Evaluation of harvest and information needs for North American sea ducks

• Published in: PloS one 2017-04, Vol.12 (4), p.e0175411-e0175411
• Main Authors: Koneff, Mark D, Zimmerman, Guthrie S, Dwyer, Chris P, Fleming, Kathleen K, Padding, Paul I, Devers, Patrick K, Johnson, Fred A, Runge, Michael C, Roberts, Anthony J
• Format: Article
• Language: English
• Subjects: Abundance; Aerial surveys; Age; Algorithms; Analysis; Animals; Aquatic birds; Bayesian analysis; Biology and Life Sciences; Bird migration; Birds; Breeding; Canada; Census; Coastal environments; Computer programs; Conservation; Conservation of Natural Resources - methods; Constrictions; Decision making; Ducks; Ducks - classification; Ducks - physiology; Ecological research; Ecology; Economic importance; Ecosystem; Emigration; Endangered & extinct species; Environmental aspects; Estimates; Evaluation; Evolution; Expert Testimony; Female; Fertility - physiology; Geography; Humans; Hunting; Information management; Male; Methods; Monte Carlo Method; Oceans and Seas; People and Places; Physical Sciences; Population biology; Population decline; Population Density; Population Dynamics; Population growth; Population status; Population studies; Populations; Protection and preservation; Regression analysis; Research Personnel - statistics & numerical data; Resource management; Seasons; Simulation; Software; Survival; Sustainability; Telemetry; Threatened species; Uncertainty; United States; Waterfowl; Wildlife; Wildlife conservation; Wildlife management; Winter
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0175411

Wildlife managers routinely seek to establish sustainable limits of sport harvest or other regulated forms of take while confronted with considerable uncertainty. A growing body of ecological research focuses on methods to describe and account for uncertainty in management decision-making and to prioritize research and monitoring investments to reduce the most influential uncertainties. We used simulation methods incorporating measures of demographic uncertainty to evaluate risk of overharvest and prioritize information needs for North American sea ducks (Tribe Mergini). Sea ducks are popular game birds in North America, yet they are poorly monitored and their population dynamics are poorly understood relative to other North American waterfowl. There have been few attempts to assess the sustainability of harvest of North American sea ducks, and no formal harvest strategy exists in the U.S. or Canada to guide management. The popularity of sea duck hunting, extended hunting opportunity for some populations (i.e., special seasons and/or bag limits), and population declines have led to concern about potential overharvest. We used Monte Carlo simulation to contrast estimates of allowable harvest and observed harvest and assess risk of overharvest for 7 populations of North American sea ducks: the American subspecies of common eider (Somateria mollissima dresseri), eastern and western populations of black scoter (Melanitta americana) and surf scoter (M. perspicillata), and continental populations of white-winged scoter (M. fusca) and long-tailed duck (Clangula hyemalis). We combined information from empirical studies and the opinions of experts through formal elicitation to create probability distributions reflecting uncertainty in the individual demographic parameters used in this assessment. Estimates of maximum growth (rmax), and therefore of allowable harvest, were highly uncertain for all populations. Long-tailed duck and American common eider appeared to be at high risk of overharvest (i.e., observed harvest < allowable harvest in 5-7% and 19-26% of simulations, respectively depending on the functional form of density dependence), whereas the other populations appeared to be at moderate risk to low risk (observed harvest < allowable harvest in 22-68% of simulations, again conditional on the form of density dependence). We also evaluated the sensitivity of the difference between allowable and observed harvest estimates to uncertainty in individual demograph