Patrick N. Halpin

A Census of Marine Biodiversity Knowledge, Resources, and Future Challenges

The resources available for research are always limited. When setting priorities for research funding, governments, industry, and funding agencies must balance the demands of human health, food supply, and standards of living, against the less-tangible benefits of discovering more about the planets biodiversity. Scientists have discovered almost 2 million species indicating that we have made great gains in our knowledge of biodiversity. However, this knowledge may distract attention from the estimated four-fifths of species on Earth that remain unknown to science, many of them inhabiting our oceans [1], [2]. The worlds media still find it newsworthy when new species are discovered [1]. However, the extent of this taxonomic challenge no longer appears to be a priority in many funding agencies, perhaps because society and many scientists believe we have discovered most species, or that doing so is out of fashion except when new technologies are employed. Another symptom of this trend may be that the increased attention to novel methods available in molecular sciences is resulting in a loss of expertise and know-how in the traditional descriptive taxonomy of species [3]. The use of molecular techniques complements traditional methods of describing species but has not significantly increased the rate of discovery of new species (at least of fish), although it may help classify them [4]. At least in Europe, there was a mismatch between the number of species in a taxon and the number of people with expertise in it [5]. Unfortunately, because most species remain to be discovered in the most species-rich taxa [2], [5], [6], [7], there are then few experts to appreciate that this work needs to be done. Evidently, a global review of gaps in marine biodiversity knowledge and resources is overdue. History of discovering marine biodiversity Although the economic exploitation of marine resources dates back to prehistoric times, and historical documentation has existed since the third century B.C. with Aristotles contributions in the Mediterranean Sea (e.g. [8]), the establishment of systematic collections of marine organisms began only during the seventeenth and eighteenth centuries. Global marine biodiversity investigations at these times depended not only on the availability of expertise, but also on foreign policies of the colonial powers of the time. For those reasons, the specimens collected from several regions (e.g., Caribbean, Japan, South America, Africa) were mostly brought to Europe, where they were described, deposited in museum collections, and used for the production of marine biological monographs. These early publications contained descriptions and checklists of many marine species, such as molluscs, crustaceans, fishes, turtles, birds, and mammals (e.g. [9], [10], [11]). The history of research on marine biodiversity can generally be divided into three periods: early exploratory studies, local coastal “descriptive” studies, and large-scale multidisciplinary investigations and syntheses. These periods vary in timing by different seas and countries. The first exploratory studies in several regions (e.g., South America, Caribbean, South Africa, Pacific Ocean) took place from the mid-1700s until the late-1800s, in association with mainly European, North American, and Russian exploration expeditions, such as the Kamchatka Expedition in the 1740s, James Cooks voyages in the 1770s, the cruise of HMS Beagle in the 1830s, the voyage of HMS Challenger in the 1870s, and the first deep-sea investigations in the Mediterranean Sea [8], [9], [12], [13]. Pioneer investigations on deep-sea organisms were conducted in the Aegean Sea, where Forbes [14] noticed that sediments became progressively more impoverished in terms of biodiversity with increasing sampling depth. The azoic hypothesis proposed by Forbes suggested that life would be extinguished beyond 500 m depth, although a work published 68 years earlier provided indisputable evidence of the presence of life in the Gulf of Genoa at depths down to 1,000 m [15]. The taxonomists who described marine species at these times seldom collected specimens themselves in the field and, therefore, had only second-hand information about the distribution and ecology of the samples they received [4], [8]. Some of the early descriptions of tropical species thus do not even have the locality where the holotype or voucher material was collected (some examples in Chenu 1842–1853). The second period of regional studies was initiated by enhanced availability of research resources (experts, institutes, and vessels) in developing countries around the mid-1900s. The earliest institutions and research stations, many of which continue to operate, were founded in some areas as early as the late 1800s and early 1900s (e.g. [11], [16], [17]). Wide-scale establishment of laboratories in several continents (Europe, New Zealand, North and South America) have only been operational since the 1950s–1960s. The third stage, large-scale multidisciplinary investigations, has evolved since the 1990s, and is related to development and application of modern technologies and implementation of large, multinational research projects. Perhaps the largest of such investigations was the Census of Marine Life (Census).

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.

GLOBAL CLIMATE CHANGE AND NATURAL‐AREA PROTECTION: MANAGEMENT RESPONSES AND RESEARCH DIRECTIONS

During the past decade, our understanding of the potential risks that climate change poses to ecosystem function and natural-area protection has increased. Simulation studies of expected changes in species ranges and changes in ecosystem dynamics have indicated that rapidly changing climatic conditions could significantly thwart natural-area protection efforts at a global scale. In response to this potential threat, prescriptive policy and management recommendations have begun to emerge. These management responses include general guidelines for selecting new protected habitats, preemptive actions such as the development of connective corridor systems between protected areas, and active habitat management interventions. At present, many suggested natural-area management responses are only vaguely defined and have yet to be fully tested. To be effective, management responses must now be rigorously assessed with focused and practical ecological analysis. In this overview I examine the current state of resear...

