{"id":13411,"date":"2026-06-01T17:18:38","date_gmt":"2026-06-01T15:18:38","guid":{"rendered":"https:\/\/geopard.tech\/agroclimate-rice\/"},"modified":"2026-06-01T18:42:13","modified_gmt":"2026-06-01T16:42:13","slug":"agroklimatski-riz","status":"publish","type":"page","link":"https:\/\/geopard.tech\/sl\/agroclimate-rice\/","title":{"rendered":"Kje bo ri\u017e rasel do leta 2050? Spreminja se primernost podnebja"},"content":{"rendered":"\n<!-- All styles live INSIDE the body so they survive when only the body\n     is extracted for the WordPress wp:html block. -->\n<style>\n.seo-body{font-family:var(--wp--preset--font-family--nunito,\"Nunito\",\"Segoe UI\",system-ui,-apple-system,sans-serif);color:#212121;max-width:1100px;margin:0 auto;padding:8px 0 24px}\n.seo-body h1{font-family:var(--wp--preset--font-family--poppins,\"Poppins\",system-ui,sans-serif);font-weight:800;color:#0e3a1c;letter-spacing:-0.018em;font-size:2.1rem;line-height:1.15;margin:0 0 12px}\n.seo-body h2{font-family:var(--wp--preset--font-family--poppins,\"Poppins\",system-ui,sans-serif);color:#145328;font-size:1.4rem;margin:28px 0 12px;letter-spacing:-0.01em}\n.seo-body h3{font-family:var(--wp--preset--font-family--poppins,\"Poppins\",system-ui,sans-serif);color:#145328;font-size:1.05rem;margin:0 0 6px}\n.seo-body p{line-height:1.65;color:#243024;font-size:15px;margin:0 0 12px}\n.seo-body .seo-lede{font-size:17px;line-height:1.6;color:#3a4a3a;margin:0 0 20px}\n.seo-body > .seo-lede:first-child{font-size:18px;line-height:1.55;margin:0 0 22px}\n.seo-body a{color:#15701e;text-decoration:underline;text-underline-offset:2px}\n.seo-body strong{color:#145328}\n.seo-body .seo-zone{background:#fff;border:1px solid #e8ebe2;border-left:3px solid #15701e;border-radius:8px;padding:16px 20px;margin:0 0 12px;box-shadow:0 1px 3px rgba(20,83,40,0.05)}\n.seo-body .seo-zone h3{display:flex;align-items:baseline;gap:8px;flex-wrap:wrap;margin-bottom:6px}\n.seo-body .seo-zone .badge{font-family:var(--wp--preset--font-family--dm-mono,\"DM Mono\",ui-monospace,monospace);font-size:11px;text-transform:uppercase;letter-spacing:0.06em;color:#f76a0c;font-weight:700}\n.seo-body .seo-zone p{margin:6px 0;font-size:14px}\n.seo-body .seo-grid{display:grid;grid-template-columns:repeat(auto-fit,minmax(170px,1fr));gap:8px;margin:6px 0 0;font-family:var(--wp--preset--font-family--dm-mono,\"DM Mono\",ui-monospace,monospace);font-size:11.5px;color:#4c6066}\n.seo-body .seo-grid .k{font-weight:700;color:#212121}\n.seo-body .seo-cta{display:inline-block;background:#f76a0c;color:#fff;padding:11px 22px;border-radius:999px;font-family:var(--wp--preset--font-family--poppins,\"Poppins\",sans-serif);font-weight:600;font-size:14px;text-decoration:none;margin:18px 0 0;box-shadow:0 6px 16px rgba(247,106,12,.3)}\n.seo-body .seo-cta:hover{background:#ff7d24;color:#fff}\n.seo-body .seo-table{width:100%;border-collapse:collapse;font-size:14px;margin:6px 0 18px}\n.seo-body .seo-table th,.seo-body .seo-table td{padding:8px 10px;border-bottom:1px solid #e8ebe2;text-align:left;font-family:var(--wp--preset--font-family--dm-mono,\"DM Mono\",ui-monospace,monospace)}\n.seo-body .seo-table th{font-size:11px;text-transform:uppercase;letter-spacing:0.06em;color:#4c6066;font-weight:700;border-bottom:2px solid #cfe4d4}\n.seo-body .seo-table tr:hover{background:#fbfcf6}\n.seo-body .seo-table td:last-child{font-weight:700;color:#212121}\n.seo-body .seo-table .up{color:#15701e}.seo-body .seo-table .down{color:#c8232c}\n.seo-foot{max-width:1100px;margin:0 auto;padding:14px 0;border-top:1px dashed #cfe4d4;font-family:var(--wp--preset--font-family--dm-mono,\"DM Mono\",ui-monospace,monospace);font-size:11px;color:#4c6066;text-align:center;letter-spacing:0.03em}\n.seo-foot a{color:#15701e}\n<\/style><div class=\"seo-body\"><p class=\"seo-lede\">Climate-suitability trajectory for <strong>rice<\/strong> across 16 agroclimatic zones, 2020\u20132060. Where the envelope is opening, where it&#8217;s closing, plus current trade exposure: <strong>$480\/t<\/strong> baseline, <strong>15%<\/strong> 10y volatility, top-5 exporters control <strong>78%<\/strong> of trade.<\/p><h2>Top 10 zones for rice by 2050<\/h2><table class=\"seo-table\"><thead><tr><th>Rank<\/th><th>Zone<\/th><th>Country<\/th><th>2020<\/th><th>2050<\/th><th>\u0394<\/th><\/tr><\/thead><tbody><tr><td>1<\/td><td><a href=\"\/agroclimate-explorer\/?zone=th-central\">Central Plain<\/a><\/td><td>Thailand<\/td><td>88<\/td><td>76<\/td><td class=\"down\">-12 pts<\/td><\/tr><tr><td>2<\/td><td><a href=\"\/agroclimate-explorer\/?zone=bd-delta\">Ganges Delta<\/a><\/td><td>Bangladesh<\/td><td>88<\/td><td>76<\/td><td class=\"down\">-12 pts<\/td><\/tr><tr><td>3<\/td><td><a href=\"\/agroclimate-explorer\/?zone=us-delta\">Mississippi Delta<\/a><\/td><td>United States<\/td><td>88<\/td><td>74<\/td><td class=\"down\">-14 pts<\/td><\/tr><tr><td>4<\/td><td><a href=\"\/agroclimate-explorer\/?zone=cn-n-plain\">North China Plain<\/a><\/td><td>China<\/td><td>78<\/td><td>69<\/td><td class=\"down\">-9 pts<\/td><\/tr><tr><td>5<\/td><td><a href=\"\/agroclimate-explorer\/?zone=cn-northeast\">Northeast China<\/a><\/td><td>China<\/td><td>72<\/td><td>69<\/td><td class=\"down\">-3 pts<\/td><\/tr><tr><td>6<\/td><td><a href=\"\/agroclimate-explorer\/?zone=in-indo-gangetic\">Indo-Gangetic Plain<\/a><\/td><td>India<\/td><td>82<\/td><td>68<\/td><td class=\"down\">-14 pts<\/td><\/tr><tr><td>7<\/td><td><a href=\"\/agroclimate-explorer\/?zone=br-sul\">Sul (south)<\/a><\/td><td>Brazil<\/td><td>75<\/td><td>65<\/td><td class=\"down\">-10 pts<\/td><\/tr><tr><td>8<\/td><td><a href=\"\/agroclimate-explorer\/?zone=vn-central\">Central Highlands + Mekong<\/a><\/td><td>Vietnam<\/td><td>80<\/td><td>65<\/td><td class=\"down\">-15 pts<\/td><\/tr><tr><td>9<\/td><td><a href=\"\/agroclimate-explorer\/?zone=eg-nile\">Nile Delta<\/a><\/td><td>Egypt<\/td><td>75<\/td><td>60<\/td><td class=\"down\">-15 pts<\/td><\/tr><tr><td>10<\/td><td><a href=\"\/agroclimate-explorer\/?zone=id-sumatra\">Sumatra \/ palm belt<\/a><\/td><td>Indonesia<\/td><td>72<\/td><td>60<\/td><td class=\"down\">-12 pts<\/td><\/tr><\/tbody><\/table><h2>Biggest declines for rice \u00b7 2020 \u2192 2050<\/h2><table class=\"seo-table\"><thead><tr><th>Zone<\/th><th>Country<\/th><th>\u0394 suitability<\/th><\/tr><\/thead><tbody><tr><td><a href=\"\/agroclimate-explorer\/?zone=au-murray\">Murray-Darling<\/a><\/td><td>Australia<\/td><td class=\"down\">-23 pts (55 \u2192 32)<\/td><\/tr><tr><td><a href=\"\/agroclimate-explorer\/?zone=us-california\">California Central<\/a><\/td><td>United States<\/td><td