A Novel Formulation for Designing a Monitoring Strategy: Application to the Design of a River Quality Monitoring System

In this work, we propose a technique to automatically optimize the monitoring of any distributed indicator (concentration of a substance along a river, blood pressure of a patient over time, etc.) for which a reliable estimate is previously available. From a mathematical point of view, the problem is based on obtaining a reliable estimate of the chosen indicator (e.g., by numerical simulation), and then solving a multi-objective optimization problem (with mixed real and integer variables) whose solution must provide an efficient and satisfactory monitoring strategy. As an illustrative case, we show the steps to follow in order to implement that strategy when designing a system for monitoring water quality in a river. Finally, we present and analyze the results when applying the proposed technique to study a real case in the Neuse River (North Carolina, USA).     

Integrating intraseasonal grassland dynamics in cross-scale distribution modeling to support waterbird recovery plans

Despite much discussion about the utility of remote sensing for effective conservation, the inclusion of these technologies in species recovery plans remains largely anecdotal. We developed a modeling approach for the integration of local, spatially measured ecosystem functional dynamics into a species distribution modeling (SDM) framework in which other ecologically relevant factors are modeled separately at broad scales. To illustrate the approach, we incorporated intraseasonal water-vegetation dynamics into a cross-scale SDM for the Common Snipe (Gallinago gallinago), which is highly dependent on water and vegetation dynamics. The Common Snipe is an Iberian grassland waterbird characteristic of European agricultural meadows and a member of one of the most threatened bird guilds. The intraseasonal dynamics of water content of vegetation were measured using the standard deviation of the normalized difference water index time series computed from bimonthly images of the Sentinel-2 satellite. The recovery plan for the Common Snipe in Galicia (northwestern Iberian Peninsula) provided an opportunity to apply our modeling framework. Model accuracy in predicting the species’ distribution at a regional scale (resulting from integration of downscaled climate projections with regional habitat–topographic suitability models) was very high (area under the curve [AUC] of 0.981 and Boyce's index of 0.971). Local water-vegetation dynamic models, based exclusively on Sentinel-2 imagery, were good predictors (AUC of 0.849 and Boyce's index of 0.976). The predictive power improved (AUC of 0.92 and Boyce's index of 0.98) when local model predictions were restricted to areas identified by the continental and regional models as priorities for conservation. Our models also performed well (AUC of 0.90 and Boyce's index of 0.93) when projected to updated water-vegetation conditions. Our modeling framework enabled incorporation of key ecosystem processes closely related to water and carbon cycles while accounting for other factors ecologically relevant to endangered grassland waterbirds across different scales, allowed identification of priority areas for conservation, and provided an opportunity for cost-effective recovery planning by monitoring management effectiveness from space.     

2,4-dichlorophenoxyacetic acid (2,4-D) micropollutant herbicide removing from water using granular and powdered activated carbons: a comparison applied for water treatment and health safety

Abstract

Activated carbons are well-known porous materials as an effective adsorbent used for the removal of emerging contaminants, such as herbicides, which are increasingly present in water bodies. Most water treatment plants, specially in Brazil, are unable to completely remove such contaminants by the conventional process and advanced treatment using activated carbons is required. The aim of this paper was to verify the influence of the activated carbons granulometry and specific surface area on the 2,4-dichlorophenoxyacetic acid (2,4-D) herbicide removal efficiency using distilled-deionized water and filtered water collected from a conventional Water Treatment Plant. Commercial activated carbons samples used in this work were obtained from two different manufacturers. Activated carbons were analyzed by the specific surface area, pore size and volume distribution, nuclear magnetic resonance, infrared and x-ray spectroscopy, moisture, volatile matter and ash contents. Batch adsorption isotherms experiments were used and performed by Langmuir and Freundlich models. Granular and powdered activated carbons removed over 99% of 2,4-D in distilled water and near to 99% using filtered water. The activated carbons evaluated in this work presented high performance and played a key role in water treatment by removing 2,4-D herbicide, ensuring the protection of human health and the ecosystem.     

Addressing social attitudes toward lethal control of wildlife in national parks

The extraordinary population growth of certain ungulate species is increasingly a concern in agroforestry areas because overabundance may negatively affect natural environments and human livelihoods. However, society may have negative perceptions of killing wildlife to reduce their numbers and mitigate damage. We used an online survey that included a choice experiment to determine Spanish citizens’ (n = 190) preferences toward wildlife population control measures related to negative effects of ungulate overabundance (negative impacts on vegetation and other wildlife species and disease transmission to livestock) in 2 agroforestry national parks in Spain. We used latent-class and willingness-to-pay in space models to analyze survey results. Two percent of respondents thought a national park should have no human intervention even if lack of management may cause environmental degradation, whereas 95% of respondents favored efforts to reduce damage caused by overabundant ungulate species. We estimated human well-being losses of survey respondents when sustainable effects of deer overabundance on the environment became unsustainable effects and well-being gains when sustainable effects transitioned to no visible effects. We found that the type of wildlife-control program was a very relevant issue for the respondents; indirect control in which killing was avoided was the preferred action. Sixty-six percent of respondents agreed with the option of hunters paying for culling animals to reduce ungulate impacts rather than management cost coming out of taxes, whereas 19% of respondents were against this option and willing to pay for other solutions in national parks. Our results suggest that killing wildlife in national parks could be a socially acceptable tool to manage overabundance problems in certain contexts, but it could also generate social conflicts.     

