179

An Adaptive Management Scheme for Wetland Restoration
Incorporating Participatory Monitoring into Scientific Predictions
Using Dragonflies as an Indicator Taxon
Taku KADOYA* and Izumi WASHITANI
Institute of Agriculture and Life Science, The University of Tokyo,
1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-8657, Japane-mail: kadoya@e-mail.jp*corresponding author

Abstract
Here we propose an adaptive management scheme for wetland restoration using data collected by citizens to make scientific predictions. We assessed the potential advantages of such a scheme using a wetland
restoration project conducted in a small floodplain area along the Matsu-ura River in Kyushu, Japan. For thecase study, we compiled data provided by amateur naturalists on distribution patterns of dragonflies on the
eco-regional scale, as well as ecological characteristics such as behavior and habitat preferences. Based on
this information, we predicted a species recovery trajectory at the wetland restoration site. By monitoring
species recovery to test our prediction, we demonstrated that colonization by dragonfly species at the restored site could be predicted using species prevalence on the regional scale based on the nestedness rule.
The data collected by the amateur naturalists were critical in making this prediction, which highlights theimportance of citizen participation in the proposed scheme.
Key words: agricultural ecosystem, assembly rule, immigration potential, Odonata, participation,satoyama

1. An Adaptive Framework for Restoration
Programs
Rapid biodiversity loss is occurring on global, regional and local scales, and biodiversity conservation isan urgent international issue. For example, the 2002
World Summit on Sustainable Development (WSSD)
endorsed the Hague Ministerial Declaration of the 6th
Conference of the Parties to the Convention of Biological Diversity (CBD) in its Plan of Implementation.
Specifically, its mandate was “to achieve by 2010 a
significant reduction of the current rate of biodiversity
loss at the global, regional and national levels as acontribution to poverty alleviation and to the benefit of
all life on earth” (United Nations, 2002). In addition, the
3rd National Biodiversity Strategy of Japan, which wasapproved in 2007 based on the CBD’s provisions, aims
to “reinforce the protected-area system, expand thedesignation of protected areas, improve conservationand management activities based on scientific data” and“promote the restoration of nature by having humanbeings assist with natural restoration processes throughlaunching of nature restoration projects” to prevent speGlobal Environmental Research
11: 179-185 (2007)
printed in Japancies extinction and conserve biodiversity (Ministry of
the Environment of Japan, 2007). Ecological restoration,
defined as the process of assisting the recovery andmanagement of ecological integrity (Society for Ecological Restoration International, 2004), is a fundamental and effective approach to preventing the loss of
biodiversity and to achieving progress toward the
CBD’s objective, especially for ecosystems that havebeen severely damaged.
The early establishment of a guiding image based onan understanding of the dynamic nature of ecosystems isthought to be the most critical aspect of successful
ecological restoration projects (Gillilan et al., 2005;
Palmer et al., 2005). The guiding image, which must be
shared by all project participants, should stand on soundscientific predictions (Halle & Fattorini, 2004). This will
help with the quantitative and/or qualitative evaluationof the results of restoration actions to create an ongoing
feedback loop, which will ultimately improve the understanding of ecosystems and subsequent predictions. This
process, called “adaptive management,” assumes thatscientific knowledge is provisional, and focuses on management as a learning process or continuous experimentthat incorporates the results of actions, thereby allowing©2007 AIRIES180

T. KADOYA and I. WASHITANI

managers to remain flexible and adapt to uncertainty(Grumbine, 1994).
In the face of limited funding, knowledge and time,
predictions often rely on shortcuts, or indicators, for thecreation of biodiversity maintenance plans. Indicators
are measurable surrogates for environmental endpoints
such as biodiversity conservation that are assumed to beof value to the public (Niemi & McDonald, 2004).
Selecting appropriate indicator species that satisfy scientific (ecological) needs as well as public interests (e.g.,charismatic species) is important for facilitating citizen
participation in restoration programs and for stimulating
meaningful interactions between scientists and citizens.
An enormous amount of ecological data with related
mechanistic understanding is needed to make reliablepredictions. To predict species colonization potential, forexample, which is fundamental for designing restorationplans (Keddy, 1999; Campbell et al., 2003; Srivastava,2005), data concerning species distribution, abundance,and ecological characteristics including dispersal ability,
tolerance and habitat preference are required. Ecological
data for various popular species are often available indeveloped countries such as Japan, which has many active amateur naturalists. However, this information isoften random or inconsistent with respect to temporaland spatial scales.

