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Conservation priorities for birds and biodiversity: Do East African Important Bird Areas represent species diversity in other terrestrial vertebrate groups?

Authors:
  • UN Environment Programme World Conservation Monitoring Centre

Abstract

Wondafrash, M. 2001. Conservation priorities for birds and biodiversity: do East African Important Bird Areas represent species diversity in other terrestrial vertebrate groups? Ostrich supplement: 000–000. An urgent question in biodiversity conservation is the extent to which priority areas for one well-known indicator group, like birds, "capture" species within other groups. The first tests of this question have indicated that capture is high. BirdLife International's "Important Bird Areas" (IBAs) work on this assumption. We test this for East African IBAs using databases on the distribution of all Afrotropical birds, mammals, snakes and amphibians, compiled at the Zoological Museum of the University of Copenhagen and mapped on a 1-degree grid in the software WORLDMAP. We assess how well the IBAs capture terrestrial vertebrate species in the region, and find that absolute capture is high. Moreover, capture of regionally endemic and threatened species is also very high. We indicate those few important species and areas not covered by IBAs. However, the IBAs do not generally capture other groups significantly better than do random selection sets of areas covering the same extent. Further, systematically selected near-minimum sets of areas can capture more species in considerably less area. Nevertheless, these near-minimum sets take into account neither ecological processes (in particular, avian migration) nor actual land-use patterns. As data become available to incorporate these factors and other taxa into quantitative priority-setting techniques, IBAs may be able to be planned with added area-efficiency. For now, though, we suggest that IBAs are not only very effective on-the-ground priorities for the conservation of birds but they also represent the majority of other terrestrial vertebrate diversity.
PLE/03
Conservation priorities for birds and biodiversity: do East
African Important Bird Areas represent species diversity
in other terrestrial vertebrate groups?
Thomas Brooks1,2,3, Andrew Balmford3, Neil Burgess4, Louis A. Hansen2, Joslin Moore2,3,
Carsten Rahbek2, Paul Williams5, Leon Bennun6, Achilles Byaruhanga7, Panta Kasoma8, Peter
Njoroge6, Derek Pomeroy8 & Mengistu Wondafrash9
1Center for Applied Biodiversity Science, Conservation International, 2501 M St. Suite 200, Washington DC 20037, U.S.A.
E-mail: t.brooks@conservation.org.
2Vertebrate Department, Zoological Museum of the University of Copenhagen, Universitetsparken 15, DK-2100 Copenhagen , Denmark
3Conservation Biology Group, Department of Zoology, University of Cambridge, Downing Street, Cambridge CB2 3EJ, U.K.
4Wildlife Conservation Society of Tanzania, P.O. Box 70919, Dar es Salaam, Tanzania
5Biogeography and Conservation Laboratory, Department of Entomology, The Natural History Museum, Cromwell Road, London SW7 5BD, U.K.
6Ornithology Department, National Museums of Kenya, P.O. Box 40658, Nairobi, Kenya
7NatureUganda, The East Africa Natural History Society, P.O. Box 27034, Kampala, Uganda
8Makerere University Institute of Environment and Natural Resources, P.O. Box 7298, Kampala, Uganda
9Ethiopian Wildlife & Natural History Society, P.O. Box 13303, Addis Ababa, Ethiopia
Brooks, T., Balmford, A., Burgess, N., Hansen L.A., Moore, J., Rahbek, C., Williams, P., Bennun, L., Byaruhanga, A., Kasoma, P.,
Njoroge, P., Pomeroy, D. & Wondafrash, M. 2001. Conservation priorities for birds and biodiversity: do East African Important
Bird Areas represent species diversity in other terrestrial vertebrate groups? Ostrich supplement: 000–000.
An urgent question in biodiversity conservation is the
extent to which priority areas for one well-known
indicator group, like birds, “capture” species within
other groups. The first tests of this question have
indicated that capture is high. BirdLife International’s
“Important Bird Areas” (IBAs) work on this assumption.
We test this for East African IBAs using databases on
the distribution of all Afrotropical birds, mammals,
snakes and amphibians, compiled at the Zoological
Museum of the University of Copenhagen and mapped
on a 1-degree grid in the software WORLDMAP. We
assess how well the IBAs capture terrestrial vertebrate
species in the region, and find that absolute capture is
high. Moreover, capture of regionally endemic and
threatened species is also very high. We indicate those
few important species and areas not covered by IBAs.
However, the IBAs do not generally capture other
groups significantly better than do random selection
sets of areas covering the same extent. Further,
systematically selected near-minimum sets of areas can
capture more species in considerably less area.
Nevertheless, these near-minimum sets take into
account neither ecological processes (in particular, avian
migration) nor actual land-use patterns. As data become
available to incorporate these factors and other taxa
into quantitative priority-setting techniques, IBAs may
be able to be planned with added area-efficiency. For
now, though, we suggest that IBAs are not only very
effective on-the-ground priorities for the conservation
of birds but they also represent the majority of other
terrestrial vertebrate diversity.
INTRODUCTION
Priority-setting for conservation
Current species extinction rates are at least 1000 times as great
as those typical of the earth’s history (Pimm et al. 1995). This
is largely because threats to biodiversity are disproportionately
concentrated in centers of endemism where many species with
small ranges co-occur (Myers 1988). Thus, traditional
conservation targeting areas of scenic or cultural significance
cannot be expected to conserve biodiversity effectively
(Pressey 1994). Further, it will not be efficient or effective to
conserve one species at a time (Pitelka 1981). Only for two
classes - birds (Collar et al. 1994) and mammals (Baillie &
Groombridge 1996) - do we have a good idea of the
conservation status of each species. Conservation must set
priorities that enable multiple species to be conserved
simultaneously (Ehrlich 1992).
The most obvious way of doing this is to conserve concentrations
of species richness (Prendergast et al. 1993). However, this
approach may select ecotones with high alpha diversity at the
expense of rare species (Pressey & Nicholls 1989). Thus,
concentrations of restricted-range (Terborgh & Winter 1983)
or threatened (Collar 1994) species, or both (Myers et al. 2000)
may be better conservation targets. An alternative approach relies
not just on the numbers of species in an area, but on the identity
of these species relative to those in other areas. This is
complementarity, which aims to select sets of conservation areas
holding the most species overall, rather than individually
(Pressey et al. 1993). This approach has considerable theoretical
merit but is data-hungry and so has been little used in practice
except in the temperate zone (Pimm & Lawton 1998).
A further shortfall of each of these approaches is that in
applications to date they only represent pattern - species
disitributions - and do not target processes promoting persistence
(Nicholls 1998). An excellent example of such a process is
migration - migratory species must be conserved in different
places at different times of year (Gómez de Silva Garza 1996).
Others range from tiny (e.g. pollination) through medium (e.g.
predator-prey dynamics) to huge (e.g. resilience to climate change)
scales (Cowling et al. 1999). Techniques are only just beginning
to be developed to incorporate such processes into conservation
priority-setting (Williams 2000). Finally, it is essential that
priority-setting exercises incorporate not just irreplaceable features
(in both pattern and process) but also are sensitive to how
vulnerable a particular area is (Margules & Pressey 2000).
Indicator taxa for conservation priorities
A potentially major constraint for any prioritization of areas
for the conservation of biodiversity is that most biodiversity
remains unknown (May 2000). Systematic priority-setting must
therefore rely on samples of well-known taxa on the assumption
that such taxa represent biodiversity generally (Gaston 1996).
Some studies have suggested that this assumption may be valid
(Pearson & Cassola 1992) but at local scales there appears to
be very little direct correlation in patterns of richness between
major taxa (Lawton et al. 1998). This may well be due to scale-
dependence (Pomeroy 2000), maybe because species within a
single major taxon are unlikely to share similar fine-grained
habitat with species in other major taxa (Reid 1998). To
circumvent this problem, Faith & Walker (1996) suggested that
congruence between complementary sets of priority areas for
indicator taxa might be a better measure. However, van Jaarsveld
et al. (1998) found that complementary sets for eight taxa in
the Transvaal, South Africa shared few selected areas.
Nevertheless, even if diversity patterns and conservation priorities
do not directly correspond between taxa, indicator taxa may still
be useful in practice if priority areas for the conservation of one
taxon also represent (“capture”) many species in others (Balmford
1998). A test of this idea showed that, despite poor cross-taxon
congruence in species richness or conservation priority areas, key
areas for five taxa in Ugandan forests performed remarkably well
at capturing species from the other groups (Howard et al. 1998).
Burgess et al. (2000) supported this conclusion for forest birds
and mammals on a 1-degree grid across Africa, finding that
complementary sets of areas to represent birds captured 77% of
mammals and that complementary sets of areas for mammals
captured 94% of birds.
