Geospatial Approaches towards Biodiversity Conservation◆特集＊招待論文◆

Geospatial Approaches towards
Biodiversity Conservation
Case study in Fuji-Tanzawa regions in Japan

生物多様性保全に向けた
空間情報学的アプローチ
富士丹沢地域を事例研究として

Tomoko Doko
Doctoral Program, Graduate School of Media and Governance, Keio University
Research Fellow of the Japan Society for the Promotion of Science
土光 智子
慶應義塾大学大学院政策・メディア研究科後期博士課程
日本学術振興会特別研究員 (DC)

Hiromichi Fukui
福井 弘道

Professor, Faculty of Policy Management, Keio University
慶應義塾大学総合政策学部教授

In this paper, we introduce several geospatial approaches for biodiversity conservation, taking an
example of our on-going project. Chapter 1 introduces the needs of ecological networks formation, andFuji-Tanzawa regions as the study area. Chapter 2 presents the ecological modeling approach which canmodel species’ geographic distribution and assess present needs for the ecological networks. Chapter
3 outlines fieldwork for Asiatic black bears’ ecology, which focuses on the capture and collecting
fieldsigns. Chapter 4 introduces few experimental results on an advanced satellite tracking system,
namely GPS-AROGS, concerning animal movement. Chapter 5 presents a Web-based GIS development
as a policy making support system for conserving biodiversity. Chapter 6 briefly described future
works.
本稿では、生物多様性保全に向けた空間情報アプローチを紹介する。第 1 章では、エコロジカル
ネットワークと研究対象地域の富士丹沢地域を概観した。第 2 章では、生息地域空間的分布モデリ
ングを用いて、エコロジカルネットワークの必要性をアセスメントする定量的手法を提案した。第3 章は、ツキノワグマの生態を調査するフィールドワーク方法を紹介した。第 4 章では、最新型の動物衛星追跡システムの精度実証実験を紹介した。第 5 章においては、政策決定支援システムとして、Web-GIS を開発した。第 6 章では、将来展望を述べた。
Keywords: Ecological networks, Asiatic black bear, ARGOS, Modeling, Web-GIS

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1 Introduction

belt. Vegetation is varied from the plants in the warm-

1.1 Biodiversity loss and ecological networks

temperature zone in Izu Island chain to the ones inInternational awareness of the need to protect

the Alperstein zone of Mt. Fuji. Throughout the park,biodiversity has been growing steadily as the 10th

there are a number of habitats and breeding place forConference of the Parties to the Convention on

wild bird species. On the other hand, Tanzawa region

Biological Diversity (COP 10) is scheduled in 2010,is the mountainous area which consists of Hirugatake

Aichi-Nagoya, Japan. In 2007, Japanese government(1673 m), Mt. Tanzawa, Sagami oyama, Togadake.

adopted the third National Biodiversity Strategy,

It across three prefectures: Kanagawa, Yamanashi,

which stipulates the seven major themes for

and Shizuoka. This region is designated as a Quasi-

implementing biodiversity conservation policies,

National Park in Japan.

including formation of “ecological networks”. The

Fuji region and Tanzawa region are geogra-

development of the ecological networks can connect

phically not far; however, because of the recent

the fragmented habitats of wild animals, stem theurbanization and new road construction, thebiodiversity loss, and promote dispersal and genetic

exchange of genes between the metapopulation of

exchange of wild species.

big mammals, especially Asiatic black bear, in thetwo regions are reported to almost cease (Japanese
Mammals Society 1997). In both of Mt. Fuji and

1.2 Study area
The area of our interest is the ‘Fuji region’

Tanzawa region, there exist the big mammals suchin part of the Fuji-Hakone-Izu National Park andas Asiatic black bear (Ursus thibetanus japonicus)

the ‘Tanzawa region’, Japan. The Fuji-Hakone-Izu

and Japanese serow (Naemorhedus crispus). The area

National Park covers area of 121,851 ha, which is

121,851 ha of the National Park is considered as an

across four prefectures and consists of Mt. Fuji,

appropriate size for large mammal species. There

Hakone, Izu Peninsula, and Izu Island chain. The

exist a variety of endemic species in the park as well

various types of volcanoes can be seen, because thebecause of the specific biota caused by the ‘Fossa

park is located from the Pacific Ocean to the central

Magna’. Landscape and biodiversity in this area is inpart of the Main Island crossing the Fuji volcanica variety.

