 Okay, good morning everyone. Nice to see you again for this second day of the virtual training on the SDG 241. We have some new participants today that were not able to attend the sessions yesterday or they did only partially. So first of all, let me again introduce myself. My name is Stefania Bacci. I am a statistician working in the Statistics Division of FAO at Quater. And I am the facilitator of this virtual training. So whatever issue you have, you can count on me. Mr. Arbab Asbandeyar Khan is an economist working also in the Statistics Division of FAO at Quater. And he will be your leading resource person for this virtual training. We have also behind the scene Mrs. Alda Elizabeth Diaz Cavallo, advisor for calculation of the SDG indicators from FAO Regional Office of Latin American and Caribbean. She's helping during these three days sessions to translate for me English, all the questions that the participants are writing in Spanish in the chat box. She has done a gorgeous job yesterday. We have had so active sessions. So before starting, I would like to recap quickly what we have learned yesterday. So we have seen the 21 SDG indicators that are under the FAO custodianship. And we have August, of course, on the SDG 241. We have seen in general its background, the scope of periodicity and other and so on. And finally, we have we have moved to the framework, which is the core content of this training. We have seen in details the first dimension, which is the economic dimension. And it has been a very interesting day full of consent and many doubts have been clarified through the questions and answer session. Yesterday, we didn't have time to go through all the sessions originally scheduled. So we will we have readapted the agenda of today to fit all of them. Therefore, we need to squeeze a bit the plan for today, and we will skip a couple of presentations, but I will tell you quickly about them later or tomorrow. Let's see. So today, we will see the remaining two dimensions. We will see the 241 data collection questionnaires. And a colleague from Statistics Canada will illustrate their experience in the SDG 241 reporting. Okay. So can you can you see my screen? Yes. Okay, perfect. So the first sub indicator in the environmental dimension is prevalence of soil degradation. In the context of 241, we have selected four main threats to soil health that are universal across the globe. At least that's what came up in our discussions with the experts. So the theme for this indicator is is soil health, the coverage for this indicator is all fun types. And the reference period is last three calendar years. So the four main threats that we have considered in the context of 241 are fairly universal soil erosion, reduction in soil fertility, salinization, water logging, and other like say for example, there would be many countries for which you know the four threats that we have listed here may not be relevant. So in that context, they can drop the one which is irrelevant for them and you know pick another one which is relevant in the country context. So in case of 241, a simple question is asked in a farm survey to capture the farmer's knowledge or declaration about the situation of agriculture holding in terms of soil degradation. So in terms of sustainability threats, this is how we structured it. So we classified the farm and its associated area as green. If the combined area affected by any of the four selected threats to soil health is less than 10% of the total agriculture area of the farm. So if any of the threat is affecting less than 10% of the agriculture area of the farm, then we will consider that their farm is green. For yellow, the combined area affected by any of the four selected threats to soil health is between 10 to 50%. Then we will classify the farm and its associated agriculture area as yellow. And if the combined area affected by any of the four selected threats to soil health is above 50% of the agriculture land area of the farm, then we will classify it as red. So it's very simple. I mean, we have three questions in the survey questionnaire that I will show you in my next presentation. And using those questions, you can easily collect information on all these aspects to classify the farm according to the traffic light approach. So this is again the one example of the pilot test that we conducted in 2018 and 19. So from this example, as you can see here, the holding one replied that we don't have any soil erosion on our farm. Yes, there was reduction in soil fertility. There was water logging observed or experienced by the farmer and there was no salinization. The total agriculture area of that particular farm was 0.9 hectares. The total agriculture area affected that was reported by the farmer to the question that we have asked was 0.4. So if we calculate this percentage simply by dividing the total agriculture area affected by the total agricultural land area of the farm, the percentage area affected is 45. As it falls between 10 and 50 percent, we classify this farm as yellow or acceptable. Let me give you another example. So holding three, they mentioned that they don't have any problem as for soil degradation is concerned on its holding. So they replied no to all the questions. The total agriculture area of the farm was 0.2 hectares. Of course, none of the area was affected by any of this threat and hence we classify this as desirable because if it is less than 10 percent of the total agriculture area of the farm, the problematic area, then we classify it as green. And likewise in this case, as you can see, this holding mentioned that they have soil erosion and reduction in soil fertility as two major threats experienced on the farm. The total agriculture area of the farm was 0.27 hectares. The total area affected by these two threats was 0.20 hectare, which is 74 percent of the total agriculture area. And hence we classify this farm as red or non-sustainable. Now once we again, the last step for all the subindicators remain the same, we add up the agriculture areas by green, yellow, and red statuses. We aggregate those and then we divide it by the nationally representative agriculture area of the entire country to calculate the proportion of the agriculture area by traffic light approach. Okay, so the second subindicator in the framework of two for one in the environmental dimension is variation in water availability. The theme is water use, the coverage is all farm types and the reference period is last three calendar years. Now agriculture, more specifically irrigated agriculture is by far the main economic sector that use freshwater resources. In many places, water withdrawal from rivers and groundwater aquifers is beyond what can be considered environmentally sustainable, which affects both rivers and groundwater resources. Sustainable agriculture therefore requires that the level of use of fresh water for irrigation remain within acceptable boundaries. Now having said that there is no internationally agreed standard of water use sustainability. Signals associated with unsustainable use of water typically typically include progressive reduction in the level of groundwater and drying out of springs and rivers. So though we don't have any objective standard to measure sustainability of water use, but then we can take some indications as to how it is doing in terms of its reduction. This subindicator captures the extent to which agriculture contributes to unsustainable patterns of water use. So in terms of the thresholds that we have came up with to assign green, yellow and red statuses to the agriculture holding and the agriculture land area that it owns, manages and operates. So the farm will be classified as green. If the water availability remain stable over the years for farms irrigating crops on more than 10% of its agriculture area, the farms will be automatically classified as green if they are irrigating less than 10% of their agriculture area with water. So what it means is that basically here we are assessing the impact of agriculture on the environment. So if a farm is not using any water for irrigation or less