Browsing by Subject "Biological oceanography"

Primary production regulates fisheries yield, but testing the degree to which it is so is complicated by our limited ability to measure and model net primary production in the ocean. Herein, I analyze primary production and fisheries yields in the tropical Pacific Ocean, and how uncertainties in physiology parameterizations and in field primary production measurements used in the models’ formulations limit model skill. I find that primary production model choice has an effect on designating sustainable fisheries levels, that model parameterizations are not tuned to the tropical Pacific systems, and that model skill assessment is highly dependent on our understanding of local biomass-productivity dynamics. Moving forward, improving the primary production estimates in the tropical Pacific can be done incorporating understanding of local ocean dynamics into model skill assessments.

This dissertation research focused on the ways in which clear crustaceans with complex bodies (i.e. with hard cuticles, thick muscles, and other internal organs) maintain transparency across their entire body volume. I used transparent crustacean species that had relatively large (> 25 mm long and > 2 mm thick) bodies and that occupied physically different (pelagic vs. benthic reef) habitats. Studying these transparent crustaceans and making comparisons with closely related opaque crustaceans provided some of the first insights into the puzzling problem of the physical basis of transparency in whole organisms.

First, I examined the ultrastructure of the cuticle of hyperiid amphipods, the first surface to interact with light, to understand what features may minimize reflectance. I investigated the cuticle surfaces of seven species of mostly transparent hyperiids using scanning electron microscopy and found two previously undocumented features that reduced reflectance. I found that the legs of Cystisoma spp. were covered with an ordered array of nanoprotuberances that functioned optically as a gradient refractive index material to reduce reflections. Additionally, I found that Cystisoma and six other species of hyperiids were covered with a monolayer of homogenous nanospheres (approximately 50 nm to 350 nm in diameter) that were most likely bacteria. Optical modeling demonstrated that both the nanoprotuberances and the monolayers reduced reflectance by as much as 250-fold. Even though the models only considered surface reflectance and not internal light scattering, these models showed that the nanoprotuberances and spheres could improve crypsis in a featureless habitat where the smallest reflection could render an animal vulnerable to visual predation.

Second, I took a morphological approach to investigate how light scattering may be minimized internally. Using bright field microscopy, I explored whether there were any gross anatomical differences in the abdominal muscles between a transparent species of shrimp, Ancylomenes pedersoni, and a similarly sized opaque shrimp species, Lysmata wurdemanni. I found no differences in muscle fiber size or any other features. Using transmission electron microscopy (TEM) to visualize muscle ultrastructure, I found that the myofibrils of the transparent species were twice the diameter of the opaque species (mean values of 2.2 μm compared to 1.0 μm). Over a given distance of muscle, light passes through fewer myofibrils due to their larger diameter, with fewer opportunities for light to be scattered at the interfaces between the high-index myofibrillar lattice and the surrounding lower-index fluid-filled sarcoplasmic reticulum (SR). Additionally, because transparency is not always a static trait and can sometimes be disrupted after exercise or physiological stress, I compared the ultrastructure of muscle in transparent A. pedersoni shrimp with the ultrastructure of muscle in A. pedersoni that had temporarily turned opaque after exercise. I found that in this opacified tissue, the fluid-filled space around myofibrils had an increased thickness of 360 nm as compared to a normal thickness of 20 nm. While this could have been a fixation artifact, this result still suggests that opacified tissue had some change in osmolarity or increase in fluid. Models of light scattering across a range of thicknesses and possible refractive indices showed that this observed increase in fluid-filled space dramatically reduced transparency.

Third, I further investigated how exertion or physiological stress may disrupt transparency, what may occur in the tissues to cause this disruption, and what may explain the increased fluid-filled SR interface. I hypothesized that increased perfusion, or an increase in blood volume between muscle fibers, can disrupt the normal organization of tissue, resulting in increased light scattering. I measured pre- and post-exercise perfusion via the injection of a specific fluorescent stain (Alexa Fluor 594-labeled wheat germ agglutinin) that labeled the sarcolemmal areas in contact with hemolymph and the endothelial cells of the blood vessels, and found more open vessels and greater hemolymph perfusion around fibers post-exercise. Changing salinity in the shrimps’ tanks, wounding the shrimp, and injecting proctolin (a vasodilator) were also associated with increased opacity and perfusion. To visualize the shrimps’ overall muscle morphology, I used Diffusible Iodine-based Contrast-Enhanced Computed Tomography (DICECT) to scan one control (transparent) and one experimental (opaque) A. pedersoni. The resulting images added further support to my hypothesis that hemolymph volume in the muscle increases in post-exercise opacified A. pedersoni.

