 So Stefania, please confirm if you can see my presentation. Absolutely, yes. OK, so before we kickstart the formal training and dive deep into the methodology of STG241 and start disentangling its intricacies step by step, in this very first presentation, I will give you a bird-eye view of the STG indicator under FAO mandate, particularly highlighting the progress that we have made until so far, both on the methodological and capacity development fronts. During the course of the presentation, I will also let you know about our future plans for capacity development, that is technical assistance and training of the country officials and respective institutions, and support to data collection and reporting efforts by the countries to facilitate the global and regional monitoring of the STG indicators under our custodian chip. So the learning objectives for this session are, I will introduce you to the STG indicator of under FAO mandate, walk you through the work undertaken by FAO so far on STGs, as I mentioned, both on the methodological capacity development and support to data collection and reporting. I will provide you with the necessary means and ways that is links to the websites, et cetera, where you can find information on the FAO STGs. And lastly, to introduce you to our potential future lines of work that will maximize data reporting on the STGs. So let me start by giving you an overarching or holistic overview of the global indicator framework and the process adopted by United Nations for putting in place at the national region and global level. The global indicator framework comprises of 231 unique indicators and was endorsed by the United Nations General Assembly in July 2017. Now in order to oversee and manage this process, United Nations Statistical Commission was made responsible for development and implementation of STG monitoring framework. And in addition, an interagency and expert group on sustainable development goals, that is IAEG STG, was constituted to prepare initial proposals on the methodology and to oversee this work until 2030. Now the IAEG STG has 28 countries as members, representing their respective region. An important point to note is that the process with IAEG STG has been fully led by countries with international organizations like FAO, only serving as observers. On top of this, for each STG indicator, a custodian UN agency was identified and was assigned the following responsibilities. First one to lead methodological development and documentation of the indicators. Second one to support statistical capacity of the countries to generate and disseminate national data. Third one to collect data from national sources, ensure its comparability and consistency and disseminate it at a global level. And lastly to contribute to monitoring the progress at the global, regional and national levels. For example, storylines and data for annual STG reports or agency flagship publications. Now the global indicators are a core set of matrices that all countries are invited to monitor. The key point to remember is if national data are not produced, regional and global indicators cannot be produced. Another important point to be noted is that the global indicators can be complimented but not replaced. And this is very important. So it can be complimented but not replaced with national or regional indicators. This is as paragraph, as per paragraph 75 of the United Nations resolution on the 2030 agenda. And lastly, global monitoring is based on data produced by the countries and the source having a key coordinating role at the national level. So even if the estimates for the indicators are produced by international organizations, prior consultation or validation and its triangulation is needed with countries before its publication. We are part of the Stodian United Nations Agency for 21 STG indicators and a contributing agency for five others, primarily related to food and agriculture space. In this capacity, us as FAO is supporting countries' efforts in monitoring the 2030 agenda. The 21 STG indicator are spread across the following six goals that include goal two, food security, nutrition, and sustainable agriculture. Goal five on gender equality. Goal six on use of water. Goal 12 on sustainable consumption and production. Goal 14 on oceans and goal 15 on life on land. Now, as I mentioned to you earlier, FAO key areas of work on STG indicator involve methodological development, statistical capacity development, global data collection and dissemination, global progress report, and voluntary review submitted by the countries to FAO. And lastly, the communication and advocacy part of the STG indicators. In terms of FAO work on STG indicators, back in 2015 of the 21 STG indicators that we are custodian agency for 13 World Tier 3 indicators, which means that neither international methodology nor data existed on these indicators. This meant that FAO had to develop new methodological proposals in consultation with countries and compile it with the IAEG STG criteria for tier 3 reclassification. This was the case for numerous indicators, which I'm not going to go through the list, but just to exemplify, 231, 232, 241, and so on. For some STG indicators, FAO also had to develop new international definitions for the key concepts. This was the case with indicator 231 and 232, whereby we came up with a definition of small scale food producers and the definition of rural and urban areas, which is still under process of development. And once developed, it's going to be used for desegregation of many STGs that goes beyond the mandate of FAO. The work, of course, didn't stop at the methodological development stage, but continued at fast pace, where in addition for all indicators under our custodianship, we developed improved data collection tools, guidelines, and supporting documents and materials to facilitate countries reporting on the newly developed, approved, and endorsed methodologies. Now this, like, rises the tier 3 of the 21 STG indicators, with red being tier 3, which I already mentioned, nor methodology, neither the data existed. Yellow tier 2, for which methodology exists, but no data collection is available. And tier 3 and green tier 1, which means that both methodology and data exist and is regularly reported by the countries to FAO. Now, as of November 2015, 13 indicators were tier 3, 5 were tier 2, and only 3 were tier 1. Meaning a lot of our work back then was focused on methodological development of the indicators. Hence, given the intensity of the work involved, we as FAO realigned our work programs both strategically and operationally to support the methodological development of the tier 3 indicators. With the four years of steadfast technical work of cross-functional teams responsible for respective STGs at FAO headquarters, while leveraging a participatory, consultative, and inclusive process, and most importantly, with support from officials like yourself and experts from countries, international organizations, private sector, and academia, we were able to establish methodological basis for all the remaining tier 3 indicators. As you may see in the matrix, as of now, currently none of the indicator remain as tier 3. In parallel with the methodological development, lots of efforts were targeted to support countries to enable them start adopting, implementing, and reporting data on the 21 SDG indicators. This included testing the methodologies in selected countries for finalizing the methodological proposals, development of e-learning courses, organization of country, regional, and global training workshops to build statistical capacity of the countries, and development of a comprehensive SDG data and communication portal that serve as a one-stop shop for all information on the 21 SDG indicators. Of course, our new vision of FAO for 2019 and 2030 is to scale up capacity development at a country level to maximize country reporting on the 21 SDGs. Now, in terms of the training workshop that I just spoke about on the previous slide, the very aim of this exercise was, including this very virtual training that is progressing now, has been to enlarge the pool of SDG monitoring experts at the country level, facilitate South-South cooperation amongst the country, especially developing ones, and to facilitate the testing of the new methods that were developed earlier in the process. In total, until so far, we have conducted 50-plus training workshops between 2017 and 2020 that were participated by experts from 150-plus countries belonging to different regions of the world. The ultimate focus was obviously to increase the number of data points, that is the number of reporting countries. Now, as I've mentioned, we have developed e-learning courses for most of the SDGs that we are custodian agency for. These e-learning courses have been published and available freely online on FAO SDG page, which I would provide you the link to. You can go there and take these courses at your own convenience to familiarize yourself with the methodology of these SDG indicators. Here are some more online courses that we have developed. And there are a few indicators for which we are still in process of developing e-learning courses and these will be available soon. One of the key feature of these e-learning courses of courses, once you take these courses, you will be awarded a course completion certificate. So all the information on the e-learning courses, as you can see in the bottom, of course, we will share all these presentations with you after the training workshop. So you can click there and you can access these online courses on the SDGs. And mind you, apart from the SDG indicators, there are many other subjects or disciplines