Time and energy are finite resources in any environment, and how and when organisms use their available resources to survive and reproduce is the crux of life history theory (Gadgil and Bossert 1970; Balon 1975; Stearns 1976). The different survival strategies used by animals are often shaped by their environment in addition to their biology (Winemiller and Rose 1992), which allows for exploration into biological variability when environmental factors are known. For this reason, the Line Islands in the Central Pacific provide an ideal location to perform observational studies due to their unique productivity gradient and fish assemblage structures across the island chain (Sandin et al. 2008; DeMartini et al. 2008; Fox et al. 2018; Zgliczynski et al. 2019). Many of the world’s coral reefs are in remote regions that lack monitoring programs or even local populations, so conducting ecological surveys on fish communities in these regions can require extensive amounts of time, energy, resources and people. The inherent variability an environment exerts on the many factors that contribute to growth over a lifetime make it difficult to generate a directly proportional formula that calculates age. A novel age estimation method was developed that utilizes in-situ visual census data to estimate the age of fishes, and as a case study, several fish were chosen as representative species to explore its capabilities. Through this process, new ecological information and insight can be gained about the age structures of fish populations both between and throughout the Line Islands.
Aerosol-cloud interactions are one of the largest sources of uncertainty in our understanding of the Earth’s climate system. In order to develop better predictive models and understand how the climate will respond to future changes in atmospheric composition, we must determine the sources and nature of aerosols which serve as cloud condensation nuclei (CCN), thus influencing the properties of clouds. Oceans cover 70% of the Earth’s surface and represent a major source of atmospheric aerosols. Sea spray aerosol (SSA) is formed by the action of breaking waves, whereas secondary marine aerosols (SMA) are formed from the oxidation products of gases emitted from the oceans. Biological activity in seawater (i.e. the life, death, and interactions of marine phytoplankton, bacteria, and viruses) can significantly affect the chemical composition of SSA through processing of dissolved organic matter and SMA through the emission of volatile gases. This dissertation investigates the cloud-relevant properties of SSA and SMA generated using ocean-atmosphere simulators in the laboratory, with a specific emphasis on the influence of biological activity in seawater on the properties of these aerosols. For the first time, SMA was produced from the oxidation of the headspace gases of a phytoplankton bloom grown in natural seawater, enabling measurements of its chemical composition and CCN activity. Overall, these studies show that the formation and properties of SMA are much more sensitive to biological activity in seawater than SSA. In addition, the chemical composition of SMA is highly dependent on the extent of photochemical oxidation, with a distinct shift from organic-rich to sulfate-rich composition in response to increased atmospheric aging. This change in SMA composition leads to a significant change in its hygroscopicity. These results suggest that the properties of SMA evolve temporally in the atmosphere, which has implications for CCN concentrations and cloud properties over the oceans.
Understanding fish diversity patterns is critical for fisheries management amidst overfishing and climate change. Fish egg surveys have been used to characterize pelagic spawning fish communities, estimate biomass, and track population trends in response to perturbations. Environmental DNA (eDNA) metabarcoding has been implemented to rapidly and non-invasively survey marine ecosystems. To understand the efficacy of eDNA metabarcoding for assessing pelagic spawning fish community composition, concurrent eDNA metabarcoding and fish egg DNA barcoding off Scripps Institution of Oceanography’s Pier (La Jolla, CA) were conducted. Both methods revealed seasonal patterns in agreement with previous fish and fish egg surveys. Species richness was highest in late spring and summer. The presence and spawning of commercially important species and species of conservation concern were detected. Both methods showed overlap for pelagic spawning fishes for broadcast spawners, schooling fish, and locally abundant species. Some actively spawning species were not co-detected with eDNA, likely due to different sampling strategies, taxonomic biases, and abiotic/biotic factors influencing eDNA transport, shedding, and degradation. We identified key advantages and disadvantages of each method. Fish egg barcoding provided information on spawning trends but did not detect taxa with alternate reproduction strategies. Metabarcoding eDNA detected species not found in fish egg sampling, including demersal and viviparous bony fishes, non-spawning adults, Chondrichthyan, and Mammalian species, but missed abundant pelagic fish eggs. This study demonstrates that DNA barcoding of fish eggs and eDNA metabarcoding work best in tandem as each method identified unique fish taxa and provided complementary ecological and biological insight.
