Jason Vleminckx

Oscar Valverde Barrantes

Claire Fortunel

C E Timothy Paine

David Bauman

Julien Engel

Pascal Petronelli

Nállarett Dávila

Marcos Rios

Elvis Harry

Valderrama Sandoval

Oscar Valverde Barrantes

Italo Mesones

Elodie Allié

Jean-Yves Goret

Freddie C Draper

Juan Ernesto Guevara Andino

Solène Béroujon

Paul V A Fine

Christopher Baraloto

Niche breadth of Amazonian trees increases with niche optimum across broad edaphic gradients

Keywords: abiotic filtering, competitive exclusion, functional traits, Neotropical forests, niche breadth, niche position, range of resource use, soil nutrient availability, tree community assembly

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

Introduction

A major interest among plant community and evolutionary biologists is to better understand how environmental filtering and biotic interactions shape community assembly.

Many studies examining the determinants of plant β-diversity have emphasized the role of abiotic conditions, such as soil properties, through filtering processes related to species resource acquisition strategies and tolerance to drought and toxicity [START_REF] Condit | Species distributions in response to individual soil nutrients and seasonal drought across a community of tropical trees[END_REF][START_REF] Kraft | Plant functional traits and the multidimensional nature of species coexistence[END_REF][START_REF] Vleminckx | The influence of spatially structured soil properties on tree community assemblages at a landscape scale in the tropical forests of southern Cameroon[END_REF][START_REF] Van Breugel | Soil nutrients and dispersal limitation shape compositional variation in secondary tropical forests across multiple scales[END_REF]. Several theories have suggested that hyperdiverse communities such as tropical forests also experience strong biotic interactions, mediated by intense inter-specific competition for resources and enemy attacks (Schemske 2009[START_REF] Fine | The growth-defense trade-off and habitat specialization by plants in Amazonian forests[END_REF][START_REF] Baraloto | Rapid simultaneous estimation of aboveground biomass and tree diversity across Neotropical forests: a comparison of field inventory methods[END_REF]. Over time, these biotic interactions would have resulted in the local coexistence of species displaying narrower species niches [START_REF] Rproject | Evolution in the tropics[END_REF][START_REF] Pianka | Latitudinal gradients in species diversity: a review of the concepts[END_REF][START_REF] Macarthur | Patterns of communities in the tropics[END_REF].

Habitat heterogeneity remains a major determinant of species turn-over in tropical forests. In the Amazon, for instance, white-sand habitats show extremely nutrient-depleted conditions that select for species investing into costly but well-defended tissues (e.g. thick leaves, hard wood), which render these species less competitive on relatively more fertile conditions (the growth-defense trade-off; [START_REF] Fine | The growth-defense trade-off and habitat specialization by plants in Amazonian forests[END_REF][START_REF] Fine | Floristic Study of the White-Sand Forests of Peru[END_REF]. Species relative investment in costly tissues should therefore reflect their optimum along a resource availability gradient. This optimum should correlate well with the range of resource availability a species can tolerate, under the assumption that poor-soil specialists are poor competitors in fertile conditions and are thereby confined to more restricted niches than faster-growing, rich-soil specialists. Therefore, comparing the range and optimum of species along a steep resource availability gradient would help to determine whether conservative species with a high degree of specialization for poor soil conditions exhibit narrower niches than acquisitive species that grow faster and are more competitive in fertile soils (assuming that no other processes are becoming important across a broad gradient in soil fertility). Such a comparison would address a major concern that most studies may overstate the role of abiotic filtering as a community assembly rule because they fail to consider the potential influence of biotic processes (Kraft et al. 2014). Additionally, examining how species range and optimum align with different functional strategies may help to identify adaptive trade-offs that delimit species' niches.

Despite the rapid accumulation of plant functional trait data from diverse ecosystems, few studies have attempted to link tree species range, optimum, and functional traits (but see [START_REF] Treurnicht | Functional traits explain the Hutchinsonian niches of plant species[END_REF] for Fynbos plant communities of the Cape Floristic Region).

Species niche range and optimum relate to the two fundamental parameters proposed by

Hutchinson in his hypervolume model (1957), which has provided one of the most successful mechanistic constructs of the ecological niche concept. The niche range is commonly referred to as "niche breadth", "niche width", "niche size", or "ecological amplitude" [START_REF] Carscadden | Niche breadth: Causes and consequences for ecology, evolution, and conservation[END_REF]. Following the Hutchinson's concept of the niche, the niche breadth determines the range of environmental conditions that a species can tolerate and the range of resources that it uses (the potential, or fundamental niche), a range that in reality is more contracted due to antagonistic interactions mediated by competition for resources, natural enemies, or dispersal barriers (the realized, or observed niche) [START_REF] Malanson | Realized versus fundamental niche functions in a model of chaparral response to climatic change[END_REF][START_REF] Mcgill | Rebuilding community ecology from functional traits[END_REF][START_REF] Kraft | Community assembly, coexistence and the environmental filtering metaphor[END_REF]. The niche optimum represents the set of environmental conditions where the fitness of a species is highest, as reflected by growth rate, reproduction success, survival, population size or distribution range [START_REF] Sexton | Evolution of Ecological Niche Breadth[END_REF]. This parameter can be assessed by calculating the niche position, which can be defined as the average, or median value of an environmental variable where the species occurs, or sometimes as the marginality of this average value compared to the community mean [START_REF] Roughgarden | Niche width: biogeographic patterns among Anolis lizard populations[END_REF]. The niche position is generally used as a proxy for the niche optimum, since the "true" optimal conditions for a species is generally unknown (as its "true" niche breadth) or only estimated via habitat suitability models (Zuquim et al. 2019). Most studies examine species distributions across only a portion of their geographic and environmental ranges (Sheth et al. 2020), with sampling protocols that are rarely explicitly designed to cover an exhaustive representation of the habitat heterogeneity occurring within a study area, or to provide an equilibrated sampling effort across contrasted habitat conditions.

