Jérémy Carlot
email: jeremy.carlot@hotmail.fr

A Rovère

E Casella

D Harris

C Grellet-Muñoz

Y Chancerelle

E Dormy

L Hédouin

V Parravicini

L Hedouin

Community composition

Keywords:

Introduction

Global concerns are emerging about the increasing frequency of mass mortality of corals associated to coral bleaching events [START_REF] Van Oppen | Coral Bleaching Patterns, Processes, Causes and Consequences[END_REF]Heron et al. 2016;[START_REF] Hughes | Global warming and recurrent mass bleaching of corals[END_REF]. These disturbances are associated to severe habitat destruction that reduces the structural complexity (i.e., flattening) of coral reefs [START_REF] Newman | Reef flattening effects on total richness and species responses in the Caribbean[END_REF]. Structural complexity is the three-dimensional spatial arrangement of an ecosystem [START_REF] Mccormick | Comparison of field methods for measuring surface tomography and their associations with a tropical reef fish assemblage[END_REF][START_REF] Chazdon | Second Growth, the promise of tropical forest regeneration in an age of deforestation[END_REF]), which is largely due to the growth form and distribution of hard coral.

According to the habitat heterogeneity hypothesis [START_REF] Macarthur | The Theory of Island Biogeography[END_REF], the more complex the structure of an ecosystem, the greater the diversity and abundance of associated organisms. On coral reefs, the 3D structural complexity of the habitat is correlated to the biomass and diversity of fish [START_REF] Willis | Structure of cryptic reef fish assemblages: relationships with habitat characteristics and predator density[END_REF][START_REF] Gratwicke | Effects of habitat complexity on Caribbean marine fish assemblages[END_REF][START_REF] Alvarez-Filip | Flattening of Caribbean coral reefs: Region-wide declines in architectural complexity[END_REF]Rogers et al. 2014), to the reef capacity to recover from disturbance [START_REF] Graham | Predicting climatedriven regime shifts versus rebound potential in coral reefs[END_REF], but also to the reef ability to dissipate wave energy, thus protecting the shoreline from extreme inundations [START_REF] Harris | Coral reef structural complexity provides important coastal protection from waves under rising sea levels[END_REF]. Broad-scale declines in the complexity of coral reefs have been observed both in the Caribbean and the Pacific as a result of both human impacts and climate changes (Hoegh-Guldberg 1999; [START_REF] Hughes | Climate Change, Human Impacts, and the Resilience of Coral Reefs[END_REF][START_REF] Hoegh-Guldberg | Coral reefs under rapid climate change and ocean acidification[END_REF][START_REF] Perry | Loss of coral reef growth capacity to track future increases in sea level[END_REF]. Despite the well-known important relationship between structural complexity, ecological diversity, abundance and biomass, information on structural complexity is sparse in monitoring programs with the result that long-term trends for this variable are virtually unknown [START_REF] Graham | Predicting climatedriven regime shifts versus rebound potential in coral reefs[END_REF].

Methods to measure structural complexity (often referred as rugosity, in particular in older literature) on coral reefs first arose in the 70' in articles by [START_REF] Risk | Fish diversity on a coral reef in the virgin islands. Atoll Res Bull Rogers A[END_REF] and [START_REF] Hobson | Surface Roughness in Topography: A Quantitative Approach[END_REF]. These authors defined three criteria for measuring complexity: 1) the measure had to be easily understandable, 2) it had to be measurable during the fieldwork and, 3) it should be comparable. In early studies, it was proposed that rugosity could be recorded by draping a steel chain over the reef surface, and then measuring the ratio between the total length of the chain and the planar distance between the ends of the chain. The higher the ratio, the more complex the substratum (Hill and Wilkinson 2004;[START_REF] Graham | The importance of structural complexity in coral reef ecosystems[END_REF]. Despite the ease of use of such metric, laying a chain represents a bi-dimensional measure which does not capture the full complexity of complex three-dimensional (3D) habitats such as coral reefs. Although some time-consuming 3D metrics have been proposed in the past (e.g. [START_REF] Parravicini | A method to measure threedimensional substratum rugosity for ecological studies: an example from the date-mussel fishery desertification in the north-western Mediterranean[END_REF]), the recent progress in underwater photogrammetry are finally affording researchers the opportunity to capture the three-dimensionality of coral reefs. For example, [START_REF] Friedman | Multi-Scale Measures of Rugosity, Slope and Aspect from Benthic Stereo Image Reconstructions[END_REF] started to use a georeferenced survey work and each includes a downward-looking camera pair with a baseline of approximately 7cm, pixel resolution of 1360 ´ 1024 to define rugosity. Others authors like [START_REF] Burns | Integrating structure-from-motion photogrammetry with geospatial software as a novel technique for quantifying 3D ecological characteristics of coral reefs[END_REF] were using these new advances for defining the rugosity about a transect and extract a complexity index at the species level for 6 species. [START_REF] Leon | Measuring coral reef terrain roughness using "Structure-from-Motion" close-range photogrammetry[END_REF], defined three roughness parameters, namely the root means square height, tortuosity (i.e. rugosity) and fractal dimension, and were derived and compared in order to asses which one better characterizes reef flat roughness. [START_REF] Naughton | Scaling the Annotation of Subtidal Marine Habitats[END_REF] succeed with an accuracy never equaled to define maps of community structures between taxa. Some writers have even pushed the boundaries to measure the small-scale three-dimensional features of a shallow-water coral reef thanks to drone [START_REF] Casella | Mapping coral reefs using consumer-grade drones and structure from motion photogrammetry techniques[END_REF]. Thus, a plethora of works have emerged asking several authors about the chain-tape future [START_REF] Storlazzi | End of the chain? Rugosity and finescale bathymetry from existing underwater digital imagery using structure-from-motion (SfM) technology[END_REF]. However, whatever the metric employed (chain-tape or photogrammetry methods), there is still no clear evidence concerning what is driving structural complexity. Some authors claim that it is driven by the presence of some branching species like the Acropora spp. and thus the overall coral cover would not matter [START_REF] Aronson | Conservation, precaution, and Caribbean reefs[END_REF][START_REF] Alvarez-Filip | Flattening of Caribbean coral reefs: Region-wide declines in architectural complexity[END_REF][START_REF] Alvarez-Filip | Region-wide temporal and spatial variation in Caribbean reef architecture: Is coral cover the whole story?[END_REF]. Others have found that coral cover is significantly and highly correlated to the rugosity [START_REF] Halford | Resilience to Large-Scale Disturbance in Coral and Fish Assemblages on the Great Barrier Reef[END_REF][START_REF] Graham | The importance of structural complexity in coral reef ecosystems[END_REF] or species composition [START_REF] Richardson | Cross-scale habitat structure driven by coral species composition on tropical reefs[END_REF]. But in both cases, there is a common consensus for admitting coral drives complexity which could be used for rebuilding past rugosities.

