The Economics of Ocean Acidification
– a scoping study
Claire W. Armstrong1, Silje Holen2, Ståle Navrud3 and Isabel Seifert2
April 2012
1
University of Tromsø, Norway
2
3
NIVA, Oslo, Norway
University of Life Sciences, Ås, Norway
1
Summary
Despite the fear that ocean acidification may have serious consequences for human well-being in
the future, very little economic research on ocean acidification has been carried out to date. In this
scoping report the economic aspects of ocean acidification are presented; applying an ecosystem
services approach. After a brief presentation of the ocean acidification issue, we provide an overview
of marine ecosystem services that are expected to be affected by ocean acidification. The relevant
economic theory and methods for estimating the economic costs of ocean acidification are laid out
and discussed. To illustrate the possible magnitude of these economic costs, a case study is carried
out presenting selected ecosystem services in Norwegian waters, and how they, based on the
current natural science research, are expected to be impacted by ocean acidification. Then the
economic effect of these impacts is estimated. The results show that ocean acidification may have
negative as well as positive effects upon provisioning services of fisheries and aquaculture with
annual net effects being in the order of several million NOK. However, for the regulating service of
carbon storage the estimated negative impacts are several orders of magnitude higher than for
fisheries and aquaculture. Finally, knowledge gaps with regards to estimating the economic loss due
to ocean acidification are identified.
2
Acronyms
AB
AC
BT
C
CBA
CE
CO2
CS
CV
EU
GDP
GIS
HP
IPCC
MC
MEA
NOK
NPV
OA
PV
RP
SP
SRES
SSC
TC
TEEB
TEV
US
USD
USDA
WTA
WTP
Averting Behaviour
Averting Costs
Benefit Transfer
Carbon
Cost Benefit Analysis
Choice Experiments
Carbon dioxide
Consumer Surplus
Contingent Valuation
European Union
Gross Domestic Product
Geographic Information System
Hedonic Price analysis
Intergovernmental Panel on Climate Change
Mitigation Costs
Millennium Ecosystem Assessment
Norwegian kroner
Net Present Value
Ocean Acidification
Present Value
Revealed Preference
Stated Preference
Special Report on Emission Scenarios
Social Cost of Carbon
Travel Cost
The Economics of Ecosystems and Biodiversity
Total Economic Value
United States
United States Dollar
United States Department of Agriculture
Willingness to Accept compensation
Willingness to Pay
Acknowledgements
The authors gratefully acknowledge financing through the FRAM Centre and NIVA, Norway.
Furthermore, we are the beneficiaries of the knowledge of several scientists at NIVA regarding
chemical and biological effects of ocean acidification. We also thank Kristy J. Kroeker, who kindly
provided us with the original data from her meta-analysis.
3
Contents
Introduction............................................................................................................................................. 6
Ocean acidification – a brief background ................................................................................................ 8
The economics of ocean acidification in the literature ........................................................................... 9
The concept of ecosystem goods and services ..................................................................................... 10
Framework for economic valuation of impacts of ocean acidification ................................................. 13
Affected ecosystem goods and services................................................................................................ 15
Supporting services ........................................................................................................................... 16
Nutrient cycling and primary production ...................................................................................... 18
Resilience ....................................................................................................................................... 18
Habitat ........................................................................................................................................... 19
Food web ....................................................................................................................................... 19
Biodiversity .................................................................................................................................... 20
Provisioning services ......................................................................................................................... 20
Fish and shellfish ........................................................................................................................... 21
Genetic/Chemical resources ......................................................................................................... 22
Regulating services ............................................................................................................................ 22
Natural carbon storage.................................................................................................................. 22
Noise absorption ........................................................................................................................... 23
Cultural services ................................................................................................................................ 23
Recreation and tourism ................................................................................................................. 23
Education and research ................................................................................................................. 24
Legacy of nature ............................................................................................................................ 24
Economic analysis of Ocean Acidification ............................................................................................. 25
Ecosystem services and social costs and benefits ............................................................................. 25
Valuation ........................................................................................................................................... 26
Non-market valuation techniques................................................................................................. 26
Value transfer ................................................................................................................................ 30
Scaling-up of ecosystem values ..................................................................................................... 32
Discounting .................................................................................................................................... 34
Natural resource management ............................................................................................................. 35
4
Exogenous environmental effects in fisheries models...................................................................... 36
Norwegian marine ecosystem goods and services at risk from ocean acidification - a back-of-theenvelope estimation.............................................................................................................................. 37
Impact scenarios for ocean acidification ........................................................................................... 37
Impact scenarios of provisioning services ..................................................................................... 38
Impact scenarios of regulating services ........................................................................................ 40
Impact scenarios of cultural services ............................................................................................ 41
Impact scenarios of supporting services ....................................................................................... 41
Economic approach and applied data ............................................................................................... 41
Provisioning services ..................................................................................................................... 42
Regulating services ....................................................................................................................... 43
Results ............................................................................................................................................... 44
Provisioning services ..................................................................................................................... 44
Regulating services ........................................................................................................................ 46
Knowledge gaps..................................................................................................................................... 47
Some concluding remarks ..................................................................................................................... 50
References ............................................................................................................................................. 52
5
Introduction
As often observed, what happens beneath the sea surface struggles to gain popular attention. Ocean
acidification, known as “the other CO2 crisis”, still in the shadow of global warming, is however
increasingly gaining the attention of the science community as well as the public.
In the last few years the natural science research on ocean acidification has exploded (Doney 2012),
and it is expected to keep growing. Nonetheless, our knowledge of the quantified consequences of
ocean acidification is still very limited, despite growing evidence that ocean acidification will have
large and negative (but also variable) effects on marine organisms (Ries, Cohen et al. 2009; Kroeker,
Kordas et al. 2010). How this translates into population and ecosystem effects, and further into
human welfare via services is even less well known. Very little economic or social science research
has been carried out in connection with ocean acidification, though some studies indicate impacts of
ocean acidification on for instance fisheries (Cooley and Doney 2009; Narita, Rehdanz et al.
Forthcoming), coral habitats that are valued by humans (Brander, Rehdanz et al. 2009), as well as
general reductions in goods and services from the sea (Turley, Brownlee et al. 2010).
It is safe to say that the studies on the economics of ocean acidification carried out to date are
limited both in scope and depth. This is mainly due to the limited natural science knowledge about
the impacts of ocean acidification. The existing economic studies are partial analyses, not taking into
account that the loss of one service may be replaced by another, or alternatively second best
alternatives. This may take place via changes in human consumption, or changes in the ecosystems
where ocean acidification may reduce some goods and services, while increasing others. The studies
to date are also mainly focussed on provisioning services, such as fisheries on calcifying organisms, or
the recreational and tourism values connected to tropical coral reefs. These provisioning services
give direct use values, but also supporting services that more indirectly affect market and nonmarket values may be affected by ocean acidification, as well as other regulating and cultural services
less easily identified and valued.
There are a number of issues that complicate the economic evaluation of ocean acidification:
i) Limited knowledge of effects of ocean acidification in the natural environment.
ii) Limited knowledge of how goods and services in the sea are/will be affected by ocean
acidification.
iii) Little knowledge of values in the ocean.
iv) Methodological limitation as regards economic valuation of such goods and services.
v) Scant knowledge of human preferences for goods and services in the ocean.
Endeavouring to bridge these knowledge gaps is important in order to supply more information
about the consequences of our fossil fuelled lifestyles. Identification of the costs and perhaps even
benefits of ocean acidification are vital in order to give some underlying input into political agendas
and choices for managing human behaviour, both nationally and internationally. Alternatively, the
6
knowledge gleaned can guide human societal adaptive behaviour in the face of environmental
change and a high CO2 world 1.
Relevant economic research questions are then what are the consequences of ocean acidification,
and what are their costs, or for that matter, revenues? And if costs exceed revenues, how can they
be mitigated? The Stern review on the economics of climate change (Stern 2006) does not include
ocean acidification. Hence, an addition of ocean acidification effects, depending on their magnitude,
may strengthen the climate change arguments for early mitigation. Alternatively, if what we face is
irreversible environmental change, what may we expect, what are the consequences, and how can
we adapt in order to mitigate these changes? In this scoping study we identify the costs and benefits
of ocean acidification, as far as the current knowledge allows us.
The studies to date on economic effects of ocean acidification have been on regional or global levels,
(Cooley and Doney 2009; Narita, Rehdanz et al. Forthcoming) despite most natural science studies
being highly local in scope, often consisting of laboratory experiments on single species (see
overviews in Kroeker et al (2010) and Hendriks et al (2010)), or in situ studies at specifically acidic
environments (Hall-Spencer, Rodolfo-Metalpa et al. 2008). There is a large natural science knowledge
gap that must be bridged, linking local or single species effects of ocean acidification to larger
ecosystem consequences. In this study we focus on potential regional effects of ocean acidification in
Norwegian waters.
Recent studies have referred to the potential for over-dramatisation of the consequences of ocean
acidification (Hendriks and Duarte 2010; Hendriks, Duarte et al. 2010; Le Quesne and Pinnegar 2011).
It is therefore important to note that the presentation in this report regarding potential effects of
ocean acidification in Norwegian waters are highly preliminary, focusing on a limited number of
species and services, and constrained by the knowledge available so far.
The main aims of this scoping study are therefore as follows:
1) Identify goods and services that may be expected to be affected by ocean acidification.
2) Identify the methods to assess the values connected to ocean acidification impacts, as well as
optimal management in the face of ocean acidification.
3) Illustrate possible damage costs of ocean acidification in Norwegian waters, focussing on
provisioning and regulating services.
4) Present knowledge gaps
The layout of this is report is as follows: After a brief introduction to what acidification of oceans
consists of, and how it is analysed economically in the literature so far, a framework for economic
valuation of impacts of ocean acidification is presented. The following section presents relevant
marine ecosystem services, and how they may be affected by ocean acidification. The economic
analysis of ocean acidification is divided into a section on economic valuation and a section on
1
The economic arguments applied here are by far the sole input into policy and management, but
can be seen as complements to other e.g. ethical arguments related to the management of natural
environments.
7
natural resource management. This is followed by a back-of-the-envelope estimation of the
economic value of ecosystem services at risk in Norwegian marine ecosystems due to ocean
acidification. The report concludes with a presentation of knowledge gaps.
Ocean acidification – a brief background
Anthropogenic CO2 emissions have not only increased the atmospheric concentration of CO2 but also
the CO2-concentration in the world oceans. Atmospheric CO2 dissolves into the ocean, and it is
estimated that currently between one third (Sabine, Feely et al. 2004) and half of the aggregated
global emissions (Raven 2005) has been absorbed in this manner. The uptake of CO2 has
consequences for the chemistry of the ocean. It is becoming more acid (increase of H+ ions), and the
concentration of carbonate ions [CO32- ] is decreasing.
The oceanic carbonate system is mainly characterized by the chemical equilibriums shown in
equations (1) and (2).
(1) CO2 (atmos) ↔ CO2 (aq) + H2O ↔ H2CO3 ↔ H+ + HCO3- ↔ 2H+ + CO32(2) Ca2+ + CO32- ↔ CaCO3
Absorbed CO2 reacts with seawater and forms carbonic acid (H2CO3), which dissociates into hydrogen
ions (H+) and bicarbonate ions (HCO3-). The hydrogen ions released by carbonic acid bind to
carbonate (CO32-) to form another bicarbonate ion and thus further decrease the amount of
carbonate in the water. Lower carbonate concentrations lead to the disturbance of the carbonate
formation as shown in equation (2) i.e. more calcium carbonate will dissolve, a process called decalcification.
The opposite process, i.e. the formation of carbonate in the oceans (calcification) is due to calcifying
organisms. Whether calcification or de-calcification takes place depends on the saturation of the
ocean water with carbonate ions, and here especially the saturation with aragonite and calcite.
These two polymorphs of carbonate crystals are used by calcifying organisms to build their shells or
external skeletons. In undersaturated conditions it becomes more difficult, and for some organisms
nearly impossible to build their shells or other structures of carbonate (Raven 2005). In the worst
case, de-calcification degrades existing shells (Orr, Fabry et al. 2005).
Currently, average seawater pH is around 8.1 (Tyrrell 2008), but large daily and seasonal fluctuations
of up to 0.7 and 1.3 pH-units, respectively, can be observed (Wootton, Pfister et al. 2008). The actual
surface ocean pH is in comparison to preindustrial times already reduced by 0.1 pH units (Caldeira
and Wickett 2003), due to an increase of atmospheric CO2. The carbonate system of the ocean
surface will follow the ongoing atmospheric CO2 increase with a time lag of less than one year (Zeebe
and Wolf-Gladrow 2001). Projections based on the IPCC SRES scenarios (IPCC 2007) predict additional
reductions between 0.14 and 0.35 pH units in the 21st century. This would mean that an average
ocean surface pH between 7.9 and 7.7 can be expected for 2100 or before.
8
Even though atmospheric CO2 concentrations are relatively uniformly distributed over the planet, the
bio-chemical conditions in the seawater vary. As the CO2 enters the ocean by gas exchange across the
air-sea interface, and due to the limited vertical transport of oceanic water, impacts of acidification
will mainly be observed in the top few hundred meters of the ocean (IPCC 2007). Regions with deep
water formation as the Norwegian Sea, where CO2 concentrations have increased also in mid and
abyssal depths (Sabine, Feely et al. 2004) are the exceptions. Higher latitudes have naturally lower
carbonate concentrations (Doney, Fabry et al. 2009). Model simulations under IPCC business as usual
(BAU) scenarios indicate that within a few decades arctic surface waters can become undersaturated
for aragonite (Steinacher, Joos et al. 2009). This process is predicted to start already in 2020 (Feely,
Doney et al. 2009).
The economics of ocean acidification in the literature
The literature on the economic impacts of ocean acidification on ecosystem services is scarce, and
there are less than a handful peer reviewed, published papers on this topic. Yet, if the explosion of
natural science papers on ocean acidification is any indication, we may in the near future expect a lot
more economic studies on the topic. However, for now we have to relate to the few studies
available, as presented below.
Calcifying organisms in the sea are, as mentioned above, especially vulnerable to ocean acidification
(Fabry, Seibel et al. 2008). Cooley and Doney (2009) construct future US harvest trends for one type
of calcifier, molluscs, based on specific assumptions regarding reduced calcification. They find that US
mollusc harvest declines 6-25% with a 0.1-0.2 pH-units decrease over 50 years, but argue that this is
in the lower end compared to other studies showing greater declines over a shorter time span
(Wootton, Pfister et al. 2008). They therefore estimate the net present value (NPV) of a 10-25%
decrease in US mollusc harvests for different discount rates, and finds that this gives substantial
economic losses as molluscs account for 19% of US domestic ex-vessel revenues (Cooley and Doney
2009). Multiplier effects will increase the impact. Furthermore, (Cooley and Doney 2009) underline
the fact that some coastal communities, such as New Bedford, are especially dependent on these
fisheries, exacerbating already existing social problems. Another study of mollusc loss due to ocean
acidification (Narita, Rehdanz et al. Forthcoming) indicates potential annual costs globally to be
greater than 100 billion USD, when taking into account future income rise.
Though no values are estimated explicitly, Sumaila et al (2011) focus on economic effects for fisheries
in general due to changes in the sea. Based on the current knowledge, they expect ocean
acidification to lead to decreases in the catch potential. They assume that a lower catch globally will
lead to higher prices, but also higher costs of fishing due to declines in availability. They argue that
the open access nature of most fisheries, especially in developing countries, leads to a zero resource
rent situation, which could be improved (at least in the short run) by the increase in harvest costs
reducing effort in the fisheries.
