# Moult is associated with higher diversity of food items in the diet of Common Bulbuls (Pycnonotus barbatus) in Cameroon

Crinan Jarrett, Chima J Nwaogu, Christian N Tchana, Michelle F M Kamkeng, Alma L S Quiñones, Monica C Olguin-villa, Barbara Helm, Luke L Powell, Andreanna J Welch

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Crinan Jarrett, Chima J Nwaogu, Christian N Tchana, Michelle F M Kamkeng, Alma L S Quiñones, et al.. Moult is associated with higher diversity of food items in the diet of Common Bulbuls (Pycnonotus barbatus) in Cameroon. Ibis, 2025, 167 (3), pp.803 - 811. 10.1111/ibi.13395. hal-05306550

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IBIS

international journal of avian science

Ibis (2025), **167**, 803–811

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doi: 10.1111/ibi.13395

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Short Communication

# Moult is associated with higher diversity of food items in the diet of Common Bulbuls (*Pycnonotus barbatus*) in Cameroon

CRINAN JARRETT,*¹,²,³ ID CHIMA J. NWAOGU,¹,⁴,⁵

CHRISTIAN N. TCHANA,³,⁶,⁷

MICHELLE F. M. KAMKENG,³,⁷

ALMA L. S. QUIÑONES,³,⁸

MONICA C. OLGUIN-VILLA,⁸ BARBARA HELM,¹,²

LUKE L. POWELL²,³,⁹,¹⁰ & ANDREANNA J. WELCH³,⁸

¹Swiss Ornithological Institute, Bird Migration Unit, Seerose 1, Sempach, CH-6204, Switzerland

²School of Biodiversity, One Health and Veterinary Medicine, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, G12 8QQ, UK

³Biodiversity Initiative, 1400 Townsend Drive, Houghton, MI, 49931-1295, USA

⁴A.P. Leventis Ornithological Research Institute, PO Box 13404, Laminga, 930001, Jos-East LGA, Plateau State, Nigeria

⁵FitzPatrick Institute of African Ornithology, DST-NRF Centre of Excellence, University of Cape Town, Rondebosch, Cape Town, 7701, South Africa

⁶Department of Biology-Ecology, Faculty of Sciences, University of Montpellier, Montpellier, 34095, France

⁷Department of Animal Biology and Physiology, Faculty of Sciences, University of Yaoundé 1, PO Box 812, Yaoundé, Cameroon

⁸Department of Biosciences, Durham University, South Road, Durham, DH1 3LE, UK

⁹CIBIO-InBIO, Research Centre in Biodiversity and Genetic Resources, University of Porto, Campus de Vairão, Vairão, 4485-661, Portugal

¹⁰BIOPOLIS Program in Genomics, Biodiversity and Land Planning, CIBIO, Campus de Vairão, Vairão, 4485-661, Portugal

Moult is an essential part of birds' annual cycle, and requires sufficient intake of energy and nutrients, but we understand little about how such nutritional

requirements are met by wild birds. Using faecal metabarcoding, we analysed the diet of moulting and non-moulting Common Bulbuls *Pycnonotus barbatus*, captured in Cameroon. We found that the diet of moulting birds was more diverse than that of non-moulting birds, with approximately 1.5 times more arthropod and plant taxa, plus evidence of dietary composition differences between groups. Our results provide novel insight of a likely strategy used by wild birds to fuel the essential self-maintenance task of moult.

Keywords: arthropod, breeding, Common Bulbul, diet, fruit, metabarcoding, moult, seasonality.

INTRODUCTION

Moult, defined as the replacement of feather material and accompanying tissues, is an essential process in the life cycle of all birds (Jenni & Winkler 2020). However, moult has been widely overlooked in many ecological studies, which more commonly focus on breeding or migration (Jenni & Winkler 2020). Successful moult in birds increases survival prospects (Class & Moore 2013, Jenni & Winkler 2020), and yet the process of moult imposes important costs on birds, including the direct energetic cost of feather and tissue growth, and indirect costs associated with lower thermoregulatory capacity and reduced flight capacity during moult (Murphy & King 1992, Jenni & Winkler 2020). Birds must minimize such costs by appropriately timing moult in their annual cycle, and through sufficient energy and nutrient intake in their diet (Murphy & King 1992).

