Prioritization Of Sites Research Articles

Flood risk assessment in South Asia to prioritize flood index insurance applications in Bihar, India

Floods cause catastrophic destruction to life and livelihood in South Asia than any other parts of the world. This research assessed long term (2001 to 2015) flood risk at South Asia level using eight-day Moderate Resolution Imaging Spectroradiometer data and subsequently expanded this methodology to identify potential zones for piloting flood index insurance scheme in Bihar, India. Bihar was further assessed for sub-regional segmentation of its 37 districts into four flood risk zones based on k-means clustering and Getis-Ord Gi* analysis of multi-modal dataset consisting of demographics, meteorological, agricultural, flood characteristics and economic loss from floods. Satellite based risk assessment identified parts of Indus basin in Pakistan, Ganges basin in North India and majority of Bangladesh as flood hotspots. Site prioritization for flood index insurance in Bihar identified Madhubani, Darbhanga, Muzaffarpur and Sitamarhi districts as very high flood risk districts by both methods signifying large impact of any potential interventions implemented in these districts.

National Gas Hydrate Program expedition 02: Identification of gas hydrate prospects in the Krishna-Godavari Basin, offshore India

After completing the first expedition of India's National Gas Hydrate Program (NGHP-01) in 2006, it was concluded that for the next expedition (National Gas Hydrate Program 02; NGHP-02), a new drill site review effort should focus on identifying potential deep-water offshore gas hydrate accumulations in sand dominated depositional environments. Therefore, geological and geophysical data analysis and 3D seismic data interpretation along with associated seismic modeling were carried out in three areas of the Krishna-Godavari Basin: Areas B, C, and E. Conventional petroleum exploration approaches of seismic amplitude evaluation were adapted to prospect for potentially sand-rich depositional systems within the gas hydrate stability zone. Subsequently, these prospective areas were further assessed through the geological and geophysical evaluation of depositional setting, gas sources, and gas migration pathways. In Area B, prospecting focused on a large anticlinal structure with a prominent bottom-simulating reflector and several key horizons that indicated evidence for potential sand-hosted hydrate occurrences. In Area C, the prospects were distributed throughout various settings within a very large deep-water channel-levee-fan system with complex indications of potential gas hydrate occurrence in sand-prone seismic facies. In Area E, prospects were associated with high amplitude events within inferred channel-levee sequences. Based on the pre-expedition/onboard drill-site evaluation, the 22 most promising sites in the Krishna-Godavari Basin were identified and prioritized to investigate and delineate a total of 17 identified gas hydrate prospects. This paper describes the geo-scientific studies carried out prior to NGHP-02 for site identification, evaluation and prioritization. An important outcome of this study is the identification of two potentially producible gas hydrate systems inferred to host significant quantities of gas hydrate in stratigraphic-structural traps.

Evaluating a focal-species approach for tidal marsh bird conservation in the northeastern United States

ABSTRACT Insufficient time and funding remain obstacles to collecting data across broad spatial scales on the fine-scale distribution of multiple species, their life histories, and interactions with other species and the environment. This often necessitates the use of focal species to inform conservation and management decisions. We used the systematic conservation-planning software Marxan to assess quantitatively whether a focal species can aid in conservation and management of tidal marsh birds. Using a metric of relative cost in the region and current protected areas, we identified priority areas for conservation of 5 specialist taxa—Clapper Rail (Rallus crepitans), Eastern Willet (Tringa semipalmata semipalmata), Acadian Nelson's Sparrow (Ammospiza nelsoni subvirgatus), Saltmarsh Sparrow (A. caudacuta), and Seaside Sparrow (A. maritima)—that nest primarily in tidal marshes in the northeastern United States. We compared the spatial prioritization of sites and cost-effectiveness of alternative protectio...

Assessment and management of pesticide pollution at a river basin level part II: Optimization of pesticide monitoring networks on surface aquatic ecosystems by data analysis methods

