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Contributed Paper
How economic contexts shape calculations of yieldin biodiversity offsetting
L. Carver1 and S. Sullivan 2 ∗1Birkbeck College, Malet Street, London WC1E 7HX, U.K.2Bath Spa University, Newton Park, Newton St, Loe, Bath BA2 9BN, U.K.
Abstract: We examined and analyzed methods used to create numerical equivalence between sites affectedby development and proposed conservation offset sites. Application of biodiversity offsetting metrics in develop-ment impact and mitigation assessments is thought to standardize biodiversity conservation outcomes, some-times termed yield by those conducting these calculations. The youth of biodiversity offsetting in application,however, means little is known about how biodiversity valuations and offset contracts between developmentand offset sites are agreed on in practice or about long-term conservation outcomes. We examined how siteswere made commensurable and how biodiversity gains or yields were calculated and negotiated for a specificoffset contract in a government-led pilot study of biodiversity offsets in England. Over 24 months, we conductedparticipant observations of various stages in the negotiation of offset contracts through repeated visits to 3(anonymized) biodiversity offset contract sites. We conducted 50 semistructured interviews of stakeholdersin regional and local government, the private sector, and civil society. We used a qualitative data analysissoftware program (DEDOOSE) to textually analyze interview transcriptions. We also compared successiveiterations of biodiversity-offsetting calculation spreadsheets and planning documents. A particular focus wasthe different iterations of a specific biodiversity impact assessment in which the biodiversity offsetting metricdeveloped by the U.K.’s Department for Environment, Food and Rural Affairs was used. We highlight 3main findings. First, biodiversity offsetting metrics were amended in creative ways as users adapted inputsto metric calculations to balance and negotiate conflicting requirements. Second, the practice of makingdifferent habitats equivalent to each other through the application of biodiversity offsetting metrics resultedin commensuration outcomes that may not provide projected conservation gains. Third, the pressure ofcreating value for money diminished projected conservation yields.
Keywords: biodiversity yield, commensuration, conservation policy, English Biodiversity Offsetting Pilot,ethnography, value
Como los Contextos Economicos Dan Forma a los Calculos del Redito en la Compensacion de la Biodiversidad
Resumen: Examinamos y analizamos los metodos utilizados para crear equivalencias numericas entrelos sitios afectados por el desarrollo y propusimos sitios de compensacion de la conservacion. Se cree quela aplicacion de las medidas compensadoras de la biodiversidad en el impacto del desarrollo y en las val-oraciones de mitigacion estandariza los resultados de la conservacion de la biodiversidad, que a veces esdenominada redito por aquellos que realizan estos calculos. Sin embargo, lo joven que es la compensacion dela biodiversidad en la aplicacion significa que se conoce poco sobre como las valoraciones de la biodiversidady los contratos de compensaciones entre los sitios de desarrollo y compensacion son acordados en la practica,o sobre los resultados a largo plazo de la conservacion. Examinamos como se hicieron equiparables los sitios ycomo las ganancias o el redito de la biodiversidad fueron calculados y negociados para un contrato especıficode compensacion en un estudio piloto de la compensacion de la biodiversidad dirigido por el gobiernoen Inglaterra. A lo largo de 24 meses observamos a los participantes de varias etapas de la negociacionde los contratos de compensacion por medio de visitas (anonimas) repetidas a tres sitios de contrato de
∗email [email protected] submitted August 23, 2016; revised manuscript accepted February 19, 2017.
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproductionin any medium, provided the original work is properly cited.
1053Conservation Biology, Volume 31, No. 5, 1053–1065C© 2017 The Authors. Conservation Biology published by Wiley Periodicals, Inc. on behalf of Society for Conservation Biology.DOI: 10.1111/cobi.12917
1054 Biodiversity Offsetting
compensacion de la biodiversidad. Realizamos 50 entrevistas semi-estructuradas a los accionistas en elgobierno regional y local, al sector privado y a la sociedad civil. Utilizamos un programa de software deanalisis cualitativo de datos (DEDOOSE) para analizar textualmente las transcripciones de las entrevistas.Tambien comparamos las repeticiones sucesivas del calculo de la compensacion de la biodiversidad en lashojas de calculo y en los documentos de planeacion. Un enfoque particular fueron las repeticiones diferentesde la valoracion de un impacto especıfico sobre la biodiversidad en el que se uso la medida compensadorade la biodiversidad desarrollado por el Departamento de Ambiente, Alimentos y Asuntos Rurales del ReinoUnido. Tuvimos tres hallazgos principales. Primero, las medidas compensadoras de la biodiversidad fueronmodificadas de formas creativas conforme los usuarios adaptaban los resultados a los calculos de las medidaspara balancear y negociar los requerimientos conflictivos. Segundo, la practica de la elaboracion de diferenteshabitats equivalentes a sı mismos por medio de la aplicacion de las medidas compensadoras de la biodiver-sidad resulto en la equiparacion de los resultados que podrıan no proporcionar ganancias proyectadas dela conservacion. Tercero, la presion por crear valor para el dinero disminuyo los reditos proyectados de laconservacion.
Palabras Clave: equiparacion, etnografıa, Piloto Ingles de Compensacion de la Biodiversidad, polıtica de con-servacion, redito de la biodiversidad, valor
Introduction
In recent years the mitigation practice of biodiversityoffsetting (BDO) and associated conservation policyframeworks have expanded globally to secure con-servation investment from infrastructure development(Carroll et al. 2008; Quintero & Mathur 2011; Ben-abou 2014). Preceded by wetland mitigation bankingand species banking in the United States from the1970s and 1990s respectively (e.g., Fox & Nino-Murcia,2005; Robertson & Hayden 2008; Pawliczek & Sulli-van 2011), BDO is a relatively new conservation tech-nology. This means that there are few detailed casehistories of offset implementation or of actual, as op-posed to projected, conservation outcomes. We thusexamined the application of BDO in England under a2-year pilot study by the Department of Environment,Food and Rural Affairs (DEFRA) to assess the proposal thatapplication of the DEFRA technical metric standardizesassessments of biodiversity value so as to offer robustnumerical foundations on which to base planning fordevelopment and offset sites in England.