9
Brander et al (2009) combine a meta-analysis study of global coral reef value, including all goods and
services, with an impact assessment of coral reef loss due to ocean acidification. Though they find
that the economic impact escalates rapidly due to the assumption of rapid economic growth in the
relevant countries, increasing the value of a luxury good such as coral, the value is nonetheless a
fraction of total income. The annual value by 2100 is found to be one order of magnitude smaller
than that estimated previously for climate change (Tol 2008).
It is worthwhile to note that the few studies carried out to date on the economic side of ocean
acidification are all partial analyses and encompass large uncertainties.
The concept of ecosystem goods and services
In recent literature, the links between nature and the economy are often described using the
concept of ecosystem services, or flows of value to human societies as a result of the state and
quantity of natural capital (TEEB 2010). The Millennium Ecosystem Assessment (MEA) defines
four categories of ecosystem services that contribute to human well-being, each underpinned by
biodiversity (MEA 2005); see also Figure 1:
•
Provisioning services – for example commercial fisheries, agriculture and other raw materials.
•
Regulating services – for example climate regulation through carbon storage and water
cycling, pollination and protection from disasters.
•
Cultural services – for example recreation, spiritual and aesthetic values, education.
•
Supporting services – for example photosynthesis, nutrient cycling, habitat, resilience,
primary production, biodiversity.
10
Figure 1 Ecosystem goods and services from the marine environment (revised from MEA (2005)).
Estimating the value of the various services and benefits that ecosystems and biodiversity generate,
may be done with a variety of valuation approaches. All of these have their advantages and
disadvantages. Hybrid approaches may overcome disadvantages of particular valuation methods. The
limitations of monetary valuation are especially important when ecosystems approach critical
thresholds and ecosystem change is irreversible or reversible only at prohibitive cost. Under
conditions of high or radical uncertainty and existence of ecological thresholds, policy should be
guided by the “safe-minimum-standard” and “precautionary approach” principles
Based on Armstrong, Kahui et al. (2008), Anon (2005), Toman (1998), Brander, Rehdanz et al. (2009),
MEA (2005) and Kumar (2010) the different economic valuation methods are evaluated in terms of
their suitability for assessment of different marine ecosystem services impacted by ocean
acidification. Table 1 provides an overview of which economic valuation methods can be used, and
the data needed for the different valuation methods.
11
Table 1. Economic valuation methods for marine ecosystem goods and services.
Valuation
methods
Stated
Preference
(SP)
methods
Revealed
Preference
(RP)
methods
Production
function
approach
Cost-based
methods
Benefit
transfer
(Value
Transfer)
Approach
Willingness-to-pay (WTP) (or Willingness-to- accept
(WTA) compensation) for changes in provision of
ecosystem services are “stated” by respondents in
surveys using structured questionnaires. These
methods include contingent valuation and choice
experiments.
Values are “revealed” through studying consumers’
choices and the resulting price changes in actual
markets that can then be associated with changes in
provision of ecosystem services. These methods include
the Hedonic Price method where differences in
residential property prices are explained by differences
in the characteristics of the house/apartment;
accessibility to public transport, schools, shop etc; and
neighborhood characteristics which also include
environmental qualities like water and air quality,
ocean views etc.: the partial impact of environmental
quality on the sales price represents the WTP for this
attribute. The Travel cost method uses people´s travel
costs to recreational areas to estimate the recreational
benefits of ecosystems. Averting behaviour (AB) in
terms of the costs households incur to avoid impacts
can under a set of assumptions also be used to value
environmental costs
Marine
ecosystem
services
Supporting
services
Cultural
services
Cultural
services
A group of methods used to value regulating and
supporting services, where ecosystem services are one
of several “inputs” to a final service or good enjoyed by
people. Ecosystems’ marginal contribution to the final
service is valued. When a change of ecosystem
characteristics leads to off-site or downstream loss of
services, biophysical damage functions of this
“pressure-state-impact” relationship are used.
Provisioning
services
These methods assume that the expenditures involved
in preventing/mitigating or replacing losses of
ecosystem services represents what people are willing
to pay for the ecosystem services. However, WTP could
be lower or higher than these costs.
Provisioning
services
Refer to the use of secondary, existing study estimates,
from any of the valuation methods mentioned above.
Transfer could be based on unit value estimates (e.g.
WTP per household per year), a WTP functions from a
single study, or a WTP function from a meta-analysis of
many valuation studies.
All services
12
Regulating
services
Supporting
services
Regulating
services
Data needs
Survey with
scenario
description and
questions about
WTP/WTA for
specific services
Data of
environmental
quality attributes,
consumers choices
and the resulting
price changes in
actual markets
connected to the
public good in
question
Production
function approach
can be used when
it is known how the
ecosystem services
are contributing to
the production of
market goods.
Data on
expenditures
involved in
preventing,
mitigating or
replacing lost
ecosystem services.
Suitable, relevant
and high-quality
original valuation
studies.
Framework for economic valuation of impacts of ocean acidification
In the following we suggest a framework for studying impacts of ocean acidification from an
economic perspective, applying a damage function approach.
Figure 2. Impact pathway of ocean acidification using the Damage Function Approach (DFA), and
how changes in human behavior (for instance via mitigation and adaptation/management) can
affect this pathway.
Figure 2 is a general description of the Damage Function Approach (DFA) (or Impact Pathway
Approach) applicable to Ocean Acidification, the increased “emission” would be CO2, and the
”transport” would be uptake of CO2 in the oceans; which again would increase
“Concentrations/conditions” and result in lower pH. Exposure-response models (ERMs) between
lower pH and services and goods provided by the marine and coastal ecosystems would then be used
to predict the (bio-)physical effects on ecosystem services . The Millennium Ecosystem Assessment
(MEA) describes four types of services: i) supporting, ii) provisioning, ii) regulating, and iv) cultural
(see Figure 1), as described in the previous section. The effects on these ecosystem services,
provided by the oceans, are then assigned an economic value based on the impacts on human
wellbeing/welfare. These marginal impacts are valued in terms of individuals´ willingness-to-pay
13
(WTP), either as reflected in market prices for private goods (such as commercial fishing) or from
non-market environmental valuation techniques in terms of Revealed Preference (RP) and Stated
Preference (SP) (see Table 1). The estimated Total Economic Value (TEV) of the marginal change in
ecosystem services constitutes i) Direct use value , ii) Indirect use value, iii) Option value and iv) Nonuse values (i.e. existence and bequest value). Direct use values encompass economic production
where the natural environment is a factor of production, and non-use values represent values
connected to the pure existence of the natural environment or desire to bequest it to future
generations. Option values describe the willingness to pay to secure the potential future value from
an ecosystem service. If the acidification impacts could lead to irreversible effects like extinction of
species, the Quasi–Option value (QOV) should be added to TEV. QOV was first proposed by Arrow
and Fisher (1974), and is the economic value of increased information we could obtain by avoiding
irreversible effects; i.e. it can be viewed as the flexibility premium we are willing to pay to keep
options open and avoid irreversible losses.
Economic valuation of non-market environmental goods is performed by conducting either: i) a new
primary study using SP or RP techniques, or ii) value transfer. Value transfer (often termed “benefit
transfer” although the same method can also be used to assess costs) transfer economic values from
existing primary studies (i.e. “study sites”) to a site where the economic analysis, often Cost-Benefit
analysis (CBA), is performed (i.e. “policy site”). Often we lack time and money to conduct new,
primary studies, and value transfer is performed – that is: if there are relevant high quality primary
valuation studies of the same type of impact, which we can transfer from. The focus of this report is
mainly on the last step, i.e. economic valuation of costs and benefits; where there is uncertainty,
both due to the uncertainty in the environmental valuation techniques ability to estimate the “true”
economic value, and the added uncertainty of transferring these estimates in space and time to
address a current policy question at the policy site. Unfortunately there is a lack of knowledge, and
uncertainty (both in methodology, empirical applications and transfer of information across space
and time) in all steps, which adds up in the last valuation step.
Whereas most of the discussion above has focused on the spatial dimension, there is also a temporal
dimension that needs to be considered in order to calculate aggregate ecosystem service loss and
thus damage costs over time – see Figure 3 below for an illustration. Note that remedial actions will
shorten the recovery time and thus the magnitude and present value of the service loss. Adaptive
measures could also reduce the economic cost of the service loss.
14
Figure 3. Time path of ocean acidification (OA) impact, and ecosystem service loss with and without management or
adaptation. Note that we here assume that the aggregated effect of ocean acidification is negative.
Note that in Figure 3 we assume that the aggregated effect of ocean acidification is negative. Note
also that the economic value of these potentially lost ecosystem services can be viewed as the
avoided damage costs if effective adaptation and management measures are implemented; and
thus, must be compared to the costs of these measures.
Affected ecosystem goods and services
In the context of this work, it is important to identify which of the four ecosystem services defines by
MA (2005); i) supporting, ii) provisioning, iii) regulating , and iv) cultural, can be expected to be
affected by ocean acidification, and to what degree.
This report will present a pre-evaluation review and some underlying qualitative and quantitative
goods and service identification, as described in Figure 4. Thus, we attempt to determine the
characteristics of the use and non-use values of goods and services that are affected by ocean
acidification, present previous valuation attempts, and suggest methods and priorities for the further
development of understanding the effects of ocean acidification. This approach is chosen since both
the underlying qualitative and quantitative review of goods and services is limited or non-existent, as
well as there being substantial limitations in knowledge with regards to how these goods and
services are affected by ocean acidification; hampering monetary valuation .
15
Figure 4. The pyramid of ecosystem goods and services evaluation (Armstrong, Foley et al. 2010)
Supporting services
Supporting services are those services necessary for the production of all other ecosystem services,
i.e. they feed into provisioning, regulating and cultural services, as described in Figure 1, and thereby
only enter into human well-being indirectly. They differ from regulating, provisioning, and cultural
services in that their impacts on people are usually indirect, both physically and temporally, whereas
changes in the other services have relatively direct impacts on people. Some services can be
categorized as either a supporting or a regulating service, depending on the time scale and
immediacy of their impact on people. Relevant examples of supporting services are habitat, nutrient
cycling, primary production, and resilience.
From an economic perspective, a natural way to value supporting services would be to estimate the
flow of values emanating from natural sources. However, the danger of double counting these
values; first as supporting service values, and then as values inherent in provisioning, regulating and
cultural values was pointed to as a serious problem early on (Aylward and Barbier 1992), and has
underlined the need to keep these values separate (Beaumont, Austen et al. 2008).
16
This issue raises the question of whether supporting services should be treated in an economically
different manner to for instance provisioning, regulating and cultural services. I.e. rather than
assessing supporting services as flows, they could instead be seen as stocks. Alternatively the links
between ecosystem stocks and supporting services, as suggested in Figure 5 should be made clear. In
the natural resource economics tradition, the supplier of goods and services, for instance a fish stock,
determines the potential flow of sustainably harvestable fish, i.e. the provisioning service. The aim is
usually to maximise the long term flow of economic net benefits from the use of the natural
resource, i.e. profits from fish harvesting, which thereby determines the optimal fish stock size.
Similarly one could think of the natural environment functioning as such a stock, supplying benefits
to society in the shape of provisioning, regulating and cultural services. Hence the maximisation of
the net benefits of these services is a function of the ecosystem stock or the supporting services, as
described in Figure 5.
Figure 5. Direct services (regulating, provisioning and cultural) as functions of the supporting services. a, b and c illustrate
different relationships between the supporting services/ecosystem stocks and the direct services. The second x-axis
visualizes the link between supporting services and ecosystem stocks. Three types of links are presented; in a) there is a
carrying capacity (K) as regards ecosystem services, where so large ecosystem stocks disallow any direct services to
humans. In case c) ecosystem stocks over the maximum sustainable yield level (Smsy) give the maximum amount of direct
services. Case b lies between two extremes a) and c).
Note that the Figure 5 presents a static or equilibrium picture of interactions between the different
services. To give an example in relation to Figure 5, the regulating service of untreated waste disposal
into the ocean carries a substantial opportunity cost. The ability of the oceans to absorb this waste is
dependent upon the nitrification rate, or nutrient cycling, a supporting service. This nutrient cycling is
again dependent upon the pH in the ocean (Beman, Chow et al. 2011). A reduction in pH may be
expected to reduce the nitrification rate of the oceans, leading to the capacity to absorb waste
declining, i.e. potentially reducing regulating services of waste disposal below the maximum direct
service level in Figure 5 .
17
In renewable natural resource management, different regulations are implemented in order to
ensure the optimal stock size of the resource in question. These regulations may control the inputs
applied in the utilisation of the resource, and/or the extracted outputs from the resource base. In the
fisheries case this would mean regulating the actual fishing activity, for instance via gear restrictions,
and/or controlling the amount of fish harvested. Recent management methods have included long
term goals and measures to reach these goals (e.g. so called reference points and harvest control
rules). Relating this to the natural environment and ocean acidification this would involve
management to ensure the maximum net benefits accruing from provisioning, regulating and cultural
services. In the case of ocean acidification the problem becomes somewhat harder to manage, as the
management must presumably take ocean acidification as an exogenous variable. Yet, this raises the
question of how to optimally manage the natural environment in the face of these exogenous forces.
Central supporting services both terrestrially and in the marine are nutrient cycling, primary
production, resilience and habitats. We will discuss these services with regards to the marine and
ocean acidification specifically, below.
Nutrient cycling and primary production
Studies have shown that ocean acidification affects nutrient cycling, such as oceanic nitrification.
Beman et al (2011) showed experimentally that nitrification rates decreased for pH declines. This
reduction changes the nitrogen composition in the ocean, favouring smaller primary producers, with
potential effects for food-webs as well as carbon export to the deep sea (Beman, Chow et al. 2011).
Hence we observe that this potential change in supporting service may feed directly into provisioning
and regulating services (see below), the former through changes in commercial fish stocks, the latter
via carbon sequestration and waste absorption.
Increased pCO2 has been shown to both increase primary production (Qiu and Gao 2002), but also to
decrease it for some species (Riebesell, Zondervan et al. 2000).
Resilience
It is well known that different organisms react in different ways to changes in environmental
conditions, such as lower pH. Studies have shown that many species are flexible and can handle
changes in their natural environments, but that it comes at a cost, i.e. many organisms survive under
lower pH, but functions such as growth or health may decline (Wood, Spicer et al. 2008; Findlay,
Wood et al. 2009). Alternatively, mobile species may move to different areas with a higher pH. But
this also comes at a cost, either with regard to energy use of transport, or the choice of some second
best habitat. Furthermore, as noted by Hall-Spencer et al. (2008), ocean acidification changes will
come much faster than the historic changes in pH, rendering evolutionary adaptation often
impossible. Hence, these diverse costs reduce the resilience of species, and thereby also the
potential supporting service that feeds into for instance provisioning, regulating or cultural services.
18
Habitat
Coral reefs are well known high-biodiversity habitats, both as regards the shallow and deep water
versions (Roberts, McClean et al. 2002; Freiwald, Fosså et al. 2004). That ocean acidification can be
expected to affect tropical coral is well known (Hoegh-Guldberg, Mumby et al. 2007), but also cold
water coral may be expected to be affected (Roberts, Wheeler et al. 2006; Turley, Roberts et al.
2007; Veron 2008). Connections between coral habitats and fisheries are described in several
economic studies (Crépin 2007; Foley, Kahui et al. 2010), illustrating the supporting service function
of coral habitats. Considering the connection between ocean acidification and calcifying organisms, it
seems clear that ocean acidification may be expected to affect the supporting services of habitats. It
is worth noting that corals also supply a much broader set of services (Cesar and Beukering 2004;
Brander, Van Beukering et al. 2007; Foley, van Rensburg et al. 2010).
