2f:T45d,// viewof Area_chart_type = Inputs.radio(["Stock", "GHG Emissions", "Value of production"], {label: "Variable", value: 'Stock'}) viewof Area_chart_type = { const data = [ { key: "stock", label: _lang( nbText.sections.livestockExplosion.chart.variables.stock.label ), yLabel: _lang(nbText.sections.livestockExplosion.chart.variables.stock.tip) }, { key: "ghg", label: _lang( nbText.sections.livestockExplosion.chart.variables.ghg.label ), yLabel: _lang(nbText.sections.livestockExplosion.chart.variables.ghg.tip) }, { key: "vop", label: _lang( nbText.sections.livestockExplosion.chart.variables.vop.label ), yLabel: _lang(nbText.sections.livestockExplosion.chart.variables.vop.tip) } ].map((d) => ({ // common values ...d, xLabel: _lang(nbText.sections.livestockExplosion.chart.labels.year) })); return Inputs.radio(data, { label: _lang(nbText.sections.livestockExplosion.chart.inputLabel), format: (x) => x.label, value: data.find((x) => x.key == "stock") }); }30:T4d1,areaChart = { // Note the colour change in the origional plots is from stock vs dataStock in other notebook... // TODO: Double check this if (Area_chart_type.key === "stock") { const titles = [ _lang(nbText.sections.livestockExplosion.chart.variables.stock.tip), _lang(nbText.sections.livestockExplosion.chart.labels.year) ]; return buildAreaChart( dataStock.map((obj, i) => convertToFloat(obj, "TLU (millons)")), titles, colorblindData.key ); } else if (Area_chart_type.key === "ghg") { const titles = [ _lang(nbText.sections.livestockExplosion.chart.variables.ghg.tip), _lang(nbText.sections.livestockExplosion.chart.labels.year) ]; return buildAreaChart( dataGHG.map((obj, i) => convertToFloat(obj, "emissions (MtCo2e)")), titles, colorblindData.key ); } else if (Area_chart_type.key === "vop") { const titles = [ _lang(nbText.sections.livestockExplosion.chart.variables.vop.tip), _lang(nbText.sections.livestockExplosion.chart.labels.year) ]; return buildAreaChart( dataVOP.map((obj, i) => convertToFloat(obj, "VOP (billions usd)")), titles, colorblindData.key, true ); } }31:T50b,{ const div = document.createElement("div"); div.style.display = "flex"; div.style.flexDirection = "row"; FileAttachment("country_emissions_hazards-4.csv") .csv() .then((data) => { div.appendChild( build_download_button_dev( data, _lang(nbText.sections.leversOfChange.livestockProductionSystems.download.ghg), "GHG emissions and exposure", ".button_container_ghg", "button_download_ghg" ) ); }); FileAttachment("3_country_lps_hazards.csv") .csv() .then((data_lps) => { div.appendChild( build_download_button_dev( data_lps, _lang(nbText.sections.leversOfChange.livestockProductionSystems.download.lps_hazards), "LPS Hazards", ".button_container_ghg", "button_download_lps_hazards" ) ); }); FileAttachment("3_country_lps_emissions.csv") .csv() .then((data_lps) => { div.appendChild( build_download_button_dev( data_lps, _lang(nbText.sections.leversOfChange.livestockProductionSystems.download.lps_emissions), "LPS Emissions", ".button_container_ghg", "button_download_lps_emissions" ) ); }); return div; }32:T64b,{ // summary, based on num countries in 'levers of change' const iIntro = _lang(nbText.sections.summary.intro); const countryListFunc = _lang(nbText.sections.summary.countryListFunc); const multiCountryString = num_priorities > 1 ? _lang(nbText.sections.summary.countryListSupport.topStringFunc)({ num: num_priorities }) : ""; const topCountry = _lang( nbText.sections.summary.countryListSupport.topCountryFunc )({ top: _lang(nbText.general.country_article1[summary_object.firstCountry]) }); let countryList = summary_object.countryArray .map((d, i) => (i < 4 ? ` **${_lang(nbText.general.country_article1[d])}**` : "")) .filter(Boolean) .join(", "); const followedBy = _lang(nbText.sections.summary.countryListSupport.followedBy); countryList = summary_object.countryArray.length > 0 ? `${followedBy} ${countryList}` : countryList; const severalOthers = summary_object.countryArray.length > 4 ? _lang(nbText.sections.summary.countryListSupport.severalOthers) : ""; const iCountryList = countryListFunc({ num: num_priorities, multiCountryString: multiCountryString, topCountryString: topCountry, multiString: countryList, severalOthersString: severalOthers }); const outroFunc = _lang(nbText.sections.summary.outroFunc); const iOutro = outroFunc({ people: summary_object.sumPopulationMillion.toFixed(0), livestock: summary_object.sumVOPBillion.toFixed(0), footprint: summary_object.sumGHG.toFixed(2) }); return md`${iIntro} ${iCountryList} ${iOutro}`; }33:T723,

${_lang(nbText.sections.methods.title)}

${_lang(nbText.sections.methods.sections.datasets.title)}

${_lang(nbText.sections.methods.sections.datasets.body)}

${_lang(nbText.sections.methods.sections.livestockProdSystems.title)}

${_lang(nbText.sections.methods.sections.livestockProdSystems.body)}

${_lang(nbText.sections.methods.sections.exposureData.title)}

${_lang(nbText.sections.methods.sections.exposureData.body)}

${_lang(nbText.sections.methods.sections.hazardData.title)}

${_lang(nbText.sections.methods.sections.hazardData.body)}

${_lang(nbText.sections.methods.sections.povertyData.title)}

${_lang(nbText.sections.methods.sections.povertyData.body)}

${_lang(nbText.sections.methods.sections.greenhouseEmissionsData.title)}

${_lang(nbText.sections.methods.sections.greenhouseEmissionsData.body)}

${_lang(nbText.sections.methods.sections.boundaries.title)}

${_lang(nbText.sections.methods.sections.boundaries.body)}

${_lang(nbText.sections.methods.sections.adaptationOptions.title)}

${_lang(nbText.sections.methods.sections.adaptationOptions.body)}

${_lang(nbText.sections.methods.sections.methods.title)}

${_lang(nbText.sections.methods.sections.prioritizationAnalysis.title)}

${_lang(nbText.sections.methods.sections.prioritizationAnalysis.body)}

${_lang(nbText.sections.methods.sections.references.title)}

${_lang(nbText.sections.methods.sections.references.body)}

34:T795,buildAreaChart = (data, titles, colorBlind= 'None', condition = false) => { // const areaContainer = d3.select("#main_area_chart") // .append("div") // .attr("id", "area_container"); const data_titles = Object.keys(data[0]) let plotAreaGraph = Plot.areaY(data, { x: data_titles[0], y: data_titles[2], fill: data_titles[1], tip: { channels: { cat: { label: _lang(nbText.sections.livestockExplosion.chart.labels.category), value: d => _lang(nbText.sections.livestockExplosion.chart.legend[d.category.replace(" ", '').toLowerCase()]) } }, format: { x: d => d3.format("d")(d).replace(/\D/g,''), cat: true, y: true, fill: false, z: false } }, }) let chartColor = { legend: true, range: getColorBlind(colorBlind), tickFormat: label => _lang(nbText.sections.livestockExplosion.chart.legend[label.replace(" ", '').toLowerCase()]) } if(condition){ plotAreaGraph = Plot.areaY(data, { x: data_titles[0], y: data_titles[1], fill: true, tip: { format: { x: d => d3.format("d")(d).replace(/\D/g,''), z: false, fill: false, } }, }) chartColor = { range: getColorBlind(colorBlind), tickFormat: label => _lang(nbText.sections.livestockExplosion.chart.legend[label.replace(" ", '').toLowerCase()]) } } const plotArea = Plot.plot({ color: chartColor, y: { label: titles[0], }, x: { label: titles[1], tickFormat: d => d3.format("d")(d).replace(/\D/g,'') }, marginBottom: 35, marginLeft: condition ? 65 : titles[0] == "Emissions" ? 45 : 60, marks: [ plotAreaGraph, Plot.ruleY([0]) ] }) // document // .querySelector("#area_container") // .appendChild( // plotArea // ) return plotArea }35:T559,async function dynamicTextLivestockExplosion(){ // // await createAreaChart(select); // const lastYear = [...document.querySelectorAll('#area_container .plot-d6a7b5-figure g[aria-label="x-axis tick label"] text')].map(label => label.textContent).pop(); // const firstYear = [...document.querySelectorAll('#area_container .plot-d6a7b5-figure g[aria-label="x-axis tick label"] text')].map(label => label.textContent).shift() // let labels = Array.from(test_areachart.querySelectorAll('.plot-d6a7b5-figure g[aria-label="x-axis tick label"] text')) // .map(label => label.textContent); // // Crear un nuevo elemento con el contenido del último año // const boldElement = document.createElement('b'); // boldElement.textContent = `(${d3.min(labels)} - ${d3.max(labels)})`; // hardc oding these as they seem constany anyway... const boldElement = document.createElement('b'); boldElement.textContent = `(2010 - 2021)`; return Object.assign( html`
The livestock explosion
The visualization below helps you explore historical ${boldElement.textContent} trends in livestock population, value of production (VoP), and greenhouse gas (GHG) emissions. These trends give a measure of the rapid pace of growth of the sector, and therefore its importance for people and the environment.
` ); }36:T100c,function dynamicTextQuickInsightsRegion() { const maxYearStock = Math.max(...dataStock.map((obj) => parseInt(obj.year))); const minYearStock = Math.min(...dataStock.map((obj) => parseInt(obj.year))); const lastYearDataStock = dataStock.filter( (obj) => parseInt(obj.year) === maxYearStock ); const firstYearDataStock = dataStock.filter( (obj) => parseInt(obj.year) === minYearStock ); const sumTLULastMillion = lastYearDataStock.reduce( (acc, obj) => acc + parseFloat(obj["TLU (millons)"]), 0 ); const sumTLULastBillion = sumTLULastMillion / 1000; const sumTLUFirstMillion = firstYearDataStock.reduce( (acc, obj) => acc + parseFloat(obj["TLU (millons)"]), 0 ); const sumTLUFirstBillion = sumTLUFirstMillion / 1000; const percentageIncreaseStock = ((sumTLULastBillion - sumTLUFirstBillion) / sumTLUFirstBillion) * 100; const maxYearVOP = Math.max(...dataVOP.map((obj) => parseInt(obj.year))); const minYearVOP = Math.min(...dataVOP.map((obj) => parseInt(obj.year))); const lastYearDataVOP = dataVOP.filter( (obj) => parseInt(obj.year) === maxYearVOP ); const firstYearDataVOP = dataVOP.filter( (obj) => parseInt(obj.year) === minYearVOP ); const sumVOPLastMillion = lastYearDataVOP.reduce( (acc, obj) => acc + parseFloat(obj["VOP (millones usd)"]), 0 ); const sumVOPLastBillion = sumVOPLastMillion / 1000; const sumVOPFirstMillion = firstYearDataVOP.reduce( (acc, obj) => acc + parseFloat(obj["VOP (millones usd)"]), 0 ); const sumVOPFirstBillion = sumVOPFirstMillion / 1000; const percentageIncreaseVOP = ((sumVOPLastBillion - sumVOPFirstBillion) / sumVOPFirstBillion) * 100; const maxYearGHG = Math.max(...dataGHG.map((obj) => parseInt(obj.year))); const minYearGHG = Math.min(...dataGHG.map((obj) => parseInt(obj.year))); const lastYearDataGHG = dataGHG.filter( (obj) => parseInt(obj.year) === maxYearGHG ); const firstYearDataGHG = dataGHG.filter( (obj) => parseInt(obj.year) === minYearGHG ); const sumGHGLast = lastYearDataGHG.reduce( (acc, obj) => acc + parseFloat(obj["emissions (MtCo2e)"]), 0 ); const sumGHGFirst = firstYearDataGHG.reduce( (acc, obj) => acc + parseFloat(obj["emissions (MtCo2e)"]), 0 ); const timesIncreaseGHG = sumGHGLast / sumGHGFirst; // insight, translated const i = { title: _lang(nbText.sections.quickInsightsGeneral.header)({ selection: _lang(nbText.legends.ssa) }), livestock: _lang(nbText.sections.livestockExplosion.insights.livestock)({ selection: _lang(nbText.legends.ssa), year: maxYearStock, population: sumTLULastBillion.toFixed(0), percent: percentageIncreaseStock.toFixed(1), yearSince: minYearStock }), vop: _lang(nbText.sections.livestockExplosion.insights.vop)({ selection: _lang(nbText.legends.ssa), year: maxYearVOP, population: sumVOPLastBillion.toFixed(0), percent: percentageIncreaseVOP.toFixed(1), yearSince: minYearVOP }), ghg: _lang(nbText.sections.livestockExplosion.insights.ghg)({ mult: timesIncreaseGHG.toFixed(1) }) }; return Object.assign( html`
${i.title}

