species diversity of longicorn beetles in humid warm temperate
TRANSCRIPT
Biodiversity and Conservation 11: 1919–1937, 2002. 2002 Kluwer Academic Publishers. Printed in the Netherlands.
Species diversity of longicorn beetles in humid warm-temperate forests: the impact of forest managementpractices on old-growth forest species in southwesternJapan
1,3, 1 2*KAORU MAETO , SHIGEHO SATO and HIROAKI MIYATA1Shikoku Research Center, Forestry and Forest Products Research Institute, Asakura-Nishimachi, Kochi
2780-8077, Japan; Kochi Prefectural Forest Technology Center, Ouhira, Tosayamada 782-0078,3Japan; Current address: Entomological Laboratory, Faculty of Agriculture, Kobe University, Nada-ku,
*Kobe 657-8501, Japan; Author for correspondence (e-mail: [email protected]; fax: 181-78-803-5871)
Received 22 June 2001; accepted in revised form 26 November 2001
Key words: Attractant trap, Bio-indicator, Chronosequence, Coarse woody debris, Conifer plantation,Insect biodiversity, Pidonia, Pollinator, Saproxylic Coleoptera
Abstract. In the humid warm-temperate zone of southwestern Japan, old-growth forests have beenseriously fragmented to small remnants due to traditional agriculture and coppicing as well as recentrapid plantation with conifers. Assemblages of longicorn beetles (Coleoptera: Disteniidae andCerambycidae) were compared among old-growth forests, second-growth forests and conifer plantationsusing collision traps baited with chemical attractants. Species richness of longicorn beetles was poorer insecond-growth forests and conifer plantations than in old-growth forests. It was proved by multi-dimensional scaling (MDS) that the beetle assemblages of old-growth forests were distinct from those ofconifer plantations, while those of second-growth forests were intermediate between them. Furtheranalysis showed that a number of species, including many Pidonia spp., were specific to or closelyassociated with old-growth forests, and the results were largely supported by the indicator value (IndVal)approach. It is likely that many of such old-growth forest species in the larval and pupal stages requirelarge broad-leaved trees standing or fallen with thick bark. At the same time, the flower-visiting adultswould play an important role in pollinating various herbaceous and woody plants. Regional forestmanagement for the conservation of insect biodiversity is also discussed.
Introduction
Southwestern Japan was formerly widely covered by humid warm-temperateevergreen or deciduous broad-leaved forests often mixed with evergreen conifers,but such forests have been extensively exploited since ancient times (Shidei 1974).Almost all lowland forests have been converted to rice paddies, farmland andresidential areas. In hilly and mountain areas, the forests have been severely alteredthrough shifting cultivation, coppicing for manure and fuel wood production, andplantation with conifers. After World War II, remaining old-growth forests wererapidly cleared and usually converted to plantations of Japanese cedar and cypress(Japan FAO Association 1997). As a result, relatively unchanged forests cover lessthan 1% of the potential area of this forest type in Japan (Sasse 1998). NACS-J and
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WWF Japan (1996) reported that warm-temperate forests have been seriouslyaffected by deforestation and plantation with conifers, and the remnants need urgentconservation. Although arthropod diversity may be deteriorated due to the forestconversion, only a little is known about the importance of old-growth forests in themaintenance of insect diversity in Japan (Maeto and Makihara 1999).
For sustainable forest management in consideration of regional biodiversity, it isnecessary not only to know the effects of forest conversion on insect speciesrichness but also to understand the ecological requirements and functional interac-tions of the insects that depend on old-growth forests (e.g. Fisher 1998). Quite a fewstudies have been conducted on the influence of forest management practices onarthropod communities or assemblages in temperate and boreal forests, e.g., canopy
¨arthropods (Schowalter 1989), ground beetles (Niemela et al. 1993; Magura et al.2000), boreal forest beetles (Martikainen et al. 2000). However, the implications offorest treatments for longicorn beetles are largely unknown, although they areprincipal components of forest ecosystems as herbivores and detritivores of woodyplants, pollinators of herbaceous and woody plants, and prey of insectivorousanimals (Linsley 1959; Ohbayashi et al. 1992; Hanks 1999).
The purpose of this study was to compare the assemblage of longicorn beetlesamong old-growth forests without logging records, second-growth forests andconifer plantations in the humid warm-temperate zone of Japan, in order to identifythe characteristic species of old-growth forests and understand their ecologicalrequirements. Collision traps baited with chemical attractants (Maeto et al. 1995;Shibata et al. 1996) were used for a quantitative comparison of beetle assemblages.
