assessing the consequences of land use change in the upper potomac
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Assessing the Consequences of Land Use Change in the Upper Potomac. Robert H. Gardner with Jason Julian, Andrew J. Elmore, Todd R. Lookingbill, Marcella Suarez-Rubio. Appalachian Laboratory University of Maryland Center for Environmental Science. The Appalachian Laboratory. - PowerPoint PPT PresentationTRANSCRIPT
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Assessing the Consequences of Land Use Change in the Upper Potomac
Robert H. Gardnerwith
Jason Julian, Andrew J. Elmore,Todd R. Lookingbill, Marcella Suarez-Rubio
Appalachian LaboratoryUniversity of Maryland Center for Environmental Science
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The Appalachian Laboratory
To “… determine the effects of natural and human-induced changes on organisms, landscapes, and biogeochemical and hydrological cycles.”
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Outline
1. Importance of land-use and land-cover
(LULC) change in the Potomac River
Basin
2. The challenge of determining effects
3. An integrated approach for prediction
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1. Importance of LULC change• LULC is accelerating and is global in extent• Directly linked with declines in
– Biodiversity– Water quality and availability– Ecosystem productivity (especially
economically important species)• LULC may also
– Accelerate climate change– Enhance the spread of disease (new
pandemics)
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• Basin: 38,000 km2
• Mainstem:617 km (170 km tidal)
• 6 physiographic provinces
• Climate boundary
The Potomac River Basin
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Key attributes of the PRB• Located in one of most rapidly
urbanizing areas in the US– 5.3 million people w/n basin– Coal mining affects Appalachians– Agriculture in Ridge and Valley– Piedmont and Coastal Plain continue
to be urbanized• The 617 km river main stem has
relatively unregulated flows
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History of LULC change• Not glaciated – but glacial runoff produced
coastal plain & Chesapeake Bay• Frontier stage – (17th century)
– natural resource use, local deforestation• Agricultural Expansion – (18th century)
– Pops of 380,000– 20-30% of forests cleared– Sediment accumulation in Bay affect
navigation
http://www.chesapeakebay.net/history.htm
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More history• Industrialization – (late 18th century)
– Urban corridor formed– Population of 2.5 million, raw sewerage
in Bay– Railroads consume 15-20 million acres
of Eastern Deciduous Forest• Population expansion – (19th century)
– Beginning of environmental legislation and control (Clean Air Act, etc.)
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Effects of LULC within the Potomac• Hardened surfaces result in buried streams
with increased throughput– Nutrient retention declines, export
increases• Population growth increases water demands
– From Upper Potomac to Lower• Ecosystem recovery from wide variety of
disturbances remains unknown• New invasives impact terrestrial and aquatic
habitats
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The problem of buried streams
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The gradient of population density
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Lower Potomac >> Upper Potomac
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Low-flow correlated with high demand
Lookingbill et al., in press
Low flow frequency Low flow demand
112 year record shows 13% of years have extremely low flows
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Invasive organisms are here to stay– Gypsy moth– Hemlock wooly adelgid– Chestnut blight
• New (potential)– Emerald ash borer has been found in MD– Sirex noctilio – wasp (horntail) kills pines– Sudden oak death– Asian long horned beetle (in MD)
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Potomac River Ecosystem has not been adequately studied
River ISI References
Columbia 3,263Mississippi 2,921Colorado 2,195Hudson 1,193Missouri 826Potomac 309
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2. Determining effectsLandscapes are composed of many
“elements” including …– roads– agricultural “units”– forests of diverse types and ages– urban & suburban development
And diverse economic conditions
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We know that the spatial arrangement of “elements” is critical
• Riparian buffers effectively reduce sediment and nutrient export
• While development selectively removes headwaters ecosystems*
• No single sub-watershed is representative of the Potomac
• Small critical areas (wetlands) are most effective nutrient and sediment filters
*Elmore and Kaushal, 2008
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Effects of LULC are not additive
• If linear then effects of change are additive– we can extrapolate using mean value(s) – landscape assessment can be produced
by simple summation (spread sheet)– or by sampling extremes (boundaries)
and interpolating for each set of unique conditions
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“Many challenges remain in extending our understanding of how hydrologic processes within small catchments scale to larger river basins.”
