The relationship of boat movements to environmental management at some Queensland marinas

Marinas currently exist primarily to service recreational boats, and these vessels are a potential cause of both problems and opportunities in environmental management. Thus, on the one hand, destructive fuel and other pollutants may be expelled, boat wakes can cause littoral soil erosion, physical damage results from collisions with marine life, and litter and noise pollution occur in otherwise pristine habitat. Boats also provide access to otherwise inaccessible natural environments for educational and other management reasons. In this study, boat traffic at three large marinas located along the Queensland coastline has been field surveyed for introductory information. No attempt was made at this juncture to survey the behaviour of the boat crews and passengers (concerning actual destinations, activities on board, etc. or to survey the recreational boat industry. Such studies rely on boat registration records and personal questionnaires. Some other surveys relating to fishing draw on boat ramp surveys and direct submissions by recreational fishers; these provide some data on daily usage of boat ramps, but without particular attention to boats. We believe field observations of overall boat activities in the water are necessary for environmental management purposes. The aim of the survey was to provide information to help prioritize the potential impacts that boats’ activities have on the surrounding natural environment. Any impact by boats will be a product of their numbers, size, frequency of movement, carrying capacity and routes/destinations. The severity of impacts will dictate the appropriate management action.

Methods to achieve net environmental gain in the course of development in Queensland

To achieve best environmental management practice in Queensland, effort needs to be extended into the private sector. A Regional Landscape Strategy compiled for any substantial new proposal must identify the most promising technique(s) (from an available tool kit of 13) by which a developer (of any type) is more likely to sustain on-site resources while assisting government deliver its future plans in any region of the State. Offsetting may prove to be one of the most effective of these tools. However, policy must address‘offset land mitigation’, whereby the necessary financial incentives are introduced. Practicable methods by which offset sites can be selected, and measurement of their consequent environmental benefit, have now been devised and tested to assist this process.

A site selection process for environmental offsetting purposes in Queensland

A method of selecting land in any region of Queensland for offsetting purposes is devised, employing uniform standards. The procedure first requires that any core natural asset lands, Crown environmental lands, prime urban and agricultural lands, and highly contentious sites in the region be eliminated from consideration. Other land is then sought that is located between existing large reservations and the centre of greatest potential regional development/disturbance. Using the criteria of rehabilitation (rather than preservation) plus proximity to those officially defined Regional Ecosystems that are most threatened, adjacent sites that are described as ‘Cleared’ are identified in terms of agricultural land capability. Class IV lands – defined as those ‘which may be safely used for occasional cultivation with careful management’,2 ‘where it is favourably located for special usage’,3 and where it is ‘helpful to those who are interested in industry or regional planning or in reconstruction’4 – are examined for their appropriate area, for current tenure and for any conditions such as Mining Leases that may exist. The positive impacts from offsets on adjoining lands can then be designed to be significant; examples are also offered in respect of riparian areas and of Marine Parks. Criteria against which to measure performance for trading purposes include functional lift, with other case studies about this matter reported separately in this issue. The procedure takes no account of demand side economics (financial additionality), which requires commercial rather than environmental analysis.

Environmental management and wildlife in Queensland : a review of Queensland mammal species designated as scarce

From 19 authoritative lists with 164 entries of ‘endangered’ Australian mammal species, 39 species have been reported as extinct. When examined in the light of field conditions, the 18 of these species thought to be from Queensland consist of (a) species described from fragmentary museum material collected in the earliest days of exploration, (b) populations inferred to exist in Queensland by extrapolation from distribution records in neighbouring States or countries, (c) inhabitants of remote and harsh locations where search effort is extraordinarily difficult (especially in circumstances of drought or flooding). and/or (d) individuals that are clearly transitory or peripheral in distribution. ‘Rediscovery’ of such scarce species - a not infrequent occurrence - is nowadays attracting increasing attention. Management in respect of any scarce wildlife in Queensland presently derives from such official lists. The analyses here indicate that this method of prioritizing action needs review. This is especially so because action then tends to be centred on species chosen out of the lists for populist reasons and that mostly addresses Crown lands. There is reason to believe that the preferred management may lie private lands where casual observation has provided for rediscovery and where management is most desirable and practicable.

Measurement of the net environmental benefit of offsetting in Queensland

The process of offsetting land against unavoidable disturbance of development sites in Queensland will benefit from a method that allows the best possible selection to be made of alternative lands. With site selection now advocated through a combination of Regional Ecosystem and Land Capability classifications state-wide, a case study has determined methods of assessing the functional lift – that is, measures of net environmental gain – of such action. Outcomes with potentially high functional lift are determined, that offer promise not only for endangered ecosystems but also for managing adjacent conservation reserves.

Management of a tributyl tin issue in a marina development in Queensland

Tributyl tin (TBT) deposits in the sediments are one of many impacts that have been imposed on both the environment and the up-coming development of Boat Haven, Airlie Beach, Queensland. The current costly solution to this problem (that is, removal and re-burial) could be put in future to the credit of the developer rather than be treated (as at present) as a penalty. The Queensland Government’s Offsets Scheme provides an opportunity to promote effective conservation of regional landscapes. Because this scheme plans for offsetting in terrestrial vegetation systems through rehabilitation, so credits could be given to those approved developers who rehabilitate valuable marine habitats disturbed by TBT deposits.

