OR

Browse By

Dr Nicholas Clark

UQ Amplify Lecturer

School of Veterinary Science
Faculty of Science
n.clark@uq.edu.au
+61 7 535 15104

Overview

An ecologist by training – I hold a B.Sc. (Hons) in Marine Ecology from the University of North Carolina, Wilmington and a Ph.D. in Ecological Modelling from Griffith University. I am broadly interested in exploring new ways to (1) understand how natural communities are formed and (2) predict how they will change over time. As an Amplify Fellow at UQ, my current research focuses on developing computational tools and adapting techniques from epidemiology and statistical forecasting to study how organisms and ecosystems respond to environmental change. This work is being applied to investigate natural dynamics for a range of natural systems including host-parasite interactions, wildlife populations and veterinary diseases.

I am an active member of the R community and have written and/or maintain several popular R packages. For example, I’m a lead developer on the MRFcov package for multivariate conditional random fields analyses. I also wrote the mvgam R package for fitting dynamic Generalised Additive Models to analyse and forecast multivariate ecological time series, and I regularly provide training seminars and workshops to help researchers learn techniques in ecological data analysis.

I am currently seeking Honours and PhD candidates with interests and/or skills in veterinary epidemiology, spatial / spatiotemporal modeling and quantitative ecology.

Research Interests

  • Using forecasts to anticipate how ecosystems respond to environmental change
    I am leading projects to develop new stastical and machine learning models that aim to advance our ability to predict and forecast ecological change. Expected applications of this work cover many fields where time series are very important, including conservation prioritisation, agriculture, species distribution modeling and biosecurity. Currently seeking both Honours and PhD students who are interested in ecological forecasting.
  • The macroecology and biogeography of infectious dieases
    This work aims to describe large-scale patterns in the distributions of wildlife and their pathogens to identify processes governing ecological community assembly and the spread of pathogens. I'll be very happy to accept Honours or PhD students who are interested in biogeography, wildlife research and infectious disease epidemiology.
  • The epidemiology of animal pathogens across the human-wildlife interface
    I am interested in using molecular genetics and epidemiology to improve our understanding of how pathogen infection rates and emergence will change as human encroachment alters natural environments. This work mostly focuses on wildlife and domestic animals, but it can also be used to study human diseases. I'll be very happy to accept Honours or PhD students who are interested in this line of work.

Research Impacts

My research is geared towards understanding how ecological communities, pathogen infection rates and pathogen emergence will change as climate change and human encroachment continue to alter natural environments. This work has generated translational benefits by helping to provide insights into factors that can be targeted to reduce the spread of pathogens in our animals and how to build better models for understanding wildlife responses to climate change. Some key media coverage of this body of work includes:

Ecological Forecasting with Dynamic Generalized Additive Models

Detecting how ecological communities respond to temperature changes

Understanding parasite spread through wildlife: the crucial role of statistical models

Adapting statistical network models to identify biotic interactions in changing communities

Using evolutionary models to trace the emergence of harmful viruses in pet dogs

Tracing the spread of fleas from pets to wildlife and vice versa

Detecting invasive malaria parasites in Australian birds

Qualifications

  • Doctor of Philosophy, Griffith University

Publications

View all Publications

Grants

View all Grants

Supervision

  • Epidemiology of canine-mediated rabies in Nigeria

    (2023) Doctor Philosophy

  • Epidemiology of feline upper respiratory tract infections in shelter cats in Australia

    Doctor Philosophy

  • Forecasting ecosystem responses to environmental change

    Doctor Philosophy

View all Supervision

Available Projects

  • Forecasting ecosystem responses to environmental change

    There is a growing consensus that using models to anticipate the future is vital to mitigate the impacts of environmental change on ecosystems. Yet most ecological models are one-off attempts to predict what ecosystems might be like in many years or decades. This makes it hard for decision-makers to use these models. It also favours models that are not easily scrutinised and improved. This research will use an iterative cycle to 1) forecast how species occurrences and abundances will change over short timescales; 2) use predictions to inspect model failures and 3) improve models so that we can continue to learn. This represents a new way of thinking in ecology that, like weather forecasting, has the power to advance our understanding of ecological processes.

    I am looking for students who want to work within a vibrant team of quantitative ecologists and spatio-temporal modellers to tackle interesting questions in ecological modeling and forecasting. This project will help develop the candidate’s skills in critical thinking, project management, data management and analysis, writing and communication. Expected applications of the project are incredibly diverse, meaning the student will be well prepared for a future career in research or with government and non-government land management, biosecurity or conservation agencies.

  • How is global change impacting ecological communities?

    Global change is heavily impacting natural ecosystems thorough climate change, landscape alterations, invasive species and many other processes. We are offering projects investigating time series from around the world to ask key questions such as:

    Do ensemble forecasts outperform forecasts from individual models in ecological settings?

    How are wildlife populations from different groups (insects, mammals, birds) responding?

    How does climate variablity affect population dynamics?

    How does population variance and stability change over time and in relation to climate variation?

    How are Australia's marine ecosystem responding to climate change?

    We are looking for students interested in understanding how globally pressing changes are impacting our wildlife communities. Ideal candidates will have demonstrated skills in statistical modelling, coding experience (in any programming language), and strong written and communication skills. You do not need to have experience in wildlife ecology, but you must have a keen interest to learn.

