domain: phys.cond chim spi

text:
Jean -Baptiste D'espinose De Lacaillerie

Fabien Barberon

Bruno Bresson

Philippe Fonollosa

Hélène Zanni

Vladimir E Fedorov

Nikolai G Naumov

Zhehong Gan

Applicability of natural abundance 33 S solid-state NMR to cement chemistry

Keywords: Sulfate, Sulphate, 33 S NMR

With the development of high-magnetic field spectrometers, 33 S solid-state NMR is now clearly feasible but remains complex, especially considering the low sensitivity of 33 S NMR. This communication briefly explores the potential of 33 S NMR in the field of cement chemistry. Based on a few significant examples such as the one of ettringite, whose sulfur NMR spectrum is reported here for the first time, it appears that 33 S solid-state NMR might be able to distinguish between the sulphates present in a cement paste taking advantage of both the chemical shift and the quadrupolar interaction.

Introduction

Sulphate solubility, chemistry, and reactivity are among the key elements needed for understanding the durability of cementicious materials. Several processes of the deterioration of cement matrices, such as delayed ettringite formation, can be interpreted in terms of sulphate-phase stability and sulphate ions' interactions with hydrates. Consequently, the development of spectroscopies able to probe quantitatively the local environment of sulphates inside a cement matrix appear as desirable experimental complements to theoretical attempts to model the evolution of cementitious materials with temperature and time. In particular, Raman spectroscopy has recently received attention as a tool able to distinguish the sulphate species according to the split and shift of the sulphate group vibration modes [1]. However, Raman spectroscopy of cement samples remains difficult to operate in a quantitative manner due to strong absorption and fluorescence at the Raman frequency range by the matrix. Moreover, significant overlap can be expected in complex hydrated materials. By comparison, NMR has the potential to provide quantitative information on the local environment of chemical groups regardless of the crystallinity and the nature of the matrix (provided it is diamagnetic). For this reason 29 Si and 27 Al NMR have been extensively used to study cement pastes. However, except for a few remarkable studies [2,3], until recently, the literature has remained silent on sulfur NMR. Indeed, 33 S NMR appeared out of reach in the solid state, mainly because of its low resonance frequency and reduced sensitivity due to its low gyromagnetic ratio (γ) (2.055 × 10 7 rad T -1 s -1 , that is less than 10% of the one of proton) and low natural abundance (0.76%) [START_REF] Smith | Advances in NMR[END_REF]. As highfield (> 17 T) spectrometers are now being serviced worldwide, the limitations associated with the low γ are expected to vanish, and it has been recognized that it is now time to revisit the potential of 33 S NMR to identify local structures of sulphides [START_REF] Wagler | [END_REF], sulphites [6], and sulphates [6,7]. Nevertheless, solid-state 33 S NMR is still clearly in its infancy as only one published study has gone beyond demonstrating feasibility and has actually applied the technique [6]. In order to explore more specifically this new potential in chemical systems relevant to cement science, we thus report and discuss here the feasibility of one-pulse, natural abundance 33 S solid-state MAS NMR spectra obtained at 63.6 MHz (19.6 T) for three bulk compounds representative of sulphate speciation in cement paste: magnesium sulphate, gypsum, and ettringite.

Materials and methods

Materials

MAS NMR

Magic angle spinning nuclear magnetic resonance (MAS NMR) experiments were performed at 19.6 T on a Bruker DRX spectrometer in 4 mm zirconia rotors at the NHMFL in Tallahassee (USA). 33 S (I = 3/2) one-pulse experiments were performed at 63.6 MHz, spinning between 6 and 8 kHz. For a quadrupolar nucleus, it was necessary to selectively excite the central transition in order to remain quantitative. This was performed by applying a pulse whose length correspond to a tilt angle of less than (2I+ 1), namely π/4 in the case of 33 S (I =3/2). Consequently, the pulse duration was 2 μs for a radio-frequency magnetic field strength corresponding to a precession frequency of about 45 kHz. The spectral width was 40 kHz with digital filtering. Numbers of acquisitions and recycle times for each sample are indicated in the relevant figure captions. The chemical shift was referred to the resonance of a 1 M Cs 2 SO 4 aqueous solution, taken as a secondary reference at 333 ppm from the primary standard of neat CS 2 . The central bands of the one-pulse spectra were fitted assuming a central transition second-order quadrupolar line shape using the DMFIT program [8].

Results

The natural abundance spectra of caesium [3,6,7], magnesium [7], and calcium sulphates [3,7] have already been reported in the literature and our results are presented here for comparison purpose only (Fig. 1). Our results are in agreement with the ones of Wagler et al. [7]. The fitting of the spectra with second-order quadrupolar line shapes produced a satisfactory estimate of the NMR parameters (Table 1). Of importance to the applicability to cement science, it must be noted that although high fields increase the signal-to-noise ratio due to a simultaneous increase of sensitivity and decrease of the quadrupolar line width, the overall sensitivity remained poor due to the low natural abundance of 33 S. The acquisition of the spectrum of bulk gypsum with a signal to noise ratio of 10 took a total of 8 h. Moreover, sulphate groups are about twenty times less abundant in Portland cement than in gypsum. Considering that the signal-to-noise ratio scales with the square of the number of scans, it follows that the acquisition of a signal of same quality in Portland cement would require 133 days. This is obviously impractical. Conversely, the acquisition of the spectrum of the 33 S enriched gypsum sample provided a signal to noise over 50 in 5 min. Obviously, 33 S NMR is not adapted to the characterization of field samples, and, without isotopic enrichment, would be limited to samples with exceptionally high sulphate contents or to fundamental studies of a chemical subsystem equilibrium. Besides sensitivity, to probe the potential of sulphur NMR, it is necessary to address its ability to discriminate between different sulphate speciations. On the one hand, the chemical environment of the sulphur atom in a sulphate group is not expected to vary greatly in one sulphate or another from the expected distorted tetrahedron of the sulphate anion. Indeed, all the sulphates studied here presented similar isotropic chemical shifts within 10 ppm. On the other hand, however, the secondorder quadrupolar line shape depends not on the electron density around the nucleus but on the electrical field gradient. It is therefore a very sensitive probe of the electronic symmetry around the nucleus, and thus indirectly of the lattice structure. Thus, for quadrupolar nuclei, the line shape often provides a clearer signature of a particular chemical occurrence than the chemical shift, and it can be related unequivocally to a particular structure through ab initio DFT-based calculations [9]. This conjecture was verified for cement chemical systems by comparing, as an example, the spectrum of the trisulphoaluminate ettringite with the one of gypsum (Fig. 2). The line shape of ettringite was significantly distinctive and clearly different from the one of gypsum. In particular, the symmetry of the sulphate group is not as severely distorted in ettringite [10] as in gypsum [11]. This translated in an asymmetry parameter (η) reduced from 1 in gypsum to circa 0.4 in ettringite and thereby in significantly different line shapes. The two sulphates could thus be distinguished despite having close isotropic chemical shifts: 328 ppm for gypsum and 331 ppm for ettringite. In this case, the quadrupolar interaction spread apart the maxima of each resonance by about 15 ppm in the present field of 19.6 T. There is a thus good prospect that it might be possible to distinguish sulphates in complex cement samples by 33 S solidstate NMR at high fields.

Conclusion

Despite the low natural abundance of 33 S, working at high field provided enough sensitivity to collect spectra in natural abundance for bulk compounds in a reasonable time. It is however clear that dilution of the sulphate in cements (typical values are less than 3% w/w SO 3 in CEM I Portland cement) will have to be compensated by enrichment if one intends to study cementitious matrices.

Despite this limitation, comparison of the gypsum and ettringite 33 S MAS NMR line shapes gave strong hope that the 33 S signature of sulphate groups will allow quantitative analysis of sulphate mineralogy in cement-related chemical systems. In that case, it might prove a useful complement to XRD or vibrational spectroscopy.

Cs 2

 2 SO 4 and MgSO 4 were purchased from Aldrich. Three gypsum (CaSO 4 •2H 2 O) samples were studied. Synthetic 90%+ enriched 33 S CaSO 4 •2H 2 O was precipitated from an enriched sulphate solution obtained by the oxidation of elemental 33 S with bromine. Reagent grade synthetic natural abundance 33 S CaSO 4 •2H 2 O was purchased from Aldrich. Mineral technical grade was courtesy of Soletanche-Bachy (France). Ettringite (Ca 6 Al 2 (SO 4 ) 3 (OH) 12 •26H 2 O) was courtesy of Dr. Divet (LCPC, France). The samples were ground to powder when necessary and used as such. XRD patterns were verified prior to NMR using a Philips X'Pert MPD diffractometer at the Cu K α radiation.

Fig. 1 .

 1 Fig. 1. Powder 33 S MAS NMR of sulphates. The one-pulse spectra were obtained at 63.6 MHz (19.6 T). The traces below the spectra are second-order quadrupolar models of the central transition adjusted to the experimental data using DMFIT and the NMR parameters reported inTable 1. Cs 2 SO 4 : 752 scans, 10 s recycle time. MgSO 4 : 30 000 scans, 200 ms recycle time. CaSO 4 •2H 2 O natural abundance: 1000 scans, 20 s recycle time. CaSO 4 •2H 2 O 33 S enriched: 16 scans, 20 s recycle time.

Table 1 33

 1

	S NMR parameters from lineshape fitting
	Compound	C Q (MHz) η Q δ iso (ppm) Line broadening
				(Hz)
	Cs 2 SO 4	0.8	0.45 335	200
	MgSO 4	2.1	0.15 315	200
	CaSO 4 •2H 2 O	0.7	1.0 328	30
	Ca 6 [Al(OH) 6 ] 2 (SO 4 ) 3 •26H 2 O 0.7	0.45 331	50


Rafael Lima Costa
email: rlimacosta@ufba.br

Aline Carneiro Viana

Artur Ziviani
email: ziviani@lncc.br

Leobino Nascimento Sampaio
email: leobino@ufba.br

Tactful opportunistic forwarding: What human routines and cooperation can improve?