The Important Bird Areas programme
Birds are the single major taxon most commonly used to set
conservation priorities, because they are widespread, diverse,
easily-surveyed, taxonomically well-known, and have a broad
popular appeal (ICBP 1992). BirdLife International, in
particular, has pioneered the use of birds in conservation
planning, through four programmes (in the tropics). The first is
the Red Listing programme, for which global Red Data Books
are being compiled (e.g., Collar & Stuart 1985) and for which
many regional and national Red Lists are also now available
(e.g. Bennun & Njoroge 1996). The second is the Endemic Bird
Areas (EBAs) programme, for defining all areas to which two
or more bird species with globally restricted ranges of <50 000
sq. km are completely restricted (Stattersfield et al. 1998). Third,
particular attention is paid to the conservation of migratory
species (Salathé 1991), especially, in response to the Ramsar
convention, waterbirds (Rose & Scott 1994).
Fourth, the Important Bird Areas (IBAs) programme has been
developed to combine the priorities set by the other programmes
in specific sites for conservation action on the ground. IBAs have
already been defined for Europe (Heath et al. 2000) and the Middle
East (Evans 1994), and the IBA programme is now well-underway
in Africa (Bennun & Fishpool 2000). Specifically, IBA inventories
have been completed for southern Africa (Barnes 1998) and now
for East Africa (EWNHS 1996; Bennun & Njoroge 1999; Baker
& Baker in press; Byaruhanga et al. in press).
IBAs are defined as sites of significance for birds in any one of
four categories (Bennun & Fishpool 2000): globally threatened
species (Collar et al. 1994); restricted range species (Stattersfield
et al. 1998); “biome-restricted assemblages” - being a category
defined ad hoc to represent species (regardless of range size) but
endemic to a particular biome; and particular congregations of
individual birds. This fourth category is subdivided into four
criteria: >1% of the biogeographic population of a waterbird;
>1% of the global population of other species; >20 000 individuals
of waterbirds or seabirds; or other thresholds (defined species by
species) for migratory species at bottleneck sites.
In total, 228 IBAs have been identified in East Africa (Table
1). In addition to these, Ethiopia has eight potential IBAs
(EWNHS 1996) and Kenya five (Bennun & Njoroge 1999).
Note that since the publication of EWNHS (1996), the number
of IBAs in Ethiopia has increased to 73 (with areas delimited
for 38 of these); these data have yet to be published and so we
do not include them here. The size of the Ethiopian IBAs
relative to those in the other three countries is primarily driven
by seven IBAs each larger than a million hectares; the Awash
River Valley [ET12] at 11 370 000 ha and the Baro River
[ET17] at 38 400 000 ha are particularly huge (EWNHS 1996).
Only five other East African IBAs are larger than a million
hectares. The area of 47 IBAs, particularly large IBAs and
particularly in Ethiopia, has yet to be delimited.
TABLE 1. Numbers and areas of East African IBAs, and their coverage as a percentage of national areas. Data are from EWNHS (1996),
Bennun & Njoroge (1999), Byaruhanga et al. (in press) and Baker & Baker (in press) respectively.
Known Known Known Known
Number of IBAs (with data) total area (ha) Mean area (ha) Median area (ha) %
Ethiopia 62 (36) 70 868 538 1 968 571 106 284 63
Kenya 60 (59) 5 503 250 93 275 18 000 10
Uganda 30 (24) 1 164 008 48 500 27 800 6
Tanzania 76 (62) 15 767 688 254 318 46 850 17
Total 228 (181) 93 303 484 515 489 32 000 32
The aim of this study is to assess how well these 228 East African
IBAs perform as “Important Biodiversity Areas”, for terrestrial
vertebrate biodiversity, at least. Specifically, we ask how well
IBAs represent mammal, snake and amphibian species. We aim
to identify species not represented in IBAs and suggest sites for
their conservation, and then draw general conclusions as to the
potential of IBAs for conserving biodiversity overall.
METHODS
The ZMUC databases
Over the last five years, data have been compiled at the
Zoological Museum of the University of Copenhagen (ZMUC)
on the distribution of all currently-recognized species of birds
(terrestrial and freshwater), mammals, snakes and amphibians
found in mainland sub-Saharan Africa south of 20°N (Burgess
et al. 1998). Data are derived from secondary sources wherever
possible, although for many small mammals, snakes and
amphibians it was necessary to compile primary point locality
data. Where this was the case we consulted with taxonomic
specialists to extrapolate ranges across suitable habitat; only
the least known species were plotted without extrapolation.
These data have been mapped onto a 1-degree grid (1957 cells
each approximately 105 km on the side) and entered into the
program WORLDMAP (Williams 1996). This is a dynamic
database into which new grid-cell data-entries are added almost
daily. Nevertheless, it already comprises the most complete
cross-taxonomic species distributional database for any tropical
continent. Hereafter we refer to these species collectively as
“terrestrial vertebrates” for convenience, always remembering
that it has not been possible to include all reptiles in the
databases. In Figure 1a-c we illustrate the East African portion
of the databases. We give full details of data sources for
taxonomy and distribution in Brooks et al. (in press).
Allocating IBAs to grid cells
In order to analyze the representation of mammal, snake and
amphibian species in IBAs, it was first necessary to take the
central coordinates for each IBA and allocate each to their
respective grid cell. For Ethiopia (EWNHS 1996), numerous
IBAs were located by ranges of coordinates; we took the mid-
point, guided by the national map (EWNHS 1996: 13) for these
to locate them on our grid. We corrected a few coordinates which
were askew in the accounts.
Two potential problems exist in this method of allocating IBAs to
grid cells. One is that some species present in a particular grid cell
may be absent from the part of that grid cell covered by an IBA
(errors of commission). Conversely, some IBAs are larger than a
single grid cell and so species from multiple cells may actually be
present in the IBA (errors of omission). Here, we assume that on
average these problems should cancel out. Although we only have
data on the area of 181/228 IBAs (Table 1), the mean IBA area per
cell (i.e. amalgamating multiple IBAs where they lie in the same
cell; we have data for 102/122 IBA grid cells) is 914 142 ha, i.e.
~10 000 sq. km. This is equivalent to approximately one 1-degree
grid cell, although note that the median is considerably smaller, at
109 284 ha, only a tenth of a 1-degree grid cell. Species not covered
in one IBA but counted in our database as represented should
therefore be balanced by species covered by other IBAs in reality
but not in our database. However, this may not be true to the extent
that errors of omission are caused mainly by a few very large
Ethiopian IBAs whereas errors of commission are caused by many,
more widely scattered IBA.
We carried out all analyses in the four-nation East African block
of Ethiopia, Kenya, Uganda and Tanzania. This region covers a
total of 277 1-degree grid cells, an area of just under 3 million
hectares, or about 15% of Sub-Saharan Africa. It holds 1516
bird, 574 mammal and 490 snake and amphibian species.
Clearly, restricting our analyses to this politically-defined region
leads to the bisection of some biogeographically important areas,
such as the Albertine Rift. Further, because it is bounded by the
edges of 1-degree grid cells, it includes small portions of each
of the neighbouring countries. We therefore excluded from the
database the 60 bird (Dowsett & Forbes-Watson 1993), 29
mammal (Wilson & Reeder 1993), 20 snake (Uetz & Etzold
1996) and 39 amphibian (Frost 1985) species occurring only in
these neighbouring countries within the 277 cell region.
RESULTS
Absolute and percentage representation in IBAs of all species,
endemic species and threatened species of terrestrial vertebrates
in the region.
We first assessed the numbers and proportions of East African
terrestrial vertebrate species represented in the IBA network
(Table 2a). We did this for birds, mammals, snakes and
amphibians together, and all species combined. Representation
of species in IBAs is high, over 90% in all cases. The results for
birds (and, to some degree, those for all species - because these
of course include birds) are essentially trivial. Given that the
IBAs are defined by the distributions of birds, and much of the
data used in compiling the ZMUC bird databases was also used
in defining the IBAs, we expect East African IBAs to adequately
represent the region’s birds. These results were included merely
to give an indication of the proportions of peripheral species
that - even for birds - the IBAs are not seeking to represent.
Such species are better conserved elsewhere.
TABLE 2. a) Absolute and percentage representation in 122 IBA grid cells of all species, endemic species and threatened species of
terrestrial vertebrates in the region. b) Mean absolute and percentage (±2.5% tail) representation in 1000 random sets of 122 cells of all
species, endemic species and threatened species of terrestrial vertebrates in the region. c) Number of cells required to represent all
species, all endemic species and all threatened species of terrestrial vertebrates in the region by a simple greedy complementary area-
selection algorithm. d) Number of cells required to represent all species, all endemic species and all threatened species twice.
All species Endemic species Threatened species
a) Representation in 122 IBA grid cells
Birds 1414/1456 (97%) 98/98 (100%) 53/55 (96%)
Mammals 525/545 (96%) 94/97 (97%) 72/80 (90%)
Snakes and amphibians 394/431 (91%) 121/131 (92%) -
Total 2333/2432 (96%) 313/326 (96%) 125/135 (93%)
We repeated this analysis restricting ourselves to species
endemic to the region of 277 1-degree grid cells covering East
Africa (Table 2a). This should be of rather more significance
than the analyses for all species: East African endemics can be
conserved nowhere else. Representation is again over 90% in
each case. Finally, we repeated the analysis considering only
species included in the Red List (Baillie & Groombridge 1996)
as globally threatened (Table 2a). No East African snakes or
amphibians are considered globally threatened (probably a
reflection of lack of assessment and knowledge rather than of
actual conservation status). Once again, representation of
threataned species in IBAs is very high. (Incidentally, using the
newly-published 2000 Red List http://www.redlist.org makes
no difference to the representation of threatened taxa in IBAs.)
