Carbon, nitrogen, and water stable isotopes in plant tissue and soils across a moisture gradient in Puerto Rico
Bibliographic record
Abstract
Abstract Stable isotopes in the water molecule (2H or D and 18O), carbon, and nitrogen are useful tracers and integrators of processes in plant ecohydrological systems across scales. Over the last few years, there has been growing interest in regional to continental scale synthesis of stable isotope data with a view to elucidating biogeochemical and ecohydrological patterns. Published datasets from the humid tropics, however, are limited. To be able to contribute to bridging the “data gap” in the humid tropics, here, we publish a relatively novel and unique suite of δ13C, δ15N, δ2H, and δ18O isotope data from three sites across a moisture gradient and contrasting land use in Puerto Rico. Plant tissue (xylem and leaf) samples from two species of mahogany (Swietenia macrophylla and Swietenia mahagoni) and soil samples down to 60 cm in the soil profile were collected in relatively “wet” (July 2012) and “dry” (February 2013) periods at two sites in northeastern (Luquillo) and southwestern (Susua) Puerto Rico. The same sampling suite is also being made available from a highly urbanized site in the capital San Juan. Leaf samples taken in July 2012 and February 2013 were analyzed for δ13C and δ15N; all xylem and bulk soil samples were analyzed for δ2H and δ18O. Soil samples taken in July 2012 were analyzed for δ13C and δ15N. Leaf δ15N and δ13C dataset showed patterns that are possibly associated with site differences. While spatial patterns were also apparent in soil δ15N and δ13C dataset, the positively linear δ15N –δ13C relationship tends to weaken with site moisture. Soil depth and site moisture patterns were also observed in the δ2H and δ18O datasets of bulk soil and xylem samples. The purpose of these datasets is to provide baseline information on soil–plant water (δ2H and δ18O, N = 319), δ13C (N = 272), and δ15N (N = 269) that may be useful in a wide range of research questions from ecohydrological relations to biogeochemical patterns in soils and vegetation.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".