Materials and methods
Study sites
The study focused on the Shimanto River Basin of Kochi Prefecture in Shikoku, thefourth largest island of the Japanese archipelago. The river basin is covered withlowland and hilly forests up to 1400 m in elevation, principally composed of coniferplantations (about 60% of total forest area), second-growth forests (about 40%), andremnants of old-growth forests without historical records of clearance (less than1%). Old-growth forests are dominated by evergreen conifers (Abies firma, Tsugasieboldii, Chamaecyparis obtusa) as well as by diverse evergreen broad-leaved trees(Quercus spp., Castanopsis cuspidata, Machilis japonica, Cleyera japonica, etc.).Starting at 800 m a.s.l., evergreen broad-leaved trees are gradually replaced bydeciduous trees (Carpinus spp., Fagus spp., Betula grossa, Acer spp., etc.). Second-growth forests have been repeatedly cut at intervals of 30–80 years; coppicesdominated by evergreen broad-leaved trees (C. cuspidata, Quercus glauca, etc.) aredeveloped in lowlands, and mixed forests of red pine (Pinus densiflora) anddeciduous broad-leaved trees (Q. serrata, Carpinus spp., etc.) are widespread in thehills. Conifer plantations are monocultures of Japanese cedar (Cryptomeriajaponica) or Japanese cypress (C. obtusa); in appropriately managed plantations
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over 30 years old, forest floors are covered with rich species of shrubs after thinning,and diverse tree species grow along forest edges, paths and streams. Annual meantemperature and annual precipitation in 1991–2000 at Yusuhara (415 m a.s.l.,Figure 1) averaged 13.4 8C and 2722 mm, respectively.
Seven old-growth forests (without any records of clearance at least for 120 years),five second-growth forests (30–70 years old) and two appropriately managedconifer plantations (30–40 years old) were selected for sampling sites within a 50 3
50 km area of the river basin (338059–338309 N, 1328359–1338059 E; Figure 1). Foreach site, woody plant species observed in a plot of about 0.05 ha were recorded,and the diameter at breast height (DBH) of the trees (DBH .5 cm) with the canopyhanging over a 20 m randomly placed straight line was measured. Site location,forest type, approximate forest age, altitude, direction, slope, the number of woodyplant species, and the maximum DBH of conifers and broad-leaved trees are listedin Table 1.
Sampling and identification
Specimens were collected with yellow or white collision traps, each baited with
Figure 1. Location of the study sites in Kochi Prefecture, Shikoku Island, Japan.
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Tab
le1.
Loc
atio
n,fo
rest
type
,ap
prox
imat
efo
rest
age
and
stan
dva
riab
les
ofth
est
udy
site
s.
ab
cSi
teLo
catio
nFo
rest
type
Age
offo
rest
(yea
rs)
App
rox.
area
(ha)
Alti
tude
(m)
Dire
ctio
nSl
ope
(8)
Num
bero
fwoo
dyM
axim
umD
BH
(cm
)d
epl
ant
spec
ies
oftre
es
Con
ifers
Bro
ad-le
aved
trees
AIr
azu,
HO
LD.
190
150
1050
N15
2399
.8(2
)33
.1(2
0)f
BTe
ngu,
HO
LD.
120
100
1250
S40
8,
5.0
(0)
26.8
(11)
CY
okog
ai,Y
SEC
40–5
0.
200
800
N20
2442
.0(6
)13
.5(1
5)
DTa
rohg
awa,
YSE
C30
–40
.20
070
0W
4011
12.4
(5)
25.3
(10)
EK
ohno
shi,
YC
PL30
–35
.20
070
0S
2517
23.0
(11)
,5.
0(0
)
FTa
kato
ri,Y
OLD
.17
090
350
N20
2758
.2(2
)78
.6(1
9)
GK
ubot
ani,
YO
LD.
200
8070
0W
4524
76.3
(4)
27.9
(5)
HTs
uzur
agaw
a,T
SEC
40–5
020
400
W40
3643
.2(2
)14
.3(1
4)
IIc
hino
mat
a,T
OLD
.18
050
500
N40
2251
.0(2
)42
.4(1
2)
JIc
hino
mat
a,T
CPL
30–3
5.
200
450
N35
2316
.9(9
),
5.0
(0)
KN
akab
a,N
SEC
20–3
0.
200
100
N45
21,
5.0
(0)
21.7
(30)
LK
uros
on,N
SEC
7030
350
S40
1537
.6(2
)30
.6(1
2)
MK
uros
on,N
OLD
.12
025
070
0E
3515
116.