We reviewed studies of BDO, focusing on the develop-ment and application of metrics that create comparablemeasures of biodiversity so as to demonstrate measur-able gains (or yields) in biodiversity value. In researchingthe BDO pilot in England (2012–2014), we focused onthe application in practice of DEFRA’s biodiversity offsetmetrics. Over 24 months, we documented negotiationsand calculations that gave rise to a specific BDO contract,set within a broader data set of site visits, interviews, bio-diversity impact calculations, and grey-literature planningdocuments for 6 DEFRA BDO pilot sites in England (dataheld by L.C.).
Shaping the Calculation of Biodiversity Yield
Biodiversity offsetting policy and best practice guidelines(BBOP 2009, 2012; DEFRA 2012a, 2012b, 2013; Gardner
et al. 2013) are intended to support biodiversity conserva-tion outcomes by providing methodologies for the techni-cal calculation and apparent quantification of biodiversityvalues. Such methods aim to determine commensurablelosses and gains in biodiversity at different sites,thereby creating the possibility of offset compensation.Biodiversity offsets inevitably pertain to 2 separate sites.They constitute quantitative biodiversity gains reflectedas units or credits beyond a baseline over time at an offsetsite. These predicted biodiversity gains compensate forbiodiversity unit losses at a development site and shouldbe additional to a projected counter-factual scenario inthe absence of compensation (Bull et al. 2014; Tuckeret al. 2014). Following the wording of a respondent inour research, we use the term “biodiversity yield” todescribe projected gains in calculated biodiversity values.
A variety of metrological approaches exist for calculat-ing and creating equivalence between biodiversity lossesand gains at different sites and temporal moments. Inapplication, these are normally linked to the use of a stan-dardized reference system for the classification of habitatsor land cover (Quintero & Mathur 2011). In the UnitedKingdom, the basis for such calculations is the biodiver-sity offset metric developed by DEFRA (2012b), discussedin more detail below. Habib et al. (2013:1313–1314)state that “[e]xchanging dissimilar biodiversity elementsrequires assessment via a generalized metric” and therepresentation of biodiversity units by an appropriatelyfungible currency or system of credits. An aim of BDOis thus to standardize state and private-sector BDO audit-ing methods so as to improve and stabilize approachesconsidered ad hoc in practice (Gardner 2013: 1254). It isnoticeable, however, that these standardizing assessmenttechniques and metrics are themselves proliferating, suchthat direct comparisons of offset quality between con-texts becomes difficult. This phenomenon has also beenobserved for assessment methods in carbon accounting(Lohmann 2009; Lippert 2014). Tensions between ease
Conservation BiologyVolume 31, No. 5, 2017
Carver & Sullivan 1055
Table 1. Habitat scoring system for biodiversity offsetting in England.∗
Biodiversity distinctiveness
Habitat condition low (2) medium (4) high (6)
Good (3) 6 12 18Moderate (2) 4 8 12Poor (1) 2 4 6
∗Source: DEFRA (2012b).
of compliance for development interests and robustnessof conservation gain in terms of measurable biodiversityyield (Maron et al. 2012) make studies of applied BDO rel-evant for understanding how these tensions are workedout in practice.
English Biodiversity Offsetting Pilot
Along with the United States, Australia, South Africa, andGermany, England is considered at the forefront of devel-oping BDO. In England, BDO has been enthusiasticallyendorsed at the ministerial level (DEFRA 2013) and in anumber of recent environmental-policy documents andreports (e.g., Lawton et al. 2010; DEFRA 2011; NPPF2012). A DEFRA BDO pilot project ran for 2 years fromApril 2012 to April 2014 and involved 6 local planningauthorities (Devon, Doncaster, Essex, Greater Norwich,Nottinghamshire, and Coventry, Warwickshire, and Soli-hull) as well as private-sector organizations (e.g., DEFRA2012a; Apostolopoulou & Adams 2015; Carver 2015).
Key to the DEFRA BDO pilot was the metric for numer-ically scoring the harm to biodiversity by a developmentand then scoring the possibilities for onsite and offsitemitigation of this harm (Table 1). These numerical scoresenable the calculation of commensurable losses and gainsof biodiversity in development and potential offset sites(DEFRA 2012b; Hannis & Sullivan 2012; Sullivan 2013). Inapplying the metric, development sites are first “mappedand divided into habitat parcels” (DEFRA 2012b: 7)and then classified according to the habitat designationsof the Joint Nature Conservation Committee, a publicbody that advises the U.K. central and devolved govern-ments on nature conservation (http://jncc.defra.gov.uk).These mapped and classified sites are then scored ac-cording to their observed condition and biodiversity dis-tinctiveness with the scoring matrix of the BDO metric(Table 1). Distinctiveness is determined based on theguidelines in Treweek et al. (2010) and especially onspecies richness, diversity, rarity, and the unique poten-tial for the area to support species rarely found else-where (DEFRA 2012b). The habitat condition grades areadapted from the Higher Level Agri-Environment Scheme(HLS) Farm Environment Plan Manual (FEP). A habitattype scored as in good condition (specific to habitattype within the FEP but usually based on percent cover
Table 2. Categories and subcategories (abbreviations in parenthe-ses) of stakeholders interviewed regarding biodiversity offsetting inEngland.
Category Subcategory
Regional and localgovernment
1. local planning authority (LPA)2. natural England (NE)
Private sector 3. developer (DEV)4. consultant ecologist (CE)5. planning consultant (PC)
Civil society 7. conservation and wildlife NGO (NGO)8. local resident (LR)9. landowning offset provider (OP)
of indicator species, for example, cover of undesirablespecies <5%) with high distinctiveness (incorporatingrarity and endemism) would be assigned the highest nu-merical score. The metric thus aligns a numerical scorefor an area’s ecological distinctiveness with a score forits condition. Scores for an area of habitat range from 2(lowest distinctiveness and condition) to 18.
