The Pelagic Species Trait Database, an open data resource to support trait-based ocean research.

Trait-based frameworks are increasingly used for predicting how ecological communities respond to ongoing global change. As species range shifts result in novel encounters between predators and prey, identifying prey 'guilds', based on a suite of shared traits, can distill complex species interactions, and aid in predicting food web dynamics. To support advances in trait-based research in open-ocean systems, we present the Pelagic Species Trait Database, an extensive resource documenting functional traits of 529 pelagic fish and invertebrate species in a single, open-source repository. We synthesized literature sources and online resources, conducted morphometric analysis of species images, as well as laboratory analyses of trawl-captured specimens to collate traits describing 1) habitat use and behavior, 2) morphology, 3) nutritional quality, and 4) population status information. Species in the dataset primarily inhabit the California Current system and broader NE Pacific Ocean, but also includes pelagic species known to be consumed by top ocean predators from other ocean basins. The aim of this dataset is to enhance the use of trait-based approaches in marine ecosystems and for predator populations worldwide.

The effect of reef morphology on coral recruitment at multiple spatial scales.

Coral reefs are in decline worldwide, making it increasingly important to promote coral recruitment in new or degraded habitat. Coral reef morphology-the structural form of reef substrate-affects many aspects of reef function, yet the effect of reef morphology on coral recruitment is not well understood. We used structure-from-motion photogrammetry and airborne remote sensing to measure reef morphology (rugosity, curvature, slope, and fractal dimension) across a broad continuum of spatial scales and evaluated the effect of morphology on coral recruitment in three broadcast-spawning genera. We also measured the effect of other environmental and biotic factors such as fish density, adult coral cover, hydrodynamic larval import, and depth on coral recruitment. All variables combined explained 72% of coral recruitment in the study region. Coarse reef rugosity and curvature mapped at ≥2 m spatial resolution-such as large colonies, knolls, and boulders-were positively correlated with coral recruitment, explaining 22% of variation in recruitment. Morphology mapped at finer scales (≤32 cm resolution) was not significant. Hydrodynamic larval import was also positively related to coral recruitment in Porites and Montipora spp., and grazer fish density was linked to significantly lower recruitment in all genera. In addition, grazer density, reef morphology, and hydrodynamic import had differential effects on coral genera, reflecting genus-specific life history traits, and model performance was lower in gonochoric species. Overall, coral reef morphology is a key indicator of recruitment potential that can be detected by remote sensing, allowing potential larval sinks to be identified and factored into restoration actions.

The influence of social cues on timing of animal migrations.

Animal migration plays a central role in many ecological and evolutionary processes, yet migratory populations worldwide are increasingly threatened. Adjusting migration timing to match ecosystem phenology is key to survival in dynamic and changing ecosystems, especially in an era of human-induced rapid environmental change. Social cues are increasingly recognized as major components of migratory behaviour, yet a comprehensive understanding of how social cues influence the timing of animal migrations remains elusive. Here, we introduce a framework for assessing the role that social cues, ranging from explicit (for example, active cueing) to implicit (for example, competition), play in animals' temporal migration decisions across a range of scales. By applying this theoretical lens to a systematic review of published literature, we show that a broad range of social cues frequently mediate migration timing at a range of temporal scales and across highly diverse migratory taxa. We further highlight that while rarely documented, several social cue mechanisms (for example, social learning and density dependency) play important adaptive roles in matching migration timing with ecosystem dynamics. Thus, social cues play a fundamental role in migration timing, with potentially widespread ecological consequences and implications for the conservation of migratory species. Furthermore, our analysis establishes a theoretical basis on which to evaluate future findings on the role of both conspecific and interspecific social cues in this intersection of behavioural ecology and global change biology.

Trait-based approaches to global change ecology: moving from description to prediction.

Trait-based approaches are increasingly recognized as a tool for understanding ecosystem re-assembly and function under intensifying global change. Here we synthesize trait-based research globally (n = 865 studies) to examine the contexts in which traits may be used for global change prediction. We find that exponential growth in the field over the last decade remains dominated by descriptive studies of terrestrial plant morphology, highlighting significant opportunities to expand trait-based thinking across systems and taxa. Very few studies (less than 3%) focus on predicting ecological effects of global change, mostly in the past 5 years and via singular traits that mediate abiotic limits on species distribution. Beyond organism size (the most examined trait), we identify over 2500 other morphological, physiological, behavioural and life-history traits known to mediate environmental filters of species' range and abundance as candidates for future predictive global change work. Though uncommon, spatially explicit process models-which mechanistically link traits to changes in organism distributions and abundance-are among the most promising frameworks for holistic global change prediction at scales relevant for conservation decision-making. Further progress towards trait-based forecasting requires addressing persistent barriers including (1) matching scales of multivariate trait and environment data to focal processes disrupted by global change, and (2) propagating variation in trait and environmental parameters throughout process model functions using simulation.

