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Abstract: To date seagrass monitoring has involved the removal of seagrass from its environment. In fragile or highly disturbed systems, monitoring using destructive techniques may interfere with the environment or add to the burden of disturbance. Video photography is a form of non-destructive monitoring that does not require the removal of seagrass or interference with the environment and has the potential to be a valuable tool in monitoring seagrass systems. This study investigated the efficacy of video photography as a tool for detecting change in seagrass cover, using the temperate Australian species Amphibolis antarctica (Labill.) Sonder ex Aschers. Using visual and random point estimates of seagrass cover from video footage, it was possible to determine the minimum sample size (number of random video frames) needed to detect change in seagrass cover, the minimum detectable change in cover and the probability of the monitoring design committing a Type II error. Video footage was examined at three scales: transects (m apart), sites (km apart) and regions (tens of km apart). Using visual and random point estimation techniques, a minimum sample size of ten quadrats per transect was required to detect change in uniform and variable seagrass cover. With ten quadrats it was possible to identify a minimum detectable change in cover of 15% for uniform and 30% for variable seagrass cover. Power analysis was used to determine the probability of committing a Type II error from the data. Region level data had low power, corresponding to a high risk of committing a Type II error. Site and transect level data had high power corresponding to a low risk of committing a Type II error. Based on this study''s data, managers using video to monitor for change in seagrass cover are advised to use data from the smaller scale, for example, site and transect level data. By using data from the smaller scale, managers will have a low risk of incorrectly concluding there has not been a disturbance when one has actually occurred. [Copyright &y& Elsevier]

Abstract A systematic approach to formulate consistent, technically robust and scientifically tractable problems will facilitate achieving innovative and effective solutions in risk evaluation. The fundamentals of problem formulation have been adapted from environmental and human health risk assessments. A structured problem formulation enables focus on describing and evaluating the specifics of the problem to be solved, instead of immediately creating solutions. First the problem should be framed to provide clarity and gain agreement on the problem to be addressed, resulting in a specific problem statement. Second the problem is explored in order to transform it into an operational state through questions to answer, hypotheses to test, and represented by a conceptual model. Finally the approach to testing hypotheses is mapped and the analysis plan is developed to address the problem statement. This simple adaptable framework can be applied to any circumstance to resolve a specific problem and describe a path to resolution. Graphical abstract Image 1 Highlights • Simple problem formulation framework facilitates innovative and effective solutions. • Describe and evaluate problem to solve instead of immediately creating solutions. • A framework that provides clarity on the problem to be addressed. • Transformation of the problem into an operational state. • Problem represented by conceptual model to facilitate developing a successful plan. [ABSTRACT FROM AUTHOR]

Broad scale monitoring of marine diversity is challenging, with many techniques limited to sampling only a small portion of the actual diversity present. For this reason, molecular methods, such as environmental DNA (eDNA) metabarcoding, are becoming increasingly popular, especially in locations that are logistically difficult to sample (for example, ports, offshore platforms and other restricted marine infrastructure). eDNA studies in marine environment have predominantly focused on the collection and isolation of DNA from water. Recent literature suggests this approach may not be effective for detecting taxa from adjacent epibenthic substrates. In this study we compare a visual, morphological approach utilizing three eDNA sampling methods targeting the water column and four methods targeting the epibenthic substrate: three methods scraping and one swabbing the epibenthos. Sampling was completed at two depths on and adjacent to a decommissioned jetty, with all methods detecting significant community compositions. Only 2.8% of family-level taxonomic detections were found across all eDNA sampling methods, and all but one scraping method were able to detect fine scale community shifts associated with depth. The epibenthic sampling methods ranged from 50 to 117 families detected, with those methods that collected bulk DNA material (all scraping methods) detecting considerably lower diversity. The methods targeting the water column detected between 78 and 154 families, with the polyurethane foam (PUF) tow method detecting the highest number of families, indicating that the physical matrix may be better at retaining traces of DNA within the water column. While further validation is required, this study provides a base toolkit for the broad characterisation of vertical diversity at both natural and man-made marine structures such as oil and gas platforms. Additionally, these highly varied results demonstrate the importance of appropriate substrate selection to sample for a given study objective and indicates that multiple sampling methods may be required to holistically characterise diversity across a chosen environment using eDNA. • Only 2.8% of family-level taxonomic detections were found across all eDNA sampling methods. • Epibenthic methods detection ranged from 50 to 117 families, with methods collecting bulk organic material detecting lower diversity. • Methods targeting the water column detected between 78 and 154 families. • Increased eDNA concentration does not necessarily correspond to increased diversity. [ABSTRACT FROM AUTHOR]

Coastal ecosystem management typically relies on subjective interpretation of scientific understanding, with limited methods for explicitly incorporating process knowledge into decisions that must meet multiple, potentially competing stakeholder objectives. Conversely, the scientific community lacks methods for identifying which advancements in system understanding would have the highest value to decision-makers. A case in point is barrier island restoration, where decision-makers lack tools to objectively use system understanding to determine how to optimally use limited contingency funds when project construction in this dynamic environment does not proceed as expected. In this study, collaborative structured decision-making (SDM) was evaluated as an approach to incorporate process understanding into mid-construction decisions and to identify priority gaps in knowledge from a management perspective. The focus was a barrier island restoration project at Ship Island, Mississippi, where sand will be used to close an extensive breach that currently divides the island. SDM was used to estimate damage that may occur during construction, and guide repair decisions within the confines of limited availability of sand and funding to minimize adverse impacts to project objectives. Sand was identified as more limiting than funds, and unrepaired major breaching would negatively impact objectives. Repairing minor damage immediately was determined to be generally more cost effective (depending on the longshore extent) than risking more damage to a weakened project. Key gaps in process-understanding relative to project management were identified as the relationship of island width to breach formation; the amounts of sand lost during breaching, lowering, or narrowing of the berm; the potential for minor breaches to self-heal versus developing into a major breach; and the relationship between upstream nourishment and resiliency of the berm to storms. This application is a prototype for using structured decision-making in support of engineering projects in dynamic environments where mid-construction decisions may arise; highlights uncertainty about barrier island physical processes that limit the ability to make robust decisions; and demonstrates the potential for direct incorporation of process-based models in a formal adaptive management decision framework. [ABSTRACT FROM AUTHOR]