A statistical framework for natural feature representation

This paper presents a robust stochastic framework for the incorporation of visual observations into conventional estimation, data fusion, navigation and control algorithms. The representation combines Isomap, a non-linear dimensionality reduction algorithm, with expectation maximization, a statistical learning scheme. The joint probability distribution of this representation is computed offline based on existing training data. The training phase of the algorithm results in a nonlinear and non-Gaussian likelihood model of natural features conditioned on the underlying visual states. This generative model can be used online to instantiate likelihoods corresponding to observed visual features in real-time. The instantiated likelihoods are expressed as a Gaussian mixture model and are conveniently integrated within existing non-linear filtering algorithms. Example applications based on real visual data from heterogenous, unstructured environments demonstrate the versatility of the generative models.

Learning articulated motion structures with Bayesian Networks

This paper presents a general methodology for learning articulated motions that, despite having non-linear correlations, are cyclical and have a defined pattern of behavior Using conventional algorithms to extract features from images, a Bayesian classifier is applied to cluster and classify features of the moving object. Clusters are then associated in different frames and structure learning algorithms for Bayesian networks are used to recover the structure of the motion. This framework is applied to the human gait analysis and tracking but applications include any coordinated movement such as multi-robots behavior analysis.

A Bayesian approach for place recognition

This paper presents a robust place recognition algorithm for mobile robots. The framework proposed combines nonlinear dimensionality reduction, nonlinear regression under noise, and variational Bayesian learning to create consistent probabilistic representations of places from images. These generative models are learnt from a few images and used for multi-class place recognition where classification is computed from a set of feature-vectors. Recognition can be performed in near real-time and accounts for complexity such as changes in illumination, occlusions and blurring. The algorithm was tested with a mobile robot in indoor and outdoor environments with sequences of 1579 and 3820 images respectively. This framework has several potential applications such as map building, autonomous navigation, search-rescue tasks and context recognition.

Rich probabilistic representations for bearing only decentralised data fusion

The aim of this paper is to demonstrate the validity of using Gaussian mixture models (GMM) for representing probabilistic distributions in a decentralised data fusion (DDF) framework. GMMs are a powerful and compact stochastic representation allowing efficient communication of feature properties in large scale decentralised sensor networks. It will be shown that GMMs provide a basis for analytical solutions to the update and prediction operations for general Bayesian filtering. Furthermore, a variant on the Covariance Intersect algorithm for Gaussian mixtures will be presented ensuring a conservative update for the fusion of correlated information between two nodes in the network. In addition, purely visual sensory data will be used to show that decentralised data fusion and tracking of non-Gaussian states observed by multiple autonomous vehicles is feasible.

Applying ISOMAP to the learning of hyperspectral image

In this paper, we present the application of a non-linear dimensionality reduction technique for the learning and probabilistic classification of hyperspectral image. Hyperspectral image spectroscopy is an emerging technique for geological investigations from airborne or orbital sensors. It gives much greater information content per pixel on the image than a normal colour image. This should greatly help with the autonomous identification of natural and manmade objects in unfamiliar terrains for robotic vehicles. However, the large information content of such data makes interpretation of hyperspectral images time-consuming and userintensive. We propose the use of Isomap, a non-linear manifold learning technique combined with Expectation Maximisation in graphical probabilistic models for learning and classification. Isomap is used to find the underlying manifold of the training data. This low dimensional representation of the hyperspectral data facilitates the learning of a Gaussian Mixture Model representation, whose joint probability distributions can be calculated offline. The learnt model is then applied to the hyperspectral image at runtime and data classification can be performed.

Prioritizing land and sea conservation investments to protect coral reefs

Background: Coral reefs have exceptional biodiversity, support the livelihoods of millions of people, and are threatened by multiple human activities on land (e.g. farming) and in the sea (e.g. overfishing). Most conservation efforts occur at local scales and, when effective, can increase the resilience of coral reefs to global threats such as climate change (e.g. warming water and ocean acidification). Limited resources for conservation require that we efficiently prioritize where and how to best sustain coral reef ecosystems.----- ----- Methodology/Principal Findings: Here we develop the first prioritization approach that can guide regional-scale conservation investments in land-and sea-based conservation actions that cost-effectively mitigate threats to coral reefs, and apply it to the Coral Triangle, an area of significant global attention and funding. Using information on threats to marine ecosystems, effectiveness of management actions at abating threats, and the management and opportunity costs of actions, we calculate the rate of return on investment in two conservation actions in sixteen ecoregions. We discover that marine conservation almost always trumps terrestrial conservation within any ecoregion, but terrestrial conservation in one ecoregion can be a better investment than marine conservation in another. We show how these results could be used to allocate a limited budget for conservation and compare them to priorities based on individual criteria.----- ----- Conclusions/Significance: Previous prioritization approaches do not consider both land and sea-based threats or the socioeconomic costs of conserving coral reefs. A simple and transparent approach like ours is essential to support effective coral reef conservation decisions in a large and diverse region like the Coral Triangle, but can be applied at any scale and to other marine ecosystems.

Validation Gating for Non-Linear Non-Gaussian Target Tracking

This paper develops a general theory of validation gating for non-linear non-Gaussian mod- els. Validation gates are used in target tracking to cull very unlikely measurement-to-track associa- tions, before remaining association ambiguities are handled by a more comprehensive (and expensive) data association scheme. The essential property of a gate is to accept a high percentage of correct associ- ations, thus maximising track accuracy, but provide a su±ciently tight bound to minimise the number of ambiguous associations. For linear Gaussian systems, the ellipsoidal vali- dation gate is standard, and possesses the statistical property whereby a given threshold will accept a cer- tain percentage of true associations. This property does not hold for non-linear non-Gaussian models. As a system departs from linear-Gaussian, the ellip- soid gate tends to reject a higher than expected pro- portion of correct associations and permit an excess of false ones. In this paper, the concept of the ellip- soidal gate is extended to permit correct statistics for the non-linear non-Gaussian case. The new gate is demonstrated by a bearing-only tracking example.