The marine leeches of California are found on many host species, but the biology, distribution, and ecology of these leeches is not well understood. In this thesis I describe two previously unknown species: the leeches Mysidobdella californiensis, found on mysid shrimp hosts in Bodega Bay, CA, and Heptacyclus cabrilloi, found on giant kelpfish in San Pedro, CA. I also describe a method that addresses the problem of measuring the size of leeches, which is considered to be difficult because of the inconsistencies in the body proportions of soft-bodied invertebrate organisms. I utilize digital photography to measure leech size and use maximum- likelihood estimation to fit a model of size/age cohort distributions to a sample of leeches.
The western North Atlantic is a dynamic region characterized by the Gulf Stream western boundary current and inhabited by a diverse host of odontocete, or toothed whale, top predators. Their habitats are highly exploited by commercial fisheries, shipping, marine energy extraction, and naval exercises, subjecting them to a variety of potentially harmful interactions. Many of these species remain poorly understood due to the difficulties of observing them in the pelagic environment. Their habitat utilization and the impacts of anthropogenic activities are not well known. Over the past decade, passive acoustic data has become increasingly utilized for the study of a wide variety of marine animals, and offers several advantages over traditional line-transect visual survey methods. Passive acoustic devices can be deployed at offshore monitoring sites for long periods of time, enabling detection of even rare and cryptic species across seasons and sea states, and without altering animal behaviors. Here we utilized a large passive acoustic data set collected across a latitudinal habitat gradient in the western North Atlantic to address fundamental knowledge gaps in odontocete ecology. I approached the problem of discriminating between species based on spectral and temporal features of echolocation clicks by using machine learning to identify novel click types, and then matching these click types to species using spatiotemporal correlates. I was able to identify novel click types associated with short-beaked common dolphins, Risso’s dolphins, and short-finned pilot whales in this way. Next I characterized temporal patterns in presence and activity for ten different species across our monitoring sites at three different temporal scales: seasonal, lunar, and diel. I observed spatiotemporal separation of apparent competitors, and complex behavioral patterns modulated by interactions between the seasonal, lunar, and diel cycles. Finally I investigated the relationships between species presence and oceanographic covariates to predict habitat suitability across the region, and explored niche partitioning between potentially competitive species. The insights gained here significantly advance our understanding of toothed whale ecology in this region, and can be used for more effective population assessments and management in the face of anthropogenic threats and climate change.
Here we show that air-sea coupling significantly impacts the simulation of sea surface temperature (SST) variability in the California Current System (CCS). Previous work has shown important differences between coupled and uncoupled models in simulating coastal SST, but only using empirical coupling or idealized scenarios. We compare the output of the UCLA Mesoscale Coupled Model to the output of a similar but uncoupled model over the CCS. These high resolution, realistic regional models have identical coastlines, bathymetry, and topography. They are forced at the boundaries by reanalysis data over the historical period 1981-1990. This model setup allows us to evaluate how including air-sea coupling impacts the accuracy of our simulation by comparing our model output to buoy observations. Both the spatial patterns and the amount of variability are more realistic in the coupled model, which is likely due to improved simulation of internal variability.