Keywords: Human-centered computing, social computing, network architectures, Deviceto-Device (D2D) forwarding

Opportunistic D2D forwarding algorithms have leveraged human mobility characteristics to improve cost-effective content delivery. Most previous proposals focused on traditional or simplistic human-centered metrics to improve performance in scenarios such as cellular data offloading. Still, there is a need to approximate algorithm's metrics to inherent in-depth aspects of human mobility hidden into real datasets while leveraging more realistic scenarios interesting to mobile operators. This work proposes TOOTS, a novel human-aware opportunistic D2D forwarding strategy for cost-effective content delivery on cellular networks. TOOTS features a dissemination policy and a forwarding algorithm that leverages wireless encounters patterns, temporal, spatial, geographic, and direction awareness to improve costeffectiveness delivery. These characteristics are extracted from NCCU and GRM datasets. We compare TOOTS with the most popular state-of-art social-aware algorithm, Bubble Rap, combined with three dissemination policies. Results from TOOTS show increased performance in terms of delivery rate, delivery latency, and overhead.

Introduction

The advent of 5G wireless networks will drive new business models in nearly every vertical industry. Device-to-Device (D2D) communication and opportunistic forwarding are considered enablers of 5G [START_REF] Akyildiz | 5g roadmap: 10 key enabling technologies[END_REF] and 6G [START_REF] Zhang | Envisioning device-to-device communications in 6g[END_REF] network communication and, consequently, of emerging applications. They represent a new paradigm to offload traffic from wireless communication networks, which have attracted multiple research initiatives involving user participation [START_REF] Rebecchi | Data offloading techniques in cellular networks: A survey[END_REF]. D2D opportunistic forwarding algorithms tackled cost-effective and timely delivery of data [START_REF] Hui | Bubble rap: Social-based forwarding in delay-tolerant networks[END_REF][START_REF] Nunes | Combining spatial and social awareness in d2d opportunistic routing[END_REF]: that is, delivering as many contents as possible with less overhead and delay. In these scenarios, contents (or messages) are forwarded user-to-user, from source to destination in an opportunistic fashion (i.e., relying on user devices' intermittent connectivity).

Previous research discussed opportunistic networks' deployment to deal with networking performance challenges, such as traffic growth (e.g., through data offloading). Most initiatives focused on proposing algorithms and evaluating their metrics, but they still lack more evaluations with real traces to show opportunistic gain in real-world applications (i.e., in scenarios with more realistic settings). These algorithms typically consider users encounters and individual mobility [START_REF] Hui | Bubble rap: Social-based forwarding in delay-tolerant networks[END_REF][START_REF] Nunes | Leveraging d2d multihop communication through social group meeting awareness[END_REF][START_REF] Nunes | Combining spatial and social awareness in d2d opportunistic routing[END_REF], points of interest (PoIs) [START_REF] Nunes | Combining spatial and social awareness in d2d opportunistic routing[END_REF], and time-evolving social ties between node pairs [START_REF] Moreira | Opportunistic routing based on daily routines[END_REF]. Apart from that, not much was done to approximate the evaluation metrics to broader inherent aspects of human mobility while targeting QoE and QoS [START_REF] Costa | Towards human-aware d2d communication[END_REF]. There is thus a lack of initiatives beyond traditional techniques or limited human-mobility features to identify routines (spatiotemporal patterns), related consequences (e.g., wireless encounters), and movement decisions (e.g., motion direction) with more granularity and precision. This work focuses on metrics able to reflect human mobility features during periods of the day. Still, each population has particular habits that can change wireless contact dynamics [START_REF] Cuttone | Understanding predictability and exploration in human mobility[END_REF]. Therefore, such metrics must be evaluated throughout different populations, while spatiotemporal aspects must fit each population's habits.

In this work, we combine features extracted from a real-world and a synthetic dataset and apply them into a novel Tactful Opportunistic cOmmunicaTion Strategy (TOOTS). This strategy features a dissemination policy and a forwarding algorithm. In the former, users' spatiotemporal properties and induced wireless encounters are leveraged to choose content-disseminating nodes that have shown previous encounter routine with destination nodes. The forwarding algorithm relies on nodes' popularity, displacement, network-cell (as PoIs) visiting and proximity, and displacement direction.

In [START_REF] Costa | Towards human-aware d2d communication[END_REF], we presented and detailed the features of TOOTS, including mathematical formulations, and results from metrics characterizations using MACACO (a private European Dataset) [START_REF] Viana | Mobile context-Adaptive CAching for COntent-centric networking[END_REF]. In [START_REF] Costa | Towards human-aware d2d communication[END_REF], we discussed mobility datasets handling and characterization. The same methodology is applied here with different datasets. Conversely, the word tactful, which is part of the strategy's name, means having or showing skill and sensitivity in handling with people. In [START_REF] Costa | Tactful networking: Humans in the communication loop[END_REF], we discuss the Tactful Networking paradigm, whose goal is to add perceptive senses to wireless networks by assigning it with human-like capabilities of observation, interpretation, and reaction to daily-life features and associated entities. Our contributions with TOOTS are thus the following: -The TOOTS design combining human-aware metrics in a more granular and precise way than state-of-art to improve networking and system performance; -The comparison of the TOOTS effectiveness in each stage using a real-world and a synthetic dataset with state-of-art enhanced Epidemic and Store-wait-forward, and Bubble Rap alternatives; -TOOTS reaches 100% delivery rate with respectively 28%, and 73% less delivery latency, and with 16%, and 27% less overhead in the real-world and synthetic datasets. -The notion of going beyond traditional techniques when dealing with human-aware metrics to reach a superior system and networking performance. We also emphasize the need to evaluate such opportunistic strategies through more realistic scenarios and real datasets, incentivizing mobile network operators to deploy opportunistic networks more widely. The results mentioned above cope with [START_REF] Costa | Tactful networking: Humans in the communication loop[END_REF], which talks about the need to have a more in-depth look into human characteristics to build tactful networking solutions. The remainder of this work is organized as follows. Sec. 2 discusses related work. Sec. 3 presents the mobility models (datasets) used and motivates the strategy design. Sec. 4 discusses TOOTS, including its architecture, features, and algorithms for content-dissemination and forwarding. Sec. 5 presents the experimentation results, analysis, and discussions. Sec. 6 concludes this paper and points out future work.

Related Work

Over the years, different works extracted user mobility metrics to assist routing algorithms and opportunistic forwarding strategies. Due to the dynamic human mobility, choosing the nodes to forward the content is challenging.

In [START_REF] Hui | Bubble rap: Social-based forwarding in delay-tolerant networks[END_REF], authors introduced Bubble Rap, a distributed forwarding algorithm for delay-tolerant networks. The algorithm exploits centrality and community detection; characteristics remarked as less volatile than user mobility. Bubble Rap outperformed other state-of-art algorithms and is used as a benchmark with recently published research [START_REF] Nunes | Combining spatial and social awareness in d2d opportunistic routing[END_REF][START_REF] Tao | Contacts-aware opportunistic forwarding in mobile social networks: A community perspective[END_REF]. Despite its broad contributions, the major shortcomings relate to evaluations with small scenarios (available traces were below 100 nodes). Further, community detection algorithms are computationally expensive and require parameters calibration, which is not feasible in real-time D2D scenarios.

In [START_REF] Moreira | Opportunistic routing based on daily routines[END_REF], authors propose dLife, a forwarding algorithm relying on contacts duration and degree during daily hour periods. They capture the social behavior and interactions dynamism, resulting in improved delivery rate, cost, and latency. Like Bubble Rap, dLife was simulated through small traces. The evaluation setup and scenario are also a shortcoming (e.g., content size ranging from 1 to 100 kb).

In [START_REF] Nunes | Leveraging d2d multihop communication through social group meeting awareness[END_REF], authors introduced GROUPS-NET, an opportunistic algorithm that relies on social group meetings. GROUPS-NET requires a centralized computation of group-to-group paths whenever a given device wishes to send content to a destination. This requirement is challenging in larger populations. Furthermore, the algorithm is validated within two campus datasets, and other kinds of environments must be evaluated. In large-scale scenarios, they had a similar delivery ratio as Bubble Rap, but with reduced overhead.

In [START_REF] Nunes | Combining spatial and social awareness in d2d opportunistic routing[END_REF], the algorithm SAMPLER combines individual mobility, PoIs, and social-awareness for opportunistic routing. Despite showing improved delivery ratio, reduced overhead, and delivery latency, this work has a few shortcomings. The algorithm requires static relay points deployment and social community computations, which require parameters calibration. Second, there is a lack of details about the simulation scenario and parameters to turn possible reproducibility for comparison reasons. Finally, the evaluations need more realistic settings. For example, the authors considered any contact as enough to forward a message. Other parameters, such as message time-to-live and more realistic content-size, must be evaluated.

TOOTS positioning: From the related initiatives described herein, we consider that understanding human-behavior and context from mobility is important for networking solutions. Different from such studies, we use metrics with a more granular link with time. We focused on identifying different human activities during periods of the day. Through the dataset and our metrics analysis, we found that their coefficients vary according to the moment (period) observed [START_REF] Costa | Towards human-aware d2d communication[END_REF]. Considered human-mobility features are routines (spatiotemporal patterns), related consequences (e.g., wireless encounters), and movement decisions (e.g., motion direction). Metrics and insights based on generic aspects might not apply to all populations, so datasets of different kinds, and more users need to be evaluated. Facets such as node density, proximity, transportation mode, and even cultural factors can change contact dynamics. Therefore, temporal aspects and other characteristics must be chosen accordingly.

