Ecological forecasting is going to transform our understanding of ecology. I am thrilled to have the opportunity to help coordinate efforts to improve and move the field forward.
Summary: Ecological forecasts can be used to predict changes in ecosystems and subsequent impacts on communities. In addition to long-term projections, there is an important need for forecasts in shorter-term decision-making time periods of weeks and months. Scientists at the Ecological Forecasting Initiative are working to advance the field through a process that enables them to continually update model predictions with observed data in order to improve our ability to foresee what may happen in the future. These scientists are calling on greater investment in these efforts, asking the scientific community to collectively commit to building the capacity to improve the field while calling on world nations, major corporations, and NGOs to integrate ecological forecasting into their climate adaptation and mitigation strategies.
Climate and biodiversity crises threaten our ability to manage and conserve natural resources, putting many ecosystems at risk of collapse. Ecological forecasts are a tool used to predict changes in ecosystems and how communities may be impacted. These forecasts can then be used to make decisions to mitigate environmental impacts and build a future that is climate resilient. But while many ecological forecasts have focused on predictions for 2100 and beyond, climate change is happening now and there is an urgent need for forecasts in shorter-term decision-making time periods of weeks and months.
This urgency has led scientists organized through the Ecological Forecasting Initiative (EFI) to call for increased infrastructure for predicting nature and environmental events. This call to action was recently published in Nature Climate Change. EFI is also urging world nations and UN bodies, major international corporations, and NGOs to integrate ecological forecasting into their climate adaptation and mitigation strategies while encouraging the scientific community to commit to building the technological and institutional capacity to respond to this urgent need.
Ecological forecasting is at a critical point for future growth according to Michael Dietze, EFI’s chair and lead of the Ecological Forecasting Laboratory at Boston University. “We have a lot of know-how and advances in sensing technologies, AI, and computing have opened new doors, but we now need to scale up the overall forecasting enterprise considerably to help society mitigate and adapt to widespread change in ecosystems in the face of climate change.”
Specifically, EFI scientists are talking about advancing the field of near-term iterative ecological forecasting, through which forecasts are regularly updated given new data. The forecasts can be compared to what actually happened, and the models can then be improved given what is learned to make more accurate predictions.
“Because you are constantly updating the forecasts as new information becomes available, near-term iterative ecological forecasting establishes a learning loop that is a win-win situation for ecology and decision making,” added Dietze. “The same forecasts that improve decision making on actionable timeframes also accelerate scientific understanding and help us probe new frontiers of discovery about how nature works.”
This iterative approach has been used by atmospheric scientists for decades, who, helped by large-scale investments in weather monitoring, modeling, and data assimilation, were able to continuously improve weather forecasts. In the early days of numerical weather prediction, weather forecasters had the choice between stepping away from forecasting until the mechanics of the atmosphere were better understood or stepping forward into an iterative forecast cycle of learning by doing – through choosing the latter, they achieved a critical win-win of relentless improvements.
Ecological forecasting is at a similar crossroads, though the challenge is more complicated because of the complexity of biodiversity and environmental systems. Scientists are seeing dramatic improvements in the field of ecological forecasting that were unimaginable even a decade ago, much of it fueled by advances in sensor technologies, satellites, computation methods, and machine learning. And, due to shifts towards large-scale networked science, data access has become more standardized and equitable. Thus, the time is right to accelerate our investment.
One of the ways that EFI has supported these advancements is through the ongoing National Ecological Observatory Network (NEON) Forecasting Challenge, which has the goal of predicting NEON data before it is collected. This challenge has involved over 200 teams and developed new educational resources and community cyberinfrastructure. “Ecological forecasting needs to build communities of practice to support its growth as a discipline to leverage these technical advances,” Quinn Thomas, who co-directs the Virginia Tech Center for Ecosystem Forecasting and leads the EFI NEON Forecasting Challenge.
One of the areas where there has been traction is exploring opportunities for cross-government agency collaborations on cyberinfrastructure. Cyberinfrastructure – such as models, community standards, consistent server time, and workflows – have community-scale benefits by reducing the costs, time, and learning curve involved in launching and maintaining forecasts. As an international grassroots consortium, EFI has taken a leadership role in piloting and hosting conversations about scaling cyberinfrastructure for the benefit of the larger community of practice.
