Oceania Ecological Forecasting Initiative

The Oceania Forecasting Initiative is a grassroots regional group of individuals from Australia, New Zealand, Melanesia, Micronesia, and Polynesia interested in creating and using ecological forecasts.

  • 2024 Webinar Schedule: Details about speakers, titles, and abstracts will be added below as they are confirmed
    • 8 May 2024 – 3:00pm (Sydney time); Anna Richards (CSIRO), “Could the state and transition models concept be a useful tool for ecological forecasting?” A recording from Anna’s presentation is now available at https://youtu.be/RwllLjgPUmM
    • 22 July 2024 – 4:00pm (Sydney time); Whitney Woelmer (University of Waikato), Register Here
    • 30 September 2024 – 4:00pm (Sydney time); Register Here
    • 26 November 2024 – 4:00pm (Sydney time); Register Here

Email us at info@ecoforecast.org if you are willing to present on an ecological forecasting related topic or know of someone in the Oceania region you would like to hear from!

  • Sign-up to be added to a listserv to receive announcements about activities.
  • Here is a Miro Board which shows forecasting projects and interests of the group from two OEFI community calls

OEFI Co-Chairs: Alistair Hobday, CSIRO; Belinda Medlyn, Western Sydney University; Glenda Wardle, Sydney University; Jamie Cleverly, TERN & James Cook University

EFI has a Slack group and the OEFI has a #oceania-chapter channel. Slack is a great way to stay up to date with OEFI events, communicate within the group and across EFI, and find information about forecasting-related papers, funding, etc. Email info@ecoforecast.org to be added to the EFI Slack group and the #oceania-chapter channel.

Paper By OEFI Collaborators

Sun C, Hobday AJ, Condie SA, Baird ME, Eveson JP, Hartog JR, Richardson AJ, Steven ADL, Wild-Allen K, Babcock RC, Yang D, Yu R, Mongin M. Ecological Forecasting and Operational Information Systems Support Sustainable Ocean Management. Forecasting. 2022; 4(4):1051-1079. https://doi.org/10.3390/forecast4040057

Upcoming Webinars

22 July 2024 – Whitney Woelmer (University of Waikato); Process-based forecasts of lake water temperature and dissolved oxygen outperform null models, with variability over time and depth

Register at: https://bit.ly/3V5PIBk

Abstract: Forthcoming

Previous Events – click the links to get to recordings from each session

  1. 8 May 2024: Anna Richards, CSIRO. Could the state and transition models concept be a useful tool for ecological forecasting?
  2. 2 November 2023: Nicholas Clark, University of Queensland. Ecological forecasting with Dynamic Generalized Additive Models
  3. 21 September 2023: Natalie Briscoe and Michael Kearney, University of Melbourne. Forecasting environmental responses with physics and physiology
  4. 24 August 2023: Chaojiao Sun, CSIRO. Ecological forecasting and operational information systems support sustainable ocean management
  5. 22 June 2023: Rob Clemens, Griffith University. “Online digital analytics platforms – EcoCommons & Biosecurity Commons”
  6. 25 May 2023: Steph Brodie, CSIRO. “Skillful ecological forecasts for marine resource management”
  7. 23 March 2023: Jamie Cleverly, James Cook University & TERN. “The statistical predictability from climate factors of carbon, water and energy fluxes across Australian and New Zealand agricultural sites”
  8. 12 February 2023: Alfredo Huete, University of Technology Sydney. “Pollen forecasting and satellite-derived ecological connections between the environment and human health”
  9. 18 October 2022: Justin Welbergen, Western Sydney University.Flying-Fox Heat Stress Forecaster and Flying-Fox Radar Monitor – applications and implications for proactive flying-fox conservation management.” A recording of this talk is not available.
  10. 30 August 2022: Claire Spillman and Christopher Pickett-Heaps, Bureau of Meteorology. “Data sources for ecological forecasting in Oceania”
  11. 23 May 2022: Paige Eveson, CSIRO Oceans and Atmosphere; Quinn Thomas, Virginia Tech; Sean Walsh, University of Melbourne. Examples of Ecological Forecasts.
  12. 12 April 2022: Introductions, ecological forecasting in Oceania, and opportunities to participate as a community.

8 May 2024: Anna Richards, CSIRO
Title: Could the state and transition models concept be a useful tool for ecological forecasting?
Abstract: State and transition models (S&TMs) were developed Westoby et al. in 1989 as a simple tool for communicating non-linear change in rangeland ecosystems. Since then they have been used extensively in different land management applications, particularly in the United States, including providing a conceptual underpinning for monitoring land condition and predicting landscape change. The models have evolved from simple box and arrow descriptions of local-scale ecosystem processes to complex models that include spatially-explicit descriptions of variability within ecosystem states over large regions. These advanced S&TMs (termed ‘state and transition simulation models) have been quantified using empirical observations combined with sophisticated expert elicitation tools and process-based models. In this presentation Dr. Richards will give a background to STMs, their use in a simulation framework, as well as explore examples and future options for applying these types of models as a tool for ecological forecasting.

