Mitigating Impact of Devils Lake Flooding on the Sheyenne River Sulfate Concentration

Devils Lake is a terminal lake located in northeast North Dakota. Because of its glacial origin and accumulated salts from evaporation, the lake has a high concentration of sulfate compared to the surrounding water bodies. From 1993 to 2011, Devils Lake water levels rose by ~10 m, which flooded surrounding communities and increased the chance of an overspill to the Sheyenne River. To control the flooding, the State of North Dakota constructed two outlets to pump the lake water to the river. However, the pumped water has raised concerns about of water quality degradation and potential flooding risk of the Sheyenne River. To investigate these perceived impacts, a Soil and Water Assessment Tool (SWAT) model was developed for the Sheyenne River and it was linked to a coupled SWAT and CE‐QUAL‐W2 model that was developed for Devils Lake in a previous study. While the current outlet schedule has attempted to maintain the total river discharge within the confines of a two‐year flood (36 m³/s), our simulation from 2012 to 2018 revealed that the diversion increased the Sheyenne River sulfate concentration from an average of 125 to >750 mg/L. Furthermore, a conceptual optimization model was developed with a goal of better preserving the water quality of the Sheyenne River while effectively mitigating the flooding of Devils Lake. The optimal solution provides a “win–win” outlet management that maintains the efficiency of the outlets while reducing the Sheyenne River sulfate concentration to ≤600 mg/L.     

Improving dialogue among researchers,local and indigenous peoples and decision-makers to address issues of climate change in the North

Ambio - The Circumpolar North has been changing rapidly within the last decades, and the socioeconomic systems of the Eurasian Arctic and Siberia in particular have displayed the most dramatic...     

Circumpolar status of Arctic ptarmigan: Population dynamics and trends

Rock ptarmigan (Lagopus muta) and willow ptarmigan (L. lagopus) are Arctic birds with a circumpolar distribution but there is limited knowledge about their status and trends across their circumpolar distribution. Here, we compiled information from 90 ptarmigan study sites from 7 Arctic countries, where almost half of the sites are still monitored. Rock ptarmigan showed an overall negative trend on Iceland and Greenland, while Svalbard and Newfoundland had positive trends, and no significant trends in Alaska. For willow ptarmigan, there was a negative trend in mid-Sweden and eastern Russia, while northern Fennoscandia, North America and Newfoundland had no significant trends. Both species displayed some periods with population cycles (short 3–6 years and long 9–12 years), but cyclicity changed through time for both species. We propose that simple, cost-efficient systematic surveys that capture the main feature of ptarmigan population dynamics can form the basis for citizen science efforts in order to fill knowledge gaps for the many regions that lack systematic ptarmigan monitoring programs.

     

Correction to: Keeping pace with forestry: Multi-scale conservation in a changing production forest matrix

Ambio - In the original published article, the sentence “Nevertheless, semi-natural forest remnants continue to be harvested and fragmented (Svensson et al. 2018; Jonsson et al. 2019), and...     

Growth of Dehalococcoides spp. and increased abundance of reductive dehalogenase genes in anaerobic PCB-contaminated sediment microcosms

Polychlorinated biphenyls (PCBs) contaminate 19% of US Superfund sites and represent a serious risk to human and environmental health. One promising strategy to remediate PCB-contaminated sediments utilizes organohalide-respiring bacteria (OHRB) that dechlorinate PCBs.

However, functional genes that act as biomarkers for PCB dechlorination processes (i.e., reductive dehalogenase genes) are poorly understood. Here, we developed anaerobic sediment microcosms that harbor an OHRB community dominated by the genus Dehalococcoides. During the 430-day microcosm incubation, Dehalococcoides 16S rRNA sequences increased two orders of magnitude to 10⁷ copies/g of sediment, and at the same time, PCB118 decreased by as much as 70%. In addition, the OHRB community dechlorinated a range of penta- and tetra-chlorinated PCB congeners including PCBs 66, 70?+?74?+?76, 95, 90?+?101, and PCB110 without exogenous electron donor. We quantified candidate reductive dehalogenase (RDase) genes over a 430-day incubation period and found rd14, a reductive dehalogenase that belongs to Dehalococcoides mccartyi strain CG5, was enriched to 10⁷ copies/g of sediment. At the same time, pcbA5 was enriched to only 10⁵ copies/g of sediment. A survey for additional RDase genes revealed sequences similar to strain CG5’s rd4 and rd8. In addition to demonstrating the PCB dechlorination potential of native microbial communities in contaminated freshwater sediments, our results suggest candidate functional genes with previously unexplored potential could serve as biomarkers of PCB dechlorination processes.

     

Influence of Chronic Man-made Pollution on Bromus inermis Genome Size

Russian Journal of Ecology - Technogenic pollution can accelerate microevolutionary processes in natural populations. We estimated the nuclear DNA content of 10 Bromus inermis Leyss. samples from...     

