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Climate change has marked effects on global weather patterns and oceanic systems, impacting animal behaviour and fitness in potentially profound ways. Despite this, we lack detailed information about species’ responses to climatic variation. Using an 11-year tracking dataset of over 300 individual birds, we explore the consequences of variation in the Southern Annular Mode (SAM) and Southern Oscillation Index (SOI) for individual behaviour and fitness in wandering albatrosses Diomedea exulans breeding in the Southern Indian Ocean. Our results reveal distinct responses between males and females to climatic variation that align with the impacts of each climatic index on the distinct foraging ranges of each sex. In positive SAM phases, linked to poorer foraging conditions in female ranges and better conditions in male ranges, females exhibited behaviour consistent with reduced foraging success: that is, fewer prey capture attempts, and more movement between feeding patches. Males, on the other hand, showed no behavioural change. During positive SOI phases, associated with good foraging conditions in both male and female foraging ranges, both sexes showed evidence of more successful foraging, with birds engaging in more search behaviour, and taking shorter trips with fewer prey capture attempts, together indicating increased food intake per unit time. We found limited evidence for a role of individual variation, as measured through differences in personality, suggesting that plastic responses to climate are sufficiently important so as to obscure inter-individual variation. Supporting this was the finding that individual breeding success was unaffected by climatic variation, suggesting that plastic foraging behaviour allows albatrosses to mitigate climate impacts and maintain reproductive output. 

Personality predicts divorce rates in humans, yet how personality traits affect divorce in wild animals remains largely unknown. In a male-skewed population of wandering albatross ( Diomedea exulans ), we showed that personality predicts divorce; shyer males exhibited higher divorce rates than bolder males but no such relationship was found in females. We propose that divorce may be caused by the intrusion of male competitors and shyer males divorce more often because of their avoidance of territorial aggression, while females have easier access to mates regardless of their personality. Thus, personality may have important implications for the dynamics of social relationships. 

Abstract Population ecology and biogeography applications often necessitate the transfer of models across spatial and/or temporal dimensions to make predictions outside the bounds of the data used for model fitting. However, ecological data are often spatiotemporally unbalanced such that the spatial or the temporal dimension tends to contain more data than the other. This unbalance frequently leads model transfers to become substitutions, which are predictions to a different dimension than the predictive model was built on. Despite the prevalence of substitutions in ecology, studies validating their performance and their underlying assumptions are scarce.Here, we present a case study demonstrating both space‐for‐time and time‐for‐space substitutions (TFSS) using emperor penguins (Aptenodytes forsteri) as the focal species. Using an abundance‐based species distribution model (aSDM) of adult emperor penguins in attendance during spring across 50 colonies, we predict long‐term annual fluctuations in fledgling abundance and breeding success at a single colony, Pointe Géologie. Subsequently, we construct statistical models from time series of extended counts on Pointe Géologie to predict average colony abundance distribution across 50 colonies.Our analysis reveals that the distance to nearest open water (NOW) exhibits the strongest association with both temporal and spatial data. Space‐for‐time substitution performance of the aSDM, as measured by the Pearson correlation coefficient, was 0.63 and 0.56 when predicting breeding success and fledgling abundance time series, respectively. Linear regression of fledgling abundance on NOW yields similar TFSS performance when predicting the abundance distribution of emperor penguin colonies with a correlation coefficient of 0.58.We posit that such space–time equivalence arises because: (1) emperor penguin colonies conform to their existing fundamental niche; (2) there is not yet any environmental novelty when comparing the spatial versus temporal variation of distance to the nearest open water; and (3) models of more specific components of life histories, such as fledgling abundance, rather than total population abundance, are more transferable. Identifying these conditions empirically can enhance the qualitative validation of substitutions in cases where direct validation data are lacking. 

