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 Mali and Burkina Faso are subject to decreasing soil fertility and biodiversity largely as a result of rising population pressure and uncertain water supply. These are widely accepted precursors to increased poverty and reduction in quality of life. Traditional methods of agriculture and animal husbandry are becoming difficult to sustain, requiring reassessment of methods of land use management in particular the use of appropriate fallow systems.  A brief reconnaissance was undertaken from 6 – 20 February 2000 to assess existing land use conditions and to consider whether certain exotic fallow species could be screened for possible introduction in addition to indigenous species. In several village centres the team examined progress in the establishment of ‘live fences’  enclosing both agricultural subsistence and animal fodder crops. A subsequent, intensive, four-day reconnaissance was conducted along a rainfall gradient (500 to 950mm annual) from the Dogon Plateau to the Neguela area north-west of Bamako. The survey employed a recently developed rapid-vegetation survey method to record data from a variety of land use types and natural resource conditions.  These included geocoded (GPS) site physical features including land use type and site history, vegetation structure, vascular plant species and plant functional types. Soil samples (surface 15cm) were collected in each site for subsequent laboratory analysis. A total of 16 (40x5m) transects were recorded under various land use types ranging from semi-desertic, combretaceous shrub savanna on skeletal sandstone in the Dogon plateau to mixed woodland savanna and cultivated Faidherbia and Vitellaria dominated ‘parkland’ on deeper soils. A cluster analysis of mean canopy height (m), basal area (m2ha-1) total species and plant functional types and spp:PFT ratios identified three key groups: woodland savanna tending to be dominated by Combretaceae and Bombax costatum; more open and more intensively used, sometimes seasonally flooded, woodland savannas with Combretaceae and Lannea velutina dominants, often with conspicuous termitaria, and ‘parkland’ dominated by Faidherbia, Vitellaria and Borassus often with Adansonia (Baobab). Outliers were depauperate, shrubby woodland savannas on skeletal soils (Dogon Plateau) and Acacia nilotica dominant shrublands on poorly drained soils. Apart from cultivation, grazing is identifiably the most dominant ecological pressure. Reduction of this pressure would result in a corresponding resurgence of growth in suppressed seedlings of Acacia, Faidherbia and Vitellaria. Recent research has shown that certain Asteraceae such as Tithonia diversifolia are capable of improving soil fertility when used in managed ‘Daisy’ fallows. In several locations (notably peri-urban Ougadougou and Bamako),  Tithonia diversifolia was observed as an adventive weed. This occurrence, together with several other exotic Asteraceae,  suggests that with adequate water supply such taxa may be manipulated as extended fallows to improve soil fertility.  Further research is indicated to ascertain which Asteraceae are best suited to this region and to particular land uses. Certain Australian arid-land Acacia and Casuarina species may help improve soil and serve as added fodder crops. With this in mind, following the survey, seeds of Allocasuarina decasineana, Casuarina obesa, Acacia  cooleyi  var. cooleyi, A. cooleyivar. ileocarpa,  A. epacanthaand A. torulosa from different Australian provenances were supplied by the CSIRO Australian Tree Seed Centre, CSIRO Forestry and Forest Products. These have been forwarded to the ICRAF office in Bamako for screening.  The DOMAIN spatial mapping software package was used to generate an environmental ‘domain’ based on rainfall precipitation and temperature for the sixteen transects.  When compared with global data this domain matched extensive areas in Northern Australia thus indicating potential for germplasm exchange. Certain species and PFTs for possible use in improving fodder production and soil conditions are considered as an initial set for further investigation together with a suggested framework for biodiversity-related research.

 

 

 

 

1.         Introduction and terms of reference

 

The purpose of my task was to help draft a concept paper related to biodiversity conservation in the Sahel and to help identify candidate plant species for soil fertility improvement.  As background to this task ICRAF has been instrumental in identifying certain species that have been shown to improve soil fertility, in particular Tithonia diversifolia from Mexico that belongs to the Daisy family (Asteraceae).  Parallel studies in Mexico, Cameroon and South East Asia (Gillison, 1999; Gillison and Liswanti, 1999) also indicated that under late fallows dominated by other Asteraceae (e.g. Chromolaena odorata, Senecio and Vernonia spp.)  soil fertility also appeared to improve, in some cases with increased biodiversity.  With this in mind a reconnaissance of land use types and landscapes in Mali and Burkina Faso sought to identify conditions where the introduction of certain herbaceous and woody species might prove beneficial. As well as seeking species to help improve soil fertility, of equal concern are species that can be used as fodder for domestic grazing animals. Although not part of the present TOR,  this was also kept in mind during the field visit. An itinerary is listed in Annex II.

