Decreasing body size is associated with reduced calving probability in critically endangered North Atlantic right whales.

Body size is key to many life-history processes, including reproduction. Across species, climate change and other stressors have caused reductions in the body size to which animals can grow, called asymptotic size, with consequences for demography. A reduction in mean asymptotic length was documented for critically endangered North Atlantic right whales, in parallel with declines in health and vital rates resulting from human activities and environmental changes. Here, we tested whether smaller body size was associated with lower reproductive output, using a state-space model for individual health, survival and reproduction that quantifies the mechanistic links between these processes. Body size (as represented by the cube of length) was strongly associated with a female's calving probability at each reproductive opportunity. This relationship explained 62% of the variation in calving among reproductive females, along with their decreasing health (20%). The effects of decreasing mean body size on reproductive performance are another concerning indication of the worsening prospects for this species and many others affected by environmental change, requiring a focus of conservation and management interventions on improving conditions that affect reproduction as well as reducing mortality.

An expert-based system to predict population survival rate from health data.

Timely detection and understanding of causes for population decline are essential for effective wildlife management and conservation. Assessing trends in population size has been the standard approach, but we propose that monitoring population health could prove more effective. We collated data from 7 bottlenose dolphin (Tursiops truncatus) populations in the southeastern United States to develop a method for estimating survival probability based on a suite of health measures identified by experts as indices for inflammatory, metabolic, pulmonary, and neuroendocrine systems. We used logistic regression to implement the veterinary expert system for outcome prediction (VESOP) within a Bayesian analysis framework. We fitted parameters with records from 5 of the sites that had a robust network of responders to marine mammal strandings and frequent photographic identification surveys that documented definitive survival outcomes. We also conducted capture-mark-recapture (CMR) analyses of photographic identification data to obtain separate estimates of population survival rates for comparison with VESOP survival estimates. The VESOP analyses showed that multiple measures of health, particularly markers of inflammation, were predictive of 1- and 2-year individual survival. The highest mortality risk 1 year following health assessment related to low alkaline phosphatase (odds ratio [OR] = 10.2 [95% CI: 3.41-26.8]), whereas 2-year mortality was most influenced by elevated globulin (OR = 9.60 [95% CI: 3.88-22.4]); both are markers of inflammation. The VESOP model predicted population-level survival rates that correlated with estimated survival rates from CMR analyses for the same populations (1-year Pearson's r = 0.99, p = 1.52 × 10-5 ; 2-year r = 0.94, p = 0.001). Although our proposed approach will not detect acute mortality threats that are largely independent of animal health, such as harmful algal blooms, it can be used to detect chronic health conditions that increase mortality risk. Random sampling of the population is important and advancement in remote sampling methods could facilitate more random selection of subjects, obtainment of larger sample sizes, and extension of the approach to other wildlife species.

Un sistema basado en conocimiento experto para predecir la tasa de supervivencia a partir de datos de salud Resumen La detección y el entendimiento oportunos de la declinación poblacional son esenciales para que el manejo y la conservación de fauna tengan efectividad. La evaluación de las tendencias en el tamaño poblacional ha sido la estrategia estándar, pero proponemos que el monitoreo de la salud poblacional podría ser más efectivo. Recopilamos datos de siete poblaciones de delfines (Tursiops truncatus) en el sureste de Estados Unidos para desarrollar un método de estimación de la probabilidad de supervivencia con base en un conjunto de medidas sanitarias identificadas por expertos como índices para los sistemas inflamatorio, metabólico, pulmonar y neuroendocrino. Usamos la regresión logística para implementar el sistema de expertos veterinarios para la predicción de resultados (SEVPR) en un análisis bayesiano. Ajustamos los parámetros con los registros de cinco sitios que contaban con una buena red de respondientes a los varamientos de mamíferos marinos y censos de identificación fotográfica (foto-ID) que documentaron los resultados de supervivencia definitivos. También realizamos análisis de marcaje-recaptura (MR) en los datos de identificación fotográfica para obtener estimados separados de las tasas de supervivencia poblacional para compararlos con los estimados del SEVPR. Los análisis del SEVPR mostraron que varias medidas sanitarias, particularmente los marcadores de inflamación son buenos predictores de la supervivencia individual para uno y dos años. El riesgo de mortalidad más alto un año después de la valoración sanitaria se relacionó con una fosfatasa alcalina baja (cociente de probabilidades de 10.2 [95% CI 3.41-26.8]), mientras que la mortalidad a los dos años estuvo más influenciada por una globulina elevada (9.60 [95% CI 3.88-22.4]); ambas son marcadores de la inflamación. El modelo del SEVPR predijo las tasas de supervivencia a nivel poblacional en correlación con las tasas estimadas de supervivencia de los análisis de MR para las mismas poblaciones (Pearson de un año r = 0.99, p = 1.52e-05; dos años r = 0.94, p = 0.001). Aunque nuestra propuesta no detecta las amenazas agudas de mortalidad que en su mayoría son independientes de la salud animal, como la proliferación de algas nocivas, puede usarse para detectar las condiciones crónicas de salud que incrementan el riesgo de mortalidad. Es importante el muestreo aleatorio de la población y los avances en los métodos de muestreo remoto podrían facilitar una selección más aleatoria de los sujetos, la obtención de muestras de mayor tamaño y la expansión de la estrategia a otras especies de fauna.

