Prioritization of knowledge-needs to achieve best practices for bottom trawling in relation to seabed habitats

Management and technical approaches that achieve a sustainable level of fish production while at the same time minimizing or limiting the wider ecological effects caused through fishing gear contact with the seabed might be considered to be ‘best practice’. To identify future knowledge-needs that would help to support a transition towards the adoption of best practices for trawling, a prioritization exercise was undertaken with a group of 39 practitioners from the seafood industry and management, and 13 research scientists who have an active research interest in bottom-trawl and dredge fisheries. A list of 108 knowledge-needs related to trawl and dredge fisheries was developed in conjunction with an ‘expert task force’. The long list was further refined through a three stage process of voting and scoring, including discussions of each knowledge-need. The top 25 knowledge-needs are presented, as scored separately by practitioners and scientists. There was considerable consistency in the priorities identified by these two groups. The top priority knowledge-need to improve current understanding on the distribution and extent of different habitat types also reinforced the concomitant need for the provision and access to data on the spatial and temporal distribution of all forms of towed bottom-fishing activities. Many of the other top 25 knowledge-needs concerned the evaluation of different management approaches or implementation of different fishing practices, particularly those that explore trade-offs between effects of bottom trawling on biodiversity and ecosystem services and the benefits of fish production as food.Fil: Kaiser, Michel J.. Bangor University; Reino UnidoFil: Hilborn, Ray. University of Washington; Estados UnidosFil: Jennings, Simon. Fisheries and Aquaculture Science; Reino UnidoFil: Amaroso, Ricky. University of Washington; Estados UnidosFil: Andersen, Michael. Danish Fishermen; DinamarcaFil: Balliet, Kris. Sustainable Fisheries Partnership; Estados UnidosFil: Barratt, Eric. Sanford Limited; Nueva ZelandaFil: Bergstad, Odd A. Institute of Marine Research; NoruegaFil: Bishop, Stephen. Independent Fisheries Ltd; Nueva ZelandaFil: Bostrom, Jodi L. Marine Stewardship Council; Reino UnidoFil: Boyd, Catherine. Clearwater Seafoods; CanadáFil: Bruce, Eduardo A. Friosur S.A.; ChileFil: Burden, Merrick. Marine Conservation Alliance; Estados UnidosFil: Carey, Chris. Independent Fisheries Ltd.; Estados UnidosFil: Clermont, Jason. New England Aquarium; Estados UnidosFil: Collie, Jeremy S. University of Rhode Island,; Estados UnidosFil: Delahunty, Antony. National Federation of Fishermen; Reino UnidoFil: Dixon, Jacqui. Pacific Andes International Holdings Limited; ChinaFil: Eayrs, Steve. Gulf of Maine Research Institute; Estados UnidosFil: Edwards, Nigel. Seachill Ltd.; Reino UnidoFil: Fujita, Rod. Environmental Defense Fund; Reino UnidoFil: Gauvin, John. Alaska Seafood Cooperative; Estados UnidosFil: Gleason, Mary. The Nature Conservancy; Estados UnidosFil: Harris, Brad. Alaska Pacific University; Estados UnidosFil: He, Pingguo. University of Massachusetts Dartmouth; Estados UnidosFil: Hiddink, Jan G. Bangor University; Reino UnidoFil: Hughes, Kathryn M. Bangor University; Reino UnidoFil: Inostroza, Mario. EMDEPES; ChileFil: Kenny, Andrew. Fisheries and Aquaculture Science; Reino UnidoFil: Kritzer, Jake. Environmental Defense Fund; Estados UnidosFil: Kuntzsch, Volker. Sanford Limited; Estados UnidosFil: Lasta, Mario. Diag. Montegrande N° 7078. Mar del Plata; ArgentinaFil: Lopez, Ivan. Confederacion Española de Pesca; EspañaFil: Loveridge, Craig. South Pacific Regional Fisheries Management Organisation; Nueva ZelandaFil: Lynch, Don. Gorton; Estados UnidosFil: Masters, Jim. Marine Conservation Society; Reino UnidoFil: Mazor, Tessa. CSIRO Marine and Atmospheric Research; AustraliaFil: McConnaughey, Robert A. US National Marine Fisheries Service; Estados UnidosFil: Moenne, Marcel. Pacificblu; ChileFil: Francis. Marine Scotland Science; Reino UnidoFil: Nimick, Aileen M. Alaska Pacific University; Estados UnidosFil: Olsen, Alex. A. Espersen; DinamarcaFil: Parker, David. Young; Reino UnidoFil: Parma, Ana María. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Nacional Patagónico; ArgentinaFil: Penney, Christine. Clearwater Seafoods; CanadáFil: Pierce, David. Massachusetts Division of Marine Fisheries; Estados UnidosFil: Pitcher, Roland. CSIRO Marine and Atmospheric Research; AustraliaFil: Pol, Michael. Massachusetts Division of Marine Fisheries; Estados UnidosFil: Richardson, Ed. Pollock Conservation Cooperative; Estados UnidosFil: Rijnsdorp, Adriaan D. Wageningen IMARES; Países BajosFil: Rilatt, Simon. A. Espersen; DinamarcaFil: Rodmell, Dale P. National Federation of Fishermen's Organisations; Reino UnidoFil: Rose, Craig. FishNext Research; Estados UnidosFil: Sethi, Suresh A. Alaska Pacific University; Estados UnidosFil: Short, Katherine. F.L.O.W. Collaborative; Nueva ZelandaFil: Suuronen, Petri. Fisheries and Aquaculture Department; ItaliaFil: Taylor, Erin. New England Aquarium; Estados UnidosFil: Wallace, Scott. The David Suzuki Foundation; CanadáFil: Webb, Lisa. Gorton's Inc.; Estados UnidosFil: Wickham, Eric. Unit four –1957 McNicoll Avenue; CanadáFil: Wilding, Sam R. Monterey Bay Aquarium; Estados UnidosFil: Wilson, Ashley. Department for Environment; Reino UnidoFil: Winger, Paul. Memorial University Of Newfoundland; CanadáFil: Sutherland, William J. University of Cambridge; Reino Unid

