constructing probability surfaces of ecological changes in ... · dennis whigham, karin kettering,...
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Constructing Probability Constructing Probability Surfaces of Ecological Surfaces of Ecological
Changes in Coastal Aquatic Changes in Coastal Aquatic Systems Through Systems Through
Retrospective Analysis of Retrospective Analysis of Phragmites Phragmites australisaustralis
Invasion and ExpansionInvasion and Expansion
Denice Heller Wardrop, Jessica PetersonDenice Heller Wardrop, Jessica Peterson--Smith, Mary Easterling, Smith, Mary Easterling, Hannah Ingram, Hannah Ingram, MuraliMurali HuranHuran and G.P. and G.P. PatilPatil Penn StatePenn StateDennis Whigham, Karin Kettering, Melissa McCormick, Dennis Whigham, Karin Kettering, Melissa McCormick,
Smithsonian Environmental Research CenterSmithsonian Environmental Research CenterKirk Havens, Virginia Kirk Havens, Virginia InsitutueInsitutue of Marine Scienceof Marine Science
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Estuarine IndicatorsEstuarine Indicators
The Chesapeake Bay is highly monitored. While there are many indicators of changes in the Bay, it is difficult to link these indicators to what is occurring on land. This project is working to link these indicators to the land. The hope is that the researchers will be able to identify linkages and detail how those linkages occur.
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The researchers sampled the Chesapeake Bay from north to south, focusing on estuarine segments. An estuarine segment is a watershed that is large enough to have a perennial stream flowing into the subestuaries of the Chesapeake Bay. A broad range of indicators that responded to land use patterns was identified. In particular, there appeared to be a strong association between an invasive plant species called Phragmites and land use.
The dots on the map represent the places where the researchers sampled the water for Phragmites. Estuarine segments were chosen using GIS data to represent the three dominant land use types: development, agriculture, and forest (reference condition).
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r2 = 0.61, P < 0.001
% Developed Land in Watershed
0 20 40 60 80
Phra
gmite
sab
unda
nce
estim
ate
0
1
2
3
4
5
6
7
DevelopedMixed-DevAgriculturalMixed-AgForested
r2 = 0.61, P < 0.001r2 = 0.61, P < 0.001
% Developed Land in Watershed
0 20 40 60 80
Phra
gmite
sab
unda
nce
estim
ate
0
1
2
3
4
5
6
7
DevelopedMixed-DevAgriculturalMixed-AgForested
King et al. (2007) Estuaries and Coasts
There was a significant correlation between the amount of development on the watershed and the abundance of Phragmites.
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0 10 20 30 40 50 60 70 80 90
0
1
2
3
4
5
6
7
Phra
gmite
s Ab
unda
nce
Inde
x
0.0
0.2
0.4
0.6
0.8
1.0
Cum
ulat
ive
Thre
shol
d Pr
obab
ility
41000004150000
42000004250000
43000004350000
0
1
2
3
4
5
6
7
Phra
gmite
s Ab
unda
nce
Inde
x
0.0
0.2
0.4
0.6
0.8
1.0
Cum
ulat
ive
Thre
shol
d Pr
obab
ility
% IDW Developed Land (Local)
25 35 45 55 65 75
0
1
2
3
4
5
6
7
Phra
gmite
sAb
unda
nce
Inde
x
0.0
0.2
0.4
0.6
0.8
1.0
Cum
ulat
ive
Thre
shol
d P
roba
bilit
y
% IDW Forested Land (Watershed)Northing (m)
PhragmitesAbundance Index
Model r2 = 73.4%
The three most important variables affecting Phragmites are: developed land; northing (location of the subestuary in the Chesapeake Bay), which has shown that the invasion front is moving from the north to the south in the Chesapeake Bay; and forested land.
The researchers identified a threshold using these indicators. The data show that only a small amount of development is needed to reach the threshold and, once a certain point is reached, change occurs very quickly.
Developed land is the most important variable related to the abundance of Phragmites. Although the amount of developed land along the watershed is important, where the developed land is occurring along the watershed also is very important. The closer the disturbance to the water, the stronger the relationship.