In this study, we combined statistical modeling to 3D reef transects reconstructed using photogrammetry in order to test the potential to predict coral reef structural complexity on the basis of benthic community composition. We study the reefs of Moorea (French Polynesia) where, using benthic communities time series we back-calculate reef structural complexity. We were able to retrace two relevant episodes of habitat destruction: the Acanthaster planci outbreak of 2006-2009 and cyclone Oli of 2010.

Material and Methods

Study area

Moorea is a tropical volcanic island of volcanic origin, located in the Pacific Ocean between 17.4714° and 17.6058° South and 149.7522° and 149.9269°' West. The island is shaped as a triangle with a perimeter of 61 km and coastlines facing north, southwest and southeast (Fig. 1). The island is encircled by a coral reef, that is 500 to 700 m wide; the only exception to this pattern is the Northeast extremity where the lagoon width is limited to few tens of meters. Moorea is exposed to Northwest winds from January to March. Tides are semidiurnal with an amplitude of less than 0.3 m [START_REF] Chazottes | Bioerosion rates on coral reefs : interactions between macroborers , * Experimental site[END_REF][START_REF] Leichter | Biological and physical interactons on a tropical island coral reef: transport, and retention processes on Moorea, French Polynesia[END_REF].

The swell direction is from southwest to northeast during the whole year.

The reefs of Moorea are threatened by several disturbances of biotic and abiotic origin [START_REF] Adjeroud | Recovery of coral assemblages despite acute and recurrent disturbances on a South Central Pacific reef[END_REF]. The most devastating biotic disturbances were the 1979 and 2006

Acanthatster planci outbreak, which reduced coral cover from 50% to 10% [START_REF] Ullman | The interpretation of structure from motion[END_REF][START_REF] Berumen | Recovery without resilience: Persistent disturbance and long-term shifts in the structure of fish and coral communities at Tiahura Reef, Moorea[END_REF] and from 50% to less than 10% (in 2006; [START_REF] Lamy | Three decades of recurrent declines and recoveries in corals belie ongoing change in fish assemblages[END_REF]. Abiotic disturbances also impacted Moorea island, with main cyclones recorded in 1991 (Wasa) and 2010 (Oli). The impact of Wasa reduced the coral cover by 5% to over 20% across all the island. In contrast, coral cover was reduced to lower than 5% by Cyclone Oli [START_REF] Lamy | Three decades of recurrent declines and recoveries in corals belie ongoing change in fish assemblages[END_REF][START_REF] Adjeroud | Recovery of coral assemblages despite acute and recurrent disturbances on a South Central Pacific reef[END_REF]) (Fig. 2).

Rugosity measures

In Moorea, a total of 57 photogrammetric transects were surveyed in end-of-2015beginning-of-2016, at three different sites: Tiahura (North Coast, 21 transects); Haapiti (Southwest coast, 20 transects) and Temae (Southeast coast, 16 transects) (Fig. 1). Each transect consisted of swaths of 20m length and 2m width and all transects were carried out in the outer reef, between 5 and 8m depth. Each transect was set up fixing on the bottom a 2m-long chain and, perpendicularly to it, a 20m-long metered tape. A diver swam »2m above the sea-bottom, maintaining the swimming speed as constant as possible and collecting images with a GoPro Hero camera pointed towards the sea-bottom. The camera was set to collect photos (12 megapixels) in time-lapse mode (2 pictures per second). For each transect, we collected approximately 200 photos with a forward overlap of »90%, with the diver swimming over the length of the entire transect four times to allow optimal side overlap. After the collection of the photos, the diver noted the depth of each extremity of the chain and metered tape to use them in the photogrammetric process as Ground Control Points (GCPs). In the case of an on-the-job self-calibration, the camera calibration is derived from image coordinates measured in the mapping photography and including the camera calibration parameters as unknowns in a selfcalibrating bundle adjustment [START_REF] Harwin | The Impact of the Calibration Method on the Accuracy of Point Clouds Derived Using Unmanned Aerial Vehicle Multi-View Stereopsis[END_REF].

The set of photos and the GCPs collected were then used as input to Agisoft Photoscan (www.agisoft.com), a photogrammetry software based on the Structure from Motion (SfM) method [START_REF] Ullman | The interpretation of structure from motion[END_REF][START_REF] Westoby | Structure-from-Motion" photogrammetry: A low-cost, effective tool for geoscience applications[END_REF]. We used Agisoft to build the orthophotomosaic and the Digital Elevation Model (DEM) of each transect, with the same procedure explained by [START_REF] Storlazzi | End of the chain? Rugosity and finescale bathymetry from existing underwater digital imagery using structure-from-motion (SfM) technology[END_REF]. Details of the photogrammetric process are shown in the Annex S1.

Subsequently, we imported the DEM in ArcGIS v10.2 and calculated the reef rugosity by dividing the surface of the DEM area by the area of its planar projection (approximately 40m 2 ) (Fig. 3). For the 57 transects, we estimated an average horizontal error of 0.1±0.06m and average vertical error of 0.04±0.04m, internal to the reconstructed model. Only the vertical error had an influence on the estimation of rugosity, but given the range of the error, it was considered negligible.

Benthic community description and assessment

The orthophotomosaics were imported into Coral Point Count, which was used with an Excel extension v4.1 [START_REF] Kohler | Coral Point Count with Excel extensions (CPCe): A Visual Basic program for the determination of coral and substrate coverage using random point count methodology[END_REF]. We assessed the benthic cover placing 100 random points on the photomosaic and described 8 distinct benthic cover categories (Table 1). A second dataset was used according to the CRIOBE surveys from 2004 to nowadays and consists of 25m point intercept transects data collected at 13 sites around the island across three habitats (fringing reef, back reef, outer reef) and using the same benthic categories (Fig. 1).

This classification is based on the guideline of the monitoring program created by SO CORAIL (http://observatoire.criobe.pf/CRIOBEData/), the coral reef observation program of the French National Institute for Earth Sciences and Astronomy (INSU). These categories enabled us to back-calculate structural complexity on time series data from Moorea. For matching both datasets according to the habitat, only the outer reef was selected.

Statistical analysis

Our main goal was to calibrate a model that predicts structural complexity according to the benthic community composition. Since benthic community cover is expressed as percentages, we preferred not to use them as predictor variables as they are heavily correlated, and collinearity would have been high. We preferred to build a database that include the time series data and our photogrammetry transects without transforming the data to perform multivariate analysis. Thus, the Euclidean distance could be used to conduce a Principal Component Analyses (PCA). The first five orthogonal axes (accounted for more than 75% of the variance) were then extracted to be used as predictor variables in the model. A lasso generalized linear model has been conducted to predict coral reef structural complexity according to the 5 PCA axes. A 10-Fold cross validation was done and a step AIC procedure defining the best model was applied. Because the 57 transects were measured at the same depth, those transects were pooled together rather to apply a mixed model due to the lack of the data, making us benefit from a solid robustness. The best model selected kept only 3 PCA dimensions. According to the k-fold analysis, k R 2 were obtained giving a necessary uncertainty for the model. This method appears more meaningful estimate than classical R 2 when the model has to be used for predictions. The lasso generalized linear model was then applied to time series data to back-calculate structural complexity and to test whether our model was able to detect drops of structural complexity due to the major perturbations.

