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A4. Global biodiversity impacts of UK economic activity / sustainable consumption

Experimental Statistic - indicator under development. The UK biodiversity indicators project team would welcome feedback on the novel methods used in the development of this indicator. For example, does this new indicator measure something readers feel should be measured, and how well does it measure global impacts? As this is an experimental statistic it has not been assessed.

Type: State indicator

Revised 28 October 2021.

Introduction

This experimental statistic estimates the global environmental impacts of UK consumption of agricultural crop commodities* (and for some metrics additionally cattle-related** and timber commodities), between 2005 and 2017.*** Impacts considered include:

  • Tropical deforestation (headline result)
  • Biodiversity loss
  • Greenhouse gas (GHG) emissions related to tropical deforestation
  • Water consumption and scarcity-weighted water footprint
  • Cropland area harvested
  • Material consumption (tonnes of biomass production)

In this experimental statistic, results are shown for total UK consumption of agricultural commodities. However, the underlying data set also breaks this down by the commodity responsible for the impact, and the production countries in which the impacts take place (covering all production countries globally, except for the two metrics relating to deforestation for which data is only available on tropical and subtropical forest, thereby restricting geographic coverage). This breakdown of results can also be visualised through an external dashboard.

Key results

UK consumption of crop, cattle-related and timber commodities in 2017 was associated with an estimated 31,126 hectares of agriculture-driven tropical deforestation worldwide (Figure A4i), a decrease of 58% since the time-series began in 2005. Comparing the 2017 footprint with 2012 reveals a short-term decrease of 41% (five years is the standard short-term comparison for all UKBIs). For the latest year (2017) a decrease is observed (6% decrease).

Figure A4i. Area of tropical deforestation associated with UK consumption (hectares).

A bar chart showing area of tropical deforestation associated with UK consumption over a time-series from 2005 to 2017. The trend appears to be decreasing.

Notes:

  1. Estimates refer to tropical and subtropical deforestation as a result of crop, cattle-related, and timber commodities only.

Source: Calculated via application within the IOTA (Input Output Trade Analysis) framework (Croft et al., 2018) using data from Exiobase; the Food and Agriculture Organisation of the United Nations; and Pendrill et al., 2019a,b, 2020.

Results for other impact metrics are presented within the Background section, below.

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Indicator description

The full methodology for this indicator can be found in the technical documentation. This indicator is being published as an experimental statistic in order to facilitate user involvement in its development – information on how the underlying data have been obtained and how the indicator has been prepared is available in the technical documentation. We would welcome any feedback, particularly on the usefulness and value of these statistics, via enviro.statistics@defra.gov.uk.

The indicator is based on MRIO (multi regional input-output) modelling, which is used to model global trade flows representing the monetary inputs and outputs across different countries and their commercial sectors (e.g. oilseeds, cattle farming, paddy rice, etc.). The MRIO data used for this indicator were from Exiobase. The Exiobase dataset has been selected to increase alignment and consistency with other UK footprint accounts (the UK GHG and Material Footprints) and due to its considerable temporal coverage. As well as this, it allows for data to be broken down into a high number of different sectors compared to other MRIO datasets (although country data are more aggregated).

The MRIO data is hybridised with physical data (tonnes of each commodity) from the Food and Agricultural Organisation, using the Stockholm Environment Institute’s IOTA (Input Output Trade Analysis) model (Croft et al., 2018). This step allows for a higher resolution breakdown of commodities (e.g. palm oil, soybeans, etc., instead of just oilseeds) and of countries of origin than MRIO data would alone, and allows trade – in physical units – at a commodity level to also be included before these data are integrated into the MRIO framework. This gives the results at a greater level of product-specificity than a standalone MRIO-based account. The Food and Agriculture Organisation Statistics were chosen for use because they are a comprehensive set of global production statistics, collected from official national statistics of each country, which can be easily incorporated into the modelling framework. The modelling framework allows for an estimation of the country of origin of a commodity, accounting for cases where commodities are embedded within other products as an ingredient or input, and cases where commodities are re-exported through multiple countries before the point of consumption in the UK.

