Panpan Liu

Ying Zhou

Min Guo

Shuguang Yang

Olivier Félix

David Martel

Yiping Qiu

Ying Ma
email: yingma@dhu.edu.cn

Gero Decher

Fluorescence-enhanced bio-detection platforms obtained through controlled "step-by-step" clustering of silver nanoparticles

niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction:

Fluorescence is one of the most commonly used techniques for the detection of biomolecules and it has been employed extensively in the fields of biotechnology and life sciences. [1][2][3][4] Though fluorescencebased detection is highly sensitive, there is always a demand to push the detection limits. To this end, considerable attention has been given to the modification of the spectral properties of fluorophores and the enhancement of their emissive fluorescence. [5][6][7][8] Two-dimensional (2D) sensing platforms composed of metal nanoparticles (NPs) have frequently been used as fluorescence-enhanced substrates in bio-detection. [9][10][11][12] In such 2D platforms, the metal NPs are considered to play an essential role in fluorescence enhancement, owing to the coupling effect between their surface plasmons and the fluorophores. 13,14 Their fluorescence enhancement effect is closely related to the interparticle distance 15,16 and to the fluorophore-nanoparticle distance. [17][18][19] The relatively close proximity between the metal NPs enhances the local electric fields around them and thus results in strong fluorescence emission. The fluorescence quenching usually occurs for a fluorophore-nanoparticle distance below 5 nm because of the nonradiative energy transfer to the metal particle. Beyond 5 nm, the quenching effect decreases quickly and a fluorescence enhancement can be observed because of the enhanced excitation and radiative decay pathways by metal nanostructures. It is apparent that the uniform fluorophore-nanoparticle distance on the metal NP platforms is greatly contributing to enhance the fluorophore-nanoparticle coupling efficiency and reduces the number of experimental variables. 20,21 Therefore, one of the main problems for the construction of these fluorescence-enhanced platforms is the control of the number of particles per aggregate and of their packing. Up to now, various methods have been employed for the preparation of 2D metal NP platforms, for instance, lithography, 22,23 physical and chemical vapor deposition, 24,25 electromigration, 26,27 template technique, 28,29 or a combination of these, 30,31 for use in biological detection. Although these methods worked well for the preparation of metal NP platforms, several drawbacks have hindered their development, such as the tedious preparation procedures, need for high temperatures, and high costs. It is therefore highly desirable to develop simple, cheap and versatile approaches for the construction of metal NP platforms with a satisfactory fluorescence enhancement. Self-assembly techniques based on non-covalent interactions, which include electrostatic, hydrogen bonding, host-guest, and charge-transfer interactions, are especially attractive as they allow to adjust a large variety of control parameters under mild conditions. [32][33][34][35] It was shown that the control of these non-covalent interactions can induce individual metal NPs in aqueous colloidal suspensions to form aggregates in solution, resulting in fluorescence enhancement. [36][37][38][39] In addition, screening of electrostatic repulsion among metal NPs, achieved by adding polyelectrolytes or inorganic salts to screen the surface charges, has been proven to be effective in obtaining fluorescence enhanced aggregates. 40 However, approaches using NP colloidal suspensions are not suitable for point-of-care testing due to their inherent stability issues related to the colloidal system. Therefore many groups developed self-assembled nanostructures immobilized on planar substrates.12,41 While record fluorescence enhancement factors up to several thousand times were obtained for single molecules systems, 11,41,42 fluorescence enhancement factors around several tenfold were observed for selfassembled nanostructures. 43,44 The substantial value difference between these two systems is explained by the use of various detection modes based on single-molecular level or bulk ensemble measurements. In terms of practical applications platforms based on bulk ensemble measurements compare favourably to single molecule devices due to the ease of their preparation (limited synthetic and technical steps) although their fluorescence enhancement is significantly lower. Among available self-assembly techniques layer-by-layer (LbL) assembly is considered an universal, convenient and efficient method to build nanocomposite films with tunable morphology and functionality. [45][46][47][48][49][50][51][52][53] Here we used a variant of LbL assembly in which we intentionally work at a low coverage of NPs per assembly step which strongly favors island growth over the growth of regular dense particle/polyelectrolyte layers. The objective of the present work is to control the island growth (or step-by-step clustering) in a way so that the resulting NP islands (clusters) have small NP-NP distances for obtaining high fluorescent enhancement. At the same time the step-by-step clustering prevents the formation of large aggregates which would lead to a strong blue shift of the plasmon absorbance. It therefore allows to tailor position and width of the plasmon band well enough for device fabrication. After synthesis and characterization of Ag NPs we first studied their density, their morphology and their spectroscopic properties on poly(diallyldimethylammonium chloride) (PDDA) terminated multilayers by SEM, UV-vis spectroscopy and fluorescence spectroscopy as a function of spray deposition conditions. In order to demonstrate the importance of the aggregate morphology (2D versus 3D) on spectroscopic properties, we further increased the number of NP per aggregate through step-by-step clustering using PDDA to reduce interparticle distance via charge screening and to grow NP islands preferentially in 2D prior to 3D. Fluorescence enhancement at low NP density and of NP islands was measured through bioassays using rabbit immunoglobulin G and a conjugate of goat antirabbit immunoglobulin G with cyanine (Cy5). Cyanine-5 (Cy5), a near-infrared fluorescent dye, has broad applications in biological detection because of its low autofluorescence and limited bleaching. 54- 56 Usually, its fluorescence enhanced factor through the bulk ensemble detection on metal platforms is around 5-20. [57][58][59] In our work, the simple and versatile step-by-step assembly allows the controllable construction of metal NP platforms, reaching a satisfactory fluorescence enhancement of 12.3-fold after twelve deposition cycles. In addition, the use of spray deposition technique [60][61][62] considerably accelerated the assembly process, which is very useful for scaling up.

Experimental:

-Materials Trisodium citrate dihydrate (Na3C6H5O7•2H2O), poly(sodium 4-styrenesulfonate) (PSS, average Mw = 70 000) and poly(diallydimenthylammonium chloride) (PDDA, average Mw = 100 000-200 000, 20 wt% aqueous solution) were purchased from Sigma-Aldrich. Silver nitrate (AgNO3) was obtained from J&K Chemical Co., Ltd. Goat anti-rabbit IgG-Cy5 and rabbit IgG used in bioassay experiments was provided by Thermo Fisher Scientific. All chemicals were used as received without further purification. Milli-Q water (18.2 MΩ.cm) was used throughout the present study. Spray guns (SATAminijet 3000B HVLP) were purchased from SATA GmbH&Co.KG (Germany).

-Synthesis of Ag NPs The silver nanoparticles (Ag NPs) used for platform preparation were synthesized by the citrate reduction of silver nitrate using a procedure previously described in the literature. 63 Briefly, 90 mg AgNO3 were dissolved in 500 mL of Milli-Q water and the resultant solution was heated to boiling under stirring. Then, 10 mL of 1% sodium citrate were added. After boiling for 1 h, Ag NPs were obtained. The concentration of the resulting Ag NP colloidal suspension was calculated to be 1.42 × 10 -10 M, as calculated from the absorbance of the 6-fold diluted colloidal suspension (Fig. 1c) and the already reported extinction coefficient for 60 nm Ag NPs (6.75 × 1010 M -1 cm -1 ). 64 During the reaction, the color of the colloidal suspension changed from transparent to opaque yellow-gray. The as-prepared Ag NPs are negatively charged as confirmed by zeta potential measurements (-30 mV). Under stirring, the Ag NP colloidal suspensions can be kept over 3 days at 4 °C.