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Luzula campestris (2.5)Centaurea jacea (4.33)
Several metres
Upper limit several metres under stormy conditions
Selective release mechanismsWind ballists
Cirsium dissectum (0.38)Eupatorium cannabinum (0.4)Narthecium ossifragum (0.6)Senecio paludosus (0.6)Valeriana dioica (0.6)Leontodon autumnalis (0.9)Holcus lanatus (1.1)Anthoxanthum odoratum (1.4)Filipendula ulmaria (1.7)Molinia caerulea (1.8)Cardamine pratensis (1.9)Succisa pratensis (2.14)
Several tens of metres
Upper limit ranges from at least several kilometres to at least several tens of metres under stormy conditions.
Low terminal velocity seeds (0.3 m/s < terminal velocity < ± 2 m/s) and relatively high release heights, often in combination with selective release mechanisms
Species with low terminal velocity seeds
Typha latifolia (0.1)Phragmites australis (0.1)Epipactis palustris (0.2)Liparis loeselii (0.2)Epilobium hirsutum (0.2)Epilobium palustre (0.2)Eriophorum angustifolium (0.2)Dactylorhiza species (0.3)Cirsium palustre (0.3) Aster tripolium (0.3)
Several kilometresUpper limit is at
least several kilometres under highly convective or stormy conditions
Low terminal velocity seeds (terminal velocity ≤ 0.3 m/s) and relatively high release heights, often in combination with selective release mechanisms
Species with low terminal velocity seeds
Representative species(terminal velocity in m/s)Dispersal distancesAdaptationsCategory
Source: Sooms (Applied Veg. Sci.)
Phragmites can spread rapidly and colonize a large area. In fact, their seeds can disperse up to several kilometers.
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% IDW Developed Land (Watershed)0 15 30 45 60 75 90
2.00
2.25
2.50
2.75
3.00
3.25
3.50
Leaf
-tiss
ue %
N
0.0
0.2
0.4
0.6
0.8
1.0
Cum
ulat
ive
Thre
shol
d P
roba
bilit
y
>14.3%≤14.3%r2 = 65.3%
p=0.0178
The concentration of nitrogen in the leaves of the plant showed the same pattern. As more development close to the wetland occurs, the percentage of nitrogen in the leaves begins to increase rapidly. Thus, there may be a second important factor: the nutrient status of the ecosystem of the subestuaries.
The researchers initially hypothesized that there were two important factors in the establishment and spread of Phragmites: (1) a disturbance was needed to establish Phragmites in a new area, and (2) nutrient enrichment in the system was needed to allow Phragmites to spread.
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Patterns of canopy-air CO2 concentration in a brackish wetland: analysis of a decade of measurements and the simulated effects on the vegetation.
Daniel P. Rasse, Stavroula Stolaki, Gary Peresta, Bert G. Drake Agricultural and Forest Meteorology 114 (2002) 59–73
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ObjectivesObjectivesChoose an aquatic ecosystem with clearly identifiable alternative states, and define a limited number of variables that are considered to be the driving factors in state changesEstablish the database of explanatory and response variables over both a spatial and temporal extent. A retrospective analysis is the most powerful if performed over a truly temporal extent, instead of a “space for time” experimental design.Construct a probability surface of state change over the n-dimensional space of selected explanatory variablesDescribe thresholds in terms of the probability surface
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Selection of Anne Arundel Selection of Anne Arundel County, MDCounty, MD
Abundance of Abundance of historical datahistorical dataRapid developmentRapid developmentInvaded/Invaded/uninvadeduninvadedmarshesmarshesExisting management Existing management infrastructureinfrastructure
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Prioritized Slow VariablesPrioritized Slow VariablesAccumulating potential for an alternativeAccumulating potential for an alternative
ecosystemecosystem1. Flooding2. Organic vs. mineral soil3. Presence of non-native haplotype4. Genetic variation in population5. Drought6. Developed Land Cover7. Agricultural Land Cover8. Forested Land Cover9. Nitrogen from septic systems10. Nitrogen from point sources11. Hydrologic connectivity to Bay12. Salinity13. Atmospheric CO2
14. Atmospheric nitrogen deposition15. Phosphorus16. Precipitation and Climate
