Summary Habitat destruction and fragmentation have led to precipitous declines in a number of species of concern. For these species, traditional models that group individuals into age or stage cohorts may not accurately capture the stochasticity associated with small populations. Additionally, traditional models do not explicitly incorporate landscape‐level structure, which becomes increasingly important at small population sizes. Thus, for declining species, spatially explicit individual‐based models (SEIBM) can be used to understand both population demography and the impacts of habitat destruction, and to guide management practices to increase the chances of species survival. To gauge the impacts of changes in habitat and also demographic rates on a US endangered species, we constructed an SEIBM for the Cape Sable seaside sparrow (Ammodramus maritimus mirabilis Howell) of the South Florida Everglades. The model simulates temporal and spatial dynamics of individual sparrows using local GIS‐based topography, vegetation and hydrology along with behavioural and demographic rates derived from field studies. When adult mortality and, to a lesser extent, juvenile mortality were increased in model simulations, there was an increase in extinction risk and a decrease in population size, whereas changes in number of clutches or female mating range had little impact. In contrast to the effects of simulating changes in mortality rates, simulated landscape‐level changes (increasing water levels or decreasing habitat availability) were associated with dramatic population declines and increases in extinction risk. The sparrow appears to be particularly sensitive to the loss of higher‐elevation breeding habitat. These results highlight the importance of proper water‐ and land‐use management in assuring the species’ survival. Synthesis and applications. Although changes in demographic rates affect population growth and are often the focus of conservation efforts, changes in habitat structure can also dramatically alter population viability. When both landscape‐level and demographic data are available, spatially explicit models are particularly advantageous. Not only do they allow researchers and resource managers to prioritize areas for habitat restoration and species management, but they can also be used to help focus future research efforts.

Global climate cycles have been shown to influence demographic rates of birds at local scales, but few analyses have examined these effects at larger, regional scales. We examined the relationship of broad-scale climate indices to apparent survival of a subspecies of Swainson's Thrush (Catharus ustulatus) across a large portion of the subspecies' breeding range along the Pacific slope of North America. We developed 69 a priori Cormack-Jolly-Seber models to examine effects of El Nino-Southern Oscillation (ENSO), North Atlantic Oscillation, Pacific Decadal Oscillation, latitude, region, and residency status on survival. The most parsimonious model included an ENSO effect, a regional effect, and a residency effect on survival. The ENSO had a positive effect on survival probability, and the effect was consistent across the entire portion of the breeding range examined. Additional analyses of a posteriori models provided strong support for an effect of dry-season precipitation along the spring migration route in western Mexico on annual survival. Our results suggest that survival of this Neotropical migrant is strongly influenced by ENSO-related weather changes during one or more periods of its annual cycle. Because many western Neotropical migrants migrate through and winter in the same general geographic area as Swainson's Thrushes, it is possible that other such species are similarly influenced by ENSO. If, as some climate models predict, annual variation in ENSO increases, Swainson's Thrush may suffer greater variation in annual survival. Directly associating climate with key demographic parameters provides a powerful approach to predicting a species' response to climate change. Received 6 February 2012, accepted 4 July 2012.

Background: Avian 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).Methods: We 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.Results: Analysis 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.Conclusions: Although 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.

Mist-netting and banding networks can complement count-based monitoring and provide focus for research and conservation of migratory landbirds. Here we describe two banding networks, one that operates during the breeding season, the Monitoring Avian Productivity and Survivorship (MAPS) pro- gram, and one that operates during the overwintering period, the Monitoreo de Sobrevivencia Invernal (MoSI) program. We provide an example, using data for Swainson's Thrush (Catharus ustulatus), of how data from these networks can be used to infer spatial patterns in adult apparent survival rates (sur- vival) and understand linkages between breeding and wintering populations. We estimated survival of Swainson's Thrush from MAPS data at the scale of Bird Conservation Regions (BCRs). Survival was highest in the Northern Rockies and Atlantic Northern Forest BCRs and lowest in the Northwestern Interior Forest and Boreal Taiga Plains BCRs. We used wing chord to study migratory connectivity. Spatial patterning in wing chord suggested links between northerly portions of the breeding range and northern Rocky Mountains and birds overwintering farthest south. This pattern is consistent with the literature and illustrates the utility of using a simple metric measured at banding stations to understand migratory connectivity. Although our example analysis for Swainson's Thrush highlights the utility of these banding programs for providing focus for research and conservation, it also highlights the need for growth of these programs to fi ll geographic gaps in the distribution of banding stations and to target habitats and species of high conservation priority.

