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Journal of Applied Ecology
Volume 53, Issue 6 p. 1635-1641
Practitioner's Perspective
Free Access
LACK OF SOUND SCIENCE IN ASSESSING WIND FARM IMPACTS ON SEABIRDS
Rhys E. Green,
Corresponding Author
Rhys E. Green
* reg29@cam.ac.uk
Conservation Science Group, Department of Zoology, University of Cambridge,
David Attenborough Building, Pembroke Street, Cambridge, CB2 3QZ UK
RSPB Centre for Conservation Science, RSPB, The Lodge, Sandy Bedfordshire, SG19
2DL UK
Correspondence author. E-mail: reg29@cam.ac.ukSearch for more papers by this
author
Rowena H. W. Langston,
Rowena H. W. Langston
RSPB Centre for Conservation Science, RSPB, The Lodge, Sandy Bedfordshire, SG19
2DL UK
Search for more papers by this author
Aly McCluskie,
Aly McCluskie
RSPB Centre for Conservation Science, RSPB Scotland, 2 Lochside View, Edinburgh
Park, Edinburgh, EH12 9DH UK
Search for more papers by this author
Rosie Sutherland,
Rosie Sutherland
RSPB Centre for Conservation Science, RSPB, The Lodge, Sandy Bedfordshire, SG19
2DL UK
Search for more papers by this author
Jeremy D. Wilson,
Jeremy D. Wilson
* orcid.org/0000-0001-7485-5878
RSPB Centre for Conservation Science, RSPB Scotland, 2 Lochside View, Edinburgh
Park, Edinburgh, EH12 9DH UK
Search for more papers by this author
Rhys E. Green,
Corresponding Author
Rhys E. Green
* reg29@cam.ac.uk
Conservation Science Group, Department of Zoology, University of Cambridge,
David Attenborough Building, Pembroke Street, Cambridge, CB2 3QZ UK
RSPB Centre for Conservation Science, RSPB, The Lodge, Sandy Bedfordshire, SG19
2DL UK
Correspondence author. E-mail: reg29@cam.ac.ukSearch for more papers by this
author
Rowena H. W. Langston,
Rowena H. W. Langston
RSPB Centre for Conservation Science, RSPB, The Lodge, Sandy Bedfordshire, SG19
2DL UK
Search for more papers by this author
Aly McCluskie,
Aly McCluskie
RSPB Centre for Conservation Science, RSPB Scotland, 2 Lochside View, Edinburgh
Park, Edinburgh, EH12 9DH UK
Search for more papers by this author
Rosie Sutherland,
Rosie Sutherland
RSPB Centre for Conservation Science, RSPB, The Lodge, Sandy Bedfordshire, SG19
2DL UK
Search for more papers by this author
Jeremy D. Wilson,
Jeremy D. Wilson
* orcid.org/0000-0001-7485-5878
RSPB Centre for Conservation Science, RSPB Scotland, 2 Lochside View, Edinburgh
Park, Edinburgh, EH12 9DH UK
Search for more papers by this author
First published: 25 June 2016
https://doi.org/10.1111/1365-2664.12731
Citations: 26
About
* * REFERENCES
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* INFORMATION
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Sections
* Introduction
* Estimates of the effects of wind farms on seabird demographic rates are
neither robust nor validated
* Procedures for translating effects on demographic rates into projected
impacts on seabird population size and trends are inappropriate and untested
* The danger of acceptability thresholds without a logical or empirical basis
* A robust effect–impact translation procedure without a built-in threshold
* Conclusions
* Data accessibility
* References
* Biosketch
* Citing Literature
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INTRODUCTION
Electrical power generation from wind farms has grown rapidly in the UK and
European Union (EU) in the last decade and is set to grow further. By 2020, the
EU proposes to source 20% of energy from renewable sources (Directive
2009/28/EC). Wind energy is expected to provide 9–14% of global electricity
generation by 2050 (IPCC 2011). This may eventually reduce climatic change and
its negative impacts on biodiversity, but there are also several poorly
quantified negative effects on wild species of renewable energy generation,
including wind turbines. For example, birds and bats are killed by colliding
with turbine blades or towers and there may be effects of wind farms on
mortality and reproductive rates of a wide range of species from avoidance and
displacement. Birds may incur additional costs or forego benefits because of
reduced transit or foraging within or near to wind farms (Drewitt & Langston
2006; Searle et al. 2014). Depending upon the strength of density-dependent
compensatory processes, these effects could reduce the population to a lower
stable level or cause its extinction (Wade 1998; Niel & Lebreton 2005). Except
in the rare circumstances where density dependence is exactly compensating, such
effects would always diminish population size. Positive effects of renewable
energy infrastructure on populations of wild species have also been proposed
and, in a few cases, quantified. These include possible enhancement of food
resources of seabirds by protection from fishing from the presence of offshore
installations and the provision of artificial substrates as habitat for fish and
invertebrates (Inger et al. 2009; Langhamer, Wilhelmsson & Engström 2009).
