pb), magma source U/Pb and Th/U, and model ages. The samples selected for this study encompass U- and Th-poor media (i.e., K-feldspar), and U- and Th-bearing sampling media (i.e., whole-rock), providing a temporally and spatially resolved image of U and Th distribution in the crust, and their influence on crustal Pb through radiogenic ingrowth. This dataset has the potential to benefit a wide variety of different disciplines and is an important resource for addressing earth science questions ranging from unravelling crustal differentiation and architecture, through tracing magma source U- and Th-enrichment, to mineral deposit genesis.

Showy birds on attractive food sources: rainbow lorikeets and their plant-related functions at a residential area in South-eastern Australia

Showy birds on attractive food sources: rainbow lorikeets and their plant-related functions at a residential area in South-eastern Australia

U-Net Convolutional Neural Network for Mapping Natural Vegetation and Forest Types from Landsat Imagery in Southeastern Australia.

Accurate and comparable annual mapping is critical to understanding changing vegetation distribution and informing land use planning and management. A U-Net convolutional neural network (CNN) model was used to map natural vegetation and forest types based on annual Landsat geomedian reflectance composite images for a 500 km × 500 km study area in southeastern Australia. The CNN was developed using 2018 imagery. Label data were a ten-class natural vegetation and forest classification (i.e., Acacia, Callitris, Casuarina, Eucalyptus, Grassland, Mangrove, Melaleuca, Plantation, Rainforest and Non-Forest) derived by combining current best-available regional-scale maps of Australian forest types, natural vegetation and land use. The best CNN generated using six Landsat geomedian bands as input produced better results than a pixel-based random forest algorithm, with higher overall accuracy (OA) and weighted mean F1 score for all vegetation classes (93 vs. 87% in both cases) and a higher Kappa score (86 vs. 74%). The trained CNN was used to generate annual vegetation maps for 2000-2019 and evaluated for an independent test area of 100 km × 100 km using statistics describing accuracy regarding the label data and temporal stability. Seventy-six percent of pixels did not change over the 20 years (2000-2019), and year-on-year results were highly correlated (94-97% OA). The accuracy of the CNN model was further verified for the study area using 3456 independent vegetation survey plots where the species of interest had ≥ 50% crown cover. The CNN showed an 81% OA compared with the plot data. The model accuracy was also higher than the label data (76%), which suggests that imperfect training data may not be a major obstacle to CNN-based mapping. Applying the CNN to other regions would help to test the spatial transferability of these techniques and whether they can support the automated production of accurate and comparable annual maps of natural vegetation and forest types required for national reporting.

FC26: What have staff got to do with it? Untangling complex relationships between residential aged care staff, the quality of care they provide, and the quality of life of people with dementia

Background:Despite the integral role long term residential care staff play in the lives of residents with dementia, the mechanisms for supporting staff to bring about good quality of care (QOC) and quality of life (QOL) are poorly understood. This study focused on establishing the key mechanisms to improve QOC and in turn QOL of residents with dementia.Method:Over a 10-month period we followed: 247 older adults with dementia from 12 not-for-profit residential care facilities, their families/care partners (n=225), managers (n=12) and staff (n=232). Facilities ranged in size from 10 to 137 beds, located across remote, rural and metropolitan areas of south eastern Australia. Measures included: staff surveys, family member and resident interviews, resident file audits, live resident and staff observations and organisational audits. Multilevel Modelling or Generalised Estimating Equations analyses were conducted for each of the 12 QOC variables, with 22 staff and control variables as the predictors, and for each of the 11 QOL variables, with 20 QOC and control variables as predictors.Results:Analyses established significant associations between a large number of staff and QOC variables and between QOC and QOL variables.Conclusions:The quality of the care provided to residents has strong, widespread influences on the QOL of residents. The most promising areas for intervening with staff were: increasing the relevance and applicability of staff training and qualifications, upskilling staff in empathic care provision, communication, and restraint reduction, using a mixture of permanent and rotating shifts, prioritising recreational activity provision by all staff and increasing assistance with meals. patients with cognitive impairment in rural hospitals.

Mycobacterium ulcerans not detected by PCR on human skin in Buruli ulcer endemic areas of south eastern Australia.

