Online Resource 1
Mapping Ethiopian wolf habitats in the Bale Mountains
Article name: Ecological bases of philopatry and cooperation in Ethiopian wolves
Journal: Behavioural Ecology and Sociobiology
Authors: Jorgelina Marino, Claudio Sillero-Zubiri, Paul J. Johnson, David W.
Macdonald
Corresponding author: Jorgelina Marino, e-mail: jorgelina.marino@zoo.ox.ac.uk,
address: Wildlife Conservation Research Unit (WildCRU), Department of Zoology,
University of Oxford, Tubney House, Abingdon Road, Tubney OX13 5QL, UK.
Content:
1. Study areas
2. Field data
3. Vegetation classifications
4. Validation of habitat quality types for wolves
5. Habitat mapping
6. References
1. Study areas
Ethiopian wolves (Canis simensis) inhabit the Afroalpine zone of the Ethiopian
highlands. In the Bale Mountains their distribution follows that of their diurnal rodent
prey, giant molerats (Tachyoryctes macrocephalus) and Murinae grass rats, whose
distribution correlates in turn with vegetation types and micro-topography (SilleroZubiri et al. 1995a, b). Optimal habitats for rodents in Bale are valley floors, swamp
shores and meadows, where vegetation is kept in permanent pioneer stages by the
fossorial activity of rodents and frost-induced soil movements (Sillero-Zubiri et al.
1995b). Giant molerats in particular - the largest and most preferred Ethiopian wolf
prey - prefer deep soils along drainage lines and swamp shores, in and around
rounded mounds called mima mounds (Gottelli and Sillero-Zubiri 1992).
Such optimal habitats for rodents characterize the Web Valley at around 3,500m and
the Sanetti Plateau between 3,800 and 4,000m, with vegetations dominated by short
herbs and grasses (typically Alchemilla abyssinica, Polygonum plebejum, Trifolium
acaule, Anthemis tigrensis, and Poa muhavurensis) and specked by bushes of
Helichrysum and Artemesia (Miehe and Miehe 1993). Heathlands instead dominate
the Tullu Deemtu area on the drier southern declivity of the Sanetti Plateau, up to
above 4,300m, with shrubs of Helichrysum splendidum up to 50cm tall and tussock
grasses in the open spaces in between (typically Agrostris quinqueseta and Festuca
richardii) (Miehe and Miehe 1993). In Tullu Deemtu the most productive areas are
restricted to drainage lines and bogs.
2. Field data
Variables relevant to the distribution of rodents were surveyed extensively in 179
point-samples during the 1999 dry season, mostly in January, covering the range of
vegetation types and landforms. Point samples were located every 200m along linetransects, between 2.2 and 4km in length, separated by 2,000m (four transects in
Web, five in Sanetti, and two in Tullu Deemtu). This sampling strategy covered the
range of vegetation variation more efficiently than a random sampling, deemed
impractical by the sheer size of the study area. Relevant vegetation changes occur at
fine-scales in relation to micro-topographic features, and the distances between
transects and sample points were considered large enough to avoid spatial autocorrelation and points were treated as independent.
Variables used to describe the vegetation at each sample point were:

percentage cover of vegetation (grasses, flowering plants or mosses)

percentage cover of bare ground

percentage cover of stone
Soil and rocks form a significant portion of the landscape and are likely to be captured
by image reflectance (Lewis 1998). The cover of bare ground, stone, and plants were
visually assessed on a circular area of 5m radius, referred to as a quadrat, using the
Braun-Blanquet scale (1= <5%; 2= 5-25%; 3= 25-50%; 4= 50-75%; 5= >75%). The
choice of quadrat size responds to the fine scale at which variations in plant
communities occur and follows previous studies to describe rodent-habitat
associations in the Bale Mountains. Most flowering plants were identified to the level
of species, and the National Herbarium in Addis Ababa helped with identifications of
some specimens. For grasses instead, approximations to species-level identification in
the field require much expertise and are particularly difficult during the dry season.
