Forest Landscape Integrity Index

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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

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)
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

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 (2025-08-07). "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 2025-08-07.
^ "Anthropogenic modification of forests means only 40% of remaining forests have high ecosystem integrity". Nature-based Solutions Initiative. University of Oxford. 2025-08-07. Retrieved 2025-08-07.
^ Попова, Марина (2025-08-07). "Прямое влияние человека обошло стороной 40 процентов современных лесов" [Direct human influence bypassed 40 percent of modern forests] (in Russian). Retrieved 2025-08-07.
^ "New Forest Landscape Integrity Index Reveals that Only 40 Percent of World's Forests Have High Integrity". WCS Newsroom. Wildlife Conservation Society. 2025-08-07. Retrieved 2025-08-07.
^ "Forest Landscape Integrity Index". www.forestintegrity.com. Retrieved 2025-08-07.
^ "Forest Landscape Integrity Index - Further Information". www.forestintegrity.com. Retrieved 2025-08-07.
^ 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

Official site & map

[OriginalArticle-1] 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.

[Vanguardia-2] Elcacho, Joaquim (2025-08-07). "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 2025-08-07.

[Oxford-3] "Anthropogenic modification of forests means only 40% of remaining forests have high ecosystem integrity". Nature-based Solutions Initiative. University of Oxford. 2025-08-07. Retrieved 2025-08-07.

[4] Попова, Марина (2025-08-07). "Прямое влияние человека обошло стороной 40 процентов современных лесов" [Direct human influence bypassed 40 percent of modern forests] (in Russian). Retrieved 2025-08-07.

[PressRelease-5] "New Forest Landscape Integrity Index Reveals that Only 40 Percent of World's Forests Have High Integrity". WCS Newsroom. Wildlife Conservation Society. 2025-08-07. Retrieved 2025-08-07.

[6] "Forest Landscape Integrity Index". www.forestintegrity.com. Retrieved 2025-08-07.

[7] "Forest Landscape Integrity Index - Further Information". www.forestintegrity.com. Retrieved 2025-08-07.

[ParrishBraun2003-8] 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.

[Supplementary-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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v t e Deforestation and desertification
Deforestation	Assarting Deforestation Deforestation and climate change Deforestation by region Illegal logging Mountaintop removal Slash-and-burn Slash-and-char
Desertification	Aridification Historic desertification Moisture recycling Soil retrogression and degradation Water scarcity By region: China Gobi Desert Lebanon Libya Mali Mauritania Mongolia Sahel Yemen
Mitigation	Afforestation Arid Lands Information Network Biochar Conservation grazing Desert greening Ecoforestry Ecological engineering Farmer-managed regeneration Flexible Mechanisms Great Green Wall (Africa) Great Green Wall (China) Managed intensive rotational grazing Oasification Reforestation United Nations Convention to Combat Desertification
Related articles	Forest Landscape Integrity Index Forestry Intact forest landscape Land surface effects on climate Land use, land-use change and forestry List of global issues Natural landscape Terra preta Wilderness

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