than 10% of its agriculture area for irrigation, then by default it's not contributing to the imbalance or reduction of water in the ground level and hence it will be classified as green. Now the farm will be classified as yellow if it uses water to irrigate crops on more than 10% of its agriculture area and he doesn't know whether the water availability remain stable over the years or experience reduction in water availability over the years, but there are no organizations that effectively allocate water amongst the users. And the farm will be classified as red if the farmer use water to irrigate at least 10% of its agriculture area of the farm does not know whether the water availability remain stable over the years or experience reduction on water availability over the years, but there is no organization that effectively allocate water. So red is all other cases. So just to exemplify for the Bangladesh tests that we carried out in 2018-19 holding one, they mentioned an answer to our question that we asked in a survey. They mentioned that no, we are not using no water is always available in sufficient quantity. Area irrigated is approximately 90% and hence we classified it as green or desirable. So if we go back, so the first condition is water availability remains stable over the years for the farm irrigating crops on more than 10% of the agriculture area. So if you are using water on more than 10% of your area, but the water availability remains stable, you are automatically classified as green. The second, we asked, was there a reduction in water availability? The farmer says, yes. Water in my wells is progressively going down. So the follow up question was, are there organization dealing with water allocation in your area? And the farmer says, yes, and they are working well. So the total area irrigated by this holding was 71%. And because of these two conditions, we classify it as yellow or acceptable. And the third one, they said, yes, water in my wells is progressively going down. And there are no organization that efficiently allocate water in my area. The holding irrigates 74% of its area with water, and hence we classify it as unsustainable. The last step remains the same. We aggregate the farms and the associated agriculture area that are classified green, yellow, and red. And then we calculate the proportions using the traffic light approach. So are there any questions? Yes, but I'm still waiting for the Spanish translation. So I don't know if you want to go on while I'm still translating. Okay. So the third sub indicator in the environmental dimension is management of fertilizer. In the context of 241, sustainable agriculture implies that the level of chemicals in the soil and water bodies remains within the acceptable thresholds. The theme for this sub indicator is fertilizer risk. The coverage is all farm types. And the reference period for this sub indicator is last calendar year. Now, this sub indicator is calculated using data collected through a set of questions. Again, asked to ask to the farmers about their use of fertilizer in particularly the synthetic or mineral fertilizers and manure and slurry about their awareness of the environmental risks associated with the use of fertilizers and their behavior in terms of plant nutrient management. So these are eight measures that we propose as best practices that the farmer needs to have or adhere to on its agriculture land area. And based on how many of these are practiced by the farmer, we then assign the green, yellow and red statuses to the agriculture holding. And I'm not going to go through each measure separately. All these measures that are listed here have been decided in discussion with the relevant experts on fertilizers. And all these are explained in both in the enumerator manual, the definitions of all these all these measures as well in the in the data analysis guidelines that we will that we will show to the participants later on. So, so of these eight measures, if the farmer is using fertilizer, but is taking at least four specific measure to mitigate environmental risks, then the farm will be classified as green. If the farmer is not using any fertilizer, then by default, we will consider that farm is a sustainable or green. So there are two conditions for green. One is if the farm is not using any fertilizer. And second, if the farm is using fertilizer by taking four specific measures, the holding or the agriculture holding will be classified as yellow. If the farm uses fertilizer, and is taking at least two measures to mitigate environmental risks. And lastly, the farm uses fertilizer and does not take any of the specific measures listed on the previous slide to mitigate environmental risk, then it will be classified as red. Now again, the example from Bangladesh tests, holding one, we asked them as to whether they use fertilizers, they said yes. Then we asked the follow up question of the eight measure, how many do you practice and they, they said two. Okay. And hence, based on the criteria, which I just listed here, they are classified as yellow. Now let's take another example, holding two, they said yes, we use fertilizer. And then we asked them follow up question as to which practices do you adhere to, and they said none. And hence, the agriculture holding is considered as non sustainable. And then another holding holding 37, they are not using any fertilizer. So by default, they are considered as green. And holding number 39, they are using fertilizer, but out of the eight, they adhere to four. And hence, the criteria that we have set for this indicator based on that they're classified as desirable or green. And the last step remain the same. So we aggregate the agriculture area by green, yellow, and red, and then using the total agriculture area of the country, we then calculate these proportions or percentages. So management of pesticides. This is the seventh sub indicator of SG241, the third and the fourth in the environmental dimension. The theme is pesticide risk. Coverage is all fun types and reference period is last calendar year. To contextualize, pesticides are important inputs in modern agriculture for both crops and livestock production systems. But if not well managed, they can cause harm to the people health and as well to the environment. The proposed sub indicator is based on information on the use of pesticides on the farm, the type of pesticide use, and the type of measures taken to mitigate the associated risk. So there are three things. Like in case of fertilizers, we first see as to whether this particular agriculture holding is using fertilizer or not. So if the holding is not using pesticide, we classify that particular holding as green because that holding is not contributing negatively to the environment. If the holding is using pesticide, then we ask a follow up question as to which type of pesticide are you using. And then based on the type of pesticide that the holding is using, then we recommend the holding to adopt some of these measures, both health related for the human beings and environmental related. So again, I'm not going to go through these. You can read it for yourself. These are very self-explanatory. But of course, I mean, we will come back to this in any questions. So green, yellow, and red statuses. So let me start with the last thing, the green. The farm will be automatically classified as green if they are not using pesticide. Again, visualize this problem from the point of view of negative impact of fertilizer usage on the environment. So the farm is not using pesticide for any reason, affordability, high prices, non-availability, no access, etc. So the reasons could be multiple. But if the farm is not using it, the farm is classified as green. However, if the farm uses only moderately or slightly hazardous pesticides, so we have two categories of pesticides. One is moderately or slightly hazardous pesticides. And then the second one is highly or extremely hazardous pesticides. These two classes of pesticides are defined by the World Health Organization. And the link to the guidelines for this classification is