Community participatory landscape classification and biodiversity assessment and monitoring of grazing lands in northern Kenya

Journal of Environmental Management 90 (2009) 673e682 www.elsevier.com/locate/jenvman

Community participatory landscape classification and biodiversity assessment and monitoring of grazing lands in northern Kenya Hassan G. Roba, Gufu Oba* ˚ s, Norway NORAGRIC, Department of International Environment and Development Studies, Norwegian University of Life Science, P.O. Box 5003, N-1432 A Received 2 June 2007; received in revised form 22 November 2007; accepted 23 December 2007 Available online 12 February 2008

Abstract In this study, we asked the Ariaal herders of northern Kenya to answer ‘‘why, what and how’’ they classified landscape, and assessed and monitored the biodiversity of 10 km2 of grazing land. To answer the ‘‘why question’’ the herders classified grazing resources into 39 landscape patches grouped into six landscape types and classified soil as ‘warm’, ‘intermediate’ or ‘cold’ for the purpose of land use. For the ‘‘what question’’ the herders used soil conditions and vegetation characteristics to assess biodiversity. Plant species were described as ‘increasers’, ‘decreasers’ or ‘stable’. The decreaser species were mostly grasses and forbs preferred for cattle and sheep grazing and the increasers were mostly woody species preferred by goats. The herders evaluated biodiversity in terms of key forage species and used absence or presence of the preferred species from individual landscapes for monitoring change in biodiversity. For the ‘‘how question’’ the herders used anthropogenic indicators concerned with livestock management for assessing landscape potential and suitability for grazing. The anthropogenic indicators were related to soils and biodiversity. The herders used plant species grazing preferences to determine the links between livestock production and biodiversity. By addressing these three questions, the study shows the value of incorporating the indigenous knowledge of herders into classification of landscape and assessment and monitoring of biodiversity in the grazing lands. We conclude that herder knowledge of biodiversity is related to the use as opposed to exclusive conservation practices. This type of knowledge is extremely valuable to conservation agencies for establishing a baseline for monitoring changes in biodiversity in the future. Ó 2008 Elsevier Ltd. All rights reserved. Keywords: Anthropogenic indicators; Ariaal; Biodiversity; Indigenous knowledge; Grazing suitability; Landscape classification; Landscape potential

1. Introduction The assessment and monitoring of the biodiversity of grazing lands in Africa in general face methodological problems in understanding how the exploitation of grazing lands contributes to the loss of biodiversity. Ecologists and conservationists often make two assumptions. The first assumption is that the traditional system of land use by livestock grazing contributes to the loss of rangeland biodiversity. The second assumption is that the assessment and monitoring of the changes in biodiversity of the communal grazing lands would require technical methods implemented by ecologists. In both

* Corresponding author. Tel.: þ47 64965517. E-mail address: [email protected] (G. Oba). 0301-4797/$ - see front matter Ó 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.jenvman.2007.12.017

cases, the information collected would assist conservationists to make management decisions or to test scientific hypotheses on the relationship between the status of biodiversity and the pressure of exploitation. However, there is a third dimension of biodiversity that is rarely considered by conservationists, namely the decisions taken by local pastoralists with regard to the management of daily livestock grazing. The wealth of knowledge that resource users gather from their daily assessment and monitoring of rangeland biodiversity for livestock grazing is seldom acknowledged. The systematic indigenous knowledge of herders for assessing and monitoring the grazing lands could be incorporated into ecological methods for decision-making with regard to the status of biodiversity. Answering such questions as ‘‘why monitor’’, ‘‘what should be monitored’’ and ‘‘how to conduct monitoring or assessments’’ (Yoccoz et al., 2001) is relevant

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H.G. Roba, G. Oba / Journal of Environmental Management 90 (2009) 673e682

in understanding participatory assessment of rangeland biodiversity. The ‘‘why question’’ calls for rationalizing the reasons for monitoring biodiversity, the ‘‘what question’’ demands variables that need to be measured, while answering the ‘‘how question’’ would help resource managers to interpret the data collected in terms of management decisions (Yoccoz et al., 2003). By addressing the three questions, resource managers and conservationists will reach important decisions on how to combine the use of ecological methods and indigenous knowledge methods in order to promote community participation in biodiversity assessment and monitoring. For herding communities throughout Eastern Africa, range management incorporates the mosaics of landscapes that comprise the vast grazing lands. Herders’ knowledge of landscapes, which includes the broader traditional ecological knowledge of humaneenvironmental relations (BarreraBassols and Zinck, 2003; Berkes et al., 2000; Hellier et al., 1999; Johnson, 2000; Jungerius, 1998; Turner et al., 2000), could be used to answer the three research questions (Fernendez-Gimenez, 2000; Scoones, 1989). Herders’ knowledge of landscape plays an important role in livestock and biodiversity management, and answering the question of ‘‘why’’ could be relevant for understanding the purposes of landscape classification. In answering the ‘‘what question’’ for example, empirical data used for making decisions may vary between ecological methods and the variables (hereafter referred to as ‘indicators’) used by ecologists and herders. These ecological indicators are well known by scientists and standardized methods for measuring them exist. The pastoralists, for their part, use composite indicators that include both environmental variables (physical and biological) and anthropogenic indicators (Oba and Kotile, 2001; Oba and Kaitira, 2006). They use such indicators for making decisions with regard to livestock production, land use suitability related to conditions of soils, and value-weighted changes in plant species preferred by livestock for grazing. The anthropogenic indicators are value-weighted variables that use inferences from livestock production based on biological indicators, such as plant species. We suggest that ecological and anthropogenic indicators that could be used to address the ‘‘what question’’ could have complementary roles in assessing and monitoring biodiversity (Berkes et al., 1998). For example, pastoral herders are known to describe landscapes according to the physical characteristics of soil, landforms and vegetation (Oba et al., 2000; Verlinden and Dayot, 2005). These methods are also used in conventional landscape analysis (Fairbanks and Benn, 2000; Pressey et al., 2000). In addition, herders use vegetation and socio-cultural values of land use potential to reconstruct the effects of historical land use on landscape change (Sheuyange et al., 2005). Our study used local landscape knowledge of the Ariaal pastoralists of northern Kenya to address the ‘‘why’’, ‘‘what’’ and ‘‘how’’ questions of grazing land classification, biodiversity assessment and monitoring. Based on previous research (e.g. Oba et al., 2000; Mapinduzi et al., 2003; Oba and Kotile, 2001; Sheuyange et al., 2005; Oba and Kaitira, 2006), we established herder knowledge of landscapes as being universal for range