${i.livestock}

${i.vop}

${i.ghg}
` ); // return Object.assign( // html`
Quick Insights for Sub-Saharan Africa
//
Sub-Saharan Africa’s livestock population in ${maxYearStock} is ${sumTLULastBillion.toFixed( // 0 // )} billion, and has grown by ${percentageIncreaseStock.toFixed( // 1 // )}% since ${minYearStock}
//
Sub-Saharan Africa’s value of production in ${maxYearVOP} is ${sumVOPLastBillion.toFixed( // 0 // )} billion, and has grown by ${percentageIncreaseVOP.toFixed( // 1 // )}% since ${minYearVOP}
//
The explosion in livestock numbers comes at the expense of a growth in GHG emissions of ${timesIncreaseGHG.toFixed( // 1 // )} times in the same period
` // ); }37:T463c,icons = new Object( { bovine: '', pig: '', poultry: '', shoat: '', 'forest loss to pasture': '', 'forest loss to soy': '', } )38:T25c0,icons1 = new Object({ "Tropical livestock units": '', "Pasture area": '', "Rural population": '', "Value of production": '' }, )39:T964,function map_legend(colorBlind) { const legendWidth = 270; const legendHeight = 80; const padding = 5; const legendScale = d3.scaleLinear() .domain([0.2, 1]) .range([0, legendWidth - 60]); const legendSvg = d3.create("svg") .attr("width", legendWidth) .attr("height", legendHeight) .attr("font-size", "10") .attr("font-family", "system-ui, sans-serif") .attr("font-weight", "bold"); const gradient = legendSvg.append("defs").append("linearGradient") .attr("id", "gradient") .attr("x1", "0%") .attr("y1", "0%") .attr("x2", "100%") .attr("y2", "0%"); const text = { title: _lang(nbText.sections.leversOfChange.chart.map.legend.title), lo: _lang(nbText.sections.leversOfChange.chart.map.legend.lo), md: _lang(nbText.sections.leversOfChange.chart.map.legend.md), hi: _lang(nbText.sections.leversOfChange.chart.map.legend.hi), } gradient.append("stop") .attr("offset", "0%") .attr("stop-color", getColorBlindRGB(colorBlind, "#F4BB21")) gradient.append("stop") .attr("offset", "100%") .attr("stop-color", getColorBlindRGB(colorBlind, "#EC5A47")) legendSvg.append("rect") .attr("width", legendWidth - 60) .attr("height", 10) .attr("transform", "translate(30,30)") .style("fill", "url(#gradient)"); legendSvg.append("line") .attr("x1", 30) .attr("y1", 30) .attr("x2", 30) .attr("y2", 45) .style("stroke", "#000") .style("stroke-width", 1); legendSvg.append("text") .attr("x", 20) .attr("y", legendHeight - 15) .text(text.lo) legendSvg.append("line") .attr("x1", legendWidth / 2) .attr("y1", 30) .attr("x2", legendWidth / 2) .attr("y2", 45) .style("stroke", "#000") .style("stroke-width", 1); legendSvg.append("text") .attr("x", legendWidth / 2) .attr("y", legendHeight - 15) .attr("text-anchor", "middle") .text(text.md) legendSvg.append("line") .attr("x1", legendWidth - 30) .attr("y1", 30) .attr("x2", legendWidth - 30) .attr("y2", 45) .style("stroke", "#000") .style("stroke-width", 1); legendSvg.append("text") .attr("x", legendWidth - 40) .attr("y", legendHeight - 15) .text(text.hi) legendSvg.append("text") .attr("x", legendWidth / 2) .attr("y", 25) .attr("text-anchor", "middle") .text(text.title) return legendSvg.node(); }3a:T947,getTooltipContents = (d, colorBlind) => { function showAttributes(group, data) { var atributos = ""; for (var atributo in group) { let unidad; switch (atributo) { case "Rural population": unidad = _lang(nbText.sections.leversOfChange.chart.map.tooltip.data.hazards.popRural.unit); break; case "Value of production": unidad = _lang(nbText.sections.leversOfChange.chart.map.tooltip.data.hazards.vop.unit); break; case "Tropical livestock units": unidad = _lang(nbText.sections.leversOfChange.chart.map.tooltip.data.hazards.tlu.unit); break; case "Pasture area": unidad = _lang(nbText.sections.leversOfChange.chart.map.tooltip.data.hazards.pastureArea.unit); break; default: unidad = _lang(nbText.sections.leversOfChange.chart.map.tooltip.data.emissions.unit); } const filterData = data.find(country => country.ISO3 === d.properties.iso_a3) const perc = filterData[atributo + "_perc"] ? filterData[atributo + "_perc"] : 0 const value = filterData[atributo] ? filterData[atributo] : 0 const deg = (perc * 3.6 ) + "deg" //atributo[0].toUpperCase() + atributo.slice(1) atributos += `

${ group[atributo] }
${ td.leversChangeMap?.[atributo] }:
${value} (${unidad})
` } return atributos } const headers ={ hazards: _lang(nbText.sections.leversOfChange.chart.map.tooltip.headers.hazards), emissions: _lang(nbText.sections.leversOfChange.chart.map.tooltip.headers.emissions), } console.log('attrData:', d) return html`

${_lang(nbText.general.admin0_ISO3[d.properties.iso_a3])}

${headers.hazards}: ${ showAttributes(icons1, hazards) }

${headers.emissions}: ${ showAttributes(icons, emissions) }

`; }3b:T8a7,html` `3c:Tdea,function create_map (colorBlind){ const width = 1200; const height = 1200; let value = null; // const countriesFil = filterCountries1(mode, cobined, NaN, countd); //crear componentes const projection = d4.geoCylindricalStereographic().scale(1000); const path = d4.geoPath().projection(projection); const root = d4.create("div").style("position", "relative"); const svg = root.append("figure").attr("id", "svg_contain"); svg.append(() => map_legend(colorBlind)).attr("transform", "translate(10,0)"); const svg_map = svg .append("svg") .attr("viewBox", [150, -250, width, 1150]) .attr("id", "svg_map"); const tooltip = root.append("div").attr("class", "cooltip"); //Agregar Paises al svg const countries = svg_map .append("g") .attr("stroke", "white") .attr("stroke-linejoin", "round") .selectAll("path") .data(world.features) .enter() .append("path") .attr("fill", function (d) { // if (!mode) { const index = countriesFiltered.indexOf(d.properties.iso_a3); if (index === -1) return getColorBlindRGB(colorBlind, "#EFEFEF"); // Si no está en countriesFil, color predeterminado const fillScale = d4 .scaleLinear() .domain([0, countriesFiltered.length]) // Rango de índices en countriesFil .range(["#EC5A47", "#F4BB21"]); // Rango de colores deseados return getColorBlindRGB(colorBlind, fillScale(index)) }) // else { // return countriesFil.includes(d.properties.iso_a3) || // !composite?.adaptation || // !composite?.mitigation // ? getColorBlind_Input(colorBlind, "purple") // : color1(getTrafficLight(d.properties.iso_a3), colorBlind, mode); // } // }) .attr("d", path) .on("mouseover", function (d) { let node = tooltip.node(); node.innerHTML = ""; if (countriesFiltered.includes(d.properties.iso_a3)) { tooltip.style("display", ""); this.classList.add("hovered"); d4.select(this).attr("stroke", "black").raise(); node.appendChild(getTooltipContents(d, colorBlind)); } }) .on("mousemove", function (d) { if (countriesFiltered.includes(d.properties.iso_a3)) { const rootBounds = d4 .select("#svg_contain") .node() .getBoundingClientRect(); const tooltipBounds = tooltip.node().getBoundingClientRect(); const mouseX = d4.event.pageX; const mouseY = d4.event.pageY - rootBounds.top + 20; const tooltipWidth = tooltipBounds.width; const containerWidth = root.node().offsetWidth; const screenWidth = window.innerWidth; const tooltipX = mouseX - 20; // posición predeterminada del tooltip const isSmallScreen = screenWidth <= 600; // Verificar si el cursor está en la mitad derecha o izquierda del contenedor const isCursorOnRightHalf = mouseX > containerWidth / 2; let tooltipLeft; if (isSmallScreen) { tooltipLeft = 20; } else { tooltipLeft = isCursorOnRightHalf ? mouseX - tooltipWidth + 20 : tooltipX - 20; } tooltip .style("top", mouseY + "px") .style("left", tooltipLeft + "px") .style("display", "block"); } }) .on("mouseout", function () { this.classList.remove("hovered"); d4.select(this).attr("stroke", null).lower(); tooltip.style("display", "none"); }); return root.node(); }3d:T9b7,insight_object = { const totalEmissions = 566.1; const totalVop = 22785.2; const dataIni = data_ghg.map(obj => ({ ...obj })); let dataTable = dataIni const countryFilter = countriesFiltered const selectedValue = country_select !== ""? dataIni.filter((d) => d.ISO3 === country_select)[0].country : undefined let totalData = { country: 'Total', "direct_emissions (Mt C02e)": 0, "indirect_emission(Mt C02e)": 0, "total_emissions(Mt C02e)": 0, "rural_pop (Millions)": 0, "VOP(Millons usd)": 0, "TLU(Millons)": 0, "Pasture_area(Millions Ha)": 0 }; if(countryFilter.length > 0){ dataTable = [] countryFilter.forEach(name => { const filteredData = dataIni.filter(ghg => ghg.ISO3 === name); dataTable = dataTable.concat(filteredData); }); } dataTable.forEach(entry => { delete entry.ISO2; // delete entry.ISO3; for (const key in entry) { if (key !== 'country' && entry[key] && entry[key] !== "-") { totalData[key] += parseFloat(entry[key]); } } }); dataTable.push(totalData); const countrySelect = selectedValue ? dataTable.find(country => country.country === selectedValue) : dataTable[0] const hazardTop = getTopHazards(dataTable[0]) const top_country = hazardTop.country console.log(hazardTop) const top_hazard = _lang(nbText.sections.leversOfChange.insights.hazard_defs[hazardTop.climate_hazards]) const top_haz_vop = parseFloat(hazardTop.value).toFixed(1) //USD Billion VoP` const LPStop = getTopLPS(countrySelect) const lps1 = LPStop[0].lps const lps2 = LPStop[1].lps || "" const lps3 = LPStop[2].lps || "" const vop_text = (totalData["VOP(Millons usd)"] / 1000 ).toFixed(1) // billion USD const people = totalData["rural_pop (Millions)"].toFixed(0) // million const emissions = totalData["total_emissions(Mt C02e)"].toFixed(0) //MT CO2e const country_selected = countrySelect.country const iso_selected = countrySelect.ISO3 const per_vop = ((countrySelect["VOP(Millons usd)"]/totalVop)*100).toFixed(0) //% const per_emi = ((countrySelect["total_emissions(Mt C02e)"]/totalEmissions)*100).toFixed(0) // % return { top_country: top_country, top_hazard: top_hazard, top_haz_vop: top_haz_vop, lps1: lps1, lps2: lps2, lps3: lps3, vop_text: vop_text, people: people, emissions: emissions, country_selected: country_selected, iso_selected: iso_selected, per_vop: per_vop, per_emi: per_emi } }3e:T4a1,dataTable_dev = { const totalEmissions = 566.1; const totalVop = 22785.2; const dataIni = data_ghg.map(obj => ({ ...obj })); let dataTable = dataIni const countryFilter = countriesFiltered const selectedValue = country_select !== ""? dataIni.filter((d) => d.ISO3 === country_select)[0].country : undefined let totalData = { country: 'Total', ISO3: "TOTAL", "direct_emissions (Mt C02e)": 0, "indirect_emission(Mt C02e)": 0, "total_emissions(Mt C02e)": 0, "rural_pop (Millions)": 0, "VOP(Millons usd)": 0, "TLU(Millons)": 0, "Pasture_area(Millions Ha)": 0 }; if(countryFilter.length > 0){ dataTable = [] countryFilter.forEach(name => { const filteredData = dataIni.filter(ghg => ghg.ISO3 === name); dataTable = dataTable.concat(filteredData); }); } dataTable.forEach(entry => { delete entry.ISO2; // delete entry.country; for (const key in entry) { if (key !== 'country' && key !== 'ISO3' && entry[key] && entry[key] !== "-") { totalData[key] += parseFloat(entry[key]); } } }); dataTable.push(totalData); return dataTable }3f:T476,createHtmlTable = (title) => { const tableContainer = d3 .create("div") .attr("id", "table_container") .style("overflow", "auto") .style("max-height", "900px") .style("margin-top", "10px"); const headerGhg = _lang( nbText.sections.leversOfChange.livestockProductionSystems.table.headers .ghgEmissions ); const headerExposure = _lang( nbText.sections.leversOfChange.livestockProductionSystems.table.headers .climateExposure ); tableContainer.html(`

