Recommendations for quantifying and reducing uncertainty in climate projections of species distributions.

Projecting the future distributions of commercially and ecologically important species has become a critical approach for ecosystem managers to strategically anticipate change, but large uncertainties in projections limit climate adaptation planning. Although distribution projections are primarily used to understand the scope of potential change-rather than accurately predict specific outcomes-it is nonetheless essential to understand where and why projections can give implausible results and to identify which processes contribute to uncertainty. Here, we use a series of simulated species distributions, an ensemble of 252 species distribution models, and an ensemble of three regional ocean climate projections, to isolate the influences of uncertainty from earth system model spread and from ecological modeling. The simulations encompass marine species with different functional traits and ecological preferences to more broadly address resource manager and fishery stakeholder needs, and provide a simulated true state with which to evaluate projections. We present our results relative to the degree of environmental extrapolation from historical conditions, which helps facilitate interpretation by ecological modelers working in diverse systems. We found uncertainty associated with species distribution models can exceed uncertainty generated from diverging earth system models (up to 70% of total uncertainty by 2100), and that this result was consistent across species traits. Species distribution model uncertainty increased through time and was primarily related to the degree to which models extrapolated into novel environmental conditions but moderated by how well models captured the underlying dynamics driving species distributions. The predictive power of simulated species distribution models remained relatively high in the first 30 years of projections, in alignment with the time period in which stakeholders make strategic decisions based on climate information. By understanding sources of uncertainty, and how they change at different forecast horizons, we provide recommendations for projecting species distribution models under global climate change.

Flexible use of a dynamic energy landscape buffers a marine predator against extreme climate variability.

Animal migrations track predictable seasonal patterns of resource availability and suitable thermal habitat. As climate change alters this 'energy landscape', some migratory species may struggle to adapt. We examined how climate variability influences movements, thermal habitat selection and energy intake by juvenile Pacific bluefin tuna (Thunnus orientalis) during seasonal foraging migrations in the California Current. We tracked 242 tuna across 15 years (2002-2016) with high-resolution archival tags, estimating their daily energy intake via abdominal warming associated with digestion (the 'heat increment of feeding'). The poleward extent of foraging migrations was flexible in response to climate variability, allowing tuna to track poleward displacements of thermal habitat where their standard metabolic rates were minimized. During a marine heatwave that saw temperature anomalies of up to +2.5°C in the California Current, spatially explicit energy intake by tuna was approximately 15% lower than average. However, by shifting their mean seasonal migration approximately 900 km poleward, tuna remained in waters within their optimal temperature range and increased their energy intake. Our findings illustrate how tradeoffs between physiology and prey availability structure migration in a highly mobile vertebrate, and suggest that flexible migration strategies can buffer animals against energetic costs associated with climate variability and change.

Recent prey capture experience and dynamic habitat quality mediate short-term foraging site fidelity in a seabird.

Foraging site fidelity allows animals to increase their efficiency by returning to profitable feeding areas. However, the mechanisms underpinning why animals 'stay' or 'switch' sites have rarely been investigated. Here, we explore how habitat quality and prior prey capture experience influence short-term site fidelity by the little penguin (Eudyptula minor). Using 88 consecutive foraging trips by 20 brooding penguins, we found that site fidelity was higher after foraging trips where environmental conditions were favourable, and after trips where prey capture success was high. When penguins exhibited lower site fidelity, the number of prey captures relative to the previous trip increased, suggesting that switches in foraging location were an adaptive strategy in response to low prey capture rates. Penguins foraged closer to where other penguins foraged on the same day than they did to the location of their own previous foraging site, and caught more prey when they foraged close together. This suggests that penguins aggregated flexibly when prey was abundant and accessible. Our results illustrate how foraging predators can integrate information about prior experience with contemporary information such as social cues. This gives insight into how animals combine information adaptively to exploit changing prey distribution in a dynamic environment.

Supervised accelerometry analysis can identify prey capture by penguins at sea.

Determining where, when and how much animals eat is fundamental to understanding their ecology. We developed a technique to identify a prey capture signature for little penguins from accelerometry, in order to quantify food intake remotely. We categorised behaviour of captive penguins from HD video and matched this to time-series data from back-mounted accelerometers. We then trained a support vector machine (SVM) to classify the penguins' behaviour at 0.3 s intervals as either 'prey handling' or 'swimming'. We applied this model to accelerometer data collected from foraging wild penguins to identify prey capture events. We compared prey capture and non-prey capture dives to test the model predictions against foraging theory. The SVM had an accuracy of 84.95±0.26% (mean ± s.e.) and a false positive rate of 9.82±0.24% when tested on unseen captive data. For wild data, we defined three independent, consecutive prey handling observations as representing true prey capture, with a false positive rate of 0.09%. Dives with prey captures had longer duration and bottom times, were deeper, had faster ascent rates, and had more 'wiggles' and 'dashes' (proxies for prey encounter used in other studies). The mean (±s.e.) number of prey captures per foraging trip was 446.6±66.28. By recording the behaviour of captive animals on HD video and using a supervised machine learning approach, we show that accelerometry signatures can classify the behaviour of wild animals at unprecedentedly fine scales.