We can propose at least four hypothetical scenarios predicting the shape of niche breadth-position relationships along a gradient of soil nutrient availability (Fig. 1). The relationship between realized species niche breadth and niche position, as well as with their traits, can be illustrated using Gaussian-like curves for simplicity, as in the classic resource utilization model of McArthur (1958) (Fig. 1a), even though actual distributions may follow other forms (Le [START_REF] Bagousse-Pinguet | Testing the environmental filtering concept in global drylands[END_REF]. These curves can be translated into values describing the relationship of niche breadth plotted against niche position (Fig. 1b).

In the first scenario, species niche breadth varies randomly across species, regardless of their niche position along a gradient of soil resource availability. This pattern would arise if species were competitively equivalent on any level of that specific soil resource availability, i.e. if species edaphic distribution is only driven by stochastic and dispersal processes. In that sense, this scenario is consistent in its outcome with Hubbell's neutral theory (2001). In the second scenario, poor soil resources select for species investing in protection against physical and biological damages, to the detriment of growth, which would render these species increasingly less competitive when soil fertility increases. In this case, niche breadth should increase with niche position, and the strength (slope) of this relationship should reflect how much the cost of adaptation to nutrient-poor soils restricts the ability of conservative species to compete with more acquisitive species and establish in more fertile habitats. This scenario is consistent with previous studies showing that poor-soil specialists exhibit resource conservation strategies (e.g. durable tissues with slow turnover), whereas species preferring more fertile soils are characterized by resource acquisitive traits (e.g. cheap tissues with high turnover) [START_REF] Fine | The growth-defense trade-off and habitat specialization by plants in Amazonian forests[END_REF][START_REF] Pinho | Soilmediated filtering organizes tree assemblages in regenerating tropical forests[END_REF][START_REF] Poorter | Can traits predict individual growth performance? A test in a hyperdiverse tropical forest[END_REF]. Scenario 3 is similar to the second scenario, except that the soil nutrient is not limiting for any species beyond a certain threshold, above which the nutrient availability does not impact fitness anymore. Niche breadth therefore tends to reach a plateau. Such a pattern has rarely been emphasized but see [START_REF] Steidinger | Qualitative differences in tree species distributions along soil chemical gradients give clues to the mechanisms of specialization: why boron may be the most important soil nutrient at Barro Colorado Island[END_REF] for soil calcium concentration optimum in Panama, which stabilizes and shows a trend consistent with scenario 3. In the fourth scenario, the increase of potential niche breadth as soil resource availability becomes less limiting is counter-balanced by a greater "species packing", i.e. a constriction of species' realized niches (MacArthur 1969) resulting from stronger competition for resources. In this scenario, niche breadth increases with soil resource availability optima, up to a certain intermediate level of soil fertility, then decreases as a consequence of species packing, forming a bell-shaped curve.

To further shed light on the goodness-of-fit of each scenario to real species assemblages, we may also inquire whether niche breadth-position relationships show consistent patterns along decoupled environmental gradients, and whether the same functional trade-offs align along each gradient. Environmental axes may covary, or vary independently from each other, either because they are spatially structured at different spatial scales (e.g. climate vs microhabitat variables), or in the case of soil properties because they are influenced by different pedological or biogeochemical processes. For instance, some key soil nutrients like base cation (e.g. calcium, magnesium, potassium) are known to covary, as their concentrations depend on common chemical and geological conditions (e.g. soil acidity, nature of the bedrock). Other soil variables, notably anionic nutrients (e.g. PO4 3-, NO3 2-), may display decoupled spatial variations, as they undergo different chemical constraints (e.g. P immobilization) or different biogeochemical processes (e.g. N-fixation, nitrification) [START_REF] Hedin | The nitrogen paradox in tropical forest ecosystems[END_REF][START_REF] Vleminckx | Impact of fine-scale edaphic heterogeneity on tree species assembly in a central African rainforest[END_REF][START_REF] Quesada | Variations in chemical and physical properties of Amazon forest soils in relation to their genesis[END_REF]). Whether we observe similar niche breadth-position relationships along decoupled environmental dimensions, or whether niche breadth and niche position are influenced by the same resource use traits along those environmental dimensions, are key questions to improve our understanding of community assembly mechanisms. However, these questions remain poorly examined [START_REF] Futuyma | The evolution of ecological specialization[END_REF][START_REF] Sultan | Contrasting ecological breadth of co-occurring annual Polygonum species[END_REF][START_REF] Carscadden | Niche breadth: Causes and consequences for ecology, evolution, and conservation[END_REF].

The "world-wide plant economics spectrum hypothesis" [START_REF] Reich | The world-wide 'fast-slow' plant economics spectrum: a traits manifesto[END_REF] suggests that fastslow economics spectra would be consistently observed along decoupled soil fertility gradients, with resource conservation traits being selected on nutrient-depleted soils in general. Although some evidence has supported this hypothesis [START_REF] Poorter | Can traits predict individual growth performance? A test in a hyperdiverse tropical forest[END_REF], previous studies have also shown that tree communities display decoupled trait syndromes across leaf, stem and roots [START_REF] Baraloto | Decoupled leaf and stem economics in rain forest trees[END_REF][START_REF] Fortunel | Leaf, stem and root tissue strategies across 758 Neotropical tree species[END_REF][START_REF] Laughlin | The intrinsic dimensionality of plant traits and its relevance to community assembly[END_REF], Vleminckx et al. 2021[START_REF] Asefa | Above and belowground plant traits are not consistent in response to drought and competition treatments[END_REF]). These decoupled wood and leaf economic traits have been shown to respond to similar fertility gradients in tropical forests [START_REF] Fortunel | Environmental factors predict community functional composition in Amazonian forests[END_REF], Vleminckx et al. 2021). Yet, to date there has been no attempt to integrate niche breadth data to examine how individual nutrient availability gradients potentially determine species edaphic ranges, and whether decoupled traits align with the same fertility gradients.