The UK has the best wind resources in Europe (DECC 2011). Although the cost per
megawatt-hour of electricity generation from offshore wind turbines averages
about twice that for onshore installations (Bilgili, Yasar & Simsek 2011; Chu &
Majumdar 2012), offshore wind power is currently favoured over onshore by the
present UK government because of public perceptions of nuisance and landscape
consequences of onshore turbines. The UK also has internationally important
breeding populations of seabirds. It holds more than 10% of the world's breeding
population of eight species, of which three have more than half of their global
breeding population in the UK (Brown et al. 2015). Because seabirds range over
long distances, there may be cumulative impacts on a breeding colony from
several wind farms (Masden et al. 2010). Seabirds are long-lived and
late-maturing, which renders their population growth rate particularly sensitive
to additional mortality from collisions or displacement (Niel & Lebreton 2005).
The importance of these seabird populations and their sensitivity places a heavy
responsibility on those conducting and acting upon scientific assessments of the
impacts of offshore wind farms on seabirds to comply with the protection
measures and the precautionary principle enshrined in the EU Birds and Habitats
Directives (Directive 2009/147/EC and Council Directive 92/43/EEC).
For the UK, and other countries within the European Union, the regulation of
wind farm construction requires the assessment of possible damage to the
integrity of sites and populations under the EU Habitats and Birds Directives.
Consideration must be given to impacts on bird populations of a project on its
own and in combination with others already in existence, given consent or
planned. Governments give or refuse consent for the construction of wind farms
after taking into account the scale and level of certainty of the impacts
indicated by these assessments. However, there are no definitive quantitative
thresholds or criteria defining how large or likely expected impacts must be for
damage to the integrity of sites and populations to be anticipated and for
consent for wind farm construction to be denied or limited. Consent can be
granted only if it is ascertained that there will not be an adverse effect on
the integrity of a Natura site, excepting in cases where there are imperative
reasons of overriding public interest for consent and no alternative solutions
(Article 6(4) of Directive 92/43/EEC). In recent years, several plans for large
offshore wind farms have been approved and some built in UK and EU waters close
to large seabird populations because the competent authority judged there was no
expected adverse effect on the integrity of the Natura sites involved. For
example, in 2014 approval was granted for several extensive wind farms at
Hornsea (England, UK Government) and the Firth of Forth (Scotland, Scottish
Government), close to internationally important breeding populations of
seabirds. This approach contrasts with that in some other EU states. In Germany
and Denmark, for example, offshore wind farms have been subject to rigorous
marine spatial planning with the aim of avoiding potential conflict with nature
conservation as part of the required Strategic Environmental Assessment (SEA)
process recommended in EU Commission guidance (European Commission 2011). The
German Cabinet approved Europe's first maritime spatial plan in September 2009,
after a considerable effort in terms of surveys and research to identify marine
sites of high nature value and potential conflict areas with wind farms and to
establish zones for various activities and infrastructure. The offshore SEA
covering UK waters is not of comparable quality.
In this perspective, we argue that the methods and data used in these cases for
estimating effects upon seabird demographic rates and translating them into
potential impacts on seabird populations do not allow adequate assessment of
effects on site integrity. As a result, sound science and its logical
interpretation are lacking in Environmental Impact Assessments of this large and
expanding industry.
ESTIMATES OF THE EFFECTS OF WIND FARMS ON SEABIRD DEMOGRAPHIC RATES ARE NEITHER
ROBUST NOR VALIDATED
Collision risk models (CRMs) are used to predict the number of fatal collisions
of flying birds with wind turbines and per capita additional mortality rates. In
the UK, the most widely used CRM is that of Band (2012) (see review by Masden &
Cook (2016)). The model requires estimates or assumptions about bird numbers and
ages at the wind farm, attribution of birds at the wind farm to source
populations, sizes and age structure of source populations, flight behaviour and
avoidance rates. Data specific to the project and species being assessed are
usually collected on seabird numbers and flight heights, judged by eye, but
these estimates are subject to substantial uncertainties, variability and
potential biases (Johnston et al. 2014), including:
1. accuracy of input variables is rarely quantified, is often poor, and the CRM
outputs are highly sensitive to the values used, including flight speed
(Masden 2015), and avoidance rate estimates;
2. in many cases, birds at risk are not attributed to source populations
because recently developed tracking technologies are either not deployed at
all or not on a sufficient scale for robust estimation;
3. count and flight height data are usually insufficient in quantity and
quality for precise estimation of seasonal variation, age structure and age
differences (Band 2012).
