Modeling Complex Interactions of Overlapping River and Road

Networks in a Changing Landscape

UMBC February 20, 2004

Programmatic overview

Structure and Hypothesis

Preliminary findings

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

NSF’s Solution RFP’s 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”

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

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

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

Modeling Complex Interactions of Overlapping River and Road Networks in a Changing Landscape

Overall GoalDevelop set of integrated models than can predict

what happens if a road is built at a specific location

Geomorphic changes Recreation changes

Biotic changes

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

Island of many rivers

Study area

Luquillo Mountains, NE Puerto Rico

Road density, km/km2

km a

ll ro

ad

s/km

2

0

1

2

3

4

5

6

Island of many roads

All roads

Roads per capitaKm roads/1000 people

km a

ll ro

ad

s/1

00

0

0

5

10

15

20

25

30

More people using the same roads

Influence of public transport

Road Density of US States' km/km2km

/km

2

0

2

4

6

8

PR Top 5 in USRhode IslandNew JerseyMassachusettsConnecticutPuerto Rico

MD is 6th, 4.25km./km2

Why large breaks in distribution?

Road Density of US States' km/1000 people

PR MD USA ND

km/1

000

peo

ple

0

100

200

300

400

500

Lowest 5Hawaii

Puerto RicoNew JerseyCalifornia

Massachusetts

Maryland = 7thMaryland is 7th

–Subtropical Dry (1200 mm/yr) to Wet (5000 mm/yr)

–Intense population pressure;

–Highest visitor/area of National Forests

Rio Fajardo

Rio Espiritu Santo Rio Mameyes

Three study watershed Develop models in 2 Test in third

Elevation Climate, geology, landownership

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?

0

5

10

15

20

25

30

P

S

T

C4

12

34

Nu

mb

er o

f N

od

es

River Order

Stream Order – Road Order - # nodes

Second order streams & Second and Tertiary Roads

0

2000

4000

6000

8000

P

S

T

C4

12

34

Ha/

No

des

Roa

d O

rder

River Order

River order - Road order - drainage area/node

3rd Order streams and Secondary and Tertiary Roads

Climate TopoDem

LanduseUPR

UrbanCenters

Stream NetworkRamirez, Wohl

Scatena

Road NetworkTomlin, Laituri

StreamHabitatScatenaCrowl Visitor

LoomisUPR

AquaticsCrowlCovich

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

Climate TopoDem

LanduseUPR

UrbanCenters

Stream NetworkRamirez, Wohl

Scatena

Road NetworkTomlin, Laituri

StreamHabitatScatenaCrowl Visitor

LoomisUPR

AquaticsCrowlCovich

History and energy

Legend

Drains2

Streams

Feature Type

APPARENT LIMIT

CLOSURE LINE

DAM OR WEIR

DITCH OR CANAL

LEFT BANK

MANMADE SHORELINE

REEF

RIGHT BANK

SHORELINE

STREAM

Drains2 is the Project-Derived Stream coverage. Streams is the USGS hydrography coverage.

Apparent limits, closure lines, dam or weir, left bank, manmade shorelines, reefs, right banks and natural shorelines were removed to create drains2. River centerlines were manually digitized to replace the left bank and right bank features. ®

0.25 0 0.25 0.5 0.750.125 Miles

0.3 0 0.3 0.6 0.90.15 Kilometers

1:25,179

Scale

Rio Espiritu Santo

Rio Fajardo

Rio Mameyes

Urbanizations

IndustrialParks

Overall pattern since

Pre-Columbian and Colonial times

Climate TopoDem

LanduseUPR

UrbanCenters

Stream NetworkRamirez, Wohl

Scatena

Road NetworkTomlin, Laituri

StreamHabitatScatenaCrowl Visitor

LoomisUPR

AquaticsCrowlCovich

Population structure = f(network location, reach morphology, visitors)

Life Cycle of Freshwater Snail Life Cycle of Freshwater Snail (Neritidae: Neritinae: Gastropoda)(Neritidae: Neritinae: Gastropoda)

Headwaters

Ocean

Newly hatched larva

AdultJuvenile

Spat

Planktotrophic larva

Neritina virgineaNeritina virginea

1 day downstream migration

6+ years upstream migration

Blanco and Scatena, in review

Main channelof bridge

1000’s ofmigrating

snails

1 m

3 cm1 cm

SideChannel

Cooperationvs

Predation

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 predationinfluence

Main channelof bridge

1000’s ofmigrating

snails

Ugly concrete maybe good!

Velocity & channel margin

habitat are critical

Food web componentabsolute 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)

MethodSampling at study nodes..

Developing habitat abundance relationships

Freshwater shrimp

0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.450

5

10

15

20

0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45

Ind

ivid

ual

s o

bse

rved

0

40

80

120

160

Atya – Daytime 47 individuals

Atya – Nightime353 individuals

Abundance vs depth

Policy implications

Relative role of recreation vs. land-use

• Swimming vs harvesting

• Downstream barriers to migration vs reach level impacts

Climate TopoDem

LanduseUPR

UrbanCenters

Stream NetworkRamirez, Wohl

Scatena

Road NetworkTomlin, Laituri

StreamHabitatScatenaCrowl Visitor

LoomisUPR

AquaticsCrowlCovich

Habitat = f(network location, bridge influences, type of use)Shrimp, People, and Roads seek low energy environments; deep pools

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)

Scatena and Johnson, 2001

Head water stream morphology and shrimp biomassIndividual pool scale

Swimming pool size vs shrimp pool size

Shrimp Biomass vs Pool depthTwo headwater streams

Human recreation preference; pool depth > 1 meterSwimming may not have influence on abundance

Harvesting will….

Reach-scalevariability in habitat

abundance

0

0.5

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Drainage area vs Channel slope

0 10 20 30 40

Slo

pe

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FFFBBBD FFBDF

BDBD

BD

BD

BBDB

BD

BD

F

B

BDBDBD

B

BD

BB

BDBDBBDBDBBD

F

FRR

RR RR

R

PP PP

P

PPPPP FFFF

Majority of recreation at mid elevation, moderate slopesBalance between water quality, abundance, slope, access

Longitudinal continuum vs geomorphic discontinuities

Mameyes

0.0

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Distance from Headwaters (m)

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vati

on

Sabana

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600.0

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Distance from Headwaters (m)

Ele

vati

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Longitudinal Profiles Pike, in progress

Knick pointSt. Johns Peneplain

Fish barrier

Knick pointSt. Johns Peneplain

???

Mameyes

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Distance from Headwaters (m)

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eam

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pe *

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ff)

Sabana

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Distance from Headwaters (m)

Str

eam

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wer

Ind

ex

(Slo

pe *

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tal

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ff)

“Stream Power” ~ slope*total runoff

Water slides

Family recreation

Mameyes

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0 2000 4000 6000 8000 10000 12000 14000 16000 18000

Distance from Headwaters (m)

Str

eam

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wer

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ex

(Slo

pe *

To

tal

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no

ff)

Mameyes

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0 2000 4000 6000 8000 10000 12000 14000 16000 18000

Distance from Headwaters (m)

Ele

vati

on

Runoff and slope…knick point retreat

Climate Topo LanduseUPR

UrbanCenters

Stream NetworkRamirez, Wohl

Scatena

Road NetworkTomlin, Laituri

StreamHabitatScatenaCrowl Visitor

LoomisUPR

AquaticsCrowlCovich

Where are we headed?Field work, High-school teachers workshop