U. Fernandez-Arcaya

Ecological Role of Submarine Canyons and Need for Canyon Conservation: A Review

Submarine canyons are major geomorphic features of continental margins around the world. Several recent multidisciplinary projects focused on the study of canyons have considerably increased our understanding of their ecological role, the goods and services they provide to human populations, and the impacts that human activities have on their overall ecological condition. Pressures from human activities include fishing, dumping of land-based mine tailings, and oil and gas extraction. Moreover, hydrodynamic processes of canyons enhance the down-canyon transport of litter. The effects of climate change may modify the intensity of currents. This potential hydrographic change is predicted to impact the structure and functioning of canyon communities as well as affect nutrient supply to the deep-ocean ecosystem. This review not only identifies the ecological status of canyons, and current and future issues for canyon conservation, but also highlights the need for a better understanding of anthropogenic impacts on canyon ecosystems and proposes other research required to inform management measures to protect canyon ecosystems.

Relationships between shallow-water cumacean assemblages and sediment characteristics facing the Iranian coast of the Persian Gulf

During two sampling campaigns carried out in August 199 8 and November 2002 , 232 cumaeans from eight species belonging to the families Bodotriidae and Nannastacidae were collected. This paper presents the first ecological data on a shallow water tropical cumacean assemblage from the Persian Gulf, where 50 % of the existing species were recently described as new for the science. Neither the environmental conditions (except for the sediment organic content) nor the cumacean assemblage descriptors differed between the two sampling periods. However, two different species dominated in each period (i.e. Eocuma travancoricum and Heterocuma inerme in 199 8 and 2002 , respectively) and the MDS analysis revealed differences in the assemblage composition between periods, particularly for the deepest sampling stations. An increasing density together with the increase in gravel content, and a decreasing density together with the increasing silt content characterized the distribution pattern of both the whole cumacean assemblages and the two dominant species, the latter being also positively correlated with the mean grain size and negatively correlated with depth and organic matter (E. travancoricum) and with depth (H. inerme).

Expert, Crowd, Students or Algorithm: who holds the key to deep‐sea imagery ‘big data’ processing?

1.Recent technological development has increased our capacity to study the deep sea and the marine benthic realm, particularly with the development of multidisciplinary seafloor observatories. Since 2006, Ocean Networks Canada cabled observatories, have acquired nearly 65 TB and over 90,000 hours of video data from seafloor cameras and Remotely Operated Vehicles (ROVs). Manual processing of these data is time-consuming and highly labour-intensive, and cannot be comprehensively undertaken by individual researchers. These videos are a crucial source of information for assessing natural variability and ecosystem responses to increasing human activity in the deep sea. 2.We compared the performance of three groups of humans and one computer vision algorithm in counting individuals of the commercially important sablefish (or black cod) Anoplopoma fimbria, in recorded video from a cabled camera platform at 900 m depth in a submarine canyon in the Northeast Pacific. The first group of human observers were untrained volunteers recruited via a crowdsourcing platform and the second were experienced university students, who performed the task for their ichthyology class. Results were validated against counts obtained from a scientific expert. 3.All groups produced relatively accurate results in comparison to the expert and all succeeded in detecting patterns and periodicities in fish abundance data. Trained volunteers displayed the highest accuracy and the algorithm the lowest. 4.As seafloor observatories increase in number around the world, this study demonstrates the value of a hybrid combination of crowdsourcing and computer vision techniques as a tool to help process large volumes of imagery to support basic research and environmental monitoring. Reciprocally, by engaging large numbers of online participants in deep-sea research, this approach can contribute significantly to ocean literacy and informed citizen input to policy development.