Model selection for the North American Breeding Bird Survey.

The North American Breeding Bird Survey (BBS) provides data that can be used in complex, multiscale analyses of population change, while controlling for scale-specific nuisance factors. Many alternative models can be fit to the data, but most model selection procedures are not appropriate for hierarchical models. Leave-one-out cross-validation (LOOCV), in which relative model fit is assessed by omitting an observation and assessing the prediction of a model fit using the remainder of the data, provides a reasonable approach for assessing models, but is time consuming and not feasible to apply for all observations in large data sets. We report the first large-scale formal model selection for BBS data, applying LOOCV to stratified random samples of observations from BBS data. Our results are for 548 species of North American birds, comparing the fit of four alternative models that differ in year effect structures and in descriptions of extra-Poisson overdispersion. We use a hierarchical model among species to evaluate posterior probabilities that models are best for individual species. Models in which differences in year effects are conditionally independent (D models) were generally favored over models in which year effects are modeled by a slope parameter and a random year effect (S models), and models in which extra-Poisson overdispersion effects are independent and t-distributed (H models) tended to be favored over models where overdispersion was independent and normally distributed. Our conclusions lead us to recommend a change from the conventional S model to D and H models for the vast majority of species (544/548). Comparison of estimated population trends based on the favored model relative to the S model currently used for BBS summaries indicates no consistent differences in estimated trends. Of the 18 species that showed large differences in estimated trends between models, estimated trends from the default S model were more extreme, reflecting the influence of the slope parameter in that model for species that are undergoing large population changes. WAIC, a computationally simpler alternative to LOOCV, does not appear to be a reliable alternative to LOOCV.

On the robustness of N-mixture models.

N-mixture models provide an appealing alternative to mark-recapture models, in that they allow for estimation of detection probability and population size from count data, without requiring that individual animals be identified. There is, however, a cost to using the N-mixture models: inference is very sensitive to the model's assumptions. We consider the effects of three violations of assumptions that might reasonably be expected in practice: double counting, unmodeled variation in population size over time, and unmodeled variation in detection probability over time. These three examples show that small violations of assumptions can lead to large biases in estimation. The violations of assumptions we consider are not only small qualitatively, but are also small in the sense that they are unlikely to be detected using goodness-of-fit tests. In cases where reliable estimates of population size are needed, we encourage investigators to allocate resources to acquiring additional data, such as recaptures of marked individuals, for estimation of detection probabilities.

On the reliability of N-mixture models for count data.

N-mixture models describe count data replicated in time and across sites in terms of abundance N and detectability p. They are popular because they allow inference about N while controlling for factors that influence p without the need for marking animals. Using a capture-recapture perspective, we show that the loss of information that results from not marking animals is critical, making reliable statistical modeling of N and p problematic using just count data. One cannot reliably fit a model in which the detection probabilities are distinct among repeat visits as this model is overspecified. This makes uncontrolled variation in p problematic. By counter example, we show that even if p is constant after adjusting for covariate effects (the "constant p" assumption) scientifically plausible alternative models in which N (or its expectation) is non-identifiable or does not even exist as a parameter, lead to data that are practically indistinguishable from data generated under an N-mixture model. This is particularly the case for sparse data as is commonly seen in applications. We conclude that under the constant p assumption reliable inference is only possible for relative abundance in the absence of questionable and/or untestable assumptions or with better quality data than seen in typical applications. Relative abundance models for counts can be readily fitted using Poisson regression in standard software such as R and are sufficiently flexible to allow controlling for p through the use covariates while simultaneously modeling variation in relative abundance. If users require estimates of absolute abundance, they should collect auxiliary data that help with estimation of p.

Multidirectional abundance shifts among North American birds and the relative influence of multifaceted climate factors.

