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Marine plankton abundance and dynamics in the open and interior ocean is still an unknown field. The knowledge of gelatinous zooplankton distribution is especially challenging, because this type of plankton has a very fragile structure and cannot be directly sampled using traditional net based techniques. To overcome this shortcoming, Computer Vision techniques can be successfully used for the automatic monitoring of this group.This paper presents the GUARD1 imaging system, a low-cost stand-alone instrument for underwater image acquisition and recognition of gelatinous zooplankton, and discusses the performance of three different methodologies, Tikhonov Regularization, Support Vector Machines and Genetic Programming, that have been compared in order to select the one to be run onboard the system for the automatic recognition of gelatinous zooplankton. The performance comparison results highlight the high accuracy of the three methods in gelatinous zooplankton identification, showing their good capability in robustly selecting relevant features. In particular, Genetic Programming technique achieves the same performances of the other two methods by using a smaller set of features, thus being the most efficient in avoiding computationally consuming preprocessing stages, that is a crucial requirement for running on an autonomous imaging system designed for long lasting deployments, like the GUARD1. The Genetic Programming algorithm has been installed onboard the system, that has been operationally tested in a two-months survey in the Ligurian Sea, providing satisfactory results in terms of monitoring and recognition performances., Competing Interests: The authors declare no conflict of interest. The founding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.

The general aim of this paper is to present a possible multidisciplinary approach to the problem of connectivity among marine protected areas (MPAs) describing some of the mechanisms and vectors that control the dispersal of propagules among spatially distributed marine communities of MPAs in the Southern Adriatic Sea. A joint approach is described that focuses on (a) measurements of surface water current and model data integrated with a dedicated software (LAVA, LAgrangian Variational Analysis), (b) measurements of rafting objects and their evaluation as an alternative way to species dispersal, and (c) a tool to automatically monitor propagules and plankton species in the water column. Studies on the dynamics of water currents demonstrated that the Gargano area has the potential to supply dispersal propagules to the Southern Adriatic both along the Italian coastline and offshore across the basin, thus providing important services to the dispersal processes and the connectivity routes among MPAs. The natural dispersion is however enhanced by floating objects, on which entire marine communities are living and travelling. The number of these objects has greatly increased with the introduction of human litter: in the Adriatic, man-made litter composes nowadays the majority (79 %) of all floating objects, with this corresponding to an almost fourfold increase in the abundance of floating objects since pre-industrial times. Such enhanced dispersion may benefit transmission of propagules from MPAs along biodiversity corridors, but may also enhance the arrival of invasive species. The direct observation of organisms can provide information on the species distribution and mobility. New technology (GUARD-1 system) has been developed to automatically identify spatial or temporal distributions of selected species in the water column by image analysis. The system has so far successfully detected blooms of ctenophores in the water column and is now being tested for identification of other zooplankton groups, such as copepods, as well as marine litter. This low-cost, long-lasting imaging system can be hosted on mobile devices such as drifters, which makes it very suitable for biological dispersal studies.