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<p><strong>URL: </strong><a href="http://www.fao.org/forest-resources-assessment/en/"><u>http://www.fao.org/forest-resources-assessment/en/</u></a> </p>
<p><strong>References:</strong></p> <p>Global Forest Resources Assessment 2020, Terms and Definitions (<a href="http://www.fao.org/3/I8661EN/i8661en.pdf"><u>www.fao.org/3/I8661EN/i8661en.pdf</u></a>).</p> <p>United Nations. Resolution adopted by the General Assembly on 17 December 2007 (<a href="https://undocs.org/en/A/RES/62/98">https://undocs.org/en/A/RES/62/98</a>). </p> <p><strong>Annex 1 – Terms and Definitions </strong></p> <p><strong>FOREST</strong></p> <p>Land spanning more than 0.5 hectares with <u>tree</u>s higher than 5 meters and a <u>canopy cover</u> of more than 10 percent, or trees able to reach these thresholds <em>in situ</em>. It does not include land that is predominantly under agricultural or urban land use. </p> <p><u>Explanatory notes</u></p> <ol> <li>Forest is determined both by the presence of trees and the absence of other predominant land uses. The trees should be able to reach a minimum height of 5 meters. </li> <li>Includes areas with young trees that have not yet reached but which are expected to reach a canopy cover of at least 10 percent and tree height of 5 meters or more. It also includes areas that are temporarily unstocked due to clear-cutting as part of a forest management practice or natural disasters, and which are expected to be regenerated within 5 years. Local conditions may, in exceptional cases, justify that a longer time frame is used.</li> <li>Includes forest roads, firebreaks and other small open areas; forest in national parks, nature reserves and other protected areas such as those of specific environmental, scientific, historical, cultural or spiritual interest.</li> <li>Includes windbreaks, shelterbelts and corridors of trees with an area of more than 0.5 hectares and width of more than 20 meters.</li> <li>Includes abandoned shifting cultivation land with a regeneration of trees that have, or are expected to reach, a canopy cover of at least 10 percent and tree height of at least 5 meters.</li> <li>Includes areas with mangroves in tidal zones, regardless whether this area is classified as land area or not.</li> <li>Includes rubberwood, cork oak and Christmas tree plantations. </li> <li>Includes areas with bamboo and palms provided that land use, height and canopy cover criteria are met.</li> <li><u>Excludes</u> tree stands in agricultural production systems, such as fruit tree plantations, oil palm plantations, olive orchards and agroforestry systems when crops are grown under tree cover. <u>Note:</u> Some agroforestry systems such as the “Taungya” system where crops are grown only during the first years of the forest rotation should be classified as forest.</li> </ol> <p><strong>ABOVE-GROUND BIOMASS</strong></p> <p>All living biomass above the soil including stem, stump, branches, bark, seeds, and foliage.</p> <p><u>Explanatory note </u></p> <ol> <li>In cases where forest understorey is a relatively small component of the aboveground biomass carbon pool, it is acceptable to exclude it, provided this is done in a consistent manner throughout the inventory time series.</li> </ol> <p><strong>PROTECTED AREAS</strong></p> <p>Areas especially dedicated to the protection and maintenance of biological diversity, and of natural and associated cultural resources, and managed through legal or other effective means.</p> <p><strong>FOREST AREA WITHIN PROTECTED AREAS</strong></p> <p>Forest area within formally established protected areas independently of the purpose for which the protected areas were established. </p> <p><u>Explanatory notes</u></p> <ol> <li>Includes IUCN Categories I – IV</li> <li><u>Excludes</u> IUCN Categories V-VI</li> </ol> <p><strong>FOREST AREA WITH MANAGEMENT PLAN</strong></p> <p>Forest area that has a long-term documented management plan, aiming at defined management goals, which is periodically revised. </p> <p><u>Explanatory notes</u></p> <ol> <li>A forest area with management plan may refer to forest management unit level or aggregated forest management unit level (forest blocks, farms, enterprises, watersheds, municipalities, or wider units).</li> <li>A management plan must include adequate detail on operations planned for individual operational units (stands or compartments) but may also provide general strategies and activities planned to reach management goals.</li> <li>Includes forest area in protected areas with management plan.</li> </ol> <p><strong>INDEPENDENTLY VERIFIED FOREST MANAGEMENT CERTIFICATION</strong></p> <p>Forest area certified under a forest management certification scheme with published standards and is independently verified by a third-party.</p> <p><strong>Annex 2 – Methodology</strong></p> <p><strong>Sub-indicator 1 - Annual forest area change rate</strong></p> <p><u>Unit</u>: Percent</p> <p><u>Reference period:</u> 2010-2020</p> <p><u>Method of estimation:</u> Compound annual change rate formula as follows:</p> <p><math xmlns="http://www.w3.org/1998/Math/MathML"> <mi>r</mi> <mo>=</mo> <mfenced open="[" close="]" separators="|"> <mrow> <msup> <mrow> <mfenced separators="|"> <mrow> <mfrac> <mrow> <msub> <mrow> <mi>A</mi> <mi>F</mi> </mrow> <mrow> <mi>t</mi> <mn>2</mn> </mrow> </msub> </mrow> <mrow> <msub> <mrow> <mi>A</mi> <mi>F</mi> </mrow> <mrow> <mi>t</mi> <mn>1</mn> </mrow> </msub> </mrow> </mfrac> </mrow> </mfenced> </mrow> <mrow> <mfrac bevelled="true"> <mrow> <mn>1</mn> </mrow> <mrow> <mfenced separators="|"> <mrow> <mi>t</mi> <mn>2</mn> <mo>-</mo> <mi>t</mi> <mn>1</mn> </mrow> </mfenced> </mrow> </mfrac> </mrow> </msup> <mo>-</mo> <mn>1</mn> </mrow> </mfenced> <mo>×</mo> <mn>100</mn> </math></p> <p>where: </p> <p><em>r</em> = compound annual change rate for the period <em>t<sub>1 - </sub>t<sub>2</sub></em><sub> </sub></p> <p><em>t<sub>i</sub></em> = time i (year)</p> <p><em>AF<sub>t1</sub></em> = forest area at <em>t<sub>1</sub></em> </p> <p><em>AF<sub>t2</sub></em> = forest area at <em>t<sub>2</sub></em></p> <p><u>Translation to dashboard/traffic light:</u></p> <p>The following flowchart explains the logic behind the translation of this indicator to a dashboard/traffic light:</p> <p>Forest area change direction</p> <p>Forest area stable </p> <p>or increasing</p> <p>Forest area decreasing</p> <p>Change in forest area loss rate </p> <p>Loss rate</p> <p>decreasing</p> <p>Loss rate stable</p> <p>or increasing</p> <p>The forest area change direction is determined by examining the value of the forest area change rate for the most recent period, a negative value indicate a loss of forest area, a zero value means that forest area is stable, and a positive value means that forest area has increased. The change in forest area loss rate<sup><a href="#footnote-2" id="footnote-ref-2">[1]</a></sup> is based on a comparison of the annual forest area change rate for the period 2010-2020 with the annual <u>forest area change rate for the period 2000-2010 </u>(<u>baseline).</u></p> <p><u>Comments:</u></p> <p>This traffic light takes into consideration both the direction of forest area change (if forest area increases or decreases) as well as changes in the rate of forest area loss – the latter important in order to indicate progress among countries that are losing forest area but manage to reduce the loss rate. </p> <p>The baseline should be updated every 5 years. In 2020 a new baseline was calculated for the period 2000-2010 based on updated country data. </p> <p><strong>Sub-indicator 2 – Above-ground biomass in forest </strong></p> <p><u>Unit</u>: tonnes/hectare</p> <p><u>Reference year:</u> Latest reporting year</p> <p><u>Method of estimation:</u> Reported directly by countries</p> <p><u>Translation to dashboard/traffic light:</u></p> <p>The indicator value for the latest reporting year is compared with the indicator value reported for 2010.</p> <p>The ratio (r) between the current indicator value and the value reported for 2010 is calculated; r>1 means an increase in stock per hectare, r<1 means a decrease while 1 indicates no change. A narrow interval for r has been established to indicate a stable condition, and traffic-light colors are assigned as follows:</p> <p> r ≥ 1.01 </p> <p> 0.99 < r < 1.01</p> <p> r ≤ 0.99</p> <p><strong>Sub-indicator 3 – Proportion of forest area within legally established protected areas.</strong></p> <p><u>Unit</u>: Percent</p> <p><u>Reference year:</u> Latest reporting year</p> <p><u>Method of estimation:</u> </p> <p><math xmlns="http://www.w3.org/1998/Math/MathML"> <mi>r</mi> <mo>=</mo> <mi>&nbsp;</mi> <mfrac> <mrow> <msub> <mrow> <mi>A</mi> <mi>F</mi> <mi>P</mi> </mrow> <mrow> <mfenced open="[" close="]" separators="|"> <mrow> <mi>r</mi> <mi>e</mi> <mi>f</mi> <mi>e</mi> <mi>r</mi> <mi>e</mi> <mi>n</mi> <mi>c</mi> <mi>e</mi> <mi>&nbsp;</mi> <mi>y</mi> <mi>e</mi> <mi>a</mi> <mi>r</mi> </mrow> </mfenced> </mrow> </msub> </mrow> <mrow> <msub> <mrow> <mi>A</mi> <mi>F</mi> </mrow> <mrow> <mn>2015</mn> </mrow> </msub> </mrow> </mfrac> <mo>×</mo> <mn>100</mn> </math></p> <p>Where:</p> <p><em>AFP</em> = Forest area within legally established protected areas</p> <p><em>AF</em> = Total forest area</p> <p><u>Translation to dashboard/traffic light:</u></p> <p>The indicator value for latest reporting year is compared with the indicator value reported for 2010.</p> <p>The ratio (r) between the current indicator value and the value reported for 2010 is calculated; r>1 means an increase in forest area within protected areas, r<1 means a decrease while 1 indicates no change. A narrow interval for r has been established to indicate a stable condition, and traffic-light colors are assigned as follows:</p> <p> r ≥ 1.01 </p> <p> 0.99 < r < 1.01</p> <p> r ≤ 0.99</p> <p><u>Comment:</u></p> <p>Using forest area in 2015 as denominator for estimating this indicator ensures that the time series of percentages reflect real changes in the forest area within legally established protected areas and is not affected by changes (losses or gains) in total forest area. </p> <p><strong>Sub-indicator 4 – Proportion of forest area under a long-term management plan.</strong></p> <p><u>Unit</u>: Percent</p> <p><u>Reference year:</u> Latest reporting year</p> <p><u>Method of estimation:</u> </p> <p><math xmlns="http://www.w3.org/1998/Math/MathML"> <mi>r</mi> <mo>=</mo> <mi>&nbsp;</mi> <mfrac> <mrow> <msub> <mrow> <mi>A</mi> <mi>F</mi> <mi>M</mi> <mi>P</mi> </mrow> <mrow> <mfenced open="[" close="]" separators="|"> <mrow> <mi>r</mi> <mi>e</mi> <mi>f</mi> <mi>e</mi> <mi>r</mi> <mi>e</mi> <mi>n</mi> <mi>c</mi> <mi>e</mi> <mi>&nbsp;</mi> <mi>y</mi> <mi>e</mi> <mi>a</mi> <mi>r</mi> </mrow> </mfenced> </mrow> </msub> </mrow> <mrow> <msub> <mrow> <mi>A</mi> <mi>F</mi> </mrow> <mrow> <mn>2015</mn> </mrow> </msub> </mrow> </mfrac> <mo>×</mo> <mn>100</mn> </math></p> <p>Where:</p> <p><em>AFMP</em> = Forest area under a long-term management plan</p> <p><em>AF</em> = Total forest area</p> <p><u>Translation to dashboard/traffic light: </u>The indicator value for latest reporting year is compared with the indicator value reported for 2010.</p> <p>The ratio (r) between the current indicator value and the value reported for 2010 is calculated; r>1 means an increase in areas under management plan, r<1 means a decrease while 1 indicates no change. A narrow interval for r has been established to indicate a stable condition, and traffic-light colors are assigned as follows:</p> <p> r ≥ 1.01 </p> <p> 0.99 < r < 1.01</p> <p> r ≤ 0.99</p> <p><u>Comment:</u></p> <p>Using forest area in 2015 as denominator for estimating this indicator ensures that the time series of percentages reflect real changes in the forest area under management plan and is not affected by changes (losses or gains) in total forest area. </p> <p><strong>Sub-indicator 5 – Forest area under an independently verified forest management certification scheme.</strong></p> <p><u>Unit</u>: Thousand hectares</p> <p><u>Reference year:</u> Latest reporting year (as of June 30)</p> <p><u>Method of estimation:</u> Data is collected directly from the databases of each certification scheme and provided to countries for validation.</p> <p><u>Translation to dashboard/traffic light: </u>The indicator value for latest reporting year is compared with the indicator value for previous reporting year for assessment of continuity of progress since last report.</p> <p>The ratio (r) between the current indicator value and the previously reported value is calculated; r>1 means an increase in areas under an independent forest management certification scheme, r<1 means a decrease while 1 indicates no change. A small interval for r has been established to indicate a stable condition, and traffic-light colors are assigned as follows:</p> <p> r ≥ 1.01 </p> <p> 0.99 < r < 1.01</p> <p> r ≤ 0.99</p> <p><u>Comments:</u></p> <p>Using June 30 as the date for reporting, allows for the certification bodies to have their databases updated so they can provide information to FAO by end of the year, and then be included in the annual reporting to SDG in the beginning of the following year.</p><div class="footnotes"><div><sup class="footnote-number" id="footnote-2">1</sup><p> If forest area change rate is negative (= forest loss) then: annual forest area loss rate = <strong>-</strong> (annual forest area change rate) <a href="#footnote-ref-2">↑</a></p></div></div> |
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<p><strong>URL: </strong><a href="http://www.fao.org/forest-resources-assessment/en/"><u>http://www.fao.org/forest-resources-assessment/en/</u></a> </p>
<p><strong>References:</strong></p> <p></p> <p>Global Forest Resources Assessment 2020, Guidelines and Specifications (<a href="http://www.fao.org/3/I8699EN/i8699en.pdf"><u>www.fao.org/3/I8699EN/i8699en.pdf</u></a>)</p> <p>Global Forest Resources Assessment 2020, Terms and Definitions (<a href="http://www.fao.org/3/I8661EN/i8661en.pdf"><u>www.fao.org/3/I8661EN/i8661en.pdf</u></a>).</p> <p>United Nations. Resolution adopted by the General Assembly on 17 December 2007 (<a href="https://undocs.org/en/A/RES/62/98">https://undocs.org/en/A/RES/62/98</a>). </p> <p><strong>Annex 1 – Terms and Definitions </strong></p> <p><strong>FOREST</strong></p> <p>Land spanning more than 0.5 hectares with <u>tree</u>s higher than 5 meters and a <u>canopy cover</u> of more than 10 percent, or trees able to reach these thresholds <em>in situ</em>. It does not include land that is predominantly under agricultural or urban land use. </p> <p><u>Explanatory notes</u></p> <ol> <li>Forest is determined both by the presence of trees and the absence of other predominant land uses. The trees should be able to reach a minimum height of 5 meters. </li> <li>Includes areas with young trees that have not yet reached but which are expected to reach a canopy cover of at least 10 percent and tree height of 5 meters or more. It also includes areas that are temporarily unstocked due to clear-cutting as part of a forest management practice or natural disasters, and which are expected to be regenerated within 5 years. Local conditions may, in exceptional cases, justify that a longer time frame is used.</li> <li>Includes forest roads, firebreaks and other small open areas; forest in national parks, nature reserves and other protected areas such as those of specific environmental, scientific, historical, cultural or spiritual interest.</li> <li>Includes windbreaks, shelterbelts and corridors of trees with an area of more than 0.5 hectares and width of more than 20 meters.</li> <li>Includes abandoned shifting cultivation land with a regeneration of trees that have, or are expected to reach, a canopy cover of at least 10 percent and tree height of at least 5 meters.</li> <li>Includes areas with mangroves in tidal zones, regardless whether this area is classified as land area or not.</li> <li>Includes rubberwood, cork oak and Christmas tree plantations. </li> <li>Includes areas with bamboo and palms provided that land use, height and canopy cover criteria are met.</li> <li><u>Excludes</u> tree stands in agricultural production systems, such as fruit tree plantations, oil palm plantations, olive orchards and agroforestry systems when crops are grown under tree cover. <u>Note:</u> Some agroforestry systems such as the “Taungya” system where crops are grown only during the first years of the forest rotation should be classified as forest.</li> </ol> <p><strong>ABOVE-GROUND BIOMASS</strong></p> <p>All living biomass above the soil including stem, stump, branches, bark, seeds, and foliage.</p> <p><u>Explanatory note </u></p> <ol> <li>In cases where forest understorey is a relatively small component of the aboveground biomass carbon pool, it is acceptable to exclude it, provided this is done in a consistent manner throughout the inventory time series.</li> </ol> <p><strong>PROTECTED AREAS</strong></p> <p>Areas especially dedicated to the protection and maintenance of biological diversity, and of natural and associated cultural resources, and managed through legal or other effective means.</p> <p><strong>FOREST AREA WITHIN PROTECTED AREAS</strong></p> <p>Forest area within formally established protected areas independently of the purpose for which the protected areas were established. </p> <p><u>Explanatory notes</u></p> <ol> <li>Includes IUCN Categories I – IV</li> <li><u>Excludes</u> IUCN Categories V-VI</li> </ol> <p><strong>FOREST AREA WITH MANAGEMENT PLAN</strong></p> <p>Forest area that has a long-term documented management plan, aiming at defined management goals, which is periodically revised. </p> <p><u>Explanatory notes</u></p> <ol> <li>A forest area with management plan may refer to forest management unit level or aggregated forest management unit level (forest blocks, farms, enterprises, watersheds, municipalities, or wider units).</li> <li>A management plan must include adequate detail on operations planned for individual operational units (stands or compartments) but may also provide general strategies and activities planned to reach management goals.</li> <li>Includes forest area in protected areas with management plan.</li> </ol> <p><strong>INDEPENDENTLY VERIFIED FOREST MANAGEMENT CERTIFICATION</strong></p> <p>Forest area certified under a forest management certification scheme with published standards and is independently verified by a third-party.