Over 100 free-ranging adult California sea lions ( Zalophus californianus) and one Northern fur seal ( Callorhinus ursinus), predominantly adult females, were intoxicated by domoic acid (DA) during three harmful algal blooms between 1998 and 2000 in central and northern California coastal waters. The vector prey item was Northern anchovy ( Engraulis mordax) and the primary DA-producing algal diatom was Psuedonitzschia australis. Postmortem examination revealed gross and histologic findings that were distinctive and aided in diagnosis. A total of 109 sea lions were examined, dying between 1 day and 10 months after admission to a marine mammal rehabilitation center. Persistent seizures with obtundation were the main clinical findings. Frequent gross findings in animals dying acutely consisted of piriform lobe malacia, myocardial pallor, bronchopneumonia, and complications related to pregnancy. Gross findings in animals dying months after intoxication included bilateral hippocampal atrophy. Histologic observations implicated limbic system seizure injury consistent with excitotoxin exposure. Peracutely, there was microvesicular hydropic degeneration within the neuropil of the hippocampus, amygdala, pyriform lobe, and other limbic structures. Acutely, there was ischemic neuronal necrosis, particularly apparent in the granular cells of the dentate gyrus and the pyramidal cells within the hippocampus cornu ammonis (CA) sectors CA4, CA3, and CA1. Dentate granular cell necrosis has not been reported in human or experimental animal DA toxicity and may be unique to sea lions. Chronically, there was gliosis, mild nonsuppurative inflammation, and loss of laminar organization in affected areas.

The vaquita is the most critically endangered marine mammal, with fewer than 19 remaining in the wild. First described in 1958, the vaquita has been in rapid decline for more than 20 years resulting from inadvertent deaths due to the increasing use of large‐mesh gillnets. To understand the evolutionary and demographic history of the vaquita, we used combined long‐read sequencing and long‐range scaffolding methods with long‐ and short‐read RNA sequencing to generate a near error‐free annotated reference genome assembly from cell lines derived from a female individual. The genome assembly consists of 99.92% of the assembled sequence contained in 21 nearly gapless chromosome‐length autosome scaffolds and the X‐chromosome scaffold, with a scaffold N50 of 115 Mb. Genome‐wide heterozygosity is the lowest (0.01%) of any mammalian species analysed to date, but heterozygosity is evenly distributed across the chromosomes, consistent with long‐term small population size at genetic equilibrium, rather than low diversity resulting from a recent population bottleneck or inbreeding. Historical demography of the vaquita indicates long‐term population stability at less than 5,000 (Ne) for over 200,000 years. Together, these analyses indicate that the vaquita genome has had ample opportunity to purge highly deleterious alleles and potentially maintain diversity necessary for population health.

The prevalence of cancer in wild California sea lions (Zalophus californianus) is one of the highest amongst mammals, with 18–23% of adult animals examined post-mortem over the past 40 years having urogenital carcinoma. To date, organochlorines, genotype and infection with Otarine herpesvirus-1 (OtHV-1) have been identified in separate studies using distinct animals as associated with this carcinoma. Multi-year studies using large sample sizes to investigate the relative importance of multiple factors on marine mammal health are rare due to logistical and ethical challenges. The objective of this study was to use a case control approach with samples from 394 animals collected over 20 years in a multifactorial analysis to explore the relative importance of distinct factors identified to date as associated with sea lion cancer in the likelihood of sea lion carcinoma. Stepwise regression indicated that the best model to explain carcinoma occurrence included herpesvirus status, contaminant exposure, and blubber depth, but not genotype at a single microsatellite locus, PV11. The odds of carcinoma was 43.57 times higher in sea lions infected with OtHV-1 (95% CI 14.61, 129.96, p < 0.001), and 1.48 times higher for every unit increase in the log_e[contaminant concentrations], ng g^–1 (an approximate tripling of concentration), in their blubber (95% CI 1.11, 1.97, p < 0.007), after controlling for the effect of blubber depth. These findings demonstrate the importance of contaminant exposure combined with OtHV1 infection, in the potential for cancer occurrence in wild sea lions.

