Giguet-Covex, Charline (2023): Intensity index of pastoral activities reconstructed from Lake Gers sediments, over the last 4600 years [dataset]. PANGAEA, https://doi.org/10.1594/PANGAEA.958885, In: Giguet-Covex, Charline; Chen, Wentao; Ficetola, Francesco Gentile; Gielly, Ludovic; Pansu, Johan (2023): Plant DNA analyses, nature and intensity of human activities, and erosion intensities in the North-western Alps over the last 4000-6000 years inferred from lake sediments [dataset bundled publication]. PANGAEA, https://doi.org/10.1594/PANGAEA.958732
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Keyword(s):
Related to:
Giguet-Covex, Charline; Bajard, Manon; Chen, Wentao; Walsh, Kevin; Rey, Pierre-Jérôme; Messager, Erwan; Etienne, David; Sabatier, Pierre; Ficetola, Francesco Gentile; Gielly, Ludovic; Blanchet, C; Guffond, Christophe; Chiquet, Patricia; Arnaud, Fabien; Poulenard, Jérôme (2023): Long-term trajectories of mountain agro-ecosystems in the North-Western Alps. Regional Environmental Change, 23(2), 58, https://doi.org/10.1007/s10113-023-02030-5
Coverage:
Latitude: 46.027233 * Longitude: 6.729512
Date/Time Start: 2016-01-18T00:00:00 * Date/Time End: 2016-01-18T00:00:00
Minimum Elevation: 1532.0 m * Maximum Elevation: 1532.0 m
Event(s):
Comment:
Method used to calculate the index: This index has been calculated on the basis of pastoral indicators obtained from the coprophilous fungi spore analysis and the DNA metabarcoding approach targeting plants (ruderal/nitrophilous taxa associated with pastoralism) and mammals (for domesticated animals). The selected pastoral indicators, here, are Sporormiella sp. for fungi spores, Plantago sp. and Rumex sp. for plants, and Bos, Ovis and Capra hircus for mammals. The index is calculated, after a transformation of each of these indicators (calculation of a z-score), as the average value of all these standardized indicators.
Method used to produce the sedimentary DNA datasets: DNA sequences were produced by using g (5'-GGGCAATCCTGAGCCAA-3') and h (5'-CCATTGAGTCTCTGCACCTATC-3') primers for plants and MamP007F (5'-CGAGAAGACCCTATGGAGCT-3') and MamP007R (5'-CCGAGGTCRCCCCAACC-3') primers and the human-blocking primer (5'-GGAGCTTTAATTTATTAATGCAAACAGTACCC-3') for mammals. The sequences have been produced by the Illumina technology (HiSeq instrument). The bioinformatic treatment of the sequences was operated applying the Obitool program (Boyer, F. et al. OBITOOLS:aUNIX-inspired software package for DNA metabarcoding. Mol. Ecol. Resour. 16, 176–182 (2016)) and following the procedure described in Giguet-Covex et al. New insights on lake sediment DNA from the catchment: importance of taphonomic and analytical issues on the record quality. Scientific Reports. 9, 14676 (2019) (DOI https://doi.org/10.1038/s41598-019-50339-1). Further filtering treatments were then applied, as also described in Giguet-Covex et al. 2019. These second treatments allow the removal of 1) taxa assigned to a reference taxon at <95 % of sequence identity, 2) potential contaminations (based on sampling, extraction and PCR controls, and recognition of exotic taxa) and 3) stochastic detections. Several analytical replicates by samples were performed (8 for both, the plants and mammals). Data are presented in number of positive replicates by sample. A replicate is considered as positive if more than 5 sequences are detected.
