Recently completed PhD & Masters projects
The impacts of assisted migration and translocation on community genetics in restoration ecology
Supervisors: Dr Peter Harrison, Assoc Prof Julianne O’Reilly-Wapstra & Dr Glen Bain
This Masters project aims to investigate how the genetics of trees shape dependent community composition using a multi-provenance field trial of two eucalypt species, Eucalyptus pauciflora and Eucalyptus ovata. I will apply community genetics theory to an applied restoration problem by investigating how the provenance of foundation trees influence the arthropod and fungal communities that colonise and establish in the canopy, and whether this has extended effects across trophic levels through the foraging behaviour of insectivorous birds.
The flow-on effects of translocation are particularly important to understand in a restoration context, as foundation species such as forest trees have been shown to exert an extended phenotype effect on above- and below-ground dependent communities. Results from this study will improve understanding of differential provenance performance and inform restoration planting strategies for future climate change resilience.
Non-destructive evaluation of plantation logs for segregation into different product types
Assoc Prof Julianne O'Reilly-Wapstra, Prof Mark Hunt, Assoc Prof Greg Nolan, Dr Nathan Kotlarewski, Dr Andrew Jacobs, Dr Dean Williams
There are great opportunities to extend the use of the hardwood plantation estate in Tasmania for higher-value products such as sawn material, veneers and engineered wood products. To maximise these opportunities, it is important to understand the wood quality traits of the current resource.
This project aims to investigate wood quality traits of standing eucalypt trees, logs and boards using non-destructive techniques. The project works across the full value chain of growers, harvesters and processors to:
- Investigate and map environmental effects on wood quality traits in fibre-grown Eucalyptus nitens plantations
- Examine the capacity to sort and segregate trees and logs on a harvesting landing using Non-Destructive Techniques to predict wood properties
- Investigate the perceived and effective characteristics of the raw material impacting different products
- Assess the volume and value recovery of eucalypt sawn material for structural production
- Investigate in-forest segregation systems to sort logs into different quality classes at the moment of harvest
The outcomes of this research will enable a greater understanding of the characteristics of the fibre-managed eucalypt plantation resource, its suitability for different product types and its potential uses, while validating the use of readily available and novel technologies to test wood quality.
Measuring and assessing structural complexity in restoration plantings
Prof Brad Potts, Prof Mark Hunt, Dr Arko Lucieer, Dr Peter Harrison, Dr Neil Davidson
This project aims to establish and test a methodology to measure and assess forest structural complexity using a combination of remote sensing technologies and field surveyed data in the Tasmanian Midlands, one of Australia’s 15 biodiversity hotspot regions. Forest structure is commonly recognised to be a good indicator of biodiversity complexity, following the concept that ecosystems containing different stands with a broad variety of structural attributes are more likely to provide resources for a variety of species utilising them.
The project starts with a review of recent literature on structural complexity indices and ways to measure and assess its main attributes using remote sensing technology. Ecological questions will be investigated in the restoration planting at Dungrove, near Bothwell, where stability of provenance performance in pure and mixed species ecology trials has been tested. The project will then look at the tree-level assessment of structural attributes, in the restoration plantings, using a combination of field work and LiDAR data acquired from an unmanned aerial vehicle (UAV). We will focus on the capabilities of hyperspectral imagery acquired from UAV to effectively differentiate between eucalypt species and potentially genetic provenances, and look at temporal changes in the development of structural attributes at Dungrove restoration site, using ground-based LiDAR (ZEB1) scans from three different years over three 0.1 ha plots.
The determinants of optimal leaf area in eucalypt plantations
Supervisors: Prof Mark Hunt, Assoc Prof Mark Hovenden, Dr Daniel Mendham, Dr Dean Williams
This project will explore the influences of fertiliser and temperature on optimal leaf area in eucalypt plantations. Dramatic increases in leaf area have been observed under high fertiliser treatments in nutrition trials. Extra leaf area increases photosynthetic area, but also incurs a respiratory cost to the plant in terms of leaf construction and maintenance. Extra leaf area may be an adaptation to store nutrients for re-translocation in times of nutrient deficit. The project will explore the relationship between nitrogen and phosphorous fertiliser treatments and total leaf area, the vertical distribution of leaf area and the longevity of N and P in foliar stores. It will also measure rates of photosynthesis and respiration as a function of light, temperature, and nutritional status.
Development of an autonomous unmanned aerial system for below-canopy laser scanning of forests.
Supervisors: Assoc Prof Paul Turner, Dr Mohammad Sadegh Taskhiri, Dr Dean Williams
Drones are a cost-effective means of collecting forest data and are conventionally used above the forest canopy. This project seeks to develop an autonomous, unmanned aerial system for mapping the forest from beneath the canopy. The purpose of this approach is to provide a mapping solution for areas of dense undergrowth and dense canopy, where ground-based methods are difficult/hazardous and above canopy methods struggle to penetrate to the stems. The end goal of this project is to be able to autonomously map a difficult region of forest in less time and in far greater detail than can humans, reducing inventory costs and improving worker safety.
Silvicultural options to optimise the productivity of Eucalyptus nitens
Supervisors: Assoc Prof Julianne O'Reily-Wapstra, Prof Mark Hunt, Dr Mark Neyland, Dr Andrew Jacobs, Dr Dean Williams
This project aims to enhance plantation productivity by understanding the effects of silvicultural management on growth and wood characteristics. In particular this project will examine the effects of tree spacing and thinning on critical wood properties such as basic density, tension wood and modulus of elasticity.
The Business Case for trees on farms
Prof Mark Hunt, Dr Dugald Tinch, Dr Thomas Baker, Dr Daniel Mendham, Dr Anthony O'Grady, Dr Martin Moroni
Farmers are running a business and commonly will criticise a proposal for the establishment of trees on a farm if it does not include a business case. Trees within an agricultural setting provide valuable ecosystem services such as shade and shelter for stock and crops, reduced erosion, clean water and nutrient cycling. Such ecosystem services are rarely quantified and are therefore excluded from financial analyses. This means that the true economic value of tree establishment is misunderstood, especially when trees are established for non-fiber purposes. Therefore, there is a need to develop new models for estimating the true economic value for tree establishment. This project looks at the use of natural capital accounting as a way of measuring the varied benefits of trees on farms. This work will involve collating known benefits such as timber production and shelter benefits as well as calculating the potential economic value of other ecosystem services such the impacts of pests and predators.
Using developed models, this project will also asses how the benefits of trees on farms varies between planting for timber production and native forests established for restoration/ecosystem services.
Zara is currently running a survey to understand farmers preferences relating to the design of agroforestry plantings.