Forest Landscape Integrity Index Global index of forest condition
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] [ 6] 2 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
An ecosystem is considered to have integrity when its structure, composition, and ecological processes are within their natural range.[ 8]
Country rankings
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
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
References
^ 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 . ^ 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 . Retrieved 2020-12-16 . ^ "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 .^ 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 . ^ "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 .^ "Forest Landscape Integrity Index" . www.forestintegrity.com . Retrieved 2024-11-17 .^ "Forest Landscape Integrity Index - Further Information" . www.forestintegrity.com . Retrieved 2024-11-17 .^ 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 . ^ 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 .
External links
