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While the distribution patterns of cold-water corals, such as Paragorgia arborea, have received increasing attention in recent studies, little is known about their in situ activity patterns. In this paper, we examine polyp activity in P. arborea using machine learning techniques to analyze high-resolution time series data and photographs obtained from an autonomous lander cluster deployed in the Stjernsund, Norway. An interactive illustration of the models derived in this paper is provided online as supplementary material. We find that the best predictor of the degree of extension of the coral polyps is current direction with a lag of three hours. Other variables that are not directly associated with water currents, such as temperature and salinity, offer much less information concerning polyp activity. Interestingly, the degree of polyp extension can be predicted more reliably by sampling the laminar flows in the water column above the measurement site than by sampling the more turbulent flows in the direct vicinity of the corals. Our results show that the activity patterns of the P. arborea polyps are governed by the strong tidal current regime of the Stjernsund. It appears that P. arborea does not react to shorter changes in the ambient current regime but instead adjusts its behavior in accordance with the large-scale pattern of the tidal cycle itself in order to optimize nutrient uptake., 25 pages

To successfully manage marine fisheries using an ecosystem-based approach, long-term predictions of fish stock development considering changing environmental conditions are necessary. Such predictions can be provided by end-to-end ecosystem models, which couple existing physical and biogeochemical ocean models with newly developed spatially-explicit fish stock models. Typically, Individual-Based Models (IBMs) and models based on Advection-Diffusion-Reaction (ADR) equations are employed for the fish stock models. In this paper, we present a novel fish stock model called SPRAT for end-to\hyp{}end ecosystem modeling based on Population Balance Equations (PBEs) that combines the advantages of IBMs and ADR models while avoiding their main drawbacks. SPRAT accomplishes this by describing the modeled ecosystem processes from the perspective of individuals while still being based on partial differential equations. We apply the SPRAT model to explore a well-documented regime shift observed on the eastern Scotian Shelf in the 1990s from a cod-dominated to a herring-dominated ecosystem. Model simulations are able to reconcile the observed multitrophic dynamics with documented changes in both fishing pressure and water temperature, followed by a predator-prey reversal that may have impeded recovery of depleted cod stocks. We conclude that our model can be used to generate new hypotheses and test ideas about spatially interacting fish populations, and their joint responses to both environmental and fisheries forcing., 20 pages

It is a long-standing hypothesis that the concise and customized notation of a DSL improves the performance of developers when compared with a GPL. For non-technical domains—e.g., science—, this hypothesis lacks empirical evidence. Given this lack of empirical evidence, we evaluate a DSL for ecological modeling designed and implemented by us with regard to performance improvements of developers as compared to a GPL. We conduct an online survey with embedded controlled experiments among ecologists to assess the correctness and time spent of the participants when using a DSL for ecosystem simulation specifications compared with a GPL-based solution. We observe that (1) solving tasks with the DSL, the participants’ correctness point score was —depending on the task— on average 61 % up to 63 % higher than with the GPL-based solution and their average time spent per task was reduced by 31 % up to 56 %; (2) the participants subjectively find it easier to work with the DSL, and (3) more than 90 % of the subjects are able to carry out basic maintenance tasks concerning the infrastructure of the DSL used in our treatment, which is based on another internal DSL embedded into Java. The tasks of our experiments are simplified and our web-based editor components do not offer full IDE-support. Our findings indicate that the development of further DSL for the specific needs of the ecological modeling community should be a worthwhile investment to increase its members’ productivity and to enhance the reliability of their scientific results.