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Journal of Cleaner Production xxx (xxxx) 142079
Contents lists available at ScienceDirect
Journal of Cleaner Production
journal homepage: www.elsevier.com/locate/jclepro
Glaring gaps in tools to estimate businesses’biodiversity impacts hinder
alignment with the Kunming-Montreal global biodiversity framework
Yingtong Zhu a,⁎, Graham W. Prescott b, Patricia Chu c, Luis R. Carrasco a
aDepartment of Biological Sciences, National University of Singapore, 14 Science Drive 4, Singapore, 117543, Republic of Singapore
bThe Biodiversity Consultancy, 3E King's Parade, Cambridge, CB2 1SJ, United Kingdom
cMana Impact, 6 Battery Road, Singapore, 049909, Republic of Singapore
ARTICLE INFO
Handling Editor: Tomas B. Ramos
Keywords:
Biodiversity conservation
Business sustainability
Post-2020 global biodiversity framework
Business biodiversity impacts
Corporate biodiversity footprint analysis
Gap analysis
ABSTRACT
The Kunming-Montreal Global Biodiversity Framework, in a first-time move, calls for companies and financial in-
stitutions to measure and report their impacts on biodiversity. While many tools that measure businesses' biodi-
versity footprints have recently emerged (“biodiversity indices”), it is unclear whether they really allow compa-
nies to measure what the Global Biodiversity Framework requires. Identifying gaps in biodiversity indices con-
cerning the GBF would aid businesses and strengthen its implementation. To fill this gap, here we assessed the
degree of the alignment between the indices and the Global Biodiversity Framework. The businesses’biodiver-
sity indices identified by the European Union Business @ Biodiversity Platform and the Taskforce for Nature Fi-
nancial Disclosures were selected. A semi-quantitative gap analysis was applied to compare their capabilities
against the metrics extracted from the Global Biodiversity Framework. The glaring gaps were found in existing
biodiversity indices in the coverage of the metrics needed to support the implementation of the Global Biodiver-
sity Framework by businesses. Metrics related to ecosystem integrity, connectivity and restoration, nature-based
solutions, sea use change, aquatic biodiversity, genetic diversity and resources, the territory and knowledge by
Indigenous Peoples, and urban green and blue spaces were insufficiently addressed by most available biodiver-
sity indices. There is an urgent need to develop integrated biodiversity indices if businesses are to effectively
measure and disclose their impacts on biodiversity in a way more consistent with the Global Biodiversity Frame-
work.
1. Introduction
Biodiversity is changing rapidly and dynamically, including both
gains and losses, yet biodiversity losses have been identified to exceed
planetary boundaries (Steffen et al., 2015). Current extinction rates are
at least tens to hundreds of times higher than the background extinction
rate (Ceballos et al., 2015). As a result, approximately one million
species of animals and plants are facing extinction with around 25% of
species in assessed groups threatened (Brondizio et al., 2019). Biodiver-
sity loss is multi-dimensional and goes however beyond species
(Lyashevska and Farnsworth, 2012), encompassing functional diversity
and genetic diversity loss, and loss in ecosystem multifunctionality. The
resulting loss in functional diversity may erode ecosystem function (Pan
et al., 2016), undermine ecosystem stability and ultimately lead to their
irreversible collapse (MacDougall et al., 2013).
The three objectives of the Convention on Biological Diversity
(CBD) are the conservation of biological diversity, the sustainable use
of the components of biodiversity and sharing of the benefits arising
from the utilization of genetic resources (CBD, 2022). To achieve these
objectives, the Kunming-Montreal Global Biodiversity Framework
(GBF) was adopted during the fifteenth meeting of the Conference of
the Parties (COP 15) of the CBD. The framework has four long-term
goals and 23 targets to achieve the 2050 vision: biodiversity is valued,
conserved, restored and wisely used, maintaining ecosystem services,
sustaining a healthy planet and delivering benefits essential for all peo-
ple (CBD, 2022). The GBF proposes specific sub-targets progressing to-
wards positive biodiversity outcomes and brings new biodiversity con-
servation aspects compared to its predecessor, the Aichi Biodiversity
Targets (Table S1). For instance, the GBF places emphasis on ecological
connectivity, nature-based solutions, spatial planning addressing land
and sea use change, Indigenous and traditional territories and urban
green and blue spaces. Importantly, for the first time, the GBF explicitly
calls transnational companies and financial institutions for regular
monitoring, assessment, and transparent disclosure of the risks, depen-
⁎Corresponding author.
E-mail address: yingtong.zhu@u.nus.edu (Y. Zhu).
https://doi.org/10.1016/j.jclepro.2024.142079
Received 16 October 2023; Received in revised form 20 March 2024; Accepted 1 April 2024
0959-6526/© 20XX
Note: Low-resolution images were used to create this PDF. The original images will be used in the final composition.
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Y. Zhu et al. Journal of Cleaner Production xxx (xxxx) 142079
dencies and impacts on biodiversity along their operations, supply and
value chains and portfolios.
Concomitantly, there is an increasing realization that tackling the
biodiversity crisis necessitates increased joint efforts from businesses.
While businesses and biodiversity are interdependent and sustain each
other (Destailleur, 2022), businesses are facing ever-increasing biodi-
versity-related risks. There is a lack of disclosure of business biodiver-
sity impacts, while those that do disclose biodiversity impacts do so
mostly qualitatively (Addison et al., 2019). The GBF's call for business
to act chimes with a growing number of businesses committed to ambi-
tious biodiversity targets. This trend catalysed the demand for credible
tools to measure businesses' impacts on biodiversity, which could also
be applied to financial institutions and enable them to assess the biodi-
versity risks of their investment portfolio (Lammerant et al., 2022).
