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

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 2018. 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 (see also the accompanying datasheet). However, the underlying data-set (accompanying the technical documentation) also breaks this down by the commodity responsible for the impact, and the production countries/territories in which the impacts take place. The production countries/territories included align with those reported by the Food and Agriculture Organisation of the United Nations. For the two metrics relating to deforestation, coverage is restricted to FAO countries/territories in which tropical and subtropical forest is found. The breakdown of results for each impact can also be visualised through an external dashboard. The UK is included as one of the production countries within this breakdown (i.e. the indicator does not only focus on consumption of overseas production, but of total consumption wherever this is sourced from).

Key results

UK consumption of crop, cattle-related and timber commodities in 2018 (the latest year for which data are available) was associated with an estimated 35,977 hectares of agriculture-driven tropical deforestation worldwide (Figure A4i), a decrease of 51% since the time-series began in 2005. Between 2013 and 2018 there was a decrease of 15%. Between 2017 and 2018 (the latest year of data) there was a 0.2% decrease.

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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/territories and their commercial sectors (for example, oilseeds, cattle farming and paddy rice). 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 (for example, palm oil and soybeans, instead of just oilseeds) and of countries/territories 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/territory, which can be easily incorporated into the modelling framework. The modelling framework allows for an estimation of the country/territory 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 carbon dioxide (CO₂) emissions from deforestation, data from Chalmers University of Technology linking deforestation and commodity production (Pendrill et al. 2022) are used to proportionally attribute UK deforestation impacts based on the volumes of each commodity the UK consumes within each production country/territory (for example, if the Pendrill et al. (2022) dataset links x hectares of deforestation in that country/territory with the production of a particular commodity, and the UK consumes y% of that commodity produced in that country/territory, 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 likely be represented by a reduction in deforestation and CO₂ emissions from deforestation but would need to be interpreted alongside additional information (such as remaining forest area, deforestation per tonne of production, and understanding drivers behind the change) for a robust assessment.

To estimate biodiversity loss, two separate methods are utilised. The first method uses crop- and country/territory-specific characterisation factors (used as estimates of an environmental impact per unit of stressor (e.g. the land use per kg of production or the biodiversity loss per unit of pollutant)), 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 (the number of species predicted to be committed to extinction if current conditions continue 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 (a modelled global dataset of which crops are grown where) 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 consumption was estimated from the Water Footprint Network. To account for water scarcity in regions of production, blue (irrigated) water consumption was 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. Last year’s release fed into this indicator in the 2022 reporting for the Outcome Indicator Framework. 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. 2022), 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 CO₂ emissions, land use footprint (hectares per commodity), scarcity-weighted water footprint and material footprint (tonnes per commodity). Further graphs (for example 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/territories can be visualised using the associated dashboard.

 

Biodiversity loss

UK consumption of crop commodities in 2018 was responsible for a predicted regional species loss of approximately 63 species (Figure A4ii), a decrease of 31% since 2005. Between 2013 and 2018 there was an 8% decrease. Between 2017 and 2018 (the latest year) there was a 2% increase.

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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/territories 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/territories of origin.
• Only the country/territory 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/territory, 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 objective of this data set is to identify impacts that are geographically specific, so linking consumption to production location is key to understanding these impacts. An MRIO is therefore linked to additional data through a modelling framework to estimate consumption via production location. We use Exiobase for this, so that the financial flows (the picture of the whole economy) align with the UK Material and Carbon footprints. However, each of these is measuring something that does not vary with location (for example, estimates of carbon from consumption are based on factors applied to the production process, not the location of the process). Hence there are limits to how much the biodiversity indicator and the carbon and material indicators can be directly compared.
• Lags in the underlying data sets mean that data is only available in the current release up to 2018. 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 data reveal 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/territories where commodities are driving rapid impacts, the UK represents a small proportion of the total demand. However, the understanding data set allows the proportion of demand to be identified and the other consumers also contributing to the demand, hence providing better opportunities to work with producer countries and to work multi-laterally with other consumer countries to address sustainable production and reduce impacts.

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Additional notes

• 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).

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Goals and Targets

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Web links for further information

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), 368–378.

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

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

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. 

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.

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 3 August 2020.

Pendrill, F., Persson, U. Martin, Kastner, T., Wood, R. 2022. Deforestation risk embodied in production and consumption of agricultural and forestry commodities 2005-2018 (1.1) [Data set]. Zenodo. https://zenodo.org/record/5886600

Route2 Sustainability & Carbon Smart. 2019. Piloting Indicators for The Global Environmental Impacts of UK Consumption. Defra Report. 

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Downloads

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

Additional datasheets, including those breaking down the data by commodity and by country/territory of production, and those relevant to other consuming countries/territories assessed, can be accessed from the accompanying technical document and the associated dashboard, respectively.

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Last updated: 14 December 2022

Latest data: 2018

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.