Methods
We observed how biodiversity calculations and valua-tions were made for a 2-year pilot study of BDO led byDEFRA from 2012 to 2014. Field research followed threephases and was based primarily on repeat site visits to DE-FRA pilot and voluntary offset sites as well as analysis andcomparisons of associated policy and planning texts andsuccessive biodiversity impact assessment (BIA) spread-sheets. We conducted 50 semistructured interviews with30 key actors, organized into three stakeholder categories(regional and local government, the private sector andcivil society) and nine subcategories (see Table 2) (seeSupporting Information for interview questions). In re-ferring to interview transcripts below, stakeholder cat-egories for the DEFRA pilot sites are numbered 1 to 5(as a sample of the 6 local planning authorities [LPA]that took part in the pilot), and the complementary vol-untary pilot offsetting site is denoted by a “comp” pre-fix. Sequential codes for interviewees follow the formatof stakeholder category, followed by site number, theindividual within that site, and date of interview (e.g.,LPA2.3 130515 means the third individual interviewedwithin the LPA stakeholder category at pilot site 2, onMay 13, 2015). We conducted structured textual analysisof interview transcripts with DEDOOSE, a cloud-basedqualitative data-analysis program that facilitates deductiveand inductive coding of text excerpts to enable assess-ment of overarching themes and perspectives (Sullivan &Hannis 2015). All respondents and offsetting cases wereanonymized.
From June 2013 to January 2014, we interviewed indi-viduals from the ecology or green infrastructure depart-ments of county or district councils where pilot sites had
Conservation BiologyVolume 31, No. 5, 2017
1056 Biodiversity Offsetting
been established (see Supporting Information for inter-view questions). Following interviews, we selected 2 ofthe DEFRA pilot sites for the compilation of detailed casestudies. Our selection was based on the availability ofbiodiversity impact as well as receptor site biodiversityunit calculations (in this case study) and on the treat-ment of protected species (in the second selected casestudy) (Carver forthcoming). An additional private-sectorDEFRA pilot offset site was also selected for comparisonwith a developer-led voluntary biodiversity offset initia-tive. From January 2014 to January 2016, we made re-peated site visits to observe BDO-related scoring activitiesand negotiations at the 3 sites, conducted semistructuredinterviews, and examined planning documents and BIAs.This triad of methods formed the basis of our 3 detailedcase histories that tracked the design and developmentof offset contracts in England from 2013 to the present(data held by L.C.). A third and ongoing research phaseentailed textual analysis of documents connected withBDO policy in England, interviews of participants in otherlocal government, nongovernmental, and private-sectoroffset efforts (i.e., projects not part of the DEFRA pilotstudy). These interviews were categorized by stakeholdertype and analyzed as for interviews of stakeholders in theDEFRA pilot study. The scope and depth of these casestudies and space limitations mean that, while drawingon perspectives and findings derived from the broaderdata set, for this paper we focused on the negotiatedcalculations of development and offset locations that ledto one particular BDO contract.
We examined the process used to make biodiversitycalculations so that biodiversity values could be referredto in terms of losses or gains (or yields) and prices couldbe assigned to different sites in the offset agreement fora particular offset contract. These values and prices werenegotiated over 32 months from March 2013 to Decem-ber 2015. We drew on our multiple sources of data todescribe the development site and to present in detailthe metric calculations in the BIA applied to the devel-opment and offset sites. We focused on the negotiationprocess that ensued regarding the levels of mitigation andcompensation payments required and on the biodiversityyields projected to arise from these transactions. The orig-inal format of the BIA Excel spreadsheet (version 17.4) isin Supporting Information. At the time of writing, localgovernment ecologists were using version 18 of the BIA.The different iterations of the BIA affected the scores ofvalues arising from its application independently of thebiophysical dimensions of the areas being assessed.
Results
The Development Case
A planning application was submitted for delivery of 200residential properties, a sports stadium, and playing fields
across 13 ha of mostly agricultural fields. Under the guid-ance of the DEFRA BDO pilot and with the assistanceof a private offsetting brokerage firm, the developmentbecame subject to BDO compensation payments in linewith the calculated value of affected biodiversity at thedevelopment site. The proposed development site con-sisted largely of amenity grassland, improved grassland,hedgerows, scattered tall ruderal vegetation, and 4 ponds,one with great crested newts (Triturus cristatus), whichare protected under the Conservation of Habitats andSpecies Regulations 2010. The site formed the south-western fringe of a small medieval market town and wasbordered to the north by an industrial and residentialdevelopment and to the west and east by roads withopen countryside beyond. The planning application wassubmitted in March 2013 by the property owners, thelocal football and bowls clubs, and a large residentialdeveloper who would oversee the bulk of the planningprocess and build, market, and sell the residential prop-erties. Under new requirements shaped by the DEFRABDO pilot study, the local planning authority asked thedeveloper to apply the DEFRA metric, in the form of a BIA,to guide the biodiversity mitigation and compensationmeasures required to offset the development.
The Biodiversity Impact Assessment (BIA)
The developer’s consultant ecologists completed site sur-veys and used existing records to provide information onthe condition and distinctiveness of the habitats consid-ered represented at the development site. These recordsformed the basis of an ecological impact assessment re-port for the planning application. Subsequently, to es-tablish the site’s biodiversity unit baseline and mitigationvalues in the format necessary for BDO under the DEFRApilot, the contents of the ecological impact assessmentreport were translated into a BIA by an LPA ecologist andthe offset broker assisting the LPA with the contract. Theecological condition and proposed mitigation actions atthe development site were determined by entering theexisting (i.e., pre-development) habitat scores into theBIA produced by the County Council planning-authorityecologist. The BIA spreadsheet operationalized the DE-FRA BDO metric to yield biodiversity unit scores for eachhabitat type on the development site.
