Deforestation for agriculture increases microbial carbon use efficiency in subarctic soils

This repository contains all necessary raw data as well as the R code used to conduct statistical analysis and create figures of the publication

Deforestation for agriculture increases microbial carbon use efficiency in subarctic soils

Julia Schroeder1, Tino Peplau1, Frank Pennekamp2, Edward Gregorich3, Christoph C. Tebbe4, Christopher Poeplau1

1 Thünen Institute of Climate-Smart Agriculture, Bundesallee 68, 38116 Braunschweig, Germany

2 Department of Evolutionary Biology and Environmental Studies, University of Zurich, Winterthurerstrasse 190, 8057 Zürich, Switzerland

3 Research and Development Centre, Central Experimental Farm, Agriculture and Agri-Food Canada, 960 Carling Ave, Ottawa, Ontario K1A 0C6, Canada

4 Thünen Institute of Biodiversity, Bundesallee 65, 38116 Braunschweig, Germany

DOI: https://doi.org/10.1007/s00374-022-01669-2 

This study investigated how and  through which pathways deforestation and conversion to agricultural land (i.e. grassland, cropland) alters the microbial carbon use efficiency (CUE) in subarctic soils to allow the development of mitigation strategies to alleviate C losses. We assessed CUE using 18O-labelled water in a paired-plot approach on soils collected from 19 farms across the subarctic region of Yukon, Canada, comprising 14 pairs of forest-to-grassland conversion and 15 pairs of forest-to-cropland conversion. Microbial CUE significantly increased following conversion to grassland and cropland. Land-use conversion resulted in a lower estimated abundance of fungi, while the archaeal abundance increased, as assessed by qPCR. Interestingly, structural equation modelling revealed that increases in CUE were mediated by a rise in soil pH and a decrease in soil C:N ratio rather than by shifts in microbial community composition, i.e. the ratio of fungi, bacteria and archaea. Our findings indicate a direct control of abiotic factors on microbial CUE via improved nutrient availability and facilitated conditions for microbial growth.

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_site.csv - general soil data assessed on pooled reference forest plot (n=19)
• general_soil_parameters_per_plot.csv - general soil data assessed on pooled replicated field samples (n=48)
• sample_data.csv - data measured for each laboratory sample (n=147)

• Land-use change effects on 18O-CUE.Rproj - Rproject (load project to work on provided scripts and data)
• load_data_script.R - loads required data
• Multivariate_normality_script.R - tests for multivariate normaility in dataset
• PCA_script.R - calculates PC1 and 2 of clay mineralogy data to reduce dimensions
• map_Yukon_script.R - create Figure 1
• plot_density_script.R - create Figure 2
• linear_mixed-effects_models_script.R - calculates response ratios
• plot_boxplots_script.R - plot boxplots per land use including compact letter display indicating significant differences, create Figure 3 + 4
• correlogram_script.R - correlation analysis to identify drivers of CUE, create Figure 6
• plot_correlations_script.R - plot drivers of CUE, create Figure 5 + 7
• SEM_script.R - development of structural equation model, create Figure 8