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Forest Landscape Integrity Index

From Wikipedia, the free encyclopedia
Forest Landscape Integrity Index 2019 map of the Earth. 0 = Most modification; 10= Least.

The Forest Landscape Integrity Index (FLII) is an annual global index of forest condition measured by degree of anthropogenic modification.[1][2][3][4][5] Created by a team of 47 scientists,[6] the FLII, in its measurement of 300m pixels of forest across the globe, finds that ~17.4 million km2 of forest has high landscape-level integrity (with a score from 9.6–10), compared to ~14.6 million with medium integrity (6–9.6) and ~12.2 million km2 with low integrity (0–6).[7]

The FLII finds that most remaining high-integrity forest landscapes are found in Canada, Russia, the Rocky Mountains, Alaska, the Amazon, the Guianas, southern Chile, Central Africa, and New Guinea. Low integrity forests, on the other hand, are found in Western and Central Europe, the American Southeast, South-East Asia, west of New Guinea, the Andes, much of China and India, the Albertine Rift, West Africa, Mesoamerica, and the Atlantic Forests of Brazil.

The results are meant to help decision-makers at all levels achieve their commitments to the Sustainable Development Goals (SDGs), United Nations Convention on Biological Diversity (CBD), Convention to Combat Desertification (UNCCD), and the Framework Convention on Climate Change (UNFCCC).[1]

Forest Integrity

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An ecosystem is considered to have integrity when its structure, composition, and ecological processes are within their natural range.[8]

Country rankings

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172 countries have been ranked: [9]