 

 

            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 Mali and Burkina Faso have relatively little relief overall, minor changes in drainage pattern translate into significant differences in soil depth and fertility for indigenous people.  A total of 16 such transects were established ranging from the Dogon plateau in the North East to the Foret Classeé des Monts Maniague towards Siby west of Bamako and the Neguela region to the North West of Bamako.  Fourteen of these were recorded in 3.5 days following departure of the main team. The general survey design followed the gradsect method (Gillison and Brewer, 1985; Wessels et al., 1998) that is designed to improve chances of detecting changes in biodiversity compared with more traditional designs based on probability theory. In each transect data were recorded according to the proforma technique devised by Gillison  (1988, 1999a,b). Data included location (Latitude, Longitude in deg. min. sec.) recorded by GPS, slope%, aspect (deg.), elevation (m) recorded using clinometer, compass and digital altimeter respectively; soil depth, soil type (where information available), litter depth 9cm), and terrain position. Surface soil samples (top 15cm) were taken for each site and forwarded to ICRAF Nairobi for analyses. Vegetation structure (mean canopy height, crown cover percent, basal area m2ha-1  estimated using the Bitterlich technique, furcation index (and architectural index based on forking in the main stem of a woody plant),  cover-abundance of woody plants <2m tall and cover-abundance of bryophytes (both Domin scale estimates).

 

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 Australia, especially those areas in North-West Queensland with similar vegetation formations and with North-West Australia also with similar vegetation structure and many families including Bombacaceae (Adansonia, Bombax)  and closely related Cochlospermaceae (Cochlospermum). It is of interest that Mimosa pigra of the Sahel and indigenous to Central and South America has become an aggressive, invasive exotic weed in the Australian North-West as have Acacia nilotica and Parkinsonia aculeata (also tropical America) in the highly seasonal, outwash plains of the Gulf of Carpentaria in NW Queensland. Another widespread weed common to both areas is Calotropis gigantea. More restricted areas with very similar climate domains can be seen in many other countries including some sub-tropical areas in Africa and in Central and North America.

 

 

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 Madagascar, Saudi Arabia, the Indian sub-continent and parts of mainland South East Asia and Central and South America.  A conspicuous feature of the Mali woodland savannas is the dominance of Combretaceae and the development of some extreme life forms that possess woody upper parts but well-developed, below-ground storage organs (Cochlospermum spp., Entada africana). (Fig. 4). These features provide insurance against extreme drought and fire but create difficulties for classification into specific PFTs as they defy Raunkiaerean life form classification (Raunkiaer, 1934).  Other than this, the occurrence of ‘parklands’ typifies this part of the Sahel (Figs, 5,6) as do Baobabs (Fig. 7). Functional diversity and, possibly biodiversity, are clearly highest in the least modified vegetation types. The evident resilience of life forms and highly efficient dispersal mechanisms for seed and fruit are likely to support rehabilitation of degraded landscapes provided these are within range of source material.

 

 

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 Mali for screening trials.

 

 

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 Sahel.  Atriplex species and similar arid-land ‘salt-bush’ Chenopodiaceae should be investigated as potential fodder species.  Other potential indigenous and exotic ‘Live-fence’ species should also be explored, one such indigenous species being Pterocarpus erinaceus that is common in woodland savannas in Mali.

 

The climate and soil similarities between the Sahelian lands of Mali and Burkina Faso and Northern Australia point to likely sources of germplasm for species that may be introduced to the Sahel to assist with enhancing fuel, fodder and soil improvement. The types of plant species most likely to succeed should match the more arid climates in order to cope with unforeseen climate fluctuations such as El Niño events. To this extent species of Acacia, Allocasuarina, Casuarina and Melaleuca might be profitably screened for introduction. For fodder plants, arid Australian and Asian Chenopodiaceae should be carefully examined, especially Atriplex spp.  as these are well established fodder species in arid and semi-arid environments and their management is relatively well known. Further research is needed to explore likely sources of Asteraceae in particular Olearia, Senecio, Tithonia and Vernonia species.