Some seagrass species grow better under elevated CO2 levels, which might have a positive effect on
fish recruitment (Fabry, Seibel et al. 2008). Seagrass has been shown to be a high biodiversity habitat
(Waycott, Duarte et al. 2009), hence in this case ocean acidification may have positive effects feeding
into provisioning services.
Food web
Disruptions in the foodweb by ocean acidification are very probable (Fabry, Seibel et al. 2008;
Wootton, Pfister et al. 2008; Comeau, Gorsky et al. 2009; Kroeker, Kordas et al. 2010). Changes in
growth, composition and allocation of organisms can be expected and changes on lower trophic
levels may have an impact on higher trophic levels. Commercially important fish species may be
indirectly affected by ocean acidification via reduction in prey species, and this may well have the
greatest impact on fisheries (Le Quesne 2011). As many calcifying organisms play important roles in
the marine food web, the potential effects of ocean acidification on abundance of these species (see
more below in the Provisioning section), and thereby the supporting service of prey for commercial
species could be important.
However, dietary flexibility may buffer the effects of prey decline, and some species have over time
changed diets substantially without this having notable effects on productivity (Le Quesne and
Pinnegar 2011). However, second best food choices may be just that; second best, indicating that
there is a price to pay in the form of some detrimental effects. Similar issues are relevant for food
species used in aquaculture (Børsheim and Golmen 2009), but here the possibilities for substitution
are greater.
Ecosystem shifts where one species is transplanted by another, whether due to natural changes or
anthropogenic interaction, will not necessarily result in reduced provisioning benefits, as new species
may compensate for the original ones, the “cod to crustacean” shift in Canadian fisheries in the late
1990s being the classical example (Hamilton and Butler 2001).
19
The most fundamental source of energy in marine foodwebs is photosynthesis by phytoplankton.
Increased CO2 may fertilise phytoplankton growth in the oceans. However, the limiting factor for this
growth is usually the availability of nutrients rather than carbon. Nonetheless, as mentioned above,
nitrification may be negatively affected by ocean acidification (Beman, Chow et al. 2011). Other
suggested problems could be changes in timing of phytoplankton production (Le Quesne 2011). For
instance, many larval stages of commercially important fish have a limited window in time well
adapted to phytoplankton blooms, where small changes in timing of the blooms may reduce
recruitment to the fish stocks.
Biodiversity
In situ studies of low pH, shallow water areas in the sea (Hall-Spencer, Rodolfo-Metalpa et al. 2008)
illustrate the changes that may be expected as regards biodiversity at lower pH levels. Though no
species counts are presented, Hall-Spencer et al. (2008) show that species such as seagrasses thrive
at lower pH, while calcifying organisms are not present, and argue that ocean acidification will
probably bring about reductions in biodiversity. Though many papers on ocean acidification refer to
biodiversity, the focus is on specific responses to low pH for given species.
Provisioning services
Provisioning services are the products used by humans that are obtained directly from habitats and
ecosystems. In the context of the ocean, these include in particular fisheries and aquaculture, oil and
gas extraction and waste disposal sites. In most cases, the exploitation of provisioning services
involves a significant input of man-made capital and labour, for example in the form of fishing boats,
oil rigs, and their crews.
For oil and gas extraction no major impacts are expected due to ocean acidification. Corrosion effects
on infrastructure used to exploit these ecosystem services depends, in addition to the pH, on the
type of steel and the composition of seawater. Corrosion can increase or decrease with lower pH
(Subir 2011). As the expected changes in pH due to ocean acidification are unlikely to lead to a
significant increase in corrosion rate (Raven 2005), we will not consider corrosion effects.
Submarine waste disposal sites may be affected by ocean acidification. Experimental studies have
shown that the changes in seawater chemistry due to elevated CO2 concentrations affect the
solubility, adsorption, toxicity, and rates of redox processes of metals in seawater (Millero, Woosley
et al. 2009). Higher dissolution from sediments was found for Al, Cr, Ni, Cu, Zn, Cd and Pb, and the
released metals may affect bioavailability and toxicity of the metals to biota (Ardelan, Steinnes et al.
2009). Near a submarine disposal of mine waste in Greenland, elevated concentrations of metals
could be found in biota even after the closure of the mine (Sondergaard, Asmund et al. 2011). This
indicates that ocean acidification may aggravate contamination problems around submarine waste
disposal sites due to an increased release of metals, which is a relevant problem for several sites in
Norway.
20
Fisheries and aquaculture can be impacted by ocean acidification due to physiological impacts at the
single organisms level; followed by effects on ecosystem level, changes in habitats, and in the
foodweb (Kleypas, Feely et al. 2006). These impacts can be negative as well as positive (Kroeker,
Kordas et al. 2010). In general, the early life stages of fish such as eggs, larvae and juveniles are
considered to be more vulnerable to changes in environmental conditions (Guinotte, Orr et al. 2006),
whereas adult marine fish appear to be highly tolerant to elevated CO2-levels (Kikkawa, Kita et al.
2004; Kikkawa, Sato et al. 2006). As the early life-stages of fish in aquaculture are raised in landbased tank-systems, they are not exposed to ocean acidification. In freshwater experiments salmon
parr (i.e. young fishes, ca. 10-13g) have showed reasonable tolerance to elevated CO2 levels
(Fivelstad, Waagbo et al. 2007). Thus, it can be expected that salmon when put in ocean pens may be
old enough to withstand the expected elevated CO2 levels. Cod fertility is likely to be robust in the
face of near-future ocean acidification (Frommel, Stiebens et al. 2010), but further pH reductions i.e.
below the expected values for 2100 may lead to weight reductions in young cod (Moran and Stottrup
2011).
Fish and shellfish
As mentioned in the introduction, ocean acidification affects humans directly via provisioning, as well
as indirectly through the supporting services 2. From the effects of ocean acidification upon
supporting services we can point to a number of consequences for provisioning, as presented above.
With regards to the direct physiological effects upon marine organisms, these can roughly be
grouped in three main types: 1) changes in internal acid-base balance, 2) impacts upon reproduction
and early development, and 3) effects on calcification (see Le Quesne and Pinnegar (2011) for a more
detailed overview of physiological effects that have been studied).
Regarding internal acid-base balance, active animals such as most fish species, squid and some crabs,
are expected to be less sensitive to changes in acid-base balance, as CO2 builds up naturally in their
bodies during active movement (Le Quesne 2011). However, this so called ionic regulation may come
at a cost, as has been shown in some studies to date (Seibel and Walsh 2003; Spicer, Raffo et al.
2007). Furthermore, early life stages are often more vulnerable than fully grown individuals, and may
therefore be expected to be more severely impacted by ocean acidification.
Of the provisioning services listed in Figure 1, services consisting of the supply of calcifying organisms
are expected to be directly affected (Cooley and Doney 2009; Narita, Rehdanz et al. Forthcoming).
Calcifying organisms, such as corals and molluscs, are expected to be amongst the first organisms to
be affected by ocean acidification (Fabry, Seibel et al. 2008), and yet it may not be the actual
calcification that is threatened by ocean acidification, but rather other activities (Kleypas and
Langdon 2006; Findlay, Wood et al. 2009). I.e., under conditions of declining pH in the oceans,
calcification may be kept up, but ensuring this activity can be expected to come at a cost for
2
Le Quesne and Pinnegar (2011) point to a third mechanism coined the “indirect management effect”, as
fishery managers balance the many different objectives for the marine environment, taking into account the
various exogenous forcing factors, one being ocean acidification. From the perspective of the Economics
discipline, it is natural to study this latter effect as a choice of human optimising behaviour, and we concentrate
on the effects via provisioning.
21
organisms in the form of physiological trade-offs. These trade-offs have been shown to include
reduced metabolism, health and behavioural responses (Findlay, Wood et al. 2009), as well as muscle
wastage (Wood, Spicer et al. 2008).
Whether it is calcification or some other physiological activity that is affected by ocean acidification,
most of the studies to date point to effects that would reduce natural and potentially also cultured
production of calcifying organisms in the marine environment (though see some references of the
opposite in Kroeker et al (2010)). This would reduce the sustainable yield of these organisms,
potentially increasing market prices, while the reduction in availability could increase costs of
harvesting (Sumaila, Cheung et al. 2011).
Genetic/Chemical resources
Though provisioning of genetic and chemical resources is a function of available biodiversity, the use
is direct (or potentially direct), making this a provisioning rather than a supporting service. As
mentioned earlier, potential biodiversity decline due to ocean acidification has been suggested (HallSpencer, Rodolfo-Metalpa et al. 2008; Dupont, Dorey et al. 2010) questioning option values.
Regulating services
Regulating services are the direct benefits obtained through the natural regulation of habitats and
ecosystem processes such as gas and climate regulation, natural carbon sequestration and storage,
waste absorption and biological control.
For instance, tropical coral reefs supply regulating services in the shape of coastal protection and
shoreline stabilisation valued at US$ 9 billion worldwide (Cesar 2003). In 2005 in Asia, this was also
made especially when a tsunami devastated the coastline of a number of countries, raising the
question whether several decades of loss of coral reefs and mangrove forests increased the damages
caused by the sea (Dahdouh-Guebas, Jayatissa et al. 2005).
Natural carbon storage
Natural carbon storage by CO2-uptake in the ocean is expected to decrease in the future due to
limited buffering capacity. of the oceans, resulting in a positive feedback of ocean acidification to
atmospheric CO2 levels (Gehlen M. 2011). Comparative measurements in 1994/1995 and 2002-2004
found an average yearly decrease in CO2 uptake of 1.1 ± 0.1 mol m-2 a-1 in the North Atlantic between
20oN and 65oN (Schuster and Watson 2007). In temperate/subpolar regions the rise of sea surface
temperature accounts for 30% of this decrease (Schuster and Watson 2007). Assuming that ocean
acidification is responsible for the remaining 70% of the decrease we can expect a yearly decrease in
oceanic CO2 uptake of 0.77 ± 0.07 mol m-2 a-1, i.e. 9.24 ± 0.84 g C m-2 a-1.
22
In a modelling experiment Hofmann and Schellhuber (2009) assume reductions in biogenic
calcification, as demonstrated in many studies, and unsurprisingly show how this results in a negative
feedback further destabilising the Earth’s climate. However, they also show that reduced CaCO3 in
the ocean results in less deep sinking particulate organic carbon (POC), hence weakening of the
marine carbon pump. In addition their model results include a decline in oxygen concentration in
depths between 200 and 800 meters, expanding the hypoxic zones in the ocean, with potential
detrimental effects for ocean life.
But not only the oceanic carbon cycle, but as well other biogeochemical cycles will change due to
ocean acidification (Gehlen M. 2011). Field experiments showed that a decrease of oceanic microbial
nitrification rates by 3-44% can be expected within the next decades (Beman, Chow et al. 2011).
Changes in biogeochemical cycles and the water chemistry will probably have consequences for
regulating services.
Noise absorption
Another regulating service is noise absorption. At lower pH an increase of low-frequent noise due to
the decrease in ocean sound absorption can be expected (Hester, Peltzer et al. 2008). This will
probably mainly affect marine mammals which communicate via acoustic signals, but currently there
is too much uncertainty to quantify this effect (Golmen 2010).
Cultural services
Cultural services are usually the non-material benefits people obtain from habitats and ecosystems
through recreational, aesthetic and inspirational enjoyment. Cultural services will mainly be affected
where the impacts of ocean acidification become “visible”. This might be the case e.g. when coral
reefs are damaged or transfer to different latitudes (Andersson, Mackenzie et al. 2008) or if certain
species disappear.
Recreation and tourism
Recreational and tourism values connected to for instance tropical corals are examples of cultural
services from the oceans. Several studies have shown the general public’s valuation of these
resources (Cesar and Beukering 2004; Brander, Van Beukering et al. 2007), and being calcifying
organisms, coral reefs have been identified as being vulnerable to ocean acidification. Coral reefs are
highly dependent on calcification, for cementing the organism to hard substrate, for support of
colony expansion, for elevating the coral so that it increases access to food, nutrients and welloxygenated and lighter waters, as well as for increasing reproduction and photosynthesis (Kleypas
and Langdon 2006). Tropical coral reefs are therefore expected to be especially affected by ocean
23
acidification, thus affecting the recreational and other services (Brander, Van Beukering et al. 2007;
Brander, Rehdanz et al. 2009) rendered by these structures.
Cold water coral reefs are from the human perspective most often far less accessible than their
tropical cousins, yet studies have indicated willingness to pay for their protection based on option
values and existence values (Glenn, Wattage et al. 2010; Wattage, Glenn et al. 2011).
Increased noise in the ocean due to human activities such as petroleum exploration and extraction,
fishing as well as shipping, has been receiving increased attention, especially related to unexplainable
marine mammal deaths (Wright, Soto et al. 2007). Though the ocean absorbs sound, increasing
temperatures reduce this capacity. Also reduction in pH reduces the ocean’s ability to absorb sound,
exacerbating the already increasing trends of anthropogenic noise in the sea (Hester, Peltzer et al.
2008). Though increased mammal death has food web consequences, more relevant perhaps for
supporting services, clearly there may also be consequences for the recreational and tourism services
connected to whale and marine mammal watching.
Marine mammals and birds are not expected to be directly affected by lower pH, as birds have only
limited direct contact with the ocean and cetaceans dive to great depths where high CO2
concentration are normal. However, if prey species are negatively affected, this may clearly affect
birds and cetaceans, which again has an effect upon marine recreational values from bird and whale
watching.
Education and research
Valuing the ocean environments via educational and research expenditure, is not straight forward, as
these entities are in effect costs. However, willingness to incur costs indicates that benefits are
perceived to be greater (Armstrong, Foley et al. 2010). Beaumont et al (2008) present so called
cognitive values related to UK marine biodiversity, including research and education, but argue that
they represent valuation of more than merely biodiversity.
There are a number of studies of fisheries management costs, and the fact that these costs are
sometimes substantial, e.g. up to 25% of gross value of fish landings (Arnason, Hannesson et al.
2000), may to some degree reflect the broader values connected to marine environments, or
perhaps rather that of the coastal communities that depend on them. How these cultural, including
research and education values, would be affected by ocean acidification, is at this point mere
speculation.
Legacy of nature
The awe and inspiration, aesthetic enjoyment that life in the sea generates, visible in art and
literature, are clearly cultural values, though hard to quantify, and few studies have been carried out
to this effect in marine environments (Soderqvist and Hasselstrom 2008). Furthermore, how these
values may be affected by ocean acidification is even harder to determine. Indeed, the threat of loss
24
may increase the value of resources potentially affected by ocean acidification, often indicated by
the willingness to support non-governmental organisations’ efforts to protect threatened nature.
However, how these and other cultural values may be affected by ocean acidification is at this point
beyond even speculation.
Economic analysis of Ocean Acidification
In the following we will divide the economic analysis of ocean acidification in two; valuation and
management. Clearly valuation of the consequences of ocean acidification as portrayed in
Figure 2 is an important contribution to understanding the economic and social consequences of this
change in the marine environment. Results from valuation exercises may input into mitigating efforts
related to carbon emissions globally. However, mitigation may not be feasible, or if feasible, at least
limited, and adaptation and/or management in the face of ocean acidification is another area where
economic analysis may give valuable input. Hence, valuation results may feed into for instance
bioeconomic models of natural resource management, giving lessons on how society best can meet
the challenges of ocean acidification. Hence in the following we discuss how economic valuation of
ocean acidification effects can be carried out, followed by a presentation of how natural resource
management in the face of ocean acidification may be developed.