“The field of ecological forecasting has included partnerships across many sectors – academia, governmental agencies, industry, and NGOs,” stated Melissa Kenney, Director of Research at the University of Minnesota’s Institute on the Environment and a founding leader of EFI. “Such partnerships are critical to support the design and improvement of regularly updated forecasts that both improve the science and support decisions.”
“This is a new field of science that is at a transition point,” says Dietze. “Key investments in investments in education, training, community building, sensing and computational infrastructure, tool and model development, and research to operations is critical to rapidly scale forecast innovations in ways that will help address climate and biodiversity crises.”
The ESA Statistical Ecology section presented the 2024 Ecological Forecasting Outstanding Publication Award to Cerres Barrosand co-authors, Yong Luo, Alex Chubaty, Ian Eddy, Tatiane Micheletti, Céline Boisvenue, David Andison, Steven Cumming, & Eliot McIntire, for their 2023 Methods in Ecology and Evolution paper:
The award committee was strongly impressed by the way this paper clearly organized and presented cyberinfrastructure principles that are an increasingly important part of doing ecology well. This paper helps to translate software engineering concepts into clear take home messages that are accessible to ecologists (e.g., predictions depend on workflows, not just models) and draws attention to the need for Interdisciplinary teamwork in successful ecological forecasting. The committee was further impressed by this team’s commitment to developing tools that are accessible, reusable, and multi-purpose, and that address the challenges of operationalizing ecological forecasts.
In addition to an award plaque and prize ($200), this year’s recipient will also receive a £120 credit from Routledge books.
2024 – Cerres Barros (University of British Columbia) Barros, C., Luo, Y., Chubaty, A. M., Eddy, I. M. S., Micheletti, T., Boisvenue, C., Andison, D. W., Cumming, S. G., & McIntire, E. J. B. (2023). Empowering ecological modellers with a PERFICT workflow: Seamlessly linking data, parameterisation, prediction, validation and visualisation. Methods in Ecology and Evolution, 14, 173–188. https://doi.org/10.1111/2041-210X.14034
2023 – Jacob Zwart (USGS) Zwart, J.A., Oliver, S.K., Watkins, W.D., Sadler, J.M., Appling, A.P., Corson-Dosch, H.R., Jia, X., Kumar, V., and Read, J.S. 2023. “Near-Term Forecasts of Stream Temperature Using Deep Learning and Data Assimilation in Support of Management Decisions.” JAWRA Journal of the American Water Resources Association 59 (2): 317–37. https://doi.org/10.1111/1752-1688.13093.
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.
EFI is excited about the opportunity to connect with the broader ecological forecasting community through a number of events at ESA in Long Beach, California this year! Below are details about the EFI Social, a workshop about the NEON Forecasting Challenge, multiple sessions organized by EFI and others about forecasting EFI-organized and other forecasting, and a Career Central panel. 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 to this list!
We will again have EFI badges to add to your name tags! We will continue to make updates to this page prior to ESA. All times listed below are in US Pacific Time.
EFI Badges
We will have EFI badges that can be attached to the ESA name tags available for individuals who are part of the Ecological Forecasting Initiative community. Find Mike Dietze throughout the week or at the EFI Social on Wednesday to get a badge and look for others with the green badge!
Schedule Summary
Schedule Details
EFI Social Wednesday, August 7 at 6:30-8:30 PM
Connect and network with others in the EFI community over food, including vegan and vegetarian options at The Auld Dubliner. The Auld Dubliner is just 400 feet from the Convention Center.
This workshop will provide an overview of the EFI RCN NEON Ecological Forecasting Challenge theme forecasting ground beetle abundance and richness across NEON terrestrial sites. The workshop will include code-along instructions to help participants create and submit a simple forecast to the Forecasting Challenge platform as well as interpret metrics of forecast skill. Participants will gain a foundation that can be built upon to create more sophisticated predictions about ecological communities and use the EFI RCN resources in future forecasting applications.
This session, organized by Charlotte Malmborg (Boston University) and R. Alex Thompson (Washington State University), has been in the works since ESA 2023 with conversations about the then-blog post, now-published paper about model complexity (https://doi.org/10.1002/met.2202). There will be an audience discussion following the panelists and it would be great to have fellow forecasters join that discussion.