management. Thus, in addressing the ‘‘why classify grazing landscape’’ question, we tried to understand the indigenous range management knowledge, which has an impact on the way government departments should address conservation. For addressing the ‘‘what question for assessing and monitoring biodiversity’’ we were interested in understanding the indicators herders used, while for addressing the ‘‘how question’’ we were interested in the way herders used the physical and biodiversity indicators of the grazing lands to make livestock management decisions concerning landscape grazing potential (LGP) and landscape grazing suitability (LGS). In this regard our aims were: (1) to understand the criteria the Ariaal herders used for landscape classifications and their reasons for doing so (the ‘‘why’’ question); (2) to identify (with the help of the herders) the indicators that the community used for the assessment of biodiversity change (the ‘‘what’’ question); and finally (3) to understand how herders used ecological and anthropogenic indicators for decision-making with regard to livestock management (the ‘‘how’’ question). 2. Methods 2.1. Study area The study was conducted in Karare on the southern fringes of Marsabit Mountain in northern Kenya (N 02 100 and E 037 520 ). The area is geologically of volcanic origin (Sinda, 1981) with Calcaric Regosols and Chromic Vertisol soils (Awere-Gyekye, 1984). The climate is sub-humid with bimodal rainfall, with long rains between March and May and short rains between October and November. The mean annual rainfall is about 600 mm yr1 (Jatzold, 1995). The vegetation is classified as Pennisetum/Bothriochloa (perennial grassland) (Awere-Gyekye, 1984). The landscapes of Karare are presently threatened by bush encroachment (Roba and Oba, unpublished data). The Ariaal pastoralists manage cattle and small stock and conduct limited cultivation. Livestock stocking density in the settlement rangelands varies between 5 and 10 tropical livestock units/km2 (1 TLU ¼ 250 kg bovine). The settlement rangelands have been exploited for more than 30 years, more intensively since 1974 when the first batch of the families settled in Karare (Roba and Oba, unpublished data). Livestock management is based on herder landscape assessments and monitoring during daily herding activities. Seasonal livestock mobility takes advantage of heterogeneous landscapes and grazing resource monitoring. We selected a rangeland of 10 km2 in the vicinity of Karare settlements for conducting the survey to address the ‘‘why, what and how’’ questions of landscape classification, biodiversity assessment and monitoring. The selected area is within the daily grazing distance with which the herders from Karare were most familiar. 2.2. Data collection Between July and August 2004, four herders from the Karare and nearby settlements who were knowledgeable about the local landscapes joined our team to conduct rangeland

H.G. Roba, G. Oba / Journal of Environmental Management 90 (2009) 673e682

biodiversity assessments. From the previous studies in the region, we had established that herders have environmental knowledge that is comparable across the community, particularly those of decision-making age (>40 years). The elderly herders had numerous years of herding experiences since their youth. As reported elsewhere, the number of herders involved in a survey is not as important as the selection of key knowledgeable individuals (Oba and Kaitira, 2006). The elders who joined the field survey team in this study varied in age from 50 to 60 years. After briefing them on the objectives of the study, we conducted interviews in the field while walking across heterogeneous landscapes over a period of two days. This was aimed at establishing baseline information as well as agreeing on terminologies the herders used for landscape classification and the indicators they selected for assessing and monitoring biodiversity change. We asked the following questions: (i) why do the Ariaal herders classify the landscapes of the grazing lands? (ii) What ecological and anthropogenic indicators do they use for landscape and biodiversity assessment and monitoring? (iii) How do they use physical characteristics of the landscape, biodiversity and anthropogenic indicators to make management decisions? The next field activity involved joint transect walks across 39 landscape patches (see below) for about two weeks to conduct assessments according to the traditional methods described by the Ariaal herders (the method locally referred to as sarr). Here we had two aims. Firstly we wanted to demonstrate ‘‘the how’’ the task of herder landscape classification and biodiversity assessment and monitoring could be achieved. Secondly, we wished to conduct the actual assessments with herders to understand the environmental status of the herders’ indicators in the sampled area, based on the herders’ knowledge. We requested the herders to conduct assessments of different environmental indicators using traditional methods. To ensure that our approach was comparable to that used by the herders, we requested them to use landscape patches for making grazing resource assessments. We then used conventional transects to capture as many diverse landscape patches across different landforms as possible. The assessments were made along eight 2 km transects that transverse the 39 heterogeneous landscapes patches (see Supplementary data). Along each transect, we made 14 stops to conduct landscape assessments with the herders. To address the ‘‘why question’’ herders classified the landscape using soil and vegetation characteristic. For each of the landscape patches, herders used soil colour and texture to classify and assess soil conditions for the purpose of livestock management. The soils were classified into three types: ‘warm’, ‘cold’ and ‘intermediate’. For ‘‘what question’’ herders used soil conditions and vegetation indicators to assess landscape change. The soil conditions were categorized into degraded and stable. We focused on vegetation assessment and monitoring by requesting the herders to make ‘plots’ across each landscape patch each stop along the transects. They did this by stepping one step backward (herbaceous species), two steps (shrubs species) and five steps for (tree species) from central points. We formed nested ring ‘plots’