Rationale

Datasets description: We use the real-world NCCU trace [START_REF] Tsai | Nccu trace: social-network-aware mobility trace[END_REF], which features the displacements (given by GPS coordinates) of 115 users on a campus (3764 m × 3420 m) throughout two weeks. Additionally, we adopted the synthetic GRM dataset, which captures social regularity by human mobility [START_REF] Nunes | Grm: Group regularity mobility model[END_REF]. The GRM dataset has 1000 users displacements in a 1500 m x 1500 m area throughout two weeks and applies here to simulate a larger network (i.e., with more nodes). Overhead and Latency evaluation: In Fig. 1, we evaluate the Epidemic forwarding with a consumer set size equal to 1% of each dataset number of nodes. Note that 1% represents a limited number of consumers, which puts the Epidemic strategy in a challenging scenario. Depending on the strategy's kind and the datasets' characteristics, this can result in lower bound results for dissemination strategies, which will also be used in the TOOTS evaluation hereafter. Although mostly evaluated in the literature, we illustrate here the performance constraints related to the Epidemic forwarding algorithm using the two mentioned datasets. The Epidemic algorithm always tries forwarding a content to an encountered node that does not have it. In an opportunistic scenario, Epidemic forwarding is known as having smaller delays and a higher delivery ratio; however This is an Author Accepted Manuscript version of the following chapter: Rafael L. Costa, Aline C. Viana, Artur Ziviani, and Leobino N. Sampaio, "Tactful opportunistic forwarding: What human routines and cooperation can improve?", published in "Advanced Information Networking and Applications -Proceedings of the 35th International Conference on Advanced Information Networking and Applications (AINA-2021), Volume 3 , edited by Leonard Barolli, Isaac Woungang, Tomoya Enokido, 2021, Springer reproduced with permission of Springer Nature Switzerland AG. The final authenticated version is available online at: (to be updated when the link is available) Users may only view, print, copy, download and text-and data-mine the content, for the purposes of academic research. The content may not be (re-)published verbatim in whole or in part or used for commercial purposes. Users must ensure that the author's moral rights as well as any third parties' rights to the content or parts of the content are not compromised.

bringing a heavy network overhead burden. Source and destination nodes were chosen randomly with a content generation per hour during one full day. The experiments were carried 30 times, and so the confidence intervals are presented.

The Epidemic algorithm delivers the contents with an average latency of 2.6 and 3.6 hours, respectively, for NCCU and GRM. On those experiments, the delivery-rate was 100%, but with 98.44%, and 99.62% average network "infection" (overhead). The latter means that most network nodes became forwarders. For reaching such a delivery rate and small delivery latency, the network was flooded, which is not feasible in the real-world and is highly costly. Furthermore, one of the Epidemic Forwarding characteristics is a higher average of hops (i.e., intermediary nodes) for delivering the message. For example, in these experiments, there are 6.62 and 8.85 average hops respectively for content-delivery on NCCU and GRM. This characteristic brought an insight and motivation for our strategy, which is taking the content closer to the destination and try reducing the number of hops and so possibly the delay and overhead by combining rational dissemination with intelligent forwarding decisions. In the next section, we introduce TOOTS.

TOOTS Architecture and Strategy Description

TOOTS architecture: Fig. 2 describes the architecture for TOOTS. It features a mobile network owned by a cellular operator with an infrastructure of mobile edge computing (MEC) [START_REF] Mao | A survey on mobile edge computing: The communication perspective[END_REF]. In this MEC site, the operator stores contents commonly requested by its subscribers. The operator's goal is to offload content through opportunistic D2D communication, assuming the users are willing to cooperate through incentives (e.g., data plan savings). We assume the operator controls the offloading process, while the forwarding decisions happen in the user devices based on locally calculated metrics. TOOTS learns from users' mobility for seven days. Upon having a set of user requests for a given content, the operator runs our Tactful Dissemination Policy (TDP) (Sec. 4.1) to choose the disseminator nodes. In Fig. 2, we see two different contents offloading through the chosen disseminators. Subsequently, an algorithm (Sec. 4.2) runs locally (in the node) for taking a forwarding decision. TOOTS metrics: TOOTS combines a novel temporal approach described below with other insights into a Tactful Dissemination Policy (TDP)(Sec. 4.1); the other metrics herein described are combined into a forwarding algorithm (Sec. 4.2). Following, we resume these metrics, which are detailed (including mathematical formulations) and evaluated in [START_REF] Costa | Towards human-aware d2d communication[END_REF]. We discuss the intuitions behind the use of each metric in the descriptions of the algorithms.

-Temporal Approach: We divided the day into six non-uniform periods, with different durations. This decision is justified by associating the periods to the instants the population travels and has longer confinements (e.g., the period from 06:00 to 09:59 accounts for most individuals' Users may only view, print, copy, download and text-and data-mine the content, for the purposes of academic research. The content may not be (re-)published verbatim in whole or in part or used for commercial purposes. Users must ensure that the author's moral rights as well as any third parties' rights to the content or parts of the content are not compromised.

home-to-work displacement, while from 10:00 to 13:59 there is more confinement at work and smaller displacements on lunchtime). With this temporal division, the intention is to extract decision factors increasingly accurate and closer to the real human routines. In [START_REF] Costa | Towards human-aware d2d communication[END_REF], we show metrics coefficients heterogeneity per period in MACACO Dataset. The same phenomenon was observed here with NCCU and GRM, which reinforces our intuition. -Social Awareness Centrality Degree (C Dp (u)): Measures the social bonds of a user u in a period of the day p, that is, his number of encounters given a certain communication range. Someone with a higher degree is more "popular" (i.e., has further encounters). -Coverage Area Radius of Gyration (R Gp (u)): Quantifies in meters a user (u) individual mobility related to a center of mass, calculated from his movements in a period p. -Sojourn Time (ST c p (u)): Quantifies in hours a user's u stay in a network cell c in a period p. We divided [START_REF] Costa | Towards human-aware d2d communication[END_REF] the limited geographic space from each dataset into cells (original local operators' cells were too large) and calculated users' stay.

-Destination Proximity as Geographical Awareness (M P c p (u)): through a geodesic formula we calculate the maximum proximity a node u reached towards a cell c in a period p.

-Geographic Direction Awareness: analyzes the last 30 minutes of node mobility to determine if his displacement is towards a given cell.

1st TOOTS phase: TDP Policy

Herein, we detail our Tactful-Based Dissemination Policy (TDP). TDP (Alg. 1) chooses nodes based on their social behavior according to each time window. The intuition behind this is to start the offloading process with the content closer to their consumers. Following, we show how we apply the predictive regularity of user routines for choosing content disseminators. From the dynamic contact graph G t = (V, E p ), where V is the set of users (mobile nodes), and E p is the set of edges found at the period p of the week k. We assume that there is a logically centralized operator entity that, at the end of a week k, receives the following information from each one of its nodes u ∈ V : -(a): σ(u) p -the set of users v encountered by u in each period p.

-(b): ∆ C LIDp (u) -the average local improved centrality degree metric [START_REF] Thilakarathna | Design and analysis of an efficient friend-to-friend content dissemination system[END_REF] for a user u in a period p. This metric accounts for the number of contacts (i.e., encounters), considering their duration and earliness. With that said, higher coefficients belong to nodes with more contacts that had longer durations and happened earlier in a time window (i.e., in a period p).

Algorithm 1:

SelectDisseminators input : Gt, C, c, p output: D(c) 1 begin 2 D(c) ←-∅ 3 while C = ∅ do 4 let u ∈ V maximizing | |σp(u) ∩ C| |C| + ∆C LIDp (u)| 5 D(c) ←-u 6 C ←-C -σ(u) 7 end 8 Return D(c) 9 end
During the week k + 1, upon having a set of consumers C(c) ∈ V interested in a content c, Alg. 1 runs for choosing disseminator nodes. We justify the use of σ(u) p obtained at the week k by the fact that the policy tries to select nodes that had direct contact with the consumers, and due to their routines, they are most likely to repeat those interactions [START_REF] Oliveira | On the regularity of human mobility[END_REF]. We prioritize the direct contacts, i.e., higher proximity as they are most likely to repeat, possibly minimizing the spending of network and user device resources. Further, the C LID measures neighbourhood coverage capabilities through contacts and is used to identify the nodes' popularity in the network, This is an Author Accepted Manuscript version of the following chapter: Rafael L. Costa, Aline C. Viana, Artur Ziviani, and Leobino N. Sampaio, "Tactful opportunistic forwarding: What human routines and cooperation can improve?", published in "Advanced Information Networking and Applications -Proceedings of the 35th International Conference on Advanced Information Networking and Applications (AINA-2021), Volume 3 , edited by Leonard Barolli, Isaac Woungang, Tomoya Enokido, 2021, Springer reproduced with permission of Springer Nature Switzerland AG. The final authenticated version is available online at: (to be updated when the link is available) Users may only view, print, copy, download and text-and data-mine the content, for the purposes of academic research. The content may not be (re-)published verbatim in whole or in part or used for commercial purposes. Users must ensure that the author's moral rights as well as any third parties' rights to the content or parts of the content are not compromised.

giving importance to their contacts' duration and earliness. We use this metric because, in an opportunistic communication scenario, a contact that can transmit a message (i.e., the encounter lasts enough to send the data) earlier in the time window might decrease the total delivery latency. Furthermore, depending on the content size, choosing short contacts can waste node resources without proper message transmission.

Alg. 1 selects a set of disseminators D(c) for offloading a content c on period p. D(c) starts empty as the algorithm runs when there is a set of Consumers C requisitions for a content c. The policy selects (line 4) the user with the higher coefficient for the direct contacts with Consumers (σ p (u) ∩ C), normalized by C's size, summed with the ∆ C LIDp (u) (u's average C LID in p). The Consumers covered by u are then removed (line 6). In this way, we guarantee a next user u with similar coefficient for direct contacts do not get selected. Alg. 1 loops (line 3) until the consumer set is not fully covered (C = ∅). The policy assumes there are no isolated users in the traces. In Sec. 5, we evaluate the performance of the proposed dissemination policy with different sizes of consumer set (1%, 5%, and 10% of each dataset size).

2nd TOOTS phase: Human-Aware Forwarding

After the disseminator set D(c) for a content c is chosen, the operator sends the content to each node u ∈ D(c), for storing in its local buffer. From this moment, upon an encounter, any node carrying c runs Alg. 2 to decide on the next forwarding neighbor. The input is: the destination node d (that is, d ∈ C), the content c, the period p, the encountered node v, and l as the coordinates of d's cell. Each node stores the metrics coefficients locally by period p during the whole simulation, and a node u transmits c to v only if a certain algorithm condition is satisfied. First (line 2), if v already has c, u waits for the next encounter. Second (line 4), if v = d, (v is the destination), c is transmitted. The content is successfully sent if the edge e between u and v is persistent enough (there is no topology change causing a disconnection) until the time t necessary to transfer c.