Ecosystem services and social costs and benefits
As the ecosystem services categorization in Figure 1 suggests, the Millennium Ecosystem Assessment
adopts a very broad definition of ecosystem services, limited only by the requirement of a direct or
indirect contribution to human well-being. This broad approach recognizes the myriad ways in which
ecosystems support human life and contribute to human well-being. Boyd and Banzhaf (2007)
propose a narrower definition that focuses only on those services that are end products of nature,
i.e., “components of nature, directly enjoyed, consumed or used to yield human well-being”
(emphasis added). They stress the need to distinguish between intermediate products and final (or
end) products and include only final outputs in the definition of ecosystem services, because these
affect people most directly and consequently are what people are most likely to understand. In
addition, the focus on final products reduces the potential for double-counting, which can arise if
both intermediate and final products or services are valued. Under this definition, ecosystem
functions and processes, such as nutrient cycling, are not considered services. Although they
contribute to the production of ecological end products or outputs, they are not outputs themselves.
Likewise, because supporting services contribute to human well-being indirectly rather than directly,
they are recognized as being potentially very important but are not included in Boyd and Banzhaf’s
definition of ecosystem services.
25
Many, if not most, components and functions of an ecosystem are intermediate products in that they
are necessary inputs to the production of services but are not services themselves. We emphasize
that this does not mean these intermediate products are not valuable, rather that their value will be
captured in the measurement of services.
A final, important constraint imposed by the definition is that services are not benefits nor are they
necessarily the final product consumed. For example, recreation often is called an ecosystem service.
It is more appropriately considered a benefit produced using both ecological services and
conventional goods and services. Recreational benefits arise from the joint use of ecosystem services
and conventional goods and services. Consider, for example, the benefits of recreational angling.
Angling requires ecosystem services, including surface waters and fish populations, and other goods
and services including tackle, boats, time allocation, and access. For this reason, angling itself—or
“fish landed”—is not a valid measure of ecosystem services.
Regardless of the specific definition used, ecosystem services play a key role in the evaluation of
policies that affect ecosystems because they reflect contributions of the ecosystem to human wellbeing. Simply listing the services derived from an ecosystem, using the best available ecological,
social, and behavioral sciences, can help ensure appropriate recognition of the full range of potential
ecological responses to a given policy and their effects on human well-being. It can also help make
the analysis of the role of ecosystems more transparent and accessible. To ensure consideration of
the full range of contributions, this report uses the term ecosystem services to refer broadly to both
intermediate and final/end services. In specific valuation contexts, however, it may be important to
identify whether the service being valued is an intermediate or a final service.
Valuation
In the following, we will review non-market valuation techniques that can put economic values on
these ecosystem services in order to reflect how they contribute to human wellbeing.
Non-market valuation techniques
Economists have developed a variety of techniques to value non-market environmental goods
consistent with the valuation of marketed goods; i.e. based on individual preferences. These
techniques are based upon either observed behaviour (revealed preferences; RP) towards some
marketed good with a connection to the non-marketed good of interest, or stated preferences (SP) in
surveys with respect to the non-marketed good; see table 2 for an overview of these techniques.
26
Table 2. Classification of Environmental Valuation Techniques (based on individual preferences)
Revealed preference
(RP)
Stated Preferences
(SP)
Indirect
Direct
Travel Cost (TC) method
Hedonic Price (HP) analysis
Averting Behaviour (AB)
Production Function
(Market prices)
Replacement Costs (RC)
Mitigation Costs (MC)
Choice Experiments (CE)
Contingent Valuation (CV)
Revealed Preference (RP) techniques can be divided into direct and indirect methods. Direct methods
include production function approaches where environmental impacts are valued using “pressurestate-impact” relationship and market prices, e.g. impacts on commercial fisheries from ocean
acidification. This approach uses only the physical or biological “pressure-state-impact” relationship to
estimate the response to a change in some environmental parameter. The observed market price of
the activity or entity is then multiplied by the magnitude of the physical or biological response to
obtain a monetary measure of damage. Thus, neither behavioural adaptations nor price responses
are taken into account. Simple multiplication provides an accurate estimate of economic behaviour
and value – in this case changes in gross revenue of commercial fisheries – only if economic agents
are limited in the ways in which they can adapt to the environmental effect and if the impact is small
enough to have little or no impact on relative prices. This combination of circumstances is very
unlikely. If e.g. the expected reduction in molluscs harvest due to ocean acidification could be large
enough to change prices, changes in consumer and producer surpluses have to be calculated. If the
fishermen undertake preventive measures, e.g. switching to harvesting other species that are less
sensitive to acidification, the simple multiplication approach will overestimate damage costs. Thus,
we should use approaches that consider both behavioural changes and price changes; both to the
affected good itself and to other goods,
The replacement cost method (also termed the restoration cost method) has been used to estimate
economic damages to coral reefs, by looking at the costs of establishing artificial reefs at market
prices to replace the lost reefs. However, this assumes that the replacement project offers a perfect
substitute to the lost ecosystem service. Moreover, replacement costs are just arbitrary values that
might bear little relationship to true social values. Individuals` willingness-to-pay (WTP) for the
restoration of ecosystem services may be more or less than the cost of replacement. The same is
true for the other main cost-based approach of Mitigation costs (MC) (also termed preventive costs).
MC includes costs of (theoretical) measure such as large scaling liming of the oceans to offset the
27
acidification effects (similar to efforts in the liming acidified rivers and lakes). However, these costs
could be larger or smaller than households´ WTP to avoid the impacts of ocean acidification. It is only
in the case that the marginal avertive costs are equal to the avoided damage costs of the mitigating
measures that the cost-based approach will provide the correct estimate.
The greatest advantage of these direct RP methods is that they are relatively easy to use. But as
noted earlier, the methods ignore the behavioural responses of individuals to changes in the
environmental amenities. They also obscure the distinction between benefits and costs – there is no
guarantee that people are actually willing to pay the estimated cost.
The indirect RP methods include the Travel Cost (TC) method; Averting Cost (AC) method, and the
Hedonic Price (HP) analysis. The first two methods are often involved with investigating changes in
consumption of commodities that are substitutes or complements for the environmental attribute.
The Travel Cost (TC) method, used widely to measure the demand for recreation such as going to the
beach to walk and swim, snorkelling and diving, is a prominent example. The costs of travelling to a
recreation site, together with participation rates, visitor attributes, and information about substitute
sites are used to derive a measure for the use value of the recreational activity at the site. Travel can
be used to infer the demand for recreation, only if it is a necessary part of the visit, or in economic
terms is a weak complement. TC models build on a set of strict assumptions, which are seldom
fulfilled, and the results are sensitive to the specification of the TC model, the choice of functional
forms, treatment of travel time and substitute sites etc. However, they can be relatively cheap to
perform (compared to SP methods), and give reasonably reliable estimates for use values of natural
resources (e.g. whale watching) for the current quality of a site.
Another example of the use of the household production function approach is the use of Averting
Costs (AC) (also known as defensive expenditures) to infer value. Averting inputs include buying a
small plastic swimming pool for children to avoid exposing them to potential health impacts from
polluted marine water at the beaches, and other means of mitigating personal impacts of pollution.
Such inputs substitute for changes in environmental attributes; in effect the quality of a consumer’s
personal environment is a function of the quality of the collective environment and the use of
averting inputs. We measure the value of changes in the collective environment by examining costs
incurred in using averting inputs to make the personal environment different from the collective
environment. A rational consumer will buy averting inputs to the point where the marginal rate of
substitution between purchased inputs and the collective environment equals the price ratio. By
characterizing the rate of substitution and knowing the price paid for the substitute, we can infer the
price that consumers would be willing to pay for a change in the environment.
Hedonic Price (HP) analysis refers to the estimation of implicit prices for individual attributes of a
market commodity. Some environmental goods and services can be viewed as attributes of a market
commodity, such as real property. For example, proximity of residential and holiday houses to the
ocean (i.e. ocean view, oceanscape, coastal cultural heritage etc) or proximity to polluted beaches
are purchased along with residential property. Part of the variation in property prices is due to
differences in these amenities. HP data can be quite costly to access, as there is often no database of
residential properties or cabins, which have data on all attributes, including environmental amenities
that could affect property prices. In addition the second stage of the HP analysis is often impossible
to do since we lack socio-economic data of the buyers of these properties. The HP function is very
28
sensitive to the specification and functional form, and it is often difficult to find a measure for the
environmental amenity where data exist, and which the bidders for properties can recognize
marginal changes in and have complete information about at the time they bid for the property.
While (indirect) RP methods are based on actual behaviour in a market for goods related to the
environmental good in question (and thus the value for the environmental good is elicited based on
sets of strict assumptions about this relationship), SP methods measure the value of the
environmental good in question by constructing a hypothetical market for the good. The hypothetical
nature is the main argument against SP methods. However, no strict assumptions about the
relationship between marketed complements or substitutes, or attributes of a marketed good and
the environmental good have to be made. SP methods also have the advantages of being able to
measure the Total Economic Value (TEV), including both use and non-use value (also termed passive
use value), and can measure future changes in environmental quality.
The Stated Preference methods can be divided into direct and indirect approaches. The direct
Contingent Valuation (CV) method is by far the most used method, but over the last decade the
indirect approach of Choice Experiments (CE) (Choice Modelling) has gained popularity. The main
difference between these two approaches is that while the CV method typically is a two-alternative
(referendum) approach, CE ask the respondents repeatedly to choose between two or more policies
described by different attributes/characteristics (including the costs of provision) of the
environmental good in question, and where the levels of attributes are varied across the choice sets
respondents are given.
A Contingent Valuation (CV) survey constructs scenarios that offer different possible future
government actions. Under the simplest and most commonly used CV question format, the
respondent is offered a binary choice between two alternatives, one being the status quo policy, the
other alternative policy having a cost greater than maintaining the status quo. The respondent is told
that the government will impose the stated cost (e.g. increased taxes, higher prices associated with
regulation, or user fees) if the non-status quo alternative is provided. The key elements here are that
the respondent provides a “favour/not favour answer” with respect to the alternative policy (versus
the status quo), what the alternative policy will provide, how it will be provided, and how much it will
cost, and how it will be charged for (i.e. payment vehicle), have been clearly specified. This way of
eliciting willingness-to-pay is termed binary discrete choice. An alternative elicitation method is openended questions where respondents are asked directly about the most they would be willing to pay
to get the alternative policy (with or without the visual aid of a payment card, i.e. randomly chosen
amounts ranging from zero to some expected upper amount). One of the main challenges in a CV
study is to describe the change in the environmental good and the alternative policy will provide in a
way that is understandable to the respondent and at the same time scientifically correct.
Producing a good CV survey instrument requires substantial development work; typically including
focus groups, in-depth interviews, pre-test and pilot studies to help determine how plausible and
understandable the good and scenario presented are. Translating technical material into a form
understood by the general public is often difficult. Open-ended survey questions typically elicit a
large number of so-called protest zeros and a small number of extremely high responses. In discrete
choice CV questions, econometric modelling assumptions will often influence the estimated values. A
29
careful analysis will involve a series of judgmental decisions about how to handle specific issues
involving the data, and these decisions should be clearly noted.
Among the very few CV surveys valuing biodiversity in open waters is Ressurreição et al (2011), that
estimated households´ willingness-to-pay (WTP) to avoid increased levels of species loss (10 and 25
%) in five marine taxa (mammals, fish, algae, birds and invertebrates) around the Azores archipelago.
There are more CV studies in coastal and near-shore marine ecosystems, which are reviewed and
combined in a meta-analysis by Liu and Stern (2008). They collected 39 CV studies with a total of 120
economic estimates of coastal and near-shore ecosystems. They used the resulting meta regression
for benefit transfer , and found a transfer error of 57 % , which is the same magnitude as found in
similar analyses of terrestrial ecosystems (see e.g. Lindhjem and Navrud (2008)),
Choice experiments (CEs) arose from conjoint analysis, and had been used in the fields of marketing,
transportation and psychology literature before the first application in environmental valuation in
the early 1990s. In CE respondents are asked to pick their most favoured out of a set of two or more
alternatives described as bundles of attributes. They are typically given multiple sets of choice
questions. Because CE is based on attributes, they allow the researcher to value attributes of the
environmental change as well as the overall environmental change. Furthermore, in the case of
damage to a particular attribute, compensating amounts of other goods (rather than compensation
based on money) can be calculated. An attribute-based approach is necessary to measure the type or
amount of other “goods” that are required for compensation (Adamowicz, Boxall et al. 1998). This
approach can provide substantially more information about a range of possible alternative policies as
well as reduce the sample size needed, compared to CV. However, survey design issues with the CE
approach are often much more complex due to the number of goods/attributes that must be
described and the statistical methods that must be employed.
Value transfer
The transfer of economic values of individual ecosystem services from a particular study site to
another – but similar – site (the policy site) has become a common tool to estimate the value of
natural resources. Value transfer is applied when there are not sufficient resources (time or money)
available to carry out primary valuation studies at the policy site. The values estimated for particular
ecosystem services at the original study site are applied in an area where there is a need to be
informed about the economic value of a certain ecosystem or particular ecosystem component
There are two main groups of benefit transfer techniques (Navrud 2004):
1. Unit Value Transfer
i) Simple (naïve) unit value transfer
ii) Unit value transfer with adjustments for differences in income between the study and policy
site; as we know that the ability to pay will affect the willingness to pay.
30
2. Function Transfer
i) Benefit Function Transfer, i.e. WTP as a function of income, sosio-economic characteristics of
the households, the change in quality of the environmental good etc.
ii) Meta-analysis
Simple (naïve) unit transfer (from one study or as a mean value estimate from several studies) is the
most simple approach to transferring benefit estimates from a study site (or as a mean from several
study sites) to the policy site. This approach assumes that the wellbeing experienced by an average
individual at the study site is the same as will be experienced by the average individual at the policy
site, and that the change in the ecosystem service being valued is the same at the two sites. Thus,
we can directly transfer the benefit estimate, often expressed as mean willingness-to-pay
(WTP)/household/year (or as consumer surplus per visitor day or per visitor (per year) for
recreational use values), from the study site to the policy site.
For the past few decades this procedure has routinely been used in the United States to estimate the
recreational use benefits associated with multipurpose reservoir developments and forest
management (USDA Forest Service). The selection of these unit values could be based on estimates
from only one or a few valuation studies considered being close to the policy site (both
geographically, and in terms of similarity of the characteristics of the good valued).
The obvious problem with simple unit value transfer for recreational activities is that individuals at
the policy site may not value recreational activities the same as the average individual at the study
sites. There are two principal reasons for this difference. First, people at the policy site might be
different from individuals at the study sites in terms of income, education, religion, ethnic group or
other socio-economic characteristics that affect their demand for recreation. Second, even if
individuals´ preferences for recreation at the policy and study sites were the same, the recreational
opportunities (i.e., substitute sites and activities) and the change in the good valued might not be.
Unit values for non-use values of e.g. ecosystem services from CV studies might be even more
difficult to transfer than recreational (use) values for at least two reasons. First, the unit of transfer is
more difficult to define. While the obvious choice of unit for use values are consumer surplus (CS)
per activity day, there is greater variability in reporting non-use values from CV surveys, both in
terms of WTP for whom, and for what time period. WTP is reported both per household or per
individual, and as a one-time payment, annually for a limited time period, annually for an indefinite
time, or even monthly payments. Second, the WTP is reported for one or more specified discrete
changes in ecosystem services, and not on a marginal (e.g per km2) basis. The Benefit transfer
guidelines cited below recommend using WTP/household/year as the transfer unit for non-use
values, and then aggregate over the total number of affected households to get an estimate of total
benefits. Thus, e.g. for marginal changes in marine biodiversity we would use mean /WTP/year for
Norwegian households (if there was a SP survey on this topic )of a representative sample of
Norwegian households and multiply with the number of households in Norway, given that we think
that the change in biodiversity might affect the wellbeing of all Norwegian households.
