Linking riparian vegetation spatial structure in Australian tropical savannas to ecosystem health indicators: semi-variogram analysis of high spatial resolution satellite imagery

Government agencies responsible for riparian environments are assessing the combined utility of field survey and remote sensing for mapping and monitoring indicators of riparian zone health. The objective of this work was to determine if the structural attributes of savanna riparian zones in northern Australia can be detected from commercially available remotely sensed image data. Two QuickBird images and coincident field data covering sections of the Daly River and the South Alligator River - Barramundie Creek in the Northern Territory were used. Semi-variograms were calculated to determine the characteristic spatial scales of riparian zone features, both vegetative and landform. Interpretation of semi-variograms showed that structural dimensions of riparian environments could be detected and estimated from the QuickBird image data. The results also show that selecting the correct spatial resolution and spectral bands is essential to maximize the accuracy of mapping spatial characteristics of savanna riparian features. The distribution of foliage projective cover of riparian vegetation affected spectral reflectance variations in individual spectral bands differently. Pan-sharpened image data enabled small-scale information extraction (< 6 m) on riparian zone structural parameters. The semi-variogram analysis results provide the basis for an inversion approach using high spatial resolution satellite image data to map indicators of savanna riparian zone health.

Monitoring the condition of savanna riparian zones in Northern Australia using high spatial resolution imagery and a field based rapid assessment method

Government agencies responsible for riparian environments are assessing the combined utility of field survey and remote sensing for mapping and monitoring indicators of riparian zone condition. The objective of this work was to compare the Tropical Rapid Appraisal of Riparian Condition (TRARC) method to a satellite image based approach. TRARC was developed for rapid assessment of the environmental condition of savanna riparian zones. The comparison assessed mapping accuracy, representativeness of TRARC assessment, cost-effectiveness, and suitability for multi-temporal analysis. Two multi-spectral QuickBird images captured in 2004 and 2005 and coincident field data covering sections of the Daly River in the Northern Territory, Australia were used in this work. Both field and image data were processed to map riparian health indicators (RHIs) including percentage canopy cover, organic litter, canopy continuity, stream bank stability, and extent of tree clearing. Spectral vegetation indices, image segmentation and supervised classification were used to produce RHI maps. QuickBird image data were used to examine if the spatial distribution of TRARC transects provided a representative sample of ground based RHI measurements. Results showed that TRARC transects were required to cover at least 3% of the study area to obtain a representative sample. The mapping accuracy and costs of the image based approach were compared to those of the ground based TRARC approach. Results proved that TRARC was more cost-effective at smaller scales (1-100km), while image based assessment becomes more feasible at regional scales (100-1000km). Finally, the ability to use both the image and field based approaches for multi-temporal analysis of RHIs was assessed. Change detection analysis demonstrated that image data can provide detailed information on gradual change, while the TRARC method was only able to identify more gross scale changes. In conclusion, results from both methods were considered to complement each other if used at appropriate spatial scales.

Remotely sensed data for ecosystem analyses: Combining hierarchy and scene models

Remotely sensed data have been used extensively for environmental monitoring and modeling at a number of spatial scales; however, a limited range of satellite imaging systems often. constrained the scales of these analyses. A wider variety of data sets is now available, allowing image data to be selected to match the scale of environmental structure(s) or process(es) being examined. A framework is presented for use by environmental scientists and managers, enabling their spatial data collection needs to be linked to a suitable form of remotely sensed data. A six-step approach is used, combining image spatial analysis and scaling tools, within the context of hierarchy theory. The main steps involved are: (1) identification of information requirements for the monitoring or management problem; (2) development of ideal image dimensions (scene model), (3) exploratory analysis of existing remotely sensed data using scaling techniques, (4) selection and evaluation of suitable remotely sensed data based on the scene model, (5) selection of suitable spatial analytic techniques to meet information requirements, and (6) cost-benefit analysis. Results from a case study show that the framework provided an objective mechanism to identify relevant aspects of the monitoring problem and environmental characteristics for selecting remotely sensed data and analysis techniques.

