Potential use of plant species for soil improvement in Mali and Burkina Faso
“Best bet” Land-use Systems
Thematic reports
Impact of different land uses on biodiversity
Biodiversity and Productivity Assessment for Sustainable Agroforest Ecosystems
Unique id: IDA1AQCE
Source file: D:\Projects\ASB\ASB Country and Thematic reports\Above ground biodiversity assessmet WG\MaliRep.xml
Authors: Andrew N. Gillison
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EXECUTIVE SUMMARY
The Sahelian countries of
1. Introduction and terms
of reference
The purpose of my task was to help draft a concept paper related to
biodiversity conservation in the
Methods
I accompanied the ICRAF team on
a reconnaissance of a range of field conditions where various trials were in progress (Annex I). In
order to gain some preliminary understanding of vegetation response to
different land management practices a series of
40x5 m strip transects were established along gradients of soil types
and rainfall precipitation. Because landscapes in
Where identifications were possible, all vascular plant species were recorded together with local names of key species and Plant Functional Types (PFTs – after the method of Gillison and Carpenter, 1997). All data were subsequently entered into a computer using the recently developed Windows-based ‘VegClass’ software (Gillison, unpubl.) that enables summaries and graphic output of all data including derived diversity indices for PFTs (Shannon-Wiener, Simpson’s and Fisher’s a). Because the data are summarised for each 5x5m quadrat within the 40x5m transect it is possible to use VegClass to generate species:area and PFT:area curves to assess sampling efficiency. Raw data and metadata summaries can be output to Excel and MS Access. Because the survey method is generic, comparative analyses are possible between geographically remote locations where, for example, environments and vegetation response may be similar but where the taxa may differ. In this way the method provides a basis for identifying species with similar adaptive response characteristics in different countries and ecoregions. In the present Sahelian study this is potentially useful in identifying exotic species from other countries that show parallel adaptive features and vice versa. Observers were A N. Gillison (CBM) and D-Y. Alexandré (IRD/ICRAF).
The data were analysed using the CSIRO PATN pattern analysis software (Belbin 1992). Five variables that are known from previous studies (Gillison and Liswanti, 1999a,b) to be key indicators of animal habitat and soil nutrient availability were used in the analysis. These were vegetation structure (mean canopy height (m), basal area (m2ha-1 ), total vascular plant species, total Plant Functional Types (PFTs) and the ratio of Species:PFTs. The data were classified using a Gower metric similarity measure and an unweighted pair group average fusion strategy. A multi-dimensional scaling (MDS) analysis was applied to produce a two-vector solution and the scores used to construct a 2-dimensional graph. Diversity indices based on PFTs rather than taxa (Gillison et al., 2000) were generated by VegClass. These include Shannon-Winer, Simpson’s and Fisher’s a diversity indices. An additional measure of PFT complexity within each plot is indicated by the Plant Functional Complexity (PFC) measure (Gillison et al., 2000).
A climatic domain was generated for the sixteen sites using the DOMAIN potential mapping software package (Carpenter et al., 1993) based on temperature and rainfall precipitation minimal and maximal acquired from a public domain data set. This domain was then compared with the global data set and a thematic map produced showing differing similarity matches.
Results
Site location and physical data are listed in Table 1, with land use management regime and vegetation structure in Table 2 and species, PFT and PFT diversity indices in Table 3. Detailed taxonomic and PFT data are listed in Annex II.
Classification
The dendrogram in Fig.1 indicates a primary division between ‘parkland’ (variously dominated by Faidherbia albida (Gau), Vitellaria paradoxa (Karité) and Borassus aethiopum with occasional Adansonia digitata (Baobab) (Sites 3,5,6,7,15,16) including two outlier sites (sparse Combretum shrub savanna on skeletal sandstone soils (site 4) and an Acacia nilotica shrub savanna on poorly drained soils (site 8). The other side of the dendrogram contains two main groups: one composed of woodland savannas dominated by Combretaceae and Bombax costatum commonly with Cochlosperum tinctorium and C. planchoni (sites 2,12,13,14) and the other with more open woodland savanna with mixed species (Acacia macrostachya, Combretaceae, Entada africana, Lannea velutina and Sclerocarya birrea) commonly with termitaria (sites 9,10,11) and an outlying site (1) that is a Faidherbia /A. nilotica parkland on a cultivated, stony terrrace.
