2.1 Soil sampling
The soil, described in Obriot et al., (2016) as a luvisol with 11g/kg of organic carbon and pH 6.9, was sampled in January 2017 in the control plot of the experimental Qualiagro site (48°87’N, 1° 97’E 17). This agricultural plot is not contaminated with Cu (no registered inputs since more than 20 years).Its Cu content is around 12 mgCu.kg-1 consistent with the regional pedogeochemical background. Several fresh soil samples were pooled and immediately sieved at 5mm and stored at 4°C few days before building-up the microcosms to drive soil moisture regimes. Aliquots of this sieved soil were used to measure the fresh soil moisture at the time of sampling which was 15% and the field capacity as maximum water holding capacity (WHC) which was set up at 32% (w/w).
2.2 Experimental setup
To evaluate the impact of soil moisture on the sensitivity of nitrification to Cu toxicity, a two steps experimental approach was carried out: a first pre-incubation period of five weeks was running under different moisture stresses before application of a secondary metal contamination stress during a 72h bioassay allowing evaluation of the absolute and relative potential nitrifying activities).
a) Microcosms to drive soil moisture regime
Five microcosms of about 500 g of soil were incubated in five plastic boxes maintained half-open during 35 days and submitted to different treatments. Starting from the known initial moisture, three microcosms were set up at 30%, 60% and 90% of the soil WHC. This WHC was then kept constant by weighting and were made in order to roughly span respectively limiting, optimal, and close to water saturation treatments for the microbial activity. Later on, these three treatments will be called “30%, 60% and 90%”, respectively. The two others microcosms were incubated with variable WHC in order to simulate two kinds of drought and dry-rewetting cycles. One was left for about 3 weeks dry period without water inputs (gentle air drying) until 10% of the WHC before progressively rewetting at 60% WHC, while the other was treated with alternative cycles of one-week dry period (10% of the WHC by air-drying) followed by one week near-saturation period (90% WHC). Drying was performed by natural evaporation and moisture control by weighting. These two samples will be called thereafter “Drought” (DO) and “Dry-rewetting” (DR). The concentrations of N-NO2, N-NO3, N-NH4 and dissolved organic carbon (DOC) at the end of the pre-incubation period for the controls without added Cu and for each of the 5 moisture treatments are presented in table 1.
b) Bioassay to assess further Cu impact
After the pre-incubation period, the soil bioassays were immediately performed by measuring nitrate (NO3-) production rates over a short-term aerobic incubation in soil slurries (ratio soil:solution 1:6) with ammonium in excess and in the presence of gradients of Cu concentrations. The soil potential nitrification was then calculated on the basis of NO3- measurement over the time period. The PNA bioassays were adapted from the methods proposed by (Tom-Petersen et al., 2004). Briefly, 5 g of fresh soil (approximately 4.7g of soil equivalent dry weight), were mixed in a Falcon® tubes with 29mL of a 10 mM HEPES buffer solution (hydroxyethyl piperazineethanesulfonic acid, Sigma-Aldrich, France) to maintain a constant pH under Cu spiking and nitrification activity, and containing the substrate (NH4)2SO4 (3 mM) (Sigma-Aldrich, France). Then, 1mL of Cu solutions at different concentrations were added to reach final added Cu concentrations of 50, 100, 250, 500, 750, 1000 and 2000 mgCu. kg-1 soil. Controls with only Milli-Q® water (Millipore) were also performed. Three independent samples (n = 3) from each pre-incubation treatment were ran in three concomitant bioassays for each Cu concentrations. Following an initial horizontal shaking step (250 rpm, 10 min), the soil slurries were left incubated on a rotary shaker (150rpm), under aerobic treatments, at 25°C during 72h. After 10 min, 24 h and 72 h of incubation, 2 mL aliquots of the soil-solution mixture were transferred in Eppendorf® vials and centrifuged for 5 min at 13000 g at 4°C. The supernatants were collected and stored in microplates at – 20 °C until analyses of NO3- and NO2- by colorimetric determinations, following the reduction of NO3- in NO2- by vanadium(III) and then the detection of NO2- by the acidic Griess reaction (Miranda et al., 2001). Three different aliquots from each bioassay tube were analysed. Finally, the absolute value of PNA, aPNA in µg N-NO3 g-1 soil h-1, was calculated on the basis of N-NO3- + N-NO2- concentrations measured at the different time steps. The points Cu=0 allowed us to verify that NO2- contents were negligible (table 1), so that aPNA followed eq. 1, by checking the linear production rate between 2 h, 24 h and 72h:
Vs: Volume of solution
W: Weight of fresh soil
T: Time of incubation
For each moisture treatment, the relative PNA values, rPNA values in %, were calculated by dividing aPNA for each added Cu level by the aPNA without added Cu.
2.3 Statistical analysis for the different moisture treatment on Cu comparison
Data of aPNA values between the different moisture treatments were compared for each Cu level with the use of Kruskal Wallis test followed by a post-hoc Dunnett test. Adjustment of p-value for multiple comparison was made by Holm procedure to limit false negatives.
Dose responses curves for rPNA were analysed with the DRC package, following recommendations of (Ritz 2010; Ritz et al., 2015). For the dose responses curves fitted by the same functions, the parameters were compared using the compParm function of the DRC package (see 2.4).
ECx comparisons were made through the estimated confidence intervals (IC), so that for each ECx the moisture treatment with overlapping IC was not significant different.
All analysis were conducted using R v4.1 (R Core Team 2021).
2.4 Dose-response curves analysis
To fit the dose-response curves, we have proceeded by different steps according to our aims of both estimate and compare the variations in rPNA due to Cu contamination stress under the different moisture stresses. Expected results are to provide EC5, EC10, EC20 and EC50 values as % response (at 95% confidence interval) expressed as rPNA for each moisture treatment.
For the first aim, i.e. estimating the variations in rPNA, the selection of the best dose-response model able to fit the experimental data was achieved by testing the following widely used models in ecotoxicology studies (Ritz et al., 2015): the log-normal (LN) dose-response model, or the log-logistic (LL) and their Weibull derivative (W1 or W2), or the hormetic models as the Cedergreen models (CD, tested with alpha =1 and alpha=0.25), the Gompertz (G) model, or the Braincousens models (BC.4 or BC.5 depending of the number of parameters to be fitted). Lower asymptotes were fixed to 0 and upper to 1 except for the hormetic models.
For the second aim, we considered that the comparison of the dose response curves and their parameters as a whole between all the moisture treatments better required using a common model for all the curves, contrarily to ECx determinations that required more precise fits to extract ECx values. We thus compared the five best models per moisture treatment according to AIC and logLik criteria and confirmed the choices by visual confidence interval accordance (limited confidence interval). From these five pre-treatments x 5 models we looked for a common model. If no common type of model was found powerful enough to extract ECx values, we selected more types of models for these extractions.