The PCA data for the time series in Moorea were used to produce PCA plots and define the long-term tendencies in order to descriptively assess the entity of the effect of the Acanthaster planci outbreak (2006)(2007)(2008)(2009) and the Oli cyclone (2010) on benthic communities.

An ANOVA was then applied with the aim to define several bunches of similar years according to the PCA axes. To match those years with each other, a Tukey post-hoc analysis was conducted and a matrix of results was elaborated. Finally, special attention has been given about the Acropora spp. cover, Pocillopora spp. cover and rugosity index in 2004 (pre-disturbance year, with the high percent cover of corals) and 2017 (post-disturbance year, with the high percent cover of corals) to define a potential resilience or recovery (Table S1).

Results

The analysis of time series revealed that coral diversity was higher in 2004 with a percent cover of corals (CC) of 44.08% (Fig. 4). The CC decreased from 2004 to 2010 down to a minimum of 3.62%, which corresponds to the event of Cyclone Oli. After the cyclone passed, the coral cover increased over time until the end of the series (2017) with a final value of 42.77%. In 2004 the coral reefs of Moorea also showed a greater diversity of coral morphology (massive, branching in general, columns and encrusting). The assemblages remained fairly stable despite a slow decline of the CC the first 2 years (CC2004 = 44.08% to CC2006 = 40.62%). Then, a first Crown-Of-Thorns Starfish (COTS) outbreak was reported in early 2006 [START_REF] Kayal | Predator Crown-of-Thorns Starfish (Acanthaster planci) Outbreak, Mass Mortality of Corals, and Cascading Effects on Reef Fish and Benthic Communities[END_REF] and continued until 2009. The following year, cyclone Oli hit the island further decreasing the CC. After these events and until 2014, the substrate consisted of rubble and cobbles. From 2015, the CC recovered to a state similar to that of 2004. However, compared to 2004, the coral cover in 2017 was dominated by Pocillopora spp. (20.10 ± 6.78% in 2004 vs 26.61 ± 14.52% in 2017) instead of a more diverse assemblage with a high abundance of Acropora spp (9.76 ± 5.61% vs 2.53 ± 1.90% in 2017).

The cross-validated R 2 (CV-R 2 ) from our model reaches 0.81 ± 0.12. The 3 dimensions used were all significant and non-correlate (Table 2,Fig S1). The back calculation of structural complexity captured these major shifts in community structure. High structural complexity was observed in 2005 and 2006. All sites were then predicted to lose complexity corresponding to the timing of COTS outbreak models present patterns of decrease and increase in rugosity, matching with the biotic and abiotic changes like the COTS outbreak and the Cyclone Oli, as discussed above (Fig. 5). The model also exemplifies that the resilience of structural complexity differs among the thirteen reefs studied around Moorea island. In 2004, the highest values of structural complexity were measured respectively at Pihaena (North), Motu Ahi (East) and Haapiti (Northwest) (3.86, 3.51 and 2.92 respectively) while the lowest were recorded in Maatea (Southeast), Tiahura (North) and Aroa (North) (2.26, 2.07 and 1.81 respectively). After the disturbances in 2010, the higher values were defined in Taotaha (Northwest), Afareaitu (Southeast) and Entre 2 Baies (North) (2.08, 2.10 and 2.10 respectively) while the lowest values were documented at Haapiti (Northwest), Tiahura (North) and Maatea (Southeast) (1.84, 1.66 and 1.15 respectively).

Finally, in 2017, the 3 lowest values were measured on the East coast (Motu Ahi, Maatea and Temae with rugosity values of 2.35, 2.12 and 1.98 respectively) while the sites located on the northwest side (Entre 2 Baies, Tiahura and Gendron) presented the 3 higher rugosity scores (4.36, 4.31 and 3.53 respectively).

Finally, rugosity values rise to values equivalent to the first year of monitoring, during the last year of monitoring in 2017. The presence of Acropora spp. shows a significant difference between 2004 and 2017. However, no significant difference could be observed in either the Pocillopora spp. presence or the rugosity score (Fig. 6). In addition, the ANOVA followed by the post-hoc analysis confirmed a difference between two bunches of years according to the complexity around the island. Indeed, two profiles were highlighted: 1) one from 2004 to 2007 and 2016 to 2017 and 2) one from 2008 to 2015. These results support that the 3D complexity came back to an equilibrium four years after the Oli cyclone (Table S1).

