Global Impacts:
Measuring the Impact of UK Consumption on
Biodiversity Overseas
Chris West, Elena Dawkins, Simon Croft,
David Raffaelli, William Sheate
6th December 2012
Outline of Global Impacts Session
Time
Activity
11.15
Presentation: An introduction to preliminary work on developing a
potential Global Impacts methodology
11.30
Questions related to the presentation
11.45
Discussion: Limitations and Assumptions of the methodology
12.25
Discussion: Moving from prototype to indicator
12.55
Discussion: Targets
13.15?
Close, and lunch
Defra Project Background
• Project Duration: Nov 2011 – March 2013
• The Issue
–
–
–
–
Growing consumption, increasing reliance on imports
Complex supply chains
Indirect and direct impacts of consumption
Overseas biodiversity impacts
• Project Aim
– provide a database-driven methodology for linking UK imports to
geographically-defined impacts on biodiversity
Existing studies
Study
Products covered Method Applied
Biodiversity Indicator(s)
Trends in EU virtual land
flows: EU agricultural
land use through
international trade, Van
Sleen (2009)
Wheat case study Material flow analysis with a multi-criteria
assessment of impacts
•
•
•
Genetic diversity
Species diversity
Overall environmental
utility
•
Relative species
richness
Relative species
richness of original
species
Ecoregion land area
apportioned by import
demand
Dutch Trade and
Soya, palm oil
Biodiversity, Kamphuis et and tropical
al. (2011)
timber products
Trade flow analysis, combined with land
area production data.
•
Global Biodiversity
Database, Scott Wilson
(2007)
Soya, lumber
Trade flow analysis. Identification of
palm oil, cotton, ecoregions (WWF) in the country of
shrimps and wine production, threats to ecoregion.
•
The global biodiversity
footprint of UK biofuel
consumption, JNCC
(2009)
Biofuels
•
Trade data; source countries and crops,
estimate land use requirement and
identify the ecosystems under pressure
Land use matched to
region
Existing studies
Study
The global land use
impact of the United
Kingdom’s biomass
consumption, JNCC
(2011) Part I
UK National Ecosystem
Assessment Technical
Report. Chapter 21: UK
Dependence on non-UK
Ecosystem Services,
UNEP-WCMC (2011)
Lenzen et al. (2012)
MRIO and biodiversity
threats
Products
covered
Biomass
Method Applied
Biodiversity Indicator
Material flow data (e.g. domestic
material consumption) and biomass
import data . Land required to supply
products, with crop yields and crop
water requirements.
•
Biomass
Import data from converted to land area •
requirements using crop yields and
matched to the Biogeographical Realms .
MFA used to track the history of biomass
consumption in the UK.
Those that
‘threaten’
species
Multi-regional input-output model linked •
to listed ‘threats’ within the IUCN Red
List.
Matched land area
requirements of
imports to
Biogeographical
realms, biomes and
specific countries
Matched land area
requirements of
imports to
Biogeographical
realms, biomes and
specific countries
IUCN Red List Species
under threat
Defra Project Background
• Our approach:
– Understanding consumption:
• Measuring trade and supply chains
• Linking production abroad with imports to the UK
– Understanding potential biodiversity impacts:
• Selecting indicators of biodiversity
• Linking indicators to production abroad
Understanding Trade and Consumption
Trade information:
•
Import, export data exists from HMRC, FAO, UN, Eurostat, OECD...
–
–
Physical
Financial
•
Input-Output (IO) tables map interactions between industry throughout the whole
economy. They are necessary to measure indirect/embedded materials within
products. They capture the full supply chains of goods.
•
We selected GTAP data based on the criteria:
–
–
–
–
Availability (current and likely future)
Number of regions covered vs no. of sectors covered
Regularly updated
New version just released
MRIO data
GTAP/MRIO approach:
• Financial flows between 129 countries (multi-regional), across
57 sectors.
• Interactions between economic sectors (all inputs and
outputs of whole economy) mapped out in tables (inputoutput).