for which we have developed these e-learning courses. So it is a very good resources for building capacities of the country staff. Going forward at FAO, we will continue to work closely in collaboration with our member states to pursue and implement our future activities, particularly from capacity development perspective that includes first further work on different methodological aspects of the indicators and its testing, that is data desegregation techniques, forecasting, now casting, and small area estimation to facilitate reporting on the SDGs. Secondly, to carry out data gap assessment at a national level and to further strengthen engagement with the national stakeholders, particularly on the alignment of national and regional indicators frameworks with SDG framework. We believe in doing so, it will reduce data collection and reporting burden on the countries that already face resource constraints. Thirdly, to support the development and implementation of new data collection tools, including alternative data sources and new means of data collection, especially amid COVID-19 pandemic, that has slowed down if not start the face-to-face data collection due to travel restrictions. Fourthly, to continue to provide capacity development through various means and ways, including through virtual trainings to support countries in the adoption, implementation, and reporting of FAO SDG indicators. And lastly, to provide assistance in improving the analysis and use of FAO SDG indicators in making decisions and policies at the national level. I will stop here. This was more of an introductory presentation to FAO SDG indicators. If you need more information, of course you can always write to us using the following email addresses. For overall overview of the 21 SDG indicators, I will suggest to you to write to the office of the chief statistician, the second email address that I've given. For SDG 2, for one related matters, please write to us on the first email address. So thank you very much. So if you don't have any questions at this stage, then I will rapidly move to my next presentation on SDG 2, for one. Yes, please go on. We don't have any question for now. Okay. So let me just open my presentation. So Sifanya, please confirm if you can see my presentation. Yes. Perfect. So this presentation, I will give you another view of SDG 2, for one, which is defined as proportion of agriculture area under productive and sustainable agriculture. So before I start the actual training, let me walk you through the objectives of this particular training that we are going to have over the course of three days. So today we will cover first and foremost, the SDG 2, for one methodology is compilation and interpretation. Secondly, to introduce the data collection tools and instruments developed for collecting and reporting data on the indicator. To discuss with you concrete plans to collect data on the indicator in the short, medium, and long term. This session we will cover tomorrow. And overall aim of this training, of course, is to assemble key stakeholders who are responsible for collecting and reporting the data and those responsible for data production so that we ensure evidence-based policies at the national and subnational level. So as highlighted in the previous presentation, at FAO we developed global public goods, methodology, standards, and classification in coordination, concentration, and close partnership with key stakeholders at all levels, especially countries. To give you some historical perspective, in early 2016, the FAO strategic program on sustainable agriculture and global strategy to improve agriculture and rural statistics joined forces to develop the pioneer methodology for the then tier three SDG indicator 2.4.1 to measure progress towards target 2.4. Now, as many of you may know, defining and measuring sustainable agriculture which the multidimensional concept is challenging as it is complex and country specific and thus despite several attempts in the past 50 years, since 1970s has never been done before. Given the multidimensionality of a sustainability concept, FAO initiated a global discussion to deliberate the fundamental questions. That is, what sustainability means in the context of agriculture? What are its fundamental building blocks? What are the economic, social, and environmental factors and are in turn affected by sustainability in agriculture? What's thematic aspects to keep as part of the framework of SDG 2.4.1 and what to let go of? How to strike a balance between the different sustainability issues faced by different regions and countries? How it will be measured and monitored consistently over time using a framework and data collection tools that are applicable and universal globally? So as you will find out in the course of this training, the methodology of SDG 2.4.1 has been designed in a very simple way. It involves simple, automatic rules to arrive at sustainability assessment of the country once the data has been collected, cleaned, processed, and analyzed. They proved an endorse methodology of SDG 2.4.1 is a result of long participatory and consultative process that I mentioned earlier. It involved discussion with and contribution of thematic or subject matter experts, statisticians, policy makers, and researchers from country institutions, both national statistical offices, Ministry of Agriculture's International Organization, civil society, private sector, and academia on various issues. The reason behind us involving key stakeholders with diverse background was to make this indicator owned by everyone, especially countries. The current methodology of SDG 2.4.1 embody this principle that is its universal policy relevant and practical. The way the methodology of this multi-dimensional indicator is designed, and you will see that as we progress during this training, it's very simple, logical, and practical. This was to ensure the sustainability of the indicator monitoring our time at a country level. Now, this training will be interactive. I will gradually, in a phased manner, cover different aspects of the indicator. That is the conceptual methodological basis, the scope and coverage, the data collection and analysis tools, and processes developed for reporting it to FAO. I will take breaks for question, if possible, and discussion throughout and try to answer the question that you may have. With this short background and expectation of active participation and constructive discussion, I will now formally begin the training. So, let me go to the previous slide. SDG goal to zero hunger has five targets. The target we are interested in today is target 2.4, which is written in extensive here. As you can see, like many other SDG targets, this target is very complex one. We highlighted in red some of the key aspects that needs to be captured as we try to measure progress toward this target. Sustainability, resilience, productivity, production, environmental consideration, that is climate change, soil quality, et cetera, all in one single target. Clearly, this would require an indicator that captures these different dimensions or aspects. The indicator that was submitted to the IAEG SDG and was approved in March, 2015, is proportion of agriculture area under productive and sustainable agriculture. This is a tier two indicator, which means that methodology of the indicator has now been approved and endorsed as an international standard. But however, data in general is not available or partially available at the country level. The formula that we propose to measure the indicator is very simple and straightforward. It's area under productive and sustainable agriculture divided by agriculture land area. So let us focus on the denominator first. The agriculture land area is a well-known and established concept. And it's usually collected by statistical bodies in the countries and compiled internationally via a questionnaire by FAO and it's disseminated through FAO stack, which is our data dissemination platform. The issue is obviously with the numerator of the formula. How do we measure area under productive and sustainable agriculture? What is clear from the description of the target, which I showed you on the previous slide, that we have to look at the sustainability across its dimensions, that is economic, social and environmental. Meaning the agriculture area under productive and sustainable agriculture will be the area of those farms that satisfy the sustainability criteria for all the sub indicators selected across the three dimensions of sustainability. Here are the steps that were used in the methodological development of SDG 241. We discussed and chose the scale for assessment for 241 and the choice made for 241 was to adopt a bottoms up approach whereby we selected farm or agricultural holding level that will in turn be aggregated to national level. The second step was to determine the scope of the activities of the holding to be covered by this indicator. The choice made for 241 was to cover crops and livestock activities. Then we reviewed the dimension that will be covered as part of SDG 241 and we decided to stick to the classical dimension of sustainability, that is economic, social and environmental. Let me add here that in the beginning of the process when we embarked on developing the methodology of SDG 241, we selected five dimension that included in addition to the three which I just mentioned, economic, social and environmental. Two other dimension which was governance and resilience. However, later during the process, it was decided to integrate resilience with economic, environmental and social dimension and to drop the governance dimension as we are exclusively focused on