Wing size and abundance alteration in social hymenopterans across forest loss and fragmentation gradients within Atlantic Forest

Alteração no tamanho e abundância das asas em himenópteros sociais ao longo de gradientes de perda e fragmentação florestal na Mata Atlântica

Abstract

Land uses for anthropogenic activities have been transforming large, forested areas into small, isolated fragments embedded in a matrix of non-natural land-cover classes. The implications of this process extend beyond species occurrence, also resulting in morphological changes in organisms, for instance, wing size in sensitive species such as social wasps and bees. These changes in key structures, such as wings, can ultimately affect associated ecosystem services, including population regulation and pollination. In this study we aimed to evaluate the influence of loss and fragmentation of forests and landscape spatial heterogeneity on the abundance and wing size of Apoica gelida (caterpillar hunter wasps) and Apis mellifera (pollen and nectar collector bee), both eusocial species. Over twelve months of sampling, we collected 5,179 individuals of A. gelida and 5,755 individuals of A. mellifera. The effects of landscape structure differed between species, landscape metrics, and spatial scales analyzed. The abundance of A. gelida was negatively associated with increasing distance from forest edges toward the anthropogenic matrix. Wing size in both species was significantly influenced by landscape structure, although responses varied across spatial scales. A. gelida responded primarily at smaller spatial scales, showing negative associations with forest loss (lower forest cover percentage) and forest fragmentation (lower connectivity). However, individuals also exhibited larger wings in landscapes with higher edge density, a metric commonly associated with increased forest fragmentation. In contrast, A. mellifera responded mainly at broader spatial scales, exhibiting larger wings in landscapes with lower forest fragmentation (i.e., higher connectivity), while also showing larger wing sizes in landscapes with higher edge density. Additionally, wing size in A. mellifera was positively associated with greater spatial heterogeneity. Such morphological changes in key fitness-related structures in A. gelida and A. mellifera have direct consequences for maintaining natural ecosystems and for global economic development, as both species provide essential supporting ecosystem services by regulating crop pests’ population and providing pollination. Therefore, this study contributes to a deeper understanding of how social insect populations respond to landscape structure variation, moving beyond analyses based solely on species presence or absence and incorporating phenotypic effects. Furthermore, our results offer valuable insights into planning multifunctional landscapes that reconcile natural ecosystem conservation with sustainable agriculture production for different land uses.

Keywords:
bioindicators; invertebrates; morphometry; pollination; population control

Resumo

O uso da terra para atividades antrópicas tem transformado grandes áreas florestais em pequenos fragmentos isolados, inseridos em uma matriz de classes de cobertura do solo não naturais. As implicações desse processo vão além da ocorrência de espécies, resultando também em mudanças morfológicas nos organismos, como a alteração no tamanho das asas de espécies sensíveis, como vespas e abelhas sociais. Essas alterações em estruturas-chave, como as asas, podem, em última instância, afetar serviços ecossistêmicos associados, incluindo a regulação populacional de pragas e a polinização. Neste estudo, avaliamos a influência da perda e da fragmentação florestal, bem como da heterogeneidade espacial da paisagem sobre a abundância e o tamanho das asas de Apoica gelida (vespa predadora de lagartas) e Apis mellifera (abelha coletora de pólen e néctar), ambas espécies eussociais. Ao longo de doze meses de amostragem, coletamos 5.179 indivíduos de A. gelida e 5.755 indivíduos de A. mellifera. Os efeitos da estrutura da paisagem diferiram entre as espécies, as métricas da paisagem e as escalas espaciais analisadas. A abundância de A. gelida associou-se negativamente com o aumento da distância da borda florestal em direção à matriz antrópica. O tamanho das asas de ambas as espécies foi significativamente influenciado pela estrutura da paisagem, embora as respostas tenham variado conforme a escala espacial. A. gelida respondeu principalmente a escalas espaciais menores, apresentando associações negativas com a perda florestal (menor porcentagem de cobertura florestal) e a fragmentação florestal (menor conectividade). No entanto, os indivíduos também exibiram asas maiores em paisagens com maior densidade de borda, métrica comumente associada ao aumento da fragmentação florestal. Em contraste, A. mellifera respondeu principalmente a escalas espaciais mais amplas, exibindo asas maiores em paisagens com menor fragmentação florestal (maior conectividade), e, simultaneamente, maior tamanho de asas em paisagens com maior densidade de borda. Além disso, o tamanho das asas de A. mellifera foi positivamente associado a uma maior heterogeneidade espacial. Tais mudanças morfológicas em estruturas fundamentais para a aptidão biológica de A. gelida e A. mellifera acarretam consequências diretas para a manutenção dos ecossistemas naturais e para o desenvolvimento econômico global, uma vez que ambas as espécies fornecem serviços ecossistêmicos essenciais ao regular populações de pragas agrícolas e promover a polinização. Portanto, este estudo contribui para uma compreensão mais aprofundada de como populações de insetos sociais respondem a variações na estrutura da paisagem, indo além de análises baseadas apenas na presença ou ausência de espécies e incorporando efeitos fenotípicos. Além disso, nossos resultados oferecem informações valiosas para o planejamento de paisagens multifuncionais que conciliem a conservação de ecossistemas naturais com a produção agrícola sustentável em diferentes usos do solo.

