{"id":167,"date":"2026-10-13T10:55:30","date_gmt":"2026-10-13T10:55:30","guid":{"rendered":"https:\/\/therisk.global\/biodiversity-nexus\/?page_id=167"},"modified":"2026-10-13T15:59:24","modified_gmt":"2026-10-13T15:59:24","slug":"spatial-statistics","status":"publish","type":"page","link":"https:\/\/therisk.global\/biodiversity-nexus\/stem\/spatial-statistics\/","title":{"rendered":"Spatial statistics for biodiversity"},"content":{"rendered":"\n<!-- Nexus network page \u00b7 https:\/\/therisk.global\/biodiversity-nexus\/stem\/spatial-statistics\/ \u00b7 source template \u00b7 generated by integrations\/wordpress\/network\/build.mjs, never edit this file --><script type=\"text\/x-nexus\" class=\"_iub_cs_skip\" id=\"nxe-fig-engine\" 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auto;padding:0 16px;font-family:ui-sans-serif,system-ui,-apple-system,\"Segoe UI\",sans-serif;line-height:1.55;overflow-wrap:break-word}#nxe-nas67gyl.nxe :where(*,*::before,*::after){box-sizing:inherit}#nxe-nas67gyl.nxe :where(section,header,footer,nav,aside){display:block;margin:0 0 32px}#nxe-nas67gyl.nxe :where(h1,h2,h3,h4){line-height:1.2;margin:24px 0 12px;font-weight:600}#nxe-nas67gyl.nxe :where(p,ul,ol,dl,table,figure,details){margin:0 0 16px}#nxe-nas67gyl.nxe :where(ul,ol){padding-left:20px}#nxe-nas67gyl.nxe a{color:inherit;text-decoration:underline;text-underline-offset:2px}#nxe-nas67gyl.nxe table{border-collapse:collapse;width:100%;display:block;overflow-x:auto}#nxe-nas67gyl.nxe :where(th,td){padding:6px 8px;text-align:left;vertical-align:top;border-bottom:1px solid;border-color:inherit}#nxe-nas67gyl.nxe svg{display:none}#nxe-nas67gyl.nxe svg.nx-i{display:inline-block;width:18px;height:18px;vertical-align:-3px}#nxe-nas67gyl.nxe :where([role=\"tablist\"],[role=\"toolbar\"],[hidden],button,.nx-theme-toggle,.nx-live-slot){display:none}#nxe-nas67gyl.nxe img{max-width:100%;height:auto}<\/style><svg class=\"nx-defs\" aria-hidden=\"true\" focusable=\"false\" width=\"0\" height=\"0\"><defs><linearGradient id=\"nx-gi\" x1=\"0\" y1=\"0\" x2=\"1\" y2=\"1\"><stop offset=\"0\" class=\"nx-gi-a\"\/><stop offset=\"0.55\" class=\"nx-gi-b\"\/><stop offset=\"1\" class=\"nx-gi-c\"\/><\/linearGradient><linearGradient id=\"nx-giu\" gradientUnits=\"userSpaceOnUse\" x1=\"0\" y1=\"0\" x2=\"800\" y2=\"0\"><stop offset=\"0\" class=\"nx-gi-a\"\/><stop offset=\"0.55\" class=\"nx-gi-b\"\/><stop offset=\"1\" class=\"nx-gi-c\"\/><\/linearGradient><linearGradient id=\"nx-gp\" x1=\"0\" y1=\"0\" x2=\"1\" y2=\"1\"><stop offset=\"0\" class=\"nx-gp-a\"\/><stop offset=\"1\" class=\"nx-gp-b\"\/><\/linearGradient><\/defs><\/svg><section class=\"nx-hero\" data-layout=\"workbench\" aria-labelledby=\"nx-title-1\"><div class=\"nx-container\"><div class=\"nx-theme-toggle\" role=\"group\" aria-label=\"Appearance of this page\" hidden><button type=\"button\" data-mode=\"light\" aria-pressed=\"false\">Light<\/button><button type=\"button\" data-mode=\"dark\" aria-pressed=\"false\">Dark<\/button><button type=\"button\" data-mode=\"auto\" aria-pressed=\"true\">Auto<\/button><\/div><div class=\"nx-folio\" aria-label=\"Document reference\"><strong>G05 \u00b7 METHOD \u00b7 spatial-statistics<\/strong>GCRI dossier \u00b7 service level R0<\/div><div class=\"nx-hero-grid\"><div class=\"nx-hero-text\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">GCRI<\/span><span class=\"nx-eyebrow\" aria-hidden=\"true\">\u00b7<\/span><span class=\"nx-eyebrow\">Biodiversity Nexus<\/span><span class=\"nx-eyebrow\" aria-hidden=\"true\">\u00b7<\/span><span class=\"nx-eyebrow\">Established<\/span><\/div><div class=\"nx-accent-row\"><span class=\"nx-accent-rule\" aria-hidden=\"true\"><\/span><span>Method page \u00b7 Spatial statistics and geostatistics<\/span><\/div><h1 id=\"nx-title-1\" class=\"nx-hero-title\">Spatial statistics for biodiversity<\/h1><p class=\"nx-tagline\">Biodiversity data are clustered, unevenly sampled and dependent from place to place. Spatial statistics accounts for that dependence, interpolates between sparse samples, detects hotspots and gives every map an uncertainty surface, so that gaps in sampling are not mistaken for gaps in nature.