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METHODS FOR ASSESSING ECONOMIC, ENVIRONMENTAL AND SOCIAL IMPACTS OF AQUACULTURE TECHNOLOGIES: ADOPTION OF INTEGRATED AGRICULTURE-AQUACULTURE IN MALAWI
Abstract
There is a growing demand for assessment of economic, environmental and social impacts of new food-related technologies, including the impacts of new methods for aquaculture management. This paper presents a new “minimum-data Tradeoff Analysis” (TOA-MD) model that can be applied to assess economic, environmental and social impacts in a wide array of agricultural systems that incorporate aquaculture, crops, and livestock (Antle 2011; Antle and Valdivia 2010). This model is widely applicable to assess impacts because it utilizes a generic model structure that can be parameterized with data available from a variety of sources, including farm surveys, experimental data, simulated data from bio-physical simulation models, and expert judgment. A key feature of this model is that it takes into account the fact that farmers systematically selected themselves into adopting and non-adopting groups. Analysis shows that this selection must be taken into account to obtain accurate estimates of impact.
To illustrate the use of the TOA-MD model, we use it to implement an impact assessment of integrated agriculture-aquaculture (IAA) systems in southern Malawi developed by the World Fish Center, using a WorldFish farm survey data collected in 2004, together with data from other public sources. We use the TOA-MD model to demonstrate how it is possible to use available data to move a conventional economic impact assessment “along the impact assessment pathway” to estimate adoption rates in the relevant populations, and to quantify impacts on distributional outcomes such as poverty, environmental impacts such as soil and water quality, and social and health- related outcomes such as nutrition or gender impacts. The analysis predicts an adoption rate of about 44%. In two districts, there is a substantial increase in protein consumption associated with the adoption of IAA and substantial reductions in poverty, whereas in others the effects are smaller.
... These were beans, coffee, pigeon peas, sorghum and millet, and dairy. Economic analyses were performed using the Trade-off Ana lysis Multi-Dimensional (TOA-MD) impact as sess ment tool , 2011, Antle 2011, Claessens et al. 2012). ...
... These were beans, coffee, pigeon peas, sorghum and millet, and dairy. Economic analyses were performed using the Trade-off Ana lysis Multi-Dimensional (TOA-MD) impact as sess ment tool , 2011, Antle 2011, Claessens et al. 2012). ...
... For the analysis of impacts of climate change on current agricultural systems we used the TOA-MD. The TOA-MD model is a parsimonious, generic model for analysis of technology adoption and impact assessment, and ecosystem services analysis (Antle 2011). In this model, households are presented with a simple binary choice: they can operate with a current or base production System 1 (current climate, current technology), or they can switch to an alternative system (Claessens et al. 2012). ...
Natural and artificial (e.g. agricultural) ecosystems confer benefits in the form of provisioning, regulating, cultural and habitat/supporting goods and services. Degradation of eco systems by natural and anthropogenic drivers compromises their ability to provide these goods and services. In Kenya, as in other regions worldwide, climate change and variability are driving weather pattern changes, and causing seasonal shifts. Such changing weather patterns and seasonal shifts act as stresses on agricultural ecosystems, compromising the production of agricultural goods and services, and leading to reduced farm returns, reduced household incomes, and increase in poverty levels. Using the example of Embu County in central Kenya as a case study, this study seeks to assess the impacts of climate change on household welfare (net farm returns, per capita incomes, and poverty) in current agricultural production systems. To address this objective we conducted a multi-disciplinary study involving climatologists, crop modellers and economic modellers. Primary data from 441 households were collected using a combination of stratified and multistage sampling. In climate modelling, 5 climate models were used to downscale future projected climate change scenarios for the mid-century timeframe of 2041-2070. Crop modelling for maize was done using DSSAT and APSIM crop models. Representative agricultural pathways were used to project the production of other non-modelled crops and dairy. Finally, economic analyses were done using the trade-off analysis multi-dimensional impact assessment tool. Results show that about 36 to 66% of the households in agro-ecological zones (AEZs) receiving limited rainfall are likely to lose from climate change. In addition, crop models indicate mixed results for net farm returns, per capita income and poverty levels in different AEZs, with poverty level declines being between 0.6 and 3.8% for APSIM, and between 0.7 and 11% for DSSAT. This therefore calls for adaptation, especially for households in AEZs likely to experience negative impacts from climate change.