Which species are not represented in IBAs?
In Figure 1d-f we illustrate the distributions of all East African
terrestrial vertebrates not represented in IBAs, and those of East
African endemic and threatened species. The two threatened
birds unrepresented in IBAs but apparently appearing in the
region in our databases are in fact of only marginal occurrence.
White-eyed Gull Larus leucophthalmus breeds along the Red
Sea coast of Eritrea, but is only known to the south as a vagrant,
and while Sociable Plover Vanellus gregarius winters in Eritrea,
there are no confirmed records to the south (Urban et al. 1986).
No East African endemic birds are unrepresented in the IBAs.
For threatened mammals, similarly, Mormopterus acetabulosus
of Madagascar and the Mascarenes is only known from two
mainland African reords, one from South Africa and one from
Ethiopia (Baillie & Groombridge 1996). The once-widespread
Gazella rufifrons occurred historically along the extreme
northern border of Ethiopia, but there is no recent information
on its survival here, and Dorcatragus megalotis has only been
recorded twice in the region (in 1899 and 1972), on the Djibouti
border (East 1998).
Thus the only characteristically East African threatened species
not represented in IBAs are: Taphozous hamiltoni from extreme
north-west Kenya and southern Sudan (Aggundey & Schlitter
1984); Gerbillus cosensi from Ngamatak on the Turkwel River
in north-west Kenya (Lay 1983); Myotis morrisi, known from
single specimens from Nigeria and Ethiopia (Largen et al. 1974);
Gerbillus bilensis from Bilen in Ethiopia (Lay 1983); and
Ammodillus imbellis, from Ethiopia and Somalia (Yalden et al.
1976). In addition, Phacocheros aethiopicus, listed by Baillie
& Groombridge (1996) as threatened for the subspecies delameri
(the nominate Cape subspecies is extinct), should be added to
this list. The two Gerbillus are of particular concern, being
endemic to the region, and a further unrepresented species, G.
dunni, occurs only in Ethiopia and immediately adjecent
Somalia (Lay 1983).
No threatened snakes or amphibians occur in East Africa (Baillie
& Groombridge 1996). Of the 10 species apparently endemic
to the region but unrepresented in the IBAs, three are known
only from border regions: Hyperolius discodactylus from the
DRC as well as Uganda (Laurent 1972a); Bufo urunguensis
from Zambia as well as Tanzania (Poynton & Broadley 1988);
and Telescopus pulcher from Somalia as well as Ethiopia
(Scortecci 1935). This leaves seven exclusively East African
endemics unrepresented in IBAs: Hemisus brachydactylus from
southern Tanzania (Laurent 1972b); Chilorhinophis carpenteri
from south-east Tanzania (Loveridge 1951); Bitis parviocula
from several localities in central Ethiopia (Böhme 1977);
Ptychadena nana from Arussi, Ethiopia (Perret 1980);
Phrynobatrachus minutus from Duro, Ethiopia (Duellman
1993); Coluber somalicus from eastern Ethiopia (Largen &
Rasmussen 1993); and Leptotyphlops parkeri from Degeh Bur,
Ethiopia (Broadley 1999).
Comparison with random area selection
One method by which to evaluate the peformance of IBAs in
representing terrestrial vertebrate species is to test how many
species would be represented in an equivalent area to that covered
by the IBAs but selected at random. We use the number of grid
cells holding IBAs (122) as the area to represent species at random.
Although this represents an area of ~1 220 000 sq. km, rather
larger than the total documented area of IBAs at ~930 000 sq.
km (Table 1), this latter figure does not include the areas of 47
(mainly large) IBAs, which we assume make up the difference.
We therefore selected 122 cells from the East African total of
277 at random 1000 times (only cells holding species were
included in the randomization), and considered the mean (±2.5%
tail) representation of East African species, endemic species and
threatened species in these random sets (Table 2b). The random
sets represent between 81% and 98% of East Africa’s species,
endemic species and threatened species, generally capturing as
many or only marginally fewer species than do IBAs.
Comparison with greedy complementary sets
Another method against which to evaluate the performance of
IBAs is to compare them against sets of areas selected in a
complementary fashion with the explicit goal of representing
all species (Pressey et al. 1993). The simplest complementary
area-selection technique is to select the first grid cell as that
holding the largest number of species. All species represented
within this first cell are then discounted, and the second cell is
All species Endemic species Threatened species
b) Representation in random sets of 122 cells
Birds 1418/1456 (97±2%) 93/98 (95±5%) 46/55 (83±12%)
Mammals 497/545 (91±3%) 95/97 (98±2%) 65/80 (81±9%)
Snakes and amphibians 377/431 (87±4%) 117/131 (89±7%) -
Total 2290/2432 (94±3%) 278/326 (84±7%) 111/135 (81±8%)
TABLE 2. b) Absolute and percentage representation in 122 IBA grid cells of all species, endemic species and threatened species of
terrestrial vertebrates in the region. b) Mean absolute and percentage (±2.5% tail) representation in 1000 random sets of 122 cells of all
species, endemic species and threatened species of terrestrial vertebrates in the region. c) Number of cells required to represent all
species, all endemic species and all threatened species of terrestrial vertebrates in the region by a simple greedy complementary area-
selection algorithm. d) Number of cells required to represent all species, all endemic species and all threatened species twice.
FIG. 1. a) Species richness of all terrestrial vertebrate species across East Africa. b) Species richness of all endemic terrestrial vertebrates
across East Africa. c) Species richness of all threatened terrestrial vertebrates (which in practice are just birds and mammals) across
East Africa. d) Distribution of all East African terrestrial vertebrate species unrepresented in IBAs. e) Distribution of endemic East
African terrestrial vertebrate species unrepresented in IBAs. f) Distribution of threatened East African terrestrial vertebrate species
(excluding the subspecies of Warthog Phacocheros aethiopicus delameri) unrepresented in IBAs. g) The greedy near-minimum
complementary set of 1-degree grid cells representing all East African terrestrial vertebrates. 2423 species are represented in 97 cells.
h) The greedy near-minimum complementary set of 1-degree grid cells representing all East African endemic terrestrial vertebrates.
326 species are represented in 57 cells. i) East African IBAs (grey circles) and the important areas for conserving East Africa’s threatened,
endemic or near-endemic terrestrial vertebrates which fall through the IBA network (stars). Only 14 additional areas would be necessary
to represent these 17 species. Three areas (grey stars) hold two unrepresented species each, while the remaining 11 (white stars) hold
single unrepresented species. Throughout, the large grid represents 10-degrees latitude and longitude, the scale bar 500 km, and the
arrow north.
chosen as that holding the largest number of species
unrepresented in the first cell. Next, all species represented
within this cell are discounted to indicate where our third cell
lies, and so on until we have represented every species desired
in a near-minimum set of areas. This procedure is termed simple
greedy complementarity, because it selects the area holding the
largest number of unrepresented species at every step. Numerous
other complementary methods exist, all of which achieve similar
efficiency to simple greedy complementarity (Csuti et al. 1997).
We therefore use simple greedy complementarity to select near-
minimum sets of areas for representing all species, all endemics
and all threatened species of East African vertebrates. We give
the sizes of these greedy sets in Table 2c. Probably the most
informative of these sets are those for all four major taxa
combined, because in these we maximize use of all the data
available. In Figure 1g we therefore illustrate greedy near-
minimum sets for all East African terrestrial vertebrates, and in
Figure 1h those for all East African endemic terrestrial
vertebrates - these latter are the species that can only be
conserved within the region. In Table 2d we repeat the greedy
near-minimum set selection, this time representing all species
in the dataset in at least two areas.
DISCUSSION
Which additional conservation areas should be
considered?
Given the marginal occurrence of those birds - especially
threatened birds - occurring in East Africa (according to the
ZMUC databases) but unrepresented in IBAs, we can state that
the region’s birds are fully represented by the East African IBA
network. Maybe one of the most useful results of this exercise,
however, is to suggest important areas for conserving those of
East Africa’s threatened, endemic and near-endemic terrestrial
vertebrates which fall through the IBA network. That most of
these species are desert specialists and that desert is poorly-
represented within IBAs suggests that this lack of representation
is real and not simply due to our limited knowledge of the
species’ distributions. In total, 14 additional areas would be
necessary to represent these 17 species (Figure 1i), and in fact
three of these probably already fall within two IBAs leaving
just 11 additional areas necessary.