class=\"down\">-18 pts (65 \u2192 47)<\/td><\/tr><tr><td><a href=\"\/agroclimate-explorer\/?zone=pk-indus\">Indus Plain<\/a><\/td><td>Pakistan<\/td><td class=\"down\">-17 pts (75 \u2192 58)<\/td><\/tr><tr><td><a href=\"\/agroclimate-explorer\/?zone=in-deccan\">Deccan Plateau<\/a><\/td><td>India<\/td><td class=\"down\">-16 pts (48 \u2192 32)<\/td><\/tr><tr><td><a href=\"\/agroclimate-explorer\/?zone=vn-central\">Central Highlands + Mekong<\/a><\/td><td>Vietnam<\/td><td class=\"down\">-15 pts (80 \u2192 65)<\/td><\/tr><\/tbody><\/table><h2>Trade context for rice<\/h2><p><strong>Baseline price:<\/strong> $480\/t \u00b7 <strong>10y volatility:<\/strong> 15% \u00b7 <strong>Top-5 exporter share:<\/strong> 78% \u00b7 <strong>Trade chokepoint:<\/strong> Bab-el-Mandeb \/ Suez\u00b7 <strong>Export restrictions active<\/strong> in last 3 years.<\/p><a class=\"seo-cta\" href=\"\/agroclimate-explorer\/\">Open the interactive tool \u2192<\/a><!--\n  Tool-specific bottom (CTA + FAQ) for \/agroclimate-explorer\/.\n  Self-contained CSS so it renders correctly WITHOUT depending on block\n  13099's .gpx-* styles (which only ship with the field-explorer hero).\n\n  Replaces the shared Reusable Block 13099 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.gpb-integ{display:flex;flex-wrap:wrap;gap:8px;justify-content:center;margin:10px 0 20px}\n.gpl-bottom .gpb-integ-label{font-size:.86rem;color:rgba(255,255,255,0.86);margin:0 0 8px;font-weight:500;letter-spacing:.01em}\n.gpl-bottom .gpb-integ-chip{background:rgba(255,255,255,0.16);border:1px solid rgba(255,255,255,0.32);color:#fff;padding:6px 14px;border-radius:999px;font-size:.85rem;font-weight:600;letter-spacing:.02em}\n.gpl-bottom .gpb-faq{margin:36px 0 8px}\n.gpl-bottom .gpb-faq h2{text-align:center;margin:0 0 20px;font-size:1.6rem}\n.gpl-bottom .gpb-tabs{border:1px solid #e8ebe2;border-radius:16px;overflow:hidden;background:#fff;box-shadow:0 2px 14px rgba(20,83,40,0.06)}\n.gpl-bottom .gpb-tablist{display:flex;gap:0;background:#f6f7f1;border-bottom:1px solid #e8ebe2;overflow-x:auto;scrollbar-width:none}\n.gpl-bottom .gpb-tablist::-webkit-scrollbar{display:none}\n.gpl-bottom .gpb-tab{flex:1 1 auto;min-width:max-content;background:transparent;border:0;padding:16px 22px;font-family:var(--wp--preset--font-family--poppins,\"Poppins\",sans-serif);font-size:.95rem;font-weight:600;color:#4c6066;cursor:pointer;border-bottom:3px solid transparent;transition:color .15s,border-color .15s,background .15s;white-space:nowrap;letter-spacing:.01em}\n.gpl-bottom .gpb-tab:hover{color:#145328;background:rgba(123,220,181,0.14)}\n.gpl-bottom .gpb-tab[aria-selected=\"true\"]{color:#145328;border-bottom-color:#15701e;background:#fff}\n.gpl-bottom .gpb-tab:focus{outline:2px solid #15701e;outline-offset:-2px}\n.gpl-bottom .gpb-panel{padding:28px 32px;display:none;animation:gpbfade .25s ease}\n.gpl-bottom .gpb-panel.is-active{display:block}\n@keyframes gpbfade{from{opacity:0;transform:translateY(6px)}to{opacity:1;transform:none}}\n.gpl-bottom .gpb-panel p{margin:0;line-height:1.7;color:#243024;font-size:1rem}\n.gpl-bottom .gpb-panel p+p{margin-top:10px}\n.gpl-bottom .gpb-panel kbd,.gpl-bottom .gpb-panel code{background:#f0f3ec;padding:2px 6px;border-radius:4px;font-family:var(--wp--preset--font-family--dm-mono,\"DM Mono\",ui-monospace,monospace);font-size:.88em;color:#145328}\n@media (max-width:760px){\n  .gpl-bottom h2{font-size:1.3rem}\n  .gpl-bottom .gpb-cta{padding:24px 22px}\n  .gpl-bottom .gpb-panel{padding:22px 20px}\n  .gpl-bottom .gpb-tab{padding:14px 16px;font-size:.9rem}\n}\n<\/style>\n<section class=\"gpb-cta\">\n  <h2>Country-zone resolution is the start. GeoPard runs this at the field.