given in the SDG 241 methodological note as well as in support documents. So you can find the definition of what do we mean by moderately or slightly hazardous and highly or extremely hazardous pesticides. Anyway, coming back to the green. So if the farm uses moderately or slightly hazardous pesticide, which is World Health Organization class two and class three, in this case, the holding adheres to all three health-related measures, these ones, which are adherence to label direction for pesticide use, maintenance and cleansing of protection equipment after use, and safe disposal of pesticide waste, that is cartons, bottles and bags. So in this case, the farm should adhere to all three health-related measures and at least four out of the seven environmental-related measures. So three from these, all three, and four from the seven for the farm to be classified as green, if it is using moderately or slightly hazardous pesticides. Now, the farm is classified as yellow. If it only uses moderately or slightly hazardous pesticide, again, WHO class two and three, and take at least two measures each from health and environment-related. So instead of three and four, which was the case in green for yellow, the farm needs to qualify two from here and two from here. And the farm will be classified as red if it uses highly or extremely hazardous pesticides, which is WHO class 1A or 1B or illegal pesticides. So the farm is using highly or extremely hazardous pesticide or illegal pesticide by defaulted screen. It is red, sorry. Or if it is used moderately or slightly hazardous pesticide without taking specific measure to mitigate environment or health-related risk associated with the use, fewer than two from each category. So in case of red, if the farm is using moderately or slightly hazardous pesticide, if they are, you know, adhering to less than two of these three measures and less than two from the seven measures, then it will be classified as red. So let's go to the example and it will further clarify as to what these threshold means. So the Bangladesh test, we interviewed holding for this sub indicator. We asked them as to whether they use pesticide or they don't use it. As you can see, majority of them said, yes, we use pesticide. Then the follow-up question was which type of pesticides do you use? Highly or extremely hazardous or illegal or moderately or slightly hazardous? Okay. So this is the second question. So then if depending on their answer, then we ask them about the measures. So which measures do you adopt? So in this case, this holding is using highly and extremely hazardous or illegal pesticide. So by default, no matter if this holding is adhering to all three health-related and all seven environment-related measures, still it will be classified as non-sustainable or red. Holding two, they said, yes, we use pesticides. We use moderately or slightly hazardous type. They adhere to two from the environmental measures and two from the health measures and hence this holding and its associated agriculture area will be classified yellow or acceptable. Now let's go to another one. So number 12. So this holding said, yes, we use pesticide. The type that we use is moderately or slightly hazardous. They adhere to three environment related and three health-related measures. And hence this agriculture holding was classified as desirable. And the last step again is the same. I mean, we then start aggregating the agriculture area by green, yellow and red colors or sustainability statuses. And then we use the nationally representative agriculture area to calculate the proportions for this particular subindicator. So any questions? We don't have any for now. Maybe we wait a few seconds and then you can move on. Okay, so let me cover the next one and then perhaps we will take questions together. So the last subindicator in the environmental dimension is the use of agrobiodiversity supported practices. This subindicator, let me highlight, was subject to intense discussion and eventually refinement in 2019 as part of the 2020 comprehensive review of the global indicator framework. These refinements were carried out in consultation with a country-led working group constituted by FAO. It was coordinated by Canada and other countries represented in that group were Brazil, USA, Argentina, Chile, France and Russia. So after an air long discussions and consultation throughout 2019 towards the very end of the year, a compromise consensus on the indicator's criteria was reached after which it was tabled again for IAEG-STG review, where the group re-approved and re-endorsed this particular subindicator in November 2019. From a methodological perspective, this subindicator measures the level of adoption of agrobiodiversity supported practices by agriculture holding at ecosystems, species and genetic level for both crops and livestock. One important point that I would emphasize is that specifically in case of this subindicator, the scope is the entire area of the farm holding as opposed to the agricultural land area that is used as a denominator for all other indicators. So up until now, for all the subindicators, we were using agricultural land areas as a denominator. Particularly for this one, we are going to take the entire farm, entire area of the agricultural holding. So this is very important to take note of. Now, so based on whether certified organic agriculture is practiced at a country level, two set of criteria were proposed. One for countries practicing traditional agriculture and another one for countries where organic agriculture certification system is in place. So these were the list of the criteria that were decided after thorough deliberations with the group of countries that I just mentioned of which some are represented here in this virtual training as well. Like say for example, Brazil, Argentina and Chile. So these were the set of the criteria for countries with no organic certification or practicing traditional agriculture. And then the same set, so all other remains the same from the previous slide. The only one additional criteria added for the countries with organic agriculture is, farm produces agriculture products that are organically certified or its products are undergoing the certification process applies only to countries with with with organic certification. And then based on the set of criteria, okay. We classify the agriculture area of the farm, you know, based on based on the following based on the following thresholds. So sustainability status for countries with organic certification in place. In that case, the agriculture holding meets at least three of the above criteria. So of the six, the country needs to adhere to three of these criteria for it to be classified as green, yellow, the agriculture holding meet at least one of the above criteria, then it will be classified as yellow. And if the agriculture holding meets none of the above criteria, then it will be classified as red. For the countries with no organic certification, because we have, we are proposing one less measure. In this case, the agriculture holding meets at least two of the above criteria. Okay. Two of the five yellow agriculture holding meets at least one of the above criteria and red if the agriculture holding meets none of the above criteria. And the last step remains the same. We assign the agriculture farm and the agriculture area that it owns manages on our rates. Sustainability status is based on based on the fulfillment of the of the thresholds that we have set for for this sub indicator. So I stop here. So I stop here. Go through the, you know, so this one wage rate in agriculture. So in the social dimension, now we have completed with the environmental dimension. We entered into the the last dimension of SCG 241 framework. We have three sub indicators in this dimension of which the first one is wage rate in agriculture. So this team, which is on decent employment, provide information on the compensation of unskilled employees working for the farm that belongs to the elementary occupation group is defined by the international standard classification of occupation