Th F t f GIS d S ti lThe Future of GIS and Spatial Analyses in Fisheries:Analyses in Fisheries:  

Challenges and Opportunities

Willi L Fi hWilliam L. Fisher

U S Geological SurveyOklahoma Coop Fish and Wildlife Research Unit

Oklahoma State University

Presentation OutlinePresentation Outline

k d• Background– History– Evolution

• Review: applications, challenges, opportunitiesReview: applications, challenges, opportunities– Marine ecosystemsInland freshwater ecosystems– Inland freshwater ecosystems

– Aquaculture

F• Future– Challenges and opportunities

Background of GIS/SABackground of GIS/SA

Old World MapOld World Map

Future PerspectiveFuture Perspective

• The future is only a projection, missing many details. – Joseph J. Dewey

Model of Fisheries GIS/SAORGANISMS

/

Maps of pspecies 

distributions

Overlay Overlay

GIS/SA

Maps of habitat 

Maps of fishing 

Overlay

/

conditionsg

effort

HABITATS PEOPLEFisher (2004)

History of GIS/SAy /

1st international1960s – Birth of GIS1970s – Computer mapping 1 international 

fisheries GIS/SA  symposium

1970s  Computer mapping1980s – Spatial database management1990s – Map analysis and modeling2000s Multimedia mapping

1st fisheries

symposium2000s – Multimedia mappingBerry (2007) Beyond Mapping III

Canadian GIS

1 fisheries GIS publication

GPSGIS GPS

Landsat Radarsat

1960 19801970 20001990

Landsat Radarsat

1960 19801970 20001990

Fisheries GIS/SA PublicationsFisheries GIS/SA Publications

40

50

ons 300

350

ons

30

40

publ

icat

io

200

250

publ

icat

io

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mbe

r of p

100

150

mul

ativ

e p

0

10

Num

0

50 Cum

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

Meaden (2001) Fisher (2007)Meaden (2001)                 Fisher (2007)

Evolution of GIS/SAEvolution of GIS/SA

“GIS technology has evolved from a softwareGIS technology has evolved from a software tool used in computer labs to a common language that our global society is using tolanguage that our global society is using to communicate, collaborate, and make better 

b l ”decisions about our planet.”

28th ESRI International User Conference

Evolution of GIS/SAEvolution of GIS/SA

Holland (2005) ArcUser

Mega technologiesMega‐technologies

Three most important emerging and evolving fields in the 21st centuryevolving fields in the 21 century

1 Biotechnology1. Biotechnology

2. Nanotechnology

3. Geotechnology

Gewin (2004) Nature

Geotechnology Community EvolutionGeotechnology Community Evolution

(RS, GIS, GPS, WWW)

Berry (2007) Beyond Mapping III

Review of GIS/SAReview of GIS/SA

Future PerspectivesFuture Perspectives

• The future is only a projection, missing many details. – Joseph J. Dewey

• There is (are) no data on the future. – Laurel Cutler

MethodsMethods

R i d GIS/SA bli ti• Reviewed GIS/SA publications– Primary literatureSymposia proceedings– Symposia proceedings

– Organization/agency reports– Industry magazines– Industry magazines

• Queried other GIS/SA keynote speakers– Geoff Meaden– Geoff Meaden– Pepe AguilarManjarrez– Jim KapetskyJim Kapetsky

• Attended recent GIS/SA meeting/symposium– American Fisheries SocietyAmerican Fisheries Society

Spatial Analyses in Fisheries GISSpatial Analyses in Fisheries GIS

Nishida and Booth (2001) Fisher (2007)

StatisticalQUANTITATIVE ANALYSES

Non‐statisticalMultiple Parameter

Single Parameter

QUALITATIVE ANALYSES Multiple 

Parameter

Single Parameter

Marine Ecosystems: ApplicationsMarine Ecosystems: Applications

• Mapping

• Site selectionSite selection

• Vessel monitoring

• Distribution and abundance patterns

• Species‐environmental relationshipsSpecies environmental relationships

• Modeling and forecasting catch and harvest

• Manage marine conservation areas

Marine Ecosystems: MappingMarine cosystems: Mapping

• Objective: Assess efficacy  Side‐scanj yof sides‐can sonar, image classification & GIS to 

Side scan sonar map

map sea floor bottom

• Analysis: UnsupervisedAnalysis: Unsupervised classification 20 spectral classesclasses

• Results: Classified 9bottom habitat typesbottom habitat types, weakly correlated with 2 fish species occurrence

