Cyanorak v2.1: a scalable information system dedicated to the visualization and expert curation of marine and brackish picocyanobacteria genomes.

Cyanorak v2.1 (http://www.sb-roscoff.fr/cyanorak) is an information system dedicated to visualizing, comparing and curating the genomes of Prochlorococcus, Synechococcus and Cyanobium, the most abundant photosynthetic microorganisms on Earth. The database encompasses sequences from 97 genomes, covering most of the wide genetic diversity known so far within these groups, and which were split into 25,834 clusters of likely orthologous groups (CLOGs). The user interface gives access to genomic characteristics, accession numbers as well as an interactive map showing strain isolation sites. The main entry to the database is through search for a term (gene name, product, etc.), resulting in a list of CLOGs and individual genes. Each CLOG benefits from a rich functional annotation including EggNOG, EC/K numbers, GO terms, TIGR Roles, custom-designed Cyanorak Roles as well as several protein motif predictions. Cyanorak also displays a phyletic profile, indicating the genotype and pigment type for each CLOG, and a genome viewer (Jbrowse) to visualize additional data on each genome such as predicted operons, genomic islands or transcriptomic data, when available. This information system also includes a BLAST search tool, comparative genomic context as well as various data export options. Altogether, Cyanorak v2.1 constitutes an invaluable, scalable tool for comparative genomics of ecologically relevant marine microorganisms.

Evaluating economic impacts of protected areas in contexts with limited data; the case of three national parks in Iceland.

Economic impacts of protected areas (PAs) are receiving more attention in recent years and methodology in this area is advancing. Multiple studies have illustrated that PAs are a potent land use strategy to generate multiple and direct economic benefits. These benefits are driven by tourism as the central economic activity in PAs worldwide. This study takes the case of Snæfellsjökull, Vatnajökull and þingvellir National Parks (NPs) in Iceland, characterized by limited regional economic data and multi-destination and -purpose visitor travel patterns. Its main objective is to advance understanding of the economic impacts related to PAs in the context of limited data availability. Our analysis is based on the widely used Money Generation Model (MGM2) -methodology, localized to the Icelandic context by using Icelandic labour data and national input-output (I-O) tables regionalized using the Flegg Location Quotient (FLQ). We provide a consistent approach for handling multi-destination and -purpose trips, and separating spending data between local and overall impacts. Based on 2019 visitor and economic data, the visitors (N = 2087) spent, on average, $113 per day in the parks and generated estimated total economic impacts between $30-99 MM with 347-1140 jobs generated across the study sites. For example, in Vatnajökull NP's southern region, the jobs supported locally by the park constituted 36% of all the jobs in the municipalities. Combined tax revenue to the state from the three parks was $88 MM. The localized methodology generated similar economic impacts as earlier studies but showed that employment impacts were previously overestimated by the default models. Our approach and findings can be used as a reference for others applying the MGM2 or similar methods, and they support policy development, decision-making and informed discussion between researchers, practitioners in PA and tourism management, municipalities and communities around PAs. Being able to show economic impacts is increasingly important for PAs to ensure sustained funding amid budget cuts and the transition of government bodies to business units. Limitations of the study include a lack of winter data for Vatnajökull and þingvellir NPs and broad categorization of the Icelandic economic data used in the I-O table regionalization. In further research, a comprehensive sustainability analysis is needed to complement the economic impact analysis and site-specific factors could be analysed in more detail.

Differential global distribution of marine picocyanobacteria gene clusters reveals distinct niche-related adaptive strategies.

The ever-increasing number of available microbial genomes and metagenomes provides new opportunities to investigate the links between niche partitioning and genome evolution in the ocean, especially for the abundant and ubiquitous marine picocyanobacteria Prochlorococcus and Synechococcus. Here, by combining metagenome analyses of the Tara Oceans dataset with comparative genomics, including phyletic patterns and genomic context of individual genes from 256 reference genomes, we show that picocyanobacterial communities thriving in different niches possess distinct gene repertoires. We also identify clusters of adjacent genes that display specific distribution patterns in the field (eCAGs) and are thus potentially involved in the same metabolic pathway and may have a key role in niche adaptation. Several eCAGs are likely involved in the uptake or incorporation of complex organic forms of nutrients, such as guanidine, cyanate, cyanide, pyrimidine, or phosphonates, which might be either directly used by cells, for example for the biosynthesis of proteins or DNA, or degraded to inorganic nitrogen and/or phosphorus forms. We also highlight the enrichment of eCAGs involved in polysaccharide capsule biosynthesis in Synechococcus populations thriving in both nitrogen- and phosphorus-depleted areas vs. low-iron (Fe) regions, suggesting that the complexes they encode may be too energy-consuming for picocyanobacteria thriving in the latter areas. In contrast, Prochlorococcus populations thriving in Fe-depleted areas specifically possess an alternative respiratory terminal oxidase, potentially involved in the reduction of Fe(III) to Fe(II). Altogether, this study provides insights into how phytoplankton communities populate oceanic ecosystems, which is relevant to understanding their capacity to respond to ongoing climate change.