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Aim: Globally, many bird species nest in tree cavities that are either excavated or formed through decay or damage processes. We assembled an overview of all tree-cavity nesters (excavators and non-excavators) in the world, analysed their geographic distribution and listed the conservation status of all species. Location: This is a global analysis of species from every continent except for Antarctica where the lack of trees precludes the occurrence of this group. Methods: We reviewed the online version of the Handbook of the Birds of the World Alive, http://www.hbw.com/, and primary literature for species known to nest in tree cavities, with tree cavities defined as holes that a bird can enter such that it is not visible from the outside. We classified species by nester type (excavator or non-excavator, and obligate or facultative where possible), conservation threat status and zoogeographic region, and tested for statistical differences in species distributions across realms using chi-square tests. Results: At least 1878 species (18.1% of all bird species in the world) nest in tree cavities, of which we considered 355 to be primary excavators, 126 facultative excavators and 1357 non-excavators (we were unable to classify nesting type for 40 species). At least 338 species use cavities created by woodpeckers (Picidae), excluding reuse by woodpeckers themselves. About 13% (249 species) of tree-cavity nesters experience major threats (i.e., status of vulnerable, endangered or critically endangered). The highest richness of tree-cavity nesters is found in the Neotropical (678 species) and Oriental (453) regions, and the highest proportion of threatened species in Australasia (17%). Main conclusion: Maintenance of a continual supply of cavities, a process in which woodpeckers and the processes of decay play critical roles, is a global conservation priority as tree cavities provide important nesting sites for many bird species.

Biodiversity forecasts are important for conservation, management, and evaluating how well current models characterize natural systems. While the number of forecasts for biodiversity is increasing, there is little information available on how well these forecasts work. Most biodiversity forecasts are not evaluated to determine how well they predict future diversity, fail to account for uncertainty, and do not use time-series data that captures the actual dynamics being studied. We addressed these limitations by using best practices to explore our ability to forecast the species richness of breeding birds in North America. We used hindcasting to evaluate six different modeling approaches for predicting richness. Hindcasts for each method were evaluated annually for a decade at 1,237 sites distributed throughout the continental United States. All models explained more than 50% of the variance in richness, but none of them consistently outperformed a baseline model that predicted constant richness at each site. The best practices implemented in this study directly influenced the forecasts and evaluations. Stacked species distribution models and “naive” forecasts produced poor estimates of uncertainty and accounting for this resulted in these models dropping in the relative performance compared to other models. Accounting for observer effects improved model performance overall, but also changed the rank ordering of models because it did not improve the accuracy of the “naive” model. Considering the forecast horizon revealed that the prediction accuracy decreased across all models as the time horizon of the forecast increased. To facilitate the rapid improvement of biodiversity forecasts, we emphasize the value of specific best practices in making forecasts and evaluating forecasting methods.

Standardized data on large‐scale and long‐term patterns of species richness are critical for understanding the consequences of natural and anthropogenic changes in the environment. The North American Breeding Bird Survey (BBS) is one of the largest and most widely used sources of such data, but so far, little is known about the degree to which BBS data provide accurate estimates of regional richness. Here, we test this question by comparing estimates of regional richness based on BBS data with spatially and temporally matched estimates based on state Breeding Bird Atlases (BBA). We expected that estimates based on BBA data would provide a more complete (and therefore, more accurate) representation of regional richness due to their larger number of observation units and higher sampling effort within the observation units. Our results were only partially consistent with these predictions: while estimates of regional richness based on BBA data were higher than those based on BBS data, estimates of local richness (number of species per observation unit) were higher in BBS data. The latter result is attributed to higher land‐cover heterogeneity in BBS units and higher effectiveness of bird detection (more species are detected per unit time). Interestingly, estimates of regional richness based on BBA blocks were higher than those based on BBS data even when differences in the number of observation units were controlled for. Our analysis indicates that this difference was due to higher compositional turnover between BBA units, probably due to larger differences in habitat conditions between BBA units and a higher likelihood of observing geographically restricted species. Our overall results indicate that estimates of regional richness based on BBS data suffer from incomplete detection of a large number of rare species, and that corrections of these estimates based on standard extrapolation techniques are not sufficient to remove this bias. Future applications of BBS data in ecology and conservation, and in particular, applications in which the representation of rare species is important (e.g., those focusing on biodiversity conservation), should be aware of this bias, and should integrate BBA data whenever possible.

