Differential contribution of demographic rate synchrony to population synchrony in barn swallows

Synchrony in adult survival is remarkably strong among common temperate songbirds across France

Synchronous variation in demographic parameters across species increases the risk of simultaneous local extinction, which lowers the probability of subsequent recolonization. Synchrony therefore tends to destabilize meta-populations and meta-communities. Quantifying interspecific synchrony in demographic parameters, like abundance, survival, or reproduction, is thus a way to indirectly assess the stability of meta-populations and meta-communities. Moreover, it is particularly informative to identify environmental drivers of interspecific synchrony because those drivers are important across species. Using a Bayesian hierarchical multisite multispecies mark-recapture model, we investigated temporal interspecific synchrony in annual adult apparent survival for 16 common songbird species across France for the period 2001-2016. Annual adult survival was largely synchronous among species (73%, 95% credible interval [47%-94%] of the variation among years was common to all species), despite species differing in ecological niche and life history. This result was robust to different model formulations, uneven species sample sizes, and removing the long-term trend in survival. Synchrony was also shared across migratory strategies, which suggests that environmental forcing during the 4-month temperate breeding season has a large-scale, interspecific impact on songbird survival. However, the strong interspecific synchrony was not easily explained by a set of candidate weather variables we defined a priori. Spring weather variables explained only 1.4% [0.01%-5.5%] of synchrony, while the contribution of large-scale winter weather indices may have been stronger but uncertain, accounting for 12% [0.3%-37%] of synchrony. Future research could jointly model interspecific variation and covariation in breeding success, age-dependent survival, and age-dependent dispersal to understand when interspecific synchrony in abundance emerges and destabilizes meta-communities.

Interpopulation differences and temporal synchrony in rates of adult survival between two seabird colonies that differ in population size and distance to foraging grounds

Understanding the processes that drive interpopulation differences in demography and population dynamics is central to metapopulation ecology. In colonial species, populations are limited by local resource availability. However, individuals from larger colonies will travel greater distances to overcome density-dependent competition. Consequently, these individuals may also experience greater carry-over effects and interpopulation differences in demography. To test this prediction, we use mark-recapture data collected over four decades from two breeding colonies of a seabird, the Manx shearwater (Puffinus puffinus), that exhibit strong spatial overlap throughout the annual cycle but differ in population size and maximum foraging distances. We quantify interpopulation differences and synchrony in rates of survival and assess whether local mean wind speeds act to strengthen or disrupt synchrony. In addition, we examine whether the imputed interpopulation differences in survival can generate population-level consequences. The colony where individuals travel further during the breeding season had slightly lower and more variable rates of survival, indicative of individuals experiencing greater carry-over effects. Fluctuations in survival were highly synchronous between the colonies, but neither synchronous, nor asynchronous, variation could be strongly attributed to fluctuations in local mean wind speeds. Finally, we demonstrate that the imputed interpopulation differences in rates of survival could lead to considerable differences in population growth. We hypothesise that the observed interpopulation differences in rates of adult survival reflect carry-over effects associated with foraging distances during the breeding season. More broadly, our results highlight that breeding season processes can be important for understanding interpopulation differences in the demographic rates and population dynamics of long-lived species, such as seabirds.

Relative effects of sample size, detection probability, and study duration on estimation in integrated population models