Several studies have shown that food shortage during moult can result in depletion of body reserves (Murphy et al. 1988), lower quality of newly grown feathers (Hill 2000, Pap et al. 2008), increased shedding intervals of feathers (Murphy et al. 1988) and reduced feather growth rates (Swaddle & Witter 1997). The limited information available on birds moulting in the wild suggests that birds in habitats with poorer food sources may grow poorer quality feathers or moult more slowly (Freed & Cann 2012, Barshep et al. 2013, Hernández-Palma & Stouffer 2018). Such changes in moult parameters driven by food limitation have important fitness implications: for instance, lower feather quality means that new feathers will abrade quicker, resulting in reduced flight capacity, and a reduced feather growth rate means an extended period of increased vulnerability to predation (Jenni & Winkler 2020).

In addition to simple food intake, birds may require specific nutrients for moult, including protein (Pap et al. 2008), sulphur amino acids, which are important components of keratin (Murphy & King 1984),

<footnote>*Corresponding author.
Email: crinan.jarrett@gmail.com</footnote>
carotenoids, which contribute to feather coloration (Saks *et al.* 2003), and flavonoids, anti-oxidants that counter-
act the increased oxidative stress incurred during moult (Cecere *et al.* 2016). These nutrients must be acquired
by wild birds through their diet, yet we currently know
little about how birds may adjust their dietary composi-
tion to meet the food and nutrient requirements of
moult.

Food is clearly important for moult but, paradoxi-
cally, birds fly poorly during moult because of growing
feathers. Consequently, they may need to remain incon-
spicuous and avoid far-ranging foraging, which could
result in a reduction in diet diversity in moulting birds
(Vega-Rivera *et al.* 1998, Jenni & Winkler 2020). There-
fore, there are two conflicting hypotheses concerning
the diet of birds during moult: first, birds increase the
breadth and diversity of their diet to meet the height-
ened nutrient and energy requirements of moult (nutri-
tion hypothesis). Second, moulting birds have a less
diverse diet due to restrictions in foraging (flight impair-
ment hypothesis). Here, we tested these two hypotheses
using diet metabarcoding data from a wild Afrotropical
bird, the Common Bulbul *Pycnonotus barbatus*.

Diet metabarcoding consists of the identification of
prey taxa from DNA extracted from faecal matter (Hoe-
nig et al. 2022). DNA extracted from faecal samples is
amplified using primers that target specific taxonomic
groups (e.g. arthropods, vertebrates, plants) and then
sequenced. Dietary sequences are matched to published
sequences of known organisms. Depending on the qual-
ity of the match, dietary sequences (called Operational
Taxonomic Units, or OTUs) are assigned a given taxon-
omy; for nearly perfect matches, the assignment may be
to species level, while for poorer matches it may be
genus, family, order, etc. Therefore, diet metabarcoding
generates a dataset of prey items contained within a
given faecal sample, identified at varying levels of taxo-
nomic resolution. Such datasets can provide insight not
only into the diversity of predators' diets, but also into
diet composition (e.g. relative abundance of different
OTUs; Deagle et al. 2019). Here we aimed to compare
diet diversity and composition between moulting and
non-moulting Common Bulbul s.

The Common Bulbul as a study species allowed us to
overcome the difficulty of disentangling the influences of
life-cycle stage and phenology on diet, which is a com-
mon issue in studies from temperate environments
(Jenni & Winkler 2020). As most temperate passerines
moult within a narrow time-window, their diet could be
a result of life-cycle requirements or of the availability
of food in the environment. For Common Bulbul s,
moult is somewhat seasonal, but it is nonetheless possi-
ble to find moulting bulbuls throughout the year
(Nwaogu et al. 2019). Hence, we could compare diet in
moulting versus non-moulting birds without the con-
founding effect of seasonality in food availability. We

used diet metabarcoding to test whether diet diversity
increased (nutrition hypothesis) or decreased (flight
impairment hypothesis) during moult. Additionally, we
tested for differences in diet composition between
moulting and non-moulting birds, including relative
abundance of arthropods versus fruit.

