Benjamin D. Best

An index to assess the health and benefits of the global ocean

The ocean plays a critical role in supporting human well-being, from providing food, livelihoods and recreational opportunities to regulating the global climate. Sustainable management aimed at maintaining the flow of a broad range of benefits from the ocean requires a comprehensive and quantitative method to measure and monitor the health of coupled human–ocean systems. We created an index comprising ten diverse public goals for a healthy coupled human–ocean system and calculated the index for every coastal country. Globally, the overall index score was 60 out of 100 (range 36–86), with developed countries generally performing better than developing countries, but with notable exceptions. Only 5% of countries scored higher than 70, whereas 32% scored lower than 50. The index provides a powerful tool to raise public awareness, direct resource management, improve policy and prioritize scientific research.

Understanding movement data and movement processes: current and emerging directions

Animal movement has been the focus on much theoretical and empirical work in ecology over the last 25 years. By studying the causes and consequences of individual movement, ecologists have gained greater insight into the behavior of individuals and the spatial dynamics of populations at increasingly higher levels of organization. In particular, ecologists have focused on the interaction between individuals and their environment in an effort to understand future impacts from habitat loss and climate change. Tools to examine this interaction have included: fractal analysis, first passage time, Lévy flights, multi-behavioral analysis, hidden markov models, and state-space models. Concurrent with the development of movement models has been an increase in the sophistication and availability of hierarchical bayesian models. In this review we bring these two threads together by using hierarchical structures as a framework for reviewing individual models. We synthesize emerging themes in movement ecology, and propose a new hierarchical model for animal movement that builds on these emerging themes. This model moves away from traditional random walks, and instead focuses inference on how moving animals with complex behavior interact with their landscape and make choices about its suitability.

Marine Geospatial Ecology Tools: An integrated framework for ecological geoprocessing with ArcGIS, Python, R, MATLAB, and C++

With the arrival of GPS, satellite remote sensing, and personal computers, the last two decades have witnessed rapid advances in the field of spatially-explicit marine ecological modeling. But with this innovation has come complexity. To keep up, ecologists must master multiple specialized software packages, such as ArcGIS for display and manipulation of geospatial data, R for statistical analysis, and MATLAB for matrix processing. This requires a costly investment of time and energy learning computer programming, a high hurdle for many ecologists. To provide easier access to advanced analytic methods, we developed Marine Geospatial Ecology Tools (MGET), an extensible collection of powerful, easy-to-use, open-source geoprocessing tools that ecologists can invoke from ArcGIS without resorting to computer programming. Internally, MGET integrates Python, R, MATLAB, and C++, bringing the power of these specialized platforms to tool developers without requiring developers to orchestrate the interoperability between them. In this paper, we describe MGETs software architecture and the tools in the collection. Next, we present an example application: a habitat model for Atlantic spotted dolphin (Stenella frontalis) that predicts dolphin presence using a statistical model fitted with oceanographic predictor variables. We conclude by discussing the lessons we learned engineering a highly integrated tool framework.

Dynamic habitat models: using telemetry data to project fisheries bycatch

Fisheries bycatch is a recognized threat to marine megafauna. Addressing bycatch of pelagic species however is challenging owing to the dynamic nature of marine environments and vagility of these organisms. In order to assess the potential for species to overlap with fisheries, we propose applying dynamic habitat models to determine relative probabilities of species occurrence for specific oceanographic conditions. We demonstrate this approach by modelling habitats for Laysan (Phoebastria immutabilis) and black-footed albatrosses (Phoebastria nigripes) using telemetry data and relating their occurrence probabilities to observations of Hawaii-based longline fisheries in 1997–2000. We found that modelled habitat preference probabilities of black-footed albatrosses were high within some areas of the fishing range of the Hawaiian fleet and such preferences were important in explaining bycatch occurrence. Conversely, modelled habitats of Laysan albatrosses overlapped little with Hawaii-based longline fisheries and did little to explain the bycatch of this species. Estimated patterns of albatross habitat overlap with the Hawaiian fleet corresponded to bycatch observations: black-footed albatrosses were more frequently caught in this fishery despite being 10 times less abundant than Laysan albatrosses. This case study demonstrates that dynamic habitat models based on telemetry data may help to project interactions with pelagic animals relative to environmental features and that such an approach can serve as a tool to guide conservation and management decisions.