To support the need for business to measure their biodiversity im-
pacts, some biodiversity tools have been recently developed
(Lammerant et al., 2022). Hereafter “biodiversity index”was defined as
a tool that allows estimation of the impact of business on biodiversity
using a combination of quantitative metrics, datasets and models. The
main platform to support biodiversity impact reporting by businesses is
the Taskforce for Nature Financial Disclosures (TNFD), which provides
an overview of biodiversity indices to measure businesses' biodiversity
impacts. Some available biodiversity indices for business are, for exam-
ple, the Global Biodiversity Score (GBS) that evaluates the footprint of
businesses on biodiversity, breaking down impacts across the value
chains (Biodiversité, 2020), the Corporate Biodiversity Footprint (CBF)
that calculates the direct biodiversity impacts from companies’prod-
ucts or processes (Iceberg Data Lab, 2022) or the Species Threat Abate-
ment and Restoration (STAR) that quantifies the contribution that in-
vestments can make to stem species losses (Mair et al., 2021). Many of
these biodiversity indices apply metrics such as the Mean Species Abun-
dance (MSA) and Potential Disappeared Fraction of species (PDF) as
common currencies that can be applicable in different contexts.
Reviews of tools for measuring businesses' biodiversity impacts have
been recently conducted. Damiani et al. (2023) reviewed the methods
and models for biodiversity impact assessment in life-cycle assessment
(LCA) based on previous reviews. Among them, Crenna et al. (2020) re-
viewed the impacts of value chains on biodiversity from an LCA per-
spective, and Winter et al., 2017 analysed how biodiversity was cov-
ered or integrated in LCA. Curran et al. (2016) evaluated the perfor-
mance of both LCA and non-LCA models but only focused on land use
change impact. These reviews, however, have focused on LCA without
delving into the biodiversity indices available. There is thus a lack of
comparative reviews of biodiversity indices that can be employed by
businesses. As a result, it is hard for businesses to navigate a rapidly
evolving field and for researchers to understand where businesses'
needs may lay. More importantly, given the fundamental role of the
GBF in businesses’biodiversity impacts measurement, it is essential to
examine to what extent the available biodiversity indices can assess im-
pacts of businesses on the different aspects of the GBF. Identifying cur-
rent gaps in biodiversity indices with regards to the GBF would help
support businesses and reinforce the implementation of the GBF.
To fill these existing gaps, a gap analysis of GBF metrics and targets
against a selection of biodiversity indices was developed to answer: (1)
How do the available biodiversity indices compare in terms of capabili-
ties offered to businesses? (2) To which degree do the biodiversity in-
dices align with the metrics and targets of the GBF? and (3) What are
the main gaps in coverage of the metrics and targets by these indices?
This review assessed current biodiversity indices for the first time and
can assist businesses to choose biodiversity indices to enhance the qual-
ity of their disclosures on their biodiversity impacts. Bridging the tar-
gets of the GBF and businesses' assessment and reports can further fos-
ter the integration and implementation of the GBF into businesses’deci-
sion-making processes towards sustainability. Enhanced integration be-
tween the GBF and businesses can, ultimately, be an important step in
mitigating the biodiversity crisis.
2. Methods
2.1. Extraction of metrics from the GBF
From the 23 targets in the GBF, this study selected the targets that
covered reducing threats to biodiversity, sustainable use of biodiversity
and tools as well as the solutions for implementation and mainstream-
ing of biodiversity conservation. As a result, the first 18 targets were se-
lected (Table S2). For each target, the “metrics”were identified based
on the following criteria: (1) metrics are variables that should be di-
rectly derived from the targets; (2) metrics should be measurable; (3)
metrics should be related to biodiversity conservation, the sustainable
use of biodiversity and sharing of the benefits from utilization of ge-
netic resources; and (4) metrics should not overlap with each other. In
case of overlap, metrics were merged into a single metric. 30 metrics
were identified and categorised into several fields: ecosystems (4 met-
rics), area-based conservation (5 metrics), species (2 metrics), genetics
(3 metrics), human-nature relations (5 metrics) and risks and opportu-
nities (11 metrics) (Table S3).
2.2. Selection of biodiversity indices
To select appropriate biodiversity indices to be assessed, the study
filtered those included in the Assessment of Biodiversity measurement ap-
proaches for businesses and financial institutions by the EU Business @
Biodiversity Platform (EU B@B) (Lammerant et al., 2022) and those in
the TNFD tool catalogue. These two repositories were chosen as the EU
B@B represents an authoritative official source to develop strategies to
integrate biodiversity considerations into businesses’operations and
TNFD is probably the main framework for biodiversity impact recog-
nized globally by business. The following criteria were used: (1) the
biodiversity index should comprise a set of quantitative metrics,
datasets and models in a way that can be used as a tool to estimate bio-
diversity impacts, i.e. datasets or models in isolation were excluded; (2)
it should have a focus on biodiversity impacts estimation (e.g. indices
intended for carbon emissions estimation, water pollution or natural
capital accounting without an explicit focus on biodiversity were ex-
cluded); (3) it should be science-based, supported by scientific evi-
dence, methods or research as a foundation; (4) it should be able to
evaluate the impacts of businesses on biodiversity at the business level;
(5) it should be open-source in a way that can be directly adopted by
businesses themselves, i.e. the products or services provided commer-
cially by other consultancy companies without disclosing their specific
methods were excluded; and (6) it should have sufficient accessible
documentation for the assessment.