Bottom habitat type 

Lathrop et al. (2006) Estuarine, Coastal & Shelf Sci

fish species occurrence map

Marine Ecosystems: Modelingy gAcoustic survey

Trawl• Objective: Estimate Station

jbiomass and distribution of herrings with acoustic gsurveys and trawling

• Analysis: Omni‐

Atlantic thread herring Scaled herring

Analysis: Omnidirectional spherical variograms krigingvariograms, kriging

• Results: Spatial structure of 4 herrings

ScadRound sardinella

structure of 4 herrings related to temperatureupwellingsPáramo and Roa (2003) Fish Res

upwellings

Marine Ecosystems: Web GISMarine Ecosystems: Web GISNational Estuaries Restoration Inventory: web portalNational Estuaries Restoration Inventory: web portal

http://neri.noaa.gov

Marine EcosystemsMarine Ecosystems

• Challenges and Opportunities*– Fishery‐based or area‐based managementy g

– Cooperation or competition among fishery groups

Different boundaries: spatial research– Different boundaries:  spatial, research, management, social

f / i l– Loss of GIS/SA specialness

– Lack of awareness of GIS/SA availability, capability and potential for spatially‐based management

*Geoff Meaden

Freshwater Ecosystems: ApplicationsFreshwater Ecosystems: Applications

• Mapping

• Site selectionSite selection

• Distribution and abundance patterns

• Species‐environmental relationships

• Habitat modeling at multiple spatial scalesHabitat modeling at multiple spatial scales

• Catchment conservation and management

Freshwater Ecosystems: ModelingFreshwater Ecosystems: Modeling

(a)(a)Obj ti Id tif ti lSampling unit

2

120 m

(a)

22 22

120 m120 m120 m

(a)

2222

• Objective: Identify spatial patterns of river minnows at two spatial scales 1

3

Rs

Dis4

F

11

333

Rs

Dis4

Rs

Dis44

F

two spatial scales

• Analysis: GLM, CHLOE (moving window analysis)

(b)

Refuge/resting habitat (Rs)Feeding habitat (Fj)

Sampling unit (i)

Spawning habitat

Rs

Fs

(b)

Refuge/resting habitat (Rs)Feeding habitat (Fj)

Sampling unit (i)

Spawning habitat

Refuge/resting habitat (Rs)Feeding habitat (Fj)

Sampling unit (i)

Spawning habitat

Rs

Fs(moving window analysis) ANAQUALAND (hydrographic distance)

Feeding habitat patch

Rs

Djs 7Djs

Rs

Djs 77Djs

(hydrographic distance)

• Results: Supplementation for feeding habitat patches and

50 m

N

5

Fj

Fs

Djs 6

50 m

N

55

Fj

Fs

Djs 66

feeding habitat patches and complementation with spawning habitat patches.

Le Pichon et al. (2006)

spawning habitat patches. Variables used to evaluate the spatial 

structure of sampling units at two scales

Freshwater Ecosystems: ModelingFreshwater Ecosystems: Modeling

• Objective: Develop spatial statistical models for stream networks

• Methods: kernel (moving average function), kriging

• Results: Predict at esu s ed c aunsampled locations using stream flow and gstream distance

VerHoef et al. (2006) Environ Ecol Stat Predicted chemical concentrationslg circle = actual, sm circle = predict, shaded = std err

Freshwater Ecosystems: Web GISFreshwater Ecosystems: Web GIS

http://www.niwa.cri.nz/rc/freshwater/fishatlas

Freshwater EcosystemsFreshwater Ecosystems

• Challenges and Opportunities– Sparse data and collectionsp

– Geostatistical and distributional modeling of fishes

Remote sensing and sensor networks– Remote sensing and sensor networks

– Spatially‐explicit fish population modeling

– Global climate change and predicted species distributions

Aquaculture: ApplicationsAquaculture: Applications

• Mapping

• Site suitability and selectionSite suitability and selection

• Inventory and monitoring

• Assess environmental impacts

• Strategic planningStrategic planning

Aquaculture: ModelingAquaculture: Modeling 

BackgroundNot suitableMarginally suitable

• Objectives:  Assess carp farming potential using 

g yModerately suitableVery suitableGIS

• Analysis: Multi Criteria Evaluation with weighted linear combinations

• Results: 58% of the area very and moderately 

Suitable sites for carp farm development in Barhatta Upazilla, Bangladesh.

y ysuitable for carp culture

Salam et al. (2004) Aquaculture

Aquaculture: Web GISAquaculture: Web GIS

http://www.fao.org/fishery/gisfish/index.jsp

Aquaculture: Web GISAquaculture: Web GIS

http://pdacrsp.oregonstate.edu/

AquacultureAquaculture

• Challenges and Opportunities*– Involvement of administrators in GIS deploymentp y