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Prioritized Fast VariablesPrioritized Fast VariablesEvents which precipitate a Events which precipitate a
reorganization of the plant communityreorganization of the plant community1. Aerial distance to nearest Phragmites2. Water distance to nearest Phragmites3. Sedimentation4. Road/Bridge5. Tidal Restrictions/ Bulkhead6. Upland Fills/Construction7. Marsh modification (Dock, Boardwalk)8. Marsh surface water input9. Storms10. Fetch11. Species composition of marsh12. Ditches/Tidal Creek
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Data SourcesData Sources
Complete inventory, classification, and mapping of Complete inventory, classification, and mapping of MD tidal marshes, 1970s (training set)MD tidal marshes, 1970s (training set)Aerial photographs for 1970, 1977, 1984, 1992, 2001 Aerial photographs for 1970, 1977, 1984, 1992, 2001 (preliminary analysis for (preliminary analysis for PhragPhrag expansion)expansion)Remote sensing data for 1984, 1992, 2001Remote sensing data for 1984, 1992, 2001Shoreline Survey for Maryland, completed in 2005 Shoreline Survey for Maryland, completed in 2005 (1441 shoreline miles surveyed)(1441 shoreline miles surveyed)
Immediate riparian zoneImmediate riparian zoneBankBankShorelineShoreline
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PhragmitesPhragmites Invasion in South River Invasion in South River MarshesMarshes
1.89 ha
0.07 ha
• 1970: Present only in two marshes; < 2 ha 2.90 ha
0.11 ha
0.07 ha
0.14 ha
• 1977: Invades two additional marshes; expands to 3.2 ha
3.32 ha
0.04 ha 0.11 ha
0.33 ha
0.17 ha
0.04 ha
• 1984: Present in all six marshes; area increases to 4.1 ha
• 2000: Large increases in all marshes (38%-800% over 1984 areas); total area = 7.1 ha
4.60 ha
0.41 ha 0.26 ha
0.58 ha
0.98 ha
0.23 ha
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Shoreline Situation ReportsShoreline Situation Reports
Immediate riparian area Immediate riparian area for land usefor land useHeight, stability, and Height, stability, and natural protection of natural protection of bankbankRecreational and access Recreational and access structures on shorelinestructures on shoreline
Red represents sites where shoreline surveys have been completed.
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Rhode River. 1-km buffer in yellow; SERC sites in red; DNR wetland polygons in blue;VIMS Phrag in bright pink; VIMS unknown in pale pink: VIMS no Phrag in gray
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Expansion of temporal/spatial Expansion of temporal/spatial data setdata set
Decision to Decision to ““recreaterecreate”” inventory, land cover, inventory, land cover, and shoreline survey for all available time and shoreline survey for all available time periods, proceeding from 2005 periods, proceeding from 2005 ““backwardsbackwards””Increases temporal Increases temporal datapointsdatapoints from 5 to 15from 5 to 15
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CompleteCompleteComplete2005
CompleteCompleteComplete2002
CompleteCompleteComplete2000
CompleteCompleteComplete1998
CompleteCompleteComplete1995
CompleteCompleteComplete1990
IncompleteIncompleteIncomplete1988
CompleteCompleteComplete1984
IncompleteIncompleteIncomplete1980
CompleteIncompleteComplete1977
IncompleteCompleteComplete1970
IncompleteCompleteComplete1962/3
CompleteCompleteComplete1957
CompleteIncompleteIncomplete1952
CompleteIncompleteX1943
Curtis BaySouth RiverRhode RiverYear
Availability of Aerial PhotographyAvailability of Aerial Photography
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Explanatory Variables from Explanatory Variables from Aerial PhotographyAerial Photography
Aerial distance to nearest Aerial distance to nearest PhragmitesPhragmitespopulationpopulationWater distance to nearest Water distance to nearest PhragmitesPhragmitespopulationpopulationLand coverLand coverShoreline disturbancesShoreline disturbancesSpecies composition of marshSpecies composition of marsh
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pixels whichinclude marsh1 measure (1970’s)
% of species (plant community type) in pixel
Salinity, Flooding, Anoxia tolerance; Response to N;Aggressiveness
Species Composition ofMarsh
1) within 1 km of marsh, 2) within200 m of marsh, 3)within 10m ofmarsh
1) period of the aerial photo, 2) previous photos (periodof 10, 20, 50 years ago?)