Mycobacterium ulcerans (MU) causes Buruli ulcer (Buruli), a geographically restricted infection that can result in skin loss, contracture and permanent scarring. Lesion-location maps compiled from more than 640 cases in south eastern Australia suggest biting insects are likely involved in transmission, but it is unclear whether MU is brought by insects to humans or if MU is already on the skin and inoculation is an opportunistic event that need not be insect dependent. We validated a PCR swab detection assay and defined its dynamic range using laboratory cultured M. ulcerans and fresh pigskin. We invited volunteers in Buruli-endemic and non-endemic areas to sample their skin surfaces with self-collected skin swabs tested by IS2404 quantitative PCR. Pigskin validation experiments established a limit-of-detection of 0.06 CFU/cm2 at a qPCR cycle threshold (Ct) of 35. Fifty-seven volunteers returned their self-collected kits of 4 swabs (bilateral ankles, calves, wrists, forearms), 10 from control areas and 47 from endemic areas. Collection was timed to coincide with the known peak-transmission period of Buruli. All swabs from human volunteers tested negative (Ct ≥35). M. ulcerans was not detected on the skin of humans from highly Buruli endemic areas.

Atlantic Multidecadal Variability modulates the climate impacts of El Niño–Southern Oscillation in Australia

Atlantic Multidecadal Variability (AMV) modulates El Niño–Southern Oscillation (ENSO) dynamics. Here, we explore the effect of warm (AMV+) and cold (AMV−) AMV conditions on the austral summer teleconnection of ENSO to Australia using idealized simulations performed with the NCAR-CESM1 model. AMV+ strengthens the mean and extreme precipitation and temperature responses to El Niño in south-western Australia and weakens the mean precipitation and temperature impacts in north-eastern Australia. The modulation of La Niña impacts by AMV is asymmetric to El Niño, with a weakening of the mean and extreme precipitation and temperature responses in eastern Australia. Decomposing the total difference in ENSO response between AMV phases, we find that the signals are mainly explained by the direct AMV modulation of ENSO and its teleconnections rather than by changes in background climate induced by AMV. The exception is ENSO-driven fire impacts, where there is a significant increase in burned area in south-eastern Australia only when El Niño and AMV+ co-occur. However, modulation of ENSO between AMV+ and AMV− does offset ∼37% of the decrease in burned area extent during La Niña summers. The altered surface climate response to ENSO in Australia by AMV is attributed to variations in large-scale atmospheric circulation. Under AMV+, there is increased subsidence over western Australia during El Niño associated with a westward shift of the local Walker circulation. A weakening of the upwelling branch of the local Hadley circulation over north-eastern Australia is responsible for the weakening of La Niña impacts in AMV+, accompanied by a strengthening of subsidence in south central Australia due to a weakening of the local Hadley circulation, amplifying La Niña impacts over this region. The results suggest the potential for AMV to drive multidecadal variability in ENSO impacts over Australia.

Microplastic pollution on hiking and running trails in Australian protected environments

Microplastics (MPs) are ubiquitous worldwide, present even in remote areas of the natural environment. Hiking and trail running are a source of MPs on recreational trails in protected environments, which are characterised by high biodiversity and natural, ecological or cultural significance. Our understanding of the risks of microplastic pollution is impeded however by a lack of information on MPs present in the soil environment in such areas. This study characterised the quantity and physicochemical characteristics of MPs in two conservation areas in south-eastern Australia: 1) the adjacent Duval Nature Reserve and Dumaresq Dam Reserve, and 2) the Washpool and Gibraltar Range National Parks. We measured atmospheric deposition over a six-month period in the Reserves, and baseline amounts of MPs on recreational trails in the Reserves and National Parks. Atmospheric deposition averaged 17.4 MPs m−2 day−1 and was dominated by fibres, comprising 84 % of MPs. Microplastics detected on trail surfaces ranged from 162.5 ± 41.6 MPs/linear metre to 168.7 ± 18.5 MPs/linear metre and exhibited a very wide range of physical and chemical characteristics. The majority of MPs on the trail surfaces comprised polyurethane, polyethylene terephthalate and polystyrene, and 47–71 % were fibres. Microplastics were attributed to clothing, footwear, litter, and diffuse sources. Minimising and preventing MP pollution, however, is complex given there are multiple direct and diffuse sources, and several factors influencing increased MP deposition and retention in the environment.

