Limits...
Will Passive Protection Save Congo Forests?

Galford GL, Soares-Filho BS, Sonter LJ, Laporte N - PLoS ONE (2015)

Bottom Line: We estimate the Historical Trends trajectory will result in average emissions of 139 million t CO2 year-1 by the 2040s, a 15% increase over current emissions.The Conservation scenario would result in 58% less clearing than Historical Trends and would conserve carbon-dense forest and woodland savanna areas.Our results suggest that 1) passive protection of the DRC's forest and woodland savanna is insufficient to reduce deforestation; and 2): enactment of a REDD+ plan or similar conservation measure is needed to actively protect Congo forests, their unique ecology, and their important role in the global carbon cycle.

View Article: PubMed Central - PubMed

Affiliation: The Gund Institute for Ecological Economics, University of Vermont, 617 Main Street, Burlington, Vermont, 05405, United States of America.

ABSTRACT
Central Africa's tropical forests are among the world's largest carbon reserves. Historically, they have experienced low rates of deforestation. Pressures to clear land are increasing due to development of infrastructure and livelihoods, foreign investment in agriculture, and shifting land use management, particularly in the Democratic Republic of Congo (DRC). The DRC contains the greatest area of intact African forests. These store approximately 22 billion tons of carbon in aboveground live biomass, yet only 10% are protected. Can the status quo of passive protection - forest management that is low or nonexistent - ensure the preservation of this forest and its carbon? We have developed the SimCongo model to simulate changes in land cover and land use based on theorized policy scenarios from 2010 to 2050. Three scenarios were examined: the first (Historical Trends) assumes passive forest protection; the next (Conservation) posits active protection of forests and activation of the national REDD+ action plan, and the last (Agricultural Development) assumes increased agricultural activities in forested land with concomitant increased deforestation. SimCongo is a cellular automata model based on Bayesian statistical methods tailored for the DRC, built with the Dinamica-EGO platform. The model is parameterized and validated with deforestation observations from the past and runs the scenarios from 2010 through 2050 with a yearly time step. We estimate the Historical Trends trajectory will result in average emissions of 139 million t CO2 year-1 by the 2040s, a 15% increase over current emissions. The Conservation scenario would result in 58% less clearing than Historical Trends and would conserve carbon-dense forest and woodland savanna areas. The Agricultural Development scenario leads to emissions of 212 million t CO2 year-1 by the 2040s. These scenarios are heuristic examples of policy's influence on forest conservation and carbon storage. Our results suggest that 1) passive protection of the DRC's forest and woodland savanna is insufficient to reduce deforestation; and 2): enactment of a REDD+ plan or similar conservation measure is needed to actively protect Congo forests, their unique ecology, and their important role in the global carbon cycle.

No MeSH data available.


Deforestation extent under the Historical Trends, Conservation (including development of new protected areas based on population density and carbon in aboveground biomass), and Agricultural Development scenarios (including deforestation for croplands and oil palm).
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pone.0128473.g003: Deforestation extent under the Historical Trends, Conservation (including development of new protected areas based on population density and carbon in aboveground biomass), and Agricultural Development scenarios (including deforestation for croplands and oil palm).

Mentions: Across all scenarios, deforestation is simulated to occur in 25–30% of the DRC by 2050, producing a total deforested area of 0.5 to 0.7 million km2 (Table 4). In all scenarios, deforestation is greatest near areas with high population densities, roads, rivers and areas of median biomass. Under HT (Fig 3), annual deforestation rates are estimated to reach 2,065 km2 year-1 by the final decade of the study. By comparing the CON (Fig 3) and HT scenarios, we find that by shifting population densities to favor lower density in rural areas, 58% less clearing is achieved. In the CON scenario, annual deforestation rates average 800 km2 year-1 by the 2040s. In the AD scenario, vast areas in close proximity to roads are used for deforestation once there are no limits to forest access (AD, Fig 3). In this scenario, annual average deforestation rates reached 5,393 km2 year-1 in the 2040s. In all scenarios, deforestation is largely driven by proximity to rivers, roads and previously deforested lands.


