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The Journal of Island and Coastal Archaeology
ISSN: 1556-4894 (Print) 1556-1828 (Online) Journal homepage: https://www.tandfonline.com/loi/uica20
Climate Change and Cultural Heritage: A
Landscape Vulnerability Framework
Isabel Cook, Robert Johnston & Katherine Selby
To cite this article: Isabel Cook, Robert Johnston & Katherine Selby (2019): Climate Change
and Cultural Heritage: A Landscape Vulnerability Framework, The Journal of Island and Coastal
Archaeology, DOI: 10.1080/15564894.2019.1605430
To link to this article: https://doi.org/10.1080/15564894.2019.1605430
Published online: 10 Jun 2019.
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Climate Change and Cultural Heritage:
A Landscape Vulnerability Framework
Isabel Cook,
1
Robert Johnston,
1
and Katherine Selby
2
1
Department of Archaeology, University of Sheffield, Sheffield, UK
2
Department of Environment and Geography, University of York, York, UK
ABSTRACT
This paper proposes a new framework for calculating vulnerability
indices within archaeological resource management on a landscape-
scale. Current approaches consider archaeological sites in isolation
from their context within the historic landscape. The new frame-
work advocated in this article assesses the vulnerability of landscape
character areas, as defined through historic landscape characteriza-
tion. This framework uses a two-step vulnerability index: the first
assesses the vulnerability of archaeological sites and landscape fea-
tures; the second uses the results of the first vulnerability index, as
well as spatial data on the landscape character areas and the threat
in question to calculate the vulnerability of each landscape charac-
ter area. The framework is applied to a brief case study in coastal
North Wales, UK.
Keywords climate change, vulnerability, archaeology, landscape, historic landscape
characterization
INTRODUCTION
There is no single definition of vulnerabil-
ity, as it is used across many disciplines in
relation to a wide range of systems, phe-
nomena, and hazards (Barnett et al. 2008).
For the purpose of this paper, vulnerability
will refer to the accepted use within the
disciplines of archaeology and physical
geography, namely the probability that a
system or phenomenon will experience
harm because of a hazard or threat,
whether a short-term event or long-term
stress (Accardo et al. 2003; Turner et al.
2003). This definition of vulnerability is
considered a function of three factors:
exposure, sensitivity (or susceptibility),
and adaptive capacity (or coping capacity
or resilience) (e.g., (Balica and Wright,
2010; Balica et al. 2012; Glick et al. 2011;
Nguyen et al. 2016). Exposure is the likeli-
hood that a system will be affected by a
Received 6 September 2018; accepted 15 March 2019.
Address correspondence to Isabel Cook, Department of Archaeology, University of Sheffield,
Western Bank, Sheffield S10 2TN, UK. E-mail: imcook1@sheffield.ac.uk.
Color versions of one or more of the figures in the article can be found online at www.tandfon-
line.com/uica.
1
The Journal of Island & Coastal Archaeology, 0:1–19, 2019
Copyright #2019 Taylor & Francis Group, LLC
ISSN: 1556-4894 print/1556-1828 online
DOI: 10.1080/15564894.2019.1605430
threat as a result of its location. For
instance, a coastal town has higher expos-
ure, and therefore higher vulnerability, to
storm surges compared to an inland town.
Sensitivity is defined as the degree to
which the exposed elements of a system
are affected by the threat, which influences
the probability of damage occurring to or
within the system. Adaptive capacity is the
capacity of a system to respond to change,
maintain its functions, and cope with the
consequences. This can be influenced by
anthropogenic factors, but can also be an
inherent attribute of the system.
Anthropogenic adaptive capacity can
include institutional planning, technology
such as warning systems, and defense infra-
structure (Nguyen et al. 2016). Other sys-
tems, such as ecosystems, can have
inherent adaptive capacity influenced by
factors such as species diversity and abun-
dance, evolutionary adaptive potential, and
connectivity of ecosystem patches
(Whitney et al. 2017). The adaptive cap-
acity of a particular system can be influ-
enced by both anthropogenic and inherent
factors, so this paper uses “adaptive capaci-
ty” to refer to both anthropogenic and
inherent aspects of system resilience. In
general, the adaptive capacity of built heri-
tage and archaeological features is influ-
enced by anthropogenic systems, while
that of “living” heritage features, such as
ancient woodland and historic parks, is
influenced by the robustness of species
and ecosystems.
A high level of vulnerability will result
from high exposure, high susceptibility,
and low adaptive capacity; an increase in
adaptive capacity or a decrease in exposure
or susceptibility will reduce the overall vul-
nerability of a system.
Vulnerability indices (VIs) are created
and used to assess the potential impact of
natural and anthropogenic hazards on his-
torical and archaeological assets (e.g.,
Boruff and Cutter 2007; Hegde and Reju
2007; McLaughlin and Cooper 2010;
McLaughlin et al. 2002; Thieler and
Hammar-Klose 2000). However, there are
conceptual weaknesses in the way that his-
torical and archaeological assets are framed
within most VI studies. These weaknesses
influence the methodologies and results of
these studies, and the subsequent outcomes
for archaeological resource management.