Palavras-chave:
bioindicadores; invertebrados; morfometria; polinização; controle populacional

1. Introduction

Deforestation has caused numerous consequences for ecosystems, transforming large continuous forest areas into small fragments, isolated by anthropogenic barriers (Fahrig, 2017; Vancine et al., 2024). Among the primary effects of this process are the forest loss caused by a reduction in vegetation cover (Johnson et al., 2017), and forest fragmentation that results in intensification of edge effects (Murcia, 1995), and a decrease in functional habitat connectivity (Boscolo et al., 2017). In addition, landscape spatial heterogeneity is also altered, which affects the dynamics of biological communities (Boscolo et al., 2017; Vizentin-Bugoni et al., 2018; Ryser et al., 2021; Saito, 2022). The consequences of landscape changes on a regional scale have led to increased environmental homogenization, reduced movement of animals and dispersion of plants, reduction or loss of habitat specialist species, and an increase in generalist species, which are usually more resistant to environmental changes (Cunha et al., 2014; Nery et al., 2018; Rosa et al., 2019). The implications of this process extend beyond species’ occurrence, also causing morphological changes in organisms (Benton et al., 2003; Rösch et al., 2013; Oliveira et al., 2015; Paiva et al., 2020). Nevertheless, the effect of landscape structure on morphological changes in species remains underexplored, despite its relevance for changes in species’ ecological functions and ecosystem services (Sánchez-Bayo and Wyckhuys, 2019; Cardoso et al., 2020).

For flying animals, especially the most sensitive ones such as insects, wing size is one of the most important body traits for individual survival and reproduction (i.e., fitness), and it is also influenced by regional processes (Yadav, 2003; Wang, 2005; Dickinson, 2006). Wings are closely related to individuals’ foraging ability (Córdoba-Aguilar, 1995), predator escapability (Bots et al., 2009) and mating (Stewart and Vodopich, 2013). In insects, wing size is mainly determined during the larval stage, therefore environmental stress during this period can directly affect adult individuals (Benke et al., 2001; Dmitriew et al., 2007; Pinto et al., 2012). For example, increased temperature or reduced food availability, accelerating their development and resulting in adults with alterations in their wings compared to those that developed in less stressful conditions (Roulston and Cane, 2000; Shpigler et al., 2013; Grass et al., 2021).