Water quality monitoring: A combined approach to investigate gradients of change in the Great Barrier Reef, Australia

For the managers of a region as large as the Great Barrier Reef, it is a challenge to develop a cost effective monitoring program, with appropriate temporal and spatial resolution to detect changes in water quality. The current study compares water quality data (phytoplankton abundance and water clarity) from remote sensing with field sampling (continuous underway profiles of water quality and fixed site sampling) at different spatial scales in the Great Barrier Reef north of Mackay (20 degrees S). Five transects (20-30 km long) were conducted from clean oceanic water to the turbid waters adjacent to the mainland. The different data sources demonstrated high correlations when compared on a similar spatial scale (18 fixed sites). However, each data source also contributed unique information that could not be obtained by the other techniques. A combination of remote sensing, underway sampling and fixed stations will deliver the best spatial and temporal monitoring of water quality in the Great Barrier Reef. (c) 2004 Elsevier Ltd. All rights reserved.

Genetic resource impacts of habitat loss and degradation; reconciling empirical evidence and predicted theory for neotropical trees

The theoretical impacts of anthropogenic habitat degradation on genetic resources have been well articulated. Here we use a simulation approach to assess the magnitude of expected genetic change, and review 31 studies of 23 neotropical tree species to assess whether empirical case studies conform to theory. Major differences in the sensitivity of measures to detect the genetic health of degraded populations were obvious. Most studies employing genetic diversity (nine out of 13) found no significant consequences, yet most that assessed progeny inbreeding (six out of eight), reproductive output (seven out of 10) and fitness (all six) highlighted significant impacts. These observations are in line with theory, where inbreeding is observed immediately following impact, but genetic diversity is lost slowly over subsequent generations, which for trees may take decades. Studies also highlight the ecological, not just genetic, consequences of habitat degradation that can cause reduced seed set and progeny fitness. Unexpectedly, two studies examining pollen flow using paternity analysis highlight an extensive network of gene flow at smaller spatial scales (less than 10 km). Gene flow can thus mitigate against loss of genetic diversity and assist in long-term population viability, even in degraded landscapes. Unfortunately, the surveyed studies were too few and heterogeneous to examine concepts of population size thresholds and genetic resilience in relation to life history. Future suggested research priorities include undertaking integrated studies on a range of species in the same landscapes; better documentation of the extent and duration of impact; and most importantly, combining neutral marker, pollination dynamics, ecological consequences, and progeny fitness assessment within single studies.

Detecting the effects of physical disturbance on benthic assemblages in a subtropical estuary: A Beyond BACI approach

The effects of dredging on the benthic communities in the Noosa River, a subtropical estuary in SE Queensland, Australia, were examined using a 'Beyond BACF experimental design. Changes in the numbers and types of animals and characteristics of the sediments in response to dredging in the coarse sandy sediments near the mouth of the estuary were compared with those occurring naturally in two control regions. Samples were collected twice before and twice after the dredging operations, at multiple spatial scales, ranging from metres to kilometres. Significant effects from the dredging were detected on the abundance of some polychaetes and bivalves and two measures of diversity (numbers of polychaete families and total taxonomic richness). In addition, the dredging caused a significant increase in the diversity of sediment particle sizes found in the dredged region compared with elsewhere. Community composition in the dredged region was more similar to that in the control regions after dredging than before. Changes in the characteristics of the sedimentary environment as a result of the dredging appeared to lead to the benthic communities of the dredged region becoming more similar to those elsewhere in the estuary, so dredging in this system may have led to the loss or reduction in area of a specific type of habitat in the estuary with implications for overall patterns of biodiversity and ecosystem function. (c) 2006 Elsevier B.V. All rights reserved.

Planted forests and biodiversity

Expansion of planted forests and intensification of their management has raised concerns among forest managers and the public over the implications of these trends for sustainable production and conservation of forest biological diversity. We review the current state of knowledge on the impacts of plantation forestry on genetic and species diversity at different spatial scales and discuss the economic and ecological implications of biodiversity management within plantation stands and landscapes. Managing plantations to produce goods such as timber while also enhancing ecological services such as biodiversity involves tradeoffs, which can be made only with a clear understanding of the ecological context of plantations in the broader landscape and agreement among stakeholders on the desired balance of goods and ecological services from plantations.

Species accumulation curves and their applications in parasite ecology

Species accumulation curves (SACs) chart the increase in recovery of new species as a function of some measure of sampling effort. Studies of parasite diversity can benefit from the application of SACs, both as empirical tools to guide sampling efforts and predict richness, and because their properties are informative about community patterns and the structure of parasite diversity. SACs can be used to infer interactivity in parasite infra-communities, to partition species richness into contributions from different spatial scales and different levels of the host hierarchy (individuals, populations and communities) or to identify modes of community assembly (niche versus dispersal). A historical tendency to treat individual hosts as statistically equivalent replicates (quadrats) seemingly satisfies the sample-based subgroup of SACs but care is required in this because of the inequality of hosts as sampling units. Knowledge of the true distribution of parasite richness over multiple host-derived and spatial scales is far from complete but SACs can improve the understanding of diversity patterns in parasite assemblages.

