# Do sex, age or ecological needs shape an endangered Brown Bear population diet? New insights from faecal metabarcoding

Grégoire Pauly, Mélanie Roy, Cécile Vanpé, Jérôme Sentilles, Pierre-Yves Quenette, Anne-Sophie Benoiston, Lucie Moreau, Amaia Iribar, Tanguy Daufresne, Christophe Baltzinger

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## To cite this version:

Grégoire Pauly, Mélanie Roy, Cécile Vanpé, Jérôme Sentilles, Pierre-Yves Quenette, et al. Do sex, age or ecological needs shape an endangered Brown Bear population diet? New insights from faecal metabarcoding. Biological Conservation, 2026, 313, pp.111548. 10.1016/j.biocon.2025.111548. hal-05480371

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https://hal.science/hal-05480371v1

Submitted on 27 Jan 2026

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# Do sex, age or ecological needs shape an endangered Brown Bear population diet? New insights from faecal metabarcoding

Grégoire Pauly<sup>a,b,c,*</sup> <sup>Id</sup>, Mélanie Roy<sup>d,e</sup> <sup>Id</sup>, Cécile Vanpé<sup>c</sup> <sup>Id</sup>, Jérôme Sentilles<sup>c</sup>, Pierre-Yves Quenette<sup>c</sup> <sup>Id</sup>, Anne-Sophie Benoiston<sup>d</sup> <sup>Id</sup>, Lucie Moreau<sup>d</sup> <sup>Id</sup>, Amaia Iribar<sup>d</sup> <sup>Id</sup>, Tanguy Daufresne<sup>b,f</sup> <sup>Id</sup>, Christophe Baltzinger<sup>a</sup> <sup>Id</sup>

## ARTICLE INFO

### Keywords:

Ursid
omnivory
mycophagy
predation
frugivory
arthropods

## ABSTRACT

Conservation strategies usually focus on megafauna and keystone species to protect habitats. In temperate ecosystems, brown bear appears as one of the potential megafauna keystone species thanks to its omnivorous diet. However, most of the trophic interactions' studies used coproscopic analyses that generally miss highly digested items and rarely investigated the effect of sex, age and individual. In addition, the diet was frequently investigated according to climatic seasons, while Bear Ecological Periods - BEP - (e.g. mating, hyperphagia) really drive individual movement and foraging. In this study, we collected brown bear faeces of different age class and sex across BEP from a critically endangered population. We used metabarcoding and four markers specific to plants, fungi, arthropods and vertebrates to investigate the brown bear diet in the Pyrénées mountains. The diet was mainly composed of plants but also of arthropods, vertebrates and fungi. Pyrenean brown bear consumed significantly fewer arthropods during hyperphagia than other BEP, and exhibited preferences for different plant life forms during mating (diversified herbs), pre-hyperphagia (fleshy- fruits) and hyperphagia (dry- fruits). Females consumed plants more often than males, which in turn consumed more wild vertebrates. We highlighted the most diverse level of mycophagy (21 genera) of an omnivore Ursid thanks to metabarcoding. We showed the high variability of this brown bear population diet among BEP and sexes, but not among age-classes. This detailed diet study provides new insights for brown bear conservation, and invites similar approaches on other animals.

## 1. Introduction

Conservation strategies often target pivotal species with significant impacts on the ecosystem functioning. These keystone species usually belong to the megafauna (Shukla et al., 2023). However, the first step to propose an effective conservation strategy is to properly understand species' trophic interactions and ecological needs across its life cycle. In temperate areas, megafauna are diverse including canids, felids, bovids, cervids, suids, or ursids. The ursids count for the most abundant large carnivore species in the world (Ripple et al., 2014), among which brown bear (Ursus arctos) distribution cover the entire temperate zone (IUCN).

Brown bear is a typical omnivore that consumes diverse food types at various trophic levels (e.g. plants, insects, vertebrates) and triggers various forms of ecosystem engineering after foraging (e.g. endozoochory), turning it into a potential keystone species (Levi et al., 2020; Pauly et al., 2025).

Basically, brown bear's diet can be highly biased towards plants with local and temporal predominance of fleshy-fruits, hard mast or herbs, but also towards meat consumption of terrestrial vertebrates (e.g. wild, domestic ungulates but also smaller mammals, Edwards et al., 2011) constituting a substantial part of the diet as shown in its northern range (Bojarska and Selva, 2012). Locally, arthropods such as colonial

<footnote><sup>a</sup> INRAE, UR 1455 EFNO, F-45290, Nogent-sur-Vernisson, France</footnote>

<footnote><sup>b</sup> UMR Eco&Sols, INRAE, Montpellier Cedex 2, France</footnote>

<footnote><sup>c</sup> Office Français de la Biodiversité (OFB), Service Espèces à Enjeux, Villeneuve de Rivière, France</footnote>

<footnote><sup>d</sup> UMR CRBE, Université Toulouse 3, 31062, Toulouse Cedex 9, France</footnote>

<footnote><sup>e</sup> Instituto Franco-Argentino para el Estudio del Clima y sus Impactos (IRL IFAECI/CNRS-CONICET-UBA-IRD), Universidad de Buenos Aires, Buenos Aires, Argentina</footnote>

<footnote><sup>f</sup> UMR 5175 CEFE, 1919, route de Mende, 34293, Montpellier cedex 5, France</footnote>

<footnote>* Corresponding authors at: INRAE, UR 1455 EFNO, F-45290, Domaines des Barres, Nogent-sur-Vernisson, France.
E-mail address: gregoire.pauly@inrae.fr (G. Pauly).</footnote>
hymenoptera complete the diet (Bojarska and Selva, 2012), and else-
where, the return of salmons to freshwater provides key resources for
the brown bear (Mowat and Heard, 2006). Over the year, brown bears
exhibit distinct timing of activities such as mating, hyperphagia or
winter dormancy, representing typical ecological periods that may
shape the diet. Indeed, these bear ecological periods (hereafter BEP)
drive individual movement and foraging strategies (Penteriani et al.,
2022, 2025), and in relation to resource phenology shape feeding op-
portunities. Yet, most studies investigated brown bear diet according to
climatic seasons and therefore food availability (e.g. Pereira et al., 2021;
Vulla et al., 2009; but see García-Rodríguez et al., 2021b; Naves et al.,
2006).

Besides the spatio-temporal variability of brown bear diet, intra-
population variation can be explained by sex, age or individual prefer-
ences. For instance, adults are the most active during the best period for
salmon fishing in coastal British Columbia (Klinka and Reimchen,
2002), and males consume more fish than females in North America
(Mowat and Heard, 2006). The consumption of wild terrestrial meat is
also more frequent in adult males than females in the Canadian Arctic
(Edwards et al., 2011), while similar consumption of herbs is reported
for both sexes (in Himalaya: Nawaz et al., 2019; in Croatia: Pereira et al.,
2021). However, among plant resources, hard mast availability is usu-
ally restricted to small areas, in which adults can be dominant in Spain
(Ruiz-Villar et al., 2019). More broadly, females with cubs may avoid
prime bear habitats to limit the risk of infanticide by males (Steyaert
et al., 2012). However, part of the variability may also be explained by
individual foraging preferences (Edwards et al., 2011).

In fact, studying the diet of an omnivorous species with a flexible diet
is particularly challenging. Most of the studies describing brown bear
diet were based on coproscopic analyses using visual identification
(Pauly et al., 2025) subject to the variable digestibility of food items and
our ability to identify altered food items (e.g. Spaulding et al., 2000).
Conversely, some less digested food items (e.g. fibrous plants) may be
overestimated in the diet (Lagaisse et al., 2003) while highly digested
ones (e.g. mosses, fungi) may be overlooked and rarely reported (e.g.
Pereira et al., 2021). Nevertheless, faeces are also a pool of DNA se-
quences (i.e. environmental DNA) sourced from ingested food, which
combined with advances in metabarcoding (Taberlet et al., 2018)
greatly contributed in detailing animal diet (Ando et al., 2020). For
endangered species, this noninvasive, time- and cost-effective approach
appears appropriate (Ando et al., 2020). It was used only three times for
brown bear, with a focus on plants in Himalaya (Nawaz et al., 2019), and
plants, vertebrates and invertebrates in Slovenia (García-Rodríguez
et al., 2021b) and Italy (De Barba et al., 2014). Hence, the use of a
marker specific to fungi has never been tested to investigate brown bear
mycophagy.

In this study, we analysed the content of faeces in the critically-
endangered population of European brown bears (Ursus arctos arctos)
in the Pyrénées (IUCN, 2017), accounting for sexes, different age-classes
and collected within different BEP. We used a metabarcoding approach
with four markers specific to plants, fungi, arthropods and vertebrates.
We first hypothesized an effect of BEP especially on the frequency of
vertebrate and plant food items in the diet due to the short availability
period of weak body condition preys and nutritious plant phenology
(Niedzialkowska et al., 2019; García-Rodríguez et al., 2021b) and brown
bear movement variations among BEP (Penteriani et al., 2022, 2025).
We also hypothesized an effect of the sex, with a more diverse and
carnivorous diet expected for males than for females due to greater
distances travelled (Penteriani et al., 2022, 2025) and the greater male
ability to predate wild vertebrates (Mowat and Heard, 2006), both of-
fering a greater prey encounter probability and food spatial variability.
We finally expected a difference in the diet among age-classes related to
reproduction and dominance relationships (Ruiz-Villar et al., 2019),
thus predicting less rich food items for subadults.

## 2. Materials and methods

2.1. Study site and population

Our study was conducted in the Pyrénées, a mountain chain (36,600 km²) shared between France, Andorra and Spain, peaking at 3400 m above sea level. Forest covers >40 % of the landscape and is dominated by hard mast trees. Above the timberline, large open areas are covered by fleshy-fruited shrubs and herbaceous plants. Pyrénées host a highly diverse flora, including endemics, and megafauna species such as the brown bear, wild and domestic ungulates and mesocarnivores.

The local brown bear population was on the edge of extinction in the
1990s and has, since then, been subject to five phases of Slovenian bear
translocations, initiating a partial demographic recovery (Vanpé et al.,
2022) but still with genetic concerns (Auclair et al., 2025). In 2023, the
population amounted to at least 90 individuals covering about 7200 km²
(Sentilles et al., 2025) (Fig. 1).

## 2.2. Faeces collection and metabarcoding

We collected 148 very fresh brown bear faeces (<48 h) from 2017 to
2023 covering different BEPs, with the help of dogs trained to detect
bear faeces (Sentilles et al., 2021). We divided the year in six different
BEPs: Winter dormancy (hibernal period of brown bear), Post-winter
dormancy (hibernation recovery), Mating (reproduction period with
high movement rate), Pre-hyperphagia (muscle recovery), Hyperphagia
(massive consumption of aggregated resources), Pre-winter dormancy
(Period of den searching) (Fig. 2). Those BEP timings were defined based
on local expertise and long-term monitoring of this population. We
collected the outer part of the faeces composed of brown bear epithelial
cells to identify the individual and the sex through genotyping and sex-
markers (Vanpé et al., 2022). Thanks to the intensive monitoring of this
population (Sentilles et al., 2025), individual identification helped to
determine the age-class and reproductive status at the time of the faeces
release. Brown bears were thus classified as “cub” (<1 year), “subadult”
(1–5 years for males, 1–3 years for females) and as “adults” when older
than subadults. The inner part of the faeces was collected to perform
metabarcoding analyses using four universal markers (Taberlet et al.,
2018) to detect plants (Sper01, trnl region), fungi (Fung02, ITS1 nu-
clear), arthropods (Arth02, 16S mtDNA) and vertebrates (Vert01, 12S
mtDNA) taxa (see Appendix A for metabarcoding details). Only fungi
producing edible fruit bodies were kept in the analysis to be parsimo-
nious with brown bear real mycophagy. After metabarcoding and data
curation, we thus ended up with 126 samples with DNA sequences,

<figure><img src="image_3.png" /><figcaption>**Fig. 1.** Female subadult brown bear in the Pyrénées (South-West of Europe). Photo by Jérôme Sentilles.</figcaption></figure>
<figure><img src="image_4.png" /><figcaption>**Fig. 2.** Year-round spatial and temporal distribution of the brown bear faeces collected (n = 127) in each of the six bear ecological periods, according to sexes (♀: Female, ♂: Male, All: both sexes and undetermined individuals) and age categories (Adult in bold, subadult in normal text, cubs in italics, and All combined underlined). Roman numerals indicate months (from I January to XII December). The blue line delimits the French administrative departments, in red the Spanish autonomous communities, and to the East the border with Andorra. Some faeces are not assigned to age or sex. One faeces of post-winter dormancy and two of hyperphagia are not visible on the maps as they were collected to the East (Ariège department) and the West of the Pyrénées (Hautes Pyrénées and Pyrénées-Atlantiques department). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>

including 72 females and 44 males distributed in 9 cubs, 23 subadults and 79 adults (Fig. 2). For the diet analysis, we only considered the mating (n = 43), pre-hyperphagia (n = 35) and hyperphagia (n = 45) BEP resulting in a sample size of 123 faeces samples. Results from pre-(n = 1) and post-winter (n = 2) dormancy are also presented.

## 2.3. *Diet approach*

### 2.3.1. *Food types*

We first analysed the diet using the frequency of occurrences (FO) of at least 250 reads from the four food types: plants, fungi, arthropods and vertebrates. We interpreted the absence of a food type in a sample, as a non-consumption, fully aware it may be due to metabarcoding failures.

### 2.3.2. *Food items*

Secondly, we analysed the diet based on the genera identified (i.e. Food items) by metabarcoding using the four markers. A food item was considered present if it occurred in a sample with at least 250 reads.

Among the reads not annotated at the genus level, 76 % of them belong to Apiaceae or Poaceae families (i.e. dry-fruited herbs). To limit this potential loss of information, we decided to include the MOTUs annotated to both families as two additional food items. However, MOTUs annotated to genera of these two families were also included independently. Thus, the selected food items cover almost all of the sequences detected for plants (95.4 %), vertebrates (99.3 %) and in-vertebrates (79.9 %), but much less for fungi (4.4 %), but fungi sequences were not annotated at family level either (4.8 %).

### 2.3.3. *Diet analysis*

Beforehand, we checked the spatial auto-correlation of our 123

samples using Moran test and did not detect any (p = 0.51).

