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Landscape evolution space and the relative importance of geomorphic
processes and controls
Jonathan D. Phillips ⁎
Southern Landscape Systems Research Program, Department of Geography, University of Kentucky, Lexington, KY 40506-0027, USA
a b s t r a c ta r t i c l e i n f o
Received 12 November 2008
Received in revised form 13 January 2009
Accepted 15 January 2009
Available online 27 January 2009
Landscape evolution space
The concept of landscape evolution space (LES) is introduced as a tool for assessing landscapes and geomorphic
systems, intended to be a systematic means for assessing the various factors that contribute to the potential for
change in geomorphic systems. The LES conceptual model is based on the energy and mass available to drive
and accommodate landscape evolution. An n-dimensional landscape evolution space is deﬁned not only by
spatial coordinates, but also by the availability of mass and energy. The LES is thus a space or hypervolume
representing the resources available for geomorphic evolution and landscape change. An expression for LES is
derived based on elevation, material density, surface area, and inputs of solar, meteoric, and biological energy
and mass. Though primarily an heuristic device, the LES model can be used to address concrete problems. Two
examples are given. In one, increased surface area due to topographic roughening and dissection of an incised
plateau is found to only slightly offset erosional removals of mass in terms of the magnitude of the LES. In
the other, sensitivity of coastal plain rivers to several impacts of sea level and climate change is explored. The
LES model also leads to the concept of a geomorphological niche, representing the resources available to drive
or support a speciﬁc process or suite of processes. Considerations of landscape evolution have traditionally
focused on the interplay of endogenic vs. exogenic processes, uplift vs. denudation, or soil formation vs. erosion.
The LES model explicitly broadens the conceptual framework of landscape evolution beyond the traditional
© 2009 Elsevier B.V. All rights reserved.
1.1. Landscape evolution space concept
The presence, intensity, and relative importance of geomorphic
processes and controls exhibit immense geographical variability,
associated with spatial variations in climate, tectonic setting, environ-
mental and geologic history, biological activity, human agency, and
other factors. Our perception and understanding of processes, controls,
and their relative impacts are inﬂuenced not only by their intrinsic
real-world variability, but also by our ability to observe or measure
them, and by our conceptual frameworks and experiences. The
interpretation of layering in soils, sediments, and weathering proﬁles,
for example, is inﬂuenced not only by the features themselves, but
also by the training, background, and dominant paradigms of soil
science, sedimentology, archaeology, and geomorphology (Phillips
and Lorz, 2008).
In this paper the concept of landscape evolution space is introduced
as a tool for assessing landscapes and geomorphic systems. The
concept is intended to be a systematic means for assessing the various
factors that contribute to the potential for change in geomorphic
systems. Systematic application of the landscape evolution space
framework obliges consideration of all major types of energy and mass
inputs and resources, and provides a means to evaluate their relative
importance. This is important because background and experience
inﬂuence perceptions (and thus analyses and interpretations) of, for
example, whether or not landscapes are geomorphically active. A
tectonically stable tropical plain, for instance, may appear relatively
inactive with respect to mechanical denudation and sediment
transfers, but may be extremely active with respect to chemical
weathering and bioturbation. Conversely, a cold high-altitude land-
scape may appear somewhat sterile to an earth scientist accustomed to
thick regoliths, rapid chemical weathering, and extensive bioturbation,
when in actuality sediment production by frost-shattering and mass
movements may be extensive.
In addition, some contemporary debates and controversies in
geomorphology are focused on the relative importance of particular
forcings or environmental controls. The role of biological processes vs.
abiotic factors is one example (e.g., Butler, 1995; Wilkinson and
Humphreys, 2005; Dietrich and Perron, 2006; Corenblit et al., 2008;
Phillips, 2009b). Another is the relative inﬂuence of sea level,
tectonics, and climate on ﬂuvial systems (e.g., Blum and Tornqvist,
2000; Vandenberghe, 2002; Schumm, 2005; Blum and Aslan, 2006).
Further, conventional notions such as the primacy of sea level change
Geomorphology 109 (2009) 79–85
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in coastal sedimentary systems, the effectiveness of solar heating as a
weathering process, and limited chemical weathering in cold climates
are being challenged (e.g., Catuneanu, 2002; Dixon and Thorn, 2005;
McFadden et al., 2005; Turkington and Paradise, 2005; Yoshida et al.,
2007; Dixon et al., 2008; Moucha et al., 2008).
