A Study on Biodiversity Offset Assessment Methodology in Japan
－Combination of GIS Screening for Site Selection and On-site Field Assessment－
Abstract:
In Japan, there is no legal obligation and also no established assessment methodologies for biodiversity offsets. In this
study, a preliminary research framework of forest assessment methodology for a biodiversity offset and banking system was studied
as a hypothetical case study in Nagoya City, Japan. Three step approaches were employed. First the wide scale assessment of
biodiversity/ ecosystem services (BD/ESs) by GIS was conducted as a screening stage of potential offset site selection. Second,
simple field surveys were conducted to do equivalency and offset-possibility assessment in 131 forests in the city. Third, on-site field
surveys by utilizing biodiversity assessment methods implemented in other countries were done for testing the applicability of these to
Japan.
Keywords: Biodiversity offset and banking, ecosystem service, forest, Japan, Nagoya
Introduction
In Japan, the expansion of urban area caused the degradation of forest and biodiversity. This was
remarkable especially for large cities, such as, Tokyo, Osaka, Nagoya, etc. For example, the forest
coverage in Nagoya was decreased from 29.8% in 1990 to 23.3% in 2010 (Nagoya City 2012).
One of the policy instruments to compensate the loss of forest and biodiversity by development
activities was called biodiversity offset, which was defined in, for example, BBOP (2013). Biodiversity
offset and banking systems were widely introduced in many countries (Madsen, Carroll and Kelly 2010),
such as, conservation banking (CB) and Mitigation banking(MB) in the USA(State of California 2014),
BioBanking(BB) in Australia (NSW Government 2014a), etc. However, there is no legally binding
national biodiversity offset system implemented in Japan even though several local governments have
already introduced biodiversity offset like systems, such as, Aichi Prefecture (Aichi Prefecture 2013).
Ministry of the Environment, Government of Japan (MOE-J) made a draft report on biodiversity offset
(MOE-J 2014). The discussion on the possibility of biodiversity offset and banking systems were
gradually increased in Japan in recent years.
In Japan, there is no established biodiversity assessment method for biodiversity offset. In the
world many kinds of biodiversity offset and banking assessment methods were implemented (Quétier,
Lavorel 2011), such as, HSI (Habitat Suitability Index) model (Ito and Hayashi 2014, Dhakal et al.
2014), HH (Habitat Hectares scoring method) (The State of Victoria 2014), BBAM (BioBanking
assessment methodology)(NSW Government 2014b). In the discussion of the possibility of biodiversity
offset and banking system in Japan, the equivalency and alternativeness between the loss and gain of
biodiversity were one of the critical issues (Hayashi and Ooba 2014). Several studies touched on the
assessment of the applicability of biodiversity offset assessment methods implemented in other
countries into Japan (Hasegawa et al. 2013, Hasegawa and Hayashi 2014, Ito and Hayashi 2014). Most
of these were focused on the on-site scale applicability of the existing methods.
Forest provides a variety of benefits to human society, namely, ecosystem services (ESs) (MA
2005). Regarding biodiversity bankings, for example, the CB and MB in the USA, the scope of the
assessment of biodiversity components were limited, mainly for evaluating the habitat of endangered
species and the ecological function of wetland respectively. Also Ito et al. (2014b) revealed that only
one part of biodiversity and ecosystem service (BD/ES) values was included in the credit value of a MB
by a contingent valuation method based on environmental economic valuation. However, most of these
values were not appropriately included in biodiversity offset and banking systems. The potential scope
of BD/ESs should be considered beforehand for a biodiversity offset and banking implementation.
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Study objective
In this study, a preliminary research framework of forest assessment methodology of a biodiversity
offset and banking system was studied as a hypothetical case study in Nagoya City, Japan. Three step
approaches were employed. First the wide scale assessment of BD/ESs by GIS (Geographical
information system) was conducted as a screening stage of offset site selection. Second, simple field
surveys for forests were conducted to do equivalency and offset-possibility assessment in forests in
Nagoya City. Third, on-site field surveys by utilizing biodiversity assessment methods implemented in
other countries were done for testing the applicability of these to Japan. Through this case study, the
method of a site selection, the spatial assessment of ESs and the preliminary research framework were
tested. The results presented here were tentative version and will be updated in the future after further
analysis.
Methodology
Study area
Nagoya City is located in Aichi Prefecture (Figure 1(a) and (b)). The City hall is located at 35.181N,
136.906E. The average annual temperature for the city in 2014 was 16.1°C and the average precipitation
was 1505.5 mm (Japan Meteorological Agency 2015). The area of the city is approximately 326.43 km2
and the population of the city was 2.27 million, as of April 1st 2014, which was the third largest city in
Japan (Nagoya City 2015).