The study identified several modelling aspects and intended use of
the biodiversity indices for categorization. These were, namely, the in-
tended scale of application and the direct drivers of biodiversity loss
considered (land use change, climate change, direct exploitation, pollu-
tion and invasive alien species). The models underpinning the biodiver-
sity indices were also summarised (Table S4).
2.3. Gap analysis
To assess the alignment of the biodiversity indices with the GBF, a
table with the GBF metrics in rows and biodiversity indices in columns
was generated. For each biodiversity index, the authors checked if it ex-
plicitly considered each identified GBF metric. This was done by revis-
ing information that the biodiversity index covers, the criteria it
screens, its calculation methods and its functions, practices and applica-
tions in real-world case studies from the available documentation. If the
2
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Y. Zhu et al. Journal of Cleaner Production xxx (xxxx) 142079
metric was explicitly mentioned in the documentation of the index, a
score of 1 was assigned, if not, a score of 0 was assigned instead.
To assess how well a biodiversity index covered the metrics, for each
biodiversity index, the authors calculated the proportion of the metrics
it covered out of the total number of metrics as , the performance
score of the indices in covering metrics. To assess how well a metric
was covered by the biodiversity indices, for each metric, the authors
calculated the ratio of the number of biodiversity indices covering
that metric and the total number of indices as , as the coverage of
the metrics by the indices (Table 1).
Subsequently, a table with the biodiversity indices in rows and the
GBF targets in columns was developed to assess how well an index cov-
ered a target. The authors first identified the targets in which the met-
rics were covered by this biodiversity index. Each of these targets could
have one or more metrics, and the biodiversity index might cover only
some of these metrics. Hence, in each square in the table, the authors
calculated the proportion of the metrics covered by a biodiversity index
in the targets that this index is involved in, as an alignment score, to re-
flect the degree to which this index met that target. The authors then
summed the alignment scores across the indices for each target and di-
vided them by the number of indices to obtain the proportion of indices
that met the target, as the coverage of the target by the indices. Like-
wise, the authors also summed the alignment scores across the targets
for each index and divided them by the number of targets to obtain the
proportion of targets that the index met, as the performance score of the
index in covering the targets (Table 1).
Because the targets that have multiple metrics might be harder to
cover than those with a single metric, two other scenarios were addi-
tionally considered: (1) scenario 1: as long as the index covered at least
one of the metrics in a target, it was considered to cover the target; (2)
scenario 2: only when the biodiversity index covered all of the metrics
Table 1
Summary of the generated indicators for quantitatively evaluating the perfor-
mance of the biodiversity indices in covering the GBF metrics and Targets,
and how well these metrics and Targets were covered.
Indicator Calculation Meaning
Performance score of
a biodiversity index in
covering the metrics:
the proportion of the
metrics covered by an
index
Coverage of a metric
by the biodiversity
indices: the proportion
of the indices that
covered a metric
Alignment Score
between an index and
a target: the proportion
of the metrics covered
by an index in a target
that this index is
involved in
summed
across targets
for each
index, divided
by the total
number of
targets
Performance score of
a biodiversity index in
covering targets: the
proportion of the
targets covered by an
index
summed
across indices
for each
target,
divided by
the total
number of
indices
Coverage of a target
by the biodiversity
indices: the proportion
of the indices that
covered a target
in a target, the target was considered as covered. A score of 1 was as-
signed if a biodiversity index covered a target, otherwise, a score of 0
was assigned.
This gap analysis allowed quantifying the alignment between the
biodiversity index and the GBF. All the visualisations above were con-
ducted in R v.4.2.3 (R Core Team, 2023).
3. Results
16 tools out of the 29 tools in EU B@B and 13 out of 145 in TNFD
were filtered, and there was a total of 17 indices after duplicates were
removed (Table 2). They differed in targeted levels of application as
well as the coverage of the direct drivers of biodiversity loss. Company
level was the most frequent intended scale (10 out of 17), followed by
product and process (including supply option) levels. Only PBF and BISI
covered all the five direct drivers of biodiversity loss. The indices were
not considered to cover the metric ecological integrity, despite that most
of them applied MSA or PDF that are deemed as measurement of eco-
logical intactness, as ecological integrity is complex and not equal to in-
tactness (Table 2).
EXIOBASE, GLOBIO and ReCiPe were the models that underpinned
most biodiversity indices, among which GLOBIO was the most fre-
quently used, supporting seven biodiversity indices (B-INTACT, BFC,
BFM, BIM, BNGC, CBF & GBS), followed by ReCiPe supporting 6 biodi-
versity indices (BFC, BFFI, BFM, BIM, Bioscope & PBF), and EXIOBASE
supporting GBS, BFFI & Bioscope (Table 2 &Fig. S2).
3.1. Gaps in the coverage of the metrics by the biodiversity indices
The coverage of the metrics by the biodiversity indices varied across
the metrics. Metric 28 (risks, dependencies and impacts on biodiversity
along the operations, supply and value chains and portfolios) were covered
by all indices. This is expected as biodiversity indices were designed for
corporations (Fig. 1a).
3.1.1. Key drivers of biodiversity loss
Two key drivers of biodiversity loss, Metric 6 (land and sea use
change), and Metric 25 (climate change and ocean acidification), had
prominently high coverage rates of 71% (Fig. 1a). They were more fre-
quently covered by the indices than the other three drivers, pollution
(metric 23), invasive species (metric 22) and exploitation (metric 15),
which had the coverage rate of 53%, 41% and 41% respectively (Fig.
