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Scientific Opinion addressing the state of the science on risk assessment of plant protection products for in-soil organisms

EFSA Panel on Plant Protection Products and their Residues (PPR) et al. EFSA J. .

Abstract

Following a request from EFSA, the Panel on Plant Protection Products and their Residues developed an opinion on the science behind the risk assessment of plant protection products for in-soil organisms. The current risk assessment scheme is reviewed, taking into account new regulatory frameworks and scientific developments. Proposals are made for specific protection goals for in-soil organisms being key drivers for relevant ecosystem services in agricultural landscapes such as nutrient cycling, soil structure, pest control and biodiversity. Considering the time-scales and biological processes related to the dispersal of the majority of in-soil organisms compared to terrestrial non-target arthropods living above soil, the Panel proposes that in-soil environmental risk assessments are made at in- and off-field scale considering field boundary levels. A new testing strategy which takes into account the relevant exposure routes for in-soil organisms and the potential direct and indirect effects is proposed. In order to address species recovery and long-term impacts of PPPs, the use of population models is also proposed.

Keywords: effects; in‐soil invertebrates; microorganisms; pesticides; protection goals; risk assessment.

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Figures

Figure 1
Figure 1
Representation of the main taxonomic groups of soil organisms on a body‐width basis (Reprinted with permission from John Wiley and Sons after Swift et al., 1979) from Decaens (2010) and Barrios (2007) (all photo credits: Flickr, http://www.flickr.com/)
Figure 2
Figure 2
Aporrectodea icterica dispersal rates in response to soil properties. Suit: suitable soil (high pH, high org. matter); Uns: unsuitable soil (sandy soil, low pH). Reprinted from Mathieu et al. (2010), Copyright (2010) with permission from Elsevier
Figure 3
Figure 3
Average functional effect of the elimination of species from a soil biota community composed of a very rich group of redundant species and a small group of functionally important species. Graph a) no interaction between species; Graph b) effect of redundant species on survival and/or performance of functionally important species. From Wolters (2001) copyright Elsevier
Figure 4
Figure 4
Organismal influence on soil processes, with factors (abiotic, ecosystem engineers and assimilators/dissimilators) in compartments. White arrows: energy and material flows between the compartments under external abiotic control (dotted bow tie). Black arrows: physical ecosystem engineering changes the physical soil structure and influence assimilatory‐ and dissimilatory‐related flows (gray bow tie), including biogeochemical processes (black bow tie). Modified after Jones et al. (2006), copyright Elsevier
Figure 5
Figure 5
Self‐organising systems in soils at different scales from microbial biofilms to the landscape. The stability of delivery of ecosystem services at scales > 5 is supported by the resistance of species to disturbances and/or the stability of physical structures (from Lavelle et al., , copyright Elsevier)
Figure 6
Figure 6
Soil food web (Reprinted from Hunt and Wall, . Copyright John Wiley and Sons from Hunt et al., 1997)
Figure 7
Figure 7
Relation between relative volume of earthworms in badger diet and the live weight of badgers during March‐June: males: r = 0.89, P < 0.05; females: r = 0.99, P < 0.001. Redrawn after Kruuk and Parish (1985), copyright John Wiley and Sons
Figure 8
Figure 8
Percentage of Pardosa spiders collected in spring‐sown cereals that tested positive for aphid consumption, springtail consumption or consumption of both prey by polymerase chain reaction (PCR)‐based gut‐content analysis. Reprinted from Kuusk and Ekbom (2010), Copyright (2010), with permission from Elsevier
Figure 9
Figure 9
Spatial scales considered for the environmental risk assessment of in‐soil organisms. Please, note that the landscape scale is not considered relevant for in‐soil organisms. * If present as non‐cropped or unsprayed area
Figure 10
Figure 10
Tiers in the risk assessment process, showing the refinement of the process through the acquisition of additional data (EFSA PPR Panel, 2010a)
Figure 11
Figure 11
Illustration of the relationship between tiers of the risk assessment process and protection goals, in the approach used by the PPR Panel (EFSA PPR Panel, 2010a)
Figure 12
Figure 12
Reference tier vs surrogate reference tier in the risk assessment of in‐soil species
Figure 13
Figure 13
