Seasonal variation, habitat protection, and disturbance influence bird assemblages in a tropical Guinea savannah

Seasonality and anthropogenic disturbance are key drivers of avian community structure in tropical savannah ecosystems, yet their effects on taxonomic and functional diversity across protected and unprotected landscapes remain insufficiently understood, especially in Nigeria. We examined how seasonal variation and human disturbance shape bird assemblages at different site protection statuses in the Nigerian Guinea savannah. We conducted point count surveys across four stratified habitats (forest, woodland, grassland, and riverside) at four sites in the Guinea savannah of Nigeria, covering dry and wet seasons, and protected and unprotected sites. Patterns in taxonomic richness, diversity, functional richness, and functional diversity were analyzed alongside quantified indices of anthropogenic disturbance. During the wet season, taxonomic richness and diversity were higher, whereas functional metrics, especially functional richness, were lower. Unprotected sites supported higher taxonomic richness and diversity, particularly in the dry season. In contrast, protected sites, despite lower species richness, retained broader functional trait representation. An increase in anthropogenic disturbance resulted in declines in both taxonomic and functional richness across all sites, with particularly steep losses in functional richness within protected areas. We provide evidence of a complex influence of seasonality, protection status, and anthropogenic disturbance on avian communities in the Nigerian Guinea savannah, revealing notable divergences between taxonomic and functional diversity metrics. Higher wet-season taxonomic diversity and richness, with contrasting functional richness and diversity, reflect increased resource availability and favourable breeding conditions and a decoupling between species richness and functional roles, respectively. Observable higher taxonomic metrics and yet a high functional redundancy at the unprotected sites may indicate dominance by disturbance-tolerant generalist species with overlapping ecological roles. Furthermore, the observable steeper decline in functional richness within protected sites highlights that these sites are more affected by disturbance than the more human-modified unprotected sites. Our findings demonstrate that reliance on taxonomic metrics alone may obscure functional erosion within bird communities and emphasize the need for landscape management and monitoring focused on functional and taxonomic dimensions of biodiversity coupled with the influence of seasonal dynamics and disturbance to ensure long−term ecosystem resilience.

Seasonal dynamics are a fundamental driver of biodiversity patterns, particularly in tropical ecosystems where fluctuations in rainfall, temperature, and vegetation phenology regulate resource availability and habitat structure. In avian communities, these seasonal changes influence food supply, breeding opportunities, and movement patterns, thereby shaping species composition, abundance, and community structure across time (Burns et al., 2021; Ehlers Smith et al., 2018; Yabuhara et al., 2019). Consequently, understanding how bird assemblages respond to seasonal variability is essential for predicting biodiversity responses to environmental changes and for informing adaptive conservation strategies.

Beyond natural seasonal variation, anthropogenic pressures increasingly interact with ecological processes to influence biodiversity patterns. Activities such as bush burning, livestock grazing, agricultural expansion, road construction, and human and vehicular traffic alter habitat structure, reduce resource availability, and impose environmental filtering on ecological communities (Danmallam et al., 2024; Matthew et al., 2024; Mouillot et al., 2013). Environmental filtering typically favours generalist and disturbance-tolerant species while disproportionately excluding specialist species, leading to shifts not only in species richness but also in the functional composition of communities (Awoyemi et al., 2024; Iniunam et al., 2025; Ngila et al., 2024). As a result, biodiversity assessments that rely solely on taxonomic metrics may overlook important changes in ecosystem functioning (Fraixedas et al., 2020).

Functional diversity, which captures the range, value, and distribution of species’ ecological traits within communities, provides a more mechanistic understanding of how ecosystems respond to environmental changes (Díaz et al., 2013). While taxonomic richness reflects the number of species present, functional richness reveals how species contribute to ecosystem processes and resilience. Disturbance-driven communities may exhibit high species richness but low functional richness due to redundancy among generalist species, whereas more intact habitats often support functionally distinct species that contribute unique ecological roles (Cazalis et al., 2020; Mouillot et al., 2013). Integrating taxonomic and functional metrics is therefore critical for a comprehensive evaluation of biodiversity patterns across landscapes (Díaz et al., 2013; Mouillot et al., 2013).