Discussion

In this study we used a combination of methods -coral reef photogrammetry and statistical models -to test the potential to use species composition data to predict the structural complexity of coral reef assemblages. The use of the photogrammetry allowed us to obtain a three-dimensional metric of structural complexity, compared to linear metrics classically used such as the chain transect [START_REF] Burns | Integrating structure-from-motion photogrammetry with geospatial software as a novel technique for quantifying 3D ecological characteristics of coral reefs[END_REF]. Photogrammetry permits us to cover 40m 2 of the reef in one dive of about 90 minutes, whereas the chain method usually requires approximatively 15 minutes for a simple 20m transect. However, even if the pixel size of 1. 73´ 1.73 µm -used for defining the complexity -is higher resolution than what is achieved using chain and tape, the results have to be interpreted with cautious. Indeed, a number of studies have shown photogrammetry to be error prone in a number of different ways. [START_REF] Lavy | A quick , easy and non-intrusive method for underwater volume and surface area evaluation of benthic organisms by 3D computer modelling[END_REF] and [START_REF] Figueira | Accuracy and Precision of Habitat Structural Complexity Metrics Derived from Underwater Photogrammetry[END_REF] both found that branching corals and other complex growth forms produce more error in photogrammetry-based estimates of complexity compared to in situ methods. Furthermore, [START_REF] Bryson | Characterization of measurement errors using structure-motion and photogrammetry to measure marine habitat structural complexity[END_REF] found that environmental conditions, postprocessing, and even taking photos underwater can impact the accuracy of 3D structure estimates using photogrammetry. In addition, this model is relevant for planar parts of the reef, however, facing dropoff would be challenging. This technique requires swimming over the bottom, nevertheless, as the more the distance you add between you and the bottom, the worst the reconstruction will be. Finally, all the hidden part (not present in the photos) are not reconstructed (e.g. what is inside a hole). The latter limit causes relatively heavy consequences to define an accurate measure of the rugosity in those conditions. From a statistical point of view, [START_REF] Carroll | Sexual reproduction of Acropora reef corals at Moorea , French Polynesia[END_REF] defined 3 different regimes of swell in Moorea which could altered the benthic composition, according to the exposure due to the side of the island. Even if these affirmations are directly observable concerning the rugosity in 2017 with our current model (lowest values on the east coast and higher values on the north coast) a mixed model would have been more relevant. Unfortunately, only 16 transects were done on the southeast side of Moorea which is not allowed us for using a mixed model. The robustness of the model would have been directly impacted by the lack of residuals (rugosity values sometimes lower than 1; [START_REF] Launer | Robustness in statistics[END_REF]. As per any statistical model, the accuracy of prediction will increase with the size of the calibrating dataset. In that context, more data will likely be needed to accurately capture spatial variation. Despite these limits, we have found a significant relationship between reef structural complexity and the composition of the benthic assemblages. Indeed 3 PCA axes were enough to accurately predict complexity with a high accuracy (CV-R 2 = 0.81 ± 0.12). To validate our model, we compared our values to [START_REF] Kayal | Bias associated with the detectability of the coraleating pest crown-of-thorns seastar and implications for reef management Subject Category : Subject Areas[END_REF]). These authors have found values at 12mdepth of 1.44 ± 0.08, 1.41 ± 0.05 and 1.70 ± 0.03 for Haapiti, Tiahura and Entre 2 Baies respectively. Our model suggests values for these locations of 1.75 ± 0.50, 1.68 ± 0.47 and 1.70 ± 0.60 respectively. Thus, even according the huge range of the uncertainties, our results highlight the potential to use statistical modeling to predict structural complexity when this information is lacking. Given the importance of structural complexity in ecological functioning of coral reefs, the reconstruction of structural complexity is critical from long-term benthic historical data, if we want to better understand and predict changes in coral reefs. For example, [START_REF] Graham | The importance of structural complexity in coral reef ecosystems[END_REF] reviewed 20 studies using chain method to measure coral reef rugosity in the Caribbean and found a strong negative relationship between structural complexity and algal cover, a positive relationship between the structural complexity and the coral cover, and a strong positive relationship between structural complexity and fish density and biomass.

Later, [START_REF] Graham | Predicting climatedriven regime shifts versus rebound potential in coral reefs[END_REF] demonstrated that structural complexity is the main predictor of coral reef recovery capacity after acute disturbance. This metric represents thus a key variable of coral reef status, and apodictically exists also regarding the present day flattening of coral reefs under the influence of climate change and human impacts. Back-calculating structural complexity, with due caution, may be important to infer present coral reef status compared to historical or quasi-pristine conditions.

Here, we have documented major changes in benthic assemblages across Moorea's coral reefs [START_REF] Berumen | Recovery without resilience: Persistent disturbance and long-term shifts in the structure of fish and coral communities at Tiahura Reef, Moorea[END_REF][START_REF] Adjeroud | Recovery of coral assemblages despite acute and recurrent disturbances on a South Central Pacific reef[END_REF]). Acropora spp. and Pocillopora spp.

were dominant species in 2003 [START_REF] Berumen | Recovery without resilience: Persistent disturbance and long-term shifts in the structure of fish and coral communities at Tiahura Reef, Moorea[END_REF] and this was still the case in 2004.

Pocillopora spp. then, Acropora spp. were affected by both COTS outbreak and the Oli cyclone more than any other taxon [START_REF] Kayal | Predator Crown-of-Thorns Starfish (Acanthaster planci) Outbreak, Mass Mortality of Corals, and Cascading Effects on Reef Fish and Benthic Communities[END_REF]. Branching and table-shaped species belonging to the genus Acropora were affected first and most heavily. Then, it was followed by those of sub-branching Pocillopora. Finally, Populations of encrusting Montipora, massive Porites, and other hard-coral assemblages also declined, showing a synchronized collapse with the entire coral communities. From 2011 onward, benthic assemblages started to recover mainly thanks to encrusting coral forms and Pocillopora spp. that is presently the dominating coral form in Moorea. The current Pocillopora-dominated state may be a transitional phase, indicative of either continuing degradation or recovery [START_REF] Aronson | Phase shifts alternative states and the unprecedented convergence of two reef systems[END_REF]). Our back-calculated structural complexity was able to capture major changes due to COTS outbreak and Cyclone Oli, thus attesting the potential to use statistical modeling when the rugosity has not been empirically collected. However, the status of coral reefs in 2004 when Acropora spp. was on average »10% and the present status (average Acropora cover »2%) was not enough to distinguish difference in back-calculated structural complexity. There are two proposed explanations for this observation: (a) our model is calibrated with present-day data. Only two transects in 2017 had assemblages with an Acropora cover higher than 5% which is a consequent statistic assumption according to the Acropora cover in 2004 (9.76 ± 5.61% in 2004 vs 2.53 ± 1.90% in 2017). This again results in an extremely cautious interpretation of the results due to a possible underestimation of Acropora spp. in the past years [START_REF] Aronson | Conservation, precaution, and Caribbean reefs[END_REF][START_REF] Alvarez-Filip | Flattening of Caribbean coral reefs: Region-wide declines in architectural complexity[END_REF][START_REF] Alvarez-Filip | Region-wide temporal and spatial variation in Caribbean reef architecture: Is coral cover the whole story?[END_REF]. And/or (b) Acropora and Pocillopora taxa harbored branching form and similarly contribute to the complexity [START_REF] Reichert | The power of 3D fractal dimensions for comparative shape and structural complexity analyses of irregularly shaped organisms[END_REF]. Thus, the complexity could be rebuilt according to the coral cover underlying the different coral morphologies [START_REF] Halford | Resilience to Large-Scale Disturbance in Coral and Fish Assemblages on the Great Barrier Reef[END_REF][START_REF] Graham | The importance of structural complexity in coral reef ecosystems[END_REF][START_REF] Richardson | Cross-scale habitat structure driven by coral species composition on tropical reefs[END_REF]. In order to sharp our hindcasting, the reproducibility of this method could allow us to find a new area with the needed information (i.e. past Acropora and Pocillopora cover vs post Acropora and Pocillopora cover and past and post rugosity) and to test our model. Waiting for this improvement, the CC could be enough accurate to rebuild the past and to predict the complexity for the coming years. Indeed, today more than ever, global coral reefs are witnessing the effects of climate changes, local impacts and natural stressors. Coral bleaching is affecting global coral reefs with an unprecedented frequency and intensity and the future structural complexity of coral reefs is expected to be reduced by these repeated perturbations [START_REF] Hughes | Spatial and temporal patterns of mass bleaching of corals in the Anthropocene[END_REF][START_REF] Lough | Increasing thermal stress for tropical coral reefs : 1871 -2017[END_REF]. As a consequence a loss of ecological diversity productivity is likely [START_REF] Alvarez-Filip | Flattening of Caribbean coral reefs: Region-wide declines in architectural complexity[END_REF]). is representing in red. The p-value is represented on the top of each barplot according to the significant R code (*** highly significant (<0.001), **very significant (<0.01), * significant (<0.05), . almost significant (<0.1), N.S non-significant; threshold: p-value = 0.05) Tab. 1 Categories of shape classification defined and used to rebuild the rugosity these last 14 years. 9 variables are morphologic instead a distinction at the genus level is done for Acropora spp. and Pocillopora spp. The CCA was differentiated from the pavement according to their extension: when this later was higher than 100 cm 2 , which corresponds to a projected surface of a circle of radius of 5-6 cm it was considered as CCA rather than pavement. The dead corals category understands rubbles and cobbles. The flattening category represents sand or mud substrate. The categories Encrusting, Other Erect Forms and Massive represent different coral morphologies. Finally, the others category represents mostly benthic organism like echinoid or even sponges.

