SUSTAINABLE BY NATURE SEQUEL:EXPLORING THE ROOTS OFOUR EXPOSURE TO DEFORESTATION
Research paper - November 2023

The sustainable
investor for achanging world

S U STA I N A B L E B Y N AT U R E S E Q U E L :E X P LO R I N G T H E R O OT S O F O U R E X P O S U R E TO D E F O R E STAT I O N-2-CONTENTSEXECUTIVE SUMMARY					3INTRODUCTION					4OBJECTIVE					8GENERAL APPROACH 					10STEP 1: IDENTIFYING THE COMPANIES WE HOLD THAT ARE KNOWN TO BE EXPOSED TO AT LEAST ONE FERC		

14

A. Methodology and coverage					14B. Findings					14STEP 2: IDENTIFYING THE QUANTITY OF FERC PRODUCED AND/OR CONSUMED					16A. Methodology and coverage					16B. FERCs consumption and production quantities					17STEP 3: E STIMATE THE POTENTIAL DEFORESTATION AND CONVERSION
OF NATURAL ECOSYSTEMS LINKED TO FERC PRODUCTION AND/OR CONSUMPTION				19

STEP 4: OVERLAYING COMPANIES’ IMPACTS WITH A HIGH-LEVEL REVIEW OF THEIR POLICIES AND PROCESSES		
22
A. Assessing deforestation-free claims of companies					22B. Assessing the impact of commitments					24EXPLORATORY OUTCOMES					27A. Closing the data gap					27B. Engaging with the laggards					28C. Educating portfolio managers and clients					28D. Leveraging the six pillars of our approach to sustainability to address deforestation challenges		 29APPENDIX IAPPENDIX IIAPPENDIX III

General approach of our in-house methodology
to estimate potential contribution to deforestation 					30Interpreting deforestation results 					

34F ERCs coverage in the selected datasets,
and the EU Regulation (alphabetical order)					

36APPENDIX IV 	 P ercentage of AUM covered at each step of our proprietary methodology
to quantify the extent to which our corporate holdings drive potential
deforestation and conversion of natural ecosystems 					APPENDIX V

Availability of full, useable, quantitative consumption and/or production data 		

APPENDIX VI 	 D escription of Trase and Dr Pendrill’s methodologies
to derive FERC and country-specific deforestation coefficient 					APPENDIX VII 	 Details of disclosed FERCs consumption andproduction quantities and geographical split (disclosed or estimated)			
APPENDIX VIII  Criteria used to decide whether a corporate commitment
or traceability-system is ‘strong’					

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38
39
40
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S U STA I N A B L E B Y N AT U R E S E Q U E L :E X P LO R I N G T H E R O OT S O F O U R E X P O S U R E TO D E F O R E STAT I O N-3-EXECUTIVE SUMMARY
Since 2021, we have been analysing the exposure of our corporate universe to deforestation risk throughdifferent approaches such as the evaluation of deforestation policies1 of our corporate holdings or theassessment of the potential impact of our corporate holdings on land use and land use change using the
Corporate Biodiversity Footprint methodology of Iceberg Datalab2.
This year, we want to go further and quantitatively assess the exposure of our corporate holdings
to potential deforestation and conversion of natural ecosystems through corporate production andconsumption3 of forest and ecosystem-risk commodities (FERCs). The objective of this analysis is tofurther assess the current state of quantitative data and set a precedent for the industry, but also to
identify companies we hold and FERCs that are driving deforestation and conversion of natural ecosystems.
To do so, we established a proprietary methodology4 based on publicly available datasets developed byNGOs (i.e., CDP, Trase, Forest 500 and Forest IQ) to estimate the potential deforestation and conversion ofnatural ecosystems, in hectares, linked to our corporate holdings production and consumption of selected
FERCs5, by combining 1) disclosed production and consumption data for each FERC and 2) deforestation
risk coefficient estimates for these FERCs.
This work is exploratory and among the 171 billion euros of our corporate assets under management6(AUM), we manage to retrieve estimates of deforestation and conversion of natural ecosystems in
hectares for 6% of these AUM. Even though narrow, this perimeter is still interesting considering that we
focused our analysis on four sectors consuming or producing the highest share of FERCs (the consumer
staples7, consumer discretionary8, materials and energy sectors). They represent 24% of our corporate
holdings. Outside of these sectors, the exposure to deforestation is limited. It is important to note that
this analysis presents the total exposure of all investors in the companies we assessed, since we did notconsider our ownership share in each company.
Results show our corporate holdings are mainly exposed to potential deforestation and conversion ofnatural ecosystems associated with palm oil in Indonesia, Malaysia and Colombia, as well as cocoa in
Ivory Coast. Palm oil have been on investors’ radar for some time, but these results suggest cocoa should
be a priority too. We find that a large share of the potential deforestation and conversion of natural
ecosystems is declared ‘deforestation-free’ by companies, but few of them have strong traceability
systems in place, which raises questions over the credibility of these claims.
This study enables us to further delineate the companies on which we want to focus our research andengagement, such as 1) companies in relevant sectors that report only partial quantitative data and/or noquantitative data, 2) companies in our portfolios that potentially drive the largest share of deforestation andconversion of natural ecosystems and that do not have strong No deforestation, no peat, no exploitation(NDPE) policies or traceability systems, 3) companies that claim deforestation-free production andconsumption, but have not put in place strong traceability systems. In addition, to close the data gap,
we urge companies to further disclose quantitative information related to their FERCs sourcing andproduction. Finally, we plan to apply this methodology to specific portfolios, and use this information to
engage and educate portfolio managers and clients about deforestation-related risks in their portfolios,
and identify potential investment opportunities in companies that are managing their FERC impacts andrisks appropriately. Lastly, we will continue to leverage the six pillars of our approach to sustainability
to reduce the environmental impact of our investments with a focus on forests.
1 As part of our whitepaper Sustainable by Nature: Our Biodiversity Roadmap
2 Sustainable By Nature Sequel: Our Portfolio Biodiversity Footprint
3 Consumption meaning companies sourcing/processing the FERC, irrespective of geographical location.
4 With contribution from Julie Raynaud, independent consultant, Julie Raynaud | LinkedIn
5 Beef and derived products, cocoa and derived products, coffee and derived products, palm oil and derived products, rubber, soy,timber and derived products. We have quantity data on production and consumption of these seven FERCs; but have deforestation
risk coefficients estimated for only six FERCs (i.e., the commodities listed excluding timber).
6 Please note this scope does not include residual exposures in some funds delegated by BNPP AM or managed by BNPP AM affiliate
entities.
7 Manufacturers and distributors of food, beverages and tobacco and producers of non-durable household goods and personal
products. It also includes distributors and retailers of consumer staples products including food & drug retailing companies.
8
Manufacturing segment includes automobiles & components, household durable goods, leisure products and textiles& apparel. The services segment includes hotels, restaurants, and other leisure facilities. It also includes distributors and retailers ofconsumer discretionary products.

S U STA I N A B L E B Y N AT U R E S E Q U E L :E X P LO R I N G T H E R O OT S O F O U R E X P O S U R E TO D E F O R E STAT I O N-4-INTRODUCTION
Let’s set the scene in a few charts.
• Humanity has been converting forest and natural ecosystems for 10 000 years, mostly for agricultural use9
(figure 1). The so-called soft commodities have been found to contribute to 90% of tropicaldeforestation10 and almost 90% of all deforestation worldwide11.
Figure 1: Largest drivers of deforestation for 10 000 years• 95% of the world’s deforestation12 occurs in the tropics and is due to agriculture, and in contrast;
two thirds of forest degradation occurs in temperate countries, mostly due to wildfires and logging(figure 2).
• Even though temperate regions have seen a net gain in forest since 1990, it is important to rememberthat deforestation in the world’s temperate forests peaked in the first half of the 20th century.

9 Max Roser, 2022. Humans destroyed forests for thousands of years – we can become the first generation that achieves a worldin which forests expand
10 Pendrill et al, 2022. Disentangling the numbers behind agriculture-driven tropical deforestation
11 FAO, 2022. How much do large-scale and small-scale farming contribute to global deforestation?
12 Hannah Ritchie and Max Roser, 2021. Deforestation and forest loss

S U STA I N A B L E B Y N AT U R E S E Q U E L :E X P LO R I N G T H E R O OT S O F O U R E X P O S U R E TO D E F O R E STAT I O N-5-Figure 2: Causes of forest loss – deforestation and forest degradation• Global forest loss keeps increasing. In 2022, tropical primary forest loss totalled 4.1 million hectares,
up from 2.7 million hectares13 in 2002.
• 	According to a WWF report14, there are 24 ‘deforestation fronts’ globally, i.e., places that have asignificant concentration of deforestation hotspots.
• Different ‘response options’ to deforestation include commodity or sector specific responses thatinvolve the private sector and investors (figure 3).

