Seasonal changes in water quality and Sargassum biomass in southwest Australia

Sargassum C. Agardh is one of the most diverse genera of marine macro-algae and commonly inhabits shallow tropical and sub-tropical waters. This study aimed to investigate the effect of seasonality and the associated water quality changes on the distribution, canopy cover, mean thallus length and the biomass of Sargassum beds around Point Peron, Shoalwater Islands Marine Park, Southwest Australia. Samples of Sargassum and seawater were collected every three months from summer 2012 to summer 2014 from four different reef zones. A combination of in situ observations and WorldView-2 satellite remote-sensing images were used to map the spatial distribution of Sargassum beds and other associated benthic habitats. The results demonstrated a strong seasonal variation in the environmental parameters, canopy cover, mean thallus length, and biomass of Sargassum, which were significantly (P < 0.05) influenced by the nutrient concentration (PO43-, NO3-, NH4+) and rainfall. However, no variation in any studied parameter was observed among the four reef zones. The highest Sargassum biomass peaks occurred between late spring and early summer (from September to January). The results provide essential information to guide effective conservation and management, as well as sustainable utilisation of this coastal marine renewable resource

Adaptive carbon export response to warming in the Sargasso Sea

Ocean ecosystem models predict that warming and increased surface ocean stratification will trigger a series of ecosystem events, reducing the biological export of particulate carbon to the ocean interior. We present a nearly three-decade time series from the open ocean that documents a biological response to ocean warming and nutrient reductions wherein particulate carbon export is maintained, counter to expectations. Carbon export is maintained through a combination of phytoplankton community change to favor cyanobacteria with highcellular carbon-to-phosphorus ratios and enhanced shallow phosphorus recycling leading to increased nutrient use efficiency. These results suggest that surface ocean ecosystems may be more responsive and adapt more rapidly to changes in the hydrographic system than is currently envisioned in earth ecosystem models, with positive consequences for ocean carbon uptake

Heme metabolism genes Downregulated in COPD Cachexia.

IntroductionCachexia contributes to increased mortality and reduced quality of life in Chronic Obstructive Pulmonary Disease (COPD) and may be associated with underlying gene expression changes. Our goal was to identify differential gene expression signatures associated with COPD cachexia in current and former smokers.MethodsWe analyzed whole-blood gene expression data from participants with COPD in a discovery cohort (COPDGene, N = 400) and assessed replication (ECLIPSE, N = 114). To approximate the consensus definition using available criteria, cachexia was defined as weight-loss &gt; 5% in the past 12 months or low body mass index (BMI) (&lt; 20 kg/m2) and 1/3 criteria: decreased muscle strength (six-minute walk distance &lt; 350 m), anemia (hemoglobin &lt; 12 g/dl), and low fat-free mass index (FFMI) (&lt; 15 kg/m2 among women and &lt; 17 kg/m2 among men) in COPDGene. In ECLIPSE, cachexia was defined as weight-loss &gt; 5% in the past 12 months or low BMI and 3/5 criteria: decreased muscle strength, anorexia, abnormal biochemistry (anemia or high c-reactive protein (&gt; 5 mg/l)), fatigue, and low FFMI. Differential gene expression was assessed between cachectic and non-cachectic subjects, adjusting for age, sex, white blood cell counts, and technical covariates. Gene set enrichment analysis was performed using MSigDB.ResultsThe prevalence of COPD cachexia was 13.7% in COPDGene and 7.9% in ECLIPSE. Fourteen genes were differentially downregulated in cachectic versus non-cachectic COPD patients in COPDGene (FDR &lt; 0.05) and ECLIPSE (FDR &lt; 0.05).DiscussionSeveral replicated genes regulating heme metabolism were downregulated among participants with COPD cachexia. Impaired heme biosynthesis may contribute to cachexia development through free-iron buildup and oxidative tissue damage

Spring plankton dynamics in the Eastern Bering Sea, 1971-2050 : mechanisms of interannual variability diagnosed with a numerical model

A new planktonic ecosystem model was constructed for the Eastern Bering Sea based on observations from the 2007-2010 BEST/BSIERP (Bering Ecosystem Study/Bering Sea Integrated Ecosystem Research Program) field program. When run with forcing from a data-assimilative ice-ocean hindcast of 1971-2012, the model performs well against observations of spring bloom time evolution (phytoplankton and microzooplankton biomass, growth and grazing rates, and ratios among new, regenerated, and export production). On the southern middle shelf (57°N, station M2), the model replicates the generally inverse relationship between ice-retreat timing and spring bloom timing known from observations, and the simpler direct relationship between the two that has been observed on the northern middle shelf (62°N, station M8). The relationship between simulated mean primary production and mean temperature in spring (15 February to 15 July) is generally positive, although this was found to be an indirect relationship which does not continue to apply across a future projection of temperature and ice cover in the 2040s. At M2, the leading direct controls on total spring primary production are found to be advective and turbulent nutrient supply, suggesting that mesoscale, wind-driven processes - A dvective transport and storminess - may be crucial to long-term trends in spring primary production in the southeastern Bering Sea, with temperature and ice cover playing only indirect roles. Sensitivity experiments suggest that direct dependence of planktonic growth and metabolic rates on temperature is less significant overall than the other drivers correlated with temperature described above