This article proposes a landscape-scale
framework (Landscape Vulnerability
Framework) for archaeological VIs. The
need for vulnerability studies to address
landscapes rather than sites in isolation can
be illustrated with an example from
England’s coastline. Coastal erosion is
known to have already destroyed over 150
documented settlements around the North
Sea in the last millennium, such as Eccles,
Clare, Foulness, Keswick, and Shipden
(Custard 2017; Sear et al. 2011). The town
of Dunwich on the coast of Suffolk, with a
current population of less than 200 (Office
for National Statistics 2013), was once a
large port. In the fourteenth century it was
similar in size to London at the time, and
was an important center for shipbuilding
(Sear et al. 2015). The local geology is par-
ticularly susceptible to coastal erosion,
with large areas recorded to have been lost
in single events over the last 1,000 years
(Sear et al. 2011). The cultural heritage and
historic character of the town has been
destroyed due to erosion: Dunwich was
unable to continue to act as a center for
trade following the loss of the market place
and town hall in the seventeenth century,
while the All Saints church, St James leper
chapel, Maison Dieu hospital, and
Franciscan Friary were all damaged or
destroyed in the eighteenth century (Sear
et al. 2011). The loss experienced at
Dunwich does not relate just to the dis-
appearance of individual buildings and sites
in isolation, but also the loss of the heritage
of the town and the historic character of
the urban landscape. The projected
impacts of future climate change, such as
sea-level rise and an increased frequency of
extreme weather, will only exacerbate the
risk of erosion to coastal regions.
Several studies assess the vulnerability
of archaeological heritage to environmental
processes (e.g., Daire et al. 2012; Reeder
et al. 2012; Reeder-Myers 2015; Westley
et al. 2011; Westley and McNeary 2014).
However, these studies base their VIs on
Isabel Cook et al.
2 VOLUME 0 ISSUE 0 2019
historic or observed rates of environmental
change, and therefore do not consider the
ways in which climate change is predicted
to alter current environmental processes.
For example, under a medium emissions
scenario, UKCP09 projects a likely increase
in winter precipitation of 30–40% on the
UK west coast, and a decrease in summer
precipitation of 10–20% in the south of the
UK by 2080, relative to 1961–1990
(UKCP09: Watts et al. 2015). Under the
same emissions scenario, the IPCC projects
a mean rise in global sea level of 0.52 m by
2081–2100 compared to the period
1986–2005 (Palmer et al. 2016). In the
unlikely scenario that all intended nation-
ally determined contributions (INDCs) sub-
mitted to the UNFCCC prior to the Paris
COP21 Agreement were met, global tem-
peratures are still predicted to increase by
2.7 C by 2100 compared to 1990
(G€
utschow et al. 2015). These major
changes in global climate and regional wea-
ther systems will have dramatic effects in
the environmental processes that impact
archaeological heritage. Sea-level rise will
cause the intertidal zone to shift inland,
subjecting new sites to potential damage
through inundation and wet/dry cycles
(Anderson et al. 2017). Changes to precipi-
tation patterns may lead to desiccation of
previously wetland sites during the sum-
mer months, and an increase in gullying
erosion and flooding during the winter
(Cassar and Pender 2003). It is for this rea-
son that the Landscape Vulnerability
Framework uses near-future climate projec-
tions (up to ca. 2100) to assess the vulner-
ability of cultural heritage assets and
landscapes, rather than basing VI assess-
ments on current or historic wea-
ther conditions.
This article first reviews and identifies
limitations with the current approaches
used in VI assessments for archaeology, in
particular in relation to natural hazards. It
then proposes a Landscape Vulnerability
Framework for VIs that addresses the limi-
tations within current approaches. The
implications for archaeological heritage
management will also be demonstrated
using a brief case study from coastal North
Wales, UK. In this article, cultural heritage
will be used to refer to physical heritage
assets such as archaeological remains and
historic buildings, and the influence they
have on local culture (for instance creating
a physical connection with local history,
continuing traditional land-use practices,
and imparting a sense of place and belong-
ing). It can also be used to refer to intan-
gible elements of culture such as language,
customs, artistic expression, and values;
however, these aspects of cultural heritage
are beyond the scope of this paper.
CURRENT APPROACHES TO
VULNERABILITY INDICES IN
ARCHAEOLOGICAL
HERITAGE MANAGEMENT
A vulnerability index is a tool used to quan-
tify the likelihood that an asset will be
affected by predicted threats. VIs are
derived from indicators such as distance to
shoreline and rate of erosion, which are
themselves proxies for threats posed by
complex and uncertain systems like cli-
mate change (Balica et al. 2012; Barnett
et al. 2008). The quantification of vulner-
ability using these indicators makes it feas-
ible to compare different entities, such as
cities, areas of coastline, or archaeological
sites. Quantification, and therefore compar-
ability, also increases decision-makers’
understanding of the systems in question,
and can inform more efficient resource
management by identifying the areas that
are most at risk and the reasons for varia-
tions in vulnerability (Balica et al. 2012;
Boruff and Cutter 2007; Glick and Stein
2010; Reeder et al. 2012).
Glick and Stein (2010) argue that there
is no single correct approach for calculat-
ing VIs, as the suitability of the approach
depends on the object and purpose of the
vulnerability assessment. These factors,
and the difficulties attempting to simplify
complex systems such as climate change,
mean that there have been hundreds of
attempts to create VIs (Barnett et al. 2008).
This section reviews the most common
approaches to vulnerability assessment
Climate Change: Landscape Vulnerability Framework
3THE JOURNAL OF ISLAND & COASTAL ARCHAEOLOGY
within archaeology, covering studies
worldwide, in places such as the
Caribbean, USA, France, and Northern
Ireland. It identifies the different variables
used as proxies in VI calculations, the
range of threats considered by VIs, and the
objects selected for VI assessments. In this
context, the “object” of the VI refers to the
sites, monuments, and areas whose vulner-
ability is being assessed.
The following review was limited to
the use of VIs to assess the vulnerability of
archaeological sites—a total of 19 studies
were identified. Although the search was
not limited spatially, the majority of studies
focus on coastal areas and principally on
natural hazards, such as flooding and ero-
sion. Those addressing solely anthropo-
genic threats such as urban expansion
were not included in the study; however,
the proposed Landscape Vulnerability
Framework could be applied to any threat.
