Ingmar R Staude

Donald M Waller

Markus Bernhardt-Römermann

Anne D Bjorkman

Jörg Brunet

Pieter De Frenne

Radim Hédl

Ute Jandt

Jonathan Roger Michel

Henri Lenoir

František Máliš

Jonathan Lenoir

Kris Verheyen

Monika Wulf

Henrique M Pereira

Pieter Vangansbeke

Adrienne Ortmann-Ajkai

Remigiusz Pielech

Imre Berki

Markéta Chudomelová

Guillaume Decocq

Thomas Dirnböck

Tomasz Durak

Thilo Heinken

Bogdan Jaroszewicz

Martin Kopecký

Martin Macek

Marek Malicki

Tobias Naaf

Thomas A Nagel

Petr Petřík

Kamila Reczyńska

Fride Høistad Schei

Wolfgang Schmidt

Tibor Standovár

Krzysztof Świerkosz

Balázs Teleki

Hans Van Calster

Ondřej Vild

Lander Baeten

Affiliations

à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d

enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Replacements of small-by large-ranged species scale up to diversity loss in Europe's temperate forest biome

Introduction

The biological diversity on Earth is changing due to human activities. At the global scale, species are going extinct at rates that signal a mass extinction [START_REF] Barnosky | Has the Earth's sixth mass extinction already arrived?[END_REF][START_REF] Díaz | Summary for policymakers of the global assessment report on biodiversity and ecosystem services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (Advance unedited version)[END_REF] . Per contra, at local scales whether or not diversity is declining is controversial. Time-series studies find that sites may gain or lose species with no directional global trend [START_REF] Vellend | Global meta-analysis reveals no net change in local-scale plant biodiversity over time[END_REF][START_REF] Dornelas | Assemblage time series reveal biodiversity change but not systematic loss[END_REF][START_REF] Vellend | Estimates of local biodiversity change over time stand up to scrutiny[END_REF] . Space-for-time comparisons find substantial losses in local diversity globally due to human land use [START_REF] Newbold | Global effects of land use on local terrestrial biodiversity[END_REF] . While spatial comparisons are criticized for neglecting that community dynamics are much slower than the speed of environmental changes [START_REF] Damgaard | A critique of the space-for-time substitution practice in community ecology[END_REF] , time-series studies are challenged for not being spatially representative of human land use effects [START_REF] Vellend | Estimates of local biodiversity change over time stand up to scrutiny[END_REF][START_REF] Cardinale | Is local biodiversity declining or not? A summary of the debate over analysis of species richness time trends[END_REF][START_REF] Gonzalez | Estimating local biodiversity change: a critique of papers claiming no net loss of local diversity[END_REF] . Yet even in relatively intact places and independent from changes in local diversity, species appear to be replacing each other more rapidly than predicted from only natural changes [START_REF] Dornelas | Assemblage time series reveal biodiversity change but not systematic loss[END_REF][START_REF] Magurran | Rapid biotic homogenization of marine fish assemblages[END_REF] . These local-scale replacements alone could lead to species loss at larger spatial scales, if species with small geographic ranges are frequently replaced by species with larger ranges. Tests of this prediction remain, however, sparse.

Why should small-ranged species decline relative to those with larger ranges within sites? A greater tendency of species with small ranges to decline or go locally extinct could reflect lower abundance, greater ecological specificity (narrower niches), or both. Species with small geographic ranges generally tend to have smaller local populations [START_REF] Brown | On the relationship between abundance and distribution of species[END_REF][START_REF] Gaston | The multiple forms of the interspecific abundance-distribution relationship[END_REF][START_REF] Gaston | Abundance--occupancy relationships[END_REF] , and with decreasing population size, vulnerability to environmental change increases [START_REF] Schoener | High population persistence in a system with high turnover[END_REF] . Species with small range size also tend to be more specialized with narrower niche breadth [START_REF] Kambach | Of niches and distributions: range size increases with niche breadth both globally and regionally but regional estimates poorly relate to global estimates[END_REF] and may therefore lack flexibility to cope with anthropogenic changes in their abiotic and biotic environment. As these changes increase, we might expect niche effects to strengthen leading to high species replacement.

For plants, a primary limiting factor in many natural environments is nitrogen (N) [START_REF] Berendse | Nitrogen-use-efficiency: a biologically meaningful definition[END_REF] . Humans have substantially altered the distribution and availability of N over the last century [START_REF] Galloway | Nitrogen cycles: past, present, and future[END_REF] . Chronic high Ndeposition has now saturated many ecological systems, exceeding critical loads [START_REF] Aber | Is nitrogen deposition altering the nitrogen status of northeastern forests?[END_REF][START_REF] Gilliam | Response of the herbaceous layer of forest ecosystems to excess nitrogen deposition[END_REF][START_REF] Aber | Nitrogen saturation in temperate forest ecosystems: hypotheses revisited[END_REF][START_REF] Tian | Global evidence on nitrogen saturation of terrestrial ecosystem net primary productivity[END_REF] . Increases in a key resource like N reorder competitive relationships among plant species within communities, favoring Ndemanding species at sites of high N-deposition across many ecosystems [START_REF] Clark | Loss of plant species after chronic low-level nitrogen deposition to prairie grasslands[END_REF][START_REF] Stevens | Impact of nitrogen deposition on the species richness of grasslands[END_REF][START_REF] Bobbink | Plant species richness and the exceedance of empirical nitrogen critical loads: an inventory[END_REF][START_REF] Smith | A framework for assessing ecosystem dynamics in response to chronic resource alterations induced by global change[END_REF][START_REF] Bobbink | Global assessment of nitrogen deposition effects on terrestrial plant diversity: a synthesis[END_REF][START_REF] Clark | Potential vulnerability of 348 herbaceous species to atmospheric deposition of nitrogen and sulfur in the United States[END_REF][START_REF] Ortmann-Ajkai | Twenty-years' changes of wetland vegetation: effects of floodplain-level threats[END_REF] . Yet, beyond local-scale community changes, how these shifts link to biodiversity change across spatial scales remains largely unexplored.

Here, we explore the role of species range size and N-deposition in driving the systematic shifts in species composition and scale-dependent patterns of diversity changes observed in extensive long-term vegetation data [START_REF] Clark | Potential vulnerability of 348 herbaceous species to atmospheric deposition of nitrogen and sulfur in the United States[END_REF][START_REF] Hernández | Nitrogen pollution is linked to US listed species declines[END_REF][START_REF] Simkin | Conditional vulnerability of plant diversity to atmospheric nitrogen deposition across the United States[END_REF] . The N-niche of species relates to their range size in that species that use N more efficiently tend to have smaller ranges relative to N-demanding species [START_REF] Sonkoly | Do large-seeded herbs have a small range size? The seed mass--distribution range trade-off hypothesis[END_REF] . This may reflect the ability of Ndemanding species to grow faster [START_REF] Bartelheimer | Functional characterizations of E llenberg indicator values--a review on ecophysiological determinants[END_REF][START_REF] Grime | Evidence for the existence of three primary strategies in plants and its relevance to ecological and evolutionary theory[END_REF] . Faster-growing species usually have smaller seeds [START_REF] Grotkopp | Toward a causal explanation of plant invasiveness: seedling growth and life-history strategies of 29 pine (Pinus) species[END_REF] enabling further dispersal [START_REF] Fenner | The ecology of seeds[END_REF] , and more widely dispersed species tend to have wider ranges [START_REF] Van Der Veken | Life-history traits are correlated with geographical distribution patterns of western European forest herb species[END_REF] . Increases in N are thus hypothesized to favor larger-ranged species that grow faster under more fertile conditions, allowing them to become superior competitors, reducing the survivorship of N-efficient, small-ranged species. Patterns of global biodiversity loss and local maintenance of diversity would be consistent with such species replacements, with a few large-ranged species replacing many small-ranged species in a process termed biotic homogenization [START_REF] Mckinney | Biotic homogenization: a few winners replacing many losers in the next mass extinction[END_REF] .

We compiled a database of 68 resurvey studies of herb-layer communities from semi-natural, temperate forests spread across Europe (Fig. 1). We use these data to ask: 1. Have small-ranged forest plant species declined over time? 2. Do any such trends simply reflect their lower abundance (given the range size -abundance correlation), or does it reflect niche effects that strengthen with N-deposition? 3. Do species replacements under N-deposition evoke a homogenization pattern with small-scale richness remaining constant on average while larger-scale richness declines?