Total avoidance rates used for CRM calculations for seabirds, including
within-wind farm avoidance of individual turbines and macro-avoidance by
movement of birds around the turbine array, are most often based upon judgement
or extrapolation from other contexts rather than pertinent data. Empirical
values are only available from a few species (mostly gulls and terns) and
usually extrapolated from studies of onshore wind farms, where different
circumstances prevail (Cook et al. 2014). Robust direct estimates of within-wind
farm avoidance rates are lacking for seabird species frequently present in and
near planned and consented offshore wind farms in the UK, such as northern
gannet Morus bassanus and black-legged kittiwake Rissa tridactyla (Cook et al.
2014). Macro-avoidance and displacement rates have been estimated using radar,
visual surveys and imaging, but robust quantitative estimates with confidence
intervals are generally not used in impact assessments. Estimates of
macro-avoidance for the same species can be highly variable (e.g. Petersen
et al. 2006; Krijgsveld et al. 2011; Vanermen et al. 2012, 2013 for northern
gannet). This may well be because macro-avoidance varies with the relative
positions of nesting and foraging sites, foraging site quality and seasonal
timing of studies.
At onshore wind farms, carcasses of some of the birds killed by collisions with
turbines can be collected during systematic searches and probabilities of their
detection can be estimated. This allows estimation of numbers of deaths per unit
time and confidence intervals, even if with low precision (e.g. Bellebaum et al.
2013). These methods help to quantify uncertainty and remove bias, but are
currently impractical for offshore wind farms. Alternatives that use video or
thermal camera systems have not yet been deployed sufficiently to substitute for
them. Where direct measurements of avoidance rates are lacking, Band (2012)
recommends use of a range of plausible values. However, this can result in a
20-fold variation in assumed per capita mortality rates (APEM 2015).
Overall, CRM outputs are sensitive to the combined effects of multiple
assumptions of unknown accuracy, sampling errors and unquantified biases. Only
for species that almost completely avoid entering wind farms can the annual per
capita mortality rate from collisions be estimated reliably and with robust
confidence limits (Desholm & Kahlert 2005). Validation tests of offshore seabird
CRM outputs, in which expectations from pre-consent data and modelling are
compared with independent robust post-construction measurements of numbers of
collision deaths, have not been conducted.
Estimation of effects on seabird demographic rates of the displacement and
barrier effects of wind farms is even less well developed. Avoidance of wind
farms by foraging and migrating birds can be substantial and operate over long
distances from the turbines (Desholm & Kahlert 2005; Petersen et al. 2006;
Percival 2010), but the degree to which this affects travel times and costs,
access to food and mortality and reproductive rates of breeding seabirds has not
been measured reliably. In the case of migrating birds, the displacement and
increased travel costs caused by avoidance of a single wind farm may be trivial
relative to the total length and cost of the journey (Masden et al. 2009), but
effects on demographic rates have not been robustly quantified by empirical
studies for central-place foraging breeding seabirds repeatedly subjected to
barrier or displacement effects. Simulation modelling has been performed of
potential effects of displacement by as yet unconstructed wind farms on seabird
time and energy budgets and demographic rates (Searle et al. 2014). Modelled
potential effects of displacement included considerable declines in adult
survival of up to 2·1% for black-legged kittiwake and up to 4·9% for Atlantic
puffin Fratercula arctica (both for the Forth Islands cumulative effects: table
3·3 of Searle et al. 2014), though simulated effects on survival for other
species and sites and for breeding productivity generally were small. The
species for which collision mortality can be reliably estimated as low, because
of strong avoidance, are those for which displacement and barrier effects upon
demographic rates are potentially the largest, but currently unquantified.
In summary, the procedures currently used to calculate expected effects of
proposed wind farms on seabird per capita mortality rates and breeding success
largely involve modelling with little firm empirical data. Moreover, actual
outcomes at wind farms that have been constructed have not been measured, so
model predictions are not tested and there is no adaptive improvement of the
decision-making process (Nichols et al. 2015). As a result, scientifically
robust and defensible calculations of effect sizes for changes in seabird
demographic rates caused by collision, displacement and barrier effects of
offshore wind farms, with confidence intervals, are currently lacking.
PROCEDURES FOR TRANSLATING EFFECTS ON DEMOGRAPHIC RATES INTO PROJECTED IMPACTS
ON SEABIRD POPULATION SIZE AND TRENDS ARE INAPPROPRIATE AND UNTESTED
Assessments of the impacts of offshore wind farms in the UK on seabirds require
that the highly uncertain estimates of effects on demographic rates are
translated into projections of impacts on population size or trend. Decisions
about UK offshore wind farms have been based upon, or influenced by, the
following effect–impact translation procedures.