Shifts in species distributions are major fingerprint of climate change. Examining changes in species abundance structures at a continental scale enables robust evaluation of climate change influences, but few studies have conducted these evaluations due to limited data and methodological constraints. In this study, we estimate temporal changes in abundance from North American Breeding Bird Survey data at the scale of physiographic strata to examine the relative influence of different components of climatic factors and evaluate the hypothesis that shifting species distributions are multidirectional in resident bird species in North America. We quantify the direction and velocity of the abundance shifts of 57 permanent resident birds over 44 years using a centroid analysis. For species with significant abundance shifts in the centroid analysis, we conduct a more intensive correlative analysis to identify climate components most strongly associated with composite change of abundance within strata. Our analysis focus on two contrasts: the relative importance of climate extremes vs. averages, and of temperature vs. precipitation in strength of association with abundance change. Our study shows that 36 species had significant abundance shifts over the study period. The average velocity of the centroid is 5.89 km·yr-1 . The shifted distance on average covers 259 km, 9% of range extent. Our results strongly suggest that the climate change fingerprint in studied avian distributions is multidirectional. Among 6 directions with significant abundance shifts, the northwestward shift was observed in the largest number of species (n = 13). The temperature/average climate model consistently has greater predictive ability than the precipitation/extreme climate model in explaining strata-level abundance change. Our study shows heterogeneous avian responses to recent environmental changes. It highlights needs for more species-specific approaches to examine contributing factors to recent distributional changes and for comprehensive conservation planning for climate change adaptation.

An integrated population model for bird monitoring in North America.

Integrated population models (IPMs) provide a unified framework for simultaneously analyzing data sets of different types to estimate vital rates, population size, and dynamics; assess contributions of demographic parameters to population changes; and assess population viability. Strengths of an IPM include the ability to estimate latent parameters and improve the precision of parameter estimates. We present a hierarchical IPM that combines two broad-scale avian monitoring data sets: count data from the North American Breeding Bird Survey (BBS) and capture-recapture data from the Monitoring Avian Productivity and Survivorship (MAPS) program. These data sets are characterized by large numbers of sample sites and observers, factors capable of inducing error in the sampling and observation processes. The IPM integrates the data sets by modeling the population abundance as a first-order autoregressive function of the previous year's population abundance and vital rates. BBS counts were modeled as a log-linear function of the annual index of population abundance, observation effects (observer identity and first survey year), and overdispersion. Vital rates modeled included adult apparent survival, estimated from a transient Cormack-Jolly-Seber model using MAPS data, and recruitment (surviving hatched birds from the previous season + dispersing adults) estimated as a latent parameter. An assessment of the IPM demonstrated it could recover true parameter values from 200 simulated data sets. The IPM was applied to data sets (1992-2008) of two bird species, Gray Catbird (Dumetella carolinensis) and Wood Thrush (Hylocichla mustelina) in the New England/Mid-Atlantic coastal Bird Conservation Region of the United States. The Gray Catbird population was relatively stable (trend +0.4% per yr), while the Wood Thrush population nearly halved (trend -4.5% per yr) over the 17-yr study period. IPM estimates of population growth rates, adult survival, and detection and residency probabilities were similar and as precise as estimates from the stand-alone BBS and CJS models. A benefit of using the IPM was its ability to estimate the latent recruitment parameter. Annual growth rates for both species correlated more with recruitment than survival, and the relationship for Wood Thrush was stronger than for Gray Catbird. The IPM's unified modeling framework facilitates integration of these important data sets.

Bayesian cross-validation for model evaluation and selection, with application to the North American Breeding Bird Survey.

