Search

This paper discusses the day and night capability of a newly developed optical sensing suite flown on manned and unmanned aircraft in Monterey Bay and Santa Barbara, CA, during 2022 to detect marine mammals. New developments of electro-optical sensors integrated on medium and long-endurance unmanned aerial vehicles (UAVs) can provide cost-effective, qualitative sensing of marine biodiversity, to include species identification. Processing of captured imagery in both day and night applications has proven effective in removing surface-level reflections and background noise, which allows sensing of subsurface marine life to several attenuation lengths. Leveraging bioluminescence as a natural image enhancement phenomenon along with advanced signal processing of imagery captured by this sensing suite improves the quality of nighttime detection and species identification. Concepts and applications for this sensing suite integrated on UAV platforms for ocean food-chain modeling and maritime traffic avoidance are discussed, including deployment strategies for the Channel Islands National Marine Sanctuary off the California coast. [ABSTRACT FROM AUTHOR]

From February 2019 through January 2021, data were collected by an acoustic vector sensor moored on the seafloor at a depth of approximately 900 m just outside of Monterey Bay, California, near a major shipping lane off the California coast. Analysis of the vector sensor data has shown the ability to accurately determine bearings to merchant vessels at ranges up to 60 km. This paper examines the features of the low-frequency soundscape using spectral probability densities and evaluates directional features through vector intensity processing as well as coherent linear and adaptive processing of the vector sensor channels. Merchant vessel acoustic data were analyzed using the 1/3 octave band centered at 63 Hz. Over the period analyzed, a reduction in merchant vessel noise was observed between February and June 2020 relative to the same period in 2019, consistent with a reduction in vessel traffic due to the worldwide response to COVID-19. The directional features of the data evaluated through adaptive processing methods also suggest this reduction can be most clearly distinguished towards the south, where the shipping lane is limited to transiting vessels, rather to the north-northwest, where merchant vessels tend to congregate on approach into the San Francisco Bay area. [ABSTRACT FROM AUTHOR]

This paper discusses the value added by using a single vector sensor over a conventional pressure-only hydrophone for geoacoustic inversions. Inversion methods based on genetic algorithms are used to estimate the seabed properties. Synthetic signals of impulsive arrivals first are modeled using KRAKEN and RAM propagation models, each being modified to predict components of the vector field. While KRAKEN is utilized to directly compute dispersion curves, RAM provides full-field results that require the application of time warping to separate the modal arrivals. Combinations of dispersion curves utilizing all vector sensor channels are compared to curves estimated with the pressure-only channel. Within the time warping analysis, both binary masking and band-pass filter masking methods are applied to compare stability of results. The environment modeled for the synthetic analysis and inversion method utilize sound speed profiles measured during the Monterey Bay 2019 at-sea experiment and assume a sediment layer of constant thickness overlying a deeper sub-bottom type. White noise is added to the synthetic data at different signal-to-noise ratios to evaluate the impact of signal excess on the results. A hybrid optimization approach is used to improve the results of the genetic algorithm method. The analysis with synthetic data is consistent with the analysis of broadband, impulsive data collected from the experiment, indicating that the additional information from the vertical velocity channel further improves the geoacoustic parameter estimates. [ABSTRACT FROM AUTHOR]

The accelerated pace of climate-driven shifts is surpassing the temporal scope of conventional field research, potentially leading to a disconnect between ecosystem changes and scientific data collection. Climate change is producing rapid transformations within dynamic marine ecosystems, with a pronounced effect on high trophic-level species such as loggerhead sea turtles (Caretta caretta). We present a new model for data collection using ethnobiological methods, emphasizing how local community members can contribute to expanding scientific knowledge via context-informed observations, to document species occurrences beyond their anticipated habitats during climatic anomalies. In rapidly changing conditions, local expert knowledge can complement conventional scientific methods, providing high-quality data with extensive coverage--especially for elusive species--and yielding insight into potential emerging phenomena that may otherwise go unnoticed. Conventional methods for predicting distribution shifts in rare species are vulnerable to spatial biases, favoring predictions based on the most probable habitats. We present the case study of a live sea turtle sighting by a local expert in Monterey Bay, California, USA, identified post hoc as a loggerhead, to illustrate methods which can be transferred and applied to other rare and highly migratory marine species such as marine mammals, sharks, and seabirds. This emerging framework incorporates diverse knowledge sources and methodologies in monitoring climate-driven ecological shifts, enriching conservation strategies, enhancing our understanding of complex ecosystems, and contributing to robust evidentiary standards for rare species observations. [ABSTRACT FROM AUTHOR]

