Community persistence in Broadstone Stream (U.K.) over three decades

1. Few detailed long-term data sets exist for fresh waters with which to examine large-scale temporal changes in community composition. Consequently, insight into community persistence has been restricted to a few, contingent case studies. We collated and analysed data for the aquatic macroinvertebrate community of Broadstone Stream in south-east England, spanning three decades. The pH of this naturally acid stream has risen progressively since the 1970s, and we sought to examine the potential effects of this environmental change upon the community.
2. Persistence within Broadstone was high when compared with other systems that have been analysed using similar methods. The stream was characterised by a `core' community of eight taxa that were always present, and contributed 75–97% of total invertebrate abundance, with a trailing limb of progressively rarer and more acid-sensitive taxa. There was little species turnover, although the time-series exceeded 20 generations for most species.
3. Despite this high persistence, a long-term response to rising pH was detected: species indicating profound acidity (identified a priori from independent studies) have declined since the 1970s, whereas indicators of moderate acidity increased. The structure of the community food web has also changed since the 1970s, with increased predator diversity and abundance, and a lengthening of food chains following the invasion of a new top predator.
4. These changes in the community appeared to be driven by an interaction between pH and climate. The unusually hot, dry summers characteristic of the 1990s may have raised pH during the more sensitive (i.e. early) stages of the life-cycle, and thus provided a window of opportunity for less acid-tolerant taxa to colonise and become established. Changes in pH appeared to set the boundaries of the available local species pool, within which biotic interactions ultimately shaped the community.     

What Do We Know About Metal Recycling Rates?

The recycling of metals is widely viewed as a fruitful sustainability strategy, but little information is available on the degree to which recycling is actually taking place. This article provides an overview on the current knowledge of recycling rates for 60 metals. We propose various recycling metrics, discuss relevant aspects of recycling processes, and present current estimates on global end‐of‐life recycling rates (EOL‐RR; i.e., the percentage of a metal in discards that is actually recycled), recycled content (RC), and old scrap ratios (OSRs; i.e., the share of old scrap in the total scrap flow). Because of increases in metal use over time and long metal in‐use lifetimes, many RC values are low and will remain so for the foreseeable future. Because of relatively low efficiencies in the collection and processing of most discarded products, inherent limitations in recycling processes, and the fact that primary material is often relatively abundant and low‐cost (which thereby keeps down the price of scrap), many EOL‐RRs are very low: Only for 18 metals (silver, aluminum, gold, cobalt, chromium, copper, iron, manganese, niobium, nickel, lead, palladium, platinum, rhenium, rhodium, tin, titanium, and zinc) is the EOL‐RR above 50% at present. Only for niobium, lead, and ruthenium is the RC above 50%, although 16 metals are in the 25% to 50% range. Thirteen metals have an OSR greater than 50%. These estimates may be used in considerations of whether recycling efficiencies can be improved; which metric could best encourage improved effectiveness in recycling; and an improved understanding of the dependence of recycling on economics, technology, and other factors.     

Multiomic Metabolic Enrichment Network Analysis Reveals Metabolite–Protein Physical Interaction Subnetworks Altered in Cancer

Metabolism is recognized as an important driver of cancer progression and other complex diseases, but global metabolite profiling remains a challenge. Protein expression profiling is often a poor proxy since existing pathway enrichment models provide an incomplete mapping between the proteome and metabolism. To overcome these gaps, we introduce multiomic metabolic enrichment network analysis (MOMENTA), an integrative multiomic data analysis framework for more accurately deducing metabolic pathway changes from proteomics data alone in a gene set analysis context by leveraging protein interaction networks to extend annotated metabolic models. We apply MOMENTA to proteomic data from diverse cancer cell lines and human tumors to demonstrate its utility at revealing variation in metabolic pathway activity across cancer types, which we verify using independent metabolomics measurements. The novel metabolic networks we uncover in breast cancer and other tumors are linked to clinical outcomes, underscoring the pathophysiological relevance of the findings.     