2 if c ∈ v then 3 exit(0) 4 else if v = d then 5 v ←-c 6 else if v.cell = l then 7 if ∆C Dp (v) > ∆C Dp (u) then 8 v ←-c 9 else if ∆R Gp (v) > ∆R Gp (u) and ∆ ST l p (v) > ∆ ST l p (u) then 10 v ←-c 11 else 12 if testDirection(v, l) then 13 v ←-c 14 else if ∆ M P l p (v) < ∆ M P l p (u) then 15 v ←-c 16 end 17 end
As explained in Sec. 4, the geographic space was divided into cells. If v is at l (line 6), the nodes avg. centrality degree in the period p are compared. If v has a higher avg. CD, it means v met more nodes in p, so c is forwarded to v, given his higher capacity of dissemination inside that cell. In the contrary case (line 9), if ∆ RGp (v) > ∆ RGp (u) and ∆ ST cell p (v) > ∆ ST cell p (u), v is less "popular" (lower ∆ C Dp ) than u. Nevertheless, v can potentially cover a larger area inside the cell l (given his higher RG) and routinely stays longer in l (given his higher avg. ST). Hence, c is then forwarded to v (line 10). If v is not in l, his recent mobility in relation to l is checked. If the direction test This is an Author Accepted Manuscript version of the following chapter: Rafael L. Costa, Aline C. Viana, Artur Ziviani, and Leobino N. Sampaio, "Tactful opportunistic forwarding: What human routines and cooperation can improve?", published in "Advanced Information Networking and Applications -Proceedings of the 35th International Conference on Advanced Information Networking and Applications (AINA-2021), Volume 3 , edited by Leonard Barolli, Isaac Woungang, Tomoya Enokido, 2021, Springer reproduced with permission of Springer Nature Switzerland AG. The final authenticated version is available online at: (to be updated when the link is available) Users may only view, print, copy, download and text-and data-mine the content, for the purposes of academic research. The content may not be (re-)published verbatim in whole or in part or used for commercial purposes. Users must ensure that the author's moral rights as well as any third parties' rights to the content or parts of the content are not compromised. is true (line 12), i.e., v moves towards the aim and has the potential to reach or to get closer to l, c is sent to v. Finally, if the direction test is false, the avg. destination proximity is checked. If ∆ M P l p (v) < ∆ M P l p (u) , c is forwarded to v, meaning that node v got closer (or visited) l during p and it is more likely to repeat this behavior.

Experimentation Results and Analysis

As stated previously, the operator's goal is to offload content through opportunistic communication.

The contents consist of 60 seconds advertising videos with the average size of a YouTube 720P HD 30fps video, ranging from 11-14 MB. TOOTS learns from users mobility for seven days; one day is for content generation, with an offloading task started by the operator every hour, and three days are the delivery deadline [START_REF] Thilakarathna | Design and analysis of an efficient friend-to-friend content dissemination system[END_REF]. The consumers of each content are chosen randomly, with different consumer set sizes. The operator injects the contents on the network through their subscribers, who run a forwarding algorithm upon each contact. Every node has an 802.11/11 Mbps network interface. The communication range evaluated is 30 m (avg. for WiFi Direct). This scenario simulation is through the Opportunistic Network Environment (ONE) Simulator [START_REF] Keränen | The one simulator for dtn protocol evaluation[END_REF], with NCCU and GRM imported as mobility models. Each experiment was carried 30 times. The confidence intervals are calculated when necessary. This section evaluates the TDP policy only. For this, we modify two literature forwarding strategies, named store-wait-forward (a.k.a., direct delivery) and epidemic forwarding. This modification consists of using the dissemination-nodes given by the TDP policy as the starting content sources, executing then each of the literature strategies. Fig. 3 plots the performance of the TDP-enhanced store-wait-forward and epidemic forwarding. The store-wait-forward transmits the message only if the encountered node is the destination (consumer). In both traditional and TDP-enhanced versions, the store-wait-forward has zero overhead. Traditional epidemic had 98.44%, and 99.62% overhead, as shown in Sec. 3. On the other hand, the TDP-enhanced epidemic might get a comparable delivery rate and decreased delay. TDP-enhanced store-wait-forwarding has a potentially higher delivery rate and decreased delivery latency, as its success, though still depending on direct encounters, is improved by the TDP's initial content dissemination. Improvements might still take time (or never happen) depending on the source and destination social bonds.

TDP Results and Analysis

Fig. 3(a) reveals that combined with store-wait-forward, TDP induces an average delivery rate of 82% on NCCU and 75% on GRM, regardless of the number of consumers evaluated (1%, 5%, and This is an Author Accepted Manuscript version of the following chapter: Rafael L. Costa, Aline C. Viana, Artur Ziviani, and Leobino N. Sampaio, "Tactful opportunistic forwarding: What human routines and cooperation can improve?", published in "Advanced Information Networking and Applications -Proceedings of the 35th International Conference on Advanced Information Networking and Applications (AINA-2021), Volume 3 , edited by Leonard Barolli, Isaac Woungang, Tomoya Enokido, 2021, Springer reproduced with permission of Springer Nature Switzerland AG. The final authenticated version is available online at: (to be updated when the link is available) Users may only view, print, copy, download and text-and data-mine the content, for the purposes of academic research. The content may not be (re-)published verbatim in whole or in part or used for commercial purposes. Users must ensure that the author's moral rights as well as any third parties' rights to the content or parts of the content are not compromised.

-Random-Based Dissemination Policy (RDP): selects origin nodes randomly (i.e., working like the traditional Bubble Rap); -Centrality-Based Dissemination Policy (CDP): selects the higher centrality node as the origin; -Tactful-Based Dissemination Policy (TDP): proposed in Sec. 4.1. Selects the nodes with more direct encounters and higher C LID . In Fig. 4(a), we evaluate the delivery rate for both TOOTS and Bubble Rap on NCCU trace. TOOTS achieved a 100% delivery ratio and had the fastest delivery (90% of the contents delivered in up to 9 hours). Bubble Rap-CDP failed in delivering all contents, even in the NCCU's smaller population, which has overall high centrality degree nodes. Furthermore, using a CDP in the realworld is not feasible, as it creates a bottleneck and tends to drain the most "popular" users' devices resources. Bubble Rap-RDP reaches 100% of delivery ratio but is expected to show higher overhead (analysis to follow). Finally, Bubble Rap-TDP reaches a 100% delivery ratio but takes slightly more time to forward all contents successfully than TOOTS.

In the GRM trace (Fig. 4(b)), TOOTS delivers 100% of the contents, with an average of 97% in up to 12 hours. Bubble Rap-CDP shows an even worst delivery performance than in NCCU. That happens due to (i) communication bottlenecks, as there is a higher node density, and each node interface can transmit only one content at a time, and (ii) the fact that the GRM dataset has overall nodes with much lower centrality degrees. Bubble Rap-RDP delivers 100% but is also expected to show higher overhead (analysis to follow). Bubble Rap-TDP reaches close to 94% delivery ratio. This result can also be explained by GRM's lower centrality degrees (explanation to follow), calling for more time needed to reach 100% delivery ratio in Bubble Rap-TDP. In Fig. 5(a), we evaluate the delivery latency. TOOTS has the lower average delivery latency on both datasets, followed by Bubble Rap-RDP on NCCU and Bubble Rap-TDP on GRM. We remind that on GRM, only TOOTS and Bubble Rap-RDP reached 100% delivery rate in up to 72h. On GRM, Bubble Rap-CDP shows a much higher average latency, justified by the bottlenecks on the fewer higher centrality nodes, and by a dataset characteristic: from the content-generation time till the end of the simulation, over 90% of the nodes has low centrality degrees (up till 0.4). These dataset characterization results were not plotted as we focus on the full strategy proposal and its results.

Finally, in Fig. 5(b), we find the Bubble Rap-CDP with the smaller overhead on both datasets. On NCCU, this happens as the higher centrality degree node can find the destination directly for most of the contents generated. On the other hand, still, a bottleneck arises. Despite the lower overhead, Bubble Rap-CDP has a shallow delivery rate compared with the other proposals. The time windows used by Bubble Rap here also might be a reason for the slower delivery performance.

This is an Author Accepted Manuscript version of the following chapter: Rafael L. Costa, Aline C. Viana, Artur Ziviani, and Leobino N. Sampaio, "Tactful opportunistic forwarding: What human routines and cooperation can improve?", published in "Advanced Information Networking and Applications -Proceedings of the 35th International Conference on Advanced Information Networking and Applications (AINA-2021), Volume 3 , edited by Leonard Barolli, Isaac Woungang, Tomoya Enokido, 2021, Springer reproduced with permission of Springer Nature Switzerland AG. The final authenticated version is available online at: (to be updated when the link is available) Users may only view, print, copy, download and text-and data-mine the content, for the purposes of academic research. The content may not be (re-)published verbatim in whole or in part or used for commercial purposes. Users must ensure that the author's moral rights as well as any third parties' rights to the content or parts of the content are not compromised.

Bubble Rap-RDP presents the worst-case in terms of overhead. Compared with Bubble Rap-TDP, there is respectively 53% and 65% less overhead on NCCU and GRM. On the other hand, we must remember this combination does not deliver 100% of the contents on GRM when the deadline is up to 72h. Using other real datasets with larger populations would be interesting to evaluate this strategy. TOOTS is the fastest strategy able to deliver 100% of the contents on both datasets. Its overhead is respectively 10% and 17% smaller than Bubble Rap-RDP.

Conclusion and Future Work

Despite remarked as an enabler of future networking generations since 4G/LTE, opportunistic communications have not been widely deployed by cellular operators. In this work, we discussed a more realistic application scenario and introduced a human-aware opportunistic communication strategy named TOOTS. Compared to Bubble RAP and in both datasets (i.e., NCCU and GRM), TOOTS shows increased delivery performance and reduced delivery delay and overhead. Besides, TOOTS does not rely on complex communities calculation requiring parameter calibration. These characteristics make Bubble Rap challenging to be implemented in real-world scenarios.