Three would represent two species each: the Warder Desert of
south-east Ethiopia (6°N45°E) for Ammodillus imbellis and
Gerbillus dunni; the Aware Desert of eastern Ethiopia (8°N44°E)
for Phacocheris aethiopicus and Telescopus pulcher; and the
Didda Plateau of central Ethiopia (7°N39°E) for Bitis parviocula
and Ptychadena nana. Five of the remaining eleven areas
representing one additional species each would be in Ethiopia:
the Didessa River mouth (10°N35°E) for Myotis morrisi; the
Bilen steppe (9°N41°E) for Gerbillus bilensis; the Degeh Bur
desert (8°N43°E) for Leptotyphlops parkeri; the Duro mountains
(7°N41°E) for Phrynobatrachus minutus; and the Imi steppe
(6°N41°E) for Coluber somalicus. Two would need to be in
Kenya: the Kaitherin Hills (4°N35°E) for Taphozous hamiltoni
and the Kozibiri River (2°N35°E) for Gerbillus cosensi. One,
for Hyperolius discodactylus, would be in the far west of Uganda
(0°S29°E), and is probably actually represented in Bwindi-
Impenetrable National Park [UG04]. Finally, three would need
to be in Tanzania: the Urungu mountains (8°S31°E) for Bufo
urunguensis; and the miombo woodland in the western portion
of the Selous for Hemisus brachydactylus (8°S37°E) and
Chilorhinophis carpenteri (9°S37°E) which are presumably
already represented in the Selous Game Reserve [TZ18].
Which IBAs are the highest priority for representing
all taxa?
A useful way to assess which of the IBAs are of the highest
priority for representing not just birds but also mammals, snakes
and amphibians is to compare the greedy complementary set of
areas for representing all endemic species (Figure 1h) with the
IBAs. The greedy complementary set for all species, as opposed
to that for just endemics, is less useful because it picks so many
peripheral sites, where species are occurring at the very edge of
their ranges, although note that techniques are now being
developed to avoid this problem (Araújo & Williams 2000). Of
the 57 1-degree grid cells within the near-minimum greedy
complementary set to represent all endemics, 43 also hold IBAs
(101 IBAs in total): 13 in Tanzania (29 IBAs); 12 in Kenya (39
IBAs); 12 (16 IBAs) in Ethiopia; and 6 (17 IBAs) in Uganda.
The near-minimum set includes all but three of the 19 Kenyan
IBAs scored as “critical” by Bennun & Njoroge (1999). The
missing three IBAs are all in the far west of Kenya and are all
extremely important in the national context: South Nandi Forest
[KE55] (Waiyaki 1998), the Busia Grasslands [KE57] (Nasirwa
& Njoroge 1997) and Kakamega Forest [KE58] (Bennun &
Waiyaki 1992). However, their only species not widely-
represented in the rest of East Africa is the threatened Turner’s
Eremomela Eremomela turneri, present in KE55 and KE58
(Collar & Stuart 1985). This is otherwise known in East Africa
only from historical records from Nyondo forest in Uganda
(Chapin 1953) and South Nandi appears to be its global
stronghold (Kosgey 1998).
The top ten cells of the near-minimum set (which between
them represent nearly three-quarters of the region’s endemics)
All species Endemic species Threatened species
c) Number of cells required to represent all taxa
Birds 51 23 17
Mammals 58 29 29
Snakes and amphibians 58 38 -
Total 97 57 38
TABLE 2. c) Absolute and percentage representation in 122 IBA grid cells of all species, endemic species and threatened species of
terrestrial vertebrates in the region. b) Mean absolute and percentage (±2.5% tail) representation in 1000 random sets of 122 cells of all
species, endemic species and threatened species of terrestrial vertebrates in the region. c) Number of cells required to represent all
species, all endemic species and all threatened species of terrestrial vertebrates in the region by a simple greedy complementary area-
selection algorithm. d) Number of cells required to represent all species, all endemic species and all threatened species twice.
are the West Usambara-Mkomazi complex [TZ16 and 71],
Ethiopia’s Didda Plateau, the central Kenyan Rift Valley [KE1,
3, 4, 46, 48, 49 and 52], the Uluguru-Mikumi complex [TZ6,
68 and 72], the Udzungwa National Park [TZ66], Samburu
National Park [KE33, 34 and 54], the Addis Ababa region
[ET32 and 36], Rwenzori Mountains National Park [UG5, 6,
7 and 9], Arabuko-Sokoke forest [KE7 and 8] and Nechisar
National Park [ET55].
An additional interesting question is to ask how IBAs defined
by each of the four categories (Bennun & Fishpool 2000) are
distributed in the greedy near-minimum set of cells that represent
all East African endemic terrestrial vertebrates (Table 3). We
assessed whether the occurrence in the near-minimum set of
each of the four categories was significantly different from that
expected at random (i.e., the overall proportion of IBAs in the
set, 101/228). Significantly more IBAs wholly or partly defined
by restricted range species were represented in the near-
minimum set than expected. There was no significant difference
between the proportion of IBAs defined by threatened or biome-
restricted species, or by congregations, occurring and not
occurring in the near-minimum set. This result is unsurprising:
restricted range bird species by definition occur in very few
grid cells (no more than a maximum five 1-degree grid cells),
and each have to be represented at least once in the greedy near-
minimum set.
Possible future refinements
A key difficulty with conducting this exercise is the resolution
at which data are available. This makes it impossible to tell
conclusively from the ZMUC databases whether or not a species
is actually represented within an IBA. This could have dangerous
consequences: species which are considered to be fully
represented within the IBA network could actually only occur
outside of (albeit close by) the areas, and suffer conservation
neglect in consequence. It seems unlikely that this is a major
problem, because most of East Africa’s habitat is heavily
modified (Hannah et al. 1995) while most IBAs and presumably
most surviving populations lie together in what remains
unmodified. Nevertheless, it is clear that there is an urgent need
to collect and compile finer resolution biological distributional
data (da Fonseca et al. 2000). One short-cut towards this could
be building deductive environmental models of species
distributions based on satellite imagery - such data are already
available for large African mammals (Boitani et al. 1999).
Ultimately, though, the most effective data for incorporation
into priority-setting will be that collected at “point” localities
representing actual land management units, especially existing
protected areas (e.g., Howard et al. 2000); such work is now
underway for non-forest IBAs in Uganda, for example.
A second important field of research should involve collecting
data on other groups to test the degree to which conservation
priorities set for one group, like birds, are effective more
generally. Such work is already underway for plants (Lovett et
al. 2000). Clearly, freshwater and marine taxa, and ecological
processes, which until now have not been adequately represented
by pattern-based terrestrial priority-setting, must be the focus
of specific efforts (Balmford et al. 1998). It is likely that IBAs
actually represent these relatively well for birds, due to the
inclusion of a category for congregations of migratory species
(often waterbirds or seabirds). However, as data become
available to represent such processes into quantitative priority-
setting techniques, it may be possible to increase the area-
efficiency with which they are represented in IBAs.
In addition, research should continue into other possible short-
cut techniques for conservation priority-setting. One technique,
that of conserving flagship species with the aim of representing
all species (Ryti 1992) has now been shown to be rather
ineffective (Williams et al. 2000). Another alternative is research
into environmental surrogates for conservation planning (Faith
et al. 1996). This strategy may be more effective for representing
ecological process than are pattern-based approaches (Olson &
Dinerstein 1998). The danger with such planning is that without
explicit attention to species, even highly-valued vertebrate
species may be lost if they happen to be unrepresented within
the ecoregional net (Noss 1987).
All species Endemic species Threatened species
d) Number of cells required to represent all taxa twice
Birds 88 43 33
Mammals 92 45 51
Snakes and amphibians 95 54 -
Total 151 86 66
TABLE 3. Occurrence of IBAs defined by each of four categories in the greedy near-minimum set of areas to represent all East African
terrestrial vertebrates. * significant P < 0.05.
Threatened Restricted range Biome-restricted Congregations
Occurs 76 57 65 28
Does not occur 88 37 79 45
Expected to occur 73 42 64 32
Chi-squared (1 d.f). 0.28 10.17* 0.04 1.70
TABLE 2. d Absolute and percentage representation in 122 IBA grid cells of all species, endemic species and threatened species of
terrestrial vertebrates in the region. b) Mean absolute and percentage (±2.5% tail) representation in 1000 random sets of 122 cells of all
species, endemic species and threatened species of terrestrial vertebrates in the region. c) Number of cells required to represent all
species, all endemic species and all threatened species of terrestrial vertebrates in the region by a simple greedy complementary area-
selection algorithm. d) Number of cells required to represent all species, all endemic species and all threatened species twice.
Overall performance of IBAs
East Africa’s IBAs appear to represent other terrestrial vertebrate
species effectively. Overall, representation of vertebrates is over
90%, and that for mammals and birds even higher. The capture
of endemic species is even higher, which is particularly
important given that these can be conserved nowhere else in
the world. Further, threatened vertebrates, the most immediate
targets for conservation action, are also well represented, with
only five regularly occurring threatened East African species
(all mammals) unrepresented in IBAs.
When compared with quantitative techniques, however, the
degree to which IBAs capture other groups of species is less
surprising. The performance of IBAs is significantly better than
random only for each group of threatened species, and for all
endemic vertebrates (although it is never significantly worse
than random). In addition, simple greedy complementary
techniques could represent all East African species in
considerably less area than is covered by the IBAs at present,
although the degree to which this is true must vary by country
because three-quarters of all of the IBA area of East Africa lies
in Ethiopia alone. Simple greedy complementarity can even
represent all taxa twice in only 25% again more area than
covered by the IBAs. One possible explanation is that the “extra”
area required by IBAs is due to their representation of
concentrations of individual birds. Table 3 provides some evidence
for this. In addition, much of the “efficiency” of the near-minimum
sets is achieved by the selection of peripheral areas where species
from different regions meet (Figure 1g-h). Such areas may well
be ecologically unviable or politically undesirable to conserve.