In this paper we argue that effective management of landbirds should be based on assessing and monitoring their vital rates (primary demographic parameters) as well as population trends. This is because environmental stressors and management actions affect vital rates directly and usually without time lags, and because monitoring vital rates provides a) information on the stage of the life cycle where population change is being effected, b) a good measure of the health and viability of populations, and c) a clear index of habitat quality. We suggest that modeling lambda (�� , the rate of change in population size) as a function of vital rates provides useful information on potential responses of populations to management actions, but because of covariation among vital rates and density dependence, the predicted responses may not occur. We suggest that modeling spatial variation in vital rates as a function of spatial variation in lambda provides added insight into the proximate demographic “cause(s)” of population change and permits identification of “deficient” vital rates. We illustrate this at two spatial scales with analyses of BBS and MAPS data on Gray Catbird and MAPS data on five other species. We then suggest that the formulation of effective avian management actions should be based on modeling vital rates as functions of habitat characteristics and, because of substantial amounts of annual variation in vital rates, as functions of weather and climate variables. We illustrate these concepts with threshold relationships between productivity and mean forest/woodland patch size in four forest-inhabiting species; relationships between precipitation and annual productivity indices for two landbird species in Texas; and relationships between reproductive indices in Pacific Northwest landbirds and both the El Nino/Southern Oscillation and the North Atlantic Oscillation. These latter results indicate that annual variation in the productivity of Neotropicalwintering birds may be driven more by events and conditions on their wintering grounds and migration routes than on their breeding grounds. Finally, we suggest that, because avian management should be based on vital rates as well as population trends, effectiveness monitoring must include the monitoring of the targeted vital rates along with monitoring the appropriate population trends.

To model the effects of global climate phenomena on avian population dynamics, we must identify and quantify the spatial and temporal relationships between climate, weather and bird populations. Previous studies show that in Europe, the North Atlantic Oscillation (NAO) influences winter and spring weather that in turn affects resident and migratory landbird species. Similarly, in North America, the El Nino/ Southern Oscillation (ENSO) of the Pacific Ocean reportedly drives weather patterns that affect prey availability and population dynamics of landbird species which winter in the Caribbean. Here we show that ENSO- and NAO-induced seasonal weather conditions differentially affect neotropical- and temperate-wintering landbird species that breed in Pacific North-west forests of North America. For neotropical species wintering in western Mexico, El Nino conditions correlate with cooler, wetter conditions prior to spring migration, and with high reproductive success the following summer. For temperate wintering species, springtime NAO indices correlate strongly with levels of forest defoliation by the larvae of two moth species and also with annual reproductive success, especially among species known to prey upon those larvae. Generalized linear models incorporating NAO indices and ENSO precipitation indices explain 50-90% of the annual variation in productivity reported for 10 landbird species. These results represent an important step towards spatially explicit modelling of avian population dynamics at regional scales.

Abstract The demographic,causes of avian population change may be identified by demographic monitoring techniques, including mist-netting and nest monitoring, that provide inferences regarding productivity and survivorship parameters. Accurate estimates of these parameters are essential for the construction of predictive population models. Constant-effort mist netting provides spatially-explicit estimates of adult survival rates from mark-recapture modeling,of banding data and indices of productivity from the ratio of young to adult birds. This technique provides both within-year and between-year information allowing modifications to be made to mark-recapture models that consider the existence of transient individuals and provide estimates of demographic parameters for the resident proportion of the population. We describe the flexibility of constant effort

There are three important reasons why monitoring vital rates (primary demographic parameters such as productivity and survivorship) must be a component of any integrated avian population monitoring scheme (Baillie 1990). First, environmental stressors and management actions affect vital rates directly and usually without the time lags that so often occur with population size (Temple and Wiens 1989, DeSante and George 1994). Second, vital rates provide crucial information about the stage of the life cycle at which population change is being effected (DeSante 1992). This information is particularly important for migratory birds that winter in tropical latitudes, because it can determine whether management actions should be directed toward a species’ temperate breeding grounds, tropical wintering grounds, or both. Third, monitoring vital rates provides crucial information about the viability of the population being monitored and about the quality of the habitat or landscape in which the population occurs (DeSante and Rosenberg 1998). Because of the vagility of most bird species, local variations in population size may often be masked or accentuated by recruitment or lack thereof from a wider region (DeSante 1990, George et al. 1992). Thus, density of a species in a given area may not be indicative of population viability due to source-sink dynamics (Van Horne 1983, Pulliam 1988, Donovan et al. 1995).