METHODS

Study sites

The data for this study were collected in Elat Farm
(Cameroon: 3°54′12″N, 11°42′59″E). The farm itself is
planted with cocoa trees *Theobroma cacao*, intercropped
with some fruit trees such as avocado *Persea americana*
and citrus (genus *Citrus*). The surrounding habitat is a
mix of natural vegetation and agricultural land (Jarrett
*et al.* 2021). Approximately once per month, between
March 2021 and March 2022 (for precise dates see
Appendix S1), we visited the site and captured Com-
mon Bulbuls.

Bird data collection

During each visit we captured Common Bulbuls using
mist-nets. Between 10 and 14 mist-nets (12 m long)
were set up at dawn, and left open for approximately
6 h. We checked nets every 20 min. All bulbuls were
brought back to the processing station, where they were
ringed. Then, we scored moult using the EURING sys-
tem, where each of the 19 flight feathers (10 primaries,
9 secondaries) of the right wing are given a score
between 0 and 5 (Euring 2010). A score of 0 indicates
an old non-moulted feather, scores 1-4 indicate progres-
sively growing feathers, and 5 indicates a fully newly
grown feather. Then, we added up the score across the
19 flight feathers to give a total moult score between 0
(all old feathers) and 95 (all new feathers). We then
considered birds with a moult score > 0 and < 95 as
moulting. Although our focus was on moulting birds,
we also recorded breeding activity as this could influence
diet selection. We scored brood patch (BP) and cloacal
protuberance (CP) using EURING standard codes (Eur-
ing 2010). We considered male birds with an obvious
CP swelling and female birds with BP score 1-4 as
actively breeding, and all other individuals as not
actively breeding.

We collected faecal samples for diet analyses by plac-
ing captured individuals into a single-use paper bag that
was placed inside a regular cloth bird bag. Cloth bags
were washed between uses in cold water with bleach
(~1% concentration). After the bird was processed, the
paper bag was checked for faecal material. We collected
faecal material directly from the bag into a tube contain-
ing Longmire buffer with 2% sodium dodecyl sulphate
(Longmire *et al.* 1997). Samples were kept at room temperature during the field visit (a few days), and then stored in the freezer at -20°C.

## Diet metabarcoding

We successfully extracted DNA from 38 faecal samples collected during the 2021/22 fieldwork. We supplemented these with an additional 10 samples collected during previous field campaigns (see Appendix S1 and Jarrett *et al.* 2021), two extraction controls (containing no faecal matter) and eight polymerase chain reaction (PCR) controls. We used 0.06–0.08 g of faecal matter (wet weight) and followed a modified protocol of the EZNA Tissue Extraction kit (Appendix S2). After extraction, three to five replicates of PCR were conducted for each sample to identify arthropod and plant diet items. FWH2 primers (Vamos *et al.* 2017) were used for arthropod diet items, and ch primers were used for plant diet items (Taberlet *et al.* 2007; Appendix S2). For each sample, the replicate PCR products were pooled and cleaned. A second PCR was conducted using primers complementary to the overhang sequence and containing an individual specific pair of indices. Samples were then bead cleaned, quantified, pooled, and sequenced on the Illumina MiSeq platform (Appendix S2).

Raw sequences were processed following the methods described in Jarrett *et al.* (2020) (Appendix S2). Sequences were clustered into molecular OTUs at the 97% identity level, and only OTUs with five or more sequences were retained. We assigned taxonomy via a BLAST search of the GenBank NT database (Appendix S2): for matches with ≥95% identity we assigned order-level taxonomy, for ≥96.5% we assigned family-level, and for ≥98% we assigned genus- and species-level taxonomy (Aizpurua *et al.* 2018, Jarrett *et al.* 2020). After taxonomic assignment, the arthropod dataset contained 1651 OTUs, and the plant dataset contained 812 OTUs. However, many of these OTUs occurred at low numbers of reads, or in some cases corresponded to non-target taxa (e.g. birds). Consequently, we performed several data cleaning steps, including removing OTUs that occurred frequently in control samples (Appendix S2).