<\/p><div class=\"nx-actions\"><a class=\"nx-btn\" data-variant=\"primary\" href=\"https:\/\/therisk.global\/biodiversity-nexus\/contact\/\">Make an enquiry <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a class=\"nx-btn\" data-variant=\"secondary\" href=\"https:\/\/therisk.global\/biodiversity-nexus\/stem\/\">Back to STEM foundation of Biodiversity Nexus<\/a><\/div><\/div><div class=\"nx-hero-panel\"><div class=\"nx-register\"><div class=\"nx-register-head\"><span class=\"nx-eyebrow\"><strong>Method record<\/strong><\/span><span class=\"nx-eyebrow\">spatial-statistics<\/span><\/div><ol class=\"nx-register-rows\"><li><div><span class=\"nx-register-k\">Method<\/span><span class=\"nx-register-v\">Spatial statistics and geostatistics<\/span><\/div><\/li><li><div><span class=\"nx-register-k\">Steward<\/span><span class=\"nx-register-v\"><a class=\"nx-link\" href=\"https:\/\/therisk.global\/space-earth-observation\/\">Space and Earth Observation<\/a><\/span><\/div><\/li><li><div><span class=\"nx-register-k\">Applied in<\/span><span class=\"nx-register-v\">Biodiversity Nexus<\/span><\/div><\/li><li><div><span class=\"nx-register-k\">Data<\/span><span class=\"nx-register-v\"><a class=\"nx-link\" href=\"#nx-sec-data\">4 inputs<\/a><\/span><\/div><\/li><li><div><span class=\"nx-register-k\">Checks<\/span><span class=\"nx-register-v\"><a class=\"nx-link\" href=\"#nx-sec-checks\">3 validation steps<\/a><\/span><\/div><\/li><li><div><span class=\"nx-register-k\">Canonical page<\/span><span class=\"nx-register-v\"><a class=\"nx-link\" href=\"https:\/\/therisk.global\/stem\/mathematics\/spatial-statistics\/\">STEM Commons<\/a><\/span><\/div><\/li><\/ol><p class=\"nx-register-foot\">GCRI \u00b7 Established \u00b7 service level R0<\/p><\/div><\/div><\/div><\/div><\/section> <nav class=\"nx-index-strip\" data-nx-spy=\"true\" aria-label=\"On this page\"><div class=\"nx-container\"><a href=\"#nx-sec-brief-answer\"><span>01<\/span>The short answer<\/a><a href=\"#nx-s-3-sec\"><span>02<\/span>Spatial model, in outline<\/a><a href=\"#nx-sec-application\"><span>03<\/span>What spatial statistics and\u2026<\/a><a href=\"#nx-sec-terms\"><span>04<\/span>Terms used on this page<\/a><a href=\"#nx-sec-field\"><span>05<\/span>Landscapes and remoteness in the\u2026<\/a><a href=\"#nx-sec-canvas\"><span>06<\/span>The method as a run graph<\/a><a href=\"#nx-sec-data\"><span>07<\/span>What the method consumes<\/a><a href=\"#nx-sec-checks\"><span>08<\/span>How results are checked<\/a><\/div><\/nav> <section id=\"nx-sec-brief-answer\" class=\"nx-section\" data-hue=\"biodiversity\" data-variant=\"split\" aria-labelledby=\"nx-s-2\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">01<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">In brief<\/span><\/div><h2 id=\"nx-s-2\" class=\"nx-section-title\">The short answer.<\/h2><p class=\"nx-lede\">Spatial statistics is the set of methods that model how values vary and correlate across space. For biodiversity it corrects for clustered and uneven sampling, interpolates between sparse field measurements, detects hotspots of change and threat, and attaches an uncertainty surface so gaps in sampling are not read as gaps in nature.<\/p><\/div><\/div><\/section><section id=\"nx-s-3-sec\" class=\"nx-section\" data-hue=\"climate\" data-tone=\"alt\" aria-labelledby=\"nx-s-3\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">02<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Console<\/span><\/div><h2 id=\"nx-s-3\" class=\"nx-section-title\">Spatial model, in outline.<\/h2><p class=\"nx-lede\">The working screen behind this method: its structure, terms and states. Names are placeholders and values illustrative.<\/p><\/div><div class=\"nx-section-body\"><figure class=\"nx-fk nx-cx\" data-fk=\"cx-biodiversity-method-spatial\" data-cx=\"biodiversity.method-spatial\" data-variant=\"section\" aria-label=\"Spatial model: illustrative console with placeholder names and values\" data-nx-z=\"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\"><figcaption class=\"nx-fk-cap\"><span>Spatial model: the screen's structure, terms and states for Biodiversity.<\/span><span data-honesty=\"true\">Placeholder names and illustrative values; a design, not a record or a live system.