Terrestrial invertebrates are highly important for the decomposition of dung from large mammals. Mammal dung has been present in most of Earth’s ecosystems for millions of years, enabling the evolution of a broad diversity of dung-associated invertebrates that process various components of the dung. Today, large herbivore mammals are increasingly introduced to ecosystems with the aim of restoring the ecological functions formerly provided by their extinct counterparts. However, we still know little about the ecosystem functions and nutrient flows in these rewilded ecosystems, including the dynamics of dung decomposition. In fact, the succession of insect communities in dung is an area of limited research attention also outside of a rewilding context. In this study, we use environmental DNA metabarcoding of dung from rewilded Galloway cattle in an experimental setup to investigate invertebrate communities and functional dynamics over a time span of 53 days, starting from the time of deposition. We find a strong signal of successional change in community composition, including for the species that are directly dependent on dung as a resource. While several of these species were detected consistently across the sampling period, others appeared confined to either early or late successional stages. We believe this is indicative of evolutionary adaptation to a highly dynamic resource, with species showing niche partitioning on a temporal scale. However, our results show consistently high species diversity within the functional groups that are directly dependent on dung. Our findings of such redundancy suggest functional stability of the dung-associated invertebrate community, with several species ready to fill vacant niches if other species disappear. Importantly, this might also be a potential mechanism buffering the ecosystem functions related to dung decomposition against environmental change. Interestingly, alpha diversity peaked after approximately 20-25 days in both meadow and pasture habitats, and did not decrease substantially during the experimental period, probably due to preservation of eDNA in the dung after the disappearance of visiting invertebrates, and from detection of tissue remains and cryptic life stages.

The dataset consists of DNA reads from High Throughput sequencing of samples collected through an natural experiment investigating invertebrate succession in cattle dung. The experiment was conducted in the Mols Laboratory area in Denmark (56°13′36”N, 10°34′33″E), where 60 kg of fresh dung was collected, homogenized, and separated out in 18 pools, which were placed in six experimental plots. Three plots were located in meadows and three were located in pastures. Samples were collected from all 18 dung pools after 1, 4, 11, 25, 39, and 53 days, resulting in 108 samples in total. In addition, three fresh dung samples were collected, and three samples were taken from the homogenized pool before if was divided in the 18 sub-pools, as starting-point controls. DNA was extracted from the samples with the Fast DNA Stool Mini Kit from Qiagen, and amplified by PCR reactions (see PCR reagents and thermal settings, etc. in the associated manuscript) with the BF-1/BR-1 primers (Elbrecht & Leese, 2017, https://doi.org/10.3389/fenvs.2017.00011), targeting a 217 bp fragment of COI optimized for invertebrates. During the laboratory pipeline, 13 extraction blanks, and nine PCR blanks were included, which were sequenced alongside the rest of the samples. Furthermore, 9 samples from another study was included in the sequencing libraries (sample names including "_tx.1" - "_tx.9"). Hence, in total, the uploaded sequencing output includes DNA reads obtained from 145 samples, which were separated in three batches, each in 4 PCR replicates. For 4 libraries (Pool7, 10, 11 & 12) additional sequencing were performed, and thus two separate raw data files exist from these libraries. See README.md for description of how to treat these in the bioinformatic pipeline.

The raw sequencing data were run through the MetaBarFlow pipeline (https://github.com/evaegelyng/MetaBarFlow), with parameters following Thomassen et al. (2024) (https://doi.org/10.1111/mec.16847). The pipeline produces an ASV list (Succession_DADA2_nochim.otus), and a matrix with read counts of each ASV in each sample (Succession_DADA2_nochim.table), as well as a list with taxonomic assignment of all ASVs (Succession_classified.txt). The taxonomic identification of DNA sequencing reads were made by blasting (blastn) against a custom build COI database containing all COI sequences from BOLD (www.boldsystems.org) and NCBI Genbank (https://www.ncbi.nlm.nih.gov/) See Klepke et al. (2022) (https://doi.org/10.1002/edn3.340) for further description of how the database was built, and the associated publication for details of Blast parameters.

For final taxonomic assignment (score_ID column in "Succession_classified.txt") was defined as the last common ancestor of all blast hits within the range of sequence similarity of hits to the best match, including hits within a 2% margin of the best ID, and species ID was only assigned if the best match was >98% similar.

The list of taxonomic assignement was manually checked for errors resulting from spurious reference database sequences or similar, and when such errors were spotted, the taxonomic assignement of the given ASV was corrected manually. Also, ASVs identified at higher levels than species were assigned to "putative species", which were units including the same possible IDs. This final manually edited IDs is found in the "final_ID" column in the file "Succession_classified_corrected.txt".

See manuscript for further details about subsequent analysis.

All raw sequencing output files are uploaded (end in .fq.gz), the files for demultiplexing (end in tags.txt) and an example file to use in MetaBarFlow (Succession_example_batchfileDADA2.list) and the following output files from MetaBarFlow:

• Succession_classified.txt (the original taxonomic classification file of ASVs from MetaBarFlow)
• Succession_classified_corrected.txt (the manually corrected taxonomy-file)
• Succession_DADA2_nochim.otus (List of all ASVs defines by MetaBarFlow)
• Succession_DADA2_nochim.table (ASV/sample read count matrix