6(1
)34
.4(1
6)
NH
arai
kaw
a,N
OLD
.14
050
500
N40
16,
5.0
(0)
39.4
(17)
ab
H–
Hig
ashi
tsun
o-m
ura;
Y–
Yus
uhar
a-ch
o;T
–T
aish
oh-c
ho;N
–N
ishi
tosa
-mur
a.O
LD
–ol
d-gr
owth
fore
st;S
EC
–se
cond
-gro
wth
fore
st;C
PL–
coni
fer
plan
tatio
n.c
de
App
roxi
mat
ely
estim
ated
area
ofth
esa
me
type
,con
tinuo
usfo
rest
s.N
umbe
rof
woo
dypl
ant
spec
ies
obse
rved
ina
plot
ofab
out
0.05
ha.
For
all
tree
sha
ngin
gov
era
fst
raig
htlin
eof
20m
;nu
mbe
rsin
pare
nthe
ses
indi
cate
the
num
ber
oftr
ees
with
DB
H.
5cm
.Fo
rest
floor
was
poor
insp
ecie
s,be
ing
cove
red
with
dwar
fba
mbo
o.
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Figure 2. Collision trap baited with benzyl acetate and ethyl alcohol.
benzyl acetate and ethyl alcohol. The collision traps consisted of a roof, twocollision plates (about 25 3 20 cm) intersecting each other, and a bucket (Figure 2;Sankei Chemical Co., Ltd.; Maeto et al. 1995; Shibata et al. 1996). Benzyl acetate isone of the main components of floral fragrance, and it lures various flower-visitingbeetles (Ikeda et al. 1993; Sakakibara et al. 1997b). Ethyl alcohol is known to attractxylophagous beetles for oviposition (Ikeda et al. 1980). Dispensers of the chemicals,each about 25 ml, were placed under the roof. Water containing a surface-activeagent and sorbic acid was poured into the bucket to preserve the specimens. Thetraps were set at about 1.5 m above the ground.
At each site, two white and two yellow traps were placed alternatively at intervalsof about 50 m in line. Trapping was conducted from early April to mid-September in1998. Every 2 weeks, chemicals were renewed and materials in the buckets weretaken to the laboratory. Trap sampling was repeated in the same manner at five sites(A, C–F) in 1999, to confirm the invariability of species assemblages between years.
Longicorn beetles (Coleoptera: Disteniidae and Cerambycidae) were pinned foridentification. They were identified with Ohbayashi et al. (1992).Voucher specimenswill be deposited in the Shikoku Research Center, Forestry and Forest ProductsResearch Institute, Kochi, Japan.
To evaluate the taxonomic bias in the trap sampling, the number of speciescollected in this study was compared with the number of species collected bygeneral methods in the same region for each family and subfamily (Nakayama et al.1994). They reported 148 species of longicorn beetles collected by hand, in beating,
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Table 2. Number of longicorn beetle species collected in white and yellow collision traps attached withbenzyl acetate and ethanol in 1998, and of those collected with general methods (i.e. by hand, in beating,in light traps and in collision traps) over 6 years (1987–1993) in the same region.
Family Subfamily Number of species Number of species T/Ocollected in the collected with
a btraps in 1998 general methods (O)
WT YT Total (T)
Disteniidae 0 2 2 2 1.00Cerambycidae Prioninae 2 2 3 4 0.75
Spondylinae 1 1 1 4 0.25Lepturinae 34 13 34 36 0.94Necydalinae 0 0 0 1 0.00Cerambycinae 17 17 19 36 0.53Lamiinae 16 18 23 65 0.35
Total number of species 70 53 82 148 0.55a bWT – white traps; YT – yellow traps; both were baited with benzyl acetate and ethanol. At Mt.Ohnakayama (Figure 1), Yusuhara-cho, Kochi Prefecture (Nakayama et al. 1994).
in light traps and in various bait traps for 7 years on Mt. Ohnakayama, KochiPrefecture, up to about 800 m in elevation (Figure 1). Vegetation was composed ofsecond-growth forests, plantations of Japanese cypress, plantations of Q. acutissima,and old-growth remnants.
Data analyses
All the specimens captured in the two white and two yellow traps at each site everyyear were pooled together for the following analyses. Two species richness indices,i.e. the number of species and the Margalef index (Magurran 1988), were comparedamong three forest types and among four directions by the Kruskal–Wallis testbased on the samples of 1998. Kendall’s coefficient of rank correlation (Kendall’stau, t) between the species richness indices and the stand variables (altitude, slope,the number of woody plant species, and the maximum DBH of conifers andbroad-leaved trees) were tested. The Margalef index was calculated as
Margalef index5(S21) / lnN
where S is the number of species and N the number of individuals.Similarity of assemblages between each pair of samples was computed from
abundance data using the rank correlation coefficient (Kendall’s tau, t) (Ghent1963; Huhta 1979). From the matrix of similarity (t), the samples were plotted in atwo-dimensional space by multidimensional scaling (MDS). First, we performedtwo-dimensional MDS for all samples collected in 1998 (14 sites) and 1999 (5sites). The samples were clustered with the group average method based on theEuclidean distance between each pair of them in the MDS space. After weconfirmed that the samples of 1998 and 1999 collected at every site were fairly closeto each other in the dendrogram, we performed two-dimensional MDS for the
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samples of 1998 (14 sites) again. For each of the two MDS dimensions, thedifferences in site score among forest types and among directions were tested by theKruskal–Wallis test. Kendall’s coefficient of rank correlation was tested betweenthe MDS site scores and the stand variables. For the species collected at three ormore sites, Kendall’s coefficient was tested between the MDS scores and thenumber of individuals. All statistical analyses were performed with STATISTICA(StatSoft Inc. 1998).
