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Case Study of the ArcGIS Marine Data Model: Examining Habitat Utilization Patterns of Reef Fish Along the West Coast of Hawaii Alyssa Aaby, OSU Dawn Wright,

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Presentation on theme: "Case Study of the ArcGIS Marine Data Model: Examining Habitat Utilization Patterns of Reef Fish Along the West Coast of Hawaii Alyssa Aaby, OSU Dawn Wright,"— Presentation transcript:

1 Case Study of the ArcGIS Marine Data Model: Examining Habitat Utilization Patterns of Reef Fish Along the West Coast of Hawaii Alyssa Aaby, OSU Dawn Wright, OSU Brian Tissot, WSU ESRI UC 2004 Photos from

2 2 Outline Background Background Part 1: The ArcGIS Marine Data Model (MDM) Part 1: The ArcGIS Marine Data Model (MDM) Research QuestionsResearch Questions MethodsMethods ResultsResults Part 2: Habitat Analysis Part 2: Habitat Analysis Research QuestionsResearch Questions MethodsMethods ResultsResults Discussion and Conclusion Discussion and Conclusion

3 3 Marine Resource Management Marine resources are at risk (eg. Leslie et al., 2003, Mumby et al., 2001, Puniwai et al., 2003) Marine resources are at risk (eg. Leslie et al., 2003, Mumby et al., 2001, Puniwai et al., 2003) Growing interest in Marine Protected Areas (MPAs) Growing interest in Marine Protected Areas (MPAs) Management toolManagement tool Effective both ecologically and economically (eg. Carr et al., 2003, Friedlander and Brown, 2003, Tissot et al., 2004)Effective both ecologically and economically (eg. Carr et al., 2003, Friedlander and Brown, 2003, Tissot et al., 2004)

4 4 Marine Resource Management How can we make MPAs as effective as possible? How can we make MPAs as effective as possible? Identify areas with patterns of high habitat utilization

5 5 Two Main Questions Question 1: What is the habitat utilization of specific fish species at a coarse-scale? Question 1: What is the habitat utilization of specific fish species at a coarse-scale?

6 6 Two Main Questions Question 1: What is the habitat utilization of specific fish species at a coarse-scale? Question 1: What is the habitat utilization of specific fish species at a coarse-scale? To answer question, use ArcGIS MDMTo answer question, use ArcGIS MDM

7 7 Two Main Questions Question 1: What is the habitat utilization of specific fish species at a coarse-scale? Question 1: What is the habitat utilization of specific fish species at a coarse-scale? To answer question, use ArcGIS MDMTo answer question, use ArcGIS MDM Use real data to test model itselfUse real data to test model itself

8 8 Two Main Questions Question 1: What is the habitat utilization of specific fish species at a coarse-scale? Question 1: What is the habitat utilization of specific fish species at a coarse-scale? To answer question, use ArcGIS MDMTo answer question, use ArcGIS MDM Use real data to test model itselfUse real data to test model itself Question 2: How well does the MDM meet the needs of the marine GIS community? Question 2: How well does the MDM meet the needs of the marine GIS community?

9 9 Conceptualizing the MDM Building industry-specific data models for ArcGIS Building industry-specific data models for ArcGIS In 2001, researchers decided to create a model specifically for the marine community In 2001, researchers decided to create a model specifically for the marine community The ArcGIS Marine Data Model The ArcGIS Marine Data Model

10 10 What is the MDM? A geodatabase template A geodatabase template A new way to spatially model marine data A new way to spatially model marine data A database used to assemble, store and query data A database used to assemble, store and query data Model that captures the behavior of real-world objects Model that captures the behavior of real-world objects

11 11 Why use the MDM? 1. Standardized template Implement project Implement project Organize data Organize data 2. GIS and data management Easy to share Easy to share Build upon Build upon 3. Querying ability 4. Object orientation

12 12 Outline Background Background Part 1: The Marine Data Model (MDM) Part 1: The Marine Data Model (MDM) Research QuestionsResearch Questions MethodsMethods ResultsResults Part 2: Habitat Analysis Part 2: Habitat Analysis Research QuestionsResearch Questions MethodsMethods ResultsResults Discussion and Conclusion Discussion and Conclusion

13 13 Testing the ArcGIS Marine Data Model: 3 Goals Case study tested 3 goals (Wright et al, 2002): Goal 1: Assembling, managing, and querying in ArcGIS Goal 2: Provide a template Goal 3: Improve the understanding of geodatabase models

