A lesson from cyclone Larry: An untold story of the success of good coastal planning

When tropical cyclone Larry crossed the Queensland coast on 20 March 2006, commercial, recreational and naval vessels in the port of Cairns, 60 km north of the eye of the cyclone and others closer to the eye, were protected from the destructive winds by sheltering in deep mangrove creeks in Trinity Inlet and off other coastal rivers. The Trinity Inlet mangroves are protected under the comprehensive multi-use Trinity Inlet Management Plan, agreed by the local and state government agencies (Cairns City Council, the Cairns Port Authority and the Queensland Government). Using this Australian example and one from the town of Palompon in Leyte province, central Philippines, we show how long-term mangrove habitat protection resulting from well-conceived coastal planning can deliver important economic and infrastructure benefits.

Otolith morphology of four mackerel species (Scomberomorus spp.) in Australia: Species differentiation and prediction for fisheries monitoring and assessment

Four species of large mackerels (Scomberomorus spp.) co-occur in the waters off northern Australia and are important to fisheries in the region. State fisheries agencies monitor these species for fisheries assessment; however, data inaccuracies may exist due to difficulties with identification of these closely related species, particularly when specimens are incomplete from fish processing. This study examined the efficacy of using otolith morphometrics to differentiate and predict among the four mackerel species off northeastern Australia. Seven otolith measurements and five shape indices were recorded from 555 mackerel specimens. Multivariate modelling including linear discriminant analysis (LDA) and support vector machines, successfully differentiated among the four species based on otolith morphometrics. Cross validation determined a predictive accuracy of at least 96% for both models. An optimum predictive model for the four mackerel species was an LDA model that included fork length, feret length, feret width, perimeter, area, roundness, form factor and rectangularity as explanatory variables. This analysis may improve the accuracy of fisheries monitoring, the estimates based on this monitoring (i.e. mortality rate) and the overall management of mackerel species in Australia.