Extreme weather events, including heat waves, droughts, flooding, and unusual cold periods, are a major component of global climate change. Despite increases in the frequency and magnitude of extreme weather events, direct and indirect effects on biodiversity, phenology, and ecosystem services remain poorly understood. Assessing and anticipating impacts of extreme weather presents unique obstacles across systems, geographies, and scales. Key challenges include availability of and accessibility to relevant data resources, development of methods and approaches to characterize extreme weather events, and obstacles to predicting and forecasting. Solutions require multidisciplinary collaborations across the ecological community to develop effective tools and resources to address these challenges. We propose a session to convene a panel of experts spanning multiple career stages in the fields of biodiversity informatics, plant and insect phenology, and vector borne disease systems to discuss key challenges to understanding and anticipating extreme weather effects across organisms, phenology, and ecosystems. Session hosts will provide a talk outlining work within their field of expertise, followed by an interactive panel and audience discussion. The session will culminate in a dedicated 10-minute discussion, facilitated by the organizer, focusing on facilitating cross-disciplinary collaborations to leverage knowledge and approaches applicable to addressing challenges across domains.
Speakers: Robert Guralnick (University of Florida), Michael Belitz (Michigan State University), Daijiang Li (Louisiana State University), Assaf Anyamba (Oak Ridge National Laboratory)
Join this insightful session with founders of ecological organizations, consulting services, and innovative initiatives. Panelists are entrepreneurs who have demonstrated initiative, leadership, and innovation in creating and leading their communities of practice. If you identify with these qualities, you too can become an entrepreneur.
Panelists: Tim Nuttle (Oikos Ecology), Michael Dietze (Ecological Forecasting initiative), Shah Selbe (Conservify and FieldKit)
The EFI2024 Conference provided the second opportunity for EFI to give out 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. Awards were given to students who gave both Posters and Oral Presentations. Poster or oral presentations were anonymously reviewed by three volunteer reviewers with no conflicts of interest with the presenters. In addition to being recognized for their outstanding work, award winners get to select any item from 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!
Gabrielle Koerich (University of Canterbury) won for her oral presentation, “Modelling bryophyte distributions in Antarctica: unveiling the influence of water availability, sampling bias, and spatially complex dynamics” and
Nima Farchadi (San Diego State University) won for his poster “Integrating diverse data for robust species distribution models in a dynamic ocean.”
See Gabrielle and Nima’s presentation details below.
Modelling bryophyte distributions in Antarctica: unveiling the influence of water availability, sampling bias, and spatially complex dynamics
Gabrielle Koerich1 , Hao Ran Lai1 , Grant Duffy2 , Eva B. Nielsen1 , Jonathan D. Tonkin1 1University of Canterbury, Christchurch, New Zealand. 2University of Otago, Dunedin, New Zealand
Abstract: In Antarctica, observations of biodiversity are often incomplete and commonly restricted to presence-only data, as sampling in the continent is difficult. Thus, understanding and forecasting the range dynamics of key taxa, such as bryophytes, requires a modelling framework capable of dealing with such challenges. Here, we developed log-Gaussian Cox process models of bryophytes’ across the entire Antarctic continent to (1) assess whether broad-scale bryophytes distributions are driven by water availability, as widely hypothesized; (2) map and forecast their distributions and identify under sampled regions; and (3) determine if there’s a spatial dependency between “patches” of bryophytes, which may be related to their limited dispersal in Antarctica. Results show that the main driver of bryophytes distributions in Antarctica is indeed related to areas where water tends to accumulate (97.5% CI:-0.886;-0.797). Maximum temperature was the second most important predictor (97.5% CI: 0.511; 0.681), signalling the importance of elevated temperatures for bryophytes’ restricted metabolism in this extreme environment. The covariate related to human activity showed a high level of sampling bias, and by accounting for this covariate in predictions, we detected habitat suitability for bryophytes in two under-sampled mountain ranges. Finally, the inclusion of a Gaussian random field to account for spatial autocorrelation increased model performance (pseudo R2 and mapped mean estimated density), indicating a spatial dependency between the presence of mosses. Our study demonstrates that a spatially structured modelling framework can provide robust results and allow for valuable forecasts of biodiversity change in data-poor regions.
