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This volume contains in part papers presented at the Symposium on Monitoring Bird Population Trends by Point Counts, which was held November 6-7, 1991, in Beltsville, Md., in response to the need for standardization of methods to monitor bird populations by point counts. Data from various investigators working under a wide variety of conditions are presented, and various aspects of point count methodology are examined. Point counts of birds are the most widely used quantitative method and involve an observer recording birds from a single point for a standardized time period. Statistical aspects of sampling and analysis were discussed and applied to the objectives of point counts. Symposium participants agreed upon standards of point counts that should have wide applicability to a variety of habitats and terrain.

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Abstract. We used vegetation data collected in areas before they were burned by the 2500 ha Quartz fire in southern Oregon and the 50 600 ha Big Bar complex in northern California to evaluate the ability of vegetation and topographic characteristics to predict patterns of fire severity. Fire severity was characterized as high, moderate, or low based on crown scorch and consumption, and changes in soil structure. In both fires, vegetation plots with southern aspects were more likely to burn with high severity than plots with eastern, northern, or western aspects. This was the only consistent predictor across both fires. In the Quartz fire, we found that plots at higher elevations and with larger diameter trees were more likely to burn with low or moderate severity. These correlations may have been influenced in part by the effects of unmeasured weather conditions. We found few strong correlates in the Big Bar complex, owing in part to the fact that most (75%) of our plots were in the low-severity category, providing relatively little variation. These results, in combination with previous studies of fire severity in the Klamath-Siskiyou region, suggest that areas with southern aspects tend to burn with greater severity than those of other aspects, areas with large trees burn less severely than those with smaller trees, and that correlates of fire severity vary extensively among fires.

Argentina, in the vicinity of Bariloche. Over a 60-km distance, the 12 sites ranged from grassland at lower elevations to upland climax Nothofagus forests of the eastern Andes. Here, I correlated bird abundance and diversities with various vegetation measures. Using all sites, bird diversities and abundances were positively correlated with various foliage measures. When grasslands were excluded, however, an inverse relationship was found: birds were more diverse and abundant in the lower stature shrub communities than in complex forests. Multiple regression analyses of this apparently paradoxical situation indicated that certain species of plants probably had important effects on community structure.

Reliable estimates of trends in population size are critical to effective management of landbirds. We propose a standard for considering that landbird populations are adequately monitored: 80% power to detect a 50% decline occurring within 20 years, using a 2-tailed test and a significance level of 0.10, and incorporating effects of potential bias. Our standard also requires that at least two-thirds of the target region be covered by the monitoring program. We recommend that the standard be achieved for species' entire ranges or for any area one-third the size of the temperate portions of Canada and the United States, whichever is smaller. We applied our approach to North American Breeding Bird Survey (BBS) data. At present, potential annual bias for the BBS is estimated at ±0.008. Further, the BBS achieves the monitoring standard for only about 42% of landbirds for which the BBS is considered the most effective monitoring approach. Achieving the proposed monitoring target for ≥80% of these species would require increasing the number of BBS-or similar survey-routes by several-fold, a goal that probably is impractical. We suggest several methods for reducing potential bias and argue that if our methods are implemented, potential bias would fall to ±0.003. The required number of BBS or similar routes would then be 5,106, about 40% more than in the current BBS program. Most of the needed increases are in 15 states or provinces. Developing a comprehensive landbird monitoring program will require increased support for coordination of the BBS (currently 2 people) and new programs for species that are poorly covered at present. Our results provide a quantitative goal for long-term landbird monitoring and identify the sample sizes needed, within each state and province, to achieve the monitoring goal for most of the roughly 300 landbird species that are well suited to monitoring with the BBS and similar surveys. JOURNAL OF WILDLIFE MANAGEMENT 68(3):611-626

BackgroundAvian influenza virus (AIV) is an important public health issue because pandemic influenza viruses in people have contained genes from viruses that infect birds. The H5 and H7 AIV subtypes have periodically mutated from low pathogenicity to high pathogenicity form. Analysis of the geographic distribution of AIV can identify areas where reassortment events might occur and how high pathogenicity influenza might travel if it enters wild bird populations in the US. Modelling the number of AIV cases is important because the rate of co-infection with multiple AIV subtypes increases with the number of cases and co-infection is the source of reassortment events that give rise to new strains of influenza, which occurred before the 1968 pandemic. Aquatic birds in the orders Anseriformes and Charadriiformes have been recognized as reservoirs of AIV since the 1970s. However, little is known about influenza prevalence in terrestrial birds in the order Passeriformes. Since passerines share the same habitat as poultry, they may be more effective transmitters of the disease to humans than aquatic birds. We analyze 152 passerine species including the American Robin (Turdus migratorius) and Swainson's Thrush (Catharus ustulatus).MethodsWe formulate a regression model to predict AIV cases throughout the US at the county scale as a function of 12 environmental variables, sampling effort, and proximity to other counties with influenza outbreaks. Our analysis did not distinguish between types of influenza, including low or highly pathogenic forms.ResultsAnalysis of 13,046 cloacal samples collected from 225 bird species in 41 US states between 2005 and 2008 indicates that the average prevalence of influenza in passerines is greater than the prevalence in eight other avian orders. Our regression model identifies the Great Plains and the Pacific Northwest as high-risk areas for AIV. Highly significant predictors of AIV include the amount of harvested cropland and the first day of the year when a county is snow free.ConclusionsAlthough the prevalence of influenza in waterfowl has long been appreciated, we show that 22 species of song birds and perching birds (order Passeriformes) are influenza reservoirs in the contiguous US.

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