Simulating the Potential Effects of a Changing Climate on Black Spruce and Jack Pine Plantation Productivity by Site Quality and Locale through Model Adaptation
Bibliographic record
Abstract
Modifying the stand dynamic functional determinates of structural stand density management models (SSDMMs) through the incorporation of site-specific biophysical height-age equations enabled the simulation of the effects of increasing mean temperature and precipitation during the growing season on black spruce (Picea mariana (Mill.) BSP) and jack pine (Pinus banksiana Lamb.) plantation productivity. The analytical approach consisted of calculating future values of growing season mean temperature and precipitation rates under three emissions scenarios (no change (NC); B1; and A2), spanning three continuous commitment periods (2011–2040; 2041–2070; and 2071–2100), for three geographically separated sites throughout the central portion of the Canadian Boreal Forest Region (north-eastern (Kirkland Lake); north-central (Thunder Bay); and north-western (Dryden) Ontario, Canada), using the Canadian Coupled Global Climate Model (CGCM3) in conjunction with a geographic-referencing climatic surface model. These estimates were entered into the embedded biophysical equations in the SSDMMs in order to forecast emission-scenario-specific developmental patterns of plantations managed under a conventional density management regime by species and site quality (poor-to-medium and good-to-excellent) at each locale; from which stand development rates and associated productivity metrics over 75 year-long rotations were estimated and compared (e.g., mean sizes, volumetric, biomass and carbon yields, end-products, economic worth, stand stability, wood quality indices, and operability status). Simulation results indicated that black spruce plantations situated on both site qualities at the north-western location and on the lower site quality at the north-eastern location were negatively affected from the predicted increased warming and rainfall as evidenced from consequential declines in stand development rates and resultant decreases in rotational mean sizes, biomass yields, recoverable end-product volumes, and economic worth (A2 > B1). Conversely, black spruce plantations situated on both site qualities at the north-central location and on the higher site quality at the north-eastern location were minimally and positively affected under the A2 and B1 scenarios, respectively. Jack pine plantations situated on both site qualities at all three locations were negatively affected as evident by the reductions in stand development rates and rotational mean sizes, biomass yields, recoverable end-product volumes, and economic worth (A2 > B1). Collectively, these response patterns suggest that stand-level productivity under a changing climate will vary by species, site quality, geographic locale, and emission scenario, potentially resulting in a landscape-level mosaic of both negative and positive productivity impacts in the case of black spruce, and mostly negative impacts in the case of jack pine. As demonstrated, modelling stand-level responses to projected increases in thermal and moisture regimes through the modification of existing stand-level forecasting models, and accounting for divergent effects due to species, site quality, and geographic locale differences, is a viable and efficient alternative approach for projecting productivity outcomes arising from anthropogenic-induced changes in growing conditions.
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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".