many restoration projects in Japan aim to restore theaquatic habitats that were once maintained in the traditional agricultural landscape and floodplain wetlands(Washitani, 2003a; Yoshimura et al., 2005).
Dragonflies (Odonata) are one of the major taxa that
inhabit aquatic ecosystems. They have been used asindicators of the ecological quality of land-water
ecotones, aquatic habitat heterogeneity (e.g., bankmorphology and aquatic vegetation), and the hydrological dynamics of water bodies (e.g., Clark & Samways,
1996; Chovanec & Waringer, 2001; D’Amico et al.,2004). In Japan, dragonflies constitute one of the major
taxa inhabiting the aquatic habitat networks maintainedin the satoyama landscape (Sugimura et al., 1999). In
addition, the Japanese people are particularly fond of
this insect group (Primack et al., 2000). The distribution
patterns and ecological characteristics such as behavior
and habitat preferences of approximately 200 resident
dragonfly species have been well described by a numberof professional and amateur dragonfly enthusiasts (e.g.,
Sugimura et al., 1999). Therefore, dragonflies exhibit
the ideal features of an indicator taxon for aquatic
ecosystems in the satoyama landscape of Japan.

2. Dragonflies as an Indicator Taxon for
Traditional Agricultural Ecosystems inJapan

An adaptive scheme for ecological restoration consists of three stages: (1) data collection, (2) prediction,and (3) examination and feedback (Fig. 1). Public
participation plays an important role at the data collection stage. Stimulating relationships between scientists
and citizens should be encouraged for the cyclic prediction and monitoring processes of an adaptive management plan. A rational approach to any of the stages inthe scheme depends on the outcome of other activities
and, in practice, a stage may have to be repeated if feedback from other stages indicates that changes areneeded.

The satoyama, a traditional rural agricultural ecosystem that was common before the rapid development andmodernization of Japanese communities, consisted of amosaic of patches of forests, grasslands, paddies, ponds,
and creeks supplying various resources to support traditional agriculture and village life (Washitani, 2001;
Kobori & Primack, 2003). In the satoyama, the landscape mosaic maintained by human disturbance for agricultural purposes provided a variety of habitats for wild
animals and plants, and contributed to high inter-habitat
diversity (Washitani, 2003b). In particular, the aquatic
habitat complex consisting of a network of paddy fields,
ponds, and creeks connected to adjacent rivers or
streams provided various habitats for a number ofaquatic organisms including plants, invertebrates, fish
and amphibians (e.g., Mukai et al., 2005; Takeda et al.,2006).
The abandonment of satoyama ecosystems, whichlost their instrumental value as a result of the fuelrevolution and the popularization of chemical fertilizers,
and their destruction due to regional development projects during periods of rapid growth and the “bubble
economy,” resulted in the loss of various habitat types
constituting traditional rural landscapes (Fukamachi
et al., 2001). This caused serious threats to many aquaticorganisms including those that were among the mostfamiliar to people several decades ago (Washitani, 2001;
Ministry of the Environment of Japan, 2007). As a result,

3. Scientific Processes and Participation with
Respect to Indicator Species

Immigration
potential

Species pool

Prediction

Filters
Isolation
Abiotic
BioticRestoredassemblages

Compiling data
provided byamateur naturalists

Distribution
database

Assemblyrules

Participatory
monitoring

Life history
data

UpdateFig. 1 Structure of a scheme for restoration projects using thecooperation of volunteers. The framework is a set of
linked activities carried out by scientists and citizens
consisting of three stages: (1) data collection,(2) prediction, and (3) examination and feedback.

