Forecasting the path towards
a Net Positive Impact on
biodiversity for Rio Tinto QMM

H. J. Temple, S. Anstee, J. Ekstrom, J. D. Pilgrim,
J. Rabenantoandro, J-B. Ramanamanjato,
F. Randriatafika and M. Vincelette.

IUCN and Rio Tinto Technical Series No.2

Forecasting the path
towards a Net Positive
Impact on biodiversity
for Rio Tinto QMM

H. J. Temple, S. Anstee, J. Ekstrom, J. D. Pilgrim, J. Rabenantoandro,
J-B. Ramanamanjato, F. Randriatafika and M. Vincelette
IUCN and Rio Tinto Technical Series No.2

The designation of geographical entities in this book, and the presentation of thematerial, do not imply the expression of any opinion whatsoever on the part of
IUCN or Rio Tinto concerning the legal status of any country, territory, or area,
or of its authorities, or concerning the delimitation of its frontiers or boundaries.

ISBN: 978-2-8317-1441-7
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This publication captures the experience of an innovative and scientifically robust
attempt to assess, forecast, and subsequently account for procedures put inplace by Rio Tinto to mitigate and remediate the input of their operations at the
QMM site.
As the scientific basis and operational procedures to attain a net positive impact
are still in the process of being established, this report is intended to be strictly
technical in nature. It does not represent endorsement of a particular approachor standard towards attaining “net positive impact”.
IUCN does not take responsibility for the operational delivery of the outcomesanticipated in the forecast.
Published by: IUCN, Gland, Switzerland and Rio Tinto, London, UK
Copyright: © 2012 International Union for Conservation of Nature andNatural Resources
Reproduction of this publication for educational or other non-commercial
purposes is authorized without prior written permission from the copyrightholder provided the source is fully acknowledged.
Reproduction of this publication for resale or other commercial purposes is
prohibited without prior written permission of the copyright holder.
Citation: Temple, H.J., Anstee, S., Ekstrom, J., Pilgrim, J.D., Rabenantoandro, J.,
Ramanamanjato, J.‑B., Randriatafika, F. & Vincelette, M. (2012). Forecasting thepath towards a Net Positive Impact on biodiversity for Rio Tinto QMM. Gland,
Switzerland: IUCN. x + 78pp.

Contents
Foreword
Acknowledgements
Executive summary
1
2

3

Introduction
Background15

2.1 National and regional context 5

		

2.1.1 Madagascar

5		

2.1.2 Fort Dauphin region5

2.2 Physical environment

6

2.3 Biological environment 6

		

2.3.1 Habitats6		

2.3.2 Species

8

2.4 Rio Tinto QMM project

10

2.5 The Biodiversity Committee

10

2.6 Rio Tinto’s NPI commitment

10

2.7 The mitigation hierarchy

12

Methods

15

3.1 Identify and prioritize biodiversity features for inclusion in		 NPI accounting15

3.2 Decide which metrics to use16

3.3 Select counterfactual scenario(s) against which to		 measure losses and gains

17

3.4 Quantify habitat losses for the periods 2004–2015
			and 2004–2065

20

3.4.1 Assessing forest condition

21

3.5 Quantify habitat gains for the periods 2004–2015
			and 2004–2065

22		

3.5.1 Restoration

22		

3.5.2 Quality gains in the Avoidance Zones

25

		

3.5.3 Averted deforestation gains25		

3.5.4 Credit claims

27

3.6 Calculating species losses and gains for the periods
		 2004–2015 and 2004–2065

27

4

Results29

4.1 Is Rio Tinto QMM on track to achieve a Net Positive
		 Impact on biodiversity for the period 2004–2065?   

29		

4.1.1 Summary29		

4.1.2 Impacts on habitats—Quality Hectares

30		

4.1.3 Impacts on species—Units of Global Distribution

35

4.2 Is Rio Tinto QMM on track to achieve a Net Positive
		 Impact on biodiversity for the period 2004–2015?

40		

4.2.1 Impacts on habitats—Quality Hectares40		

4.2.2 Impacts on species—Units of Global Distribution40

		4.3 Is Rio Tinto QMM on track to achieve a Net Positive
		 Impact on biodiversity throughout the lifecycle of the mine?
5

6

Conclusions and next steps

43

5.1 Summary

43

5.2 Achieving NPI—what does it mean for Rio Tinto QMM?

44

5.3 Rio Tinto QMM’s biodiversity offsets

45

5.4 Monitoring forest loss

47

5.5 The broader context—drivers of biodiversity loss in		 southeastern Madagascar

49

5.6 NPI analysis updates and adaptive management49

Lessons learned and directions for future research

50

6.1 Potential impacts of climate change

50

6.2 Defining a standard set of species included in NPI accounting

50

6.2.1 Undescribed species

7

41

51

6.3 Counterfactual scenarios, baselines, and calculating
		 biodiversity gains from averted loss

51

6.4 Calculating Units of Global Distribution—methods for		 measuring species distribution area

51

Bibliography

53

Appendix 1

61

Appendix 2

62

Appendix 3

64

Appendix 4

66

Appendix 572

List of tables
1

Predicted net impact of Rio Tinto QMM 2004–2065

30

2

Losses and gains in QH predicted for 2004–2065

32

3

Animal species with a net negative impact at 2065

37

4

Like-for-not-like gains in site-endemic plant species

38

5

Like-for-not-like gains in site-endemic, Endangered andCritically Endangered animal species

39

List of figures
1

Map of Rio Tinto QMM project area

3

2

The mitigation hierarchy

13

3

Predicted changes in littoral forest cover

18

4

The three counterfactual scenarios considered

19

5

Littoral forest extent and condition at Rio Tinto QMM in 2005

24

6

Losses and gains of Quality Hectares of forest 2004–2065

33

7

NPI forecast

34

8

Cumulative gains in littoral forest over time42

9

Current biodiversity offset sites

48

Foreword
This publication aims to provide the data, theory, and predictions for the potential
long-term outcome of a biodiversity conservation programme at a mining site.
Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto
QMM is a joint initiative between IUCN and Rio Tinto, a global mining Group.
Rio Tinto and IUCN signed a three year collaborative agreement in 2010, with theoverall objective to build a business focused collaboration that enables Rio Tinto
to improve its conservation outcomes, strengthen IUCN and Rio Tinto capacities
for market-based approaches to conservation, and contribute to industry-wide
improvements in the mining and associated sectors. By working together, bothorganizations aim to better understand each other’s issues and priorities, draw
on each other’s experience and expertise, and develop programmes and actions
that provide on-the-ground conservation value and contribute to improved
performance – for IUCN, Rio Tinto, and the mining sector more broadly.
This report contributes to the ongoing discussion around applying a mitigation
hierarchy to managing biodiversity risks and challenges and discussion aroundbiodiversity offsets and biodiversity metrics. IUCN and Rio Tinto believe an
important input to the discussion is rigorous on-the-ground testing of theories
and methodologies, which is robustly and transparently documented.
IUCN is the world’s oldest and largest global environmental organisation, withmore than 1200 government and NGO members and almost 11 000 volunteer
experts in some 160 countries. IUCN’s work is supported by more than 1000
staff in 45 offices and hundreds of partners in public, NGO and private sectors
around the world. IUCN works on biodiversity, climate change, energy, human
livelihoods and greening the world economy by supporting scientific research,
managing field projects all over the world, and bringing governments, NGOs,
the UN and companies together to develop policy, laws and best practice.
Rio Tinto is a leading global mining group, involved in every stage of the mining
business. Its interests are diverse both in geography and product and it works
in some of the world’s most difficult terrains and climates. Most of Rio Tinto’s
assets are in Australia and North America, but it also operates in Europe, SouthAmerica, Asia and Africa. Businesses include open pit and underground mines,
mills, refineries and smelters as well as a number of research and service facilities.
Rio Tinto comprises five principal product groups - Aluminium, Copper, Diamonds& Minerals, Energy, and Iron Ore – plus two support groups: Technology &Innovation, and Exploration.
Clare Verberne, Dennis Hosack, and Stuart Anstee

Acknowledgements
This report has been written by The Biodiversity Consultancy Ltd., Cambridge,
UK, with contributions from the QMM Biodiversity Team and Rio Tinto HSE.
The first draft of this report was prepared by Helen Temple (The Biodiversity
Consultancy), with input from the Rio Tinto QMM biodiversity team (Manon
Vincelette, Johny Rabenantoandro, Faly Randriatafika, Jean-Baptiste
Ramanamanjato, Dominique Andriambahiny) and Jonathan Ekstrom (The
Biodiversity Consultancy) gathered in workshops held in Fort Dauphin, Madagascar
in January and February 2010. At this stage, the document was intended as a
discussion paper to inform debate with the Rio Tinto QMM Biodiversity Committee
regarding what ‘Net Positive Impact’ meant in practice for Rio Tinto QMM. The
methodology and draft text was reviewed by the Rio Tinto QMM Biodiversity
Committee at a workshop held on 3-6 May 2010 in Fort Dauphin (a full day
was dedicated to this task). The following committee members were present
and contributed to the discussion: Porter P. Lowry (Missouri Botanical Gardens);
Jörg Ganzhorn (Hamburg University); Alison Jolly (Sussex University); Rob Brett(Fauna and Flora International); Paul Smith (Royal Botanic Gardens, Kew); andLisa Gaylord (Wildlife Conservation Society). A number of significant changes
and improvements were made to the methodology and draft report based on
the Committee’s requirements. The document was then internally reviewed by
Rio Tinto Health, Safety, Environment and Communities (Stuart Anstee), Rio
Tinto QMM (Manon Vincelette, Johny Rabenantoandro) and The Biodiversity
Consultancy (John Pilgrim, Jonathan Ekstrom). At this stage it was decided thatthe document would be of value to a number of external audiences and should
be formally published. Consequently a further round of review and improvement
was initiated in December 2010, involving the Rio Tinto QMM Biodiversity
Committee and a number of additional experts. These experts were selected by
IUCN rather than Rio Tinto QMM, and were: Thomas Brooks (NatureServe), Sue
Mainka (IUCN), Dennis Hosack (IUCN), Monica Barcellos-Harris (UNEP-WCMC),
Leon Bennun (BirdLife International), Conrad Savy (Conservation International)
and James Watson (Wildlife Conservation Society). In addition, the document
was reviewed at the first meeting of the IUCN-Rio Tinto Working Group on NPI
Verification, held on 17-18 March 2011 in London, attended by Stuart Anstee(Rio Tinto), Rachel Asante-Owusu (IUCN), Dennis Hosack (IUCN), Sally Madden(Rio Tinto), Thomas Brooks (NatureServe), Manon Vincelette (Rio Tinto), Conrad
Savy (Conservation International), Simon Wake (Rio Tinto), Monica Harris (UNEPWCMC), James Watson (Wildlife Conservation Society) and Rainer Schneeweiss(Rio Tinto). Finally, the document was also graciously reviewed by Richard Jenkins(IUCN) and Paul Racey (University of Exeter).
The authors should like to thank all of them for their contributions to this report.

	Executive summary
The Rio Tinto ilmenite
mine in southeastern
Madagascar, run by
QIT Madagascar
Minerals, has beenchosen as a pilot site to
test the tools designed
to achieve andquantify a NPI on
biodiversity.

Rio Tinto is committed to achieving a Net Positive Impact (NPI) on biodiversity,
a strategy launched at the 2004 IUCN World Conservation Congress. The Rio
Tinto ilmenite mine in southeastern Madagascar, run by QIT Madagascar Minerals(Rio Tinto QMM), has been chosen as a pilot site to test the tools designed toachieve and quantify NPI on biodiversity. The most important direct negative
biodiversity impact resulting from the Rio Tinto QMM operation is the loss oflittoral forest habitat at the Mandena, Petriky and Sainte Luce (hereafter Ste
Luce) mining sites. Approximately 1,665 ha (3.5% of Madagascar’s remaining
47,900 ha of littoral forest) are expected to be lost over the next 40 years as aresult of mining and associated activities. Rio Tinto QMM operates a dredge minerather than a conventional open cast mine so habitat loss will be incremental
over decades as the mine moves slowly through the landscape; the total direct
footprint is anticipated to be c.8,000 ha over the mine’s lifetime; however themine itself occupies c.50 ha at any one time (covering c.100 ha per year: Rio Tinto
QMM, 2001). Rio Tinto QMM began its mining activities in 2009. Littoral forest
has been identified as a national conservation priority (Ganzhorn et al., 2001)
owing to its limited extent and its high concentrations of nationally and locallyendemic plant species (Du Puy and Moat, 1998; Dumetz, 1999), diverse tree flora(Dumetz, 1999), and high diversity of fauna (Ganzhorn, 1998; Ramanamanjato
et al., 2002; Watson et al., 2005). Littoral forests on the mining concession
harbour many restricted-range species and species classified as Threatened on
the IUCN Red List, including 42 plants and at least 14 invertebrate species thatare found nowhere else in the world.
In the present analysis, biodiversity losses and gains were measured and forecast
for the period 2004–2065 (i.e. from the date of the NPI commitment to theanticipated date of mine closure), in order to determine whether the current andproposed mitigation activities of Rio Tinto QMM are sufficient to achieve NPI
by closure. NPI was defined (in consultation with Rio Tinto QMM’s Biodiversity
Committee) as Net Positive Impact on littoral forest (measured in Quality Hectares,
QH) and Net Positive Impact on High Priority species (measured in Units of
Global Distribution, UD).
Four main types of conservation actions are being implemented by Rio Tinto
QMM to mitigate project impacts on key habitats and species. These are:
• Avoidance—at Mandena, Petriky and Ste Luce. Avoidance Zones (AZ) havebeen established. They represent a cost to Rio Tinto QMM of c.8% of
foregone ilmenite, as well as the management cost of maintaining theseareas, and protect 27% of the best quality remaining forest cover on thedeposit. Collectively, these cover an area of 624 ha.

• Minimization—reduction of the likelihood or magnitude of biodiversity
impacts from mining activities that cannot be avoided. At Rio Tinto QMM
this includes a diverse range of activities such as minimizing disturbanceand roadkill from mining-related traffic by educating drivers and enforcing
strict speed limits.
• Rehabilitation and restoration—re-establishment of littoral forest on areasthat have been completely cleared, by replacing topsoil (stored during themining process) and planting with appropriate native species propagatedin Rio Tinto QMM’s nursery. There are plans for the restoration of c.225
ha at each of the three sites (Mandena, Petriky and Ste Luce), amounting
to c.675 ha in total. Restoration zones will be located adjacent to the
Avoidance Zones, to provide a buffer, improve connectivity and facilitate
natural regeneration and re-colonization.
• Biodiversity offsets—Rio Tinto QMM is investing in biodiversity offsets
at several forest sites in the region, with the aim of reducing the highbackground rate of deforestation. These offset sites cover c.6,000 haof forest.
In addition, Rio Tinto QMM is carrying out a number of additional conservation
actions (e.g. environmental education, capacity-building, livelihoods alternatives,etc.) with the aim of making a positive contribution to sustainable developmentin the region and reducing human pressure on biodiversity.
Net impact on littoral forest is forecast to be +350 QH in 2065,1 representing an
increase in forest extent and quality of 13% in comparison to 2004 (measured in
QH). Net impact on littoral forest is forecast to be +48 QH in 2015, representing
an increase of 2% in comparison to 2004 levels. Net impact on the forest asa whole (including the humid forests of the Bemangidy 2 offset) is forecast to
be +1,251 QH.
Loss of littoral forest caused by direct impacts of mining is predicted to be -428
QH. Total littoral forest gain is predicted to be +778 QH. Consequently the ratioof gain to loss is approximately 2:1. Considering all forest types, loss remains
constant at -428 QH; gain in all forest types (including Bemangidy humid forest)
is +1,679 QH. In this case the ratio of gain to loss is approximately 4:1.
Of the 90 High Priority terrestrial species (54 plants, 26 invertebrates, 10vertebrates) individually, 83 (92%) are forecast to show a Net Positive Impact
at 2065. For 59 of these, area-based calculations predict that NPI will be reached;
for a further 24 plant species, area-based calculations predict a moderate
negative impact (-1.3% to -17.9%) requiring Rio Tinto QMM to reach NPI by
2065 through enrichment of the avoidance and restoration zones (e.g. returning
species from their current depleted levels towards estimated natural densities in
Based on a background deforestation rate of the Madagascar national average for c.1990 to c.
2000 of 0.9% per year.

1

Bemangidy is part of the Tsitongambarika forest – it lies within the area of the forest that issometimes called ‘TGK III’.

2

optimal conditions3). Seven animal species show residual negative impacts—fourvertebrates (including the Critically Endangered gecko Phelsuma antanosy) show
residual negative impacts of up to 5.1%, and three invertebrates show residual
negative impacts of up to 17.9%. It is not known whether enrichment would
be feasible or desirable for these species,4 research is underway to investigate
options.
Only 32 of the 90 High Priority species are likely to be at NPI by 2015, and somespecies show losses of up to 39% of their global distribution at this point (twomillipedes and one plant, all endemic to Mandena, show population reductionsof this magnitude). This is because there will already have been major impacts
by this date (particularly at Mandena), but rehabilitation/restoration zones will
not as yet have reached sufficient maturity to generate gains that can counttowards NPI.
Importantly, this analysis is primarily a forecast based on the best available data.
Accounting of biodiversity losses and gains will be required periodically, using
the same principles and methods, and incorporating better information as it
becomes available.
Overall, this analysis shows that Rio Tinto QMM could be on track to achieve a Net
Positive Impact on biodiversity by the date of closure of the mine, provided that:
1. The assumptions upon which the analysis is based (inter alia backgrounddeforestation rate, levels of habitat degradation, rate at which habitat
quality can be restored) are either accurate or precautionary.
2. The conservation measures detailed here are successfully implemented.
3. Further research is conducted into conservation options for the four
vertebrate and three invertebrate species predicted to have a net negative
impact in 2065, and the best of these options is implemented as a highpriority.
4. Sustained investment in conservation action is assured.
5. Rigorous monitoring and independent verification are implemented toensure that real biodiversity gains are achieved.

At present, littoral forest at Mandena, Petriky and Ste Luce is somewhat degraded as a result ofvarious human activities (not only mining) —consequently, for some species (e.g. plant species
highly sensitive to disturbance or degradation) it is desirable to ultimately aim to restore them togreater densities than are currently observed.

3

Note that Phelsuma antanosy is found at Ambatotsirongorongo, which has been protected
through a joint QMM-Wildlife Conservation Society initiative. The ‘gains’ from this site are notincluded in the summary figures presented here.

4Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM1 Introduction

Rio Tinto is committed
to achieving NPI on
biodiversity at sites
where it operates, astrategy launched atthe 2004 IUCN World
Conservation Congressand reinforced at the2008 Congress.

Rio Tinto is committed to achieving a Net Positive Impact (NPI) on biodiversity atsites where it operates, a strategy launched at the 2004 IUCN World Conservation
Congress and reinforced at the 2008 Congress (Rio Tinto, 2008a). The Rio
Tinto ilmenite mine in the Fort Dauphin region of southeastern Madagascar
run by QIT Madagascar Minerals (Rio Tinto QMM) has been chosen as one of
Rio Tinto’s pilot sites to test the tools designed to achieve and quantify NPI on
biodiversity. It consists of three sites to be mined sequentially (Mandena, Ste
Luce and Petriky), a new deepwater port, and ancillary infrastructures such as
roads, quarry, housing and industrial areas (Figure 1). Mining at the first ofthese three sites, Mandena, began in 2009. Rio Tinto QMM has made a formal
commitment in its Biodiversity Action Plan to achieve NPI on biodiversity.
The most important direct negative biodiversity impact resulting from Rio Tinto
QMM’s activities is the loss of littoral forest habitat at Mandena, Petriky and Ste
Luce. Littoral forest is a rare and threatened habitat within Madagascar—c.90%of this habitat type has already been lost as a result of human activities (Consiglio
et al., 2006). Approximately 1,665 ha (3.5% of Madagascar’s remaining 47,900
ha of littoral forest) is expected to be lost to dredging, which entails not only
clearance of vegetation but also removal of soil and its constituent seed bank.
Littoral forests on the mining concession harbour many restricted-range species
and species classified as Threatened by the IUCN Red List, including 42 plants
and at least 14 invertebrate species that are found nowhere else in the world.
The project will have substantial residual impacts on a number of these species.
Four main types of conservation actions are being used by Rio Tinto QMM tomitigate project impacts on key habitats and species. These are:
• Avoidance Zones (AZ)—at Mandena, Petriky and Ste Luce, AvoidanceZones have been established on the ilmenite deposits to protect thoseblocks of littoral forest that are in the best condition. These AZ have been
officially incorporated into Madagascar’s national Protected Areas network.
They represent a cost to Rio Tinto QMM of c.8% of foregone ilmenite andprotect 27% of forest cover on the deposit. Collectively, they cover a total
area of 624 ha.
• Minimization—reduction of the likelihood or magnitude of biodiversity
impacts from mining activities that cannot be avoided. At Rio Tinto QMM
this includes a diverse range of activities such as minimizing disturbanceand roadkill from mining-related traffic through road-safety awarenesscampaigns and by enforcing strict speed limits.