POTENTIAL BIOLOGICAL REMOVAL (PBR)
The recommended and robust application of this method is to identify a level of
additional mortality above which a decline of the affected population to
eventual extinction would be likely (Niel & Lebreton 2005). In recent cases,
such as Hornsea, the UK statutory conservation agencies advised using this
method in wind farm assessments to identify demographic rate thresholds below
which additional mortality estimated from CRMs and related methods is unlikely
to adversely impact the population (Natural England 2014). This reverse
application involves faulty logic because PBR's value of maximum potential
excess growth may not be realizable in the ecological circumstances of a
particular population of interest. In addition, PBR does not estimate the effect
of additional mortality on population size.
Potential biological removal provides thresholds of additional mortality that
are sensitive to assumptions made about the form of density dependence. The
studies of Wade (1998) and Bellebaum et al. (2013) show that the shape parameter
of the generalized logistic equation has a strong effect on PBR results. Details
of the form of density-dependent relationships are rarely known for animal
populations and are unknown for any of the UK seabird populations to which PBR
has been applied. These uncertainties have prompted the use of ‘recovery
factors’, which are constants by which the maximum possible value of the PBR
threshold is multiplied to give a safety margin (Dillingham & Fletcher 2008).
The values used for these recovery factors are based upon judgement. There has
been no empirical validation of their safety by observation of the effects on
population size of known additional mortality rates from any source in any bird
species.
ACCEPTABLE BIOLOGICAL CHANGE (ABC)
This method, which has not yet been published in the peer-reviewed scientific
literature, was developed by Marine Scotland, a Scottish government agency, and
used in a recent assessment of the impact of wind farms on internationally
important seabird populations in the Firth of Forth (Marine Scotland, 2015). It
uses probabilistic forecasts from stochastic seabird population models to assess
the probability of a particular level of population size occurring at some
future time, such as the end of the period of operation of a wind farm, in the
absence of the wind farm. In practice, this probability is obtained from a
simulation model of the population in which variation in expected future
population size arises from supposed future demographic and environmental
stochasticity in demographic rates, when applied to the population of a
specified initial size over a period of 25 years, which is the usual licence
period for an offshore wind farm. If the best estimate of future population
size, after the expected effects of the wind farm on demographic rates are taken
into account, equals or exceeds the population size that is 66·7% likely to be
equalled or exceeded in the absence of the wind farm, then ABC deems that the
impact of the wind farm is acceptable.
The weaknesses of this approach are severe. First, the accuracy of projections
of the demographic rates used in the model of the unimpacted seabird population
long into the future is highly uncertain and untested. Perversely, the greater
the estimated uncertainty, the larger the acceptable population decline.
Secondly, it does not address the uncertainties in size of the effects of the
wind farm on demographic rates, which are mostly unquantified. Hence, ABC does
not assess the risk or probability that the wind farm itself will cause a
particular specified outcome or change at all. It simply proposes that an event
half as likely to occur as not if there is no wind farm should be the threshold
for acceptability. Thirdly, the threshold probability for acceptance is
arbitrary and is plucked from an unrelated context: IPCC guidelines about the
appropriate language to describe the likelihood of an event or outcome of at
least given size happening, based upon available evidence (Mastrandrea et al.
2010). The threshold chosen for ABC is described as ‘unlikely’ in the IPCC
lexicon. However, this lexicon was not developed for the purpose of determining
acceptable levels of risk, which also requires that the societal costs and
benefits of possible outcomes are evaluated. It is not only the chance of being
wrong that is important, but also the scale of the damage caused by being wrong.
No justification is given by the proponents of ABC for using as a tolerable risk
threshold for damage to important nature conservation sites and their species a
term selected arbitrarily from a lexicon developed by IPCC for a different
purpose.
DECLINE PROBABILITY DIFFERENCE (DPD) METHOD
Large uncertainties in predicting future seabird population changes might not
matter if differences in the probability of a specific population outcome
between scenarios with and without wind farms could be predicted reliably and
used as criteria for acceptability. This focus on differences in risk has been
proposed by the Joint Nature Conservation Committee & Natural England (2012). It
was suggested that assessments of acceptable impact should be based upon an
arbitrary threshold level of absolute difference between the impacted and
unimpacted scenarios in the probability that a population decline by an
arbitrary proportion of the initial level would occur. In principle, this
approach is preferable to ABC because it takes the uncertainty in the predicted
magnitude of the effect of the wind farm into account. However, the results of
this procedure are sensitive to the selection of unpredictable baseline
(unimpacted) demographic rates. For example, in a model in which the selected
values of baseline demographic rates imply a rapid increase in projected
population size, it is unlikely that even large additional mortality would give
rise to an appreciable absolute difference in the probability of population
decline between impacted and unimpacted scenarios. Both probabilities would be
very small. If the selected rates were inaccurate and the true values instead
led to the unimpacted population being approximately stable, the same level of
additional mortality could result in a large difference in the probability of
population decline between impacted and unimpacted scenarios.