Adaptive Scheme for Wetland Restoration

3.1 Defining the guiding image with indicatorspecies in scientific terms
For ecological restoration to be successful, the guiding image of a restoration project should be defined
primarily based on the scientific predictions of thecolonizing potential of indicator species (Keddy, 1999;
Campbell et al., 2003; Srivastava, 2005). Although thecolonization by a species is the outcome of complex
interactions among spatio-temporal processes, we canquantify the colonizing potential of a species to predict:(1) how likely the species is to reach the restored sitefrom the regional species pool (i.e., the immigration
potential of the species), and (2) whether the species
will be able to establish itself at the site by interactingwith other species (i.e., the establishment potential of
the species). However, some dispersal-limited species
including plants may require physical introduction to therestored site to facilitate the immigration process and therecovery of their populations, and thus of the target
ecosystem. On the other hand, in the case of species
with greater dispersal abilities, a project should beplanned to take advantage of their natural immigrationfrom the existing species pool to restore self-sustaining
populations.
3.2 Evaluation of the regional sources ofimmigrating species
A species’ potential to reach the restoration site involves spatial processes, and to predict the immigration
potential of a species, we must understand how different
spatial levels, such as the regional species pool and theassemblage at the local restored site, are connected by
the dispersal of the species. In general, the immigration
potential of a given species is defined as its expectedease of immigration to a habitat. This can be predictedfrom landscape connectivity, which is defined as “thedegree to which the landscape facilitates or impedes
movement among resource patches” (Taylor et al.,1993), as well as the source size at the meta-level (i.e.,
the regional species pool). Landscape connectivity canbe assessed using the data regarding the landscape structure around the restored site including the spatialconfiguration of habitats, dispersal ability, and behaviorof the species (Taylor et al., 2006). In addition, dataarchived in distributional databases of wildlife records
collected by amateur naturalists at eco-regional scales
can be used to evaluate the source size of the regional
species pool of some major species, including dragonflies in Japan.
3.3 Evaluating species selection throughenvironmental filters
Once a species has reached the restored site, whether
it can become established at the site depends on the concerted operation of biotic and abiotic environmental filters, as well as a list of species traits that determine
whether the species can persist through the filters(Temperton & Hobbs, 2004). Specification of the assembly rules, namely, the identification of the fundamental

181

filters and species traits interacting to govern the target
community, is thus one of the most important tasks ofthe predictions in the establishment stage (Keddy, 1999).
The life history data for species archived by amateur
naturalists can be of great help for this purpose.
Most assembly models assume a static species poolfrom which potential colonizers are drawn (Aviron et al.,2005). All members of this pool have equal access to thecommunity in the sense that they all attempt to invade
an approximately equal number of times and are seeded
into the community at the same initial population densities. Therefore, as described above, consideration ofboth immigration potential and assembly rules is fundamental at the scientific prediction stage.
3.4 Data compilation and updates throughmonitoring
In the adaptive approach to ecological restoration,
predictions based on data collected at the appropriate
spatial scales should be tested through the implementation of the restoration projects. This would create feedback to the prediction stage and would therefore provide
powerful tests of the ecological models used for thepredictions. This would ultimately provide information
as to whether the model assumptions were correct andhow far the scientists have come in the understanding of
nature.
The outcome of the monitoring would also directly
and/or indirectly provide feedback on the amateur
naturalist data. Therefore, the information collectedshould be used to update the data, so that the outcome of
the monitoring could encourage improvements to thedata collection methods used by volunteer citizens. In
particular, given the need to estimate the source size of a
species accurately, the establishment of a citizen-driven
systematic data collecting system may be useful or evenrequired in order to archive more precise distributional
records of the target species on the eco-regional scale.
These processes will benefit researchers as well as
citizens participating in ecological restoration projects
because their activities are tightly linked to a sociallyrelevant task, namely conserving biodiversity. In addition, the citizens participating in the project will enjoy asense of satisfaction brought about by the restoredbiodiversity, and may therefore improve their quality oflife through such activities. The formation of stimulatinginteractions between citizens and researchers will facilitate further data accumulation for scientific predictions
in subsequent restoration projects and the establishmentof long-term monitoring, which is otherwise often difficult to carry out.