Here, we address these questions using a unique dataset of 246 tree species inventoried in 101 plots located across Eastern (French Guiana) and Western (Peru) Amazonia, together with accurate measurements of 14 leaf, stem and root traits. We first examine whether species niche breadth and niche position, taken separately, are aligned or decoupled among five soil nutrient availability gradients (N, P, Ca, Mg and K). Second, we examine how well the four scenarios presented in Fig. 1 match the observed niche breadth-position relationship along each soil gradient. We address the following specific questions: nutrient gradients?

(2) How well do our four scenarios (Fig. 1) fit the niche breadth-position relationship?

(3) Are decoupled niche breadth and position dimensions associated with different plant functional strategies?

Methods

Study areas

We established a nested experimental design with replicated plots in habitats displaying contrasting soil conditions, characteristic of lowland Amazonian forests -white-sand (WS), Terra Firme (TF) and seasonally flooded forests (SF) [START_REF] Fortunel | Environmental factors predict community functional composition in Amazonian forests[END_REF], Baraloto et al. 2021) -at both regional (c.100 km) and basin-wide (2500 km) distances. A total of 101 0.1-ha plots were inventoried between 2008 and 2018 in ten subregions of tropical moist forest in French Guiana (hereafter FG; 63 plots) and between 2008 and 2011 in three subregions in Peru (38 plots) (Fig. 2). French Guiana forests stand on an old Precambrian tableland, with old, highly weathered and nutrient-depleted soils [START_REF] Gourlet-Fleury | Ecology and management of a neotropical rainforest: lessons drawn from Paracou, a long-term experimental research site in French Guiana[END_REF]). Mean annual rainfall across inventory subregions ranges between 2160 and 3130 mm (http://www.worldclim.com/) and is distributed seasonally throughout the year. The wet season stretches from December to July and is usually interrupted in February or March by a short dry period, while the dry season occurs from August to November with monthly rainfall never exceeding 100 mm. Mean temperature oscillates between 23.0 and 26.6°C with low seasonal variation [START_REF] Gourlet-Fleury | Ecology and management of a neotropical rainforest: lessons drawn from Paracou, a long-term experimental research site in French Guiana[END_REF]).

Elevation among subregions ranged from 42 to 529 m. Forests from the Western Amazon in Peru cover heterogeneous soil conditions consequent to the combined impact of marine incursions, the Andean uplift, and the weathering of volcanic sediments [START_REF] Hoorn | Amazonia through time: Andean uplift, climate change, landscape evolution, and biodiversity[END_REF].

Mean annual rainfall varies between 2405 and 2750 mm, whereas mean temperature ranges from 26.3°C to 26.7°C (http://www.worldclim.com/), and elevation from 95 to 173 m. The study areas are further detailed in [START_REF] Baraloto | Biogeographic history and habitat specialization shape floristic and phylogenetic composition across Amazonian forests[END_REF].

Tree species inventories

Trees were inventoried following a modified version of the Gentry plots proposed by [START_REF] Phillips | Efficient plot-based floristic assessment of tropical forests[END_REF] and described by [START_REF] Baraloto | Rapid simultaneous estimation of aboveground biomass and tree diversity across Neotropical forests: a comparison of field inventory methods[END_REF]. Each plot consisted of ten parallel 50 mlong transects departing perpendicularly from a main 180 m-long central line, successively in alternate directions every 20 m along the line (a schematic illustration of a plot is provided in Appendix S1: Figure S1). All stems with a circumference ≥ 8 cm at 1.3 m above the ground (2.5 cm DBH) were inventoried over a two-meter width along each transect. At least one individual of every putatively-distinct taxon encountered was collected in the field to create plot-level voucher collections. In rare cases (0.2% of all stems sampled), no identification was achieved nor could vouchers be collected due to lack of leaves or obstructed canopies. The plot level vouchers were meticulously sorted so that independent distinct taxa had at least one collection in each plot. Further sorting resulted in standardized project type collections for all distinct taxa which were identified at regional herbaria for the Peru (AMAZ) and French Guiana (CAY) collections. We then further standardized and resolved vouchers from both these collections during a five-month period at the herbarium of the Missouri Botanical Garden (MO), such that any unnamed, putative novel species was compared to other congeners from the other region [START_REF] Baraloto | Biogeographic history and habitat specialization shape floristic and phylogenetic composition across Amazonian forests[END_REF]. At the end, we provided a full detail of all project vouchers describing our standardized inventories (vouchers and/or photos are available for loan upon request). Species diversity was characterized in each subregion using species richness, as well as the effective number of species expected from 1000 random samplings of 2 individuals to weight for species abundance [START_REF] Dauby | Sampled-based estimation of diversity sensu stricto by transforming Hurlbert diversities into effective number of species[END_REF] (Table 1).

Soil data

We collected bulked soil cores at 0-15 cm depth at ten regularly spaced positions along the central line of the plot (Appendix S1: Figure S1). The ten cores were mixed into a 500 g sample that was dried to constant mass (at 25°C) and sieved (2 mm mesh). Samples from were shipped to the University of California, Davis DANR laboratory for physical and chemical analyses (see [START_REF] Baraloto | Disentangling stand and environmental correlates of aboveground biomass in Amazonian forests[END_REF] for full protocol details). The bioavailability of three base cations (Ca, Mg, K) and P, and the total soil nitrogen concentration (N) were then quantified for each soil sample, following a protocol described in details [START_REF] Baraloto | Disentangling stand and environmental correlates of aboveground biomass in Amazonian forests[END_REF]. We lack data on other soil variables like soil pH and soil Al, Mn and Fe concentration to evaluate the impact of soil acidity and toxicity on species niches. The mean and the standard deviation of each soil variable in each habitat and each study region (Peru and French Guiana, separately) is shown in Table 2.

The distribution of plot values for each soil variable within each edaphic habitat (SF, TF and WS), and a test of comparison (Wilcoxon-Mann-Withney) of these values across habitats for each soil variable are shown in supplementary information (Appendix S2: Figure S1). As a complementary information, we also show the projection of plots and soil variables in a Principal Component Analysis (PCA) (see details in Appendix S3: Figure S1).