13 World Resources Institute, 2023. Tropical Primary Forest Loss Worsened in 2022, Despite International Commitments to End
Deforestation
14 WWF, 2021. Deforestation fronts: drivers and responses in a changing world

S U STA I N A B L E B Y N AT U R E S E Q U E L :E X P LO R I N G T H E R O OT S O F O U R E X P O S U R E TO D E F O R E STAT I O N-6-Figure 315: Response options at the deforestation fronts level• Focusing on the private sector, just a few agricultural commodities produced and consumed bycompanies are driving most of the deforestation and conversion of natural ecosystems in theworld, with cattle, palm oil and soy being the top three contributors16 (figure 4).
Figure 4: Agriculture driven deforestation per commodity
Oil Palm

9%10.5 Mha

Soy

7%

8.2 MhaCattle37%45.1 Mha1%

1.8 MhaCocoa
Rubber plantation
CoffeeWood fiber plantation

123 Mha42%51.1 Mha

Other

15 IPLC: Indigenous people and local communities REDD+: Reducing emissions from deforestation and forest degradation indeveloping countries. The ‘+’ represents activities related to the sustainable management of forests, and the conservation andenhancement of forest carbon stocks.
16 WWF, 2022. Seeing the forest for the trees - a practical guide for financial institutions to take action against deforestation andconversion risks

S U STA I N A B L E B Y N AT U R E S E Q U E L :E X P LO R I N G T H E R O OT S O F O U R E X P O S U R E TO D E F O R E STAT I O N-7-How has BNP Paribas Asset Management addressed this systemic risk so far?
Conscious that deforestation and conversion of natural ecosystems is a systemic risk, we set
ambitious targets in our 2019 Global Sustainability Strategy to reduce the environmental impactof our investments, with a focus on forests: “To support global efforts to halve forest loss by 2020and end forest loss by 2030, we have set targets for relevant companies in our portfolios to comply
with NDPE commitments by 2020 for agricultural commodities (palm oil, soy, paper, timber, and beef
products) and by 2030 from non-agricultural sectors (mining, metals, infrastructure).”As part of our 2021 white paper Sustainable by Nature: Our Biodiversity Roadmap, we published a firstassessment of our exposure to deforestation. We analysed the disclosure, deforestation policies andprocesses of our investees in three GICS17 sectors representing 48% of our corporate AUM18, namely
consumer staples, consumer discretionary and financials. We used selected indicators from the CDP
Forest, Forest 500 and SPOTT databases.
We believe this policy-based assessment was a good first step in understanding our exposure to
deforestation, but it did not allow us to quantify the extent to which our corporate holdings are
driving potential deforestation and conversion of natural ecosystems, in hectares. Indeed, somecommodities contribute more than others to deforestation and conversion of natural ecosystems,with large variations at the country, subnational, municipality and field levels.
In 2022, we analysed the biodiversity footprint of our corporate AUM using the Corporate Biodiversity
Footprint methodology of Iceberg Datalab. The methodology assessed the impact on biodiversity
arising from the use of natural resources and land, including land conversion and deforestation, andemissions of pollutants by the companies in our investment portfolios. We found that land use andland use change accounted for 78% of these corporates’ potential impact on biodiversity.

17 Global Industry Standard Classifications
18 Equities and fixed-income securities, including
asset-backed securities, that we hold in publicly
traded companies. This analysis does not include
asset classes such as sovereign debt, municipal
bonds, private debt or real assets.

S U STA I N A B L E B Y N AT U R E S E Q U E L :E X P LO R I N G T H E R O OT S O F O U R E X P O S U R E TO D E F O R E STAT I O N-8-OBJECTIVE
This research paper aims to quantitatively assess the extent to which our corporate holdings are
driving potential deforestation and conversion of natural ecosystems, in hectares, through theirproduction and consumption of selected forest and ecosystem risk commodities (FERCs) and theirderived products19. We focus on soft commodities as they have been found to contribute the lion’sshare to deforestation worldwide (see introduction section).
Through this quantitative assessment, we want to:• 	Determine whether publicly available datasets developed by NGOs can be used to quantitatively
assess the exposure of our corporate holdings to potential deforestation and conversion of natural
ecosystems and whether they provide satisfactory coverage. In particular, we want to further assessthe data gap and push companies to disclose more.
• 	Identify companies’ production and sourcing of FERCs in countries and regions that have experienced
or are at risk of experiencing recent deforestation and conversion of natural ecosystems, with theobjective to further engage with these companies.
• 	Identify the FERCs produced or consumed by companies we hold that are driving most of thedeforestation and conversion of natural ecosystems. While according to literature, cattle, palm oiland soy are the top three contributors20 to deforestation and conversion of natural ecosystems in
the world, we would like to know if our corporate holdings follow the same trends, and identify
some less obvious FERCs that should also be on our radar.
• 	Create a precedent for the industry through the publication of the quantified potential exposure of
our corporate holdings to deforestation and conversion of natural ecosystems. This should encourage
an open discussion with investors on the usefulness of such analysis to inform their research andengagement.
• 	Identify companies that can make the largest contribution to halting deforestation and conversionof natural ecosystems, and use the results in our internal decision-making tools and engagement.

19 We researched whether we could derive estimates for beef and derived products, chicken, cocoa and derived products, coffeeand derived products, corn, cotton, palm oil and derived products, pork, rubber, soy, sugarcane, timber and derived products.
Our final assessment focuses on beef and derived products, cocoa and derived products, coffee and derived products, palm oiland derived products, rubber and soy. Please see figure 2 for details.
20 WWF, 2022. Seeing the forest for the trees - a practical guide for financial institutions to take action against deforestation andconversion risks

S U STA I N A B L E B Y N AT U R E S E Q U E L :E X P LO R I N G T H E R O OT S O F O U R E X P O S U R E TO D E F O R E STAT I O N-9-HOW OUR WORK RELATES TO EMERGINGVOLUNTARY AND MANDATORY FRAMEWORKS
Several regulations, disclosure frameworks and technical guidance documents
have been published recently that relate to land and biodiversity. Our work
since 2020 relates to a number of the metrics required and recommended bythese frameworks and builds on best practices as detailed in the GHG Protocol
Land sector and Removals (draft) guidance and the Science-based target for Land
guidance.
In particular, a number of metrics disclosed in this research paper can be used
to meet• TNFD21 recommendations for financial institutions, in particular the Recommended
Disclosure B in the Metrics and Targets pillar, which aims at disclosing themetrics used by the organisation to assess and manage dependencies andimpacts on nature.
• 	EU SFDR PAI22, in particular voluntary PAI 1023, 1124, and 1525 as we have notreported these three indicators in our 2023 PAI statement.
• 	Article 29 of the French Law on Energy and Climate. Since 2022, asset managers
are required to report their alignment strategy with long-term biodiversity
targets under this French law. In our Article 29 entity level report, we published
our potential biodiversity footprint and found that land use change is the main
environmental pressure, contributing about 80% of the weighted biodiversity
intensity of our corporate AUM.
This study also helps us conduct materiality screening to prepare for EU legislation
on deforestation-free products and uses some of the same data sources as theEuropean Commission for its materiality assessment.

21 Taskforce on Nature-related Financial Disclosures
22 European Union Sustainable Finance Disclosure Regulation, Principal adverse impact
23 Share of investments in investee companies the activities of which cause land degradation, desertification or soil sealing
24 Shares of investments in investee companies without sustainable land/agriculture practices or policies
25 Share of investments in companies without a policy to address deforestation

S U STA I N A B L E B Y N AT U R E S E Q U E L :E X P LO R I N G T H E R O OT S O F O U R E X P O S U R E TO D E F O R E STAT I O N-10-GENERAL APPROACH
We seek to understand the exposure of our corporate holdings to the risk of sourcing FERCs from anarea recently deforested. Our assessment relies on desk-based estimates rather than field measures,
hence the wording ‘potential deforestation and conversion of natural ecosystems’ (Appendix I & II).
We do not seek to estimate our financed deforestation footprint based on our ownership share ineach company. When providing data at the aggregate level in this research paper, we use two lenses:• 	Sum of our AUM invested in corporates which we know to be exposed to potential deforestationand conversion of natural ecosystems based on publicly available datasets developed by NGOs
• 	Sum of the quantity in tonnes of the FERCs produced/consumed by these corporates, and theassociated number of hectares potentially deforested and/or converted.
Indeed, our objective is not to quantify the potential impact linked to deforestation of our specificfinancial flows and portfolios. We aim to identify the companies we hold that potentially drive
the largest deforestation and conversion of natural ecosystems. In addition, we do not attempt toassess the financial risk associated with our holdings’ contribution to potential deforestation andconversion of natural ecosystems – this would necessitate additional analysis. Our assessment canbe seen, however, as an indication of systemic risk.
We use a constrained perimeter for this study. Namely, we focus on our corporate AUM, referringto the proportion of our assets under management accounted for by investment instruments issuedby companies, as opposed to those issued by sovereigns, sub-sovereigns or agencies. In addition,
we focus on four GICS sectors: consumer staples, consumer discretionary, materials and energy.
These are covered by our deforestation target defined in our Global Sustainability Strategy and/or
are often highlighted as the sectors consuming or producing the highest share of FERCs26.
We devise our own approach to quantify, in hectares, the extent to which our corporate holdings inthese ‘relevant sectors’ drive potential deforestation and conversion of natural ecosystems, basedon four steps (figure 5).

26 We exclude the financial sector because of a lack of data in certain datasets and potential double counting issues. For an assessment of our financial sector AUM exposure to deforestation, see our biodiversity roadmap.

S U STA I N A B L E B Y N AT U R E S E Q U E L :E X P LO R I N G T H E R O OT S O F O U R E X P O S U R E TO D E F O R E STAT I O N-11-Figure 5: Description of the four steps to quantify the extent to which our corporate holdings drive
potential deforestation and conversion of natural ecosystems

Research step

Data sources

FERCs covered

Notes

STEP 1 

Identify thecompanies we holdthat are known to
produce or source
at least one FERC

Analyse thecompanies covered by
CDP, Trase, Forest 500
and Forest IQ

1. Beef and derived
products
2. Chicken
3. Cocoa and derived
products
4. Coffee and derived
products
5. Corn
6. Cotton
7. Palm oil and derived
products
8. Pork
9. Rubber
10. Soy
11. Sugarcane
12. T
 imber andderived products

CDP, Trase, Forest 500
and Forest IQ are publicly available datasetsthat provide information
on FERCs with large
coverages

STEP 2 

Determine the quantityof FERC(s) produced
and/or consumed,
as disclosed by
the companies in
our universe

CDP Forest
Disclosure

1. Beef and derived
products
2. Cocoa andderived products
3. Coffee andderived products
4. Palm oil andderived products
5. Rubber
6. Soy7. Timber andderived products

Further examination of
the datasets revealed
that only CDP Forest
Disclosure provided
data on production andconsumption quantities
of FERCs in a format
that can be easily usedwithout further
treatment28. Thus, thenumber of commodities
we are able to assess
decreased to the seven
shown.

