Confronting Management Challenges in Highly Uncertain Natural Resource Systems: a Robustness–Vulnerability Trade-off Approach

This paper presents a framework for the study of policy implementation in highly uncertain natural resource systems in which uncertainty cannot be characterized by probability distributions. We apply the framework to parametric uncertainty in the traditional Gordon–Schaefer model of a fishery to illustrate how performance can be sacrificed (traded-off) for reduced sensitivity and hence increased robustness, with respect to model parameter uncertainty. With sufficient data, our robustness–vulnerability analysis provides tools to discuss policy options. When less data are available, it can be used to inform the early stages of a learning process. Several key insights emerge from this analysis: (1) the classic optimal control policy can be very sensitive to parametric uncertainty, (2) even mild robustness properties are difficult to achieve for the simple Gordon–Schaefer model, and (3) achieving increased robustness with respect to some parameters (e.g., biological parameters) necessarily results in increased sensitivity (decreased robustness) with respect to other parameters (e.g., economic parameters). We thus illustrate fundamental robustness–vulnerability trade-offs and the limits to robust natural resource management. Finally, we use the framework to explore the effects of infrequent sampling and delays on policy performance.     

Climate change vulnerability in a tropical region based on environmental and socio-economic factors

The understanding of the regional and local dimensions of vulnerability due to climate change is essential to develop appropriate and targeted adaptation efforts. We assessed the local dimensions of vulnerability in the tropical state of Kerala, India, using a purposely developed vulnerability index, which accounts for both environmental and socio-economic factors. The large extents of coastal wetlands and lagoons and high concentration of mangrove forests make the state environmentally vulnerable. Low human development index, large population of socially deprived groups, which are dependent on the primary sector, and high population density make the state vulnerable from a socio-economic point of view. The present study investigates climate change vulnerability at the district level in the State of Kerala relying on a purposely developed composite vulnerability index that encompasses both socio-economic and environmental factors. The Kerala coast contains the socio-economically and ecologically most vulnerable regions, as demonstrated by a composite vulnerability index.     

Compositing climate change vulnerability of a Mediterranean region using spatiotemporally dynamic proxies for ecological and socioeconomic impacts and stabilities

The study presents a new methodology to quantify spatiotemporal dynamics of climate change vulnerability at a regional scale adopting a new conceptual model of vulnerability as a function of climate change impacts, ecological stability, and socioeconomic stability. Spatiotemporal trends of equally weighted proxy variables for the three vulnerability components were generated to develop a composite climate change vulnerability index (CCVI) for a Mediterranean region of Turkey combining Landsat time series data, digital elevation model (DEM)-derived data, ordinary kriging, and geographical information system. Climate change impact was based on spatiotemporal trends of August land surface temperature (LST) between 1987 and 2016. Ecological stability was based on DEM, slope, aspect, and spatiotemporal trends of normalized difference vegetation index (NDVI), while socioeconomic stability was quantified as a function of spatiotemporal trends of land cover, population density, per capita gross domestic product, and illiteracy. The zones ranked on the five classes of no-to-extreme vulnerability were identified where highly and moderately vulnerable lands covered 0.02% (12 km²) and 11.8% (6374 km²) of the study region, respectively, mostly occurring in the interior central part. The adoption of this composite CCVI approach is expected to lead to spatiotemporally dynamic policy recommendations towards sustainability and tailor preventive and mitigative measures to locally specific characteristics of coupled ecological–socioeconomic systems.     

Climatic Implications of Revised IPCC Emissions Scenarios, the Kyoto Protocol and Quantification of Uncertainties

In December 1997, the United Nations Framework Convention on Climate Change (FCCC) adopted the Kyoto Protocol. This paper describes a framework that models the climatic implications of this international agreement, using Monte Carlo simulations and the preliminary Intergovernmental Panel on Climate Change emissions scenarios (SRES). Emissions scenarios (including intervention scenarios), climate sensitivity, and terrestrial carbon sink are the key sampled model parameters. This framework gives prior probability distributions to these parameters and, using a simple climate model, posterior distributions of global temperature change are determined for the future. Our exercise showed that the Kyoto Protocol's effectiveness will be mostly dependent upon which SRES world evolves. In some worlds the Protocol decreases the warming considerably but in others it is almost irrelevant. We exemplified this approach with a current FCCC issue, namely “hot air”. This modelling framework provides a probabilistic assessment of climate policies, which can be useful for decision-makers involved in global climate change management. This revised version was published online in July 2006 with corrections to the Cover Date.     