Functional trait data

We used data for 14 chemical and morphological traits related to resource use and structural defense, comprising ten leaf, two stem and two fine root traits: Leaf thickness and toughness, SLA, Leaf C, N, P, Ca, Mg and K concentration, leaf 13 C, sapwood-specific gravity, trunk bark thickness, fine root tissue density and fine root specific root length (SRL). The unit and functional role of each trait, along with additional information on trait sampling locations are provided as online supplementary information [START_REF] Vleminckx | Niche breadth of Amazonian trees increases with niche optimum across broad edaphic gradients: Supplementary information provided through the Harvard Dataverse repository[END_REF]. These functional data were obtained from accurate trait measurements from Peruvian and French Guianan samples collected for 8345 individuals from 1625 species in 371 genera, 78 families and 26 orders covering the Rosidae, Asteridae and early eudicots [START_REF] Baraloto | Decoupled leaf and stem economics in rain forest trees[END_REF][START_REF] Fortunel | Leaf, stem and root tissue strategies across 758 Neotropical tree species[END_REF], Vleminckx et al. 2021). Missing trait data ranged from 34.96% for leaf thickness up to 74.17% for root SRL (see Table S2 in [START_REF] Vleminckx | Resolving whole-plant economics from leaf, stem and root traits of 1467 Amazonian tree species[END_REF]. Missing values were imputed using a Bayesian hierarchical matrix factorization method (BHMF), based on taxonomic information and co-variation among traits [START_REF] Fazayeli | Uncertainty quantified matrix completion using Bayesian hierarchical matrix factorization[END_REF]; see Vleminckx et al. 2021 for details). All these traits reflect species economics spectrum potentially associated to soil nutrient availability levels, or intrinsic water-use efficiency (Leaf 13 C) [START_REF] Baraloto | Decoupled leaf and stem economics in rain forest trees[END_REF].

Data analysis

Niche breadth and niche position data

Species abundance at the plot level was calculated after weighting each tree by the logarithm of its basal area, to take into account that later life stages are likely to be more representative of the influence of habitat conditions on species distributions, whereas the assembly rules of younger trees can be more stochastic [START_REF] Vleminckx | Impact of fine-scale edaphic heterogeneity on tree species assembly in a central African rainforest[END_REF]. We then calculated the niche breadth and the niche position of each of the 246 species that were present in at least three subregions (i.e., areas comprising plots), across each of the five soil nutrients (N, P, Ca, Mg and K). For each soil variable, the niche position of each species corresponded to the median of the soil variable calculated among plots where the species was found (weighting each plot according to the abundance of the species). The niche breadth was calculated as the interquartile range (25-75%) of values for the soil variable. The 25-75% range was chosen to provide robust niche breadth values that were weakly sensitive to outliers [START_REF] Steidinger | Qualitative differences in tree species distributions along soil chemical gradients give clues to the mechanisms of specialization: why boron may be the most important soil nutrient at Barro Colorado Island[END_REF]. Calculations using a 20-80% and a 15-85% range provided highly consistent results that did not modify our interpretations. Prior to any subsequent analysis, niche breadth and niche position values were normalized (using a Box-Cox transformation) and standardized (z-score transformation). We then detrended niche breadth values to remove any potential biased inflation of these values induced by the effects of: (i) the total abundance of each species across all plots, (ii) the number of subregions and (iii) plots in which each species is present, and (iv) their regional distribution (i.e. dummy variable columns indicating whether each species is present in one region, i.e. Western or Eastern Amazon, or both regions). This detrending was performed by using the residuals of a linear regression of niche breadth against these effects (see details in Appendix S4).

Niche breadth and niche position correlations among soil variables

To specifically address question 1, we performed a PCA on the species niche breadth values corresponding to the different soil nutrients, and the same PCA for species niche position values. We then tested whether the Pearson correlations of niche breadth and niche position among the five soil nutrients were statistically significant. Correlations were considered significant when they were lower or higher than the 2.5-97.5% quantiles of correlation values obtained after randomizing each nutrient concentration values at the plot level and recalculating niche breadth and niche position, while preserving the multi-scale spatial structure of each nutrient within each study region (Peru and French Guiana), independently. To do so, we used Moran Spectral Randomization (MSR, Wagner and Dray 2015), a procedure that allows considering multiscale spatial autocorrelation structures for any type of quantitative variable, based on spatially weighted connectivity information among sampling points (i.e. the 101 plots in our case). This information was obtained from an optimized procedure used to choose a spatial weighted matrix and select a subset of Moran's eigenvector maps (MEMs, [START_REF] Dray | Spatial modelling: a comprehensive framework for principal coordinate analysis of neighbour matrices (PCNM)[END_REF], following Bauman et al. (2018a,b), using the R package 'adespatial' [START_REF] Dray | adespatial: Multivariate Multiscale Spatial Analysis[END_REF].

MEMs are spatial eigenvectors that model multi-scale spatial structures in any type of numerical variable. We tested a minimum spanning tree configuration and a Gabriel's graph to model connectivity among plots, which have been shown appropriate to accurately modeling structures even when dealing with nested and irregular sampling designs such as ours (Bauman et al. 2018a). The spatial weighted connectivity information from the best MEM model (i.e., the eigenvector combination that best described the spatial structures in the soils nutrients' concentration, based on a forward selection with double stopping criterion) is then used in a spatially constrained randomization algorithm in the MSR method to reproduce variables that accurately mimic the observed spatial structures of the randomized variable(s).

Species in each PCA graph were also characterized by their affinity for each of the three habitats, by calculating and testing their indicator value (indval), following [START_REF] Dufrêne | Species assemblages and indicator species: the need for a flexible asymmetrical approach[END_REF]. This allowed combining quantitative soil information with qualitative visualization of three well-defined and contrasted habitats of the Amazon region (white-sand, terra firme and seasonally flooded).

