Informing the management of multiple stressors on estuarine ecosystems using an expert-based Bayesian Network model.

The approach of applying stressor load limits or thresholds to aid estuarine management is being explored in many global case studies. However, there is growing concern regarding the influence of multiple stressors and their cumulative effects on the functioning of estuarine ecosystems due to the considerable uncertainty around stressor interactions. Recognising that empirical data limitations hinder parameterisation of detailed models of estuarine ecosystem responses to multiple stressors (suspended sediment, sediment mud and metal content, and nitrogen inputs), an expert driven Bayesian network (BN) was developed and validated. Overall, trends in estuarine condition predicted by the BN model were well supported by field observations, including results that were markedly higher than random (71-84% concordance), providing confidence in the overall model dynamics. The general BN framework was then applied to a case study estuary to demonstrate the model's utility for informing management decisions. Results indicated that reductions in suspended sediment loading were likely to result in improvements in estuarine condition, which was further improved by reductions in sediment mud and metal content, with an increased likelihood of high abundance of ecological communities relative to baseline conditions. Notably, reductions in suspended sediment were also associated with an increased probability of high nuisance macroalgae and phytoplankton if nutrient loading was not also reduced (associated with increased water column light penetration). Our results highlight that if stressor limit setting is to be implemented, limits must incorporate ecosystem responses to cumulative stressors, consider the present and desired future condition of the estuary of interest, and account for the likelihood of unexpected ecological outcomes regardless of whether the experts (or empirical data) suggest a threshold has or has not been triggered.

Major conservation policy issues for biodiversity in Oceania.

Oceania is a diverse region encompassing Australia, Melanesia, Micronesia, New Zealand, and Polynesia, and it contains six of the world's 39 hotspots of diversity. It has a poor record for extinctions, particularly for birds on islands and mammals. Major causes include habitat loss and degradation, invasive species, and overexploitation. We identified six major threatening processes (habitat loss and degradation, invasive species, climate change, overexploitation, pollution, and disease) based on a comprehensive review of the literature and for each developed a set of conservation policies. Many policies reflect the urgent need to deal with the effects of burgeoning human populations (expected to increase significantly in the region) on biodiversity. There is considerable difference in resources for conservation, including people and available scientific information, which are heavily biased toward more developed countries in Oceania. Most scientific publications analyzed for four threats (habitat loss, invasive species, overexploitation, and pollution) are from developed countries: 88.6% of Web of Science publications were from Australia (53.7%), New Zealand (24.3%), and Hawaiian Islands (10.5%). Many island states have limited resources or expertise. Even countries that do (e.g., Australia, New Zealand) have ongoing and emerging significant challenges, particularly with the interactive effects of climate change. Oceania will require the implementation of effective policies for conservation if the region's poor record on extinctions is not to continue.