Can we avoid adding pressure (due to the food we eat) on the genetic and functional diversity of species on our planet?
The following section describe the metrics on Biodiversity conversation that were embedded in Deliverable 6.3.
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Performance metric 3: Biodiversity conservation
Food supply chains might affect biodiversity both directly through reduction of farmland biodiversity and marine biological diversity, and indirectly through land use change, land fragmentation, and pollution processes; pressures are often larger outside of the EU than within, masked by international supply chains (Lenzen et al. 2012). In SUSFANS, we assess biodiversity conservation with three indicators focusing on general terrestrial (non-farmland) biodiversity, farmland biodiversity, and marine biodiversity.
Reduction of the contribution of the agrifood chain to loss of Mean Species Abundance (MSA)
Description: Terrestrial biodiversity is affected through land use and pollution effects. Land use effects include (historic) land use changes, land fragmentation with consequently truncation of migratory routes (Reid et al. 2010). Pollution effect can be direct through deposition of nutrients affecting soil acidity and (micro)organism composition (Dise et al. 2011; Stevens et al. 2010), or indirectly via climate change (Alkemade et al. 2009).
The Mean Species Abundance (MSA) represents an index of the naturalness of an ecosystem. This indicator has been linked to causes of loss of species abundance in the GLOBIO-model (Alkemade et al. 2009; Kram & Stehfest 2012; van Vuuren et al. 2015) and attributes 64% of MSA loss to land conversions, 30% to land
fragmentation and 5% to pressures from atmospheric deposition and climate change (Leip et al. 2015b).
Land use is therefore the single most important indicator for terrestrial biodiversity. It is measured in total area required for the food supply chain. It should be calculated based on an LCA thus considering also land use embedded in imported (feed) products, multiplied with the total consumption of products. This aggregate indicator, however, is of importance beyond the relevance for biodiversity: low land requirements for agricultural production alleviates the pressure on land and reduces land competition. For example, according to current scenarios for the targets of 2 or 1.5 degree, afforestation and biomass production is needed, and the necessary area could go to 800 Mha by 2100 or higher (Popp et al. 2017); agriculture will need to contribute to making this possible.
Policy vision: No further increase for land used for agricultural production. In contrast to most of the other aggregated indicators, this is an absolute policy vision which needs to consider the number of persons.
Policy targets: Same as policy goal.
Aggregated variables: Land use [ha]
Agricultural land use diversity
Description: Agricultural land use diversity could be approximated by the concept of ‘Biodiversity-Friendly Farming Practices’ (BFP) which captures the causality between certain types of farming activity and their potential impacts on biodiversity. This is closely linked to the High Nature Value (HNV) farmland and is therefore a key indicator for the assessment of the impact of policy interventions with respect to the preservation and enhancement of biodiversity, habitats and ecosystems dependent on agriculture and of traditional rural landscapes. Terres et al. (2012) define BFP as a composite indicator with four sub-indicators (arable crops: Shannon index and N input index, grassland: stocking density index, permanent crops: N input, olive groves: surface).
The BFP indicator is calculated at high spatial resolution, such as the disaggregated results from the CAPRI model (Leip et al. 2015a).
In order to avoid duplication with other aggregate indicators, we use the Shannon index as proxy for agricultural land use ‘patchiness’ (Weissteiner et al. 2016) or diversity in SUSFANS. In contrast to most aggregate indicators, agricultural land use diversity cannot be calculated for individual food supply chains, as it intrinsically evaluates local crop diversity of agricultural systems. The aggregate
indicator is therefore calculated as the average Shannon index of the farms/spatial units which contribute to the food supply chain.
Policy vision: A policy vision for agricultural diversity is difficult to define. The vision formulated in the states EU biodiversity strategy (European Commission 2011b) “By 2050, European Union biodiversity and the ecosystem services it provides — its natural capital — are protected, valued and appropriately restored for biodiversity’s intrinsic value and for their essential contribution to human wellbeing and economic prosperity, and so that catastrophic changes caused by the loss of biodiversity are avoided.”. We here tentatively set a goal of an increase of the Shannon index by two points until the year 2050. Note that this is a relative measure and interpretation might vary depending on the implementation of the Shannon index in different models. Possible, regional differentiated policy visions might be defined, taking protected areas and species hotspots into consideration.
Policy targets: Linear interpolation of the Shannon index calculated for the reference year and the value plus two points by 2050 to the policy target year.
Aggregated variables: The Shannon’s entropy index Hr is a measure for the crop diversity in a region r, which is one of the ‘greening’ elements that had been introduced in the latest CAP reform (EU 2013c). The index is computed based on the agricultural sector’s land use variety, i.e. the higher the number i of different crops Pi including grass cultivated and the more homogeneous their distribution (thus less dominance from few crops), the higher the diversity.
Marine biological diversity
Description: Seafood from capture fisheries represents the only large-scale food production based on a wild resource. It is sometimes argued that fisheries is be a good alternative to produce food with less impacts and resource use than many land-based protein production systems, as fisheries do not require inputs like feeds, fertilizers or pesticides. However, there are limits to natural production, and many stocks are overexploited and thus produce less than optimal. Direct and indirect ecosystem effects from over-exploitation include feedback such as altered ecosystem functioning (Howarth et al. 2014). This is manifested in the form of depletion of predatory fish (Christensen et al. 2003), collapse of major fish stocks (Pinsky et al. 2011), altered seafloor structure and function (Tillin et al. 2006) and biodiversity loss of target and non-target species (Dulvy et al. 2003; LEWISON et al. 2004). From an ecosystem production perspective, it has been estimated that current global fisheries exceed levels of sustainable exploitation, and have to decrease considerably to avoid risk of impaired function (Coll et al. 2008; Watson et al. 2015); the full effects of fisheries on marine ecosystems are still largely unknown.
Environmental pressures from aquaculture include: some species and farming practices require high level of feed input based on capture fisheries and may release invasive species, cause eutrophication, conversion of ecologically sensitive coastal land, and transmit diseases to wild fish (Diana 2009).
Policy vision: The vision of the descriptor on marine biodiversity in the Marine Strategy Framework Directive (EU 2008) states that the “quality and occurrence of habitats and the distribution and abundance of species are in line with prevailing physiographic, geographic and climatic conditions.” There are also several other commitments, agreements and policies of relevance to the EU goals on marine biodiversity, to mention a few:
- The Convention on Biological Diversity (1992) is a multilateral treaty with commitments to conserve and sustainable use of biological diversity in order to halt rate of biodiversity loss. One proposed indicator is the Red List Index (RLI; Butchart et al. 2010, 2005), measuring the trend in proportion of threatened species occurring (species complexes or nationally).
- Agreement on the Conservation of Small Cetaceans of the Baltic, North East Atlantic, Irish and North Seas (ASCOBANS), with the goal to protect marine mammals.
- The Birds Directive, protecting birds.
- The Habitats Directive, requires e.g. establishments of Special Areas of Conservation (target amounts) including marine habitats.
We set the SUSFANS policy vision to no adverse effects on marine habitats and non-commercial marine species from seafood production from either capture fisheries or aquaculture.
Policy targets: The descriptor for marine biodiversity in the Marine Strategy Framework Directive should be a good, overarching target for the SUSFANS policy vision. However, there are different national indicators to measure progress towards achieving Good Environmental Status of EU coastal waters by 2020, and many are not developed yet. Therefore, this cannot be included at this point.
Aggregated variables: Not applicable.