The analysis of ecological data has changed in two important ways over the last 15 years. The development and easy availability of Bayesian computational methods has allowed and encouraged the fitting of complex hierarchical models. At the same time, there has been increasing emphasis on acknowledging and accounting for model uncertainty. Unfortunately, the ability to fit complex models has outstripped the development of tools for model selection and model evaluation: familiar model selection tools such as Akaike's information criterion and the deviance information criterion are widely known to be inadequate for hierarchical models. In addition, little attention has been paid to the evaluation of model adequacy in context of hierarchical modeling, i.e., to the evaluation of fit for a single model. In this paper, we describe Bayesian cross-validation, which provides tools for model selection and evaluation. We describe the Bayesian predictive information criterion and a Bayesian approximation to the BPIC known as the Watanabe-Akaike information criterion. We illustrate the use of these tools for model selection, and the use of Bayesian cross-validation as a tool for model evaluation, using three large data sets from the North American Breeding Bird Survey.

Modeled distribution shifts of North American birds over four decades based on suitable climate alone do not predict observed shifts.

As climate change alters the global environment, it is critical to understand the relationship between shifting climate suitability and species distributions. Key questions include whether observed changes in population abundance are aligned with the velocity and direction of shifts predicted by climate suitability models and if the responses are consistent among species with similar ecological traits. We examined the direction and velocity of the observed abundance-based distribution centroids compared with the model-predicted bioclimatic distribution centroids of 250 bird species across the United States from 1969 to 2011. We hypothesized that there is a significant positive correlation in both direction and velocity between the observed and the modeled shifts. We then tested five additional hypotheses that predicted differential shifting velocity based on ecological adaptability and climate change exposure. Contrary to our hypotheses, we found large differences between the observed and modeled shifts among all studied bird species and within specific ecological guilds. However, temperate migrants and habitat generalist species tended to have higher velocity of observed shifts than other species. Neotropical migratory and wetland birds also had significantly different observed velocities than their counterparts, which may be due to their climate change exposure. The velocity based on modeled bioclimatic suitability did not exhibit significant differences among most guilds. Boreal forest birds were the only guild with significantly faster modeled-shifts than the other groups, suggesting an elevated conservation risk for high latitude and altitude species. The highly idiosyncratic species responses to climate and the mismatch between shifts in modeled and observed distribution centroids highlight the challenge of predicting species distribution change based solely on climate suitability and the importance of non-climatic factors traits in shaping species distributions.

Modeling the effects of environmental disturbance on wildlife communities: avian responses to prescribed fire.

Prescribed fire is a management tool used to reduce fuel loads on public lands in forested areas in the western United States. Identifying the impacts of prescribed fire on bird communities in ponderosa pine (Pinus ponderosa) forests is necessary for providing land management agencies with information regarding the effects of fuel reduction on sensitive, threatened, and migratory bird species. Recent developments in occupancy modeling have established a framework for quantifying the impacts of management practices on wildlife community dynamics. We describe a Bayesian hierarchical model of multi-species occupancy accounting for detection probability, and we demonstrate the model's usefulness for identifying effects of habitat disturbances on wildlife communities. Advantages to using the model include the ability to estimate the effects of environmental impacts on rare or elusive species, the intuitive nature of the modeling, the incorporation of detection probability, the estimation of parameter uncertainty, the flexibility of the model to suit a variety of experimental designs, and the composite estimate of the response that applies to the collection of observed species as opposed to merely a small subset of common species. Our modeling of the impacts of prescribed fire on avian communities in a ponderosa pine forest in Washington indicate that prescribed fire treatments result in increased occupancy rates for several bark-insectivore, cavity-nesting species including a management species of interest, Black-backed Woodpeckers (Picoides arcticus). Three aerial insectivore species, and the ground insectivore, American Robin (Turdus migratorius), also responded positively to prescribed fire, whereas three foliage insectivores and two seed specialists, Clark's Nutcracker (Nucifraga columbiana) and the Pine Siskin (Carduelis pinus), declined following treatments. Land management agencies interested in determining the effects of habitat manipulations on wildlife communities can use these methods to provide guidance for future management activities.

Microarray analysis of gene expression changes in feeding female and male lone star ticks, Amblyomma americanum (L).