1) % of land within acertain radius; 2) N load,3) Sediment load (typical load determined fromliterature)
nitrogen in surface H2O, sedimentation, flooding, salinity
Land Cover: Developed, Agricultural, Forested
pixels whichinclude marsh:in or within 10m(30m?) ofmarsh
aerial photo time step;time steps beforelinear m in pixel
sedimentation, flooding, salinity, dispersal
Road/Bridge, Upland Fill/Construction, Marsh Modification (Dock, Boardwalk)
pixels whichinclude marsh
aerial photo time step;time steps before
1) closest pixel withPhragmites, 2) % ofpixel in Phragmitescoverage
Increase dispersal; within marsh: decrease anoxia andflooding (clonalIntegration);
Aerial Distance to Nearest PhragmitesPopulation
Spatial ScaleTemporal PeriodMetric of MeasureVariables ImpactedVariable
Historical Photo Interpretation: Excerpt of Explanatory Variable Metrics, Temporal and Spatial Scale
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Additional Historical DataAdditional Historical Data
SedimentationSedimentationSalinitySalinityPhosphorousPhosphorousDroughtDroughtPrecipitationPrecipitationClimateClimateFloodingFloodingMean Sea Level RiseMean Sea Level RiseMetonicMetonic cyclescyclesNitrogen Nitrogen -- Atmospheric deposition, point sources, Atmospheric deposition, point sources, septic systems, surface waterseptic systems, surface water
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Curtis Bay and South RiverCurtis Bay and South RiverMarley Creek Curtis Bay
0
5000
10000
15000
20000
25000
30000
35000
40000
45000
50000
1970 1977 1984 1990 2000
Are
a of
Phr
agm
ites
(m^2
)
Furnace Creek Curtis Bay
0
5000
10000
15000
20000
25000
30000
35000
40000
45000
50000
1977 1984 1990 2000
Are
a of
Phr
agm
ites
(m^2
)
South River 1
0
5000
10000
15000
20000
25000
30000
35000
40000
45000
50000
1970 1977 1984 1990 2000
Are
a of
Phr
agm
ites
(m^2
)
South River 2
0
5000
10000
15000
20000
25000
30000
35000
40000
45000
50000
1 2 3 4 5
Are
a of
Phr
agm
ites
(m^2
)
23
Rhode RiverRhode RiverRhode River 11A
0
5000
10000
15000
20000
25000
30000
35000
40000
45000
50000
1 2 3 4 5
Are
a of
Phr
agm
ites
(m^2
)
Rhode River 11B
0
5000
10000
15000
20000
25000
30000
35000
40000
45000
50000
1 2 3 4 5
Are
a of
Phr
agm
ites
(m^2
)
Rhode River 12
0
5000
10000
15000
20000
25000
30000
35000
40000
45000
50000
1 2 3 4 5
Are
a of
Phr
agm
ites
(m^2
)
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Curtis Bay sub-estuary, with the original SERC sites outlined in red, and the 1 km buffer of the shoreline outlined in yellow.
The researchers hypothesized that there was a correlation between nutrient increase and Phragmites increase, but they do not appear to be correlated.
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Airport: Land designated or used for air traffic.Airport: Land designated or used for air traffic.
Commercial: Retail and office uses.Commercial: Retail and office uses.
Industrial: Industrial and industrial parks.Industrial: Industrial and industrial parks.
UtilityUtility: : Corridors defined by electrical line paths. May be represented bCorridors defined by electrical line paths. May be represented by cleary clear--cuts in noncuts in non--urban areas or cleared urban areas or cleared paths through urban areas.paths through urban areas.
Residential 1/8Residential 1/8--acreacre: : Single or Single or MulitMulit--Family Residential or Townhouses Family Residential or Townhouses -- 1/8 acre lot size.1/8 acre lot size.
Residential 1/4Residential 1/4--acreacre: : Single Family Residential Single Family Residential -- 1/4 acre lot size.1/4 acre lot size.
TransportationTransportation: : Highway, road and railroad right of way.Highway, road and railroad right of way.
Residential 1/2Residential 1/2--acreacre: : Single Family Residential Single Family Residential -- 1/2 acre lot size.1/2 acre lot size.
Residential 1Residential 1--acreacre: : Single Family Residential 1 Single Family Residential 1 -- acre lot size.acre lot size.
Residential 2Residential 2--acreacre: : Single Family Residential Single Family Residential -- 2 acre lot size.2 acre lot size.
Open SpaceOpen Space: : Open, Recreational, or vacant space maintained in turf.Open, Recreational, or vacant space maintained in turf.