To arrive at these scores the development site wasfirst categorized by the LPA ecologist into habitat typesentered on separate rows of the BIA spreadsheet, eachwith a code, description, size, and numerical score forhabitat distinctiveness and condition (Table 3 & Support-ing Information). The spreadsheet allowed 3 sets of cal-culations. The first (see Table 3 rows 15–28) generated ahabitat impact score (HIS) for the total scored habitat onsite prior to the development (46.68 biodiversity units,cell O53).
Conservation BiologyVolume 31, No. 5, 2017
Carver & Sullivan 1057
Tabl
e3.
Spre
adsh
eet(
vers
ion1
7.4,
draf
t1)
used
inbi
odiv
ersi
tyim
pact
asse
ssm
ents
toca
lcul
ate
the
resi
dual
loss
esof
biod
iver
sity
from
deve
lopm
enti
mpa
cts
ata
spec
ific
site
.a
AB
CD
EF
GH
IJ
KL
MN
O
11
12
Exi
stin
gh
abit
ats
on
site
Ha
bit
at
dis
tin
ctiv
enes
sH
abit
at
con
dit
ion
Ha
bit
ats
tobe
reta
ined
wit
hn
och
an
gew
ith
indev
elopm
ent
Ha
bit
ats
tobe
reta
ined
an
dre
store
dw
ith
indev
elopm
ent
Ha
bit
ats
tobe
lost
wit
hin
dev
elopm
ent
13
T.n
ote
bh
abit
at
code
ph
ase
Ih
abit
at
des
crip
tion
Ha
bit
at
are
a(h
a)
dis
tin
ctiv
enes
ssc
ore
con
dit
ion
score
are
a(h
a)
exis
tin
gva
lue
are
a(h
a)
exis
tin
gva
lue
Are
a(h
a)
exis
tin
gva
lue
14d
irec
tim
pac
tsan
dre
tain
edh
abit
ats
AB
CA
×B
×C
=D
EA
×B
×E
=F
GA
×B
×G
=H
15F1
B4
gras
slan
d:i
mp
rove
dgr
assl
and
1.78
low
2m
od
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e2
1.78
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16P
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nd
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nd
ing
wat
er0.
01h
igh
6go
od
30.
010.
14
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and
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pro
ved
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slan
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10lo
w2
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ate
23.
1012
.40
18F2
C31
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slan
d:a
men
ity
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slan
d0.
18lo
w2
mo
der
ate
20.
180.
70
19B
ow
ling
gree
nJ1
2gr
assl
and
:am
enit
ygr
assl
and
0.12
low
2p
oo
r1
0.12
0.24
20F6
J12
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d:a
men
ity
gras
slan
d0.
97lo
w2
po
or
10.
971.
94
21W
est
of
foo
tbal
lgri
dB
4gr
assl
and
:im
pro
ved
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slan
d0.
08lo
w2
goo
d3
0.08
0.48
25n
/ab
uilt
envi
ron
men
t:b
uild
ings
/h
ard
stan
din
g
0.32
no
ne
0p
oo
r1
0.32
0.00
26F3
B4
gras
slan
d:i
mp
rove
dgr
assl
and
4.88
low
2m
od
erat
e2
4.88
19.5
2
27Sl
urr
yp
itG
1w
etla
nd
:sta
nd
ing
wat
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igh
6p
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r1
0.01
0.05
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B4
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d:i
mp
rove
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assl
and
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od
erat
e2
1.52
6.08
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l12
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tal
0.00
0.00
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648
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H47
site
hab
itat
bio
div
ersi
tyva
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8J
48In
dir
ect
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acts
,in
clu
din
go
ffsi
teh
abit
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lue
of
loss
fro
min
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ect
imp
acts
c
49B
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reo
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ter
imp
act
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efo
re51
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er52
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l0.
00M
0.00
HIS
=J+
M53
hab
itat
imp
act
sco
re(H
IS)
46.6
8
Con
tin
ued
Conservation BiologyVolume 31, No. 5, 2017
1058 Biodiversity Offsetting
Tabl
e3.
Cont
inue
d.
AB
CD
EF
GH
IJ
KL
MN
O
11
12
Exi
stin
gh
abit
ats
on
site
Ha
bit
at
dis
tin
ctiv
enes
sH
abit
at
con
dit
ion
Ha
bit
ats
tobe
reta
ined
wit
hn
och
an
gew
ith
indev
elopm
ent
Ha
bit
ats
tobe
reta
ined
an
dre
store
dw
ith
indev
elopm
ent
Ha
bit
ats
tobe
lost
wit
hin
dev
elopm
ent
13
T.n
ote
bh
abit
at
code
ph
ase
Ih
abit
at
des
crip
tion
Ha
bit
at
are
a(h
a)
dis
tin
ctiv
enes
ssc
ore
con
dit
ion
score
are
a(h
a)
exis
tin
gva
lue
are
a(h
a)
exis
tin
gva
lue
Are
a(h
a)
exis
tin
gva
lue
54C
auti
on
:Des
tru
ctio
no
fh
abit
ats
of
hig
hd
isti
nct
iven
ess,
e.g.
low
lan
dm
ead
ow
or
anci
ent
wo
od
lan
d,m
ayb
eag
ain
stlo
calp
olic
y.H
asth
em
itig
atio
nh
iera
rch
yb
een
follo
wed
,can
imp
act
toth
ese
hab
itat
sb
eav
oid
ed?
An
yu
nav
oid
able
loss
of
hab
itat
so
fh
igh
dis
tin
ctiv
enes
sm
ust
be
rep
lace
dlik
efo
rlik
e.
