Maximizing biodiversity conservation in a forest ecosystem by identifying zones of hotspot overlap. In: Radoglou, K. Proceedings of the International Conference: Forest Research: A Challenge For an Integrated European Approach.pp 581-585

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Maximizing biodiversity conservation in a forest ecosystem by identifying zones
of hotspot overlap.
Vassiliki I. Kati.
The identification of sites of exceptional conservation value for biodiversity maintenance in a forest
ecosystem constitutes the guideline for sustainable forest management. Six taxonomic groups are
selected to represent the concept of biological diversity at local scale - vegetation, orchids, Orthoptera,
aquatic herpetofauna, terrestrial herpetofauna and small terrestrial birds. The diversity assessment of
vegetation is carried out with the help of standard quadrats, of orchids and aquatic herpetofauna using
the method of time-constraint visits, of Orthoptera and terrestrial herpetofauna with the help random
transects of fixed length and of avifauna conducting the acoustic method of point counts of unlimited
distance (I.P.A.). In total, 36 sites of 20ha maximum surface each one are exhaustively sampled in the
forest of Dadia reserve (N.E. Greece), representing 18 Corine habitat types. Local hotspots of each
biological group are identified, as the top one to four sites with the greatest species number, and the
degree of their coincidence is examined. If we decided to protect the top one, two, three and four
richest sites of every group, we should protect 18%, 25%, 32% and 40% of the sampled surface
respectively. For these four levels, hotspots coincide only partially covering 0%, 7.5%, 15% and 21%
of the sampled surface, respectively. The zones of partial hotspot coincidence are mosaic character
habitats, derived from mild human activities, situated either in forest openings or in rural zone. Forest
openings combine a diversity of microhabitats such as patches of woods, mesophile grasslands and
shrubs, whilst rural mosaics include small agricultural plots, wood patches, hedges and tree lines. In
conclusion, poor hotspot overlap is revealed for the forest of Dadia reserve. Forest management should
be orientated towards the enhancement of the heterogeneity of forest ecosystem, maintaining small
wood clearings and rural patches, so as to maximize the conservation of biological diversity.
Biodiversity, conservation, hotspot, overlap, mosaics.
I. INTRODUCTION
One of the most critical issues in the field of conservation biology is to identify sites of exceptional
biological wealth, where a great number of species or threatened species is concentrated in limited
surface (Muyers et al. 2000). The identification of such “biodiversity hotspots” is a necessary first step
in priority setting for conservation (Cincotta et al. 2001).
At local scale, the identification of local biodiversity hotspots pinpoints practically localities that
should be the first to be protected and also guides environmental management towards the maintenance
of such type of habitats.
In the current research, we represent the concept of biodiversity by six different biological groups, we
define as “hotspot” the top richer sites of each one biological group studied and we investigate the
degree of hotspot overlap, so al to pinpoint zones of coincidence that constitute the local biodiversity
hotspots.
II. METHODS
Study area
The study area is situated in northeastern Greece, in the region of Thrace, at longitude between 26° 00'
and 26°19' and at latitude between 40°59' and 41°15'. The whole study area covers 43,000ha, of which
42,450ha belong to the forest reserve of Dadia-Lefkimmi-Soufli complex. It is forest-dominated area
(70% of the reserve) mainly of Pinus brutia woods.
Sampling sites
Thirty-six sites, having from 2 to 20ha surface, are sampled. They represent 18 different habitat types
or combinations of habitat types, according to the typology of CORINE database (Devillers et al. 1996)
(Table 1).
TABLE 1: Classification of the habitat types in the study area and number of sampling sites.

