New World palm (Arecaceae) species richness in relation to

mean climate variables

University of ArizonaSemester Project, ATMO 529

Brad ChristoffersenDecember 05, 2007

Outline

• Background & Motivation• Methods of Analysis• Upcoming Results• Summary

Background and Motivation

• A little about palms:– Family: Arecaceae– Diverse habitats and hence morphologically diverse

• Key terms:– Species Richness (or Alpha diversity) – The number of

species in a given area.– Beta diversity – Change in species composition across a

landscape from one area to another.

• Why study species diversity in a spatial context?– Insight into how limiting factors control evolutionary

processes of speciation and extinction.– Provides basis for development of conservation areas.– Extensive body of theory from community ecology.

Methods of Analysis

• Palms dataset:– What: 1x1 degree grid of presence/absence

data for 547 species of palms.– Spatial Extent: New World– Calculated species richness by grid cell.

• Climate data:– What: CRU TS2.1 0.5x0.5 degree grid of

monthly precip and average temperature– Spatial Extent: Brazilian Amazon

• Plant rooting depth:– What: Maximum Plant Available Water (PAW),

from Kleidon et al. 2002

Methods of Analysis

• Palms dataset (Henderson et al. 2005):– Structure into presence/absence for the

547 species.– Convert to relative abundance (0-1)– EOF analysis of the matrix.

• Examine spatial pattern correlation among climate and dominant species range modes.

References• Henderson, A., G. Galeano, and R. Bernal. 1995. Field

Guide to the Palms of the Americas. Princeton University Press, Princeton, New Jersey, U.S.A.

• R Development Core Team (2007). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, URL http://www.R-project.org.

• Fields Development Team (2006). fields: Tools for Spatial Data. National Center for Atmospheric Research, Boulder, CO. URL http://www.cgd.ucar.edu/Software/Fields.

• Ter Braak, C. J. F. (1986) Canonical correspondence analysis: A new eigenvector technique for multivariate direct gradient analysis. Ecology 67:1167-1179.