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Placing the power of real options analysis into the hands of natural resource
managers eTaking the next step
Rohan Nelson
a
,
*
, Mark Howden
a
, Peter Hayman
b
a
CSIRO Climate Adaptation Flagship, GPO Box 284, Canberra, ACT 2601, Australia
b
South Australian Research and Development Institute, GPO Box 397, Adelaide, SA 5001, Australia
article info
Article history:
Received 4 March 2012
Received in revised form
31 October 2012
Accepted 15 March 2013
Keywords:
Real options
Climate change
Covenants
Decision support
Natural resource management
abstract
This paper explores heuristic methods with potential to place the analytical power of real options analysis
into the hands of natural resource managers. The complexity of real options analysis has led to patchy or
ephemeral adoption even by corporate managers familiar with the financial-market origins of valuation
methods. Intuitively accessible methods for estimating the value of real options have begun to evolve, but
their evaluation has mostly been limited to researcher-driven applications. In this paper we work closely
with Bush Heritage Australia to evaluate the potential of real options analysis to support the intuitive
judgement of conservation estate managers in covenanting land with uncertain future conservation value
due to climate change. The results show that modified decision trees have potential to estimate the option
value of covenanting individual properties while time and ongoing research resolves their future con-
servation value. Complementing this, Luehrman’s option space has potential to assist managers with limited
budgets to increase the portfolio value of multiple properties with different conservation attributes.
Ó2013 Elsevier Ltd. All rights reserved.
1. Introduction
In this paper we explore the potential of real options analysis to
assist natural resource managers to manage the uncertainty that
climate change introduces to the future conservation value of land.
Real options analysis has evolved to overcome the limitations of
discounted cash flow analysis for valuing the flexibility to adapt
corporate investment strategies as new information resolves un-
certainty. It does so by refocusing risk management away from
minimising adverse outcomes within an existing set of activities,
towards exploiting the valuable opportunities inherent in future
uncertainty. The challenge we confront in this paper is whether the
complexity of real options analysis can be distilled into intuitive
rules of thumb (heuristics) and analytical tools to assist natural
resource managers to adapt to climate uncertainty. We then
explore whether these heuristics have potential to support the
intuitive judgement of conservation estate managers in covenant-
ing land in response to the uncertainty posed by climate change.
We begin by briefly reviewing the origins and nature of real
options analysis. A supporting appendix reviews the evolution of
heuristic approaches with potential to distil the analytical power of
real options analysis into forms intuitively accessible to decision
makers. We then report on a collaborative evaluation of two of the
most promising approaches emodified decision trees and Luehr-
man’s option space ewith conservation estate managers in Bush
Heritage Australia (BHA). Through this collaboration, we investi-
gate the potential for these two approaches to support the design of
appropriate conservation covenants and management actions.
2. Real options analysis
2.1. Why use real options analysis?
Real options analysishas evolved in the worldof corporate finance
to overcome the limitations in valuing uncertain investments that
arise when discounted cash flow analysis is simplistically applied
(Copeland and Antikarov, 2003;Dixit and Pindyck, 1994). If a single
linear pathway of project development and investment is assumed,
discounted cash flow analyses incorporate the probability of failure
into expected monetary values regardless of whether these can later
be avoided via adaptive management. Simplistic application of dis-
counted cashflow analysis candirect the focus of riskmanagement to
reducing downside risk by reducing the variability of all future out-
comes eboth positive and negative.
The problem is that reducing the variability of future outcomes
can also reduce the upside potential of strategies that create new
opportunities with uncertain but potentially highly valuable
*Corresponding author. Present address: Tasmanian Institute of Agriculture,
University of Tasmania, Private Bag 98, Hobart, TAS 7001, Australia.
E-mail address: rohan.nelson@utas.edu.au (R. Nelson).
Contents lists available at SciVerse ScienceDirect
Journal of Environmental Management
journal homepage: www.elsevier.com/locate/jenvman
0301-4797/$ esee front matter Ó2013 Elsevier Ltd. All rights reserved.
http://dx.doi.org/10.1016/j.jenvman.2013.03.031
Journal of Environmental Management 124 (2013) 128e136
outcomes. The capacity to defer irreversible decisions until new in-
formation begins to resolve future uncertainty gradually truncates
the downsidefrom the probability distribution of expected outcomes
over time (Copeland and Antikarov, 2003;Dixit and Pindyck, 1994).
This refocuses risk management on actively creating upside uncer-
tainty by investing in the development of new and potentially high
value investment opportunities (de Neufville, 2003;Triantis, 2005).
2.2. What is a “real”option?
An option in this sense is a right, but not an obligation, to make
an investment decision. The two most basic types of financial op-
tion are call and put options. A call/put option is the right but not
obligation to purchase/sell shares at an agreed price at a future date
known as the exercise date. The value of financial options derives
from volatility in the price of the underlying shares on which they
are written. The value of call/put options starts to be realised as
share prices rise/fall above/below the amount paid for the option.
