1. Modeling Complex Interactions of Overlapping River and Road Networks in a Changing Landscape UMBC February 20, 2004 Programmatic overview Structure and Hypothesis Preliminary findings

2. Challenge for modern science Integrate different disciplines –DNA, Plate tectonics, Mass extinction's Promote advances in modern technology –Data acquisition and information Remote sensing, DNA…. –Information management Public access to data, monitoring, 5 year rule Public relevance –Pure vs applied science –Education, increasing science literacy

3. NSFs Solution RFPs for Integrated Research Proposals Multi-year, multidisciplinary research teams with outreach and education component –LTER, Margins, EMSI Biocomplexity –Beyond biodiversity; interactions –Complex biological interactions over range of spatial and temporal scales Advantages and disadvantages to approach –Expectations vs. resources –Integrated research vs. old boy network

4. Successful Biocomplexity proposals must Address the inherent complexity and highly coupled nature of relevant natural and human systems as well as their interactions Describe plans for the work of interdisciplinary teams from the natural, social, mathematical sciences, engineering, and education –Whose coordinated work will enhance theoretical understanding

5. Evaluation Criteria Strength of the collaborations planned and degree of interdisciplinary UPENN, CSU, USU, UGA, UPR Effectiveness of the group organization and management plan 4 year work plan, previous interactions Value to education in these topical areas; –Graduate and undergraduate students in 5 Universities Strength of the dissemination plans –Workshops with high-school teachers, managers Extent, effectiveness, and long-term potential of collaborations with industries, national laboratories …. USDA Forest Service, Commonwealth of PR

6. Modeling Complex Interactions of Overlapping River and Road Networks in a Changing Landscape Three overlapping networks Rivers, Roads, Aquatic food webs Major response variables Channel Morphology, Recreation & Aquatic populations

7. Modeling Complex Interactions of Overlapping River and Road Networks in a Changing Landscape Overall Goal Develop set of integrated models than can predict what happens if a road is built at a specific location Geomorphic changes Recreation changes Biotic changes

8. Modeling Complex Interactions of Overlapping River and Road Networks in a Changing Landscape Complexity is greatest at intersections –Aquatic diversity, channel and habitat structure, recreational use Energy minimization (is not everything) –Stream channel network: Ramirez, Wohl, Scatena –Road networks; energy or history: Tomlin, Gutiérrez –Aquatic migrations: Covich, Crowl, Scatena –Recreation use; travel cost; Loomis, Caban Underlying template –Structure, process and time –Scale dependence

10. Island of many rivers Study area

11. Luquillo Mountains, NE Puerto Rico

12. Island of many roads All roads

13. More people using the same roads Influence of public transport

14. PR MD is 6 th, 4.25km./km 2 Why large breaks in distribution?

15. Maryland is 7th

17. –Subtropical Dry (1200 mm/yr) to Wet (5000 mm/yr) –Intense population pressure; –Highest visitor/area of National Forests

20. Three study watershed Develop models in 2 Test in third

21. Elevation Climate, geology, landownership

22. Nodes Order of road Order of stream Road Order Highway Two lane One-lane Dirt Sampling at, above & below nodes Aquatic, Recreation, Geomorphologic Sample Design How to define area of node?

23. Stream Order – Road Order - # nodes Second order streams & Second and Tertiary Roads

24. River order - Road order - drainage area/node 3 rd Order streams and Secondary and Tertiary Roads

25. Climate Topo Dem Landuse UPR Urban Centers Stream Network Ramirez, Wohl Scatena Road Network Tomlin, Laituri Stream Habitat Scatena Crowl Visitor Loomis UPR Aquatics Crowl Covich

26. Recreation/human behavior models Human visitation; amount and type –F (road type, travel time, channel morphology) –Travel costs and scale issues; Method –Visitor use surveys, channel surveys Previous WTP studies –Picnic, family access, swimming and age, –channel structure vs recreation potential ?? Policy Implications –Where to promote and limit recreation