Relationship between niche optimum, niche breadth and traits for each soil nutrient

To address question 2, we plotted the niche breadth of species against their niche position values, for each soil variable. The linear and non-linear relationships between niche breadth and niche position were fitted using Bayesian regression models. The posterior distributions of the slope coefficients of interest were summarized through the median and 95% posterior credibility interval. The linear and non-linear (quadratic) slope coefficient distributions were fitted (Bayesian updating) using a quadratic approximation (McElreath 2020). The shape of the niche breadth-position associations and the importance of the linear and quadratic coefficients were used to verify which scenario in Fig. 1 best fits the observed niche breadth-position relationship, for each soil nutrient. Coefficient values were considered as clearly positive or negative whenever at least 95% of their posterior mass probability was positive or negative (i.e., did not encompass zero). Scenarios 2 and 3 predict positive values for the linear coefficient and non-important values for scenarios 1 and 4. Scenarios 3 and 4 predict negative values for the quadratic coefficient, while the latter is expected to be non-important for scenarios 1 and 2.

To address question 3, we performed a variation partitioning to quantify, for each soil variable, the fraction (adjusted R²) of species niche breadth variation explained purely by their niche position and by their functional traits. We then tested the significance of each fraction by testing whether the observed fraction (adjusted R² values) was higher than 95% of null values obtained with the MSR method described above. If the observed adjusted R² value quantifying the effect of all traits combined was higher than 95 % of the 4999 adjusted R² values obtained with the MSR procedure, than we performed a forward selection to identify the traits that significantly explained niche breadth variation [START_REF] Blanchet | Forward selection of explanatory variables[END_REF].

Prior to the variation partitioning, we verified whether niche breadth values were influenced by phylogeny. Phylogeny was modelled using a matrix of dummy variables assigning "1" for each species (lines) in their corresponding genus and family (in columns), and "0" for non-matching taxa. The phylogenetic effect was then tested using a residuals permutation test [START_REF] Anderson | An empirical comparison of permutation methods for tests of partial regression coefficients in a linear model[END_REF], which showed no significant effect for any soil variable (Appendix S5: Table S1).

All analyses described in the methods were performed in the R statistical environment (R Development Core Team, 2022). We provide the soil, tree inventory and trait data, along with our R script in the online repository folder: https://doi.org/10.7910/DVN/VWAJYR. References for the R packages used are detailed in the R code.

Results

Correlation of niche breadths and positions among soil variables

The two PCAs performed on niche breadth and niche position values showed highly consistent patterns of variables' projection, revealing a strong relationship between these two niche parameters (Procrustes correlation = 0.587; P <= 0.001; MSR test; Fig. 3). There was a strong coordination of species niche breadth and position for soil cations (Ca, Mg and K) and to a lesser extent for N. Increasing niche breadth and position values for N, Ca, Mg and K aligned well with increasingly acquisitive functional traits such as higher leaf N concentration (Fig. 3). Soil P concentration showed a clear decoupling of niche breadth and position values compared to the other nutrients (Fig. 3). Species significantly indicative of seasonally flooded and terra firme habitats displayed significantly higher niche breadth and niche position, as well as higher leaf N and P concentration for soil N, Ca, Mg and K concentration, compared to whitesand specialists, (Appendix S6: Figure S1, and Appendix S7: Figure S1; for sample size details, see Appendix S8: Figure S1). The following analyses examine in more details the relationship between niche breadth, niche position and functional traits for each soil nutrient.

Functional strategies associated with niche breadth and position

Species niche breadth was positively associated with niche position for each of the five soil nutrients (Fig. 4). No clear negative quadratic term was detected for niche position, indicating that relationships were mostly linear and consistent with scenario 2 (Fig. 1). The niche breadth-position linear relationship was the strongest for soil Ca concentration (R² value = 45.1%), followed by soil N (40.2%), P (26.2%) and K (18.2%) concentration. The effect of functional traits on niche breadth nearly entirely co-varied with the effect of niche position. In other words, we did not observe any trait explaining species niche breadth alone. Niche breadth and position values were not significantly explained by the genus and family identity of species for any soil variable (R² < 1%; Appendix S5: Table S1).

Functional traits contributed to species niche breadth (P ≤ 0.05; MSR test) for soil N (R² = 3.7%) and Ca (12.4%) concentration, with high niche breadth values for these two soil nutrients being associated with more resource acquisitive strategies among species, in particular higher SLA, Leaf N and Ca concentrations, and higher fine root SRL (Fig. 4). The Pearson correlations between each individual trait and species niche breadth for soil N, Ca, Mg and P concentration are shown in supplementary material (Appendix S9: Figure S1). Species niche breadth for soil K concentration was not significantly explained by functional traits (Fig. 4).

Results obtained with soil Mg concentration were consistent with the ones obtained with soil Ca concentration (Appendix S10: Figure S1). Functional traits less clearly explained the niche breadth of soil P (R²=1.9%), although sapwood density was retained by the forward selection procedure, with species distributed on the most P-depleted soils showing denser wood than on less P-limiting conditions.

Discussion

Niche properties, characterized by species range (niche breadth) and optimum (niche position) along soil nutrient gradients, were coordinated among soil N, Ca, Mg and K, but not soil P (Fig. 3). The decoupling of species niches between soil P concentration and the other nutrients was associated with different functional strategies (Fig. 4). Our results suggest that species undergo increasing abiotic constraints that favor costly resource conservation strategies when soil fertility decreases. These abiotic constraints decrease with increasing soil fertility, allowing species exhibiting more resource acquisitive traits to occupy increasingly larger niches, in line with scenario 2 (Fig. 1).

Costly poor-soil adaptations limit species edaphic ranges

We found a strong positive and linear increase of species niche breadth with their niche position, for each soil nutrient (Fig. 3,4), in contrast with predictions from scenario 1. The quadratic term of the niche breadth-position relationship was never clearly different from zero and always positive, which invalidated scenarios 3 and 4 and provided support for scenario 2.

Although our sampling may not have captured the full edaphic distribution for every species, the gradients that we measured and the care with which we effected taxonomic determinations, represent a nearly complete picture for most of these species' distributions [START_REF] Quesada | Variations in chemical and physical properties of Amazon forest soils in relation to their genesis[END_REF], Baraloto et al. 2021), such that additional sampling would be unlikely to change the present results. It is also worth noting that the way we accounted for spatial distribution disparities among species in the analyses strongly limited the potential influences of spatial biases related to the statistical design [START_REF] Taylor | Aggregation, Variance and the Mean[END_REF].