1a). However, all the biodiversity indices that covered metric 6 only
considered land use but neglected sea use, despite they were mentioned
in parallel in Target 1 of the GBF. For metric 25, many biodiversity in-
dices involved climate change, while ocean acidification and the im-
pacts of climate action on biodiversity were barely covered. Metric 15
was derived from 5 out of 18 Targets, yet as mentioned, its coverage
rate was much lower than metrics 6, 25, 23 and 28 that were derived
from only one to three targets (Fig. 1a). This indicates the dispropor-
tionate coverage of the metrics by the indices relative to the emphasis
from the GBF Targets.
3.1.2. Ecosystem integrity, connectivity and restoration
Ecosystem aspects, including metric 1 (ecological integrity), metric 2
(ecological connectivity) and metric 3 (ecological restoration) were poorly
addressed. Metric 1 was not covered by any of the indices despite the
frequent use of MSA, except SEED, which applied reference area ap-
proach to calculate terrestrial integrity (Fig. 2). Metrics 2 and metric 3
had low coverage, 29% and 24% respectively. Nevertheless, metric 4
(ecosystem functions and services) had comparatively high coverage
(41%), possibly because of its broad scope.
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Y. Zhu et al. Journal of Cleaner Production xxx (xxxx) 142079
Table 2
Summary of the filtered biodiversity indices.
Index name (short
name)
Description Target Level Underpinning model &
Calculation Method
Direct drivers of
biodiversity loss
Source
Global Biodiversity
Score® (GBS) &
GBS®for financial
institutions (GBS-FI)
Evaluates the impacts of companies and investments on
biodiversity, covering the pressures: land use,
fragmentation of natural ecosystems, human
encroachment, atmospheric nitrogen deposition, climate
change, hydrological disturbance, wetland conversion,
freshwater eutrophication, land use in catchment and
ecotoxicity (experimental)
Company, the
whole value chain
from cradle to
grave
MSA from GLOBIO or
EXIOBASE
Land use, climate
change & invasive
species
Biodiversité, 2020;
Lammerant et al.
(2022)
Corporate Biodiversity
Footprint (CBF)
Calculates a company's direct biodiversity impact (Scope
1), the impact of its electricity suppliers (scope 2), its
upstream and downstream impacts (Scope 3), the
underlying environmental impact of a company's
product or processes and the overall impact at portfolio
level
Company, product,
portfolio & process
MSA from GLOBIO Land use, climate
change & invasive
species; pollution was
added in a case study
Iceberg Data Lab,
2022;Lammerant et
al. (2022)
Species Threat
Abatement and
Restoration metric
(STAR)
Quantifies business, governments and civil society's
potential contributions to stemming global species loss;
measures the change in risk of species extinction by
measuring the contribution that investments can make to
reduce species extinction risk via mitigating existing risk
factors and assessing contributions of habitat restoration
Company, sector,
project & site
Integrated
Biodiversity Assessment
Tool (IBAT), Exploring
Natural Capital
Opportunities, Risks and
Exposure (ENCORE)
Land use, exploitation
& invasive species
Mair et al. (2021);
Lammerant et al.
(2022)
Product Biodiversity
Footprint (PBF)
Assesses the impacts of products and services, and
provides indicators for each of the five drivers of
biodiversity loss throughout the value chain
Products &
services
PDF
ReCiPe/LCA/LCIA
Land use,
exploitation, climate
change, pollution &
invasive species
Asselin et al. (2020);
Lammerant et al.
(2022)
Biodiversity Footprint
Methodology (BFM)
Assesses the impacts of a range of businesses to compare
biodiversity improvement options; determines changes
in biodiversity due to human impact pressures, including
terrestrial land use, climate change, water extraction,
aquatic emission of nitrogen and phosphorus emission to
water
Company,
sector
product (could be
extended to site &
supply chain)
MSA from GLOBIO,
GLOBIO-Aquatic,
ReCiPe/LCA
Land use, climate
change & pollution
(emission to water)
Plansup (2018);
Lammerant et al.
(2022)
Biodiversity Footprint
Calculator (BFC)
The simplified operational webtool of the full BFM;
identify which parts of a company's' chain contribute
most to the biodiversity footprint, focusing on land use
and greenhouse gas emissions
Company &
product
BFM,
MSA from GLOBIO,
GLOBIO-Aquatic,
ReCiPe/LCA
Land use, climate
change;
Pollution &
exploitation were
added in a case study
Plansup (2018);
Lammerant et al.
(2022)
LIFE Key Quantifies organizations' impacts on natural resources;
calculates and monitor through time the pressure from
business ‘activities on biodiversity via the Biodiversity
Pressure Index (BPI) including the GHG index, energy
index, area index, land use index and water index, and
the Biodiversity Minimum Performance (BMP) required
on conservation to offset the impact
Company & supply
options,
Three metrics:
Biodiversity Pressure
Index (BPI), Biodiversity,
Minimum Performance
(BMP), Biodiversity
Positive Performance
(BPP)
Land use, climate
change, pollution
(waste generation
and destination);
invasive species was
added in a case study
LIFE Institute, 2018;
Lammerant et al.
(2022)
Biodiversity Indicators
for Site-based
Impacts (BISI)
Aggregates biodiversity impact and performance data at
the site level to provide indicators of biodiversity
management performance at the corporate level, using
the state-pressure-response framework
From Site to
Corporate
Integrated Biodiversity
Assessment Tool (IBAT)
Land use,
exploitation, climate
change, pollution &
invasive species
UNEP-WCMC, 2020;
Lammerant et al.
