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Chip designWe used our micro-engineered silicone chip termed the “Obstacle chip”26, representing a proxy of a soil pore space system containing different sets of microstructures. The chip consists of an artificial pore system open on one side for inoculum, and it is designed to investigate the growth and dispersal behaviour of soil microbes (Supplementary Fig. 1a, b). The chip’s pore-space dimensions are optimized to match the dimensions of fungal hyphae, with structure widths ranging between 4 and 100 µm, and a uniform height of ~7 µm to aid microscopy, since cells are located in the same focal plane and rarely overlay. It contains five different geometric sections accessible by soil microbes via a common entry area (Supplementary Fig. 1a). The entry area consists of an open area with round pillars of 100 µm diameter at a separation of 100 µm, holding up the chip’s ceiling. It was cut open longitudinally with a scalpel prior to bonding (see below, section ‘Chip fabrication’), ensuring direct contact of the soil with the chip’s interior. The inner section comprises a combination of differently shaped channels and obstacles constituting five experimental sections, of which two were systematically examined in this study: (1) Section C: A set of channels with sharp corners of three different types (n = 12, randomly distributed): zigzag channels (90° turns with all channel sections at ±45° angle from the main growth direction), meandering square channels (90° turns with each section oriented in either the main growth direction or perpendicular to it), ‘z’-shaped channels (sharp corners diverting 135° from the previous growth direction, with channel sections in the main growth direction and at angles of 45° and 135° from it); (2) Section D: So-called ‘diamond channels,’ with a repeated combination of 10 µm wide and 400 µm long straight channels alternating with 140 µm wide diamond-shaped widenings. This channel type is replicated in 36 channels, each containing 33 diamond widenings. The widenings were used as quantification units to count bacteria and protist cell numbers, and for determination of liquid ingression, for the experiments on dispersal via fungal hyphae. Section A of the chip contains systems of hexagonal pillars of different diameters, Section B consists of straight channels with different widths, and Section E contains two types of obstacle courses comprised of complex structures. Those and the entrance system provided space for general observations. The design was constructed in AutoCad 2015 (Autodesk), in which patterns within experimental Sections A and C were randomized using a custom script from UrbanLISP (http://www.urbanlisp.com).Chip fabricationThe microfluidic chips were moulded in PDMS on a photoresist master defined by UV lithography and bonded to glass slides, according to Aleklett et al.26. The master was made by spin coating a thick negative photoresist (SU-8 5, MicroChem Corp, USA) on a glass plate for 60 s at 1250 rpm. This generated a photoresist layer of ~7 µm. The photoresist was soft baked for 5 min at 90 °C on a hot plate, patterned by UV exposure (Karl-Suss MA4 mask aligner) and post-exposure baked. It was then developed for 3 min in mr-Dev 600 (MicroChem) and finally rinsed with isopropanol (VWR International). The PDMS slabs were produced by thoroughly mixing a PDMS base and a curing agent (both Sylgard 184, Dow Corning, USA) in a 10:1 ratio, followed by pouring the mix onto the master in a 4-mm-thick layer, and degassing it in a vacuum chamber at −25 kPa for 45 min. Then the PDMS was cured in an oven for 2.5 h at 60 °C. Once cooled, the PDMS was cut slightly larger than the designed pattern, covering an area of about 40 × 65 mm, and cut though the entry system, creating a lateral opening to the chip along the pillar system.The PDMS slabs were bonded to glass slides. Glass slides, 55 × 75 mm and 1 mm thick (Thermo Scientific), were first cleaned with acetone, 75% ethanol and deionized water, and then dried under an air-blower. The pieces of PDMS and the glass slides were treated separately in an oxygen plasma chamber (Diener Electronic Zepto). For each chip, a glass slide was exposed to oxygen plasma under UV light for 1 min, followed by exposure of the PDMS piece for 10 s. Once both samples were plasma-treated, they were immediately brought in contact with their activated surfaces facing each other, and gently pressed to each other in the centre parts of the chip. To avoid collapse of the ceiling of the entrance, none of the chip edges were pressed. The chips were heated on a heating plate for ~15 s at 100 °C to ensure a proper bonding. After another 15 s, the chips with liquid treatments were filled with the different media using a micropipette, taking advantage of the PDMS’s temporary hydrophilia following plasma treatment so that liquids were readily drawn into its structures. The chips were filled with one of the following three treatments: (1) deionized water, (2) liquid malt medium, a complex medium to provide a nutrient-rich environment including reduced sugars such as disaccharide maltose and in lower proportion nitrogenous components such as peptides, amino acids purines and vitamins (malt extract for microbiology, Merck KGaA), or (3) chips were left empty, i.e., air-filled. The eight chips filled with liquid were then placed in a vacuum chamber for 30 min at −25 kPa to remove any bubbles. Finally, the chips were kept in sterile Petri dishes, sealed with Parafilm and stored overnight in a cold