Ordination
The MDS (Fig2) reflects the classification to a large extent, with the above groups clearly identifiable. The first vector (X axis) indicates increasing plant biodiversity towards the more complex woodland savannas in the positive direction while vector 2 (Y axis) separates tall ‘parkland’ (negative) from the shorter and more sparse shrub savannas (positive).
Diversity indices
To the extent that vegetation complexity (richness and composition of taxa and PFTs) can be said to reflectsoverall biodiversity, this is least in the highly modified ‘parkland’ land use types. A measure of this is indicated in Table 3 that includes diversity indices based on PFTs rather than species. The Plant Functional Complexity and Shannon-Wiener values correspond most closely with obvious ecological interpretations of adaptive complexity and available ecological niches.
DOMAIN mapping
The map (Fig. 3) shows
remarkable similarities with extensive areas of northern
4. Discussion
Aside from the influence of rainfall precipitation and distribution, the major ecological determinants of vegetation are cultivation and grazing by domestic animals. In all ‘parklands’ first inspection suggests the dominant species are not being replaced by any juveniles. Closer investigation however, indicates the presence of many tree seedlings that are suppressed by grazing animals (cattle, goats, sheep). The removal of grazing pressure would therefore result in the regeneration of such species The presence of large evergreen trees (e.g. Karité, Gau, Mango) in an otherwise arid environment indicates root access to artesian water over much of the area surveyed. Many villagers commented that the water table can be highly variable within and between years, causing local hardship and a corresponding changes in plant species composition.
Pattern analysis showed a clear
separation of vegetation types that reflect mainly variation in soil fertility,
in particular run-on versus run-off
sites. With some exceptions (such as swamps, swamp margins and seasonal
floodplains) the former support the productive parklands whereas the latter
support the more depauperate woodland savannas especially on skeletal soils or
landscapes with lateritic crusts. It is expected that results from soil
analyses will contribute further to an understanding of the vegetation
dynamics. The Sahelian landscapes of Mali and Burkina Faso show striking
parallels with the savannas on Proterozoic, Jurassic and Cretaceous sandstones
and Late Miocene, lateritic duricrusts of Northern Australia the main exception
being the lack of naturally occurring Eucalyptus
and Melaleuca species in the otherwise
Combretaceae-dominant Sahel. Many plant families (e.g. Anacardiaceae,
Bombacaceae, Capparidaceae, Cochlospermaceae, Combretaceae, Fabaceae and
Rubiaceae) are found in both regions, often with the same genera (Acacia, Adansonia, Bombax, Cochlospermum, Erythrina,
Gardenia, Grewia, Strychnos, Terminalia …). It is therefore hardly
surprising that the DOMAIN map (Fig. 3) highlights similar climate matches
based on temperature and rainfall precipitation. Other regional matches are also evident in
the seasonal, dry landscapes of Eastern and Southern Africa, including
5. Screening trials of
Australian arid zone species
On request from CBM, the
Australian Tree Seed Centre[1], kindly provided seed
from a range of species considered to be potentially useful as either fuel or
fodder crops or soil ameliorants (Casuarinaceae). These are listed in Table 4.
Information supplied by the ATSC includes provenance location and elevation,
phytosanitary certificate, procedures for pre-treatment of seed and seed
viability. Both the seeds and the information have been forwarded by CBM to the
ICRAF office in
6. Conclusions and
Recommendations
Soil fertility and crop
production seem certain to decline under the currently increasing population
and associated land use pressures. Within the framework of traditional land use
practices that appear to be well entrenched, significant improvements in fallow
management may be possible with introduction of Tithonia and Tithonia-like
species where adequate water harvesting and water management are feasible. Recent developments in small, low-cost,
solar-powered, medium-lift, impeller pumps could be explored for trialling in
several representative sites where artesian water is available. These would
make water more readily available during periods of reduced water levels and
assist in nursery production of species for transplanting into selected trial
cultivation areas. Further research is needed to identify and review likely
species for screening trials given the climate and soil domains in the
The climate and soil
similarities between the Sahelian lands of
To better understand grazing effects, exclosures are one
obvious experimental design. Previous experience with exclosures in the
Human impact in the
7. References
Belbin, L.
(1992). PATN Pattern Analysis Package: Technical Reference. CSIRO Div. Wildlife
and Ecology,
Carpenter, G., Gillison, A.N. and Winter, J. (1993). DOMAIN: A flexible modelling procedure for mapping potential distributions of plants and animals. Biodiv. Cons. 2, 667-680.
Gillison, A.N.
(1988). 'A Plant Functional Proforma for
Dynamic Vegetation Studies and Natural Resource Surveys' Tech Rep. 88/3.