‘You can’t be green if you’re in the red’: Local discourses on the production-biodiversity intersection in a mixed farming area in south-eastern Australia

Limiting biodiversity loss is a global challenge, especially in areas where biodiversity conservation conflicts with intensifying agricultural production. The different views and preferences about how to protect biodiversity, and why it is valuable, make concerted action to improve conservation outcomes difficult. Exploring different discourses that represent shared understandings of an issue or a topic can help to understand this plurality. We focused on a mixed farming area in south-eastern Australia where intensive agricultural production is linked to an ongoing loss of biodiversity. Using the Q-methodology, we conducted 94 interviews with people who may influence biodiversity outcomes in farming landscapes to explore shared understandings of the farming-biodiversity intersection. We also sought to understand how such discourses relate to perceptions of biodiversity in agricultural contexts and if they are associated with particular stakeholder groups. We identify four discourses on the relationship between farming and biodiversity, the farmers’ role and responsibility for biodiversity, and the preferred approaches to improve biodiversity outcomes. Our findings highlight how perceptions of biodiversity by agricultural stakeholders varied substantially between discourses, but that discourses were not significantly associated with stakeholder group. We discuss our findings in the context of policy development and broader governance. We consider how a balanced mix of policy instruments, including market and community-based instruments, can better engage with contrasting understandings of the production-biodiversity intersection. To improve biodiversity outcomes, it is necessary to integrate a plurality of biodiversity values and ensure a broad and balanced set of policy instruments that supports land managers as stewards of the land.

Public satisfaction with urban trees and their management in Australia: The roles of values, beliefs, knowledge, and trust

The success of urban forest management strategies is dependent on public support for and engagement with urban trees. Satisfaction with urban trees and their management, and the level of trust people have in urban tree managers, are useful for understanding public opinions. Yet these concepts, and the mechanisms leading to the formation of public opinions remain poorly explored in the literature. Here we explore how satisfaction with urban trees and with urban tree management, and trust in the agencies responsible for urban tree management, are explained by cognitive factors (values, beliefs, and knowledge) and socio-ecological contextual factors (tree presence/canopy cover, cultural diversity, and socioeconomic status) using an online survey of 16 local government areas in south-eastern Australia. Analyses of 2367 responses revealed that people’s opinions about trees in general (values and beliefs) were overwhelmingly positive, while their opinions about more contextualised measures such as satisfaction and trust were more mixed. Two distinct pathways that influence satisfaction were identified: one linked to beliefs about having trees in cities, and another one linked to trust in urban tree management. At the local government level, satisfaction was negatively associated with a measure of cultural diversity and very low levels of tree canopy cover, but not with socioeconomic disadvantage. Satisfaction with local trees could be improved by increasing the quality of ecological function of trees, such as habitat provision and tree diversity. Community engagement could also improve satisfaction and trust, particularly perceived procedural fairness of decision-making, reinforce positive beliefs about the outcomes of having trees in cities, and dispel negative beliefs. Engagement processes should recognise that people hold complex and diverse opinions about urban trees, and by incorporating these opinions into decision-making we can meet the increasingly complex and diverse expectations being placed on urban forests.

Landscape‐scale distribution of nest predators and its relationship with regent honeyeater nest success

AbstractOvercoming low breeding success is a major challenge for reversing population decline in threatened species. High nest predation rates are a common cause of low productivity in birds, but implementing evidence‐based management actions to reduce nest predation is challenging. Targeted breeding management requires a good understanding of where threatened species breed, the identity and distribution of nest predator species and the impact of these nest predators on breeding success. For rare and nomadic species, this information is hard to come by. The breeding success of regent honeyeater Anthochaera phrygia has declined over recent decades, and nest predation is the primary cause of breeding failure. We conducted point‐count surveys of nine avian and three mammalian nest predator species across 80% of the regent honeyeater’s contemporary breeding area in south eastern Australia. We used occupancy models to determine the presence of predator species at survey sites and spatial models to predict predator abundance and species richness across the breeding area. We incorporated predator predictions for regent honeyeater nest locations into nest fate and daily nest survival models. Predator abundance was correlated positively with tree hollow abundance and proximity to water and negatively with shrub cover. Regent honeyeater nest success showed no significant relationship with predator abundance or predator species richness. Given how abundant and widespread avian and mammalian nest predators were throughout the breeding area, improving regent honeyeater nest success is likely to require implementation of simultaneous nest protection measures to avoid potential compensatory nest predation. Further research is required to better understand the relationship between nest predator abundance and regent honeyeater nest success.