${title}

${headerGhg}

${headerExposure}

`); const tabla = tableContainer.select("#main_table"); tabla .select("#second_head") .selectAll("th") .data(table_titles) .enter() .append("th") .append("h4") .text((d) => d); return tableContainer.node(); }40:T97e,doble_tittle_table = (data) => { const tableName = _lang(nbText.sections.leversOfChange.livestockProductionSystems.table.headers.country) createHtmlTable(tableName) const tableNode = createHtmlTable(tableName) // const tabla = d3.select("#main_table"); const tabla = d3.select(tableNode); // const tabla = d3.select("#main_table"); if(data.length > 0){ const tooltip = d3.select("body") .append("div") .style("opacity", 0) .style("position", "absolute") .style("background-color", "white") .style("padding", "10px 15px") .style("box-shadow", "rgba(149, 157, 165, 0.2) 0px 8px 24px") .style("border-radius", "12px") .style("z-index", 100) .style("font-size", "16px"); tabla.select(".body") .selectAll("tr") .data(data) .enter() .append("tr") .on("mouseover", function(event, d) { const country = d.country; if (country !== "Total") { const filteredData = data_lps.filter(obj => obj.country === country); tooltip.style("opacity", 1) .style("display", "block") .style("position", "fixed") .style("left", `${event.pageX + 10}px`) .style("top", `${event.pageY}px`) .style("box-shadow", "rgba(149, 157, 165, 0.2) 0px 8px 24px"); if(filteredData.length > 0){ const lps_data = filteredData[0].LSP.split(",").map((v) => _lang(nbText.general.lps[v])).join(", ") const constraints = `${_lang(nbText.general.admin0_ISO3[d.ISO3])}
${_lang(nbText.sections.leversOfChange.livestockProductionSystems.table.headers.livestockSystem)}
` + `${lps_data}
`; tooltip.html(constraints) } } }) .on("mouseout", function() { tooltip.style("opacity", 0) .style("display", "none") .style("box-shadow", "0") .html(""); }) .on("mousemove", function(event, d) { tooltip.style("left", `${event.pageX + 10}px`) // Adjust tooltip position .style("top", `${event.pageY}px`); }) .selectAll("td") .data(d => Object.values(d).slice(1,9)) .enter() .append("td") .text(d => !isNaN(parseFloat(d)) ? parseFloat(d).toFixed(1) : _lang(nbText.general.admin0_ISO3[d] ) || "-"); } return tableNode; }41:Tc97,doble_tittle_table1 = (lps_emissions, lps_hazards) => { const tableName = _lang( nbText.sections.leversOfChange.livestockProductionSystems.table.headers .livestockSystem ); const tableNode = createHtmlTable(tableName); // const tabla = d3.select("#main_table"); const tabla = d3.select(tableNode); // const tabla = d3.select("#main_table"); const body = tabla.select(".body"); const tooltip = d3 .select("body") .append("div") .style("opacity", 0) .style("position", "absolute") .style("background-color", "white") .style("padding", "10px 15px") .style("box-shadow", "rgba(149, 157, 165, 0.2) 0px 8px 24px") .style("border-radius", "12px") .style("z-index", 100) .style("font-size", "16px"); function format(str) { if (str !== "0" && str.trim() !== "") { let numero = parseFloat(str); if (!isNaN(numero)) { if (numero < 0.05) { return "< 0.05"; } else { return numero.toFixed(2); } } else { return "NaN"; } } else { return "0"; } } let tableBody = ""; for (const key in mapping_lps) { tableBody += `${_lang(nbText.general.lps[key])}`; mapping_lps[key].forEach((code) => { const emissions = lps_emissions.find((item) => item.lps === code) || {}; const hazards = lps_hazards.find((item) => item.lps === code) || {}; tableBody += `${_lang(nbText.general.lps[code])}`; tableBody += `${ emissions.direct_emissions ? format(emissions.direct_emissions) : "-" }`; tableBody += `${ emissions.indirect_emissions ? format(emissions.indirect_emissions) : "-" }`; tableBody += `${ emissions.total_emissions ? format(emissions.total_emissions) : "-" }`; tableBody += `${ hazards["rural_pop (millons)"] ? format(hazards["rural_pop (millons)"]) : "-" }`; tableBody += `${ hazards["VOP (millos usd)"] ? format(hazards["VOP (millos usd)"]) : "-" }`; tableBody += `${ hazards["TLU (millons))"] ? format(hazards["TLU (millons))"]) : "-" }`; tableBody += `${ hazards["pasture_area (millons)"] ? format(hazards["pasture_area (millons)"]) : "-" }`; }); } body.html(tableBody); body .selectAll("tr") .on("mouseover", function (event) { const id = d3.select(this).attr("id"); if (id && id !== "Other") { tooltip .style("opacity", 1) .style("display", "block") .style("left", `${event.pageX + 10}px`) .style("top", `${event.pageY}px`); tooltip.html(`${_lang(nbText.general.lps[id])}`); } }) .on("mouseout", function () { tooltip.style("opacity", 0).style("display", "none"); }) .on("mousemove", function (event) { tooltip .style("left", `${event.pageX + 10}px`) // Adjust tooltip position .style("top", `${event.pageY}px`); }); return tableNode; }42:T4f1,filterSolutions = { let select_species_notebook = solution_Selectors[1] let select_system_notebook = solution_Selectors[0] let filteredData = dataOption; // Verificar si al menos una opción está seleccionada en select_species_notebook const speciesSelected = select_species_notebook && select_species_notebook.length > 0; console.log(speciesSelected) // Verificar si al menos una opción está seleccionada en select_system_notebook const systemsSelected = select_system_notebook && select_system_notebook.length > 0; console.log(systemsSelected) // Filtrar los datos solo si al menos una opción está seleccionada en uno de los select if (speciesSelected && systemsSelected) { if (systemsSelected) { filteredData = filteredData.filter(d => { return select_system_notebook.every(s => d[_lang(solution_table_columns_translations.system)].includes(s)); }); } if (speciesSelected) { filteredData = filteredData.filter(d => { return select_species_notebook.every(s => d[_lang(solution_table_columns_translations.species)].includes(s)); }); } } else { // Si no hay opciones seleccionadas, mantener los datos sin filtrar filteredData ={}; } return filteredData }43:T90e,createSolutionTable = (filteredData) => { // Seleccionar el contenedor de tabla const tableContainer = d3.create("div") .attr("id", "table_container") // .style("overflow", "auto") // .style("max-height", "727px") .style("margin-top", "10px");//.select("#table_container_options"); // Si el contenedor no existe, crear uno nuevo if (tableContainer.empty()) { tableContainer = d3.select("#table_options") .append("div") .attr("id", "table_container_options"); } else { // Vaciar el contenido anterior del contenedor tableContainer.html(""); } // Crear la tabla dentro del contenedor const table = tableContainer.append("table"); // Encabezados de la tabla const headers = [ _lang(nbText.sections.scalableSolutions.table.headers.option), _lang(nbText.sections.scalableSolutions.table.headers.priority), _lang(nbText.sections.scalableSolutions.table.headers.description), ]; table.append("thead") .append("tr") .selectAll("th") .data(headers) .enter() .append("th") .text(d => d); // Verificar si filteredData está vacío if (Object.keys(filteredData).length === 0) { const noDataMessage = table.append("tbody") .append("tr") .append("td") .attr("colspan", 3) // Colspan para ocupar todas las columnas .text("We could not find information for the values you selected. Please try with other parameters"); return; // Terminar la función si no hay datos } // Filas de la tabla const rows = table.append("tbody") .selectAll("tr") .data(filteredData) .enter() .append("tr"); // Celdas de la tabla rows.selectAll("td") .data(d => [d.Option, d[_lang(solution_table_columns_translations.priority)], d[_lang(solution_table_columns_translations.description)]]) .enter() .append("td") .html(function(d) { // Verificar si la descripción contiene un hipervínculo if (/]*?\s+)?href=(["'])(.*?)\1/i.test(d)) { return d; // Si contiene un hipervínculo, mantenerlo como está } else { // Si no contiene un hipervínculo, agregar etiqueta si es necesario return d.replace(/\b(https?:\/\/\S+)/gi, '$1'); } }); return tableContainer.node() } 44:T48c,summary_object = { const countryOptions = countriesFiltered const countryArray = []; countryOptions.forEach(option => { if (option !== "") { // Asegurarse de no incluir la opción vacía countryArray.push(option); } }); const dataFiltered = dataSummary.filter(d => countryArray.includes(d.ISO3)); const sumPopulationMillion = dataFiltered.reduce((acc, obj) => acc + parseFloat(obj['rural_pop (Millions)']), 0); const sumPopulationBillion = sumPopulationMillion/1000; const sumVOPMillion = dataFiltered.reduce((acc, obj) => acc + parseFloat(obj['VOP(Millons usd)']), 0); const sumVOPBillion = sumVOPMillion/1000; const sumGHG = dataFiltered.reduce((acc, obj) => acc + parseFloat(obj['total_emissions(Mt C02e)']), 0); const firstCountry = countryArray.shift(); return { firstCountry: firstCountry, sumPopulationMillion: sumPopulationMillion, sumPopulationBillion: sumPopulationBillion, sumVOPMillion: sumVOPMillion, sumVOPBillion: sumVOPBillion, sumGHG: sumGHG, countryArray: countryArray } }45:T4157,styling = { const ns = Inputs.text().classList?.[0]; return htl.html`` }46:T4cf,function tocOneliner({ selector = "h1", // selectors to include (can comma-separate, like "h1,h2,h3") heading = "In this notebook", // heading for ToC delim = ' | ', // delimiter between links skip = [], // text content for headers to exclude } = {}) { // return a one-liner table of contents // allow for skips // modified from https://observablehq.com/@mbostock/toc return Generators.observe(notify => { let headings = []; function observed() { let h = Array.from(document.querySelectorAll(selector)); h = h.filter((d) => !skip.includes(d.textContent)) if (h.length !== headings.length || h.some((h, i) => headings[i] !== h)) { notify(html`${heading}
${Array.from(headings = h, (h, i) => { const end = i === headings.length - 1 return Object.assign( html`${DOM.text(h.textContent)}${end ? '' : delim}`, {onclick: e => (e.preventDefault(), h.scrollIntoView())} ); })}`); } } const observer = new MutationObserver(observed); observer.observe(document.body, {childList: true, subtree: true}); observed(); return () => observer.disconnect(); }); }47:Te0c2,nbText = { return { legends: { language: { en: "language", fr: "langue" }, toc: { en: "in this notebook", fr: "dans ce notebook" }, ssa: { en: "Sub-Saharan Africa", fr: "d'Afrique subsaharienne" }, colorblind: { label: { en: "Do you see colors clearly or have trouble distinguishing them?", fr: "Voyez-vous clairement les couleurs ou avez-vous du mal à les distinguer?" }, values: { non: { en: "None", fr: "Aucun" }, deu: { en: "Deuteranopia", fr: "Deutéranopie" }, pro: { en: "Protanopia", fr: "Protanopie" }, tri: { en: "Tritanopia", fr: "Tritanopie" } } } }, sections: { quickInsightsGeneral: { header: { en: ({ selection } = {}) => md`Quick Insights for ${selection}`, fr: ({ selection } = {}) => md`Aperçu Rapide pour ${selection}` } }, overview: { title: { en: `Overview`, fr: `Vue d’Ensemble` }, intro: { en: md`No conceivable Global Future can neglect livestock production. Livestock production systems are the main source of income and livelihood for 300 million people in sub-Saharan Africa. Animals generate revenue through milk and meat production, provide draught power for on-farm activities, and act as insurance when everything else fails. Livestock are at risk from a plethora of climate hazards, and they also generate greenhouse gas emissions that warm the planet. Given livestock are both at risk from and a source of climate change, where should investment be directed for impact?`, fr: md`Aucun avenir mondial imaginable ne peut négliger la production de bétail. Les systèmes de production de bétail constituent la principale source de revenus et de subsistance pour 300 millions de personnes en Afrique subsaharienne. Les animaux génèrent des revenus grâce à la production de lait et de viande, fournissent de la puissance de traction pour les activités agricoles sur place, et servent d'assurance lorsque tout le reste échoue. Les animaux sont menacés par une multitude de risques climatiques, et ils produisent également des émissions de gaz à effet de serre qui réchauffent la planète. Étant donné que le bétail est à la fois en danger par et une source de changement climatique, où les investissements doivent-ils être dirigés pour avoir un impact?` }, inspiration: { en: md`This spotlight is inspired by the Nature Sustainability Publication Priority areas for investment in more sustainable and climate-resilient livestock systems.`, fr: md`Ce *spotlight* est inspiré par la publication de Nature Sustainability sur les zones prioritaires pour l'investissement dans des systèmes de bétail plus durables et résilients au climat..` } }, livestockExplosion: { title: { en: `The Livestock Explosion`, fr: `L’explosion du Bétail` }, intro: { en: `The visualization below helps you explore historical **(2010 - 2021)** trends in livestock population, value of production (VoP), and greenhouse gas (GHG) emissions. These trends give a measure of the rapid pace of growth of the sector, and therefore its importance for people and the environment.`, fr: `La visualisation ci-dessous vous aide à explorer les tendances historiques **(2010 - 2021)** de la population de bétail, de la valeur de la production (VDP) et des émissions de gaz à effet de serre (GES). Ces tendances donnent une mesure de la rapidité de croissance du secteur, et donc de son importance pour les personnes et l'environnement.` }, chart: { legend: { "breedinganimals": {en: 'Breeding animals', fr: "Animaux d'élevage"}, "marketanimals": {en: 'Market animals', fr: "Animaux de marché"}, "grazinganimals": {en: 'Grazing animals', fr: "Animaux de pâturage"}, "poultry": {en: 'Poultry', fr: "Volaille"}, "workinganimals": {en: 'Working animals', fr: "Animaux de travail"} }, labels: { year: { en: "Year", fr: "Année" }, category: { en: "Category", fr: "Catégorie" } }, inputLabel: { en: "Variable", fr: "Variable" }, variables: { stock: { label: { en: "Stock", fr: "Stock" }, tip: { en: "Stock (million)", fr: "Stock (millions)" } }, ghg: { label: { en: "GHG Emissions", fr: "Émissions de GES" }, tip: { en: "Emissions (MtCo2e)", fr: "Émissions (MtCo2e)" } }, vop: { label: { en: "Value of production", fr: "Valeur de la production" }, tip: { en: "VOP (billion usd)", fr: "VDP (milliard de dollars)" } } } }, download: { labelFunc: { en: (d) => `Download ${d} Data`, fr: (d) => `Télécharger les Données ${d}` } }, insights: { livestock: { en: ({ selection, year, population, percent, yearSince } = {}) => htl.html`${selection}’s livestock population in ${year} is ${population} billion, and has grown by ${percent}% since ${yearSince}.`, fr: ({ selection, year, population, percent, yearSince } = {}) => htl.html`Le bétail de ${selection} au ${year} s’élève à ${population} milliards et a augmenté de ${percent}% depuis ${yearSince}.` }, vop: { en: ({ selection, year, population, percent, yearSince } = {}) => htl.html`${selection}’s value of production in ${year} is ${population} billion, and has grown by ${percent}% since ${yearSince}.`, fr: ({ selection, year, population, percent, yearSince } = {}) => htl.html`La valeur de la production de ${selection} en ${year} est de ${population} milliards de dollars et a augmenté de ${percent}% depuis ${yearSince}.` }, ghg: { en: ({ mult } = {}) => htl.html`The explosion in livestock numbers comes at the expense of a growth in GHG emissions of ${mult} times in the same period.`, fr: ({ mult } = {}) => htl.html`L’explosion du bétail se fait au détriment d’une croissance des émissions de GES de ${mult} fois sur la même période.` } } }, leversOfChange: { title: { en: "Countries As Levers Of Change", fr: "Les Pays Comme Leviers de Changement" }, intro: { en: `Livestock’s exposure to climate hazards and GHG emissions totals imply that climate actions need to address both adaptation and mitigation outcomes. Investing in actions begs the question of where those investments should be targeted. This section explores geographic priorities for investment in climate action for livestock systems. Hover over the selected priorities to get an overview of emissions totals and hazard exposure.`, fr: `L'exposition du bétail aux aléas climatiques et le total des émissions de GES impliquent que les actions climatiques doivent aborder à la fois les résultats d'adaptation et d'atténuation. Investir dans des actions soulève la question de savoir où ces investissements devraient être ciblés. Cette section explore les priorités géographiques pour l'investissement dans l'action climatique pour les systèmes de bétail. Survolez les priorités sélectionnées pour obtenir un aperçu du total des émissions et de l'exposition aux risques.` }, inputs: { radio: { label: { en: "Configuration", fr: "Configuration" }, values: { adap: { en: "Adaptation only", fr: "Adaptation uniquement" }, adap_mit: { en: "Adaptation and mitigation equally", fr: "Adaptation et atténuation à parts égales" }, mit: { en: "Mitigation only", fr: "Atténuation uniquement" } } }, num: { label: { en: "Maximum number of priorities", fr: "Nombre maximum de priorités" } } }, chart: { map: { legend: { title: { en: "Prioritization", fr: "Priorisation" }, lo: { en: "Low", fr: "Faible" }, md: { en: "Medium", fr: "Moyen" }, hi: { en: "High", fr: "Élevé" } }, tooltip: { headers: { hazards: { en: "Hazards", fr: "Dangers" }, emissions: { en: "Emissions", fr: "Émissions" } }, data: { hazards: { tlu: { name: { en: "Tropical livestock units", fr: "Unités de bétail tropicales" }, unit: { en: "Million", fr: "Millions" } }, pastureArea: { name: { en: "Pasture area", fr: "Superficie de pâturage" }, unit: { en: "Million ha", fr: "Millions ha" } }, popRural: { name: { en: "Rural population", fr: "Population rurale" }, unit: { en: "Million people", fr: "Millions de personnes" } }, vop: { name: { en: "Value of production", fr: "Valeur de la production" }, unit: { en: "Million USD", fr: "Millions de dollars" } } }, emissions: { unit: { en: "Mt CO2e", fr: "Mt CO2e" }, values: { bovine: { en: "Bovine", fr: "Bovine" }, pig: { en: "Pig", fr: "Cochon" }, poultry: { en: "Poultry", fr: "Volaille" }, shoat: { en: "Shoat", fr: "Shoat" }, flPasture: { en: "Forest loss to pasture", fr: "Perte de forêt au profit des pâturages" }, flSoy: { en: "Forest loss to soy", fr: "Perte de forêt à cause du soja" } } } } } }, download: { categories: { en: "Download Data Categories", fr: "Télécharger Données sur les Catégories" }, climate: { en: "Download Data Climate Hazard", fr: "Télécharger les Données sur les Aléas Climatiques" }, emissions: { en: "Download Data Emissions", fr: "Télécharger les Données sur les Émissions" } } }, insights: { title: { en: "Quick Insights For The Identified Priority Countries", fr: "Aperçus rapides pour les pays prioritaires identifiés" }, investmentPriorities: { en: ({ percAdaptation, percMitigation, countryCount, livestockProd, peopleExposed, ggEmissions } = {}) => `The selected weighting of **${percAdaptation}%** adaptation, **${percMitigation}%** mitigation, and number of geographies selected, result in investment priorities that span **${countryCount}** countries and encompass **${livestockProd} billion USD** in livestock production. Climate actions in these countries can benefit **${peopleExposed} million** people exposed to hazards, and contribute to reducing some of the **${ggEmissions} MT CO2e** in greenhouse gas emissions.`, fr: ({ percAdaptation, percMitigation, countryCount, livestockProd, peopleExposed, ggEmissions } = {}) => `La pondération sélectionnée de **${percAdaptation}%** d'adaptation, **${percMitigation}%** d'atténuation et le nombre de zones géographiques sélectionnées aboutissent à des priorités d'investissement qui couvrent **${countryCount}** pays et englobent **${livestockProd} milliards de dollars** dans la production animale. Les actions climatiques dans ces pays peuvent bénéficier à **${peopleExposed} millions** de personnes exposées à des aléas et contribuer à réduire une partie des **${ggEmissions} MT CO2e** des émissions de gaz à effet de serre.