<\/span><\/figcaption><\/figure><\/div><\/div><\/section><section id=\"nx-sec-application\" class=\"nx-section\" data-hue=\"water\" data-variant=\"split\" aria-labelledby=\"nx-s-4\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">03<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Application<\/span><\/div><h2 id=\"nx-s-4\" class=\"nx-section-title\">What spatial statistics and geostatistics does here.<\/h2><p class=\"nx-lede\">Spatial statistics and geostatistics analyse data that vary across space, accounting for spatial dependence. They estimate values at unsampled locations and test for spatial patterns. In biodiversity and nature, climate and hazards and oceans and coasts, spatial statistics produce continuous hazard and exposure surfaces with uncertainty. They reveal geographic clustering of risks and vulnerabilities across sectors. The canonical description is on <a class=\"nx-link\" href=\"https:\/\/therisk.global\/stem\/mathematics\/spatial-statistics\/\">the STEM Commons<\/a>.<\/p><\/div><div class=\"nx-section-body\"><div class=\"nx-cols\"><article><div class=\"nx-glyph-row\"><span class=\"nx-glyph\" data-tone=\"accent\" data-size=\"lg\"><svg class=\"nx-i\" viewBox=\"0 0 24 24\" aria-hidden=\"true\" focusable=\"false\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M14.106 5.553a2 2 0 0 0 1.788 0l3.659-1.83A1 1 0 0 1 21 4.619v12.764a1 1 0 0 1-.553.894l-4.553 2.277a2 2 0 0 1-1.788 0l-4.212-2.106a2 2 0 0 0-1.788 0l-3.659 1.83A1 1 0 0 1 3 19.381V6.618a1 1 0 0 1 .553-.894l4.553-2.277a2 2 0 0 1 1.788 0z\"\/><path d=\"M15 5.76v15\"\/><path d=\"M9 3.24v15\"\/><\/svg><\/span><\/div><h3 class=\"nx-h3 nx-mt-2\">Bias-corrected distribution surfaces<\/h3><p class=\"nx-p nx-mt-1\">Point process models with sampling-effort covariates separate where species occur from where people look for them, and report prediction uncertainty by cell.<\/p><\/article><article><div class=\"nx-glyph-row\"><span class=\"nx-glyph\" data-tone=\"accent\" data-size=\"lg\"><svg class=\"nx-i\" viewBox=\"0 0 24 24\" aria-hidden=\"true\" focusable=\"false\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 3v18h18\"\/><path d=\"m19 9-5 5-4-4-3 3\"\/><\/svg><\/span><\/div><h3 class=\"nx-h3 nx-mt-2\">Hotspots of change and threat<\/h3><p class=\"nx-p nx-mt-1\">Local spatial autocorrelation statistics identify clusters of forest loss, species decline or overlapping threats, tested against randomised expectations.<\/p><\/article><article><div class=\"nx-glyph-row\"><span class=\"nx-glyph\" data-tone=\"accent\" data-size=\"lg\"><svg class=\"nx-i\" viewBox=\"0 0 24 24\" aria-hidden=\"true\" focusable=\"false\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"m12.83 2.18a2 2 0 0 0-1.66 0L2.6 6.08a1 1 0 0 0 0 1.83l8.58 3.91a2 2 0 0 0 1.66 0l8.58-3.9a1 1 0 0 0 0-1.83Z\"\/><path d=\"m22 17.65-9.17 4.16a2 2 0 0 1-1.66 0L2 17.65\"\/><path d=\"m22 12.65-9.17 4.16a2 2 0 0 1-1.66 0L2 12.65\"\/><\/svg><\/span><\/div><h3 class=\"nx-h3 nx-mt-2\">Interpolating field measurements<\/h3><p class=\"nx-p nx-mt-1\">Kriging and spatial regression estimate soil carbon, water quality or species richness between plots, with variance maps published beside the estimates.<\/p><\/article><\/div><\/div><\/div><\/section><section id=\"nx-sec-terms\" class=\"nx-section\" data-hue=\"biodiversity\" data-tone=\"alt\" data-variant=\"stack\" aria-labelledby=\"nx-s-5\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">04<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Key terms<\/span><\/div><h2 id=\"nx-s-5\" class=\"nx-section-title\">Terms used on this page.<\/h2><p class=\"nx-lede\">Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.<\/p><\/div><div class=\"nx-section-body\"><div class=\"nx-table-wrap\"><table class=\"nx-table\" data-stack=\"true\"><thead><tr><th scope=\"col\">Term<\/th><th scope=\"col\">Definition<\/th><\/tr><\/thead><tbody><tr><td data-label=\"Term\">Sampling bias<\/td><td data-label=\"Definition\">Uneven survey effort, such as records clustered near roads, that distorts apparent species distributions.<\/td><\/tr><tr><td data-label=\"Term\">Hotspot analysis<\/td><td data-label=\"Definition\">A statistical test for clusters of high or low values that are unlikely to arise by chance.<\/td><\/tr><tr><td data-label=\"Term\">Uncertainty surface<\/td><td data-label=\"Definition\">A map showing how reliable an estimate is at each location.