基于广西河池市胁迫风险的土壤环境脆弱性评价

采用层次分析法划分了土壤环境各因素的敏感性和重要程度,从而建立起能科学表达土壤环境承载能力的土壤环境脆弱性评价体系。基于广西河池市指标数据,借助地理信息系统软件Arc GIS9.3、ENVI5.1、MATLAB7.0等计算平台对空间数据进行模型训练与验证,得出可视化表征土壤环境脆弱性空间分布状况的评价图件。结果表明,河池市北部、南部存在高度脆弱区,占全市国土面积的36.3%,中度脆弱区占38.3%,低度脆弱区占25.4%。总体来看,河池市大部分区域的土壤环境属中高度脆弱。     

Using multi-criteria decision analysis to assess the vulnerability of drinking water utilities

Outbreaks of microbiological waterborne disease have increased governmental concern regarding the importance of drinking water safety. Considering the multi-barrier approach to safe drinking water may improve management decisions to reduce contamination risks. However, the application of this approach must consider numerous and diverse kinds of information simultaneously. This makes it difficult for authorities to apply the approach to decision making. For this reason, multi-criteria decision analysis can be helpful in applying the multi-barrier approach to vulnerability assessment. The goal of this study is to propose an approach based on a multi-criteria analysis method in order to rank drinking water systems (DWUs) based on their vulnerability to microbiological contamination. This approach is illustrated with an application carried out on 28 DWUs supplied by groundwater in the Province of Québec, Canada. The multi-criteria analysis method chosen is measuring attractiveness by a categorical based evaluation technique methodology allowing the assessment of a microbiological vulnerability indicator (MVI) for each DWU. Results are presented on a scale ranking DWUs from less vulnerable to most vulnerable to contamination. MVI results are tested using a sensitivity analysis on barrier weights and they are also compared with historical data on contamination at the utilities. The investigation demonstrates that MVI provides a good representation of the vulnerability of DWUs to microbiological contamination.     

Environmental vulnerability assessment using Grey Analytic Hierarchy Process based model

Environmental management of an area describes a policy for its systematic and sustainable environmental protection. In the present study, regional environmental vulnerability assessment in Hirakud command area of Odisha, India is envisaged based on Grey Analytic Hierarchy Process method (Grey–AHP) using integrated remote sensing (RS) and geographic information system (GIS) techniques. Grey–AHP combines the advantages of classical analytic hierarchy process (AHP) and grey clustering method for accurate estimation of weight coefficients. It is a new method for environmental vulnerability assessment. Environmental vulnerability index (EVI) uses natural, environmental and human impact related factors, e.g., soil, geology, elevation, slope, rainfall, temperature, wind speed, normalized difference vegetation index, drainage density, crop intensity, agricultural DRASTIC value, population density and road density. EVI map has been classified into four environmental vulnerability zones (EVZs) namely: ‘low’, ‘moderate’ ‘high’, and ‘extreme’ encompassing 17.87%, 44.44%, 27.81% and 9.88% of the study area, respectively. EVI map indicates that the northern part of the study area is more vulnerable from an environmental point of view. EVI map shows close correlation with elevation. Effectiveness of the zone classification is evaluated by using grey clustering method. General effectiveness is in between “better” and “common classes”. This analysis demonstrates the potential applicability of the methodology.     

Rabbit Population Landscape-Scale Simulation to Investigate the Relevance of Using Rabbits in Regulatory Environmental Risk Assessment

This paper describes the development and testing of the ALMaSS rabbit model and its baseline, and subsequently its application to the question of lagomorph population vulnerability in environmental risk assessment (ERA). Development and testing following a pattern-oriented modelling protocol resulted in a model able to replicate local and landscape-level rabbit population patterns. We then tested how robust rabbit populations are to an (imaginary) extreme toxic stressor at a landscape level in a variety of landscapes, and to what extremes key uncertain model parameters must be pushed to cause extinctions. This was contrasted with the same (imaginary) toxic stressor applied to the already existing ALMaSS hare model. For EU risk assessment of plant protection products, these results clearly indicate that if the protection goal is population-level impacts, either in abundance and/or distribution, then the hare is a much more vulnerable species than the rabbit under all the conditions tested. Rabbits would only be more vulnerable than hares if the entire population were to be exposed simultaneously, when lower body mass would then be a critical factor. This did not occur even though the toxicant and exposure scenarios tested here were extreme and, in fragmented landscapes at scales used here, will not occur in reality from the use of plant protection products on crop fields. As well as specifically answering the question on rabbit versus hare vulnerability, this study generally illustrates the potential application of models for setting focal species for risk assessments.     

Using multiple-criteria decision-making techniques for eco-environmental vulnerability assessment: a case study on the Chi-Jia-Wan Stream watershed, Taiwan

The Chi-Jia-Wan Stream watershed, located in the area of the upstream Da-Chia River in central Taiwan, is famous for slopeland agriculture and the land-locked salmon. Improper agricultural activities have caused apparent ecosystem vulnerability and sensitivity. In this study, a system that combined three watershed-based environmental indicators with multiple-criteria decision-making techniques, the Analytical Hierarchy Process, and the Preference Ranking Organization METHod for Enrichment Evaluations was developed to assess eco-environmental vulnerability. The composite evaluation index system was set up including sediment, runoff, and nutrient factors. Supported by geographic information system and K-means clustering and taking the subwatershed as the evaluation unit, the vulnerability is classified into four levels: potential, low, moderate, and high. The evaluated results show that 8.82% of subwatersheds (six subwatersheds) are in the moderately and highly vulnerable zones. These subwatersheds represent vertical-belt distribution, mainly concentrated in the right side of the studied area and near the riparian zone along the Chi-Jia-Wan Stream. The exploited farmland in the moderately and highly vulnerable zones is about 142.21 ha, occupying 75.38% of the total farmland in the studied watershed. These seriously vulnerable zones that have caused degradation in the quality of the eco-environment should be treated with more best management practices for eco-environmental rehabilitation. Additionally, the proposed model can effectively evaluate the eco-environmental vulnerability grade for reference in policy planning and ecological restoration in this area.     

A multi criteria analog model for assessing the vulnerability of rural catchments to road spills of hazardous substances

Road spills of hazardous substances are common in developing countries due to increasing industrialization and traffic accidents, and represent a serious threat to soils and water in catchments. There is abundant literature on equations describing the wash-off of pollutants from roads during a storm event and there are a number of watershed models incorporating those equations in storm water quality algorithms that route runoff and pollution yields through a drainage system towards the catchment outlet. However, methods describing catchment vulnerability to contamination by road spills based solely on biophysical parameters are scarce. These methods could be particularly attractive to managers because they can operate with a limited amount of easily collectable data, while still being able to provide important insights on the areas more prone to contamination within the studied watershed. The purpose of this paper was then to contribute with a new vulnerability model. To accomplish the goal, a selection of medium properties appearing in wash-off equations and routing algorithms were assembled and processed in a parametric framework based on multi criteria analysis to define the watershed vulnerability. However, parameters had to be adapted because wash-off equations and water quality models have been developed to operate primarily in the urban environment while the vulnerability model is meant to run in rural watersheds. The selected parameters were hillside slope, ground roughness (depending on land use), soil permeability (depending on soil type), distance to water courses and stream density. The vulnerability model is a spatially distributed algorithm that was prepared to run under the IDRISI Selva software, a GIS platform capable of handling spatial and alphanumeric data and execute the necessary terrain model, hydrographic and thematic analyses. For illustrative purposes, the vulnerability model was applied to the legally protected Environmental Protection Area (APA), located in the Uberaba region, state of Minas Gerais, Brazil. In this region, the risk of accidents causing chemical spills is preoccupying because large quantities of dangerous materials are transported in two important distribution highways while the APA is fundamental for the protection of water resources, the riverine ecosystems and remnants of native vegetation. In some tested scenarios, model results show 60% of vulnerable areas within the studied area. The most sensitive parameter to vulnerability is soil type. To prevent soils from contamination, specific measures were proposed involving minimization of land use conflicts that would presumably raise the soil's organic matter and in the sequel restore the soil's structural functions. Additionally, the present study proposed the preservation and reinforcement of riparian forests as one measure to protect the quality of surface water.     

Hare or Tortoise? Trade-offs in Recovering Sustainable Bioeconomic Systems

In this paper, we develop a framework for (a) the study of sustainability of dynamic bioeconomic systems and (b) the definition of recovery paths from unsustainable situations. We assume that the system follows a sustainable trajectory if it evolves over time within a set of multidimensional constraints. We use the mathematical concept of viability to characterize sustainability. Recovery paths are studied with regards to their duration and their acceptability. This general framework is applied to the issue of recovering sustainable fisheries. We define sustainability in a fishery as the requirement that a set of economic, ecological, and social constraints is satisfied at all times. Recovery paths are characterized by the time required to obtain sustainable exploitation conditions in the fishery and by the acceptable recovery costs for fishermen. In particular, we identify the recovery path which minimizes the time of crisis under a minimum transition profit constraint. We then describe the trade-off between speed and accepted costs of recovery paths, by comparing “Hare”-like high-speed–high-cost strategies to “Tortoise”-like low-speed–low-cost strategies. We illustrate our results by means of a numerical analysis of the Bay of Biscay Nephrops fishery.     

Groundwater vulnerability assessment using DRASTIC and Pesticide DRASTIC models in intense agriculture area of the Gangetic plains,India

Delineating areas susceptible to contamination from anthropogenic sources form an important component of sustainable management of groundwater resources. The present research aims at estimating vulnerability of groundwater by application of DRASTIC and Pesticide DRASTIC models in the southern part of the Gangetic plains in the state of Bihar. The DRASTIC and Pesticide DRASTIC models have considered seven parameters viz. depth to water level, net recharge, aquifer material, soil material, topography, impact of vadose zone and hydraulic conductivity. A third model, Pesticide DRASTIC LU has been adopted by adding land use as an additional parameter, to assess its impact on vulnerability zonation. The DRASTIC model indicated two vulnerable categories, moderate and high, while the Pesticide DRASTIC model revealed moderate, high and very high vulnerable categories. Out of the parameters used, depth to water level affected the vulnerability most. The parameter caused least impact was topography in DRASTIC, while in case of Pesticide DRASTIC and Pesticide DRASTIC LU models, the parameter was hydraulic conductivity. A linear regression between groundwater NO₃ concentrations and the vulnerability zonation revealed better correlation for Pesticide DRASTIC model, emphasising the effectiveness of the model in assessing groundwater vulnerability in the study region. Considering all three models, the most vulnerable areas were found to be concentrated mainly in two zones, (i) in the south-western part along Ekangarsarai-Islampur patch and (ii) around Biharsharif-Nagarnausa area in the central part. Both zones were characterised by intensive vegetable cultivation with urban areas in between.     

Application of thresholds of potential concern and limits of acceptable change in the condition assessment of a significant wetland

We propose a framework in which thresholds of potential concern (TPCs) and limits of acceptable change (LACs) are used in concert in the assessment of wetland condition and vulnerability and apply the framework in a case study. The lower Murrumbidgee River floodplain (the ‘Lowbidgee’) is one of the most ecologically important wetlands in Australia and the focus of intense management intervention by State and Federal government agencies. We used a targeted management stakeholder workshop to identify key values that contribute to the ecological significance of the Lowbidgee floodplain, and identified LACs that, if crossed, would signify the loss of significance. We then used conceptual models linking the condition of these values (wetland vegetation communities, waterbirds, fish species and the endangered southern bell frog) to measurable threat indicators, for which we defined a management goal and a TPC. We applied this framework to data collected across 70 wetland storages’, or eco-hydrological units, at the peak of a prolonged drought (2008) and following extensive re-flooding (2010). At the suggestion of water and wetland mangers, we neither aggregated nor integrated indices but reported separately in a series of chloropleth maps. The resulting assessment clearly identified the effect of rewetting in restoring indicators within TPC in most cases, for most storages. The scale of assessment was useful in informing the targeted and timely management intervention and provided a context for retaining and utilising monitoring information in an adaptive management context.     

Assessment of groundwater vulnerability in the coastal region of Oman using DRASTIC index method in GIS environment

A study was carried out to develop a vulnerability map for Barka region in the North Batina of Oman using DRASTIC vulnerability index method in GIS environment. DRASTIC layers were created using data from published reports and the seven DRASTIC layers were processed by the ArcGIS geographic information system. Finally, DRASTIC maps were created for 1995 and 2004 to understand the long-term changes in the vulnerability index. DRASTIC vulnerability maps were evaluated using groundwater quality data such as chemical and biological parameters. DRASTIC vulnerability maps of 1995 and 2004 indicate that the northern part of Barka is more vulnerable to pollution than southern part and the central part of Barka also shows high relative vulnerability which is mostly related to the high conductivity values. Moreover, the changes in water level due to high abstraction rate of groundwater reflect in the vulnerability maps and low vulnerability area is increased in the southern part during 2004 compared to 1995. Moreover, regional distribution maps of nitrate, chloride and total and fecal coliforms are well correlated with DRASTIC vulnerability maps. In contrast to this, even though DRASTIC method predicted the central part of the study region is highly vulnerable, both chemical and biological parameters show lower concentrations in this region compared to coastal belt, which is mainly due to agricultural and urban development. In Barka, urban development and agricultural activities are very high in coastal region compared to southern and central part of the study area. Hence, this study concluded that DRASTIC method is also applicable in coastal region having ubiquitous contamination sources.     

Distributed process modeling for regional assessment of coastal vulnerability to sea-level rise

Sea-level rise involves increases in the coastal processes of inundation and erosion which are affected by a complex interplay of physical environmental parameters at the coast. Many assessments of coastal vulnerability to sea-level rise have been detailed and localised in extent. There is a need for regional assessment techniques which identify areas vulnerable to sea-level rise. Four physical environmental parameters – elevation, exposure, aspect and slope, are modeled on a regional scale for the Northern Spencer Gulf (NSG) study area using commonly available low-resolution elevation data of 10 m contour interval and GIS-based spatial modeling techniques. For comparison, the same parameters are modeled on a fine-scale for the False Bay area within the NSG using high-resolution elevation data. Physical environmental parameters on the two scales are statistically compared to coastal vulnerability classes as identified by Harvey et al. [1] using the Spearman rank-correlation test and stepwise linear regression. Coastal vulnerability is strongly correlated with elevation and exposure at both scales and this relationship is only slightly stronger for the high resolution False Bay data. The results of this study suggest that regional scale distributed coastal process modeling may be suitable as a first cut in assessing coastal vulnerability to sea-level rise in tide-dominated, sedimentary coastal regions. Distributed coastal process modeling provides a suitable basis for the assessment of coastal vulnerability to sea-level rise of sufficient accuracy for on-ground management and priority-setting on a regional scale.     

Northern Rivers Ecosystem Initiative: Context and Prevailing Legacy

The Northern River Ecosystem Initiative (NREI), 1997–2004, has provided new scientific knowledge in response to specific recommendations from its predecessor, the Northern River Basins Study (NRBS), 1990–1996. The two initiatives together provide a remarkable body of science which is, and will continue to be, used by resource managers responsible for economic and environmental sustainability in the northern watersheds of Alberta. The NREI focused its investigative efforts on improving our understanding related to ecological considerations of changes in river flow, effect of climate change on flow, ecological responses to pollution and cumulative effects, vulnerability of drinking water quality, and to a lesser degree, wildlife (birds) response to large scale changes within the watersheds. Key findings are briefly presented in this paper and discussed in greater detail in the other NREI papers included in this. Commensurate with the undertakings of NREI, provincial and territorial governments, First Nation and Métis communities, and other administrative organizations such as the Mackenzie River Basin Board, undertook policy, regulatory, and watershed initiatives towards achieving sustainability and providing reliable drinking water quality.     

Coastal Flood Risk Analysis Using Landsat-7 ETM+ Imagery and SRTM DEM: A Case Study of Izmir, Turkey

The Intergovernmental Panel on Climate Change (IPCC) reports an acceleration of the global mean sea-level rise (MSLR) in the twentieth century in response to global climate change. If this acceleration remains constant, then some coastal areas are most likely to be inundated by the year 2100. The ability to identify the differential vulnerability of coastlines to future inundation hazards as result of global climate change is necessary for timely actions to be taken. Yildiz et al. (Journal of Mapping, 17, 1-75, 2003) reported that the local MSLR in the city of Izmir rose at a rate of 6.8 +/- 0.9 mm year(-1) between 1984 and 2002. In this study, the spatial distribution of the coastal inundation hazards of Izmir region was determined using not only land-use and land-cover (LULC) types derived from the maximum likelihood classification of Landsat-7 Enhanced Thematic Mapper Plus (ETM+) multi-spectral image set but also the classification of the digital elevation model (DEM) acquired by the shuttle radar topography mission (SRTM). Coastal areas with elevations of 2 and 5 m above mean sea-level vulnerable to inundation were found to cover 2.1 and 3.7% of the study region (6,107 km(2)), respectively. Our findings revealed that Menemen plain along Gediz river, and the settlements of Karsiyaka, Alacati, Aliaga, Candarli and Selcuk are at high risk in order of decreasing vulnerability to permanent and episodic inundation by 2100 under the high MSLR scenarios of 20 to 50 mm year(-1).     

Assessment of groundwater vulnerability in the Yinchuan Plain,Northwest China using OREADIC

Groundwater vulnerability assessments provide a measure of the sensitivity of groundwater quality to an imposed contaminant load and are globally recognized as an essential element of all aquifer management and protection plans. In this paper, the vulnerability of groundwaters underlying the Yinchuan Plain of Northwest China is determined using OREADIC, a GIS-based assessment tool that incorporates the key characteristics of the universally popular DRASTIC approach to vulnerability assessment but has been modified to consider important additional hydrogeological factors that are specific to the region. The results show that areas of high vulnerability are distributed mainly around Qingtongxia City, Wuzhong City, Lingwu City, and Yongning County and are associated with high rates of aquifer recharge, shallow depths to the water table, and highly permeable aquifer materials. The presence of elevated NO₃⁻ in the high vulnerability areas endorses the OREADIC approach. The vulnerability maps developed in this study have become valuable tools for environmental planning in the region and will be used for predictive management of the groundwater resource.     

A method to the impact assessment of the returning grazing land to grassland project on regional eco-environmental vulnerability

The Chinese government has conducted the Returning Grazing Land to Grassland Project (RGLGP) across large portions of grasslands from western China since 2003. In order to explore and understand the impact in the grassland's eco-environment during the RGLGP, we utilized Projection Pursuit Model (PPM) and Geographic Information System (GIS) to develop a spatial assessment model to examine the ecological vulnerability of the grassland. Our results include five indications: (1) it is practical to apply the spatial PPM on ecological vulnerability assessment for the grassland. This methodology avoids creating an artificial hypothesis, thereby providing objective results that successfully execute a multi-index assessment process and analysis under non-linear systems in eco-environments; (2) the spatial PPM is not only capable of evaluating regional eco-environmental vulnerability in a quantitative way, but also can quantitatively demonstrate the degree of effect in each evaluation index for regional eco-environmental vulnerability; (3) the eco-environment of the Xianshui River Basin falls into the medium range level. The normalized difference vegetation index (NDVI) and land use cover and change (LUCC) crucially influence the Xianshui River Basin's eco-environmental vulnerability. Generally, in the Xianshui River Basin, regional eco-environmental conditions improved during 2000 and 2010. The RGLGP positively affected NDVI and LUCC structure, thereby promoting the enhancement of the regional eco-environment; (4) the Xianshui River Basin divides its ecological vulnerability across different levels; therefore our study investigates three ecological regions and proposes specific suggestions for each in order to assist in eco-environmental protection and rehabilitation; and lastly that (5) the spatial PPM established by this study has the potential to be applied on all types of grassland eco-environmental vulnerability assessments under the RGLGP and under the similar conditions in the Returning Agriculture Land to Forest Project (RALFP). However, when establishing an eco-environmental vulnerability assessment model, it is necessary to choose suitable evaluation indexes in accordance with regional eco-environmental characteristics.