</p> <p><strong>Annex 2 – Methodology</strong></p> <p><strong>Sub-indicator 1 - Annual forest area change rate</strong></p> <p><u>Unit</u>: Percent</p> <p><u>Reference period:</u> 2010-2020</p> <p><u>Method of estimation:</u> Compound annual change rate formula as follows:</p> <p><math xmlns="http://www.w3.org/1998/Math/MathML"> <mi>r</mi> <mo>=</mo> <mfenced open="[" close="]" separators="|"> <mrow> <msup> <mrow> <mfenced separators="|"> <mrow> <mfrac> <mrow> <msub> <mrow> <mi>A</mi> <mi>F</mi> </mrow> <mrow> <mi>t</mi> <mn>2</mn> </mrow> </msub> </mrow> <mrow> <msub> <mrow> <mi>A</mi> <mi>F</mi> </mrow> <mrow> <mi>t</mi> <mn>1</mn> </mrow> </msub> </mrow> </mfrac> </mrow> </mfenced> </mrow> <mrow> <mfrac bevelled="true"> <mrow> <mn>1</mn> </mrow> <mrow> <mfenced separators="|"> <mrow> <mi>t</mi> <mn>2</mn> <mo>-</mo> <mi>t</mi> <mn>1</mn> </mrow> </mfenced> </mrow> </mfrac> </mrow> </msup> <mo>-</mo> <mn>1</mn> </mrow> </mfenced> <mo>×</mo> <mn>100</mn> </math></p> <p>where: </p> <p><em>r</em> = compound annual change rate for the period <em>t<sub>1 - </sub>t<sub>2</sub></em><sub> </sub></p> <p><em>t<sub>i</sub></em> = time i (year)</p> <p><em>AF<sub>t1</sub></em> = forest area at <em>t<sub>1</sub></em> </p> <p><em>AF<sub>t2</sub></em> = forest area at <em>t<sub>2</sub></em></p> <p><u>Translation to dashboard/traffic light:</u></p> <p>The following flowchart explains the logic behind the translation of this indicator to a dashboard/traffic light:</p> <p>Forest area change direction</p> <p>Forest area stable </p> <p>or increasing</p> <p>Forest area decreasing</p> <p>Change in forest area loss rate </p> <p>Loss rate</p> <p>decreasing</p> <p>Loss rate stable</p> <p>or increasing</p> <p>The forest area change direction is determined by examining the value of the forest area change rate for the most recent period, a negative value indicate a loss of forest area, a zero value means that forest area is stable, and a positive value means that forest area has increased. The change in forest area loss rate<sup><a href="#footnote-2" id="footnote-ref-2">[1]</a></sup> is based on a comparison of the annual forest area change rate for the period 2010-2020 with the annual <u>forest area change rate for the period 2000-2010 </u>(<u>baseline).</u></p> <p><u>Comments:</u></p> <p>This traffic light takes into consideration both the direction of forest area change (if forest area increases or decreases) as well as changes in the rate of forest area loss – the latter important in order to indicate progress among countries that are losing forest area but manage to reduce the loss rate. </p> <p>The baseline should be updated every 5 years. In 2020 a new baseline was calculated for the period 2000-2010 based on updated country data. </p> <p><strong>Sub-indicator 2 – Above-ground biomass in forest </strong></p> <p><u>Unit</u>: tonnes/hectare</p> <p><u>Reference year:</u> Latest reporting year</p> <p><u>Method of estimation:</u> Reported directly by countries</p> <p><u>Translation to dashboard/traffic light:</u></p> <p>The indicator value for the latest reporting year is compared with the indicator value reported for 2010.</p> <p>The ratio (r) between the current indicator value and the value reported for 2010 is calculated; r>1 means an increase in stock per hectare, r<1 means a decrease while 1 indicates no change. A narrow interval for r has been established to indicate a stable condition, and traffic-light colors are assigned as follows:</p> <p> r ≥ 1.01 </p> <p> 0.99 < r < 1.01</p> <p> r ≤ 0.99</p> <p><strong>Sub-indicator 3 – Proportion of forest area within legally established protected areas.</strong></p> <p><u>Unit</u>: Percent</p> <p><u>Reference year:</u> Latest reporting year</p> <p><u>Method of estimation:</u> </p> <p><math xmlns="http://www.w3.org/1998/Math/MathML"> <mi>r</mi> <mo>=</mo> <mi>&nbsp;</mi> <mfrac> <mrow> <msub> <mrow> <mi>A</mi> <mi>F</mi> <mi>P</mi> </mrow> <mrow> <mfenced open="[" close="]" separators="|"> <mrow> <mi>r</mi> <mi>e</mi> <mi>f</mi> <mi>e</mi> <mi>r</mi> <mi>e</mi> <mi>n</mi> <mi>c</mi> <mi>e</mi> <mi>&nbsp;</mi> <mi>y</mi> <mi>e</mi> <mi>a</mi> <mi>r</mi> </mrow> </mfenced> </mrow> </msub> </mrow> <mrow> <msub> <mrow> <mi>A</mi> <mi>F</mi> </mrow> <mrow> <mn>2015</mn> </mrow> </msub> </mrow> </mfrac> <mo>×</mo> <mn>100</mn> </math></p> <p>Where:</p> <p><em>AFP</em> = Forest area within legally established protected areas</p> <p><em>AF</em> = Total forest area</p> <p><u>Translation to dashboard/traffic light:</u></p> <p>The indicator value for latest reporting year is compared with the indicator value reported for 2010.</p> <p>The ratio (r) between the current indicator value and the value reported for 2010 is calculated; r>1 means an increase in forest area within protected areas, r<1 means a decrease while 1 indicates no change. A narrow interval for r has been established to indicate a stable condition, and traffic-light colors are assigned as follows:</p> <p> r ≥ 1.01 </p> <p> 0.99 < r < 1.01</p> <p> r ≤ 0.99</p> <p><u>Comment:</u></p> <p>Using forest area in 2015 as denominator for estimating this indicator ensures that the time series of percentages reflect real changes in the forest area within legally established protected areas and is not affected by changes (losses or gains) in total forest area. </p> <p><strong>Sub-indicator 4 – Proportion of forest area under a long-term management plan.</strong></p> <p><u>Unit</u>: Percent</p> <p><u>Reference year:</u> Latest reporting year</p> <p><u>Method of estimation:</u> </p> <p><math xmlns="http://www.w3.org/1998/Math/MathML"> <mi>r</mi> <mo>=</mo> <mi>&nbsp;</mi> <mfrac> <mrow> <msub> <mrow> <mi>A</mi> <mi>F</mi> <mi>M</mi> <mi>P</mi> </mrow> <mrow> <mfenced open="[" close="]" separators="|"> <mrow> <mi>r</mi> <mi>e</mi> <mi>f</mi> <mi>e</mi> <mi>r</mi> <mi>e</mi> <mi>n</mi> <mi>c</mi> <mi>e</mi> <mi>&nbsp;</mi> <mi>y</mi> <mi>e</mi> <mi>a</mi> <mi>r</mi> </mrow> </mfenced> </mrow> </msub> </mrow> <mrow> <msub> <mrow> <mi>A</mi> <mi>F</mi> </mrow> <mrow> <mn>2015</mn> </mrow> </msub> </mrow> </mfrac> <mo>×</mo> <mn>100</mn> </math></p> <p>Where:</p> <p><em>AFMP</em> = Forest area under a long-term management plan</p> <p><em>AF</em> = Total forest area</p> <p><u>Translation to dashboard/traffic light: </u>The indicator value for latest reporting year is compared with the indicator value reported for 2010.</p> <p>The ratio (r) between the current indicator value and the value reported for 2010 is calculated; r>1 means an increase in areas under management plan, r<1 means a decrease while 1 indicates no change. A narrow interval for r has been established to indicate a stable condition, and traffic-light colors are assigned as follows:</p> <p> r ≥ 1.01 </p> <p> 0.99 < r < 1.01</p> <p> r ≤ 0.99</p> <p><u>Comment:</u></p> <p>Using forest area in 2015 as denominator for estimating this indicator ensures that the time series of percentages reflect real changes in the forest area under management plan and is not affected by changes (losses or gains) in total forest area. </p> <p><strong>Sub-indicator 5 – Forest area under an independently verified forest management certification scheme.</strong></p> <p><u>Unit</u>: Thousand hectares</p> <p><u>Reference year:</u> Latest reporting year (as of June 30)</p> <p><u>Method of estimation:</u> Data is collected directly from the databases of each certification scheme and provided to countries for validation.</p> <p><u>Translation to dashboard/traffic light: </u>The indicator value for latest reporting year is compared with the indicator value for previous reporting year for assessment of continuity of progress since last report.</p> <p>The ratio (r) between the current indicator value and the previously reported value is calculated; r>1 means an increase in areas under an independent forest management certification scheme, r<1 means a decrease while 1 indicates no change. A small interval for r has been established to indicate a stable condition, and traffic-light colors are assigned as follows:</p> <p> r ≥ 1.01 </p> <p> 0.99 < r < 1.01</p> <p> r ≤ 0.99</p> <p><u>Comments:</u></p> <p>Using June 30 as the date for reporting, allows for the certification bodies to have their databases updated so they can provide information to FAO by end of the year, and then be included in the annual reporting to SDG in the beginning of the following year.</p><div class="footnotes"><div><sup class="footnote-number" id="footnote-2">1</sup><p> If forest area change rate is negative (= forest loss) then: annual forest area loss rate = <strong>-</strong> (annual forest area change rate) <a href="#footnote-ref-2">↑</a></p></div></div>
<h1>Ссылки </h1>
<h2>URL: </h2> <p><a href="http://www.fao.org/forest-resources-assessment/en/">http://www.fao.org/forest-resources-assessment/en/</a> </p> <h2>Рекомендации:</h2> <p><a href="http://www.fao.org/forest-resources-assessment/current-assessment/en/">http://www.fao.org/forest-resources-assessment/current-assessment/en/</a></p> <h1>Приложение 1 Обозначения и определения<sup><a href="#footnote-1" id="footnote-ref-1">[1]</a></sup></h1> <p><strong><em>ЛЕС</em></strong></p> <p>Участок земли площадью более 0,5 гектара, на котором растут деревья высотой более пяти метров с сомкнутостью крон более десяти процентов, или деревья, способные на данном участке достичь этих пороговых значений. Не включаются земли, которые используются преимущественно для целей сельского хозяйства или поселений<strong>. </strong></p> <p><u>Пояснительные примечания</u></p> <ol> <li>Лес определяется как наличием деревьев, так и отсутствием других преобладающих видов землепользования. Деревья должны быть способны достигать минимальной высоты 5 м. </li> <li>Сюда входят участки с молодыми деревьями, с сомкнутостью крон еще не достигшей, но которая, как ожидается, достигнет 10 %, а деревья – высоты 5 метров. Он также включает участки, которые являются временно обезлесенными из-за сплошных рубок в рамках практики ведения лесного хозяйства или из-за стихийных бедствий, но которые, как ожидается, будут восстановлены в течение 5 лет. В исключительных случаях, с учетом местных условий, могут устанавливаться более продолжительные временные сроки.</li> <li>Лес включает лесные дороги, противопожарные полосы и другие небольшие открытые пространства, леса в национальных парках, природных заповедниках и на других охраняемых территориях, представляющих особый экологический, научный, исторический, культурный или духовный интерес.</li> <li>Лес включает ветрозащитные полосы, лесозащитные полосы и полосы деревьев площадью более 0,5 га и шириной более 20 м.</li> <li>Сюда входят заброшенные земли со сменной культивацией, где производится восстановление лесонасаждений, которые имеют или, как ожидается, будут иметь сомкнутость крон 10 %, а деревья – высоту 5 метров.</li> <li>Лес включает площади, занятые мангровыми лесами в приливных зонах, независимо от того, классифицируются ли эти площади в качестве земельных площадей.</li> <li>Лес включает плантации каучуковых деревьев, пробкового дуба и рождественских елок. </li> <liСюда входят площади, занятые бамбуковыми и пальмовыми лесами при условии, что землепользование, высота деревьев и сомкнутость крон соответствуют установленным критериям.</li> <li>Лес не включает древесные насаждения, вовлеченные в сельскохозяйственное производство, такие как плантации плодовых деревьев, плантации масличной пальмы, оливковые рощи и агролесоводственные системы, при которых сельскохозяйственные культуры выращиваются под кронами деревьев. <u>Примечание:</u>Площади, включенные в некоторые агролесоводственные системы, такие как система Taungya, при которых сельскохозяйственные культуры выращиваются только в первые годы оборота лесного хозяйства, должны рассматриваться как лес.</li> </ol> <p><strong><em>НАДПОЧВЕННАЯ БИОМАССА</em></strong></p> <p>Вся биомасса живого растительного покрова, как древесного, так и травянистого, включая стволы, пни, ветви, кору, семена и листву.</p> <p><u>Пояснительные примечания </u></p> <ol> <li>В случаях, когда подрост является относительно незначительным компонентом пула углерода в надпочвенной биомассе, его допустимо исключить при условии, что это будет осуществляться последовательно в ходе инвентаризаций в отчетные годы.</li> </ol> <p><strong><em>ОХРАНЯЕМЫЕ ТЕРРИТОРИИ</em></strong></p> <p>Территории, специально предназначенные для защиты и поддержания биологического разнообразия, природных и связанных с ними культурных ресурсов и управляемые законными или другими эффективными способами.</p> <p><strong><em>ЛЕСНЫЕ ПЛОЩАДИ НА ЗАКОННО УСТАНОВЛЕННЫХ ОХРАНЯЕМЫХ ТЕРРИТОРИЯХ</em></strong></p> <p>Лесная площадь на официально созданных охраняемых территориях, независимо от цели, с которой были образованы охраняемые территории. </p> <p><u>Пояснительные примечания</u></p> <ol> <li>Включает категории МСОП I – IV</li> <li>Исключает категории МСОП V – VI</li> </ol> <p><strong><em>ЛЕСНАЯ ПЛОЩАДЬ С ДОЛГОСРОЧНЫМ ПЛАНОМ УПРАВЛЕНИЯ ЛЕСАМИ</em></strong></p> <p>Лесная площадь, имеющая долгосрочный документированный план управления лесами, направленный на достижение определенных целей управления, и периодически пересматривающийся.</p> <p><u>Пояснительные примечания</u></p> <ol> <li>Лесная площадь с планом управления лесами может означать уровень лесоустроительного подразделения или агрегированный уровень лесоустроительного подразделения (лесные участки, фермы, предприятия, водосборные бассейны, муниципальные образования или более крупные участки).</li> <li>План управления лесами может включать подробную информацию об операциях, запланированных для отдельных эксплуатационных единиц (насаждений или кварталов), но он также может ограничиваться предоставлением общих стратегий и мероприятий, запланированных для достижения целей в области управления лесами.</li> <li>Включает лесную площадь на охраняемых территориях с планом управления лесами.</li> </ol> <p><strong><em>СИСТЕМА СЕРТИФИКАЦИИ ИСПОЛЬЗОВАНИЯ ЛЕСОВ, ПРОШЕДШАЯ НЕЗАВИСИМУЮ ПРОВЕРКУ</em></strong></p> <p>Лесные территории, сертифицированные по схеме сертификации управления лесами с опубликованными стандартами и прошедшие независимую проверку третьей стороной.</p> <h1>Приложение 2 Методология</h1> <p><strong><em>Субпоказатель 1 - Темп годового чистого изменения площади лесов</em></strong></p> <p><u>Единица измерения</u>: Процент</p> <p><u>Отчетный период:</u> Самый последний период</p> <p><u>Метод оценки:</u> Формула сложных процентов</p> <p><u>Перевод на инструментальную панель / световые сигналы:</u></p> <p>Следующая блок-схема объясняет логику перевода этого показателя на инструментальную панель / световые сигналы:</p> <p><img src="data:image/png;base64,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"></p> <p>Направление изменения площади лесов определяется путем изучения значения скорости изменения площади лесов за последний период, отрицательное значение указывает на потерю площади лесов, нулевое значение означает, что площадь лесов стабильна, а положительное значение означает, что площадь лесов возросла. Изменение скорости потери площади лесов основано на сравнении текущей скорости чистого изменения площади лесов с базовой скоростью чистого изменения площади лесов за период 2010-2015 гг.</u></p> <p><u>Комментарии:</u></p> <p>Этот световой сигнал учитывает как направление изменения площади лесов (если площадь лесов увеличивается или уменьшается), так и изменения скорости потери площади лесов; последнее важно для определения прогресса среди стран, которые теряют площади лесов, но сумели снизить скорость потерь.</p> <p>Для годовой отчетности ФАО может предоставлять странам условно исчисленные значения на основе предыдущих тенденций, которые они могут использовать в случае, если у них нет новой / обновленной информации. Базовый уровень должен обновляться каждые 5 лет, поэтому в 2020 году рассчитывается новый базовый уровень. Кроме того, на страновом уровне, если страна получает новую информацию и обновляет исторические временные ряды, базовый уровень для страны будет пересчитан с учетом периода 2010-2015 гг.</p> <p><strong><em>Субпоказатель 2 – Запасы наземной лесной биомассы</em></strong></p> <p><u>Единица измерения</u>: тонна/гектар</p> <p><u>Отчетный период:</u> Самый последний период</p> <p><u>Метод оценки:</u> Запас лесной биомассы (в тоннах) / лесная территория (в гектарах)</p> <p><u>Перевод на инструментальную панель / световые сигналы:</u></p> <p>Значение показателя за последний отчетный год сравнивается со значением показателя за предыдущий отчетный год для оценки непрерывности прогресса с момента последнего отчета.</p> <p>Рассчитывается соотношение (r) между текущим значением показателя и ранее отраженным значением; r & gt; 1 означает увеличение запасов на гектар, r & lt; 1 означает уменьшение, а 1 означает отсутствие изменений. Был установлен узкий интервал для r, чтобы указать стабильное состояние, и цвета светового сигнала обозначаются следующим образом:</p> <p><img src="data:image/png;base64,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"></p> <p><strong><em>Субпоказатель 3 –Доля лесных площадей, расположенных в пределах установленных законом охраняемых территорий</em></strong></p> <p><u>Единица измерения</u>: Процент</p> <p><u>Отчетный период:</u> Самый последний период</p> <p><u>Метод оценки:</u> Доля лесных площадей, расположенных в пределах установленных законом охраняемых территорий / Лесная площадь в 2015 году * 100</p> <p><u>Перевод на инструментальную панель / световые сигналы:</u></p> <p>Значение показателя за последний отчетный год сравнивается со значением показателя за предыдущий отчетный год для оценки непрерывности прогресса с момента последнего отчета.