Measures for Business

Aligning Biodiversity Measures for Business Sub-group 3A

Corporate data inputs

Webinar

8 July 2019

❑ 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

❑ Presentation of the database on state, pressure, activity and response data sets

❑ Review of the SG3A working paper and preparation of the position paper

▪ Common framework (data quality tier, uncertainties)

▪ Data mapping – data used by each tool

▪ Agreement on common nomenclatures to request data from companies

❑ Other discussion questions

❑ Choice of dates for the next (and final for 2019) webinar

Agenda

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

1. Map the data sets required by each methodology as assessment inputs and briefly describe them (public or

private, modelled or real data, geographic coverage, etc.). The focus is on data used to assess the extent of the impacts, and not to attribute them among stakeholders.

2. Identify common input data sets and agree on a limited set of input indicators and formats (including granularity) which companies could collect to feed most measurement approaches.

3. Determine links between site and corporate / portfolio level approaches and how data sets differ / are

complementary or can reinforce each other.

Objectives of the sub-group

1. Complete data mapping for each initiative to determine which data sets are used and what further data may be available now and in the future (a call has gone out from the European B@B platform for

information from which we will draw).

2. Common nomenclature for data used within measurement

approaches, relating this to the ‘tiers’ of accuracy within the IPCC.

The Natural Capital Protocol also needs to be considered.

3. Discussion and agreement to support common ground principles identified previously.

4. Exploration of linkages of approaches that rely on data estimates and proxies with approaches that rely on measured data through common ground nomenclature of data pressures, for example.

Expected outputs of the sub-group

Linkage of the sub-group with sub-group 3B on metrics and midpoint characterisation factors

Input data

Sub-group 3A

Biodiversity impact assessment Tools or approach

Impact factors Midpoints Endpoints

Sub-group 3B

① Company’s data

② Fall back data sets

1. Clarify the collaboration process.

2. Review the SG3A working paper and provide feedback to transform it into a SG3A position paper (input to the Brazil workshop).

3. In particular, build consensus on output #1 (input data mapping) and output #2 (common nomenclature)

4. Plan the next webinar.

Objectives of the webinar

Review of the SG3A working paper and preparation

of the position paper

❑ aligning_biodiversity_measures_SG3A-

datasets_working_paper_v4_03072019.docx

❑ Sent by Julie Dimitrijevic on 3 ^rd July

❑ Objective: have comments and edit proposals in track changes by SG3A members in July and August to build into a position paper open for suggestions for all ABMB members in September.

SG3A working paper

REVIEW - Common framework (data quality tier,

uncertainties)

❑ Accuracy refers to how close an assessed value is to the actual (true) value.

❑ Precision refers to how close the assessed values are to each other. A precise assessment will for instance be

able to claim that the assessed value is “15.126” and not just “15”.

Accuracy and precision

Impact factor and data quality tiers to quickly assess data accuracy

Real or modelled

Data quality

tier

Description Example for impact factors

Modelled

1 Simple linear approach. Tier 1 impact factors are international defaults.

Average agricultural yield of wheat across the world.

2 Region (country)-specific linear factors or more refined empirical estimation methodologies.

Average agricultural yield of wheat in Brazil.

3

Impact factors derived from the use of relationships (equations) linking the impact

source (for instance a land use change) to biodiversity impacts, with inputs requiring a

translation into the appropriate typology.

Impact factors for data in formats requiring transformation to be fed

to dynamic bio-geophysical simulation models using multi-year

time series and context-specific parameterization (such as GLOBIO).

4 Impact factors derived from the use of direct relationships (equations) to biodiversity

Impact factors for data which can be directly fed to dynamic bio- geophysical simulation models using

multi-year time series and context- specific parameterization.

Real 5 Direct measurements.

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Which data quality for which use?

Business applications (BAs) Desired and appropriate data quality tier

1.Assessment of current biodiversity performance

2.Assessment of future biodiversity performance

3. Tracking progress to targets 4. Comparing options

5. Biodiversity Return on

Investment / Testing effectiveness of reduction measures

6. Assessment / rating of biodiversity performance by third

parties, using external data

7. Certification by third parties

8. Screening and assessment of

biodiversity risks and opportunities

The sub-group agrees/does not agree on:

❑ The use of 5 data quality tiers

❑ The need to quantify as much as possible

uncertainties about the value of each measure.

▪ Uncertainties can be further broken down into different levels: inventory data, data in model, model

assumptions.