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Vegetation
type
Corine code Corine description N. of
sites
Site code of
hotspot
coincidence
Forest 41.1B x
41.19311
Mediterraneo-Moesian beech forests x Balkan
Range woodrush
-
beech forests
2
41.76 Balkano-Anatolian thermophilous oak forests 2
41.733 Hellenic [Quercus pubescens] woods 4 QyA
43.7 Thermophilous pine-oak forest 2
42.661(C) Thracian Pallas' pine forests 1
42.85 A Thracio-Macedonian Aegean Pine forests 3
44.514 East Mediterranean Alder Galleries 2
44.615 East Mediterranean Poplar Galleries 2
Scrub 32.313 Eastern Mediterranean high maquis 2
32.161 Eastern deciduous oak mattoral 1 Qph
32.21A4 x
34.53
Eastern Phyllirea thickets x East -Mediterranean
xeric grasslands
1
Heath 32.32 Low ericaceous maquis 2
Grassland 37.4 (x
41.8221)
Mediterranean tall humid grasslands (x Helleno-
Pelagonide oriental hornbeam woods)
2
34.53 East Mediterranean xeric grasslands 2
34.2 Heavy-metal grasslands 1
Agricultural
land
84.4 Rural mosaics 2 AgtraA, AgtraB
82.11 Field crops 2
Mosaic 37.4 x 38.1 x
32.71 x 44.12
x 41.733
Mediterranean tall humid grasslands x Mesophile
pastures x Helleno-Balkanic pseudomaquis x
Lowland and collinear riverine willow shrubs x
Hellenic [
Quercus pubescens
] woods
3 MosA
MosB
MosC
Total
21
18
36
Sampling methods
Six different biological groups are sampled to represent the concept of biodiversity (Pearson 1995;
Noss 1990): vegetation, Orthoptera, orchids, aquatic herpetofauna (amphibians and freshwater
terrapins), terrestrial herpetofauna (lizards and terrestrial tortoises) and small terrestrial birds.
Vegetation was qualitatively sampled with the help of three standard quadrats of [25m*25m], randomly
located in each site (Kent and Coker 1994). Orchids were recorded in a qualitative way, using visits of
fixed time duration. Sampling repeated twice during springtime for two successive years (1998-99).
Species were identified in situ (Delforge 1994). Semi-quantitative data were collected during
Orthoptera sampling, counting individuals during transects of 30m and 90m for open sites (shadow less
than 60%) and closed (shadow more than 60%) sites respectively. Each site was sampled by two
transects. Sampling repeated three times: late spring, summer, autumn. Species were identified
stereoscopically (Willemse 1985). Time constraint visits were conducted for collecting presence-
absence data for aquatic herpetofauna (Crump and Scott 1994). Sampling was carried out once during
early spring at dusk for acoustic identification of species choruses, and three more times during early
spring, spring and summer for visual identification of adults, larvae and egg masses. We used random
transects of 300m fixed length, counting individuals of terrestrial herpetofauna (Krebs 1989). Sampling
repeated during early spring, late spring and summer. Small terrestrial birds were identified
acoustically, using the point count method of unlimited distance (I.P.A) (Blondel et al. 1970). Up to
five sampling stations were carried out in each site. Sampling repeated twice during early spring and
late spring.
Prendergast (1993) defined as hotspot the top 5% of grids with the maximum number of species of the
taxonomic group concerned. If we select the richest site of each taxonomic group, we define as a
hotspot the top 2.7% (1site/36sites) of sites with the maximum number of species. In the same way, if

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we select the first two, three and four richer sites, for every taxonomic group, we define the hotspot as
the top 5.5% (2/36), 8% (3/36) and 11% (4/36) of sites with the maximum number of species.
III. RESULTS
Sampling resulted in the record of 55 species of trees and bushes, 25 orchid species (Kati et al. 2000),
39 Orthoptera species (Kati and Willemse in press), 10 species of aquatic herpetofauna, 10 species of
terrestrial herpetofauna and 72 species of small terrestrial birds (Kati 2001).
According to table 3, if we decided to protect the richest site of each targeted group (level 2.7%), then
we would form a network of 6 sites and we would protect 18% of the sampled surface. In this level,
there is no hotspot overlap at all.
If we selected the first two richer sites of each group (hotspot level 5.5%), we would conserve 25% of
sampled area forming a network of 8 sites. The overlap of the different networks is poor. There is no
site where all networks coincide. Three networks coincide in two sites that cover 30% of the protected
surface.