... For the analysis of climate change economic impact and adaptation strategies, this study used the Tradeoff Analysis model for Multi-Dimensional Impact Assessment (TOA-MD). This model has been used for the analysis of technology adoption (Antle and Validivia, 2006;Nalukenge et al., 2006;Stoorvogel, 2006, 2008;Immerzeel et al., 2008;Claessens et al., 2008;Antle, 2011b;Antle and Valdivia, 2011) provides an overview of the methodology, and present a validation of the TOA-MD approach against more complex, spatially-explicit models of semi-subsistence agricultural systems. ...
... In the TOA-MD model, farmers are assumed to be economically rational. This meant that thery make decisions based on maximizing expected value and presented with a simple binary choice: they can continue to operate with production System 1, or they can switch to an alternative System 2 (Antle and Valdivia, 2011). The logic of the analysis is summarized as follows: farmers are initially operating a base technology with a base climate. ...
... If some farmers are worse off economically under the perturbed climate, they are said to be vulnerable to climate change. Overall vulnerability can be measured by the proportion of farmers made worse off, and can also be defined relative to some threshold, such as the poverty line, in which case it says how many more households are put into poverty by climate change (Antle and Valdivia, 2011). ...
The aim of this research is to examine the impact of climate change in maize farmers’ livelihood in Zambezi region, Namibia and benefit of adaptation. Trade-off analysis–multidimensional (TOA-MD) model was presented as a method for evaluation with a combination of simulated baseline production and future simulated yield using Decision Support Systems for Agro-technology Transfer (DSSAT) in maize production system, under five different climate scenarios of Global Circulation Models (GCMs). Even though the magnitude and the impact of different GCMs differs, the projections shows to have a negative economic impact with the highest going up to 76% and lowest to be around 46% loss without any adaption strategies in the Zambezi region. Adaptation strategies and some policy options were tested. The analysis suggests that the introduction of an irrigation system may be sufficient to offset the negative effects of climate change. Since various assumptions and uncertainties are associated with using the proposed approach and results should be interpreted with caution. Despite these limitations, the methodology presented in this study shows the potential to yield new insights into the way that realistic adaptation strategies could improve the livelihoods of smallholder farmers. To safeguard the limited productive assets of rural Namibian’s, the study suggested policy aim to target pro-poor disaster management and other adoption mechanism is very important. Apart from protecting productive resources of the rural population, policy should target the diversification of the rural economic environment and strengthen rural-urban linkages.
... These were beans, coffee, pigeon peas, sorghum and millet, and dairy. Economic analyses were performed using the Trade-off Ana lysis Multi-Dimensional (TOA-MD) impact as sess ment tool , 2011, Antle 2011, Claessens et al. 2012). ...
... These were beans, coffee, pigeon peas, sorghum and millet, and dairy. Economic analyses were performed using the Trade-off Ana lysis Multi-Dimensional (TOA-MD) impact as sess ment tool , 2011, Antle 2011, Claessens et al. 2012). ...
... For the analysis of impacts of climate change on current agricultural systems we used the TOA-MD. The TOA-MD model is a parsimonious, generic model for analysis of technology adoption and impact assessment, and ecosystem services analysis (Antle 2011). In this model, households are presented with a simple binary choice: they can operate with a current or base production System 1 (current climate, current technology), or they can switch to an alternative system (Claessens et al. 2012). ...