675

with radius of approximately 1 m (one step), 2 m (two steps) and 5 m (five steps). A total of 112 nested ‘plots’ corresponding with different patches were surveyed and herders identified all the plant species. We then made estimations of herbaceous and woody covers. Herders described plant species either as: ‘‘not changing’’ (stable), ‘‘increasing’’ (increasers), or ‘‘decreasing’’ (decreasers) in reference to species trends at landscape scale. These are common terms herders used when assessing trends of vegetation or any other populations of animals. For each landscape patch, they identified the key indicator plant species and noted their presence or absence. In order to address the ‘‘how question’’, we requested the herders to assess the anthropogenic indicators that reflected the potential of landscapes for grazing (LGP) and landscape grazing suitability (LGS) by different livestock species. The herders relied on the ecological indicators and their implications for livestock production. Herders rated the two anthropogenic indicators for the same patches on ordinal scales as high, moderate, or low. Landscapes with high potential can withstand high exploitation pressure without undergoing irreversible degradation, while the opposite holds true for landscapes with low grazing potential (Oba et al., in press). LGP is influenced mostly by soil types (Oba and Kotile, 2001) and is a more permanent feature of landscapes than LGS (Oba et al., in press). Herders traditionally observed the LGS through livestock production performances, including changes in body weight and fur quality, the level of milk produced and rumen fill. Herders were also asked to give livestock grazing preferences for each plant species and rank the preferences on a scale of 1e6 (from most preferred to unpalatable by different livestock species).

2.3. Data analysis To address the ‘‘why question’’, we analysed herder landscape classification criteria and reported their narratives on the reasons for rangeland assessments. We also analysed herder assessments of soils in terms of distribution of soil types across the landscapes. For the ‘‘what question’’, firstly, we described herder soil condition types. Secondly, the general linear model (GLM) (SAS, 2003) was used to understand spatial variations of herbaceous and woody species richness, cover and abundance of increaser, decreaser and stable species across landscape types. Thirdly, we used the abundance of increaser, decreaser and stable species to determine the importance of plant species grazed by different livestock species (cattle, goats and sheep). Fourthly, we used the absence and presence data of indicator species to corroborate levels of key species losses in individual landscapes. To address the ‘‘how question’’, first we used GLM to analyse herder assessments of anthropogenic indicators showing how the LGP and LGS indices varied across grazing landscape patches. To investigate if there was a direct relationship between anthropogenic and biodiversity indicators, we used the Pearson correlation. Finally, livestock grazing forage preference ranks were

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used to determine important plant species grazed by different stock species. 3. Results 3.1. The ‘‘why’’ question for landscape classification and assessment Landforms are the main criteria used by the Ariaal herders to classify landscapes. The common names used in landscape taxonomy are based on soils (n’gulopo). The landscape names begin with the soil colour followed by the landform and then by the vegetation description. The soil colours are of three types: red soil (n’gulopo nanyoko), dark soil (n’gulopo narok) and grey soil (n’gulopo naibor). Next in importance were herders’ descriptions of landscape patches (Table 1). The main landscape units were Loruko (raised with good drainage), Erokor (gentle slope with scattered volcanic rocks), Engumoto (valley bottom), Lodonyo (elevated area including hills and hillocks) and Lbaa (riverine) (Table 1). Thirty-three percent of the landscape patches was of the type Loruko, 18% was Lodonyo, 17% was Lbaa, 11% was Ngosoro, 11% were Erokor and 10% were Engumoto. Full descriptions of the main landscape units are given in Table 1. The herders included vegetation attributes in the description of the landscapes, depending on whether or not a patch is dominated by a species of a higher life form (e.g. trees). For example, a landscape patch characterized by red soil (n’gulopo nanyoko) representing uplands with good drainage (Loruko) and dominated by stands of Acacia tortilis (ntepes) is referred to as n’gulopo nanyokoeLorukoentepes in one word. If a landscape patch is characterized by thickets (essar), the landscape description becomes n’gulopo nanyokoeLorukoeessar. The physical and biological combinations of a landscape are considered for distributing livestock grazing. In addition to landscape patch names, the herders have local geographical names

that are used for directing grazing and settlement patterns. Herders are knowledgeable about each grazing area in terms of resource distribution, and associate each landscape with specific use during different seasons by different livestock species (Fig. 1A and Table 1). For the purpose of land use, herders classified the soils as ‘warm’ (n’gulopo nariwa), ‘cold’ (n’gulopo nairob) or ‘intermediate’ (ngulopo nariwaenairob). The concept of cold and warm soils is related to livestock management and encampments. The folk soil classes in the Karare area are mostly warm n’gulopo nariwa (68%) and intermediate n’gulopo nariwaenairob (20%). The cold n’gulopo nairob (13%), which is considered undesirable for establishing livestock encampments, is less common. The herders used the ‘warm’ and ‘cold’ soil dichotomy as indicator for assessing landscape functions in relation to the suitability for livestock grazing. A herder stressed the importance of soil and landscape preference as follows: ‘‘Usually we select ‘warm’ soils like those found in lmari for the livestock camps. We then graze the livestock in the nearby loruko, sirata, ntabas, sabsab, lodonyo (Local landscape types, see Supplementary data) and ngosoro (when it is not wet). Generally we avoid rocky landscapes including lbaa and erokor in addition to places with steep slopes such as upata’’. Herders inferred landscape suitability using the proxies of livestock production performances in terms of rumen fill, mating frequency, weight gains, and fur quality. Warm soils were considered better able to withstand livestock trampling pressure and therefore less susceptible to degradation than cold soils. According to another herder: ‘‘Both for grazing and setting up camps, n’gulopo nairob is not good as it forms dust that affects animal fur and causes livestock breathing problems. Livestock weight gain is less when settlements are placed in n’gulopo nairob. The cold

