A comparison of vector population indices for forecasting barley yellow dwarf virus in autumn sown cereal crops

Two approaches based on the concept of a vector population index are considered as possible deterministic elements for an empirical forecast of barley yellow dwarf virus (BYDV) in autumn sown cereals. The first, an aerial vector index, is a further elaboration of the infectivity index proposed by Plumb, Lennon & Gutteridge (1981), which assumes that virus damage is a function of the number of infective migrant alatae of the two main aphid vectors, Rhopalosiphum padi L. and Sitobion avenae F., integrated over time from crop planting or emergence. The new formulation, however, excludes holocyclic alate morphs (i.e. males and gynoparae) of the former species, which, although generally abundant in autumn, are nevertheless perceived as relatively unimportant virus vectors since they colonise only the alternative woody host, Prunus padus (the bird-cherry tree). The second approach, a crop vector index, is a more fundamental departure which argues that field populations of viruliferous aphids, both alatae and apterae, which have already colonised cereals, may be a better criterion of potential virus spread than the density of aerial migrant vectors. This index retains a similar integral form, but evaluates crop exposure to BYDV as accumulated infectious aphid-days. A method is described whereby this function can be derived from irregular or infrequent aphid samples in the crop. Both methods, unlike Plumb's (1976) original concept, produced indices which were significantly related to subsequent virus infection and yield loss in winter barley at Long Ashton (S.W. England, UK), 1978–1986. The best models were obtained with the crop vector index, fitted to observed virus infection by generalised linear regression using a complementary log-log link function, or to observed yield loss by simple linear regression using a log transformation of yield (r = 0.84 in each case; compared with r-values > 0.65 for the aerial vector index, and > 0.35 for Plumb's (1976) index). However, the residual errors and hence confidence limits of these fitted regressions were too large for predicting damage that was significantly less than a reasonable economic damage threshold for BYDV control. Analyses of the separate components of each index showed a good general relationship between aphid infectivity and the severity of crop infection, confirming the epidemiological importance of this factor. The functional expressions of aphid density, however, were not significant. This evident weakness in the models, and alternative approaches to BYDV forecasting are discussed.     

Factors Influencing Reporting and Harvest Probabilities in North American Geese

ABSTRACT We assessed variation in reporting probabilities of standard bands among species, populations, harvest locations, and size classes of North American geese to enable estimation of unbiased harvest probabilities. We included reward (US$10, $20, $30, $50, or $100) and control ($0) banded geese from 16 recognized goose populations of 4 species: Canada (Branta canadensis), cackling (B. hutchinsii), Ross's (Chen rossii), and snow geese (C. caerulescens). We incorporated spatially explicit direct recoveries and live recaptures into a multinomial model to estimate reporting, harvest, and band-retention probabilities. We compared various models for estimating harvest probabilities at country (United States vs. Canada), flyway (5 administrative regions), and harvest area (i.e., flyways divided into northern and southern sections) scales. Mean reporting probability of standard bands was 0.73 (95% CI = 0.69–0.77). Point estimates of reporting probabilities for goose populations or spatial units varied from 0.52 to 0.93, but confidence intervals for individual estimates overlapped and model selection indicated that models with species, population, or spatial effects were less parsimonious than those without these effects. Our estimates were similar to recently reported estimates for mallards (Anas platyrhynchos). We provide current harvest probability estimates for these populations using our direct measures of reporting probability, improving the accuracy of previous estimates obtained from recovery probabilities alone. Goose managers and researchers throughout North America can use our reporting probabilities to correct recovery probabilities estimated from standard banding operations for deriving spatially explicit harvest probabilities.     

Korean Shamans and the Spirits of Capitalism

Recent studies have taught us that "religion" is not a fixed category but an instrument of popular consciousness. While the studies' subjects have often been victims of colonialism and capitalist exploitation, cultural production through magical means need not be restricted to a society's most oppressed elements. Counter to the expectations of Max Weber, for whom capitalism marched to the drumbeat of "rationalization," many of the clients who patronize the shaman shrines of Seoul, Republic of Korea, are engaged in high-risk petty-capitalist enterprises. Shamans, clients, and spirits address the seemingly arbitrary fluctuations of good and bad fortune that can bring sudden wealth or ruin, and offer wry commentary upon what their world has become.     

Monitoring in the Context of Structured Decision-Making and Adaptive Management

Abstract: In a natural resource management setting, monitoring is a crucial component of an informed process for making decisions, and monitoring design should be driven by the decision context and associated uncertainties. Monitoring itself can play ≥3 roles. First, it is important for state-dependent decision-making, as when managers need to know the system state before deciding on the appropriate course of action during the ensuing management cycle. Second, monitoring is critical for evaluating the effectiveness of management actions relative to objectives. Third, in an adaptive management setting, monitoring provides the feedback loop for learning about the system; learning is sought not for its own sake but primarily to better achieve management objectives. In this case, monitoring should be designed to reduce the critical uncertainties in models of the managed system. The United States Geological Survey and United States Fish and Wildlife Service are conducting a large-scale management experiment on 23 National Wildlife Refuges across the Northeast and Midwest Regions. The primary management objective is to provide habitat for migratory waterbirds, particularly during migration, using water-level manipulations in managed wetlands. Key uncertainties are related to the potential trade-offs created by management for a specific waterbird guild (e.g., migratory shorebirds) and the response of waterbirds, plant communities, and invertebrates to specific experimental hydroperiods. We reviewed the monitoring program associated with this study, and the ways that specific observations fill ≥1 of the roles identified above. We used observations from our monitoring to improve state-dependent decisions to control undesired plants, to evaluate management performance relative to shallow-water habitat objectives, and to evaluate potential trade-offs between waterfowl and shorebird habitat management. With limited staff and budgets, management agencies need efficient monitoring programs that are used for decision-making, not comprehensive studies that elucidate all manner of ecological relationships.     

A Hierarchical Model for Estimating Change in American Woodcock Populations

Abstract The Singing-Ground Survey (SGS) is a primary source of information on population change for American woodcock (Scolopax minor). We analyzed the SGS using a hierarchical log-linear model and compared the estimates of change and annual indices of abundance to a route regression analysis of SGS data. We also grouped SGS routes into Bird Conservation Regions (BCRs) and estimated population change and annual indices using BCRs within states and provinces as strata. Based on the hierarchical model–based estimates, we concluded that woodcock populations were declining in North America between 1968 and 2006 (trend = −0.9%/yr, 95% credible interval: −1.2, −0.5). Singing-Ground Survey results are generally similar between analytical approaches, but the hierarchical model has several important advantages over the route regression. Hierarchical models better accommodate changes in survey efficiency over time and space by treating strata, years, and observers as random effects in the context of a log-linear model, providing trend estimates that are derived directly from the annual indices. We also conducted a hierarchical model analysis of woodcock data from the Christmas Bird Count and the North American Breeding Bird Survey. All surveys showed general consistency in patterns of population change, but the SGS had the shortest credible intervals. We suggest that population management and conservation planning for woodcock involving interpretation of the SGS use estimates provided by the hierarchical model.