Protected areas are widely regarded as the cornerstone of biodiversity conservation, as they are expected to buffer ecosystems against anthropogenic pressures and maintain higher levels of biodiversity relative to unprotected landscapes (Pulido-Chadid et al., 2023). However, increasing evidence suggests that protected areas are not immune to human disturbance, particularly in tropical regions where enforcement challenges and resource dependence by local communities can lead to habitat degradation (Cazalis et al., 2020; Danmallam et al., 2025). Moreover, unprotected landscapes, often characterized by varying degrees of human modification, may still retain conservation value by supporting subsets of biodiversity, including generalist and adaptable species (Rayner et al., 2014). In some cases, these landscapes may function as complementary habitats or even seasonal refugia, particularly during periods of environmental stress such as the dry season when resources become limited in more natural habitats (Ringim and Aliyu, 2018; Thomas et al., 2020).

The potential role of unprotected areas as seasonal refugia remains insufficiently explored in tropical savanna ecosystems. Seasonal resource bottlenecks may drive shifts in bird distributions, with some species temporarily utilizing human-modified landscapes that provide alternative resources such as water, food, or reduced competition (Abdullahi et al., 2025; Nsor and Obodai, 2014). Understanding whether and how bird communities redistribute across protected and unprotected habitats across seasons is therefore essential for developing landscape-scale conservation strategies that extend beyond formally protected areas.

In this study, we investigate the combined effects of seasonality, site protection status, and anthropogenic disturbance on avian communities in the Guinea savanna of Nigeria. Specifically, we: (i) compared avifaunal composition, including taxonomic and functional diversity, between protected and unprotected habitats; (ii) examine how seasonal variation influences avian assemblages across these habitats, with particular attention to the potential role of unprotected areas as seasonal refugia; and (iii) assess the influence of anthropogenic disturbance, characterized by activities such as cattle grazing, bush burning, farming, road construction, and human and vehicular traffic, on bird communities and their functional diversity. By integrating taxonomic and functional perspectives across spatial and temporal gradients, this study provides insights into the mechanisms shaping bird diversity, their functional roles and informs conservation planning in human-disturbed tropical landscapes.

Description of the study area

The study was conducted across selected locations within the Guinea savanna ecological zone of Nigeria, spanning latitudes 7°42′55.29″N to 11°05′55.62″N and longitudes 4°00′44.05″E to 8°43′53.40″E (Figure 1). This region represents a major tropical savanna system characterized by a mosaic of grasslands, woodlands, riparian forests, and freshwater bodies.

The Guinea savanna experiences two distinct seasonal regimes: a wet season (April–October) and a dry season (November–March). The mean annual precipitation ranges from approximately 900 to 1,400 mm, with peak precipitation typically occurring between July and September (Ezealor, 2002). Vegetation structure is dominated by tall grasses interspersed with scattered trees and shrubs (Ezealor, 2002). We conducted field surveys in four purposively selected sites representing both protected and unprotected landscapes within the Guinea savanna: Kainji Lake National Park (Niger State), a formally protected area managed by the National Park Service; Ahmadu Bello University campus, Zaria (Kaduna State), a semi-protected landscape with restricted access; Lokoja (Kogi State), an unprotected landscape with mixed land-use activities; and Barutein (Kwara State), an unprotected area characterized by agro-pastoral land use. These sites were selected to capture variation in protection status, habitat composition, and anthropogenic pressure across the Guinea savanna. We defined protected sites here as areas with formal conservation status or restricted access that limits human activities, whereas unprotected sites were characterized by open access and higher levels of anthropogenic disturbance, including farming, grazing, and infrastructure development. This classification enabled direct comparison of bird communities across contrasting management regimes.

