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How detritivores, plant traits and time modulate coupling of leaf versus woody litter decomposition rates across species

Cite this dataset

Guo, Chao et al. (2022). How detritivores, plant traits and time modulate coupling of leaf versus woody litter decomposition rates across species [Dataset]. Dryad. https://doi.org/10.5061/dryad.qjq2bvqkj

Abstract

1. Plant functional traits are increasingly used to understand ecological relationships and (changing) ecosystem functions. For understanding ecosystem-level biogeochemistry, we need to understand how (much) traits co-vary between different plant organs across species, and its implications for litter decomposition. However, we do not know how the degree of synchronous variation in decomposition rates between organs across species could be influenced by different keystone invertebrates decomposing different senesced plant organs, especially in warm-climate forests. Here we asked whether interspecific patterns in wood and leaf decomposition rates and in the spectra of resource economics traits underpinning them, co-vary across woody species; and how (much) the keystone invertebrate decomposers of the litter of these organs enhance or lower such co-variation of decomposition rates through time. 

2. We addressed these questions through an 18-month “common-garden” decomposition experiment using leaf, twig and branch litter of 41 woody species in two distant subtropical forest sites in east China. We quantified the effects of leaf, twig, and branch functional traits and their respective key invertebrates (moth larvae, termites) on the decomposition rates of those organs. 

3. Interspecific variation in wood traits was partly decoupled from that in leaf traits across species, while strong coupling was found between twigs and branches. The co-variation between leaf and woody organ decomposition rates was altered dynamically through the shifting activities of the key decomposers, which created non-linear relationships of invertebrate litter consumption as a function of species rankings along the resource economic trait spectra of leaves and branches.

4. The deviations from coupling of decomposition rates between organs were likely caused by combinations of three mechanisms: (1) (de-)coupling between organs of other traits, not commonly considered in resource economics spectra (e.g., resins) (2) leaf and wood decomposers having specific diet requirements, and (3) temporal patterns of the decomposers’ activity.

5. Synthesis. Our study highlights the importance of considering the different ways by which invertebrate detritivores drive decomposition processes through time. Under the ongoing biodiversity decline, future research would benefit from a better understanding of the role of the dynamic interactions between detritivore activities and plant functional traits on the carbon turnover in ecosystems.

Methods

The twig component of this experimental work, including the huge twig-related dataset for traits, termite consumption and decomposition across 41 species in two sites, is entirely new and critical to testing our conceptual model and hypotheses. The work and datasets for leaf and branch traits and decomposition rates overlap strongly (but not completely; see our new data subsets on leaf and branch decomposition below) with those used in two previous studies on single tree organs to test different hypotheses unrelated to organ co-variation of traits and decomposition (Guo et al., 2020; 2021); for these organs we provide brief methods here with reference to these two studies for further details.

Study sites

We conducted the in situ decomposition experiment Funlog in two subtropical evergreen broad-leaf forest sites in Zhejiang Province, E-China (details in Suppl. Table S1; Guo et al., 2020; 2021), both with subtropical monsoon climate: i) Tiantong National Forest Park (TT) (29°52′N, 121°39′E) on the mainland, with Schima superba as the predominant tree species; ii) Putuo island (PT) (29°97′N, 121°38′E), in the Zhoushan archipelago, with Quercus glauca being predominant. Based on previous observations (Guo et al., 2020), the moth Arippara indicator Walker is a key leaf litter detritivore in the PT forest litter layer. While 3-4 generations inhabit the litter layer from May to November (Leraut, 2013), larval abundance and consumption activity peak from August through November (details in Appendix S1: Fig. S1). In both sites, termites are the main detritivores of deadwood including branches in the litter layer (details in Appendix S1: Fig. S2; Guo et al., 2021).

Tree species and sampling

In October-November 2017, we collected leaf, twig, and branch samples from 41 common woody species in TT and PT, 8 evergreen trees, 12 evergreen shrubs (including short understory trees), 11 deciduous trees, 5 deciduous shrubs and 5 conifer trees (see Guo et al., 2021, details in Appendix S1: Table S2). In total, 195 individual healthy adult trees/shrubs were selected, i.e., 27 species × 3 tree individuals and 19 species × 6 shrub individuals. The rationale for selecting living trees was (1) to standardize the initial, undegraded phase for all samples (Cornelissen et al., 2012); (2) to mimic typhoon-induced wind-throw and logging as predominant agents of deadwood formation on the forest floor. We chain-sawed 20 cm long branch sections of approx. 5cm diameter; cut twig samples into 10 cm long sections of approx. 2 cm diameter (to standardize diameter as a possible covariate of decomposition rate). Adjacent to each end of a branch we cut off a 2 cm thick disk for initial branch trait analyses, while for twigs and leaves we randomly selected subsamples from each individual per species for initial trait measurement. All leaf litter and twig samples were stored air-dried until further use. Due to space/time constraints, branch samples were weighed at field moisture before sealing them into litter-bags (see below).