 

To better understand grazing effects, exclosures are one obvious experimental design. Previous experience with exclosures in the Sahel suggest these should be approached with caution: One early experiment resulted in sand build up against the exclosure fence that subsequently prevented surface flow of water into the exclosure creating a localised droughting effect. Another resulted in a heavy legume seed crop that attracted rodents. When the seed supply was exhausted the rodents attacked other plants inside and outside the exclosure resulting in severe damage (D-Y Alexandre, pers. com.). 

 

Human impact in the Sahel has resulted in highly manipulated ecosystems with mosaics of locally intensive cultivation and loosely controlled grazing and indeterminate fire control. These conditions create difficulties in assessing the actual and potential role of biodiversity in sustaining agricultural productivity and environmental services.  To better understand these interactions will require a series of intensive baseline studies to be establshed along a series of predefined biophysical environments under known land management systems. Results from recent developments in gradient-based, rapid biodiversity assessment methods in the ICRAF ASB project indicate these methods would be well suited to designing and implementing a baseline study for selected areas of the Sahel.  Baseline data of this kind are essential in identifying range distributions of key plant and animals taxa and in establishing and simulating dynamic linkages between soil nutrient availabilty, biodiversity and profitability. Provided efficient correlations can be detected, these can be used to help forecast land use impacts on biodiversity and profitability (cf. Tomich et al., 2000) and thereby assist in generating options for adaptive and sustainable management.


 

 

7.         References

 

Belbin, L. (1992). PATN Pattern Analysis Package: Technical Reference. CSIRO Div. Wildlife and Ecology, Canberra.

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, Canberra.

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 Sumatra, Indonesia. Part C In: Gillison, A.N. (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. Incl. Maps and Annexes.

  Gillison, A.N. and Liswanti, N. (1999b). Biodiversity and productivity assessment for sustainable agroforest ecosystems. Mae Chaem, Northern Thailand: Preliminary Report. Part D 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. 38, plus maps and Annexes.

  Gillison, A.N. (1999b). Biodiversity and productivity assessment for sustainable agroforest ecosystems. Mbalmayo, Cameroon. Part E. 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. 43, plus Annexes.

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.  Oxford at the Clarendon Press. 632 pp.

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 Sumatra, Indonesia" In: DR Lee and CB Barrett, eds, Tradeoffs or Synergies? Agricultural Intensification, Economic Development and the Environment.Wallingford, UK: CAB International, 2000. (in press).

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

Mali01

 

Wakoro

10-Feb-00

AG

12-56-24

5-41-24

290

0

0

>100

0.50

Plain

Sandy alfisol

Mali02

 

Foret clasée des Monts Mandiague, en route Siby ex Bamako

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

Sandy loam

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

Sandy loam

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 Bamako -> Segou

16-Feb-00

AG/DA

12-35-46

7-39-00

387

0

0

>100

0.10

Run-on plain

-

Mali10

 

40 Km ex Bamako -> Segou (across road from Mali09)

16-Feb-00

AG/DA

12-35-50

7-31-00

392

0

0

>100

1.00

Run-off plain

-

Mali11

 

Centre de Formation forestiere, 19 km ex Bamako -> Segou

16-Feb-00

AG/DA

12-35-19

7-50-59

363

0

0

>100

2.00

Run-off plain

-

Mali12

 

Neguela village area NW of Bamako

17-Feb-00

AG/DA

12-49-30

8-16-43

426

0

0

>100

1.00

Run-off plain

-

Mali13

 

Neguela village area NW of Bamako

17-Feb-00

AG/DA

12-51-44

8-25-58

352

0

0

>100

1.00

Low rise - run-off

-

Mali14

 

Neguela area NW of Bamako

17-Feb-00

AG/DA

12-52-31

8-28-04

358

1

200

>100

0.20

Upper rise - run-off

-

Mali15

 

Bamabougou, NW of Bamako

17-Feb-00

AG/DA

12-49-58

8-18-06

436

0

0

>100

1.50

Run-on plain

-

Burkina01

 

Dossi

07-Feb-00

AG

11-30-53

3-23-51

380

10

105

<50

1.00

Lower slope

Inceptisol

 

*AG: Andy Gillison; DA: Daniel-Yves Alexandre; Lat: Latitude; Long: Longitude; Elev: Elevation; S_dpt: Soil Depth; Ltr: Litter

 

 

 

 


Table 2.   Plantation management regime and vegetation structure

Site

Symbols

Vegetation

Remarks

M_Can

CC

CW

CNW

M_BA

Bry

Wdy

M_FI

Mali01

 

Open woodland.