Results

Plant species that went extinct from a study site had smaller range sizes than species that persisted and those that colonized. In contrast, persisting and colonizing species had similar range sizes (Fig. 2a and Supplementary Table 2). If this pattern reflected only lower abundance at the study site, range size should not add power for predicting extinctions once abundance is controlled for. Here, we estimate abundance as occupancy across plots within a site [START_REF] Hanski | Dynamics of regional distribution: the core and satellite species hypothesis[END_REF][START_REF] Wright | Correlations between incidence and abundance are expected by chance[END_REF] . Occupancy was a strong predictor of probability of extinction (slope: = -3.63, standard deviation: = 0.28). Over an average time interval of 38 years, species of average occupancy had a 10% chance of going extinct from a study site relative to up to 60% for species of low occupancy (Fig. 2b and Supplementary Table 3). Range size still had a negative effect on species' extinction probability even after controlling for occupancy ( = -0.21 , = 0.05). For species of average occupancy, extinction probabilities declined by more than 50% as range size increased (Fig. 2c and Supplementary Table 3). The total effect of range size became only slightly stronger when occupancy was not controlled for ( = -0.28 , = 0.06), suggesting that only 25 % of the range size effect reflects occupancy (Supplementary Table 3). As species' range size presents a basic summary of the ecological characteristics of species (mainly in terms of climatic and edaphic niches [START_REF] Mason | The edaphic factor in narrow endemism. I. The nature of environmental influences[END_REF][START_REF] Sandel | The influence of Late Quaternary climate-change velocity on species endemism[END_REF] ), the remaining effects of range size likely reflect aspects of species niches. Higher cumulative N-deposition (ΔN, see Methods for details) between surveys sharply increased probabilities of extinction from a site ( = 0.37 , = 0.15;

Fig. 3a, Supplementary Table 4), having accounted for confounding variables such as inter-census time period, study area and latitude (see Methods for all variables). This increase in extinction probability disproportionally affected small-ranged species, as shown by the negative interaction between range size and N-deposition ( = -0.1 , = 0.03). Extinction probability of the species with the smallest range sizes increased from ~4% to ~27% as N-deposition increased from 45 to 721 kg ha -1 (with other predictors at their mean). In contrast, risks of extinction for large-ranged species were much lower and more stable (Fig. 3b and Supplementary Table 4).

These results show that probabilities of extinction increase with N-deposition, mostly due to the loss of small-ranged species. Has this eroded study-level species richness or have increases in colonization balanced these extinctions? We found no systematic shifts in species richness within study sites as Ndeposition increased, again accounting for covariates ( = 0.11 , = 0.15; Fig. 3c, Extended Data 1 and Supplementary Table 5). This implies that higher levels of N-deposition have facilitated the replacement of small-ranged species. Colonizing species had larger ranges (Fig. 2a) and included several non-native species ( = 0.44 , = 0.16; Fig 3d, Supplementary Table 5). As more N-efficient species went extinct with higher N-deposition ( = -0.25 , = 0.12; Fig 3e) and colonizing species generally had higher N-demands (Extended Data 2), community composition has shifted systematically towards more Ndemanding species ( = 0.28 , = 0.12; Fig. 3e and Supplementary Table 6).

Although small-scale diversity has not declined, N-deposition may threaten other forms of diversity. As small-ranged, N-efficient species are extirpated and replaced by wide-ranging, non-native and Ndemanding species, these forest plant communities have converged in composition. Gilliam [START_REF] Gilliam | Response of the herbaceous layer of forest ecosystems to excess nitrogen deposition[END_REF] predicted that such declines in beta (and thus gamma) diversity would occur as N-deposition tends to increase the spatial homogeneity of nutrient availability. Variation in nutrient availability among sites has indeed declined since the baseline surveys (difference between variances: = -0.16 , = 0.08) (Fig. 3f and Supplementary Table 7, see Methods for estimation of nutrient availability). This homogenization in nutrient availability appears linked to declines in overall (biome-scale) species richness as gamma-diversity across these 68 sites declined by 4% (from 1,012 to 972 species).

Discussion

Using large-scale temporal vegetation change datasets, we provide evidence that the geographic range size of species predicts long-term shifts in forest-floor plant communities. Small-ranged species are replaced by those with larger ranges and our results suggest this is more due to species niches than abundances. The loss of small-ranged species amplified under high N-deposition and, consistent with our expectation that species' range size and N-demand positively correlate, communities shifted towards species with higher N-demand. Despite the loss of small-ranged species, the number of species within study sites has not declined in response to increasing N-deposition, suggesting that species losses have been balanced by species gains. Nevertheless, the floristic distinctiveness of these forests erodes as more cosmopolitan and non-native species replace a set of more finely-adapted species. These replacements ran in parallel with the abiotic homogenization resulting from chronic N-deposition and scaled to a loss of biodiversity in Europe's temperate forests in recent decades.

Our study confirms that small population size is a strong predictor of extinction from a site [START_REF] Schoener | High population persistence in a system with high turnover[END_REF][START_REF] Hubbell | The unified neutral theory of biodiversity and biogeography (MPB-32)[END_REF][START_REF] Suding | Functional-and abundance-based mechanisms explain diversity loss due to N fertilization[END_REF] . Yet this did not provide much explanation for the greater extinction risk of small-ranged species as would be expected given a positive range size-abundance relationship. This suggests not all small-ranged plant species in these forests have small populations. In fact, plants show many exceptions to this relationship.

For example, 87% of small-ranged species from the British Isles are locally common [START_REF] Rabinowitz | Seven forms of rarity and their frequency in the flora of the British Isles[END_REF] ; conversely one of the largest ranging woody species of the globe, Juniperus communis, has small populations in many regions [START_REF] Köckemann | The relationships between abundance, range size and niche breadth in Central European tree species[END_REF] . Indeed, several plant studies find that range size and abundance do not necessarily covary [START_REF] Köckemann | The relationships between abundance, range size and niche breadth in Central European tree species[END_REF][START_REF] Thompson | Abundance--range size relationships in the herbaceous flora of central England[END_REF] .

This suggests that range size affects species' extinction probability mostly via niche rather than demographic effects, a conjecture supported by the fact that N-deposition mostly affected small-ranged (narrow niche) species.

Despite declines in small-ranged species, forest sites in our study did not systematically decrease in species richness. This suggests species losses are offset by species gains. This finding echoes other resurvey studies that document little directional temporal trend in small-scale species richness despite increased species turnover [START_REF] Dornelas | Assemblage time series reveal biodiversity change but not systematic loss[END_REF][START_REF] Magurran | Rapid biotic homogenization of marine fish assemblages[END_REF] . But similarly, this finding is likely to not reflect the full impact of intensive human land use [START_REF] Cardinale | Is local biodiversity declining or not? A summary of the debate over analysis of species richness time trends[END_REF][START_REF] Gonzalez | Estimating local biodiversity change: a critique of papers claiming no net loss of local diversity[END_REF] as our study sites are confined to semi-natural forests. Given that the effect of range size reflects species' niches, species turnover accelerated under N-deposition and communities not only shifted towards larger range size but also towards higher average N-demands. Other studies from forest ecosystems report the same shifts towards more N-demanding species from eutrophication and similarly limited effects of N-deposition on forest-floor plant species richness [START_REF] Bobbink | Plant species richness and the exceedance of empirical nitrogen critical loads: an inventory[END_REF][START_REF] Verheyen | Driving factors behind the eutrophication signal in understorey plant communities of deciduous temperate forests[END_REF][START_REF] Dirnböck | Forest floor vegetation response to nitrogen deposition in Europe[END_REF][START_REF] Bernhardt-Römermann | Drivers of temporal changes in temperate forest plant diversity vary across spatial scales[END_REF] . This contrasts with opencanopy ecosystems that, being not primarily light limited, consistently lose species from N-addition through shading [START_REF] Borer | Herbivores and nutrients control grassland plant diversity via light limitation[END_REF][START_REF] Hautier | Competition for light causes plant biodiversity loss after eutrophication[END_REF] . Beyond a threshold, however, N-deposition also reduces plant diversity in forests, as shown in North America where roughly a quarter of 14,000+ sites showed susceptibility to N-driven species losses [START_REF] Simkin | Conditional vulnerability of plant diversity to atmospheric nitrogen deposition across the United States[END_REF] .

Although we find no evidence of a directional change in species richness within studies, the total number of species across studies (gamma diversity) has declined. The observed 4% decline in gamma-diversity likely underestimates the true species loss in the European temperate forest biome, as studies in our database are not completely spatially representative of key human pressures in Europe. Resurveys have been selected to be especially located in large, historically continuously forested (ancient) and seminatural forests where no land-use change took place prior to the baseline survey and no large change in management occurred between the surveys. Change in land use and other disturbances that open up forest canopies and increase light availability may exacerbate effects of global warming by eliminating the thermal insulating layer that protects understories from thermophilisation [START_REF] De Frenne | Global buffering of temperatures under forest canopies[END_REF][START_REF] De Frenne | Microclimate moderates plant responses to macroclimate warming[END_REF] . However, changes in light availability usually occur at the plot-level as opposed to N-deposition that acts at the scale of an entire study area. Because we evaluated community dynamics at the study-level, we expect that light availability changes do not confound the N-signal we found.

Nitrogen releases to the environment remain high in Europe (https://www.eea.europa.eu/airs/2018).

