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Chapter 6
Tidal Forested Wetlands: Mechanisms,
Threats, and Management Tools
Thomas Williams, Devendra Amatya, William Conner, Sudhanshu Panda,
Guangjun Xu, Jihai Dong, Carl Trettin, Changming Dong, Xiaoqian Gao,
Haiyun Shi, Kai Yu, and Hongjun Wang
6.1 Introduction
Tidal wetlands, occurring at the interface between terrestrial and marine systems,
have high rates of productivity and biogeochemical processes driven by periodic
subsidies of water and nutrients brought about by tidal water level fluctuations
(Odum 1988; Day et al. 2007; Baldwin et al. 2009). These tidal wetland areas are
known for performing several important ecosystem services, such as water yield
and storage, flood buffering, filtering and removing/recycling pollutants, storm water
protection, support of entire food webs sustaining human consumption, biodiversity
conservation, recreational opportunities, and wildlife/aquatic habitat provision
(Carter 1990). Forested tidal wetlands, mangroves, and tidal freshwater forested
wetlands (TFFWs) represent an important subset of these valuable coastal wetlands.
Barbier et al. (2011) showed that six coastal landforms (including non-wetland dune
and sea grass beds) produced over US$10,000 ha
1
of environmental service values.
T. Williams · W. Conner
Baruch Institute of Coastal Ecology and Forest Science, Clemson University, Georgetown, SC,
USA
D. Amatya (*) · C. Trettin
USDA Forest Service, Center for Forested Wetlands Research, Santee Experimental Forest,
Cordesville, SC, USA
e-mail: Devendra.M.Amatya@usda.gov
S. Panda
Institute of Environmental Spatial Analysis, University of North Georgia, Oakwood, GA, USA
G. Xu · J. Dong · C. Dong · X. Gao · H. Shi · K. Yu
Oceanic Modeling and Observation Laboratory, Nanjing University of Information Science and
Technology, Nanjing, PR China
H. Wang
Duke University Wetland Center, Nicholas School of the Environment, Duke University,
Durham, NC, USA
©Springer Nature Switzerland AG 2019
S. An, J. T. A. Verhoeven (eds.), Wetlands: Ecosystem Services, Restoration
and Wise Use, Ecological Studies 238, https://doi.org/10.1007/978-3-030-14861-4_6
129
Their evaluation of mangroves included over US$13,000 ha
1
for coastal protection,
erosion control, and fishery maintenance, plus up to US$615 ha
1
year
1
for raw
material production and carbon sequestration. Their evaluation concentrated only on
the coastal zone proper and did not include TFFW as a separate category.
While tidal wetlands provide valuable environmental services, they are greatly
threatened by land use change and sea level rise. Halpern et al. (2008) found moderate
or major human impacts on 42% of the worlds coastal areas. Algoni (2002) reported
that one third of the world’s mangroves had been lost to human activities in the last
50 years. TFFWs with Sitka spruce (Picea sitchensis) in Northwestern North America
have not been recognized in many compilations of TFFWs because so little of this
ecosystem remains after human utilization of these wetlands (Diefenderfer et al.
2008). Sea level rise may displace many tidal wetlands with open water (Craft et al.
2009), but it is more likely that the fate of salt marshes and mangroves will be
determined by a much more complex interaction of sedimentation and productivity
versus decomposition and settling, in relation to the rate of sea level rise (Kirwan and
Megonigal 2013). Ensign et al. (2012) suggest that TFFW may be the most vulner-
able coastal wetland category due to both a decline in productivity caused by salt
inundation and a low sediment input due to river hydraulics.
Both mangrove forests and TFFW are valuable wetlands that are at risk due to
human development and sea level rise. This chapter cannot do justice to the large
body of knowledge already accumulated on these subjects. Readers interested in the
ecology and botany of mangroves will find information in Twilley and Day (2012),
Tomlinson (2016), or Teas (2013). Likewise, TFFWs are the subject of Conner et al.
(2007), and related information can also be found in Barendregt et al. (2009) and
Batzer and Baldwin (2012) although, in general, research on this ecotone between
coastal rivers and marine waters is limited. Ensign et al. (2012) stated that the tidal
river represents a combination of the forces of tidal mechanics studied by oceanog-
raphy and linear hydraulics of riverine floodplains which has not been specifically
studied by any discipline. In this chapter, we will attempt to examine tidal and
freshwater forces that are important to understanding distribution, functions, and
values of tidal forests and the threats posed to these ecosystems from human
development and climate change. We will also attempt to describe general and
global processes with examples from our experience in the Southeastern United
States and China. In addition, we will describe how new advances in remote sensing
and spatial analysis have changed our ability to observe and predict these forces.
6.2 Historical to Present Understanding of the Tide
and Tidal Wetlands
6.2.1 The Tides
Following a trip to what is now England in 330 BC, the Greek astronomer Pytheas
described the connection of the moon to the large daily tide cycles he observed there
130 T. Williams et al.
(Ekman 1993). Nearly 20 centuries later, Newton described scientifically how tides
were driven by gravitation of the sun and the moon. In the late nineteenth century,
Lord Kelvin applied Newtonian physics, Laplace mathematics, and hydraulic
principles of Bernoulli to explain tidal fluctuations as harmonic waves driven by
various periods of astronomical forcing. These relationships were used to develop
tidal predictions until the middle twentieth century (Darwin 1901; Doodson 1921;
Macmillan 1966).
Until the mid-1990s, tidal fluctuation and sea level were measured at hundreds of
locations around the earth. Each gauge stage was recorded relative to a practical
datum for that particular gauge, often chosen to be some depth below mean lower
low water to assure navigation in the local channels. Many nations used profile
leveling between the gauges to develop a national datum relative to mean sea level at
those stations. In the United States, that was the National Geodetic Vertical Datum of
1929. However, the global sea surface is currently measured by satellite altimetry by
the TOPEX/Poseidon and subsequent JASON series satellites (Albain et al. 2017).
