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Dryad

Data for: Stratification and recovery time jointly shape ant functional re-assembly in a Neotropical forest

Cite this dataset

Hoenle, Philipp et al. (2023). Data for: Stratification and recovery time jointly shape ant functional re-assembly in a Neotropical forest [Dataset]. Dryad. https://doi.org/10.5061/dryad.jsxksn0fc

Abstract

Microhabitat differentiation of species communities such as vertical stratification in tropical forests contributes to species coexistence and thus biodiversity. However, little is known about how the extent of stratification changes during forest recovery and influences community reassembly. Environmental filtering determines community reassembly in time (succession) and in space (stratification), hence functional and phylogenetic composition of species communities are highly dynamic. It is poorly understood if and how these two concurrent filters – forest recovery and stratification – interact.

In a tropical forest chronosequence in Ecuador spanning 34 years of natural recovery, we investigated the recovery trajectory of ant communities in three overlapping strata (ground, leaf litter, lower tree trunk) by quantifying 13 traits, as well as the functional and phylogenetic diversity of the ants. We expected that functional and phylogenetic diversity increase with recovery time and that each ant community within each stratum shows a distinct functional reassembly. We predicted that traits related to ant diet show divergent trajectories reflecting an increase in niche differentiation with recovery time. On the other hand, traits related to the abiotic environment were predicted to show convergent trajectories due to a more similar microclimate across strata with increasing recovery age.

Most of the functional traits and the phylogenetic diversity of the ants were clearly stratified, confirming previous findings. However, neither functional nor phylogenetic diversity increased with recovery time. Community-weighted trait means had complex relationships to recovery time and the majority were shaped by a statistical interaction between recovery time and stratum, confirming our expectations. However, most trait trajectories converged among strata with increasing recovery time regardless of whether they were related to ant diet or environmental conditions.

We confirm the hypothesized interaction among environmental filters during the functional reassembly in tropical forests. Communities in individual strata respond differently to recovery, and possible filter mechanisms likely arise from both abiotic (e.g., microclimate) and biotic (e.g., diet) conditions. Since vertical stratification is prevalent across animal and plant taxa, our results highlight the importance of stratum-specific analysis in dynamic ecosystems and may generalize beyond ants.

Methods

This data sets contains the raw data and R-script associated with our research article. It contains ant collection data in a chronosequence in Ecuador, as well as measurements of the ant traits. Note that a similar version of the ant and trait dataset has already been uploaded here for another article: https://doi.org/10.5061/dryad.83bk3j9sk

We collected ants by leaf-litter extraction with Winkler, handsampling on the ground and handsampling on tree trunks on 61 plots. Ants are recorded as  occurrences (=presence/absence) per method per plot (3 methods per plot). The methods represent different strata, and we analyse their traits and phylogeny across stratification and forest recovery. Our files include metadata on the plots, a list of the collected ant species and their occurence in each stratum, and a list of trait measurements on ant individuals. The ant traits were measured from individuals collected in our study site. A description of trait abbreviations can be found in our R-script. For more detailed descriptions of the sampling protocols, plot selection and statistical analysis can be found in the associated paper. 

The R-script is annotated and describes our statistical procedures and used R-packages, and contains also descriptive information on the csv.-files.

Usage notes

Data can be accessed using Excel and R.

Funding

German National Academic Foundation

Deutsche Forschungsgemeinschaft, Award: FOR 5207

National Polytechnic School, Award: PII-ICB-02-2017

National Polytechnic School, Award: PII-DB-2019-02