Variables
Most VI projects have been desk-based,
allowing a wider geographical area to be
included in the study and reducing the
time required to undertake the assess-
ments. Only a few projects involved the
detailed, field-based examination of the vul-
nerability of individual sites (e.g., Daly
2013). This may be because one purpose
of VIs is to act as a replicable and efficient
management tool. As a result, most VIs
only considered characteristics that could
be assessed remotely and across large
areas, for instance, topographic slope
angles, rates of relative sea-level rise, and
tidal ranges of the nearest coastlines (e.g.,
Chadwick-Moore 2014; Pendleton et al.
2005; Reeder et al. 2012; Reeder-Myers
et al. 2015; Rockman et al. 2016; Van
Rensselaer 2014; Westley et al. 2011;
Westley and McNeary 2014). Only a few
VIs considered the characteristics of the
archaeological sites themselves, including
the materials from which sites are con-
structed and current levels of preservation
(e.g., Daire et al. 2012; Daly 2013;
Robinson et al. 2010). Daly (2013), in a
study limited to two World Heritage sites,
considered a wide variety of characteristics
that could influence the vulnerability of
each site, including the structural damage
from visitors, the vegetation cover, and
numbers of animal burrows.
The spatial extent and number of sites
included in a study influences the reso-
lution of the assessment. However, studies
solely considering the threats determined
by sites’ locations only address the expos-
ure element of vulnerability; they neglect
the resilience of the site to threats. For
instance, an archaeological site may be
buried and well preserved, or constructed
of durable materials, and therefore have
much greater resilience to any threat than
a site in the same location that is exposed
and susceptible to damage (Daire et al.
2012). This can also be seen in a vulnerabil-
ity model for Bering Land Bridge National
Preserve by the U.S. National Park Service,
which was based only on a coastal erosion
model and local climate change projec-
tions, and included no information on site
resilience or susceptibility (Devenport and
Hays 2015; Rockman et al. 2016).
Although the studies considered vul-
nerability across a range of scales, none
acknowledged that spatial scale and the
resolution of the data can influence the var-
iables included in the VIs. This is an
important consideration, partly because
some datasets are only available for specific
areas or resolutions (Torresan et al. 2008).
McLaughlin and Cooper (2010) argue that
some variables are scale-sensitive, while
others are important regardless of the spa-
tial extent or resolution of the study. For
example, they suggest that geology is a
scale-sensitive variable, as at a regional
level there may be different types of bed-
rock, but at a local level the geological vari-
ation is likely to be negligible. McLaughlin
and Cooper’s approach is valid when calcu-
lating relative vulnerability, which is lim-
ited to the comparison of vulnerability
between sites within a study area (see
Pendleton et al. 2005; Reeder et al. 2012;
Westley et al. 2011). However, relative VIs
reduce the potential for inter-
regional comparison.
Isabel Cook et al.
4 VOLUME 0 ISSUE 0 2019
Threats
The threats considered within VIs vary
between studies, with some incorporating
both natural and anthropogenic processes
(e.g., Daire et al. 2012; Reeder et al. 2012;
Van Rensselaer 2014), while others only
measure the vulnerability of sites to natural
hazards (e.g., Reeder-Myers 2015; Westley
et al. 2011). Despite the importance of cli-
mate change as an emerging threat, few
studies explicitly included the threat of cli-
mate change or its effects. Van Rensselaer
(2014) mentions climate change and
includes specific sea-level rise projections
in his calculation of vulnerability.
Consideration of changes to temperature,
precipitation patterns, and wind were
included in Daly’s (2013) vulnerability
assessment of Skellig Michael and Br
una
B
oinne (see also Chadwick-Moore 2014;
Grossi et al. 2007; Westley et al. 2011). In
contrast, while acknowledging that climate
change may increase the vulnerability of
archaeological and heritage sites, several
studies only based the VI on historic or
observed rates of erosion or sea-level rise,
rather than projected future change (e.g.,
Daire et al. 2012; Reeder et al. 2012;
Reeder-Myers et al. 2015; Westley and
McNeary 2014). Several studies did not
even acknowledge the impact that climate
change is likely to have on the threats
posed to archaeological heritage (e.g.,
Accardo et al. 2003; Fitzpatrick et al. 2006;
Minos Minopolous 2015).
Objects
The majority of the studies focus spe-
cifically on archaeological “sites”. Reeder
et al. (2012:189) define archaeological sites
in their study as encompassing features
from “large villages and workshops to frag-
mented shell middens and lithic scatters”,
while Daire et al. (2012:175) say that their
research looks at sites comprising “all
remains of built structures of anthropo-
genic origin or materials transformed by
human activities.” Three studies
(Chadwick-Moore 2014; Robinson et al.
2010; Westley and McNeary 2014) only
define sites as the records included in arch-
aeological databases. All other studies pro-
vided no definition for archaeological
“site”, despite this being the focal level of
their VIs (e.g., Chadwick-Moore 2014;
Fitzpatrick et al. 2006; Reeder-Myers 2015;
Van Rensselaer 2014; Westley et al. 2011).
There have been important debates within
archaeology over what constitutes a “site”
and how it may be delineated from the sur-
rounding landscape. Often, the term “site”
is used to refer to a concentration of evi-
dence of human activity, such as monu-
ments, shipwrecks, or large clusters of
artifacts, but it is not used for single find-
spots (Dunnell 1992). Dunnell (1992:29)
argues that “sites” are “not really things or
qualities, but rather concentrations or
quantities.” Using this argument, the arch-
aeological record could be seen not as a
collection of individual sites, but as a more
or less concentrated distribution of evi-
dence of human activity across the Earth’s
surface (Dunnell and Dancey 1983).
This raises questions about how
“sites”, as concentrations of evidence of
activity, can be assessed in isolation from
the surrounding landscape in which human
activity also took place (Cooney 2003).
