Benthic and substrate cover data derived from a time series of photo-transect surveys for the Eastern Banks, Moreton Bay Australia, 2004-2015

This paper describes seagrass species and percentage cover point-based field data sets derived from georeferenced photo transects. Annually or biannually over a ten year period (2004-2015) data sets were collected using 30-50 transects, 500-800 m in length distributed across a 142 km**2 shallow, clear water seagrass habitat, the Eastern Banks, Moreton Bay, Australia. Each of the eight data sets include seagrass property information derived from approximately 3000 georeferenced, downward looking photographs captured at 2-4 m intervals along the transects. Photographs were manually interpreted to estimate seagrass species composition and percentage cover (Coral Point Count excel; CPCe). Understanding seagrass biology, ecology and dynamics for scientific and management purposes requires point-based data on species composition and cover. This data set, and the methods used to derive it are a globally unique example for seagrass ecological applications. It provides the basis for multiple further studies at this site, regional to global comparative studies, and, for the design of similar monitoring programs elsewhere.

Motivation, development and validation of a new spectral greenness index : a spectral dimension related to foliage projective cover

A method is presented for the development of a regional Landsat-5 Thematic Mapper (TM) and Landsat-7 Enhanced Thematic Mapper plus (ETM+) spectral greenness index, coherent with a six-dimensional index set, based on a single ETM+ spectral image of a reference landscape. The first three indices of the set are determined by a polar transformation of the first three principal components of the reference image and relate to scene brightness, percent foliage projective cover (FPC) and water related features. The remaining three principal components, of diminishing significance with respect to the reference image, complete the set. The reference landscape, a 2200 km2 area containing a mix of cattle pasture, native woodland and forest, is located near Injune in South East Queensland, Australia. The indices developed from the reference image were tested using TM spectral images from 19 regionally dispersed areas in Queensland, representative of dissimilar landscapes containing woody vegetation ranging from tall closed forest to low open woodland. Examples of image transformations and two-dimensional feature space plots are used to demonstrate image interpretations related to the first three indices. Coherent, sensible, interpretations of landscape features in images composed of the first three indices can be made in terms of brightness (red), foliage cover (green) and water (blue). A limited comparison is made with similar existing indices. The proposed greenness index was found to be very strongly related to FPC and insensitive to smoke. A novel Bayesian, bounded space, modelling method, was used to validate the greenness index as a good predictor of FPC. Airborne LiDAR (Light Detection and Ranging) estimates of FPC along transects of the 19 sites provided the training and validation data. Other spectral indices from the set were found to be useful as model covariates that could improve FPC predictions. They act to adjust the greenness/FPC relationship to suit different spectral backgrounds. The inclusion of an external meteorological covariate showed that further improvements to regional-scale predictions of FPC could be gained over those based on spectral indices alone.

Our neighbour's view : Australian media cover of PNG

This chapter reviews the incidence of coverage of Papua New Guinea affairs in the Australian press and in Australian broadcast media. It presents the findings of a formal monitoring of selected newspaper coverage and news broadcasts of the leading Australian television and radio outlets. The study also includes news stories published on ABC Online. The findings for print media suggest that coverage of PNG is inadequate and may be contributing towards negative images of that country in Australia. The broadcast monitoring found also that beyond the ABC's regular and balanced coverage, there was very little mention of PNG on Australian airwaves. The deployment of resources by the ABC was seen as a potential model for increased quantity and quality of coverage, with its maintenance of a correspondent and office in the country, and use of reports from PNG across a wide range of programs. The investigation noted some early indications of a shift in media attention, following the election of a new government in Australia in 2007, which gave some priority attention to PNG including a visit by the then Prime Minister.

Simulating land cover changes and their impacts on land surface temperature in Dhaka, Bangladesh

Despite research that has been conducted elsewhere, little is known, to-date, about land cover dynamics and their impacts on land surface temperature (LST) in fast growing mega cities of developing countries. Landsat satellite images of 1989, 1999, and 2009 of Dhaka Metropolitan (DMP) area were used for analysis. This study first identified patterns of land cover changes between the periods and investigated their impacts on LST; second, applied artificial neural network to simulate land cover changes for 2019 and 2029; and finally, estimated their impacts on LST in respective periods. Simulation results show that if the current trend continues, 56% and 87% of the DMP area will likely to experience temperatures in the range of greater than or equal to 30°C in 2019 and 2029, respectively. The findings possess a major challenge for urban planners working in similar contexts. However, the technique presented in this paper would help them to quantify the impacts of different scenarios (e.g., vegetation loss to accommodate urban growth) on LST and consequently to devise appropriate policy measures.