Table 1 Different landscape units as described by the Ariaal herders of the Marsabit district, northern Kenya Landscape types

Descriptions

Engumoto

This landscape is characterized by depressions or valleys. The soil type is mainly characterized as ‘warm’ with colours ranging from dark to dark brown. Key fodder species include Andropogon longipes and Argyrolobium fischeri, among others. The vegetation in this landscape remains green even during the dry season, and the landscape is useful for all livestock types, mainly in the dry season. The main physical characteristic of this landscape is the presence of boulders of volcanic lava origin that limit livestock movements. The soil is characterized mainly as ‘warm’ with variable colours. The vegetation is also variable but dominated by species such as Terminalia brownii, Grewia villosa, Croton dichogamus and Leptochloa obtusiflora. This landscape is preferred for small stock management. This landscape is associated with seasonal streams and dry riverbeds. The soil is classified mainly as ‘cold’ with variable colour. The vegetation is dominated by species such as Andropogon longipes and Exatheca abyssinica and remains green for a longer time, even in the dry season. The landscape is a key dry season grazing area, and is preferred by all classes of livestock. This landscape is wedge-shaped with gentle slopes on two sides. The herders referred to this shape as the ‘‘back of a chameleon’’. The soil is mainly characterized as ‘warm’, and in a few places as ‘cold’, with variable colour. The vegetation cover is quite variable but characteristic species included Securinega virosa and Acacia horrida, among others. The landscape is preferred by all livestock classes. This landscape is characterized by black cotton soil that tends to form deep cracks during dry seasons, while in the wet seasons it turns into sticky mud. The soils in this landscape are generally considered ‘warm’ with variable colour. Major vegetation types include Duosperma eremophilum and Acacia seyal. The landscape is preferred for grazing all livestock classes especially in the dry season. This landscape has high elevations with good drainage. The soil is mainly perceived as ‘cold’, especially on the sides facing direct wind. Soil colour is variable. The vegetation is highly variable and includes species such as Securinega virosa and Abutilon mauritanium. The landscape is mainly preferred by goats, but is used by all livestock classes during the dry season, as it is endowed with pasture due to inaccessibility.

Erokor

Lbaa

Loruko

Ngosoro

Lodonyo

H.G. Roba, G. Oba / Journal of Environmental Management 90 (2009) 673e682

A

677

Dry

Lodonyo

Erokor

Lbaa

Loruko

Engumoto

Dry & Wet

100 80 60 40 20 0 Ngosoro

Use frequency (%)

Wet

Local landscape types

B 100 80 60 40 20 0 -20

Lodonyo

Engumoto

Erokor

Lbaa

-60

Loruko

-40 Ngosoro

% Frequency of indicator species

Presence Absence

Local landscape types Fig. 1. (A) Local landscape types and the preferred season of grazing and (B) fodder value of plant species categories for different livestock species in local landscapes of the Karare rangelands in northern Kenya.

soil is mainly represented by n’gulopo nanyoko (red soil). Although this soil type may support as many plant species as n’gulopo nariwa (warm soil), the vegetation quickly ‘disappears’ due to loose rooting when livestock grazing is heavy’’. 3.2. The ‘‘what question’’ for landscape and biodiversity assessment and monitoring In addressing the ‘‘what question’’, herders assessed landscape change in terms of soil and vegetation indicators. They used the physical characteristics of soil and the effects on livestock to assess landscape change, and described soil as ‘stable’ (kesopat n’gulopo) or ‘eroded’ (metoki n’gulopo). Fifty-three percent of the landscapes in the study area,

according to herder assessments, had stable soil, while 47% were considered eroded. The degraded soils are referred to as kogolkwe or torok. Such landscapes have poor herbaceous cover and are perceived by the herders to have low utility value for livestock grazing. For vegetation indicators they expressed woody cover as sparse, thick or very thick, and used woody species and herbaceous species richness (which are proxy indicators of biodiversity) when describing landscapes (Table 2). In terms of changes in the quality of vegetation, herders monitored individual forage species in relation to their fodder values. They identified 59 plant species in 26 families during the joint transects walks. Of these plant species, they described 66% as stable, 12% as increaser and 14% as decreasers (Table 3). The increasers were mainly shrubs in

Table 2 Distribution of vegetation indicators across local landscapes in the Marsabit district, northern Kenya Landscapes types

Ngosoro Loruko Lbaa Erokor Engumoto Lodonyo F-test P

Indicators Herbaceous species richness

Woody species richness

Herbaceous cover (%)

Woody cover (%)

‘Increaser’ species (abudance)

‘Decreaser’ species (abudance)

‘Stable’ species (abudance)

5.66  0.63 6.9  0.35 7.5  0.35 7.2  0.27 7.40  0.40 6.57  0.53 1.44 NS

1.33  0.39 3.08  0.20 3.5  0.35 4.25  0.39 3.90  0.37 3.00  0.35 6.69 ***

24.6  7.28 29.4  4.03 38.12  4.88 35.25  7.01 36.20  7.92 29.52  5.40 1.13 NS

7.5  2.0 22.85  2.65 18.6  3.09 16.08  2.30 34.50  2.83 24.15  4.81 3.92 ***

2.0  0.46 3.85  0.27 4.04  0.27 3.58  0.37 4.80  0.35 3.21  0.35 5.41 ***

0.83  0.27 1.68  0.18 2.04  0.21 2.33  0.28 1.80  0.29 1.42  0.24 3.1 **

3.91  0.64 3.72  0.28 4.10  0.41 5.00  0.42 4.00  0.42 4.38  0.44 1.03 NS

*P < 0.05, **P < 0.01, ***P < 0.001,

NS

P > 0.05.