To determine deforestation rates and CO2 emissions from deforestation, data from Chalmers University of Technology linking deforestation and commodity production (Pendrill et al., 2020) are used to proportionally attribute UK deforestation impacts based on the volumes of each commodity the UK consumes within each production country (for example, if the Pendrill et al. (2020) dataset links x hectares of deforestation in that country with the production of a particular commodity, and the UK consumes y % of that commodity produced in that country, then it is assumed that the UK is responsible for y % of those x hectares. This deforestation dataset was selected as it provides data on deforestation in tropical and sub-tropical regions and its associated agricultural commodity drivers, with comprehensive coverage. Positive change would be represented by a reduction in deforestation and CO2 emissions from deforestation.

To estimate biodiversity loss, two separate methods are utilised. The first method uses crop- and country-specific characterisation factors****, provided by Chaudhary and Kastner (2016), which are used to estimate the impact per tonne of production for 152 crops/crop groups in 171 territories. This gives an estimate of regional species loss (species loss per ecoregion). Positive change would be represented by a decrease in predicted species loss. The other method to estimate biodiversity loss (providing separate results from the first method) uses MAPSPAM data alongside species richness information from the International Union for the Conservation of Nature (IUCN) and BirdLife International to estimate ‘species richness-weighted extent of crop production’. This represents the hectares of crop production scaled by the number of species present in that hectare, and therefore where there is overlap between production and areas of biodiversity importance. Positive change would be represented by a decrease in ‘species richness weighted extent of crop production’ embedded in consumption.

Water footprints were estimated from the Water Footprint Network. To account for water scarcity in regions of production, blue (irrigated) water consumption was then scaled by water availability in a region after human and aquatic ecosystem demand has been met, using conversion factors sourced from Boulay et al. (2018). Positive change would be represented by a reduction in scarcity-weighted blue water use.

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Relevance

The government’s 25 Year Environment Plan has set out a series of indicators (the Outcome Indicator Framework) to track progress. One of these indicators (K1) relates to the “overseas environmental impacts of UK consumption of key commodities” and is designed to measure the impacts associated with UK consumption of key commodities. It is planned that this experimental statistic will contribute to this aim and feed into Outcome Indicator Reporting for 2022. The full list of indicators in development can be found in the 25 Year Environment Plan Outcome Indicator Framework.

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Background

This indicator was calculated by the Stockholm Environment Institute under a project managed by the Joint Nature Conservation Committee (JNCC) and contracted by Defra for developing an indicator for the 25 Year Environment Plan. It builds on data from a variety of sources, including the Norwegian University of Science and Technology’s (NTNU) Exiobase trade model, Chalmers University of Technology (Pendrill et al., 2020), the Food and Agriculture Organisation of the United Nations, the Water Footprint Network, WULCA (Boulay et al., 2018), ETH Zurich and the Institute of Social Ecology Vienna (Chaudhary and Kastner, 2016), BirdLife International and the IUCN. It also builds on previous work including a proof of concept study which recommended MRIO as the approach to use for this indicator (Route2 and Carbon Smart) and a separate study investigating an alternative approach which was not recommended to be taken forward (Harris et al., 2019). JNCC has also produced an entry-level guide introducing people to the area of sustainable production and consumption more generally, which may be of interest to anyone wishing to learn more (Hawker et al., 2020).

In addition to the headline metric presented in the key results section (tropical deforestation), footprints were also calculated for biodiversity, deforestation related GHG emissions, land use footprint, scarcity-weighted water footprint and material footprint. Further graphs (for example showing an alternative biodiversity metric and showing the intensity of each footprint rather than the magnitude) can be found in Annex 1 of the technical documentation. Additional breakdowns of commodities and producing countries can be visualised using the associated dashboard.

Biodiversity loss

UK consumption of crop commodities in 2017 was responsible for a predicted regional species loss of approximately 61 species (Figure A4ii), a decrease of 32% since 2005. Comparing the 2017 footprint with 2012 reveals a 14% decrease. For the latest year (2017) a minor increase is observed (2% increase).

Figure A4ii. Regional species loss associated with UK consumption (regional numbers of species lost).

A bar chart showing regional species loss associated with UK consumption over a time-series from 2005 to 2017. The trend appears to be slightly decreasing.

Notes:

  1. Estimates refer to crop commodities only.

Source: Calculated via application within the IOTA (Input Output Trade Analysis) framework (Croft et al., 2018) using data from Exiobase; the Food and Agriculture Organisation of the United Nations; and Chaudhary and Kastner (2016).

