IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Research article
erdAnalysis of Urban Ecosystem Services Considering
Conservation Priority
MAKOTO OOBA*National Institute for Environmental Studies, Tsukuba, Japan
Email: ooba.makoto@nies.go.jp

KIICHIRO HAYASHI
Nagoya University, Nagoya, Japan

TAKAHIRO SUZUKI
Nagoya University, Nagoya, JapanRUI LI
Nagoya University, Nagoya, Japan
Received 16 December 2014

Accepted 31 May 2015(*Corresponding Author)

Abstract Many cities lose their green space and ecosystem services, especially in developing
countries, which represent a problem as serious as an environmental pollution. Japan has also
experienced the problem as a result of rapid economic growth. A system to assess ecosystemservices and to create conservation maps in urban area was developed for use as a policy
suggestion for urban planning. Nine ecosystem services were calculated by proxy variables inthe studied area, Nagoya city, Japan. After selecting a subset of relatively and highly
independent proxy variables, five ecosystem services significantly decreased before and after aperiod of strong economic growth (1955 and 1997). Distributions of the ecosystem services hadtrends of fragmentation indicated by a cluster analysis. Conservation priority maps created byusing the conservation planning software called Zonation were presented. In the eastern andwestern areas, ecosystem services decreased with the loss of green space indicated by theauthors in a previous study. The conservation priority level of the central area was relatively
high due to the loss of green space. The results of this study are helpful planning for green
space and offset-evaluating system.
Keywords Geographical Information System, green space, landuse, Nagoya, Zonation

INTRODUCTIONMany cities lose their green space (parks, agricultural fields, and secondary forests) and related
ecosystems due to an increase in population, industry, and business, especially in developing countries.
This loss represents a problem as serious as an environmental pollution. Japan has also experienced theproblem as a result of rapid economic growth. Currently, the green space in many Japanese cities isstill over 10% of the land area. However, it appears that the quality of this green space, as measured bycharacteristics such as continuousness and ecological complexity, has not remained high.
Ecosystem services (e.g., Costanza et al., 1997; Millennium Ecosystem Assessment, 2005),
defined as goods and services provided by ecosystems to human society, are essential for a sustainablesociety. Green space in urban areas, including grass, agricultural, and forest ecosystems, provides
ecosystem services such as biodiversity conservation, air and water purification, climate mitigation,
disaster control, and cultural services (recreation, landscape, etc.). However, ecosystem services fromthese ecosystems decrease with urban development.
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From a socioeconomic point of view, setting ecosystem conservation priorities is an effective way
to maximize ecosystem services and/or biodiversity under economic constraints. Many software
programs have been applied to conservation planning for biodiversity, including C-Plan, Marxan, andZonation. Moilanen et al. (2011) researched competing land uses (in terms of their biodiversity, carbon
storage, agricultural production, and urban area) in Great Britain using Zonation software. Fan andShibata (2014) applied Zonation to the evaluation of ecosystem services in a river basin and found thatforest ecosystems should be prioritized, especially for the water supply service that they provide, for
Hokkaido, Japan.
In a previous study (Ooba and Hayashi, 2014), the authors indicated that land use in Nagoya,Japan differed before and after a period of strong economic growth, with the green space in Nagoya,including agricultural fields and forests, decreasing drastically. Those results mentioned that theprovisioning of ecosystem services also decreased drastically; however, quantitative evaluation was notperformed. In addition, conservation policy suggestions would be useful for the remaining green space,especially information on the areas that are the most important for maintaining or enhancing ecosystemservices based on detailed geographical and quantitative research.
OBJECTIVE
The aim of this study is the development of a system to assess ecosystem services in urban areas andcreate maps of ecosystem conservation priorities for use as a policy suggestion for urban planning.
METHODOLOGY
Study Area and Data Set
The study area (the city of Nagoya) is the same area as the previous study (Ooba and Hayashi, 2014).
The annual average temperature and precipitation are 15.8°C and 1,535.3 mm, respectively. With apopulation of approximately 2,260,000, metro Nagoya (ca. 32,600 ha) is Japan’s fourth largest city andis representative of urban Japan.
Digital maps of land use in 1955 and 1997 at a 10 m resolution were developed in the previousstudy. The maps categorized 5 types of land use: water surface, built-up urban (residential andindustrial) areas, roads, agricultural fields, and forest. In this study, green space was defined as theagricultural field and forest land uses. A digital elevation map (10-m resolution) was also used toestimate prevention of soil erosion. The following geographical processing and calculations wereperformed using ArcGIS 10.2.
Evaluation of Ecosystem Services
Several variables were calculated as proxies for supply of ecosystem services from the studied area(Table 1) at the resolution of the Japanese standard mesh defined by the Japan Industrial Standard,corresponding to approximately 1 km. The following variables were calculated using an area-based
primary unit for each land use: carbon sequestration, prevention of eutrophication, food supply, airpurification, climate mitigation (contribution to increase of air temperature), infiltration rate, andprevention of soil erosion. The detailed calculations used to generate these values are indicated in Table
1. For cultural services, a proxy variable was estimated from the distance to the nearest relatively large
green space (recreation index), defined as an area larger than 1 ha. A proxy for biodiversity
conservation was estimated from the continuousness of green space (biodiversity index) by using Focal
Statistics in ArcGIS and setting the proximity radius to 2 km. For the 1997 data set, these 9 variablesⒸISERD67