Thus grasses were considered a single category, and differentiated into short or tall
grass where they belonged to the ground or herbaceous layer respectively.
Information on vegetation height was recorded using the three-layer model
conventionally applied for Afroalpine-type vegetation, with few and low strata:

ground level: modal height <5 cm

herbaceous level: 5-30cm, and

shrub level: >20cm
Due to the small size and high diversity of the plants in the ground level layer, this
layer was described from a concentric small quadrat of 80cm radius (percentage cover
of ground level vegetation correlated closely between the quadrats and small
quadrats, r=0.74).
Environmental variables describing the landscape at each sample point included:

presence of mima mounds (completely or partially included in the quadrat)

four categories of slope: flat, gentle, moderate and steep

terrain forms: swamp, plateau, valley bottom, mesa top, low ridge, hill slope, and
mountain slope. The valley bottom category includes accumulation plains, small
valleys, depressions and drainage lines. Low ridges are short and mainly rocky
slopes, including mesa slopes, banks and cliffs.
The abundance of rodents at each sample point was assessed from signs of their
presence and activity in each 5m-radius quadrat. Burrow holes of Murinae rats and
Rhizomyinae molerats, the two main prey for wolves, are sufficiently different to be
visually discriminated. We excluded old unused rat holes (distinguished by plant
growth around the entrance). Molerat signs included open and plugged holes and also
earth mounds.
3. Vegetation classifications
Cluster analyses were used to derive classes of vegetation-soil-rock complexes from
the percentage cover data, a method conventionally used to define mapping units
(Jongman 1987). Such classification methods assume that communities can be
described by characteristic combinations of species, and the most widely used for
data such as percentage cover in community ecology is the two-way indicator species
analysis, or TWINSPAN (Tabachnick and Fidell 1989; Community Analysis Package,
Henderson and Seaby 2002). TWINSPAN defines a set of differential species that
prevail in one side of a dichotomy produced by an ordination of the samples in an
iterative process. The indicator species are the set of most highly preferential species
that reproduce as good a refined ordination as possible. A divisive method,
TWINSPAN starts with all quadrats as a group and divides it into two smaller groups,
and so on, so that large differences between groups prevail over the less important
smaller differences.
Separated classifications were run for Web Valley and Sanetti Plateau on the bases of
exploratory analyses unveiling site-specific relationships between prey types and
environmental variables. Firstly a lack of correlation between counts of signs of rats
and giant molerats showed that these two main prey types had independent spatial
distributions, both at the level of the whole sample (Spearman R= –0.066 P>0.1) and
within study area (Web Valley R= 0.016, P>0.1, Sanetti R= -0.069, P>0.1). Secondly,
pairwise comparisons showed that the relationships between single environmental
variables and rodent abundances varied with prey type and study area. Also counts of
signs of each prey type correlated more closely with the first or second axis of a
Principal Component Analysis of all sample points’ cover data, but these correlations
were strongest when sites were ordinated separately for each study area.
A division level of TWINSPAN clusters that represented the diversity of habitats for
rodents in the study areas defined four vegetation-soil-rock complexes in Web Valley
and four in Sanetti Plateau (the latter including Tullu Deemtu). The variables that
emerged as indicator species at these levels were also variables that correlated
individually with rodent abundance (Fig1), mainly: the percentage cover of soil, stone,
short grass, of the herb Alchemilla abyssinica, or the shrub Helichrysum spp. Overall,
short grasses and A. abyssinica appeared in most classes; H. splendidum was
frequent in some (e.g. class 1 and 2), but absent or rare in others; the herb Alchemilla
pedata characterized waterlogged and seasonally flooded environments (class 5);
Artemesia and Kniphofia shrubs dominated class 7. Figure 2 is a synoptic description
of each vegetation class, including associated terrain variables, which overall
coincided with the results of previous studies of rodent-vegetation relationships in
Bale. Two classes not shown in this table, but nevertheless used for the image
classification, were ‘sedge swamps’ and ‘Alchemilla haumanii heaths’, which differed
markedly from all other clusters and were represented by a few sites (n=4 and n=8
respectively). The sedge swamps with Carex spp. occupy permanently flooded
depressions with no value for wolves in terms of prey availability (Sillero-Zubiri et al.