</p> <p>Рассчитывается соотношение (r) между текущим значением показателя и ранее отраженным значением; r & gt; 1 означает увеличение запасов на гектар, r & lt; 1 означает уменьшение, а 1 означает отсутствие изменений. Был установлен узкий интервал для r, чтобы указать стабильное состояние, и цвета светового сигнала обозначаются следующим образом:</p> <p><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAcYAAAC1CAYAAADFo1/yAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAAIdUAACHVAQSctJ0AADFMSURBVHhe7Z0HeFTXmffj2Pm+L9n0bBLvl+JkHTu2s052k80WJ9k4YGOHjui9d7BBQhQBEh0kISSqKUL03gSI3nsVokp0EIjeqySEePf+j+65vpoZjWakkcSM/r/neZ9h7jn33HNHw/3P+573nPMVIYQQQogFhZEQQgixQWEkhBBCbFAYCSGEEBsURkIIIcQGhZEQQgixQWEkhBBCbFAYCSGEEBsURkIIIcQGhZEQQgixQWEkhBBCbFAYCSGEEBsURkIIIcQGhZEQQgixQWEkhBBCbFAYCSGEEBsURkIIIcQGhZEQQsoZdx8+lbT0m5J8OkN2HL0g6w6clqQ9J9Ur3iefypBUoxz1yiMURkIIKQc8ycpWohe3eJd0il0ujYcskDoRc6R62Ez5JHSaVAyeql6rGe9xvJFRjnpxi3bJ9iMX5HFmttlS4ENhJISQAOXFixdyz/D6Zq47JH/rHl9sm74uWXmRuUa7gQyFkRBCApBLN+7Lgs1HpcWIRU4CVyFkolQNj5agoYOkbmR/aRjTSxrH9lCveB80dKBRHqXqOZ7bfPgimbf5iKTfuGdeKfCgMBJCSACR8zxX9qVeli6jVziI2hSp3DdGWk/qID0Tq8jAjX+SETt/L9F735fYg+/I6JS31Cve4zjKeyVWljZG/cr9YtT59vY6xy2XvamX1PUCDQojIYQEEMt3pUmV3jPyiVjlviMleGEtiUt+2xDAX8mYw2/K2COFG+qhPs4LXlRLtWNvF9dJ3HHCvHLgQGEkhJAA4OGTLBm/bE8+4arcb6R0mt7U8AL/xaXweWsj9/5GOs9oYrQbne86Y5bslgePM82e+D8URkII8XOeZGZLfNIBqRSaYIlVnRH9JXzthx57h54a2gtf96HUNdrX1/q4R4JMWrFPHj8NjMxVCiMhhPg5iTtS1VSLPKGaLI1ie8iIXf/mUth8ZZG7/lWaxIWo6+G6EOUl2wMjrEphJIQQPyblzDX5e6/ppijGS9CwCBmxs2RFUVukIb7wTPW10Y+U01fMnvkvFMYAIScnR9LS0mTOnDnKTp48aZYUn4cPH8r+/ftl+fLlMmvWLGX496FDh+TRo0dmLc/YtWuX6t+8efPk5s2b5lFCSFG48+CJdBiVaAlT7WEDZOi2P7oUsZKyYdv/KLWHR1h9aBu9VG7ff2L20D+hMAYIEKpWrVpJ5cqVlS1evNgsKR4ZGRkSFhYmDRo0kBo1aljt498NGzaUYcOGyYMHD8zaBQMRjI2NlXr16qnzq1SpIsnJyWYpIaQoLNpyVD4KnqoECYk2g7f8l0vxKmkbuvU/pHL/vIScCsHxMm/TEbOH/gmFsYRYt26d8o7gbeXmlsw8n+fPn0t6eroMHz7cEixtixYtMmsVnUuXLknLli1Ve9WqVZP69etLixYtpGnTplKnTh3rWj179pQnT1z/QszOzpbDhw9L586drfraDh48aNYihHhL+vV70nbkUlOMJku7qa0lLvktl8JV0hZ36C3pkNBS9QP9aR21RC5cu2v21P+gMJYQQ4cOVQ//Pn36yOrVq+XWrVtmiW9A6HTt2rXSrl07dZ3atWtLhw4dpGrVqup9cYXx7t27ylPUbU+cOFFSU1NV2f3792X37t3Su3dvVQ4bP368KrNz/fp1mTp1qvI2UadRo0bSsWNH6xwKIyFFA0u9rd13SmWDQoiqDxguQ7b+p0vRKi0buu0/pMbAoao/H4VMlaQ9aaqf/giFsYTYsGGDCjVCACAsXbp0UeFOiIovgCeqw5IQx23btsnKlSutcGdxhXHLli2q32gLHqmrfkMoW7durerAk7xw4YJZksfcuXOVUFevXl21gfoJCQmqPozCSEjRyM19IUNmblYiBGsX30ZNxHclWKVluH77hFZWnwbN2OS3q+JQGB3AL5ynT5+q0CBClXiPcCDew7Kysjz+FQQvMTo62hIYjKuFhobK8ePH5dmzZ8X6NQVhbNasmUyfPt1qZ+vWrVKzZk11reIIY2ZmpowdO1a1U6tWLdm7d69Zkh98HlFRUaoe7nHz5s1mSR6zZ89WYddNmzaZR0Rmzpyp6sMojIQUjeycHKnZb5YpQlNkwIa/uBSr0raBG/+s+oN+1ew7S55m+ee8RgqjAwghwguCl4OxsWPHjsmgQYPUgxzjbPD8vPH6IIBHjx6VUaNGSePGjVU78OoGDx4sO3fuLLIHCdF2zOr0lTDeuXNHgoODVTsIf7rrY2JiorofiD4yTe2gHcfEHAojIcVnS8o5UxTjpVrECJciVVaG/ui+bTp01uyxf0FhdAAPc4QF8eBeuHChdOrUyXqQayvKeCE8TQjByJEjLfFCMku/fv2UR1VQ8oo3+EoYMTaoM1zh4bpj+/btlkeMrFN4m+6gMBJSfMYn7rXEp/3UVi4FqqysQ0ILq2/jlu4xe+xfUBgdsAujzryEeF2+fFmuXr0qS5cuLbKIIeSJDNWzZ8/my9KEt/X555/L+fPnzZpFw1fCiCka+t7Dw8PNo67B/Ma6deuquvCCC5u6QWEkpPj0m7reEp+QxTVcClRZWY+l1ay+hcWvM3vsX1AYHbALIwxhVF9nlAJ4kJjS8dlnn1nXiomJKdbUDl8JI6aA6D4hBOwOiDzCrahLYSSkdGgVudgSn4h1/+NSoMrKBmzAOGNe31qO8M186tKGwuiAXRgxJoi5fCUBQo6YboFQpRYKJOq8bMIIIXMHhZGQ0ufTnnpd1HiJ3P07lwJVVha1532rb+inP0JhdMAujF988YV51LdAwDDn0L6SDCbJQ2SKk6lKYSSkfBDUf7YlPsO2/7tLgSorG779D1bf0E9/hMLogF0YMTndVyDbFUIAAcTcPowrYp4jFgBAAosvKAlhLGyM8dSpU9Z8TQojIaWDfXf+vqs+cilQZWX9Vlew+oZd/v0RCqMDvhZGzDdcv369SuDBnEC0ixAtMjiRuII5k77CV8KI5BudUFOYMB44cMCqizHSwhKTKIyEFJ9hs7dY4tNtfh2XAlVW1n1BbatvQ2bln9vsL1AYHfClMGL1G2SbBgUFqfYgWhCPc+fO+VQQNb4SxmvXrknz5s1VO3h1x8aNG637w64bhYWCKYyEFJ9pa5It8Wk+7jOXAlVW1nx8V6tvU1f75/9xCqMDvhLGCRMmqDYQNkWoEdmtJ06U7CaevhJGhH11UhC8QUxVcQUShbDyDsLC8IaRTFQYFEZCik/qxRtS0dxVo2KPCRKX/GuXIlXahn6gP6pfRv+Onb9u9ti/oDA64CthxCLibdq0kUmTJqkl4LBSTUnjK2GEN4tQL9rBCkBJSUlmSX4wjUUvJI6l386cOWOWFAyFkZDi89z4UYodLLRn1nNZVZdCVdrWK7Gy1adWkUsk+1mO2WP/gsLogK+EEdM8YJivWFp4I4wIeWLHjB49ekhcXJx5NA+UIQysV7SB94jVcBzBhsP6eljRB8vfFQaFkZDig0XEJ67YZ4lQo9hQiU1+26VYlZbh+k1GB1t9wuo8z7mIeGDgK2HEPEVkaHpjOMfT6Rqo9/jx43znr1mzxpoCgvE+e5njUm1XrlyxBAqG3f/tIJyKDFpd3q1bN9mxY4dqC+vHYpspXYZtpZDJ6giE0t4H2JQpU6zzkI2rjyNJyRNhJYTkcSDtslTpPUOJ0Kd9YqVv0scy5rBr0Sppw3X7raoon4bFqv5U7jVd9pxwfib4CxRGB3wljHbh8NQQvvR0gj+yP12t41qQOe6XmJKSkq8cC507gm2isGi63uPR0TC2iC2vsCGzK7DbhqvzXBkEHftWEkI84+7DpxKesMHy0BrF9pCY/e+6FK6StlEH35HGcSFWX/rGr5M7D4u//nNZQWF0AJ4SxgbxsMYi4kVlzJgxTg//wmz06NFeCaOrXfELMiQD2YEHqYW1V69e8ujRI7MkPwgHY19FZNfqtjDuiHOxtyLWdy1o/BR7OupzCjOEZOHxEkI8Z1/qJfkkNG8VnI9CJ0i3BWUzdaP7wiDj+uPz+hEy1a+9RUBhJIQQPyZy7nbLU4P1Wv73Ugup4jq9V3ya7/rDZm81e+a/UBgJIcSPuXnvsXQYlWgJ0ye9R0uflZ/I6JS3XIqZrww79oclVVLjm/ra7WOWqf74OxRGQgjxczBfsGWknr4xRar0j5LgRbVcCpqvDNtdVQ2PUtfDdVuMWCxHzl41e+TfUBgJIcTPyX3xQvaeuCTVw2aa4hgvFUMmStv4NoZn51rYimpor118a9W+vhayY3cfv6j6EQhQGAkhJEDYfuSCNB6yQCoE5wnW37pPlroj+kmfpEoSvfd9l0LnqeH8sKSPpV5kP6PdSap9XAfX23q4eJusv2xQGAkhJIA4mX5TIqZtlEo9EkxxjJePQ8dJ/eje0nV2Qxm8+QOPvUgk1wze/N/y2ZwG0mBkb9WO1abRPqaLpF68aV45cKAwEkJIAIHFPx49zZKpqw5YIpZnU6RCyET5tE+c1Bw8WDpMbyG9V/xd7bgfuet3EnvwHfU6YOOfVaZph+nNVT3Uzwub5o0lapuStF9dx9NFSfwJCiMhhAQoGbfuy/DZW6SWbWPj4hjaGTJri1y6ed+8QmBCYSSEkAAGC3kfPntVxifukZAvVkvt8DkuRa8gC+o/R0ImrJZxy/ZIypkrkuWnC4N7A4WREELKAdiR486DJ3L+6l1Zs++0RM/fLr0nr5V20UuVWH7ac5p6bWu872UcR/mqvSdVfZznrwuCFwUKIyGEEGKDwkgIIYTYoDASQgghNiiMhBBCiA0KIyGEEGKDwkgIIYTYoDASQgghNiiMhBBSznj8NFuu3H4gF67dlVOXbqltq1LOXFWveI/jKEe98giFkRBCygGZ2c/UyjXzNh2RAdM3ScdRidJs+CKpGzFXKveeIR+FJKjXOsZ7HMfmx6g3b+MROXT6ijw1zi8vUBgJISSAeZKZLYk7TkjdAXOlWthMtSuGq6XfCjLUx3k4f+mO4/LYaC/QoTASQkgAcvfhU7VPYvuYZU5iVzF4ktToFyv1B0ZK46FDpcWIgdI6KkK9NjHe1x8UKTWNctRzPLfdyGWyJeWcaj9QoTASQkgAgTVRUy/ekL7x6x1EbYoE9Y+R8GkdZM7GT2XPifflTMbP5OqdH8jDJ9+QZzmvGa9fl2vGexxHOepFGPVrh8eo8+3t9ZmyTk5cuKGuF2hQGAkhJIDYlHzOYRf/eAkKj5aZ66pI+vXXlQi+eIFHf+GGehBLnDdrfWVDIKOtNtF+oyHzZcPBM0bdwAJ3TwghxM/B9lKz1h+yhAtWtc9oiV3UWG7d/7ZRw1n4vLU7D74tcYsbSrWw0fmuM2NtckBtR4W7JQXw+PFjSUlJkXXr1sny5ctlxYoVsmXLFjl16pRkZmaatYrOw4cP5ciRI7Jp0ybVPgz/Pn78uDx9Wnj8PisrS06ePCnbt2+3zl+7dq0cPHhQ7t8P7I1ESxv8rXbu3Kk+461bt8qjR4/MkuKRk5Mj586ds9rWtn79ejl69Kg8efLErFk4z58/l2PHjsnKlStVG1evXjVLSKCTmZ0jCzYfVVtHabFqFRUhW1L+ILm5rxg1nEWuqIb2th7+vbSODreu9UnoNJm78bA8zQqMzFXcKXEBBKtPnz7SpEkTqVGjhlSuXFlZUFCQtGrVSsaOHSu3b982a3vP4cOHZdCgQdK0aVOpVauW1T7+3bx5c9W+O/G9ceOGxMXFqb7UqVPHOr969erSqFEjiYiIkPT0dLM2KQ4QmFGjRkndunXVZ9yhQwc5f/68WVo8EhISpE2bNlbb2vCda9asmQwfPlzu3btn1i4YCPfcuXPVOVWqVFFtbNy40Swlgc6GA2ekRt9ZplBNlpAJ3eXUpZ8bJc7C5is7ffmn0nNiN3U9XLd62ExZu++0Ueb/4A6JjRcvXkhaWpq0bNlSPVzwkMFDCoII0apWrZp1HA9LeJXegPYhiloMq1atKrVr15bevXtL586d84lw//79lRfgCESxdevWVj9q1qwp3bt3V4Z+6gcj7gF1iffg7wRvbteuXeqHhv6bwNq3b6+8vOKAv+vIkSOtNvGDBt8JbXivy9q1a1fgj7Dc3Fw5c+aMBAcHW/W1IdJBAp+zV+5I5d7TTVGMlyZDh8ilmz80SpzFzNeWYVyn+fBB1rXRj7MZRXcYXhZwd8QGfnnDU8SDBSI1btw4Fa7EA+jBgweyevVq5aWhHIKEkJc3ZGRkSNu2bdX5DRs2lPnz56traiDKAwYMsMRt6dKlZkkeEGJ4mijDA3TMmDFy5coVs1Tk2rVr8sUXX6i+oU5kZKRPwr7lDXymEyZMsH7AtGjRwvLMiyuMz549kwULFqgfWfhhFBISosKz+H7hb4W/MQS5V69eqhzXxN/Z8e+IcO6SJUusH3H4gaV/MMEojIHPwydZEjx+lSVMzYYPlrT0XxglziJWUnYy/Y184vj5mJXywOiXP4M7IzY2b95seYUxMTEuPcIDBw5Yv+i7dOliHvWMpKQkJVp44E2aNEmNEzoCIdbi+fnnn8vdu3fNElFjngjvogwCfufOHbPkS1C/b9++qg7ENzU11SwhnjJ58mT1N8KPI0QG8IMFHjk+0+IKI34cffbZZ6othM0xLogfXnbgseLvhjAr6kHw8L2wA+FD/9BPfBcwtrxw4UJVH0ZhDHxW7k6Tj0KmKkGqHREtKaffNo46i1dJ25Fzb0pd4/roR8XgeEncecI47r/grogNjM3hoQLxchXGBHhoIfSpH0CePiSRUIOHLM7BmNL+/fvNkvzAMxgxYoSqB2Gz11u1apUSZTwMFy9erPriCI6hDAKPuo5ep69Au6GhoXLr1i3zyMsHQpD4gQPzJmEmNjZWCSASobRowYPD36S4wnjo0CHLE4V37+pvCHBcf1/wfdy2bZtZkseyZctU6ByJNtqbXLNmjaoPozAGNlduPZBOscstTy1uSSPJyn7NKHEWrpK27Gevydhl9a2+dIhZJpdv+m8CIO6KmEC49BgfPC53zJs3z3oAIVvVExAq02FQjFudPXvWLHFGCxseiMg01eA4zkc/kSFbEBDTevXqqbp4+GK8rLjgQY0QI+63Y8eOqm2E8bwRRoR2cd6MGTNUUsns2bOtMTx4wvv27TNrFp3s7GzlXU2ZMsX6DJDE4o0wwhPH38uOr4QRCTdoB7Z7927zqGvsQjd16tR8f0eE4K9fv26+y4PCWD7A/8VNh85KpdC85d2wek1a+htGibNolZadvvwzaTpssOpPpR4Jsv7A6QJ/9L3s4I6ICbwD/VCZOHGiedQ1ycnJVl2MRXmCXRgbNGigpn0UBDIKtUgvWrTIPJpfGN1lHUIYtOAMHjzY6SHvLQj/IUyH0K7uV9euXZXX4s0Y5pAhQ9S5UVFRyivTY6Hapk2bZtb0HozdYYoDxuMwDoxxWnjM+MwhuCgvDr4SxmHDhln3W1jGKbxLXRfi7ir0bofCWD7IzX0hUfO2WR5a7KJGkvP8q0aJs2CVluH6Y5Y0sPo0fM5W45h/roqDOyImmEOoHyrwaNyBTEA9FomHvSdgTprORESixI4dO8wSZxA206IBQdJgjFInbcyaNcs86gwe3HoscuDAgUWe14gHMbw6eIb6fpGIkpiYqDywgsLNBaGFsX79+uoeMMaGBziShiD6+FyLwunTp9Vni3YhiDAIGcbvEAlwHMMrCr4Sxh49eqh2YIWBz0PXDQsLK/RHCIWxfIBl2LArhhahg6d+bRx1FqvStkOn37b6VCd8jlp0wB/B3RAT7Y3BMG7jjkuXLqk5iKjrqTACCIr2uCBY8MTswKtBaHLOnDlWgg/Cj3qiNxIstCfYqVMn9eB3DFcg+QZhVh1GRKIHhMdTEK5DyBR9gGeLNiDSSACBGBdn/qYWRhjm3MEjKipIjIKHCO9Tt4mxW0xdQJanN56sJ/hKGHViFT5bT9D3RmEkmt3H0y0BqhsRZTwDnEWqLAz9qDcgyurbjqMXjeP+B+6GmNiFEdmf7iiqMF64cEEJGs6DB9azZ081MRtJNRBjhGWRvq+TM2DwhLQwIiSqxQVeESabI/yI82HwdPv162eJIqxbt25OY1EFgfAu2sDDX3teCJ/is/HFggF2YcQKLUUBn8WePXvUDwb9IwHCjZAxsop9tSqNI74WRvxg8QT9eVEYiWbiin2W+IxbWs844ixSZWUTEutaffti+V7jmP+BOyEmpSGMCOkh7IdJ2/paEB882LUnifcIg+IV7+G52UOBGJfS2bPacL4OvcIaN25seZzh4eH5pnwUBMZY0S+EOHEePESINTxEXyTvAC2MEBckyRQFhJMRMkU7+HGBRCmsVIRkFF+ETAuCwkheFiKmbbDEZ9XePxlHnAWqrGzt/v+2+tY/wbt53i8LuBNiYhfGwsYY4T1BfFDXG2HU4AGH7E54ORAgGB6UmFaAxB77GKM9+UaDsT1kNKK+Ph/eI9rT663qMUYkn3gyxggvTC9Nhjl7yJotbsKKI1oYkbhTVDDmiTYg4FiAobSmi/haGGGFgR8kui6FkWjaRi+1xCe5jOYuFmSY06j71sbopz+COyEmWMVGP1QKE0aIhvbIkF3pa7DCDtpHSLUoDziMPWIOJPqH8KwnAgcvGCKqw7gQW0x5gFB7sqi5J/hCGCHgWFgB7eAzQjILwrIQK195tq7wlTDqhQJghYHvma6Lvw2FkYAqtiXgrt35vnHEWaDKym7d+67VN/TTH8GdEBMktuiHChI63IEdLXRde9aor4CYoW14pUVJUMEDEgKH8Kyn8ywBQq4QQixgoLNQMY43dOjQQsPLnuALYYTIIzkIU0Ug3mgP3iM8Mcz1K05ykDt8JYxIukI7MITV3YFpJrquJz9wKIzlgxp9Z1ric+XWD4wjzgJVVoaNjnXf0E9/BHdCbOhxPSTAuGP8+PHWAwhLxPkS+5JhmEjvaeKMBtmaeuUcjMUVVdAg/hhz1GOfMMzBw84SRQ2x+kIY7WC8debMmWr6ixZyrAaDNWgxSd/b6STu8JUw2if4F7YDBtZURT18Lz1Zl5fCWD7oGJtoic/Bk+8YR5wFqqws+fSvrb51GJVoHPM/cCfEhg5zIURXUBYmkjzwcEQ9zO/zNUh40WFaeEDeAqHW2Zp4mBcWfnMHBBBTHyBoeuoGQrTY8gq7hLhaS9YdvhZGDTxILKiNsCo+OwgJflTAmy+OkNvxlTDiB4f++7qbtI/vGRaURz1MbUF4vDAojOWDwTM3W+KzYtdfjCPOAlVWlrTnz1bfBs7YZBzzP3AnxAbGqvSDBeuAOm4Ui7E2u7eIX/R24KFASOBZwWvzdsI6HmY6qQfJM94mlkCssH0Vzoent3evb9KlMU0EmZ+YIgHvTPcPyS/eiGNJCSPAZ4/5mhs2bFAeP8KrMCQlIZO1uOLojTDis0I4HsKHv4kdTNnRP6zwAwYhfEdwLwiB62QojC86fhddQWEsH8SvOmCJz8j5TY0jzgJVVjZqYWOrb1OSXK8H/bKDOyE2kL2JeX/64YJMwBMnTqhJ9BA5iJ0O2SEB5ObNm+aZeeDXP+Ym6vMdk3gwXghPBuNF8AAwZQEPQQgYplXo8yBqrh6YCKuifxAorJyj5+xhrApLoem+wTDNw5drFaItGHZ9wI8GXAOr4Hgj3iUpjBr0EX8HCIP2nPFDpbjzG70RRvuyb7hnO+gfvhc6bI/Vf5ARrUGkAnNb7dNvXH0XXEFhLB+knLliiU/lXmON75SzQJWFoR/oj+7bwVP5FzDxF3A3xAZECtMg9HY/BRnEzZU3hrAlPBRdLz4+3izJAw84PQevIMO4HhYOd5VhiZChfQ6kK4Mnh0n/vsokLQh8Ttg6y5vl5kpDGO3A00WIFVNevPk8sFiC4+dakGExBcfPwL7sGzacdgQbSCNMqkOqBRnmyhaUPIWtsFyd48pwHWQ6k8AAS8I1HbbQEqAdR39nHHUWqtK2Xcd+a/Wp6dCFXBIukIAgYR7g6NGjVaaj9sLwcMGqNRj3g/foKjSHY9pzQxhs586dZkkeyPqEaGHZMrtA4uGKY/Ak0HZB0w7gCSHci6xRhFy114EMVIiNHvvzJOzmC3C/3kyq10lB8L5KC/TP2zCqPaRemOHv7LgYOHZfgceHsHNBwobkIFwHEQYdntaGH2b4HiFDuCDgudvPcWf47kLsSWCARcTHLN1lidCQWa0NEXrVKHEWq9KyZzmvyvA5Law+xS3aaTgaXEQ84MDDFONnSIKA54FXCI67uXI6jIe6MHigjuB8eC8I7aFdGP6NY67qO4I68Ezt5+u+eSsApQ3uEf0tLeEuKghx68+2MMNn7/jjAH8H/R1w933BefhMUM/eJr53aAPfp4LA98B+jjtD+0VdaYi8fOB7sfvYRfm05zQlQnUHREnKmbKd6H/k3K+k/sBI1Z9PQhNk+5Hzbr+/LzO4I0IIIX7GrXuPJXTiGstDGzq7tTzJ/D9GibNolbRlZn9NRsz90lsMmbBKbtwtmTWLSwPcFSGEED9ka8o5tSkwxKha2GjZmPxH46izcJW0bUn5g1TvG6f68VHIVNl8qOBN2P0B3BUhhBA/JDvnuURM22R5ahDHfWnvGSXO4lVSduDku+q6ug/9pm5Q/fJncGeEEEL8lCu3H0qjIQssYaoTES1Hz70pubmvGKXOQuYrQ/vHz78p9cxxRVjDwfPlyq0HRrl/gzskhBDix+xLuyyNBmtxnCxto/vLzmMlO4Vj1/H3pd3Ifup6ShQHzZfdJ4q/Z+vLAO6QEEKIH5PzPFc2HDgjVXrPMMUxXoL6x8j8zZXk+XPfeo5ob8GWjyQoPMa61t97TZd1+0/LMz8PoWpwp4QQQgKA1XtPSmWbOFYIniRhUzrLmSs/kaxnXzNqOAudp4bzz139/9IvvpNUNNrV18D1knanGXUCB9wxIYSQACH5VIZ0G5ckH4fkZavCkDE6Ym5z2ZryB8m4+UPJ9XAJOSzxlnHrH2Xb4d9L5LzmVuYpDNmnn49dKQdO+ueyb+7A3RNCCAkQsCrOtTsPJXbRTkvE8myK4d2NlTbR4TJgejtZtuNDlVF61vAm7zz4tmQaHuGdB99S7w+celcSd/xV1WsT3V+qGOfhfHt7MQt3yNXbWNzCPyfxu4PCSAghAcqFa3clZPwqqRA8NZ+oFdUqBMcb3ugqOXf1jnmFwITCSAghAUxm1jPZcfSC9I1fb3h/S6Va2Je7/3tiVfvMlNZRSyUsfp1sO3JenhrtBToURkIIKQcgY/Ti9Xuy58Qlmb72kJqI33XMCmk2bJHU6DtLKoVOU6/Nhi2ULsZxlE9bk2zUT1fn+fukfW+gMBJCSDkD21ZBKLOe5Uhmdo7yAp8Yhle8x3GUo155hMJICCGE2KAwEkIIITYojIQQQogNCiMhhBBig8JICCGE2KAwEkIIITYojIQQUs7AVIzHT7PlweNMufvwqdy+/0Ru3nusXvEex1EeKLtleAuFkRBCygGYoH8m47ZsPnROvli+T3pNWisdYxOlyZAFUj1splQKTVCvjY33ON7TKEc91Md52c9yzJYCHwojIYQEMJi0v+nQWbXjRtNhC/NtS+WJoT7Ow/kbD53hknCEEEL8E2xefDL9plr2zUnwuk2Rjz6bJJW6fiGfdJ0gn3aBjVeveI/jKEc9x3O7jl4hqRdvqPYDFQpjAHDjxg05fPiw7NixQ7Zs2SLbtm2TI0eOqOPF5cWLF3Lnzh05evSobN++3Wr/4MGDcu3aNcnJKTy88uTJE0lNTZXdu3er82EHDhyQCxcuSGZmplmLEOILcnNz5dKNexI5d1t+UTNErmrH0dKlXi+JrthUVr/3Jzn8k7fkwvdfl7tf/6Zkvfo19Yr3OL7mvQ9UPdSvZpznKJLD52yV9Ov31PUCDQqjH5OdnS3r16+X4OBgadSokVSrVk0qV64sVatWlcaNG0tISIhs3brVrF00Vq9eLWFhYdKkSZN87derV0969Oihrv/sWcGhleTkZBk2bJi0aNFCatWqpc6H1a1bVzp27CizZs2SR48embUJIcVlb+ol6RS7XG0krEWsRvtREve3RrLvjd/I9W99X3K/Yjz6PbAXhl3/5vdk/8/fk9EfNpCaRju6TbSPscg9x9PNKwcOxt2Tl4GLFy8qLwoemifgV9q6deuUwGixcWUoL6o4zpw5U4mgbqtp06bSrVs3qV+/vnUMYrdp0ybzjPzs2rXLElNYUFCQOh8iqY9VqVJFpkyZYp5BCCkOy3em5hPECp9PkvCqHSXj2/8oz195xUn4vDGcf/VbP5CIKu2lotGuXSCXbT9h9iAwMO6YlBWPHz+WtLQ0iYmJUaIxaNAgj8MS58+fV14hxAXe4vz58+XmzZuq7OTJkzJmzBipUaOGKu/QoYNcuXJFlXkC+oCwKbxCff7GjRvN0rx+r127Vl0X5fAmb9++bZbmcfbsWWnTpo3Vv3nz5uULu+7fv186deqkytHPvXv3miWEEG/BtIrVe05JFVtiTb3WkbL0d3+T518pniA6GtpL/O1fpb7Rvr7Wpz2nS9LutIDZmsq4U1IWQAiio6OlYcOGShwgQomJiR57jBEREeo8eGwYs3ME4cnIyEhVB17Z8uXLzZLCwZggxBrn1qxZU4ni8+fOX/ikpCSpXr26qgfvUoO6S5YsscqmTp3qcizx0KFDlrj37t3bPEoI8ZZdxy5K/YHz8oSq22Tp2CBMhT9dCZuv7MDP3pHO9fuo6+G6dQfMle1HLpg98m+MOySlCbw5jNnBQ4RgQRQwFnjq1Ck1ZuiJMGZkZFghTniZBSXA4FqoA+vbt695tHBu3bolnTt3Vue1bNmywDHE9PR0adu2raqH8UIIKnj69KkaV8Rx9BP9cMX9+/clPDxc1cMPg4LqEUIKJuPWA6kzYI7lvdVtEyVpP/q5x+OIRTW0f+qHP5cGrUZY164TMUcybt43e+a/GHdI7Ny9e1eFABHeO378uBr7i42NVQ9vjJch4eThw4dmbc9A6BEZmPAQdQIKhDE0NLTA8Tl3rFy5UrUBW7FihVsxRRgU9TDW6CnINm3evLk6D8JVEBC2AQMGqHoIp54+fVodh0DCA8RxeI3uQIgV9QryfAkhBYNNhfvGr7eEKahdjCT/9NdOIlaSlvKTt9V1dR96T16r+uXPGHdG7GBqgk4OWbZsmfTq1cvy7LTBo/KUY8eOyejRo62EFQguBHHDhg1KhIvC5MmTVVu1a9dWWZ/uGDJkiNVvCJ4n2IWxT58+5lFn4Eni3lAP94cpHMAujPgx4W5KBsKx+EwgoEuXLjWPEkI8YVPyWfm4R4ISpBrtY2Xbm//mJFylYTv/+bdS07g++lExOF7WH8j7keyvGHdF7NiFEa8QRXiJyBiFCCUkJCgPsDCQfAIPEYknOuzZvn175RUVVRA1Q4cOVe1hfBLzC90xduxYVRe2Z88e86h7kMSDvuIcZKK6u99JkyapehBGJNQACOPAgQPVcdw7fhwUBDJr4S1CGBcvXmweJYQUxo27jyR4wirLUxvxcQt5+trXnESrNAxzIDHnUfel27iVcu2Od5G1lwnjrogduzDC4DFevXrVLPUciKJuAwkm06dPV6FHXwChRrsQLWS1ugNemO4HJth7AkLFgwcPVufAm0NSUFZWllmaB95jAQE9logknVWrVqkyjHlifqL2tOPi4pS42kO+8DYfPHggc+fOtZJ0xo0bZ5YSQtyB/0s7jl6QT3pOU0JUr9UIOfJPv3ISrNK046//szRsOVz155PQBNly+JzHyYQvG8YdETt2YYQXVJjwFERUVJRqAx4TMkgRZvTVKi9aGOHVYezSHUURRmSVYuJ+nTp11HkNGjRQnifCv5gTuWbNGvUeCTraG4Yw4rjmxIkT0rp1a1UGjxAhXQgnzkfb8fHxKtwK4dX9mzBhgnk2IcQdubkvJG7xTstDG16phTz76qtOYlWahutHf9TM6lPMwh3Gs8Q/V8Ux7ojYsQsjkm6KCpZog7eJduA5wWuEOGCpNk+WUXNHSQsjQDgU3hwET58PgcO4phYzvNdzHZHcY28fGbaYCwlR1efDM8T5uk2IKsLBeMVYJBJxCCGF8zw3V+2CoUVo9y/fdxKqsrC9v/iN1adGg+f77Y4cxt0QO3ZhxPy74rJz5041kV2HC2EQTHhUnk7PcEQLoydjjBi309f1Rhg1mBoCT65du3ZK/GBdunSR8ePHy+XLl12OMdrBYgGY49i9e3clojgfWb+YY5mSksIxRkKKQPKpDEuAqnUYrZZucyVUpW3oB/qj+7Y/7bLZY//CuBtix9fCCDC2iDAjxu30hH54XRifw7JpGGvzBj253xNhhKihLsxdEkxRgLCPGjVKtW2fruENWHgAoghx3Lx5s3mUEOKOKUkHLPEZVaGRk0CVpcV92Mjq26SVzj+W/QHjToidkhBGDZJakN0Kb0mHIxFqxJQIjL1hYrwn6ExTCMq+ffvMo67R2aGo65hAU1yuX7+uPEG0j/FGT/uvQX09RxSeJBY5IIQUzqAZmyzxWfEvf3ESp7K0Ve/9yerbgOlfLiXpTxh3QuyUpDAChE5hmM4BQbTPkUQmpyehVcyv1Ocg/OjuHL2eKcYjfQ22ksJCBWgf8xm9BcKqFyDACjpFCSsTUh7pMCrREp/9P3/XSZzK0g799G2rb+1jEs0e+xfGnRA7JS2MduDBYQwSq8sgOQfzEz1ZRBzhU/QPhszOggQF67HqelgUwJeg7zqkC+8XY6beMnv2bKt/nNxPiOdUD5tpiU/Gd37oJE5lade/+X2rb+inP2LcCbFTmsKowRw/LKiNJeg88ZogSnotU4iSq6XUkBijw5zwGh3HInEdLPSNOYbeZoNi5R8sdKCnaiA07A2YtoIxV53RimQeb8dZCSnPVO3z5S4a17/1PSdxKku7+c3vWX1DP/0R406InbIQxqIAb1CPU2L6AzI/9dZPSOjBsnM6TIudMhxXr8HkfPvGw2fOnDFL8sBSbf3791dzDy9duqSOQUwhaBAyLYpdu3ZVbTmCVYLgzS5cuDDf4uDIjIWnqfvOxcMJ8Z52I5dZ4pPyk7ecxKks7fBPfmX1rW30MrPH/oVxJ8SOr4QRq7igDW8M4U5P92NERig2+NVjfK5ML3qOhdAdQdKOvS7mV9pZtGhRvnJHQzJPcHBwgSFUCKD2CF0ZRBvTNrBoQHHndRJS3kBSixafVe994CROZWlr3v3A6lv4tA1mj/0L406IHaxjqldsKc6Ec51t6Y1hc2FPhRFgGgg8OyTx2CfSY8UaiBbEraDl7LBfo75PeH34QWAHiTWYXoI69kn+WFwc8zAxzcLdUnlYiBzZs9iOSq+gA0M/sYv/tGnT6CkSUkQwDUKLz5i/NnASp7K0cf9Tz+rbxBXus+ZfVow7IXawHBoe6hij83Z7KTv37t1TbXhjEDpvMzPRX5yn+wyDYOH67kQW18Fi4ajvKIoA50I8UQe7/+u2ETb1tJ+YjoHwLvqjz0c/8eOjoD0eCSGFsy/1kiU+QW1jXqoJ/kFtR1p923083eyxf2HcDSGEEH8CS8JZO/Ybtv+Nl2PKxsGfvWP1qf6AeVwSjhBCSOmARcRHLthuidDIik3l2StfdRKq0rQc4/qxf/ty1Zuoedskh4uIE0IIKQ0wlLE15Zx8Epq37VTDlsPkxI9/6SRWpWlpP3pDGjcfqvpTqUeCbEw+4/XQ0MuCcUeEEEL8jWu3H0rXMSstDy2mQhPJfPU1J8EqDcv+6msS92FDqy+d45bLlVv+OzfZuCtCCCH+yJq9p+TjkAQlRrXaxci+N37jJFqlYRhbrN0uL+mmYnC8JO3x74xz464IIYT4I4+fZkvPiWssTw076B/7pzedhKskDTv3N2o5zOpDyPhVql/+jHFnhBBC/JX0G/elatiXS8TVbx0pF773eolP4UD76d99PZ8ooh/p1++ZPfNfjDskhBDiz2xJOS9B/efkCVS3yfJ5nVA5WsKe4/HXfynda/dQ18N1a/WfrRJuAgHjDgkhhPgzWc9yZOn2E/L3XtMt761Z88Gy9t3/ktyvvOIkasUxtLf+nf9U7etrfdJzmizeekyysgNjeUfjTgkhhPg7z5/nyoLNRy2xUoLVZbwMr9RSbv7Dd50Erih2+xvfkciPW8inRrv268zbeERdP1Aw7pYQQkigsO3IeWkZuVgqBk+1hAsZq1M+qCknf/yG3P36tzwef0Q91D/5ozck3jg/yGhHt4n2W4xYLFtTzptXDhyMuyeEEBIoYLm4Mxm3ZeD0TZaIKes2RWq0j5WeNT+TyR/Ukq1v/UFSf/wLufydH8r9//cPkv3qa3L//35DbXyM41vf+r2q18uoX7P9KHW+vb2IaRvl9OVb6nqBBoWREEICEEyZ2J92WTrFJuYTNFiFzydLlU5jDcGLVfMP67WJkgatR6hXvMdxlKOe47kdRiXK3tRL8sjPp2S4g8JICCEBzJPMZ7Jq70kV9qwTMVclyjiKnTvDsnN1Iuao85P2pKn2Ah0KIyGElAOQuXr8wnVZvjNVouZtl8/GrpTWUUvULh1V+8yQj3skqFe8b2UcR3nkvG2SaNQ/fv66ZGaXn63iKIyEEFLOeJr1TG7dfyxXbz+U9Bv35NyVO2q8EK94j+MoR73yCIWREEIIsUFhJIQQQmxQGAkhhBAbFEZCCCHEBoWREEIIsUFhJIQQQmxQGAkhhBAbFEZCCCHEBoWREEIIsUFhJIQQQmxQGAkhhBAbFEZCCCHEBoWREEIIsUFhJIQQQmxQGAkhhBAbFEZCCCHEBoWREEIIsUFhJIQQQmxQGAkhhBAbFEZCCCHEBoWREEIIsUFhJIQQQmxQGAkhhBAbFEZCCCHEBoWREEIIsUFhJIQQQixE/he3libKizKV9wAAAABJRU5ErkJggg=="></p> <p><u>Комментарий:</u></p> <p>Использование площади лесов в 2015 году в качестве знаменателя для оценки этого показателя гарантирует, что временной ряд в процентах отражает реальные изменения площади лесов в пределах установленных законом охраняемых территорий и не зависит от изменений (потерь или прибылей) в общей площади лесов.</p> <p><strong><em>Субпоказатель 4 – Доля лесных площадей, имеющих долгосрочный план управления лесами.</em></strong></p> <p><u>Единица измерения</u>: Процент</p> <p><u>Отчетный период:</u> Самый последний период</p> <p><u>Метод оценки:</u> Лесные площади, имеющие долгосрочный план управления лесами / Лесная площадь в 2015 году * 100</p> <p><u>Перевод на инструментальную панель / световые сигналы: </u>Значение показателя за последний отчетный год сравнивается со значением показателя за предыдущий отчетный год для оценки непрерывности прогресса с момента последнего отчета.</p> <p>Рассчитывается соотношение (r) между текущим значением показателя и ранее отраженным значением; r & gt; 1 означает увеличение запасов на гектар, r & lt; 1 означает уменьшение, а 1 означает отсутствие изменений. Был установлен узкий интервал для r, чтобы указать стабильное состояние, и цвета светового сигнала обозначаются следующим образом:</p> <p><img src="data:image/png;base64,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"></p> <p><u>Комментарий:</u></p> <p>Использование площади лесов в 2015 году в качестве знаменателя для оценки этого показателя гарантирует, что временной ряд в процентах отражает реальные изменения площади лесов, имеющих долгосрочный план управления лесами, и не зависит от изменений (потерь или прибылей) в общей площади лесов. </p> <p><strong><em>Субпоказатель 5 – Площадь лесов, на которых действует система сертификации использования лесов, прошедшая независимую проверку.</em></strong></p> <p><u>Единица измерения</u>: Тысяч гектаров</p> <p><u>Отчетный период:</u> Самый последний период (по состоянию на 30 июня)</p> <p><u>Метод оценки:</u> Данные собираются непосредственно из баз данных каждой системы сертификации и предоставляются странам для проверки.</p> <p><u>Перевод на инструментальную панель / световые сигналы: </u>Значение показателя за последний отчетный год сравнивается со значением показателя за предыдущий отчетный год для оценки непрерывности прогресса с момента последнего отчета.</p> <p>Рассчитывается соотношение (r) между текущим значением показателя и ранее отраженным значением; r & gt; 1 означает увеличение запасов на гектар, r & lt; 1 означает уменьшение, а 1 означает отсутствие изменений. Был установлен узкий интервал для r, чтобы указать стабильное состояние, и цвета светового сигнала обозначаются следующим образом:</p> <p><img src="data:image/png;base64,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"> </p> <p><u>Комментарии:</u></p> <p>Использование 30 июня в качестве отчетной даты позволяет органам по сертификации обновлять свои базы данных, чтобы они могли предоставлять информацию в ФАО к концу года, а затем включать ее в годовую отчетность для ЦУР в начале следующего года.</p><div class="footnotes"><div><sup class="footnote-number" id="footnote-1">1</sup><p> Глобальная оценка лесных ресурсов 2015 г. – Обозначения и определения <a href="http://www.fao.org/docrep/017/ap862e:/www.fo.org/docrep/017/ap862e/ap862e00.pdf</a> <a href="#footnote-ref-1">↑</a></p></div></div> |
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<p><strong>URL: </strong><a href="http://www.fao.org/forest-resources-assessment/en/"><u>http://www.fao.org/forest-resources-assessment/en/</u></a> </p>