ˆWe also applied the indicator value method proposed by Dufrene and Legendre(1997) to identify the most characteristic species of each forest type for the samplesof 1998. This method combines a species relative abundance with its relativefrequency of occurrence in a particular habitat type to obtain the indicator value forthe habitat type. The species indicator value (IndVal) is the maximum indicatorvalue over all habitat types (three forest types in our study). Statistical significanceof IndVal was evaluated with a Monte Carlo test (McCune and Mefford 1997).
Results
Taxonomic bias in trap sampling
A total of 25115 individuals belonging to 82 species of longicorn beetles werecollected in 1998. As compared with the fauna of longicorn beetles in the sameregion (Nakayama et al. 1994), our trapping system collected all species of thefamily Disteniidae, most of the subfamily Lepturinae, but a rather small portion ofthe subfamilies Cerambycinae and Lamiinae (Table 2). The lepturine species wereall captured in the white traps, while the disteniid species and some cerambycineand lamiine species were captured only in the yellow traps.
Figure 3. Species richness indices of longicorn beetles in relation to the number of individuals collectedin 1998. For forest type symbols, see Figure 1.
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Figure 4. Margalef index in relation to the number of woody plant species (a), and to the maximum DBHof broad-leaved trees (b) (cf. Table 4). For forest type symbols, see Figure 1.
Table 3. Median and range (in parentheses) of the species richness indices and MDS site scores forlongicorn beetle assemblages of three forest types in 1998.
Type of forest H
Old-growth Second-growth Coniferforest n 5 7 forest n 5 5 plantation
n 5 2
Species richnessNumber of species 27 (15–33) 22 (9–24) 21 (20–22) 2.61
*Margalef index 3.79 (3.03–4.27) 2.97 (1.67–3.32) 2.41 (2.03–2.79) 8.14MDS site scores
**First dimension 20.60 (21.05 to 20.04) 0.33 (20.24–0.82) 1.45 (1.35–1.55) 10.13Second dimension 0.03 (21.34–0.74) 20.07 (20.44–1.21) 20.38 (20.98–0.22) 0.56
* **Differences were examined by the Kruskal–Wallis test. P , 0.05; P , 0.01.
Table 4. Rank correlation coefficient (t) between the species richness indices and MDS site scores forlongicorn beetle assemblages of 1998 and the stand variables of study sites (n 5 14 sites).
Altitude Slope Number of woody Maximum DBH Maximum DBH ofplant species of conifers broad-leaved trees
Species richness indicesmsNumber of species 20.036 20.217 0.268 0.430* 0.380
msMargalef index 0.265 20.061 0.156 0.380 0.420*MDS site scoresFirst dimension 20.219 0.012 0.045 20.313 20.508*
msSecond dimension 20.357 0.209 20.022 20.067 0.331ms*P , 0.05; 0.05,P , 0.1.
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Figure 5. Cluster analysis of the longicorn beetle assemblages from 1998 to 1999. For site abbreviations,see Figure 1. Boldfaced letters and italic letters indicate the samples of 1998 and 1999, respectively.
Species richness
The number of longicorn beetle species rose as the number of individuals collectedincreased (Figure 3a; t 5 0.412, n 5 14, P , 0.05). It was not significantlydifferent among forest types, whereas the median value was largest in old-growthforests (Table 3). The Margalef index was independent of the number of individuals(Figure 3b; t 5 20.121, n 5 14, P . 0.5). It was significantly different amongforest types, and the median value decreased from old-growth forests to second-growth forests to conifer plantations (Table 3). Neither value was significantlydifferent among directions (Kruskal–Wallis test; H 5 1.36, P . 0.5, for the numberof species; H 5 0.79, P . 0.5, for the Margalef index). While not correlated withaltitude, slope or the number of woody plant species, they were positively correlatedwith the maximum DBH of conifers and broad-leaved trees, either significantly ormarginally (Table 4). Figure 4 shows the relationship of the Margalef index to thenumber of woody plant species, and to the maximum DBH of broad-leaved trees.
