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

Antje Ahrends*, Mark T. Bulling, Philip J. Platts, Ruth Swetnam, Casey Ryan, Nike Doggart, Peter M. Hollingsworth, Robert Marchant, Andrew Balmford, David J. Harris, Nicole Gross-Camp, Peter Sumbi, Pantaleo Munishi, Seif Madoffe, Boniface Mhoro, Charles Leonard, Claire Bracebridge, Kathryn Doody, Victoria Wilkins, Nisha OwenAndrew R. Marshall, Marije Schaafsma, Kerstin Pfliegner, Trevor Jones, James Robinson, Elmer Topp-Jørgensen, Henry Brink, Neil D. Burgess

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

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.

Original languageEnglish
Pages (from-to)268-281
Number of pages14
JournalPlants, People, Planet
Volume3
Issue number3
Early online date27 Apr 2021
DOIs
Publication statusPublished - May 2021

Bibliographical note

Special Issue: Plants, people and long‐term ecological monitoring plots.

Funding Information:
We are very grateful for the contributions of extensive data from Frontier Tanzania, the Tanzanian Forest Conservation Group, WWF Tanzania, the Forestry and Beekeeping Division of the Ministry of Natural Resources and Tourism, the Sokoine University of Agriculture and the University of Dar es Salaam. We would like to thank the many volunteers and data collectors working for these institutions between 1996 and 2010. Permissions for fieldwork were provided by the Tanzanian Commission for Science and Technology. Funding was provided inter alia by the Darwin Initiative (grant 25-019), the Global Environment Facility, Marie Curie Actions (grant MEXT-CT-2004-517098 to R.M.), the Leverhulme Trust's Valuing the Arc grant to A.B. (P.J.P., R.S.), the Critical Ecosystem Partnership Fund, and the Governments of Finland and Denmark. The Royal Botanic Garden Edinburgh is supported by the Scottish Government's Rural and Environment Science and Analytical Services Division.

Funding Information:
We are very grateful for the contributions of extensive data from Frontier Tanzania, the Tanzanian Forest Conservation Group, WWF Tanzania, the Forestry and Beekeeping Division of the Ministry of Natural Resources and Tourism, the Sokoine University of Agriculture and the University of Dar es Salaam. We would like to thank the many volunteers and data collectors working for these institutions between 1996 and 2010. Permissions for fieldwork were provided by the Tanzanian Commission for Science and Technology. Funding was provided by the Darwin Initiative (grant 25‐019), the Global Environment Facility, Marie Curie Actions (grant MEXT‐CT‐2004‐517098 to R.M.), the Leverhulme Trust's Valuing the Arc grant to A.B. (P.J.P., R.S.), the Critical Ecosystem Partnership Fund, and the Governments of Finland and Denmark. The Royal Botanic Garden Edinburgh is supported by the Scottish Government's Rural and Environment Science and Analytical Services Division. inter alia

Publisher Copyright:
© 2021 The Authors. Plants, People, Planet © New Phytologist Foundation.

Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.

Keywords

  • biodiversity conservation
  • carbon emissions
  • community-based forest management
  • East Africa
  • global forest watch
  • human disturbance
  • synthetic aperture radar
  • village land forest reserves

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