Figures Fig. 1

 1 Figures

  Fig. 3 GCP locations Tab. 2 Control points Label XY error(m) Z error (m) Error (m) Projections Error (pix) point1 0.206298 -0.0677987 0.217153 13 1.992 point2 0.0963633 0.0426041 0.105361 16 1.153 point3 0.039409 3.96756e-05 0.039409 17 0.051 point4 0.205045 0.0251539 0.206582 9 0.044 Total 0.154468 0.0419657 0.160067 1.151

Conflict of interest:

On behalf of all authors, the corresponding author states that there is no conflict of interest.

Appendix

Tab. S1 Post Hoc (Tukey HSD) matrix for testing the rugosity difference according to each year combination. The P-value (threshold: 0.05) for each combination is written in the matrix data as follows. The red values are significantly differents and the blue values are not.

Annex

Annex S1 Report from Agisoft Photoscan for one site, detailing the settings used for the processing of underwater photos.

1. Survey Data Fig. 1


Maxime Fréneau

Corentin Lefebvre

Mario Andrés Gomez Fernandez

Claire Richard

Norbert Hoffmann

Photochemical reactivity of phenyl (methyl)tetrazolium ketone-Hydrogen atom transfer vs electron transfer

Keywords: Fungicide, laser flash photolysis, ketyl radical, zwitterionic diradical, hydrogen atom transfer, proton coupled electron transfer

Phenyl (methyl)tetrazolium ketone (1) is a synthesis intermediate of tetrazolyloxime fungicides and can be also generated upon their irradiation. Its photolysis is highly solvent dependent which prompted us to investigate more deeply the reaction mechanism. Nanosecond laser flash photolysis of 1 yielded the triplet excited state ( max = 390/570 nm) immediately after the pulse. This latter was converted into different secondary species that were identified using their specific reactivity as well as product studies. The ketyl radical ( max = 315/475 nm) was generated in less than 0.02 s in a good H-donor solvent such as 2-propanol and in around 0.06 s in cyclohexane, a medium H-donor solvent. In 2-propanol, ketyl radicals decayed by a second order reaction to yield pinacol (yield 45%) while in cyclohexane, they decayed by a second order reaction in the bulk leading to pinacol (yield 21%) and by recombination with the cyclohexyl radical in the cage in an apparent first order reaction to generate an adduct (yield 10%). In a polar and non H-atom donor solvent as acetonitrile, the zwitterionic diradical ( max = 460 nm) was formed in 0.6 s with final formation of an atypic dimer. Thus two mechanisms of hydrogen atom transfer are observed. In polar acetonitrile solvent, a twostep-process occurs where the electron is transferred first and the proton follows. In non-polar 2propanol and cyclohexane solvents, a one-step process takes place where the electron and the proton are simultaneously transferred.

Introduction

Plant protection is a key issue in connection with food supply of the mankind. Due to resistance to existing pesticides and environmental requirements and legislation, an increasing number of chemical compounds are synthesized and tested in this regard. Chemical structures of such compounds become more and more complex. Concomitantly with these developments, the weak stability of highly active compounds becomes a decisive problem. In this context, photostability plays a key role. Often, new highly active compounds loss almost completely their activity when exposed to solar light in field. A deep understanding of the mechanisms of corresponding photochemical reactions is necessary for either suppress or at least reduce these processes or to conceive or design photostable molecules and finally diminish the "chemical impact" of plant protection in the environment.

Recently, we performed a detailed investigation on the photodegradation mechanism of tetrazolyloxime fungicides in order to increase their photostability. [START_REF] Fréneau | Phototransformation of Tetrazoline oxime ethers: Photoisomerization vs photodegradation[END_REF] In the course of these investigations, we observed the formation of the aromatic ketone 1 (Scheme 1) among other compounds. Compound 1 is also a synthesis intermediate of fungicides such as picarbutrazox (Scheme 1). [START_REF] Ichinari | Generation of hazardous methyl azide and its application to the synthesis of key-intermediates of picarbutarox[END_REF] Scheme 1. Chemical structure of 1 and picarbutrazox We became interested in the photochemical transformations of ketone 1 because of the possibility of hydrogen atom transfer. In fact in such reactions, hydrogen is often transferred according to two mechanisms: Either the electron and the proton are transferred simultaneously (hydrogen atom transfer, HAT) to the electronically excited reaction partner or the electron is transferred first and the proton follows. [START_REF] Hoffmann | Electron and hydrogen transfer in organic photochemcial reactions[END_REF] These two elementary steps are part of a larger ensemble of proton coupled electron transfer processes (PCET). [START_REF] Reece | Photon-coupled electron transfer: the mechanistic underpinning for radical transport and catalysis in biology[END_REF] , 5

Experimental

General information

Ketone 1 was a gift from Bayer Crop Science. All other reagents were of the highest grade available and used as received. UV-vis spectra were recorded using a Varian Cary 3 spectrophotometer. [START_REF] Fréneau | Phototransformation of Tetrazoline oxime ethers: Photoisomerization vs photodegradation[END_REF] H and 13 C NMR spectra were measured in CDCl 3 with TMS as an internal standard by using a 600 MHz ( 1 H resonance) a Bruker spectrometer. The identification of photoproducts was performed using High resolution mass spectrometry (HRMS) constituted of an Orbitrap Q-Exactive (Thermoscientific) coupled to an ultra-high performance liquid chromatography (UHPLC) instrument Ultimate 3000 RSLC (Thermoscientific). Analyses were carried out in both negative and positive electrospray modes (ESI + and ESI -). UHPLC separations were performed using a Phenomenex reversed phase column C 18 grafted silica, (100 mm length, 2.1 mm i.d., 1.7 μm particle size). The binary solvent system used was composed of acetonitrile (MeCN) and water acidified with 0.5‰ v/v formic acid. The gradient program was 5% ACN for the 7 first min, followed by a linear gradient to 99% in 7.5min and kept constant until 20 min. The flow rate was set at 0.45 mL/min and injection volume was 5 μL. Identification of photoproducts was based on structural elucidation of mass spectra and the use of accurate mass determination obtained with the Orbitrap high resolution. HPLC-UV analyses were performed using a NEXERA XR HPLC-DAD apparatus using the same column and the same HPLC conditions as previously indicated.