1995a); A. haumanii heaths occupied a restricted area in the Sanetti Plateau.
Cluster
H. splendidum
Short grass
1 (n=17)
H. splendedidum 0.1523
SN
A. abyssinica
2 (n=27)
Stone
3 (n=23)
0.1944
Stone
Short grass
0.2123
A. abyssinica
4 (n=27)
A. pedata
5 (n=10)
A. abyssinica 6 (n=29)
WB
0.3725
A. abyssinica 0.2602
Stone
Short grass
0.3101
7 (n= 17)
Short grass
Artemesia
Kniphofia
8 (n=13)
Figure 1 Dendrogram of TWINSPAN clusters with eigenvalues and indicator species
associated to each division. SN= Sanetti; WB=Web Valley; n= quadrats per division.
soil
stone
short grass
Alchemilla abyssinica
H. splendidum
Thymus schimpery
Erigeron alpinus
Tall grass
H. cymosum
Euryops postratus
Dichrocephala spp
Wahlenbergia pusilla
H. citrispinum
Sagina afroalpina
Veronica spp
H. gofense
Sagina abyssinica
Geranium arabicum
Galium aparinodies
Anthemis tigreensis
Alchemilla microbetula
Haplocarpa spp
Alchemilla pedata
Carex monostachya
Cyperacea
Mosses
Salvia merjamie
Carduus chamaecephalus
Polygala spp
Senecio spp
Trifolium spp
Kniphofia isoetifolia
Artemesia afra
Erica spp
Hebenstretia dentata
Crepis carbonaria
1
V
IV
V
V
V
III
IV
V
III
II
II
II
I
I
II
II
I
I
I
Sanetti
2
3
V
V
V
V
V
V
V
IV
V
II
IV
I
III
II
III
II
III
II
I
I
I
I
I
II
III
III
II
I
II
II
IV III
I
III
I
I
I
I
I
I
I
I
I
I
I
I
I
4
V
IV
V
V
I
I
I
I
II
I
II
I
I
I
I
I
I
II
II
II
II
I
I
II
II
I
I
I
II
5
IV
III
III
III
Web
6
7
V
V
II
IV
V
V
V
IV
II
I
I
I
I
I
I
8
IV
V
V
II
IV
I
I
II
II
I
I
II
II
I
III
III
IV
I
I
I
IV
III
II
I
II
I
I
II
IV
II
II
I
II
I
I
II
I
I
I
I
I
II
II
I
I
I
I
IV
IV
IV
III
II
II
Table 1 Frequency of occurrence of plant species, bare soil or rock per vegetation
class 1 to 8. Values I to V represent within-cluster frequencies: 0-20%, 20-40%, 4060%, 60-80% and 80-100% respectively. In grey shading are shown the most
common species in each cluster; squares highlights bush life-forms.
