Por favor, use este identificador para citar o enlazar a este item:
http://hdl.handle.net/10261/60840
COMPARTIR / EXPORTAR:
SHARE BASE | |
Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL | DATACITE | |
Título: | Testing a new multigroup inference approach to reconstructing past environmental conditions |
Autor: | Thompson, R.; Kamenik, C.; Schmidt, Roland; Pla-Rabes, Sergi CSIC ORCID; Rieradevall, María; Catalán, Jordi CSIC ORCID | Palabras clave: | Chironomids Chrysophyte cysts Cold environment Lake Diatom |
Fecha de publicación: | 2008 | Editor: | Istituto italiano di idrobiologia (Pallanza, Italia) | Citación: | Journal of Limnology 67(2): 155-162 (2008) | Resumen: | A new, quantitative, inference model for environmental reconstruction (transfer function), based for the first time on the simultaneous analysis of multigroup species, has been developed. Quantitative reconstructions based on palaeoecological transfer functions provide a powerful tool for addressing questions of environmental change in a wide range of environments, from oceans to mountain lakes, and over a range of timescales, from decades to millions of years. Much progress has been made in the development of inferences based on multiple proxies but usually these have been considered separately, and the different numeric reconstructions compared and reconciled post-hoc. This paper presents a new method to combine information from multiple biological groups at the reconstruction stage. The aim of the multigroup work was to test the potential of the new approach to making improved inferences of past environmental change by improving upon current reconstruction methodologies. The taxonomic groups analysed include diatoms, chironomids and chrysophyte cysts. We test the new methodology using two cold-environment training-sets, namely mountain lakes from the Pyrenees and the Alps. The use of multiple groups, as opposed to single groupings, was only found to increase the reconstruction skill slightly, as measured by the root mean square error of prediction (leave-one-out cross-validation), in the case of alkalinity, dissolved inorganic carbon and altitude (a surrogate for air-temperature), but not for pH or dissolved CO2. Reasons why the improvement was less than might have been anticipated are discussed. These can include the different life-forms, environmental responses and reaction times of the groups under study. | Descripción: | 8 páginas, 4 tablas. | Versión del editor: | http://www.jlimnol.it/index.php/jlimnol/article/view/jlimnol.2008.155/175 | URI: | http://hdl.handle.net/10261/60840 | ISSN: | 1723-8633 |
Aparece en las colecciones: | (CEAB) Artículos |
Ficheros en este ítem:
Fichero | Descripción | Tamaño | Formato | |
---|---|---|---|---|
175-349-1-SM.pdf | 221,9 kB | Adobe PDF | Visualizar/Abrir |
CORE Recommender
Page view(s)
292
checked on 22-abr-2024
Download(s)
152
checked on 22-abr-2024
Google ScholarTM
Check
NOTA: Los ítems de Digital.CSIC están protegidos por copyright, con todos los derechos reservados, a menos que se indique lo contrario.