Fate and transport of pathogens in lakes and reservoirs

Outbreaks of water-borne disease via public water supplies continue to be reported in developed countries even though there is increased awareness of, and treatment for, pathogen contamination. Pathogen episodes in lakes and reservoirs are often associated with rain events, and the riverine inflow is considered to be major source of pathogens. Consequently, the behaviour of these inflows is of particular importance in determining pathogen transport and distribution. Inflows are controlled by their density relative to that of the lake, such that warm inflows will flow over the surface of the lake as a buoyant surface flow and cold, dense inflows will sink beneath the lake water where they will flow along the bathymetry towards the deepest point. The fate of pathogens is determined by loss processes including settling and inactivation by temperature, UV and grazing. The general trend is for the insertion timescale to be shortest, followed by sedimentation losses and temperature inactivity. The fate of Cryptosporidium due to UV light inactivation can occur at opposite ends of the scale, depending on the location of the oocysts in the water column and the extinction coefficient for UV light. For this reason, the extinction coefficient for UV light appears to be a vitally important parameter for determining the risk of Cryptosporidium contamination. For risk assessment of pathogens in supply reservoirs, it is important to understand the role of hydrodynamics in determining the timescale of transport to the off-take relative to the timescale of inactivation. The characteristics of the riverine intrusion must also be considered when designing a sampling program for pathogens. A risk management framework is presented that accounts for pathogen fate and transport for reservoirs.     

Radiostrontium hot spot in the Russian Arctic: ground surface contamination by (90)Sr at the "Kraton-3" underground nuclear explosion site

Strontium-90 activity concentrations in surface soils and areal deposition densities have been studied at a site contaminated by an accidental release to atmosphere from the underground nuclear explosion "Kraton-3" conducted near the Polar Circle (65.9 degrees N, 112.3 degrees E) within the territory of the former USSR in 1978. In 2001-2002, the ground surface contamination at 14 plots studied ranged from 20 to 15 000 kBq m(-2), which significantly exceeds the value of 0.44 kBq m(-2) deduced for three background plots. The zone with substantial radiostrontium contamination extends, at least, 2.5 km in a north-easterly direction from the borehole. The average (137)Cs/(90)Sr ratio in the ground contamination originated from the "Kraton-3" fallout was estimated to be 0.55, which is significantly different from the ratio of 2.05 evaluated for background plots contaminated mostly from global fallout. Although vertical migration of (90)Sr in all undisturbed soil profiles studied is more rapid than that for (137)Cs, the depth of percolation of both radionuclides into the ground is mostly limited to the top 10-20 cm, which may be explained, primarily, by permafrost conditions. The horizontal migration rate of radiostrontium in the aqueous phase exceeds the radiocaesium migration rate by many times. This phenomenon seems to be a reason for the significant enrichment of the soil surface layers by radiostrontium at some sites, with variations occurring in accordance with small-scale irregularities of landscape.     

Surface ground contamination and soil vertical distribution of 137Cs around two underground nuclear explosion sites in the Asian Arctic, Russia

Vertical distributions of 137Cs have been determined in vegetation-soil cores obtained from 30 different locations around two underground nuclear explosion sites--"Crystal" (event year - 1974) and "Kraton-3" (event year - 1978) in the Republic of Sakha (Yakutia), Russia. In 2001-2002, background levels of 137Cs surface contamination densities on control forest plots varied from 0.73 to 0.97 kBq m(-2) with an average of 0.84+/-0.10 kBq m(-2) and a median of 0.82 kBq m(-2). 137Cs ground contamination densities at the "Crystal" site ranged from 1.3 to 64 kBq m(-2); the activity gradually decreased with distance from the borehole. For "Kraton-3", residual surface contamination density of radiocaesium varied drastically from 1.7 to 6900 kBq m(-2); maximal 137Cs depositions were found at a "decontaminated" plot. At all forest plots, radiocaesium activity decreased throughout the whole vertical soil profile. Vertical distributions of 137Cs in soil for the majority of the plots sampled (n=18) can be described using a simple exponential function. Despite the fact that more than 20 years have passed since the main fallout events, more than 80% of the total deposited activity was found in the first 5 cm of the vegetation-soil cores from most of the forested landscapes. The low annual temperatures, clay-rich soil type with neutral pH, and presence of thick lichen-moss carpet are the factors which may hinder 137Cs transport down the soil profile.     

Spatial attributes and reserve design models: A review

A variety of decision models have been formulated for the optimal selection of nature reserve sites to represent a diversity of species or other conservation features. Unfortunately, many of these models tend to select scattered sites and do not take into account important spatial attributes such as reserve shape and connectivity. These attributes are likely to affect not only the persistence of species but also the general ecological functioning of reserves and the ability to effectively manage them. In response, researchers have begun formulating reserve design models that improve spatial coherence by controlling spatial attributes. We review the spatial attributes that are thought to be important in reserve design and also review reserve design models that incorporate one or more of these attributes. Spatial modeling issues, computational issues, and the trade-offs among competing optimization objectives are discussed. Directions for future research are identified. Ultimately, an argument is made for the development of models that capture the dynamic interdependencies among sites and species populations and thus incorporate the reasons why spatial attributes are important.     