The slow–fast continuum is a commonly used framework to describe variation in life-history strategies across species. Individual life histories have also been assumed to follow a similar pattern, especially in the pace-of-life syndrome literature. However, whether a slow–fast continuum commonly explains life-history variation among individuals within a population remains unclear. Here, we formally tested for the presence of a slow–fast continuum of life histories both within populations and across species using detailed long-term individual-based demographic data for 17 bird and mammal species with markedly different life histories. We estimated adult lifespan, age at first reproduction, annual breeding frequency, and annual fecundity, and identified the main axes of life-history variation using principal component analyses. Across species, we retrieved the slow–fast continuum as the main axis of life-history variation. However, within populations, the patterns of individual life-history variation did not align with a slow–fast continuum in any species. Thus, a continuum ranking individuals from slow to fast living is unlikely to shape individual differences in life histories within populations. Rather, individual life-history variation is likely idiosyncratic across species, potentially because of processes such as stochasticity, density dependence, and individual differences in resource acquisition that affect species differently and generate non-generalizable patterns across species. 

Abstract Many ecological systems dominated by stochastic dynamics can produce complex time series that inherently limit forecast accuracy. The ‘intrinsic predictability’ of these systems can be approximated by a time series complexity metric called weighted permutation entropy (WPE). While WPE is a useful metric to gauge forecast performance prior to model building, it is sensitive to noise and may be biased depending on the length of the time series. Here, we introduce a simple randomized permutation test (rWPE) to assess whether a time series is intrinsically more predictable than white noise.We apply rWPE to both simulated and empirical data to assess its performance and usefulness. To do this, we simulate population dynamics under various scenarios, including a linear trend, chaotic, periodic and equilibrium dynamics. We further test this approach with observed abundance time series for 932 species across four orders of animals from the Global Population Dynamics Database. Finally, using Adélie (Pygoscelis adeliae) and emperor penguin (Aptenodytes forsteri) time series as case studies, we demonstrate the application of rWPE to multiple populations for a single species.We show that rWPE can determine whether a system is significantly more predictable than white noise, even with time series as short as 10 years that show an apparent trend under biologically realistic stochasticity levels. Additionally, rWPE has statistical power close to 100% when time series are at least 30 time steps long and show chaotic or periodic dynamics. Power decreases to ~10% under equilibrium dynamics, irrespective of time series length. Among four classes of animal taxa, mammals have the highest relative frequency (28%) of time series that are both longer than 30 time steps and indistinguishable from white noise in terms of complexity, followed by insects (16%), birds (16%) and bony fishes (11%).rWPE is a straightforward and useful method widely applicable to any time series, including short ones. By informing forecasters of the inherent limitations to a system's predictability, it can guide a modeller's expectations for forecast performance. 

In a fast-changing world, polar ecosystems are threatened by climate variability. Understanding the roles of fine-scale processes, and linear and nonlinear effects of climate factors on the demography of polar species is crucial for anticipating the future state of these fragile ecosystems. While the effects of sea ice on polar marine top predators are increasingly being studied, little is known about the impacts of landfast ice (LFI) on this species community. Based on a unique 39-year time series of satellite imagery and in situ meteorological conditions and on the world's longest dataset of emperor penguin ( Aptenodytes forsteri ) breeding parameters, we studied the effects of fine-scale variability of LFI and weather conditions on this species' reproductive success. We found that longer distances to the LFI edge (i.e. foraging areas) negatively affected the overall breeding success but also the fledging success. Climate window analyses suggested that chick mortality was particularly sensitive to LFI variability between August and November. Snowfall in May also affected hatching success. Given the sensitivity of LFI to storms and changes in wind direction, important future repercussions on the breeding habitat of emperor penguins are to be expected in the context of climate change. 

Antarctic terrestrial biodiversity faces multiple threats, from invasive species to climate change. Yet no large-scale assessments of threat management strategies exist. Applying a structured participatory approach, we demonstrate that existing conservation efforts are insufficient in a changing world, estimating that 65% (at best 37%, at worst 97%) of native terrestrial taxa and land-associated seabirds are likely to decline by 2100 under current trajectories. Emperor penguins are identified as the most vulnerable taxon, followed by other seabirds and dry soil nematodes. We find that implementing 10 key threat management strategies in parallel, at an estimated present-day equivalent annual cost of US$23 million, could benefit up to 84% of Antarctic taxa. Climate change is identified as the most pervasive threat to Antarctic biodiversity and influencing global policy to effectively limit climate change is the most beneficial conservation strategy. However, minimising impacts of human activities and improved planning and management of new infrastructure projects are cost-effective and will help to minimise regional threats. Simultaneous global and regional efforts are critical to secure Antarctic biodiversity for future generations.