Are all seeds equal? Spatially explicit comparisons of seed fall and sapling recruitment in a tropical forest

Understanding demographic transitions may provide the key to explain the high diversity of tropical tree communities. In a faunally intact Amazonian forest, we compared the spatial distribution of saplings of 15 common tree species with patterns of conspecific seed fall, and examined the seed-to-sapling transition in relation to locations of conspecific trees. In all species, the spatial pattern of sapling recruitment bore no resemblance to predicted distributions based on the density of seed fall. Seed efficiency (the probability of a seed producing a sapling) is strongly correlated with distance from large conspecific trees, with a >30-fold multiplicative increase between recruitment zones that are most distant vs. proximal to conspecific adults. The striking decoupling of sapling recruitment and conspecific seed density patterns indicates near-complete recruitment failure in areas of high seed density located around reproductive adults. Our results provide strong support for the spatially explicit predictions of the Janzen-Connell hypothesis.

Geospatial web services within a scientific workflow: Predicting marine mammal habitats in a dynamic environment

Abstract Our ability to inform conservation and management of species is fundamentally limited by the availability of relevant biogeographic data, use of statistically robust predictive models, and presentation of results to decision makers. Despite the ubiquity of presence-only models, where available, survey effort should be included in the modeling process to limit spatial bias. The biogeographic archive therefore should be able to store and serve related spatial information such as lines of survey effort or polygons of the study area, best accomplished through geospatial web services such as the Open Geospatial Consortium (OGC) Web Feature Service (WFS). Ideally data could then be easily fetched by modelers into a scientific workflow, providing a visually intuitive, modular, reusable canvas for linking analytical processes without the need to code. Species distribution model results should be easily accessible to decision makers, such as through a web-based spatial decision support system (SDSS). With these principles in mind, we describe our progress to date serving marine animal biogeographic data from OBIS-SEAMAP ( http://seamap.env.duke.edu ), and consuming the data for predictive environmental modeling of cetaceans. Using geospatial web services to automate the scientific workflow process, marine mammal observations from OBIS-SEAMAP are used to sample through date-synchronous remotely sensed satellite data for building multivariate habitat models using a variety of statistical techniques (GLM, GAM, and CART). We developed custom scientific workflows using ESRI Model Builder, ArcGIS geoprocessor, R statistical package, Python scripting language, PostGIS geodatabase, and UMN MapServer. These model outputs are then passed to an SDSS with spatial summary capability. Custom products will be open-source and freely available. In the future, we hope to integrate technologies such as OGC WCS, OPeNDAP, and Kepler. The principles and lessons described here can be broadly applied to serving biogeographic data, species distribution modeling, and decision support within the ecological informatics community.

Patterns and Emerging Trends in Global Ocean Health

International and regional policies aimed at managing ocean ecosystem health need quantitative and comprehensive indices to synthesize information from a variety of sources, consistently measure progress, and communicate with key constituencies and the public. Here we present the second annual global assessment of the Ocean Health Index, reporting current scores and annual changes since 2012, recalculated using updated methods and data based on the best available science, for 221 coastal countries and territories. The Index measures performance of ten societal goals for healthy oceans on a quantitative scale of increasing health from 0 to 100, and combines these scores into a single Index score, for each country and globally. The global Index score improved one point (from 67 to 68), while many country-level Index and goal scores had larger changes. Per-country Index scores ranged from 41–95 and, on average, improved by 0.06 points (range -8 to +12). Globally, average scores increased for individual goals by as much as 6.5 points (coastal economies) and decreased by as much as 1.2 points (natural products). Annual updates of the Index, even when not all input data have been updated, provide valuable information to scientists, policy makers, and resource managers because patterns and trends can emerge from the data that have been updated. Changes of even a few points indicate potential successes (when scores increase) that merit recognition, or concerns (when scores decrease) that may require mitigative action, with changes of more than 10–20 points representing large shifts that deserve greater attention. Goal scores showed remarkably little covariance across regions, indicating low redundancy in the Index, such that each goal delivers information about a different facet of ocean health. Together these scores provide a snapshot of global ocean health and suggest where countries have made progress and where a need for further improvement exists.

