Null model analysis of species nestedness patterns

Nestedness is a common biogeographic pattern in which small communities form proper subsets of large communities. However, the detection of nestedness in binary presence-absence matrices will be affected by both the metric used to quantify nestedness and the reference null distribution. In this study, we assessed the statistical performance of eight nestedness metrics and six null model algorithms. The metrics and algorithms were tested against a benchmark set of 200 random matrices and 200 nested matrices that were created by passive sampling. Many algorithms that have been used in nestedness studies are vulnerable to type I errors (falsely rejecting a true null hypothesis). The best-performing algorithm maintains fixed row and fixed column totals, but it is conservative and may not always detect nestedness when it is present. Among the eight indices, the popular matrix temperature metric did not have good statistical properties. Instead, the Brualdi and Sanderson discrepancy index and Cutler's index of unexpected presences performed best. When used with the fixed-fixed algorithm, these indices provide a conservative test for nestedness. Although previous studies have revealed a high frequency of nestedness, a reanalysis of 288 empirical matrices suggests that the true frequency of nested matrices is between 10% and 40%.     

Using DNA barcoding to track seafood mislabeling in Los Angeles restaurants

Seafood mislabeling is common in both domestic and international markets. Studies on seafood fraud often report high rates of mislabeling (e.g., >70%), but these studies have been limited to a single sampling year, which means it is difficult to assess the impact of stricter governmental truth‐in‐labeling regulations. We used DNA barcoding to assess seafood labeling in 26 sushi restaurants in Los Angeles over 4 years. Seafood from 3 high‐end grocery stores were also sampled (n = 16) in 2014. We ordered 9 common sushi fish from menus, preserved tissue samples in 95% ethanol, extracted the genomic DNA, amplified and sequenced a portion of the mtDNA COI gene, and identified the resulting sequence to known fish sequences from the National Center for Biotechnology Information nucleotide database. We compared DNA results with the U.S. Food and Drug Administration (FDA) list of acceptable market names and retail names. We considered sushi‐sample labels that were inconsistent with FDA names mislabeled. Sushi restaurants had a consistently high percentage of mislabeling (47%; 151 of 323) from 2012 to 2015, yet mislabeling was not homogenous across species. Halibut, red snapper, yellowfin tuna, and yellowtail had consistently high (<77%) occurrences of mislabeling on menus, whereas mislabeling of salmon and mackerel were typically low (>15%). All sampled sushi restaurants had at least one case of mislabeling. Mislabeling of sushi‐grade fish from high‐end grocery stores was also identified in red snapper, yellowfin tuna, and yellowtail, but at a slightly lower frequency (42%) than sushi restaurants. Despite increased regulatory measures and media attention, we found seafood mislabeling continues to be prevalent.     

A meta-ethnography to synthesise household cultural research for climate change response

Cultural change is critical to climate change responses, but the in-depth qualitative research that investigates culture is necessarily conducted at scales difficult to integrate with policy. A focus of climate change mitigation and adaptation is affluent developed world households. Adapting methods used elsewhere in social science, we report and assess a meta-ethnography of household sustainability research, scaling up findings from 12 studies encompassing 276 Australian households. Seven themes are dominant: family concerns are central to household practice; adaptiveness is contingent but more pervasive than often assumed; households make sense of climate change not through abstract arguments, but through physical resources and materials; boundaries of the home space are dynamic and subjective; daily time is an important currency; paradoxes abound among everyday practice; and privacy and a sense of autonomy are prioritised. Insights from the method include new light on familiar themes when seen through an environmental lens, thickening and triangulation of existing research, and a stronger basis for international comparisons. Some findings have straightforward application to policy, others identify potential areas of risk and resistance, others still are more conceptual. We conclude the method has considerable potential and is worth developing further, providing a critical perspective is maintained.     