sustainability assessments at the farm level. We then zoomed inside the dimension into what we call teams or aspects. So in total, we have 11 teams within the framework of SDG 241. And then the sub indicators that are needed to measure progress within each team. So in total, we have 11 sub indicators, three in the economic dimension, three in the social dimension and five in the environmental dimension. Then of course one key aspect that we established was sustainability criteria or thresholds for each sub indicator at a farm level to classify the farm and its agriculture area that it owns or operates sustainability statuses that is to assign it red, yellow or green color which I will explain in the next slides. We also discussed the data collection instrument or vehicle for collecting and reporting data on the country on the indicator at a country level. We also decided on the periodicity or frequency of data collection and reporting the indicator that is set at three years. And finally the modality for reporting the indicator for which we developed both a dashboard which I will show you shortly. We are all the 11 sub indicators or themes are presented in one chart though separated by sustainability status and an aggregate SDG 241 indicator that can be calculated directly from the dashboard. The principles that were used to develop this indicator, first the policy relevance, action ability. We wanted to make sure that every sub indicator selected as part of the SDG 241 framework has a meaning for policy maker and thus provided information based on which informed decision can be taken to improve the situation. The indicator must be easily understood, the primarily the reason why it is selected and the result easily interpreted by policy makers. That is, is the agriculture sustainability increased or decreased and why what policy needs to be implemented to address these issues. Universality and comparability are fundamental. We are in an SDG process, a universal process. Thus we needed to make sure that the indicator is valid every year, everywhere. It must be relevant for all countries of the world both developing and developed. Majorability and cost effectiveness were very high in our mind in trying to find the right balance between an ideal indicator and the one which can be measured consistently with a reasonable cost. The affordability of the indicator in terms of data collection and reporting was our top priority. And lastly, minimum cross correlation amongst the sub indicators. So for this principle, we selected a limited set of themes and sub indicators. And in doing so efforts were made to reduce cross correlation among different sub indicators. High cross correlation means that two or more sub indicator capture the same sustainability theme. In this case, I mean, of course inclusion of one single sub indicator instead of several would be sufficient to adequately measure agriculture sustainability performances. All these choices of course and decision has had an implication for the choice of sub indicator for different dimension, the choice of sustainability criteria for each sub indicator and the level of sophistication and data collection. The measurement scope, because we are interested in assigning agriculture area sustainability status, the basic unit of measurement for us for this indicator is found survey. So as I mentioned, the basic, the measurement scope is agriculture holdings and the agriculture area that it owns and operates. So naturally we resorted to farm survey as the main tool for data collection. Now what's included as part of the scope of this indicator is given in this matrix. So on the left-hand side, you can see as to what aspect of production are part of the indicator scope. So intensive and extensive crops and livestock production systems, subsistence agriculture, food and non-food crops and livestock products, that is tobacco, cotton, sheep and bull, crops grown for fodder or for energy purposes. Aquaculture to the extent it takes place within the agriculture area as a secondary activity. Agroforestry or trees on farm, especially if it is grown on the agriculture land area of the holding. And common land is included within the scope if it is exclusively managed by the farm holding. What is out of scope is of course, common land not exclusively managed by the agriculture holding, nomadic testoralism, production from gardens, backyards and hobby farms, food harvested from the wild, holding focused exclusively on aquaculture or agroforestry, and lastly, forest and other wooded lands. The periodicity or reporting frequency of the indicator is set at three years. SCG 241 measure progress toward more productive and sustainable agriculture and countries are already collecting and reporting data on several of the indicator selected as part of the framework of 241. So for many of the sub indicators that we have selected, it is unlikely that the values of these indicators will change from one ear to another. So a three year data collection and reporting will enable countries to have at least three data points on the indicator before 2030 to make a trend to assess their performance over time and across countries. And of course, it will reduce data collection and reporting burden on the countries. Now the SCG 241, as I already mentioned, is designed to be collected through farm surveys and the result expressed as a national value. However, the methodology scale independent and can be adopted at any geographical level. Though any introduction or adoption of other stratification variables will have implication for the sample size and thus the cost of data collection. So to further enraged the analysis for national policy making, the indicator can be disaggregated at a sub national level according to the types of farms that is household, non household, type of production activities, crops, livestock mixed and whether the agriculture holding is using water to irrigate its agriculture area. Other stratification variables could also include the size of the farm or the gender of the owner or the holder of the agriculture holding. Now as mentioned earlier, the indicator is a multi-dimensional indicator. This light presents a table or a matrix that includes everything that we need to know about this indicator. Toward the extreme left, you can see the indicator cut across the three dimension of sustainability, economic, social and environmental. Within each dimension, we have a theme. For instance, as you can see within the economic dimension, we have three themes or aspects and corresponding three sub indicators that are used to measure the progress within each theme and thus in the dimension as a whole. Likewise, we have five themes in the environmental dimension and three in the social dimension. In total, we have 11 themes and 11 sub indicators to measure progress towards those themes. The decision was of course, in relation to measurability and cost effectiveness, the list of issues, themes and the sub indicators to measure and monitor sustainability much longer that could be captured. But there was a feeling that capturing 11 in total would be a very good step forward to measure sustainability at a country level. One more important point that we would cover of course in detail in my next presentation, that not all these 11 sub indicators are applicable to all kinds of form types. So for instance, the sub indicator nine and 10 within the social dimension, the wage rate in agriculture is applicable only to farms hiring unskilled labor while the food insecurity experience scale or FIAS is applicable only to household farms. Another consideration that I would like to take note of is that the reference period for data collection for all the indicators is not the same. So for instance, in the economic dimension, the net farm income sub indicator has a three years reference period and so is the case with the sub indicator four and five which is prevalence of soil degradation and the variation in water availability that has a three years reference period and as well FIAS which has a reference period of the last 12 months. Now, as I said earlier and on the previous slide, the hardest choice was to limit the framework of two, four, one to 11 themes and sub indicators. Series of expert discussion in meetings, consultation and literature review that we carried out has shown that sustainability is so complex that in general, there is a much longer list of issues that could be considered and used to capture sustainability in agriculture. In this slide, you can see some issues that are considered important but are not captured in SDG 241. So if a country wishes, we still recommend them to consider these in order to assess their agriculture sustainability at a national level but these are not required for countries to monitor in context of 241. One critical aspect that we will discuss in detail as part of each sub indicator was the establishment of thresholds or cut off points that will be used to assign sustainability status to each farm and the agriculture area that it owns or operates. Thresholds or sustainability criteria to define it very briefly are national policy based or international targets or science based absolute or relative values or levels below or above which each sub indicator of the farm is assigned the sustainability stages. So for each sub indicator criteria to assess sustainability levels are developed. The concept of sustainability implies an idea of continuous progress and improvement towards better performances across all teams. While such performances can therefore be more or less sustainable. In order to capture the concept of continuous progress towards sustainability, a traffic light approach is