Figure 1 Study area: Tanzawa and Fuji regionsGeospatial Approaches towards Biodiversity Conservation

The study area, shown in Figure 1, was ranged

the fragmented habitats of wild animals, stem thefrom 3830925.47 to 3949185.47 N and 177284.971 tobiodiversity loss, and promote dispersal and genetic

390854.971 E in a datum of WGS 1984 and projection

exchange of wild species. Serious fragmentation ofof UTM Zone North 54.

habitats has been caused by the industrialization ofagriculture, restructuring of land use, the building of
huge transport networks and metropolitan (Stanners

1.3 Outline of this paper
In this paper, we introduce several geospatial

and Bourdeau 1995). For fragmented habitats, theapproaches towards biodiversity conservation,

theory of island biogeography (MacArthur andtaking an example of our on-going project. Chapter

Wilson 2001) can be applied, and connecting the

1 introduces the needs of ecological networks‘islands’ through the ecological networks can reduceformation, and Fuji-Tanzawa regions as the study

the risk of extinction of species.

area. Chapter 2 presents the ecological modeling

As for the Japanese mammals, the Ministry

approach which can model species’ geographicof Environment of Japan has conducted the

distribution and assess present needs for thenational distributional survey of Japanese animals

ecological networks. Chapter 3 outlines fieldwork(Biodiversity Center of Japan 2004) in 1978 and in

for Asiatic black bears’ ecology, which focuses on

2003 as a monitoring activity. The main objective

the capture and collecting fieldsigns. Chapter 4

was to acquire national distributional maps of ten

introduces few experimental results on an advanced

main mammals, including key wildlife species in thissatellite tracking system, namely GPS-AROGS,

study. Based on survey data from interviews andconcerning animal movement. Chapter 5 presents

questionnaires on a sampling grid of 5 by 5km, thesea Web-based GIS development as a policy making

distribution maps were compiled at a national scale (1:support system for conserving biodiversity. Chapter

2,500,000).

6 briefly described future works.

Although these maps provide insight inspecies’ distribution at a glance, they do not reflect

2 Modeling of Species’ Gegraphic
Distribution for Assessing Present
Needs for the Ecological Networks

distribution at local population level. An appropriate

2.1 Introduction

distribution at a local scale with more accurate

2.1.1 Background and research problem statement

resolution. With this information, the core area ofapproach for preparing conservation and zoning
plans requires spatially explicit information of species

The third National Biodiversity Strategy ofa suitable habitat can be identified, and ecologicalJapan (2007) stipulates seven major themes for

networks can be designed if necessary. There are

implementing biodiversity conservation policies.

several studies that have integrated habitat models

The first theme is conservation of priority areas

into GIS (for example, see Corsi et al. (1999). However,and formation of ecological networks. Its basis is tothese have not assessed the need for ecologicalreinforce the protected-area system. In addition to

networks of large mammals. Also, to date, no studies

the perspective of conserving natural landscape ofwere found on quantitative needs assessment of

the Natural Parks, measures from the perspective

ecological networks.

of ecosystem conservation, especially of animal

In this paper, we present a quantitative

habitat conservation, should be institutionalized. The

methodology for the modeling of the geographic

development of the ecological networks can connect

distribution of two key species of large mammals in

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order to assess the need for ecological networks.

931 points were digitized manually. Geographic
coordinates were calculated from point features by
the ArcMap’s VBA built-in function.

2.1.2 Research objectives
There are three main objectives of this study: 1)

The national distributional map of Japaneseto acquire more accurate potential spatial distribution

mammals (Biodiversity Center of Japan 2004) wasof habitats of ‘key’ wildlife species, 2) to identify theused to create points representing species’ absence‘core areas’ of these habitats, and 3) to assess thedata. It was based on interviews and questionnaires

present needs for ecological networks.

in 1978 and in 2003 for grids of 5 by 5km. Following

At present, the most accurate distribution map(Corsi et al. 1999), any area where no evidence ofof the target species has a resolution of 2 by 2.5km

stable target species’ presence had been gathered(Ohba 2002). This study aims to create distribution

in the last 26 years has been defined as species’

maps with a resolution of 90 by 90 m, or at best 30

absent area. Each image was geo-referenced usingby 30 m. The area of interest is the Fuji and Tanzawa

the intersections of administrative boundaries,

regions located in the central part of Japan’s main

whereafter the species’ known presence and absence

island. The administrative boundaries of Kanagawa

areas was digitized as a polygon. Random points

Prefecture and Shizuoka Prefecture have been

distributed within the absent range for each species

selected as the study area. The Asiatic black bear

were considered to represent each species’ absence

and the Japanese serow were identified as the target

data. To ensure a balance in the number of species’

species.

presence and absence records, the same number ofrecords was plotted for each species: 770 random

2.2 Data management

points for the Asiatic black bear and 160 random

2.2.1 Species’ records extraction

points for the Japanese serow.

