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COLONY GIS: A NEW APPROACH TO MAPPING AND ANALYZING POPULATION PRODUCTIVITY Cortney Pylant and Falk Huettmann EWHALE Lab Inst. of Arctic Biology Dept.

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Presentation on theme: "COLONY GIS: A NEW APPROACH TO MAPPING AND ANALYZING POPULATION PRODUCTIVITY Cortney Pylant and Falk Huettmann EWHALE Lab Inst. of Arctic Biology Dept."— Presentation transcript:

1 COLONY GIS: A NEW APPROACH TO MAPPING AND ANALYZING POPULATION PRODUCTIVITY Cortney Pylant and Falk Huettmann EWHALE Lab Inst. of Arctic Biology Dept. of Biology & Wildlife University of Alaska Fairbanks

2 Presentation Outline Conventional Monitoring Description of Study Area and Species Colony GIS Method Methods Analysis Results Application Future of Colony GIS Method

3 Conventional Monitoring Track individual nests throughout season Limitations: –Weather –Vantage points –Number of birds monitored –Effort –Etc. Ram Papish

4 Study Area St. George Island –Second largest of Pribilof Island group –Eroding basalt cliffs create dynamic habitat CP

5 Study Species Red-Legged Kittiwake (Rissa brevirostris) –Endemic to Bering Sea region –Four known breeding colonies St. George Island Annual monitoring by AMNWR CP

6 Colony GIS Method Integrate small-scale GIS and habitat mapping Incorporate monitoring data and predictive modeling Identify “hotspots” for productivity across entire colony Habitat Mapping Few Monitoring Data Small-scale GIS Predictive Modeling Identify “hotspots” across entire colony => More efficient

7 Methods Current photographs with marked nests

8 Methods Current photographs with marked nests Map habitat features

9 Methods Current photographs with marked nests Map habitat features Determine distances from features in GIS

10 Methods Current photographs with marked nests Map habitat features Determine distances from features in GIS Create grid of regularly occurring points

11 Analysis Create statistical model (TreeNet Salford Ltd.) using monitoring data, training data, and regularly occurring points Generate predictions from model characterizing probability of success/failure at each point Compare predictions to actual monitoring data

12 Results Variable Importance (n = 92) 0.00ROCK ||||||||||||||||||||||||||||||||76.22DIST ||||||||||||||||||||||||||||||||||||86.01VEGE ||||||||||||||||||||||||||||||||||||||||||99.40Y (VERT) ||||||||||||||||||||||||||||||||||||||||||100.00EDGE ScoreVariable Position of nest with respect to distance from edge and vertical height most important variables Predicting a Successful Nest

13 Results Importance of Edge –Increased distance from edge yields greater probability of success Importance of Height (Y) –Probability of success favors some mid-value with respect to vertical position Success Failure Success Failure

14 Results Importance of Neighbors –Increased distance between nearest neighbor yielded greater probability of success (to a point) Importance of Vegetation –Greater distance from vegetation seems to increase probability of success Success Failure

15 Results Predicting to Colony Plot 70 Real Data [Failed; Success]

16 Results Predicting to Colony Plot 67 Ram Papish Real Data [Failed; Success]

17 Results Predicting to Colony Plot 69 Real Data [Failed; Success] CP

18 Application Does the colony GIS method work?

19 Application CP Plot 68

20 Application Predicting to Colony Plot 68

21 Application Plot 68 Predicting to Colony Real Data [Failed; Success]

22 Application Overall Model Accuracy Real Data 1520Success 1674Failed SuccessFailed Predicted 79% of failed nests correctly predicted 52% of successful nests correctly predicted Overall, 71% model accuracy

23 Future of Colony GIS Method Goal: Use small-scale GIS, habitat mapping, and monitoring data to predict productivity “hotspots” across entire colony, cliffs, and islands Future considerations: –More habitat features –Time photographs taken –Species competition for nest sites –Oceanic parameters –Etc.

24 Future of Colony GIS Method 9 CP

25 A Word of Caution: “Today's scientists have substituted mathematics for experiments, and they wander off through equation after equation, and eventually build a structure which has no relation to reality.” -Nikola Tesla Modern Mechanics and Inventions, July, 1934 When working with models: –Check for biological realism –Compare with actual data –Constantly revise models to reflect patterns and processes

26 Acknowledgements Alaska Maritime National Wildlife Refuge –Art Sowls 2006 St. George Field Technicians –Jade Cash, Karin Holser, Rachel Holser, Ryan Kingsbery, Ram Papish Dean Kildaw (St. George Island photographs)

27 Questions?


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