STEP 3 

Estimate the potential deforestation andconversion of natural
ecosystems in hectares
linked to FERC production and/or consumptionof the companies weholdMultiply the quantities
As above, excluding
identified in STEP 2 with timber and derived
deforestation coefficients products
derived from Trase.earthand Dr Pendrill research

We were not able toderive deforestation
coefficients for timberand derived productsof sufficient quality(please refer to Appendix
I for details)

STEP 4 Overlay step 3 resultswith a high-level reviewof the policies andprocesses put in place by
the companies for which
we were able to derivea quantitative potential
deforestation (ha)contribution estimate

Use Forest 500, CDP
and Forest IQ data oncommitments and traceability

These three datasets
include a large range
of indicators on policies
and processes.

As above, excluding
timber and derived
products

27 With contribution from Julie Raynaud, independent consultant, Julie Raynaud | LinkedIn
28 We will explore integrating other data sources in the future, such as FOREST 500, Forest IQ and Trase.

S U STA I N A B L E B Y N AT U R E S E Q U E L :E X P LO R I N G T H E R O OT S O F O U R E X P O S U R E TO D E F O R E STAT I O N-12-Publicly available datasets developed by NGOs allowed us to estimate the potential deforestationand conversion of natural ecosystems in hectares of the companies we hold for six FERCs: beef andderived products, cocoa and derived products, coffee and derived products, palm oil and derived
products, rubber, soy.
Unfortunately, we could not estimate the potential deforestation and conversion of natural
ecosystems linked to timber (and derived products) production and/or consumption due to data
quality issues of the deforestation coefficients. Even though we did not manage to quantify thepotential deforestation and conversion of natural ecosystems in hectares of companies producing or
consuming timber and derived products, we are already engaging with companies in these sectors
where we found that they do not have strong deforestation policies and commitments.
Why did we devise our own approach, instead of using deforestation figures as reported bycorporates themselves?
Several options exist to quantify, in hectares, the extent to which our corporate holdings drive
potential deforestation and conversion of natural ecosystems. The first, and easiest option, consistsof using deforestation figures reported by corporates, for example, via CDP Forests.
The issue is that it is often unclear how these figures are estimated by these corporates and whether
their approach is comparable. Indeed, until recently, no standards on deforestation and land use
conversion existed. With the recent publication of the GHG Protocol Land sector and Removals(draft) guidance and the Science-based target for Land guidance, this is likely to change.
To tackle this, we devise a standardised approach to quantify, in hectares, the extent to which
our corporate holdings drive potential deforestation and conversion of natural ecosystems. Usefulavailable data at the corporate level includes:• Disclosed production and consumption data for each FERC, in tonnes, globally and where available
at national and subnational levels• Deforestation risk coefficient estimates, in hectares per tonnes produced/consumed, globally andwhere available at national and subnational levels, from available datasets and the literature29.
Appendix I describes how we derived these coefficients and Appendix II how to interpret them.

29 Pendrill et al, 2022. Disentangling the numbers behind agriculture-driven tropical deforestation and trase.earth

S U STA I N A B L E B Y N AT U R E S E Q U E L :E X P LO R I N G T H E R O OT S O F O U R E X P O S U R E TO D E F O R E STAT I O N-13-Company A
potential exposure
to deforestation andconversion of natural
ecosystems,in hectares

BNPP AM
corporate holdings
production andconsumption of FERCs,
in tonnes

BNPP AM corporate
holdings exposure topotential deforestationand conversionof natural ecosystems,in hectares=

Quantity of FERC
produced or consumed,by country and/or
subnational whereavailable, in tonnesx

FERC-specificdeforestation risk
coefficient, country
and/or subnational
where available,
in tonnes/hectare=

SUM of the production and consumptionof FERCs of all the corporates
in which we are invested and for which
we have useable data, without taking
into account ownership=

SUM of the potential deforestationand conversion of natural ecosystems of all
the corporates in which we are invested
and for which we have useable data,
without taking into accountour ownership share

S U STA I N A B L E B Y N AT U R E S E Q U E L :E X P LO R I N G T H E R O OT S O F O U R E X P O S U R E TO D E F O R E STAT I O N-14-STEP 1: IDENTIFYING THE COMPANIES WE HOLD THAT ARE KNOWNTO BE EXPOSED TO AT LEAST ONE FERC
A. Methodology and coverage
We first identify the companies in which we invest that are known to produce or source at least one
FERC. We do so by analysing companies covered by CDP, Trase, Forest 500 and Forest IQ.
Together, these four datasets cover twelve FERCs and their derived products: beef and derived
products, chicken, cocoa and derived products, coffee and derived products, corn, cotton, palm oiland derived products, pork, rubber, soy, sugarcane, timber and derived products, as described inAppendix III. Of these, cocoa, palm oil, timber products, soy, cattle products and their derivatives
are included in the new EU legislation on deforestation-free products. These datasets vary in theircoverage of the FERCs, geographies, and actors of the agricultural supply chain. We retained a wide
scope at this stage of the research, reviewing each FERC and company even if covered by only oneof the four datasets.
We focus on four GICS sectors representing 24% of our total AUM. We selected consumer staples,
consumer discretionary, materials, and energy. These are covered by our deforestation target
defined in our Global Sustainability Strategy and/or are often highlighted as the sectors consuming
or producing the highest share of FERCs30. For example, the energy sector is exposed to palm oil andthe materials sector to timber products.
Assessing the overlap between these datasets and our corporate holdings enables us to identify
the companies in which we invest that are known to produce or source at least one of the FERCs in
scope, given the selection methodology followed by the organisations responsible for these datasets.
However, we recognise that other companies in which we invest which are not covered by these four
data providers may also produce or source one or more of these commodities.
To produce aggregate figures of all of our corporate holdings, we aggregated our AUM in the companies
knowingly exposed to at least one of the FERCs in scope.

B. Findings
273 companies in the four sectors are covered by, and report to, at least one of the above datasets,meaning that they are likely to produce or consume at least one FERC. These companies represent
37% of our corporate AUM in the four sectors we are focusing on in this research paper (Appendix IV).
Importantly, this means that we do not know the extent to which the other 63% of our corporate
AUM in relevant sectors is invested in companies that produce or source one or more of the twelve
FERCs, although we expect the figure to be relatively low given that the four datasets we use (CDP,
Forest IQ, Forest 500 and Trase) aim to cover the most important consumers and producers of FERCs.
Breaking down the data further: over 90% of our corporate AUM invested in these 273 companies
were found to be exposed to timber and its derived products; over 70% to palm oil and its derived
products; over 60% to cattle and its derived products; over 50% to soy; and about 30% to rubber, cocoa
and coffee (Figure 6). This split can be explained by the fact that we invest in many downstream
companies that buy multiple FERCs, in particular paper products for packaging. We found little
exposure to cotton, sugarcane, pork and chicken.

30 We exclude the financial sector because of a lack of data in certain datasets and potential double counting issues. For an assessment of
our financial sector AUM exposure to deforestation, see our biodiversity roadmap.

S U STA I N A B L E B Y N AT U R E S E Q U E L :E X P LO R I N G T H E R O OT S O F O U R E X P O S U R E TO D E F O R E STAT I O N-15-These findings are to be interpreted with care as they depend on the coverage of the datasets weuse. For example, corn, cotton, sugarcane, pork and chicken are only covered by Trase, which focuseson traders rather than consumers. This means that our exposure to these FERCs is substantially
underestimated. For example, we invest in many apparel and footwear companies that likely source
large quantities of cotton, but this has not surfaced in our analysis because of the narrow focus ofTrase on traders.

100%
90%
80%

High coverage

70%

Medium coverage
Low coverage

60%
50%
40%
30%
20%
10%

Chicken

Pork

Sugarcane

CottonCorn

CoffeeCocoa

RubberSoy

Cattle products

Oil palm products

0%Timber products% of corporate AUM in relevant sectors
and covered by the four datasets invested
in companies with found exposure to:

Figure 6: Percentage of our corporate holdings invested in companies with direct exposure to thetwelve FERCs considered as part of this research paper within the relevant sectors. Orange: highly
underestimated as the FERC is part of the scope of 1 out of 4 datasets used; Light green: potentially
underestimated (2 out of 4 datasets); Dark green: covered by at least 3 out of 4 datasets.

This first step helps us to understand our exposure to companies sourcing and/or producing FERCs.
However, FERCs contribute differently to deforestation and conversion of natural ecosystems, withlarge variation at the country, subnational, municipality and field levels. Therefore, we need to go
further than assessing data on production and sourcing exposure alone to understand the extent
to which our corporate holdings drive deforestation and conversion of natural ecosystems.
The second step to reach such a result consists in determining the quantity of FERC produced and/or consumed.
We know from our literature review that cattle expansion is currently the most important deforestation
driver, contributing to around half of tropical agricultural deforestation, mostly in South America.
Palm oil and soy account for at least a fifth of agricultural deforestation in both South America andsoutheast Asia. Finally, rubber, cocoa, rice, maize and cassava contribute to the remaining tropicalagricultural deforestation31.