Fine-resolution mapping of wildfire fuel types for Canada: Fuzzy logic modeling for an Alberta pilot area

The Canadian Forest Fire Danger Rating System (CFFDRS) is used daily across Canada for evaluating forest fire danger. Fuel-type information is one of the inputs required by the models used in the CFFDRS. In this project, three fuel-type maps with a 25 m resolution were produced for a pilot study area located in Alberta using land cover only; land cover and biomass; and, land cover, biomass and leaf area index data derived from satellite imagery. The relationships between inputs and fuel types were determined mainly by the opinions of forest fire scientists and incorporated into a computer program using fuzzy set methodology. Not all the CFFDRS fuel types could be distinguished using these inputs; three of the coniferous types had to be grouped into one common fuel type. Overall accuracy was between 74 and 83% based on ground-truth comparisons. The most accurate map resulted from land cover and biomass data. Detailed accuracy assessment indicated that the overall accuracy increased up to 86% if ambiguous fuel type identification was considered. No combination of inputs was able to define a fuel type with absolute certainty, which is a reflection of differing expert opinions and the small number of inputs used to produce the maps.     

An Experimental Methodology for Monitoring Contaminant Transport Through Geotechnical Centrifuge Models

In this paper, an attempt has been made to highlight an experimental methodology for monitoring contaminant transport through locally available silty soil and commercially available clay in geotechnical centrifuge models, for different compaction states. Use of multiple depth sensors to determine depth distribution of sodium chloride in the soil column has been detailed. The obtained results have been compared with argentometric method. To validate the centrifuge modelling, modelling of models has been used. The test setup developed can simulate contaminant transport mechanisms through the soil mass, which is approximately 10 m deep, over a period of 600 days. R _e and P _e are found to be N times higher in the centrifuge models. These numbers are found to be several orders less than unity. This indicates that laminar flow prevails and the dominating Cl⁻ transport mechanism in centrifuge is diffusion. The study also highlights the fact that the geotechnical centrifuge modelling can be used as a viable alternative to field scale experimentation.     

Assessing Respiratory Morbidity Through Pollution Status and Meteorological Conditions for Delhi

The study focuses on assessing the status of respiratory morbidity in Delhi over a four years period from 2000–2003. An attempt was made to investigate the role of important pollutants (SO₂, NO₂, SPM and RSPM) and various meteorological factors (temperature minimum & maximum, relative humidity at 0830 and 1730 hrs. and wind speed) in being responsible for respiratory admissions on account of COPD, asthma and emphysema. The study showed that winter months had greater exposure risk as pollutants often get trapped in the lower layers of atmosphere resulting in high concentrations. Statistical analysis revealed that two pollutants have significant positive correlation with the number of COPD cases viz., SPM (r = 0.474; p < 0.01) and RSPM (r = 0.353; p < 0.05), while a meteorological factor temperature (minimum) has a significant negative correlation (r = −0.318; p < 0.05) with COPD. Stepwise multiple regression analysis was performed for COPD as dependent variable and R² value of 0.33 was obtained indicating that SPM and RH(1730) were able to explain 33 percent variability in COPD. The partial correlation of SPM and RH(1730) on COPD was higher than any other combination and therefore they can be regarded as important contributing variables on COPD.     

The Influence of Linear Elements on Plant Species Diversity of Mediterranean Rural Landscapes: Assessment of Different Indices and Statistical Approaches

This paper mainly aims to study the linear element influence on the estimation of vascular plant species diversity in five Mediterranean landscapes modeled as land cover patch mosaics. These landscapes have several core habitats and a different set of linear elements -habitat edges or ecotones, roads or railways, rivers, streams and hedgerows on farm land- whose plant composition were examined. Secondly, it aims to check plant diversity estimation in Mediterranean landscapes using parametric and non-parametric procedures, with two indices: Species richness and Shannon index.Land cover types and landscape linear elements were identified from aerial photographs. Their spatial information was processed using GIS techniques. Field plots were selected using a stratified sampling design according to relieve and tree density of each habitat type. A 50×20 m² multi-scale sampling plot was designed for the core habitats and across the main landscape linear elements. Richness and diversity of plant species were estimated by comparing the observed field data to ICE (Incidence-based Coverage Estimator) and ACE (Abundance-based Coverage Estimator) non-parametric estimators.The species density, percentage of unique species, and alpha diversity per plot were significantly higher (p < 0.05) in linear elements than in core habitats. ICE estimate of number of species was 32% higher than of ACE estimate, which did not differ significantly from the observed values. Accumulated species richness in core habitats together with linear elements, were significantly higher than those recorded only in the core habitats in all the landscapes. Conversely, Shannon diversity index did not show significant differences.