Species’ presence data consist of localities of1) 14 tracked Asiatic black bears in the South Alps

2.2.2 Geo-database for predictors

region (715 points) and 56 observed field signs of

Based on known Asiatic black bear’s andAsiatic black bear in the Fuji region (Mochizuki etJapanese serow’s ecology, the selected environmental

al. 2005) and 2) 160 observed Japanese serow in

predictors can be categorized in five groups: 1)

Tanzawa region (Yamaguchi et al. 1998). In total

topographical variables, 2) water-related variables,

49 paper maps of the above mentioned sources3) climatic variables (Guisan and Zimmermann 2000;

were scanned; four maps for bears of the Fuji local

Pearson and Dawson 2003), 4) variables related topopulation, 44 maps for bears of the South Alps

roads (Okumura et al. 2003), and 5) variables related

local population, and one map for Japanese serow

to vegetation (Hashimoto et al. 2003; Huygens etin Tanzawa Mountains. Next, the scanned maps

al. 2003). All variables were obtained digitally fromwere geo-referenced respectively. The 1st ordervarious sources (See Appendix) and stored in a GIS

polynominal affine transformation was conducted toenvironment. Considering the relatively small size

rectify the scanned images within 50 m of the totalof important landscape elements in the Japanese

RMS error for the bear’s maps. The maximum totallandscape and the high precision of the species’

RMS error was 251 m for the distribution maps ofrecords, all predictor variables were compiled at a

the Japanese serow. Thereafter, the rectified images

resolution of 30 by 30m. For calculating NDVI value,

were used to extract species observation points.

Erdas Imagine® 8.7 was used, and for other variables,

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Geospatial Approaches towards Biodiversity Conservation

ArcGIS® 9.0 was used.

McCullagh 1989) were used in this research in orderto predict the probability of species occurrences by
the environmental variables as limiting factors for2.2.3 Preparation for test and train data
Plotting 1861 species records, 25 records fell

species’ survival. The accuracy of the predictive

outside the study area. These records were discarded

models was measured using the test dataset by theso that the total number became 1836. From all

Kappa statistics (Landis and Koch 1977).

layers of environmental predictor variables, pixel
values were extracted for the geographic coordinates

2.4 Estimation of population size within habitat patchesof species’ presence and absence records by ArcMap

Based on the comparison of the predictive®

models, the predictive maps by the best modeling

Subsequently the dataset, containing species

algorithm for each species were chosen to estimate

presence-absence records, geographic coordinates,

the population size. The population of the target

and each environmental predictor’s value, was split

species was estimated based on known population

into a train and a test dataset. The train dataset wasdensity and area in km 2, derived by a following

used to make predictive models. Then, the test

equation.

9.0 ’s in-built function.

dataset was used to assess the accuracy of thesemodels. An independent dataset is ideal for testing

N=A*PDthe models. Thus for Asiatic black bear, all records in(Equation 1)

the South Alps were used for training and all records
in Fuji area were used for testing the models. By thiswhere N is estimated population (head-count),

method, also the model’s transferability can be tested

A is area (km2), and PD is population density (head-

whether models developed on one local population,

count/km2).

South Alps, can be applied to another neighboring
local population in Fuji. To maintain proportion of

2.5 Results and conclusion

presence and absence data, approximately the same

For bear, MaxEnt performed best with thenumber of records was taken from absence data forpredictor variables: altitude, distance to paths andtraining and testing. Because no independent datasetstone steps, distance to wide roads, and vegetation

for the Japanese serow was available, its records

cover types (Figure 2: above). GARP failed towere randomly partitioned into two subsamples. One

predict presence in Fuji. Its best GLM equation

subsample was used as the train dataset and anotherwas log(p/(1-p))=(-1.486e+01)+(7.335e-04)*distancesubsample was kept for testing models. This method

to paths and stone steps+(9.470e-03)*altitude. For

is known as “split-sample approach” (Guisan andserow’s distribution, GARP performed best with

Zimmermann 2000).

altitude, slope, distance to highways, distanceto general roads, distance to paths and stone
steps, distance to rivers, and NDVI (Figure 2:

2.3 ModelingThree modeling algorithms: GARP - Genetic

below). Its best GLM equation was log(p/(1-p))=Algorithm for Rule-set Production (Stockwell-5.91785430+0.04024136*slope+0.26478759*squareand Peters 1999), MaxEnt -Maximum Entropy

root of altitude. The estimated numbers of individuals(Phillips et al. 2006), and GLMs - Generalized Linear

for bear was 5~ 9 in Mt. Ashitaka, 51 ~ 102 in Fuji-

Models (logistic regression models) (Nelder andTanzawa, 160 ~ 320 in South Alps, 4 ~ 8 in Mt.