(2022)
Biodiversity Net Gain
Calculator (BNGC)
Quantifies land use related biodiversity value on
operational sites of a company, actual and potential
biodiversity value of the different spatial units of the site
by means of a metric built on extent, condition and
significance.
Company MSA from GLOBIO Land use & invasive
species
Lammerant et al.
(2022)
Biodiversity Impact
Metric (BIM/CISL)
Assesses and tracks how businesses’sourcing affects
nature through biodiversity loss as a result of land and
habitat transformation for agricultural production and
the intensity of land use; compare the impacts of
different commodities and supply chains
Company,
agricultural
commodities &
supply chain
MSA from GLOBIO,
Biodiversity Intactness
Index (BII) from
Projecting Responses of
Ecological Diversity in
Changing Terrestrial
Systems (PREDICTS)
database
Land use &
exploitation
Cambridge Institute
for Sustainability
Leadership (CISL),
2020;Lammerant et
al. (2022)
LafargeHolcim or
Biodiversity
Indicator and
Reporting System
Holcim (BIRS/
Holcim)
Assesses the existing ecosystem services in a phase prior
to exploitation, during exploitation and after restoration;
Measures habitats and species condition by Biodiversity
Indicator and Reporting System and Long Term
Biodiversity index with an approach for measuring and
monetizing ecosystem services; assesses how habitats
(ecosystem assets) and social benefits from restoration
evolve over time (ecosystem services flows)
Company LBI (Long-Term
Biodiversity Index
Land use IUCN, 2014;
Lammerant et al.
(2022)
Bioscope Screens companies supply chains on impacts on
biodiversity; indicates the potential impact of the
commodity and upstream supply chain
Company products
& supply chain
EXIOBASE, ReCiPe/LCA Climate change, land
use & pollution
(focused on the first
two)
PRé Sustainability,
Arcadis & CODE,
2022;Lammerant et
al. (2022)
(continued on next page)
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Y. Zhu et al. Journal of Cleaner Production xxx (xxxx) 142079
Table 2 (continued)
Index name (short
name)
Description Target Level Underpinning model &
Calculation Method
Direct drivers of
biodiversity loss
Source
Biodiversity Footprint
for Financial
Institutions (BFFI)
Assesses environmental inputs and outputs,
environmental pressure, and biodiversity footprints of
companies' investment and economic activity's location
Portfolio,
investments within
an investment
portfolio (asset
class & balance
sheet)
PDF
EXIOBASE, ReCiPe/LCA,
ECOINVENT database
Pollution & climate
change
Netherlands
Enterprise Agency,
2021;Lammerant et
al. (2022)
SEED Measures the interconnectedness of nature, enables
governments, companies, and financial institutions to
quantify, monitor, and finance biodiversity at scale, with
measurement of biocomplexity including phylogenetic
diversity, functional diversity, species richness, species
evenness, ecosystem structure, connectivity and
disturbance
Site Climate change Crowther Lab
Biodiversity Integrated
Assessment and
Computation Tool
(B-INTACT)
Provides a thorough biodiversity assessment of project-
level activities in the agriculture, forestry and other land
use sectors, considering the impacts from land use
changes, habitat fragmentation, infrastructure and
human encroachment to measure the intended impacts
on the landscape and on agrobiodiversity
Project & site MSA from GLOBIO
Land use
FAO, 2021;
Lammerant et al.
(2022)
Agrobiodiversity Index
(ABDI)
Measures agrobiodiversity across three ‘pillars’for food
and agriculture industries: consumption and markets,
agricultural production, and genetic resource
conservation. Risk and resilience assessment of food
system actors' exposure to different risk areas
(malnutrition, poverty traps, climate change, land
degradation, pests and diseases, and biodiversity loss)
Companies,
projects Land use &
exploitation
Jones et al. (2021);
Lammerant et al.
(2022)
Biodiversity
Monitoring System
(BMS)
Monitors the impacts on biodiversity that are achieved
through certification of standards and labels for the food
sector, inducing the positive changes including reduction
of the direct pressures and risks on biodiversity, creation
and protection of habitats and increase of
agrobiodiversity
Actors in food
sectors Exploitation pollution
& invasive species
LIFE Food &
Biodiversity & Lake
Constance
Foundation;
Lammerant et al.,
2022
3.1.3. Biodiversity
The majority of the biodiversity indices only considered species di-
versity, overlooking the genetic aspect of biodiversity, despite that GBF
includes it prominently. Only SEED, ABDI and BMS covered metric 14
(genetic diversity within populations of wild and domesticated species), and
only ABDI (for agrobiodiversity) addressed metric 12 (utilization of ge-
netic resources, digital sequence information) and metric 13 (traditional
knowledge associated with genetic resources). These three metrics only
had a coverage of 18%, 6% and 6% respectively (Fig. 1a). Besides,
aquatic biodiversity was considered in only six biodiversity indices
(GBS, PBF, STAR, BFM, Bioscope & BFFI), while other indices only con-
sidered terrestrial biodiversity and neglected the freshwater, inland wa-
ter, coastal and marine realms.
3.1.4. Specificity and complete gaps
Some metrics were only covered by a single biodiversity index,
showing high specificity. In addition to metric 12 and metric 13 above,
metric 18 (effective management of human-wildlife interactions and coexis-
tence), metric 21 (natural hazards & disasters) and metric 24 (nutrient
loss, cycling and use) were only covered by B-INTACT, STAR and ABDI
respectively (Fig. 2).