<\/h2>\n  <p>This page works at the agroclimatic-zone level. The full GeoPard platform combines your actual yield, soil tests, NDVI, and real elevation into per-field management zones, then generates variable-rate prescriptions that respect the local climate trajectory and rotation logic.<\/p>\n  <div class=\"gpb-integ-label\">Push prescriptions and pull as-applied data with:<\/div>\n  <div class=\"gpb-integ\">\n    <span class=\"gpb-integ-chip\">John Deere Operations Center<\/span>\n    <span class=\"gpb-integ-chip\">CNH FieldOps<\/span>\n    <span class=\"gpb-integ-chip\">AGCO \/ PTx FarmEngage<\/span>\n  <\/div>\n  <a class=\"gpb-btn\" href=\"https:\/\/app.geopard.tech\/sign-up?utm_source=geopard.tech&amp;utm_medium=lead-magnet&amp;utm_campaign=agroclimate-explorer&amp;utm_content=below-tool-cta\">Register free in GeoPard &rarr;<\/a>\n<\/section>\n\n<section class=\"gpb-faq\" aria-labelledby=\"gpb-faq-h\">\n  <h2 id=\"gpb-faq-h\">Frequently asked questions<\/h2>\n  <div class=\"gpb-tabs\">\n    <div class=\"gpb-tablist\" role=\"tablist\" aria-label=\"Agroclimate Explorer FAQ\">\n      <button class=\"gpb-tab\" role=\"tab\" id=\"gpb-tab-1\" aria-controls=\"gpb-panel-1\" aria-selected=\"true\" tabindex=\"0\">Zones<\/button>\n      <button class=\"gpb-tab\" role=\"tab\" id=\"gpb-tab-2\" aria-controls=\"gpb-panel-2\" aria-selected=\"false\" tabindex=\"-1\">Projections<\/button>\n      <button class=\"gpb-tab\" role=\"tab\" id=\"gpb-tab-3\" aria-controls=\"gpb-panel-3\" aria-selected=\"false\" tabindex=\"-1\">Suitability<\/button>\n      <button class=\"gpb-tab\" role=\"tab\" id=\"gpb-tab-4\" aria-controls=\"gpb-panel-4\" aria-selected=\"false\" tabindex=\"-1\">Trade scenarios<\/button>\n      <button class=\"gpb-tab\" role=\"tab\" id=\"gpb-tab-7\" aria-controls=\"gpb-panel-7\" aria-selected=\"false\" tabindex=\"-1\">Costs &amp; access<\/button>\n      <button class=\"gpb-tab\" role=\"tab\" id=\"gpb-tab-5\" aria-controls=\"gpb-panel-5\" aria-selected=\"false\" tabindex=\"-1\">Limitations<\/button>\n      <button class=\"gpb-tab\" role=\"tab\" id=\"gpb-tab-6\" aria-controls=\"gpb-panel-6\" aria-selected=\"false\" tabindex=\"-1\">Who uses it<\/button>\n    <\/div>\n    <div class=\"gpb-panel is-active\" role=\"tabpanel\" id=\"gpb-panel-1\" aria-labelledby=\"gpb-tab-1\">\n      <h3>Why split big countries into multiple agroclimatic zones?<\/h3>\n      <p>Big countries span fundamentally different climates. The US Corn Belt (Iowa, Illinois) and the US Cotton Belt (Mississippi, Alabama) sit in different agroclimatic conditions: different soils, growing seasons, dominant crops, and trade flows. A single national average hides the signal entirely.