Using individual-based bioenergetic models to predict the aggregate effects of disturbance on populations: A case study with beaked whales and Navy sonar.

Anthropogenic activities can lead to changes in animal behavior. Predicting population consequences of these behavioral changes requires integrating short-term individual responses into models that forecast population dynamics across multiple generations. This is especially challenging for long-lived animals, because of the different time scales involved. Beaked whales are a group of deep-diving odontocete whales that respond behaviorally when exposed to military mid-frequency active sonar (MFAS), but the effect of these nonlethal responses on beaked whale populations is unknown. Population consequences of aggregate exposure to MFAS was assessed for two beaked whale populations that are regularly present on U.S. Navy training ranges where MFAS is frequently used. Our approach integrates a wide range of data sources, including telemetry data, information on spatial variation in habitat quality, passive acoustic data on the temporal pattern of sonar use and its relationship to beaked whale foraging activity, into an individual-based model with a dynamic bioenergetic module that governs individual life history. The predicted effect of disturbance from MFAS on population abundance ranged between population extinction to a slight increase in population abundance. These effects were driven by the interaction between the temporal pattern of MFAS use, baseline movement patterns, the spatial distribution of prey, the nature of beaked whale behavioral response to MFAS and the top-down impact of whale foraging on prey abundance. Based on these findings, we provide recommendations for monitoring of marine mammal populations and highlight key uncertainties to help guide future directions for assessing population impacts of nonlethal disturbance for these and other long-lived animals.

Managing the effects of multiple stressors on wildlife populations in their ecosystems: developing a cumulative risk approach.

Assessing cumulative effects of human activities on ecosystems is required by many jurisdictions, but current science cannot meet regulatory demands. Regulations define them as effect(s) of one human action combined with other actions. Here we argue for an approach that evaluates the cumulative risk of multiple stressors for protected wildlife populations within their ecosystems. Monitoring effects of each stressor is necessary but not sufficient to estimate how multiple stressors interact to affect wildlife populations. Examining the mechanistic pathways, from cellular to ecological, by which stressors affect individuals can help prioritize stressors and interpret how they interact. Our approach uses health indicators to accumulate the effects of stressors on individuals and to estimate changes in vital rates, driving population status. We advocate using methods well-established in human health and integrating them into ecosystem-based management to protect the health of commercially and culturally important wildlife populations and to protect against risk of extinction for threatened species. Our approach will improve abilities to conserve and manage ecosystems but will also demand significant increases in research and monitoring effort. We advocate for increased investment proportional to the economic scale of human activities in the Anthropocene and their pervasive effects on ecology and biodiversity.

Estimating the abundance of the critically endangered Baltic Proper harbour porpoise (Phocoena phocoena) population using passive acoustic monitoring.

