Predicting future land-use change as a planning

tool for biodiversity conservation in the

Cape West Coast Biosphere Reserve, South Africa

Waafeka Vardien

The Cape Floristic Region (CFR)1,2

• Exceptional botanical richness, diversity, and endemism

• Late Cenozoic climatic stability

• 1 of 5 Mediterranean global hotspots

Conservation in the CFR3

• 10 859 km2 conserved– 50% mountain landscapes

– 9% lowlands

• Identified threats: invasive alien species, agriculture, and urbanization

Conservation assessments and land use4,5

• Appropriate measures of biodiversity in conservation planning

• More attention given to species and populations, rather than habitat

• Habitat loss is however, a major biodiversity threat

• The use of a land use classification system has been useful in estimating

habitat loss and risks to biodiversity

• Land use: human modification of natural environment into built environment

• Land use and land management practices impact natural resources

The Cape West Coast Biosphere Reserve (CWCBR)6

• Situated on the southwestern part of the CFR, north of Cape Town

• Rich built environment and cultural heritage

• Includes 18 vegetation types

• Climate is described as arid

• All the rivers in the area are classified as critically endangered

• Urban expansion has been relentless

• Lowland areas are particularly poorly conserved, especially where rare and

threatened species occur

Cape Towns’ major development corridor is northwards

along the CWCBR.

It has been predicted that between 2002 and 2012, the

population of the CWCBR will double.

Due to natural lowland being at risk of destruction, pro-

active conservation planning is essential.

Research objectives

Materials and Methods

• Landsat data acquisition

1990 & 2006GLCF

• Geometric correction

Align & projectENVI 4.5

• Land use detection & classification

IDRISIISODATA algorithm

• Land change modeling

MarkovCA Markov

Land use classes

Natural vegetationAgricultural landWaterbodiesBarren landUrban/ built up land

Verification

Google EarthS.A Land cover data set

Accuracy assessment

Cross tabulationKappa analysis

• Proteaceae species data

Protea Atlas Project

• Distribution• Richness• Diversity

DIVA-GIS 5.2 • Ecological niche modeling

Worldclim data7 Bioclim model

Materials and Methods

Results

Figure 1: Land use maps of (A) 1990 and (B) 2006 of the Cape West Coast Biosphere Reserve.

A. B.

Natural vegetation

Agricultural land

Warebodies

Barren Land

Urban/ built up land

Table 1. Area of land use classes in 1990 and 2006, and percentage change in land use

classes between 1990 and 2006. Percentage change in land use classes are derived from

the difference in area between land classes in 1990 and 2006, divided by the area in 1990.

Figure 2. Net change (in hectares) by land use category, for Cape West Coast Biosphere

Reserve, based on land use maps derived from Landsat TM images of 1990 and 2006.

Natural vegetation

Agricultural land

Waterbodies

Barren land

Urban/ built up

-50000 -40000 -30000 -20000 -10000 0 10000 20000 30000

Net change in hectares

Land

use

cat

egor

y

Figure 3. Predicted land use map of the Cape West Coast Biosphere Reserve, by 2020,

based on Cellular Automaton Markov modeling of a 1990 and 2006 land use map.

Natural vegetation

Agricultural land

Warebodies

Barren Land

Urban/ built up land

Table 2. The spatial extent of land use classes in 1990, 2006 and 2020 and the associated percentage change between 1990 and 2006, and between 2006

and 2020. Values for 2020 are predicted values based on transitional models derived from land use maps of the Cape Wes Coast Biosphere reserve.

Land use class 1990 2006 2020 % change between

1990 & 2006

% change between

2006 & 2020 area (ha) area (ha) area (ha)

Natural vegetation 174444 129843 106527 -25.57 -17.96

Agricultural land 136147 162145 165262 19.10 1.92

Waterbodies 15400 18064 18104 17.30 0.22

Barren land 16292 12200 11269 -25.12 -7.63

Urban/ built up land 6290 26321 47411 318.46 80.13

Table 3. Transitional probability matrix of land use change between 2006 and 2020, based

on a Markov analysis of a 1990 and 2006 land use map of the Cape West Coast Biosphere

Reserve.

