The meaning of the term ‘function’ in ecology: A coral reef perspective
Bibliographic record
Abstract
Abstract The inherent complexity of high‐diversity systems can make them particularly difficult to understand. The relatively recent introduction of functional approaches, which seek to infer ecosystem functioning based on species’ ecological traits, has revolutionized our understanding of these high‐diversity systems. Today, the functional structure of an assemblage is widely regarded as a key indicator of the status or resilience of an ecosystem. Indeed, functional evaluations have become a mainstay of monitoring and management approaches. But is the heavy focus on broad metrics of functional structure grounded in empirical research? On tropical coral reefs, the ocean’s most diverse ecosystems, remarkably few studies directly quantify ecosystem functions and the term ‘function’ is widely used but rarely defined, especially when applied to reef fishes. Our review suggests that most ‘functional’ studies do not study function as it relates to ecological processes. Rather, they look at easy‐to‐measure traits or proxies that are thought to have functional significance. However, these links are rarely tested empirically, severely limiting our capacity to extend results from community structure to the dynamic processes operating within high‐diversity ecosystems such as coral reefs. With rapid changes in global ecosystems, and in their capacity to deliver ecosystem services, there is an urgent need to understand and empirically measure the role of organisms in various ecosystem functions. We suggest that if we are to understand and manage transitioning coral reefs in the Anthropocene, a broad definition of the word ‘function’ is needed along with a focus on ecological processes and the empirical quantification of functional roles. In this review, we propose a universal operational definition of the term ‘function’ that works from a cellular to a global level. Specifically, it is the movement or storage of energy or material . Within this broad definitional framework, all functions are part of a continuum that is tied together by the process‐based unifier of material fluxes. With this universal definition at hand, we then present a path forward that will allow us to fully harness the power of functional approaches in understanding and managing high‐diversity systems such as coral reefs. A plain language summary is available for this article.
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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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.002 | 0.028 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.002 | 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".