31 Pendrill et al, 2022. Disentangling the numbers behind agriculture-driven tropical deforestation

S U STA I N A B L E B Y N AT U R E S E Q U E L :E X P LO R I N G T H E R O OT S O F O U R E X P O S U R E TO D E F O R E STAT I O N-16-STEP 2: IDENTIFYING THE QUANTITY OF FERC PRODUCED AND/OR CONSUMED
A. Methodology and coverage
We retrieve and consolidate disclosed data on FERC production and consumption quantities. To do so,
we use CDP Forest disclosures as further examination of the datasets revealed that only CDP Forest
Disclosure provided data on production and consumption quantities of FERCs in a format that caneasily be used without further treatment. We will investigate in the future whether data from otherdatasets can be incorporated to expand coverage.
We also retrieve information, where disclosed, on sourcing and production locations. In the case thatsome companies provide only partial geographic disclosure, we allocate a percentage of quantities
of FERCs to a specific country based on FAOstat. Details on how quantity data on FERCs produced or
consumed have been gathered are available in Appendix I & VII.
Since CDP Forest covers a subset of seven FERCs and their derived products, the number of commodities
we are able to include in step 2 decreases to these seven: Beef and derived products Cocoa and derived products Coffee and derived products
 Palm oil and derived products
 Rubber
 Soy
 Timber and derived productsCompanies that are likely to produce or consume the covered FERCs are invited to reply to CDPForest every year, but this does not necessarily mean that they do. These data are self-reported bycompanies, and it is unclear whether all the data is audited. In 2022, we participated in the annual
CDP Non-Disclosure Campaign designed to encourage companies with big impacts on climate, forests
and water to improve their disclosure using the long-established and widely used CDP questionnaires.
In relation to the engagement in which we were directly involved, we had an encouraging 19% successrate in terms of companies actually disclosing to CDP Forest as of 2022.
On average, nearly 40% of our corporate AUM in the four sectors found to be exposed to the FERCs
on any of the four datasets report quantitative data to CDP on production and/or consumption32.
Most of these companies report data for their entire operations. Data availability is higher on palmoil, and scarcer on cocoa and coffee (Appendix V).

32 Please note we could obtain quantitative data on FERC production and/or consumption for 152 companies representing 29% ofcorporate AUM in the 4 relevant GICS sectors, and that the scope of our corporate AUM does not include residual exposures insome funds delegated by BNPP AM or managed by BNPP AM affiliate entities.

S U STA I N A B L E B Y N AT U R E S E Q U E L :E X P LO R I N G T H E R O OT S O F O U R E X P O S U R E TO D E F O R E STAT I O N-17-On average, nearly 25% of our corporate AUM in these sectors found to be exposed to one or more
FERCs on any of the four datasets report quantitative data to CDP on production and/or consumption
in at least one country considered at risk by CDP. Again, there is more data available for palm oiland less for rubber.
In addition, 27% of our corporate AUM in these sectors report subnational exposure on palm oil inIndonesia (province), 22% on soy in Paraguay (department), Argentina (province) and/or Brazil (region),and 8% on cocoa in Ivory Coast (department) and cattle products in Brazil (region).

B. FERCs consumption and production quantities
When taking into account quantities based on disclosure, the companies we hold are exposed mostly
to timber products and palm oil production, as well as companies consuming timber products, soy,palm oil and cattle products. Cocoa, rubber and coffee are the commodities to which they are theleast exposed33 (figure 7).
Most companies we hold are exposed to FERCs through their supply chains, except for palm oil,where we invest in three producers (due to our palm oil policy which has led to exclusion of manysuch producers) for which we could obtain production data; and timber products for which we could
obtain production data for 20 companies that produce timber and related products that we invest in.
The 28 companies we hold for which we could retrieve data on cattle product consumption collectively
sourced less than 10% of the global beef production in 2020. We estimate that 10% of the consumed
cattle product quantities of our corporate holdings is likely to come from Brazil based on companies’
disclosure and FAOstat, and less than 1% from Paraguay, which is a high-risk geography.
In addition, our agriculture policy has led us to reduce our exposure to beef producers.
The 10 companies for which we could retrieve data on cocoa consumption sourced about 30% of the
global production in 2020. About half comes from Ivory Coast, based mostly on company disclosure.
The 85 companies for which we could retrieve data on palm oil consumption and production together
represented about 40% of global production in 2020. About 60% of our corporate holdings palm oil
consumption and production came from Indonesia (based on company disclosure and FAOstat data.)

33 Please note this scope does not include residual exposures in some funds delegated by BNPP AM or managed by BNPP AM
affiliate entities.

S U STA I N A B L E B Y N AT U R E S E Q U E L :E X P LO R I N G T H E R O OT S O F O U R E X P O S U R E TO D E F O R E STAT I O N-18-

Figure 7: Disclosed FERCs production quantities (left) and consumption quantities (right) in tonnes
and geographical split (disclosed or estimated)
PRODUCTIONCONSUMPTION
Cattle products~ 6 000 000 t

Palm oil~ 13 000 000 t

Cocoa~ 2 000 000 t

Other countries~ 68 000 000 t

Coffee~ 1 000 000 t

Other countries

Palm oil~ 180 000 000 t~ 17 000 000 t

Soy~ 24 000 000 t

Timber~ 84 000 000 t

BrazilBrazil~ 23 000 000 t~ 34 000 000 t

Indonesia~ 12 000 000 t

Indonesia~ 4 000 000 t

Malaysia~ 3 000 000 t

Timber~ 184 000 000 t

Colombia

Ivory Coast

Argentina
Ivory Coast
Colombia

Argentina

RubberMalaysia~ 5 000 000 t

Paraguay
Peru
Rubber

~ 1 000 000 t

S U STA I N A B L E B Y N AT U R E S E Q U E L :E X P LO R I N G T H E R O OT S O F O U R E X P O S U R E TO D E F O R E STAT I O N-19-

STEP3 : E STIMATE THE POTENTIAL DEFORESTATION AND CONVERSION OF NATURALECOSYSTEMS LINKED TO FERC PRODUCTION AND/OR CONSUMPTION
We estimate the potential deforestation and conversion of natural ecosystems linked to the production
and/or consumption of FERCs driven by the companies we hold (Figure 5). We multiply the quantities
identified in STEP 2 with deforestation coefficients derived from Trase.earth and the work of Dr Pendrill,a recognized expert at Chalmers University of Technology. Please refer to Appendix I & II for details
on the methodology used to estimate potential contribution to deforestation and the interpretationof deforestation results.
Since we could not derive deforestation and conversion of natural ecosystems coefficients for timberand derived products of sufficient quality, the number of commodities we can include in STEP 3
decreases to these six: Beef and derived products Cocoa and derived products Coffee and derived products
 Palm oil and derived products
 Rubber Soy
Using our proprietary methodology of estimation of deforestation and conversion of natural
ecosystems, we found that the largest share of potential deforestation and conversion of natural
ecosystems accounted for by our corporate holdings’ production and consumption of FERCs is inIndonesia, Malaysia, Ivory Coast and Colombia (figures 8 & 9).
Palm oil is the FERC that contributes the most, by far, to the potential deforestation and conversionof natural ecosystems of our corporate holdings, followed by cocoa and cattle-related products. Palmoil and cattle products have been on investors’ radar for some time, but these results suggest thatcocoa should be a priority too. Cattle products do not contribute much due to our agriculture policy(explained above). As a result, many companies in which we invest source only by-products (fat orleather) which are attributed a lower potential deforestation and conversion of natural ecosystems
impact than beef products.

S U STA I N A B L E B Y N AT U R E S E Q U E L :E X P LO R I N G T H E R O OT S O F O U R E X P O S U R E TO D E F O R E STAT I O N-20-

Figure 8: Estimated amount of deforestation and conversion of natural ecosystems by companies in
relevant sectors in our corporate holdings disclosing at least partial quantitative data on production
and consumption (in hectares). Please note timber products are not included in this assessment due
to methodology limitations (please refer to Appendix I – general approach for details)
OTHER COUNTRIES~ 37 000ha~ 30 000haConsumption

Production

MALAYSIA
COLOMBIA
Cattle products
Cocoa
CoffeePalm Oil
Soy
Rubber~ 33 000haConsumption~ 400 haConsumption

PERU~ 2000ha
Consumption~ 43 000
ha

BRAZIL~ 14 000haConsumption~ 133 000ha

IVORY COAST

Consumption~ 26 000ha~ 14 000haConsumption

Production~ 19 000
ha

PARAGUAY
Consumption

Production

INDONESIA

Figure 9: Estimated amount of deforestation and conversion of natural ecosystems by companies
in relevant sectors in our corporate holdings production (left) and consumption (right) in hectares,
and geographical split
PRODUCTIONCONSUMPTION
Cattleproducts~ 26 000 ha

Cocoa~ 47 000 ha

Other countries~ 30 000 ha

Indonesia~ 133 000 ha

Coffee~ 5 000 ha

Ivory Coast~ 43 000 ha

Other countries~ 37 000 ha

Palm oil~ 64 000 ha

Indonesia

Palm oil~ 202 000 ha~ 19 000 ha

Colombia~ 33 000 ha

Malaysia~ 26 000 ha

BrazilMalaysia~ 14 000 ha~ 14 000 ha

Soy

Paraguay

Rubber~ 400 ha~ 7 000 ha~ 5 000 ha~ 2 000 ha

Peru

Argentina~ 70 haS U STA I N A B L E B Y N AT U R E S E Q U E L :E X P LO R I N G T H E R O OT S O F O U R E X P O S U R E TO D E F O R E STAT I O N-21-The potential deforestation and conversion of natural ecosystems driven by our corporate holdings
FERC production and/or consumption is concentrated among a few companies, based on the data
available. We find that the top-10 contributing companies represent 8% of our corporate AUM and
82% of the total potential deforestation to which companies in our universe are linked (figure 10).
Figure 10: Top-10 companies in AUM (left) and hectares (right) exposed to deforestation (bothfrom production and consumption).
100%

100%

80%

80%

60%

60%

40%

40%

20%

20%

0%

0%
% of AUM of the rest of companies exposed
to deforestation (both from production
and consumption)% of AUM of top 10 companies exposed
to deforestation (both from production
and consumption)% deforestation in hectares driven
by the rest of the companies exposed
to deforestation(both from production
and consumption)% deforestation in hectares driven
by top 10 companies exposed
to deforestation(both from production
and consumption)

