A northwest North American training set: distribution of freshwater midges in relation to air temperature and lake depth

Freshwater midges, consisting of Chironomidae, Chaoboridae and Ceratopogonidae, were assessed as a biological proxy for palaeoclimate in eastern Beringia. The northwest North American training set consists of midge assemblages and data for 17 environmental variables collected from 145 lakes in Alaska, British Columbia, Yukon, Northwest Territories, and the Canadian Arctic Islands. Canonical correspondence analyses (CCA) revealed that mean July air temperature, lake depth, arctic tundra vegetation, alpine tundra vegetation, pH, dissolved organic carbon, lichen woodland vegetation and surface area contributed significantly to explaining midge distribution. Weighted averaging partial least squares (WA-PLS) was used to develop midge inference models for mean July air temperature (r _boot² = 0.818, RMSEP = 1.46°C), and transformed depth (ln (x+1); r _boot² = 0.38, and RMSEP = 0.58).     

The effects of seasonal variability and weather on microbial fecal pollution and enteric pathogens in a subtropical estuary

The Charlotte Harbor estuary in southwest Florida was sampled monthly for one year at twelve stations, in the lower reaches of the Myakka and Peace Rivers. The objectives of the study were to address the distribution and seasonal changes in microbial indicators and human pathogen levels in Charlotte Harbor shellfish and recreational waters, and to determine those factors that may be important in the transport and survival of pathogens. Monthly water samples and quarterly sediment samples were analyzed for fecal coliform bacteria, enterococci,Clostridium perfringens, and coliphage. Quarterly samples also were analyzed for the enteric human pathogens,Cryptosporidium spp.,Giardia spp., and enteroviruses. Fecal indicator organisms were generally concentrated in areas of low salinity and high densities of septic systems; however, pollution became widespread during wet weather in, the late fall and winter of 1997–1998, coincident with a strong El Nino event. Between, December 1997 and February 1998, enteroviruses were detected at 75% of the sampling stations; none were detected in other months. Enteric protozoa were detected infrequently and were not related to seasonal influences. Fecal indicators and enteroviruses were each significantly associated with rainfall, streamflow, and temperature. Regression models suggest that temperature and rainfall can predict the occurrence of enteroviruses in 93.7% of the cases. Based on findings in this watershed, factors such as variability in precipitation, streamflow, and temperature show promise in modeling and forecasting periods of poor coastal water quality.     

Variation in groundwater salinity in a tidal salt marsh basin,North Inlet Estuary,South Carolina

Groundwater flow of freshwater from upland forests into salt marshes is influenced by hydrologic forces that operate over a wide range of temporal scales, including storm events, tidal fluctuations, seasonal variations in rainfall and evapotranspiration (ET). Groundwater salinity can be a useful first order indicator of the balance between these flow processes. A dipole-dipole electrical resistivity survey was conducted approximately monthly during 2005 to measure groundwater salinity across a portion of Crabhaul Creek, a tidal salt marsh basin at the boundary of the upland forest and the North Inlet marsh in South Carolina. The monthly electrical resistivity surveys were designed to provide a detailed, spatially continuous measurement of subsurface conductivity to a depth of 4 m in order to further investigate the seasonal variation in groundwater salinity. Resistivity models were corroborated by simultaneous measurements of salinity in nearby piezometers. The freshwater-brackish water interface was clearly imaged by the resistivity. Movement of this interface occurs on a timescale of months rather than a regular seasonal variation. The average salinity in the marsh basin is highest in late Summer (July–August) when ET is highest, and lowest during the Winter (November–December). The position of the brackish-freshwater interface changes, but is not well correlated to local rainfall or tidal cycles except under specific circumstances. A steady-state hydrological model correctly predicts the average position of the freshwater-brackish interface and suggests a linear relationship between the height of the water table and the location of the interface. These results suggest a complex relationship between precipitation events and groundwater flow from the forest into the marsh.     

The levelized cost of carbon: a practical,if imperfect,method to compare CO2 abatement projects*

Calculating the cost effectiveness of projects and policies with respect to reducing carbon emissions provides a simple way for local government agencies to consider the climate impacts of their actions. Yet, defining a metric for cost-effectiveness in relation to climate change is not straightforward for several reasons. In this paper, we focus primarily on dynamics, reflecting the time value of money and how the benefits of reducing carbon emissions may change over time. We define a cost-effectiveness metric called Levelized Cost of Carbon (LCC) that carefully accounts for these dynamics. We also investigate the theoretical and practical implications and limitations of using a cost-effectiveness metric as an approach to rank projects. We apply our metric to a set of transportation projects to illustrate the insights that can be gained by such a process.

