Integrated biomarker response index as a useful tool for environmental assessment evaluated using transplanted mussels

Mytilus galloprovincialis mussels from a clean area were transplanted from 2003 to 2005 to several stations in the Bay of Cannes (North-Western Mediterranean Sea) including a site considered as reference, for 1 month at the end of spring (May). Several biomarkers (AChE, GST and CAT activities, TBARS and MT concentrations) were measured in the transplanted organisms. The concentrations of metals (Cd, Cu and Zn) were determined in the transplanted mussels, PAH and PCB analyses were performed in the mussels caged in 2004. The integrated biomarker response (IBR) was calculated; pollutant concentrations in mussels were displayed as star plots and compared to IBR star plots. Visualization was thus possible between sites for comparison with exposure conditions. Results demonstrated that the mussels from the Old harbour site (VP) are characterized by elevated copper and PCB concentrations, those from Canto harbour (PC) presented high PCB contents and those from the mouth of the Siagne River (ES) high PAH concentrations compared to the animals transplanted in the reference site (IL). In 2003, there was a visual correlation between the copper gradient measured in the transplanted mussels and the IBR variation. In 2004, the agreement between the copper gradient and the PCB gradient measured in the caged mussels and the IBR variation was good whereas the PAH gradient did not seem to contribute to the IBR demonstrating that the chosen biomarkers did not respond to PAHs. In 2005, IBR showed that other contaminants, not measured might be present in VP, PC and ES compared to the reference station (IL).     

Methods for integrated assessment

Integrated assessment is an approach that seeks to involve all disciplines in policy-relevant assessment. The process aims to encompass environmental science, technology and policy problems. The aim is to establish an overview of the environmental issue in question that attempts to avoid the mistakes of the past associated with narrow, one-sided or unidimensional approaches. A number of methods are available for such assessments. However, they are also subject to a number of limitations, difficulties and dilemmas. Integrated methods are inherently complicated and the tradition is that only experts are involved. New more inclusionary procedures have to be devised in order to involve all stakeholders. They have to be involved in the framing of the issue and in the value judgements associated with the approach. The dilemmas cannot be solved by integrated approaches, but they can be mitigated via proper identification, analysis and evaluation of the gains and losses involved. In structuring the analysis the existence of ignorance has to be accounted for and communicated to the managers and the political decision makers. The ignorance/uncertainty aspects can be partially accommodated for via an intensification of feasible monitoring and research so as to minimise the risks of unpleasant surprises. Electronic Publication     

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.     

A safety analysis of roundabouts and turbo roundabouts based on Petri nets

Objective: In this work, a roundabout and a turbo roundabout model are compared and previous modeling with continuous Petri nets and safety are analyzed through indicators of complexity. Petri nets are a graphic and mathematical representation that allow a faithful modeling of urban systems.

Method: The methodology has been designed for the transformation of a real system to small subgraphs that represent the maneuvers in roundabouts, approximated as roads and lanes of incorporation. Places within the roundabout have been located and defined as continuous places from their influence and visibility toward adjacent conditions. The transitions have been modeled by time and inhibitory arcs, which represent priorities and areas where drivers must pay attention. The created networks represent a faithful model of vehicle flow trajectories in the roundabouts.

Results: The methodology is applied to the same real road intersection. The case study is a recent transformation from roundabout to turbo roundabout. The roundabout network complexity is corroborated by a greater number of entries and exits that lead to each roundabout place (reflected in the maneuvers that can be performed) and a greater number of inhibiting arcs. In most of the turbo roundabout places, the driver’s only option is reduced to occupying next place. The possibility of choosing between several places supposes a greater trajectory intersection and an increased time for decision making. The only situation where the complexity is the same between both systems is when a vehicle accesses the inner lane of the roundabout from the left lane on a single-lane road. The main maneuvers causing accidents have been modeled and their solution in a turbo roundabout is presented.

Conclusions: The reduced complexity of the turbo roundabout is due to the strict limitations in lane changes, turning turbo roundabouts into a safer model: A lower number of possible movements that can be performed by drivers and a smaller number of trajectories with collision risk. Petri nets have proven to be perfectly applicable to the representation of traffic circular systems (such as roundabouts and turbo roundabouts) and to measure the complexity and security of the system.     

Numerical modelling of uncongested wood transport in the Rienz river

Environmental Fluid Mechanics - The Eulerian–Lagrangian model ORSA2D_WT is employed for the simulation of uncongested wood transport, with reference to a field experiment that studied the...     

Evaluation of copper-induced DNA damage in Vitis vinifera L. using Comet-FISH

The contamination of soils and water with copper (Cu) can compromise the crops production and quality. Fungicides containing Cu are widely and intensively used in viticulture contributing to environmental contamination and genotoxicity in Vitis vinifera L. Despite the difficulty in reproducing field conditions in the laboratory, hydroponic solutions enriched with Cu (1, 10, 25 and 50 μM) were used in forced V. vinifera cuttings to evaluate the DNA damage in leaves of four wine-producing varieties (‘Tinta Barroca’, ‘Tinto Cão’, ‘Malvasia Fina’ and ‘Viosinho’). Alkaline comet assay followed by fluorescence in situ hybridisation (Comet-FISH) was performed with the 45S ribosomal DNA (rDNA) and telomeric [(TTTAGGG)_n] sequences as probes. This study aimed to evaluate the tolerance of the four varieties to different concentrations of Cu and to determine which genomic regions were more prone to DNA damage. The comet assay revealed comets of categories 0 to 4 in all varieties. The DNA damage increased significantly (p < 0.001) with the Cu concentration. ‘Tinto Cão’ appeared to be the most sensitive variety because it had the highest DNA damage increase in 50 μM Cu relative to the control. Comet-FISH was only performed on slides of the control and 50 μM Cu treatments. Comets of all varieties treated with 50 μM Cu showed rDNA hybridisation on the head, ‘halo’ and tail (category III), and their frequency was significantly higher than that of control. The frequency of category III comets hybridised with the telomeric probe was only significantly different from the control in ‘Malvasia Fina’ and ‘Tinta Barroca’. Comet-FISH revealed partial damage on rDNA and telomeric DNA in response to Cu but also in control, confirming the high sensitivity of these genomic regions to DNA fragmentation.

     

A fuzzy logic expert system for evaluating policy progress towards sustainability goals

Evaluating progress towards environmental sustainability goals can be difficult due to a lack of measurable benchmarks and insufficient or uncertain data. Marine settings are particularly challenging, as stakeholders and objectives tend to be less well defined and ecosystem components have high natural variability and are difficult to observe directly. Fuzzy logic expert systems are useful analytical frameworks to evaluate such systems, and we develop such a model here to formally evaluate progress towards sustainability targets based on diverse sets of indicators. Evaluation criteria include recent (since policy enactment) and historical (from earliest known state) change, type of indicators (state, benefit, pressure, response), time span and spatial scope, and the suitability of an indicator in reflecting progress toward a specific objective. A key aspect of the framework is that all assumptions are transparent and modifiable to fit different social and ecological contexts. We test the method by evaluating progress towards four Aichi Biodiversity Targets in Canadian oceans, including quantitative progress scores, information gaps, and the sensitivity of results to model and data assumptions. For Canadian marine systems, national protection plans and biodiversity awareness show good progress, but species and ecosystem states overall do not show strong improvement. Well-defined goals are vital for successful policy implementation, as ambiguity allows for conflicting potential indicators, which in natural systems increases uncertainty in progress evaluations. Importantly, our framework can be easily adapted to assess progress towards policy goals with different themes, globally or in specific regions.     

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.