In practice, uncertainties in future projections of both unimpacted and impacted
populations are mostly unquantified, so the probability distribution of an
outcome for population size cannot be calculated. This problem makes approaches,
such as ABC and DPD, which are based upon assessments of probability or
difference in probability unworkable, given present knowledge.
THE DANGER OF ACCEPTABILITY THRESHOLDS WITHOUT A LOGICAL OR EMPIRICAL BASIS
All the effect–impact translation procedures described above have a built-in
threshold for an acceptable impact. Such thresholds are naturally attractive to
decision-makers because they appear to offer a clear-cut, evidence-based way to
establish whether damage to the integrity of a designated site will or will not
occur. However, in the case of ABC and DPD, the thresholds offer only false
security because they are arbitrary, have no foundation in population biology
and embed the acceptance of some adverse impact on population size. Whilst PBR
does identify a threshold based upon population biology, it is one that is
misapplied to the problem at hand. PBR could be used to identify a threshold
level of effect of wind farms on demographic rates above which a decline of an
affected closed population to eventual extinction would be almost certain.
However, population declines of a wide range of magnitudes, short of
extirpation, could be caused by effects of wind farms on demographic rates well
below this. How large these declines would be depends upon the form and strength
of density dependence, which are unlikely to be measured with sufficient
precision, and the magnitude of such declines has not been quantified using PBR
in any UK wind farm assessment. We argue that such declines would constitute
adverse effects on site integrity. Hence, PBR is not an appropriate method for
assessing population impacts of a development in a manner that is relevant to
the concerns of the public and decision-makers.
A ROBUST EFFECT–IMPACT TRANSLATION PROCEDURE WITHOUT A BUILT-IN THRESHOLD
A more robust procedure for evaluating population-level impacts of wind farms on
seabirds is to calculate, using a density-independent Leslie matrix model (LMM),
expected population sizes, with and without the expected effects on demographic
rates of the wind farm, at the end of its lifetime. The ratio of the expected
population size with the wind farm to that without it (the counterfactual of
population size) is a robust metric for likely population-level impact of a
specified set of effects of the wind farm on seabird demographic rates. This
LMM-ratio approach is relatively insensitive to the assumptions made about the
magnitude, variability and trends of demographic rates in the model from which
it is calculated, because the same uncertainties apply to both the impacted and
unimpacted scenarios. Hence, this effect–impact translation procedure
contributes little to the uncertainty in the difference in population size
caused by the wind farm.
Density dependence tends to reduce the impact on population size of a given
effect of the wind farm on demographic rates, so the LMM ratio calculated from
the density-independent model is a precautionary worst-case outcome. We think it
probable that density-dependent compensation occurs in UK seabird populations
and that including it in LMMs (e.g. Miller, Jensen & Hammill 2002) could lead to
more accurate estimates of population impact than those based upon
density-independent LMMs. However, accuracy would only be increased if robust
estimates of the form and strength of density dependence were available or
population outcomes could be shown to be insensitive to assumptions made about
density dependence in the absence of reliable quantification. In practice, no
assessments of population impacts of additional mortality from wind farms on UK
seabirds have included empirical estimates of the form and strength of density
dependence because applicable estimates seem not to be available. Until adequate
quantification of density dependence is available, we recommend the use of
density-independent LMM ratios.
Whether density dependence is included or not, there is no threshold value of
acceptability built into the LMM-ratio metric. Population estimates from Leslie
matrix models, for example Trinder (2014), and population models fitted using a
Bayesian approach (Marine Scotland, 2015) have been calculated as part of
offshore wind farm impact assessments, but their results have not been used
explicitly as counterfactuals in decision-making about the acceptability or
otherwise of UK offshore wind farm projects. Based upon the documentation of UK
wind farm assessments, we believe that methods such as PBR, ABC and DPD have
been used in preference to LMMs because they provide thresholds which can be
used to argue that site integrity will not be affected by the project, whilst
LMMs deliberately do not provide a threshold. We argue that, because the
thresholds offered by the other methods are arbitrary and invalid, LMMs should
be used as the standard, best-practice method, and we note that any of the
potential positive effects of offshore wind farms on seabird demographic rates,
if quantified, could be included in an integrated assessment using an LMM-ratio
metric.
CONCLUSIONS
Current procedures for collecting empirical data, modelling effects on
demographic rates and translating those effects into projected impacts of
offshore wind farms on seabird populations are inadequate. Empirical
measurements of effects of offshore wind farms on seabird demographic rates from
fieldwork are not sufficiently precise and unbiased. In the case of some
important parameters such as turbine avoidance rates and the strength of
density-dependent compensation, estimation is rarely even attempted. As a result
of these holes in the evidence base, the magnitude of effects of wind farms on
seabird demographic rates cannot be estimated accurately and the level of bias
and precision in the estimates used cannot be calculated.