We can drill down to understand the sub-national impacts of companies. For example, we find thatmost companies disclosing province level exposure for their palm oil sourcing and production sourcefrom provinces identified as most at risk in Trase.earth (Figure 11).
Figure 11: Sub-national exposure to deforestation risk – palm oil in Indonesia (above: Trase.earth
data publicly available, below: BNPP AM exposure based on CDP Forest disclosure)% of corporate AUM exposed
to FERCs as per all datasets,in relevant sectors, withsubnational exposure
disclosure, exposed
to region of production

100%
80%
60%
40%
20%
0%

Kalimantan
Barat

Kalimantan
TenggahKalimantan
Timur

Papua

S U STA I N A B L E B Y N AT U R E S E Q U E L :E X P LO R I N G T H E R O OT S O F O U R E X P O S U R E TO D E F O R E STAT I O N-22-STEP 4 : O VERLAYING COMPANIES’ IMPACTS WITH A HIGH-LEVEL REVIEWOF THEIR POLICIES AND PROCESSESThe above results indicate the potential deforestation and conversion of natural ecosystems driven
by our corporate holdings’ FERC consumption and/or production, without considering the measuresand policies that these companies may have already put in place to stem or end such nature loss.
We continue our assessment by combining our estimates of potential deforestation and conversionof natural ecosystems with policy-based indicators, as found in Forest 500, CDP, SPOTT and Forest
IQ, and in line with the assessment in our Sustainable by Nature publication in 2021. As in step 3, we
focused on six FERCs (beef and derived products, cocoa and derived products, coffee and derived
products, palm oil and derived products, rubber, soy).
We look at two aspects:
1 - ‘Deforestation-free’ claims made by companies
2 - No deforestation commitments.

A. Assessing deforestation-free claims of companies
A growing number of companies that produce or source FERCs claim their supply chains are
deforestation-free.
We investigate the actual share of the potential deforestation and conversion of natural ecosystems
driven by our corporate holdings’ consumption and/or production of FERCs that is:• Already deforestation-free based simply on the company’s assertion that this is the case• Already deforestation-free based on company’s assertion and our assessment that a strong
traceability system is in place34.

34 See Appendix VIII for more details.

S U STA I N A B L E B Y N AT U R E S E Q U E L :E X P LO R I N G T H E R O OT S O F O U R E X P O S U R E TO D E F O R E STAT I O N-23-

Figure 12a and 12b: Land deforested or natural ecosystems converted (in hectares) due to theconsumption and production of FERCs by the companies in our universe, taking into account any
deforestation-free claims by companies (second bar) and taking into account deforestation-freeclaims only from companies with strong traceability systems (third bar)
PRODUCTION
Potential hectares
deforested or converted

Potential hectares
deforested or converted
70 000300 000

Other - Rubber

250 000

60 00050 00030 000Palm
oilPalm oilPalm
oil

20 000
10 000

Other - Rubber

Deforestation

Cattle products

Other - Coffee

Soy

Other - Rubber

200 000

Other - Rubber

40 000

CONSUMPTION

Deforestation
Deforestation
when netting out
when netting out"deforestation free" "deforestation free"claims by companies
claims bycompanies
with adequate
traceability

150 000Palmoil

100 000
50 000-

Other Cocoa
Deforestation

Palm
oil
Other Cocoa

Palm
oil
Other Cocoa

Deforestation
Deforestation
when netting out
when netting out"deforestation free" "deforestation free"claims by companies
claims bycompanies
with adequate
traceability

A large share of the potential deforestation and conversion of natural ecosystems driven by our
corporate holdings’ consumption and/or production of FERCs is declared ‘deforestation-free’ by thecompanies reporting to CDP.
Figure 12a shows that most of the potential deforestation and conversion of natural ecosystems linked
to FERCs producers in scope – effectively 100% - are covered by deforestation-free claims (second
column). Figure 12b shows that for companies that consume the six commodities covered, around
60% of potential deforestation and conversion of natural ecosystems is covered by deforestation-freeclaims. These figures vary substantially by FERC, with over 70% of soy and palm oil consumption said
to be deforestation-free compared to less than 5% for cocoa (second column).
Yet, this is not the end of the story. Indeed, additional research is needed to determine whether we,as an investor:• Agree with the definition of ‘deforestation-free’ used by companies• Can trust their deforestation-free claims.

S U STA I N A B L E B Y N AT U R E S E Q U E L :E X P LO R I N G T H E R O OT S O F O U R E X P O S U R E TO D E F O R E STAT I O N-24-For example, a preliminary assessment shows that:• 	Only about 37% of the potential deforestation and conversion of natural ecosystems is declared‘deforestation-free’ by producer companies that have ‘strong’ traceability systems (third column
in figure 12a).
• 	Only about 36% of the potential deforestation and conversion of natural ecosystems is declared‘deforestation-free’ by consumer companies that have ‘strong’ traceability systems (third column
in figure 12b).
This raises questions over the credibility of these claims.

Additional research and engagement are needed with the most exposed companies to deforestationand conversion of natural ecosystems that:• Do not claim ‘deforestation-free’ consumption or production• Declare a large proportion of commodities ‘deforestation-free’, but do not have strong traceability
systems in place based on our preliminary research• Declare a large proportion of commodities ‘deforestation-free’ and have traceability systems inplace, based on our preliminary research, to understand if it is truly adequate when digging deeper
into their practices.

B. Assessing the impact of commitments
As a last step, we investigate what the potential deforestation and conversion of natural ecosystems
driven by our corporate holdings’ consumption and/or production of FERCs would be in 2030 if allcompanies that have made a strong commitment ‘walked the talk’ and deliver on those commitments.
To do so, we :1. Hold constant the production/consumption of relevant FERCs for companies that do not havea strong ‘No deforestation’ or ‘No land conversion commitment’ (or have no commitment);
2. Suppose that companies with a strong35 commitment will respect it by the stated time horizon;
and
3. Assume that companies that state that they have already achieved their targets did so in 2023.

35 By strong commitment, we mean full coverage. See Appendix VIII for details

S U STA I N A B L E B Y N AT U R E S E Q U E L :E X P LO R I N G T H E R O OT S O F O U R E X P O S U R E TO D E F O R E STAT I O N-25-We then compare the projected rate of decrease of our corporate holdings potential deforestation andconversion of natural ecosystems to the required rate as embedded in the Inevitable Policy Response(IPR) Forecast Policy Scenario (FPS) + Nature scenario (see Box 2 for details).
• We find that if companies we hold with a strong ‘No deforestation’ or conversion’ commitment walkthe talk, nearly 1.8m hectares of deforestation or conversion of natural ecosystems will have been
avoided by 2030 versus business-as-usual (representing a decrease of over 80% between 2020 and2030). The largest contribution to this change, by far, is palm oil.
• The IPR FPS + Nature scenario estimates that between 2010 and 2020, global net deforestation
was 4.7 million hectares per year, based on FAOStat data. It also estimates that between 2020 and
2030, on average 3.3 million hectares will need to be protected from deforestation each year. If webelieve that the corporates we hold will deliver on their commitments, the deforestation avoided
by these companies will contribute a growing share of avoided deforestation as required under the
IPR FPS + Nature scenario of up to 6% in 2030, i.e., 1.8 million divided by about 33 million hectares,
as illustrated in Figure 13. In addition, the cumulative deforestation of companies we hold should
fall at a faster pace than what is required under the IPR FPS + Nature scenario to reach global
climate and biodiversity goals.
These results are to be interpreted with care because corporates disclosing FERCs data are potentiallymore advanced, and more likely to have a commitment, than others. In addition, the assessment
above, including the comparison with the IPR FPS + Nature scenario, is based on a range of strong
assumptions and takes at face value corporate commitments.

3000 000

7%2500 000

6%2000 000
1500 000

5%4%3%1000 0002%500 000

1%-

0%2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030
Cumulative ha of land where deforestation and land conversion
was potentially avoided due to commitments
Cumulative ha of land deforested or converted
Universe cumulative avoided as a % of scenario cumulative avoided% of cumulative deforestation
avoided as a % of avoided
deforestation in IPR + Nature

Ha of land deforested
or natural habitat converted

Figure 13: Scenario analysis – What if corporates walk the talk on their sourcing commitments?

S U STA I N A B L E B Y N AT U R E S E Q U E L :E X P LO R I N G T H E R O OT S O F O U R E X P O S U R E TO D E F O R E STAT I O N-26-PROJECTING THE POTENTIAL DEFORESTATION AND CONVERSION OF
NATURAL ECOSYSTEMS DRIVEN BY OUR CORPORATE HOLDINGS’
CONSUMPTION AND/OR PRODUCTION OF FERCSAs outlined above, we have used the data to undertake a scenario analysis, as mentioned by
the TNFD Guidance. Our objective was to investigate whether we can project the potential
deforestation and conversion of natural ecosystems driven by our corporate holdings’
consumption and/or production of FERCs to 2030 and compare it to a scenario that captures
what is needed to achieve global climate and biodiversity goals.
We used corporate commitment data to project the potential deforestation and conversion ofnatural ecosystems driven by our corporate holdings’ FERC consumption and/or production
to 2030, using only commitments that have an appropriate coverage, relate to deforestationor conversion, and which are accompanied by the implementation of a traceability system.
For companies that have no commitment (or a commitment that is not strong enough by ourcriteria, see Appendix V), we hold their potential deforestation constant. These hypotheses
would need to be further refined in the future.
There are few publicly available model pathway scenarios for achieving both climate andbiodiversity goals. According to the UN PRI, the “IPR FPS + Nature is the first integrated natureand climate scenario for use by investors. […] It represents a ‘beta version’ scenario of whatmight happen when nature-related policy is incorporated into a climate-related scenario.
[…] The IPR FPS + Nature incorporates key additional policy levers that support the naturetransition – land protection, land restoration and nature markets.” BNPP AM is one of IPR
project’s strategic partners.
Levers include government efforts to protect and restore land, the emergence of voluntary
nature markets and a range of other policy measures at the nexus of land use, climate andnature (carbon pricing, bioenergy, diets, deforestation, sustainable agriculture and food waste).
Among the key outcomes for the environment of the IPR FPS + Nature scenario are the following:• Planned policy action by governments would halt and reverse global biodiversity loss,
potentially achieving 2000 levels of biodiversity intactness by 2045.
• Global forest land could increase by 273 million ha by 2050, with net deforestation endingby 2030, achieving levels of forest cover equivalent to levels in the early 1990s and reflecting
a strong enforcement of legislation protecting forests in countries with high levels ofdeforestation.
Net zero is a key focus of organisations, governments and businesses worldwide. It is becoming
clear that achieving net zero only through the reduction of CO2 emissions by large corporates
is unlikely to suffice. Unavoidable emissions will remain despite best efforts given the existing
technological constraints. Therefore, significant investment in reforestation, afforestationand nature-based solutions will be critical to achieving net zero. With our new sustainable
forestry partner IWC, we aim to offer clients an enhanced range of sustainable solutions thatcomplement our private markets capabilities and contribute to reducing the net zero financing
gap and enabling a just transition for nature.