The GRACE (Gravity Recovery and Climate Experiment) satellites have developed
maps of the gravity differences to create a global equipotential surface that can be
compared to the reference ellipsoid of satellite orbits. From satellite altimetry, the
range of tides can be estimated for all of the oceans of the world (Fig. 6.1). In
addition to the wide range of tide heights, the period of the tide varies from diurnal
Fig. 6.1 Range of tidal fluctuation for oceans of the world. (Calculated as tidal ranges in meters
from principal lunar and solar semidiurnal and diurnal harmonic amplitudes, 2(M2 + S2 + K1 + O1)
from data by National Tidal Centre, Australian Bureau of Meteorology, in Matthews and Matthews
(2014). Used with permission. The symbols M2, S2, K1, and O1 are standard tidal constituents)
6 Tidal Forested Wetlands: Mechanisms, Threats, and Management Tools 131
(one tide per day) to semidiurnal (two equal tides per day) to mixed (two tides of
differing amplitude and period per day) (Fig. 6.2).
6.2.2 Example of Coastal Wetland Variation Along
the Eastern China Coast
Jiangsu Province, located on the eastern China coast (Lat. 33N Long. 121E), has
the largest tidal flats in China due to large river sediment supply, gentle coastal slope,
and large tidal flows (Gao 2009). Between 1127 AD and 1885 AD, the Yellow River
developed a large delta (40–60 km wide) along the Jiangsu coast before the river
coarse changed to the north in 1885 AD (Zhang 1984). The coastal flats have shown
dynamic redistribution of sediments with erosion near the delta with redistribution
and accretion along the central coast (Gao 2009).
Coastline changes and their implications to coastal wetlands variation are of great
significance to environmental change in coastal zones. Many researchers have
studied satellite coastline mapping in different areas of the world (Dellepiane et al.
2004; Alesheikh et al. 2007; Gens 2010; Zhang et al. 2013; Liu et al. 2016; Nunziata
et al. 2016). However, developing methods to examine coastline change remains a
challenge. High-resolution satellite remote sensing images [synthetic aperture radar
(SAR)] and Landsat TM (Thematic Mapper) data have been used to explore coast-
line changes in Jiangsu and Zhejiang Provinces of China.
Images of Envisat ASAR (Advanced Synthetic Aperture Radar) produced by the
European Space Agency (ESA) and Landsat TM (Thematic Mapper) produced by
the National Aeronautics and Space Administration (NASA) were used in this study.
The Envisat ASAR images, in image mode, possess a spatial resolution of 30 m and
Fig. 6.2 Distribution of tidal periods across the earth (NOAA 2017)
132 T. Williams et al.
a swath width of 100 km. TM images had a spatial resolution of 30 m. Orbit height of
both satellites was 705 km and collected data for the same area once every 16 days.
In ASAR images, land and water features are depicted on a varying gray scale
with the coastline defined as the place with the greatest gradient of gray scale.
Figure 6.3 shows the coastal areas along Jiangsu Province in eastern China on
August 30, 2004 and May 31, 2010. The coastline in 2010 was more offshore than
in 2004 in the ASAR images, suggesting an accretion of sediments.
Zhejiang Province (Lat. 29N Long. 120E) lies south of the delta of the Yangtze
River which once delivered large sediment loads, over 400 Mt year
1
(Chen et al.
1985), to the coastal region. However, human management impacts, primarily
completion of the Three Gorges Dam in 2003, have reduced sediment transport to
the coast by 70% and are expected to decrease transport even more, to approximately
110 Mt year
1
by 2050 (Yang et al. 2014). Understanding the impact of these
changes to the coastal systems is an area of great concern.
The coastal changes of Zhejiang Province can be clearly shown by comparing
TM images, in which the difference between land and sea water is more obvious
in the near-infrared image (Band 5 of TM images) (Fig. 6.4). Apparent coastline
movement, to both the west and the east, between 1984, 1990, 1995, 2001, and 2015
images (Fig. 6.5) indicates both positive (east) and negative (west) changes in coastal
area with no obvious trend.
These findings reveal a major difficulty in satellite-based wetland mapping of the
western coastline of the East China Sea. This region has strong semidiurnal tidal
fluctuations (Fig. 6.1) with a mean tidal range of 2.66 m and a maximum range of
4.62 m in the Yangtze Estuary (Luan et al. 2016). Land slopes of the coastal region
are very flat, 0.00010 to 0.0005 (Gao 2009), allowing large lateral movements of the
water’s edge over the tidal range. In order to use satellite data to determine influences
of human impact, a tidal correction must be applied to each scene analyzed.
Fig. 6.3 Coastlines detected along Jiangsu Province in eastern China on August 30, 2004 (a) and
May 31, 2010 (b) in Envisat SAR images. (c) A comparison of coastlines in 2004 with that in 2010.
Yellow lines in (a) and (b) are the coastlines interpreted from ASAR data
6 Tidal Forested Wetlands: Mechanisms, Threats, and Management Tools 133
Hydrodynamic models are generally used to predict tidal elevations over oceanic
regions. A modern hydrodynamic model is essentially an extension of the analytic
models first proposed by Lord Kelvin in the late nineteenth century.
The development of high speed computing has allowed numerical approximations
of the differential equations describing water movement dynamics that include terms
to define changes in gradient, density, salinity, wind shear, bottom friction, and basin
geometry which cannot be solved analytically. The Princeton Ocean Model
(Blumberg and Mellor 1987) is such a numerical model that has been widely used
and modified to study ocean basins around the world. Song et al. (2013) used a
variation of that model, modified for parallel computer processing (Jordi and Wang
2012) and wetting and drying of tidal flats (Oey 2005), to model the entire East
China Sea. The model was integrated for 56 years (1955–2010) with a full range of
dynamic forces, including tides, sea surface fluxes of momentum, heat, and
Fig. 6.4 Coastlines detected along Zhejiang Province in eastern China on April 23, 1984 (a),
December 04, 1990 (b), October 31, 1995 (c), November 16, 2001 (d), and August 03, 2015 (e)in
TM images. (f) Comparison of coastlines extracted from TM images. Yellow lines mark the
extracted coastlines
134 T. Williams et al.
freshwater, lateral flux (see Fig. 6.6a, b for the model domain). The power spectrum
of the wetland area has several peaks at different periods, ranging from hours to
decades.
The anomaly from the mean value can be viewed as the variation of wetland area,
indicating the difference in dry land between flood and ebb tide. Positive variation
indicates an emerging wetland and lower tide, while negative variation indicated
rising tide and submerging land. Generally, these peaks can be classified into nine
bands: high-frequency (less than half day), semidiurnal, diurnal, semimonthly,
monthly, semiannual, annual, interannual (3–10 years), and decadal (>10 years).
Overall, the range in variation of the wetland, about 5000 km
2
, demonstrates the very
large intertidal wetlands found along the coast of Jiangsu Province and the large
differences that may occur in satellite images from differing stages of the tide.
