Project Descriptions

Molecular identification of ornamental fishes for biosecurity

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Project status: 
In Progress
Student: 
Rupert Collins
Staff: 
Dr Karen Armstrong (Lincoln University)
Staff: 
Dr Rob Cruikshank (Lincoln University)

Ensemble models for prediction in bioprotection and biosecurity

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Project status: 
In Progress
Project Leader(s): 
Dr Sue Worner, Lincoln University
Team Member(s): 
Gabriella Lankin, University of Adelaide
Team Member(s): 
Dr David Teulon, Crop & Food Research
Team Member(s): 
Dr Jacques Régnière, Canadian Forest Service
Team Member(s): 
Joel Pitt, Lincoln University
A model ensemble of change in likelihood of establishment of gypsy moth under climate change.

This project focuses on the development of ensemble approaches, linking various models and databases to assist in decision support in bioprotection and biosecurity.

Closely related to Machine Learning and Bioclimatic Mapping and Prediction, this project is based on the well-known fact that ecological systems represented by predictive models are highly complex and often stochastic by nature. Subsequently our understanding of them is always incomplete.

Machine learning and bioclimatic mapping and prediction

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Project status: 
In Progress
Project Leader(s): 
Dr Sue Worner, Lincoln University
Team Member(s): 
Dr Mike Joy
Team Member(s): 
Dr Takayoshi Ikeda
Team Member(s): 
Gwénaël Leday
Team Member(s): 
Joel Pitt
Models such as this can predict the future establishment and spread of invasive species.

Bioclimate mapping of pest species is used to identify risks under current and projected climates using a range of statistical, Artifical Neural Network (ANN), process and machine learning models.

Predicting the future establishment and spread of invasive species is an integral part of pest risk analysis. Increasingly, different classes of models are used to integrate the high dimensional array of climate and biotic information required to gain greater predictive precision.

Modelling invasive species spread over the heterogeneous landscape

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Project status: 
In Progress
Project Leader(s): 
Dr Sue Worner, Lincoln University
Team Member(s): 
Joel Pitt, Lincoln University
Team Member(s): 
Dr Jacques Régnière, Canadian Forest Service
Team Member(s): 
Dr Jennifer Brown, Canterbury University
A a snapshot of the dispersal model of Argentine ant in NZ.

Once a species arrives in New Zealand and establishes successfully, there is a need to predict where it is likely to spread. Such a prediction is possible using information about what the species requires to establish a successful population. This might include a suitable climate to complete its life cycle, appropriate food and habitats.

We're developing high resolution, stochastic spread models, using stratified dispersal integrated with Geographic Information Systems (GIS), to model invasive species spread over varied (heterogeneous) landscapes.

Artificial neural networks and emergent pests

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Project status: 
In Progress
Project Leader(s): 
Dr Sue Worner, Lincoln University
Team Member(s): 
Professor Nik Kasabov, AUT
Team Member(s): 
Dr Mike Watts, Sydney University
Team Member(s): 
Dr Dean Paini, CSIRO, Australia
We're using predictive models to fight against invasive species.

We are using Artificial Neural Network (ANN) analytical methods to identify emergent pest problems and create risk indices for specific species.

ANNs are computational tools that have novel application to problems in invasion biology.

Stepping up fight against exotic pest insects

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Project status: 
In Progress
Student: 
Peter Holder, Lincoln University
Staff: 
Dr Karen Armstrong, Lincoln University (Project Leader)
Staff: 
Tim Clough, Lincoln University; Russel Frew, University of Otago
Staff: 
George Gill, MAFBNZ
Peter Holder with an Helicoverpa armigera from his collection.

A new weapon being developed for New Zealand's fight against exotic pest insects could save the taxpayer millions of dollars each year.

Bio-Protection Research Centre PhD student Peter Holder is heading the world-leading project that aims to provide Biosecurity New Zealand with a means of determining the geographic origin of exotic insects intercepted in New Zealand.

Spatial dynamics, dispersal and the spread of weeds

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Project status: 
In Progress
Project Leader(s): 
Professor Richard Duncan, Lincoln University
Team Member(s): 
Professor Phil Hulme, Lincoln University
Team Member(s): 
Post-doctoral Fellows Dr Sami Aikio and Dr Jeff Diez, Lincoln University
Team Member(s): 
PhD student, Steve Wangen, Lincoln University
Pilosella (Hieracium pilosella) - a major weed of high country tussock.

Biological invasions are dynamic processes that involve the spread of species across previously unoccupied areas.

The rate at which species spread and the drivers of dispersal are important attributes that distinguish problematic from non-problematic species and an understanding of spatial dynamics is often necessary for management.

This project aims to develop realistic models of the spread of alien species in natural landscapes in order to use these to understand why some habitats are more vulnerable to invasion.

Assessment and development of weed risk assessment tools and approaches

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Project status: 
In Progress
Project Leader(s): 
Professor Phil Hulme, Lincoln University
Team Member(s): 
PhD student Wayne Dawson, Aberdeen University
Nodding thistle (Carduus nutans ) - a major weed of lowland pasture.

Due to the high costs often associated with the control and eradication of introduced weeds (alien plants), prevention is widely regarded as the most effective strategy in the management of biological invasions.

Developing prevention strategies based on introduction pathways

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Project status: 
In Progress
Project Leader(s): 
Professor Phil Hulme, Lincoln University
Team Member(s): 
Dr Phil Lambdon, RSPB
Buddleia (Buddleja davidii) - a major weed of riparian areas.

Weeds arrive into a new region either deliberately (for example, as garden plants) or accidentally (for example, as contaminants of grain). Our research examines the importance of why and how weeds are introduced in the establishment of weeds worldwide.

It is becoming increasingly clear that while some plant traits may favour the successful establishment of plants introduced into new regions, the mechanism, scale and frequency of introduction events are often as important.

Optimising early warning, surveillance and monitoring approaches to weed invasion

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Project status: 
In Progress
Project Leader(s): 
Professor Phil Hulme, Lincoln University
Team Member(s): 
Professor Richard Duncan, Lincoln University
Team Member(s): 
Post-doctoral Fellow, Dr Sami Aikio, Lincoln University
Bindweed invasion

Managing weeds is costly and, in some cases, almost impossible if the weed has become widespread.

Development of tools that can provide early warning of invasion are thus effective if they can mobilise resources against weeds before they become too widespread and expensive to control.

This project examines a variety of surveillance and monitoring schemes to assess their reliability and effectiveness for assessing the rates of change in weed distributions.

Key publications relating to this research:

 
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