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As the basis of oceanic food webs and a key component of the biological carbon pump, planktonic organisms play major roles in the oceans. Their study benefited from the development of in situ imaging instruments, which provide higher spatio-temporal resolution than previous tools. But these instruments collect huge quantities of images, the vast majority of which are of marine snow particles or imaging artifacts. Among them, the In Situ Ichthyoplankton Imaging System (ISIIS) samples the largest water volumes (> 100 L s-1) and thus produces particularly large datasets. To extract manageable amounts of ecological information from in situ images, we propose to focus on planktonic organisms early in the data processing pipeline: at the segmentation stage. We compared three segmentation methods, particularly for smaller targets, in which plankton represents less than 1% of the objects: (i) a traditional thresholding over the background, (ii) an object detector based on maximally stable extremal regions (MSER), and (iii) a content-aware object detector, based on a Convolutional Neural Network (CNN). These methods were assessed on a subset of ISIIS data collected in the Mediterranean Sea, from which a ground truth dataset of > 3,000 manually delineated organisms is extracted. The naive thresholding method captured 97.3% of those but produced ~340,000 segments, 99.1% of which were therefore not plankton (i.e. recall = 97.3%, precision = 0.9%). Combining thresholding with a CNN missed a few more planktonic organisms (recall = 91.8%) but the number of segments decreased 18-fold (precision increased to 16.3%). The MSER detector produced four times fewer segments than thresholding (precision = 3.5%), missed more organisms (recall = 85.4%), but was considerably faster. Because naive thresholding produces ~525,000 objects from 1 minute of ISIIS deployment, the more advanced segmentation methods significantly improve ISIIS data handling and ease the subsequent taxonomic classifica

Despite their long-standing and central role in the dissemination, promotion and defense of science. scientific societies currently face a unique combination of economic, social and technological changes. As a result, one of the most pressing challenges facing many societies is declining membership due to reduced recruitment and a failure to retain members, particularly early-career scientists (ECSs). To ensure that professional biological societies retain long-term viability and relevance, the recruitment and retention of ECSs needs to be a main priority. Here we propose a series of recommendations that we, a group of ECSs, believe will help professional societies better integrate and retain ECSs. We discuss each recommendation and detail its implementation using examples from our personal experiences in the global seabird research and management communities and from our collective experience as members of several professional societies. We believe these recommendations will not only help recruit and retain ECSs as society members, but will also directly benefit the organizations themselves.