Despite recent declines, these emissions still exceed critical loads for most of Europe's protected habitats [START_REF] Amann | Progress towards the achievement of the EU's air quality and emissions objectives[END_REF] . It is important to learn what long-lasting effects N-deposition may have on Europe's ecosystems and how reversible these are as emissions decline. In contrast to the rapid recovery of plotscale experimental communities, where species are still present in the area and able to colonize once N additions are ceased [START_REF] Clark | Loss of plant species after chronic low-level nitrogen deposition to prairie grasslands[END_REF][START_REF] Storkey | Grassland biodiversity bounces back from long-term nitrogen addition[END_REF] (but see ref. [START_REF] Isbell | Low biodiversity state persists two decades after cessation of nutrient enrichment[END_REF] ), the loss of small-ranged species from entire regions is far less likely to be reversed in the short term. At this point, it is thus unclear whether the declines in N emissions mandated under the EU National Emission Ceilings Directive (2016/2284/EU) will be feasible or sufficient to allow the recovery of Europe's plant species and communities.

Methods

Database

We compiled a database containing data from 68 understory resurvey studies distributed across the European temperate deciduous forest biome (see www.forestreplot.ugent.be and ref. [START_REF] Verheyen | Combining biodiversity resurveys across regions to advance global change research[END_REF] for inclusion criteria). These studies cover 15 European countries, from Norway in the north to Slovenia in the south and from Ireland in the west to Poland in the east (Fig. 1). All surveys were conducted in historically continuously forested 'ancient' and semi-natural deciduous forest (sensu ref. [START_REF] Peterken | Natural woodland: ecology and conservation in northern temperate regions[END_REF] ). These forests did thus not experience historical land-use change prior to the first (baseline) survey and between the surveys. Furthermore, the forests are mostly managed, but did not experience stand-replacing disturbances between the baseline survey and the most recent resurvey. In each survey, the herbaceous understory was recorded in multiple permanent or quasi-permanent plots. Plot size ranged between 1m 2 to 1000m 2 across studies (median: 400 m 2 ). Number of plots ranged from 10 to 190 across studies (median: 43 plots, Supplementary Figure 1b). Plots were allocated across areas ranging from 1ha to c. 2.5x10 6 ha (median: 1700 ha, Supplementary Figure 1d). Baseline surveys were carried out between 1933 and 1999. The most recent resurveys were made between 1969 and 2017 generating time intervals between surveys from 15 to 78 years (median: 42 years, Supplementary Figure 1c). We accounted for changes in taxonomy between surveys by determining the accepted species name for each species using GBIFs backbone taxonomy (gbif.org). Harmonization thus ensured no double-counting species due to synonymy. Our database contains 1,162 species in total.

Species level variables

Species' trajectory

We determined the trajectory of species at the study level. We classified species present in the baseline survey but absent in the resurvey as extinct. Those present in both surveys were classified as persisting. Those absent in the baseline survey but present in the resurvey were classified as colonizing. Resurveys of permanent plots always miss some species, generating pseudo-colonizations and extinctions that can inflate these estimates for rare species [START_REF] Beck | Field sampling is biased against small-ranged species of high conservation value: a case study on the sphingid moths of East Africa[END_REF][START_REF] Verheyen | Observer and relocation errors matter in resurveys of historical vegetation plots[END_REF] .

We did not correct our estimates of colonization and extinction for bias proposed by Beck [START_REF] Beck | Field sampling is biased against small-ranged species of high conservation value: a case study on the sphingid moths of East Africa[END_REF] as we adjust for initial abundance (occupancy across plots) in our model which is strongly correlated with any such bias [START_REF] Kopecký | Vegetation resurvey is robust to plot location uncertainty[END_REF] . This means our estimates of the effects of initial abundance on extinction may be slightly inflated.

Occupancy

For each study, we calculated the initial occupancy of species. This is the number of plots that a species has occupied in the baseline survey, divided by the total number of plots in that survey. Occupancy approximates abundance because, empirically and for any biologically relevant point process pattern, they strongly and positively correlate at local to regional scales [START_REF] Hanski | Dynamics of regional distribution: the core and satellite species hypothesis[END_REF][START_REF] Wright | Correlations between incidence and abundance are expected by chance[END_REF] .

Range size

Species range sizes were estimated from the species point occurrence records in GBIF (gbif.org, 18 January 2019). In total, c. 100 million geographically referenced records were available for 1,147 species in our database (1.3 % missing species) after excluding unlikely and impossible coordinates [START_REF] Chamberlain | scrubr: Clean Biological Occurrence Records[END_REF] . Records were aggregated to a hexagonal grid (ISEA3H) at three spatial grains: 3.6 km 2 , 10.7 km 2 and 32 km 2 . The number of cells any given species occupies on such grid represents its range size. Range size therefore measures species' area of occupancy (AOO, expressed in km [START_REF] Díaz | Summary for policymakers of the global assessment report on biodiversity and ecosystem services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (Advance unedited version)[END_REF] ). Results in the main text are based on range sizes estimated at mid-resolution (10.7 km 2 ). At this resolution, the smallest ranging species was Poa pannonica A.Kern. with an estimated AOO of 21.4 km 2 , the species with the largest range was the annual meadow grass, Poa annua L., with an AOO of c. 1.6x10 6 km 2 (Extended Data 3).

For our analyses we use AOO and not the extent of occurrence (EOO, which includes also discontinuities in occupancy) as AOO is a markedly better predictor of mean site abundance and population size [START_REF] Gaston | Abundance--occupancy relationships[END_REF][START_REF] Gaston | The sizes of species' geographic ranges[END_REF] . While AOO measured from GBIF point occurrence data is increasingly used in the scientific literature, incomplete spatial coverage of digital biodiversity data can lead to an underestimation of range sizes [START_REF] Isaac | Bias and information in biological records[END_REF] . Specifically, Middle and Northern Asia are some of the most data deficient regions of the world [START_REF] Meyer | Multidimensional biases, gaps and uncertainties in global plant occurrence information[END_REF] . This may be problematic for European species that extend into these regions. We therefore tested how well our estimates of AOO match estimates of EOO for species where range maps from two renowned distribution atlases were available [START_REF] Hultén | Atlas of North European vascular plants north of the Tropic of Cancer[END_REF][START_REF] Meusel | Vergleichende chorologie der zentraleuropaischen flora[END_REF] (available for 796 species, 31% missing).The distribution ranges were digitized from scanned atlas pages and rasterized on a 20 km x 20 km grid in the Lambert azimuthal equal-area projection to calculate EOO for all 796 species. Spearman's correlation between AOO and EOO was high ( = 0.71) for these species. As an overall positive correlation might obscure a weak correlation for continental species that extend into data deficient regions, we also tested for range attribution. We identified 155 species as continental using species indicator values for continentality from ref. [START_REF] Berg | Revising Ellenberg's indicator values for continentality based on global vascular plant species distribution[END_REF] (species with values >=6 were classified as continental). Excluding those species made the correlation between AOO and EOO only slightly stronger ( = 0.74; Extended Data 3). We therefore assume that data limitations are a less material problem for our set of species.

Study-level variables

Nitrogen-deposition

We quantified N-deposition using the EMEP database (https://emep.int/mscw/mscw_moddata.html) with c. 11 km (0.1°) grid resolution. Here we chose to focus singly on NOx deposition for three reasons. 1) Increasing evidence suggest that the two forms of N-deposition, oxidized (NOx) and reduced (NHy) N-deposition, have differential, habitat-specific effects on plant communities [START_REF] Stevens | Ecosystem responses to reduced and oxidised nitrogen inputs in European terrestrial habitats[END_REF][START_REF] Van Den Berg | Evidence for differential effects of reduced and oxidised nitrogen deposition on vegetation independent of nitrogen load[END_REF][START_REF] Dorland | Differential effects of oxidised and reduced nitrogen on vegetation and soil chemistry of species-rich acidic grasslands[END_REF] . Whereas NHy is the most important driver for the decline in plant diversity in grasslands, forest vegetation is found to be most responsive to NOx [START_REF] Van Den Berg | Evidence for differential effects of reduced and oxidised nitrogen deposition on vegetation independent of nitrogen load[END_REF] . 2) Model estimates of NOx deposition also have a lower degree of uncertainty and bias than estimates of NHy [START_REF] Gauss | EMEP MSC-W model performance for acidifying and eutrophying components, photo-oxidants and particulate matter in[END_REF] . Local-scale variability of NHy deposition is considerably higher as most of it is deposited near the source [START_REF] Asman | Factors influencing local dry deposition of gases with special reference to ammonia[END_REF] , this variability is likely to be poorly reflected when studying N-effects over larger regions as done in this study. 3) NOx is spatially correlated with NHy deposition in Europe (ρ =.69 in this study) and thus representative for broader N-effects. We quantified the cumulative wet and dry deposition of oxidized N (hereinafter and in the main text referred to simply as N-deposition) based on the methods described in ref. [START_REF] Bernhardt-Römermann | Drivers of temporal changes in temperate forest plant diversity vary across spatial scales[END_REF] . First, we calculated N-deposition between 1900 and the year of the baseline survey (Nt1), second we quantified the cumulative N-deposition between 1900 and the resurvey (Nt2), and third we calculated the difference, Nt2 -Nt1, to quantify N-deposition between surveys (inter-census N-deposition or ΔN). ΔN ranged from 45 to 721 kg ha -1 (Supplementary Figure 1). Results in the main text are based on ΔN.

