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Enregistrement W2886175104 · doi:10.1186/s13750-018-0131-5

What is the effect of prescribed burning in temperate and boreal forest on biodiversity, beyond pyrophilous and saproxylic species? A systematic review

2018· review· en· W2886175104 sur OpenAlex

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Notice bibliographique

RevueEnvironmental Evidence · 2018
Typereview
Langueen
DomaineEnvironmental Science
ThématiqueFire effects on ecosystems
Établissements canadiensCarleton University
Organismes subventionnairesStiftelsen för Miljöstrategisk Forskning
Mots-clésBiodiversityEcologySpecies richnessBorealForest managementTemperate forestTaigaTemperate rainforestChecklistEnvironmental resource managementGeographyTemperate climateEnvironmental scienceBiologyEcosystem

Résumé

récupéré en direct d'OpenAlex

Abstract Background While the effects of prescribed burning on tree regeneration and on pyrophilous and/or saproxylic species are relatively well known, effects on other organisms are less clear. The primary aim of this systematic review was to clarify how biodiversity is affected by prescribed burning in temperate and boreal forests, and whether burning may be useful as a means of conserving or restoring biodiversity, beyond that of pyrophilous and saproxylic species. Methods The review examined primary field studies of the effects of prescribed burning on biodiversity in boreal and temperate forests in protected areas or under commercial management. Non-intervention or alternate levels of intervention were comparators. Relevant outcomes were species richness and diversity, excluding that of pyrophilous and saproxylic species. Relevant studies were extracted from a recent systematic map of the evidence on biodiversity impacts of active management in forests set aside for conservation or restoration. Additional searches and a search update were undertaken using a strategy targeted to identify studies focused on prescribed burning interventions. Grey literature and bibliographies of relevant published reviews were also searched for evidence. Studies were assessed for internal and external validity and data were extracted, using validity assessment and data extraction tools specifically designed for this review. Studies were presented in a narrative synthesis and interactive map, and those which were suitable were quantitatively synthesised using meta-analyses, subgroup analysis and meta-regression. Results Searches generated a total of 12,971 unique records. After screening for relevance, 244 studies (from 235 articles) were included in this review. Most studied forests were located in the USA (172/244), with the rest located in Canada, Europe and Australia. Eighty-two studies reporting 219 comparisons were included in the quantitative synthesis. Within the meta-analyses for each group of taxa, we identified a small to moderate volume of evidence, and heterogeneity was ubiquitous. Prescribed burning had significant positive effects on vascular plant richness, non-native vascular plant richness, and in broadleaf forests, herbaceous plant richness. Time since the burn, forest type and climate zone were significant moderators predicting the effect of burning on herbaceous plant richness. No other significant relationships were identified. Conclusions Knowledge gaps exist for studies outside North America, in mixed forests and for non-plant organism outcomes. We identify a need to apply study designs consistently and appropriately, minimising the impact of confounding factors wherever possible, and to provide extensive detail in study reports. We recommend that researchers build long-term datasets charting the impacts of prescribed burning on succession. The lack of consistent findings was likely due to high inter-study heterogeneity, and low numbers of comparable studies in each quantitative synthesis. We found no consistent effects of moderators, and were unable to test the effect of many potential moderators, due to a lack of reporting. Rather than making any general recommendations on the use of prescribed burning for biodiversity restoration, we provide an evidence atlas of previous studies for researchers and practitioners to use. We observe that outcomes are still difficult to predict, and any restoration project should include a component of monitoring to build a stronger evidence base for recommendations and guidelines on how to best achieve conservation targets. Prescribed burning may have harmful effects on taxa that are conservation-dependent and careful planning is needed.

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Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Revue systématique · Signal consensuel: Revue systématique
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,026
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,000
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0020,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,001
Communication savante0,0000,001
Science ouverte0,0010,001
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,001

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.

Tête enseignante Opus0,017
Tête enseignante GPT0,248
Écart entre enseignants0,231 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle