# Extending the growth rate hypothesis to species development: Can stoichiometric traits help to explain the composition of macroinvertebrate communities?

Miriam Beck, Cédric Mondy, Michael Danger, Elise Billoir, Philippe

Usseglio-polatera

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Miriam Beck, Cédric Mondy, Michael Danger, Elise Billoir, Philippe Usseglio-polatera. Extending the growth rate hypothesis to species development: Can stoichiometric traits help to explain the composition of macroinvertebrate communities?. Oikos, 2021, 130 (6), pp.879-892. 10.1111/oik.08090. hal-03451691

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Research

# Extending the growth rate hypothesis to species development: Can stoichiometric traits help to explain the composition of macroinvertebrate communities?

Miriam Beck, Cédric P. Mondy, Michael Danger, Elise Billoir and Philippe Usseglio-Polatera

M. Beck (https://orcid.org/0000-0001-8179-3820) ✉ (miriam.beck@univ-lorraine.fr), M. Danger, E. Billoir and P. Usseglio-Polatera, Univ. de Lorraine, CNRS, LIEC, Metz, France. MB, MD and PU-P also at: LTER-'Zone Atelier Moselle', Metz, France. – C. P. Mondy, Office Français de la Biodiversité, Direction Régionale d'Ile-de-France, Vincennes, France.

Oikos

130: 879-892, 2021

doi: 10.1111/oik.08090

Subject Editor: Shawn Wilder

Editor-in-Chief: Dries Bonte

Accepted 26 February 2021

Ecological stoichiometry seeks to understand the ecological consequences of elemental imbalances between consumers and their resources. Therein, the well-accepted growth rate hypothesis (GRH) states that organisms exhibiting rapid growth have higher phosphorus (P) demand – and thus lower C:P and N:P ratios – than slow growing ones, due to a higher allocation to P-rich rRNA. However, GRH has rarely been extended to other biological traits than growth, especially at the community level. In this study, we investigated whether macroinvertebrate stoichiometric traits (e.g. C:P and N:P ratios) can be linked to their development traits, and whether these stoichiometric traits are related to macroinvertebrate community assemblage under different nutrient conditions. We allocated more than 400 European taxa to different groups, defined using available information about three development-related traits: ‘life span’, ‘voltinism’ and ‘number of reproductive cycles per individual’. We sampled 18 invertebrate taxa in six streams exhibiting different levels of nutrient concentration and measured their stoichiometric traits. Further, we quantified invertebrate taxon abundances in these streams during an annual survey. Based on these data, we tested whether community composition regarding the developmental groups differs, depending on nutrient concentration. We found significant differences in the proportions of the developmental groups along a gradient of water N:P, in relation to their stoichiometric traits. Taxa with low C:P and N:P ratios were generally associated with faster development groups, and these taxa tended to occur at higher proportions in streams exhibiting low dissolved N:P ratios. In contrast, communities from P-poor, high dissolved N:P streams, were dominated by slowly developing taxa with high N:P ratios. Our results highlight that extending the GRH to species development rate might give some insights about the mechanisms by which nutrient concentrations in ecosystems influence consumers’ community composition.

Keywords: bottom-up control, community structure, ecological stoichiometry, functional traits, nutrient content

<figure><img src="image_3.png" /></figure>
Introduction

In the past decades, human activities, among which agricul-
ture, dramatically increased the nutrient load of streams and
terrestrial ecosystems compared to natural conditions (Smil
2000). The large anthropogenic inputs of phosphorus (P)
and nitrogen (N) have largely altered nutrient cycles and eco-
system functions (Falkowski et al. 2000, Elser et al. 2009),
and nutrient releasing processes such as fertilization and sew-
age discharge are going to continue in the future. However,
the input of both elements is imbalanced, altering also the
proportions of available nutrients (Peñuelas et al. 2013,
Yan et al. 2016).

Basal resources such as plants, algae or leaf litter are vari-
able in their elemental composition and directly display
nutrient availability in the environment (Cross et al. 2003,
Ventura et al. 2008, Farrell et al. 2018), thereby exhibit-
ing different stoichiometric quality as resources for consum-
ers. Changes in resource quantity, e.g. following nutrient
enrichment, often go along with changes in resource quality,
although the strength of their respective effects differs from
one context to another (Marcarelli et al. 2011, Sauvadet et al.
2016, Jochum et al. 2017). This can strongly impact con-
sumer' life history traits (Elser et al. 2001, Danger et al.
2013), alter consumer biomass (Greenwood et al. 2007,
Spivak et al. 2009) and lead to major changes in com-
munity structure over various trophic levels (Singer and
Battin 2007, Ott et al. 2012). Therefore it is not only
worth investigating community and ecosystem responses to
increasing nutrient levels, but also the effects towards their
changing ratio.

Ecological stoichiometry specifically investigates the bal-
ance of elements (mainly carbon, nitrogen, phosphorus) in
an ecological context, permitting to relate the natural avail-
ability of several nutrients to nutrient cycling and trophic
interactions (Sterner and Elser 2002, González et al. 2010).
This allows 1) understanding how organisms and their envi-
ronment interact via their elemental composition and 2)
answering ecological questions related to species dominance
in ecosystems (Schade et al. 2005), patterns of species inva-
sions (González et al. 2010) or species distribution along pol-
lution gradients (Dang et al. 2009). Within the ecological
stoichiometry framework, the growth rate hypothesis (GRH;
Elser et al. 1996) links stoichiometry to species life history
traits. This concept states that organism requirements for
phosphorus result, in a large part and in particular for inver-
tebrates, from varying demands for ribosomal RNA (rRNA)
(Elser et al. 1996, 2003). Ribosomal RNA plays a major role
in protein synthesis, which is essential for growth, i.e. the
increase in size or mass of an organism. High growth rates
involve large quantities of synthesized proteins thus requir-
ing a higher content of P-rich rRNA. This means that fast-
growing organisms will exhibit lower body C:P or N:P ratios
than slow-growing ones. This linkage between growth and
stoichiometry has been examined and confirmed for various
organisms, ranging from microbes to crustaceans (Elser et al.
2003, Acharya et al. 2004).

The question arises whether and how this relationship
affects assemblages of different taxa. Despite the recurrence
of laboratory tests carried out on individual species, there is
to date limited knowledge about the applicability of stoichio-
metric traits as predictors for consumer community com-
position (Moe et al. 2005, Van de Waal et al. 2018). Yet,
the use of stoichiometric traits could largely improve our
understanding of complex ecosystem dynamics (Leal et al.
2017, Meunier et al. 2017). Among the few studies dealing
with stoichiometric traits and community structures, Evans-
White et al. (2009) showed that higher nutrient loads influ-
enced stream macroinvertebrate diversity. Species richness
in some functional groups declined, following GRH. More
recently, Demi et al. (2019) demonstrated that experimental
instream manipulations of dissolved N:P ratios led to large
changes in invertebrate community structure. Predator and
shredder biomass increased under high-phosphorus condi-
tions, with small, short-lived taxa tending to be more posi-
tively affected than larger taxa. However, they did not show
any relationship between consumer body stoichiometry and
species replacements. This link towards body stoichiometry
was demonstrated by Singer and Battin (2007), who found
a community shifting towards P-rich and fast-growing taxa
after nutrient enrichment, and changes in community struc-
ture due to different responses of functional feeding groups.

In this context, to go further in the understanding of
the ecological consequences of stoichiometric relationships
within consumer communities and with the environment,
we investigated whether the link between organism stoichi-
ometry and growth rate as – proposed by GRH – can be
generalized to other functional traits, e.g. related to species
development. Functional traits can describe physiological,
morphological, behavioural or ecological features of organ-
isms such as life history, body form, mobility or ecological
tolerances (Usseglio-Polatera et al. 2000, Vieira et al. 2006).
Using species biological traits rather than taxonomy alone to
describe communities would provide a more functional view
on the investigated ecosystem, and could help to more deeply
understand the role of stoichiometric traits in community
structuration. In contrast to growth rate, which concerns
body size at individual-level, development can be seen as its
transformation towards maturity, affecting the growth and
structure of a whole population.

In this study, we aimed at investigating the relationships
between species biological traits – including stoichiometric
traits – and nutrient concentrations in ecosystems, focus-
ing on aquatic macroinvertebrate assemblages. This group
of organisms is widely used in water quality biomonitor-
ing. Large scale routine surveys have provided huge datas-
ets gathering information on their distribution, community
composition and some of their traits (Tachet et al. 2010,
Schmidt-Kloiber and Hering 2015, Sarremejane et al. 2020).
Based on the assumption that macroinvertebrate develop-
ment follows predictions of GRH originally addressing
growth rate, we specifically addressed the questions whether
1) the stoichiometry (N:P, C:P, C:N) of macroinvertebrates
can be linked to their development-related traits and 2) the
community composition regarding development characteristics can be related to changes in environmental nutrient concentrations. As development is closely linked to (body) growth in macroinvertebrates, the underlying mechanism is probably similar to that stated in GRH. Organisms with a fast development might also express high growth rates to quickly reach a body size that allows reproduction (i.e. body size at maturity), as shown for example for mayfly larvae (Back and King 2013). We thus hypothesize that, due to different demands for P-rich rRNA synthesis, macroinvertebrates with trait characteristics of fast development would exhibit low N:P and/or C:P ratios, whereas macroinvertebrates with trait characteristics of slow development would exhibit high N:P and/or C:P ratios. Therefore, macroinvertebrates with traits related to fast development would be favored in low N:P environments while high N:P conditions would select for slow developing taxa. This would lead to differences in community stoichiometry and composition in different nutrient availability conditions. We tested these hypotheses based on functional groups specifically defined in this study, using information on three development-related characteristics of macroinvertebrates – ‘life span’, ‘voltinism’ and ‘number of reproductive cycles per individual’ – and organisms sampled in six streams exhibiting contrasting levels of dissolved N:P concentrations. We thereby aim to consider the community as a whole, an approach that distinguishes our study from previous studies in this field which have generally looked at individual taxa when comparing communities.

# Material and methods

## Stoichiometric data

### Sampling

Six streams were sampled in the Vosges mountains (northeastern France). They display similar natural environmental conditions, such as belonging to the same stream category (TP4 = very small streams from the hydroecoregion ‘Vosges’ (Wasson et al. 2002, Chandesris et al. 2006)), presenting comparable land cover of catchment area dominated by forest as well as similar resource types (leaf litter, perilithon, FPOM, bryophytes, algae; with only algae and leaf litter appearing in minor quantities from one (low1) and two sites (medium2, high2), respectively) (Table 1, Supporting information). The study sites were selected to represent three site types, well discriminated based on water physico-chemical parameters (e.g. nutrients, oxygen, pH, cations; Supporting information). In particular, these three site types cover a gradient of dissolved nutrient level with either high, medium or low water N:P. We also verified that these three site types differed by their basal resource elemental quality, these resources matching well the availability of dissolved nutrients (Table 2, Supporting information).

The sampling of the most abundant macroinvertebrates for stoichiometric analyses was conducted in March 2011. The different types of substrates (defined in the French standard AFNOR XP T90-333 (2009), e.g. boulders/rocks, pebbles/

<table><caption>Table 1. Chemical, physical and geographical information of the study sites. For chemical variables, the mean over the whole sampling period is given in mg [–1 with values in parentheses indicating standard variation (13 visits between 03/2009 and 04/2010). Forest cover was evaluated within a riparian corridor of 50 m wide and 1 km long upstream from each site using forest cover data from the BD Forêt ver. 2 (2014) (IGN) and the hydrographic referential from the BD Topage (2020) (IGN, OFB and Sandre). Temperatures refer to the mean water temperature measured in the two coldest (January, February) and warmest (July, August) months using temperature loggers.</caption><thead><tr><th>Site</th><th>Lat N</th><th>Long E</th><th>Width (m)</th><th>Forest cover (%)</th><th>Temp min (°C)</th><th>Temp max (°C)</th><th>NO<sub>3</sub><sup>-</sup></th><th>PO<sub>4</sub><sup>-</sup></th><th>N:P</th><th>O<sub>2</sub></th></tr></thead><tbody><tr><td>low1</td><td>48°40'13"</td><td>7°08'34"</td><td>2.75</td><td>41.15</td><td>5.02 (± 1.24)</td><td>16.15 (± 1.18)</td><td>1.61 (± 0.40)</td><td>0.13 (± 0.04)</td><td>12.38 (± 0.39)</td><td>9.21 (± 1.43)</td></tr><tr><td>low2</td><td>48°30'15"</td><td>6°52'40"</td><td>2.50</td><td>72.60</td><td>4.71 (± 1.15)</td><td>16.63 (± 1.14)</td><td>1.21 (± 0.34)</td><td>0.19 (± 0.06)</td><td>6.37 (± 0.42)</td><td>6.99 (± 1.90)</td></tr><tr><td>medium1</td><td>48°30'33"</td><td>7°05'14"</td><td>6.30</td><td>75.56</td><td>3.89 (± 0.85)</td><td>14.19 (± 1.31)</td><td>0.81 (± 0.14)</td><td>0.02 (± 0.01)</td><td>40.50 (± 0.53)</td><td>10.46 (± 1.04)</td></tr><tr><td>medium2</td><td>48°29'27"</td><td>7°03'12"</td><td>3.35</td><td>100</td><td>5.03 (± 0.67)</td><td>11.56 (± 0.63)</td><td>0.70 (± 0.03)</td><td>0.02 (± 0.00)</td><td>35.00 (± 0.004)</td><td>10.63 (± 0.68)</td></tr><tr><td>high1</td><td>48°26'59"</td><td>7°03'41"</td><td>2.60</td><td>100</td><td>2.71 (± 0.96)</td><td>13.75 (± 1.35)</td><td>0.81 (± 0.15)</td><td>&lt; 0.01</td><td>&gt; 81.00</td><td>10.77 (± 1.23)</td></tr><tr><td>high2</td><td>48°24'48"</td><td>6°55'23"</td><td>6.60</td><td>100</td><td>5.10 (± 0.87)</td><td>12.94 (± 1.07)</td><td>0.48 (± 0.05)</td><td>0.01 (± 0.00)</td><td>48.00 (± 0.14)</td><td>11.19 (± 0.84)</td></tr></tbody></table>
<table><caption>Table 2. Stoichiometry (N:P, C:P, C:N) of resources (bryophytes, FPOM, litter, perilithon) at the three different site types with either low, medium or high water N:P (n indicates sample size). Values correspond to the mean of the molar ratios, values in parentheses indicate the range of raw data. For each resource, letters indicate significant differences in stoichiometry between site types (Kruskal-Wallis Anova followed by Dunn's rank-sum test with Bonferroni correction with α=0.05). The resources were sampled during the sampling of macroinvertebrates for stoichiometric analysis.</caption><thead><tr><th>Resource</th><th>Water N:P (n)</th><th>N:P</th><th>C:P</th><th>C:N</th></tr></thead><tbody><tr><td rowspan="3">Bryophytes</td><td>low (3)</td><td>11.83 (10.38-12.62)</td><td>139.59 (121.77-149.66)<sup>a</sup></td><td>11.80 (11.73-11.86)<sup>a</sup></td></tr><tr><td>medium (6)</td><td>14.78 (12.32-17.48)</td><td>297.84 (236.30-364.07)<sup>b</sup></td><td>20.06 (17.81-21.74)<sup>a</sup></td></tr><tr><td>high (6)</td><td>25.21 (7.07-45.60)</td><td>930.90 (177.43-1774.24)<sup>ab</sup></td><td>32.58 (23.63-39.11)<sup>b</sup></td></tr><tr><td rowspan="3">FPOM</td><td>low (6)</td><td>7.30 (2.01-12.16)</td><td>91.48 (30.33-143.76)<sup>a</sup></td><td>13.47 (11.73-15.20)<sup>a</sup></td></tr><tr><td>medium (6)</td><td>13.35 (10.99-15.81)</td><td>299.81 (275.93-345.77)<sup>b</sup></td><td>22.77 (19.75-26.71)<sup>b</sup></td></tr><tr><td>high (6)</td><td>12.77 (7.30-18.51)</td><td>318.81 (201.16-464.48)<sup>b</sup></td><td>25.35 (23.67-27.54)<sup>b</sup></td></tr><tr><td rowspan="3">Litter</td><td>low (3)</td><td>12.95 (12.66-13.11)<sup>a</sup></td><td>337.48 (302.25-368.08)<sup>a</sup></td><td>26.07 (23.10-28.08)<sup>a</sup></td></tr><tr><td>medium (6)</td><td>26.04 (22.02-32.46)<sup>ab</sup></td><td>1016.31 (816.98-1244.65)<sup>ab</sup></td><td>39.12 (33.78-48.10)<sup>ab</sup></td></tr><tr><td>high (6)</td><td>57.58 (26.63-91.68)<sup>b</sup></td><td>2578.93 (1199.17-4303.98)<sup>b</sup></td><td>44.74 (40.20-47.43)<sup>b</sup></td></tr><tr><td rowspan="3">Perilithon</td><td>low (3)</td><td>7.77 (7.27-8.26)<sup>a</sup></td><td>55.31 (52.55-58.16)<sup>a</sup></td><td>7.12 (7.04-7.23)<sup>a</sup></td></tr><tr><td>medium (6)</td><td>16.26 (14.91-17.99)<sup>b</sup></td><td>190.19 (141.18-241.55)<sup>ab</sup></td><td>11.8 (8.83-14.63)<sup>ab</sup></td></tr><tr><td>high (6)</td><td>24.90 (13.44-37.94)<sup>ab</sup></td><td>352.47 (178.72-544.84)<sup>b</sup></td><td>13.90 (13.29-14.81)<sup>b</sup></td></tr></tbody></table>

cobbles, gravel, sand, organic litter, bryophytes, (other) submerged macrophytes, etc.) present on a given site were sampled in proportion to their individual benthic coverages. Individuals were gathered until a sufficient biomass of each identified taxon was reached for stoichiometric trait analyses (minimum of ~1 mg dry mass per taxon and per site). The organisms were collected with a Surber net (1/20 m², 500 µm mesh size) and directly identified to genus level or the highest level possible under a microscope using identification keys of Tachet et al. (2010). In the field, larger organisms (~1 cm and above) were dissected to remove the gut in order to avoid a possible impact of gut content on stoichiometry measurement. All organisms were stored in a freezer at -20°C until further analysis.

## Elemental analysis

Invertebrate individuals were oven-dried (48 h at 65°C) and grinded. Carbon and nitrogen were measured from samples (~1 mg) using an elemental combustion analyzer.

Organic phosphorus was measured by oxidizing the samples with sodium persulfate under alkaline conditions. The samples (~1 mg) were suspended in 4 ml Milli-Q water and then 1 ml sodium hydroxide (NaOH 1 M) and 2.38 ml sodium persulfate (Na₂S₂O₈ 125 g l⁻¹) were added to the sample suspension. Each solution was adjusted to 10 ml with Milli-Q water before put in heat chamber at 120°C for two h to accelerate the process of phosphorus mineralization. After cooling, 2 ml of reagent solution (H₂SO₄: 15% v/v; K(SbO)₄H₄O₆, 0.5 H₂O: 2.8 g l⁻¹; (NH₄)₆Mo₇O₂₄, 4 H₂O: 40 g l⁻¹) and 0.5 ml of ascorbic acid (20 g l⁻¹) were added to each sample vial. After 30 min, 2 ml of each solution were used to measure absorbance at 880 nm by spectrophotometry. The phosphorus concentration was calculated by comparing absorbances of samples to those of standard solutions.

## Faunal community survey

The sites at which macroinvertebrates were collected for stoichiometric measurements, were additionally visited every

four weeks from March 2009 to April 2010 (thirteen campaigns) to quantify abundances. At each site, coarse gravel, as the common dominant habitat at the six streams, was sampled three times per site and per campaign. Samples were taken with a Surber net (1/20 m², 500 µm mesh size) and directly fixed with 3% formaldehyde.

Invertebrates were identified at the genus level [except for Oligochaeta, some Diptera (mainly family level), trichopteran Limnephilidae, coleopteran Dytiscidae and Hydrophilidae (sub-family level)] and counted.

During each sampling campaign a water sample (1 l) was taken to analyze water chemistry. The sample bottle was stored at 5°C until analysis within the next few (< 6) days. Water was filtered (Whatmann GF/C in case of N measurement; filter paper of pore size 0.25 µm in case of P measurement) before nitrate concentration was determined via ionic chromatography and phosphate was measured using molecular absorption spectrophotometry.

## Data analysis

### Groups based on developmental traits

We used biological traits as descriptors of specific aspects of the biology and life history of species. Macroinvertebrate trait profiles were described using a fuzzy coding approach, where each trait is described by several trait categories and the affinity of taxa for each category is coded based on numerical scores from 0 (= 'no affinity for the corresponding category') to 3 (= 'high affinity') (Chevenet et al. 1994).

For characterizing macroinvertebrate development, the biological traits 'life span' (with the trait categories: 'one year or less', 'more than one year'), 'voltinism' ('less than one generation per year', 'one generation per year', 'more than one generation per year') and 'number of reproductive cycles per individual' ('one', 'two', 'three to six', 'more than six') were used to gather macroinvertebrate taxa in development trait-based homogeneous groups. A fuzzy correspondence analysis (= FCA, Chevenet et al. 1994) was applied to the profiles of 447 taxa for which information for these traits was available (mainly from Juget and Lafont 1994, Richoux 1994, Tachet et al. 1994, 2010, Usseglio-Polatera
<figure><img src="image_4.png" /><figcaption>Figure 1. Trait profiles of the seven groups with their affinity for each category of the traits ‘life span’, ‘voltinism’ and ‘number of reproductive cycles per individual’. Violin plots represent the symmetric density of the trait affinity distribution. Black dots represent the median affinity of the group for each trait category.</figcaption></figure>

1994, Usseglio-Polatera and Tachet 1994; further information in the Supporting information). A hierarchical cluster analysis (applying the minimum variance criterion (Ward 1963) based on a matrix of Euclidean distances) was then performed using the first three axes of the FCA (explaining 70% of the total trait variability among taxa) to aggregate taxa in groups with similar suites of traits. The final number of groups was determined according to the shape of the dendrogram, by selecting a partitioning level (i.e. a given distance value) corresponding to the best compromise between 1) the number of groups and 2) the homogeneity of group size (i.e. maximizing evenness of taxa among groups). The definition of these groups of taxa was supported by their trait profiles (Fig. 1).

## Stoichiometric traits

After measuring the molar concentrations of carbon (C), nitrogen (N) and phosphorus (P), the organisms' nutrient molar ratios C:N, C:P and N:P were calculated. After

assigning the organisms to their corresponding trait-based group the mean nutrient ratio of each group was calculated. Mean group nutrient ratios were statistically compared for identifying between-groups differences.

Community ratios were calculated as the mean of stoichiometric values of all the individuals found at a site type, independently of their trait-based group. We tested for an effect of water N:P on community stoichiometry by comparing ratios of all the invertebrates sampled at the different site types. This analysis was performed considering either both inter-taxa and intra-taxon ratio variations (raw elemental ratios) or only the intra-taxon ratio variation. To analyze intra-taxon variation only, we standardized the elemental ratios using a z-transformation: $(obs_{i,s} - mu_s)/sd_s$ where obs$_{i,s}$ is the observed elemental ratio for taxon ‘i’ at site ‘s’ whereas mu$_s$ and sd$_s$ represent the mean and the standard deviation of the elemental ratio for taxon ‘i’ among all the sites, respectively. Note that since the stoichiometric measurements only covered the most abundant taxa at the sites without further
quantification, the calculated community ratios represent only this subset of the whole community. Nevertheless, since collected organisms were among the dominant ones in terms of biomass, our analyses should be quite representative of the whole community.

A non-parametric approach (i.e. Kruskal-Wallis tests followed by Dunn's rank-sum tests with Bonferroni correction) was applied for comparing stoichiometry between the trait-based groups as well as community stoichiometry between site types, as graphical examination of residual plots and tests (Shapiro test, Levene test) revealed non-normality of data and/or heterogeneity of variances.

## Community composition

Community composition regarding developmental groups was assessed in two ways: 1) based on taxon richness and 2) based on taxon abundance, both using data from the one-year community survey performed between March 2009 and April 2010. The approaches are complementary, since the first approach permits to test the impact of water N:P on the proportion of the taxa that belong to each developmental group, while the second one permits to evaluate the impact of water N:P on the proportion of macroinvertebrate individuals that belong to the different groups.

The number of taxa within each trait-based group during each sampling event was assessed, separately for the different site types. Likewise, the number of individuals within each trait-based group was calculated for each sampling event and site type. To test whether taxon richness and abundance of the developmental groups differ between site types, Friedman tests were applied for each developmental group, followed by paired Wilcoxon rank tests in case of significance. The use of blocks in the design of Friedman test allows controlling for additional variation among the seasons.

All the statistical analyses were done using R (<www.r-project.org>).

# Results

## Trait-based groups of macroinvertebrates

Using information about three biological traits related to species development: 'life span', 'voltinism' and 'number of reproductive cycles per individual', from a database covering 447 European taxa, it was possible to define seven groups of taxa with contrasted trait profiles (Fig. 1, Supporting information). The clustering resulted in six groups, one of which was further subdivided into two sub-groups ($I_3$ and F), to achieve a more balanced number of taxa in each group. This additional splitting followed that of the clustering process and was supported by differences in trait profiles. The final classification explained 73.47% of the trait variation among taxa (between-group Monte Carlo permutation test with $n=9999$ permutations; $p=10^{-4}$) and the number of taxa within each group varied between 40 and 142 (Table 3).

The groups vary in their affinity for the different trait categories with taxa of groups S and F clearly expressing either

<table><caption>Table 3. Composition of the trait-based groups regarding the number of taxa (genus level or highest level of identification) and their taxonomic homogeneity (Shannon diversity index H'). H' for each group was calculated, using the relative number of taxa per taxonomic group (order for insects, class for other branches).</caption><thead><tr><td>Group</td><td>Number of taxa</td><td>Taxonomic homogeneity</td></tr></thead><tbody><tr><td>F</td><td>52</td><td>2.3442</td></tr><tr><td>$I_1$</td><td>53</td><td>1.9766</td></tr><tr><td>$I_2$</td><td>40</td><td>2.2670</td></tr><tr><td>$I_3$</td><td>142</td><td>2.8560</td></tr><tr><td>$I_4$</td><td>49</td><td>1.6256</td></tr><tr><td>$I_5$</td><td>64</td><td>2.9331</td></tr><tr><td>S</td><td>47</td><td>2.1037</td></tr></tbody></table>

slow or fast development (Fig. 1). Most of the taxa of group S, e.g. including the genus *Cordulegaster* (Odonata), tend to live longer than one year, although some of them have also some affinity for a shorter life span. Further, these taxa are characterized by having just one reproductive cycle per individual and producing less than one generation per year. In contrast, taxa from group F live less than one year and produce one or more than one generation per year. This group includes among others the insect genera *Baetis* (Ephemeroptera) and *Hydropsyche* (Trichoptera). Regarding the number of potential reproductive cycles per individual, they show a similar profile as group S. Profiles of the five other groups expressed characteristics of both modes and thus show intermediate development rate. Labelling among these groups was based on decreasing voltinism (but this could have been based on one of the other traits). Taxa in group $I_1$, such as the crustaceans *Asellus* and *Gammarus* and group $I_2$ (e.g. Hydrozoa and Oligochaeta) tend to live longer than one year while producing more than one generation per year. Individuals tend to go through two to six (group $I_1$) or more than six (group $I_2$) reproductive cycles. Group $I_3$ contains taxa with short life duration (less than one year) and only one reproductive cycle per individual. Representatives of this group are *Brachyptera*, *Protonemura* (Plecoptera) and *Plectrocnemia* (Trichoptera). The majority of taxa in groups $I_4$ and $I_5$ tend to live longer than one year by producing mainly one generation per year. While almost all taxa in group $I_5$ (e.g. *Rhyacophila* and *Sericostoma* (Trichoptera)) are supposed to express only one reproductive cycle per individual, taxa in group $I_4$ (e.g. *Limnius* (Coleoptera) and *Erpobdellidae* (Hirudinea)) are able to have two reproductive cycles during their life.

## Macroinvertebrate elemental ratios among groups

The taxa collected for stoichiometric analyses belonged to groups $I_3$ (6 taxa), $I_5$ (4), S (4), $I_1$ (2) and F (2). Taxa belonging to groups $I_2$ and $I_4$ were not found during this sampling event (Supporting information).

There was a trend of increasing N:P ratio from group $I_1$ to groups F, $I_3$, $I_5$ and S, with group $I_1$ having a significantly lower N:P ratio value than groups $I_3$, $I_5$ and S (Fig. 2, Kruskal-Wallis test with $p < 0.05$ followed by Dunn's rank-sum test with $p < 0.05$ for groups $I_1/I_3$, $I_1/I_5$, $I_1/S$). The C:P ratio tended also to increase in this order, with group $I_1$
<figure><img src="image_5.png" /><figcaption>Figure 2. Differences in macroinvertebrate stoichiometry (N:P, C:P, C:N) among developmental groups. For each ratio and each group, the thick horizontal line represents the median, the boxes range from the 25th to the 75th percentiles and the whiskers extend to 1.5 times the inter-quartile range with black dots representing outliers. Different letters indicate significant differences using Dunn's rank-sum test with Bonferroni correction following a significant Kruskal–Wallis test with significance threshold set to α=0.05. Groups are ordered along the x-axis according to decreasing development rate, n indicates the number of individuals analyzed within each developmental group.</figcaption></figure>

having the lowest ratio value which was significantly different from those of groups F, I₅ and S. The C:N ratio was highest in group F and it differed significantly from those of groups I₃ and S. The lowest C:N ratio found in group I₃ differed significantly from those of groups I₅ and F.

## Macroinvertebrate stoichiometry along gradient of water N:P

Macroinvertebrate stoichiometry at the community level changed along a gradient of water N:P.

Community N:P ratio increased with increasing water N:P. When considering inter-taxa differences, i.e. changes in community composition, macroinvertebrate N:P ratios at high water N:P sites were significantly higher than at medium and low water N:P sites (Fig. 3 top panel, p < 0.05 in Kruskal–Wallis test with following Dunn's rank-sum test with p < 0.05 for high/medium and high/low N:P ratio). Within each taxon the elemental ratios did not differ between site types, but tended to decrease with lower water N:P (Fig. 3 bottom panel, Kruskal–Wallis test with p > 0.05 for each ratio).

The C:N ratios of communities showed the opposite, but not significant, trend and tended to decrease with increasing water N:P. Community C:P ratio did not differ significantly between the three water N:P conditions. For both C:P and C:N ratios the differences were not significant, but the trend was the same in scenarios including intra-taxon and/or inter-taxa variation.

## Community composition based on trait-based groups

During the annual faunal survey, taxa from all seven trait-based groups were found. The composition of macroinvertebrate communities differed between sites with different water N:P conditions in terms of these developmental groups.

Taxa richness of all seven groups differed significantly between sites with different water N:P ratios (Fig. 4, individual Friedman test with p < 0.05 for each group). In all groups, taxa richness was the highest at sites with medium water N:P and on average 1.7–14.3 taxa were found in each group during the sampling events over the year. This difference was significant compared to either both other site types (groups I₃, I₅ and F) or only low (group S) or high water N:P sites (groups I₁, I₂ and I₃) (Wilcoxon rank tests with p < 0.05 for pair-wise comparisons between medium/low and medium/high sites for groups I₃, I₅ and F, medium/low for group S and medium/high for groups I₁, I₂ and I₃). While in groups F, I₁, I₂ and I₄ taxa richness was significantly higher at low water N:P sites than at high water N:P sites, the number of taxa in groups I₃ and S showed the inverse pattern between these site types (Wilcoxon rank tests with p < 0.05 for high/low). Taxa richness of group I₅ was also higher in high water N:P sites than in low ones, but this difference was not significant.

Also the abundances of developmental groups differed between site types, except for group I₄ (Fig. 4e, Friedman test with p < 0.05). The abundance of individuals decreased in groups F, I₁ and I₂ with increasing water N:P and differed significantly between all site types for groups F and I₂ (Wilcoxon rank tests with p < 0.05 for medium/low, medium/high and high/low sites for groups F and I₂, medium/high and high/low for group I₁). For example in group F on average 1465.3 individuals were found at low water N:P sites compared to 247.8 individuals at high water N:P sites, abundances in group I₁ decreased from 371.8 at low water N:P sites to only two individuals at high water N:P sites. Abundances of group S increased along this gradient. At low water N:P sites only one individual of this group was found during the whole sampling period, which was significantly less compared to medium and high water N:P sites (30.5 and 60.8, respectively). Groups I₃,
<figure><img src="image_6.png" /><figcaption>Figure 3. Changes in macroinvertebrate stoichiometry among groups of sites with increasing N:P ratios. Top panel graphs consider intra- and inter-specific variation, while bottom panel shows only intra-specific variation. Inter-specific variation was suppressed by standardization of elemental ratios using z-transformation. For each macroinvertebrate ratio (N:P, C:P, C:N) and each group of sites (low, medium, high water N:P), the thick horizontal line represents the median, the boxes range from the 25th to the 75th percentiles and the whiskers cover 95% of the values. Different letters indicate significant differences (α=0.05) based on the multiple comparison Dunn's rank-sum test with Bonferroni correction following a Kruskal-Wallis rank-sum test. Sample size was n=23/51/29 for low/medium/high water N:P sites.</figcaption></figure>

I₄ and I₅ had the highest abundances at sites with medium water N:P (956.8, 272.1 and 211.1, respectively). In groups I₃ and I₄ the number of individuals was significantly higher at high water N:P sites compared to low water N:P sites (which also differed significantly), while in group I₄ it was slightly higher at low water N:P sites, although this difference was not significant. A list of all the taxa found during the annual sampling campaigns and their corresponding development group can be found in the Supporting information.

## Discussion

In this study, we were able to show that macroinvertebrate groups with contrasted developmental traits differ in their stoichiometry and their relative frequency in communities

under different stream nutrient regimes, both in terms of number of individuals and taxa. These results suggest the potential interest of incorporating stoichiometric traits into trait-based approaches of community ecology.

## Links between organism development rates and body stoichiometry

For two trait-based groups, the trend of the relationship between developmental traits and stoichiometry was in accordance with our first hypothesis, i.e. taxa with fast development exhibit lower N:P and C:P ratios than slow development taxa. Taxa from both groups S and F mostly have only one reproductive cycle per individual, but taxa from group F displayed characteristics of fast development such as a short life span with more than one generation per year, whereas
<figure><img src="image_7.png" /><figcaption>Figure 4. Community composition regarding taxonomic richness (upper panel) and abundances (lower panel) of the developmental groups among sites with different water N:P ratio levels (low, medium and high). For each group, bar height shows mean number of taxa or mean number of individuals per 0.15 m² of each group over the different sampling events during the one-year survey with error bars indicating the variation between sampling events as standard deviation and n indicating the range of the numbers of sampling events for each group.</figcaption></figure>

taxa from group S exhibited a slow development, indicated by traits such as a longer life span with less than one generation per year. We showed that differences in C:N, C:P and N:P stoichiometry exist between these two groups, although only significant for C:N, (Fig. 2), at least for species and populations collected at our sites. Having a high content of phosphorus (low N:P and C:P) thus not only allows fast growth as predicted by GRH (Elser et al. 1996), but also seems to favor a fast development of species. The opposite trend in C:N compared to C:P ratio underlines different requirements and suggests a tradeoff between nitrogen and phosphorus acquisition: Taxa with a high demand for phosphorus (often related to low body C:P) probably require less nitrogen and thus express higher body C:N ratios. In contrast, slow-developing taxa with a lower demand for phosphorus are richer in nitrogen, probably displaying higher requirements

for N-rich molecules such as proteins (Elser et al. 1996). This could be the case due to a greater investment in somatic development, for example in muscle tissue for predators such as the long-lived larvae of *Cordulegaster*. Considering that all the taxa in group S that were analyzed for stoichiometry may be viewed as predators, this might have also led to the significantly lower C:N ratio compared to group F containing herbivorous and omnivorous species. Predators generally show higher N-content than primary consumers (Fagan et al. 2002, Evans-White et al. 2005).

Using the three selected traits, it was not possible to define a clear gradient of potential development rate for the other groups. Groups I₁, I₃ and I₅ had intermediate trait profiles, exhibiting a variable combination of characteristics of both fast and slow development, according to their position between the two extreme groups. This corresponds to smaller
(non-significant) differences in stoichiometry between those
groups, compared to the two extreme groups. N:P ratio of
groups I₃ and I₅ was located between the values of fast- and
slow-developing groups, suggesting a link to their devel-
opmental traits. A further analysis on an extended dataset,
including more taxa, could help to clarify this link.

Group I₁ was the only group containing crustaceans and
only consisted of the crustaceans *Gammarus* sp. and *Asellus*
sp. in our stoichiometric dataset. In addition, when using
data sets of the annual survey, crustaceans clearly dominated
the individuals belonging to group I₁. This may explain its
significantly higher phosphorus content compared to the
three other groups (groups I₃, I₅, S), for which only insects
were sampled and analyzed. This is in accordance with the
findings of Evans-White et al. (2005), who found that crus-
taceans had on average lower C:P and N:P stoichiometry and
that such phylogenetic differences might explain large dif-
ferences with other groups mainly composed of insects and
mollusks. The authors assigned this phylogenetic difference
to a generally higher content of rRNA of crustaceans and/or
complexes of phosphorus and calcium found in their cara-
pace as suggested by Vrede et al. (1999). In contrast, insects
generally have higher N:P ratios, due to their high protein
contents but also their chitinous cuticle (Elser et al. 1996).
Furthermore, crustaceans generally exhibit clear differences
in life history to most of the insects considered in this study.
They are fully aquatic and mature by growing and moulting
while juveniles of most of amphibiotic insects emerge into
terrestrial adults after metamorphosis with major morpho-
logical changes. This may lead to varying demands for phos-
phorus in new morphological structures in amphibiotic taxa
even during their aquatic instars, compared to fully aquatic
taxa. Mayflies for example were found to vary in stoichiom-
etry with life stage with later development instars of females
(nearing emergence) allocating higher amounts of P into
reproductive tissues (Back et al. 2008). Other aquatic and
terrestrial insects have shown decreasing P content during
ontogeny (Elser et al. 2006, Back and King 2013), which is
probably due to different life history characteristics of adults.
Also crustaceans may face a decreasing ontogenic demand
for phosphorus during their development (Main et al. 1997,
Villar-Argaiz et al. 2002), which might simply be the result of
decreasing growth rate at older age. Therefore, although simi-
lar patterns occur during development, general differences
in the speed or degree in which the stoichiometry changes,
might exist between organisms with fully aquatic or amphibi-
otic life cycle. In our stoichiometric analysis, no fully aquatic
insect was present, but it might be important to consider this
difference in future studies.

Response of community stoichiometry along a
gradient of stream N:P ratio

We expected that stoichiometry on community level follows
the gradient in water N:P and basal resource N:P. Changing
nutrient concentrations in the environment has gener-
ally been associated with changes in basal resource quality,

which in turn can affect consumer levels (Cross et al. 2003,
Demi et al. 2018, 2019). In our study, analyses of bryophytes,
FPOM, leaf litter and perilithon confirmed that changes
in the elemental composition of these basal resources were
clearly associated with water N:P gradient. These changes
are generally mediated by the non-homeostatic nature of
primary producers and decomposers. For example, leaf lit-
ter, the main basal resource in detritus-based systems, varies
broadly in stoichiometry and reflects nutrient availability in
ecosystems (Cross et al. 2003, Farrell et al. 2018, Demi et al.
2019). Nutrient enrichment (N, P) increases the activity of
and colonization by microbial decomposers, thereby increas-
ing leaf litter phosphorus content and its quality as resource
(Cross et al. 2003, Danger et al. 2016). Some microbial
decomposers themselves are not homeostatic and can store
excess phosphorus in their biomass which lowers their body
N:P and C:P ratios and those of the whole leaf litter detritus
(Danger et al. 2013, Gulis et al. 2017). Due to the high num-
ber of studies confirming the link between water nutrient
concentrations, resource stoichiometry and primary as well
as secondary consumers as cited above, we assume that this
could be the mechanism by which community composition
has been affected. Besides resource quality, also its quantity
may change under different nutrient concentrations, which
might especially affect long-lived taxa (Cross et al. 2005).

Generally, there are two ways in which a community might
adapt to changing nutrient concentrations: 1) the taxa adapt
their elemental composition to the nutrient content of their
resources (Small and Pringle 2010) or 2) the composition of
benthic community changes, supporting taxa whose elemen-
tal demands best fit the resources provided (Singer and Battin
2007). Both of these strategies will lead to changes in com-
munity stoichiometry. Our findings indicate that the elemen-
tal composition of the overall community tends to change,
reflecting the differences in dissolved N:P concentrations in
the water. Although the differences in nutrient concentra-
tions between low, medium and high water N:P sites did not
significantly impact the macroinvertebrate community C:P
ratios, we observed a significant increase in community N:P
and a marginal but insignificant decrease in community C:N
along this N:P gradient. The opposite patterns in commu-
nity C:P (and N:P) versus C:N ratio indicate that a tradeoff
between nitrogen and phosphorus stoichiometry can also be
observed on community level. The loss of these effects when
focusing on intraspecific differences (Fig. 3) suggests that
the observed community changes in stoichiometry along the
water N:P gradient likely results for a large part from taxo-
nomic changes and not from stoichiometric plasticity of simi-
lar taxa. Sites with a high N:P ratio seem thus to select for
taxa with a high N:P demand and vice versa. In agreement
with our results, similar changes in community stoichiometry
and composition over a nutrient gradient or after nutrient
enrichment have already been observed in previous studies
(Singer and Battin 2007, Prater et al. 2015). In both studies,
the community C:P decreased when water phosphorus load
increased, due to a shift towards P-rich taxa. The preponder-
ance of taxonomic shifts over taxon stoichiometry plasticity
for explaining changes in community stoichiometry, is further confirmed in this study, insofar as seven out of nine taxa that were found at more than one site type, showed no difference in stoichiometric ratios (C:N, C:P, N:P) when nutrient load in the stream varied (Supporting information). This observation is a major assumption in GRH (Elser et al. 1996) and in accordance with several results in the literature stating general homeostasis for aquatic macroinvertebrates when nutrient content changes in the environment (Evans-White et al. 2005, Persson et al. 2010). However other studies found deviation from strict homeostasis under different nutrient regimes (Cross et al. 2003, Small and Pringle 2010), which underlines the potential confounding effect of factors such as sex or size/age on the variability of C:N:P ratios and the difficulty to actually confirm homeostasis using field data (Halvorson and Small 2016). We are aware that it is therefore questionable to apply the concept of strict homeostasis without accounting for these additional factors, but we think that here it can serve as an indication that macroinvertebrates keep a stable stoichiometry under changing nutrient concentration.

## Community trait composition shifts with stream water N:P ratio

Changes in community stoichiometry along a gradient of water N:P ratio were linked to a selection of species according to certain biological traits, as the communities differed regarding macroinvertebrate groups with distinct developmental traits. With increasing water N:P level, the abundances of fast-developing taxa (group F) decreased, while that of slow-developing taxa (group S) increased. Taxon richness followed a similar pattern of response for part of the water N:P gradient. This is in agreement with our second hypothesis, predicting differences in developmental trait composition in stream communities. Singer and Battin (2007) and Prater et al. (2015) have already shown a shift in traits towards fast-growing and small-bodied species under high phosphorus conditions. These observations on species growth and body size, following assumptions based on GRH, seem to be applicable to development and could be extended to the whole community as well. Taxa with fast growth and/or development seem to be favored at P-rich sites. Their high phosphorus requirements cannot be met at phosphorus depleted sites. At these sites, taxa with lower phosphorus demand are favored, leading to the dominance of taxa with slow growth and/or development in communities. This matches with the expected and observed differences in stoichiometry between the trait-based groups (discussed above). The groups to which no clear development speed could be assigned, also partly showed a pattern of increasing (group I₃) or decreasing (group I₁ and I₂) abundances with increasing water N:P, but the relationship between this pattern and developmental traits needs to be further investigated.

The ability of some taxa to regulate growth rate and to maintain it also under varying resource quality (Fuller et al. 2015), might further hinder the detection of a clear response to nutrient concentration changes in some groups.

Communities at low water N:P sites were clearly dominated by taxa belonging to group I₂. This was due to the large number of Oligochaeta, whose dominance at this site type might be explained by low body N:P ratios as reported by Singer and Battin (2007).

## Perspectives

This study, combining stoichiometric traits with other biological traits to investigate patterns of changes in community C:N:P ratios, suggests that there is a great potential of using and extending this approach for investigating numerous questions. Specifically, it would be interesting to:

1) *Integrate other biological traits.* There is further evidence that nutrient load is linked to functional traits, as taxa differing in life span or feeding type respond differently to nutrient changes in the environment (Cross et al. 2005, 2006). In other studies, only some functional groups were affected by nutrient enrichment (Dang et al. 2009, Evans-White et al. 2009). The integration of feeding and/or food type seems to be particularly promising, as basal resources vary in stoichiometry with nutrient load in the stream (Farrell et al. 2018), leading to a larger effect of nutrient enrichment on primary consumers than predators (Demi et al. 2019). Additionally, stoichiometric differences between feeding groups have already been reported (Cross et al. 2003, Evans-White et al. 2005) and also in this study we found a signal in C:N stoichiometry probably related to trophic level.

2) *Increase the number of taxa and environmental situations.* The scope of our analysis has been restricted by the number of taxa that we were able to collect and analyze for stoichiometry. Especially very small taxa are often difficult to identify and to collect in sufficient quantities. Therefore, they have often not been considered or only integrated as pooled groups at lower taxonomic level, although they can make large proportions of a community. Improving the stoichiometric data set by increasing the number of taxa as well as their sample size would allow a finer analysis and might strengthen the first observations. Using the dataset of a one-year survey on community composition has already supported our approach of using stoichiometry and developmental traits to distinguish macroinvertebrate communities along a nutrient gradient. Testing community hypotheses on a larger number of situations might be useful (e.g. increasing the number and the environmental diversity of stream types). Likewise, increasing the number of study sites could help to reduce the confounding effect of other non-nutrient water parameters (e.g. pH, O₂), that are necessary to account for when relying to field data rather than controlled experimental set-ups. In general, the approach might be extended to other ecosystem types and animal communities, as similar trait databases are available for example for zooplankton (Brun et al. 2016) or for terrestrial invertebrates (Pey et al. 2014).
3) *Define the consequences of changes in the stoichiometric structure of animal communities on ecosystem functioning.* In this study, changes in community stoichiometry went along with changes in community composition and community traits. Reported ecosystem responses following such changes on community level after nutrient enrichment involve changes in nutrient flux and cycling (Cross et al. 2007). More precisely, food chains become smaller (Singer and Battin 2007) and consumer biomass increases due to a higher amount of faster growing species (Prater et al. 2015). The production of macroinvertebrate primary consumers increases as the result of increased resource quality. This effect only reaches predators, i.e. secondary consumers, in some studies (Cross et al. 2006, Demi et al. 2018) and seems to depend on prey identity (Spivak et al. 2009). Davis et al. (2010) observed a shift towards larger prey organisms, which turned the positive effects of increased consumer production into negative effects for secondary consumers, as preys became morphologically not suited for consumption. This underlines the complexity in tracing such bottom-up effects along trophic levels and the importance of integrating traits in such analyses. Body stoichiometry is also linked to nutrient recycling. Besides taxonomic differences, P-rich taxa tend to excrete material that is less rich in P. The same negative relationship holds for N:P ratio (Vanni et al. 2002). Consequently, the stoichiometric traits of a consumer affect the elemental composition of the basal resources via its nutrient release (Evans-White and Lamberti 2006, Knoll et al. 2009). Although the strength of consumer-driven nutrient recycling seems to depend on nutrient availability, changes in community stoichiometry will alter the concentration of the nutrients released into the environment.

## Conclusion

We have shown that the community stoichiometry changed over a nutrient gradient of water N:P, following the nutrient concentrations. This went along with a change in community composition regarding developmental groups, which, for some trait-based groups, clearly followed our assumptions based on GRH. By extending the GRH to developmental traits, we have demonstrated the potential of using stoichiometric traits to address changes in community composition. Integrating other functional traits to stoichiometric traits and linking them to alterations in nutrient loads could help to better understand the consequences of nutrient changes on community structure, and, in turn, on ecosystem functioning.

## Data availability statement

Data available from the Dryad Digital Repository: <http://dx.doi.org/10.5061/dryad.bnzs7h4b0> (Beck et al. 2021).

*Acknowledgements* – We thank P. Rousselle and F. Charmasson for their help during sample processing and elemental analyses.

*Funding* – This research was funded by the Lorraine Université d'Excellence SPACE project to MD and MB, and by the 'Benthic invertebrates: reference conditions, bioindication methods and expert-system' (MEEDDAT/ONEMA) project to PU-P and CPM. MD benefited of funding from the Institut Universitaire de France (IUF).

*Conflict of interest* – The authors declare no conflicts of interest.

## Author contribution statement

**Miriam Beck** and **Cedrid P. Mondy** contributed equally to this publication. **Miriam Beck:** Formal analysis (lead); Methodology (equal); Writing – original draft (lead); Writing – review and editing (equal). **Cedric P. Mondy:** Conceptualization (equal); Formal analysis (lead); Methodology (equal); Writing – original draft (lead); Writing – review and editing (equal). **Michael Danger:** Conceptualization (equal); Methodology (equal); Resources (equal); Supervision (lead); Writing – original draft (equal); Writing – review and editing (equal). **Elise Billoir:** Formal analysis (equal); Methodology (equal); Writing – original draft (equal); Writing – review and editing (equal). **Philippe Usseglio-Polatera:** Conceptualization (equal); Methodology (equal); Resources (equal); Supervision (lead); Writing – original draft (equal); Writing – review and editing (equal).

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