Therefore, the results of these studies can
only indicate which “sites” or archaeo-
logical features are at more or less risk of
damage from a certain threat. They cannot
provide information on how the historic
character of the landscape may be affected
by impacts of climate change.
Furthermore, only known, recorded sites
will be included in vulnerability assess-
ments. This excludes features in areas that
have not yet been systematically surveyed
or where archaeological material is masked
by overlying sediments.
That is not to say that site-specific VIs
cannot be useful for cultural heritage man-
agement. Assessments of significant heri-
tage sites can provide insight into the
specific management requirements of each
site (see Daly 2013’s detailed assessment of
Skellig Michael and Br
unaB
oinne,
Ireland). However, for the most part vul-
nerability assessments that include a large
Climate Change: Landscape Vulnerability Framework
5THE JOURNAL OF ISLAND & COASTAL ARCHAEOLOGY
number of sites within a landscape fail to
acknowledge the interconnectivity
between sites and how they influence the
historic landscape (see below).
A LANDSCAPE
VULNERABILITY FRAMEWORK
The preceding review identified several
limitations with the most common
approaches to VIs in archaeological heri-
tage management. Most studies focus on
the hazards to which sites are exposed,
and not the susceptibility and resilience of
the sites to hazards. This accounts for only
one of the three factors influencing vulner-
ability, according to its accepted definition.
A second limitation is that most studies do
not account for the future influence of cli-
mate change. The majority predict the like-
lihood of exposure to a hazard based on
past trends such as historic or observed
rates of erosion or sea-level rise. This
neglects the impact that climate change
will have on natural systems, and may
therefore miscalculate the impact the sys-
tems and their resulting phenomena may
have on archaeological heritage. Finally,
previous studies focus on “sites” as a unit
of investigation without consideration of
the historicity of the landscape of which
sites are constituents.
This article proposes an alternative
framework to vulnerability assessment for
archaeological heritage that addresses the
limitations outlined above. The framework
assesses the vulnerability of historic land-
scapes to threats such as future climate
change. This section will summarize the
concept of the historic landscape and
explain why it is an important consider-
ation in vulnerability studies. It then intro-
duces Historic Landscape Characterisation
(HLC) as a method of landscape analysis.
The scope of the landscape vulnerability
framework is then described, including
which vulnerability variables are included,
and which threats are considered. Finally,
the Landscape Vulnerability Framework is
applied to a brief case study.
Historic Landscape
The concept of the “historic land-
scape” has existed in the academic litera-
ture since at least the 1950s, with J. B.
Jackson and W. G. Hoskins amongst the
most frequently cited authors who are
credited with inspiring and popularizing
the idea (e.g., Wylie 2007:30–53). At heart,
the idea is simple, even common-sensical:
our landscapes were created through his-
torical processes, and the traces of those
processes are visible in the present-day
physical fabric and in cultural representa-
tions of landscapes. The historic landscape
can therefore be compared with and ana-
lyzed like other human-made objects, such
as artifacts or texts. Fairclough et al.
(2002:70) describe the historic landscape
as “an artefact of past land-use, social struc-
tures and political decisions”. This consid-
ers the structure of a landscape, such as
field boundary morphology, settlement
structure, and the location of industry, as a
product of a long history of human activ-
ities that continues up to the present day
(Fairclough 2003a,2003b,2006). A historic
landscape perspective therefore does not
assume that modern changes are intrinsic-
ally destructive or valueless, but rather it
treats modernity as another layer of histor-
icity in the formation of landscapes
(Bradley et al. 2004).
The historic landscape can be analyzed
and interpreted using Historic Landscape
Characterisation (HLC) (see Fairclough
2003a,2006; Turner 2006). In HLC, attrib-
utes such as field boundary morphology,
the location of historic and modern indus-
try and settlement, and archaeological fea-
tures, are used to define landscape
character areas (LCAs), such as Historic
Settlement, Ancient Enclosed Land,
Military, etc. (e.g., Cornwall County
Council 2011). HLC identifies and maps
areas in which previous and current land
use is evident in the visual structure of the
landscape, so the landscape’s character is
influenced by the cumulative outcome of
human activity.
Some HLC projects have identified the
potential for assessing the vulnerability of
Isabel Cook et al.
6 VOLUME 0 ISSUE 0 2019
landscape character. For instance A Guide
to Using the Cumbria Historic Landscape
Characterisation Database for Cumbria’s
Planning Authorities states that “character
areas also facilitate the identification of the
most vulnerable aspects of local landscape
character” (Newman and Newman
2009:11). Indeed, Historic England states
that “Historic Landscape Characterisation
(HLC) shows the need for broader historic
landscape-based [conservation] policies as
well [as those that focus on individual sites
and monuments]” (Clarke et al. 2004:27).
These examples acknowledge the potential
for LCAs to be objects of vulnerability
assessment. However, to date, archaeo-
logical vulnerability assessments have main-
tained the focus on sites and features,
without acknowledging the wider implica-
tions on the landscape as a whole.
Therefore, the Landscape Vulnerability
Framework proposed in this article
assesses the vulnerability of LCAs to threats
such as climate change. This uses a cumula-
tive approach; the VI score for archaeo-
logical and historical features is used as a
variable for calculating the vulnerability
of LCAs.
New Framework: Vulnerability Variables
Most VIs employ a one-step approach
to assessing vulnerability, with all variables
incorporated within a single equation (e.g.,
Alexandrakis et al. 2010; Chadwick-Moore
2014; Daire et al. 2012; Daly 2013;
McLaughlin and Cooper 2010;Van
Rensselaer 2014—Reeder et al. 2012 is an
exception). The Landscape Vulnerability
Framework uses two equations. First, it cal-
culates the vulnerability of “landscape char-
acter features” (LCFs), before scaling these
up to consider threats to the LCAs. LCFs
are parts of a landscape that influence the
character of LCAs, such as drystone walls,
historic military defensive features, and
areas of ancient and plantation woodland.