Data collection

Point count surveys were conducted in 2023 and 2024. To ensure spatial representation of bird data and to avoid missing species that may prefer specific habitats, we sampled all available terrestrial habitats (forest, grassland, woodland, and locations around water bodies such as rivers, and dams or ponds) at each site. Four random point count stations were generated in ArcGIS using “random point” in each of the four habitats across the sites, resulting in a total of 64 points that were sampled. Each point was visited four times, with two visits conducted annually: one during the dry season and the other during the wet season. These points were at least 100 m apart (Dami Filibus Danjuma, 2020; Matthew et al., 2024). Birds were observed and counted at each sampling point within a 50-m radius for 10 min between 6:30 and 10:30 am (Matsuoka et al., 2014; Matthew et al., 2024). All birds observed or heard within the given radius were recorded. To minimize detection bias, we avoided sampling on rainy days (during the wet season) and windy days. We also ensured that birds were counted by only one observer who is a trained ornithologist with very good auditory and visual bird identification, and good knowledge of the birds in the study area (Awoyemi et al., 2024; Matthew et al., 2024). The 50-m observation radius at a point was adopted to minimize problems of detectability associated with increasing distance of birds from the observer (Matthew et al., 2024).

Determination of bird diversity metrics

Taxonomic richness and diversity were calculated using the “Vegan” package in R (Oksanen et al., 2026). Taxonomic richness, also known as species richness, was calculated as the number of unique species observed at a given sampling point. The accumulation of all unique species at sampling points made up the taxonomic richness of a habitat. The taxonomic diversity was the Shannon-Wiener diversity Index and calculated as a function of species richness and evenness (how evenly individuals are distributed among species, calculated from species richness and abundance data) (Shannon, 1948).

Functional richness (the number of unique functional traits in a community) and functional diversity, also known as Rao’s quadratic entropy (a function of functional traits and species relative abundance), were calculated using the “fundiversity” package in R (Grenié and Gruson, 2023). The analyses were based on a trait matrix with species as rows and continuous as well as categorical trait values as columns. Community composition was represented by a site-by-species matrix, with sites as rows and species as columns with their corresponding abundance.

A total of 13 functional traits in three functional categories of habitat specialization, mass (in grams) and diets, in addition to species abundance data, were used to calculate the functional metrics. These traits were obtained from an already compiled list in a previous study (Danmallam et al., 2025; Iniunam et al., 2025) that contained data for all the species we recorded in our study (https://www.frontiersin.org/journals/conservation-science/articles/10.3389/fcosc.2024.1503408/full#supplementary-material). The selected for their direct links to ecological functions such as scavenging, herbivory, pollination, and predation (Child et al., 2009; Lee et al., 2021). These traits provide insight into the roles birds play in ecosystem processes, including carcass disposal, landscape productivity, plant reproduction, and pest control (Danmallam et al., 2025). Omnivorous birds were grouped into the appropriate number of dietary guilds in order to avoid bias in grouping them into a single guild (Iniunam et al., 2025).

Calculation of disturbance index across sites

Human disturbance index was derived from six key anthropogenic footprint variables common in the study area. These include bush burning, road construction, farming (that involves bush clearing and tree felling before land tilling), human traffic, and vehicles. Each variable was recorded at each sampling point for the different seasons and coded as 0 and 1, where 0 represented absence and 1 represented presence. The trait matrix structure for the calculation consisted of sites as rows and disturbance variables as columns. For each point, the scaled mean value of the six disturbance variables was computed to generate a single index. A higher human disturbance index indicates greater cumulative disturbance intensity.

Data analyses

All analyses were carried out in R version 4.5.2 (R Core Team, 2025). Before running formal analysis, exploratory data analysis was conducted using specialization. Generalized linear mixed effect models (GLMM) were used to analyze all variables using the glmmTMB function in the glmmTMB package. For all models, sampling points and sampling sites were used as the random components of the model. Season, site protection status and human disturbance index were used as fixed effects. Response variables were bird diversity metrics (taxonomic richness, taxonomic diversity, functional richness and functional diversity).

