Moving Toward a Strategy for Addressing Climate Displacement of Marine Resources: A Proof-of-Concept

Abstract

However, to be effective they must be based on high spatial-and temporal resolution environmental data. Such a sensitive and spatially explicit predictive approach may be used to inform more effective adaptive management strategies of resources in novel climatic conditions.

Seascape connectivity of European anchovy in the Central Mediterranean Sea revealed by weighted Lagrangian backtracking and bio-energetic modelling

“…Here we perform simulations to investigate potential variations in the ultimate fecundity of European Anchovy under temperature and food availability conditions observed during the study period (2009–2012). The model output, expressed in terms of Total Reproductive Output (TRO, i.e., the total number of eggs per life span), is presented in a scenario-based quantitative map 28 , 40 .…”

“…DEB represents a reliable and powerful tool to mechanistically describe the whole life cycle of an organism individual performance and to make predictions of life-history traits 27 , 40 , 50 – 52 . In particular, DEB is a complex mechanistic model that relies on several differential equations that are solved to obtain the final amount of energy allocated to vital functions, such as metabolic maintenance and to growth and reproduction 53 .…”

“…In the present study, we followed a well-tested spatially explicit contextualized approach already successfully adopted in several companion studies 27 , 40 , 57 . This approach consists in running DEB models in each spatial pixel of the study area using organismal body temperature (which is assumed to be similar to the Sea Surface Temperature, as extracted through satellite imagery for every single pixel) and environmental food availability.…”

“…This approach consists in running DEB models in each spatial pixel of the study area using organismal body temperature (which is assumed to be similar to the Sea Surface Temperature, as extracted through satellite imagery for every single pixel) and environmental food availability. Food availability was expressed as density (wet mass mg m −3 ), which for anchovy primarily comprise zooplankton, and obtained as a spatially continuous dataset on the distribution of food throughout the study area 40 . Nevertheless, to run DEB model in each pixel with local temperature and food density is a long computational process.…”

“…Nevertheless, to run DEB model in each pixel with local temperature and food density is a long computational process. Thus, due to the large number of pixels of the study area, we moved the standard DEB model from the original Kooijman’s Matlab code ( https://www.bio.vu.nl/thb/ )—once adapted it using anchovy DEB parameters 40 —to an R code. In doing so, we were able to automatize and speed up the process since R coding improve the computational effort and allows running DEB models at larger spatial and temporal scales 27 , 40 , 58 .…”