Soil Bacterial Community Responds to Land-Use Change in Riparian Ecosystems

Riparian forests were frequently cleared and converted to agricultural pastures, but in recent times these pastures are often revegetated in an effort to return riparian forest structure and function. We tested if there is a change in the soil bacterial taxonomy and function in areas of riparian forest cleared for agricultural pasture then revegetated, and if soil bacterial taxonomy and function is related to vegetation and soil physicochemical properties. The study was conducted in six riparian areas in south-eastern Australia, each comprising of three land-use types: remnant riparian forest, cleared forest converted to pasture, and revegetated pastures. We surveyed three strata of vegetation and sampled surface soil and subsoil to characterize physicochemical properties. Taxonomic and functional composition of soil bacterial communities were assessed using 16S rRNA gene sequences and community level physiological profiles, respectively. Few soil physiochemical properties differed with land use despite distinct vegetation in pasture relative to remnant and revegetated areas. Overall bacterial taxonomic and functional composition of remnant forest and revegetated soils were distinct from pasture soil. Land-use differences were not consistent for all bacterial phyla, as Acidobacteria were more abundant in remnant soils; conversely, Actinobacteria were more abundant in pasture soils. Overall, bacterial metabolic activity and soil carbon and nitrogen content decreased with soil depth, while bacterial metabolic diversity and evenness increased with soil depth. Soil bacterial taxonomic composition was related to soil texture and soil fertility, but functional composition was only related to soil texture. Our results suggest that the conversion of riparian forests to pasture is associated with significant changes in the soil bacterial community, and that revegetation contributes to reversing such changes. Nevertheless, the observed changes in bacterial community composition (taxonomic and functional) were not directly related to changes in vegetation but were more closely related to soil attributes.

Sun-Angle Effects on Remote-Sensing Phenology Observed and Modelled Using Himawari-8

Satellite remote sensing of vegetation at regional to global scales is undertaken at considerable variations in solar zenith angle (SZA) across space and time, yet the extent to which these SZA variations matter for the retrieval of phenology remains largely unknown. Here we examined the effect of seasonal and spatial variations in SZA on retrieving vegetation phenology from time series of the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) across a study area in southeastern Australia encompassing forest, woodland, and grassland sites. The vegetation indices (VI) data span two years and are from the Advanced Himawari Imager (AHI), which is onboard the Japanese Himawari-8 geostationary satellite. The semi-empirical RossThick-LiSparse-Reciprocal (RTLSR) bidirectional reflectance distribution function (BRDF) model was inverted for each spectral band on a daily basis using 10-minute reflectances acquired by H-8 AHI at different sun-view geometries for each site. The inverted RTLSR model was then used to forward calculate surface reflectance at three constant SZAs (20°, 40°, 60°) and one seasonally varying SZA (local solar noon), all normalised to nadir view. Time series of NDVI and EVI adjusted to different SZAs at nadir view were then computed, from which phenological metrics such as start and end of growing season were retrieved. Results showed that NDVI sensitivity to SZA was on average nearly five times greater than EVI sensitivity. VI sensitivity to SZA also varied among sites (biome types) and phenological stages, with NDVI sensitivity being higher during the minimum greenness period than during the peak greenness period. Seasonal SZA variations altered the temporal profiles of both NDVI and EVI, with more pronounced differences in magnitude among NDVI time series normalised to different SZAs. When using VI time series that allowed SZA to vary at local solar noon, the uncertainties in estimating start, peak, end, and length of growing season introduced by local solar noon varying SZA VI time series, were 7.5, 3.7, 6.5, and 11.3 days for NDVI, and 10.4, 11.9, 6.5, and 8.4 days for EVI respectively, compared to VI time series normalised to a constant SZA. Furthermore, the stronger SZA dependency of NDVI compared with EVI, resulted in up to two times higher uncertainty in estimating annual integrated VI, a commonly used remote-sensing proxy for vegetation productivity. Since commonly used satellite products are not generally normalised to a constant sun-angle across space and time, future studies to assess the sun-angle effects on satellite applications in agriculture, ecology, environment, and carbon science are urgently needed. Measurements taken by new-generation geostationary (GEO) satellites offer an important opportunity to refine this assessment at finer temporal scales. In addition, studies are needed to evaluate the suitability of different BRDF models for normalising sun-angle across a broad spectrum of vegetation structure, phenological stages and geographic locations. Only through continuous investigations on how sun-angle variations affect spatiotemporal vegetation dynamics and what is the best strategy to deal with it, can we achieve a more quantitative remote sensing of true signals of vegetation change across the entire globe and through time.

