New research, co-authored by BioSS researcher Phil Bouchet and published in Ecological Applications provides an important step forward in understanding how combinations of anthropogenic stressors affect the recovery of long-lived, endangered species — and how this knowledge can be used to better inform conservation action.

Using the critically endangered North Atlantic right whale (Eubalaena glacialis) as an example, the study explores how multiple stressors—such as entanglement in fishing gear, vessel strikes, and changes in prey availability—interact to influence individual health, survival, reproduction, and ultimately population recovery. Rather than treating these pressures in isolation, the authors use a sophisticated hierarchical Bayesian modelling framework to link stressor exposure at the individual level to long-term population dynamics, showing how pressures can interact in complex ways that make their combined impact greater — or at least different — than the sum of their parts. Importantly, the model also demonstrates that the effects of stressors are often scale-dependent, such that some impacts act immediately on individual behaviour or body condition, while others only become apparent years or even decades later as a result of reduced breeding success or survival. For species that reproduce slowly, even small, repeated impacts can accumulate over time and significantly hinder population recovery.

The authors also reflect on the practical challenges of studying cumulative impacts, including data limitations, uncertainty, and the difficulty of linking short-term observations to long-term population outcomes. They outline clear priorities for future work, including better integration of long-term monitoring, individual-based data, and population models, as well as closer collaboration between researchers, managers, and policymakers.

By combining long-term data with advanced modelling approaches, the study provides a framework for identifying which combinations of stressor reductions are most likely to deliver meaningful conservation gains. The findings offer clear guidance for policymakers, managers, and regulators seeking to prioritise actions that will most effectively support the recovery of endangered marine species.

This work was supported by the Office of Naval Research (N000142012697, N000142112096) and the Strategic Environmental Research and Development Program (RC20-1097, RC20-7188, RC21-3091).

Full study details are available here:

Pirotta et al. (2025). The combined effects of multiple stressors in an endangered, long-lived species: Lessons learned and ways forward. Ecological Applications, 35(8): e70144. DOI: 10.1002/eap.70144.

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Figure: Schematic representation of the spatial version of the model. Model processes are represented for individual i at time t. The yellow boxes indicate the data streams, including age informing the somatic growth model (ai,t), intrinsic stressors (Zj,i,t) affecting health, the values of the stressor surfaces across the R regional polygons (G1:R,t representing entanglement risk, representing vessel strike risk, and prey1:R,t representing prey conditions), NARW density derived from published density surface models (DSM1:R,t), and the observation models (VHA data oi,t,x, where x indicates each of the four VHA variables, sightings ei,t, and photogrammetric measures of length Pi,t; dotted arrows).

Photo credit (BioSS home page): Georgia Department of Natural Resources/ NOAA permit #20556