6.3 From the Ocean to Upland: Modeling Water Levels
In the preceding example, ocean tides directly impacted the extent of coastal tidal
wetlands. The semidiurnal component contributed to more than 60% of the total
wetland variability. In shallow coastal waters, bottom friction induces significant
nonlinearity, resulting in the generation of higher- and lower-frequency harmonics
(Fang et al. 2004; Egbert et al. 2010). The biweekly (fortnightly) periods are caused
by alignment of the sun and moon with phases in the moon. Semiannual periods are
due to more linear alignment of the earth, moon, and sun during the equinoxes.
Annual cycles are produced by seasonal ocean thermal expansion and atmosphere
Fig. 6.5 Time series of changed area along Zhejiang Province compared to the 1984 situation
using TM images
6 Tidal Forested Wetlands: Mechanisms, Threats, and Management Tools 135
ocean interactions. In the example from eastern China, an Ekman current caused by
the East Asian Monsoon, which blows northwesterly during the winter, induces
onshore flow and, southeastward during the summer, creates offshore flow. Ekman
transport (Ekman 1905) also causes long-term cycles associated with variation in
Pacific gyres such as the El Niño-Southern Oscillation (ENSO) and the Pacific
Fig. 6.6 (a) The location of the model domain (the red rectangle) in the East China Sea and water
depth in kilometers; (b) expanded map of model domain with water depth in meters; and (c) the
power spectrum of the wetland area variation. The dashed black line denotes the 95% confidence
level
136 T. Williams et al.
Decadal Oscillation (PDO). Finally, lunar precession alters the coincidence of
perigee, equinox, and lunar phase over a period of 18.6 years.
Numeric hydrodynamic models, calibrated for a particular area, have been devel-
oped and used for a variety of estuaries (e.g., Canestrelli et al. 2010; Kim 2013;
Geleynse et al. 2011; Oey et al. 2007). Such models must be modified with local data
to be used on another. Savenije (1992), in order to develop equations that were
solvable analytically, assumed an ideal estuary, with cross-sectional area decreasing
exponentially with distance from the ocean, bottom slope that was negligible, and
the convergence controlled by damping of the tidal range by friction (Langbein
1963). With that assumption, tidal flow within the estuary could be modeled as a
single wave at the dominant tidal frequency. Savenije et al. (2008) developed
analytical solutions to model flows within such estuaries and showed the utility of
such solutions to ungauged estuaries (Savenije 2015). Although not all estuaries fit
the assumptions of the ideal estuary (Torres 2017), these analytic solutions have
proven useful in understanding relationships related to coastal engineering, sea level
rise, and ecological changes associated with salt intrusion (Savenije 2015).
Lugo et al. (1988) classified forested wetlands as riverine, fringe, and basin for
both freshwater and saltwater ecosystems. They defined basin wetlands as saltwater
if the basin received saline tidal water on spring tides, biweekly higher than normal
tides during full and new moon. In the tropics, mangroves are present in all three of
these wetland types, but TFFWs are most extensive in riverine-estuarine systems and
represent the only tidal forests in temperate regions where high-salinity wetlands are
dominated by marshes (Dame et al. 2000). Modeling water elevations in fringe and
basin-type tidal wetlands can be accomplished with hydrodynamic models outlined
above, although the basin type may also require upland hydrologic models to define
freshwater inputs to the basin. Modeling TFFW water levels must involve influences
of both tidal forcing and the freshwater flow (Ensign et al. 2012). This involves
modeling and mapping the “tidal river”(Hoitlink and Jay 2016).
We will use the definitions of estuary and tidal river proposed by Hoitlink and Jay
(2016), with the estuary upper limit at the upper point of mixed salt and fresh waters.
The tidal river extends from there to the limit where tidal fluctuation of river stage is
identifiable. They suggest the best method to define the upper end of the tidal river be
where the variation of spring and neap tide can be identified by wavelet analysis,
which will be further inland than the traditional head of the tide. These regions also
fit well with the ideal estuary assumptions used by Savenije (2015) to examine
ungauged estuaries. The limit of saltwater intrusion often coincides with the region
where estuary width and flow are no longer decline exponentially with distance
upstream. Likewise, Hackney and Avery (2015) suggest there is a distinct change in
biogeochemical reactions; methanogenesis is replaced by sulfate reduction as an
energy source for respiration where tidal salt concentration is 1 ppt. Horrevoets et al.
(2004) combined the Savenije equations with a one-dimensional model of river
hydraulics to examine influence of freshwater flow on tidal damping. They showed
there is a point where tidal flow matched river flow and velocity is zero for each rate
of river flow. Using a similar approach, Zhang et al. (2013) examined saltwater
6 Tidal Forested Wetlands: Mechanisms, Threats, and Management Tools 137
intrusion in the Pearl River Delta, and Kuang et al. (2017) used the two-dimensional
commercial hydraulic model MIKE 21 to examine water level changes in the
Yangtze Estuary caused by river discharge (over 25,000 m
3
s
1
). Kuang et al.
(2017) were able to estimate sea level rise into the East China Sea caused by river
flood flows. Similarly, Cai et al. (2014) developed an iterative analytical model to
include the residual slope due to nonlinear friction that was shown to have a
substantial influence on tidal wave propagation when including the effect of river
discharge when applied on Modaomen and Yangtze River estuaries. These studies
demonstrate that a hydrodynamic model can be applied throughout the estuary and,
similarly, a linear hydraulic model can be extended into the coastal sea to examine
large river discharges.
Recent development in modeling can define tidal influence in tidal rivers that are
gauged at a point upstream of the tidal reach. Estimating water budget and freshwater
flow rate and timing in ungauged watersheds requires some type of hydrologic
and hydraulic transport model. Several watershed-scale models have been used to
predict the hydrology of inland freshwater forested wetlands (Amatya et al. 2003;Wu
and Xu 2006; Wu and Johnson 2008; Dai et al. 2010,2011; Amatya and Jha 2011;
Amoah et al. 2012; Liu and Kumar 2016; Samadi et al. 2017). Recently, Golden et al.