Microbial communities of upland peat swamps were no different 1 year after a hazard reduction burn

Fire in wetlands is poorly understood, yet hazard reduction burns are a common management practice and bushfires are becoming increasingly prevalent because of climate change. Fire may have long-lasting implications for the microbial component of these wetland ecosystems that regulate carbon and nutrient cycling. The extremely fire-prone Blue Mountains World Heritage Area in south-eastern Australia contains hundreds of endangered peat-forming upland swamps that regularly experience both bushfires and hazard reduction burns. In a before–after control–­impact study, we surveyed the sediment microbial community of these swamps to test the impact of a low-intensity hazard reduction burn. Along with sediment pH, moisture and organic content, we measured gene abundances including those relating to carbon cycling (quantitative PCR (qPCR) of pmoA, mcrA, bacterial 16S rRNA and archaeal 16S rRNA), and bacteria community fingerprint (terminal restriction fragment length polymorphism (T-RFLP)). One year after the hazard reduction burn, there were no significant differences in the gene abundances or microbial community fingerprint that could be attributed to the fire, suggesting that the hazard reduction burn did not have a long-term impact on these microbial communities.

Multiscale Applications of Two Online-Coupled Meteorology-Chemistry Models during Recent Field Campaigns in Australia, Part I: Model Description and WRF/Chem-ROMS Evaluation Using Surface and Satellite Data and Sensitivity to Spatial Grid Resolutions

Air pollution and associated human exposure are important research areas in Greater Sydney, Australia. Several field campaigns were conducted to characterize the pollution sources and their impacts on ambient air quality including the Sydney Particle Study Stages 1 and 2 (SPS1 and SPS2), and the Measurements of Urban, Marine, and Biogenic Air (MUMBA). In this work, the Weather Research and Forecasting model with chemistry (WRF/Chem) and the coupled WRF/Chem with the Regional Ocean Model System (ROMS) (WRF/Chem-ROMS) are applied during these field campaigns to assess the models’ capability in reproducing atmospheric observations. The model simulations are performed over quadruple-nested domains at grid resolutions of 81-, 27-, 9-, and 3-km over Australia, an area in southeastern Australia, an area in New South Wales, and the Greater Sydney area, respectively. A comprehensive model evaluation is conducted using surface observations from these field campaigns, satellite retrievals, and other data. This paper evaluates the performance of WRF/Chem-ROMS and its sensitivity to spatial grid resolutions. The model generally performs well at 3-, 9-, and 27-km resolutions for sea-surface temperature and boundary layer meteorology in terms of performance statistics, seasonality, and daily variation. Moderate biases occur for temperature at 2-m and wind speed at 10-m in the mornings and evenings due to the inaccurate representation of the nocturnal boundary layer and surface heat fluxes. Larger underpredictions occur for total precipitation due to the limitations of the cloud microphysics scheme or cumulus parameterization. The model performs well at 3-, 9-, and 27-km resolutions for surface O3 in terms of statistics, spatial distributions, and diurnal and daily variations. The model underpredicts PM2.5 and PM10 during SPS1 and MUMBA but overpredicts PM2.5 and underpredicts PM10 during SPS2. These biases are attributed to inaccurate meteorology, precursor emissions, insufficient SO2 conversion to sulfate, inadequate dispersion at finer grid resolutions, and underprediction in secondary organic aerosol. The model gives moderate biases for net shortwave radiation and cloud condensation nuclei but large biases for other radiative and cloud variables. The performance of aerosol optical depth and latent/sensible heat flux varies for different simulation periods. Among all variables evaluated, wind speed at 10-m, precipitation, surface concentrations of CO, NO, NO2, SO2, O3, PM2.5, and PM10, aerosol optical depth, cloud optical thickness, cloud condensation nuclei, and column NO2 show moderate-to-strong sensitivity to spatial grid resolutions. The use of finer grid resolutions (3- or 9-km) can generally improve the performance for those variables. While the performance for most of these variables is consistent with that over the U.S. and East Asia, several differences along with future work are identified to pinpoint reasons for such differences.