room before being dug down into or inoculated with soil.Expt. 1: in situ incubation of chipsTo evaluate the effect of different nutritional conditions on colonization of the soil chips by microbes, we evaluated three pore space filling treatments: (1) deionized water, (2) malt extract medium, or (3) air; n = 3 chips per treatment. The experimental site was a small grove of deciduous trees in the city of Lund, Sweden (55° 42′ 49.5′′ N, 13° 12′ 32.5′′ E; Supplementary Fig. 1c). The season chosen for burial of the chips was early autumn (October 2017) to guarantee a moist soil during the experiment. Groups of replicates of all three chip treatments were buried randomly within the inner parts of the grove (n = 3 chips per filling treatment). The litter layer was removed, and 20 × 20 cm holes were carefully dug into the ground with a spade. The chips were placed horizontally in the soil at a depth of 10 cm in which the PDMS chip was facing up and the glass slide down. Horizontal placement was chosen to probe a single stratum of the soil, serving as a comparable inoculum to the whole of the entry system, and to aid nondestructive recovery. The soil was carefully placed back in its original orientation, and the litter layer was placed back. A string attached to each chip was placed with its opposite end above the soil surface and attached to a pin, to guide future retrieval. There was a minimum distance of one meter between each chip replicate.Preliminary experiments had shown that a 2-month incubation period would grant the colonization of different types of soil microorganisms and minerals, and a stabilization of the inner environmental conditions between the soil chip and the surrounding soil. Thus, after 64 days (December 2017), the chips were collected by carefully removing soil around the string leading to each chip. We carefully kept the adjacent soil atop the glass slide along the opening of the chip, to keep our artificial pore system connected to the real soil pore system, and to avoid such disturbances as hyphal tearing or evaporation of the liquid inside the chips (Supplementary Fig. 1d). We cleaned the chip windows by softly wiping them with a clean wipe and deionized water. Samples were carefully transported to the microscopy facilities, located adjacent to the burial site. The chips were harvested one at a time and analysed under the microscope immediately after collection and cleaning.We recorded the presence or absence of the main soil microbial groups in the entry systems and in the different channels, including their furthest extent into the chips, with help of the internal rulers.To analyse the effect of fungal hyphae on bacterial abundance, we recorded real-time videos slowly scanning along the whole length of the diamond-shaped opening channels (each 33 diamonds, Section D in Supplementary Fig. 1a; Fig. 3). The rather sparse hyphal colonization allowed us to select pairs of channels where in the first channel a hypha had proliferated far into the channel, combined with a directly adjacent channel without hyphae, n = 4. In each diamond-shaped widening we counted the number of bacterial cells, the presence or absence of fungal hyphae, and the presence or absence of liquid. After completion of all measurements, the chips were left uncovered at room temperature for 60 min to initiate air drying in the adjacent soil, in order to observe the real-time effects of drying on organisms and particles in the pore space system of the chips. The adjacent soil was re-wetted by adding 400 µl of water. The water inside the chips corresponded to the adjacent soil pore water, regressed upon evaporation, and refilled the chip structures upon rewetting of the adjacent soil.Expt. 2–3: laboratory incubation of soil on chipsIn a complementary approach, we collected soil from a lawn in Lund, Sweden, at 10 cm depth, and placed 5 g of this soil in front of the entry system of the chip. Chips received the three nutrient condition treatments as described above, air, water or malt medium (n = 2, Expt. 2). An additional set of air-filled chips was studied to quantify fungal highways (n = 3, Expt. 3). Chips were monitored under the microscope after inoculation, observation was documented with images and videos. Chips were kept in sealed Petri dishes with wet cotton cloths to maintain high humidity and were taken out for analysis only. The soil inoculum on the chips and the interior of the chips were kept moist with 500 µl of water added to the soil once a week. The artificial waterlogging event in the chips of Expt. 3 (‘fungal highways’) was achieved by adding a total of 2 ml of water to the inoculum soil over the course of a week, and the drying event was achieved by discontinuing the watering.During Expt. 2, we recorded the abundance and the furthest extent of bacteria, protists (including the morpho-groups ciliates, flagellated, and amoeboids), and the extent of hyphal colonization into the diamond section over time. After 2 months of incubation, we measured the furthest extent of colonization into the angled channels for the organism groups bacteria, fungi, and protists. During Expt. 3, we recorded the presence and the furthest extent of hyphae, liquid, bacteria, and protists in the diamond channels over time. We also recorded the number of protists, bacteria (in categories 0, More

EDITORIAL
20 July 2021

Vulnerable nations lead by example on Sustainable Development Goals research

A United Nations study of world science is a wake-up call that richer countries must also shift science towards the SDGs.

