Ten‐year responses of ground‐dwelling spiders to retention harvest in the boreal forest
Bibliographic record
Abstract
The Ecosystem Management Emulating Natural Disturbances (EMEND) project tests the hypothesis that varying levels of green tree retention maintain and retain forest biodiversity better than conventional clear-cutting. We studied epigaeic spiders to assess biodiversity changes 2, 5, and 10 yr following a range of partial retention harvests (clear-cut, 10-75% retention) and unharvested controls in four boreal mixedwood cover types. A total of 56 371 adult spiders representing 220 species was collected using pitfall traps. Lasting effects on forest structure were proportional to harvest intensity. These changes strongly influenced spider richness, abundance, and species composition, as well as assemblage recovery. Distinctive assemblages were associated with disturbance level, especially with partial harvests (≤50% retention), and these were dominated by open-habitat species even 10 yr after harvest. Assemblages were more similar to those of controls in the highest (75%) retention treatment, but significant recovery toward the structure of pre-disturbance assemblages was not detected for any prescription in any cover type. Although early responses to retention harvest suggested positive effects on spider assemblages, these are better explained as lag effects after harvest because assemblages were less similar to those of unharvested controls 5 yr post-harvest, and only minor recovery was observed 10 yr following harvest. Retention of forest biodiversity decreased over time, especially in conifer stands and the lower (10-50%) retention treatments. Overall, retention harvests retained biodiversity and promoted landscape heterogeneity somewhat better than clear-cutting; however, there was a clear gradient of response and no retention "threshold" for conservation can be recommended on the basis of our data. Furthermore, results suggest that retention harvest prescriptions should be adjusted for cover type. We show that low retention ameliorated impacts in broadleaved forests characteristic of earlier stages in mixedwood succession, but only higher retention was associated with less impact in successionally older conifer forests. Although these short-term responses (10 yr) of spider assemblages support use of retention harvests, understanding the true conservation merit of these practices, relative to conventional approaches, requires evaluation over longer time scales, with work more focused on recovery of biodiversity than on its preservation after harvest.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".