Laser flash photolysis

Transient absorption experiments were carried outon a nano laser flash photolysis spectrometer from Applied Photophysics (LKS.60) using a frequency-quadrupled Nd:YAG laser (Quanta-Ray GCR-130-1, pulse duration 9 ns). The procedures used for transient absorption spectroscopy measurements have been described previously. [START_REF] Bonnichon | Phototransformation of 3-hydroxybenzonitrile in water[END_REF] The spectral characteristics of 1 are given in Table SI-1 and Figure SI-1. The maximum of absorption is just below 270 nm and 1 was therefore excited at 266 nm. Peroxodisulfate was used as a chemical actinometer.

Steady state irradiations

For preparative purpose, irradiations were conducted in a tube placed in a Rayonet (λ = 300 nm). For quantum yield measurements, solutions were irradiated in parallel beam using a high pressure mercury lamp equipped with an Oriel monochromator. The photon flux was measured using a radiometer QE65000 from Ocean optics. The percentage of 1 conversion was determined by HPLC-UV.

Identification of photoproducts

Photoproduct 2: Compound 1 (220.5 mg, 1.17 mmol) was dissolved in 30 mL of MeCN, poured in quartz tubes and degassed with argon during 10 min. The tubes were then placed in a Rayonet and irradiated at 300 nm for 40 min. The solvent was evaporated under reduced pressure and the crude was purified by silica column chromatography (petroleum ether/ethyl acetate: 80:20). Starting material was isolated in 58 % yield (150 mg, 0.68 mmol) and product 2 was obtained in 26 % yield (48.3 mg, 0.13 mmol) as a white solid (R f (petroleum ether/ethyl acetate: 70/30) = 0.22, melting point range : [82.0°C-82.7°C]). NMR [START_REF] Fréneau | Phototransformation of Tetrazoline oxime ethers: Photoisomerization vs photodegradation[END_REF] Photoproduct 3 in 2-propanol (i-PrOH): Compound 1 (92 mg, 0.49 mmol) was dissolved in 60 mL of i-PrOH, poured in quartz tubes and degassed with argon during 10 min. The tubes are then placed in a Rayonet and irradiated at 300 nm for 4 h. The solvent was evaporated under reduced pressure and the crude was purified by silica column chromatography (petroleum ether/ethyl acetate: 95/5 to 50/50). Product 3 was obtained in 46 % yield (85 mg, 0.22 mmol) as a white solid (R f (petroleum ether/ethyl acetate: 80/20) = 0.76, brown stain on TLC with vanillin revelator, melting point range : Photoproduct 3 in n-heptane: Compound 1 (96 mg, 0.51 mmol) was dissolved in 110 mL of nheptane, poured in quartz tubes and degassed with argon during 10 min. The tubes were then placed in a Rayonet and irradiated at 300 nm for 2 h 30. The solvent was evaporated under reduced pressure and the crude was purified by silica column chromatography (petroleum ether/ethyl acetate: 95/5 to 50/50). Product 3 was obtained in 15 % yield (29 mg, 0.08 mmol) as a white solid.

Photoproduct 4: Compound 1 (220.2 mg, 1.17 mmol) was dissolved in 80 mL of cyclohexane, poured in quartz tubes and degassed with argon during 10 min. The tubes were then place in a Rayonet and irradiated at 300 nm for 6 h. The solvent was evaporated under reduced pressure and the crude was purified by silica column chromatography (petroleum ether/ethyl acetate: 90:10). Stains on TLC plates were revealed with vanilline. Product 3 was obtained as major product in 21 % yield (94 mg, 0.25 mmol) as a white solid. Minor product 4 was obtained in 10 % yield (31 mg, 0.11 mmol) as a clear liquid (R f (petroleum ether/ethyl acetate : 80/20) = 0.30, blue stain on TLC with vanillin revelator). NMR 1 H (600 MHz, CDCl 3 , ppm) :  = 0.99 (qd, J = 3.48, 12.42 Hz, 1 H), 1.13 (m, 2 H), 1.24 (m, 2 H), 1.47 (qt, J = 3.48, 13.02 Hz, 1 H), 1.70 (m, 2 H), 1.82 (m, 1 H), 2.05 (d, J = 12.18 Hz, 1 H), 2.7 (tt, J = 2.82, 12.12 Hz, 1 H), 2.85 (s, 1 H), 3.83 (s, 3 H), 7.30 (m, 5 H) ppm. NMR [START_REF] Mayer | Understanding Hydrogen Atom Transfer: From Bond Strengths to Marcus Theory[END_REF]

Results

Product studies

When compound 1 was irradiated in acetonitrile at λ=300 nm, we observed the formation of compound 2. The reaction was stopped at a conversion of 42% (Scheme 2). Further irradiation led to a very unselective transformation and the complex product mixture could not be characterized. Irradiation of compound 1 in i-PrOH, cyclohexane or n-heptane yielded compound 3. In cyclohexane, compound 4 was also obtained in small amounts. Formation of compound 3 resembles the wellknown photo-pinacolization [START_REF] Rubin | Photoinduced Intermolecular Hydrogen Abstraction Reactions of Ketones[END_REF] while the formation of compound 2 is unusual.

Compound 3 results from a reaction in which hydrogen atom transfer plays a central role. In such processes stable ketyl radicals are formed and dimerization leads to pinacol products such as 3. It must be noted that the best yield of this product is observed when i-PrOH was used as an efficient Hatom donor and as a solvent. In the case of the poor hydrogen atom donor n-heptane, the formation of 3 is much less efficient. In cyclohexane that is a medium hydrogen atom donor, the yield is intermediate. Interestingly, the cyclohexyl radicals resulting from the oxidation of the solvent are able to combine with the ketyl radicals generated from ketone 1 to form compound 4. The behavior of 1 in MeCN used as a polar solvent with poor hydrogen atom donation properties looks very atypic. The detection of 2 suggests the intermediary formation of a methyl radical and a ketyl radical localized on two different starting molecules. We hypothesized that photochemical electron transfer is involved in the formation of these radicals and of compound 2.

In order to get a deeper insight into the reaction mechanism, a detailed physico-chemical investigation was performed. Scheme 2. Photochemical transformations of the aromatic ketone 1.

Formation of the triplet excited state.

