Cropping system influences on soil physical properties in the Great Plains
Bibliographic record
Abstract
Abstract Agricultural systems produce both detrimental and beneficial effects on soil quality (SQ). We compared soil physical properties of long-term conventional (CON) and alternative (ALT) cropping systems near Akron, Colorado (CO); Brookings, South Dakota (SD); Bushland, Texas (TX); Fargo, North Dakota (ND); Mandan (ND); Mead, Nebraska (NE); Sidney, Montana (MT); and Swift Current, Saskatchewan (SK), Canada. Objectives were to quantify the changes in soil physical attributes in cropping systems and assess the potential of individual soil attributes as sensitive indicators of change in SQ. Soil samples were collected three times per year from each treatment at each site for one rotation cycle (4 years at Brookings and Mead). Water infiltration rates were measured. Soil bulk density (BD) and gravimetric water were measured at 0–7.5, 7.5–15, and 15–30 cm depth increments and water-filled pore space ratio (WFPS) was calculated. At six locations, a rotary sieve was used to separate soil (top 5 cm) into six aggregate size groups and calculate mean weight diameter (MWD) of dry aggregates. Under the CON system at Brookings, dry aggregates (>19 mm) abraded into the smallest size class (<0.4 mm) on sieving. In contrast, the large aggregates from the ALT system abraded into size classes between 2 and 6 mm. Dry aggregate size distribution (DASD) shows promise as an indicator of SQ related to susceptibility of soil to wind erosion. Aggregates from CON were least stable in water. Soil C was greater under ALT than CON for both Brookings and Mead. At other locations, MWD of aggregates under continuous crop or no tillage (ALT systems) was greater than MWD under CON. There was no crop system effect on water infiltration rates for locations having the same tillage within cropping system. Tillage resulted in increased, decreased, or unchanged near-surface BD. Because there was significant temporal variation in water infiltration, MWD, and BD, conclusions based on a single point-in-time observation should be avoided. Elevated WFPS at Fargo, Brookings, and Mead may have resulted in anaerobic soil conditions during a portion of the year. Repeated measurements of WFPS or DASD revealed important temporal characteristics of SQ that could be used to judge soil condition as affected by management.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".