## Data analyses

After laboratory analyses and data cleaning, our diet dataset consisted of 19 samples from moulting birds, 22 from non-moulting non-breeding birds, 4 from breeding birds and 3 from breeding & moulting birds. Hereafter, we use the following terms to describe life-cycle stages: 'moulting-only' means moulting and not breeding, 'non-moulting non-breeding' means not moulting or breeding, 'breeding-only' means breeding and not

moulting, and 'breeding and moulting' implies both simultaneously. Given the paucity of detailed diet data from tropical birds, we present results from the full dataset throughout the paper; however, for statistical analyses we consider just moulting-only and non-moulting non-breeding birds (i.e. results from other groups are purely descriptive due to sample size limitations). Importantly, samples from moulting-only and non-moulting non-breeding birds were spread throughout the year (Appendix S1).

We conducted all analyses using RStudio version 2023.3.0.386 in the R computing environment (R Core Team 2023). First, to test differences in overall diversity of diet between moulting-only and non-moulting non-breeding birds, we considered richness of OTUs. This is similar to considering species richness of the diet, though OTUs may not always map exactly to species identities (Cristescu 2014). We estimated OTU richness using Hill numbers with up to double the reference sample, which is an effective way to robustly test for differences between communities (extrapolation to 40 samples, from 19 moulting-only and 22 non-moulting non-breeding; Chao *et al.* 2014, Hsieh *et al.* 2016). We used the package iNEXT (Hsieh *et al.* 2016) for this analysis.

To test whether Common Bulbuls increase fruit or arthropod consumption during moulting, we compared the number of OTUs of plants and arthropods detected in each sample. Given that all samples for each primer were processed simultaneously and identically, number of OTUs should give a comparable representation of diversity of arthropod and plant items in the diet (Deagle *et al.* 2019). We modelled number of OTUs using a Generalized Linear Mixed Model with a negative binomial distribution, after detecting overdispersion in a Poisson model using the package DHARMa (Hartig 2022). As explanatory variables, we included an interaction between diet type (plant or arthropod) and activity (moulting-only or non-moulting non-breeding), and a random effect for collection session (month of year) to account for potential similarities between samples collected on similar dates. The interaction term captured differential consumption of plant or arthropod items with life-cycle stage. We used the package 'emmeans' (Lenth 2023) to compute estimated marginal means and confidence intervals and we calculated effect sizes using eta-squared ($\eta^2$) in the package 'effectsize' (Ben-Shachar *et al.* 2020).

To test the differences between diet composition of birds according to life-cycle activity, we used Generalized Linear Models for multivariate data using the function 'manyglm' from the package 'mvabund' (Wang *et al.* 2022). We made this analysis at two levels: first, for overall differences in diet composition, we built a model at the OTU level, considering presence or absence of each OTU in each sample, using a binomial distribution. Then, to examine which prey orders
showed most contrasts between moulting-only and non-moulting non-breeding birds, we summarized data at the order level by considering the number of OTUs of each order occurring in each sample. For this model we used a negative binomial distribution. In both models, we included activity (moulting-only or non-moulting non-breeding) and collection session (month of year) as explanatory variables. We tested for significance of the explanatory variables using the function 'anova.manyglm'. In the order-level model, we used univariate tests from the same function to assess which prey orders were driving differences in diet between life-cycle stages.

## RESULTS

After filtering, the datasets included 297 arthropod OTUs and 41 plant OTUs. For arthropod OTUs, 23% were identified to order level, 22% to family, 15% to genus and 13% to species level. For plant OTUs, 95% were identified to order and family level, 59% to genus and 24% to species level. The diet items occurring at highest frequency across all birds corresponded to unidentified arthropod and plant orders. Considering the OTUs identified to at least order level, the most common arthropods were *Pseudacanthotermes militaris* (Blattodea: Termitidae; in 17 samples), *Pyralidae* sp. (Lepidoptera; in 14 samples) and other termite species (*Acanthotermes acanthothorax* and *Pseudocanthotermes* sp.; in 10 samples). For plants, the most common OTUs were from the family Musaceae (in eight samples) and the genus *Macaranga* (in five samples).