Normality of the variables was checked using histograms and confirmed with the Shapiro-Wilk test of normality (Shapiro and Wilk, 1965). For taxonomic richness, which is a count variable, we used the Poisson distribution in the GLMM where the richness was normally distributed; otherwise, we used the negative binomial distribution that can handle a non-normally distributed variable. Similarly, for continuous response variables that were normally distributed, we used the Gaussian distribution, and the Gamma distribution when they were not normally distributed. All predictor variables were checked and made sure they were in the correct data class, such as numeric for a continuous variable (human disturbance index) and factor for categorical variables (Season and site protection status). Models were examined by checking for overdispersion and multicollinearity using the Performance package in R. The best models were selected based on meeting the above assumptions, in addition to having the lowest AIC values.

In addition, residuals of all the models were checked for spatial autocorrelation using Moran’s I with the Monte Carlo permutation applied at 9,999 randomizations. No significant spatial autocorrelation was observed for any model (p > 0.05), indicating the absence of spatial structure. In addition, habitat-level analysis was carried out for every response variable to check for potential confounding effects of habitat on site protection status and disturbance level. Figures were plotted from model residuals using the emmeans and ggplot2 packages. Multi-panel figures were arranged using the “cowplot” package.

The model containing the interaction terms of disturbance index and protection status was collinear, showing high variance inflation factors (VIF) values (>20) for both predictor variables. Removing the interaction terms resulted in low VIF values (< 2.5), indicating that they could be included in the same model provided their interaction terms were not considered. Although the interaction terms were removed from the model, we still wished to evaluate the impact of human disturbance on bird diversity metrics in different site status. We therefore stratified site protection status and carried out separate analyses for each site protection category. This stratification avoids redundancy of the predictor variables, eliminates collinearity problems, and clarifies the ecological meaning of each predictor, as we are still able to see the impact of human disturbance at different site protection categories.

A total of 1184 birds in 138 species were recorded in this study. Generally, the vinaceous dove (Streptopelia vinacea), red-eyed dove (Streptopelia semitorquata) and common bulbul (Pycnonotus barbatus) were the most recorded species with relative abundance of 4.9%, 4.6% and 4.6%, respectively. A few Palearctic migrant species such as the Garden Warbler (Sylvia borin), Blackcap (Sylvia atricapilla) and Common Sandpiper (Actitis hypoleucos) were recorded in the dry season. There were also records of intra-African migrant species such as the Klaas’s Cuckoo (Chrysococcyx klaas), Diederick Cuckoo (Chrysococcyx caprius), Red-chested Cuckoo (Cuculus solitarius) and African Cuckoo (Cuculus gularis).

Influence of site protection status on bird diversity metrics

Both taxonomic richness and diversity were significantly higher at unprotected sites (Richness: GLMM: Estimate = 0.221 ± 0.12, z = 2.311, p = 0.021, Figure 2a; Diversity: Estimate = 0.129 ± 0.06, z = 3.166, p = 0.002, Figure 2b). In contrast to taxonomic metrics, functional richness and diversity were lower at the unprotected sites but the differences were not sufficient to result in statistical significance (Functional richness: GLMM: Estimate = -0.016 ± 0.22, z = -0.074, p = 0.941, Figure 2c; Functional diversity: Estimate = 0.105 ± 0.14, z = -0.772, p = 0.44, Figure 2d).

Seasonal variation in species diversity metrics in relation to site protection status

Generally, the wet season recorded a higher taxonomic richness (Mean ± SD, 9.20 ± 3.12) than the dry season (Mean ± SD, 8.48 ± 2.63), and the difference was statistically significant (GLMM: Estimate = 0.201 ± 0.09, z = 2.277, p = 0.023, Figure 3a). Similarly, taxonomic diversity was significantly higher in the wet season than in the dry season (GLMM: Estimate = 0.129 ± 0.04, z = 3.169, p = 0.002, Figure 3b). The influence of season on taxonomic richness was slightly dependent on on-site protection status (season x site status: richness: Estimate = 0.221 ± 0.121, z = 1.827, p = 0.068). While the protected site showed a clear dry-to-wet season increase, the unprotected site showed a slight wet-to-dry season increase. Moreover, in the dry season taxonomic richness was lower at protected sites with a clear-cut difference compared to overlapping bars in the wet season. Taxonomic diversity showed similar seasonal patterns at both protected and unprotected sites (season x site status: Estimate = 0.101 ± 0.061, z = 1.746, p = 0.082, Figure 3b).