Habitat-based cetacean density models for the U.S. Atlantic and Gulf of Mexico

Cetaceans are protected worldwide but vulnerable to incidental harm from an expanding array of human activities at sea. Managing potential hazards to these highly-mobile populations increasingly requires a detailed understanding of their seasonal distributions and habitats. Pursuant to the urgent need for this knowledge for the U.S. Atlantic and Gulf of Mexico, we integrated 23 years of aerial and shipboard cetacean surveys, linked them to environmental covariates obtained from remote sensing and ocean models, and built habitat-based density models for 26 species and 3 multi-species guilds using distance sampling methodology. In the Atlantic, for 11 well-known species, model predictions resembled seasonal movement patterns previously suggested in the literature. For these we produced monthly mean density maps. For lesser-known taxa, and in the Gulf of Mexico, where seasonal movements were less well described, we produced year-round mean density maps. The results revealed high regional differences in small delphinoid densities, confirmed the importance of the continental slope to large delphinoids and of canyons and seamounts to beaked and sperm whales, and quantified seasonal shifts in the densities of migratory baleen whales. The density maps, freely available online, are the first for these regions to be published in the peer-reviewed literature.

A Regional-Scale Ocean Health Index for Brazil

Brazil has one of the largest and fastest growing economies and one of the largest coastlines in the world, making human use and enjoyment of coastal and marine resources of fundamental importance to the country. Integrated assessments of ocean health are needed to understand the condition of a range of benefits that humans derive from marine systems and to evaluate where attention should be focused to improve the health of these systems. Here we describe the first such assessment for Brazil at both national and state levels. We applied the Ocean Health Index framework, which evaluates ten public goals for healthy oceans. Despite refinements of input data and model formulations, the national score of 60 (out of 100) was highly congruent with the previous global assessment for Brazil of 62. Variability in scores among coastal states was most striking for goals related to mariculture, protected areas, tourism, and clean waters. Extractive goals, including Food Provision, received low scores relative to habitat-related goals, such as Biodiversity. This study demonstrates the applicability of the Ocean Health Index at a regional scale, and its usefulness in highlighting existing data and knowledge gaps and identifying key policy and management recommendations. To improve Brazils ocean health, this study suggests that future actions should focus on: enhancing fisheries management, expanding marine protected areas, and monitoring coastal habitats.

Assessing the Health of the U.S. West Coast with a Regional-Scale Application of the Ocean Health Index

Management of marine ecosystems increasingly demands comprehensive and quantitative assessments of ocean health, but lacks a tool to do so. We applied the recently developed Ocean Health Index to assess ocean health in the relatively data-rich US west coast region. The overall region scored 71 out of 100, with sub-regions scoring from 65 (Washington) to 74 (Oregon). Highest scoring goals included tourism and recreation (99) and clean waters (87), while the lowest scoring goals were sense of place (48) and artisanal fishing opportunities (57). Surprisingly, even in this well-studied area data limitations precluded robust assessments of past trends in overall ocean health. Nonetheless, retrospective calculation of current status showed that many goals have declined, by up to 20%. In contrast, near-term future scores were on average 6% greater than current status across all goals and sub-regions. Application of hypothetical but realistic management scenarios illustrate how the Index can be used to predict and understand the tradeoffs among goals and consequences for overall ocean health. We illustrate and discuss how this index can be used to vet underlying assumptions and decisions with local stakeholders and decision-makers so that scores reflect regional knowledge, priorities and values. We also highlight the importance of ongoing and future monitoring that will provide robust data relevant to ocean health assessment.