Ms Megan McNellie

BSc (Hons) James Cook University
PhD Student

I am a landscape ecologist and a spatial analyst. I am working as an Biodiversity Modeller in the Science Division of the New South Wales Office of Environment and Heritage. Both my work and my PhD are looking at delivering spatially explicit models of landscape condition over broad scales. I am undertaking this research in collaboration with CSIRO and Department of Environment and Industry (Victoria). Prior to working as a  spatial modeller, I was a field botanist in NSW, and prior to that, I worked as a remote sensing and GIS analyst in the  Northern Territory.

Research interests

THESIS TITLE

Predicting spatial patterns in vegetation across landscapes: from structure and composition to condition and change

THESIS DESCRIPTION

Mapping change and trends in the state of vegetation can be used to gauge where and how much of the landscape has been modified. This information can be used to support evidence based decisions for conservation and land management. However, mapping change can be challenging because quantities long-term, site-based data are limited; vegetation communities can be structurally and compositionally complex; defining reference states from which to measure change is context dependent and different vegetation attributes respond differently to disturbance.

This research aims to address these challenges. We propose that archived site-based floristic data (n = 9752) can be assimilated into discrete structural (overstorey cover, midstorey cover, total groundcover, grassy groundcover, other growthforms in the groundcover) or compositional components (exotic cover, proportion of exotic species and native species richness). With this information we will explore patterns in structural complexity and composition of plant growth forms. Raster-based analyses will be used to model spatially explicit, continuous representations of intact, contemporary and changed components of vegetation. The outcomes of this research will support conservation practitioners, planners and policy makers with evidence needed to make informed decisions.

Megan J McNellie, Ian Oliver and Philip Gibbons. (accepted). The pointy-end of predictive modelling: pitfalls and possible solutions for using geo-referenced site data to inform models. Ecological Informatics.
 
Megan J McNellie, Ian Oliver, Simon Ferrier, Graeme Newell, Glenn Manion, Peter Griffioen, Matt White, Philip Gibbons. A solution to modelling vegetation condition for whole-of-landscape conservation planning. Spatial Ecology and Conservation Conference Presentation, University of Birmingham, 17-20th June 2014

Oliver, I., E. A. Broese, M. L. Dillon, D. Sivertsen, and M. J. McNellie. 2013. Semi-automated assignment of vegetation survey plots within an a priori classification of vegetation types. Methods in Ecology and Evolution 4:73-81.