A technique for identifying the proximate demographic cause(s) of population decline at two spatial scales is proposed and evaluated. The approach involves modelling spatial variation in vital rates (productivity and survivorship) as a function of spatial variation in population trends. Productivity indices and time-constant annual adult survival-rats estimates were modelled from the Monitoring Avian Productivity and Survivorship (MAPS) Program. For the larger scale, productivity and survivorship of Gray Catbird Dumetella carolinensis during 1992-98 were modelled from stations in areas comprised of physiographic strata where the breeding bird survey (BBS) population trend was either significantly positive or negative. Adult survival-rate estimates were area-dependent while productivity indices were independent of area. Differences in modelled population changes agreed well with differences in BBS population trends, although the modelled population changes for both areas were substantially more negative than BBS trends. Although MAPS productivity indices appear to be biased low, these results suggest that low survival of adults was the proximate demographic cause of population decline in catbirds in physiographic strata where they were declining, and that management strategies to reverse the declines in catbirds by increasing their productivity will not be successful. At the smaller scale, productivity and survivorship were modelled during 1994-99 for Carolina Chickadee Poecile carolinensis, Gray Catbird, Ovenbird Sciurus aurocapillus, Yellow-breasted Chat Icteria virens, and Field Sparrow Spizella pusilla from stations on military installations in Kansas and Missouri (western Midwest) and Indiana and Kentucky (eastern Midwest). Selected species were those whose trend in adult captures over the six years 1994-99 was significantly positive or negative in the eastern or western Midwest and of the opposite sign (but not necessarily significant) in the other area. We were able to identify the proximate dempographic cause(s) of population decline for each species. Moreover, the regression of modelled population change on trend in adult captures showed a significant positive relationship, although the y-intercept was negative (-0.418), again suggesting that MAPS productivity indices are biased low, but that the biases are relatively constant between areas and among species. The short-comings of this approach are discussed. We conclude that the approach is in deed useful for identifying the proximate demographic cause of population change, but that an optimal approach would include consideration of both spatial and temporal variation in vital rates and population treads.

We conducted point counts three dines during the 1994 breeding season at 48 stations across the northwestern United States, and used cumulative totals from the three visits to rank the sites by two potential indices of conservation value: species richness and overall abundance of birds. We then recalculated each of the indices (1) using data from only a single visit to each site and (2) using data from only two visits. Rankings based on only one or two visits revealed that eliminating one, and even two of the visits had relatively minor effects on species richness rankings but affected rankings based on overall abundance more substantially. We also evaluated how effectively one or two visits to each site detected particular species of management concern. We conclude that when resources are limited, species richness based on point counts conducted during just one ol two visits to potential conservation sites may provide a reliable index for prioritizing conservation efforts. When the primary objective is to determine the presence or absence of a particular species, however, at least two visits may be warranted. Finally, we conclude that, in general, researchers must be careful when using overall abundance as an index for establishing conservation priorities, as values may fluctuate substantially throughout the season.

As part of the effort to restore the ∼10 000-km2 Everglades drainage in southern Florida, USA, we developed spatially explicit species index (SESI) models of a number of species and species groups. In this paper we describe the methodology and results of three such models: those for the Cape Sable Seaside Sparrow and the Snail Kite, and the species group model of long-legged wading birds. SESI models are designed to produce relative comparisons of one management alternative to a base scenario or to another alternative. The model outputs do not provide an exact quantitative prediction of future biotic group responses, but rather, when applying the same input data and different hydrologic plans, the models provide the best available means to compare the relative response of the biotic groups. We compared four alternative hydrologic management scenarios to a base scenario (i.e., predicted conditions assuming that current water management practices continue). We ranked the results of the comparisons for each set of models. No one scenario was beneficial to all species; however, they provide a uniform assessment, based on the best available observational information, of relative species responses to alternative water-management plans. As such, these models were used extensively in the restoration planning.