  • Developing new statistical methods to advance near-term forecasting

    What will nature look like in the future? This question is difficult to answer because ecology, and ecosystem dynamics, are very complex. The abundances of species, for example, fluctuate for many reasons. Food and shelter availability limit survival. Biotic interactions affect colonization and vital rates. Severe weather events and climate variation alter habitat suitability. Current changes in abundance can have carry-on effects on future abundance, irrespective of local conditions. These sources of variation make it difficult to understand, let alone predict, ecosystem change. Another problem when trying to understand these effects is that common statistical methods for analysing time series are not suitable for dealing with most ecological data (which can have many zeros, missing values and are often represented as multivariate count data).

    This project aims to develop new modeling tools that will allow researchers around the globe to better analyse their data. Work will centre around the development of Bayesian dynamic models for time series and forecasting purposes. Ideal candidates should be interested in software development and statistical programming, so candidates with backgrounds in computer science or some othe field that provides skills in programming will be well placed to make an impact here. It is not necessary that you have strong skills in time series analysis or forecasting, but you should be keen to learn about these fields.

View all Available Projects

Publications

Featured Publications

Journal Article

Conference Publication

PhD and MPhil Supervision

Current Supervision

Completed Supervision

Possible Research Projects

Note for students: The possible research projects listed on this page may not be comprehensive or up to date. Always feel free to contact the staff for more information, and also with your own research ideas.

  • Forecasting ecosystem responses to environmental change

    There is a growing consensus that using models to anticipate the future is vital to mitigate the impacts of environmental change on ecosystems. Yet most ecological models are one-off attempts to predict what ecosystems might be like in many years or decades. This makes it hard for decision-makers to use these models. It also favours models that are not easily scrutinised and improved. This research will use an iterative cycle to 1) forecast how species occurrences and abundances will change over short timescales; 2) use predictions to inspect model failures and 3) improve models so that we can continue to learn. This represents a new way of thinking in ecology that, like weather forecasting, has the power to advance our understanding of ecological processes.

    I am looking for students who want to work within a vibrant team of quantitative ecologists and spatio-temporal modellers to tackle interesting questions in ecological modeling and forecasting. This project will help develop the candidate’s skills in critical thinking, project management, data management and analysis, writing and communication. Expected applications of the project are incredibly diverse, meaning the student will be well prepared for a future career in research or with government and non-government land management, biosecurity or conservation agencies.

  • How is global change impacting ecological communities?

    Global change is heavily impacting natural ecosystems thorough climate change, landscape alterations, invasive species and many other processes. We are offering projects investigating time series from around the world to ask key questions such as:

    Do ensemble forecasts outperform forecasts from individual models in ecological settings?

    How are wildlife populations from different groups (insects, mammals, birds) responding?

    How does climate variablity affect population dynamics?

    How does population variance and stability change over time and in relation to climate variation?

    How are Australia's marine ecosystem responding to climate change?

    We are looking for students interested in understanding how globally pressing changes are impacting our wildlife communities. Ideal candidates will have demonstrated skills in statistical modelling, coding experience (in any programming language), and strong written and communication skills. You do not need to have experience in wildlife ecology, but you must have a keen interest to learn.

  • Developing new statistical methods to advance near-term forecasting

    What will nature look like in the future? This question is difficult to answer because ecology, and ecosystem dynamics, are very complex. The abundances of species, for example, fluctuate for many reasons. Food and shelter availability limit survival. Biotic interactions affect colonization and vital rates. Severe weather events and climate variation alter habitat suitability. Current changes in abundance can have carry-on effects on future abundance, irrespective of local conditions. These sources of variation make it difficult to understand, let alone predict, ecosystem change. Another problem when trying to understand these effects is that common statistical methods for analysing time series are not suitable for dealing with most ecological data (which can have many zeros, missing values and are often represented as multivariate count data).

    This project aims to develop new modeling tools that will allow researchers around the globe to better analyse their data. Work will centre around the development of Bayesian dynamic models for time series and forecasting purposes. Ideal candidates should be interested in software development and statistical programming, so candidates with backgrounds in computer science or some othe field that provides skills in programming will be well placed to make an impact here. It is not necessary that you have strong skills in time series analysis or forecasting, but you should be keen to learn about these fields.

  • Modeling and forecasting paralysis tick infestation rates in Australia

    Tick paralysis, caused by neurotoxins contained in the saliva of paralysis ticks, is a life-threatening condition for dogs and cats requiring immediate medical attention. In Australia tick paralysis is a leading cause of emergency admissions, with tens of thousands of tick paralysis cases admitted to veterinary emergency services each year. While preventative treatments and avoidance of tick-prone areas during periods of heightened risk are effective reduction measures, surveillance systems are inadequate to provide timely information to clinicians and pet owners located in areas most at-risk.

    Working as part of a vibrant research team involving a diversity of collaborators, students will benefit in the following ways:

    (1) Experience in data mining and generating critical summaries for time series data

    (2) Quantitative analysis of multistructure datasets

    (3) Contributing to the planning, writing and submission of peer-reviewed publications

    We are looking for students who are interested in the health of pets and in using data to inform disease management. Ideal candidates will have demonstrated skills in statistical modeling, coding experience (in any programming language), and strong written and communication skills. You do not need to have experience in veterinary epidemiology, but you must have a keen interest to learn.

This staff member is a UQ Expert for media in the following fields:

Community ecology, Forecasting, Ecological modeling, Host-parasite interactions, Disease ecology

They are happy to lend their expertise to your articles or broadcasts and share their research discoveries and insights with the community via media channels.

For additional assistance with story ideas, general advice and information or help with seeking further experts, please email the UQ Media Team or telephone (07) 3365 1120.

Links

ORCID: 0000-0001-7131-3301

Scopus ID: 56048761800

Google Scholar ID: eKT6SGcAAAAJ

Unit Links
Other Media
Social Media

Related Resources

Similar Staff
Researchers in Associated Units
Fields of Research