The laser flash photolysis of 1 at 266 nm yielded the same transient species in MeCN, i-PrOH, cyclohexane and n-heptane. It was observed immediately following the laser pulse and showed two maxima at 390 and 570 nm (Figure 1). By plotting the absorbance measured at 380 nm at the end of the pulse against the pulse energy, one got an × product of 3300±500 M -1 cm -1 in cyclohexane and n-heptane, where  is the molar absorption coefficient of the species at 380 nm and the quantum yield of the transient formation. The assignment of this transient to the triplet excited state, 3 1 * , was made possible by studying its reactivity with oxygen and anthracene. In MeCN, the lifetime of the transient was reduced by a half upon deoxygenation of the solution (0.34 s in air-saturated solution against 0.6 s in argon-saturated solution) demonstrating the scavenging effect of oxygen (Figure 2). Moreover, the irradiation of 1 in the presence of anthracene led to an accelerated decay of the transient at 380 nm and to the formation of the triplet excited state of anthracene well visible at 420 nm (Figure SI-5). This result brings evidence that an energy transfer took place between the transient and ground state anthracene and confirms that the transient was 3 1 * . The quantum yield of 3 1 * formation was estimated to be equal to 0.26±0.05. The decay of 3 1 * in deoxygenated medium obeyed an apparent first order kinetics, but was solventdependent. As shown in Table 1, the apparent first-order decay rate constant varied in the order MeCN  n-heptane < cyclohexane < i-PrOH, i.e. increased with the H-donor capacity of the solvent. In pure i-PrOH, the decay of 3 1 * was too fast to be accurately measured. The rate constant of reaction of 3 1 * with i-PrOH was therefore measured in MeCN/i-PrOH mixtures. From the linear dependence of the apparent first-order decay rate constant on i-PrOH concentration, a value of (4.3±0.4)×10 6 M -1 s -1 was obtained (Figure SI-6).

Table 1 : Decay rate constants of the transients in deoxygenated solvents and quantum yields of 1 photolysis air air-saturated medium. (1)= 6x10 -5 M

The reactivity of 3 1 * with 1 was also investigated using concentrations of 1 up to 10 -2 M. In this set of experiments, the solutions were excited at 355 nm to reduce the absorption of solutions. The decay A bimolecular reaction rate constant of (9.2±0.9)×10 7 M -1 s -1 was deduced from the linear plot.

Characterization of the secondary transients.

Secondary species were detected after the decay of 3 1 * in i-PrOH, cyclohexane and MeCN. In MeCN, the growth of the secondary species was slow and kinetically correlated with the decay of 3 1 * (Figure 2). Moreover, the addition of oxygen accelerated the secondary transient formation while reducing the intensity of the signal in accordance with a partial scavenging of 3 1 * by oxygen (Figure 2). This fully confirmed the mother-daughter relationship between the two species. In i-PrOH and cyclohexane, the formation of the secondary transient and the 3 1 * decay were both very fast in agreement with a relationship between the two species (Figure SI-7). In i-PrOH and cyclohexane, the secondary species absorption spectra were very similar. They presented two absorption bands with maxima located at 310-320 nm and 470-480 nm. For these two maxima, the intensity of the absorption is twice higher in i-PrOH than in cyclohexane reflecting a more efficient formation in the former solvent. The secondary transient formed in MeCN was different as it showed an absorption band with maximum at 460 nm and no visible other band within the wavelength range 310-350 nm (Figure 3). The lifetimes and reactivities of the secondary species are presented in Table 1. The secondary species formed in i-PrOH and cyclohexane were not detected in air-saturated medium, probably due to a fast quenching by oxygen. In deoxygenated i-PrOH, the secondary species decayed by a second order kinetics with a rate constant equal to 2k/=2.7x10 5 cm -1 s -1 at 330 nm (Figure SI-8). Based on these kinetic data, on the formation of pinacol 2 and on the known photoreactivity of benzophenones in i-PrOH, the secondary transient can be assigned to the ketyl radical A (Scheme 3). [START_REF] Turro | Modern Molecular Photochemistry of Organic Molecules[END_REF] In deoxygenated cyclohexane, the decay of the ketyl radical was about 10-fold faster than in i-PrOH (Table 1, Figure SI-9). The lower viscosity of cyclohexane compared to i-PrOH (0.98×10 -3 Pa.s against 2.37×10 -3 Pa.s at 20°C) can only explain a part of this difference. Indeed, 2k/ in cyclohexane at 330 nm is expected to be equal to 6.5x10 5 cm -1 s -1 , i.e. 2.4-fold bigger than in i-PrOH. The fast decay of the ketyl radical in cyclohexane could also be due to a mixture of pseudo-first order and second order kinetics. This is possible if we make the hypothesis that a part of the ketyl radicals A react with the cyclohexyl radicals B, formed after the H atom abstraction, before escaping the cage. This recombination would be the first order contribution of the decay. It is fully in agreement with the detection of 4. Once in the bulk, the ketyl radical would decay by a second order kinetics. Such a dual kinetics was nicely described in the photolysis of benzophenone dissolved in soft rubber poly(ethylene-co-butylene) films. [START_REF] Levin | Kinetics of benzophenone ketyl free radicals recombination in a polymer: reactivity in the polymer cage vs. reactivity in the polymer bulk[END_REF] By fitting the ketyl radical decay taking 2k/  = 6.5x10 5 cm -1 s -1 , we obtained that about 80% of the reaction corresponds to the first order geminate recombination in the cage and 20% to the bimolecular recombination in the bulk. When 1 was irradiated in i-PrOH, no geminate recombination was observed. This is in accordance with the literature data that reports the exclusive pinacols formation for benzophenones irradiated in i-PrOH. [START_REF] Moore | Mechnisms of Photoreactions in Solutions. I. Reduction of Benzophenone by Benzhydrol[END_REF] The formation of 3 in n-heptane suggests that the ketyl radical A is also formed in this solvent. However, we could not observe it at 480 nm. It is probably formed in too small amounts to be detected.

The secondary species formed in MeCN is not the ketyl radical A for several reasons. First, its transient absorption spectrum was different from that of the ketyl radical. Moreover, it reacted with oxygen but with a moderate rate constant (2.9x10 7 M -1 s -1 ) (Figure SI -10). In deoxygenated medium, it decayed by a clean pseudo-first order kinetics with a rate constant of 1.7×10 5 s -1 . The last peculiarity of the secondary transient formed in MeCN is its reactivity with water. A significant enhancement on its decay was measured upon the addition of water (4 and 30%, v/v) (Figure 4) while the ketyl radical was not affected by water in i-PrOH. This result suggests an ionic character for the species and we concluded that it is the zwitterionic diradical.

Mechanisms.

In i-PrOH, the formation of a ketyl radical by H-atom abstraction from i-PrOH is very usual (scheme 3). This is consistent with the known photoreactivity of aromatic carbonyls in H-donor solvents. [START_REF] Bonnichon | Phototransformation of 3-hydroxybenzonitrile in water[END_REF] In the presence of oxygen, the ketyl radical would give the H atom to oxygen [START_REF] Scaiano | Laser Flash Photolysis Studies of the Reactions of Some 1,4-Biradicals[END_REF] and regenerate 1. This explains the absence of phototransformation of 1 in air-saturated medium (Table 1). In the absence of oxygen, the recombination of two ketyl radicals A would lead to pinacol 3. This pinacolisation is fully in line with the observed second order decay kinetics observed by laser flash photolysis.

