DOI: 10.6084/m9.figshare.27823221.v1
title: Global engineering effects of soil invertebrates on ecosystem functions

description: We compiled a global dataset and synthesized published data from 1,047 studies (Fig. 1 and Fig. S1; see the dataset for details) of the engineering effects of termites, ants, and earthworms on 47 ecosystem properties (with the number of observations varying from 2 to 598). We extracted 14 properties for soil nutrients, 11 for soil physical and chemical properties, 8 for nutrient cycling, and 14 for the state (e.g. biomass and diversity) of associated biota including plants, microbes, and animals. Among these ecosystem properties, soil C, N, and P content, soil respiration, and plant biomass were more frequently investigated than the others, and thus stressed in this meta-analysis. We calculated the effect of soil engineering (i.e. biogenic structure vs. reference soil; or presence vs. absence of invertebrate engineers) on the ecosystem properties as the log response ratio (LnRR). The density (or weight) of biogenic structures ranged between 0.63~~1,500/ha (0.2~~151.3 ton/ha) for termite mounds, 0.3~~58,622/ha (0.2~~652 ton/ha) for ant hills, and 200~~935,000/ha (0.1~~192.2 ton/ha) for earthworm casts according to the studies included. To include data with incomplete statistics (i.e. averages without standard deviations or sample sizes), we modelled the log-response ratio of ecosystem properties with and without sampling variance as parameter weight simultaneously. To include data with incomplete statistics (i.e. averages without standard deviations), we modelled the log-response ratio of ecosystem properties with the sample size or sampling variance as parameter weight respectively. We therefore defined the “significant” effects only if they were significant (p &lt; 0.05) in both models, or significant in one model and marginally significant (p &lt; 0.1) in another model. Our synthesis addressed three major questions: (1) What are the similarities and differences among the three dominant invertebrate taxa in soil engineering effects on each ecosystem property? (2) Can resource availability (e.g. as represented by NPP and soil depth) or climate (e.g. MAT and water availability) explain the latitudinal patterns of soil engineering effects? (3) Does the impact of these taxa on soil nutrients and physical properties co-determine C dynamics, by increasing soil respiration and plant biomass, respectively?

We found that all three taxa increased soil macronutrients, soil respiration, microbial and plant biomass in bioturbated soil compared with surrounding soil. Temperature and aridity were the dominant drivers for termite and earthworm effects that exhibited linear latitudinal patterns, while net primary productivity (NPP) was responsible for the hump-shaped latitudinal patterns of ant effects. Notably, termite effects on plant growth and soil respiration increased with temperature, while termite and earthworm effects on plant growth and survival, respectively, strengthened with aridity. Besides, termites and ants boosted plant growth by resolving plant P and N limitation, respectively, in the tropics and temperate regions.

Description of the data and file structure
This study provided seven datasets for analyses and visualization. The first three datasets ("Data source compilation_taxa.xlsx") contain the original records and reference source of ecosystem properties in treatment and control soil for termites, ants and earthworms. The log-response ratio and sampling variance were calculated according to the formula in Lajeunesse 2011 (Ecology), while the replication weighting was calculated according to the formula in Adams et al. 1997 (Ecology). We also grouped similar ecosystem functions into another dataset ("Data source compilation_multifunctionality.xlsx") to test if the three taxa can simultaneously enhance multiple ecosystem functions. We further extracted environmental predictors (wetness, MAT, NPP, soil depth and the ratio of N limitation and P limitation index) based on the spatial coordinates of field studies, which could be found in the fourth dataset ("coordinates with predictors.csv"). Moreover, we summarized the pairwise observations of soil properties (nutrients, moisture content and clay content) and C dynamics (soil respiration and plant biomass) from the same study ("Pairwise correlation between soil engineering effects.xlsx"). Finally, we also provided the summary tables ("Tables.S1-S3.xlsx") for the overall soil engineering effects on individual function and on grouped functions to plot Figure 2, considering that it may take ~10 hr to generate summary tables. Please put all files (except the "Tables.S1-S3.xlsx") under the same working directory to reproduce the results and figures.