1

2

Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM• Rehabilitation and restoration—attempts to re-create littoral forest
on areas that have been completely cleared, by replacing topsoil (stored
during the mining process) and planting with appropriate native species
propagated in Rio Tinto QMM’s nursery. Rehabilitation/restoration zones
will be located adjacent to the AZ to provide a buffer, improve connectivity
and facilitate natural regeneration and re-colonization.
• Biodiversity offsets—Rio Tinto QMM is investing in biodiversity offsets
at several forest sites in the region, with the aim of reducing the highbackground rate of deforestation. These offset sites cover c.6,000 haof forest.
Rio Tinto QMM is
implementing a
number of additional
conservation actions
intended to make apositive contribution tobiodiversity conservationand sustainable
development in
the region.

In addition, Rio Tinto QMM is implementing a number of additional conservation
actions (environmental education, capacity-building, livelihoods alternatives,etc.) intended to make a positive contribution to biodiversity conservation andsustainable development in the region. These actions will be essential to reduce
human pressure on remaining forest and to allow restoration, biodiversity offsets
and avoidance to deliver conservation gains.
This report quantifies the current and projected direct impacts on key habitats
and species caused by mining and associated activities, and the potential
conservation gains that may be achieved through habitat restoration and averted
deforestation at Avoidance and Offset Zones. It is intended to shed light on thefollowing questions:
1. Is Rio Tinto QMM on track to achieve a Net Positive Impact on biodiversity
for the period 2004-2065?
2. Is Rio Tinto QMM on track to achieve a Net Positive Impact on biodiversity
by 2015?
The 2004 to 2065 time frame has been chosen as it corresponds to the period
starting from the launch of the biodiversity NPI policy in 2004 to the current
projected date of mine closure and relinquishment of the tenement in 2065.
The 2015 date represents an interim milestone that has been set as part of Rio
Tinto’s performance target-setting process.
It should be noted that the complexity associated with setting and monitoring
biodiversity metrics means that value judgements are often required in the initialestablishment of relevant targets for achieving NPI. In the case of the Rio Tinto
QMM project the validity of these value judgements was tested by an external
committee of biodiversity and conservation specialists.5 Quantitative analyses
such as those presented here can provide useful background information and
A Biodiversity Advisory Committee was formed in 2001 to review the Rio Tinto QMM biodiversity
strategy and conservation measures on the ground. It consists of biodiversity experts withextensive experience and global renown for their research in Madagascar. This committee currently
comprises: Dr. Porter P. Lowry (Missouri Botanical Gardens); Prof. Joerg Ganzhorn, (Hamburg
University); Prof. Alison Jolly (Sussex University); Dr. Rob Brett (Fauna & Flora International); Dr.
Paul Smith (Royal Botanic Gardens, Kew); and Lisa Gaylord (Wildlife Conservation Society).

5Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMMinsights, but they should not replace consultation with appropriate biodiversity
stakeholders and experts.
Finally, it should be noted that this report focuses on technical biodiversity issues
because its remit is to answer specific technical questions. It only very briefly
touches on local communities and broader sustainable development issues. Thisshould not be taken as implying that “biodiversity issues are more important
than social issues for Rio Tinto QMM”, rather it reflects the specific aims of thereport. It is essential that mining and implementation of mitigation and offset
measures are done in a way that takes into account the needs and rights oflocal communities and does not leave them worse off than before. Faced with
development of a mine and development of biodiversity offsets, there is a realrisk that local communities may face a ‘double whammy’ of negative impacts
from both initiatives (e.g. if a community is dependent upon forest resources,
and its access to forest is reduced through mining-caused deforestation andthe implementation of a ‘fortress-style’ protected area)(BBOP, 2009). Rio Tinto
QMM’s expressed aim is to implement mitigation and offsets in a way that
benefits both biodiversity and local communities (Rio Tinto QMM, 2010).

3

4Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM

Figure 1. Map of Rio Tinto QMM project area, showing the three deposits(Mandena, Petriky, Ste Luce) and remaining littoral forest cover on
the deposits in 1998.

Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM2

Background
This section provides an overview of the environmental context for Rio Tinto
QMM’s operation in the Fort Dauphin region of southeastern Madagascar. It
also summarises Rio Tinto’s Net Positive Impact commitment and outlines the
mitigation hierarchy, a conceptual tool used by Rio Tinto and others to think about
impacts and mitigation measures. A large number of technical reports, scientificpapers, a Social and Environmental Impact Assessment6 (Rio Tinto QMM, 2001),
a Biodiversity Action Plan (Rio Tinto QMM, 2010) and a 400-page monograph(Ganzhorn et al., 2007. Biodiversity, ecology and conservation of littoral ecosystems
in southeastern Madagascar) have been compiled by Rio Tinto QMM and themany scientists who have worked at the mine site and its environs. This section
does not replicate this detailed information but rather gives a concise summaryand directs the reader to sources where more detailed information can be found.

2.1 National and regional context
2.1.1 Madagascar
Madagascar is a global
biodiversity hotspot
with a rich and uniquebiodiversity that is
subject to high levelsof threat. It is home to
12–14,000 vascularplant species, 90%of which are endemic
and found only
at a few sites.

Madagascar is the fourth largest island in the world, covering 587,000 km2, about
the size of Texas or France. The country is a global biodiversity hotspot with arich and unique biodiversity that is subject to high levels of threat (Mittermeier
et al., 2004). Madagascar is home to 12–14,000 vascular plant species, 90%of which are endemic and found only at a few sites (Mittermeier et al., 2004).
The island has 340 native species of reptile, including more than half the world’s
chameleon species (Raxworthy, 2003). There is almost 100% endemism among
Madagascar’s 222 amphibian species. The country is characterized by high rates
of poverty, large rural populations, subsistence agriculture, and low levels of
industry (Vincelette et al., 2007a). It ranks amongst the poorest of the world’s
countries with per capita GDP estimated at US$221 in 2003 (Vincelette et al.,2007a) and US$392 in 2010 (IMF, 2011).

2.1.2 Fort Dauphin region
The mine is situated near the town of Fort Dauphin in the Anosy region ofsoutheastern Madagascar. This is one of the most ecologically diverse regionsof Madagascar (Goodman and Ramanamanjato, 2007), but also one of thepoorest and most isolated. Eighty-two per cent of Anosy inhabitants live below
the poverty line (US1$/day) and the regional population is expected to double by2020 (Vincelette et al., 2007a). The low-level commercial economy is supported
by just three main products—rice, sisal and lobster—and there is growing pressure
on the environment from unsustainable subsistence use of natural resources(Vincelette et al., 2007b)7.
This SEIA covers the Mandena site. SEIAs for the other sites (Petriky and Ste Luce) will be carriedout in the future (and in advance of any mining activity at those sites).

6

Further information on the national and regional context can be found in the Social andEnvironmental Impact Assessment (SEIA) (Rio Tinto QMM, 2001) and in Vincelette et al. (2007a).

7

5

6

Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM

2.2 Physical environment
The Fort Dauphin region is dominated by the Vohimena Mountains and a rolling
coastal plain that extends down to the Indian Ocean. This plain is composed
mainly of littoral sands (often mineralized) that form a series of low dunes
terminating at the shoreline in a series of coastal lagoons. The regional climate
is warm and humid, with occasional cyclones. Average monthly temperatures
range from 26.9°C in January to 20.3°C in July. January is typically the wettest
month and September the driest. Annual precipitation shows a steep gradientfrom Petriky in the south (the driest of the three sites) to Ste Luce in the north.
Mandena, located between Petriky and Ste Luce, has a mean annual rainfallof about 1,600 mm.8

2.3 Biological environment
2.3.1 Habitats

Southeastern
Madagascar contains asignificant diversity ofnatural forest habitats
within a complex
topographic relief,
with few parallels inany other regionof the island.

Southeastern Madagascar contains a significant diversity of natural forest habitats
within a complex topographic relief, with few parallels in any other region of theisland. Forest types include coastal littoral forests on sandy substrates, humid
forest habitats ranging from lowland to montane formations, dry forest andspiny bush. A diverse biota is associated with these habitats, many species andsub-species of which are locally endemic (Rio Tinto QMM, 2001; Goodman and
Ramanamanjato, 2007). The north-south aligned Anosyenne Mountains act asa major barrier for weather systems reaching the island from the east. There
are very abrupt ecotones9 on the western flank of this chain on account of thisrain shadow effect, including one of the most extreme known in the world on
the western flank of the Anosyenne Mountain chain between parcels I and II
of Andohahela National Park (Nussbaum et al., 1999). Here, evergreen humid
forest characteristic of the east coast mountain ranges merges into the spiny
sub-desert scrub characteristic of southwestern Madagascar over a remarkably
short distance of about 5 km. For those unfamiliar with Madagascan vegetation
types, this is equivalent to a change from ‘rainforest’ to ‘scrub or maquis-type’
habitat, a change of structural and compositional magnitude with few parallels
globally (Goodman and Ramanamanjato, 2007).

2.3.1.1 Littoral forest
A particularly important terrestrial habitat type found in the mining zone islittoral forest. Madagascan littoral forests are a sub-type of humid and subhumid evergreen forest occurring on sandy substrates (Rabevohitra et al., 1998;de Gouvenain and Silander, 2000). Littoral forest is notable for its high floristic
diversity—although it originally occupied less than 1% of Madagascar’s land
surface, 13% of the island’s total native flora has been recorded from this habitat
type (Consiglio et al., 2006). Littoral forest is thought once to have formed a
For further information on geology, hydrology and climate in the Fort Dauphin region, see
Vincelette et al. (2007c).

8

An ecotone is a transitional area between two distinct habitats, where the ranges of theorganisms in each bordering habitat overlap.

9Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMMcontinuous 1,600 km strip along most of Madagascar’s eastern seaboard, however
only c.10% of this remains in the form of small fragments, with only 1.5%
included within the existing Protected Areas network (Consiglio et al., 2006).
Between 1950 and2005 forest cover in
the Fort Dauphin
region further declinedby over 50%.

Prior to human disturbance, the coastal region including the mining zone
is believed to have been covered in coastal littoral forest (Lowry and FaberLangendoen, 1991; Consiglio et al., 2006; but see Virah-Sawmy, 2009). By 1950,
when the first known aerial images of the area were taken, forest cover was
already fragmented and patchy;10 between 1950 and 2005 forest cover in theFort Dauphin region further declined by over 50% (Vincelette et al., 2007b).11
At the present time, the mining zone is made up of littoral forest fragmentsof varying size and quality, interspersed with highly degraded vegetation, baresand, agricultural and inhabited land, and stands of exotics (e.g. Eucalyptus sp.)and alien invasive tree species (e.g. Melaleuca quinquenervia) (Rio Tinto QMM,
2001; Vincelette et al., 2007a; Rabenantoandro et al., 2007).
In 2005, 3,128 ha of coastal littoral forest remained in the mining zone (Mandena,
Petriky, and Ste Luce; Vincelette et al., 2007b). Since only 47,900 ha of thishabitat remain in the whole of Madagascar (Consiglio et al., 2006), the miningzone’s forests represent 6.5% of the residual area of this distinctive and highly
floristically diverse habitat type.

2.3.1.2 Comparison of the three sites—Mandena, Petriky and Ste Luce
Dumetz (1999) classified the three southeastern forests (Mandena, Petriky and
Ste Luce) as a unique sub-type of littoral forest on sand. Each of these threesites has distinct social, physical and ecological characteristics despite their close
geographic proximity to one another (Ingram and Dawson, 2006).
One of the distinctive features of Ste Luce, by comparison with the two othersites, is that it contains relatively large tracts of littoral forest that remain in fairly
good condition. For example, parcel S912 shows all the characteristics of nearly
intact low elevation dense humid forest, with about 60% cover among treesthat are 12 m or more in height, and a clearly stratified structure (Lowry andFaber-Langendoen, 1991; Rabenantoandro, 2001; Rabenantoandro et al., 2007).
The extent to which this is due to natural factors versus anthropogenic factors is debated in theliterature (see e.g. Virah-Sawmy, 2009). The landscape in the Fort Dauphin region may well benaturally a mosaic habitat (Virah-Sawmy, 2009), but there is also evidence of anthropogenic loss
and degradation dating from before the arrival of QMM (Vincelette et al., 2007b; Virah-Sawmy,2009), although this was potentially mainly caused by immigrants from other parts of Madagascar
rather than by local people and may have been exacerbated by QMM’s exploration-related
activities since the 1990s (Ingram and Dawson, 2006; Virah-Sawmy, 2009).

10

It is possible that, in more recent years, (e.g. 1990s and 2000s) the rate of loss has been
exacerbated by the presence of the mining project. However, comparison of imagery fromc.1950, 1972 and 1989 indicates that there was considerable loss of forest cover over this earlier
time period (Figures 2 & 4 in Vincelette et al., 2007; e.g. from c.7,000 ha in 1950 to c.4,500 ha
in 1989).

11

12
All parcels of littoral forest at Mandena, Petriky and Ste Luce have been mapped and given
individual numbers.

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Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM

At Mandena, the bioclimatic factors are nearly identical to those at Ste Luce,although precipitation is slightly less. However, remnant parcels of forest aresmaller and in poorer condition, with lower canopy height, smaller trunk
diameters and less stratification. The observed differences in structure foundat Mandena indicate that the forest present there today is a degraded form ofa vegetation type that is shared with Ste Luce. Located just 9 km north of thetown of Fort Dauphin, Mandena has clearly been heavily impacted by humans.
By comparison with Ste Luce, Mandena shows a striking lack of individual trees
belonging to families that are widely used for their wood, such as Ebenaceae,
Sapotaceae and Lauraceae. This is likely a reflection of the previous exploitationof economically valuable species (Rabenantoandro et al., 2007).
Floristically and faunistically, Petriky can be interpreted as a transition between
dry forest and humid littoral forest (Rabenantoandro et al., 2007). Locatedat the extreme southern end of Madagascar’s east coast, Petriky has species
characteristic of humid formations, such as Intsia bijuga (Fabaceae), Homalium
axillare (Flacourtiaceae), Asteropeia multiflora (Asteropeiaceae), and Beilschmiedia
madagascariensis (Lauraceae) but differs from the other two sites through thepresence of taxa typical of dry areas, including Oplonia vincoides (Acanthaceae),
Folotsia madagascariense (Asclepiadaceae), Deinbolia boinesis (Sapindaceae) andCordia caffra (Boraginaceae). Similarly, the fauna of Petriky shows clear affinities
with those of dry forest areas in southwestern Madagascar (Ramanamanjato etal., 2002). One other notable characteristic of the Petriky forest is the lack ofmembers of the Arecaceae and Pandanaceae families, which are prominent in
the Mandena and Ste Luce forests (Rabenantoandro et al., 2007).

2.3.2 Species
2.3.2.1 Terrestrial species—vascular plants
Of the 614 vascular plant species and varieties recorded from remnant littoral forest
in the mining zone, 83% are endemic to Madagascar, of which 54% are sharedwith low- and mid-elevation humid forests, 7% are restricted to southeastern
Madagascar littoral forests,13 6% are restricted to scattered small remnants ofregional littoral forests in the zone between Petriky and Manantenina, and 7%
are found only in the mining zone (Rabenantoandro et al., 2007).14 The numberof plant species strictly endemic to the mining zone currently stands at 42.15

2.3.2.2 Terrestrial species—vertebrates
About 168 species of reptiles and amphibians are found in the Anosy region,
representing around a third of the total herpetofauna of Madagascar (Goodman
and Ramanamanjato, 2007). Ninety-six of these are found in the mining zone.

13

E.g. forests between Mananjary and Fort Dauphin.

14

See Rabenantoandro et al. (2007) for further details and a complete vascular plant species list.

15

The exact number changes over time as a result of research and taxonomic revisions.

Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMMSpecies richness is highest at Ste Luce (69 species), followed by Mandena (63)and Petriky (45) (Ramanamanjato, 2007).
The Fort Dauphin
region exhibits aparticularly highbird species richness,reflecting theexceptional habitat
diversity in the
Anosy region.

The Fort Dauphin region exhibits a particularly high bird species richness,reflecting the exceptional habitat diversity in the Anosy region. Goodman etal. (1997) listed 189 species occurring in the area south of Manantenina andeast of the Mandrare River, representing 68% of the island’s known avifauna atthat time. Within the mining zone, Watson (2007) recorded 77 bird species inlittoral forest fragments, and Watson et al. (2005) describe these fragments asholding a unique assemblage of avian species, including both humid and spiny
forest-dependent species, a combination found nowhere else on the island.
However, endemism16 in the region is low—there is only one regional endemic,
Bluntschli’s Vanga Hypositta perdita, which has not been recorded in the miningzone (Goodman and Ramanamanjato, 2007; Watson, 2007).
The southeastern portion of the island has a rich small mammal fauna, owing
to the varied habitats in the region and the high mountains of the Anosyenne
and Vohimena Mountains. No endemic species of extant small mammal are
known from the Anosy region. As with other groups of organisms, there are two
principal gradients that show high levels of species turnover within this region: an
east-west gradient from humid forests to dry forests and an elevational gradient,particularly in parcel I of the Parc National d’Andohahela, from lowland habitats
to sclerophyllous forest in the higher areas. However, compared with other
Malagasy forest types, the littoral forests are depauperate in large mammals.
The Malagasy Ring-tailed Mongoose Galidia elegans and Malagasy Civet Fossa
fossana, familiar inhabitants of many Madagascar ecosystems, are present. In
addition, the Fossa Cryptoprocta ferox, the island’s top predator, was recorded
in Mandena for the first time in 2004. Both micro- and mega-chiropterans havebeen recorded in the project area. Several of the mega-chiropteran species roostat locations near the mining zone, and are believed to be important dispersers
of seeds of the littoral forest. Additionally, the zone has an interesting collectionof primate species. There is at least one restricted-range form of lemur, Eulemur(fulvus) collaris present in southeast Madagascar and within the mining zone.17

2.3.2.3 Terrestrial species—invertebrates
Invertebrate groups surveyed at the Rio Tinto QMM site to date include
dragonflies (Odonata: Schütte and Razafindraibe, 2007), mantids (Mantodea:
Schütte, 2007), stick insects (Phasmatodea: Schütte, 2007), giant pill-millipedes(Sphaerotheriida: Wesener and Wägele, 2007; Wesener, 2009), and spirobolid
millipedes (Spirobolida: Wesener et al., 2009).

16‘Endemism’ here refers to Anosy regional endemics; see Goodman and Ramanamanjato (2007)
for further details.
17
For more details on the vertebrate species found at QMM’s sites, see Ganzhorn (2007) andreferences therein.

910Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM

Based on these surveys, the littoral forests within the mining zone at Mandena,
Petriky and Ste Luce hold a diverse array of invertebrate species, including a
number of species that are endemic or near-endemic to the mining zone.18 The
surveys resulted in the discovery and description of a number of new species,
including the genus Riotintobolus.

