Climate-Biome Envelope Shifts Create Enormous Challenges and Novel Opportunities for Conservation
Bibliographic record
Abstract
Research Highlights: We modeled climate-biome envelopes at high resolution in the Western Great Lakes Region for recent and future time-periods. The projected biome shifts, in conjunction with heterogeneous distribution of protected land, may create both great challenges for conservation of particular ecosystems and novel conservation opportunities. Background and Objectives: Climate change this century will affect the distribution and relative abundance of ecological communities against a mostly static background of protected land. We developed a climate-biome envelope model using a priori climate-vegetation relationships for the Western Great Lakes Region (Minnesota, Wisconsin and Michigan USA and adjacent Ontario, Canada) to predict potential biomes and ecotones—boreal forest, mixed forest, temperate forest, prairie–forest border, and prairie—for a recent climate normal period (1979–2013) and future conditions (2061–2080). Materials and Methods: We analyzed six scenarios, two representative concentration pathways (RCP)—4.5 and 8.5, and three global climate models to represent cool, average, and warm scenarios to predict climate-biome envelopes for 2061–2080. To assess implications of the changes for conservation, we analyzed the amount of land with climate suited for each of the biomes and ecotones both region-wide and within protected areas, under current and future conditions. Results: Recent biome boundaries were accurately represented by the climate-biome envelope model. The modeled future conditions show at least a 96% loss in areas suitable for the boreal and mixed forest from the region, but likely gains in areas suitable for temperate forest, prairie–forest border, and prairie. The analysis also showed that protected areas in the region will most likely lose most or all of the area, 18,692 km2, currently climatically suitable for boreal forest. This would represent an enormous conservation loss. However, conversely, the area climatically suitable for prairie and prairie–forest border within protected areas would increase up to 12.5 times the currently suitable 1775 km2. Conclusions: These results suggest that retaining boreal forest in potential refugia where it currently exists and facilitating transition of some forests to prairie, oak savanna, and temperate forest should both be conservation priorities in the northern part of the region.
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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".