UK consumption of crop commodities in 2017 was responsible for an estimated 4.96 billion species richness weighted hectares of land use worldwide (Figure A4iii), a long-term decrease of 19% since 2005. Comparing the 2017 footprint with 2012 reveals a short-term decrease of 11%. For the latest year (2017) a minor increase is observed (4%). Species richness-weighted hectares represent the hectares of crop production scaled by the number of species present in that hectare, and therefore where there is overlap between production and areas of biodiversity importance.

Figure A4iii. Species richness weighted crop area associated with UK consumption.

A bar chart showing species richness weighted crop area associated with UK consumption over a time-series from 2005 to 2017. The trend appears to be slightly decreasing.

Notes:

  1. Estimates refer to crop commodities only.

Source: Calculated via application within the IOTA (Input Output Trade Analysis) framework (Croft et al., 2018) using data from Exiobase; the Food and Agriculture Organisation of the United Nations; MAPSPAM; Birdlife International; and the IUCN.

Greenhouse gas (GHG) emissions related to tropical deforestation

UK consumption of crop, cattle-related and timber commodities in 2017 was responsible for an estimated 16 million tonnes of CO2 emissions linked to tropical and sub-tropical deforestation worldwide (Figure A4iv), inclusive of peat drainage, a long-term decrease of 60% since 2005. Comparing the 2017 footprint with 2012 reveals a short-term decrease of 39%. For the latest year (2017) a decrease is observed (6% decrease).

Figure A4iv. Tropical deforestation emissions (including peat drainage) associated with UK consumption (million tonnes carbon dioxide).

A bar chart showing tropical deforestation emissions (including peat drainage) associated with UK consumption (tonnes of carbon dioxide) over a time-series from 2005 to 2017. The trend appears to be decreasing.

Notes:

  1. Estimates refer to GHG emissions from tropical and subtropical deforestation as a result of crop, cattle related and timber commodities only.

Source: Calculated via application within the IOTA (Input Output Trade Analysis) framework (Croft et al., 2018) using data from Exiobase; the Food and Agriculture Organisation of the United Nations; and Pendrill et al., 2019a,b, 2020.

Water consumption and scarcity-weighted water footprint

UK consumption of crop commodities in 2017 was responsible for an estimated 366.94 billion cubic-metres of scarcity-weighted blue water use worldwide (Figure A4v), a long-term decrease of 48% since 2005. Comparing the 2017 footprint with 2012 reveals a short-term decrease of 27%. For the latest year (2017), a 1% increase is observed. Scarcity-weighted blue water use scales the blue water footprint (surface and groundwater consumed as a result of production) according to water availability in a region after human and aquatic ecosystem demands have been met.

Figure A4v. Scarcity-weighted blue water use associated with UK consumption (billion cubic metres).

A bar chart showing scarcity-weighted blue water use associated with UK consumption over a time-series from 2005 to 2017. The trend appears to be decreasing.

Notes:

  1. Estimates refer to crop commodities only.

Source: Calculated via application within the IOTA (Input Output Trade Analysis) framework (Croft et al., 2018) using data from Exiobase; the Food and Agriculture Organisation of the United Nations; the Water Footprint Network; and Boulay et al., 2018.

Cropland area harvested

UK consumption of crop commodities in 2017 was associated with an estimated total land use footprint of 14.96 million hectares – a long-term decrease of 28% since 2005 (Figure A4vi). Comparing the 2017 footprint with 2012 reveals a short-term decrease of 18%. For the latest year (2017), a 1% increase is observed.

Figure A4vi. Cropland area harvested associated with UK consumption (million hectares).

A bar chart showing cropland area harvested associated with UK consumption over a time-series from 2005 to 2017. The trend appears to be decreasing.

Notes:

  1. Estimates refer to crop commodities only.

Source: Calculated via application within the IOTA (Input Output Trade Analysis) framework (Croft et al., 2018) using data from Exiobase; and the Food and Agriculture Organisation of the United Nations.

Material consumption (tonnes of biomass production)

UK consumption of crop, cattle-related, and timber commodities in 2017 was responsible for an estimated 121.63 million tonnes of material production worldwide (Figure A4vii), a long-term decrease of 23% since 2005. Comparing the 2017 footprint with 2012 reveals no short-term change (2% decrease). For the latest year (2017) a 1% increase is observed.

