DOI: 10.5061/dryad.qn119
title: Data from: Resource stoichiometry and availability modulate species richness and biomass of tropical litter macro-invertebrates

description: 1. The high biodiversity and biomass of soil communities is crucial for
 litter decomposition in terrestrial ecosystems such as tropical forests.
 However, the leaf litter that these communities consume is of particularly
 poor quality as indicated by elemental stoichiometry. The impact of
 resource quantity, quality, and other habitat parameters on species
 richness and biomass of consumer communities is often studied in
 isolation, although much can be learned from simultaneously studying both
 community characteristics. 2. Using a data set of 780 macro-invertebrate
 consumer species across 32 sites in tropical lowland rainforest and
 agricultural systems on Sumatra, Indonesia, we investigated the effects of
 basal resource stoichiometry (C:X ratios of N, P, K, Ca, Mg, Na, S in
 local leaf litter), litter mass (basal resource quantity and habitat
 space), plant species richness (surrogate for litter habitat
 heterogeneity), and soil pH (acidity) on consumer species richness and
 biomass across different consumer groups (i.e., three feeding guilds and
 ten selected taxonomic groups). 3. In order to distinguish the most
 important predictors of consumer species richness and biomass, we applied
 a standardised model averaging approach investigating the effects of basal
 resource stoichiometry, litter mass, plant species richness, and soil pH
 on both consumer community characteristics. This standardised approach
 enabled us to identify differences and similarities in the magnitude and
 importance of such effects on consumer species richness and biomass. 4.
 Across consumer groups, we found litter mass to be the most important
 predictor of both species richness and biomass. Resource stoichiometry had
 a more pronounced impact on consumer species richness than on their
 biomass. As expected, taxonomic groups differed in which resource and
 habitat parameters (basal resource stoichiometry, litter mass, plant
 species richness, and pH) were most important for modulating their
 community characteristics. 5. The importance of litter mass for both
 species richness and biomass indicates that these tropical consumers
 strongly depend on habitat space and resource availability. Our study
 supports previous theoretical work indicating that consumer species
 richness is jointly influenced by resource availability and the balanced
 supply of multiple chemical elements in their resources.
description: Predictor variables for
 model averaging procedureLitter mass, plant
 species richness, soil pH and litter carbon to element ratios for N, P, K,
 Ca, Mg, Na, and S measured on the core sites of the EFForTS project
 (http://www.uni-goettingen.de/en/310995.html) in the Jambi Province on
 Sumatra, Indonesia in 2012. Sites are coded as landscape-land use
 system-replicate (two landscapes: Bukit Duabelas (B) and Harapan (H); four
 land-use systems: Forest (F), Jungle rubber (J), Rubber (R), Oil palm (O);
 four replicates). Litter_mass gives the dry litter mass per ground area in
 g cm-2 (Krashevska et al., Biol. Fertil. Soils, 2015). Plant_rich gives
 the species richness of all trees with a diameter equal to or larger than
 10 cm at breast height as well as all vascular plants per site. Soil pH,
 analysed in a 1:4 soil-to-water ratio, was taken from Allen et al. (PLoS
 ONE, 2015). Elemental ratios (CX) were calculated based on mg per g dry
 weight of the analysed leaf litter material. To obtain these site-averaged
 ratios, ratios of single leaf samples were weighted according to their
 relative importance in local leaf litter at each site (Jochum et al., The
 American Naturalist, 2017). Note that prior to analyses, predictor
 variables were transformed and standardized (see main
 article).Jochum_JAE2017_predictors.csvObserved litter macro-invertebrate species richness per consumer group and siteLitter macro-invertebrate species richness of 14 consumer groups observed on the core sites of the EFForTS project (http://www.uni-goettingen.de/en/310995.html) in the Jambi Province on Sumatra, Indonesia in 2012. Sites are coded as landscape-land use system-replicate (two landscapes: Bukit Duabelas (B) and Harapan (H); four land-use systems: Forest (F), Jungle rubber (J), Rubber (R), Oil palm (O); four replicates). Values represent species richness observed on 3 square metres per site for ten selected taxonomic groups (ants, blattodea, chilopoda, coleoptera, diplopoda, isopoda, isoptera, opiliones, orthoptera, spiders), three functional feeding guilds (detritivores, predators, omnivores) and the complete consumer community (all). It should be noted that the values for the selected taxonomic consumer groups do not necessarily add up to the values of the functional feeding guilds or the complete community as these aggregated groups