The high cost of extensive pesticide monitoring studies, required for the protection of water resources, and the necessity of early identification of environmental threats, highlighted the need for prioritization of pesticides and sampling sites to be monitored. The aim of this study was to develop an optimum surface water monitoring network at a catchment scale including only the sites of a catchment vulnerable to pesticide pollution. The identification of sampling sites vulnerable to pesticide pollution (VPS) was based on the data of an intensive monitoring survey of 302 pesticides in 102 stationary sampling sites located on the surface water network of a river basin. In the proposed methodology the left-censored data of the analytical results derived from the above mentioned monitoring campaign were included in the statistical analyses by transforming all the raw data into categorical variables and arranging them in ordinal scales based on ecotoxicological thresholds derived from pesticide toxicity tests on aquatic non-target organisms. The categorized data were subjected to Categorical Principal Component Analysis with Optimal Scaling. For the identification of the VPS, the Squared Mahalanobis Distance criterion was applied on the extracted values (scores) of the significant principal components. With this methodology a 46% reduction in the number of the monitoring stations was achieved. This approach will be valuable in establishing more cost effective monitoring schemes in the future in other basins and in developing targeted measures to eliminate or limit the effect of critical pollution sources in surface aquatic systems. Moreover, by applying the proposed methodology, historical monitoring data can be used to initiate more efficient pesticide monitoring campaigns in the future.

Considerations for using turbidity as a surrogate for suspended sediment in small, ungaged streams: Time‐series selection, streamflow estimation, and regional transferability

AbstractSuspended sediment (SS) transport is an important and natural process in aquatic ecosystems. However, accelerated erosion due to anthropogenic land uses causes excessive sedimentation, which makes SS pollution one of the most prevalent stressors causing biological impairments of freshwater. Despite the ubiquitous nature of sedimentation and the ways in which it negatively impacts streams, inherent obstacles exist to effective measurement and characterization of fluvial SS loading. SS concentrations (SSCs) can vary widely during similar hydrologic conditions, making discharge an unreliable predictor variable. Alternatively, turbidity has been shown to be an effective surrogate for SSC, and methods using in situ optical turbidity sensors to indirectly measure SSCs have been developed. We present data and results from research using turbidity as a surrogate for SSC in five small, ungaged streams in the Chesapeake Bay watershed. Objectives of this study include presenting practical considerations and strategies for applying the turbidity–SSC surrogate method in small headwater streams. Empirical evidence is presented illustrating the potential correlation between land use and sediment loading. Additionally, accurate estimates of sediment loading require utilization of high frequency time‐series data and on‐site monitoring to capture timing and magnitude of streamflow, especially during intense, short‐duration runoff events. Similar turbidity–SSC relationships across watersheds suggest that regional regression curves could be established to allow more efficient and cost‐effective estimation of sediment loading. The broad application of this method would also benefit water resource management, by enabling prioritization of sites for stream restoration, standardizing techniques for monitoring stream recovery, or documenting impacts of discrete land‐use changes.

Functional rarity of coral reef fishes at the global scale: Hotspots and challenges for conservation

Characterizing functional diversity has become central in ecological research and for biodiversity assessment. Understanding the role of species with rare traits, i.e. functionally rare species, in community assembly, ecosystem dynamics and functioning has recently gained momentum. However, functional rarity is still ignored in conservation strategies.Here, we quantified global functional and evolutionary rarity for 2073 species of coral reef fishes and compared the rarity values to IUCN Red List status. Most species were functionally common but geographically rare. However, we found very weak correlation between functional rarity and evolutionary rarity. Functional rarity was highest for species classified as not evaluated or threatened by the IUCN Red List. The location of functional rarity hotspots (Tropical Eastern Pacific) did not match hotspots of species richness and evolutionary distinctiveness (Indo-Australian Archipelago), nor the currently protected areas. We argue that functional rarity should be acknowledged for both species and site prioritization in conservation strategies.

Estimating transient populations of unmarked individuals at a migratory stopover site using generalized N‐mixture models

Abstract Migration counts are popular indices used to monitor population trends over time. Advanced analytical methods for estimating abundance of unmarked, open populations now incorporate population growth models and simultaneously test for covariate effects on abundance and detection probability. However, estimating population abundance at a staging site is complicated by daily immigration and emigration of unmarked individuals. We applied a set of generalized N‐mixture models to simulated count data to test their applicability for transient populations. Using simulated datasets, parameters were unbiased when the apparent survival rate varied within a season or was mis‐specified in a model, but not when the immigration or detection probability was mis‐specified. With knowledge from the simulated data, we applied these models to daily counts of staging migratory shorebirds and estimated daily abundances accounting for variation in the detection and immigration rates. Daily counts of ruddy turnstones (Arenaria interpres) staging at Westhampton Island, New York, were collected during northward migration (1997–1999). We tested the effects of weather and tides on detection probability, and we modelled within‐season variation in immigration rates as a function of time. Covariates affecting the detection probability differed among years, but tide height consistently was correlated with detection probability. Accounting for detection and immigration rates, the predicted maximum single‐day populations of ruddy turnstones were 172%, 165% and 129% of the observed counts for each year. Synthesis and applications. Management and conservation plans for migratory species require abundance estimates that are near the true population size though they are difficult to obtain. Our study is the first empirical application of the generalized N‐mixture model that incorporates temporal trends in immigration and estimates daily abundance of a staging unmarked migratory population. Despite its inherent limitation, we suggest that the generalized N‐mixture model can estimate the abundance of transient populations with low individual heterogeneity when counts are intensively surveyed. Correct estimation of population sizes and the environmental factors affecting them can aid the conservation prioritization of species and staging sites. Moreover, the use of generalized N‐mixture models can improve our understanding of the environmental factors that shape migratory movements.