proposed for SDG 241 in which three sustainability levels are considered for each sub indicator. Green is considered as desirable, yellow is considered as acceptable and red is considered as unsustainable. To elaborate further, this approach allows identification for each team condition of critical unsustainability that is red, conditions that can be considered ideal classified as green and in between intermediate conditions that are considered acceptable or yellow. This approach also acknowledges the trade-offs existing between sustainability dimension and themes and the need to find an acceptable balance between them. Each sub indicator is assessed at the level of a agriculture holding. The sustainability level is then associated with agriculture land area of the holding. All sub indicators for a given agriculture holding therefore refers to the same agriculture area. As I mentioned earlier, reporting of SDG 241 can be done at various level using both a dashboard and aggregate indicator. What we require countries to report on is the dashboard and aggregate indicator at the national level. Now, what makes the dashboard approach more interesting and appealing is that it helps visualize the performance across the dimension, as well as across independent teams or sub indicators separately, that what makes the dashboard policy relevant and actionable. Now, from the same dashboard, we can derive the aggregate indicator SDG 241. Now, this is an example, a fictitious or made up example, whereby, as you can see on the horizontal axis, we have the 11 teams or sub indicators. And on the vertical axis, we have percentage of agriculture area. As you can see from this dashboard, each sub indicator is color coded based on the sustainability criteria or the farm performance based on the threshold values. And it's visually very informative because at a single look, you can see that the most problematic aspect for this country axis profitability, which has recorded the most level of unsustainability, which is 40%. Now, as I mentioned to you earlier, we can also derive an aggregate indicator very easily from the dashboard approach. So for us to derive the aggregate indicator, you can see this horizontal red line, which cut across the 11 teams. And this line is set at the indicator level, which has recorded the highest unsustainability level. In this case, of course, it's profitability. And hence, once we are reporting the indicator at a national level, the overall unsustainability at the country level will be 40%. Or the value of SDG 241 at a national level will be 40%. These are the formulas that can be used to basically derive the aggregate indicator. So we can visualize it both ways. So we can visualize in terms of the maximum sustainable agriculture area, which is basically an addition of the yellow and green. So the area acceptable and the area desirable or the maximum unsustainable area across all the 11 teams. So as you can see on the previous slide, the unsustainable area is for profitability sub indicator. Now, in terms of the dashboard level, I mentioned that basically it's very helpful in terms of policy use and interpretation, because it helps us adhere to international standards and methods and provide a structured and transparent framework. The dashboard approach help us focus on main issues and encourage discussion on how to make it more sustainable. I'm talking about the agricultural land area across the 11 teams, while linking it to the policy action. And it drives the policy to focus on intervention at various levels. Interpretation, it's very easy to interpret in terms of the accent to which agriculture, country agriculture is far from being productive and sustainable, and it's very easy to identify and prioritize the area that require intervention. So I will stop here. If you have any questions, I'm very happy to take those. Thank you. And we don't have so far any question in the chat. We'll leave a few seconds to the participant. It's starting, not yet. Yes, now it's working. Okay, so in the previous presentation, we learned about the conceptual and methodological basis of SDG 241, that is its scope, crops and livestock, coverage, teams, sub-indicators, periodicity, et cetera. In this session, we will go through the 11 teams and sub-indicators of SDG 241, particularly focusing on the rationale for including a team and sub-indicator within the framework. Data items required to construct the respective sub-indicator, and the sustainability criteria developed to assign the farm, and its agriculture area, red, green or yellow statuses, which we call the traffic light approach. So as highlighted earlier, SDG 241 is defined using the simple formula, which is area under productive and sustainable agriculture divided by agriculture land area. So again, let's focus on the denominator first, agriculture land area. As I already mentioned, it's a well-known concept and is derived by adding cropland and land under permanent meadows and pastures. For estimation of the agriculture land area, of course, we adhere to the system of environmental economic accounting for agriculture, forestry and fisheries and world census of agriculture 2020 standards and classification systems. So as you can see here, we are interested in agriculture land area as defined by CAAFFF. Then from the land tenor perspective, it's very important to take note, particularly from this perspective, the scope of the indicator include agricultural land area that is owned and operated or rented in or land borrowed for free occupied and common land exclusively managed by the holding. The land which is owned by the holding but is rented out is out of the scope of the indicator. So it's very obvious from the chart that I'm showing you now. So as you can see from this chart, parcel one is owned and used. So it will be included as part of the scope of the indicator. Parcel two is again owned and used. So of course, this is gonna be considered for sustainability assessment of the farm. Parcel four is rented in, though it's not owned by the agriculture holding but it will be included in the sustainability assessment while parcel three which is owned by the holding but rented out to other agriculture farms will be considered as out of scope of the indicator. One important point to notice that common land which is used by this agriculture holding is going to be included in the scope if and only if it is exclusively managed by the agriculture holding. If the agriculture holding is sharing the common land with other farms, then it's not gonna be considered for sustainability assessment and that should be excluded from the agriculture land area of the farm. Now the indicator framework. This slide illustrates once again, the framework of SG241. We have three dimension which I will show you in turn and 11 themes and 11 subindicators. It's applicability and reference period for data collection. So in the economic dimension, we have three themes and three subindicators. So the first subindicator is farm output value per hectare. The second subindicator is net farm income and the third one is risk mitigation mechanism. Likewise in the environmental dimension, we have five subindicators, prevalence of soil degradation, variation in water availability, management of fertilizers, management of pesticides and use of agro-biodiversity supportive practices. And in turn, in the social dimension, we have three subindicators, wage rate in agriculture, food insecurity experience scale or FIS, which is also an SDG indicator in its own self, 2.1.2, and then secure rights to land. Of course, as I mentioned to you earlier, some of the subindicators are not applicable all kinds of communism. So the wage rate in agriculture that falls within the social dimension is only applicable to farm that higher unskilled labor. And likewise, FIS or food insecurity experience scale is applicable only to household farms. As I mentioned to you earlier, as part of the disaggregation recommended by SDG 241, we have recommended household stratification of results by household and non-household farms. So FIS we believe is not applicable to non-household sector. Again, in terms of the reference period for data collection or recall, for some of the subindicator, it's set at three years. While for others, it's still, we still consider last calendar year. Now, before going into the details of the respective subindicator, let me give you generic steps. These are very simple ones that will be used to estimate each subindicator. Now, of course, once relevant qualitative information is collected through agriculture surveys and thereafter checked, cleaned, validated and stored on computers as spreadsheets, it must be transformed into appropriate quantitative primary variables, which are in turn will be used to construct the 11 subindicator of SDG 241. A set of scripts and procedures typically carried out with statistical software such as Stata or R or SPSS are applied to the survey data for constructing the primary variables that will in turn get used to construct the 11 subindicators. So let's go to the first subindicator in the economic dimension, which is farm output value per hectare. So the dimension is economic, the theme is land productivity. The coverage for this indicator is all farm types and the reference period of data for this indicator is last calendar year. Now, why did we include land productivity or farm output value per hectare as part of the framework of 241? Land productivity is a measure of agriculture value of outputs obtained on a given area of land for a given time period. As farm, at farm level, land productivity reflects the technology and production processes for the given agroecological conditions. In