Intensively grazed and managed, dominated by Sclerocarya - Vitellaria (some Adansonia and Acacia nilotica). Water table ca. 25m Fertilised, cultivation <12 months., intensively grazed

1.50

30

10

20

0.67

0

4

69

Mali02

 

Woodland savanna

Degraded, fired and grazed, Combretaceae dominated with Cochlospermum tinctorium flowering at ground level.

4.00

65

15

65

7.33

0

4

81

Mali03

 

Faidherbia albida parkland

Cultivated, Faidherbia parkland with Millet; grazed

6.00

15

10

5

0.33

0

0

68

Mali04

 

Low woodland savanna dominated by Combretaceae

and Euphorbiaceae suculents

Heavily degraded woodlnad savanna; grazed, cut over

2.50

15

5

10

0.33

0

1

95

Mali05

 

Riverine parkland with scattered Parkinsonia aculeata

and Acacia nilotica.

Riverine flood plain, heavily grazed and cut-over

3.50

30

5

25

0.33

0

0

82

Mali06

 

Highly modified Vitellearia/ Baobab woodland (parkland) ;

Cultivated Vitellaria (Kapite) woodland with millet. Cut and grazed; heavily modified; occasional Baobab

9.00

70

15

55

0.67

0

1

74

Mali07

 

Tall open woodland totally modified, with Borassus and Faidherbia

Cultivated Borassus palm parkland with Faidherbia albida dominant over cultivated Millet

14.00

50

5

45

1.00

0

0

16

Mali08

 

Acacia nilotica, Combretum shrubland.

Heavily grazed Acacia nilotica, Combretum shrub savanna. Not fired.

2.50

60

15

45

0.67

0

2

88

Mali09

 

'Woodland savanna ‘Bowe’ (with termites)

Heavily degraded and periodically flooded, 'Termite' savanna ("Bowe") - occassionally fired. Heavily grazed and cut over. Some Neem trees planted.

2.50

70

10

60

1.33

0

1

98

Mali10

 

Heavily disturbed, grazed, cut over woodland savanna with emergent Bombax costatum

Heavily disturbed, grazed, cut over woodland savanna with emergent Bombax costatum

5.50

70

20

50

4.67

0

3

83

Mali11

 

Woodland savanna mixed species.

Highly disturbed - heavily cut-over althought 'protected'

3.00

75

40

35

2.33

1

6

88

Mali12

 

Woodland savanna with Bombax costatum and

Combretaceae.

Heavily disturbed and cut-over with Bombax costatum and Combretaceae. many ground termites.

3.00

75

15

65

1.67

0

4

74

Mali13

 

Woodland savanna on old fallow.

Heavily disturbed ;with ground termites

4.50

75

30

45

3.67

0

5

90

Mali14

 

Woodland savanna with many mixed tree species

Heavily disturbed with many mixed tree species and termites/ much fire and grazing

5.00

70

15

55

3.33

0

3

77

Mali15

 

Karite (Vitellaria paradoxa) parkland.

Cultivated (Sorghum)  with occasional fruit trees (Mango). Grazed

15.00

40

7

33

1.67

0

1

68

Burkina01

 

Faidherbia albida parkland.

Faidherbia albida parkland, cropped and grazed, Millet and Maize: completely modified landscape; many suppressed (grazed) seedlings of both F. albida and Acacia nilotica.

12.00

70

10

60

1.67

1

0

74

 

M_Can: Mean Canopy Height; CC: Crown Cover%; CW: Crown Cover% Woody plants; CNW: Crown Cover% Non Woody Plants; M_BA: Mean Basal Area m2ha-1;

Bry: Bryophyte cover-abundance; Wdy: Woody Plants<1.5m tall, cover-abundance; M_FI: Mean Furcation Index; FI CV%: Coefficient Variation% of FI


 

Table 3.  Summary data for vascular plant species, PFTs or modi and species/PFT richness ratios,

S/W PFT index,  Simpson FPT Index*

 

 

No.