<\/td><\/tr><\/tbody><\/table><\/div><\/div><\/div><\/section><section id=\"nx-sec-field\" class=\"nx-section\" data-hue=\"climate\" aria-labelledby=\"nx-s-6\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">05<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Geography<\/span><\/div><h2 id=\"nx-s-6\" class=\"nx-section-title\">Landscapes and remoteness in the Mekong Basin.<\/h2><p class=\"nx-lede\">Mountain ranges, deserts, wetlands, glaciers and reefs, and how remote each division is from large cities, shown for the Mekong Basin as an example geography for this subject.<\/p><\/div><div class=\"nx-section-body\"><div class=\"nx-canvas-wrap\"><div class=\"nx-map nx-cmap\" data-nx-map=\"ctx\" data-cmap=\"mekong:biodiversity\" data-ramp=\"green\" data-basis=\"case\" data-focus=\"0 0 2000 1400|594 462 1144 1364|516 0 849 1201|911 260 1406 1290|778 321 1279 917\"><figure class=\"nx-fk\" data-fk=\"map-mekong-biodiversity\" data-ramp=\"green\" 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\"><figcaption class=\"nx-fk-cap\"><span>Mountain ranges, deserts, wetlands, glaciers and reefs, and how remote each division is from large cities.<\/span><span data-honesty=\"true\">Indicator derived from Natural Earth at map scale; a screening view, not an assessment.<\/span><\/figcaption><\/figure><div class=\"nx-live-slot nx-live-slot--map\" data-nxf-slot=\"map\" data-nxf-kind=\"map\" data-nxf-resource=\"nexus:\/\/gcri\/G05\/stem\/spatial-statistics\/#map\" data-nxf-title=\"Biodiversity Nexus live map\" data-nxf-height=\"560\" hidden><\/div><div class=\"nx-map-hud\"><span class=\"nx-eyebrow\">GCRI \u00b7 Biodiversity Nexus \u00b7 field<\/span><span class=\"nx-eyebrow nx-map-hud-right\">DESIGN FIGURE<\/span><\/div><\/div><\/div><\/div><\/div><\/section><section id=\"nx-sec-canvas\" class=\"nx-section\" data-hue=\"water\" data-tone=\"alt\" aria-labelledby=\"nx-s-7\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">06<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Canvas<\/span><\/div><h2 id=\"nx-s-7\" class=\"nx-section-title\">The method as a run graph.<\/h2><p class=\"nx-lede\">Data from the source register feeds the methods; calibration and an independent test gate the estimate and its limits; the decision stays with the competent authority.<\/p><\/div><div class=\"nx-section-body\"><div class=\"nx-plate\" data-wide=\"true\"><div class=\"nx-plate-label\"><span class=\"nx-eyebrow\"><strong>Method canvas<\/strong> \u00b7 Spatial statistics and geostatistics as applied here<\/span><span class=\"nx-eyebrow\">Design, not a record<\/span><\/div><div class=\"nx-figure-frame\" data-scene=\"true\"><svg class=\"nx-figure nx-ui nx-dag\" viewBox=\"0 0 1200 564\" data-nx-dag=\"true\" data-w=\"1200\" data-h=\"564\" role=\"img\" aria-labelledby=\"nx-dag-g05-stem-spatial-statistics-gis-chain-t nx-dag-g05-stem-spatial-statistics-gis-chain-d\" data-nx-z=\"zVzNcuO4EX4VFHPZrZgy8cO\/qpGrvLYyo1qP7IzlbOYIk7DEHYpUSMp\/pxxzzkPkFXLPo+yTpPBDipRECTTl2T3Yomyh0d3o\/tD4AOhDyB7ysw9LWhQsS0AUDo3k2QzpzJxZtpkXbGHmS1pENDbzghZRXkRBbs6i3AzmNErMMC1yAzxFYTEfGtAxwJxFs3khn5XUuyQq8qGxyll2u6QBu07ucmacfQiiLIgZCGKa839zWQ8Ri0MDBM9DwzNA8CJesqFhDVzj9OzDqZJ49mFBs28s664vzbL0yQCPEXv6KX0eGhawgAd4J+zh70PDFQ9fhwYxgOziF2maU77\/pOxzDJBmEUuKoUFXRcp7ywozY48sE8YtaTFfm6a6DYfGZ8C7vAIeIOBKdP4qLJPSexpmxtEj+52sU31rmHgqYy5jQbGWEdDkkdZCCVnWOphshxgge+Z6naqG7Z97iOJ4aKyy+Ic\/dQ7lHyv5lWJLmrDY5EINwF1qgBfxe6cCjsUFxFFSC+s5jTIzN8AzFO2eUdnoBYoG4AWVDQv2XOt5kSYpWJlR8g2JrqEn+sa2AR7SpDDz6JUNDWgNbAPwliZNgnmaDQ0xWgaIGU8WbnQQJTOeRBZhC+MsWyU5OAX3URpGfECj4sVM2POK\/3EW8d87\/EST8MMp72XTP0kaMrOgM7Ayi3vznoYzJrQlFhw4QmEEK2\/5qIYQnhxT3Gp5Kdrk\/5VCiauEYjxo+sHbcsMiCsOY7fID5G64HN2OP07Al7tJadhsrUFxb4CQFtSkQRGlydB4TdOFGSUGyNKYDY37VVGkiQEKeh8lIZOBQbOImjG9Z7H8PIgSYyvO59FSmOJ77oBI\/6yjCZFBDUP5P7iHyOHY8H1\/4ErHkEPh0e4Xy+GO+XPpj9OZhk\/SVdHNKbxBu1dsMvCO5xXHHcAjeeW3f\/1b1y8Pkb5L+GfbvWH5m77ALvfPW3yB3IF\/JF\/8ZTzV9cUypi\/azhAfbvWGZzsloqz9QQjPojf4w3M9FWn9\/XFzdf617pAWA1x7K7R9642h7Vl4gI+k\/tX51+u7Kfjff8HVl90gP8vSlbQBywnQ9WsRWQN1jJA0wdtnAlYzhBDl44b+vu5kBpFA8fPp+SGdCSTHUxqRI2h9Pjm\/+no7vj2kuevLiIEe3q06hERbdc9Swny3j+43dz9djS\/Op+PrauJsloMsnDEgX8qikCNCXrAln+3lu4csXQyN+EW9LdKhsfxVLBnmVyyZidJKVZPQ9wAiDrgACCPxhCwLQIIAwoS\/ltWryZLwLZXfun4V9d+2NeZDXJXvh7U57eQQu90h80UXh2DbEipg2\/oDOKSuTTeHuA2H8KCoHEKT3Q7BvhyBC0CQGAOAfakKQQ5\/\/a4OOaxNH4fwoNByCB8BqQJ\/+r0dsl+bvQ5JRPVfc4jXcAj3QeWQ6Hm3Q2wPqSB1oOgS2J4cGwd6R8OQHzsaAq12S1ZJF0u4U7klx0r+Fkua2qOG9tz1lfZFvFt71yUqNzxL+B24rrTCg9bRAvMN2q8STe1lIHPt+dPvpj1paM8VXs+jq\/vd6vuOo0IHWpbQF\/iOBG9oWei4BsyaFEG5nA\/TpGlJOQz8v7X5T60IrugLy\/LSuJclGxr8MWfrRKIFGxqX15OR+ssCDo2LdLFYJVHxAhZpEhVpFiUzkLEgzcJS2AINjTgKWBKw8k+i7hoal7Sg2ksWqeAJUFqdAGHgTpLkPn1WJaRaBbhrFsmurQJcb5PsasqZMxpqCUJOR0E1pqYhCKIWCVHAnfM8NGxLUT3rOhXW1mVllYq3Q1vImcUvy7kBiowm+UOa8YjmjzEt2A+2dYIg\/lHGMAZkYAeWCQEy4cAGhP\/OCeCPAA7sRzuwADQRfzbFX3KTmPyZf\/D1MwYu\/wAQH5BNcv5\/KWi7hs5pkssaGoKV+eRw3o7X5cpcRDZYKMilnMmgKKvj\/VV56TniH6CzNBZCt6PpoU5Ro1NHZxVz1pZNv\/3zP91sdB2d7sqs3M83SkrUxgMVu6TGkTh1jgTa3XlG6FbkpQ2b49KRZLyejEo7Nvc7likfT77XAX212yGsyIYGlrGo08JG9RYbdMxe5MUN5K0KbQVsX9gyS39lQdEA34Lm3\/Yib5AuFmkCZlkU1oA2Y3karzgj1ANqK41OAFdDB2oRlqt1aOGeWHtQkjbYVpKg+1a0RQqwoeUfHW4RQSfQ8iu8xXPv0fuEX7WxETlKOWTtBMdqGPWwo7KV2P0Acnp++7MeOlZd2r4OXtVCvqNJnMk5LH+dPBqIiImtEBFi54iIiB2sEBES9\/0RUSRJIHpDeoiIfWtniy6IaDcQsVppK\/z5RDM+\/+WsGyLymTPn5KrQgdXrz5AWvYrPSqPuiIghPBIitkrqjIgY2X0REddB9YiIiKHbHxEx8nYiYjWM3eAD2\/h7IyJ2dKjjs82Q72iXZ+l0IpKnEyJiQt4FEbFtf0dEFBRPJ0TcaLEHEVu5R4mIFUGl8Oc8ofHLBh4u0pDFTUD8cjeZjCcfa5iYPrIspi88RF7ThMaAf7KOjBcpzQsag4yxB\/4R1kRJ2XGUayOl0vQECPVOQLZKkiiZHVqoO0dbqTtHW6o7fdfqRMHteyzWCSaN1TqEMTZtgAAG2HS0EZPYZO8CWw2nHq5U9vZdYn++vhxd6QFm1afeCnt3PnQ0T291vZVZGhBqQ69cDteW2bZd33p\/C4TaxFGb2D2X2Qph2lCUBgFLCrBS+BYISsLnJslFt8sjIVO6twOqyL1Oy\/R1C\/tgGQvkS11HD2n3t6+1NkXwjxVbsXDnXoucACqOX8HqRbpYpnlUMCBg99BE8Ne70d3osjYPPIngyUW4szphkLMkj4roMSpeeiL\/horVDKBs3TsBOOrIXX\/64KAk7QmgkvR2+sBRc8h70AcOchr0wRsnAIc4e0mEjVHVQ8rK7r5UQoeJoOpTj0toJkRHs\/TohFpqaUC\/Cx11TKrOJxB\/gPpBv0ugOv7Yk0+QmHK4fhZ504lRcF3SlVGY0YLt3uGV+LnaKKDvkoBlBY2SCuYkdjbkCOj8eD6tkwoZTWYMLFkGAhbHNeBc0PwbC0H0AJ4Y\/dYTO2vqnQCuk\/ytB5r9GYaDkjqDZg+Gocyy92AYOGiuGQYXoNgGtil+TPu1M2i28Qy14eyGLL2ZBh693fBSk2lo5kFHq\/R4hmZG6UAm8t+FcHDXh9\/7EQ710dAATG3CoQJMfcJhR8UJmycCqqMNCpOmUcw0DgRslZri7HnMHllc5xnE\/Yc0qVRQSHmzuo+jgMoNK02wFIrVDgLoFJgetI7EMByUpI2VlaS3Mwyegtv3YBg86P3xzgN42NvLV4jY0EOnynff9UBA1aseX1FLpo5W6ZEUVVpqwK1vlQf56+RE\/wrVx7i8oNOPnNCtUEXidaIX1i1szZrWdyoKw9HdJWNBlK937jfOn6nDA6v7JkoLAM3nLAQLumyi9aY4Adfnd9NP11\/G0681xL7J0oIFBQsBzRgFdFXM02xNCHD4XtI8l8b1Re+Gwieg1PKk1u1eJOcH6I4E5YdFaWP5WtTbwRxa8P0Od3HhNThHwJ1Di1fAj9DSRl9o4f3nsRqDqwdYa6t74\/DoYnxbuyxx4JJn1a8eErclSVcr9XC5zDedo1mWh3aczXLc3mezIHTUrb6ewFyBjsYJLZFIh4FzESURR7ydt4iVX9Tyw6slZO0KMSG1O2BNIYvFjuMLMv5LkgYJTr6UK278VYKlXNhFru2pO4PQHvjvIReT\/nIl5S1DDg6so\/mhXJuImLOwirljeELSO025x\/BEQ2NUbnsfJSaqWVvIJm5P2fwrCsrYLc93reVgr345T8pBZbZ1uF1PkLpezx9O23NS3ekjaJ2Tbv1aP0T17x\/YD6lYZjchzsZEpD1rELWjBabjz6Or8WTEtwWvJyPw+fymRKptJ0gXQL4EF07gD8IHfLbnPrCJhvbQlThCHPLWWU\/eKR0nM5YXh9TFtjXgRA\/XuHzurjS2iWx5BL23zuK0qW4jd4CxVL187q66jaFseQTVNzbF2xR3LRUi4qG7yq51pBBRVZlepVKm1QZn19bpxhH8ZuIXGQ2+qXBXme+u0cfG9S\/0qNUnG0Ji855m23ObS9QUVJfpeXyfe5dQPat9a6C3ZbV9uvag6Z6omY9iPHKQ2s9vSu1pvm1BPeO3kveg8f47mO73MRw2DBfLFy3TN5L\/kOG2Zfcd9ars4sDt7pDad9QR0jO9ZS\/4oAug088BtWqLYF9lfV1qXwdgpDv6O3Z2DpqPnL4RUJWxNfMbUvs6gOhtOzXp1YOGY\/do4y4m\/i2p7WY3KLanJqNWfnHKs1kqW75\/Uooqwu3JlKe+Br6LfAdDx3c85LrG5pSfiBvaAp9g2UDO\/OWznPxRY\/JvWi5PTqlv0XBkI17c1i9b1epkXKvV24bYTJOG2FIXLtYf9NrYmlz\/0v41LOty31XfPFKv90nDjg71vmujoxT848ntzehiev2FV\/u3o6vRxXR0CSbXly0bp9tcmHiXm0VUxKypmrOhGqqdoeTdqdOwepVYJdV7c\/0nBuv6l8noS6NLEd9Rkg+N9ClhmbHWgdv1CHZsW6ibhZu6tNBXH8e3oGB00dFQ3+9l6Hhycze9bbE0SpYrfvJZ31Rf6yDRvCyFQhB3uI1a2mzDnoN7N91jdLoqOlq9qU+L1VEScuI\/zUC+yh5owDpajfqN9Ohv48vR5GLUYjZ7jEJ+s7WL3UhrtMWBtKvRJU\/mBSvmaQiWdMZAEGmfIqt8QPqN\/N3k6vri57aRXyVxGnzrNPJEa+TH8nDnaqsQ+j8=\"><title id=\"nx-dag-g05-stem-spatial-statistics-gis-chain-t\">Spatial statistics and geostatistics in Biodiversity Nexus: from layers to a published map<\/title><desc id=\"nx-dag-g05-stem-spatial-statistics-gis-chain-d\">Layers are ingested with their licences, reprojected and harmonised, analysed (overlay, zonal statistics, indices), checked for uncertainty and published as a map with its passport. Design of the process, not a record of a run.<\/desc><\/svg><\/div><\/div><p class=\"nx-caption\"><strong>Fig. 01<\/strong><span>Nodes carry their type, metrics and state; connectors show what feeds what; the gates are the validation steps; the timeline is one application. Design of the method's use, not a record of a run.