(2014) reviewed, in detail, models like SWAT, MIKESHE, HSPF, TOPMODEL,
DRAINWAT, VELMA, and GBMM that are applicable for predicting wetland
hydrology and assessing watershed-scale impacts of isolated wetlands. In more
process-based models like MIKESHE/MIKE11 and DRAINWAT, flow in a stream/
river is often modeled using the St. Venant-type continuity and momentum equations,
where the upstream freshwater discharge is known and the tidal stage as the down-
stream boundary condition.
Depending upon the scale and nature of the problems studied, some models have
also been developed specifically for estuarine tidal creeks and associated mangrove
forests (Nuttle and Hemond 1988; Twilley and Chen 1998; Twilley and R-Monroy
2005; Burger et al. 2008; Blair et al. 2012; Ellis et al. 2017). However, there are only
a limited number of watershed-scale models that can reliably address the hydrology,
rainfall-runoff processes (Torres et al. 2004), and stream/river dynamics and their
interactions in a landscape that includes the intertidal zone also affected by wind-
generated waves and tidal motion and storm surge (Larson and Sato 2017).
Although basin forested wetlands cover most of the total intertidal zone in some
regions of South Florida, their ecology is the least understood among mangrove
types because of the complex nature of their hydrology and hydraulics. Twilley and
Chen (1998) used the HYMAN model to represent the hydrology of a mangrove
stand. They found runoff loss of 896 mm year
1
and evapotranspirational loss of
967 mm year
1
with rain input of 1097 mm year
1
indicating subsidy from tidal
inundation that occurred <5 tides per month in February to 30 tides per month in
September.
Meselhe and Habib (2005) tested four different models ranging from Artificial
Neural Networks (ANN), Nonparametric Regression (NPA), US Army Corps of
Engineers’Gridded Surface Subsurface Hydrologic Analysis (GSSHA), HEC-HMS,
138 T. Williams et al.
and MIKESHE to produce hydrologic predictions for a very low-gradient Vermillion,
LA watershed with complex fluvial systems and tidal channels and to assess their
modeling challenges. The authors concluded that while the data-driven ANN and NPR
were able to reproduce the nonlinear and complex stage discharge, all three rainfall-
runoff models produced similar results in predicting storm hydrographs. Rainfall
resolution of 1-h duration was found adequate for simulating hydrologic processes.
Nuttle and Hemond’s(1988) study showed that infiltration and ET during tidal
inundation and precipitation are the dominant hydrological processes in the sediment
on a marsh-wide scale. The authors also suggested that the rate and extent of advective
transport by pore water drainage is controlled by marsh surface topography.
Thompson et al. (2004) linked the MIKESHE with the MIKE11 model to
successfully simulate the dynamics of flooding and groundwater table for a lowland
wet grassland in Southeast England. The authors pointed out the role of topographic
depressions in flooding that enhanced riparian shallow water table conditions as well
as evaporation from flooded ditches, conditions consistent to the TFFW. Most
recently, Larson and Sato (2017) emphasized a greater need of research on processes
and coupling for the complex interactions with strong feedback between the terres-
trial and tidal hydrology that has to be included to improve modeling, particularly for
longer time periods and larger areas in view of climate variability and change.
6.4 TFFW of the Southeastern United States: Examples
from Coastal South Carolina
Although TFFWs have been studied in the Southeastern United States (Conner et al.
2007 and references therein), Coastal South Carolina (SC) is the closest equivalent to
eastern China of our previous examples. Situated between 30N and 35N latitude,
it is also in Köppens climate zone Cf with well-distributed rainfall and mild winters,
as well as semidiurnal tides with a mean range of 1.5–2 m. The primary difference is
in freshwater flow and sediment supply. Since the Eastern North American conti-
nental divide is within 400 km of the Atlantic coast, rivers of the US Atlantic
drainage basin are much smaller than those of eastern China.
South Carolina has three watersheds that extend to the continental divide, with
rivers that form estuaries: Savannah, Santee, and Pee Dee (Fig. 6.7 inset). Tidal data
has been collected for more than 50 years at three stations along the South Carolina
coast: Fort Pulaski, Charleston Harbor, and Springmaid Pier. Savannah River flow is
highly regulated by a series of hydroelectric reservoirs, and the lower estuary is
dominated by the port of Savannah shipping channel. The Santee River flow is also
regulated for hydroelectric generation as well as diverted into Charleston Harbor by
an inter-basin transfer. The Pee Dee River flow is the one least impacted with only
one hydroelectric reservoir in North Carolina and a shallow (<8 m) shipping channel
in the lower estuary.
6 Tidal Forested Wetlands: Mechanisms, Threats, and Management Tools 139
6.4.1 Winyah Bay/Pee Dee River: Sea Level Rise
in an Estuarine TFFW, Salt Impacts
The Winyah Bay estuary in Northeastern South Carolina extends from a 1-km-wide
inlet (Lat. 331201700 N; Long. 791005300 W) for 23 km to near Georgetown, SC. The
estuary is fed by four tidal rivers (Pee Dee, Little Pee Dee, Black, and Waccamaw) in
the US Geologic Survey (USGS 2017) Pee Dee Hydrologic Unit (USGS Hydrologic
Unit Code 0304). Within the estuary, tidal prediction is based on tidal data from the
NOAA gauge at Charleston, SC (NOAA Station 8,665,530, Lat. 32460N, Long. 79
550W). The Winyah Bay system has been the site with a number of studies on the
TFFW (Noe et al. 2013;Kraussetal.2009;Ensignetal.2014a,b). Over 85% of
freshwater flow into Winyah Bay originates from the Pee Dee River (Patchineelam
and Kjerfve 2004), which has USGS Gauge 02135200, located 63 km from the ocean.
The gauge provides continuous data on river stage, flow velocity, instantaneous
discharge, and flow-averaged discharge. In addition to the rivers and estuary, the
system is loosely linked to the North Inlet euhaline tidal marshes (Fig. 6.7 point N).
Work at North Inlet includes early research on marsh response to sea level rise
Fig. 6.7 Winyah Bay estuary and approximate locations of transitions to and within tidal rivers
during average freshwater flow. Letters N, S,T,B,R, and O refer to locations of studies mentioned in
text: N, North Inlet (Gardner and Bohn 1980; Wolaver et al. 1988; Morris et al. 2002); S, Strawberry
Swamp (Williams et al. 2012; Jayakaran et al. 2014; Liu et al. 2017); T, B, and R, Turkey Creek,
Butler Island, and Richmond Island (Noe et al. 2013,2016; Krauss et al. 2009; Ensign et al. 2014a;
Pierfelice et al. 2017); O, Bull Island (Ozalp et al. 2007)
140 T. Williams et al.
(Wolaver et al. 1988;Morrisetal.2002; Gardner and Bohn 1980), as the area has
experienced relative sea level rise for the last 6000 years (Gardner et al. 1992).
