Abstract
Empirical migration models deliver migration patterns using collected data in multiobserve-record sessions of the migratory species' behavior. Such modeling is time-consuming, costly, and is not fit for investigation of habitat migration. As an alternative, use of collected data in one-time-test-record session reduces the observation time and cost significantly. However, new methodologies are needed to deliver the migration patterns. In this chapter, we introduce such methodology, Expansion-CONtraction (ECON), which is a hybrid clustering technique following a two-phase process - expansion and contraction. ECON (a) clusters the data set once using the coordinates of the point of capture and the second time using DNA markers and (b) maps the tightly grid-dense (TGD) DNA clusters over the TGD location clusters producing one trivial, and seven nontrivial migration patterns along with their features.
| Original language | English |
|---|---|
| Title of host publication | Emerging Trends in Applications and Infrastructures for Computational Biology, Bioinformatics, and Systems Biology |
| Subtitle of host publication | Systems and Applications |
| Publisher | Elsevier Inc. |
| Pages | 157-169 |
| Number of pages | 13 |
| ISBN (Electronic) | 9780128042595 |
| ISBN (Print) | 9780128042038 |
| DOIs | |
| State | Published - Mar 22 2016 |
Scopus Subject Areas
- General Computer Science
Keywords
- Ecosystem
- Florida scrub habitat
- Habitat migration modeling
- Hybrid clustering
- Migration modeling
- Tightly grid-dense clustering