Methods
A hypothetical development activity will damaged a forest area in Nagoya City (Figure 1(c)). The
hypothetical development site (4.05ha) was a typical secondary broadleaf deciduous forest dominated
by Q. serrata and Q. variabilis in the east part of Nagoya City. To compensate the hypothetical loss of
the BD/ESs, the potential offset sites should be considered. In this case, the boundary of the site
selection was set to be within the city so that the study was conducted focusing on the city.
The first step was to grasp the BD/ES provisioning potential in Nagoya City as a screening
stage (Inagaki et al. 2013, Li et al.2014). It could show the general tendency of BD/ES provisioning
potential from each area. Based on the Nagoya land use metric survey GIS data provided by Nagoya
City, 6 land use categories were developed by the authors, including urban area, forest area, urban park,
water area, paddy field and agricultural land. Then 12 ESs were selected for the ES estimations by
utilizing unit value assessment from existing literatures. These included the following: supporting
services (soil formation, CO2 absorption, nutrient cycling), provisioning services (agricultural products),
regulating services (air purification, climate regulation, rain infiltration capacity, flood mitigation, etc.),
cultural services (recreation, spiritual value, aesthetic value, etc.). By Maxent model (Phillips et al.
2006), Li et al. (2014) estimated the potential distributions of mammals, namely, raccoon dog
(Nyctereutes procyonoides) and weasel (M. itatsi and/or M. sibirica). By utilizing land use data, the 2
species occurrence data and environment variables (year mean temperature, year mean precipitation,
snow cover and elevation), the Maxent model was conducted to explore the potential distributions of
these mammals in Nagoya City.
Figure 1. Maps of the study area, (a) Japan with Nagoya City in the star symbol, (b) Nagoya
City outlined in red, (c) hypothetical development site in the star symbol
Source: Satellite image: (b)ALOS by JAXA/ Distribution RESTEC, (c) ArcGIS with Nagoya green coverage GIS data
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Second, simple filed surveys were conducted focusing on forests in Nagoya City because in the
first step, it was difficult to assess the quality of forest, tree species, the situations of understory and
litter layer, cultural service use, etc. In the offset site selection, the quality of biodiversity was one of the
important points so it needed to collect some field data from each forest. According to the Nagoya green
coverage GIS data by Nagoya City, the number of forests (equal or more than 1 ha size) were 239. In
this study, the definition of forest was continual tree crown area by tree species, which had equal or
more than 1 ha size. Among them, the authors conducted simple field surveys for 131 forests in the
Nagoya City from 2013 to 2014. The survey items were listed in Table 1. After conducting simple field
surveys, the authors could categorize forest into 13 types tentatively and compared with each other from
the perspective of equivalency and offset-possibility of the ES provisioning potential.
Table 1. Simple field survey items by survey size
Basic survey items
Biomass surveys
Soil survey
In 100-m2 area
Longitude, Latitude, Elevation, Slope, Topography,
Temperature+, Relative humidity, Whole-sky
photography++, etc.
Tree species, Tree height, DBH
Crown area of each tree,
Vegetation cover (tall trees, medium trees, short trees,
very short trees, etc.),
Recruitment (seedling growth)
Mass of dead wood, etc.
Water content+++, Soil hardness++++, Surface soil and
litter thickness, etc.
In 400-m2 area
Other
Outside of forest
Temperature,
Relative humidity
Number of gingko trees (Ginkgo biloba )
Number of large trees (DBH > 40 cm)
Number of large trees
Number of oak trees (e.g., Quercus
(DBH > 80 cm)
serrata , Quercus variabilis , Quercus
glauca , and Quercus myrsinifolia )
Aesthetic value, Recreation, Spiritual value,
Cultural heritage value, etc.
Cultural survey
Habitat survey
Entire forest area
Human intervention, Human accessibility, Human and
vehicular traffic, etc.
Non-native species, Number of hollow trees
+: illumination meter (LM -8000, M K Scientific, Inc., Japan); ++: fish-eye lens(IDF-3, Izawaopt, Japan); +++:soil water content meter (ProCheck, Decagon Devices Inc., U.S.A.)
++++: soil hardness meter (Daiki Rika Kogyo Co., Ltd., Japan); DBH means Diameter at Breast Height.
Third, on-site more detailed field surveys were conducted for testing a variety of biodiversity
assessment methods including HSI, HH and BBAM with several diversity indexes (Simpson’s diversity
index, Shannon-Wiener’s index, etc). The authors selected 4 forests near the hypothetical development
site in the east part of Nagoya City. The detailed methods of HH and BBAM conducted in this study
were summarized in Hasegawa et al. (2013) and Hasegawa and Hayashi (2014). And Ito and Hayashi
(2014) developed a forest HSI model by combining integrated SI models for the indicator species,
firefly (Luciola parvula), large Japanese field mouse (Apodemus speciosus), and northern goshawk
(Accipiter gentilis). In the course of the study, the authors could get the characteristics, limitation and
problems of each assessment methods for the potential application to Japan.
