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Enregistrement W1496143141 · doi:10.1111/conl.12044

A More Realistic Portrayal of Tropical Forestry: Response to Kormos and Zimmerman

2013· article· en· W1496143141 sur OpenAlexaff
Francis E. Putz, Pieter A. Zuidema, T.J. Synnott, Marielos Peña‐Claros, Michelle A. Pinard, Douglas Sheil, Jerome K. Vanclay, Plínio Sist, Sylvie Gourlet‐Fleury, John Palmer, Roderick Zagt, Bronson W. Griscom

Notice bibliographique

RevueConservation Letters · 2013
Typearticle
Langueen
DomaineEnvironmental Science
ThématiqueConservation, Biodiversity, and Resource Management
Établissements canadiensUniversity of British Columbia
Organismes subventionnairesnon disponible
Mots-clésLoggingStewardship (theology)Government (linguistics)Illegal loggingForest managementSustainable forest managementTropicsBiodiversityBusinessAgroforestrySubsidyTropical forestTropical and subtropical moist broadleaf forestsCommunity forestryDeforestation (computer science)GeographyForestryEcologyPolitical sciencePoliticsEnvironmental science

Résumé

récupéré en direct d'OpenAlex

In their response to our recent article (Putz et al. 2012), Kormos and Zimmerman (K&Z) do not take issue with the result of our meta-analysis of more than 100 published studies that biodiversity and carbon stocks are mostly retained in selectively logged tropical forests. Instead, they object to what they misconstrue as our advocacy of subsidies for logging operations. To be clear, what we advocate is support for efforts to improve tropical forest management and the safety of forest workers. For example, we endorse efforts to restrict logging in riparian buffer zones and on steep slopes, to promote careful planning of harvesting operations, and to provide worker training and safety gear. K&Z disregard the contributions of groups like the Forest Stewardship Council (FSC), the Tropical Forest Foundation, the Borneo Initiative, and the various environmental and social welfare groups that are helping to develop ways to compensate companies and communities for the costs of retaining more carbon in living trees through REDD+ and other mechanisms. K&Z's portrayal of all tropical forests as lawless frontiers is not accurate. Tropical forest logging is admittedly a messy business and apparently the areas in Brazil where K&Z's work are particularly problematic, but control over production forests is often substantial. Evidence for this claim is accumulating from government-issued forest concessions in Indonesia (Gaveau et al. 2012) to community-managed forests in Mexico (Duran-Medina et al. 2005) and elsewhere in the tropics (Porter-Bolland et al. 2012). Furthermore, while governance failures still occur far too frequently, steady increase in the area of natural tropical forest certified as responsibly managed by the FSC (now >13 million hectares) provides evidence that forest owners are increasingly able to protect and manage their resources. We applaud K&Z's advocacy of community-based forest management but question their assumptions about the fates of forests under community control. Although in many places in the tropics, rural livelihoods can only be maintained by forest clearing for agriculture, under some conditions communities try to retain their forest. To derive financial benefits from these forests and to mobilize logging capacity, communities increasingly employ industrial forestry models, often by partnering with industrial forestry firms, which means that the focus on good management practices should remain a priority. What should be avoided are community–company contracts that are unsatisfactory on either environmental or social grounds (e.g., Pokorny et al. 2010). Fortunately, there are already good examples of communities working effectively with industrial forestry firms under clear and well-defined contracts (Benneker 2008). Given the unlikelihood of huge expansions of strictly protected areas in the tropics, it seems logical to focus conservation efforts on forests from which timber will be harvested. Substantial improvements in management practices are possible, but their implementation will require the concerted efforts of the full range of environmental advocates (Sabogal & Casaza 2010). Disregard of these opportunities benefits no one (Sheil & Meijaard 2010). We agree with K&Z that some forests should be spared from logging, but where the likely and lucrative alternative to forest management for timber involves conversion, efforts should be made to increase the financial value of standing forests for all of their benefits, including their wood resources. Finally, given that wood is one of the lowest carbon-footprint structural materials (Perez-Garcia et al. 2005), banning industrial logging would have some perverse environmental outcomes. Although forest management has been widely demonized, and often for good reason, we should be prepared to look beyond weak generalizations and examine the evidence. Providing evidence for the conservation values of selectively logged tropical forests was exactly the aim of the meta-analysis in our 2012 article (Putz et al. 2012). Now the challenge is to discover the best ways to improve management practices so that even more of these values are maintained.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

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)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,058
Score d'incertitude au seuil0,494

Scores Codex et Gemma par catégorie

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

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.

Tête enseignante Opus0,009
Tête enseignante GPT0,200
Écart entre enseignants0,191 · 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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2013
Routes d'admission1
Résumé présentoui

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