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Iraq’s wetlands are threatened by climate change; the country is pivoting its research towards the SDGs.Credit: Murtadha Al-Sudani/Anadolu Agency/Getty

With the United Nations Sustainable Development Goals, world leaders pledged to end poverty and hunger, protect biodiversity and the climate, and get all children into schools by 2030. How have researchers and funders responded? Has there been a shift in research priorities?The UN’s Paris-based science and education agency has answers to these and other questions in the latest UNESCO Science Report, published last month (see go.nature.com/3zlojva). UNESCO says the 700-page report is a first attempt at understanding the impact of the Sustainable Development Goals (SDGs) on research priorities. The findings are a mixed picture.Using the Scopus database, UNESCO mapped publications from almost 200 countries between 2011 and 2019 on 56 research topics relevant to the SDGs. For the most part, the high-income countries that account for 64% of the world’s research spending — including Japan, South Korea, the United States and many European countries — showed relatively little change in the number of publications produced concerning the SDGs, and a declining share of global research.
How science can put the Sustainable Development Goals back on track
But it’s a different story for low- and middle-income countries, which have begun to shift their research priorities towards the goals.For example, the share of publications on photovoltaics — which could address the SDG on boosting renewable energy — from low-income and lower-middle-income countries more than trebled, going from 6.2% to 22% of the world total in the study period. The share of papers on biofuels and biomass nearly trebled, from 8.5% to 23%.Low-income countries more than doubled their share of research publications on crops that are more resilient to climate change, from 5% of the total to 11%. And researchers from sub-Saharan Africa contributed 361 out of 885 publications on smallholder farming in 2019 — more than the European Union’s 294. Ecuador, Ethiopia, Indonesia, Iraq, Russia and Vietnam all increased their output on most topics, albeit from low starting points in some cases.Much of the growth is powered by China. According to UNESCO, China’s researchers now publish around half of the world’s output on battery efficiency, 43% on hydrogen energy and 41% on carbon pricing. Their research on carbon capture and storage increased from 1,300 publications between 2012 and 2015 to 2,049 in 2016–19. By contrast, high-income nations — including France, Germany and the United States — showed declining shares during the same period, and some showed declining numbers. One exception is research into floating marine plastics. The field, which barely existed a decade ago, recorded 853 publications in 2019, mostly from high-income nations. But, overall, wealthier nations reported falls in their share of publishing across 54 out of the 56 fields assessed.
Does the fight against hunger need its own IPCC?
It’s disappointing to see so little progress from the richer countries. But it is something of a pattern. UNESCO’s researchers calculated that, between 2000 and 2013, wealthy nations spent less than US$25 billion on international development assistance in environmental areas such as climate change and biodiversity — about one-fifth of the $130 billion given for assistance in industry and innovation.At the same time, it’s heartening to see scientific output being slowly revived in many low-income countries — some of which were engines of scholarship in times past. But UNESCO also finds that funding trends in these countries have become harder to track. Some 98 countries reported funding data in 2015, but this fell to 68 in 2018. Some 28% of high-income and 78% of low- and middle-income countries are not reporting their science-funding data — and that is both problematic and troubling. The ability to correlate funding data with publishing information would provide a richer picture of the gains, and identify areas that would benefit from more resources. Countries need to comply with UNESCO’s requests for information, partly because they are obliged to track these data for the SDGs.Even before the pandemic, the world was not on track to reach most of the Sustainable Development Goals. With less than a decade to go before the 2030 deadline to end poverty and protect the environment, the UNESCO report aptly says that the world is “running out of time”. The report needs to be read closely in every world capital. It’s still not too late for everyone to pivot science to sustainability.