Raster modelling of coastal flooding from sea-level rise

As rates of sea‐level rise continue to increase due to climate change, land planners require accurate spatial analyses on the extent and timing of coastal flooding and associated hazards. Digital elevation data used to evaluate coastal vulnerability to flooding are available at various horizontal and vertical resolutions. However, the quality of digital elevation models (DEM) used in environmental assessment can significantly affect the detection of topographic features and the magnitude of hydrological processes. We used lidar elevation data in coastal North Carolina, USA to investigate the effects of horizontal resolution and connectivity on the extent and timing of flooding from sea‐level rise. We found that the rate and extent of inundation were dependent on horizontal resolution and assumptions made on hydrological connectivity. The variation in flood extent was much larger (760 km2) at low sea‐level projections (<0.4 m) than at high sea‐level projections (>∼0.9 m, 114 km2) due to the effect of hydrological corrections on the coarse‐scale DEM and topographic complexity at low elevations. Lidar elevation data provide a significant advance in mapping potential coastal flooding, but the extent and timing of inundation are sensitive to horizontal resolution and the modelling of hydrological connectivity.

Forest gradient response in Sierran landscapes: the physical template

Vegetation pattern on landscapes is the manifestation of physical gradients, biotic response to these gradients, and disturbances. Here we focus on the physical template as it governs the distribution of mixed-conifer forests in Californias Sierra Nevada. We extended a forest simulation model to examine montane environmental gradients, emphasizing factors affecting the water balance in these summer-dry landscapes. The model simulates the soil moisture regime in terms of the interaction of water supply and demand: supply depends on precipitation and water storage, while evapotranspirational demand varies with solar radiation and temperature. The forest cover itself can affect the water balance via canopy interception and evapotranspiration. We simulated Sierran forests as slope facets, defined as gridded stands of homogeneous topographic exposure, and verified simulated gradient response against sample quadrats distributed across Sequoia National Park. We then performed a modified sensitivity analysis of abiotic factors governing the physical gradient. Importantly, the models sensitivity to temperature, precipitation, and soil depth varies considerably over the physical template, particularly relative to elevation. The physical drivers of the water balance have characteristic spatial scales that differ by orders of magnitude. Across large spatial extents, temperature and precipitation as defined by elevation primarily govern the location of the mixed conifer zone. If the analysis is constrained to elevations within the mixed-conifer zone, local topography comes into play as it influences drainage. Soil depth varies considerably at all measured scales, and is especially dominant at fine (within-stand) scales. Physical site variables can influence soil moisture deficit either by affecting water supply or water demand; these effects have qualitatively different implications for forest response. These results have clear implications about purely inferential approaches to gradient analysis, and bear strongly on our ability to use correlative approaches in assessing the potential responses of montane forests to anthropogenic climatic change.

Global patterns of marine mammal, seabird, and sea turtle bycatch reveal taxa-specific and cumulative megafauna hotspots

Significance Loss of megafauna, termed trophic downgrading, has been found to affect biotic interactions, disturbance regimes, species invasions, and nutrient cycling. One recognized cause in air-breathing marine megafauna is incidental capture or bycatch by fisheries. Characterizing megafauna bycatch patterns across large ocean regions is limited by data availability but essential to direct conservation and management resources. We use empirical data to identify the global distribution and magnitude of seabird, marine mammal, and sea turtle bycatch in three widely used fishing gears. We identify taxa-specific hotspots and find evidence of cumulative impacts. This analysis provides an unprecedented global assessment of the distribution and magnitude of air-breathing megafauna bycatch, highlighting its cumulative nature and the urgent need to build on existing mitigation successes. Recent research on ocean health has found large predator abundance to be a key element of ocean condition. Fisheries can impact large predator abundance directly through targeted capture and indirectly through incidental capture of nontarget species or bycatch. However, measures of the global nature of bycatch are lacking for air-breathing megafauna. We fill this knowledge gap and present a synoptic global assessment of the distribution and intensity of bycatch of seabirds, marine mammals, and sea turtles based on empirical data from the three most commonly used types of fishing gears worldwide. We identify taxa-specific hotspots of bycatch intensity and find evidence of cumulative impacts across fishing fleets and gears. This global map of bycatch illustrates where data are particularly scarce—in coastal and small-scale fisheries and ocean regions that support developed industrial fisheries and millions of small-scale fishers—and identifies fishing areas where, given the evidence of cumulative hotspots across gear and taxa, traditional species or gear-specific bycatch management and mitigation efforts may be necessary but not sufficient. Given the global distribution of bycatch and the mitigation success achieved by some fleets, the reduction of air-breathing megafauna bycatch is both an urgent and achievable conservation priority.

