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1.
Philos Trans R Soc Lond B Biol Sci ; 378(1867): 20210081, 2023 01 02.
Artigo em Inglês | MEDLINE | ID: mdl-36373926

RESUMO

Many natural forests in Southeast Asia are degraded following decades of logging. Restoration of these forests is delayed by ongoing logging and tropical cyclones, but the implications for recovery are largely uncertain. We analysed meteorological, satellite and forest inventory plot data to assess the effect of Typhoon Doksuri, a major tropical cyclone, on the forest landscapes of central Vietnam consisting of natural forests and plantations. We estimated the return period for a cyclone of this intensity to be 40 years. Plantations were almost twice as likely to suffer cyclone damage compared to natural forests. Logged natural forests (9-12 years after cessation of government-licensed logging) were surveyed before and after the storm with 2 years between measurements and remained a small biomass carbon sink (0.1 ± 0.3 Mg C ha-1 yr-1) over this period. The cyclone reduced the carbon sink of recovering natural forests by an average of 0.85 Mg C ha-1 yr-1, less than the carbon loss due to ongoing unlicensed logging. Restoration of forest landscapes in Southeast Asia requires a reduction in unlicensed logging and prevention of further conversion of degraded natural forests to plantations, particularly in landscapes prone to tropical cyclones where natural forests provide a resilient carbon sink. This article is part of the theme issue 'Understanding forest landscape restoration: reinforcing scientific foundations for the UN Decade on Ecosystem Restoration'.


Assuntos
Tempestades Ciclônicas , Agricultura Florestal , Ecossistema , Vietnã , Florestas , Clima Tropical , Árvores , Conservação dos Recursos Naturais
2.
PLoS One ; 10(12): e0143886, 2015.
Artigo em Inglês | MEDLINE | ID: mdl-26632842

RESUMO

Protected areas (PAs) have been established to conserve tropical forests, but their effectiveness at reducing deforestation is uncertain. To explore this issue, we combined high resolution data of global forest loss over the period 2000-2012 with data on PAs. For each PA we quantified forest loss within the PA, in buffer zones 1, 5, 10 and 15 km outside the PA boundary as well as a 1 km buffer within the PA boundary. We analysed 3376 tropical and subtropical moist forest PAs in 56 countries over 4 continents. We found that 73% of PAs experienced substantial deforestation pressure, with >0.1% a(-1) forest loss in the outer 1 km buffer. Forest loss within PAs was greatest in Asia (0.25% a(-1)) compared to Africa (0.1% a(-1)), the Neotropics (0.1% a(-1)) and Australasia (Australia and Papua New Guinea; 0.03% a(-1)). We defined performance (P) of a PA as the ratio of forest loss in the inner 1 km buffer compared to the loss that would have occurred in the absence of the PA, calculated as the loss in the outer 1 km buffer corrected for any difference in deforestation pressure between the two buffers. To remove the potential bias due to terrain, we analysed a subset of PAs (n = 1804) where slope and elevation in inner and outer 1 km buffers were similar (within 1° and 100 m, respectively). We found 41% of PAs in this subset reduced forest loss in the inner buffer by at least 25% compared to the expected inner buffer forest loss (P<0.75). Median performance (P) of subset reserves was 0.87, meaning a reduction in forest loss within the PA of 13%. We found PAs were most effective in Australasia (P = 0.16), moderately successful in the Neotropics (P = 0.72) and Africa (p = 0.83), but ineffective in Asia (P = 1). We found many countries have PAs that give little or no protection to forest loss, particularly in parts of Asia, west Africa and central America. Across the tropics, the median effectiveness of PAs at the national level improved with gross domestic product per capita. Whilst tropical and subtropical moist forest PAs do reduce forest loss, widely varying performance suggests substantial opportunities for improved protection, particularly in Asia.


Assuntos
Conservação dos Recursos Naturais/estatística & dados numéricos , Florestas , Clima Tropical , Humanos , Árvores
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