Nature 595, 472 (2021)
doi: https://doi.org/10.1038/d41586-021-01992-y

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Archaeoglobales as systematic (electro)lithoautotrophs of the communityWe have evidenced the development of microbial electrotrophic communities and metabolic activity supported by current consumption (Fig. 1), product production (Fig. 2), and qPCRs (Fig. 3). These data suggest that growth did occur from energy supplied by the cathode. Our study is the first to show the possibility of growth of biofilm from environments harboring natural electric current in the total absence of soluble electron donors. To further discuss the putative mechanism, it is necessary to have a look at our conditions unfavorable for water electrolysis (see Supplementary Fig. S2). The equilibrium potential for water reduction into hydrogen at 80 °C, pH 7, and 1 atm was calculated at − 0.490 V vs SHE in pure water. The operational reduction potential is expected to be lower than the theoretical value due to internal resistances (from electrical connections, electrolytes, ionic membranes, etc.)16 and overpotentials (electrode material). This was confirmed with the on-set potential of H2 evolution measured at − 0.830 mV vs SHE in both experimental condition and abiotic control, indicating the absence of catalytic effect of putative hydrogenases secreted by the biofilm or metals from inoculum. Also, during preliminar potentials screening, the increase in current consumption and H2 production was observed only below − 0.7 V vs SHE (Supplementary Figs. S1 and S2). In addition, the presence of catalytic waves observed by CV with midpoint potentials between − 0.217 V to − 0.639 V indicate the implication of enzymes directly connected to the surface of the electrode (see Supplementary Fig. S2). Finally, the fixation of 267–1596 Coulombs day−1 into organics (Fig. 1) exceeds the maximum theoretical abiotic generation of hydrogen from abiotic current (~ 3 C day−1) 90- to 530-fold17.Therefore, under our experimental conditions, the biofilm growth should be largely ensured by a significant part of a direct transfer of electrons from the cathode, thereby demonstrating the presence of electrolithoautotroph microorganisms. This is supported by obtaining a similar biodiversity on sulfate with the cathode poised at − 300 mV [compared to − 590 mV vs SHE (Fig. 3)], whose potential is 190 mV more positive than the Equilibrium potential of H2 evolution (− 490 mV vs SHE), with then no electrochemical possibility of H2 production, even at molecular level.Taxonomic analysis of the enriched microbial communities at the end of the experiments showed the systematic presence of Archaeoglobales on cathodes. Moreover, the qPCR and MiSeq data (Fig. 3) highlighted a strong correlation between current consumption and density of Archaeoglobales in the biofilm (Supplementary Fig. S4, R2 = 0.945).The OTUs were related to some Archaeoglobales strains with 95–98% identities. Thus, we assume that under our experimental conditions new specific electrotrophic metabolisms or new electrolithoautotrophic Archaeoglobaceae species were enriched on the cathode. They were retrieved in all conditions and belonged to the only order in our communities exhibiting autotrophic metabolism. Autotrophic growth in the Archaeoglobales order is ensured mainly through using H2 as energy source and requires both branches of the reductive acetyl-CoA/Wood-Ljungdahl pathway for CO2 fixation18. Terminal electron acceptors used by this order include sulfate, nitrate, poorly crystalline Fe (III) oxide, and sulfur oxyanions19. Moreover, Archaeoglobus fulgidus has been recently shown to grow on iron by directly snatching electrons under carbon starvation during the corrosion process20. Furthermore, Ferroglobus and Geoglobus species were shown to be exoelectrogens in pure culture in a microbial electrosynthesis cell12 and have been enriched within a microbial electrolysis cell11,13. Given these elements, the identified Archaeoglobales species could be, under our electrolithoautotrophic conditions, the first colonizers of the electrode during the first days of growth. This hypothesis was confirmed into a more detailed study focusing on the enrichment on nitrate21.The growth of Archaeoglobales species in presence of oxygen is a surprising finding. Archaeoglobales have a strictly anaerobic metabolism, and the reductive acetyl-CoA pathway is very sensitive to the presence of oxygen22. This can be firstly explained by the low solubility of oxygen at 80 °C. Secondly, carbon cloth mesh reduces oxygen in the environment, allowing for anaerobic development of microorganisms into a protective biofilm23. This observation was supported by the near absence of Archaeoglobales in the liquid medium (Fig. 3). One of the hypotheses concerns direct interspecies electron transfer (DIET)24,25, with Archaeoglobales transferring electrons to another microorganism as an electron acceptor. Research into DIET is in its early stages, and further investigations are required to better understand the diversity of microorganisms and the mechanism of carbon and electron flows in anaerobic environments25 such as hydrothermal ecosystems.Electrosynthesis of organic compoundsAccumulation of pyruvate, glycerol and acetate was measured, while another set of compounds that appeared transiently were essentially detectable in the first few days of biofilm growth (Supplementary Table S1). They included amino acids (threonine, alanine) and volatile fatty acids (formate, succinate, lactate, acetoacetate, 3-hydroxyisovalerate) whose concentrations did not exceed 0.1 mM. Despite their thermostability, this transient production suggests they were used by microbial communities developing on the electrode in interaction with the primary producers during enrichment.On the other hand, in presence of nitrate, sulfate and oxygen as electron acceptors, the liquid media accumulated mainly acetate, glycerol, and pyruvate (Fig. 1). Coulombic efficiency calculations (Fig. 2) showed that electron content of the carbon products represented 60–90% of electrons consumed, the rest being potentially used directly for biomass or transferred to an