Forest Landscape Integrity 2019
Country Mean FLII Low integrity (km2) Medium integrity (km2) High integrity (km2) Total forest area (km2) Map
Seychelles 10 0 0 68 68
Sudan 9.8 1 72 495 569
Guyana 9.58 4,162 40,817 147,413 192,391
South Sudan 9.45 5,083 59,389 146,218 210,691
Suriname 9.39 6,796 25,031 107,954 139,781
Mongolia 9.36 520 11,915 27,407 39,841
Central African Republic 9.28 30,161 139,350 379,097 548,608
Botswana 9.13 13 187 372 572
Gabon 9.07 11,780 118,348 120,852 250,979
Russia 9.02 739,484 2,245,281 5,137,079 8,121,843
Canada 8.99 480,206 1,027,386 2,968,268 4,475,860
Congo 8.89 24,512 124,215 158,184 306,911
Kyrgyzstan 8.86 329 2,819 2,761 5,909
Peru 8.86 85,793 190,547 509,720 786,061
Afghanistan 8.85 90 1,475 977 2,542
Bhutan 8.85 1,620 16,769 10,140 28,529
Papua New Guinea 8.84 37,294 183,415 216,355 437,064
Vanuatu 8.82 734 5,322 4,448 10,504
Venezuela 8.78 64,650 170,792 351,112 586,554
Tajikistan 8.65 34 137 130 301
Bolivia 8.47 78,745 280,532 272,007 631,284
Namibia 8.43 5 13 17 36
Angola 8.35 105,487 284,054 315,895 705,436
Fiji 8.35 1,753 10,802 3,594 16,148
Colombia 8.26 150,737 272,442 428,320 851,499
Kazakhstan 8.23 6,068 18,926 15,294 40,288
Palau 8.09 45 333 9 387
North Korea 8.02 8,374 40,156 8,410 56,939
Cameroon 8 66,191 181,336 119,263 366,789
Equatorial Guinea 7.99 3,982 17,595 5,007 26,585
Georgia 7.79 6,982 17,803 9,784 34,570
Brunei Darussalam 7.71 1,102 2,842 1,498 5,442
Comoros 7.69 284 1,149 82 1,515
Iran 7.67 3,361 12,930 2,162 18,453
Ecuador 7.66 48,822 77,585 73,492 199,900
DRC 7.56 533,118 935,508 727,983 2,196,608
Micronesia 7.55 8 35 0 43
Brazil 7.52 1,374,902 1,354,961 2,338,101 5,067,963
Zambia 7.5 96,969 164,376 110,822 372,167
North Macedonia 7.42 2,034 7,090 459 9,583
Pakistan 7.42 2,090 7,859 1,139 11,088
Lesotho 7.4 1 4 0 5
Chile 7.37 56,849 41,971 93,537 192,357
Bahamas 7.35 741 1,935 399 3,075
  Nepal 7.23 13,785 41,992 3,760 59,538
Australia 7.22 117,672 239,624 103,852 461,148
Argentina 7.21 98,249 189,966 72,557 360,772
Solomon Islands 7.19 6,871 15,310 3,149 25,329
Myanmar 7.18 129,745 220,188 96,924 446,857
Ethiopia 7.16 52,652 84,430 44,397 181,479
Mali 7.16 451 996 140 1,586
Somalia 7.16 347 1,384 46 1,777
China 7.14 533,800 974,431 301,051 1,809,282
Tanzania 7.13 123,997 159,712 122,812 406,521
New Zealand 7.12 34,503 44,155 35,334 113,992
Senegal 7.11 847 2,456 162 3,465
Timor-Leste 7.11 1,783 7,008 47 8,838
India 7.09 117,992 254,792 54,428 427,211
Cyprus 7.06 388 1,026 18 1,432
Norway 6.98 39,343 67,383 16,627 123,352
Saint Vincent and the Grenadines 6.95 91 221 0 312
Mozambique 6.93 150,665 189,362 115,379 455,406
Mexico 6.82 193,908 280,445 121,842 596,195
Albania 6.77 2,426 5,256 122 7,805
Uzbekistan 6.77 214 227 199 640
Morocco 6.74 2,260 4,076 451 6,787
United States 6.65 1,328,079 1,144,693 658,645 3,131,417
Sao Tome and Principe 6.64 31 140 0 171
Trinidad and Tobago 6.62 1,478 2,176 418 4,072
Greece 6.6 14,548 27,833 1,078 43,459
Indonesia 6.6 535,370 509,018 431,973 1,476,361
Azerbaijan 6.55 4,820 7,189 1,534 13,543
Montenegro 6.41 2,949 4,778 82 7,809
Paraguay 6.39 78,538 102,626 29,877 211,041
Turkey 6.39 43,043 68,243 3,516 114,801
Taiwan 6.38 8,786 14,547 1,453 24,786
Cabo Verde 6.37 27 38 0 65
Panama 6.37 25,420 21,310 14,605 61,336
Cambodia 6.31 30,143 31,939 16,349 78,431
Turkmenistan 6.31 5 33 0 37
Zimbabwe 6.31 9,450 14,417 1,644 25,511
Nigeria 6.2 64,621 65,355 24,307 154,283
Chad 6.18 5,261 6,016 1,910 13,187
Saint Lucia 6.17 235 316 0 551
Belize 6.15 7,004 7,957 2,744 17,705
Bulgaria 6.09 18,884 26,325 847 46,057
South Korea 6.02 25,060 32,009 888 57,956
Thailand 6 86,276 89,326 33,612 209,214
Bosnia and Herzegovina 5.99 13,387 17,031 574 30,993
Romania 5.95 38,395 48,394 607 87,395
Philippines 5.91 91,820 100,831 8,393 201,044
Togo 5.88 5,064 4,522 1,076 10,662
Benin 5.86 4,724 3,698 1,769 10,191
Sri Lanka 5.83 20,.541 22,390 1,613 44,544
Japan 5.8 135,783 133,480 16,005 285,268
Malawi 5.74 12,514 12,167 2,396 27,078
Guinea-Bissau 5.7 9,274 8,702 855 18,831
Laos 5.59 92,986 80,564 19,252 192,801
Armenia 5.46 1,894 1,681 3 3,577
Mauritius 5.46 567 478 0 1,045
Bangladesh 5.45 10,013 7,251 1,947 19,211
Cuba 5.4 22,605 18,460 1,632 42,697
Sweden 5.35 174,415 109,779 23,494 307,687
Vietnam 5.35 82,551 75,353 9,588 167,492
Serbia 5.29 17,513 14,112 516 32,141
Algeria 5.22 7,418 6,044 81 13,543
Kosovo 5.19 2,628 1,775 47 4,450
Tunisia 5.14 1,354 987 0 2,340
Finland 5.08 144,310 83,572 9,294 237,176
Jamaica 5.01 5,362 3,249 158 8,770
Malaysia 5.01 130,825 91,957 21,499 244,281
South Africa 4.94 45,489 34,968 3,196 83,653
Croatia 4.92 15,732 10,522 379 26,633
Guinea 4.9 81,702 54,877 2,895 139,475
Libya 4.85 15 2 0 17
Liberia 4.79 51,975 31,162 11,025 94,163
Antigua and Barbuda 4.72 114 92 0 206
Costa Rica 4.65 27,164 12,838 4,164 44,167
Madagascar 4.63 120,340 66,584 11,922 198,846
Gambia 4.56 181 85 0 266
Saint Kitts and Nevis 4.55 95 50 0 145
Ghana 4.53 57,519 28,901 2,160 88,580
France 4.52 161,987 49,496 74,121 285,604
Burundi 4.5 6,882 3,841 46 10,769
Liechtenstein 4.5 59 42 0 101
Honduras 4.48 57,899 23,802 3,692 85,392
Andorra 4.45 170 49 0 219
Uganda 4.36 77,303 36,381 7,507 121,190
Slovakia 4.34 17,615 8,165 0 25,781
Spain 4.23 82,770 46,013 133 128,916
Grenada 4.22 221 86 0 308
Eswatini 4.21 5,054 2,501 14 7,569
Kenya 4.2 28,427 13,558 4,702 46,686
Dominican Republic 4.19 19,890 9,364 518 29,772
Israel 4.14 170 85 0 255
El Salvador 4.05 8,837 2,947 0 11,784
Haiti 4.01 7,116 2,831 12 9,959
Guatemala 3.85 58,572 18,764 5,592 82,928
Rwanda 3.85 5,665 2,170 619 8,454
Slovenia 3.78 11,065 3,791 0 14,856
Lebanon 3.76 541 115 0 656
Italy 3.65 79,403 26,858 25 106,286
Cote d'Ivoire 3.64 158,010 41,005 7,288 206,303
Syria 3.64 841 282 0 1,123
Belarus 3.63 77,870 20,847 91 98,808
Nicaragua 3.63 65,356 17,646 4,858 87,860
Uruguay 3.61 11,793 3,998 0 15,791
Iraq 3.59 104 9 0 113
Austria 3.55 36,666 12,422 21 49,109
 Switzerland 3.53 13,636 4,412 10 18,058
Ukraine 3.3 89,540 20,183 176 109,900
Estonia 3.05 24,473 4,832 52 29,358
Jordan 2.79 12 0 0 12
Sierra Leone 2.76 52,512 11,858 640 65,010
Germany 2.28 122,168 11,307 0 133,475
Hungary 2.25 18,729 2,047 0 20,776
Poland 2.24 101,886 7,103 0 108,989
Moldova 2.2 3,113 202 0 3,315
Latvia 2.09 38,164 2,137 0 40,301
Czechia 1.71 32,161 1,611 0 33,772
United Kingdom 1.65 29,149 2,917 35 32,101
Lithuania 1.62 24,554 930 0 25,484
Belgium 1.36 8,803 297 0 9,099
Luxembourg 1.12 1,170 0 0 1,170
Singapore 1.11 170 2 0 172
Dominica 1.06 531 2 0 533
Ireland 0.92 5,283 96 0 5,378
Portugal 0.82 25,966 553 0 26,519
Netherlands 0.6 5,250 72 0 5,322
Egypt 0.56 4,772 218 69 5,059
Denmark 0.5 5,756 31 0 5,787
San Marino 0.01 7 0 0 7
  Countries with high mean FLII (8-10)
  Countries with medium mean FLII (5-7.99)
  Countries with low mean FLII (0-4.99)

