Translation Needs for the EFI Community

February 2, 2023
By the Translation Working Group

Translational ecology aims to increase the usability of knowledge and products beyond scientific communities by integrating socio-environmental knowledge and stakeholders or end users as partners in the process and projects. For the past few months, the Translation and Actionable Science Working Group has been working to gauge the translational needs of the EFI community and to identify where modelers and physical scientists see gaps in connecting to stakeholders and end users to conduct translational research.  The goal of this post is to share what the working group has identified as priorities for translational needs and share where there are connections to what other working groups and organizations are doing.

Michael Gerst (University of Maryland) led interviews in October-November 2022 with nine individuals across EFI that represent a range of early to late career stages, institutional type (academic, NGO, U.S. government agency), and gender to learn about interviewees’ experiences with forecasting projects that required stakeholder interaction, what went well, what didn’t, and what would have been useful to improve stakeholder engagement. The EFI Translation Working Group is using the results from these interviews to prioritize and develop activities that can help to fill those gaps.

The following seven topics were identified from the interviews and Working Group discussions that could be developed into self-contained seminars, manuals, or guidance documents (for short-term activities) or hosting larger workshops or proposal writing opportunities (for longer-term activities).  Cases where topics overlap with other EFI working group discussions and activities are also highlighted. 

  1. How can EFI serve as an advocate for ecological forecasting to stakeholder groups, especially the public sector?
    In some cases, the individuals interviewed found that the stakeholders they work with were not interested as much in the forecasts provided as they were in the real-time data that was provided during the data collection and forecast process.  These real-time data allowed the stakeholders to use their expert knowledge to make informed decisions that may or may not have been related to the forecasts that the teams provided. Within academia, there has been quite a bit of work to raise the profile of ecological forecasting, but there is now the opportunity to bring this awareness outside academia to private and government sectors to both promote the benefits of ecological forecasts in settings outside academia and listen to the needs of stakeholders. 
  1. What’s the appropriate level of stakeholder engagement? Is co-production always the right answer?
    Co-production is increasingly seen as a method for improving the fit between science and stakeholder needs. However, it can be time-consuming and expensive, necessitating assessment of whether its potential benefits are a good match for a project. While understanding of the contexts in which co-production can be fruitful has improved, there is still a gap in distilling guidelines for scientists on when it is appropriate, and if not, what other options exist.
  1. How to help colleagues find collaborators across disciplines (i.e., matchmaking) as well as providing guidance on what makes a fruitful multi-disciplinary collaboration?
    This topic, as well the previous point about the appropriate level of stakeholder engagement connects with conversations and a blog post the EFI Diversity, Equity, and Inclusion (DEI) working group is having and developing that highlights the need to bring in collaborators at the beginning of a project to learn what is of most interest to them. The DEI group has focused on underrepresented individuals in terms of race/gender, but this can also be applicable to underrepresented disciplines in ecological forecasting like social science.
    This topic also connects with previous discussions in the former Partners and Knowledge Translation working group (which merged with the former Social Science group to become the current Translation working group). Previous discussions have revolved around how to keep a database of individuals and groups that support matchmaking connections. The group has also discussed the need for forums or meetings to allow groups to pitch ideas and socialize early ideas that can then be followed up to develop proposals to fund those ideas.  Clearly, this is something that resonates both within the working groups and across the broader EFI community.
  1. How to initiate, foster, and maintain stakeholder relationships?
    In 2021 and early 2022 the Partners and Knowledge Transfer and Social Science working groups hosted a number of seminars on science communication and co-production.  In particular, the May 4, 2021 seminar on co-production provides some initial resources that could be built out further for this topic.  The discussions and the upcoming blog post the EFI DEI working group is developing that highlight ways to connect to underrepresented groups will also provide useful resources related to fostering relationships.
  1. How to understand stakeholder decision-making processes?
    In the interviews, a few anecdotes were shared that ultimately can be summarized as: we thought we knew how stakeholders make decisions (with forecasts!) but experience eventually proved otherwise. In addition to learning the process of stakeholder engagement, interviewees thought there would be utility in helping modelers understand the universe of ways stakeholders might make decisions and where forecasts fit in (or don’t!).
  1. How to set up extended project planning to ensure continued operationalization?
    It is important to have a plan in place for how ecological forecasts will be operationalized after the initial set of funding expires. Stakeholders are frustrated if they start to use a forecast and then it is no longer available when the funding is over.  NASA provides one example of how to avoid this issue.  In NASA’s Ecological Conservation Applications, solicitations (e.g., A.40 Earth Science Applications: Ecological Conservation) often require proposal teams to include partners/end users who will also be responsible for maintaining the ecological forecasting products (e.g, web apps) beyond the NASA funding period.
  1. How to make data, models, and systems that are documented and reusable (FAIR data, models)?This is a topic that is of interest across multiple working groups in the EFI community. The Forecasting Standards working group has recently submitted a manuscript for publication titled “A Community Convention for Ecological Forecasting: Output Files and Metadata.” The preprint is available here: https://ecoevorxiv.org/9dgtq/. The manuscript focuses on suggestions for documenting ecological forecasts.  The Cyberinfrastructure and Methods working group has also been thinking about the issue where groups creating ecological forecasts continue to develop one-off or boutique workflows.  That working group is writing a workshop proposal to bring the together people from government agencies, industry, NGOs, and academia together to develop a way to share forecasts and workflows so people don’t need to reinvent a forecast workflow. Instead, new forecasts can be created that borrow strength from resources already developed for similar models or workflows and instead be able to focus on the details and nuances of applying a forecast in their own study system or domain. This also resonates with what the EFI NEON Ecological Forecasting Challenge is working on with the cyberinfrastructure that is set up for accessing target and meteorological data and accepting, scoring, and visualizing forecasts across multiple NEON Data streams.

