Local-scale impacts of extreme events drive demographic asynchrony in neighbouring top predator populations.

Extreme weather events are among the most critical aspects of climate change, but our understanding of their impacts on biological populations remains limited. Here, we exploit the rare opportunity provided by the availability of concurrent longitudinal demographic data on two neighbouring marine top predator populations (the black-browed albatross, Thalassarche melanophris, breeding in two nearby colonies) hit by an exceptionally violent storm during one study year. The aim of this study is to quantify the demographic impacts of extreme events on albatrosses and test the hypothesis that extreme events would synchronously decrease survival rates of neighbouring populations. Using demographic modelling we found that, contrary to our expectation, the storm affected the survival of albatrosses from only one of the two colonies, more than doubling the annual mortality rate compared to the study average. Furthermore, the effects of storms on adult survival would lead to substantial population declines (up to 2% per year) under simulated scenarios of increased storm frequencies. We, therefore, conclude that extreme events can result in very different local-scale impacts on sympatric populations. Crucially, by driving demographic asynchrony, extreme events can hamper our understanding of the demographic responses of wild populations to mean, long-term shifts in climate.

Environmental variability directly affects the prevalence of divorce in monogamous albatrosses.

In many socially monogamous species, divorce is a strategy used to correct for sub-optimal partnerships and is informed by measures of previous breeding performance. The environment affects the productivity and survival of populations, thus indirectly affecting divorce via changes in demographic rates. However, whether environmental fluctuations directly modulate the prevalence of divorce in a population remains poorly understood. Here, using a longitudinal dataset on the long-lived black-browed albatross (Thalassarche melanophris) as a model organism, we test the hypothesis that environmental variability directly affects divorce. We found that divorce rate varied across years (1% to 8%). Individuals were more likely to divorce after breeding failures. However, regardless of previous breeding performance, the probability of divorce was directly affected by the environment, increasing in years with warm sea surface temperature anomalies (SSTA). Furthermore, our state-space models show that warm SSTA increased the probability of switching mates in females in successful relationships. For the first time, to our knowledge, we document the disruptive effects of challenging environmental conditions on the breeding processes of a monogamous population, potentially mediated by higher reproductive costs, changes in phenology and physiological stress. Environmentally driven divorce may therefore represent an overlooked consequence of global change.

Intra-dance variation among waggle runs and the design of efficient protocols for honey bee dance decoding.

Noise is universal in information transfer. In animal communication, this presents a challenge not only for intended signal receivers, but also to biologists studying the system. In honey bees, a forager communicates to nestmates the location of an important resource via the waggle dance. This vibrational signal is composed of repeating units (waggle runs) that are then averaged by nestmates to derive a single vector. Manual dance decoding is a powerful tool for studying bee foraging ecology, although the process is time-consuming: a forager may repeat the waggle run 1- >100 times within a dance. It is impractical to decode all of these to obtain the vector; however, intra-dance waggle runs vary, so it is important to decode enough to obtain a good average. Here we examine the variation among waggle runs made by foraging bees to devise a method of dance decoding. The first and last waggle runs within a dance are significantly more variable than the middle run. There was no trend in variation for the middle waggle runs. We recommend that any four consecutive waggle runs, not including the first and last runs, may be decoded, and we show that this methodology is suitable by demonstrating the goodness-of-fit between the decoded vectors from our subsamples with the vectors from the entire dances.