2 November 2023: Nicholas Clark, University of Queensland
Title: Ecological forecasting with Dynamic Generalized Additive Models
Abstract: Time series analysis and forecasting are standard goals in applied ecology.  But ecological forecasting is difficult because ecology is 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. These sources of variation make it difficult to understand, let alone predict, ecosystem change. Moreover, most available time series software cannot handle features that dominate ecological data, including overdispersion, clustering, missingness, discreteness and nonlinear effects.
In this talk, Dr. Clark introduces Dynamic Generalized Additive Models (DGAMs) as one solution to meet this complexity. He illustrates a number of models that can be tackled with the {mvgam} R package, which builds Stan code to specify probabilistic Bayesian models that include nonlinear smooth functions, random effects and dynamic processes, all with a simple interface that is familiar to most R users.

21 September 2023: Natalie Briscoe, Michael Kearney, University of Melbourne
Title: Forecasting environmental responses with physics and physiology
Abstract: To forecast a species’ response to environmental change we need a model that captures the organism-environment interaction. Frequently this model is descriptive and statistical in nature, capturing the underlying processes implicitly. In this talk, we will introduce an approach to model organism-environment interactions explicitly, known as ‘mechanistic niche modelling’. The aim is to characterise the organism as a dynamical system in terms of its exchange of energy and matter, allowing predictions of its heat and water budget and of its trajectory of growth, development and reproduction. This approach integrates the interdisciplinary fields of ‘microclimatology’, ‘biophysical ecology’ and ‘metabolic theory’ and links functional traits directly to the environment. It allows explicit inferences of environmental conditions that are physiologically out of bounds and can inform vital rates for population models as well as informing behavioural and microhabitat constraints for dispersal models. We will give some example applications of the approach based on the NicheMapR package, and introduce some Shiny apps demonstrate aspects of the approach in an accessible way.

24 August 2023: Chaojiao Sun, CSIRO
Title: Ecological forecasting and operational information systems support sustainable ocean management
Abstract: In times of rapid change and rising human pressures on marine systems, information about the future state of the ocean can provide decision-makers with time to avoid adverse impacts and maximise opportunities. An ecological forecast predicts changes in ecosystems and its components due to environmental forcing such as climate variability and change, extreme weather conditions, pollution, or habitat change. Here, we summarise examples from several sectors and a range of locations. We describe the need, approach, forecast performance, delivery system, and end user uptake. This examination shows that near-term ecological forecasts are needed by end users, decisions are being made based on forecasts, and there is an urgent need to develop operational information systems to support sustainable ocean management. An operational information system is critical for connecting to decision makers and providing an enduring approach to forecasting and proactive decision making. These operational systems require significant investment and ongoing maintenance but are key to delivering ecological forecasts for societal benefits. Iterative forecasting practices could provide continuous improvement by incorporating evaluation and feedback to overcome the limitations of the imperfect model and incomplete observations to achieve better forecast outcomes and accuracy.

22 June 2023: Rob Clemmens, Griffith University
Title: Online digital analytics platforms – EcoCommons & Biosecurity Commons
Abstract: Recent technologies have enabled consistent and continuous collection of ecological data at high resolutions across large spatial scales. A big challenge that all ecologists, conservation scientists and practitioners face is to find the best available data and then to apply appropriate methods to that data. EcoCommons Australia is building a platform where an increasing number of datasets are accessible at the click of a button, and where we will grow the number of scientific workflows that are shared as online dashboard tools within the research community. The EcoCommons platform provides Virtual Laboratories where you can run Species Distribution Models, Climate Projections, Ensemble Modelling, Species Trait Models and a limited capacity Jupyter Environment where R or Python code can be run. Biosecurity Commons is built on top of the EcoCommons tech stack and offers users SDMs, Climate and Ensemble models from EcoCommons as well as biosecurity Risk Mapping, spread (Dispersal) Modelling, Surveillance Design, Proof of Freedom and Impact Analysis.

The vision of these platforms includes saving time for people running analyses, leaving more time to focus on the hardest parts of any study, the Science. I will provide an overview of EcoCommons and then spend some time discussing the case study of Species Distribution Modelling (SDM). This is the most rigorously developed workflow on both platforms and SDMs are popular as they can be used to understand the potential distribution of a species based on available species occurrence records and environmental variables. I will highlight the methodological considerations that are important within SDM workflows, and discuss which are available on the platform dashboard tools, which could be, and which will likely always remain in the domain of a coding environment. I will then take you on a tour of the functionality available on the platform, and perhaps if there is time provide a brief tour of Biosecurity Commons which is providing workflows never before available in such an easy-to-use dashboard environment.