a broader sense, an increase in the level of land productivity enables higher production with reducing pressures on increasingly scarce land resources, commonly linked to deforestation and associated losses of ecosystem services and biodiversity. Now, if you remember, if you recall the target 2.4, one of the key aspect that we needed to capture as part of the target was land productivity. And hence, we chose this indicator to be part of the framework of 241. For this indicator, we are interested in the following data items that will help us estimate the three primary variables called value of output of farm, agriculture area of the farm, and then further categorization of the farms by different typologies. Once we combine the value of output of produced by the agriculture holding with the agriculture land area, we will arrive at the farm output value effect here for that particular holding. Now, to estimate the value of output of that particular agriculture holding, we resorted or confined ourselves to five main commodities produced by the holding. So, what we need basically quantities and farm prices of five main crops and it's by products, if the holding primarily is produced crops, there is some kind of Sifanya. Yeah, I'm trying to mute. Okay, perfect. So, to estimate the value of output, we confined ourselves to five main commodities produced by the holding. Is it okay? Okay, so let me recollect. So, basically, we confined ourselves to five main commodities or five main crops and it's by products or if it is a livestock producing a holding, then five main livestock and it's products produced or if it is a mix of both crops and livestock producing a holding, then the top five commodities or activities that the holding is engaged in. Now, what we require is basically for value of output, we need quantities and we need farm gate prices. So, if we have these two variables, we just simply multiply these two to get at the value of output. And then, of course, we divide it by the agriculture land area of the holding to get to the farm output value of per hectare. So, this slide gives an example of some of the crops and by product produced by a typical agriculture holding. Of course, this list will vary from agriculture holding to, from one agriculture holding to another and from one country to another. So, this is just an indicative list of the crops that a given agriculture holding can produce. In terms of byproducts of the crops, of course, once if we are producing wheat, we can as byproduct of that particular crop when we harvest the wheat, stock can be produced that can be sold by the holding as well. For rice, we have strion husk, for cotton, we have sticks. For sugar cane, we have tops that are usually fed to the livestock. For maize, we have stock and straw and for mustard we have strion and so on. Now, this is very important. So, as I mentioned to you that basically as part of the scope of SCG2 for one, primarily we focus on crops and livestock production system. Now, having said that, we don't rule out other on-farm activities or commodities produced by the farm as secondary activities. So, if a farm is identified as a crop producer or a livestock producer, but then on the sideline, there is a small operation whereby a farm is engaged in some other activities. It could be manufacturing of wine or processing of fresh fruits and vegetables or maybe aquaculture or agroforestry, but not as a major or primary activity, then of course we will consider those on-farm activities as part of the productivity or farm output value per hectare calculations. Now, the first step for us to calculate the agriculture area of the farm output value of hectare of the farm is to categorize the farms by different types. Now, let me again reiterate as per recommended stratification of SCG2 for one, we offer or we propose or recommend to countries three variables for stratification. First is household and non-household sector. The second one is to whether this agriculture holding is a primary producer of crops, is a primary producer of livestock or this agriculture holding produce a mix of both crops and livestock. And the third stratification variable is as to whether this agriculture holding uses water to irrigate its agriculture area. So based on these three stratification variable, once we combine these three criteria we arrive at 12 combinations of an agriculture holding. So it could either be a household farm producing crops and it can be irrigated or it can be a household farm producing only livestock and it can be non-arrigated and so on. So based on these combinations and permutations, we arrive at a total of 12 groups. Of course, not all these 12 groups will be relevant for a given country but then again, I mean, we recommend countries to go to this level of precision for them to have a proper understanding as to what is going on in terms of sustainability issues related to land productivity in their country. So as I mentioned to you earlier, in order to estimate the farm output value per hectare, we need two basically variables. One is farm output value, which is a multiplication of quantity of the respective commodity produced multiplied by the respective farm gate prices. And then we have to divide it by the agriculture land area of the farm. And we do this exercise separately for each category of farm. The reason being that the productivity of a household farm which is irrigated and producing crop may be entirely different from a non-household livestock sector agriculture holding that is using highly sophisticated technology to raise livestock, to raise and produce livestock. So in order for us to compare the productivities of the agriculture holding with similar kind of farms, we have to categorize the agriculture holding accordingly by these different categories. Now, categorization into different, categorization of agriculture farms by different typologies would mean a rich sample size. And of course that translates into more costly data collection because you need to have more agriculture holding as part of your sample so that you have a representative for statistically successful farmers. A representative of statistically significant estimates. So as I mentioned to you earlier, farm output value is very easily can be estimated, quantity into prices. So this is basically an example from based on actual data that we collected in Bangladesh in 2000, early 2019. So we have quantity of price multiplied by the respective farm gate price to arrive at the total farm output value. Now, once we have this, another important step in calculation of the farm output value per hectare indicator to basically arrange the farms, right? Arrange the farms from lowest to highest in terms of their productivity per each category, okay? And then we will have to derive the 90th percentile. Now, as you can see in this chart, I mean, we have, let's say for example, we have a sample of 20 farms. Now, these farms are arranged in terms of its farm output value per hectare. And then we do it by category and then we identify the 90th percentile, okay? Within the distribution. And we select the productivity associated with the 90th percentile, which in our case is highlighted as green in this matrix and it's appearing to be 600. Based on this, we calculate the 2 third and 1 third of the 90th percentile, which estimates to be 400 and 200 in this case. Now, why we need to first derive the 90th percentile and then in turn have this 2 third and 1 third of the 90th percentile because of the fact that this is built into the sustainability criteria of this indicator. So as you can see in this slide, the farm will be classified as green if the farm output value per hectare is equal to or the value corresponding to the 2 third of the 90th percentile estimated for the distribution of categories of farm to which this farm belongs. So we have estimated the farm output value per hectare for a given farm. Then we take the distribution of the farms to which this farm belongs. We arrange the farms productivities from lowest to highest. We calculate the 90th percentile. From the 90th percentile, we calculate the 2 third and 1 third ratios. And based on that, then we start comparing that this particular farm productivity with the 2 third and 1 third threshold that we estimated from the distribution. So if the farm output value per hectare is greater than 2 third, we highlight it as green. If the farm output value per hectare is between 1 third and 2 third of the 90th percentile value, then we highlight it as yellow. And if the farm output value is less than 1 third of the 90th percentile, then we classify it as red. Now to give you an example, so this is again actual data from Bangladesh. So as you can see, we have classified the farms by different categories. And for each category, in total I mentioned to you, we have 12. So for each category, we have a sample of farms. And then based on the steps that I just explained to you, we calculated the 90th percentile, which for category one appears to be 600. So based on the 600, the 2 third is 400 and the 1 third is 200. And so on. For the next category, livestock household irrigated the 90th percentile was 800. The 2 third is 533 and the 1 third is 267 and so on. So we need to derive it for the respective categories. And then as you can see from the data for the holding number one in our sample, which we have from Bangladesh, the land productivity is estimated for this particular holding to be 900. Now this particular holding belong to household irrigated sector. And 90th percentile, which I showed you earlier that we have estimated from the distribution for this particular category 600. So we compare the 900 with the 2 