Horrevoets et al. (2004) report that within the estuary-tidal river system, a point of
zero velocity will exist where the upstream tidal flow equals downstream freshwater
flow. The location of that point varies with downstream flow of the river and
upstream tidal flow that depends on the tidal range and the cross-sectional area of
the inlet. Ensign et al. (2015) argued that sediment, C, N, and P accumulation peaked
as velocity declined near the head of the tide, declined downstream within the TFFW
zone, and increased again with tidal flows within the oligohaline marsh. The USGS
Gauge 02135200 (USGS 2017) provides insight into variation of both the head of
the tide and the point of balanced upstream and downstream flow in the Winyah Bay
system. In Fig. 6.8a, the head of the tide is downstream of the gauge location for
flows above approximately 730 m
3
s
1
. In Fig. 6.8b zero velocity occurs near this
point at an average daily flow of approximately 155 m
3
s
1
. During the driest decade
(2000–2009) of the 60-year record, Pee Dee median flow was 170 m
3
s
1
, indicating
the point of zero velocity was more often downstream of the gauge site, while the
head of the tide was usually well upstream of the gauge.
TFFW research within the Winyah Bay system evolved from early studies of
productivity on Bull Island (Ozalp et al. 2007). Bull Island (Fig. 6.7 point O) is
formed by one of the several creeks connecting the tidal Pee Dee River to the tidal
Waccamaw River. They found higher productivity on plots adjacent to the Pee Dee
River, but productivity was lower than reported for nontidal wetlands with the same
species.
The sequence of sites (Fig. 6.7 points T, B, R) from Turkey Creek (high salinity),
to Butler Island (medium salinity), to Richmond Island (low salinity) has been well-
studied in terms of mortality, productivity, sediment accumulation, and biogeochem-
istry in order to predict impact of sea level rise on TFFW.
Fig. 6.8 Flow of the Pee Dee River USGS gauge 021135200. Panel areflects discharge and daily
mean for 10 days from 3-5-2016 to 3-15-2016. It demonstrates a constant downstream flow with no
tidal fluctuation above an average flow of 730 m
3
s
1
with flow showing semidiurnal fluctuation
below that flow rate. Panel bfrom the same site for the period 6-15-2016 to 7-5-2016 shows
unidirectional flow with a semidiurnal fluctuation above flow of 155 m
3
s
1
and bidirectional flow
when the average flow was below that value
6 Tidal Forested Wetlands: Mechanisms, Threats, and Management Tools 141
Krauss et al. (2009) found stand basal area and growth decreases from the least
saline (R) to most saline sites (T). There were also differences in soil total nitrogen,
and salinity over 2 ppt resulted in forest decline. Noe et al. (2013) noted an increase
in nitrogen and phosphorus mineralization R <B<T with an increase in salinity but
did not see indication of sulfate reduction. Ensign et al. (2014a) found sediment
accumulations decrease in the TFFW than in the adjacent mesohaline marsh at
Turkey Creek (T) but did not find a significant difference in the TFFW site that
had been found in a tidal river tributary to the Chesapeake Bay (Ensign et al. 2014b).
They attributed the discrepancy to the location of Richmond Island (R) near a creek
connected to the alluvial Pee Dee River. Noe et al. (2016) did find minimum
sediment accumulations for TFFW on these sites when they examined
210
Pb soil
profiles. Along the Waccamaw and Savannah Rivers in South Carolina, an inverse
relationship between litterfall and tree woody growth and increasing salinity has
been observed (Cormier et al. 2013; Pierfelice et al. 2017). Aboveground net primary
productivity (litterfall plus tree woody growth) declined from 1062 g m
2
year
1
in
healthy freshwater swamp to 492 g m
2
year
1
in moderately saline forested
wetland to 79 g m
2
year
1
in highly saline impacted swamp (Pierfelice et al.
2017), but there can be a great deal of variability from year to year depending
upon rainfall and river discharge (Fig. 6.9).
Similar to the Turkey Creek site (T), Strawberry Swamp (S) is a small freshwater
tributary of the Winyah Bay estuary within the zone of mesohaline marshes and has
been subject to forest die back documented by aerial photography since 1949
(Williams et al. 2012). Presently, the area receives water with 2–10 PSU. Liu et al.
(2017) found mortality of species, other than bald cypress (Taxodium distichum [L.]
Rich.), in plots with salinity >2.6 PSU (Fig. 6.9).
Studies in the Winyah Bay estuary-tidal river system have shown that TFFW may
be very susceptible to sea level rise (Figs. 6.6,6.7,6.8,6.9,and6.10). Increasing
salinity associated with sea level rise will lower both biological and sedimentary
input to the soil surface, suggesting they will less likely accrete material at a rate
matching sea level rise. The hydraulics of the tidal rivers and hydrology of the
Fig. 6.9 Change in stemwood productivity along a salinity gradient in the Winyah Bay estuarine
system, SC
142 T. Williams et al.
upland watersheds can also have a large impact on potential accretion. In the Winyah
Bay system, the head of the tide moved over 35 km downstream with a moderately
high freshwater flow.
6.4.2 Charleston–East Cooper River: Sea Level Rise
and TFFW Impact of Higher Freshwater Tides
In contrast to the Pee Dee River system, the Santee system and the Charleston harbor
drainage have been highly impacted by human intervention. By exploiting the
location of a prominent marine terrace (Cooke 1936), the Santee River could be
dammed to produce a large upstream reservoir (Lake Marion) and diverted to create
another large reservoir (Lake Moultrie). From Lake Moultrie another short canal
connected to the upper west Cooper River creates over 20 m of head for hydroelec-
tric generation. Flow from the Santee was diverted into this station in 1947. Siltation
and high dredging costs in the Charleston Harbor required digging another canal
from Lake Moultrie back to the Santee with much less efficient hydroelectric
generation in 1987. The need to maintain a freshwater supply to industrial develop-
ment during the intervening 40 years required that a flow of 142 m
3
s
1
be
Fig. 6.10 Strawberry Swamp, fall 2017. Liu et al. (2017) plots are in deciduous stand in center of
photograph. Dead bald cypress in foreground date from 2003 to 2017
6 Tidal Forested Wetlands: Mechanisms, Threats, and Management Tools 143
maintained in the West Branch of the Cooper River. Due to this, upper reaches of the
East Branch of the Cooper River have a freshwater tide with a mean range of 1.28 m
(Czwartacki 2013) at the upland freshwater forested wetland watersheds maintained
by the USDA Forest Service Santee Experimental Forest (SEF).