Knowing the abundance of a population is a crucial component to assess its conservation status and develop effective conservation plans. For most cetaceans, abundance estimation is difficult given their cryptic and mobile nature, especially when the population is small and has a transnational distribution. In the Baltic Sea, the number of harbour porpoises (Phocoena phocoena) has collapsed since the mid-20th century and the Baltic Proper harbour porpoise is listed as Critically Endangered by the IUCN and HELCOM; however, its abundance remains unknown. Here, one of the largest ever passive acoustic monitoring studies was carried out by eight Baltic Sea nations to estimate the abundance of the Baltic Proper harbour porpoise for the first time. By logging porpoise echolocation signals at 298 stations during May 2011-April 2013, calibrating the loggers' spatial detection performance at sea, and measuring the click rate of tagged individuals, we estimated an abundance of 71-1105 individuals (95% CI, point estimate 491) during May-October within the population's proposed management border. The small abundance estimate strongly supports that the Baltic Proper harbour porpoise is facing an extremely high risk of extinction, and highlights the need for immediate and efficient conservation actions through international cooperation. It also provides a starting point in monitoring the trend of the population abundance to evaluate the effectiveness of management measures and determine its interactions with the larger neighboring Belt Sea population. Further, we offer evidence that design-based passive acoustic monitoring can generate reliable estimates of the abundance of rare and cryptic animal populations across large spatial scales.

Understanding the combined effects of multiple stressors: A new perspective on a longstanding challenge.

Wildlife populations and their habitats are exposed to an expanding diversity and intensity of stressors caused by human activities, within the broader context of natural processes and increasing pressure from climate change. Estimating how these multiple stressors affect individuals, populations, and ecosystems is thus of growing importance. However, their combined effects often cannot be predicted reliably from the individual effects of each stressor, and we lack the mechanistic understanding and analytical tools to predict their joint outcomes. We review the science of multiple stressors and present a conceptual framework that captures and reconciles the variety of existing approaches for assessing combined effects. Specifically, we show that all approaches lie along a spectrum, reflecting increasing assumptions about the mechanisms that regulate the action of single stressors and their combined effects. An emphasis on mechanisms improves analytical precision and predictive power but could introduce bias if the underlying assumptions are incorrect. A purely empirical approach has less risk of bias but requires adequate data on the effects of the full range of anticipated combinations of stressor types and magnitudes. We illustrate how this spectrum can be formalised into specific analytical methods, using an example of North Atlantic right whales feeding on limited prey resources while simultaneously being affected by entanglement in fishing gear. In practice, case-specific management needs and data availability will guide the exploration of the stressor combinations of interest and the selection of a suitable trade-off between precision and bias. We argue that the primary goal for adaptive management should be to identify the most practical and effective ways to remove or reduce specific combinations of stressors, bringing the risk of adverse impacts on populations and ecosystems below acceptable thresholds.

Modeling population effects of the Deepwater Horizon oil spill on a long-lived species.

The 2010 Deepwater Horizon (DWH) oil spill exposed common bottlenose dolphins (Tursiops truncatus) in Barataria Bay, Louisiana to heavy oiling that caused increased mortality and chronic disease and impaired reproduction in surviving dolphins. We conducted photographic surveys and veterinary assessments in the decade following the spill. We assigned a prognostic score (good, fair, guarded, poor, or grave) for each dolphin to provide a single integrated indicator of overall health, and we examined temporal trends in prognostic scores. We used expert elicitation to quantify the implications of trends for the proportion of the dolphins that would recover within their lifetime. We integrated expert elicitation, along with other new information, in a population dynamics model to predict the effects of observed health trends on demography. We compared the resulting population trajectory with that predicted under baseline (no spill) conditions. Disease conditions persisted and have recently worsened in dolphins that were presumably exposed to DWH oil: 78% of those assessed in 2018 had a guarded, poor, or grave prognosis. Dolphins born after the spill were in better health. We estimated that the population declined by 45% (95% CI 14-74) relative to baseline and will take 35 years (95% CI 18-67) to recover to 95% of baseline numbers. The sum of annual differences between baseline and injured population sizes (i.e., the lost cetacean years) was 30,993 (95% CI 6607-94,148). The population is currently at a minimum point in its recovery trajectory and is vulnerable to emerging threats, including planned ecosystem restoration efforts that are likely to be detrimental to the dolphins' survival. Our modeling framework demonstrates an approach for integrating different sources and types of data, highlights the utility of expert elicitation for indeterminable input parameters, and emphasizes the importance of considering and monitoring long-term health of long-lived species subject to environmental disasters. Article impact statement: Oil spills can have long-term consequences for the health of long-lived species; thus, effective restoration and monitoring are needed.