<p><strong>References:</strong></p> <p></p> <p>Global Forest Resources Assessment 2020, Guidelines and Specifications (<a href="http://www.fao.org/3/I8699EN/i8699en.pdf"><u>www.fao.org/3/I8699EN/i8699en.pdf</u></a>)</p> <p>Global Forest Resources Assessment 2020, Terms and Definitions (<a href="http://www.fao.org/3/I8661EN/i8661en.pdf"><u>www.fao.org/3/I8661EN/i8661en.pdf</u></a>).</p> <p>United Nations. Resolution adopted by the General Assembly on 17 December 2007 (<a href="https://undocs.org/en/A/RES/62/98">https://undocs.org/en/A/RES/62/98</a>). </p> <p><strong>Annex 1 – Terms and Definitions </strong></p> <p><strong>FOREST</strong></p> <p>Land spanning more than 0.5 hectares with <u>tree</u>s higher than 5 meters and a <u>canopy cover</u> of more than 10 percent, or trees able to reach these thresholds <em>in situ</em>. It does not include land that is predominantly under agricultural or urban land use. </p> <p><u>Explanatory notes</u></p> <ol> <li>Forest is determined both by the presence of trees and the absence of other predominant land uses. The trees should be able to reach a minimum height of 5 meters. </li> <li>Includes areas with young trees that have not yet reached but which are expected to reach a canopy cover of at least 10 percent and tree height of 5 meters or more. It also includes areas that are temporarily unstocked due to clear-cutting as part of a forest management practice or natural disasters, and which are expected to be regenerated within 5 years. Local conditions may, in exceptional cases, justify that a longer time frame is used.</li> <li>Includes forest roads, firebreaks and other small open areas; forest in national parks, nature reserves and other protected areas such as those of specific environmental, scientific, historical, cultural or spiritual interest.</li> <li>Includes windbreaks, shelterbelts and corridors of trees with an area of more than 0.5 hectares and width of more than 20 meters.</li> <li>Includes abandoned shifting cultivation land with a regeneration of trees that have, or are expected to reach, a canopy cover of at least 10 percent and tree height of at least 5 meters.</li> <li>Includes areas with mangroves in tidal zones, regardless whether this area is classified as land area or not.</li> <li>Includes rubberwood, cork oak and Christmas tree plantations. </li> <li>Includes areas with bamboo and palms provided that land use, height and canopy cover criteria are met.</li> <li><u>Excludes</u> tree stands in agricultural production systems, such as fruit tree plantations, oil palm plantations, olive orchards and agroforestry systems when crops are grown under tree cover. <u>Note:</u> Some agroforestry systems such as the “Taungya” system where crops are grown only during the first years of the forest rotation should be classified as forest.</li> </ol> <p><strong>ABOVE-GROUND BIOMASS</strong></p> <p>All living biomass above the soil including stem, stump, branches, bark, seeds, and foliage.</p> <p><u>Explanatory note </u></p> <ol> <li>In cases where forest understorey is a relatively small component of the aboveground biomass carbon pool, it is acceptable to exclude it, provided this is done in a consistent manner throughout the inventory time series.</li> </ol> <p><strong>PROTECTED AREAS</strong></p> <p>Areas especially dedicated to the protection and maintenance of biological diversity, and of natural and associated cultural resources, and managed through legal or other effective means.</p> <p><strong>FOREST AREA WITHIN PROTECTED AREAS</strong></p> <p>Forest area within formally established protected areas independently of the purpose for which the protected areas were established. </p> <p><u>Explanatory notes</u></p> <ol> <li>Includes IUCN Categories I – IV</li> <li><u>Excludes</u> IUCN Categories V-VI</li> </ol> <p><strong>FOREST AREA WITH MANAGEMENT PLAN</strong></p> <p>Forest area that has a long-term documented management plan, aiming at defined management goals, which is periodically revised. </p> <p><u>Explanatory notes</u></p> <ol> <li>A forest area with management plan may refer to forest management unit level or aggregated forest management unit level (forest blocks, farms, enterprises, watersheds, municipalities, or wider units).</li> <li>A management plan must include adequate detail on operations planned for individual operational units (stands or compartments) but may also provide general strategies and activities planned to reach management goals.</li> <li>Includes forest area in protected areas with management plan.</li> </ol> <p><strong>INDEPENDENTLY VERIFIED FOREST MANAGEMENT CERTIFICATION</strong></p> <p>Forest area certified under a forest management certification scheme with published standards and is independently verified by a third-party.</p> <p><strong>Annex 2 – Methodology</strong></p> <p><strong>Sub-indicator 1 - Annual forest area change rate</strong></p> <p><u>Unit</u>: Percent</p> <p><u>Reference period:</u> 2010-2020</p> <p><u>Method of estimation:</u> Compound annual change rate formula as follows:</p> <p> <p>with: </p> <p>r = compound annual change rate for the period t<sub>1 - </sub>t<sub>2 </sub></p> <p>t<sub>i</sub> = time i (year)</p> <p>A<sub>t1 </sub>= forest area at t<sub>1 </sub></p> <p>A<sub>t2 </sub>= forest area at t<sub>2</sub></p> <p><u>Translation to dashboard/traffic light:</u></p> <p>The following flowchart explains the logic behind the translation of this indicator to a dashboard/traffic light:</p> <p>Forest area change direction</p> <p>Forest area stable </p> <p>or increasing</p> <p>Forest area decreasing</p> <p>Change in forest area loss rate </p> <p>Loss rate</p> <p>decreasing</p> <p>Loss rate stable</p> <p>or increasing</p> <p>The forest area change direction is determined by examining the value of the forest area change rate for the most recent period, a negative value indicate a loss of forest area, a zero value means that forest area is stable and a positive value means that forest area has increased. The change in forest area loss rate<sup><a href="#footnote-2" id="footnote-ref-2">[1]</a></sup> is based on a comparison of the annual forest area change rate for the period 2010-2020 with the annual <u>forest area change rate for the period 2000-2010 </u>(<u>baseline).</u></p> <p><u>Comments:</u></p> <p>This traffic light takes into consideration both the direction of forest area change (if forest area increases or decreases) as well as changes in the rate of forest area loss – the latter important in order to indicate progress among countries that are losing forest area but manage to reduce the loss rate. </p> <p>The baseline should be updated every 5 years. In 2020 a new baseline was calculated for the period 2000-2010 based on updated country data. Also, if a country reports new historical data to FAO within a 5-year cycle, the baseline for the country will be recalculated accordingly.</p> <p><strong>Sub-indicator 2 – Above-ground biomass stock in forest </strong></p> <p><u>Unit</u>: tonnes/hectare</p> <p><u>Reference year:</u> Latest reporting year</p> <p><u>Method of estimation:</u> Reported directly by countries</p> <p><u>Translation to dashboard/traffic light:</u></p> <p>The indicator value for the latest reporting year is compared with the indicator value for previous reporting year for assessment of continuity of progress since last report.</p> <p>The ratio (r) between the current indicator value and the previously reported value is calculated; r>1 means an increase in stock per hectare, r<1 means a decrease while 1 indicates no change. A narrow interval for r has been established to indicate a stable condition, and traffic-light colors are assigned as follows:</p> <p> r ≥ 1.01 </p> <p> 0.99 < r < 1.01</p> <p> r ≤ 0.99</p> <p><strong>Sub-indicator 3 – Proportion of forest area located within legally established protected areas.</strong></p> <p><u>Unit</u>: Percent</p> <p><u>Reference year:</u> Latest reporting year</p> <p><u>Method of estimation:</u> Forest area within legally established protected areas / forest area 2015 * 100</p> <p><u>Translation to dashboard/traffic light:</u></p> <p>The indicator value for latest reporting year is compared the indicator value for previous reporting year for assessment of continuity of progress since last report.</p> <p>The ratio (r) between the current indicator value and the previously reported value is calculated; r>1 means an increase in forest area within protected areas, r<1 means a decrease while 1 indicates no change. A narrow interval for r has been established to indicate a stable condition, and traffic-light colors are assigned as follows:</p> <p> r ≥ 1.01 </p> <p> 0.99 < r < 1.01</p> <p> r ≤ 0.99</p> <p><u>Comment:</u></p> <p>Using forest area in 2015 as denominator for estimating this indicator ensures that the time series of percentages reflect real changes in the forest area within legally established protected areas and is not affected by changes (losses or gains) in total forest area. </p> <p><strong>Sub-indicator 4 – Proportion of forest area under a long-term forest management plan.</strong></p> <p><u>Unit</u>: Percent</p> <p><u>Reference year:</u> Latest reporting year</p> <p><u>Method of estimation:</u> Forest area under a long term forest management plan / forest area 2015 * 100</p> <p><u>Translation to dashboard/traffic light: </u>The indicator value for latest reporting year is compared with the indicator value for previous reporting year for assessment of continuity of progress since last report.</p> <p>The ratio (r) between the current indicator value and the previously reported value is calculated; r>1 means an increase in areas under forest management plan, r<1 means a decrease while 1 indicates no change. A narrow interval for r has been established to indicate a stable condition, and traffic-light colors are assigned as follows:</p> <p> r ≥ 1.01 </p> <p> 0.99 < r < 1.01</p> <p> r ≤ 0.99</p> <p><u>Comment:</u></p> <p>Using forest area in 2015 as denominator for estimating this indicator ensures that the time series of percentages reflect real changes in the forest area under forest <mi>r</mi> <mo>=</mo> <mfenced open="[" close="]" separators="|"> <mrow> <msup> <mrow> <mfenced separators="|"> <mrow> <mfrac> <mrow> <msub> <mrow> <mi>A</mi> <mi>F</mi> </mrow> <mrow> <mi>t</mi> <mn>2</mn> </mrow> </msub> </mrow> <mrow> <msub> <mrow> <mi>A</mi> <mi>F</mi> </mrow> <mrow> <mi>t</mi> <mn>1</mn> </mrow> </msub> </mrow> </mfrac> </mrow> </mfenced> </mrow> <mrow> <mfrac bevelled="true"> <mrow> <mn>1</mn> </mrow> <mrow> <mfenced separators="|"> <mrow> <mi>t</mi> <mn>2</mn> <mo>-</mo> <mi>t</mi> <mn>1</mn> </mrow> </mfenced> </mrow> </mfrac> </mrow> </msup> <mo>-</mo> <mn>1</mn> </mrow> </mfenced> <mo>×</mo> <mn>100</mn> </math></p> <p>where: </p> <p><em>r</em> = compound annual change rate for the period <em>t<sub>1 - </sub>t<sub>2</sub></em><sub> </sub></p> <p><em>t<sub>i</sub></em> = time i (year)</p> <p><em>AF<sub>t1</sub></em> = forest area at <em>t<sub>1</sub></em> </p> <p><em>AF<sub>t2</sub></em> = forest area at <em>t<sub>2</sub></em></p> <p><u>Translation to dashboard/traffic light:</u></p> <p>The following flowchart explains the logic behind the translation of this indicator to a dashboard/traffic light:</p> <p>Forest area change direction</p> <p>Forest area stable </p> <p>or increasing</p> <p>Forest area decreasing</p> <p>Change in forest area loss rate </p> <p>Loss rate</p> <p>decreasing</p> <p>Loss rate stable</p> <p>or increasing</p> <p>The forest area change direction is determined by examining the value of the forest area change rate for the most recent period, a negative value indicate a loss of forest area, a zero value means that forest area is stable, and a positive value means that forest area has increased. The change in forest area loss rate<sup><a href="#footnote-2" id="footnote-ref-2">[1]</a></sup> is based on a comparison of the annual forest area change rate for the period 2010-2020 with the annual <u>forest area change rate for the period 2000-2010 </u>(<u>baseline).</u></p> <p><u>Comments:</u></p> <p>This traffic light takes into consideration both the direction of forest area change (if forest area increases or decreases) as well as changes in the rate of forest area loss – the latter important in order to indicate progress among countries that are losing forest area but manage to reduce the loss rate. </p> <p>The baseline should be updated every 5 years. In 2020 a new baseline was calculated for the period 2000-2010 based on updated country data. </p> <p><strong>Sub-indicator 2 – Above-ground biomass in forest </strong></p> <p><u>Unit</u>: tonnes/hectare</p> <p><u>Reference year:</u> Latest reporting year</p> <p><u>Method of estimation:</u> Reported directly by countries</p> <p><u>Translation to dashboard/traffic light:</u></p> <p>The indicator value for the latest reporting year is compared with the indicator value reported for 2010.</p> <p>The ratio (r) between the current indicator value and the value reported for 2010 is calculated; r>1 means an increase in stock per hectare, r<1 means a decrease while 1 indicates no change. A narrow interval for r has been established to indicate a stable condition, and traffic-light colors are assigned as follows:</p> <p> r ≥ 1.01 </p> <p> 0.99 < r < 1.01</p> <p> r ≤ 0.99</p> <p><strong>Sub-indicator 3 – Proportion of forest area within legally established protected areas.</strong></p> <p><u>Unit</u>: Percent</p> <p><u>Reference year:</u> Latest reporting year</p> <p><u>Method of estimation:</u> </p> <p><math xmlns="http://www.w3.org/1998/Math/MathML"> <mi>r</mi> <mo>=</mo> <mi>&nbsp;</mi> <mfrac> <mrow> <msub> <mrow> <mi>A</mi> <mi>F</mi> <mi>P</mi> </mrow> <mrow> <mfenced open="[" close="]" separators="|"> <mrow> <mi>r</mi> <mi>e</mi> <mi>f</mi> <mi>e</mi> <mi>r</mi> <mi>e</mi> <mi>n</mi> <mi>c</mi> <mi>e</mi> <mi>&nbsp;</mi> <mi>y</mi> <mi>e</mi> <mi>a</mi> <mi>r</mi> </mrow> </mfenced> </mrow> </msub> </mrow> <mrow> <msub> <mrow> <mi>A</mi> <mi>F</mi> </mrow> <mrow> <mn>2015</mn> </mrow> </msub> </mrow> </mfrac> <mo>×</mo> <mn>100</mn> </math></p> <p>Where:</p> <p><em>AFP</em> = Forest area within legally established protected areas</p> <p><em>AF</em> = Total forest area</p> <p><u>Translation to dashboard/traffic light:</u></p> <p>The indicator value for latest reporting year is compared with the indicator value reported for 2010.</p> <p>The ratio (r) between the current indicator value and the value reported for 2010 is calculated; r>1 means an increase in forest area within protected areas, r<1 means a decrease while 1 indicates no change. A narrow interval for r has been established to indicate a stable condition, and traffic-light colors are assigned as follows:</p> <p> r ≥ 1.01 </p> <p> 0.99 < r < 1.01</p> <p> r ≤ 0.99</p> <p><u>Comment:</u></p> <p>Using forest area in 2015 as denominator for estimating this indicator ensures that the time series of percentages reflect real changes in the forest area within legally established protected areas and is not affected by changes (losses or gains) in total forest area. </p> <p><strong>Sub-indicator 4 – Proportion of forest area under a long-term management plan.</strong></p> <p><u>Unit</u>: Percent</p> <p><u>Reference year:</u> Latest reporting year</p> <p><u>Method of estimation:</u> </p> <p><math xmlns="http://www.w3.org/1998/Math/MathML"> <mi>r</mi> <mo>=</mo> <mi>&nbsp;</mi> <mfrac> <mrow> <msub> <mrow> <mi>A</mi> <mi>F</mi> <mi>M</mi> <mi>P</mi> </mrow> <mrow> <mfenced open="[" close="]" separators="|"> <mrow> <mi>r</mi> <mi>e</mi> <mi>f</mi> <mi>e</mi> <mi>r</mi> <mi>e</mi> <mi>n</mi> <mi>c</mi> <mi>e</mi> <mi>&nbsp;</mi> <mi>y</mi> <mi>e</mi> <mi>a</mi> <mi>r</mi> </mrow> </mfenced> </mrow> </msub> </mrow> <mrow> <msub> <mrow> <mi>A</mi> <mi>F</mi> </mrow> <mrow> <mn>2015</mn> </mrow> </msub> </mrow> </mfrac> <mo>×</mo> <mn>100</mn> </math></p> <p>Where:</p> <p><em>AFMP</em> = Forest area under a long-term management plan</p> <p><em>AF</em> = Total forest area</p> <p><u>Translation to dashboard/traffic light: </u>The indicator value for latest reporting year is compared with the indicator value reported for 2010.</p> <p>The ratio (r) between the current indicator value and the value reported for 2010 is calculated; r>1 means an increase in areas under management plan, r<1 means a decrease while 1 indicates no change. A narrow interval for r has been established to indicate a stable condition, and traffic-light colors are assigned as follows:</p> <p> r ≥ 1.01 </p> <p> 0.99 < r < 1.01</p> <p> r ≤ 0.99</p> <p><u>Comment:</u></p> <p>Using forest area in 2015 as denominator for estimating this indicator ensures that the time series of percentages reflect real changes in the forest area under management plan and is not affected by changes (losses or gains) in total forest area. </p> <p><strong>Sub-indicator 5 – Forest area under an independently verified forest management certification scheme.</strong></p> <p><u>Unit</u>: Thousand hectares</p> <p><u>Reference year:</u> Latest reporting year (as of June 30)</p> <p><u>Method of estimation:</u> Data is collected directly from the databases of each certification scheme and provided to countries for validation.</p> <p><u>Translation to dashboard/traffic light: </u>The indicator value for latest reporting year is compared with the indicator value for previous reporting year for assessment of continuity of progress since last report.</p> <p>The ratio (r) between the current indicator value and the previously reported value is calculated; r>1 means an increase in areas under an independent forest management certification scheme, r<1 means a decrease while 1 indicates no change. A small interval for r has been established to indicate a stable condition, and traffic-light colors are assigned as follows:</p> <p> r ≥ 1.01 </p> <p> 0.99 < r < 1.01</p> <p> r ≤ 0.99</p> <p><u>Comments:</u></p> <p>Using June 30 as the date for reporting, allows for the certification bodies to have their databases updated so they can provide information to FAO by end of the year, and then be included in the annual reporting to SDG in the beginning of the following year.</p><div class="footnotes"><div><sup class="footnote-number" id="footnote-2">1</sup><p> If forest area change rate is negative (= forest loss) then: annual forest area loss rate = <strong>-</strong> (annual forest area change rate) <a href="#footnote-ref-2">↑</a></p></div></div> |
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<p><strong>URL: </strong><a href="http://www.fao.org/forest-resources-assessment/en/"><u>http://www.fao.org/forest-resources-assessment/en/</u></a> </p>
