The accuracy of varietal selection using factor analytic models for multi-environment plant breeding trials

Modeling of cultivar x trial effects for multienvironment trials (METs) within a mixed model framework is now common practice in many plant breeding programs. The factor analytic (FA) model is a parsimonious form used to approximate the fully unstructured form of the genetic variance-covariance matrix in the model for MET data. In this study, we demonstrate that the FA model is generally the model of best fit across a range of data sets taken from early generation trials in a breeding program. In addition, we demonstrate the superiority of the FA model in achieving the most common aim of METs, namely the selection of superior genotypes. Selection is achieved using best linear unbiased predictions (BLUPs) of cultivar effects at each environment, considered either individually or as a weighted average across environments. In practice, empirical BLUPs (E-BLUPs) of cultivar effects must be used instead of BLUPs since variance parameters in the model must be estimated rather than assumed known. While the optimal properties of minimum mean squared error of prediction (MSEP) and maximum correlation between true and predicted effects possessed by BLUPs do not hold for E-BLUPs, a simulation study shows that E-BLUPs perform well in terms of MSEP.

Management objectives of Queensland fisheries: Putting the horse before the cart

A review of future management arrangements for the Queensland East Coast Trawl fishery was undertaken in 2010 to develop a management plan for the next 10 years. A key question raised at the start of the review process was: what should the management plan achieve? As with fisheries management in most countries, multiple management objectives were implicit in policy statements, but were poorly specified in some areas (particularly social objectives) and strongly identified in others (e.g., an objective of sustainability). As a start to the management review process, an analysis of what objectives the management system should aim to achieve was undertaken. A review of natural resource management objectives employed internationally was used to develop a candidate list, and the objectives most relevant to the fishery were short-listed by a scientific advisory group. Additional objectives specific to Queensland fisheries management, but not identified in the international review, were also identified and incorporated into the objective set. The relative importance of the different objectives to different stakeholder groups was assessed using the Analytic Hierarchy Process. As with other studies, the relative importance of the different objectives varied both within and between the different stakeholder groups, although general trends in preferences were observed.

Social objectives of fisheries management: What are managers' priorities?

Increasingly, social considerations are having an influence on fisheries policy as well as day-to-day management decision making. Social objectives, unlike economic or conservation objectives, are often poorly defined in fisheries policy, providing substantial leeway for managers to develop management plans in response to the perceived importance of different social outcomes, and potential inconsistencies between different fisheries and jurisdictions. In this paper, through a literature review and workshop with managers across different Australian jurisdictions, we develop a set of social objectives that may be applicable in Australian fisheries. We assess the importance of these different objectives using the Analytic Hierarchy Process, and find considerable diversity in opinion as to which social objectives fisheries management should prioritise to achieve. This diversity of opinion is not directly related to jurisdiction, but does seem related to the context and social environment in which fisheries managers are operating.