Hierarhcies, scales and desertification

8/3/2019 Hierarhcies, scales and desertification

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,

Thomas Theis Nielsen

3rd international conference on

Drylands, Deserts and Desertification

Ben Gurion University of the Negevovem er 08, 2010

Department of Environmental,Social and Spatial Change


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Dynamic causal patterns of desertification, Bioscience;54, 9 Meta study research design

132 cases included in total, 42 in Africa

Site in human use no wilderness In depth field investigation Quantitative data for rate assessment No obvious biases

Geist & Lambin are not trying to

establish wether or not desertification isoccurr ng, u o nves ga e w y soccurring. Hence an unstated onthologythat desertification is real and can be


measured at any given level.


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Dynamic causal patterns of

desertification

Broad underlying driving forces

1. Demographic factors 1. A ricultural activities2. Economic factors3. Technological factors4. Climatic factors

2. Infrastructure extension3. Wood extraction

5. Policy and institutional factors6. Cultural factors

.

Specific proximate causes

1. Livestock production (76%)2. Annual cropping (40%)3. Climatic variability (64%)4. Increased rainfall deficit (57%)



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Demo ra h Econom Technolo Institutional Cultural Climatic

Local

Regional

National

Global

Individual scales Cross scalar interactions

Geist & Lambin comments that: Some factors intervene in the interplay of,are important at the same hierarchical level of organization (p 825)



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A set of governing principles withinwhich it has an array of optoins of

Global HOLON

possible responses.

Fundamentally asymetrical and holonsat higher levels are generally less

affected by changes in lower level than

National HOLON

v ce versa

Many geographers would argue

HOLON

these due to the inherent properties of

these terms and labels



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Heterogenous surfaces may be less wellpresented than very homogeneous ones

Different enerations have different

8 km resolution

characteristics and sensors degrade in time

-

Bi-monthly coverage MVC NDVI

to 2 images per months in order to reducenoise and atmospheric contamination

Fully geo-referenced

Coverage from 1982

Arguments for and against the use of NDVI,especially soil signals and canopy cover.

Only consistent data source offering longterm data for trend analysis studies



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50

Land degradationmeans reduction or loss, in arid,- -

40

,

or economic productivity[] resulting from land

uses or from a process or combination of processes,

including processes arising from human activities-

20

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of natural vegetation

010

iNDVIend

Begin

NDVIiNDVINPP



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1. Soil signal contained in NDVI signal may obscure real signal for low,

covering most desertification studies.2. iNDVI correlates to NPP only for moderate to low canopy cover. If

canopy cover excee s approx ma e y corre a ons su erconsiderably.

3. iNDVI correlation to NPP is biome specific and cannot be establishedat continental level. This will render the option to verify many of theresults near impossible. This would be further problematic at a spatial

resolution of 64 square kilometers.



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1. We will argue that much work lacks a strong ontological focus where

2. We will argue that the results of the above analysis do not lendthemselves to easy explanations and one should take care not to fall

.

3. We will argue that the ontology and construct validity of this analysis issound, bearing in mind the point of departure (UNCCD).

. broad surveys []which have consistently shown to be ephemeral

products of their time, bringing with them the inevitably ill-informedprejudices of their creators

5. Yet, we will be happy to receive good ideas and inputs


Documents

Hierarhcies, scales and desertification