2.4 Rio Tinto QMM project
The Rio Tinto QMM project will mine ilmenite ore as a mineral sand, to provide
titanium dioxide to the world market. Titanium is a major ingredient in steels
and other alloys; titanium dioxide is the white pigment found in most paints
The Rio Tinto QMM and plastics. The Rio Tinto QMM project consists of three sites to be minedproject will mine sequentially (Mandena, Ste Luce and Petriky) over a period of c.40–50 years. A
ilmenite ore as a new deepwater port has been constructed at Fort Dauphin. Ancillary infrastructuremineral sand, to includes a dedicated port industrial zone, road networks, housing areas and aprovide titanium stone quarry. Ilmenite is mined using a dredge situated on artificial ponds that
dioxide to the world moves across the ore body as mining progresses; the mining process entails themarket. Titanium is a removal of all vegetation cover along with the soil. Approximately 100 ha of the
major ingredient in deposit will be mined each year; the mine itself occupies about 50 ha of land
steels and other as it progresses slowly through the deposit area. Rehabilitation of the minedalloys; titanium area will be carried out once the dredge has moved on to the next part of thedioxide is the white deposit. The total mine footprint at all three sites collectively is about 8,000 ha.
pigment found in most Ore processing is minimal and takes place on site through physical separation.
paints and plastics. Processed ore is transported by truck to the port for export.19

2.5 The Biodiversity Committee
A Biodiversity Advisory Committee was formed in 2001 to review the biodiversity
strategy and conservation measures on the ground. It consists of biodiversity
experts with extensive experience and global renown for their research in
Madagascar. This committee currently comprises: Dr. Porter P. Lowry (Missouri
Botanical Gardens); Prof. Jörg Ganzhorn, (Hamburg University); Prof. Alison Jolly(Sussex University); Dr. Rob Brett (Fauna & Flora International); Dr. Paul Smith(Royal Botanic Gardens, Kew); and Lisa Gaylord (Wildlife Conservation Society).
Further details are given in Appendix 1.

2.6 Rio Tinto’s NPI commitment
The goal of Rio Tinto’s biodiversity strategy is a ‘Net Positive Impact’ (NPI) on
biodiversity (Rio Tinto, 2004, 2008a). This means “minimising [sic.] the impactsof our business and contributing to biodiversity conservation to ensure a region
ultimately benefits as a result of our presence” (Rio Tinto, 2008a). Rio Tinto’s
position on biodiversity is embedded in the company’s land use stewardshipstandard (Rio Tinto, 2008b). The company’s environmental approach is describedin the policy document The Way We Work (Rio Tinto, 2009). The biodiversity
18
For some of these species, there has been insufficient study conducted outside the mining zone todetermine conclusively whether they are strictly endemic to the mining zone or more widespread.

More information on the project can be found in the Social and Environmental Impact
Assessment (Rio Tinto QMM, 2001) and at www.riotintomadagascar.com.

19Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMMstrategy was launched in 2004 at the IUCN World Conservation Congress in
Bangkok. Since then, Rio Tinto’s Chief Executive Officer, Tom Albanese, hasreaffirmed the NPI policy in a number of subsequent forums including the 2008
IUCN World Conservation Congress in Barcelona. Rio Tinto’s position statement
and guiding principles on biodiversity are presented in Boxes 2 and 3.
The NPI goal means
ensuring that Rio
Tinto’s actions havepositive effects on
biodiversity that not
only balance but arebroadly accepted tooutweigh theinevitable negative
effects of the physicaldisturbances andimpacts associatedwith mining andmineral processing.

In simple terms, the NPI goal means ensuring that Rio Tinto’s actions have positiveeffects on biodiversity that not only balance but are broadly accepted to outweighthe inevitable negative effects of the physical disturbances and impacts associatedwith mining and mineral processing. The company proposes to achieve this by:• Avoiding unacceptable impacts on ecosystems.
• Reducing the impacts that may occur.
• Restoring impacted ecosystems.
• Compensating for residual impacts with offsets.
• Seeking additional opportunities to contribute to local conservation.
A key facilitator of the commitment to NPI is the development of comprehensive,
simple, scientifically sound metrics to quantify losses and gains. The lack of such
metrics has been a major reason for the lack of investment and enthusiasm bydevelopers (public and private alike) to attempt measurement and full mitigationof biodiversity impacts (ten Kate et al., 2004).

Box 1: Rio Tinto’s position statement on biodiversity (from Rio Tinto, 2008a)
Rio Tinto recognizes that conservation and responsible management of biodiversity
are important business and societal issues. Our goal is to have a net positive
impact on biodiversity.
We are committed to the integration of biodiversity conservation considerations
into environmental and social decision making in the search for sustainable
development outcomes. We recognize that this might mean that we do notproceed in some cases.
We want to be biodiversity leaders within the mining industry, for the competitive
advantage and reputational benefit this provides. Our performance on biodiversity
conservation and management issues will create benefits for our business.
We are committed to:• The identification of biodiversity values impacted by our activities.
• The prevention, minimization, and mitigation of biodiversity risks
throughout the business cycle.
• Responsible stewardship of the land we manage.
• The identification and pursuit of biodiversity conservation opportunities.
• The involvement of communities and other constituencies in ourmanagement of biodiversity issues.

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Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM

Box 2: Rio Tinto’s guiding principles on biodiversity (from Rio Tinto, 2008a)• Our goal is to have a net positive impact on biodiversity by minimizing thenegative impacts of our activities and by making appropriate contributions
to conservation in the regions in which we operate.
• We are committed to the conservation of threatened and endemic species
and high priority conservation areas, and support local, national and global
conservation initiatives.
• We will seek equity and the reconciliation of differing perspectives andideals in biodiversity decisions and actions.
• We will enhance biodiversity outcomes through consultation, constructive
relationships, and partnerships with key stakeholders.
• We will integrate the identification, evaluation, and management of
biodiversity issues into the planning, decision making, and reporting
processes throughout the business cycle.
• We will apply appropriate expertise and resources to biodiversity issues,building internal and external capacity where necessary.
• Subject to appropriate consent, we promote the collection, analysis, anddissemination of biodiversity information and knowledge.

2.7 The mitigation hierarchy (avoidance,
minimization, restoration and rehabilitation,and biodiversity offsets)
The mitigation
hierarchy is aconceptual framework
for thinking aboutbiodiversity risks andopportunities anddeveloping
appropriate responses.

The mitigation hierarchy (Figure 2) is a conceptual framework for thinking
about biodiversity risks and opportunities and developing appropriate responses.
Variations on the mitigation hierarchy were first developed around 2004 by Rio
Tinto and others. It is now a well established model for private sector biodiversity
management and conservation and has been adopted by a number of government
initiatives and private sector organizations (McKenney and Kiesecker, 2010;
TEEB, 2010). Proper use of the mitigation hierarchy means one must first seek
to avoid impacts, then minimize, then restore, and finally only use offsets as
an option to compensate for the residual impacts after all other options havebeen exercised (ten Kate et al., 2004; Rio Tinto, 2008a). The meaning, scope
and use of stages in the mitigation hierarchy are summarized in this section.

Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM- Biodiversity values +Net positive impact
Additional
conservation
actions
OffsetOffsetRehabilitation

Rehabilitation

Rehabilitation

Minimization

Minimization

Minimization

Minimization

Avoidance

Avoidance

Avoidance

Avoidance

Residual impact
Biodiversity
impactBiodiversity
impactAvoidance

Biodiversity
impactBiodiversity
impactFigure 2. The mitigation hierarchy. From Rio Tinto and Biodiversity: achieving
results on the ground (Rio Tinto, 2008a).

The biggest opportunity
for avoidance is during
project development—it
is often possible toimplement relatively
cheap avoidance
measures thatsignificantly reduce
impacts on biodiversity,
thereby reducing future
costs of restoration,offsets and closure.

Avoidance
Rio Tinto (2008a) defines ‘avoidance’ as activities that change the scope of
impacts (reducing them, moving them, or avoiding them completely). Avoidancechanges or stops actions before they take place, preventing their expected impacts
on biodiversity. It involves a decision to change the expected or normal courseof action. A real-world example can be found at Rio Tinto Simandou’s iron ore
project in southeastern Guinea where stockpiles and waste dumps have been
relocated to avoid impacts on tropical forest; they are instead mainly being locatedin areas of relatively degraded savannah (a common habitat type in the region).
The biggest opportunity for avoidance is during project development—it is often
possible to implement relatively cheap avoidance measures that significantly
reduce impacts on biodiversity, thereby reducing future costs of restoration,offsets and closure.
Minimization‘Minimization’ reduces the severity of impacts on biodiversity that result frommining and associated activities20 already underway. These actions reduce thelikelihood or magnitude of biodiversity impacts, but cannot completely prevent
them. It can sometimes be difficult to distinguish between avoidance andminimization because some actions have aspects of both. Improvements tothe water quality treatment of outflows from mining areas, thereby reducing
impacts on aquatic systems is a good example of minimization, while routing
water outflows away from biodiversity-sensitive areas would qualify as avoidance.
20‘Mining and associated activities’ include all activities required to find, mine and processminerals, at any stage of the mine life cycle from exploration to closure.

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Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM

Rehabilitation and restoration‘Rehabilitation’ involves the preparation of safe and stable landforms on sitesthat have been disturbed by mining and associated activities, followed by revegetation with the aim of establishing a specific habitat type. Rehabilitation isimportant for improving basic ecosystem functions such as erosion control andwater quality regulation. ‘Restoration’ is a term generally used where the aim
is to recreate a habitat type similar to the original vegetation type, including
the targeting of some specific biodiversity features such as rare species.21 The
re-establishment of dune forest at Richard’s Bay Minerals on recreated sanddune systems (following ilmenite sand mining) is an example of attempted
restoration within Rio Tinto’s portfolio (van Aarde et al., 1996). For the purposesof NPI calculations, typically restoration can count towards achieving NPI22 but
rehabilitation cannot.

Offsets are not
employed in place ofappropriate on-site
avoidance andminimization
measures, but rather
seek exclusively toaddress the residualloss after mitigation.

Offsets
Rio Tinto is committed to achieving a Net Positive Impact on biodiversity. Even
with the best possible mitigation measures in place at business units, mining andassociated activities will result in some level of residual impacts on biodiversity.
Consequently biodiversity offsets are needed—conservation activities in thewider region that result in measurable biodiversity gains to compensate forthese residual losses, resulting in a Net Positive Impact at the regional level.
Offsets are not employed in place of appropriate on-site avoidance andminimization measures, but rather seek exclusively to address the residual loss
after mitigation. Offsets can achieve biodiversity ‘gains’ in two ways. They may
reduce existing pressures and therefore losses to biodiversity (e.g. reducing
background deforestation rates)—this is known as an ‘averted loss offset’.
Alternatively, they may directly enhance the state of biodiversity (such as throughspecies re-introductions or habitat restoration).
Additional conservation actions‘Additional conservation actions’ include a broad range of activities that are
intended to benefit biodiversity, but where effects or outcomes are difficult
to quantify in terms of biodiversity gains. Examples include scientific research,environmental education, and building capacity and expertise in conservation
organizations. Although the biodiversity outcomes of these actions are difficult
to measure, these kinds of intangible assets form an essential part of Rio Tinto’s
contribution to biodiversity conservation, often underpinning the success ofother mitigation actions, and are often some of the most highly valued byinterested stakeholders.
21

E.g. see Society for Ecological Restoration International Science & Policy Working Group (2004).

Partially successful restoration, or restoration that is in progress but has not yet reached its
end goal, will be accounted for pro rata based on the extent to which biodiversity value has
been restored. This can be taken into account using the Quality Hectares and Units of Global
Distribution metrics. Restoration is very seldom (or never) ‘100% successful’ in returning an area toa facsimile of its previous ‘natural’ state (or to the appropriate defined benchmark). Nevertheless,biodiversity gains from restoration attempts can be quantified.
22

Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM3

Methods
To obtain the information needed to determine if Rio Tinto QMM is on track toachieve NPI, the following steps were followed:
1. Identify and prioritize biodiversity features for inclusion in NPI accounting.
2. Decide which metrics to use.
3. Select the counterfactual scenario(s) against which to measure losses
and gains.
4. Quantify biodiversity losses likely to be caused by Rio Tinto QMM in the
periods 2004–2015 and 2004–2065.
5. Quantify biodiversity gains likely to be caused by Rio Tinto QMM in the
periods 2004–2015 and 2004–2065.
Each of these five steps is summarized below.

3.1 Identify and prioritize biodiversity features forinclusion in NPI accounting
Biodiversity is complex
and can be measured
at many levels, butlacks a single uniform
and globally fungible
metric (in contrast withcarbon, for example).

Biodiversity is complex and can be measured at many levels, but lacks a single
uniform and globally fungible metric (in contrast with carbon, for example).
In addressing this issue an attempt was made to identify metrics that wereboth practical to measure and reflective of the impacts associated with thedevelopment of the Rio Tinto QMM mining operation. This report therefore
only considers losses and gains in terrestrial systems and in intrinsic/existencevalues of biodiversity. For the purposes of this study, this effectively means
consideration of natural habitats and species.
Losses and gains in aquatic systems and in service values of biodiversity (biodiversitybased ecosystem services, livelihoods and cultural values) have been covered inprevious reports and discussion papers, including Rio Tinto (2008c) and Rio Tinto
QMM (2001, 2008); and several aquatic studies including Jacques Whitford Inc.
(2007). Aquatic systems and service values are not considered further in thequantitative analysis presented here. Mitigation measures for these biodiversity
features are detailed in the Biodiversity Action Plan (Rio Tinto QMM, 2010).
Potential losses and gains were measured for the following biodiversity features:• Habitats—all forest; littoral forest and its sub-types (including Fort
Dauphin-type littoral forest; losses and gains were measured individuallyfor Mandena, Petriky and Ste Luce).
• Species—all High Priority terrestrial species listed in the BAP (restrictedrange23 and/or highly threatened24 vertebrates, invertebrates and plants).
23‘Restricted-range’ here includes site endemics and near-endemics, and possible site endemics.

‘Highly Threatened’ here includes species assessed as Critically Endangered or Endangered on
the IUCN Red List.
24

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Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM

For further information on how biodiversity features were identified and prioritized,
refer to the QMM Biodiversity Action Plan (Rio Tinto QMM, 2010).

3.2 Decide which metrics to use

Quality Hectares are
Rio Tinto’s current
metric for tracking
progress towards the
NPI target at the
global and site levels.

Two metrics (or currencies) were used—Quality Hectares (QH) and Units of
Global Distribution (UD). Quality Hectares are Rio Tinto’s current metric for
tracking progress towards the NPI target at the global and site levels. A wide
range of biodiversity values, including threatened species, rare habitats or
non-timber forest products, may be expressed in terms of their quantity andquality. For example, 100 ha of forest in pristine condition would count as 100
Quality Hectares (100 ha × 100% quality = 100 QH), whereas 100 ha of fairly
degraded forest at 40% ‘optimum quality’ would be expressed as 40 Quality
Hectares (100 ha × 40% quality = 40 QH).
Units of Global Distribution are a novel metric, developed for this analysis, butconceptually related to Quality Hectares. A Unit of Global Distribution is equivalent
to 1% of a species’ global population25 (or 1% of its global distribution,26 in theevent that population data are unavailable).27 Units of Global Distribution arecalculated as follows: if a species has a global population of 1,000 individuals,
and 10 of those are killed, that would be a loss of 1% of the global population or
1 ‘Unit of Global Distribution’ (UD). Similarly, if a species has a global distributionof 100 ha, and 1 ha of its distribution is lost as a result of habitat loss causedby mining, that would be a loss of 1% of its global distribution or 1 ‘Unit of
Global Distribution’ (UD).
A detailed discussion of both metrics is provided in Appendix 2.
Losses and gains were measured in Quality Hectares for all habitats considered.
For species, losses and gains were measured in Units of Global Distribution. For avery small number of High Priority species it was not possible to measure losses
and gains in UD as global range and/or population size could not be quantified.
For these species, losses and gains were simply measured in hectares.
The UD metric provides additional information which is useful for making‘like-for-not-like’ biodiversity offset comparisons. Most frequently, biodiversity
offsetting involves ‘like-for-like’ or ‘like-for-better’ (also known as ‘trading up’)exchanges. For example, a like-for-like offset would occur when a loss of anarea of a particular habitat type is offset by proportionately equal or greater
gains in area in an essentially identical habitat type. A like-for-better offset might
25

Calculated in number of mature individuals.

26

Calculated in hectares.

It should be noted that assuming such a link between distribution and population size may beparticularly problematic for wide-ranging and nomadic species (it goes against ecological theory
on population and range size). However, no such species are included in the present analysis.
A precedent for making such a link is given in the Key Biodiversity Area guidelines (Langhammer
et al., 2007, p.65).

27

Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMMentail offsetting an area of low-value habitat (e.g. a very common habitat
type harbouring no threatened species) with a greater area of higher-value
habitat (e.g. a rare habitat type harbouring several threatened species). The
Rio Tinto QMM project is particularly complex because it potentially involves
like-for-not-like offsets, where the offset has different values to the area lost,
but it is not always objectively possible to claim that the values of the offset
site are greater.28
The relative values of different habitat types or biodiversity features (e.g.
what constitutes ‘trading up’) are fundamentally societal and thus require
subjective judgements and stakeholder consultation. In the case of Rio Tinto
QMM, guidance would be given by a range of stakeholders including (but not
restricted to) the Biodiversity Committee.29

3.3 Select counterfactual scenario(s) against which
to measure losses and gains
When measuring losses and gains, a key factor to consider is the counterfactual
scenario (or baseline) against which any loss or gain is measured. For Rio Tinto
QMM, this is particularly significant because the project is located in an area
which has experienced significant deforestation since at least the 1950s when
the first aerial photographs of the region were taken (Du Puy and Moat, 1998;
Vincelette et al., 2007b).
Three counterfactual scenarios were considered in the present analysis:• No mining and ‘no deforestation’.
• No mining and a ‘national average’ deforestation rate for all forest types
extrapolated from c.1990—c.2000 of 0.9% per year (Table 4 in Harper etal., 2007).30

28
For example, the Bemangidy offset is humid forest rather than littoral forest. QMM’s target is‘Net Positive Impact on littoral forest’, so in this specific case Bemangidy is a kind of ‘insurance
policy’ against incomplete mitigation/offset success elsewhere because it contains many of thesame species, but it is also a like-for-not-like offset.
29
Such guidance has not been needed at QMM to date, because the Biodiversity Committee set
a relatively strict ‘like-for-like’ target requiring that NPI is achieved for (i) littoral forest, and (ii)all priority species, individually. This target is described here as ‘relatively strict’ rather than ‘very
strict’ because it could be argued that, for example, because ‘Petriky-type littoral forest’ is distinct
from ‘Mandena-type littoral forest’ (Dumetz, 1999), NPI should be achieved at the level of these
forest sub-types rather than for littoral forest as a whole. However the recommendation of thecommittee at the end of the May 2010 meeting was to measure NPI at the level of littoral forest
sensu lato.
30
Note that there is much evidence to show that historic deforestation rates do not necessarilyreflect future deforestation rates. A number of REDD (Reducing Emissions from Deforestation
and Degradation—another methodology where background deforestation rate is very important)projects around the world are moving away from using past baselines to predict future rates,
to methods that that look at population density, roads, etc. to predict future deforestation. The
issue of calculating background deforestation rates is one that would merit further considerationin future, as discussed in the ‘Lessons learned’ section.

17

18

Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM• No mining and a calculated Fort Dauphin regional average deforestation
rate extrapolated from c.1995—c.2005 of 3.89% per year. Regional averagedeforestation rate was calculated for the period 1995–2005 based on
digitized aerial photographs using GIS31.
Figure 3 shows how forest cover would be predicted to change from 2004 to
2065 for Scenarios 1–3 in remaining forest at Mandena, Petriky and Ste Luce. In
2004, there were 2,289 ha of littoral forest on the mining leases (Mandena, Petriky
and Ste Luce), of which 1,665 ha fell under the mine path. Within the AvoidanceZones (AZs), 624 ha of littoral forest are protected.

Hectares of littoral forest in Fort Dauphin area

2500

2000

1500

1000
0%
0.90%
3.89%

500

2064

2061

2058

2055

2052

2049

2046

2043

2040

2037

2034

2031

2028

2025

2022

2019

2016

2013

2010

2007

2004

0

Year

Figure 3. Predicted changes in littoral forest cover on the Rio Tinto QMM mining
leases from 2004 to 2065, under three different annual deforestation
The counterfactual rate scenarios—0% (no deforestation from 2004 onwards), 0.9%
scenario is a critical (Madagascar national average) and 3.89% (Fort Dauphin regional average).
element of the NPI loss
and gain calculations The counterfactual scenario is a critical element of the NPI loss and gain calculations
as it determines the as it determines the magnitude of loss for which Rio Tinto QMM is consideredmagnitude of loss for to be responsible (Figure 4). Point ‘a’ in Figure 4 shows that if there had been
which Rio Tinto QMM no mine and if deforestation had continued at the Fort Dauphin regional rate ofis considered to be 3.89%, by c.2035 there would have been less forest remaining than the 624 ha
responsible. that are currently protected in the Avoidance Zones.
31
Note that although mining did not start until 2009, Rio Tinto QMM was active in the region during
this period and its activities (e.g. road construction) may have facilitated access and indirectly resulted
in elevated rates of forest loss.

Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMMHectares of littoral forest in Fort Dauphin area

2500

a

0%

2000

0.90%
3.89%
size of AZs

1500

x

1000

y

500
z

2064

2061

2058

2055

2052

2049

2046

2043

2040

2037

2034

2031

2028

2025

2022

2019

2016

2013

2010

2007

2004

0

Year

Figure 4. The three counterfactual scenarios considered. Distance x showsthat, assuming no mitigation beyond Avoidance Zones (AZs), basedon Scenario 1 (0% annual deforestation), Rio Tinto QMM would be
responsible for the loss of 1,665 ha of forest by 2065, i.e. the wholearea of forest on the ilmenite deposit (2,289 ha) minus the 624 haprotected within the AZs. Distance y shows that, based on Scenario
2 (0.9% annual deforestation: national average), Rio Tinto QMM
would be responsible for the loss of 695 ha by 2065. Distance z showsthat, based on Scenario 3 (3.89% annual deforestation: Fort Dauphin
regional average), Rio Tinto QMM would be responsible for a net gainof 421 ha of forest by 2065 simply by putting in place the AvoidanceZones: the AZs protect an area of 624 ha of forest, whereas only 203
ha would be left by 2065 if forest loss continued at a rate of 3.89%
per year. Point ‘a’ shows the point at which, under Scenario 3, net
impact becomes positive based on AZs alone.
We suggest that out of these three possible counterfactual scenarios, Scenario
2—the conservative national deforestation rate of 0.9%—is the most appropriate
baseline against which to measure NPI. To use a 0% deforestation rate baseline
would be highly unrealistic, given the very high rate of deforestation that has
occurred since 1950 and continues to occur in the local region. The 3.89%
regional deforestation rate was not selected, partly to be precautionary, andpartly because it is problematic to use a rate that may have been caused (atleast in part) by the mine. For example, it is possible that prospecting activities

19

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Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM

undertaken by Rio Tinto QMM since the 1990s, including road construction,
have indirectly facilitated the loss and degradation of the remaining forest(e.g. Ingram and Dawson, 2006; Virah-Sawmy and Ebeling, 2010). Based on
aerial photographs from 1950, 1974 and 1989 (before the arrival of Rio Tinto
QMM), the annual deforestation rate in the Fort Dauphin region was 1.1% peryear (Vincelette et al., 2007b). Thus, adopting the 1990–2000 national average(0.9%) as a baseline is conservative in comparison to this historical rate.
Furthermore, there is a view amongst some stakeholders that, given the occurrenceof many site endemic and Critically Endangered plants and animals, it is possiblethat the remaining forests would have been designated a Protected Area atsome point in the next decade or so.32 If a protected area covering the wholeof Mandena, Petriky and Ste Luce were to have been put in place in 2020 (andif that protected area was 100% successful in stopping forest loss), the forest
cover would have stabilized at 1,213 ha (Figure 4), assuming a background rateof 3.89% annual loss. By comparison with this alternative scenario, Rio Tinto
QMM would be considered responsible for the loss of 589 ha. Consequently
this scenario is somewhat less conservative than Scenario 2 (under which Rio
Tinto QMM is considered responsible for the loss of 695 ha). Following the same
logic but assuming a 0.9% rate of loss, Rio Tinto QMM would be considered
responsible for the loss of 1,356 ha. This is more conservative than Scenario 2,
although Rio Tinto QMM would still be predicted to achieve NPI on the littoral
forest under this counterfactual scenario.33

3.4 Quantify habitat losses for the periods
2004–2015 and 2004–2065
Losses caused by Rio
Tinto QMM’s mining
activities were
measured and predicted
for littoral forest
habitat, using the
Quality Hectares metric.

Losses caused by Rio Tinto QMM’s mining activities were measured (pastlosses) and predicted (future losses) for littoral forest habitat, using the Quality
Hectares metric. Only primary impacts of Rio Tinto QMM’s mining operations
were quantified (e.g. loss of habitat directly caused by mining and associatedactivities such as building roads and other infrastructure). Secondary impacts(e.g. potential negative impacts caused by invasive alien species brought into
the region by mine transport, increased human pressure on ecosystems caused
by prospective in-migration) are difficult to measure and no attempt has been
made to formally quantify them here. In Rio Tinto QMM’s particular case,because there is so little littoral forest left in the Fort Dauphin region, it is almost
all within Rio Tinto QMM’s direct influence (e.g. part of the Avoidance Zones,
the Ste Luce offset or the wider mining lease). Consequently Rio Tinto QMM
has more influence over what happens in the whole region’s littoral forest thanwould be typical of a mining operation in another area. Rio Tinto QMM has
This view was expressed verbally by Porter P. Lowry at the QMM Biodiversity Committee meetingin May 2010.

32

33
Under Scenario 2 (0.9% deforestation), net impact by 2065 is +350 QH of littoral forest. Underan alternative scenario of 0.9% deforestation per year to 2020, followed by Protected Area
designation for Mandena, Petriky and Ste Luce forests and no further forest loss, the project would
be projected to have a Net Positive Impact of c.+190 QH by 2065.

Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMMprogrammes to monitor and mitigate secondary impacts such as those describedabove; mitigation measures include those described elsewhere in this reportsuch as planting fast-growing tree plantations to meet community needs forwood and fuel and to relieve pressure on littoral forest. Indeed, the success of
Rio Tinto QMM’s Avoidance Zones and offsets rests on the ability of Rio Tinto
QMM (in partnership with local communities, government and other relevantorganizations) to address these secondary impacts; without doing so it would
be very difficult to slow or halt deforestation.
Losses were estimated by mapping forest extent and assessing forest conditionat all three mining leases, and overlaying these maps with the predicted dredge
path and any other mining infrastructure using GIS. Because no littoral forest
condition index existed in Madagascar, Rio Tinto QMM developed a fivecategory scale of forest condition, based on a range of habitat structure variables
that were measured in the field, particularly canopy cover (Vincelette et al.,2007b). The five categories range from ‘very good’ to ‘extreme deterioration’(Figure 5). The methodology for assessing forest condition is summarized in
the following section (a full description can be found in Vincelette et al., 2007b
and Rabenantoandro et al., 2007).
For Scenario 2 (no mining and national average deforestation rate of 0.9% peryear) and Scenario 3 (no mining and a Fort Dauphin average deforestation rateof 3.89% per year), losses were adjusted to take into account the amount offorest that would have been remaining by 2065 under these counterfactuals.
For Scenario 1 (0% annual deforestation), losses were not adjusted.

3.4.1 Assessing forest condition
The forest condition assessment method involves mapping all remaining littoral
forest blocks (based on the interpretation of the most recent aerial photographs
or satellite images) and establishing transects to cover each forest block witha 50 × 50 m grid. Sample points are established at the grid intersections. The
following data are obtained at each sampling position within the grid: generalcondition of the forest; signs of cutting (stumps); openings; agricultural areas;
fires; and observations of the vertical structure of the forest canopy level (upper,
intermediary, or lower). Finally, the field observer evaluates percentage canopy
cover at the sampling position.
There is a progressive decrease in canopy height and tree diameter at breast
height (dbh) from Ste Luce to Mandena to Petriky; this is a natural feature ofthese areas that relates to climatic differences (e.g. Petriky sees markedly lessrainfall than Ste Luce; Rabenantoandro, et al. 2007). For example, in the study
plots sampled by Rabenantoandro et al. (2007), canopy height decreased froma mean of 14.7 m in Ste Luce to 4.4 m in Petriky. Consequently it was necessary
to calibrate the method to reflect these intrinsic differences in stature, and so
the reference (‘100% optimal quality’) was different for each of the three sites.

21

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Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM

The forest conditionassessment was firstcarried out in 1998; themethod used in thisassessment wasverified by Missouri
Botanical Garden,
Royal Botanic Gardens,
Kew and FOFIFA.

The forest condition assessment was first carried out in 1998; the method used inthis assessment was verified by Missouri Botanical Garden (MBG), Royal Botanic
Gardens (RBG Kew), and FOFIFA34 (Lowry et al., 2001). The forest conditionassessment was updated and improved based on new field data and Quickbird
images obtained in 2005 and by adding information from other studies on
the level of deterioration of a given block, dendrometric criteria, and floristic
composition (Henderson, 1999; Ingram and Dawson, 2005, 2006; Ingram etal., 2005a, 2005b).
The analysis presented in the present report is based on the updated 2005
habitat condition assessment. Figure 5 shows the results of the 2005 forest
condition assessment.35

3.5 Quantify habitat gains for the periods
2004–2015 and 2004–2065
Measurable biodiversity gains can be generated either by increasing quality or
quantity (or both) of a given biodiversity value, for example a habitat type. The
key factor in each case is additionality—there must be a measurable increasein quality or quantity that can reasonably be attributed to actions taken by Rio
Tinto QMM.
Three types of biodiversity gains are considered in the present analysis—quality
gains and averted deforestation in the Avoidance Zones, restoration on
post-mining land, and averted deforestation at the biodiversity offset sites.   

3.5.1 Restoration
At Rio Tinto QMM, restoration entails the replacement of natural habitat
surrogates following the completion of the mining process. Strictly speaking,restoration on post-mining land does not represent a true gain in biodiversity
value, but instead reduces loss of biodiversity compared to a scenario where no
post-mining restoration was to take place, or a monoculture habitat was returned
post-mining. However for the sake of simplifying the loss-gain calculation wetreat post-mining restoration as a biodiversity gain.
Restoration gains were calculated in terms of Quality Hectares (area × quality),
assuming that by 2065 habitat will have been restored to 35% of optimal
quality at Mandena, 25% of optimal quality at Ste Luce and 20% of optimal

34

The National Centre for Applied Research into Rural Development, www.fofifa.mg.

Note that, in an earlier draft version of this analysis, a map showing forest cover and conditionin 1998 was erroneously included. However, the analyses presented in this report (and in previous
draft versions of the report) are based on forest condition assessment data from 2005.
35

Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM

quality at Petriky.36 This was estimated with reference to the littoral forest quality
measures developed by Vincelette et al. (2007b). Predictions of future forest
quality were made in consultation with botanical experts from RBG Kew andMissouri Botanical Garden, along with Rio Tinto QMM’s in-house botanists. The
predictions took into account experience from restoration field trials carried out
since 1999 (Vincelette et al., 2007d).
These quality estimates are conservative, taking into account some uncertainties
that exist around restoration of Madagascan littoral forest. They are based on
the assumption that restoration at Mandena will start in c.2020, at Petriky inc.2030 and Ste Luce in c.2035 (this is possible because Rio Tinto QMM is adredge mine; restoration can start on post-mining areas while mining is stillongoing elsewhere on the site). They are also based on the assumption that
restoration at Petriky will be more difficult and quality gains will accrue more
slowly (this is the advice of botanical experts; Petriky is significantly more arid
and trees establish with greater difficulty and grow more slowly).

These assumptions about forest quality in 2065 were based on discussion with M. Vincelette,
J. Rabenantoandro and F. Randriatafika (who have been running littoral forest restoration trials
for 10+ years), experience of success to date with the field trials, and consultation with botanicalexperts on the biodiversity committee (Porter P. Lowry and Paul Smith). The intention is to err on
the side of caution as littoral forest restoration has never been attempted before.

36

23

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Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM

Figure 5. Littoral forest extent and condition at Rio Tinto QMM in 2005.37

37
Note that, in an earlier draft version of this analysis, a map labelled as showing forest cover andcondition in 1998 was erroneously included. However, the analyses presented in this report (andin previous draft versions of the report) are based on the forest condition assessment data for
2005, which according to Vincelette et al. (2007) take into account the work of Henderson (1999),
Ingram and Dawson (2005, 2006), and Ingram et al. (2005a, 2005b).

Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM

3.5.2 Quality gains in the Avoidance Zones
The Avoidance Zones reduce the amount of habitat lost, by protecting areas offorest on top of the deposit that would otherwise have been cleared for mining.
However, if Rio Tinto QMM carries out conservation activities that improve thequality of the littoral forest in the AZs, it is valid to count this as a biodiversity gain.
The Avoidance Zones
reduce the amount of
habitat lost, byprotecting areas offorest on top of thedeposit that would
otherwise have beencleared for mining.

Although the Avoidance Zones were situated to protect the best-quality habitat
remaining at Mandena, Petriky and Ste Luce, the habitat quality at each AZ site
varies considerably and is often far from pristine. In 2004, average quality scores
were 0.57 for forest fragments in Mandena AZ, 0.39 for Petriky AZ and 0.80 for
Ste Luce AZ (Figure 5). Consequently there is significant scope for the quality to
be improved, generating gains in QH. This will be achieved through appropriate
habitat management and by relieving pressure from local human populations byinter alia providing plantations38 of fast-growing non-native39 trees outside the
Avoidance Zones for charcoal production and providing alternative livelihoods.
Quality scores were predicted to increase by 0.1 every 15 years in the Mandena
and Ste Luce AZs and by 0.05 every 15 years at Petriky.40, 41

3.5.3 Averted deforestation gains (long-term protectionof Avoidance Zones and biodiversity offsets)
Averted deforestation (also known as ‘averted loss’) generates biodiversity
gains both at Rio Tinto QMM’s biodiversity offset sites (Mahabo, Bemangidy,
Ste Luce Forests) and in the Avoidance Zones (Mandena, Ste Luce and Petriky
AZs). Mahabo, Ste Luce, Mandena and Petriky all contain littoral forest.
It is important that ‘averted deforestation’ is not confused with ‘avoidance’.
The Avoidance Zones (AZs) are, as their name implies, primarily an avoidance
measure—they represent a significant area of the deposit (c.8% of total ilmenite,
and 27% of remaining forest on the deposit) foregone in order to protect
habitat and in particular to save certain locally endemic species from extinction.
These plantations will principally be located in areas that have been cleared for mining, after
the dredge has passed (dredge mining moves steadily through the landscape, so such areas will
be available from an early stage in the project). We say ‘principally’ rather than ‘entirely’ becausesome plantation has been established already as there is a pressing need among local communities
for wood; these plantations were sited taking into account the conservation value of the existinglandscape as well as human needs. There has been and will be no additional clearance of littoral
forest to site these plantations.

38

Both native and non-native tree species (including littoral forest species, species from elsewhere
in Madagascar, and exotic species that were already found in the Fort Dauphin area) were included
in rehabilitation trials (Rarivoson and Mara, 2007; Vincelette et al., 2007), but ultimately thedecision was made to use non-natives.

39

40
The rates of improvement in quality score were estimated based on discussion with M.
Vincelette, J. Rabenantoandro and F. Randriatafika, and informed by progress with restoration
trials to date. Restoration trials started in earnest in 1999 (field observations and less formal
experiments related to littoral forest restoration had been ongoing since 1992), details can befound in Vincelette et al. (2007d). These estimates were discussed and agreed with the Biodiversity
Committee (in particular Paul Smith [RBG Kew] and Porter P. Lowry [MBG]) at a workshop in Fort
Dauphin, Madagascar, in May 2010.

In comments on an earlier draft of this analysis, Paul Smith (RBG Kew) noted that “This is quite
conservative. But better to err on the side of caution.”

41

25

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Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM

However, had Rio Tinto QMM not taken active steps to protect the AZs, theforest within them would have continued to decline at the same rapid rate as
before due to pressure from local human populations, particularly for charcoal
production. Consequently, over time, this averted deforestation is effectively an
additional measurable gain (in the two scenarios where a shifting baseline of
0.9% or 3.89% background annual deforestation rate is used; in the scenario
of 0% background deforestation on the mining leases there are no gains fromaverted loss in the AZs).
By implementing
active conservation
measures at offset sites
and providing
alternative livelihoods
to local communities,
this high rate of
deforestation canbe decreased.

The background rate of deforestation in the project area and surrounding region ishigh. By implementing active conservation measures at offset sites and providing
alternative livelihoods to local communities, this high rate of deforestation canbe decreased, and consequently the area of forest remaining after one year (or50 years) is greater than would have been the case if the offset sites had notbeen brought under conservation management.
Gains accruing through averted deforestation were estimated based on theassumption that the background deforestation rate will be reduced by 50%
through Rio Tinto QMM’s conservation activities in the period 2004–2065. For
example, in the case of a 1,000 ha forest that had been declining at a rate of
2% per year prior to 2004, one could assume an averted loss of 10 ha in thefirst year (1000 ha × (0.02/2)).
Gains were calculated in an analogous way to compound interest on a bankaccount, as follows.
Gains from averted loss were calculated as:
G = [x × (1-0.5y)z] - [x × (1-y)z]
Where G = gains; x = QH at a site; y = background deforestation rate andz = years of intervention.
For example, from 2004–2015 (11 years of intervention), gains would be:
G = [x × (1-0.5y)11] - [x × (1-y)11]
However, if at one site interventions were only started in 2011, then from2004–2015 there would be eight years of ‘business as usual’ and three yearsof conservation intervention, and so gains would be:
G = [x × (1-y)8 × (1-0.5y)3] - [x × (1-y)11]

Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMMFor the Avoidance Zones, which are under Rio Tinto QMM’s direct management
and subject to intensive management, it was estimated that the deforestation
rate would be reduced by 100%—i.e. no further area would be lost. For the Ste
Luce Forests offset, which is under Rio Tinto QMM’s direct influence (unlike theother offset sites), it was estimated that deforestation could be reduced by 75%.

3.5.4 Credit claims
A number of Rio Tinto QMM’s offset sites are co-funded by other organizations.
To ensure that credit is apportioned appropriately, the following rule was used inthese analyses when calculating biodiversity gains attributable to Rio Tinto QMM:
If Rio Tinto QMM leads on a particular project and starts it up and maintains
it, 100% of the resulting gains can be claimed. However, if Rio Tinto QMM
joins and co-funds a pre-existing project being led by another organization,
benefits are only attributed on a pro rata basis proportionate to investment.
This rule attributes gain in proportion to investment, whilst also providing an
incentive to make the first move. Following this rule Rio Tinto QMM is able toclaim 100% of gains at all offset sites except for Mahabo, where conservation
measures had been started with funding from Missouri Botanical Gardens
prior to the involvement of Rio Tinto QMM. In the case of Mahabo, annual
management costs are c.US$65,000, of which 63% is provided by Rio Tinto
QMM—consequently 63% of the annual biodiversity gains from the site canbe attributed to Rio Tinto QMM (assuming the same proportion of investment
continues in future).

3.6 Calculating species losses and gains for theperiods 2004–2015 and 2004–2065
For species includedin the analysis, losses
and gains were
calculated in Units of
Global Distribution.

For species included in the analysis (High Priority species as defined in the
Biodiversity Action Plan), losses and gains were calculated in Units of Global
Distribution (UD). For most species, losses and gains were initially calculated in
hectares. Each High Priority species was coded by occurrence at the following
sites: Mandena, Petriky, Ste Luce Deposit, Ste Luce Avoidance Zone, Ste Luce
Offsets (Ste Luce was sub-divided in this way because it is a larger site, and somespecies occur in e.g. the Ste Luce Offsets but not the other two sub-sites), Mahabo
and Bemangidy. Area of distribution on the mining leases, and concomitantlosses, were calculated assuming that a species was found throughout thewhole surface area of forest at any site at which it occurred. Custom estimatesof predicted loss, based on detailed field mapping and population estimates,
were made for four locally endemic plant species at Petriky that were known
to have particularly patchy or restricted distributions, such that this assumption

27

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Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM

would not be valid.42 Custom estimates of predicted loss were also made for
the Critically Endangered gecko Phelsuma antanosy.
To convert losses and gains in hectares to Units of Global Distribution, thetotal global Area of Occupancy (AOO) was estimated for all species. Different
methods were used to estimate global AOO depending on the taxonomic group
under consideration and the information available. For locally endemic plants,
global distribution area was calculated based on the total area of known sites
for most species43 and custom estimates for certain Petriky species. For mostbirds, mammals, and amphibians, Extent of Occurrence (EOO) was measured
based on the polygon area of GIS distribution maps from the IUCN Red List of
Threatened Species (IUCN, 2009), and AOO was inferred as 10% of EOO (this isa very rough approximation that will not hold in all cases; the 10% relationshipbetween AOO and EOO is implied by the thresholds set for Criterion B of the
IUCN Red List). For some birds, mammals and amphibians, a more detailed
estimate of AOO is given in the IUCN Red List (2009); this was used whereavailable. For reptiles, estimates were based on draft maps provided by R. Jenkins
and prepared for the January 2011 IUCN Global Reptile Assessment workshop
held in Madagascar. For a very small number of High Priority species, it was notpossible to measure losses and gains in UD as global range and/or population
size could not be quantified based on existing data. For these species, losses
and gains were simply measured in hectares.

