AAG 2010 Washington DC

Savanna Vegetation Changes as Influenced by Climate in East Africa

Gopal Alagarswamy, Chuan Qin, Jiaguo Qi, Jeff Andresen, Jennifer Olson and

Nathan Moore

Biocomplexity in the Environment Award 0709671

AAG 2010 Washington DC

The EACLIPSE Loop

Climate Change

Land Management

Savanna Vegetation

Livelihood Systems

AAG 2010 Washington DC

Goal of savanna vegetation modeling• What is physical relation between climate and

vegetation? • What shifts in vegetation and changes of grass

production are likely to occur in future?• How will vegetation changes influence livelihood

systems that depend on livestock and savanna natural resources?

AAG 2010 Washington DC

Activities

1. Simulate relation between current climate and savanna vegetation production using ecosystem model Century (Parton et al., 1992) and historical gridded climate data from WorldClim(1950-2000: WorldClim – Hijmans et al., 2005) (18km and 6 km).

2. Validate ecosystem model Century using remotely sensed net primary productivity (NPP).

3. Project vegetation (grass, bush, trees) changes in the future based on projected climate from RAMS.

Land Cover of Case Study Sites

Mt. Kenya

Satellite picture of Mount Kenya

Classes

Forest

Savanna

Water Bodies

Agriculture

AAG 2010 Washington DC

Grass Biomass (g/m2)

Unsuitable for vegetation

75 - 150

151 - 225

226 - 300

301 - 375

376 - 450

Grass Biomass as Simulated by the Century Model in the Northern Site

AAG 2010 Washington DC

Validating Century Model to simulate biomass (as NPP)

• Need measured NPP data over large area to validate Century model.

• Field measurements of NPP data over large areas are scarce in the study area.

• Can we use remotely sensed NPP data to validate the Century model?

AAG 2010 Washington DC

Comparison of NPP between Century and MODIS

Century NPP MODIS NPP

Grass Biomass (g/m2)

Unsuitable for vegetation

75 - 150

151 - 225

226 - 300

301 - 375

376 - 450

gC/m2

1441 - 1800

1081 - 1440

721 - 1080

Unsuitable for Vegetation

140 - 360

361 - 720

MODIS/ Century NPP Correlation

2010 AAG Washington, D.C.

– CENTURY and MODIS NPP are generally correlated with each other.

– However, the magnitude of MODIS NPP is much larger than the CENTURY NPP.

– WHY?

Validation Steps

1. Compare CENTURY and MODIS grassland NPP of pixels

– Using Landcover data: GlobCover 2005.– Problem: Other plant species contribute to NPP.

2. Calculate grassland-only MODIS NPP– CENTURY Assumption: Whole pixel is covered by

grassland.– remotely sensed NPP of a pixel is explained by:

2010 AAG Washington, D.C.

Summary of Validation

• CENTURY Model can be validated using R.S. data and be used to simulate grass biomass.

2010 AAG Washington, D.C.

AAG 2010 Washington DC

Relative change in grass biomass from 2000 to 2050

AAG 2010 Washington DC

Conclusion

1. Century does satisfactory job of estimating NPP

2. Remotely sensed NPP can be used to validate Century Model.

3. Impact of climate change on NPP varies widely across study area.

AAG 2010 Washington DC

Next steps

1. Simulate NPP at higher resolution (6 km) and use additional GCMs.

2. Simulate NPP of other vegetation types (bush, trees, and crops).

3. Link vegetation modeling results to field data results to assess the influence of climate on the livelihood systems.

The EACLIPSE Loop

Climate Change•Temperature•Precipitation•Droughts•Floods

SavannaVegetation

Local level•Ecosystem structure ( spp., composition, ratio woody/ herbaceous)•Forage quant & quality (palatability)

Regional level•Length of growing period•Ecosystem structure•Productivity

Temporal & spatial lag effects, non -linear response. Resilience to droughts

Land ManagementGrazing Scale:• Intensity• Mobility - Household• Length of Orbit - CommunityFire Frequency - RegionalLand Use

Livelihood Systems

- Non-farm

- Crops

- Livestock

Income diversification strategies within dynamic socio -economic system .Household Level decisions on: herd size and composition, grazing strategy, drought response

Landscape Level : fire frequency, land use conversion

Figure 1. The savanna human-land-climate system loop.

Research issues, questions

1. Seasonality shifts: The impact of highly variable and changing rainy seasons on natural vegetation, agriculture, people and livestock. Questions of recovery time of different vegetation types, flexibility of livestock & cropping.

2. Droughts: How will livelihood systems changes as short-term drought coping strategies evolve to long-term climate change adaptation?

AAG 2010 Washington DC

Land cover Composition

• Those categories contain grassland, but they also have portion of other species.

• Thus NPP still includes influence from forest or shrubland.

• Since forest or shrubland normally have higher NPP than grassland, the grassland NPP here was overestimated.

1 Rainfed cropland 2 Mosaic cropland(50-70%)/vegetation3 Mosaic vegetation(50-70%)/cropland4 Forest 5 Mosaic forest or shrubland(50-70%)/grassland

6 Mosaic grassland(50-70%)/forest or shrubland7 Closed to open Shrubland8 Closed to open grassland9 Sparse vegetation 10 Bare areas 11 Water bodies

AAG 2010 Washington DC

Grassland-only NPP

• CENTURY assume a pixel is covered only by grassland.• While, remotely sensed NPP of a pixel is:

where n is the number of land cover types; NPPEndmember (i) is the NPP of pure pixel covered by landcover type i.

• Our objective is to get NPPEndmember-grassland in each pixel, which is the actual grassland NPP if the whole pixel is grassland.

( ) ( )0 0

*n n

Total i Endmember i LandCover ii i

NPP NPP NPP Percentage