Not logged in
PANGAEA.
Data Publisher for Earth & Environmental Science

Mensing, Scott; Piovesan, Gianluca; Tunno, Irene (2018): XRF analysis of sediments of Lake Lungo, Italy [dataset]. PANGAEA, https://doi.org/10.1594/PANGAEA.885938

Always quote citation above when using data! You can download the citation in several formats below.

RIS CitationBibTeX CitationShow MapGoogle Earth

Related to:
Mensing, Scott; Schoolman, Edward M; Tunno, Irene; Noble, Paula; Sagnotti, Leonardo; Florindo, Fabio; Piovesan, Gianluca (accepted): Historical ecology reveals landscape transformation coincident with cultural development in central Italy since the Roman Period.
Mensing, Scott; Tunno, Irene; Cifani, Gabriele; Passigli, Susanna; Noble, Paula; Archer, Claire; Piovesan, Gianluca (2016): Human and climatically induced environmental change in the Mediterranean during the Medieval Climate Anomaly and Little Ice Age: A case from central Italy. Anthropocene, 15, 49-59, https://doi.org/10.1016/j.ancene.2016.01.003
Mensing, Scott; Tunno, Irene; Sagnotti, Leonardo; Florindo, Fabio; Noble, Paula; Archer, Claire; Zimmerman, Susan; Pavón-Carrasco, Francisco Javier; Cifani, Gabriele; Passigli, Susanna; Piovesan, Gianluca (2015): 2700 years of Mediterranean environmental change in central Italy: a synthesis of sedimentary and cultural records to interpret past impacts of climate on society. Quaternary Science Reviews, 116, 72-94, https://doi.org/10.1016/j.quascirev.2015.03.022
Schoolman, Edward M; Mensing, Scott; Piovesan, Gianluca (submitted): Local Patterns of land use and the human impact on the environment in the Rieti Basin, 600-1000 AD. Journal of Interactive Humanities
Coverage:
Latitude: 42.476200 * Longitude: 12.847000
Minimum DEPTH, sediment/rock: 0.000 m * Maximum DEPTH, sediment/rock: 14.380 m
Event(s):
Lake_Lungo * Latitude: 42.476200 * Longitude: 12.847000 * Location: Europe, Italy * Method/Device: Piston corer (PC)
Size:
105741 data points

Download Data

Download dataset as tab-delimited text — use the following character encoding:

View dataset as HTML (shows only first 2000 rows)