1. Species richness is the most widely used biodiversity metric, but cannot be observed directly as, typically, some species are overlooked. Imperfect detectability must therefore be accounted for to obtain unbiased species-richness estimates. When richness is assessed at multiple sites, two approaches can be used to estimate species richness: either estimating for each site separately, or pooling all samples. The first approach produces imprecise estimates, while the second loses site-specific information. 2. In contrast, a hierarchical Bayes (HB) multispecies site-occupancy model benefits from the combination of information across sites without losing site-specific information and also yields occupancy estimates for each species. The heart of the model is an estimate of the incompletely observed presence-absence matrix, a centrepiece of biogeography and monitoring studies. We illustrate the model using Swiss breeding bird survey data, and compare its estimates with the widely used jackknife species-richness estimator and raw species counts. 3. Two independent observers each conducted three surveys in 26 1-km² quadrats, and detected 27-56 (total 103) species. The average estimated proportion of species detected after three surveys was 0·87 under the HB model. Jackknife estimates were less precise (less repeatable between observers) than raw counts, but HB estimates were as repeatable as raw counts. The combination of information in the HB model thus resulted in species-richness estimates presumably at least as unbiased as previous approaches that correct for detectability, but without costs in precision relative to uncorrected, biased species counts. 4. Total species richness in the entire region sampled was estimated at 113·1 (CI 106-123); species detectability ranged from 0·08 to 0·99, illustrating very heterogeneous species detectability; and species occupancy was 0·06-0·96. Even after six surveys, absolute bias in observed occupancy was estimated at up to 0·40. 5. Synthesis and applications. The HB model for species-richness estimation combines information across sites and enjoys more precise, and presumably less biased, estimates than previous approaches. It also yields estimates of several measures of community size and composition. Covariates for occupancy and detectability can be included. We believe it has considerable potential for monitoring programmes as well as in biogeography and community ecology.

1. Abundance-occupancy relationships comprise some of the most general and well-explored patterns in macro-ecology. The theory governing these relationships predicts that species will exhibit a positive interspecific and intraspecific relationship between regional occupancy and local abundance. Abundance-occupancy relationships have important implications in using distributional surveys, such as atlases, to understand and document large-scale population dynamics and the consequences of environmental change. A basic need for interpreting such data bases is a better understanding of whether changes in regional occupancy reflect changes in local abundance across species of varying life-history characteristics. 2. Our objective was to test the predictions of the abundance-occupancy rule using two independent data sets, the New York State Breeding Bird Atlas and the North American Breeding Bird Survey. The New York State Breeding Bird Atlas consists of 5332 25-km² survey blocks and is one of the first atlases in the USA to be completed for two time periods (1980-85 and 2000-05). The North American Breeding Survey is a large-scale annual survey intended to document the relative abundance and population change of songbirds throughout the USA. 3. We found that regional occupancy was positively correlated with relative abundance across 98 (β = 0·60 ± 0·11 SE, P < 0·001, R² = 0·60) and 85 species (β = 0·67 ± 0·06 SE, P < 0·001, R² = 0·57) in two separate time periods. This relationship proved stable over time and was notably consistent between breeding habitat groups and migratory guilds. 4. Between 1980 and 2005, changes in regional occupancy were highly correlated with long-term abundance trend estimates for 75 species (β = 5·73 ± 0·24 SE, P < 0·001, R² = 0·88). Over a 20-year period, woodland and resident birds showed an increase in occupancy while grassland species showed the greatest decline; these patterns were mirrored by changes in local abundance. 5. Although exceptions existed, we found most changes in occupancy parallel changes in local abundance. These findings support the basic predictions of the abundance-occupancy rule and demonstrate its consistency and stability in species and groups of varying life-history characteristics.

Altitudinal patterns in the population ecology of mountain bird species are useful for predicting species occurrence and behavior. Numerous hypotheses about the complex interactions among environmental factors have been proposed; however, these still remain controversial. This study aimed to identify the altitudinal patterns in breeding bird species richness or density and to test the hypotheses that climate, habitat heterogeneity (horizontal and vertical), and heterospecific attraction in a temperate forest, South Korea. We conducted a field survey of 142 plots at altitudes between 200 and 1,400 m a.s.l in the breeding season. A total of 2,771 individuals from 53 breeding bird species were recorded. Altitudinal patterns of species richness and density showed a hump-shaped pattern, indicating that the highest richness and density could be observed at moderate altitudes. Models constructed with 13 combinations of six variables demonstrated that species richness was positively correlated with vertical and horizontal habitat heterogeneity. Density was positively correlated with vertical, but not horizontal habitat heterogeneity, and negatively correlated with migratory bird ratio. No significant relationships were found between spring temperature and species richness or density. Therefore, the observed patterns in species richness support the hypothesis that habitat heterogeneity, rather than climate, is the main driver of species richness. Also, neither habitat heterogeneity nor climate hypotheses fully explains the observed patterns in density. However, vertical habitat heterogeneity does likely help explain observed patterns in density. The heterospecific attraction hypothesis did not apply to the distribution of birds along the altitudinal gradient. Appropriate management of vertical habitat heterogeneity, such as vegetation cover, should be maintained for the conservation of bird diversity in this area.