The problem of scale
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0
0.2
0.4
0.6
0.8
1
1.2
0 10 20 30 40
Impervious Land Cover (%)
Bro
ok T
rout
Den
sity
(#/m
2 )
AbsentPresent
Critical thresholds: Brook trout density and impervious cover
Stranko et al. 2008
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Disturbance induces time lags• Disturbances are not simple transient
events?– History of change is important
• We may not be able to predict the future from the past
• Forest harvesting has altered age and species distribution of flora– Decline (possibly permanent declines)
in oak and pine abundance
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Gypsy Moth Defoliation and Annual Nitrate-N Export
1980 1985 1990 19950
20
40
60
80
100
0.0
1.0
2.0
3.0
4.0
5.0
Water Year
% o
f for
este
d ar
ea
kg/h
adefoliation
nitrate-N export
White Oak Run, Virginia
Eshleman et al. 2005
Significant effects on nutrient cycling
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AMD
Permanent effects of coal mining
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3. An integrated, predictive approach
Understanding -> predictionBut this requires:• Spatial and temporal characterization of
weather patterns• Determination of trends in land use change• A process-based representation considers
interactive effects of multiple changes• Estimation of unknowns and uncertainties
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Interactive effects are important?• Flood potential – is a combined effect of
LULC and climate change• Denitrification – depends on the location
of critical habitat placement– Sources and sinks– Effectiveness of restoration
• Meeting water quality demands – A moving target: growth, development,
LULC and climate change
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SLEUTH: a model of land-use change
• USGS sponsored development– Slope, Land use, Exclusion, Urban
extent, Transportation, Hillshade – Clark (1998)
• Being explored and widely used w/n Chesapeake Watershed
• A pattern-based model – Uses a fine-scale, gridded landscape– Projects urban growth
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Historical records are necessary
• Required GIS layers– Urban growth (3-4 layers)– Roads (2 layers)– Exclusion (1 layer) – protected lands– Hillshade (1 layer)– Slope (1 layer)– Land use (1 layer) – current
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Empirical (best fit) of 5 growth parameters govern probability of urbanization• Spontaneous dispersion – formation of
new urban locations• Growth (increase in size) of new urban
locations• Growth of old (established) locations• Road gravity – increased growth rates
near roads• Slope resistance – decreased growth
with increasing slopeDietzel (2007)
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Calibration first
• Brute force calibration (inefficient)– Parameters varied over broad range– Monte Carlo techniques applied– Subset (“best fit”) determined by
spatial comparison to history of change
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Prediction requires
• Current land use maps for initialization– Urban extent– Transportation network– Exclusion layer
• Future scenarios performed by varying– Exclusion layer (e.g., streams, etc.)
•And exclusion “rules”– Constraints on transportation network
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Baltimore-Washington projections (Jantz et al. 2003)
• Three scenarios for piedmont & coastal plain of Maryland and Northern Virginia
• Variable exclusion layers developed– By state and land use type
• Scenarios:A. Current trendsB. Managed growthC. Ecological preservation
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ResultsChange (km2 / y)
Scenario Urban Forest Agriculture
A. Current trends
110 -43 -51B. Managed
growth41 -15 -15
C. Ecological preservation
28 -10 -9
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Summary• Moderate “exclusions” have large effects
on patterns of LULC change• Population trends continue to drive
change• Model improvements always desirable
– Local policies not yet implemented• Linkage of land use projections with
ecosystem models urgently needed– Water, nutrients, sediments as a
function of land-use change– Biotic effects of land-use change
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Our efforts for the Potomac
• We have spent ~1 year on data acquisition, verification
• Calibration has been performed• Simulations begun on development
scenarios in the Upper Potomac– Focus on effects of habitat change on
bird community (Ph.D. thesis)
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Next steps
• This summer– Plans for a workshop at Appalachian Lab
•Include relevant parties using SLEUTH w/n Chesapeake
•Share “mutual” resources (data layers)•Apply uniform methods for calibration
and prediction – for cross-comparisons•Shared effort – data enhancement,
model improvement
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Special thanks Sujay KaushalWalter BoyntonTom FisherLarry SanfordJeff CornwellBill DennisonClair Jantz