The Selection of Wind Power Project Location in the Southeastern Corridor of Pakistan: A Factor Analysis, AHP, and Fuzzy-TOPSIS Application

Pakistan has sufficient wind energy potential across various locations of the country. However, so far, wind energy development has not attained sufficient momentum matching its potential. Amongst various other challenges, the site selection for wind power development has always been a primary concern of the decision-makers. Principally, wind project site selection decisions are driven by various multifaceted criteria. As such, in this study, a robust research framework comprising of factor analysis (FA) of techno-economic and socio-political factors, and a hybrid analytical hierarchy process (AHP) and fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS) have been used for the prioritization of sites in the southeastern region of Pakistan. The results of this study reveal economic and land acquisition as the most significant criteria and sub-criteria, respectively. From the eight different sites considered, Jamshoro has been prioritized as the most suitable location for wind project development followed by Hyderabad, Nooriabad, Gharo, Keti Bandar, Shahbandar, Sajawal, and Talhar. This study provides a comprehensive decision support framework comprising of FA and a hybrid AHP and Fuzzy TOPSIS for the systematic analysis to prioritize suitable sites for the wind project development in Pakistan.

Pesticide monitoring and ecotoxicological risk assessment in surface water bodies and sediments of a tropical agro-ecosystem

A pesticide monitoring study including 80 and 60 active ingredients (in surface waters and sediments, respectively) was carried out in a river basin in Costa Rica during 2007–2012. A special emphasis was given on the exceptional ecological conditions of the tropical agro-ecosystem and the pesticide application strategies in order to establish a reliable monitoring network. A total of 135 water samples and 129 sediment samples were collected and analyzed. Long-term aquatic ecotoxicological risk assessment based on risk quotient in three trophic levels was conducted. Short-term risk assessment was used to calculate the toxic unit and prioritization of sampling sites was conducted by the sum of toxic units in both aquatic and sediment compartments. Dimethoate (61.2 μg/L), propanil (30.6 μg/L), diuron (22.8 μg/L) and terbutryn (4.8 μg/L) were detected at the highest concentrations in water samples. Carbendazim and endosulfan were the most frequently detected pesticides in water and sediment samples, respectively. Triazophos (491 μg/kg), cypermethrin (71.5 μg/kg), permethrin (47.8 μg/kg), terbutryn (38.7 μg/kg), chlorpyrifos (18.2 μg/kg) and diuron (11.75 μg/kg) were detected at the highest concentrations in sediment samples. The pesticides carbendazim, diuron, endosulfan, epoxyconazole, propanil, triazophos and terbutryn showed non-acceptable risk even when a conservative scenario was considered. Sum TUsite higher than 1 was found for one and two sampling sites in water and sediment compartments, respectively, suggesting high acute toxicity for the ecosystem. Main finding of the workExceptional ecological conditions of the tropical agro-ecosystem affect the fate of pesticides in water and sediment environment differently than the temperate one.

Assessing the Land and Vegetation Cover of Abandoned Fire Hazardous and Rewetted Peatlands: Comparing Different Multispectral Satellite Data