There is growing evidence that climate change poses significant risks to agriculture in many parts of the world, especially to the small-scale farmers in Eastern Africa region because of its high dependence on rainfed agriculture which is highly sensitive to climate variability and change. Despite the availability of overwhelming evidence in support of large negative impacts of climate change on agriculture, uncertainty prevails over the precise nature of projected changes in climate and their effects on agricultural systems, especially at point scale levels, making it difficult to plan and develop appropriate adaptation strategies, programs, and technologies. Under the global Agricultural Model Intercomparison and Improvement Project (AgMIP), teams of researchers from four Eastern Africa countries viz., Ethiopia, Kenya, Tanzania and Uganda have initiated studies to make a comprehensive assessment of climate change impacts on smallholder agriculture and this paper examines the farm level impacts of climate change on maize productivity in Embu county, Kenya. Agriculture in this county is predominantly characterized as smallholder, with farm sizes ranging from 0.9 to 2.5 hectares, dedicated to subsistence with limited marketable surpluses. Maize is the most important staple food crop and is grown by almost all farmers under diverse conditions across the county. The average annual rainfall varies from more than 1200 mm to less than 600 mm and the average annual temperatures varies from about 200C at an altitude of 1500 m to about 240C at 700 m. Most farmers use labor intensive traditional farming methods that include use of local varieties and very low levels of inputs such as fertilizers. Mean grain yields of maize are generally low and vary from 1 t/ha in high potential areas to less than 0.5 t/ha in low potential areas. Crop yields under current and future climates were simulated using crop models APSIM and DSSAT by setting model parameters that reflect farmer management practices and using observed climate data and generated future climates for A2 and B1 emission scenarios based on the Hadcm3 GCM for the mid-century period (2040-2069). On an average, the temperature increased by about 1.890C under the A2 scenario and by about 1.190C under B1 scenario. The models APSIM and DSSAT differed in simulating maize temperature response. While DSSAT predicted a 15% decline in yields under all test environments and management conditions, APSIM predicted an increase in yield in some environments especially those under low input systems with less than 25 kg N/ha. Further analysis of these changes in maize yield with the Tradeoff Analysis Minimum Data model (TOA-MD) has indicated that with current technology and a changed climate--with increased temperature and rainfall--a mean of 51% of all farmers in all environments will be better off. However, there are differences across environments and across management practices. The paper discusses these differences and their implications for climate change adaptation.
... In this study, we use the Tradeoff Analysis for Multi-Dimensional Impact Assessment (TOA-MD) model to evaluate the impact of integrated aquaculture-agriculture (IAA) adoption in Malawi. The TOA-MD model is a multi-dimensional impact assessment model recently developed by Antle and Valdivia (2011). The model uses a statistical description of a farm population to simulate adoption and impacts of a new set of technologies or practices. ...
... To date, several impact assessments of IAA systems in Malawi have been carried out (Dey et al. 2006(Dey et al. , 2010FAO 2008;Russell et al. 2008). These previous assessments focused on analyzing determinants of adoption, evaluating aggregate economic impacts, and estimating a rate of return on investment using economic assessment approaches (Antle and Valdivia 2011). Previous studies also used qualitative and descriptive statistics approaches to assess non-economic impacts such as nutrition by examining impacts on a stratified random sample of farms with and without aquaculture production. ...
... Previous studies also used qualitative and descriptive statistics approaches to assess non-economic impacts such as nutrition by examining impacts on a stratified random sample of farms with and without aquaculture production. These studies failed to provide an estimate of overall adoption rate, economic impacts, and non-economic impacts of IAA adoption in the target population of farms; that is, those farms that have the potential to adopt the IAA technology (Antle and Valdivia 2011). Furthermore, since these impact assessments were carried out within a few years of project termination, the findings are representative only for short-term project impacts, not long-term impacts on the farm population. ...
... Adoption rates are often difficult to predict with other models, mostly due to unavailability of data (Dey et al., 2006;Antle, 2011;Jahan et al., 2013). The TOA-MD is less demanding in terms of data needs and can be used with less complex data from surveys, experiments and institutional data bases, and is amenable to expert judgment (Antle and Valdivia, 2011). For this study, the TOA-MD model was found suited to the sources and nature of the data being used: for example, the subsistence farm settings where technologies get disseminated and the level and extent of adoption varying greatly among farms due to factors that determine adoption and intensity of adoption. ...
... The TOA-MD model utilizes means, variances and correlations of outcome variables from the available data. Specifically, the main variables utilized by the TOA-MD model include: (1) Population means and variances of production; (2) Output prices; (3) Cost of production of the activities in the different systems (the activities may be a combination of crop, livestock, and aquaculture or one or two of the three); (4) Population means and variances of (environmental, social and economic) outcomes associated with each system; (5) Correlations between system returns and outcomes; (6) Population means and variances of farm household characteristics (farm size, pond size, household size, off-farm income, etc.) (Antle and Valdivia, 2011). For this paper, the economic outcomes, namely household income and poverty level were used in the analysis. ...