Species distributed on the most N and Ca-depleted soils had lower leaf nutrient concentrations, in particular N and Ca, while also showing relatively low SLA (Fig. 4, Appendix S7: Figure S1), indicating resource conservation strategies [START_REF] Fortunel | Environmental factors predict community functional composition in Amazonian forests[END_REF].

These species also displayed relatively low niche breadth values, which may suggest that their resource conservation traits confine them to these poor soil conditions (generally white-sands), and exclude them from the more fertile terra firme and seasonally flooded soils.

The positive association between species niche breadth for soil Ca concentration and SRL may reflect the existence of a fast-slow trade-off associated with soil fertility conditions, with poor soils occupied by species investing in longer roots with lower tissue quality, possibly associated with higher uptake capacity in more competitive environments. Our results may suggest that soil Ca limitation has had more influence than the four other soil nutrients studied here on fine root evolutionary history and is consistent with previous manipulative studies in tropical Amazonian forests [START_REF] Wurzburger | Fine-root responses to fertilization reveal multiple nutrient limitation in a lowland tropical forest[END_REF]. Nevertheless, root traits were generally poor predictors of niche breadth, possibly because of the multiple alternatives that plants use for nutrient capture, including investments in mycorrhizal associations, that make possible a wide spectrum of trait syndromes in the same soil conditions [START_REF] Valverde-Barrantes | A worldview of root traits: the influence of ancestry, growth form, climate and mycorrhizal association on the functional trait variation of fine-root tissues in seed plants[END_REF]).

The niche breadth-position relationship was significantly positive but relatively weaker for soil K concentration (R² = 18.2%) than for soil Ca, N and P concentration (≥ 26.2%; Fig. 4). Yet, niche position and niche breadth for soil K concentration did not show any significant association with any functional trait, contrary to the three other soil nutrients. Thus, while our results suggest that K may indeed limit primary productivity, which is consistent with previous studies in lowland tropical forests [START_REF] Wright | Potassium, phosphorus, or nitrogen limit root allocation, tree growth, or litter production in a lowland tropical forest[END_REF][START_REF] Baribault | Tropical tree growth is correlated with soil phosphorus, potassium, and calcium, though not for legumes[END_REF][START_REF] Santiago | Tropical tree seedling growth responses to nitrogen, phosphorus and potassium addition[END_REF], they also nuance the idea that single functional traits reflect edaphic adaptations among tree species. The decoupling of fast-slow economic spectra reported among Amazonian tree communities [START_REF] Baraloto | Decoupled leaf and stem economics in rain forest trees[END_REF][START_REF] Fortunel | Leaf, stem and root tissue strategies across 758 Neotropical tree species[END_REF], Vleminckx et al. 2021) may partly introduce statistical noise when testing a signal between a single trait and a soil variable, and thus partly explains the weak predictive power of traits on species niche breadth.

The marked niche breadth-position relationship observed for soil P (R² = 26.2%) was highly decoupled from the other four soil nutrients (Fig. 3,4). This pattern was consistent with the orthogonality between soil P variation and the four other soil nutrients (Appendix S3: Figure S1). This orthogonality supports previous evidence that soil P availability often varies independently from cationic nutrients (Ca, Mg, K) or can even be higher on cation-poor sandy soils, due to the immobilization of P into Al oxyhydroxide complex forms in more fertile, clayey tropical soils [START_REF] Walker | The fate of phosphorus during pedogenesis[END_REF][START_REF] Vleminckx | Impact of fine-scale edaphic heterogeneity on tree species assembly in a central African rainforest[END_REF][START_REF] Turner | Pervasive phosphorus limitation of tree species but not communities in tropical forests[END_REF][START_REF] Cunha | Direct evidence for phosphorus limitation on Amazon forest productivity[END_REF]. In fact, P availability was even higher on white-sand forests than on the other edaphic habitats in Peru (Table 2), whereas the reverse pattern was observed in French Guiana. Yet, the overall niche breadth-position correlation remained strongly positive, even when considering the disparities of habitat differences for P availability across regions.

The decoupling of niche dimensions between soil P and the other four soil nutrients was associated with different functional dimensions. More specifically, species preferences for terra firme and seasonally flooded soils, which contained the highest soil N and cation concentrations, were mostly reflected by acquisitive traits in the leaves, whereas species whose optimum was on low P availability soils tended to have denser wood. The latter signal was weak but nevertheless significant (Fig. 4), and while further studies are needed to verify consistent patterns, it may partly explain the decoupling of traits that has previously been reported among leaf and woody aboveground organs when measured across broad edaphic gradients [START_REF] Baraloto | Decoupled leaf and stem economics in rain forest trees[END_REF][START_REF] Fortunel | Environmental factors predict community functional composition in Amazonian forests[END_REF], Vleminckx et al. 2021).

In parallel with using combinations of forward-selected traits in the variation partitioning, we also followed the approach of previous studies which examined the association between functional strategies and species niche parameters by using multivariate functional variables [START_REF] Kraft | Plant functional traits and the multidimensional nature of species coexistence[END_REF][START_REF] Muscarella | Do community-weighted mean functional traits reflect optimal strategies?[END_REF][START_REF] Pistón | Multidimensional ecological analyses demonstrate how interactions between functional traits shape fitness and life history strategies[END_REF]. This multivariate trait approach was generally less predictive than the forward-selected trait approach shown in Fig. 4 (for more details, see Appendix S11: Figure S1 and Figure S2).

The overall effect of functional traits on niche breadth variation co-varied with the effect of niche position (Fig. 4). This suggests that the resource use traits studied here mostly reflect species edaphic optima and not their range of resource use. It is also worth noting that intraspecific trait variation may have partly limited the detection of niche-trait association at the species level [START_REF] Zuleta | Interspecific and intraspecific variation of tree branch, leaf and stomatal traits in relation to topography in an aseasonal Amazon forest[END_REF]), but we lack enough trait measurements across habitats for each species to have more accurate insights.