The landscape evolution space (LES) model is a tool for addressing
these issues, for comparing different sites and environments, and for
placing results and observations in a broader context. The LES
construct is an heuristic device rather than a mechanistic or predictive
model, but can be usefully applied to speciﬁc problems, as shown
below in two case studies. The LES conceptual model is also still
evolving, and is presented here in the hope that it can be expanded,
elaborated, and improved by others.
1.2. Energy and mass inputs and resources
The LES concept is based on the energy and mass available to drive
and accommodate landscape evolution. A global energy balance
approach to geomorphology was developed by Devlin (2003), and a
comprehensive survey of earth surface system energetics by Smil
(2008).Phillips (20 09b) compared biological energy inputs to
geological processes with those associated with uplift and potential-
to-kinetic energy conversions during denudation. The energetics of
soil formation was investigated by Volobuyev (1964, 1974),Rasmus-
sen et al. (2005), and Rasmussen and Taylor (2007). Together, these
papers suggest that the energy inputs to landscape evolution include
solar radiation, radiogenic heat from radioactive decay within the
earth, rotational energy, and gravity. Potential energy is stored as
landscape relief, as heat in the solid earth, and in the biosphere. Solar
energy also powers climatological and hydrological processes that
drive geomorphic change. The mass inputs are the rock mass within
the landscape, uplift of new rock mass into the unit of study, mass
ﬂuxes from other landscape units, meteoric inputs, and biomass.
The energy balance according to Devlin (2003) is
Ereceived =Elost +Estored =Esolar +Egeothermal +Erotational
ð Þ +ΔEhydrologic +Ebiota +Epotential +Eheat
! " ð1Þ
represents the solar inputs; E
is the radiogenic heat
from radioactive decay within the earth, and E
energy. Energy is stored as relief (E
), biomass (E
) and heat
). The energy associated with atmospheric processes and the
hydrologic cycle is denoted by E
Devlin (2003) reduced Eq. (1) by assuming that E
is in steady-
state and not signiﬁcantly changing, and that E
is small relative
to potential and geothermal (endogenic) energy. The latter is
reasonable because the Coriolis effect inﬂuences the direction and
distribution, but not the energy, of ﬂuid ﬂows (Devlin also assumed
steady-state in biological energy storage, but that assumption is not
made here). The simpliﬁed balance is then
! " =Eradiated +Ereflected
ð Þ +Ehydrologic +Epotential +Ebiota
Using Mto represent mass gains or losses above a given vertical
base or reference level, and with notation analogous to Devlin (2003),
a mass balance can be presented as
Mreceived =Mlost +Mstored =ΔMuplift +Mbaselevel +Mgeomorphic +Mhydrologic +Mbiota
is the mass uplifted above (or subsided below) the reference
level by tectonic or isostatic processes; M
associated with sea level or local base level movements; M
represents gains or losses due to mass ﬂuxes; M
meteoric inputs or losses; and M
the net change in biomass.
These conceptual energy and mass balances provide the basis for
deﬁning landscape evolution space.
2. Landscape evolution space
An n-dimensional landscape evolution space is deﬁned not only by
spatial coordinates, but also by the availability of mass and energy as
described above. The LES is a space or hypervolume representing the
resources available for geomorphic evolution and landscape change.
The total geomorphic productivity G(deﬁned as geomorphic work,
rate of mass ﬂux, or some other appropriate measure) is a function of
the size of the LES and the rate (r) at which geomorphic processes
convert mass and energy per unit of LES:
G=r S ð4Þ
Sdenotes the size or extent of the LES. This paper emphasizes the
extent of the LES, though Eq. (4) will be revisited later.