... Selected adaptations were assessed with the Tradeoff Analysis Model for Multi-Dimensional Impact Assessment (TOA-MD Model) (Antle & Valdivia 2011). This is a unique simulation tool that can use the socioeconomic data sets collected earlier in the overall study project and combine them further with macroeconomic data sets of farms and then project the current and future viability of specific interventions. ...
In recent decades, the global demand for food and biomass has been increasing, while natural resources continue to deplete and are further stressed by the impacts of climate change. Additionally, rising energy and input costs have pushed agricultural production to its limits, placing farming communities in an increasingly precarious position. This volume presents a collection of papers that challenge us to reconsider existing agri-food and farming systems from a local perspective, and to explore alternative, more sustainable production approaches.
The volume is structured around four key themes. The first theme scrutinizes agricultural modernization, with a particular focus on technological innovations and monoculture-based agricultural production. The second theme centres on the political-economic dynamics and local challenges. The third theme assesses participatory methods for knowledge production on processes of agrarian change across various regional settings. Finally, the fourth theme explores alternative production systems that are socially and ecologically sustainable, offering potential solutions for reshaping agricultural systems under pressure.
... There are very few economic models that can be utilized specifically for policy evaluations. The socioeconomic viability of the recommendations is relevant to the impact of the research and interventions, as the economic rationality influences decisions about the adoption or non-adoption of the proposed adaptations at the farm level [21]. ...
Water is the most important resource; it is utilized largely in agricultural production and is fundamental to ensuring global food security. This study aims to assess sustainable water management interventions and their impact on the farm economy. To increase water productivity, the most important adaptations that have been proposed are high-efficiency irrigation systems, drought-resistant varieties, the substitution of water-intensive crops with less water-demanding crops, the mulching of soil, zero tillage, and all on-farm operations that can save water, especially ground water. The recent analysis utilized farm survey data from 469 representative farmers along with secondary statistics. The data were collected via a multi-stage sampling technique to ensure the availability of representative farm populations based on a comprehensive site selection criterion. The TOA-MD model estimates the adoption rate of a proposed adaptation based on net farm returns. The impact of high-efficiency irrigation systems and the substitution of high delta crops for low delta crops had a positive impact on net farm returns and per capita income, and a negative impact on farm poverty in the study area. It is recommended that policymakers consult farmer representatives about agricultural and water-related issues so that all the policies can be implemented properly.
... The poverty line was set to USD 1.25/person/day (USD 1 = RS 103) (RS: Pakistani rupee, it can also be written as PKR) in the analysis according to international standards, which were to check the vulnerability level of households with respect to climatic changes [80]. For climate change impact assessment (CC-IA) analysis, all the prices of inputs/outputs were site-specific according to the production system(s), and net returns were evaluated accordingly. ...
There are numerous anticipated effects of climate change (CC) on agriculture in the developing and the developed world. Pakistan is among the top ten most prone nations to CC in the world. The objective of this analysis was to quantify the economic impacts of CC on the agricultural production system and to quantify the impacts of suggested adaptation strategies at the farm level. The study was conducted in the Punjab province's rice-wheat cropping system. For this purpose, climate modeling was carried out by using two representative concentration pathways (RCPs), i.e., RCPs 4.5 and 8.5, and five global circulation models (GCMs). The crop modeling was carried out by using the Agricultural Production Systems Simulator (APSIM) and the Decision Support System for Agrotechnology Transfer (DSSAT) crop simulation models (CSMs), which were tested on the cross-sectional data of 217 farm households collected from the seven strata in the study area. The socioeconomic impacts were calculated using the Multidimensional Impact Assessment Tradeoff Analysis Model (TOA-MD). The results revealed that CC's net economic impact using both RCPs and CSMs was negative. In both CSMs, the poverty status was higher in RCP 8.5 than in RCP 4.5. The adaptation package showed positive results in poverty reduction and improvement in the livelihood conditions of the agricultural households. The adoption rate for DSSAT was about 78%, and for APSIM, it was about 68%. The adaptation benefits observed in DSSAT were higher than in APSIM. The results showed that the suggested adaptations could have a significant impact on the resilience of the atmospheric changes. Therefore, without these adaptation measures, i.e., increase in sowing density, improved cultivars, increase in nitrogen use, and fertigation, there would be negative impacts of CC that would capitalize on livelihood and food security in the study area.