Understanding to what extent a particular ecosystem can influence the larger environment is the driving question behind my research. To begin examining this topic, several factors should be considered including 1) the community composition within a certain ecosystem 2) what factors drive community assembly, to predict the composition and organization of other related communities, and 3) the extent of influence of the ecosystem on the surrounding environments.

Chemosynthetic ecosystems are systems that are dependent on chemicals as the base of the food chain, rather than light as in photosynthesis. These systems are frequently biological hotspots within the ocean, where benthic communities can research a higher density than surrounding regions. Methane seeps, where methane and other hydrocarbons migrate through sediments to the seafloor, are one of the major forms of chemosynthetic ecosystems. The known environmental influence of seeps grows stronger as the number of discovered seeps increases, making understanding their breath of impact increasingly relevant.

Data collected in this study utilized two types of underwater research tools, an autonomous underwater vehicle (AUV) and a remotely operated vehicle (ROV). The study begins by examining seep fields about 200 nm off the South Carolina coast, at the Blake Ridge (~2150 m depth) and Cape Fear (~2580 m depth) Diapirs. Geophysical and photographic data were collected during surveys were used to examine the relationship between biomass-dominant invertebrates (mussels, Bathymodiolus heckerae, and clams, Vesicomya cf. venusta) and seafloor physiography. Concentric zonation of mussels and clams at each of the four sites within the seep field suggests the influence of chemical gradients on megafaunal distribution. Distributions of dominant seep features (bivalves, carbonates, bacterial mats) were used to define the active seep site. The relationship between seeps and nearby non-endemic fauna is examined in this study, with a focus on trophic guilds. Geospatial mapping indicated that non-seep-endemic taxa (those not hosting chemoautotrophic endosymbionts) either show positive association (e.g., squat lobsters, cake urchins), negative association (e.g., sea urchins, certain sea cucumbers), or no distributional bias (e.g., sea stars, certain fish) to the presence of a seep.

Further investigation into these faunal relationships may improve understanding of predictive community assembly rules, as well as clarifying the services that seeps provide to the larger ocean ecosystem. Data collection and analytical techniques used here yielded high-resolution habitat maps that can serve as baselines to constrain temporal evolution of seafloor seeps, and to inform ecological niche modeling and resource management.

Another aspect of the study is how seep communities differ when in an extremely low oxygen environment. Methane seeps are typically biological hotspots on the seafloor, with dense faunal communities relative to background (non-chemosynthetic) areas (Carney, 1994). However, some areas of the ocean are extremely low in oxygen, leading to decreases in overall fauna diversity, which can sometimes also affect seep communities. The eastern Pacific contains extensive oxygen minimum zones (OMZs), areas where the dissolved oxygen concentration falls below 22 μM, or 0.5 mg/L (Helly and Levin, 2004; Karstensen et al., 2008), as opposed to averages of 180-270 μM (4-6 mg/L) typically found in the ocean. These zones can intersect the continental slope, affecting benthic organisms, including those found at methane seeps in the region.

The Redondo Knoll Seep (~900 m depth), located just ~30 km off the California coast, shares features of both a seep and an oxygen minimum zone. High-resolution imaging providing a highly detailed photo mosaic and 1 cm resolution bathymetric maps, allowed for a comprehensive site view to further the geologic and microbial examinations. Particularly notable were the extensive microbial mats and, due to its location near the core of a local OMZ (averaging <1 μM oxygen), the lack of endemic seep megafauna or other non-endemic fauna.

While both seeps and OMZs are common by themselves, only a small number of studies have examined them together, such as off the coast of Chile (Sellanes et al., 2010), Pakistan (Fischer et al., 2012; Himmler et al., 2015), and Oregon (Levin et al., 2010). Consequently, there is still much to learn about the ecosystem and organisms at these combination sites.

Overall, this study considers the sphere of influence methane seeps provide the surrounding area through examination of the relationship between endemic fauna, their geologic habitat, and non-endemic fauna, with the intention to use these interactions to better inform seep roles in the environment in the face of anthropogenic disruptions, such as deep-sea mining and climate change, and as well as sites to consider for astrobiological studies.