27. Climate Topo Dem Landuse UPR Urban Centers Stream Network Ramirez, Wohl Scatena Road Network Tomlin, Laituri Stream Habitat Scatena Crowl Visitor Loomis UPR Aquatics Crowl Covich History and energy

28. Urbanizations Industrial Parks Overall pattern since Pre-Columbian and Colonial times

29. Climate Topo Dem Landuse UPR Urban Centers Stream Network Ramirez, Wohl Scatena Road Network Tomlin, Laituri Stream Habitat Scatena Crowl Visitor Loomis UPR Aquatics Crowl Covich Population structure = f(network location, reach morphology, visitors)

30. Life Cycle of Freshwater Snail (Neritidae: Neritinae: Gastropoda) Headwaters Ocean Newly hatched larva Adult Juvenile Spat Planktotrophic larva Neritina virginea

31. 1 day downstream migration 6+ years upstream migration

32. Blanco and Scatena, in review

33. Main channel of bridge 1000s of migrating snails

34. 1 m 3 cm 1 cm

35. Side Channel Cooperation vs Predation

37. Main Reach Higher velocities Turbulent, Fr > 1 Lower fish predators/area Smaller snails migrate in side boundary layer Side Reach, high flow channel Lower velocities Less turbulent, Fr <1 Higher fish predator/area Larges snails migrate Velocity and predation influence

38. Main channel of bridge 1000s of migrating snails Ugly concrete maybe good! Velocity & channel margin habitat are critical

39. Food web component absolute and relative abundance of aquatic organisms (shrimp, fish, snails) H1: In headwater streams social factors (visitation, harvests) are better predictors of food web structure than habitat; (bedrock vs people) H2: Lower elevation streams, physical factors are better predictors…(alluvial channel vs recreational quality) Method Sampling at study nodes.. Developing habitat abundance relationships

40. Freshwater shrimp

41. Atya – Daytime 47 individuals Atya – Nightime 353 individuals Abundance vs depth

42. Policy implications Relative role of recreation vs. land-use Swimming vs harvesting Downstream barriers to migration vs reach level impacts

43. Climate Topo Dem Landuse UPR Urban Centers Stream Network Ramirez, Wohl Scatena Road Network Tomlin, Laituri Stream Habitat Scatena Crowl Visitor Loomis UPR Aquatics Crowl Covich Habitat = f(network location, bridge influences, type of use) Shrimp, People, and Roads seek low energy environments; deep pools

44. Stream Habitat Morphology Habitat-Visitor –Controls local reach section for type of recreation Habitat-channel network –Network energy gradients vs local habitat abundance –Bedrock vs self adjusting channels Road network-aquatic habitat –Local habitat changes, bridge scour Methods Channel cross-sections; hydraulic analysis (Pike) DEM Energy based modeling (Ramirez)

45. Scatena and Johnson, 2001 Head water stream morphology and shrimp biomass Individual pool scale Swimming pool size vs shrimp pool size

46. Shrimp Biomass vs Pool depth Two headwater streams Human recreation preference; pool depth > 1 meter Swimming may not have influence on abundance Harvesting will…. Reach-scale variability in habitat abundance

49. Majority of recreation at mid elevation, moderate slopes Balance between water quality, abundance, slope, access Longitudinal continuum vs geomorphic discontinuities

50. Longitudinal Profiles Pike, in progress Knick point St. Johns Peneplain Fish barrier Knick point St. Johns Peneplain ???

51. Stream Power ~ slope*total runoff Water slides Family recreation

52. Runoff and slope…knick point retreat

53. ClimateTopo Landuse UPR Urban Centers Stream Network Ramirez, Wohl Scatena Road Network Tomlin, Laituri Stream Habitat Scatena Crowl Visitor Loomis UPR Aquatics Crowl Covich Where are we headed? Field work, High-school teachers workshop