Botanical name

Duosperma eremophilum (Milne-Redh.) Brummitt Cardamine Africana L. Seddera hirsuta Damm ex Hallier f. Abutilon mauritanium Sweet Securinega virosa (Willd.) Baill. Pennisetum mezianum Leek. Hoslundia opposita Vahl Cordia crenata Roem. & Schult. Acacia horrida Willd. Volutaria lippii Cass. Andropogon longipes Hack. Commiphora africana (Engl.) J.B. Gillett Zanthoxylum chalybeum Engl. Hibiscus micranthus L. f. Dichanthium foveolatum (Delile) Roberty Grewia villosa Willd. Tragus berteronianus Schult. Osyris lanceolata Hochst. & Steud. Aspilia mossambicensis (Oliv.) Wild. Acacia tortilis Hayne Paspalidium desertorum Stapf. Carissa edulis Vahl

Samburu (Ariaal) name

Trends

Fodder value

PI

Asparagaceae Leguminosae Burseraceae Leguminosae Poaceae Boraginaceae Poaceae

Arigeek Girigiri Hagar Husura Ikawa Ilgoita Ilperesiwas

Leguminosae

Life form

Frequency (%)

S S S I D I D

GO GO, CAM GO, SHP GO, SHP C, GO GO, SHP C

2 1 3 2 1 4 1

SH SH T H G SH G

8.3 16.6 16.6 8.3

Imiim

S

GO

3

H

Tiliaceae Gramineae

Irii Laburan

S S

SHP NON

3 6

Euphorbiaceae Gramineae Lamiaceae Gramineae Simaroubaceae Combretaceae Ebenaceae Leguminosae (Papilionoideae) Acanthaceae

Lageridinai Lamruai Lamuran Lanana Lasarmai Lbukoi Lchingei Ldakaat

I S D S I S I S

NON SHP GO, SHP C GO NON NON SHP

Ldurukunyanto

I

Brassicaceae Convolvulaceae Malvaceae Euphorbiaceae Poaceae Lamiaceae Boraginaceae Leguminosae Asteraceae Poaceae Burseraceae

Lecholo Leturot Lkarbotia Lkirebuk Lkurme Lkurong Lmanturee Lmunyi munyi Lodwaporo Loisao Loishimi

Rutaceae Malvaceae Poaceae Tiliaceae Poaceae Santalaceae Compositae Leguminosae Poaceae Apocynaceae

Ngosoro

Loruko

Lbaa

Erokor

Engumoto

Lodonyo

65.6

16.8 5 10 55

16.6 91.6

10 60

25

12.5

9.45

25

60

15

8.3

21.8

5

16.6

10

5

SH G

0 0

6.25 0

0 0

0 8.3

10 0

5 0

6 2 3 1 4 6 6 3

SH G H G T SH

16.6 16.6 16.6 16.6 0

6.2 21.8 40.6 25 18.7

25 10 30 15 35

8.3 0 50 8.3 0

0 0 20 30 70

H

16.6

3.1 15.2

15 35

0 41.6

0 20

5 25 20 25 5 5 5 25

ALL

4

SH

0

6.2

5

S S I S S S S I I D S

SHP NON GO, SHP GO C NON GO GO C, SHP C SHP

1 6 5 1 2 6 5 3 3 1 3

SH H SH G G SH T H G T

8.3 25 66.6 0 50 0 0 16.6 0 25 8.3

0 3.1 71.8 12.5 31.2 3.1 3.1 34.3 6.2 9.3 46.8

5 0 85 40 50

8.3 0 66.6 8.3 33.3

20 60 30 90

5 65 20 40

5 50 20 30 45

41.6 16.6 8.3 75

70 30 0 30

25 5 20 35

Loisugii Lokimeki Lonoro

S S D

GO GO C

4 3 2

T SH G

8.3 16.6 0

12.5 3.1

0 5

8.3 8.3

0 10

5 0

Lopopoi Lorimowo Losesiai Loyia pasoi Ltepes Lterian Misigiyoi

S S S S S D S

GO GO, SHP GO NON GO SHP GO

2 2 4 6 1 2 3

SH G

0 0

15.6 3.1

66.6 8.3

0 0

25 5

SH T G SH

25 16.6 0 0

6.2 15.6 3.1 0

15 0 5 5 10 0 5

16.6 41.6 8.3 0

10 10 20 0

5 15 5 5

20

H.G. Roba, G. Oba / Journal of Environmental Management 90 (2009) 673e682

Asparagus buchananii Baker Acacia brevispica Harms Commiphora paolii Chiov Indigofera lupatana Baker f. Setaria appendiculata Stapf Cordia sinensis Lam. Leptochloa obtusiflora Trin. ex Steud. Tephrosia subtriflora Hochst. ex Baker Grewia tembensis Fresen. Dactyloctenium bogdanii S.M. Philips Croton dichogamus Pax Cynodon lemfuensis Vanderyst Ocimum basilicum L. Brachiaria leersioides Stapf Harrisonia abyssinica Oliver Terminalia brownii Fresen. Euclea schimperi (A. DC.) Dandy Argyrolobium fischeri Taub.