El derrame de petróleo Deepwater Horizon (DWH) en 2010 expuso gravemente a este hidrocarburo a los delfines (Tursiops truncatus) de la Bahía Barataria, Luisiana, causando un incremento en la mortalidad y en las enfermedades crónicas, y deteriorando la reproducción de los delfines sobrevivientes. Realizamos censos fotográficos y evaluaciones veterinarias durante la década posterior al derrame. Asignamos un puntaje pronóstico (bueno, favorable, moderado, malo, o grave) a cada delfín para proporcionar un indicador integrado único de la salud en general. También examinamos las tendencias temporales de estos puntajes. Usamos información de expertos para cuantificar las implicaciones de las tendencias para la proporción de delfines que se recuperaría dentro de su periodo de vida. Integramos esta información, junto con información nueva, a un modelo de dinámica poblacional para predecir los efectos sobre la demografía de las tendencias observadas en la salud. Comparamos la trayectoria poblacional resultante con aquella pronosticada bajo condiciones de línea base (sin derrame). Las condiciones de enfermedad persistieron y recientemente han empeorado en los delfines que supuestamente estuvieron expuestos al petróleo de DWH: 78% de aquellos evaluados en 2018 tuvieron un pronóstico moderado, malo o grave. Los delfines que nacieron después del derrame contaron con mejor salud. Estimamos que la población declinó en un 45% (95% CI 14-74) relativo a la línea base y tardará 35 años (95% CI 18-67) en recuperar el 95% de los números de línea base. La suma de las diferencias anuales entre el tamaño poblacional de línea base y el dañado (es decir, los años cetáceos perdidos) fue de 30,993 (95% CI 6,607-94,148). La población actualmente está en un punto mínimo de su trayectoria de recuperación y es vulnerable a las amenazas emergentes, incluyendo los esfuerzos de restauración ambiental planeada que probablemente sean nocivos para la supervivencia de los delfines. Nuestro marco de modelado demuestra una estrategia para la integración de diferentes fuentes y tipos de datos, resalta la utilidad de la información de expertos para los parámetros de aportación indeterminable, y enfatiza la importancia de la consideración y el monitoreo de la salud a largo plazo de las especies longevas sujetas a los desastres ambientales. Modelado de los Efectos Poblacionales del Derrame de Petróleo Deepwater Horizon sobre Especies Longevas.

Discrete-space continuous-time models of marine mammal exposure to Navy sonar.

Assessing the patterns of wildlife attendance to specific areas is relevant across many fundamental and applied ecological studies, particularly when animals are at risk of being exposed to stressors within or outside the boundaries of those areas. Marine mammals are increasingly being exposed to human activities that may cause behavioral and physiological changes, including military exercises using active sonars. Assessment of the population-level consequences of anthropogenic disturbance requires robust and efficient tools to quantify the levels of aggregate exposure for individuals in a population over biologically relevant time frames. We propose a discrete-space, continuous-time approach to estimate individual transition rates across the boundaries of an area of interest, informed by telemetry data collected with uncertainty. The approach allows inferring the effect of stressors on transition rates, the progressive return to baseline movement patterns, and any difference among individuals. We apply the modeling framework to telemetry data from Blainville's beaked whale (Mesoplodon densirostris) tagged in the Bahamas at the Atlantic Undersea Test and Evaluation Center (AUTEC), an area used by the U.S. Navy for fleet readiness training. We show that transition rates changed as a result of exposure to sonar exercises in the area, reflecting an avoidance response. Our approach supports the assessment of the aggregate exposure of individuals to sonar and the resulting population-level consequences. The approach has potential applications across many applied and fundamental problems where telemetry data are used to characterize animal occurrence within specific areas.

Alternative method for assessment of southwestern Atlantic humpback whale population status.

The population of humpback whales (Megaptera novaeangliae) wintering off eastern South America was exploited by commercial whaling almost to the point of extinction in the mid-twentieth century. Since cessation of whaling in the 1970s it is recovering, but the timing and level of recovery is uncertain. We implemented a Bayesian population dynamics model describing the population's trajectory from 1901 and projecting it to 2040 to revise a previous population status assessment that used Sampling-Importance-Resampling in a Bayesian framework. Using our alternative method for model fitting (Markov chain Monte Carlo), which is more widely accessible to ecologists, we replicate a "base case scenario" to verify the effect on model results, and introduce additional data to update the status assessment. Our approach allowed us to widen the previous informative prior on carrying capacity to better reflect scientific uncertainty around historical population levels. The updated model provided more precise estimates for population sizes over the period considered (1901-2040) and suggests that carrying capacity (K: median 22,882, mean 22,948, 95% credible interval [CI] 22,711-23,545) and minimum population size (N1958: median 305, mean 319, 95% CI 271-444) might be lower than previously estimated (K: median 24,558, mean 25,110, 95% CI 22,791-31,118; N1958: median 503, mean 850, 95% CI 159-3,943). However, posterior 95% credible intervals of parameters in the updated model overlap those of the previous study. Our approach provides an accessible framework for investigating the status of depleted animal populations for which information is available on historical mortality (e.g., catches) and intermittent estimates of population size and/or trend.