Aiming for even better performance, future work related to TOOTS must focus on evaluating the involved decision factors individually. In particular, in the real dataset NCCU, TOOTS showed a better correlation with the leveraged human characteristics. The time-window proposal also made it possible to calculate more precise metrics reflecting the routine-based human mobility behavior at different daily periods.

There is still a lack of datasets with larger populations to be evaluated for real-world data offloading applications. We found that a dissemination strategy to inject the contents into the network is valuable in a scenario such as the one presented. Further, research must also evaluate the presented algorithm and other similar proposals regarding different contact-range, available bandwidth, variable content-size, and node energy constraints.

When it comes to human-aware metrics in the big data era, there is also a multitude of possibilities. Thus, future research shall invest efforts in proposing different metrics to identify human routines and social aspects. Finally, different application scenarios must be discussed so we can have a clearer idea of what opportunistic D2D communication will be able to do or enhance. Showing opportunistic gains in more realistic scenarios and innovative applications can motivate cellular network operators to invest more efforts in the context of human-centered networks.

Fig. 1 .

 1 Fig. 1. Epidemic Forwarding Average Delivery Latency Performance Evaluation.

Fig. 2 .

 2 Fig. 2. TOOTS Architecture.

Algorithm 2 :

 2 HumanAwareForwarding input : d, c, p, v, l output: A forwarding Decision 1 begin

Fig. 3 .

 3 Fig. 3. Tactful Dissemination Policy Average Delivery Rate and Average Delivery Latency Performance Evaluation.

Fig. 5 .

 5 Fig. 5. Delivery Latency and Overhead Performance Comparison of TOOTS, Bubble Rap-CDP, Bubble Rap-TDP, and Bubble Rap-RDP on NCCU and GRM datasets.

  This is an Author Accepted Manuscript version of the following chapter: Rafael L. Costa, Aline C. Viana, Artur Ziviani, and Leobino N. Sampaio, "Tactful opportunistic forwarding: What human routines and cooperation can improve?", published in "Advanced Information Networking and Applications -Proceedings of the 35th International Conference on Advanced Information Networking and Applications (AINA-2021), Volume 3 , edited by Leonard Barolli, Isaac Woungang, Tomoya Enokido, 2021, Springer reproduced with permission of Springer Nature Switzerland AG. The final authenticated version is available online at: (to be updated when the link is available)

Acknowledgements This work was supported in part by the FAPERJ, FAPESB, CNPq, CAPES, INCT-CiD, EMBRACE associate team Inria project, and ANR MITIK project (PRC AAPG2019).

10%). TDP enhancement assures choosing nodes with past direct encounters with the consumers, which favors the delivery rate increase. Compared with the traditional store-wait-forward, the TDP-enhanced average delivery rate with 1% of consumers was 18% higher on NCCU and 60% higher on GRM. In Fig. 3(a), as expected, the TDP-enhanced epidemic forwarding reaches 100% average delivery rate in all scenarios. Besides, the TDP enhancement favors the decrease of the average hop count of the traditional Epidemic forwarding.

In Fig. 3(b), we evaluate the average delivery latency. We see that regardless of the size of consumers set, the contents take on average 13h-15h to be delivered with TDP-enhanced storewait-forward on NCCU and 18h-19h on GRM, respectively. Thanks to the TDP policy, most of the delay-tolerant content is forwarded in an acceptable time [START_REF] Thilakarathna | Design and analysis of an efficient friend-to-friend content dissemination system[END_REF]. Compared with the traditional storewait-forward with 1% of consumers, TDP-enhanced reduced the average delivery latency by 23% on NCCU and 48% on GRM. As expected, when the forwarding is the enhanced epidemic, the average delay is smaller (18.6% less on NCCU and 64.5% less on GRM with 1% of consumers), but with comparable networking infection (overhead), which is unfeasible or very costly in real scenarios. From these findings above, we look for a forwarding algorithm able to increase the delivery rate with as lower as possible overhead and delivery latency. Finally, TOOTS (i.e., the full strategy) is evaluated in terms of delivery rate, delivery latency, and overhead within NCCU and GRM datasets. The chosen scenario is with random consumer sets with a size equal to 1% of dataset nodes (as used for the epidemic performance evaluation). TOOTS's performance is compared with Bubble Rap, the most popular social-based forwarding algorithm for delay-tolerant content. In Bubble Rap, each node gets a GlobalRank, and a LocalRank. The first measures the popularity in the whole network, while the second stores the popularity inside a community. Both centrality ranks are calculated with the C-Window technique, which measures nodes' popularity as the average number of unique nodes encountered throughout a time window of fixed length from the last 24 hours. Furthermore, Bubble Rap identifies social communities, and each node must belong to at least one. Given these metrics, the forwarding strategy transmits a content c carried by u to v when: v is the destination node (d); v has higher GlobakRank or belongs to d's community; v belongs to d's community and has higher LocalRank.

TOOTS forwarding Results and Analysis

We combine Bubble Rap with three dissemination policies responsible for injecting the contents into the network upon the start of the offloading process by the operator:

This is an Author Accepted Manuscript version of the following chapter: Rafael L. Costa, Aline C. Viana, Artur Ziviani, and Leobino N. Sampaio, "Tactful opportunistic forwarding: What human routines and cooperation can improve?", published in "Advanced Information Networking and Applications -Proceedings of the 35th International Conference on Advanced Information Networking and Applications (AINA-2021), Volume 3 , edited by Leonard Barolli, Isaac Woungang, Tomoya Enokido, 2021, Springer reproduced with permission of Springer Nature Switzerland AG. The final authenticated version is available online at: (to be updated when the link is available) Users may only view, print, copy, download and text-and data-mine the content, for the purposes of academic research. The content may not be (re-)published verbatim in whole or in part or used for commercial purposes. Users must ensure that the author's moral rights as well as any third parties' rights to the content or parts of the content are not compromised.


Serge Michalet
email: serge.michalet@univ-lyon1.fr

PhD Soraya Rouifed

Master Thomas Pelassa-Simon

IUT Manon Fusade-Boyer

Master Guillaume Meiffren

PhD, HDR Sylvie Nazaret

PhD Florence Piola

Keywords: Metallic trace elements, Fallopia spp. (syn. Reynoutria spp.), Plant performance 15 traits, Metabolite profiling, Plant secondary metabolites. 16 17

The expansion of invasive Japanese Knotweed s.l. is of particular concern because of its aptitudes to rapidly colonize diverse environments, especially anthropized habitats generally characterized by their pollution with heavy metals. Whether the presence of heavy metals impacts the performance traits of this plant is a central question to better understand its invasive properties, though no controlled approach to assess these effects were yet reported. In this aim, we undertook greenhouse experiments where rhizome fragments of Japanese Knotweed s.l. (Fallopia japonica and Fallopia x bohemica) were grown during 1 and 3 months, in soil pot artificially polluted or not with heavy metals added in mixture (Cd, Cr, Pb, Zn). Our results showed that (i) the presence of heavy metals delayed rhizome regeneration and induced lowered plant part weights but did not affect plant height after three months; (ii) the effect of metals on the metabolic profiles of belowground part extracts was only detectable after 1 month and not after 3 months of growth, though, it was possible to highlight the effect of metals independently of time and genotype for root extracts, and torosachrysone seemed to be the most induced compound; (iii) the hybrid genotype tested was able to accumulate relatively high concentrations of metals, over or close to the highest reported ones for this plant for Cr, Cd and Zn, whereas Pb was not accumulated. These findings evidence that the presence of heavy metals in soil has a low impact on Fallopia spp. overall performance traits during rhizome regeneration, and has a rather stimulating effect on plant growth depending on pollution level.

the Authors took into account the most of suggestion, however, in my opinion this report cannot be acceptable at this moment, because of the lack of some important data. The manuscript is dedicated to two invasive species of the Fallopia genus (Fallopia japonica and the hybrid -Fallopia x bohemica). In this study the results connected with heavy metals content in investigated plants are incomplete. The author did not shown the concentration of heavy metals in both species. In my opinion the heavy metals in Fallopia japonica should be done. It is important, because both taxa belongs to the most invasive plants in Europe. Therefore, I recommended to fill in the missing results.

Analysis were undertaken (in the same laboratory as for F. x bohemica) and showed that overall, F. japonica accumulate metals in the same ranges of what was found with F. x bohemica, though differences exist: In highly polluted conditions (M3 treatment) F. japonica accumulated more metals than the hybrid for all the metal tested tested in the study and in all plant parts except for Cd concentration in roots which was greater for F. x bohemica. It is also interesting to notice that, except for Zn, F. japonica accumulated very limited amounts of metals compared to F. x bohemica in the control M0 condition. Though, its translocation factor varies not much in the presence of high metal concentrations (from 3 to 5 for Cd and from 2 to 3 for Zn in M0 and M3 conditions respectively) compared to F. x bohemica for which the translocation factors of these two metals were even inverted with metal contamination (from 0,5 to 3 for Zn and from 0,1 to 1 for Cd).