Family

678

Table 3 List of species recorded in the Karare location of the Marsabit district during joint transect walks

3.3. The ‘‘how question’’ for biodiversity monitoring The whole purpose of herder landscape classification, assessment and monitoring of vegetation change is aimed at improving livestock management. Changes in livestock production

A 100 90 80

Frequency (%)

2.2 SH 5 GO S Sunoni Verbenaceae

Malvaceae

D ¼ decreaser, I ¼ increaser, S ¼ stable, H ¼ herbs, G ¼ Grass, Sh ¼ shrubs, T ¼ tree, C ¼ cattle, GO ¼ goats, SHP ¼ sheep, CAM ¼ camels, PI ¼ preference index.

18.7 15.6 3.1 25 0 16.6 8.3 0 0 0

679

contrast to the decreasers, which were mostly grasses and forbs. The stable species included diverse life forms (Table 3). The analysis of landscape level variations in increaser, decreaser and stable species, as well as the different life forms are summarized in Table 2. At landscape level, the dominance of individual species was varied (Table 3). In terms of fodder values, the increaser species were mainly useful for goats, while the decreaser species were reported to be the main fodder for cattle and sheep (Fig. 2A). The key indicator species associated with individual landscape types were identified. These indicator species included Andropogon longipes (for Ngosoro and Lbaa), Leptochloa obtusiflora (for Loruko), Setaria appendiculata (for Erokor and Engumoto) and Brachiaria leersioides (for Lodonyo). Engumoto was codominated by three species (the other two being L. obtusiflora and Pennisetum mezianum) mostly preferred by cattle. Loruko was co-dominated by the least preferred species (Abutilon mauritanium and Solanum incanum) (Table 3). Ngosoro had greater losses of the key fodder species, while Lodonyo experienced the least decline (Fig. 1B).

Increaser Decreaser Stable

70 60 50 40 30 20 10 0 Cattle

Goats

Sheep

All stock

Non

Grazing preference class

B 100 90 80

Frequency (%)

20 5 0 35 0 10 10 0 30 0

20 50

33.3 8.3 8.3 50 16.6 75 8.3 25

Euphorbiaceae Acanthaceae Tiliaceae Acanthaceae

Sharda Sieti Sigit Sigtet Sucha Sugumai Surubei

S S S S S I S

ALL GO SHP GO, SHP CAM NON GO

3 4 3 1 2 6 3

H H H SH H SH H

16.6

40 10 10 5 0 55 10

5 10 0 10 8.3 8.3 0 5 0 5 Capparaceae Balanitaceae Cyperaceae

Sangaretai Sarai Seyey

S S S

GO G, SHP SHP

4 4 4

T G

0

0 60 10 50 41.6 41.6

F H G H G

6.2 3.1

0 10 33.3 16.6 16.6

12.5 3.1 12.5 3.1 9.3 68.7 18.7 6.2

Flueggea virosa (Willd.) Royke Isoglossa oerstediana Lindau Commelina africana L. Indigofera arrecta Hochst. ex Rich. Sporobolus fimbriatus Nees Solanum incanum Ruiz & Pav. Sporobolus stapfianus Gand. Plectranthus igniarius (Schweinf.) Agnew Thilachium africanum Lour. Balanites aegyptiaca Sands Schoenoxiphium lehmannii Kunth ex Steud. Indigofera sp. Acalypha fruticosa Forssk. Justicia diclipteroides Lindau Grewia bicolor Juss. Barleria spinisepala E.A. Bruce Not identified Abutilon pannosum (G. Forst.) Schltdl. Lippia somalensis Vatke

Euphorbiaceae Acanthaceae Commelinaceae Leguminosae Poaceae Solanaceae Poaceae Labiatae

Nargoki Nasungoyo Natitiye Nchode Ndalangwanyi Ntulelei Nyaput Sali

I S D S S I D S

NON GO SHP GO SHP SHP ALL GO

6 2 2 4 2 5 4 4

SH

0 0 0 8.3 0 41.6 16.6 0

5 10 5 5 10 35 15

0 0

15 30 25

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Goats Sheep Cattle

70 60 50 40 30 20 10 0 1

2

3

4

5

Plant species grazing preference categories Fig. 2. (A) Frequency (%) of ‘absence’ and ‘presence’ of key indicator species in local landscapes and (B) grazing preferences of plant species by different livestock species in the Karare area of northern Kenya.

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performances were inferred from soils which influences landscape grazing potential and suitability. According to herders, the Karare landscapes varied in grazing potential, with 85% categorized as having ‘high’, 3% as having ‘moderate’ and 12% as having ‘low’ potential. Landscape grazing potential (LGP) varied across landscape types (F5,112 ¼ 3.43, P ¼ 0.007). The LGP was significantly correlated with herbaceous cover (r ¼ 0.23, P ¼ 0.01) and composition (i.e. abundance) of increaser (r ¼ 0.3, P ¼ 0.002) and decreaser (r ¼ 0.2, P ¼ 0.01) species. There was no correlation between LGP and the herbaceous and woody species richness, woody cover and the abundance of stable species (P > 0.05). Herders described the Karare landscapes generally as suitable for all livestock species (cattle, goats and sheep) (84%), and less suitable for cattle alone (10%) or for goats/ sheep alone (6%). Although landscape grazing suitability (LGS) did not show spatial variability across landscape types (P > 0.05), it was positively correlated with woody cover (r ¼ 0.24, P ¼ 0.01), reflecting little changes in herder management decisions. There was no significant correlation (P > 0.05) between LGS and herbaceous and woody species richness, herbaceous cover and the abundance of increaser, decreaser and stable species. Cattle grazing was influenced mostly by the availability of the most preferred species, sheep by moderately preferred species, while goats were mixed feeders (Fig. 2A, B). According to herder knowledge, some species were preferred as fodder more than others (Table 3). Herders confirmed that when they assessed and monitored the grazing land biodiversity, they did not always ask all the three questions, since the ‘‘why question’’ has been established over long periods of herding and the ‘‘what question’’ is a daily exercise. It is the ‘‘how question’’ which is linked to the requirements of livestock that concerns them on daily basis. 4. Discussion 4.1. The ‘‘why question’’ for landscape classification and assessment Herders’ use of soils, landforms and vegetation in landscape classifications corresponded with the folk taxonomy of Berlin (1973). Soil types formed the basic level at which the herders classified landscapes, which is a common feature that all herders are known to use (e.g. Western and Dunne, 1979). The herders perceived that the different indicators used in landscape analysis are interrelated and that each factor influences the other at the next lower levels. As a basis for landscape classification, the soil types determined the characteristics of landforms, which in turn affected the vegetation types, especially the woody vegetation. Reliance on the knowledge of woody vegetation among herding communities has also been reported elsewhere (Barrow, 1996; Smith et al., 1996). The herbaceous vegetation was the product of recent rains and was therefore not used, at least not in the Karare landscape classifications. Dwarf shrubs similar to trees are important in classifying landscapes (Roba and Oba, unpublished).