-Step-by-step clustering of Ag NPs to prepare Ag platforms Cleaned quartz slides were modified with a PDDA/(PSS/PDDA) × 3 film using alternate dipping into PDDA (1 mg mL -1 , 15 min) and PSS (1 mg mL -1 , 15 min) with intermediate rinsing (1 min, 3 times) and drying steps. Then, the step-by-step clustering of Ag NPs was conducted on the pretreated quartz substrates by spray-assisted assembly as follows. Firstly, the as-prepared Ag NP aqueous colloidal suspension was sprayed on the pretreated quartz at 20 psi for 30 s, followed by the rinsing with Milli-Q water to remove physical absorption. Subsequently, 1 mg mL -1 PDDA aqueous solution was sprayed at 30 psi for 10 s and adsorbed on Ag NPs. The spraying and rinsing steps were repeated until reaching the desired Ag platform ending with an Ag NP layer. No drying step was used during assembly.

-Bioassay procedures The substrates uncoated and coated by Ag platforms were covered with 150 μL of 17 μg mL -1 IgG aqueous solution with a pH of 7.4 and then incubated in a shaker (90 rpm) at 20 °C for 1 h. Then, the slides were immersed into 150 μL of 1% bovine serum albumin (BSA) for 1 h, followed by 150 μL of goat anti-rabbit IgG-Cy5 at 17 μg mL -1 for 1 h. BSA was used to block the substrate sites during the adsorption of goat antirabbit IgG-Cy5 on Ag platform. BSA molecules covered completely the Ag platform, including the surface of the PDDA/(PSS/ PDDA) × 3 and the Ag NPs. Subsequently, the goat anti-rabbit IgG-Cy5 replaced the BSA on Ag NPs to interact with the exposed IgG, owing to their specific binding. All samples were rinsed with a PBS solution (pH = 7.4) for three times after each step, and were always kept in a wet condition to prevent protein unfolding or denaturation.

-Finite-difference time-domain (FDTD) calculations The FDTD method was employed to determine the electric field intensities and distributions at the surface of planar and stacked silver cluster. In the simulation, Ag NPs were defined as spheres with a diameter of 68 nm. The planar clusters were simply modeled as three Ag NPs arranged linearly and horizontally. And the stacked clusters were modeled as three Ag NPs on the bottom and two Ag NPs on the top. All interparticle distances were set to 1 nm. Irradiation was carried out using a 633 nm plane light wave normal to the samples. As boundary conditions, all outmost sides were defined as perfect matching layer (PML). 39 -Characterization UV-Vis spectra were measured using a Hitach U-3030 UV-Vis spectrometer. The TEM image of Ag NPs was taken using a JEM-2100F transmission electron microscope (JEOL, Japan). The surface morphologies of Ag platforms were determined by a Hitachi S-4800 scanning electron microscope. Fluorescence spectra and lifetime were recorded using a Quant Master 40 and Timemaster 3 fluorescence spectrometer (Photon Technology International Inc.) under an excitation of 615 nm, respectively. Fluorescence intensity images were captured on a TCS SP5 confocal laser scanning microscope (Leica company, Germany) with an excitation at 633 nm.

Results and discussion:

Here we report on the control of particle clustering for providing a maximum of fluorescence enhancement using an easy, cheap and scalable approach for preparing new sensors coatings for future point-of-care testing. Ag NPs were chosen as plasmonic nanostructures and were prepared by conventional citrate reduction (see Experimental section for details). 63 As shown in Fig. 1a, the asobtained Ag NPs were a mixture of spherical, ellipsoidal and rod-like particles. To determine the diameter and size distribution of the resulting Au NPs, both the major and minor axes of more than 200 NPs were measured. The average diameter was determined to be 68 ± 9 nm (Fig. 1b), which meets the size requirement of Ag NPs for fluorescence enhancement (>40 nm). 65 The citrate ligands on the Ag NPs lead to a surface potential of -30 mV. This negative charge stabilized their colloidal suspensions. The UV-Vis absorption spectrum of the Ag NP aqueous colloidal suspension (Fig. 1c) shows a broad and asymmetric peak which can be attributed to the convoluted signal of the dipole and quadrupole plasmon resonances of individual Ag NPs at 417 and 388 nm.66 Macroscopically the colloidal suspensions have an opaque yellow-gray appearance, as shown in the inset of Fig. 1c, which corresponds well to the expectations for the size and concentration range of the colloidal particle suspensions reported here. The Ag NPs were deposited on the substrate by spray-assisted assembly (Fig. 2a). The quartz substrate was precoated with a multilayer film composed of PDDA and poly (sodium 4-styrenesulfonate) (PSS), which is denoted as PDDA/(PSS/PDDA) × 3, to provide sufficient positive charges for the adsorption of the negatively charged Ag NPs. Subsequently, the aqueous colloidal suspension of Ag NPs was sprayed perpendicular to the receiving surface, with a fixed distance of 15 cm between the nozzle and the substrate. All spraying steps were carried out at identical conditions. Fig. 2b shows the Ag platform obtained using a pressure of 20 psi for 30 s after a one-time spraying. The Ag NPs were distributed randomly on the substrate and were fairly isolated from each other, owing to their electrostatic repulsion which is weakly screened by polyelectrolytes present on the surface. 67 To assess the fluorescence enhancement, the average interparticle distances (L) of the one-time sprayed Ag platform were calculated as