electron acceptor. This concurs with the energy yield from the Wood-Ljungdahl pathway of Archaeoglobales, with only 5% of carbon flux directed to the production of biomass and the other 95% diverted to the production of small organic end-products excreted from the cell26.Pyruvate is a central intermediate of CO2 uptake by the reducing pathway of the acetyl-CoA/WL pathway27. It can be used to drive the anabolic reactions needed for biosynthesis of cellular constituents. Theoretically, the only explanation for improved production and accumulation of pyruvate (up to 5 mM in the liquid media of sulfate experiment) would be that pyruvate-consuming enzymes were inhibited or that pyruvate influx exceeded its conversion rate. Here we could suggest that in-cell electron over-feeding at the cathode leads to significant production of pyruvate when the electron acceptor runs out.In an ecophysiological context, similar pyruvate and glycerol production could occur on hydrothermal chimney walls into which electric current propagates28. The electrotroph biofilms would continually receive electrons, leading to an excess of intracellular reducing power which would be counterbalanced by overproduction of glycerol and pyruvate29,30. Furthermore, these products can serve as carbon and energy sources for heterotrophic microorganisms or for fermentation. In our experiments, pyruvate and glycerol concentrations varied over time, suggesting they were being consumed by heterotrophic microorganisms. Acetate production would thus result from the fermentation of pyruvate or other compounds produced by electrotrophic Archaeoglobales.Enrichment of rich heterotrophic biodiversity from electrotrophic Archaeoglobales communityDuring our enrichment experiments, the development of effective and specific biodiversity was dependent on the electron acceptors used (Fig. 3). Heatmap analyses (Supplementary Fig. S3) showed four distinct communities for the three electron acceptors and the initial inoculum. Thus, at the lower taxonomic level of the biodiversity analysis, most OTUs are not common to multiple enrichments, except for one OTU of Thermococcales that was found in both the nitrate and sulfate experiments. This suggests a real specificity of the communities and a specific evolution or adaptation of the members of the shared phyla to the different electron acceptors available in the environment. However, the various enrichments also showed the presence of Thermococcales regardless of the electron acceptors used, thus demonstrating a strong interaction between Thermococcales, assumed to be heterotrophs, and Archaeoglobales, the only demonstrated autotrophs. Moreover, members of these two groups have frequently been found together in various hydrothermal sites4,5,31,32, where they are considered potential primary colonizers33,34,35,36,37. After Thermococcales, the rest of the heterotrophic biodiversity was specific to each electron acceptor.On nitrate, two additional phylogenetic groups were retrieved: Desulfurococcales and Thermales. OTUs of Desulfurococcales are mainly affiliated to Thermodiscus or Aeropyrum species, which are hyperthermophilic and heterotrophic Crenarchaeota growing by fermentation of complex organic compounds or sulfur/oxygen reduction (Huber and Stetter, 2015). Concerning Thermales, a new taxon was enriched on cathode and only affiliated to Vulcanithermus mediatlanticus with similarity of 90%. This new taxon of Thermales (OTU 15, Supplementary Fig. S3) was also enriched up to 2% on the cathode of sulfate enrichment. Thermales are thermophilic (30–80 °C) and heterotrophic bacteria whose only four genera (Marinithermus, Oceanithermus, Rhabdothermus, and Vulcanithermus) are all retrieved in marine hydrothermal systems. They can grow under aerobic, microaerophilic and some anaerobic conditions with several inorganic electron acceptors such as nitrate, nitrite, Fe (III) and elemental sulfur38. All of the Thermales species can utilize the pyruvate as carbon and energy source with the sulfate or nitrate as electron acceptors.Pseudomonadales and Bacillales were found in the oxygen experiment. Most Pseudomonas are known to be aerobic and mesophilic bacteria, with a few thermophilic species (up to 65 °C)39,40. There have already been some reports of mesophilic Pseudomonas species growing in thermophilic conditions in composting environments41. Moreover, some Pseudomonas sp. are known to be electroactive in microbial fuel cells through long-distance extracellular electron transport42,43,44, and were dominant on the cathodes of a benthic microbial fuel cell on a deep-ocean cold seep45. In Bacillales, the Geobacillus spp. and some Bacillus sp. are known to be mainly (hyper)thermophilic aerobic and heterotrophic Firmicutes46.Hydrothermal electric current: a new energy source for the development of primary producersThe presence of so many heterotrophs in an initially autotrophic condition points to the hypothesis of a trophic relationship inside the electrotrophic community (Fig. 5). This suggests that the only autotrophs retrieved in all communities, the Archaeoglobales, might be the first colonizer of the electrode, using CO2 as carbon source and the cathode as energy source. Models using the REACT module of the Geochemist’s Workbench (GWB) and based on electron donor acceptor availability predicted low abundances of Archaeoglobales ( More