To overcome these problems, responsible governments should require the renewable
energy industry to co-fund an adequate level of field-based research to estimate
effects of wind farms on seabird demographic rates more reliably. The Offshore
Renewables Joint Industry Partnership (ORJIP) intends to address this need
(Carbon Trust 2015), but the objectives of its project need to be greatly
expanded with regard to the number of species covered, proximity to their
breeding colonies and robustness of estimation. Further development and
deployment of radar, imaging and tracking techniques are likely to be required,
including remote download 3D tracking (Cleasby et al. 2015). A defensible
approach is then needed to translate these effect measurements, and their
uncertainties, into expected impacts on populations. We propose that the
counterfactual population ratio from a density-independent Leslie matrix model
would be an appropriate method for this translation.
Quite separate from these problems of measurement, estimation and modelling,
there is a fundamental logical flaw in the link between scientific assessment
and decision-making about the acceptability of wind farm impacts. Modelling
approaches have been contrived that seek to define an acceptable threshold for a
projected negative impact of a wind farm on seabird populations, below which
this negative impact is regarded as causing no adverse effect on site integrity.
However, the emperor has no clothes: the thresholds used to define the
acceptability of projected offshore wind farm impacts are arbitrary, poorly
reasoned, not designed for the purpose and have no valid biological basis.
Hence, it is necessary to revise decision-making procedures, regardless of what
effect-to-impacts translation procedure is used. At present, inadequate data are
being combined with arbitrary and scientifically unsupportable thresholds to
argue that wind farms will cause no damage to the integrity of sites designated
to restore and maintain Europe's biodiversity.
Population viability analysis indicates that the probability of long-term
persistence of an animal population and its mean time to extinction generally
increases with its average size (Akçakaya, Burgman & Ginzburg 1999). According
to European Commission guidance on managing the network of protected sites
established by the EU Birds and Habitats Directives (Natura 2000 sites), Article
6 of the Habitats Directive provides that ‘The integrity of the site involves
its ecological functions. The decision as to whether it is adversely affected
should focus on and be limited to the site's conservation objectives’ (European
Commission 2000). In addition, for the integrity of a site not to be adversely
affected, a Court of Justice of the European Union decision (Court of Justice of
the European Union 2013; Para. 39) found that the ‘site needs to be preserved at
a favourable conservation status’, which entails ‘the lasting preservation of
the constitutive characteristics of the site concerned that are connected to the
presence of a natural habitat type whose preservation was the objective
justifying the designation of that site’. Based upon this reasoning, we argue
that some damage to the integrity of a designated site will have been sustained
if populations of the seabirds for which it was designated are diminished, even
to a small degree, by the effects of a wind farm, compared with what they would
otherwise have been. If that is expected to be the case, it does not mean that
the competent authority cannot give consent for a wind farm. Article 6(4) of the
Habitats Directive sets out tests that determine whether the expected damage can
be accepted and compensated for. However, poor science should not be used to
avoid those tests by claiming that no damage will occur.
DATA ACCESSIBILITY
Data have not been archived because this article does not contain data.
REFERENCES
* Akçakaya, H.R., Burgman, M.A. & Ginzburg, L.R. (1999) Applied Population
Ecology, 2nd edn. Sinauer, Sunderland, MA, USA.
Google Scholar
* APEM (2015) East Anglia 3 Windfarm Environmental Statement. Appendix 13.3
Collision Risk Modelling Methodology and Predictions. Document Reference
6.3.13 (3).
Google Scholar
* Band, W. (2012) Using a collision risk model to assess bird collision risk
for offshore wind farms. Report to SOSS.
Google Scholar
* Bellebaum, J., Korner-Nivergelt, F., Durr, T. & Mammen, U. (2013) Wind
turbine fatalities approach a level of concern in a raptor population.
Journal for Nature Conservation, 21, 394– 400.
CrossrefWeb of Science®Google Scholar
* Bilgili, M., Yasar, A. & Simsek, E. (2011) Offshore wind power development in
Europe and its comparison with onshore counterpart. Renewable and Sustainable
Energy Reviews, 15, 905– 915.
CrossrefWeb of Science®Google Scholar
* Brown, D., Wilson, J., Douglas, D., Thompson, P., Foster, S., McCulloch, N.
et al. (2015) The Eurasian Curlew –the most pressing bird conservation
priority in the UK? British Birds, 108, 660– 668.
Google Scholar
* Carbon Trust (2015) Offshore Renewables Joint Industry Programme (ORJIP).
Available at:
http://www.carbontrust.com/client-services/technology/innovation/offshore-renewables-joint-industry-programme-orjip
Downloaded 1 April 2015.
Google Scholar
* Chu, S. & Majumdar, A. (2012) Opportunities and challenges for a sustainable
energy future. Nature, 488, 294– 303.