Understanding mechanistic causes of population change is critical for managing and conserving species. Integrated population models (IPMs) allow for quantifying population changes while directly relating environmental drivers to vital rates, but power of IPMs to detect trends and environmental effects on vital rates remains understudied. We simulated data for an IPM fewer than 41 scenarios to determine the power to detect trends and environmental effects on vital rates based on study duration, sample size, detection probability, and effect size. Our results indicated that temporal duration of a study and effect size, rather than sample size of each individual data set or detection probability, had the greatest influence on the power to identify trends in adult survival and fecundity. When using only 10 years of data, we were unable to identify a 50% increase in adult survival but were able to identify this increase with 22 years of data. When using only capture-recapture data in a traditional Cormack-Jolly-Seber analysis, we lacked sufficient power to identify trends in survival, and power of the Cormack-Jolly-Seber model was always less than the IPM. The IPM had greater power to identify trends and environmental effects on fecundity (e.g., we detected a 58% change in fecundity using 12 years of data). Models with effects of environmental variables on vital rates had less power than trends, likely to be due to increased annual variation in the vital rate when modeling responses to environmental effects that varied by year. Lack of power in the Cormack-Jolly-Seber analysis could be due to the relatively small variability in adult survival compared with fecundity, given the life history of our simulated species. As interannual variation in environmental conditions will probably increase with climate change, this type of analysis can help to inform the study duration needed, which may be a shifting target given future climate uncertainty and the complex nature of environmental correlations with demography.

Using citizen science to determine if songbird nesting parameters fluctuate in synchrony

As global temperatures continue to rise, population or spatial synchrony (i.e., the degree of synchronization in the fluctuation of demographic parameters) can have important implications for inter- and intraspecific interactions among wildlife populations. Climatic fluctuations are common drivers of spatial synchrony, and depending on the degree of synchronization and the parameters impacted, synchrony can increase extinction probabilities. Although citizen science is an inexpensive method to collect long-term data over large spatial scales to study effects of climate changes on wildlife, few studies have used citizen science data to determine if this synchrony is occurring across populations and species. We used 21 years of citizen science nesting data collected on Eastern Bluebirds (Sialia sialis) and Carolina Chickadees (Poecile carolinensis), two widespread North American species with similar life histories and abundant data, to assess the degree of synchrony between and within their populations in the southeastern United States. We found little evidence of synchronous fluctuations in the nesting parameters of hatching success, hatchability, and fledging success between and within species, nor did we observe consistent patterns towards increased or decreased synchrony. Estimates of nesting parameters were high (≥ 0.83) and showed little variability (relative variance ≤ 0.17), supporting the hypothesis that parameters that strongly contribute to population growth rates (i.e., typically fecundity in short-lived species) show little interannual variability. The low variability and lack of synchrony suggest that these populations of study species may be resilient to climate change. However, we were unable to test for synchronous fluctuations in other species and populations, or in the survival parameter, due to large gaps in data. This highlights the need for citizen science projects to continue increasing public participation for species and regions that lack data.

Demographic variation in space and time: implications for conservation targeting

The dynamics of wild populations are governed by demographic rates which vary spatially and/or temporally in response to environmental conditions. Conservation actions for widespread but declining populations could potentially exploit this variation to target locations (or years) in which rates are low, but only if consistent spatial or temporal variation in demographic rates occurs. Using long-term demographic data for wild birds across Europe, we show that productivity tends to vary between sites (consistently across years), while survival rates tend to vary between years (consistently across sites), and that spatial synchrony is more common in survival than productivity. Identifying the conditions associated with low demographic rates could therefore facilitate spatially targeted actions to improve productivity or (less feasibly) forecasting and temporally targeting actions to boost survival. Decomposing spatio-temporal variation in demography can thus be a powerful tool for informing conservation policy and for revealing appropriate scales for actions to influence demographic rates.

Integrated population modelling reveals potential drivers of demography from partially aligned data: a case study of snowy plover declines under human stressors