An introduction and overview of the Bering Sea Project : volume IV

© The Author(s), 2016. This is the author's version of the work and is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Deep Sea Research Part II: Topical Studies in Oceanography 134 (2016): 3-12, doi:10.1016/j.dsr2.2016.09.002.The seasonal rhythm of sea-ice advance and retreat in the eastern Bering Sea (EBS) moves ice hundreds of kilometers across the broad continental shelf and exerts a powerful influence on the ecology of these waters. In winter, the combination of latitude, geology, winds, and ocean currents produces ice cover extending far into the southern Bering Sea. In the spring and summer, retreating ice, longer daylight hours, and nutrient-rich ocean water result in exceptionally high marine production, vital to both sea life and people. The intense burst of spring production, together with more episodic summer and early fall production, provides the energy that powers the complex food web and ultimately sustains nearly half of the US annual commercial fish landings, as well as providing food and cultural value to thousands of Bering Sea coastal and island residents.Finally, we acknowledge the National Science Foundation (NSF Award No. 1308087) and the North Pacific Research Board (NPRB) for author support during the concluding phase of the Bering Sea Project, and we thank many colleagues at NSF, NPRB, and NOAA for their management partnership and expertise. Funding for the Bering Sea Project was provided by NSF and NPRB, with in-­‐kind contribution from participants.2018-09-1

Body mass index change in gastrointestinal cancer and chronic obstructive pulmonary disease is associated with Dedicator of Cytokinesis 1

Background: There have been a number of candidate gene association studies of cancer cachexia-related traits, but no genome-wide association study (GWAS) has been published to date. Cachexia presents in patients with a number of complex traits, including both cancer and COPD. The objective of the current investigation was to search for a shared genetic aetiology for change in body mass index (ΔBMI) among cancer and COPD by using GWAS data in the Framingham Heart Study. Methods: A linear mixed effects model accounting for age, sex, and change in smoking status was used to calculate ΔBMI in participants over 40 years of age with three consecutive BMI time points (n = 4162). Four GWAS of ΔBMI using generalized estimating equations were performed among 1085 participants with a cancer diagnosis, 204 with gastrointestinal (GI) cancer, 112 with lung cancer, and 237 with COPD to test for association with 418 365 single-nucleotide polymorphisms (SNPs). Results: Two SNPs reached a level of genome-wide significance (P < 5 × 10−8) with ΔBMI: (i) rs41526344 within the CNTN4 gene, among COPD cases (β = 0.13, P = 4.3 × 10−8); and (ii) rs4751240 in the gene Dedicator of Cytokinesis 1 (DOCK1) among GI cancer cases (β = 0.10, P = 1.9 × 10−8). The DOCK1 SNP association replicated in the ΔBMI GWAS among COPD cases (βmeta-analyis = 0.10, Pmeta-analyis = 9.3 × 10−10). The DOCK1 gene codes for the dedicator of cytokinesis 1 protein, which has a role in myoblast fusion. Conclusions: In sum, one statistically significant common variant in the DOCK1 gene was associated with ΔBMI in GI cancer and COPD cases providing support for at least partially shared aetiology of ΔBMI in complex diseases

Comprehensive ecosystem model-data synthesis using multiple data sets at two temperate forest free-air CO2 enrichment experiments: Model performance at ambient CO2 concentration

Free-air CO2 enrichment (FACE) experiments provide a remarkable wealth of data which can be used to evaluate and improve terrestrial ecosystem models (TEMs). In the FACE model-data synthesis project, 11 TEMs were applied to two decadelong FACE experiments in temperate forests of the southeastern U.S.—the evergreen Duke Forest and the deciduous Oak Ridge Forest. In this baseline paper, we demonstrate our approach to model-data synthesis by evaluating the models' ability to reproduce observed net primary productivity (NPP), transpiration, and leaf area index (LAI) in ambient CO2 treatments. Model outputs were compared against observations using a range of goodness-of-fit statistics. Many models simulated annual NPP and transpiration within observed uncertainty. We demonstrate, however, that high goodness-of-fit values do not necessarily indicate a successful model, because simulation accuracy may be achieved through compensating biases in component variables. For example, transpiration accuracy was sometimes achieved with compensating biases in leaf area index and transpiration per unit leaf area. Our approach to model-data synthesis therefore goes beyond goodness-of-fit to investigate the success of alternative representations of component processes. Here we demonstrate this approach by comparing competing model hypotheses determining peak LAI. Of three alternative hypotheses—(1) optimization to maximize carbon export, (2) increasing specific leaf area with canopy depth, and (3) the pipe model—the pipe model produced peak LAI closest to the observations. This example illustrates how data sets from intensive field experiments such as FACE can be used to reduce model uncertainty despite compensating biases by evaluating individual model assumptions