The Benefit Function Approach transfers a valuation function (e.g. WTP regressed upon income,
sosio-economic characteristics of the respondent and the quantity and/or quality of environmental
31
change values (if more than one change is valued within the valuation study) from one selected
valuation study. However, results from several valuation studies could be combined in a metaanalysis to utilize the information from several studies to estimate one common benefit function
(meta-regression). Meta-analysis has been used to synthesize research findings and improve the
quality of literature reviews of valuation studies in order to come up with adjusted unit values. In a
meta-analysis, several original studies are analysed as a group, where the estimates from each study
are treated as single observations in a regression analysis.
The meta analysis allows us to evaluate the influence of a wider range in characteristics of the
environmental good, the features of the samples used in each analysis (including characteristics of
the population affected by the change in environmental quality), and the modelling assumptions. In
practice, however, detailed characteristics of the good/study site and the population are often not
reported in the primary studies (especially not if they are published journal papers, which often focus
on methodological tests of valuation methods rather than reporting monetary estimates and the
data needed in a meta regression analysis), and it requires a large effort to find them (if at all
possible).The resulting regression equations explaining variations in unit values can then be used
together with data collected on the independent variables in the model that describes the policy site
to construct an adjusted unit value. Meta analyses typically find that differences in valuation
methodologies account for a significant part of the variation in mean willingness-to-pay across
studies sites. Thus, limiting the scope to studies using the same methodology can provide more
information about how WTP varies with characteristics of the affected households and the
environmental good in question.
There are just a few detailed guidelines on value transfer, and none addressing marine ecosystems
specifically. In the US there exist guidelines that cover the key aspects of conducting a value transfer,
notably Desvouges et al (1998) aimed at transfers for valuing environmental and health impacts of air
pollution from electricity production. More recently Bateman et al (2010) and Navrud (2007) have
constructed guidelines for value transfer of environmental goods in general in a CBA context; and
Bateman et al (2011) provide guidelines for valuing water quality improvements in lakes and rivers in
CBAs conducted in the implementation of the EU Water Framework Directive. These recent
guidelines can also be used to estimate the economic valuation of damage costs of ocean
acidification to ecosystem services for use in CBAs and other policy use. The main challenge for
applying value transfer techniques and guidelines to value impacts on marine ecosystems is,
however, the lack of original, primary valuation studies (especially of non-use values), to transfer
values from.
Scaling-up of ecosystem values
An alternative approach to transferring economic values for ecosystem services is called upscaling. In
the scaling-up exercise, economic values from a particular study site are transferred to another
geographical setting, for instance to a regional, national or global scale. Local values are thus not
applied in another local context, but are used to estimate the values of all ecosystems (or ecosystem
services) of similar characteristics in a certain region. Value transfer is usually applied on a case-by32
case basis. For instance, a cost-benefit analysis carried out for an individual marine reserve can be
transferred to a similar marine reserve.
The upscaling of economic values, on the other hand, is usually applied in more strategic policy
contexts, for example in the field of policy evaluation, and is mainly used for strategic policyplanning. While the value-transfer exercise is already complex, the scaling-up exercise is
accompanied by even more complexity, methodological difficulties and uncertainty. The word
“upscaling” already reveals that (spatial) scale is a vital element of the method.
Spatial scale is recognized as an important issue to the valuation of ecosystem services (Hein, van
Koppen et al. 2006). The spatial scales at which ecosystem services are supplied and demanded
contribute to the complexity of ecosystem valuation and management. On the supply-side,
ecosystems themselves vary in spatial scale (e.g. small individual patches, large continuous areas,
regional networks) and provide services at varying spatial scales. The services that ecosystems
provide can be both on and off-site. For example, oceans might provide recreational opportunities
(on-site), and climate regulation (global off-site). On the demand-side, beneficiaries of ecosystem
services also vary in terms of their locational distribution. The spatial scale over which ecosystem
services are provided and received is determined by the spatial scale over which an ecosystem
function has effect and the spatial scale of (potential) beneficiaries. For conceptualising the
relationship between the supply and demand of ecosystem services one might imagine two overlaid
maps – one representing the spatial extents of an ecosystem and the (potential) services it provides,
and the other representing the spatial location of the (potential) beneficiaries of these services
Ecosystem services often have different groups of beneficiaries (different in terms of spatial location
and socio-economic characteristics). For example, the provision of recreational opportunities by an
ecosystem will generally only benefit people in the immediate vicinity, whereas the existence of a
high level of biodiversity may be valued by people at a much larger spatial scale. Differences in the
size and characteristics of groups of beneficiaries per ecosystem service need to be taken into
account in aggregating values for each service. The management of ecosystems may be further
complicated in cases where the interests of different groups of beneficiaries (possibly at different
spatial scales) are in conflict. This may occur when ecosystem services are mutually exclusive, e.g.
commercial fishing such as bottom trawling in areas with cold water corals, and the establishment of
marine parks to preserve exactly the same resource.
The values held by beneficiaries for ecosystem services may vary with a number of different factors
that can be spatially defined (distance, availability of substitute and complementary sites, income,
culture, and preferences). Direct use values are generally expected to decline with distance to an
ecosystem – so called distance decay. Non-use values may also decline with distance between the
ecosystem and beneficiary, although this relationship may be less related to distance than to cultural
or political boundaries. The availability of substitute (complementary) sites within the vicinity of a
selected ecosystem is expected to reduce (increase) the value of ecosystem services from that
ecosystem. Socio-economic characteristics of beneficiaries (e.g. income, culture, and preferences)
are not spatial variables per se, but differences in these variables between (groups of) beneficiaries
can often be usefully defined in a spatial manner (e.g. by administrative area, region or country).
Consideration of the spatial scale of the provision and beneficiaries of ecosystem services is
important for the calculation of the TEV of these services (i.e. the aggregation of values across
33
relevant areas and populations). In addition, accounting for spatial scale may be of further use in the
formulation of policies to manage ecosystem services, for example in the identification of winners
and losers, the need for compensation/incentives, and the design of policies such as payments for
environmental services.
Regarding the estimation of ecosystem service values, there are a number of important issues to be
considered related to spatial scale. In discussing these scale related issues we make a distinction
between the estimation of values for an individual ecosystem site and for the entire stock of an
ecosystem within a large geographic area. We refer to the latter case as ‘scaling-up’ ecosystem
values when insufficiency of data requires applying value transfer methods.
At the level of an individual ecosystem site, unit values for ecosystem services are likely to vary with
the characteristics of the ecosystem site (area, integrity, and type of ecosystem), beneficiaries
(number, income, preferences), and context (availability of substitute and complementary sites and
services). All of these variables have a spatial dimension that can be accounted for in estimating sitespecific values. For example, in terms of ecosystem area, many ecosystem service values have been
observed to exhibit diminishing returns to scale (i.e. adding an additional unit of area to a large
ecosystem increases the total value of ecosystem services less than an additional unit of area to a
smaller ecosystem). It is therefore important to account for the size of the ecosystem being valued.
For scaling-up ecosystem values to estimate the total economic value of the stock of ecosystems in a
large geographic area, in addition to controlling for other spatial variables, it is necessary to account
for the non-constancy of marginal values across the stock of an ecosystem. This consideration is also
important for valuing large-scale changes to the stock of ecosystems. At the margin, a small change
in ecosystem service provision (e.g. the loss of a small area) will not affect the value of services from
other ecosystem sites. Non-marginal changes in ecosystem service provision, however, will affect the
value of services from the remaining stock of ecosystems. As the ecosystem service becomes scarcer,
its marginal and average values will tend to increase. This means that simply multiplying a constant
per unit value by the total quantity of ecosystem service provision is likely to underestimate total
value. Appropriate adjustments to marginal values to account for large-scale changes in ecosystem
service provision need to be made.
For an example of a meta-analytic benefit transfer and scaling-up exercise utilizing GIS ; see Brander,
Bräuer et al. (2012) that value impacts of climate change on European wetland ecosystem services.
Discounting
The impacts of ocean acidification are not momentary, and thus there is a need to aggregate the
costs of the expected impacts over time. This is the present value of the impacts over time,
discounted at the social discount rate d. The social discount rate is the economic measure of how
timing affects values (Birol, Koundouri et al. 2010). Large impacts will often occur far into the future
and are usually assumed to be less likely to occur than smaller impacts. This is why disasters must be
discounted in both time and probability.
34
Standard models for economic growth often assume a constant and positive social discount rate
(Groom, Hepburn et al. 2005). Though a constant discount rate is in many ways an attractive trait, it
also results in present and future generations being valued in a very different way. Ocean
acidification can e.g. produce impacts that occur in the distant future. A positive constant discount
rate takes less account of future generations' welfare than present generations’ welfare and causes
an exponentially decreasing emphasis on the future. By using a positive discount rate, large losses
happening in the future will be discounted to minor present values. This could be a problem in terms
of the principle of sustainable development in today’s policy making. One possible alternative could
be to not use any discount rate at all (Li and Lofgren 2000). This will however lead to the problem of
today’s generation having to forfeit consumption for the welfare of future, presumably more wealthy
and technologically, advanced generations. Furthermore, there are so many future generations, that
saving today will not make much difference in the welfare for future generations in general. The
world’s low income countries will also be hard hit by the decline in income. There are therefore a
multitude of ethical aspects surrounding the use of a zero discount rate, that many do not find
acceptable (Groom, Hepburn et al. 2005).
Hyperbolic discounting could be a possible solution to this problem. Experimental work by both
psychologists and economists on individual choice has revealed that individuals discount the future
at a declining rate that follows a hyperbolic path (see e.g. Karp (2005) and Weitzman (2001)). This
means that events in the distant future will be strongly emphasized. Hyperbolic discount models
have in common that they provide the decision maker with the ability to distinguish between events
in the near and distant future. This is very relevant when we talk about long term environmental
problems such as ocean acidification. Hyperbolic discounting cannot be found in the
recommendations for Cost Benefit Analysis (CBA) in Norway (Anon 2005), but is included in e.g. the
CBA guidelines for projects in the United Kingdom
In the application in this study we will stick to a positive social discount rate, but will use different
rates in order to illustrate how sensitive the economic losses are to changes in the discount rate. We
also use a zero discount rate to visualise the effects of discounting (versus just adding up annual
values to a present value in the case of the zero discount rate).
Natural resource management
Bioeconomic models of natural resource management are a tool with which to study optimal
adaptation or management in the face of ocean acidification. Bioeconomic models consist of a
biological and economic model connected via a management option (see Figure 6), often consisting
of either open access to the resource in question, or some optimal management, rendering different
results with regards to harvests, effort input and resource stocks.
35
Ecological model
Management options
Results
Economic model
Figure 6. The bioeconomic model.
With reference to the marine environment, bioeconomic models of fisheries have been developed
since the seminal work of Scott Gordon (1954), to identify optimal management options for the
interaction between fishing activity and a targeted fish stock. Though fish are only one of the many
services provided by marine ecosystems, we will concentrate on fisheries models, as these are the
most developed bioeconomic models for marine environments. The fisheries models have also been
expanded from single stock models to include other related fish stocks, such as predator, prey or
bycatch species (Flaaten 1988; Eide and Flaaten 1998), as well as marine habitats (Barbier and Strand
1998; Foley, Kahui et al. 2010) and other recreational activities (Boncoeur, Alban et al. 2002). These
models may well be relevant for study, as ocean acidification may affect a broad specter of species,
habitats and services.
Exogenous environmental effects in fisheries models
Most bioeconomic fisheries models focus on endogenous environmental effects, i.e. how fisheries
affect either the target or bycatch species, or habitats. When it comes to ocean acidification,
however, exogenous environmental effects are the most relevant. A number of studies have focused
on different environmental effects outside, or exogenous to the model at hand. An early study was
carried out by Bell (1972), who presents a bioeconomic model including a habitat variable, namely
water temperature, in an empirical model of a fishery. Ellis and Fischer (1987) present a standard
Cobb-Douglas harvesting function which depends on effort and environmental quality, rather than
the usual stock size. Effort is the control variable, while environmental quality is exogenously
determined. Kahn (1987) studies how an exogenous environmental quality, which influences the
intrinsic growth rate or the carrying capacity of a target species, affects optimal strategies. Schnier
(2005) expands upon this approach allowing the intrinsic growth rate and the carrying capacity to
vary over a distribution. Smith (2007) studies the North Carolina blue crab fishery using a
bioeconomic model that includes spatially differentiated exogenous nutrient loading, entering
indirectly through growth. Freeman (1991) introduces environmental quality into the cost function of
harvesting as well as the growth function of the resource in question, hence combining the Ellis and
Fischer (1987) and the Kahn (1987) approaches, and setting it in a dynamic model. Mikkelsen (2007)
presents an interaction between aquaculture and fisheries, where aquaculture affects fisheries
through the intrinsic growth, the carrying capacity or the catchability of the wild fish stock in
question. Again, aquaculture effort is exogenous in this model also.
36
The above mentioned models are largely theoretical or conceptual models designed to visualise
management issues connected to natural resource utilisation affected by some exogenous change.
These models, or versions of them, are possible approaches to understanding how ocean
acidification may affect ecosystem services and their use, and how management behaviour or
incentive structures may be applied to ensure optimal utilisation.
Norwegian marine ecosystem goods and services at risk from ocean
acidification3 - a back-of-the-envelope estimation
For Norway all ecosystem goods and services described in the sections above can be
affected by ocean acidification. To quantify the economic impact it is necessary to first
translate biological and scientific findings into impact scenarios which lends themselves to
economic valuation. Second one must assign values to the ecosystem goods and services
using the methods described in the “Valuation” section. Thus changes due to ocean
acidification can be expressed in monetary values.
The following chapter is a first, back-of-the-envelope attempt to economically assess the
impacts of ocean acidification for Norway. Due to the high uncertainties concerning future
development of CO2 emissions, biological and scientific impacts, but also concerning the
values of goods and services, we limit our analyses to a time period of 100 years: from 2010
to 2110. From biological and scientific findings we first develop impact scenarios for the
identified services, translate them into economic scenarios and set the economic “boundary
conditions” prior to modelling the impact. Clearly our findings are highly uncertain, but
nonetheless provide an order-of-magnitude estimate of possible economic impacts of ocean
acidification.
Impact scenarios for ocean acidification
To assess the economic impact of ocean acidification, it is important to determine how an impact
occurs and at what intensity. In this chapter we therefore develop impact scenarios, which can be
used in our economic analysis. As the intensity of the impact depends on the degree of acidification
and thus CO2 emissions, we focus only on the actual projections of IPCC, which predict an ocean pH
between 7.7 and 7.9 by 2100 (IPCC 2007). For the creation of scenarios we consider studies with a pH
in this range, i.e. CO2 concentrations lower than 2000 ppmv pCO2 or pH reductions less than 0.5 pH
units.
3
This chapter contains parts of a draft version of a paper on the economic assessment of ocean acidification for
Norway, forthcoming in 2012. For more please contact the authors.
37
Impact scenarios of provisioning services
Due to the current state of knowledge we can only develop impact scenarios for the provisioning
services of fisheries and aquaculture. As there are many studies on the impacts of acidified
conditions at a single organism level, we use the results of meta-studies to create more general
scenarios. Kroeker, Kordas et al. (2010) and Hendriks, Duarte et al. (2010) performed meta-studies on
the impact of ocean acidification on a broad range of marine organisms. Both meta-analyses checked
the impact of ocean acidification on different taxonomic groups and life-stages of these organisms
(larvae, juvenile, adult) and studied parameters such as survival, calcification, growth, metabolism,
fertility and photosynthesis. We apply their results only when three or more experimental values are
used within their meta-analysis. Selected and aggregated results of both meta-analyses are
presented in Table 2. Kroeker, Kordas et al. (2010) converted the results from the single studies into
natural log-transformed response ratios: LNRR = ln(effect in experiment group) – ln(effect in control
group).We reconverted them to derive the percentage values for the observed changes.