Financial options with a predefined exercise date are known as
European options, whereas those with a flexible exercise date are
known as American options.
The term real option is used to describe the option value of in-
vestments in physical rather than financial assets, and has been
attributed to Myers (1977) by Borison (2003) and Triantis (2005).
Real options can involve the right to defer,expand,contract,abandon
or extend the life of a physical investment (Copeland and Antikarov,
2003). Investments that can be deferred or later expanded, for
example, have similar characteristics to call options. Examples
include mining leases, manufacturing plants and pharmaceutical
research, all of which represent a right, but not an obligation to
commercialise production depending on fluctuations in market
prices. In contrast, options to contract or abandon investments have
characteristics similar to put options. Insurance, for example, is the
right, but not obligation, to sell a damaged asset at a predefined
price if an uncertain adverse event occurs (de Neufville, 2003). The
ability to halt production until market prices improve is a common
example of a put real option in manufacturing industries.
The characteristics of real versus financial options have been
comprehensively reviewed by Copeland and Antikarov (2003) and
Mun (2006). Financial options are relatively easy to value because
they are well defined and because historical share price informa-
tion is readily available. The only source of risk is the future price of
the underlying security which is set in well established and publicly
accessible markets. Because the value of the underlying financial
security is beyond the immediate and direct influence of manage-
ment in the normal course of business, it can be modelled as a well
defined stochastic process. Financial options are relatively easy and
costless to exercise.
In contrast, real options can be difficult to value. The future value
of a real option is determined by an interaction of technical, mana-
gerial and market factors, many of which can be influenced by
managers. Real options are much less liquid than financial options,
being less divisible and often maturing over longer periods (Woolley
and Cannizzo, 2005). Many are not traded at all, and their value is
intrinsically confined to, and influenced by, the investment decisions
of a specific business and its immediate competitors. It can therefore
be unclear what asset the holder of a real option has a right to, or
what criteria should beused to determinewhen to exercisean option.
Exercising a real option may not be a single instantaneous market
transaction, and may incur significant transaction costs (Boer, 2002).
3. The utility of real options analysis to decision makers
Numerous analytical techniques for valuing real options have
evolved from the techniques used to value financial options. These
are comprehensively reviewed in Appendix A. We argue in this
paper that the choice of appropriate analytical techniques for
valuing real options depends both on the mathematically validity of
each method, and whether the results can be intuitively under-
stood and applied effectively by decision makers. The literature
review in Appendix A reveals two analytical approaches with po-
tential to meet both of these criteria: modified decision trees
(Copeland and Antikarov, 2003;Borison, 2003;Hertzler, 2007) and
Luehrman’s options space (Luehrman, 1998a,b).
3.1. Capacity and preferences of decision makers
There is mounting evidence that the complexity of real options
analysis has led to patchy or ephemeral adoption even by corporate
managers. Amram and Kulatilaka (2000) attributed interest in the
1990s to the novel valuation methods developed by Dixit and
Pindyck (1994). Since then, adoption has waned. A survey by
Busby and Pitts (1997) suggested that although investment
rescaling options were frequently assessed by 44 senior finance
officers in the United Kingdom, few of them had heard the term real
options. A later survey of 392 chief financial officers by Graham and
Harvey (2001) found that nearly 27% of them always or almost al-
ways incorporate the real options of a project when evaluating it (pg
199). However, an unpublished survey by Bain & Company (cited by
Copeland and Tufano, 2004: pg 1) of 451 senior executives that had
trialled real options analysis showed that one third of them had
abandoned the approach within the same year. Similarly, a survey
of 205 Fortune 1000 chief financial officers by Ryan and Ryan
(2002) found that only 10e15 per cent were using real option
techniques always or often.
There have been ongoing challenges to the intuitive accessi-
bility and hence adoptability of the most commonly promoted
forms of real options analysis (Lander and Pinches, 1998;Borison,
2003). The title of a paper by Borison (20 05) encapsulates this
sentiment eReal options analysis: where are the emperor’s
clothes? The most commonly cited reason for the limited adop-
tion of real options analysis by corporate managers is the
complexity of its analytical techniques (Copeland and Tufano,
2004;Copeland and Antikarov, 2003;Cortazar, 2004;Lander
and Pinches, 1998). A key point of contention has been the
extent to which the concept of risk neutral probabilities used in
binomial lattices is intuitively accessible to decision makers
(Lander and Pinches, 1998). Throughout this debate, even those
committed to promoting real options analysis have lamented a
lack of heuristics for communicating its analytical power to de-
cision makers (Triantis, 2005).
The issue of complex analytical techniques is a relative one,
and depends on the context and preferences of potential users.