by by ILO international labor organization. In other words, this sub indicator informs about economic risk faced by unskilled workers, those who perform simple and routine tasks in terms of average remuneration received. So we are not focused here on skilled labor force, but on the labor force, which is doing basic and routine activities on the on the agriculture holding. So the formula for estimation of the wage rate that is getting paid to the unskilled worker on the farm holding is very simple. I mean, if you have access to the daily wage, the daily average wage rate paid to the unskilled labor, that is very good. But otherwise, usually the holder or the respondent doesn't have information on the on the daily wage rate. So what they provide you is the total annual compensation. And from the total annual compensation, we divided by the total number of annuals our work and multiplied by eight to convert in two days. So it's it's very simple. And the sustainability criteria that we have developed for this particular sub indicator are as follows. So the farm will be classified as green if the wage rate paid to unskilled labor is above the national wage rate or minimum agriculture sector wage rate if available. And a default result for farms which are not hiring any any labor. The farm will be classified as yellow if the wage rate paid to unskilled labor is equal to the minimum national wage rate or minimum agriculture sector wage rate if available, and will be classified as red if the wage rate paid to the unskilled labor is below the national minimum wage rate or minimum agriculture sector wage rate available. And the last step, I mean, again, is the same which which which I explained earlier. So we calculate the proportions using the nationally representative agriculture area of the country to to derive the sustainability statuses for for this for this sub indicator. So I stop here. So let's now go to the the tenth sub indicator in the in the framework of SDG 2 for one. Now FIS is already a tier one SDG indicator, which is indicator 2.1.2. And tier one means established methodology exists, and data on it is regularly collected by countries, and it's reported by a few. Now, in context of two for one, it's customized or tell us tailored version tries to measure the extent to which household of the holder or owner of the farm are food secure despite having some agriculture production. So I will not go into the details of how to estimate the severity of food insecurity using fierce, first assuming that many of you may know about this indicator already. And secondly, because of the because of the shortage of time that that we are having now. However, I will touch upon the basics of its methodology while referring you to the training material on the indicator that is published by by FAO. In short, FIS is the measure of is the metric of severity of food insecurity that is measured at the household level. It's a statistical measurement scale designed to measure unobservable or latent traits and is measured based on people direct. Yes or no answer to the eight fierce questions. So here are the eight standard fierce questions that are used to collect data on the food insecurity of the household of the holder of the agriculture holding. I will again be afraid from going into details of explaining each question, a detailed explanation on what these question entails is given in the PDF file that that will be shared with you as part of this presentation. So once the data on the eight fierce question is collected, the first step is to prepare the data for analysis where the standard labels are added to the eight fierce questions, which I will show to you on the second slide. As a second step, the data is inputted into the model prepared by the FAO fierce team for parameter estimation. That is calculation of a level of severity of food insecurity associated with each question and each respondent using a rush model. In total, two parameters are estimated. The first one is called the item parameter, which we also technically call the difficulty parameter. And it refers to and is derived from the eight fierce questions. And then we have the respondent parameter, which we also call the ability parameters. These are derived from the number of people who responded to the to the eight fierce question. The third step is statistical validation, where an assessment is made as to whether depending on the quality of data collected, the estimated parameters are valid. That is, the data are consistent with theoretical assumptions that that that are used to inform the model. And finally, as a last step, the calculation of sustainability status of the culture holding is carried out. So once a measure of severity of food insecurity condition experienced by each respondent, that is the holder of the agriculture holding based on their answer to the eight questions has been derived, the sustainability status is assigned to the holding, like we were doing for the other sub indicators. So we assign desirable acceptable and non-sustainable statuses accordingly. So let me write the step described on the previous slide. So based on the data collected using the eight fierce question, it is prepared for analysis first, where each data item is coded, where two is assigned for a no response, and one is assigned for four years. After the coding, the standard labels are added to the eight fierce question as per the model developed by the FAO fierce team. So instead of the question codes that we had on the previous slide, and these will vary from, you know, based on the survey from one country to another, we add the standard labels worried, healthy, few food skipped, ate less, run out, hungry, whole day, etc. So once the data has been properly codified and standard labels are added to the data of the eight fierce questions, the next step implies estimating the parameters associated with the eight questions. The methodology underlying the estimation of parameters for the prevalence of severity of foods insecurity is based on the item response theory or IRT, which is used to analyze responses to the survey or test questions. Now the IRT is a quantitative measure of non-observable traits that I previously mentioned that can be derived from a set of dichotomous variables or binary variables that takes a value one or zero. Now Rush model is one of the several model in the item response theory, which is applied to the to the fierce data. So once the model is is executed, I mean the analysis is carried out, the item parameters or difficulty parameters are estimated using the model and arranged from least severe, which is which is worried, to the most severe, which is if you are hungry for the entire day for the whole day. Thereafter, the exponent parameters are estimated from the raw score. The raw score is also estimated by the model. The raw scores are a number of affirmative or yes responses given to the eight fierce questions. Raw score is an integer number with a value between zero and eight, thus the total number of respondent parameters are nine. So, you know, depending on how many questions the holder of the agriculture holding has responded to, we can have a raw score from zero from zero to eight. So this is this is how the output of the model looks like. Whereby, as you can see here, we have the ability parameters here. These are the standard errors. These are the number of of agriculture holdings that said yes to a particular question. And this is the expected score. So based on the information that we have estimated using the model, all what we do is we plug in the item severity raw score and respondent parameters into the standard metric or an Excel sheet that is prepared by FAO into appropriate places. So the difficulty parameters are plugged into the to the Excel sheet at appropriate place, which can be this Excel sheet can be accessed here. And likewise, the ability parameters are plugged into the respective place within the within the Excel sheet, along with the standard errors and the number of the frequency of the of the agriculture holdings to estimate the the value the final