Eligmocarpus cynometroides, Eulophia filifolia, Myrtus madagascariensis, and Peponium
poissonii. Note that E. filifolia may have recently been found at Mahabo (C. Birkinshaw pers.
comm. 2010), but is precautionarily retained as a local endemic in the present analysis.

42

This is arguably too generic a use of the term ‘area of occupancy’, which has a very specificdefinition in the IUCN Red List guidelines, and a different term might be more appropriate.
The intention here is to provide an approximation, albeit rough, of the size of the distribution
area where a species is actually found; it is well known that broad measures such as extent of
occurrence typically overestimate (sometimes vastly so) the area occupied by each species (Jetz,
Sekercioglu and Watson, 2008; Rodrigues, 2011).

43Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM4

Results

4.1 Is Rio Tinto QMM on track to achieve a Net
Positive Impact on biodiversity for the period
2004–2065?   

4.1.1 Summary
Biodiversity losses
and gains were
calculated in two
ways: using Quality
Hectares and Units of
Global Distribution.

Biodiversity losses and gains were calculated in two ways: using Quality Hectares
as a metric (for forest, littoral forest and littoral forest sub-types); and using
Units of Global Distribution as a metric (for High Priority species, i.e. Highly
Threatened and restricted-range species).
Three offset sites were included in the quantitative analysis—Ste Luce Forests,
Mahabo and Bemangidy. Two of these sites (Ste Luce Forests and Mahabo)
already have active conservation programmes, the third (Bemangidy) has a draft
management plan and is awaiting confirmation as an offset from Rio Tinto
QMM and the Biodiversity Committee.
Two further sites (Ambatotsirongorongo and TGK I Direct Payments Project) have had
active conservation projects, but are currently under review regarding whether theyshould be maintained as offset sites in the future. In the case of Ambatotsirongorongo,
work at the site will continue in future44, although this may be formally classed as anadditional conservation action rather than an offset within the Rio Tinto mitigation
hierarchy (in this case because of the high risk that even well-managed conservation
projects may not deliver measurable biodiversity gains because of the very greatpressure that the site is under – Ambatotsirongorongo is very small, fragmented,
and degraded as a result of pre-existing threats). Consequently, these two sites havenot been included as offset sites in the quantitative analysis presented here. Further
details on each of the offset sites are given in the discussion.
Losses and gains were therefore calculated based on the following assumptions:• Rio Tinto QMM will maintain three offset sites: Mahabo, Bemangidy and
Ste Luce Forests.
• 225 ha of restoration will be carried out at Mandena, Petriky and Ste Luce,
respectively (775 ha in total).
• Avoidance Zones at Mandena, Petriky and Ste Luce will be maintained andenhanced.45
Rio Tinto QMM is currently contributing to two projects at Ambatotsirongorongo: a natural
resources management project with UNDP and the local NGO FAFAFI; and a management planfor the Critically Endangered gecko Phelsuma antanosy with Fauna & Flora International and thenational NGO Voakajy.

44

45‘Enhanced’ means enhanced in quality rather than increased in area. This may involvee.g. enrichment planting of High Priority plant species, where this is deemed appropriate bybotanical experts.

29

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Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM

Additionally, a series of drop-out analyses were carried out to examine theimpact on NPI of partial or total failure of restoration or offsets (e.g. removing
the offsets component from the analysis or greatly reducing the magnitudeof projected gains, and seeing whether NPI could still be reached based on
restoration and Avoidance Zone gains alone). Rio Tinto QMM does not envisagethat the restoration, Avoidance Zones or offset sites will fail, but it is important
to consider this possibility when forecasting to ensure that there is a sufficientbuffer to secure NPI even in the case of partial failure.
Based on the portfolio of offsets, restoration and Avoidance Zones describedabove, for the period 2004 to 2065 (the latter being the current mine closuredate), Rio Tinto QMM is predicted to have a Net Positive Impact on the forests
in general, and on the littoral forest in particular.
Loss of littoral forest caused by direct impacts of mining is predicted to be -428
QH. Total gain of littoral forest is predicted to be +778 QH. Consequently net
impact is positive, at +350 QH, and the ratio of gain to loss (or compensation
to impact) is approximately 2:1. Considering all forest types, loss remains
constant at -428 QH; gain in all forest types (including Bemangidy humid forest)
is +1,679 QH. In this case the ratio of gain to loss (or compensation to impact)
is approximately 4:1. This information is particularly relevant given discussion
in the biodiversity offsetting community around multipliers (BBOP Multipliers
Consultation Working Group, 2008).
In terms of Units of Global Distribution, there is predicted to be a Net Positive
Impact on all High Priority plants (54/54 species) and most High Priority animals(29/36) over the same time period.
Thus, if Net Positive Impact is to be achieved by 2065 overall, urgent research
and action are necessary to mitigate the residual impacts on the remaining sevenanimal species, along with efforts to ensure the continued implementation ofcurrent mitigation measures for the rest of the region’s species and habitats.
Table 1.

Predicted net impact of Rio Tinto QMM for the period 2004–2065,
based on Scenario 2 (0.9% annual deforestation rate, equivalent to
the Madagascar average).
2004-2065
Quality Hectares

Units ofGlobal Distribution

1. All forest+1,251

2. Littoral forest+350

3. Fort Dauphin littoral forest(including Mandena, Petriky, Ste
Luce; excluding Mahabo)+216

1. All High Priority species

83/90 positive

2. Priority plants only

54/54 positive

3. Priority animals only

29/36 positiveForecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM

4.1.2 Impacts on habitats—Quality Hectares
4.1.2.1 Results for 2004–2065
The results of this NPI forecast show that, in terms of Quality Hectares, Rio
Tinto QMM is predicted to have a Net Positive Impact in the period 2004–2065,
based on the conservative national average deforestation rate of 0.9% per year.
Net Impact is predicted to be positive for littoral forest (Mandena, Petriky, Ste
Luce and Mahabo; Table 2, Figure 6), and for all forest types combined (i.e.
including the humid forests of the Bemangidy offset) (Table 2, Appendix 3).
Net impact on littoral forest is forecast to be +350 QH in 2065 (Table 2),
representing an increase of 13% by comparison with 2004, when there were
2,747 QH of littoral forest in Fort Dauphin (Mandena, Petriky and Ste Luce) and
Mahabo, collectively.
A similar result is seen if the analysis is simply based on hectares of littoral
forest rather than Quality Hectares—in this case, by 2065, the net impact is anincrease of 205 ha (an increase of 5% by comparison with 2004 forest cover,which was 4,352 ha in Fort Dauphin and Mahabo).
As can be seen in Figure 6, a similar magnitude of gains in QH is generated byrestoration (collectively), averted loss in Avoidance Zones (collectively), quality
gains in the Avoidance Zones (collectively) and averted loss in the Ste Luce and
Mahabo offsets. Gains at Bemangidy are predicted to be of significantly greater
magnitude; however as this is humid forest it is not a like-for-like offset forlittoral forest (although there is significant overlap of species, c.50% for plants:
Rabenantoandro et al., 2007).
Based on the results per site presented in Table 2, it is possible to calculate net
position for any individual site or combination of sites. For example, Petriky on
its own (which is distinct from Mandena and Ste Luce, see Section 3.3.1.2),
is forecast to be at a net position of -9 QH in 2065. Looking at Mandena, Ste
Luce and Petriky together but excluding Mahabo (which may be relevant froma conservation perspective as Dumetz, 1999, classified these three forests asa unique type of littoral forest on sand), net position in 2065 is forecast to be+216 QH.

31

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Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM

Table 2.

Losses and gains in QH predicted for 2004–2065 for each category ofloss and gain and by forest type, based on counterfactual Scenario 2
for the Fort Dauphin region (i.e., 0.9% annual deforestation rate,equivalent to the Madagascar average).
QH offorestlost/ gained

Hectaresof forest
lost /
gainedType of loss/gain

Site

LOSSES

Mandena mining

-23

-208

LOSSES

Petriky mining

-98

-425

LOSSES

Ste Luce mining

-307

-417

RESTORATION GAINSMandena restoration

79

225

RESTORATION GAINSPetriky restoration

45

225

RESTORATION GAINSSte Luce restoration

56

225

AVERTED LOSS IN AZs

Mandena Avoidance

56

97

AVERTED LOSS IN AZsPetriky Avoidance

20

51

AVERTED LOSS IN AZs

Ste Luce Avoidance

92

116

INCREASED QUALITY IN AZs

Mandena Avoidance

92

0

INCREASED QUALITY IN AZsPetriky Avoidance

24

0

INCREASED QUALITY IN AZs

Ste Luce Avoidance

56

0

AVERTED LOSS IN OFFSETSSte Luce Offset

124

147

AVERTED LOSS IN OFFSETS

Mahabo (littoral forest)

134

168

AVERTED LOSS IN OFFSETS

Bemangidy (humid forest)

901

1001

Total all forest types

1251

1206

Total Fort Dauphinlittoral forest

216

37

Total littoral forest
habitat type (Mandena,
Petriky, Ste Luceand Mahabo)

350

205

1800

Biodiversity impact

1000

500

0

-500

Impacts measured in QH / Cumulative QH gains

Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM

Avoidance Zones (AZs)
Averted loss in AZs
Increased AZ quality
Restoration
Offsets
Impacts-1000

Figure 6. Losses and gains of Quality Hectares of forest for the period 2004–
2065. Note that ‘offsets’ includes both the littoral forest offsetsof Ste Luce and Mahabo (+259 QH) and the humid forest offset of
Bemangidy (+901 QH).

4.1.2.2 Alternative scenarios
As explained in the discussion of the Methods, one assumption that makes
a significant difference to the outcome of the NPI analysis is the backgrounddeforestation rate used for the Fort Dauphin region. The Madagascar national
average from c.1990 – c.2000 (0.9% annual deforestation) was selected as themost appropriate precautionary baseline against which to forecast and measure
Rio Tinto QMM’s performance against the goal of reaching NPI.
One assumptionthat makes asignificant difference
to the outcome of
the NPI analysis isthe backgrounddeforestation rateused for the Fort
Dauphin region.

However, in order to fully understand the implications of selecting this baseline,
alternative baselines were analysed for comparison. Littoral forest QH was
calculated looking at three different scenarios: 0%, 0.9% (national average)
and 3.89% (Fort Dauphin regional average 1995–2005). The method used
was the same in each case (e.g. see Appendix 3; to recalculate NPI for different
scenarios, the background deforestation rate for Mandena, Petriky and Ste Lucewas changed; all other variables remained the same). Additionally, a scenario of
0.1% was calculated to clarify the relationship between NPI and deforestation
rate, which is non-linear (Figure 7).

33

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Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM

1200

Net impact (Quality Hectares)

1000

800

600

400

200

0
-0.5

0

-200

0.5

1

1.5

2

2.5

3

3.5

4

4.5

Background deforestation rate (% per year)

Figure 7. NPI forecast (net impact for 2004–2065) based on different presumed
background annual deforestation rates (0%, 0.1%, 0.9%, 3.89%) for
the Fort Dauphin region.
As can be seen in Figure 7, net impact from 2004 to 2065 is negative (-68
QH) if the background deforestation rate for the Fort Dauphin region is set atzero. This represents a reduction in littoral forest QH of 2% by comparison with
2004 levels. However, as soon as it is assumed that even a small degree of forest
loss is likely to have occurred in the absence of Rio Tinto QMM between 2004
and 2065 (between 0.1% and 0.2%; the point shown just below the x axis on
Figure 7 is based on a background rate of 0.1%), net impact becomes positive.
At the 1995–2005 measured regional background rate (3.89%), the Rio Tinto
QMM project would have a major positive impact (952 QH, representing an
increase of 35% by comparison with the 2004 littoral forest QH).

4.1.2.3 Risk of failure of offsets or restoration
A series of drop-out analyses was carried out to examine the impact upon NPI
at 2065 of total or partial failure of offsets or restoration to deliver measurable
gains. This could happen, for example, if external factors outside Rio Tinto
QMM’s control caused the deforestation rates at the off-site offsets to remain
as high as before 2004 (e.g. major political or socio-economic problems that

Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMMrendered Rio Tinto QMM and its partners’ best conservation efforts ineffectual
in reducing deforestation). In the case of restoration, no other organization
has ever attempted to restore littoral forest and, although Rio Tinto QMM has
made significant investment in research and restoration trials over the past 10
years, with good progress, there is a risk that restoration may not deliver eventhe conservatively estimated gains forecast by the present analysis. All dropout analyses were based on a precautionary shifting baseline (0.9% annual
deforestation rate, the Madagascar average).
If restoration completely fails, the net impact at 2065 is forecast to be +170
QH of littoral forest (a gain of 6% by comparison with 2004). If both off-site
offsets (Mahabo and Bemangidy) fail, the net impact at 2065 is forecast to be+216 QH of littoral forest (a gain of 8% by comparison with 2004).
However, if both restoration and offsets fail completely (and only the AvoidanceZones are successful), the project would have a net negative impact of -88 QH(3% loss).

4.1.3 Impacts on species—Units of Global Distribution
4.1.3.1 Results for 2004–2065
Biodiversity losses and gains were also calculated in terms of Units of Global
Distribution (UD) for High Priority species. This is essentially an extension of the
Quality Hectares method that calibrates losses and gains in terms of % global
range/population size. All High Priority species analyses were based on the
Scenario 2 baseline (0.9% annual deforestation rate, the Madagascar average).
Of the 90 HighPriority terrestrial
species 83 areforecast to show a
Net Positive Impact
by 2065.

Of the 90 High Priority terrestrial species (54 plants, 26 invertebrates, 10vertebrates; Appendices 4 and 5), 83 (92%) are forecast to show a Net Positive
Impact by 2065. For 59 of these, area-based calculations predict that NPI will
be reached. For a further 24 plant species, area-based calculations predict amoderate negative impact (-1.3% to -17.9%) but it is predicted that NPI canbe reached by 2065 through enrichment of the AZs and restoration zones(e.g. planting species at a somewhat greater density than they currently occur
in nature).46 As Rio Tinto QMM tracks its progress towards achieving NPI overthe coming years and decades, gains in priority plant species will be measured
in terms of UD based on population size—this means that enrichment gains
can be accounted for.

Because some of the littoral forest at Mandena, Petriky and Ste Luce was already degradedprior to the arrival of QMM, it is considered likely that some priority plant species (especially latesuccession species requiring a closed canopy) currently occur at a lower density than they would
do in optimal conditions. Consequently ‘enrichment planting’ to increase the density of priority
species in the AZs and restoration areas can be seen as restoring habitat to an optimal state, rather
than creating an artificial landscape. QMM is being advised in these matters by experts in in situ
and ex situ plant conservation from RBG Kew and MBG.

46

35

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Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM

Seven animal species show residual negative impacts—four vertebrates (two frogs,
two reptiles, including the Critically Endangered gecko Phelsuma antanosy) show
residual negative impacts of up to 5.1%, and three invertebrates (all millipedes)
show residual negative impacts of up to 17.9% (Table 3). It is not known whether
enrichment or ex situ conservation would be feasible for these species. Research
is underway to investigate options for achieving NPI for Phelsuma antanosy.
In the majority of cases, achievement of NPI for individual High Priority species isdependent upon the success of restoration efforts. Targeted restoration will beneeded as it cannot be guaranteed that species will naturally colonize the restoration
zones. At present, 27 of the 54 High Priority plant species are being propagatedin a nursery, and it is intended that all High Priority species will be included in thenear future; careful attention is needed in the next few years to check that all
High Priority plants can be successfully propagated and planted out (e.g. into the
Avoidance Zones; many are late-successional species and consequently cannot
be planted in restoration zones until many years from now—trials in the AZs arerecommended, so that any potential problems can be identified early).
Ex situ conservation
measures such as
seed banking andestablishment of
populations inbotanical gardens areneeded for all HighPriority plant species.

Ex situ conservation measures (seed banking, establishment of populations inbotanical gardens, etc.) are needed for all High Priority plant species. Currently
17 of the 54 High Priority plant species (31%) have been stored in seed banks;
the aim is that seeds of all High Priority plant species should be banked by 2015
(Rio Tinto QMM, 2010). Some ex situ actions such as seed banking serve as akind of ‘insurance policy’, others such as establishment of populations in botanic
gardens can produce measurable gains in UD when reintroduced into the wild.
These measures will help to ensure a net positive impact on all species, and inparticular those species for which the NPI forecast predicts residual losses in wild
populations in 2065. It is a general principle in conservation that ex situ conservation
should not replace in situ conservation, although it is often an essential part ofconservation strategies for very rare or threatened species. Because ex situ andin situ biodiversity gains are not the same, Rio Tinto QMM will account for thesegains separately as it tracks its future performance towards NPI.
Further trials and monitoring are needed to determine whether High Priority
animals will naturally colonize restoration zones or whether active measures(e.g. translocation or captive breeding and release) are needed and would be
effective. Phelsuma antanosy shows a potential residual loss of 5.1% of its
global population; further research is needed to determine the most appropriate
conservation measures for this species and Rio Tinto QMM are supporting thisresearch through a Phelsuma antanosy Management Plan project with Fauna& Flora International and the national NGO Voakajy. It has been protected at
Ambatotsirongorongo forest through a joint Rio Tinto QMM-Wildlife Conservation
Society (WCS) initiative47—however this site was already very small and degraded,
WCS are no longer as active at Ambatotsirongorongo as they previously were; however Rio Tinto
QMM retains engagement with the site in the form of two projects: a natural resources management
project with UNDP and the local NGO FAFAFI; and a management plan for the Critically Endangered
gecko Phelsuma antanosy with Fauna & Flora International and the national NGO Voakajy.

47

Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMMand further research is necessary to determine whether the local population
is likely to be viable in the long term. ‘Gains’ from Ambatotsirongorongo are
not included in the summary figures for Phelsuma antanosy presented here.
Table 3.

Animal species with a net negative impact at 2065.
IUCN Red
List category*Net
impact (UD)Group

Species

Amphibians

Guibemantis (Mantidactylus)
bicalcaratus ?sp. nov.

NE

-1.6

Amphibians

Madecassophryne truebae

EN

-0.3

ReptilesPseudoxyrhopus kely

EN

-3.0

ReptilesPhelsuma antanosy

CR

-5.1

Giant pill-millipedes

Zoosphaerium alluaudi

NE

-17.9

Giant pill-millipedes

Sphaeromimus splendidus

NE

-12.7

Spirobolid millipedes

Alluviobolus laticlavius

NE

-17.9

*NE = Not Evaluated, EN = Endangered, CR = Critically Endangered

For all High Priority species together (note that individual results per species
were presented at the beginning of this section), there is forecast to be a net
gain of +1,256 UD. If site-endemic and Critically Endangered plants and animals
that occur at the offset sites but not on the mining leases are also considered,
there are additional gains of +493 UD (+60.3UD for animals and +432.7UD forplants; Tables 4 and 5). These comprise 19 plant species with gains of 10-25
UD and six vertebrate species with gains of 1-25 UD (Tables 4 and 5). Overall,
the project is thus forecast to result in a gain of like-for-like and like-for-notlike High Priority species of c.+1,750 UD. The net losses and gains for all HighPriority species are presented here for illustrative purposes and to highlight theadditional benefits that the offset sites bring for High Priority species that are
not found within the Rio Tinto QMM mining area. They should not be taken to
imply that one species can be exchanged for another species.
If restoration fails completely to generate measurable gains in any of the HighPriority species, there would be a deficit of -1,426 UD. The like-for-not like gainsof +493 UD at Mahabo and Bemangidy provide a partial but insufficient buffer incase of complete failure. By expanding the size of the offset at Bemangidy (e.g.
from the currently proposed 4,000 ha to c.10,000 ha) a more complete buffer
could be provided, although it should be borne in mind that this would not belike-for-like. Ex situ conservation will also help to provide a backup and buffer
in case of failure. Rio Tinto QMM intends to make its restoration a success, but
it is important to consider the worst case scenario during planning.

37

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Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM

Table 4.