` }, mostCritical: { en: ({ lever, percVop, percEmissions } = {}) => `The most critical lever of change in the priority list is **${lever}**, which constitutes **${percVop}%** of exposed value of production and **${percEmissions}%** of emissions in relation to the overall sub-Saharan Africa total.`, fr: ({ lever, percVop, percEmissions } = {}) => `Le levier de changement le plus critique dans la liste des priorités est **${lever}**, qui constitue **${percVop}%** de la valeur exposée de la production et **${percEmissions}%** des émissions par rapport au total global de l’Afrique subsaharienne.` }, countrySystems: { en: ({ first, second, third } = {}) => `In this country, the systems that have the greatest exposure and emissions, and should therefore be the highest priorities are **${first}**, followed by **${second}**, and **${third}**.`, fr: ({ first, second, third } = {}) => `Dans ce pays, les systèmes les plus exposés et les plus émetteurs, et qui devraient donc être les plus prioritaires, sont **${first}**, suivis de **${second}** et **${third}**.` }, sigHazard: { en: ({ location, hazard, vop } = {}) => `The most significant hazard(s) in **${location}** is **${hazard}** potentially impacting **${vop} USD billion VoP**.`, fr: ({ location, hazard, vop } = {}) => `Le(s) danger(s) le plus important(s) **${location}** est **${hazard}**, avec un impact potentiel de **${vop} milliard de dollars de VDP**.` }, hazard_defs: { "Thi": { en: "Livestock heat stress", fr: "Le stress thermique du bétail" }, "RF": { en: "Extreme or high rainfall variability", fr: "La variabilité extrême ou élevée des précipitations" }, "D": { en: "Drought", fr: "La sécheresse" }, "F": { en: "Flooding", fr: "L'inondation" }, "CV": { en: "Rainfall variability", fr: "La variabilité des précipitations" }, "ExCV": { en: "Extremely high rainfall variability", fr: "La variabilité extrêmement élevée des précipitations" }, "HCV": { en: "High rainfall variability", fr: "La variabilité élevée des précipitations" }, "CV+D": { en: "Rainfall variability and drought", fr: "La variabilité des précipitations et la sécheresse" }, "CV+D+F": { en: "Rainfall variability, drought and flooding", fr: "La variabilité des précipitations, la sécheresse et l'inondation" }, "CV+F": { en: "Rainfall variability and flooding", fr: "La variabilité des précipitations et l'inondation" }, "CV+Thi": { en: "Rainfall variability and livestock heat stress", fr: "La variabilité des précipitations et le stress thermique du bétail" }, "CV+Thi+D": { en: "Rainfall variability, livestock heat stress and drought", fr: "La variabilité des précipitations, le stress thermique du bétail et la sécheresse" }, "CV+Thi+D+F": { en: "Rainfall variability, livestock heat stress, drought and flooding", fr: "La variabilité des précipitations, le stress thermique du bétail, la sécheresse et l'inondation" }, "CV+Thi+F": { en: "Rainfall variability, livestock heat stress and flooding", fr: "La variabilité des précipitations, le stress thermique du bétail et l'inondation" }, "D+F": { en: "Drought and flooding", fr: "La sécheresse et l'inondation" }, "Thi+D": { en: "Livestock heat stress and drought", fr: "Le stress thermique du bétail et la sécheresse" }, "Thi+D+F": { en: "Livestock heat stress, drought and flooding", fr: "Le stress thermique du bétail, la sécheresse et l'inondation" }, "Thi+F": { en: "Livestock heat stress and flooding", fr: "Le stress thermique du bétail et l'inondation" } } }, livestockProductionSystems: { header: { en: `Livestock Production Systems Within Priority Countries`, fr: `Systèmes de Production Animale Dans les Pays Prioritaires` }, tableIntro: { en: `Explore the overall country ranking and their livestock production systems using the table below.`, fr: `Explorez le classement général des pays et leurs systèmes de production animale à l’aide du tableau ci-dessous.` }, countryInput: { label: { en: "Country", fr: "Pays" } }, table: { headers: { country: { en: "Country", fr: "Pays" }, ghgEmissions: { en: "GHG Emissions", fr: "Émissions de GES" }, livestockSystem: { en: "Livestock production system", fr: "Système de production animale" }, climateExposure: { en: "Climate Hazard Exposure", fr: "Exposition aux Aléas Climatiques" }, emissionsDirect: { en: "Direct emissions (Mt CO2e)", fr: "Émissions directes (Mt CO2e)" }, emissionsIndirect: { en: "Indirect emissions (Mt CO2e)", fr: "Émissions indirectes (Mt CO2e)" }, emissionsTotal: { en: "Total emissions (Mt CO2e)", fr: "Émissions totales (Mt CO2e)" }, popRural: { en: "Rural population (Million people)", fr: "Population rurale (Millions de personnes)" }, vop: { en: "Value of production (Million USD)", fr: "Valeur de la production (Millions de dollars)" }, tlu: { en: "Tropical livestock units (Million)", fr: "Unités de bétail tropicales (Millions)" }, pastureArea: { en: "Pasture area (Million ha)", fr: "Superficie de pâturage (Millions ha)" } } }, download: { ghg: { en: "Download GHG Data", fr: "Télécharger les Données sur les GES" }, lps_hazards: { en: "Download LPS Hazards Data", fr: "Télécharger les Données sur les Dangers du LPS" }, lps_emissions: { en: "Download LPS Emissions Data", fr: "Télécharger les Données sur les Émissions LPS" } } } }, scalableSolutions: { title: { en: `Scalable Solutions`, fr: `Solutions Évolutives` }, intro: { en: `Many actions exist that would be no-regret investments, delivering benefits for both adaptation and mitigation. However, why are they not yet reaching scale? This section helps explore some key adaptation and mitigation actions and their typical adoption constraints.`, fr: `Il existe de nombreuses actions qui constitueraient des investissements sans regret, apportant des bénéfices tant pour l'adaptation que pour l'atténuation. Cependant, pourquoi ne sont-elles pas encore déployées à grande échelle ? Cette section permet d'explorer certaines actions clés d'adaptation et d'atténuation ainsi que les contraintes habituelles à leur adoption.` }, table: { title: { en: "Hazard Selectors (One of each must be selected)", fr: "Sélecteurs de danger (un de chaque doit être sélectionné)" }, inputs: { selectLivestock: { label: { en: "Livestock System", fr: "Système d'Élevage" }, placeholder: { en: "Select Livestock System...", fr: "Sélectionnez le système d'élevage..." } }, selectSpecies: { label: { en: "Species", fr: "Espèces" }, placeholder: { en: "Select species...", fr: "Sélectionner une espèce..." } } }, headers: { option: { en: "Option", fr: "Option" }, priority: { en: "Priority", fr: "Priorité" }, description: { en: "Description", fr: "Description" } } }, download: { en: "Download Data", fr: "Télécharger les Données" } }, summary: { title: { en: `Summary`, fr: `Résumé` }, intro: { en: `The livestock sector must transform in sub-Saharan Africa, if the region is to meet Sustainable Development Goals (SDGs). Critically, the livestock sector affects 10 of 17 SDGs.`, fr: `Le secteur de l’élevage doit se transformer en Afrique subsaharienne si la région veut atteindre les objectifs de développement durable (ODD). De manière cruciale, le secteur de l’élevage affecte 10 des 17 ODD.` }, countryListFunc: { en: ({ num, multiCountryString, topCountryString, multiString, severalOthersString } = {}) => `Based on the analysis above, ${multiCountryString} ${topCountryString}${multiString}${severalOthersString}.`, fr: ({ num, multiCountryString, topCountryString, multiString, severalOthersString } = {}) => `Sur la base de l'analyse ci-dessus, ${multiCountryString} ${topCountryString}${multiString}${severalOthersString}.` }, countryListSupport: { topStringFunc: { en: ({ num } = {}) => `of the top **${num}** countries,`, fr: ({ num } = {}) => `parmi les **${num}** principaux pays` }, topCountryFunc: { en: ({ top } = {}) => `**${top}** is the most critical lever of change in the region`, fr: ({ top } = {}) => `**${top}** est le levier de changement le plus critique dans la région` }, followedBy: { en: `, followed by`, fr: `, suivi par` }, severalOthers: { en: ` **and several others**`, fr: ` **et plusieurs autres**` } }, outroFunc: { en: ({ people, livestock, footprint } = {}) => `Catalyzing climate action in these countries could help address adaptation for **${people} million** people, avoid devastating impacts that could affect some of the **${livestock} billion** in livestock production, while contributing to reducing livestock’s carbon footprint of **${footprint} MT CO2e**.`, fr: ({ people, livestock, footprint } = {}) => `Catalyser l’action climatique dans ces pays pourrait contribuer à l’adaptation pour **${people} millions** de personnes, éviter les impacts dévastateurs qui pourraient affecter une partie des **${livestock} milliards** de production animale, tout en contribuant à réduire l’empreinte carbone de l’élevage de **${footprint} MT CO2e**.` } }, methods: { title: { en: htl.html`Methods & Sources`, fr: htl.html`Méthodes & Sources` }, sections: { datasets: { title: { en: htl.html`Datasets`, fr: htl.html`Ensembles de Données` }, body: { en: htl.html`The data and methods used here are all documented by Bonilla-Cedrez et al. (2023). Here we provide a summarized version, and encourage the readers to read the original study. The data and code for the analysis of the original study is available in GitHub. The original study and this Spotlight were conducted in collaboration with the CGIAR Livestock & Climate Initiative.`, fr: htl.html`Les données et méthodes utilisées ici sont toutes documentées par Bonilla-Cedrez et al. (2023). Nous fournissons ici une version résumée et encourageons les lecteurs à lire l’étude originale. Les données et le code pour l'analyse de l'étude originale sont disponibles sur GitHub. L'étude originale et ce Spotlight ont été menés en collaboration avec l'Initiative CGIAR Livestock & Climate.` } }, livestockProdSystems: { title: { en: htl.html`Livestock production systems`, fr: htl.html`Systèmes de production animale` }, body: { en: htl.html`We used the livestock production system classification from the Food and Agriculture Organization of the United Nations (FAO) (Robinson et al., 2011). This classification divides livestock production systems into landless, rangeland, mixed irrigated, and mixed rainfed systems. Rangelands, and the mixed systems are each divided by agroecology into arid, hyperarid, temperate, and humid. This gives rise to twelve categories (the category landless is not considered for the analysis) for analysis.`, fr: htl.html`Nous avons utilisé la classification des systèmes de production animale de l'Organisation des Nations Unies pour l'alimentation et l'agriculture (FAO) (Robinson et al., 2011). Cette classification divise les systèmes de production animale en systèmes sans terre, en parcours, irrigués mixtes et pluviaux mixtes. Les parcours et les systèmes mixtes sont chacun divisés par l'agroécologie en arides, hyperarides, tempérés et humides. Cela donne lieu à douze catégories (la catégorie sans terre n'est pas prise en compte pour l'analyse).` } }, exposureData: { title: { en: htl.html`Exposure data`, fr: htl.html`Données d'exposition` }, body: { en: htl.html`Exposure was represented by the total value of production, total rural population, pasture area, and Total Livestock Units (TLUs). TLU values were computed using data from the Gridded Livestock of the World database (GLW version 3).`, fr: htl.html`L'exposition était représentée par la valeur totale de la production, la population rurale totale, la superficie des pâturages et le nombre total d'unités de bétail (UBT). Les valeurs TLU ont été calculées à l'aide des données de la base de données Gridded Livestock of the World (GLW version 3).` } }, hazardData: { title: { en: htl.html`Hazard data`, fr: htl.html`Données sur les aléas` }, body: { en: htl.html`This notebook uses six climate hazard data layers, namely, rainfall variability, heat stress, flooding risk, and risk of drought. Rainfall variability is represented by the coefficient of variation of annual mean rainfall (15–30% = highly variable; >30% = extremely variable) computed using rainfall data from the Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) dataset. Areas of heat stress were defined as having thermal stress with a Thermal Humidity Index (THI) of ≥79, with THI data derived from Thornton et al. (2021). To define areas at risk of flooding, we used the UN Environment Programme–Division of Early Warning and Assessment–GRID-Europe dataset, in which flooding risk is ranked from 0 (no risk) to 5 (extreme). Areas at risk of drought were defined as having more than 25 days without rain per month on average based on historical rainfall records from CHIRPS.`, fr: htl.html`Ce notebook utilise six couches de données sur les risques climatiques, à savoir la variabilité des précipitations, le stress thermique, le risque d'inondation et le risque de sécheresse. La variabilité des précipitations est représentée par le coefficient de variation des précipitations moyennes annuelles (15 à 30 % = très variable ; > 30 % = extrêmement variable) calculé à l'aide des données pluviométriques de l'ensemble de données sur les précipitations infrarouges avec stations du Climate Hazards Group (CHIRPS). Les zones de stress thermique ont été définies comme présentant un stress thermique avec un indice d'humidité thermique (THI) ≥79, les données THI étant dérivées de Thornton et al. (2021). Pour définir les zones à risque d'inondation, nous avons utilisé l'ensemble de données GRID-Europe du Programme des Nations Unies pour l'environnement – Division de l'alerte précoce et de l'évaluation – dans lequel le risque d'inondation est classé de 0 (aucun risque) à 5 (extrême). Les zones à risque de sécheresse ont été définies comme ayant plus de 25 jours sans pluie par mois en moyenne sur la base des enregistrements de précipitations historiques du CHIRPS.` } }, povertyData: { title: { en: htl.html`Poverty data`, fr: htl.html`Données sur la pauvreté` }, body: { en: htl.html`National-level poverty headcount ratios at US$1.90 per day at 2021 international prices were gathered from The World Bank indicators database (World Bank Maps).`, fr: htl.html`Les ratios de pauvreté au niveau national, à 1,90 USD par jour aux prix internationaux de 2021, ont été collectés à partir de la base de données d'indicateurs de la Banque mondiale (World Bank Maps).` } }, greenhouseEmissionsData: { title: { en: htl.html`Greenhouse gas emissions data`, fr: htl.html`Données sur les émissions de gaz à effet de serre` }, body: { en: htl.html`Greenhouse gas emissions, totals of livestock, and value of production per year for the period 2010-2021 were all gathered from FAOSTAT, and used to produce the stacked line plot in the first section of this notebook. For the remaining sections, total livestock emissions by geography were computed as the sum of direct and estimated emissions from deforestation. Direct emissions data come from Herrero et al. (2013) and are for the year 2010, updated to 2019 using FAOSTAT. Emissions linked to deforestation combined above- and below-ground carbon biomass data from Soto-Navarro et al. (2020), tree cover data (Hansen et al., 2013), and commodity-linked deforestation data (for soybean and pasture) from . We included deforestation due to soybeans given that a substantial portion of soybean production is used for livestock feed.`, fr: htl.html`Les émissions de gaz à effet de serre, le total du bétail et la valeur de la production annuelle pour la période 2010-2021 ont tous été collectés à partir de FAOSTAT et utilisés pour produire le graphique linéaire empilé dans la première section de ce cahier. Pour les sections restantes, les émissions totales du bétail par géographie ont été calculées comme la somme des émissions directes et estimées dues à la déforestation. Les données sur les émissions directes proviennent de Herrero et al. (2013) et concernent l’année 2010, mis à jour jusqu’en 2019 à l’aide de FAOSTAT. Les émissions liées à la déforestation combinaient les données sur la biomasse de carbone aérienne et souterraine de Soto-Navarro et al. (2020), les données sur la couverture arborée (Hansen et al., 2013), et les données sur la déforestation liée aux produits de base (pour le soja et les pâturages) de Goldman et al. (2020). Nous avons inclus la déforestation due au soja étant donné qu'une part substantielle de la production de soja est utilisée pour l'alimentation du bétail.` } }, boundaries: { title: { en: htl.html`Boundaries`, fr: htl.html`Délimitations` }, body: { en: htl.html`Administrative areas used in this notebook come from geoBoundaries 6.0.0. The gbHumanitarian boundaries are used and if not available then the gbOpen boundaries are substituted.`, fr: htl.html`Les zones administratives utilisées dans ce bloc-notes proviennent de geoBoundaries 6.0.0. Les limites gbHumanitarian sont utilisées et si elles ne sont pas disponibles, les limites gbOpen sont remplacées.` } }, adaptationOptions: { title: { en: htl.html`Adaptation and mitigation options`, fr: htl.html`Options d’adaptation et d’atténuation` }, body: { en: htl.html`Adaptation and mitigation options were compiled through literature review and expert input.`, fr: htl.html`Les options d'adaptation et d'atténuation ont été compilées grâce à une revue de la littérature et à la contribution d'experts.` } }, methods: { title: { en: htl.html`Methods`, fr: htl.html`Méthodologie` } }, prioritizationAnalysis: { title: { en: htl.html`Prioritization analysis`, fr: htl.html`Analyse de priorisation` }, body: { en: htl.html`All indicators were normalized by dividing the value of each indicator per country by the maximum value across all considered countries to rank countries and visualize adaptation and mitigation indicators. Each normalized exposure indicator was then weighted and summed, creating a unique adaptation index. Adaptation indicators were four: (i) TLUs exposed to climate hazards, (ii) rural population exposed to climate hazards, (iii) value of production exposed to climate hazards, and (iv) pasture area exposed to climate hazards. For the case of mitigation, each indicator corresponding to emissions was normalized by dividing by the maximum value across geographies. A total of six individual indicators were considered, namely, emissions from bovine, pigs, poultry, shoats, forest loss to pasture, and forest loss to soybean. In the prioritization analysis, a weight factor is considered that shifts the relative importance of adaptation and mitigation.`, fr: htl.html`Tous les indicateurs ont été normalisés en divisant la valeur de chaque indicateur par pays par la valeur maximale pour tous les pays considérés afin de classer les pays et de visualiser les indicateurs d'adaptation et d'atténuation. Chaque indicateur d'exposition normalisé a ensuite été pondéré et additionné, créant ainsi un indice d'adaptation unique. Les indicateurs d'adaptation étaient au nombre de quatre : (i) les UGT exposées aux aléas climatiques, (ii) la population rurale exposée aux aléas climatiques, (iii) la valeur de la production exposée aux aléas climatiques et (iv) la superficie des pâturages exposée aux aléas climatiques. Dans le cas de l’atténuation, chaque indicateur correspondant aux émissions a été normalisé en divisant par la valeur maximale selon les zones géographiques. Au total, six indicateurs individuels ont été pris en compte, à savoir les émissions provenant des bovins, des porcs, de la volaille, des chevreuils, la perte de forêt au profit des pâturages et la perte de forêt au profit du soja. Dans l’analyse de priorisation, un facteur de pondération est pris en compte, qui modifie l’importance relative de l’adaptation et de l’atténuation.` } }, references: { title: { en: htl.html`References`, fr: htl.html`Les références` }, body: { en: htl.html`