CSIRO Division of Water and Land Resources,
Gillison, A.N. (1999a) (coord.), Above-ground biodiversity assessment working group summary report 1996-99. Impact on biodiversity of different land uses. Alternatives to slash and burn project. ICRAF. Part A: Executive summary., pp.2-3 Part B: Above-ground, ecoregional benchmark surveys. Pp. 4-14.
Gillison, A.N. and Brewer, K.R.W. (1985). The use of gradient directed transects or gradsects in natural resource surveys. J. Environ. Manag. 20: 103-127
Gillison, A.N. and
Carpenter, G. (1997). A generic plant functional attribute set and
grammar for dynamic vegetation
description and analysis. Funct. Ecol. 11, 775-
783.
Gillison, A.N.,
Liswanti, N.L., (Eds.), (1999a). An
intensive biodiversity baseline study in Jambi province, Central
Gillison, A.N. and
Liswanti, N. (1999b). Biodiversity and productivity assessment for sustainable
agroforest ecosystems. Mae Chaem,
Gillison, A.N.
(1999b). Biodiversity and productivity assessment for sustainable agroforest
ecosystems.
Gillison, A.N., Liswanti, N., van Noordwijk, M., Suseno, and Tomich, T. (2000). . Biodiversity and productivity assessment for sustainable agroforest ecosystems. Lampung, S. Sumatra. Part F. In Gillison, A.N. (1999) (coordinator), Above-ground biodiversity assessment working group summary report 1996-99. Impact on biodiversity of different land uses. Alternatives to slash and burn project. ICRAF, Nairobi.pp ##.
Raunkiaer, C. (1934). The
Life Forms of Plants and Statistical Plant Geography Being the collected papers
of C. Raunkiaer.
Tomich, T.P., van Noordwijk, M., Budidarsono, S., Gillison,
A.N., Kusumanto, T., Mudiyarso, D., Stolle, F.and Fagi, A.M. Kusumanto, T.,
(2000). "Agricultural Intensification,
Deforestation, and the Environment: Assessing Tradeoffs in
Wessels, K.J., Van Jaarsveld, A.S., Grimbeek, J.D. and Van der Linde, M.J. (1998). An evaluation of the gradsect biological survey method. Biodiversity and Conservation 7: 1093-1121.
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Table 1. Site location and physical features
|
Site |
Symbols |
Location |
Date |
Observers |
Lat. (N) |
Long (W) |
Elev (m) |
Slope (%) |
Aspect (Deg) |
S_Dpt (cm) |
Ltr (cm) |
Terrain Unit |
Soil Type |
|
|
|
Wakoro |
10-Feb-00 |
AG |
12-56-24 |
5-41-24 |
290 |
0 |
0 |
>100 |
0.50 |
Plain |
|
|
Mali02 |
|
Foret clasée des Monts Mandiague, en route
Siby ex |
13-Feb-00 |
AG/DA* |
12-29-13 |
8-10-23 |
390 |
3 |
20 |
>100 |
0.10 |
Midd-slope/flat crest |
Inceptosol |
|
Mali03 |
|
Bandiagara |
15-Feb-00 |
AG |
14-21-34 |
3-28-27 |
329 |
0 |
0 |
>100 |
0.01 |
Run-on plain |
- |
|
Mali04 |
|
Near Songho, Dogon Plateau |
14-Feb-00 |
AG |
14-22-04 |
3-43-37 |
370 |
1 |
270 |
>100 |
0.01 |
Plateau |
Sand |
|
Mali05 |
|
Djenne |
14-Feb-00 |
AG |
13-53-46 |
4-32-02 |
305 |
0 |
0 |
>100 |
0.10 |
Plain |
|
|
Mali06 |
|
Near San village (2.5km from Tene) |
14-Feb-00 |
AG |
13-26-39 |
4-32-45 |
323 |
0 |
0 |
>100 |
0.10 |
Run-on plaun |
|
|
Mali07 |
|
Near Fono |
15-Feb-00 |
AG |
13-01-18 |
5-21-54 |
327 |
0 |
0 |
>100 |
0.10 |
Run-on plain |
Run-on plain |
|
Mali08 |
|
Near Segou, |
16-Feb-00 |
AG |
13-13-29 |
6-28-24 |
305 |
0 |
0 |
>100 |
1.00 |
Run-on plain |
- |
|
Mali09 |
|
40 km from |
16-Feb-00 |
AG/DA |
|