Population viability analysis (PVA) has been an important tool for evaluating species extinction risk and alternative management strategies, but there is little information on how well PVA predicts population trajectories following changes in management actions. We tested previously published predictions from a stage-structured PVA of Peregrine Falcons (Falco peregrinus) in California, USA (Wootton and Bell 1992), against population trajectories following the 1992 termination of statewide, active management (population supplementation of captive-reared young). In the absence of extensive post-management monitoring, we developed surrogate estimates of breeding population size by calibrating several citizen science data sets (Christmas Bird Count, CBC; and North American Breeding Bird Survey, BBS) to intensive population surveys taken primarily during the active management period. CBC abundance data standardized by observer effort exhibited a strong relationship to intensive survey data (r2 = 0.971), indicated significantly reduced annual population growth rates after management was terminated (λ = 0.023 ± 0.013 SE) than when supplementation occurred (λ = 0.089 ± 0.023 SE), and demonstrated an increasing population as predicted by the PVA. The population trajectory fell within the 95% CI of stochastic simulations of the model either with or without density dependence and assuming either measurement error or process error, but models with process error were most strongly supported by the data. These results indicate that PVA can quantitatively anticipate population trajectories following changes in management, highlight the importance of post-management monitoring of species of concern, and illustrate the benefits of using management changes as large-scale experiments to more rigorously test PVA.

Over the past half century, migratory birds in North America have shown divergent population trends relative to resident species, with the former declining rapidly and the latter increasing. The role that climate change has played in these observed trends is not well understood, despite significant warming over this period. We used 43 y of monitoring data to fit dynamic species distribution models and quantify the rate of latitudinal range shifts in 32 species of birds native to eastern North America. Since the early 1970s, species that remain in North America throughout the year, including both resident and migratory species, appear to have responded to climate change through both colonization of suitable area at the northern leading edge of their breeding distributions and adaption in place at the southern trailing edges. Neotropical migrants, in contrast, have shown the opposite pattern: contraction at their southern trailing edges and no measurable shifts in their northern leading edges. As a result, the latitudinal distributions of temperate-wintering species have increased while the latitudinal distributions of neotropical migrants have decreased. These results raise important questions about the mechanisms that determine range boundaries of neotropical migrants and suggest that these species may be particularly vulnerable to future climate change. Our results highlight the potential importance of climate change during the nonbreeding season in constraining the response of migratory species to temperature changes at both the trailing and leading edges of their breeding distributions. Future research on the interactions between breeding and nonbreeding climate change is urgently needed.

Land-cover changes from the last decades are leading to important declines in habitat quality, giving rise to changes in bird species distribution all over the world. However, land-cover changes result from a variety of different processes, and it is not clear how effective species distribution models are in capturing species responses to these changes. In this study, we evaluated our ability to predict the effects of land-cover changes on shifts in species distributions at large spatial and temporal scales using Mediterranean landscapes and early-successional, open-habitat birds as study models. Based on presence—absence data from the second Catalan Breeding Bird Atlas (1999—2002), we applied six different species distribution modeling techniques for 10 bird species using climate, topographic, and land-cover data as predictor variables. Then we back-projected the models on land-cover conditions from 1980 to evaluate the projections with field observation data from the first Catalan Breeding Bird Atlas (1975—1983). Finally, we assessed if, in addition to changes in habitat suitability resulting from land-cover shifts, descriptors of fire impact contributed to further explain species distribution dynamics: colonization and local extinction. We developed accurate model projections of current and past global patterns of species distribution, but our ability to predict species distribution dynamics was reduced. Colonization dynamics were generally more strongly related to fire descriptors than to changes in overall habitat suitability derived from land-cover changes. Our results warn of the dangers of projecting species distribution models onto future conditions if processes behind species distribution dynamics are not explicitly included. Consideration of ecologically meaningful processes for species (i.e., fire disturbance) when modeling species' distribution might contribute to a better explanation of species' colonization dynamics.