Abundance, Composition, and Sinking Rates of Fish Fecal Pellets in the Santa Barbara Channel

Rapidly sinking fecal pellets are an important component of the vertical flux of particulate organic matter (POM) from the surface to the ocean\u27s interior; however, few studies have examined the role fish play in this export. We determined abundance, size, prey composition, particulate organic carbon/nitrogen (POC/PON), and sinking rates of fecal pellets produced by a forage fish, likely the northern anchovy, in the Santa Barbara Channel. Pellet abundance ranged from 0.1-5.9 pellets m(-3). POC and PON contents averaged 21.7 mu g C pellet(-1) and 2.7 mu g N pellet(-1). The sinking rate averaged 787 m d(-1); thus pellets produced at the surface would reach the benthos (similar to 500 m) in m(-2) d(-1). This is equal to or exceeds previous measurements of sediment trap POM flux, and thus may transport significant amounts of repackaged surface material to depth

Toward a better understanding of fish‐based contribution to ocean carbon flux

Fishes are the dominant vertebrates in the ocean, yet we know little of their contribution to carbon export flux at regional to global scales. We synthesize the existing information on fish‐based carbon flux in coastal and pelagic waters, identify gaps and challenges in measuring this flux and approaches to address them, and recommend research priorities. Based on our synthesis of passive (fecal pellet sinking) and active (migratory) flux of fishes, we estimated that fishes contribute an average (± standard deviation) of about 16.1% (± 13%) to total carbon flux out of the euphotic zone. Using the mean value of model‐generated global carbon flux estimates, this equates to an annual flux of 1.5 ± 1.2 Pg C yr−1. High variability in estimations of the fish‐based contribution to total carbon flux among previous field studies and reported here highlight significant methodological variations and observational gaps in our present knowledge. Community‐adopted methodological standards, improved and more frequent measurements of biomass and passive and active fluxes of fishes, and stronger linkages between observations and models will decrease uncertainty, increase our confidence in the estimation of fish‐based carbon flux, and enable identification of controlling factors to account for spatial and temporal variability. Better constraints on this key component of the biological pump will provide a baseline for understanding how ongoing climate change and harvest will affect the role fishes play in carbon flux

Winter and spring controls on the summer food web of the coastal West Antarctic Peninsula

Understanding the mechanisms by which climate variability affects multiple trophic levels in food webs is essential for determining ecosystem responses to climate change. Here we use over two decades of data collected by the Palmer Long Term Ecological Research program (PAL-LTER) to determine how large-scale climate and local physical forcing affect phytoplankton, zooplankton and an apex predator along the West Antarctic Peninsula (WAP). We show that positive anomalies in chlorophyll-a (chl-a) at Palmer Station, occurring every 4-6 years, are constrained by physical processes in the preceding winter/spring and a negative phase of the Southern Annular Mode (SAM). Favorable conditions for phytoplankton included increased winter ice extent and duration, reduced spring/summer winds, and increased water column stability via enhanced salinity-driven density gradients. Years of positive chl-a anomalies are associated with the initiation of a robust krill cohort the following summer, which is evident in Adelie penguin diets, thus demonstrating tight trophic coupling. Projected climate change in this region may have a significant, negative impact on phytoplankton biomass, krill recruitment and upper trophic level predators in this coastal Antarctic ecosystem

Toward a better understanding of fish‐based contribution to ocean carbon flux

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Recommended Priorities for Research on Ecological Impacts of Ocean and Coastal Acidification in the U.S. Mid-Atlantic

The estuaries and continental shelf system of the United States Mid-Atlantic are subject to ocean acidification driven by atmospheric CO2, and coastal acidification caused by nearshore and land-sea interactions that include biological, chemical, and physical processes. These processes include freshwater and nutrient input from rivers and groundwater; tidally-driven outwelling of nutrients, inorganic carbon, alkalinity; high productivity and respiration; and hypoxia. Hence, these complex dynamic systems exhibit substantial daily, seasonal, and interannual variability that is not well captured by current acidification research on Mid-Atlantic organisms and ecosystems. We present recommendations for research priorities that target better understanding of the ecological impacts of acidification in the U. S. Mid-Atlantic region. Suggested priorities are: 1) Determining the impact of multiple stressors on our resource species as well as the magnitude of acidification; 2) Filling information gaps on major taxa and regionally important species in different life stages to improve understanding of their response to variable temporal scales and sources of acidification; 3) Improving experimental approaches to incorporate realistic environmental variability and gradients, include interactions with other environmental stressors, increase transferability to other systems or organisms, and evaluate community and ecosystem response; 4) Determining the capacity of important species to acclimate or adapt to changing ocean conditions; 5) Considering multi-disciplinary, ecosystem-level research that examines acidification impacts on biodiversity and biotic interactions; and 6) Connecting potential acidification-induced ecological impacts to ecosystem services and the economy. These recommendations, while developed for the Mid-Atlantic, can be applicable to other regions will help align research towards knowledge of potential larger-scale ecological and economic impacts