contained more individuals than just the selected groups. These values are given as reference points for the extrapolated consumer species richness values actually used in the model averaging procedure.Jochum_JAE2017_observed_consumer_richness.csvExtrapolated litter macro-invertebrate species richness per consumer group and siteExtrapolated litter macro-invertebrate species richness of 14 consumer groups for the core sites of the EFForTS project (http://www.uni-goettingen.de/en/310995.html) in the Jambi Province on Sumatra, Indonesia in 2012. Sites are coded as landscape-land use system-replicate (two landscapes: Bukit Duabelas (B) and Harapan (H); four land-use systems: Forest (F), Jungle rubber (J), Rubber (R), Oil palm (O); four replicates). Values represent extrapolated species richness per site for ten selected taxonomic groups (ants, blattodea, chilopoda, coleoptera, diplopoda, isopoda, isoptera, opiliones, orthoptera, spiders), three functional feeding guilds (detritivores, predators, omnivores) and the complete consumer community (all). For each consumer group, extrapolated species richness was calculated based on the three subplot samples, using the nonparametric “jacknife 2” estimator (Brose et al., Ecology, 2003).Jochum_JAE2017_extrapolated_consumer_richness.csvLitter macro-invertebrate biomass per consumer group and siteFresh biomass of 14 litter macro-invertebrate groups from the core sites of the EFForTS project (http://www.uni-goettingen.de/en/310995.html) in the Jambi Province on Sumatra, Indonesia in 2012. Sites are coded as landscape-land use system-replicate (two landscapes: Bukit Duabelas (B) and Harapan (H); four land-use systems: Forest (F), Jungle rubber (J), Rubber (R), Oil palm (O); four replicates). Values represent fresh biomass per site for ten selected taxonomic groups (ants, blattodea, chilopoda, coleoptera, diplopoda, isopoda, isoptera, opiliones, orthoptera, spiders), three functional feeding guilds (detritivores, predators, omnivores) and the complete consumer community (all). Fresh biomass in mg m-2 was calculated as the sum of individual body masses of all sampled individuals that were, in turn, calculated using length-mass regressions from the literature (Barnes et al., Nat. Commun., 2014). It should be noted that the values for the selected taxonomic consumer groups do not necessarily add up to the values of the functional feeding guilds or the complete community as these aggregated groups contained more individuals than just the selected groups.Jochum_JAE2017_consumer_biomass.csvCoefficients and 95% confidence intervals for averaged consumer species richness models (Fig1)Standardized coefficients and 95% confidence intervals for each of the ten predictors from each of 14 averaged consumer species richness models presented in Figure 1. Consumer groups are the ten selected taxonomic groups (ants, blattodea, chilopoda, coleoptera, diplopoda, isopoda, isoptera, opiliones, orthoptera, spiders), three functional feeding guilds (detritivores, predators, omnivores) and the complete consumer community (all). Predictor variables are litter mass (LM), plant species richness (prich), soil pH (pH), and litter carbon to element ratios for N, P, K, Ca, Mg, Na, and S. Coef gives the standardized coefficient of each predictor for each averaged model. Confint_lower_boundary and confint_upper_boundary give the 95% confidence interval for the coefficients. It should be noted that for all stoichiometric parameters, negative coefficients indicate a positive effect of the respective elemental availability as the models were run on C:element ratios. As such, a positive effect of e.g. C:N corresponds to a negative effect of N in main text Fig. 1.Jochum_JAE2017_Fig1_richness_coefs_confint.csvCoefficients and 95% confidence intervals for averaged consumer biomass models (Fig2)Standardized coefficients and 95% confidence intervals for each of the ten predictors from each of 14 averaged consumer biomass models presented in Figure 2. Consumer groups are the ten selected taxonomic groups (ants, blattodea, chilopoda, coleoptera, diplopoda, isopoda, isoptera, opiliones, orthoptera, spiders), three functional feeding guilds (detritivores, predators, omnivores) and the complete consumer community (all). Predictor variables are litter mass (LM), plant species richness (prich), soil pH (pH), and litter carbon to element ratios for N, P, K, Ca, Mg, Na, and S. Coef gives the standardized coefficient of each predictor for each averaged model. Confint_lower_boundary and confint_upper_boundary give the 95% confidence interval for the coefficients. It should be noted that for all stoichiometric parameters, negative coefficients indicate a positive effect of the respective elemental availability as the models were run on C:element ratios. As such, a positive effect of e.g. C:N corresponds to a negative effect of N in main text Fig. 2.Jochum_JAE2017_Fig2_biomass_coefs_confint.csv