Can linear transportation infrastructure verges constitute a habitat and/or a corridor for insects in temperate landscapes? A systematic review
Notice bibliographique
Résumé
Abstract Background The role of linear transportation infrastructures (roads, railways, oil and gas pipelines, power lines, rivers and canals) in fragmenting natural habitats is fully acknowledged. Up to now, the potential of linear transportation infrastructures verges (road and railway embankments, strips of grass under power lines or above buried pipelines, or waterway banks) as habitat or corridor for biodiversity, remains controversial. In a context of decreasing natural habitats, the opportunities of anthropogenic areas for contributing to wildlife conservation have to be considered. The present paper is the first synthesis of evidence about the potential of linear transportation infrastructure verges as corridor and/or habitat for insects in temperate landscapes. Methods A systematic literature survey was made using two online publication databases, a search engine and by sending a call for literature to subject experts. Identified articles were successively screened for relevance on titles, abstracts and full texts using criteria detailed in an a priori protocol. We then used six specific questions to categorize and to critically appraise the retained studies. These questions encompassed the potential of verges as habitats and corridors for insects, and the effects of management and landscape context on these potentialities. A user-friendly database was created to sort the studies with low and medium susceptibility to bias. We used these studies to synthesize results of each specific question in a narrative synthesis. Finally, studies that met the meta-analysis requirements were used for a quantitative synthesis. Results Our searches identified 64,206 articles. After critical appraisal, 91 articles that reported 104 studies were included in our review. Almost all of them had “control-impact” design, only two studies used “before-after-control-impact” design, and one study used “before-after” design. In some cases, artificialization of transportation infrastructures lowered insect biodiversity while vegetation restoration had a moderate positive effect; the trend remained unclear for mowing/grazing practices. Urbanization and agriculture in the surroundings tended to lower the biodiversity hosted by verges, while natural and forested areas tended to promote it. No study dealt with the influence of management or surrounding landscape on insect dispersal along the verge. The small number of studies that compared the dispersal along verges and in habitats away from transportation infrastructures, together with the inconsistencies of their results, prevented us from drawing conclusions. Meta-analyses were performed on 709 cases from 34 primary studies that compared biodiversity in verges vs. other habitats. Overall insect species richness did not differ between LTI verges and compared habitats. Globally, insect abundance seemed higher on LTI verges than in compared habitats, a result driven by the higher abundance of pollinators and primary consumers on non-highway road verges than in habitats away from roads. Conclusions A major knowledge gap regarding the potential of linear transportation infrastructure verges as corridors for insects has been identified. Thus, we encourage more research on this topic. Infrastructure practitioners could benefit from our results about linear transportation infrastructure verges as habitat for certain taxa and about the impact of their management practices on insect abundance and species richness.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,015 | 0,065 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,007 | 0,006 |
| Bibliométrie | 0,018 | 0,017 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,004 | 0,004 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».