Long livestock farming history and human landscape shaping revealed by lake sediment DNA

Abstract

The reconstruction of human-driven, Earth-shaping dynamics is important for understanding past human/environment interactions and for helping human societies that currently face global changes. However, it is often challenging to distinguish the effects of the climate from human activities on environmental changes. Here we evaluate an approach based on DNA metabarcoding used on lake sediments to provide the first high-resolution reconstruction of plant cover and livestock farming history since the Neolithic Period. By comparing these data with a previous reconstruction of erosive event frequency, we show that the most intense erosion period was caused by deforestation and overgrazing by sheep and cowherds during the Late Iron Age and Roman Period. Tracking plants and domestic mammals using lake sediment DNA (lake sedDNA) is a new, promising method for tracing past human practices, and it provides a new outlook of the effects of anthropogenic factors on landscape-scale changes.

First human impacts and responses of aquatic systems: A review of palaeolimnological records from around the world

“…However, while detecting human impacts at local scales can be challenging for the stated reasons, recent techniques are promising, including specific biomolecular markers (see Dubois and Jacob, 2016, for a review), ancient DNA (e.g. Anderson-Carpenter et al, 2011;Domaizon et al, 2017;Giguet-Covex et al, 2014), high-resolution stratigraphy and sediment scanning techniques (e.g. Arnaud et al, 2012;Flower et al, 2012;Marquer et al, 2008) as well as wider use of macrofossils combined with stable isotope studies (e.g.…”

“…At a higher elevation site (Lake Anterne, located at 2063 m a.s.l. ), fluctuations in sedimentation are dominated by the terrigenous fraction, and follow roughly regional climate signals since at least 4000 b2k, but sedimentary ancient DNA (aDNA) demonstrated that the most intense erosion period was caused by deforestation and overgrazing by sheep and cattle during the Late Iron Age and Roman Period (400 bce-200 ce; Giguet-Covex et al, 2014). In a high alpine Lake in Switzerland (Sägistalersee, located at 1935 m a.s.l.…”

“…In addition, the ability of small organisms (such diatoms) to disperse, makes the concept of non-native taxa rather controversial. However, recent developments in the analysis of ancient DNA preserved in lake sediments (see Anderson-Carpenter et al, 2011;Domaizon et al, 2017;Giguet-Covex et al, 2014) may make it possible to trace the timing and extent of species introductions with better accuracy, or to assess if certain species are in fact invasive or native (Preston et al, 2004;Stager et al, 2015). This powerful new tool in the palaeolimnological toolbox provides the possibility of tracing a greater range of species introductions even further into the past and to link them with early human presence.…”

Lake sediment multi-taxon DNA from North Greenland records early post-glacial appearance of vascular plants and accurately tracks environmental changes

“…DNA from both plants and plankton has been found in sediment cores spanning centennial to millennial time scales at lower latitudes (e.g. Epp et al, 2010;Stoof-Leichsenring et al, 2012;Boessenkool et al, 2014;Giguet-Covex et al, 2014), but highlatitude lakes, such as in the Arctic, can supposedly yield results going back further in time, because conditions for DNA preservation are optimal under cold conditions (Lindahl, 1993;P€ a€ abo et al, 2004;Willerslev et al, 2004;Hofreiter et al, 2012).…”

Proper experimental design requires randomization/balancing of molecular ecology experiments

“…Potential contamination and false detection biases were controlled for by following the recommendations of Giguet-Covex et al, 2014;Pansu et al, 2015) were run with GNU "parallel" when possible (Tange, 2011 (Hill, 1973) to estimate the effects of potential laboratory biases and biological factors of interests. The first three Hill numbers correspond to species richness (H1), the exponent of Shannon diversity (H2), and the inverse of the Simpson diversity (H3).…”