55 56P
rop
ose
dh
abit
ats
on
site
(on
-sit
em
itig
atio
n)
Tar
get
hab
itat
dis
tin
ctiv
enes
sT
arge
th
abit
atco
nd
itio
n
Tim
eti
llta
rget
con
dit
ion
Dif
ficu
lty
of
crea
tio
no
rre
sto
rati
on
Hab
itat
bio
-d
iver
sity
valu
e
57p
has
eI
hab
itat
des
crip
tio
nh
abit
atar
ea(h
a)d
isti
nct
iven
ess
sco
reco
nd
itio
nsc
ore
tim
esc
ore
dif
ficu
lty
sco
re
58h
abit
atcr
eati
on
NO
PQ
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×O
×P
)/Q
/R59
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n/a
Bu
ilten
viro
nm
ent:
bu
ildin
gso
rh
ard
stan
din
g
2.27
no
ne
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oo
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5ye
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low
10.
00
60F1
&F6
n/a
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ilten
viro
nm
ent
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en(l
awn
and
pla
nti
ng)
0.76
low
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r1
5ye
ars
1.2
low
11.
27
61F2
,F3,
F4n
/ab
uilt
envi
ron
men
t:b
uild
ings
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and
ing
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no
ne
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oo
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5ye
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1.2
low
10.
00
62F2
,F3,
F4n
/ab
uilt
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ron
men
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rden
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and
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low
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ars
1.2
low
12.
23
63J1
2gr
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and
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low
14.
07
64A
rea
4B
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assl
and
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mi-i
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rove
dn
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and
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med
ium
4go
od
315
year
s1.
7m
ediu
m1.
53.
58
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rea
3G
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nd
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nd
ing
wat
er0.
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igh
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od
315
year
s1.
7m
ediu
m1.
50.
92
66A
rea
1B
22gr
assl
and
:se
mi-i
mp
rove
dn
eutr
algr
assl
and
0.16
med
ium
4go
od
315
year
s1.
7m
ediu
m1.
50.
75
67G
1w
etla
nd
:sta
nd
ing
wat
er0.
05h
igh
6go
od
315
year
s1.
7m
ediu
m1.
50.
35
Con
tin
ued
Conservation BiologyVolume 31, No. 5, 2017
Carver & Sullivan 1059
Tabl
e3.
Cont
inue
d.
AB
CD
EF
GH
IJ
KL
MN
O
11
12
Exi
stin
gh
abit
ats
on
site
Ha
bit
at
dis
tin
ctiv
enes
sH
abit
at
con
dit
ion
Ha
bit
ats
tobe
reta
ined
wit
hn
och
an
gew
ith
indev
elopm
ent
Ha
bit
ats
tobe
reta
ined
an
dre
store
dw
ith
indev
elopm
ent
Ha
bit
ats
tobe
lost
wit
hin
dev
elopm
ent
13
T.n
ote
bh
abit
at
code
ph
ase
Ih
abit
at
des
crip
tion
Ha
bit
at
are
a(h
a)
dis
tin
ctiv
enes
ssc
ore
con
dit
ion
score
are
a(h
a)
exis
tin
gva
lue
are
a(h
a)
exis
tin
gva
lue
Are
a(h
a)
exis
tin
gva
lue
68La
nd
scap
eA
112
wo
od
lan
d:
bro
adle
aved
pla
nta
tio
n
0.16
med
ium
4go
od
332
+ye
ars
3m
ediu
m1.
50.
43
69A
rea
2B
22gr
assl
and
:se
mi-i
mp
rove
dn
eutr
algr
assl
and
0.19
med
ium
4go
od
315
year
s1.
7m
ediu
m1.
50.
89
70B
22gr
assl
and
:se
mi-i
mp
rove
dn
eutr
algr
assl
and
0.73
med
ium
4m
od
erat
e2
15ye
ars
1.7
med
ium
1.5
2.29
71T
ota
l13
.01
ERR
OR
:to
tala
rea
of
hab
itat
scr
eate
dm
ust
equ
alto
tala
rea
of
hab
itat
slo
st72
Hab
itat
rest
ora
tio
nex
isti
ng
valu
eS
(=
F)
((N
×O
×P
)-S)
/Q
/R
88T
ota
ltr
adin
gd
ow
nco
rrec
tio
nva
lue
0.00
89h
abit
atm
itig
atio
nsc
ore
(HM
S)16
.78
90H
BIS
-HM
S=
HIS
91h
abit
atb
iod
iver
sity
imp
act
sco
re−3
1.90
92p
erce
nta
geo
fb
iod
iver
sity
imp
act
loss
65.5
3
aN
um
ber
sa
cross
row
s1
5–2
8a
rem
ult
ipli
edto
pro
du
ceth
eh
abit
at
bio
div
ersi
tyva
lue
for
each
coded
are
asu
bje
ctto
dev
elopm
ent.
Nu
mber
sa
rero
un
ded
to2
dec
ima
lpla
ces
an
da
ssu
chif
calc
ula
ted
ma
nu
ally
her
em
ay
pro
du
cedif
fere
nt
resu
lts.
Th
esu
mof
the
valu
esin
colu
mn
Ofo
rro
ws
15
–28
(sh
ow
nin
cell
O5
3)
isth
ebio
div
ersi
tyba
seli
ne
of
the
ha
bit
at
impa
ctsc
ore
(HIS
).In
row
s5
9–7
0n
um
ber
sa
cross
row
sa
rem
ult
ipli
edto
pro
du
ceth
eh
abit
at-m
itig
ati
on
score
(HM
S)(c
ell
O8
9),
wh
ich
isth
eva
lue
of
ha
bit
ats
tha
tw
ill
be
rest
ore
dor
crea
ted
on
site
soa
sto
mit
iga
teor
min
imiz
epro
ject
edbio
div
ersi
tylo
sses
.Th
eori
gin
alsp
rea
dsh
eet
isin
Support
ing
Info
rma
tion
.bTa
rget
are
aa
sh
abit
at
pa
rcel
ssu
bje
ctto
impa
cts
coded
on
the
dev
elopm
ent
site
ma
ps
(see
Fig.
1a
).c L
eft
empty
on
ori
gin
alB
IA.