values for the fierce sub indicator. So in this case these two values, which is 12.2 and 2.3 are the two values for the for the fierce indicator 2.1.2. So the prevalence rate moderate and severe food insecurity is 12.2% and the prevalence rate for severe food insecurity is 2.2.3% from the data that we gathered in in in validation. Now there is one additional step which is classification of the agriculture holding based on the probability of the severity of food insecurity that we we estimated using the model. So if the probability of the household of the holder, okay, of that particular agricultural holding will is to be moderate of or severe food insecure is less than 0.5 and the probability to be severe food insecure is less than 0.5 then we classify this agriculture holding as is green. If the probability of the household of the holder to be moderate to severe food insecure is greater than 0.5 and the probability to be severe food insecure is less than 0.5 then we classify it as yellow and lastly if the probability of a household of the holder of the holding to be severe food insecure is greater than 0.5 then we classify it as it is red. So all the information that is needed for for this particular sub indicator is given in this table. So as you can see here the probability to be moderately and severely food insecure for this holding 1 is 0 and the probability to be severely food insecure is 0 as well. So this one is classified as desirable. So let me go back here to this condition. So the probability of household is less than 0.5 to be moderately or severely food insecure and the probability to be severely food insecure less than 0.5. So in this case it's it's green. So let's go to another example holding number four for this household the probability to be moderately and severely food insecure is greater than 0.5 while the probability to be severely food insecure is less than 0.5. Hence we classified it as acceptable and in this case as you can see for a holding 13 both the probabilities to be moderately and severely food insecure and severely insecure is greater than 0.5. Hence it is classified as unsustainable. Now this sub indicator is easy in terms of collecting information. It's a bit technical in terms of analyzing and processing information but we have developed a very logical and a comprehensive e-learning course on indicator 2.1.2 which is which is we will provide you the link to that e-learning course that is self-explanatory. After going through that course you will you will have a good idea as to what I spoke about in relation to to the FIES in the context of 2.1. Finally once we classify the agriculture holding and the agriculture land area that it owns manages and operates by sustainability statuses that is green yellow and red we calculate the proportions of of agriculture area using the nationally representative agriculture land area. So I will stop here Sifanya. So now we are we have reached almost the end. This is the last sub indicator within the framework of STG 2.41 which is Secure Tenure Rights to Land. The sub indicator allow assistance sustainability in terms of rights over the use of agriculture land areas. Since agriculture land is a key input for agriculture production having secure rights over land ensures that agriculture holding have control over key asset that is land and does not risk losing it in the short to medium term. Evidence shows that farmers tend to be less productive as they are reluctant to invest if they have limited access to or control of economic resources and services particularly particularly land. So in the context of 2.41 here is how we classify farms and agriculture green yellow and red. So if the agriculture holding has a formal document with the name of the holder or the holding on it or has the right to sell or bequeath any parcel of the holding then this particular holding and its agriculture area will be classified as green. The holding will be classified as yellow if they still have a formal document but the name of the holder of the of the holding is not on it. Okay and it will be classified as red if they don't have a formal document and the name of the of the holder or the or the holding is not on the formal document then in that case this holding will be classified as red. So in for Bangladesh example holding one we asked them as to whether they have formal document they said yes we asked them as to whether your name is on the formal document they said yes we have a right to sell and they have a right to bequeath as well. So they are considered as desirable. Another holding they said yes we have a formal document. My name is not on the document I don't have the right to sell I don't have the right to bequeath we call this acceptable because he still has a formal document and then the last one you don't have a formal document you know of course if you don't have a formal document your name doesn't appear anywhere you don't have the right to sell and you don't have the right to bequeath and hence you are classified as non-sustainable and the last step remains the same we aggregate the agriculture areas of the farm classified as green as yellow and as red and then divided by the nationally representative agriculture area to estimate the proportions and with this I would like to thank everyone and if you have any questions any clarity I mean please ask us now or you can always write to us you know using the following email addresses thank you very much. Okay thank you very much Asfandia. So we still don't have Martin so or we go through the next presentation so we start a new chapter let's say or or maybe you can show the the web page which is still something interesting for the participants. I'll show you the my screen and then I will show you as to where you can find more information on on on both land tenure indicator and the fias which is two one two. Okay can you see my screen? Yes. Okay so for the indicator on land tenure it's a 5a1 okay but you know it's a it's a separate indicator in so on right it's customized and tailored for sg241 but all these questions which our colleagues from Brazil and and other countries are asking in terms of why we have selected selling and be quitting as a as a condition why only formal document with even without the name of the owner on it all these can be you know can be is detailed you know here on on this page so you can you can go to the metadata and then you can go to the measuring individual sorry go there yeah and and then you can you can look look through all these all these background documents for you to for you to have more understanding and plus we have this e-learning course as well okay which you can take and then familiarize yourself more with the concept of of land tenure in terms of two one two which is severity of food insecurity all the information on the metadata classification e-learnings and and other requisite information can be can be can be found here so this is just to show you that if you are interested in if you have more questions you know that you need to have answers to then you can always go to these additional resources or write to us and we will be happily answering those so in this session we will cover in detail the data collection tools that have been developed by FAO to support countries in their data collection and reporting efforts on stg-241 as highlighted yesterday and today as well the focus of stg-241 is to assess the sustainability of farm holdings and its agriculture land area and thus farm survey offers an opportunity for collecting data through a single instrument which is which is recommended by FAO to the decision to use farm survey is in line with the country's effort which are supported by FAO of course to develop farm survey as the most appropriate tool for generating agriculture statistics the choice of farm survey was made because of the following reasons farm survey does exist in countries in one shape or form or another to collect data on different aspects of agriculture sector use of farm survey will help collect information on all sub indicators using one single data collection instruments thus