Fine-scale habitat modeling of a top marine predator: do prey data improve predictive capacity?

Predators and prey assort themselves relative to each other, the availability of resources and refuges, and the temporal and spatial scale of their interaction. Predictive models of predator distributions often rely on these relationships by incorporating data on environmental variability and prey availability to determine predator habitat selection patterns. This approach to predictive modeling holds true in marine systems where observations of predators are logistically difficult, emphasizing the need for accurate models. In this paper, we ask whether including prey distribution data in fine-scale predictive models of bottlenose dolphin (Tursiops truncatus) habitat selection in Florida Bay, Florida, U.S.A., improves predictive capacity. Environmental characteristics are often used as predictor variables in habitat models of top marine predators with the assumption that they act as proxies of prey distribution. We examine the validity of this assumption by comparing the response of dolphin distribution and fish catch rates to the same environmental variables. Next, the predictive capacities of four models, with and without prey distribution data, are tested to determine whether dolphin habitat selection can be predicted without recourse to describing the distribution of their prey. The final analysis determines the accuracy of predictive maps of dolphin distribution produced by modeling areas of high fish catch based on significant environmental characteristics. We use spatial analysis and independent data sets to train and test the models. Our results indicate that, due to high habitat heterogeneity and the spatial variability of prey patches, fine-scale models of dolphin habitat selection in coastal habitats will be more successful if environmental variables are used as predictor variables of predator distributions rather than relying on prey data as explanatory variables. However, predictive modeling of prey distribution as the response variable based on environmental variability did produce high predictive performance of dolphin habitat selection, particularly foraging habitat.

Characterizing Fishing Effort and Spatial Extent of Coastal Fisheries

Biodiverse coastal zones are often areas of intense fishing pressure due to the high relative density of fishing capacity in these nearshore regions. Although overcapacity is one of the central challenges to fisheries sustainability in coastal zones, accurate estimates of fishing pressure in coastal zones are limited, hampering the assessment of the direct and collateral impacts (e.g., habitat degradation, bycatch) of fishing. We compiled a comprehensive database of fishing effort metrics and the corresponding spatial limits of fisheries and used a spatial analysis program (FEET) to map fishing effort density (measured as boat-meters per km2) in the coastal zones of six ocean regions. We also considered the utility of a number of socioeconomic variables as indicators of fishing pressure at the national level; fishing density increased as a function of population size and decreased as a function of coastline length. Our mapping exercise points to intra and interregional ‘hotspots’ of coastal fishing pressure. The significant and intuitive relationships we found between fishing density and population size and coastline length may help with coarse regional characterizations of fishing pressure. However, spatially-delimited fishing effort data are needed to accurately map fishing hotspots, i.e., areas of intense fishing activity. We suggest that estimates of fishing effort, not just target catch or yield, serve as a necessary measure of fishing activity, which is a key link to evaluating sustainability and environmental impacts of coastal fisheries.

Super-Aggregations of Krill and Humpback Whales in Wilhelmina Bay, Antarctic Peninsula

Ecological relationships of krill and whales have not been explored in the Western Antarctic Peninsula (WAP), and have only rarely been studied elsewhere in the Southern Ocean. In the austral autumn we observed an extremely high density (5.1 whales per km2) of humpback whales (Megaptera novaeangliae) feeding on a super-aggregation of Antarctic krill (Euphausia superba) in Wilhelmina Bay. The krill biomass was approximately 2 million tons, distributed over an area of 100 km2 at densities of up to 2000 individuals m−3; reports of such ‘super-aggregations’ of krill have been absent in the scientific literature for >20 years. Retentive circulation patterns in the Bay entrained phytoplankton and meso-zooplankton that were grazed by the krill. Tagged whales rested during daylight hours and fed intensively throughout the night as krill migrated toward the surface. We infer that the previously unstudied WAP embayments are important foraging areas for whales during autumn and, furthermore, that meso-scale variation in the distribution of whales and their prey are important features of this system. Recent decreases in the abundance of Antarctic krill around the WAP have been linked to reductions in sea ice, mediated by rapid climate change in this area. At the same time, baleen whale populations in the Southern Ocean, which feed primarily on krill, are recovering from past exploitation. Consideration of these features and the effects of climate change on krill dynamics are critical to managing both krill harvests and the recovery of baleen whales in the Southern Ocean.