Predictable waves of sequential forest degradation and biodiversity loss spreading from an African city

TY - JOUR

T1 - Predictable waves of sequential forest degradation and biodiversity loss spreading from an African city

AU - Ahrends, A.

AU - Burgess, N.D.

AU - Milledge, S.A.H.

AU - Bulling, M.T.

AU - Fisher, B.

AU - Smart, James Christopher Rudd

AU - Clarke, G.P.

AU - Mhoro, B.E.

AU - Jensen Lewis, Marie-Louise

PY - 2010/8/17

Y1 - 2010/8/17

N2 - Tropical forest degradation emits carbon at a rate of ∼0.5 Pg·y-1, reduces biodiversity, and facilitates forest clearance. Understanding degradation drivers and patterns is therefore crucial to managing forests to mitigate climate change and reduce biodiversity loss. Putative patterns of degradation affecting forest stocks, carbon, and biodiversity have variously been described previously, but these have not been quantitatively assessed together or tested systematically. Economic theory predicts a systematic allocation of land to its highest use value in response to distance from centers of demand. We tested this theory to see if forest exploitation would expand through time and space as concentric waves, with each wave targeting lower value products. We used forest data along a transect from 10 to 220 km from Dar es Salaam (DES), Tanzania, collected at two points in time (1991 and 2005). Our predictions were confirmed: high-value logging expanded 9 km·y-1, and an inner wave of lower value charcoal production 2 km·y-1. This resource utilization is shown to reduce the public goods of carbon storage and species richness, which significantly increased with each kilometer from DES [carbon, 0.2 Mg·ha-1; 0.1 species per sample area (0.4 ha)]. Our study suggests that tropical forest degradation can be modeled and predicted, with its attendant loss of some public goods. In sub-Saharan Africa, an area experiencing the highest rate of urban migration worldwide, coupled with a high dependence on forest-based resources, predicting the spatiotemporal patterns of degradation can inform policies designed to extract resources without unsustainably reducing carbon storage and biodiversity.

AB - Tropical forest degradation emits carbon at a rate of ∼0.5 Pg·y-1, reduces biodiversity, and facilitates forest clearance. Understanding degradation drivers and patterns is therefore crucial to managing forests to mitigate climate change and reduce biodiversity loss. Putative patterns of degradation affecting forest stocks, carbon, and biodiversity have variously been described previously, but these have not been quantitatively assessed together or tested systematically. Economic theory predicts a systematic allocation of land to its highest use value in response to distance from centers of demand. We tested this theory to see if forest exploitation would expand through time and space as concentric waves, with each wave targeting lower value products. We used forest data along a transect from 10 to 220 km from Dar es Salaam (DES), Tanzania, collected at two points in time (1991 and 2005). Our predictions were confirmed: high-value logging expanded 9 km·y-1, and an inner wave of lower value charcoal production 2 km·y-1. This resource utilization is shown to reduce the public goods of carbon storage and species richness, which significantly increased with each kilometer from DES [carbon, 0.2 Mg·ha-1; 0.1 species per sample area (0.4 ha)]. Our study suggests that tropical forest degradation can be modeled and predicted, with its attendant loss of some public goods. In sub-Saharan Africa, an area experiencing the highest rate of urban migration worldwide, coupled with a high dependence on forest-based resources, predicting the spatiotemporal patterns of degradation can inform policies designed to extract resources without unsustainably reducing carbon storage and biodiversity.

KW - biodiversity conservation

KW - carbon emissions

KW - reducing emissions from deforestation and forest degradation sustainability

KW - tropical forest degradation

KW - GREENHOUSE-GAS EMISSIONS

KW - TROPICAL FORESTS

KW - BRAZILIAN AMAZON

KW - LAND-USE

KW - DEFORESTATION

KW - MANAGEMENT

KW - RESOURCES

KW - ECONOMICS

KW - TANZANIA

KW - IMPACTS

U2 - 10.1073/pnas.0914471107

DO - 10.1073/pnas.0914471107

M3 - Journal article

C2 - 20679200

SN - 0027-8424

VL - 107

SP - 14556

EP - 14561

JO - Proceedings of the National Academy of Sciences of the United States of America

JF - Proceedings of the National Academy of Sciences of the United States of America

IS - 33

ER -