Integrating diverse data for robust species distribution models in a dynamic ocean
Nima Farchadi1 , Camrin Braun2 , Martin Arostegui2 , Rebecca Lewison1 1San Diego State University, San Diego, USA. 2Woods Hole Oceanographic Institution, Woods Hole, USA
Abstract: Species distribution models (SDMs) are an important tool for marine conservation and management. Despite the burgeoning use of SDMs, limited guidance is available on how to leverage distinct data types to build robust models. Here we assess whether an integrative model framework improves performance over traditional data pooling or ensemble approaches when synthesizing multiple data types. We trained traditional, correlative SDMs and integrative SDMs (iSDMs) with three distinct data types that represent the distribution of a heavily exploited pelagic fish, the blue shark (Prionace glauca), in the North Atlantic. Weevaluated data pooling and ensembling approaches in a correlative SDM framework and compared performance to a model-based data integration approach designed to explicitly account for data-specific biases while retaining the strengths of each dataset. We found that while each integration approach can result in robust models, there was variation in predictive accuracy among data types, with all models predicting fishery-dependent data more accurately than fishery-independent data. Differences in performance were primarily attributed to each model’s ability to explain the spatiotemporal dynamics of the training data, with iSDMs including spatiotemporal terms to have the most accurate and ecological realistic estimates. Our findings reveal trade-offs in the current techniques for integrating data in SDMs between accurately estimating species distributions, generating ecologically realistic predictions, and practical feasibility. With increasing access to growing and diverse data sources, comparing integration approaches can provide valuable guidance for practitioners navigating diverse data types in SDM development and will help users better understand model biases and estimate error.
The Diversity, Equity, and Inclusion (DEI, see point 1 below) working group was created because EFI recognizes that we need involvement and collaboration with underrepresented groups to equitably meet the needs of diverse communities who are using and impacted by ecological forecasts. To this end, the EFI DEI working group, led by input from Diana Dalbotten (University of Minnesota) began in October 2019 to develop an EFI DEI Working Group Strategic Plan (Figure 1) with steps to broaden participation in EFI. At the time, the focus had mainly been on broadening racial diversity based on racial categories common within the United States. Yet other metrics of diversity (gender, nationality, career stage, academic discipline, occupation sector) are also important to EFI. By May 2020, the group posted the Strategic Plan on the EFI DEI working group page to publicly share the plan and use it as official guidance for group activities.
Four years later, the DEI working group is revisiting the plan to remind ourselves of our activities and place them within the context of the Strategic Plan. Our goal is to consider which activities the group sees as successful and where there continue to be opportunities for growth.
Point 1Although the working group name uses the acronym DEI, we recognize that Justice is an integral part of DEI work. We therefore refer to the EFI Working Group as DEI and the activities of the group as DEIJ.
Figure 1 . Steps in the original DEI Strategic Plan
The original DEI Strategic Plan highlighted that, just as the iterative approach is useful for ecological forecasting, likewise it is beneficial for the process of engaging with people from underrepresented backgrounds. However, during our reecnt review process, the DEI Strategic Plan instead appeared as a fairly linear process, which in practice, it has not been. Instead, the group has worked on projects across all six steps as opportunities have become available or aligned with ongoing work.
The working group is planning to revise the original Strategic Plan. To this end, the group envisions adding Diversity, Equity, Inclusion, and Justice (DEIJ) perspectives and actions into EFI activities as a spiral rather than a circle (Figure 2). The group will continue to refine the iterative nature of EFI’s DEIJ efforts and will share details about that in the future. For this blog, however, our goal is to compile a record of what has been done to acknowledge past efforts and inspire and inform future efforts. Future steps will assess what has been successful, examine whether or not we have the metrics to measure success, and reflect on challenges that we can learn from to improve the iterative process in future efforts.
Figure 2. A potential new way to think of the EFI Strategic Plan
Strategic Plan Steps
Below we list the six steps of the Strategic Plan and the DEI working group activities for each step.
Step 1: Identify and clarify the problem.
