Medium Vulnerability Research Articles

Hydrological drought vulnerability assessment in Ethiopia using multi-criteria decision-making

ABSTRACT Drought significantly impacts the livelihoods of communities over extensive regions, with Ethiopia being particularly prone to frequent and persistent occurrences. Hydrological drought analysis necessitates spatially distributed data, a challenge faced in Ethiopian studies. We employed remote sensing and analytical hierarchy process (AHP) to assign weightage values to nine hydrological drought-influencing factors, namely land use and land cover, soil texture, population density, elevation, drainage density, aridity index, slope, rainfall departure, and water storage deficit index. Our results identify spatial diversity of hydrological drought vulnerability, with six categories of extreme and very high vulnerability areas covering over 22% of the country from January to June, primarily in the northeast and southeast lowlands. The majority of the country falls within high and medium vulnerability areas, emphasizing the prevalence of hydrological drought, particularly from June to October, while some southwest regions experience low vulnerability. Overall, a substantial portion of the country is susceptible to severe hydrological drought throughout most months.

Spatial-Based Flood Susceptibility Mapping Using Analytical Hierarchy Process Techniques (Case Study : Gresik Regency)

Abstract Over the past four years, Gresik Regency has frequently been hit by floods. In 2019, there were 17 occurrences, followed by 13 occurrences in 2020, 19 occurrences in 2021, and a rise to 33 occurrences in 2022. To support the 11th Sustainable Development Goals (SDGs) on sustainable cities and communities, especially in the mitigation of water-related disasters, research on flood-prone areas in Gresik Regency is needed. This study analyzes flood-prone areas in the Gresik Regency using the Analytical Hierarchy Process (AHP) and weighted overlay methods to provide information to the community and agencies to be used as a reference in disaster mitigation. The data utilized include the Digital Elevation Model, river network data, Sentinel image data, soil type data, rainfall data, and questionnaire results. The criteria used in this research are land elevation, slope, land cover, river distance, soil type, rainfall, and flood extent. Results show that rainfall criteria have the highest weight at 25%, followed by elevation at 17%, flood extent at 17%, land cover at 15%, river distance at 10%, slope at 9%, and soil type at 7%. The area of Gresik Regency classified as low vulnerability is 8.79 km2 or 0.82% of the total area, the medium vulnerability category is 936.13 km2 or 87.60% of the total area, and the high vulnerability category is 123.66 km2 or 11.57% of the total area. The most flood-prone sub-districts are Driyorejo with 28.46 km2 of highly vulnerable flood-prone area, followed by Wringinanom with 13.17 km2 Benjeng with 12.50 km2.

Pengelompokkan daerah rawan bencana di kabupaten Boyolali menggunakan algoritma k-means

The country of Indonesia, which is located in the Southeast Asia region, faces a high challenge of disasters due to demographic, geological and geographical factors that influence the occurrence of disasters, both those caused by natural, non-natural and human factors. In the Province of Central Java, especially Boyolali, disasters pose a significant threat, especially when the weather is uncertain. However, to identify priority areas for the lowest and highest levels of natural disasters in Boyolali, it is necessary to improve using data mining methods, therefore to facilitate analysis and grouping of data in identifying disaster-prone areas in Boyolali, the K-Means clustering algorithm is used. The method used in this research is qualitative and the data is analyzed using the Rapidminer Studio Ver application. 9.10. Based on the results of the analysis, there is a division of disaster-prone areas into 3 clusters in Boyolali Regency, namely very high vulnerability, medium vulnerability, and low vulnerability. The results of calculations with Rapidminer show that there are 3 sub-districts in cluster 2, 2 sub-districts in cluster 1, and 17 sub-districts in cluster 0. It should be noted that manual calculations can produce differences because the cluster center point or centroid is taken randomly for each calculation method. It is hoped that this grouping of areas can be used as a support for the Boyolali regional BPBD to focus on anticipatory steps to reduce the impact of disasters on society that may occur in the future.