Since the 1990s, many peatlands that were drained for peat extraction and agriculture in Russia have been abandoned with high CO2 emissions and frequent fires, such as the enormous fires around Moscow in 2010. The fire hazard in these peatlands can be reduced through peatland rewetting and wetland restoration, so monitoring peatland status is essential. However, large expanses, poor accessibility, and fast plant succession pose as challenges for monitoring these areas without satellite images. In this study, a technique involving multispectral satellite data was used to identify six land cover classes that meet the requirements for peatland monitoring using the Meschera National Park as the testing area. This park is the largest area of once-exploited and now rewetted peatlands. However, data from one scanner are often insufficient to successfully implement this technique. In this study, we compared the land cover classifications obtained by using data from Spot-5, Spot-6, Landsat-7, Landsat-8, and Sentinel-2 satellites. The Spot-6 data were insufficient, despite having a higher spatial resolution, due to the lack of a shortwave infrared (SWIR) band. The high classification accuracy attained using data from other sensors enabled their combined use to provide an acceptable accuracy in the final product. The classification results were compared using minimum distance Erdas Imagine and the object-oriented ScanEx Image Processor, and the classification accuracy was similar between satellite images, which facilitates the transition from one method to another without quality loss. The proposed and tested approach can be used to analyze the status of abandoned and rewetted peatlands in other locations for the inventory and prioritization of sites for rewetting and restoration, monitoring status changes, and assessing restoration efficacy. The comparability of the data from different sensors allows for the combination of classified images and creates new possibilities for time series analysis.

A proposed decision support tool for prioritising conservation planning of Southeast Asian seagrass meadows: combined approaches based on ecosystem services and vulnerability analyses

AbstractSeagrass habitats provide a range of goods and benefits to coastal communities by supporting ecosystem functioning, food provisioning, and cultural values. However, they are at risk worldwide from anthropogenic activities, climate change impacts and limited resources, which hamper efforts to protect them. Effective conservation planning requires prioritisation of sites based on multiple factors, including their relative value and vulnerability (VU). The current study examines the efficacy of combining two well-established approaches – ecosystem service assessments and habitat VU analyses – to test a method for determining conservation priority for selected seagrass meadows in Southeast Asia. Seven seagrass meadows around Southeast Asia were selected and scored by the authors based on (1) the cumulative contribution of 12 ecosystem services (ES) and the condition of the meadows, (2) VU from 16 anthropogenic threats, which were each ranked against five factors (spatial scale, frequency, functional impact, resistance and recovery time) and (3) the combination of the two approaches to create a single numerical index. Prioritisation of sites differed when meadows were scored solely for the ES they provide, compared to how vulnerable they are to anthropogenic threats. The new combined analysis brought the two metrics together to give conservation priority to sites where management intervention will yield maximum conservation benefits from conservation effort, and resulted in the prioritisation of three sites: Barrang Lompo (Indonesia), Cape Bolinao (Philippines) and Beting Tanjung Kupang (Malaysia). This method is easy to use and does not require great technical expertise. It is also auditable, allowing for clear and transparent understanding of decision-making process.

GIS-based multi-criteria site selection for zebra mussel cultivation: Addressing end-of-pipe remediation of a eutrophic coastal lagoon ecosystem

Farming of shellfish and seaweeds is a tested tool for mitigating eutrophication consequences in coastal environments, however as many other marine economic activities it should be a subject of marine spatial planning for designating suitable sites. The present study proposes site selection framework for provisional zebra mussel farming in a eutrophic lagoon ecosystem, aimed primarily at remediation purposes. GIS-based multi-criteria approach was applied, combining data from empirical maps, numerical models and remote sensing to estimate suitability parameters. Site selection and prioritisation of suitable areas considered 15 environmental and socio-economic criteria, which contributed to 4 optimisation models (settlement, growth and survival of mussels, environmental and socio-economic) and 3 predefined scenarios representing provisional goals of mussel cultivation: spat production, biomass production and bioremediation. The relative importance of each criterion was assessed utilizing the Analytical Hierarchy Process. Site suitability index was calculated and the final result of the site selection analysis was summarized for 3 scenarios and overall suitability map. Four suitability classes (unsuitable, least, moderately and most suitable) were applied, and 3 most suitable zones for provisional zebra mussel cultivation with 12 candidate sites were selected accordingly. The integrated approach presented in this study can be adjusted for designating zebra mussel farming sites in other estuarine lagoon ecosystems, or cultivation of other mussel species for bioremediation purposes. The analytical framework and the workflow designed in this study are also adoptable for addressing other aquaculture-related spatial planning issues.

Sustainable Site Selection for Offshore Wind Farms in the South Aegean—Greece

The present research study develops and implements an integrated methodology for the evaluation and prioritization of appropriate sites for sustainable offshore wind-farm development at a regional level. The methodological framework includes the application of several siting criteria (technical, spatial, economic, social and environmental) proposed either by the national legislative framework (Specific Plan for Spatial Planning and Sustainable Development for Renewable Energy) or the international literature with the combined use of geographic information systems (GIS) and multi-criteria decision methods, namely the analytical hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS). The whole methodology provides a decision-making process for offshore wind-farm planning at regional level. The proposed methodology and the outputs of this work can be used to ensure the sustainable spatial development and policy of renewable energy resources.