<p><strong>References:</strong></p> <p>Global Forest Resources Assessment 2020, Guidelines and Specifications (<a href="http://www.fao.org/3/I8699EN/i8699en.pdf"><u>www.fao.org/3/I8699EN/i8699en.pdf</u></a>)</p> <p>Global Forest Resources Assessment 2020, Terms and Definitions (<a href="http://www.fao.org/3/I8661EN/i8661en.pdf"><u>www.fao.org/3/I8661EN/i8661en.pdf</u></a>).</p> <p>United Nations. Resolution adopted by the General Assembly on 17 December 2007 (<a href="https://undocs.org/en/A/RES/62/98">https://undocs.org/en/A/RES/62/98</a>). </p> <p><strong>Annex 1 – Terms and Definitions </strong></p> <p><strong>FOREST</strong></p> <p>Land spanning more than 0.5 hectares with <u>tree</u>s higher than 5 meters and a <u>canopy cover</u> of more than 10 percent, or trees able to reach these thresholds <em>in situ</em>. It does not include land that is predominantly under agricultural or urban land use. </p> <p><u>Explanatory notes</u></p> <ol> <li>Forest is determined both by the presence of trees and the absence of other predominant land uses. The trees should be able to reach a minimum height of 5 meters. </li> <li>Includes areas with young trees that have not yet reached but which are expected to reach a canopy cover of at least 10 percent and tree height of 5 meters or more. It also includes areas that are temporarily unstocked due to clear-cutting as part of a forest management practice or natural disasters, and which are expected to be regenerated within 5 years. Local conditions may, in exceptional cases, justify that a longer time frame is used.</li> <li>Includes forest roads, firebreaks and other small open areas; forest in national parks, nature reserves and other protected areas such as those of specific environmental, scientific, historical, cultural or spiritual interest.</li> <li>Includes windbreaks, shelterbelts and corridors of trees with an area of more than 0.5 hectares and width of more than 20 meters.</li> <li>Includes abandoned shifting cultivation land with a regeneration of trees that have, or are expected to reach, a canopy cover of at least 10 percent and tree height of at least 5 meters.</li> <li>Includes areas with mangroves in tidal zones, regardless whether this area is classified as land area or not.</li> <li>Includes rubberwood, cork oak and Christmas tree plantations. </li> <li>Includes areas with bamboo and palms provided that land use, height and canopy cover criteria are met.</li> <li><u>Excludes</u> tree stands in agricultural production systems, such as fruit tree plantations, oil palm plantations, olive orchards and agroforestry systems when crops are grown under tree cover. <u>Note:</u> Some agroforestry systems such as the “Taungya” system where crops are grown only during the first years of the forest rotation should be classified as forest.</li> </ol> <p><strong>ABOVE-GROUND BIOMASS</strong></p> <p>All living biomass above the soil including stem, stump, branches, bark, seeds, and foliage.</p> <p><u>Explanatory note </u></p> <ol> <li>In cases where forest understorey is a relatively small component of the aboveground biomass carbon pool, it is acceptable to exclude it, provided this is done in a consistent manner throughout the inventory time series.</li> </ol> <p><strong>PROTECTED AREAS</strong></p> <p>Areas especially dedicated to the protection and maintenance of biological diversity, and of natural and associated cultural resources, and managed through legal or other effective means.</p> <p><strong>FOREST AREA WITHIN PROTECTED AREAS</strong></p> <p>Forest area within formally established protected areas independently of the purpose for which the protected areas were established. </p> <p><u>Explanatory notes</u></p> <ol> <li>Includes IUCN Categories I – IV</li> <li><u>Excludes</u> IUCN Categories V-VI</li> </ol> <p><strong>FOREST AREA WITH MANAGEMENT PLAN</strong></p> <p>Forest area that has a long-term documented management plan, aiming at defined management goals, which is periodically revised. </p> <p><u>Explanatory notes</u></p> <ol> <li>A forest area with management plan may refer to forest management unit level or aggregated forest management unit level (forest blocks, farms, enterprises, watersheds, municipalities, or wider units).</li> <li>A management plan must include adequate detail on operations planned for individual operational units (stands or compartments) but may also provide general strategies and activities planned to reach management goals.</li> <li>Includes forest area in protected areas with management plan.</li> </ol> <p><strong>INDEPENDENTLY VERIFIED FOREST MANAGEMENT CERTIFICATION</strong></p> <p>Forest area certified under a forest management certification scheme with published standards and is independently verified by a third-party.</p> <p><strong>Annex 2 – Methodology</strong></p> <p><strong>Sub-indicator 1 - Annual forest area change rate</strong></p> <p><u>Unit</u>: Percent</p> <p><u>Reference period:</u> 2010-2020</p> <p><u>Method of estimation:</u> Compound annual change rate formula as follows:</p> <p><math xmlns="http://www.w3.org/1998/Math/MathML"> <mi>r</mi> <mo>=</mo> <mfenced open="[" close="]" separators="|"> <mrow> <msup> <mrow> <mfenced separators="|"> <mrow> <mfrac> <mrow> <msub> <mrow> <mi>A</mi> <mi>F</mi> </mrow> <mrow> <mi>t</mi> <mn>2</mn> </mrow> </msub> </mrow> <mrow> <msub> <mrow> <mi>A</mi> <mi>F</mi> </mrow> <mrow> <mi>t</mi> <mn>1</mn> </mrow> </msub> </mrow> </mfrac> </mrow> </mfenced> </mrow> <mrow> <mfrac bevelled="true"> <mrow> <mn>1</mn> </mrow> <mrow> <mfenced separators="|"> <mrow> <mi>t</mi> <mn>2</mn> <mo>-</mo> <mi>t</mi> <mn>1</mn> </mrow> </mfenced> </mrow> </mfrac> </mrow> </msup> <mo>-</mo> <mn>1</mn> </mrow> </mfenced> <mo>×</mo> <mn>100</mn> </math></p> <p>where: </p> <p><em>r</em> = compound annual change rate for the period <em>t<sub>1 - </sub>t<sub>2</sub></em><sub> </sub></p> <p><em>t<sub>i</sub></em> = time i (year)</p> <p><em>AF<sub>t1</sub></em> = forest area at <em>t<sub>1</sub></em> </p> <p><em>AF<sub>t2</sub></em> = forest area at <em>t<sub>2</sub></em></p> <p><u>Translation to dashboard/traffic light:</u></p> <p>The following flowchart explains the logic behind the translation of this indicator to a dashboard/traffic light:</p> <p>Forest area change direction</p> <p>Forest area stable </p> <p>or increasing</p> <p>Forest area decreasing</p> <p>Change in forest area loss rate </p> <p>Loss rate</p> <p>decreasing</p> <p>Loss rate stable</p> <p>or increasing</p> <p>The forest area change direction is determined by examining the value of the forest area change rate for the most recent period, a negative value indicate a loss of forest area, a zero value means that forest area is stable, and a positive value means that forest area has increased. The change in forest area loss rate<sup><a href="#footnote-2" id="footnote-ref-2">[1]</a></sup> is based on a comparison of the annual forest area change rate for the period 2010-2020 with the annual <u>forest area change rate for the period 2000-2010 </u>(<u>baseline).</u></p> <p><u>Comments:</u></p> <p>This traffic light takes into consideration both the direction of forest area change (if forest area increases or decreases) as well as changes in the rate of forest area loss – the latter important in order to indicate progress among countries that are losing forest area but manage to reduce the loss rate. </p> <p>The baseline should be updated every 5 years. In 2020 a new baseline was calculated for the period 2000-2010 based on updated country data. </p> <p><strong>Sub-indicator 2 – Above-ground biomass in forest </strong></p> <p><u>Unit</u>: tonnes/hectare</p> <p><u>Reference year:</u> Latest reporting year</p> <p><u>Method of estimation:</u> Reported directly by countries</p> <p><u>Translation to dashboard/traffic light:</u></p> <p>The indicator value for the latest reporting year is compared with the indicator value reported for 2010.</p> <p>The ratio (r) between the current indicator value and the value reported for 2010 is calculated; r>1 means an increase in stock per hectare, r<1 means a decrease while 1 indicates no change. A narrow interval for r has been established to indicate a stable condition, and traffic-light colors are assigned as follows:</p> <p> r ≥ 1.01 </p> <p> 0.99 < r < 1.01</p> <p> r ≤ 0.99</p> <p><strong>Sub-indicator 3 – Proportion of forest area within legally established protected areas.</strong></p> <p><u>Unit</u>: Percent</p> <p><u>Reference year:</u> Latest reporting year</p> <p><u>Method of estimation:</u> </p> <p><math xmlns="http://www.w3.org/1998/Math/MathML"> <mi>r</mi> <mo>=</mo> <mi>&nbsp;</mi> <mfrac> <mrow> <msub> <mrow> <mi>A</mi> <mi>F</mi> <mi>P</mi> </mrow> <mrow> <mfenced open="[" close="]" separators="|"> <mrow> <mi>r</mi> <mi>e</mi> <mi>f</mi> <mi>e</mi> <mi>r</mi> <mi>e</mi> <mi>n</mi> <mi>c</mi> <mi>e</mi> <mi>&nbsp;</mi> <mi>y</mi> <mi>e</mi> <mi>a</mi> <mi>r</mi> </mrow> </mfenced> </mrow> </msub> </mrow> <mrow> <msub> <mrow> <mi>A</mi> <mi>F</mi> </mrow> <mrow> <mn>2015</mn> </mrow> </msub> </mrow> </mfrac> <mo>×</mo> <mn>100</mn> </math></p> <p>Where:</p> <p><em>AFP</em> = Forest area within legally established protected areas</p> <p><em>AF</em> = Total forest area</p> <p><u>Translation to dashboard/traffic light:</u></p> <p>The indicator value for latest reporting year is compared with the indicator value reported for 2010.</p> <p>The ratio (r) between the current indicator value and the value reported for 2010 is calculated; r>1 means an increase in forest area within protected areas, r<1 means a decrease while 1 indicates no change. A narrow interval for r has been established to indicate a stable condition, and traffic-light colors are assigned as follows:</p> <p> r ≥ 1.01 </p> <p> 0.99 < r < 1.01</p> <p> r ≤ 0.99</p> <p><u>Comment:</u></p> <p>Using forest area in 2015 as denominator for estimating this indicator ensures that the time series of percentages reflect real changes in the forest area within legally established protected areas and is not affected by changes (losses or gains) in total forest area. </p> <p><strong>Sub-indicator 4 – Proportion of forest area under a long-term management plan.</strong></p> <p><u>Unit</u>: Percent</p> <p><u>Reference year:</u> Latest reporting year</p> <p><u>Method of estimation:</u> </p> <p><math xmlns="http://www.w3.org/1998/Math/MathML"> <mi>r</mi> <mo>=</mo> <mi>&nbsp;</mi> <mfrac> <mrow> <msub> <mrow> <mi>A</mi> <mi>F</mi> <mi>M</mi> <mi>P</mi> </mrow> <mrow> <mfenced open="[" close="]" separators="|"> <mrow> <mi>r</mi> <mi>e</mi> <mi>f</mi> <mi>e</mi> <mi>r</mi> <mi>e</mi> <mi>n</mi> <mi>c</mi> <mi>e</mi> <mi>&nbsp;</mi> <mi>y</mi> <mi>e</mi> <mi>a</mi> <mi>r</mi> </mrow> </mfenced> </mrow> </msub> </mrow> <mrow> <msub> <mrow> <mi>A</mi> <mi>F</mi> </mrow> <mrow> <mn>2015</mn> </mrow> </msub> </mrow> </mfrac> <mo>×</mo> <mn>100</mn> </math></p> <p>Where:</p> <p><em>AFMP</em> = Forest area under a long-term management plan</p> <p><em>AF</em> = Total forest area</p> <p><u>Translation to dashboard/traffic light: </u>The indicator value for latest reporting year is compared with the indicator value reported for 2010.</p> <p>The ratio (r) between the current indicator value and the value reported for 2010 is calculated; r>1 means an increase in areas under management plan, r<1 means a decrease while 1 indicates no change. A narrow interval for r has been established to indicate a stable condition, and traffic-light colors are assigned as follows:</p> <p> r ≥ 1.01 </p> <p> 0.99 < r < 1.01</p> <p> r ≤ 0.99</p> <p><u>Comment:</u></p> <p>Using forest area in 2015 as denominator for estimating this indicator ensures that the time series of percentages reflect real changes in the forest area under management plan and is not affected by changes (losses or gains) in total forest area. </p> <p><strong>Sub-indicator 5 – Forest area under an independently verified forest management certification scheme.</strong></p> <p><u>Unit</u>: Thousand hectares</p> <p><u>Reference year:</u> Latest reporting year (as of June 30)</p> <p><u>Method of estimation:</u> Data is collected directly from the databases of each certification scheme and provided to countries for validation.</p> <p><u>Translation to dashboard/traffic light: </u>The indicator value for latest reporting year is compared with the indicator value for previous reporting year for assessment of continuity of progress since last report.</p> <p>The ratio (r) between the current indicator value and the previously reported value is calculated; r>1 means an increase in areas under an independent forest management certification scheme, r<1 means a decrease while 1 indicates no change. A small interval for r has been established to indicate a stable condition, and traffic-light colors are assigned as follows:</p> <p> r ≥ 1.01 </p> <p> 0.99 < r < 1.01</p> <p> r ≤ 0.99</p> <p><u>Comments:</u></p> <p>Using June 30 as the date for reporting, allows for the certification bodies to have their databases updated so they can provide information to FAO by end of the year, and then be included in the annual reporting to SDG in the beginning of the following year.</p><div class="footnotes"><div><sup class="footnote-number" id="footnote-2">1</sup><p> If forest area change rate is negative (= forest loss) then: annual forest area loss rate = <strong>-</strong> (annual forest area change rate) <a href="#footnote-ref-2">↑</a></p></div></div>
<h1>Ссылки </h1>
<h2>URL: </h2> <p><a href="http://www.fao.org/forest-resources-assessment/en/">http://www.fao.org/forest-resources-assessment/en/</a> </p> <h2>Рекомендации:</h2> <p><a href="http://www.fao.org/forest-resources-assessment/current-assessment/en/">http://www.fao.org/forest-resources-assessment/current-assessment/en/</a></p> <h1>Приложение 1 Обозначения и определения<sup><a href="#footnote-1" id="footnote-ref-1">[1]</a></sup></h1> <p><strong><em>ЛЕС</em></strong></p> <p>Участок земли площадью более 0,5 гектара, на котором растут деревья высотой более пяти метров с сомкнутостью крон более десяти процентов, или деревья, способные на данном участке достичь этих пороговых значений. Не включаются земли, которые используются преимущественно для целей сельского хозяйства или поселений<strong>. </strong></p> <p><u>Пояснительные примечания</u></p> <ol> <li>Лес определяется как наличием деревьев, так и отсутствием других преобладающих видов землепользования. Деревья должны быть способны достигать минимальной высоты 5 м. </li> <li>Сюда входят участки с молодыми деревьями, с сомкнутостью крон еще не достигшей, но которая, как ожидается, достигнет 10 %, а деревья – высоты 5 метров. Он также включает участки, которые являются временно обезлесенными из-за сплошных рубок в рамках практики ведения лесного хозяйства или из-за стихийных бедствий, но которые, как ожидается, будут восстановлены в течение 5 лет. В исключительных случаях, с учетом местных условий, могут устанавливаться более продолжительные временные сроки.</li> <li>Лес включает лесные дороги, противопожарные полосы и другие небольшие открытые пространства, леса в национальных парках, природных заповедниках и на других охраняемых территориях, представляющих особый экологический, научный, исторический, культурный или духовный интерес.</li> <li>Лес включает ветрозащитные полосы, лесозащитные полосы и полосы деревьев площадью более 0,5 га и шириной более 20 м.</li> <li>Сюда входят заброшенные земли со сменной культивацией, где производится восстановление лесонасаждений, которые имеют или, как ожидается, будут иметь сомкнутость крон 10 %, а деревья – высоту 5 метров.</li> <li>Лес включает площади, занятые мангровыми лесами в приливных зонах, независимо от того, классифицируются ли эти площади в качестве земельных площадей.</li> <li>Лес включает плантации каучуковых деревьев, пробкового дуба и рождественских елок. </li> <liСюда входят площади, занятые бамбуковыми и пальмовыми лесами при условии, что землепользование, высота деревьев и сомкнутость крон соответствуют установленным критериям.</li> <li>Лес не включает древесные насаждения, вовлеченные в сельскохозяйственное производство, такие как плантации плодовых деревьев, плантации масличной пальмы, оливковые рощи и агролесоводственные системы, при которых сельскохозяйственные культуры выращиваются под кронами деревьев. <u>Примечание:</u>Площади, включенные в некоторые агролесоводственные системы, такие как система Taungya, при которых сельскохозяйственные культуры выращиваются только в первые годы оборота лесного хозяйства, должны рассматриваться как лес.</li> </ol> <p><strong><em>НАДПОЧВЕННАЯ БИОМАССА</em></strong></p> <p>Вся биомасса живого растительного покрова, как древесного, так и травянистого, включая стволы, пни, ветви, кору, семена и листву.</p> <p><u>Пояснительные примечания </u></p> <ol> <li>В случаях, когда подрост является относительно незначительным компонентом пула углерода в надпочвенной биомассе, его допустимо исключить при условии, что это будет осуществляться последовательно в ходе инвентаризаций в отчетные годы.</li> </ol> <p><strong><em>ОХРАНЯЕМЫЕ ТЕРРИТОРИИ</em></strong></p> <p>Территории, специально предназначенные для защиты и поддержания биологического разнообразия, природных и связанных с ними культурных ресурсов и управляемые законными или другими эффективными способами.</p> <p><strong><em>ЛЕСНЫЕ ПЛОЩАДИ НА ЗАКОННО УСТАНОВЛЕННЫХ ОХРАНЯЕМЫХ ТЕРРИТОРИЯХ</em></strong></p> <p>Лесная площадь на официально созданных охраняемых территориях, независимо от цели, с которой были образованы охраняемые территории. </p> <p><u>Пояснительные примечания</u></p> <ol> <li>Включает категории МСОП I – IV</li> <li>Исключает категории МСОП V – VI</li> </ol> <p><strong><em>ЛЕСНАЯ ПЛОЩАДЬ С ДОЛГОСРОЧНЫМ ПЛАНОМ УПРАВЛЕНИЯ ЛЕСАМИ</em></strong></p> <p>Лесная площадь, имеющая долгосрочный документированный план управления лесами, направленный на достижение определенных целей управления, и периодически пересматривающийся.</p> <p><u>Пояснительные примечания</u></p> <ol> <li>Лесная площадь с планом управления лесами может означать уровень лесоустроительного подразделения или агрегированный уровень лесоустроительного подразделения (лесные участки, фермы, предприятия, водосборные бассейны, муниципальные образования или более крупные участки).</li> <li>План управления лесами может включать подробную информацию об операциях, запланированных для отдельных эксплуатационных единиц (насаждений или кварталов), но он также может ограничиваться предоставлением общих стратегий и мероприятий, запланированных для достижения целей в области управления лесами.</li> <li>Включает лесную площадь на охраняемых территориях с планом управления лесами.</li> </ol> <p><strong><em>СИСТЕМА СЕРТИФИКАЦИИ ИСПОЛЬЗОВАНИЯ ЛЕСОВ, ПРОШЕДШАЯ НЕЗАВИСИМУЮ ПРОВЕРКУ</em></strong></p> <p>Лесные территории, сертифицированные по схеме сертификации управления лесами с опубликованными стандартами и прошедшие независимую проверку третьей стороной.</p> <h1>Приложение 2 Методология</h1> <p><strong><em>Субпоказатель 1 - Темп годового чистого изменения площади лесов</em></strong></p> <p><u>Единица измерения</u>: Процент</p> <p><u>Отчетный период:</u> Самый последний период</p> <p><u>Метод оценки:</u> Формула сложных процентов</p> <p><u>Перевод на инструментальную панель / световые сигналы:</u></p> <p>Следующая блок-схема объясняет логику перевода этого показателя на инструментальную панель / световые сигналы:</p> <p><img src="data:image/png;base64,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"></p> <p>Направление изменения площади лесов определяется путем изучения значения скорости изменения площади лесов за последний период, отрицательное значение указывает на потерю площади лесов, нулевое значение означает, что площадь лесов стабильна, а положительное значение означает, что площадь лесов возросла. Изменение скорости потери площади лесов основано на сравнении текущей скорости чистого изменения площади лесов с базовой скоростью чистого изменения площади лесов за период 2010-2015 гг.</u></p> <p><u>Комментарии:</u></p> <p>Этот световой сигнал учитывает как направление изменения площади лесов (если площадь лесов увеличивается или уменьшается), так и изменения скорости потери площади лесов; последнее важно для определения прогресса среди стран, которые теряют площади лесов, но сумели снизить скорость потерь.</p> <p>Для годовой отчетности ФАО может предоставлять странам условно исчисленные значения на основе предыдущих тенденций, которые они могут использовать в случае, если у них нет новой / обновленной информации. Базовый уровень должен обновляться каждые 5 лет, поэтому в 2020 году рассчитывается новый базовый уровень. Кроме того, на страновом уровне, если страна получает новую информацию и обновляет исторические временные ряды, базовый уровень для страны будет пересчитан с учетом периода 2010-2015 гг.</p> <p><strong><em>Субпоказатель 2 – Запасы наземной лесной биомассы</em></strong></p> <p><u>Единица измерения</u>: тонна/гектар</p> <p><u>Отчетный период:</u> Самый последний период</p> <p><u>Метод оценки:</u> Запас лесной биомассы (в тоннах) / лесная территория (в гектарах)</p> <p><u>Перевод на инструментальную панель / световые сигналы:</u></p> <p>Значение показателя за последний отчетный год сравнивается со значением показателя за предыдущий отчетный год для оценки непрерывности прогресса с момента последнего отчета.