CNR ExploRA

Poster, 2019, ENG

Pollen as a proxy for elevational ecoclimatic gradients - integrating climate, biodiversity, and time dimensions of biogeography

RAVAZZI C., FURLANETTO G., BADINO F., BRUNETTI M., COMOLLI R., DE NASCIMENTO L., FERNÁNDEZ PALACIOS J.M., MAGGI V., NARANJO CIGALA A., PINI R., SERGE M.A., VALLÉ F.

1 CNR - Institute for the Dynamics of Environmental Processes (IDPA), Laboratory of Palynology and Palaeoecology, Milano (I) 2 Univ. of Milano - Bicocca, Dept. of Environmental and Earth Sciences, Milano (I) 3 University of Bologna, Dept of Cultural Heritage, Ravenna (I) 4 CNR- Institute of Atmospheric Sciences and Climate (ISAC), Bologna (I). 5 La Laguna University, La Laguna, Tenerife (E) 6 University of Las Palmas de Gran Canaria, Las Palmas (E)

During his explorations in temperate and tropical mountains, Humboldt made crucial observations about the importance of elevational climate gradients as drivers for biodiversity. We show here that pollen deposition may be a suitable, and statistically robust proxy for climate-driven elevational eco-gradients, thus assisting in the interpretation of modern ecosystem dynamics as well as in past climate reconstructions from fossil records. Our specific challenges are: (1) to derive consistent pollen-climate relationships in complex mountain regions bearing differences in local climates and intensity of human impact; (2) to find potential indicator taxa useful for paleoclimate reconstructions; (3) to estimate the effect of local parameters on the relationships linking pollen percentages variations, elevation and climate and put forward new hints for calibration of fossil sites; (4) to obtain quantitative climate reconstructions and compare the results with instrumental modelled data and finally (5) to integrate the newly-obtained pollen spectra into larger modern pollen samples datasets. We analyzed pollen deposition in the European Alps and the Canaries, captured by surface samples (subsampling mosses, forest litter, surface soil in open ground land) and artificial traps both at the ground level and over it. To examine the variance explained by climate parameters, elevational training sets were equipped with site-specific climatologies, together with an array of environmental variables (i.e. proxies for fire, nutrients, pastoralism, terrain parameters, plant cover). The potential for a quantitative reconstruction of sensible climate parameters was tested by canonical correspondence analysis (CCA), enhanced hierarchical logistic regression (extended eHOF models), and weighted averaging (WA).

Humboldt 250 - International Biogeographical Society, Quito (Ecuador), 4/8/2019, 9/8/2019