<\/p>\n      <p>The tool currently splits 36 countries into <strong>62 agroclimatic zones<\/strong>. The US has nine (Corn Belt, Cotton Belt, Mississippi Delta, Pacific Northwest, California Central, Northern Plains, Southern Plains, Lake States, Northeast). Ukraine has six (Polissia, Forest-Steppe, Steppe, Black Sea Coast, Carpathian, Podillia). Africa is covered through C\u00f4te d&#8217;Ivoire cocoa belt, Ethiopian + Kenyan highlands, Nigerian savanna, Egyptian Nile Delta, Moroccan Atlas, Zambian commercial belt, the South African Highveld and Western Cape. Asia-Pacific now covers India, China, Bangladesh, Pakistan, Vietnam, Indonesia, Thailand, Turkey, and Israel. Latin America adds Argentina, Chile, Colombia, and Mexico. Brazil, India, China, Australia, and Canada all carry multiple zones. Each map marker carries a dataset that matches what a farmer or planner in that specific zone actually faces.<\/p>\n    <\/div>\n    <div class=\"gpb-panel\" role=\"tabpanel\" id=\"gpb-panel-2\" aria-labelledby=\"gpb-tab-2\" hidden>\n      <h3>What data drives the projections?<\/h3>\n      <p>Decade snapshots are aggregated from <strong>leading climate-model ensembles<\/strong> on a moderate-emissions trajectory, decadal averages 2020-2060. Crop suitability comes from a <strong>recognized global crop-suitability framework<\/strong>, shifted by the projected climate. Commodity prices use <strong>authoritative global commodity-price indices<\/strong> plus 10-year annualized volatility. Trade-flow concentration uses <strong>international trade-flow statistics<\/strong> for the top-5 exporter share.<\/p>\n      <p>What this tool gives you is <strong>direction and magnitude<\/strong>: where the climate is heading, which crops follow that direction, which trade flows get squeezed. It is not a forecast. It is a planning framework for the next 5-30 years.<\/p>\n    <\/div>\n    <div class=\"gpb-panel\" role=\"tabpanel\" id=\"gpb-panel-3\" aria-labelledby=\"gpb-tab-3\" hidden>\n      <h3>How are suitability scores calculated?<\/h3>\n      <p>Each zone \u00d7 decade \u00d7 crop combination gets a <strong>0-100 score<\/strong>:<\/p>\n      <p><code>80-100<\/code> \u2014 ideal climate conditions, high yield potential.<br><code>60-80<\/code> \u2014 good fit, normal yields with standard management.<br><code>40-60<\/code> \u2014 fair, marginal yields, heat or drought stress reduces upside.<br><code>20-40<\/code> \u2014 poor, the crop survives but isn&#8217;t competitive against alternatives.<br><code>0-20<\/code> \u2014 unsuitable, the climate envelope no longer supports the crop.<\/p>\n      <p>Scores shift across decades as growing-degree days, heat-stress days, season length, and rainfall change. Use the heatmap to spot the trajectory: green tiles drift down (crop becoming less competitive) or up (crop expanding into a new zone). The winners\/losers panel surfaces the biggest moves.<\/p>\n    <\/div>\n    <div class=\"gpb-panel\" role=\"tabpanel\" id=\"gpb-panel-4\" aria-labelledby=\"gpb-tab-4\" hidden>\n      <h3>What do the three trade scenarios model?<\/h3>\n      <p><strong>Open trade<\/strong> is the baseline \u2014 free-flowing exports, volatility at 10-year norms, no shocks.<\/p>\n      <p><strong>Bloc fragmentation<\/strong> models tariff walls between trade blocs. Importers pay 6-10 % more, exporters lose 10-15 % margin from lost market access. Volatility rises ~30 %. Input costs (fertilizer, fuel) creep up.