𝐿𝐿 = 𝑎𝑎 √𝑛𝑛 -𝐷𝐷
where a is the length of the square deposition area, and D is the average diameter of the deposited Ag NPs (68 nm), and n is the number of Ag NPs deposited on the object area counted using the software package Image J. For the Ag platform in Fig. 2b (obtained by one-time spraying at 20 psi for 30 s), the average interparticle distance was determined to be 222 nm. This value is much higher than the radius of the used Ag NPs (34 nm), which is the maximum interparticle distance (LMax) for strong fluorescence enhancement. 9,68 Of course, the fluorescence enhancement of this one-time sprayed Ag platform is expected to be poor. As shown in Fig. 2c, our Ag platform displayed similar fluorescence intensity at 685 nm with the PDDA/(PSS/PDDA) × 3 modified quartz control sample when being treated with rabbit immunoglobulin G (IgG) and goat anti-rabbit immunoglobulin G labeled with cyanine-5 (denoted as goat anti-rabbit IgG-Cy5). Thus, the fluorescence enhancement factor (EF) is only 1.1. In order to improve the fluorescence enhancement of onetime sprayed Ag platforms, the spraying time and the operating pressure were varied for reducing the interparticle distance. The UV-Vis absorption spectra of the one-time sprayed Ag platforms were recorded to quantify the Ag NPs deposited on the substrate as a function of the spraying time (Fig. 2d) Compared with those of the aqueous colloidal suspension of Ag NPs, the plasmon resonance peaks of the one-time sprayed Ag platforms were blueshifted to 404 and 372 nm, as a result of changing the medium around the Ag NPs from water to air or PDDA layer. 69 The polyelectrolyte induced blue-shift of the plasmon band of metal nanoparticles that has been reported before. 70 More importantly, with the augmentation of spraying time from 20 to 30, 40 and 60 s, the absorbance increased towards a maximum value indicating that the increasing NP adsorption is reaching a plateau at prolonged spraying times. The increasing density of Ag NPs was easily visualized by scanning electron microscopy (SEM; see ESI Fig. S1 †). Based on the SEM images, the average interparticle distances (L) after spray times of 20, 30, 40 and 60 s were calculated to be 292, 222, 215 and 181 nm, respectively, as illustrated in the right-hand panel of Fig. 2d. For a constant spray time of 30 s, the adsorption of Ag NPs did not continuously increase when the spray pressure was increased from 10 to 20 and 30 psi, but instead reached a maximum at 20 psi (Fig. 2e). The arrival of spray droplets on the receiving surface is a complex process, increasing the spray pressure leads to higher mass transport, but may also remove weakly bound material. As one-time assembly process led to a low density of mostly individual NPs it was necessary to increase the number of NPs per aggregate to meet the requirement of Ag NP platforms in fluorescence enhancement. Ag NPs were then step-by-step assembled with the counter polyelectrolyte PDDA to yield bio-detection platforms with a substantial fluorescence enhancement. At our optimal spraying conditions (20 psi for 30 s), the step-by-step assembled Ag platforms were prepared conveniently and rapidly on PDDA/ (PSS/PDDA) × 3 pretreated quartz substrates (see Experimental section for details) through the electrostatic interactions between the negatively charged Ag NPs and the positively charged PDDA. In all films, Ag NPs were deposited as last step. Fig. 3a shows the UV-Vis absorption spectra of the resulting assembled Ag platforms. With the assembly of Ag NPs, the characteristic peak of the dipole plasmon resonance increased linearly (Fig. 3b) and was blue-shifted from 404 to 381 nm owing to the increase of electron delocalization 71 among the Ag NPs. Furthermore, we noted the appearance of a broad peak at around 700 nm, which is associated with the in-plane resonance of Ag NPs and strongly depends on the interparticle distances. 65 The surface morphologies of Ag platforms with 5, 12 and 20 assembly cycles (denoted as 5-Ag, 12-Ag and 20-Ag platforms, respectively) were characterized by SEM (Fig. 3c). Further assembly steps of NPs on 1-Ag platform led to islands growth which starts in-plane (planar clusters) and later also extends in the third dimension (stacked clusters). The Ag NPs are initially deposited on the substrate with fairly large gaps between them (Fig. 2b). During the subsequent stepby-step clustering (Fig. 3c), the additionally deposited particles are more and more filling the interspaces likely facilitated by the electrostatic screening of the repulsion between the negatively charged particles and by the electrostatic attraction of the particles by the cationic PDDA present on the surface. When the interspaces were not big enough, stacked structures of Ag NPs began to appear on the surface. In any case, the step-by-step clustering enables the construction of Ag platforms with successively smaller interparticle distances, which contributes to the enhancement of the electric field around the Ag NPs. In order to estimate the fluorescence enhanced capability of the step-by-step assembled Ag platforms, computations of the electric field density for the Ag clusters were conducted using the finite-difference time-domain (FDTD) method. 39,[START_REF] Taflove | Computational Electrodynamics: The Finite-Difference Time-Domain Method[END_REF][START_REF] Taylor | [END_REF] Fig. 3d shows the electric field distribution of the planar and stacked Ag clusters under perpendicular irradiation with a 633 nm plane light wave. The interparticle distance was set to 1 nm, because the Ag NPs are concatenated by the polyelectrolyte PDDA on the nanoscale. As shown in the corresponding line plot (Fig. 3e), the electromagnetic field amplitudes along the lines of a-a′, b-b′ and c-c′ in Fig. 3d of the planar and stacked Ag clusters were presented. The electric field intensity at the center point between two adjacent NPs has maximum values of 112.7 (planar) and 57.3 (stacked), respectively. This result indicates the negative effect of the stacking structure on the electric field enhancement. Moreover, the electric field of a planar cluster composed of 5 aggregated Ag NPs was also simulated by FDTD (Fig. S3 of ESI †). In comparison with the stacked structure in Fig. 3d, the 5-aggregated Ag NPs in the planar structure showed a higher electric field intensity (93.6), underlining the importance of 2D nanostructures in the electric field enhancement and fluorescence enhancement.

To characterize the fluorescence enhancement, we measured the fluorescence of goat anti-rabbit IgG-Cy5 on IgG modified Ag platforms after 3, 5, 8, 10, 12, 15 and 20 assembly cycles and on a quartz slide coated only with a PDDA/(PSS/PDDA) × 3 film (control). As shown in Fig. 4a, the emission region of Cy5 is centered at ∼685 nm, which overlaps with the emerging broad absorption peak (∼700 nm) of the step-by-step assembled Ag platforms. This wavelength overlap is expected to facilitate fluorescence enhancement. 74,75 The large goat anti-rabbit IgG molecules, which are several nanometers in size, 10,76 may also help to separate the fluorescent Cy5 dye molecules from the plasmonic Ag NPs for reducing fluorescence quenching effects.77 Integration of these fluorescence intensities gave enhancement factors for the step-by-step assembled Ag platforms as compared with the control (PDDA/ (PSS/PDDA) × 3 on quartz). In Fig. 4b, with the assembly of Ag NPs, these enhancement factors initially increased to a maximum of 3.1 for the 12-Ag platform, followed by a decrease. The above-mentioned negative effect of the stacking structure on the electric field density was believed to be responsible for this decreased enhancement factor after 12 assembly cycles. Additionally, we attributed the rebound of the enhancement factor for the 20-Ag platform (i.e., its rise compared with that of the 15-Ag platform) to the coincidence of the stacking and filling of Ag NPs during assembly. This shows that the fluorescence enhancement of metal nanomaterial platforms can be fine-tuned by controlling the stepby-step process. Furthermore, the fluorescence enhancement is generally accompanied by a decrease in the fluorescence lifetime, both of which are derived from the high radiative decay rate of the fluorophores. 13,31 In Fig. 4c, the fluorescence intensity decay of anti-rabbit IgG-Cy5 shows a shorter Cy5 lifetime of 0.94 ns for the 12-Ag platform, compared with that of the control (1.36 ns). The 31% lifetime shortening suggests that the enhanced fluorescence intensity of the 12-Ag platform mainly comes from the intensive electric field rather the increased radiative decay rate. This conclusion also could be drawn from the weak absorption of 12-Ag platform at the emission peak of Cy5 (∼685 nm). The enhanced fluorescence on the 12-Ag platform was readily observed in photographs taken using a confocal laser scanning microscope (CLSM) (Fig. 4d). Compared with the control sample (bottom half), Cy5 on the 12-Ag platform (upper half) exhibited a brighter red color. The corresponding enhancement factor of the 12-Ag platform was calculated to be 3.0 from the analysis of the color intensity by Image J. This result is in agreement with the value calculated from the fluorescence emission spectra

Conclusions.

In summary, we have shown that step-by-step clustering is a simple, cheap and versatile method for the preparation of self-assembled metal NP-based platforms with controlled aggregate density and morphology. This approach based on a low coverage of NPs par assembly step favours island growth over the growth of regular dense particle/polyelectrolyte layer as reported for LbL-assembled systems. Starting from mostly individual NPs, we showed that this process can be tuned to lead to an island growth that starts in-plane and later also extends in the third dimension. So the resulting NP islands (clusters) have small NP-NP distances for obtaining high fluorescent enhancement. While a poor fluorescence enhancement (1.1) was observed at low NP density, a substantial fluorescence enhancement (12.3) was measured for an Ag NP platform obtained after twelve deposition cycles. This fluorescence enhancement value is within the ballpark of values reported in the literature for biossay platforms using metal nanoparticles. Due to the ease of controlling the position of the plasmon band for tuning the fluorescence enhancement through aggregate size and NP-NP distance, step-by-step clustering fulfils two important prerequisites for mass-scale device fabrication.