Human use of the oceans is increasingly in conflict with conservation of endangered species. Methods for managing the spatial and temporal placement of industries such as military, fishing, transportation and offshore energy, have historically been post hoc; i.e. the time and place of human activity is often already determined before assessment of environmental impacts. In this dissertation, I build robust species distribution models in two case study areas, US Atlantic (Best et al. 2012) and British Columbia (Best et al. 2015), predicting presence and abundance respectively, from scientific surveys. These models are then applied to novel decision frameworks for preemptively suggesting optimal placement of human activities in space and time to minimize ecological impacts: siting for offshore wind energy development, and routing ships to minimize risk of striking whales. Both decision frameworks relate the tradeoff between conservation risk and industry profit with synchronized variable and map views as online spatial decision support systems.

For siting offshore wind energy development (OWED) in the U.S. Atlantic (chapter 4), bird density maps are combined across species with weights of OWED sensitivity to collision and displacement and 10 km2 sites are compared against OWED profitability based on average annual wind speed at 90m hub heights and distance to transmission grid. A spatial decision support system enables toggling between the map and tradeoff plot views by site. A selected site can be inspected for sensitivity to a cetaceans throughout the year, so as to capture months of the year which minimize episodic impacts of pre-operational activities such as seismic airgun surveying and pile driving.

Routing ships to avoid whale strikes (chapter 5) can be similarly viewed as a tradeoff, but is a different problem spatially. A cumulative cost surface is generated from density surface maps and conservation status of cetaceans, before applying as a resistance surface to calculate least-cost routes between start and end locations, i.e. ports and entrance locations to study areas. Varying a multiplier to the cost surface enables calculation of multiple routes with different costs to conservation of cetaceans versus cost to transportation industry, measured as distance. Similar to the siting chapter, a spatial decisions support system enables toggling between the map and tradeoff plot view of proposed routes. The user can also input arbitrary start and end locations to calculate the tradeoff on the fly.

Essential to the input of these decision frameworks are distributions of the species. The two preceding chapters comprise species distribution models from two case study areas, U.S. Atlantic (chapter 2) and British Columbia (chapter 3), predicting presence and density, respectively. Although density is preferred to estimate potential biological removal, per Marine Mammal Protection Act requirements in the U.S., all the necessary parameters, especially distance and angle of observation, are less readily available across publicly mined datasets.

In the case of predicting cetacean presence in the U.S. Atlantic (chapter 2), I extracted datasets from the online OBIS-SEAMAP geo-database, and integrated scientific surveys conducted by ship (n=36) and aircraft (n=16), weighting a Generalized Additive Model by minutes surveyed within space-time grid cells to harmonize effort between the two survey platforms. For each of 16 cetacean species guilds, I predicted the probability of occurrence from static environmental variables (water depth, distance to shore, distance to continental shelf break) and time-varying conditions (monthly sea-surface temperature). To generate maps of presence vs. absence, Receiver Operator Characteristic (ROC) curves were used to define the optimal threshold that minimizes false positive and false negative error rates. I integrated model outputs, including tables (species in guilds, input surveys) and plots (fit of environmental variables, ROC curve), into an online spatial decision support system, allowing for easy navigation of models by taxon, region, season, and data provider.

For predicting cetacean density within the inner waters of British Columbia (chapter 3), I calculated density from systematic, line-transect marine mammal surveys over multiple years and seasons (summer 2004, 2005, 2008, and spring/autumn 2007) conducted by Raincoast Conservation Foundation. Abundance estimates were calculated using two different methods: Conventional Distance Sampling (CDS) and Density Surface Modelling (DSM). CDS generates a single density estimate for each stratum, whereas DSM explicitly models spatial variation and offers potential for greater precision by incorporating environmental predictors. Although DSM yields a more relevant product for the purposes of marine spatial planning, CDS has proven to be useful in cases where there are fewer observations available for seasonal and inter-annual comparison, particularly for the scarcely observed elephant seal. Abundance estimates are provided on a stratum-specific basis. Steller sea lions and harbour seals are further differentiated by ‘hauled out’ and ‘in water’. This analysis updates previous estimates (Williams & Thomas 2007) by including additional years of effort, providing greater spatial precision with the DSM method over CDS, novel reporting for spring and autumn seasons (rather than summer alone), and providing new abundance estimates for Steller sea lion and northern elephant seal. In addition to providing a baseline of marine mammal abundance and distribution, against which future changes can be compared, this information offers the opportunity to assess the risks posed to marine mammals by existing and emerging threats, such as fisheries bycatch, ship strikes, and increased oil spill and ocean noise issues associated with increases of container ship and oil tanker traffic in British Columbia’s continental shelf waters.

