Aligning Biodiversity Measures for Business Sub-group 3A Corporate data inputs Webinar 20 September 2019
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 ❑ Presentation of the database on state, pressure, activity and response data sets ❑ Review of the SG3A position paper to finalize it for the Brazil workshop ▪ Output #1 - Data mapping – data used by each tool ▪ Output #2 - Agreement on common nomenclatures to request data from companies ▪ Output #3 – Link between between inventories of species and habitat and aggregated metrics approaches ▪ Output #4 – Other common ground principle
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
Mentimeter ❑ Go to www.menti.com and use the code 76 29 81 ❑ What is this session about?
Objectives of the sub-group 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.
Expected outputs 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 based on a call for information from the European B@B platform for information. 2. Common nomenclature for data used within measurement approaches, relating this to the ‘tiers’ of accuracy within the IPCC and the the Natural Capital Protocol, and agreement on common data requests to companies . 3. 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. 4. Discussion and agreement to support other common ground principles identified previously.
Linkage of the sub-group with sub-group 3B on metrics and characterisation factors Modeling of biodiversity impacts based on pressures and economic activity Tools or approach ① Company’s data Secondary Impacts on Endpoints Input inventory data CF biodiversity CF data & midpoints CF (endpoint) ② Fall back data sets Sub-group 3B (rationale of the different metrics) Sub-group 3B Sub-group 3A (characterisation factors) Direct evaluation of biodiversity impacts based on data on biodiversity state ① Company’s data Input data Impacts on biodiversity ② Fall back data sets Sub-group 3B (rationale of the Sub-group 3A different metrics)
Objectives of the webinar 1. Review the SG3A draft position paper and provide feedback to validate it as input of the sub-group to the Brazil workshop.
Mentimeter ❑ Go to www.menti.com and use the code 76 29 81 ❑ Questions? ➔ add them to the parking lot
Review of the SG3A position paper to finalize it for the Brazil workshop
SG3A position paper ❑ 20190917_ABMB_SG3A-datasets_position- paper_v2.docx ❑ Sent by Julie Dimitrijevic on 17 th September
Remaining open questions ❑ QUESTION #1: Should “attribution” data inputs be covered by the sub-group and how comprehensively? ❑ Go to www.menti.com and use the code 76 29 81
REVIEW - Output #1 - Data mapping – data used by each tool
Remaining open questions ❑ QUESTION #2A: In Table 1, should pressure categories be classified by sub-pressure instead? For instance, hydrological disturbance, etc. ❑ QUESTION #2B: Should data categories be mutually exclusive? Especially for data on biodiversity state. ❑ Go to www.menti.com and use the code 76 29 81
www.menti.com Data mapping – Figure 2 Code 76 29 81 ① Economic ② Pressures, SG3A quantification of ③ State resources and human activities emissions Inventory data SG3B Economic Resources quantification & Pressures State of human emissions activities PAGE 16
www.menti.com Data mapping – Figure 3 Code 76 29 81 Categories Input indicator names Values Units Area of irrigated ① 10 ha cropland These 6 input indicators are all input Area of intensive ② data. 5 ha cropland Land use The input indicators within a category Area of monoculture ③ 10 ha crops/weeds are expressed based on a Area of intensive nomenclature . For instance input ④ 5 ha crops/weeds indicator ① and ② are expressed with the GLOBIO’s land use nomenclature and ③ and ④ are ⑤ m 3 Water resources Water consummed 100 expressed with ReCiPe’s land use Greenhouse gas nomenclature ⑥ Methane emissions 1 567 kg emissions Coming from company data ( user-collected data ) or from data sets originating from external databases (e.g. Production/Crops data set originating from FAOSTAT database) PAGE 17
www.menti.com Data mapping – Figure 4 Code 76 29 81 Database (e.g. FAOSTAT) Data set #1 (e.g. Data set #2 (e.g. Forestry Production/Crops) Production and Trade) Input indicator #1.1 Input indicator #2.1 (e.g. Production Quantity) (e.g. Area harvested) Input indicator #1.2 Input indicator #2.2 (e.g. (e.g. Yield) Import Quantity) Input indicator #1.3 (e.g Etc. Production Quantity) PAGE 18
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. PAGE 19
Data mapping ❑ Each initiative can use the database to map the data inputs it uses as externally collected input data or as inputs to build characterisation 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 20
Data mapping – Key messages ❑ Missing data for several approaches: Kering EP&L, Agrobiodiversity Index, STAR, Biodiversity Footprint calculator, BFFI. ❑ Overlap on some input data: ▪ FAO data on area harvested, yield, production of crops ▪ EXIOBASE data on emissions and resource consumption ▪ IBAT data on presence of threatened species, protected area proximity, etc. PAGE 21
Data mapping – Biodiversity state – Table 3 Externally collected input data (e.g. global data sets) Measurement User-collected input data (company’s data) Used to build approach Used as direct inputs characterisation factors Integration of abundance IBAT data for extinction risk GBS data (ecological surveys) NA screening. under consideration. BIM NA Range rarity layer. NA Company data on one or more species identified as a BIE priority biodiversity feature or Not known NA area of priority habitat (as a proxy). Sectoral and local ecological PBF studies used to adjust NA IBAT data. characterisation factors. BFFI NA NA NA PAGE 22
Data mapping – Biodiversity state – Table 3 Externally collected input data (e.g. global data sets) Measurement User-collected input data (company’s data) Used to build approach Used as direct inputs characterisation factors STAR Not known Not known Not known ABD Index Not known Not known Not known BF NA NA NA Status of conservation of #45 – Ecoregions; Biological natural vegetation; Length Importance of the Area LIFE Index and width of biodiversity Protected area categories; (national classifications); corridors; Stage of vegetal threat status of species; dynamics. PAGE 23
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