Exposing ecological and economic costs of the research-implementation gap and compromises in decision making.

The frequently discussed gap between conservation science and practice is manifest in the gap between spatial conservation prioritization plans and their implementation. We analyzed the research-implementation gap of one zoning case by comparing results of a spatial prioritization analysis aimed at avoiding ecological impact of peat mining in a regional zoning process with the final zoning plan. We examined the relatively complex planning process to determine the gaps among research, zoning, and decision making. We quantified the ecological costs of the differing trade-offs between ecological and socioeconomic factors included in the different zoning suggestions by comparing the landscape-level loss of ecological features (species occurrences, habitat area, etc.) between the different solutions for spatial allocation of peat mining. We also discussed with the scientists and planners the reasons for differing zoning suggestions. The implemented plan differed from the scientists suggestion in that its focus was individual ecological features rather than all the ecological features for which there were data; planners and decision makers considered effects of peat mining on areas not included in the prioritization analysis; zoning was not truly seen as a resource-allocation process and not emphasized in general minimizing ecological losses while satisfying economic needs (peat-mining potential); and decision makers based their prioritization of sites on site-level information showing high ecological value and on single legislative factors instead of finding a cost-effective landscape-level solution. We believe that if the zoning and decision-making processes are very complex, then the usefulness of science-based prioritization tools is likely to be reduced. Nevertheless, we found that high-end tools were useful in clearly exposing trade-offs between conservation and resource utilization.

Using dimension reduction PCA to identify ecosystem service bundles

The concept of ecosystem services (ES) has facilitated the identification, mapping and communication about the many non-marketable benefits of green infrastructure. These benefits are important to consider during a spatial planning process. For spatial prioritisation of sites with a high societal importance, there is need to filter this information to insightful spatial indicators. The mapping of ES-hotspots and identification of ES-bundles have been put forward as promising methods for spatial prioritisation and the assessment of multifunctionality. While “hotspot mapping” and “ES-bundles” speak to the imagination of many, it is open to many different interpretations. In addition, there is a risk that the commonly applied hotspot mapping of single services and subsequent overlay analysis does not capture true hotspots of multifunctionality, where we expect multiple services to co-occur, but at lower intensities. Therefore, hotspot mapping should be applied on ES-bundles, rather than single ES. Yet, there are few methods to objectively identify and map such bundles of co-occurring services. In this research we propose dimension reduction principal component analysis (PCA), as a solution to identify and map bundles of ES. This technique is an established technique in remote sensing, where it is used to reduce unnecessary clutter in a data set. This research shows that if the methods for quantification and mapping of ES are sufficiently independent and biophysically sound, the PCA method can reveal multifunctionality between services and lead to (new) insights that can be used for better informed decisions on management and planning. The PCA graphs, ES-bundle maps and the integrated RGB-visualisation are objective and factual outputs of a statistical analysis that can be used for communication and discussion with stakeholders. It gives insight in co-occurrence of services and challenges to look for answers to why things are the way they are. Although scale effects did not play an important role in the results of this study, we advise to use this method on relatively small scales and repeat analysis rather than generalizing large scale results to the local scale or transfer findings between study sites as land-use patterns (and its interplay with abiotic conditions) are the result of many different socio-ecological developments throughout history, which can obviously differ from region to region.

A human fecal contamination score for ranking recreational sites using the HF183/BacR287 quantitative real-time PCR method

Human fecal pollution of recreational waters remains a public health concern worldwide. As a result, there is a growing interest in the application of human-associated fecal source identification quantitative real-time PCR (qPCR) technologies for water quality research and management. However, there are currently no standardized approaches for field implementation and interpretation of qPCR data. In this study, a standardized HF183/BacR287 qPCR method was combined with a water sampling strategy and a novel Bayesian weighted average approach to establish a human fecal contamination score (HFS) that can be used to prioritize sampling sites for remediation based on measured human waste levels. The HFS was then used to investigate 975 study design scenarios utilizing different combinations of sites with varying sampling intensities (daily to once per week) and number of qPCR replicates per sample (2–14 replicates). Findings demonstrate that site prioritization with HFS is feasible and that both sampling intensity and number of qPCR replicates influence reliability of HFS estimates. The novel data analysis strategy presented here provides a prescribed approach for the implementation and interpretation of human-associated HF183/BacR287 qPCR data with the goal of site prioritization based on human fecal pollution levels. In addition, information is provided for future users to customize study designs for optimal HFS performance.