According to this, modifications were made in the manuscript in the Material and Methods (lines 176-180 ), Results (lines 275-283) and Discussion (lines 311-314) of the revised manuscript. in soil pot artificially polluted or not with heavy metals added in mixture (Cd, Cr, Pb, Zn). Our 26 results showed that (i) the presence of heavy metals delayed rhizome regeneration and induced 27 lowered plant part weights but did not affect plant height after three months; (ii) the effect of 28 metals on the metabolic profiles of belowground part extracts was only detectable after 1 month 29 and not after 3 months of growth, though, it was possible to highlight the effect of metals 30 independently of time and genotype for root extracts, and torosachrysone seemed to be the most 31 induced compound; (iii) the hybrid genotype tested was able to accumulate relatively high 32 concentrations of metals, over or close to the highest reported ones for this plant for Cr, Cd and 33 Zn, whereas Pb was not accumulated. 34

These findings evidence that the presence of heavy metals in soil has a low impact on Fallopia 35 spp. overall performance traits during rhizome regeneration, and has a rather stimulating effect 36 on plant growth depending on pollution level. 37

Introduction 39

The increased prevalence of heavy metals in the environment, which is largely due to the 40 intensification of anthropogenic activities, is of particular concern because it affects living 41 organisms at the whole ecosystem level. Concerning plants, two main adaptive strategy may be 42 used to cope with an excess of heavy metals [START_REF] Baker | Accumulators and excludersstrategy in the response of plants to heavy 393 metals[END_REF]) : (i) exclusion which is the most 43 common strategy used, where metal concentration in shoots remains low and constant while 44 external concentration is varying, or (ii) accumulation where metal is more translocated in 45 shoots than in roots, with the distinction between indicators that concentrate metals at levels 46 close to that of soil and hyperaccumulators which are able to accumulate metals at very high 47 levels (van der Ent et al. 2013;[START_REF] Van Der Ent | Commentary: toward a 481 more physiologically and evolutionary relevant definition of metal hyperaccumulation in 482 plants[END_REF]. 48

In order to assess the effects of heavy metals on plants and better understand the molecular 49 mechanisms involved in plant tolerance to metal stress, omics tools have been used to 50 characterize stress-induced metabolites, phytohormones, transcription factors or proteins 51 [START_REF] Singh | Heavy metal tolerance in plants: role 455 of transcriptomics, proteomics, metabolomics, and ionomics[END_REF]), as well as key genes acquired during plant evolution conferring 52 hypertolerance [START_REF] Hanikenne | Metal hyperaccumulation and hypertolerance: a model for plant 421 evolutionary genomics[END_REF]. Among the metabolic changes occurring during 53 metal exposure, plant secondary metabolites like polyphenols have been quite less studied 54 compared to primary ones or plant hormones for example, at least qualitatively, and only an 55 induction of polyphenol biosynthesis of metal exposed plants has been reported in a few studies, 56 as recently reviewed by [START_REF] Singh | Heavy metal tolerance in plants: role 455 of transcriptomics, proteomics, metabolomics, and ionomics[END_REF]. Though, these compounds are well-known free-57 radical scavengers that protect cells from oxidative stress, they also possess strong metal 58 chelating properties, especially polymers like tannins, and they also act as molecular signals 59

involved in many plant biotic interactions from symbiosis establishment and insect visual 60 attraction to disease resistance [START_REF] Cheynier | Plant phenolics: recent 399 advances on their biosynthesis, genetics, and ecophysiology[END_REF]. This implies that the metal-induced 61 changes in plant polyphenol biosynthesis also probably affects plant biotic interactions, 62 especially in the root system which is directly exposed to metal toxicity and play a major role 63 in shaping rhizosphere microbial communities through root exudation (e.g. Michalet et al. 64 2013). Some authors hypothesised that this modulation of root exudates composition under 65 contaminant exposure might select for microbes that confer plant tolerance to the stress and is 66 referred to as the "plant call for support" theory (Thijs et al. 2016). Indeed plant-associated 67 microbes are believed to play a great role in plant adaptation to metallic stress and this area of 68 research has recently taken much attention, since it could be a way to drastically improve 69 phytoremediation [START_REF] Rajkumar | Perspectives of plant-associated 452 microbes in heavy metal phytoremediation[END_REF]Thijs et al. 2016). Plant-microbiome interactions are 70 also described as important drivers for the establishment of weed and invasive species (Trognitz 71 et al. 2016). Whether invasive plant species are positively influenced by soil metal pollution, at 72 least for those that are able to grow on metalliferous area, remains an open question that has 73 not yet been clearly examined in the literature. Indeed, metal-polluted environments like urban 74 or industrial settings are disturbed habitats where contaminants exert a strong selective pressure 75 which render them more prompt to biological invasions (i.e. the so-called "empty niche" theory, 76 as early stated by [START_REF] Elton | The ecology of invasions of animals and plants[END_REF]. 77

A well-known invasive species able to grow on metal polluted soil is the plants belonging to 78 the genus Fallopia (syn. Reynoutria, Polygonaceae) which includes two Asian herbaceous 79 perennial polyploid species (F. japonica and F. sachalinensis) and their interspecific hybrid F. 80

x bohemica, forming a polyploid complex of species, generally referred to as Japanese 81 Knotweed s.l. [START_REF] Bailey | Asexual spread versus sexual reproduction and 385 evolution in Japanese Knotweed s.l. sets the stage for the "Battle of the Clones[END_REF]). Because of their high performance traits [START_REF] Bailey | Asexual spread versus sexual reproduction and 385 evolution in Japanese Knotweed s.l. sets the stage for the "Battle of the Clones[END_REF]) 82 leading to dominance in the community, these species impact ecosystem functioning 83 [START_REF] Dassonville | Niche construction by the 402 invasive Asian knotweeds (species complex Fallopia): impact on activity, abundance and 403 community structure of denitrifiers and nitrifiers[END_REF]) and pose severe socio-economical issue in Europe and North America 84 as no conventional method to efficiently control their expansion is currently known. Actually, 85 the annual cost to control Japanese Knotweed is estimated to be of more than 1.5 billion £/year 86 only for Great Britain, representing one third of the total annual cost for alien weed management 87 [START_REF] Williams | The economic cost of invasive non-native species on Great 486 Britain[END_REF]. Their capacity to tolerate abiotic stress [START_REF] Rouifed | Invasive Knotweeds are highly tolerant to salt 475 stress[END_REF] and their 88 strong competitive aptitudes allow them to rapidly colonize various environments. They mainly 89 spread by rhizome (or stem) regeneration through vegetative reproduction, though the hybrid 90 is also able to produce seeds and back-crosses with parental species (Bailey et al. 2009, 91 Soltysiak and[START_REF] Sołtysiak | Characteristics that make the Fallopia genus (Polygonaceae) highly 465 invasive[END_REF][START_REF] Groeneveld | Sexual reproduction of Japanese Knotweed[END_REF][START_REF] Gaskin | 408 Extreme differences in population structure and genetic diversity for three invasive congeners: 409 knotweeds in western North America[END_REF]. The later (F. japonica 92 and F. sachalinensis) are native to Eastern Asia including volcanic areas presenting very high 93 metallic trace elements concentrations in soil: actually more than 90 and 9000 mg/kg of Cd and 94 Zn were respectively found in metalliferous site of Japan where these species naturally grow 95 [START_REF] Nishizono | Accumulation of heavy metals in cell walls 443 of Polygonum cuspidatum roots from metalliferous habitats[END_REF]. This may in part explain why they are mainly found in anthropized 96 environments like railroads or industrial and urban areas, and that these disturbed habitats seem 97 to promote specifically their expansion (Soltysiak and Brej, 2012;Soltysiak and Brej, 2014). 98 Japanese knotweed s.l. are able to accumulate metallic trace elements and the ability to 99 concentrate toxic metals in plant parts of these species has been extensively studied, but 100 exclusively from field measurements (e.g. Soltysiak et al. 2011;[START_REF] Rahmonov | Chemical composition of 471 the leaves of Reynoutria japonica Houtt. and soil features in polluted areas[END_REF]Širka 101 et al. 2016). Most of these studies reported higher amounts of metals accumulated in 102 underground parts of the plant but no clear correlations between a rather accumulated type of 103 metal or relationships between soil concentrations and plant metal accumulation could be made 104 from these studies due to the variability of the published values. 105

Facing this, controlled studies need to be developed in order to better understand the impact of 106 the presence of metals in soils on Japanese Knotweed s.l. performance traits, especially during 107 vegetative propagation. In this aim we undertook greenhouse experiments, where rhizome 108 fragments of genotypes of Japanese Knotweed s.l. were grown during one and three months 109 respectively, in soil pot artificially polluted or not with heavy metals in mixture (Cd, Cr, Pb, 110 Zn) at three different concentrations from faintly polluted to highly polluted soils respectively. 111

These metals were chosen because they are among the main pollutants generated by anthropic 112 activities and are often found in urban soils, and also because two of them are essential trace 113 elements (Cr and Zn), whereas the two others are toxic to most organisms (Cd, Pb). To assess 114 if performance traits were impacted, the growth kinetic as well as final plant part dry weights 115 were recorded. A metabolic profiling approach on belowground plant parts (roots and rhizomes 116 separately) and based on UV-absorbing compounds was also achieved in order to target more 117 specifically phenolic and other aromatic compounds that might be induced during metal stress. 118 119

Materials and Methods 120

Greenhouse experiments settings 121

Two independent microcosm experiments of one month and three months respectively were 122 conducted in greenhouse. For the one month experiment which occurred between February and 123

March 2014, a loamy Luvisol (WRB, 2006) continuously cropped with maize and collected at 124 La Côte Saint-André (Isère, France) possessing the following characteristics: sand 37.5%; loam 125 42.7%; clay 19.8%; OM 2.23%; pH 6.4; CEC: 8.79 cmol.kg -1 and exempt of heavy metal 126 pollution, was sieved (2 mm mesh size) and rehydrated to its field capacity (28% m/v) by adding 127 either Ultra-Pure water (UP) (control, M0) or a solution containing Cd, Cr, Pb and Zn (added 128 as chloride salts) at concentrations close to common recognized soil pollution threshold (M2 129 treatment; [START_REF] Baize | Analyses totales et pseudo-totales 389 d'éléments en trace dans les sols. Principaux résultats et enseignement d'une collecte nationale[END_REF], ten times lower (M1 treatment) or ten times higher (M3 treatment) 130 and summarized in Table 1. Then 200 g of moistened soil were placed into 0.3 L plastic pots 131 and rhizome fragments of 2 genotypes of Japanese Knotweed s.l. (F. x bohemica or F. japonica) 132 were planted. These rhizome fragments were obtained from individuals morphologically 133 identified (F. Piola, personal communication) using leaf shape and size [START_REF] Bailey | Asexual spread versus sexual reproduction and 385 evolution in Japanese Knotweed s.l. sets the stage for the "Battle of the Clones[END_REF] and 134 collected from the field on the riverbanks of the Suran river (Ain, France) for F. x bohemica 135 and on the riverbanks of the Valencizes river (Rhône, France) for F. japonica and that were 136 acclimated for more than a year to greenhouse conditions in order to avoid any "mother effect". 137