Functional richness was slightly lower in the wet season with no significant difference between the wet and dry seasons (GLMM: Functional richness: Estimate = -0.04 ± 0.21, z = -0.206, p = 0.836). Functional diversity was, however, significantly lower in the wet season (Estimate = -0.248 ± 0.12, z = -2.269, p = 0.023).

Functional richness was lower in both dry and wet seasons at the unprotected sites, thereby showing no significant interaction terms (season x site status: Estimate = 0.116 ± 0.3, z = 0.383, p = 0.701, Figure 3c). On the other hand, functional diversity was lower in the dry season at the unprotected site but slightly higher in the wet season at the same site (season x site status: Estimate = 0.268 ± 0.16, z = 1.726, p = 0.084, Figure 3d).

Impact of anthropogenic disturbance on bird diversity metrics

The human disturbance index ranged from 0 to 0.83, with an overall mean of 0.49± 0.25 (Mean ± SD). Disturbance level was not the same across sampling sites. There was a comparably higher mean disturbance index of 0.695± 0.09 at unprotected sites compared to 0.289 ± 0.21 at protected sites. Checks for confounding effect of habitat on site protection and disturbance index did not show significance except for the habitat × site model containing functional diversity as the response.

Impact of anthropogenic disturbance on bird diversity metrics at protected sites

At protected sites, taxonomic richness showed a weakly negative relationship with human disturbance index (GLMM: Estimate = -0.0756 ± 0.21, z = -0.355, p = 0.723, Figure 4a). Similarly, taxonomic diversity had a weakly negative relationship with disturbance index (Estimate = 0.039 ± 0.12, z = -0.319, p = 0.75, Figure 4b). Functional richness showed a significant decrease with disturbance index (Estimate = -1.118± 0.6, z = -2.032, p = 0.042, Figure 4c). In contrast, there was an observable positive but non-significant relationship of functional diversity with disturbance index (Estimate = 0.332 ± 0.3, z = 1.097, p = 0.273, Figure 4d).

Impact of anthropogenic disturbance on bird diversity metrics at unprotected sites

At unprotected sites, both taxonomic richness and diversity showed a weakly negative relationship with human disturbance index (Richness: GLMM: Estimate = -0.062 ± 0.47, z = -0.13, p = 0.897, Figure 4e; Diversity: Estimate = 0.136 ± 0.18, z = -0.737, p = 0.461, Figure 4f). Functional richness showed a weakly negative relationship with disturbance index (Estimate = -0.177 ± 1.104, z = -1.16, p = 0.873, Figure 4g). In contrast, there was an observable positive but non-significant relationship of functional diversity with disturbance index (Estimate = 1.071 ± 0.86, z = 1.246, p = 0.213, Figure 4h).

This study provides an assessment of the influence of seasonality, site protection status and anthropogenic disturbance on taxonomic and functional metrics of bird diversity in Nigerian Guinea savannah habitats. The high relative abundance of Vinaceous Dove, Red-eyed Dove and Common Bulbul observed in this study is attributed to their widespread nature and adaptability to a variety of habitats including savannah scrub, farmland and human-dominated areas. Their dominance is consistent with patterns observed in a previous study from Nigeria (Danmallam et al., 2025).

Effects of site protection status on bird communities

Comparatively, taxonomic richness and diversity were significantly higher at the unprotected sites while functional richness and diversity were only slightly lower. The observation of significantly higher taxonomic metrics at unprotected sites is contrary to general expectation that protected areas maintain more biodiversity. The effectiveness of site protection may however, be dependent on the type of habitat and even the species found in such habitat (Mouillot et al., 2013; Rayner et al., 2014). For example, overall lower species richness but higher forest dependent, canopy foragers and endemic species have been reported at protected sites compared to unprotected sites (Asefa et al., 2017; Cazalis et al., 2020). Knowledge of species composition is essential for evaluating the specific impacts of site protection on different species groups.