4. A Case Study: Azame Wetland Restoration
Project in Japan
We assessed the potential advantages of a scheme
combining data collected by citizens and scientificpredictions in an adaptive framework using a wetland
restoration project conducted in a small part of the182

T. KADOYA and I. WASHITANI

floodplains of the Matsu-ura River in Kyushu, Japan, asa case study (Kadoya et al., in press). Specifically, we
compiled data on the distributional patterns of dragonfly
species on the eco-regional scale as well as ecologicalcharacteristics such as behavior and habitat use. These
data were provided by amateur naturalists, and based on
this information, we predicted the species recovery
trajectory at the wetland restoration site. We then tested
our prediction by monitoring species recovery at therestoration site.
The Matsu-ura River is one of the largest rivers on
Kyushu Island, with a catchment area of approximately
446 km2 and an annual average discharge of about
12.46 m3/s. The Azame restoration area (33º20’N,
129º59’E; 6 ha) is located in the old floodplain in the
middle reaches of the Matsu-ura River, approximately
15.8 km from the mouth of the river, and was farmed as
rice paddies until 2001. Prior to the restoration, theground level of the Azame area was approximately 5 m
above the normal water level of the river because of the
deeply incised main channel, the aggraded floodplain,
and regulation of the river’s flow path by embankments.
Consequently, the connectivity and ecotones between
the habitats of aquatic organisms had been entirely lost.
Therefore, the restoration project prioritized solutions
that would eliminate this lack of connectivity and create
ecotones from the river to the study site by lowering theaggraded site and partially removing the embankments(Fig. 2).
As a second step, restoration of agricultural aquatic
habitats maintained by traditional forms of agriculture,including paddy fields, marshes, ponds and creeks connected to the river, was started in 2005. The projectrequired frequent meetings of the planning group andcontinuous monitoring of the effects of the restoration.
Active participation of the local people and a nongovernmental organization through discussions held
every month with a governmental office (Takeo Officeof Rivers, Ministry of Land, Infrastructure and Transport of Japan) played an important role in the planning.
4.1 Data compilation and evaluation of the source
size on the eco-regional scale
Dragonflies are an insect group with relatively highdispersal capabilities that enable them to colonize even
newly restored aquatic environments. Therefore, westarted with an evaluation of the source size of dragonfly species on the eco-regional scale to predict the species immigration potential based on the collected data.
Specifically, data on the distributional pattern of dragonfly species in northern Kyushu were obtained from thenational database on wildlife distribution archived byamateur naturalists (Environment Agency of Japan,
2000). The database included records of the occurrence

1a

1b

1c

2a

2b

2c

3a

3b

3c

4a

4b

4c

Fig. 2 Habitat types at the Azame restoration site (1a-c) and in nearby
habitats (3a-c). At the restoration site, colonizer species such as
Crocothemis servilia mariannae (2a), Orthetrum albistylum speciosum(2b), and Ischnura senegalensis (2c), all of which prefer temporary
pools, were frequently observed. In the nearby habitats, we observed
species that require abundant aquatic vegetation in their habitat, suchas Libellula quadrimaculata asahinai (4a) and Platycnemis foliacea
sasakii (4b), and species that inhabit open marshes, such as
Sarasaeschna pryeri (4c).

Adaptive Scheme for Wetland Restorationof every species on a grid with a cell size of 5’ latitude
by 7’30’’longitude (about 10 km × 10 km) that covers
all of Japan. We used the species occurrence data from
320 grid cells in northern Kyushu, which covers one of
the eco-regions of dragonflies in Japan (Sugimura et al.,1999). Based on the database, we calculated the order ofprevalence on the regional scale for each species as anindex of source size on the regional scale (for details see
Kadoya et al., in press).
4.2 Specification of assembly rules of dragonfly
species
Previous studies (Sahlen & Ekestybbe, 2001;
Kadoya et al., 2004) as well as existing natural history
knowledge have indicated that the distribution of
dragonfly species within a community is strongly“nested;” that is, prevalent species are found everywhere,
whereas rare species tend to occur only at the richestsites (Patterson & Atmar, 1986). Therefore, we assumed
that immigration by dragonflies to the restored sitewould be governed mainly by the nestedness rule.
We tested the nestedness of the distributional patternof dragonfly species using the species database. Amongthe 320 grid cells, 154 grid cells contained at least one
species, and the presence of 91 species had been recorded in the database. As expected, the presence–absence matrix for the 91 species recorded innorthern Kyushu represented a significantly nested
distribution (T = 12.4°, p < 0.0001; Fig. 3).
The nested distribution of dragonfly species indicated a positive correlation between immigration potential and habitat tolerance. That is, prevalent species with
G1