Attributing changes in land cover using independent disturbance datasets: a case study of the Yucatan Peninsula,Mexico

Detailed observations of natural and anthropogenic disturbance events that impact forest structure and the distribution of carbon are essential to estimate changes in terrestrial carbon pools and the associated emissions and removals of greenhouse gasses. Recent advances in remote sensing approaches have resulted in annual and decadal estimates of land-cover change derived from observations using broad-scale moderate resolution imaging spectroradiometer (MODIS) 250 m–1 km imagery. These land-use change estimates, however, are often not attributed directly to a cause or activity and are not well validated, especially in tropical areas. Knowledge of the type of disturbance that caused the observed land-cover changes is important, however, for the quantification of the associated impacts on ecosystem carbon stocks and fluxes. In this paper, we provide estimates of the amount of forest land-cover change in a Mexican forested region and propose an approach for attributing the cause of the observed changes to the underlying disturbance driver. To do so, we collate geospatial and remote sensing data from a variety of sources to summarize statistics about the major disturbances within the Yucatan Peninsula, an “early action” region for the reduction of emissions from deforestation and degradation, from 2005 to 2010. We combine the datasets to develop rules to estimate the likely disturbances that caused the observed land-cover changes based on their spatially explicit location. Finally, we compare our observed disturbance rates to those detected using classified land-cover data derived from MODIS.     

Does geopolitical risk escalate CO2 emissions? Evidence from the BRICS countries

Environmental Science and Pollution Research - High levels of CO2 emissions are extensively cited as one of the main global concerns nowadays. Therefore, researchers have been investigating the...     

Vertical response of microbial community and degrading genes to petroleum hydrocarbon contamination in saline alkaline soil

A column microcosm was conducted by amending crude oil into Dagang Oilfield soil to simulate the bioremediation process. The dynamic change of microbial communities and metabolic genes in vertical depth soil from 0 to 80 cm were characterized to evaluate the petroleum degradation potential of indigenous microorganism. The influence of environmental variables on the microbial responds to petroleum contamination were analyzed. Degradation extent of 42.45% of n-alkanes(C8–C40) and 34.61% of 16ΣPAH were reached after 22 weeks. Relative abundance of alkB, nah, and phe gene showed about 10-fold increment in different depth of soil layers. Result of HTS profiles demonstrated that Pseudomonas, Marinobacter and Lactococcus were the major petroleum-degrading bacteria in0–30 and 30–60 cm depth of soils. Fusarium and Aspergillus were the dominant oil-degrading fungi in the 0–60 cm depth of soils. In 60–80 cm deep soil, anaerobic bacteria such as Bacteroidetes, Lactococcus, and Alcanivorax played important roles in petroleum degradation.Redundancy analysis(RDA) and correlation analysis demonstrated that petroleum hydrocarbons(PHs) as well as soil salinity, clay content, and anaerobic conditions were the dominant effect factors on microbial community compositions in 0–30, 30–60, and 60–80 cm depth of soils, respectively.     

Preservation methods alter stable isotope values in gelatinous zooplankton: implications for interpreting trophic ecology

Jellyfish are increasingly topical within studies of marine food webs. Stable isotope analysis represents a valuable technique to unravel the complex trophic role of these long-overlooked species. In other taxa, sample preservation has been shown to alter the isotopic values of species under consideration, potentially leading to misinterpretation of trophic ecology. To identify potential preservation effects in jellyfish, we collected Aurelia aurita from Strangford Lough (54^o22′44.73″N, 5^o32′53.44″W) during May 2009 and processed them using three different methods prior to isotopic analysis (unpreserved, frozen and preserved in ethanol). A distinct preservation effect was found on δ¹⁵N values: furthermore, preservation also influenced the positive allometric relationship between individual size and δ¹⁵N values. Conversely, δ¹³C values remained consistent between the three preservation methods, conflicting with previous findings for other invertebrate, fish and mammalian species. These findings have implications for incorporation of jellyfish into marine food webs and remote sampling regimes where preservation of samples is unavoidable.