Unexpected microbial metabolic responses to elevated temperatures and nitrogen addition in subarctic soils under different land-use
Bibliographic record
Abstract
This repository contains all necessary raw data as well as the R code used to conduct statistical analysis and create figures of the publication Unexpected microbial metabolic responses to elevated temperatures and nitrogen addition in subarctic soils under different land-use Julia Schroeder1, Tino Peplau1, Edward Gregorich2, Christoph C. Tebbe3, Christopher Poeplau1 1 Thünen Institute of Climate-Smart Agriculture, Bundesallee 68, 38116 Braunschweig, Germany2 Research and Development Centre, Central Experimental Farm, Agriculture and Agri-Food Canada, Ottawa, Canada3 Thünen Institute of Biodiversity, Bundesallee 65, 38116 Braunschweig, Germany DOI: https://doi.org/10.1007/s10533-022-00943-7 This study investigated how subarctic soils under different land use will respond to warming and increasing N availability to allow for better predictions of C cycling under global change. The short-term temperature sensitivity as well as N-input effects on microbial CUE, respiration, growth and turnover were assessed in a one-day incubation experiment according to the 18O-CUE approach. The warming and N response of SOM decomposition were assessed in a 50-days incubation experiment via measurement of cumulative respiration. Both experiments were conducted with the following three treatments: incubation at 10 °C, incubation at 20 °C, and incubation at 20 °C plus N-fertiliser addition at an amendment rate of 100 kg N ha-1. The response to warming or N addition were expressed as response ratios RRT = 20°C/10°C and RRN = 20°C+N/20°C for warming and N response, respectively. The R code was developed under R v3.6.3 and adapted to work under version R v.4.1.2. The repository includes the following files: general_soil_parameters_per_sample.csv - general soil data for each field sample (n=27) general_soil_parameters_per_plot.csv - general soil data assessed on pooled replicated field samples (n=9) respiration_over_50d_incubation.csv - respiration rate and cumulative respiration for each time-point and laboratory sample over the 50-days incubation sample_data.csv - data measured for each laboratory sample (n=81) Warming_and_nitrogen_response_of_CUE_in_subarctic_soils.Rproj - Rproject (load project to work on provided scripts and data) load_data_script.R - loads required data absolute_values_script.R - summary of absolute ranges of parameters per land-use type and site absolute_linear_mixed_effects_model_script.R - run statistical analysis correlograms_absolute_soil_params_script.R - correlation analysis to identify what drives absolute values plot_correlations_absolute_soil_params_script.R - plot drivers of CUE and cumulative respiration RRT_RRN_calculation_script.R - calculates response ratios plot_RRT_RRN_script.R - plot response ratios RRT_RRN_linear_mixed_effects_models_script.R - run statistical analysis correlograms_RRT_RRN_soil_param_script.R - correlation analysis to identify drivers of response ratios plot_correlations_RRT_RRN_soil_params_script.R - plot drivers of response ratios RRT_RRN_resprate_cumulresp_over_time_50d_incubation_script.R - plot response ratios over time course
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".