Fig. 1

 1 Fig. 1 (a) TEM image of the Ag NPs used for platform preparation and (b) histogram showing an average diameter of 68 ± 9 nm with a wide size distribution. (c) UV-Vis absorption spectrum and photograph (inset) of the Ag NP aqueous suspension.

Fig. 2

 2 Fig. 2 (a) Schematic of spraying Ag NPs on the substrate. (b) SEM image of a one-time sprayed Ag platform at 20 psi for 30 s. (c) Fluorescence intensity of goat anti-rabbit IgG-Cy5 dried onto the one-time sprayed Ag platform (20 psi, 30 s) and the bare quartz modified with PDDA/(PSS/PDDA) × 3 (the control). UV-Vis absorption spectra and sketches of average interparticle distance (L) for one-time sprayed Ag platforms (d) at 20 psi for 20, 30, 40, 60 s and (e) at 10, 20, and 30 psi for 30 s.

Fig. 3

 3 Fig. 3 (a) UV-Vis absorption spectra and (b) absorption maxima around 404 nm of step-by-step assembled Ag platforms with different assembly cycles. (c) SEM images of the 5-Ag, 12-Ag and 20-Ag platforms. The insets illustrate the step-by step clustering of Ag NPs. (d) Electric field density distribution and (e) corresponding line plot of field enhancement in the gaps between two particles for the aggregated Ag NPs with the planar and stacked structures simulated using FDTD.

  (3.1). To reveal the potential of the 12-Ag platform on biological detection, rabbit IgG was adsorbed onto the Ag nanostructure by physisorption,76 followed by the intermediate deposition of bovine serum albumin (BSA) prior to the deposition of goat anti-rabbit IgG-Cy5. The details are described in Experimental section. Concentrating the local electric field around the planar Ag clusters, in which the Ag NPs are in relatively close proximity because of the electrostatic attraction with PDDA, accelerated the excitation of Cy5 and thus enhanced the fluorescence. The fluorescence enhancement on the 12-Ag platform over the control, a quartz slide coated with a PDDA/(PSS/PDDA) × 3 film, was determined from the fluorescence emission images in Fig. 5b. The average fluorescence intensity for Cy5 was 2.1 ± 1.1 for the control and 25.8 ± 7.1 for the 12-Ag platform, respectively. The satisfactory enhancement factor of 12.3 indicates that the controlled step-by-step clustering of metal NPs allows the simple and fast preparation of efficient fluorescence enhancing platforms for bio-detection.

Fig. 4

 4 Fig. 4 (a) Fluorescence intensity of goat anti-rabbit IgG-Cy5 dried onto step-by-step assembled Ag platforms with different assembly cycles. (b) Fluorescence enhancement factors of step-by-step assembled Ag platforms as a function of the number of assembly cycles, compared to the control of a bare quartz modified with PDDA/(PSS/PDDA) × 3. (c) Fluorescence lifetimes and (d) CLSM images of goat anti-rabbit IgG-Cy5 on the 12-Ag platforms and on the control.

Fig. 5

 5 Fig. 5 (a) Schematic illustration of the bioassay procedure on step-by-step assembled Ag platforms. (b) CLSM images and fluorescence intensity distribution of Cy5 on the control and on the 12-Ag platform.

Acknowledgements

This work was supported by National Key Research and Development Program of China (No. 2016YFB0303300), and National Natural Science Foundation of China (No. 21304016).

Notes and references


Francine Ricouart
email: ricouart@univ-tlse2.fr

Regis Cereghino

Charles Gers

Peter Winterton

Luc Legal
email: legal@cict.fr

Influence of fire prevention management strategies on the diversity of butterfly fauna in the eastern Pyrenees

Keywords: Lepidoptera, Biological indicators, Fire cuts management, Pyrenees

Fire prevention management is becoming a necessity in many Mediterranean locations to regulate fire of natural or human origin. However, very few studies have determined the real effects of the strategies adopted on local fauna. Butterfties are sensitive to local changes and they can thus serve as indicators of environmental changes. Three different types of fire prevention management approaches in three different localities in the Eastern Pyrenees (France) were performed and the butterfly community composition was investigated. We show that of the 80 species of butterflies observed, 36 % can be considered as biological markers. An original objective treatment of data using hierarchical distance analysis combined with a neural network analysis (Self-Organizing Maps) was applied in this study. Our conclusions are that the overall number of species is maintained independently of the fire prevention type but that sorne important changes are observed among butterfly communities, with a clear reduction of the nombers of endemic/specialized species in favour of generalist ones for the two most drastic fire prevention management approaches studied here. The influence of such approaches is

Introduction

A major risk for Mediterranean forests is fires of human origin. On average, 30,000 ha/year hum in the Mediterranean region of France. For instance, 45,600 ha have bumed during the last 30 years in the Département of Pyrenées Orientales alone (0.8 % of the total surface area; from Promethee database: www.promethee.com).

Many management policies have been applied to protect endangered biota from fire, among which partial or undergrowth clearing is currently the preferred technique, and is chosen for most slope orientations, and prevailing winds, etc. Depending on how drastic the clearing is, such policies result in changes in flora and the thus in the associated fauna, but have been proved to reduce the risk of complete destruction of vast areas (Ricouart 2005;Quartau 2009).

Many insects have already been used as ecological indicators (Kimberling et al. 2001 ;Paoletti 1999) including Coleoptera (Bohac 1999), ants (King et al. 1998;Labry de Bruyn 1999), grasshoppers (Andersen et al. 2001 ;[START_REF] Zschokke | Short-term responses of plants and invertebrates to experimental small-scale grassland fragmentation[END_REF], Diptera (Frouz 1999) and Syrphidae [START_REF] Sommaggio | Syrphidae: can they be used as environmental bioindicators[END_REF][START_REF] Speight | Predicting the changes in farm syrphid faunas that could be caused by changes in farm management regimes (Diptera, Syrphidae)[END_REF]. Resilience of the various insects to fire events (whether natural or provoked) is notably variable, but most can rebuild their initial population levels a few years after a total hum of the area (Braby 2010; [START_REF] Warren | Response of grassland arthropods to burning: a review[END_REF]). In sorne specifie cases, fires can even be a necessity to maintain populations of endangered species by renewing the host-plant population [START_REF] Warren | Response of grassland arthropods to burning: a review[END_REF]). Anyway, most of time, the effects are deleterious for the specialized species but neutra! to beneficiai for generalists (Powell et al. 2007;[START_REF] Swengel | Declines of prairie butterflies in the Midwestem USA[END_REF].

Lepidoptera were not included among the insects first used as indicators. lt was generally considered, as a first approximation, that due to their ability to fly, they are not sufficiently specifie to act as indicators of perturbations. However, many field studies (Erhardt 1985;Oostermeijer and van Swaay 1998;Thomas and Hanski 1997;[START_REF] Thomas | Spatial dynarnics of a patchily distributed butterfly species[END_REF] oppose this view, showing a high specificity of these insects for certain micro-habitats or anthropogenically disturbed areas (Luque et al. 2007(Luque et al. , 2009;;[START_REF] Van Halder | Conserving butterflies in fragmented plantation forests: are edge and interior habitats equally important?[END_REF]. Furthermore, butterflies and moths have one of the highest sensitivities to rapidly changing environmental conditions (New 1997). Anyway as recently demonstrated by Rosin et al. (2011), this sensitivity and specificity is highly variable among Lepidoptera species even belonging to the same genus.