First, we tested the effect of BEP, sex and age class on the presence or absence of a given food type (plants, fungi, arthropods, vertebrates) (n = 123 samples), using different Firth's Bias-Reduced Logistic Regressions (i.e. one per food type). We used this model because in one of the categories we only had successes (presence of a food type) and no failures (absence of a food type, i.e. complete separation of data). We excluded the effect of age class in the final model due to an absence of effect and a substantial increase in the number of parameters weakening the model.

Secondly, we investigated the food item diversity based on the bipartite interaction network linking food items and faeces (representing a bear individual for a specific BEP of a given sex within a particular age-class) using a subdataset with food items and sex information (n = 109). According to the unequal sample distribution per sex and BEP we conducted a bootstrap resampling method using eight samples per sex in each of the three BEP (i.e. the minimum collected) to build a sub-network (n = 48 samples). We did not have sufficient samples per age-class to include it in re-sampling. To estimate the diversity of food items, we calculated the degree (i.e. number of food items within faeces), *d* of Blühgen (i.e. specialization of each faeces within the network, Blühgen et al., 2006) and the species strength of food items (i.e. sum of dependencies of each item) within the sub-network. We resampled 1000 times and averaged the degree and *d* of each faeces sample and species strength of each food item. We tested the effect of BEP, sex and age as fixed factor and year of sample and bear individual as random factors on the degree using a negative binomial model to account for overdispersion and on *d* using a quasibinomial model, which deals with data underdispersed. Based on AIC and BIC score, the BEP and sex fixed effects were kept in both final models.
Thirdly, we investigated the difference in the food item composition among BEP and age-classes and between sexes using a dissimilarity matrix approach. We performed a Permanova on the matrix according to BEP, sex and age-class. If significant, we used five variables to identify the drivers of the difference observed: number of dry-fruited herbs, fleshy-fruited shrubs, dry-fruited trees, domestic and wild vertebrates.

Finally, we investigated the food item composition according to the plant life form (i.e. dry-fruited herbs, fleshy-fruited shrubs or dry-fruited trees) and the meat origin (domestic vs wild). For the former we investigated the effect of BEP, sex and age-class as fixed factors and year of sample collection and brown bear individual as random factor on the presence or absence (expressed in FO) of plants according to their life form using a binomial model. Based on AIC and BIC score the final model contained only BEP and sex as fixed effect. For the latter, we investigated the effect of BEP, sex and age as fixed factor and year of sample and brown bear individual as random factor on the presence or absence (expressed in FO) of vertebrates according to origin using a binomial GLMM. We considered *Ovis* as domestic *Ovis aries* due to the rarity of mouflons *Ovis gmelini* in our study area. Based on AIC and BIC score the

final model contained only BEP and sex as fixed effect and the year as random factors. No specific analysis were conducted on fungi and arthropod item composition.

All analyses were performed with R (v.4.3.2). We used several packages, *logistf* (v.1.26.0, Heinze et al., 2003) to compute Firth's model and *performance* (v.0.12.3, Lüdecke et al., 2021) to calculate the R². For network analysis, we used *bipartite* (v.2.20, Dormann et al., 2008) to calculate metrics. We used *glmmTMB* (v.1.1.9, Brooks et al., 2017) for negative binomial, quasibinomial and binomial GLM and GLMM computation and *MuMln* (v.1.48.4) to calculate the R² using delta method (Barton, 2024). To perform NMDS, Permanova and fit drivers we used *vegan* (v.2.6–8, Oksanen et al., 2009). Fig. 2 was computed using QGIS (v.3.30) and the others using *ggplot2* (v.3.5.1) (Wickham, 2011) and associated with *ggvenn* (v.0.1.10) for Fig. 3. We computed each figure to be understandable to colour-blind people.

### 3. Results

We found 13,369 OTUs and 21,066,708 reads in the 126 samples,

<figure><img src="image_5.png" /><figcaption>**Fig. 3.** Predicted frequency of occurrence (median and standard error symbolised by open symbol and bar) per food type (Plants: darkgreen, #006400; Fungi: darkblue, #00008B; Arthropods: gold, #CDAD00; Vertebrates: darkred #8B0000) according to the bear ecological period BEP (Mating; Pre-hyperphagia; Hyperphagia) (A) and the sex of the individual (B) in the top row. In the bottom left (C), per plant life form (Herbs: darkgreen, #006400, Shrubs: purple #A020F0 and Trees: darkorange #FF8C00) according to the bear ecological period BEP. In the bottom right (D), per terrestrial vertebrate origin (Domestic: coral, #FF7256; Wild: darkred #8B0000) according to the sex of the individual in the bottom row. For subfigure A) and B), results are based on a Firth model using food type, BEP and sex as fixed factors, for C) and D) results are based on two separate GLM binomial. The letters indicate the significant differences among BEP (A) or sexes (B) and the stars (*) the observed mean. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>
mostly obtained using the plant marker (see Supplementary Tables S1-S2).

## 3.1. Food type consumption

Most of the faeces were composed of one (n = 58) or two (n = 50) food types, and less frequently of three (n = 13) or all the four (n = 2) food types (Appendix B Fig. S1). We observed significant differences among food types in faeces collected from mating to hyperphagia (n = 123, Firth's model: Pseudo-R² of McFadden = 0.42). We found more faeces containing plants (92%, n = 113) than fungi (37%, n = 45, t-ratio = 5.75, p < 0.01), arthropods (24%, n = 29, t-ratio = 6.72, p < 0.01) or vertebrates (15%, n = 18, t-ratio = 7.29, p < 0.01) across BEP. Faeces containing fungi were significantly more frequent than faeces containing vertebrates (t-ratio = 3.17, p = 0.01) and marginally than faeces containing arthropods (t-ratio 2.09, p = 0.08). We observed no differences in the FO of faeces containing arthropods vs. vertebrates.

We showed that each food type FO varies among mating (n = 43), pre-hyperphagia (n = 35) and hyperphagia (n = 45) (Firth's model: Pseudo-R² of McFadden = 0.42 Fig. 3.A). We found plants marginally at higher FO during mating (98 % of occurrences) compared to pre-hyperphagia (83%, t-ratio = 2.30, p = 0.07), whereas no difference was found between hyperphagia (91%) and the two other BEP. Conversely, we found arthropods at a significantly higher FO during mating (30%) and pre-hyperphagia (37%) than during hyperphagia (7%, t-ratio = 3.06, p = 0.01 and t-ratio = 2.30, p = 0.04 respectively) while there was no difference between pre-hyperphagia and mating. For vertebrates and fungi, we only observed non-significant trends (mating = 23% and 35%, pre-hyperphagia = 12% and 29% and hyperphagia = 11% and 44% respectively).

We also observed that food types FO varied between females (n = 72) and males (n = 42) (Firth's model: R² = 0.42; Fig. 3.B).

Females significantly consumed plants (FO = 96%) more often than did males (86%, t-ratio = 2.53, p = 0.01). Conversely, males consumed vertebrates (24%) marginally more frequently than females (10%, t-ratio = 1.80, p = 0.07). Finally, we found no significant differences in arthropod and fungi consumption between males (26% and 31% respectively) and females (19% and 43% respectively).

We could not find any significant effect of age-class on the food types FO. Adults (n = 78), subadults (n = 22) and cubs (n = 9) consumed plants (92%, 86%, 100% respectively), fungi (41%, 41%, 22%, respectively), arthropods (19%, 32%, 11%, respectively). Only adults and subadults consumed vertebrates (18%, 9% respectively).

## 3.2. Food item diversity

We identified 79 different food items (including Apiaceae and Poaceae) consumed across the (three) BEP (see details in supplementary). Among them, we identified 50 plants including 44 dry-fruited herbs, four dry-fruited trees and two fleshy-fruited shrubs. We also retrieved 21 fungi, one domestic and four wild vertebrates and three arthropods, all hymenopteran (see Appendix B, Fig. B.2). During post-winter dormancy, one faeces contained only Sus (food item only found once) and the other seven herbaceous plant items (including Apiaceae and Poaceae). The sole pre-winter dormancy faeces contained only Fagus (Fig. 4).

Based on interaction network analyses using the subdataset with sex information (n = 109), we found significant differences among BEP on the number of food items (GLM negative binomial, R² = 0.17), with significantly more items during mating (4.2 items) than during pre-hyperphagia (2.6, t-ratio = 2.63, p = 0.02) or hyperphagia (2.4, t-ratio = 3.41, p = 0.01), but no significant differences between pre-hyperphagia and hyperphagia. In addition, the number of food items did not differ significantly between sexes (males: 3.1 vs. females: 3.0), but we found a marginal effect during hyperphagia with more items per

<figure><img src="image_6.png" /><figcaption>**Fig. 4.** Bipartite interaction network between food items consumed (top) and their occurrences in brown bear faeces (bottom). Food items are colour-coded for plants (darkgreen, #006400), fungi (darkblue, #00008B), arthropods (gold, #CDAD00) and vertebrates (darkred #8B0000). Faeces are colour-coded according to male (brown, #A52A2A) female (blurywood, #DEB887) and undetermined (grey, #BEBEBE). Bear Ecological Periods are indicated at the bottom. The width of the boxes (a food item or faeces) is proportional to the number of links. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>
male (3.0) than female faeces (2.0, t-ratio = 1.84, *p* = 0.07). We did not detect an effect of age-class and it was not included in the final model (adults = 2.9, subadults = 3.4, cubs = 3.2). Furthermore, we observed no effect of BEP on *d* of Blüthgen (GLM Binomial, R² = 0.10), with similar specialization during mating (*d* = 0.35), pre-hyperphagia (0.32) and hyperphagia (0.35) or between females (0.34) and males (0.34) across BEP. However, during hyperphagia we observed significant higher specialization by females (0.28) than males (0.43, t-ratio = 2.01, *p* = 0.04). We did not detect an effect of age-class on specialization and it was not included in the model based on AIC and BIC score (adults *d* = 0.35, subadults *d* = 0.29, cubs *d* = 0.37). Based on this subnetwork, 76 food items were retrieved in faeces, and we identified eight taxa (10 % of the food items) with the highest species strength value: Apiaceae (8.6), Quercus (8.0), *Formica* (3.7), *Festuca* (2.6), *Ovis* (2.5), Poaceae (2.1), *Lasius* (1.5), *Fagus* (1.5) (Fig. 4).

### 3.3. Food item composition

Based on the dissimilarity matrix, we removed two singletons that increased stress and similarity (one female sample during mating and one during hyperphagia). We observed a significant effect of the BEP (see Appendix B, Fig. B.3) on the food item composition between mating and pre-hyperphagia (Permanova, F-value = 2.56, *p* = 0.004), mating and hyperphagia (Permanova, F-value = 17.41, *p* = 0.001), and pre-hyperphagia and hyperphagia (Permanova, F-value = 13.30, *p* = 0.001). We identified three significant drivers of those differences, the consumption of herbs (R² = 0.11, *p* = 0.001), trees (R² = 0.40, *p* = 0.001) and domestic vertebrates (R² = 0.24, *p* = 0.001), whereas the consumption of wild vertebrates as driver of those differences remained marginal (R² = 0.50, *p* = 0.064) and the consumption of fleshy-fruited-bearing shrubs plant has no effect. We observed no effect of sex or age-class on food items composition.

Among samples composed of plants (*n* = 113), we identified plant food items in 91 % of those samples. Based on plant life forms, we observed significant differences among them (GLM Binomial: R² = 0.41). From mating to hyperphagia, herbs occurred significantly at higher FO (66 %) than trees (37 %, t-ratio = 4.60, *p* < 0.01) and shrubs (16 %, t-ratio = 6.72, *p* < 0.01), and tree at higher FO than shrubs (t-ratio = 2.40, *p* = 0.02). We observed significant differences among BEP (GLM Binomial: R² = 0.41, Fig. 3.B), herbs FO was significantly higher during mating (93 %) than during pre-hyperphagia (69 %, z-ratio = 2.45, *p* = 0.02) and hyperphagia (38 %, z-ratio = 4.23, *p* < 0.01), and significantly higher during pre-hyperphagia than during hyperphagia (z-ratio = 2.45, *p* = 0.02). Fleshy-fruited shrubs were significantly more frequent during pre-hyperphagia (34 %) than during mating (9 %, z-ratio = 2.32, *p* = 0.04) and hyperphagia (7 %, z-ratio = 2.95, *p* = 0.01), with no difference between mating and hyperphagia. Finally, dry-fruited trees were significantly more frequent during hyperphagia (76 %) than during mating (19 %, z-ratio = 4.47, *p* < 0.01) and pre-hyperphagia (9 %, z-ratio = 4.92, *p* < 0.01), with no significant difference between mating and pre-hyperphagia. Females and males did not differ in the consumption of herbs (62 % and 67 %, respectively), shrubs (19 % and 12 %, respectively) or trees (39 % and 40 %, respectively). Similarly, among adults, subadults and cubs did not differ in their consumption of herbs (63 %, 59 %, 89 %, respectively), shrubs (14 %, 14 %, 56 %, respectively) and trees (40 %, 41 %, 22 %, respectively). We also identified five families (Boraginaceae, Hyacinthaceae, Iridaceae, Onagraceae) with no genus identified.

Among samples containing fungi (*n* = 45), we identified fungi items (genus level) in 48 % of those samples. The most consumed genus of fungi were Mycena, Melanogaster and Peniophora (*n* = 3), Phallus, Plicaturopsis and Trametes (*n* = 2). Brown bear consumed wood saprotroph (*n* = 9), ectomycorrhizae (*n* = 4) or plant pathogen (*n* = 4), soil saprotroph, litter saprotroph and lichenized fungi (*n* = 1). No fungi was only identified at family level.

Among samples containing arthropods (*n* = 29), we identified

arthropod items in 90 % of those samples. Three taxa were identified: *Formica* (*n* = 21), *Lasius* (*n* = 7) and *Vespula* (*n* = 2). *Formica* were consumed during each BEP, *Lasius* during mating and pre-hyperphagia, whereas *Vespula* only during hyperphagia. Each sex- and age-class consumed hymenopterans. We also identified Aphidae and Psychodiidae in faeces.

Among samples containing vertebrates (*n* = 18), we identified vertebrate items in 88 % of those samples including wild (*n* = 11, *Cervus*, *Capreolus*, *Rupicapra* and aquatic *Salmo*) and domestic vertebrates (*n* = 8, *Ovis*) in similar proportions (GLMM binomial with year of faeces as random effect, R² marginal = 0.20, R² conditional = 0.36). However, wild vertebrates were consumed in higher frequency by males (*n* = 7 of 42 faeces) than females (*n* = 3 of 72 faeces, z-ratio = 2.350, *p* = 0.02), whereas domestic vertebrates were found in similar proportions in both males and females (*n* = 3 and 4 respectively) (Fig. 3.D). Adults and subadults consumed vertebrates twice, whereas females with cubs did not consume vertebrates. Furthermore, we found Anatidae (i.e. ducks) in a single male sample.

### 4. Discussion

We showed that the critically endangered Pyrenean brown bear population diet is mainly plant based and secondarily composed of arthropods, vertebrates and even fungi, in agreement with previous Pyrenean studies (Berducou et al., 1982; Lagalisse et al., 2003) and more broadly in other populations of low latitudes (Bojarska and Selva, 2012; Vulla et al., 2009). We identified targeted food resources including herbs, hard mast trees, ants and ungulates, illustrating the omnivorous diet. This study updated and broadly detailed the knowledge of its diet, adding new information on mycophagy. We benefitted from a long-term ongoing project to study its diet among BEP, age-classes and sexes, accounting for individual identification.

We highlighted important differences among BEP with significant consumption of diversified herbs and arthropods during mating and pre-hyperphagia, and a quasi-exclusive consumption of hard-mast trees during hyperphagia, as shown by others (García-Rodríguez et al., 2021b; Naves et al., 2006) but never in this population. The almost exclusive consumption of various herbs during mating is probably related to the consumption of large quantities of vegetation in order to reach requirements in macronutrients (Coogan et al., 2014), few alternative resources or mating needs that do not drive foraging for rich resources (Penteriani et al., 2022, 2025). During pre-hyperphagia, we found a peak of fleshy-fruited shrubs consumption combined with other resources that may result in an optimal balance of protein, fat and carbohydrates (Coogan et al., 2014), ideal for this period of muscle and body recovery. Whereas hard mast are consumed for their high fat content and spatial aggregation during hyperphagia (Coogan et al., 2018; Ruiz-Villar et al., 2019). Accordingly, the preservation of *Vaccinium* spp. or oak forests in the Pyrénées is a key component for the brown bear conservation. We also observed trends with higher FO for fungi during hyperphagia and vertebrates during mating. For vertebrates, the temporal pattern can be explained by the high mobility during mating (Penteriani et al., 2022, 2025) associated with diversified resources available, including carcasses or weak preys (Niedzialkowska et al., 2019). Obviously, another main driver of these dietary differences was the plant phenology. In this sense, the presence of hard-mast trees during mating can be related to the consumption of cambium, young leaves or fruits from previous fructification. Fungi consumption appears as opportunistic, with few occurrences but high diversity, and may represent a significant and effective source of nutrient including unique elements such as Selenium, which are not accessible in other food items but are key elements in muscle health (Elliott et al., 2022). However, despite considerable effort to target real mycophagy, it is possible that some of the fungi were not consumed deliberately. Finally, ants were especially consumed during mating and pre-hyperphagia and wasp during hyperphagia, which may be related to opportunistic
consumption to meet energy requirements, particularly in terms of lipids (Coogan et al., 2014), or to the seasonal availability of pupae (e.g. Ursus thibetanus myrmecophagy, Fujiwara et al., 2013).

Brown bear diet seems to be shaped by sex differences with more herbivorous females while males preying more upon wild animals, in agreement with our second prediction. Higher meat consumption by males confirms previous studies in Europe (Pereira et al., 2021), North America (Edwards et al., 2011; Mowat and Heard, 2006) or Asia (Nawaz et al., 2019). It can be explained by higher energy requirements or predation ability for males (Mowat and Heard, 2006). The fact that females and males both similarly predate defenseless ewes in our study strengthen this idea. The higher herbivory by females contrasts with previous studies (Nawaz et al., 2019; Pereira et al., 2021). Some authors suggested this difference may be explained by the vegetation alone being sufficient to meet energy requirements (Mowat and Heard, 2006), however others stated it could be due to the fear of infanticide and the use of second choice habitats by females (Steyaert et al., 2012). This is consistent with our observation that no faeces contained meat for females with cubs. We did not find any difference between sexes on fungi consumption, contrary to Yellowstone NP where females consumed more false-truffles than males monopolising richer resources (Fortin et al., 2013). We did not detect any age effect on the diet (Pereira et al., 2021), which may be related either to sufficient resources that limit competition or to the few faeces of cubs and sub-adults compared to adults. Exclusion of subadults by adults has already been reported in fruit rich oak forests (Ruiz-Villar et al., 2019).

