Recent developments in methods to detect impacts in coastal benthic habitats in Western Australia

Abstract

Benthic habitats are those areas of seabed below the highest astronomical tide that support living organisms and influence the distribution and abundance of benthic primary producers and associated fauna. These habitats are generally regarded as important functional drivers of biodiversity and productivity at an ecosystem level. In coastal areas they are also often characterised by a high degree of spatial and temporal variance. During coastal and port developments and operations, detection of impacts on benthic habitats and associated biota is pivotal to understanding the system-scale effects that may occur as a result of anthropogenic activities. However, the inherent variability of these habitats introduces a degree of complexity that presents a challenge in sampling design and interpretation of results in environmental impact assessments. Effective monitoring of these variable benthic environments is an imperative in marine related project environmental impact assessments and can represent a significant component of project costs. Here we discuss improved quantitative and qualitative methods to detect impacts that also address the spatial and temporal variance commonly encountered in impact assessment programs in coastal environments including ports.These improved methods include designs for monitoring benthic assemblages including corals using diver-free sampling techniques; techniques to remove the chemical species of concern from saline matrices thereby allowing greater precision; speciation of potential contaminants using stable isotopic ‘fingerprinting’ methods for identifying contaminant source and provenance in benthic environments; and organic isotope methods for establishing historical baselines and characterising food web dynamics in coastal fish habitats are described. Finally, statistical methods for effectively presenting and interpreting space-time data are discussed. The methods provide means to better characterise and contextualise spatial and temporal data in indicators of interest and improve the assessment of potential impacts and changes at a system level.