This presentation examines the changing ecology of tropical forests and the effect that this has on maintaining data quality when it comes to monitoring large-scale sites over time. Some lessons learned are also outlined. This presentation formed part of the CRP6 Sentinel Landscape planning workshop held on 30 September – 1 October 2011 at CIFOR’s headquarters in Bogor, Indonesia. Further information on CRP6 and Sentinel Landscapes can be accessed from http://www.cifor.org/crp6/ and http://www.cifor.org/fileadmin/subsites/crp/CRP6-Sentinel-Landscape-workplan_2011-2014.pdf respectively.

1. 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 201

2. 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

3. Dja, Cameroon

4. 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

5. Each site
Collaboration/partnership
Field data collection
Data entry
Data quality checks
Analysis
Publication of results

6. Long-term monitoring plot locations, ~1 ha
www.rainfor.org
www.afritron.org
www.forestplots.net

7. www.forestplots.net
Lopez-Gonzalez, Lewis, Burkitt, Phillips 2011. J. Veg. Sci.

10. tblPlot
Column Name Data Type
PlotID int
PlotName nvarchar(150)
tblBiogeographicalRegion PlotCode nvarchar(10)
BiogeographicalRegionID int tblForestEdaphic
ClusterID int
SiteID int
CountryID int tblForestMoisture
tblCluster
Area nvarchar(50)
State nvarchar(50)
Altitude int
tblForestElevation
tblSite LatitudeDecimal float
LongitudeDecimal float
tblForestComposition
PlotLocationSourceID int
PlotArea float
MinimumDimension float
tblForestStatus
MaximumDimension float
tblContinent tblCountry TotalPlotEdge float
ForestMoistureID int
NearestAntrhopogenicEdgeStart int
tblAveragePlotSlope
FragmentSizeStart int
webUser
MinTreeDiameter int
ForestElevationID int
Liana tinyint
LocalClimate tinyint
tblShapeType
LocalSoil tinyint
ForestEdaphicID int
ForestCompositionID int
SubstrateGeologyID int
ForestStatusID int
IsSingle tinyint
tblPlotMeasurement
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

11. 2+ census plots in intact closed canopy forest
n = 135

12. Basic dataset statistics
• 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

13. Aboveground Carbon Stock change, Africa
Aboveground C stock change, 79 AfriTRON plots
25 Extrapolation to
unmeasured tree
20 roots and small
No. of plots
15 trees and scaled
to the continent
10 implies a sink of
5 0.3 Pg C yr-1
0
-6 -4 -2 0 2 4
Carbon stock change
(Mg C ha-1 yr-1)
Lewis et al. 2009, Nature.

14. Pan et al. incl. Lewis, 2011, Science

15. New pan-tropical biomass map
Saatchi et al. incl. Lewis, White, 2011 PNAS

16. Drive DGVM’s with 1980-2000 climate data and CO2,
gives a sink of similar magnitude
Lewis et al. 2009 . Ann. Rev. Ecol. Sys.

17. Monitoring in Gabon: Lopé
Mitchard, et al. incl. Lewis, White, in review, Biogeosciences

18. 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.
51 Tg C (1 Tg = 1 million
tonnes)of the pan-tropical Tg C)
The release
in 1996 (±15
using JERS.analysis should
ALOS mosaic in early 2010
allow this change to be
64 Tg C in 2007 (±16 Tg C)
extended to the whole of Gabon.
using ALOS
Aboveground 1996 2007
Biomass
(Mg ha-1)
>1 million T C per yearcoupled uptake suggest that it is possible, using satellite-based Earth / yr
Conclusion: While the maps are preliminary, they
+2.4 tonnes C / ha
observation instruments net with extensive direct on-the-ground measurements of trees, to

19. 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

20. 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...

21. 2+ census plots in intact closed canopy forest
n = 135

22. Deciding focal services
Compiling existing data
Collecting new data
Modelling production,
flow, use and value
Exploring scenarios of
plausible change
Non-timber forest
Integrating across
products
Timber Nature-based
services and costs
Informing policy
tourism
Carbon storage +
sequestration Pollination
Biodiversity
Water
Policy
messages Balmford et al. incl. Lewis, unpubl. data

23. Land Tanzania land
Cover in Tanzania
cover types
5 km resolution for
illustration, and 30
classes reduced to 9

24. 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
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
Swetman, et al. incl. Lewis, 2011 J. Env. Man

25. Hopeful vision
Charcoal extraction steady
Pole extraction decreases
Timber extraction steady
Encroachment of agriculture
Improvements in
existing agriculture
Small decreases through
degradation & logging,
coupled with small scale
Small expansion as expansion of plantation
Steady expansion
woodlands cleared forests.
Swetman, et al. incl. Lewis, 2011 J. Env. Man
Swetman, et al. incl. Lewis, in review

26. Contrasting scenarios
2000 Sus. Development 2025 Business as usual 2025
Land cover
Carbon storage

27. Carbon scenarios in 2025
Present More sustainable Business as Usual
Land Cover Scenario 2025 Scenario 2025
3.11 Pg C
LOSS LOSS
0.02 Pg C 0.2 Pg C
0.5% of 2000 value 5.1% of 2000 value
1 Pg = 1 x 1015 g = 1 billion metric tonnes

28. Simon L. Lewis
s.l.lewis@leeds.ac.uk
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