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.     

Evaluation and comparison of advanced oxidation processes for the degradation of 2,4-dichlorophenoxyacetic acid (2,4-D): a review

Environmental Science and Pollution Research - Organochlorine pesticides have generated public concern worldwide because of their toxicity to human health and the environment, even at low...     

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.     

Inflammatory effects of particulate matter air pollution

Environmental Science and Pollution Research - Air pollution is an important cause of non-communicable diseases globally with particulate matter (PM) as one of the main air pollutants. PM is...     

The risk of cross-border pollution and the influence of regional climate on the rainwater chemistry in the Southern Carpathians,Romania

Environmental Science and Pollution Research - The aim of this study is the assessment of rainwater composition, regarding the various sources of major ions and heavy metals, taking into account...     

From past to future: impact of climate change on range shifts and genetic diversity patterns of circumboreal plants

Climate change is projected to influence the genetic resources of plant species. Recent research has examined genetic diversity patterns under current climate conditions, with little attention to the future genetic consequences for species. In this study, we combined ecological niche modeling and population genetic approaches to project future changes in genetic diversity using plastid and nuclear DNA and reconstructed distribution patterns of three circumboreal plants (Chamaedaphne calyculata, Linnaea borealis ssp. borealis, and Pedicularis sceptrum-carolinum ssp. sceptrum-carolinum) in the last glacial maximum. We found that circumboreal plants could potentially lose their geographic ranges in the future (2070; 35–52% in RCP 4.5 (representative concentration pathways), 37–53% in RCP 6.0, and 56–69% in RCP 8.5), only slightly compensated by a predicted range gain of 18–33% (across the three RCPs). It is expected that future genetic diversity level could remain similar or lower than the present level. On the other hand, the homogeneity of the genetic background—a lack of admixture and domination of one gene pool in most populations of C. calyculata and L. borealis ssp. borealis—was predicted to become more pronounced in the future. Combining the paleoecological niche modeling and genetic data revealed, more precisely, the climate refugia for circumboreal plants in the Alps, central Asia, Beringia, and southern North America and the macrorefugia more restricted to the northern part of Eurasia and North America, reaching the arctic zone.