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Publication . Article . 2021

Detecting and predicting forest degradation: A comparison of ground surveys and remote sensing in Tanzanian forests

A comparison of ground surveys and remote sensing in Tanzanian forests
Antje Ahrends; Mark T. Bulling; Philip J. Platts; Ruth D. Swetnam; Casey M. Ryan; Nike Doggart; Peter M. Hollingsworth; +21 Authors
Open Access
English
Abstract

Societal Impact Statement: Large areas of tropical forest are degraded. While global tree cover is being mapped with increasing accuracy from space, much less is known about the quality of that tree cover. Here we present a field protocol for rapid assessments of forest condition. Using extensive field data from Tanzania, we show that a focus on remotely‐sensed deforestation would not detect significant reductions in forest quality. Radar‐based remote sensing of degradation had good agreement with the ground data, but the ground surveys provided more insights into the nature and drivers of degradation. We recommend the combined use of rapid field assessments and remote sensing to provide an early warning, and to allow timely and appropriately targeted conservation and policy responses. Summary: 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 example 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 optical remote‐sensing maps of complete tree cover loss only detected severe impacts (≥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 spatial 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 important in areas where forest degradation is more widespread than deforestation, such as in eastern and southern Africa.

Funder: Scottish Government’s Rural and Environment Science and Analytical Services Division

Funder: Danish International Development Agency; Id: http://dx.doi.org/10.13039/501100011054

Funder: Critical Ecosystem Partnership Fund; Id: http://dx.doi.org/10.13039/100013724

Funder: Global Environment Facility; Id: http://dx.doi.org/10.13039/100011150

Funder: Leverhulme Trust; Id: http://dx.doi.org/10.13039/501100000275

Funder: Finnish International Development Agency

Subjects by Vocabulary

Microsoft Academic Graph classification: Logging Remote sensing Remote sensing (archaeology) Deforestation Warning system Greenhouse gas Environmental science Biodiversity Threatened species Spatial ecology

Subjects

biodiversity conservation, carbon emissions, community‐based forest management, East Africa, global forest watch, human disturbance, Environmental sciences, GE1-350, Botany, QK1-989, RESEARCH ARTICLE, RESEARCH ARTICLES, biodiversity conservation, carbon emissions, community‐based forest management, East Africa, global forest watch, human disturbance, synthetic aperture radar, village land forest reserves, Horticulture, Plant Science, Ecology, Evolution, Behavior and Systematics, Forestry, community-based forest management, community-based forest management, synthetic aperture radar, village land forest reserves, RESEARCH ARTICLE, RESEARCH ARTICLES, life_on_land, climate_action, reduced_inequalities

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