Aligning Biodiversity Measures for Business Sub-group 3B
Metrics and midpoint characterisation factors
Webinar
5 September 2019
Introduction of participants and reminder of the objectives and context of the Aligning Biodiversity Measures for Business initiative
Reminder of the objectives and terms of reference of the sub-group and of the webinar
Review of the SG3B position paper to finalize it for the Brazil workshop
Output #1 - Language mapping (30min)
Impacts persistent over time
Output #2 - Differences between metrics (30min)
Output #3B - Link between inventories of species and habitat and aggregated metrics approaches (15min)
Remaining open questions and discussions
Choice of dates for the next webinar
Agenda
Introduction of participants
Reminder of the objectives and context of the
Aligning Biodiversity Measures for Business initiative
Reminder of the objectives of the sub-group and of
the webinar
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What is this session about?
Mentimeter
1. Explore the differences between metrics and
midpoint calculations across different measurement approaches and the reasons for the current divergence.
Explore the difference between metrics and calculation intermediaries across different
measurement approaches and the reasons for the current divergence.
Objectives of the sub-group (and suggestion of
rephrasing)
2. Propose bridges between metrics (e.g. conversion factors or translation of characterisation factors in
different metrics) and propose common midpoint characterisation factors.
Propose bridges between metrics (e.g. conversion factors or translation of characterisation factors in
different metrics) and common characterisation factors.
Objectives of the sub-group (and suggestion of
rephrasing)
3. Identify how to disaggregate footprinting metrics and aggregate site level metrics, creating complementarity between the two.
Explore complementarity between aggregate metrics and metrics focused on elementary components of biodiversity (taxa, habitats)
Objectives of the sub-group (and suggestion of
rephrasing)
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Potential outcome of the sub-groups 3A and 3B: a (partial) harmonisation of inputs and calculation intermediaries facilitating conversions between metrics
Input data Calculation intermediaries
Impacts on biodiversity Initiative 1
Initiative 2 Initiative 3
Initiative 1
Initiative 2 Initiative 3
Corporate data input sub- group #3A
Metrics and midpoint characterisation
factors sub-group #3B
1. Mapping of the language of the LCA community with
language used to describe a more direct measurement of biodiversity. This mapping will comprise language used by LCA practitioners, EIA practitioners, biodiversity specialists and natural capital assessment (Natural Capital Protocol) and accounting
2. Analysis of differences between metrics and calculation intermediaries and reason for divergence
3. Exploration of:
a. Linkages between the different metrics and the different characterisation factors
b. How approaches focusing on aggregated metrics or elementary components of biodiversity can link and complement each other.
Expected outputs of the sub-group
Linkage of the sub-group with sub-group 3A on corporate data inputs
Input data
Sub-group 3A
Impacts on biodiversity
(endpoint)
Tools or approach
Secondary inventory data CF
& midpoints CF
Endpoints CF
Sub-group 3B
(characterisation factors)
① Company’s data
② Fall back data sets
Sub-group 3B (rationale of the different metrics)
Modeling of biodiversity impacts based on pressures and economic activityInput data Impacts on biodiversity
① Company’s data
② Fall back data sets
Direct evaluation of biodiversity impacts based on data on biodiversity state
Sub-group 3A
Sub-group 3B
(rationale of the
different metrics)
1. Review the SG3B draft position paper and provide feedback to validate it as input of the sub-group to the Brazil workshop.
2. Plan the next webinar on bridges between metrics.
Objectives of the webinar
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Questions? add them to the parking lot
Mentimeter
Review of the SG3B position paper to finalize it for
the Brazil workshop
REVIEW - Introduction
20190902_ABMB_SG3B-metrics-midpoints_position- paper_v2_04092019.docx
Sent by Julie Dimitrijevic on 4 th September
SG3B position paper
REVIEW – OUTPUT #1 - Language mapping
#1 - Midpoint: Strictly speaking, a midpoint is a point in the cause-effect chain (environmental mechanism) of a particular impact category.). In other words, it is an intermediary step in the calculation of impacts allowing to link input data to impact results. For example, if the endpoint is the loss of biodiversity linked to eutrophication at some point, then a midpoint could be nitrogen concentration.
#2 - Characterisation factor: Coefficients used in
calculations (e.g. the Global Warming Potential of methane is a characterisation factor which allows to calculate how much kg CO2-eq. is worth a kg of methane).
Definitions www.menti.com
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#3 - Inventory data: Data related to emissions and extraction of resources such as raw materials, water, land use and land conversion.