Pesticide residues in organic productsNon-use of synthetic pesticides is a major characteristic of organic farming, with the objectives of protecting (a) the environment, (b) consumer health, and (c) farm worker health. In consumer studies, “no chemical pesticides” is usually mentioned as one of the most important criteria for buying organic food1,2. These consumer expectations are mostly met in what is referred to in objective (b). Both European and U.S. sources consistently found the percentage of samples with residues of pesticides above the limit of quantification ( > LOQ) to be much lower in organic than in conventional food (Fig. 1a, see also Supplementary Fig. 1). This is especially true when it comes to fresh fruits and vegetables (Fig. 1c), which are known to be the most critical food groups in terms of pesticide residues3. It is elucidating, however, to not only look at the number of samples with an (unknown) level of residues  > LOQ, but to quantify the residues found per sample. In many cases, more than one substance is found in a sample, therefore one meaningful indicator is the mean cumulative pesticide load per sample (MCPL, see Supplementary Table 1). This is represented in Fig. 1b for three out of the four datasets. The food authority CVUA (Chemisches- und Veterinäruntersuchungsamt) in Baden-Württemberg, Germany, has been comparing pesticide residues between organic and conventional food since 2002. In 2019, on average the residues in organic produce were more than 150 times lower than in the corresponding conventional products4 (Ratio Org./Conv., bottom of Fig. 1d). The USDA (U.S. Department of Agriculture) numbers tend to be higher than the European ones, both in percentages (Fig. 1a,c) and in MCPL (Fig. 1b). One reason for this is probably USDA’s risk-oriented sampling approach, in which some highly contaminated commodities are over-represented, as compared to their importance in most people’s diet (Supplementary Table 2, column C). If we correct this possible bias by assuming that every commodity would have been sampled with the same frequency, the MCPL across all commodities is cut by 40% (Supplementary Table 2, last row). Different LOQs and numbers of analytes covered by USDA on one hand, and different European laboratories on the other hand, also make comparison difficult.Figure 1Pesticide residues in conventional and organic food in tests conducted by four organisations: EFSA (European Food Safety Authority) collects official data from all EU member states3, CVUA from one federal state in Germany4, USDA from government laboratories across the U.S.5, while Eurofins is a commercial laboratory in Germany. Figures in brackets represent the number of samples. The legend is valid for (a), (b) and (c). In order to increase the number of samples (represented in brackets) and thus their representativeness, figures from several years were grouped together, as available from each organisation. Black bars symbolise standard errors across years. (a) Shows the percentage of samples with residues above the limit of quantification (LOQ), for all types of food ( available from two organisations only). (b) Represents the mean cumulative pesticide load (MCPL) for fruits and vegetables (available from three organisations). (c) Similar to (a), but for fresh fruits and vegetables only (CVUA uses “above 0.01 mg/kg” instead of LOQ, but this is identical for most substances). The same datasets were used for (b) and (c). (d) Multi-layer sieving model for residue testing at different points of the organic supply chain. The data above the white arrows are from the commercial laboratory Eurofins, and mostly represent the situation before products are released to the market, while the figures below the white arrows are from CVUA, representing the situation on the market (both wholesale and retail). Ratios from “before market” to “on market” are shown in the white arrows. In this process, the MCPL remains in the same range for conventional products (blue rectangle to the right), while it is reduced massively for organic products (green trapezium in the centre). As a result of this sieving mechanism, residues in samples from the market are 150 and more times lower in organic than in conventional produce (trapezium at the bottom). This shows that the process represented by the blue arrows works fairly well—which is not always the case for the investigation of the origin of such residues, symbolised by the yellow arrows.Full size imageOrganic businesses’ testing strategiesUnfortunately, the generally good news for consumers with respect to objective (b) does not always mean that objectives (a) and (c) are also met. With the steady growth of the organic market and globalisation of supply chains, integrity of the system is often at stake. Organic products mostly fetch higher prices, and therefore also attract fraud6,7. Since pesticide residues are easily detectable parameters, often indicating non-compliance with organic production rules, many organic businesses test each batch for such residues, before placing it on the market. Positive results should then lead to an investigation of the origin of the found residues: Did an organic farmer spray? Do the residues come from drift, from ubiquitous contamination, or from (avoidable or unavoidable) contamination during processing, transport, storage? Were organic and conventional products mixed at some point of the supply chain—or is somebody simply labelling conventional products as “organic”? The idea behind this is depicted in Fig. 1d. The filter process as such, and the exclusion of contaminated batches from the organic market, as represented by the blue and red arrows, often work well. Thus, there are remarkably lower average amounts of residues after undergoing this filtering process. Residues in organic produce reported from the market were reduced by 22 and 89 times in fruits and vegetables, respectively, compared to the levels reported by the commercial laboratory, which represent mostly pre-market samples, while the values for conventional samples remained in the same range. This shows that market actors often remove problematic batches by declaring them conventional. In Supplementary Tables 3 and 4 we provide further explanations why the datasets “before release to the market” and “on the market” in Fig. 1d are comparable.We do not have test results from a commercial laboratory in the U.S. that could be compared to Eurofins data. But, as opposed to the other sources of information, the USDA database identifies the country of origin of each sample. Anybody working in international organic certification would expect residues in imported food to be higher than in domestic products, because fraud is more widespread when the distance is bigger between producers on the one hand, and consumers and the competent authorities on the other. The U.S. data, however, suggest the opposite trend: Not only at the aggregate level, but also for most individual commodities, the MCPL is lower