Bonilla-Cedrez, C., Steward, P., Rosenstock, T.S., Thornton, P.K., Arango, J., Kropff, M., and Ramirez-Villegas, J. 2023. Priority areas for investment in more sustainable and climate-resilient livestock systems. Nature Sustainability, 6, 1279–1286. https://doi.org/10.1038/s41893-023-01161-1

Goldman, E., Weisse, M. J., Harris, N. & Schneider, M. (2020) Estimating the Role of Seven Commodities in Agriculture-Linked Deforestation: Oil Palm, Soy, Cattle, Wood Fiber, Cocoa, Coffee, and Rubber. World Resources Institute.

Hansen, M. C. et al. (2013) High-resolution global maps of 21st-century forest cover change. Science 342, 850–853. https://doi.org/10.1126/science.1244693

Herrero, M. et al. (2013) Biomass use, production, feed efficiencies, and greenhouse gas emissions from global livestock systems. Proc. Natl Acad. Sci. USA 110, 20888–20893. https://doi.org/10.1073/pnas.1308149110

Robinson TP, Thornton PK, Franceschini G, Kruska RL, Chiozza F, et al. (2011) Global livestock production systems. Rome: Food and Agriculture Organization of the United Nations (FAO) and International Livestock Research Institute (ILRI). pp. 152.

Soto-Navarro, C. et al. (2020) Mapping co-benefits for carbon storage and biodiversity to inform conservation policy and action. Phil. Trans. R. Soc. B Biol. Sci. 375, 20190128. https://doi.org/10.1098/rstb.2019.0128

Thornton, P., Nelson, G., Mayberry, D. & Herrero, M. (2021) Increases in extreme heat stress in domesticated livestock species during the twenty‐first century. Glob. Change Biol. 27, 5762–5772. https://doi.org/10.1111/gcb.15825

`, fr: htl.html`

Bonilla-Cedrez, C., Steward, P., Rosenstock, T.S., Thornton, P.K., Arango, J., Kropff, M., and Ramirez-Villegas, J. 2023. Priority areas for investment in more sustainable and climate-resilient livestock systems. Nature Sustainability, 6, 1279–1286. https://doi.org/10.1038/s41893-023-01161-1

Goldman, E., Weisse, M. J., Harris, N. & Schneider, M. (2020) Estimating the Role of Seven Commodities in Agriculture-Linked Deforestation: Oil Palm, Soy, Cattle, Wood Fiber, Cocoa, Coffee, and Rubber. World Resources Institute.

Hansen, M. C. et al. (2013) High-resolution global maps of 21st-century forest cover change. Science 342, 850–853. https://doi.org/10.1126/science.1244693

Herrero, M. et al. (2013) Biomass use, production, feed efficiencies, and greenhouse gas emissions from global livestock systems. Proc. Natl Acad. Sci. USA 110, 20888–20893. https://doi.org/10.1073/pnas.1308149110

Robinson TP, Thornton PK, Franceschini G, Kruska RL, Chiozza F, et al. (2011) Global livestock production systems. Rome: Food and Agriculture Organization of the United Nations (FAO) and International Livestock Research Institute (ILRI). pp. 152.