#4 - Activity data: The amount of material the organisation assessed extracts, produces, purchases or finances: for
instance the amount of cotton that goes into a T-shirt, or the amount a financial institution invests in a company.
#5 - Primary data: Inputs directly based on company data.
#6 - Secondary data: Data derived from external (sometimes global) data sets.
Definitions www.menti.com
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#7 – Endpoint: The final element that is being assessed, corresponding to ecosystem quality (e.g. quantified with local species loss integrated over time, in species.year) , resource scarcity or human health (e.g. quantified in
disability adjusted life years).
Definitions www.menti.com
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#8 - Impact driver: A measurable quantity of a natural resource that is used as an input to production (e.g., volume of sand and gravel used in construction) or a measurable non-product output of
business activity (e.g., a kilogram of NOx emissions released into the atmosphere by a manufacturing facility) (Natural Capital
Coalition, 2016).
#9 - Pressure: Driving forces lead to human activities such as transportation or food production, i.e. result in meeting a need.
These human activities exert 'pressures' on the environment, as a result of production or consumption processes, which can be divided into three main types: (i) excessive use of environmental resources, (ii) changes in land use, and (iii) emissions (of chemicals, waste, radiation, noise) to air, water and soil (Peter Kristensen 2014). Also called “direct drivers” of biodiversity loss by the International Panel on Biodiversity and Ecosystem Services (IPBES).
Definitions www.menti.com
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#10 – Impact on biodiversity: The negative or positive effect of business activity on biodiversity.
#11 - Input data: All the data fed as inputs to the different tools (cf. sub-group #3A).
#12 - Calculation intermediaries: All the items involved in modelling calculations between input data and impacts on biodiversity.
Definitions www.menti.com
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Language mapping – Table 1
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Associated NCP steps Natural Capital EIA Life Cycle Assessments Vocabulary used in SG3B’s position paper
Examples (non- exhaustive)
5 – Measure impact drivers and/or dependencies
Impact drivers
- Inputs
Inventory data
Activity data
Input data
Tons of wheat consumed
- Outputs
Primary inventory data
Tons of CO2 or CH4
emitted
Hectares of natural forest converted Secondary
inventory data
Calculation intermediaries Midpoints
Tons of CO2 equivalent
Pressures
Global Mean
Temperature Increase Land occupation Land transformation 6 – Measure changes in
the state of natural capital
Impacts on biodiversity Biodiversity endpoint Impacts on biodiversity
Number of species lost MSA.km2 or PDF.km2.yr lost
7 – Value impacts and/or dependencies
Impacts on industry and
society NA Loss of agricultural yield
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The EIA column is currently only partially filled. Inputs from sub-group #3B members are welcome to complete it.
Cf. SG3A:
Indicator: “A quantitative or qualitative factor or variable that provides a simple and reliable means to measure achievement, to reflect changes connected to an intervention, or to help assess the performance of a development actor”
Measure: an assessment of the amount, extent or condition, usually expressed in physical terms. Can be either qualitative or quantitative.
Metric: “A system or standard of measurement”. A combination of measures or modelled elements. The Mean Species Abundance (MSA) and the Potentially Disappeared Fraction (PDF) are for instance metrics expressed as a
percentage.
Unit: a standard measure that is used to express amounts. For instance MSA.m
2or PDF.yr.m
2are units.
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Definitions
What is your general feedback on output #1 – Language mapping?
Language mapping
REVIEW - Impacts persistent over time
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What is time integration about?
Mentimeter
Some impacts persist over time
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Illustration of the question of impacts persistent over
time (CDC Biodiversité, 2019) with the example of
MSA
Impact persistence over time is unrelated to tracking biodiversity over time and comparing evolutions to counterfactual scenarios (sub-group #2).
Persistent over time = specific to impact sources active over several years (e.g. pollutants).
Require the knowledge of the shape of the impulse response function (how impacts evolve over time).
Technically, if the shape is unknown, approximations
necessary, e.g. discount factors if likely to match the real shape
Impacts persistent over time
1. Integrate impacts over time PDF.yr
2. Distinguish between impacts over the period considered (could be called dynamic) and the stock of past impacts (could be called static)
3. Ignore persistent effect
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How to deal with effects persistent over time?
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Overview of current practices regarding time integration among measurement approaches
Time integration approach Measurement approaches
Time integration embedded in the unit used (e.g.
