This is to share the short power point on my MSc research - Thesis defense at ITC, NL. It was a 10 minutes presentation, followed by questions from the assessment board. And I got a green card, was a successful defense :)

1. Modelling the abundance and spatial
distribution of mountain gorilla forage
species in the Virunga massif
Prepared by: Providence Akayezu
Thesis Assessment Board:
Dr. I.C. van Duren (1st Supervisor)
Dr. Ir. T.A. Groen (2nd Supervisor)
Dr. Y.A.Hussin (Chair)
Dr. Ir. R.A. (Rolf) de By (Eternal Examiner, ITC-GIP)
MSc. Thesis defense
01 March 2016

2. 1. Research problem
Mountain gorillas (G. beringei beringei)
and their food species
Suitable habitat
Growing population
Herbivorous
Conservation Encroachment
Climate change
Study area

3. 2. Datasets
Systematic sampling:
Braun-Blanquet scores for
food species abundance.
Random stratified
sampling for food
species biomass:
• Measure the stem length
• Harvest leaves and weigh
• Sundry
• Weigh until there is no
loss of weight.
1
2
1
94 plots 956 plots

4. 3. Significant difference in gorilla food
species abundance or biomass between
vegetation types
Vegetation
types
Gorilla food
species
abundance
/biomass
• ANOVA test
• Games-Howell pairwise
comparison
• F statistics,
• p value,
• Significant
groups
Herbaceous Hagenia
Alpine
Hypericum Neoboutonia
Bamboo & herbaceous
H1: There is a significant difference in
individual gorilla food species abundance
or biomass between vegetation types

5. 4. Relationship between gorilla food species
abundance/biomass and:
o Forest structure/topography variables
o Vegetation indices
Gorilla food
species
abundance
/biomass
Field variables
• Tree height
• Stem density
• Tree canopy
GIS and RS variables
• Vegetation indices
• Slope
• Northness
• Eastness
• Elevation
• Solar radiation
(Multiple) Linear Regression
R-square, F statistics,
p value
H1: Gorilla food species abundance/biomass increases in higher elevations,
west-facing slopes and small tree densities.
H1: The abundance/biomass of
gorilla food species is better
explained by NDVI than EVI2.

6. 5. Mapping the forest canopy cover from
Aster imagery band reflectance
Nine Aster
bands
reflectance
values
Field
measured
forest canopy
Stepwise Multiple Linear
Regression
R-square, p
value
Forest
canopy
cover map
H1: There is a significant positive relationship between
the forest canopy cover and the Aster imagery band
reflectance values.

7. 6. Modelling the distribution of five most
preferred gorilla food species
Species distribution modelling :
BRT
Five SDM
maps
Predictor variables
Species locations
H1: The BRT model can discriminate
gorilla food species presence/absence
with an accuracy greater than random
guess.

8. 7. Results: Significant difference in gorilla food species
abundance/biomass between vegetation types

9. Results: Relating gorilla food species abundance/biomass
and forest structure/topography variables

10. Results: Relationship between gorilla food species
abundance/biomass and vegetation indices

11. Results: Forest canopy cover

12. Results: Five gorilla food species distribution maps
AUC=0.78
AUC=0.65
AUC=0.80
AUC=0.77
AUC=0.72

13. 8.Conclusion
 The ANOVA and stepwise regression were mainly significant for
dataset 2.
 The Aster imagery poorly predicted the Virunga forest canopy.
 The EVI2 predicted gorilla species abundance than NDVI for dataset1;
but lower variance explained by the model.
 The BRT model performed with a reasonable accuracy (AUC> 0.70)
for four species and an AUC= 0.65 for one species.
 Most important predictors: elevation, eastness, slope, solar radiation,
vegetation types and forest canopy
 Galium spp. and Rubus spp. predicted to occur in elevations greater
than 3,500 m.
 P. linderi, L. alatipes and C. nyassanus lower probabilities of
occurrence in elevations greater than 3,500 m.