Knowledge of demography is essential for understanding wildlife population dynamics and developing appropriate conservation plans. However, population survey and demographic data (e.g., capture-recapture) are not always aligned in space and time, hindering our ability to robustly estimate population size and demographic processes. Integrated population models (IPMs) can provide inference for population dynamics with poorly aligned but jointly analysed population and demographic data. In this study, we used an IPM to analyse partially aligned population and demographic data of a migratory shorebird species, the snowy plover (Charadrius nivosus). Snowy plover populations have declined dramatically during the last two decades, yet the demographic mechanisms and environmental drivers of these declines remain poorly understood, hindering development of appropriate conservation strategies. We analysed 21 years (1998-2018) of partially aligned population survey, nest survey, and capture-recapture-resight data in three snowy plover populations (i.e., Texas, New Mexico, Oklahoma) in the Southern Great Plains of the US. By using IPMs we aimed to achieve better precision while evaluating the effects of wetland habitat and climatic factors (minimum temperature, wind speed) on snowy plover demography. Our IPM provided reasonable precision for productivity measures even with missing data, but population and survival estimates had greater uncertainty in years without corresponding data. Our model also uncovered the complex relationships between wetland habitat, climate, and demography with reasonable precision. Wetland habitat had positive effects on snowy plover productivity (i.e., clutch size and clutch fate), indicating the importance of protecting wetland habitat under climate change and other human stressors for the conservation of this species. We also found a positive effect of minimum temperature on snowy plover productivity, indicating potential benefits of warmth during night on their population. Based on our results, we suggest prioritizing population and capture-recapture surveys for understanding population dynamics and underlying demographic processes when data collection is limited by time and/or financial resources. Our modelling approach can be used to allocate limited conservation resources for evidence-based decision-making.

High turn-over rates at the upper range limit and elevational source-sink dynamics in a widespread songbird

The formation of an upper distributional range limit for species breeding along mountain slopes is often based on environmental gradients resulting in changing demographic rates towards high elevations. However, we still lack an empirical understanding of how the interplay of demographic parameters forms the upper range limit in highly mobile species. Here, we study apparent survival and within-study area dispersal over a 700 m elevational gradient in barn swallows (Hirundo rustica) by using 15 years of capture-mark-recapture data. Annual apparent survival of adult breeding birds decreased while breeding dispersal probability of adult females, but not males increased towards the upper range limit. Individuals at high elevations dispersed to farms situated at elevations lower than would be expected by random dispersal. These results suggest higher turn-over rates of breeding individuals at high elevations, an elevational increase in immigration and thus, within-population source-sink dynamics between low and high elevations. The formation of the upper range limit therefore is based on preference for low-elevation breeding sites and immigration to high elevations. Thus, shifts of the upper range limit are not only affected by changes in the quality of high-elevation habitats but also by factors affecting the number of immigrants produced at low elevations.

Demographic responses to climate change in a threatened Arctic species

The Arctic is undergoing rapid and accelerating change in response to global warming, altering biodiversity patterns, and ecosystem function across the region. For Arctic endemic species, our understanding of the consequences of such change remains limited. Spectacled eiders (Somateria fischeri), a large Arctic sea duck, use remote regions in the Bering Sea, Arctic Russia, and Alaska throughout the annual cycle making it difficult to conduct comprehensive surveys or demographic studies. Listed as Threatened under the U.S. Endangered Species Act, understanding the species response to climate change is critical for effective conservation policy and planning. Here, we developed an integrated population model to describe spectacled eider population dynamics using capture-mark-recapture, breeding population survey, nest survey, and environmental data collected between 1992 and 2014. Our intent was to estimate abundance, population growth, and demographic rates, and quantify how changes in the environment influenced population dynamics. Abundance of spectacled eiders breeding in western Alaska has increased since listing in 1993 and responded more strongly to annual variation in first-year survival than adult survival or productivity. We found both adult survival and nest success were highest in years following intermediate sea ice conditions during the wintering period, and both demographic rates declined when sea ice conditions were above or below average. In recent years, sea ice extent has reached new record lows and has remained below average throughout the winter for multiple years in a row. Sea ice persistence is expected to further decline in the Bering Sea. Our results indicate spectacled eiders may be vulnerable to climate change and the increasingly variable sea ice conditions throughout their wintering range with potentially deleterious effects on population dynamics. Importantly, we identified that different demographic rates responded similarly to changes in sea ice conditions, emphasizing the need for integrated analyses to understand population dynamics.