This study evaluates the feasibility of applying the Estimating the Circulation and Climate of the Ocean (ECCO) data assimilation (DA) framework to a submesoscale-resolving model [Massachusetts Institute of Technology General Circulation Model (MITgcm), at 1-km grid resolution]. This is in preparation for future studies to understand and assimilate the novel swath measurements of sea surface height from the Surface Water and Ocean Topography (SWOT) satellite mission. The model domain is centered at the SWOT calibration/validation (CalVal) site, located 300 km offshore of Monterey Bay, California. We assimilate vertical profiles of temperature and salinity from a linear array of three SWOT prelaunch CalVal moorings, between September and December 2019. Two model solutions are analyzed: 1) a nonassimilating forward simulation termed "first-guess" and 2) an optimized solution that assimilates the in situ observations. Both runs are nested within the global 1/12° Hybrid Coordinate Ocean Model that uses Navy Coupled Ocean Data Assimilation (HYCOM/NCODA) analysis. We evaluate the performance by comparing the two model solutions against assimilated and withheld in situ observations. We show that by assimilating hydrographic data, the model performance over the first-guess solution is improved with an error-to-observation reduction of 30%–45% for temperature, 14%–41% for salinity, and 44%–56% for steric height. Over the study period, the average steric height error at the three assimilated moorings was 1.27 cm for the optimized solution versus 2.6 cm for the first-guess solution. A comparison to withheld glider observations shows that the optimized solution outperforms the first-guess solution with an error-to-observation reduction of approximately 38% in steric height (1.5 versus 2.4 cm). This study indicates, for the first time, that the MITgcm–ECCO framework can be successfully applied to the reconstruction of submesoscale ocean variability, via the nesting of a high-resolution regional domain into a global outer domain. [ABSTRACT FROM AUTHOR]

Animal culture evolves alongside genomes, and the two modes of inheritance—culture and genes—interact in myriad ways. For example, stable geographic variation in culture can act as a reproductive barrier, thereby facilitating genetic divergence between "cultural populations." White-crowned sparrows (Zonotrichia leucophrys) are a well-established model species for bird song learning and cultural evolution, as they have distinct, geographically discrete, and culturally transmitted song types (i.e., song dialects). In this study, we tested the hypothesis that divergence between culturally transmitted songs drives genetic divergence within Nuttall's white-crowned sparrows (Z. l. nuttalli). In accordance with sexual selection theory, we hypothesized that cultural divergence between mating signals both preceded and generated genetic divergence. We characterized the population structure and song variation in the subspecies and found two genetically differentiated populations whose boundary coincides with a major song boundary at Monterey Bay, California. We then conducted a song playback experiment that demonstrated males discriminate between songs based on their degree of divergence from their local dialect. These results support the idea that discrimination against non-local songs is driving genetic divergence between the northern and southern populations. Altogether, this study provides evidence that culturally transmitted bird songs can act as the foundation for speciation by sexual selection. [ABSTRACT FROM AUTHOR]

Managing for the effects of climate change on species whose populations are currently imperiled requires detailed knowledge of the relationship between their demographic rates and climate variables. We sought this information for the West Coast breeding population of snowy plover (Charadrius nivosus), which was federally listed as threatened in 1993 due to substantial declines in the numbers of plovers breeding along the coast and in the number of sites occupied for breeding. Snowy plovers employ a serially polygamous breeding system in which the male typically tends chicks to independence. This unusual breeding system is favored by male‐biased sex ratios in local populations. As part of a multispecies study of the effect of climate change on population growth, we used mark–capture models to examine climate drivers of adult survival for 1219 snowy plovers banded at Monterey Bay over 38 years and known to overwinter on the surrounding north‐central California outer coast. Nonclimate variables, including sex and unmeasured annual mortality risks (e.g., predator abundance), were the primary factors affecting adult survival. However, there is evidence that cold weather, particularly extended cold snaps with daily low temperatures below 2°C and daily high temperatures below 10°C, decreases overwinter survival. Exceptionally cold winters had a particularly strong effect on adult female plovers, contributing to the male‐biased adult sex ratios. Future winter climate on the north‐central California coast is projected to be generally warmer with fewer and shorter cold snaps. Reduced mortality from cold winter weather may mitigate other threats faced by plovers, such as anthropogenically enhanced predator populations, habitat loss, and accelerated sea level rise, while altering the adult sex ratio and potentially shifting the evolutionary landscape maintaining the plover's unusual breeding system. [ABSTRACT FROM AUTHOR]