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

were converted to normalize values due to difference of units by subtracting the mean and dividing by
the standard deviation. Some variables (prevention of eutrophication, climate mitigation, prevention ofsoil erosion, and distance to a large green space) were of the opposite scale to the other variables.
These variables were reversed by multiplying by −1. For comparison to 1997, the variables for 1955
were normalized by the statistics of 1997.
A matrix of correlation coefficients among all proxy variables was generated to identify linearrelationships. After selecting a subset of relatively highly independent proxy variables, a cluster
analysis was performed using the k-mean method for the 1997 data set to clarify the characteristics ofecosystem services at each mesh cell in the city. For the 1955 data set, each mesh cell was reclassified
and compared to the result for 1997 to obtain the differences between the two years. These calculations
were performed using statistical software (Excel statistics, Social Survey Research Information, Japan)
in Microsoft Excel 2013.
Table 1 Proxy variables of ecosystem services in urban area
NameCarbon sequestration
Prevention ofeutrophication**
Food supply
Air purification
Climate mitigation**
Rain infiltration
Prevention of soil
erosion**Cat*
SS

Recreation **

CPRR
R
R

Estimation Method
Primary unit

Values or Details
3.09(F)16.5(U), 42(A), 3.8(F)

Unit
t/y

2.98(A)
0.00615(A), 0.011(F)
6(U), −2.9(A), −1.3(F), 2(W)12.7(U), 89.3(A), 258.2(F)kg-N/yt/yt-NO2/y°Cmm/h

S = 65.41sin2T+ 4.56sinT+ 0.065
C = 1 (U), 0.33(A), 0.0085(F)S and C coefficient inRUSLE 6-Distance of relatively Enquired distance for large green
mlarge green space
space (A and F) polygon (> 1ha)
Biodiversity
S
continuousness of green Focal statistics (proximity radius 2spacekm) (ArcGIS spatial tools)
Abbreviation: U: Urban area and road, A: Agricultural area, F: Forest area, W: Water surface* Category of ecosystem services: Supporting (S), Provisioning (P), Regulating (R), Cultural (C)** Opposite scale. High value of the variable indicated negative effect about the concerned ecosystem service.
1. Ogawa et al. (2003)
2. Japan Sewage Works Association (1997)
3. Aichi prefecture (2012)
4. Yokoo et al. (2003)
5. Murai and Iwasaki (1975)
6. Renard et al. (1997), RUSLE: Revised Universal Soil Loss Equation.
7. Ogawa et al. (2005)
8 Kitahara et al. (2000)
9 Li (2014)

Ref.
12
3
1
4
5
67(A)
8(F)
99

Algorithm of Calculating Conservation Priority
The conservation planning software Zonation provides several algorithms to determine conservation
priorities (e.g., core-area zonation). The authors chose the simplest algorithm, the additive benefit
function, which calculated the sum of all calculated values of ecosystem services for each mesh celland produced a mesh-map of the sums. In this study, the input values were the proxy values ofecosystem services. The weight and cost for each proxy variable were assumed to be 1.0 (the default).
For a technical reason, the raster data for Zonation were created at a 500-m mesh converted from theabove mentioned approximately 1-km mesh.