Understanding the genetic and fitness consequences of anthropogenic bottlenecks is crucial for biodiversity conservation. However, studies of bottlenecked populations combining genomic approaches with fitness data are rare. Theory predicts that severe bottlenecks deplete genetic diversity, exacerbate inbreeding depression and decrease population viability. However, actual outcomes are complex and depend on how a species’ unique demography affects its genetic load. We used population genetic and veterinary pathology data, demographic modelling, whole-genome resequencing and forward genetic simulations to investigate the genomic and fitness consequences of a near-extinction event in the northern elephant seal. We found no evidence of inbreeding depression within the contemporary population for key fitness components, including body mass, blubber thickness and susceptibility to parasites and disease. However, we detected a genomic signature of a recent extreme bottleneck (effective population size = 6; 95% confidence interval = 5.0–7.5) that will have purged much of the genetic load, potentially leading to the lack of observed inbreeding depression in our study. Our results further suggest that deleterious genetic variation strongly impacted the post-bottleneck population dynamics of the northern elephant seal. Our study provides comprehensive empirical insights into the intricate dynamics underlying species-specific responses to anthropogenic bottlenecks.

Confronted with the challenge of understanding population-level processes, disease ecologists and epidemiologists often simplify quantitative data into distinct physiological states (e.g. susceptible, exposed, infected, recovered). However, data defining these states often fall along a spectrum rather than into clear categories. Hence, the host-pathogen relationship is more accurately defined using quantitative data, often integrating multiple diagnostic measures, just as clinicians do to assess their patients. We use quantitative data on a major neglected tropical disease (Leptospira interrogans) in California sea lions (Zalophus californianus) to improve individual-level and population-level understanding of this Leptospira reservoir system. We create a “host-pathogen space” by mapping multiple biomarkers of infection (e.g. serum antibodies, pathogen DNA) and disease state (e.g. serum chemistry values) from 13 longitudinally sampled, severely ill individuals to characterize changes in these values through time. Data from these individuals describe a clear, unidirectional trajectory of disease and recovery within this host-pathogen space. Remarkably, this trajectory also captures the broad patterns in larger cross-sectional datasets of 1456 wild sea lions in all states of health but sampled only once. Our framework enables us to determine an individual’s location in their time-course since initial infection, and to visualize the full range of clinical states and antibody responses induced by pathogen exposure. We identify predictive relationships between biomarkers and outcomes such as survival and pathogen shedding, and use these to impute values for missing data, thus increasing the size of the useable dataset. Mapping the host-pathogen space using quantitative biomarker data enables more nuanced understanding of an individual’s time course of infection, duration of immunity, and probability of being infectious. Such maps also make efficient use of limited data for rare or poorly understood diseases, by providing a means to rapidly assess the range and extent of potential clinical and immunological profiles. These approaches yield benefits for clinicians needing to triage patients, prevent transmission, and assess immunity, and for disease ecologists or epidemiologists working to develop appropriate risk management strategies to reduce transmission risk on a population scale (e.g. model parameterization using more accurate estimates of duration of immunity and infectiousness) and to assess health impacts on a population scale. A pathogen can cause variable disease severity across different host individuals, and these presentations change over the time-course from infection to recovery. In addition, different pathogens may induce similar clinical presentations. These facts complicate efforts to identify infections caused by rare or neglected pathogens and to understand factors governing disease spread in humans and animals, particularly when data are limited. These biological complexities are omitted from classical approaches to modeling infectious disease, which typically rely on discrete and well-defined disease states. Here we show that by analyzing multiple biomarkers of health and infection simultaneously, treating these values as quantitative rather than binary indicators, and including a modest amount of longitudinal sampling of hosts, we can create a map of the host-pathogen interaction that shows the full spectrum of disease presentations and opens doors for new insights and predictions. By accounting for individual variation and capturing changes through time since infection, this mapping framework enables more robust interpretation of cross-sectional data; e.g., to detect predictive relationships between biomarkers and key outcomes such as survival, or to assess whether observed disease is associated with the pathogen of interest. This approach can help epidemiologists, ecologists and clinicians to better study and manage the many infectious diseases that exhibit complex relationships with their hosts.