text-only page produced automatically by Usablenet Assistive Skip all navigation and go to page content Skip top navigation and go to directorate navigation Skip top navigation and go to page navigation
National Science Foundation
Awards
design element
Search Awards
Recent Awards
Presidential and Honorary Awards
About Awards
Grant Policy Manual
Grant General Conditions
Cooperative Agreement Conditions
Special Conditions
Federal Demonstration Partnership
Policy Office Website



Award Abstract #1325452

Coastal SEES (Track 1): Novel Approaches to Understanding Human Use Patterns and Mobility for Coastal Natural Resources Management

NSF Org: OCE
Division Of Ocean Sciences
divider line
Initial Amendment Date: August 7, 2013
divider line
Latest Amendment Date: August 7, 2013
divider line
Award Number: 1325452
divider line
Award Instrument: Standard Grant
divider line
Program Manager: Michael Sieracki
OCE Division Of Ocean Sciences
GEO Directorate For Geosciences
divider line
Start Date: October 1, 2013
divider line
End Date: September 30, 2016 (Estimated)
divider line
Awarded Amount to Date: $550,641.00
divider line
Investigator(s): Steven Murawski smurawski@usf.edu (Principal Investigator)
James Sanchirico (Co-Principal Investigator)
divider line
Sponsor: University of South Florida
3702 Spectrum Blvd.
Tampa, FL 33612-9446 (813)974-2897
divider line
NSF Program(s): SEES Coastal
divider line
Program Reference Code(s):
divider line
Program Element Code(s): 8088

ABSTRACT

This project will address a critical gap in fisheries science and management by developing better models of fisher location choice in response to management measures such as closed areas and individual fishing quotas. Coastal and marine spatial planning and management is increasingly viewed as the basis with which to allocate access to resources and reduce negative interactions among sectors that are not compatible with long term ecosystem sustainability. Yet, ecological-behavioral models that might assist managers in addressing these needs are rudimentary. This project will evaluate the utility of new classes of behavioral models and entropy statistics, originally developed from terrestrial studies of human activity patterns enabled by advanced technologies for tracking human movements. Assessing traditional methods of predicting human use patterns, introducing and testing new methods, and empirically testing for changes in use patterns due to regulations and ecological conditions are critical for formulating new predictive modeling tools supporting coastal sustainability. While this project focuses on fisheries, the methods will have broader applicability for coastal sustainability, e.g. shipping, coastal wind power, military preparedness, oil production, and other sectors. The project will build upon collaborative networks and partnerships among scientists, academia, government agencies, and others involved in coastal resource management.

A unique dataset that includes millions of observations of individual choices of where, when, and what to fish for under a number of regulatory regimes, will be used. Past approaches of modeling and predicting human use patterns (random utility and logit modeling) have, for the most part, utilized data recorded at coarse spatial resolutions (e.g., National Marine Fisheries Service statistical areas) and timespans. In addition to assessing the implications of underlying key assumptions of the past approaches (e.g., spatial aggregation), new methods (entropy models) will be tested for modeling and predicting human-use patterns that have been developed in other research fields that also have high frequency location data (e.g., cellphone usage). Vessel monitoring system (VMS) data that are updated every 60 minutes by satellite provide high fidelity observations of the actual locations of fishing across years. Location choices are determined by ecological conditions (e.g., fish aggregations) and by the incentives created by the regulatory institutions. For example, fishermen engaging in a race to catch fish will likely behave differently than those that have more secure rights to the fish at the beginning of the fishing season as is the case in catch share fisheries. Due to the long time series of VMS data and the changing regulatory institutions in the management of the Gulf of Mexico fisheries during the period of analysis, observational research will estimate how spatial decision making has changed in response to changing regulations.

This project is supported under NSF's Coastal SEES (Science, Engineering and Education for Sustainability) program.

 

Please report errors in award information by writing to: awardsearch@nsf.gov.

 

 

Print this page
Back to Top of page
  FUNDING   AWARDS   DISCOVERIES   NEWS   PUBLICATIONS   STATISTICS   ABOUT NSF   FASTLANE  
Research.gov  |  USA.gov  |  National Science Board  |  Recovery Act  |  Budget and Performance  |  Annual Financial Report
Web Policies and Important Links  |  Privacy  |  FOIA  |  NO FEAR Act  |  Inspector General  |  Webmaster Contact  |  Site Map
National Science Foundation Logo
The National Science Foundation, 4201 Wilson Boulevard, Arlington, Virginia 22230, USA
Tel: (703) 292-5111, FIRS: (800) 877-8339 | TDD: (800) 281-8749
  Text Only Version