Preprints
Filtering by Subject: Aquaculture and Fisheries Life Sciences
Resilient foods for preventing global famine: a review of food supply interventions for global catastrophic food shocks including nuclear winter and infrastructure collapse
Published: 2024-09-12
Subjects: Agricultural Science, Agriculture, Animal Sciences, Aquaculture and Fisheries Life Sciences, Chemical Engineering, Engineering, Food Science, Life Sciences, Plant Sciences, Risk Analysis
Global catastrophic threats to the food system upon which human society depends are numerous. A nuclear war or volcanic eruption could collapse agricultural yields by inhibiting crop growth. Nuclear electromagnetic pulses or extreme pandemics could disrupt industry and mass-scale food supply by unprecedented levels. Global food storage is limited. What can be done? This article presents the state [...]
Tracing timing of growth in cultured mollusks using strontium spiking
Published: 2022-12-23
Subjects: Aquaculture and Fisheries Life Sciences, Biogeochemistry, Geochemistry, Paleontology
Growth experiments present a powerful tool for determining the effect of environmental parameters on growth and carbonate composition in biogenic calcifiers. For successful proxy calibration and biomineralization studies, it is vital to exactly identify volumes of carbonate precipitated at precise intervals during the experiment. Here, we investigate the use of strontium labelling in mollusk [...]
Revealing the Global Longline Fleet with Satellite Radar
Published: 2022-04-06
Subjects: Aquaculture and Fisheries Life Sciences, Remote Sensing
Because many vessels use the Automatic Identification System (AIS) to broadcast GPS positions, recent advances in satellite technology have enabled us to map global fishing activity. Understanding of human activity at sea, however, is limited because an unknown number of vessels do not broadcast AIS. Those vessels can be detected by satellite-based Synthetic Aperture Radar (SAR) imagery, but this [...]
Fish species classification in underwater video monitoring using Convolutional Neural Networks
Published: 2018-05-15
Subjects: Animal Sciences, Aquaculture and Fisheries Life Sciences, Computer Sciences, Environmental Monitoring, Environmental Sciences, Life Sciences, Other Life Sciences, Physical Sciences and Mathematics, Software Engineering
This report presents a case study for automatic fish species classification in underwater video monitoring of fish passes. Although the presented approach is based on the FishCam monitoring system, it can be used with any video-based monitoring system. The presented classification scheme in this study, is based on Convolutional Neural Networks that do not require the calculation of any [...]