In order to provide a critical appraisal of the use of adult Lepidoptera as biological indicators in the special context of fire prevention management in the Eastern Pyrenees, we used a novel strategy. First, we determined whether, among the species encountered in this region, sorne possess a specificity to a certain type of habitat. An original approach based on a hierarchical distance analysis was tested. Then, we checked the specificity of distribution among the study sites and for different types of tire prevention managements on the Lepidoptera. To do this, a neural network model was applied. Finally, we determined whether Lepidoptera species groupings occurred, depending on the type of fire prevention management. Distance treatment was used for this step. Based on these three conditions, we discuss the relevance of the use of adult butterflies as markers of anthropogenically disturbed areas to evaluate the effects of fire prevention management strategies on the Lepidopteran fauna. In conclusion, we measured the balance between fire prevention management and the impact on the diversity of Lepidoptera.

Materials and methods

Localities studied

The three study sites were situated in the Département of Pyrénées Orientales (Southem France; Fig. 1). The localities (Argeles-sur-mer ARG, Calmeilles CAL, Campoussy CAM) were chosen to compare different types of Mediterranean habitat (Table 1).

Argeles and Calmeilles are typically Mediterranean locations, but the former (ARG) is composed more of open fieldlshrubs while the latter is dominated by shrubs/maquis and therefore does not experience the same extremes of beat. The third locality (CAM) is an open field in a Mediterranean mountainous location much cooler than the other two locations.

Each locality was divided into three sub-localities depending on the type of tire protection management system adopted (Table 2). The management actions were carried out during the winter of 1999/2000. Our study then started the tirst year after implementation of the new management approaches. Note that for CAM, virtually no trees were present before the management strategy, meaning that no, or few differences, existed between Zone A and Zone B (Zone C was also accidentally subjected to this management strategy). Fences were placed around the study zones to avoid cattle from biasing the protocol.

Zone A: This zone class was totally cleared of vegetation with on1y the herbaceous level remaining. The goal of this drastic treatment was to ensure that no bumable material is present and to provide safe refuges for firemen if a tire does occur.

Zone B: The treatment of this type of zone consists main1y in removing bushes (minimum: 2/3 of the zone) while the trees are kept. As bushes represent the main source of combustible material, this treatment is assumed to limit tires in such zones.

Zone C: The treatment of type C zones consists only of placing grazing animais in the area (goats or cows, depending on the location). Zones C are thus considered as "sub natural" but with herbivory over-pressure. As livestock will eat mainly the herbaceous and shrub level, the expectation is that any tires will be slowed.

Butterfly sampling

Samples were collected 5 times a year: once a month from May to September. The study covered two successive years: 2000 and 2001. Butterflies were collected with standard Lepidoptera band nets (Sticks 1.5 rn, diameter 40 cm) in a single plot per zone and per site of 1 ha (the largest area available in ali the studied zones without approaching the edge). The three locations were sampled during the same week, taking care that weather conditions were similar. Two people performed the sampling for 90 min at every location and sub-location. For each location, samples were collected on the same day, to avoid variations due to weather conditions. Except for a few species, none bad a strict circadian rhythm that would make their densities and occurrences vary within the day. The insects were then released, or killed for identification using KCN jars (mainly for Lycaenidae and Hesperiidae) and/or for further molecular analysis studies. Identification was performed using various field guides (Geiger 1987;Leraut 1992;[START_REF] Tolman | Guide des Papillons d'Europe et d'Afrique du Nord[END_REF]. For a (1999). Naming follows the proposais of www.Ieps.it.

Data analysis

Distance method

An original approach of lùerarchical classiication was performed. By using the different ecological traits of each of the species found. we assimilated them to characters to achieve a network. of inter-relationships between taxa.

Beiog convinced that such rough groupings (even though due to local conditions in our sampling zones, some species are miss-placed when analysing distribution patterns.

The species were classified according to two main eoological criteria: the openness of the terrain and humidity factors. For both these main criteria three sub-categories were defined.

For terrain openness, a lùerarchical gradient was defined:

1. Orassland, open field without shrubs over 30 cm. 2. Shrub areas, up to the forest zone, where trees accounted for less than 10 % of the cover. Humidity conditions were divided into the three following categories: xeric, mesophilic and hydrophilic.

Many species have a potential habitat covering two or more of our categories (according to various field guides and our own experience). However, most are observed to occur preferentially in one habitat type. Note that, sorne species which live strictly in dry habitats in Northem Europe prefer relatively cool damp conditions in Mediterranean areas. In our ecological matrix, we coded: 0 for absent or very rare, 1 for regular occurrence in a biota and 2 for a clear preference.

Distance trees were dealt with using the same principle except that we took into account the presence (1)/absence (0) of species in each location studied. Only species forming a potential population were included in the final analysis (at least two specimens sampled and the presence of a potential host plant, data not shown).

All analyses were performed using Paup* 4.0b10 software [START_REF] Swofford | P AUP: phylogenetic analysis using parsimony (*and other methods), version 4.0[END_REF]. All heuristic searches for optimal trees were carried out by TBR (tree-bisection-reconnection) branch swapping. Negative branch lengths were allowed, but set to zero for tree-score calculations. The steepest descent option was not in effect. Distance measurement used mean character difference. Starting tree(s) were obtained by neighbour joining.

As our intention was not to perform a phylogenetic classification, we decided not to include any outgroups in our data set. The distance trees obtained are represented umooted. When multiple sub-equal trees were found, a Majority Rule (50 %) consensus tree was calculated. Bootstrap values were not calculated as no information was available from the literature to judge if such treatment was relevant using ecological characters and furthermore because we did not perform a character-state treatment (parsimony). A pattern code was attributed to each species depending on distribution type and place on the distance trees. The code was determined from the neural network results.

Considering the specificity per zone inside locations, we checked if specialized species were more represented in conserved areas ( corresponding to Zones C) rather than in managed areas (Zones A and B). Species specifie to one zone or mainly found in one zone are expected to be in the same clade. Species encountered in Zone C are circled.

Modelling species assemblages

Inspired by the structure and the mechanism of the human brain, Artificial Neural Networks (ANNs) provide convenient tools to maximize the information extracted from "simple" presence-absence data (Lek and Guégan 2000). The Self-Organizing Map (SOM, unsupervised neural network, Kohonen 2001) performs a topology-preserving projection of the input data onto regular two-dimensional space. In the output layer of the network the neurons act as virtual samples and approximate the probability density function of the input data. Therefore, using a binary dataset of species occurrences, the SOM calculates continuous quantitative values which vary between 0 and 1, so that the occurrence probability of any species in a given area, in the form of a connection intensity (visualized in gray shades), can be visualized on a virtual map. Additionally, the SOM algorithm averages the input dataset using weight vectors and thus removes noise. These features were relevant in our study because we analysed a binary dataset with many zeroes. The SOM Toolbox (version 2) for Matlab® developed by the Laboratory of Information and Computer Science at the Helsinki University of Technology (http:// www.cis.hut.fi/projects/somtoolboxl) was used (see [START_REF] Vesanto | Selforganizing map in Matlab: the SOM Toolbox[END_REF] for practical instructions).

The structure of the SOM for our study consisted of two layers of neurons connected by weights (i.e., connection intensities): the input layer was composed of 80 neurons (one per species) connected to the 18 samples (3 sites x 3 zones x 2 years), the output layer was made up of 21 neurons (visualized as hexagonal cells) organized in an array with 7 rows and 3 columns. In the output layer, the neurons act as virtual sites and approximate the probability density function of the input data. The occurrence probability of each species in a given area in the form of the connection intensity was visualized on the SOM map in grey scale, and therefore allowed us to predict the occurrence probability of each species in the various geographie areas. The SOM algorithm is an unsupervised learning procedure which can be summarised as follows:

• The virtual sites are initialised with random samples drawn from the input data set. • They are updated in an iterative way:

• A sample unit is randomly chosen as an input unit.