Coupling Coordination Relationships Between Ecosystems and Economic Development in Qinghai and Tibet

The coordinated development of ecological protection and socioeconomics in the Tibetan Plateau is of great significance. This study examines the coupling coordination of urban ecosystems and economic development across 15 municipal administrative units in Qinghai Province and the Tibet Autonomous Region, the core areas of the Tibetan Plateau. The findings reveal that a larger proportion of the Qinghai and Tibet ecosystems are classified above the medium vulnerability level, primarily due to inherent natural geographic conditions. Additionally, the area of the two provinces and regions below the medium development level is larger, which is mainly influenced by indicators of economic strength and industrial structure. The degree of coupling coordination between the ecosystem and economic system in Qinghai and Tibet is predominantly driven by economic factors. Given the existing natural environmental conditions, the eastern regions of Qinghai and Tibet still possess certain development potential, while the economic development in the western areas is somewhat constrained by the natural environment. Based on this, further policy recommendations have been proposed to adjust and upgrade the industrial structure, aligning ecological protection with economic development in the Qinghai–Tibet Plateau. These recommendations aim to facilitate the formulation of strategies and policies for sustainable urban construction and social development in such high-ecological-value regions as the Tibetan Plateau.

Vulnerability assessment of elasmobranch species to fisheries in coastal Kenya: Implications for conservation and management policies

Ecological Risk Assessment (ERA) of species is useful for making informed management decisions based on relative vulnerability of species to fisheries. Understanding the vulnerability of species to fishing gears is important for targeted management measures especially for species known to have delicate life-history strategies such as the elasmobranchs. Productivity and Susceptibility Analysis (PSA), an ERA approach, was applied to 61 elasmobranch species (32 shark and 29 ray species) to assess their relative vulnerability (low, medium and high) to fishing by artisanal, prawn trawl and tuna longline fisheries in Kenya’s coastal waters. Overall, results showed 28 % of rays and 31 % of sharks were highly vulnerable to the fisheries, with the pelagic longline tuna fishery having the largest proportions of rays (50 %) and sharks (54 %) being highly vulnerable. Most of the species were in the medium vulnerability category. Among the artisanal gears, only gillnets had species that were highly vulnerable to the fishery, while relatively fewer species (n = 9) of both sharks and rays were highly vulnerable to the prawn trawlers compared to those in the medium vulnerability category (n = 25). Seventeen species classified as High Vulnerability Species Assemblage (HVSA), were assessed to be at high risk of overfishing by different gears, and are recommended for management as a complex. Of the HVSA group, two species; Pseudoginglymostoma brevicaudatum and Rhina ancylostoma are classified by the IUCN Red List of Threatened Species as Critically Endangered (CR), while another four; Rhinoptera jayakari, Mobula birostris, Stegostoma tigrinum and Carcharhinus plumbeus are Endangered (EN), with the rest being either Vulnerable (Gymnura poecilura, Pastinachus ater, Pateobatis jenkinsii, Taeniurops meyeni, Triaenodon obsesus, Carcharhinus falciformis, and Carcharhinus carcharias), Near Threatened (Maculabatis ambigua, Mustelus mosis, Prionace glauca) or classified as Data Deficient (Pliotrema warreni). Although majority of the species have been placed in the medium vulnerability category, some of them are those that are threatened with extinction globally, calling for a more precautionary management approach. A validation approach has been used to mitigate the problems of PSAs associated with data quality and uncertainty around estimated vulnerability indices. More robust application of PSA will require continuous updating of life-history attributes to improve on sensitivity. A precautionary Shark and Ray Management Plan (SRMP) that takes into account the outputs of the PSA is recommended for management and conservation of the elasmobranch stocks in Kenya’s marine waters.