Decomposing fecundity and evaluating demographic influence of multiple broods in a migratory bird

Relevance of breeding season fecundity as a driver of population dynamics has been highlighted by many studies. Despite that, knowledge about how brood type specific (i.e. first, second or replacement) fecundity affects demography of multiple-brooded species is limited. In fact, estimation of brood type specific fecundity is often challenging due to imperfect detection of nesting attempts. We examined the demographic contribution and the feedback on population density of different components of fecundity, along with other vital rates, in a facultative multiple-brooded migratory bird. We used a novel formulation of a fecundity model that allows incorporating reproductive data for which information on the type of brood was unknown in some cases, and embedded it into an integrated population model (IPM) to obtain consensual estimates of all demographic rates, including brood type specific fecundities, reproductive success probabilities and proportion of breeding pairs that performed a second or replacement brood. We then conducted transient life table response experiments on IPM estimates to account for non-stationary environments. We applied the model to two 20-year datasets collected in a Swiss and a German local population of wrynecks Jynx torquilla. Brood type specific fecundities and temporal patterns of brood type specific probabilities of success, number of successful and unsuccessful first broods, probability of starting a second or a replacement brood and proportion of pairs that performed a second or a replacement brood differed between the two populations. However, changes in immigration rate and apparent survival were the dominant contributors to temporal variation and large sequential changes in realized population growth rates in both populations. In the Swiss population we also found that second brood fecundity declined when population size increased. Our study provides insight into the reproductive processes that affect population dynamics and mediate density-dependent fecundity in a migratory bird. In addition, the analytical approach proposed can be used in other studies of multiple-brooded species to maximize the use of available fecundity data through the estimation of unknown brood types, thus favouring a better understanding of the demographic contribution of brood type specific fecundity.

Drivers of amphibian population dynamics and asynchrony at local and regional scales

Identifying the drivers of population fluctuations in spatially distinct populations remains a significant challenge for ecologists. Whereas regional climatic factors may generate population synchrony (i.e. the Moran effect), local factors including the level of density dependence may reduce the level of synchrony. Although divergences in the scaling of population synchrony and spatial environmental variation have been observed, the regulatory factors that underlie such mismatches are poorly understood. Few previous studies have investigated how density-dependent processes and population-specific responses to weather variation influence spatial synchrony at both local and regional scales. We addressed this issue in a pond-breeding amphibian, the great crested newt Triturus cristatus. We used capture-recapture data collected through long-term surveys in five T. cristatus populations in Western Europe. In all populations-and subpopulations within metapopulations-population size, annual survival and recruitment fluctuated over time. Likewise, there was considerable variation in these demographic rates between populations and within metapopulations. These fluctuations and variations appear to be context-dependent and more related to site-specific characteristics than local or regional climatic drivers. We found a low level of demographic synchrony at both local and regional levels. Weather has weak and spatially variable effects on survival, recruitment and population growth rate. In contrast, density dependence was a common phenomenon (at least for population growth) in almost all populations and subpopulations. Our findings support the idea that the Moran effect is low in species where the population dynamics more closely depends on local factors (e.g. population density and habitat characteristics) than on large-scale environmental fluctuation (e.g. regional climatic variation). Such responses may have far-reaching consequences for the long-term viability of spatially structured populations and their ability to respond to large-scale climatic anomalies.