S U STA I N A B L E B Y N AT U R E S E Q U E L :E X P LO R I N G T H E R O OT S O F O U R E X P O S U R E TO D E F O R E STAT I O N-27-

EXPLORATORY OUTCOMES
The objective of this research paper is to determine whether publicly available data developed byNGOs can be used to quantitatively assess the extent to which our corporate holdings are driving
potential deforestation and conversion of natural ecosystems.
We have shown in our key findings that it is possible for a large asset manager to do so based on
publicly available data with higher-than-expected coverage. We made our methodology open-source
to help other investors on their own journey towards deforestation-free portfolios. This investigation
to quantify the potential deforestation and conversion of natural ecosystems driven by our corporate
holdings’ consumption and/or production of FERCs is another step on our biodiversity journey which
we embarked on several years ago.
Our analysis does not take the final step of assessing the proportion of deforestation and conversionof natural ecosystems that we are exposed to, i.e., by multiplying the final figures by our holdings
in each company to generate a ‘financed deforestation’ figure. It presents the total exposure of all
investors in these companies. As such, we urge investors to use this type of analysis to inform theirresearch and engagement, especially those joining the Nature Action 100 (NA100) initiative.

A. Closing the data gap
We acknowledge there are gaps and weaknesses, but these serve only to reinforce calls we and others
have made for some time. There are gaps in company and sector coverage of the four organisations
whose data we have used; we hope funders and regulators will come forwards soon to help close
these gaps and thereby furnish investors (and other stakeholders) with the critical data we need tounderpin our research and engagement. The data we have used from CDP Forest Disclosure is (forthe most part) not audited; to have greater confidence in this data, we urge companies to subject
this type of traceability data to third-party validation. We have not assessed all soft commodities
nor all GICS sectors, but focused on those known to be the largest users of FERCs. To improve thescope and data quality of this analysis, the following avenues could be explored:• Extending the potential deforestation estimate to timber products (including pulp and paper) as
we could not go further than step two, i.e., identifying the quantity of timber produced and/or
consumed in this analysis• Exploring additional data sources such as the percentage of certified commodities. In particular, theACOP (Annual Communication of Progress) reports submitted by RSPO members gauge their progress
towards 100% RSPO certified sustainable palm oil• Pushing companies to disclose quantitative information related to their sourcing and productionof FERCs, through CDP Forest questionnaire, for example• Devising a solid estimation approach for corporates that do not disclose any quantitative data on
FERC sourcing and production• Exploring whether a similar analysis could be done for deforestation driven by non-agriculturalcommodities, e.g., mining or in other GICS sectors.

S U STA I N A B L E B Y N AT U R E S E Q U E L :E X P LO R I N G T H E R O OT S O F O U R E X P O S U R E TO D E F O R E STAT I O N-28-

B. Engaging with the laggards
Nevertheless, this study enables us to focus our research and engagement on the systematicallymost important contributors to potential deforestation and conversion of natural ecosystems, andcreate engagement and action lists. Several angles could be explored:• Inadequate disclosure: Companies in relevant sectors that report only partial quantitative data and/or no quantitative data. We found that 97 companies out of 273 do not disclose any quantitative
data related to their production or consumption of FERCs.
• Inadequate policy commitments or traceability systems36: Companies in our portfolios that
potentially drive the largest share of deforestation and conversion of natural ecosystems and that
do not have strong NDPE policies or traceability systems.
• 	Inadequate claims: Companies that claim deforestation-free production and consumption, buthave not put in place strong traceability systems. We found that 35 companies out of 66 claim
deforestation-free production and consumption, but do not have strong traceability systems inplace.
Out of these companies, 32 are on the target list of Nature Action 100, a global investor engagement
initiative which we helped launch. To address systemic risk in our portfolios, we believe collaboration
with other investors is key.
In addition, it would be interesting to engage with companies with strong NDPE policies and traceability
systems that potentially drive the largest share of deforestation and conversion of natural ecosystems
to ensure that they ‘walk the talk.’
Finally, an exploratory assessment of the projected potential deforestation impacts driven by our
corporate holdings in 2030 finds that if all companies that have made a strong commitment deliver it,
our corporate holdings (for which we have data) are likely to be on the right track in terms of curbing
and halting deforestation and conversion of natural ecosystems. Engagement with companies andpublic authorities remains our priority to ensure that these companies walk the talk. Worryingly, we
remain ‘blind’ with respect to a large number of our corporate holdings that do not report any data.

C. Educating portfolio managers and clients
This exploratory work has resulted in a systematic corporate investment screening tool that allows
us to sense-check and continue the implementation of our biodiversity roadmap. In particular, we
now have a better picture of the geographies (i.e., countries or sometimes even more precise areas
such as a Brazilian region or an Indonesian province) from which the companies in which we invest
are sourcing or producing FERCs.
We plan to apply this methodology to specific funds and client portfolios, taking into account ourownership of these corporates and comparing it to their benchmarks, and then using this information
to engage with and educate clients on deforestation-related risks in their portfolios. The database that
we have built allows us to provide tailor-made analysis for clients based on their specific portfolios.
We intend to use this research as a lens to identify potential investment opportunities in companies
that are managing their FERC impacts and risks appropriately.

36 It should be noted that these companies have been identified from among our holdings that disclose adequate data to allow
us to make these assessments. Our holdings that lack adequate disclosure may include companies with a greater share ofpotential deforestation.

S U STA I N A B L E B Y N AT U R E S E Q U E L :E X P LO R I N G T H E R O OT S O F O U R E X P O S U R E TO D E F O R E STAT I O N-29-D. Leveraging the six pillars of our approach to sustainability to address deforestation challenges
Through the six pillars of our approach to sustainability, we will continue to seek to reduce theenvironmental impact of our investments, with a focus on forests.
• Over the past years, we have been working to quantify our dependencies and impact on biodiversity
and forests. This study is an additional step to quantitatively assess the exposure of our corporate
holdings to potential deforestation and conversion of natural ecosystems through corporate production
and consumption of FERCs. Ideally, we would update this analysis regularly to follow up on theevolution of our investments. Ultimately, we aim to include these datasets systematically into
investment decisions through our ESG scoring. In particular, through this analysis, we can provide
portfolio managers with a better picture by FERCs of companies either lagging or leading efforts tohalt deforestation and conversion of natural ecosystems.
• We engage with the highest-impact industries with a core focus on deforestation and water issues. We
have joined the Investor Policy Dialogue on Deforestation (IPDD) initiative to target our engagement
on deforestation with public agencies and industry associations in Indonesia, Brazil and consumer
countries. We have been playing a leading role in developing and launching the collaborative
investor initiative Nature Action 100 which aims to engage companies that are the systemicallymost important in reversing nature loss by 2030.
• Our palm oil, wood pulp and agriculture sector policies include criteria related to deforestation. In
particular, BNP Paribas will require full traceability of beef and soy (direct and indirect) channels by
2025 in the Brazilian Amazon and Cerrado. We intend to review the potential to extend the scopeof the BNPP AM target for relevant companies in our portfolios to comply with NDPE commitments
for agricultural commodities (palm oil, soy, paper, timber, and beef products) to cocoa, coffee andrubber products.
• We are participating in private and public partnerships and collaboration initiatives to give more
visibility to nature and learn how to better account for it. We helped launch the Task Force on Naturerelated Financial Disclosures (TNFD), a corporate reporting framework to address nature-related risks.
• We are providing clients with a range of solutions targeted at solving biodiversity challenges.
The BNP Paribas Ecosystem Restoration fund invests in companies that are engaged in improving
aquatic, terrestrial and urban ecosystems services through their products, services or processes.
Examples include sustainable forestry or alternative proteins. In addition, we took a majority stakein International Woodland Company. IWC will enhance our offering in sustainable timberland
investments through our Private Assets unit.

S U STA I N A B L E B Y N AT U R E S E Q U E L :E X P LO R I N G T H E R O OT S O F O U R E X P O S U R E TO D E F O R E STAT I O N-30-APPENDIX I

General approach of our in-house methodology to estimate potential
contribution to deforestation
Our corporate holdings’ potential exposure to deforestation and conversion of natural ecosystems is
estimated following the formula below:

Company A
potential contribution
to deforestationand conversionof natural ecosystems,in hectares=

Quantity of FERC
produced or consumed,by country and/or
subnational
where available,
in tonnesx

FERC-specificdeforestation risk
coefficient, country
and/or subnational
where available,
in tonnes/hectare

In addition to deforestation and conversion of natural ecosystems analysis at national level, we also
look at subnational exposure for some FERCs in some regions such as soy in Brazil (region), Argentina(province) and Paraguay (department), palm oil in Indonesia (province), cattle products in Brazil(region) and Paraguay (department), and cocoa in Ivory Coast (department).