The statistical analysis was conducted using Excel ver. 2010(Microsoft corp.), SPSS statistics
ver.22 (IBM corp.). The ArcGIS 10.1 (ESRI Japan Inc.) was used for the spatial analysis.
Results and discussion
In the first step, the 12 ES provisioning potential maps and the 2 potential distributions of mammals
were calculated. Figure 2 showed tentative examples of BD/ES provisioning potential maps (Inagaki et
al. 2013, Li et al. 2014). Based on these, it was easy to understand which area had what kinds of ES
provisioning potential compared with the hypothetical development site. Also the trade-off and synergy
of ES provisioning potential among ESs could visually identified by GIS.
In the second step, by utilizing simple field survey data, forests were categorised into several
groups. According to Iwai and Hayashi (2015), tentative results showed that 131 forests were classified
into 13 categories by utilizing 16 ESs by a cluster analysis (Figure 3). These broad categories included
bamboo forests, deciduous forests (5 sub categories), evergreen forests (5 sub categories), and parks (2
sub categories). The detailed results will be summarized in the future. Based on this analysis, the forest
quality of potential offset sites could be compared with the hypothetical development site. So
equivalency and offset-possibility could be roughly grasped by this offset site selection stage.
In the third steps, based on the on-site field surveys, more detailed biodiversity assessment was
conducted (Table 2). As for the SI model, only the average SI score of the site D was lower than that of
the hypothetical development site. Because, the results of SI models for firefly and large Japanese field
mouse were lower than those of the development site. As of the BBAM assessment, the score of the site
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C was lower than that of the development site. In this case, the score of the site D was highest.
Regarding the HH assessment, the score of the site C was lower than that of the development site, too.
And the site B was the same score with the development site. The score of site A and B for HSI, HH
and BBAM were higher or equal to the development site so that the site A and B could be potential
offset sites. However, taking a look at other indexes, such as, individual number and above ground
biomass, the scores of the site A and B were lower than those of the development site. So individual
assessment methods or indexes had different viewpoints for their own assessment. So the priority of the
site assessment for BD/ESs should be considered carefully beforehand. More detailed results were
summarized in Ito et al. (2014a), Ito and Hayashi (2014), Hasegawa et al. (2013) and Hasegawa and
Hayashi (2014).
Conclusion
In the study, a preliminary research framework of a biodiversity offset and banking assessment
methodology was tested from a site selection by spatial GIS assessment and on-site assessment with the
inclusion of BD/ESs comprehensively. Individual assessment methods or indexes had different
viewpoints for their own assessment. So the priority setting for BD/ESs should be considered carefully
beforehand. Future studies included a study on more linkage between spatial ES assessment and on-site
assessment. The results presented here were tentative version and will be updated in the future.
Figure 2. BD/ES provisioning potential in Nagoya City (tentative examples)
(a) infiltration capacity, (b) CO2 absorption, (c) Potential distributions of raccoon dog
Source: Inagaki et al. (2013) and Li et al. (2014)
revised
Figure
3. Categorization of urban forest in Nagoya City
(tentative results)
Note: This results of a cluster analysis using the following parameters under the
group-average method and the squared Euclidean distance method: (1)
Supporting services (Soil formation, carbon stock, etc.), (2) Regulating
services (NO2 absorption, climate regulation, etc.), (3) Provisioning services,
(4) Cultural services (Spiritual value, aesthetic value, education value,
recreation), (5) Habitat (forest size, naturalness, etc.)
Source: Iwai and Hayashi (2015)
Table 2. On-site biodiversity assessment results of the hypothetical development site
and 4 potential offset sites
HSI model assessment
SI for firefly(Luciola parvula )
SI for northern goshawk(Accipiter gentilis )
SI for large Japanese field mouse(Apodemus
Average of three SI models
Inhabitation of mammals
BBAM
HH
Individual number
Species numeber
Simpson λ
Shannon-Wiener H'
Above ground biomass(kg/400㎡)
Development site
A
0.92
0.39
0.80
0.70
raccoon dog
145
56
289
21
0.77
2.99
5,243
0.92
0.37
0.83
0.71
raccoon dog
190
64
127
12
0.83
3.23
4,751
B
C
1.00
0.92
0.47
1.00
0.67
0.80
0.71
0.91
raccoon dog raccoon dog, weasel
125
208
54
56
215
179
23
34
0.94
0.87
4.70
5.20
3,169
7,888
D
0.47
0.67
0.55
0.56
raccoon dog, weasel
210
63
167
17
0.88
4.47
6,869
Source: Ito et al. (2014a) revised
Note: BBAM means BioBanking assessment methodology; HH means Habitat Hectares scoring method; Index species for HSI model
included firefly (Luciola parvula), northern goshawk (Accipiter gentilis) and large Japanese field mouse (Apodemus speciosus).
4
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