CLUSTER MAPPING OF HOTSPOTS USING KERNEL DENSITY ESTIMATION IN WEST KALIMANTAN

Forest and land fires pose a recurring concern every year in Indonesia, often taking place in West Kalimantan Province, particularly during the dry season. This study aims to use the Kernel Density Estimation (KDE) to categorize the data of the hotspots in the province of West Kalimantan according to their density and to map the cluster level of the fire risks in the region. The data utilized in this study are secondary data obtained from the images of the MODIS (Moderate Resolution Imaging Spectroradiometer) instrument, which are available on firms.modaps.eosdis.nasa.gov and provided by NASA. The data focuses on hotspots dispersed across West Kalimantan province during 2020. The variables examined in the study were the confidence level (≥80%) of forest and land fire hotspots, the distance from each point to the nearest river, and the distance from each point to the nearest road. The kernel density estimation method with a Gaussian kernel function yielded clustering results into three distinct groups according to their vulnerability levels. Low vulnerability areas comprise Cluster 1, which consists of 127 points or 50.97% of the total hotspots. Medium vulnerability areas belong to Cluster 2, which has 47 points or 30.32% of the total. Cluster 3 includes high vulnerability locations, consisting of 29 points or 18.71% of the total. The most susceptible areas to forest and land fires are located within the Ketapang regency.

Vulnerability of elasmobranchs caught by artisanal fishery in the Southeastern Caribbean

The Caribbean is recognized as one of the regions with significant elasmobranch diversity; however, the lack of scientific data has made it difficult to conduct traditional fish stock assessments. A Productivity Susceptibility Analysis (PSA) was used to evaluate the vulnerability of the most important elasmobranch species caught by artisanal fishery carried out in the northeastern region of Venezuela. The fishing database created by the INIA and CIT was used as a starting point to obtain catch composition, and biological and fishing information. Of the 37 elasmobranch species captured in the study area, 12 were selected for the PSA. Analysis indicated that the selected species, most of them small-sized sharks, had medium and high productivity; while all species evaluated showed high susceptibility to artisanal fishing. Among the elasmobranch species with high vulnerability, seven of them comprised five sharks (C. limbatus, R. lalandii, R. porosus, C. brevipinna and C. acronotus) and two batoids (H. guttatus and A. narinari). Elasmobranchs species with medium vulnerability included two sharks (M. higmani and M. minicanis) and one batoid (H. americanus); while those with low vulnerability comprised two shark species (M canis and M. norrisi). In the study area, elasmobranch fishing has been carried out for decades without effective management strategies, and the artisanal fishery poses a potential threat to the populations of this group of fish. The species identified in this study as having high vulnerability or risk should be immediately prioritised for serious management by the national agencies responsible for fishing administration.

Factors Driving Sustainability of Food and Beverage Industries

This study has two objectives, namely compiling and analyzing vulnerability indexes of business unit, and analyzing key success variables for food and beverage industries after the COVID-19 pandemic. The analysis tool used in this study is business vulnerability analysis. The vulnerability analysis is derived from the vulnerability index to the COVID-19 threat, which is collected from all aspect indicator values of MSMEs' vulnerability to the COVID-19 theeat. These values consist of exposure, sensitivity, and adaptive capacity. The results of the study explain that food and beverage MSMEs are categorized into medium vulnerability to the threat of COVID-19, where sensitivity is the highest influence aspect as a determinant of the vulnerability level. Due in part to the high number of MSMEs that are sensitive to the threat of COVID-19 and lack the ability to adjust, there may have been a fall in sales and bankruptcy of food and beverage MSMEs during the COVID-19 pandemic.

Assessing exploitation vulnerability risk of marine ornamental reef fish in Sri Lanka: A productivity susceptibility analysis

We conducted a Productivity Susceptibility Analysis (PSA) to empirically assess the vulnerability risk of marine ornamental reef fish in Sri Lanka for exploitation. We considered distribution, accessibility, ecological niche, and market price as susceptibility attributes, while fecundity, larval development, maximum length, and longevity were productivity attributes. The vulnerability score, demand, and market price were used to assess species prioritization, and then compositions of the prioritized species were computed. The veracity of primary and secondary data collected on susceptibility and productivity attributes was confirmed by interviewing traditional fishers in situ. The IUCN and present PSA classifications for the medium susceptibility risk species were comparatively assessed. Four species out of 17 medium susceptibility risk species were encountered as the medium vulnerability risk species for exploitation. The Pacific cleaner shrimp (Lysmata amboinensis) emerged as the highest prioritized species. In addition, we observed significant differences in the species’ status assessed through the PSA approach compared to the IUCN status. The study affirms that demand and market prices substantially influence the exploitation vulnerability of species, and the PSA offers a promising multidisciplinary approach to evaluating intrinsic and extrinsic factors in conservation ecology compared to widely used IUCN status for assessing extinction risk. Furthermore, the present findings have practical implications, as they warrant essential policy changes for conserving the prioritized species and the medium vulnerability risk species encountered in the present research to extinction risk.

