PhD course

Spatial Data Analysis in Macroecology

13-17 August 2007 - Copenhagen, Denmark

Course folder (pdf)   Course flier (pdf)

The powerpoint presentation of each lecture can be downloaded here, along with the pdf notes used for the practical.

Lecture notes (ppt)    Practical notes (pdf)

Introduction

Whereas spatially structured data present an interesting opportunity to investigate ecological and evolutionary mechanisms underlying spatial patterns, spatial structure may be also a source of model misspecification. Despite the importance of this issue, there are still difficulties in dealing with spatial autocorrelation, mainly due to the lack of computational tools.

Scope of the course

The purpose of the course is to introduce students to basic concepts in the analysis of autocorrelated data, focusing on spatial and phylogenetic dimensions, and their application in macroecology, biogeography and comparative biology.
The course will combine presentations with discussions of published studies, as well as practical classes using the SAM (Spatial Analysis in Macroecology – see www.ecoevol.ufg.br/sam). There will be full space for formal and informal interactions between students and teachers, so that students will be the driving force behind the course and not simply spectators

Guest teacher

• Alexandre Diniz-Filho
  University of Goiás


• Thiago Rangel
  University of Connecticut

Organisers

• Carsten Rahbek
  CRahbek@bi.ku.dk


• Tom S. Romdal
  TSRomdal@bi.ku.dk.

Address:
Center for Macroecology
Institute of Biology
Department of Population Biology
Universitetsparken 15
University of Copenhagen
DK-2100 Copenhagen

Course set-up

The course is five days. The first, second and third days will include plenary lectures given by the teachers, each followed by open discussion, and group-work consisting of discussion of seminal papers published in international peer-reviewed journals. Students will be given the opportunity to present their own research in two sessions of short talks. The fourth and fifth day will be devoted to a guided tour and practical work in SAM.

Outline

The course aims at imparting a solid understanding of spatial analytical concepts. This will include a coverage of:

1. Conceptual aspects of spatial analysis in ecology and macroecology
2. Mapping techniques (trend surfaces and kriging)
3. Creating spatial connections among observational units
4. Global and local coefficients of spatial autocorrelation
5. Spatial correlograms and variograms: interpretation and applications in ecology, genetics and evolutionary biology
6. Spatial correlation
7. Partial regression and path analysis
8. Ordinary Least-Squares (OLS) regression and spatial autocorrelation
9. Spatial regression (GLS, AR, SAR, CAR, GWR)
10. Eigenvector-based spatial filtering

Software

Basic papers

Cressie, N. A. C. (1993). Statistics for spatial data analysis. John Wiley & Sons, NY.
Fotheringham, A. S., Brunsdon, C. & Charlton, M. (2002). Quantitative Geography: perspectives on spatial data analysis. SAGE, London.
Griffith, D. A. (1987). Spatial Autocorrelation: a primer. Resource publications in Geography, Association of American Geographers, Washington DC.
Griffith, D.A. (2003) Spatial autocorrelation and spatial filtering. Springer-Verlag, Berlin.
Haining, R. (1990). Spatial Data Analysis in the Social and Environmental Sciences. Cambridge University Press, Cambridge.
Legendre, P. & Legendre, L. (1998). Numerical Ecology. Elsevier, Amsterdam.
Schabenberger, O. & Gotway, C. A. (2005) Statistical methods for spatial data analysis. Chapman & Hall, London.

Journals: Global Ecology & Biogeography, Ecography, Biological Journal of Linnean Society, Ecology, Ecological Applications, Journal of Biogeography, American Naturalist

Registration and fees

Deadline: 1st May 2007