14 14 Outline Background Background Part 1: The Marine Data Model (MDM) Part 1: The Marine Data Model (MDM) Research QuestionsResearch Questions MethodsMethods ResultsResults Part 2: Habitat Analysis Part 2: Habitat Analysis Research QuestionsResearch Questions MethodsMethods ResultsResults Discussion and Conclusion Discussion and Conclusion

15 15 Methodology Goals 1 and 2: Goals 1 and 2: Data GatheredData Gathered FormattingFormatting ImportingImporting QueryingQuerying Goal 3 Goal 3 Tutorial createdTutorial created

16 16 Data Gathered West Hawaii Aquarium Project (WHAP) (Tissot et al., 2004) West Hawaii Aquarium Project (WHAP) (Tissot et al., 2004) Coral Reef Assessment and Monitoring Program (CRAMP) (Brown et al., 2004) Coral Reef Assessment and Monitoring Program (CRAMP) (Brown et al., 2004) State of Hawaii’s Division of Aquatic Resources (DAR) (DAR, 2004) State of Hawaii’s Division of Aquatic Resources (DAR) (DAR, 2004) Saving Maui’s Reefs project (Brown, 1998) Saving Maui’s Reefs project (Brown, 1998) Individual peer-reviewed journal articles Individual peer-reviewed journal articles Date, sites, method, frequency, infoDate, sites, method, frequency, info

17 17 Formatting: Getting Data into the MDM Formatting data to fit MDM template MS Access Portion of MDM

18 18 Importing: Personalizing the MDM Adding fields to the feature classes, tables Adding fields to the feature classes, tables Adding new tables and relationships Adding new tables and relationships Attention to detail required Attention to detail required Worth it in the end! Worth it in the end! Can add new fields

19 19 Database Set Up Table NamesSurvey Location (Survey Point) DivemasterRunDetailSpecies Information (Integrated Species) Information stored in each table SurveyID Reference location Latitude Longitude Island Site Area_Desc Depth Comments Reference location Transect_Co TransectRunID Transect Date Time Observer Source Transect_Co TaxonID Count Size Comments TaxonID EBrownID TaxonName Alpha Type Family FamCode Quest DAR Synomyn HawaiiName CommonName Trophic Status

20 20

21 21 Querying

22 22 Goal 3: Improve Understanding of Geodatabase Model Benefits of MDM Benefits of MDM The MDM Tutorial The MDM Tutorial Response Response

23 23 Outline Background Background Part 1: The Marine Data Model (MDM) Part 1: The Marine Data Model (MDM) Research QuestionsResearch Questions MethodsMethods ResultsResults Part 2: Habitat Analysis Part 2: Habitat Analysis Research QuestionsResearch Questions MethodsMethods ResultsResults Discussion and Conclusion Discussion and Conclusion

24 24 GoalsResults Goal 1: Common structure for assembling, managing, and querying in ArcGIS Met Goal 2: Provide a templateMet Goal 3: Improve the understanding of the Geodatabase model Met Results: Goals

25 25 Outline Background Background Part 1: The Marine Data Model (MDM) Part 1: The Marine Data Model (MDM) Research QuestionsResearch Questions MethodsMethods ResultsResults Part 2: Habitat Analysis Part 2: Habitat Analysis Research QuestionsResearch Questions MethodsMethods ResultsResults Discussion and Conclusion Discussion and Conclusion

26 26 Habitat Utilization 1. What is the habitat utilization pattern of selected fish species at a coarse-scale? 2. Can fine-scale substrate info be correlated to coarse-scale habitat info? 3. Does depth play a role in the location of coarse-scale habitat types?

27 27 Outline Background Background Part 1: The Marine Data Model (MDM) Part 1: The Marine Data Model (MDM) Research QuestionsResearch Questions MethodsMethods ResultsResults Part 2: Habitat Analysis Part 2: Habitat Analysis Research QuestionsResearch Questions MethodsMethods ResultsResults Discussion and Conclusion Discussion and Conclusion

28 28 Done with the MDM

29 29 Fish Analysis done with MDM Select WHAP data Select WHAP data Determined site location in each habitat type and zone Determined site location in each habitat type and zone

30 30 Sites classified by Habitat and Zone Habitat Type Reef/Aggregate Coral (RA) Reef/Colonized Volcanic Rock/Boulder (RCB)No data LocationAnaehoomaluKalahiki BeachHonokohau KeawaikiKamilo GultchHookena (Auau) KeeiKaupulehuMakalawena N. KeauhouKealakekua BayManuka S. Oneo BayKeopukaOmakaa Red HillKualanui PtWawaloli Waiakailio BayLapakahiWawaloli Beach Papawai Puako Zone: All sites with data were located in the shelf zone, with the exception of Puako which was located in the fore-reef zone.