Soto-Navarro, C. et al. (2020) Mapping co-benefits for carbon storage and biodiversity to inform conservation policy and action. Phil. Trans. R. Soc. B Biol. Sci. 375, 20190128. https://doi.org/10.1098/rstb.2019.0128

Thornton, P., Nelson, G., Mayberry, D. & Herrero, M. (2021) Increases in extreme heat stress in domesticated livestock species during the twenty‐first century. Glob. Change Biol. 27, 5762–5772. https://doi.org/10.1111/gcb.15825

` } } } } }, general : { "admin0_ISO3": { "AGO": { "en": "Angola", "fr": "Angola" }, "BEN": { "en": "Benin", "fr": "Bénin" }, "BWA": { "en": "Botswana", "fr": "Botswana" }, "BFA": { "en": "Burkina Faso", "fr": "Burkina Faso" }, "BDI": { "en": "Burundi", "fr": "Burundi" }, "CMR": { "en": "Cameroon", "fr": "Cameroun" }, "CAF": { "en": "Central African Republic", "fr": "République Centrafricaine" }, "TCD": { "en": "Chad", "fr": "Tchad" }, "COG": { "en": "Congo - Brazzaville", "fr": "Congo - Brazzaville" }, "COD": { "en": "Congo - Kinshasa", "fr": "Congo - Kinshasa" }, "CIV": { "en": "Côte d’Ivoire", "fr": "Côte d’Ivoire" }, "DJI": { "en": "Djibouti", "fr": "Djibouti" }, "GNQ": { "en": "Equatorial Guinea", "fr": "Guinée Équatoriale" }, "ERI": { "en": "Eritrea", "fr": "Érythrée" }, "SWZ": { "en": "Eswatini", "fr": "Eswatini" }, "ETH": { "en": "Ethiopia", "fr": "Éthiopie" }, "GAB": { "en": "Gabon", "fr": "Gabon" }, "GMB": { "en": "Gambia", "fr": "Gambie" }, "GHA": { "en": "Ghana", "fr": "Ghana" }, "GIN": { "en": "Guinea", "fr": "Guinée" }, "GNB": { "en": "Guinea-Bissau", "fr": "Guinée-Bissau" }, "KEN": { "en": "Kenya", "fr": "Kenya" }, "LSO": { "en": "Lesotho", "fr": "Lesotho" }, "LBR": { "en": "Liberia", "fr": "Libéria" }, "MDG": { "en": "Madagascar", "fr": "Madagascar" }, "MWI": { "en": "Malawi", "fr": "Malawi" }, "MLI": { "en": "Mali", "fr": "Mali" }, "MRT": { "en": "Mauritania", "fr": "Mauritanie" }, "MOZ": { "en": "Mozambique", "fr": "Mozambique" }, "NAM": { "en": "Namibia", "fr": "Namibie" }, "NER": { "en": "Niger", "fr": "Niger" }, "NGA": { "en": "Nigeria", "fr": "Nigéria" }, "RWA": { "en": "Rwanda", "fr": "Rwanda" }, "SEN": { "en": "Senegal", "fr": "Sénégal" }, "SLE": { "en": "Sierra Leone", "fr": "Sierra Leone" }, "SOM": { "en": "Somalia", "fr": "Somalie" }, "ZAF": { "en": "South Africa", "fr": "Afrique du Sud" }, "SSD": { "en": "South Sudan", "fr": "Soudan du Sud" }, "SDN": { "en": "Sudan", "fr": "Soudan" }, "TZA": { "en": "Tanzania", "fr": "Tanzanie" }, "TGO": { "en": "Togo", "fr": "Togo" }, "UGA": { "en": "Uganda", "fr": "Ouganda" }, "ZMB": { "en": "Zambia", "fr": "Zambie" }, "ZWE": { "en": "Zimbabwe", "fr": "Zimbabwe" }, "TOTAL" : { "en": "Total", "fr": "Total" }, }, country_article1: { "AGO": {"en": "Angola", "fr": "L’Angola"}, "BEN": {"en": "Benin", "fr": "Le Bénin"}, "BWA": {"en": "Botswana", "fr": "Le Botswana"}, "BFA": {"en": "Burkina Faso", "fr": "Le Burkina Faso"}, "BDI": {"en": "Burundi", "fr": "Le Burundi"}, "CMR": {"en": "Cameroon", "fr": "Le Cameroun"}, "CAF": {"en": "Central African Republic", "fr": "La République Centrafricaine"}, "TCD": {"en": "Chad", "fr": "Le Tchad"}, "COG": {"en": "Congo - Brazzaville", "fr": "Le Congo - Brazzaville"}, "COD": {"en": "Congo - Kinshasa", "fr": "Le Congo - Kinshasa"}, "CIV": {"en": "Côte d'Ivoire", "fr": "La Côte d'Ivoire"}, "DJI": {"en": "Djibouti", "fr": "Djibouti"}, "GNQ": {"en": "Equatorial Guinea", "fr": "La Guinée Équatoriale"}, "ERI": {"en": "Eritrea", "fr": "L’Érythrée"}, "SWZ": {"en": "Eswatini", "fr": "L’Eswatini"}, "ETH": {"en": "Ethiopia", "fr": "L’Éthiopie"}, "GAB": {"en": "Gabon", "fr": "Le Gabon"}, "GMB": {"en": "Gambia", "fr": "La Gambie"}, "GHA": {"en": "Ghana", "fr": "Le Ghana"}, "GIN": {"en": "Guinea", "fr": "La Guinée"}, "GNB": {"en": "Guinea-Bissau", "fr": "La Guinée-Bissau"}, "KEN": {"en": "Kenya", "fr": "Le Kenya"}, "LSO": {"en": "Lesotho", "fr": "Le Lesotho"}, "LBR": {"en": "Liberia", "fr": "Le Libéria"}, "MDG": {"en": "Madagascar", "fr": "Madagascar"}, "MWI": {"en": "Malawi", "fr": "Le Malawi"}, "MLI": {"en": "Mali", "fr": "Le Mali"}, "MRT": {"en": "Mauritania", "fr": "La Mauritanie"}, "MOZ": {"en": "Mozambique", "fr": "Le Mozambique"}, "NAM": {"en": "Namibia", "fr": "La Namibie"}, "NER": {"en": "Niger", "fr": "Le Niger"}, "NGA": {"en": "Nigeria", "fr": "Le Nigéria"}, "RWA": {"en": "Rwanda", "fr": "Le Rwanda"}, "SEN": {"en": "Senegal", "fr": "Le Sénégal"}, "SLE": {"en": "Sierra Leone", "fr": "Sierra Leone"}, "SOM": {"en": "Somalia", "fr": "La Somalie"}, "ZAF": {"en": "South Africa", "fr": "L’Afrique du Sud"}, "SSD": {"en": "South Sudan", "fr": "Le Soudan du Sud"}, "SDN": {"en": "Sudan", "fr": "Le Soudan"}, "TZA": {"en": "Tanzania", "fr": "La Tanzanie"}, "TGO": {"en": "Togo", "fr": "Le Togo"}, "UGA": {"en": "Uganda", "fr": "L’Ouganda"}, "ZMB": {"en": "Zambia", "fr": "La Zambie"}, "ZWE": {"en": "Zimbabwe", "fr": "Le Zimbabwe"} }, country_article2: { "AGO": {"en": "Angola", "fr": "En Angola"}, "BEN": {"en": "Benin", "fr": "Au Bénin"}, "BWA": {"en": "Botswana", "fr": "Au Botswana"}, "BFA": {"en": "Burkina Faso", "fr": "Au Burkina Faso"}, "BDI": {"en": "Burundi", "fr": "Au Burundi"}, "CMR": {"en": "Cameroon", "fr": "Au Cameroun"}, "CAF": {"en": "Central African Republic", "fr": "En République Centrafricaine"}, "TCD": {"en": "Chad", "fr": "Au Tchad"}, "COG": {"en": "Congo - Brazzaville", "fr": "Au Congo - Brazzaville"}, "COD": {"en": "Congo - Kinshasa", "fr": "Au Congo - Kinshasa"}, "CIV": {"en": "Côte d'Ivoire", "fr": "En Côte d'Ivoire"}, "DJI": {"en": "Djibouti", "fr": "A Djibouti"}, "GNQ": {"en": "Equatorial Guinea", "fr": "En Guinée Équatoriale"}, "ERI": {"en": "Eritrea", "fr": "En Érythrée"}, "SWZ": {"en": "Eswatini", "fr": "En Eswatini"}, "ETH": {"en": "Ethiopia", "fr": "En Éthiopie"}, "GAB": {"en": "Gabon", "fr": "Au Gabon"}, "GMB": {"en": "Gambia", "fr": "En Gambie"}, "GHA": {"en": "Ghana", "fr": "Au Ghana"}, "GIN": {"en": "Guinea", "fr": "En Guinée"}, "GNB": {"en": "Guinea-Bissau", "fr": "En Guinée-Bissau"}, "KEN": {"en": "Kenya", "fr": "Au Kenya"}, "LSO": {"en": "Lesotho", "fr": "Au Lesotho"}, "LBR": {"en": "Liberia", "fr": "Au Libéria"}, "MDG": {"en": "Madagascar", "fr": "À Madagascar"}, "MWI": {"en": "Malawi", "fr": "Au Malawi"}, "MLI": {"en": "Mali", "fr": "Au Mali"}, "MRT": {"en": "Mauritania", "fr": "En Mauritanie"}, "MOZ": {"en": "Mozambique", "fr": "Au Mozambique"}, "NAM": {"en": "Namibia", "fr": "En Namibie"}, "NER": {"en": "Niger", "fr": "Au Niger"}, "NGA": {"en": "Nigeria", "fr": "Au Nigéria"}, "RWA": {"en": "Rwanda", "fr": "Au Rwanda"}, "SEN": {"en": "Senegal", "fr": "Au Sénégal"}, "SLE": {"en": "Sierra Leone", "fr": "À Sierra Leone"}, "SOM": {"en": "Somalia", "fr": "En Somalie"}, "ZAF": {"en": "South Africa", "fr": "En Afrique du Sud"}, "SSD": {"en": "South Sudan", "fr": "Au Soudan du Sud"}, "SDN": {"en": "Sudan", "fr": "Au Soudan"}, "TZA": {"en": "Tanzania", "fr": "En Tanzanie"}, "TGO": {"en": "Togo", "fr": "Au Togo"}, "UGA": {"en": "Uganda", "fr": "En Ouganda"}, "ZMB": {"en": "Zambia", "fr": "En Zambie"}, "ZWE": {"en": "Zimbabwe", "fr": "Au Zimbabwe"} }, lps :{ "Mixed irrigated": {en: "Mixed Irrigated", fr: "Mixte Irrigué"}, "Mixed rainfed": {en: "Mixed Rainfed", fr: "Mixte Pluvial"}, "Rangelands": {en: "Rangelands", fr: "Pâturages"}, "Other": {en: "Other", fr: "Autre"}, MIA: {en: "Mixed irrigated arid", fr: "Mixte irrigué aride"}, MIH: {en: "Mixed irrigated humid", fr: "Mixte irrigué humide"}, MIT: {en: "Mixed irrigated temperate", fr: "Mixte irrigué tempéré"}, MIY: {en: "Mixed irrigated hyperarid", fr: "Mixte irrigué hyperaride"}, MRA: {en: "Mixed rainfed arid", fr: "Mixte pluvial aride"}, MRH: {en: "Mixed rainfed humid", fr: "Mixte pluvial humide"}, MRT: {en: "Mixed rainfed temperate", fr: "Mixte pluvial tempéré"}, MRY: {en: "Mixed rainfed hyperarid", fr: "Mixte pluvial hyperaride"}, LGA: {en: "Rangelands arid", fr: "Pâturages arides"}, LGH: {en: "Rangelands humid", fr: "Pâturages humides"}, LGT: {en: "Rangelands temperate", fr: "Pâturages tempérés"}, LGY: {en: "Rangelands hyperarid", fr: "Pâturages hyperarides"} } } } }48:T55b,td = { // translation data return { leversChangeMap: { // uses data values from map data (hazards/emissions) "Tropical livestock units": _lang( nbText.sections.leversOfChange.chart.map.tooltip.data.hazards.tlu.name ), "Pasture area": _lang( nbText.sections.leversOfChange.chart.map.tooltip.data.hazards.pastureArea.name ), "Rural population": _lang( 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\n`\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":996,"value":"makeQuartoFlag(\"https://adaptationatlas.github.io/atlas_notebooksV1/notebooks/livestock-notebook/notebook.html\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":989,"value":"// pretty view of language toggle\nviewof prettyLanguageView = {\n return Inputs.bind(\n Inputs.radio(languages, {\n label: _lang(nbText.legends.language),\n format: (d) => d.label\n }),\n viewof language\n );\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":5,"value":"viewof colorblindData = {\n const data = [\n { key: \"None\", label: _lang(nbText.legends.colorblind.values.non) },\n { key: \"Deuteranopia\", label: _lang(nbText.legends.colorblind.values.deu) },\n { key: \"Protanopia\", label: _lang(nbText.legends.colorblind.values.pro) },\n { key: \"Tritanopia\", label: _lang(nbText.legends.colorblind.values.tri) },\n ];\n return Inputs.select(data, {\n label: _lang(nbText.legends.colorblind.label),\n format: x => x.label,\n value: data.find(d => d.key == 'None')\n });\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":415,"value":"tocOneliner({\n skip: [notebookTitle, \"Appendix\"],\n heading: `${Lang.toSentenceCase(_lang(nbText.legends.toc))}`\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":544,"value":"{\n const title = _lang(nbText.sections.overview.title);\n const intro = _lang(nbText.sections.overview.intro);\n const inspiration = _lang(nbText.sections.overview.inspiration);\n\n return md`# ${title}\n\n${intro}\n\n${inspiration}`;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":547,"value":"{\n const title = _lang(nbText.sections.livestockExplosion.title)\n const intro = _lang(nbText.sections.livestockExplosion.intro)\n\n return md`# ${title}\n\n ${intro}`\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":983,"value":"$2f","pinned":false,"hidden":false,"mode":"ojs"},{"id":982,"value":"$30","pinned":false,"hidden":false,"mode":"ojs"},{"id":981,"value":"areaDownload = {\n let button;\n let data;\n let filename;\n\n const fButtonLabel = _lang(\n nbText.sections.livestockExplosion.download.labelFunc\n );\n const buttonLabel = fButtonLabel(Area_chart_type.label);\n\n if (Area_chart_type.key === \"stock\") {\n data = await FileAttachment(\"1_FAO_stocks_years.csv\").csv();\n filename = \"stock\";\n } else if (Area_chart_type.key === \"ghg\") {\n data = await FileAttachment(\"1_FAO_ghg_years.csv\").csv();\n filename = \"ghg\";\n } else if (Area_chart_type.key === \"vop\") {\n data = await FileAttachment(\"1_FAO_vop_year.csv\").csv();\n filename = \"vop\";\n }\n\n button = build_download_button_dev(data, buttonLabel, filename);\n\n return button;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":631,"value":"dynamicTextQuickInsightsRegion()","pinned":false,"hidden":false,"mode":"ojs"},{"id":845,"value":"{\n const title = _lang(nbText.sections.leversOfChange.title)\n const intro = _lang(nbText.sections.leversOfChange.intro)\n\n return md`# ${title}\n\n ${intro}`\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":979,"value":"viewof map_configuration = Inputs.radio(\n new Map([\n [_lang(nbText.sections.leversOfChange.inputs.radio.values.adap), 'adaptation'],\n [_lang(nbText.sections.leversOfChange.inputs.radio.values.adap_mit), 'adaptation_mitigation'],\n [_lang(nbText.sections.leversOfChange.inputs.radio.values.mit), 'mitigation']\n ]),\n {label: _lang(nbText.sections.leversOfChange.inputs.radio.label), value: 'adaptation_mitigation'}\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":978,"value":"viewof num_priorities = {\nlet num_selector = Inputs.number([1, 42], {label: _lang(nbText.sections.leversOfChange.inputs.num.label), value : 5})\n\n num_selector.addEventListener('input', (event) => {\n d3.select(\"#num_countries\").html(`${event.target.value}`)\n });\n\n\nreturn num_selector\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":977,"value":"create_map(colorblindData.key)","pinned":false,"hidden":false,"mode":"ojs"},{"id":976,"value":"{\n const div = document.createElement(\"div\");\n div.style.display = \"flex\";\n div.style.flexDirection = \"row\";\n\n div.appendChild(\n build_download_button_dev(\n data_categories,\n _lang(nbText.sections.leversOfChange.chart.download.categories),\n \"adaptation_mitigation_categories\",\n \".download_data_am\"\n )\n );\n div.appendChild(\n build_download_button_dev(\n climate,\n _lang(nbText.sections.leversOfChange.chart.download.climate),\n \"climate_hazards_per_adaptation\",\n \".download_data_am\"\n )\n );\n div.appendChild(\n build_download_button_dev(\n emissions,\n _lang(nbText.sections.leversOfChange.chart.download.emissions),\n \"emissions_per_animals\",\n \".download_data_am\",\n \"clasetatata\"\n )\n );\n\n return div;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":975,"value":"viewof country_select = Inputs.select([''].concat(countriesFiltered), {label: _lang(nbText.sections.leversOfChange.livestockProductionSystems.countryInput.label), value: '', format: l => _lang(nbText.general.admin0_ISO3[l])})","pinned":false,"hidden":false,"mode":"ojs"},{"id":974,"value":"{\n const title = _lang(nbText.sections.leversOfChange.insights.title)\n return md`### ${title}`\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":973,"value":"{\n const template = _lang(\n nbText.sections.leversOfChange.insights.investmentPriorities\n );\n const insight = template({\n percAdaptation: initial_data[0].percent,\n percMitigation: initial_data[1].percent,\n countryCount: num_priorities,\n livestockProd: insight_object.vop_text,\n peopleExposed: insight_object.people,\n ggEmissions: insight_object.emissions\n });\n\n return md`${insight}`;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":972,"value":"{\n const template = _lang(\n nbText.sections.leversOfChange.insights.mostCritical\n );\n const insight = template({\n lever: _lang(nbText.general.country_article1[insight_object.iso_selected]), \n percVop: insight_object.per_vop, \n percEmissions: insight_object.per_emi\n });\n\n return md`${insight}`;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":971,"value":"{\n const template = _lang(\n nbText.sections.leversOfChange.insights.countrySystems\n );\n const insight = template({\n first: _lang(nbText.general.lps[insight_object.lps1]),\n second: _lang(nbText.general.lps[insight_object.lps2]),\n third: _lang(nbText.general.lps[insight_object.lps3]),\n });\n\n return md`${insight}`;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":970,"value":"{\n const template = _lang(\n nbText.sections.leversOfChange.insights.sigHazard\n );\n const insight = template({\n location: _lang(nbText.general.country_article2[insight_object.iso_selected]),\n hazard: insight_object.top_hazard,\n vop: insight_object.top_haz_vop\n });\n\n return md`${insight}`;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":969,"value":"{\n const header = _lang(nbText.sections.leversOfChange.livestockProductionSystems.header)\n const intro = _lang(nbText.sections.leversOfChange.livestockProductionSystems.tableIntro)\n\n return md`### ${header}\n\n ${intro}`\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":968,"value":"render_country_table()","pinned":false,"hidden":false,"mode":"ojs"},{"id":967,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":966,"value":"{\n const title = _lang(nbText.sections.scalableSolutions.title)\n const intro = _lang(nbText.sections.scalableSolutions.intro)\n\n return md`# ${title}\n\n ${intro}`\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":965,"value":"viewof solution_Selectors = {\n const title = _lang(nbText.sections.scalableSolutions.table.title);\n return Inputs.form([viewof select_system, viewof select_species], {\n template: (inputs) =>\n html`
${title}
${Object.values(\n inputs\n )}
`\n });\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":964,"value":"createSolutionTable(filterSolutions);","pinned":false,"hidden":false,"mode":"ojs"},{"id":963,"value":" build_download_button_dev(solutionData, _lang(nbText.sections.scalableSolutions.download), \"Adaptation and mitigation options\", \".button_container\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":962,"value":"{\n const title = _lang(nbText.sections.summary.title)\n return md`# ${title}`\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":961,"value":"$32","pinned":false,"hidden":false,"mode":"ojs"},{"id":804,"value":"$33","pinned":false,"hidden":false,"mode":"html"},{"id":959,"value":"# Appendix","pinned":false,"hidden":false,"mode":"md"},{"id":958,"value":"### Download Button","pinned":false,"hidden":false,"mode":"md"},{"id":957,"value":"build_download_button_dev = (data, text, file_name) => {\n const container = DOM.element('div');\n const button = DOM.element('button');\n button.className = \"button_download_data\";\n button.textContent = text;\n button.onclick = () => download_data(data, file_name);\n container.appendChild(button);\n return container\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":956,"value":"download_data = (data, file_name) => {\n const csv_file_name = file_name + \".csv\";\n const csvContent = convertToCSV(data);\n const blob = new Blob([csvContent], { type: 'text/csv' });\n const url = window.URL.createObjectURL(blob);\n\n const link = document.createElement('a');\n link.href = url;\n link.setAttribute('download', csv_file_name);\n document.body.appendChild(link);\n\n link.click();\n\n // Limpiar y revocar el objeto URL creado\n window.URL.revokeObjectURL(url);\n document.body.removeChild(link);\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":955,"value":"convertToCSV = (data) => {\n const csvContent = [];\n \n // En cabezados del CSV\n const headers = Object.keys(data[0]);\n \n csvContent.push(headers.join(','));\n\n // Filas de datos del CSV\n data.forEach(item => {\n const values = headers.map(header => item[header]);\n csvContent.push(values.join(','));\n });\n\n return csvContent.join('\\n');\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":954,"value":"### Color Blind Helpers","pinned":false,"hidden":false,"mode":"md"},{"id":953,"value":"color_blind = import(\"https://cdn.jsdelivr.net/npm/color-blind@0.1.3/+esm\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":952,"value":"function getColorBlind(colorBlind) {\n let colorScaleBase = d3[`schemeTableau10`]\n if (colorBlind===\"Deuteranopia\")\n colorScaleBase = colorScaleBase.map(e => color_blind.default.deuteranopia(e))\n else if (colorBlind === \"Protanopia\")\n colorScaleBase = colorScaleBase.map(e => color_blind.default.protanopia(e))\n else if (colorBlind === \"Tritanopia\")\n colorScaleBase = colorScaleBase.map(e => color_blind.default.tritanopia(e))\n return colorScaleBase\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":951,"value":"function getColorBlind_Input(colorBlind, color) {\n if (colorBlind===\"Deuteranopia\")\n color =color_blind.default.deuteranopia(color)\n else if (colorBlind === \"Protanopia\")\n color = color_blind.default.protanopia(color)\n else if (colorBlind === \"Tritanopia\")\n color = color_blind.default.tritanopia(color)\n return color\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":950,"value":"function getColorBlindRGB(colorBlind, color) {\n if (colorBlind===\"Deuteranopia\")\n color =color_blind.default.deuteranopia(color, true)\n else if (colorBlind === \"Protanopia\")\n color = color_blind.default.protanopia(color, true)\n else if (colorBlind === \"Tritanopia\")\n color = color_blind.default.tritanopia(color, true)\n \n return !color.R ? color :`rgb(${color.R}, ${color.G}, ${color.B})`;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":949,"value":"getColorBlindRGB(colorblindData.key, \"#216729\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":948,"value":"## Livestock Explosion / Area Plot","pinned":false,"hidden":false,"mode":"md"},{"id":947,"value":"function convertToFloat(obj, i) {\n obj[i] = parseFloat(obj[i]);\n obj[\"year\"] = parseInt(obj[\"year\"]);\n return obj;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":946,"value":"$34","pinned":false,"hidden":false,"mode":"ojs"},{"id":531,"value":"$35","pinned":false,"hidden":false,"mode":"ojs"},{"id":564,"value":"$36","pinned":false,"hidden":false,"mode":"ojs"},{"id":943,"value":"## Countries as Levers / Map","pinned":false,"hidden":false,"mode":"md"},{"id":942,"value":"### Icons","pinned":false,"hidden":false,"mode":"md"},{"id":941,"value":"$37","pinned":false,"hidden":false,"mode":"ojs"},{"id":940,"value":"$38","pinned":false,"hidden":false,"mode":"ojs"},{"id":939,"value":"### Data","pinned":false,"hidden":false,"mode":"md"},{"id":938,"value":"data_categories = FileAttachment(\"adaptation-mitigation-categories-subsahara.csv\").csv()","pinned":false,"hidden":false,"mode":"ojs"},{"id":937,"value":"hazards = await FileAttachment(\"country_emissions_hazards-2(1).csv\").csv()","pinned":false,"hidden":false,"mode":"ojs"},{"id":936,"value":"emissions = FileAttachment(\"emissions_per_animals_subsahara.csv\").csv()","pinned":false,"hidden":false,"mode":"ojs"},{"id":935,"value":"climate = FileAttachment(\"2_climate_hazards_per_adapatation_areas_subshara(1).csv\").csv()","pinned":false,"hidden":false,"mode":"ojs"},{"id":934,"value":"### Map","pinned":false,"hidden":false,"mode":"md"},{"id":933,"value":"d3_geoProj = require('d3-geo-projection')","pinned":false,"hidden":false,"mode":"ojs"},{"id":932,"value":"$39","pinned":false,"hidden":false,"mode":"ojs"},{"id":931,"value":"world = FileAttachment(\"africa_50m-1.json\").json()","pinned":false,"hidden":false,"mode":"ojs"},{"id":930,"value":"initial_data ={\n if( map_configuration === \"adaptation_mitigation\"){\n d3.select(\"#per_adap\").html(`50%`)\n d3.select(\"#per_miti\").html(`50%`)\n return [\n {\n percent: 50,\n color: \"#C51617\",\n name: \"Adaptation\"\n },\n {\n percent: 50,\n color: \"#5651FF\",\n name: \"Mitigation\",\n last: true\n }\n]\n } else if (map_configuration === \"adaptation\"){\n d3.select(\"#per_adap\").html(`100%`)\n d3.select(\"#per_miti\").html(`0%`)\n return [\n {\n percent: 100,\n color: \"#C51617\",\n name: \"Adaptation\"\n },\n {\n percent: 0,\n color: \"#5651FF\",\n name: \"Mitigation\",\n last: true\n }\n]\n } else {\n d3.select(\"#per_adap\").html(`0%`)\n d3.select(\"#per_miti\").html(`100%`)\n return [\n {\n percent: 0,\n color: \"#C51617\",\n name: \"Adaptation\"\n },\n {\n percent: 100,\n color: \"#5651FF\",\n name: \"Mitigation\",\n last: true\n }\n]\n }\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":929,"value":"filterCountries1= (mode, combined, composite, count, name) => {\n if (mode)\n return data_categories.filter((d) => {\n return (composite.adaptation === \"\" || composite.mitigation === \"\") ? true : (d.adaptation_cat === composite.adaptation && d.mitigation_cat === composite.mitigation) \n }).map((d) => {return d.ISO3})\n else {\n return data_categories.sort((a, b) => {\n if (combined[0].percent === 0) {\n return b.mitigation_index - a.mitigation_index;\n } else if (combined[0].percent === 100) {\n return b.adaptation_index - a.adaptation_index;\n } else {\n const prop = `${combined[0].percent}ada-${combined[1].percent}mit`;\n return b[prop] - a[prop];\n }\n }).map((d) => {\n return name ? d.country : d.ISO3;\n }).slice(0, count || -1)\n } \n} ","pinned":false,"hidden":false,"mode":"ojs"},{"id":928,"value":"getTrafficLight = (name) => {\n const countryData = data_categories.find((d) => d.ISO3 === name);\n return countryData ? parseInt(countryData.traffic_light) : 0;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":927,"value":" colors= [\n //low mitigation / low adaptation, middle mitigation / low adaptation, high mitigation / low adaptation\n \"#B22222\", \"#FF0000\", \"#FFE800\",\n //low mitigation / middle adaptation, middle mitigation / middle adaptation, high mitigation / middle adaptation\n \"#FF0000\", \"#FFE800\", \"#3CB371\",\n //low mitigation / high adaptation, middle mitigation / high adaptation, high mitigation / high adaptation\n \"#FFE800\", \"#3CB371\", \"#008000\"\n ]","pinned":false,"hidden":false,"mode":"ojs"},{"id":926,"value":"color1 = {\n return (value, select, mode) => {\n //Makes features with null values black\n if (!value || !mode ) return \"#EFEFEF\";\n //Defines color's relationship to the variables\n return getColorBlind(select, colors[value - 1]);\n };\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":925,"value":"$3a","pinned":false,"hidden":false,"mode":"ojs"},{"id":924,"value":"$3b","pinned":false,"hidden":false,"mode":"ojs"},{"id":923,"value":"countriesFiltered = filterCountries1(false, initial_data, NaN, num_priorities )","pinned":false,"hidden":false,"mode":"ojs"},{"id":922,"value":"$3c","pinned":false,"hidden":false,"mode":"ojs"},{"id":921,"value":"d4 = require(\"d3@5\", \"d3-geo@1\", \"d3-geo-projection@2\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":920,"value":"### Dynamic Insight and Table","pinned":false,"hidden":false,"mode":"md"},{"id":919,"value":"data_climate_hazards = FileAttachment(\"2_climate_hazards_per_adapatation_areas_subshara(2).csv\").csv()","pinned":false,"hidden":false,"mode":"ojs"},{"id":918,"value":"data_ghg = FileAttachment(\"country_emissions_hazards-4.csv\").csv()","pinned":false,"hidden":false,"mode":"ojs"},{"id":917,"value":"data_lps_top = FileAttachment(\"3_quickinsights_sort_lps_country.csv\").csv()","pinned":false,"hidden":false,"mode":"ojs"},{"id":916,"value":"data_lps_hazards = FileAttachment(\"3_country_lps_hazards.csv\").csv()","pinned":false,"hidden":false,"mode":"ojs"},{"id":915,"value":"data_lps_emissions = FileAttachment(\"3_country_lps_emissions-1(1).csv\").csv()","pinned":false,"hidden":false,"mode":"ojs"},{"id":914,"value":"data_lps = FileAttachment(\"LPS-2.csv\").csv()","pinned":false,"hidden":false,"mode":"ojs"},{"id":913,"value":"$3d","pinned":false,"hidden":false,"mode":"ojs"},{"id":912,"value":"$3e","pinned":false,"hidden":false,"mode":"ojs"},{"id":911,"value":"render_country_table = () => {\n const selectedValue = country_select !