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Common ground reached in the sub-group

❑ Primary data: inputs directly based on company data.

❑ Secondary data: data derived from global data sets.

▪ Secondary data are usually not responsive to actions taken by businesses: those actions may not show up in global data sets, especially when these data sets were developed prior to the implementation of the actions.

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Definitions (1/4)

❑ 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”.

❑ Key Performance Indicators (KPI): indicators can further be built into against which to measure corporate performance. Such a KPI could for instance be the total biodiversity impact of a business, and it could for example be associated to a reduction target by 2030.

❑ Input indicator: the term “indicator” can also be used to describe specific data required by tools to conduct biodiversity impact

assessments. Such “input indicators” could include for instance yearly corporate turnover by industry or region (EUR), area of natural forest converted into intensive agriculture every year (ha), etc

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Definitions (2/4)

❑ Impact indicators: sometimes known as ‘performance’ or

‘outcome’ indicators. These provide information on actual impacts of actions taken to address biodiversity or drivers of change. They help to answer the question, ‘how are our

activities affecting biodiversity?’

❑ Implementation indicators: sometimes known as ‘process’

or ‘output’ indicators, these are used to monitor the completion of actions that enable conservation to be achieved: e.g.

whether a Biodiversity Action Plan has been developed and implemented or not (but not to track the actual impacts on biodiversity of the Biodiversity Action Plan). They help to

answer the question, ‘did we do what we said we would, when we said we would?’.

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Definitions (3/4)

❑ 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

or PDF.yr.m

are units.

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Definitions (4/4)

REVIEW - Data mapping – data used by each tool

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Data mapping

❑ A database has been built by UNEP-WCMC and participants to the Gaining Consensus workshop in May 2019 in

Cambridge, UK

❑ It has been refined to map the data sets used by approaches followed by the ABMB initiative and can be found here:

https://www.dropbox.com/sh/ym0agydww9haz40/AABhLuktuX Ny3Ue8qfWv696Ca?dl=0

❑ The following slides list categories of data contained in this

database. The objective is NOT to have an exhaustive list

of categories but rather to categorize properly data already in

the database.

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Data categories - State

Type Theme Category

State Ecosystem Ecoregion

Functional richness Marine

Soil

Ecosystem service Provision - fish

Gene Genetic diversity

Habitat Wetland map

Other habitats Species Risk of extinction

Species distribution Species richness

Taxa Plant

Other Biomass

Ecological integrity

Priority areas

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Data categories - Pressure

Type Theme Category

Pressure Land / sea use change (including in aquatic ecosystems, e.g. hydrological disturbance)

Forest cover

Infrastructure and roads Land cover

Land cover change

Land use (cover + intensity) Land tenure and value

Water resources Direct exploitation

Invasive alien species

Pollution Air pollution

Nitrogen and phosphorous Pesticides

Climate change Greenhouse gas emission

Other Indirect driver

Natural disaster Soil erosion

Synthetic indicator of pressures

Multi-pressure Extractive

Tourism

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Data categories - Response

Type Theme Category

Response Response Indigenous land

Protected area

Restoration

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Data categories - Economic quantification of human activities

Type Theme Category

Economic quantification of human activities

Activity Company turnover

Company purchase

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Data mapping

❑ Each initiative can use the database to map the data inputs it uses as secondary data or as inputs to build impact factors.

❑ This mapping is led coherently with the EU B@B update on biodiversity accounting tools for business led by Johan

Lammerant: no need to do the work twice!

❑ The ID (#14 etc.) cited refer to the database here:

https://www.dropbox.com/sh/ym0agydww9haz40/AABhLuktuX

Ny3Ue8qfWv696Ca?dl=0

PAGE 27

Data mapping – Biodiversity state

Approach Primary input data (company’s data)

Secondary input data (e.g.

global data sets)

GBS Integration of abundance data

(ecological surveys) under consideration.

To update

BIM Not known Not known

BIE Company data on one or more

species identified as a priority biodiversity feature or area of priority habitat (as a proxy).

To update

PBF Not known Not known

BFFI NA NA

STAR Not known To update

AI Not known Not known

BF NA NA

LIFE Index Ecological surveys (used in the management recommendations but not directly in the Index metric)

Not known

Bioscope Not known Not known

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Data mapping – Pressures (1/2)

Approach Primary input data (company’s data) Secondary input data (e.g. global data sets)

GBS Company data on land use change (LUC, including wetlands), GHG emissions, water consumption, N & P concentration (and in the future pollutant emissions).

