EconPapers    
Economics at your fingertips  
 

Decreasing fractal dimensions as a strategy for oceanic wildlife conservation: Application to species with large migration patterns

J.C. Flores

Ecological Modelling, 2018, vol. 384, issue C, 30-33

Abstract: Wildlife dispersion patterns are responses of populations confronting variable environmental conditions. Additionally, industry depredation in oceans develops spatial patterns to optimize wildlife capture. Soft scaling conditions between protected and exploited marine zones define operative fractional dimensions for industry and wildlife. When reduction of the fractional dimension of industry ship trajectories is suitably established, the chances for wildlife to survive are increased. Accordingly, a protection strategy is proposed focusing on trajectory patterns rather than uniform areas. As a specific case, narwhals (Monodon monoceros) in the Arctic are considered. This approach best suits species with large-scale migratory patterns. Parameters are evaluated using current oceanic data.

Keywords: Wildlife protection; Fractional dimension; Power-law scaling; Nonlinear systems; Factory-ship trajectories (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S030438001830200X
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:384:y:2018:i:c:p:30-33

DOI: 10.1016/j.ecolmodel.2018.06.001

Access Statistics for this article

Ecological Modelling is currently edited by Brian D. Fath

More articles in Ecological Modelling from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:ecomod:v:384:y:2018:i:c:p:30-33