Non‐native species outperform natives in coastal marine ecosystems subjected to warming and freshening events
Bibliographic record
Abstract
Abstract Aims Contemporary climate change and biological invasions are two main drivers of biodiversity redistribution. Interactive effects between these drivers have been reported in a variety of studies, yet results are conflicting. Some studies find that contemporary climate change facilitates the spread and success of non‐native species, especially those with broad physiological tolerances. Other studies conclude that non‐natives are vulnerable to current and future changes in climatic conditions. Given that most studies have focused on terrestrial species, here we contribute to this debate by analysing responses of marine native and non‐native fauna and flora to key climate‐related stressors, namely increased temperature (warming) and decreased salinity (freshening). Location Global. Time period 2002–2019. Major taxa studied Marine benthic macrophytes and invertebrates. Methods We conducted a meta‐analysis of experiments investigating the performance (e.g. growth, survival and reproduction) of benthic species in response to warming and freshening. Results We found that non‐native species tended to respond positively to elevated temperature, whereas the performance of native species declined. Similarly, decreased salinity negatively affected the biological processes of native species, but non‐natives showed neutral or negative overall responses to freshening. Main conclusions We find evidence that non‐native species outperform natives under a wide variety of warming and freshening conditions. The growth and reproduction of non‐natives are enhanced by warmer temperatures, and thus ocean warming is expected to facilitate future spread and success of non‐native species. Increased freshening along future coastal areas, however, will likely have a negative impact in both native and non‐native species and thus is expected to be a driver of significant change in coastal marine ecosystems. Our comprehensive analysis highlighted the need to expand our understanding of climate change effects beyond warming and specifically, studies focusing on salinity changes.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".