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Testing alternative indicators for
biodiversity conservation in oldgrowth boreal forests: ecology
and economics
Artti Juutinen1 & Mikko Mönkkönen2
1
University of Oulu/Faculty of Economics and Industrial Management,
Finland
2 University of Oulu/Department of Biology, Finland
Background





Habitat loss
Setting aside areas that are particularly
biodiverse: site selection problem
The contribution, which the area can make to
represent the overall biodiversity
It is costly to measure the overall biodiversity
Surrogate measures of biodiversity
Background
How is one to choose a good indicator?
 Indicators should reflect the overall
biodiversity (the chosen ecological
features that are regarded important)
 Indicators should not be expensive to
monitor
 Formal tests are required

Method
Site selection models
 Clear-cutting or protection
 We compare the benchmark models
and indicator models
 In the benchmark the focus is on
species diversity, best available data
 The benchmark selection represents the
maximum level of biodiversity in the
area at given resources devoted to
conservation

Method
Funds available for conservation (A)
Representation of species
Benchmark selection
a
B
The goal level of representation (B)
b
Indicator selection
A
Conservation costs (excluding inventory costs)
Method
Table 1. Site selection models. Site constraint is used in the ecological models (E), and a
budget constraint in the integrated models (I). Notation is explained in Appendix 2.
EDIV* & IDIV**
ENUM* & INUM**
Max Z   y i
Max Z 
x , y 
iZs
x
 
iZs jJ
EDW* & IDW**
yij x j Max Z  a  x j v j  b  qi
x, q
j J
(1)
iQ
Subject to
 x j  yi
 x j  qi
 i  Zs
j  Ni
n
xj  k
j 1
n
i  Q
j Mi
n
xj  k
j 1
n
n
xj  k
(3)*
n
(4)**
j 1
b j x j  I s  B
b j x j  I s  B
b j x j  I s  B
x j , y i  0,1  i  Zs,  j  J
x j  0,1  j  J
x j , qi  0,1  i  Q,  j  J
j 1
(2)
j 1
j 1
(5)
Method

IDIV-model
 Maximize species richness in the selected stands
subject to the given budget constraint (species are
counted once, if they are present in the selected
stands)
 The IDIV model, which incorporates information on all
species, is the benchmark model with which all the
other models are compared.
n
 Budget constraint:  b j x j  I s  B
j 1
 INUM-model
 Maximize count of species in the selected stands
subject to the given budget constraint (species are
counted as many times as they are present in the
selected stands)
Method
STAND 1
STAND 2
A
A
B
C
IDIV: Z = 3
INUM: Z = 4
STAND 1
STAND 2
STAND 3
STAND 4
A
A
B
C
A
C
D
A
C
D
IDIV
INUM
Data

32 SEMI-NATURAL OLD GROWTH FORESTS STANDS FROM
FINLAND
 IN THE OPTIMIZATIONS THE STANDS WERE TREATED AS HAVING
EQUAL SIZE
 FOUR FOREST TYPES, EIGHT REPLICATES OF EACH
 XERIC CONIFEROUS FORESTS, MESIC SPRUCE FORESTS, SPRUCE
MIRES, HERB RICH SPRUCE DOMINATED HEATH FORESTS
 SPECIES, 632 (PRESENCE/ABSENCE)
 VASCULAR PLANTS (103), BIRDS (30), WOOD-INHABITING FUNGI
(64), BEETLES (435)
 DECAYING WOOD
 COMMERCIAL VALUES OF THE STANDS
 THE OPPORTUNITY COSTS OF CONSERVATION
 MAXIMUM NPV FOR EACH STAND, MELA-MODEL
 FAUSTMANN ROTATION MODEL
 INVENTORY COSTS OF THE SPECIES GROUPS AND DECAYING
WOOD
Data

INDICATORS
 TAXONOMIC GROUPS
 A SUBGROUP OF OLD-GROWTH FOREST INDICATOR SPECIES
BASED ON THEIR KNOWN STATUS AS OLD-GROWTH FOREST
SPECIALISTS (42 species including species of birds, beetles and woodinhabiting fungi)
 THE AMOUNT AND QUALITY OF DECAYING WOOD
Table 2. Total inventory costs for different indicators.
Inventory costs
Beetles (435 spp.)
€
34 479
Birds (30 spp.)
2 691
Vascular plants (103 spp.)
3 868
Wood-inhabiting fungi (64 spp.)
5 718
Old-growth forest indicators (42 spp.)*
Decaying wood (amount in 114 quality classes)
31 788
4 205
Results
b) Vascular plants
100
90
80
Beetles
Birds
70
60
0
20
40
60
80
Species
representation, %
Species
representation, %
a) Beetles and birds
100
90
80
70
60
100 120
0
Opportunity costs, 1000 €
90
80
70
60
20
40
60
80
100 120
d) Old forest species
100
0
40
Opportunity costs, 1000 €
Species
representation, %
Species
representation, %
c) Wood-inhabiting fungi
20
60
80
100 120
100
90
80
70
60
0
Opportunity costs, 1000 €
20
40
60
80
100 120
Opportunity costs, 1000 €
Figure 4. Relative number of species represented (= (1-(Ybench-Yind)/Ybench)*100) in the
selected conservation network, plotted as a function of opportunity costs, based on the
IDIV model excluding inventory costs using (a) beetles and birds, (b) vascular plants, (c)
wood-inhabiting fungi, and (d) old-growth forest indicator species.
Results
Table 3. Mean cost difference (=(Cbench-Cind)/Cbench*100) between indicator species
groups and benchmark at different levels of species represented in the selected network
relative to total species number (%), based on the IDIV models. The last row includes the
mean cost difference calculated over the whole range, where the particular indicator is
operative. The mark (–) indicates the range, where the indicator is not operative.
IDIV models
Range of
Vascular
Wood-
plants
inhabiting
forest
fungi
indicator
species
Birds
Beetles
Old-growth
represented
species
1-60 %
84
79
83
24
20
61-70 %
69
60
63
20
-3
71-80 %
55
38
-
17
-27
81-90 %
45
15
-
13
-
91-100 %
-
-
-
7
-
1-100 %
68
56
79
14
12
Results
Table 4. Mean cost difference (=(Cbench-Cind)/Cbench*100) between indicator species
groups and benchmark at different levels of species represented in the selected network
relative to total species number (%), based on the INUM models. The last row includes
the mean cost difference calculated over the whole range, where the particular indicator is
operative. The mark (–) indicates the range, where the indicator is not operative.
INUM models
Range of
Vascular
Wood-
plants
inhabiting
forest
fungi
indicator
species
Birds
Beetles
Old-growth
represented
species
1-60 %
81
78
84
24
26
61-70 %
71
66
72
20
19
71-80 %
58
56
61
17
7
81-90 %
41
41
46
12
1
91-100 %
26
18
26
5
-3
1-100 %
48
44
53
13
8
Conclusions
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The use of indicators seems to result in a loss of overall
diversity.
It is important to consider trade-offs between conservation costs
and diversity loss when assessing the goodness of an indicator.
Biodiversity indicators can be tested in economic context by
using integrated site selection model.
Species richness based model may not be appropriate for
indicator groups having small number of species.
It seems to be more efficient to use indicators than execute
large biodiversity survey.
how to reduce inventory costs of biodiversity surveys?
Birds and vascular plants should be used as indicators in
protecting boreal old-growth forests in the study area.