Rethinking "normal": The role of stochasticity in the phenology of a synchronously breeding seabird

High individual repeatability of the migratory behaviour of a long-distance migratory seabird

BACKGROUND

Understanding the evolution of migration requires knowledge of the patterns, sources, and consequences of variation in migratory behaviour, a need exacerbated by the fact that many migratory species show rapid population declines and require knowledge-based conservation measures. We therefore need detailed knowledge on the spatial and temporal distribution of individuals across their annual cycle, and quantify how the spatial and temporal components of migratory behaviour vary within and among individuals.

METHODS

We tracked 138 migratory journeys undertaken by 64 adult common terns (Sterna hirundo) from a breeding colony in northwest Germany to identify the annual spatiotemporal distribution of these birds and to evaluate the individual repeatability of eleven traits describing their migratory behaviour.

RESULTS

Birds left the breeding colony early September, then moved south along the East Atlantic Flyway. Wintering areas were reached mid-September and located at the west and south coasts of West Africa as well as the coasts of Namibia and South Africa. Birds left their wintering areas late March and reached the breeding colony mid-April. The timing, total duration and total distance of migration, as well as the location of individual wintering areas, were moderately to highly repeatable within individuals (repeatability indexes: 0.36-0.75, 0.65-0.66, 0.93-0.94, and 0.98-1.00, respectively), and repeatability estimates were not strongly affected by population-level inter-annual variation in migratory behaviour.

CONCLUSIONS

We found large between-individual variation in common tern annual spatiotemporal distribution and strong individual repeatability of several aspects of their migratory behaviour.

Fine scale prediction of ecological community composition using a two-step sequential Machine Learning ensemble

Prediction is one of the last frontiers in ecology. Indeed, predicting fine-scale species composition in natural systems is a complex challenge as multiple abiotic and biotic processes operate simultaneously to determine local species abundances. On the one hand, species intrinsic performance and their tolerance limits to different abiotic pressures modulate species abundances. On the other hand, there is growing recognition that species interactions play an equally important role in limiting or promoting such abundances within ecological communities. Here, we present a joint effort between ecologists and data scientists to use data-driven models to predict species abundances using reasonably easy to obtain data. We propose a sequential data-driven modeling approach that in a first step predicts the potential species abundances based on abiotic variables, and in a second step uses these predictions to model the realized abundances once accounting for species competition. Using a curated data set over five years we predict fine-scale species abundances in a highly diverse annual plant community. Our models show a remarkable spatial predictive accuracy using only easy-to-measure variables in the field, yet such predictive power is lost when temporal dynamics are taken into account. This result suggests that predicting future abundances requires longer time series analysis to capture enough variability. In addition, we show that these data-driven models can also suggest how to improve mechanistic models by adding missing variables that affect species performance such as particular soil conditions (e.g. carbonate availability in our case). Robust models for predicting fine-scale species composition informed by the mechanistic understanding of the underlying abiotic and biotic processes can be a pivotal tool for conservation, especially given the human-induced rapid environmental changes we are experiencing. This objective can be achieved by promoting the knowledge gained with classic modelling approaches in ecology and recently developed data-driven models.

Consequences of phenological shifts and a compressed breeding period in Magellanic penguins

Phenological shifts may ameliorate negative effects of climate change or create carryover effects and mismatches that decrease fitness. Identifying how phenological shifts affect performance is critical for understanding how individuals and populations will respond to climate change, but requires long-term, longitudinal data. Using 34 yr of data from the Magellanic penguin (Spheniscus magellanicus) colony at Punta Tombo, Argentina, we examined the consequences of the delayed onset of breeding (i.e., arrival and egg-laying dates) that has occurred at the colony since 1983. To understand how the delay propagates through the rest of the reproductive cycle, we identified phenological trends in hatch and fledge dates. Median hatch dates were 0.29 d later each year, amounting to a 10-d shift over the course of the study. Median fledge dates did not shift over the 34-yr period, however, thus shortening the median nestling period duration by 14%. We tested several predictions regarding performance outcomes of the compressed nestling period, finding that later-hatched chicks fledged significantly younger than earlier-hatched chicks, and that younger fledglings left the colony with smaller bills and with more chick down. Interestingly, although younger chicks fledged significantly lighter and in worse body condition than older fledglings early in the study, this trend reversed over time, with younger chicks actually fledging heavier and in better body condition in more recent years. Smaller and lighter fledglings were less likely to recruit to the colony as adults. We find that delayed breeding has significantly compressed nestling periods at Punta Tombo, influencing chick growth and fledgling condition. These findings highlight the importance of studying phenology across multiple life events to understand the consequences of phenological shifts for organismal fitness.