SANETTI PLATEAU
WEB VALEY
Cluster
4
1
2
3
5
6
7
8
Soil
Stone
A. abyssinica
Short grass
H. splendidum
0
25
50
0
75
0
25
50
0
25
50
0
25
50
0
25
50
0
25
50
0
25
50
0
25
50
Vegetation layers
Ground level
Herbaceous level
Shrub level
0
25
50
25
50
75
0
25
50
75
0
25
50
75
0
25
50
75
0
25
50
75
0
25
50
75
0
25
50
Dominant cover
components
1 H. splendidum
2 Soil
3 Short grass
1 Soil
2 A.abyssinica
3 H. splend. & H
cittrispinun (14%)
1 Stone
2 Soil
3 Short grass
(H cit. 6%)
1 A. abyssinica
2 Soil
3 Short grass
1 A. pedata
2 Soil
3 Stone & tall
grasses (14%)
1 A. abyssinica
2 Soil
3. Short grass
1 Short grass
(61%)
2. Stone
1 Short grass
2 Artemesia
3 Stone
(Kniphofia 11%)
Mima mounds
Terrain
12 %
Plateau 82%
Hill slope 12%
20%
Plateau 50%
Valley bott.40%
59%
Plateau 48%
Valley bott.34%
29%
Plateau 41%
Mesa top 29%
***
*******
*
********
**
*
** * * * * * * *
*
*****
****
*
*******
**
**
HELICHRYSU
M HEATH
30%
Plateau 52%
Ridges 22%
Hill slope 13%
***
******
**
*
ROCKY
GRASSLANDS
52%
Plateau 52%
Valley bott.30%
Slope
30%
Hill slope 56 %
Plateau 22%
Ridges 19%
**
*****
**
*
OPEN HELICH.
HEATH
ALCHEMILLA
BOGS
ALCHEMILLA
SHORT
GRASSLAND
0%
Hill slope 54%
Ridges 23%
Mesa top 15%
**
*
****
***
ARTEMESIAGRASSLAND
RAT 1
RAT 3
RAT 3
RAT 2
RAT 2
RAT 2
RAT 2
RAT 1
GMR 0
GMR 1
GMR 2
GMR 2
GMR 2
GMR 2
GMR1
GMR 0
0
1
2
3
Vegetation classes
and rodents
75
Figure 2 Synopsis of habitat quality types for Ethiopian wolves from vegetation clusters 1 to 8, associated terrain variables and
abundance of rats (RAT 1 to 3) and giant molerats (GMR 0 to 2). From darker to lighter the shading of grey show three main habitat
quality types with decreasing relative prey abundances (HQ1, HQ2 and to HQ3 as described in the text).
4. Validation of habitat quality types for wolves
The number of rodent signs counted in each sample was used to assess the validity of
vegetation classes as a proxy for the abundance and distribution of the main rodent
prey. Other studies in Bale successfully validated measures of rodent abundance
derived from counts rat holes (using live trapping) and indexes based on signs of giant
molerats (using head counts) (Sillero-Zubiri et al. 1995, b). The same studies detected
a positive correlation between prey abundance and wolf numbers, confirming the link
between rodent abundance and their availability to wolves.
The number of rat holes per quadrat was compared across vegetation classes using
one-way ANOVA and post-hoc Tukey tests, after log-transforming the data to fit the
assumptions of GLM models. Rat holes were found in between 60 to 100% of
quadrats across vegetation classes and mean numbers varied from around 3 in
Artemesia-grassland to 22 in open Helichrysum heath (Fig. 3). Differences among
classes were statistically significant (log+1 ANOVA F (7,155)= 8.779, P<0.001) and
explained over 50% of the variability in the counts (R-sq= 53.3%). From multiple
comparisons between vegetation classes we derived three categories of rat
abundance (shaded in Table 2):
RAT 1= average 3 to 6 holes per quadrat
RAT 2= average 9 to 13 per quadrat
RAT 3= average 20 to 22 per quadrat
Not all classes within each group were significantly different from all other classes in
the other groups, but this division represented well the observed range of variation
(see Figure 3), perhaps with the exception of ‘bogs’, the class with larger variation in
rat sign counts.
rat ho les per q uadrat
30
25
20
15
10
5
0
Rocky G (sn)
Open HH (sn)
Alche m (wb)
Alche m (sn)
Bog
Short
G (wb)
Hel. H (sn)
Artem. (wb)
-5
20
15
10
5
0
Alche m. (sn)
Bog
Alche
m. (wb)
Rocky G. (sn)
Short G. (wb)
Open HH (sn)
Artem (wb)
Helic.Hh (sn)
-5
Figure 3 Mean and 95% confidence interval for the average number of rat (a) or giant
molerat (b) signs in quadrats of various vegetation classes. sn=Sanetti, wb=Web
Valley. Horizontal lines indicate the three classes of rodent abundance derived from
these data.