A collection of EST clones from female tick Amblyomma americanum salivary glands was hybridized to RNA from different feeding stages of female tick salivary glands and from unfed or feeding adult male ticks. In the female ticks, the expression patterns changed dramatically upon starting feeding, then changed again towards the end of feeding. On beginning feeding, genes possibly involved in survival on the host increased in expression as did many housekeeping genes. As feeding progressed, some of the survival genes were downregulated, while others were upregulated. When the tick went into the rapid feeding phase, many of the survival genes were downregulated, while a number of transport-associated genes and genes possibly involved in organ degeneration increased. In the males, the presence of females during feeding made a small difference, but feeding made a larger difference. Males showed clear differences from females in expression, as well. Protein synthesis genes were expressed more in all male groups than in the partially fed females, while the putative secreted genes involved in avoiding host defenses were expressed less.

Decline of the North American avifauna.

Species extinctions have defined the global biodiversity crisis, but extinction begins with loss in abundance of individuals that can result in compositional and functional changes of ecosystems. Using multiple and independent monitoring networks, we report population losses across much of the North American avifauna over 48 years, including once-common species and from most biomes. Integration of range-wide population trajectories and size estimates indicates a net loss approaching 3 billion birds, or 29% of 1970 abundance. A continent-wide weather radar network also reveals a similarly steep decline in biomass passage of migrating birds over a recent 10-year period. This loss of bird abundance signals an urgent need to address threats to avert future avifaunal collapse and associated loss of ecosystem integrity, function, and services.

Seasonal components of avian population change: joint analysis of two large-scale monitoring programs.

We present a combined analysis of data from two large-scale surveys of bird populations. The North American Breeding Bird Survey is conducted each summer; the Christmas Bird Count is conducted in early winter. The temporal staggering of these surveys allows investigation of seasonal components of population change, which we illustrate with an examination of the effects of severe winters on the Carolina Wren (Thryothorus ludovicianus). Our analysis uses a hierarchical log-linear model with controls for survey-specific sampling covariates. Temporal change in population size is modeled seasonally, with covariates for winter severity. Overall, the winter-spring seasons are associated with 82% of the total population variation for Carolina Wrens, and an additional day of snow cover during winter-spring is associated with an incremental decline of 1.1% of the population.

Consistent response of bird populations to climate change on two continents.

Global climate change is a major threat to biodiversity. Large-scale analyses have generally focused on the impacts of climate change on the geographic ranges of species and on phenology, the timing of ecological phenomena. We used long-term monitoring of the abundance of breeding birds across Europe and the United States to produce, for both regions, composite population indices for two groups of species: those for which climate suitability has been either improving or declining since 1980. The ratio of these composite indices, the climate impact indicator (CII), reflects the divergent fates of species favored or disadvantaged by climate change. The trend in CII is positive and similar in the two regions. On both continents, interspecific and spatial variation in population abundance trends are well predicted by climate suitability trends.

Endocannabinoids and related fatty acid amides, and their regulation, in the salivary glands of the lone star tick.

The salivary glands and saliva from the lone star tick Amblyomma americanum (L.) were analyzed for the presence of the two endogenous agonists of cannabinoid receptors, N-arachidonoylethanolamine (anandamide) and 2-arachidonoylglycerol (2-AG), as well as of the anandamide congener, N-palmitoylethanolamine (PEA), an anti-inflammatory and analgesic mediator that is inactive at cannabinoid receptors. Two very sensitive mass-spectrometric techniques were used for this purpose. Both 2-AG and PEA, as well as other N-acylethanolamines (NAEs), were identified in salivary glands, but anandamide was below detection. The levels of 2-AG were considerably higher in the salivary glands of partially fed than replete females. Ex vivo gland stimulation with arachidonic acid increased the levels of 2-AG, but not of PEA or other NAEs, and caused the formation of anandamide and of the potent analgesic compound N-arachidonoylglycine. Instead, the amounts of anandamide, 2-AG and PEA were not influenced by treatment of salivary glands with dopamine, which stimulates saliva secretion. The possible biosynthetic precursors of anandamide, PEA and other NAEs were also detected in salivary glands, whereas only PEA was detected in tick saliva. These data demonstrate for the first time that the salivary glands of an obligate ectoparasite species can make endocannabinoids and/or related congeners with analgesic and anti-inflammatory activity, which possibly participate in the inhibition of the host defense reactions.