Third, the IBAs do not aim to represent species in a minimum
number of areas, and actually aim to represent some (e.g.,
threatened) species in as many sites as possible.
The IBA strategy has other key advantages which cannot be
evaluated by species representation alone. An obvious one is
the explicit incorporation of ecological process (avian migration)
into the priority-setting (Williams & Araújo 2000). While
vulnerability is not an explicit factor in determining IBAs,
degree of threat is increasingly being used to rank IBAs in
priority order for action (e.g. Bennun & Njoroge 1999). Of
course, the incorporation of threats and processes for birds does
not necessarily mean that these are incorporated for other groups.
For example, the representation of Elephants Loxodonta
africana in IBAs will not lead to their conservation unless the
IBAs are managed not just for birds but also for allowing
seasonal movements and preventing poaching of the species.
Another advantage over species representation is that the IBA
process focuses on actual land management units, increasing
the feasibility of conservation action based on the strategy
(Lombard et al. 1997). Thus, IBAs concentrate on “conservation
-efficiency” more than area-efficiency. Least tangible, the IBA
priority-setting process is a consensual one, involving
considerable fieldwork and public outreach by local
organizations; this is particularly important because action is
only likely to be taken on the ground if people in the area are
sufficiently motivated (Mittermeier et al. 1995).
To conclude, while IBAs do not represent biodiversity pattern
with the maximum efficiency possible, they have considerable
(although unquantified) other advantages which explain this.
Further, it is clear that all species from other taxa will not be
represented in priority sets unless information about those taxa
is incorporated into the priority-setting process. Nevertheless,
IBAs do not only represent bird species extremely well, but
also capture enough mammals, snakes and amphibians for us
to have confident that they are in practice effective sites for the
representation of nearly all terrestrial vertebrate biodiversity.
ACKNOWLEDGEMENTS
Many thanks to the dozens of individuals and institutions who
provided and compiled the ZMUC data (Brooks et al. in press),
to E. Baker and N. Baker for providing the IBA data for
Tanzania, to C. Bibby, P. Buckley, L. Fishpool, J. Fjeldså, S.
Goodman, L. Lens, D. Mutekanga, D. Pain, L. Sørensen, H.
Tushabe and C. Williams for help and to the Danish Council
for Development Research, the Isaac Newton Trust of the
University of Cambridge, and Conservation International’s
Center for Applied Biodiversity Science for funding.
REFERENCES
Araújo, M.B. & Williams, P.H. 2000. Selecting areas for species
persistence from occurrence data. Biological Conservation 96:
331–345.
Baillie, J. & Groombridge, B. 1996. 1996 IUCN Red List of
Threatened Animals. The IUCN Species Survival Commission,
Gland, Switzerland.
Baker, N. & Baker, E. (in press) Important Bird Areas in Tanzania.
Wildlife Conservation Society of Tanzania, Dar es Salaam,
Tanzania.
Balmford, A. 1998. On hotspots and the use of indicators for reserve
selection. Trends in Ecology and Evolution 13: 409.
Balmford, A., Mace, G.M. & Ginsberg, J.R. 1998. The challenges
to conservation in a changing world: putting processes on the
map. In: Mace, G.M., Balmford, A. & Ginsberg, J. (eds.).
Conservation in a Changing World. Cambridge University Press,
Cambridge, UK.
Barnes, K.N. 1998. The Important Bird Areas of Southern Africa.
BirdLife South Africa, Pretoria, South Africa.
Bennun, L.A. & Waiyaki, E.M. 1992. An ornithological survey of
Kakamega Forest. Research Reports of the Centre for
Biodiversity, National Museums of Kenya: Ornithology 2.
Bennun, L. & Njoroge, P. 1996. Birds to watch in East Africa: a
preliminary Red Data list. Research Reports of the Centre for
Biodiversity, National Museums of Kenya: Ornithology 23.
Bennun, L. & Njoroge, P. 1999. Important Bird Areas in Kenya.
NatureKenya, Nairobi, Kenya.
Bennun, L.A. & Fishpool, L.D.C. 2000. Important Bird Areas in
Africa. Ostrich 71: 150–153.
Böhme, W. 1977. Eine neue Art der Gattung Bitis (Serpentes,
Viperidae) aus Äthiopien. Monitore Zoologico Italiano, N.S.,
Supplemento 9: 59–68.
Boitani, L., Corsi, F., De Biase, A., D’Inzillo Carranza, I., Ravagli,
M., Reggiani, G., Sinibaldi, I. & Trapanese, P. 1999. AMD
African Mammals Databank - A Databank for the Conservation
and Management of the African Mammals. Istituto di Ecologia
Applicata, Rome, Italy.
Broadley, D. 1999. A new species of worm snake from Ethiopia
(Serpentes: Leptotyphlopidae). Arnoldia Zimbabwe 10: 141–144.
Brooks, T., Balmford, A., Burgess, N., Fjeldså, J., Hansen, L.A.,
Moore, J., Rahbek, C. & Williams, P. (in press) Towards a
blueprint for conservation in Africa. BioScience.
Burgess, N., Fjeldså, J. & Rahbek, C. 1998. Mapping the distributions
of Afrotropical vertebrate groups. Species 30: 16–17.
Burgess, N., de Klerk, H., Fjeldså, J., Crowe, T. & Rahbek, C.
2000. A preliminary assessment of congruence between
biodiversity patterns in Afrotropical forest birds and forest
mammals. Ostrich 71: 286–290.
Byaruhanga, A., Pomeroy, D. & Kasoma, P. (in press) Important
Bird Areas in Uganda. NatureUganda, Kampala, Uganda.
Chapin, J.P. 1953. The birds of the Belgian Congo. Part 3. Bulletin
of the American Museum of Natural History 75A.
Collar, N.J. 1994. Red Data Books, Action Plans, and the need for
site-specific synthesis. Species 21–22: 132–133.
Collar, N.J. & Stuart, S.N. 1985. Threatened Birds of Africa and
Related Islands. ICBP/IUCN Red Data Book, Part 1. Third edition.
International Council for Bird Preservation, Cambridge, UK.
Collar, N.J., Crosby, M.J. & Stattersfield, A.J. 1994. Birds to Watch
2. The World List of Threatened Birds. BirdLife Conservation
Series No. 4. BirdLife International, Cambridge, UK.
Cowling, R.M., Pressey, R.L., Lombard, A.T., Desmet, P.G. &
Ellis, A.G. 1999. From representation to persistence:
requirements for a sustainable system of conservation areas in
the species-rich Mediterranean-climate desert of southern Africa.
Diversity & Distributions 5: 51–71.
Csuti, B., Polasky, S., Williams, P.H., Pressey, R.L., Camm, J.D.,
Kershaw, M., Kiester, A.R., Downs, B., Hamilton, R., Huso,
M. & Sahr, K. 1997. A comparison of reserve selection
algorithms using data on terrestrial vertebrates in Oregon.
Biological Conservation 80: 83–97.
da Fonseca, G.A.B., Balmford, A., Bibby, C., Boitani, L., Corsi, F.,
Brooks, T., Gascon, C., Olivieri, S., Mittermeier, R.A., Burgess,
N., Dinerstein, E., Olson, D., Hannah, L., Lovett, J., Moyer, D.,
Rahbek, C., Stuart, S. & Williams, P. 2000. Following Africa’s
lead in setting priorities. Nature 405: 393–394.
Dowsett, R.J. & Forbes-Watson, A.D. 1993. Checklist of birds of
the Afrotropical and Malagasy regions. Volume 1: Species Limits
and Distribution. Tauraco Press, Liege, Belgium.
Duellman, W.E. 1983. Amphibians in Africa and South America:
evolutionary history and ecological comparisons. In: Goldblatt,
P. (ed). Biological Relationships between Africa and South
America. Yale University Press, Newhaven, USA.
East, R. 1998. African Antelope Database 1998. IUCN - The World
Conservation Union, Gland, Switzerland.
Evans, M.I. 1994. Important Bird Areas in the Middle East. BirdLife
Conservation Series No. 2. BirdLife International, Cambridge, UK.
EWNHS 1996. Important Bird Areas of Ethiopia. Ethiopian Wildlife
& Natural History Society, Addis Ababa, Ethiopia.
Ehrlich, P.R. 1992. Population biology of checkerspot butterflies
and the preservation of global diversity. Oikos 63: 6–12.
Faith, D.P. & Walker, P.A. 1996. How do indicator groups provide
information about the relative biodiversity of different sets of
areas?: on hotspots, complementarity and pattern-based
approaches. Biodiversity Letters 3: 18–25.
Faith, D.P., Walker, P.A., Ive, J. & Belbin, L. 1996. Integrating
conservation and forestry production: exploring trade-offs
between biodiversity and production in regional land-use
assessment. Forest Ecology and Management 85: 251–260.