Strikingly, in addition to the aforementioned metric 1, many metrics
were completely disregarded by the indices. Whist land use was fre-
quently covered, Recognizing the traditional territories of indigenous peo-
ples and local communities (metric 8) and green and blue spaces in urban
and densely populated areas (metric 9) were omitted in all indices. Metric
19 (human connection to nature) was not measured by any of the biodi-
versity indices. Metric 26 (biosafety measures & biotechnology) and met-
ric 27 (negative & positive incentives-subsidies harmful/beneficial for biodi-
versity conservation) also remained unaddressed (Figs. 1a and 2).
3.2. The performance of biodiversity indices in covering metrics
The number of metrics covered by each biodiversity index varied,
with an average coverage of 7.41 metrics. ABDI and STAR performed
best with the highest coverage rate of 43% and 40%, respectively, fol-
lowed by BMS and BISI (both 37 %). They were however still quite far
from an ideal biodiversity index that covered most of GBF's metrics. All
the other indices displayed relatively low coverage (all below 30%)
(Fig. 1b). While the index that covered most of the metrics was ABDI, it
was designated for agricultural production and agrobiodiversity, which
may limit its use in assessing biodiversity impacts from businesses in
other sectors and financial institutions.
3.3. Gaps in the coverage of the GBF's targets by the biodiversity indices
The targets differed substantially in the coverage rate, indicating an
overall unbalanced emphasis on the targets by the biodiversity indices.
Only a few specific targets were heavily covered, particularly Target 14,
which includes Strategic Environmental Assessments and Environmen-
tal Impact Assessment (EIA) were reached by all the indices in all cases
(Fig. 3,Fig. 4a, Fig. S3,Fig. S4a,Fig. S5 &Fig. S6a). The following was
Target 15 with a coverage by the indices of 53% (Fig. 4a). Though this
Target contained metric 28 that was covered by all the indices, it did
not show the highest coverage by the indices, because its other two
metrics, sustainable production (metric 15) and sustainable consumption
(metric 16) were merely covered by 35% and 24% of the indices respec-
tively (Fig. 1a).
Many other targets were not adequately covered, particularly Tar-
gets 12, 4, 13 and 17, with 20%, 19%, 19%, 6% and 0% of the indices
covering them respectively (Fig. 4a). The results changed when differ-
ent weights were assigned to the metrics and targets according to the
prevalence. Under Scenario 1, Target 15 (containing metric 28, 29 &
30) and Target 14 (containing metric 28) reached a full coverage by the
indices. Target 13 regarding genetic resources showed markedly low
5
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Y. Zhu et al. Journal of Cleaner Production xxx (xxxx) 142079
Fig. 1. The degree to which the metrics from GBF's targets were covered by the
biodiversity indices. (a) The coverage of the metrics by the indices, calculated
as the proportion of the indices that covered a metric. (b) The performance
score of the indices in covering metric, calculated as the proportion of metrics
covered by each index.
coverage by the indices (6%) (Fig. S3&Fig. S4a). Under Scenario 2,
strikingly, a large number of targets were not met by any of the biodi-
versity indices, and only Target 14 reached 100% coverage (Fig. S5 &
Fig. S6a). Further, Target 17 (biosafety and biotechnology) was not cov-
ered by any of the biodiversity indices in all scenarios.
3.4. The performance of the indices in aligning with the targets
The biodiversity indices significantly differed in the degree of align-
ment with the targets. ABDI covered 56% of the targets, followed by
BMS, STAR and BISI that covered 50%, 47% and 46% of the targets re-
spectively. BFC showed the lowest coverage (11%), and those of the
rest of the indices ranged from 16% to 41% (Fig. 4b).
Under Scenario 1, both ABDI and BISI presented considerable high
coverage rate (83%) of the targets, and STAR, GBS and BMS also kept
relatively good performance, with a coverage of 78%, 78% and 72% re-
spectively. BNGC and BFC showed low coverage, 28% and 22% respec-
tively, and the others’ranged from 33% to 61% (Fig. S4b).
Under Scenario 2, only ABDI presented remarkably high coverage
rate compared to other indices, completely meeting 39% of the targets.
BMS, STAR and LIFE had relatively high coverage, but all below 30%.
The coverage of the remaining indices was notably low, with seven of
them covering less than 6% of the targets (Fig. S6b).
4. Discussion
The analysis depicts glaring gaps in the tools available for compa-
nies to align with the GBF. A large proportion of the GBF's metrics such
as ecological integrity, connectivity and restoration, genetic diversity
and resources, aquatic diversity, urban green and blue spaces, Indige-
nous and traditional territories, and sustainable production and con-
sumption remained overlooked by the main available biodiversity in-
dices, leaving marked gaps in the alignment between these tools and
the GBF. Moreover, most of the biodiversity indices focused on terres-
trial biodiversity, overlooking freshwater, coastal and marine biodiver-
sity. Only six indices (GBS, PBF, STAR, BFM, Bioscope & BFFI) consid-
ered aquatic realms. These findings agree with previously identified im-
plementation gaps in conserving aquatic biodiversity (Barmuta et al.,
2011). Likewise, most indices covered land use change, whose measure-
ment and data could be more accessible, but all of them omitted sea use
change regardless of their equal importance in the GBF. Biosafety and
biotechnology were absent from all indices, while the emerging tools
and technologies (e.g., rapid sequencing, barcoding) now allow better
integration with them (Armstrong and Ball, 2005). Overall, the insuffi-
cient coverage of the GBF by the indices is likely to impair companies'
progress towards the GBF. The identified gaps call for urgent develop-
ment and expansion of biodiversity indices to support the implementa-
tion of the GBF.