avoiding the the additional work of integrating information from different data sources that are usually managed by different institutions and organization third using the farm survey all information will be collected from holding selected through a nationally representative sample thus avoiding the problem associated with the use of different data sources and fourth farm survey is expected to be cost effective in comparison to putting in place monitoring systems that is soil and water sampling and laboratory testing geographical information systems and robust administrative regard systems however though farm surveys are well suited to measure the economic dimension of sustainability it may not be the ideal tool for measuring environmental and social sustainability of the holding typically environmental impacts of agriculture are measured through monitoring systems which I just spoke about like the more sensing water water and soil sampling and and other tools in addition we do understand that for several environmental teams it is unlikely that farmers will be able to assess the environmental impact of their farming practices on issues like fertilizer pollution or pesticide use etc so similarly the information in the social dimension teams is generally captured through household surveys while in majority of the cases agriculture farm holdings are closely associated with a given whole household this is not always the case and therefore care must be given to capturing this information through dedicated survey design having said that the methodological note of sg241 does offer the country's the flexibility of of using combination of different data sources other than farm surveys called alternative data sources so in case of 241 we have we we offer the first approach which is farm survey it's we have all we have developed a standalone farm survey questionnaire model that I will show you in a bit plus we have also developed an option around agris survey program and 50 by 2030 initiative questionnaire that we will cover in detail tomorrow and then I spoke briefly about the alternative data sources which can be potentially used to report on different sub indicators of 241 and the methodological note of of the indicator mentioned alternative data sources but this option hasn't been developed fully as yet so we currently as FAO are in process of working on on this solution to report on sg241 hopefully we we think that the guidelines practical guidelines on how countries can use these different data sources to report on 241 will be available by the end of 2021 so let me explain in turn as to what you mean by different options so option one is the standalone farm survey questionnaire it's designed as a module that contains the minimum set of questions needed to assess sg241 it is flexible it can be administered independently or attached as a separate module or it can be integrated at appropriate places within existing farm surveys that are operational at the national level now for us to develop this standalone survey questionnaire for 241 we carried out cognitive tests of the of the questionnaire in in Mexico, Bangladesh and Rwanda back in 2017 and 18 the objective was to to refine the survey questionnaire from the design flow comprehension recall and respondent judgment perspective and to assess if the questions asked are sufficient and fully understood by a limited number of heterogeneous respondents as well we carried out extended tests in Bangladesh that I was referring to during my presentation today and yesterday so in Bangladesh we carried out these extended tests to collect data to test the sustainability criteria assess time of the survey which on average was approximately 50 minutes in some cases it took us longer than 50 minutes but you know more or less that was the time which which took the surveyors to interview the the respondents and of course one of the key objective of the extended tests in Bangladesh was to revise the support documents that accompany the the standalone survey questionnaire now the the survey questionnaire has five sections we have an introductory section then the second section is about estimation of area of the holding the third section has all the questions regarding the three sub indicators of the economic dimension the section four has all the question required for estimation of the environmental dimension and section five has all the questions addressing the social dimension of the holding so this is how the model look like we have shared it with you already as part of the link that was sent by by us maybe a week earlier but we will happily share you know the survey model once again with you for for your information so as I mentioned we have also developed the support documents that again let me reiterate what's shared with you before the training so the support document includes an enumerator manual to train the enumerator surveyors and supervisors before their field deployment to administer the questionnaire this manual also has definition of the key terms concepts and meaning behind the question asked it provide guidance on the use of skip questions and filter questions and provide examples of how commonly encountered incenses where questions and responses may not be easily may not be easy to administer and record respectively then we have a manual on data into operation and analysis it contains all the steps that must be performed in order to organize the collected data into excel spreadsheets or other statistical packages it also includes the processes and procedures to analyze the data collected and construct the 11 sub indicators according to the dashboard approach then we have guidelines on on data analysis and reporting this is for use for use of both data producers and data users and it gives the step-by-step process on how to calculate the thresholds and final sub indicators according to the dashboard approach and as well the aggregate indicator then we have a document on sampling guidance for SDG 241 and we have also developed this statistical toolkit which comprises of a code book, tabulation plan and modular status scripts to support data analysis so I'm not going to go into the detail of of all these documents because I already explained that and you can always go through this you know it's part of the presentation so here are the are the documents that I was just talking about the numerator manual data interpretation sampling guidance data analysis document etc which I just spoke about the second option which I showed you on my very first slide is that we have integrated the questions from 241 questionnaire into aggregate survey program and 50 by 2030 initiative survey questionnaires now the the questions from 241 survey module have been integrated into the core and core module as well as into the economy and production methods and environment module of the aggregate survey program and as well into the production methods and environment module of the 50 by 2030 initiative I'm not going to go again into the detail of of of this slide because we have a full-fledged presentation scheduled for tomorrow which is going to which is going to elaborate more as to what aggregate survey program and 50 by 2030 constitute for for scg 241 in terms of data collection so here are the different documents on the survey program we call it handbook on agriculture integrated survey and then we have also prepared a technical note on mainstreaming sdg indicator 241 in the agris and 50 by 2030 initiative now as I mentioned earlier the methodological note of scg 241 does recommend using alternative data sources to report on to report on the indicator however several aspects needs to be carefully considered prior to using alternative data sources in order to produce consistent and reliable data as per recommended periodicity it is advised that the use of alternative data sources may be considered when the available data set fulfill certain criterias so anyways I will go through those criterias in my next slide but here you know for for the different sub indicators of 241 some potential alternative data sources have been have