The higher taxonomic species richness at unprotected sites in our study may have been influenced by the presence and abundance of more generalist and disturbance-tolerant species, including scavengers, at the unprotected sites with higher disturbance indices. This is corroborated by the high relative abundance of generalist species and the lower functional species metrics recorded in this study.

While our result of higher taxonomic metrics at unprotected sites agrees with previous studies (Asefa et al., 2017; Rayner et al., 2014; Ringim and Aliyu, 2018), it is contrary to others such as Danmallam et al. (2025), who posited that protected habitats recorded higher taxonomic richness because they had lower human impacts. Essentially, the unprotected sites in our study were not exclusively homogenized like the situation in a typical urban habitat (Awoyemi et al., 2024). They were areas of varied land-use types shaped by agriculture, grazing, bush burning and to some extent human habitation, creating heterogeneous habitats that favoured more avian richness than the more intact but less heterogeneous protected sites (Padilla and Sutherland, 2022). However, this heterogeneity tends to support a variety of species that are only functionally similar as they are mostly disturbance tolerant species adapted to modified landscapes.

Seasonal differences in bird diversity

Our results present evidence that seasonality is an important driver of bird diversity in the Guinea savannah ecoregion of Nigeria. This observation is not only observable in Nigeria. Globally, seasonal changes play a major role in shaping bird phenology and assemblage (Burns et al., 2021; Fraixedas et al., 2020; Ganguly, 2025). In the Afrotropic especially, temporal variations such as seasonal changes are found to have a strong influence on the biodiversity of the region (Sumasgutner et al., 2023). We observed a significantly higher bird taxonomic richness and diversity in the wet season. This observation aligns with typical ecological expectations, as rainfall enhances food availability, vegetation structure, and breeding opportunities for many species. However, essentially, the dry season may have recorded lower richness and diversity because it presents both physiological and habitat limitation to birds. For example, in the dry season, in order to avoid stress, birds may reduce their activities including vocalization (Budka et al., 2023), resulting in lower detectability. Also, as vegetations are dry, and water becomes scarce in most cases, suitable habitats become limited and birds are mostly concentrated around few suitable habitats (Babura, 2022).

While our observation of higher taxonomic richness and diversity in the wet season agrees with many reports (Awash and Tekalign, 2023; Nsor and Obodai, 2014; Salim et al., 2025), it contradicts the patterns found in some reports (Ringim and Aliyu, 2018; Thomas et al., 2020). This contradiction may be due to differences and peculiarities of habitats. For example, a seasonal study of understory birds in seasonally flooded forests in Brazil, recorded a higher diversity in the dry season. During the wet season the forests are flooded as such the dry season during which the water retreats but still leaving the forest damp provided a larger habitat availability and increased abundance of several invertebrate groups for understory birds (Thomas et al., 2020). Furthermore, studies of avifauna in some wetlands in Northern Nigeria reported higher species abundance and richness in the dry season (Abdullahi et al., 2025; Muhammad et al., 2025). These wetlands are located in the Sahel savannah zone of the country and as such may serve as a refuge for avifauna as the surrounding environment become very dry leaving the wetlands the major suitable habitat in that region. It is however worth mentioning that this variation may be influenced by migrating bird populations that visit during the dry season (Ringim and Aliyu, 2018), highlighting the influence of the prevailing situation in different habitats. Interestingly, functional diversity and richness did not follow the seasonal pattern of taxonomic richness and diversity. Unlike for taxonomic metrics, the wet season did favour functional metrics; functional diversity was significantly lower in this season. Functional richness, although not significant was also lower, suggesting that despite more species occurring in the wet season (taxonomic richness and diversity), they may not represent additional functional roles.