Application of RNA interference in tick salivary gland research.

Ticks are obligate ectoparasites that feed on a variety of hosts including mammals, birds and reptiles. Prolonged attachment on the host and an ability to transmit a wide variety of pathogens are the special features of tick feeding. Salivary glands are the major route for secretion of excess fluid, several proteins, and factors that counteract the host immune response and hence play a significant role in the success of tick feeding. RNA interference (RNAi) enables scientists to silence genes encoding proteins in an absolutely sequence specific manner at the mRNA level. This technique has already been successfully employed in analyzing roles of proteins of important functions or in assigning roles to several proteins of unknown functions in a variety of animals. In this review, we outline the process of RNAi and the applicability of RNAi in tick salivary gland research.

Comparison of differentially expressed genes in the salivary glands of male ticks, Amblyomma americanum and Dermacentor andersoni.

Genes expressed differentially in the salivary glands of unfed and fed male ticks, Amblyomma americanum (L.), were identified, cloned and sequenced, and some were compared with those expressed in the salivary glands of Dermacentor andersoni. Total protein and RNA increased sixfold in the salivary glands of fed male A. americanum, while in fed male D. andersoni salivary glands, RNA increased approximately 3.5 times. Feeding D. andersoni in the presence of females increased total RNA by 25% over those fed in the absence of females. Complementary DNAs were synthesized from RNA obtained from unfed and fed ticks and amplified using RNA arbitrarily primed polymerase chain reaction (RAP-PCR) with three different primers in separate reactions. Differential display showed clear banding differences between the fed and the unfed ticks in A. americanum and D. andersoni. Sixty-one cDNA fragments that appeared to be from differentially expressed genes in A. americanum were isolated, cloned and sequenced. Hybridization reactions with labeled cDNA probes confirmed the differential expression of many of the genes in unfed and fed ticks' salivary glands; however, many of the bands contained more than one fragment and some of the fragments isolated from apparently differential bands were not specific. Sequences for 28 of the cDNA fragments (150-600 nucleotides in length) demonstrated similarity to genes in the databases, but nine of these were similar to sequences of unknown function. Some of the gene fragments identified may be important to tick feeding or tick salivary gland physiology, including a histamine-binding protein, an organic ion transporter, an apoptosis inhibitor, a cathepsin-B-like cysteine protease, proteins involved in gene regulation and several proteins involved in protein synthesis. Cross-hybridization of identified cDNAs from A. americanum with cDNA probes synthesized from D. andersoni total RNA did not show significant similarity between the two species.

Amblyomma americanum salivary glands: double-stranded RNA-mediated gene silencing of synaptobrevin homologue and inhibition of PGE2 stimulated protein secretion.

Protein secretion into the saliva from the tick salivary glands is due to exocytosis of vesicular membrane bound granular material regulated by SNARE complex proteins after salivary gland stimulation by PGE2 [Insect Biochem. Mol. Biol. 32 (2002) 1711]. Proteins associated with vesicles (v-SNAREs) are essential components of the exocytotic process. Synaptobrevin is a key v-SNARE in all secreting cells studied to date. A vesicle-associated synaptobrevin cDNA fragment homologue from the salivary glands of partially fed lone star tick females was cloned and sequenced. Double-stranded (ds) RNA interference (RNAi) is an effective method to silence specific gene expression. The functional role of synaptobrevin in protein secretion in partially fed tick salivary glands was studied with an in vitro RNAi method. Incubation of isolated salivary glands with double-stranded RNA (dsRNA) transcribed from a tick salivary gland synaptobrevin cDNA fragment resulted in decreased expression of the transcript, a reduction in the level of synaptobrevin protein and inhibition of PGE2 stimulated anticoagulant protein secretion by isolated salivary glands. We demonstrate the applicability of RNAi for studying individual steps in the mechanism of PGE2 stimulated exocytosis in the salivary glands of ixodid ticks.

