Large-scale long-term networks to monitor and understand the changing ecology of tropical forests
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Transcript of Large-scale long-term networks to monitor and understand the changing ecology of tropical forests
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Large-scale long-term networks
to monitor and understand
the changing ecology of tropical forests
Simon L. Lewis
Department of Geography, School of Geography,
University College London, UK University of Leeds, UK
CIFOR, Bogor, Indonesia, 30 Sept 2011
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Changing ecology of tropical forests
• Hypothesis:
– Large-scale and global environmental changes are consistently changing the structure, function, dynamics and composition of otherwise intact and undisturbed tropical forests.
• Therefore need consistent long-term data over large areas.
Lewis et al. 2009 Annual Reviews in Ecology, Evolution & Systematics
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Dja, Cameroon
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Tropical Forest networks
• RAINFOR – PI, Oliver Phillips, U. Leeds – Latin America-focussed, c. 150 locations – Typical monitoring, 1 ha plot, >10 cm dbh monitored
• AfriTRON – PI, Simon Lewis, UCL+U. Leeds – Africa-focussed, c. 130 locations – Typical monitoring, 1 ha plot, >10 cm dbh monitored
• CTFS – PI, Stuart Davies, Smithsonian Institution, USA – Pan-tropical, c. 25 locations – Typical monitoring, 50 ha plot, >1 cm dbh monitored
• TEAM – PI, Sandy Andelman, Conservation International, USA – Pan-tropical, ?? locations (aim is 50) – Typical monitoring, 1 ha plot, >10cm dbh monitored plus other taxa
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Collaboration/partnership
Field data collection
Data entry
Data quality checks
Analysis
Publication of results
Each site
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www.rainfor.org www.afritron.org
www.forestplots.net
Long-term monitoring plot locations, ~1 ha
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www.forestplots.net
Lopez-Gonzalez, Lewis, Burkitt, Phillips 2011. J. Veg. Sci.
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tblBiogeographicalRegion
tblCluster
tblContinent tblCountry
tblForestComposition
tblForestElevation
tblForestStatus
tblPlot
PlotID int
PlotName nvarchar(150)
PlotCode nvarchar(10)
BiogeographicalRegionID int
ClusterID int
SiteID int
CountryID int
Area nvarchar(50)
State nvarchar(50)
Altitude int
LatitudeDecimal float
LongitudeDecimal float
PlotLocationSourceID int
PlotArea float
MinimumDimension float
MaximumDimension float
TotalPlotEdge float
ForestMoistureID int
NearestAntrhopogenicEdgeStart int
FragmentSizeStart int
MinTreeDiameter int
ForestElevationID int
Liana tinyint
LocalClimate tinyint
LocalSoil tinyint
ForestEdaphicID int
ForestCompositionID int
SubstrateGeologyID int
ForestStatusID int
IsSingle tinyint
PartOfLargerPlot tinyint
LargerPlotID int
IsConfirmed tinyint
IsOpenAccess tinyint
IsMetaDataPublic tinyint
ManagerID int
ShapeTypeID int
AreaTypeID int
AveragePlotSlopeID int
LianasDataLocation nvarchar(200)
LocalClimateDataLocation nvarchar(200)
LocalSoilDataLocation nvarchar(200)
TreesUnder100MMSampled tinyint
AllTreesOver100MMSampled tinyint
Column Name Data Type
tblSite
tblForestMoisture
tblForestEdaphic
webUser
tblAveragePlotSlope
tblShapeType
tblPlotMeasurement
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n = 135
2+ census plots in intact closed canopy forest
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• Total 135 plots
• Total 69,593 stems ≥100 mm diameter at initial census
• Total 167 ha monitored
• Mean start monitoring year 1995
• Mean end monitoring year 2005
Mean plot is:
1.2 ha, 515 stems, 9.9 year monitoring period
Basic dataset statistics
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420-2-4-6
25
20
15
10
5
0
Carbon stock change (Mg C ha-1 yr-1)
No
. of
plo
ts
Aboveground C stock change, 79 AfriTRON plots
Lewis et al. 2009, Nature.