Despite marginal significance observed for the interactive effects of season and site protection on taxonomic diversity and richness, the metrics were higher at unprotected sites during the dry season suggesting the potential role of unprotected sites as seasonal refugia for birds. During the dry season (which can be really dry) food scarcity and competition may drive species to utilize the unprotected sites for their relatively more abundant food for example, from human wastes and residuals from farm harvests. It is however, good to note that the corresponding functional redundancy observed at the unprotected sites implies that the marginal increase in taxonomic metrics may be driven largely by species with overlapping ecological roles rather than by functionally distinct taxa. Given that specialist species tend to avoid disturbed habitats (Danmallam et al., 2025; Iniunam et al., 2025), unprotected areas are likely to be dominated by generalist species that can exploit anthropogenic food resources especially during the dry season.

Influence of anthropogenic disturbance

Human disturbance was associated with declines in taxonomic richness and diversity at both protected and unprotected sites. Although these associations were not statistically significant, the results suggest a potential and generally negative influence of human disturbance on bird communities at both protected and unprotected sites. The significant decline in functional richness due to disturbance at protected sites compared to the unprotected sites suggests that more intact habitats suffer severe biodiversity loss from disturbance compared to already disturbed habitats. This is so, because the protected areas have more specialist species that are easily affected by disturbance than the more generalist and human adapted species found at unprotected sites (Asefa et al., 2017). The result highlights the importance of more stringent management in protected areas in Nigeria.

“Functional diversity showed a positive but non-significant relationship with disturbance at unprotected sites. While this may reflect the presence of generalist species adapted to human-modified habitats, the lack of statistical support only suggests potential effects. However, a previous study by Danmallam et al. (2025) using country-wide citizen science data from the country of our study reported significantly higher functional diversity at unprotected sites, highlighting the role of generalist-driven resilience in disturbed landscapes. Interestingly, a positive change in functional diversity was also observed at protected sites, but also not a significant change. This pattern may indicate that higher disturbance levels within certain sections of protected areas allow disturbance-tolerant species to occupy these patches, which could become concerning if disturbance intensifies further. A study in Brazil reported similar levels of functional bird metrics at protected and unprotected areas due to comparable levels of disturbance across both site types (Cavarzere, 2024).

Although the patterns in our results are obvious, we acknowledge that there could still be some limitations to the study. For example, the changes in species diversity metrics due to disturbance and site protection status could be affected by other variables that we did not measure in this study. These include distance of sampling points to habitat edges, adjacency to different land-cover types, edge density and the proportion of surrounding habitat and fine-scale habitat variables. In addition, we checked and confirmed that habitat-level differences across sites did not influence the observed patterns of species metrics due to disturbance and site protection, except for functional diversity in the habitat × site model. We therefore acknowledge that habitat-related variation may influence the pattern of functional diversity in relation to site protection status, thereby underscoring the importance of considering habitat-specific influences when interpreting functional diversity. Furthermore, the disturbance index employed in this study was based on presence/absence of disturbance variables, which assigns equal weight to all disturbance types. While this approach provides a straightforward measure of disturbance occurrence, it does not capture variation in ecological intensity among different disturbance sources. Consequently, the index should be interpreted as reflecting disturbance occurrence rather than disturbance severity. We recommend that future work of this sort should refine the sampling approach by incorporating weighted measures that account for the relative ecological impacts of specific disturbance types, and measure other variables that may be sources of unexplained variation in species diversity metrics.

This study highlights the complex influences of seasonality, protection status, and anthropogenic disturbance on avian communities in the Nigerian Guinea savannah, revealing notable divergences between taxonomic and functional diversity metrics. Although unprotected sites supported higher species richness and diversity, this may have largely been driven by functionally redundant, generalist species associated with human−modified habitats. Seasonality was also an important driver of bird diversity in the Guinea savannah ecoregion of Nigeria, with the wet season recording higher taxonomic richness and diversity; whereas functional metrics were lower indicating a decoupling between species numbers and ecological roles. Increasing anthropogenic disturbance was generally associated with lower taxonomic and functional richness across sites, with protected sites showing a particularly pronounced and significant decline in functional richness, highlighting vulnerability of protected areas to disturbance-driven loss of functional species richness. Overall, our findings underscore the need for stronger management and monitoring focused on functional as well as taxonomic dimensions of biodiversity to ensure long−term ecosystem resilience.