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An improved method for the identification of areas of endemism using species co-occurrences
- Source :
- Journal of Biogeography, J.Biogeogr.
- Publication Year :
- 2008
- Publisher :
- Wiley, 2008.
-
Abstract
- Aim: To develop a simple method that (1) combines the notions of biotic elements (groups of taxa with ranges significantly more similar to each other than to the ranges of other taxa) and of areas of endemism (AoE, areas of non-random distributional congruence among taxa), and (2) overcomes the constraints of a previously suggested null model-based method that cannot deal with disjunctions and is strictly grid-dependent. Location: We used test data sets from southern Africa and Crete. Methods: First, we used a null-model approach to detect pairs of species that have a significant degree of co-occurrence, in order to determine biotic elements. Subsequently, we used a parsimony analysis of endemicity to delineate candidate AoE, and multivariate analysis to define groups of biotic elements on the basis of species interactions (co-occurrence, mutual exclusion, neutral) using only the species detected in the previous step. We applied this method to the well known data set for Sciobius in southern Africa, as well as to endemic invertebrates of Crete (Greece), in order to evaluate its performance. Results: Our results are very similar to those of previous analyses, and produce meaningful delineation of AoE and biotic elements in both data sets. The method is flexible regarding null models and significance levels, and eliminates noise in the data. Main conclusions: We offer a simple method that provides reasonable identification of both biotic elements and AoE, produces good-fit statistics, reduces uninformative or junk output, and reduces computational time. © 2007 The Authors. 35 893 902 Cited By :18
- Subjects :
- Biotic elements
identification method
Southern Europe
Biology
Historical biogeography
parsimony analysis
South Africa
Statistics
Co-occurrence
species occurrence
Endemism
Invertebrata
Ecology, Evolution, Behavior and Systematics
Statistical hypothesis testing
Greece
Sub-Saharan Africa
Ecology
Null model
coexistence
endemic species
Statistical model
Crete
PAE
Europe
Areas of endemism
Data set
multivariate analysis
Taxon
Null (SQL)
endemism
Africa
Sciobius
ecological modeling
Eurasia
Null models
Southern Africa
Subjects
Details
- ISSN :
- 13652699 and 03050270
- Volume :
- 35
- Database :
- OpenAIRE
- Journal :
- Journal of Biogeography
- Accession number :
- edsair.doi.dedup.....f0888b354cf160be0f74aede3b5e08f6