Earlier modeling studies using the MIKE SHE model (Dai et al. 2010,2011) for
first- and second-order watersheds successfully captured both daily water table and
streamflow dynamics, while the SWAT model (Amatya and Jha 2011) captured
streamflow dynamics for adjacent third-order forested wetland watersheds at the
SEF site on the South Carolina Atlantic coastal plain. These freshwater wetland sites
are headwaters of the tidally influenced Huger Creek with an area of 235 km
2
that
discharges to the East Branch of the Cooper River draining into the Charleston
Harbor/estuary. Based on a limited shallow groundwater table behavior pilot study
on the intertidal riparian forest buffer affected by diurnal tidal fluctuation (Fig. 6.12),
Czwartacki (2013) suggested the tidal creek functions as a freshwater reservoir to the
adjacent riparian wetland through the daily tide cycle. The results demonstrate the
need to assess nontidal and tidally influenced wetlands separately when considering
their hydrology and functions in the landscape, which is fundamental to understand-
ing how sea level rise will affect habitat quality, nutrient exchange, and sediment
transport to the estuary. Although Larson and Sato (2017) recently reviewed some
complex equations to model short and long waves, nearshore circulation, and
sediment transport for these systems, as a current state of the art, the MIKESHE-
DNDC model linked with MIKE11 using high-resolution geospatial and other
ecohydrological data (as shown below) has been proposed as a tool, after a proper
validation, to assess the fate of upstream freshwater outflow and material from this
intertidal site (Fig. 6.11) during its transport downstream to tidal creek/estuaries that
is further complicated by changing land use and climate change.
Fig. 6.11 Huger Creek site layout of monitoring infrastructure (left); Huger Creek stream channel
at SC Highway 402 Bridge (top middle); hummock and hollow typical micro-topography (bottom
middle); tidal stream and riparian freshwater forested wetland (top-right); and mean water table
elevation trend from downstream tidal to upstream freshwater stream bank (bottom-right)
144 T. Williams et al.
6.4.2.1 Geospatial Modeling of Climate Change Tidal Ranges
on the East Copper River Region
Using a global geospatial framework, Vörösmarty et al. (2010) demonstrated that the
pandemic impacts on both human water security (HWS) and freshwater biodiversity
(BD) were highly coherent, although not identical. They scaled the HWS and BD of
the Atlantic and Gulf coasts of the United States as high to very high. The incident
threats arose from the spatial coincidence of multiple themes, such as water distur-
bance, water resources development, biotic, and pollution factors that includes soil
salinity (Vörösmarty et al. 2010). Freshwater systems, including coastal ones, are
directly vulnerable to human activities (e.g., widespread land cover change, urban
sprawl, and engineering designs like reservoirs, irrigation, and inter-basin water
transfers) (Meybeck 2003; Karl et al. 2009; WWAP 2009) and are expected to be
further impacted by anthropogenic climate change (e.g., tidal surge and subsequent
soil salinity intensification) (Karl et al. 2009). TFFWs are directly impacted by sea
level rise and climate change (Baldwin et al. 2009). The findings by Kirwan et al.
(2010) that coastal marshes with low suspended sediment concentration (SSC) and
low tidal range would be submerged at smaller sea level rise rates than the marshes
with high SSC and high tidal ranges would potentially be applicable to the intertidal
TFFW as well. Enormous quantities of water flow in and out of southeastern Atlantic
coast wetlands twice a day and at higher tidal stages a minimum of two times a lunar
month, which create alternately flooded and non-flooded conditions throughout
these wetlands (Savenije 2005; Baldwin et al. 2009).
Biodiversity in the southeastern Atlantic coastal plain would be immensely
affected when TFFWs are inundated with saline water, and, hence, prior spatial
knowledge would help in its mitigation decision support. Long duration water
intrusion, due to increase in height of the low amplitude tides that inundates
TFFW twice every day, would convert those stands to freshwater marsh (some of
these factors, particularly vegetation, will be discussed in Sect. 6.4.3). Well-drained
soil in TFFW may quickly drain the water, and thus impact is anticipated to be less to
the plant roots and vice versa. Najjar et al. (2000), through their study on potential
impacts of climate change on the mid-Atlantic coastal region, concluded that tidal
surges of more than 2 m above the present mean sea level could be the future norm.
The lower South Carolina coastal plain near Charleston (Fig. 6.12) was delineated
using ArcSWAT (Soil & Water Assessment Tool, http://swat.tamu.edu/) using the
Cooper River confluence of the East and West branch of the Copper as the exit point.
The change in elevation on the river ranges from 0 MSL at Charleston Harbor to
approximately 1.5 m above MSL at the upstream point (USACOE 2017). According
to Kana et al. (1984), the tidal range increases considerably from north to south along
South Carolina’s shoreline, from approximately 1.7 m at the northern border to 2.7 m
at the southern border. Due to the flatness of the study area, soils in this watershed
range from mostly poorly drained with few well drained, possibly enhancing the
impact of tidal inundation on TFFW. It is to be noted that the yellow line in Fig. 6.12
represents South Carolina Division of Natural Resources’(SC-DNR) delineation of
the saltwater/freshwater interface, approximately limit of 1 ppt salinity in tidal creeks.
6 Tidal Forested Wetlands: Mechanisms, Threats, and Management Tools 145
6.4.2.2 Discussion of Modeling Results
Figure 6.13a depicts the area that will be inundated with an assumed 2 m high tide as
the elevation of the spatial locations is 2 m above MSL. Figure 6.13b shows the
four gSSURGO-based soil characteristic rasters (drainage, available water storage
(AWS), soil hydrologic group, and texture) that were classified and reclassified to
show the potential area that would be affected due to saltwater intrusion according to
their ability to drain saline/brackish water after tidal surge. If the tidal inundated area
does not drain quickly, creating saturated soil for long periods, it will likely affect the
flora and subsequent ecosystems of the TFFW. Figure 6.13c shows impacted spatial
locations and classified land cover (including vegetation) of the area, which was
developed with both elevation and soil characteristics integration. The affected land
cover classes are Huger Park (estuarine marine wetland), HC201 (freshwater emer-
gent wetland), HC101 (freshwater forested shrub), and swamp (nomenclature based
on the National Wetland Inventory (NWI) classification scheme). Figure 6.13c also
shows the selected sample point locations for ground-truthing and subsequent
accuracy assessment. Table 6.1 shows the TFFW land cover class distribution that
Fig. 6.12 Area used for studying climate change indicated tidal range impact on TFFW biodiver-
sity in South Carolina
146 T. Williams et al.
will be inundated and affected due to probable 2 m tidal surges. OBIA-based land
cover classification results (2015) differed from the NWI (2011) classification
results, and this was attributed to the temporal difference of the image analysis.