... The poverty line was set to USD 1.25/person/day (USD 1 = RS 103) (RS: Pakistani rupee, it can also be written as PKR) in the analysis according to international standards, which were to check the vulnerability level of households with respect to climatic changes [80]. For climate change impact assessment (CC-IA) analysis, all the prices of inputs/outputs were site-specific according to the production system(s), and net returns were evaluated accordingly. ...
The objective of this study was to measure the impacts of climate change sensitivity and how it is affecting economic conditions of farmers in current rice wheat cropping system. Cross-sectional data of 210 farmers from the seven different strata were collected from Punjab, Pakistan. Climate data of baseline (1980-2010) and future (2039-2040) under representative concentration pathways 4.5 and 8.5 for five global circulation models were collected from secondary sources. The climate scenarios were used in two crop simulation models, i.e., DSSAT and APSIM. Tradeoff Analysis Model for Multidimensional Impact Assessment (TOA-MD) was used for the economic analysis. The crop modeling results of the study using different GCMs and RCPs show that there was negative impact of climate change on the yields of both major crops i.e., rice and wheat. The comparison of both CSMs given the insight that the percent losses were higher in APSIM as compared to DSSAT. The economic analysis endorsed the negative impacts of climate change on farming community. The major economic indicators (net returns, per capita income and poverty) of the study area expressed the declining trend in both RCPs (4.5 and 8.5) and all five GSMs. The observed household vulnerability to climate change percentage was more intense in RCP 8.5 as compared to RCP 4.5, however, among GCMs the figures shown higher vulnerability in hot dry climate conditions and lower in cool wet. The poverty of the study area increased with climate change and it was more prominent while using RCP 8.5 as compared with RCP 4.5. The highest increase in poverty was observed using APSIM crop model for hot-dry conditions. The study concluded that to ensure food security, poverty alleviation and to minimize climatic risks there is the need to update agronomic practices and develop adaptation strategies.
... Generally, system 1 is defined as production system with base temperature and technology while system 2 is defined as system with base technology and changed climate. Vulnerability can be defined in terms of the poverty line, showing how many more households are put into poverty by climate change (Antle and Valdivia 2011). ...
This study involves the climate change impact assessment of wheat producers in Khyber Pakhtunkhwa, Pakistan. An extensive farm survey of 150 farms was designed. From study area, three districts, namely, Chitral, D.I. Khan, and Peshawar, were selected through multistage sampling process. Yield simulation from Crop model DSSAT (Decision Support System for Agro Technology Transfer) was used for socio-economic impact assessment. Future climate scenarios were generated by selecting five GCMs from latest CMIP5 family with two RCPs 4.5 and 8.5, at two carbon concentrations of 499 ppm and 571 ppm, respectively. Yield simulations were analyzed for each GCM. Results of crop model revealed that wheat yield will increase in district Chitral, while in D.I. Khan and Peshawar, yields would be reduced due to climate change. For socio-economic impact assessment, TOA-MD (Trade-Off Analysis for Multi-Dimensional Impact Assessment) version 6 was used. Climate change impacts on poverty, net farm returns, and per capita income were calculated for different scenarios. The analysis was carried out on per-farm basis. The economic model results revealed that climate change has negative impact on wheat producers in D.I. Khan and Peshawar while making wheat producers better off in Chitral. The number of losers ranged from 54 to 66.21% and 50 to 61.99% in D.I. Khan and Peshawar, respectively. Losers are the farmers who would be economically worse off under perturbed climate. With current climate, the observed poverty rate would be 34 to 49 in D.I. Khan while 21.26 to 34.03 in Peshawar. The study recommended need for adaptation strategies to overcome the vulnerabilities of climate change.
... [13] ...
The coconut fiber is produced in large quantities in Brazil, even though very small quantities are being used by some industries, mainly cordage mats and handicrafts. An alternative usage would be the use of these fibers in biosorption of heavy metals from aqueous solutions. This present study aimed to evaluate the potentiality of cadmium biosorption by coconut fiber. The coconut fibers were used at kinetic analysis, influence of pH and adsorption isotherms were also carried out. It can be concluded that there is great potential for the use of coconut fiber, and the optimum pH for adsorption was around 5.0. The adsorption kinetics is fast and equilibrium occurs within 120 min. The Langmuir isotherm was considered the most suitable to describe the experimental data.