LAND MOVEMENT VULNERABILITY ZONING IN THE HILLY AREA OF NORTHERN CILACAP, CENTRAL JAVA

The northern part of Cilacap has an area with hilly morphology with slopes that are relatively gentle to steep. The geological setting in this region is quite complex, the combination of tectonics and the physical properties of the rocks means that this region is strongly deformed. This has an impact on areas prone to landslides as one of land movement types. To what extent can this area be classified based on the vulnerability of its land to landslides is the problem be studied. There are five aspects used in this research, namely rainfall, rock type, slope, land cover and soil type. The multi-aspect overlay method is used to determine the spatial distribution of land movement-prone zones. Geographic Information System-based software support makes the data analysis process easier. Based on the results of the spatial analysis of five aspects, it was concluded that the North Cilacap area could be grouped into 3 land movement vulnerability zones, namely the low vulnerability zone with a score of 8-17, the medium vulnerability zone with a score of 18-27, and the high vulnerability zone with a score of 28-37. The complex tectonic order is the main controller of land movement events in this region.

Multi-Parameter Approach to Determine the Floods Causes in North Luwu, South Sulawesi.

Abstract Floods occur annually in North Luwu, South Sulawesi Province, Indonesia. The exact cause of the flooding is yet to be known; thus, this study aimed to find the main factors causing floods in North Luwu using a multi-parameter approach. The methods applied are hydrological, flood susceptibility, and land use changes in the analysis. The return period and intensity duration frequency of rain (1983-2021) was used for hydrological analysis. Flood susceptibility is obtained from the processing of slope, elevation, rainfall, stream density, soil type, and land use parameters. Land use change was analyzed using the Climate Change Initiative and Land Cover (CCI LC) data in 2000 and 2015. The results of the 1-year rainfall return period in North Luwu were relatively high, namely 83 mm/day, the 2-year return period of 119 mm/day, 5 years of 142 mm/day, 10 years of 155 mm/day, and 100 years 184 mm/day. The results of the IDF analysis obtained that the early rainy hours showed an intensity of 41-46 mm/hour with a total of 259 mm/day, which was considered extreme. There is unity between the results of the correlation of flood events in 2021 with recorded rainfall of 64-153 mm/day. Flood susceptibility analysis shows the dominant high vulnerability in the downstream area of 101,337 Ha, medium vulnerability (208,545 Ha) in the middle stream, and low vulnerability of 57,719 Ha upstream. The high flood susceptibility map results followed the flood events distribution from 2017-2021, while there is a lack of change in the land use analysis.

Vulnerability of Mass Movement Zonation Using DEM in Upstream – Midstream Kelara Watershed, Jeneponto Regency, South Sulawesi

Mass movement is one of the major natural disasters that claim many lives and property. The Kelara watershed, which is the research area, often encounters land movements that often cause casualties. The problem of mass movement often occurs in the upstream - midstream part of the Kelara watershed with mountainous to hilly morphology with moderately steep to steeply sloping relief. The parameters used in this analysis are lithology, distance from faults, distance from rivers, distance from streets, land use, rainfall, soil type, slope, profile curvature, and slope aspect. The analysis was conducted by giving weights based on the comparison of soil movement events to the class of each parameter using the Weight of Evidence method. Based on the Weight of Evidence method, the mass movement vulnerability zone is divided into five zones, very low vulnerability zone occupies 7.75%, low vulnerability zone occupies 27.11%, medium vulnerability zone occupies 31.76%, high vulnerability zone occupies 21.72%, and very high vulnerability zone occupies 11.66% of the total study area. Based on validation using the AUC value, the Weight of Evidence Method has a value of 0.771 (Fairly Good Model).