Scheme 3: Formation of pinacol 3 via the ketyl radical A

In cyclohexane, the formation of the ketyl radical A also takes place as indicated by the formation of pinacol 3 (Scheme 4). The yield is however lower than in i-PrOH, 21% against 46%, in accordance with the existence of competitive reactions, in particular the geminate recombination in the cage of solvent. In such a reaction also compound 4 is formed by combination of a ketyl radical A with a cyclohexyl radical B.

Scheme 4: Formation of pinacol 3 and of the adduct 4 via the ketyl radical A

In n-heptane, that is a poor H-atom donor solvent, the ketyl radical A could not be detected in the laser flash photolysis experiments. Yet, photoproduct 3 was formed in the preparative product studies. These experiments being conducted at a very high 1 concentration, 1 might have been the Hdonor, since we demonstrated that a non-negligible reaction between 3 1 * and 1 can take place. The high 1 concentration used in preparative reactions has probably affected the photoproducts yields. In particular in cyclohexane where the ketyl radical A decays by a mixed first order and second order kinetics, increasing 1 concentration is expected to increase the ketyl radical A concentration and to favor pinacolisation. Due to the poor H-donor capacity of n-heptane, we initially considered as possible to detect in this solvent the neutral diradical C formed through intramolecular H atom transfer. [START_REF]This reaction step would be related to the reactions of o-tolylphenyl ketone and similar derivatives[END_REF] This hypothesis was not confirmed experimentally. Either the reaction does not take place, or this species is too short lived to be detected as shown for other benzophenone derivatives. [START_REF] Scaiano | Laser Flash Photolysis Studies of the Reactions of Some 1,4-Biradicals[END_REF] In MeCN that is more polar than the other solvents together with a poor H-donor molecule, a very different situation seems to take place. The experimental data are in line with the formation of an ionic intermediary structure that is likely the zwitterionic radical D formed by an intramolecular electron transfer (Scheme 5). This assignment is confirmed by the specific reactivity of the secondary species formed in MeCN compared that of ketyl radical A.

Under these conditions, we didn't detect a ketyl radical intermediate. As a consequence, we exclude an intermolecular hydrogen transfer from the solvent and suggest an intermolecular hydrogen transfer between the zwitterionic intermediate D and 1 at its ground state (Scheme 5). The zwitterionic intermediate D can be deprotonated leading to a diradical anion E and the protonated ketone [H-1] + . An electron is then transferred and the neutral radicals H and I are formed. Radical combination leads to the unusual regioisomer of the coupling product 2. Alternatively, an electron is transferred first leading to the intermediates F and G. Proton transfer leads again to the neutral intermediates H and I. Most probably, the transfer of both particles of the hydrogen atom is coupled (proton coupled electron transfer, PCET). As the intermolecular hydrogen transfer is favored in a polar solvent an increase of the polarity in the transition state of the PCET step is possible. In a corresponding intermolecular step (HAT), the neutral diradical intermediate C would be formed as depicted in Scheme 4, this is not the case. Furthermore, it must be pointed out that the one step hydrogen transfer needs a highly structured transition state with highly negative ΔS ≠ values while for the electron transfer in a two-step hydrogen transfer this value is close to zero. [START_REF] Mayer | Understanding Hydrogen Atom Transfer: From Bond Strengths to Marcus Theory[END_REF] The herein described reaction compound 1 leading to the unusual coupling product 2 is therefore directly linked to the formation of the zwitterionic diradical D.

Scheme 5: Formation of dimer 2 via the zwitterionic diradical D involving proton coupled electron transfer.

Conclusion

The photochemical reactivity of phenyl (methyl)tetrazolium ketone 1 has been studied in detail by means of preparative product studies and laser flash photolysis. When efficient hydrogen atom donor compounds such as isopropanol are used as solvents, ketyl radicals are formed which dimerize leading to photopinacol analogue products as it has previously been reported for aromatic ketones such as benzophenone. A completely different intermediate is formed when ketone 1 is irradiated in acetonitrile. This intermediate possesses a zwitterionic character. A proton coupled electron transfer from this intermediate to 1 at its ground state is suggested to explain the formation of the unusual final product 2.

…

[

  189.6°C-190.3°C]). NMR 1 H (600 MHz, CDCl 3 , ppm) :  = 3.89 (s, 3 H), 6.85 (d, J = 7.54 Hz, 4 H), 7.07 (s, 2 H), 7.13 (t, J = 7.78 Hz, 4 H), 7.25 (t, J = 7.40 Hz, 2 H) ppm. NMR 13 C (150 MHz, CDCl 3 , ppm) :  = 35.55, 79.07, 127.12, 127.45, 128.78, 134.29, 157.70 ppm (Figure SI-3). UHPLC-HRMS: m/z= 379.1618 in ES + and 377.1485 in ES -.

Figure 1 :

 1 Figure 1 : Transient absorption spectrum measured immediately after the pulse by excitation of 1 at 266 nm in aerated MeCN. (1)= 6x10 -5 M, A 266 = 0.77

Figure 2 :

 2 Figure 2: Decay of 3 1 * at 550 nm and growth of the secondary transient at 460 nm. Curves 1 and 2 in deoxygenated MeCN and curves 3 and 4 in air-saturated MeCN. (1)= 6x10 -5 M, A 266 = 0.77

Figure 3 :

 3 Figure 3: Transient absorption spectra measured by excitation of 1 at 266 nm in argon-saturated i-PrOH (), cyclohexane (), and acetonitrile () after the disappearance of 3 1 * : 100 ns following the pulse in i-PrOH, 350 ns in cyclohexane, and 2 s in MeCN. The other experimental conditions are the same as those in Figure 1.

Figure 4 :

 4 Figure 4 : Decay at 460 nm of the secondary species formed in MeCN in the absence of water (a), in the presence of 4% of water (b), in the presence of 30% of water (c). The other experimental conditions are the same as those in Figure 1. Mechanisms.

  C (150 MHz, CDCl 3 , ppm) :  = 26.24, 26.29, 26.36, 27.73, 35.72, 46.82, 77.53, 125.43, 127.90, 128.58, 140.32, 157.57 ppm (Figure SI-4). UHPLC-HRMS: m/z= 273.1703 in ES + .

Acknowledgments

We would like to thank Jye-Shane Yang (National Taiwan University, Taipei) for helpful discussions. We are grateful for financial support from the University of Reims, the French Ministry of Higher Education, Research and Innovation and to Bayer SA (Lyon) for financial support. …