This can include archaeological “sites”, nat-
ural/living features, and buildings and trans-
port routes that are still in use. This first
equation calculates the vulnerability of
LCFs, with a focus on the susceptibility and
resilience of LCFs to climate change
impacts. The second VI equation works at
the level of the LCA: it calculates the vul-
nerability of LCAs using the vulnerability of
the LCFs (as calculated using the first equa-
tion), the susceptibility of the LCA to soil
erosion, and exposure to projected sea-
level rise and coastal erosion. These two
stages to the calculation will now be
explained in depth.
Stage 1—Vulnerability of landscape
character features
It is acknowledged that there are a
multitude of variables that would measure
the vulnerability of LCFs to climate change
impacts. However, McLaughlin and Cooper
(2010) argue that it is not necessary to con-
sider every variable for which data exists,
as some of them are highly correlated, and
so would likely be measuring the same
phenomena. For instance, the susceptibility
of the LCF to predicted precipitation
change is likely to be closely related to the
susceptibility of the feature to storminess,
as the impact of storms includes heavy pre-
cipitation. In addition, Lane et al. (1999)
argue that the variables used in VIs should
be “measurable, accessible, transferable,
easy to be applied in practice, and not
redundant” (p. 24). Therefore, the variables
used in this study were chosen on the basis
of their accessibility and their transferabil-
ity between regions.
Five variables are considered in the vul-
nerability equation for the LCFs: current
levels of preservation (a), resistance of the
remains (b), resistance of the local sub-
strate (c), the susceptibility of the LCF to
projected temperature changes (d), and
the susceptibility of the LCF to projected
precipitation changes (e).Table 1 provides
an example of how these variables may be
classified in the VI.
V¼aþbþcþdþe
5(1)
Variables aand baddress the susceptibility
and adaptive capacity of the LCF, variable c
Climate Change: Landscape Vulnerability Framework
7THE JOURNAL OF ISLAND & COASTAL ARCHAEOLOGY
Table 1. Description and division of the variables used to calculate the vulnerability
score for archaeological sites.
Variable Classes Score
Level of preservation No visible damage/buried. 1
Some small damage or visible weathering to
structure.
Buried archaeological feature slightly exposed.
2
Structures show structural damage and weak-
ness.
Buried features are exposed and show signs
of weathering.
3
Significant weathering damage, little evidence
remains of the features.
4
Extremely damaged, ephemeral remains. 5
Resistance of the remains Solid built feature, actively used, managed,
or protected.
1
Made of resistant materials such as rock/stone,
but is less fixed, i.e., a drystone structure.
2
Made of less resistant materials, such as organic
remains or earthwork, but remains buried or
has a small amount of protection.
3
Feature or site characterized by a collection of
artifacts rather than a structure, so lacking
foundations. Also made of less resist-
ant materials.
4
Features made of a less resistant or very fragile
material, previously buried but are
now exposed.
5
Resistance of local substrate Feature is positioned on solid bedrock, in an
area of low relief (<5) with no visible weath-
ering or erosion nearby.
1
Feature is positioned on solid bedrock in an area
of medium relief (5–15). Little or no visible
weathering or erosion in the area.
2
Feature is positioned on bedrock in an area of
high relief (>15), or on unconsolidated sedi-
ments in a low relief area. Some visible ero-
sion and weathering in the vicinity.
3
Feature is positioned on or in unconsolidated
sediments in a medium relief area, or sand in a
low relief area. Visible weathering or ero-
sion nearby.
4
Feature is positioned on or in unconsolidated
sediments in an area of high relief (>15)or
sand in an area of medium or high relief.
Significant visible erosion and weathering near
the remains.
5
Susceptibility to projected
temperature change
Solid built feature, made of rock or other resist-
ant material.
1
2
(Continued)
Isabel Cook et al.
8 VOLUME 0 ISSUE 0 2019
addresses the exposure of the LCF, and var-
iables dand eaddress the susceptibility of
the LCF. For variables a,b, and d, field-
work may be required to determine the
current level of preservation, and to gather
data on the constituent materials of the
LCFs. Some landscapes may have been sub-
ject to previous archaeological surveys, so
the location, type, and form of the LCFs
may already have been recorded. In this
case, up-to-date archaeological or monu-
ment databases will suffice as a record for
the state of LCFs. A small number of site-
visits should nevertheless be undertaken to
ground-truth the available archaeological
information and determine its suitability for
satisfying the VI.
Variable ccan be based on geological
survey data, which will indicate which
LCFs are located on unconsolidated materi-
als and are therefore more susceptible to
erosion. For variable e,amodelofflow
accumulation can be calculated in GIS to
identify the areas most susceptible to pro-
jected increases in precipitation. Flow
accumulation is an indication of where
water flowing down a slope will accumu-
late based on the topography, for instance,
Table 1. Description and division of the variables used to calculate the vulnerability
score for archaeological sites. (Continued).
Buried features not thought to include
organic remains.
Organic or wet-preserved remains, but located in
areas unlikely to be prone to desiccation, such
as the intertidal zone.
3
Living features such as parks and gardens. 4
Organic or wet-preserved remains, in areas sus-
ceptible to desiccation or peat fires,
i.e., uplands.
5
Susceptibility to projected
precipitation change
Solid built feature, actively used, managed, or
protected, or made of resistant materials,
located in very low flow accumulation area
(<20). Or in intertidal zone.
1
Made of resistant materials such as rock/stone,
in a low flow accumulation area (20–50). Not
affected by drought.