Landscape Pattern Vulnerability and Its Driving Forces in Different Geomorphological Divisions in the Middle Yellow River

The ecological environment of the middle Yellow River is highly vulnerable. Conducting a scientific assessment of landscape pattern vulnerability holds great significance, as it serves as the basis for the rational construction of the ecological environment in this area. Based on five periods of land use data from the middle Yellow River from 1990 to 2018, the landscape pattern vulnerability index was employed to analyze the spatio-temporal evolution of the landscape pattern vulnerability. Furthermore, the influencing factors for landscape pattern vulnerability in different natural geomorphological divisions were explored using an optimal parameters-based geographical detector model. The results showed that:① From 1990 to 2018, cultivated land (which accounted for 36.96 % to 39.97 % of the area) remained the predominant landscape in the middle Yellow River. Among all landscape types, cultivated land and construction land exhibited the most significant changes. The area of cultivated land decreased by 10 185.00 km2, whereas the area of construction land increased by 7 678.46 km2. ② From 1990 to 2018, the landscape pattern was dominated by low and medium vulnerability and accounted for 70 %-80 % of the total area. The high and higher vulnerability areas were concentrated in the loess hilly and gully region, whereas the lower vulnerability area was concentrated in the valley plain and the earth-rock mountain regions. During this period, landscape pattern vulnerability underwent an incipient decrease, followed by a subsequent increase. From 1990 to 2000 and from 2000 to 2005, the changes in the level of landscape pattern vulnerability were dominated by a "reduction in the degree of vulnerability". However, from 2005 to 2010 and from 2010 to 2018, it was mainly an "increase in the degree of vulnerability". ③ Annual precipitation and NDVI were the main factors influencing the vulnerability of landscape patterns, whereas the influencing factors varied across different natural geomorphological divisions:the loess hilly and gully region and the earth-rock mountain region were dominated by natural factors, with annual precipitation and DEM being the dominant factors, respectively; the loess plateau tableland-gully region, valley plain region, and sandy land and desert region were dominated by human factors, with population density, degree of land use, and distance from roads being the dominant factors, respectively. The interaction results of any two influencing factors were manifested as two-factor enhancement or nonlinear enhancement. Risk detection revealed that high vulnerability areas of landscape patterns in different natural geomorphological divisions were distributed over distinct ranges of their corresponding dominant factors. Therefore, in the practices of ecological management in the middle Yellow River, appropriate management strategies should be implemented based on the vulnerability characteristics of different natural landforms, to further improve the ecological management level of the watershed.

PENILAIAN TINGKAT KERENTANAN AIR TANAH TERHADAP PENCEMARAN BERDASARKAN METODE SIMPLE VERTICAL VULNERABILITY DI KECAMATAN DIWEK KABUPATEN JOMBANG

The water source that is widely used to meet the domestic needs of people in the Diwek District, Jombang Regency is ground water through the use of dug wells. The groundwater at this location has the potential to be polluted by industrial waste. To anticipate this, research is needed on assessing the level of intrinsic vulnerability of groundwater to pollution based on the physical properties of rocks. The aim of this research is to assess the level of intrinsic vulnerability of groundwater to pollution and map its distribution. This research was carried out on 24 samples of dug wells in the Diwek District area which were observed periodically for 5 months from July 2023 to November 2023. The assessment of the level of intrinsic vulnerability of groundwater to pollution was carried out using the Simple Vertical Vulnerability (SVV) method based on 3 parameters i.e. the type of water unsaturated zone material (La), recharge/percolation (Wu), and the thickness of the water unsaturated zone (Z). Based on the research results, it can be stated that the SVV index value during the research period ranged from 14.89 to 40.96 with 3 categories of groundwater vulnerability levels, namely medium, high and very high. The distribution of groundwater vulnerability levels in the research location is dominated by medium vulnerability with an area varying from 46% - 48% of the study area.