== \"\"? data_ghg.filter((d) => d.ISO3 === country_select)[0].country : undefined\n let table\n if (!selectedValue){\n table = doble_tittle_table(dataTable_dev)\n } else {\n const countrySelect = selectedValue ? dataTable_dev.find(country => country.country === selectedValue) :dataTable_dev[0]\n \n const lps_hazards = data_lps_hazards.filter(d => d.country === countrySelect.country);\n const lps_emissions = data_lps_emissions.filter(d => d.country === countrySelect.country);\n table = doble_tittle_table1(lps_emissions, lps_hazards)\n }\n table.classList.add('.table')\n\n// const style = document.createElement(\"style\");\n// style.innerHTML = `\n// thead {\n// color: green !important;\n// }\n// `;\n \n// table.appendChild(style);\n\n\n \n return table\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":910,"value":"getTopHazards = (country) => {\n const dataFilter = data_climate_hazards.filter(lps => lps.country == country.country && lps.variable == \"Value\")\n\n let maxIndex = 0;\n let maxValueProp = parseFloat(dataFilter[0].value_prop);\n for (let i = 1; i < dataFilter.length; i++) {\n const currentValueProp = parseFloat(dataFilter[i].value_prop);\n if (currentValueProp > maxValueProp) {\n maxIndex = i;\n maxValueProp = currentValueProp;\n }\n }\n const hazardTop = dataFilter[maxIndex];\n\n return hazardTop\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":909,"value":"getTopLPS = (country) => {\n const dataFilter = data_lps_top.filter(lps => lps.country == country.country)\n \nreturn dataFilter\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":908,"value":"hazards_descrip = new Object({\n Thi: \"Livestock heat stress\",\n RF: \"Extreme or high rainfall variability\",\n D: \"Drought\",\n F: \"Flooding\",\n CV: \"Rainfall variability\",\n ExCV: \"Extremely high rainfall variability\",\n HCV: \"High rainfall variability\",\n \"CV+D\": \"Rainfall variability and drought\",\n \"CV+D+F\": \"Rainfall variability, drought and flooding\",\n \"CV+F\": \"Rainfall variability and flooding\",\n \"CV+Thi\": \"Rainfall variability and livestock heat stress\",\n \"CV+Thi+D\": \"Rainfall variability, livestock heat stress and drought\",\n \"CV+Thi+D+F\": \"Rainfall variability, livestock heat stress, drought and flooding\",\n \"CV+Thi+F\": \"Rainfall variability, livestock heat stress and flooding\",\n \"D+F\": \"Drought and flooding\",\n \"Thi+D\": \"Livestock heat stress and drought\",\n \"Thi+D+F\": \"Livestock heat stress, drought and flooding\",\n \"Thi+F\": \"Livestock heat stress and flooding\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":907,"value":"lps_descrip = new Object({\n MIA: \"Mixed irrigated arid\", \n MIH: \"Mixed irrigated humid\", \n MIT: \"Mixed irrigated temperate\",\n MIY: \"Mixed irrigated hyperarid\",\n MRA: \"Mixed rainfed arid\",\n MRH: \"Mixed rainfed humid\",\n MRT: \"Mixed rainfed temperate\",\n MRY: \"Mixed rainfed hyperarid\",\n LGA: \"Rangelands arid\",\n LGH: \"Rangelands humid\",\n LGT: \"Rangelands temperate\",\n LGY: \"Rangelands hyperarid\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":906,"value":"mapping_lps = new Object({\n \"Mixed irrigated\":[\"MIA\", \"MIH\", \"MIT\", \"MIY\"],\n \"Mixed rainfed\": [\"MRA\", \"MRH\", \"MRT\", \"MRY\"],\n \"Rangelands\": [\"LGA\", \"LGH\", \"LGT\", \"LGY\", \"Other\"]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":905,"value":"table_titles = [\n _lang(nbText.sections.leversOfChange.livestockProductionSystems.table.headers.emissionsDirect),\n _lang(nbText.sections.leversOfChange.livestockProductionSystems.table.headers.emissionsIndirect),\n _lang(nbText.sections.leversOfChange.livestockProductionSystems.table.headers.emissionsTotal),\n _lang(nbText.sections.leversOfChange.livestockProductionSystems.table.headers.popRural),\n _lang(nbText.sections.leversOfChange.livestockProductionSystems.table.headers.vop),\n _lang(nbText.sections.leversOfChange.livestockProductionSystems.table.headers.tlu),\n _lang(nbText.sections.leversOfChange.livestockProductionSystems.table.headers.pastureArea),\n]","pinned":false,"hidden":false,"mode":"ojs"},{"id":904,"value":"$3f","pinned":false,"hidden":false,"mode":"ojs"},{"id":903,"value":"$40","pinned":false,"hidden":false,"mode":"ojs"},{"id":902,"value":"$41","pinned":false,"hidden":false,"mode":"ojs"},{"id":901,"value":"## Solution Table","pinned":false,"hidden":false,"mode":"md"},{"id":900,"value":"dataOption = {\n if (language.key === \"en\"){ \n return FileAttachment(\"4_livestock_prod_system_priority_countries-5.csv\").csv()\n} else if (language.key === \"fr\"){ \n return FileAttachment(\"french_livestock_prod_system_priority_countries.csv\").csv()}\n}\n\n ","pinned":false,"hidden":false,"mode":"ojs"},{"id":899,"value":"$42","pinned":false,"hidden":false,"mode":"ojs"},{"id":898,"value":"getLivestockSystem = () => {\n let livestockSystemArray = [];\n dataOption.forEach((d) => {\n const systems = d[_lang(solution_table_columns_translations.system)].split(',').map(s => s.trim()); // Divide por comas y quita espacios en blanco\n livestockSystemArray.push(...systems); // Agrega todos los sistemas al arreglo\n });\n livestockSystemArray = Array.from(new Set(livestockSystemArray)); // Elimina duplicados\n livestockSystemArray = livestockSystemArray.filter(item => item !== \"\")\n \n return livestockSystemArray;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":897,"value":"getSpecies = () => {\n let speciesArray = [];\n dataOption.forEach((d) => {\n const species = d[_lang(solution_table_columns_translations.species)].split(',').map(s => s.trim()); // Divide por comas y quita espacios en blanco\n speciesArray.push(...species); // Agrega todos los sistemas al arreglo\n });\n speciesArray = Array.from(new Set(speciesArray)); // Elimina duplicados\n speciesArray = speciesArray.filter(item => item !== \"\")\n \n return speciesArray;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":896,"value":"$43","pinned":false,"hidden":false,"mode":"ojs"},{"id":895,"value":"solutionData =FileAttachment(\"adaptation-mitigation-options-with-constraints-4.csv\").csv()","pinned":false,"hidden":false,"mode":"ojs"},{"id":894,"value":"solution_table_columns_translations = new Object({\n species: {en: \"Species for which suitable\", fr:\"Espèces appropriées\"},\n system: {en: \"Systems where suitable\", fr: \"Systèmes appropriés\" },\n priority: {en: \"Priority addressed\", fr: \"Priorité abordée\"},\n description: {en: \"Description and implementation constraints\", fr: \"Description et contraintes de mise en œuvre\"}\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":893,"value":"## Summary","pinned":false,"hidden":false,"mode":"md"},{"id":892,"value":"$44","pinned":false,"hidden":false,"mode":"ojs"},{"id":891,"value":"## Styling and imports","pinned":false,"hidden":false,"mode":"md"},{"id":401,"value":"$45","pinned":false,"hidden":false,"mode":"ojs"},{"id":889,"value":"$${styling} ","pinned":false,"hidden":false,"mode":"html"},{"id":412,"value":"$46","pinned":false,"hidden":false,"mode":"ojs"},{"id":417,"value":"notebookTitle = \"Prioritize Livestock Investments\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":741,"value":"import {dropdownInput, dropdownCSS} from '@tashapiro/dropdown-input'","pinned":false,"hidden":false,"mode":"ojs"},{"id":744,"value":"dropdownCSS","pinned":false,"hidden":false,"mode":"ojs"},{"id":746,"value":"debounce = (delay, input) => {\n class DelayedEvent extends Event {};\n let id;\n input.addEventListener(\"input\", (e) => {\n if(e instanceof DelayedEvent) return;\n e.stopImmediatePropagation();\n clearTimeout(id);\n id = setTimeout(() => input.dispatchEvent(new DelayedEvent(\"input\", {bubbles: true})), delay);\n });\n return input;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":748,"value":"// admin multi-select: countries\nviewof select_species = {\n const data = getSpecies().map((d) => ({\n value: d,\n label: d\n }));\n const input = dropdownInput({\n inputLabel: _lang(nbText.sections.scalableSolutions.table.inputs.selectSpecies.label),\n inputId: \"positionsTest\",\n placeholderText: _lang(nbText.sections.scalableSolutions.table.inputs.selectSpecies.placeholder),\n options: data,\n selected: [data[0].value]\n });\n return debounce(500, input);\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":759,"value":"// admin multi-select: countries\nviewof select_system = {\n const data = getLivestockSystem().map((d) => ({\n value: d,\n label: d\n }));\n const input = dropdownInput({\n inputLabel: _lang(nbText.sections.scalableSolutions.table.inputs.selectLivestock.label),\n inputId: \"positionsTest\",\n placeholderText: _lang(nbText.sections.scalableSolutions.table.inputs.selectLivestock.placeholder),\n options: data,\n selected: [data[0].value]\n });\n return debounce(500, input);\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":601,"value":"dataStock = FileAttachment(\"1_FAO_stocks_years.csv\").csv()","pinned":false,"hidden":false,"mode":"ojs"},{"id":612,"value":"dataVOP = FileAttachment(\"1_FAO_vop_year.csv\").csv()","pinned":false,"hidden":false,"mode":"ojs"},{"id":618,"value":"dataGHG = FileAttachment(\"1_FAO_ghg_years.csv\").csv()","pinned":false,"hidden":false,"mode":"ojs"},{"id":657,"value":"dataSummary = FileAttachment(\"country_emissions_hazards.csv\").csv()","pinned":false,"hidden":false,"mode":"ojs"},{"id":883,"value":"## Translation","pinned":false,"hidden":false,"mode":"md"},{"id":882,"value":"import { Lang } from \"7d46679f7d0d917e\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":881,"value":"languages = [\n { key: \"en\", label: \"English\", locale: 'en-US' },\n { key: \"fr\", label: \"Français\", locale: 'fr-FR' }\n]","pinned":false,"hidden":false,"mode":"ojs"},{"id":880,"value":"// get the default language key from parameter, or use default\ndefaultLangKey = {\n const name = \"lang\";\n const list = languages.map((d) => d.key);\n const defaultKey = \"en\";\n\n const queryParam = await Lang.getParamFromList({ name, list });\n\n return queryParam ?? defaultKey;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":879,"value":"// helper shorthand for Lang text-getting\n_lang = Lang.lg(language.key)","pinned":false,"hidden":false,"mode":"ojs"},{"id":878,"value":"// main toggle of language key\nviewof language = Inputs.radio(languages, {\n label: \"Main language toggle\",\n format: (d) => d.key,\n value: languages.find((x) => x.key === defaultLangKey),\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":877,"value":"$47","pinned":false,"hidden":false,"mode":"ojs"},{"id":876,"value":"$48","pinned":false,"hidden":false,"mode":"ojs"},{"id":994,"value":"makeQuartoFlag = (url) => {\n const baseText = _lang(\n {\n en: \"New version available! This notebook has been rebuilt in Quarto for a better experience:\",\n fr: \"Nouvelle version disponible ! Ce carnet a été reconstruit avec Quarto pour une meilleure expérience:\"\n }\n )\n const openText = _lang(\n {\n en: \"Open Updated Notebook\",\n fr: \"Ouvrir le carnet mis à jour\"\n }\n )\n \n return htl.html`\n
\n ${baseText} ${openText} →\n
\n `\n}","pinned":true,"hidden":false,"mode":"ojs"}],"files":"$W49","stdlib":"1","titling":"auto"}