2
Made of resistant materials, but located in areas
with moderate flow accumulation (51–100) or
on the banks of water courses. Alternatively,
made of less resistant materials such as earth-
works or organics and located on unconsoli-
dated sediments in areas with very low flow
accumulation (<50).
3
Made of less resistant materials such as earth-
works or organics and located in unconsoli-
dated sediments in areas with moderate flow
accumulation (50–100) or on the banks of
water courses/rivers.
Or made of resistant materials in areas with
high flow accumulation (>100).
4
Made of less resistant materials and located in
valley or gully areas with high flow accumula-
tion (>100).
Organic, living, or wet preserved remains sus-
ceptible to desiccation.
5
Climate Change: Landscape Vulnerability Framework
9THE JOURNAL OF ISLAND & COASTAL ARCHAEOLOGY
in gullies and valley bottoms. Areas with
greater flow accumulation are more likely
to experience torrents and gully erosion
during high rainfall events (Mitasova et al.
1996; Zlocha and Hofierka 2014).
The variables addressing projected
temperature (d) and precipitation change
(e) are based on the most up-to-date avail-
able information on projected climate
change in the study area. The temporal
extent of most integrated model assess-
ments and emission scenarios within cli-
mate change research focus solely on the
current century (up to 2100) (e.g., Collins
et al. 2013; Meinshausen et al. 2011). The
uncertainties inherent in climate models,
future greenhouse gas emissions, and the
reaction of the climate to radiative forcing
means that the range of potential outcomes
in the longer term is so great as to be
unhelpful to decision-makers. However,
using near-future (twenty-first-century) cli-
mate projections will provide data that is
more relevant for informing future archaeo-
logical heritage management than VIs
based on historic levels of precipitation,
erosion, or temperature variation.
When undertaking the fieldwork at all
or a sample of LCFs, it is important to cover
a variety of types of feature in order to factor
in the variability of feature types and their
differingvulnerability.Thespecificnatureof
the variability in LCF types will be context-
specific and influenced by the landscape and
LCFs under scrutiny, so the approach taken
will require a qualitative judgement by the
researchers undertaking the study. A useful
approach may be to base feature variability
on the materials that constitute the feature
and influence its susceptibility to threats like
erosion and desiccation. For instance, sam-
pling could be based on different material
categories: earthwork, stone or rubble, and
brick or concrete features. Categorizing and
sampling the features in this way would
account for the variation in vulnerability of
different types of features more effectively
than taking a random sample, which may
not cover all LCF types.
The number of LCFs that should be
included in the VI also depends on the con-
text; in a landscape with little variability in
LCFs, fewer may need to be sampled than
in a landscape with lots of variation in LCF-
type. This is because the second equation
(see below) uses the mean LCF vulnerabil-
ity as a variable to measure LCA vulnerabil-
ity. Furthermore, some LCAs may contain a
high number of discrete features, such as
mineshafts, whereas others are character-
ized by spatially extensive LCFs such as
field-systems or woodland. Therefore, the
appropriate sample size of LCFs to include
in the VI is dependent on the landscape
context, the LCA, and the type of LCFs that
characterize it. Critically, the researchers
must have sampled sufficient LCFs to be
confident that the results are representative
of the whole population.
Stage 2—Vulnerability of Landscape
Character Areas
A vulnerability score for the LCAs is cal-
culated using the following variables: the
vulnerability of the LCFs that characterize
the LCA (f—the outcome of the first VI
equation), the proportion of the LCA that is
threatened by sea-level rise and inundation
(g), the proximity of the LCA to an eroding
stretch of shoreline (h), and the susceptibil-
ity of the soil types in the LCA to erosion (i)
(see Table 2). The latter two variables were
chosen as indicators of the exposure of
LCAs to climate change impacts, while the
former three variables address the suscepti-
bility and resilience of the character of the
LCA. This equation will be applied to each
of the LCAs established in the HLC.
LCA V¼fþgþhþi
4(2)
Variables gand haddress the issue of expos-
uretothethreat,inthiscaseclimatechange.
The areas threatened by sea-level rise and
inundation (variable g)canbemodeledusing
digital elevation models in GIS, based on
national, regional, and global sea-level projec-
tions (e.g., Church et al. 2013). The recent
rate of shoreline erosion can be informed by
comparing the location of the mean high-
water mark on modern and historic maps, or
in areas with high erosion rates by using aerial
Isabel Cook et al.
10 VOLUME 0 ISSUE 0 2019
Table 2. Description and division of the variables used to calculate the vulnerability
score for LCAs.
Variable Classes Score
Mean vulnerability score
of the features characteristic
of this LCA
1<¼x<1.5 1
1.5<¼x<22
2<¼x<33
3<¼x<44
4<¼x<¼55
% of LCA at risk of flooding
and storm surge
<5% the LCA area at risk of sea-level rise, or at risk of
flooding from rivers and seas by 2100 (RoFRS).
1
<20% threatened by any RoFRS.
High storm surge or flooding from rivers, but none
threatened by sea-level rise.
2
20%–50% threatened by high or medium RoFRS and
<20% threatened by sea-level rise alone.
3
>50% threatened by high or medium RoFRS. Storm surges
(below 5.715 m OD) and river flooding, and/or
20–50% of the LCA threatened by sea-level rise 2100
(within 2.965 m OD).
4
>50% at risk of inundation by 2100 (within 2.88 m OD)
and/or >70% at high RoFRS.
5
Proximity to unprotected
eroding shoreline
None of the LCA is located within 100 m of unprotected
shoreline or in front of defenses.
1
LCA has <10% of area within 100 m of unprotected
shoreline or in front of defenses, or shoreline with
managed retreat policy.
2
10–50% of LCA area is within 100 m away from unpro-
tected shorelines or shoreline with managed
retreat policy.