No evidence for fitness signatures consistent with increasing trophic mismatch over 30 years in a population of European shag Phalacrocorax aristotelis

As temperatures rise, timing of reproduction is changing at different rates across trophic levels, potentially resulting in asynchrony between consumers and their resources. The match-mismatch hypothesis (MMH) suggests that trophic asynchrony will have negative impacts on average productivity of consumers. It is also thought to lead to selection on timing of breeding, as the most asynchronous individuals will show the greatest reductions in fitness. Using a 30-year individual-level dataset of breeding phenology and success from a population of European shags on the Isle of May, Scotland, we tested a series of predictions consistent with the hypothesis that fitness impacts of trophic asynchrony are increasing. These predictions quantified changes in average annual breeding success and strength of selection on timing of breeding, over time and in relation to rising sea surface temperature (SST) and diet composition. Annual average (population) breeding success was negatively correlated with average lay date yet showed no trend over time, or in relation to increasing SST or the proportion of principal prey in the diet, as would be expected if trophic mismatch was increasing. At the individual level, we found evidence for stabilising selection and directional selection for earlier breeding, although the earliest birds were not the most productive. However, selection for earlier laying did not strengthen over time, or in relation to SST or slope of the seasonal shift in diet from principal to secondary prey. We found that the optimum lay date advanced by almost 4 weeks during the study, and that the population mean lay date tracked this shift. Our results indicate that average performance correlates with absolute timing of breeding of the population, and there is selection for earlier laying at the individual level. However, we found no fitness signatures of a change in the impact of climate-induced trophic mismatch, and evidence that shags are tracking long-term shifts in optimum timing. This suggests that if asynchrony is present in this system, breeding success is not impacted. Our approach highlights the advantages of examining variation at both population and individual levels when assessing evidence for fitness impacts of trophic asynchrony.

Sea ice predicts long-term trends in Adélie penguin population growth, but not annual fluctuations: Results from a range-wide multiscale analysis

Understanding the scales at which environmental variability affects populations is critical for projecting population dynamics and species distributions in rapidly changing environments. Here we used a multilevel Bayesian analysis of range-wide survey data for Adélie penguins to characterize multidecadal and annual effects of sea ice on population growth. We found that mean sea ice concentration at breeding colonies (i.e., "prevailing" environmental conditions) had robust nonlinear effects on multidecadal population trends and explained over 85% of the variance in mean population growth rates among sites. In contrast, despite considerable year-to-year fluctuations in abundance at most breeding colonies, annual sea ice fluctuations often explained less than 10% of the temporal variance in population growth rates. Our study provides an understanding of the spatially and temporally dynamic environmental factors that define the range limits of Adélie penguins, further establishing this iconic marine predator as a true sea ice obligate and providing a firm basis for projection under scenarios of future climate change. Yet, given the weak effects of annual sea ice relative to the large unexplained variance in year-to-year growth rates, the ability to generate useful short-term forecasts of Adélie penguin breeding abundance will be extremely limited. Our approach provides a powerful framework for linking short- and longer term population processes to environmental conditions that can be applied to any species, facilitating a richer understanding of ecological predictability and sensitivity to global change.