Ecological integrity remained a conspicuous gap despite the applica-
tion of MSA in many biodiversity indices. MSA is a biodiversity intact-
ness indicator in the scenario-based model GLOBIO underpinning many
biodiversity indices to gauge impacts from environmental drivers on
biodiversity (Schipper et al., 2020). It however overlooks several as-
pects of biodiversity that are important in the GBF such as connectivity,
resilience and recovery of ecosystems, species extinction risk and the
degradation of genetic diversity. In addition, Nature-based solutions,
referring to the actions to protect, sustainably manage and restore nat-
ural or modified ecosystems (Cohen-Shacham et al., 2019;IUCN,
2012), also warrant emphasis as only the biodiversity indices GBS,
STAR, BISI and LafargeHolcim considered ecological restoration. The
lack of mention of nature-based solutions in these indices reflects we
still need deeper integration to facilitate the conservation and restora-
tion of natural ecosystems. Relatedly, only 5 out of 18 biodiversity in-
dices considered or measured ecosystem functions, which are necessary
for the restoration, maintenance and enhancement of ecosystem ser-
vices (Kelly-Quinn et al., 2020).
The biodiversity indices presented clear gaps in covering Indigenous
aspects. Recognizing the traditional territories of indigenous peoples
and local communities was missing in all indices, and traditional
knowledge from Indigenous peoples was only mentioned by one index.
Nevertheless, Indigenous traditional knowledge for sustainable devel-
opment (Segger and Phillips, 2015) and Indigenous Peoples' Rights to
Biodiversity (Posey, 1996) have been well recognized previously. In-
digenous Peoples are global stewards over one-quarter of lands
(Garnett et al., 2018), which contain 80% of Earth's remaining biodi-
versity (Sogbanmu et al., 2023). Their conceptualizations of nature sus-
tain and manifest CBD's 2050 vision vision (Reyes-García et al., 2022).
There is a need to include Indigenous aspects in business impact mea-
surements, including the recognition of their lands, rights and knowl-
edge for realistic and effective biodiversity conservation.
Among the five direct drivers of biodiversity loss, climate change
was widely considered. Conversely, ocean acidification, though is held
together with climate change in Target 8 of the GBF, was covered by
none of the biodiversity indices. The large and negative biological ef-
fects of ocean acidification as pervasive stressor on a variety of organ-
isms have been well recognized (Kroeker et al., 2013). Future work
6
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Y. Zhu et al. Journal of Cleaner Production xxx (xxxx) 142079
Fig. 2. The coverage of metrics by indices. Red squares indicate the biodiversity indices covered the metrics. (For interpretation of the references to colour in this fig-
ure legend, the reader is referred to the Web version of this article.)
Fig. 3. The alignment between the biodiversity indices and the GBF's targets. Alignment was calculated as the proportion of the metrics covered by an index in the
targets where the index covered at least one of the metrics.
could build upon the recently developed characterization factors of
ocean acidification, which can be applied in life cycle impact assess-
ment to fill this gap (Scherer et al., 2022).
Other drivers of biodiversity loss, such as invasive species and the
use, harvesting, exploitation and the trade of wild species were less cov-
ered by the indices, revealing an unbalanced emphasis on only a few
drivers of biodiversity loss. These gaps are concerning, considering that
the trade and exploitation of wildlife are the main driver of species ex-
tinction (Maxwell et al., 2016), and there is an agreement that invasive
species not only are a leading direct driver of biodiversity loss
(Brondizio et al., 2019;Díaz et al., 2019), but also poses risks to non-
market environmental goods and services (Andersen et al., 2004).
Only three indices (SEED, ABDI & BMS) covered genetic diversity.
Whilst there is a consensus that biodiversity is multifaceted and one in-
dicator cannot fully capture the multidimensional nature of biodiver-
sity (Molotoks et al., 2023), species diversity tends to capture most of
the attention. Disregarding less commonly used biodiversity dimen-
sions could hinder the estimation of companies’impacts on functional
and phylogenetic diversity, both indispensable components of biodiver-
sity (Hughes et al., 2008). For example, restoration with diverse geno-
types enhance the evolutionary potential of populations as well as
ecosystem functioning (Kettenring et al., 2014). Future developments
in biodiversity indices would thus need to incorporate multiple and
complementary biodiversity indicators (Marques et al., 2021;Purvis,
2020) in business impact assessments.
All the biodiversity indices addressed the monitoring, assessment,
and transparent disclosure of the risks, dependencies and impacts on
biodiversity from businesses. This indicates that the common intent of
these biodiversity indices is to support biodiversity impact reporting,
e.g., long-established processes like EIA. However, the approaches they
7
CORRECTED PROOF
Y. Zhu et al. Journal of Cleaner Production xxx (xxxx) 142079
Fig. 4. The degree to which the GBF's targets were covered by the biodiversity
indices. (a) The coverage of a target by the indices, calculated as the proportion
of the indices that covered a target. (b) The performance of a biodiversity index
in covering targets, calculated as the proportion of the targets that the index
covered.
adopt to estimate biodiversity impacts are too narrow to reflect the
complexities of biodiversity in a way that they align with the GBF.