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Figure 2 Modelled distribution for Asiatic black bear (above) and Japanese serow (below)

Table 1 Estimated population size and needs assessment of ecological networks
Location
Asiatic black bear Mt. Ashitaka

30

5〜9

serious danger of extinction

Fuji and Tanzawa regions

340

51 〜 102

serious danger of extinction

South Alps region1066

160 〜 320

endangered

Mt. Kenashi

28

4〜8

serious danger of extinction

Izu Peninsula

28

4〜8

serious danger of extinction

HakoneJapanese serow

Area (km2) Estimated population Needs assessment of ecological networks

37

6 〜 11

serious danger of extinction

Fuji and Tanzawa regions

1581< 1581

healthySouth Alps region

537

< 537

healthyKenashi, 4~8 in Izu Peninsula, and 6~11 in Hakone;

GLM has good transferability. There is a need forfor serow, < 1581 were estimated in Fuji-Tanzawa,

ecological networks in Fuji-Tanzawa for bear, but not

and < 537 in other areas (Table 1). For bear MaxEnt

for serow.

and for serow GARP are the best algorithms, but

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3 Fieldwork for Asiatic Black Bear’s Ecology

localities and field signs. Whilst Tanaka-Way trap,

3.1 Introduction

a kind of a box trap, has a risk to make bears’ teeth

Fieldwork for Asiatic black bear’s ecologicalor mandible damage by biting barred door (Maida

research requires tremendous efforts as they inhabit1998), the double-barreled drum can is suitable forwide home range and steep mountainous area

the capture because that trap cannot be bitten. After(Japanese Mammals Society 1997). The ecological“a certificate to capture beasts and birds” was issued

research on the Asiatic black bear’s Tanzawa local

by Kanagawa Prefecture, traps were located on 13

population has rarely been published; to date, only

July 2008. We aimed to capture one bear before 15

one article on food habit investigation of Asiatic black

November 2008, the starting date of hunting. Inside ofbear by scatting analysis in Tanzawa was reported

traps, 0.5 little of honey was located as inducing food.

by Koyama et al. (1994). Therefore, it is necessary

Animal capture reporting systems were installed withto collect Asiatic black bear’s observation point data

the traps. When the reporting system was activated,

as primary sources. We have collected these data by

we went straight to the scene immediately. If not, we

locating field signs (bear’s net, scratch, droppings

went to field at least once a week regularly for visual(Figure 3: right), footprints, or hair). Also, we

confirmation.

attempted to capture few Asiatic black bears in order
to track individual ones by satellite tracking system

3.3 Immobilization and Release

which is described in section 4. In preparation for

An Asiatic black bear was found captured in a

tracking bears, the most substantially difficult work

trap on 7 October 2008. We carried out immobilization

is to capture a bear alive and release with a collar. In

and release of that bear on 8 October 2008 (Figure

this section, we introduce a methodology, which we

3: left). Firstly, for chemical immobilization, domitor-

succeeded to capture an Asiatic black bear alive andketamine mixture was dosed by a blowpipe. Secondly

released in a Tanzawa local population where is well-

the body of the Asiatic black bear was measured andknown as low population density of Asiatic black bear.

we recorded location, date, and sex. The captured
bear was female, 1.5 years old; the body length was
86cm; and the body weight was 14.5kg (The bear

3.2 Capturing strategy of the Asiatic black bear
The Asiatic black bear was captured by 2 traps ofwas named“MOMO”). Hair of bear and blood weredouble-barreled drum cans (Figure 3: middle). The

sampled for DNA analysis. We implanted a microchip

traps were set up in forests of surrounding Miyagase

in an ear for identification (ID is 968000005393497).

Lake in Kiyokawa-village, Kanagawa Prefecture,

We were planning to collar the bear with GPS-considering recently observed Asiatic black bear’s

ARGOS (920g), but because the body weight of the

Figure 3 Captured bear (left), trap of double -barreled drum cans (middle), and bear’s droppings (right)

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captured bear was not sufficient compared to the

4.2 Objectives

weight of the collar, we could not implement the

However, cases using GPS-ARGOS has been

tracking system. After we administered intravenous

rarely published. Till now very few cases havefluids, the bear was released naturally at the same

been reported; For instance Ito et al. (2006) reported

place it was captured.

Mongolian gazelle’s habitat use by using ARGOS
tracking system, but gazelle’s habitat is characterized

4 Testing Accuracy of GPS Using SatelliteTracking System for Collared Animals

by open grassland, which differs drastically from

4.1 Backgroundare characterized by steep terrain and high canopy

Japanese mountainous habitat. Mountains in JapanFor wildlife researchers, location data andclosure density. More investigation is needed to test

movement pattern of target animals is the mostwhether GPS-ARGOS can be useful for highly dense

essential information. Recently GPS telemetry has

canopy closure in forest with comparison in otherbecome an important wildlife research techniquetype of locations. The objective of this study is to(Jiang et al. 2008), because of its automatic andtest accuracy of GPS using satellite-tracking systemobjective method to collect location data and its(ARGOS; (CLS (Collecte Localisation Satellites)

high accuracy. For example, Garneau et al. (2008)2007)) in three perspectives of a) GPS fix, b) ARGOS

examined habitat use of GPS-collared black bears.