Accounting for multiple testing in the analysis of spatio-temporal environmental data

The statistical analysis of environmental data from remote sensing and Earth system simulations often entails the analysis of gridded spatio-temporal data, with a hypothesis test being performed for each grid cell. When the whole image or a set of grid cells are analyzed for a global effect, the problem of multiple testing arises. When no global effect is present, we expect $$ \alpha $$% of all grid cells to be false positives, and spatially autocorrelated data can give rise to clustered spurious rejections that can be misleading in an analysis of spatial patterns. In this work, we review standard solutions for the multiple testing problem and apply them to spatio-temporal environmental data. These solutions are independent of the test statistic, and any test statistic can be used (e.g., tests for trends or change points in time series). Additionally, we introduce permutation methods and show that they have more statistical power. Real-world data are used to provide examples of the analysis, and the performance of each method is assessed in a simulation study. Unlike other simulation studies, our study compares the statistical power of the presented methods in a comprehensive simulation study. In conclusion, we present several statistically rigorous methods for analyzing spatio-temporal environmental data and controlling the false positives. These methods allow the use of any test statistic in a wide range of applications in environmental sciences and remote sensing.     

European Atlantic: the hottest oil spill hotspot worldwide

Oil spills caused by maritime transport of petroleum products are still an important source of ocean pollution, especially in main production areas and along major transport routes. We here provide a historical and geographic analysis of the major oil spills (>700 t) since 1960. Spills were recorded from several key marine ecosystems and marine biodiversity hotspots. The past four decades have been characterized by an overall decrease in the number of accidents and tonnes of oil spilled in the sea, but this trend was less distinct in the European Atlantic area. Recent black tides from the Erika and Prestige vessels provided new evidence for the high risk of accidents with serious ecological impact in this area, which according to our analysis is historically the most important oil spill hotspot worldwide. The English Channel and waters around Galicia in Spain were the areas with most accidents. Maritime transport in European Atlantic waters has been predicted to continue increasing. Together with our own results this suggests that, in addition to measures for increased traffic safety, deployment of emergency capacities in the spill hotspot areas may be crucial for a sustainable conservation of sea resources and ecosystems.Electronic Supplementary Material  Supplementary material is available for this article if you access the article at . A link in the frame on the left on that page takes you directly to the supplementary material.     

Influence of water hardening of the chorion on cadmium accumulation in medaka (Oryzias latipes) eggs

This report describes a study in which in vitro fertilization methods were used to expose medaka (Oryzias latipes) eggs to cadmium (Cd(2+)). This approach was applied to address the differential sensitivity and cumulative potential of Cd(2+) when exposure was initiated early (before fertilization and water hardening of the chorion) versus later during embryo development (i.e., well after the chorion has undergone water hardening). Following range finding exposures (2.5, 10, 20, 40 or 80 mg/l) under artificially controlled experimental procedures, results from hatching success and embryo malformations showed the earlier exposure interval more sensitive than the assay involving only the embryonated egg. Subsequent accumulation studies have shown that the exposure initiated before fertilization apparently led to more Cd(2+) deposition in the chorion compared to the exposure during embryonated stages of the eggs. Similarly, values for total Cd(2+) indicated higher concentrations in those eggs exposed prior to--and during--water hardening. Results suggest an alteration of the properties of the zona radiata in the early-stage eggs, making it more permeable to the potential exit or entrance of waterborne agents even after water hardening. Ongoing studies must now address the development of more realistic exposure conditions of the gametes by using incubation media with osmolarities similar to surface waters, and by shortening duration for gamete exposure. Also, sensitive methods to localize Cd(2+) and to delineate the transfer from the chorion to the embryo are needed.     

Simultaneous estimation of effective and apparent diffusion coefficients in compacted bentonite

Effective diffusion coefficients (D(e)) are usually measured by means of "through-diffusion" experiments in which steady state is reached, and the "time-lag" methods are used to estimate the apparent diffusion coefficient (D(a)). For sorbing radionuclides (as caesium), the time needed to reach steady-state conditions is very large, and the precision in D(a) determinations is not satisfactory. In this paper, a method that allows determining simultaneously effective and apparent diffusion coefficients in compacted bentonite without reaching steady-state conditions is described. Basically, this method consists of an "in-diffusion" experiment in which the concentration profile in the bentonite sample is used to estimate D(a), and the temporal evolution of the solute concentration in the reservoir is used to estimate D(e). This method has several advantages over the typical "through-diffusion" experiments, in particular: (a) experiment duration is significantly shorter, (b) D(a) values are measured with greater precision and (c) it is not necessary to maintain a constant solute concentration in the reservoir. This new method has been used to estimate the effective and apparent diffusion coefficients for caesium in FEBEX bentonite and in order to validate it, the results have been compared with results previously obtained with standard methods. Experimental results have been satisfactorily modelled using a simple model of diffusion in porewater and the measured value of D(e)(Cs) is very similar to D(e)(HTO) in the same bentonite. There is no evidence of "surface diffusion" in FEBEX bentonite for caesium.