Site ordination
As shown in the dendrogram in Figure 5, the longicorn beetle samples of 1998 and1999 collected at every site (A, C–F) were close to each other, indicating that thebeetle assemblages were stable and did not change considerably from 1998 to 1999.
Figure 6 shows the final two-dimensional configuration of study sites by MDSbased on the rank correlation coefficients between them calculated from the samplesof 1998. The site score for the first dimension was significantly different amongforest types, while the score for the second dimension was not (Table 3). The former
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Figure 6. Two-dimensional ordination of study sites by the MDS based on the degree of similaritybetween each pair of sites measured by means of the rank correlation coefficient (Kendall’s tau, t) on theabundance of longicorn beetle species collected in 1998. For site abbreviations, see Figure 1.
Figure 7. Relationships between the site score on the first MDS dimension and the maximum DBH ofbroad-leaved trees (a), and between that on the second MDS dimension and altitude (b) (cf. Table 4). Forforest type symbols, see Figure 1.
increased from old-growth forests to second-growth forests to conifer plantations(Figure 6). The site score for the first dimension was significantly correlated withthe maximum DBH of broad-leaved trees, whereas the score for the seconddimension was marginally correlated with altitude (Table 4, Figure 7). The sitescores were not different among directions (Kruskal–Wallis test; H 5 0.99, P . 0.5,for the first dimension; H 5 4.61, P . 0.2, for the second dimension). Neither were
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Figure 8. Number of longicorn beetle species collected in 1998 in relation to the site score on the firstMDS dimension.
they correlated with the slope, the number of woody plants and the maximum DBHof conifers (Table 4).
Table 6 shows the rank correlation coefficients between the abundance and theMDS site scores for 40 species collected at three or more sites. Negative correlationwith the site score for the first dimension was significant in 12 species, including sixspecies of the genus Pidonia. This shows that they are specific to or closelyassociated with old-growth forests. On the other hand, positive correlation wassignificant in four species, e.g. Parastrangalis spp., suggesting that they are absentor uncommon in old-growth forests. For the other 24 species, no significantcorrelation with the site score was shown for the first dimension. Three speciesshowed a positive correlation with the site score for the second MDS dimension,which was somewhat correlated with altitude (Table 4).
For all eight species of Pidonia listed in Table 5, the correlation between theabundance and the site score for the first MDS dimension was negative if notsignificant at the 5% level. Eleven species of Pidonia, including three infrequentspecies (P. yamato, P. neglecta, P. chujoi), were collected in 1998. The number ofPidonia species was highly and negatively correlated with the site score for the firstMDS dimension (Figure 8; t 5 20.716, n 5 14, P , 0.001), although the numberof the other species was not correlated with it (Figure 8; t 5 0.012, n 5 14, P .
0.5). Also the number of Pidonia species was significantly different among threeforest types (Kruskal–Wallis test; H 5 6.65, P , 0.05).
Species indicator values
Species indicator values (IndVal) were computed for 40 species collected at three ormore sites in 1998. The values over 40% are shown in Table 5. Large IndVal forold-growth forests were indicated in Dinoptera minuta, many Pidonia species, andPseudalosterna misella. Many species, including Parastrangalia spp., exhibited
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Table 5. Rank correlation coefficient (t) between the number of individuals and the site scores in theMDS ordination (n 5 14 sites) for the species collected at three or more sites in 1998, and the speciesindicator value (IndVal .40%) for the species.