• The Euclidean distance between this sample unit and every virtual site is computed. • The virtual site closest to the input is selected and called 'best matching unit' (BMU). • The BMU and its neighbours are moved a bit towards the input unit.

• Training was broken down into two parts previously defined in Lek and Guégan (2000): • Ordering phase (the 2,000 first steps): when this first phase takes place, the sites are highly modified in a wide neighbourhood of the BMU. • Tuning phase (75,000 steps): during this phase, only the virtual sites adjacent to the BMU are slightly modified.

The network was trained with different map sizes (from 10 to 200 units), and the optimum map size was chosen based on local minimum values for quantization and topographie errors (see Céréghino and Park (2009) for practical considerations). Quantization error (QE) is the average distance between each data vector and its BMU and, thus, measures map resolution (Kohonen 2001 ). Topographie error (TE) measures map quality (i.e., to assess whether the map has been properly trained), it represents the proportion of a11 data vectors for which 1st and 2nd BMUs are not adjacent, and is thus used for the measurement of topology preservation. The total of 21 output neurons retained for this study fits the heuristic rule proposed by [START_REF] Vesanto | Clustering of the self-organizing map[END_REF] who reported that the optimal number of map units is close toC = 5-Jn, where n is the number of samples. 18 samples were classified on the basis of eight environmental variables. At the end of the learning process, each sample was set in the corresponding hexagon of the SOM. Neurons that are neighbours on the grid are expected to represent neighbouring clusters of samples; consequently, samples separated by a large distance from each other, according to species assemblages, are expected to be distant in the output space.

Ward's algorithm was applied to the weight vectors of the 21 neurons in order to divide the SOM units (hexagons) into clusters.

Analysis and interpretation

The occurrence probability of each species in a given area in the form of the connection intensity was visualized on the SOM map (in gray scale), and therefore allowed us to predict the occurrence probability of each species in areas (i.e., subsets of sites, or clusters) where they were not consistently collected during the sampling. In other words, the patterns of distribution for each Lepidoptera species among the various sites become apparent by superimposing the various species maps on the clustering of sites observed in the SOM map. This treatment allowed us to determine qualitatively and quantitatively (see Fig. 3b) the specificity of distribution of each species among the three Mediterranean locations studied (Arg: dry and low elevation, Cal: cooler and low elevation, CAM: cooler and higher elevation). A completely generalist species will occupy ail the Kohonen map and with an almost regular probability of presence (scale of grays), and for example a specialized species for low elevation open field Mediterranean biota (Type Argeles) will show only a few hexagons filled with a high probability (black) on the bottom right of the SOM grid. These two extreme situations never strictly occurred, but sorne dominant patterns are visible which allowed us to qualify the specificity of each species sampled, see Fig. 3c where a few examples of the different situations are shown.

A comparison was performed between the theoretical habitat of each species and results obtained using the SOM approach in order to test our a priori hypothesise. When congruence was found: we noted Y; when congruence was not found: N and finally, when a species is considered as generalist for one approach (theoretical or observed) and considered as specialist for the other, we noted: O.

Results

The species of Rhopalocera (including Hesperiidae) collected in 2000 and in 2001 are presented in Table 3 with their respective occurrences by zone.

The three localities were not equivalent in numbers of species: we recorded 37 species in Argelès (ARG); 47 in Calmeilles (CAL) and 57 in Campoussy (CAM) i.e. there were large differences between the three study zones.

Using data from the literature (Geiger 1987; Lafranchis 2000) and persona! observations in other regions, a first

Aglais urticae

x Arethusana dentata x

x x

x x

x Argynnis adippe x

x x

x Argynnis aglaja x grouping of species was performed and some functional groups were defined independently of coll.ection locations.

x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x
The 80 species collected were classified depending on their theoretical ocological constraints (Fig. 2; Table 4). Functional groups are defincd and no species were found to be outside or isolated from their respective theoretical group.

In particular, there is a clear separation between xeric and mesolbydrophilic species.

Study by site

Using the SOM, we checloed what the groupings were for the sampling sites independently of years, on the basis of Lepidoptera species occurrences.

A fust result i.s that main associations are by site, but not by fire prevention management treabnent (Fig. 3a). The locality of Campoussy (CAM) is notably different from the two others. Moreover, except for calBOl (Calmeilles, Zone B, year 2001) the two sites Calmeilles and Argeles are not mixed.. These last two sites are warmer and are also situated at lower elevations than Campoussy (Table 1).

We may group CAL + CAM in terms of coolness, CAL + ARG for low elevation Mediterranean biota and CAM + ARG for being more open fields (Fig. 3a).

Except for Campoussy, but due to local conditions and because the local farmer was not applying the fire pre.. vention procedure strictly (see "Materials and methods" section) no groupings by zones or year emerged.

Distribution specificity of Lepidoptera

The SOM treatment shows the levet of specificity of each species for a type of location and/or a specifie type of fire prevention management (Fig. 3b). In our study, 36% (29 out of 80) of the butterllies encountered showed habitat specificity in the field and additively 23 % (18 out of 80) of species tended to occupy just one type of habitat. Finally, for 41 % (33 out of 80) we were unable to assign a special type of habitat in the limited context of the locations studied and considering the resolution of our treatment.

A selection of the different patterns encountered is given in Fig. 3b.

The first line of Fig. 3b napi and Pieris rapae). Note that the maximum probability of presence of collection for P. napi was lower than P. rapae (71 vs. 98 %, respectively). The third, Anthocharis cardamines, occurred dominantly in the cooler area which is logical knowing that this species possesses its main distribution in Northem Europe. In opposition, the fourth species Leptotes pirithous is a Mediterranean species which is less common in cool areas even though it is widely distributed in the region studied (partially migratory species).

The second line of Fig. 3b can be separated into two groups. Species whose main distribution is in the North of Europe (species at the southem limit of their distribution e.g. Aporia crataegi and Carcharodus alceae) and species highly specialized for hills/mountainous Mediterranean biota (Satyrus feru/a and Polyommatus hispana). The pattern of the Kohonen map is of the same type in both these cases (only the upper part of the grid filled) but the specialized Mediterranean mountain species show less covering of the SOM map. The third line of Fig. 3b is composed of strictly Mecliterranean species (Giaucopsyche melanops, Euchloe ausonia, Satyrus actea. Pieris mannii). lt iB notable tbat the probability of collection was much lower tban for generalist species indicative of the endangered status of these species (average= 23.3 %). Finally the fourth line shows the speci.ficities of the three European Pyronia species (P. titlwnus, P. bathseba and P. caecilia). Pyronia tithonus presents an ample distribution in noetbem Europe and was mainly found in the coolest location. Pyronia bathseba is a southern species but prefers coole.r humid zones. Finally P. caecilia is a strict Fig. 3 a Kohonen (SOM) map of the three fire prevention managements for the three studied sites for 2 years depending on occurrences of Lepidoptera species and variations of abiotic conditions. Gradients: vertical; from white (hot) to dark gray (cooler), horizontal from dotted (fresh/humid) to no dots (dry). Circled in white are numbers corresponding to those indicated in b (see also Table 3 for more details). b Clustering of the 21 SOM neurons using Ward's algorithms. Numbers as in a (circled in white). Biota specificity of each butterfly species (c) is determined by checking occurrences in the various clusters defined here: A: Mediterranean hill specialist (Neurons 1, 2, 8); B: Northem cool specialist species (Neurons 1, 2, 8, 9, 15, 16); C: Northem cool generalist species (Neurons 1,2,8,9,15,16,3,10,17,11,18); D: strict Mediterranean species (Neurons 20,19,14,13,21); E: Southem dry generalist species (Neurons 20,19,14,13,21,6,7,4,5,12). Generalist species are deterrnined when SOM patterns are almost equally distributed between C and E. c Gradient analysis of the probability of occurrence of 15 selected butterfly species on the trained SOM, with visualization in shading scale (dark high probability of occurrence, light low probability of occurrence). Each little map is to be compared, or superimposed on the map in a for location. Species name above the map highlighted using symbols: No symbols: generalist species, circled + white: Northem cool generalist species, rectangular + white: Southem dry generalist species, circled + gray: Northem cool specialist species, trapezoïdal + gray: Mediterranean hill specialists and rectangular + gray: strict Mediterranean species Mediterranean species, which occurs only in the driest and warmest locations. This last example illustrates the specificity and the resolution level of our treatment. The probability of collection of the two most restricted species (average = 37.9 %) was notably lower than for the generalist species (99.8 %).