CrossrefCASPubMedWeb of Science®Google Scholar
* Cleasby, I.R., Wakefield, E.D., Bearhop, S., Bodey, T.W., Votier, S.C. &
Hamer, K.C. (2015) Three-dimensional tracking of a wide-ranging marine
predator: flight heights and vulnerability to offshore wind farms. Journal of
Applied Ecology, 52, 1474– 1482.
Wiley Online LibraryWeb of Science®Google Scholar
* Cook, A.S.C.P., Humphreys, E.M., Masden, E.A. & Burton, N.H.K. (2014) The
avoidance rates of collision between birds and offshore turbines. BTO
Research Report No. 656. BTO, Thetford.
Google Scholar
* Court of Justice of the European Union (2013) Decision in Peter Sweetman,
Ireland, Attorney General, Minister for the Environment, Heritage and the
Local Government v An Bord Pleanala [2014] PTSR 1092, [2013] EUECJ C-258/11.
Google Scholar
* DECC (2011) UK Renewable Energy Roadmap. Department of Energy and Climate
Change, London, UK.
Google Scholar
* Desholm, M. & Kahlert, J. (2005) Avian collision risk at an offshore wind
farm. Biology Letters, 1, 296– 298.
CrossrefPubMedWeb of Science®Google Scholar
* Dillingham, P.W. & Fletcher, D. (2008) Estimating the ability of birds to
sustain additional human-caused mortalities using a simple decision rule and
allometric relationships. Biological Conservation, 141, 1783– 1792.
CrossrefWeb of Science®Google Scholar
* Drewitt, A.L. & Langston, R.H.W. (2006) Assessing the impacts of wind farms
on birds. Ibis, 148(Suppl. 1), 29– 42.
Wiley Online LibraryWeb of Science®Google Scholar
* European Commission (2000) Managing Natura 2000 sites. The provisions of
Article 6 of the ‘Habitats’ Directive 92/43/CEE. Office for Official
Publications of the European Communities, Luxembourg.
Google Scholar
* European Commission (2011) EU Guidance on Wind Energy Development in
Accordance With the EU Nature Legislation. Publications Office of the
European Union, Luxembourg.
Google Scholar
* Inger, R., Attrill, M.J., Bearhop, S., Broderick, A.C., Grecian, W.J.,
Hodgson, D.J. et al. (2009) Marine renewable energy: potential benefits to
biodiversity? An urgent call for research. Journal of Applied Ecology, 46,
1145– 1153.
Wiley Online LibraryWeb of Science®Google Scholar
* IPCC (2011) IPCC Special Report on Renewable Energy Sources and Climate
Change Mitigation. Cambridge University Press, Cambridge, UK & New York, NY,
USA.
CrossrefGoogle Scholar
* Johnston, A., Cook, A.S.C.P., Wright, L.J., Humphreys, E.M. & Burton, N.H.K.
(2014) Modelling flight heights of marine birds to more accurately assess
collision risk with offshore wind turbines. Journal of Applied Ecology, 51,
31– 41.
Wiley Online LibraryWeb of Science®Google Scholar
* Joint Nature Conservation Committee & Natural England (2012) Defining the
level of additional mortality that the North Norfolk Coast SPA Sandwich tern
population can sustain. Unpublished report, JNCC & Natural England.
Google Scholar
* Krijgsveld, K.L., Fijn, R.C., Japink, M., van Horssen, P.W., Heunks, C.,
Collier, M.P., Poot, M.J.M., Beuker, D. & Dirksen, S. (2011) Effect Studies
Offshore Wind Farm Egmond aan Zee: Final report on fluxes, flight altitudes
and behaviour of flying birds. Bureau Waardenburg Report No 10-219.
Google Scholar
* Langhamer, O., Wilhelmsson, D. & Engström, J. (2009) Artificial reef effect
and fouling impacts on offshore wave power foundations and buoys – a pilot
study. Estuarine, Coastal and Shelf Science, 82, 426– 432.
CrossrefWeb of Science®Google Scholar
* Marine Scotland (2015) Appropriate Assessment: Marine Scotland's
Consideration of a Proposal Affecting Designated Special Areas of
Conservation (“SACs”) or Special Protection Areas (“SPAs”)
http://www.gov.scot/Resource/0046/00460542.pdf
Google Scholar
* Masden, E.A. (2015) Developing an avian collision risk model to incorporate
variability and uncertainty. Scottish Marine and Freshwater Science, 6.
Available at: http://www.gov.scot/Resource/0048/00486433.pdf
Google Scholar
* Masden, E.A. & Cook, A.S.C.P. (2016) Avian collision risk models for wind
energy impact assessments. Environmental Impact Assessment Review, 56, 43–
49.
CrossrefWeb of Science®Google Scholar
* Masden, E.A., Haydon, D.T., Fox, A.D., Furness, R.W., Bullman, R. & Desholm,
M. (2009) Barriers to movement: impacts of wind farms on migrating birds.
ICES Journal of Marine Science, 66, 746– 753.