3
10–50% of LCA area is located 0–50 m away from unpro-
tected shorelines or shoreline with managed retreat
policy. OR most sites (>50%) are located within 100 m
of unprotected shoreline or in front of defenses or
shoreline with managed retreat policy.
4
>50% of the LCA located within 50 m of unprotected
shoreline, shoreline with managed retreat policy or in
front of defenses.
5
Susceptibility of soil type to
erosion (information from
British Geological Survey);
the classification chosen
should be based on the most
common soil characteristics
for each LCA
Very little risk, as soils are freely draining, relatively cohe-
sive, and low relief.
1
One of the following criteria:
In an area at risk of floodwater scouring or runoff;
Sandy/unstable soils at risk of wind erosion during dry
periods;
Risk of sheet erosion during high-precipitation events;
Shallow soils and bare rock in places;
Risk of soil erosion due to grazing and trampling;
Slow or impeded drainage;
Steep slopes.
2
Two of the above criteria. 3
Three of the above criteria. 4
Four or more of the above criteria. 5
Climate Change: Landscape Vulnerability Framework
11THE JOURNAL OF ISLAND & COASTAL ARCHAEOLOGY
photographs and LiDAR. This method only
considers scenarios in which future rates of
shoreline erosion reflect current or historic
rates. However, it does indicate the areas in
which the geomorphological conditions and
coastal processes result in higher rates of ero-
sion, and therefore where erosion is likely to
continue in the future. Due to the uncertain-
ties regarding future emission levels and the
reaction of the climate system to increased
radiative forcing (Burke et al. 2015), there are
inherent difficulties with basing vulnerability
assessments on predicted future conditions
rather than historic or current trends.
Therefore, for complex processes such as
coastal erosion, identifying areas at risk based
on the location of a presently actively eroding
shoreline may be as reliable as developing a
complex model to predict future erosion.
Variable iaddresses the susceptibility
of the whole LCA to soil erosion, rather
than just the susceptibility of the LCFs
within it. This can be calculated using soil
survey data, which, if available, includes
information such as the soil type, rate of
drainage, and susceptibility to certain
threats (e.g., Cranfield University 2018).
An important objective with this frame-
work is to identify the absolute vulnerability
of LCAs to climate change, rather than their
relative vulnerability. As previously discussed,
several studies exclude certain variables, such
as geology, from the VIs as it is unlikely for
the geology to vary significantly over the
study areas, and therefore it does not influ-
ence the relative vulnerability of the sites
studied. This is only suitable if the aim is to
compare sites within a single, geologically
homogenous study area. This approach does
not allow the VIs to be compared across dif-
ferent study areas. Nor is it appropriate for
areas with significant geological variation, for
example, where differences in superficial
deposits can influence vulnerability
to erosion.
Case study: Dysynni Valley, North
Wales, UK
This section provides a brief example
of the way that the Landscape Vulnerability
Framework was applied to a coastal land-
scape in North Wales. The Dysynni Valley,
Gwynedd, is designated as a Landscape of
Special Historic Importance by Cadw, the
Welsh Government’s historic environment
service, as this region has a long and rich
history of human settlement. Most known
archaeological sites are in the upland areas,
due to the disruption caused by centuries
of agricultural activity in the lowlands, as
well as a lack of archaeological survey in
these areas. However, complex cropmarks,
field boundary morphology, and the loca-
tion of findspots indicate that there
remains a wealth of archaeological informa-
tion on the valley floor. Furthermore, there
is a wealth of evidence of the importance
of the area to early Welsh Christianity,
such as inscribed stones and almost 100
extant churches and chapels (GAT 2019;
RCAHMW 2019). Military structures along
the coast also indicate the influence of
modern conflict on the character of this
landscape. The valley floodplain lies below
10 m OD (Ordnance Datum) up to 10 km
inland along the river valley, making it vul-
nerable to the impacts of climate change
such as sea-level rise, storm surges, and
high rainfall events (Kriebel et al. 2015).
HLC was applied to the Dysynni Valley
using information from historical and mod-
ern OS maps, aerial photography, national
archaeological databases, and geophysical
surveys (see Figure 1). Seventeen LCAs
were established based on the evidence of
current and historical land-uses in the land-
scape, including pastoral agriculture, post-
medieval industrial activity like mining, and
Second World War military activity.
LCFs such as historic buildings, arch-
aeological sites, parks and gardens, and field
boundaries, were identified using Level 1
surveys and the Historic Environment
Record (HER) and National Monuments
Record Wales (NMRW) databases. In total,
1,455 LCFs were identified in the study
area, approximately 180 km
2
. As it was not
feasible to visit all LCFs to assess their level
of preservation, 64 LCFs were visited to
ground-truth the information in the HER
and NMRW databases. This assessed
whether the information and description
Isabel Cook et al.
12 VOLUME 0 ISSUE 0 2019
included in these databases would be suit-
able for undertaking the VI without visiting
each LCF. Following the methodology out-
lined above, a range of LCFs were selected
based on their different constituent materi-
als. The outcomes of this fieldwork indi-
cated that the archaeological databases
were suitable for assessing the level of pres-
ervation and resistance of the LCFs for the
purposes of this VI. Following this initial
assessment, a further 81 LCFs in the arch-
aeological databases were assessed using
the VI, to increase the number of LCFs
assessed to 145, 10% of the total population.
Those chosen were proportional across all
LCAsandwerealsoinproportionwiththe
different constituent material groups in
each LCA (Brick and Concrete; Stone and
Rubble; Living and Organic; Earthwork).