Social relationship dynamics mediate climate impacts on income inequality: evidence from the Mexican Humboldt squid fishery.

Small-scale fisheries are critically important for livelihoods around the world, particularly in tropical regions. However, climate variability and anthropogenic climate change may seriously impact small-scale fisheries by altering the abundance and distribution of target species. Social relationships between fishery users, such as fish traders, can determine how each individual responds and is affected by changes in fisheries. These informal cooperative and competitive relationships provide access, support, and incentives for fishing and affect the distribution of benefits. Yet, individuals' actions and impacts on individuals are often the primary focus of the economic analyses informing small-scale fisheries' formal management. This focus dismisses relevant social relationships. We argue that this leads to a disconnect between reality and its model representation used in formal management, which may reduce formal fisheries management's efficiency and efficacy and potentially trigger adverse consequences. Here, we examine this argument by comparing the predictions of a simple bioeconomic fishery model with those of a social-ecological model that incorporates the dynamics of cooperative relationships between fish traders. We illustrate model outcomes using an empirical case study in the Mexican Humboldt squid fishery. We find that (1) the social-ecological model with relationship dynamics substantially improves accuracy in predicting observed fishery variables to the simple bioeconomic model. (2) Income inequality outcomes are associated with changes in cooperative trade relationships. When environmental temperature is included in the model as a driver of species production dynamics, we find that climate-driven temperature variability drives a decline in catch that, in turn, reduce fishers' income. We observe an offset of this loss in income by including cooperative relationships between fish traders (oligopoly) in the model. These relationships break down following species distribution changes and result in an increase in prices fishers receive. Finally, (3) our social-ecological model simulations show that the current fishery development program, which seeks to increase fishers' income through an increase in domestic market demand, is supported by predictions from the simple bioeconomic model, may increase income inequality between fishers and traders. Our findings highlight the real and urgent need to re-think fisheries management models in the context of small-scale fisheries and climate change worldwide to encompass social relationship dynamics. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at (10.1007/s10113-021-01747-5).

Rethinking megafauna.

Concern for megafauna is increasing among scientists and non-scientists. Many studies have emphasized that megafauna play prominent ecological roles and provide important ecosystem services to humanity. But, what precisely are 'megafauna'? Here, we critically assess the concept of megafauna and propose a goal-oriented framework for megafaunal research. First, we review definitions of megafauna and analyse associated terminology in the scientific literature. Second, we conduct a survey among ecologists and palaeontologists to assess the species traits used to identify and define megafauna. Our review indicates that definitions are highly dependent on the study ecosystem and research question, and primarily rely on ad hoc size-related criteria. Our survey suggests that body size is crucial, but not necessarily sufficient, for addressing the different applications of the term megafauna. Thus, after discussing the pros and cons of existing definitions, we propose an additional approach by defining two function-oriented megafaunal concepts: 'keystone megafauna' and 'functional megafauna', with its variant 'apex megafauna'. Assessing megafauna from a functional perspective could challenge the perception that there may not be a unifying definition of megafauna that can be applied to all eco-evolutionary narratives. In addition, using functional definitions of megafauna could be especially conducive to cross-disciplinary understanding and cooperation, improvement of conservation policy and practice, and strengthening of public perception. As megafaunal research advances, we encourage scientists to unambiguously define how they use the term 'megafauna' and to present the logic underpinning their definition.

Parsing human and biophysical drivers of coral reef regimes.

Coral reefs worldwide face unprecedented cumulative anthropogenic effects of interacting local human pressures, global climate change and distal social processes. Reefs are also bound by the natural biophysical environment within which they exist. In this context, a key challenge for effective management is understanding how anthropogenic and biophysical conditions interact to drive distinct coral reef configurations. Here, we use machine learning to conduct explanatory predictions on reef ecosystems defined by both fish and benthic communities. Drawing on the most spatially extensive dataset available across the Hawaiian archipelago-20 anthropogenic and biophysical predictors over 620 survey sites-we model the occurrence of four distinct reef regimes and provide a novel approach to quantify the relative influence of human and environmental variables in shaping reef ecosystems. Our findings highlight the nuances of what underpins different coral reef regimes, the overwhelming importance of biophysical predictors and how a reef's natural setting may either expand or narrow the opportunity space for management interventions. The methods developed through this study can help inform reef practitioners and hold promises for replication across a broad range of ecosystems.

Combining fish and benthic communities into multiple regimes reveals complex reef dynamics.

