Plantations and biodiversity: A comment on the debate in New Brunswick
Bibliographic record
Abstract
The importance of biodiversity has become widely recognized but the best methods for conserving forest biodiversity are still being debated. Central to this debate is the influence of plantations and managed stands on local and landscape-scale biodiversity. A recent paper by Erdle and Pollard in The Forestry Chronicle (2002), which concluded that few plantations are strict monocultures in terms of the total number of tree species, could be interpreted as making the case that plantations have relatively minor consequences for biodiversity. We argue that: (1) it is not only the number of species, but also the identities and relative abundances of species that are of ecological importance, and (2) defining biodiversity in terms of tree species alone is of limited applicability. Existing research in New Brunswick on the impact of plantations on biodiversity at the stand scale reveals potentially significant biodiversity losses, at least in certain taxa. The proposal that incorporating more structural elements (e.g., snags, coarse woody debris, vertical structure) and retaining greater tree species diversity to ameliorate negative consequences of plantations remains a hypothesis to be tested in this region. Scientific information gathered in the following areas will allow better decision making: (1) to what degree are older plantations used by native species? (2) are productivity and survivorship of vertebrates in intensively managed stands similar to those in unmanaged forest? (3) are intensively managed stands suitable habitat for non-vertebrates? (4) are there thresholds in the response of some species to landscape-scale habitat loss caused by intensive forest management? Key words: plantations, biodiversity, species composition, landscape scale, stand structures
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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.009 | 0.012 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.008 | 0.005 |
| Research integrity | 0.025 | 0.034 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".