Background

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The index was authored by a global team of forest conservation experts, including:[1]

Institution Author(s)
Wildlife Conservation Society, The Bronx H.S. Grantham; A. Duncan; T. D. Evans; K. R. Jones; J. Walston; J. G. Robinson; M. Callow; T. Clements; H. M. Costa; A. DeGemmis; P. R. Elsen; P. Franco; S. Jupiter; A. Kang; S. Lieberman; M. Linkie; M. Mendez; C. Samper; J. Silverman; T. Stevens; E. Stokes; T. Tear; R. Tizard; S. Wang; J. E. M. Watson
University of Queensland, Brisbane H. L. Beyer; S. Maxwell; H. Possingham; J. E. M. Watson
Carleton University, Ottawa R. Schuster
Wildlife Conservation Society Canada, Toronto J. C. Ray
United Nations Development Program, Manhattan J. Ervin
World Resources Institute, Washington, DC E. Goldman; R. Taylor
Northern Arizona University, Flagstaff S. Goetz; P. Jantz
Montana State University, Bozeman A. Hansen
Rainforest Foundation Norway, Oslo E. Hofsvang
Global Wildlife Conservation, Austin, Texas P. Langhammer; R. Mittermeier
Arizona State University, Tempe, Arizona P. Langhammer
James Cook University, Cairns W. F. Laurance; N. J. Murray
University of Oxford, Oxford Y. Malhi
The Nature Conservancy, Arlington, Virginia H. Possingham
Jet Propulsion Laboratory, Pasadena, California S. Saatchi
World Wide Fund for Nature Germany, Berlin A. Shapiro
International Institute of Sustainability, Rio de Janeiro B. Strassburg
University of Northern British Columbia, Prince George, British Columbia O. Venter
International Institute for Applied Systems Analysis, Laxenburg, Austria P. Visconti