Complete results are given in Table 4 and an evaluation of the congruence between theoretical (results of Fig. 2) and SOM treatment (Fig. 3) was provided.

Note that probability of collection was notably different between generalist and specialized species (Table 4) 80 ± 20 versus 63 ± 35 % even though SD values are high. The values became really low when considering only the strict Mediterranean species with 25 ± 5 %.

Search for functional groups of species

In order to check if species can be grouped depending on their specificity, we built distance trees using the methodology described in "Materials and methods" section. This original approach provides a per-site image of the association of species in each location. The trees are a superimposition of ecological factors (same matrix as the one used to construct Fig. 2) and local occurrences (presence/ absence by zone/year and location; Fig. 3b ).

Except for very few species, separation between cooV humid areas and hot/dry areas is visible. Grouping by level of openness of the area was also observed.

Considering fire prevention management treatments, the only clear results were for the locality of Argelès, most species specialized for dry Mediterranean areas are grouped in Zone C (circled; Fig. 4a). For the locality of Calmeilles, species encountered in Zone C were mainly thermophilic preferring open or bushy areas but included species with a wide geographical distribution (Fig. 4b ). Finally, even though it is the most diverse location in terms of species number, the locality of Campoussy did not give any significant results and, furthermore, most of the specialized species of mountainous Mediterranean areas (in purple) were absent from Zone C (Fig. 4c).

Discussion

Specificity of Lepidoptera habitat Sorne Lepidoptera species have been shown to possess high habitat specificity (Geiger 1992;Luque et al. 2007). Caterpillars are much more reliable to prove the presence of a population but as one of the aims of our study was to design an approach that non-specialists would be able to follow i.e. the dynamics of butterfly communities and the influence of fire cuts, we preferred to use adults. In any case, the presence of at least one potential host plant was checked for every species (data not shown). Caterpillars possess the main disadvantage of being more difficult to find (sorne live in trees, others are mainly nocturnal) and are, most of time, much more difficult to identify.

Sorne Lepidoptera species were found in the field in full accordance with their theoretical habitat but a certain number were found to be in discordance with it, similar results were pointed out in the South West of France (V an [START_REF] Van Halder | Conserving butterflies in fragmented plantation forests: are edge and interior habitats equally important?[END_REF]. This was especially true for species found strictly in or on the edge of "maquis" (dense Mediterranean scrub/woodland in granitic areas) as these species were assumed to be open-field specialists (Glaucopsyche. melanops, Glaucopsyche alexis, Pyrgus cirsii, Euchloe ausonia, and Satyrus actaea). Our interpretation is that these species are the most sensitive to the management of their biota and may survive only in the few open areas close to or in this type of Mediterranean forest. Sorne theoretically open-field species were also found preferentially in the "maquis" such as Thymelicus acteon, Polyommatus thersites, Pyrgus malvoides or even Coenonympha arcania, but a more plausible explanation is that these species, widely distributed in Northem Europe, prefer cool refuges in more bushy/forest areas when living in sometimes extremely hot Mediterranean locations [START_REF] Stefanescu | Butterfly species richness in the north-west Mediterranean Basin: the role of the natural and human-factors[END_REF]). When comparing species with rather similar ecological demands such as the big Satyrinae (Chazara briseis, Satyrus ferula, Satyrus actaea and Hipparchiafidia), we found that the two with the widest ranges (in France, C. briseis and S. ferula are present in many xeric locations outside the Mediterranean area (Lafranchis 2000)) are less sensitive to management. On the other band, the two strictly Mediterranean species (S. actaea and H. fidia) seem to need the stability of their original biota (none or a type C fire prevention management) to maintain a population.

L.boeffcus G.cleopatra P.napi C. ui

The total number of species collected in the various zones for each site was fairly stable. Maximum stability was found in Calmeilles where, surprisingly, for both years of collection, we found exactly 30, 31 and 31 species for In the South West of France, Van Halder et al. (2011 ) found that, for a limited number of butterfly species (23) 12 showed habitat specificity (7 for edges, 5 for inner forest), while 11 were not specifie. Moreover, sorne species which were defined as generalists in our study can become specifie when changing sampling scale (a good example is S. esculi, which was present and common in our three locations, therefore: generalist in our study, but which could be specifie if sorne of our sampling sites were situated outside the Mediterranean region).

Impact of fire prevention management on Lepidoptera

Our distance approach allowed us to present a possible grouping of species. These distance approaches (phenetic) are designed for phylogenetic studies and more recently have been applied to the study of populations using cuticular markers (Roux et al. 2006) but have never been used with ecological constraints. We attempted to compare our approach with more classical ACP and canonical approaches, but the resolution obtained with such methods was very poor.

Our analysis shows us that on1y when experimental conditions are strictly applied by field managers is it possible to reach interpretable results. In the case of Argelès, fire prevention management was strictly applied under our proposed specifications. In Calmeilles, treatment was well done but Zone B was not in direct contact with the two other zones (500 m away). Finally Zone B of Campoussy was totally cleared (Zone A type treatment) and we managed to stop field managers before Zone C was heavily damaged too. A special mention in this locality, as many specialized Mediterranean species prefer open field conditions, they are naturally absent from type C Zones.

Such management problems are finally very informative as they show the high sensitivity of our statistical treatments to define functional groups. Anyway, there is sorne serious support for the functional groups as our results for the locality of Argelès clearly show that specialized species prefer conserved habitats when available. In the two other locations, sorne specialized species were able to survive and were found flying in disturbed areas as long as sorne patches of host plants remain.

Fire prevention management therefore favoured sorne generalist species but damaged populations of specifie/ endemie Lepidoptera but also other insects (Fowles et al. 2004, Quartau 2009). However, it seems that the resilience of these insects is high (Fowles et al. 2004;Luque et al. 2007) as shown between our 2 years of collection ( especially clear for CAM). That is why a balance must be drawn between the efficiency of complete cuts ("Zone A" type) to protect Mediterranean forest and long-term damage to populations of specialized Lepidoptera (y./ arren et al. 1987) even if such policies show a high level of efficiency in comparable areas (Collins and Stephens 2007). Our approach therefore clearly shows for the first time that, in choosing between the degrees of fire protection afforded by the different types of measure studied here, the degree of disturbance to native fauna should also be taken into account. Although treatments A and B, do not change people's global perception (Ricouart 2005) of the landscape, maintaining the same number of butterflies species in each type of treatment area, they significantly reduce populations of specialized and endemie insects of the zone to be protected from tires. The present results involving granitic areas are furthermore congruent with sorne studies done in calcareous areas where persistence of sheltered areas (our type C) favoured endemic/specialized species while opening of the forest and colonization by grasses (our types A and B) represents a negative factor which favoured generalistlmigrating species (Rosin et al. 2011 ). Therefore, from an angle of conservation of endemie/specifie species our results indicate that the type C management approach should be favoured whenever possible mainly for species naturally living in shrub/forest bi ota.