<\/span><\/p><\/div><\/div><\/section><section id=\"nx-sec-data\" class=\"nx-section\" data-hue=\"biodiversity\" data-variant=\"split\" aria-labelledby=\"nx-s-8\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">07<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Data<\/span><\/div><h2 id=\"nx-s-8\" class=\"nx-section-title\">What the method consumes.<\/h2><p class=\"nx-lede\">Datasets and records used by spatial statistics and geostatistics on this platform, with the role each plays and the label its values carry. Sources are listed in <a class=\"nx-link\" href=\"https:\/\/therisk.global\/biodiversity-nexus\/research\/sources\/\">the source register<\/a>.<\/p><\/div><div class=\"nx-section-body\"><div class=\"nx-table-wrap\"><table class=\"nx-table\" data-stack=\"true\"><thead><tr><th scope=\"col\">Data<\/th><th scope=\"col\">Role<\/th><th scope=\"col\">Label<\/th><\/tr><\/thead><tbody><tr><td data-label=\"Data\">Occurrence records with effort metadata<\/td><td data-label=\"Role\">Bias correction<\/td><td data-label=\"Label\"><span class=\"nx-chip\">OBSERVED<\/span><\/td><\/tr><tr><td data-label=\"Data\">Field plots and transects<\/td><td data-label=\"Role\">Interpolation and model fitting<\/td><td data-label=\"Label\"><span class=\"nx-chip\">OBSERVED<\/span><\/td><\/tr><tr><td data-label=\"Data\">Remote sensing covariates<\/td><td data-label=\"Role\">Predictors for spatial models<\/td><td data-label=\"Label\"><span class=\"nx-chip\">OBSERVED<\/span><\/td><\/tr><tr><td data-label=\"Data\">Administrative and ecosystem reporting units<\/td><td data-label=\"Role\">Aggregation and reporting<\/td><td data-label=\"Label\"><span class=\"nx-chip\">OFFICIAL<\/span><\/td><\/tr><\/tbody><\/table><\/div><div class=\"nx-live-slot\" data-nxf-slot=\"data\" data-nxf-kind=\"data\" data-nxf-resource=\"nexus:\/\/gcri\/G05\/stem\/spatial-statistics\/#data\" data-nxf-title=\"Method record\" data-nxf-height=\"520\" hidden><\/div><div class=\"nx-live-slot\" data-nxf-slot=\"evidence\" data-nxf-kind=\"evidence\" data-nxf-resource=\"nexus:\/\/gcri\/G05\/stem\/spatial-statistics\/#evidence\" data-nxf-title=\"Evidence\" data-nxf-height=\"520\" hidden><\/div><\/div><\/div><\/section><section id=\"nx-sec-checks\" class=\"nx-section\" data-hue=\"climate\" data-tone=\"alt\" data-variant=\"split\" aria-labelledby=\"nx-s-9\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">08<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Validation<\/span><\/div><h2 id=\"nx-s-9\" class=\"nx-section-title\">How results are checked.<\/h2><p class=\"nx-lede\">Predictions are tested using spatial cross-validation that respects dependence. Uncertainty maps are compared with independent observations.<\/p><\/div><div class=\"nx-section-body\"><div class=\"nx-table-wrap\"><table class=\"nx-table\" data-stack=\"true\"><thead><tr><th scope=\"col\">Check<\/th><th scope=\"col\">How it is done<\/th><\/tr><\/thead><tbody><tr><td data-label=\"Check\">Spatial cross-validation<\/td><td data-label=\"How it is done\">Test data are held out in spatial blocks so that dependence does not inflate skill<\/td><\/tr><tr><td data-label=\"Check\">Residual autocorrelation<\/td><td data-label=\"How it is done\">Model residuals are tested for remaining spatial structure<\/td><\/tr><tr><td data-label=\"Check\">Scale sensitivity<\/td><td data-label=\"How it is done\">Results are compared across grid sizes and zonings to expose the effects of aggregation<\/td><\/tr><\/tbody><\/table><\/div><p class=\"nx-note nx-mt-3\">Results depend on the scale and zoning of analysis. Sparse or clustered sampling limits prediction in unsampled areas.<\/p><\/div><\/div><\/section><section id=\"nx-sec-connections\" class=\"nx-section\" data-hue=\"water\" data-variant=\"stack\" aria-labelledby=\"nx-s-10\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">09<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Connections<\/span><\/div><h2 id=\"nx-s-10\" class=\"nx-section-title\">Topics that rely on this method.