All of those trophic interactions triggered by the brown bear may lead to several associated engineering processes (Pauly et al., 2025). By consuming several plants of different life forms, brown bear ingests and disperses many seeds in our study site (Lalleroni et al., 2017; Pauly et al., 2024) and elsewhere (García-Rodríguez et al., 2021a). Similarly, consumption of fungi, especially mycorrhizae, can induce similar spore dispersal as shown for other vertebrates (Correia et al., 2018; Vasutová et al., 2019). In contrast, the low proportion of wild ungulates consumed (through predation or scavenging) suggests that brown bear predation is probably not an important mortality factor in the Pyrénées, as observed elsewhere (Zager and Beecham, 2006). However, the consumption of domestic ungulates, although rare in the diet, has implications for local stakeholders (Ouvrier et al., 2025). The consumption of *Salmo salar* in our study is intriguing, and it is hard to determine whether it comes from anadromous fish, lake fish or fish remains, but it echoes the keystone interaction between bear and salmon in North America (Levi et al., 2020). Finally, ant consumption may reduce local defense of ants to aphids, beneficial to plants (Grinath et al., 2015).

Part of our diet results could also be explained by our metabarcoding approach and the choice of the markers. The combined use of markers such as trnl and rbcL for plant items could have improved our results (Botha et al., 2024) and some of the plants consumed may be missed, as shown in a previous study in Asia (Nawaz et al., 2019). However, in this study, we were particularly cautious using very fresh faeces, but also with our assignment methods, the read threshold and the use of one parsimonious taxonomic level, contrasting with other studies (García-Rodríguez et al., 2021b; Nawaz et al., 2019). For example, using the Inse01 marker, García-Rodríguez et al. (2021b) identified 48 taxa, most of them being coprophagous insects (i.e. potential sample contamination). However, the use of such an arbitrary read threshold may be also a source of bias within and among studies (Drake et al., 2022). Furthermore, the use of different taxonomic levels to describe the diet also raises concerns, with artificial segregation or similarity among faeces or in the functional interpretation of the diet. In fact, the genus level is more sensitive to the reference database and the marker resolution than the family level, which can at the same time bias the results and provide robust functional information of the diet. Metabarcoding of faecal eDNA also bears limitations to estimate the amount of each food item, a metric relevant to describe the diet (Bojarska and Selva, 2012). A trade-off would probably be to combine metabarcoding and coproscopic

approaches to obtain more precise diet information.

Our study highlighted within one population various findings from different studies and sites, meaning a plant-based diet with sexual and BEP differences. The use of BEP that are more related to habitat use and animal movement may favour among-site comparisons for this worldwide distributed species, and it could be used for other species with a well-defined biological cycle. We gained knowledge on the important diversity of fungi consumed, a cryptic food item with potential ecological implications, suggesting the need to include them in future brown bear diet studies. Our detailed diet description according to sex and age-class also means that conservation programmes for brown bear could be better framed by focusing on key resources, which depend on climate and land use and may thus shift with global change for this opportunistic species (Lucas et al., 2025). In this context, the differences observed in the diet between sexes or BEP may also be altered with climate change and food distribution variation (Lucas et al., 2025). Moreover a thorough understanding of trophic and associated engineering interactions appears crucial to understand ecosystem functioning and thus effectively conserved ecosystems, be it for brown bear or other species.

Supplementary data to this article can be found online at https://doi.org/10.1016/j.biocon.2025.111548.

### CRediT authorship contribution statement

**Grégoire Pauly:** Writing – review & editing, Writing – original draft, Visualization, Validation, Project administration, Methodology, Formal analysis, Data curation, Conceptualization. **Mélanie Roy:** Writing – review & editing, Visualization, Validation, Supervision, Project administration, Methodology, Data curation, Conceptualization. **Cécile Vanpé:** Writing – review & editing, Validation, Supervision, Project administration, Methodology, Funding acquisition, Conceptualization. **Jérôme Sentilles:** Writing – review & editing, Investigation, Conceptualization. **Pierre-Yves Quenette:** Funding acquisition, Conceptualization. **Anne-Sophie Benoiston:** Writing – review & editing, Validation, Data curation. **Lucie Moreau:** Validation, Investigation. **Amaia Iribar:** Writing – review & editing, Validation, Data curation. **Tanguy Daufresne:** Writing – review & editing, Validation, Supervision, Project administration, Methodology, Funding acquisition, Conceptualization. **Christophe Baltzinger:** Writing – review & editing, Visualization, Validation, Supervision, Project administration, Methodology, Funding acquisition, Conceptualization.

### Declaration of competing interest

The authors have no conflict of interest to declare.

### Acknowledgements

This study was financed by the agreement N°OFB-22-1125 of ‘Office français de la biodiversité’ with INRAE and the agreement N°OFB.22.0773 and N°OFB-23-0498 with the CNRS. A warm thanks to the ‘Réseau Ours Brun’ (Brown Bear Network) for their help in finding faeces.

### Data availability

The data used in this study are available in data.inrae.gouv.fr with the name ‘Do sex, age or ecological needs shape an endangered Brown Bear population diet? New insights from faecal metabarcoding.’

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