Illustrative risk assessment flowchart for in‐soil organisms exposed to (active substances in) plant‐protection products. A high risk from an intended use of a PPP is possible unless both the effects measurement and population modelling components indicate low risk. In the lowest tier of effects measurement, organisms like macro‐, meso‐ and microfauna are addressed by single species tests and functional responses are assessed for microorganisms. At the highest tier, effects on different groups of in‐soil organisms are assessed jointly, in order to detect possible indirect effects of PPP intended uses
Figure 14
Figure 14
Flowcharts for possible routes through the combined effect and field‐exposure. The boxes from E‐1 to E‐4 are four effect tiers and the boxes from F‐1 to F‐4 are four tiers for assessment of exposure in the field (‘F’ from ‘field’). Dashed arrows indicate movement to a higher tier. Arrows from right to left indicate delivery of field‐exposure estimates for comparison with effect concentrations in the effect flow chart (EFSA, 2013)
Figure 15
Figure 15
Schematic representation of the two types of exposure assessments that are needed in any combination of tiers of the effect and field‐exposure flowcharts
Figure 16
Figure 16
Scientific concepts on the bioavailability of organic chemicals. (Reprinted with permission from Ortega‐Calvo J, Harmsen J, Parsons J, Semple K, Versonnen B, Aitken M, Ajao C, Eadsforth C, Galay‐Burgos M, Naidu R, Oliver R, Peijnenburg W, Roembke J and Streck G, . From bioavailability science to regulation of organicbchemicals. Environmental Science and Technology, 49, 10255–10264. Copyright (2015) American Chemical Society). Bioavailability can be examined through chemical activity, the potential of the contaminant for direct transport and interaction with the cell membrane (processes B, C and D), or bioaccessibility measurements, which incorporate the time‐dependent phase exchange of the contaminant between the soil/sediment and the water phase (process A). Depending on biological complexity, the passage of the contaminant molecule across the cell membrane (process D) may represent multiple stages within a given organism before the site of biological response is reached (process E)
Figure 17
Figure 17
Distribution of three different active substances (a, b, h) in the soil profile over time (modified according to Boesten, ; Poßberg et al., ; Toschki et al., ; Egerer et al., 2015). The different coloured bars indicate the concentrations of a.s. in the different sampled soil depths (Copyright permissions UBA, Germany).
Figure 18
Figure 18
Dominance of the three ecological groups of earthworms at grassland and crop sites in Central Europe (Römbke et al., , copyright permissions UBA, Germany)
Figure 19
Figure 19
3D‐Reconstructions of the burrow systems made different earthworm species and increasing imidacloprid concentrations. Colours range from light to dark according to the distance from the point of observation. (a) Aporrectodea nocturna, anecic and (b) Allolobophora icterica, endogeic. Reprinted From Capowiez et al., , Copyright (2006) with permission from Elsevier
Figure 20
Figure 20
Decrease of total abundance of Collembolan species in the imidacloprid‐treatments 0.75 kg a.s./ha and 2.0 kg a.s./ha (5 replicates each) for the different soil layers in comparison to the control (10 replicates). Columns show the measured total concentration for the two treatment concentrations at the respective sampling date. *: significant difference according to Williams t‐test; bars showing the minimum detectable difference (MDD) as value for the specific possible statistical resolution. MDD values higher than 100% are not shown (from Toschki et al., 2015)
Figure 21
Figure 21
Scaling factor of the toxicity endpoint as a function of the mass fraction of organic matter of the exposure scenarios for a range of values of K om. In this example, the mass fraction of organic matter in the test medium is 0.1 g/g (or 10%)
Figure 22
Figure 22
Map of the three regulatory zones according to Regulation EC No 1107/2009 of the European Parliament and the Council
Figure 23
Figure 23
Cropping and application systems covered by this guidance
Figure 24
Figure 24
Comparison of sensitivity to a set of PPPs (active substances, metabolites or formulations) of Folsomia candida and Hypoaspis aculeifer. The solid line indicates a 1:1 relationship between Folsomia candida and Hypoaspis aculeifer. The light grey area in the figure indicates where Folsomia is more sensitive to pesticides
Figure 25
Figure 25
Average field sizes in Europe (see Reuter and Eden, 2008)
Figure E.1
Figure E.1
Link of analytical and biological data out of the field and indoor laboratory by sampling in Terrestrial Model Ecosystem (TME). From Toschki et al. (2014, 2015)
See this image and copyright information in PMC

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