in imported than in domestic products (Supplementary Table 2, columns J and K). The reason is probably that samples are tested before signing purchase contracts, and products rejected or bought as conventional, if they do not comply with the expectations.This is good quality control practice—the problem is that the information about the “downgrading” of organic products to conventional is not always reaching the certification bodies (CBs), thus impeding the investigation of the origin of residues and the exclusion of fraudulent actors from the market (yellow arrows in Fig. 1d). It is in the nature of things that these processes are not publicly known and therefore cannot be quantified, but in Supplementary Fig. 2 we present anecdotic evidence, which also suggests that for some market actors the definition of “organic” is limited to “free of pesticide residues”.Certifiers’ testing strategiesThe two most important markets for organic food are the EU, where the “organic” label is legally governed by an EU Regulation, and the USA, where the corresponding rule is the National Organic Program (NOP). Although they have different approaches on how to deal with spray-drift and with residues (Supplementary Table 5), both regulations require CBs to take samples from at least 5% of their clients every year. A large amount of data is being generated through this mechanism, but the sampling procedures and interpretation of results often do not allow deriving clear results. A recent unpublished BSc thesis at the University of Kassel revealed that 80% of the samples by CBs in ten EU member countries are taken of final products, but only 20% from the field or during the production process. This suggests that not only for market actors, but also for many CBs, the purpose of sampling and testing is limited to ensuring that food sold on the market with an organic claim, is free of pesticide residues, without digging deeper to find the origin of contamination.The differentiation between active use and non-intentional contamination is difficult, if only final products are tested. Plant (mainly leaf) samples from the field have several advantages in this regard: (a) Often, there is a long time span between pesticide application and harvest. Because of dissipation of the residues, nothing or only traces may be found in the final product (Supplementary Table 6). Field samples can be taken during or shortly after a suspected pesticide application, so that the dissipation effect is reduced and residues are found even for substances with a short half-life. (b) Leaves have a surface/weight ratio between 10 and 118 cm2/g8, whereas for fruits this ratio is between 0.6 and 2.29, and for seeds between 2 and 10 cm2/g only10,11,12. Residues in leaves are therefore normally higher than in seeds, fruits or roots, which makes interpretation of test results easier. (c) Field sampling allows taking separate samples from centre and margin of the field, as explained below in more detail.Unfortunately, if CBs take field samples at all, they often take them only from field margins13,14 (“let’s see if there is a drift problem”). Positive results are then attributed to spray-drift, and farmers are required to establish buffers—without even considering the possibility of residues originating from an application by the organic farmer. Such procedures open the door for fraudulent use of pesticides by organic farmers.Other CBs have established so-called “action levels”, below which they consider the presence of residues in organic products to be the result of ubiquitous environmental contamination, with no need to investigate their origin13. While such thresholds may be necessary for specific cases (see below concerning the banana industry), using this approach as a general procedure disregards not only the spatial distribution, but also temporal dynamics of pesticides in plant tissue. As opposed to soil, half-lives in plant tissue exposed to UV radiation and weather, are relatively short for most modern pesticides15. A residue level of 0.02 mg/kg, used by some CBs as “action level”, is typically reached one to two months after the application of a pesticide, in some cases even after only five days (Supplementary Table 6).The time that has elapsed since an application, however, is unknown in most cases. Spraying records kept by conventional neighbours are normally not part of the inspection. In case of suspicious test results in samples from the organic farm, such records may sometimes be accessed as part of a follow-up investigation, but at that point the organic farmer may have asked the neighbour to manipulate the records. And if the organic farmer has sprayed, he or she obviously tries to hide this fact. This situation makes interpretation of low levels of residues found in samples from organic fields even more challenging, and increases the importance of being able to differentiate application from drift through other methods.Two forms of spray-driftOver the past decades, a distinction has been made between short distance primary spray-drift during the application, and long distance secondary spray-drift occurring after the application16. The latter was attributed to evaporation and considered to play a role only for pesticides with high vapour pressure17. On the one hand, recent studies have shown that evaporation and long-distance transport can already play a role during, not only after application18. On the other hand, long-distance transport has been found to be linked not only to evaporation. Pesticides adherent to dust from wind erosion can contaminate large areas19. In the present context, we use the terms short-range and long-range drift, instead of primary and secondary drift (Fig. 2).Figure 2Simplified model of short-range vs. long-range drift originating from air-blast spraying in a fruit orchard. The specific values for pesticide concentrations (mg/kg) expected for different downwind distances from the orchard can vary by a factor 10 or more, depending on the applied substance, dose, weather conditions, vegetation, etc., but the graph provides an approximate estimate of the ratios that can be expected. In the case presented here, pesticide