Change in species numbers

Changes in the number of species found in the resurvey versus the baseline survey were quantified as the difference in size of the recorded species pool for each study (Extended Data 1).

Change in non-native species

The entire statistical analysis and R-code is provided in the supplementary information as an R markdown file. The rethinking package [START_REF] Mcelreath | Statistical rethinking: A Bayesian course with examples in R and Stan[END_REF] was used to compile the following models to Stan Hamiltonian Monte Carlo code. For brevity, all models are presented without priors (complete models and R code is available on figshare [https://figshare.com/s/45d71eb77c23c11bc857]).

We first compared range sizes between extinct, persisting and colonizing species, where species' trajectories are defined at the study scale. Clearly range size is non-normal distributed and starkly right skewed. Since normality of the outcome conditional on the covariates is the central assumption of Gaussian linear models and range size was too skewed for Poisson regression, we normalized range size using an order-quantile transformation [START_REF] Peterson | bestNormalize: Normalizing Transformation Functions[END_REF] . We predicted range size ( ) with trajectory ( ) and allowed each coefficient to vary by each study ( , ). The mathematical form of the resulting model is:

∼ !"#(% , ) % = + ,
We calculated pairwise contrasts (e.g., ()*)+ , +--./ +( ) to compare range sizes between species trajectories.

Next, we asked can species' extinction probability be predicted by species' occupancy at the time of the baseline survey? Here, we only analyzed species present at the baseline survey, omitting colonizing species. The outcome is a 0/1 (Bernoulli) indicator that a given species persisted or became extinct in a study (0 ). As the outcome is binomially distributed, we used logistic regression to predict species' extinction probabilities as a function of occupancy. We allowed intercepts to vary with study ID ( ) and species (1 2.( . ) and the effect of occupancy (3 ) to vary by study ID ( 4, ). The mathematical form of the model is:

0 ∼ 567 !6"#(1, 8 ) # 96:(8 ) = + + 1 2.( . + 4, * 3
Controlling for the effect of occupancy, we then added the range size predictor to the previous model. We used the Widely Applicable Information Criterion (WAIC) to decide whether the model's out of sample predictions improve when varying slopes on range size are included [START_REF] Mcelreath | Statistical rethinking: A Bayesian course with examples in R and Stan[END_REF] . The resulting model is:

0 ∼ 567 !6"#(1, 8 ) # 96:(8 ) = + + 1 2.( . + 4, * 3 + < *
where < is the effect of range size ( ).

We also modelled the effect of range size alone to estimate by how much it decreases occupancy when is part of the model:

0 ∼ 567 !6"#(1, 8 ) # 96:(8 ) = + + 1 2.( . + < *
Next, we sought to explain variation in average extinction probability across species between studies. In particular, we tested the effect of inter-census N-deposition on the outcome. The effect of N-deposition could, however, be confounded by the time between surveys (Δt). Cumulative N-deposition is a function of Δt, and Δt itself is likely to affect average extinction probability. We therefore include Δt in the model.

Furthermore, the year of the baseline survey (t1) can influence the outcome. For example, baseline surveys from later years are likely to be associated to higher cumulative N-deposition than those from earlier years. This might have already affected community composition to the extent that fewer extinctions occur in communities that were sampled in later years as these have already lost species. In our data t1 is strongly and negatively correlated to Δt;

the earlier the year of the baseline survey, the longer the time between surveys ( = -0.91, Extended Data 4). This correlation is also reflected in a strong negative correlation between cumulative N-deposition at the year of the baseline survey and time between surveys ( = -0.67; Extended Data 4). A directed acyclic graph of presumed causal links between predictors and response (Extended Data 5) shows that including time between surveys in the model controls for the confounding effect of year of the baseline survey and importantly, for environmental changes that preceded this survey, such as the cumulative N-deposition at the year of the baseline survey.

In addition to these potential confounding variables, the number of plots, their size and the size of the area in which surveys were carried out may directly affect the outcome. For instance, a species with occupancy 0.1 occupied 1 or 10 plots in studies of 10 or 100 plots, respectively and demographic fluctuations should be higher in smaller plots/areas that naturally comprise fewer individuals. As this may clearly affect the average extinction probability across species, we included these variables in the model. Finally, we also included latitude as a covariate in order to account for latitudinal patterns that might be associated to climate change. Together, this generates the following model: where + , , > , , , * are the effects of inter-census N-deposition (7 ), inter-census time period (: ), plot number (? ), plot size (@ ), site area (" ) and latitude (# ), respectively.

0 ∼ 567 !6"#(1,
We then asked whether any increase in average extinction probability across species due to N-deposition is driven by an increasing extinction probability among small-ranged species or simply a generally higher extinction probability across all range sizes. For this, we included the interaction effect between N-deposition and range size in the model: where +< is the slope of the interaction between inter-census N-deposition (7 ) and range size ( ).

0 ∼ 567 !6"#(1,
Until now, we only analyzed the dynamics of species present at the baseline. To these, we added further models to assess effects on colonizing species. We first asked: are changes in species number (A ) explained by N-deposition? Again we controlled for inter-census time period, plot number, plot size, site area and latitude, generating the following model:

A ∼
!"#(% , ) % = + + * 7 + * : + > * ? + * @ + * " + * * #

To visualize the effect of N-deposition, we used a predictor residual plot. In these, the outcome is regressed against the variation of N-deposition that is left unexplained by the other predictor variables in the model. Predictor residual plots allow us to display the actual data while controlling for all other predictors. Because the unit of observation in this model is the study, we have 68 observations. To display the influence of each data point on posterior predictions, we scaled point sizes by their Pareto k value [START_REF] Mcelreath | Statistical rethinking: A Bayesian course with examples in R and Stan[END_REF] . We then predicted the percentage point change in nonnative species using the same predictors as in the previous model, again using a predictor residual plot to display the results.

We also tested whether community composition shifts towards more N-demanding species with higher Ndeposition. For this, we regressed 1) the average N-demand of extinct species (! ) and 2) the change in mean Ndemand of the entire community (B ) against N-deposition:

! /B ∼ !"#(% , ) % = + + * 7
Finally, we tested whether the variance of nutrient availability across studies was greater in the period of the resurveys than in the period of the baseline surveys. Here, the model is: [START_REF] Olson | Terrestrial Ecoregions of the World: A New Map of Life on Earth: A new global map of terrestrial ecoregions provides an innovative tool for conserving biodiversity[END_REF] and forest cover for the year 2000 (in green) [START_REF] Hansen | High-resolution global maps of 21st-century forest cover change[END_REF] . Light to dark shades of green represent forest cover ranging from 0 to 100% at a spatial resolution of 30 meters.

" D ∼ !"#(% D ,
Figure 2: Species that go extinct from a study site have smaller ranges than persisting and colonizing ones.

Even after controlling for site occupancy, species' range size predicts probability of extinction. a, Expected differences in normalized range size between colonizing, persisting and extinct species. b, Effect of species' site occupancy at the time of the baseline survey on probability of extinction, x axis is standardized, so that zero represents the average site occupancy. c, Effect of species' range size on probability of extinction, after controlling for site occupancy (line shows expectation for site occupancy at its mean). Line segments in a represent ±2 standard deviations from the mean. Transparent ribbons in b and c represent the 89% credible intervals for model mean predictions. Model parameters are shown in Supplementary Table 2 and3

  + 1 F * : D where " D is the availability of N for the 6th study and Gth survey period, E and 1 E are the mean and standard deviation of the baseline survey respectively, F and 1 F are the expected difference between mean and standard deviation of the resurvey and baseline survey respectively, and : D is a 0/1 indicator for survey period. Author Contributions I.R.S., D.M.W. and L.B. conceived the study, with input from the sREplot working group (M.B.R., A.D.B., J.B., P.D.F, R.H., U.J., J.L., F.M., K.V., and M.W.). I.R.S. performed the analyses, with input from D.M.W. and L.B. I.R.S., D.M.W. and L.B. wrote the manuscript, with input and contributions from M.B.R., A.D.B, J.B., P.D.F., R.H., U.J., J.L., F.M., K.V., M.W., H.M.P., P.V., A.O.A., R.M., I.B., M.C., G.D., T. Dirnböck, T. Durak., W.S., T.H., F.H.S., B.J., M.K., M. Macek, M. Malicki, T.N., T.A.N., P.P., K.R., T.S., K.S., B.T., H.V.C., O.V. Authorship order was determined as follows: (1) core authors; (2) sREplot participants (alphabetical) and other major contributors; (3) authors contributing community composition data and to an advanced version of the manuscript (alphabetical).