Spatial management is a popular tool for resource managers to protect and conserve natural resources. However, a number of emerging threats are testing the ability of these tools to address management needs. Marine protected areas and slow speed zones are popular tools employed by resource managers to mitigate anthropogenic threats; however climate change and whale ship strikes represent new threats that may complicate the benefits of these tools. This dissertation examines the efficacy of incentivizing slow vessel transits to reduce cetacean mortality risk and the application of MPAs to mitigate climate change. A trial program to monetarily incentivize slow transits through the Santa Barbara Channel showed high compliance compared to a similar voluntary program. During incentivized transits, the large majority of ships maintained a 12 knot transit speed as determined by the program guidelines. An incentivized program may be key in reducing risk to whale mortality and reducing ships speeds; however scaling up this program may face financial difficulty.Marine Protected Areas have been claimed to offer additional protection to areas affected by climate change. However, a recent warm water marine heatwave changed the fish community’s abundance, biodiversity, and recruitment around the Channel Islands. While the ecological community changes across strong longitudinal biogeographic patterns, forecasts built from GLMs with environmental conditions predict shifts in species abundance. Upwelling and cool waters coming to the surface may mitigate warming ocean conditions in the region but marine protected areas showed no increased resilience to acute climate affects like marine heatwaves.
Many infectious bacterial and viral agents exist in the world and are located in areas where humans may come into contact with them. Food, water, and environmental locations may be contaminated with infectious material, and detecting the presence of these harmful biologic agents is of import to public health agencies. One method that has been used to determine if infectious agents may be present in food or water is measurement of "indicator" bacteria or viruses. Indicator organisms are easily measured bacteria or viruses whose presence in water or food is thought to parallel the potential presence of infectious agents in the same food or water samples. Because there are so many potential bacteria (or viruses) that may infect a sample, it is impractical to test for all of them; rather, measurement of a single indicator organism may be more feasible. Indicator bacteria have been used to determine if marine waters at beaches across the United States are safe for swimming. Guidelines issued by the U.S. Environmental Protection Agency (U.S. EPA) have focused on determining when recreational waters may pose a risk of excess gastrointestinal illness among swimmers when compared to non-swimmers. However, marine environments are very complex, and tidal patterns, solar inactivation, water temperature, and many other factors all can influence the presence or absence of indicator and infectious microorganisms in the water. Research has indicated that indicator organisms may be useful in predicting gastrointestinal illness in marine environments, but other health outcomes have been less studied. In order to verify that indicator organisms do track well with infectious organisms, a systematic review and meta analysis was conducted to determine if indicator organisms can predict a different health outcome, skin infection. Once the link between indicator organisms and health outcomes was established, the next goal was to explore different methods to strengthen the relationship between indicator organisms and health. Currently, the U.S. EPA advises that a single bacterial indicator, Enterococcus, be measured in marine waters. A binary cutoff of above or below 104 colony forming units per 100 mL is used to advise whether a beach is unsafe or safe for swimming. In order to improve prediction of illness at beaches using indicator organisms, several methods were considered. Flexible statistical modeling techniques, such as SuperLearning, were used, as well as consideration of multiple biological and physical indicators at the same time. The final aim was to examine the potential sources of the infectious agents, as well as the indicator bacteria, at Avalon beach in Southern California. The results of this investigation suggest that indicator bacteria can be quite useful in predicting human illness, but perform better under certain conditions. The systematic review and meta-analysis showed that there was a strong relationship between certain indicator organisms and skin infections in marine water settings. Higher concentrations of total coliform, fecal coliform, E. coli, Enterococcus, and fecal Streptococci were associated with increased risk of skin related illness in marine waters. These findings support the biological plausibility of using indicator organisms to predict illness, even in a complicated, dynamic environment such as a marine beach. The second investigation found that application of the U.S. EPA guidelines at Avalon Beach did not accurately predict when waters were unsafe for swimming. However, use of flexible statistical methods (SuperLearner) greatly improved prediction of gastrointestinal illness over traditional modeling methods, such as logistic regression. Further improvements were seen when, instead of using a single indicator organism, combinations of biological and physical indicators were used. By combining physical and biological indicators, it was possible to identify circumstances when elevated concentrations of Enterococcus predicted excess gastrointestinal illness in swimmers. When solar radiation levels were low, indicator bacteria concentrations were more strongly associated with adverse health outcomes, whereas higher solar radiation levels were protective. This finding is biologically plausible because it is thought that solar radiation can directly damage indicator bacteria as well as pathogens and render them non-viable. Thus, under high solar radiation conditions, indicator organisms as well as infectious organisms would be inactivated. The final analysis examined groundwater flow as a potential risk to swimmers at Avalon beach. Because of a leaking sewage infrastructure at Avalon, it is thought that groundwater flux might be transporting raw sewage contents into the ocean water. Sewage is known to carry potentially high levels of pathogenic organisms, and thus groundwater flow levels might pose a direct threat to swimmers. When groundwater flow was higher, the incidence of gastrointestinal illness was elevated among swimmers who swallowed water, relative to swimmers who swallowed water on days when groundwater flow was lower. Additionally, the relationship between groundwater flow and solar radiation was similar to that seen with Enterococcus and solar radiation. When solar radiation levels were high, groundwater flow was less predictive of excess gastrointestinal illness, as would be expected. When traditional analysis methods were used to relate traditional and rapid indicators to illness, relationships were much stronger when groundwater flow was high versus when groundwater flow levels were lower. In conclusion, the results of these analyses suggest that indicator organisms can be used to predict health outcomes in recreational water settings, but that their performance may be greatly improved by using flexible modeling techniques as well as other indicators, such as solar radiation.