higher immigration potential tended to exhibit a wider
habitat preference whereas rare species with lower
immigration potential tended to have narrower habitat
preferences. We therefore expected that the colonizationof dragonflies to a restored site could be predicted simply from the source size (i.e., prevalence) on the regional scale. Testing this prediction required monitoringof the colonization by dragonfly species at the restoration site and analyzing the relationships between thespecies prevalence on the regional scale and species
occurrence at the site.
4.3 Prediction testing by monitoring
We conducted a census of adult dragonflies from2003 to 2005 at the restoration site. The restoration site
was rather new for the assessment of the colonization bya species. To compensate for this, we also conducted acensus of species occurrences in nearby habitats (Fig. 2).
We recorded 17 and 52 species at the restoration site andin the nearby habitats, respectively. All of these species
had been previously recorded in the regional database.
We excluded some non-target species from the analysis(for details see Kadoya et al., in press). Consequently,
we analyzed 15 and 50 species observed at the restoration site and in the nearby habitats, respectively. An
analysis using logistic regression revealed that the probability of occurrence of restoration-site species decreased significantly with decreasing species prevalence(Fig. 4b). A similar relationship was detected in the
nearby habitats (Fig. 4a). These data support the prediction that colonization of the restored site by dragonfly
species can be predicted from their prevalence on theregional scale.

Grid cells

Probability of occurrence

1

G154

S1

S91

SpeciesFig. 3 Nested distribution of 91 dragonfly species in
154 grid cells in northern Kyushu. Each shadedsquare represents the presence of a species in agrid cell. The 91 species were ordered to maximize the nestedness of the matrix on the basisof the algorithm proposed by RodriguezGirones and Santamaria (2006). The degree ofnestedness in the matrix was examined using arandomization test (n = 5,000, Monte Carlosimulations) with the binary matrix nestedness
temperature calculator of Rodriguez-Girones
and Santamaria (2006), and significant nestedness (T＝12.4°, p < 0.0001) was detected(modified from Kadoya et al., in press).

183

0
1

0

0

a

Nearby-habitat
speciesb

Restoration-site
species

10

20

30

40

50

60

70

80

90

Rank order of prevalenceFig. 4 Probability of occurrence of dragonfly species(a) observed in nearby habitats and (b) at the restoration site based on logistic regression models
using the rank order of prevalence of the species
as an explanatory variable. Binary numbers wereassigned to each species based on presence/
absence, and the number was plotted with a line
representing the occurrence probabilities estimated by the logistic regression (nearby habitats:likelihood ratio test, p < 0.0001; restoration site:
likelihood ratio test, p < 0.001); modified from
Kadoya et al., in press).

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T. KADOYA and I. WASHITANI

5. Scientific Predictions Combined with
Participatory Monitoring
Our case study demonstrated that species colonization could be predicted using species prevalence on aregional scale based on the nestedness rule. Although
long-term monitoring at the local restoration site is aremaining task for the project, the study showed thatdata archived by amateur naturalists are critical in theprediction of species colonization, and thus highlights
the importance of the proposed scheme that incorporates
data collected by citizens into an adaptive framework of
ecological restoration. Once species colonization becomes predictable, we can specify the recovery trajectory of a given species and can adaptively improve theproject design for the subsequent microhabitat restoration of species that are expected to colonize a site. A
credible prediction of species colonization also enables
us to quantitatively assess the success of restoration bymonitoring the extent of colonization at the site in orderof prevalence on the eco-regional scale.
Cultivated systems (areas where at least 30% of thelandscape are croplands or are used for shifting cultivation, livestock production or freshwater aquaculture)
now cover one-quarter of the Earth’s terrestrial surface(Millennium Ecosystem Assessment, 2004). The loss ofsemi-natural habitats due to agricultural intensificationand marginalization of traditional agricultural systems,
both of which have led to the abandonment of traditional land uses, is one of the main threats to biodiversity in agricultural ecosystems (Krebs et al., 1999;
Ormerod et al., 2003). Citizen participation would playa particularly important role in the restoration ofsemi-natural habitats in agricultural ecosystems giventhat the heterogeneous habitats of the agricultural landscape had been maintained by various human activities
concerning agricultural production (Washitani, 2001),
and that reinstating such activities would be fundamental to restoring the habitats. In this situation, the proposed scheme is also useful for stimulating interactions
between citizens and researchers through the cyclic
process of predictions and monitoring in an adaptive
framework. This would ultimately help to establish asystem of citizen participation in restoration projects.