Figure 1 :

 1 Figure1: Map of all 68 resurvey studies included in the forestREplot database, the temperate deciduous forest biome in Europe (shaded area)[START_REF] Olson | Terrestrial Ecoregions of the World: A New Map of Life on Earth: A new global map of terrestrial ecoregions provides an innovative tool for conserving biodiversity[END_REF] and forest cover for the year 2000 (in green)[START_REF] Hansen | High-resolution global maps of 21st-century forest cover change[END_REF] . Light to dark

  .

Figure 3 :

 3 Figure 3: Small-ranged species drive the increase in average extinction risk from high N-deposition. Although

  , 5, 6 and 7.

  kg ha -1 ) change in eiv N eiv N of extinctions f

Acknowledgments

This paper is an outcome of the sREplot working group supported by sDiv, the Synthesis Centre of the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig (DFG FZT 118). P.D.F. and P.V. received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (ERC Starting Grant FORMICA 757833). K.V. received funding through ERC Consolidator Grant PASTFORWARD 614839. M.K. and M.M. were supported by the Czech Academy of Sciences (RVO 67985939). F.M. was supported by the Slovak Research and Development Agency (APVV-15-0270). R.H, M.C. and O.V. were supported by the grant agency of the Czech Republic (17-09283S) and Czech Academy of Sciences (RVO 67985939). T.N. was supported by the Slovenian Research Agency (J4-1765). I.B. was supported by EFOP-3.6.1-16-2016-00018. R.P. was supported by a grant from the National Science Centre, Poland (2016/20/S/NZ800428). B.T. was financed by the Higher Education Institutional Excellence Program of the Ministry for Innovation and Technology in Hungary, within the framework of the 3rd thematic program of the University of Pécs.

Data availability

Community change and environmental site-level data are available on figshare, [https://figshare.com/s/45d71eb77c23c11bc857]. Species composition data are available from forestreplot.ugent.be but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon request and with permission of the forestREplot consortium.

Code availability R code for all analyses is available on figshare [https://figshare.com/s/45d71eb77c23c11bc857].

For each study, species were classified as native or non-native. This classification is based on the Global Register of Introduced and Invasive Species (GRIIS; http://www.griis.org). GRIIS lists species that are non-native in a given country. With these species lists we could flag, for each study, species that are non-native in the country of the study. To calculate the change in non-native species between surveys, we subtracted the proportion of non-native species in the total pool of species recorded in the baseline from the proportion of non-native species in the total pool of species recorded in the resurvey. Thus, we quantify the change in percentage points (Supplementary Figure 3b). Calculation of relative change was not possible because frequently there were no non-native species in the baseline survey (26% of studies, Supplementary Figure 3a). The mean number of non-native species in the baseline survey and the resurvey was 5 and 7 (rounded to the next integer), respectively. The mean number of native species was 110 (baseline survey) and 102 (resurvey).

Change in nitrophilous species and nutrient availability

We estimated changes in species' N-demands using Ellenberg's indicator values (EIVs). EIVs were developed for Central Europe and classify species' habitat niches and their peak occurrence along environmental gradients [START_REF] Ellenberg | Zeigerwerte von Pflanzen in Mitteleuropa.-3[END_REF] . In particular, we used EIVs for N or more general productivity [START_REF] Diekmann | Species indicator values as an important tool in applied plant ecology--a review[END_REF] that classify species growing on the poorest soils (Nnumber = 1) to species growing on the most productive soils with excessive nutrient availability (N-number= 9) (Extended Data 2). For each study and survey, we averaged N-numbers across species. Because EIVs equally reflect environmental conditions [START_REF] Verheyen | Driving factors behind the eutrophication signal in understorey plant communities of deciduous temperate forests[END_REF] , these average values approximate both the mean N-demand of a community and the nutrient availability at each survey. To quantify the change in a community's mean N-demand, we subtracted the mean N-demand of the baseline community from the mean N-demand of the resurvey community. To better understand what drives changes in communities mean N-demands, we calculated the average N-demand of extinct and colonizing species (Extended Data 2) for each study.

Data analyses

Competing interests

The authors declare no competing interests.


Sylvie Lautru
email: sylvie.lautru@i2bc.paris-saclay.fr

Anthelvencins A and B are pyrrolamide metabolites produced by Streptomyces venezuelae ATCC 14583 and 14585. Isolated in 1965, they were reported to exhibit anthelmintic and moderate antibacterial activities. In this study, we revise the structure of anthelvencin A and identify a third anthelvencin metabolite, bearing two N-methylated pyrrole groups, which we named anthelvencin C. We sequenced the genome of S. venezuelae ATCC 14583 and identified a gene cluster predicted to direct the biosynthesis of anthelvencins. Functional analysis of this gene cluster confirmed its involvement in anthelvencin biosynthesis and allowed us to propose a biosynthetic pathway for anthelvencins. In addition to a nonribosomal peptide synthetase (NRPS), the assembly of anthelvencins involves an enzyme from the ATP-grasp ligase family, Ant23. We propose that Ant23 uses a PCP-loaded 4aminopyrrole-2-carboxylate as substrate. As observed for the biosynthesis of the other pyrrolamides congocidine (produced by Streptomyces ambofaciens ATCC 25877) and distamycin (produced by Streptomyces netropsis DSM 40846), the NRPS assembling anthelvencins is composed of stand-alone domains only. Such NRPSs, sometimes called type II NRPSs, are less studied than the classical multimodular NRPSs. Yet, they constitute an interesting model to study protein-protein interactions in NRPSs and are good candidates for combinatorial biosynthesis approaches.

Anthelvencins A and B (Figure 1A) are specialized metabolites that were isolated in 1965 from cultures of Streptomyces venezuelae ATCC 14583 and 14585 and exhibit moderate antibacterial and anthelmintic activities [START_REF] Probst | Anthelvencins, new antibiotics with anthelmintic properties[END_REF] . They belong to the family of pyrrolamide metabolites, the best-characterized members of which are congocidine (also called netropsin, produced by Streptomyces ambofaciens ATCC 25877) and distamycin (produced by Streptomyces netropsis DSM 40846) (see Supplementary Figure S1). These metabolites are known to bind to the DNA minor groove with some sequence specificity for regions of four (or more) A or T bases [START_REF] Neidle | DNA minor-groove recognition by small molecules[END_REF] . During the last decade, the biosynthetic gene clusters of congocidine and distamycin have been identified and the biosynthesis of these metabolites has been elucidated [START_REF] Juguet | An iterative nonribosomal peptide synthetase assembles the pyrroleamide antibiotic congocidine in Streptomyces ambofaciens[END_REF][START_REF] Vingadassalon | Natural combinatorial biosynthesis involving two clusters for the synthesis of three pyrrolamides in Streptomyces netropsis[END_REF][START_REF] Hao | Mining of the pyrrolamide antibiotics analogs in Streptomyces netropsis reveals the amidohydrolase-dependent "iterative strategy" underlying the pyrrole polymerization[END_REF][6][START_REF] Lautru | A sweet origin for the key congocidine precursor 4-acetamidopyrrole-2carboxylate[END_REF] . One remarkable aspect of this biosynthesis is that it involves noncanonical non-ribosomal peptide synthetases (NRPSs), solely constituted of stand-alone modules or domains. Such NRPSs are sometimes called type II NRPSs. They participate in the biosynthesis of unusual precursors of non-ribosomal peptides (NRP) [START_REF] Jaremko | Type II nonribosomal peptide synthetase proteins: structure, mechanism, and protein-protein interactions[END_REF] and are involved in the assembly of some NRP such as phosphinothricin [START_REF] Schinko | Phosphinothricintripeptide biosynthesis: an original version of bacterial secondary metabolism?[END_REF] and rhabdopeptide/xenortide peptides [START_REF] Cai | Entomopathogenic bacteria use multiple mechanisms for bioactive peptide library design[END_REF] .

A structural analysis of anthelvencins shows that these metabolites most likely share two precursors with congocidine and distamycin: 4-acetamidopyrrole-2-carboxylate (5) and 3-aminopropionamidine (6). The remaining precursor is probably 5-amino-3,4-dihydro-2Hpyrrole-2-carboxylate (4), a precursor shared with other pyrrolamides such as kikumycins [START_REF] Takaishi | Structure of Kikumycin A and B[END_REF] or TAN 868A [START_REF] Takizawa | A new pyrrole-amidine antibiotic TAN-868 A[END_REF] (Figure S1). In fact, a limited number of precursors seems to be assembled in various combinations to give birth to the different members of the pyrrolamide family.

Understanding how these precursors are assembled and combined may improve our comprehension of type II NRPS enzymatic mechanisms and help to design functional synthetic NRPSs using synthetic biology. For these reasons, we undertook to identify and characterize the anthelvencin biosynthetic gene cluster of S. venezuelae ATCC 14583. In this study, we revise the structure of anthelvencin A based on HR-MS 2 and NMR data. We show that S. venezuelae ATCC 14583 produces, in addition to the already known anthelvencins A and B, a third anthelvencin, methylated on the two pyrrole groups. We named this new anthelvencin anthelvencin C. We also identify the gene cluster directing the biosynthesis of anthelvencins in S. venezuelae ATCC 14583 genome and we functionally characterize this gene cluster.