Parameter(s):
| # | Name | Short Name | Unit | Principal Investigator | Method/Device | Comment |
|---|---|---|---|---|---|---|
| 1 | Lake | Lake | Giguet-Covex, Charline | |||
| 2 | AGE | Age | ka BP | Giguet-Covex, Charline | Age model, radiocarbon dates and short radionuclides | Geocode |
| 3 | Age | Age | a AD/CE | Giguet-Covex, Charline | Age model, radiocarbon dates and short radionuclides | |
| 4 | Period, cultural | Period cultural | Giguet-Covex, Charline | |||
| 5 | Intensity, z-score | Intensity z | Giguet-Covex, Charline | Calculating the mean of z-scores of all taxa associated with pastoral activities |
License:
Creative Commons Attribution 4.0 International (CC-BY-4.0)
Status:
Curation Level: Enhanced curation (CurationLevelC)
Size:
140 data points
Data
| 1 Lake | 2 Age [ka BP] | 3 Age [a AD/CE] | 4 Period cultural | 5 Intensity z |
|---|---|---|---|---|
| Gers | -0.0500 | 2000.0 | Contemporary | -0.530507737 |
| Gers | 0.0715 | 1878.5 | Late modern | 0.116348754 |
| Gers | 0.1280 | 1822.0 | Late modern | 0.634057772 |
| Gers | 0.2230 | 1727.0 | Early modern | 1.094578780 |
| Gers | 0.3585 | 1591.5 | Early modern | 1.518675677 |
| Gers | 0.4540 | 1496.0 | Early modern | 0.328427753 |
| Gers | 0.5560 | 1394.0 | Late middle age | 0.324983835 |
| Gers | 0.6680 | 1282.0 | Late middle age | 1.269199001 |
| Gers | 0.7110 | 1239.0 | High middle age | 0.651381355 |
| Gers | 0.7545 | 1195.5 | High middle age | 0.652332521 |
| Gers | 0.8115 | 1138.5 | High middle age | 1.830677014 |
| Gers | 0.8595 | 1090.5 | High middle age | 1.744372199 |
| Gers | 0.9635 | 986.5 | Early middle age | -0.542904720 |
| Gers | 1.0915 | 858.5 | Early middle age | -0.332805456 |
| Gers | 1.2485 | 701.5 | Early middle age | -0.326962891 |
| Gers | 1.4305 | 519.5 | Early middle age | 0.016914150 |
| Gers | 1.6885 | 261.5 | End Roman period-Early Middle Age | -0.065476597 |
| Gers | 1.7320 | 218.0 | End Roman period-Early Middle Age | -0.154609860 |
| Gers | 1.9665 | -16.5 | Roman period | -0.214903914 |
| Gers | 2.0440 | -94.0 | Iron Age | -0.327259967 |
| Gers | 2.2145 | -264.5 | Iron Age | -0.507484772 |
| Gers | 2.4960 | -546.0 | Iron Age | -0.515468978 |
| Gers | 2.5855 | -635.5 | Iron Age | -0.455160963 |
| Gers | 2.7075 | -757.5 | Mid-late Bronze age | -0.627079235 |
| Gers | 2.8795 | -929.5 | Mid-late Bronze age | -0.613069510 |
| Gers | 3.1120 | -1162.0 | Mid-late Bronze age | -0.335257771 |
| Gers | 3.2775 | -1327.5 | Mid-late Bronze age | -0.466080457 |
| Gers | 3.5535 | -1603.5 | Mid-late Bronze age | -0.427616825 |
| Gers | 3.7605 | -1810.5 | Early Bronze age | -0.605437902 |
| Gers | 3.9780 | -2028.0 | Early Bronze age | -0.575985431 |
| Gers | 4.1495 | -2199.5 | Early Bronze age | -0.462079063 |
| Gers | 4.2260 | -2276.0 | Neolithic | -0.605277603 |
| Gers | 4.3050 | -2355.0 | Neolithic | -0.587009328 |
| Gers | 4.4140 | -2464.0 | Neolithic | -0.506644063 |
| Gers | 4.5570 | -2607.0 | Neolithic | -0.396865770 |