Effects are reported on individual, i.e. at the single organism level, but we assume that these effects
are the same for the whole population. We do not consider further effects on population dynamics.
Impacts at the ecosystem level are also omitted, as there are not enough studies scaling from
physiology to ecosystem effects (Le Quesne and Pinnegar 2011).
To acknowledge the variation in the results, we created best and worst case impact scenarios (see
Table 2). For the best case scenario we picked the most optimistic observation, while for the worst
case the most pessimistic observation was chosen. If several effects were reported we considered
them all assuming that they would multiply. Decreases are denoted negative, increases positive. For
provisioning services all changes in catch weight due to ocean acidification were calculated using the
following formula: new catch weight = old catch weight * (1+growth) * (1+survival). The impact itself
is the difference between the old catch weight and the new catch weight or in economic terms the
difference in catch value.
As the reported effects in the meta-studies apply for future pH-values, we assume that the impacts
increase over the 100 year time period. This means that there is no impact in 2010, our starting
point, and the values given in Table 2 reflect the impact in the year 2110. The increase of impact
differs from species to species, but Doney, Fabry et al. (2009) found predominantly a linear response
for some major groups of marine biota. Thus we assume a linear response for all species in our
model, even though Doney, Fabry et al. (2009) provide no results for fish and crustaceans.
Furthermore we assume that the impact is the same along the whole Norwegian coastline,
disregarding possible regional variations.
38
Table 2. Selected and aggregated results of the meta-analysis of (1) Hendriks, Duarte et al. (2010)
and (2) Kroeker, Kordas et al. (2010)
Organisms:
Contribute to:
Crustaceans (lobster, crab, krill, etc.)
Survival
Growth
Calcification
Provisioning services
26.55% reduction – 5.58% increase (2)
2.64% reduction – 17.64% increase (2)
0.60% – 34.81% increase* (2)
Fish
Growth
Provisioning services
1.84%-18.35% increase* (2)
Phytoplankton (including coccolithophores,
cyanobacteria, calcifying algae)
Growth
Supporting services
Fleshy algae
Growth
Supporting services
2.84% – 65.78% increase* (2)
Zooplankton (including sea urchin embryos,
copepods larvae, echinoderm larvae and
mollusk larvae)
Survival
Fertility
Growth
Supporting services
Seagrass
Growth
Photosynthesis
Supporting services
32-62% increase (1)
15.28% reduction – 18.58% increase (2)
Corals 2)
Growth
Calcification
Supporting and cultural services
5.76 – 69.91% reduction* (2)
8-36% reduction (1)
16.85 – 54.00% reduction* (2)
Bivalves/Mollusks
Survival
Growth
Calcification
Provisioning services
59.44% reduction - 2.7% increase (2)
39.49% reduction – 18.79% increase (2)
32-46% reduction (1)
66.38% reduction – 3.67% increase (2)
8% reduction - 28% increase (1)
87.85% reduction* – 6.65% increase (2)
6-18% reduction 1) (1)
6-12% reduction 1) (1)
13-19% reduction (1)
1)
These numbers are given for adult sea urchin. They were included because the number of adult sea
urchins determines the number of sea urchin embryos afterwards.
2)
Increased photosynthesis found in corals will be neglected as for Norway only cold-water corals are
relevant and these do not have symbiotic algae;
* denotes significant results in these studies.
39
Table 3. Economic impact scenarios for different categories of ecosystem services, separated in
best and worst case scenarios. Assumptions for modeling concerning the effect over 100 years and
the economic impact are given in italics (C is carbon).
Ecosystem service
Provisioning services
Oil and gas extraction
Waste disposal
Fisheries &
Aquaculture
Regulating services
Oceanic carbon
storage
Other biogeochemical cycles
Noise absorption
Cultural services
Supporting services
Food-web
Habitat
Impact Scenario
Best case
Worst case
Marginal impacts expected, lack of detailed data and knowledge gaps
No scenario, due to knowledge gaps
Effect over 100 years: linear
Economic impact: difference in catch value
Fish:
Fish:
18.35% increase in growth, no
1.84% increase in growth, no changes
changes in survival
in survival
Bivalves/Mollusks:
Bivalves/Mollusks:
2.7% increase in survival and
59.44% reduction in survival and
18.79 % increase in growth
39.49% reduction in growth
Crustaceans:
Crustaceans:
5.58% increase in survival and
26.55% reduction in survival and
17.64% increase in growth
2.64% reduction in growth
Effect over 100 years: best case: constant, worst case: linear
economic impact: marginal damage costs for the C not taken up in
Norwegian waters
C storage decrease of 0.56 g C m-2 C storage decrease of 0.56 to 1.44 g C
a-1
m-2 a-1
No scenario, due to knowledge gaps
No scenario, due to knowledge gaps
Marginal impact, disregarded
No scenario, due to knowledge gaps
No scenario; positive (sea grass) and negative (cold water corals) impacts
reported, overall effect can currently not be estimated.
Impact scenarios of regulating services
Regulating services which might be impacted by ocean acidification were identified to be natural
carbon storage, biogeochemical cycles and noise absorption. For noise absorption and biogechemical
cycles excepting carbon, the current state of knowledge is not sufficient to derive impact scenarios.
40
For the impact scenarios we assume that carbon chemistry, i.e. ocean acidification, accounts for
4.76% of the observed decrease in carbon storage in the North Atlantic in the initial year. For the
future in the best case this ratio will be constant, whereas for the worst case this ratio will increase
linearly up to 10% by 2110. This is reasonable as the IPCC scenarios A1B, A1Fl, and A2 predict CO2
concentrations over 750ppm by 2100, whereas the other scenarios predict lower values (IPCC 2007).
Additionally, in the best case scenario we apply the given decreases minus standard deviation and for
the worst case plus standard deviation. Furthermore, it is assumed that the same rate of reduction
applies for the whole Norwegian coastal area. To derive results for Norway we used the Norwegian
Exclusive Economic zone as the relevant coastal area, encompassing 819628 km2.
Impact scenarios of cultural services
Cultural services of economic relevance which are endangered by ocean acidification are mainly
linked to future tourism such as e.g. submarine trips for cold water corals. So far the only known cold
water coral reef at a reasonably i.e. diveable depth is the reef in the Trondheim fjord. All other
known reefs are too deep for tourism activities other than potential submarine tours. We therefore
disregard the impact of ocean acidification on cultural services.
Impact scenarios of supporting services
The foodweb and habitat services were identified as important supporting services that will be
affected by ocean acidification. Due to the fact that the impacts of supporting services on people are
indirect, it is necessary for an economic impact assessment to quantify the impact via the other
service categories. So even though it is possible to calculate the decline in coral habitats in area and
volume, it is not possible to create an economic impact scenario as quantitative information on how
these changes affect other categories of services is missing.
Economic approach and applied data
To assess the economic costs of ocean acidification for Norway, we use the impact scenarios as
described in Table 3. The social discount rate often plays a crucial role in economic analyses. In order
to illustrate the sensitivity of our results to the choice of the social discount rate we calculate the
present value (PV) for discount rates of 0%, 2% and 4% (which is the same approach as taken by
Cooley and Doney (2009)). As opposed to Narita, Rehdanz et al. (Forthcoming), we did not consider
price changes due to supply changes, but assumed that prices would not be affected by ocean
acidification. Thus, we assume constant prices (in 2010-NOK) over time in the PV calculations.
Calculations are done with GNU Octave, version 3.2.4 and Excel 2010.
41
Provisioning services
Data for fish and aquaculture catch volumes and first hand sale profits were obtained from the
Norwegian Directorate of Fisheries (Fiskeridirektoratet). Our data covers 48 species, 39 were
classified as fish, five as crustaceans and four as molluscs and bivalves (Table 4). For most species,
data was available from 2001 to 2010, while for some species the time series were shorter. In
comparison to the studies of Cooley and Doney (2009) and Narita, Rehdanz et al. (Forthcoming), we
did not use calcification as a proxy for changes in catch decrease. We could not find data on how
catch volumes are influenced by calcification rates, whereas growth and survival are directly linked to
catch volumes.
Catch volumes for different species varied considerably over the last 10 years, so we calculated the
average, as well as the 5-percentile and the 95-percentile to reflect good, bad and average fishing
years in our economic analysis. From the catch volumes and sales revenues we calculated the annual
prices and normalized them to the year 2010 using the Norwegian consumer price index (derived
from Statistics Norway). A look at the price development over the last 10 years reveals different
trends for different species. But the price changes from year to year are very small for most species.
The average annual price change lies between -2.7% and +2.6%, with the exception of lobster, sole,
oysters from aquaculture and the category “other unspecified fish” (Table 4). Due to the minor
changes in price and the lack of a clear price trend, we decided to keep all prices (in real terms)
constant over the whole period of 100 years. The economic impact per year is then calculated as the
difference between the sale profit for 2010 and the year under consideration, taking into account
different discount rates, as mentioned before.
42
Table 4. Price development, average annual price change and average prices for relevant species. All prices are
converted to 2010-NOK using the Norwegian consumer price index obtained by Statistics Norway (Statistics Norway
www.ssb.no)
Regulating services
Using the Norwegian Exclusive Economic Zone as the relevant coastal area, the annual carbon uptake
is reduced by 6,884,875 and 8,261,850 tons carbon in the best case and worst case, respectively. In
order to estimate the economic loss due to reduced carbon uptake in the ocean we use unit
estimates of marginal damage costs from these carbon emissions that are now not captured by the
43
oceans. Tol (2008) performed a meta-analysis of 211 estimates of marginal damage costs of carbon
emissions (also termed “the Social Cost of Carbon” (SCC)). From Tol (2008) we use the median SCC
estimate from peer-reviewed papers, fitted to a Fisher-Tippet distribution. This distribution reflects
the uncertainty of the sample, which was right-skewed and fat-tailed. By using only the results from
peer-reviewed papers, the estimates are presumably more conservative, as the SCC estimates in
peer-reviewed papers were lower and less uncertain than in the grey literature (Tol 2008). The
median is also a more stable estimate than mean for skewed distributions. SCC-estimates were
provided in 1995 USD per ton carbon. These estimates were adjusted to 2010-NOK using the US
consumer price index from the U.S. Department of Labor 4 and an average daily currency conversion
rate for 2001-2010 from Norway´s central bank 5. Tol (2008) reported a median marginal damage
costs (SCC) of 48 1995- USD per ton carbon, which is equivalent to 463 2010-NOK)
Results
Provisioning services
The present value of the aggregated economic loss in the provisioning services due to ocean
acidification for the period 2011 to 2110, for average prices and catch volumes, using a social
discount rate of 4%, is positive for the best and negative for the worst case scenarios (see Table 5).
Splitting the result for the worst case scenario into different species shows that the impacts of ocean
acidification on mollusks/bivalves and crustaceans are negative, while the effect on fish is positive.
The application of different discount rates shows, as expected, a decrease in the economic loss with
increasing discount rate (see Table 5). Both for the best and worst case scenarios the present value
of the economic impact at a discount rate of 0% (which means just adding up the annual impacts
over this 100 year time period) is eight to nine times higher, than at a discount rate of 4%.
4
5
See: ftp://ftp.bls.gov/pub/special.requests/cpi/cpiai.txt
See: http://www.norges-bank.no/valuta/usd/
44
Table 5. Aggregate economic loss (present value) in provisioning services for the 100 years period
(2010-2110), calculated using average prices and catch volumes and different discount rates (d). All
numbers are stated in million 2010-NOK
Input data
d=0%
d=2%
d=4%
Species
Best case
Total (all species) and for different groups of species at d=4%
Total (all species)
12213
fish
11003
mollusks/bivalves
34
crustaceans
1176
Total (all species) for different discount rates; d = 0, 2 and 4 %
Total (all species)
105059
Total (all species)
31353
Total (all species)
12213
Worst case
-475
1103
-140
-1437
-3926
-1195
-475
Table 6. Annual economic loss (annual discounted value) in provisioning services for selected years
(2011, 2060 and 2110); calculated using average catch volumes and average prices in the selected
years and applying different discount rates (d = 0 % and 4 %). All numbers are stated in million
2010-NOK.
Input data
year 2011
year 2060
year 2110
year 2011
year 2060
year 2110
Species
d=0%
Total (all species)
Total (all species)
Total (all species)
d=4%
Total (all species)
Total (all species)
Total (all species)
Best case
Worst case
21
1039
2080
-1
-40
-74
20
146
41
-1
-6
-1
Table 6 presents and compares the annual economic impacts (annual discounted value) for the
individual years 2011, 2060 and 2110 using a discount rate of 0% (which means no discounting) and
4%. Compared to zero, using a discount rate of 4% (which is the social discount rate recommended
by the Ministry of Finance (2005) for project with low systematic risk) results in an increase of the
annual economic loss from 2011 to 2060, and thereafter a decrease in the annual loss. These
variations indicate that the model results are at different times driven by different factors, where the
biological factors dominate in the near future before the effect of discounting sets in.
45
Regulating services
For Norway as well as for all countries emitting CO2 or bearing the consequences of elevated
atmospheric CO2 levels, oceanic carbon storage is a relevant ecosystem service, which we estimate
the value of here.
For natural carbon storage comparative measurements in 1994/1995 and 2002-2004 found an
average yearly decrease in CO2 uptake of 1.1 ± 0.1 mol m-2 a-1 in the North Atlantic between 20oN and
65oN (Schuster and Watson 2007). While Yi, Gong et al. (2001) argue that the ocean carbonate
chemistry is insensitive to global temperature and CO2 uptake and reduction is mainly due to changes
in carbonate chemistry, Schuster and Watson (2007) argue that carbonate chemistry is of minor
importance. They accounted for 30% of this decrease in temperate/subpolar regions to the rise of
sea surface temperature and another – not quantified – big part to changes in ventilation. At
constant alkalinity they calculated a change in the Revelle factor of 5% due to their observations. The
Revelle factor is a measure of the resistance to atmospheric carbon dioxide being absorbed by the
ocean surface layer posed by bicarbonate chemistry. This means a decrease in seawater buffer
capacity of 4.76%. Other studies state that the relative CO2 storage capacity, i.e. the proportion of
human CO2 emissions taken up by the oceans relative to the total human CO2 emissions, is expected
to decrease by a few percentage points at atmospheric CO2 levels of 450 ppm and around 10% at 750
ppm (WBGU 2006).
For our impact scenarios we assume that carbon chemistry, i.e. ocean acidification, accounts for
4,76% of the observed decrease in carbon storage in the North Atlantic (Schuster and Watson 2007)
in the start year. For the future in the best case, this ratio will be constant, whereas for the worst
case this ratio will linearly increase up to 10% by 2110. This is reasonable as the IPCC scenarios A1B,
A1Fl, A2 predict CO2 concentrations by 2100 over 750ppm whereas the other scenarios predict lower
values (IPCC 2007). Additionally, for the best case scenario we apply the given decreases minus
standard deviation and for the worst case plus standard deviation. Furthermore we assume that the
reduction rates apply with the same strength for the whole Norwegian coastal area.