RESULTS AND DISCUSSION

In silico identification of a gene cluster putatively involved in anthelvencin biosynthesis in S. venezuelae ATCC 14583. To identify the gene cluster directing anthelvencin biosynthesis, we sequenced the genome of the S. venezuelae ATCC 14583 strain by the Illumina technology, using a paired-end genomic library. The 5.45 million reads of 301 bps were assembled using Velvet v1.2.10, resulting in 63 contigs with a total length of 9.08 Mbps (180-fold coverage).

The gene cluster directing the biosynthesis of anthelvencins was identified by mining the genome of S. venezuelae ATCC 14583 for homologs of genes involved in the biosynthesis of congocidine [START_REF] Juguet | An iterative nonribosomal peptide synthetase assembles the pyrroleamide antibiotic congocidine in Streptomyces ambofaciens[END_REF] . We identified a gene cluster (ant, GenBank accession number MK483114) that spans 26 kb and contains 22 genes (Figure 1B). The deduced products of twenty of these genes exhibit a high amino acid sequence identity with Cgc proteins involved in congocidine biosynthesis (from 64 to 84 % sequence identity, Table 1) and they most likely have similar Ectoine synthase-like protein None function to their Cgc homologs. Thus, the gene numbers attributed to the ant genes were chosen to follow the cgc nomenclature whenever possible. The genetic organization of the ant cluster is remarkably similar to the one of the cgc cluster 3 from S. ambofaciens ATCC23877 (Figure S2). Two cgc genes (cgc7 and cgc18) have no homologs in the ant gene cluster. These two genes are involved in the biosynthesis of the guanidinoacetate precursor (absent in anthelvencins) and its assembly. Based on the high level of sequence identity between Ant and Cgc proteins and on the previously published biosynthetic pathways for congocidine and distamycin [START_REF] Juguet | An iterative nonribosomal peptide synthetase assembles the pyrroleamide antibiotic congocidine in Streptomyces ambofaciens[END_REF][START_REF] Vingadassalon | Natural combinatorial biosynthesis involving two clusters for the synthesis of three pyrrolamides in Streptomyces netropsis[END_REF]6,[START_REF] Lautru | A sweet origin for the key congocidine precursor 4-acetamidopyrrole-2carboxylate[END_REF] , we propose the following roles for the Ant proteins. Ant8 to Ant13, Ant3 and Ant17 are involved in the biosynthesis of 4acetamidopyrrole-2-carboxylate (5) and Ant14 is involved in its deacetylation. Ant4 to Ant6 are involved in the biosynthesis of 3-aminopropionamidine (6). Ant2, Ant16, Ant19, and Ant22 are involved in the assembly of anthelvencins. In addition to these, proteins are necessary for the biosynthesis and assembly of 5-amino-3,4-dihydro-2H-pyrrole-2carboxylate (4). The ant cluster contains two genes, ant24 and ant23, which have no homolog in the cgc cluster. We hypothesized that they might be involved in the biosynthesis of (4) and its assembly. Indeed, a protein blast [START_REF] Altschul | Basic local alignment search tool[END_REF] and a conserved domain searches [START_REF] Marchler-Bauer | CDD/SPARCLE: functional classification of proteins via subfamily domain architectures[END_REF] on the Ant24 sequence suggested that Ant24 belongs to the L-ectoine synthase (EC 4.2.1.108) family of enzymes. L-ectoine synthases catalyze the ring closure of N-acetyl-L-2,4diaminobutyric acid, yielding the osmolyte ectoine, a metabolite structurally related to (4). In 2011, Witt and collaborators reported that the ectoine synthase from Halomonas elongata can catalyze the intramolecular condensation of glutamine to form (4) as a side reaction [START_REF] Witt | Unexpected property of ectoine synthase and its application for synthesis of the engineered compatible solute ADPC[END_REF] .

This enzyme has 34% sequence identity and 51% sequence similarity with Ant24. Thus, it appears likely that Ant24 catalyzes the same reaction (Scheme 1).

Scheme 1: Proposed biosynthesis of 5-amino-3,4-dihydro-2H-pyrrole-2-carboxylate (4) by

Ant24

Ant23 contains an ATP-grasp domain. ATP-grasp enzymes usually catalyze the ATPdependent ligation of a carboxylate-containing molecule to an amino or thiol group-containing molecule [START_REF] Galperin | A diverse superfamily of enzymes with ATPdependent carboxylate-amine/thiol ligase activity[END_REF] . Some of these ATP-grasp enzymes play a role in the biosynthesis of specialized metabolites [START_REF] Goswami | Enzymatic strategies and biocatalysts for amide bond formation: tricks of the trade outside of the ribosome[END_REF] . They can function as an alternative to or in combination with non-ribosomal peptide synthetases (NRPS), to elongate a peptide chain [START_REF] Goswami | Enzymatic strategies and biocatalysts for amide bond formation: tricks of the trade outside of the ribosome[END_REF][START_REF] Hollenhorst | The ATP-dependent amide ligases DdaG and DdaF assemble the fumaramoyl-dipeptide scaffold of the dapdiamide antibiotics[END_REF] . Thus, it appears plausible that Ant23 catalyzes the amide bond formation between (4) and a PCP (Ant19)-bound 4aminopyrrole-2-carboxylate.

Abolition of the production of four metabolites in a S. venezuelae ATCC 14583 mutant deleted for ant8 (coding for a putative nucleotidyl N-acetylglucosamine dehydrogenase).

To verify that the ant gene cluster is involved in the biosynthesis of anthelvencins, we inactivated ant8. This gene is the ortholog of cgc8, the product of which is involved in the biosynthesis of the 4-acetamidopyrrole-2-carboxylate (5). The ant8 gene was replaced by an aac(3)IV resistance cassette by homologous recombination using the pANT007 suicide plasmid, yielding the S. venezuelae ANT007 strain. This strain and the wild type S. venezuelae strain were cultivated for three days in MP5 liquid medium. The culture supernatants were then filtered and analyzed by HPLC. The chromatograms show that four metabolites present in the wild type strain supernatant (peaks I to IV) are absent in the supernatant of the ANT007 mutant strain (Figure 2). The first metabolite (peak I, retention time of 11.

Chemical nature of metabolites II, III and IV.

To determine the chemical nature of the metabolites II, III and IV, we partially purified them. For that purpose, we used ANT012, a strain that expressed a second copy of the genes ant23 and ant24 under the control of the promoter rpsL(TP) [START_REF] Shao | Refactoring the Silent Spectinabilin Gene Cluster Using a Plug-and-Play Scaffold[END_REF] , as this strain produces compounds III and IV in slightly higher titers (data not shown). The ANT012 culture supernatant was recovered after three days of culture in MP5 medium and the compounds of interest were partially purified on a XAD16 resin. The and 5), indicates that the position of the methyl group is not on the B pyrrole ring, as previously proposed (but never experimentally established 1 ) but rather on the A pyrrole ring (Figure 1). To confirm the structure of anthelvencin A, we purified compound III and carried out NMR experiments. [START_REF] Probst | Anthelvencins, new antibiotics with anthelmintic properties[END_REF] H NMR of anthelvencin A hydrochloride proved to be very similar to the one reported for the authentic sample synthesized by Lee and coworkers [START_REF] Goswami | Enzymatic strategies and biocatalysts for amide bond formation: tricks of the trade outside of the ribosome[END_REF] assuming the position of the methyl group on the B pyrrole ring. However, a combination of twodimensional NMR experiments confirmed the position of this methyl on the A ring. We therefore propose a revised structure for anthelvencin A (Figure S6).

The exact mass and fragmentation pattern of compound IV (Figure S7) are consistent with IV being an anthelvencin metabolite methylated on both pyrrole groups ([M+H] + m/z = 442.2311; calculated 442.2310), a metabolite that we named anthelvencin C (Figure 1A, 3).

We tried to purify anthelvencin C to confirm its chemical structure with NMR analyses but this metabolite turned out to be highly unstable, as already observed by Lee and coworkers [START_REF] Lee | Total synthesis and absolute configuration of the antibiotic oligopeptide (4S)-(+)-anthelvencin A and its 4R-(-) enantiomer[END_REF] .

Involvement of ant24 in 5-amino-3,4-dihydro-2H-pyrrole-2-carboxylate (4) biosynthesis.

To verify that ant24 is involved in the biosynthesis of anthelvencins, we replaced it by an aac(3)IV resistance cassette by homologous recombination, following the same procedure as described above. The culture supernatant of the resulting mutant strain, called ANT009, was analyzed by HPLC. No production of anthelvencins was observed, confirming that ant24 is necessary for the production of these metabolites (Figure 3A). To ensure that the observed phenotype was due to the replacement of ant24 by the aac(3)IV cassette, we genetically complemented the ANT009 strain using a plasmid expressing ant23 and ant24 under a constitutive promoter. The production of anthelvencins was restored in the complemented strain, named ANT014 (Figure S8A), thus confirming that ant24 is involved in anthelvencin biosynthesis.