third and the 1 third of the 90th percentiles. And then, you know, as you can see, 900 is greater than 2 third. So basically we classify this farm as green. Likewise for agriculture holding number two, the land productivity is estimated to be 300 and it falls between the 533 and 267. So it is highlighted as or classified as yellow. And then the third one, which is has a productivity of 200. It falls below the 1 third percentile. So it is high, you know, classified as red. So this is how we estimate the farm output value per hectare and, you know, assign sustainability statuses to the farm and the agriculture area that it's own and operate. Of course, once we have the green, yellow and reds identified for all the farms, we start adding up the agriculture areas by respective colors. And then we divided by the total agriculture area of the country estimated from the agriculture survey to evaluate the proportion of agriculture area for this subindicator by traffic light approach. So if you have any questions, because this is the a bit tricky indicator, rest all are very straightforward. If you have any question regarding this one, I'm happy to take question now. Let me quickly go to the second subindicator within the economic dimension because we still have to cover 10 and I'm not sure as to whether we will be able to finish it up, you know, today. But but let's let's try. So an important part of sustainability in agriculture is its economic liability of the farm, which is driven to larger extent by its profitability in the context of two for one profitability is measured using the net farm income that the farmer is able to unfarm farming operations. Now availability and use of information on the farm economic performances measured using profitability will support better decisions making both decision making both at the micro and micro levels. And since performance measures drive behavior better information on performance can alter behavior and decision making by government and producer both in the large scale commercial farming and medium and small scale subsistence agriculture. So as I mentioned to you earlier for this indicator the reference period is three calendar years which I will explain to you why in the in the coming slides. Stefano, can you see my slides changing? No. Let me just. Yeah. So for for estimation of this particular subindicator we propose two options. Two options are approaches to countries on how to report on this indicator a sophisticated approach which we recommend and a simpler approach which is based on farmer education profit. Now the sophisticated approach the net farm income is calculated using the formula and NFI is net farm income and then the respective variables included in this formula are described below. So you can see CR is total farm cash receipts including direct program payments YK is income in kind OE is total operating expenses after debates including cost of labor DEP is depreciation and delta INV is value of inventory change the sophisticated approach is adopted from statistics Canada and is recommended. However, it's used by the country is made conditional if data on farm financial records that are documented or recorded daily, weekly or on monthly basis are available. In general, large scale commercial farms maintain detailed financial records using which the net farm income can be calculated. Now for net farm income what we need is value of output of course again quantity and farm gate prices of crops, livestock or other on farm activities or products produced by the holding and then we need information on direct program payments we need information on income in kind and we need the value of inventory change on the cost side we take into account both operating and fixed cost as well as depreciation the operating expenses includes labeling expenses which is cash wages or in-kind wages fertilizer expenses pesticide fuel electricity feed irrigation costs taxes depreciation which I already mentioned in others so more information on how to use this approach is given in the link below it's published by statistics Canada to estimate the net farm income then we are as I mentioned to you earlier we are also offering a simplified option this simplified option can be used in it's a two tiered option so the first simplified option is if detailed data are not available at the farm level this is an approach which is better adopted to small holders and household sector so what we need information on again is quantity of output and farm gate prices of crops, livestock its products and byproducts whether it's marketed or self consumed operating expenses including input quantity and its market prices which could be fertilizer, pesticides, labor etc which I explained on the previous slide output quantity and farm gate prices of other on farm activities carried out on the holding like say for example I exemplified that primarily as for 241 we are focused on crops and livestock production systems but if there are other second activities practiced by the farm then those needs to be included in the profitability and land productivity indicators and of course input quantities and prices utilizing the production of other on farm outputs now for this simplified option one we exclude depreciation and value of inventory of crops but we also exclude depreciation change I mean from experience and from data that we have received from countries usually this information is not captured by the small scale food producers or small subsistence agriculture production systems now the second simplified option which is which we tested in Bangladesh as well is basically we ask the respondent reviewing or administering the agriculture survey too to declare on the farm on the farm or agriculture holding profitability over the last three calendar years so this simplified option is used in case of SEG indicator 2.4.1 survey questionnaire as well that I will show you tomorrow so in terms of the threshold to assign the perfect light to the farm and agriculture area that it own manages and operates again we have three colors green is desirable yellow is acceptable and red is unsustainable so if the farm profitability of the agriculture holding profitability is above zero for all three consecutive past three consecutive years then we will classify that farm as green if the farm profitability is above zero for at least one of the past three consecutive years then we classify it as yellow and if the farm profitability is below zero for all the past three consecutive years it's classified as red as you may have noticed the threshold for this indicator is set using three years data and hence on the very first slide when I was telling you that we are using three year recall period for this indicator this is the reason why this is to make proper assessment of the farm profitability over an extended period to account for a bad year due to market failure such as low prices of outputs in a certain year or negative environmental or ecological factors that may have impacted negatively the farm profitability such as heavy or untimely rains floods, pest attacks etc. to account for that instead of one year we are using a three year recall period so again based on the example of Bangladesh you know table based on actual data that we collected from 420 households and non-household agriculture farms in Bangladesh in 2019 the first agriculture holding was profitable for two out of three years hence we classify it as yellow the second agriculture holding was profitable for three out of three years hence it is classified as desirable or green and the holding number 181 was unprofitable in all three years and hence it is unsustainable based on the net farm income sub indicator now again as a last step as I mentioned to you earlier we aggregate the green yellows and red respectively and then we divided by the agriculture land area of the country based on the nationally representative sample that we have selected for the survey to arrive at the proportion so in this case 47% of the holding that we interviewed that was selected as part of the sample 47% of the area at the national or for that particular sample was classified as green 10% was classified as yellow and 4% was classified as red so if you have any question related to this indicator I can stay here a bit otherwise I move on to the next one okay we have a question from Ratna from Indonesia so in this survey do we make this survey as a panel survey or we take samples every survey period not necessarily so as long as your sample is nationally representative you can still have you know you can still select other agriculture holding as part of your sample so it not necessarily be a panel survey it can be a randomly selected agriculture household every single time different ones but it's obviously a panel survey would be good because you can track and monitor performance of the same forms over an extended time period for you to say as to whether agricultural sustainability is improving or it's decreasing you know over time for these particular farms so it could be a mix of both it could be you can select a certain portion of your sample to be fixed and then you randomize the rest of the part of the sample every three years so it's entirely dependent on the country but obviously a hybrid approach whereby you have a panel survey whereby you keep on rotating the panel farms which has been fixed every maybe three years 40% share can be changed every three years while the rest of the portion of the samples can remain the same okay thank you we have another question from Mr. Kadarmanto from Indonesia as well so he is asking if this income indicator is collected every year to determine the sustainable