EFI at AGU 2022

Date: December 4, 2012

Below is the list of poster and oral presentations for EFI’s hosted session at the American Geophysical Union (AGU) 2022 Conference in Chicago, as well as other ecological forecasting-related talks that may be of interest to the community. All times are listed in US Central Time.

Thursday EFI Social – Anyone who is available to meet up on December 15, Thursday evening, we’ll have a group getting together at Kroll’s South Loop starting around 6:30 – 8:30pm. It’s an 18-minute walk from the Convention Center. Find directions here.

Friday Poster and Oral Sessions – EFI’s oral and poster sessions on “Ecological Forecasting in the Earth System” will be held on Friday, December 16, 2012. The in-person Poster Session is from 9am-12:30pm in Poster Hall A (South, Level 3). The Online Poster Session is from 1:45-2:45pm. The Oral session is from 4:45-6:15pm in S501bcd (South, Level 5). We’re excited to have a great set of speakers that really span the full gradient from terrestrial to freshwater to marine. Come check out the following talks!

Friday EFI In-Person Poster Session (9:00-12:30, Poster Hall A)

Friday EFI Online Poster Session (1:45-2:45pm, Online)

Friday EFI Oral Session (4:45-6:15pm, S501bcd – South, Level 5)

Other Forecasting Presentations

If you are presenting an ecological forecasting-related talk or poster that you don’t see on the list, reach out so we can get it added!

Congratulations to Kelly Heilman on the 2022 ESA Ecological Forecasting Award!

The ESA Statistical Ecology section is proud to present the 2022 Ecological Forecasting Outstanding Publication Award to Kelly Heilman and collaborators for their 2022 Global Change Biology Paper:

“Ecological forecasting of tree growth: Regional fusion of tree-ring and forest inventory data to quantify drivers and characterize uncertainty”

The award committee felt that the paper illustrates the strength of combining multiple data constraints across regional scales to improve predictions of forest growth for a climatically-vulnerable ecoregion, the American Southwest, parsing out the complex interactions among climate, stand, and individual-scale effects. Furthermore, the paper provides a detailed accounting of how different uncertainties impact growth projections across a range of time scales and climate projections, finding that tree growth and tree size were sensitive to very different uncertainties (year-to-year growth was dominated by driver uncertainty and process error, while tree size was more sensitive to initial conditions and plot random effects).