Like-for-not-like gains in site-endemic plant species that occur atoffset sites but not on the mining leases.
Species
distribution
(ha)

Gains
2004–
2065 (ha)Gains2065 as %global range

Site

Species

Bemangidy

Lowryanthus rubens Pruski, gen. et sp.
Nov., ined.

4,000

1,001

25.03

Bemangidy

Gnidia razakamalalana Z.S. Rogers

4,000

1,001

25.03

Bemangidy

Ixora bemangidiensis Guédès

4,000

1,001

25.03

Bemangidy

Micronychia bemangidiensis Randrian.
& Lowry

4,000

1,001

25.03

Bemangidy

Diospyros bemangidiensis G.E. Schatz& Lowry, sp. nov. ined.

4,000

1,001

25.03

Bemangidy

Diosypros “Sclerophylla group” sp.
14, ined.

4,000

1,001

25.03

Bemangidy

Hyperacanthus gereaui Rakotonas. &A.P. Davis, sp. nov. inéd.

4,000

1,001

25.03

Bemangidy

Hyperacanthus rajeriarisoniae
Rakotonas. & A.P. Davis, sp. nov. inéd.

4,000

1,001

25.03

Bemangidy

Ivodia anosiensis Rabarimanarivo et al.,sp. nov. ined.

4,000

1,001

25.03

Bemangidy

Polyscias bemangidiensis Lowry & G.M.
Plunkett, sp. nov. ined.

4,000

1,001

25.03

Bemangidy

Polyscias ericii Lowry & G.M. Plunkett,sp. nov. ined.

4,000

1,001

25.03

Bemangidy

Polyscias manonae Lowry & G.M.
Plunkett, sp. nov. ined.

4,000

1,001

25.03

Bemangidy

Polyscias urceolata Lowry & G.M.
Plunkett, sp. nov. ined.

4,000

1,001

25.03

Bemangidy

Schefflera bemangidiensis Lowry &G.M. Plunkett, sp. nov. ined.

4,000

1,001

25.03

Bemangidy

Schizolaena charlotteae Lowry et al.,sp. nov. ined.

4,000

1,001

25.03

Bemangidy

Schrebera trifoliata C. Frasier & G.E.
Schatz, sp. nov., ined.

4,000

1,001

25.03

MahaboBrackenridgia sp. nov.

1,565

168

10.74

MahaboCassinopsis sp. nov.

1,565

168

10.74

MahaboOctolepis cf dioica

1,565

168

10.74
432.67

Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM

Reptilia

Mammalia

MahaboMahabo

60.33

1.08
168
1,252
0.8
1,565

1

Reptilia
MahaboPhelsuma sp. nov. High
Eulemurcinereiceps
High

High

1
High
Amphibia
MahaboHighertaxon

Bemangidy Amphibia

Species

Bemangidy Amphibia

Mantidactylus
aff.grandidieri
Boehmantis
microtympanum
Heterixalus sp.
nov.
Phelsuma cf
quadriocellata

Priority

High

High

1

Strict endemic

11

Regional endemic

EN

IUCN EN or CR?

1,5613

10.74
168
1,252
0.8
1,565
1,565

10.74
168
1,252
0.8
1,565
1,565

10.74
166
1,252
0.8
1,565

2.00
1,001
3,600
EN

Global distribution of
species (ha)1,565

Total area of site (ha)4,000

Condition

4,000

0.9

Total QH at site

0.9

3,600

Gains 2004-2065 (ha)

4,000

1,001

Gains 2065 as %global range

50,00025.03

Like-for-not-like gains in site-endemic, Endangered and CriticallyEndangered animal species that occur at offset sites but not on themining leases.

Site

Table 5.

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Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM

4.2 Is Rio Tinto QMM on track to achieve a
Net Positive Impact on biodiversity forthe period 2004–2015?
4.2.1 Impacts on habitats—Quality Hectares
4.2.1.1 Results for 2004–2015
The QH analysis was also carried out for the period 2004–2015, as 2015 is thefirst internal Rio Tinto benchmark date when all business units subject to the
NPI target must measure their progress towards meeting this goal.
Rio Tinto QMM is predicted to have a Net Positive Impact on littoral forest QH
in the period 2004–2015, based on the national average deforestation rateof 0.9% per year. NPI is predicted to be positive for littoral forest (Mandena,
Petriky, Ste Luce and Mahabo), and for all forest types combined (i.e. including
the humid forests of the Bemangidy offset as well).
Net impact on littoral forest is forecast to be +48 QH in 2015, representing
an increase of 2% by comparison with 2004 levels. This comes primarily fromavoided deforestation, as restoration will only recently have started.

4.2.2 Impacts on species—Units of Global Distribution

Carefully targeted
restoration is
critically importantfor minimizing
residual losses andachieving NPI forHigh Priority species.

The UD analysis indicates that only 32 of the 90 High Priority species are likely
to be at NPI by 2015, and some species show losses of up to 39 UD (twomillipedes, Sphaeromimus inexpectatus and Riotintobolus mandensis, and one
plant Eulophia palmicola show population reductions of this magnitude; all ofthese are Mandena endemics). This is because there will already have been major
impacts by this date (particularly at Mandena), but restoration zones will not
yet have reached sufficient maturity to count towards NPI. Carefully targeted
restoration is critically important for minimizing residual losses and achieving NPI
for High Priority species. However even at these sites, where research and trialsof restoration techniques were instigated well in advance of the start of mining
operations, it still takes time for restoration to create functioning natural habitat
analogues. Furthermore, many of the High Priority species are late-successional
species and cannot be planted out in restoration zones until the restored forest
is reasonably mature. Consequently, even with the best possible conservation
action, it is likely that the majority of High Priority species will not reach NPI by
2015, based on predicted losses and gains in their wild populations.

Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM

4.3 Is Rio Tinto QMM on track to achieve a Net
Positive Impact on biodiversity throughout the
lifecycle of the mine?
Temporal loss isrecognized as asignificant issue thatneeds to be tackled bybiodiversity offsettingand ‘no net loss’ or‘net positive impact’
initiatives.

Temporal loss is recognized as a significant issue that needs to be tackled
by biodiversity offsetting and ‘no net loss’ or ‘net positive impact’ initiatives(ten Kate et al., 2004; Burgin, 2008; Bekessy et al., 2010). It can be said tooccur when a loss occurs in advance of sufficient gains being accrued throughrestoration, averted loss at offsets, or other measures. To determine whether Rio
Tinto QMM is forecast to be ‘net negative’ with respect to littoral forest habitat
at any point during the lifecycle of the mine, losses and gains were calculatedusing the same methods and assumptions as above and displayed on a yearby-year cumulative basis (Figure 8). To calculate losses on a year-by-year basis,
some additional assumptions had to be made. These were (i) that Mandena,
Ste Luce and Petriky would be mined sequentially (this is the current plan), (ii)that a constant number of QH will be lost to mining every year of ‘active’ minelife (during the last few years of mine life, the ‘closure phase’, there will be
no further mining activity; activities such as decommissioning and restoration
and rehabilitation are carried out during this phase); and (iii) that mining willstop c.12 years before final closure (this is the current plan). Assumption (ii) is
simplistic, first because although the dredge moves steadily and more-or-lessconstantly through the landscape, covering c.100 ha per year (Rio Tinto QMM,
2001), the forest cover is patchy both in terms of quantity and quality. Second,the extent of forest QH at Ste Luce is greater than that at Petriky, so the timingof losses depends on whether Ste Luce or Petriky is mined after Mandena.
However, despite these caveats, better predictive data are not yet available and it
was felt that a year-by-year cumulative analysis would provide useful additional
information. This analysis was carried out for forest habitats only, measured in
Quality Hectares, because it would have been very significantly more complex
to carry out an analogous analysis for High Priority species.
The results (Figure 8) suggest that there will be no temporal loss of littoral forest,
and that Rio Tinto QMM will remain net positive in terms of littoral forest QH
throughout mine life.

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Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM

Cumulative QH gains / impacts measured in QH

1800
1600
1400
1200

Bemangidy offset
Littoral offsets

1000

Restoration
Increased AZ quality

800

Averted loss in AZs
Impacts

600
400
200
0

Time (2004-2065)

Figure 8. Cumulative gains in littoral forest over time (measured in QH)
compared to cumulative impacts from mining (measured in QH).

Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM5

Conclusions
and next steps

5.1 Summary
Detailed analyses based on the best available scientific information were carriedout to project biodiversity losses and gains over the life of the mine (2004–2065)
and to determine whether Rio Tinto QMM will have a Net Positive Impact at
closure. Biodiversity losses and gains were calculated in two ways: using Quality
Hectares as a metric (for forest habitats); and using Units of Global Distribution
as a metric (for High Priority species, e.g. threatened and restricted-range
species). Rio Tinto QMM’s Biodiversity Committee has approved the use of these
metrics. Results show that Rio Tinto QMM is anticipated to have a Net Positive
Impact on biodiversity, both in terms of Quality Hectares of littoral forest andUnits of Global Distribution for the majority (83/90) of High Priority species, if
the mitigation measures outlined in this report are successfully implemented.
The mitigation portfolio proposed by Rio Tinto QMM is as follows:
Offsets: at (i) Mahabo, (ii) Tsitongambarika III Bemangidy, (iii) Ste Luce Forests.
Ambatotsirongorongo and the Tsitongambarika (TGK I) Direct Payments project
are currently under review as formal offsets, so gains from these two sites are
not included in the quantitative analysis presented here. Each of these sites isdiscussed in more detail later in the report.
Restoration: 225 ha of restoration each at Mandena, Petriky, Ste Luce. Restoration
zones will be located adjacent to the Avoidance Zones, to provide a buffer,improve connectivity and facilitate natural regeneration and recolonization.
Avoidance Zones: at Mandena, Petriky, Ste Luce.
The project is predicted
to have a Net Positive
Impact on littoral
forest in 2065, anda significant Net
Positive Impact onregional forest types.

The project is predicted to have a Net Positive Impact on littoral forest in 2065(+350 QH), and a significant Net Positive Impact on regional forest types,
including Bemangidy humid forest (+1,251 QH).
The project is predicted to have a Net Positive Impact on 83/90 High Priority
species, comprising a total of +1,256 UD (including like-for-like species only)
and +c.1,750 UD (including like-for-not-like High Priority species that are foundin the offsets but not on the mine site). For individual High Priority species,
area-based predictions indicate that 59/90 will experience net gains by 2065;
for the remaining 31 (24 plants and seven animals: four vertebrates and three
invertebrates), it is intended that NPI will be met by a combination of enrichment(e.g. by restoring species towards presumed natural densities from their currently
depleted densities; this may be more feasible for plants than for animals; trials

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Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM

are needed) and ex situ conservation measures such as propagation in botanicalgardens. Based on area-based predictions, no plant or invertebrate is predicted tohave a residual decline greater than 18% and no vertebrate species is predicted
to have a residual decline greater than 5% of its global distribution (i.e. 5 UD)
requiring compensation through enrichment and insurance through ex situ
conservation measures.
These calculations are based on a number of assumptions; they are based on thebest data available at present although there is significant uncertainty aroundany prediction of what will happen 55 years hence.
A key assumption that makes a significant difference to the analysis is
the counterfactual scenario considered. We propose that a precautionary
counterfactual scenario (0.9%, the Madagascar national average) is the mostappropriate to use. The analyses presented here show that, even if only a very
low rate of deforestation is presumed (Figure 7), the Rio Tinto QMM projectwill have a Net Positive Impact on littoral forest over the life of the mine basedon the proposed mitigation portfolio.

5.2 Achieving NPI—what does it mean for
Rio Tinto QMM?
One of the original
reasons for carryingout this analysis was toprovide transparent
quantification of likely
losses and gains.

One of the original reasons for carrying out this analysis was to provide transparent
quantification of likely losses and gains, in order to inform debate and allow a
consensus to be reached between Rio Tinto QMM and the Biodiversity Committee
regarding what ‘achieving NPI’ means for Rio Tinto QMM.
Following discussion of an earlier draft version of this report at the Biodiversity
Committee Meeting held on 3-6 May 2010 in Fort Dauphin, Madagascar, theBiodiversity Committee recommended that ‘achieving NPI’ means achieving a
Net Positive Impact on littoral forest48 (using QH as a metric) and achieving a
Net Positive Impact on species (using UD of High Priority species as a metric).
The target is to achieve NPI for each High Priority species individually. Measuresof UD should be based on population size as well as distribution area whereappropriate; it is likely that population information will become available formore species as time goes on. It is assumed that QH will provide an adequate
surrogate for other species. Rio Tinto QMM accepted these recommendations.
It is important to note that QH and UD are the main metrics used to forecast
NPI over the mine life, and to plan for the type and scale of interventions
required, but they are not the only metric or indicator that will be used at Rio
Tinto QMM. In addition, to track progress against broader conservation goals
I.e. offsets in a different forest type, such as the humid forest offset at Tsitongambarika, canact as an ‘insurance policy’ and a kind of additional benefit (as well as providing key ecosystemservices such as water for local communities), but it was agreed that a loss of littoral forest cannot
be compensated for by a gain in a different habitat type. This decision was made at QMM basedon the local context; however at other sites a different decision might be made.

48

Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMMas outlined in the Biodiversity Action Plan (Rio Tinto QMM, 2010), Rio Tinto
QMM and partners will be monitoring a number of indicators of e.g. ecosystem
integrity, diversity of common species, forest regeneration, presence/absence andnumbers of invasive species, etc. Further details can be found in the Biodiversity
Action Plan and in specific monitoring protocols developed (or currently underdevelopment) in consultation with the Biodiversity Committee.

5.3 Rio Tinto QMM’s biodiversity offsets
Figure 8 shows sites that are current Rio Tinto QMM biodiversity offsets, orthat are under consideration as Rio Tinto QMM offsets. Three offset sites were
included in the quantitative analysis in this report; two of these sites (Ste Luce
Forests and Mahabo) already have active conservation programmes, while thethird (Bemangidy) is awaiting confirmation as an offset by Rio Tinto QMM and
the Biodiversity Committee.
Two further potential offset sites are discussed below (Ambatotsirongorongo and
TGK I Direct Payments Project)—both of these sites have had active conservation
projects funded by Rio Tinto QMM over several years, but review is ongoingregarding whether they should be maintained as offset sites in the future.
Consequently they have not been included in the quantitative NPI forecast in
this report.
Ste Luce Forests are 500 ha of littoral forest, adjacent to (but not overlapping)
the Ste Luce ilmenite deposit. They are very similar to forests on the Rio Tinto
QMM deposits, and so are a like-for-like offset for both habitat type and species.
They are part of the mining leases so Rio Tinto QMM has greater control thanat other offset sites (reducing uncertainty). A conservation programme has
been operating at this site since before 2004, initiated, funded and managed
by Rio Tinto QMM.
Mahabo is a 1,500 ha littoral forest offset site located several hundred kilometres
north of Fort Dauphin. In collaboration with Missouri Botanical Gardens it
was chosen as a ‘like-for-like’ offset site for littoral forest as a habitat type. Its
distant location is not ideal but it represents the best option, after Ste Luce, fora littoral forest habitat offset through averted deforestation and degradation.
A conservation and development programme with local communities has been
operating since 2004 at this site (jointly funded and managed by Rio Tinto QMM
and Missouri Botanical Gardens).
Bemangidy provides
important ecosystemservice benefits such as
water provision andcarbon sequestration.

Bemangidy (Tsitongambarika III) is a c.4,000 ha parcel of lowland humid
forest within the larger c.60,000 ha Tsitongambarika forest. It is a like-for-not-like
offset for locally endemic species, and a like-for-like offset for more widespread
species. Additionally, it provides important ecosystem service benefits such as
water provision and carbon sequestration. Bemangidy currently has the statusof a proposed offset site—a Management Plan has been drafted for the site.
As a large parcel of remaining forest, even though it is not a ‘like-for–like’

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Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM

offset, it provides a crucial ‘insurance policy’ in case conservation at some ofthe smaller sites is less successful than hoped in the long term. Even with active
conservation intervention, small parcels of forest can be difficult to protect andmanage in the long term.
In 2004, through discussions with BirdLife International and Asity Madagascar(the BirdLife partner in Madagascar), the value of the whole Tsitongambarika
unprotected area of humid forest was identified as a strategic priority for Rio
Tinto QMM. It was clear the area had the potential to act as an offset site formany littoral forest species and also had huge value as the regional ecosystemservices hub for water, soil fertility, non-timber forest products, littoral forest
pollination and seed dispersal, and local climate regulation. Significant conservation
activities have already been implemented with the involvement and support of
Rio Tinto QMM that benefit the whole forest.
1. Policy and legislation: protected area designation under national law. Rio
Tinto QMM and Asity Madagascar have carried out the preparatory work
necessary to have Tsitongambarika designated a new national protected
area, within the Système des Aires Protegées de Madagascar. This work
was funded by Rio Tinto QMM. Tsitongambarika currently has temporary
protection status N°21480 of 02/12/2008, pending political processes.
2. Long-term planning: a Tsitongambarika Conservation Management
Plan. A coalition of agents including government, CBOs, NGOs and local
communities has collaboratively developed a long-term management planfor the forest.
3. A community-based forest conservation project has been implemented in
Tsitongambarika 1 by Asity Madagascar (funded by Rio Tinto QMM); this is
described further under ‘Tsitongambarika 1’ below.
4. Ongoing surveys of flora and fauna since 2003.
Rio Tinto QMM is currently deciding where in Tsitongambarika its offset activities
should be focused. At present, the most likely strategy is that Rio Tinto QMM’s
offset activities will be focused in a particular area within Tsitongambarika (e.g.
Bemangidy or similar), but that Rio Tinto QMM will seek partner organizations(such as Asity Madagascar, which is the lead responsible party for the wholeprotected area under government policy) and co-financing to carry out conservation
activities throughout the whole of Tsitongambarika.
Tsitongambarika 1 is the southern part of the large forest massif that also
encompasses Bemangidy. A Direct Payments community-based avoided
deforestation programme was operated by Asity Madagascar in six villages inthis area from 2007 to 2009, funded by Rio Tinto and QMM. It is an incentivebased community conservation project whereby forest integrity is conserved in
exchange for local community development such as schools and clinics. This wasa pilot project and longer-term involvement of Rio Tinto QMM in Tsitongambarika
as a whole is currently under review, as described above.

Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM

Ambatotsirongorongo is an area of transitional forest to the west of Petriky
which has suffered a high rate of deforestation. The forest is home to a significant
population of Phelsuma antanosy (Critically Endangered) currently only otherwise
found in the littoral forests in Ste Luce (including the Ste Luce Forests offset).
This small gecko was previously also observed in Petriky, but background habitat
loss through subsistence agriculture appears to have eliminated this population.
The Ambatotsirongorongo programme is a partnership between Rio Tinto QMM,
the Wildlife Conservation Society and local communities.

5.4 Monitoring forest loss

Measuring averted
deforestation will
be a key piece of
NPI accounting in
the future, andneeds to be given
careful thought at
an early stage inproject planning.

A significant proportion of biodiversity gains for Rio Tinto QMM will accrue
through averted loss. For Rio Tinto QMM to be able to credibly claim these gains
in 2065, a robust and consistent monitoring system will be needed to document
rates of forest loss across the mining leases and all the offset sites, to show that
real measurable averted loss is occurring. It would also be advisable to measurerates of loss in the wider region over the same period to provide context and tohelp monitor Rio Tinto QMM’s success in tackling potential secondary impacts
such as habitat conversion resulting from in-migration. Measuring averted
deforestation will be a key piece of NPI accounting in the future, and needs to begiven careful thought at an early stage in project planning. Whatever method ischosen, care must be taken that it does not provide a ‘perverse incentive’ for Rio
Tinto QMM to encourage (or fail to help reduce) forest loss in the wider region.

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Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM

Figure 9. Current biodiversity offset sites or sites that are under consideration
as offsets.

Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM

5.5 The broader context—drivers of biodiversity
loss in southeastern Madagascar
Forest conservation
in southeastern
Madagascar will only
be successful in thelong term if theunderlying drivers of
biodiversity loss are
addressed.