With a total of 13 ground-truthed samples (Fig. 6.12c) selected from freshwater
emergent wetland (8) and freshwater forested shrub (5) classes, a 100% overall
accuracy was obtained with land cover classification, and all locations were
ascertained with zero salinity. The swamp (freshwater herbaceous wetland) and
the estuarine marine wetland classes were visually verified with NWI data layer
(Table 6.1), and 100% accuracy of land use class was obtained with randomly
chosen 11 sample points (Fig. 6.13c).
6.4.2.3 Conclusions of Modeling Efforts
Ultra-high-resolution data like LiDAR are very data-intensive and need advanced
knowledge and high-end processing computers to obtain DEM and other interme-
diary products like nDSM. However, it is very useful as the elevation information
obtained from the LiDAR data is accurate and up-to-date. High-resolution (10 m)
Table 6.1 Land cover distribution of the probable 2 m tidal surge affected TFW in Charleston,
SC area
Land cover class
Area
(ha)
Land cover class
Area
(ha)
NWI classification (https://www.fws.gov/
wetlands/data/mapper.html) OBIA image segmentation
Estuarine marine wetland 1019 Estuarine marine wetland 2794
Freshwater emergent wetland 4955 Freshwater emergent wetland 3485
Freshwater forested shrub 9390 Freshwater forested shrub 7954
Swamp 1418
Fig. 6.13 Results (shown in a workflow basis) of saline water inundation analysis using (a) DEM
(0.75 m), (b) gSSURGO (10 m), and (c) NAIP (1 m) imagery OBIA classification-based decision
support
6 Tidal Forested Wetlands: Mechanisms, Threats, and Management Tools 147
gSSURGO data available in the United States provides a better perspective of
decision-making on such tidal-based TFFW effect analyses. gSSURGO data con-
tains many soil hydraulic characteristics (attributes) that enhance analyses. However,
this model uses a static LIDAR-based estimation of surge elevations, similar to the
method of Craft et al. (2009). Surge estimates made with hydrodynamic models such
as SLOSH (Jelesnianski et al. 1992) or CEST (Xiao et al. 2006) allow estimation of
surge attenuation due to friction and are likely to produce more accurate estimates of
tidal elevation in the upper reaches of the estuary.
6.4.3 Review of TFFW in the Southeastern United States
TFFWs in general are defined as occurring at salinities below 0.5 ppt (Odum et al.
1984), with an important transition occurring as mean salinity levels exceed 2 ppt
(Hackney et al. 2007). These forests are flooded and drained regularly by freshwater
overflow attributed to local high tides, and they are also prone to saltwater influx
during low river discharge (as occurs in drought years) or high storm tides (usually
during hurricanes) and by sea level rise and climate change (Baldwin et al. 2009).
Tide patterns vary across the range of tidal forests from diurnal, semidiurnal, or
mixed and are of different amplitudes and range depending upon the location (Doyle
et al. 2007). Hydrology within these forests can be difficult to interpret because of
river discharge, tidal stage and bidirectional flow, local precipitation, evapotranspi-
ration, groundwater, and prevailing winds (Anderson and Lockaby 2011). River
discharge and tidal stage vary on a seasonal basis and have potential implications for
wetland saltwater intrusion. The geomorphology of the estuary and coast determines
the amplitude, duration, and velocity of ebb and flow stages, resulting in forests
subject to regular flooding from <1 m once a day in the western Gulf of Mexico
(Apalachicola Bay in Florida to southern tip of Texas) to between 2 and 3 m twice a
day on the Atlantic coast (southern North Carolina to Northeast Florida) (Officer
1976; Savenije 2005; Doyle et al. 2007; Wolanski 2007; Baldwin et al. 2009).
Information regarding tidal freshwater swamps is generally sparse in the literature,
but there has been an increased interest in these areas since the publication of the
book Ecology of Tidal Freshwater Forested Wetlands of the Southeastern United
States (Conner et al. 2007) and also the increased coastal urbanization encroaching
these sensitive systems.
6.4.3.1 Composition
Canopy tree richness varies from region to region (see, e.g., Rheinhardt 1992; Light
et al. 2007; Duberstein and Kitchens 2007) depending on hydrology, geomorphol-
ogy, soils, and salinity (Sharitz and Mitsch 1993; Brinson 1995; Lockaby and
Walbridge 1998; Mitsch and Gosselink 2000), but bald cypress (Taxodium distichum
[L.] Rich.), water tupelo (Nyssa aquatica L.), swamp tupelo (Nyssa biflora Walter),
148 T. Williams et al.
red maple (Acer rubrum L.), and ash (Fraxinus spp.) are the tree species most
commonly associated with TFFW of the Southern United States. These trees are
sensitive to saltwater intrusion, with bald cypress generally being the most salt
tolerant, although its growth is reduced considerably at mean annual salinity concen-
trations above 2 ppt (Hackney et al. 2007; Krauss et al. 2009). Understory trees,
shrub, and herb layers are generally sparse and low in diversity because of dense
canopy and frequent flooding in the upper reaches of the river. However, as salinity
levels increase, tree canopy decreases, resulting in more extensive and species-rich
subcanopies and herbaceous layers (Mitsch et al. 2009).
There are areas on the Atlantic coast (primarily North Carolina) and Gulf Coast
(Mississippi) where Atlantic white cedar (Chamaecyparis thyoides [L.] Britton,
Sterns & Poggenb.) occurs in areas subjected to wind-driven tides (Keeland and
McCoy 2007), and the trees are concentrated on hummocks (Laderman 1989).
Atlantic white cedar is not typically tolerant of salinity (Moore and Carter 1987),
and mature tree vigor is impacted when storm surges bring brackish waters into these
forests (Keeland and McCoy 2007).