25 May 2023: Steph Brodie, CSIRO
Title: Skillful ecological forecasts for marine resource management
Abstract: Forecasting physical conditions and ecological responses on sub-seasonal to annual timescales benefits marine resource users and decision-makers to anticipate environmental variability and change yet remains operationally elusive. We applied seasonal forecasts to assess the capacity of two management tools in the California Current Ecosystem (CCE) to provide information up to 12 months ahead. The tools use ocean temperature anomalies to: (1) inform risk assessments that mitigate whale entanglements in a crab fishery; and (2) guide the timing of a fishery closure to protect loggerhead sea turtles. In both cases, forecasts accurately predicted anomalous conditions, and may prepare resource managers and conservation practitioners, in some cases a year in advance. Importantly, skillful forecasts were made during an extended marine heatwave coinciding with high rates of turtle bycatch and whale entanglements. We compared the efficacy of readily available global forecasts versus dynamically downscaled forecasts to the CCE and found these management tools can be skillfully forecast using global ocean forecasts. We show that regionally downscaled forecasts are not a necessity and may be less skillful than global forecasts if they have fewer ensemble members than global forecasts. These results highlight capacity for transitioning ocean management tools to forecast systems, providing information for managers and stakeholders to anticipate and adapt to seasonal and longer-term climate variability. 

23 March 2023: Jamie Cleverly, James Cook University & TERN
Title: The statistical predictability from climate factors of carbon, water and energy fluxes across Australian and New Zealand agricultural sites
In this webinar, we focus on the predictability of carbon, water and energy fluxes in a temporal-statistical framework. A comprehensive understanding of the effects of agricultural management on climate–crop interactions has yet to emerge. Using a novel wavelet–statistics conjunction approach, we analysed the synchronisation amongst fluxes (net ecosystem exchange NEE, evapotranspiration and sensible heat flux) and seven environmental factors (e.g., air temperature, soil water content) on 19 farm sites across Australia and New Zealand. Irrigation and fertilisation practices improved positive coupling between net ecosystem productivity (NEP = −NEE) and evapotranspiration, as hypothesised. Highly intense management tended to protect against heat stress, especially for irrigated crops in dry climates. By contrast, stress avoidance in the vegetation of tropical and hot desert climates was identified by reverse coupling between NEP and sensible heat flux (i.e., increases in NEP were synchronised with decreases in sensible heat flux). Some environmental factors were found to be under management control, whereas others were fixed as constraints at a given location. Irrigated crops in dry climates (e.g., maize, almonds) showed high predictability of fluxes given only knowledge of fluctuations in climate (R2 > 0.78), and fluxes were nearly as predictable across strong energy- or water-limited environments (0.60 < R2 < 0.89). However, wavelet regression of environmental conditions on fluxes showed much smaller predictability in response to precipitation pulses (0.15 < R2 < 0.55), where mowing or grazing affected crop phenology (0.28 < R2 < 0.59), and where water and energy limitations were balanced (0.7 < net radiation ∕ precipitation < 1.3; 0.27 < R2 < 0.36). By incorporating a temporal component to regression, wavelet–statistics conjunction provides an important step forward for understanding and forecasting direct ecosystem responses to environmental change, for modelling that understanding, and for quantifying nonstationary, nonlinear processes such as precipitation pulses, which have previously defied quantitative analysis.

12 February 2023: Alfredo Huete, University of Technology Sydney
Title: Pollen forecasting and satellite-derived ecological connections between the environment and human health
Abstract: Pollen allergen exposure have increased dramatically since the 1960s, yet we don’t understand why. Changes in climate, invasive species, and landscape modification have been identified as potential environmental drivers for changes in airborne pollen levels. Warmer temperatures can shift compositional changes in cool (C3) and warm (C4) season grass species as well as alter flowering times and pollen activation periods of allergenic plant species. Pollen forecasting research and methods are site-dependent and tend to be empirically-derived composites of expert knowledge, meteorology and in some cases, patients’ symptom reports. However, site-based empirical relationships are hampered by a sparsity of pollen sampling and forecasting methods rarely incorporate ecological information on allergenic plant species nor land cover conditions or phenological status of the vegetation. Yet, such data are vital to understand ecological and climate drivers of pollen aerobiology and to predict future trends of pollen aerobiology. In this study, we investigate the use of satellite data to monitor grass pollen sources, land cover conditions and grassland phenology status. Grasslands are ecologically sensitive biomes to climate variability and are particularly subject to rapid species invasions and shifts in species diversity. Notably, most allergenic grass species are invasive. Our aim is to discern aero-allergen evolution amidst changing ecological landscapes and climate variations. The long-range goal is to associate and understand pollen aerobiology with environmental changes of the past 40 years in order to be able to predict allergen exposures and mitigate emerging threats to future climates and landscape modifications.

30 August 2022: Claire Spillman and Christopher Pickett-Heaps, Bureau of Meteorology
Title: Data Sources for Ecological Forecasting in Oceania

23 May 2022: Speakers: Paige Eveson (CSIRO Oceans and Atmosphere), Quinn Thomas (Virginia Tech), Sean Walsh (University of Melbourne)
Presentations about Ecological Forecasts

12 April 2022: Introductions, ecological forecasting in Oceania, and opportunities to participate as a community.

  • Miro Board which shows forecasting projects and interests of the group that met

Other Resources

Recording of 2 March 2022 Webinar Hosted by TERN: Forecasting Ecosystem Changes

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