As in other parts of the world, forest conservation in southeastern Madagascar
will only be successful in the long term if the underlying drivers of biodiversity
loss are addressed. Prior to the arrival of Rio Tinto QMM in the 1990s, the littoral
forest was already in rapid decline (Vincelette et al., 2007b). Apart from mining,other major causes of current forest loss are unsustainable levels of charcoal
production and tavy (slash-and-burn agriculture). People using forests in theseways do so because they have no other option—82% of Anosy inhabitants live
below the poverty line (US1$/day; Vincelette et al., 2007a).
Many of Rio Tinto QMM’s Additional Conservation Actions seek to address theseunderlying causes of biodiversity loss, for example by setting up plantations offast-growing non-native trees to reduce charcoal production pressure on native
forest, or providing alternative livelihoods by training local people in skills suchas blacksmithing, crop production and diversification, vetiver grass production
and planting, improved rice production, animal breeding, handicrafts, etc.
However, southeastern Madagascar’s social and environmental problems cannot
be solved by the actions of a single company; broader initiatives are needed
involving multiple agencies and stakeholders.

5.6 NPI analysis updates and adaptive management
As part of Rio Tinto QMM’s biodiversity action planning process, this analysis
and forecast should be periodically revisited to take into account changes suchas newly discovered or described species, new listings (and up- or down-listings)
on the IUCN Red List, and methodological improvements that can be made as
the state of knowledge and best practice in relevant fields such as biodiversity
metrics and biodiversity offsetting evolve. This will help Rio Tinto QMM to trackprogress and will contribute to adaptive management. It will also allow theassumptions made in the present analysis to be tested based on empirical data
(e.g. is it reasonable to assume that deforestation can be completely stopped
in the Avoidance Zones? Is it reasonable to assume that conservation actions
will improve the quality score of the Avoidance Zone in Petriky by 0.05 every 15
years?). It is recommended that this analysis should be revisited at least every
five years (the same periodicity is recommended for revisiting the Biodiversity
Action Plan: Rio Tinto QMM, 2010). Section 7 details lessons learned in carryingout the present analysis and recommends areas for future research—subsequent
iterations of this NPI forecast should take into account these lessons, as well as
any relevant new research findings.

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6

Lessons learned
and directions for
future research

6.1 Potential impacts of climate change
An important point to consider in the future is how Rio Tinto QMM can factor
the potential impacts of climate change into biodiversity action planning andimplementation of restoration and offsets. The impact sites, avoidance andrestoration zones, and littoral forest offset sites are all close to the coast andat very low altitudes. Consequently, by 2065, they may plausibly be impacted
by sea level rise (especially when associated with storm surges), and will face
increased temperatures and decreased rainfall. This could pose problems for the
long-term viability of Rio Tinto QMM’s littoral forest conservation areas. Among
many other things it may affect the ease and effectiveness of restoration, andcould wipe out other gains in Quality Hectares as the climate becomes lesssuitable for littoral forest or the coast is inundated. There may be a need tosecure and re-vegetate areas that are further inland or upslope, and to think
about buffers and corridors for existing sites. This underlines the importance of
Rio Tinto QMM’s ongoing monitoring of the habitats and species and adaptive
management to changing conditions as they occur (Rio Tinto QMM, 2010).
Recent researchmodelling species
range shifts in
Madagascar in
response to futureclimate change
predicted that thelittoral forest will
disappear.

Recent research modelling species range shifts in Madagascar in response to
future climate change predicted that the littoral forest will disappear (Hannah
et al., 2008), and palaeoecological reconstruction indicates that littoral forest
in the Fort Dauphin region has been highly dynamic in response to climaticchanges in the past (Virah-Sawmy et al., 2010). Given that the Rio Tinto QMM
mine is planning for the 2004–2065 time period, it would be useful to evaluate
the vulnerability of the conservation actions described in this report to different
climate change scenarios (i.e. less rain, warmer temperatures, higher sea level,
increased frequency of storms) to determine how resilient the proposed activities
would be. It would also be informative to supplement the broad-scale modellingof Hannah et al. (2008) with a more detailed study at the regional level.

6.2 Defining a standard set of species to be
included in NPI accounting
At present, Rio Tinto’s guidance on which species to include in NPI accounting is
not prescriptive, although it does state that this decision should be based on theclassic conservation priority-setting principles of vulnerability and irreplaceability,
and should be done in consultation with relevant experts and stakeholders(Ekstrom and Anstee, 2007; Rio Tinto, 2010). For this analysis, and following
these principles, Rio Tinto QMM (in consultation with the biodiversity committee

Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMMand other experts) determined that High Priority species as defined in the
Biodiversity Action Plan (Rio Tinto QMM, 2010) should be included. These
include globally Critically Endangered and Endangered species and species witha highly restricted distribution (see Rio Tinto QMM, 2010 for a definition), but
excluded Vulnerable species.
One of the lessons learned from this process is that it may be valuable for Rio
Tinto to define a standard set of species to be included in NPI accounting, basedon criteria that are applied in the same way to all Rio Tinto sites globally. Thisshould likely include Vulnerable species as well as those listed as Endangered andCritically Endangered on the IUCN Red List. It may also be valuable to establish
standard definitions for what constitutes ‘restricted range’. If Rio Tinto develops
such standard guidelines, they should be used in subsequent iterations of thepresent analysis.

6.2.1 Undescribed species
When it comes todefining a standard setof species for inclusion
in NPI accounting,undescribed species
present an interesting
conundrum.

When it comes to defining a standard set of species for inclusion in NPI accounting,undescribed species present an interesting conundrum. The present analysis
includes a number of possible new species that have yet to be formally described.
Many of these will be described over the course of the project, and Rio Tinto
QMM arguably has a responsibility to support the taxonomic research to allow
this. However, it is debatable whether it is appropriate to include such taxa informal NPI calculations. Based on experience from carrying out this analysis, wewould recommend that Rio Tinto develops a standard policy for dealing with
undescribed species.

6.3 Counterfactual scenarios, baselines, andcalculating biodiversity gains from averted loss
This is a particularly fertile and fast-moving field of research at the moment
given interest in REDD (Reducing Emissions from Deforestation and Degradation)and growing interest in biodiversity offsets. It will be important to keep abreastof developments in this field, and evaluate their relevance to calculation of
biodiversity offset gains at the site level, to ensure that NPI accounting andforecasting is as robust as possible. Specific questions raised elsewhere in thisreport include how to ensure that calculation methods do not inadvertently
create perverse incentives, and how best to monitor deforestation and measuregains going forward.

6.4 Calculating Units of Global Distribution—
methods for measuring species distribution area
In the present analysis, in cases where UD was measured based on distribution
rather than population (e.g. where population data were unavailable at the global
and site level), it was necessary to estimate the global distribution area for eachspecies. Different methods were used depending on the taxon in question. For

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example, for some mammals and birds area of occupancy (AOO) was calculated
by measuring extent of occurrence (EOO) based on maps from the IUCN Red
List of Threatened Species (IUCN, 2009), and inferring AOO based on a very
rough ‘rule of thumb’ of 10% of EOO (this relationship between AOO andEOO is implied by the thresholds set for Criterion B of the IUCN Red List). EOO
cannot be used without some modification because it typically overestimates(sometimes vastly) the area occupied by each species (Jetz et al., 2008; Rodrigues,2011). However, for future analyses of this type, it could be worth exploring
whether other metrics such as Extent of Suitable Habitat (ESH) offer a usefulalternative. ESH is the area of potentially suitable vegetation types within thealtitudinal preferences of the species (Rondinini, et al., 2005; Buchanan et al.,2008). In a recent study using the ESH method, species’ range was restricted on
average to 28% of its original EOO (Beresford et al., 2011). However, the ESH
method is not without its problems, as detailed by Rodrigues et al. (2011); a
recent ground-truthing exercise suggested that the ESH method had very little
capacity to distinguish between occupied and non-occupied parts of species’
EOOs (Beresford et al., 2011; Rodrigues et al., 2011).

Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM

7

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McKenney, B. and Kiesecker J.M. 2010. Policy Development for Biodiversity Offsets:
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Nussbaum, R.A., Raxworthy, C.J., Raselimanana, A.P. and Ramanamanjato, J.-B.
1999. Amphibians and reptiles of the Réserve Naturelle Intégrale d’Andohahela,
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Naturelle Intégrale d’Andohahela, Madagascar: With reference to elevationalvariation. Fieldiana: Zoology, 94: 155–173.
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vegetation: the ‘habitat hectares’ approach. Ecological Management andRestoration, 4: S29–S38.
Rabenantoandro, J. 2001. Floral, structural and dendrometric analysis of low
altitude humid forest on the western slopes of the Masaola National Park
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Antananarivo University.
Rabenantoandro, J., Randriatafika, F. and Lowry II, P.P. 2007. Floristic and Structural
Characteristics of Remnant Littoral Forest Sites in the Tolagnaro Area. Pp. 6593 in: Ganzhorn, J.U., Goodman, S.M. and Vincelette, M. (eds.). Biodiversity,
Ecology and Conservation of Littoral Ecosystems in Southeastern Madagascar;
Tolagnaro (Fort Dauphin). Smithsonian Institution, Washington DC.
Rabevohitra, R., Wilmé, L., Lowry II, P.P. and Schatz, G.E. 1998. Pp. 65–99 in:
Ratsirarson, J. and Goodman, S.M. (eds.). Biological inventory of the littoral forestof Tampolo. Volume 14. [Inventaire biologique la Foret Littorale de Tampolo.]
Volume 14. Centre d’Information et de Documentation Scientifique et Technique,
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Ramsar Convention Secretariat. 2004. Designating Ramsar Sites. Strategic
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Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMMRaxworthy, C.J. 2003. Introduction to the Reptiles. Pp. 934–949 in: Goodman,
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Washington DC.
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Wesener, T. and Wägele, J.W. 2007. Giant Pill-Millipedes (Diplopoda:
Sphaerotheriida) in the Littoral Forest Fragments of Southeastern Madagascar.
Pp. 147–154 in: Ganzhorn, J.U., Goodman, S.M. and Vincelette, M. (eds.).
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Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMMAppendix 1
QMM Biodiversity Committee
QMM invited external biodiversity experts to participate in a formal Biodiversity
Committee in 2003. The Committee had operated informally for several years
prior to this. The Committee operates with full autonomy, being free to publicallycriticize Rio Tinto QMM (either individually or collectively), and receiving no
remuneration for time spent on Committee meetings.49
The purpose of the Committee is to advise QMM on how best to conserve andenhance biodiversity within the project area before, during and after mining.
The Committee also advises QMM and the regional authorities on biodiversity
issues within the Fort Dauphin area. The Committee assists QMM with theimplementation of its Biodiversity Programme, for example by critically reviewing
and providing input to the draft Biodiversity Action Plan (Rio Tinto QMM, 2010)
and the present report, and assisting with the preparation of the biodiversity
monograph (Ganzhorn et al., 2007).
The Guiding Principles of operation for the Biodiversity Committee include:• Open and honest communication;• Non-attribution of discussions;• Full access to social and environmental information;• Information and Committee process accessible to public;• Members retain freedom to communicate, singly or collectively, about
Committee activities and the project.
The Committee meets once a year; additional ad hoc meetings may be arranged
between some or all members at other times. Meetings normally last threedays, and include a mixture of technical and strategic issues. The Committee
provides expert advice to QMM and can identify its own topics of interest andagenda priorities. The last day of each meeting includes a ‘closed session’ that
only the Committee can attend (e.g. no Rio Tinto QMM staff may be present).
The Committee typically gives Rio Tinto QMM a set of formal comments andrecommendations at the end of each meeting, to which QMM must respond.
QMM provides for any additional work requested by the Committee andmutually agreed upon.
Committee meetings are hosted by QMM; travel and living expenses related
to meetings are reimbursed by QMM; however Committee members are notremunerated for their time and contribution to Committee meetings.
49
Travel and living expenses are reimbursed, and committee members (or their institutions) may
at times be engaged to deliver specific pieces of work which are financed either as separate
contracts, or through the existing partnership frameworks (e.g. Rio Tinto has formal partnershipprogrammes with a number of NGOs including RBG Kew), as appropriate.

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Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM

Appendix 2
Quality Hectares and Units of
Global Distribution
Quality Hectares (QH)
Quality Hectares are Rio Tinto’s standard metric for tracking progress towards
the NPI target at the global and site level. They are conceptually related tothe ‘habitat hectares’ metric used in Victoria, Australia (Parkes et al., 2003). A
wide range of biodiversity values, including threatened species, rare habitats
or non-timber forest products, may be expressed in terms of their quantity andquality. This is expressed as an ‘Area × Quality’ metric, referred to here as Quality
Hectares (QH). For example, 100 hectares of forest in pristine condition would
count as 100 Quality Hectares (100 ha × 100% quality = 100 QH), whereas 100
hectares of fairly degraded forest at 40% ‘optimal quality’ would be expressed
as 40 Quality Hectares (100 ha × 40% quality = 40 QH).
Quality or condition can be measured in a variety of different ways, depending
upon the habitat in question. Rio Tinto does not have a single ‘one-size-fits-all’global method for measuring habitat quality because it is so context dependent,
but rather recommends using established and accepted methods where these
are available at the regional (e.g. national or state) level. Because there was no
established methodology for evaluating habitat condition in Madagascar, QMM
has developed its own classification method, with input from Missouri Botanical
Garden (MBG), Royal Botanic Gardens (RBG Kew), FOFIFA,50 and other experts.
This method is described in Vincelette et al., (2007b) and Rabenantoandro etal. (2007).
Units of Global Distribution (UD)Units of Global Distribution are a novel metric, developed for this analysis, butconceptually related to Quality Hectares. A Unit of Global Distribution is equivalent
to 1% of a species’ global population (or 1% of its global distribution, in theevent that population data are unavailable). Units of Global Distribution arecalculated as follows: if a species has a global population of 1,000 individuals,
and 10 of those are lost, that would be a loss of 1% of the global population or
1 ‘Unit of Global Distribution’ (UD). Similarly, if a species has a global distributionof 100 ha, and 1 ha of its distribution is lost as a result of habitat loss causedby mining, that is a loss of 1% of its global distribution or 1 ‘Unit of Global
Distribution’ (UD).
A precedent for the use of this kind of metric can be found in the quantitative
thresholds used to identify sites of global significance for biodiversity conservation.
Under the Convention on Wetlands (Ramsar Convention, 1971), sites are
50

The National Centre for Applied Research into Rural Development, www.fofifa.mg.

Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM

selected for the List of Wetlands of International Importance according to a suiteof criteria adopted by the Conference of Parties, one of these being Criterion
6: “A wetland should be considered internationally important if it regularly
supports 1% of the individuals in a population of one species or subspecies ofwaterbird” (Ramsar Convention Secretariat, 2004). Similarly, the criteria for theidentification of Key Biodiversity Areas (KBAs) use thresholds of 1% or 5% of
the species’ global population (depending on the type of species in question)
to identify Key Biodiversity Areas (Langhammer et al., 2007).
This is the first offsets analysis to use Units of Global Distribution (UD) as a metricor currency, so their use warrants a brief discussion. Crucially, the use of the‘Units of Global Distribution’ metric should not be seen to imply that different
species are directly exchangeable. It will never be acceptable to simply statethat it is permissible to render a species of plant extinct so long as one protects
in perpetuity the entire global range of a particular frog species. Rather, it gives
an idea of the scale of losses, and the concomitant scale of gains required togive a Net Positive Impact.
The advantage of Units of Global Distribution is that this metric is much moreclosely linked to the extinction risk51 faced by a species than is simple hectares(or even Quality Hectares). For example, a loss of 80 ha of habitat would becatastrophic for a species with a total global distribution of 100 ha, but would
be of negligible significance for a species with a total global distribution of
1,000,000 ha. The disadvantage is that it is slightly more difficult and timeconsuming to calculate, although as demonstrated by the present analysis it isfeasible. Essentially, Units of Global Distribution are a way of calibrating losses/
gains measured in hectares (or Quality Hectares) so that they take into accountthe total global area of distribution of a particular biodiversity value. UD canbe calculated for species, habitats, or other types of biodiversity value (e.g.
non-timber forest products).

51
Indeed, a reduction in Units of Global Distribution is essentially the same as what is measured byCriterion A of the IUCN Red List of Threatened Species. Under Criterion A, if a species loses >80%
of its global population in 10 years/3 generations (which can be inferred based on reduction in
distribution), it would be classed as Critically Endangered. Similarly, a reduction of >50% would
render a species Endangered and a reduction of >30% would render a species Vulnerable (IUCN,
2001).

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Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM

Appendix 3
Estimated forest coverremaining in 2065 givenno mineQuality in 2004

Total QH Lost

330 0.009

208

0.11

23

LOSSES

Petriky Mining

674 0.009

425

0.23

98

LOSSES

Ste Luce Mining

661 0.009

417

0.74

307

RESTORATIONGAINSRESTORATIONGAINSRESTORATIONGAINSAVERTED LOSSIN AZsAVERTED LOSSIN AZsAVERTED LOSSIN AZs
INCREASEDQUALITY IN AZs
INCREASEDQUALITY IN AZs
INCREASEDQUALITY IN AZs
AVERTED LOSSIN OFFSETSAVERTED LOSSIN OFFSETSAVERTED LOSSIN OFFSETS

Mandena
restoration
Petriky
restoration
Ste Luce
restoration
Mandena
Avoidance (AZ)
Petriky
Avoidance (AZ)
Ste Luce
Avoidance (AZ)
Mandena
Avoidance (AZ)
Petriky
Avoidance (AZ)
Ste Luce
Avoidance (AZ)
Ste Luce Offset

HA forest cover AZor Offset

Quality in 2004

QH in 2004

Forest cover in 2004

Type of loss/gain Site
LOSSES
Mandena Mining

Backgrounddeforestation rate

Losses and gains in Quality Hectares (QH) of littoral forest

230

0.57

132

120

0.39

46

274

0.80

218

230

0.57

132

120

0.39

46

274

0.80

218

498

0.84

420

Mahabo

1565

0.80

1252

Bemangidy

4000

0.90

3600

Total All
forest Types
Total Fort
DauphinLittoral Forest
Total Littoral
ForestNet QH of Forest
Gained throughQMM investment

What proportion of
offset gains can beclaimed by Rio Tinto?

QH remaining after 61
years @ 50%/75%/100%
background rate

QH remaining after 61
years @ background rateYears of Intervention
since 2004 baseline

Reduceddeforestation rate

Deforestation rate

QH in 2065

Area in 2065

Quality in 2065

Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM

-23.3
-97.7
-307.1
0.35

225

79

79

0.20

225

45

45

0.25

225

56

56
0.009

0

61

76.1

132.1

1.00

56.0

0.009

0

61

26.6

46.3

1.00

19.6

0.009

0

61 125.6

218.1

1.00

92.4

0.97

230

224

1.00

92.0

0.59

120

70

1.00

24.0

1.00

274

274

1.00

55.9

0.009

0.002361 242.0

366.1

1.00

124.1

0.008

0.004061 767.0

980.4

0.63

134.5

0.02550.012861 744.7

1645.71.00

901.0
1251.4
215.9

350.4

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Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM

Appendix 4

Scientific name

Amphibians

Guibemantis (Mantidactylus) bicalcaratus nov. sp.

Amphibians

Guibemantis (Mantidactylus) cf pulcher nov. sp.

Amphibians

Guibemantis (Mantidactylus) punctatus nov. sp.

Amphibians

Madecassophryne truebae

Amphibians

Stumpffia cf tridactyla nov. sp.

ReptilesPseudoxyrhopus kely

ReptilesPhelsuma antanosy

Birds

Anas melleri

Birds

Ardea humbloti

Terrestrial mammals

Microcebus cf rufus nov. sp.

Giant pill-millipedes

Zoosphaerium alluaudi

Giant pill-millipedes

Zoosphaerium arborealis

Giant pill-millipedes

Zoosphaerium sp. ‘Sainte-Luce’

Giant pill-millipedes

Sphaeromimus inexpectatus

Giant pill-millipedes

Sphaeromimus splendidus

Spirobolid millipedes

Riotintobolus mandensis

Spirobolid millipedes

Riotintobolus minutus

Spirobolid millipedes

Granitobolus sp.‘black’

Spirobolid millipedes

Alluviobolus laticlavius

Mantises (Mantodea)

Nesogalepsus sp.

Mantises (Mantodea)“Tarachodinae” sp.

Mantises (Mantodea)

Apterocorypha sp.

Mantises (Mantodea)

Platycalymma sp.

Mantises (Mantodea)

Tarachomantis sp.

