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Detection of archival Phyllonorycter mines in historical herbariaOnly 1.5% (225 out of 15,009) of herbarium specimens of Tilia spp. examined from the Palearctic contained Ph. issikii leaf mines. These 225 herbarium specimens occurred in 185 geographical locations across the Palearctic, with the westernmost point in Germany (Hessen; the herbarium specimen dated by 2004) to the most eastern locations in Japan (on the island of Hokkaido; 1885–1974) (Fig. 1).Figure 1The localities where herbarium specimens of Tilia spp. carrying Phyllonorycter mines were collected in the Palearctic in the last 253 years. The dotted line divides Ph. issikii range to native (below the line) and invaded (above the line). The map was generated using ArcGIS 9.3 (Release 9.3. New York St., Redlands, CA. Environmental Systems Research Institute, http://www.esri.com/software/arcgis/eval-help/arcgis-93).Full size imageMost specimens with leaf mines (90%; 203/225) originated from Eastern Palearctic, in particular from the Russian Far East (RFE) (67.5%, 137/203) (Fig. 2a). In some cases, leaves were severely attacked, carrying up to 12 mines per leaf (as documented in the Russian Far East in 1930s–1960s). On the other hand, we found only 22 herbarium specimens with mines (10%; 22/225) from the putative invaded region in Western Palearctic, with the majority of herbarium specimens with mines (7% 15/225) from European Russia (Fig. 2b).Figure 2The presence of Phyllonorycter issikii mines in the herbarium specimens collected in the putative native (a) and invaded (b) ranges over the past 253 years (1764–2016). The number of herbarium specimens with and without mines and the percentage of the specimens with mines in each region or country from all herbarium specimens examined in a region or country (in brackets) are given next to each graph. The total number of herbarium specimens, including those with and without mines, is given for Eastern (a) and Western Palearctic (b) separately and altogether (a + b).Full size imageThe average number of leaf mines per herbarium specimen found in native (5.68 ± 0.77) and invaded regions (6.09 ± 1.70) was not significantly different (Mann–Whitney U-test: U = 20,145; Z = 0.43; p = 0.43). However, the infestation rate by Ph. issikii, i.e. percentage of leaves with mines per herbarium specimen was statistically higher in the West than in the East: 35% ± 8.19 versus 23% ± 1.94 (Mann–Whitney U-test: U = 1339; Z = 2.30; p = 0.02).Leaf mines from the East were significantly older than those from the West (Mann–Whitney U-test: U = 81; Z =  − 4.4; p  400 bp) were obtained for 71 archival specimens that were between 7 and 162 years old (Fig. 4, the points in dashed frame) (Table S4). Nine of these 71 specimens were over one century old (106–162-year-old): eight originated from the Palearctic and one from the Nearctic (Fig. 4, the points in gray cloud).In the Palearctic, the oldest successfully DNA barcoded Ph. issikii specimen (obtained sequence length 408 bp) was a 162-year-old larva dissected from the leaf mine on Tilia amurensis from the RFE (village Busse, Amur Oblast, the year 1859), sequence ID LMINH119-19 (Fig. 5, Table S5). In the Nearctic, the oldest sequenced specimen (obtained sequence length 658 bp) was 127-year-old larva of Ph. tiliacella on T. americana from USA, Pennsylvania (Fig. 5, Table S5).Figure 5A maximum likelihood tree of 81 COI sequences of Phyllonorycter spp. Overall, 71 archival sequenced specimens were dissected from herbaria collected in the Palearctic and the Nearctic in 1859–2014 and ten specimens (highlighted in blue) originated from the modern range20. The tree was generated with the K2P nucleotide substitution model and bootstrap method (2500 iterations), p  More

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Global patterns of ARG distributionWe used a set of 4572 metagenomic samples to illustrate the global patterns of ARG distribution (Supplementary Data 1). These samples were collected from six types of habitats: air, aquatic, terrestrial, engineered, humans and other hosts (Fig. 1a and Supplementary Data 1). From these samples, we identified a total of 2561 ARGs that conferred resistance to 24 drug classes of antibiotics based on the Comprehensive Antibiotic Research Database (CARD). Of these, 2401 were genes conferring resistance to only one drug class, and 160 conferred resistances to multiple drug classes (Supplementary Data 2). Twenty-five ARGs were found in more than 75% samples, however, the frequency of most ARGs (2313/2561) were More