Dual-purpose cereals offer increased productivity across diverse regions of Australia’s high rainfall zone

Dual-purpose (DP) cereals provide an opportunity to graze vegetative crops in autumn and winter when pasture forage levels are low, and then harvested for grain after the exclusion of stock. The dual use provides significant increases in mixed farm returns and the area of DP crops is expanding from traditional areas in south-eastern Australia. DP crops have particular potential in the 9 M ha high rainfall zones (HRZ, >500–600 mm annual rainfall) where the crop growing season is longer, increasing the potential grazing period and the capacity to recover high grain yield. To capitalise on this potential, management packages that combine the most suitable varieties and sowing times to maximise forage and grain production are required. We conducted six experiments across the south-eastern, north-eastern and south-western regions of Australia’s HRZ to assess potential forage and grain production of DP cereal species (wheat, barley and triticale) and phenology types. In the south-eastern HRZ, slow winter cultivars out-performed spring types due the increased forage production in the ‘safe’ grazing period (stem elongation, DC30) providing up to 2600 DSE.days/ha and 7.5 t/ha grain yield from a mid-March sowing. Early-sown spring cultivars provided a shorter period of ‘safe’ grazing as the lack of vernalisation requirement hastened development and reduced grain yield potential. In the south-western HRZ, early sowing opportunities (March) are rare and the season much shorter. The best results were achieved with mid-April sowing of barley and longer season spring and facultative wheat, providing 640 DSE.days/ha and grain yields of 3.0 t/ha and 3.4 t/ha, respectively. In the north-eastern HRZ, grain recovery was more sensitive to grazing, however 2000 DSE.days/ha and 6.5 t/ha grain yield were achieved with winter cereals sown in early April. Grazing in the safe phenological window had no effect on grain yield in the south-west region, but reduced yield of some cultivars in the eastern regions. The reduction in grain yield of early-sown winter wheat cultivars due to grazing (17–28%) was greatest when yield potential was high (>6.8 t/ha). Overall, the experiments confirm the predicted potential for dual-purpose production of cereals across the Australian HRZ region provided appropriate cultivar and sowing dates are combined with careful grazing management. Further work is required to refine grazing management to reduce reductions in grain yield in well-managed DP crops grazed prior to stem elongation.

Examining trends in abundance of an overexploited elasmobranch species in a nursery area closure

Determining the dynamics of ecological communities following periods of anthropogenic change is critical to assessing the effectiveness of management strategies. Several coastal areas in south-eastern Australia were proclaimed shark refuge areas (SRAs) following overfishing of the school shark (Galeorhinus galeus) during the 1940s and 1950s. In conjunction with catch reduction measures, these areas provide spatial protection for juvenile G. galeus. In the present study, we compared recent (2012–14) and historic (1991–97) longline catch rates to determine whether young-of-year (YOY) and juvenile G. galeus continue to use these nursery areas (42°47′60.00″S, 147°30′0.00″E). Our data suggest that YOY abundances in the SRAs may have increased, or at least have remained stable, since the 1990s. Data from research fishing conducted from 1947 to 1956 showed that YOY abundance in the SRA correlated well with overall stock abundance in the past. If this relationship still holds, our longline data indicate that the stock may be showing signs of recovery. However, the present-day importance of the SRA to overall stock recruitment, as well as the relationship between YOY abundance in the SRA and stock health, need to be resolved before monitoring of YOY abundance in the SRA can be used as a fisheries-independent stock-assessment tool.

TerraGIS – a web GIS for delivery of digital soil maps in cotton‐growing areas of Australia

AbstractEffective management of soil requires the spatial distribution of its various physical, chemical and hydrological properties. This is because properties, for example clay content, determine the ability of soil to hold cations and retain water. However, data acquisition is labour intensive and time‐consuming. To add value to the limited soil data, remote sensing (e.g. airborne gamma‐ray spectrometry) and proximal sensing, such as electromagnetic (EM) induction, are being used as ancillary data. Here, we provide examples of developing Digital Soil Maps (DSM) of soil physical, chemical and hydrological properties, for seven cotton‐growing areas of southeastern Australia, by coupling soil data with remote and proximal sensed ancillary data. A greater challenge is how to get these DSM to a stakeholder in a way that is useful for practical soil use and management. This study describes how we facilitate access to the DSMs, using a simple‐to‐use web GIS platform, called terraGIS. The platform is underpinned by Google Maps API, which is an open‐source development environment for building spatially enabled Internet applications. In conclusion, we consider that terraGIS and the supporting information, available on the sister web page (http://www.terragis.bees.unsw.edu.au/), allow easy access to explanation of DSM of soil properties, which are relevant to cotton growers, farm managers, consultants, extension staff, researchers, state and federal government agency personnel and policy analysts. Future work should be aimed at developing error budget maps to identify where additional soil and/or ancillary data is required to improve the accuracy of the DSMs.

