Conspecific density dependence and community structure: Insights from 11 years of monitoring in an old‐growth temperate forest in Northeast China
Bibliographic record
Abstract
Forest community structure may be influenced by seedling density dependence, however, the effect is loosely coupled with population dynamics and diversity in the short term. In the long term the strength of conspecific density dependence may fluctuate over time because of seedling abundance, yet few long-term studies exist. Based on 11 years of seedling census data and tree census data from a 25-ha temperate forest plot in Northeast China, we used generalized linear mixed models to test the relative effects of local neighborhood density and abiotic factors on seedling density and seedling survival. Spatial point pattern analysis was used to determine if spatial patterns of saplings and juveniles, in relation to conspecific adults, were in accordance with patterns uncovered by conspecific negative density dependence at the seedling stage. Our long-term results showed that seedling density was mainly positively affected by conspecific density, suggesting dispersal limitation of seedling development. The probability of seedling survival significantly decreased over 1 year with increasing conspecific density, indicating conspecific negative density dependence in seedling establishment. Although there was variation in conspecific negative density dependence at the seedling stage among species and across years, a dispersed pattern of conspecific saplings relative to conspecific adults at the local scale (<10 m) was observed in four of the 11 species examined. Overall, sapling spatial patterns were consistent with the impacts of conspecific density on seedling dynamics, which suggests that conspecific negative density dependence is persistent over the long term. From the long-term perspective, conspecific density dependence is an important driver of species coexistence in temperate forests.
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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 | 0.001 |
| 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".