31 31 Querying to Determine Fish Location

32 32 Logistic Regression Analysis Fish Species Percentage of species found in RA habitat type Percentage of species found in RCB habitat type N (absent)Y (present)N (absent)Y (present) Acanthurus triostegus Ctenochaetus strigosus Scarus dubius Scarus psittacus Zebrasoma flavescens01000 Chaetodon ornatissimus01000 Chaetodon quadrimaculatus** Forcipiger spp Acanthurus achilles01000 Naso lituratus01000 Paracirrhites arcatus01000 Paracirrhites foresteri01000 Acanthurus nigrofuscus01000

33 33 Can fine-scale substrate info be correlated to coarse-scale habitat info?

34 34 Substrate Results Substrate type RA Mean % Cover (SD) RCB Mean % Cover (SD) P Boulder0.29 (0.59)2.26 (3.92)0.153 Porites compressa 34.9 (13.6)12.2 (11.1)0.004* Porites lobata (9.97)33.1 (8.96)0.059 Pocillopora meandrina (0.44)0.88 (1.87)0.277 Rubble 6.73 (6.23)7.14 (6.68)0.897 Sand 0.92 (1.77)7.00 (10.9)0.117 Dead Coral 28.6 (10.1)32.3 (17.6)0.601

35 35 Does depth play a role in the location of coarse-scale habitat types? Study SiteHabitat TypeDepth (ft) Anaehoomalu RA32.00 Kealakekua Bay RCB32.00 Puako BayRCB32.00 PapawaiRCB34.00 KeopukaRCB35.00 Kualanui Pt.RCB36.00 S. Oneo BayRA37.00 Ke'eiRA39.00 Hookena (Kalahiki) RCB39.00 Kamilo Gultch RCB40.00 LapakahiRCB40.00 Ka'upulehu RCB42.00 Waiakailio BayRA45.00 Keawaiki RA46.00 N. KeauhouRA46.00 Red HillRA47.00 Mean depth for RCB habitat type is 37 +/- 3.65ft Mean depth for RCB habitat type is 37 +/- 3.65ft Mean depth for RA habitat type is /- 5.77ft Mean depth for RA habitat type is /- 5.77ft

36 36 Does depth play a role in the location of coarse-scale habitat types? P=0.088 P=0.088 Trend indicates that RA habitat occur deeper than RCB Trend indicates that RA habitat occur deeper than RCB

37 37 Outline Background Background Part 1: The Marine Data Model (MDM) Part 1: The Marine Data Model (MDM) Research QuestionsResearch Questions MethodsMethods ResultsResults Part 2: Habitat Analysis Part 2: Habitat Analysis Research QuestionsResearch Questions MethodsMethods ResultsResults Discussion and Conclusion Discussion and Conclusion

38 38 Discussion: Habitat Analysis Regional Habitat Utilization Patterns? A. WHAP Fish Info B. Coarse-scale NOAA habitat info C. Fine-scale WHAP substrate info 1. How do specific fish utilize coarse- scale habitats? A: Inconclusive 2. Can fine-scale substrate info be correlated to coarse- scale habitat types? A: Yes, PC (p<.05) in RA and a strong trend with PL (p=.059) in RBC 3. Does depth play a role in the location of RA and RCB habitat types? A: Strong trend, p=.088 Future research: Tie fine-scale substrate info be tied to specific fish?