Free space optical (FSO) communication in a maritime environment involves unique challenges due to the existing environmental conditions. An important degradation factor is atmospheric turbulence that causes irradiance fluctuations (scintillation) at the detector. A significant amount of theoretical and experimental research has been conducted to quantify those effects. This paper presents the results of an experimental campaign that took place during September and October of 2020 over the Monterey Bay in California. The main goal of this campaign was to measure atmospheric turbulence over the water and compare the results with a theoretical model called the Navy Surface Layer Model (NAVSLaM), developed by the Meteorology Department at the Naval Postgraduate School (NPS), as well as conduct a regression analysis for turbulence predictive modeling based on environmental parameters. The results showed very good agreement between theory and experiment. [ABSTRACT FROM AUTHOR]

Simple Summary: Zoos and aquaria play an important role in preventing the mass extinction of wildlife through public awareness of conservation issues and providing a safe haven for wildlife populations. Because aquatic populations face many challenges due to pollution and global warming, it is important to develop an understanding of how species can cope with their environment whether it be in the wild or under human care. Here, we were interested in developing non-invasive methods to study fish stress physiology. We use the unique ocean sunfish (Mola mola) to develop the use of skin swabs to measure the stress hormone, cortisol. We used known times of stress including when a mola was injured or ill and during acclimation to the Monterey Bay Aquarium. We found that cortisol increased initially within the first month of being admitted to the aquarium, but returned to normal values afterward. Molas also had elevated cortisol when being treated for an injury or illness. This is the first step in the development of the use of skin swabs to collect samples for stress analysis in the mola. Additional biochemical analysis is needed to confirm these results and allow this method to be applied to other species of fish. The ocean sunfish (mola; Mola mola) is the heaviest bony fish in the world. This slow-moving fish often is injured by fishing boats that use drift gillnets attributing to its listing as Vulnerable by the IUCN. The Monterey Bay Aquarium (Monterey, CA, USA) has a program that brings in smaller molas from the ocean and acclimates them for an exhibit. When they grow too large for the million-gallon Open Seas exhibit, they are returned to Monterey Bay through a "reverse" acclimatization. Our overall goal was to use skin swabs to evaluate mola stress physiology to better understand the effects of this program. Our objectives were to validate this non-invasive method by taking opportunistic swabs throughout acclimatization and during stressful events. We swabbed each individual (n = 12) in three different body locations. Swabs were analyzed using a cortisol enzyme immunoassay. We averaged the three swabs and examined the absolute change of cortisol from the first taken upon handling to during treatments and the different acclimation stages. We considered elevated cortisol concentrations to be ≥1.5-fold higher than the first sample. Overall, mean (±SEM) cortisol varied among individuals (564.2 ± 191.5 pg/mL swab (range, 18.3–7012.0 pg/mL swab). The majority (four of six) of molas swabbed within the first week or month had elevated skin cortisol compared to their first sample. All seven molas that were being treated for an injury or illness had elevated skin cortisol (range, 1.7- to 127.6-fold higher) compared to their post-acclimation sample. This is the first step in validating the use of non-invasive skin swabs for glucocorticoid analysis in the mola. Further biochemical analysis is needed to determine the specific steroids that are being measured. [ABSTRACT FROM AUTHOR]

In this paper, a novel finite volume model with unstructured mesh and implicit dual time stepping is proposed for simulating unsaturated infiltration flows based on Richards's equation (RE), which is one of the most challenging problems in earth science. In time, a matrix-free fully implicit dual time stepping algorithm is developed to discrete the equation, and in space, the equation is discretized by the finite volume model with unstructured grid. The new method is assessed and evaluated by benchmark and engineering water infiltration cases. Both numerical solutions in the literature and solutions of a commercial package called GEO-Studio are used to verify the accuracy of the proposed algorithm. An unsteady water infiltration simulation case is carried out as the application of the current model by using the topographic dataset of the Monterey Bay in California. The results demonstrate that the new algorithm is robust and practical, with fast convergence and high accuracy. [ABSTRACT FROM AUTHOR]

