Abstract

The Population Consequences of Disturbance (PCoD) model is a conceptual framework used to assess the potential for population-level consequences following exposure of animals to a disturbance activity or stressor. This framework is a four-step process, progressing from changes in individual behavior and/or physiology, to changes in individual health, then vital rates, and finally to population-level effects. Despite its simplicity, there are few complete PCoD models available for any marine mammal species due to a lack of data available to parameterize many of the steps. Here, we present an application of the PCoD framework for migrating humpback whales exposed to a simulated commercial seismic survey scenario. We approached the framework in two ways; first, progressing sequentially forwards through the steps and basing our assessment on lactating females. This cohort was considered to be the most vulnerable in terms of energetic costs of disturbance, and most likely to influence any change in population growth due to future breeding success. Field measurements of behavioral responses of migrating humpback whales to seismic air guns from a previous study were used to parameterize an agent-based model (ABM). This ABM was used to estimate the probability of response, where a response was defined as a change in the migratory movement of female-calf pairs, and the duration of any resulting delay in migration. We then estimated the energetic consequences of any delay in migration for the lactating females and created population growth models with which to assess any population-level effects. The results of the forwards approach suggested a low potential for population consequences of seismic surveys on migrating humpbacks. Working backwards through the framework, we investigated “worst case” scenarios that could potentially lead to a population-level effect. Here, we started with increasing calf mortality and assumed that an exposure time greater than 48 h would increase mortality risk. We determined the most likely context in which this exposure would occur (resting area) and then tested this context within an ABM. This backwards approach illustrates how the PCoD model can be used to make management decisions regarding animal populations and exposure to anthropogenic stressors.

Highlights

  • Assessing the non-lethal effects of anthropogenic disturbance on marine mammal populations is a challenging goal, but one that is necessary for environmental decision makers and managers

  • The “population consequences of disturbance (PCoD)” model has been proposed as a framework with which to relate the response of individuals to a stressor to changes in their vital rates and health, and subsequently to changes in population dynamics (National Research Council, 2005; Harwood et al, 2016)

  • The physiological constraints of migration mean that a marine migratory species, such as the humpback whale, are likely to be susceptible to human-induced changes in environmental conditions as they must travel through habitat with human presence (Lennox et al, 2016)

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Summary

Introduction

Assessing the non-lethal effects of anthropogenic disturbance on marine mammal populations is a challenging goal, but one that is necessary for environmental decision makers and managers. While legislation in Europe (Council Directive 92/43/EEC, 1992) and the United States (Marine Mammal Protection Act, 1972) requires the assessment of population-level effects, management decisions are normally based on studies of individual behavioral responses. PCoD models have been developed to evaluate the effect of wind farm construction on the North Sea harbor porpoise (Phocoena phocoena) populations (e.g., King et al, 2015; Nabe-Nielsen et al, 2018) These models include a mix of empirical data, expert elicitation (King et al, 2015) and simulations of animals’ movements, energetics, and/or survival (New et al, 2014; Nabe-Nielsen et al, 2018). Full PCoD models assessing the effects of the Deepwater Horizon oil spill on bottlenose dolphin (Tursiops truncatus) populations (Schwacke et al, 2017) and the effects of oil and gas field developments on foraging gray whales (Eschrichtius robustus; Villegas-Amtmann et al, 2017) included theoretical modeling for certain parts

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