To deﬁne the LES, we start with a topographic evolution space
which is a function of the total mass of material above base level. This
is consistent with potential energy of mass transfers (PE) within a
deﬁned geomorphic system,
PE =m g h ð5Þ
Where mis the mass, gthe gravity constant, and hthe height above
the system's base level. Total potential energy in a landscape is then
PE =HρA g H =H2ρA g ð6Þ
where His the mean elevation above base level, ρis mean density
of the rock and regolith, and Ais the surface area. Base level may be
sea level or the geoid, or some locally or regionally deﬁned reference
level. Surface area is based on actual area exposed to solar and
meteoric inputs rather than a projected plane. Thus, for example, for a
geometric space with rectangular boundaries, area would be calcu-
lated based on mean length times mean width, with the later based on
actual slope distances (i.e., straight-line walking vs. as-the-crow-ﬂies
Eq. (6) does not account for additional inputs of matter and energy,
such as insolation and precipitation. Tectonic forcings and base level
change can be presumed to be reﬂected by H. Absent, or indepen-
dently of, biota, inputs of solar radiation energy and moisture are
related to the surface area, so that
LES =H2ρA g ksAkpA=H2ρg kskpA3ð7Þ
are parameters reﬂecting the prevailing climatic
inputs of solar energy and precipitation with dimensions of mass
divided by time squared (M T
Biota are capable of capturing and storing solar energy which would
otherwise be reﬂectedor dissipatedas heat. Vernadsky (1926), generally
credited with the origin of the concept of the biosphere, viewed the
biosphere as a planetary membrane for capturing and processing solar
radiation energy. Organisms, particularly vegetation, may also serve
to maximize the rates of moisture and other biogeochemical cycling
(Eagleson, 2002; Lapenis, 2002). P
is deﬁned as that portion of
biological productivity which provides a net energy supplement to
geomorphic processes—accounting for biological weathering and mass
transport, minus any effects (such as increases in surface resistance)
which reduce the rate of geomorphic change (see Phillips, 2009b). We
LES =H2ρg kskpA3Pgð8Þ
Potential energy, the k
Aterms, and P
all have dimensions
of M L
80 J.D. Phillips / Geomorphology 109 (2009) 79–85
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One way to assess the relative importance of various factors
deﬁning LES is via a simple ratio comparison. Using subscripts 1, 2 to
denote the observed, modeled, or hypothesized states of the land-
scape at any two times or under any two scenarios,
ð Þ ks2 =ks1
ð Þ kp2 =kp1
! " A2=A1
ð Þ3Pg2 =Pg1
In many cases, where rock mass is large relative to regolith, (ρ
)≈1. Further, in some circumstances k
, and P
may also be
considered constant, providing other possibilities for simplifying Eq. (9).
Two example applications are given below.
3. Fluvial dissection, mass removal, and surface roughening
3.1. Study area
The dissection of landscapes by ﬂuvial action removes mass, and
thereby, other things being equal, reduces the LES. However, incision
of low-relief plateaus by ﬂuvial networks increases the roughness and
the surface area, the effect of which is to increase the size of the LES.
With ﬁxed horizontal boundaries, Acan be changed only by changes
in relief and surface roughness. The relative importance of mass
removal and increased surface area due to dissection was investigated
for a portion of the Cumberland Plateau in Kentucky and Tennessee.
The area was chosen due to other research in progress on the Big
South Fork River and its tributaries, a portion of the drainage basin of
which is in the study area (Fig. 1).
The Cumberland Plateau is the southern portion of the Alleghany
Plateau section of the Appalachians. Within the study area the geology
consists of horizontally-bedded Paleozoic sedimentary rocks, with
little or no evidence of tectonic deformation. Sandstones comprise
the ridgetops and most of the higher elevation units, with shales,
limestone, and coal beds occurring at lower elevations. No uplift or
other neotectonic activity has been proposed or demonstrated in the
area, and 1:24,000 scale geological maps of the area show no mapped
faults. The review of Wheeler and Crone (2001) of known and
suggested Quaternary faulting in the midcontinental U.S. west of the
Appalachians does not indicate any activity in the Cumberland Plateau
region of Kentucky and Tennessee. Thus any late Cenozoic uplift which
is occurring must be isostatically driven.
The Big South Fork (sometimes called the Big South Fork of the
Cumberland River) is a tributary of the Cumberland River, which
drains to the Ohio River. Streams of the study area began the most
Fig. 1. Shaded relief map of the study area in the Big South Fork area, Tennessee and Kentucky, showing the strongly dissected topography in the Cumberland Plateau region.
81J.D. Phillips / Geomorphology 109 (2009) 79–85
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recent episode of incision about 1.5 Ma, in response to glacially-driven
reorganization of the Ohio River drainage system (Andrews, 2004;
Anthony and Granger, 2007). Topography is typical of a dissected
plateau, with topographically accordant ridgetops and peaks, and
deeply incised stream valleys with steep hillslopes.
Mass removal was calculated relative to the surface represented by
the current ridgelines and peaks. A digital elevation model (DEM)
with a horizontal resolution of 10 m was obtained from the U.S.
