Hokkaido University

About: Hokkaido University is a education organization based out in Sapporo, Hokkaidô, Japan. It is known for research contribution in the topics: Catalysis & Population. The organization has 53925 authors who have published 115403 publications receiving 2651647 citations. The organization is also known as: Hokudai & Hokkaidō daigaku.

Environmental DNA metabarcoding reveals local fish communities in a species-rich coastal sea

Abstract: Environmental DNA (eDNA) metabarcoding has emerged as a potentially powerful tool to assess aquatic community structures. However, the method has hitherto lacked field tests that evaluate its effectiveness and practical properties as a biodiversity monitoring tool. Here, we evaluated the ability of eDNA metabarcoding to reveal fish community structures in species-rich coastal waters. High-performance fish-universal primers and systematic spatial water sampling at 47 stations covering ~11 km2 revealed the fish community structure at a species resolution. The eDNA metabarcoding based on a 6-h collection of water samples detected 128 fish species, of which 62.5% (40 species) were also observed by underwater visual censuses conducted over a 14-year period. This method also detected other local fishes (≥23 species) that were not observed by the visual censuses. These eDNA metabarcoding features will enhance marine ecosystem-related research, and the method will potentially become a standard tool for surveying fish communities.

Generalized ocean color inversion model for retrieving marine inherent optical properties

Abstract: Ocean color measured from satellites provides daily, global estimates of marine inherent optical properties (IOPs). Semi-analytical algorithms (SAAs) provide one mechanism for inverting the color of the water observed by the satellite into IOPs. While numerous SAAs exist, most are similarly constructed and few are appropriately parameterized for all water masses for all seasons. To initiate community-wide discussion of these limitations, NASA organized two workshops that deconstructed SAAs to identify similarities and uniqueness and to progress toward consensus on a unified SAA. This effort resulted in the development of the generalized IOP (GIOP) model software that allows for the construction of different SAAs at runtime by selection from an assortment of model parameterizations. As such, GIOP permits isolation and evaluation of specific modeling assumptions, construction of SAAs, development of regionally tuned SAAs, and execution of ensemble inversion modeling. Working groups associated with the workshops proposed a preliminary default configuration for GIOP (GIOP-DC), with alternative model parameterizations and features defined for subsequent evaluation. In this paper, we: (1) describe the theoretical basis of GIOP; (2) present GIOP-DC and verify its comparable performance to other popular SAAs using both in situ and synthetic data sets; and, (3) quantify the sensitivities of their output to their parameterization. We use the latter to develop a hierarchical sensitivity of SAAs to various model parameterizations, to identify components of SAAs that merit focus in future research, and to provide material for discussion on algorithm uncertainties and future emsemble applications.

Distal Pancreatectomy With En Bloc Celiac Axis Resection for Locally Advanced Pancreatic Body Cancer: Long-term Results

Abstract: Objective: To analyze the long-term results of distal pancreatectomy with en bloc celiac axis resection (DP-CAR), a newly designed extended surgical procedure for locally advanced cancer of the pancreatic body.