39 39 Conclusions: Management Use information from this study to evaluate current protected areas Use information from this study to evaluate current protected areas For example: For example: RA habitat shows trends toward being located deeperRA habitat shows trends toward being located deeper P. compressa is found significantly more often in RA habitatP. compressa is found significantly more often in RA habitat P. compressa provides and important habitat for yellow tang (Tissot et al., 2003, Dollar, 1982)P. compressa provides and important habitat for yellow tang (Tissot et al., 2003, Dollar, 1982) Thus, to protect the yellow tang, must have protected areas that extend into deeper watersThus, to protect the yellow tang, must have protected areas that extend into deeper waters Consistent with study that MPA encompassing range to depth values shown to be more efficient for yellow tang (Tissot et al, 2004)Consistent with study that MPA encompassing range to depth values shown to be more efficient for yellow tang (Tissot et al, 2004)

40 40 Discussion Through habitat analysis: Through habitat analysis: Goal 1: MetGoal 1: Met Goal 2: MetGoal 2: Met Goal 3: MetGoal 3: Met

41 41 Discussion: Ideal User? MDM is tailored to a specific user: DataData Amount Amount Variety Variety Time Time Cost Cost Experience of userExperience of user Experienced GIS—use object-orientation Experienced GIS—use object-orientation Inexperienced—use template Inexperienced—use template

42 42 Conclusions The MDM is a powerful tool The MDM is a powerful tool Information to aid managers evaluate the West Coast MPAs Information to aid managers evaluate the West Coast MPAs Future research Future research Data to HNHPData to HNHP

43 43 Thanks to: All the Rogues in Davy Jones All the Rogues in Davy Jones The Hawaii Natural Heritage Program The Hawaii Natural Heritage Program DAR, WHAP, CRAMP, and Saving Maui’s Reefs for letting me use their data DAR, WHAP, CRAMP, and Saving Maui’s Reefs for letting me use their data

44 44 Questions? For more information on the marine data model go to: For more information on the marine data model go to:http://dusk.geo.orst.edu/djl/arcgis/

45 45

46 46

47 47 Habitat Utilization Analysis Regional Habitat Utilization Patterns? (A) WHAP Fish Info (B) coarse-scale NOAA habitat info (C) fine-scale WHAP substrate info 1.What is the habitat utilization pattern of selected fish species at a coarse-scale? 2. Can fine-scale substrate information be correlated to coarse-scale habitat types? 3. Does depth play a role in the classification of RA and RCB habitat types?

48 48 The 13 reef fish analyzed Aquarium Fish Acanthurus achilles (Achilles Tang) Chaetodon ornatissimus (Ornate Butterflyfish) Chaetodon quadrimaculatus (Foursport Butterflyfish) Forcipiger spp (eg., Longnose Butterflyfish) Naso lituratus (Orangespine Unicornfish) Zebrasoma flavescens (Yellow Tang) Non-aquarium fish Acanthurus nigrofuscus (Brown surgeonfish) Acanthurus triostegus (Convict surgeonfish) Ctenochaetus strigosus (Striated surgeonfish) Paracirrhites arcatus (Arc-eye hawkfish) Paracirrhites foresteri (Blackside hawkfish) Scarus dubius (Regal parrot) Scarus psittacus (Common parrotfish) All photos from

49 49 Statistical Analysis Porites lobata (lobe coral) p=.059 Porites lobata (lobe coral) p=.059 Shows strong trends toward being found in RCB relative to RA Shows strong trends toward being found in RCB relative to RA Porites compressa (finger coral) P=.004 Porites compressa (finger coral) P=.004 Significantly more abundant in RA relative to RCB Significantly more abundant in RA relative to RCB

50 50 What is the habitat utilization pattern of selected fish species at a coarse-scale? fine vs. coarse-scale habitat information fine vs. coarse-scale habitat information Importance Importance Habitat utilizationHabitat utilization ManagementManagement ?

51 51 Can fine-Scale Substrate Info be Correlated to coarse-Scale Habitat Info? fine-scale WHAP substrate information Importance: CostCost TimeTime InformationInformation ?

52 52 Study SiteHabitat TypeDepth (ft) Anaehoomalu RA32.00 Kealakekua Bay RCB32.00 Puako BayRCB32.00 PapawaiRCB34.00 KeopukaRCB35.00 Kualanui Pt.RCB36.00 S. Oneo BayRA37.00 Ke'eiRA39.00 Hookena (Kalahiki) RCB39.00 Kamilo Gultch RCB40.00 LapakahiRCB40.00 Ka'upulehu RCB42.00 Waiakailio BayRA45.00 Keawaiki RA46.00 N. KeauhouRA46.00 Red HillRA47.00 Importance: Importance: ManagementManagement Does depth play a role in the classification of coarse-scale habitat types?

53 53 Why use the MDM Model? Why a data model? 1. Standardized template Implement project Organize data 2. GIS and data management Easy to share Build upon 3. Querying ability 4. Object orientation

54 54


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