Optimisation of sampling for the temporal monitoring of technetium-99 in the Arctic marine environment

Monitoring of the marine environment for radioactivity, for both radiological protection and oceanographic purposes, remains an expensive and labour intensive activity due to the large sample volumes needed and the complex and lengthy analytical procedures required to measure low levels of contamination. Because of this, some consideration must be given to the design of sampling plans to ensure effective and efficient sampling that can be defended on the basis of scientific rationale. This article tests the hypothesis that geostatistical techniques may prove of use in the optimisation and design of sampling regimes for the monitoring of temporal fluctuations in the levels of technetium at a location in the Norwegian Arctic marine environment. The level of temporal correlation exhibited by two relevant time series was investigated and the information used to observe the effect of sampling frequency on the production of monthly estimates of activity of technetium in both seawater and seaweed. The results indicate that reduced sampling frequency allows production of estimates that acceptably replicate the actual data and that use of geostatistical procedures may offer advantages in the planning of monitoring systems for marine radioactivity. The use of an oceanographic model was also investigated as a means of assessing the temporal correlation prior to actual sampling, an approach that may offer significant advantages by reducing the need to have lengthy time series prior to designing sampling regimes.     

Effectiveness of a fixed-depth sensor deployed from a buoy to estimate water-column cyanobacterial biomass depends on wind speed

Water quality sondes have the advantage of containing multiple sensors, extended deployment times, high temporal resolution, and telecommunication with stakeholder accessible data portals. However, sondes that are part of buoy deployments often suffer from typically being fixed at one depth. Because water treatment plants are interested in water quality at a depth of the water intake and other stakeholders (ex. boaters and swimmers) are interested in the surface, we examined whether a fixed depth of approximately 1 m could cause over- or under-estimation of cyanobacterial biomass. We sampled the vertical distribution of cyanobacteria adjacent to a water quality sonde buoy in the western basin of Lake Erie during the summers of 2015–2017. A comparison of buoy cyanobacteria RFU (Relative Fluorescence Unit) at 1 m to cyanobacteria chlorophyll a (chla) measured throughout the water column showed occurrences when the buoy both under and overestimated the cyanobacteria chla at specific depths. Largest differences between buoy measurements and at-depth grab samples occurred during low wind speeds (< 4.5 m/sec) because low winds allowed cyanobacteria to accumulate at the surface above the buoy's sonde. Higher wind speeds (> 4.5 m/sec) resulted in better agreement between the buoy and at-depth measurements. Averaging wind speeds 12 hr before sample collection decreased the difference between the buoy and at-depth samples for high wind speeds but not low speeds. We suggest that sondes should be placed at a depth of interest for the appropriate stakeholder group or deploy sondes with the ability to sample at various depths.     

Prey risk allocation in a grazing ecosystem.

Understanding the behaviorally mediated indirect effects of predators in ecosystems requires knowledge of predator-prey behavioral interactions. In predator-ungulate-plant systems, empirical research quantifying how predators affect ungulate group sizes and distribution, in the context of other influential variables, is particularly needed. The risk allocation hypothesis proposes that prey behavioral responses to predation risk depend on background frequencies of exposure to risk, and it can be used to make predictions about predator-ungulate-plant interactions. We determined non-predation variables that affect elk (Cervus elaphus) group sizes and distribution on a winter range in the Greater Yellowstone Ecosystem (GYE) using logistic and log-linear regression on surveys of 513 1-km2 areas conducted over two years. Employing model selection techniques, we evaluated risk allocation and other a priori hypotheses of elk group size and distributional responses to wolf (Canis lupus) predation risk while accounting for influential non-wolf-predation variables. We found little evidence that wolves affect elk group sizes, which were strongly influenced by habitat type and hunting by humans. Following predictions from the risk allocation hypothesis, wolves likely created a more dynamic elk distribution in areas that they frequently hunted, as elk tended to move following wolf encounters in those areas. This response should dilute elk foraging pressure on plant communities in areas where they are frequently hunted by wolves. We predict that this should decrease the spatial heterogeneity of elk impacts on grasslands in areas that wolves frequently hunt. We also predict that this should decrease browsing pressure on heavily browsed woody plant stands in certain areas, which is supported by recent research in the GYE.     

Restoring habitat corridors in fragmented landscapes using optimization and percolation models

Landscape fragmentation and habitat loss are significant threats to the conservation of biological diversity. Creating and restoring corridors between isolated habitat patches can help mitigate or reverse the impacts of fragmentation. It is important that restoration and protection efforts be undertaken in the most efficient and effective way possible because conservation budgets are often severely limited. We address the question of where restoration should take place to efficiently reconnect habitat with a landscape-spanning corridor. Building upon findings in percolation theory, we develop a shortest-path optimization methodology for assessing the minimum amount of restoration needed to establish such corridors. This methodology is applied to large numbers of simulated fragmented landscapes to generate mean and variance statistics for the amount of restoration needed. The results provide new information about the expected level of resources needed to realize different corridor configurations under different degrees of fragmentation and different characterizations of habitat connectivity (“neighbor rules”). These results are expected to be of interest to conservation planners and managers in the allocation of conservation resources to restoration projects.