</p> <p>Рассчитывается соотношение (r) между текущим значением показателя и ранее отраженным значением; r & gt; 1 означает увеличение запасов на гектар, r & lt; 1 означает уменьшение, а 1 означает отсутствие изменений. Был установлен узкий интервал для r, чтобы указать стабильное состояние, и цвета светового сигнала обозначаются следующим образом:</p> <p><img src="data:image/png;base64,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"></p> <p><strong><em>Субпоказатель 3 –Доля лесных площадей, расположенных в пределах установленных законом охраняемых территорий</em></strong></p> <p><u>Единица измерения</u>: Процент</p> <p><u>Отчетный период:</u> Самый последний период</p> <p><u>Метод оценки:</u> Доля лесных площадей, расположенных в пределах установленных законом охраняемых территорий / Лесная площадь в 2015 году * 100</p> <p><u>Перевод на инструментальную панель / световые сигналы:</u></p> <p>Значение показателя за последний отчетный год сравнивается со значением показателя за предыдущий отчетный год для оценки непрерывности прогресса с момента последнего отчета.</p> <p>Рассчитывается соотношение (r) между текущим значением показателя и ранее отраженным значением; r & gt; 1 означает увеличение запасов на гектар, r & lt; 1 означает уменьшение, а 1 означает отсутствие изменений. Был установлен узкий интервал для r, чтобы указать стабильное состояние, и цвета светового сигнала обозначаются следующим образом:</p> <p><img src="data:image/png;base64,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"></p> <p><u>Комментарий:</u></p> <p>Использование площади лесов в 2015 году в качестве знаменателя для оценки этого показателя гарантирует, что временной ряд в процентах отражает реальные изменения площади лесов в пределах установленных законом охраняемых территорий и не зависит от изменений (потерь или прибылей) в общей площади лесов.</p> <p><strong><em>Субпоказатель 4 – Доля лесных площадей, имеющих долгосрочный план управления лесами.</em></strong></p> <p><u>Единица измерения</u>: Процент</p> <p><u>Отчетный период:</u> Самый последний период</p> <p><u>Метод оценки:</u> Лесные площади, имеющие долгосрочный план управления лесами / Лесная площадь в 2015 году * 100</p> <p><u>Перевод на инструментальную панель / световые сигналы: </u>Значение показателя за последний отчетный год сравнивается со значением показателя за предыдущий отчетный год для оценки непрерывности прогресса с момента последнего отчета.</p> <p>Рассчитывается соотношение (r) между текущим значением показателя и ранее отраженным значением; r & gt; 1 означает увеличение запасов на гектар, r & lt; 1 означает уменьшение, а 1 означает отсутствие изменений. Был установлен узкий интервал для r, чтобы указать стабильное состояние, и цвета светового сигнала обозначаются следующим образом:</p> <p><img src="data:image/png;base64,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"></p> <p><u>Комментарий:</u></p> <p>Использование площади лесов в 2015 году в качестве знаменателя для оценки этого показателя гарантирует, что временной ряд в процентах отражает реальные изменения площади лесов, имеющих долгосрочный план управления лесами, и не зависит от изменений (потерь или прибылей) в общей площади лесов. </p> <p><strong><em>Субпоказатель 5 – Площадь лесов, на которых действует система сертификации использования лесов, прошедшая независимую проверку.</em></strong></p> <p><u>Единица измерения</u>: Тысяч гектаров</p> <p><u>Отчетный период:</u> Самый последний период (по состоянию на 30 июня)</p> <p><u>Метод оценки:</u> Данные собираются непосредственно из баз данных каждой системы сертификации и предоставляются странам для проверки.</p> <p><u>Перевод на инструментальную панель / световые сигналы: </u>Значение показателя за последний отчетный год сравнивается со значением показателя за предыдущий отчетный год для оценки непрерывности прогресса с момента последнего отчета.</p> <p>Рассчитывается соотношение (r) между текущим значением показателя и ранее отраженным значением; r & gt; 1 означает увеличение запасов на гектар, r & lt; 1 означает уменьшение, а 1 означает отсутствие изменений. Был установлен узкий интервал для r, чтобы указать стабильное состояние, и цвета светового сигнала обозначаются следующим образом:</p> <p><img src="data:image/png;base64,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"> </p> <p><u>Комментарии:</u></p> <p>Использование 30 июня в качестве отчетной даты позволяет органам по сертификации обновлять свои базы данных, чтобы они могли предоставлять информацию в ФАО к концу года, а затем включать ее в годовую отчетность для ЦУР в начале следующего года.</p><div class="footnotes"><div><sup class="footnote-number" id="footnote-1">1</sup><p> Глобальная оценка лесных ресурсов 2015 г. – Обозначения и определения <a href="http://www.fao.org/docrep/017/ap862e:/www.fo.org/docrep/017/ap862e/ap862e00.pdf</a> <a href="#footnote-ref-1">↑</a></p></div></div> |
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<p><strong>URL: </strong><a href="http://www.fao.org/forest-resources-assessment/en/"><u>http://www.fao.org/forest-resources-assessment/en/</u></a> </p>
<p><strong>References:</strong></p> <p>Global Forest Resources Assessment 2020, Guidelines and Specifications (<a href="http://www.fao.org/3/I8699EN/i8699en.pdf"><u>www.fao.org/3/I8699EN/i8699en.pdf</u></a>)</p> <p>Global Forest Resources Assessment 2020, Terms and Definitions (<a href="http://www.fao.org/3/I8661EN/i8661en.pdf"><u>www.fao.org/3/I8661EN/i8661en.pdf</u></a>).</p> <p>United Nations. Resolution adopted by the General Assembly on 17 December 2007 (<a href="https://undocs.org/en/A/RES/62/98">https://undocs.org/en/A/RES/62/98</a>). </p> <p><strong>Annex 1 – Terms and Definitions </strong></p> <p><strong>FOREST</strong></p> <p>Land spanning more than 0.5 hectares with <u>tree</u>s higher than 5 meters and a <u>canopy cover</u> of more than 10 percent, or trees able to reach these thresholds <em>in situ</em>. It does not include land that is predominantly under agricultural or urban land use. </p> <p><u>Explanatory notes</u></p> <ol> <li>Forest is determined both by the presence of trees and the absence of other predominant land uses. The trees should be able to reach a minimum height of 5 meters. </li> <li>Includes areas with young trees that have not yet reached but which are expected to reach a canopy cover of at least 10 percent and tree height of 5 meters or more. It also includes areas that are temporarily unstocked due to clear-cutting as part of a forest management practice or natural disasters, and which are expected to be regenerated within 5 years. Local conditions may, in exceptional cases, justify that a longer time frame is used.</li> <li>Includes forest roads, firebreaks and other small open areas; forest in national parks, nature reserves and other protected areas such as those of specific environmental, scientific, historical, cultural or spiritual interest.</li> <li>Includes windbreaks, shelterbelts and corridors of trees with an area of more than 0.5 hectares and width of more than 20 meters.</li> <li>Includes abandoned shifting cultivation land with a regeneration of trees that have, or are expected to reach, a canopy cover of at least 10 percent and tree height of at least 5 meters.</li> <li>Includes areas with mangroves in tidal zones, regardless whether this area is classified as land area or not.</li> <li>Includes rubberwood, cork oak and Christmas tree plantations. </li> <li>Includes areas with bamboo and palms provided that land use, height and canopy cover criteria are met.</li> <li><u>Excludes</u> tree stands in agricultural production systems, such as fruit tree plantations, oil palm plantations, olive orchards and agroforestry systems when crops are grown under tree cover. <u>Note:</u> Some agroforestry systems such as the “Taungya” system where crops are grown only during the first years of the forest rotation should be classified as forest.</li> </ol> <p><strong>ABOVE-GROUND BIOMASS</strong></p> <p>All living biomass above the soil including stem, stump, branches, bark, seeds, and foliage.</p> <p><u>Explanatory note </u></p> <ol> <li>In cases where forest understorey is a relatively small component of the aboveground biomass carbon pool, it is acceptable to exclude it, provided this is done in a consistent manner throughout the inventory time series.</li> </ol> <p><strong>PROTECTED AREAS</strong></p> <p>Areas especially dedicated to the protection and maintenance of biological diversity, and of natural and associated cultural resources, and managed through legal or other effective means.</p> <p><strong>FOREST AREA WITHIN PROTECTED AREAS</strong></p> <p>Forest area within formally established protected areas independently of the purpose for which the protected areas were established. </p> <p><u>Explanatory notes</u></p> <ol> <li>Includes IUCN Categories I – IV</li> <li><u>Excludes</u> IUCN Categories V-VI</li> </ol> <p><strong>FOREST AREA WITH MANAGEMENT PLAN</strong></p> <p>Forest area that has a long-term documented management plan, aiming at defined management goals, which is periodically revised. </p> <p><u>Explanatory notes</u></p> <ol> <li>A forest area with management plan may refer to forest management unit level or aggregated forest management unit level (forest blocks, farms, enterprises, watersheds, municipalities, or wider units).</li> <li>A management plan must include adequate detail on operations planned for individual operational units (stands or compartments) but may also provide general strategies and activities planned to reach management goals.</li> <li>Includes forest area in protected areas with management plan.</li> </ol> <p><strong>INDEPENDENTLY VERIFIED FOREST MANAGEMENT CERTIFICATION</strong></p> <p>Forest area certified under a forest management certification scheme with published standards and is independently verified by a third-party.</p> <p><strong>Annex 2 – Methodology</strong></p> <p><strong>Sub-indicator 1 - Annual forest area change rate</strong></p> <p><u>Unit</u>: Percent</p> <p><u>Reference period:</u> 2010-2020</p> <p><u>Method of estimation:</u> Compound annual change rate formula as follows:</p> <p><math xmlns="http://www.w3.org/1998/Math/MathML"> <mi>r</mi> <mo>=</mo> <mfenced open="[" close="]" separators="|"> <mrow> <msup> <mrow> <mfenced separators="|"> <mrow> <mfrac> <mrow> <msub> <mrow> <mi>A</mi> <mi>F</mi> </mrow> <mrow> <mi>t</mi> <mn>2</mn> </mrow> </msub> </mrow> <mrow> <msub> <mrow> <mi>A</mi> <mi>F</mi> </mrow> <mrow> <mi>t</mi> <mn>1</mn> </mrow> </msub> </mrow> </mfrac> </mrow> </mfenced> </mrow> <mrow> <mfrac bevelled="true"> <mrow> <mn>1</mn> </mrow> <mrow> <mfenced separators="|"> <mrow> <mi>t</mi> <mn>2</mn> <mo>-</mo> <mi>t</mi> <mn>1</mn> </mrow> </mfenced> </mrow> </mfrac> </mrow> </msup> <mo>-</mo> <mn>1</mn> </mrow> </mfenced> <mo>×</mo> <mn>100</mn> </math></p> <p>where: </p> <p><em>r</em> = compound annual change rate for the period <em>t<sub>1 - </sub>t<sub>2</sub></em><sub> </sub></p> <p><em>t<sub>i</sub></em> = time i (year)</p> <p><em>AF<sub>t1</sub></em> = forest area at <em>t<sub>1</sub></em> </p> <p><em>AF<sub>t2</sub></em> = forest area at <em>t<sub>2</sub></em></p> <p><u>Translation to dashboard/traffic light:</u></p> <p>The following flowchart explains the logic behind the translation of this indicator to a dashboard/traffic light:</p> <p>Forest area change direction</p> <p>Forest area stable </p> <p>or increasing</p> <p>Forest area decreasing</p> <p>Change in forest area loss rate </p> <p>Loss rate</p> <p>decreasing</p> <p>Loss rate stable</p> <p>or increasing</p> <p>The forest area change direction is determined by examining the value of the forest area change rate for the most recent period, a negative value indicate a loss of forest area, a zero value means that forest area is stable, and a positive value means that forest area has increased. The change in forest area loss rate<sup><a href="#footnote-2" id="footnote-ref-2">[1]</a></sup> is based on a comparison of the annual forest area change rate for the period 2010-2020 with the annual <u>forest area change rate for the period 2000-2010 </u>(<u>baseline).</u></p> <p><u>Comments:</u></p> <p>This traffic light takes into consideration both the direction of forest area change (if forest area increases or decreases) as well as changes in the rate of forest area loss – the latter important in order to indicate progress among countries that are losing forest area but manage to reduce the loss rate. </p> <p>The baseline should be updated every 5 years. In 2020 a new baseline was calculated for the period 2000-2010 based on updated country data. </p> <p><strong>Sub-indicator 2 – Above-ground biomass in forest </strong></p> <p><u>Unit</u>: tonnes/hectare</p> <p><u>Reference year:</u> Latest reporting year</p> <p><u>Method of estimation:</u> Reported directly by countries</p> <p><u>Translation to dashboard/traffic light:</u></p> <p>The indicator value for the latest reporting year is compared with the indicator value reported for 2010.</p> <p>The ratio (r) between the current indicator value and the value reported for 2010 is calculated; r>1 means an increase in stock per hectare, r<1 means a decrease while 1 indicates no change. A narrow interval for r has been established to indicate a stable condition, and traffic-light colors are assigned as follows:</p> <p> r ≥ 1.01 </p> <p> 0.99 < r < 1.01</p> <p> r ≤ 0.99</p> <p><strong>Sub-indicator 3 – Proportion of forest area within legally established protected areas.</strong></p> <p><u>Unit</u>: Percent</p> <p><u>Reference year:</u> Latest reporting year</p> <p><u>Method of estimation:</u> </p> <p><math xmlns="http://www.w3.org/1998/Math/MathML"> <mi>r</mi> <mo>=</mo> <mi>&nbsp;</mi> <mfrac> <mrow> <msub> <mrow> <mi>A</mi> <mi>F</mi> <mi>P</mi> </mrow> <mrow> <mfenced open="[" close="]" separators="|"> <mrow> <mi>r</mi> <mi>e</mi> <mi>f</mi> <mi>e</mi> <mi>r</mi> <mi>e</mi> <mi>n</mi> <mi>c</mi> <mi>e</mi> <mi>&nbsp;</mi> <mi>y</mi> <mi>e</mi> <mi>a</mi> <mi>r</mi> </mrow> </mfenced> </mrow> </msub> </mrow> <mrow> <msub> <mrow> <mi>A</mi> <mi>F</mi> </mrow> <mrow> <mn>2015</mn> </mrow> </msub> </mrow> </mfrac> <mo>×</mo> <mn>100</mn> </math></p> <p>Where:</p> <p><em>AFP</em> = Forest area within legally established protected areas</p> <p><em>AF</em> = Total forest area</p> <p><u>Translation to dashboard/traffic light:</u></p> <p>The indicator value for latest reporting year is compared with the indicator value reported for 2010.</p> <p>The ratio (r) between the current indicator value and the value reported for 2010 is calculated; r>1 means an increase in forest area within protected areas, r<1 means a decrease while 1 indicates no change. A narrow interval for r has been established to indicate a stable condition, and traffic-light colors are assigned as follows:</p> <p> r ≥ 1.01 </p> <p> 0.99 < r < 1.01</p> <p> r ≤ 0.99</p> <p><u>Comment:</u></p> <p>Using forest area in 2015 as denominator for estimating this indicator ensures that the time series of percentages reflect real changes in the forest area within legally established protected areas and is not affected by changes (losses or gains) in total forest area. </p> <p><strong>Sub-indicator 4 – Proportion of forest area under a long-term management plan.</strong></p> <p><u>Unit</u>: Percent</p> <p><u>Reference year:</u> Latest reporting year</p> <p><u>Method of estimation:</u> </p> <p><math xmlns="http://www.w3.org/1998/Math/MathML"> <mi>r</mi> <mo>=</mo> <mi>&nbsp;</mi> <mfrac> <mrow> <msub> <mrow> <mi>A</mi> <mi>F</mi> <mi>M</mi> <mi>P</mi> </mrow> <mrow> <mfenced open="[" close="]" separators="|"> <mrow> <mi>r</mi> <mi>e</mi> <mi>f</mi> <mi>e</mi> <mi>r</mi> <mi>e</mi> <mi>n</mi> <mi>c</mi> <mi>e</mi> <mi>&nbsp;</mi> <mi>y</mi> <mi>e</mi> <mi>a</mi> <mi>r</mi> </mrow> </mfenced> </mrow> </msub> </mrow> <mrow> <msub> <mrow> <mi>A</mi> <mi>F</mi> </mrow> <mrow> <mn>2015</mn> </mrow> </msub> </mrow> </mfrac> <mo>×</mo> <mn>100</mn> </math></p> <p>Where:</p> <p><em>AFMP</em> = Forest area under a long-term management plan</p> <p><em>AF</em> = Total forest area</p> <p><u>Translation to dashboard/traffic light: </u>The indicator value for latest reporting year is compared with the indicator value reported for 2010.</p> <p>The ratio (r) between the current indicator value and the value reported for 2010 is calculated; r>1 means an increase in areas under management plan, r<1 means a decrease while 1 indicates no change. A narrow interval for r has been established to indicate a stable condition, and traffic-light colors are assigned as follows:</p> <p> r ≥ 1.01 </p> <p> 0.99 < r < 1.01</p> <p> r ≤ 0.99</p> <p><u>Comment:</u></p> <p>Using forest area in 2015 as denominator for estimating this indicator ensures that the time series of percentages reflect real changes in the forest area under management plan and is not affected by changes (losses or gains) in total forest area. </p> <p><strong>Sub-indicator 5 – Forest area under an independently verified forest management certification scheme.</strong></p> <p><u>Unit</u>: Thousand hectares</p> <p><u>Reference year:</u> Latest reporting year (as of June 30)</p> <p><u>Method of estimation:</u> Data is collected directly from the databases of each certification scheme and provided to countries for validation.</p> <p><u>Translation to dashboard/traffic light: </u>The indicator value for latest reporting year is compared with the indicator value for previous reporting year for assessment of continuity of progress since last report.</p> <p>The ratio (r) between the current indicator value and the previously reported value is calculated; r>1 means an increase in areas under an independent forest management certification scheme, r<1 means a decrease while 1 indicates no change. A small interval for r has been established to indicate a stable condition, and traffic-light colors are assigned as follows:</p> <p> r ≥ 1.01 </p> <p> 0.99 < r < 1.01</p> <p> r ≤ 0.99</p> <p><u>Comments:</u></p> <p>Using June 30 as the date for reporting, allows for the certification bodies to have their databases updated so they can provide information to FAO by end of the year, and then be included in the annual reporting to SDG in the beginning of the following year.</p><div class="footnotes"><div><sup class="footnote-number" id="footnote-2">1</sup><p> If forest area change rate is negative (= forest loss) then: annual forest area loss rate = <strong>-</strong> (annual forest area change rate) <a href="#footnote-ref-2">↑</a></p></div></div>
<h1>Ссылки </h1>