Scepticism has been reported amongst corporate managers as to
whether the intuition and creativity of managerial decision
making can be reduced to an analytical decision tool (Copeland
and Tufano, 2004;Lander and Pinches, 1998). This scepticism
has been echoed by researchers evaluating the adoption of deci-
sion support systems in agriculture (such as Hayman, 2004;
Matthews et al., 2008). Complexity has tended to confine the
application of real options analysis to extractive natural resource
industries such as minerals, oil and forestry, where price uncer-
tainty can be analysed in well-developed markets (Triantis and
Borison, 2001;Saphores, 2001;Rocha et al., 2001). Complexity
has also tended to confine application of real options analysis to
companies where sophisticated analytical tools are common,
particularly those populated by engineers (Triantis and Borison,
2001). Contrary to its origins, the banking and finance industries
have expressed little interest in real options analysis (Triantis and
Borison, 2001).
R. Nelson et al. / Journal of Environmental Management 124 (2013) 128e136 129
3.2. Application to conservation and natural resource management
Early applications of real options analysis to natural resource
management included those exploring the phased development of
extractive (mining and oil) industries (Cortazar, 1999;Cortazar and
Casassus, 2000). Real options analysis has subsequently been
applied to a number of forest-related applications. Saphores (2001)
used real options analysis to explore harvesting decisions for nat-
ural forests where uncertain growth limited effective evaluation by
traditional methods. Rocha et al. (2001) found that the estimated
value of Amazon forest concessions to be consistently higher using
real options analysis than estimates derived using costebenefit
analysis. Saphores et al. (2002) used real options analysis to show
that ignoring unexpected price changes can lead to sub-optimal
decisions to harvest old growth timber. In contrast, real options
analysis has been found to add little to existing valuation methods
for plantation forest investment decisions (Manley and Niquidet,
2010;Hildebrandt and Knoke, 2011).
Irrigation and dam investment have also been the focus of real
options analysis, often contrasted with net present value ap-
proaches. In some cases, real options analysis ranks projects as
more profitable than indicated by discounted cash flow analysis
because of economic shocks and design uncertainties (Michailidis
and Mattas, 2007). In other cases, real options analysis has indi-
cated that projects are less profitable than suggested by discounted
cash flow analyses (Michailidis et al., 2009). Real options analysis
has informed public policy on water conservation in irrigated
agriculture, focussing attention on upgrading irrigation systems
rather than structural adjustment (Seo et al., 2008). It has also been
used to show that policies that reduce uncertainty in water prices
can encourage adoption of more water-efficient irrigation systems
(Carey and Zilberman, 2002).
In agriculture, Tozer (2009) applied real options analysis to
determine whether or not to invest in precision agriculture relative
to conventional farming. He found that standard costebenefit
analysis consistently overvalued precision farming relative to
conventional agriculture because it does not adequately account for
uncertainty or irreversibility. Mithoefer et al. (2004) used real op-
tions analysis to explore decisions by farmers in southern Africa to
conserve indigenous fruit trees when clearing woodland for agri-
culture. Similarly, Schatzki (2003) showed that agricultural land-
owners in the United States value the ability to keep their land
conversion opportunities open when making land use conversion
decisions. This helps to explain why land is often not converted
even though cost-benefit analysis suggests specific land conversion
opportunities are profitable.
Real options analysis has also been applied to wildlife conser-
vation decisions and in the valuation of biodiversity. Arrow and
Fisher (1974) explored the amount of wilderness to conserve
assuming that development was irreversible and the future value of
wilderness was uncertain. They found that the inclusion of a quasie
option value led to the allocation of more land to wilderness than
would have been the case if only expected benefits and costs were
assessed. Kassar and Lasserre (2004) explored the value of
conserving biodiversity using real options analysis, in cases where
more than one species provide similar ecological functions. They
demonstrated that the availability of substitute species has
inherent option value, and that this option value increases as cor-
relation in conservation value between species decreases. Bakshi
and Saphores (2004) used real options analysis to come up with
intuitive rules for managing the reintroduction of wolves into re-
gions of North America.
There has been some preliminary investigation of the potential
for real options analysis to support decisions to adapt to the un-
certainty introduced by climate change. Dobes (2008) has argued
that using real option thinking should underpin adaptation policy.
Whitten et al. (2012) found that real option analysis is a potential
pathway for applying resilience thinking to the management of
environmental risks, including adaptation to climate change. In
agriculture, Hertzler (2007) used modified decision trees to show
that real options analysis can provide insights into how to manage
climate change uncertainty in cropping and grazing systems.
Our focus in this paper is supporting the management of land as
a natural resource for the purpose of maintaining or enhancing
biodiversity. The evolving literature shows that the potential of real
options analysis to improve decision making in conservation and
related natural resource management has been known for some
time. However, few applications of real options analysis attempt
to frame the decision problem from the perspective of decision
makers. They are either researcher-invented stylised examples, or
complex researcher interpretations of real world investment sce-
narios. Either way, the lack of adoption and use suggests that
neither approach has been particularly helpful to decision makers.