– Communication & collaboration among organizations & institutions about GISorganizations & institutions about GIS

– Employing GIS in developing countries

i i– More GIS training

– Limited availability of GIS data

– Socio‐economic GIS studies

– Free and open source GIS/SA softwareFree and open source GIS/SA software*Pepe AguilarManjarrez & Jim Kapetsky

Future of GIS/SAFuture of GIS/SA

New World map

Future PerspectivesFuture Perspectives

• The future is only a projection, missing many details. – Joseph J. Dewey

• There is (are) no data on the future. – Laurel Cutler

• The future is only the past again, entered through another gate. – Arthur Wing Pinero

Cycles of GIS/SACycles of GIS/SA

Berry (2007) Beyond Mapping III

Challenges and OpportunitiesChallenges and Opportunities

• Multidimensional GIS

• Sensors and networks• Sensors and networks

• GeoWeb

Multidimensional GISMultidimensional GIS

Dimensions

• 2D: x (easting), y (northing)2D:  x (easting), y (northing)

• 3D:  x, y, z (altitude)

• 4D:  x, y, z, t (time) ~ animation

Multidimensional GISMultidimensional GIS

S i i id d li• Static coincidence modeling– Cartesian system 

– 2D square grid

– 3D cube– 3D cube

• Dynamic flows modeling – Hexagonal systemg y

– 2D hexagon grid

3D polyhedron– 3D polyhedron Berry (2007) GeoWorld

Multidimensional GISMultidimensional GIS

• Dynamic flows modeling– Track movements over space and time in 3D pgeographic space

– Current 2D applicationsCurrent 2D applications• Transportation patterns and traffic simulation

• Hazard evacuation planning• Hazard evacuation planning

– Potential 3D applicationsRi fl d i l i• River flood simulation

• Fish movements

Sensors and NetworksSensors and Networks

• Types– Wireless sensor networks

– Global sensors

GPS enabled mobile devices– GPS‐enabled mobile devices

• Provide– Real‐time, wireless geospatial data

– Location‐based contentLocation based content

Wireless Sensor NetworksWireless Sensor Networks

3D underwater acoustic sensor networkhttp://www.ece.gatech.edu/research/labs/bwn/UWASN/index.html

Global Sensor NetworksGlobal Sensor Networks

http://nosa.noaa.gov

Global Sensor NetworksGlobal Sensor NetworksOceanic and Atmospheric Research network

http://nosa.noaa.gov

GPS enabled Mobile DevicesGPS‐enabled Mobile Devices

• Cell phones with GPS & camera

Photo tag of fly fisherman in Ithaca, NY

GeoWebGeoWeb

• “GeoWeb” or Geospatial Web – ability to locally/globally integrate and share geospatial y g y g g pinformation via the Internet.

• “Neogeography” – use of geographical techniques and tools for personal and community activities or for utilization by acommunity activities or for utilization by a non‐expert group of users.

Wikipedia (2008)

GeoWebGeoWeb

Use

Serve

AuthorAuthor

ContentMaps, Data, Models

Dangermond (2007) ArcNews

GeoWeb: PortalsGeoWeb: Portals

http://www.fao.org/fishery/gisfish/index.jsp

GeoWeb: Google OceanGeoWeb: Google OceanSea Surface Temperature ‐ 24 Aug 08p g

GeoWeb: Google EarthGeoWeb: Google EarthUser‐created content:  photo of cast netting, Rio de Janeiro, Brazil

GeoWebGeoWeb

Is resulting in…• Democratization of GIS• Democratization of GIS

• Geospatial citizen science

• Ubiquitous, real‐time, accurate geospatial informationinformation

• Geospatially‐enabled social networking

• Caution: issues of privacy, confidentiality, propriety, integrityp p y, g y

Future PerspectiveFuture Perspective

• The future is only a projection, missing many details. – Joseph J. Dewey

• There is (are) no data on the future. – Laurel Cutler

• The future is only the past again, entered through another gate. – Arthur Wing Pinero

• The most profound revolutionary technologies are those that disappear –Mark Weiserare those that disappear  Mark Weiser

Fisheries GIS/SA Community EvolutionFisheries GIS/SA Community Evolution

(RS, GIS, GPS, WWW)

Berry (2007) Beyond Mapping III

Evolution of Fisheries GIS/SAEvolution of Fisheries GIS/SA

Fisheries GIS/SA

Holland (2005) ArcUser

/

Thank youThank you