Finally, the absence of genus or family-level signal on niche breadth and position (Appendix S5: Table S1) may suggest that various edaphic niches have evolved multiple times within many different genera and families, which is consistent with recent reports (Fine andBaraloto 2016, Baraloto et al. 2021).

Our results provide further support for the determinant role of soil properties in shaping tree species assembly in tropical forests [START_REF] Russo | Soil-related performance variation and distributions of tree species in a Bornean Rain Forest[END_REF][START_REF] Condit | Species distributions in response to individual soil nutrients and seasonal drought across a community of tropical trees[END_REF][START_REF] Vleminckx | The influence of spatially structured soil properties on tree community assemblages at a landscape scale in the tropical forests of southern Cameroon[END_REF][START_REF] Wright | Plant responses to nutrient addition experiments conducted in tropical forests[END_REF][START_REF] Umaña | Shifts in taxonomic and functional composition of trees along rainfall and phosphorus gradients in central Panama[END_REF], while they also provide indirect support to the hypothesis that the strength of abiotic filtering, here mediated by soil nutrient contents, determines the degree of species habitat specialization, i.e. to what extent species are confined to smaller niches because of their costly investments in resource conservation that would potentially make them less competitive in more fertile habitats. Definitive evidence of competitive exclusion would further require adding a temporal dimension to these analysesi.e. tree demography -, for instance relating tree growth or mortality responses to the interplay of soil, traits, and the functional similarity of the neighborhood [START_REF] Fortunel | Functional trait differences influence neighbourhood interactions in a hyperdiverse Amazonian forest[END_REF][START_REF] Muledi | Tree growth, recruitment, and survival in a tropical dry woodland: The importance of soil and functional identity of the neighbourhood[END_REF][START_REF] Rozendaal | Competition influences tree growth, but not mortality, across environmental gradients in Amazonia and tropical Africa[END_REF]. Such dynamics data unfortunately remain too scarce in the tropics for accurate characterization of demographic parameters for many species across the breadth of their distribution ranges, emphasizing the need for continued efforts towards establishing and monitoring long-term permanent sample plots in the tropics [START_REF] Blundo | Taking the pulse of Earth's tropical forests using networks of highly distributed plots[END_REF][START_REF] Davies | ForestGEO: Understanding forest diversity and dynamics through a global observatory network[END_REF].

Here, we did not investigate the possibility that the steep nutrient gradient occurring across habitat may overlap with a gradient of forest dynamics. Canopy disturbance and forest turnover rate are likely greater in the most fertile habitats [START_REF] Baraloto | Disentangling stand and environmental correlates of aboveground biomass in Amazonian forests[END_REF][START_REF] Baker | Fast demographic traits promote high diversification rates of Amazonian trees[END_REF], with more productive tree communities exhibiting more acquisitive traits (e.g., high SLA, low leaf thickness…) for soil nutrients and light [START_REF] Fortunel | Environmental factors predict community functional composition in Amazonian forests[END_REF][START_REF] Vleminckx | Past human disturbances and soil fertility both influence the distribution of light-demanding tree species in a Central African tropical forest[END_REF], 2021). A greater light extinction profile is also expected on fertile soils [START_REF] Russo | Covariation between understorey light environments and soil resources in Bornean mixed dipterocarp rain forest[END_REF], which may limit the competitiveness of fast-growing species in the understory, although this effect might be compensated by lower air evaporative demand and thermal constraints [START_REF] Vinod | Thermal sensitivity across forest vertical profiles: patterns, mechanisms, and ecological implications[END_REF] in the more shaded vegetation strata. Accurate gap dynamics history and light availability data will need to be better studied to further examine how light and soil nutrient gradients interact to influence niche parameters.

Implications regarding forest conservation and tree responses to climate change

Species adapted to poor soil conditions likely have large potential edaphic niches compared to their realized one, as they could in theory thrive on a much wider range of soil fertilities in the absence of faster-growing competitors, unlike species with higher niche fertility optimum whose realized and fundamental niches are expected to be more packed. The costly resource conservation traits displayed by poor-soil specialists are likely to exclude them from more fertile habitats, explaining the disparities between their realized and fundamental niches.

These adaptations might also allow these species to extend their tolerance to other environmental constraints such as water deficiency [START_REF] Baraloto | Decoupled leaf and stem economics in rain forest trees[END_REF], which occurs more frequently on highly drained white-sands than on terra firme or seasonally flooded soils. This would potentially render white-sand tree communities more resilient to more prolonged dry seasons and temperature increases predicted by climate models, predictions that are particularly threatening in the North-Eastern Amazon [START_REF] Fortunel | Environmental factors predict community functional composition in Amazonian forests[END_REF][START_REF] Guevara | Low phylogenetic beta diversity and geographic neo-endemism in Amazonian white-sand forests[END_REF][START_REF] Esquivel-Muelbert | Compositional response of Amazon forests to climate change[END_REF], IPCC 2022). These results could also pave the way for developing more evidence-based forest restoration management plans, for instance by improving the selection of tree species that would be able to establish in a wide range of environmental conditions. Further investigations of the interplay of species niche breadth, niche position and functional strategies for complementary key edaphic and climatic niche dimensions and across different tropical regions and spatial scales will be urgently needed to better predict how the current context of rapid environmental changes is likely to affect tropical forest species composition and associated ecosystem functions.

  postdoctoral fellow funded by a G. Evelyn Hutchinson Environmental Postdoctoral Fellowship from the Yale Institute for Biospheric Studies (Yale University, CT, USA). DB was funded by the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No. 895799. This work was supported by collaborative research grants funded by "Investissement d'Avenir" grants of the ANR (CEBA:ANR-10-LABX-25-01); by the National Science Foundation (NSF) grant DEB-0743103/0743800 to CB and PVAF; by ANR Blanc NEBEDIV (Projet ANR-13-BSV7-009) and an INRAE Package grant to CB; and by NSF DEB 1254214 to PVAF.