See also

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References

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  1. ^ a b c Grantham, H. S.; Duncan, A.; Evans, T. D.; Jones, K. R.; Beyer, H. L.; Schuster, R.; Walston, J.; Ray, J. C.; Robinson, J. G.; Callow, M.; Clements, T.; Costa, H. M.; DeGemmis, A.; Elsen, P. R.; Ervin, J.; Franco, P.; Goldman, E.; Goetz, S.; Hansen, A.; Hofsvang, E.; Jantz, P.; Jupiter, S.; Kang, A.; Langhammer, P.; Laurance, W. F.; Lieberman, S.; Linkie, M.; Malhi, Y.; Maxwell, S.; Mendez, M.; Mittermeier, R.; Murray, N. J.; Possingham, H.; Radachowsky, J.; Saatchi, S.; Samper, C.; Silverman, J.; Shapiro, A.; Strassburg, B.; Stevens, T.; Stokes, E.; Taylor, R.; Tear, T.; Tizard, R.; Venter, O.; Visconti, P.; Wang, S.; Watson, J. E. M. (2020). "Anthropogenic modification of forests means only 40% of remaining forests have high ecosystem integrity". Nature Communications. 11 (1): 5978. Bibcode:2020NatCo..11.5978G. doi:10.1038/s41467-020-19493-3. ISSN 2041-1723. PMC 7723057. PMID 33293507.
  2. ^ Elcacho, Joaquim (2020-12-14). "Descubre con este mapa dónde están los mejores bosques de tu país y del mundo" [Discover with this map where are the best forests in your country and in the world]. La Vanguardia (in Spanish). Barcelona. Retrieved 2020-12-16.
  3. ^ "Anthropogenic modification of forests means only 40% of remaining forests have high ecosystem integrity". Nature-based Solutions Initiative. University of Oxford. 2020-12-10. Retrieved 2020-12-16.
  4. ^ Попова, Марина (2020-12-09). "Прямое влияние человека обошло стороной 40 процентов современных лесов" [Direct human influence bypassed 40 percent of modern forests] (in Russian). Retrieved 2020-12-16.
  5. ^ "New Forest Landscape Integrity Index Reveals that Only 40 Percent of World's Forests Have High Integrity". WCS Newsroom. Wildlife Conservation Society. 2020-12-08. Retrieved 2020-12-16.
  6. ^ "Forest Landscape Integrity Index". www.forestintegrity.com. Retrieved 2024-11-17.
  7. ^ "Forest Landscape Integrity Index - Further Information". www.forestintegrity.com. Retrieved 2024-11-17.
  8. ^ Parrish, Jeffrey D.; Braun, David P.; Unnasch, Robert S. (2003). "Are We Conserving What We Say We Are? Measuring Ecological Integrity within Protected Areas". BioScience. 53 (9): 851. doi:10.1641/0006-3568(2003)053[0851:AWCWWS]2.0.CO;2. ISSN 0006-3568.
  9. ^ Grantham, H. S.; Duncan, A.; Evans, T. D.; Jones, K. R.; Beyer, H. L.; Schuster, R.; Walston, J.; Ray, J. C.; Robinson, J. G.; Callow, M.; Clements, T.; Costa, H. M.; DeGemmis, A.; Elsen, P. R.; Ervin, J.; Franco, P.; Goldman, E.; Goetz, S.; Hansen, A.; Hofsvang, E.; Jantz, P.; Jupiter, S.; Kang, A.; Langhammer, P.; Laurance, W. F.; Lieberman, S.; Linkie, M.; Malhi, Y.; Maxwell, S.; Mendez, M.; Mittermeier, R.; Murray, N. J.; Possingham, H.; Radachowsky, J.; Saatchi, S.; Samper, C.; Silverman, J.; Shapiro, A.; Strassburg, B.; Stevens, T.; Stokes, E.; Taylor, R.; Tear, T.; Tizard, R.; Venter, O.; Visconti, P.; Wang, S.; Watson, J. E. M. (2020). "Anthropogenic modification of forests means only 40% of remaining forests have high ecosystem integrity - Supplementary Material". Nature Communications. 11 (1): 5978. doi:10.1038/s41467-020-19493-3. ISSN 2041-1723. PMC 7723057. PMID 33293507.
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