Detecting and predicting forest degradation: a comparison of ground surveys and remote sensing in Tanzanian forests
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Date
2021-01-08
Journal Title
Journal ISSN
Volume Title
Publisher
Plants, People, Planet (PPP)
Abstract
Tropical forest degradation is widely recognised as a driver of biodiversity loss and
a major source of carbon emissions. However, in contrast to deforestation, more
gradual changes from degradation are challenging to detect, quantify and monitor.
Here, we present a field protocol for rapid, area-standardised quantifications of
forest condition, which can also be implemented by non-specialists. Using the ex-
ample of threatened high-biodiversity forests in Tanzania, we analyse and predict
degradation based on this method. We also compare the field data to optical and
radar remote-sensing datasets, thereby conducting a large-scale, independent
test of the ability of these products to map degradation in East Africa from space.
• Our field data consist of 551 ‘degradation’ transects collected between 1996
and 2010, covering >600 ha across 86 forests in the Eastern Arc Mountains and
coastal forests.
• Degradation was widespread, with over one-third of the study forests—mostly
protected areas—having more than 10% of their trees cut. Commonly used opti-
cal remote-sensing maps of complete tree cover loss only detected severe im-
pacts (≥25% of trees cut), that is, a focus on remotely-sensed deforestation would
have significantly underestimated carbon emissions and declines in forest quality.
Radar-based maps detected even low impacts (<5% of trees cut) in ~90% of cases.
The field data additionally differentiated types and drivers of harvesting, with spa-
tial patterns suggesting that logging and charcoal production were mainly driven
by demand from major cities.
• Rapid degradation surveys and radar remote sensing can provide an early warning
and guide appropriate conservation and policy responses. This is particularly im-
portant in areas where forest degradation is more widespread than deforestation,
such as in eastern and southern Africa.
Description
Research Article
Keywords
Biodiversity conservation, Carbon emissions, Community-based forest management, East Africa, Global forest watch, Human disturbance, Synthetic aperture radar, Village land forest reserves