Predictive models are central to many scientific disciplines and vital for informing management in a rapidly changing world. However, limited understanding of the accuracy and precision of models transferred to novel conditions (their 'transferability') undermines confidence in their predictions. Here, 50 experts identified priority knowledge gaps which, if filled, will most improve model transfers. These are summarized into six technical and six fundamental challenges, which underlie the combined need to intensify research on the determinants of ecological predictability, including species traits and data quality, and develop best practices for transferring models. Of high importance is the identification of a widely applicable set of transferability metrics, with appropriate tools to quantify the sources and impacts of prediction uncertainty under novel conditions. Predicting the UnknownPredictions facilitate the formulation of quantitative, testable hypotheses that can be refined and validated empirically [1]. Predictive models have thus become ubiquitous in numerous scientific disciplines, including ecology [2], where they provide means for mapping species distributions, explaining population trends, or quantifying the risks of biological invasions and disease outbreaks (e.g., [3,4]). The practical value of predictive models in supporting policy and decision making has therefore grown rapidly (Box 1) [5]. With that has come an increasing desire to predict (see Glossary) the state of ecological features (e.g., species, habitats) and our likely impacts upon them [5], prompting a shift from explanatory models to anticipatory predictions [2]. However, in many situations, severe data deficiencies preclude the development of specific models, and the collection of new data can be prohibitively costly or simply impossible [6]. It is in this context that interest in transferable models (i.e., those that can be legitimately projected beyond the spatial and temporal bounds of their underlying data [7]) has grown.Transferred models must balance the tradeoff between estimation and prediction bias and variance (homogenization versus nontransferability, sensu [8]). Ultimately, models that can Highlights Models transferred to novel conditions could provide predictions in data-poor scenarios, contributing to more informed management decisions.The determinants of ecological predictability are, however, still insufficiently understood.Predictions from transferred ecological models are affected by species' traits, sampling biases, biotic interactions, nonstationarity, and the degree of environmental dissimilarity between reference and target systems.We synthesize six technical and six fundamental challenges that, if resolved, will catalyze practical and conceptual advances in model transfers.We propose that the most immediate obstacle to improving understanding lies in the absence of a widely applicable set of metrics for assessing transferability, and that encouraging the development of models grounded in well-established mech...

Dynamic management approaches protect endangered bycatch species but with much greater efficiency than existing static closures.

Overfishing is arguably the greatest ecological threat facing the oceans, yet catches of many highly migratory fishes including oceanic sharks remain largely unregulated with poor monitoring and data reporting. Oceanic shark conservation is hampered by basic knowledge gaps about where sharks aggregate across population ranges and precisely where they overlap with fishers. Using satellite tracking data from six shark species across the North Atlantic, we show that pelagic sharks occupy predictable habitat hotspots of high space use. Movement modeling showed sharks preferred habitats characterized by strong sea surface-temperature gradients (fronts) over other available habitats. However, simultaneous Global Positioning System (GPS) tracking of the entire Spanish and Portuguese longline-vessel fishing fleets show an 80% overlap of fished areas with hotspots, potentially increasing shark susceptibility to fishing exploitation. Regions of high overlap between oceanic tagged sharks and longliners included the North Atlantic Current/Labrador Current convergence zone and the Mid-Atlantic Ridge southwest of the Azores. In these main regions, and subareas within them, shark/vessel co-occurrence was spatially and temporally persistent between years, highlighting how broadly the fishing exploitation efficiently "tracks" oceanic sharks within their space-use hotspots year-round. Given this intense focus of longliners on shark hotspots, our study argues the need for international catch limits for pelagic sharks and identifies a future role of combining fine-scale fish and vessel telemetry to inform the ocean-scale management of fisheries.animal telemetry | distribution | conservation | fisheries | predator-prey O ceanic pelagic sharks are iconic top predators with relatively low resilience to exploitation (1-3), yet many tens of millions of individuals are caught each year by high-seas fisheries (2) with significant reductions in catch rates documented for many species (4-6). This level of exploitation is especially problematic because the harvest of oceanic sharks remains largely unregulated (2, 7). For the majority of shark species that make up more than 95% of oceanic shark catches, no international or bilateral harvest limits have been imposed (2, 7). Consequently, analysis indicates that extinction risk in oceanic and coastal sharks and rays is higher than for most other vertebrates (3). Accordingly, there is a critical need and concern for improved management and conservation of oceanic sharks.Management action for oceanic sharks such as catch quotas, size limits, and/or area closures (i.e., marine protected areas, MPAs) is hampered by a paucity of high-quality data on total catches, landings, species identification, catch locations, and the susceptibility of sharks to fisheries (2, 4, 7). In addition, poor recordkeeping, a lack of reporting or deliberate underreporting of pelagic shark catches by the high seas longlining fleet and/or fishing nations (7), contributes to poor data quality that can lead to increased unce...

Summary1. Identifying priority areas for marine vertebrate conservation is complex because species of conservation concern are highly mobile, inhabit dynamic habitats and are difficult to monitor. 2. Many marine vertebrates are known to associate with oceanographic fronts -physical interfaces at the transition between water masses -for foraging and migration, making them important candidate sites for conservation. Here, we review associations between marine vertebrates and fronts and how they vary with scale, regional oceanography and foraging ecology. 3. Accessibility, spatiotemporal predictability and relative productivity of front-associated foraging habitats are key aspects of their ecological importance. Predictable mesoscale (10s-100s km) regions of persistent frontal activity ('frontal zones') are particularly significant. 4. Frontal zones are hotspots of overlap between critical habitat and spatially explicit anthropogenic threats, such as the concentration of fisheries activity. As such, they represent tractable conservation units, in which to target measures for threat mitigation. 5. Front mapping via Earth observation (EO) remote sensing facilitates identification and monitoring of these hotspots of vulnerability. Seasonal or climatological products can locate biophysical hotspots, while near-real-time front mapping augments the suite of tools supporting spatially dynamic ocean management. 6. Synthesis and applications. Frontal zones are ecologically important for mobile marine vertebrates. We surmise that relative accessibility, predictability and productivity are key biophysical characteristics of ecologically significant frontal zones in contrasting oceanographic regions. Persistent frontal zones are potential priority conservation areas for multiple marine vertebrate taxa and are easily identifiable through front mapping via EO remote sensing. These insights are useful for marine spatial planning and marine biodiversity conservation, both within Exclusive Economic Zones and in the open oceans.