<\/h2><\/div><div class=\"nx-section-body\"><ul class=\"nx-list\" data-nav=\"true\"><li><a class=\"nx-link\" href=\"https:\/\/therisk.global\/biodiversity-nexus\/topics\/ecosystem-integrity\/\"><span>Ecosystem integrity<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-link\" href=\"https:\/\/therisk.global\/biodiversity-nexus\/topics\/species-and-genetic-diversity\/\"><span>Species and genetic diversity<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-link\" href=\"https:\/\/therisk.global\/biodiversity-nexus\/topics\/forest-and-landscapes\/\"><span>Forests and landscapes<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-link\" href=\"https:\/\/therisk.global\/biodiversity-nexus\/topics\/wetlands-and-freshwater\/\"><span>Wetlands and freshwater<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-link\" href=\"https:\/\/therisk.global\/biodiversity-nexus\/topics\/coastal-marine-biodiversity\/\"><span>Coastal and marine biodiversity<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-link\" href=\"https:\/\/therisk.global\/biodiversity-nexus\/topics\/restoration-and-nature-based-solutions\/\"><span>Restoration and nature-based solutions<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-link\" href=\"https:\/\/therisk.global\/biodiversity-nexus\/topics\/ecosystem-services\/\"><span>Ecosystem services<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-link\" href=\"https:\/\/therisk.global\/biodiversity-nexus\/topics\/nature-data-rights\/\"><span>Nature data and rights<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><\/ul><\/div><\/div><\/section><section id=\"nx-sec-stewardship\" class=\"nx-section\" data-hue=\"biodiversity\" data-tone=\"alt\" aria-labelledby=\"nx-s-11\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">10<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Stewardship<\/span><\/div><h2 id=\"nx-s-11\" class=\"nx-section-title\">Who maintains the method.<\/h2><p class=\"nx-lede\"><a class=\"nx-link\" href=\"https:\/\/therisk.global\/space-earth-observation\/\">Space and Earth Observation<\/a> stewards spatial statistics and geostatistics for the Consortium and reviews how it is applied across platforms.<\/p><\/div><div class=\"nx-section-body\"><p class=\"nx-p\"><a class=\"nx-link\" href=\"https:\/\/therisk.global\/stem\/mathematics\/spatial-statistics\/\">Canonical page: Spatial statistics and geostatistics<\/a><\/p><\/div><\/div><\/section><section id=\"nx-s-12-sec\" class=\"nx-section\" data-hue=\"climate\" aria-labelledby=\"nx-s-12\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">11<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Connected<\/span><\/div><h2 id=\"nx-s-12\" class=\"nx-section-title\">Where this page leads across the Consortium.<\/h2><\/div><div class=\"nx-section-body\"><ul class=\"nx-dest\"><li><a class=\"nx-dest-card\" href=\"https:\/\/therisk.global\/stem\/mathematics\/spatial-statistics\/\"><span class=\"nx-dest-top\"><span class=\"nx-dest-rel\">Canonical method page<\/span><span class=\"nx-dest-host\">GCRI<\/span><\/span><span class=\"nx-dest-title\">Spatial statistics and geostatistics<\/span><span class=\"nx-dest-why\">Platform application links to the canonical method page.<\/span><span class=\"nx-dest-go\" aria-hidden=\"true\"><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/span><\/a><\/li><li><a class=\"nx-dest-card\" href=\"https:\/\/therisk.global\/space-earth-observation\/stem\/spatial-statistics\/\"><span class=\"nx-dest-top\"><span class=\"nx-dest-rel\">Steward platform<\/span><span class=\"nx-dest-host\">GCRI<\/span><\/span><span class=\"nx-dest-title\">Spatial statistics for EO<\/span><span class=\"nx-dest-why\">Space and Earth Observation stewards this method.<\/span><span class=\"nx-dest-go\" aria-hidden=\"true\"><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/span><\/a><\/li><\/ul><\/div><\/div><\/section><section id=\"nx-s-13-sec\" class=\"nx-section\" data-hue=\"water\" data-tone=\"alt\" aria-labelledby=\"nx-s-13\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">12<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Questions<\/span><\/div><h2 id=\"nx-s-13\" class=\"nx-section-title\">Questions and answers.<\/h2><\/div><div class=\"nx-section-body\"><div class=\"nx-faq\"><details><summary>What are the limits of spatial statistics and geostatistics in this field?