Freitag, S., Nicholls, A.O. & van Jaarsveld, A.S. 1996. Nature
reserve selection in the Transvaal, South Africa: what data should
we be using? Biodiversity and Conservation 5: 685–698.
Frost, D.R. 1985. Amphibian Species of the World: a Taxonomic
and Geographical Reference. Association of Systematics
Collections, Lawrence, USA.
Gaston, K.J. 1996. Biodiversity—congruence. Progress in Physical
Geography 20: 105–112.
Gómez de Silva Garza, H. 1996. The conservation importance of
semiendemic species. Conservation Biology 10: 674–675.
Hannah, L., Carr, J.L. & Lankerani, A. 1995. Human disturbance
and natural habitat: a biome level analysis of a global data set.
Biodiversity and Conservation 4: 128–155.
Heath, M.F., Evans, M.I., Hoccom, D.G., Payne, A.J. & Peet,
N.B. 2000. Important Bird Areas in Europe: Priority Sites for
Conservation. BirdLife Conservation Series No. 8. BirdLife
International, Cambridge, UK.
Howard, P.C., Viskanic, P., Davenport, T.R.B., Kigenyi, F.W.,
Baltzer, M., Dickinson, C.J., Lwanga, J.S., Matthews, R.A.
& Balmford, A. 1998. Complementarity and the use of indicator
groups for reserve selection in Uganda. Nature 394: 472–475.
Howard, P.C., Davenport, T.R.B., Kigenyi, F.W., Viskanic, P.,
Baltzer, M.C., Dickinson, C.J., Lwanga, J., Matthews, R.A.
& Mupada, E. 2000. Protected area planning in the tropics:
Uganda’s national system of forest nature reserves. Conservation
Biology 14: 858–875.
ICBP 1992. Putting Biodiversity on the Map. Priority Areas for
Global Conservation. International Council for Bird
Preservation, Cambridge, UK.
Largen, M.J. & Rasmussen, J.B. 1993. Catalogue of the snakes of
Ethiopia (Reptilia, Serpentes), including identification keys.
Tropical Zoology 6: 313–434.
Largen, M.J., Kock, D. & Yalden, D.W. 1974. Catalogue of the
mammals of Ethiopia. 1. Chiroptera. Monitore Zoologico
Italiano, N.S., Supplemento 5(16): 221–298.
Laurent, R.F. 1972a. Amphibiens. Volume 22. (Exploration du Parc
National des Virunga, Deuxième sèrie). Fondation pour favoriser
les recherches scientifiques en Afrique, Bruxelles, Belgium.
Laurent, R.F. 1972b. Tentative revision of the genus Hemisus
Günther. Annales du Musée Royal de l’Afrique Centrale. Série
in Octavo, Sciences Zoologique 194: 1–67.
Lawton, J.H., Bignell, D.E., Bolton, B., Bloemers, G.F., Eggleton,
P., Hammond, P.M., Hodda, M., Holt, R.D., Larsen, T.B.,
Mawdsley, N.A. & Stork, N.E. 1998. Biodiversity indicators,
indicator taxa and effects of habitat modification in tropical
forest. Nature 391: 72–76.
Lay, D.M. 1983. Taxonomy of the genus Gerbillus (Rodentia:
Gerbillinae) with comments on the applications of generic and
subgeneric names and an annotated list of species. Zeitschrift
für Säugetierkunde 48: 329–354.
Lombard, A.T., Cowling, R.M., Pressey, R.L. & Mustart, P.J.
1997. Reserve selection in a species-rich and fragmented
landscape on the Agulhas Plain, South Africa. Conservation
Biology 11: 1101–1116.
Loveridge, A. 1951. On reptiles and amphibians from Tanganyika
Territory collected by C. J. P. Ionides. Bulletin of the Museum
of Comparative Zoology 106: 175–204.
Lovett, J.C., Rudd, S., Taplin, J. & Frimodt-Møller, C. 2000.
Patterns of plant diversity in Africa south of the Sahara and their
implications for conservation management. Biodiversity and
Conservation 9: 33–42.
Kosgey, D.K. 1998. Status and Habitat Choice of Turner’s
Eremomela Eremomela turneri (Van Someren 1920) in South
Nandi Forest Reserve, Kenya. MPhil Thesis. Moi University,
Eldoret, Kenya.
Margules, C.R. & Pressey, R.L. 2000. Systematic conservation
planning. Nature 405: 243–253.
May, R.M. 2000. The dimensions of life on earth. In: Raven, P.H. &
Williams, T. (eds.). Nature and Human Society: the Quest for a
Sustainable World. National Academy Press, Washington, D.C., USA.
Mittermeier, R.A., Bowles, I.A., Cavalcanti, R.B., Olivieri, S. &
da Fonseca, G.A.B. 1995. A Participatory Approach to
Biodiversity Conservation: the Regional Priority Setting
Workshop. Conservation International, Washington, DC, USA.
Myers, N. 1988. Threatened biotas: “hotspots” in tropical forests.
The Environmentalist 8: 1–20.
Myers, N., Mittermeier, R.A., Mittermeier, C.G., da Fonseca,
G.A.B. & Kent, J. 2000. Biodiversity hotspots for conservation
priorities. Nature 403: 853–858.
Nasirwa, O. & Njoroge, P. 1996. Status of the Blue Swallow
Hirundo atrocaerula sites in Busia and Suba Districts, Kenya.
Research Reports of the Centre for Biodiversity, National
Museums of Kenya: Ornithology 26.
Nicholls, A.O. 1998. Integrating population abundance, dynamics
and distribution into broad-scale priority setting. In: Mace, G.M.,
Balmford, A. & Ginsberg, J. (eds.). Conservation in a Changing
World. Cambridge University Press, Cambridge, UK.
Noss, R.F. 1987. From plant communities to landscapes in
conservation inventories: a look at The Nature Conservancy
(USA). Biological Conservation 41: 11–37.
Olson, D.M. & Dinerstein, E. 1998. The Global 200: a representation
approach to conserving the earth’s most biologically valuable
ecoregions. Conservation Biology 12: 502–515.
Pearson, D.L. & Cassola, F. 1992. World-wide species richness
patterns of tiger beetles (Coleoptera: Cicindelidae): indicator
taxon for biodiversity and conservation studies. Conservation
Biology 6: 376–391.
Perret, J.-L. 1980. Sur quelques Ptychadena (Amphibia, Ranidae)
d’Ethiopie. Monitore Zoologico Italiano, N.S., Supplemento 13:
151–168.
Pimm, S.L. & Lawton, J.H. 1998. Planning for biodiversity. Science
279: 2068–2069.
Pimm, S.L., Russell, G.J., Gittleman, J.L. & Brooks, T.M. 1995.
The future of biodiversity. Science 269: 347–350.
Pitelka, F.A. 1981. The condor case: an uphill struggle in a downhill
crush. Auk 98: 634–635.
Pomeroy, D. 2000. Birds, hotspots and congruence: a question of
scale? Ostrich 71.
Poynton, J.C. & Broadley, D.G. 1988. Amphibia Zambesiaca 4.
Bufonidae. Annals of the Natal Museum 29: 447–490.
Prendergast, J.R., Quinn, R.M., Lawton, J.H., Eversham, B.C. &
Gibbons, D.W. 1993. Rare species, the coincidence of diversity
hotspots and conservation strategies. Nature 365: 335–367.
Pressey, R.L. 1994. Ad hoc reservations: forward or backward steps
in developing representative reserve systems. Conservation
Biology 8: 662–668.
Pressey, R.L. & Nicholls, A.O. 1989. Efficiency in conservation
evaluation: scoring versus iterative approaches. Biological
Conservation 50: 199–218.
Pressey, R.L., Humphries, C.J., Margules, C.R., Vane-Wright,
R.I. & Williams, P.H. 1993. Beyond opportunism: key
principles for systematic reserve selection. Trends in Ecology
and Evolution 8: 124–128.
Reid, W.V. 1998. Biodiversity hotspots. Trends in Ecology and
Evolution 13: 275–280.
Rose, P.M. & Scott, D.A. 1994. Waterfowl Population Estimates.
IWRB Special Publication No. 29. International Waterfowl and
Wetlands Research Bureau, Slimbridge, UK.
Ryti, R.T. 1992. Effect of focal taxa on the selection of nature
reserves. Ecological Applications 2: 404–410.
Salathé, T. 1991. Conserving Migratory Birds. ICBP Technical
Publication No. 12. International Council for Bird Preservation,
Cambridge, UK.
Scortecci, G. 1935. Un nuovo genere e una nuova specie di Colubridi
Opisoglifi della penisola dei Somali. Annali dell Museo Civico
di Storia Naturale di Giacomo Doria 59: 1–5.
Stattersfield, A.J., Crosby, M.J., Long, A.J. & Wege, D.C. 1998.
Endemic Bird Areas of the World: Priorities for Biodiversity
Conservation. BirdLife Conservation Series No. 7. BirdLife
International, Cambridge, UK.
Terbough, J. & Winter, B. 1983. A method for siting parks and
reserves with special reference to Colombia and Ecuador.
Biological Conservation 27: 45–58.
Uetz, P. & Etzold, T. 1996. The EMBL/EBI Reptile Database.