The different ecological indicators used in local landscape patches played mutually reinforcing roles in herders’ management decisions, particularly in locating individual landscapes in geographical spaces for aiding livestock mobility (Oba, 1994). The herders’ principal use of soils as indicators for land use decisions was reflected by the importance they attached to soil types. Herder classifications of soils into warm and cold are important criteria for understanding local soil conditions, in relation to livestock management. Warm/cold classes have also been used in indigenous cultural soil classifications (Oba, 1994; Western and Dunne, 1979). The herder soil dichotomy could be related to soil texture. The warm soils have been shown to have greater organic carbon than the cold soils (H. G. Roba and G. Oba, unpublished data). In this study, assessments of landscapes based on herder soil descriptions showed that the area is dominated mainly by warm soils, which are highly suitable for livestock production. Herder knowledge of the physical characteristics of soil is important in monitoring land degradation, through indirect observation of change in suitability for livestock production. Such indigenous knowledge of soil conditions has also been used by the farming communities (Goma et al., 2001; Winklerprius, 1990). 4.2. The ‘‘what question’’ for landscape and biodiversity assessment and monitoring The high proportion of eroded soils across the landscapes may be associated with historical land use by livestock grazing. According to the herders, degraded soils are a threat to animal health. Such soils are avoided when establishing pastoral encampments, particularly for cattle management. However, they may be preferred by camel owning pastoralists, since soil baths are part of the requirements for good camel husbandry (Oba, 1994). The Ariaal people, as cattle pastoralists, typically avoid dusty and rocky landscapes. From herder narratives it is clear that they are knowledgeable about the conditions of the soils, vegetation rooting and the effects of heavy grazing. Although herders used soil as indicators of change in landscape suitability for livestock, changes in soil conditions have direct impacts on the vegetation and are therefore a relevant indicator for biodiversity monitoring. The Ariaal pastoralists used the quantity and distribution of vegetation, especially of fodder value, as important criteria for making landscape assessments. Observed differences in the distribution of woody species richness and cover were in agreement with herders’ criteria for landscape classification. In addition, differences in the frequencies of increaser and decreaser species showed that the landscapes experienced different levels of use. Livestock management decisions, including moving to a new locality, are usually made after continuous monitoring. When monitoring the change in the quality of livestock fodder, herders relied on their knowledge of the increaser, decreaser and stable species. Usually decreaser species were those most affected by grazing and tended to decline across landscapes where past land use has been heavier. The difference in the

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frequency of increaser, decreaser and stable species across landscape patches served mainly as indicators of change in landscape utility for livestock grazing. From the results we inferred that herders categorized biodiversity according to the ‘utilization value’. The ‘good’ biodiversity decreases with overgrazing, while the ‘bad’ biodiversity increases with heavy use. Herders’ knowledge of plant species was related to livestock grazing preferences (Verlinden and Dayot, 2005). Increaser species, which are mainly shrubs, are good fodder for goats while cattle and sheep require decreaser species, which are mostly grasses and forbs. Herders’ knowledge of the dynamics of different species and their fodder value is useful in monitoring changes in vegetation structure at landscape level and the subsequent changes in landscape grazing suitability. More importantly, herders associated each landscape with a particular indicator species considered important for grazing. According to the herders, landscapes in the study area have undergone changes in terms of indicator plant species, which may be attributed to historical land use practices. According to the herder assessments, the state of biodiversity that is useful for livestock grazing can be assessed in terms of the presence of key forage species that usually characterize different landscapes. For this reason, herders almost always anticipated what species to expect for the different landscape types. The absence of key forage species in their view discloses the loss of biodiversity. Using the absence and presence data of indicator species therefore enables herders to identify landscapes that have experienced greater losses of biodiversity. This suggests that changes in key fodder species may serve as a diagnostic tool in the assessment and monitoring of biodiversity at landscape levels. This type of knowledge is extremely valuable to ecologists and conservation agencies for establishing baseline biodiversity for future monitoring. 4.3. The ‘‘how question’’ of monitoring biodiversity Pastoralists value landscape grazing potential (LGP) for making decisions related to the effectiveness of biodiversity management. According to the herders, each landscape has unique potential and suitability defined by ecological and anthropogenic indicators. The landscapes of the Karare rangelands are generally considered by the herders to have high grazing potential. Herders’ knowledge of LGP is important for determining land use and the level for stocking individual landscapes. Landscapes differed in LGP, showing a high level of consistency with herder knowledge of individual landscapes. Woody cover, herbaceous and woody species richness did not appear to affect decisions related to LGP. The extent of herbaceous cover and increaser and decreaser species, which are important in providing livestock forage influenced herder management decisions. The lack of any differences in landscape grazing suitability (LGS) across landscape types suggests that the landscapes of Karare are generally of high suitability for livestock grazing. The LGS index was not influenced by one factor, but by a multitude of factors such as herbaceous and woody species