Site descriptionIn 2012, a field experiment was conducted in the Aksu National Experimental Station of Oasis Farmland Ecosystem27 (40°37′ N, 80°45′ E, altitude 1028 m) (Fig. 1), located in the west of Tarim River Basin in Xinjiang Province, China. The experimental area had a typical temperate arid climate. During the study period (May to October), the average minimum and maximum temperatures varied between 16.7 and 34.8 ℃ respectively.Figure 1Location of the Aksu National Experimental Station of Oasis Farmland Ecosystem (the map was created by software: QGIS Version 3.16.15 LTR: URL, https://www.qgis.org/en/site/).Full size imageThe cotton fields where the experiment conducted were public land, belong to Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, China. With the permissions of Xinjiang Institute of Ecology and Geography, we conducted experiments in the cotton field of the Aksu National Experimental Station of Oasis Farmland Ecosystem.Experimental designTwo treatments, each 10 m × 10 m in size, were established on one of cotton fields at the Aksu National Experimental Station of Oasis Farmland Ecosystem on April 5, 2012.One treatment planting cotton with TC method, the other with MC method. For the MC method, a high-density and air-tight transparent polythene film (0.01–0.02 mm thick, 1.25 m wide) was placed over the soil surface before sowing. Small holes (0.02 m × 0.02 m, at 0.1 m intervals within a row) in the plastic film were made to place cotton seeds. Four rows were sown on each strip of plastic film. For the TC treatment, the plants were sown as that for the MC treatment. The planting density (266 667plant ha−1) and irrigation pattern (frequency and volume of irrigation) for the TC method were entirely consistent with those for the MC method.Half-hourly measurements of soil CO2 efflux, soil temperature and moisture were made on 6 June 2012. The whole experiment was completed on 4 November 2012. According to irrigation, the whole experiment can be divided into three stages: stage before irrigation (from 6 to 24 June), during irrigation (from 25 June to 10 October) and irrigation stop stage (from 11October to 4 November). During the irrigation period, we conducted seven times of irrigation (once in two week). The water-soluble compound fertilizer (N + P2O5 + K2O ≥ 51%) was used for fertilization in the experimental field, and the application rate was 30 g m−2. We dissolved water-soluble compound fertilizer in water and sprayed into the field by sprayer. During the irrigation period, the fertilizer was applied for 5 times.The cottonseeds we used in this study comply with the provisions of the regulations of the People’s Republic of China on Seed Administration and the detailed rules for the implementation of crop seeds. The fertilization we used in this study comply with the provisions of the People’s Republic of China on Chemical fertilizer standard. All the experiments we conducted in the cotton field of Aksu oasis farmland ecosystem National Experimental Station met the provisions of the agricultural law of the People’s Republic of China. We also carried out the experiment of this study under the guidance of the provisions of the measures for the administration of national field scientific observation and research stations.Field measurement of soil CO2 concentrationSolid-state CO2 sensors (GMM221 and GMM222, Vaisala, Finland) were installed in the midpoint of each treatment to measure soil CO2 concentration. A cable connected each soil probe with a transimitter body placed on the ground. The transimitter sent output signals from the probe to a data logger (CR1000, Campbell Scientific Inc., Logan, UT, USA) and to an optional LCC display on the transmitter.In each treatment, four CO2 concentration sensors were buried at depths