<\/summary><div class=\"nx-answer\">Results depend on the scale and zoning of analysis. Sparse or clustered sampling limits prediction in unsampled areas.<\/div><\/details><details><summary>How are results checked?<\/summary><div class=\"nx-answer\">Predictions are tested using spatial cross-validation that respects dependence. Uncertainty maps are compared with independent observations.<\/div><\/details><details><summary>Are the values on this page real?<\/summary><div class=\"nx-answer\">The data names, roles and checks are real descriptions of practice. The canvas shows a design of the method's use, not a run; no result is reported here.<\/div><\/details><details><summary>Where else is this method applied?<\/summary><div class=\"nx-answer\">The <a class=\"nx-link\" href=\"https:\/\/therisk.global\/stem\/mathematics\/spatial-statistics\/\">canonical method page<\/a> lists every platform that applies it.<\/div><\/details><\/div><\/div><\/div><\/section><section class=\"nx-section\" data-tone=\"alt\" aria-labelledby=\"nx-rel-14\"><div class=\"nx-container\"><span class=\"nx-eyebrow\">Related<\/span><h2 id=\"nx-rel-14\" class=\"nx-h3 nx-mt-2\">Around Biodiversity Nexus.<\/h2><nav class=\"nx-related nx-mt-3\" aria-label=\"Related\"><a href=\"https:\/\/therisk.global\/biodiversity-nexus\/stem\/ecology\/\">Ecology and biodiversity science <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/therisk.global\/biodiversity-nexus\/stem\/earth-observation\/\">Earth observation for biodiversity <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/therisk.global\/biodiversity-nexus\/stem\/geospatial\/\">Geospatial analysis for biodiversity <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/therisk.global\/biodiversity-nexus\/stem\/complex-systems\/\">Complex systems in ecology <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/therisk.global\/biodiversity-nexus\/stem\/causal-inference\/\">Impact evaluation for conservation <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/therisk.global\/biodiversity-nexus\/stem\/hydrology\/\">Hydrology for ecosystems <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/therisk.global\/biodiversity-nexus\/\">Biodiversity Nexus home <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/therisk.global\/biodiversity-nexus\/counterparts\/\">Counterparts across the Consortium <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/therisk.global\/\">The Global Centre for Risk and Innovation home <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/therisk.global\/trust\/\">GCRI governance and trust <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/nav><\/div><\/section><section class=\"nx-closing\" aria-labelledby=\"nx-close-15\"><div class=\"nx-container\"><span class=\"nx-eyebrow\">Biodiversity Nexus<\/span><h2 id=\"nx-close-15\" class=\"nx-section-title\">Bring your expertise to this field.<\/h2><p class=\"nx-lede\">The current service level is R0: information and enquiries. An enquiry receives a reference and names the next step; applications, payments, compute allocations and registrations open only when their team, terms and review capacity exist.<\/p><div class=\"nx-actions\"><a class=\"nx-btn\" data-variant=\"primary\" href=\"mailto:contact@therisk.global?subject=Biodiversity%20Nexus%3A%20Spatial%20statistics%20for%20biodiversity\">Write to the team <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a class=\"nx-btn\" data-variant=\"secondary\" href=\"https:\/\/therisk.global\/biodiversity-nexus\/contact\/\">See all contact routes<\/a><\/div><\/div><\/section><\/div><\/div><script class=\"_iub_cs_skip\">window.__nxMount ? window.__nxMount(document.currentScript) : null;<\/script>\n\n\n<script type=\"application\/ld+json\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"FAQPage\",\"@id\":\"https:\/\/therisk.global\/biodiversity-nexus\/stem\/spatial-statistics\/#faq\",\"isPartOf\":{\"@id\":\"https:\/\/therisk.global\/biodiversity-nexus\/stem\/spatial-statistics\/#webpage\"},\"inLanguage\":\"en\",\"mainEntity\":[{\"@type\":\"Question\",\"name\":\"What are the limits of spatial statistics and geostatistics in this field?\",\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"Results depend on the scale and zoning of analysis. 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