<\/p>\n      <p><strong>Export ban shock<\/strong> models a major exporter going offline (2022-style Black Sea closure). Prices spike most on high-concentration crops where the top-5 exporters control over 75 % of trade \u2014 sunflower, wheat, sorghum. Fertilizer N spikes 25-40 %, so <strong>net margin can fall even as crop prices rise<\/strong> in importing countries.<\/p>\n      <p>The magnitudes are conservative midpoints from past disruption events. They show you the shape of the risk, not the exact path.<\/p>\n    <\/div>\n    <div class=\"gpb-panel\" role=\"tabpanel\" id=\"gpb-panel-7\" aria-labelledby=\"gpb-tab-7\" hidden>\n      <h3>Costs, access, and the investment composite<\/h3>\n      <p>Climate suitability is necessary but not sufficient. The tool surfaces five structural zone-level scores so the &#8220;where do I plant \u2014 or buy land?&#8221; question answers honestly.<\/p>\n      <p><strong>Logistics access (0-100).<\/strong> Distance to ports, rail density, processing infrastructure. Brazilian Cerrado scores low because it&#8217;s 1500-2000 km of poor roads to Santos. Ukrainian Black Sea Coast scores high \u2014 Odesa-Mykolaiv-Kherson ports sit at the field edge. A low logistics score typically adds 8-15% to landed cost vs port-adjacent zones.<\/p>\n      <p><strong>Input cost index (0-100, higher = more expensive).<\/strong> Fertilizer subsidies, fuel, seed cost, labor, water. India scores low (subsidies). EU zones score high (regulation + N price). California scores very high (water + labor).<\/p>\n      <p><strong>Land price index (0-100, normalized).<\/strong> Iowa Cornbelt and California Central Valley anchor the top (premium prices). Kazakhstan, Ukrainian Polissia, Ethiopia Highlands anchor the bottom (cheap dirt). For land funds, low score = where capital deploys at a discount.<\/p>\n      <p><strong>Yield gap (0-100).<\/strong> Gap between current yields and biophysical potential. US Cornbelt: ~10 \u2014 mature, near ceiling, little room for capital to lift. Nigeria savanna: 80 \u2014 huge unrealized lift if you bring inputs + mechanisation. Ethiopia Highlands: 75. The &#8220;uptake&#8221; axis \u2014 large gap means the agronomic envelope hasn&#8217;t been monetized yet.<\/p>\n      <p><strong>Investment access (0-100).<\/strong> Foreign-ownership rules + currency stability + banking depth + title clarity. US\/CA\/AU\/NZ: 90+ (open, stable). EU: 75-90. Brazil: ~60. Ukraine: ~25 (war-suppressed). China + India: ~25-30 (foreign land ownership restricted). Tells you whether outside capital can actually deploy in this zone, regardless of how good the agronomy looks.<\/p>\n      <p><strong>Investment composite (0-100)<\/strong> blends climate trajectory + cheap dirt + yield gap + logistics + access. Switch the map to the <em>Investment<\/em> metric to see the world coloured by this single score \u2014 top zones light up deep green, mature markets stay yellow, closed\/landlocked zones stay grey. The strip under the map ranks the top five.<\/p>\n    <\/div>\n    <div class=\"gpb-panel\" role=\"tabpanel\" id=\"gpb-panel-5\" aria-labelledby=\"gpb-tab-5\" hidden>\n      <h3>What this tool doesn&#8217;t model<\/h3>\n      <p><strong>Field-level variability.