Total number of OTUs found across samples was higher for moulting-only birds than non-moulting non-breeding birds, and this difference was maintained after extrapolation to double the existing sample size (moulting-only: 303 (95% CI = 267–339), non-moulting non-breeding: 206 (95% CI = 169–243); Fig. 1). Estimated total diet richness was 481 (95% CI = 367–594) OTUs for moulting-only birds and 377 (95% CI = 255–499) OTUs for non-moulting non-breeding birds. On average, samples contained 12.7 arthropod OTUs (± 7.6 standard deviation (sd)) and 2.2 plant OTUs (± 2.5 sd). Mean number of OTUs per sample of plants and arthropods was higher in moulting-only birds when compared with non-moulting non-breeding birds, with marginal statistical significance (*P* = 0.06, *η*² = 0.09 (0.01–0.23); Table 1; Fig. 2). The interaction between diet type (plant or arthropod) and life-cycle stage was not significant, indicating that the difference in number of OTUs in moulting-only versus non-moulting non-breeding birds was consistent across the two diet types (Table 1; Fig. 2).

Diet composition varied significantly between moulting-only and non-moulting non-breeding birds

<figure><img src="image_5.png" /><figcaption>**Figure 1.** Diversity of Operational Taxonomic Units (OTUs) in the diet of moulting-only and non-moulting non-breeding Common Bulbuls as a function of number of samples. Curves show OTU diversity of moulting-only (green) and non-moulting non-breeding (brown) birds. Solid lines show the diversity of OTUs in the collected samples, and dashed lines show estimated diversity of OTUs after extrapolating up to 40 samples (approximately double the existing sample size).</figcaption></figure>

both at the OTU and order levels (Residual df = 39, deviance = 481.4, *P* = 0.04; Residual df = 39, deviance = 55.1, *P* = 0.02, respectively; Fig. 3). The main orders driving this difference were Blattodea, Malpighiales and Sapindales, which were more common in moulting-only birds (Fig. 3; Appendix S3). Additionally, samples from moulting-only birds had a higher abundance of unidentified arthropod orders. In contrast, Hymenoptera were significantly more abundant in non-moulting non-breeding birds (Appendix S3).

## DISCUSSION

Moulting Common Bulbuls in our study system consumed a higher total diversity of dietary items compared with non-moulting birds, supporting the hypothesis that during moult, birds diversify their diet to meet energetic and nutritional requirements (Jenni & Winkler 2020). Under experimental settings, maximum mass gain was attained by birds fed a combination of insects and plants, rather than one or the other exclusively (Bairlein & Gwinner 1994, Simon et al. 2023). A similar process could occur in our study system, whereby bulbuls achieve better body condition with a diverse diet, thus facilitating moult (Appendix S4). The higher diet diversity of moulting birds suggests that the hypothesis of reduced foraging capacity of birds during moult due to flight impairment may not apply, at least in our system.

Bulbuls in our study system consumed both arthropods and fruit throughout the annual cycle. The overall
<table><caption>**Table 1.** Output from a generalized linear mixed model investigating the variation in number of Operational Taxonomic Units as a function of diet type (plant, arthropod) and life-cycle event (moulting-only, non-moulting non-breeding). As a measure of effect size, we calculated partial eta-squared ($\eta^2$).</caption><thead><tr><th>Fixed effect</th><th>Estimate</th><th>Standard error</th><th>P-value</th><th>η<sup>2</sup></th></tr></thead><tbody><tr><td>Intercept (arthropod, moulting-only)</td><td>2.63</td><td>0.16</td><td>&lt;0.001</td><td></td></tr><tr><td>Diet type (plant)</td><td>-1.60</td><td>0.21</td><td>&lt;0.001</td><td>0.62 (0.48-0.71)</td></tr><tr><td>Life-cycle stage (non-moulting non-breeding)</td><td>-0.35</td><td>0.19</td><td>0.06</td><td>0.09 (0.01-0.23)</td></tr><tr><td>Diet type*Life-cycle stage</td><td>-0.31</td><td>0.31</td><td>0.31</td><td>0.01 (0.00-0.10)</td></tr></tbody></table>