Mantises (Mantodea)

Tisma freyi

Mantises (Mantodea)

Tisma pauliani

Mantises (Mantodea)

Danuriella irregularis

Non-endemic
species with nolike-for-like offset

Higher taxon 2

Characteristics of High Priority species for which losses and gains
were calculated in Units of Global Distribution (UD)YesGlobalrange (hectares)

Global population
size (numberof individuals)- estimated for
endemic plants

Bespokeloss/gain
measurements
needed?

Unit of measurement

IUCN Red
List Status

Endemism status

Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMMRegional or local endemic

LC(G. bicalcaratus)

UD

1,595

Regional or local endemic

NE

UD

2,093

Regional or local endemicDD(G. punctatus)

UD

2,093

Regional endemic

EN B1ab(iii)UD

36,373

Regional or local endemic

DD

UD

2,093

Regional endemic (found onlyat two forest sites)

EN B2ab(ii,iii)

UD

11,660Regional endemic (found onlyat two forest sites)

CR B2ab(ii,iii,iv)

UD

Country endemic

EN C2a(ii)UD2,111,126

Country endemic

EN C2a(ii)UD

285,554

Regional or local endemic

LC (M. rufus)

UD

1,355

Regional or local endemic

NE

UD

890

Regional or local endemic

NE

UD

2,093

Regional or local endemic

NE

UD

498

Regional or local endemic

NE

UD

738

Regional or local endemic

NE

UD

857

Local endemic

NE

UD

738

Regional or local endemic

NE

UD

196

Local endemic

NE

UD

2,093

Local endemic

NE

UD

890

Regional or local endemic

NE

UD

2,093

Regional or local endemic

NE

UD

2,093

Regional or local endemic

NE

UD

2,093

Regional or local endemic

NE

UD

2,093

Regional or local endemic

NE

UD

2,093

Regional or local endemic

NE

UD

2,093

Regional or local endemic

NE

UD

2,093

Regional or local endemic

NE

UD

2,093

Yes

788

67

Stick insects (Phasmatodea)“Antongiliinae” sp.

Stick insects (Phasmatodea)

Cirsia sp.

Stick insects (Phasmatodea)

Pseudodatames sp.

Stick insects (Phasmatodea)

Parectatosoma cf. cervinum

Stick insects (Phasmatodea)

Leiophasma sp.1

Stick insects (Phasmatodea)

Leiophasma sp.2

Stick insects (Phasmatodea)

Xerantherix sp.1

Stick insects (Phasmatodea)

Xerantherix sp.2

Stick insects (Phasmatodea)

Anareolatae sp 1

PlantsAcalypha vulneraria

PlantsAloe helenae Danguy

PlantsAsteropeia micraster Hallier f.

PlantsAstrotrichilia elliotii (Harms) Cheek

Plants

Beccariophoenix madagascariensis Jum. &H. Perrier

Plants

Croton trichotomus Geiseler

PlantsCynorkis elata Rolfe

PlantsDalbergia delphinensis Bosser & Rabevohitra.

PlantsDalbergia maritima R. Vig.

Plants

Dombeya mandenensis Arènes

Plants

Dombeya rariflora Arènes

PlantsDracaena bakeri Scott-Elliot

PlantsDypsis mananjarensis Jum & H.Perr

PlantsDypsis saintelucei Beentje

PlantsEligmocarpus cynometroides Capuron

PlantsEnterospermum sp 30

PlantsErythroxylum myrtoides Bojer

PlantsEulophia filifolia Bosser & Morat

PlantsEulophia palmicola H. Perr.

PlantsEuphorbia elliotii Leandri

PlantsEuphorbia francoisii Leandri

Non-endemic
species with nolike-for-like offset

Scientific name

Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM

Higher taxon 2

68

Yes

Yes

Yes

Global population
size (numberof individuals)- estimated for
endemic plants

NE

UD

2,093

Local endemic

NE

UD

2,093

Local endemic

NE

UD

2,093

Local endemic

NE

UD

2,093

Local endemic

NE

UD

2,093

Local endemic

NE

UD

2,093

Local endemic

NE

UD

2,093

Local endemic

NE

UD

2,093

Local endemic

NEUD<10,000

2,093

UD>10,000

890

CR D

Ha

n/a (nonendemic)

EN A3cdUDn/a (nonendemic)

3,658

UD

n/a (nonendemic)

3,887

Ha

n/a (nonendemic)

UD>10,000

1,628
2,093

Local endemic

Local nearendemic (Mahabo)
Local nearendemic (Mahabo)

CR B1+2cd
Local endemic
Local endemic

UD>10,000

EN A2cd,
B1+2bcdeHan/a (nonendemic)

EN A1cd+2cd

Ha

n/a (nonendemic)

Globalrange (hectares)

IUCN Red
List Status

Local endemic

Unit of measurement

Endemism status

Bespokeloss/gain
measurements
needed?

Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM

Local endemic

UD>10,000

2,093

Local endemic

UD1,035,636

890

Local endemic

UD>10,000

2,093

Local endemic

VU D1

UD

>10,000

2,093

Local endemic

CR D

UD

>10,000

1,355

2,545

100

<10,000

934

Local endemic

UD

Local endemic

UD

Local endemic

UD

Local nearendemic (Mahabo)

UD

Local endemic

Local endemic

Yes<10,000498

n/a (nonendemic)

1,615

UD

<10,000738EN
B1ab(iii)+2ab(iii)Han/a (nonendemic)

CR B1ab(iii,v)

UD>10,000

Yes

1,628

69

Plants

Euphorbia lophogona Lam.

PlantsFlagenium arboreum Wernham

PlantsGrewia flavicans Boivin ex Baill.

PlantsHyperacanthus mandenensis Rakotonas. & A.P.
Davis ined.

Plants

Leptolaena delphinensis G.E. Schatz & Lowry

Plants

Leptolaena pauciflora Baker

PlantsMalleastrum mandenense J.-F. Leroy

PlantsMeineckia websteri Brunel & J. Roux

PlantsMillettia taolanaroensis Du Puy & Labat

Plants

Myrtus madagascariensis H. Perrier

Plants

Ocotea brevipes Kosterm.

Plants

Oeceoclades longebracteata Bosser & Morat

PlantsPaederia taolagnarensis Razafim. & C.M. Taylor

PlantsPeponium poissonii Keraudren

PlantsPhyllanthus nummulariifolius subsp. vinanibeae
Brunel & J.P. Roux

PlantsPhyllarthron ilicifolium (Pers.) H. Perrier

PlantsPolyalthia madagascariensis Cavaco & Keraudren

PlantsPolyalthia pendula Capuron ex G.E. Schatz &Le Thomas

PlantsPseudocatha sp nov

PlantsPyrostria sp.nov

PlantsRinorea pauciflora var. pauciflora (Thouars.) Baill.

PlantsSenecio antandroi Scott-Elliot

PlantsSideroxylon beguei var. saboureaui Aubrev.

Plants

Suregada baronii (S. Moore) Croizat

PlantsTricalysia cryptocalyx Baker

PlantsVitex bracteata Scott-Elliot

PlantsVitex grandidiana W. Piep.

PlantsVitex tristis Scott-Elliot

Non-endemic
species with nolike-for-like offset

Scientific name

Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM

Higher taxon 2

70

Globalrange (hectares)

Global population
size (numberof individuals)- estimated for
endemic plants

VU B1ab(iii,v)

Bespokeloss/gain
measurements
needed?

IUCN Red
List Status

Local endemic

Unit of measurement

Endemism status

Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMMUD

>10,000

Local endemic

UD>10,000

890

Local endemic

UD

364

890

Local near-endemic (Mahabo)UDn/a (nonendemic)

4,458
2,093

Local endemic

2,093

CR A3cdUD>10,000

EN A3cdHan/a (nonendemic)

UD>10,000

2,983

70,909890

Local endemic
Local endemicUD
EN B1+2abc

Ha

Yes

n/a (nonendemic)

Local endemic

UD

Yes

727

Local endemic

UD

Yes

Local endemic

UD

Local endemic

UD

Local endemic

UD

Local endemic

13

2,545

31

>10,000

890>10,000

1,628

727

6

UD

602,909890

Local endemic

UD>10,000

2,983

Local endemic

UD<10,000

1,595

Local endemic

UD

26,545890

Local endemic

UD>10,000

934

Local endemic

UD>10,000

1,236

Local endemic

UD408,000

1,628

Local endemic

UD21,455890

Local endemic

UD>10,000

1,432

Local near-endemic (Mahabo)UDn/a (nonendemic)

1,761

Local endemic

UD>10,000

2,983

Local endemic

UD

20,364890

Local endemic

UD>10,000

2,093

Local endemic

UD>10,000

2,093

Yes

71

72

Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM

Appendix 5
Net impact in terms of Units of Global Distribution for High Priority
species: like-for-like species onlyGroup

Scientific name

Amphibians

Guibemantis (Mantidactylus)
bicalcaratus sp nov
Guibemantis (Mantidactylus) cf pulcher
sp nov
Guibemantis (Mantidactylus) punctatus
sp nov
Madecassophryne truebae
Stumpffia cf tridactyla ?sp nov
Pseudoxyrhopus kely
Phelsuma antanosy
Anas melleri
Ardea humbloti
Microcebus cf rufus ?sp nov
Zoosphaerium alluaudi
Zoosphaerium arborealis
Zoosphaerium sp. ‘Sainte-Lucé’
Sphaeromimus inexpectatus
Sphaeromimus splendidus
Riotintobolus mandensis
Riotintobolus minutus
Granitobolus sp. ‘black’
Alluviobolus laticlavius
Nesogalepsus sp.
“Tarachodinae” sp.
Apterocorypha sp.
Platycalymma sp.
Tarachomantis sp.
Tisma freyi
Tisma pauliani
Danuriella irregularis“Antongiliinae” sp.

Amphibians
Amphibians
Amphibians
Amphibians
ReptilesReptiles
Birds
Birds
Terrestrial mammals
Giant pill-millipedes
Giant pill-millipedes
Giant pill-millipedes
Giant pill-millipedes
Giant pill-millipedes
Spirobolid millipedes
Spirobolid millipedes
Spirobolid millipedes
Spirobolid millipedes
Mantises (Mantodea)
Mantises (Mantodea)
Mantises (Mantodea)
Mantises (Mantodea)
Mantises (Mantodea)
Mantises (Mantodea)
Mantises (Mantodea)
Mantises (Mantodea)
Stickinsects (Phasmatodea)
Stickinsects (Phasmatodea)
Stickinsects (Phasmatodea)
Stickinsects (Phasmatodea)

Global range(hectares)Net
impact(ha) excl.
restoration

1,595-476.2

2,093-329.02,093-329.036,373
2,093
11,660788
2,111,126
285,554
1,355
890
2,093
498
738
857
738
196
2,093
890
2,093
2,093
2,093
2,093
2,093
2,093
2,093
2,093
2,093

-333.9-329.0-796.4-40.4
25.8-142.3-186.7-384.3-329.0147.2-142.3-333.9-142.383.1-329.0-384.3-329.0-329.0-329.0-329.0-329.0-329.0-329.0-329.0-329.0Cirsia sp.

2,093-329.0Pseudodatames sp.

2,093-329.0

Parectatosoma cf. cervinum

2,093-329.0Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMMNet impact (UD) excl.
restoration

Net impact(ha) incl.
restoration

Net impact(UD) incl.
restoration

NPI
achieved?
1=Yes;
0=No

Is NPI achievable(given proposed
offsets &restoration
portfolio)?

-29.9

-26.2

-1.6

0

?

-15.7

121.0

5.8

1

Yes

-15.7

121.0

5.8

1

Yes

-0.9
-15.7
-6.8
-5.1
0.0
0.0
-13.8
-43.2
-15.7
29.6
-19.3
-39.0
-19.3
42.4
-15.7
-43.2
-15.7

-108.9121.0-346.4
-40.4
250.8
82.7
38.3
-159.3
121.0
147.2
82.7
-108.9
82.7
308.1
121.0
-159.3
121.0

-0.3
5.8
-3.0
-5.1
0.0
0.0
2.8
-17.9
5.8
29.6
11.2
-12.7
11.2
157.2
5.8
-17.9
5.8

0
1
0
0
1
1
1
0
1
1
1
0
1
1
1
0
1

?
Yes
?
?
Yes
Yes
Yes
?
Yes
Yes
Yes
?
Yes
Yes
Yes
?
Yes

-15.7
-15.7
-15.7
-15.7
-15.7
-15.7
-15.7
-15.7

121.0
121.0
121.0
121.0
121.0
121.0
121.0
121.0

5.8
5.8
5.8
5.8
5.8
5.8
5.8
5.8

1
1
1
1
1
1
1
1

Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes

-15.7

121.0

5.8

1

Yes

-15.7

121.0

5.8

1

Yes

-15.7

121.0

5.8

1

Yes

73

74

Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM
GroupScientific nameStickinsects (Phasmatodea)
Stickinsects (Phasmatodea)
Stickinsects (Phasmatodea)
Stickinsects (Phasmatodea)
Stickinsects (Phasmatodea)
PlantsPlantsPlantsPlantsPlantsPlants

Leiophasma sp.1

2,093

-329.0

Leiophasma sp.2

2,093

-329.0Xerantherix sp.1

2,093

-329.0Xerantherix sp.2

2,093

-329.0Anareolatae sp 1

2,093

-329.0890-384.3-384.3-384.3-160.9-128.288.0

PlantsPlantsPlantsPlantsPlantsPlantsPlantsPlantsPlantsPlantsAcalypha vulneraria
Aloe helenae Danguy
Aspidostemun parvifolium
Asteropeia micraster Hallier f.
Astrotrichilia elliotii (Harms) Cheek
Beccariophoenix madagascariensis Jum.
& H. Perrier
Cadia commersoniana
Capurodendron delphinensis
Claoxylon flavum
Coffea comersoniana
Croton trichotomus Geiseler
Cynorkis elata Rolfe
Dalbergia delphinensis Bosser& Rabevohitra.
Dalbergia maritima R. Vig.
Dombeya mandenensis Arènes
Dombeya rariflora Arènes
Dracaena bakeri Scott-Elliot
Dypsis mananjarensis Jum & H.Perr
Dypsis saintelucei Beentje
Eligmocarpus cynometroides Capuron
Enterospermum sp 30
Erythroxylum myrtoides Bojer
Eulophia filifolia Bosser & Morat

PlantsPlantsPlantsPlantsPlantsEulophia palmicola H. Perr.
Euphorbia elliotii Leandri
Euphorbia francoisii Leandri
Euphorbia lophogona Lam.
Flagenium arboreum Wernham

PlantsPlantsGrewia flavicans Boivin ex Baill.
Hyperacanthus mandenensis
Rakotonas. & A.P. Davis ined.

PlantsPlantsPlantsPlantsPlantsPlantsPlantsGlobal range(hectares)

890
3,658
3,887

890
890
890
2983
1,628
2,093

2,093
890
2,093
2,093
1,355
100
934
498
1,615
738

Net
impact(ha) excl.
restoration-384.3-384.3-384.3-713.3-526.6-329.0-142.3-329.0-329.0-384.3-329.0-329.0-186.7
-0.3
-59.2
147.2
153.7

1,628
2,093
890

-142.3-443.5-526.6-329.0-384.3890
4,458-384.3-545.2Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMMNet impact (UD) excl.
restoration

Net impact(ha) incl.
restoration

Net impact(UD) incl.
restoration

NPI
achieved?
1=Yes;
0=No

Is NPI achievable(given proposed
offsets &restoration
portfolio)?

-15.7

121.0

5.8

1

Yes

-15.7

121.0

5.8

1

Yes

-15.7

121.0

5.8

1

Yes

-15.7

121.0

5.8

1

Yes

-15.7

121.0

5.8

1

Yes

-43.2
n/a
-43.2
-4.4
-3.3
n/a

-159.3-159.3-159.3
289.1
546.8
538.0

-17.9
n/a
-17.9
7.9
14.1
n/a

0
0
0
1
1
1

Provisional yes
Provisional yes
Provisional yes
Yes
Yes
Yes

-43.2
-43.2
-43.2
-23.9
-32.3
-15.7
n/a

-159.3-159.3-159.3
-38.3
-76.6
121.0
82.7

-17.9
-17.9
-17.9
-1.3
-4.7
5.8
n/a

0
0
0
0
0
1
1

Provisional yes
Provisional yes
Provisional yes
Provisional yes
Provisional yes
Yes
Yes

n/a
-15.7
-43.2
-15.7
-15.7
-13.8
-0.3
-6.3
29.6
9.5

121.0
121.0
-159.3
121.0
121.0
38.3
163.7
390.8
147.2
212.3

n/a
5.8
-17.9
5.8
5.8
2.8
163.7
41.8
29.6
13.1

1
1
0
1
1
1
1
1
1
1

Yes
Yes
Provisional yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes

-19.3
n/a
-32.3
-15.7
-43.2
-43.2
-12.2

82.7

11.2
n/a
-4.7
5.8
-17.9
-17.9
2.9

1

Yes

231.5
-76.6
121.0
-159.3-159.3
129.8

1
0
1
0
0
1

Yes
Provisional yes
Yes
Provisional yes
Provisional yes
Yes

75

76

Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMM
GroupScientific namePlants

Leptolaena delphinensis G.E. Schatz& Lowry
Leptolaena pauciflora Baker
Malleastrum mandenense J.-F. Leroy
Meineckia websteri Brunel & J. Roux
Millettia taolanaroensis Du Puy & Labat
Myrtus madagascariensis H. Perrier
Ocotea brevipes Kosterm.
Oeceoclades longebracteata Bosser& MoratPaederia taolagnarensis Razafim. &C.M. Taylor
Peponium poissonii Keraudren
Phyllanthus nummulariifolius subsp.
vinanibeae Brunel & J.P. Roux

2,093

PlantsPlantsPhyllarthron ilicifolium (Pers.) H. Perrier
Polyalthia madagascariensis Cavaco& Keraudren

PlantsPlantsPlantsPlantsPlantsPlantsPlantsPlantsGlobal range(hectares)Net
impact(ha) excl.
restoration-329.0

13
31
890

840.2
-713.3-384.3
-62.5
3.5
13.2
-384.3

1,628-526.66890

2.6-384.3

2,983
1,595

-713.3-476.2

Polyalthia pendula Capuron ex G.E.
Schatz & Le Thomas890-384.3

PlantsPlantsPlantsPseudocatha sp nov
Pyrostria sp.nov
Rinorea pauciflora var. pauciflora(Thouars.) Baill.

934
1,236
1,628

-59.2
4.9
-526.6

PlantsPlantsSenecio antandroi Scott-Elliot
Sideroxylon beguei var.
saboureaui Aubrev.
Suregada baronii (S. Moore) Croizat
Tricalysia cryptocalyx Baker
Vitex bracteata Scott-Elliot
Vitex grandidiana W. Piep.
Vitex tristis Scott-Elliot

890
1,432

-384.3
88.0

1,761
2,983
890
2,093
2,093

251.2
-713.3-384.3-329.0-329.0

PlantsPlantsPlantsPlantsPlantsPlantsPlantsPlants2,983890

Forecasting the path towards a Net Positive Impact on biodiversity for Rio Tinto QMMNet impact (UD) excl.
restoration

Net impact(ha) incl.
restoration

Net impact(UD) incl.
restoration

NPI
achieved?
1=Yes;
0=No

Is NPI achievable(given proposed
offsets &restoration
portfolio)?

-15.7

121.0

5.8

1

Yes

n/a
-23.9
-43.2
n/a
28.2
42.4
-43.2

1290.2-38.3-159.3
0.0
29.9
86.5
-159.3

n/a
-1.3
-17.9
n/a
239.1
276.8
-17.9

1
0
0
1
1
1
0

Yes
Provisional yes
Provisional yes
Yes
Yes
Yes
Provisional yes

-32.3

-76.6

-4.7

0

Provisional yes

42.4
-43.2

17.3
-159.3

276.8
-17.9

1
0

Yes
Provisional yes

-23.9
-29.9

-38.3
-26.2

-1.3
-1.6

0
0

Provisional yes
Provisional yes-43.2-159.3-17.9

0Provisional yes

-6.3
0.4
-32.3

390.8
229.9
-76.6

41.8
18.6
-4.7

1
1
0

Yes
Yes
Provisional yes

-43.2
6.1

-159.3
538.0

-17.9
37.6

0
1

Provisional yes
Yes

14.3
-23.9
-43.2
-15.7
-15.7

476.2
-38.3
-159.3
121.0
121.0

27.0
-1.3
-17.9
5.8
5.8

1
0
0
1
1

Yes
Provisional yes
Provisional yes
Yes
Yes

77