Advanced computing for systems biology

Systems biology is based on computational modelling and simulation of large networks of interacting components. Models may be intended to capture processes, mechanisms, components and interactions at different levels of fidelity. Input data are often large and geographically disperse, and may require the computation to be moved to the data, not vice versa. In addition, complex system-level problems require collaboration across institutions and disciplines. Grid computing can offer robust, scaleable solutions for distributed data, compute and expertise. We illustrate some of the range of computational and data requirements in systems biology with three case studies: one requiring large computation but small data (orthologue mapping in comparative genomics), a second involving complex terabyte data (the Visible Cell project) and a third that is both computationally and data-intensive (simulations at multiple temporal and spatial scales). Authentication, authorisation and audit systems are currently not well scalable and may present bottlenecks for distributed collaboration particularly where outcomes may be commercialised. Challenges remain in providing lightweight standards to facilitate the penetration of robust, scalable grid-type computing into diverse user communities to meet the evolving demands of systems biology.

Characterizing a tropical deforestation wave: a dynamic spatial analysis of a deforestation hotspot in the Colombian Amazon

Tropical deforestation is the major contemporary threat to global biodiversity, because a diminishing extent of tropical forests supports the majority of the Earth's biodiversity. Forest clearing is often spatially concentrated in regions where human land use pressures, either planned or unplanned, increase the likelihood of deforestation. However, it is not a random process, but often moves in waves originating from settled areas. We investigate the spatial dynamics of land cover change in a tropical deforestation hotspot in the Colombian Amazon. We apply a forest cover zoning approach which permitted: calculation of colonization speed; comparative spatial analysis of patterns of deforestation and regeneration; analysis of spatial patterns of mature and recently regenerated forests; and the identification of local-level hotspots experiencing the fastest deforestation or regeneration. The colonization frontline moved at an average of 0.84 km yr(-1) from 1989 to 2002, resulting in the clearing of 3400 ha yr(-1) of forests beyond the 90% forest cover line. The dynamics of forest clearing varied across the colonization front according to the amount of forest in the landscape, but was spatially concentrated in well-defined 'local hotspots' of deforestation and forest regeneration. Behind the deforestation front, the transformed landscape mosaic is composed of cropping and grazing lands interspersed with mature forest fragments and patches of recently regenerated forests. We discuss the implications of the patterns of forest loss and fragmentation for biodiversity conservation within a framework of dynamic conservation planning.

Ross River virus disease clusters and spatial relationship with mosquito biting exposure in Redland Shire, southern Queensland, Australia

The spatial heterogeneity in the risk of Ross River virus (family Togaviridae, genus Alphavirus, RRV) disease, the most common mosquito-borne disease in Australia, was examined in Redland Shire in southern Queensland, Australia. Disease cases, complaints from residents of intense mosquito biting exposure, and human population data were mapped using a geographic information system. Surface maps of RRV disease age-sex standardized morbidity ratios and mosquito biting complaint morbidity ratios were created. To determine whether there was significant spatial variation in disease and complaint patterns, a spatial scan analysis method was used to test whether the number of cases and complaints was distributed according to underlying population at risk. Several noncontiguous areas in proximity to productive saline water habitats of Aedes vigilax (Skuse), a recognized vector of RRV, had higher than expected numbers of RRV disease cases and complaints. Disease rates in human populations in areas which had high numbers of adult Ae. vigilax in carbon dioxide- and octenol-baited light traps were up to 2.9 times those in areas that rarely had high numbers of mosquitoes. It was estimated that targeted control of adult Ae. vigilax in these high-risk areas could potentially reduce the RRV disease incidence by an average of 13.6%. Spatial correlation was found between RRV disease risk and complaints from residents of mosquito biting. Based on historical patterns of RRV transmission throughout Redland Shire and estimated future human population growth in areas with higher than average RRV disease incidence, it was estimated that RRV incidence rates will increase by 8% between 2001 and 2021. The use of arbitrary administrative areas that ranged in size from 4.6 to 318.3 km2, has the potential to mask any small scale heterogeneity in disease patterns. With the availability of georeferenced data sets and high-resolution imagery, it is becoming more feasible to undertake spatial analyses at relatively small scales.