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.

Conspecific and not performance-based attraction on immigrants drives colony growth in a waterbird.

Local recruitment and immigration play an important part in the dynamics and growth of animal populations. However, their estimation and incorporation into open population models is, in most cases, problematic. We studied factors affecting the growth of a recently established colony of Eurasian spoonbill (Platalea leucorodia) and assessed the contribution of local recruits, i.e. birds born in the colony, and immigrants, i.e. birds of unknown origin, to colony growth. We applied an integrated population model that accounts for uncertainty in breeding state assignment and merges population surveys, local fecundity and individual longitudinal data of breeding and non-breeding birds, to estimate demographic rates and the relative role of recruitment and immigration in driving the local dynamics. We also used this analytical framework to assess the degree of support for the 'performance-based' and 'conspecific attraction' hypotheses as possible mechanisms of colony growth. Among the demographic rates, only immigration was positively and significantly correlated with population growth rate. In addition, the number of immigrants settling in the colony was positively correlated with colony size in the previous and current year, but was not correlated with fecundity of the previous year. Our results suggest that the variation in immigration affected colony dynamics and that conspecific attraction likely triggered the relevant role of immigration in the growth of a recently formed waterbird colony, supporting the need of including immigration in population analysis.

Demographic drivers of decline and recovery in an Afro-Palaearctic migratory bird population.

Across Europe, rapid population declines are ongoing in many Afro-Palaearctic migratory bird species, but the development of appropriate conservation actions across such large migratory ranges is severely constrained by lack of understanding of the demographic drivers of these declines. By constructing regional integrated population models (IPMs) for one of the suite of migratory species that is declining in the southeast of Britain but increasing in the northwest, we show that, while annual population growth rates in both regions vary with adult survival, the divergent regional trajectories are primarily a consequence of differences in productivity. Between 1994 and 2012, annual survival and productivity rates ranged over similar levels in both regions, but high productivity rates were rarer in the declining southeast population and never coincided with high survival rates. By contrast, population growth in the northwest was fuelled by several years in which higher productivity coincided with high survival rates. Simulated population trajectories suggest that realistic improvements in productivity could have reversed the decline (i.e. recovery of the population index to more than or equal to 1) in the southeast. Consequently, actions to improve productivity on European breeding grounds are likely to be a more fruitful and achievable means of reversing migrant declines than actions to improve survival on breeding, passage or sub-Saharan wintering grounds.

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.

Precision gain versus effort with joint models using detection/non-detection and banding data.

Capture-recapture techniques provide valuable information, but are often more cost-prohibitive at large spatial and temporal scales than less-intensive sampling techniques. Model development combining multiple data sources to leverage data source strengths and for improved parameter precision has increased, but with limited discussion on precision gain versus effort. We present a general framework for evaluating trade-offs between precision gained and costs associated with acquiring multiple data sources, useful for designing future or new phases of current studies.We illustrated how Bayesian hierarchical joint models using detection/non-detection and banding data can improve abundance, survival, and recruitment inference, and quantified data source costs in a northern Arizona, USA, western bluebird (Sialia mexicana) population. We used an 8-year detection/non-detection (distributed across the landscape) and banding (subset of locations within landscape) data set to estimate parameters. We constructed separate models using detection/non-detection and banding data, and a joint model using both data types to evaluate parameter precision gain relative to effort.Joint model parameter estimates were more precise than single data model estimates, but parameter precision varied (apparent survival > abundance > recruitment). Banding provided greater apparent survival precision than detection/non-detection data. Therefore, little precision was gained when detection/non-detection data were added to banding data. Additional costs were minimal; however, additional spatial coverage and ability to estimate abundance and recruitment improved inference. Conversely, more precision was gained when adding banding to detection/non-detection data at higher cost. Spatial coverage was identical, yet survival and abundance estimates were more precise. Justification of increased costs associated with additional data types depends on project objectives.We illustrate a general framework for evaluating precision gain relative to effort, applicable to joint data models with any data type combination. This framework evaluates costs and benefits from and effort levels between multiple data types, thus improving population monitoring designs.

Quantifying the contribution of immigration to population dynamics: a review of methods, evidence and perspectives in birds and mammals.

The demography of a population is often reduced to the apparent (or local) survival of individuals and their realised fecundity within a study area defined according to logistical constraints rather than landscape features. Such demographics are then used to infer whether a local population contributes positively to population dynamics across a wider landscape context. Such a simplistic approach ignores a fundamental process underpinning population dynamics: dispersal. Indeed, it has long been accepted that immigration contributed by dispersers that emigrated from neighbouring populations may strongly influence the net growth of a local population. To date however, we lack a clear picture of how widely immigration rate varies both among and within populations, in relation to extrinsic and intrinsic ecological conditions, even for the best-studied avian and mammalian populations. This empirical knowledge gap precludes the emergence of a sound conceptual framework that ought to inform conservation and population ecology. This review, conducted on both birds and mammals, has thus three complementary objectives. First, we describe and evaluate the relative merits of methods used to quantify immigration and how they relate to widely applicable metrics. We identify two simple and unifying metrics to measure immigration: the immigration rate it defined as the ratio of the number of immigrants present in the population at time t + 1 and the total breeding population in year t, and πt , the proportion of immigrants among new recruits (i.e. new breeders). Two recently developed methods are likely to provide the most valuable data on immigration in the near future: individual parentage (rather than population) assignments based on genetic sampling, and spatially explicit integrated population models combining multiple sources of demographic data (survival, fecundity and population counts). Second, we report on a systematic literature review of studies providing a quantitative measure of immigration. Although the diversity of methods employed precludes detailed analyses, it appears that the number of immigrants exceeds locally born individuals in recruitment for most avian populations (median πt  = 0.57, N = 45 estimates from 37 studies), a figure twofold higher than estimated for mammalian populations (median πt  = 0.26, N = 33 estimates from 11 studies). Third, recent quantitative studies reveal that immigration can be the main driver of temporal variation in population growth rates, across a wide array of demographic and spatial contexts. To what extent immigration acts as a regulatory process has however been considered only rarely to date and deserves more attention. Overall, it is likely that most populations benefit from immigrants without necessarily being sink populations. Furthermore, we suggest that quantitative estimates of immigration should be core to future demographic studies and plead for more empirical evidence about the ways in which immigration interacts with local demographic processes to shape population dynamics. Finally, we discuss how to tackle spatial population dynamics by exploring, beyond the classical source-sink framework, the extent to which populations exchange individuals according to spatial scale and type of population distribution throughout the landscape.

Overcoming the Data Crisis in Biodiversity Conservation.

How can we track population trends when monitoring data are sparse? Population declines can go undetected, despite ongoing threats. For example, only one of every 200 harvested species are monitored. This gap leads to uncertainty about the seriousness of declines and hampers effective conservation. Collecting more data is important, but we can also make better use of existing information. Prior knowledge of physiology, life history, and community ecology can be used to inform population models. Additionally, in multispecies models, information can be shared among taxa based on phylogenetic, spatial, or temporal proximity. By exploiting generalities across species that share evolutionary or ecological characteristics within Bayesian hierarchical models, we can fill crucial gaps in the assessment of species' status with unparalleled quantitative rigor.