Family or Correlation coefficient IndVal Total number ofsubfamily species (t) between abundance (%) individuals / sites of
aand MDS site score occurrence
First Second Old-growth Second-growth Coniferdimension dimension forests forests plantations
(7 sites) (5 sites) (2 sites)
DisteniidaeD. gracilis 20.42* 0.13 42.9 3/3PrioninaePsephactus remiger 0.04 0.01 8/5 8/3 3 /1LepturinaeLemula japonica 0.02 0.37 3/2 1/1Di. minuta 20.66** 20.17 57.1 4/4Pidonia mutata 20.54** 20.01 54.3 49/5 11/2P. signifera 20.46* 0.04 48.6 8/4 1/1P. grallatrix 20.51* 0.31 83.0* 43/6 1/1P. aegrota 20.45* 0.22 47.8 30/6 12/3 2/1P. puziloi 20.64** 20.06 92.2* 422/7 18/3 3/1P. approximata 20.38 0.36 56.5 23/6 6/3 1/1P. amentata 20.12 0.53** 19/3 2/1P. simillima 20.76** 20.09 82.3* 34/6 1/1Ps. misella 20.44* 0.23 71.4* 12/5Anoploderomorpha excavata 20.49* 0.24 42.9 3/3Anastrangalia sequensi 0.19 0.27 4/2 3/2 2 /1Leptura ochraceofasciata 0.15 20.02 70.8* 86/6 86/5 143/2Parastrangalis lesnei 0.43* 20.34 62.5 3/2 2/2Pa. shikokensis 0.62** 0.05 90.9** 1/1 4/2Idiostrangalia contracta 0.43* 20.11 81.4* 1/1 1/1 3/2CerambycinaeAllotraeus sphaerioninus 20.41* 0.00 18/5 6/3 5/1Stenodryas clavigera 20.08 20.03 17/3 25/3 2/1Ceresium holophaeum 20.02 0.41* 4/2 1/1Cleomenes takiguchii 0.04 0.19 4/3 2/2Chloridolum viride 20.37 0.40* 42.5 58/4 11/2Callidiellum rufipenne 0.44* 20.02 93.3* 1/1 4/2Xylotrechus emaciatus 0.11 20.24 6/4 2/2 5 /1X. pyrrhoderus 20.07 0.31 6/3 5/2X. cuneipennis 0.12 20.31 5/4 3/3 4 /1X. grayii 0.19 0.09 70.0* 3/1 2/2Demonax transilis 0.16 0.05 80.6* 5612/7 4118/5 13488/2LamiinaeAsaperda rufipes 20.03 0.36 48.3 42/6 35/5 3/1Pterolophia tsurugiana 20.48* 20.34 42.9 4/3Acalolepta fraudatrix 0.06 20.04 61.7* 13/6 19/5 1/1A. sejuncta 20.12 20.35 9/4 7/4 1 /1Uraecha bimaculata 20.26 0.28 190/7 111/5 38/2Xenicotela pardalina 0.07 0.27 4/3 3/3Rhodopina integripennis 20.30 20.13 5/4 2/2Pareutetrapha simulans 0.21 0.08 4/1 2/2 1 /1Praolia citrinipes 20.36 0.13 62.9 31/5 3/2Glenea relicta 20.31 0.16 2/2 1/1aBoldfaced numbers show the data set for the IndVal. *P , 0.05; **P , 0.01.
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Table 6. Host condition, larval host tissue and host trees for the indicator species with IndVal.
Host Larval host Hosta bcondition tissue trees
Indicator species for old-growth forestsD. gracilis Dying or humid dead tree IB/SW BL/CDi. minuta Dead twig BLP. mutataP. signifera Dead branch IB BLP. grallatrix BLP. aegrota Humid dead tree and branch IB BLP. puziloiP. approximataP. simillima Dead branch IB BLPs. misella Standing tree IB/SW/R BLAn. excavata Dead tree BLCh. viride Dead branch W BL/CPt. tsurugiana Dead branch IB/SW BLPr. citrinipes Dead tree and branch BLIndicator species for second-growth forestsAs. rufipes Dead twig W BLAc. fraudatrix Dead tree and branch IB/W BL/CIndicator species for conifer plantationsL. ochraceofasciata Dead tree W C/BLPa. lesnei Dried dead branch IB/SW C/BLPa. shikokensis Dead tree BLI. contracta Dead vine BLCa. rufipenne Dead or dying tree IB/SW CX. grayii Dead tree BLDe. transilis Dead tree and branch W BL/C
aData sources are Kiyosawa et al. (1981), Kojima and Nakamura (1986), Kuboki (1987). IB – inner bark;bSW – sap wood; W – wood; R – root. BL – broad-leaved tree; C – conifer.
high indicator values for conifer plantations. Acalolepta fraudatrix was alsocharacteristic of second-growth forests. The results of the IndVal approach agreedessentially with those from the MDS ordination analyses. According to literature(Kiyosawa et al. 1981; Kojima and Nakamura 1986; Kuboki 1987), host condition,larval host tissue and host trees for the indicator species with IndVal .40% arecompiled in Table 6.
Discussion
Limitations of trap sampling
As previously reported by Ikeda et al. (1993), Shibata et al. (1996) and Sakakibaraet al (1997a, b, 1998), the white collision trap baited with benzyl acetate to mimicwild flowers is efficient for collecting flower-visiting species of the subfamiliesLepturinae and Cerambycinae. On the other hand, the species without flower-
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visiting habits (Lamiinae, Prioninae and Spondylinae) are probably lured to ethylalcohol (Ikeda et al. 1980; Shibata et al. 1996; Sakakibara et al. 1997a). Whileyellow traps are generally less attractive than white traps, certain species (e.g.Disteniidae) have been largely collected in them (Sakakibara et al. 1997a). Thus, thetaxonomic bias observed in our trap sampling is fundamentally consistent with theseprevious reports. The present combination of white and yellow collision traps baitedwith benzyl acetate and ethyl alcohol appears to be useful for sampling diverselongicorn beetles, although the collection is rather poor for non-flower-visitingspecies.
