Multi‐scale heterogeneity in vegetation and soil carbon in exurban residential land of southeastern <scp>Michigan, USA</scp>
Bibliographic record
Abstract
Abstract Exurban residential land (one housing unit per 0.2–16.2 ha) is growing in importance as a human‐dominated land use. Carbon storage in the soils and vegetation of exurban land is poorly known, as are the effects on C storage of choices made by developers and residents. We studied C storage in exurban yards in southeastern Michigan , USA , across a range of parcel sizes and different types of neighborhoods. We divided each residential parcel into ecological zones ( EZ ) characterized by vegetation, soil, and human behavior such as mowing, irrigation, and raking. We found a heterogeneous mixture of trees and shrubs, turfgrasses, mulched gardens, old‐field vegetation, and impervious surfaces. The most extensive zone type was turfgrass with sparse woody vegetation (mean 26% of parcel area), followed by dense woody vegetation (mean 21% of parcel area). Areas of turfgrass with sparse woody vegetation had trees in larger size classes (> 50 cm dbh) than did areas of dense woody vegetation. Using aerial photointerpretation, we scaled up C storage to neighborhoods. Varying C storage by neighborhood type resulted from differences in impervious area (8–26% of parcel area) and area of dense woody vegetation (11–28%). Averaged and multiplied across areas in differing neighborhood types, exurban residential land contained 5240 ± 865 g C/m 2 in vegetation, highly sensitive to large trees, and 13 800 ± 1290 g C/m 2 in soils (based on a combined sampling and modeling approach). These contents are greater than for agricultural land in the region, but lower than for mature forest stands. Compared with mature forests, exurban land contained more shrubs and less downed woody debris and it had similar tree size‐class distributions up to 40 cm dbh but far fewer trees in larger size classes. If the trees continue to grow, exurban residential land could sequester additional C for decades. Patterns and processes of C storage in exurban residential land were driven by land management practices that affect soil and vegetation, reflecting the choices of designers, developers, and residents. This study provides an example of human‐mediated C storage in a coupled human–natural system.
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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".