GLOBIO scenarios as proxy of current pressures

FAO data on yields

Aqueduct data on water consumption by watershed

USGS data on mines around the world

EXIOBASE data on material

consumption BIM Company data on land use changes. Not known BIE Company data for emissions to water and air,

water abstraction, habitat

destruction/degradation, disturbance and invasive species, assessed qualitatively based on timing of pressure, proportion of population affected and severity of pressure.

National or global averages of the same data if primary data unavailable

PBF Company data on quantities and yields of agricultural products produced.

Not known

BFFI NA EXIOBASE data on resource (land

occupation) and material consumption

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Data mapping – Pressures (2/2)

Approach Primary input data (company’s data) Secondary input data (e.g. global data sets)

STAR Global pressure maps on climate change &

severe weather, transportation & service corridor based on global data sets and combined to the threat assessment from the IUCN Red List.

Combined to qualitative assessments of how threats would evolve due to actions implemented by the business assessed.

AI Not known Not known

BF Company data on LUC, GHG emissions NA LIFE

Index

Company data on land use change (LUC, including wetlands), GHG emissions, water consumption, pesticide use (used only for the management recommendations, not in the Index).

Company data on the energy source used and waste generated are also collected.

Not known

Bioscope Not known Not known

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Data mapping – Activity

Approach Primary input data (company’s data)

Secondary input data (e.g.

global data sets) GBS Consumption of commodities,

services or refined products inventories (only GBS?)

Public financial reports, private database on turnover (e.g. ISS- oekom)

BIM NA NA

BIE NA NA

PBF NA NA

BFFI NA Public financial reports, private

database on turnover (e.g. ISS- oekom)

STAR Not known Not known

AI NA NA

BF NA NA

LIFE Index NA NA

Bioscope NA NA

REVIEW - Agreement on common nomenclatures to

request data from companies

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Agreement on common nomenclatures to request

data from companies

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Top priority for convergence: land uses

❑ Yearly land occupation

▪ Forest

• Forest – Natural

• Forest – Used

▪ Grassland

• Natural grassland

• Pasture - moderately to intensively used

• Pasture - man-made

▪ Cropland

• Extensive cropland

• Intensive cropland

• Monoculture cropland

▪ Natural bare and ice

▪ Urban area

❑ Yearly wetland conversions

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Other potential area of convergence

❑ Yearly greenhouse gas (GHG) emissions

❑ Ecological survey data

❑ Yearly water withdrawals and consumptions

❑ Nitrogen and phosphorous concentrations in water

❑ Pesticides

Other discussion questions

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Generic common ground

❑ Responsive to change. The measure should be susceptible to changes in the management activity.

❑ Rigor. The information, data and methods used should be technically robust or clearly stated as to the levels of accuracy it confers

❑ Compatibility. High compatibility between impact

assessment measurement approaches should be

maintained such that similar data sets are used

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Discussion questions

❑ 1. What data sets are used by each methodology and how can they be used by others?

❑ 2. What common data types are shared by several methodologies? This probably includes GHG emissions, land use conversion and occupation, nitrogen and phosphorous concentrations, wetland conversion and pesticide concentration, among others.

❑ 3. What data types could be required from companies for use by multiple methodologies? What should be the format (or unit) of data? (e.g. GHG expressed in CO2 eq.)

❑ 4. What are the implications of using different data sets for different measurement approaches for decision making and uptake?

❑ 5. What Common Ground principles for corporate biodiversity measurement could promote alignment between different approaches?

❑ 6. Should “inventory” data be distinguished from “pressure” data? For instance, water consumption (m3) or waste generation (t) are not pressure but can be used as proxies to assess pressures. Currently associated input indicators are listed in the pressure tables.

❑ 7. Should “attribution” data inputs be covered by the sub-group and how comprehensively?

❑ 8. In Table 1, should pressure categories be classified by sub-pressure instead? For instance, hydrological disturbance, etc.

Choice of dates for the next webinar

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Choice of dates for the next webinar

❑ 10 September or 12 September (both in the afternoon Brussels time)

❑ https://doodle.com/poll/2hrknrb3n6g7udh2

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 3A chair

Joshua Berger, CDC Biodiversité Tel: +33 (0)1 80 40 15 41

Email: joshua.berger@cdc- biodiversite.fr