Innovative statistical methods for analysing high-dimensional counts. The aim is to develop fast, modern statistical methods for analysing high dimensional data in ecology at large scales, in particular, for visualising, classifying and predicting ecological communities. The benefit of the project is a set of multivariate tools that can be used to better understand biodiversity and its response to environmental drivers, a challenging statistical problem. The proposed methods for analysing high d ....Innovative statistical methods for analysing high-dimensional counts. The aim is to develop fast, modern statistical methods for analysing high dimensional data in ecology at large scales, in particular, for visualising, classifying and predicting ecological communities. The benefit of the project is a set of multivariate tools that can be used to better understand biodiversity and its response to environmental drivers, a challenging statistical problem. The proposed methods for analysing high dimensional data can provide insight into large scale questions in ecology, such as automated identification of biogeographic boundaries. The expected outcome is a powerful statistical toolset for model-based analysis of high dimensional data, introducing modern multivariate approaches to a high-impact area of ecology.Read moreRead less
Understanding the survival of forests under drought . Droughts are predicted to become more extreme in the near future, with potentially devastating impacts on Australian forest ecosystems. This project aims to address key knowledge gaps in our understanding of how plants tolerate extreme drought stress and utilise this new knowledge to improve vegetation models suitable for assessing ecosystem vulnerability. We will use innovative experimental methodology to determine the processes by which wat ....Understanding the survival of forests under drought . Droughts are predicted to become more extreme in the near future, with potentially devastating impacts on Australian forest ecosystems. This project aims to address key knowledge gaps in our understanding of how plants tolerate extreme drought stress and utilise this new knowledge to improve vegetation models suitable for assessing ecosystem vulnerability. We will use innovative experimental methodology to determine the processes by which water transport breaks down in roots, stems and leaves and the mechanisms governing recovery from severe drought stress. The project will provide a deeper understanding of drought tolerance in trees, improved forecasting of risks to native vegetation, and enhanced management of native forest resources. Read moreRead less
Advances in biodiversity modelling - analysis of high-dimensional counts. The aim is to develop flexible models for the analysis of high-dimensional count data, in particular, for studying species interactions and the response of communities to environmental factors. This project is significant because increasingly, important research questions are answered using data with many response variables, with a particular need when studying ecological communities and their response to environmental imp ....Advances in biodiversity modelling - analysis of high-dimensional counts. The aim is to develop flexible models for the analysis of high-dimensional count data, in particular, for studying species interactions and the response of communities to environmental factors. This project is significant because increasingly, important research questions are answered using data with many response variables, with a particular need when studying ecological communities and their response to environmental impacts. This project aims to develop the first models that can be used directly to draw valid community-level conclusions for common ecological data types. The expected outcome is a powerful toolset for fully model-based inference from high-dimensional counts, introducing modern approaches to a high-impact area of ecology.Read moreRead less
New insights from point event data in ecology. This project aims to develop new tools for analysing point event data from multiple species and sources, to better predict species distribution and potential response to climate change. The project proposes joint statistical models for such multivariate data, for greater accuracy and for insights about which species are related in distribution and in environmental response. The new toolset expects to provide significant benefits including improved u ....New insights from point event data in ecology. This project aims to develop new tools for analysing point event data from multiple species and sources, to better predict species distribution and potential response to climate change. The project proposes joint statistical models for such multivariate data, for greater accuracy and for insights about which species are related in distribution and in environmental response. The new toolset expects to provide significant benefits including improved understanding of the drivers of species distribution and interaction, and potential response to a changing climate.Read moreRead less
Resilience of eucalypts to future droughts. This project aims to examine how resilient Eucalyptus species are to future droughts by combining data synthesis, manipulative experiments and modelling. Climate change is expected to increase the frequency, magnitude and duration of future droughts, with major environmental and socio-economic consequences for Australia. Current predictive capacity is extremely limited: experiments are limited in scale and cannot capture important global change interac ....Resilience of eucalypts to future droughts. This project aims to examine how resilient Eucalyptus species are to future droughts by combining data synthesis, manipulative experiments and modelling. Climate change is expected to increase the frequency, magnitude and duration of future droughts, with major environmental and socio-economic consequences for Australia. Current predictive capacity is extremely limited: experiments are limited in scale and cannot capture important global change interactions, whilst models do not represent the functional characteristics and adaptions of eucalypts. This project will develop a strong evidence- and process-based understanding to quantify the functional behaviour of drought-adapted Eucalyptus species and leverage this insight to make future model projections.Read moreRead less
Climate model validation and generation of probabilistic climate projections using data from Phase 5 of the Climate Model Intercomparison Project. New climate model results will be compared with observations to test model skill. Probabilistic projections of regional-scale climate change will be developed and used to investigate a number of ecosystem impact case studies.
Utilizing the geological record to constrain the response of marine ecosystems and global carbon cycling to warming and de-oxygenation. Earth history is punctuated by a huge variety of transitions and perturbations in climate, biogeochemical cycling, and ecosystems, some of which may hold direct future-relevant information. In the oceans, these are closely linked in a complex web of feedbacks, as well as to the oxygenation of the ocean and the ultimate geological fate of excessive carbon release ....Utilizing the geological record to constrain the response of marine ecosystems and global carbon cycling to warming and de-oxygenation. Earth history is punctuated by a huge variety of transitions and perturbations in climate, biogeochemical cycling, and ecosystems, some of which may hold direct future-relevant information. In the oceans, these are closely linked in a complex web of feedbacks, as well as to the oxygenation of the ocean and the ultimate geological fate of excessive carbon released into the atmosphere – burial of carbon in sediments. This project will develop a computer model representation of this coupled carbon-climate-life system and test this against the geological record, explore the causes and consequences of carbon release events and extinctions as well as how the ocean floor delivery and preservation of organic carbon responds.Read moreRead less
An evolutionary landscape to better predict our future climate. Soil microbial communities are the most complicated and difficult to study on Earth, but their effects on our climate are profound. This project will examine the evolution of microorganisms and their viruses in soil using novel methods. It will uncover how the evolution of one microbial species influences the evolution of other community members. It will also apply a new model of evolution to the viruses that infect these microorgan ....An evolutionary landscape to better predict our future climate. Soil microbial communities are the most complicated and difficult to study on Earth, but their effects on our climate are profound. This project will examine the evolution of microorganisms and their viruses in soil using novel methods. It will uncover how the evolution of one microbial species influences the evolution of other community members. It will also apply a new model of evolution to the viruses that infect these microorganisms, constructing a viral ‘tree of life’. This improved fundamental understanding of soil communities will be used to study climate feedback from permafrost wetlands, a key and poorly constrained input of global climate models, improving predictions of our future climate.Read moreRead less
New approaches to predictive modelling of high-dimensional count data to study climate impacts on ecological communities. This project will lay methodological foundations for future studies of potential impacts of climate change on ecological communities. A flexible new toolset of predictive modelling approaches will be developed, capable of handling all common data types, which fit easy-to-interpret models, and which are more powerful than currently used methods.
Advancing tools for the analysis of high-dimensional data in ecology. This project will accelerate the development of advanced tools for answering fundamental questions concerning the potential impact of climate change on ecological communities. These advanced methodologies, more powerful than currently used methods, will fit easy-to-interpret models which can handle all common data types.