Antarctic ecosystems in transition – life between stresses and opportunities

Important findings from the second decade of the 21st century on the impact of environmental change on biological processes in the Antarctic were synthesised by 26 international experts. Ten key messages emerged that have stakeholder-relevance and/or a high impact for the scientific community. They address (i) altered biogeochemical cycles, (ii) ocean acidification, (iii) climate change hotspots, (iv) unexpected dynamism in seabed-dwelling populations, (v) spatial range shifts, (vi) adaptation and thermal resilience, (vii) sea ice related biological fluctuations, (viii) pollution, (ix) endangered terrestrial endemism and (x) the discovery of unknown habitats. Most Antarctic biotas are exposed to multiple stresses and considered vulnerable to environmental change due to narrow tolerance ranges, rapid change, projected circumpolar impacts, low potential for timely genetic adaptation, and migration barriers. Important ecosystem functions, such as primary production and energy transfer between trophic levels, have already changed, and biodiversity patterns have shifted. A confidence assessment of the degree of 'scientific understanding' revealed an intermediate level for most of the more detailed sub-messages, indicating that process-oriented research has been successful in the past decade. Additional efforts are necessary, however, to achieve the level of robustness in scientific knowledge that is required to inform protection measures of the unique Antarctic terrestrial and marine ecosystems, and their contributions to global biodiversity and ecosystem services

Transparency and Trust in Human-AI-Interaction: The Role of Model-Agnostic Explanations in Computer Vision-Based Decision Support

Computer Vision, and hence Artificial Intelligence-based extraction of information from images, has increasingly received attention over the last years, for instance in medical diagnostics. While the algorithms' complexity is a reason for their increased performance, it also leads to the "black box" problem, consequently decreasing trust towards AI. In this regard, "Explainable Artificial Intelligence" (XAI) allows to open that black box and to improve the degree of AI transparency. In this paper, we first discuss the theoretical impact of explainability on trust towards AI, followed by showcasing how the usage of XAI in a health-related setting can look like. More specifically, we show how XAI can be applied to understand why Computer Vision, based on deep learning, did or did not detect a disease (malaria) on image data (thin blood smear slide images). Furthermore, we investigate, how XAI can be used to compare the detection strategy of two different deep learning models often used for Computer Vision: Convolutional Neural Network and Multi-Layer Perceptron. Our empirical results show that i) the AI sometimes used questionable or irrelevant data features of an image to detect malaria (even if correctly predicted), and ii) that there may be significant discrepancies in how different deep learning models explain the same prediction. Our theoretical discussion highlights that XAI can support trust in Computer Vision systems, and AI systems in general, especially through an increased understandability and predictability

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

Canagliflozin and renal outcomes in type 2 diabetes and nephropathy

BACKGROUND Type 2 diabetes mellitus is the leading cause of kidney failure worldwide, but few effective long-term treatments are available. In cardiovascular trials of inhibitors of sodium–glucose cotransporter 2 (SGLT2), exploratory results have suggested that such drugs may improve renal outcomes in patients with type 2 diabetes. METHODS In this double-blind, randomized trial, we assigned patients with type 2 diabetes and albuminuric chronic kidney disease to receive canagliflozin, an oral SGLT2 inhibitor, at a dose of 100 mg daily or placebo. All the patients had an estimated glomerular filtration rate (GFR) of 30 to <90 ml per minute per 1.73 m2 of body-surface area and albuminuria (ratio of albumin [mg] to creatinine [g], >300 to 5000) and were treated with renin–angiotensin system blockade. The primary outcome was a composite of end-stage kidney disease (dialysis, transplantation, or a sustained estimated GFR of <15 ml per minute per 1.73 m2), a doubling of the serum creatinine level, or death from renal or cardiovascular causes. Prespecified secondary outcomes were tested hierarchically. RESULTS The trial was stopped early after a planned interim analysis on the recommendation of the data and safety monitoring committee. At that time, 4401 patients had undergone randomization, with a median follow-up of 2.62 years. The relative risk of the primary outcome was 30% lower in the canagliflozin group than in the placebo group, with event rates of 43.2 and 61.2 per 1000 patient-years, respectively (hazard ratio, 0.70; 95% confidence interval [CI], 0.59 to 0.82; P=0.00001). The relative risk of the renal-specific composite of end-stage kidney disease, a doubling of the creatinine level, or death from renal causes was lower by 34% (hazard ratio, 0.66; 95% CI, 0.53 to 0.81; P<0.001), and the relative risk of end-stage kidney disease was lower by 32% (hazard ratio, 0.68; 95% CI, 0.54 to 0.86; P=0.002). The canagliflozin group also had a lower risk of cardiovascular death, myocardial infarction, or stroke (hazard ratio, 0.80; 95% CI, 0.67 to 0.95; P=0.01) and hospitalization for heart failure (hazard ratio, 0.61; 95% CI, 0.47 to 0.80; P<0.001). There were no significant differences in rates of amputation or fracture. CONCLUSIONS In patients with type 2 diabetes and kidney disease, the risk of kidney failure and cardiovascular events was lower in the canagliflozin group than in the placebo group at a median follow-up of 2.62 years

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance.

Investment in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing in Africa over the past year has led to a major increase in the number of sequences that have been generated and used to track the pandemic on the continent, a number that now exceeds 100,000 genomes. Our results show an increase in the number of African countries that are able to sequence domestically and highlight that local sequencing enables faster turnaround times and more-regular routine surveillance. Despite limitations of low testing proportions, findings from this genomic surveillance study underscore the heterogeneous nature of the pandemic and illuminate the distinct dispersal dynamics of variants of concern-particularly Alpha, Beta, Delta, and Omicron-on the continent. Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve while the continent faces many emerging and reemerging infectious disease threats. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century