Starting with marine animal observations at specific coordinates and times, I combine these data with environmental data, often satellite derived, to produce seascape predictions generalizable in space and time. These habitat-based models enable prediction of encounter rates and, in the case of density surface models, abundance that can then be applied to management scenarios. Specific human activities, OWED and shipping, are then compared within a tradeoff decision support framework, enabling interchangeable map and tradeoff plot views. These products make complex processes transparent for gaming conservation, industry and stakeholders towards optimal marine spatial management, fundamental to the tenets of marine spatial planning, ecosystem-based management and dynamic ocean management.

Although there are many examples of microbial biogeography, few microbes have been studied at high taxonomic resolution over large spatial scales. As a result, the environmental and ecological processes that drive niche partitioning, diversity, composition, and activity of microbial taxa are often poorly understood. To address this gap, I examine the most abundant phytoplankton in the global ocean, Prochlorococcus sp., a marine cyanobacterium. Using amplicon libraries of the Prochlorococcus internal transcribed spacer (ITS) region and 23S rRNA gene as markers, I demonstrate several key differences between the two major high light (HL) clades of Prochlorococcus. First, by examining ITS amplicon libraries at high taxonomic resolution it is revealed that “sub-ecotype” clades have unique, cohesive responses to environmental variables and distinct biogeographies, suggesting that presently defined ecotypes can be further partitioned into ecologically meaningful units. Whereas unique combinations of environmental traits drive the distribution of the HL-I sub-ecotype clades, the HL-II sub-ecotype clades appear ecologically coherent. Second, using 23S rRNA and rDNA libraries I show that activity (rRNA) and abundance (rDNA) are highly correlated for Prochlorococcus across all sites and operational taxonomic units (OTUs) in the surface ocean, demonstrating a tight coupling between activity and abundance. Finally, I investigate the associations between Prochlorococcus and the rest of the microbial community in the North Pacific and find region-specific trends in both strength and sign. Associations with other microbes are strongest for HL-I in the temperate region and strongest for HL-II in the sub-tropical gyre. This dissertation clarifies the relative importance of the environment, geography, community, and taxonomy in terms of their role in creating complex assemblages of Prochlorococcus and helps improve our understanding of how marine microbial communities are assembled in situ.

Marine productivity is limited by nitrogen in a large portion of the global ocean. Marine nitrogen fixation, catalyzed by a select group of microorganisms called diazotrophs, converts nitrogen gas (N2) into bioavailable nitrogen that can support the growth of marine phytoplankton. By supplying new nitrogen to marine ecosystems, marine N2 fixation affects marine primary production, the uptake of carbon dioxide and ultimately the global climate. However, the environmental controls on N2 fixation and the physiologies of diverse diazotrophs remain elusive, in great part due to the limited number of observations. As part of this dissertation, I applied a variety of approaches including statistical modeling, high-resolution field measurements, and gene sequencing to characterize the biogeography of marine diazotrophy.

The first approach was to model marine N2 fixation and diazotrophs using machine learning methods. To that end, I conducted meta-analyses to update the global datasets of N2 fixation and diazotrophs. The number of observations in these updated datasets are ~80% and over 100% larger than previous datasets, respectively. Simple correlation analyses between N2 fixation rates and different environmental factors failed to identify a single factor explaining marine N2 fixation at a global scale. In contrast, individual diazotrophic phylotypes showed distinct relations to environmental properties. Machine learning methods including random forest (RF) and support vector regression (SVR) simulated the observed N2 fixation and diazotrophs fairly well by accounting for nonlinearities among multiple environmental factors. The estimated global N2 fixation fluxes from the two statistical models were within the range of other studies. However, the machine learning estimates and other simulations in some cases showed substantial disagreement in both the magnitude and distribution of N2 fixation and diazotrophs, especially in high latitudes and the eastern equatorial Pacific, where observations are scarce. The large uncertainties in simulated N2 fixation and diazotrophs emphasized the need for a better understanding of the factors regulating N2 fixation and the physiology of diazotrophs.

Achieving this goal can be labor-intensive and difficult with current techniques, which are based on discrete sampling and long incubation time. To overcome some of the drawbacks of traditional methods, our laboratory developed a method for high-frequency underway N2 fixation measurements. This method provides better coverage of the spatial and temporal heterogeneity in N2 fixation. I deployed this method over large swaths of the western North Atlantic Ocean in the summers of 2015, 2016, and 2017, covering over 10,000 km cruise tracks. This extensive survey identified new hotspots of N2 fixation in the coastal waters of the mid-Atlantic Bight. By coupling high-resolution N2 fixation observations with underway estimates of net community production (NCP) derived from O2/Ar measurements, I revealed the heterogeneous contribution of N2 fixation to NCP and to the carbon cycle, with a surprisingly large contribution in coastal waters.

