Ecosystem Services in Urbanizing South Africa

Scott M. Beck & Melissa R. McHale

NC State University | Department of Forestry & Environmental Resources

Center for Geospatial Analytics

Tools & Methods to Assess & Map ES with Communities

Urbanization - Bushbuckridge Local Municipality

Rural Urban: Migration to Small

Towns, Rural Re-Classified as Urban

Urbanization in Africa: Urban Land

Area Increase 12x

BBR: Development Pressure

Census 2011: 151 Settlements;

541,248 People

BBR Local Municipality: >1 million

people

Mapping Biodiversity for Decision Making

SANBI Biodiversity Land Use Decision Support Tool Protected

Important

Highly

Significant

Irreplaceable

Least

Concern

No Natural

Habitat

Mapping Ecosystem Services for Decision Making

Built Up & Degraded Other Essential ES Natural

Democratization of Ecosystem Services

Perceptions &

Values:

Walking

Interviews

Qualitative

Content Analysis

Categorization &

Binning

Ecosystem

Structure:

High Resolution

Land Cover

Classification

Village Clustering

Parcel to Village

Scale Analysis

Perceptions and Values

Governance, Policy, Planning

HUMAN SYSTEM

Ecosystem Structure

Ecosystem Processes

NATURAL SYSTEM

A New Multidimensional Ecosystem Services

Assessment

Capture Heterogeneity

26 Walking Interviews in 3 Villages

Qualitative Spatial Database

Ecosystem Services are Identified &

Quantified as Benefits or Burdens of

Natural Features

What ES Do Communities Value,

Where are the ES Located & What

are their Associated Land Covers?

Human System Perceptions and Values

Marula Tree – Fruits, Shade,

Protection from Wind,

Spiritual/Religious

High SES, Owns Cows, Employed,

Buys Fuelwood, Uses Electricity

• Spiritual

• Medicinal

• Aesthetic

• Gathering Space

• Crafting

• Cultivated Food

• Wild Fruits

• Fuelwood

• Building Wood

• Soil Forming

• Air Quality

• Shade

• Wind Protection

• Soil Retention

• Lightning Protection

Supporting Services

Regulating Services

Cultural Services

Provisioning Services

100% of HH 34.62% of HH

100% of HH 100% of HH

PARCEL SCALE ECOSYSTEM SERVICES

• Recreational

• Medicinal

• Aesthetic

• Generational Knowledge

• Cultivated Food

• Wild Fruits

• Fuelwood

• Wood Building

• Building Soil

• Domestic Grazing

• Wild Game

• Soil Conditioning

• Wind Protection

Supporting

Regulating

Cultural Provisioning

80.77% of HH

15.38% of HH 3.58% of HH

53.85% of HH

COMMUNAL LAND ECOSYSTEM SERVICES

SANBI

Biodiversity

Decision

Support Tool

Two Cover

Types:

1) Least

Concern

2) No Natural

Habitat

SA National Land

Use/Cover Dataset

6 LUC Types in

Developed

Areas:

1) Urban Village

2) Urban Township

(bare)

3) Thicket

4) Urban

Commercial

5) Urban Built up

6) Village (Low Veg

Grass)

Ecosystem Structure: Base Data is Critical

High Resolution (1m)

Object Oriented Land

Cover Dataset

Seven Cover Types:

1) Coarse Vegetation

2) Water

3) Pavement

4) Unpaved Roads

5) Buildings /

Structures

6) Fine Vegetation

7) Bare Earth

Village Scale Tree Cover

Typology & Location

(e.g. Pop, Size, Lat, Lon)

Parcel Scale Tree Cover

ES Location Demand

(e.g. Parcel vs. Communal)?

Welverdiend

Village & Parcel Scale Tree Cover

Coarse Veg Cover

% C

oar

se V

eg C

ove

r

Sabi Sand Reserve

Kruger National Park

Spatial Patterns at Village Scale

% Coarse

Vegetation

Village Location Coarse Vegetation %

Geographic Position Tree Cover: Environmental Factors (e.g. Rainfall, Topography)

High Variation Other Drivers of Tree Cover

Village Typologies & Clustering:

Hierarchical Cluster Analysis: 3 Categories of Villages

Large Villages w/ High Pop Most Tree Cover

High Variation Other Demographic & Morphological Drivers T

ree C

over

(%)

Village Cluster Type

Large High Pop

Informal

Medium

Small, Low

Vegeta

tion (

% C

over)

Cover Dynamics & ES Values:

Isolated Villages Dependent on Communal : Less Tree Cover on Parcels

Villages Near Town Dependent on Parcel : More Tree Cover on Parcels

Welverdiend Hluvukani Timbavati

# R

espondents

Welverdiend

Hluvukani

Timbavati

Average Tree Cover % - Parcels

Dis

tance f

rom

Tow

n

What Now?

Conduct Survey’s Across the Full Range of Village Typologies

Integrate Social-Ecological Data to Map Parcel Scale ES

Identify Trends in ES Demand at Various Scales

Use Agent Based Modeling

Explore Feedbacks between ES Supply and Demand

Predict Future Availability of ES

ES Critical for Planning, Spatially Complex, Heterogeneity,

Community Input Necessary

Acknowledgements

PEOPLE:

David N. Bunn - University of the Witwatersrand

Mary L. Cadenasso - UC Davis

Dan Childers - Arizona State University

Colleen Cluett - OTS

Liesel Ebersohn - University of Pretoria

Ross K. Meentemeyer - NC State University

Steward T.A. Pickett - Cary Institute for Ecosystem Studies

Louie Rivers III - NC State University

Louise Swemmer - SANParks

Wayne Twine - University of the Witwatersrand

ORGANIZATIONS:

NC State Center for Geospatial Analytics

NC State Department of Forestry & Environmental

Resources

Wits University Knowledge Hub for Rural

Development

South African National Parks

Bushbuckridge Local Municipality

Plowback to the Community