We take the next logical step in closing this gap between
research and decision support. We worked with conservation
reserve managers to build intuitively accessible models enabling
them to explore the potential for real options analysis to inform
decisions to purchase or covenant land with uncertain future
conservation value due to climate change. Our intention is to
identify heuristic approaches with potential to be extended more
widely to the managers of conservation estates for designing land
covenants.
4. Case study, Bush Heritage Australia
4.1. BHA and real options analysis
Bush Heritage Australia (BHA) is an independent non-profit
organisation committed to preserving Australia’s biodiversity.
1
At
the time that this research was conducted in 2008, BHA owned and
managed 34 reserves throughout Australia covering close to 1
million hectares. The implications of climate change for BHA’s land
acquisition policy were investigated via interviews with conserva-
tion estate managers. BHA recognised that climate change is likely
to have significant implications for the conservation of permanent
reserves. This is because climate change alters ecological niches and
processes throughout the landscape, altering the survival prospects
of many rare and threatened species. Climate change can mean that
a conservation estate established to protect a specific set of biodi-
versity values may end up protecting an entirely different set in the
future. BHA is tackling this problem through its Beyond the
Boundaries program that aims to maintain the biodiversity value of
land surrounding the properties that it purchases.
BHA’s strategies for maintaining conservation values on sur-
rounding properties include the use of covenants. Covenants are
agreements with landowners to conserve a range of ecological
values on areas of land that could later be brought into a reserve
system, even though this option may never be exercised. Covenants
have the properties of a real option ea small initial investment to
create the right to later purchase land at an agreed price. Climate
change, management and market factors make these future land
and ecological values highly uncertain.
Estimating the future value of land, including multiple non-
market conservation values, and weighing this against the finan-
cial cost of purchasing it pose a significant valuation challenge for
BHA. A rigorous process of research and expert judgement is
currently used to make these tradeoffs. Various tiers of assessment
1
http://www.bushheritage.org.au/.
R. Nelson et al. / Journal of Environmental Management 124 (2013) 128e136130
have been created to efficiently balance the effort expended in the
assessment process against the value of each property within BHA’s
overall portfolio of land investments.
Discussion with BHA’s staff identified several stages of the
assessment process in which real options analysis has potential to
support intuitive expert judgement. At the earliest stages of
assessment, for example, decision trees may provide BHA’sfield
ecologists with a relative sense of whether the option value of a
specific property with climate sensitive conservation values is high
or low. At later stages of assessment, Luehrman’s option space may
provide more precise estimates of option value across a portfolio of
diverse properties. Both approaches can also be used to design
appropriate covenanting arrangements for individual properties.
For example, agreeing with land owners to manage weeds and
pests could significantly increase the future conservation value of
land. These applications were evaluated using intuitive models that
broadly simulate some of the more important characteristics of
these investment decisions.
The following applications of modified decision trees and
Luehrman’s option space were developed in iterative consultation
and participatory workshops with conservation estate managers.
Models of conservation investment scenarios were developed until
conservation estate managers found them realistic enough to
explore the consequences of alternative management and invest-
ment strategies. Each property characterised in the model has the
essential characteristics of properties under consideration for in-
vestment at the time that this research was conducted in 2008.
Each model can be easily rescaled to reflect the actual size of real
investment opportunities.
4.2. Decision trees and the option value of a single property
The literature reviewed in Appendix A suggests that the chal-
lenging problem of risk neutral probabilities raises doubts as to
whether modifieddecision trees can provide preciseestimates of real
option value. Despite this, the method has intuitive appeal for
communicating the presence or absence of option value, and the
relativemagnitude of this option value sothat alternative investment
options can be ranked. The intuitive appeal of this approach from a
research perspective has been explored in agriculture by Hertzler
(2007). The case study presented in this paper confirmed this intu-
itive appeal through participatoryevaluation from the perspective of
conservation reserve managers in BHA.
Fig. 1 provides a simple example of how modified decision trees
can be used to estimate the relative value of delaying irreversible
investments in properties with uncertain future conservation value
due to climate change. In this example, the decision problem is
whether to purchase a property located on a mountain (Mnt in
Fig. 1) or one on a plain.
The plain in this example represents a large property relatively
insensitive to climate change. This may be because its ecology is
mostly defined by non-climatic attributes such as soils, or because
it is large and well connected spatially to other ecosystems. Pur-
chasing the property on the plain results in an estimated
Expected valu e of Expected value Prob ability Result
delaying or not of decision
$ per ha
Change these numbers
severe 0.33 2000
Decision Buy Mnt moderate 0.33 1750 Buy Plain
Decision Buy Plain 1485
Delay mild 0.33 750
Buy Plain 1500
1500
severe 0.70 1900 100
Act now
1500 Decision Buy Mnt moderate 0.15 1650 Buy Mnt
Buy Mnt 1675
1675 mild 0.15 650
Heading to severe Buy Plain 1400
0.33 1400
Delay for 10 years severe 0.15 1900
1522
Heading to moderate Decision Buy Mnt moderate 0.70 1650 Buy Mnt
0.33 Buy Mnt 1538
mild 0.15 650
1538
Buy Plain 1400
1400
Heading to mild severe 0.15 1900
22$ ha 0.33
Decision Buy Mnt moderate 0.15 1650 Buy Plain
Buy Plain 988
1400 mild 0.70 650
Buy Plain 1400
1400
Optimum decision
Pe nalt y for wai tng
Value of w aiting
Fig. 1. Modified decision tree showing the value of delaying irreversible investments in conservation properties with a changing climate.