Figure. 1

 1 Figure.1 (a) Hypothetical scenarios describing species frequency distributions (realized niches) along a gradient of increasing soil nutrient availability, using Gaussian curves for simplicity. (b) Translation of these scenarios into niche breadth -niche positions graphs, showing species and predicted functional strategies with symbols.

Figure 2 .

 2 Figure 2. Geographical distribution of the 13 subregions in the Amazon (red rectangles), showing the position of the plots (yellow cross symbols) within the two study regions (Peru and French Guiana).

Figure 3 .

 3 Figure 3. Projection of species and soil variables on axes 1-2 of a principal component analysis (PCA) performed on niche breadth (a) and niche position (b) values. The grey rectangle that connects both PCA graphs shows the Procrustes correlation quantifying the matching of soil variables and species projections between the two PCAs (P ≤ 0.001; MSR test). The histograms show the relative eigenvalues of each PCA axis (only the first axis in each PCA expressed more variation than expected under a broken stick model). Symbols in the graphs indicate whether species are significantly indicative of one of the three habitats (seasonally flooded, terra firme, or white-sand specialist) or not (generalist). Tables at the bottom show the Pearson correlations of niche breadth (c) and niche position (d) values among soil variables. The significant correlations (t-test of Pearson's moment correlation) are indicated in blue (grey values were not significant).

Figure 4 .

 4 Figure 4. Niche breadth-niche position relationship among the 246 species, for each of four soil nutrients. Values indicated along x and y axes corresponded to back-transformed niche breadth and niche position values, respectively. Traits significantly explained niche breadth variation for N, Ca, and P. For these three nutrients, the Venn diagram on the right of the niche breadth-position graph shows the relative linear contribution (adjusted R² from a variation partitioning analysis) of niche position alone, traits alone, and the joint influence of niche

Figure. 1 Figure

 1 Figure.1

  Figure 3.

Figure 4 .

 4 Figure 4.

Table 1 .

 1 Summary of key descriptors of study regions, subregions and habitats. NrP = Number 790 of plots; AR = Altitudinal Range (in m); MAR = Mean Annual Rainfall (in mm); MAT = Mean

	791
	792	Annual Temperature (in °C). NrSp = mean number of species per plot; ENS2 = mean (calculated
	793	at the plot level) Effective Number of Species expected from 1000 random samplings (with
		replacement) of two individuals. The three last lines of each region represent the same
			NrP AR	MAR	MAT	NrSp	ENS2
		French Guiana	64	42-529	2157-3129	23.0-26.6	80.3 (3.6)	48.6 (5.2)
		Saül-Limonade	12	196-253 2421	24.6	66.1 (4.2)	24.4 (4.5)
		Trinité	6	126-320 2671	25.1	112.8 (11.7) 77.8 (14.0)
		Itoupé	3	521-529 2530	23.0	79.7 (6.9)	30.1 (7.0)
		Mitaraka	9	317-347 2157	24.9	70.8 (10.7) 66.1 (17.2)
		Laussat	10	49-57	2402	26.2	74.1 (3.7)	28.0 (4.0)
		Nouragues	8	108-345 3328	24.8	86.9 (14.0) 68.0 (20.5)
		Petite montagne Tortue	9	47-136	3729	25.4	95.0 (10.5) 66.3 (17.0)
		Centre Spatial Guyanais 4	43-63	2932	25.8	76.0 (9.2)	25.3 (5.1)
		Kaw	2	254-282 3720	24.5	96.0 (6.0)	73.9 (18.5)
		Suriname	2	196-229 2241	26.6	38.5 (3.5)	10.1 (6.3)
		Terra Firme	20	45-347	2775	25.2	95.5 (4.4)	70.8 (7.6)
		Seasonally Flooded	35	43-529	2723	24.9	64.7 (5.2)	24.5 (4.2)
		White Sand	10	39-345	2908	25.7	59.5 (5.6)	21.1 (4.7)
		Peru	38	95-173	2405-2750	26.3-26.7	101.4 (4.99) 61.2 (6.7)
		Morona	6	143-173 2405	26.7	108.2 (6.0) 89.4 (17.2)
		North Loreto	18	105-149 2750	26.3	101.6 (8.7) 59.9 (10.5)
		South Loreto	14	95-139	2499	26.8	98.3 (7.5)	50.7 (9.0)
		Terra Firme	11	95-158	2597	26.6	128.8 (5.6) 101.6 (9.6)
		Seasonally Flooded	13	106-156 2636	26.5	87.7 (6.1)	53.4 (9.2)
		White Sand	14	106-173 2625	26.6	86.7 (7.8)	29.8 (5.0)

Table 2 .

 2 Mean (± standard deviation) of each soil variable in each habitat (SF = Seasonally Flooded; TF = Terra Firme; WS = White-Sand) and each study region (French Guiana and Peru).

		French Guiana		Peru
	Habitat	SF	TF	WS	SF	TF	WS
	TN (%)	2.29 (3.25)	1.65 (1.35)	0.17 (0.22)	0.23 (0.09)	0.14 (0.05)	0.07 (0.06)
	Avail. P (mg/kg)	10.78 (15.51)	5.07 (5.81)	3.67 (4.11)	7.4 (5.75)	2.25 (1.54)	8.4 (8.01)
	Ca (mg/kg)	1.26 (2.37)	0.53 (1.02)	0.16 (0.17)	5.96 (7.23)	0.84 (2.58)	0.04 (0.03)
	Mg (mg/kg)	0.81 (0.92)	0.32 (0.31)	0.22 (0.24)	1.35 (1.45)	0.31 (0.6)	0.05 (0.04)
	K (mg/kg)	0.13 (0.11) 0.1 (0.04)	0.05 (0.05)	0.18 (0.07)	0.06 (0.02)	0.06 (0.03)

C.B. and P.V.A.F. were co-principal investigators for the projects that supported this research.

The collection and identification of tree species was coordinated by C.B and P.V.A.F., with help of J.E., P.P., N.D., M.R., E.V., I.M., J.G., C.F., E.A., T.P.

Conflict of Interest Statement

The authors declare no conflict of interest information for each habitat. Numbers in parenthesis correspond to the standard deviation of 795 the mean.