To derive results for Norway we used the Norwegian economic zone as the relevant coastal area,
encompassing 819628 km2. Hence, the annual C uptake reduction increases by 6884875 tons C in the
best case and 8261850 in the worst case. In order to determine the economic aspects, we have to
assign a value to the C not absorbed by the ocean. Tol (2008) combined 211 estimates of the social
costs of C emissions (marginal damage costs) in a meta-analysis. From Tol’s study we use the median
cost-estimates from peer-reviewed papers, fitted to a Fisher-Tippet distribution. This distribution
reflects the uncertainty of the sample, which was right-skewed and fat-tailed. By using only the
results from peer-reviewed papers, we presumably get more conservative estimates, as the costestimates in peer-reviewed papers were lower and less uncertain than in the grey literature (Tol
2008), and the median is a more stable estimate of skewed distributions. Cost-estimates were given
as 1995 USD per ton carbon, and these were adjusted to 2010 NOK using the US consumer price
index from the U.S. Department of Labor 6 and an average daily currency conversion rate for 20016
See: ftp://ftp.bls.gov/pub/special.requests/cpi/cpiai.txt
46
2010 from the Norwegian Central Bank 7. Tol (2008) reported median marginal damage costs of 48
USD per ton carbon, which means 463.22 NOK for the year 2010.
For regulating services the resulting total damage costs over a 100 year time-period are
approximately a factor of 2 higher for the worst case compared to the best case scenario (Table 7).
We observe that these costs are several orders of magnitude greater than the fisheries and
aquaculture costs described above.
Table 7. Aggregate economic loss (present value) from reduced Carbon uptake in Norwegian
waters for the 100 year period 2010-2110 based on average prices and catch volumes and different
discount rates (d). All numbers are given in billion 2010-NOK
Discount rate
0%
2%
4%
Best case
-1095
-327
-127
Worst case
-2284
-629
-224
Knowledge gaps
Natural science knowledge concerning ocean acidification is, despite rapid increase in published
papers the last decade, still in its infancy as regards solid knowledge of effects. Disagreements within
the scientific community as to the vulnerability of e.g. marine biodiversity (Dupont, Dorey et al. 2010;
Hendriks and Duarte 2010; Hendriks, Duarte et al. 2010) and the effects on for instance fisheries (Le
Quesne and Pinnegar 2011) are rife. Conclusions in the literature are relatively careful, stating that
ocean acidification will “probably bring about reductions in biodiversity” (Hall-Spencer et al., 2008
p.99), and admit that on the ecosystem modelling level “existing tools are limited in their utility for
policy, eco- or earth-system questions” (Blackford 2010). A detailed overview over current natural
science knowledge gaps can be found in Kleypas, Feely et al. (2006).
It is important to note that the natural science knowledge gaps are related to reactions of organisms,
populations and ecosystems with regards to ocean acidification (see what is coined Level 1 in Figure
7), as services emanate from all these entities (coined Level 2 in Figure 7), as well as regarding the
links between them. Furthermore, how and to what degree the changes that ocean acidification has
7
See: http://www.norges-bank.no/valuta/usd/
47
upon these entities translates into changes in services, is only known for some services. This is also
the case for values (Level 3 in Figure 7).
Clearly, there are large natural science knowledge gaps that need filling in order to be able to carry
out robust and sound social science research regarding ocean acidification. However, regarding
values there are also a number of economic method knowledge gaps that we will discuss below.
Figure 7. Ocean acidification and its effects at different levels. Level 1: the natural environment, Level 2; ecosystem
services, Level 3; values. Based on Le Quesne and Pinnegar (2011).
Table 8. Ocean Acidification and knowledge gaps pertaining to Ecology, Ecosystem services and Valuation
Level:
Knowledge gaps:
1. Ocean acidification
itself
2. Ecology
Local and regional variations in acidification conditions
Future emission trends and CO2 uptake of the oceans
OA effects on organisms (including genes and molecules),
populations and ecosystems
Combined effects of OA with other effects e.g. overfishing, habitat
destruction
Adaptation capacity to OA
Which services are provided
How are these services affected by OA
How do services translate into values
How do we carry out valuation, especially in relation to uncertainties
How to model ocean acidification in bioeconomic models
3. Services
4. Valuation/Management
48
As shown in Table 8, the translation from services to values must be made. I.e. what kind of values
do we find in a specific service from the sea? Clearly there may be many different types of values
emanating from a single service, i.e. both use and non-use values, and how is a marginal change in
the service measured in value terms.
Regarding the third level in Table 8, value, there are a few issues connected to marine environments
related to the effects of ocean acidification on marine services that require special attention:
i)
Incomplete knowledge of marine environments amongst scientists
ii) Uncertainty of effects of ocean acidification
iii) Lack of knowledge of marine environments amongst the general public
iv) Limited knowledge of future services from marine environments
The issues in i)-iv) underline the problems of valuation under uncertainty, both regarding the
situation, the change at hand, as well as the future. I.e. there are uncertainties both on Level 1 and 2
in Figure 7, which again creates problems for the level 3 valuation. Regarding Level 2, there is
uncertainty both in relation to the current services as well as potential future services, regardless of
the change that may occur as a result of ocean acidification. For instance, the cultural values
connected to the ocean, such as the so called Legacy of nature, are not well known, and the methods
for their elicitation not well developed.
These issues complicate valuation considerably, as we are both speaking of uncertainty related to
direct use values, as well as option values, and potentially also quasi option values. Regarding option
and quasi option values, there is currently very little research, requiring a development of the survey
methods in order to carry out valuation of these entities.
In a general setting, there are also some issues that relate to both the ecological and the economic
levels. These are a) Scaling issues - how to transform individual physiological effects to stocks, food
webs and ecosystems, and how to scale up values from one geographical setting to a regional,
national or global setting, and b) Substitution or transforming from the first best situation to the
second best situation - e.g. how fish substitute one prey type that is affected by ocean acidification
for another that is not, and what this substitution costs in the form of reduced growth. And
furthermore, how do humans substitute goods and services that are affected by ocean acidification?
And who can fill the different knowledge gaps depicted in Table 8? Ecological knowledge gaps are
naturally filled by natural scientists, while the knowledge gaps related to valuation require economic
knowhow. The knowledge gaps in relation to the ecosystem services themselves are more multi- or
interdisciplinary in nature, requiring both social and natural science input. As mentioned, there are
ecological knowledge gaps that must be filled in order for it to be possible to carry out valuation.
However, though this research requires natural science knowhow, the identification of the necessary
issues that must be better understood, e.g. the damage functions of ocean acidification may also
require collaboration between natural and social scientists, underlining the need for interdisciplinary
approaches to research on ocean acidification.
49
Finally, relating back to the issue of mitigation and adaptation/management in the face of ocean
acidification, as described in
Figure 2, the application of ocean acidification in bioeconomic management models is non-existent.
Though mitigation may be not be very relevant, how to optimally adapt or manage human behaviour
in the face ocean acidification may become highly relevant . Clearly, as presented earlier, there are
many models upon which to develop the specificities of ocean acidification further, enabling the
filling of this knowledge gap an exercise of model development.
Some concluding remarks
This study focuses on the broad economic issues connected to ocean acidification, the frameworks
within which to study the issue, the relevant ecosystem services, the impacts of ocean acidification
upon these services, and the methods with which to assess the costs or revenues connected to these
impacts. In a back-of-the-envelope estimation of the costs and benefits of ocean acidification in
Norwegian waters, some provisioning and regulating services are assessed.
As regards provisioning services, our analysis regarding the ocean acidification in Norwegian waters
includes both positive and negative consequences as opposed to the purely negative focus in the
literature to date. This may clearly be controversial, but recent publications have pointed to the
potential for over-dramatization of the negative consequences of ocean acidification (Hendriks and
Duarte 2010; Hendriks, Duarte et al. 2010; Le Quesne and Pinnegar 2011). Furthermore, our both
positive and negative effects of ocean acidification are solidly based on the meta-analyses in the
literature to date (Hendriks, Duarte et al. 2010; Kroeker, Kordas et al. 2010). However, if we focus on
the negative effects of ocean acidification in our results, they show effects on provisioning services in
the same range as that of Cooley and Doney (2009) and Narita, Rehdanz et al. (Forthcoming), when it
comes to mollusk costs as a percentage of GDP.
Our analysis shows that the costs connected to ocean acidification with respect to regulating services
may be substantial, and several orders of magnitude greater than that of the provisioning services of
fisheries and aquaculture.
The main limitation connected to these results is due to the current state of knowledge disallowing
all ecosystem services to be considered. Hence, the picture is not complete, despite more services
being included here than in previous studies.
It is also worth noting that the developed scenarios are substantial simplifications and abstractions of
reality. They do not consider that e.g. single species might be completely eradicated by ocean
acidification (Dupont 2008), that the impacts of ocean acidification may be non-linear, i.e. the system
may abruptly transform above a certain threshold (Kroeker, Micheli et al. 2011) or that there are
feedback-loops in the systems, e.g. that ocean acidification decreases oceanic CO2 uptake, which in
turn lowers the process of acidification. Furthermore, our assumptions draw a line directly from
biological effects to changes in harvest volumes and revenues, which clearly is a simplification (Le
Quesne and Pinnegar 2011). But here again, current knowledge gaps limit the development of better
scenarios.
50
Clearly the knowledge gaps regarding ocean acidification are deep and wide. The limited natural
science knowledge results in further uncertainties which spill over into the economic valuation of
these uncertain impacts. This is nonetheless no excuse for not carrying out economic and social
science research on ocean acidification. On the contrary, the existing knowledge gaps make it even
more important to know how to apply this knowledge in social and economic contexts, once it
becomes available, as also within economics and the social sciences there is a need to develop
methods in order to assess consequences of ocean acidification.
51
References
Adamowicz, W., P. Boxall, et al. (1998). "Stated preference approaches for measuring passive use
values: choice experiments and contingent valuation." American Journal of Agricultural
Economics 80: 65-75.
Andersson, A., F. Mackenzie, et al. (2008). "Life on the margin: implications of ocean acification on
Mg-calcite, high latitude and cold-water marine calcifiers." Marine Ecology Progress Series
373: 265-273.
Anon (2005). Guidelines for Cost Benefit Analysis (in Norwegian; Veileder i samfunnsøkonomiske
analyser), The Minstry of Finance, Norway.
Ardelan, M. V., E. Steinnes, et al. (2009). "Effects of experimental CO(2) leakage on solubility and
transport of seven trace metals in seawater and sediment." Science of the Total Environment
407(24): 6255-6266.
Armstrong, C. W., N. Foley, et al. (2010). Ecosystem Services of the Deep Sea, HERMIONE (Hotspot
Ecosystem Research and Man’s impact on European Seas). Deliverable 6.2.
Armstrong, C. W., V. Kahui, et al. (2008). Økonomisk verdsetting av havmiljø - Anvendelse på
havområdene i Lofoten-Vesterålen Utredning for Miljøverndepartementet, Norges
fiskerihøgskole, Universitetet i Tromsø.
Arnason, R., R. Hannesson, et al. (2000). "Costs of fisheries management: the cases of Iceland,
Norway and Newfoundland." Marine Policy 24(3): 233-243.
Arrow, K. J. and A. C. Fisher (1974). "Environmental Preservation, Uncertainty, and Irreversibility."
The Quarterly Journal of Economics 88(2): 312-319.
Aylward, B. and E. B. Barbier (1992). "Valuing environmental functions in developing countries."
Biodiversity and Conservation 1: 34-50.
Barbier, E. B. and I. Strand (1998). "Valuing mangrove-fishery linkages." Environmental and resource
economics. 12(151-166).
Bateman, I., R. Brouwer, et al. (2010). Valuing Environmental Impacts: Practical Guidelines for the
Use of Value Transfer in Policy and Project Appraisal, eftec.
Bateman, I., R. Brouwer, et al. (2011). "Making benefit transfers work: deriving and testing principles
for value transfers for similar and dissimilar sites using a case study of the non-market
benefits of water quality improvements across Europe." Environmental and Resource
Economics 50(3): 365-387.
Beaumont, N. J., M. C. Austen, et al. (2008). "Economic valuation for the conservation of marine
biodiversity." Marine Pollution Bulletin 56(3): 386-396.
Bell, F. W. (1972). "Technological externalities and common property resources: an empirical study of
the US northern lobster fishery." Journal of Political Economy 21: 343-367.
Beman, J. M., C.-E. Chow, et al. (2011). "Global declines in oceanic nitrification rates as a
consequence of ocean acidification." Proceedings of the National Academy of Sciences
108(1): 208-213.
Birol, E., P. Koundouri, et al. (2010). "Assessing the economic viability of alternative water resources
in water-scarce regions: Combining economic valuation, cost-benefit analysis and
discounting." Ecological Economics 69(4): 839-847.
Blackford, J. C. (2010). "Predicting the impacts of ocean acidification: Challenges from an ecosystem
perspective." Journal of Marine Systems 81(1-2): 12-18.
Boncoeur, J., F. Alban, et al. (2002). "Fish, fishers, seals and tourists: Economic consequences of
creating a marine reserve in a multi-species, multi-activity context." Natural Resource
Modeling 15(4): 387-411.
Boyd, J. and S. Banzhaf (2007). "What are ecosystem services? The need for standardized
environmental accounting units." Ecological Economics 63(2–3): 616-626.
52
Brander, L., I. Bräuer, et al. (2012). "Using meta-analysis and GIS for value transfer: A case study of
European wetland values under climate change." Environmental and Resource Economics.
Brander, L. M., K. Rehdanz, et al. (2009). The economic impact of ocean acidification on coral reefs.
ESRI Working Paper. No 282.
Brander, L. M., P. Van Beukering, et al. (2007). "The recreational value of coral reefs: A metaanalysis." Ecological Economics 63(1): 209-218.
Børsheim, K. and L. Golmen (2009). Ocean Acidification. Current knowledge for Norwegian waters (in
Norwegian), Norwegian Pollution Control Authority.
Caldeira, K. and M. E. Wickett (2003). "Anthropogenic carbon and ocean pH." Nature 425: 365.
Cesar, H. S. J. (2003). The Economics of Worldwide coral reef degradation. The Netherlands, WWF
and Cesar Environmental Economics Consulting (CEEC).
Cesar, H. S. J. and P. v. Beukering (2004). "Economic valuation of coral reefs of Hawai'i." Pacific
Science 58(2): 231-242.
Comeau, S., G. Gorsky, et al. (2009). "Impact of ocean acidification on a key Arctic pelagic mollusc
(Limacina helicina)." Biogeosciences 6(9): 1877-1882.
Cooley, S. R. and S. C. Doney (2009). "Anticipating ocean acidification's economic consequences for
commercial fisheries " Environmental Research Letters 4: 1-8.
Crépin, A.-S. (2007). "Using Fast and Slow Processes to Manage Resources with Thresholds."
Environmental and Resource Economics 36(2): 191-213.
Dahdouh-Guebas, F., L. P. Jayatissa, et al. (2005). "How effective were mangroves as a defence
against the recent tsunami?" Current Biology 15(12): R443-R447.
Desvousges, W., F. Johnson, et al. (1998). Environmental Policy Analysis with Limited
Information.Principles and Applications of the Transfer Method. Cheltenham, UK and
Northampton, MA, USA, Edward Elgar.
Doney, S. C. (2012). "Review of Ocean Acidification, edited by J.-P. Gattuso and L. Hansson."
Oceanography 25(1): 301–303.
Doney, S. C., V. J. Fabry, et al. (2009). Ocean Acidification: The Other CO(2) Problem. Annual Review
of Marine Science. Palo Alto, Annual Reviews. 1: 169-192.
Dupont, S., N. Dorey, et al. (2010). "What meta-analysis can tell us about vulnerability of marine
biodiversity to ocean acidification?" Estuarine, Coastal and Shelf Science 89(2): 182-185.
Dupont, S., Havenhand, J., Thorndyke, W., Peck, L., Thorndyke, M. (2008). "CO2-driven ocean
acidification radically affect larval survival and development in the brittlestar Ophiothrix
fragilis." Marine Ecology Progress Series(373): 285-294.