Conservation BiologyVolume 31, No. 5, 2017
1060 Biodiversity Offsetting
The second set of calculations (Table 3 rows 59–70)yielded a habitat-mitigation score (HMS) for the total num-ber of biodiversity units to be restored or created on siteso as to mitigate or minimize projected biodiversity losses(16.78 units, cell O89). A notable feature of this HMS isthat almost 40% of on-site mitigation was projected tobe delivered through creation of a number of footballpitches of different sizes. The spreadsheet showed thefootball pitches contributed substantial amounts of on-site biodiversity unit value and had the largest spatialhabitat value of all mitigation activities. This mitigationvalue was to be achieved by attributing biodiversity valueto the amenity grassland of the pitches themselves (cellO63) and by allowing the perimeter surface area of theproposed grassy margins to grow unmowed and therebyto provide 0.73 ha of semi-improved grassland (cell O70).Although receiving low habitat scores for both distinc-tiveness (2) and habitat condition (1), the size of thefootball pitches amenity grassland meant that in 5 yearsthis aggregate spatial area was calculated to contribute4.07 units (Fig. 1). After 15 years, the grassy marginswould contribute a further 2.29 units cell. In total, then,the football pitches would eventually make up 6.36 unitsof biodiversity value of 16.78 units of total on-site mitiga-tion and habitat creation.
The third set of calculations, through comparison ofscores from the first and second calculation sets, yieldedthe residual biodiversity net loss. This value indicatedhow many biodiversity units would need to be purchasedfor mitigation purposes if an additional off-site offset wereneeded. This net loss or gain value was the habitat bio-diversity impact score (HBIS) generated by subtractingHIS from HMS. The HBIS was calculated as an overallloss of 31.90 biodiversity units (Table 3, cell O91). It isthis calculated biodiversity value that required an off-siteoffset to satisfy planning requirements for mitigation ofon-site development impacts on biodiversity.
The Offset Site
Interviews showed that established conservation non-governmental organizations (NGOs) and Wildlife Trustswere typically perceived as possessing the “experienceand expertise to ensure delivery” (LPA2.1 020714) ofoffsets, and as being familiar and experienced with con-tracted management and improvement of habitat. Theoffset site identified by the council for the supply ofscored offset units comparable to the HBIS score abovewas a 5-ha grassland meadow 5 km northeast of the de-velopment, acquired by a local wildlife and conservationNGO in 2013. The site consisted of a meadow of species-rich, semi-improved grassland in close proximity to alocal site of special scientific interest (SSSI). The site sup-ported 5 orchid species, including the largest populationof greater butterfly orchid (Plantanthera chlorantha)in the county. It also supported 4 of the county’s 6 rare
farmland butterflies, 3 of which (grizzled skipper [Pyrgusmalvae], dingy skipper [Erynnis tages], and white-letterhairstreak [Satyrium w-album]) are designated as biodi-versity priority species under the 2007 U.K. BiodiversityAction Plan. At the time of assessment the NGO was notinvesting in much active management of the site due tolimited funding, despite the site’s excellent ecologicalenhancement potential (NGO5.1 241114).
A BIA was conducted for the offset site to calculateits baseline and projected biodiversity values. This BIAindicated the NGO had intended to bring the grasslandto a moderate condition but with the offset paymentsfrom the developer would be able to fully restore thesite and thus provide a lowland meadow of national im-portance (Fig. 1). These improvements would therebydemonstrate conservation additionality (NGO5.1 OffsetSite Draft Management Plan 112013). It was hoped thatwith appropriate interventions 2 other rare farmland but-terflies, also designated nationally as biodiversity priorityspecies, would establish colonies on the site (NGO 5.1Offset Site Draft Management Plan November 2013).
To achieve this conservation additionality, the pre-dicted biodiversity yield was quantified and the cost wasestimated according to a management plan to be carriedout by the offset provider. The BDO Draft ManagementPlan was written by the NGO conservation officer. Costsincluded NGO volunteer and paid staff and external con-tractor workforces, materials, and capital or lease pay-ments for the land itself (NGO5.2 280115). The predictedbudget for improvement and 30 years of managementat the offset site totaled £204,076, of which £98,030would come from the conservation NGO budget and£106,046 from the biodiversity offset payment made bythe developers (NGO5.1 Offset Site Draft ManagementPlan 112013). The developer would pay a further 20%for brokerage fees (OB5.1 241114) and legal fees for ar-ranging the contracts among parties (NGO5.2 280115).
Negotiating Biodiversity Calculations
Tracing successive calculations of HMS, HIS, and HBISscores showed additionally that the costs arrived at abovewere also the outcome of negotiations between stake-holders. These negotiations frequently involved changingthe numerical scores in the first BIA for the developmentsite. Over the course of the planning process, the calcu-lated baseline biodiversity value of the development sitewas reduced by almost 48% from 48.68 units in BIA draft1 (Table 3 & Supporting Information) to 25.52 units indraft 2. This decrease in habitat value occurred throughcategory changes to the condition of existing habitats.
Changes made to the condition values of the baselinehabitats on site and identified through comparisons ofdrafts of the BIA excel sheets had dramatic effects onfinancial compensation requirements (Table 4). Thesechanges included lowering the perceived condition of
Conservation BiologyVolume 31, No. 5, 2017
Carver & Sullivan 1061
Figure 1. Map of development site in the United Kingdom (a) before and (b) after development.
Conservation BiologyVolume 31, No. 5, 2017
1062 Biodiversity Offsetting
4.88 ha of improved grassland on the development sitefrom moderate to poor condition such that the BIA F3baseline value of 19.52 in Table 3 (cell O26) became9.76 units. The adjustment to the condition score con-stituted a 50% reduction of baseline biodiversity valuefor this area. Because of this habitat parcel’s size thissingle modification amounted to an almost 20% overallreduction to the baseline biodiversity unit value for theentire development site. The same process was appliedto improved and amenity grasslands in different areas.Whether these modifications increased or decreased thefinal compensation costs of development-planning appli-cations was built into the numerical adjustments that tookplace. Other iterations to the BIA over the course of thepilot study included adding category values to the BDOmetric (Table 1) with the odd numbers 1, 3 and 5 forlocal habitat types that had greater regional than nationaldistinctiveness and rarity (NGO5.1 241114), as well asextensive formatting changes and numerous editions tomake the calculator more user friendly and manageable(OB5.2 050114).