Litter decomposition experiment

Similar sub-experiments were set up simultaneously at both sites. Leaf, twig, and branch subsamples from each individual per species were weighed air-dried and oven-dried (75 °C) for the calculation of initial dry mass of the litter-bag samples via water content. For the leaf litter incubation, details are in Guo et al. (2020), but here we added a harvest after 18 months, which yielded a large new dataset compared to that study. Briefly, 10g of pre-weighed air-dried leaves were sealed into 1-mm mesh nylon litter-bags, with broadly similar packing density among species. For the twig incubation, we sealed two pre-weighed twig sections per sample into 10 × 20 cm nylon litter-bags with 4 mm mesh. For branch incubation (details in Guo et al., 2021, but here we added an additional 12 woody species to the decomposition dataset), we used 4 mm mesh nylon litter-bags. These different mesh sizes were based on achieving the best compromise in terms of allowing free access to the main detritivores (allowing ranking of the “natural” contribution of invertebrates to decomposition for each organ) while preventing litter particles from falling out throughout the decomposition trajectory for each of the tree organs – the latter was especially important for leaf litter of small-leaved conifers and fragile-leaved deciduous species. Based on field surveys before the experiment, the main leaf litter detritivores were moth larvae (Guo et al., 2020), which could enter the 1 mm mesh easily. Termites, which are estimated to be responsible for > 90 % of the invertebrate contribution to decomposition, were found to have body diameters between 1.21 mm and 2.67 mm (authors’ measaurements), leading to the choice of 4 mm mesh. The only other possible significant contributor to leaf and woody litter decomposition in our study sites, large millipeds, have body diameters around 7 mm, so these had to be excluded from the experiment altogether to prevent litter particle losses from the litter-bags. In total, 2469 litter-bag samples were used, based on 46 tree species (including 5 repeated species) × 3 organs × 3 replications (plots) × 2 incubation sites × 3 harvest times.

The litter-bag samples were distributed over three replicate forest plots in each sites, in January 2018 (details in Guo et al., 2020; 2021). The litter-bags of each species were pinned onto the forest floor in their respective subplots within each of the three replicate plots randomly, and each species’ replicate had three litter-bags per organ one for each harvest. Harvests were after 6 (Jul. 2018), 12 (Jan. 2019), and 18 months (Jul. 2019).

 We carefully cleaned the collected leaf samples with a brush. Each twig and branch sample was put in a large tray with steep, tall edges to retain the termites. We cut the sample into small pieces and removed soil (brought in by termites) with a brush carefully. All samples were then oven-dried at 75 °C to constant mass and weighed (dry mass).

Plant organ trait measurements

Details of leaf trait measurements relevant to the LES, including leaf thickness, leaf chemistry, specific leaf area (SLA) and leaf dry matter content (LDMC), were reported by Guo et al. (2020).

For initial wood traits considered relevant to the WES and to decomposition, each 2 cm subsample of branch or 10 cm long twig was stored cool in a sealed plastic bag between collection in the field and processing. Within 12h, after bark removal, a subsample was cut from each disk of branch and twig to obtain fresh mass and determine initial volume (Williamson & Wiemann, 2010). All wood subsamples were dried at 75 °C for 72h. Initial wood density (WD) was calculated as dry mass per volume.

For chemical trait measurements of leaf and woody litter, initial leaf, twig and branch subsamples were ground to powder. Thereafter, 0.2g sub-samples were digested using concentrated H2SO4 to determine N and P concentrations on an infrared spectrophotometer (Smartchem 200, Alliance, France). For branches, lignin content was determined by acidolysis-titration, and cellulose content was determined by anthrone-sulfuric acid colorimetry.

Moth larvae and termite activity measurements

Upon harvesting of the leaf litter bags, macrofauna (Arippara indicator larvae) were collected and counted, and moth larvae faeces extracted, oven-dried at 75 °C and weighed for dry mass (details in Guo et al., 2020). The feeding intensity of larvae was defined by larval abundance and divided into six classes: (0), (1), (2), (3), (4) indicated 0, 1, 2 3, 4 larvae, respectively; (5) ≥ 5 larvae. 

We visually scored the termites’ feeding intensity of branches and twigs after cleaning the litter-bag samples. We (see Guo et al., 2021 for details) adjusted the method that classifies termite feeding intensity based on the bite marks (Liu et al., 2015). Briefly, we measured the percentage surface area loss due to termite activity using a visual grid method. After removing soil brought in by termites, we estimated the depth of termite damage in five random spots along the sample surface. The area loss and foraging depth were used to estimate the percentage of sample volume of twig or branch consumed by termites, distinguishing 5 classes; (1) 1-10% (2) 11-20%, (3) 21-30%, (4) 31-40%, (5) > 41% volume loss.

Funding

National Natural Science Foundation of China, Award: 32030068

National Natural Science Foundation of China, Award: 31700351

China Postdoctoral Science Foundation, Award: 2021M691029

China Postdoctoral Science Foundation, Award: 2021TQ0110