Pasture/HayPasture/Hay: : Cultivated land used for pasture or hay.Cultivated land used for pasture or hay.
Row CropsRow Crops: : Cultivated land used for crops. Includes orchards.Cultivated land used for crops. Includes orchards.
WoodsWoods: : All upland forested areas.All upland forested areas.
WaterWater: : Open or standing water.Open or standing water.
Forested WetlandForested Wetland: : Lowland forest.Lowland forest.
Open Wetland: Emergent, floating aquatic or shrub wetlands.Open Wetland: Emergent, floating aquatic or shrub wetlands.
AA Co. Land Cover Categories
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Land Cover Change in Ann Arundel Co.
-100-90-80-70-60-50-40-30-20-10
0102030405060708090
100
1950 1960 1970 1980 1990 2000 2010
Year
Perc
ent C
hang
e R
elat
ive
to 1
95
Commercial
Industrial
Open Space
Open Wetland
Pasture/Hay
Residential
Row Crops
Transportation
Water
Woods
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RHODE RIVER
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Land Cover Change in Ann Arundel Co.
0
100
200
300
400
500
600
700
800
900
1000
1950 1960 1970 1980 1990 2000 2010
Year
Hec
tare
s
Commercial
Industrial
Open Space
Open Wetland
Pasture/Hay
Residential
Row Crops
Transportation
Water
Woods
Land Cover Change in Rhode R. Sub-estuary
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CLASSNAME2Transportation
Industrial
Commercial
Residential
Pasture/Hay
Row Crops
Open Space
Woods
Open Wetland
Water1952 2005
Landcover in Rhode River Sub-estuary
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Total Length of Roads (km)
40.0
42.0
44.0
46.0
48.0
50.0
52.0
54.0
56.0
1950 1960 1970 1980 1990 2000 2010
Year
km o
f roa
ds
31
1952 2005
Roads in Rhode River Sub-estuary
32
Number of Shoreline Structures
0
50
100
150
200
250
300
350
400
1950 1960 1970 1980 1990 2000 2010
Year
No.
of s
truc
ture
s
33
1952 2005
Shoreline Structures in Rhode River Sub-estuary
34
Curtis Creek
35
Land Cover Change in Curtis Creek Sub-estuary
0
100
200
300
400
500
600
700
800
900
1000
1930 1940 1950 1960 1970 1980 1990 2000 2010
Year
hect
ares
Commercial
Industrial
Open Space
Open Wetland
Pasture/Hay
Residential
Row Crops
Transportation
Utility
Water
Woods
36
Percent Change in Land Cover in Curtis Creek Sub-estuary Relative to 1943
-150.0
-100.0
-50.0
0.0
50.0
100.0
150.0
200.0
250.0
1930 1940 1950 1960 1970 1980 1990 2000 2010
Year
Perc
en
Commercial
Industrial
Open Space
Open Wetland
Pasture/Hay
Residential
Row Crops
Transportation
Utility
Water
Woods
37
20051952
Curtis Creek Sub-estuary:Land Use Change 1952 vs. 2005
38
1943 1952
Curtis Creek Sub-estuary:Land Use Change During Initial 9-year Period of Record
39
Roads in Curtis Creek Sub-estuary
0.000
20.000
40.000
60.000
80.000
100.000
120.000
140.000
1930 1940 1950 1960 1970 1980 1990 2000 2010
Year
kilo
met
ers
Other roads
State & Federal roads
40
Roads – 1952 vs. 2005
Black roads were present in 1952; red roads have been built since that time
41
1943 1952
Curtis Creek Sub-estuary:Road Change During Initial 9-year Period of Record
42
Number of Shoreline Structures: 1943-2005Curtis Bay Sub-estuary
0
50
100
150
200
250
1930 1940 1950 1960 1970 1980 1990 2000 2010
Year
No.
of s
hore
line
stru
ctur
e
43
Shoreline Structures: 1952 vs. 2005Blue structures were present in 1952; red structures have been constructed since that time
44
0
10
20
30
40
50
60
70
1940 1950 1960 1970 1980 1990 2000 2010
Year
Perc
ent o
f lan
d ar
ea CC-Urban
CC-Ag
CC-Forest, Open, Wetl.
RR-Urban
RR-Ag
RR-Forest, Open, Wetl.