Oxygen isotope ratios of fish biominerals reflect environmental growth conditions - specifically, the temperature and δ18O values of water. In Holocene ocean sediments, phosphate δ18O (δ18OP) values of small pelagic fish bones and scales can be coupled with abundance data to study connections between past climate and population dynamics. This requires the detection of decadal scale climate variability via precise isotope measurements. To accomplish this, isotope data is best corrected by multiple regression methods that facilitate both instrumental monitoring and correction model optimization. Our measurements of δ18O values from bones, scales, and otoliths indicated that all three materials provide similar information about growth conditions, provided that each material's unique allometry is considered. For sardines cultured at controlled temperatures, δ18OP values of scales were consistent with the fractionation equation proposed by Longinelli and Nuti (1973). These results support the use of δ18OP to investigate the paleoecology of small pelagic fish.
This thesis examines the economic vs. social and symbolic importance of fish in the foodways of the prehistoric Jomon culture (16,000-2300 cal BP) of Japan. To achieve this goal, quantitative analyses of fish remains excavated from a water-logged midden of the Sannai Maruyama site (Aomori Prefecture, Japan) are conducted. Dated to the Lower Ento-a phase (ca. 5900-5650 cal BP) of the Early Jomon Period, the midden was associated with large amounts of organic remains, including fish bones. The perspective employed in this dissertation, foodways, emphasizes the importance of social and cultural roles of food. Rather than focus on bio-ecological aspects and nutritional values of food, this thesis regards food as one of the central elements of individual cultures. In Japanese archaeology, food of the Jomon Period has been a central them to the discussion reconstructing the lifeways of prehistoric people of the Japanese archipelago. Large amounts of data, including faunal and floral materials, have been accumulated from numerous rescue excavations of Jomon sites that took place between the 1970s and late 1990s. These archaeological data allowed the development of detailed culture historical studies of the Jomon Period that span over 10,000 years. Within the tradition of Japanese archaeology, however, virtually no scholar has adopted the study of foodways as a theoretical approach. This thesis is one of the few attempts to examine Jomon data from this perspective. In this thesis, the relations between Jomon people and fish as their food are examined through zooarchaeological and ethnoarchaeological analyses. Soil samples from the "Northern Valley" midden of the Sannai Maruyama site were obtained, and fish remains in these samples were separated, identified, and quantified. The results indicate that two taxa were particularly important in the diet of the Sannai Maruyama residents: Cobitidae (loaches) and Seriola (yellowtails). These results are used to address the question of why certain fish taxa were selected when the environment provided a great variety of other animals and fish. Energy investments and returns related to fishing and consumption of these two taxa are calculated, and the results are discussed in the context of energy efficiency, the assumption that lies behind the diet breadth model, one of the optimal foraging models .The results indicate that Cobitidae fishing can be explained by cost-benefit calculation, while an abundance of Seriola in the assemblage requires another explanation .The results of these analyses are discussed in the context of the study of prehistoric foodways.