Matching observations and reality: using simulation models to improve monitoring under uncertainty in the Serengeti. Issue 2 (4th February 2013)
- Record Type:
- Journal Article
- Title:
- Matching observations and reality: using simulation models to improve monitoring under uncertainty in the Serengeti. Issue 2 (4th February 2013)
- Main Title:
- Matching observations and reality: using simulation models to improve monitoring under uncertainty in the Serengeti
- Authors:
- Nuno, Ana
Bunnefeld, Nils
Milner‐Gulland, E. J.
Stephens, Phil - Abstract:
- <abstract abstract-type="main" id="jpe12051-abs-0001"> <title>Summary</title> <p> <list id="jpe12051-list-0001" list-type="order"> <list-item> <p>Planning for conservation success requires identifying effective and efficient monitoring strategies but multiple types of uncertainty affect the accuracy and precision of wildlife abundance estimates. Observation uncertainty, a consequence of sampling effort and design as well as the process of observation, is still understudied, with little attention given to the multiple potential sources of error involved. To establish error minimization priorities and maximize monitoring efficiency, the direction and magnitude of multiple sources of uncertainty must be considered.</p> </list-item> <list-item> <p>Using monitoring of two contrasting ungulate species in the Serengeti ecosystem as a case study, we developed a 'virtual ecologist' framework within which we carried out simulated tests of different monitoring strategies for different types of species. We investigated which components of monitoring should be prioritized to increase survey accuracy and precision and explored the robustness of population estimates under different budgetary scenarios.</p> </list-item> <list-item> <p>The relative importance of each process affecting precision and accuracy varied according to the survey technique and biological characteristics of the species. While survey precision was mainly affected by population characteristics and sampling effort, the<abstract abstract-type="main" id="jpe12051-abs-0001"> <title>Summary</title> <p> <list id="jpe12051-list-0001" list-type="order"> <list-item> <p>Planning for conservation success requires identifying effective and efficient monitoring strategies but multiple types of uncertainty affect the accuracy and precision of wildlife abundance estimates. Observation uncertainty, a consequence of sampling effort and design as well as the process of observation, is still understudied, with little attention given to the multiple potential sources of error involved. To establish error minimization priorities and maximize monitoring efficiency, the direction and magnitude of multiple sources of uncertainty must be considered.</p> </list-item> <list-item> <p>Using monitoring of two contrasting ungulate species in the Serengeti ecosystem as a case study, we developed a 'virtual ecologist' framework within which we carried out simulated tests of different monitoring strategies for different types of species. We investigated which components of monitoring should be prioritized to increase survey accuracy and precision and explored the robustness of population estimates under different budgetary scenarios.</p> </list-item> <list-item> <p>The relative importance of each process affecting precision and accuracy varied according to the survey technique and biological characteristics of the species. While survey precision was mainly affected by population characteristics and sampling effort, the accuracy of the survey was greatly affected by observer effects, such as juvenile and herd detectability.</p> </list-item> <list-item> <p> <italic>Synthesis and applications</italic>. Monitoring efficiency is of the utmost importance for conservation, especially in the context of limited budgets and other priorities. We provide insights into the likely effect of different types of observation and process error on population estimates for savanna ungulates, and more generally present a framework for evaluating monitoring programmes in a virtual environment. In highly aggregated species, the main focus should be on survey precision; sampling effort should be defined according to wildlife spatial distribution. For random or slightly aggregated species, accuracy is the key factor; this is most sensitive to observer effects which should be minimized by training and calibration by observer.</p> </list-item> </list> </p> </abstract> … (more)
- Is Part Of:
- Journal of applied ecology. Volume 50:Issue 2(2013:Apr.)
- Journal:
- Journal of applied ecology
- Issue:
- Volume 50:Issue 2(2013:Apr.)
- Issue Display:
- Volume 50, Issue 2 (2013)
- Year:
- 2013
- Volume:
- 50
- Issue:
- 2
- Issue Sort Value:
- 2013-0050-0002-0000
- Page Start:
- 488
- Page End:
- 498
- Publication Date:
- 2013-02-04
- Subjects:
- Agriculture -- Periodicals
Biology, Economic -- Periodicals
Agricultural ecology -- Periodicals
Applied ecology -- Periodicals
577 - Journal URLs:
- http://besjournals.onlinelibrary.wiley.com/hub/journal/10.1111/(ISSN)1365-2664/ ↗
http://onlinelibrary.wiley.com/ ↗
http://www.blackwell-synergy.com/member/institutions/issuelist.asp?journal=jpe ↗ - DOI:
- 10.1111/1365-2664.12051 ↗
- Languages:
- English
- ISSNs:
- 0021-8901
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4942.500000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 4146.xml