uplink, and c) activity sensor, in different habitat andMore recently, however, new ARGOS system,

location features. Considering the weight of GPS-

namely GPS collar with ARGOS uplink (hereinafter

ARGOS currently available (for instance, model

referred to as “GPS-ARGOS”), was developed; thisTGW-4580, Telonics Inc is 1100-1200g (Telonics Inc.

can collect highly accurate location data by GPS and2008)), medium or large mammals which inhabit

transmit collected data to satellites, such as NOAA

in forest are target species in this study. Thus, theor METOP (Figure 4). After data processing, data

ultimate objective of this study is to seek the potential

will be delivered to users through the ARGOS server,

applications for tracking terrestrial mammals, suche-mails, or CD-Roms.

as Asiatic black bear, Japanese serow, Sika Deer, orJapanese Macaque.
4.3 Fieldwork designs
We carried out an experiment using ARGOS
with GPS during 19 July to 15 August, 2008 in Japan.
The performance of a satellite transmitter (platform
terminal transmitter or PTT; model TGW-4580,
Telonics Inc.) with an Argos uplink was tested. The
PTTs were programmed (1) to collect location data
(latitude and longitude) recorded by its internal GPS,
temperature, altitude, and activity data, for every
4-hour per day and (2) to transmit above data throughFigure 4 GPS-ARGOS mechanisms

radio signals to satellites every 3-day for 6 hours.
For a comparison purpose, the location data was also
recorded with the combination of a digital camera

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Geospatial Approaches towards Biodiversity Conservation

Table 2 GPS fix rate and Test location features
Test location

A

B

C

D1

D2

Canopy closure (% )

86.91

62.61

10.85

0

0

Altitude (m)

502.8

80.4

120.2

134.8

105.88Temperature (degrees Celsius)

32

27

26

28

33

GPS fix rate (% )

88.9

97.7

92.0

88.9

44.4

GPS horizontal error (m)

60.38

45.36

55.33

53.97

34.79

GPS positional dilution

7.125

4.309

5.74

6.950

3.112

Average

A: Mountain surrounding Miyagase Lake, Tanzawa,
B: Experiment forest, Shonan Fujisawa Campus, Keio University,
C: Urban area at low altitude, Seya-ward, Yokohama City,
D: Open area; in front of railway station (D1) or on roof of building (D2)(model CAPLIO 500SE WL JPN L736-20, Ricoh Co.

University, the ARGOS uplink number per hourLtd.) and a bluetooth GPS receiver (model HI-408BT,

was 1.00. Most importantly for considering target

Haicom Electronics CORP). Forest canopy density

animal’s habitat, the test in a forest of Chamaecyparisand sky openness were estimated by photographs

obtuse showed fairly reasonable result, whose uplinktaken by a digital camera. Handy GPS (model eTrex

number per hour was 0.5.

Legend HCx,GARMIN Ltd.) was used to count the

As for the ARGOS uplink performance, generally

available satellite number for each GPS fix.

from the open area on a high building ARGOS
transmitting messages can be received successfully

4.4 Resultsby satellites, such as NOAA or METOP. Negative

4.4.1 GPS fix rate

movement effects for ARGOS uplink performance can

GPS fix success rate and location feature are

be neglected; because movement by a car does not

summarized (Table 2). Except location D2 (Opendecrease ARGOS uplink hit number. On the otherarea on roof of building) which scored 44%, GPS fix

hand, even in a forest of Chamaecyparis obtuse, whichrate was high, which has always been over 88%. In

is characterized as a place with dense forest canopy

general, GPS fix rate can be expected high in forests

closure, ARGOS uplink hit number does not decreaseof mountain with dense canopy closure though GPS

drastically. Of course, the success rate in a forest

horizontal error and GPS positional dilution increase

becomes lower compared to the one in open area.

compared to the other location.

From the average uplink number per hour, 3 times of
ARGOS uplink messages during 6 hours per day (every
3-day) can be expected to be received by satellites.

4.4.2 ARGOS uplink performance
When GPS-ARGOS was positionally-fixed on aroof of an apartment in an open area, the average

4.4.3 Activity value and activity type

ARGOS successful uplink number per hour was 1.16.

Distribution of activity values averaged per

When a GPS-ARGOS collar was fixed vertically on aminute is categorized according to activity types

front window of a car and moved by the car at speedrecorded in field. Distribution for each activity wasof 40km/h, average successful uplink number was

clearly distinguished. Mean of the activity value when

1.16 as well. On the other hand, in another open

GPS-AROGS was moving by car at speed of 40km/h

place on a roof of a building (4th floor), SFC, Keiowas 0.3667(Min. 0 to Max. 1.1000); while the one for

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walking at speed of 57m/min was 16.18 (Min. 2.75 toespecially of animal habitat conservation, should be

Max. 28.20) and the one for climbing mountain was

institutionalized. Nevertheless, knowledge on spatial

36.93 (Min. 36.14 to Max. 37.71). When GPS-ARGOS

distribution of animal habitat is obviously lack. In

was not moved at all, value was always 0.