TABLE 3: Degree of hotspot overlap and sites where the hotspot coincide in four levels of hotspot
definition: 3%, 5.5%, 8% and 11% of the sampled surface.
Hotspot
definition
N. of hotspots
selected for
every
tax. group
Total
surface of
all hotspots
Surface of
hotspot
overlap
Number of
taxonomic
groups that
coincide
Site code of
hotspot coincidence
3%
1
103ha
0ha
-
-
5.5%
2
133 ha
(8 hotspots)
40ha
(30%)
2
-
3
MosA, AgtraB
4
-
5
-
6
-
8%
3
183ha
(11 hotspots)
90ha
(49%)
2
AgtraA, Qph
3
MosA, AgtraB, MosC
4
-
5
-
6
-
11%
4
223ha
(13 hotspots)
120ha
(53%)
2
Qph, QyA
3 MosA, AgtraB, AgtraA
4 MosC
5 -
6 -
If we selected the first three richer sites of each group (hotspot level 8%), we would form a reserve of
11 sites, covering 32% of the sampled surface. In this case too, no site exists to be classified among the
richest by all studied groups. There is only a partial overlap of three networks in five sites. Hotspots
coincide partially in 90ha out of the 183 ha of the protected area.
Finally if we selected the first four richer sites of each group (level 11%), we would conserve 40% of
the sampled surface. In this level, hotspots coincide partially in 120ha out of the 223ha of the protected
area.
When we increase the surface we protect we increase the probability of hotspot overlap. Therefore,
Qph and Qy cannot be considered as really rich sites, because only two networks coincide when 40%
of the area is protected.
IV. DISCUSSION
Several studies confirm the poor overlap of hotspots of richness or rarity across different taxonomic
groups at regional or global scale (Ricketts et al. 2000; Tardif and DesGranges 1998; Dobson et al.
1997; Gaston and Williams 1996; Lombard 1995; Prendergast et al. 1993). However one study

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presented a quite important overlap of rarity hotspots in Greece at national scale (Troumbis and
Dimitrakopoulos 1998). Our results confirm that there is a rather poor hotspot overlap across different
taxonomic groups at local scale, as well.
If centres of richness across different taxonomic groups were coincident, the conservation decision
would be much easier, because the only preoccupation of reserve-designers would be to identify these
centres. However, there is a lack of congruence in biodiversity patterns. What is "good" for one taxon
is not necessarily "good" for another. Species have their own specific requirements and general patterns
among them occur only because their demands happen to coincide.
In our study area, the zones of hotspot coincide are sites of mosaic character: MosA, MosC, AgtraA
and AgtraB. As far as the mosaic sites MosA and MosC are concerned, they are semi-open patchy
habitats, hosting the greatest diversity of tree and bush species. They combine different habitat types
(table 1) and they have a great structural complexity of vegetation elements (Kati 2001). Mild human
activities such as periodical grazing and logging have contributed to their high structural complexity.
As far as the rural mosaics are concerned, they are highly heterogeneous habitats that combine
agricultural plots with hedges, streams and wood patches.
The coexistence and combination of several habitats at local scale is one of the generating factors of
local biological diversity (Law and Dickman 1998; Kerr and Packer 1997). The hotspot overlap in
mosaic character sites confirms this theory at a very fine scale (20ha).
As far as the limitation of the current study are concerned, we should emphasize that conclusions
cannot be easily extrapolated without repeated and vigorous testing, in different study areas and by
sampling different biological groups to represent the concept of biodiversity.
V. CONCLUSIONS
 There is poor and partial hotspot overlap at local scale.
 Forest management should focus on the maintenance of forest openings with high vegetation
diversity and structural complexity; such sites constitute partially local biodiversity hotspots in
the study area
 Environmental managements should target the maintenance of rural mosaics, as small
openings inside forest ecosystems; such agricultural plots constitute partially zones of hotspot
overlap in the study area.
ACKNOWLEDGEMENTS
I express my gratitude towards the Institute Bodossaki and towards the Institute Alexandros Onassis,
which funded the current research, under a frame of a Ph.D. scholarship for biodiversity issues.
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