High site-fidelity in common bottlenose dolphins despite low salinity exposure and associated indicators of compromised health.

More than 2,000 common bottlenose dolphins (Tursiops truncatus) inhabit the Barataria Bay Estuarine System in Louisiana, USA, a highly productive estuary with variable salinity driven by natural and man-made processes. It was unclear whether dolphins that are long-term residents to specific areas within the basin move in response to fluctuations in salinity, which at times can decline to 0 parts per thousand in portions of the basin. In June 2017, we conducted health assessments and deployed satellite telemetry tags on dolphins in the northern portions of the Barataria Bay Estuarine System Stock area (9 females; 4 males). We analyzed their fine-scale movements relative to modeled salinity trends compared to dolphins tagged near the barrier islands (higher salinity environments) from 2011 to 2017 (37 females; 21 males). Even though we observed different movement patterns among individual dolphins, we found no evidence that tagged dolphins moved coincident with changes in salinity. One tagged dolphin spent at least 35 consecutive days, and 75 days in total, in salinity under 5 parts per thousand. Health assessments took place early in a seasonal period of decreased salinity. Nonetheless, we found an increased prevalence of skin lesions, as well as abnormalities in serum biochemical markers and urine:serum osmolality ratios for dolphins sampled in lower salinity areas. This study provides essential information on the likely behavioral responses of dolphins to changes in salinity (e.g., severe storms or from the proposed Mid-Barataria Sediment Diversion project) and on physiological markers to inform the timing and severity of impacts from low salinity exposure.

Calibrating models of cancer invasion: parameter estimation using approximate Bayesian computation and gradient matching.

We present two different methods to estimate parameters within a partial differential equation model of cancer invasion. The model describes the spatio-temporal evolution of three variables-tumour cell density, extracellular matrix density and matrix degrading enzyme concentration-in a one-dimensional tissue domain. The first method is a likelihood-free approach associated with approximate Bayesian computation; the second is a two-stage gradient matching method based on smoothing the data with a generalized additive model (GAM) and matching gradients from the GAM to those from the model. Both methods performed well on simulated data. To increase realism, additionally we tested the gradient matching scheme with simulated measurement error and found that the ability to estimate some model parameters deteriorated rapidly as measurement error increased.

REVIEW: Assessing North Atlantic right whale health: threats, and development of tools critical for conservation of the species.

Whaling has decimated North Atlantic right whales Eubalaena glacialis (NARW) since the 11th century and southern right whales E. australis (SRW) since the 19th century. Today, NARWs are Critically Endangered and decreasing, whereas SRWs are recovering. We review NARW health assessment literature, NARW Consortium databases, and efforts and limitations to monitor individual and species health, survival, and fecundity. Photographs are used to track individual movement and external signs of health such as evidence of vessel and entanglement trauma. Post-mortem examinations establish cause of death and determine organ pathology. Photogrammetry is used to assess growth rates and body condition. Samples of blow, skin, blubber, baleen and feces quantify hormones that provide information on stress, reproduction, and nutrition, identify microbiome changes, and assess evidence of infection. We also discuss models of the population consequences of multiple stressors, including the connection between human activities (e.g. entanglement) and health. Lethal and sublethal vessel and entanglement trauma have been identified as major threats to the species. There is a clear and immediate need for expanding trauma reduction measures. Beyond these major concerns, further study is needed to evaluate the impact of other stressors, such as pathogens, microbiome changes, and algal and industrial toxins, on NARW reproductive success and health. Current and new health assessment tools should be developed and used to monitor the effectiveness of management measures and will help determine whether they are sufficient for a substantive species recovery.

Effects of a seismic survey on movement of free-ranging Atlantic cod.