Fig. 1

 1 Fig. 1 Map of the studied locaticms includiDg main rivers

Fig. 4

 4 Fig. 4 Heuristic distance trees

Fig

  Fig. 4 continued

Table 1

 1 Geograpbical, climatological and ecological toeitll of the tine stwiy sites

		Argelês-sur-mer
	CoordiDales
	Latitude	42°3l'N
	Longitude	3°3 1 8
	Altitude (in m)	200-SOO
	Geology	Graaitoi.des, gneiss
	Average 8DilWil temperature	13 "C
	Precipitaticmlyear (in mm)	800-900
	DomiDant trees	QueTCUI su#Hr
		Q.

ilex Dominant sbrubs EricCI oeboreQ Cisttu monspelien~is Ulex ptiTVijlorwr few

  species such as Melitaeini and Leptidea reali, identi.ty was confirmed by preparing genitalia. For this Iast tribe, we based our nomenclature on that of Zimmermann et al.

cvborea Cist#s lmmfoliu CalJma 'IIUlgtJris Rubuasp Genista pilo.sa SQrot/rt.mmu ICOJXITÎUS we checked

  for the presence of a potential host-plant) are often invalid (Shreeve et al. 2001; Soberon and Townsend-Peterson 2005), this preiiminary analysis should detect if,

	Calmeilles	Campoussy
	42"32'N	42°4l'N
	2°42'8	2~18
	400-600	800-900
	Schist	Granioes, prolÙlDity of limestoae
	12 "C	10 oc
	900-1,000	1,000-1.100
	Qwrctd Ua	l'nl1lus spltuna
	Q. pubescetf8	Qwrctd pubescetf8
	Erial

Table 2

 2 Description and treatment characteristics of the three study sites

		Argèles-sur-mer
	Region	Albères
	Management in 2000	Undergrowth clearing in Zones A (100 %) and B (75 %) + fencing
		in Zones A and B
	Management in 2001	Fencing in Zone C
	Zone A surface area (ha)	6.82
	Zone B surface area (ha)	11.6
	Zone C surface area (ha)	51.13
	Pasture	Goats
	Total surface area (ha)	70
	See text to explain the srnall surface of Zone C Campoussy
	3. Forest zones including edges (mainly composed of
	shrubs).

Table 3

 3 Samples collected at the three study sites

	Species	Argelès sur mer					Calmeilles					Campoussy
		Zone A		ZoneB		Zonee		Zone A		ZoneB		Zone C		Zone A		Zone B		Zone C
		2000	2001	2000	2001	2000	2001	2000	2001	2000	2001	2000	2001	2000	2001	2000	2001	2000	2001
	Carcharodus alceae													x	x	x	x
	Hesperia comma														x		x
	Pyrgus armoricanus														x		x
	Pyrgus cirsii										x								x
	Pyrgus malvoides											x
	Pyrgus serratulae														x		x
	Thymelicus acteon																	x
	Thymelicus sylvestris														x		x		x
	Aricia agestis	x	x	x	x						x							x
	Callophrys avis					x
	Callophrys rubi			x		x								x		x		x	x
	Celastrina argiolus	x	x		x		x				x	x	x		x		x
	Favonius quercus	x		x				x			x	x	x
	Glaucopsyche alexis											x
	Glaucopsyche melanops									x
	Lampides boeticus								x		x				x		x
	Leptotes pirithous		x			x	x		x	x	x
	Lycaena alciphron														x		x
	Lycaena phlaeas	x	x	x	x				x		x			x	x	x	x	x	x
	Polyommatus bellargus									x	x				x		x
	Polyommatus coridon													x	x	x	x	x	x
	Polyommatus escheri														x		x
	Polyommatus hispana													x		x
	Polyommatus icarus	x	x	x	x	x	x	x	x	x	x	x		x	x	x	x	x	x
	Polyommatus thersites									x
	Satyrium acaciae														x		x		x
	Satyrium esculi	x	x	x	x	x	x	x	x	x	x	x	x
	Satyrium ilicis							x	x				x	x		x

Table 3

 3 F1g. 2 Distance tree (Hcuristic

	continued
	Species	Argelès sur mer					Calmeilles					Campoussy
		Zone A		ZoneB		Zonee		Zone A		ZoneB		Zone C		Zone A		Zone B		Zone C
		2000	2001	2000	2001	2000	2001	2000	2001	2000	2001	2000	2001	2000	2001	2000	2001	2000	2001
	Papilio machaon	x	x											x	x	x	x
	Anthocharis cardamines					x								x	x	x	x	x	x
	Aporia crataegi													x	x	x	x		x
	Colias crocea	x	x			x	x		x	x	x			x	x	x	x	x	x
	Colias hyale										x			x		x			x
	Euchloe ausonia						x
	Gonepteryx cleopatra	x	x	x	x	x	x	x	x		x	x			x		x	x	x
	Gonepteryx rhamni								x				x
	Leptidea reali							x			x
	Pieris brassicae	x	x	x	x	x		x	x		x	x		x	x	x	x		x
	Pieris mannii		x
	Pieris napi	x	x		x			x				x		x		x
	Pieris rapae	x	x	x		x			x		x	x	x	x	x	x	x	x
	Pontia daplidice					x	x								x		x	x
	Number of species	23		18		25		30		31		31		50		50		41

Occurrences d.epending on treatment zone and year

Species are presented by familles: Hesperiidae, Lycaenidae, Nymphalidae, Papilionidae and Pieridae. Same presentation in Table

4

  represents generalist species, the tint two are widespread and common in Europe (Pieris

	Papilio machaon	Generalist	Northem cool generalist	73	0
	Anthocharis cardamines	Humid/trees and sbrubs	Northem cool generalist	99	y
	Aporia crataegi	Humid/trees and sbrubs	Northem cool specialist	95	y
	Colias crocea	Humid/open	Generalist	99	0
	Colias hyale	Humid/open	Northem cool generalist	93	y
	Euchloe ausonia	Xeric/open	Strict Mediterranean	23	y
	Gonepteryx cleopatra	Xeric/trees and sbrubs	Generalist	99	0
	Gonepteryx rhamni	Humid/trees and sbrubs	Generalist	48	0
	Leptidea reali	Humid/trees and sbrubs	Generalist	33	0
	Pieris brassicae	Humid/open	Generalist	95	0
	Pieris mannii	Generalist	Strict Mediterranean	23	0
	Pieris napi	Humid/trees and sbrubs	Generalist	71	0
	Pieris rapae	Generalist	Generalist	98	y
	Pontia daplidice	Xeric/open	Generalist	70	0
		Bio-indicator species	29/80 = 36%		N=ll%

Probabilities of collection given in %. Evaluation of the congruence theoreticallobserved Evaluation of the congruence: Y (yes), N (no) 9/80 species, 0: compatible but not positive or negative (see also "Results" section)

Acknowledgments Many thanks to the two laboratories in which this study was done: GEODE directed by Jean-Paul Métailié and ECOLAB directed during this study by Eric Chauvet.

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