Who owns the desert basins of the American West? A typology for moving beyond the public–private binary in conservation and development
Bibliographic record
Abstract
Abstract Desert lakes worldwide are being lost to human water diversions and land use change, creating ‘sacrifice zones’ that benefit distant interests. In the American West, scholarly interest has focused on water diversions by both public and private interests as the primary driver of desert lake decline, underscoring how assumptions that public interests support conservation while private interests support development can be misleading. Land use and its underlying motives are also important as they modify surrounding desert basins and impact local social conditions in ways that also defy such assumptions, but are less examined in this context. How can we move beyond the binary of public and private interests to identify distinct patterns of sacrifice zone formation through land use? Here, we propose a typology that goes beyond the public–private binary to systematically measure landowner motives according to a landowner’s publicness, economic objective, and degree of absenteeism, identifying support-, speculation- and sacrifice-motivated landowners. We test three variants of this typology across eight desert basins with differing conservation trajectories. Our results show that (1) the motives related to mixed-use public parcels strongly shape basin-level summaries of motive in terms of area, underscoring their management importance for overall basin land use; (2) although sacrifice- and speculation-motivated private landowners are few, they hold consolidated estates; and (3) their land use activities likely have disproportionate social and ecological impacts. Case summaries of the dynamics for three representative basins further demonstrate the additional insights that could be generated by applying our typology longitudinally and pairing it with qualitative insights. This typology provides a systematic tool for characterizing landowner motives in sacrifice zones. Future research should focus on longitudinal applications and identifying appropriate indicators of social and ecological conditions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".