<h2>URL: </h2> <p><a href="http://www.fao.org/forest-resources-assessment/en/">http://www.fao.org/forest-resources-assessment/en/</a> </p> <h2>Рекомендации:</h2> <p><a href="http://www.fao.org/forest-resources-assessment/current-assessment/en/">http://www.fao.org/forest-resources-assessment/current-assessment/en/</a></p> <h1>Приложение 1 Обозначения и определения<sup><a href="#footnote-1" id="footnote-ref-1">[1]</a></sup></h1> <p><strong><em>ЛЕС</em></strong></p> <p>Участок земли площадью более 0,5 гектара, на котором растут деревья высотой более пяти метров с сомкнутостью крон более десяти процентов, или деревья, способные на данном участке достичь этих пороговых значений. Не включаются земли, которые используются преимущественно для целей сельского хозяйства или поселений<strong>. </strong></p> <p><u>Пояснительные примечания</u></p> <ol> <li>Лес определяется как наличием деревьев, так и отсутствием других преобладающих видов землепользования. Деревья должны быть способны достигать минимальной высоты 5 м. </li> <li>Сюда входят участки с молодыми деревьями, с сомкнутостью крон еще не достигшей, но которая, как ожидается, достигнет 10 %, а деревья – высоты 5 метров. Он также включает участки, которые являются временно обезлесенными из-за сплошных рубок в рамках практики ведения лесного хозяйства или из-за стихийных бедствий, но которые, как ожидается, будут восстановлены в течение 5 лет. В исключительных случаях, с учетом местных условий, могут устанавливаться более продолжительные временные сроки.</li> <li>Лес включает лесные дороги, противопожарные полосы и другие небольшие открытые пространства, леса в национальных парках, природных заповедниках и на других охраняемых территориях, представляющих особый экологический, научный, исторический, культурный или духовный интерес.</li> <li>Лес включает ветрозащитные полосы, лесозащитные полосы и полосы деревьев площадью более 0,5 га и шириной более 20 м.</li> <li>Сюда входят заброшенные земли со сменной культивацией, где производится восстановление лесонасаждений, которые имеют или, как ожидается, будут иметь сомкнутость крон 10 %, а деревья – высоту 5 метров.</li> <li>Лес включает площади, занятые мангровыми лесами в приливных зонах, независимо от того, классифицируются ли эти площади в качестве земельных площадей.</li> <li>Лес включает плантации каучуковых деревьев, пробкового дуба и рождественских елок. </li> <liСюда входят площади, занятые бамбуковыми и пальмовыми лесами при условии, что землепользование, высота деревьев и сомкнутость крон соответствуют установленным критериям.</li> <li>Лес не включает древесные насаждения, вовлеченные в сельскохозяйственное производство, такие как плантации плодовых деревьев, плантации масличной пальмы, оливковые рощи и агролесоводственные системы, при которых сельскохозяйственные культуры выращиваются под кронами деревьев. <u>Примечание:</u>Площади, включенные в некоторые агролесоводственные системы, такие как система Taungya, при которых сельскохозяйственные культуры выращиваются только в первые годы оборота лесного хозяйства, должны рассматриваться как лес.</li> </ol> <p><strong><em>НАДПОЧВЕННАЯ БИОМАССА</em></strong></p> <p>Вся биомасса живого растительного покрова, как древесного, так и травянистого, включая стволы, пни, ветви, кору, семена и листву.</p> <p><u>Пояснительные примечания </u></p> <ol> <li>В случаях, когда подрост является относительно незначительным компонентом пула углерода в надпочвенной биомассе, его допустимо исключить при условии, что это будет осуществляться последовательно в ходе инвентаризаций в отчетные годы.</li> </ol> <p><strong><em>ОХРАНЯЕМЫЕ ТЕРРИТОРИИ</em></strong></p> <p>Территории, специально предназначенные для защиты и поддержания биологического разнообразия, природных и связанных с ними культурных ресурсов и управляемые законными или другими эффективными способами.</p> <p><strong><em>ЛЕСНЫЕ ПЛОЩАДИ НА ЗАКОННО УСТАНОВЛЕННЫХ ОХРАНЯЕМЫХ ТЕРРИТОРИЯХ</em></strong></p> <p>Лесная площадь на официально созданных охраняемых территориях, независимо от цели, с которой были образованы охраняемые территории. </p> <p><u>Пояснительные примечания</u></p> <ol> <li>Включает категории МСОП I – IV</li> <li>Исключает категории МСОП V – VI</li> </ol> <p><strong><em>ЛЕСНАЯ ПЛОЩАДЬ С ДОЛГОСРОЧНЫМ ПЛАНОМ УПРАВЛЕНИЯ ЛЕСАМИ</em></strong></p> <p>Лесная площадь, имеющая долгосрочный документированный план управления лесами, направленный на достижение определенных целей управления, и периодически пересматривающийся.</p> <p><u>Пояснительные примечания</u></p> <ol> <li>Лесная площадь с планом управления лесами может означать уровень лесоустроительного подразделения или агрегированный уровень лесоустроительного подразделения (лесные участки, фермы, предприятия, водосборные бассейны, муниципальные образования или более крупные участки).</li> <li>План управления лесами может включать подробную информацию об операциях, запланированных для отдельных эксплуатационных единиц (насаждений или кварталов), но он также может ограничиваться предоставлением общих стратегий и мероприятий, запланированных для достижения целей в области управления лесами.</li> <li>Включает лесную площадь на охраняемых территориях с планом управления лесами.</li> </ol> <p><strong><em>СИСТЕМА СЕРТИФИКАЦИИ ИСПОЛЬЗОВАНИЯ ЛЕСОВ, ПРОШЕДШАЯ НЕЗАВИСИМУЮ ПРОВЕРКУ</em></strong></p> <p>Лесные территории, сертифицированные по схеме сертификации управления лесами с опубликованными стандартами и прошедшие независимую проверку третьей стороной.</p> <h1>Приложение 2 Методология</h1> <p><strong><em>Субпоказатель 1 - Темп годового чистого изменения площади лесов</em></strong></p> <p><u>Единица измерения</u>: Процент</p> <p><u>Отчетный период:</u> Самый последний период</p> <p><u>Метод оценки:</u> Формула сложных процентов</p> <p><u>Перевод на инструментальную панель / световые сигналы:</u></p> <p>Следующая блок-схема объясняет логику перевода этого показателя на инструментальную панель / световые сигналы:</p> <p><img src="data:image/png;base64,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"></p> <p>Направление изменения площади лесов определяется путем изучения значения скорости изменения площади лесов за последний период, отрицательное значение указывает на потерю площади лесов, нулевое значение означает, что площадь лесов стабильна, а положительное значение означает, что площадь лесов возросла. Изменение скорости потери площади лесов основано на сравнении текущей скорости чистого изменения площади лесов с базовой скоростью чистого изменения площади лесов за период 2010-2015 гг.</u></p> <p><u>Комментарии:</u></p> <p>Этот световой сигнал учитывает как направление изменения площади лесов (если площадь лесов увеличивается или уменьшается), так и изменения скорости потери площади лесов; последнее важно для определения прогресса среди стран, которые теряют площади лесов, но сумели снизить скорость потерь.</p> <p>Для годовой отчетности ФАО может предоставлять странам условно исчисленные значения на основе предыдущих тенденций, которые они могут использовать в случае, если у них нет новой / обновленной информации. Базовый уровень должен обновляться каждые 5 лет, поэтому в 2020 году рассчитывается новый базовый уровень. Кроме того, на страновом уровне, если страна получает новую информацию и обновляет исторические временные ряды, базовый уровень для страны будет пересчитан с учетом периода 2010-2015 гг.</p> <p><strong><em>Субпоказатель 2 – Запасы наземной лесной биомассы</em></strong></p> <p><u>Единица измерения</u>: тонна/гектар</p> <p><u>Отчетный период:</u> Самый последний период</p> <p><u>Метод оценки:</u> Запас лесной биомассы (в тоннах) / лесная территория (в гектарах)</p> <p><u>Перевод на инструментальную панель / световые сигналы:</u></p> <p>Значение показателя за последний отчетный год сравнивается со значением показателя за предыдущий отчетный год для оценки непрерывности прогресса с момента последнего отчета.</p> <p>Рассчитывается соотношение (r) между текущим значением показателя и ранее отраженным значением; r & gt; 1 означает увеличение запасов на гектар, r & lt; 1 означает уменьшение, а 1 означает отсутствие изменений. Был установлен узкий интервал для r, чтобы указать стабильное состояние, и цвета светового сигнала обозначаются следующим образом:</p> <p><img src="data:image/png;base64,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"></p> <p><strong><em>Субпоказатель 3 –Доля лесных площадей, расположенных в пределах установленных законом охраняемых территорий</em></strong></p> <p><u>Единица измерения</u>: Процент</p> <p><u>Отчетный период:</u> Самый последний период</p> <p><u>Метод оценки:</u> Доля лесных площадей, расположенных в пределах установленных законом охраняемых территорий / Лесная площадь в 2015 году * 100</p> <p><u>Перевод на инструментальную панель / световые сигналы:</u></p> <p>Значение показателя за последний отчетный год сравнивается со значением показателя за предыдущий отчетный год для оценки непрерывности прогресса с момента последнего отчета.</p> <p>Рассчитывается соотношение (r) между текущим значением показателя и ранее отраженным значением; r & gt; 1 означает увеличение запасов на гектар, r & lt; 1 означает уменьшение, а 1 означает отсутствие изменений. Был установлен узкий интервал для r, чтобы указать стабильное состояние, и цвета светового сигнала обозначаются следующим образом:</p> <p><img src="data:image/png;base64,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"></p> <p><u>Комментарий:</u></p> <p>Использование площади лесов в 2015 году в качестве знаменателя для оценки этого показателя гарантирует, что временной ряд в процентах отражает реальные изменения площади лесов в пределах установленных законом охраняемых территорий и не зависит от изменений (потерь или прибылей) в общей площади лесов.</p> <p><strong><em>Субпоказатель 4 – Доля лесных площадей, имеющих долгосрочный план управления лесами.</em></strong></p> <p><u>Единица измерения</u>: Процент</p> <p><u>Отчетный период:</u> Самый последний период</p> <p><u>Метод оценки:</u> Лесные площади, имеющие долгосрочный план управления лесами / Лесная площадь в 2015 году * 100</p> <p><u>Перевод на инструментальную панель / световые сигналы: </u>Значение показателя за последний отчетный год сравнивается со значением показателя за предыдущий отчетный год для оценки непрерывности прогресса с момента последнего отчета.</p> <p>Рассчитывается соотношение (r) между текущим значением показателя и ранее отраженным значением; r & gt; 1 означает увеличение запасов на гектар, r & lt; 1 означает уменьшение, а 1 означает отсутствие изменений. Был установлен узкий интервал для r, чтобы указать стабильное состояние, и цвета светового сигнала обозначаются следующим образом:</p> <p><img src="data:image/png;base64,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"></p> <p><u>Комментарий:</u></p> <p>Использование площади лесов в 2015 году в качестве знаменателя для оценки этого показателя гарантирует, что временной ряд в процентах отражает реальные изменения площади лесов, имеющих долгосрочный план управления лесами, и не зависит от изменений (потерь или прибылей) в общей площади лесов. </p> <p><strong><em>Субпоказатель 5 – Площадь лесов, на которых действует система сертификации использования лесов, прошедшая независимую проверку.</em></strong></p> <p><u>Единица измерения</u>: Тысяч гектаров</p> <p><u>Отчетный период:</u> Самый последний период (по состоянию на 30 июня)</p> <p><u>Метод оценки:</u> Данные собираются непосредственно из баз данных каждой системы сертификации и предоставляются странам для проверки.</p> <p><u>Перевод на инструментальную панель / световые сигналы: </u>Значение показателя за последний отчетный год сравнивается со значением показателя за предыдущий отчетный год для оценки непрерывности прогресса с момента последнего отчета.</p> <p>Рассчитывается соотношение (r) между текущим значением показателя и ранее отраженным значением; r & gt; 1 означает увеличение запасов на гектар, r & lt; 1 означает уменьшение, а 1 означает отсутствие изменений. Был установлен узкий интервал для r, чтобы указать стабильное состояние, и цвета светового сигнала обозначаются следующим образом:</p> <p><img src="data:image/png;base64,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"> </p> <p><u>Комментарии:</u></p> <p>Использование 30 июня в качестве отчетной даты позволяет органам по сертификации обновлять свои базы данных, чтобы они могли предоставлять информацию в ФАО к концу года, а затем включать ее в годовую отчетность для ЦУР в начале следующего года.</p><div class="footnotes"><div><sup class="footnote-number" id="footnote-1">1</sup><p> Глобальная оценка лесных ресурсов 2015 г. – Обозначения и определения <a href="http://www.fao.org/docrep/017/ap862e:/www.fo.org/docrep/017/ap862e/ap862e00.pdf</a> <a href="#footnote-ref-1">↑</a></p></div></div> |
Things to check
English | Russian | ||
---|---|---|---|
Indicator | Показатель | SDG Metadata | |
Number | Количество | SDG Metadata | |
Number | Количество | SDG Metadata | |
Time series | Временные ряды | SDG Metadata | |
Time series | Временные ряды | SDG Metadata |
Key
OTHER_DOCFlags
ignore-inconsistent
<p><strong>References:</strong></p>
<p>Global Forest Resources Assessment 2020, Guidelines and Specifications (<a href="http://www.fao.org/3/I8699EN/i8699en.pdf"><u>www.fao.org/3/I8699EN/i8699en.pdf</u></a>)</p>
<p>Global Forest Resources Assessment 2020, Terms and Definitions (<a href="http://www.fao.org/3/I8661EN/i8661en.pdf"><u>www.fao.org/3/I8661EN/i8661en.pdf</u></a>).</p>
<p>United Nations. Resolution adopted by the General Assembly on 17 December 2007 (<a href="https://undocs.org/en/A/RES/62/98">https://undocs.org/en/A/RES/62/98</a>). </p>
<p><strong>Annex 1 – Terms and Definitions </strong></p>
<p><strong>FOREST</strong></p>
<p>Land spanning more than 0.5 hectares with <u>tree</u>s higher than 5 meters and a <u>canopy cover</u> of more than 10 percent, or trees able to reach these thresholds <em>in situ</em>. It does not include land that is predominantly under agricultural or urban land use. </p>
<p><u>Explanatory notes</u></p>
<ol>
<li>Forest is determined both by the presence of trees and the absence of other predominant land uses. The trees should be able to reach a minimum height of 5 meters. </li>
<li>Includes areas with young trees that have not yet reached but which are expected to reach a canopy cover of at least 10 percent and tree height of 5 meters or more. It also includes areas that are temporarily unstocked due to clear-cutting as part of a forest management practice or natural disasters, and which are expected to be regenerated within 5 years. Local conditions may, in exceptional cases, justify that a longer time frame is used.</li>
<li>Includes forest roads, firebreaks and other small open areas; forest in national parks, nature reserves and other protected areas such as those of specific environmental, scientific, historical, cultural or spiritual interest.</li>
<li>Includes windbreaks, shelterbelts and corridors of trees with an area of more than 0.5 hectares and width of more than 20 meters.</li>
<li>Includes abandoned shifting cultivation land with a regeneration of trees that have, or are expected to reach, a canopy cover of at least 10 percent and tree height of at least 5 meters.</li>
<li>Includes areas with mangroves in tidal zones, regardless whether this area is classified as land area or not.</li>
<li>Includes rubberwood, cork oak and Christmas tree plantations. </li>
<li>Includes areas with bamboo and palms provided that land use, height and canopy cover criteria are met.</li>
<li><u>Excludes</u> tree stands in agricultural production systems, such as fruit tree plantations, oil palm plantations, olive orchards and agroforestry systems when crops are grown under tree cover. <u>Note:</u> Some agroforestry systems such as the “Taungya” system where crops are grown only during the first years of the forest rotation should be classified as forest.</li>
</ol>
<p><strong>ABOVE-GROUND BIOMASS</strong></p>
<p>All living biomass above the soil including stem, stump, branches, bark, seeds, and foliage.</p>
<p><u>Explanatory note </u></p>
<ol>
<li>In cases where forest understorey is a relatively small component of the aboveground biomass carbon pool, it is acceptable to exclude it, provided this is done in a consistent manner throughout the inventory time series.</li>
</ol>
<p><strong>PROTECTED AREAS</strong></p>
<p>Areas especially dedicated to the protection and maintenance of biological diversity, and of natural and associated cultural resources, and managed through legal or other effective means.</p>
<p><strong>FOREST AREA WITHIN PROTECTED AREAS</strong></p>
<p>Forest area within formally established protected areas independently of the purpose for which the protected areas were established. </p>
<p><u>Explanatory notes</u></p>
<ol>
<li>Includes IUCN Categories I – IV</li>
<li><u>Excludes</u> IUCN Categories V-VI</li>
</ol>
<p><strong>FOREST AREA WITH MANAGEMENT PLAN</strong></p>
<p>Forest area that has a long-term documented management plan, aiming at defined management goals, which is periodically revised. </p>
<p><u>Explanatory notes</u></p>
<ol>
<li>A forest area with management plan may refer to forest management unit level or aggregated forest management unit level (forest blocks, farms, enterprises, watersheds, municipalities, or wider units).</li>
<li>A management plan must include adequate detail on operations planned for individual operational units (stands or compartments) but may also provide general strategies and activities planned to reach management goals.</li>
<li>Includes forest area in protected areas with management plan.</li>
</ol>
<p><strong>INDEPENDENTLY VERIFIED FOREST MANAGEMENT CERTIFICATION</strong></p>
<p>Forest area certified under a forest management certification scheme with published standards and is independently verified by a third-party.</p>
<p><strong>Annex 2 – Methodology</strong></p>
<p><strong>Sub-indicator 1 - Annual forest area change rate</strong></p>
<p><u>Unit</u>: Percent</p>
<p><u>Reference period:</u> 2010-2020</p>
<p><u>Method of estimation:</u> Compound annual change rate formula as follows:</p>
<p><math xmlns="http://www.w3.org/1998/Math/MathML">
<mi>r</mi>
<mo>=</mo>
<mfenced open="[" close="]" separators="|">
<mrow>
<msup>
<mrow>
<mfenced separators="|">
<mrow>
<mfrac>
<mrow>
<msub>
<mrow>
<mi>A</mi>
<mi>F</mi>
</mrow>
<mrow>
<mi>t</mi>
<mn>2</mn>
</mrow>
</msub>
</mrow>
<mrow>
<msub>
<mrow>
<mi>A</mi>
<mi>F</mi>
</mrow>
<mrow>
<mi>t</mi>
<mn>1</mn>
</mrow>
</msub>
</mrow>
</mfrac>
</mrow>
</mfenced>
</mrow>
<mrow>
<mfrac bevelled="true">
<mrow>
<mn>1</mn>
</mrow>
<mrow>
<mfenced separators="|">
<mrow>
<mi>t</mi>
<mn>2</mn>
<mo>-</mo>
<mi>t</mi>
<mn>1</mn>
</mrow>
</mfenced>
</mrow>
</mfrac>
</mrow>
</msup>
<mo>-</mo>
<mn>1</mn>
</mrow>
</mfenced>
<mo>×</mo>
<mn>100</mn>
</math></p>
<p>where: </p>
<p><em>r</em> = compound annual change rate for the period <em>t<sub>1 - </sub>t<sub>2</sub></em><sub> </sub></p>
<p><em>t<sub>i</sub></em> = time i (year)</p>
<p><em>AF<sub>t1</sub></em> = forest area at <em>t<sub>1</sub></em> </p>
<p><em>AF<sub>t2</sub></em> = forest area at <em>t<sub>2</sub></em></p>
<p><u>Translation to dashboard/traffic light:</u></p>
<p>The following flowchart explains the logic behind the translation of this indicator to a dashboard/traffic light:</p>
<p>Forest area change direction</p>
<p>Forest area stable </p>
<p>or increasing</p>
<p>Forest area decreasing</p>
<p>Change in forest area loss rate </p>
<p>Loss rate</p>
<p>decreasing</p>
<p>Loss rate stable</p>
<p>or increasing</p>
<p>The forest area change direction is determined by examining the value of the forest area change rate for the most recent period, a negative value indicate a loss of forest area, a zero value means that forest area is stable, and a positive value means that forest area has increased. The change in forest area loss rate<sup><a href="#footnote-2" id="footnote-ref-2">[1]</a></sup> is based on a comparison of the annual forest area change rate for the period 2010-2020 with the annual <u>forest area change rate for the period 2000-2010 </u>(<u>baseline).</u></p>