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RESULTS AND DISCUSSION
Ecosystem Services Evaluated by Proxy Variables
Nine ecosystem services were estimated at a 1-km mesh for 1955 and 1997 for Nagoya city (data notshown). The matrix of correlation coefficients among all proxy variables was also calculated. The
variables calculated from the digital maps of land use type using the primary units exhibited highcorrelations with the other variables calculated by the same method. On the other hand, the variables
calculated using ArcGIS had low correlations with the former variables. For further analysis, thefollowing five variables of which correlation coefficients were less than 0.6 were selected: carbon
sequestration, food supply, prevention of soil erosion, recreation index, and biodiversity index. The
food supply variable was the only proxy of a provisioning service that was selected; it was chosen overprevention of eutrophication, which displayed a high correlation with food supply.
The values of all of the selected variables decreased from 1955 to 1997, which was related to adecrease in green space from 55% of the total city area to 16% (Ooba and Hayashi, 2014). The
distribution of the supply of ecosystem services also changed, becoming sparse and isolated in 1997.
Classification of Supply of Ecosystem Services
The distribution of classified mesh cells from the selected 5 proxies is indicated in Fig. 1. Because thenumber of classes is arbitrary in the k-mean method, the authors chose 5, which was the same as thenumber of classified types in the original land use maps. The following labels were used in referring tothe land use maps: core urban area, urban area, agricultural area, forested area, and green area.
Between the dates of the two land use maps, urban areas expanded and agricultural and forested areas
contracted complementarily. In 1997, green areas (mixture of urban area and green space area)
appeared as a result of the fragmentation of green space.
(a) 1955(b) 1997

Nagoya Stn
Higashiyama
Park
Urban area
Urban (core) area
Agricultural area
Forest area
Mixed area

Fig. 1 Classification from the proxy variables of ecosystem servicesⒸISERD69

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

10
Carbon sequestration

Food supply

Prevention of soil erosion

Recreation index

Biodiversity Index

Fig. 2 Relative priority ranks (0-1) of the selected ecosystem services(a) 1955(b) 1997(c) Difference of 1997 to 1955

0.75
−0.95

10Fig. 3 Relative priority ranks and difference of integrated ecosystem services
Conservation Priorities
Priority maps for each of the 5 selected proxies were calculated using Zonation and are presented as
Fig. 2. The maps represent the conservation priority order of each mesh cell for each proxy variable(the blue colored cells supply the most ecosystem services). In 1955, the mesh cells on the east andwest sides in the city had relatively high values in the all ecosystem services, whereas almost half thecells in those areas had low values in 1997.
Integrated priority maps, presented as Fig. 3, were also calculated from the 5 variables using
Zonation. The conservation priority level of the marginal area of the city is high levels in 1955
provided from both agricultural and forest ecosystems. This east, especially east-south and east-north,high priority area almost disappeared by 1997. The west area remained a high priority. Compared tothe east area, the west and northeast areas were also assigned high priority. Fig. 3(c) presents thedifferences between the two years. This indicates an overall loss of ecosystem services, which isconsistent with the pattern observed above for each individual ecosystem service. It is notable that theⒸISERD70

IJERD – International Journal of Environmental and Rural Development (2015) 6-2

conservation priority level of the central area is relatively high due to the loss of green space in themarginal area.
OutlookA relatively simple method (primary units) was applied to estimate the supply of ecosystem services.
Derived variables such as carbon sequestration and prevention of eutrophication were highly correlatedwith the other variables derived by the same method. For each estimate of supply of ecosystemservices, more appropriate methods may be developed that depends not only on land use but also onother geographic, statistical, or process-based methods. For several services, especially those related toculture and biodiversity, innovative proxy variables and estimation methods are needed.
The default settings of the Zonation software program (weight and cost) were used in this study.
For widespread applicability, these values must be determined by suitable methods: Cost may be
estimated by building up the management costs of conserving an ecosystem. Weight may be estimatedby social investigation, such as an economic survey or questionnaire about the value of the ecosystem.
In a more practical context, discussions about an offset system for development have begun, andmany studies related to the design of such an offset system have been performed. Offset systems
focused on conserving natural land uses or biodiversity have already been introduced in the UnitedStates, Australia, and many European countries. The authors place a special focus on offset systems
based on assessing ecosystem services because the methodology for such a system provides not only
on-site offset (offset sites located near the development site) but also off-site offset because thesimilarity of ecosystems is assessed by the supply of ecosystem services from the target ecosystems.
CONCLUSION
The authors’ previous work revealed a drastic change in green space in Nagoya city from 1955 to 1997
(Ooba and Hayashi, 2014). This study included not only a quantitative evaluation of ecosystemservices but also an integrated assessment of ecosystem services in this area. The supply of ecosystemservices decreased along with the decreased area of green space. A high supply of ecosystem services
present in the marginal area of Nagoya city in 1955 disappeared, while in the eastern area, loss ofecosystem services was relatively low. Conservation priority maps created using Zonation software
were presented, which is helpful planning for green space and offset-evaluating system in the studiedarea.
ACKNOWLEDGEMENTS
This study was supported by the funding program for next generation world-leading researchers(MEXT, Japan) and the Environment Research and Technology Development Fund (1-1401, 2-1404,MOE, Japan). The authors thank H. Shibata, M. Fan, and Y. Inagaki.
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