Developing a Toolbox of Predictive Models for the Monitoring and Management of KEFs and CMRs in the North and North-west regions [ 2015-07-01 - ]

Research Grant

[Cite as]

Researchers: Karen Miller (Principal investigator)

Brief description


Year 1 (to Dec 2015): During the first year the project will:

• Collate existing information from various sources (NERP, WAMSI, IMOS and a range of joint projects with Industry) and develop a set of maps and other information products that document the distribution of communities and key species including megafauna in the North and NW region, and identify areas of vulnerability in the face of natural and anthropogenic impacts. These products will draw not only on the significant repositories of biological and physical data, but will also use currently available models to predict the existence of likely new areas of interest that can be sampled in future years. Integrated data collation and modelling in a case-study context will form an input to end-user and stakeholder workshops.

• Convene workshops with end-users and key stakeholders (i.e. DoE, AFMA, NOPSEMA, DFAT, Oil & Gas industry, fishing industry, Indigenous communities) to discuss and refine information needs in the context of decision settings. These workshops will focus on identifying the management framework for the North and NW Regions, and how knowledge gaps might be filled to meet the needs for monitoring, management and risk assessments.

• Evaluate existing predictive models with respect to their utility for addressing potential management and monitoring needs. These models include the 4D connectivity model (GA), pelagic hotspot model (UWA), benthic community model for the offshore banks and shoals (AIMS) and models of megafauna migration pathways and habitat use (AIMS).

• Apply existing models to identify areas of greatest uncertainty and potential data gaps and make testable predictions that can be assessed by data collected from future field surveys.

• Develop a program of research for future years for model refinement and additional data collection that will significantly improve the quality and useability of information products and advice on key management questions in the North and NW region.

Year 2 (2016): During the second year, the project will:

• Undertake field surveys to collect biological and physical data that can be used to test key predictions developed from models.

• Refine current predictive models for the North and NW. Model refinement will incorporate new data to facilitate model outputs that are of direct relevance to identified management needs, including the development of management and monitoring plans for the North and NW CMRs, and risk assessments associated with oil and gas industry operations.

• Reconvene with stakeholders and key stakeholders through formal and informal meetings to disseminate research findings and to ensure project progress and direction remains relevant to management needs

Year 3 (2017): During the third year the project will:

• Continue refinement of analyses and prediction using additional data collected in Year 2 field surveys and to incorporate a range of spatial scales, ecological processes and performance measures.

• Produce updated maps and data syntheses for end-users that capture key environmental attributes of the North and NW regions, and incorporate risk.

• Undertake further detailed discussion/workshops with DoE and other key stakeholders and end-users to outline the results from the project and to refine future management needs/directions and further extension of project especially in the context of developing appropriate monitoring approaches based on new biological and physical data, as well as the potential for development of new, targeted models. We will also assess the value of collecting additional information according to specified decision contexts (e.g. allocation of conservation management resources, EPBC Act approvals).

Notes In addition to the NESP funding, this project is matched by an equivalent amount of in-kind support and co-investment from project partners and collaborators.

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