<p><u>Comments:</u></p>
<p>This traffic light takes into consideration both the direction of forest area change (if forest area increases or decreases) as well as changes in the rate of forest area loss – the latter important in order to indicate progress among countries that are losing forest area but manage to reduce the loss rate. </p>
<p>The baseline should be updated every 5 years. In 2020 a new baseline was calculated for the period 2000-2010 based on updated country data. </p>
<p><strong>Sub-indicator 2 – Above-ground biomass in forest </strong></p>
<p><u>Unit</u>: tonnes/hectare</p>
<p><u>Reference year:</u> Latest reporting year</p>
<p><u>Method of estimation:</u> Reported directly by countries</p>
<p><u>Translation to dashboard/traffic light:</u></p>
<p>The indicator value for the latest reporting year is compared with the indicator value reported for 2010.</p>
<p>The ratio (r) between the current indicator value and the value reported for 2010 is calculated; r>1 means an increase in stock per hectare, r<1 means a decrease while 1 indicates no change. A narrow interval for r has been established to indicate a stable condition, and traffic-light colors are assigned as follows:</p>
<p> r ≥ 1.01 </p>
<p> 0.99 < r < 1.01</p>
<p> r ≤ 0.99</p>
<p><strong>Sub-indicator 3 – Proportion of forest area within legally established protected areas.</strong></p>
<p><u>Unit</u>: Percent</p>
<p><u>Reference year:</u> Latest reporting year</p>
<p><u>Method of estimation:</u> </p>
<p><math xmlns="http://www.w3.org/1998/Math/MathML">
<mi>r</mi>
<mo>=</mo>
<mi>&nbsp;</mi>
<mfrac>
<mrow>
<msub>
<mrow>
<mi>A</mi>
<mi>F</mi>
<mi>P</mi>
</mrow>
<mrow>
<mfenced open="[" close="]" separators="|">
<mrow>
<mi>r</mi>
<mi>e</mi>
<mi>f</mi>
<mi>e</mi>
<mi>r</mi>
<mi>e</mi>
<mi>n</mi>
<mi>c</mi>
<mi>e</mi>
<mi>&nbsp;</mi>
<mi>y</mi>
<mi>e</mi>
<mi>a</mi>
<mi>r</mi>
</mrow>
</mfenced>
</mrow>
</msub>
</mrow>
<mrow>
<msub>
<mrow>
<mi>A</mi>
<mi>F</mi>
</mrow>
<mrow>
<mn>2015</mn>
</mrow>
</msub>
</mrow>
</mfrac>
<mo>×</mo>
<mn>100</mn>
</math></p>
<p>Where:</p>
<p><em>AFP</em> = Forest area within legally established protected areas</p>
<p><em>AF</em> = Total forest area</p>
<p><u>Translation to dashboard/traffic light:</u></p>
<p>The indicator value for latest reporting year is compared with the indicator value reported for 2010.</p>
<p>The ratio (r) between the current indicator value and the value reported for 2010 is calculated; r>1 means an increase in forest area within protected areas, r<1 means a decrease while 1 indicates no change. A narrow interval for r has been established to indicate a stable condition, and traffic-light colors are assigned as follows:</p>
<p> r ≥ 1.01 </p>
<p> 0.99 < r < 1.01</p>
<p> r ≤ 0.99</p>
<p><u>Comment:</u></p>
<p>Using forest area in 2015 as denominator for estimating this indicator ensures that the time series of percentages reflect real changes in the forest area within legally established protected areas and is not affected by changes (losses or gains) in total forest area. </p>
<p><strong>Sub-indicator 4 – Proportion of forest area under a long-term management plan.</strong></p>
<p><u>Unit</u>: Percent</p>
<p><u>Reference year:</u> Latest reporting year</p>
<p><u>Method of estimation:</u> </p>
<p><math xmlns="http://www.w3.org/1998/Math/MathML">
<mi>r</mi>
<mo>=</mo>
<mi>&nbsp;</mi>
<mfrac>
<mrow>
<msub>
<mrow>
<mi>A</mi>
<mi>F</mi>
<mi>M</mi>
<mi>P</mi>
</mrow>
<mrow>
<mfenced open="[" close="]" separators="|">
<mrow>
<mi>r</mi>
<mi>e</mi>
<mi>f</mi>
<mi>e</mi>
<mi>r</mi>
<mi>e</mi>
<mi>n</mi>
<mi>c</mi>
<mi>e</mi>
<mi>&nbsp;</mi>
<mi>y</mi>
<mi>e</mi>
<mi>a</mi>
<mi>r</mi>
</mrow>
</mfenced>
</mrow>
</msub>
</mrow>
<mrow>
<msub>
<mrow>
<mi>A</mi>
<mi>F</mi>
</mrow>
<mrow>
<mn>2015</mn>
</mrow>
</msub>
</mrow>
</mfrac>
<mo>×</mo>
<mn>100</mn>
</math></p>
<p>Where:</p>
<p><em>AFMP</em> = Forest area under a long-term management plan</p>
<p><em>AF</em> = Total forest area</p>
<p><u>Translation to dashboard/traffic light: </u>The indicator value for latest reporting year is compared with the indicator value reported for 2010.</p>
<p>The ratio (r) between the current indicator value and the value reported for 2010 is calculated; r>1 means an increase in areas under management plan, r<1 means a decrease while 1 indicates no change. A narrow interval for r has been established to indicate a stable condition, and traffic-light colors are assigned as follows:</p>
<p> r ≥ 1.01 </p>
<p> 0.99 < r < 1.01</p>
<p> r ≤ 0.99</p>
<p><u>Comment:</u></p>
<p>Using forest area in 2015 as denominator for estimating this indicator ensures that the time series of percentages reflect real changes in the forest area under management plan and is not affected by changes (losses or gains) in total forest area. </p>
<p><strong>Sub-indicator 5 – Forest area under an independently verified forest management certification scheme.</strong></p>
<p><u>Unit</u>: Thousand hectares</p>
<p><u>Reference year:</u> Latest reporting year (as of June 30)</p>
<p><u>Method of estimation:</u> Data is collected directly from the databases of each certification scheme and provided to countries for validation.</p>
<p><u>Translation to dashboard/traffic light: </u>The indicator value for latest reporting year is compared with the indicator value for previous reporting year for assessment of continuity of progress since last report.</p>
<p>The ratio (r) between the current indicator value and the previously reported value is calculated; r>1 means an increase in areas under an independent forest management certification scheme, r<1 means a decrease while 1 indicates no change. A small interval for r has been established to indicate a stable condition, and traffic-light colors are assigned as follows:</p>
<p> r ≥ 1.01 </p>
<p> 0.99 < r < 1.01</p>
<p> r ≤ 0.99</p>
<p><u>Comments:</u></p>
<p>Using June 30 as the date for reporting, allows for the certification bodies to have their databases updated so they can provide information to FAO by end of the year, and then be included in the annual reporting to SDG in the beginning of the following year.</p><div class="footnotes"><div><sup class="footnote-number" id="footnote-2">1</sup><p> If forest area change rate is negative (= forest loss) then: annual forest area loss rate = <strong>-</strong> (annual forest area change rate) <a href="#footnote-ref-2">↑</a></p></div></div>
<h2>URL: </h2>
<p><a href="http://www.fao.org/forest-resources-assessment/en/">http://www.fao.org/forest-resources-assessment/en/</a> </p>
<h2>Рекомендации:</h2>
<p><a href="http://www.fao.org/forest-resources-assessment/current-assessment/en/">http://www.fao.org/forest-resources-assessment/current-assessment/en/</a></p>
<h1>Приложение 1 Обозначения и определения<sup><a href="#footnote-1" id="footnote-ref-1">[1]</a></sup></h1>
<p><strong><em>ЛЕС</em></strong></p>
<p>Участок земли площадью более 0,5 гектара, на котором растут деревья высотой более пяти метров с сомкнутостью крон более десяти процентов, или деревья, способные на данном участке достичь этих пороговых значений. Не включаются земли, которые используются преимущественно для целей сельского хозяйства или поселений<strong>. </strong></p>
<p><u>Пояснительные примечания</u></p>
<ol>
<li>Лес определяется как наличием деревьев, так и отсутствием других преобладающих
видов землепользования. Деревья должны быть способны достигать минимальной высоты 5 м. </li>
<li>Сюда входят участки с молодыми деревьями, с сомкнутостью крон еще не достигшей,
но которая, как ожидается, достигнет 10 %, а деревья – высоты 5 метров. Он также включает участки, которые являются временно обезлесенными из-за сплошных рубок в рамках практики ведения лесного хозяйства или из-за стихийных бедствий, но которые, как ожидается, будут восстановлены в течение 5 лет. В исключительных случаях, с учетом местных условий, могут устанавливаться более продолжительные временные сроки.</li>
<li>Лес включает лесные дороги, противопожарные полосы и другие небольшие открытые
пространства, леса в национальных парках, природных заповедниках и на других охраняемых территориях, представляющих особый экологический, научный, исторический, культурный или духовный интерес.</li>
<li>Лес включает ветрозащитные полосы, лесозащитные полосы и полосы деревьев площадью
более 0,5 га и шириной более 20 м.</li>
<li>Сюда входят заброшенные земли со сменной культивацией, где производится восстановление
лесонасаждений, которые имеют или, как ожидается, будут иметь сомкнутость крон 10 %, а деревья – высоту 5 метров.</li>
<li>Лес включает площади, занятые мангровыми лесами в приливных зонах, независимо
от того, классифицируются ли эти площади в качестве земельных площадей.</li>
<li>Лес включает плантации каучуковых деревьев, пробкового дуба и рождественских
елок. </li>
<liСюда входят площади, занятые бамбуковыми и пальмовыми лесами при условии, что
землепользование, высота деревьев и сомкнутость крон соответствуют установленным критериям.</li>
<li>Лес не включает древесные насаждения, вовлеченные в сельскохозяйственное производство,
такие как плантации плодовых деревьев, плантации масличной пальмы, оливковые рощи и агролесоводственные системы, при которых сельскохозяйственные культуры выращиваются под кронами деревьев. <u>Примечание:</u>Площади, включенные в некоторые агролесоводственные системы, такие как система Taungya, при которых сельскохозяйственные культуры выращиваются только в первые годы оборота лесного хозяйства, должны рассматриваться как лес.</li> </ol>
<p><strong><em>НАДПОЧВЕННАЯ БИОМАССА</em></strong></p>
<p>Вся биомасса живого растительного покрова, как древесного, так и травянистого, включая стволы, пни, ветви, кору, семена и листву.</p>
<p><u>Пояснительные примечания </u></p>
<ol>
<li>В случаях, когда подрост является относительно незначительным компонентом
пула углерода в надпочвенной биомассе, его допустимо исключить при условии, что это будет осуществляться последовательно в ходе инвентаризаций в отчетные годы.</li> </ol>
<p><strong><em>ОХРАНЯЕМЫЕ ТЕРРИТОРИИ</em></strong></p>
<p>Территории, специально предназначенные для защиты и поддержания биологического разнообразия, природных и связанных с ними культурных ресурсов и управляемые законными или другими эффективными способами.</p>
<p><strong><em>ЛЕСНЫЕ ПЛОЩАДИ НА ЗАКОННО УСТАНОВЛЕННЫХ ОХРАНЯЕМЫХ ТЕРРИТОРИЯХ</em></strong></p>
<p>Лесная площадь на официально созданных охраняемых территориях, независимо от цели, с которой были образованы охраняемые территории. </p>
<p><u>Пояснительные примечания</u></p>
<ol>
<li>Включает категории МСОП I – IV</li>
<li>Исключает категории МСОП V – VI</li>
</ol>
<p><strong><em>ЛЕСНАЯ ПЛОЩАДЬ С ДОЛГОСРОЧНЫМ ПЛАНОМ УПРАВЛЕНИЯ ЛЕСАМИ</em></strong></p>
<p>Лесная площадь, имеющая долгосрочный документированный план управления лесами, направленный на достижение определенных целей управления, и периодически пересматривающийся.</p>
<p><u>Пояснительные примечания</u></p>
<ol>
<li>Лесная площадь с планом управления лесами может означать уровень лесоустроительного
подразделения или агрегированный уровень лесоустроительного подразделения (лесные участки, фермы, предприятия, водосборные бассейны, муниципальные образования или более крупные участки).</li>
<li>План управления лесами может включать подробную информацию об операциях, запланированных
для отдельных эксплуатационных единиц (насаждений или кварталов), но он также может ограничиваться предоставлением общих стратегий и мероприятий, запланированных для достижения целей в области управления лесами.</li>
<li>Включает лесную площадь на охраняемых территориях с планом управления лесами.</li>
</ol>
<p><strong><em>СИСТЕМА СЕРТИФИКАЦИИ ИСПОЛЬЗОВАНИЯ ЛЕСОВ, ПРОШЕДШАЯ НЕЗАВИСИМУЮ ПРОВЕРКУ</em></strong></p>
<p>Лесные территории, сертифицированные по схеме сертификации управления лесами с опубликованными стандартами и прошедшие независимую проверку третьей стороной.</p>
<h1>Приложение 2 Методология</h1>
<p><strong><em>Субпоказатель 1 - Темп годового чистого изменения площади лесов</em></strong></p>
<p><u>Единица измерения</u>: Процент</p>
<p><u>Отчетный период:</u> Самый последний период</p>
<p><u>Метод оценки:</u> Формула сложных процентов</p>
<p><u>Перевод на инструментальную панель / световые сигналы:</u></p>
<p>Следующая блок-схема объясняет логику перевода этого показателя на инструментальную панель / световые сигналы:</p>
<p><img 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"></p>
<p>Направление изменения площади лесов определяется путем изучения значения скорости изменения площади лесов за последний период, отрицательное значение указывает на потерю площади лесов, нулевое значение означает, что площадь лесов стабильна, а положительное значение означает, что площадь лесов возросла. Изменение скорости потери площади лесов основано на сравнении текущей скорости чистого изменения площади лесов с базовой скоростью чистого изменения площади лесов за период 2010-2015 гг.</u></p>
<p><u>Комментарии:</u></p>
<p>Этот световой сигнал учитывает как направление изменения площади лесов (если площадь лесов увеличивается или уменьшается), так и изменения скорости потери площади лесов; последнее важно для определения прогресса среди стран, которые теряют площади лесов, но сумели снизить скорость потерь.</p>
<p>Для годовой отчетности ФАО может предоставлять странам условно исчисленные значения на основе предыдущих тенденций, которые они могут использовать в случае, если у них нет новой / обновленной информации. Базовый уровень должен обновляться каждые 5 лет, поэтому в 2020 году рассчитывается новый базовый уровень. Кроме того, на страновом уровне, если страна получает новую информацию и обновляет исторические временные ряды, базовый уровень для страны будет пересчитан с учетом периода 2010-2015 гг.</p>
<p><strong><em>Субпоказатель 2 – Запасы наземной лесной биомассы</em></strong></p>
<p><u>Единица измерения</u>: тонна/гектар</p>
<p><u>Отчетный период:</u> Самый последний период</p>
<p><u>Метод оценки:</u> Запас лесной биомассы (в тоннах) / лесная территория (в гектарах)</p>
<p><u>Перевод на инструментальную панель / световые сигналы:</u></p>
<p>Значение показателя за последний отчетный год сравнивается со значением показателя за предыдущий отчетный год для оценки непрерывности прогресса с момента последнего отчета.</p>
<p>Рассчитывается соотношение (r) между текущим значением показателя и ранее отраженным значением; r & gt; 1 означает увеличение запасов на гектар, r & lt; 1 означает уменьшение, а 1 означает отсутствие изменений. Был установлен узкий интервал для r, чтобы указать стабильное состояние, и цвета светового сигнала обозначаются следующим образом:</p>
<p><img src="data:image/png;base64,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"></p>
<p><strong><em>Субпоказатель 3 –Доля лесных площадей, расположенных в пределах установленных законом охраняемых территорий</em></strong></p>
<p><u>Единица измерения</u>: Процент</p>
<p><u>Отчетный период:</u> Самый последний период</p>
<p><u>Метод оценки:</u> Доля лесных площадей, расположенных в пределах установленных законом охраняемых территорий / Лесная площадь в 2015 году * 100</p>
<p><u>Перевод на инструментальную панель / световые сигналы:</u></p>
<p>Значение показателя за последний отчетный год сравнивается со значением показателя за предыдущий отчетный год для оценки непрерывности прогресса с момента последнего отчета.</p>
<p>Рассчитывается соотношение (r) между текущим значением показателя и ранее отраженным значением; r & gt; 1 означает увеличение запасов на гектар, r & lt; 1 означает уменьшение, а 1 означает отсутствие изменений. Был установлен узкий интервал для r, чтобы указать стабильное состояние, и цвета светового сигнала обозначаются следующим образом:</p>
<p><img src="data:image/png;base64,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"></p>
<p><u>Комментарий:</u></p>
<p>Использование площади лесов в 2015 году в качестве знаменателя для оценки этого показателя гарантирует, что временной ряд в процентах отражает реальные изменения площади лесов в пределах установленных законом охраняемых территорий и не зависит от изменений (потерь или прибылей) в общей площади лесов.</p>
<p><strong><em>Субпоказатель 4 – Доля лесных площадей, имеющих долгосрочный план управления лесами.</em></strong></p>
<p><u>Единица измерения</u>: Процент</p>
<p><u>Отчетный период:</u> Самый последний период</p>
<p><u>Метод оценки:</u> Лесные площади, имеющие долгосрочный план управления лесами / Лесная площадь в 2015 году * 100</p>
<p><u>Перевод на инструментальную панель / световые сигналы: </u>Значение показателя за последний отчетный год сравнивается со значением показателя за предыдущий отчетный год для оценки непрерывности прогресса с момента последнего отчета.</p>
<p>Рассчитывается соотношение (r) между текущим значением показателя и ранее отраженным значением; r & gt; 1 означает увеличение запасов на гектар, r & lt; 1 означает уменьшение, а 1 означает отсутствие изменений. Был установлен узкий интервал для r, чтобы указать стабильное состояние, и цвета светового сигнала обозначаются следующим образом:</p>
<p><img src="data:image/png;base64,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"></p>
<p><u>Комментарий:</u></p>
<p>Использование площади лесов в 2015 году в качестве знаменателя для оценки этого показателя гарантирует, что временной ряд в процентах отражает реальные изменения площади лесов, имеющих долгосрочный план управления лесами, и не зависит от изменений (потерь или прибылей) в общей площади лесов. </p>
<p><strong><em>Субпоказатель 5 – Площадь лесов, на которых действует система сертификации использования лесов, прошедшая независимую проверку.</em></strong></p>
<p><u>Единица измерения</u>: Тысяч гектаров</p>
<p><u>Отчетный период:</u> Самый последний период (по состоянию на 30 июня)</p>
<p><u>Метод оценки:</u> Данные собираются непосредственно из баз данных каждой системы сертификации и предоставляются странам для проверки.</p>
<p><u>Перевод на инструментальную панель / световые сигналы: </u>Значение показателя за последний отчетный год сравнивается со значением показателя за предыдущий отчетный год для оценки непрерывности прогресса с момента последнего отчета.</p>
<p>Рассчитывается соотношение (r) между текущим значением показателя и ранее отраженным значением; r & gt; 1 означает увеличение запасов на гектар, r & lt; 1 означает уменьшение, а 1 означает отсутствие изменений. Был установлен узкий интервал для r, чтобы указать стабильное состояние, и цвета светового сигнала обозначаются следующим образом:</p>
<p><img src="data:image/png;base64,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"> </p>
<p><u>Комментарии:</u></p>
<p>Использование 30 июня в качестве отчетной даты позволяет органам по сертификации обновлять свои базы данных, чтобы они могли предоставлять информацию в ФАО к концу года, а затем включать ее в годовую отчетность для ЦУР в начале следующего года.</p><div class="footnotes"><div><sup class="footnote-number" id="footnote-1">1</sup><p> Глобальная оценка лесных ресурсов 2015 г. – Обозначения и определения <a href="http://www.fao.org/docrep/017/ap862e:/www.fo.org/docrep/017/ap862e/ap862e00.pdf</a> <a href="#footnote-ref-1">↑</a></p></div></div>