In addition to the spatial distribution of N2 fixation, I also characterized types of diazotrophs responsible for N2 fixation and how they responded to varying environmental conditions. By measuring diazotrophic diversity, abundance and activity at high-resolution using newly developed underway sampling and sensing techniques, I captured a shift between diazotrophs from Trichodesmium to UCYN-A from oligotrophic warm (25-29°C) subtropical Sargasso Sea to the relatively nutrient-enriched cold (13-24°C) eastern American coastal waters. Meanwhile, N2 fixation rates were significantly enhanced when phosphorus and Fe availabilities, and chlorophyll-a concentration increased across the Gulf Stream into the subpolar and coastal waters. Phosphorus limitation was confirmed with changes in the expression of phosphorus uptake genes in Trichodesmium and UCYN-A. While temperature was the major factor controlling the diazotrophic community, phosphorous was dominantly driving the changes of N2 fixation rates in the western North Atlantic.

Overall, this dissertation significantly improves our understanding of the distribution of N2 fixation and diazotrophs and their environmental controls in the western North Atlantic and in the global ocean.

Seemingly against all odds, some of the microscopic larvae of deep-sea chemosymbiotic fauna make it through the largest ecosystem on earth to settle at a new population. Evidence of these migration events can be found in the distribution of extant populations, by capturing larvae in the water column and by examining the genetic makeup of adults. In this dissertation I use large genetic datasets to consider how migration and gene flow have influenced the population structure of two deep-sea mollusks. Specifically, I assess if observed connectivity is the result of migration mediated by stepping-stones, recent divergence and/or long distance dispersal.

In Chapters 1 and 4, I examine gene flow in vesicomyid clams which live on reducing habitats like hydrothermal vents, cold seeps and food falls around the world. Of particular interest is the clam Abyssogena southwardae. This clam has colonized habitats across the entire Atlantic Ocean basin and exhibit low genetic diversity between populations. I test the possibility that the Mid-Atlantic Ridge has served as a stepping-stone across the basin using cytochrome c oxidase subunit I mitochondrial sequences (Chapter 1) and 5 additional nuclear loci (Chapter 2). The results of this analysis suggest that the Mid-Atlantic Ridge does not serve as a stepping-stone. An alternative hypothesis for the low genetic diversity in the Abyssogena southwardae is recent colonization of these populations by a common source.

In Chapter 2 I ask a similar question about the connectivity between distant populations of the hydrothermal vent endemic limpet Lepetodrilus aff. schrolli. Despite being separated by thousands of kilometers and exhibiting strong population structure, the two populations of Lepetodrilus aff. schrolli show evidence of directional gene flow since population divergence. The lack of identifiable migrants and the modeled ocean currents in the region suggest that it is unlikely that a single larva could make the trip between the two basins. Instead, one or more of the active hydrothermal vents in the vicinity could serve as a stepping-stone between the two distant basins. I was able to detect directional migration in this non-equilibrium scenario due a large dataset consisting of 42 amplified gene regions across 93 individuals.

In Chapter 3 I explore how subsets of this large amplicon dataset can provide insight into how the number of loci sequenced affects accuracy, precision, type I error and type II error. This subset analysis shows a general increase in accuracy and precision and a general decrease in type I and type II error with the addition of more loci. Furthermore, in the particular case of Lepetodrilus aff. schrolli subsamples as large as 20 loci still gave inaccurate but precise estimates. By examining the gene trees of these amplicons I was also able to investigate how empirical gene tree discordance influences coalescent analysis.

Large amplicon datasets allowed me to detect gene flow in complicated demographic situations in Abyssogena southwardae and Lepetodrilus aff. schrolli. In the Atlantic, Abyssogena southwardae analysis of multiple loci suggest that there are not stepping-stones along the Mid-Atlantic ridge to connect the Atlantic Equatorial Belt. This analysis will benefit from the additional loci that have been collected but not analyzed. In the Pacific, Lepetodrilus aff. schrolli, stepping-stones seem like a much more likely hypothesis to accommodate the low level of migration seen between the two distant basins examined. These studies are among the largest genetic datasets collected to date in the deep-sea and should serve as a benchmark for the generation and analysis of datasets for studying connectivity in the deep-sea.