Analysis of landslide-prone areas in Tripe Jaya district, Gayo Lues Regency

Abstract Tripe Jaya District is one of the sub-districts of Gayo Lues regency, which has hilly and mountainous morphological areas with steep slopes and landslides in several regions of the road area. This study aims to identify and map the location of landslides and analyze landslide areas. A quantitative method for measuring landslide-prone levels from the Center for Volcanology and Geological Hazard Mitigation 2005, the method used is the score and weight of the parameters that cause landslide-prone. The causes of landslide-prone sites are rainfall data, soil type, elevation, land use, and slope. The results of this study have five classes of landslide vulnerability, including very low landslide vulnerability level covering an area of 279.21 Ha (1%), low vulnerability level covering an area of 3639.80 Ha (9%), medium vulnerability level covering an area of 17893.07 Ha (43%), high vulnerability level covering an area of 19822.91 Ha (47%), and very high vulnerability level covering an area of 150.23 Ha (0.36%). Landslide events in Tripe Jaya District based on field observations, there are landslide events in high and very high classes. This research provides an overview of landslide-prone areas so the results of the study can be used as a basis for planning mitigation strategies and as a consideration for the government in building the required mitigation developing mitigation measures related to landslide-prone risks in the Tripe Jaya.

Computer model for detecting tsunami wave hazard on built-up land using machine learning and sentinel 2A satellite imagery

<p>The aim of this research is to compile a tsunami wave hazard scale based on built-up land density extracted and classified by machine learning from Sentinel 2A satellite and digital elevation model (DEM) imageries. This research was carried out in 5 stages, namely: (i) pre-processing of Sentinel 2A and DEM images, (ii) Classification of VI data using the machine learning algorithms, (iii) Spatial prediction using the ordinary kriging method, (iv) Field testing using the confusion matrix method, (v) Preparation of decision matrix for tsunami wave hazard. The results of the study show that the most accurate classification algorithm for classifying built-up indices data is the k-nearest neighbor (k-NN) algorithm. The results of the statistical accuracy test show that the most accurate is normalized difference built-up index (NDBI) with a mean of square error (MSE) value of 0.073 and a mean of absolute error (MAE) of 0.003. DEM analysis shows that the research area is at an altitude of 0–15 meters above sea level so it is in the high vulnerability to medium vulnerability category. Field testing showed user accuracy of 91.11%, manufacturer accuracy of 92.16%, and overall average accuracy of 91%.</p>

Sensitivity Analysis and GIS Tools for Groundwater Vulnerability Assessment. (Application in the Middle Chellif Plain, Algeria)

Contamination due to rapid urban development, industrialization, and agricultural sources is increasingly threatening the groundwater resources of the plioquaternary phreatic aquifer of the Middle Western Cheliff. An intrinsic vulnerability assessment was carried out based on the DRASTIC method on parameters involved in the vertical transfer of pollution from the soil surface. The vulnerability maps obtained showed a high extension of areas of medium vulnerability (54%). On the other hand, areas of low vulnerability occupied about 36%. The high and very high vulnerability was mainly related to low water depth values (8% and 2%, respectively). The results of a sensitivity analysis using the two tests—the single parameter sensitivity analysis and the map removal sensitivity analysis—show that every parameter is, without fail, required for the computation of the vulnerability index. The validation of the vulnerability map produced by the DRASTIC method confirmed the evolution of this sensitivity which decreases towards the S.W. of the plain with nitrate concentrations between 30 and 120 mg/L. Planners can use the produced risk maps as tools to make a preliminary choice of priority locations for various forms of environmental sustainability.

Food fraud threats in UK post-harvest seafood supply chains; an assessment of current vulnerabilities.