Justify your alpha

Benjamin et al. proposed changing the conventional “statistical significance” threshold (i.e.,the alpha level) from p ≤ .05 to p ≤ .005 for all novel claims with relatively low prior odds. They provided two arguments for why lowering the significance threshold would “immediately improve the reproducibility of scientific research.” First, a p-value near .05provides weak evidence for the alternative hypothesis. Second, under certain assumptions, an alpha of .05 leads to high false positive report probabilities (FPRP2 ; the probability that a significant finding is a false positive

The James Webb Space Telescope Mission

Twenty-six years ago a small committee report, building on earlier studies, expounded a compelling and poetic vision for the future of astronomy, calling for an infrared-optimized space telescope with an aperture of at least $4m$. With the support of their governments in the US, Europe, and Canada, 20,000 people realized that vision as the $6.5m$ James Webb Space Telescope. A generation of astronomers will celebrate their accomplishments for the life of the mission, potentially as long as 20 years, and beyond. This report and the scientific discoveries that follow are extended thank-you notes to the 20,000 team members. The telescope is working perfectly, with much better image quality than expected. In this and accompanying papers, we give a brief history, describe the observatory, outline its objectives and current observing program, and discuss the inventions and people who made it possible. We cite detailed reports on the design and the measured performance on orbit.Comment: Accepted by PASP for the special issue on The James Webb Space Telescope Overview, 29 pages, 4 figure

The Science Performance of JWST as Characterized in Commissioning

This paper characterizes the actual science performance of the James Webb Space Telescope (JWST), as determined from the six month commissioning period. We summarize the performance of the spacecraft, telescope, science instruments, and ground system, with an emphasis on differences from pre-launch expectations. Commissioning has made clear that JWST is fully capable of achieving the discoveries for which it was built. Moreover, almost across the board, the science performance of JWST is better than expected; in most cases, JWST will go deeper faster than expected. The telescope and instrument suite have demonstrated the sensitivity, stability, image quality, and spectral range that are necessary to transform our understanding of the cosmos through observations spanning from near-earth asteroids to the most distant galaxies.Comment: 5th version as accepted to PASP; 31 pages, 18 figures; https://iopscience.iop.org/article/10.1088/1538-3873/acb29

A meta-analysis of genome-wide association studies identifies multiple longevity genes

Human longevity is heritable, but genome-wide association (GWA) studies have had limited success. Here, we perform two meta-analyses of GWA studies of a rigorous longevity phenotype definition including 11,262/3484 cases surviving at or beyond the age corresponding to the 90th/99th survival percentile, respectively, and 25,483 controls whose age at death or at last contact was at or below the age corresponding to the 60th survival percentile. Consistent with previous reports, rs429358 (apolipoprotein E (ApoE) ε4) is associated with lower odds of surviving to the 90th and 99th percentile age, while rs7412 (ApoE ε2) shows the opposite. Moreover, rs7676745, located near GPR78, associates with lower odds of surviving to the 90th percentile age. Gene-level association analysis reveals a role for tissue-specific expression of multiple genes in longevity. Finally, genetic correlation of the longevity GWA results with that of several disease-related phenotypes points to a shared genetic architecture between health and longevity

A meta-analysis of genome-wide association studies identifies multiple longevity genes

Publisher's version (útgefin grein).Human longevity is heritable, but genome-wide association (GWA) studies have had limited success. Here, we perform two meta-analyses of GWA studies of a rigorous longevity phenotype definition including 11,262/3484 cases surviving at or beyond the age corresponding to the 90th/99th survival percentile, respectively, and 25,483 controls whose age at death or at last contact was at or below the age corresponding to the 60th survival percentile. Consistent with previous reports, rs429358 (apolipoprotein E (ApoE) ε4) is associated with lower odds of surviving to the 90th and 99th percentile age, while rs7412 (ApoE ε2) shows the opposite. Moreover, rs7676745, located near GPR78, associates with lower odds of surviving to the 90th percentile age. Gene-level association analysis reveals a role for tissue-specific expression of multiple genes in longevity. Finally, genetic correlation of the longevity GWA results with that of several disease-related phenotypes points to a shared genetic architecture between health and longevity.Alexander von Humboldt-StiftungPeer Reviewe

Justify your alpha

In response to recommendations to redefine statistical significance to p ≤ .005, we propose that researchers should transparently report and justify all choices they make when designing a study, including the alpha level

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation