A review of vulnerability indicators for deltaic social–ecological systems

The sustainability of deltas worldwide is under threat due to the consequences of global environmental change (including climate change) and human interventions in deltaic landscapes. Understanding these systems is becoming increasingly important to assess threats to and opportunities for long-term sustainable development. Here, we propose a simplified, yet inclusive social–ecological system (SES)-centered risk and vulnerability framework and a list of indicators proven to be useful in past delta assessments. In total, 236 indicators were identified through a structured review of peer-reviewed literature performed for three globally relevant deltas—the Mekong, the Ganges–Brahmaputra–Meghna and the Amazon. These are meant to serve as a preliminary “library” of potential indicators to be used for future vulnerability assessments. Based on the reviewed studies, we identified disparities in the availability of indicators to populate some of the vulnerability domains of the proposed framework, as comprehensive social–ecological assessments were seldom implemented in the past. Even in assessments explicitly aiming to capture both the social and the ecological system, there were many more indicators for social susceptibility and coping/adaptive capacities as compared to those relevant for characterizing ecosystem susceptibility or robustness. Moreover, there is a lack of multi-hazard approaches accounting for the specific vulnerability profile of sub-delta areas. We advocate for more comprehensive, truly social–ecological assessments which respond to multi-hazard settings and recognize within-delta differences in vulnerability and risk. Such assessments could make use of the proposed framework and list of indicators as a starting point and amend it with new indicators that would allow capturing the complexity as well as the multi-hazard exposure in a typical delta SES.     

Building the role of local government authorities towards the achievement of the human right to water in rural Tanzania

In recent decades, many changes have occurred in the approach to financing and operating water services in developing countries. The demand‐responsive approach is now adopted in many countries in a context of donor‐supported decentralization processes, which gives more responsibility to end users. However, the government's responsibility at different levels is enforced by the international recognition of the human right to water. This paper examines specific actions that build the role of local government authorities in this scenario. A collaboration between an international NGO and a rural district in Tanzania from 2006 to 2009 is used as an action research case study that is representative of local capacity‐building needs in decentralized contexts and rural areas. Three main challenges were detected: i) lack of reliable information; ii) poor allocation of resources in terms of equity; and iii) lack of long‐term community management support from the district. Two mechanisms were established: i) water point mapping as a tool for information and planning; and ii) a District Water and Sanitation Unit Support (DWUS) for community management. The results show how the framework provided by the goal of human right to water helps to define useful strategies for equity‐oriented planning and post‐project support at the local level.     

Nonparametric functional data estimation applied to ozone data: prediction and extreme value analysis

The study of extreme values and prediction of ozone data is an important topic of research when dealing with environmental problems. Classical extreme value theory is usually used in air-pollution studies. It consists in fitting a parametric generalised extreme value (GEV) distribution to a data set of extreme values, and using the estimated distribution to compute return levels and other quantities of interest. Here, we propose to estimate these values using nonparametric functional data methods. Functional data analysis is a relatively new statistical methodology that generally deals with data consisting of curves or multi-dimensional variables. In this paper, we use this technique, jointly with nonparametric curve estimation, to provide alternatives to the usual parametric statistical tools. The nonparametric estimators are applied to real samples of maximum ozone values obtained from several monitoring stations belonging to the Automatic Urban and Rural Network (AURN) in the UK. The results show that nonparametric estimators work satisfactorily, outperforming the behaviour of classical parametric estimators. Functional data analysis is also used to predict stratospheric ozone concentrations. We show an application, using the data set of mean monthly ozone concentrations in Arosa, Switzerland, and the results are compared with those obtained by classical time series (ARIMA) analysis.     

Assessing spatial variability of SO2 field as detected by an air quality network using Self-Organizing Maps,cluster, and Principal Component Analysis

In Bilbao (Spain), an air quality network measures sulphur dioxide levels at 4 locations. The objective of this paper is to develop a practical methodology to identify redundant sensors and evaluate a network's capability to correctly follow and represent SO₂ fields in Bilbao, in the frame of a continuous network optimization process.The methodology is developed and tested at this particular location, but it is general enough to be useable at other places as well, since it is not tied neither to the particular geographical characteristics of the place nor to the phenomenology of the air quality over the area.To assess the spatial variability of SO₂ measured at 4 locations in the area, three different techniques have been used: Self-Organizing Maps (SOMs), cluster analysis (CA) and Principal Component Analysis (PCA). The results show that the three techniques yield the same results, but the information obtained via PCA can be helpful not only for that purpose but also to throw light on the major mechanisms involved. This might be used in future network optimization stages. The main advantage of cluster analysis and SOMs is that they provide readily interpretable results. All the calculations have been carried out using the freely available software R.     

Developing sinks for CO<Subscript>2</Subscript> through forestation of temperate coastal barriers: an environmental business

Since the 1940s, some sectors of the sand dune barriers of Buenos Aires Province have been forested to fix the sand in the neighborhoods of resort villages. Man took advantage of the maritime climate and the shallow groundwater to introduce pine forests. Today, these forests reach more than 20 m in height and have developed soils of more than 0.05 m in thickness on former arid sands. Field data were referred to Landsat (TM) composite and Normalized Difference of Vegetation Index, NDVI, images to calculate forest density and covered area. Considering published tables of wood density for each species, the amount of total carbon storage was estimated on 318 t C ha^-1 (Mg=10⁶ g) in biomass and 86 t C ha^-1 in soils. The three areas analyzed at Miramar, Necochea and Claromecó have captured 658,868 t of carbon in the last 50 years. It is estimated that 150,000,000 t C could be sequestered within temperate dune barriers of Argentina, Uruguay and Brazil. Besides this ecological point of view, there is an important socio-economic factor that cannot be excluded.Presented at and revised subsequent to the 4th LOICZ Open Science Meeting, Bahía Blanca, Argentina. October 1999.     

Spatial and seasonal dynamics of phosphorous and physicochemical variables in the Negro River Estuary (Argentina): a preliminary approach

Environmental Science and Pollution Research - Nutrient discharge into rivers and estuaries and the factors that control it need to be further understood to decrease the risk of harmful algae...     

Methodological Development of an Index of Coastal Water Quality: Application in a Tourist Area

With the aim of obtaining an index of coastal water quality, a methodological procedure based on numerical classification and discriminant analysis is presented. The procedure was applied to nutrient data (ammonia, nitrite, nitrate, and phosphate) analyzed along the coastal waters of a Spanish tourist area. Using numerical classification, three levels of nutrient loading were revealed, characterizing oligotrophic, mesotrophic, and potentially eutrophic waters. Discriminant analysis was shown to be an effective methodological tool in the discrimination between trophic groups. For every group, the discriminant procedure generated the centroids. The centroids representing oligotrophic and potentially eutrophic conditions were used to establish the two extremes of the continuum of mesotrophic conditions in these coastal waters: Standardizing values from -1 to 1, the centroids for oligotrophic and potentially eutrophic waters yielded an interval that defined the range of mesotrophic conditions. This interval is proposed as a water quality index. The ability of the coastal water quality index to successfully predict mesotrophic conditions was proved with random samples.     

Shell shape variation in populations of Mytilus chilensis (Hupe 1854) from southern Chile: a geometric morphometric approach

The pattern of shell shape variation in populations of the mussel, Mytilus chilensis (Hupe 1854) from Southern Chile was analyzed as a function of sample origin (cultivated vs. wild) and latitude, using standard tools of geometric morphometrics for landmark data. Additionally, posterior adductor muscle index (PAMI), Freeman condition index and shell thickness were measured in each sample. Highly significant differences in shell shape components were found among mussel populations. These differences are related to the origin of samples (expansion of the posterior adductor muscle scar, elongation of the lateral ligament and of the ventral umbo position in non-cultivated samples) and to latitude (more elongated shells and more extended posterior adductor muscle scar in most southern samples when compared with the northernmost ones). PAMI and shell thickness were statistically higher in wild population, and Freeman condition index was higher in cultivated shells. It is suggested that in wild populations of M. chilensis, the mussels may face higher predator pressures and other environmental stress factors. Consequently, individuals may be using higher energy fraction to reinforce shells and to promote adductor muscle growth at the expense of somatic growth. In contrast, individuals found in calm aquaculture environments are relatively protected from predators and use most of their assimilated energy in somatic growth. In turn, this growth depends on changes that covariate with shell morphology.     

Environmental assessment of dehydrated alfalfa production in Spain

Alfalfa is the major forage crop produced in temperate regions worlwide. Although this crop is currently used mainly for producing high-value livestock feed, its application for bioenergy production is a recent focus of interest. Even though it is not mandatory, alfalfa is normally dried in order to improve the quality of the final product. In this study, Life Cycle Assessment (LCA) was used to quantify the environmental impacts linked to alfalfa production in the major cultivation zone in Spain (Ebro Valley), including field activities, dehydration and transport to farms for livestock feeding. In addition, the identification of the most relevant processes contributing to the environmental impact and the potential improvements actions were also defined as objectives. Inventory data were obtained mainly from interviews with farmers complemented with published literature and comments from experts.LCA results were obtained for global warming, acidification, eutrophication, photochemical oxidant formation, land use, non-renewable cumulative energy demand and human, terrestrial and aquatic ecotoxicities. Within the life cycle of alfalfa, the dehydration process, production of phosphate fertilizer, application of nitrogen fertilizers and pesticides, water consumption and final transport to the consumer (by road and ship) were identified as hot spots. Based on these, some improvement measures were proposed and evaluated: (i) reduction of the moisture content of alfalfa and the use of a higher percentage of biomass for combustion in the dehydration process, (ii) no application of nitrogen fertilizer in maintenance years and (iii) use of more efficient trucks for transport. Their implementation would produce significant reduction of eutrophication, global warming, acidification, non-renewable cumulative energy demand and, to a lesser extent, photochemical oxidation formation and human toxicity impacts.