Fog is challenging to predict, and the accuracy of fog prediction may depend on location and time of day. Furthermore, accurate detection of fog is difficult, since, historically, it is often carried out based on visual observations which can be biased and are often not very frequent. Furthermore, visual observations are more challenging to make during the night. To overcome these limitations, we detected fog using FM-120 instruments, which continuously measured liquid water content in the air in the Monterey, California (USA), area. We used and compared the prediction performance of logistic regression (LR) and random forest (RF) models each evening between 5 pm and 9 pm, which is often the time when advection fog is generated in this coastal region. The relative performances of the models depended on the hours between 5 pm and 9 pm, and the two models often generated different predictions. In such cases, a consensus approach was considered by revisiting the past performance of each model and weighting more heavily the more trustworthy model for a given hour. The LR resulted in a higher sensitivity (hit rate) than the RF model early in the evening, but the overall performance of the RF was usually better than that of the LR. The consensus approach provided more robust prediction performance (closer to a better accuracy level between the two methods). It was difficult to conclude which of the LR and RF models was superior consistently, and the consensus approach provided robustness in 3 and 2 h forecasts. [ABSTRACT FROM AUTHOR]

Spinosyn insecticides are widely used in conventional berry production, and spinosad is regarded as the most effective insecticide for managing Drosophila suzukii (Matsumura) (Diptera: Drosophilidae), spotted-wing drosophila, in organic berry crops. Following the 2017 identification of spinosad resistance in caneberry fields in the Watsonville area, Santa Cruz Co., California, we conducted a study to examine the seasonal and annual susceptibility of D. suzukii over a three-year period. Adult flies were collected from two conventional and two organic caneberry fields in the Monterey Bay region, California, at 'early', 'middle', and 'late' time points during the 2018–2020 growing seasons, and their susceptibility to spinosad was assessed. Results demonstrated that spinosad susceptibility in the D. suzukii field populations generally decreased during the fruit production season (from June through November), and over consecutive seasons. LC50 values of adults from the conventional sites were determined to be as high as 228.7 mg l–1 in 2018, 665.6 mg l–1 in 2019, and 2700.8 mg l–1 in 2020. For the organically managed fields, LC50s of adults were as great as 300.0 mg l–1 in 2018, 1291.5 mg l–1 in 2019, and 2547.1 mg l–1 in 2020. Resistance ratios based on the LC50 values were as high as 10.7-, 13.2-, and 16.9-fold in 2018, 2019, and 2020, respectively. These results should serve as a caution for growers in other production areas, facilitate informed choice of insecticides used in D. suzukii management, and emphasize the need to develop effective insecticide resistance management strategies for this insect. [ABSTRACT FROM AUTHOR]

Very large waves, such as rogue waves, can be dangerous for ships and offshore structures. There is no consensus on the theoretical occurrence probability of these rogues and ocean measurements containing rogue waves are rare. This paper addresses the long-term occurrence probability of rogue waves using time-extreme (TE) and space–time extreme (STE) statistical wave models, evaluated with a significant amount of historical directional wave data from Monterey Bay, California, USA. A novel understanding of these models is obtained by exploring the area size for which the STE models estimate a higher rogue wave occurrence probability compared to the TE models. For four rogue wave and crest heights the return periods until a 95% rogue wave occurrence probability are estimated. To illustrate an application of this statistical analysis, the risk of rogue waves to a spar-type floating wind turbine is evaluated. Based on both the dynamic response and the long-term occurrence probability of the rogue wave, this research presents a new and advanced approach for a risk analysis of rogue waves to floating offshore structures. • Rogue wave long-term occurrence probability is estimated via historical wave data. • Time-extreme and space–time extreme statistical wave models are evaluated. [ABSTRACT FROM AUTHOR]