JEDI Database – Dave Klinges (University of Florida) and Jody Peters (University of Notre Dame) have collaborated to develop a workflow to take anonymized EFI membership information and create plots of diversity metrics (see Figures 3-7 below) to assess how the community has changed through time, relative to external baselines.
Publication: Willson et al 2023. Assessing opportunities and inequities in undergraduate ecological forecasting education. Ecology and Evolution 13(5): e10001.
Willson et al. compiled resources for teaching and learning ecological forecasting at different curriculum levels and identified gaps between ecological forecasting courses offered at doctoral universities, in comparison to other colleges and universities. The authors also noted a general lack of high-level, quantitative forecasting opportunities for undergraduates.
Step 2: Identify barriers that may be preventing students from underrepresented groups to participate in ecological forecasting as a career.
Sean Dorr (University of Minnesota) has led and fostered discussions, workshops, and focus groups for multiple EFI activities about the Design Justice Principles as they relate to the Forecasting Challenge and forecasting cyberinfrastructure
DEI Book Clubs have met since 2020 to provide opportunities for the EFI community to learn about different topics of racism, diversity, inclusion, and justice through small group discussions
Step 3: Identify possible solutions that could be taken.
The DEI working group meets monthly, and conversations include identifying solutions for barriers identified in Step 2 and then working on solutions in Step 4. Meeting notes from the monthly calls can be found at the bottom of the DEI webpage.
DEI Book Club suggestions and action items
In October 2023, the DEI Working Group created this living document to provide a summary of action items suggested during book club calls. The living document is to be used as a reference to support and inspire activities for EFI that can be developed and led as individuals have time, availability, and interest in doing so. The living document also provides an opportunity to collate and celebrate activities that have taken place that have been inspired by or align with suggestions from the book clubs.
Based on Willson et al 2023, the group identified curriculum development at minority serving institutions as a solution to address the lack of ecological forecasting in course work and a path to introduce more Native American students to ecological forecasting topics.
Step 4: Identify which solutions from Step 3 make sense to work on now for the EFI group.
The Bibliography is a living document that provides resources for learning more about anti-racism and the diversity status of fields relevant to ecological forecasting. These resources include lists of minority supporting associations, links to diversity and inclusion plans from professional societies, blog posts, publications, and compiled lists of resources from other organizations. Additional resources shared through the working group are continually added. If you are aware of additional resources to include, please submit them to this Google form.
The Bibliography resources are also included in the EFI Zotero library and tagged as “EFI DEI Paper” papers
The EFI Steering Committee is dedicated to always having one or more people with experience addressing DEIJ issues on the committee, and increasing diversity, equity, and inclusion is one of the five high level objectives of EFI’s Strategic Plan.
4-part virtual seminar series titled “Conversations on Diversity and Data Seminar Series” – foster conversations, brainstorm actions, and make community connections that help promote diversity within ecological forecasting. Recordings and resources from these panel conversations are available in the links below.
The book club group that read Braiding Sweetgrass by Robin Wall Kimmerer developed a gratitude statement regarding data as a gift from the community. You can find the statement on the DEI webpage and the Book Club webpage.
The Braiding Sweetgrass book club included student participants from the Sustainable Land and Water Resources (SLAWR) REU, which provided opportunities for discussions across career stages and sectors
Job posts and funding opportunities are listed on EFI’s Slack group and in the newsletters to increase visibility to the EFI community
Step 5: Identify who else needs to be involved in the process and make a plan to bring them in.
Note that this step might actually be better as Step 1–what groups should be involved in identifying the problem? If the problem is that the right people are not involved, how can we adequately examine the barriers and identify solutions? We realize we cannot solve the problem without broader participation in identifying the issues, barriers, and potential strategies.
Building relationships is a critical part of this step, and relationship building takes time and trust. Diana Dalbotten (University of Minnesota) has been largely influential in helping to set up collaborations with individuals at minority serving and Tribal institutions. These partnerships produced funding success from the Alfred P. Sloan Foundation and funding applications submitted to the National Science Foundation. As these relationships continue to develop, they inform actions to prioritize and relationship building efforts.