... An example is the production of tilapia in fish cages that presents a profitability rate of 22.57% for a production cycle of 180 days in the city of IlhaSolteira-SP [12]. Another example is the integrated agriculture-aquaculture which substantially increased protein intake and reduced the rate of poverty among small farmers in Malawi, Africa [13]. ...
Fish farming is a strategic activity for both the economy and food security of the Tocantins state. Nowadays, there are about eighty small fish farmers in the region of Divinópolis in Tocantins state. The technological level of fish farmers is lowand it was found that only 30% of farmers could ever get to the point of selling fish. Therefore, the objective of this paper is to investigate which socioeconomic factors have influence on the fact of fish farmers in the region of Divinópolis and in Tocantins state reach a level of efficiency in production enough that the fish can be good for sale in the local market. To estimate this relation the logit model was chosen, with methodology based on the empirical model used in Musaba and Namukwambi. Following the production of fish farms in the Western of Tocantins state, the collect of the data, during 2012, were conduct with interviews of 30 fish farms, visiting them in their homes and applying a questionnaire. Through the use of econometric models of probability for limited dependent variables, it was found that factors such as participation in federal programs to transfer income, total area of water and production in ponds are key factors in determining the likelihood of producer to sell fish.
This article develops the conceptual and empirical foundations for a parsimonious approach to assessment of economic, environmental and social impacts of agricultural technologies. Parsimony is achieved by shifting the focus from the farm-level data and models used in most assessments, to the outcome distributions that characterize a population of farms adopting a new production system. A parsimonious "minimum-data" model is derived using the moments of outcome distributions that can be parameterized using population-level data. A case study is used to compare an impact assessment based on a parsimonious model to the results of a complex farm-level simulation model.
Sustainable agricultural intensification is an urgent challenge for Sub-Saharan Africa. One potential solution is to rely on local farmers' knowledge for improved management of diverse on-farm resources and integration among various farm enterprises. In this article, we analyze the farm-level impact of one recent example, namely the integrated aquaculture-agriculture (IAA) technologies that have been developed and disseminated in a participatory manner in Malawi. Based on a 2004 survey of 315 respondents (166 adopters and 149 nonadopters), we test the hypothesis that adoption of IAA is associated with improved farm productivity and more efficient use of resources. Estimating a technical inefficiency function shows that IAA farms were significantly more efficient compared to nonadopters. IAA farms also had higher total factor productivity, higher farm income per hectare, and higher returns to family labor. Copyright (c) 2010 International Association of Agricultural Economists.
This monograph is a result of a 3-year project to produce a decision-support toolkit with supporting databases and case studies to help researchers, planners and extension agents working on freshwater pond aquaculture. The purpose of the work was to provide tools and information to help practitioners identify places and conditions where pond aquaculture can benefit the poor, both as producers and as consumers of fish. This monograph is the case study for Malawi. Written in three parts, it describes the historical background, practices, stakeholder profiles, production levels, economic and institutional environment, policy issues, and prospects for aquaculture in the country. First, it documents the history and current status of the aquaculture in the country. Second, it assesses the technologies and approaches that either succeeded or failed to foster aquaculture development and discusses why. Third, it identifies the key reasons for aquaculture adoption.
We argue that to support agriculture-environmental policy decision making, stakeholders need 'quantitative back-of-the-envelope' analysis that is timely and sufficiently accurate to make informed decisions. We apply this concept to the analysis of the supply of ecosystem services from agriculture. We present a spatially explicit production model and show how it can be used to derive the supply of ecosystem services in a region. This model shows that the supply of ecosystem services can be derived from the spatial distribution of opportunity cost of providing those services. We then show how this conceptual model can be used to develop a minimum-data (MD) approach to the analysis of the supply of ecosystem services from agriculture that can be implemented with the kinds of secondary data that are available in most parts of the world. We apply the MD approach to simulate the supply of carbon that could be sequestered in agricultural soils in the dryland grain-producing region of Montana. We find that the supply curve derived from the MD approach can approximate the supply curve obtained from a more elaborate model based on site-specific data, and can do so with sufficient accuracy for policy analysis. Copyright Australian Agricultural and Resource Economics Society Inc. and Blackwell Publishing Ltd 2006.
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