order to address this problem, Doko et al. (2008)

Activity value can be classified into its activity

developed spatial distribution models for Asiatic

type: moving by car at speed of 40km/h, walking

black bear and Japanese serow to estimate coreat speed of 57m/min, climbing mountain, or noareas of habitats, and assessed the present needs for

movement. During field survey, the author expectedecological networks as a case study in Fuji-Tanzawa

that activity value of“moving by car at speed ofregion, Japan. This result suggests that the Asiatic

40km/h”could represent high speed of movement,

black bear needs newly created ecological networks

such as running. However, the GPS-ARGOS was fixed(Doko et al. 2008).

static on the automobile thus acceleration and angle

For an effective policy making, a spatially explicit

had kept almost always same. As a result, this activity

inter-operational platform is crucial. Recently withvalue was very low (mean was 0.3667) comparedfast advancement of the Internet and rapidly growing

to walking or climbing activity values. Consideringinterests lead a number of applications on a web-method how the activity sensor functions, it isbased decision support system (DSS) (for example,

concluded that“moving by car at speed of 40km/h”

see Repoussis et al. (2009)). The combination of DSS

cannot represent high speed of movement of animals.

and GIS (Geographic Information Systems) functions

On the other hand, this experiment showed thatcan provide the ordinary Internet users with aother activities: walking, climbing in mountain, nostrong spatial communication tool for biodiversity

movement, can be successfully classified with activity

conservation. Therefore we developed an integrated

value. Also, the distribution of activity value is very

Web-based GIS system, which can facilitate communi-

distinguishable; therefore this result can be used as

cation among local habitants, experts, ministries,classification method of activity type.

and local governments, in order to support a policy
making for conserving biodiversity.

4.5 Conclusions
As conclusion, performance of GP S collar using

5.2 Web-based GIS systemsatellite-tracking system (GPS -ARGOS) can be

5.2.1 System structure

expected to be a useful tracking system for terrestrial

The Web-based GIS system for conserving bio-

mammals, such as Asiatic black bear, Japanesediversity system was operated by Google Earth (GE)serow, Sika Deer, or Japanese Macaque.

and ArcIMS®.
Google Earth (GE) is an application which

5 Web-Based GIS Development as a
Policy Making Support System forConserving Biodiversity: Case Studyin Fuji-Tanzawa Region, Japan

enables the Internet users to view global geo-spatial

5.1 Introduction

multi-layer display, and seamless data view.

information by combining satellite imageries, aerial
photos, maps, geography, or 3D models. It is an
excellent GIS data viewer to enable spatial search,

In Japan, the third National Biodiversity

On the other hand, ArcIMS ® is the software

Strategy was adopted in 2007. Hence, measuresdeveloped by ESRI ®, which can structure maps, data,from the perspective of ecosystem conservation,and tools, and then can publish and deliver spatial

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Geospatial Approaches towards Biodiversity Conservation

data through the Internet. Thus, local and global

previous work (Doko et al. 2008).

users can share information and data efficiently.

In this study, because GE supports KML

ArcIMS components and architecture consist of web(Keyhole markup language) file format, shape files

servers and client applications.

were converted to KML by ArcMap ® 9.3. For data
management in ArcIMS ® , shape file and Erdas
Imagine file formats are compatible with ArcIMS ®,5.2.2 Data management
This paper takes Fuji-Tanzawa regions as athus no conversion of data format were necessary.

case study, which is contained in Kanagawa and
Shizuoka Prefecture, Japan. In order to facilitate

5.2.3 Basic functions

an inter-operational platform through Web-based

Basic functions of the system mainly contain

GIS system, various GIS data were needed to beview, zoom, pan, distance measuring, thematic

stored in the system. According to characteristics ofmapping, overlay multi-layers, query spatial search,data, we categorized spatial data into a) base-map,

visualize 3D view (GE only), and display seamlessb) environmental layers, and c) animal localities

imageries (GE only). Users can view attribute table(See Appendix for sources). For instance, as a)(such as name, object ID, temporal data, latitude andbase-maps, we prepared roads, administrative

longitude) by pointing out object spatially. Figure 6

boundaries, National Parks, Quasi-national Parks,

and Figure 7 present the top page of a Web-based GIS

buildings, satellite imageries, location name; for b)

system for conserving biodiversity using ArcIMS ®

environmental layers, altitude, slope, precipitation,

and Google Earth, respectively. This Web-based GIS

temperature, river streams, lakes, NDVI, vegetation

system is distributed freely via the Internet.

cover types; for c) animal localities, geo-tagged
photographs of fieldsigns, as well as core areas of

5.2.4 Utility and application

animal habitat, point data of animal field signs, andUsing this system, we can update, query, andtracked animal movement data. Full description on

analyze the situation of animal movement and habitat.

