Frontiers in Ecosystem Ecology from a Community Perspective: The Future is Boundless and Bright
Bibliographic record
Abstract
In an era of increasingly multidisciplinary science, it is essential to identify the frontiers as well as the core of an inherently holistic discipline: ecosystem ecology. To achieve this, we led a series of town hall events at multiple scientific-society meetings over a two-year period followed by a workshop with a diverse set of ecosystem scientists to review and expand on those outcomes. For the society town hall events ~70 individuals were asked to give short, provocative (the so-called, soapbox) presentations and audience members (~250) filled out tailored surveys. Both presentations and surveys were transcribed and themes were extracted and analyzed before and during the follow-up workshop. Formal ethnographic analysis of the soapbox texts produced three major themes: “frontiers,” “capacity building,” and “barriers to implementation,” including several subthemes. A workshop was held to analyze the ethnographic data where workshop participants further grouped key frontiers as (1) rethinking the drivers of ecosystem change, (2) new insights into ecosystem process and function, (3) evaluating human dimensions of ecosystem ecology, and (4) new angles on problem-solving/applied research. In addition, 13 experts were interviewed to crosscheck interpretations. The survey data, workshop deliberations, and expert interviews suggest that the core of these frontiers defines the current state and provides the foundational knowledge that bounds ecosystem ecology as a discipline. In response to emerging complex environmental issues and ongoing socioecological challenges, the edges of these frontiers expand fundamental ecosystem ecology to engage and intersect with disciplinary realms to create new ways of making sense of complexity, and to develop an even more holistic understanding of ecological systems. In this paper, we present our synthesis of the frontier and core research themes with the goal of inspiring the next wave of studies in ecosystem ecology.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.023 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.017 | 0.059 |
| Scholarly communication | 0.026 | 0.047 |
| Open science | 0.002 | 0.019 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".