Figure A4vii. Crop production (biomass) associated with UK consumption (million tonnes).

A bar chart showing crop production (biomass) associated with UK consumption over a time-series from 2005 to 2017. The trend appears to be decreasing.

Notes:

  1. Estimates refer to crop commodities only.

Source: Calculated via application within the IOTA (Input Output Trade Analysis) framework (Croft et al., 2018) using data from Exiobase; and the Food and Agriculture Organisation of the United Nations.

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Caveats, limitations and uncertainties

For accurate interpretation of the results presented within this indicator, it is necessary to understand the following caveats:

  • Data tracing all commodities exactly back to their countries of origin are not publicly available. Whilst based on empirical statistics, the outputs produced by this indicator are derived from modelling so should be considered as estimates rather than exact countries of origin.
  • Only the country of origin, and not the exact location of origin, can be obtained from the current version of the indicator as only national scale data were used. This means impacts are based on average production practices per country, not the actual impacts at the exact location the product came from. This could be improved by using sub-national data (where available) in subsequent iterations of the indicator.
  • Data linking impacts to trade are compiled at national level meaning any action by the UK in specific regions will be 'averaged' across the full global supply chain. Therefore, it will be hard to differentiate UK action from the actions of other consumer nations. The indicator will be more responsive to multi-national action than to UK action specifically.
  • The data presented here are based on a fundamentally different approach to the UK Carbon Footprint or the UK Material Footprint. The results presented here are therefore not comparable to the existing Carbon and Material Footprints and should be viewed separately. This work, the UK Carbon Footprint and the UK Material Footprint are all based on the same underlying economic data (Exiobase). However, other underlying data sources differ in a way that means the Carbon and Material Footprints cannot be broken down by commodity, which is what this work aims to do (see the associated dashboard). This work therefore offers a complementary insight to better understand the impacts of UK consumption. See the technical document for further information.
  • Data lags in the underlying data sets mean that data is only available in the current release up to 2017. Care should also be taken in analysing trends over time which can reflect complex changes in production volume, trade distributions, estimated inter-sectoral demands and final consumption expenditure.
  • Use of different MRIOs as the underlying dataset (for example, GTAP rather than Exiobase) could lead to differences in results, due to factors including geographic and sectoral resolution, temporal coverage and lag.
  • The presence of oil palm and soy as key sources of UK deforestation risk is common to other assessments, but the preliminary data reveals UK linkages to other supply chains (such as beans, cassava, paddy rice) that are not often considered as 'deforestation risk' commodities in other publications. These supply chains warrant further investigation to understand which sectors of consumption link to these estimated impacts.

In many of the countries where soft commodities are driving rapid impacts, the UK represents a small proportion of the total demand. However, understanding and reducing UK impacts can help show international leadership and set an example for other countries to follow. It also provides better opportunities to work with producer countries and to work multi-laterally with other consumer countries.

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Goals and Targets

Aichi Targets for which this is a primary indicator

Strategic Goal A. Address the underlying causes of biodiversity loss by mainstreaming biodiversity across government and society.

Aichi Target 4 icon

Target 4: By 2020, at the latest, Governments, business and stakeholders at all levels have taken steps to achieve or have implemented plans for sustainable production and consumption and have kept the impacts of use of natural resources well within safe ecological limits.

Aichi Targets for which this is a relevant indicator

None

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Reference Title
BirdLife International Bird species distribution maps of the world Version 2020.1
Defra 'A Green Future: Our 25 Year Plan to Improve the Environment' 
Defra Official Statistics UK Carbon Footprint
Defra / SEI / JNCC / Trade Hub / Trase Commodity footprints dashboard
Exiobase (NTNU University of Science and Technology) Home page
Food and Agriculture Organisation of the United Nations Data home page
Office for National Statistics Official Statistics UK Material Footprint
Water Footprint Network Product water footprint statistics
WULCA Download AWARE Factors

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References

Boulay, A.M., Bare, J., Benini, L., Berger, M., Lathuillière, M.J., Manzardo, A., Margni, M., Motoshita, M., Núñez, M., Pastor, A.V. and Ridoutt, B. 2018. The WULCA consensus characterization model for water scarcity footprints: assessing impacts of water consumption based on available water remaining (AWARE). The International Journal of Life Cycle Assessment, 23(2), pp.368-378.