The interaction between island geomorphology and environmental parameters drives Adélie penguin breeding phenology on neighboring islands near Palmer Station, Antarctica

Despite many studies on Adélie penguin breeding phenology, understanding the drivers of clutch initiation dates (CIDs, egg 1 lay date) is limited or lacks consensus. Here, we investigated Adélie penguin CIDs over 25 years (1991-2016) on two neighboring islands, Torgersen and Humble (<1 km apart), in a rapidly warming region near Palmer Station, Antarctica. We found that sea ice was the primary large-scale driver of CIDs and precipitation was a secondary small-scale driver that fine-tunes CID to island-specific nesting habitat geomorphology. In general, CIDs were earlier (later) when the spring sea ice retreat was earlier (later) and when the preceding annual ice season was shorter (longer). Island-specific effects related to precipitation and island geomorphology caused greater snow accumulation and delayed CIDs by ~2 days on Torgersen compared to Humble Island. When CIDs on the islands were similar, conditions were mild with less snow across breeding sites. At Torgersen Island, the negative relationship between CID and breeding success highlights detrimental effects of delayed breeding and/or snow on penguin fitness. Past phenological studies reported a relationship between air temperature and CID, assumed to be related to precipitation, but we found air temperature was more highly correlated to sea ice, revealing a misinterpretation of temperature effects. Finally, contrasting trends in CIDs based on temporal shifts in regional sea ice patterns revealed trends toward earlier CIDs (4-6 day advance) from 1979 to 2009 as the annual ice season shortened, and later CIDs (7-10 day delay) from 2010 to 2016 as the annual ice season lengthened. Adélie penguins tracked environmental conditions with flexible breeding phenology, but their life history remains vulnerable to subpolar weather conditions that can delay CIDs and decrease breeding success, especially on landscapes where geomorphology facilitates snow accumulation.

The role of seasonal timing and phenological shifts for species coexistence

Shifts in the phenologies of coexistence species are altering the temporal structure of natural communities worldwide. However, predicting how these changes affect the structure and long-term dynamics of natural communities is challenging because phenology and coexistence theory have largely proceeded independently. Here, I propose a conceptual framework that incorporates seasonal timing of species interactions into a well-studied competition model to examine how changes in phenologies influence long-term dynamics of natural communities. Using this framework I demonstrate that persistence and coexistence conditions strongly depend on the difference in species' mean phenologies and how this difference varies across years. Consequently, shifts in mean and interannual variation in relative phenologies of species can fundamentally alter the outcome of interactions and the potential for persistence and coexistence of competing species. These effects can be predicted by how per-capita effects scale with differences in species' phenologies. I outline how this approach can be parameterized with empirical systems and discuss how it fits within the context of current coexistence theory. Overall, this synthesis reveals that phenology of species interactions can play a crucial yet currently understudied role in driving coexistence and biodiversity patterns in natural systems and determine how species will respond to future climate change.

Comparing imaging, acoustics, and radar to monitor Leach's storm-petrel colonies

Seabirds are integral components of marine ecosystems and, with many populations globally threatened, there is a critical need for effective and scalable seabird monitoring strategies. Many seabird species nest in burrows, which can make traditional monitoring methods costly, infeasible, or damaging to nesting habitats. Traditional burrow occupancy surveys, where possible, can occur infrequently and therefore lead to an incomplete understanding of population trends. For example, in Oregon, during the last three decades there have been large changes in the abundance of Leach’s storm-petrels (Hydrobates leucorhoa), which included drastic declines at some colonies. Unfortunately, traditional monitoring failed to capture the timing and magnitude of change, limiting managers’ ability to determine causes of the decline and curtailing management options. New, easily repeatable methods of quantifying relative abundance are needed. For this study, we tested three methods of remote monitoring: passive acoustic monitoring, time-lapse cameras, and radar. Abundance indices derived from acoustics and imagery: call rates, acoustic energy, and counts were significantly related to traditional estimates of burrow occupancy of Leach’s storm-petrels. Due to sampling limitations, we were unable to compare radar to burrow occupancy. Image counts were significantly correlated with all other indices, including radar, while indices derived from acoustics and radar were not correlated. Acoustic data likely reflect different aspects of the population and hold the potential for the further development of indices to disentangle phenology, attendance of breeding birds, and reproductive success. We found that image counts are comparable with standard methods (e.g., radar) in producing annual abundance indices. We recommend that managers consider a sampling scheme that incorporates both acoustics and imaging, but for sites inaccessible to humans, radar remains the sole option. Implementation of acoustic and camera based monitoring programs will provide much needed information for a vulnerable group of seabirds.