Coral reefs worldwide face an uncertain future with many reefs reported to transition from being dominated by corals to macroalgae. However, given the complexity and diversity of the ecosystem, research on how regimes vary spatially and temporally is needed. Reef regimes are most often characterised by their benthic components; however, complex dynamics are associated with losses and gains in both fish and benthic assemblages. To capture this complexity, we synthesised 3,345 surveys from Hawai'i to define reef regimes in terms of both fish and benthic assemblages. Model-based clustering revealed five distinct regimes that varied ecologically, and were spatially heterogeneous by island, depth and exposure. We identified a regime characteristic of a degraded state with low coral cover and fish biomass, one that had low coral but high fish biomass, as well as three other regimes that varied significantly in their ecology but were previously considered a single coral dominated regime. Analyses of time series data reflected complex system dynamics, with multiple transitions among regimes that were a function of both local and global stressors. Coupling fish and benthic communities into reef regimes to capture complex dynamics holds promise for monitoring reef change and guiding ecosystem-based management of coral reefs.

A dynamic ocean management tool to reduce bycatch and support sustainable fisheries.

Seafood is an essential source of protein for more than 3 billion people worldwide, yet bycatch of threatened species in capture fisheries remains a major impediment to fisheries sustainability. Management measures designed to reduce bycatch often result in significant economic losses and even fisheries closures. Static spatial management approaches can also be rendered ineffective by environmental variability and climate change, as productive habitats shift and introduce new interactions between human activities and protected species. We introduce a new multispecies and dynamic approach that uses daily satellite data to track ocean features and aligns scales of management, species movement, and fisheries. To accomplish this, we create species distribution models for one target species and three bycatch-sensitive species using both satellite telemetry and fisheries observer data. We then integrate species-specific probabilities of occurrence into a single predictive surface, weighing the contribution of each species by management concern. We find that dynamic closures could be 2 to 10 times smaller than existing static closures while still providing adequate protection of endangered nontarget species. Our results highlight the opportunity to implement near real-time management strategies that would both support economically viable fisheries and meet mandated conservation objectives in the face of changing ocean conditions. With recent advances in eco-informatics, dynamic management provides a new climate-ready approach to support sustainable fisheries.

Uncertainty analysis and robust areas of high and low modeled human impact on the global oceans.

Increasing anthropogenic pressure on marine ecosystems from fishing, pollution, climate change, and other sources is a big concern in marine conservation. Scientists have thus developed spatial models to map cumulative human impacts on marine ecosystems. However, these models are based on many assumptions and incorporate data that suffer from substantial incompleteness and inaccuracies. Rather than using a single model, we used Monte Carlo simulations to identify which parts of the oceans are subject to the most and least impact from anthropogenic stressors under 7 simulated sources of uncertainty (factors: e.g., missing stressor data and assuming linear ecosystem responses to stress). Most maps agreed that high-impact areas were located in the Northeast Atlantic, the eastern Mediterranean, the Caribbean, the continental shelf off northern West Africa, offshore parts of the tropical Atlantic, the Indian Ocean east of Madagascar, parts of East and Southeast Asia, parts of the northwestern Pacific, and many coastal waters. Large low-impact areas were located off Antarctica, in the central Pacific, and in the southern Atlantic. Uncertainty in the broad-scale spatial distribution of modeled human impact was caused by the aggregate effects of several factors, rather than being attributable to a single dominant source. In spite of the identified uncertainty in human-impact maps, they can-at broad spatial scales and in combination with other environmental and socioeconomic information-point to priority areas for research and management.

Characterizing habitat suitability for a central-place forager in a dynamic marine environment.

Characterizing habitat suitability for a marine predator requires an understanding of the environmental heterogeneity and variability over the range in which a population moves during a particular life cycle. Female California sea lions (Zalophus californianus) are central-place foragers and are particularly constrained while provisioning their young. During this time, habitat selection is a function of prey availability and proximity to the rookery, which has important implications for reproductive and population success. We explore how lactating females may select habitat and respond to environmental variability over broad spatial and temporal scales within the California Current System. We combine near-real-time remotely sensed satellite oceanography, animal tracking data (n = 72) from November to February over multiple years (2003-2009) and Generalized Additive Mixed Models (GAMMs) to determine the probability of sea lion occurrence based on environmental covariates. Results indicate that sea lion presence is associated with cool (<14°C), productive waters, shallow depths, increased eddy activity, and positive sea-level anomalies. Predictive habitat maps generated from these biophysical associations suggest winter foraging areas are spatially consistent in the nearshore and offshore environments, except during the 2004-2005 winter, which coincided with an El Niño event. Here, we show how a species distribution model can provide broadscale information on the distribution of female California sea lions during an important life history stage and its implications for population dynamics and spatial management.

Advancing the integration of spatial data to map human and natural drivers on coral reefs.