Individuals wishing to nominate papers published in the past  3 years for the 2023 award are encouraged to do so by the March 1, 2023 deadline. Additional information can be found at https://www.esa.org/stats/awards/ecological-forecasting-outstanding-publication-award/

Full List of Award Winners & Citations

2022 – Kelly Heilman (University of Arizona)
Heilman, K. A., Dietze, M. C., Arizpe, A. A., Aragon, J., Gray, A., Shaw, J. D., Finley, A. O., Klesse, S., DeRose, R. J., & Evans, M. E. K. (2022). Ecological forecasting of tree growth: Regional fusion of tree-ring and forest inventory data to quantify drivers and characterize uncertainty. Global Change Biology 28(7):2442-2460 doi.org/10.1111/gcb.16038

2021 – Sarah Saunders (National Audubon Society)
Saunders, S.P., F.J. Cuthbert, and E.F. Zipkin. “Evaluating Population Viability and Efficacy of Conservation Management Using Integrated Population Models.” Journal of Applied Ecology 55, no. 3 (2018): 1380–92. https://doi.org/10.1111/1365-2664.13080.

2020 –  Paige Howell (USGS)
Howell, P.E., B.R. Hossack, E. Muths, B.H. Sigafus, A. Chenevert‐Steffler, and R.B. Chandler. “A Statistical Forecasting Approach to Metapopulation Viability Analysis.” Ecological Applications 30, no. 2 (2020): e02038. https://doi.org/10.1002/eap.2038.

2019 – Maria Paniw (CREAF, Ecological and Forestry Applications Research Centre)
Paniw, M., N. Maag, G. Cozzi, T. Clutton-Brock, and A. Ozgul. “Life History Responses of Meerkats to Seasonal Changes in Extreme Environments.” Science 363, no. 6427 (February 8, 2019): 631–35. https://doi.org/10.1126/science.aau5905.

2018 – Quinn Thomas (Virginia Tech)
Thomas, R.Q., E.B. Brooks, A.L. Jersild, E.J. Ward, R.H. Wynne, T.J. Albaugh, H. Dinon-Aldridge, et al. “Leveraging 35 Years of Pinus Taeda Research in the Southeastern US to Constrain Forest Carbon Cycle Predictions: Regional Data Assimilation Using Ecosystem Experiments.” Biogeosciences 14, no. 14 (2017): 3525–47. https://doi.org/10.5194/bg-14-3525-2017.

NEON Case Study Part 2 – The EFI-NEON Forecasting Challenge in the Classroom

September 8, 2022

See highlights about the NEON Forecasting Challenge in a two part series from the National Ecological Observatory Network blog.

This second post provides examples of how the NEON Forecasting Challenge has been used in undergraduate and graduate classes.

https://www.neonscience.org/impact/observatory-blog/efi-neon-forecasting-challenge-classroom

You can find the first post about building a forecasting community and individual experiences participating in the Challenge here:

https://www.neonscience.org/impact/observatory-blog/building-forecasting-community-efi-rcn-neon-forecasting-challenge

EFI Futures Outstanding Student Presentation Award 2022 Results

At the May 2022 EFI Virtual Conference we debuted the EFI Futures Outstanding Student Presentation Award. This award is given to promote, recognize, and reward an outstanding student presenter and provides valuable feedback to student presenters on their research and presentation skills. Students presenting both Posters and Oral Presentations were eligible for this award. Each poster or oral presentation were anonymously reviewed by at least two volunteer reviewers with no conflicts of interest with the presenters. In addition to being recognized for their outstanding work, award winners received $50 to spend at the EFI shop. We thank all the students who presented and the volunteers who reviewed the presentations!

Congratulations to this year’s Outstanding Presentation Award recipients!

  • Yiluan Song (University of California, Santa Cruz) won for her oral presentation, “Ecological forecasting of leafing and flowering phenology during climate change to inform public health” and
  • Whitney Woelmer (Virginia Tech) won for her poster “Undergraduate student confidence and understanding of ecological forecasting concepts significantly increases after completing a Macrosystems EDDIE module.”

See Yiluan and Whitney’s presentation, poster and abstracts below.

Yiluan (left) and Whitney (right) are traveling or in the field and look forward to getting their swag when they get home!