A potential solution would be to expand biodiversity indices to in-
clude tools that can estimate companies’impacts on aquatic ecosys-
tems. For instance, the Freshwater Ecosystems Explorer assists to un-
derstand the state of freshwater ecosystems; HUB Ocean technologi-
cally provisions the ocean-related data; Ocean + brings together accu-
rate and up-to-date data and information on ocean biodiversity; the
GLOBIO-Aquatic model describes the effects of human-induced changes
to biodiversity of freshwater ecosystems Janse et al. (2015); ReCiPe
2016 can output a measure of damage to freshwater ecosystems
(Huijbregts et al., 2017). To overcome the gap in measuring sea use
change, companies could consider tools such as InVEST that could be
combined with spatially explicit maps and Geographic Information Sys-
tems tools to support maritime spatial planning (Willaert et al., 2019).
Some GBF metrics and targets such as Indigenous territories, due to
their qualitative nature, have not been routinely included in biodiver-
sity indices (Addison et al., 2019). Advancements in data availability
enable us to quantitatively measure some metrics that might be previ-
ously assessed based on qualitative approaches. For instance, the terres-
trial lands managed or owned by Indigenous Peoples globally have
been mapped (Garnett et al., 2018), and the Land Geoportal also pro-
vides geospatial data layers on Indigenous and community land rights,
which could be integrated into future biodiversity indexes.
The results can be used to complement new regulations on the re-
quirements of environmental impacts by companies. For example, the
recent Corporate Sustainability Reporting Directive (CSRD) in the EU re-
quires the corporations to disclose on all major environmental factors,
including their impacts and dependencies on and risks for biodiversity
and ecosystems, especially the undertakings relying on natural re-
sources (European Union, 2022). The Enhancement and Standardization
of Climate-Related Disclosures for Investors in the USA requires businesses
to report their climate-related risks across the value chain, but biodiver-
sity need to be further integrated (U.S. Securities and Exchange
Commission, 2024). To align with the GBF, it is necessary to scientifi-
cally refine the incorporation of the biodiversity components, such as
ecological integrity, connectivity, resilience, genetic diversity and
ecosystem services, in the global regulations and policies regarding cor-
porate environmental sustainability in light of the results. This integra-
tion will foster greater accountability and effectiveness in preserving
biodiversity while promoting sustainable business practices.
The analysis presents several limitations. First, it's not fully compre-
hensive as its scope was limited to the tools from the EU B@B and the
TNFD, meaning the biodiversity indices that are being developed or not
open source may be missed. Yet, given the authoritativeness of these
two sources, the most widely used biodiversity indices have been cap-
tured. The metrics developed from the GBF's targets could have been
chosen differently, and the study did not consider whether the indices
covered the metrics quantitatively or qualitatively, since once the met-
rics were explicitly included in the documentation of the indices, the
study considered them as covered. This study also remained focused on
biodiversity, but future research can consider the interactions and syn-
ergies between biodiversity and other issues (e.g., carbon and pollu-
tion) that may exert cascading effects and lead to a polycrisis. Future
biodiversity indices and tools would ideally consider the interactions
between multiple crises to better prepare business for future risks.
5. Conclusions
This review assessed, for the first time, the business biodiversity in-
dices, and shed light on the degree of their alignment with the GBF
leading to several unique results. Namely, the results reveal the specific
elements (metrics) of the GBF that are absent from these indices. This
could aid business in choosing the indices to enhance biodiversity im-
pact disclosures. Although there are several biodiversity indices avail-
able for businesses to measure their biodiversity impacts, given their
limitations, they cannot effectively help in achieving the GBF targets,
and businesses do not have ideal tools to align with the GBF. Many of
the GBF's targets were not covered by any of the indices, jeopardising
the efforts to conserve, restore and sustainably manage biodiversity.
Among the five drivers of biodiversity loss, invasive species and ex-
ploitation of organisms were less covered than the other three, despite
their importance. There remain other glaring gaps such as ecosystems
integrity, connectivity and restoration, nature-based solutions, sea use
change, aquatic biodiversity, genetic diversity and resources, the terri-
tory, knowledge and the sustainable use of biodiversity by Indigenous
Peoples, urban green and blue space, impacts of climate action on bio-
diversity, and sustainable production and consumption. This may be at-
tributed to the time gap: the GBF was newly released in 2022, while
many indices came out earlier, and thus they need to be updated ac-
cording to the GBF with new data and technologies to pave the way for
business to be able to properly disclose their impacts on biodiversity.
There is thus an urgent need to fill the missing gaps and develop inte-
grated biodiversity indices that align better with the GBF if business is
to contribute to stemming the biodiversity crisis effectively.
8
CORRECTED PROOF
Y. Zhu et al. Journal of Cleaner Production xxx (xxxx) 142079
CRediT authorship contribution statement
Yingtong Zhu: Writing –original draft, Methodology, Formal
analysis, Data curation. Graham W. Prescott: Writing –review &
editing. Patricia Chu: Writing –review & editing, Funding acquisi-
tion, Conceptualization. Luis R. Carrasco: Writing –review & edit-
ing, Supervision, Methodology, Funding acquisition, Conceptualiza-
tion.
Declaration of competing interest
The authors declare that they have no known competing financial
interests or personal relationships that could have appeared to influ-
ence the work reported in this paper.
Data availability
Data will be made available on request.
Acknowledgements
This work was supported by an Industry-Relevant PhD Scholarship
(IRP) from the National University of Singapore (NUS).
Appendix A. Supplementary data
Supplementary data to this article can be found online at https://
doi.org/10.1016/j.jclepro.2024.142079.
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