Seafood fraud is commonly reported on food fraud databases and deceptive practices are highlighted by numerous studies, with impacts on the economy, health and marine conservation. Food fraud assessments are a widely accepted fraud mitigation and prevention activity undertaken to identify possible points of deception within a supply chain. This study aims to understand the food fraud vulnerability of post-harvest seafood supply chains in the UK and determine if there are differences according to commodity, supply chain node, business size and certification status. The SSAFE food fraud vulnerability assessment tool was used to assess 48 fraud factors relating to opportunities, motivations and controls. The analysis found seafood supply chains to have a medium vulnerability to food fraud, with the highest perceived vulnerability in technical opportunities. Certification status was a stronger determinant of vulnerability than any other factor, particularly in the level of controls, a factor that also indicated a higher perceived level of vulnerability in smaller companies and the food service industry. This paper also reviews historic food fraud trends in the sector to provide additional insights and the analysis indicates that certain areas of the supply chain, including uncertified prawn supply chains, salmon supply chains and food service companies, may be at higher risk of food fraud. This study conducts an in-depth examination of food fraud vulnerability relating to the UK and for seafood supply chains and contributes to a growing body of literature identifying areas of vulnerability and resilience to food related criminality within the global food system.

Productivity susceptibility analysis in extremely data-poor scenarios: The case of Peruvian coastal groundfish

Coastal small-scale fisheries remain largely unassessed and unregulated worldwide, which leads to a high risk of overfishing. Availability and quality of data are major barriers to performing model-based assessments, particularly in low and middle-income countries. In that context, alternative assessment methods are key to defining priorities, as well as prompting and guiding management actions. In this study, we assessed the vulnerability to overfishing of 10 extremely data-poor species of coastal groundfish in Peru, by applying an adapted Productivity Susceptibility Analysis (PSA). We classified fisheries-related Susceptibility attributes and streamlined a process to assess and integrate multiple fisheries and gears into a single score for each attribute. The data quality scores regarding productivity and susceptibility were between “limited” and “no data”, across all stocks. Therefore, expert knowledge was key for completing the assessment. Stocks of four species presented extremely high Vulnerability to overfishing: broomtail grouper (V=2.57), grape-eye seabass (V=2.50), pacific goliath grouper (V=2.28) and galapagos sheephead wrasse (V=2.24). Three showed high Vulnerability to overfishing: black snook (V=2.13), harlequin wrasse (V=2.05) and chino (V=2.01). Two showed medium Vulnerability to overfishing: mulata (V=1.89) and pacific beakfish (V=1.89). Only the stock of bumphead parrotfish showed low Vulnerability to overfishing (V=1.73). We contrasted the resulting Vulnerability scores with the limited available information on the statuses of these stocks, to evaluate the accurateness of the overfishing probability thresholds proposed in PSA literature. We found that Vulnerability scores were mostly consistent with contrasted information and that the thresholds remain useful to inform fisheries management in extremely data-poor contexts. Our results shed light on the need for the implementation of fishing regulations and the generation of biological and fishery-related data on coastal groundfish in Peru.

Vulnerability of ground water to polution in the highlands by a combined approach of AHP method and remote sensing

The aim of this work is to develop a simple and convenient decision support tool for the highlands using a combined approach of the Analytic Hierarchy Process (AHP) method and remote sensing. The vulnerability assessment method developed is called O3P (Highlands method). It is a parametric method, adapted in the highlands and implement in the town of Bafoussam. This method takes into account 4 factors, including land use (O), permeability (P1), slope (P2) and water depth in the piezometers (P3). The AHP multi-criteria analysis coupled with geographic information systems (GIS) and the analysis of nitrate pollution, allowed the development and validation of the O3P method. The results obtained show 3 classes of vulnerabilities which evolve from the low vulnerability class (20.22% of the study area) to the classes of medium vulnerability (50.16 %) and high vulnerability (29.62 %). Classes of high vulnerability to pollution are more present in the central-northern part of the study area, with some occurrences towards the south. The superposition of the highest nitrate concentrations with the areas of high vulnerability confirms the validity of the method. It emerges from it following the study of the sensitivity that the land occupation factor has the most important effect in this model and whose reduction would influence to 35.54% the method. The statistical study shows that this method is acceptable because the value of the standard deviations of the IVO3P lower than that its mean.