Artemesia-grassland
Helichrysum heath
Bogs
Alchemilla meadow (SN)
Alchemilla meadow (WB)
Short grassland
Rocky grassland
Open Helichrysum Heath
RAT holes (log+1)
% quadrats
Tukey test
with holes
1
2
3
0.97
61
1.11
58
1.55
1.55
70
1.88
1.88
1.88
77
2.17
2.17
100
2.36
2.36
100
2.73
100
2.93
96
Significance
0.16
0.28
0.05
Table 2 Comparisons of the mean (log+1) number of rat holes and the percentage of
quadrats with rat signs among vegetation classes. Shaded are the groupings used to
define habitat quality types.
Counts of giant molerats signs in quadrats showed a skewed distribution. No signs
were found in samples from Helichrysum heaths and Artemesia-grassland, rarely in
open Helichrysum heaths (15%. 4 out of 27 quadrats), but otherwise signs were
present in between 52 to 70% of the quadrats from other vegetation types. The
number of giant molerat signs varied considerably among vegetation classes (Kruskal
Wallis test: Chi-square=37.454, df 7, P<0.001; Fig. 3), even after excluding the
classes without signs (Kruskal Wallis test: Chi-square=37.454, df 7, P<0.000) but not if
short grasslands were excluded (Fig. 3). Abundance classes were thus defined as:
GMR 0 =absent
GMR 1 = fewer than 6 holes on average
GMR 2 =between 8 and 13 holes on average
To summarize prey availability across vegetation classes and study areas the results
were combined into three main habitat quality types (in shades of grey in Fig. 2):
HQ1 (Habitat Quality 1) = vegetation classes with high rat and giant molerat
abundances (RAT 2 or 3 and GMR 2):
• Alchemilla meadows: short herbaceous vegetation with mima mounds in plateaux
and valleys (Web and Sanetti)
• rocky grasslands: short vegetation with high percentage of bare ground and pebbles
in flat areas (Sanetti)
• bogs: waterlogged and seasonally flooded depressions with bare soil, with Alchemilla
pedata and other semi-aquatic plants, in flat areas and valley bottoms (Web)
HQ2 (Habitat Quality 2)= vegetation classes with high rat abundance and few giant
molerats (RAT 2 or 3 and GMR 1):
• open Helichrysum heaths: sparse bushes of H. splendidum and H. citrispinum, with
some tall grasses and herbs, in ridges and hills with moderate slopes and some flat
areas (Sanetti)
• short grasslands: with short Afroalpine tussocks and some herbs in thin-soiled
habitats including mesa tops (Web)
HQ3 (Habitat Quality 3)= vegetation classes with few rats and no giant molerats
(RAT 1 and GMR 0)
• Helichrysum heaths: shrub-level vegetation with H. splendidum and tall grasses, on
the rain-shadow of Tullu Deemtu peak and hill slopes (Tullu Deemtu, Sanetti)
• Artemesia-grasslands: Artemesia and Kniphofia shrubs, bushes of Erica and H.