GATHERING QUANTITY DATA ON FERCS PRODUCED OR CONSUMED
We use disclosed production and consumption data at FERC-level, and in certain cases national andsub-national levels. This data is available in CDP Forest, Forest 500, Forest IQ and Trase. These data
are usually self-reported by companies, and it is unclear whether any of this data was audited. We
prioritize CDP Forest as we find them the easiest to use without further treatment and will investigate
how to integrate Forest 500, Forest IQ, and Trase quantitative data in the future.
One difficulty is the difference in coverage and partial overlap between CDP data, which is basedon corporate voluntary disclosure, and Trase.earth data, which is based on supply chain data (trade
datasets). In addition, CDP focuses on production and consumption, while Trase.earth investigates
imports and exports37. We therefore use CDP data given its wider coverage, in terms of geography
and number of companies in our universe, as well as its focus on production and consumption.

37 The overlap between imports and consumption on the one hand, and exports and production on the other hand, is notnecessarily perfect, therefore we cannot make this assumption.

S U STA I N A B L E B Y N AT U R E S E Q U E L :E X P LO R I N G T H E R O OT S O F O U R E X P O S U R E TO D E F O R E STAT I O N-31-We also gather export and import data from Trase.earth where available, but keep it separate from
CDP data, and do not disclose the results in this report. Only 17 companies in our universe are coveredby Trase.earth given our main exposure to downstream companies, and most of these companies
are covered in CDP Forest.
Our calculation procedure is as follows:• We include only quantitative disclosures when reported in units that can be converted to tonnage
using coefficients from the literature. When it is not, we exclude the disclosure.
• We quantify total exposure using full and partial disclosures38.
• We quantify country-specific exposure as reported by the company, where available, and allocate
the rest to ‘Unknown countries’39.
• We allocate our exposure to ‘Unknown countries’ to geographies with deforestation risk using
FAOStat 2020 data.
• Where disclosed, we gather exposure data at subnational levels for soy in Brazil (region), Argentina(province) and Paraguay (department), palm oil in Indonesia (province), cattle products in Brazil(region) and Paraguay (department), and cocoa in Ivory Coast (department).
• We quantify the volumes of FERCs produced or consumed at subnational levels using averagevolume data from Trase.earth.

DERIVING DEFORESTATION AND CONVERSION OF NATURAL ECOSYSTEMS COEFFICIENTSThe GHG Protocol Land sector and Removals (draft) guidance and the Science-based target for Land
guidance provide information on how to assess a company’s contribution to land use change. The
Protocols distinguish between measured land use change, at land management unit level (‘direct land
use change’), applicable in cases with high traceability, and estimated land use change (‘statisticalland use change’).
While not mentioned in these guidance documents, it is clear that only the statistical land use change
approach can be used by investors for a large universe to estimate portfolio-level deforestation
exposure. This statistical land use change estimation could be, as a second step, completed bydirect land use change data gathered though engagement with investees that use the ‘direct land
use change approach’.

38 As declared by the reporting company. Full disclosure refers to disclosure over the full perimeter of the company (geography
and activities).
39 A number of companies also report for countries/ regions not considered at risk by CDP, we include this in our analysis.

S U STA I N A B L E B Y N AT U R E S E Q U E L :E X P LO R I N G T H E R O OT S O F O U R E X P O S U R E TO D E F O R E STAT I O N-32-Deforestation and conversion of natural ecosystems data at FERC-level is available in specialized
publications, ad-hoc tools and life-cycle analysis datasets, based on a variety of methodologies.
We evaluated publicly available sources40 based on 1. FERC and country coverage 2. Frequency of
updates 3. Recognised source, and 4. Whether it follows best practice as set out in the GHG Protocol
and SBTN Land Guidance.
We find that Trase FERC deforestation exposure coefficients meet most, if not all, of our selection
criteria. They are updated annually, derived by recognized institutions and used in peer- reviewed
articles, cover a number of country-FERC with high deforestation risk, are publicly available and arederived using geospatial analysis on deforestation and crop expansion.
Yet, they cover only a small number of FERCs/countries. In order to increase the coverage of the data,
we decided to combine Trase data with data derived by Dr Pendrill, as the two datasets have alreadybeen combined in prior work. Because Trase data relies on geospatial analysis, we prioritised it over Dr
Pendrill’s data and used the latter to ‘fill the gaps’, in line with recommendations and prior studies41.
The differences between these two methods precludes any direct comparison42. In addition, it isessential to understand how these coefficients were derived and how to interpret the results. Appendix
VI details the methodology used by Trase and Dr Pendrill and Appendix II provides a deeper analysisof the interpretation of the results.
These coefficients represent averages and are uncertain. We found it difficult in some cases tounderstand how they were estimated by Trase and Dr Pendrill, in particular in relation to relative
exposures, and we therefore had to make a number of assumptions:
Our calculation procedure is as follows:• We derive country and FERC-specific deforestation coefficients using the approach described inAppendix II. Where available, we also use sub-national level coefficients.
• We apply these coefficients to disclosed production and consumption quantities (see above). When
sub-national or country level data is not available, we use volume-weighted averages.
• We use the same coefficients for consumers and producers rather than trying to assign a relative
impact to each as we believe that both types of actors are equally responsible. When adding
consumption and production data, this may lead to double counting. This is why we have kept thefigures separate throughout our assessment.

40 GHG Protocol, SBTN and from our own research
41 Trase, 2022. Assessing tropical deforestation in Germany’s agricultural commodity supply chains
42 Trase, 2022. Approaches to assessing commodity-driven deforestation

S U STA I N A B L E B Y N AT U R E S E Q U E L :E X P LO R I N G T H E R O OT S O F O U R E X P O S U R E TO D E F O R E STAT I O N-33-• When production and consumption quantities relate to a derived product (e.g., roasted coffee beansor beef extracts), we apply a conversion coefficient to take into account losses in the transformation
process. For example, we estimate that to produce 1kg of roasted beans coffee, 1.25kg of green
coffee is necessary.
• When the quantities relate to a by-product (beef fat or leather), we apply an allocation coefficient– meaning that the deforestation footprint is only a fraction of that of beef43. We derive these
allocation coefficients based on the relative weight of each by-product.
• We do not include timber products in our deforestation exposure assessment. That is because webelieve we would have to make so many assumptions that the usefulness of the results would
be substantially reduced. For example, we were not able to retrieve data on the share of timber
products from plantations vs. natural forests in production/consumption disclosure, nor data on
the share of recycled products vs certified products. In general, key challenges linked to timber
relates predominantly to forest degradation rather than deforestation44.

43 We assume a weight of 16% for leather and 5% for fat, calculated based on FAOStat anda literature review.
44 Hannah Ritchie and Max Roser, 2021. Deforestation and forest loss.

S U STA I N A B L E B Y N AT U R E S E Q U E L :E X P LO R I N G T H E R O OT S O F O U R E X P O S U R E TO D E F O R E STAT I O N-34-APPENDIX IIInterpreting deforestation results
Several challenges arise when looking for, using and interpreting deforestation and conversion ofnatural ecosystems coefficients at FERC level.
We wish to align as closely as possible to the deforestation definition of the Accountability Framework
initiative45 but we are limited by the definitions and assumptions embedded within the deforestation
coefficients we used from our literature review.

WHAT DEFINITION OF DEFORESTATION AND CONVERSION OF NATURAL ECOSYSTEMS IS
USED?
The definition and methods to measure deforestation and land use change varies across the different
studies and datasets. According to Dr Pendrill, “There is no single way to distinguish between forests
and non-forests, nor between deforestation and forest degradation, so different studies and monitoring
systems rely on different definitions.” Trase coefficients, used for the most impactful FERCs andgeographies, cover the primary loss of native vegetation, regardless of vegetation type (i.e., itencompasses forest, savannahs and grasslands), but Dr Pendrill uses only forest loss. Plantations
are counted within the scope.
Both datasets look at ‘recent’ deforestation, i.e., land that was deforested 15 to 5 years ago,
depending on the FERC (5 years for soy and cattle products; 10 years for palm oil and 15 years forcocoa products in Trase; 5 years for all FERCs in Dr Pendrill’s work).

HOW IS DEFORESTATION AT COUNTRY-LEVEL ATTRIBUTED TO AGRICULTURE AND FERCS?
WHAT ARE THE KEY ASSUMPTIONS?
The attribution of deforestation and conversion of natural ecosystems to agriculture is fraught withdifficulties.
The first challenge is the attribution of deforestation to the different drivers and co-drivers, such asurbanization in agricultural deforestation frontiers. Both Trase and Dr Pendrill attribute deforestation
to the primary driver, in that case agriculture.
The second challenge is the attribution of the share of agriculture-driven deforestation that does
not result in agriculture production, because of land speculation for example. In Trase, deforestationthat does not lead to agricultural production is not attributed to specific FERCs, and therefore notcaptured in the coefficients. In Dr Pendrill’s work, it is.

45 The Accountability Framework initiative (AFi) is a collective effort of diverse organisations dedicated to protecting forests, natural ecosystems, and human rights by making ethical production and trade the new normal. BNP Paribas is a member of thePrivate Sector Advisory Group that provides inputs to AFi.

