Scientists' warning on the need for greater inclusion of dragonflies in global conservation
Bibliographic record
Abstract
Abstract Dragonflies (Odonata) are ancient and familiar insects with a deep and strong cultural association with humans. They have an aquatic larval stage and an aerial adult stage, meaning that they respond to ecological conditions in both freshwater and the adjacent land surface. Currently, 16% of dragonflies are threatened. Overall, they face several threats, especially habitat loss, landscape transformation, pollution, altered hydrology, spread of invasive alien species, as well as certain geographic‐specific threats. Overarching these threats, which can be interactive with each other, is the issue of global climate change and attendant extreme weather events. While many localised and habitat specialist species are under extreme threat, some other dragonfly species, mostly habitat generalists, benefit from certain moderate human activities, especially the creation of high‐quality artificial ponds. As well‐researched insects, dragonflies play an important role in the protection of freshwater and riparian ecosystems. Dragonfly assemblages have great value as sentinels of both deteriorating environmental conditions and ecosystem recovery following restoration. While similar findings on both threats and conservation actions are emerging across the world, certain ecosystems require targeted approaches. Above all, dragonflies must be included more widely in general biodiversity conservation activities and policies. Overall, dragonflies are important targets, tools and model organisms for conservation action, and they can act as potential surrogates for other taxa that also depend on high water and riparian zone quality. While research has paved the way to address these challenges, including the use of new technologies, we now urge that dragonflies be included more strongly in policy and management associated with both freshwater and adjacent terrestrial realms. This inclusion is especially effective as dragonflies have great appeal to a diverse community of people from odonatologists (citizen and professional) through to policymakers and managers, all of whom can employ dragonflies to contribute more to freshwater‐associated conservation. Finally, we propose an action plan focusing on five action points that address opportunities, and we suggest where dragonflies can play a greater role in freshwater/riparian zone conservation more widely across the world.
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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 | 0.019 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.012 | 0.019 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".