For each treatment, five budding rhizome fragments from each genotype were cut into pieces 138 (average weight of 0.7 ± 0.1 g), planted in soil and grown in greenhouse (13h day 22°C/11h 139 night 18°C) with light intensity of about 8-10 klux. Soil moisture was manually controlled by 140 adding water every three days. For the three months experiment which occurred between 141 January and March 2015, the same procedure was repeated but with modifications concerning 142 the amount of soil added in pots (600 g in order to allow the plant to grow for three months; 143 0.75 L pots). Metal concentrations were also modified because of the absence of regeneration 144 of rhizome for the initial M3 dose chosen in the one month experiment, and in order to keep 145 roughly an order of magnitude of difference between each treatment. Concentrations were 146 approximatively divided by two for M1 and M2 treatments and by three for M3 treatment 147 (Table 1). 148

Growth traits 149

For the three months experiment, during growth, the height of each plant was notified three 150 times a week by measuring the distance between topsoil and the highest photosynthetic part of 151 the plant. At the time of collection, plants were carefully excavated from soil, and roots were 152 rinsed with tap water. Aboveground parts (stems + leaves) were separated from belowground 153 parts (rhizome + roots) and both were immediately frozen in liquid nitrogen and freeze-dried 154 before being weighed. 155

Metabolite profiling of belowground parts 156

For both experiments, after freeze-drying fine roots were separated from rhizomes, and about 157 100 mg of each were grounded (TissueLyserII® -Qiagen; F= 300/sec., 3 min.) and sonicated 158 with a 1 mL mixture of MeOH-H2O (1:1) for 15 minutes. After the supernatant was removed, 159 the remaining powder was sonicated with 1 mL MeOH and both supernatants were pooled and 160 concentrated under vacuum (Speedvac® -Labenco) before being dissolved at 10 mg/mL in 161 MeOH 80% and stored at -20°C before analysis. 162

Samples were analysed by UHPLC-DAD ESI-QTOF (Agilent 1290 infinity linked with Agilent 163 QTOF 6530), using poroshell 120 EC-18 column (2.7 µm, 3.0 x 100 mm, Agilent) with a 164 gradient of 0.1% formic acid in water (A) and acetonitrile (B) as follows: 1% of B from 0 to 165 1.5 min, and growing with a linear gradient to 15% of B at 8 min ; 60% of B at 14 minutes and 166 100% of B at 16 min for 1 min. All solvents were LC-MS grade (Optima). The flow rate was 167 adjusted at 1.2 mL/min and the injection volume was 2 µL. UV spectra were recorded between 168 190 and 600 nm. The ESI source was optimized as follows: positive ionization mode, scan 169 spectra from m/z 100 to 2000, capillary voltage 3.5 kV, fragmentor 120 V, fixed collision-170 induced dissociation (CID) energy at 20 eV. Nitrogen was used as the nebulizing gas with a 171 flow rate of 12 L/min and a temperature of 310°C at 40 psi. 172

Compounds were identified by analysis of their UV, HRMS and MS/MS spectra using 173

MassHunter Qualitative Analysis (Agilent Technologies, USA) 174

Heavy metal contents in plants and soil 175

Metal content in soil (three biological replicates of F. x bohemica rhizosphere soil) was 176 analysed by ICP-MS at the CRPG of Vandoeuvre-les-Nancy and metal content in plant parts 177 was analysed by ICP-MS (and ICP-radial for Zn) by USRAVE (INRA-Centre de Bordeaux ; 178

CoFrac-certification n°1-1838). Three replicates of both F. x bohemica and F. japonica 179 growing in M0-and M3-treatments were analysed 180

Statistical analysis 181

Growth traits 182

Individual plant heights measured during the three months experiment were analysed with a 183 dose/response model (package drc, [START_REF] Knezevic | Utilizing R software package for dose-response 427 studies: The concept and data analysis[END_REF]). Data obtained from both genotypes 184 tested were pooled because they did not differ significantly. 185

Concerning plant part dry weights, differences between treatments, genotypes and the 186 interaction between the two factors were analysed using variance analysis (ANOVA) on 187

RStudio software (version 3.2.2). 188 days, p<0.001). However, plants treated with M2 concentration reached the highest height (11.6 214 cm), not significantly different from plants with M3 concentration (10.9 cm, p= 0.155), but 215 significantly higher than plants in M0 and M1 concentrations (10.3 cm, p < 0.001 and 10.4cm, 216 p < 0.001, respectively). 217 F. x bohemica had significantly higher aboveground (F = 4.76, p = 0.035) and belowground (F 218 = 5.32, p= 0.026) weights than F. japonica after 3 months of growth. However, the genotype 219 did not influence the response of plants to the metal treatment (interactions genotype x 220 treatment non significant). Control plants (M0) showed significantly higher aboveground (F = 221

Metabolite profiling 189

Metabolite profiling of belowground parts 226

PCA based on metabolic profiles obtained from rhizome and root extracts after one and three 227 months of growth (Fig. 3 & Fig. 4 respectively) allowed in each case to distinguish both 228 genotypes tested along axis 1, except for root extracts at 3 months for which this distinction 229 was made along axis 2 (Fig. 3A, 3C & Fig. 4A,4C). The effect of metal treatments was 230 detectable for both plant parts after one month of growth since M2-treated plants were relatively 231 well separated from M0-treated plants along axis 2, and this was especially true for roots (Fig. 232 3B, 3D). Since the M3 treatment chosen in the one month experiment was too toxic to allow 233 rhizome regeneration, no data could have been obtained from this group which is then lacking 234 in the PCA. After three months of growth, it was not possible to distinguish any of the metal 235 treated groups from the control (Fig. 4B,4D). 236

In order to better characterize the effect of metal pollution on plant belowground metabolites, 237 biological replicate extracts of both plant parts were pooled according to time, genotype and 238 metal treatment, leading to 14 new pooled samples which underwent the same chromatographic 239 analysis and data treatment procedure (Fig. 5). This allowed for both plant parts to distinguish 240 the effect of time which was mainly explained by axis 1 (Fig. 5A,5D), from that of genotype 241 which was mainly explained by axis 2 (Fig. 5B,5E). It was also possible to discriminate metal 242 treated groups along axis 3 but this was only the case for root extracts (Fig. 5F) and not for 243 rhizome extracts (Fig. 5C), even when considering lower eigen values. 244 One of the compound for which the proportions were the most increased with metal 245 concentrations and strictly explaining axis 3, was identified as torosachrysone, a 246 dihydroanthracenone derivative, by comparing its UV, HRMS and MSMS spectra with 247 literature data (Fig. 6). Other anthracene derivatives including anthraquinone and dianthrones 248 were also found to be increased in their proportions in root extracts at one and three months 249 (data not shown). 250

Heavy metal contents in soil and plant parts of F. x bohemica 251

The content of metallic trace elements in M3-treated soil after the three months experiment was 252 relatively close to the theoretical concentrations expected (i.e. resulting from the artificial 253 contamination of soil experimented in this study) for Cd (7.2 ± 0.5 mg/kg vs 5.5 mg/kg in 254 theory), Cr (332.0 ± 39.2 mg/kg vs 440.0 mg/kg in theory) and Zn (923.7 ± 70.5 mg/kg vs 880.0 255 mg/kg in theory), whereas for Pb, the measured concentration was approximatively divided by 256 three compared to its theoretical concentration (95.9 ± 8.3 mg/kg vs 295.0 mg/kg in theory) 257 (Fig. 7 and Table 1). 258

The control soil M0 that received no metallic treatment showed low heavy metal concentrations 259 as expected, in the range of what is naturally found for this type of soil, and could thus be 260 considered as non-polluted. 261 F. x bohemica accumulated metals even if no artificial pollution was added (i.e. M0-treatment; 262 Fig. 7A-D-left), and especially in underground parts: similar contents than those found in soil 263 were actually measured for Cr and Zn (Fig. 7B and 7D respectively). In contrast Cd was 264 accumulated approximatively five times more (Fig. 7A) and Pb six time less (Fig. 7C). These 265 metals did not seem to be translocated to aerial parts in these conditions since metal 266 concentrations were very low and close to the limit of quantification for Cd, Cr and Pb. 267

When artificial metallic pollution was added at the highest concentration tested (i.e. M3-268 treatment; Fig. 7A-D In this study we assessed the effect of an artificial polymetallic pollution of soil on Fallopia 285 spp. performance, and more precisely its impact on rhizome regeneration and growth occurring 286 in the early stages of vegetative propagation, as well as its impact on belowground secondary 287

metabolism. 288

Our results showed that the presence of heavy metals in soil induced a delay for plants to reach 289 half of their maximal height, delay that was more pronounced with high metal concentrations. 290 Though, after three months of growth, plant final height of both genotypes was not impacted 291 by metal pollution and it was even significantly greater for M2-treated group compared to 292 control. This implies that plant growth speed was higher when metals were present. The 293 observed delay in rhizome regeneration induced by metallic pollution could be correlated with 294 the fact that metabolic changes in belowground parts of the plant were only observed after one 295 month of growth and not after three. This suggests that the delay in rhizome regeneration 296 induced by the presence of metals is due to plant investment in the production of secondary 297 metabolites rather than in primary metabolites needed for cell and tissue multiplications (as 298 demonstrated in the "grow or defend" theory; [START_REF] Herms | The dilemma of plant: to grow or defend[END_REF]. It also correlates with 299 the fact that lowered plant part weights were measured in metal-treated groups. One of the plant 300 growth traits affected by metal treatment was belowground part weight which was reduced 301 when metals were added at high concentrations suggesting a toxic effect. On the other hand, 302 aerial parts were not affected by these treatments indicating that this plant shows an overall 303 good tolerance to metal stress regarding the concentrations added. The fact that aerial part 304 weight was affected with low doses of metals (i.e. M1-treatment) reveals that this plant might 305 be very sensitive to soil metal concentrations. 306