Suitability of hazard rating systems for air contamination from municipal solid waste dumps and improvements to enhance performance

Close vicinity of uncontrolled municipal waste sites (or ‘waste dumps’) to well-populated communities makes the air contamination a prominent hazard from the waste dumps. The hazard rating systems, considered useful in prioritizing these sites for remediation, are investigated for their suitability to assess air contamination of municipal solid waste (MSW) dumps. Out of the eight systems employed in the study, six rating systems respond well to changes in site conditions when applied to hazardous waste sites. However for MSW sites, all eight rating systems give scores in a narrow range and do not perform well. One system is selected for improvement by modifying the indicators for waste quantity and rainfall and, introducing the indicators for waste composition and fresh waste quantity using expert judgment. The modified system performs well for MSW dumps, produces air contamination hazard ratings in a wider range, and responds to higher number of scenarios in sensitivity analysis, thus making it an appropriate tool for site prioritization for remediation.

An inventory of continental U.S. terrestrial candidate ecological restoration areas based on landscape context.

Landscape context is an important factor in restoration ecology, but the use of landscape context for site prioritization has not been as fully developed. We used morphological image processing to identify candidate ecological restoration areas based on their proximity to existing natural vegetation. We identified 1,102,720 candidate ecological restoration areas across the continental United States. Candidate ecological restoration areas were concentrated in the Great Plains and eastern United States. We populated the database of candidate ecological restoration areas with 17 attributes related to site content and context, including factors such as soil fertility and roads (site content), and number and area of potentially conjoined vegetated regions (site context) to facilitate its use for site prioritization. We demonstrate the utility of the database in the state of North Carolina, U.S.A. for a restoration objective related to restoration of water quality (mandated by the U.S. Clean Water Act), wetlands, and forest. The database will be made publicly available on the U.S. Environmental Protection Agency's EnviroAtlas website (http://enviroatlas.epa.gov) for stakeholders interested in ecological restoration.

Framework for strategic wind farm site prioritisation based on modelled wolf reproduction habitat in Croatia

In order to meet carbon reduction targets, many nations are greatly expanding their wind power capacity. However, wind farm infrastructure potentially harms wildlife, and we must therefore find ways to balance clean energy demands with the need to protect wildlife. Wide-ranging carnivores live at low density and are particularly susceptible to disturbance from infrastructure development, so are a particular concern in this respect. We focused on Croatia, which holds an important population of wolves and is currently planning to construct many new wind farms. Specifically, we sought to identify an optimal subset of planned wind farms that would meet energy targets while minimising potential impact on wolves. A suitability model for wolf breeding habitat was carried out using Maxent, based on six environmental variables and 31 reproduction site locations collected between 1997 and 2015. Wind farms were prioritised using Marxan to find the optimal trade-off between energy capacity and overlap with critical wolf reproduction habitat. The habitat suitability model predictions were consistent with the current knowledge: probability of wolf breeding site presence increased with distance to settlements, distance to farmland and distance to roads and decreased with distance to forest. Spatial optimisation showed that it would be possible to meet current energy targets with only 31% of currently proposed wind farms, selected in a way that reduces the potential ecological cost (overall predicted wolf breeding site presence within wind farm sites) by 91%. This is a highly efficient outcome, demonstrating the value of this approach for prioritising infrastructure development based on its potential impact on wide-ranging wildlife species.

Identification and prioritization of areas with high environmental risk in Mediterranean coastal areas: A flexible approach

Interdisciplinarity and transdisciplinarity are the cornerstone for the future management of coastal ecosystems with many vulnerability and hazard indexes developed for this purpose, especially in the engineering literature, but with limited studies that considered ecological implications within a risk assessment. Similarly, the concept of prioritization of sites has been widely examined in biodiversity conservation studies, but only recently as an instrument for territory management. Considering coastal plant diversity at the species and community levels, and their vulnerability to three main potential hazards threatening coastal areas (oil spills, Hazardous and Noxious Substances pollution, fragmentation of natural habitats), the objective of this paper is to define an easy-to-use approach to locate and prioritize the areas more susceptible to those stressors, in order to have a practical instrument for risk management in the ordinary and extra-ordinary management of the coastline. The procedure has been applied at pilot areas in four Mediterranean countries (Italy, France, Lebanon and Tunisia). This approach can provide policy planners, decision makers and local communities an easy-to-use instrument able to facilitate the implementation of the ICZM (Integrated Coastal Zone Management) process in their territory.