PDF.m
2.yr)
BFFI, PBF
Distinction of dynamic (integrated over the assessment period) and
static impacts
GBS
No time integration AI, BF, BIE, BIM, EP&L, LIFE Index,
STAR
Proposal: SG3B recognizes the importance to take into account the persistence of impacts over time and the need for each measurement approach to clarify how it currently deals with the issue
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How to deal with effects persistent over time? www.menti.com
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REVIEW – OUTPUT #2 - Differences between
metrics
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Mapping of the approaches to the Natural Capital Protocol’s steps - Figure 5
Step 5 - Measure impact drivers and/or dependencies
Step 6 – Measure changes in the state of natural capital
Step 7 – Value impacts and/or dependencies
MSA [GBS; BIM; BF] and PDF [BFFI; PBF]
Risk of extinction unit [STAR]
Monetary value [Kering’s EP&L]
[BIE]
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Aggregation method used by each metric – Table 4
Metric [initiatives using the metric]
Aggregation method Reasoning behind the aggregation Mean species
abundance (MSA) [GBS, BIM, BF, LIFE Index]
Arithmetic mean of abundances (same weight for all species)
Equal weights are a good default and explicit weighting is also possible.
Another aspect is that all species contribute to ecological functions and that redundancies provide an insurance policy against losses of ecological functions.
Potentially disappeared
fraction (PDF) [BFFI, PBF]
Number of species (same weight for all species)
Similar to MSA.
Risk of extinction unit [STAR]
Sum of the risks of extinction of species weighted by their threat status
Threat status of species has been evaluated in a scientifically consistent, multi-stakeholder, global process and the presence of threatened species in a site or habitat is an indication that the ecosystem is under pressure.
Natural capital monetary value
(e.g. EUR)
[Kering’s EP&L]
Sum of the economic value of ecosystem services (i.e.
more weight to more valuable services)
Economic valuation gives the expression of the worth of the benefits people gain from the environment.
Using this assessment allows to better understand and address impacts and prioritize actions.
[BIE,…] No single quantitative metric.
Aggregation approach is still to be determined
State / pressure / response indicators are required to meet sites’ needs and such indicators are difficult to aggregate quantitatively, so a qualitative aggregation is used.
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State of biodiversity covered by each metric – Table 5
Metric [initiatives using the metric]
State of biodiversity covered
Reasons why some state of biodiversity are not covered
Capacity to assess biodiversity state based on ecological surveys (direct measurements)
Mean species abundance (MSA) [GBS, BIM, BF, LIFE Index]
Terrestrial and aquatic (freshwater)
No endpoint
characterisation
factors for marine biodiversity
Possible in theory
Potentially disappeared
fraction (PDF) [BFFI, PBF]
Terrestrial, aquatic (freshwater) and marine
For PBF: not possible.
For BFFI: to be determined
Risk of extinction unit [STAR]
Terrestrial, aquatic (freshwater) and marine?
Possible
Natural capital monetary value (e.g. EUR) [EP&L]
Terrestrial only
Likely to be challenging given that values of biodiversity are known not to be well represented currently into natural capital assessments.
However data on habitats (type of ecoregion) may be used to refine assessments.
[BIE, …] Terrestrial, aquatic (freshwater) and marine?
Possible
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Impacts on biodiversity, and associated pressures, covered due to the impacts on biodiversity’s
characterisation factors available for each metric - Table 6
Impacts on biodiversity’s characterisation factors and associated capacity to assess the biodiversity impact of pressures
Metric [initiatives using the metric]
Available characterisa- tion factors
Land / sea use change
Direct
exploitation
Invasive alien species
Pollution Climate
change
Other
MSA [GBS, BIM, BF, LIFE
Index]
GLOBIO’s pressure- impact
relationships
Land use, Fragmentatio n,
Encroachme nt,
Hydrological disturbance, Wetland conversion
Not covered directly
Not covered
Atmospheric nitrogen deposition, Nutrient emissions, Land use change in catchment
Climate change
PDF [BFFI, PBF]
ReCiPe or LC Impact’s characterisati on factors
Land
occupation, Land
transformatio n, (regional) Water
scarcity
Not covered
Not covered
Terrestrial ecotoxicity, Terrestrial acidification, Marine ecotoxicity, Marine eutrophication, Freshwater eutrophication, Freshwater ecotoxicity
Climate change
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Impacts on biodiversity, and associated pressures, covered due to the impacts on biodiversity’s
characterisation factors available for each metric - Table 6
Impacts on biodiversity’s characterisation factors and associated capacity to assess the biodiversity impact of pressures
Metric [initiatives using the metric]
Available characterisat ion factors
Land / sea use change
Direct
exploitation
Invasive alien species
Pollution Climate change
Other
Risk of
extinction unit [STAR]
No
characterisat ion factor but assessment of the level of pressures through the IUCN Red List