Disentangling data discrepancies with integrated population models

A common challenge for studying wildlife populations occurs when different survey methods provide inconsistent or incomplete inference on the trend, dynamics, or viability of a population. A potential solution to the challenge of conflicting or piecemeal data relies on the integration of multiple data types into a unified modeling framework, such as integrated population models (IPMs). IPMs are a powerful approach for species that inhabit spatially and seasonally complex environments. We provide guidance on exploiting the capabilities of IPMs to address inferential discrepancies that stem from spatiotemporal data mismatches. We illustrate this issue with analysis of a migratory species, the American Woodcock (Scolopax minor), in which individual monitoring programs suggest differing population trends. To address this discrepancy, we synthesized several long-term data sets (1963-2015) within an IPM to estimate continental-scale population trends, and link dynamic drivers across the full annual cycle and complete extent of the woodcock's geographic range in eastern North America. Our analysis reveals the limiting portions of the life cycle by identifying time periods and regions where vital rates are lowest and most variable, as well as which demographic parameters constitute the main drivers of population change. We conclude by providing recommendations for resolving conflicting population estimates within an integrated modeling approach, and discuss how strategies (e.g., data thinning, expert opinion elicitation) from other disciplines could be incorporated into ecological analyses when attempting to combine multiple, incongruent data types.

Female-biased dispersal and non-random gene flow of MC1R variants do not result in a migration load in barn owls

Non-random gene flow is a widely neglected force in evolution and ecology. This genotype-dependent dispersal is difficult to assess, yet can impact the genetic variation of natural populations and their fitness. In this work, we demonstrate a high immigration rate of barn owls (Tyto alba) inside a Swiss population surveyed during 15 years. Using ten microsatellite loci as an indirect method to characterize dispersal, two-third of the genetic tests failed to detect a female-biased dispersal, and Monte Carlo simulations confirmed a low statistical power to detect sex-biased dispersal in case of high dispersal rate of both sexes. The capture-recapture data revealed a female-biased dispersal associated with an excess of heterozygote for the melanocortin-1 receptor gene (MC1R), which is responsible for their ventral rufous coloration. Thus, female homozygotes for the MC1R_WHITE allele might be negatively selected during dispersal. Despite the higher immigration of females that are heterozygote at MC1R, non-random gene flow should not lead to a migration load regarding this gene because we did not detect an effect of MC1R on survival and reproductive success in our local population. The present study highlights the usefulness of using multiple methods to correctly decrypt dispersal and gene flow. Moreover, despite theoretical expectations, we show that non-random dispersal of particular genotypes does not necessarily lead to migration load in recipient populations.

Heterogeneous responses of temperate-zone amphibian populations to climate change complicates conservation planning

The pervasive and unabated nature of global amphibian declines suggests common demographic responses to a given driver, and quantification of major drivers and responses could inform broad-scale conservation actions. We explored the influence of climate on demographic parameters (i.e., changes in the probabilities of survival and recruitment) using 31 datasets from temperate zone amphibian populations (North America and Europe) with more than a decade of observations each. There was evidence for an influence of climate on population demographic rates, but the direction and magnitude of responses to climate drivers was highly variable among taxa and among populations within taxa. These results reveal that climate drivers interact with variation in life-history traits and population-specific attributes resulting in a diversity of responses. This heterogeneity complicates the identification of conservation 'rules of thumb' for these taxa, and supports the notion of local focus as the most effective approach to overcome global-scale conservation challenges.

Modelling the effects of spatial heterogeneity and temporal variation in extinction probability on mosquito populations

