EMS in the pastoral industries of western Queensland: From customisation to implementation

This paper outlines the customisation of Environmental Management Systems (EMS) for the pastoral industry of western Queensland, the recruitment and training of pastoral producers, and their development and implementation of EMS. EMS was simplified to a 7-step process and producers were recruited to trial this customised EMS. Producers from 40 properties received EMS training, either as groups or individually. Of these, 37 commenced Pastoral EMS development through a facilitated approach that allowed them to learn about EMS while developing an EMS for their property. EMS implementation has been more effective with producers who were trained in groups. At this stage, however, most producers do not see value in EMS as there are currently no strong drivers to warrant continued development and implementation. Key findings resulting from this work were that personal contact and assistance is vital to encourage producers to trial EMS, and that a staged approach to EMS implementation, commencing with a self-assessment, is recommended. EMS training is most successful in a group situation; however, an alternative method of delivery should be provided for those producers who, either by choice or isolation, have to work alone. A support network is also necessary to encourage and maintain progress with EMS development and implementation, particularly where no strong drivers exist.

NEESTIMATOR v2: re-implementation of software for the estimation of contemporary effective population size (N-e) from genetic data

NeEstimator v2 is a completely revised and updated implementation of software that produces estimates of contemporary effective population size, using several different methods and a single input file. NeEstimator v2 includes three single-sample estimators (updated versions of the linkage disequilibrium and heterozygote-excess methods, and a new method based on molecular coancestry), as well as the two-sample (moment-based temporal) method. New features include the following: (i) an improved method for accounting for missing data; (ii) options for screening out rare alleles; (iii) confidence intervals for all methods; (iv) the ability to analyse data sets with large numbers of genetic markers (10000 or more); (v) options for batch processing large numbers of different data sets, which will facilitate cross-method comparisons using simulated data; and (vi) correction for temporal estimates when individuals sampled are not removed from the population (Plan I sampling). The user is given considerable control over input data and composition, and format of output files. The freely available software has a new JAVA interface and runs under MacOS, Linux and Windows.