Spatial match-mismatch between predators and prey under climate change.

Climate change is driving a rapid redistribution of life on Earth. Variability in the rates, magnitudes and directions of species' shifts can alter spatial overlap between predators and prey, with the potential to decouple trophic interactions. Although phenological mismatches between predator requirements and prey availability under climate change are well-established, 'spatial match-mismatch' dynamics remain poorly understood. We synthesize global evidence for climate-driven changes in spatial predator-prey overlap resulting from species redistribution across marine and terrestrial domains. We show that spatial mismatches can have vastly different outcomes for predator populations depending on their diet specialization and role within the wider ecosystem. We illustrate ecosystem-level consequences of climate-driven changes in spatial predator-prey overlap, from restructuring food webs to altering socio-ecological interactions. It remains unclear how predator-prey overlap at the landscape scale relates to prey encounter and consumption rates at local scales, or how the spatial reorganization of food webs affects ecosystem function. We identify key research directions necessary to resolve the scale of ecological impacts caused by species redistribution under climate change.

Species redistribution creates unequal outcomes for multispecies fisheries under projected climate change.

Climate change drives species distribution shifts, affecting the availability of resources people rely upon for food and livelihoods. These impacts are complex, manifest at local scales, and have diverse effects across multiple species. However, for wild capture fisheries, current understanding is dominated by predictions for individual species at coarse spatial scales. We show that species-specific responses to localized environmental changes will alter the collection of co-occurring species within established fishing footprints along the U.S. West Coast. We demonstrate that availability of the most economically valuable, primary target species is highly likely to decline coastwide in response to warming and reduced oxygen concentrations, while availability of the most abundant, secondary target species will potentially increase. A spatial reshuffling of primary and secondary target species suggests regionally heterogeneous opportunities for fishers to adapt by changing where or what they fish. Developing foresight into the collective responses of species at local scales will enable more effective and tangible adaptation pathways for fishing communities.

Variability in prey field structure drives inter-annual differences in prey encounter by a marine predator, the little penguin.

Understanding how marine predators encounter prey across patchy landscapes remains challenging due to difficulties in measuring the three-dimensional structure of pelagic prey fields at scales relevant to animal movement. We measured at-sea behaviour of a central-place forager, the little penguin (Eudyptula minor), over 5 years (2015-2019) using GPS and dive loggers. We made contemporaneous measurements of the prey field within the penguins' foraging range via boat-based acoustic surveys. We developed a prey encounter index by comparing estimates of acoustic prey density encountered along actual penguin tracks to those encountered along simulated penguin tracks with the same characteristics as real tracks but that moved randomly through the prey field. In most years, penguin tracks encountered prey better than simulated random movements greater than 99% of the time, and penguin dive depths matched peaks in the vertical distribution of prey. However, when prey was unusually sparse and/or deep, penguins had worse than random prey encounter indices, exhibited dives that mismatched depth of maximum prey density, and females had abnormally low body mass (5.3% lower than average). Reductions in prey encounters owing to decreases in the density or accessibility of prey may ultimately lead to reduced fitness and population declines in central-place foraging marine predators.

Where did they not go? Considerations for generating pseudo-absences for telemetry-based habitat models.

BACKGROUND: Habitat suitability models give insight into the ecological drivers of species distributions and are increasingly common in management and conservation planning. Telemetry data can be used in habitat models to describe where animals were present, however this requires the use of presence-only modeling approaches or the generation of 'pseudo-absences' to simulate locations where animals did not go. To highlight considerations for generating pseudo-absences for telemetry-based habitat models, we explored how different methods of pseudo-absence generation affect model performance across species' movement strategies, model types, and environments. METHODS: We built habitat models for marine and terrestrial case studies, Northeast Pacific blue whales (Balaenoptera musculus) and African elephants (Loxodonta africana). We tested four pseudo-absence generation methods commonly used in telemetry-based habitat models: (1) background sampling; (2) sampling within a buffer zone around presence locations; (3) correlated random walks beginning at the tag release location; (4) reverse correlated random walks beginning at the last tag location. Habitat models were built using generalised linear mixed models, generalised additive mixed models, and boosted regression trees. RESULTS: We found that the separation in environmental niche space between presences and pseudo-absences was the single most important driver of model explanatory power and predictive skill. This result was consistent across marine and terrestrial habitats, two species with vastly different movement syndromes, and three different model types. The best-performing pseudo-absence method depended on which created the greatest environmental separation: background sampling for blue whales and reverse correlated random walks for elephants. However, despite the fact that models with greater environmental separation performed better according to traditional predictive skill metrics, they did not always produce biologically realistic spatial predictions relative to known distributions. CONCLUSIONS: Habitat model performance may be positively biased in cases where pseudo-absences are sampled from environments that are dissimilar to presences. This emphasizes the need to carefully consider spatial extent of the sampling domain and environmental heterogeneity of pseudo-absence samples when developing habitat models, and highlights the importance of scrutinizing spatial predictions to ensure that habitat models are biologically realistic and fit for modeling objectives.

