Global beta diversity patterns of microbial communities in the surface and deep ocean

This is contribution 1112 from AZTI Marine Research Division.-- 14 pages, 4 figures, 3 tables, supporting information https://doi.org/10.1111/geb.13572.-- Data Availability Statement: DNA sequences for surface prokaryotes are publicly available at the European Nucleotide Archive [http://www.ebi.ac.uk/ena; accession number PRJEB25224 (16S rRNA genes)], for deep prokaryotes at the National Center for Biotechnology Information (NCBI) Sequence Read Archive (http://www.ncbi.nlm.nih.gov/Traces/sra) under accession ID SRP031469, and for surface and deep picoeukaryotes at the European Nucleotide Archive with accession number PRJEB23771 (http://www.ebi.ac.uk/ena). Environmental data used in this study are available from https://github.com/ramalok/malaspina.surface.metabacoding, Giner et al. (2020) and Salazar et al. (2015). The code to analyze the data and produce the figures of this research is available from the corresponding author upon request.-- This is the pre-peer reviewed version of the following article: Ernesto Villarino, James R. Watson, Guillem Chust ,A. John Woodill, Benjamin Klempay, Bror Jonsson, Josep M. Gasol, Ramiro Logares, Ramon Massana, Caterina R. Giner, Guillem Salazar, X. Anton Alvarez-Salgado, Teresa S. Catala, Carlos M. Duarte, Susana Agusti, Francisco Mauro, Xabier Irigoien, Andrew D. Barton; Global beta diversity patterns of microbial communities in the surface and deep ocean; Global Ecology and Biogeography 31(11): 2323-2336 (2022), which has been published in final form at https://doi.org/10.1111/geb.13572. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived VersionsAim: Dispersal and environmental gradients shape marine microbial communities, yet the relative importance of these factors across taxa with distinct sizes and dispersal capacity in different ocean layers is unknown. Here, we report a comparative analysis of surface and deep ocean microbial beta diversity and examine how these patterns are tied to oceanic distance and environmental gradients. Location: Tropical and subtropical oceans (30°N–40°S). Time period: 2010-2011. Major taxa studied: Prokaryotes and picoeukaryotes (eukaryotes between 0.2 and 3 μm). Methods: Beta diversity was calculated from metabarcoding data on prokaryotic and picoeukaryotic microbes collected during the Malaspina expedition across the tropical and subtropical oceans. Mantel correlations were used to determine the relative contribution of environment and oceanic distance driving community beta diversity. Results: Mean community similarity across all sites for prokaryotes was 38.9% in the surface and 51.4% in the deep ocean, compared to mean similarity of 25.8 and 12.1% in the surface and deep ocean, respectively, for picoeukaryotes. Higher dispersal rates and smaller body sizes of prokaryotes relative to picoeukaryotes likely contributed to the significantly higher community similarity for prokaryotes compared with picoeukaryotes. The ecological mechanisms determining the biogeography of microbes varied across depth. In the surface ocean, the environmental differences in space were a more important factor driving microbial distribution compared with the oceanic distance, defined as the shortest path between two sites avoiding land. In the deep ocean, picoeukaryote communities were slightly more structured by the oceanic distance, while prokaryotes were shaped by the combined action of oceanic distance and environmental filtering. Main conclusions: Horizontal gradients in microbial community assembly differed across ocean depths, as did mechanisms shaping them. In the deep ocean, the oceanic distance and environment played significant roles driving microbial spatial distribution, while in the surface the influence of the environment was stronger than oceanic distanceData collection was funded by the Malaspina 2010 Circumnavigation Expedition project (Consolider-Ingenio 2010, CSD2008-00077) and cofunded by the Basque Government (Department Deputy of Agriculture, Fishing and Food Policy). We acknowledge funding from the Spanish Government through the “Severo Ochoa Center of Excelence” accreditation CEX2019-000928-S. [...] We also acknowledge H2020 Mission Atlantic project (Ref. Grant Agreement Number 862428). EV was supported by an international exchange post-doc scholarship to Scripps Institution of Oceanography and Oregon State University granted by the Education Department of the Basque GovernmentPeer reviewe

To Spray or Not to Spray: A Decision Analysis of Coffee Berry Borer in Hawaii

Integrated pest management strategies were adopted to combat the coffee berry borer (CBB) after its arrival in Hawaii in 2010. A decision tree framework is used to model the CBB integrated pest management recommendations, for potential use by growers and to assist in developing and evaluating management strategies and policies. The model focuses on pesticide spraying (spray/no spray) as the most significant pest management decision within each period over the entire crop season. The main result from the analysis suggests the most important parameter to maximize net benefit is to ensure a low initial infestation level. A second result looks at the impact of a subsidy for the cost of pesticides and shows a typical farmer receives a positive net benefit of $947.17. Sensitivity analysis of parameters checks the robustness of the model and further confirms the importance of a low initial infestation level vis-a-vis any level of subsidy. The use of a decision tree is shown to be an effective method for understanding integrated pest management strategies and solutions