Assessing the value of monitoring to biological inference and expected management performance for a European goose population. Issue 1 (29th October 2022)

• Record Type: Journal Article
• Authors: Johnson, Fred A.; Madsen, Jesper; Clausen, Kevin K.; Frederiksen, Morten; Jensen, Gitte H.
• Is Part Of: Journal of applied ecology. Volume 60:Issue 1(2023)
• Page Start: 132
• Page End: 145
• Publication Date: 2022-10-29
• Subjects: adaptive management -- harvest -- integrated population model -- monitoring -- optimization -- pink‐footed geese -- stochastic dynamic programming -- value of information; Agriculture -- Periodicals; Biology, Economic -- Periodicals; Agricultural ecology -- Periodicals; Applied ecology -- Periodicals; 577
• DOI: 10.1111/1365-2664.14313
• Languages: English
• ISSNs: 0021-8901

Abstract

Abstract: Informed conservation and management of wildlife require sufficient monitoring to understand population dynamics and to direct conservation actions. Because resources available for monitoring are limited, conservation practitioners must strive to make monitoring as cost‐effective as possible. Our focus was on assessing the value of monitoring to the adaptive harvest management (AHM) programme for pink‐footed geese Anser brachyrhynchus . We conducted a retrospective analysis to assess the costs and benefits of a capture–mark–resight (CMR) programme, a productivity survey and biannual population censuses. Using all available data, we fit an integrated population model (IPM) and assumed that inference derived from it represented the benchmark against which reduced monitoring was to be judged. We then fit IPMs to reduced sets of monitoring data and compared their estimates of demographic parameters and expected management performance against the benchmark IPM. Costs and the precision and accuracy of key demographic parameters decreased with the elimination of monitoring data. Eliminating the CMR programme, while maintaining other monitoring instruments, resulted in the greatest cost savings, usually with small effects on inferential reliability. Productivity surveys were also expensive and some reduction in survey effort may be warranted. The biannual censuses were inexpensive and generally increased inferential reliability. The expected performance of AHM strategies was surprisingly robust to a loss of monitoring data. We attribute this result to explicit consideration of parametric uncertainty in harvest‐strategy optimization and the fact that a broad range of population sizes is acceptable to stakeholders. Synthesis and applications . Our study suggests that existing or potential monitoring instruments for wildlife populations should be scrutinized as to their cost‐effectiveness for improving biological inference and management performance. Using Svalbard pink‐footed geese as a case study, we show that the loss of some existing monitoring instruments may not be as adverse as commonly assumed if data are jointly analysed in an IPM. Finally, regardless of the monitoring data available, we suggest that conservation strategies that explicitly account for uncertainty in demography are more likely to be successful than those that do not. Abstract : Our study suggests that existing or potential monitoring instruments for wildlife populations should be scrutinized as to their cost‐effectiveness for improving biological inference and management performance. Using Svalbard pink‐footed geese as a case study, we show that the loss of some existing monitoring instruments may not be as adverse as commonly assumed if data are jointly analysed in an integrated population model. Finally, regardless of the monitoring data available, we suggest that conservation strategies that explicitly account for uncertainty in demography are more likely to be successful than those that do not.