The timing of the spring phytoplankton bloom in the subpolar North Atlantic Ocean has important consequences for the marine carbon cycle and ecosystems. There are currently several proposed mechanisms to explain the timing of this bloom. The conventional theory holds that the bloom begins when the ocean warms and the seasonal mixed layer shoals in the spring, decreasing the depth to which phytoplankton are mixed and increasing the light available to the population. Recent work has attributed the beginning of the bloom to decreases in turbulence within the upper ocean, driven by the onset of positive heat fluxes or decreases in the strength of local winds. Other studies have focused on the increase in the seasonal mixed layer in the winter as a driver of changes in ecosystem interactions and a control on the spring bloom. Finally, submesoscale eddies, occurring as a result of lateral density gradients, have been proposed as a stratification mechanism that can create phytoplankton blooms prior to the onset of ocean surface warming.

This dissertation critically examines and compares the proposed theories for the initiation of the spring bloom and draws on these theories to propose a new framework: that blooms begin when the active mixing depth shoals, a process generally driven by a weakening of surface heat fluxes and consequent shift from convective mixing to wind-driven mixing. Using surface forcing data, we develop a parameterization for the active mixing depth from estimates of the largest energy-containing eddies in the upper ocean.

Using in situ records of turbulent mixing and biomass, we find that the spring phytoplankton bloom occurs after mixing shifts from being driven by convection to being driven by wind, and that biomass increases as the active mixing depth shoals. Using remote sensing data, we examine patterns of bloom initiation in the North Atlantic at the basin scale, compare current theories of bloom initiation, and find that the shoaling of the active mixing depth better predicts the onset of the bloom across the North Atlantic subpolar basin and over multiple years than do other current theories. Additionally, using a process study model, we evaluate the importance of submesoscale eddy-driven stratification as a control on the initiation of the spring bloom, determining that this mechanism has a relatively minor effect on alleviation of phytoplankton light limitation. Finally, we describe potential techniques and tools to examine whether interannual variability in the active mixing depth acts as a control on variability in the timing of the spring bloom.

Marine microbes play key roles in driving patterns of important biogeochemical processes including primary production across the global ocean. Despite the importance of such interactions between the marine microbial community and ocean biogeochemistry, oceanographers have yet to attain a deep understanding of the ecological mechanisms underlying these connections. Due to the vast scale of ocean ecosystems, however, large-scale yet high-resolution surveys are necessary to uncover specific relationships between biology and elemental cycling for more detailed study.

With this need in mind, this dissertation takes advantage of recent advances in both underway techniques to measure in situ biogeochemical rates—most notably the dissolved O2/Ar method for measuring net community production (NCP)—as well as molecular sequencing methods to directly investigate relationships between marine microbial community structure, productivity, nitrogen (N2) fixation, and nutrient availability across large ocean regions. At the same time, this work also improves our understanding of the O2/Ar technique by evaluating its performance and key assumptions in a dynamic upwelling environment and by presenting recommendations to improve the accuracy of productivity estimates generated using this approach.

Presenting data and measurements from the most comprehensive survey of marine microbial community structure and patterns of productivity and N2 fixation in the western North Atlantic to date, this manuscript highlights intriguing connections between regional peaks in productivity and N2 fixation, the mixotrophic algae Chrysophyceae and Aureococcus anophagefferens, and Braarudosphaera bigelowii, a eukaryotic host organism for N2-fixing bacteria. In addition, we report a strong negative relationship between eukaryotic marine microbial diversity and productivity across the region. We further highlight the importance of considering diel cycles of productivity/respiration, other non-steady-state conditions, and vertical fluxes of O2/Ar when calculating and interpreting NCP rates obtained from surface O2/Ar measurements. Ultimately, these findings contribute to our ability to evaluate community production using surface ocean dissolved gas measurements and provide important insights into patterns of marine microbial activity and community structure into the western North Atlantic.

Effective conservation and management of top predators requires a comprehensive understanding of their distributions and of the underlying biological and physical processes that affect these distributions. The Mid-Atlantic Bight shelf break system is a dynamic and productive region where at least 32 species of cetaceans have been recorded through various systematic and opportunistic marine mammal surveys from the 1970s through 2012. My dissertation characterizes the spatial distribution and habitat of cetaceans in the Mid-Atlantic Bight shelf break system by utilizing marine mammal line-transect survey data, synoptic multi-frequency active acoustic data, and fine-scale hydrographic data collected during the 2011 summer Atlantic Marine Assessment Program for Protected Species (AMAPPS) survey. Although studies describing cetacean habitat and distributions have been previously conducted in the Mid-Atlantic Bight, my research specifically focuses on the shelf break region to elucidate both the physical and biological processes that influence cetacean distribution patterns within this cetacean hotspot.