Concerning plant metal accumulation, the reported values of this study are in the range of the 307 highest published, except for Pb which was not accumulated and Cr which was found at 308 concentrations up to three times more than those reported in underground parts and up to ten 309 times in aerial parts (Fig. 6 and Table 2). The fact that Cr was present at concentrations up to 310 8 times higher in soil may explain in part these results. Of particular interest is the fact that Zn 311 and Cd translocation factors were increased in the case of F. japonica and even inverted in the 312 case of F. x bohemica with Cd and Zn, when plants were exposed to high metal concentrations, 313 suggesting a change in plant nutritional strategy. Although these observations are interesting 314 for the potential valorisation of this plant in phytoremediation of contaminated sites, caution 315 must be taken for the extrapolation of these results to what occurs in situ, since we only worked 316 on young shoots which may accumulate more than old ones, and as stressed by Van der Ent et 317 al. (2012), these types of controlled-approaches have very limited relevance in explaining what 318 occurs in natural environment although the polymetallic contamination applied in our study is 319 probably closer to what happens in urban ecosystems for example. In all cases further 320 mesocosm and field studies are required to confirm the results obtained. 321

The consequences of metal accumulation in the plant and its relative high tolerance and 322 sensitivity to polymetallic stress let us hypothesize that these traits may serve the plant to 323 rapidly colonize diversely polluted environments, where other plant species might be excluded 324 because of the presence of metals in soils. Herbivory may also be limited because of metal 325 accumulation in plant aerial parts which may have a repellent effect on predators (especially 326 young shoots that may be more prompt to herbivory attacks; [START_REF] Price | The plant vigor hypothesis and herbivore attack[END_REF]. The molecular 327 mechanisms involved in metal tolerance remain to be elucidated, though the metabolic profiling 328 approach undertook in this study might bring some clue about the secondary metabolites 329 directly or indirectly involved in metal tolerance. Torosachrysone was identified as one of the 330 compound for which the relative proportions were the most increased in roots with metal 331 concentrations, this independently of plant age or genotype. To our knowledge this is the first 332 report of this compound in this genus. It has been described to be involved in anthraquinone 333 biosynthesis [START_REF] Abdel-Rahman | In vitro formation of the anthranoid scaffold by cell-free extract from yeast-382 extract-treated Cassia bicapsularis cell cultures[END_REF], compounds that are well known in Fallopia spp. 334 [START_REF] Piola | Invasive 446 Fallopia × Bohemica interspecific hybrids display different patterns in secondary metabolites[END_REF], and that have also been characterized with higher relative proportions in 335 metal-treated plant roots in this study (data not shown). The exact role of torosachrysone in 336 metal tolerance and/or accumulation is still to be elucidated but from the results of our study, it 337 seems to be well involved directly or indirectly in plant adaptation to metallic stress. Following 338 the "plant call for support theory" emitted by Thijs et al. (2016), this compound could have an 339 impact on the selection of rhizosphere microbes possessing the ability to improve plant 340 tolerance to metallic stress. Further experiments including field studies should be conducted in 341 order to confirm these findings, for example the correlation between torosachrysone content in 342 roots and heavy metal content in plant or soil collected in situ could be interesting to analyse. 343

The production of torosachrysone by fungal strain has also been reported [START_REF] Gill | Pigments of fungi (Macromycetes)[END_REF]Müller et 344 al. 2004) leading to the hypothesis that this compound might be produced by fungal endophytes. 345

The presence of such associated microbes has recently been shown in this plant through the 346 identification of Dark Septates Endophytes (DSE) microsclerotia colonizing roots (Gucwa-347 Przepióra et al. 2016). These fungal endophytes, which are characterized by their melanised 348 and septate hyphae, are frequent associated root endophytes of herbaceous plants. They have 349 been described as important determinants influencing plant tolerance to heavy metal stress 350 because they are able to tolerate high concentration of metallic trace elements, notably through 351 the increase of melanin which enables to decrease metal toxicity [START_REF] Ban | The response of Dark Septate 396 Endophytes (DSE) to heavy metals in pure culture[END_REF]. Whether 352 these micro-organisms play a role in Fallopia adaptation to heavy metal stress remains to be 353 confirmed, but the findings of our study in the light of recent literature on the subject let us 354 suggest that it is the case. 355 356

Conclusion 357

To conclude, our findings evidenced that the presence of toxic metals in soil had a low impact 358 on Japanese Knotweed s.l. overall performance traits during vegetative propagation, and had a 359 rather stimulating effect on plant growth depending on pollution level: 360 -the presence of metal in soil induced a change in plant belowground secondary metabolism 361 which only occurs at early stages of plant vegetative propagation and this might be correlated 362 with the observed metal-induced delay in rhizome regeneration and with lowered plant part 363 weights under metal stress. 364 -on the other hand the fact that plant final height was not affected (or even increased at some 365 concentrations), and that plant metal accumulation and nutritional strategies were modified 366 depending on metal concentrations in soil, might suggest that this plant is very sensitive to the 367 presence of metal in soil and that it may explain, at least in part, its capacity to rapidly colonize 368 anthropized metal-polluted environments. All these results need to be confirmed with further 369 in situ studies and/or controlled mesocosm studies using naturally polluted soils. 370 371

Figure 6 a

 6 a , Rouifed Soraya b , Pellassa-Simon Thomas a , Fusade-Boyer Manon b , Meiffren 4 Guillaume a , Nazaret Sylvie a & Piola Florence b 5 Université de Lyon, Université Claude Bernard Lyon1, CNRS, UMR 5557, INRA, UMR 7 1418, Ecologie Microbienne, F-69622, Villeurbanne, France. 8 b Université de Lyon, Université Claude Bernard Lyon 1, ENTPE, CNRS, UMR 5023 LEHNA, 9 F-69622, Villeurbanne, France. 10 11 12

  Peak areas were normalised by using relative values, i.e. percentages of each compound in the 190 chromatogram. PCA (Principal Component Analyses) were performed using R studio software 191 with "ade4" package. The compounds showing variations in their proportion between 192 treatments were analysed using ANOVA, followed by a Tukey-HSD test. All tests were done 193 in respect with the rules of normality and homoscedasticity assumptions. 194 For the one month experiment, 26 samples were analysed giving 80 peaks for rhizome extracts 195 and 114 peaks for root extracts, whereas for the three months experiment, 42 samples were 196 analysed with 107 peaks for rhizome extracts and 101 peaks for root extracts. 197 In order to compare the one month and three months experiments together, all extracts obtained 198 during both experiments from the different biological replicates were pooled according to time 199 of collection, treatment and genotype (giving 14 pooled extracts for roots and rhizome 200 respectively) and analysed with the same procedure of chromatography and data treatment (62 201 peaks analysed). As metal levels of both experiments were of the same order of magnitude data 202 were pooled in one single matrix. function of time and treatment is presented in Figure 1. Data obtained for both 207 genotypes were analysed together because their response did not differ significantly. Pairwise 208 comparison of parameters of the Log logistic model between treatments showed that 209 concentration of metals affected growth of plants during time: the higher the concentration of 210 metals, the later the plants reached 50% of their maximal height. Plants in M0 and in M1 211 treatments reached half of their height in 19 days. Plants in M2 treatment reached half of their 212 height 6 days later (25 days, p <0.001), and plants in M3 treatment needed further 5 days (30 213

  2.95, p= 0.044) and belowground (F = 5.86, p= 0.002) weights, but treatment affected 222 differently aerial and underground parts: plants treated with M1 concentration showed the 223 lowest aboveground weight whereas plants treated with M2 and M3 concentrations showed the 224 lowest belowground weight. 225

  -right), each metal except Pb was more accumulated in F. x bohemica 269 plant parts and the translocation factor ([metal]shoots/[metal]roots) of Cd was increased ten times 270 compared to control (1.0 vs 0.1; Fig. 7A) and six times for Zn (3.3 vs 0.5; Fig. 7D). The highest 271 concentrations of metal in F. x bohemica measured for this treatment were of 507.0 mg/kg for 272 Zn in aerial parts, and of 127.0 and 14.0 mg/kg for Cr and Cd respectively in belowground 273 parts. 274 By comparison, in the M3 condition F. japonica accumulated more of each metal than the 275 hybrid, especially Zn and Cd, for which, concentrations were as high as 833.0 and 19.5 mg/kg 276 respectively in aerial parts of some individuals, and of up to 244.0 mg/kg for Cr in belowground 277 parts whereas Pb was also poorly accumulated (Fig. 7A-D right). 278 It is also interesting to notice that, except for Zn, F. japonica accumulated very limited amounts 279 of metals compared to F. x bohemica in the control M0 condition (Fig. 7A-D left). Though, its 280 translocation factor varies not much with the presence of high concentrations of metal (from 3 281 to 5 for Cd and from 2 to 3 for Zn in M0 and M3 conditions respectively) compared to F. x 282 bohemica. 283 Discussion 284

Figure legends: 497 Figure 1 . 501 Figure 2 .Figure 3 .

 497150123 Figure legends: 497

Figure 4 .Figure 5 .Time

 45 Figure 4. Principal Component Analyses (PCA) of rhizome (A, B) and root (C, D) extracts 511

F

  Figure4

Table legends : 489 Table 1 .

 legends4891 Theoretical metal concentration achieved in soil (in mg/kg) after artificial pollution in 490

	491	function of treatment
	492

Table 2 .

 2 Highest reported values of heavy metal concentrations (in mg/kg) in soil and plant 493 parts of Fallopia spp. Reference literature in which values were published is indicated: 494 a Rahmonov et al. 2014; b Soltysiak et al. 2011; c Širka et al. 2016. 495

Table 1

 1

		Non polluted	Polluted +/-	Polluted +	Polluted ++
	Metals	(M0)	(M1) 1 month 3 months 1 month 3 months 1 month 3 months (M2) (M3)
	Cd	0	0.2	0.1	2	1	20	6
	Cr	0	15	9	150	90		440
	Pb	0	10	6	100	60		295
	Zn	0	30	18	300	180		880

Table Table 2

 Table

	Metals	Soil	Underground parts	Aerial parts
	Cd	6.7 a	19.7 b	6.7 b
	Cr	59.8 b	40.9 b	2.7 c
	Pb	203.0 b	27.3 b	10.7 c
	Zn	2623.0 b	357.0 b	541.7 a

Acknowledgements

Supplementary Material

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