Extrapolation to unmeasured tree roots and small trees and scaled to the continent implies a sink of 0.3 Pg C yr-1
Aboveground Carbon Stock change, Africa
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Pan et al. incl. Lewis, 2011, Science
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New pan-tropical biomass map
Saatchi et al. incl. Lewis, White, 2011 PNAS
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Drive DGVM’s with 1980-2000 climate data and CO2,
gives a sink of similar magnitude
Lewis et al. 2009 . Ann. Rev. Ecol. Sys.
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Monitoring in Gabon: Lopé
Mitchard, et al. incl. Lewis, White, in review, Biogeosciences
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1996 2007
2009, Nature), woody encroachment in some savanna areas, and post-logging recovery, partially offset by some degradation (logging) in the North and East of the park.
Conclusion: While the maps are preliminary, they suggest that it is possible, using satellite-based Earth observation instruments coupled with extensive direct on-the-ground measurements of trees, to monitor carbon stocks across whole tropical countries, enabling the quantification of changes in carbon
Aboveground Biomass (Mg ha-1)
The release of the pan-tropical ALOS mosaic in early 2010 should allow this change analysis to be extended to the whole of Gabon.
51 Tg C (1 Tg = 1 million tonnes) in 1996 (±15 Tg C) using JERS. 64 Tg C in 2007 (±16 Tg C) using ALOS
+2.4 tonnes C / ha / yr >1 million T C per year net uptake
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Lessons • Need to invest time in collaborations
• Constant vigilance required to maintain data quality – Simple field sheets
– We use post-docs with a both the training and vested interest in getting it right (some use double-collection)
– Field-team members work in more than one location (for spatial consistency) and over >1 census
• Everything should be modular
• Invest in a database and data management, but keep it simple!
• Deal with IPR and partner expectations from the start
• Needs integrated training/skills development program
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Valuing the Arc
• Monitor and map and value the flow of ecosystem services over the watersheds of the Eastern Arc Mountains, Tanzania
• Integration of several ecosystem services with policy recommendations
• Addresses question of intervention...
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n = 135
2+ census plots in intact closed canopy forest
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Biodiversity
Carbon storage + sequestration
Water
Nature-based tourism
Non-timber forest products
Pollination
Timber
Compiling existing data
Collecting new data
Modelling production, flow, use and value
Exploring scenarios of plausible change
Integrating across services and costs
Deciding focal services
Informing policy
Policy messages Balmford et al. incl. Lewis, unpubl. data
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Tanzania land cover types
5 km resolution for illustration, and 30 classes reduced to 9
Land Cover in Tanzania
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Series of workshops in Tanzania developed a series of ‘rules’ of land use change, e.g.,
• Agriculture expands in areas with:
– suitable soils, rainfall >800mm yr-1, <20 km from roads, expands
from existing agricultural areas.
• More charcoal and/or timber extraction in forested areas closer to
roads
• Some many transitions are not possible, e.g. grassland to forest within
25 yrs
Land-cover in the future Scenarios for 2025:
1. A Hopeful Future Vision (sustainable development) of Land use Change
2. A Less Hopeful Future (Business as Usual) Vision of Land Use Change
Swetman, et al. incl. Lewis, 2011 J. Env. Man
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Hopeful vision
Charcoal extraction steady Pole extraction decreases Timber extraction steady Encroachment of agriculture
Improvements in existing agriculture
Small expansion as woodlands cleared
Steady expansion
Small decreases through degradation & logging, coupled with small scale expansion of plantation forests.
Swetman, et al. incl. Lewis, in review Swetman, et al. incl. Lewis, 2011 J. Env. Man
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2000 Sus. Development 2025 Business as usual 2025
Contrasting scenarios La
nd
co
ver
Ca
rbo
n s
tora
ge
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Present Land Cover
More sustainable Scenario 2025
LOSS 0.02 Pg C
0.5% of 2000 value
Business as Usual Scenario 2025
LOSS 0.2 Pg C
5.1% of 2000 value
3.11 Pg C
Carbon scenarios in 2025
1 Pg = 1 x 1015 g = 1 billion metric tonnes
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Simon L. Lewis [email protected]
Forest plots: Lewis et al. 2009. Ann. Revs. Ecol. Evol. Syst. 40; 529-49. Afritron network: Lewis et al. 2009. Nature, 457, 1003-7. Data: www.forestplots.net