Ecosystem-based management provides practical techniques for assessing the dynamics of interactions between diverse heterogeneous patches within the environment. However, to achieve meaningful results, studies must be undertaken over sufficiently large spatial scales and over long time periods. Where it is not possible to undertake such large-scale surveys, assumptions, approximations and ad hoc indicators of landscape (or seascape) quality must be applied. This may lead to errors which could prove costly, both for the environment and, through potential penalties, litigation and protracted remediation costs, for the project proponent.
Measuring connectivity by direct observation of movement of individuals is extremely challenging, costly and time-consuming. Also, direct movement studies are unable to address movements integrated over many years to decades and centuries. However, genes flow throughout landscapes over short and long periods of time.
Assessing fauna and flora populations using both landscape ecology and population genetics techniques allows us to assess this movement in ways that direct movement studies cannot.
Through applications of ecological genomics (ecoGenomics) with numerical modelling, we can provide improved methods for observations of terrestrial and marine environments to better inform the next generation of environmental monitoring programs, assist effective management decisions and support legislative
requirements. As compared to current environmental monitoring techniques, ecoGenomics methods can yield results more quickly, more easily and with greater reliability of taxonomic identification. Ultimately this leads to improved assessment of environmental landscapes and seascapes.
Advances in molecular ecology techniques allow correlations and inferences to be made between landscape features with genetic variations within and between populations to provide assessments of gene flow over both temporal and spatial scales. The identification of spatial genetic patterns requires the collection of genetic data from many individuals whose exact geographical location is known. After sampling, genetic and statistical tools are used to determine spatial-genetic patterns and correlate these with landscape, seascape or environmental features.
Quantifying connectivity is useful in the planning, monitoring and assessment of large-scale species management programmes, developing targeted mitigation strategies and ensuring that management actions continue to achieve their intended outcomes.
• invasive and pest species management
• threatened species conservation
• marine and terrestrial food webs
• pathogen ecology
• ecological network analysis