Land Use Comparison: Rhode River vs. Curtis Creek
45
Road DensityCurtis Creek vs. Rhode River Sub-estuaries
0
0.01
0.02
0.03
0.04
0.05
0.06
0.07
1940 1950 1960 1970 1980 1990 2000 2010
Year
km ro
ad p
er h
ecta
re
Rhode River
Curtis Creek
46
0
2
4
6
8
10
12
1940 1950 1960 1970 1980 1990 2000 2010
Year
# st
ruct
ures
/ km
sho
relin
e
RR-Structures/km
CC-Structures/km
Shoreline Structures: Rhode River vs. Curtis Creek
47
Annapolis and Baltimore Tidal Data:Annapolis and Baltimore Tidal Data:Data will need to be matched to elevation data to determine flooData will need to be matched to elevation data to determine flooding for marshesding for marshes
Baltimore and Annapolis Yearly Average MSL
-0.35-0.3
-0.25-0.2
-0.15-0.1
-0.050
0.050.1
0.15
1920 1930 1940 1950 1960 1970 1980 1990 2000 2010
Year
met
ers
rela
tive
to M
SL D
atum
AnnapolisBaltimore
MSL = mean sea level
48
Historic Water Quality Data, Yearly Averages:Historic Water Quality Data, Yearly Averages:Salinity and Sedimentation for Curtis Bay (Patapsco River), RhodSalinity and Sedimentation for Curtis Bay (Patapsco River), Rhode and South Rivere and South River
Salinity Yearly Averages
0
2
4
6
8
10
12
14
16
1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006
Year
Salin
ity (p
pt)
PatapscoRhodeSouth
Total Suspended Solids Yearly Averages
0
5
10
15
20
25
30
35
1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006Year
TSS
(mg/
L) PatapscoRhodeSouth
49
Yearly Averages TN with SE bars
0
0.5
1
1.5
2
2.5
1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006
Year
TN (m
g/L) Patapsco
RhodeSouth
Yearly Averages TDP
0
0.02
0.04
0.06
0.08
0.1
1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006
Year
TDP
(mg/
L) PatapscoRhodeSouth
Historic Water Quality Data, Yearly Averages:Historic Water Quality Data, Yearly Averages:Total nitrogen and total dissolved phosphorus for Curtis Bay (PaTotal nitrogen and total dissolved phosphorus for Curtis Bay (Patapsco River), Rhode and tapsco River), Rhode and
South RiverSouth River
50
Nitrogen Additions from Point Source DataNitrogen Additions from Point Source DataCurtis Bay and Patapsco River Point Source TN Discharges
0
2000
4000
6000
8000
10000
12000
14000
Jan-
84
Jan-
85
Jan-
86
Jan-
87
Jan-
88
Jan-
89
Jan-
90
Jan-
91
Jan-
92
Jan-
93
Jan-
94
Jan-
95
Jan-
96
Jan-
97
Jan-
98
Jan-
99
Jan-
00
Jan-
01
Jan-
02
Jan-
03
Jan-
04
Jan-
05
TN (K
g/D
ay)
COX CREEKERACHEM COMILOGFT. MCHENRY TUNNELISG SPARROWS PT.LEBANON CHEM.PATAPSCOPIT. D.M. STEELSEALAND SRVS.US GYPSUM COUSCG CURTIS CREEKW R GRACE
Rhode River Point Source TN Discharge
0
10
20
30
40
50
60
70
Jan-
84
Jan-
86
Jan-
88
Jan-
90
Jan-
92
Jan-
94
Jan-
96
Jan-
98
Jan-
00
Jan-
02
Jan-
04
TN (K
g/D
ay)
MAYO LARGE COMMUNALRIVERBOAT MOTEL
51
The area (m^2) of Phragmites at Rhode River site # 10 (Fox Creek). The logarithmic growth equation is used to interpolate between points. The points in yellow are actual data points, with the annual averages for TN for Rhode River (*1000).