image-processing for spatial data was given in our

Figure 5 shows an example of Asiatic black

Figure 5 An example of Asiatic black bear’s movement

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位置情報計測技術の応用

Figure 6 Top page of a Web-GIS system [ArcIMS version]

Figure 7 Top page of a Web-GIS system [Google Earth version]

bear’s movement tracks and predicted habitat range

We can overlay many layers with satellite imageries

using ArcIMS. We can overlay multi-layers suchas background maps. Species information can beas tracked bear’s point localities, predicted bear’s

extracted by pointing out by mouse.

habitat, and tracked bear’s maximum home range, as
well as river streams. We can also identify each point

5.3 Conclusions

attribute table information, such as coordinates and

The Web-based GIS policy making support

species Scientific names, etc.

system for conserving biodiversity was developed

For instance, localities of Japanese serow’s

using Google Earth and ArcIMS®. This system can befieldsigns using Google Earth can be visualized.

expected to be useful to facilitate spatial information-

18

Geospatial Approaches towards Biodiversity Conservation

sharing with other Internet users, such as local

Osawa, Nihon University for financial assistance,

habitants, experts, ministries, and local governments,

Ms. Wenbo Chen, Keio University for assistance ofin order to support a policy making for conserving

fieldwork, image-processing and technical assistancebiodiversity.

for development of Web-based GIS system, Mr.

Future research and development of the system

Masayuki Nagasaka and Mr. Hidefumi Yatomi

will focus on 1) Participatory Geographic Informationof Cubic i Co., Ltd., and Ms. Fumiko Kasahara of

System (PGIS) so that authorized system users can

Nippon Kaiyo Co., Ltd for technical assistance for

input and edit data by themselves, and 2) display near

testing ARGOS system.

real-time movement of tracked Asiatic black bear(s).

6 Future Work

References

The following topics are expected to carry out in

Biodiversity Center of Japan, The National Survey on the Natural
Environment Report on the distributional survey of Japanese
animals (Mammals), Biodiversity Center of Japan, the Ministryof Environment, 232, 2004. (In Japanese)
CLS (Collecte Localisation Satellites)., “Argos User's Manual On
Line”, 2007, Retrieved 25 Oct., 2008, from http://www.argossystem.org/manual/.
Corsi, F., E. Dupre and L. Boitani, “A Large-Scale Model of Wolf
Distribution in Italy for Conservation Planning”, Conservation
Biology 13(1), 1999, pp.150-159.
Doko, T., A. Kooiman and A. G. Toxopeus, “Modeling of Species
Geographic Distribution for Assessing Present Needs for the
Ecological Networks. ISPRS 2008”, In Proceedings of the
XXIth ISPRS Congress, Beijing, China, ISPRS, 2008.
Garneau, D. E., T. Boudreau, M. Keech and E. Post, “Habitat use
by black bears in relation to conspecifics and competitors”,
Mammalian Biology - Zeitschrift fur Saugetierkunde, 73(1),2008, pp.48-57.
Guisan, A. and N. E. Zimmermann, “Predictive habitat distribution
models in ecology”, Ecological Modelling, 135, 2000, pp.
147-186.
Hashimoto, Y., M. Kaji, H. Sawada and S. Takatsuki, “Five-year
study on the autumn food habits of the Asiatic black bear in
relation to nut production”, Ecological Research, 18(5), 2003,
pp.485-492.
Huygens, O. C., T. Miyashita, B. Dahle, M. Carr, S. Izumiyama, T.
Sugawara and H. Hayashi, “Diet and feeding habits of Asiatic
black bears in the Northern Japanese Alps”, Ursus, 14(2), 2003,
pp.236-245.
Ito, T. Y., N. Miura, B. Lhagvasuren, D. Enkhbileg, S. Takatsuki,
A. Tsunekawa and Z. Jiang, “Satellite tracking of Mongolian
gazelles (Procapra gutturosa) and habitat shifts in their seasonalranges”, Journal of Zoology, 269(3), 2006, pp.291-298.
Japanese Mammals Society, Red Data: Japanese Mammals, Bunichi Co., Ltd, 1997. (In Japanese)
Jiang, Z., M. Sugita, M. Kitahara, S. Takatsuki, T. Goto andY. Yoshida, “Effects of habitat feature, antenna position,
movement, and fix interval on GPS radio collar performance inMount Fuji, central Japan”, Ecological Research, 23(3), 2008,
pp. 581-588.
Koyama, M. and K. Naganawa, “Food habits of Japanese black
bear in Tanzawa mountain area”, Journal of Japanese Forest
Research 105, 1994, pp. 538-542. (In Japanese)
Landis, R. and G. Koch, “The measurement of observer agreement
for categorical data”, Biometrics, 33, 1977, pp. 159-174.
MacArthur, R. H. and E. O. Wilson, The Theory of Island
Biogeography, Princeton University Press, 2001.
Maida, K., Prevent bears' nuisance by keeping them alive, Tokyo,

our project:*

Implement a censoring system to monitor thetraps in field of Asiatic black bears with remotecontrollable camera*

Carry out near-real time tracking on Asiatic
black bear(s) by GPS-ARGOS in order to collectprimary data as presence data in Tanzawa area*

Design ecological networks and evaluate thembased on several realistic scenarios in FujiTanzawa regions*

Improve a Web-based GIS system to facilitate 1)
Participatory Geographic Information System(PGIS) so that authorized system users can input
and edit data by themselves, and 2) display nearreal-time movement of tracked Asiatic blackbear(s).

