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Record W2972585250 · doi:10.1016/j.jnc.2019.125747

Towards a set of national forest inventory indicators to be used for assessing the conservation status of the habitats directive forest habitat types

2019· article· en· W2972585250 on OpenAlex
Marko Kovač, Patrizia Gasparini, Monica Notarangelo, Maria Rizzo, Isabel Cañellas, Laura Fernández‐de‐Uña, Icíar Alberdi

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal for Nature Conservation · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicForest Ecology and Biodiversity Studies
Canadian institutionsnot available
FundersInfrastructure CanadaHorizon 2020Horizon 2020 Framework ProgrammeEuropean CommissionU.S. Forest ServiceJavna Agencija za Raziskovalno Dejavnost RSNational Foundation for IndiaMinisterio de Agricultura, Pesca y Alimentación
KeywordsHabitats DirectiveHabitatEnvironmental resource managementForest inventoryIntact forest landscapeForest managementConservation statusBiodiversityGeographySet-asideEconomic shortageNational forestHabitat conservationNatura 2000Nature ConservationForest ecologyEcologyEnvironmental scienceForestryEcosystemBiology

Abstract

fetched live from OpenAlex

Since the enactment of the EU Habitats Directive, the conservation status of forest habitat types, habitats of species, and species has become the central concept of the Directive's nature conservation legislation. Despite its role, it has drawn relatively little attention. Within a rather short research period, a few research papers have addressed the existing definitions, indicators for the conservation status assessment, and assessment techniques. This paper attempted to complete the set of measurable indicators available in national forest inventories and connect them with the forest habitat types’ conservation status components (area, function, structure, and prospects). A set of 40 indicators was defined, labelled with one or more of the four conservation status components and assessed with the quality dimensions. The analysis uncovered that five indicators could be used to assess the component of range and area, 20 that of structure, 22 that of function and 27 that of prospects. It also showed that conventional forestry indicators such as tree species, diameter at breast height, and regeneration are less sensitive regarding the data quality. Conversely, some typical biodiversity indicators lacked completeness, timeliness, and precision. In addition to this analysis, the data distributions (data for them were provided by the national forest inventories of Italy, Slovenia, and Spain) of some indicators were analysed. Based on all the results, it was also possible to conclude that there is a shortage of national forest inventory indicators for the assessments of the area and function conservation status components. While the area component should be described with the indicators of forest habitat type fragmentation, mingling and perforation with non-forest and other forest vegetation communities, the functional component is bereft of indicators describing processes such as biomass growth and carbon cycling. Future research should thus search for more indicators to represent all conservation status components in a more balanced way. More efforts should also be expended into the harmonisation of indicators.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.358

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.038
GPT teacher head0.291
Teacher spread0.253 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it