R. Nelson et al. / Journal of Environmental Management 124 (2013) 128e136 131
conservation value of $1500 per hectare, regardless of whether
climate change is mild, moderate or severe.
In contrast,the property on the mountain is small and particularly
sensitive to climate change. It has high conservation value ($2000 or
$1750 per ha) as a biodiversity refuge if climate change is severe or
moderate, but lowconservationvalue ($750) if climate changeis mild.
The analysis can be thought of as abstracting from the use of dis-
counting, or alternatively as being expressed in present value terms.
The properties can be purchased now, or in 10 years time when
more information on the regional impacts of climate change are
known. This is consistent with investment scenarios that conser-
vation estate managers often face when working with farmers. In
this example, the regional climate is expected to change, but little is
currently known about the relative severity of this change. This lack
of knowledge about the future severity of regional climate change
in say 2050 is represented by an equal objective probability of mild,
moderate or severe impacts (33%).
Over time, downscaled climate projections are likely to become
available to refine these probabilities. This model assumes that
more information about the regional severity of climate change will
be known in 10 years when the option for purchase the land ma-
tures. This is represented by three possible scenarios in which an
additional 10 years of climate data and scientific advance may alter
the subjective probability of mild, moderate or severe impacts to
70% respectively in each case. Which of these three future scenarios
will occur is currently unknown, and hence they have an equal
objective probability of occurring at the time when the decision to
defer the purchase of the land needs to be made.
Regardless of which scenario eventuates, delaying the decision to
purchase land is expected to incur a penalty in terms of lost con-
servation value. If purchase is delayed by 10 years, management for
other values such as agricultural production is expected to reduce
the conservation benefits of both properties by $100 per hectare.
It is important that in both the ‘act now’branch and the ‘delay
for 10 years’branches of the decision tree, the objective probabil-
ities of mild, moderate or severe climate impacts in 2050 are
exactly the same. Subjective opinion regarding trends in climate
change over the next 10 years does not change the objective
probability of mild, moderate or severe impacts actually occurring
in the future. If there is specific scientific knowledge of the relative
probability of climate change impacts in 2050, this information
must be added to both the ‘act now’branch of the tree as well as the
‘delay for 10 years’branch. This would mean altering the equal
likelihood of each level of climate change impact in Fig. 1 (33%)
towards the most likely outcome.
The value of delaying the purchase in this case is positive, but
small ($22 per ha). The value of waiting is strongly contingent on
improved future knowledge of climate change, as well as reducing
any potential future degradation of the land. For example, if the
knowledge accumulated over the next 10 years provided only a 64%
probability of mild, moderate or severe impacts, there would be no
value in delaying the purchase. Similarly, an increase in the penalty
for waiting to $122 per hectare is also enough to make delaying the
purchase unattractive. This provides conservation estate managers
with a rough tool for exploring the relative option value of a
covenant designed to maintain the conservation value of a property
for 10 years (up to $122 per hectare).
Correctly specifying this problem as a decision tree requires
considerable expertise, and the final product appears deceptively
simple. This expertise is unlikely to rest at least initially with end-
users, and expert assistance is likely to be required until users ac-
quire this capability. Once structured correctly, the spreadsheet
model is easy to use, and can be rapidly reconfigured to explore the
sensitivity of relative option value to changes in various input pa-
rameters. With current settings, the decision tree legitimises
choices to delay land purchase while waiting to see if some of the
uncertainty in local climate change impacts can be resolved by new
knowledge over the next 10 years.
4.3. Luehrman’s option space and the option value of a conservation
portfolio
The relative option value of a single property with climate
sensitive conservation value is only part of the investment problem
faced by BHA. BHA’s overall objective is to construct a portfolio of
conservation properties, all with greatly divergent characteristics,
that together maximise the biodiversity values conserved with the
funds available. Properties can differ in their size, the rate at which
their conservation value changes over time, and the mechanisms
via which they can be brought under management. Purchasing a
property provides BHA with the strongest influence over manage-
ment, but it is also the most expensive and least reversible alter-
native. Covenants and management agreements are more flexible,
but conservation values may be at risk for as long as the property is
being managed for other uses such as grazing.
