Targets and tools for the maintenance of forest biodiversity
Bibliographic record
Abstract
Targets and tools for the maintenance of forest biodiversity - an introduction: P.Angelstam, M. Donz-Breuss and J.M. Roberge.BorNet - a boreal network for sustainable forest management: P. Angelstam, J. Innes, J. Niemela and J. Spence.The sustainable forest management vision and biodiversity - barriers and bridges for the implementation in actual landscapes: P. Angelstam, R. Persson and R. Schlaepfer.Sustainable forest management and Pan-European forest policy: E. Rametsteiner and P. Mayer.Biodiversity research in the boreal forests of Canada: protection, management and monitoring: C. Whittaker, K. Squires and J.L. Innes.Research requirements to acheive sustainable forest management in Canada: an industry perspective: D. Hebert.First Nations: measures and monitors of boreal forest biodiversity: M. Stevenson and J. Webb.IKEA's contribution to sustainable forest management: H. Djurberg, P. Stenmark and G. Vollbrecht.Biodiversity manangment in Swiss mountain forests: C.R. Neet and M. Bolliger.Management for forest biodiversity in Austria - the view of local forest enterprise: M. Donz-Breuss, B. Maiser and H. Malin.Boreal forest disturbance regimes, successional dynamics and landscape structures - a European perspective: P. Angelstam and T. Kuuluvainen.Natural disturbances and the amount of large trees, deciduous trees and coarse woody debris in the forests of Novgorod Region, Russia: E. Shorohova and S. Tetioukhin.Natural forest remants and transport infrastructure? does history matter for biodiversity conservation planning? P. Angelstam, G. Mikusinski and J. Fridman.Do empirical thresholds truly reflect species intolerance to habitat alteration? J.S. Guenette and M.A. Villard.Habitat thresholds and effects of forest landscape change on hte distribution and abundance of black grouse and capercaillie: P. Angelstam.Area-sensitivity of the sand lizard and spider wasps in sandy pine heath forests - umbrella species for early successional biodiversity conservation? S.A. Berglind.Influence of edges between old deciduous forest and clearcuts on the abundance of passerine hole-nesting birds in Lithuania: G. Brazaitis and P. Angelstam.Quantitative snag targets for the three-toes woodpecker Picoides tridactylus: R. Butler, P. Angelstam and R. Schlaepfer.Large woody debris and brown trout in small forest streams - towards targets for assessment and management of riparian landscapes: E. Degerman. B. Sers, J. Tornblom and P. Angelstam.Occurence of Siberian jay Perisoreus infaustus in relation to amount of forest at landscape and home range scale: L. Edenius, T. Brodin and N. White.Old- growth boreal forests, three-toed woodpecker and saproxylic beetles - the importance of landscape management history on local consumer-resource dynamics: P. Fayt.Management targets for the conservation of hazel grouse in boreal landscapes: G. Jansson, P. Angelstam, J. Aberg and J. Swenson.Occurence of mammals and birds with different ecological characteristics in relation to forest cover in Europe - do macroecological data make sense?: P. Reunanen, M. Monkkonen, A. Nikula, E. Hurme and V. Nivala.Habitat requirements of the pine wood-living beetle Tragosoma depsarium (Coleoptera: Cerambyciade) at log, stand, and landscape scale: L.O. Wikars.Monitoring forest biodiversity - from the policy level to the management unit: P. Angelstam, J.-M. Roberge, M. Donz-Breuss, I. J. Burfield and G. Stahl.Measuring forest biodiversity at the stand scale - an evaluation of indicators in European forest history gradients: P. Angelstam and M. Donz-Breuss.Land management data and terrestrial vertebrates as indicators of biodiversity at the landscape scale:.P. Angelstam, T. Edman, M. Donzforest Breuss and M. F. Wallis DeVries.Identifying high conservation value forests in the Baltic States from forest databases: P. Kurlavicius, R. Kuuba, M. L kins, G. Mozgeris, P. Tolvanen, H. Karjalainen, P. Angelstam and M. Walsh.The role of Geographical Information Systems and Optical Remote Sensing in monitoring boreal ecosystems: J. E. Young and G. A. Sanches-Azofeifa.Indicator species and biodiversity monitoring systems for non-industrial private forest owners - is there a communication problem?: H. Uliczka, P. Angelstam and J.-M. Roberge.Connecting social and ecological systems: an integrated toolbox for hierarchical evaluation of biodiversity policy implementation: M. Lazdinis and P. Angelstam.Loss of old-growth, and the minimum need for strictly protected forests in Estonia: A. Lohmus, K. Kohv, A. Palo and K. Viilma.Assessing actual landscapes for the maintenance of forest biodiversity - a pilot study using forest management data: P. Angelstam and P. Bergman.Habitat modelling as a tool for landscape-scale conservation - a review of parameters for focal forest birds: P. Angelstam, J.-M. Roberge, A. Lohmus, M. Bergmanis, G. Brazaitis, M. Donz-Breuss, L. Edenius, Z. Kosinski, P. Kurlavicius, V. Larmanis, M. L kins, G. Mikusinski, E. Raeinski, M. Strazds and P. Tryjanowski.Multidimensional habitat modelling in forest management - a case study using capercaillie in the Black Forest, Germany: R. Suchant and V. Braunisch.Towards the assessment of environmental sustainability in forest ecosystems: measuring the natural capital: O. Ullsten, P. Angelstam, A. Patel, D. J. Rapport, A. Cropper, L. Pinter and M. Washburn.Targets for boreal forest biodiversity conservation - a rationale for macroecological research and adaptive management: P. Angelstam, S. Boutin, F. Schmiegelow, M.-A. Villard, P. Drapeau, G. Holst, J. Innes, G. Isachenko, T. Kuuluvainen, M. Monkkonen, J. Niemela, G. Niemi, J.-M. Roberge, J. Spence and D. Stone.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.021 | 0.013 |
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".