Herpetological Review 27: 174–175.
Urban, E.K., Fry, C.H. & Keith, S. 1986. The Birds of Africa.
Volume 2. Academic Press, London, UK.
van Jaarsveld, A.S., Freitag, S., Chown, S.L., Muller, C.,
Koch, S., Hull, H., Bellemy, C., Krüger, M., Endrödy-
Younga, S., Mansell, M.W. & Scholtz, C.H. 1998.
Biodiversity assessment and conservation strategies. Science
279: 2106–2108.
Waiyaki, E.M. 1998. An avifaunal survey of South Nandi Forest.
Research Reports of the Centre for Biodiversity, National
Museums of Kenya: Ornithology 30.
Williams, P.H. 1996. WORLDMAP 4.1. Priority Areas for
Biodiversity. The Natural History Museum, London, UK.
Williams, P.H. 1998. Key sites for conservation: area-selection
methods for biodiversity. In: Mace, G.M., Balmford, A. &
Ginsberg, J. (eds.). Conservation in a Changing World.
Cambridge University Press, Cambridge, UK.
Williams, P. & Araújo, M. 2000. Integrating species and ecosystem
monitoring for identifying conservation priorities. European
Nature 4: 17-18.
Williams, P.H., Burgess, N. & Rahbek, C. 2000. Assessing large
‘flagship species’ for representing the diversity of sub-Saharan
mammals. In: Entwhistle, A. & Dunstone, N. (eds.). Priorities
for the Conservation of Mammalian Diversity. Has the Panda
had its Day? Cambridge University Press, Cambridge, UK.
Wilson, D.E. & Reeder, D.M. 1993. Mammal Species of the World:
a Taxonomic and Geographic Reference. Smithsonian Institution,
Washington, D.C., USA.
Yalden, D.W., Largen, M.J. & Kock, D. 1976. Catalogue of the
mammals of Ethiopia. 2. Insectivora and Rodentia. Monitore
Zoologico Italiano, N.S., Supplemento 8: 1–118.
... Globally, the IBA network overlaps with the distribution of 87% of mammals and 76% of amphibians (BirdLife International, 2014). Brooks et al. (2001) found that the representation of threatened and endemic mammals as well as endemic snakes and amphibians was ≥ 90% in East African IBAs 23 . ...
... Kukkala et al. (2016) compared the coverage of IBAs in Europe with the modelled ranges of amphibians, mammals and reptiles at a resolution of 1.5 km. Their findings, that all species at least partially overlap with 23 Overlap was measured in 1 degree grid cells, i.e. an area slightly larger than 10,000 km² (Brooks et al. 2001). ...
Thesis
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Key Biodiversity Areas (KBAs) are sites that contribute significantly to the global persistence of biodiversity, encompassing the composition of biodiversity as well as ecological and biological processes. In 2016, the conservation and scientific community agreed upon a global KBA Standard, outlining five different criteria for identifying KBA sites. One of these criteria is the occurrence of species threatened with global extinction. The European Red List programme has assessed the extinction risk of more than 11,000 species from 19 taxonomic or functional groups of vertebrates, invertebrates and plants since 2007 – over 5,000 of these species are only found on the European continent. In Europe, KBAs have been identified for single species groups such as Important Bird Areas, Important Plant Areas, Prime Butterfly Areas or for multiple species groups including Critical Catchments for freshwater taxa as well as KBAs in Macaronesia and the Mediterranean region. Data from the European Red Lists were partially used as a basis for identifying these KBAs. However, the broad taxonomic coverage displayed in the Red Lists has not been fully exploited in informing KBAs. Those species not already included in KBA identification and which are threatened and endemic to Europe, were selected for the identification of additional potential KBA sites. In the present work, a total of 671 species of amphibians, saproxylic beetles, butterflies, mammals, terrestrial molluscs, plants and reptiles were chosen and their occurrences were recorded in the format of 100 km² grid cells. Spatial analysis of the resulting potential KBA sites was guided by three research questions: (1) Which spatial patterns do KBAs display when adequately representing European species threatened with extinction? (2) Are existing KBAs in Europe sufficient in representing species in the additional potential KBAs or is an expansion of KBA sites necessary? (3) To which extent are potential KBAs covered by protected areas? This analysis demonstrated that potential KBA sites are predominantly located in the southern half of Europe with a clear concentration in Macaronesia and the Mediterranean region. An evaluation of the spatial relationships among the taxonomic groups chosen, including potential surrogacy-target functions, remained inconclusive. Spatial overlap was high with protected areas, Critical Catchments and Important Bird Areas, and smaller with Important Plant Areas. Spatial prioritisation techniques confirmed the overall high spatial congruence of potential KBAs with protected areas and existing KBAs and indicate that adequate representation of European threatened endemics can to a large extent be achieved within existing sites. However, the coarse resolution of the chosen grid cells is susceptible to over- and underestimation of overlap and quality checks at a finer spatial resolution are recommended. Moreover, a species’ range being covered by an existing KBA or protected area, does not mean that the conservation needs of this species are appropriately addressed by site management activities. This thesis provides a dataset of potential KBA sites that can act as frame for a qualitative analysis and can be used as a baseline for KBA delineation and stakeholder consultations. The spatial framework presented here is another step towards conservation of European endemic and threatened vertebrates, invertebrates and plants, and ultimately towards halting the loss of biological diversity.
... In Kenya habitat fragmentation is a paradigm of three main effects: degradation of habitat quality; separation of habitat fragments by anthropogenic matrix (e.g. pasture lands and settlements) and increased intensity of edge effects [14] Habitat changes migrants [15]. The main effect to less diverse and range-restricted birds, rainforest specialists and altitudinal habitat fragmentation and degradation is the reduction of population size and an increased vulnerability to extinction [15]. ...
... pasture lands and settlements) and increased intensity of edge effects [14] Habitat changes migrants [15]. The main effect to less diverse and range-restricted birds, rainforest specialists and altitudinal habitat fragmentation and degradation is the reduction of population size and an increased vulnerability to extinction [15]. This exposes risk to many tropical species, as in Kenya, forest habitats have already been drastically altered by human activities and most of the natural Species abundance is a component of biodiversity and refers to how common or rare a species is relative to other species in a defined location or community. ...
... In particular, seabirds are one of the most threatened groups within the marine environment and their populations have declined globally by almost 70% in the last century (Paleczny et al., 2015;Dias et al., 2019). The establishment of marine protected areas (MPAs) has become one of the most pragmatic approaches to mitigate biodiversity loss (Hyrenbach, Forney & Dayton, 2000;Davidson & Dulvy, 2017;Handley et al., 2020), and seabirds are effective proxies for identifying priority conservation sites for themselves and for other taxa (Brooks et al., 2001). Among seabirds, the Balearic shearwater (Puffinus mauretanicus) is one of the most threatened species in the world (Oro et al., 2004;Genovart et al., 2016;Birdlife International, 2020). ...
Article
1. Spatial modelling is an important research tool to improve our knowledge about the distribution of wildlife in the ocean. Using different modelling techniques (MaxEnt and a generalized linear mixed model), a predictive habitat suitability model was developed for one of the most threatened seabirds in the world: the Balearic shearwater, Puffinus mauretanicus. 2. Models were developed using a 10-year dataset from the Gulf of Cádiz (on the southwestern Iberian Peninsula), a key foraging area for Balearic shearwaters during migration and the non-breeding season. 3. Predictive habitat maps strongly matched the observed distribution patterns, pointing to bathymetric features as the main modelling drivers. The species was concentrated on shallow areas (up to approximately 100 m in depth) of the continental shelf, very close to the mouth of the Guadalquivir River. In contrast with previous studies, Balearic shearwater distribution in the highly dynamic Gulf of Cádiz was not correlated with areas of high chlorophyll a concentration. 4. This lack of spatial correlation probably arises from the delay between the phytoplankton bloom and the response of the zooplankton and small fish that are preyed upon by Balearic shearwaters, which may result in important displacements of this trophic chain across the Gulf of Cádiz. 5. The analysis presented contributes to a better understanding of the spatial distribution and ecology of the critically endangered top predator in the Gulf of Cádiz and offers important information to improve management plans.
... In particular, seabirds are one of the most threatened groups within the marine environment and their populations have declined globally by almost 70% in the last century Drivers for spatial modelling of a critically endangered seabird on a dynamic ocean area: Balearic Shearwaters are non-vegetarian (Paleczny et al., 2015;Dias et al., 2019). The establishment of Marine Protected Areas (MPAs) has become one of the most pragmatic approaches to mitigate the biodiversity loss (Hyrenbach et al., 2000;Davidson & Dulvy, 2017;Handley et al., 2020), and seabirds are effective proxies for identifying priority conservation sites for themselves and other taxa (Brooks et al., 2001). Among seabirds, the Balearic shearwater (Puffinus mauretanicus) is one of the most threatened species in the world (Oro et al., 2004;Genovart et al., 2016;Birdlife International, 2020). ...