Site

Symbols

Total Records

Unique PFTs

Unique Species

Unique Species/PFTs

Simpson PFT Index

S/W PFT Index

 Fisher's Alpha PFT

1

Mali01

 

24

18

24

1.33

0.0694

2.79

32.71

2

Mali02

 

24

21

23

1.10

0.0521

3.00

80.29

3

Mali03

 

5

4

5

1.25

0.2800

1.33

9.28

4

Mali04

 

8

6

8

1.33

0.1875

1.73

10.90

5

Mali05

 

5

5

5

1.00

0.2000

1.61

138.96

6

Mali06

 

8

7

8

1.14

0.1563

1.91

26.76

7

Mali07

 

6

6

6

1.00

0.1667

1.79

166.75

8

Mali08

 

10

7

10

1.43

0.1600

1.89

10.36

9

Mali09

 

16

13

16

1.23

0.0938

2.48

32.35

10

Mali10

 

23

18

23

1.28

0.0662

2.81

38.15

11

Mali11

 

36

26

36

1.38

0.0509

3.13

42.00

12

Mali12

 

27

25

26

1.04

0.0425

3.19

162.09

13

Mali13

 

33

29

31

1.07

0.0395

3.31

114.49

14

Mali14

 

23

19

21

1.11

0.0813

2.79

51.25

15

Mali15

 

15

13

14

1.08

0.0844

2.52

46.46

16

Burkina01

 

10

7

10

1.43

0.1600

1.89

10.36

 

* S/W = Shannon-Wiener diversity index for PFTs; Simpson = Simpson’s diversity index for PFTs  (Gillison and Carpenter, unpubl.)

 

 

                                                                                                                               

 

Table 4  Seed species and sources supplied by Australian Tree Seed Centre

 

 

 

Seedlot

No.

 

 

                  Species

 

No.

Parent

trees

 

Quantity

   (g)

 

             Locality

 

Elevation

    (m)

 

 

Latitude

 

        Longitude

 

Viable

seeds /10g

 

 

  Deg.

 

  Min.

 

  Deg.

 

   Min.

 

19522

 

19984

 

18813

 

18817

 

18524

 

18804

 

19037

 

20078

 

17477

 

15796

 

 

 

Acacia colei  var. colei

 

Acacia colei  var. colei

 

Acacia colei  var. ileocarpa

 

Acacia colei  var. ileocarpa

 

Acacia elachantha

 

Acacia elachantha

 

Acacia torulosa

 

Acacia torulosa

 

Allocasuarina decaisneana

 

Casuarina obesa

 

10

 

25

 

5

 

5

 

5

 

10

 

12

 

40

 

5

 

10

 

20

 

20

 

20

 

20

 

20

 

20

 

20

 

20

 

20

 

20

 

 

Panawonica  Railway

 

Arthur’s Creek

 

KimberleyDowns

 

Luiluigui

 

Urandangi

 

Moola Bulla

 

Lajamanu

 

Tanami Rd. WA/NT border

West. Hermannsberg

 

Murchison R.

 

 

 

0

 

40

 

50

 

50

 

100

 

380

 

290

 

425

 

500

 

180

 

21

 

15

 

17

 

18

 

21

 

18

 

18

 

19

 

23

 

27

 

21

 

38

 

26

 

08

 

33

 

13

 

01

 

54

 

58

 

51

 

116

 

128

 

128

 

124

 

138

 

127

 

130

 

129

 

132

 

114

 

21

 

38

 

26

 

08

 

33

 

13

 

01

 

54

 

58

 

51

 

0

 

648

 

733

 

766

 

274

 

766

 

115

 

207

 

360

 

900

 

 

 

 


 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 


Figure 1  Classification of Mali and Burkina Faso vegetation using structure,    species and PFT richness and Spp:PFT ratio (See Table 1 for symbols)

 

 

 

 

Text Box: Vec - 02
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 


Figure 2   MDS scaling of veg. structure, species and PFT richness and spp:PFT


Figure  3  DOMAIN climate matching of 16 sites in Mali and Burkina Faso using Temperature and Precipitation

(0.5 deg. grid). Red = 100% similarity; Yellow = 56%; Green = 13%; Aqua <13%.


