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.

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.

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.

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.

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.

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.

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.

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.

Passive acoustic monitoring of the decline of Mexico's critically endangered vaquita.

The vaquita (Phocoena sinus) is the world's most endangered marine mammal with approximately 245 individuals remaining in 2008. This species of porpoise is endemic to the northern Gulf of California, Mexico, and historically the population has declined because of unsustainable bycatch in gillnets. An illegal gillnet fishery for an endangered fish, the totoaba (Totoaba macdonaldi), has recently resurged throughout the vaquita's range. The secretive but lucrative wildlife trade with China for totoaba swim bladders has probably increased vaquita bycatch mortality by an unknown amount. Precise population monitoring by visual surveys is difficult because vaquitas are inherently hard to see and have now become so rare that sighting rates are very low. However, their echolocation clicks can be identified readily on specialized acoustic detectors. Acoustic detections on an array of 46 moored detectors indicated vaquita acoustic activity declined by 80% between 2011 and 2015 in the central part of the species' range. Statistical models estimated an annual rate of decline of 34% (95% Bayesian credible interval -48% to -21%). Based on results from 2011 to 2014, the government of Mexico enacted and is enforcing an emergency 2-year ban on gillnets throughout the species' range to prevent extinction, at a cost of US$74 million to compensate fishers. Developing precise acoustic monitoring methods proved critical to exposing the severity of vaquitas' decline and emphasizes the need for continual monitoring to effectively manage critically endangered species.

Last call: Passive acoustic monitoring shows continued rapid decline of critically endangered vaquita.

The vaquita is a critically endangered species of porpoise. It produces echolocation clicks, making it a good candidate for passive acoustic monitoring. A systematic grid of sensors has been deployed for 3 months annually since 2011; results from 2016 are reported here. Statistical models (to compensate for non-uniform data loss) show an overall decline in the acoustic detection rate between 2015 and 2016 of 49% (95% credible interval 82% decline to 8% increase), and total decline between 2011 and 2016 of over 90%. Assuming the acoustic detection rate is proportional to population size, approximately 30 vaquita (95% credible interval 8-96) remained in November 2016.

Spatio-temporal variation in click production rates of beaked whales: Implications for passive acoustic density estimation.

Passive acoustic monitoring has become an increasingly prevalent tool for estimating density of marine mammals, such as beaked whales, which vocalize often but are difficult to survey visually. Counts of acoustic cues (e.g., vocalizations), when corrected for detection probability, can be translated into animal density estimates by applying an individual cue production rate multiplier. It is essential to understand variation in these rates to avoid biased estimates. The most direct way to measure cue production rate is with animal-mounted acoustic recorders. This study utilized data from sound recording tags deployed on Blainville's (Mesoplodon densirostris, 19 deployments) and Cuvier's (Ziphius cavirostris, 16 deployments) beaked whales, in two locations per species, to explore spatial and temporal variation in click production rates. No spatial or temporal variation was detected within the average click production rate of Blainville's beaked whales when calculated over dive cycles (including silent periods between dives); however, spatial variation was detected when averaged only over vocal periods. Cuvier's beaked whales exhibited significant spatial and temporal variation in click production rates within vocal periods and when silent periods were included. This evidence of variation emphasizes the need to utilize appropriate cue production rates when estimating density from passive acoustic data.

Understanding the Population Consequences of Acoustic Disturbance for Marine Mammals.

Loud anthropogenic underwater noise, such as that associated with sonar operations, pile driving, or seismic surveys, can cause behavioral and physiological disturbance to many animals that may affect their survival or ability to breed. However, no formal framework for assessing the population-level consequences of this disturbance is currently available. We describe an interim version of a framework developed by a working group on the population consequences of disturbance, funded by the US Office of Naval Research through the University of California, that can be used to assess the effects of offshore renewable energy developments on marine mammal populations.

The Challenges of Analyzing Behavioral Response Study Data: An Overview of the MOCHA (Multi-study OCean Acoustics Human Effects Analysis) Project.

This paper describes the MOCHA project which aims to develop novel approaches for the analysis of data collected during Behavioral Response Studies (BRSs). BRSs are experiments aimed at directly quantifying the effects of controlled dosages of natural or anthropogenic stimuli (typically sound) on marine mammal behavior. These experiments typically result in low sample size, relative to variability, and so we are looking at a number of studies in combination to maximize the gain from each one. We describe a suite of analytical tools applied to BRS data on beaked whales, including a simulation study aimed at informing future experimental design.

Effects of Model Formulation on Estimates of Health in Individual Right Whales (Eubalaena glacialis).