Although the attractant traps lure the longicorn beetles moving just around them(T. Ikeda, personal communication), they can catch those that fly from adjacentstands as in other sampling methods. For example, adults of a lepturine species(Anaglyptus subfasciatus) were caught in the traps located at a distance of 30–50 mfrom the stands of emergence (Makihara 1992). Thus, the results may be biased bythe contamination with strong-flying species from other habitat types, especiallywhen the sampling site is small in area. However, such biases would be not seriousbecause our results show distinctive ordination of sampling sites corresponding toforest types.
Malaise traps are also useful for the investigation of beetle assemblages (Maetoand Makihara 1999). They can catch more non-flower-visiting species than thecollision traps with attractants, but they cost much more to operate than do collisiontraps. To compare beetle assemblages among many sites at a time, collision trapswith attractants would be more practical than Malaise traps.
Although abundance data obtained from attractive traps are not direct measures ofreal abundance of each species, the rank of abundance might change with thealternation of species between sampling sites. Therefore, we used the rank correla-tion coefficient (Kendall’s t) as the similarity measure between assemblages (Ghent1963). According to Huhta (1979), it is one of the best indices to measure thespecies alternation of spiders and beetles in succession after clear-cutting. Ourresults demonstrate that site ordination by MDS based on rank correlation co-efficients is practical for analyzing the changes in insect assemblage using abun-dance data obtained from attractant traps.
It is generally known that some herbivorous insects (moths, sawflies, bark beetles,etc.) exhibit wide density fluctuations over years (e.g. Varley et al. 1973). If therelative abundance of species varies greatly between years, 1-year sampling wouldbe insufficient to identify any indicator species being characteristic of certain habitattypes. However, the assemblages of longicorn beetles collected in two consecutiveyears (1998 and 1999) were very close to each other for every site, so that thegeneral pattern of the beetle assemblages may be discussed based on a single yearsampling.
Decline of species richness
An obvious decrease in the Margalef index, the number of species adjusted for thenumber of individuals, indicates that the conversion of old-growth forests into
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second-growth forests and conifer plantations has diminished the species richness oflongicorn beetles. Shibata et al. (1996) mentioned that the number of longicornbeetle species tended to increase in proportion to the number of woody plantspecies. However, except for a cool-temperate beech forest, no correlation wasshown between the number of beetle species and that of woody plant species in thewarm-temperate forests in their study (Figure 3 of Shibata et al. 1996). This agreeswith our results, and it is not likely that forest conversion has reduced the speciesrichness of longicorn beetles through the decrease of woody plant species.
Our study suggests that the species richness of longicorn beetles increases withthe maximum diameter of trees. However, it is not surprising that old-growth forestshave large trees. Further examination will require more information about thebiology and natural history of the species closely associated with old-growth forests.
Ecological requirements and functions of the old-growth forest species
It was proved by the MDS ordination that the longicorn beetle assemblages ofold-growth forests were distinct from those of conifer plantations, while those ofsecond-growth forests were intermediate between them. Further analysis showedthat 12 species were specific to or closely associated with old-growth forests. Of the12 species, six belong to the genus Pidonia of the subfamily Lepturinae. Further-more, the total number of Pidonia species has definitely increased in old-growthforests along the first MDS dimension. These findings indicate that most species ofPidonia require some ecological conditions particular to old-growth forests, andwere supported by the results from the indicator value (IndVal) approach.
While it is widely distributed in the Holarctic Region, Pidonia is most highlydiversified in humid temperate forests of East Asia (Kuboki 1981). Larvae oflongicorn beetles feed on various parts (wood, sapwood or inner bark of trunks,branches or roots) of woody plants in different conditions (decaying, dying or barelyliving) (Hanks 1999). As shown in Table 6, specialization to inner bark is a peculiarhabit of Pidonia (Kuboki 1987). The larvae of this genus are found under the thickbark of comparatively large, dead or living, trees and branches of various broad-leaved species (Aceraceae, Araliaceae, Betulaceae, Cercidiphyllaceae, Fagaceae,Rosaceae, Salicaceae) or, rarely, conifers (Pinaceae) (Kiyosawa et al. 1981; Kojimaand Nakamura 1986; Kuboki 1987). They pupate under the bark (never in wood) ordrop into humus for pupation. The humidity is unstable under thin bark, andprobably so they need thick bark under which they spend 1 or 2 years for growingup. On the other hand, a thick, stable and moist humus layer of old-growth forestsmay be also crucial to the larvae and pupae of Pidonia, which often live in humus orunder the bark of fallen logs lying on the forest floor (Kuboki 1987).