Geological Survey and a surface plot was produced. An imaginary
plane resting on top of the surface (imagine a ﬂat board supported by
the highest peaks and ridges; Fig. 2) was the reference surface for
calculating mean removal as the elevation difference between the
reference level and the actual terrain. Base level was taken as the
elevation of the Big South Fork as it exits the study area. Thus (in the
framework of Eq. (9)), H
is the elevation of the upper reference
surface minus base level elevation, and
where his the local elevation. Any isostatic compensation for mass
removal should affect the entire approximately 920 km
equally, and is thus not included in comparing the current surface to
the ridgetop reference plane.
Changes in surface area were calculated using a number of sample
transects across the study area, comparing the horizontal distance
) to the cumulative slope distance, D
(that is, as-the-crow-
ﬂies distance compared to distance covered by walking the same
path). This comparison is based on an assumption of an initially
relatively smooth surface where D
. With A
taken to be an
original ﬂat surface and A
the current surface, change in surface area
was then estimated as
A1=A2=Dhoriz =Dslope ð11Þ
All DEM analyses were conducted using RiverTools
Soil thicknesses are minimal in the study area (generally b0.5 m
except in valley bottoms) and unknown for the pre-incision surface.
However, as they are in any case small compared to rock mass above
the local base level, it was assumed that ρ
≈1. Quaternary climate
changes indicate that k
, and P
have no doubt changed during the
plateau dissection. However, for purposes of isolating the relative
inﬂuence of mass removal and topographic roughening (increase of A),
they are neglected in this example. Then, for this problem,
Minimum local base level elevation is about 220 masl, the mean
elevation of the slightly tilted upper reference surface is about 504 m,
and the mean elevation of the study area is about 410 m. Fluvial
dissection has removed a third of the mass above the local base
level, and H
=0.666. The surface area has increased by nearly 3%
=1.084, indicating that the increased surface area has
increased the landscape evolution space by about 8%. However, this is
more than offset by the decrease in H, which has decreased LES by
more than half [(H
=0.444]. Thus results in the study area
suggest that surface roughening and the associated increase in surface
area only slightly offsets the effects of mass removal with respect
4. Sea level, climate, and coastal plain rivers
The relative importance of sea level and climate (as well as
tectonics, human agency, and other factors) in determining the forms
and process regimes of coastal plain rivers has long been a source of
controversy. The coastal plain of Texas is no exception. Notwithstand-
ing debates and uncertainties about the pace and timing of sea level
changes, and of Quaternary climate variations, several recent efforts
have been made to untangle the inﬂuence of climate and sea-level on
observed features of alluvial valleys in the region (e.g., Morton et al.,
1996; Blum and Price,1998; Otvos, 2005; Blum and Aslan, 2006; Sylvia
and Galloway, 2006; Phillips and Slattery, 2008; Taha and Anderson,
2008; Phillips, 2009a).
Climate change, both in general and in southeast Texas, inﬂuences
ﬂuvial systems chieﬂy via the discharge regime and sediment supply,
both directly via precipitation, temperature, and the water balance,
and indirectly via vegetation. Climate is thus reﬂected in the k
components of the LES model.
The most obvious inﬂuence of sea level is via H, as rising or falling
sea level directly increases or decreases mass above base level. On
low-relief coastal plains, sea level changes may also lead to signiﬁcant
inundation or exposure of land areas, thus changing the surface area
if interest is restricted to the subaerial landscape. This is not to deny
the signiﬁcance of submarine processes; an LES-based analysis of an
Fig. 2. Vertically-exaggerated surface plot of the study area shown in Fig. 1. The upper reference surface is an imaginary plane resting atop the high points, and mass removal and
surface roughness are calculated relative to the reference surface.
82 J.D. Phillips / Geomorphology 109 (2009) 79–85
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estuarine and/or marine geomorphic system, could for example,
incorporate sea level rise in terms of increases in the geographic
boundaries of the LES.
4.1. Study area
For this illustration, characteristics of the Texas Coastal Plain in the
general vicinity of the lower Brazos River, southwest of Houston, are
used. The study area (Fig. 3) has a humid subtropical climate, and the
topography ranges from virtually ﬂat in the coastal marshes to gently
rolling. The case study is limited to the lower coastal plain, where
valleys are cut into late Quaternary material. Recent reviews of
debates about the Quaternary geologic framework and sea level
history of the region are provided by Blum et al. (2002),Rodriguez
et al. (2004), and Otvos (2005). More detailed information on the
lower Brazos River area is given by Sylvia and Galloway (2006),
Phillips (2007a, 2009a) and Taha and Anderson (2008).