In Chapter One I review biologically important areas for cetaceans in the Atlantic waters of the United States. I describe the study area, the shelf break region of the Mid-Atlantic Bight, in terms of the general oceanography, productivity and biodiversity. According to recent habitat-based cetacean density models, the shelf break region is an area of high cetacean abundance and density, yet little research is directed at understanding the mechanisms that establish this region as a cetacean hotspot.

In Chapter Two I present the basic physical principles of sound in water and describe the methodology used to categorize opportunistically collected multi-frequency active acoustic data using frequency responses techniques. Frequency response classification methods are usually employed in conjunction with net-tow data, but the logistics of the 2011 AMAPPS survey did not allow for appropriate net-tow data to be collected. Biologically meaningful information can be extracted from acoustic scattering regions by comparing the frequency response curves of acoustic regions to theoretical curves of known scattering models. Using the five frequencies on the EK60 system (18, 38, 70, 120, and 200 kHz), three categories of scatterers were defined: fish-like (with swim bladder), nekton-like (e.g., euphausiids), and plankton-like (e.g., copepods). I also employed a multi-frequency acoustic categorization method using three frequencies (18, 38, and 120 kHz) that has been used in the Gulf of Maine and Georges Bank which is based the presence or absence of volume backscatter above a threshold. This method is more objective than the comparison of frequency response curves because it uses an established backscatter value for the threshold. By removing all data below the threshold, only strong scattering information is retained.

In Chapter Three I analyze the distribution of the categorized acoustic regions of interest during the daytime cross shelf transects. Over all transects, plankton-like acoustic regions of interest were detected most frequently, followed by fish-like acoustic regions and then nekton-like acoustic regions. Plankton-like detections were the only significantly different acoustic detections per kilometer, although nekton-like detections were only slightly not significant. Using the threshold categorization method by Jech and Michaels (2006) provides a more conservative and discrete detection of acoustic scatterers and allows me to retrieve backscatter values along transects in areas that have been categorized. This provides continuous data values that can be integrated at discrete spatial increments for wavelet analysis. Wavelet analysis indicates significant spatial scales of interest for fish-like and nekton-like acoustic backscatter range from one to four kilometers and vary among transects.

In Chapter Four I analyze the fine scale distribution of cetaceans in the shelf break system of the Mid-Atlantic Bight using corrected sightings per trackline region, classification trees, multidimensional scaling, and random forest analysis. I describe habitat for common dolphins, Risso’s dolphins and sperm whales. From the distribution of cetacean sightings, patterns of habitat start to emerge: within the shelf break region of the Mid-Atlantic Bight, common dolphins were sighted more prevalently over the shelf while sperm whales were more frequently found in the deep waters offshore and Risso’s dolphins were most prevalent at the shelf break. Multidimensional scaling presents clear environmental separation among common dolphins and Risso’s dolphins and sperm whales. The sperm whale random forest habitat model had the lowest misclassification error (0.30) and the Risso’s dolphin random forest habitat model had the greatest misclassification error (0.37). Shallow water depth (less than 148 meters) was the primary variable selected in the classification model for common dolphin habitat. Distance to surface density fronts and surface temperature fronts were the primary variables selected in the classification models to describe Risso’s dolphin habitat and sperm whale habitat respectively. When mapped back into geographic space, these three cetacean species occupy different fine-scale habitats within the dynamic Mid-Atlantic Bight shelf break system.

In Chapter Five I present a summary of the previous chapters and present potential analytical steps to address ecological questions pertaining the dynamic shelf break region. Taken together, the results of my dissertation demonstrate the use of opportunistically collected data in ecosystem studies; emphasize the need to incorporate middle trophic level data and oceanographic features into cetacean habitat models; and emphasize the importance of developing more mechanistic understanding of dynamic ecosystems.