Phytoplankton (microscopic algae) play an important role in marine ecology. Resulting from a combination of physical, chemical, and biological processes, the distribution of phytoplankton is patchy, particularly in coastal marine ecosystems. Patches of high chlorophyll represent areas where enhanced primary productivity and biogeochemical cycling can occur. The scientific goal is to place observations within these biological hotspots to enable more extensive characterization of the environment and plankton populations. Aerial or satellite remote sensing can detect optical signal originating from phytoplankton within a limited depth range only near the ocean surface, and application of remote sensing is limited by atmospheric clarity. To observe the development of patchy phytoplankton communities in situ, we need the ability to locate and track individual patches. In this article, we present a method for an autonomous underwater vehicle (AUV) to autonomously find and climb on a positive horizontal gradient of chlorophyll to locate and track a phytoplankton patch. In two experiments in 2021, a Tethys-class long-range AUV autonomously located and tracked phytoplankton patches in southern Monterey Bay, CA, USA. The experiments demonstrated effectiveness of the method and pointed to the need for increased onboard adaptiveness in autonomous patch finding and tracking. [ABSTRACT FROM AUTHOR]

Internal wave generation due to semi‐diurnal tides (M2) through the acceleration of barotropic tidal flow over sloped topography has received considerable attention over the past several decades. However, the contribution of other tidal constituents and their interactions with M2 have not been as extensively evaluated. Moreover, on the inner shelf, the cross‐shore wind, which is often neglected in the energy conversion studies, dominates the cross‐shore transport and can also affect the energy conversion process. This study addresses this gap by including a diurnal (K1) tidal component and a shoreward diurnal sea breeze in an idealized model of southern Monterey Bay as it represents a highly stratified system that experiences active surface and internal tides. Our simulations demonstrate the role of the K1 tide and its interaction with M2, which is constructive and insensitive to the initial phase lag. Wind‐induced perturbations grow with the wind speed and enhance M2 conversion. On the other hand, the wind interaction with the K1 and M2K1 tides highly depends on the timing with constructive (destructive) conversion occurring when the shoreward wind intensifies during the ebb (flood) tide. Interactions among tides and winds lead to highly variable conversion rates, changes in timing and location of peak conversion, and a range of internal wave frequencies. Such a dynamic alone can be responsible for the complex internal wave environments often observed in the nearshore. Plain Language Summary: Tidal energy is often dissipated in the deep ocean through internal waves (waves that occur beneath the water surface). Internal waves are induced by tidal flow over sloped topography, mainly at the continental shelf break. However, internal wave generation can also occur near shore. In shallow water, tides and sea breezes can affect coastal ocean dynamics, including energy conversion. In this study, we investigate these interactions and the role of environmental parameters such as wind speed, spring‐neap cycle, wind intensification timing and ocean density stratification. We find that nearshore internal wave generation is not likely to be observed as periodic, and the magnitude of energy conversion is variable. Key Points: The linear supper‐position of energy conversion by tides and cross‐shore wind can introduce an error ≥15% on the inner‐shelf regionThe cross‐shore wind interacts constructively with M2 and destructively or constructively with M2K1 and K1 depending on their phasingThe linear superposition of conversion by M2 and K1 can introduce an error up to 40% for cases with the pycnocline shallower than 17.5 m [ABSTRACT FROM AUTHOR]

Common ravens (Corvus corax; ravens) are known nest predators that have the ability to negatively impact nesting birds, including imperiled species of seabirds and shorebirds. We conducted systematic necropsies of ravens that were lethally controlled in Monterey Bay, California, USA during 2013-2015, in or near western snowy plover (Charadrius nivosus nivosus) nesting areas, in an effort to better understand body condition, overall health, and diet of individual ravens. Raven predation of snowy plover nests has increased over the years in the Monterey Bay study area, and lethal removal of ravens has been employed to reduce predation. Most ravens examined in this study were in moderate to excellent body condition and also exhibited good organ health. There were statistically significant differences between male and female morphometrics (mass, culmen length, and wing length; P < 0.05). Stomach content analysis indicated a varied diet with consumption of animal remains and eggshell fragments, and anthropogenic sources of food (e.g., human food items and human-produced nonfood items). Our study provides evidence that lethal control of ravens targeted some individual ravens that were responsible for depredating snowy plover nests. [ABSTRACT FROM AUTHOR]