<figure><img src="image_6.png" /><figcaption>**Figure 2.** Number of arthropod (brown) and plant (turquoise) Operational Taxonomic Units (OTUs) in the diet of Common Bulbul across life-cycle stages. Dots represent raw data, presented for all life-cycle stages, and triangles and bars are mean estimates and 95% confidence intervals from the Generalized Linear Mixed Model (GLMER), applied only to data from moulting-only and non-moulting non-breeding birds, which had sufficient sample size.</figcaption></figure>

diversity of their diet (297 arthropod and 41 plant OTUs) was comparable with other dietary studies on birds (Jarrett *et al.* 2020, Cabodevilla *et al.* 2021, Garfinkel *et al.* 2022), and suggests a varied diet across the arthropod and plant phyla, from caterpillars to termites, spiders, bugs and several fruits. Our results suggest higher diversity in arthropods than plants in the diet, with almost five times more arthropod OTUs than plant OTUs in our samples. This difference could reflect the ecology of our system: we captured bulbuls in an agroforestry habitat, which consisted mostly of cocoa trees (order Malvales, detected in samples), intercropped with some fruiting trees (including detected orders Sapindales – oranges, Zingiberales – bananas, Myrtales – guava; Ferreira *et al.* 2023). The plantation in question did not therefore have a large diversity of fruiting trees. Additionally, given that tree species in the system fruit

seasonally (Jarrett *et al.* 2024), birds may simply exploit the few species with fruit available at the time. Finally, it is important to acknowledge possible technical reasons behind the lower diversity of plants in the diet, including primer efficiency, varying availability of reference sequences and other issues during sample processing.

We found support for different diet composition between moulting and non-moulting birds (Fig. 3). This difference in composition appeared to be driven by a lower abundance of Hymenoptera, and a higher abundance of Blattodea and unidentified arthropods in the diet of moulting birds, as well as occurrence (albeit at low frequencies) of multiple plant orders. Within hymenopterans, the vast majority of OTUs corresponded to ants (family Formicidae, including genera *Euponera*, *Cre-matogaster* and *Tetraponera*), which, based on previous studies, are among the most abundant groups in the system (Jarrett *et al.* 2023). Ants, however, may not constitute rich sources of macro-nutrients; in a study comparing the nutritional value of different arthropod orders, ants ranked last in crude protein content (Razeng & Watson 2015). Therefore, it is possible that during moulting, when protein requirements are higher, bulbuls switch from the common and easily foraged ants to alternative food items. Blattodea (termites and cockroaches), more frequently consumed by moulting birds, are higher in protein than Hymenoptera, and protein-rich foods may additionally be a source of sulphur amino acids, which are important for the moulting (Razeng & Watson 2015). Lepidoptera, which were found in all our samples at high frequencies, and Blattodea, are also high in lipids, which may facilitate the maintenance of body condition (Bell 1990, Razeng & Watson 2015) (Appendix S4).

For plant diet items, our data indicate that bulbuls, especially moulting individuals, consume a wide range of plant items but at low frequencies (33 OTUs for moulting birds). Our results may indicate a preference for fruit in moulting birds, perhaps because fruit is rich in lipids and carbohydrates and can therefore support the energetic demands of moulting (Bairlein & Gwinner 1994). Indeed, an experimental study showed that bulbuls fed a fruit diet started moulting earlier than bulbuls fed insects (Nwaogu *et al.* 2020). A similar process occurs in
<figure><img src="image_7.png" /><figcaption>**Figure 3.** Number of Operational Taxonomic Units (OTUs) of arthropod (brown) and plant (turquoise) orders in the diet of Common Bulbuls in Cameroon, according to life-cycle stage.</figcaption></figure>

migratory birds, with a switch to a more frugivorous diet to increase body reserves before migration (Eggers 2000, Iwajomo et al. 2017). Additionally, fruits constitute a source of nutrients such as carotenoids and flavonoids, which are important for moult (Cecere et al. 2016). Orders Malpighiales and Sapindales were consumed by ~25% of moulting birds (i.e. five samples), which is the highest frequency we found. In our diet data, these orders were represented by the taxa *Macaranga* (known for its association with ants and other insects; Fiala et al. 1994), *Mangifera* (which includes mango *Mangifera indica*), Burseraceae (which includes African plum *Dacryodes edulis*) and Rutaceae (which includes citrus trees). These fruiting species constitute some of the most common trees in our study system, aside from the cocoa trees themselves, and provide evidence that birds use such intercropped shade trees for foraging (Bennett et al. 2021, Jarrett et al. 2021). Hence, mixed agroforestry systems containing a range of tree species may

enable moulting birds to achieve a diverse and nutritious diet.