• Limitations:
– Limited sector resolution
– Released every 4 years (latest version has 2004 and 2007 data)
– Financial flows not physical quantities
Linking to detailed production data
• FAO:
– Agriculture stats: yield, area harvested, production and trade flows for 236
Countries and over 600 products
– ForeSTAT: production, import, export for wood product groups
– FishSTAT: total capture, aquaculture, commodities, production and trade
• This is more detailed than the financial data, but lacks information
about full supply chains.
• We need a method to link detailed product data to the full supplychain in input-output models…
Diagram of MRIO physical model adapted from: Brad R. Ewing, Troy R. Hawkins, Thomas O. Wiedmann, Alessandro Galli, A. Ertug Ercin, Jan
Weinzettel, Kjartan Steen-Olsen, Integrating ecological and water footprint accounting in a multi-regional input–output framework,
Ecological Indicators, Volume 23, December 2012, http://www.sciencedirect.com/science/article/pii/S1470160X12000714
Linking production data to MRIO
• Method 1: Allocate physical production of each product and country
within FAO to an equivalent producing sector and region within GTAP
– Relies solely on financial MRIO data to model trade in commodities
between sectors
• Method 2: Allocate physical production to importing regions in GTAP
– Hybrid approach; requires harmonisation of datasets and method for
dealing with re-exports in the physical data
• Method 3: Allocate physical production to regions and sectors in GTAP
– Retains product detail to greatest extent but requires seed and feed data
FAO Trade Data
DEFRA MODEL
UK Demand for products with
‘embedded’ soybeans
Exports of soybeans to UK
Country
Brazil
United States of America
Ireland
Belgium
Ukraine
Netherlands
Italy
Argentina
China
What it tells you:
•
Exports of raw
materials/commodities to a
country.
What it doesn’t tell you:
•
Where the final/processed
products end up, and whether
they are re-exported
•
Any ‘hidden’ impacts
embedded in products e.g. soya
embedded in meat products
Tonnes
619000
27908
19539
14560
10418
10097
6806
5063
4485
UK
Demand
for
products
from:
UK
UK
UK
UK
UK
China
Brazil
Total embedded
Brazilian land area
Product
used for soybean
demanded:
production
Food products nec
184,555
Trade
34,198
Beverages and
tobacco products
29,981
Public
Administration
Defense Education
Health
29,697
Vegetable oils and
fats
22,500
Wearing apparel
10,715
Vegetable oils and
fats
10,146
What it tells you:
•
Impacts (land associated with soybean
production in this case) associated with
demand for any products (including
‘hidden’ land embedded in products).
Linking production quantity to impact
• Environmental ‘extensions’ can be added to the production
data:
– From FAO we have details on yields by country and can therefore
calculate land requirements
– We also have data on water consumption and pollution (in the form of
form of green, blue, and grey water
– Some fertiliser data is available
– IUCN RedList, Important Bird Area databases contain information
about species threats
– Other regional information about endemism, habitat types etc.
• These extensions can be viewed in isolation or potentially
combined.
Physical production
linked to environmental
drivers of biodiversity
loss and indicators
Sectors linked to physical
production and land use
data – sector level (e.g. fruit
and veg, not mangos)
Method Summary
• Defra model enables a detailed look at products and land use/ water/
biodiversity impacts etc. of those products.
• Benefits of Defra Model:
– Retains product-level detail of FAO. Combines FAO physical data with MRIO financial flow
data.
– Calculates all of the ‘hidden’/embedded impacts in products that might be missed in just
direct import/export data of the actual commodity (e.g. captures soya imported via meat
products).
– Assesses impacts associated with the final consumption of products, compared to FAO
trade data where commodities are likely to go into industry (rather than final consumers)
and be processed and either consumed or re-exported elsewhere.
• Defra model:
– Still under development, builds on work from OPEN-EU project, adds additional datasets
and indicators for anything associated with production of commodities.
– Initial results are starting to become available for UK demand….
Case Studies and Knowledge Base
• The Hybrid-MRIO model still only contains information to
country-level.
