Complexity–biodiversity relationships on marine urban structures: reintroducing habitat heterogeneity through eco-engineering
Bibliographic record
Abstract
Urbanization is leading to biodiversity loss through habitat homogenization. The smooth, featureless surfaces of many marine urban structures support ecological communities, often of lower biodiversity, distinct from the complex natural habitats they replace. Eco-engineering (design for ecological co-benefits) seeks to enhance biodiversity and ecological functions on urban structures. We assessed the benefits to biodiversity of retrofitting four types of complex habitat panels to an intertidal seawall at patch (versus flat control panels) and site (versus unmodified control seawalls and reference rocky shores) scales. Two years after installation, patch-scale effects of complex panels on biodiversity ranged from neutral to positive, depending on the protective features they provided, though all but one design (honeycomb) supported unique species. Water-retaining features (rockpools) and crevices, which provided moisture retention and cooling, increased biodiversity and supported algae and invertebrates otherwise absent. At the site scale, biodiversity benefits ranged from neutral at the high- and mid-intertidal to positive at the low-intertidal elevation. The results highlight the importance of matching eco-engineering interventions to the niche of target species, and environmental conditions. While species richness was greatest on rockpool and crevice panels, the unique species supported by other panel designs highlights that to maximize biodiversity, habitat heterogeneity is essential. This article is part of the theme issue 'Ecological complexity and the biosphere: the next 30 years'.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".