Geophysical exploration of the seabed is typically done through seismic surveys, using airgun arrays that produce intense, low-frequency-sound pulses1 that can be heard over hundreds of square kilometers, 24/7.2,3 Little is known about the effects of these sounds on free-ranging fish behavior.4-6 Effects reported range from subtle individual change in activity and swimming depth for captive fish7,8 to potential avoidance9 and changes in swimming velocity and diurnal activity patterns for free-swimming animals.10 However, the extent and duration of behavioral responses to seismic surveys remain largely unexplored for most fish species.4 In this study, we investigated the effect of a full-scale seismic survey on the movement behavior of free-swimming Atlantic cod (Gadus morhua). We found that cod did not leave the detection area more than expected during the experimental survey but that they left more quickly from 2 days to 2 weeks after the survey. Furthermore, during the exposure, cod decreased their activity, with time spent being "locally active" (moving small distances, showing high body acceleration) becoming shorter, and time spent being "inactive" (moving small distances, having low body acceleration) becoming longer. Additionally, diurnal activity cycles were disrupted with lower locally active peaks at dusk and dawn, periods when cod are known to actively feed.11,12 The combined effects of delayed deterrence and activity disruption indicate the potential for seismic surveys to affect energy budgets and to ultimately lead to population-level consequences.13.

Acoustic detection range and population density of Cuvier's beaked whales estimated from near-surface hydrophones.

The population density of Cuvier's beaked whales is estimated acoustically with drifting near-surface hydrophone recorders in the Catalina Basin. Three empirical approaches (trial-based, distance-sampling, and spatially explicit capture-recapture) are used to estimate the probability of detecting the echolocation pulses as a function of range. These detection functions are used with two point-transect methods (snapshot and dive-cue) to estimate density. Measurement errors result in a small range of density estimates (3.9-5.4 whales per 1000 km2). Use of multiple approaches and methods allows comparison of the required information and assumptions of each. The distance-sampling approach with snapshot-based density estimates has the most stringent assumptions but would be the easiest to implement for large scale surveys of beaked whale density. Alternative approaches to estimating detection functions help validate this approach. The dive cue method of density estimation has promise, but additional work is needed to understand the potential bias caused by animal movement during a dive. Empirical methods are a viable alternative to the theoretical acoustic modeling approaches that have been used previously to estimate beaked whale density.

Roaring and repetition: How bowhead whales adjust their call density and source level (Lombard effect) in the presence of natural and seismic airgun survey noise.

Over 500 000 automated and manual acoustic localizations, measured over seven years between 2008 and 2014, were used to examine how natural wind-driven noise and anthropogenic seismic airgun survey noise influence bowhead whale call densities (calls/km2/min) and source levels during their fall migration in the Alaskan Beaufort Sea. Noise masking effects, which confound measurements of behavioral changes, were removed using a modified point transect theory. The authors found that mean call densities generally rose with increasing continuous wind-driven noise levels. The occurrence of weak airgun pulse sounds also prompted an increase in call density equivalent to a 10-15 dB change in natural noise level, but call density then dropped substantially with increasing cumulative sound exposure level (cSEL) from received airgun pulses. At low in-band noise levels the mean source level of the acoustically-active population changed to nearly perfectly compensate for noise increases, but as noise levels increased further the mean source level failed to keep pace, reducing the population's communication space. An increase of >40 dB cSEL from seismic airgun activity led to an increase in source levels of just a few decibels. These results have implications for bowhead acoustic density estimation, and evaluations of the masking impacts of anthropogenic noise.

Decline towards extinction of Mexico's vaquita porpoise (Phocoena sinus).

The vaquita (Phocoena sinus) is a small porpoise endemic to Mexico. It is listed by IUCN as Critically Endangered because of unsustainable levels of bycatch in gillnets. The population has been monitored with passive acoustic detectors every summer from 2011 to 2018; here we report results for 2017 and 2018. We combine the acoustic trends with an independent estimate of population size from 2015, and visual observations of at least seven animals in 2017 and six in 2018. Despite adoption of an emergency gillnet ban in May 2015, the estimated rate of decline remains extremely high: 48% decline in 2017 (95% Bayesian credible interval (CRI) 78% decline to 9% increase) and 47% in 2018 (95% CRI 80% decline to 13% increase). Estimated total population decline since 2011 is 98.6%, with greater than 99% probability the decline is greater than 33% yr-1. We estimate fewer than 19 vaquitas remained as of summer 2018 (posterior mean 9, median 8, 95% CRI 6-19). From March 2016 to March 2019, 10 dead vaquitas killed in gillnets were found. The ongoing presence of illegal gillnets despite the emergency ban continues to drive the vaquita towards extinction. Immediate management action is required if the species is to be saved.