concentration in fruit leaves immediately after the application is 15 mg/kg. In the area of short-range direct drift, deposit decreases exponentially, so that at 100 m distance, we can expect to find only 0.01 mg/kg. At further distances, deposits are often below this level.Full size imageLong-range driftLong-range drift is so far poorly understood, can lead to (normally very low) residues at distances as far as thousands of km19, and happens in the form of vapour or molecules adhering to dust. The main factors influencing long-range drift are vapour pressure of the pesticide, capacity of adherence to dust, incidence of wind erosion, and temperature inversion in the atmosphere17. Long-range pesticide drift has recently received more attention21,22,23,24,25. Examples have been used in the context of organic certification for supporting the argument of ubiquity of pesticides, linked to the assumption that low- or even medium-level residues in organic products are often derived from their omnipresence in the environment26,27.Cases from Brazil (endosulfan in soybeans), Montana (USA) and Saskatchewan (Canada) (glyphosate in khorasan wheat) and Germany (pendimethalin and prosulfocarb in different crops) have been quoted to demonstrate the ubiquity of pesticides27. None of these case studies, however, provides solid evidence for the assumption that long-distance transport of pesticides leads to residues in organic food above the level of, say, 0.01 to 0.03 mg/kg. The problem of the herbicides pendimethalin and prosulfocarb being subject to long-distance drift because of their high vapour pressure, has been known for a long time28, but this phenomenon cannot be extrapolated to other substances. Even for these herbicides, there is no evidence that residues at larger distances could be above the indicated levels. Across 15 vegetation samples from nature reserves in Germany, on average, 0.009 mg/kg pendimethalin and 0.004 mg/kg prosulfocarb were found29. Exceptions may exist, e.g., when pesticide applications are followed by heavy wind erosion, as seems to be the case in some of the North American wheat growing areas, where glyphosate is used for cereal desiccation shortly before harvest.In a survey in Switzerland30, neonicotinoid residues were found in 93% of plant samples from organic farms (as compared to 100% of samples from conventional farms), thus supporting the ubiquity suspicion. But there were substantial quantitative differences between organic and conventional farms (Fig. 3). The average sum of neonicotinoid residues in plant and soil samples from organic farms was lower by a factor of 11 than that of plant samples from conventional farms. For soil samples, this factor was as high as 71. Even the highest value for one single substance (imidacloprid) found in organic plants (2.13 µg/kg = 0.00213 mg/kg) would be below the limit of quantification (LOQ) used for this substance in most screenings (0.01 mg/kg).Figure 3Maximum and average residues of neonicotinoid insecticides in soil and plant samples from organic farms, integrated crop production (“IP Suisse”: this program involves reduced pesticide application) and conventional farms in Switzerland. The figures represent the sums of acetamiprid, chlothianidin, imidacloprid, thiacloprid and thiamethoxan. Figures in brackets represent standard errors.(Data from Humann-Guilleminot et al.30).Full size imageIn a study in Germany29, the MCPL in natural vegetation in five reference areas (average distance from arable fields  >3 km) was 0.003 mg/kg, and in 15 nature conservation areas (average distance from arable fields 143 m) it was 0.006 mg/kg, but in three buffer zones (average distance 54 m) it was 5.4 mg/kg. To make figures comparable with other data in this article, we have subtracted the concentration of non-agricultural pesticides from the total amounts, and divided the numbers by a factor five, because the residues in this study refer to dry matter, while all the others use fresh matter. Although 5.4 mg/kg at 54 m distance is a disturbingly high value, the survey confirms that concentrations at larger distances do not exceed the “traces” level. The intention of this article is not to put in doubt the environmental damage caused by such traces. What we try to show is that the “ubiquity” argument may sometimes be hiding cases of fraudulent pesticide use by organic farmers.Short-range driftAs opposed to long-range drift, short-range drift is well understood, has its impact mainly in a range from 1 m up to a maximum of 1,000 m (for aerial spraying), happens in the form of droplets, and is not substance specific. The main factors influencing this form of drift are droplet size, windspeed, and height of the boom (nozzles) above soil17,19,31,32,33. The fact that long-range drift is poorly understood and leads to low concentrations of certain substances over wide areas, should not stop certification bodies (CBs) from using the available knowledge about short-range drift as a tool for assessing farmers’ compliance with organic production rules. The dynamics of short-range spray-drift have been widely studied in the context of preventing liability problems due to herbicide damage, contamination of water bodies and natural habitats, and direct risks for human settlements19,31,32,33,34,35,36. Pesticide deposit decreases exponentially with increasing distance from the field on which the substance is applied. With a tractor boom sprayer, deposit at 25 m distance is expected to be only 1% of that in the target field. While distances are greater for air-blast or aerial spraying, the basic principle of exponential decrease is the same (Fig. 2 and Supplementary Fig. 3).ObjectivesThe objectives of our study are: (I) to demonstrate that appropriate field sampling methods can differentiate the effects of fraudulent pesticide application by the organic farmer, from the results of both short-range and long-range spray-drift, and (II) for the specific case of aerial fungicide spraying in the banana industry, identify appropriate variables, which allow us to interpret the test results correctly for the purpose of this differentiation. More

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