Residential &
Commercial Development,
Agriculture &
Aquaculture, Energy Production & Mining, Transportation &
Service Corridors, Human Intrusions &
Disturbance, Natural System Modifications
Biological Resource Use
Invasive &
Problematic Species,
Pathogens &
Genes
Pollution Climate Change
Geological Events
Natural capital monetary value [Kering’s EP&L]
No
characterisat ion factor
[BIE,…] No
characterisat ion factor
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The following types of biodiversity are suggested in line with the PBL’s presentation at the March workshop:
Ecological integrity: health of the overall ecosystem (abundance combined to species richness), including ordinary biodiversity
Extinction risk: state of key biodiversity features (and not of the overall ecosystem), including endangered and
charismatic species
Ecosystem services
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Limitations of each metric –biodiversity type
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Limitations of each metric - Table 7
Metric [initiatives using the metric]
Type of
biodiversity covered
Other limitations (on top of those listed in the previous tables)
MSA [GBS,
BIM, BF, LIFE
Index]
Ecological integrity
The use of characterisation factors instead of direct biodiversity state data increases uncertainties. The focus on ecological integrity means optimising (i.e. reducing) MSA impacts can lead to the extinctions of species already endangered.
PDF [BFFI, PBF]
Ecological integrity
Same limitations as MSA.
Risk of extinction unit
[STAR]
Extinction risk The use of implicit characterisation factors to attribute biodiversity impacts to pressures (to assess threat abatement potential) increases uncertainties. The focus on extinction risk means the optimisation (i.e. reduction) of the risk of extinction unit can lead to severe deterioration of previously healthy ecosystems (as they do not host any endangered species).
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Limitations of each metric - Table 7
Metric [initiatives using the metric]
Type of
biodiversity covered
Other limitations (on top of those listed in the previous tables)
Natural capital monetary value [Kering’s EP&L]
Ecosystem services
The use of valuation techniques to assess monetary values increase uncertainties. The focus on the value for society of ecosystem services means the optimisation (i.e. maximisation) of the monetary value can lead to the deterioration of parts of biodiversity which do not provide ecosystem services.
[BIE, …] Ecological
integrity &
extinction risk
Collecting primary data on biodiversity state at a large scale is very costly, and secondary data on biodiversity state are insufficient (e.g.
usually lack abundance data) to systematically and properly assess biodiversity impacts.
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Compatibility with Biological Diversity Protocol (BDP)’s accounting and reporting criteria - Table 8
Criteria Definition Compatibility of metrics and tools
Relevance Ensure the biodiversity impact inventory appropriately reflects the biodiversity impacts of the company [direct operations] and its value chain. It shall serve the decision-making needs of users, both internal and external to the company.
Tools with no or limited focus on the value chain do not properly reflect all the biodiversity impacts.
Equivalency Ensure that the notion of equity in the type of biodiversity (i.e. ecological equivalency or like-for-like principle) is integral to biodiversity impact inventory development and accounting. Undertake net impact accounting only for equivalent biodiversity losses (negative impacts) and gains (positive impacts).
Strict equivalency is lost when aggregating impacts (which is conducted by all the metrics and tools assessed). But equivalency rules can still be designed and used to limit net impact accounting to equivalent biodiversity losses and gains.
Currently limited thoughts put on this issue by existing tools.
Complete- ness
Account for and report on all biodiversity impacts within the chosen organisational and value chain boundaries. Disclose and justify any exclusion.
Cf. table 6 of the position paper on available characterisation factors.
Please note that this assessment goes beyond the perimeter of SG3B as it
assesses tools and not metrics (and is not related to calculation intermediaries).
The topic was suggested by one member of the sub-group.
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Compatibility with Biological Diversity Protocol (BDP)’s accounting and reporting criteria - Table 8
Criteria Definition Compatibility of metrics and tools
Consistency Use consistent methodologies to allow for meaningful comparisons of biodiversity impacts over time. Transparently document any changes to the data, inventory boundary, methods or any other relevant factors in the time series.
Some tools have specific methodologies to ensure their consistent use (though they are not yet publicly available).
Transpa- rency
Address all relevant issues in a factual and coherent manner, based on a clear audit trail. Disclose any relevant assumptions and make appropriate references to the data collection and estimation methodologies used.
Similarly, some tools have specific methodologies to ensure transparency (not yet publicly available).
