Tree functional traits, forest biomass, and tree species diversity interact with site properties to drive forest soil carbon

Forests constitute important ecosystems in the global carbon cycle. However, how trees and environmental conditions interact to determine the amount of organic carbon stored in forest soils is a hotly debated subject. In particular, how tree species influence soil organic carbon (SOC) remains unclear. Based on a global compilation of data, we show that functional traits of trees and forest standing biomass explain half of the local variability in forest SOC. The effects of functional traits on SOC depended on the climatic and soil conditions with the strongest effect observed under boreal climate and on acidic, poor, coarse-textured soils. Mixing tree species in forests also favours the storage of SOC, provided that a biomass over-yielding occurs in mixed forests. We propose that the forest carbon sink can be optimised by (i) increasing standing biomass, (ii) increasing forest species richness, and (iii) choosing forest composition based on tree functional traits according to the local conditions.

Supplementary Tables (S1 to S9) Supplementary   pairs. Boxplots represent the median, the first and third quartiles, and 1.5 × the inter-quartile range. The difference between the two groups was tested with a pairwise t-test (two-sided). "agriculture" (green symbols) includes mainly grasslands, but also a few croplands and land treated with inorganic fertilisers; "forest" (dark grey symbols) includes mainly forests, but also a few shrublands. Values are normalised (see Methods). Linear regressions were fitted (level of confidence of the error band = 0.95). The symbol size is proportional to data reliability (see Methods), and regressions take it into account as a weighting factor. ; N.dep = nitrogen atmospheric deposition (kg-N ha -1 yr -1 ); Clay, Silt, and Sand = particle size fractions of soils (mg g -1 ); pH = soil pH (unitless). The matrix shows the results of Spearman's rank correlation coefficients. The symbols *, **, and *** indicate correlations with P values respectively as follows: P < 0.05, P < 0.01, and P < 0.001. The variables that were directly related to biomass ("litterfall" and "tree biomass"), and functional traits known to be related to biomass or growth ("max height", "growth rate", "seed mass", "wood density") were used to generate a Principal Component Analysis (PCA). For full explanation, see the section "Data collection: plant functional traits" in Methods. The final value of the index score of the standing biomass was the coordinate value on the first axis ("Dimension 1"). and D, respectively) show the SOC decomposability, which is the opposite of SOC stability. Values are normalised. Boxplots represent the median, the first and third quartiles, and 1.5 × the inter-quartile range. Significant differences were tested with pairwise t-test or Wilcoxon test (two-sided), depending on data structure.  Selection process 8 Specify the methods used to decide whether a study met the inclusion criteria of the review, including how many reviewers screened each record and each report retrieved, whether they worked independently, and if applicable, details of automation tools used in the process.

Idem
Data collection process 9 Specify the methods used to collect data from reports, including how many reviewers collected data from each report, whether they worked independently, any processes for obtaining or confirming data from study investigators, and if applicable, details of automation tools used in the process. 10b List and define all other variables for which data were sought (e.g. participant and intervention characteristics, funding sources). Describe any assumptions made about any missing or unclear information.

Idem
Study risk of bias assessment 11 Specify the methods used to assess risk of bias in the included studies, including details of the tool(s) used, how many reviewers assessed each study and whether they worked independently, and if applicable, details of automation tools used in the process.
Data were extracted by both authors, working together. All studies and data were collegially evaluated to avoid inclusion/exclusion bias. See Methods Effect measures 12 Specify for each outcome the effect measure(s) (e.g. risk ratio, mean difference) used in the synthesis or presentation of results.

Methods (Data handling and normalisation; Data analysis)
Synthesis methods 13a Describe the processes used to decide which studies were eligible for each synthesis (e.g. tabulating the study intervention characteristics and comparing against the planned groups for each synthesis (item #5)). 13d Describe any methods used to synthesize results and provide a rationale for the choice(s). If meta-analysis was performed, describe the model(s), method(s) to identify the presence and extent of statistical heterogeneity, and software package(s) used.
Data were normalised to enable comparisons and synthesis of results (see Data handling and normalisation) 13e Describe any methods used to explore possible causes of heterogeneity among study results (e.g. subgroup analysis, metaregression).
Heterogeneity was assessed by using climate, soil properties, past land-use, plant functional types, and stand biomass as factors (see for instance Figures 3-4) 13f Describe any sensitivity analyses conducted to assess robustness of the synthesized results. Data were analysed using different methods, whose results were found to be consistent to each other (Methods: Data analysis) Reporting bias assessment 14 Describe any methods used to assess risk of bias due to missing results in a synthesis (arising from reporting biases). Data were evaluated collegially evaluated to avoid inclusion/exclusion bias. For regions where data were scarce, we applied the selection criteria with flexibility to avoid having areas of the world severely underrepresented in the dataset.
Certainty assessment 15 Describe any methods used to assess certainty (or confidence) in the body of evidence for an outcome. Methods: Data analysis

Study selection
16a Describe the results of the search and selection process, from the number of records identified in the search to the number of studies included in the review, ideally using a flow diagram.

Figure S15 in Supplementary Information
16b Cite studies that might appear to meet the inclusion criteria, but which were excluded, and explain why they were excluded. Examples and criteria are given lines 236   To test the reliability of the external datasets containing the estimated values, we compared them to our measured values (in the sites where the latter were available) by fitting linear regressions. Following the recommendation of Pineiro et al., the linear regressions were of the form: y = f ( ŷ ), where y and ŷ are the measured value and the estimated value, respectively. Are presented only the variables for which estimated values were found as reliable enough: MAT = mean annual temperature (°C); MAP = mean annual precipitation (mm yr -1 ); Elevation (m above sea level); soil texture (content in clay, content in sand, in mg g -1 ); base saturation of the cation exchange capacity of the soil (% capacity (µmol g -1 s -1 ); Vcmax: leaf photosynthesis carboxylation capacity (µmol/g/s); Stomatal gs: leaf stomatal conductance (mmol m -2 s -1 ); C, N, P, and Ca: content in carbon, nitrogen, phosphorus, or calcium (mg g -1 ). The proportion of estimated values presents the number of tree species for which the trait value is estimated. Because the tree species were not equally present in the SOC database, and because the tree species that had estimated trait values differed from trait to trait, the percentage value was not proportional to the number of tree species involved in the gap filling procedure. Linear regressions were fitted. Supplementary Table S10 | Data availability for the main functional traits used in the study. Leaf Amax: leaf photosynthetic maximum capacity (µmol g -1 s -1 ); LDMC: leaf dry matter content (g g -1 ); SLA: specific leaf area (mm 2 mg -1 ); SRL: specific root length (m g -1 ); Wood density (kg L -1 ); Leaf C, lignin, N, P, and Ca: content in carbon, lignin, nitrogen, phosphorus, or calcium (mg g -1 ); Seed mass (mg seed -1 ); Tree max height: maximum height observed for the tree species (m). The number of values from TRY, or other sources, represents the total data availability before applying the procedures of curation, homogenisation, and averaging (see Methods); After having calculating the mean values per each tree species, we calculated the proportion of the tree species having a non-missing measured value, and the proportion of tree species having an estimated value.