citrispinum, in hills and rocky ridges with moderate to steep slopes (Web)
5 Habitat mapping
Remotely sensed data was used to generalize the habitat classification to the whole
study area, using a Landsat Thematic Mapper Plus (U.S. Geological Survey) from
January 2001 - no clear dry season image was not available for 1999 when field
surveys were conducted. Because topographic features are the main determinants of
vegetation type in Bale’s Afroalpine zone, it is unlikely that significant changes
occurred at the time scale of this study (1988-2000). This was apparent from the close
match between the final habitat classification and hand-made field maps from the
early years (D. Gottelli & C. Sillero-Zubiri, unpublished). The assumption of stable
rodent populations, and by extension stable vegetation patterns, was also supported
by the fact that similar numbers of wolves and packs occupied the study area in 2001
and 10 years ago (Marino et al. 2006). The resolution of 28.5m per pixel was
adequate to capture the scale of vegetation variation at which rodent preferences
occur, and the dry season is when vegetation types contrast most (particularly dry
grasslands from evergreen Alchemilla meadows). The Landsat 7 TM+ (Level 1G
product) provided geometric accuracy within 250m for low-relief areas at sea level. To
geo-reference the image with sufficient accuracy, twenty control points were collected
across the study areas using hand-held GPS devices and 1:50,000 cartographic
maps. These revealed a longitudinal drift of around 300m westwards (299 ± 49m), and
no apparent drift along the latitudinal axis (average -10± 37m). All spatial data was
corrected accordingly by adding 300m to the East-West coordinate value.
To classify the satellite image into habitat types we applied a maximum likelihood
procedure that uses Bayesian probability theory (provided by IDRISI software, Clark
Labs, Clark University, Worcester, USA). Samples from each vegetation class were
used as training sets for this supervised classification (limiting the data to those
samples located within areas of relatively homogenous pixels, due to the inherent
uncertainty in GPS readings of up to 100m, Janeau et al. 2001). Because
classification accuracy generally increases as a function of the number of spectral
bands used, all six visible near and middle infra-red bands of data were used for the
classification, some of which are particularly helpful in identifying key Afroalpine
features such as rock, soil, and moisture contest. The method of choice extracts
information from a set of training sites to calculate the mean and variance-covariance
of the spectral signatures of each habitat type, and to estimate the posterior probability
that a pixel belongs to each of the seven classes in class in Figure 2. Prior
probabilities for the relative proportion of each habitat class were derived from field
maps of the Web Valley from 1988-1992 (D. Gottelli & C. Sillero-Zubiri, unpublished)
and using expert knowledge. For further analyses pixels were combined into the three
main habitat quality types (HQ1, HQ2 and HQ3 in decreasing order of wolf rodent prey
abundance) (Figure 4).
a) Web Valley
1km
HQ1= Alchemilla meadows & bogs
HQ2= Short grasslands
HQ3= Artemesia-grasslands
Others
b) Sanetti Plateau
c) Tullu Deemtu
1km
Fig 4 Maps depicting the distribution of habitat quality types in Web Valley (a), Sanneti
Plateau (b) and Tullu Deemtu (c), and the territories of Ethiopian wolf packs studied in
1989, just before the rabies epizootics.
6. References
Gottelli D, Sillero-Zubiri C (1992) The Ethiopian wolf - an endangered endemic
canid. Oryx 26:205-214
Jongman R., ter Braak C, van Tongeren O (1987) Data analysis in community and
landscape ecology. Centre for Agricultural Publishing and Documentation,
Wageningen, Netherlands.
Lewis ML (1998) Numeric classification as an aid to spectral mapping of vegetation
communities. Plant Ecol 136:133-149
Henderson P A, Seaby RMH (2002) Community Analysis Package. Pisces
Conservation Ltd, Lygmington, UK
Miehe G, Miehe S (1993) On the physiognomic and floristic differentiation of
ericaceous vegetation in the Bale Mountains, SE Ethiopia. Opera Botanica 121:85112
Sillero-Zubiri C, Tattersall FH, Macdonald DW (1995b) Habitat selection and daily
activity of giant molerats Tachyoryctes macrocephalus: Significance to the
Ethiopian wolf Canis simensis in the Afroalpine ecosystem. Biol Cons
72:77-84
Sillero-Zubiri C, Tattersall FH, Macdonald DW (1995a). Bale mountains rodent
communities and their relevance to the Ethiopian wolf (Canis simensis). Afr J Ecol
33:301-320
Tabachnick BG, Fidell LS (1989) Using multivariate statistics. Harper and Row,
New York, NY, USA