... Bird species have been used as indicator species, especially for areas where biodiversity is poorly known, as surrogates for species that are rare and thus hard to detect in the field (Brooks et al., 2001;Githiru et al., 2007;Herremans, 1998;van Eeden et al., 2006) and as indicators for the ecological effectiveness of different land-use and conservation practices (Duckworth and Altwegg, 2018;Herremans, 1998;Hugo and Van Rensburg, 2008;Larsen et al., 2012;Siddig et al., 2016;van Eeden et al., 2006). As a large and distinct bird species, the Masai ostrich (Struthio camelus massaicus) fulfills many criteria (easily detectable; established natural history; widely distributed; strong habitat fidelity; high reproductive capacity) that possibly make the species a suitable indicator (Caro and O'Doherty, 1999) for assessing the ecological effectiveness of protected areas in African savannas. ...
Article
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Assessing the ecological effectiveness of protected areas is a high priority in conservation biology and requires suitable indicators. Instead of using multiple species, single species can potentially be used as indicators to assess if conservation efforts are effective in maintaining species over time. Here, we assessed the suitability of ostrich (Struthio camelus massaicus) population densities and trends over time as indicators for the ecological effectiveness of four study areas (two national parks, a pastoral area, and a game-controlled area with manifold human impacts) in the Tarangire-Manyara ecosystem of northern Tanzania. Based on road transect surveys from 2011 to 2019, we estimated area- and season-specific population densities in a distance sampling framework and estimated temporal changes using generalized linear mixed models. Ostrich population densities and population trends over time were not associated with formal protection status. Ostriches in one national park occurred at highest densities and were constant over time, while densities were low in another national park and apparently declined over time. Ostriches in the pastoral area had the second-highest mean population density, while remaining constant over time. The study area with the highest human impact had lowest ostrich densities and a seemingly declining trend over time. Ostrich densities were positively correlated with time-matched population density estimates of nine out of ten ungulate species in the same study areas, suggesting that ostrich population densities broadly reflect those of large savanna mammals in this ecosystem. However, site-specific ostrich population trends over time were not closely correlated with trends of common large mammal species. Therefore, ostrich population densities appear as suitable management indicators to assess the broad ecological effectiveness of protected areas. However, ostrich population trajectories do not appear suitable as indicator surrogate to monitor trends of mammal populations over time.
... Previous studies that investigated the surrogacy performance in representing biodiversity showed that the suitability of surrogates varies from taxon to taxon ( Lund & Rahbek, 2002;Moore et al., 2003). For example, birds appeared to be good surrogates for other vertebrate groups in the study by Brooks et al. (2001), whereas Lund and Rahbek (2002) found them to be weak surrogates for terrestrial insects. Similarly, birds and bats were relatively good surrogates for each other, but these groups were less effective for bees (Lentini & Wintle, 2015). ...
Article
Priority‐area selection is a core phase of systematic conservation planning, often carried out using a single (surrogate) taxon. Efficient surrogates are expected to yield taxonomically representative priority areas that embrace the populations not only of the surrogate but also the surrogated taxa. Compared with the terrestrial realm, surrogacy performance of riverine taxa has received much less attention. This study compared the surrogacy performance of fishes (FI), macrophytes (MP), and benthic macroinvertebrates (MI) in terms of total area, connectedness, spatial congruence, and taxonomic representativeness of priority areas in the Middle Danube basin (Hungary). Setting three target values for each surrogate group, nine area prioritization designs were run by using a purpose‐written connectivity‐centric algorithm to emphasize the importance of longitudinal connectivity. FI provided the smallest, MP the intermediate, and MI the largest priority areas or solutions. Connectedness was greatest for FI, being one order of magnitude higher than for the other two groups. Pairwise spatial congruence was highest between FI and MP, lowest between MP and MI, and intermediate for FI and MI. MI yielded the most representative solutions, although the number of occurrences of the surrogated taxa in the solution, as a criterion of representation, modified the ratio of the taxa represented. Areas compiled from the overlapping parts of the surrogate‐specific priority sets proved to be smaller than, and similarly representative of, single‐taxon solutions. Taxon‐rich groups such as MI can serve as efficient surrogates, but that can result in larger solutions than for less taxon‐rich surrogates. Apart from the size, the compactness of the solutions seems to be determined by the identity of the surrogate taxa, and FI can be alternative surrogates in connectivity‐centric prioritization. At the same time, multi‐group approaches can enhance the robustness of area prioritization in terms of representativeness compared with single‐taxon procedures.
... Birds dispersed unequally and variably in expressions of numbers and population in the various biogeographic realms. Land use change is known to be a key driver of biodiversity change (Sala et al., 2000;Dania & Rana, 2016).Just like the world's other tropical and sub-tropical parts, sub-Saharan Africa has a higher species diversity (over 2,300 bird varieties, which constitute about 20% of the world's total), a higher proportion (408 bird species) which are endemic to the continent (BirdLife International 2000; Brooks et al., 2001;Sioni, 2006).Avian communities have been found to function as indicators of overall biodiversity and environmental decline or recovery (Nohr & Jorgensen, 1997;Canterbury, Martin, Petit, Petit, & Bradford, 2000;Chase, Kristan III, Lynam, Price, & Rotenberry, 2000), bird distribution should give an indication of the general biodiversity levels of the main land use categories. There is a management concern about the decline in population and distribution of bird's species in some Nigeria National Park. ...
Article
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Study of diversity and abundance of birds in Borgu Sector of Kainji Lake National Park was carried out to provide information on the birds of the Sector. It was conducted in late dry and early wet seasons from December, 2014 to June, 2015 using line transect method at five tracks, namely: Hussaini Mashi, Gilbert Child, Bukar Shuaib, Shehu Shagari and Mahmud Lapai Track. Data were analyzed using analysis of variance (ANOVA) to determine the variability in the distribution across the Tracks while bird' diversity was assessed using Shannon-Weiner diversity index. There was a significant difference (p≤0.05) within species abundance and the mean bird species varied significantly (p<0.05) among the five tracks. A total of 70 bird species from 31 families was recorded during the survey. The study concluded that bird diversity and species abundance are normally distributed and some species are more abundant than the others among the tracks.
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Birds are useful indicators of biodiversity. Their bones have been used for reconstructing the local environments and seasonality of human activity at Epipalaeolithic and early Neolithic sites in south-west Asia. We consider the bird bones from WF16, an early Neolithic settlement in southern Jordan, currently located in an arid environment. The settlement has elaborate pisé-built architecture and material culture. The species represented in the WF16 avian assemblage suggest the environment was considerably wetter and more wooded than today, supporting the idea that early Holocene communities targeted locations with abundant and diverse resources. However, while the range of species at WF16 is equivalent to that found at other Epipalaeolithic and early Neolithic sites in the region, the diversity of the assemblage is strikingly limited, with a heavy dominance of raptors, notably buzzards. We suggest an annual pattern of seasonally based activities, with a relatively small resident population drawing on supplies of water during the winter months for constructing and maintaining site architecture and spring/autumn gatherings of people from across the region to hunt migratory raptors and undertake performance and ceremony at the settlement.
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Anguilla is a UK Overseas Territory, the northernmost of the island groups in the Lesser Antilles, in the eastern Caribbean. It has been long known for its seabirds; 16 species currently breed, with Red-billed Tropicbird Phaethon aethereus, Brown Booby Sula leucogaster and Sooty Tern Onychoprion fuscatus occurring in globally important numbers. There are 16 Important Bird and Biodiversity Areas (IBAs), including five of the islands holding the main seabird colonies. The mainland IBAs are identified for populations of breeding seabirds, including Least Terns Sternuta antiHarum, and/or five restricted-range terrestrial species confined to the Lesser Antilles Endemic Bird Area (EBA).The Dog Island IBA is one of the most important seabird colonies in the Caribbean. Considerable economic growth in recent decades, especially from increased tourism, presents challenges to ensure that new development is sustainable, helping to maintain the rich biodiversity and natural resources upon which the growth is founded.
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The present work summarises the known distribution of Chiroptera in Ethiopia. Seventy-two species are listed, of which 12 represent new records for the country: Rousettus angolensis (Bocage, 1898), Taphozous mauritianus E. Geoffroy, 1818, Nycteris hispida hispida (Schreber, 1775), Hipposideros fuliginosus (Temminck, 1853), Eptesicus guineensis (Bocage, 1889), Mimetillus moloneyi (Thomas, 1891), Nycticeius hindei (Thomas, 1901), Nycticeius hirundo (De Winton, 1899), Scotophilus leucogaster (Cretzschmar, 1830), Otomops martiensseni martiensseni (Matschie, 1897), Tadarida condylura (A. Smith, 1833), Tadarida nanula (J. A. Allen, 1917). As far as possible, all collecting localities in Ethiopia have been gazetted and this record is supplemented with distribution maps for every species. Sixty-two of the species recorded from Ethiopia are essentially African in distribution, six of the remainder are Palaearctic forms and four are associated with the arid Saharo-Sindian belt. Only five species appear to be represented by more than one race and only four are potentially endemic to Ethiopia: Asellia patrizii De Beaux, 1931, Myotis scotti Thomas, 1927, Myotis morrisi Hill, 1971, Kerivoula eriophora (Heuglin, 1877). These figures low compared with those for other groups of small mammals and are, presumably, correlated with the comparative mobility of these flying animals.