<\/strong> This is country-zone resolution. Soil texture, slope, drainage, microclimate, and local water-table effects can move suitability \u00b115-20 pts within a single zone. For field-level trajectories, register a GeoPard account and pull the same logic against your real boundaries and yield history.<\/p>\n      <p><strong>Breeding and varietal innovation.<\/strong> Suitability assumes today&#8217;s commercial cultivars. Heat-tolerant wheat, drought-tolerant maize, late-budding wine grape selections \u2014 none of these are factored in. Expect the actual envelope for any crop to widen 5-10 pts compared to what&#8217;s shown here as breeding catches up.<\/p>\n      <p><strong>Irrigation and infrastructure.<\/strong> Suitability is calibrated for the dominant water regime in each zone (mostly rainfed). California Central Valley and Murray-Darling Basin scores assume current irrigation access; if water allocations tighten, the real picture is worse than shown.<\/p>\n      <p><strong>Policy and subsidies.<\/strong> Trade scenarios capture price-shock magnitudes but not government responses \u2014 emergency subsidies, export quotas, strategic stockpiling, tariff retaliation. Real shocks usually trigger policy interventions that smooth the worst spikes.<\/p>\n      <p><strong>Yield vs suitability.<\/strong> Suitability scores reflect climate fit, not absolute yield. Two zones at suitability 70 can produce very different t\/ha depending on management intensity, input costs, and operator skill. Treat the scores as <strong>directional<\/strong>, not bookable.<\/p>\n    <\/div>\n    <div class=\"gpb-panel\" role=\"tabpanel\" id=\"gpb-panel-6\" aria-labelledby=\"gpb-tab-6\" hidden>\n      <h3>Who is this built for?<\/h3>\n      <p><strong>Agronomists and crop consultants<\/strong> building 5-10 year rotation plans for their clients.<\/p>\n      <p><strong>Procurement and risk teams<\/strong> at ag retailers, traders, and processors who need a fast read on where exposure is shifting.<\/p>\n      <p><strong>Cooperative directors<\/strong> planning storage, contract mix, and capital projects against changing crop mixes.<\/p>\n      <p><strong>Land funds and ag-investment groups<\/strong> scouting where dirt is cheap, yield gaps are large, climate is improving, and foreign capital can actually deploy. The Investment map metric is designed for them \u2014 switch the map and look for deep-green dots, ignore grey ones.<\/p>\n      <p><strong>Investors and analysts<\/strong> modeling acreage shifts, asset relocation, and supply-chain resilience.<\/p>\n      <p><strong>Universities and extension services<\/strong> using a clean visual to teach agroclimate dynamics and trade-shock pricing.<\/p>\n      <p>For field-level planning grounded in your actual farm data, that&#8217;s the paid GeoPard platform.<\/p>\n    <\/div>\n  <\/div>\n<\/section>\n<\/div>\n<script nowprocket data-no-optimize=\"1\" data-no-defer=\"1\" data-no-minify=\"1\">\n(function(){\n  var root = document.querySelector('.gpl-bottom .gpb-faq');\n  if(!root) return;\n  var tabs = root.querySelectorAll('.gpb-tab');\n  var panels = root.querySelectorAll('.gpb-panel');\n  function activate(idx){\n    tabs.forEach(function(t,i){\n      var on = i===idx;\n      t.setAttribute('aria-selected', on ? 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