CrossrefWeb of Science®Google Scholar
* Masden, E.A., Fox, A.D., Furness, R.W., Bullman, R. & Haydon, D.T. (2010)
Cumulative impact assessments and bird/wind farm interactions: developing a
conceptual framework. Environmental Impact Assessment Review, 30, 1– 7.
CrossrefWeb of Science®Google Scholar
* Mastrandrea, M.D., Field, C.B., Stocker, T.F., Edenhofer, O., Ebi, K.L.,
Frame, D.J. et al. (2010) Guidance Note for Lead Authors of the IPCC Fifth
Assessment Report on Consistent Treatment of Uncertainties. Intergovernmental
Panel on Climate Change (IPCC).
Google Scholar
* Miller, D.H., Jensen, A.L. & Hammill, J.H. (2002) Density dependent matrix
model for gray wolf population projection. Ecological Modelling, 151, 271–
278.
CrossrefWeb of Science®Google Scholar
* Natural England (2014) Hornsea Offshore Wind Farm – Project One Application,
Written Representations of Natural England, January 2014. Planning
Inspectorate Reference EN010033.
Google Scholar
* Nichols, J.D., Johnson, F.A., Williams, B.K. & Boomer, G.S. (2015) On
formally integrating science and policy: walking the walk. Journal of Applied
Ecology, 52, 539– 543.
Wiley Online LibraryWeb of Science®Google Scholar
* Niel, C. & Lebreton, J.D. (2005) Using demographic invariants to detect
overharvested bird populations from incomplete data. Conservation Biology,
19, 826– 835.
Wiley Online LibraryWeb of Science®Google Scholar
* Percival, S.M. (2010) Kentish Flats Offshore Wind Farm: Diver Surveys
2009-2010. Ecology Consulting for Vattenfall Wind Power, Durham, NC, USA.
Google Scholar
* Petersen, I.K., Christensen, T.K., Kahlert, J., Desholm, M. & Fox, A.D.
(2006) Final Results of Bird Studies at the Offshore Wind Farms at Nysted and
Horns Rev, Denmark. National Environmental Research Institute, Aarhus,
Denmark.
Google Scholar
* Searle, K., Mobbs, D., Butler, A., Bogdanova, M., Freeman, S., Wanless, S. &
Daunt, F. (2014) Population consequences of displacement from proposed
offshore wind energy developments for seabirds breeding at Scottish SPAs
(CR/2012/03). CEH Report to Marine Scotland Science.
Google Scholar
* Trinder, M. (2014) Seabird PVA: Methods and Guidance on Result
Interpretation. MacArthur Green, 9 April 2014.
Google Scholar
* Vanermen, N., Stienen, E.W.M., Onkelinx, T., Courtens, W., Van de walle, M.,
Verschelde, P. & Verstraete, H. (2012) Seabirds & Offshore Wind Farms
Monitoring Results 2011. Report INBO.R.2012.25. INBO, Brussels.
Google Scholar
* Vanermen, N., Stienen, E.W.M., Courtens, W., Onkelinx, T., Van de walle, M. &
Verstraete, H. (2013) Bird monitoring at offshore wind farms in the Belgian
part of the North Sea - Assessing seabird displacement effects. Rapporten van
het Instituut voor Natuur- en Bosonderzoek 2013 (INBO.R.2013.755887).
Instituut voor Natuur- en Bosonderzoek, Brussel.
Google Scholar
* Wade, P.R. (1998) Calculating limits to the allowable human-caused mortality
of cetaceans and pinnipeds. Marine Mammal Science, 14, 1– 37.
Wiley Online LibraryWeb of Science®Google Scholar
BIOSKETCH
Rhys Green, Rowena Langston, Aly McCluskie and Jeremy D. Wilson are conservation
scientists at the Royal Society for the Protection of Birds (RSPB). Rosie
Sutherland is the RSPB's in-house environmental solicitor. All are directly
involved in the assessment of the impacts upon birds of proposed wind farms in
the UK.
CITING LITERATURE
Volume53, Issue6
December 2016
Pages 1635-1641
* REFERENCES
* RELATED
* INFORMATION
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* Density dependence and marine bird populations: are wind farm assessments
precautionary?
Cat Horswill, Susan H. O'Brien, Robert A. Robinson,
Journal of Applied Ecology
* Effects of wind farms and food scarcity on a large scavenging bird species
following an epidemic of bovine spongiform encephalopathy
Alejandro Martínez-Abraín, Giacomo Tavecchia, Helen M. Regan, Juan Jiménez,
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* Effects of wind turbines on flight behaviour of wintering common eiders:
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* Scaling possible adverse effects of marine wind farms on seabirds: developing
and applying a vulnerability index
STEFAN GARTHE, OMMO HÜPPOP,
Journal of Applied Ecology
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