Superpixel-Based Adaptive Kernel Selection for Angular Effect Normalization of Remote Sensing Images With Kernel Learning

Considering that satellites rarely acquire data from the exact nadir direction, angular effect normalization needs to be conducted as an important preprocessing step to correct reflectance observations from off-nadir directions into the nadir direction. Kernel-based bidirectional reflectance distribution function models have been employed for angular effect correction. The kernels used in the model are often predetermined and fixed for an entire image. However, the fixed kernels are unable to accommodate the various reflective characteristics of different ground cover types present in the imaged area. In this paper, we propose a kernel learning procedure that enables the flexible selection of kernels for different land cover types within a scene. The kernels are selected from kernel dictionaries that contain multiple candidate kernels. The selection is conducted on the superpixel level instead of the pixel level in order to reduce within-class variation and overcome the overfitting problem. Experiments are conducted on multiangular images acquired by the Sentinel-2A satellite over a rural area in southeastern Australia. Cross-validation results show that the proposed method is able to adaptively select appropriate kernels for different land cover types, leading to an improved performance for image normalization.

Landscape Structure and Mature Forest Biodiversity in Wet Eucalypt Forests: A Spatial Analysis of Timber Production Areas in South-Eastern Australia

Fire and timber harvesting can diminish the extent of older forests in the near term. The amount and configuration of mature and regenerating forest in the landscape (landscape structure) influences habitat suitability for mature-forest-associated species. We applied spatial analysis to describe the landscape structure of three wet eucalypt forest landscapes in south–eastern Australia and used the results from empirical biodiversity studies to frame interpretation of possible impacts on habitat suitability. We determined the extent of structurally mature forest, its reservation status, and the extent to which it may be edge affected. We also assessed how landscape structure potentially impacts the re-establishment of mature-forest-associated species into previously harvested areas through the proximity to (mature forest influence)—and extent of (landscape context)—mature forest in the surrounding landscape. Our analyses were designed to inform forest management initiatives that draw on these landscape-scale concepts. Central Highlands Victoria had less structurally mature eucalypt forest (4%) compared to North West Tasmania (14%) and Southern Forests Tasmania (21%). Detrimental effects of edge influence on structurally mature forest appeared relatively minor. Low levels of mature forest influence combined with low-medium surrounding mature forest cover (landscape context) indicate potential limitations on recolonisation of coupes by mature-forest-associated species. Our results vindicate the recent shift toward variable retention silviculture and landscape context planning. Our approach to landscape analysis provides a useful framework for other managed forest landscapes.

Assessment of model behavior and acceptable forcing data uncertainty in the context of land surface soil moisture estimation

The sources of uncertainty in land surface models are numerous and varied, from inaccuracies in forcing data to uncertainties in model structure and parameterizations. Majority of these uncertainties are strongly tied to the overall makeup of the model, but the input forcing data set is independent with its accuracy usually defined by the monitoring or the observation system. The impact of input forcing data on model estimation accuracy has been collectively acknowledged to be significant, yet its quantification and the level of uncertainty that is acceptable in the context of the land surface model to obtain a competitive estimation remain mostly unknown. A better understanding is needed about how models respond to input forcing data and what changes in these forcing variables can be accommodated without deteriorating optimal estimation of the model. As a result, this study determines the level of forcing data uncertainty that is acceptable in the Joint UK Land Environment Simulator (JULES) to competitively estimate soil moisture in the Yanco area in south eastern Australia. The study employs hydro genomic mapping to examine the temporal evolution of model decision variables from an archive of values obtained from soil moisture data assimilation. The data assimilation (DA) was undertaken using the advanced Evolutionary Data Assimilation. Our findings show that the input forcing data have significant impact on model output, 35% in root mean square error (RMSE) for 5cm depth of soil moisture and 15% in RMSE for 15cm depth of soil moisture. This specific quantification is crucial to illustrate the significance of input forcing data spread. The acceptable uncertainty determined based on dominant pathway has been validated and shown to be reliable for all forcing variables, so as to provide optimal soil moisture. These findings are crucial for DA in order to account for uncertainties that are meaningful from the model standpoint. Moreover, our results point to a proper treatment of input forcing data in general land surface and hydrological model estimation.