For the second VI, exposure to coastal
erosion was calculated by identifying areas
of eroding coastline by comparing the loca-
tion of Mean High-Water Springs between
the first-edition OS map with the current
OS map. Sea-level rise projections were
based on the Risk of Flooding from Rivers
and Seas (RoFRS) data available to down-
load from the Welsh Government’s
GeoPortal (lle.gov.uk). The RoFRS projec-
tions were broken down into level of risk:
High (1-in-30 chance of flooding), Medium
(1-in-30 to 1-in-100), Low (1-in-100 to 1-in-
1,000), and Very Low (greater than 1-in-
1,000). These projections took account of
existing flood defenses, including the
height and condition of the defenses.
Susceptibility to soil erosion was based on
soil data provided by the British Geological
Survey (Cranfield University 2018).
Results
The vulnerability results for the
assessed LCFs range from 1.975 to 4.4, but
are mainly distributed between 2 and 3 (see
Table 3). When displayed on a map (Figure
2), the results show that the LCAs at
Figure 1. Historic Landscape Characterisation applied to the Dysynni Valley, North
West Wales.
Climate Change: Landscape Vulnerability Framework
13THE JOURNAL OF ISLAND & COASTAL ARCHAEOLOGY
greatest risk are those located in the most
low-lying and coastal areas, due to the high
risk of flooding along the valley and coast-
line and the threat of coastal erosion.
Figure 2 also shows the VI score for
each LCF visited. This shows that in some
cases the vulnerability of the LCF does not
align with the vulnerability of the LCA as a
whole. For instance, some earthwork fea-
tures near Tirgawen (A) were classified as at
higher risk, but they characterize the Rough
Pasture LCA, which has low vulnerability, so
they should not necessarily be prioritized for
management. In contrast, on the beach near
Penllyn (B), some military features were clas-
sified as lower risk as they were made of
resistant materials such as brick. However,
their location in relation to flood and erosion
risk is such that the military LCA should be
prioritized for further research, monitoring,
and management due to the high risk posed
to it by climate change. This highlights the
importance of assessing the vulnerability of
the historic character of the landscape,
rather than individual archaeological sites.
DISCUSSION AND CONCLUSION
This article proposes a Landscape
Vulnerability Framework for archaeological
resource management, which addresses
fundamental limitations with the most
commonly used current methods for calcu-
lating VIs for archaeological sites and land-
scapes. Primarily, in developing a
framework to assess the vulnerability of
the archaeological resource on a wider
(landscape) spatial scale, this paper aims to
shift the focus of vulnerability studies in
archaeological resource management
towards the wider impact on historic land-
scapes, rather than looking only at sites
in isolation.
Site-focused vulnerability assessments
neglect the importance of the structure
and character of the historic landscape for
cultural heritage, and are therefore not use-
ful for informing archaeological heritage
management on a scale wider than site des-
ignation and conservation. As well as the
example of Dunwich (see Introduction),
there are several instances of areas in
which the historic character of the land-
scape has been lost or dramatically altered
due to coastal processes. For instance, the
southeast coastline of England is character-
ized by defensive structures and fortifica-
tions that have been built in all periods of
history since pre-Roman times (Bromhead
and Ibsen 2006). However, coastal erosion
and landslides have caused many of these
coastal defenses to be damaged or
destroyed. Not only is the loss of each of
these archaeological features significant,
but it also threatens the military and defen-
sive character of the landscape as a whole.
Furthermore, the case study in Figure 2
indicates that the vulnerability of land-
scapes is not always correlated with the
vulnerability of their individual compo-
nents. Therefore, it is important for vulner-
ability assessments to acknowledge the
wider context of the cultural heritage and
landscape character, rather than focusing
solely on archaeological “sites” in isolation
and without regard to their context.
Another criticism of many VIs used in
archaeology is that the quantified threats
Table 3. LCA VI Results.
LCA
Mean LCA
VI score
Modern Settlement 1.975
Historic Settlement 2
Modern Woodland 2.125
Ancient 2.175
Irregular Field Systems 2.225
Irregular Drained Land 2.375
Rough Pasture 2.45
Historic Industry 2.45
Modern Industry 2.5
Tourism and Recreation 2.5
Regular Field Systems 2.7
Ornamental 2.75
Ancient Woodland 2.75
Regular Drained Land 2.775
Military 3.7
Wetland and Beach 4.25
Maritime Industry 4.4
Isabel Cook et al.
14 VOLUME 0 ISSUE 0 2019
are based on current or recent historic condi-
tions or trends. In the context of rapid envir-
onmental and ecological change, and
changing socio-political attitudes towards cul-
tural heritage and landscape management, it
is crucial to be more forward-looking when
identifying the factors that may threaten his-
torical assets. Therefore, the Landscape
Vulnerability Framework incorporates rele-
vant projections from climate models. The
proposed framework could also be applied
to other threats to cultural heritage, such as
urban development and extractive industries.
To adapt the VI to incorporate these threats,
factors such as governmental and local coun-
cil policies regarding the location of develop-
ment or permissions for extractive industries
should be included in the VI, in place of the
climate-related variables. This maintains the
focus on likely future threats, rather than just
extrapolating historic trends in the location
of development.
In terms of heritage management, the
information generated by using this frame-
work is useful for informing holistic heri-
tage management within a landscape, and
reveals broader trends than would be evi-
dent in site-specific research. The frame-
work does still include consideration of
archaeological features, as they influence
the historic and visual character of the
landscape. However, they are used as prox-
ies for the vulnerability of an element of
the landscape character within the LCA VI,
so the focus remains on the LCAs and his-
toric landscape as a whole.
Figure 2. LCF vulnerability scores and LCA VI results.
Climate Change: Landscape Vulnerability Framework
15THE JOURNAL OF ISLAND & COASTAL ARCHAEOLOGY
With an increasing threat to coastal
archaeology from the impacts of climate
change worldwide, it is unlikely that the
resources exist to protect all archaeological
sites at risk. Therefore, it is important to
consider a broader perspective on cultural
heritage management, to identify the key
areas of importance to local heritage
(Landorf 2009).
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