The outer coastal plain in the lowermost Brazos River basin is
generally about 70 km wide, with a mean elevation of 6.2 m above sea
level. The mean coast-parallel slope gradient is about 0.0003. Thus,
per meter of coastline, there are about 434,400 m
above sea level.
These values were used to determine effects of sea level rise using a
simple “bathtub”model, which involves inundating existing topo-
graphy without accounting for morphological changes in response to
changing base levels. Estimates were made on a per-unit-length of
coastline basis, with the distance of retreat calculated as sea level rise
divided by mean coastal plain slope gradient. The loss of mass above
sea level is calculated from sea level rise over the width of the coastal
Potential changes in climate-related forcings were based on
scenarios of increased temperature, decreased precipitation, and
both decreased and increased biological productivity (with an
emphasis on increases) relative to 20th century norms in the lower
Brazos River area (mean annual precipitation of 1320 mm; mean
annual temperature 20.3 °C). It was assumed that changes in k
are directly proportional to changes in temperature and precipitation,
respectively. Temperature increases of up to 6 °C and precipitation
decreases of as much as 600 mm were considered. P
proportional to net primary productivity (NPP), which is inﬂuenced
by temperature, moisture, and atmospheric CO
Fig. 3. Shaded topographic map of the coastal plain in the lower Brazos River area, Texas, derived from a digital elevation model with 30-m horizontal resolution.
Fig. 4. LES ratios associated with surface area (A
and mass above base level (H
for sea level rise up to 3 m.
83J.D. Phillips / Geomorphology 109 (2009) 79–85
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Climate and crop yield models predict temperature increases,
precipitation decreases, and slight decreases to larger increases in
crop yields (assumed related to NPP) for Texas. The NPP/crop yield
increases are due to longer growing seasons and fertilization/stimulus
effects of increased atmospheric CO
The mass component of LES (decreased H) was more sensitive to
higher sea levels than area, with increasing disparities at larger values
of sea level rise (Fig. 4). The (A
term ranged from 0.986 (1.4%
decrease) with a sea level rise of 0.1 m to 0.63 (37% decrease) with a
rise of 3 m. The height above base level term (H
0.968 (3.2% decrease) to 0.266 (74.4%) over the same span of sea level
The solar input term (k
), based on temperature changes,
varied from a 1% rise (1.01) associated with a temperature increase of
0.2 °C to an increase of nearly 30% (1.296) with a 6 °C warming. A
precipitation decline of 20 mm year
yielded a k
value of 0.985
(1.5% fall), ranging down to k
= 0.545 (45.5%) with precipitation
decreased by 600 mm. These are shown in Fig. 5, along with changes
ranging from a 10% decline (P
=0.9) to a nearly 50%
The LES model can be used to examine changes in LES with any
particular climate and sea level scenario. For instance, a sea level rise of
0.5 m, 3 °C warming, precipitation decline of 300 mm year
, and P
increase of 15% leadsto a decrease in LES (LES
= 0.802). The most
important factor in that decline is the decrease in precipitation,
delivered to a smaller area [(k
The model could also be manipulated to evaluate potential effects of
increased mass input via deposition associated with rising sea level.
Traditionally, considerations of landscape evolution have focused
on the interplay of opposing forces or trends, such as endogenic vs.
exogenic processes, uplift vs. denudation, or soil formation vs. erosion.
Energy considerations have, by and large, been restricted to conver-
sion of potential to kinetic energy associated with mass transfers from
higher to lower elevations. One motivation for the landscape evolution
space concept is to propose a heuristic device which explicitly
broadens the conceptual framework of landscape evolution beyond
the dialectics outlined above. A secondary aim was to bring additional
attention to the role of solar and biological energy in geomorphology.
The LES concept is, like landscapes themselves, still evolving. Many
ﬂaws and shortcomings undoubtedly exist in the LES model outlined
above. However, these may be viewed as opportunities for enhance-
ments, improvements, and adaptations. A few of these are outlined
5.1. Productivity and geomorphological niches
We return now to geomorphic productivity (Eq. (4)), reﬂecting the
actual rates and magnitudes of geomorphic activity, as opposed to the
LES alone, which reﬂects potentials. The rate (r) at which geomorphic
processes convert mass and energy per unit of LES varies with
different processes, materials, and environments within a landscape.