Understanding the population consequences of disturbance.

Managing the nonlethal effects of disturbance on wildlife populations has been a long-term goal for decision makers, managers, and ecologists, and assessment of these effects is currently required by European Union and United States legislation. However, robust assessment of these effects is challenging. The management of human activities that have nonlethal effects on wildlife is a specific example of a fundamental ecological problem: how to understand the population-level consequences of changes in the behavior or physiology of individual animals that are caused by external stressors. In this study, we review recent applications of a conceptual framework for assessing and predicting these consequences for marine mammal populations. We explore the range of models that can be used to formalize the approach and we identify critical research gaps. We also provide a decision tree that can be used to select the most appropriate model structure given the available data. Synthesis and applications: The implementation of this framework has moved the focus of discussion of the management of nonlethal disturbances on marine mammal populations away from a rhetorical debate about defining negligible impact and toward a quantitative understanding of long-term population-level effects. Here we demonstrate the framework's general applicability to other marine and terrestrial systems and show how it can support integrated modeling of the proximate and ultimate mechanisms that regulate trait-mediated, indirect interactions in ecological communities, that is, the nonconsumptive effects of a predator or stressor on a species' behavior, physiology, or life history.

Fin whale density and distribution estimation using acoustic bearings derived from sparse arrays.

Passive acoustic monitoring of marine mammals is common, and it is now possible to estimate absolute animal density from acoustic recordings. The most appropriate density estimation method depends on how much detail about animals' locations can be derived from the recordings. Here, a method for estimating cetacean density using acoustic data is presented, where only horizontal bearings to calling animals are estimable. This method also requires knowledge of call signal-to-noise ratios, as well as auxiliary information about call source levels, sound propagation, and call production rates. Results are presented from simulations, and from a pilot study using recordings of fin whale (Balaenoptera physalus) calls from Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) hydrophones at Wake Island in the Pacific Ocean. Simulations replicating different animal distributions showed median biases in estimated call density of less than 2%. The estimated average call density during the pilot study period (December 2007-February 2008) was 0.02 calls hr-1 km2 (coefficient of variation, CV: 15%). Using a tentative call production rate, estimated average animal density was 0.54 animals/1000 km2 (CV: 52%). Calling animals showed a varied spatial distribution around the northern hydrophone array, with most detections occurring at bearings between 90 and 180 degrees.

Modelling the broadband propagation of marine mammal echolocation clicks for click-based population density estimates.

Passive acoustic monitoring with widely-dispersed hydrophones has been suggested as a cost-effective method to monitor population densities of echolocating marine mammals. This requires an estimate of the area around each receiver over which vocalizations are detected-the "effective detection area" (EDA). In the absence of auxiliary measurements enabling estimation of the EDA, it can be modelled instead. Common simplifying model assumptions include approximating the spectrum of clicks by flat energy spectra, and neglecting the frequency-dependence of sound absorption within the click bandwidth (narrowband assumption), rendering the problem amenable to solution using the sonar equation. Here, it is investigated how these approximations affect the estimated EDA and their potential for biasing the estimated density. EDA was estimated using the passive sonar equation, and by applying detectors to simulated clicks injected into measurements of background noise. By comparing model predictions made using these two approaches for different spectral energy distributions of echolocation clicks, but identical click source energy level and detector settings, EDA differed by up to a factor of 2 for Blainville's beaked whales. Both methods predicted relative density bias due to narrowband assumptions ranged from 5% to more than 100%, depending on the species, detector settings, and noise conditions.

Comparing methods suitable for monitoring marine mammals in low visibility conditions during seismic surveys.

Loud sound emitted during offshore industrial activities can impact marine mammals. Regulations typically prescribe marine mammal monitoring before and/or during these activities to implement mitigation measures that minimise potential acoustic impacts. Using seismic surveys under low visibility conditions as a case study, we review which monitoring methods are suitable and compare their relative strengths and weaknesses. Passive acoustic monitoring has been implemented as either a complementary or alternative method to visual monitoring in low visibility conditions. Other methods such as RADAR, active sonar and thermal infrared have also been tested, but are rarely recommended by regulatory bodies. The efficiency of the monitoring method(s) will depend on the animal behaviour and environmental conditions, however, using a combination of complementary systems generally improves the overall detection performance. We recommend that the performance of monitoring systems, over a range of conditions, is explored in a modelling framework for a variety of species.