Right whales are vulnerable to many sources of anthropogenic disturbance including ship strikes, entanglement with fishing gear, and anthropogenic noise. The effect of these factors on individual health is unclear. A statistical model using photographic evidence of health was recently built to infer the true or hidden health of individual right whales. However, two important prior assumptions about the role of missing data and unexplained variance on the estimates were not previously assessed. Here we tested these factors by varying prior assumptions and model formulation. We found sensitivity to each assumption and used the output to make guidelines on future model formulation.

Delphinid echolocation click detection probability on near-seafloor sensors.

The probability of detecting echolocating delphinids on a near-seafloor sensor was estimated using two Monte Carlo simulation methods. One method estimated the probability of detecting a single click (cue counting); the other estimated the probability of detecting a group of delphinids (group counting). Echolocation click beam pattern and source level assumptions strongly influenced detectability predictions by the cue counting model. Group detectability was also influenced by assumptions about group behaviors. Model results were compared to in situ recordings of encounters with Risso's dolphin (Grampus griseus) and presumed pantropical spotted dolphin (Stenella attenuata) from a near-seafloor four-channel tracking sensor deployed in the Gulf of Mexico (25.537°N 84.632°W, depth 1220 m). Horizontal detection range, received level and estimated source level distributions from localized encounters were compared with the model predictions. Agreement between in situ results and model predictions suggests that simulations can be used to estimate detection probabilities when direct distance estimation is not available.

Statistical ecology comes of age.

The desire to predict the consequences of global environmental change has been the driver towards more realistic models embracing the variability and uncertainties inherent in ecology. Statistical ecology has gelled over the past decade as a discipline that moves away from describing patterns towards modelling the ecological processes that generate these patterns. Following the fourth International Statistical Ecology Conference (1-4 July 2014) in Montpellier, France, we analyse current trends in statistical ecology. Important advances in the analysis of individual movement, and in the modelling of population dynamics and species distributions, are made possible by the increasing use of hierarchical and hidden process models. Exciting research perspectives include the development of methods to interpret citizen science data and of efficient, flexible computational algorithms for model fitting. Statistical ecology has come of age: it now provides a general and mathematically rigorous framework linking ecological theory and empirical data.

Dose-response relationships for the onset of avoidance of sonar by free-ranging killer whales.

Eight experimentally controlled exposures to 1-2 kHz or 6-7 kHz sonar signals were conducted with four killer whale groups. The source level and proximity of the source were increased during each exposure in order to reveal response thresholds. Detailed inspection of movements during each exposure session revealed sustained changes in speed and travel direction judged to be avoidance responses during six of eight sessions. Following methods developed for Phase-I clinical trials in human medicine, response thresholds ranging from 94 to 164 dB re 1 µPa received sound pressure level (SPL) were fitted to Bayesian dose-response functions. Thresholds did not consistently differ by sonar frequency or whether a group had previously been exposed, with a mean SPL response threshold of 142 ± 15 dB (mean ± s.d.). High levels of between- and within-individual variability were identified, indicating that thresholds depended upon other undefined contextual variables. The dose-response functions indicate that some killer whales started to avoid sonar at received SPL below thresholds assumed by the U.S. Navy. The predicted extent of habitat over which avoidance reactions occur depends upon whether whales responded to proximity or received SPL of the sonar or both, but was large enough to raise concerns about biological consequences to the whales.

Age is not just a number: How incorrect ageing impacts close-kin mark-recapture estimates of population size.

Population size is a key parameter for the conservation of animal species. Close-kin mark-recapture (CKMR) relies on the observed frequency and type of kinship among individuals sampled from the population to estimate population size. Knowledge of the age of the individuals, or a surrogate thereof, is essential for inference with acceptable precision. One common approach, particularly in fish studies, is to measure animal length and infer age using an assumed age-length relationship (a 'growth curve'). We used simulation to test the effect of misspecifying the length measurement error and the growth curve on population size estimation. Simulated populations represented two fictional shark species, one with a relatively simple life history and the other with a more complex life history based on the grey reef shark (Carcharhinus amblyrhynchos). We estimated sex-specific adult abundance, which we assumed to be constant in time. We observed small median biases in these estimates ranging from 1.35% to 2.79% when specifying the correct measurement error standard deviation and growth curve. CI coverage was adequate whenever the growth curve was correctly specified. Introducing error via misspecified growth curves resulted in changes in the magnitude of the estimated adult population, where underestimating age negatively biased the abundance estimates. Over- and underestimating the standard deviation of length measurement error did not introduce a bias and had negligible effect on the variance in the estimates. Our findings show that assuming an incorrect standard deviation of length measurement error has little effect on estimation, but having an accurate growth curve is crucial for CKMR whenever ageing is based on length measurements. If ageing could be biased, researchers should be cautious when interpreting CKMR results and consider the potential biases arising from inaccurate age inference.

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.