A multi-scale investigation of species richness, productivity and nutrient relationships in herbaceous plant communities of the grasslands of Southern Interior British Columbia
Bibliographic record
Abstract
Philip Grime's humped-back model predicts that species richness reaches a maximum at intermediate productivity and drops off at low and high productivities. Soil nutrient availability is known to influence primary productivity and plant species richness. In general, productivity increases with increasing soil nutrient availability, and experiments that increase soil nutrients often show increases in biomass with corresponding decreases in species richness; as such, certain patterns in soil nutrients are expected to coincide with the humped-back model. Scale is also an important factor, as the relationship between species richness and productivity may vary with scale. Objectives of this work were (1) to test the explicit humped-back model prediction that the relationship between species richness and productivity is unimodal; (2) to test implicit humped-back model predictions that species richness is related to nutrients that are tightly associated with productivity, such as carbon and nitrogen, by a unimodal relationship and identify patterns between soil nutrients, leaf nutrients, productivity and species richness; and (3) to evaluate the influence of increasing scales from 1 m2 to 64 m2 on relationships found between species richness, productivity and nutrients. This was done using biomass and litter collections and species richness counts from 14 multi-scale grids (8 m × 8 m grids containing 64, 1 m2 plots), soil samples from a subset of four of the 14 multi-scale grids, and leaf samples from a subset of nine adjacent plots in each of the four multi-scale grids that were sampled for soil nutrients. Total carbon and nitrogen contents in soil and leaf samples were analyzed with a CE-440 Elemental Analyzer. Total aluminum, boron, calcium, copper, iron, magnesium, manganese, sodium, phosphorus, potassium, sulphur, and zinc were quantified in soil samples prepared by very high-pressure closed vessel microwave acid digestion in a Milestone “Ultrawave” single reaction chamber followed by analysis with a Teledyne/Leeman Labs “Prodigy” dual view inductively coupled plasma-optical emission spectrometer. In principal component analyses of soil nutrient data, the first and second principal components appeared to represent productivity and species richness, respectively; and carbon, nitrogen, phosphorus, potassium, boron, iron, magnesium and manganese were identified as important soil nutrients. Bivariate regressions of the first principal component with total biomass (R2 = 0.76) and the second principal component with species richness (R2 = 0.35) returned strong R2 values. Species richness was related to total biomass (R2 = 0.11), soil carbon (R2 = 0.15), soil nitrogen (R2 = 0.14) and iron (R2 = 0.29) by concave down relationships, to boron (R2 = 0.17) and magnesium (R2 = 0.49) by concave up relationships, to phosphorus (R2 = 0.27) and manganese (R2 = 0.25) by positive linear relationships and to potassium (R2 = 0.14) by a negative linear relationship. Scaling results were inconclusive but suggested that patterns in the literature may be partly due to sample size. Results generally support the humped-back model and that nutrient availability is an important factor correlated with herbaceous plant productivity and species richness. Nutrient availability is likely an important driver of plant productivity and herbaceous plant diversity.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".