• To validate the model, and provide further regionally-specific
information we are conducting case studies on Brazilian
soybeans and shrimps (probably from Asia).
• It is intended that this approach can be used to drill-down into
potential impact ‘hotspots’ inferred in the model.
Preliminary results
• The following results are (very!) preliminary and therefore
only for illustration:
– Based on Method 1 (allocating products from FAO to producing
sectors in GTAP).
– Available for only a handful of commodities at present.
– Some outstanding data issues (e.g. with China data in FAO).
– Biodiversity extensions are undergoing further work.
Soybean consumption by the UK (2007)
‘Raw’ data from FAO shows
direct imports of soybeans into
the UK by exporting country:
Country
Brazil
United States of America
Ireland
Belgium
Ukraine
Netherlands
Italy
Argentina
China
Tonnes
619000
27908
19539
14560
10418
10097
6806
5063
4485
Running the data through the
hybrid-MRIO model gives us
this:
Brazil
Argentina
United States of America
Paraguay
India
Canada
Ukraine
Italy
Uruguay
Bolivia
1424584
1120954
535523
117199
44119
39477
19371
10307
9966
5976
Soybean consumption by the UK (2007)
We can also look at how
demand for different sectors
contributes to this production:
Demand from Sector
Source Country
Tonnes
Food products nec
Brazil
688573
Food products nec
Argentina
521460
Food products nec
United States of
America
Brazil
190930
Beverages and tobacco
products
Brazil
106558
Trade
Brazil
106072
Vegetable oils and fats
Argentina
Vegetable oils and fats
115469
89162
Public Administration
Brazil
Defense Education Health
85703
Trade
82316
Argentina
Beyond Production: Top Ten: Seed cotton consumption by the UK (2007)
Land
Production Production Land
Use
(tonnes)
Rank Use (ha) Rank
Country
We
can also look at how
demand
for390,124
different sectors
India
1
266,967
contributes to this production:
Pakistan
214,580
United States of
America
164,800
Blue Water
(m3)
Blue
Water
Rank
Grey
Water
(m3)
Grey
Water
Rank
1
728,122,607
1
376552408
1
121
0
Redlist IBAs
Species (A1)
2
115,439
2
462,589,208
2
152503126
2
17
0
3
68,860
4
148,839,426
5
35181297
3
56
2
Uzbekistan
136,869
4
53,359
5
457,217,578
3
1137
52
11
33
Turkmenistan
34,983
5
23,672
7
166,933,847
4
3861
48
8
26
Brazil
31,314
6
8,578
12
557,141
29
18893396
4
99
19
Greece
16,153
7
5,637
13
19,151,158
11
0
116
12
0
Tajikistan
United Republic
of Tanzania
15,462
8
9,293
10
59,604,994
6
398738
18
9
18
13,338
9
29,911
6
5,303,360
15
876390
10
120
15
Australia
12,623
10
2,630
27
23,057,790
9
401987
17
39
64
Beyond Production: Seed cotton consumption by the UK
(2007)
Country
Land Use (ha) Redlist Species RedList 'Weighting'Old Rank New Rank
India
266,967
121
32,303,044
1
1
Pakistan
115,439
17
1,962,457
2
4
United States of America
68,860
56
3,856,147
3
2
Uzbekistan
53,359
11
586,949
4
6
United Republic of Tanzania
29,911
120
3,589,376
5
3
Turkmenistan
23,672
8
189,377
6
7
Tajikistan
9,293
9
83,635
7
9
Brazil
8,578
99
849,232
8
5
Greece
5,637
12
67,640
9
10
Australia
2,630
39
102,577
10
8
Related ongoing and future work
• By SEI:
– JNCC/SNH project on material flow analysis for Scottish Biomass and
links to biodiversity impacts
– WWF European Policy Office: EU Policy and consumption-related
impacts on WWF Priority Areas for conservation (feasibility study)
• By others:
– Manfred Lenzen’s group in Australia
– WWF China
Thank you!