An additional species associated with old-growth forests, Distenia gracilis, alsoprefers dead humid logs with thick bark to dried logs, having a small preference toparticular tree species (Kiyosawa et al. 1981). Another species, Ps. misella, isknown as a bark or root borer of standing trees of Salicaceae (Ohbayashi et al.1992).
Therefore, it is most likely that the presence of large, dead or living, broad-leaved
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trees with thick bark is essential for the longicorn beetles that depend on warm-temperate old-growth forests. This is not inconsistent with our finding that the beetleassemblages change with the increase of the trunk size of broad-leaved trees. We didnot measure the volume and size of dead wood, while both the size of trees andamount of dead wood usually increase together with forest age (e.g. Spetich et al.1999; Siitonen et al. 2000).
In addition to decomposing woody materials by the larvae, Pidonia and otherlepturine beetles may be playing an important role in pollinating herbaceous andwoody plants, since they are the most dominant beetles visiting wild flowers intemperate forests (Kato et al. 1990; Sakakibara et al. 1997b). According to Kubokiand Shimamoto (1979) and Kuboki (1980), Pidonia species have been found onwild flowers of more than 15 families (e.g. Saxifragaceae, Rosaceae, Umbelliferae,Caprifoliaceae). Moreover, some species-specific relationships have been observedbetween Pidonia and flowers (Kuboki 1980). It must be noted that the old-growthforest beetles, depending on large full-grown trees, will support the reproductionand genetic diversity of other plant species. They might also be major prey forpredatory insects, spiders and birds visiting wild flowers during late spring and earlysummer. At any rate, further investigations are necessary to understand effects of thedecline in insect diversity of old-growth forests upon the forest ecosystem.
Implications for the management of forest landscape
Conversion of old-growth forests into young forests results in considerable changesin the diversity of various arthropod guilds, e.g., canopy arthropods (Schowalter
¨1989), ground beetles (Niemela et al. 1993), and xeric insects (Lattin 1993), butthere is general agreement that saproxylic arthropods, depending on large pieces ofdead wood, are most threatened by the long-term reduction of temperate old-growthforests (e.g. Warren and Key 1991; Lattin 1993; Maeto and Makihara 1999;Martikainen et al. 2000; Thunes et al. 2000). While the larvae occasionally bore intoliving tress, Pidonia species are also saproxylic in a broad sense since they dependon large woody materials that are dead or dying.
To enhance the diversity of saproxylic insects, extended rotation as well asleaving old trees, snags and dead wood in clear-cuts is recommended (Hansen et al.1991; Martikainen et al. 2000). Our results suggest that size increase of living, andthus dead or dying broad-leaved trees will augment the diversity of old-growthforest beetles like Pidonia. Extended rotation or postponement of cutting is no doubtmost important to increase large trees in second-growth forests, and thinning may bealso effective in accelerating the growth of remaining trees. Thinning in second-growth forests and plantations should be recommended since it also enhances thediversity of ground insects (Magura et al. 2000) as well as woody and herbaceousplants. After thinning, felled trees should be retained in the forests to be lateravailable for saproxylic species. As suggested by Siitonen et al. (2000), it would bethe most efficient short-term management strategy for the increase of structuraldiversity and old-growth attributes in managed forests to retain the old-growth
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characteristics (i.e. large living trees, snags and logs) that already exist in maturestands.
In southwestern Japan, old-growth forests of the warm-temperate zone have beenseriously fragmented due to traditional agriculture and coppicing as well as recentrapid plantation with conifers (e.g. Shidei 1974; Sasse 1998). On Shikoku Island,only a dozen small remnants of old-growth forests (each at most 300 ha) are found inlowlands and hills up to about 1000 m in elevation, and conifer plantations andyoung second-growth forests distantly separate them. For the conservation ofregional forest biodiversity, restoration of old forests from young second-growth orman-made forests surrounding old-growth remnants is necessary to secure thehabitat area of old-growth forest species. It is also essential to re-establish a belt orstepping-stones of old second-growth forests connecting old-growth remnantswithin the region. Pidonia and other longicorn beetles closely associated withold-growth forests, which can be easily monitored with simple traps, may bevaluable indicators for the progress of such forest restoration.
Acknowledgements
We would like to thank Ryuichi Tabuchi, Takeshi Sakai, Shigeo Kuramoto andAtsushi Sakai for the survey of site vegetation. Our thanks are also due to ToshihikoYamasaki for his help in the field, Tsuyoshi Yamada for showing us meteorologicaldata at Yusuhara, and Mariko Takeuchi for the preparation of insect specimens. Wealso thank Shikoku Regional Forest Office, Kochi Prefecture and Yusuhara Townfor the permission to do field work in their forests. This work was partly funded bythe International Collaborative Research Programme of the Ministry of Agriculture,Forestry and Fisheries.
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