Accuracy Ensure that the measurement of biodiversity impacts is systematically accurate, as far as can be judged, notably by reducing uncertainties as far as is practicable.
Achieve suitable accuracy to enable users to make decisions with reasonable assurance as to the integrity of the reported information. When no direct observation is possible, estimate impacts on the basis that they are reasonably likely to occur, recording all methodological limitations.
Accuracy is highest for primary data of direct measurements. The use of characterisation factors may increase uncertainties and decrease accuracy.
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Compatibility with Biological Diversity Protocol (BDP)’s accounting and reporting criteria - Table 8
Criteria Definition Compatibility of metrics and tools
Accuracy Ensure that the measurement of biodiversity impacts is systematically accurate, as far as can be judged, notably by reducing uncertainties as far as is practicable.
Achieve suitable accuracy to enable users to make decisions with reasonable assurance as to the integrity of the reported information. When no direct observation is possible, estimate impacts on the basis that they are reasonably likely to occur, recording all methodological limitations.
Accuracy is highest for primary data of direct measurements. The use of characterisation factors may increase uncertainties and decrease accuracy.
Time period assumption
Account for biodiversity impacts consistently across business reporting periods.
Some tools specifically advise their users to report impacts annually, while others do not specific time periods for reporting.
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General feedback?
Opinion on the tables?
Examples to share on top of the two examples listed in the position paper?
PAGE 46
Feedback from the sub-group
REVIEW – OUTPUT #3B - Link between inventories of
species and habitat and aggregated metrics approaches
PAGE 48
Link between inventories of species and habitat and aggregated metrics approaches – Figure 9
Aggregated metrics
Modeling of biodiversity state based on pressures & economic
activities
Metrics focused on elementary components of biodiversity
Habitats
Feed assessment tools (cf. sub-
group #3A) Aggregation if
comprehensive data available
MSA
MSA, PDF, risk of extinction unit Pressures and
economic activities Multiple metrics [BIE],
NatCap Taxa
Multiple metrics [BIE], NatCap
Primary Secondary Primary Secondary
Primary Secondary
Push companies to collect primary and
secondary data
SG3A explores promising linkages between site level and corporate footprint approaches focused on data collection
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Link between inventories of species and habitat and aggregated metrics approaches
LUC (common classification) Endangered
species, PA, criticial habitats
Tools using metrics focused on elementary components of biodiversity (BIE) and tools using aggregated metrics (BF, BFFI, EP&L, GBS, LIFE Index, PBF, STAR), usually meet different business applications (cf. SG1)
They are complementary, without the need for conversion
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Link between inventories of species and habitat and
aggregated metrics approaches - Complementarity
General feedback on Output #3B?
Feedback
Remaining open questions and
discussions
Should the following terms be defined in the position paper? “Biodiversity”, “Biodiversity value”.
Joël Houdet explained that approaches using only
biodiversity state data also produce “footprint metrics”.
How?
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Remaining open questions
Opinion on a distinction made in the sub-group:
The distinction is not between approaches using primary biodiversity state data (e.g. BIE uses a lot of secondary biodiversity state data) and approaches extrapolating / modeling biodiversity state based on “indirect” pressure data. Indeed, the pressure data can be primary. And
some approaches are hybrids and can use primary biodiversity state data when data is comprehensive.
So the distinction should rather be on “biodiversity state only” approaches and “biodiversity state assessed using pressure & economic activity data” approaches.
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Remaining open questions
For natural capital monetary value metrics (e.g. used by Kering’s EP&L), what is the capacity to assess biodiversity state based on ecological surveys (direct measurements)?
“Likely to be challenging given that values of biodiversity are known not to be well represented currently into natural capital assessments”?
“more challenging given the state of play of existing methodologies”?
REMINDER: it’s about using direct measurement of
biodiversity state (number of animals or plants, areas of habitats), not about monetary valuation.
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Remaining open questions
Choice of dates for the next webinar
2 hour web conference - in-depth technical discussions to try to converge on a limited number of calculation
intermediaries with the measurement approaches interested to do so
November?
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Choice of dates for the next webinar
Contacts
Aligning Biodiversity Measures for Business
Annelisa Grigg, UN Environment World Conservation Monitoring Centre
Tel: +44 (0)1223 277314 Email: annelisa.grigg@unep- wcmc.org
Sub-group 3B chair
Joshua Berger, CDC Biodiversité Tel: +33 (0)1 80 40 15 41
Email: joshua.berger@cdc- biodiversite.fr