Acknowledgements
This research was financed by the Grant-in-Aid
for Project by SFC Research Institute in 2007, Keio
University, Research promotion fund in remembranceof Mori Taikichiro in 2007 and 2008, Graduate School
Doctoral Students Grand-in-Aid Program 2008,
and Research Fellowships of the Japan Society for
the Promotion of Science for Young Scientists in2009. The authors would like to thank Dr. Satoshi

KEIO SFC JOURNAL Vol.9 No.1 2009

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特集

位置情報計測技術の応用

Rural Culture Association, 1998. (In Japanese)
Mochizuki, N., K. Sawai and T. Ohba, Report on investigationof the habitat of Asiatic black bear in Shizuoka Prefecture(1998~2002), Shizuoka Prefecture Forestry and Forest Products
Research Institute, 2005. (In Japanese)
Nelder, J. A. and P. McCullagh, Generalized Linear Models,
Chapman & Hall/CRC, 1989.
Ohba, T., “Questionnaire Investigation about the Distribution of Sike
Deer and Japanese Serow, and about the Population Condition,
the Crops and Vegetation Damage, the Hunting, etc. of the Sika
Deer in Shizuoka Prefecture”, In Research Report by Shizuoka
Prefecture Forestry and Forest Products Research Institute(translated by author), 30, 2002, pp.1-16. (In Japanese)
Okumura, T., Takii, Koike and Hazumi, “Asiatic black bear's
distribution and an issue of roadkill surrounding Mt. Fuji”, Wildlife
Conservation Society, 8(3), 2003, pp.74-75. (In Japanese)
Pearson, R. G. and T. P. Dawson, “Predicting the impacts of climatechange on the distribution of species: are bioclimate envelopemodels useful? ”, Global Ecology & Biogeography, (12), 2003,
pp.361-371.
Phillips, S. J., R. P. Anderson and R. E. Schapire, “Maximum entropy
modeling of species geographic distributions”, EcologicalModelling, 190, 2006, pp.231-259.
Repoussis, P. P., D. C. Paraskevopoulos, G. Zobolas, C. D. Tarantilis
and G. Ioannou, “A web-based decision support system for
waste lube oils collection and recycling”, European Journal ofOperational Research, 195(3), 2009, pp.676-700.
Stanners, D. and P. Bourdeau, Europe’s Environment. The Dobrís
Assessment. Copenhagen, European Environment Agency, 1995.
Stockwell, D. R. B. and D. Peters, “The GARP modelling system:
problems and solutions to automated spatial prediction”, Int. J.
Geographical Information Science, 13(2), 1999, pp.143-158.
Telonics Inc., “GEN 4 GPS Subsystems”, 2008, Retrieved 27 Oct.
2008, from http://www.telonics.com/products/gps4/.
Yamaguchi, Y., M. Nakamura and N. Watanabe, “Distribution ofJapanese serow Capricornis crispus in Tanzawa Mountains,
Kanagawa Prefecture”, BINOS, 5, 1998, pp.23 -30. (InJapanese)

Appendix
Following is spatial data sources used for modelling and Web-based
GIS:
The CGIAR Consortium for Spatial Information. “SRTM (Shuttle
Rader Topography Mission)”, http://srtm.csi.cgiar.org/
SELECTION/inputCoord.asp (accessed April 2008).
Geographical Survey Institute of Japan, 2006. “Download of the
Global Map Japan Version 1”, http://www1.gsi.go.jp/geowww/
globalmap-gsi/download/index.html (accessed April 2008).
WorldClim, “WorldClim Version 1.4”, http://www.worldclim.org/(accessed April 2008).
The National Land Agency, 2003. Digital Map 25000 (Spatial Data
Framework) KANAGAWA/ SHIZUOKA (CD-Rom).
Earth Science Data Interface, “GLCF: Earth Science Data Interface”,
http://glcf.umiacs.umd.edu/data/ (accessed April 2008).
Nature Conservation Bureau in Ministry of the Environment, 1997.
14 KANAGAWA/22 SHIZUOKA The dataset for GIS on the
Natural Environment, Japan. Nature Conservation Bureau in
Ministry of the Environment (CD-Rom).

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