Structural Decomposition Analysis of Raw Material Consumption

The aim of this article is to quantify the drivers for the changes in raw material consumption (domestic material consumption expressed in the form of all materials extracted and used in the production phase) in terms of technology, which refers to the concept of sustainable production; the product structure of final demand, which refers to the concept of sustainable consumption; and the volume of final demand, which is related to economic growth. We also aim to determine to what extent the technological development and a shift in product structure of the final demand compensate for the growth in final consumption volume. Therefore, we apply structural decomposition analysis (SDA) to the change in raw material consumption (RMC) of the Czech Republic between 2000 and 2007. To present the study in a broader context, we also show other material flow indicators for the Czech Republic for 2000 and 2007. Our findings of SDA show that final demand structure has a very limited effect on the change in material flows. The rapid change in final demand volume was not compensated for crude oil, metal ores, construction materials, food crops, and timber. For the material category of non‐iron metal ores, even the change in technology contributes to an increase in material flows. The largest relative increases are reported for non‐iron metal ores (38%) and construction materials (30%). The main changes in material flows related to the Czech Republic are driven by exports and enabled by imports, the main source of these increased material flows. This emphasizes the increasing role of international trade.     

A predictive model for freshwater bioassessment (Mondego River,Portugal)

We sampled macroinvertebrates at 75 locations in the Mondego river catchment, Central Portugal, and developed a predictive model for water quality assessment of this basin, based on the Reference Condition Approach. Sampling was done from June to September 2001. Fifty-five sites were identified as “Reference sites” and 20 sites were used as “Test sites” to test the model. At each site we also measured 40 habitat variables to characterize water physics and chemistry, habitat type, land use, stream hydrology and geographic location. Macroinvertebrates were generally identified to species or genus level; a total of 207 taxa were found. By Unweighted Pair Group Method with Arithmetic mean (UPGMA) clustering and analysis of species contribution to similarities percentage (SIMPER), two groups of reference sites were established. Using Discriminant Analysis (stepwise forward), four variables correctly predicted 78% of the reference sites to the appropriate group: stream order, pool quality, substrate quality and current velocity. Test sites’ environmental quality was established from their relative distance to reference sites, in MDS ordination space, using a series of bands (BEAST methodology). The model performed well at upstream sites, but at downstream sites it was compromised by the lack of reference sites. As with the English RIVPACS predictive model, the Mondego model should be continually improved with the addition of new reference sites. The adaptation of the Mondego model methodology to the Water Framework Directive is possible and would consist mainly of the integration of the WFD typology and increasing the number of ellipses that define quality bands. Handling editor: K. Martens     

Effects of grazing intensity and grazing exclusion on litter decomposition in the temperate steppe of Nei Mongol,China

Aims Grazing intensity and grazing exclusion affect ecosystem carbon cycling by changing the plant community and soil micro-environment in grassland ecosystems. The aims of this study were: 1) to determine the effects of grazing intensity and grazing exclusion on litter decomposition in the temperate grasslands of Nei Mongol; 2) to compare the difference between above-ground and below-ground litter decomposition; 3) to identify the effects of precipitation on litter production and decomposition. Methods We measured litter production, quality, decomposition rates and soil nutrient contents during the growing season in 2011 and 2012 in four plots, i.e. light grazing, heavy grazing, light grazing exclusion and heavy grazing exclusion. Quadrate surveys and litter bags were used to measure litter production and decomposition rates. All data were analyzed with ANOVA and Pearson’s correlation procedures in SPSS. Important findings Litter production and decomposition rates differed greatly among four plots. During the two years of our study, above-ground litter production and decomposition in heavy-grazing plots were faster than those in light-grazing plots. In the dry year, below-ground litter production and decomposition in light-grazing plots were faster than those in heavy-grazing plots, which is opposite to the findings in the wet year. Short-term grazing exclusion could promote litter production, and the exclusion of light-grazing could increase litter decomposition and nutrient cycling. In contrast, heavy-grazing exclusion decreased litter decomposition. Thus, grazing exclusion is beneficial to the restoration of the light-grazing grasslands, and more human management measures are needed during the restoration of heavy-grazing grasslands. Precipitation increased litter production and decomposition, and below-ground litter was more vulnerable to the inter-annual change of precipitation than above-ground litter. Compared to the light-grazing grasslands, heavy-grazing grasslands had higher sensitivity to precipitation. The above-ground litter decomposition was strongly positively correlated with the litter N content (R² = 0.489, p < 0.01) and strongly negatively correlated with the soil total N content (R² = 0.450, p < 0.01), but it was not significantly correlated with C:N and lignin:N. Below-ground litter decomposition was negatively correlated with the litter C (R² = 0.263, p < 0.01), C:N (R² = 0.349, p < 0.01) and cellulose content (R² = 0.460, p < 0.01). Our results will provide a theoretical basis for ecosystem restoration and the research of carbon cycling.     