Given:

Probability of changing to :

Natural vegetation Agricultural land Waterbodies Barren land Urban/ built up land

Natural vegetation 0.50 0.37 0.00 0.00 0.13

Agricultural land 0.00 0.80 0.00 0.00 0.20

Waterbodies 0.00 0.00 0.94 0.00 0.06

Barren land 0.09 0.50 0.00 0.30 0.11

Urban/ built up land 0.00 0.00 0.00 0.00 1.00

Figure 4. Distribution of Proteaceae species in the zones of the Cape West Coast

Biosphere Reserve, derived from Protea Atlas data.

• Proteaceae species

• Core zone

• Core designated

• Buffer zone

• Transition zone

• Urban area

Figure 5. Number of Proteaceae species, per 10 x 10 km grid cell, in the Cape West Coast Biosphere Reserve.

• Number of species• 1 - 2

• 3 - 4• 5 - 6• 7 - 8• 9 - 11

Figure 6. Proteaceae species diversity in the Cape West Coast Biosphere Reserve.

Brillouin’s index of diversity

0.00 – 0.40.4 – 0.80.8 – 1.21.2 – 1.61.6 - 2.00

Figure 7. Present climatic suitability for Proteaceae species in the Cape West Coast Biosphere Reserve.

Climate suitability

Not suitable

Low (0 – 2.5 percentile)

Medium (2.5 – 5 percentile)

High (5 -10 percentile)

Very high (10 – 20 percentile)

Excellent (20 – 40 percentile)

Climate suitability

Not suitable

Low (0 – 2.5 percentile)

Medium (2.5 – 5 percentile)

High (5 -10 percentile)

Very high (10 – 20 percentile)

Excellent (20 – 40 percentile)

Figure 8. Future climatic suitability for Proteaceae species in the Cape West Coast Biosphere Reserve.

Conclusion

• Between 1990 and 2006: rapid growth in urban development and

destruction of lowland habitat

• Similar patterns predicted, for the future

• With respect to Proteaceae species, zoning of the CWCBR is

inadequate

• In areas with high species concentration: conservation integrity is not

maintained

• Priority conservation areas need to be determined/ improved spatially

• Future study recommendations: usage of higher resolution satellite

images, and other plant/ animal species data

Acknowledgements

I thank the Almighty for granting me my healthand knowledge in undertaking this

project.

A big thanks to my parents and Faqeer Hassem for their words of motivation,

encouragement and support.

I thank Dr. Richard Knight for his supervision with this project.

To James Magidi & Mohammed Kraush thank you for your assistance with IDRISI and

your advice.

Lastly, I wish to thank Audrey King, Linda Van Heerden, and my Honors peers for all

the little bits of favors they have for me throughout the year, and to Professor Mark

Gibbons and the NRF for the funding of my tuition fees.

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Missouri Botanical Garden 89, 281-302.

2. Cowling, R.M., Holmes, P.M., Rebelo, A.G. 1992. Plant diversity and endemism. In: Cowling, R.M. (Ed.).The

Ecology of Fynbos: Fire, Nutrients and diversity. Oxford University Press, Cape Town, pp. 62-112.

3. Conservation International. 2007. Cape Floristic Region. Accessed 25 Nov 2009, available from:

www.biodiversityhotspots

4. Cowling, R.M., Heijnis, C.E. 2001. The identification of broad habitat units as biodiversity entities for

systematic conservation planning in the Cape Floristic Region. South African Journal of Botany 67, 15-38.

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Floristic Region, South Africa—reservation bias and representation of biodiversity patterns and processes.

Biological Conservation 112, 129–145.

6. CWCBR Spatial Development Plan. Draft Status Quo Report. Report 1474/1, prepared for the Cape West

Coast Biosphere Reserve by iKapa Envioplan in association with CLES. 68 p.

7. Hijmans, R.J., Cameron, S., Parra, J.L., Jones P.G., Jarvis A. 2005. Very high resolution interpolated climate

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