Chaudhary, A. & Brooks, T. 2018. Land Use Intensity-Specific Global Characterization Factors to Assess Product Biodiversity Footprints, Environmental Science & Technology, 52(9), pp. 5094-5104.

Chaudhary, A. & Kastner, T. 2016. Land use biodiversity impacts embodied in international food trade, Global Environmental Change, 38, pp.195-204.

Croft S.A., West C.D. & Green J.M. 2018. Capturing the heterogeneity of sub-national production in global trade flows. Journal of Cleaner Production, 203, pp. 1106–1118. https://doi.org/10.1016/j.jclepro.2018.08.267.

Croft, S., West, C., Harris, M., Otley, A. and Way, L. 2021. Towards indicators of the global environmental impacts of UK consumption: Embedded Deforestation. JNCC Report No. 681, JNCC, Peterborough, ISSN 0963-9091 Available at: https://hub.jncc.gov.uk/assets/709e0304-0460-4f83-9dcd-3fb490f5e676

Harris, M., Hawker, J., Croft, S., Smith, M., Way, L., Williams, J., Wilkinson, S., Hobbs, E., Green, J., West, C. and Mortimer, D. 2019. Is the Proportion of Imports Certified as Being from Sustainable Sources an Effective Indicator of UK Environmental Impact Overseas? Contracted Report to Defra. Available at: http://randd.defra.gov.uk/Document.aspx?Document=15026_2018-19-TowardsIndicatorsofEnvironmentalSustainability.pdf

Hawker, J., Smith, M., Way, L., Harris, M., Donovan, D., Wright, E. and Wilkinson, S. 2020. The LET (Linking Environment to Trade) Guide. JNCC, Peterborough. Available at: https://hub.jncc.gov.uk/assets/daa8e792-a36e-436b-98d7-e2f38e860650

International Union for the Conservation of Nature (IUCN) .2020. The IUCN Red List of Threatened Species. Version 2020.1. Available at: https://www.iucnredlist.org. Downloaded on 3rd August 2020.

Pendrill, F., Persson, U.M., Godar, J. and Kastner, T. 2019a. Deforestation displaced: trade in forest-risk commodities and the prospects for a global forest transition. Environmental Research Letters, 14(5), p.055003.

Pendrill, F., Persson, U.M., Godar, J., Kastner, T., Moran, D., Schmidt, S. and Wood, R. 2019b. Agricultural and forestry trade drives large share of tropical deforestation emissions. Global Environmental Change, 56, pp.1-10.

Pendrill, Florence, Persson, U. Martin, & Kastner, Thomas. 2020. Deforestation risk embodied in production and consumption of agricultural and forestry commodities 2005-2017 (1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.4250532

Route2 Sustainability & Carbon Smart. 2019. Piloting Indicators for The Global Environmental Impacts of UK Consumption. Defra Report. Available at: http://randd.defra.gov.uk/Document.aspx?Document=15028_2018-19-PilotingIndicatorsfortheGlobalEnvironmentalImpactsofUKConsumption.pdf.

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Downloads

Download the summary Datasheets and Technical background document from JNCC's Resource Hub.

Additional datasheets, including those breaking down the data by commodity and by country of production, and those relevant to other consuming countries assessed, can be downloaded from a separate Resource Hub page and the associated dashboard, respectively.

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Last updated: 28 October 2021

Latest data: 2017

 

This content is available on request as a pdf in non-accessible format. If you wish for a copy please go to the enquiries page.

 

*All crops with data recorded in FAOSTAT are included (see technical document for further detail and exceptions).

**Cattle-related commodities’ refer to meat, offal, fats and hides from cattle and buffalo as reported within FAOSTAT, and aligning with data usages within Pendril et al., 2019. Note that impacts attributed to cattle result from land used for pasture, whilst impacts from commodities used as feed are presented as impacts associated with the raw commodity (e.g. soy).

***Underlying data sets currently restrict analysis to the years 2005 to 2017. See the technical report for further information about planned data updates for each underlying data set.

****Characterisation factors are used as estimates of an environmental impact per unit of stressor (for example, the land use per kg of production or the biodiversity loss per unit of pollutant).

Categories:

UK Biodiversity Indicators 2021

Published: .

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