Acknowledgments
We are grateful for the financial support provided by
Takeo Office of Rivers, Ministry of Land, Infrastructure
and Transport of Japan, for this study.
References
Aviron, S., F. Burel, J. Baudry and N. Schermann (2005) Carabidassemblages in agricultural landscapes: impacts of habitat features, landscape context at different spatial scales and farming
intensity. Agriculture Ecosystems & Environment, 108:205-217.
Campbell, D. R., L. Rochefort and C. Lavoie (2003) Determining
the immigration potential of plants colonizing disturbed

environments: the case of milled peatlands in Quebec. Journalof Applied Ecology, 40:78-91.
Chovanec, A. and J. Waringer (2001) Ecological integrity ofriver-floodplain systems-assessment by dragonfly surveys(Insecta: Odonata). Regulated Rivers-Research & Management,
17:493-507.
Clark, T. E. and M. J. Samways (1996) Dragonflies (Odonata) as
indicators of biotope quality in the Kruger National Park, South
Africa. Journal of Applied Ecology, 33:1001-1012.
D’Amico, F., S. Darblade, S. Avignon, S. Blanc-Manel and S. J.
Ormerod (2004) Odonates as indicators of shallow lake restoration by liming: comparing adult and larval responses. Restoration Ecology, 12:439-446.
Environment Agency of Japan (2000) National red list of dragonflies and butterflies. Environment Agency of Japan, Tokyo. (inJapanese)
Fukamachi, K., H. Oku and T. Nakashizuka (2001) The change ofa satoyama landscape and its causality in Kamiseya, Kyoto
Prefecture, Japan between 1970 and 1995. Landscape Ecology,
16:703-717.
Gillilan, S., K. Boyd, T. Hoitsma and M. Kauffman (2005) Challenges in developing and implementing ecological standards forgeomorphic river restoration projects: a practitioner’s response
to Palmer et al. (2005). Journal of Applied Ecology, 42:223-227.
Grumbine, R. E. (1994) What is ecosystem management? Conservation Biology, 8:27-38.
Halle, S. and M. Fattorini (2004) Advances in restoration ecology: insights from aquatic and terrestrial ecosystems. In: V. M.
Temperton, R. J. Hobbs, T. Nuttle and S. Halle, eds., Assembly
rules and restoration ecology. Island Press, Washington DC,
10-33.
Kadoya, T., S. Suda, J. Nishihiro and I. Washitani (in press)
Procedure for predicting the trajectory of species recovery
based on the nested species pool information: dragonflies in awetland restoration site as a case study. Restoration Ecology.
Kadoya, T., S. Suda and I. Washitani (2004) Dragonfly species
richness on man-made ponds: effects of pond size and pond age
on newly established assemblages. Ecological Research,
19:461-467.
Keddy, P. (1999) Wetland restoration: The potential for assembly
rules in the service of conservation. Wetlands, 19:716-732.
Kobori, H. and R. B. Primack (2003) Participatory conservation
approaches for satoyama, the traditional forest and agriculturallandscape of Japan. Ambio, 32:307-311.
Krebs, J. R., J. D. Wilson, R. B. Bradbury and G. M. Siriwardena(1999) The second silent spring? Nature, 400:611-612.
Millennium Ecosystem Assessment (2004)(http://www.millenniumassessment.org/en/index.aspx.)
Ministry of the Environment of Japan (2007) Third national biodiversity strategy of Japan. Ministry of the Environment ofJapan, Tokyo.
Mukai, Y., N. Baba and M. Ishii (2005) The water system of traditional rice paddies as an important habitat of the giant waterbug, Lethocerus deyrollei (Heteroptera: Belostomatidae). Journal of Insect Conservation, 9:121-129.
Niemi, G. J. and M. E. McDonald (2004) Application of ecological indicators. Annual Review of Ecology, Evolution and
Systematics, 35:89-111.
Ormerod, S. J., E. J. P. Marshall, G. Kerby and S. P. Rushton(2003) Meeting the ecological challenges of agriculturalchange: editors’ introduction. Journal of Applied Ecology,
40:939-946.
Palmer, M. A., E. S. Bernhardt, J. D. Allan, P. S. Lake, G.
Alexander, S. Brooks, J. Carr, S. Clayton, C. N. Dahm, J. F.
Shah, D. L. Galat, S. G. Loss, P. Goodwin, D. D. Hart, B.
Hassett, R. Jenkinson, G. M. Kondolf, R. Lave, J. L. Meyer, T.
K. O’Donnell, L. Pagano and E. Sudduth (2005) Standards for
ecologically successful river restoration. Journal of Applied