Will Passive Protection Save Congo Forests?

Galford GL, Soares-Filho BS, Sonter LJ, Laporte N - PLoS ONE (2015)

Deforestation extent under the Historical Trends, Conservation (including development of new protected areas based on population density and carbon in aboveground biomass), and Agricultural Development scenarios (including deforestation for croplands and oil palm).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4481311&req=5

pone.0128473.g003: Deforestation extent under the Historical Trends, Conservation (including development of new protected areas based on population density and carbon in aboveground biomass), and Agricultural Development scenarios (including deforestation for croplands and oil palm).
Mentions: Across all scenarios, deforestation is simulated to occur in 25–30% of the DRC by 2050, producing a total deforested area of 0.5 to 0.7 million km2 (Table 4). In all scenarios, deforestation is greatest near areas with high population densities, roads, rivers and areas of median biomass. Under HT (Fig 3), annual deforestation rates are estimated to reach 2,065 km2 year-1 by the final decade of the study. By comparing the CON (Fig 3) and HT scenarios, we find that by shifting population densities to favor lower density in rural areas, 58% less clearing is achieved. In the CON scenario, annual deforestation rates average 800 km2 year-1 by the 2040s. In the AD scenario, vast areas in close proximity to roads are used for deforestation once there are no limits to forest access (AD, Fig 3). In this scenario, annual average deforestation rates reached 5,393 km2 year-1 in the 2040s. In all scenarios, deforestation is largely driven by proximity to rivers, roads and previously deforested lands.

Bottom Line: We estimate the Historical Trends trajectory will result in average emissions of 139 million t CO2 year-1 by the 2040s, a 15% increase over current emissions.The Conservation scenario would result in 58% less clearing than Historical Trends and would conserve carbon-dense forest and woodland savanna areas.Our results suggest that 1) passive protection of the DRC's forest and woodland savanna is insufficient to reduce deforestation; and 2): enactment of a REDD+ plan or similar conservation measure is needed to actively protect Congo forests, their unique ecology, and their important role in the global carbon cycle.

View Article: PubMed Central - PubMed

Affiliation: The Gund Institute for Ecological Economics, University of Vermont, 617 Main Street, Burlington, Vermont, 05405, United States of America.

ABSTRACT
Central Africa's tropical forests are among the world's largest carbon reserves. Historically, they have experienced low rates of deforestation. Pressures to clear land are increasing due to development of infrastructure and livelihoods, foreign investment in agriculture, and shifting land use management, particularly in the Democratic Republic of Congo (DRC). The DRC contains the greatest area of intact African forests. These store approximately 22 billion tons of carbon in aboveground live biomass, yet only 10% are protected. Can the status quo of passive protection - forest management that is low or nonexistent - ensure the preservation of this forest and its carbon? We have developed the SimCongo model to simulate changes in land cover and land use based on theorized policy scenarios from 2010 to 2050. Three scenarios were examined: the first (Historical Trends) assumes passive forest protection; the next (Conservation) posits active protection of forests and activation of the national REDD+ action plan, and the last (Agricultural Development) assumes increased agricultural activities in forested land with concomitant increased deforestation. SimCongo is a cellular automata model based on Bayesian statistical methods tailored for the DRC, built with the Dinamica-EGO platform. The model is parameterized and validated with deforestation observations from the past and runs the scenarios from 2010 through 2050 with a yearly time step. We estimate the Historical Trends trajectory will result in average emissions of 139 million t CO2 year-1 by the 2040s, a 15% increase over current emissions. The Conservation scenario would result in 58% less clearing than Historical Trends and would conserve carbon-dense forest and woodland savanna areas. The Agricultural Development scenario leads to emissions of 212 million t CO2 year-1 by the 2040s. These scenarios are heuristic examples of policy's influence on forest conservation and carbon storage. Our results suggest that 1) passive protection of the DRC's forest and woodland savanna is insufficient to reduce deforestation; and 2): enactment of a REDD+ plan or similar conservation measure is needed to actively protect Congo forests, their unique ecology, and their important role in the global carbon cycle.

No MeSH data available.