of 0 cm, 5 cm, 10 cm and 15 cm. Soil CO2 concentrations were recorded once in 30 min. The measurement of soil CO2 concentrations were conducted from 6 June 2012 to 4 November 2012.On 8 November, these sensors were excavated and recalibrated in the laboratory. We found no change in the slope or offset.Environmental and soil CO2 efflux measurementsThe soil water content and temperature at the same soil depth with solid-state CO2 sensors were measured on the cotton fields at the Aksu National Experimental Station of Oasis Farmland Ecosystem27,28, respectively. Soil volumetric water content and soil temperature were measured using soil moisture probes (pF-Meter, EcoTech GmbH, Bonn, Germany)26 and temperature probes (PT100,Heraeus Sensor Technology, Kleinostheim, Germany)26, respectively.Bulk density was determined by core method29. Briefly, a cylindrical metal sampler (volume of 100cm3) was inserted into the soil and carefully removed to preserve the sample. The sample was oven-dried at 105 °C and weighed. The ratio between dry weight of the soil sample and the cylinder volume was applied to provide the bulk density.Half-hourly soil CO2 efflux measurements were conducted using a closed dynamic chamber method26 (CIRAS-1 PP Systems, Hitchin, UK) on the TC treatment, beginning on 6 June 2012. A chamber, with a diameter of 9.96 cm and a volume of 1, 170 cm3 was inserted into the soil at depth of 3 cm. Soil CO2 concentrations were measured by infrared gas analyzer. The collecting of CO2 from each sampling point took 120 s to get reliable estimates of soil CO2 efflux.Data analysisIn order to calculate CO2 efflux in soil, Fick’s first law of diffusion was used:$$F_{i} = – D_{s} frac{dc}{{dz}}$$
(1)
where Fi is the CO2 efflux at depth zi, Ds the CO2 diffusion coefficient in the soil, and dc / dz the vertical soil CO2 gradient. In this study, the vertical CO2 gradient (dC/dz) was approximately a constant at different depths of soil in our site for the field conditions experienced in the TC treatment during study period. However, a quadratic function of depth to concentrations fitted to soil CO2 concentration gradients in the MC treatment.Ds can be estimated as$$D_{s} = xi D_{a}$$
(2)
where ξ is the gas tortuosity factor and Da is the CO2 diffusion coefficient in free air. The effect of temperature and pressure on Da is given by$$D_{a} = D_{a} 0left( {frac{T}{293.15}} right)^{1.75} left( {frac{P}{101.3}} right)$$
(3)
where T is the temperature (K), P the air pressure (kPa), Dao a reference value of Da at 20 °C (293.15 K) and 101.3 kPa, and is given as 14.7 mm2 s–130 .There are several empirical models in the literature for computing ξ31. We used the Millington–Quirk model32:$$xi = frac{{alpha^{10/3} }}{{phi^{2} }}$$
(4)
where a is the volumetric air content (air-filled porosity), Φ is the porosity. Note,$$phi = alpha + theta = 1 – frac{{rho_{b} }}{{rho_{m} }}$$
(5)
where ρb is the bulk density, and ρm is the particle density for the mineral soil.Soil surface CO2 efflux was calculated using the CO2 gradient flux method based on CO2 concentrations within the soil profile1. Briefly, the flux of CO2 between any two layers in the soil profile was calculated using the Moldrup model33.In order to determine soil CO2 storage, the equation for CO2 was performed.$${S}_{C{O}_{2}}=frac{partial (aC)}{partial t}$$
(6)
where C (ppm) is the concentration of CO2 within the soil pores, (a) is the aerial porosity of the soil layer, D is the molecular diffusivity of CO2 with the soil, and S(µmol m−3 s−1)is the source strength in the soil layer at depth.We determined temperature responses for soil CO2 efflux using the van’t Hoff equation34 (Eq. 7);$$R = R0e^{BT}$$
(7)
where R is soil CO2 efflux, T is soil temperature (°C) at 10 cm depth, and R0 is the soil respiration rate at a reference temperature of 0 °C (µmol m−3 s−1).The Q10 value for Eq. (8) was calculated according to definition as:$$Q_{{{1}0}} = R_{{{text{T}} + {1}0}} /R_{{text{T}}} = {text{ e}}^{{{1}0{text{B}}}}$$
(8)
where RT and RT+10 are Rr or Rd rates at temperature T and T + 10, respectively. The Q10 value is independent of temperature in Eq. (8). More

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