criteria no no it can be depending on the approach that country is using so let's say for example if as part of your agriculture survey system you are collecting information here both on the revenues right and on the cost of the agriculture holdings then you can readily have this indicator estimated every year okay if not then we recommend countries to collect information on this indicator every three years so it's entirely it's going to be dependent on the country but for us at least every three years this information needs to be collected now as I mentioned earlier we are offering two approaches one is basically a more sophisticated approach whereby you need to have data items and variable collected both for revenues and for the costs every year to have a very precise estimate of the profitability the second option that we are recommending to countries because it's a it's very it's not very data demanding but we are recommending to ask the farmer as to whether he was profitable in the last three consecutive years and based on his answer we can basically make an sustainability assessment but of course I mean the first approach is preferred one and for that I mean if country is regularly collecting information then they can readily estimate the value of the indicator every year and then based on that make a judgment let me again expand on this in that case you need to have a finance survey because you need to have you need to ask the same agriculture holding every year as to whether he was you know profitable in X and Y and Z okay we have another question from Mrs. Bata from from Nepal is net farmer income considered the labor cost of same household farmer come again sorry is net farm income considered the labor cost of same household farmer um yes and no I mean like say for example for small scale very small scale food producers I mean the cost of the family labor won't be considered as part of the cost of the holding because that will be automatically you know usually the norm is to consider that as a revenue okay but if it is a large scale commercial holding then of course I mean if the family labor is contributing to that then it should be subtracted from the from the revenues for us to estimate the profitability but usually I mean in case of small scale food producers the cost of the labor is not deducted from the revenues of the of the agriculture holding though it should be okay we don't have any question okay yeah so let me go to the third and the final sub indicator in the economic dimension it is called risk mitigation mechanisms so as you know resilience has emerged as a key factor in sustainability and it encompass absorptive anticipatory and adoptive capacities and refer to the processes properties of the system that allows to deal with external shocks and stresses in order for it to persist and to continue to be well functioning now in context of 241 the following external shocks are considered so drought which is a prolonged period of abnormal low rainfall leading to shortage of water flood and overflow of large water beyond its normal limits especially or what is normally dry land pests a destructive insect or other animal that attack crops food livestock and market shock any demand or supply shocks that alter the price mismatching the equilibrium in the market so in case of risk mitigation mechanisms we have opted for three shock coping or mitigation strategies in order for the farm to be considered as sustainable so the first one is as to whether the agriculture holding has access to or availed insurance which is a preventive protection measure to protect the holding against external shocks as to whether the holding has access to or availed credit which may have been obtained from formal or informal sources such as banks, relatives or local money lenders and the fact if the farm is diversified let's say for example if the share of a single agriculture commodities produced by the holding is greater than or less than 66% of the total value production of the holding now based on this access to or as to whether the holding has availed these three shock coping mechanisms we assign the green, yellow and red strategies to the agriculture holding now in terms of the last coping strategy or mitigation strategy which is on farm diversification we take the value of production of one single agriculture commodity over the total value of production of the agriculture holding which I mentioned on the previous slide the formula is very simple we take the value of production of commodity let's say for example a farm is producing five commodities so we take the value of production of commodity A and we divide it by the total value of production and then we try to estimate as to whether the value of production of this commodity is greater than 66% of the total value of production of the holding so if it is greater than 66% we consider the farm to be non-diversified if the value of this formula is less than 66% we consider the farm as diversified now of course as part of 241 methodology a farm holding is considered resilient if it has a weld or access has means to access the risk mitigation mechanism as follows so if the farm has access to or a weld at least two of the three risk mitigation mechanisms credit, insurance and diversification then we consider it as green if it has access to one of the three mitigation mechanism then it is considered as yellow or if it has no access to the mitigation mechanisms then it is classified as red the reason is very simple basically if you don't have access to credit in case of external shock or if you are not insured in case of internal shock and if you are not diversified then of course your agriculture operations may not be sustainable given the external factors so at least the farm should have one of these three coping mechanism for it to be classified as sustainable acceptable or unsustainable based on 241 methodology now this is again example from the Bangladesh test data of pilot study so as you can see in the table you know for household holding one the share of one commodity was 76 percent so this is above 66 percent the threshold that we have selected based on international standard industrial classification revision 4 which is 66 percent so based on that classification if the agriculture holding has a commodity with share above 66 percent in its total value of addition we classify the farm as non-diversified so given that share of a single commodity 76 percent it's classified based on this it will be zero zero means no and so on so based on on farm diversification this farm is non-diversified access to credit yes access to insurance yes the farm has two coping mechanism or mitigation mechanism hence it is classified as desirable or green the farm too it is very well diversified because its revenue is spread across three commodities but it doesn't have any access to credit and insurance so it is considered as acceptable and the third farm is not diversified as well it doesn't have any access to credit and insurance and hence it is labeled or classified as non-sustainable or red again the last step is for us to aggregate the areas classified as green yellow and red and divided by the total agriculture area estimated from the nationally representative sample to calculate the proportion of agriculture area at a national level as to whether it is green yellow or red so I stop here so let me start the first indicator the environmental dimension which is the second dimension within the 241 framework prevalence of soil degradation of course the dimension is environmental which I just told you about the theme is soil health the coverage for this indicator is all farm types so whether household or non household or whether irrigated or non-irrigated or crops livestock are mixed and the reference period for this particular indicator is last three calendar years and again I will explain as to why we have set the reference period for three years so FAO and intergovernmental technical panel on soils have identified 10 main threats to soil health soil erosion soil organic carbon loss nutrient imbalance acidification contamination water logging compaction soil sealing salinization and loss of biodiversity and in the context of 241 after a careful review of the 10 threats to soil health which I just spoke about shows that all but except one which is soil sealing which is loss of natural soil to construction and urbanization are potentially and primarily affected by inappropriate agriculture practices in the context of 241 amongst the 10 we have selected four main threats to soil health that are universal across the globe so these are soil erosion reduction soil fertility water logging and salinization of irrigated land now in the context of sub indicator a simple question is asked in farm survey which we have designed for 241 we will show that to you tomorrow to capture farmers knowledge or declaration about the situation of the agriculture holding in terms of its soil degradation or soil health having said that ideally all soils under agriculture land area in a country should be subject of periodic monitoring in order to assess the impact of agriculture on soils now the farm survey is not an ideal tool or the farmer declaration about the length of his holding may not be the ideal way to collect information on this sub indicator typically the other more objective and robust data collection instruments for this sub indicator are maps soil sampling, laboratory analysis field surveys or any other existing reports detailed reports on soil and land degradation at a national level however you know once we started working on the on this sub indicator we rapidly realized that these other data sources