Spatial synchrony plays an important role in dictating the dynamics of spatial and stage-structured populations. Here we argue that, unlike the Moran effect where spatial synchrony is driven by exogenous factors, spatial correlation in intrinsic/local-scale processes can affect the level of spatial synchrony among distinct sub-populations, and therefore the persistence of the entire population. To explore this mechanism, we modelled the consequences of spatial heterogeneity in aquatic habitat quality, and that of temporal variation in local extinction probability, on the persistence of stage-structured mosquito populations. As a model system, we used two widely distributed mosquito species, Aedes albopictus and Culex pipiens, both key vectors of a range of infectious diseases. Spatial heterogeneity in aquatic habitat quality led to increased population persistence, and this pattern was more pronounced at intermediate dispersal rates, and in the long-dispersing species (C. pipiens). The highest regional persistence was obtained at high dispersal rates. This is probably because dispersal, in our model, did not carry any additional costs. Population persistence of both species was negatively correlated with increased temporal variation in local extinction probability. These differences were stronger in the short-dispersing species (A. albopictus), especially at intermediate dispersal rates. The dispersal of A. albopictus adults in each time step was limited to the nearest habitat patches, weakening the positive effect of spatial heterogeneity in aquatic habitat quality on population persistence. In contrast, C. pipiens adults could disperse into more remote sub-populations, resulting in much higher recolonization rates. Hence, the negative effect of temporal variation in local extinction probability on patch occupancy disappeared at intermediate dispersal rates. We suggest that effectively controlling these two mosquito species requires making few spatially synchronized control efforts (i.e., generating high temporal variation in local extinction probability), rather than many asynchronized local control efforts. Finally, our model can be easily fitted to other organisms characterized by complex life cycles, and it can be also used to examine alternative scenarios, including the effect of spatial configuration of local habitat patches and dispersal kernel shape on population persistence.

Understanding the demographic drivers of realized population growth rates

Identifying the demographic parameters (e.g., reproduction, survival, dispersal) that most influence population dynamics can increase conservation effectiveness and enhance ecological understanding. Life table response experiments (LTRE) aim to decompose the effects of change in parameters on past demographic outcomes (e.g., population growth rates). But the vast majority of LTREs and other retrospective population analyses have focused on decomposing asymptotic population growth rates, which do not account for the dynamic interplay between population structure and vital rates that shape realized population growth rates (λt=Nt+1/Nt) in time-varying environments. We provide an empirical means to overcome these shortcomings by merging recently developed "transient life-table response experiments" with integrated population models (IPMs). IPMs allow for the estimation of latent population structure and other demographic parameters that are required for transient LTRE analysis, and Bayesian versions additionally allow for complete error propagation from the estimation of demographic parameters to derivations of realized population growth rates and perturbation analyses of growth rates. By integrating available monitoring data for Lesser Scaup over 60 yr, and conducting transient LTREs on IPM estimates, we found that the contribution of juvenile female survival to long-term variation in realized population growth rates was 1.6 and 3.7 times larger than that of adult female survival and fecundity, respectively. But a persistent long-term decline in fecundity explained 92% of the decline in abundance between 1983 and 2006. In contrast, an improvement in adult female survival drove the modest recovery in Lesser Scaup abundance since 2006, indicating that the most important demographic drivers of Lesser Scaup population dynamics are temporally dynamic. In addition to resolving uncertainty about Lesser Scaup population dynamics, the merger of IPMs with transient LTREs will strengthen our understanding of demography for many species as we aim to conserve biodiversity during an era of non-stationary global change.

Integrated population models reveal local weather conditions are the key drivers of population dynamics in an aerial insectivore

Changes to weather patterns under a warming climate are complex: while warmer temperatures are expected virtually worldwide, decreased mean precipitation is expected at mid-latitudes. Migratory birds depend on broad-scale weather patterns to inform timing of movements, but may be more susceptible to local weather patterns during sedentary periods. We constructed Bayesian integrated population models (IPMs) to assess whether continental or local weather effects best explained population dynamics in an environmentally sensitive aerial insectivorous bird, the tree swallow (Tachycineta bicolor), along a transcontinental gradient from British Columbia to Saskatchewan to New York, and tested whether population dynamics were synchronous among sites. Little consistency existed among sites in the demographic rates most affecting population growth rate or in correlations among rates. Juvenile apparent survival at all sites was stable over time and greatest in New York, whereas adult apparent survival was more variable among years and sites, and greatest in British Columbia and Saskatchewan. Fledging success was greatest in Saskatchewan. Local weather conditions explained significant variation in adult survival in Saskatchewan and fledging success in New York, corroborating the hypothesis that local more than continental weather drives the population dynamics of this species and, therefore, demographic synchrony measured at three sites was limited. Nonetheless, multi-population IPMs can be a powerful tool for identifying correlated population trajectories caused by synchronous demographic rates, and can pinpoint the scale at which environmental drivers are responsible for changes. We caution against applying uniform conservation actions for populations where synchrony does not occur or is not fully understood.