In the Big Bend area of Florida, islands of freshwater forest (isolated remnants of
a formerly continuous forest that is retreating landward) are found. These islands are
dominated by cabbage palmetto (Sabal palmetto [Walt.] Lodd ex Schult) and
southern red cedar (Juniperus virginiana var. silicicola Small) that occur on elevated
limestone substrate surrounded by salt marsh (Kurz and Wagner 1957; Williams
et al. 1999a,b,2007; DeSantis et al. 2007; Geselbracht et al. 2011). Cabbage
palmetto, which is one of the most salt-tolerant trees in the Southeastern United
States (Perry and Williams 1996), is the sole tree species on the most saline islands.
6.4.3.2 Hydroperiods
A wetland’s hydroperiod (flood frequency, duration, depth, and timing) determines
which species will germinate, become established, and persist in a given wetland
area. Seeds of bald cypress and water tupelo, two of the most flood-tolerant trees
found in tidal freshwater forested wetlands (Hook 1984), do not germinate in
continuously flooded soils (DuBarry 1963). Increased flooding and extended
waterlogging result in decreased photosynthesis (McLeod et al. 1996) and growth
(Pezeshki et al. 1987; Young et al. 1995), with eventual mortality to those species
that are less flood tolerant (Harms et al. 1980).
6.4.3.3 Salinity
Rising sea level leads not only to increases in hydroperiod with possible increased
runoff but increased salinity as well. Bald cypress trees seem to be the most salt-
tolerant trees in TFFW, with Louisiana genotypes more tolerant than genotypes from
other southeastern states (Conner and Inabinette 2005). Successful bald cypress
regeneration and establishment along the Northeast Cape Fear River only occurred
6 Tidal Forested Wetlands: Mechanisms, Threats, and Management Tools 149
in areas with interstitial salinities less than 2 ppt (Fleckenstein 2007). When inter-
stitial salinity becomes too high for even bald cypress to survive, TFFWs undergo a
state change to oligohaline marsh (Effler et al. 2007; Fleckenstein 2007). When tidal
flooding frequency exceeds 10–20 days per year, natural seedling emergence and
survival of cabbage palm trees in Florida’s tidally influenced hydric hammocks
decline drastically (Williams et al. 2007).
The establishment of species zonation along salinity gradients is thought to result
from pulses of saltwater, rather than slow gradual change (Duberstein 2011). Salinity
pulses can be a result of storm surges that occur frequently enough to have important
effects on tidal freshwater forested wetlands (Light et al. 2007) or from extended
drought conditions. Tree mortality rates of roughly 10% per year occurred for three
consecutive years following a saltwater intrusion event into the swamps immediately
adjacent to Maurepas Lake (Louisiana), though bald cypress trees were affected less
(Shaffer et al. 2003). Brinson et al. (1985) and Baldwin (2007) agree that pulses such
as these shape the structure and productivity of tidal freshwater swamps more than
long-term averages.
6.4.3.4 Productivity
Growth of bald cypress is reduced considerably at mean annual salinity concentra-
tions above 2 ppt. Above this level, basal area, forest height, and basal increment are
not sufficient to allow persistence of any forested wetland tree species into the future.
Studies on the lower Cape Fear (NC), Waccamaw River (SC), Savannah River (GA),
and southeastern Louisiana found that tidal bald cypress swamps are all actively
converting to marsh (Hackney et al. 2007; Krauss et al. 2009; Shaffer et al. 2009). In
Louisiana, bald cypress sites that are at or above the 2 ppt salinity threshold appear to
be converting to marsh at a slower rate, but these sites are definitely deteriorating
(Krauss et al. 2009). With increasing salinity, tree growth is diminished, and there is
increased mortality of tidal swamp trees. While mean annual site salinity ranged
from 0.1 to 3.4 ppt, sites with salinity concentrations of 1.3 ppt or greater supported a
basal area of less than 40 m
2
ha
1
. Where salinity was 0.7 ppt, basal area was as high
as 87 m
2
ha
1
(Krauss et al. 2009). Eventually, these forests become marsh with
standing snags, earning these areas the name “ghost forests.”
6.5 Summary and Future Prospects
Although study of tidal forested wetlands has been relatively recent, the potential to
increase our understanding of these wetlands has been greatly increased by devel-
opment of a number of advances in other sciences. Although the strong role of the
phases of the moon on tidal stage has been recognized for over 2000 years, our
ability to measure and predict tidal motions over the globe only occurred following
150 T. Williams et al.
the development of satellite altimetry with the strong feedback between satellite
altimetry and hydrodynamic modeling. We can now measure global decadal average
sea level rise with errors on the order of 0.4 mm year
1
although annual estimates
vary by well over 1 mm year
1
(Albain et al. 2017).
As demonstrated by the East China Sea wetland example, robust hydrodynamic
modeling must be combined with remote sensing to determine the tidal stage at the
time each scene is collected to produce meaningful environmental information about
tidal wetland status. Such methods are likely to also be highly beneficial to our
studies of changes to TFFW and mangrove ecosystems.
A great deal of our present knowledge of TFFW comes from plot research. Most
hydrologic understanding comes from empirical measurements made on plots that
were chosen due to vegetational characteristics. Modern hydrodynamic, hydraulic,
and hydrologic modeling may be capable of estimating all the variation in TFFW
wetlands caused by interactions of rainfall, upland runoff, river flooding, and tidal
fluctuations. Understanding these hydrologic factors may put our previous physio-
logical and biogeochemical findings into a framework that would allow prediction of
the factors that are important to productivity of TFFW. Such understanding may be
critical as Woodruff et al. (2013) suggest that uncertainty in changes in predicted
number tropical cyclones, probable increase in cyclone intensity, and sea level rise
will combine to impact coastal regions in ways that haven’t occurred since the end of
the ice age.
Acknowledgments We thank anonymous reviewers for their thoughtful comments and sugges-
tions, which improved the manuscript. Part of the research included in this review was funded by
the US Geological Survey, Climate and Land Use Change Research and Development Program,
and also supported in part by the National Institute of Food and Agriculture, US Department of
Agriculture, under award number SCZ-1700531. Technical Contribution No. 6654 of the Clemson
University Experiment Station. Thanks are also due to USDA Forest Service Southern Research
Station and 10th INTECOL Conference for their support of the INTECOL special session followed
by initiating this chapter.
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