We detected cocoa DNA in many samples but at low read abundance, so that after filtering the OTU corresponding to cocoa only occurred in three samples. This indicates that birds are unlikely to be directly consuming cocoa fruits, which makes sense given their tough outer shells, and perhaps they are just acquiring low levels of DNA in their faeces through secondary consumption (i.e. consumption of arthropods that themselves feed on cocoa) or environmental contamination (Sheppard et al. 2005). Indeed, a drawback of diet metabarcoding is the difficulty in identifying which OTUs may occur through secondary consumption. However, in our system, field observations of bulbuls eating similar fruit species support our assumption that plant DNA in diet samples comes through fruit consumption (Nwaogu 2019, Nwaogu et al. 2020). An additional important drawback of metabarcoding methods,
especially when applied to tropical regions, is the limited number of sequenced prey items. In our study, this was reflected in the taxonomic assignment rates of our arthropod data, which were lower than those from studies conducted in the northern hemisphere (Jarrett *et al. 2020*, Garfinkel *et al. 2022*). This is probably a result of the high diversity of Afrotropical arthropod species coupled with the reduced barcoding effort. To maximize the benefit of future diet metabarcoding studies in these areas, investment is needed to barcode arthropod taxa particularly in the Afrotropics.

In conclusion, we provide novel insight into the differences in diet between moulting and non-moulting birds in the wild in an Afrotropical habitat. We show that birds may meet the nutritional requirements of moult by increasing the diversity of their diet, including both plants and arthropods. This diversification strategy suggests that birds, even relatively generalist species, may suffer from arthropod declines and low plant diversity arising from increasingly intensified agricultural land-uses (Schulze *et al. 2004*, Bisseleua *et al. 2013*), and that they may be especially vulnerable during periods of increased food and nutrient requirements, such as moult.

We would like to thank Diogo Ferreira and Lara Gross for contributing to metabarcoding data filtering and the owners and managers of the land in Elat. LLP was supported via the European Union's Horizon 2020 research and innovation programme under grant agreement 854 248 and an EU-funded Marie Curie Fellowship Chocolate4Life. CJN was supported by the Schifferli Fellowship of the Swiss Ornithological Institute and the Carnegie Developing Emerging Academic Leaders Fellowship of the University of Cape Town.

## AUTHOR CONTRIBUTIONS

**Crinan Jarrett:** Conceptualization; writing – original draft; methodology; formal analysis; supervision; investigation; data curation. **Chima J. Nwaogu:** Conceptualization; methodology; writing – review and editing; project administration; supervision; data curation. **Christian N. Tchana:** Writing – review and editing; data curation; investigation. **Michelle F. M. Kamkeng:** Writing – review and editing; investigation. **Alma L. S. Quiñones:** Investigation; methodology; validation; writing – review and editing. **Monica C. Olguin-Villa:** Investigation; writing – review and editing; validation; methodology. **Barbara Helm:** Conceptualization; investigation; writing – review and editing; supervision; project administration; methodology. **Luke L. Powell:** Conceptualization; methodology; project administration; writing – review and editing. **Andreanna J. Welch:** Conceptualization; investigation; methodology; validation; writing – review and editing; project administration; supervision.

## CONFLICT OF INTEREST

The authors declare no conflict of interest.

## DATA AVAILABILITY STATEMENT

The data that support the findings of this study are available from the corresponding author upon reasonable request.

## ETHICAL NOTE

Animals were captured and handled in accordance with Durham University's Animal Welfare Ethical Review Board (careBIOL-2019-07-10T12:06:13-rgnr69). In Cameroon, no specific permissions were required to conduct activities, as this project operated under the Host Country Agreement between the Government of Cameroon and the International Institute of Tropical Agriculture (1997).

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Received 7 March 2024;
Revision 12 September 2024;
revision accepted 22 January 2025.
Associate Editor: Javier Pérez-Tris

## SUPPORTING INFORMATION

Additional supporting information may be found online in the Supporting Information section at the end of the article.

Appendix S1. Details of faecal samples used for analyses.

Appendix S2. Diet metabarcoding methods.

Appendix S3. Order-level differences in diet composition.

Appendix S4. Body mass analyses.