Identifying collaborators and building relationships can happen at any point in the process, but they are included as a step here to acknowledge that, as more work is done, it will inform which partners are still missing. We can then be intentional about bringing in more people to fill these gaps. In recognizing that this step links back to Step 1 (Identifying and clarifying problems), we again want to shift our thinking to follow a spiral rather than linear path, as a spiral builds on previous work as seen in Figure 2.
Step 6: Form collaborations and seek funding to carry out the plan.
Successful: Alfred P. Sloan Foundation grant that brings together partners from Salish Kootenai College, Cal Poly Humboldt, University of New Mexico Gallup, University of Notre Dame, and the University of Minnesota
The goals of this grant include developing culturally responsive educational resources and supporting research efforts of underrepresented undergraduate and graduate students, creating actionable paths forward to address the problems and barriers identified in Steps 1-2.
Unsuccessful: National Science Foundation
Opportunities for Growth
As the DEI working group considers our next steps and future activities, we first look back with pride at the range of activities highlighted here, noting that much of this has been done with volunteer efforts. Those in the DEI working group have also experienced personal growth in understanding racism and systemic barriers in science and ecological forecasting.
In addition to having an impact within the group, the impact of the DEI working group has expanded to other EFI activities. Recent Education working group discussions have revolved around understanding the history of Tribal and Historically Black Colleges and Universities in the US. The Education working group-led paper on Ethics in Forecasting Educational Modules (https://tiee.esa.org/vol/v19/issues/case_studies/lewis/abstract.html) includes considerations for who participates, uses, or is impacted by forecasts and data science. Additionally, Design Justice Principles were a key component of a recent EFI Cyberinfrastructure Workshop. The Translation and Actionable Science working group has discussed topics such as the racial history of the term “stakeholder”, DEIJ implications of different types of collaborations (from community-led, to collaborative, to extractive), and how different situations can support or be detrimental to relationship building along the spectrum of collaborative efforts. As demonstrated, DEIJ issues transcend beyond the DEI working group, and we encourage other EFI subgroups to continue to consider DEIJ impacts of their discussions and efforts.
One of the high level objectives of the EFI Strategic Plan is to increase diversity, equity, and inclusion, and this has been an overarching component for the EFI Steering Committee as they make decisions. As noted above, the Steering Committee is dedicated to ensuring that at least one member is experienced in addressing DEIJ issues, and in the short-term, this goal seems accomplishable (see Engagement paragraph below for more long-term considerations). Similarly, EFI Conferences consistently include DEI workshops or sessions, and when considering whether to support workshop efforts by partners, we advocate for diverse representation in speakers or participants. Given lessons learned regarding the development of workshops and sessions, we see this as a relatively straightforward space where we can continue to participate and grow.
Engagement is an area where the DEI working group has struggled. We appreciate all the work that has been done through volunteers, but we also recognize that some people who may want to get involved do not have time to volunteer. The DEI working group has expanded over the past four years, but it is often a core group of individuals who participate in calls or book clubs. Continued engagement and growth will become especially important in five to ten years for maintaining a Steering Committee member with DEIJ experience, as this will be about the time when all of the individuals from the core group will have already served. If the group has not grown, unideal solutions may include second terms of service or recruitment of individuals with expertise in the DEIJ space but who have little knowledge of EFI. We see engagement as a struggle that is not unique to EFI and reflects, in part, patterns and issues in ecology and data science more broadly. We must continue to seek new perspectives and discuss solutions to this barrier.
The DEI working group activities that are most successful are ones that align with the research and activities that people are already doing. This likely reflects the above struggles with volunteer-based progress. When DEIJ efforts align with paid work, the projects tend to be prioritized and therefore actually come to fruition. Still, finding a good balance in overlap of current research programs and DEIJ work is hard in a geographically and topically distributed community. Relationships have been built (and continue to grow), but we also recognize that it takes a long time to gain trust and demonstrate reciprocity.
The DEI working group is looking forward to revising the DEI Strategic Plan and working on the continual process of advancing DEIJ efforts within EFI.
JEDI Images
Figure 3. Changes in the discipline of EFI members.
Figure 4. Changes in the occupation section of EFI members.
Figure 5. Changes in the nationality of EFI members.
Figure 6. Changes in the race of EFI members who indicated they are from the United States.
Figure 7. Gender composition of EFI members in June 2024.