Decision trees are efficient tools for exploring the option value of
paired investment alternatives and the interaction of choice with
time, but quickly become messy when generalised to a greater
number of alternatives. For property portfolio decisions, Luehr-
man’s option space has potential to provide clearer insights to
support investment decisions. As described in more detail in
Appendix A, Leuhrman’s option space is defined by NPV
q
, which is
the ratio of the future value of the asset (S) over its cost (the present
value of its exercise price, X). This metric is compared to the
volatility of the annual returns from the asset,
s
ffiffi
t
p, estimated using
Monte Carlo simulation, historical data and/or expert opinion. Us-
ing these metrics, the value of each option can be estimated via look
up tables. Luehrman uses option space to emphasise the role that
active management plays in enhancing option value. Options tend
to move upward in option space (see Figure A1) as time to their
expiry lapses and uncertainty is resolved (Figure A1,Appendix A).
Active management can shift investments to the right and down-
wards in option space as innovation creates positive forms of
uncertainty.
A portfolio of properties with simplified but realistic conserva-
tion characteristics was developed based on conversations with
BHA estate managers (Table 1). Using Luehrman’s real options
terminology (Appendix A), the exercise price (X) is the price that
land can be purchased for, whether now or at its present value at
some pre-agreed point in the future under a covenant. It is current
practice for conservation estate managers to use expert judgement
to value each property (S
0
) including conservation value. Real op-
tions analysis provides no additional insight into the difficult
problem of estimating conservation values in monetary terms. The
properties can be purchased immediately, or put under a man-
agement agreement for Tyears. At the end of this management
period, the future value of the properties is uncertain (S
T
), and this
uncertainty can be characterised as a probability distribution by
estate managers. A triangular distribution was used because the
parameters of this type of distribution are intuitive and easy for
estate managers to manipulate to reflect their future expectations.
This probability distribution can be readily generalised to any other
form.
A spreadsheet was built so that these parameters could be
altered readily in conversation with estate managers to broadly
capture the characteristics of alternative properties. Properties A
and B in Table 1, for example, could be medium to large properties
with low current conservation value relative to their current pur-
chase price, but with potential to be of high conservation value in
the future. Their future conservation value could be expected to
R. Nelson et al. / Journal of Environmental Management 124 (2013) 128e136132
increase due to climate change or the increasing scarcity of these
ecotypes in the landscape. An important difference between op-
tions A and B is the length of time that purchase can be delayed
(T¼5, 10). Property C, in contrast, could represent a small property
of high current and future conservation value. Property D could
represent an iconic large landholding with high and relatively
certain conservation values over a long period. Property E is a small
to medium property of some conservation value that is at risk,
perhaps due to detrimental management (such as overstocking).
The management issues surrounding property E are so problematic
that its purchase under current management could incur consid-
erable future rehabilitation costs (future conservation value S
T
is
negative).
A decision to purchase one or more of these properties imme-
diately creates some difficult trade-offs, particularly with limited
budgets. For example, if the conservation estate manager has only
$14 million to spend on the properties in Table 1 then one imme-
diate implication is that the iconic property D cannot be purchased.
Properties A, B, C and E can be purchased individually, or properties
A and C, A and E, or C and E can be purchased together. However,
this poses a dilemma because only properties C and D have suffi-
cient immediate conservation value to yield a positive net present
value. Purchasing properties A and C, A and E, or C and E together
result in a net present value of zero. The only option that fits within
the budget and generates a positive net present value is the pur-
chase of property C, the smallest property, but this option may have
a low impact on regional conservation outcomes. What should the
conservation estate manager do?
As discussed in Section 4.1, BHA is using property covenants to
influence conservation values beyond the reach of the properties
that it directly owns. The option characteristics of each property in
Table 1 can be mapped in the option space designed by Luehrman
(1998a,b) (Fig. 2), and their option value estimated using lookup
tables (Brealy and Myers, 1991)(Table 1). The options values in
Table 1 suggest that all of the properties other than property E have
a positive option value. Both options A and B require proactive
management intervention to realise their potential future conser-
vation value. However, the short time available (5 years) to manage
property B towards higher conservation outcomes places a signif-
icant constraint on its potential option value. Overall, the total
amount worth paying to retain options on properties AeD is less
than $14 million, creating potential to influence their management
until more is known about their future conservation value. This
includes the larger property D, the high option value of which
derives more from its iconic nature than uncertainty in its future
conservation value.
Note that even if the budget were less than $14 million, the
estimates of real option value provide some useful quantitative
information that could assist conservation estate managers to make
difficult trade offs. For example, the analysis of future conservation
value suggests that there may be little risk to the future conser-
vation value of the large iconic property D, even if the conservation
estate manager does not get involved in its management. Proper-
ties A and C have similar option value, but completely different
ecological characteristics. The choice between the two may come
down to a discussion of the specific threats influencing the value of
property C, and the ability through management to alter the future
conservation value of property A. The analysis of option value re-
directs the conversation from a discussion of unknowns, to a dis-
cussion of how to positively influence future uncertainty from a
range of sources including climate change.