Our oceans are a key part of the Earth system, an underappreciated bastion of our carbon cycle, and the home of incredible biodiversity, yet marine ecosystems are extremely challenging to model with a range of feedbacks that are not understood. Particularly poorly understood are linkages between physics and biology at the submesoscale (horizontally O(0.1-10) km, vertically O(.1) km, temporally O(1) day) that could help explain broad scale properties in ocean biology. Persistent fronts of western boundary currents like the Gulf Stream are hotspots for submesoscale dynamics that may influence phytoplankton productivity and diversity with ramifications across marine ecosystems. In this dissertation I: 1) review the use of drones and ocean color remote sensing for observing biology at the submesoscale and below, and articulate a vision for addressing key observational needs with drones, 2) develop more robust methods for retrieving ocean color from drones, 3) integrate observations from new and existing sampling technologies to investigate phytoplankton enhancement and shifts in phytoplankton community composition on the Gulf Stream front, and 4) with a frontal eddy as a mesocosm investigate community composition in the eddy vs shelf and Gulf Stream water and then more broadly understand their impact on the marine ecosystem of the Gulf Stream and mid-Atlantic Bight. This work revealed seasonality contrasting that of the typical North Atlantic blooms, but more similar to Sargasso Sea water at this latitude with peak biomass in winter. We found shifting nutrient limitations and observed chlorophyll-a enhancement on the front in a large minority of samples with an indication of winter being more likely for enhancement. We speculate about linkages between this enhancement and ageostrophic circulation on the front but did not directly demonstrate this. Community composition shifts were present in all transects across the Gulf Stream front, though no consistent pattern emerged, with gradual shifts, step changes, and anomalies at the front. Finally the in-depth frontal eddy investigation revealed a different community, dominated by Prochlorococcus, and many optical indicators of a post-bloom shift to a microbial loop environment within the eddy. In summary the major goals of this work were to understand the interplay of ocean physics and marine ecosystems at the fine-scale. Towards this goal, I develop more robust methods for measuring ocean color from drones and then focus on the Gulf Stream, parsing out connections between the front and chl-a and biodiversity and then focus on a frontal eddy as a mesocosm for physical-ecological interactions and for their ecological impact on the mid-Atlantic Bight.

While much is known about the abundance and genetic diversity of environmental microbial communities, little is known about their taxon-specific activity. In this thesis I address this gap using a model marine microbe, the cyanobacterium Prochlorococcus spp., which numerically dominates tropical and subtropical open oceans and encompasses a group of genetically defined clades that are ecologically distinct. Ribosomal RNA is a promising indicator of in situ activity because of its essential role in protein synthesis as well as its phylogenetic information, which could be used to distinguish clades among mixed populations. Here I show that, in a laboratory system the specific growth rate of representative Prochlorococcus strains could be quantitative predicted from cellular rRNA content (assessed by RT-qPCR), cell size (assessed by flow cytometry) and temperature. Applying this approach in the field, I show unique clade-specific activity patterns for Prochlorococcus. For example, vertically within the euphotic zone, eHL-II activity is strongly impacted by light and is consistent with patterns of photosynthesis and on a horizontal transect from Hawaii to San Diego, eHL-I and eHL-II activities exhibit significant transitions and appear to be regulated by temperature, nutrient and vertical mixing gradients. Using ribosomal tag pyrosequencing of DNA and RNA, I have extended our observation to the Eubacterial community and described the biomass distribution (rDNA) and activity (rRNA) patterns from two representative depths (25 and 100 m) at a well-studied oligotrophic ocean station. These results show that for some populations the abundances and activities are significantly uncoupled, which suggests substantial top-down controls or physical transport processes. Further exploring the taxon-specific activity patterns along with abundances and environmental variables across time and space is essential to better understanding the dynamics of a complex microbial system as well as predicting the consequences of environmental change.

Ekman suction and pumping are often invoked to explain the observed difference in primary production and chlorophyll a between the North Atlantic subpolar and subtropical gyres. Between the gyres, the intergyre region can be loosely defined by its lack of a strong Ekman suction or pumping of nutrients. Despite the lack of a strong Ekman supply of nutrients, the mean seasonal cycle in chlorophyll a in the intergyre is remarkably similar to that seen in the subpolar gyre. In this thesis, we present research on mechanisms for nutrient supply to the intergyre that might support its high production. Using biogeochemical and physical reanalysis ocean data products, a nutrient budget is constructed for a region in the eastern North Atlantic, within the intergyre. Analysis of this budget shows that the seasonal entrainment flux, resultant from the movement of the mixed layer across vertical nutrient gradients, is responsible for the majority of the nutrient supply to the region. Hydrographic ocean data and particle trajectories run in a numerical model are then used to show that the waters seasonally entrained into the intergyre mixed layer likely originate in the Gulf Stream, linking nutrient supply in the North Atlantic intergyre to high downstream nutrient fluxes observed in the Gulf Stream.