One explanation for these modifications is that localplanning authorities had a relatively limited ability todetermine the exact condition of the habitats under con-sideration. Only a few habitats were visited and verifiedby a county ecologist (LPA5.2 241114) because of thewidespread shortage of ecological expertise within localgovernments more generally (NGO 270116, NGOComp1290116). Often the ecological data were assembled andcross-referenced remotely against data in the ecologicalassessment report and biological and historical data heldby the council offices at the district council’s BiologicalRecords Centre. Indeed, the good quality and extensivescope of the ecological data held by the county counciland the size of the county’s ecological team were consid-ered anomalous in this case (LPA5.2 241114).
Underlying the overall downward recalculation of thedevelopment site’s baseline value from 48.68 to 25.52units, however, was a view that the first BIA calculationswould create too large a future compensation package,thereby threatening the financial viability of the devel-opment (DEV5.1 060315). The initial calculation for thebiodiversity offset compensation package was £300,000.The developer and the local planning authority met andthe baseline habitat condition assessments for many areason site were adjusted downward to produce the newfigure of 25.52 biodiversity units in the second draft(Table 4). Described as “ . . . something we could livewith” (DEV5.1 060315), the ensuing revised cost for thefinal compensation package was £120,000.
Discussion
Our case study provides an in-depth history of the assess-ments, calculations, and negotiations of biodiversity and
financial values for a BDO compensation contract. Thiscase illustrates several problems for biodiversity conser-vation predicted in the theoretical literature on BDO.We considered 3 problems in particular and focused ontheir broader implications for biodiversity conservationthrough the implementation of BDO.
First, evidence from repeat site visits to this and otherpilot offsetting sites in England over 24 months (data heldby L.C.) showed that making the DEFRA metric applicableto real-life planning cases is a process of constant iterationand trial and error. Our BDO case history illustrates inparticular how metrics for deciding biodiversity valuesat development and off-site mitigation sites are beingredesigned during application and are generating numer-ical values that are then further negotiated and adjusted.Instead of acting as technical means for the standardizedproduction of impartial and objective calculations basedon observed site characteristics, the new metrics associ-ated with BDO design and recommendations are beingused differently by different actors with competing inter-ests in negotiations. Such differences in application maybe appropriate in response to real-world complexities,but they conflict with the stated aims in BDO policy de-sign for standardization and comparability. The nexus ofcompeting development, conservation, and LPA interestsmeant that biodiversity values calculated through appli-cation of the metric were adjusted downward to facilitatea compensation package that was cheaper for develop-ers. In a similar case at another development site, thedevelopment firm negotiated a reduction in biodiversityoffset compensation from £300,000 to £90,000 (DEV5.1060315) (also see the example in Sullivan [2013]). Aspredicted in theory (Walker et al. 2009; Hannis & Sullivan2012), then, these case studies seem consistent with con-cerns that an emphasis on market values for biodiversityconservation and compensation will encourage develop-ers, as purchasers of impact compensation, to push pricesdownward so as to lower their costs. In doing so, boththe quality and quantity of conservation yield throughBDO may also be reduced.
Second, our case shows how the commensuration pro-cess works in practice to make different habitats equiva-lent to each other through the application of BDO metrics(Tables 1 and 3). Numerical indicators form proxies forqualitatively different ecological assemblages, calculatedwith the aid of the DEFRA biodiversity metric as repre-sented by the BIA Excel spreadsheet calculations. Some-times these commensuration processes generated unin-tuitive outcomes. It was unclear, for example, how thesports pitches, with 6.36 units of biodiversity value, wasequivalent to 6.36 units of high-quality grassland habitatthat supports a range of biodiversity-action-plan speciesat the offset site. The proposed mitigation value of thesports pitches, determined to be habitats of low distinc-tiveness and poor condition, was achieved because theywere the largest habitat type within the development.
Conservation BiologyVolume 31, No. 5, 2017
Carver & Sullivan 1063
Tabl
e4.
Nego
tiate
dch
ange
sin
calc
ulat
edbi
odiv
ersi
tyba
selin
eun
itva
lues
betw
een
biod
iver
sity
impa
ctas
sess
men
t(BI
A)dr
afts
1an
d2.
The
habi
tatc
odes
inth
efir
stco
lum
nre
late
toth
eha
bita
tco
des
inFi
g.1a
.
Dis
tin
ctiv
enes
sC
on
dit
ion
BIA
ha
bit
at
code
Ha
bit
at
des
crip
tion
Are
a(h
a)
cate
gory
cha
nge
score
cha
nge
cate
gory
cha
nge
score
cha
nge
Ori
gin
alu
nit
valu
edra
ft1
New
un
itva
lue
dra
ft2
Red
uct
ion
inu
nit
valu
e(%
)
F1im
pro
ved
gras
slan
d1.
78n
on
en
on
em
od
erat
eto
po
or
2to
17.
123.
5650
P1
wet
lan
dst
and
ing
wat
er0.
01n
on
en
on
ego
od
tom
od
erat
e3
to2
0.14
0.01
93
F2im
pro
ved
gras
slan
d3.
10n
on
en
on
em
od
erat
eto
po
or
2to
112
.40
6.20
50
F2ta
llru
der
al0.
18n
on
en
on
em
od
erat
eto
po
or
2to
10.
700.
3550
Bo
wlin
ggr
een
amen
ity
gras
slan
d0.
12n
on
en
on
en
on
en
on
e0.
240.
240
F6am
enit
ygr
assl
and
0.97
no
ne
no
ne
no
ne
no
ne
1.94
1.94
0W
est
of
foo
tbal
lgr
idim
pro
ved
gras
slan
d0.