Winter temperatures limit population growth rate of a migratory songbird

Understanding the factors that limit and regulate wildlife populations requires insight into demographic and environmental processes acting throughout the annual cycle. Here, we combine multi-year tracking data of individual birds with a 26-year demographic study of a migratory songbird to evaluate the relative effects of density and weather at the breeding and wintering grounds on population growth rate. Our results reveal clear support for opposing forces of winter temperature and breeding density driving population dynamics. Above-average temperatures at the wintering grounds lead to higher population growth, primarily through their strong positive effects on survival. However, population growth is regulated over the long term by strong negative effects of breeding density on both fecundity and adult male survival. Such knowledge of how year-round factors influence population growth, and the demographic mechanisms through which they act, will vastly improve our ability to predict species responses to environmental change and develop effective conservation strategies for migratory animals.

Bringing It All Together: Multi-species Integrated Population Modelling of a Breeding Community

Integrated population models (IPMs) combine data on different aspects of demography with time-series of population abundance. IPMs are becoming increasingly popular in the study of wildlife populations, but their application has largely been restricted to the analysis of single species. However, species exist within communities: sympatric species are exposed to the same abiotic environment, which may generate synchrony in the fluctuations of their demographic parameters over time. Given that in many environments conditions are changing rapidly, assessing whether species show similar demographic and population responses is fundamental to quantifying interspecific differences in environmental sensitivity and highlighting ecological interactions at risk of disruption. In this paper, we combine statistical approaches to study populations, integrating data along two different dimensions: across species (using a recently proposed framework to quantify multi-species synchrony in demography) and within each species (using IPMs with demographic and abundance data). We analyse data from three seabird species breeding at a nationally important long-term monitoring site. We combine demographic datasets with island-wide population counts to construct the first multi-species Integrated Population Model to consider synchrony. Our extension of the IPM concept allows the simultaneous estimation of demographic parameters, adult abundance and multi-species synchrony in survival and productivity, within a robust statistical framework. The approach is readily applicable to other taxa and habitats. Supplementary materials accompanying this paper appear on-line.

Electronic Supplementary Material

Supplementary materials for this article are available at 10.1007/s13253-017-0279-4.

Identifying multispecies synchrony in response to environmental covariates

The importance of multispecies models for understanding complex ecological processes and interactions is beginning to be realized. Recent developments, such as those by Lahoz-Monfort et al. (2011), have enabled synchrony in demographic parameters across multiple species to be explored. Species in a similar environment would be expected to be subject to similar exogenous factors, although their response to each of these factors may be quite different. The ability to group species together according to how they respond to a particular measured covariate may be of particular interest to ecologists. We fit a multispecies model to two sets of similar species of garden bird monitored under the British Trust for Ornithology's Garden Bird Feeding Survey. Posterior model probabilities were estimated using the reversible jump algorithm to compare posterior support for competing models with different species sharing different subsets of regression coefficients. There was frequently good agreement between species with small asynchronous random-effect components and those with posterior support for models with shared regression coefficients; however, this was not always the case. When groups of species were less correlated, greater uncertainty was found in whether regression coefficients should be shared or not. The methods outlined in this study can test additional hypotheses about the similarities or synchrony across multiple species that share the same environment. Through the use of posterior model probabilities, estimated using the reversible jump algorithm, we can detect multispecies responses in relation to measured covariates across any combination of species and covariates under consideration. The method can account for synchrony across species in relation to measured covariates, as well as unexplained variation accounted for using random effects. For more flexible, multiparameter distributions, the support for species-specific parameters can also be measured.