To examine Ant24 putative function in the biosynthesis of (4), we undertook the chemical complementation of ANT009 by adding to the culture medium (4), the putative product of Ant24-catalyzed reaction. Thus, (4) was synthetized according to a previously described synthetic procedure [START_REF] Lee | Synthesis of (4S)-and (4R)-methyl 2-amino-1pyrroline-5-carboxylate and their application to the preparation of (4S)-(+)-and (4R)-(-)dihydrokikumycin B[END_REF] (Scheme 2).

Scheme 2: Synthesis of 5-amino-3,4-dihydro-2Hpyrrole-2-carboxylate (4)

We next fed the ANT009 strain with (4). As shown in Figure 3B, this resulted in the restoration of the production of anthelvencins A and C, hence confirming the involvement of ant24 in the biosynthesis of the anthelvencin precursor (4). Numbers above peaks correspond to the metabolite numbers in the text.

Involvement of ant23 in the biosynthesis of anthelvencins.

To confirm that Ant23 is involved in anthelvencin biosynthesis, we replaced ant23 by the aac(3)IV resistance cassette following the previously described protocol. The resulting mutant strain was called ANT008. It was cultivated for three days in MP5 medium at 28°C and the culture supernatant was analyzed by HPLC. Figure 3C shows that no anthelvencin is produced by the ANT008 mutant. To ensure that the observed phenotype was due to the replacement of ant23 by the aac(3)IV cassette, we genetically complemented the ANT008 strain using the plasmid expressing ant23 and ant24 under a constitutive promoter. The production of anthelvencins was restored in the complemented strain, named ANT013 (Figure S8B), thus confirming that ant23 is involved in anthelvencin biosynthesis.

Proposed biosynthetic pathway for anthelvencin biosynthesis. Based on the results

presented above and on previous characterizations of pyrrolamide biosyntheses [START_REF] Juguet | An iterative nonribosomal peptide synthetase assembles the pyrroleamide antibiotic congocidine in Streptomyces ambofaciens[END_REF][START_REF] Vingadassalon | Natural combinatorial biosynthesis involving two clusters for the synthesis of three pyrrolamides in Streptomyces netropsis[END_REF]6 , we proposed that anthelvencins are assembled from 3-amidinopropionamidine, 4-aminopyrrole-

MATERIALS AND METHODS

C C

Bacterial strains, plasmids and growth conditions. Strains and plasmids used in this study are listed in Table S1 andS2. Escherichia coli strains were grown at 37 °C in LB or SOB complemented with MgSO 4 (20 mM final), supplemented with appropriate antibiotics as needed [START_REF] Sambrook | Molecular Cloning: A Laboratory Manual 3rd Revised edition[END_REF] . The Soya Flour Mannitol (SFM) medium 23 was used for genetic manipulations of Streptomyces strains and spore stocks preparations at 28°C. Streptomyces strains were grown for three days at 28°C in MP5 [START_REF] Pernodet | Resistance to spiramycin in Streptomyces ambofaciens, the producer organism, involves at least two different mechanisms[END_REF] for anthelvencins (1-3) production.

DNA preparation and manipulations.

All oligonucleotides used in this study were purchased from Eurofins and are listed in Table S3. The High fidelity DNA polymerase Phusion (Thermo Fisher Scientific) was used to amplify the DNA fragments for the construction of the suicide plasmids. DreamTaq polymerase (Thermo Fisher Scientific) was used for PCR verification of plasmids and of the replacement of the targeted genes by the resistance cassette aac(3)IV. DNA fragments were purified from agarose gels using the Nucleospin Gel and PCR clean-up kit from Macherey-Nagel. E. coli transformations and E. coli/Streptomyces conjugations were performed according to standard procedures [START_REF] Sambrook | Molecular cloning: A Laboratory Manual[END_REF]23 .

S. venezuelae ATCC 14583 sequencing and assembly. Total DNA of S. venezuelae

ATCC 14583 was extracted following the salting out procedure 23 except that the mycelium was ground in liquid nitrogen. A paired-end library of the whole genome was constructed and sequenced at the high throughput sequencing core facility of I2BC with a MiSeq M01342 instrument (Illumina), generating 5.45 million 301 bp reads that were assembled using Velvet v1.2.10. The GenBank accession number of the anthelvencin gene cluster is MK483114. intergeneric conjugation from the E. coli ET12567/pUZ8002/pANT007 strain. Doublerecombinant mutants were selected on SFM plates with 50 µg/mL apramycin and screened for hygromycin sensitivity. DNA from the resulting strain, ANT007, was isolated and analyzed by PCR using the primers A5, A6, and CEA013-CEA016 (See Figure S8). The same protocol was used for the construction of the ANT008 mutant strain (replacement of ant23), using the plasmid pANT008, and the ANT009 mutant strain (replacement of ant24), using the plasmid pANT009 (see Tables S2 andS3 for plasmid names and for primer sequences).

Construction of the replacement

Construction of the ANT012 strain overexpressing Ant23 and Ant24. The DNA region containing ant23-ant24 was amplified by PCR from S. venezuelae ATCC 14583 genomic DNA using the primers CEA034/CEA035. The PCR product was purified and cloned into pCR® Blunt, yielding pANT011. The sequence of the insert was confirmed by sequencing.

The 2.0 kb NheI/AflII fragment from pANT011 was ligated into the SpeI/AflII-digested pCEA005 [START_REF] Aubry | Modular and Integrative Vectors for Synthetic Biology Applications in Streptomyces spp[END_REF] . The obtained plasmid, containing ant23 and ant24 under the rpsL(TP) promoter, was named pANT012 and confirmed by restriction digestion. This plasmid was introduced into S. venezuelae ATCC 14583 by intergeneric conjugation. The correct integration of pANT012 was verified on the extracted DNA by PCR using the primers CEA_vec_seq14 and CEA_vec_seq15 and the strain was named ANT012.

Genetic complementation of ANT008.

As the ANT008 strain bears the aac(3)IV resistance marker, the previously constructed pANT012 plasmid, bearing an aac(3)IV resistance gene cassette, could not be used for the genetic complementation of the strain. Thus, the 2.4 kb NsiI/AflII DNA fragment of pANT012 containing ant23 and ant24 under the control of the rpsL(TP) promoter was ligated into the NsiI/AflII-digested pOSV806 [START_REF] Aubry | Modular and Integrative Vectors for Synthetic Biology Applications in Streptomyces spp[END_REF] . The resulting plasmid was named pANT013 and was introduced into ANT008 by intergeneric conjugation. The strain obtained was named ANT013.

Chemical synthesis of 5-amino-3,4-dihydro-2H-pyrrole-2-carboxylate (4). Compound (4)

was prepared according to a previously described synthetic procedure 29 (Scheme 2).

Commercially available DL-pyroglutamic acid (7) was converted into the corresponding methyl ester (8) by treatment with thionyl chloride (2 equiv.), and N,N-dimethylformamide (DMF) (2 mol %) in methanol. Derivative (8) was then submitted to a reaction with triethyloxonium tetrafluoroborate (Meerwein's salt, 1.4 equiv.) in dichloromethane (DCM) to form carboximidate (9) in quantitative yield. This compound subsequently reacted with ammonium chloride (1.05 equiv.) in refluxing methanol to provide product (10) in 61% yield.

Hydrolysis of the ester moiety of compound (10) finally afforded the desired acid (4) in a quantitative yield. A detailed synthesis protocol is available in the Supporting Information.

Chemical complementation of ANT009. S. venezuelae ANT009 strain was cultivated in 50 mL of MP5. After 24 h, the cultures were separated in two 25 mL cultures, and 1 mM of (4) (final concentration) was added to one of the cultures. After a total of 72 h of cultivation, culture supernatants were analyzed by HPLC as described below.

HPLC analysis

Figure 1 .

 1 Figure 1. (A) Chemical structure of anthelvencins A, B and C; (B) Genetic organization of the anthelvencin biosynthetic gene cluster in S. venezuelae ATCC 14583. Genes in boldface are genes that were used as targets for genetic inactivation. The numbers in boldface (1a-6) are used to refer to the corresponding chemical structures.

  5 min) corresponds to 4-aminopyrrole-2-carboxylate (5), identified by its UV spectrum and by comparison with an authentic standard (Figure 2 and reference 7). The three peaks II (retention time of 13.3 min), III (retention time of 14.3 min) and IV (retention time of 15.5 min) have UV absorption spectra typical of pyrrolamides (Figure S3 and reference 4).