though very objective in terms of providing information on the soil health are very costly but we still recommend to countries if these sources exist then these should be used in combination with the farm survey to complement the information collected through this agriculture service or to cross check the farmer responses to the questions that we have that we have drafted to to measure this indicator or this sub indicator and now I mentioned to you earlier as part of this indicator we are focusing on four main issues to soil but we are not basically enforcing these four issues on all countries right so it's soil erosion reduction in soil fertility salinization of irrigated land and water logging so if there are other issues apart from these at a country level in some regions then they can swap one of these for the issues that the country is basically facing so we have given flexibility to countries to select either these four or maybe another one by dropping one of these and selecting another one which is more relevant to them so in case of sustainability criteria now we have basically again we have to classify the farm and the agricultural area that its own manages or operates by traffic light approach green yellow and red so the criteria or threshold that we have selected for this sub indicator after discussing it with the relevant expert are the farm will be classified as green if the combined area affected by any of these four selected threats to soil health is less than 10% of the total agriculture area of the farm so if one or more than one problem exists at the farm level and its combined the combined area affected by one or more these threats is less than 10% of the total agriculture area of the farm then its classified as green if the combined area affected by the four threats to soil health is between 10% to 50% of the total agriculture area of the farm then its classified as yellow and if the combined area affected by any of the four selected threats to soil health is above 50% of the total agriculture area of the farm then its highlighted as red now again the example so we ask them these questions so let's concentrate on the first agriculture holding 001 so they said we don't have any soil erosion yes I have reduction in soil fertility water logging yes its an issue for me, salinization no I don't have any issues with that as part of the questions we are asking is how much area is affected by this particular threat so in this case the total agriculture area of the holding is 0.9 hectares and the total area affected is 0.40 and we mentioned in the sustainability criteria if it is the combined area affected of the holding is between 10 to 50% then its classified as yellow in this case is 45% so this agriculture farm or the agriculture area that owns or operate is classified as yellow now holding 3 they mentioned we don't have any problem as for our agriculture area is concerned the total agriculture area of the holding is 0.2 hectares none of the area is affected hence it is considered as desirable because less than 10% of the area is impacted another holding they mentioned soil erosion reduction in soil fertility and they said that we don't have any water logging or salinization issue the total area of the holding is 0.27 hectares which is captured by the questions that we ask within the agriculture survey and the agriculture area affected in this case it is estimated to be 74% and hence it is considered as non-sustainable because more than 50% of the agriculture area of the farm is considered as unsustainable or is considered as affected and hence it is more than 50% so it is non-sustainable so again the last step you know basically we aggregate the areas classified as green yellow and red and divide the respective areas by national representative agriculture land area of the country derived from the nationally representative sample or agriculture survey and then thus we derive these proportions mentioned is variation in water availability the coverage is of course all farm types the theme is water use the reference period is last calendar year now in agriculture more specifically irrigated agriculture is by far the main economic sector using fresh water resources in many places of the world water withdrawal from rivers and groundwater aquifers is beyond what can be considered environmentally sustainable which affects both rivers and the ground aquifers sustainable agriculture therefore required that the level of use of fresh water for irrigation remains within acceptable boundaries now in terms of in terms of this particular subindicator the way we have designed the threshold is to there are multiple assessment criteria so let's say for example if a farm is not irrigating or or is irrigating less than 10 percent of its agriculture area so if a farm is irrigating less than 10 percent of its agriculture area it will be automatically considered as sustainable already or if the water availability remains stable over the years for farm irrigating crops then 10 percent of its area so here visualize this issue in terms of impact of agriculture on the environment if a farm is not using water then it's not contributing to the environmental issue and hence it is classified as green if the farm is basically using water but the water availability is stable then you know it will be considered as green for yellow we say that farm uses water to irrigate crops on at least or more than 10 percent of its agriculture area but it doesn't know as to whether water availability remains stable over the years or experience reduction on water availability of the years but there is an organization that effectively allocates waters among the users so a farm is basically using water more than 10 percent of its agriculture area it's observing you know reduction in water but then there are local organizations which which are mandated to ensure the delivery of water to different user according to established rules so basically if this organization exists this can be public or private or private operators then we say that we will classify this farm as yellow and red in all other cases by this I mean to say that if farm uses more than 10 percent of its agriculture area for irrigation the water level is going down and as well there are no organizations to effectively manage or allocate the water amongst the user that will be classified as red now again in terms of Bangladesh example you know the first holding reply no water is always available in sufficient quantity we highlighted it as desirable though it's irrigating more than 10 percent of its agriculture area with water holding to say yes water level in my wealth is progressively going down but I have organization you know in my area that are working very well so it's irrigating more than 71 percent area but you know though water availability is going down their organization hence it is classified as acceptable and then you know the holding number 36 replied that yes water level in my wealth is progressively going down but there are no organization and yet to allocate water and yet you know it's irrigating more than 74 percent area so this this agriculture holding in terms of variation of water availability is classified as as unsustainable now the in terms of sources of irrigation it could either be canals it could be a river it could be a lake or it could be a tube well or open well so we are considering all sources of of irrigation so in terms of again I mean the last step is exactly similar for the rest so we add up the agriculture areas classified as green and then as classified as yellow and red and then we divide it by nationally representative agriculture area and we calculate the proportions here thank you very much colleagues I mean it was very nice to interact with you and please don't hesitate to write any questions that you may have you know in an email you know tomorrow just note down it with you if something is unclear I can clarify it further and you know Stefania you may want to say something yes absolutely so thanks from my side as well we are going also to share an email with you or maybe you want to mention this talk taking yes so basically colleagues I mean hopefully today I mean we are going to send you a stock taking questionnaire so what this question is about is basically we have mentioned in this questionnaire all the data items that will help us calculate the primary variables for constructing the respective 11 sub indicators now given that we have only covered the economic dimension and half of environmental dimension we don't expect you to basically fill in the entire questionnaire for tomorrow but we expect you to send us this questionnaire filled in by the end of this training so that we know to what extent the current data collection at the country level or the current data that exists at the country level enables you to report on 241 so it will give us a very very clear understanding to what extent the countries are ready to report on the 11 sub indicators maybe some countries will be able to report on one others may be able to report on three but that's a very good information for us so we will share that with you today and then we expect you to send back to us on hopefully on Friday okay thank you so perfect so we know that today's session maybe was a little bit hard to follow because it's a lot of information so really thanks everyone for being connected all the time and please tomorrow as we said 30 minutes in advance event 30 am GMT time and as I said if you have questions also use our email address no problem we will check it and in case we reply for tomorrow or the day after tomorrow okay so thank you everybody and see you tomorrow take care bye bye