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richness, herbaceous cover, and the frequencies of increaser and decreaser species. Thus, when relating the LGS to such factors, one may infer that the parameters are not independent of each other in determining landscape suitability, but play a complementary role in herder decisions. The positive correlation of bush cover with LGS requires careful interpretation. Firstly, anthropogenic indicators were used for decisionmaking. Secondly, in the case of LGS, the positive response to bushy plants implies that an increase in bush cover would prompt herders to alter their management decisions, perhaps in terms of livestock species composition, such as shifting from grazer to browser species (Thomas and Twyman, 2004). According to the Ariaal herders, increased threats of bush encroachment have forced them to increase goat-herding practices (Roba and Oba, unpublished). Herders assessed landscape suitability for different livestock species on the basis of the quality and quantity of vegetation. Landscapes with a high frequency of the preferred fodder species and fewer unpalatable plant species were considered most suitable for grazing. The species preference index provided important guidelines on how herders valued each landscape for grazing by different livestock species and allocated land use between different livestock species. A given landscape may be suitable for more than one livestock type, for example, cattle and small stock, depending on the availability of fodder species during different seasons (Oba and Kotile, 2001). Changes in landscape suitability due to the altered composition of important fodder species were closely monitored by the pastoral herders through direct observation in the field and indirectly by using livestock production performances (Bollig and Schulte, 1999; Oba and Kotile, 2001; Oba and Kaitira, 2006). The evidence from the current study emphasizes that any efforts in conserving biodiversity in the communal rangelands would have to be linked very closely to the goals of herder range management and their knowledge of the grazing preferred biodiversity, as opposed to the goals of ecologists, whose assessments and monitoring of biodiversity exclude human and livestock exploitations. 5. Conclusion In this study, which we conducted jointly with the Ariaal herders, we succeeded in addressing the ‘‘why, what and how questions’’ of landscape classification, biodiversity assessment and monitoring. For the ‘‘why question’’, the herders used their knowledge of landscape classification and assessment for determining general land use and suitability for livestock grazing. For the ‘‘what question’’ the herders used soil types and vegetation indicators for making decisions for the purpose of grazing. Changes in the cover and quality of vegetation, in terms of plant species composition, were monitored for inductive assessments of livestock grazing requirements. For the ‘‘how question’’, landscape grazing potential (LGP) and landscape grazing suitability (LGS) for different livestock species were influenced by changes in plant species composition and the loss of key forage species. We used the associations between ecological and anthropogenic indicators to investigate

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the possible decisions the herders made. The negative associations between ecological and anthropogenic indicators suggest altered management decisions by moving livestock, while the positive association probably implies new management strategies for changing herd composition. We suggest that the use of herder knowledge would provide robust participatory biodiversity assessment and monitoring methods for establishing community conservation of biodiversity in the grazing lands. From this study, we conclude that herder knowledge of biodiversity is related to the utilization of biodiversity as opposed to exclusive conservation methods. This type of knowledge is extremely valuable for conservation agencies for establishing a baseline for monitoring biodiversity in the future. Acknowledgments H.G. Roba thanks the Ariaal herders for their participation in the joint surveys. John Lekur and Hussein Wellaga are thanked for their help with the fieldwork. Fieldwork and writing of the article was supported by a grant from the Research Council of Norway through project no: 16139/S30. Appendix. Supplementary data Supplementary data associated with this article can be found in the online version, at doi: 10.1016/j.jenvman.2007.12.017. References Awere-Gyekye, K., 1984. Major Range Types in the South-Western Marsabit District of Northern Kenya Basic Map, first ed. UNESCOeIPAL, Nairobi. Barrera-Bassols, N., Zinck, A., 2003. ‘Land moves and behaves’: indigenous discourse on sustainable land management in the Pichataro, Patzcuaro Basin, Mexico. Geografiska Annaler 85A, 229e245. Barrow, E.G.C., 1996. The Drylands of Africa: Local Participation in Tree Management. Intiative Publisher, Nairobi. Berkes, F., Colding, J., Folke, C., 2000. Rediscovery of traditional ecological knowledge as adaptive management. Ecological Applications 10, 1251e1262. Berkes, F., Kislalioglu, M., Folke, C., Gadgil, M., 1998. Exploring the basic ecological unit: ecosystem-like concepts in traditional societies. Ecosystems 1, 409e415. Berlin, B., 1973. Folk systematic in relation to biological classification and nomenclature. Annual Review of Ecology and Systematics 4, 259e279. Bollig, M., Schulte, A., 1999. Environmental change and pastoral perceptions: degradation and indigenous knowledge in two African pastoral communities. Human Ecology 27, 493e514. Fairbanks, D.H.K., Benn, G.A., 2000. Identifying regional landscapes for conservation planning: a case study from KwaZulu-Natal, South Africa. Landscape and Urban Planning 50, 237e257. Fernendez-Gimenez, M.A., 2000. The role of Mongolian nomadic pastoralists’ ecological knowledge in rangeland management. Ecological Applications 10, 1318e1326. Goma, H.C., Rahim, K., Nangendo, G., Riley, J., Stein, A., 2001. Participatory studies for agro-ecosystems evaluation. Agriculture Ecosystems & Environment 87, 179e190.

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