Risk of human exposure to vector-borne zoonotic pathogens is a function of the abundance and infection prevalence of vectors. We assessed the determinants of Lyme-disease risk (density and Borrelia burgdorferi-infection prevalence of nymphal Ixodes scapularis ticks) over 13 y on several field plots within eastern deciduous forests in the epicenter of US Lyme disease (Dutchess County, New York). We used a model comparison approach to simultaneously test the importance of ambient growing-season temperature, precipitation, two indices of deer (Odocoileus virginianus) abundance, and densities of white-footed mice (Peromyscus leucopus), eastern chipmunks (Tamias striatus), and acorns ( Quercus spp.), in both simple and multiple regression models, in predicting entomological risk. Indices of deer abundance had no predictive power, and precipitation in the current year and temperature in the prior year had only weak effects on entomological risk. The strongest predictors of a current year's risk were the prior year's abundance of mice and chipmunks and abundance of acorns 2 y previously. In no case did inclusion of deer or climate variables improve the predictive power of models based on rodents, acorns, or both. We conclude that interannual variation in entomological risk of exposure to Lyme disease is correlated positively with prior abundance of key hosts for the immature stages of the tick vector and with critical food resources for those hosts.

Catch inequality occurs when a small number of anglers catch a disproportionally large number of fish. Catch inequality is a common occurrence in recreational fisheries, but long-term changes in catch inequality are rarely measured. We evaluated catch inequality in archived long-term complete-trip creel census records from a trout stream in southeastern New York. These records document all fish caught for each angler over a 20-year period. Catch inequality, as measured by the Gini coefficient, increased significantly during the study period. Catch per unit effort and an inequality-standardized measure of catch per unit effort declined significantly throughout the study. We tested the hypothesis that between-angler inequality increases as catch per unit effort declines. There was no change in between-angler inequality but between-trip inequality increased substantially. Trip-to-trip variability, not between-angler variability, accounts for increased catch inequality when catch per unit effort declines. Catch inequality increases as catch per unit effort declines, but less successful anglers are not disproportionately affected.

No abstract

Harvest inequality, a situation in which most of the fish are harvested by a disproportionately small number of anglers, is a characteristic of most recreational fisheries. Harvest inequality develops when a few anglers harvest a very large number of fish or when many anglers harvest few fish. Identifying the cause of harvest inequality is critical to understanding the potential for management to reduce the inequality. Management efforts aimed at reducing the top anglers’ take will have only a modest impact if the harvest inequality is actually caused by many anglers harvesting no fish. We measured harvest inequality in 20 years of creel census data from a trout stream in southeastern New York. We calculated Lorenz curve asymmetry coefficients (S) to test whether harvest inequality was attributable to small harvests by many anglers or large harvests by a few anglers. Harvest inequality in the fishery was consistently high and the S‐value was always less than 1.0, indicating that harvest inequality was caused by many anglers harvesting no fish rather than by few anglers harvesting many fish. This influence becomes stronger with increased harvest. We conclude that management is unlikely to influence the magnitudes of harvest inequality in recreational fisheries because regulations do not target the principal cause of harvest inequality.Received May 10, 2012; accepted October 29, 2012