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Assam News

India's Tree Loss In Two Decades Hits Assam Hardest: Reports

A new report by the Global Forest Watch says that there has been a 6% decline in tree cover since 2000.

Sentinel Digital Desk

GUWAHATI: India has lost about 2.3 million hectares of tree cover from 2001 to 2023, with five northeastern states, including Assam, being the most affected.

A new report by the Global Forest Watch says that there has been a 6% decline in tree cover since 2000.

The states of Assam, Mizoram, Arunachal Pradesh, Nagaland, and Manipur, in northeast India were hit the hardest, counting for 60 of the total loss of tree cover.

Assam endured the most significant loss, with 324,000 hectares of perm fading. On average, this amounted to 66,000 hectares lost each time during the period.

The report stressed fire as a major trouble to timbers, with Odisha facing the loftiest average periodic loss of 238 hectares due to fires.

Other northeastern countries similar to Arunachal Pradesh, Nagaland, Assam, and Meghalaya also endured significant deforestation caused by fires.

Mizoram lost 312,000 hectares of tree cover, Arunachal Pradesh lost 262,000 hectares, Nagaland lost 259,000 hectares, and Manipur lost 240,000 hectares.

The Forest Conservation Amendment Act, passed in 2023, permits the use of timbers for structure systems near the border without demanding concurrence.

Moreover, the Act only protects forests that are officially classified, leaving many natural areas at risk.

Forests play a dual role in the carbon cycle: they act as a sink, absorbing carbon dioxide from the air when they’re intact or re-growing, and they act as a source, emitting carbon dioxide when they’re cleared or degraded. Therefore, the loss of forests speeds up climate change.

The Global Forest Watch uses the term "tree cover" to describe the extent, loss, and gain of forests. Tree cover is a useful measure for tracking changes in forests because it can be easily seen and measured from space using free, medium-resolution satellite images. This allows for frequent, cost-effective monitoring over large areas.

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