Fox Creek Phragmites with Scaled TN
0500
1000150020002500300035004000
1980 1985 1990 1995 2000 2005 2010
Time
Are
a an
d TN
*100
00Scaled TNInterpolated PhragActual Phrag
52
South River Graphs TKNW: All South River Graphs TKNW: All StationsStations
South River TKNW
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
2
12/14/67 12/13/68 12/13/69 12/13/70 12/13/71 12/12/72 12/12/73 12/12/74 12/12/75 12/11/76 12/11/77 12/11/78 12/11/79 12/10/80 12/10/81
mg/
L
XGE6187
XGE6778
XGE7167
XGE7551
XGE7554
XGE7747
XGE8338
XGF1905
XGF4706
XGF4805
53
Patapsco River Graphs TKNW: All Patapsco River Graphs TKNW: All StationsStations
Nitrogen load is higher than in the South River area; Still no continuous records from any station
Patapsco TKNW
0
0.25
0.5
0.75
1
1.25
1.5
1.75
2
2.25
2.5
2.75
3
3.25
3.5
3.75
4
12/14/67 12/13/68 12/13/69 12/13/70 12/13/71 12/12/72 12/12/73 12/12/74 12/12/75 12/11/76 12/11/77 12/11/78 12/11/79 12/10/80 12/10/81
mg/
L
PAT0176
XIE2293XIE2885
XIE3380
XIE5260
XIE5343
XIE6747
XIF1126
54
CART-based Probability Surface
X1<50
X1<15 X2<7
X2<10
X1<40
E FA
B
C D
Y N
Y
Y
Y
Y NN
N
N 15 50
10
7
40
A
B
C D
E
F
X1
X2
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Susceptibility versus DispersalSusceptibility versus Dispersal
Statistical model is for susceptibilityStatistical model is for susceptibilityAssumed dispersal was not limitingAssumed dispersal was not limitingDispersal and spread mechanisms investigated Dispersal and spread mechanisms investigated separatelyseparately
Karin Kettering; CO2 and nutrient enrichment, Karin Kettering; CO2 and nutrient enrichment, seed production and viabilityseed production and viabilityMelissa McCormick, genetic fingerprinting of Melissa McCormick, genetic fingerprinting of populationspopulations
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Preliminary observations Preliminary observations
Land cover does not adequately describe Land cover does not adequately describe disturbances relevant to disturbances relevant to PhragmitesPhragmites invasioninvasionSignificant interactions and lag times in a Significant interactions and lag times in a multivariate settingmultivariate settingChange in susceptibility state may have Change in susceptibility state may have occurred previouslyoccurred previously
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Future StepsFuture Steps
Historical photoHistorical photo--interpretation of land cover, interpretation of land cover, roads, and shoreline structures completed by roads, and shoreline structures completed by midmid--JuneJuneHistorical photoHistorical photo--interpretation of interpretation of PhragmitesPhragmitesexpansion by midexpansion by mid--AugustAugustStatistical Statistical modellingmodelling through summer, through summer, completed by 2008completed by 2008
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DiscussionDiscussion
A participant asked for confirmation that he had correctly interpreted the graph showing a one-third meter rise in sea level over the past few decades. Dr. Whigham confirmed that this was correct.
One participant asked if Dr. Whigham and his colleagues had examined the percent land cover as a potential indicator. In the participant’s research, he found that percent land cover was important with respect to the amount of freshwater entering the watershed. Dr. Whigam replied that he and his colleagues have found that the non-native genotype Phragmites flourish in brackish conditions; one of the reasons Phragmites are becoming established and spreading is that they do not require freshwater.
A participant asked if the Phragmites could be eradicated. Dr. Whigham responded that in Maryland there are no restrictions on the eradication of Phragmites.
One of the participants asked Dr. Whigham to define metonic cycle. According to Dr. Whigham, a metonic cycle is a drought cycle. It occurs approximately every 10 to 15 years in the area. Dr. Whigham and his colleagues have not yet been able to link this cycle to any of the patterns they have seen.
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Discussion (Continued)Discussion (Continued)
A participant asked if there was concern about insects as predators in the development and spread of Phragmites. Dr. Whigham responded that he did not know how insects might affect Phragmites development and spread. He did not know of any research on this topic.
One participant asked if the graphs on the first slides were on a watershed scale or a 1-kilometer scale. Dr. Whigham responded that those slides were on the scale of the entire estuarine segment. The participant asked if the later data shown were on a scale of 1 kilometer by 1 kilometer. Dr. Whigham confirmed that it was and explained that the two are not very different. The strongest predictor the researchers have seen to date is land use within 500 meters of the watershed.