-0.20
-0.18
-0.16
-0.14
-0.12
-0.10
-0.08
-0.06
-0.04
-0.02
0.00
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5
Value to cost ratio (NPV
q
)
Worthwhile now
Management
likely to refine
Management
may fail
Management
likely to improve
Management
may rescue
Volatility
D
C
A
B
E
Fig. 2. A hypothetical (but realistic) portfolio of conservation properties in Luehrman’s
option space.
Table 1
The option characteristics of a hypothetical portfolio of conservation properties.
Property X(input) S
0
(input) NPV ¼(S
0
X)S
T
etriangular distribution (input) T(input) Option value (look up tables)
$ million $ million $ million $ million years $ million % of S
T
Low Med High
A862 4 8 16 10 2.96 32.9
B13103 3 10 15 5 0.14 1.50
C 3 5 2 3 7 9 12 2.14 32.9
D 20 25 5 22 25 28 15 8.23 32.9
E6422 2 4 3 0.00 0.00
Total 0 13.5
X¼the purchase price of the property.
S
0
¼estimated current value of the property, including conservation value.
S
T
¼uncertain future value of the property, including conservation value.
T¼period over which a covenant or management agreement can be negotiated before a decision needs to be made to purchase the property.
AeMedium-sized property currently rundown (S
0
<X). Assessed as likely to have improved conservation potential under a 10 year covenant (S
Tmed & high
>S
0
), but some
downside risk of deteriorating conservation value (S
Tlow
<S
0
).
BeLarge property, similar to A in that it is currently rundown. Assessed as likely to have improved conservation value under a 5 year covenant, but with a risk of deteriorated
conservation value. Unlike property A, the median future conservation value is less than the purchase price (S
Tmed
<X).
CeSmall property with a high current conservation value (S
0
>X). Over a 12 year covenant the conservation value is assessed to improve or stay the same. Even in the worst
case, the conservation value remains the same as the purchase price (S
0
>S
Tlow
¼X).
DeIconic large property with a high current conservation value. Over a 15 year covenant this is assessed as likely to improve. In the worst case, the conservation value remains
greater than the purchase price (S
0
>S
Tlow
>X).
EeA small to medium property with low current conservation value and an assessment that under a 3 year covenant, the conservation value will not improve and remain less
than the purchase price (S
0
¼S
Thigh
<X).
R. Nelson et al. / Journal of Environmental Management 124 (2013) 128e136 13 3
4.4. Luehrman’s option space and the design of appropriate
covenants and management actions
Evaluation of Luehrman’s option space with BHA revealed
another application useful to conservation estate managers ethe
design of appropriate covenants. Current assessment methods tend
to suggest that a property is likely to have significant option value,
but it can be difficult to place even an approximate estimate on the
financial value of this option. Conservation estate managers may be
able to roughly assess their potential to influence the management
of a property, and how this could enhance its future conservation
values, but it can be difficult to assess how much this would alter its
current option value. How much should the conservation estate
manager pay for an option? What conditions such as expiry date
and potential management outcomes should the conservation es-
tate manager negotiate?
Luehrman’s option space can help conservation estate managers
design the appropriate attributes of covenants, and work through
important trade-offs. This can be demonstrated by revisiting the
example of property E, which is reproduced in Table 2 and Fig. 3.In
the previous example (Table 1,Fig. 2), the option value of property E
was constrained by the detrimental impacts of current management
on conservation values (future conservation value was negative),
and the limited time available to influence its management (3 years).
However, if it were possible to negotiate a longer period (say 10
years) over which management could be positively influenced, the
value of a covenant could be much higher. This is true even if there
remains some risk of negative future conservation outcomes(S
T
can
still fall as low as $2 million), providing the longer period has
greater upside potential (say the upper limits of the distribution are
now S
T
¼$8 and $10 million). The result in this example is a sub-
stantially positive option value. Real options analysis has enabled
the manager to explore the consequences of different covenant
conditions and proactive management on option value.
5. Discussion
5.1. Real options and strategy
Part of the value of real options analysis derives from reframing
and guiding strategic decision making (Triantis and Borison, 2001)
as demonstrated in the biodiversity examples in Section 4. Real
options analysis makes more explicit some of the key principles
intrinsic to innovative risk management, and provides some
quantitative tools for supporting their application. From this
perspective, real options analysis is a logical and much needed
enhancement of traditional valuation methods, rather than a rev-
olution in the way decisions are made. This inductive dimension
means that the principles of real options analysis have long been
applied at a more intuitive level without the relatively recent jar-
gon or analytical techniques. According to Copeland and Antikarov
(2003), for example, the first recorded application of real options
analysis was revealed in the story of Thales, recorded by Aristotle,
who bought exclusive rights to all the olive presses on the island of
Milos at the standard rent prior to the harvest season. When an
outstanding season eventuated, Thales reportedly made a fortune,
presumably without first completing a sophisticated real option
analysis.
