For ambiguous data sets, methods to determine areas of endemism based on an optimality criterion may result in large numbers of candidate areas, and thus some kind of consensus technique is required to summarize those results. This paper presents a formal description of two possible algorithms or rules for area consensus, which merge candidate areas if they share a user‐defined percentage of the species that define each candidate area. The two consensus rules summarize ambiguity in different ways. Applying the ‘tight’ rule will result in consensus areas defined by species present in nearly all cells, but in cases where there is significant conflict the result may be a high number of distinct consensus areas. The ‘loose’ consensus rule is more agglomerative and will result in fewer consensus areas, combining areas when overlapping distribution patterns exist. Depending on the aim and scale of the analysis, the two consensus rules can be used either to delimit areas of endemism with sharp boundaries or to identify diffuse and gradually replacing biogeographical patterns. These two different approaches are discussed and demonstrated using real data.
Consensus in the search for areas of endemism
L. Aagesen,C. Szumik,P. Goloboff
Published 2013 in Journal of Biogeography
ABSTRACT
PUBLICATION RECORD
- Publication year
2013
- Venue
Journal of Biogeography
- Publication date
2013-11-01
- Fields of study
Geography, Environmental Science
- Identifiers
- External record
- Source metadata
Semantic Scholar
CITATION MAP
EXTRACTION MAP
CLAIMS
- No claims are published for this paper.
CONCEPTS
- No concepts are published for this paper.
REFERENCES
Showing 1-23 of 23 references · Page 1 of 1
CITED BY
Showing 1-71 of 71 citing papers · Page 1 of 1