Annex I.  List of plant families, genera, and species together with PFTs arranged according

to sites, Mali and Burkina Faso.

 

No.

Site

Modus

Family

Genus

Species

Authority

Code

1

Mali01

mi-ve-do-ch

Combretaceae

Guiera

senegalensis

Lam.

GUIESENE

2

Mali01

na-ve-do-hc

Amaranthaceae

Alternanthera

mali01/02

_

ALTEMALI

3

Mali01

mi-ve-do-pv-hc

Poaceae

Indet 01/03

 

_

INDE

4

Mali01

mi-co-do-de-ct-ph

Anacardiaceae

Sclerocarya

birrea

(A. Rich) Hochst

SCLEBIRR

5

Mali01

mi-ve-do-th

Acanthaceae

Indet01/05

 

_

INDE

6

Mali01

na-ve-do-th

Caryophyllaceae

Indet01/06

 

_

INDE

7

Mali01

na-ve-do-th

Fabaceae

Cassia

tora

Linn.

CASSTORA

8

Mali01

mi-ve-do-hc-li

Convolvulaceae

Indet01/08

 

_

INDE

9

Mali01

na-ve-do-th

Rubiaceae

Borreria

mali01/09

_

BORRMALI

10

Mali01

mi-pe-do-hc-li

Convolvulaceae

Indet01/10

 

_

INDE

11

Mali01

mi-ve-do-ch

Malvaceae

Hibiscus

sabdariffa

Linn.

HIBISABD

12

Mali01

mi-pe-do-ch

Euphorbiaceae

Indet01/12

 

_

INDE

13

Mali01

mi-ve-do-pv-ph

Poaceae

Indet01/13

 

_

INDE

14

Mali01

mi-pe-do-de-ch

Meliaceae

Azadirachta

indica

A. Juss

AZADINDI

15

Mali01

mi-ve-do-de-ph

Fabaceae

Acacia

nilotica

Delile.

ACACNILO

16

Mali01

mi-ve-do-pv-hc

Poaceae

Cenchrus

ciliaris

Fig. & De Not

CENCCILI

17

Mali01

no-pe-do-ch

Malvaceae

Indet01/17

 

_

INDE

18

Mali01

mi-ve-do-ch

Indet01/18

 

 

_

 

19

Mali01

na-ve-do-ch

Fabaceae

Indet01/19

 

_

INDE

20

Mali01

na-ve-do-hc

Indet01/20

 

 

_

 

21

Mali01

me-ve-do-hc-li

Cucurbitaceae

Lagenaria

siceraria

Standley.

LAGESICE

22

Mali01

na-pe-do-ch

Solanaceae

Capsicum

minutiflorum

(Rusby) A.T. Hunziker

CAPSMINU

23

Mali01

no-co-do-ph

Sapotaceae

Vitellaria

paradoxa

Gaertn.f.

VITEPARA

24

Mali01

no-co-do-ch-ep-pa

Loranthaceae

Tapinanthus

mali01/24

_

TAPIMALI

25

Mali02

me-ve-do-de-ph

Bombacaceae

Bombax

costatum

Pellegrin & Vuillet

BOMBCOST

26

Mali02

no-ve-do-de-ct-ph

Rubiaceae

Gardenia

ternifolia

Schum. & Thonn.

GARDTERN

27

Mali02

mi-pe-do-ph

Fabaceae

Burkea

mali02/03

_

BURKMALI

28

Mali02

mi-ve-do-pv-hc

Poaceae

Andropogon

gayanus

Kunth.

ANDRGAYA

29

Mali02

no-la-do-de-ch

Combretaceae

Combretum

ghasalense

Engl. & Diels.

COMBGHAS

30

Mali02

no-co-do-de-cr

Cochlospermaceae

Cochlospermum

tinctorium

Perr.

COCHTINC

31

Mali02

no-ve-do-de-ch

Combretaceae

Combretum

glutinosum

Guill. & perr.

COMBGLUT

32

Mali02

mi-ve-do-pv-hc

Poaceae

Andropogon

ascinodis

C.B. Clarke

ANDRASCI

33

Mali02

me-ve-do-de-ch

Combretaceae

Terminalia

macroptera

Guill. & Perr.