Adaptive Scheme for Wetland Restoration
Ecology, 42:208-217.
Patterson, B. D. and W. Atmar (1986) Nested subsets and thestructure of insular mammalian faunas and archipelagos.
Biological Journal of the Linnean Society, 28:65-82.
Primack, R., H. Kobori and S. Mori (2000) Dragonfly pond
restoration promotes conservation awareness in Japan. Conservation Biology, 14:1553-1554.
Rodriguez-Girones, M. A. and L. Santamaria (2006) A new algorithm to calculate the nestedness temperature of presence-absence matrices. Journal of Biogeography, 33:924-935.
Sahlen, G. and K. Ekestybbe (2001) Identification of dragonflies(Odonata) as indicators of general species richness in boreal
forest lakes. Biodiversity and Conservation, 10:673-690.
Society for Ecological Restoration International Science & Policy
Working Group (2004) The SER international primer on ecological restoration. www.ser.org & Tucson: Society for Ecological Restoration International.
Srivastava, D. S. (2005) Do local processes scale to global patterns? The role of drought and the species pool in determining
treehole insect diversity. Oecologia, 145:205-215.
Sugimura, M., S. Ishida, K. Kojima, K. Ishida and H. Aoki (1999)
Dragonflies of the Japanese archipelago in color. Hokkaido
University Press, Sapporo. (in Japanese)
Takeda, M., T. Amano, K. Katoh and H. Higuchi (2006) The habitat requirement of the Genji-firefly Luciola cruciata (Coleoptera: Lampyridae), a representative endemic species ofJapanese rural landscapes. Biodiversity and Conservation,
15:191-203.
Taylor, P. D., L. Fahrig, K. Henein and G. Merriam (1993)

185

Connectivity is a vital element of landscape structure. Oikos,
68:571-573.
Taylor, P. D., L. Fahrig and K. A. With (2006) Landscape connectivity: a return to the basics. In: K. Crooks and M. A. Sanjayan,
eds., Connectivity Conservation. Cambridge University Press,
Cambridge, UK.
Temperton, V. M. and R. J. Hobbs (2004) The search for ecological assembly rules and its relevance to restoration ecology. In:
V. M. Temperton, R. J. Hobbs, T. Nuttle and S. Halle, eds.,
Assembly Rules and Restoration Ecology. Island Press,
Washington DC, 34-54.
United Nations (2002) Report of the world summit on sustainable
development. United Nations, Johannesburg, South Africa.
Washitani, I. (2001) Traditional sustainable ecosystem ‘satoyama’and biodiversity crisis in Japan: conservation ecological perspective. Global Environment Research, 5:119-133.
Washitani, I. (2003a) Restoration of aquatic ecosystems. In: K.
Takeuchi, R. D. Brown, I. Washitani, A. Tsunekawa and M.
Yokohari, eds., Satoyama: the traditional rural landscape ofJapan. Springer, Tokyo, 143-147.
Washitani, I. (2003b) Satoyama landscapes and conservation
ecology. In: K. Takeuchi, R. D. Brown, I. Washitani, A.
Tsunekawa and M. Yokohari, eds., Satoyama: the traditional
rural landscape of Japan. Springer-Verlag, Tokyo, 16-23.
Yoshimura, C., T. Omura, H. Furumai and K. Tockner (2005)
Present state of rivers and streams in Japan. River Research andApplications, 21:93-112.

(Received 9 October 2007, Accepted 13 December 2007)