A major challenge for coral reef conservation and management is understanding how a wide range of interacting human and natural drivers cumulatively impact and shape these ecosystems. Despite the importance of understanding these interactions, a methodological framework to synthesize spatially explicit data of such drivers is lacking. To fill this gap, we established a transferable data synthesis methodology to integrate spatial data on environmental and anthropogenic drivers of coral reefs, and applied this methodology to a case study location-the Main Hawaiian Islands (MHI). Environmental drivers were derived from time series (2002-2013) of climatological ranges and anomalies of remotely sensed sea surface temperature, chlorophyll-a, irradiance, and wave power. Anthropogenic drivers were characterized using empirically derived and modeled datasets of spatial fisheries catch, sedimentation, nutrient input, new development, habitat modification, and invasive species. Within our case study system, resulting driver maps showed high spatial heterogeneity across the MHI, with anthropogenic drivers generally greatest and most widespread on O'ahu, where 70% of the state's population resides, while sedimentation and nutrients were dominant in less populated islands. Together, the spatial integration of environmental and anthropogenic driver data described here provides a first-ever synthetic approach to visualize how the drivers of coral reef state vary in space and demonstrates a methodological framework for implementation of this approach in other regions of the world. By quantifying and synthesizing spatial drivers of change on coral reefs, we provide an avenue for further research to understand how drivers determine reef diversity and resilience, which can ultimately inform policies to protect coral reefs.

Fit to predict? Eco-informatics for predicting the catchability of a pelagic fish in near real time.

The ocean is a dynamic environment inhabited by a diverse array of highly migratory species, many of which are under direct exploitation in targeted fisheries. The timescales of variability in the marine realm coupled with the extreme mobility of ocean-wandering species such as tuna and billfish complicates fisheries management. Developing eco-informatics solutions that allow for near real-time prediction of the distributions of highly mobile marine species is an important step towards the maturation of dynamic ocean management and ecological forecasting. Using 25 yr (1990-2014) of NOAA fisheries' observer data from the California drift gillnet fishery, we model relative probability of occurrence (presence-absence) and catchability (total catch per gillnet set) of broadbill swordfish Xiphias gladius in the California Current System. Using freely available environmental data sets and open source software, we explore the physical drivers of regional swordfish distribution. Comparing models built upon remotely sensed data sets with those built upon a data-assimilative configuration of the Regional Ocean Modelling System (ROMS), we explore trade-offs in model construction, and address how physical data can affect predictive performance and operational capacity. Swordfish catchability was found to be highest in deeper waters (>1,500 m) with surface temperatures in the 14-20°C range, isothermal layer depth (ILD) of 20-40 m, positive sea surface height (SSH) anomalies, and during the new moon (<20% lunar illumination). We observed a greater influence of mesoscale variability (SSH, wind speed, isothermal layer depth, eddy kinetic energy) in driving swordfish catchability (total catch) than was evident in predicting the relative probability of presence (presence-absence), confirming the utility of generating spatiotemporally dynamic predictions. Data-assimilative ROMS circumvent the limitations of satellite remote sensing in providing physical data fields for species distribution models (e.g., cloud cover, variable resolution, subsurface data), and facilitate broad-scale prediction of dynamic species distributions in near real time.

Ocean Research Priorities: Similarities and Differences among Scientists, Policymakers, and Fishermen in the United States.

Understanding and solving complex ocean conservation problems requires cooperation not just among scientific disciplines but also across sectors. A recently published survey that probed research priorities of marine scientists, when provided to ocean stakeholders, revealed some agreement on priorities but also illuminated key differences. Ocean acidification, cumulative impacts, bycatch effects, and restoration effectiveness were in the top 10 priorities for scientists and stakeholder groups. Significant priority differences were that scientists favored research questions about ocean acidification and marine protected areas; policymakers prioritized questions about habitat restoration, bycatch, and precaution; and fisheries sector resource users called for the inclusion of local ecological knowledge in policymaking. These results quantitatively demonstrate how different stakeholder groups approach ocean issues and highlight the need to incorporate other types of knowledge in the codesign of solutions-oriented research, which may facilitate cross-sectoral collaboration.

Avoiding a crisis of motivation for ocean management under global environmental change.

Climate change and ocean acidification are altering marine ecosystems and, from a human perspective, creating both winners and losers. Human responses to these changes are complex, but may result in reduced government investments in regulation, resource management, monitoring and enforcement. Moreover, a lack of peoples' experience of climate change may drive some towards attributing the symptoms of climate change to more familiar causes such as management failure. Taken together, we anticipate that management could become weaker and less effective as climate change continues. Using diverse case studies, including the decline of coral reefs, coastal defences from flooding, shifting fish stocks and the emergence of new shipping opportunities in the Arctic, we argue that human interests are better served by increased investments in resource management. But greater government investment in management does not simply mean more of "business-as-usual." Management needs to become more flexible, better at anticipating and responding to surprise, and able to facilitate change where it is desirable. A range of technological, economic, communication and governance solutions exists to help transform management. While not all have been tested, judicious application of the most appropriate solutions should help humanity adapt to novel circumstances and seek opportunity where possible.