S U STA I N A B L E B Y N AT U R E S E Q U E L :E X P LO R I N G T H E R O OT S O F O U R E X P O S U R E TO D E F O R E STAT I O N-35-

The third challenge is the allocation to deforestation to the succession of FERCs produced on the same
piece of deforested land years after the deforestation event. One single FERC is hardly responsible for
deforestation in most cases. For example, soy expansion usually follows on cattle expansion in SouthAmerica46. Both Trase and Dr Pendrill allocate the deforestation to the FERC produced following
the deforestation event but use different allocation procedures47. To harmonize both datasets,
we annualize the results – meaning that the deforestation in year T is spread evenly to the FERC
produced thereafter, over 5 to 15 years, depending on the FERC.
The last challenge is allocating indirect deforestation, when a FERC is produced on land which is notdeforested but its land occupation led to the deforestation in another location, for the productionof another FERC. In Trase, this is not taken into account. Dr Pendrill takes this into account andallocates it to the former – however, in the final estimate, it is not possible to disentangle whether
crop expansion directly led to deforestation or whether it happened on other land uses, leading
indirectly to deforestation.

46 Song, XP., Hansen, M.C., Potapov, P. et al, 2021. Massive soybean expansion in South America since 2000 and implications forconservation.
47 In Trase, the deforestation event is fully allocated to all subsequent production (after a lag period to account for land clearance
and agricultural establishment) over 5 to 10 years (unamortized results). In Dr Pendrill, the deforestation event is spreadequally to all subsequent production (after a lag period to account for land clearance and agricultural establishment) over 5
years (amortized results).

S U STA I N A B L E B Y N AT U R E S E Q U E L :E X P LO R I N G T H E R O OT S O F O U R E X P O S U R E TO D E F O R E STAT I O N-36-APPENDIX III

FERCs coverage in the selected datasets, and the EU Regulation (alphabetical order)
FERCS

CDP

TRASE

FOREST 500

FOREST IQ

WITHIN EU
REGULATION SCOPE

Beef and derived
products

Yes, including
leatherYes, excluding
leatherYes, including
leatherYes, including
leatherYes, including
leather

ChickenNo

Soy exposure inchicken feed

No

No

No

Cocoa andderived products

Yes

Yes

No

No

Yes

Coffee andderived products

Yes

Yes

No

No

Yes

Corn

No

Yes

No

No

No

Cotton

No

Yes

No

No

No

Palm oil andderived products

Yes

Yes

Yes

Yes

Yes

Pork

No

Soy exposure inpork feed

No

No

No

Rubber

Yes

No

No

Yes

Yes

Soy

Yes

Yes

Yes

Yes

Yes

Sugarcane

No

Yes

No

No

No

Timber andderived products

Yes

Wood pulp only

Yes

Yes

Yes

S U STA I N A B L E B Y N AT U R E S E Q U E L :E X P LO R I N G T H E R O OT S O F O U R E X P O S U R E TO D E F O R E STAT I O N-37-APPENDIX IV

Percentage of AUM covered at each step of our proprietary methodology
to quantify the extent to which our corporate holdings drive potential deforestationand conversion of natural ecosystems

Total AUM
~ 500 bn€

Corporate AUM 1

6331 companies representing 171 bn€

Corporate AUM in 4 highest
impact GICS sector

1553 companies representing 24% of Corporate
AUM

AUM in companies that are
known to produce/source atleast one FERC (step 1)

273 companies representing 37% ofcorporate AUM in the 4 relevant GICS sectors

AUM in companies for whichquantitative data is available on
at least one FERC (step 2)

152 companies representing 29% of corporate
AUM in the 4 relevant GICS sectors

AUM in companies
for which exposure
to deforestation
could be estimated(step 3&4)

98 companies representing
26% of corporate AUM in the
4 relevant GICS sectors

1
Please note this scope does not include
residual exposures in some funds delegatedby BNPP AM or managed by BNPP AM affiliate
entities.

S U STA I N A B L E B Y N AT U R E S E Q U E L :E X P LO R I N G T H E R O OT S O F O U R E X P O S U R E TO D E F O R E STAT I O N-38-APPENDIX V

Availability of full, useable, quantitative consumption and/or production data

% of corporate AUM, found to be exposed
to FERC in any of the four datasets,
disclosing production or consumption data

100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%

Palm oil
Full perimeter

Soy

Cattle products Rubber

Partial perimeterNo data

Cocoa

CoffeeS U STA I N A B L E B Y N AT U R E S E Q U E L :E X P LO R I N G T H E R O OT S O F O U R E X P O S U R E TO D E F O R E STAT I O N-39-APPENDIX VI

Description of Trase and Dr Pendrill’s methodologies to derive FERC
and country-specific deforestation coefficient
TRASE

DR PENDRILLMETHODOLOGY

Brief description

Trase’s FERC deforestation indicator Dr Pendrill uses geospatial analysis
captures how much of a defined area from GFC to determine the extent of(obtained via satellite imagery) used deforestation at country-level. It thento produce a particular FERC overlap allocates deforestation to specificwith areas that have been recently
land use drivers (such as pasture anddeforested. The parameter used tocrop expansion), and at FERC level bydecide which years of deforestation
using a statistical land balance
are included in the analysis is termed model based on FAOStat data, also
the ‘allocation period.’ This accounts taking into account an allocation
for the period of time over which
period (See Trase short description).
deforestation is likely to have beencaused by the target FERC.

Definition of deforestation

Trase defines deforestation as theprimary loss of native vegetation,
regardless of vegetation type (i.e., itencompasses forest, savannahs andgrasslands).

Deforestation data source

Geospatial analysis (multiple & local Geospatial analysis (GFC remotesources depending on FERC/location) sensing)

Attribution of deforestation
to agriculture

This step is not necessary as Trase
approach is fully geospatial.

Statistical model using FAOStat
attributes forest loss to expanding
cropland, pasture or plantations
based

FERC specific attribution

Spatial analysis (overlay)

Expanding crop land is further
attributed to specific FERCs based ona statistical model using FAO Stat.

Commo/country48

Brazil: Soy, beef, chicken, pork
Argentina: Soy
Ivory Coast: Cocoa
Indonesia: Palm oil, wood pulp
Paraguay: Beef, soy
Subnational-level data on: Brazil
beef; Argentina soy; Ivory Coast
Cocoa, Paraguay beef and Indonesia
palm oil.

All in FAOStat

Granularity of deforestation
exposure coefficients

Municipality; subnational;
biome; country

CountryLatest year available

2017/2020 depending
on FERC/country

2018

Tree cover loss (includes short term
disturbances)

COVERAGE

48 Pork and chicken is based on soy consumption

S U STA I N A B L E B Y N AT U R E S E Q U E L :E X P LO R I N G T H E R O OT S O F O U R E X P O S U R E TO D E F O R E STAT I O N-40-APPENDIX VII

Details of disclosed FERCs consumption and production quantities
and geographical split (disclosed or estimated)
Quantity (tonnes) ofcompanies in relevant sectors
in our corporate AUM% of quantity with geographic disclosure vs% of quantity that was allocated to a specific country based on
FAO Stat (cf. methodology in Appendix I)% of production quantity…

Production% of consumption quantity…

ConsumptionWithcountry-level
disclosure

Wherecountry-level
exposure wasestimatedWithcountry-level
disclosure

Wherecountry-level
exposure wasestimated

BrazilCattleproducts-

565 407

0%

0%

23%

77%

Colombia

Cattleproducts-

36 708

0%

0%

11%

89%

Paraguay

Cattleproducts-

24 721

0%

0%

9%

91%

Other
countries

Cattleproducts-

4 999 734

NR

NR

NR

NR

BrazilCocoa-

159 465

0%

0%

98%

2%

Colombia

Cocoa

-

653

0%

0%

0%

100%

Ivory Coast

Cocoa

-

940 352

0%

0%

98%

2%

Peru

Cocoa

-

1 636

0%

0%

0%

100%

Other
countries

Cocoa

-

752 119

BrazilCoffee-327 139

0%

0%

96%

4%

Colombia

Coffee-81 405

0%

0%

96%

4%

Peru

Coffee-11 393

0%

0%

88%

12%

Other
countries

Coffee-744 958

BrazilPalm oil-48 316

0%

0%

38%

62%

Colombia

Palm oil-284 684

0%

0%

72%

28%

Indonesia

Palm oil3 175 277

10 414 159

100%

0%

78%

22%

Malaysia

Palm oil

2 576 063

4 842 987

100%

0%

80%

20%

Other
countries

Palm oil

7 423 073

1 908 310

BrazilSoy-

5 935 366

0%

0%

91%

9%

Argentina

Soy-

1 185 668

0%

0%

82%

18%

BoliviaSoy-

12 719

0%

0%

2%

98%

ParaguaySoy-

548 710

0%

0%

91%

9%

Other
countries

Soy-

16 094 126

BrazilTimberproducts

22 711 941

27 216 259

100%

0%

99%

1%

Argentina

Timberproducts

565 195

95 597

100%

0%

78%

22%

Colombia

Timberproducts

378 197586 619

100%

0%

98%

2%

Indonesia

Timberproducts

535 672

1 195 671

99%

1%

87%

13%

Other
countries

Timberproducts

60 221 560

154 459 792

Ivory Coast

Rubber2

64 822

0%

100%

1%

99%

Indonesia

Rubber8

360 942

0%

100%

42%

58%

Other
countries

Rubber28

917 585

S U STA I N A B L E B Y N AT U R E S E Q U E L :E X P LO R I N G T H E R O OT S O F O U R E X P O S U R E TO D E F O R E STAT I O N-41-

APPENDIX VIII

Criteria used to decide whether a corporate commitment or traceability-system is "strong"
TYPE & COVERAGE OF COMMITMENTTRACEABILITY

Forest 500

Zero gross conversion/deforestation Have a commitment to develop andcommitment - company-wide
implement supply chain traceability
systems, company-wide, within thenext two years or already achieved

CDP

No conversion of natural
ecosystems; zero grossdeforestation/ no deforestation company-wide

Have a commitment to develop andimplement supply chain traceability
systems, company-wide, within thenext two years or already achieved

Forest IQ (incl. SPOTT)No deforestation (zero-gross deforestation OR conversion) or noconversion (zero gross conversion)- company-wide

NAApril 2024 - Design: Creative Services BNPP AM - P2311014

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