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.

Epigenetics, specifically DNA methylation, allows for the estimation of animal age from blood or remotely sampled skin. This multi-tissue epigenetic age estimation clock uses 110 longitudinal samples from 34 Navy bottlenose dolphins (Tursiops truncatus), identifying 195 cytosine-phosphate-guanine sites associated with chronological aging via cross-validation with one individual left out in each fold (R² = 0.95). With a median absolute error of 2.5 years, this clock improves age estimation capacity in wild dolphins, helping conservation efforts and enabling a better understanding of population demographics.

Ecosystems are experiencing elevated levels of disturbance, and species with narrower niches are often more vulnerable to disturbances. Niche breadth is often measured in terms of either diet or habitat use but diet and spatial use are infrequently considered in tandem. These different aspects of niche breadth potentially expose species to different types of disturbances; species with narrow dietary niches may be more affected by disturbances that alter trophic relationships, while species with narrow habitat niches may be more vulnerable to habitat loss and point‐source pollutants. We examined dietary and habitat niche breadth of common bottlenose dolphins, Tursiops truncatus truncatus, from three different nearshore sites in the Gulf of Mexico (GoM). Using stable isotopes, we determined proportional contributions of different prey groups to dolphin diets at each site and through time at one site. We used satellite‐linked telemetry at two sites to determine habitat use and site fidelity. Additionally, we examined the literature on cetacean diet, habitat use, movement, and IUCN status to determine relationships between niche breadth and population status for different species. Dolphin diets varied among sites as available prey varied, but Perciformes fish were the most frequently consumed prey. At the site for which we had temporal data, dolphins consumed more cephalopods in 2015 and 2018 but otherwise consumed primarily Perciformes fish. Dolphins had small utilization distributions and exhibited high site fidelity. Data from 31 cetacean species revealed that most species with vulnerable, threatened, or endangered IUCN statuses not only have specialized diets but also exhibit high site fidelity. Dolphins had diet characteristic of flexible generalists but were habitat specialists with high site fidelity. Dolphin populations in the GoM may have altered their diets in response to environmental changes that have altered community composition and trophic dynamics. On the other hand, their high site fidelity has exposed them to point‐source pollutants, such as oil spills, persistent organic pollutants, and freshwater. Our broader analysis of cetaceans confirmed that species with specialized diets and high site fidelity were the most vulnerable to disturbances, providing a framework to predict which nearshore dolphin populations, and cetaceans in general, are most vulnerable to environmental changes.

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.

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 trun catus) 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.