Global progress toward sustainable forest management
Bibliographic record
Abstract
Sustainable forest management (SFM) is many things to many people – yet a common thread is the production of forest goods and services for the present and future generations. The promise of sustainability is rooted in the two premises; first that ecosystems have the potential to renew themselves and second that economic activities and social perceptions or values that define human interaction with the environment are choices that can be modified to ensure the long term productivity and health of the ecosystem. SFM addresses a great challenge in matching the increasing demands of a growing human population while maintaining ecological functions of healthy forest ecosystems. This paper does not seek to define SFM, but rather provides analyses of key indicators for the national-scale enabling environment to gain a global insight into progress in implementing enabling and implementing SFM at the national and operational levels. Analyses of the Global Forest Resources Assessment 2015 (FRA) country report data are used to provide insights into the current state of progress in implementing the enabling conditions for SFM. Over 2.17 billion ha of the world’s forest area are predicted by governments to remain in permanent forest land use, of which some 1.1 billion ha are covered by all of the SFM tools investigated in FRA 2015. At the global scale, SFM-related policies and regulations are reported to be in place on 97% of global forest area. While the number of countries with national forest inventories has increased over that past ten years from 48 to 112, only 37% of forests in low income countries are covered by forest inventories. Forest management planning and monitoring of plans has increased substantially as has forest management certification, which exceeded a total of over 430 million ha in 2014. However, 90% of internationally verified certification is in the boreal and temperate climatic domains – only 6% of permanent forests in the tropical domain have been certified as of 2014. Results show that more work is needed to expand the extent and depth of work on establishing the enabling conditions that support SFM over the long term and suggests where those needs are greatest.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.027 | 0.009 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".