08n
on
en
on
ego
od
tom
od
erat
e3
to2
0.48
0.32
33
F3im
pro
ved
gras
slan
d4.
88n
on
en
on
em
od
erat
eto
po
or
2to
119
.52
9.76
50
Slu
rry
pit
stan
din
gw
ater
0.01
hig
hto
low
6to
2n
on
en
on
e0.
050.
0260
Par
to
fF4
and
F5im
pro
ved
gras
slan
d1.
52n
on
en
on
em
od
erat
eto
po
or
2to
16.
083.
0450
To
tal
48.6
825
.52
48
Conservation BiologyVolume 31, No. 5, 2017
1064 Biodiversity Offsetting
Table 5. Biodiversity units calculated for football pitches as amenitygrassland at the development site compared with an equivalent area ofspecies-rich semi-improved grassland at the offset site.
Development site Offset site
Size (ha) 2.44 (3.8 full-sizefootball pitches)
0.64
Habitat type(qualitativecategory)
amenity grassland species-richsemi-improvedgrassland(lowlandmeadow)
Biodiversity units 4.07 5.48
This outcome shows how the numerical abstractions in-herent in the English BDO process can lead to large areasof low value for biodiversity becoming commensuratewith small, unique areas of high biodiversity value (Sul-livan 2013; Carver 2015) (Table 5). The packaging offootball pitches as habitat for on-site mitigation reducedthe financial compensation value in the final offset cal-culations by decreasing offset unit requirements by anequivalent number of biodiversity units.
Finally, elements of these 2 problems suggest that thepressure to create value for money (i.e., more conserva-tion gains for less money) in compensation strategies forconservation may be pushing BDO in directions that favorthe growth of market values and exchanges for offsetunits, but that may work against the robust generationof conservation value (Hannis & Sullivan 2012; Dauguet2015). Observations in our case study confirm this ten-dency. For example, although conservation NGOs wereconsidered convenient offset providers by district coun-cils (LPA5.1 010215),councils also recognized that toachieve market liquidity in offset units private landown-ers would have to play a significant role. Indeed, a bar-rier to the development of BDO in England has beena shortage of offset sites from which to purchase bio-diversity offset credits, as confirmed in DEFRA’s pilotevaluation report (Baker et al. 2014). The local authorityin our case thus forged partnerships with organizationsthat could assist in stimulating and brokering a greatersupply of offset credits and receptor sites through privatelandowners. High transaction costs for site identificationand preparation and legal fees are fostering economies ofscale by bringing offset provision together with the eco-nomically astute ways that large commercial landownerscan manage their farms (OB5.2 020315 and as predictedby Sullivan and Hannis [2015]). This is expected to resultin a better supply of offset credits from newly formedhabitat banks. Emerging offset brokerage firms hope thata high supply of offset credits will improve credit-supplycompetition and result in cheaper prices for developersseeking compensation. It is this combination of commer-cial outlook, farmer experience, and land managementthat makes the corporate broker now partnering with
the county council confident that with this approachthey can produce a “good biodiversity yield per hectare”across multiple sites (OB5.2 020315). In doing so, BDOis becoming further aligned with commercial agricul-tural productivity agendas that emphasise efficienciesand scale of production (i.e., agricultural yield).
The case we examined was of a biodiversity offset to beprovided directly by a conservation NGO to a local plan-ning authority. Despite months of preparation and con-siderable staff costs, the developer eventually rejectedthe proposed offset site in favor of developing an offsetarrangement with the farmer issuing the land for develop-ment in the first place (OB5.1 140116). The calculationsand negotiations presented here are nonetheless valuableas a detailed example of how the DEFRA metric is be-ing applied to biodiversity assessments at different sites.In tracking, documenting, and analyzing the calculationsand negotiations in this and other cases, we observed thatalthough BDO applies technical and apolitical practicesto calculate equivalence and commensurability betweensites of biodiversity damage and conservation investment,in practice the process is subject to frequent changes tothe input values of the metrics and valuation criteria tobalance these in order to meet the conflicting interests ofstakeholders. As such, instead of confining the decision-making process to a neutral calculative and technicalframework, the process opens up avenues through whichstakeholders can negotiate, and sometimes struggle over,specific outcomes (Coralie et al. 2015; Sullivan & Han-nis 2015). As suggested by Walker et al. (2009:149), theconcern is that “biodiversity protection interests will failto counter motivations for officials to resist and relaxsafeguards to facilitate exchanges and resource devel-opment at cost to biodiversity.” Application of scoringpractices that create numerical values may help stimu-late greater compensation payments for biodiversity lossin the English planning system and elsewhere, therebysupporting greater biodiversity outcomes (although seeCarver 2015). Obscured within these technical calcula-tion practices, however, and as predicted by Salzman andRuhl (2000), are additional value judgments and strugglesover arriving at the perceived right numerical values thatstraddle competing demands such that they are economi-cally palatable, politically pragmatic, and ecologically co-herent. Whether or not biodiversity yields are achievedthrough these negotiations depends on the bargainingpowers of stakeholders, beyond the application of stan-dardized practices to calculate and commensurate biodi-versity losses and gains.
Acknowledgments
We thank the respondents interviewed in this studyand gratefully acknowledge support from the Lever-hulme Trust (award RP2012-V-041) and from colleagues
Conservation BiologyVolume 31, No. 5, 2017
Carver & Sullivan 1065
in the Leverhulme Centre for the Study of Value(www.studyofvalue.org).
Supporting Information
The interview guide for semistructured interviews(Appendix S1) and the original development site BIA(version 17.4) of 27 June 2013 (Appendix S2) are avail-able online. The authors are solely responsible for thecontent and functionality of this material. Queries (otherthan absence of the material) should be directed to thecorresponding author. Appendix S2. Original develop-ment site Biodiversity Impact Assessment (BIA) v17.4,27 June 2013 (Source: OB5.1 140714, reproduced withpermission).
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Conservation BiologyVolume 31, No. 5, 2017