TERMMACR

34

Mali02

no-pe-do-th

Malvaceae

Hibiscus

sabdariffa

Linn.

HIBISABD

35

Mali02

mi-ve-do-de-ch

Fabaceae

Lonchocarpus

hockii

De Wild.

LONCHOCK

36

Mali02

no-ve-do-ct-ph

Combretaceae

Combretum

glutinosum

Guill. & Perr.

COMBGLUT

37

Mali02

na-ve-do-hc

Fabaceae

Indet02/12

 

_

INDE

38

Mali02

mi-pe-do-th

Rubiaceae

Borreria

mali01/09

_

BORRMALI

39

Mali02

mi-pe-do-de-ch

Loganiaceae

Strychnos

aculeata

Solered

STRYACUL

40

Mali02

me-co-do-ro-su-cr

Liliaceae

Indet02/16

 

_

INDE

41

Mali02

no-ve-do-de-ct-ph

Rubiaceae

Crossopteryx

febrifuga

Benth.

CROSFEBR

42

Mali02

mi-co-do-de-ch

Fabaceae

Detarium

microcarpum

Guill. & perr.

DETAMICR

43

Mali02

no-co-do-de-ph

Combretaceae

Pteleopsis

suberosa

Engl. & Diels

PTELSUBE

44

Mali02

mi-ve-do-de-ct-ph

Fabaceae

Pterocarpus

erinaceus

Lam.

PTERERIN

45

Mali02

mi-co-do-de-ct-ph

Loganiaceae

Strychnos

innocua

Delile.

STRYINNO

46

Mali02

pi-ve-do-de-ch

Fabaceae

Acacia

macrostachya

Reichb. ex. G Don.

ACACMACR

47

Mali02

mi-ve-do-de-ch

Anacardiaceae

Lannea

velutina

A. Rich.

LANNVELU

48

Mali02

mi-ve-do-ch

Sapotaceae

Vitellaria

paradoxa

Gaertn.f.

VITEPARA

49

Mali03

pi-ve-do-de-ph

Fabaceae

Faidherbia

albida

(Delile) A. Cheval.

FAIDALBI

50

Mali03

na-ve-do-pv-th

Poaceae

Indet03/02

 

_

INDE

51

Mali03

na-ve-do-hc

Asteraceae

Indet03/03

 

_

INDE

52

Mali03

na-ve-do-pv-th

Poaceae

Indet03/04

 

_

INDE

53

Mali03

na-ve-do-ch

Fabaceae

Indet03/05

 

_

INDE

54

Mali04

mi-ve-do-ct-ph

Capparidaceae

Indet04/01

 

_

INDE

55

Mali04

mi-ve-do-ct-ph

Combteaceae

Combretum

mali04/02

_

COMBMALI

56

Mali04

na-ve-do-ch

Tiliaceae

Grewia

mali04/03

_

GREWMALI

57

Mali04

na-ve-do-pv-th

Poaceae

Indet04/04

 

_

INDE

58

Mali04

na-ve-do-hc

Fabaceae

Indet04/05

 

_

INDE

59

Mali04

na-ve-do-hc

Acanthaceae

Indet04/06

 

_

INDE

60

Mali04

na-ve-do-th

Rubiaceae

Borreria

mali01/09

_

BORRMALI

61

Mali04

nc-ve-do-ph

Euphorbiaceae

Indet04/08

 

_

INDE

62

Mali05

mi-co-is-ct-ph

Fabaceae

Parkinsonia

aculeata

Linn.

PARKACUL

63

Mali05

no-pe-do-hc-li

Convolvulaceae

Convolvulus

mali05/02

_

CONVMALI

64

Mali05

na-ve-do-hc-ad

Poaceae

Cynodon

dactylon

Pers.

CYNODACT

65

Mali05

mi-la-do-hc-ad

Malvaceae

Indet05/04

 

_

INDE

66

Mali05

pi-ve-do-ct-ph

Fabaceae

Faidherbia

albida

(Delile) A. Cheval

FAIDALBI

67

Mali06

me-co-do-de-ct-ph

Bombaceae

Adansonia

digitata

Linn._

ADANAETH

68

Mali06

na-ve-do-pv-hc

Poaceae

Indet06/04

 

_

INDE

69

Mali06

no-ve-do-ch

Combretaceae

Combretum

mali06/03

_