Understanding Uncertainties in Non-Linear Population Trajectories: A Bayesian Semi-Parametric Hierarchical Approach to Large-Scale Surveys of Coral Cover

Recently, attempts to improve decision making in species management have focussed on uncertainties associated with modelling temporal fluctuations in populations. Reducing model uncertainty is challenging; while larger samples improve estimation of species trajectories and reduce statistical errors, they typically amplify variability in observed trajectories. In particular, traditional modelling approaches aimed at estimating population trajectories usually do not account well for nonlinearities and uncertainties associated with multi-scale observations characteristic of large spatio-temporal surveys. We present a Bayesian semi-parametric hierarchical model for simultaneously quantifying uncertainties associated with model structure and parameters, and scale-specific variability over time. We estimate uncertainty across a four-tiered spatial hierarchy of coral cover from the Great Barrier Reef. Coral variability is well described; however, our results show that, in the absence of additional model specifications, conclusions regarding coral trajectories become highly uncertain when considering multiple reefs, suggesting that management should focus more at the scale of individual reefs. The approach presented facilitates the description and estimation of population trajectories and associated uncertainties when variability cannot be attributed to specific causes and origins. We argue that our model can unlock value contained in large-scale datasets, provide guidance for understanding sources of uncertainty, and support better informed decision making

Hydrological consequences of land-cover change: Quantifying the influence of plants on soil moisture with time-lapse electrical resistivity

Electrical resistivity of soils and sediments is strongly influenced by the presence of interstitial water. Taking advantage of this dependency, electrical-resistivity imaging (ERI) can be effectively utilized to estimate subsurface soil-moisture distributions. The ability to obtain spatially extensive data combined with time-lapse measurements provides further opportunities to understand links between land use and climate processes. In natural settings, spatial and temporal changes in temperature and porewater salinity influence the relationship between soil moisture and electrical resistivity. Apart from environmental factors, technical, theoretical, and methodological ambiguities may also interfere with accurate estimation of soil moisture from ERI data. We have examined several of these complicating factors using data from a two-year study at a forest-grassland ecotone, a boundary between neighboring but different plant communities.At this site, temperature variability accounts for approximately 20-45 of resistivity changes from cold winter to warm summer months. Temporal changes in groundwater conductivity (mean=650 S/cm =57.7) and a roughly 100-S/cm spatial difference between the forest and grassland had only a minor influence on the moisture estimates. Significant seasonal fluctuations in temperature and precipitation had negligible influence on the basic measurement errors in data sets. Extracting accurate temporal changes from ERI can be hindered by nonuniqueness of the inversion process and uncertainties related to time-lapse inversion schemes. The accuracy of soil moisture obtained from ERI depends on all of these factors, in addition to empirical parameters that define the petrophysical soil-moisture/resistivity relationship. Many of the complicating factors and modifying variables to accurately quantify soil moisture changes with ERI can be accounted for using field and theoretical principles.

Spatially explicit perceptions of ecosystem services and land cover change in forested regions of Borneo

Spatially explicit information on local perceptions of ecosystem services is needed to inform land use planning within rapidly changing landscapes. In this paper we spatially modelled local people's use and perceptions of benefits from forest ecosystem services in Borneo, from interviews of 1837 people in 185 villages. Questions related to provisioning, cultural/spiritual, regulating and supporting ecosystem services derived from forest, and attitudes towards forest conversion. We used boosted regression trees (BRTs) to combine interview data with social and environmental predictors to understand spatial variation of perceptions across Borneo. Our results show that people use a variety of products from intact and highly degraded forests. Perceptions of benefits from forests were strongest: in human-altered forest landscapes for cultural and spiritual benefits; in human-altered and intact forests landscapes for health benefits; intact forest for direct health benefits, such as medicinal plants; and in regions with little forest and extensive plantations, for environmental benefits, such as climatic impacts from deforestation. Forest clearing for small scale agriculture was predicted to be widely supported yet less so for large-scale agriculture. Understanding perceptions of rural communities in dynamic, multi-use landscapes is important where people are often directly affected by the decline in ecosystem services.