Predicting the impacts of anthropogenic disturbances on marine populations

Abstract

Marine ecosystems are increasingly exposed to anthropogenic disturbances that cause animals to change behavior and move away from potential foraging grounds. Here we present a process-based modeling framework for assessing population consequences of such sub-lethal behavioral effects. It builds directly on how disturbances influence animal movements, foraging and energetics, and is therefore applicable to a wide range of species. To demonstrate the model we assess the impact of wind farm construction noise on the North Sea harbor porpoise population. Subsequently, we demonstrate how the model can be used to minimize population impacts of disturbances through spatial planning. Population models that build on the fundamental processes that determine animal fitness have a high predictive power in novel environments, making them ideal for marine management. K E Y W O R D Sagent-based model, anthropogenic disturbances, cumulative effects, displacement, harbor porpoise, individual-based modeling, marine spatial planning, movement model, Phocoena phocoena

Understanding the population consequences of disturbance

“…Passive acoustic monitoring techniques offer a more continuous alternative to visual sampling for collecting such data on cetaceans. They have been used to assess the responses of harbor porpoises ( Phocoena phocoena ) to wind farm developments (Brandt, Diederichs, Betke, & Nehls, ; Nabe‐Nielsen, Sibly, Tougaard, Teilmann, & Sveegaard, ; Nabe‐Nielsen et al., ), of Blainville's beaked whales ( Mesoplodon densirostris ) to sonar (Moretti et al., ; Tyack et al., ), and of bottlenose dolphins ( Tursiops truncatus ) to boat presence (Pirotta, Merchant, Thompson, Barton, & Lusseau, ). In the absence of empirical data, behavioral responses have been extrapolated from better‐studied species or assumed, often in terms of the number of lost foraging days (King et al., ; New et al., ; Villegas‐Amtmann et al., , ).…”

“…() examined the relation between foraging activity and energy stores (estimated from changes in buoyancy) of female southern elephant seals ( Mirounga leonina ) over the course of a foraging trip. Other applications have inferred changes in energy stores from models of foraging activity that either treat energy explicitly using a bioenergetic approach (Beltran, Testa, & Burns, ; Christiansen & Lusseau, ; Farmer, Noren, Fougères, Machernis, & Baker, ; McHuron, Costa, Schwarz, & Mangel, ; McHuron, Mangel, Schwarz, & Costa, ; Noren, ; Pirotta, Mangel, et al., ; Villegas‐Amtmann et al., , ) or use an arbitrarily scaled energy metric that represents an underlying motivational state (Nabe‐Nielsen et al., , ; New, Harwood, et al., ; Pirotta, Harwood, et al., ; Pirotta, New, Harwood, & Lusseau, ). Although technologies that can measure the morphometrics of individuals remotely may make it easier to estimate changes in body condition directly (e.g., Christiansen, Dujon, Sprogis, Arnould, & Bejder, ; Miller, Best, Perryman, Baumgartner, & Moore, ), extensive health assessment in cetaceans will probably remain limited to a few closely monitored coastal populations, due to logistical constraints (Wells et al., ).…”

“…In the absence of a direct estimate of calf survival, Christiansen and Lusseau () used the fetal length of minke whales ( Balaenoptera acutorostrata ) as a proxy, and investigated how fetal length was associated with female body condition (Christiansen, Víkingsson, Rasmussen, & Lusseau, ). All other PCoD studies of marine mammals have assumed a simple relationship between various health metrics and vital rates (McHuron, Costa, et al., ; Nabe‐Nielsen et al., , ; Pirotta, Mangel, et al., ; Villegas‐Amtmann et al., , ).…”

Human‐driven habitat conversion is a more immediate threat to Amboseli elephants than climate change

“…We believe IBMs present a strong option for improving our ability to predict the responses of animal populations to combined stressors and novel environmental conditions (Nabe-Nielsen et al, 2018;Stillman et al, 2015). How food availability is influenced by environmental change is estimated and underlies IBM predictions of elephant population size.…”

“…IBMs present a powerful tool for future scenario modelling as their process-based approach maintains their predictive ability under novel environmental conditions (Stillman, Railsback, Giske, Berger, & Grimm, 2015) and can capture the cumulative impacts of multiple environmental changes (Nabe-Nielsen et al, 2018). Projected food availability is used to drive an individual-based model (IBM) which predicts vital elephant demographic rates through an energy budget.…”