Prior exposure to capture heightens the corticosterone and behavioural responses of little penguins (Eudyptula minor) to acute stress.

Studies of physiology can provide important insight into how animals are coping with challenges in their environment and can signal the potential effects of exposure to human activity in both the short and long term. In this study, we measured the physiological and behavioural response of little penguins (Eudyptula minor) that were naïve to human activity over 30 min of capture and handling. We assessed relationships between corticosterone secretion, behaviour, sex and time of day in order to characterize the determinants of the natural stress response. We then compared the response of these naïve penguins with the responses of female little penguins that had been exposed to research activity (bimonthly nest check and weighing) and to both research activity (monthly nest check and weighing) and evening viewing by tourists. We found that corticosterone concentrations increased significantly over 30 min of capture, with naïve penguins demonstrating a more acute stress response during the day than at night. Penguins that had previously been exposed to handling at the research and research/visitor sites showed elevated corticosterone concentrations and consistently more aggressive behaviour after 30 min compared with naïve birds, although there were no significant differences in baseline corticosterone concentrations. Our findings demonstrate that these little penguins have not habituated to routine capture, but rather mount a heightened physiological and behavioural response to handling by humans. Less invasive research monitoring techniques, such as individual identification with PIT tags and automatic recording and weighing, and a reduction in handling during the day should be considered to mitigate some of the potentially negative effects of disturbance. Given the paucity of data on the long-term consequences of heightened stress on animal physiology, our study highlights the need for further investigation of the relationship between the corticosterone stress response and fitness outcomes, such as breeding success and survival.

High sea surface temperatures driven by a strengthening current reduce foraging success by penguins.

The world's oceans are undergoing rapid, regionally specific warming. Strengthening western boundary currents play a role in this phenomenon, with sea surface temperatures (SST) in their paths rising faster than the global average. To understand how dynamic oceanography influences food availability in these ocean warming "hotspots", we use a novel prey capture signature derived from accelerometry to understand how the warm East Australian Current shapes foraging success by a meso-predator, the little penguin. This seabird feeds on low trophic level species that are sensitive to environmental change. We found that in 2012, prey capture success by penguins was high when SST was low relative to the long-term mean. In 2013 prey capture success was low, coincident with an unusually strong penetration of warm water. Overall there was an optimal temperature range for prey capture around 19-21 °C, with lower success at both lower and higher temperatures, mirroring published relationships between commercial sardine catch and SST. Spatially, higher SSTs corresponded to a lower probability of penguins using an area, and lower prey capture success. These links between high SST and reduced prey capture success by penguins suggest negative implications for future resource availability in a system dominated by a strengthening western boundary current.

Musculoskeletal lymphoma: MRI of bone or soft tissue presentations.

AIM: To assess the MRI findings of musculoskeletal lymphoma primarily presenting clinically as a bone lesion or soft tissue mass. METHODS: Magnetic resonance imaging of 23 cases of musculoskeletal lymphoma were retrospectively reviewed. Features assessed included tumour location, morphology, signal intensity (SI) characteristics, cortical destruction, involvement of multiple anatomic compartments, encasement of adjacent neurovascular structures/tendons and subcutaneous oedema. RESULTS: Osseous lesions were typically poorly defined and hypointense on T1-weighted imaging. T2-weighted SI was usually heterogeneous, with 54% of cases having a 'mosaic' pattern of marrow replacement. Ninety-two per cent of osseous tumours had cortical abnormalities, most commonly a permeative pattern. A periosseous soft tissue cuff was present in 46% of cases while 38% had a more significant extraosseous component. All cases of soft tissue lymphoma were iso-/slightly hyperintense to muscle on T1-weighted images and hyperintense on T2-weighted images. Multicompartment involvement by extraosseous tumour was present in 75% of cases, and 67% had subcutaneous oedema. Eighty-three per cent of soft tissue tumours showed encasement of adjacent structures. Multifocal lymphoma had similar morphology and SI characteristics to single-site lesions. Histopathologically, there were 21 cases of non-Hodgkin's lymphoma and two of Hodgkin's lymphoma. CONCLUSION: Magnetic resonance imaging features of primary osseous lymphoma include T2 heterogeneity, a periosseous soft tissue cuff or a more substantial mass, and cortical disruption often disproportionate to the extent of extraosseous tumour. Features characteristic of soft tissue lymphoma include relative homogeneity on T1- and T2-weighted imaging, multicompartment involvement and encasement of neurovascular structures.