The rapid pace of environmental change in the Anthropocene necessitates the development of a new suite of tools for measuring ecosystem dynamics. Sentinel species can provide insight into ecosystem function, identify hidden risks to human health, and predict future change. As sentinels, marine apex (top) predators offer a unique perspective into ocean processes, given that they can move across ocean basins and amplify trophic information across multiple spatiotemporal scales. Because use of the terms “ecosystem sentinel” and “climate sentinel” has proliferated in the scientific literature, there is a need to identify the properties that make marine predators effective sentinels. We provide a clear definition of the term “sentinel”, review the attributes of species identified as sentinels, and describe how a suite of such sentinels could strengthen our understanding and management of marine ecosystems. We contend that the use of marine predators as ecosystem sentinels will enable rapid response and adaptation to ecosystem variability and change.

The oceanographic drivers of marine vertebrate habitat use are poorly understood yet fundamental to our knowledge of marine ecosystem functioning. Here, we use composite front mapping and high-resolution GPS tracking to determine the significance of mesoscale oceanographic fronts as physical drivers of foraging habitat selection in northern gannets Morus bassanus. We tracked 66 breeding gannets from a Celtic Sea colony over 2 years and used residence time to identify area-restricted search (ARS) behaviour. Composite front maps identified thermal and chlorophyll-a mesoscale fronts at two different temporal scales-(i) contemporaneous fronts and (ii) seasonally persistent frontal zones. Using generalized additive models (GAMs), with generalized estimating equations (GEE-GAMs) to account for serial autocorrelation in tracking data, we found that gannets do not adjust their behaviour in response to contemporaneous fronts. However, ARS was more likely to occur within spatially predictable, seasonally persistent frontal zones (GAMs). Our results provide proof of concept that composite front mapping is a useful tool for studying the influence of oceanographic features on animal movements. Moreover, we highlight that frontal persistence is a crucial element of the formation of pelagic foraging hotspots for mobile marine vertebrates.

Commercial capture fisheries produce huge quantities of offal, as well as undersized and unwanted catch in the form of discards. Declines in global catches and legislation to ban discarding will significantly reduce discards, but this subsidy supports a large scavenger community. Understanding the potential impact of declining discards for scavengers should feature in an eco-system based approach to fisheries management, but requires greater knowledge of scavenger/fishery interactions. Here we use bird-borne cameras, in tandem with GPS loggers, to provide a unique view of seabird/fishery interactions. 20,643 digital images (one min−1) from ten bird-borne cameras deployed on central place northern gannets Morus bassanus revealed that all birds photographed fishing vessels. These were large (>15 m) boats, with no small-scale vessels. Virtually all vessels were trawlers, and gannets were almost always accompanied by other scavenging birds. All individuals exhibited an Area-Restricted Search (ARS) during foraging, but only 42% of ARS were associated with fishing vessels, indicating much ‘natural’ foraging. The proportion of ARS behaviours associated with fishing boats were higher for males (81%) than females (30%), although the reasons for this are currently unclear. Our study illustrates that fisheries form a very important component of the prey-landscape for foraging gannets and that a discard ban, such as that proposed under reforms of the EU Common Fisheries Policy, may have a significant impact on gannet behaviour, particularly males. However, a continued reliance on ‘natural’ foraging suggests the ability to switch away from scavenging, but only if there is sufficient food to meet their needs in the absence of a discard subsidy.

Understanding and predicting the responses of wide‐ranging marine predators such as cetaceans, seabirds, sharks, turtles, pinnipeds and large migratory fish to dynamic oceanographic conditions requires habitat‐based models that can sufficiently capture their environmental preferences. Marine ecosystems are inherently dynamic, and animal–environment interactions are known to occur over multiple, nested spatial and temporal scales. The spatial resolution and temporal averaging of environmental data layers are therefore key considerations in modelling the environmental determinants of habitat selection. The utility of environmental data contemporaneous to animal presence or movement (e.g. daily, weekly), versus synoptic products (monthly, seasonal, climatological) is currently debated, as are the trade‐offs between near real‐time, high resolution and composite (i.e. synoptic, cloud‐free) data fields. Using movement simulations with built‐in environmental preferences in combination with both modelled and remotely‐sensed (ROMS, MODIS‐Aqua) sea surface temperature (SST) fields, we explore the effects of spatial and temporal resolution (3–111 km, daily–climatological) in predictive habitat models. Results indicate that models fitted using seasonal or climatological data fields can introduce bias in presence‐availability designs based upon animal movement datasets, particularly in highly dynamic oceanographic domains. These effects were pronounced where models were constructed using seasonal or climatological fields of coarse (> 0.25 degree) spatial resolution. However, cloud obstruction can lead to significant information loss in remotely‐sensed data fields. We found that model accuracy decreased substantially above 70% data loss. In cloudy regions, weekly or monthly environmental data fields may therefore be preferable. These findings have important implications for marine resource management, particularly in identifying key habitats for populations of conservation concern, and in forecasting climate‐mediated ecosystem changes.