Holistic evaluation of management policies: What are the consequences of modified gear use on Georges Bank?

Georges Bank haddock is a recently recovered fish stock in the New England groundfish fishery. Due to federal constraints under the Magnuson-Steven Act, however, this stock cannot be optimally exploited due to the bycatch of other critical species in the New England groundfishery such as cod and yellowtail flounder which are overfished. The Ruhle trawl and Separator trawl are examples of recent advances in gear technology that have been shown to significantly increase haddock to bycatch ratios. This study models the groundfish fishery through a mixed stock yield model which incorporates technological interactions. We also develop a socio-economic model that quantifies the amount of employment and producer surplus associated with three trawl types. Our results explore policy situations regarding the use of the new trawls. By bridging the biological and socio-economic models, we are able to view the fishery as a system that more accurately represents stakeholder views. Our model shows that each trawl, when used exclusively, produces different optimum strategies and therefore an optimum management strategy would most likely include a combination of trawl types. Our results also support the logic of using modified trawls for haddock fishing trips in which bycatch is strictly regulated as the Ruhle trawl is able to maintain 80% of catches caught by a conventional trawl while reducing bycatch up to over 60%. This paper is a first step towards an aid for policy makers to examine fishery gear trade-offs and the resulting biological and socio-economic consequences of different management actions within the constraints of the Magnuson-Stevens Act

Implementation of California COVIDNet - a multi-sector collaboration for statewide SARS-CoV-2 genomic surveillance.

INTRODUCTION: The SARS-CoV-2 pandemic represented a formidable scientific and technological challenge to public health due to its rapid spread and evolution. To meet these challenges and to characterize the virus over time, the State of California established the California SARS-CoV-2 Whole Genome Sequencing (WGS) Initiative, or California COVIDNet. This initiative constituted an unprecedented multi-sector collaborative effort to achieve large-scale genomic surveillance of SARS-CoV-2 across California to monitor the spread of variants within the state, to detect new and emerging variants, and to characterize outbreaks in congregate, workplace, and other settings. METHODS: California COVIDNet consists of 50 laboratory partners that include public health laboratories, private clinical diagnostic laboratories, and academic sequencing facilities as well as expert advisors, scientists, consultants, and contractors. Data management, sample sourcing and processing, and computational infrastructure were major challenges that had to be resolved in the midst of the pandemic chaos in order to conduct SARS-CoV-2 genomic surveillance. Data management, storage, and analytics needs were addressed with both conventional database applications and newer cloud-based data solutions, which also fulfilled computational requirements. RESULTS: Representative and randomly selected samples were sourced from state-sponsored community testing sites. Since March of 2021, California COVIDNet partners have contributed more than 450,000 SARS-CoV-2 genomes sequenced from remnant samples from both molecular and antigen tests. Combined with genomes from CDC-contracted WGS labs, there are currently nearly 800,000 genomes from all 61 local health jurisdictions (LHJs) in California in the COVIDNet sequence database. More than 5% of all reported positive tests in the state have been sequenced, with similar rates of sequencing across 5 major geographic regions in the state. DISCUSSION: Implementation of California COVIDNet revealed challenges and limitations in the public health system. These were overcome by engaging in novel partnerships that established a successful genomic surveillance program which provided valuable data to inform the COVID-19 public health response in California. Significantly, California COVIDNet has provided a foundational data framework and computational infrastructure needed to respond to future public health crises

A carbon/oxygen-dominated atmosphere days after explosion for the "super-Chandrasekhar" type Ia SN 2020esm

Seeing pristine material from the donor star in a type Ia supernova (SN Ia) explosion can reveal the nature of the binary system. In this paper, we present photometric and spectroscopic observations of SN 2020esm, one of the best-studied SNe of the class of "super-Chandrasekhar" SNe Ia (SC SNe Ia), with data obtained 12 to +360 days relative to peak brightness, obtained from a variety of ground- and space-based telescopes. Initially misclassified as a type II supernova, SN 2020esm peaked at M-B = -19.9 mag, declined slowly (Delta m(15)(B) = 0.92 mag), and had particularly blue UV and optical colors at early times. Photometrically and spectroscopically, SN 2020esm evolved similarly to other SC SNe Ia, showing the usual low ejecta velocities, weak intermediate-mass elements, and the enhanced fading at late times, but its early spectra are unique. Our first few spectra (corresponding to a phase of greater than or similar to 10 days before peak) reveal a nearly pure carbon/oxygen atmosphere during the first days after explosion. This composition can only be produced by pristine material, relatively unaffected by nuclear burning. The lack of H and He may further indicate that SN 2020esm is the outcome of the merger of two carbon/oxygen white dwarfs. Modeling its bolometric light curve, we find an Ni-56 mass of 1.23(-0.14)(+0.14) M-circle dot and an ejecta mass of 1.75(-0.20)(+0.32)M(circle dot), in excess of the Chandrasekhar mass. Finally, we discuss possible progenitor systems and explosion mechanisms of SN 2020esm and, in general, the SC SNe Ia class.</p