We can therefore expand Eq. (4) to
G=r S =XGi=XriSið13Þ
where the LES is divided into i=1, 2,..., Ncomponents where speciﬁc
relationships exist between processes and portions of the resource
If the components iare based on particular processes or process
regimes, then the components of S
would be deﬁned relative to the
processes in question, and S
can be interpreted as the geomorpholo-
gical niche for process i, representing the mass and energy resources
inﬂuencing the process. This is analogous to the ecological niche
concept, where the niche is a hypervolume representing the resources
and habitat elements associated with a given species.
Exploration of landscape evolution in terms of these geomorphic
niches could provide new insights, and would explicitly incorporate
the rate (r) as well as the LES (S) factors, and in much greater detail
than the broad-brush illustrations in this paper.
More generally, incorporation of r-factors allows an expanded
variation on Eq. (9):
ð Þ½ $ H2=H1
ð Þ ks2 =ks1
ð Þ kp2 =kp1
! " A2=A1
ð Þ3Pg2 =Pg1
5.2. Climate and biotic factors
The LES model presented here represents climate inputs as simple
linear functions of surface area (the k
sophisticated representations are possible, and presumably desirable
in cases where solar energy and climate factors are of particular
interest. With respect to biotic effects, gross or net primary
productivity is probably a good indicator of the biological energy
inputs potentially available for geomorphic processes, but the
biologically relevant fraction of this is unquestionably both highly
variable and poorly understood at present (Phillips, 2009b).
5.3. Topographic factors
Topography is denoted in the current version of the LES model by
Hand A. Topographic changes relevant to the landscape evolution
potential (S, as opposed to r) are probably reasonably well
represented. However, topographic changes often result in changes
in slope gradients which may profoundly impact gravity-driven
processes. Changes in surface area may also inﬂuence weathering
rates via surface exposure, independently of the k
Other feedbacks may also be relevant, such as fracturing due to
lithostatic pressure release during landscape dissection.
In general, the LES model is highly simpliﬁed, but a word of caution
is in order with respect to LES elaborations. The temptation is always
present to introduce more factors and more complex representations.
However, increasing size and complexity does not always improve the
Fig. 5. LES ratios for solar energy/temperature (k
), precipitation (k
) energy inputs over the range of climate and productivity changes
considered (x-axis). The horizontal (x-) axis represents temperature increases of 0.1 °C
to 6.0 °C; precipitation decreases of 10 to 600 mm; and biological productivity changes
ranging from +10 to −48%.
84 J.D. Phillips / Geomorphology 109 (2009) 79–85
Author's personal copy
appropriateness and performance of models, even if the higher costs
and difﬁculties of implementation are ignored. Simpler models geared
toward capturing essential behaviors and phenomenologies may in
many cases represent geomorphic system behavior better than larger
and more complex models (Werner, 1995; Phillips, 1999; Hergarten,
2002). Further, model expansion may actually reduce the generality of
the model and its results and implications (Beven, 2000; Sivakumar,
2004; Phillips, 2007b).
In many cases, geomorphic changes and responses, and landscape
evolution, may be dominated by a handful of the often vast number of
(potentially) relevant processes and controls. Efforts to identify and
focus on these dominant processes and controls may be more fruitful
than increasing the number and sophistication of components of LES-
The landscape evolution space concept attempts to account for all
major energy and mass resources which deﬁne the potential for
landscape evolution, and the resources available to drive and support
geomorphic processes. Despite its origin as an essentially heuristic
model, LES can be used to address concrete problems, such as those
illustrated in the case studies. The LES model is particularly well suited
to confront issues regarding the relative importance of various
controls or forcings on geomorphic evolution. It is also intended as a
framework to allow for a systematic consideration of the major energy
and mass components of earth surface systems.
In the Big South Fork river basin, the LES was applied to investigate
changes in LES associated with ﬂuvial dissection; speciﬁcally the
relative importance of mass removal by denudation vs. increased
surface area due to topographic roughening. Results indicate that
surface roughening and the associated increase in surface area only
slightly offsets the effects of mass removal with respect to LES.
The Texas coastal plain case study illustrated the use of the LES to
assess the relative inﬂuences of predicted climate changes and sea
level rise under various scenarios. For instance, a sea level rise of
0.5 m, 3 °C warming, precipitation decline of 300 mm year
biological productivity increase of 15% would result in a 20% decrease
in LES. The most important factor in that decline is the decrease in
precipitation, delivered to a smaller surface area.
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erosional surfaces determined by cosmogenic nuclides in cave sediments. Earth
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