Key policy insights:

• Levelized Cost of Carbon (LCC) provides a simple way for local governments to consider climate change mitigation in decision making.

• LCC is a cost-effectiveness metric that carefully accounts for the time value of money and possible changes in the value of reducing emissions through time, thus helping local governments to make better decisions.

• LCC can be used to rank projects, with some caveats, even in the absence of a specific value for the benefits of reducing GHG emissions, thus providing flexibility in the face of uncertainty and political constraints.

     

Ten best practices to strengthen stewardship and sharing of water science data in Canada

Water science data are a valuable asset that both underpins the original research project and bolsters new research questions, particularly in view of the increasingly complex water issues facing Canada and the world. Whilst there is general support for making data more broadly accessible, and a number of water science journals and funding agencies have adopted policies that require researchers to share data in accordance with the findable, accessible, interoperable, reusable (FAIR) principles, there are still questions about effective management of data to protect their usefulness over time. Incorporating data management practices and standards at the outset of a water science research project will enable researchers to efficiently locate, analyse and use data throughout the project lifecycle, and will ensure the data maintain their value after the project has ended. Here, some common misconceptions about data management are highlighted, along with insights and practical advice to assist established and early career water science researchers as they integrate data management best practices and tools into their research. Freely available tools and training opportunities made available in Canada through Global Water Futures, The Gordon Foundation DataStream, the Digital Research Alliance of Canada Portage Network, Compute Canada, and university libraries, among others are compiled. These include webinars, training videos, and individual support for the water science community that together enable researchers to protect their data assets and meet the expectations of journals and funders. The perspectives shared here have been developed as part of the Global Water Futures programme's efforts to improve data management and promote the use of common data practices and standards in the context of water science in Canada. Ten best practices are proposed that may be broadly applicable to other disciplines in the natural sciences and can be adopted and adapted globally.     

Detection of slow-moving landslides through automated monitoring of surface deformation using Sentinel-2 satellite imagery

Landslides are one of the most damaging natural hazards and have killed tens of thousands of people around the world over the past decade. Slow-moving landslides, with surface velocities on the order of 10⁻²–10² m a⁻¹, can damage buildings and infrastructure and be precursors to catastrophic collapses. However, due to their slow rates of deformation and at times subtle geomorphic signatures, they are often overlooked in local and large-scale hazard inventories. Here, we present a remote-sensing workflow to automatically map slow-moving landslides using feature tracking of freely and globally available optical satellite imagery. We evaluate this proof-of-concept workflow through three case studies from different environments: the extensively instrumented Slumgullion landslide in the United States, an unstable lateral moraine in Chilean Patagonia and a high-relief landscape in central Nepal. This workflow is able to delineate known landslides and identify previously unknown areas of hillslope deformation, which we consider as candidate slow-moving landslides. Improved mapping of the spatial distribution, character and surface displacement rates of slow-moving landslides will improve our understanding of their role in the multi-hazard chain and their sensitivity to climatic changes and can direct future detailed localised investigations into their dynamics.     

Harmful algal blooms in the Chesapeake and Coastal Bays of Maryland, USA: Comparison of 1997, 1998, and 1999 events

Harmful algal blooms in the Chesapeake Bay and coastal bays of Maryland, USA, are not a new phenomenon, but may be increasing in frequency and diversity. Outbreaks ofPfiesteria piscicida (Dinophyceae) were observed during 1997 in several Chesapeake Bay tributaries, while in 1998,Pfiesteria-related events were not found but massive blooms ofProrocentrum minimum (Dinophyceae) occurred. In 1999,Aureococcus anophagefferens (Pelagophyceae) developed in the coastal bays in early summer in sufficient densities to cause a brown tide. In 1997, toxicPfiesteria was responsible for fish kills at relatively low cell densities. In 1998 and 1999, the blooms ofP. minimum andA. anophagefferens were not toxic, but reached sufficiently high densities to have ecological consequences. These years differed in the amount and timing of rainfall events and resulting nutrient loading from the largely agricultural watershed. Nutrient loading to the eastern tributaries of Chesapeake Bay has been increasing over the past decade. Much of this nutrient delivery is in organic form. The sites of thePfiesteria outbreaks ranked among those with the highest organic loading of all sites monitored bay-wide. The availability of dissolved organic carbon and phosphorus were also higher at sites experiencingA. anophagefferens blooms than at those without blooms. The ability to supplement photosynthesis with grazing or organic substrates and to use a diversity of organic nutrients may play a role in the development and maintenance of these species. ForP. minimum andA. anophagefferens, urea is used preferentially over nitrate.Pfiesteria is a grazer, but also has the ability to take up nutrients directly. The timing of nutrient delivery may also be of critical importance in determining the success of certain species.