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Record W6911308416 · doi:10.5281/zenodo.11565223

PROTOCOL FOR DESIGN, IMPLEMENTATION AND MAINTENANCE OF THE NBS FOR DRYLANDS (Summary for Decision Maker)

2024· article· en· W6911308416 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicRemote Sensing in Agriculture
Canadian institutionsnot available
Fundersnot available
KeywordsProtocol (science)Restoration ecologyIUCN Red ListIdentification (biology)Natural (archaeology)Environmental restoration

Abstract

fetched live from OpenAlex

The NewLife4Drylands (NL4DL) project aimed to monitor the application, scalability, and replicability of Nature-Based Solutions (NBS) for the restoration of drylands by using satellite-based indicators. The project adopted a multifaceted approach that involved establishing a protocol for NBS in drylands, encompassing the identification of drylands characteristics and the design of NBS, and overseeing midterm and long-term restoration efforts. The NL4DL Protocol has primarily adopted the approach and the structure of the International Principles and Standards for the Practice of Ecological Restoration (SER, 2019), Principles and Guidelines for Ecological Restoration in Canada’s Protected Natural Areas (Canadian Parks Council, 2008) and Ecological Restoration for Protected Areas (IUCN, 2012), adapting them to the specific needs of ecological restoration of mediterranean drylands. These documents represent international references for ecological restoration activities in natural and semi-natural environments. Consulting these documents is recommended for interested parties (such as practitioners, academics, and decision-makers) who wish to investigate and explore specific issues related to a site in need of restoration activities. In the Protocol, the elements depicted in the reference documents (SER, IUCN and Canadian Parks Council) are tailored and further elaborated, particularly concerning activities for restoring degraded soils using NBS. The Protocol also explores the integrated use of ground-based and Remote Sensing (RS) data to identify indicators for evaluating the effectiveness of planned solutions. This approach is geared towards fostering adaptive, evidence-based and interdisciplinary management of the ecological restoration process. The Protocol follows the principles and input of the cited documents and integrates the NL4Dl project outputs into ecological restoration activity in drylands (through planning, design, implementation, and maintenance) that are: - a procedure for assessing existing degradation processes and monitoring ecosystem restoration interventions (such as NBS) in degraded drylands, combining RS techniques with in-field gathered data. It serves to evaluate the effectiveness of restoration activities and improve sustainable land management on a long-term basis; - an operational tool, the Decision Support Web tool, which identifies the best sustainable solutions (Nature-Based Solutions) based on degradation processes. It includes indices and indicators related to each degradation process and enables end-users to monitor the effectiveness of these solutions. This tool guides the users in evaluating available NBS for restoration activities in soil-degraded areas and provides relevant monitoring elements. It aims to reduce the knowledge effort, minimize subjective analysis, and help prioritize options. The collective use of these tools paves the way for an informed decision-making process regarding land and soil restoration, alongside identifying best practices that can be replicated in similar contexts

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.084
metaresearch head score (Gemma)0.170
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.386
Threshold uncertainty score0.876

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0840.170
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.004
Science and technology studies0.0040.003
Scholarly communication0.0080.005
Open science0.0040.005
Research integrity0.0060.008
Insufficient payload (model declined to judge)0.3860.138

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 head0.035
GPT teacher head0.294
Teacher spread0.260 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreProtocol

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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