In her presentation, Yiluan introduced her pollen phenology forecast used for public health that leverages the rapidly accumulating data on leafing phenology with a nonlinear, data-driven model. Yiluan and her co-authors established a workflow for data assembly, prediction, and delivery and use the PhenoForecast platform to deliver forecasts of plant phenology and to communicate pollen allergy risks.  The platform is not available online yet, but Yiluan and her collaborators are working toward that end.

In her poster, Whitney shared an overview of Module 8 of the Macrosystems EDDIE suite of educational modules that introduce students to concepts of macrosystems ecology, ecological forecasting, and quantitative literacy skills. This module in particular focuses on introducing decision-support and uncertainty communication skills, in addition to general ecological forecasting concepts and applications. Whitney’s poster also demonstrates how the effectiveness of the modules was assessed and how they increase students’ engagement and understanding of complex concepts.

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ABSTRACTS

Ecological Forecasting of Leafing and Flowering Phenology During Climate Change to Inform Public Health
Yiluan Song1, Stephan B. Munch2,3,4, Kai Zhu1
1University of California, Santa Cruz, 2Southwest Fisheries Science Center, 3National Marine Fisheries Service, 4National Oceanic and Atmospheric Administration

Changes in plant phenology caused by climate change have important implications not only in ecology but also in public health. Global warming has led to an extended pollen season and increased pollen abundance. Exposure to pollen imposes significant costs on public health and is likely to exacerbate under future environmental change. The elevating risks from phenological shift calls for major improvements in the prediction of phenology and the understanding of driving mechanisms. The success in the prediction of phenology has been limited by the performance of phenology models, in particular, a mismatch between the common linear modeling approach and the nonlinear mechanisms. Traditional models with linear structures often fail to accurately predict phenology, as mechanisms of phenology can be highly nonlinear. Models that address nonlinear mechanisms with data-driven machine learning approaches are needed to overcome the limitations in phenology models. To model the nonlinear mechanisms of leafing and flowering phenology, we adopt a state-of-the-art machine learning method, Gaussian Process empirical dynamic modeling (GP-EDM). By forecasting leafing phenology observed with satellite remote sensing (MODIS) and near-surface camera imagery (PhenoCam) in the near term (as part of the EFI RCN NEON Ecological Forecast Challenge), we validate that our approach reveals complex causal relationships from time series and outperforms parametric alternatives in prediction. Applying our ecological forecasting method, we forecast the leafing and flowering phenology of four tree taxa that produce allergenic pollen at high spatial and temporal resolution (0.05 deg and daily) over the continental US. These forecasts, published daily through a Shiny App, serve to provide early allergy health advisories and warnings, which can limit pollen exposure and reduce healthcare costs. Further, the interactive query of plant phenology on the web app can raise awareness of the impacts of climate change on our health and the ecosystem. Overall, this project develops cutting-edge machine learning models for forecasting plant phenology and is a step towards mitigating the adverse impacts of unprecedented climate changes on public health.

Undergraduate Student Confidence and Understanding of Ecological Forecasting Concepts Significantly Increases after Completing a Macrosystems EDDIE Module
Whitney Woelmer1
1Virginia Tech

Ecological forecasting is an emerging approach to estimate future states of ecological systems with uncertainty, allowing society to prepare for and manage ecosystem services. Despite the increasing need to understand, create, and communicate forecasts, forecasting training has previously focused on graduate students, representing a gap in training undergraduate students as the next generation of ecologists. In response, we developed a hands-on teaching module within the Macrosystems EDDIE (Environmental Data-Driven Inquiry & Exploration; MacrosystemsEDDIE.org) educational program to introduce ecological forecasting and forecast communication to undergraduate students through an RShiny application. Tested with >250 undergraduate students, our assessment results suggest that the module significantly increased students’ ability to correctly define ecological forecasting terms, interpret forecast visualizations with uncertainty, and identify different ways to communicate forecast uncertainty for stakeholders. These results suggest that integrating ecological forecasting into undergraduate ecology curricula via software-based learning enhances students’ abilities to engage and understand complex ecological concepts.