Review: Assessment of completeness of reporting in intervention studies using livestock: an example from pain mitigation interventions in neonatal piglets

Accurate and complete reporting of study methods, results and interpretation are essential components for any scientific process, allowing end-users to evaluate the internal and external validity of a study. When animals are used in research, excellence in reporting is expected as a matter of continued ethical acceptability of animal use in the sciences. Our primary objective was to assess completeness of reporting for a series of studies relevant to mitigation of pain in neonatal piglets undergoing routine management procedures. Our second objective was to illustrate how authors can report the items in the Reporting guidElines For randomized controLled trials for livEstoCk and food safety (REFLECT) statement using examples from the animal welfare science literature. A total of 52 studies from 40 articles were evaluated using a modified REFLECT statement. No single study reported all REFLECT checklist items. Seven studies reported specific objectives with testable hypotheses. Six studies identified primary or secondary outcomes. Randomization and blinding were considered to be partially reported in 21 and 18 studies, respectively. No studies reported the rationale for sample sizes. Several studies failed to report key design features such as units for measurement, means, standard deviations, standard errors for continuous outcomes or comparative characteristics for categorical outcomes expressed as either rates or proportions. In the discipline of animal welfare science, authors, reviewers and editors are encouraged to use available reporting guidelines to ensure that scientific methods and results are adequately described and free of misrepresentations and inaccuracies. Complete and accurate reporting increases the ability to apply the results of studies to the decision-making process and prevent wastage of financial and animal resources.     

Assessing water scarcity by simultaneously considering environmental flow requirements,water quantity,and water quality

Water scarcity is a widespread problem in many parts of the world. Most previous methods of water scarcity assessment only considered water quantity, and ignored water quality. In addition, the environmental flow requirement (EFR) was commonly not explicitly considered in the assessment. In this study, we developed an approach to assess water scarcity by considering both water quantity and quality, while at the same time explicitly considering EFR. We applied this quantity–quality-EFR (QQE) approach for the Huangqihai River Basin in Inner Mongolia, China. We found that to keep the river ecosystem health at a “good” level (i.e., suitable for swimming, fishing, and aquaculture), 26% of the total blue water resources should be allocated to meet the EFR. When such a “good” level is maintained, the quantity- and quality-based water scarcity indicators were 1.3 and 14.2, respectively; both were above the threshold of 1.0. The QQE water scarcity indicator thus can be expressed as 1.3(26%)|14.2, indicating that the basin was suffering from scarcity problems related to both water quantity and water quality for a given rate of EFR. The current water consumption has resulted in degradation of the basin's river ecosystems, and the EFR cannot be met in 3 months of a year. To reverse this situation, future policies should aim to reduce water use and pollution discharge, meet the EFR for maintaining healthy river ecosystems, and substantially improve pollution treatment.     

RNA‐seq analysis reveals new candidate genes for drip loss in a Pietrain × Duroc × Landrace × Yorkshire population

Drip loss, one of the most important meat quality traits, is characterized by low heritability. To date, the genetic factors affecting the drip loss trait have not been clearly elucidated. The objective of this study was to identify critical candidate genes affecting drip loss. First, we generated a Pietrain × Duroc × Landrace × Yorkshire commercial pig population and obtained phenotypic values for the drip loss trait. Furthermore, we constructed two RNA libraries from pooled samples of longissimus dorsi muscles with the highest (H group) and lowest (L group) drip loss and identified the differentially expressed genes (DEGs) between these extreme phenotypes using RNA‐seq technology. In total, 25 883 genes were detected in the H and L group libraries, and none was specifically expressed in only one library. Comparative analysis of gene expression levels found that 150 genes were differentially expressed, of which 127 were upregulated and 23 were downregulated in the H group relative to the L group. In addition, 68 drip loss quantitative trait loci (QTL) overlapping with 63 DEGs were identified, and these QTL were distributed mainly on chromosomes 1, 2, 5 and 6. Interestingly, the triadin (TRDN) gene, which is involved in muscle contraction and fat deposition, and the myostatin (MSTN) gene, which has a role in muscle growth, were localized to more than two drip loss QTL, suggesting that both are critical candidate genes responsible for drip loss.