Figure 2 :

 2 Figure 2: HPLC analysis of culture supernatants of A) S. venezuelae ATCC 14583 wild

  elution fraction was concentrated to dryness solution, resuspended in water and analyzed by LC-HR-MS². The exact mass and fragmentation pattern of compound II (Figure S4) are consistent with II being anthelvencin B (2) ([M+H] + m/z = 414.1998; calculated 414.1997). The exact mass of compound III (Figure S5) is consistent with III being anthelvencin A ([M+H] + m/z = 428.2151; calculated 428.2153). The fragmentation pattern however (Figure S5, fragments 4

Figure 3 :

 3 Figure 3: HPLC analysis of culture supernatants of (A) ANT009 (S. venezuelae ATCC 14583

2-carboxylate and 5 -

 5 amino-3,4-dihydro-2H-pyrrole-2-carboxylate following the biosynthetic pathway presented in Figure 4. As already observed for the biosynthesis of other pyrrolamides (congocidine, distamycin), the non-ribosomal peptide synthetase involved in anthelvencins is constituted solely of stand-alone domains (C domains Ant2 and Ant16 and PCP domain Ant19). No adenylation domain is involved in the activation of the carboxylate groups of the precursors. Instead, activation of the carboxylate group of the pyrrole precursor (5) and the covalent attachment of the activated precursor to the PCP domain Ant19 is catalyzed by Ant22, which belongs to the family of acyl-CoA synthetases. The formation of the first amide bond between (4) and Ant19-bound (5) is likely catalyzed by Ant23, an enzyme from the ATP-grasp ligase family, which form acylphosphate intermediates. Two stand-alone condensation domains, Ant16 and Ant2, catalyze the formation of the other amide bonds, adding respectively a second pyrrole precursor and the 3aminopropionamidine to Ant19-bound intermediates. Thus, during anthelvencin assembly, the stand-alone PCP domain, Ant19, interacts with two different families of enzymes (condensation domain and ATP-grasp ligase).

Figure 4 :

 4 Figure 4: Proposed biosynthetic pathway for anthelvencins A, B and C The blue ellipses represent PCP domains, and the red circles represent C domains

  mutants. The suicide plasmid pANT007 was constructed to replace the ant8 gene by an aac(3)IV resistance cassette in S. venezuelae. This vector was constructed by assembling the three following inserts in the backbone pOSV400 (bearing a hygromycin resistance gene)[START_REF] Boubakri | The Absence of pupylation (prokaryotic ubiquitinlike protein modification) affects morphological and physiological differentiation in Streptomyces coelicolor[END_REF] : a 1.8 kb fragment upstream of ant8, the resistance cassette aac(3)IV and a 2.0 kb DNA fragment downstream of ant8. The 1.8 kb and 2.0 kb DNA fragments from S. venezuelae ATCC 14583 were amplified by PCR with the primers CEA001/CEA002 and CEA003/CEA004 respectively. The PCR products were purified and ligated into pCR® Blunt, yielding pANT001 (containing the upstream DNA fragment) and pANT002 (containing the downstream DNA fragment). Both plasmids were verified by sequencing (Genewiz). The aac(3)IV resistance cassette was obtained by digestion of pW60 27 by HindIII. The 1.8 kb HindIII-XhoI fragment from pANT001, the 1.0 kb HindIII aac(3)IV fragment, and the 2.0 kb HindIII-SpeI fragment from pANT002 were then ligated into the XhoI-SpeI-digested pOSV400, yielding pANT007. The pANT007 plasmid was verified by restriction digestion and was introduced into S. venezuelae ATCC 14583 by

  of culture supernatants. S. venezuelae ATCC 14583 and its derivatives were cultivated in MP5 medium for three days at 28°C. The supernatants were filtered using Mini-UniPrep syringeless filter devices (0.2 µm, Whatman). The samples were analyzed on an Atlantis C 18 T3 column (250 mm x 4.6 mm, 5 µm, column temperature 28°C) using an Agilent 1200 HPLC instrument with a quaternary pump. Samples were eluted in isocratic conditions with 0.1% v/v HCOOH in H 2 0 (solvent A)/ 0.1% v/v HCOOH in CH 3 CN (solvent B) (95:5) at 1 ml.min -1 for 7 min, followed by a gradient to 40:60 A/B over 23 min. Anthelvencins were detected by monitoring absorbance at 297 nm.LC-HR-MS-MS analyses.The resuspended elution fraction obtained above was analyzed by LC-HR-MS 2 . The analysis was performed using a Dionex Ultimate 3000 HPLC system coupled with a Maxis II™ QTOF mass spectrometer (Bruker, MA, USA) fitted with an electrospray ionization (ESI) source. Chromatographic analysis was performed using a C 18 AcclaimTM RSLC PolarAdvantage II (2.1 x 100 mm, 2.2 µm pore size) column (Thermo Scientific, MA, USA). Column temperature was set at 40 °C and 2 μL of each sample was injected via an autosampler cooled to 4 °C. A flow rate of 0.3 mL/min was used and the eluent was introduced directly into the MS for ion detection. Elution was conducted with a mobile phase consisting of 0.1% v/v HCOOH in H 2 0 (solvent A) and 0.1% v/v HCOOH in CH 3 CN (solvent B) following the gradient elution profile: 0 min, 5% solvent B; 2 min, 5% solvent B; 9 min, 50% solvent B; 15 min 90% solvent B; 17 min 90% solvent B; 19 min 5% solvent B; 21 min 5% solvent B. In the first half minute of each run, a sodium formate solution was injected directly as an internal reference for calibration. The acquisition parameters of the ESI source were set up as follows: electrospray voltage for the ESI source: 3500V, nebulising gas (N2) pressure: 35 psi, drying gas (N 2 ) flow: 8 L/min, and drying temperature: 200°C. Mass spectra were recorded over the m/z range 100-1300 at a frequency of 2 Hz, in positive ion mode. For MS/MS analysis, the cycle time was of 3 sec. Mass spectra were recorded over the m/z range 100-1300 at a frequency of 2 Hz, in positive ion mode. Selected parent ion at m/z 442.23 was fragmented at a fixed collision energy value of 40 eV and an isolation window of 0.5 amu.

Table 1 .

 1 Sequence identities between Ant and Cgc proteins 99

	Protein Putative protein function	Cgc ortholog	%
				(Accession number)	sequence
					identity
	Ant1	Transcriptional regulator	Cgc1 (AKZ59702.1)
	Ant2	NRPS, C domain		Cgc2 (AKZ59703.1)
	Ant3	4-Acetamidopyrrole-2-carboxaldehyde	Cgc3 (AKZ59704.1)
		dehydrogenase
	Ant4	Cytosine monophosphate hydrolase	Cgc4 (AKZ59705.1)
	Ant5	Cytosine reductase	Cgc5 (AKZ59706.1)
	Ant6	Dihydrocytosine hydrolase	Cgc6 (AKZ59707.1)
	Ant8	Nucleotidyl	N-acetylglucosamine	Cgc8 (AKZ59709.1)
		dehydrogenase
	Ant9	Nucleotidyl-2-acetamido-2-	Cgc9 (AKZ59710.1)
		deoxyglucopyranuronate decarboxylase
	Ant10	Glycosyltransferase-like enzyme	Cgc10 (AKZ59711.1)
	Ant11	N-acetylglucosamine-1-phosphate	Cgc11 (AKZ59712.1)
		nucleotidyltransferase
	Ant12	Nucleotidyl threo-2-acetamido-2-deoxy-	Cgc12 (AKZ59713.1)
		pentopyran-4-ulose aminotransferase
	Ant13	Glycoside hydrolase	Cgc13 (AKZ59714.1)
	Ant14	4-Acetamidopyrrole-2-carboxylate	Cgc14 (AKZ59715.1)
		deacetylase
	Ant15	Methyltransferase		Cgc15 (AKZ59716.1)
	Ant16	NRPS, C domain		Cgc16 (AKZ59717.1)
	Ant17	4-Acetamidopyrrole-2-carboxaldehyde	Cgc17 (AKZ59718.1)
		dehydrogenase
	Ant19	NRPS, PCP domain	Cgc19 (AKZ59720.1)
	Ant20	ABC transporter		Cgc20 (AKZ59701.1)
	Ant21	ABC transporter		Cgc21 (AKZ59700.1)
	Ant22	Acyl co-A synthetase	Cgc22 (AKZ59699.1)
	Ant23	ATP-grasp domain-containing protein	None
	Ant24

Acknowledgements

We acknowledge the High-throughput sequencing facility of I2BC for its sequencing and bioinformatics expertise (Centre de Recherche de Gifhttp://www.i2bc.paris-saclay.fr/). We thank Z. Hong, Y. Li, S. Prado and D. Touboul for their help with the LC-HRMS 2 analysis.

The research received funding from ANR-14-CE16-0003-01. The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Accession codes. The GenBank accession number of the anthelvencin gene cluster is MK483114. Its MiBig 30 accession number is BGC0002042.

Supporting Information Available:

The protocol for the synthesis of 5-amino-3,4-dihydro-2H-pyrrole-2-carboxylate (4), the strains, plasmids and oligonucleotides used in this study and seven supplementary figures are available in the Supporting Information. This material is available free of charge via the internet at http://pubs.acs.org