Applications of a cell culture system for studying the interaction of Anaplasma marginale with tick cells.

A cell culture system for the tick-borne rickettsia Anaplasma marginale offers new opportunities for research on this economically important pathogen of cattle. A. marginale multiplies in membrane-bound inclusions in host cells. Whereas erythrocytes appear to be the only site of infection in cattle, A. marginale undergoes a complex developmental cycle in ticks and transmission occurs via the salivary glands during feeding. We recently developed a cell culture system for A. marginale using a cell line derived from embryos of Ixodes scapularis. Here we review the use of this cell culture system for studying the interaction of A. marginale with tick cells. Several assays were developed using the A. marginale/tick cell system. An adhesion assay was developed for the identification of proteins required by A. marginale for adhesion to tick cells. The effect of antibodies against selected major surface proteins in inhibiting A. marginale infection was tested in an assay that allowed further confirmation of the role of surface proteins in the infection of tick cells. A drug screening assay for A. marginale was developed and provides a method of initial drug selection without the use of cattle. The culture system was used to test for enhancing effects of tick saliva and saliva components on A. marginale infection. The tick cell culture system has proved to be a good model for studying A. marginale-tick interactions. Information gained from these studies may be applicable to other closely related tick-borne pathogens that have been propagated in the same tick cell line.

Explaining local-scale species distributions: relative contributions of spatial autocorrelation and landscape heterogeneity for an avian assemblage.

Understanding interactions between mobile species distributions and landcover characteristics remains an outstanding challenge in ecology. Multiple factors could explain species distributions including endogenous evolutionary traits leading to conspecific clustering and endogenous habitat features that support life history requirements. Birds are a useful taxon for examining hypotheses about the relative importance of these factors among species in a community. We developed a hierarchical Bayes approach to model the relationships between bird species occupancy and local landcover variables accounting for spatial autocorrelation, species similarities, and partial observability. We fit alternative occupancy models to detections of 90 bird species observed during repeat visits to 316 point-counts forming a 400-m grid throughout the Patuxent Wildlife Research Refuge in Maryland, USA. Models with landcover variables performed significantly better than our autologistic and null models, supporting the hypothesis that local landcover heterogeneity is important as an exogenous driver for species distributions. Conspecific clustering alone was a comparatively poor descriptor of local community composition, but there was evidence for spatial autocorrelation in all species. Considerable uncertainty remains whether landcover combined with spatial autocorrelation is most parsimonious for describing bird species distributions at a local scale. Spatial structuring may be weaker at intermediate scales within which dispersal is less frequent, information flows are localized, and landcover types become spatially diversified and therefore exhibit little aggregation. Examining such hypotheses across species assemblages contributes to our understanding of community-level associations with conspecifics and landscape composition.

Global biodiversity: indicators of recent declines.

In 2002, world leaders committed, through the Convention on Biological Diversity, to achieve a significant reduction in the rate of biodiversity loss by 2010. We compiled 31 indicators to report on progress toward this target. Most indicators of the state of biodiversity (covering species' population trends, extinction risk, habitat extent and condition, and community composition) showed declines, with no significant recent reductions in rate, whereas indicators of pressures on biodiversity (including resource consumption, invasive alien species, nitrogen pollution, overexploitation, and climate change impacts) showed increases. Despite some local successes and increasing responses (including extent and biodiversity coverage of protected areas, sustainable forest management, policy responses to invasive alien species, and biodiversity-related aid), the rate of biodiversity loss does not appear to be slowing.