been recommended but the countries can only use it if these alternative data sources fulfill certain criterias so first of all the alternative data sources should give the results of at least the same quality as the survey and ensure international comparability it should respect the recommended stratification that is the farm type sector and production systems and and that is if the data is available at the same level of territorial desegregation as farm surveys etc it should capture the same phenomena as proposed by the farm survey that is described in the sub indicator metadata sheets with at least the documented same quality and considered and standard it is compliant with as I mentioned international national standards and classification systems to be to be international comparable and finally the reference here and periodicity should be homogeneous across the different sub indicators now having said that alternative data sources can be used to complement and and or validate farm service data this combined approach has the potential to improve the validity and soundness of the results in particularly in countries that have well established monitoring systems and that are able to produce quality information consistently over time the information from other sources may be used and leverage in different ways depending on the quality and regularity of its collection for example it can be used to replace farm survey questions where alternative data sources of information are available and respond to the criteria mentioned on the on the previous slide it can also complement farm survey questions by providing additional contextual information helpful to interpret the results and as well it can be used to cross check the farm survey result to identify any inconsistencies and to ensure the robustness of the indicator the validation exercise can be done exposed that is during the data collection by providing external data to the enumerators before going to the field in this way the enumerator can probe whether the responses to the farm survey are consistent with a priori external knowledge in any case it is recommended that country complement the farm survey with monitoring systems or other sources of information that can measure the impact of agriculture on the environment this will provide additional information and help cross check the robustness of sdg indicator 241 with regards to the environmental dimension of sustainability so with this I stop here we will discuss in more detail as for our future work on alternative data sources tomorrow and and if you have any question regarding you know the data collection tool for for sdg 241 please don't hesitate to ask any question this one okay you see the correct one right yes okay so uh as fun yeah maybe you you can you check the the comments on the chart if people are asking other questions just to follow a little bit okay so um we have seen so far all the theoretical parts and notions so in the spanilla and we have just seen the data collection tools so let's now move to another practical part and I will show you now how FAO gets the data on sdg 241 for countries meaning I will show you now the questionnaire which you might have all received uh on august 10 2020 this august and it is expected to be sent back uh to us by the end of this month so we have one single questionnaire that comes in excel format and it is indeed the key instrument to collect uh the data from countries it covers all the three dimensions and all the 11 sub indicators that we have seen uh yesterday and today it is sent to countries once a year even if we have seen that the periodicity of the indicator is three years but in this way we can monitor the availability of data on an annual basis since you know very well it is really a brand new indicator identify identify changes and get the data points through the years considering also that often we do not get many data especially now that we are at the starting phase assess the country needs in terms of capacity development for example technical assistance and training on the sdg exactly how we did for this virtual training and lastly confirm the national focal points contacts which is always a crucial information for us uh so that we are sure to be immediately in contact with the appropriate person what we have done so far we have tested the question in 45 countries through a pilot exercise that was carried out between December 19 and April 2020 i was supposed to show you the results of this pilot test right after this presentation but i'm afraid we will not have time so maybe you can go through the presentation alone or if i have time tomorrow maybe i'll show you quickly a couple of slides the most important ones initially the question was only in English and we have translated in July 2020 into three official languages the ODP UN official languages which are Arabic French and Spanish then we have had our first hospital dispatch as i said on august 10th of this month this year we have sent the question to 203 countries including your countries of course and the questionnaire has been sent to the sdg 241 focal points to the general sdg focal points and to the head of nso we have copied the feo offices and all the relevant people and the deadline as i said is for the 30th of September next activity will be to translate into the remaining UN official languages which are chinese and russia yeah it is shown how the questionnaire is organized so it is composed of eight worksheets there are three introductionary sections which are the cover page instructions and the definitions then we have three data reporting sections one for each dimension and two supplemental information sections for metadata and feedback we are going to see all these in detail in a minute this is a preview on how the questionnaire is displayed you can see all the different sheets here so in detail what are these sections about the first one the cover page asks country specific information meaning the national focal point contact details that as i said there is really a key formation for us for every smooth communication with the country then there is a page with only instruction on how to complete the questionnaire and it gives also an overview of the questionnaire structure followed by another page that explains the definition of the key concepts in the end terms and the international standard used the second section is the core of the questionnaire where the data are requested meaning where the countries fill the spaces with their data and this includes all the three dimensions so the trees will be needed just for the economic they fight for the environmental and the tree for the social this is how it is displayed but i'm going to show you quickly right after this presentation the real questionnaire last section we said this about the supplementary information so the metadata part is quite intuitive it collects metadata on country coverage source of data unit of measurement frequency of data collection and so on and finally the feedback sheet that is a very simple survey with 10 questions that help us understanding if some areas maybe still need improvements now let me show you how to fill the excel properly the first page so the cover page is like this one you need to fill this column with the national focal point content details and we ask this information even if this has it has already been sent to FAO in the past because this will tell us if the focal point has been confirmed or if he or she has been changed about that these are the focal points content detail we have for your countries please let us know in case you know that they have been changed uh in particular also for Venezuela we still need the the nomination and we have also maybe uh an issue or an doubt on Mexico because we have received the last May the communication from Inejie that Inejie was the focal point to FAO so he was in charge of answering the questionnaire and they were supposed to include the data both from Inejie and CIAP while two weeks ago we have received the questionnaire back from CIAP with only CIAP data so I have indicated in this