A number of authors have questioned the need for complex
analytical techniques to precisely estimate the value of real options
(van Putten and MacMillan, 2004;Lander and Pinches, 1998;de
Neufville, 2003;Eapen, 2003). These authors suggest that deci-
sion making strategies can often be enhanced effectively using less
precise methods to rank alternatives. According to de Neufville
(2003), for example, managers don’t need high degrees of preci-
sion because they make choices between competing alternatives
rather than detailed judgements of individual options. This is
consistent with the foundational decision making theory of Herbert
Simon (see Simon, 1983). A focus on improved outcomes from
decision making helps to the bridge the gap between theory and
practice, refocusing real options analysis on its value to decision
makers (Luehrman, 1998b), rather than its mathematical elegance
and appeal to analysts. This has led to the development of the
intuitive approaches for approximating the value of real options
that have been evaluated in Section 4.
There is broad agreement that the main benefit to most users of
real options analysis lies in refocusing risk management away from
the standard approach of avoiding negative outcomes towards
proactively nuturing and exploiting positive sources of uncertainty
(de Neufville, 2003). This is clearly evident in the biodiversity ex-
amples explored in Section 4which focus attention on manage-
ment actions that increase future conservation value. Proponents of
adaptive management and adaptive governance have described
how positivism (see Lacey, 2005) has created unrealistic expecta-
tions of the degree to which reductionism can resolve the uncer-
tainty inherent in natural resource management (Holling, 1978;
Brunner and Steelman, 2005). This has led to narrowly bureau-
cratic definitions of risk management that focus on procedures to
Table 2
Alternative options characteristics of a conservation property.
Property X(input) S
0
(input) NPV ¼(S
0
X)S
T
etriangular distribution (input) T(input) Option value (look up tables)
$ million $ million $ million $ million years $ million % of S
T
Low Med High
E original 6 4 22 2 4 3 0.00 0.00
E modified 6 4 22 8 10 10 1.99 33.1
E - original
E - modified
-0.25
-0.2
-0.15
-0.1
-0.05
0
0.0 0.5 1.0 1.5 2.0
Management
may rescue
Volatility
Management
likely to improve
Value to cost ratio (NPV
q
)
Fig. 3. Using Luehrman’s option space to evaluate alternative covenants.
R. Nelson et al. / Journal of Environmental Management 124 (2013) 128e136134
maintain current activities. For example, citing the joint Australian/
New Zealand Standard on Risk Management, Hardaker et al. (2004)
define risk management as the systematic application of manage-
ment policies, procedures and practices to the tasks of identifying,
analysing, assessing, treating and monitoring risk (pg 13). As a
result, the conventional approach to managing risk is to attempt to
minimise the incidence of risky events, and negate their impact.
In contrast, more holistic approaches to risk management can
uncover additional and previously unknown opportunities through
careful analysis of the risks involved in taking a certain course of
action before the event occurs. Real options analysis refocuses risk
management on proactively seeking out and exploiting the new
opportunities embedded in future uncertainty. This is consistent
with pursuing diversification as a pathway to desired outcomes, to
enable increased substitution between activities and assets in
household livelihood strategies (Ellis, 2000). According to de
Neufville (2003), the real option approach offers a ‘fundamentally
eperhaps even cataclysmically edifferent’approach to risk man-
agement compared to today’s standard engineering approach (pg
30). Proactively seeking sources of uncertainty to create new op-
portunities can be a difficult concept for conventional risk man-
agers to accept. However, it is neither new nor untested, as the
example of Thales demonstrates.
6. Conclusions
This paper has demonstrated that real options analysis can be
distilled into intuitively accessible heuristics with potential toplace
its analytical power into the hands of natural resource managers.
The evaluation with conservation estate managers shows that the
value of real options analysis derives from enabling managers to
explore options for proactively managing the uncertainty arising
from climate change and other sources. However, this value can
only be realised if the analytical power of real options analysis is
made intuitively accessible to decision makers. Real options anal-
ysis builds on the intrinsic intuitive appeal of avoiding irreversible
decisions and creating future opportunities. This paper adds to
growing evidence that this intuition can be supported with
analytical methods that rank alternatives, without necessarily
having to provide complex and precise valuations of individual
options. In doing so this paper has demonstrated the potential to
take the next step with real options analysis beyond researcher-
driven applications, to real applications that support practitioners
in the field.
Acknowledgements
This research was funded by the Managing Climate Variability
Program of Land & Water Australia. The authors acknowledge the
generous collaboration of Bush Heritage Australia, and are grateful
for the significant contributions made by Stuart Cowell, Annette
Stewart and Mel Sheppard. The authors acknowledge the valuable
technical assistance of Mike Dunlop and Phil Kokic, and Greg Hert-
zler for contributions to the theory of real options in agriculture.
Appendix A. Supplementary data
Supplementary data related to this article can be found at http://
dx.doi.org/10.1016/j.jenvman.2013.03.031.
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