Sub-group 3B Metrics and midpoint characterisation factors Webinar - - PowerPoint PPT Presentation

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

 Go to www.menti.com and use the code 28 57 65  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)

PAGE 10

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 activity

Input 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

 Go to www.menti.com and use the code 28 57 65  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 4th 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 28 57 65

 #3 - Inventory data: Data related to emissions and extraction

• f 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 28 57 65

 #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 28 57 65

 #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

• n Biodiversity and Ecosystem Services (IPBES).

Definitions www.menti.com 28 57 65

 #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

• n biodiversity.

Definitions www.menti.com 28 57 65

Language mapping – Table 1

PAGE 24

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

www.menti.com 28 57 65

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.m2 or PDF.yr.m2 are units.

PAGE 25

Definitions

 What is your general feedback on output #1 – Language mapping?

Language mapping

REVIEW - Impacts persistent over time

 Go to www.menti.com and use the code 28 57 65  What is time integration about?

Mentimeter

 Some impacts persist over time

PAGE 29

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
• ver 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

PAGE 31

How to deal with effects persistent over time?

PAGE 32

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.m2.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

PAGE 33

How to deal with effects persistent over time? www.menti.com 28 57 65

REVIEW – OUTPUT #2 - Differences between metrics

PAGE 35

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]

www.menti.com 28 57 65

PAGE 36

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

• f

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

• f

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

• f 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

• f ecosystem services (i.e.

more weight to more valuable services) Economic valuation gives the expression of the worth

• f 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.

www.menti.com 28 57 65

PAGE 37

State of biodiversity covered by each metric – Table 5

Metric [initiatives using the metric] State

• f

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

• nly

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

www.menti.com 28 57 65

PAGE 38

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

• r

LC Impact’s characterisati

• n factors

Land

• ccupation,

Land transformatio n, (regional) Water scarcity Not covered Not covered Terrestrial ecotoxicity, Terrestrial acidification, Marine ecotoxicity, Marine eutrophication, Freshwater eutrophication, Freshwater ecotoxicity Climate change

www.menti.com 28 57 65

PAGE 39

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

• f

extinction unit [STAR] No characterisat ion factor but assessment

• f the level
• f 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

www.menti.com 28 57 65

 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

• rdinary biodiversity
• Extinction risk: state of key biodiversity features (and not
• f the overall ecosystem), including endangered and

charismatic species

• Ecosystem services

PAGE 40

Limitations of each metric –biodiversity type

PAGE 41

Limitations of each metric - Table 7

Metric [initiatives using the metric] Type

• f

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

• ptimising (i.e. reducing) MSA impacts can lead to the extinctions of

species already endangered. PDF [BFFI, PBF] Ecological integrity Same limitations as MSA. Risk

• f

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

• ptimisation (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).

www.menti.com 28 57 65

PAGE 42

Limitations of each metric - Table 7

Metric [initiatives using the metric] Type

• f

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.

www.menti.com 28 57 65

PAGE 43

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

• f

the company [direct

• perations] 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

• f biodiversity (i.e. ecological equivalency
• r 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.

www.menti.com 28 57 65

PAGE 44

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

• f

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

• ccur,

recording all methodological limitations. Accuracy is highest for primary data of direct

• measurements. The use of characterisation factors

may increase uncertainties and decrease accuracy.

www.menti.com 28 57 65

PAGE 45

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

• ccur,

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.

www.menti.com 28 57 65

 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 economicactivities

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

PAGE 49

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

• f 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

PAGE 50

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?

PAGE 53

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
• nly” approaches and “biodiversity state assessed using

pressure & economic activity data” approaches.

PAGE 54

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.

PAGE 55

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?

PAGE 57

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