slide all the three focal points Mrs. Ruiz, Mr. Espezo and Mr. Loa Iiza but I'm not sure since from the last communication actually I should consider only Mrs. Ruiz so I kindly ask Mexico or to clarify this for the three data reporting sections you have to fill two columns the first columns needs to be filled with the values following these described criteria we ask only one year so you should report the most recent one that is available in your country the reference we use in the is the calendar year from January to December if you have no data you can insert zero if it is not occurring but potentially applicable while you should write NA if it is not applicable at all while in the second column so which is the note you should insert explanation in case the data reported use a different national definitions so not the ones described in the definition worksheets or if the data reported using a different reference period so not the calendar year from January to December and here you also specify the exact year that the data are referring to so if you have filled the first column with the value in the notes you write the year this last point applies of course to this data collection cycle since we are not sure for which year you may have data and that is also to facilitate the collection of all currently available data or maybe for 1x subindicators you might have last data available from for example 2015 which is still good for us but it's important to underline it and just for future note FAO typically collects data for specific years so usually the last four to five years and probably this question will include some options in the coming years once of course the process becomes more established the metadata section is composed by a table with all the 11 subindicators listed and columns where you can specify all the metadata so the type of variables the availability unit or measurement and so on and the last section is the feedback one so as I said 10 questions among them there are six questions with the scale response from strongly agree to strongly disagree and for open questions to say something more in detail in case you need it that's all as far as the data collection question is concerned maybe I don't know if there are already some questions if not let me show you quickly let me stop sharing and I share I don't know if there are some questions so in case not are we sure this is so let's proceed sorry can you hear me yes now yes okay so I was saying that we don't have any questions so far so let's proceed okay perfect so so let me show you quickly the real survey this is the the real question this is the question you have all received just in case you didn't receive it at least the focal points that I showed didn't receive it please let us know so you see here below you have all the different sheets the first one the cover page it gives you this space and here you have also other extra information for example our contacts and all the details when you have sent back etc you have done the instruction you see how it is structured so you have different paragraphs where it is really explained everything including all the structure of the question the questionnaire including all the sheets that I just shown to you the definition is the most important probably a sheet because it gives you really a lot of information you see it is divided by subject we have the denominator and then you have the subindicator by subindicator all the definition the terms used and the international standard use so it is a very long sheet but in case you have any doubt you go here and you can see quickly if the information that you need is here then it comes the three dimension sheets are coming so we have an economic one the environmental one and the social one here as well it's divided by subindicator so it's quite intuitive you have the tree for the economic and the same for environmental and the social you have the columns so you see you have the colors you have the unit of measurement and then as I explained you have the two columns that needs to be filled and the same for the the social dimension here again you have explained a little bit how to fill this sheet and you have also the indication on the methodology used the PDF that you can download even in Spanish this has been translated in Spanish then the metadata as I explained you see you have the different subindicators always divided by subindicators and you have the different columns where you can insert all the metadata of course if you have them and always there is a space for notes in case you want to add something that could be relevant for us and then the last the last section which is the feedback very simple question these the questionnaires these questions will help us understanding if we can improve the questionnaire even more and next year when we are going to send the questionnaire again and then of course you have a free space to say whatever you want but don't forget that we are always open to listen to your suggestions so use this email address sdg241 line indicator at fero.org and you will reach us immediately I showed everything about the questionnaire I hope everything was clear do we have any questions as from there first switch on my camera it's dark here in the meantime I don't know maybe it's already 7 30 here of course always if you have any questions you will you are free to tell us tomorrow in case you have questions other questions we skipped quite a lot of sessions even today so we will coordinate with us from the year how to to deal the the last day because for sure we need to select some presentation to really be skipped for sure we will have the agris colleague coming to present the agris program and the 50 by 2030 initiative and we will have for sure the canada experience which I think is very interesting for you because it's really a practical example of one country do you want to add something as pantheon no that's it but this training is you know for you to better understand what we talked about yesterday and today especially about the framework about the 11th sub indicator so I would strongly suggest to you to read through the methodological note once more because that's where a lot of other questions that you may have may surface plus you know the support documents that I that I was mentioning in my previous presentation the numerator manual the calculation procedures the sampling guidance will give you all the necessary information on how to go about collecting information about this indicator as well as on how would you then process the data for you to construct the 11 sub indicators and and so actually I mean from from this point of view I mean it's just the beginning of the collaboration that we are having with you I mean if you have any follow-up questions you can always write to us using the email addresses that we showed you and we will be happy to answer those questions and clarify any concerns that you may have yeah maybe I want to add we had some questions from the registration phase from Daniela Lopez, Bertha, Rodriguez Jara and Diana Ramirez and then we had some questions left from yesterday it was from Mr. Caceres Leonardo from Eduardo Carvajal and Paula Villarroel from Raúl Valle Raúl Melo and Beatriz Urquiaro-Cas and then I got an email with a question from Luis Gustavo Pacheco so we have analyzed this question as from the I have seen them and he thinks that everything was answered today so in case we didn't answer your question especially these people that have I have nominated please feel free tomorrow to ask again the question okay so really thanks all of you again for having participated to this second day of virtual training today also was a very intense day we have seen many concepts and we have finally finished to see the fulcrum of the two-for-one methodology tomorrow we plan to have we hope to have time to have a more interactive session you will be asked to talk at least the the two lead representatives of the country and we really hope to have a very pleasant session as we have had today and yesterday so thanks again and see you tomorrow bye bye to all