Eide, A. and O. Flaaten (1998). Bioeconomic Multispecies Models of the Barents Sea Fisheries.
Models for Multispecies Management. T. Rødseth. Heidelberg, New York, Physica-Verlag:
141-172.
Ellis, G. M. and A. C. Fisher (1987). "Valuing the Environment as an Input." Journal of Environmental
Management 25: 149-156.
Fabry, V. J., B. A. Seibel, et al. (2008). "Impacts of ocean acidification on marine fauna and ecosystem
processes." ICES Journal of Marine Science: Journal du Conseil 65(3): 414-432.
Feely, R. A., S. C. Doney, et al. (2009). "Ocean Acidification: Present Conditions and Future Changes in
a High-CO(2) World." Oceanography 22(4): 36-47.
Findlay, H. S., H. L. Wood, et al. (2009). "Calcification, a physiological process to be considered in the
context of the whole organism." Biogeosciences Discussions 6: 2267-2284.
Fivelstad, S., R. Waagbo, et al. (2007). "Impacts of elevated water carbon dioxide partial pressure at
two temperatures on Atlantic salmon (Salmo salar L.) parr growth and haematology."
Aquaculture 269(1-4): 241-249.
Flaaten, O. (1988). The Economics of Multispecies Harvesting. Germany., Springer.
Foley, N. S., V. Kahui, et al. (2010). "Estimating Linkages between Redfish and Cold Water Coral on
the Norwegian Coast " Marine Resource Economics 25(1): 105-120.
Foley, N. S., T. M. van Rensburg, et al. (2010). "The ecological and economic value of cold-water coral
ecosystems." Ocean & Coastal Management 53(7): 313-326.
53
Freeman, A. M. (1991). "Valuing environmental resources under alternative management regimes."
Ecological Economics 3(3): 247-256.
Freiwald, A., J. H. Fosså, et al. (2004). Cold water coral reefs: out of sight - no longer out of mind.
Camebridge, UK, UNEP-WCMC.
Frommel, A. Y., V. Stiebens, et al. (2010). "Effect of ocean acidification on marine fish sperm (Baltic
cod: Gadus morhua)." Biogeosciences 7(12): 3915-3919.
Gehlen M., G. N., Gangstø R., Bopp L., & Oschlies A. (2011). Biogeochemical consequences of ocean
acidification and feedback to the Earth system. Ocean acidification. G. J.-P. H. L. Oxford,
Oxford University Press: 230-248.
Glenn, H., P. Wattage, et al. (2010). "Marine Protected Areas - substantiating their worth." Marine
Policy 34: 421-430.
Golmen, K. Y. B. a. L. (2010). Forsuring av havet. Kunnskapsstatus for norske farvann.
Gordon, H. S. (1954). "Economic theory of common-property resources: the fishery." Journal of
Political Economy 62: 124-142.
Groom, B., C. Hepburn, et al. (2005). "Declining discount rates: The long and the short of it."
Environmental & resource economics 32(4): 445-493.
Guinotte, J. M., J. Orr, et al. (2006). "Will human-induced changes in seawater chemistry alter the
distribution of deep-sea scleractinian corals?" Frontiers in Ecology and the Environment 4(3):
141-146.
Hall-Spencer, J. M., R. Rodolfo-Metalpa, et al. (2008). "Volcanic carbon dioxide vents show ecosystem
effects of ocean acidification." Nature 454(7200): 96-99.
Hamilton, L. C. and M. J. Butler (2001). "Outport adaptations: Social indicators through
Newfoundland's cod crisis." Human Ecology Review 8(2): 1-11.
Hein, L., K. van Koppen, et al. (2006). "Spatial scales, stakeholders and the valuation of ecosystem
services." Ecological Economics 57(2): 209-228.
Hendriks, I. E. and C. M. Duarte (2010). "Ocean acidification: Separating evidence from judgment – A
reply to Dupont et al." Estuarine, Coastal and Shelf Science 89(2): 186-190.
Hendriks, I. E., C. M. Duarte, et al. (2010). "Vulnerability of marine biodiversity to ocean acidification:
A meta-analysis." Estuarine Coastal and Shelf Science 86(2): 157-164.
Hendriks, I. E., C. M. Duarte, et al. (2010). "Vulnerability of marine biodiversity to ocean acidification:
A meta-analysis." Estuarine, Coastal and Shelf Science 86(2): 157-164.
Hester, K. C., E. T. Peltzer, et al. (2008). "Unanticipated consequences of ocean acidification: A noisier
ocean at lower pH." Geophys. Res. Lett. 35(19): L19601.
Hoegh-Guldberg, O., P. J. Mumby, et al. (2007). "Coral Reefs Under Rapid Climate Change and Ocean
Acidification." Science 318(5857): 1737-1742.
Hofmann, M. and H.-J. Schellnhuber (2009). "Oceanic acidification affects marine carbon pump and
triggers extended marine oxygen holes." Proceedings of the National Academy of Sciences
106(9): 3017-3022.
IPCC (2007). Climate Change 2007: Contribution of Working Group III to the Fourth Assessment
Report of the Intergovernmental Panel on Climate Change, 2007 Cambridge, United Kingdom
and New York, NY, USA., Cambridge University Press.
IPCC (2007). Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the
Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge,
United Kingdom and New York, NY, USA, Cambridge University Press.
Kahn, J. R. (1987). "Measuring the economic damages associated with environmental influences in
fisheries." Marine Resource Economics 4: 1933-1209.
Karp, L. (2005). "Global warming and hyperbolic discounting." Journal of Public Economics 89(2-3):
261-282.
Kikkawa, T., J. Kita, et al. (2004). "Comparison of the lethal effect of CO2 and acidification on red sea
bream (Pagrus major) during the early developmental stages." Marine Pollution Bulletin
48(1-2): 108-110.
54
Kikkawa, T., T. Sato, et al. (2006). "Acute toxicity of temporally varying seawater CO2 conditions on
juveniles of Japanese sillago (Sillago japonica)." Marine Pollution Bulletin 52(6): 621-625.
Kleypas, J. A., R. A. Feely, et al. (2006). Impacts of Ocean Acidification on Coral Reefs and Other
Marine Calcifiers: A Guide for Future Research, Report of a workshop held 18–20 April 2005,
St. Petersburg, FL, sponsored by NSF, NOAA, and the U.S. Geological Survey.
Kleypas, J. A. and C. Langdon (2006). Coral Reefs and Changing Seawater Carbonate Chemistry. Coral
Reefs and Climate Change: Science and Management. J. T. Phinney, O. Hoegh-Guldberg, J. A.
Kleypas, W. Skirving and A. Strong.
Kroeker, K. J., R. L. Kordas, et al. (2010). "Meta-analysis reveals negative yet variable effects of ocean
acidification on marine organisms." Ecology Letters 13(11): 1419-1434.
Kroeker, K. J., F. Micheli, et al. (2011). "Divergent ecosystem responses within a benthic marine
community to ocean acidification." Proceedings of the National Academy of Sciences of the
United States of America 108(35): 14515-14520.
Kumar, P. (2010). The Economics of Ecosystems and Biodiversity: Ecological and Economic
Foundations, London ; Washington, DC : Earthscan, ©2010.
Le Quesne, W. J. F. (2011). "Fish fry or fried fish." Ocean Challenge 18: 38-43.
Le Quesne, W. J. F. and J. K. Pinnegar (2011). "The potential impacts of ocean acidification: scaling
from physiology to fisheries." Fish and Fisheries: no-no.
Li, C. Z. and K. G. Lofgren (2000). "Renewable resources and economic sustainability: A dynamic
analysis with heterogeneous time preferences." Journal of Environmental Economics and
Management 40(3): 236-250.
Lindhjem, H. and S. Navrud (2008). "How Reliable are Meta-Analyses for International Benefit
Transfer?" Ecological Economics 66(2-3): 425-435.
Liu, S. and D. Stern (2008). A Meta-Analysis of Contingent Valuation Studies in Coastal and NearShorec Marine Ecosystems. Munich Personal RePEc Archive (MPRA).
MEA (2005). Ecosystems and Human Well-being: Synthesis. Washington, DC, Millennium Ecosystem
Assessment, Island Press.
Mikkelsen, E. (2007). "Aquaculture-fisheries interactions." Marine Resource Economics 22: 287-303.
Millero, F. J., R. Woosley, et al. (2009). "Effect of Ocean Acidification on the Speciation of Metals in
Seawater." Oceanography 22(4): 72-85.
Moran, D. and J. G. Stottrup (2011). "The effect of carbon dioxide on growth of juvenile Atlantic cod
Gadus morhua L." Aquatic Toxicology 102(1-2): 24-30.
Narita, D., K. Rehdanz, et al. (Forthcoming). "Economic costs of ocean acidification: a look into the
impacts on global shellfish production." Climatic Change.
Navrud, S. (2004). Value transfer and environmental policy. The International Yearbook of
Environmental and Resource Economics 2004/2005. A survey of Current Issues. T. Tietenberg
and H. Folmer. Cheltenham, UK and Northampton, MA, USA, Edward Elgar Publishing: 189217.
Navrud, S. (2007). Practical tools for value transfer in Denmark – guidelines and an example. Working
Report No. 28, Miljøstyrelsen (Danish Environmental Protection Agency).
Orr, J. C., V. J. Fabry, et al. (2005). "Anthropogenic ocean acidification over the twenty-first century
and its impact on calcifying organisms." Nature 437(7059): 681-686.
Qiu, B. and K. Gao (2002). "Effects of CO2 enrichment on the bloom-forming cyanobacterium
mycrocystis aeruginosa (cyanophyceae): Physiological responses and relationships with the
availability of dissolved inorganic carbon " Journal of Phycology 38(4): 721-729.
Raven, J. A. e. a. (2005). "Ocean acidification due to increasing atmospheric carbon dioxide." Royal
Society.
Ressurreição, A., J. Gibbons, et al. (2011). "Economic valuation of species loss in the open sea."
Ecological Economics 70(4): 729-739.
Riebesell, U., I. Zondervan, et al. (2000). "Reduced calcification of marine plankton in response to
increased atmospheric CO2." Nature 407(6802): 364-367.
55
Ries, J. B., A. L. Cohen, et al. (2009). "Marine calcifiers exhibit mixed responses to CO2-induced ocean
acidification." Geology 37(12): 1131-1134.
Roberts, C. M., C. J. McClean, et al. (2002). "Marine Biodiversity Hotspots and Conservation Priorities
for Tropical Reefs." Science 295(5558): 1280-1284.
Roberts, J. M., A. J. Wheeler, et al. (2006). "Reefs of the Deep: The Biology and Geology of ColdWater Coral Ecosystems." Science 312(5773): 543-547.
Sabine, C. L., R. A. Feely, et al. (2004). "The oceanic sink for anthropogenic CO(2)." Science 305(5682):
367-371.
Schnier, K. E. (2005). "Biological “hotspots” and their effects on optimal bioeconomic marine reserve
formation." Ecological Economics 52(4): 453-468.
Schuster, U. and A. J. Watson (2007). "A variable and decreasing sink for atmospheric CO2 in the
North Atlantic." Journal of Geophysical Research-Oceans 112(C11).
Seibel, B. A. and P. J. Walsh (2003). "Biological impacts of deep-sea carbon dioxide injection inferred
from indices of physiological performance." Journal of Experimental Biology 206(4): 641-650.
Smith, M. D. (2007). "Generating Value in Habitat-dependent Fisheries: The Importance of Fishery
Management Institutions." Land Economics 83(1): 59-73.
Soderqvist, T. and L. Hasselstrom (2008). The economic value of ecosystem services provided by the
Baltic Sea and Skagerrak. S. E. P. Agency. Sweden.
Sondergaard, J., G. Asmund, et al. (2011). "Long-term response of an arctic fiord system to lead-zinc
mining and submarine disposal of mine waste (Maarmorilik, West Greenland)." Marine
Environmental Research 71(5): 331-341.
Spicer, J., A. Raffo, et al. (2007). "Influence of CO2-related seawater acidification on extracellular
acid–base balance in the velvet swimming crab Necora puber." Marine Biology 151(3): 11171125.
Steinacher, M., F. Joos, et al. (2009). "Imminent ocean acidification in the Arctic projected with the
NCAR global coupled carbon cycle-climate model." Biogeosciences 6(4): 515-533.
Stern, N. (2006). Stern Review: The economics of climate change. Executive Summary.
Subir, P. (2011). "Model to Study the Effect of Composition of Seawater on the Corrosion Rate of
Mild Steel and Stainless Steel." Journal of Materials Engineering and Performance 20(3): 325334.
Sumaila, U. R., W. W. L. Cheung, et al. (2011). "Climate change impacts on the biophysics and
economics of world fisheries." Nature Clim. Change advance online publication.
TEEB (2010). The Economics of Ecosystems and Biodiversity: Mainstreaming the Economics of
Nature: A synthesis of the approach, conclutions and recomendations of TEEB., UNEP.
Tol, R. S. J. (2008). "The Social Cost of Carbon: Trends, Outliers and Catastrophes." Economics 2(25).
Tol, R. S. J. (2008). "Why Worry About Climate Change? A Research Agenda." Environmental Values
17(4): 437-470.
Toman, M. (1998). "SPECIAL SECTION: FORUM ON VALUATION OF ECOSYSTEM SERVICES: Why not to
calculate the value of the world's ecosystem services and natural capital." Ecological
Economics 25(1): 57-60.
Turley, C., C. Brownlee, et al. (2010). Ocean Acidification MCCIP Annual Report Card. 2010-11: 27.
Turley, C., J. Roberts, et al. (2007). "Corals in deep-water: will the unseen hand of ocean acidification
destroy cold-water ecosystems?" Coral Reefs 26(3): 445-448.
Tyrrell, T. (2008). "Calcium carbonate cycling in future oceans and its influence on future climates."
Journal of Plankton Research 30(2): 141-156.
Veron, J. (2008). "Mass extinctions and ocean acidification: biological constraints on geological
dilemmas." Coral Reefs 27(3): 459-472.
Wattage, P., H. Glenn, et al. (2011). "Economic value of conserving deep-sea corals in Irish waters: A
choice experiment study on marine protected areas." Fisheries Research 107(1-3): 59-67.
Waycott, M., C. M. Duarte, et al. (2009). "Accelerating loss of seagrasses across the globe threatens
coastal ecosystems." Proceedings of the National Academy of Sciences 106(30): 1237712381.
56
WBGU (2006). The Future Oceans - Warming Up, Rising High, Turning Sour. Special Report. Berlin,
WBGU: 110.
Weitzman, M. L. (2001). "Gamma discounting." American Economic Review 91(1): 260-271.
Wood, H. L., J. I. Spicer, et al. (2008). "Ocean acidification may increase calcification rates, but at a
cost." Proceedings of the Royal Society B: Biological Sciences 275(1644): 1767-1773.
Wootton, J. T., C. A. Pfister, et al. (2008). "Dynamic patterns and ecological impacts of declining
ocean pH in a high-resolution multi-year dataset." Proceedings of the National Academy of
Sciences.
Wright, A. J., N. A. Soto, et al. (2007). "Do Marine Mammals Experience Stress Related to
Anthropogenic Noise?" International Journal of Comparative Psychology 20(2).
Yi, C. X., P. Gong, et al. (2001). "The effects of buffer and temperature feedback on the oceanic
uptake of CO2." Geophysical Research Letters 28(5): 751-754.
Zeebe, R. E. and D. A. Wolf-Gladrow (2001). CO2 in seawater: equilibrium, kinetics, isotopes, Elsevier.
57