Morphological changes, especially in key structures such as wings, can affect different types of services associated with insect species. For example, the biological control of agricultural “pests” performed by some wasp species, which use these organisms as trophic resources for their offspring (Finkler, 2013; Giannini et al., 2017). Likewise, pollination, the process by which pollen grains are transferred from the anthers to the stigma of flowering plants, supports a highly profitable global market, in addition to ensuring the restoration and maintenance of natural landscapes (Giannini et al., 2017). Among these pollinators, bees stand out, as they are responsible for 73% of cultivated plant species worldwide, while wasps contribute 5% (Giannini et al., 2017). These services (i.e., “pest” control and pollination) can be enhanced when provided by species that reach high densities and require large amounts of trophic resources, such as social wasps and bees (Berti Filho and Macedo, 2011). However, regional environmental changes may trigger morphological modifications (i.e., wing size), consequently affecting both types and efficiency of ecosystem services provided by these organisms (Berti Filho and Macedo, 2011; Giannini et al., 2017).

Despite showing similarities in the way individuals within the colony interact and divide labor, social wasps and bees exhibit typical life-history traits that are specific to each group, mainly related to the type of trophic resource they use (i.e., other arthropods or floral resources, respectively; Strohm and Liebig, 2008). This difference may translate into distinct responses to the same type of environmental change, making it necessary to consider both types of organisms, as well as studies focusing on morphological changes in individuals driven by regional processes (Moreira, 2022; Andreazzi et al., 2025). In Brazil, a wide range of hymenopteran insect species can be found, therefore, choosing species that are widely distributed, easy to identify, and have well-known biology can be the first step toward developing studies from this perspective. In this context, the social wasp Apoica gelida Van Der Vecht, 1973 and the social bee Apis mellifera Linnaeus, 1758, emerge as strong candidates for addressing ecological questions within this line of research.

Apoica gelida, belonging to the family Vespidae (subfamily Polistinae), is a predator of a wide variety of invertebrates, especially Lepidoptera larvae, which serve as a nutritional resource for its offspring (Carpenter and Marques, 2001). Apis mellifera, on the other hand, from the family Apidae, is one of the main species responsible for the pollination of different crops worldwide and is widely distributed (Ramos and Carvalho, 2007, Neves and Viana, 2011). Despite their importance, the disappearance of these wasps and bees continues to occur, driven by anthropogenic factors such as excessive deforestation and the indiscriminate use of pesticides and agrochemicals (Ordunha and Faria Mucci, 2021; Coutinho et al., 2025). Both species have relatively short life cycles compared to large-bodied animals, which may result in a more pronounced and rapid response in wing morphology in fragmented landscapes and in areas with lower diversity of land use classes (Lewinsohn et al., 2005; Martins et al., 2020).

In this study, we aimed to evaluate the influence of forest loss, forest fragmentation, and landscape spatial heterogeneity on the abundance and wing size of A. gelida and A. mellifera, two eusocial hymenopteran species. We hypothesize that both response variables (abundance and wing size) will be influenced by regional landscape processes and that these effects vary across spatial scales. Specifically, we expect A. gelida to respond more strongly to landscape structure at smaller spatial scales, whereas A. mellifera is expected to respond primarily at broader scales. We further predict that greater forest loss, represented by lower forest cover percentage, and greater forest fragmentation, indicated by reduced forest connectivity, edge proximity, and edge density, will be associated with lower population abundance and smaller wing size and wing size variability in both species. Additionally, we expect landscapes with greater spatial heterogeneity to promote positive responses in both abundance and wing size, also decreasing wing size variability among individuals.

2. Material and Methods

2.1. Study area

The study area is in the region of Poços de Caldas city, Minas Gerais State, Brazil, where two types of vegetation predominate: natural grasslands and tropical forest, embedded in an agricultural landscape largely dominated by coffee production (Coffea arabica Carl von, 1753) and pasturelands (Figure 1). The climate of the region is characterized by winters from April to September, with an average temperature of 15°C and precipitation of 315 mm. Summer occurs between October and March, with an average temperature of 21°C and a yearly precipitation of approximately 1,430 mm. The annual average temperature is 17°C, with recorded minimum temperatures of -6°C and maximum temperatures of 31.7°C, and an average precipitation of 1,745 mm (Poços de Caldas, 2017).

Figure 1
The sample design used to collect Apoica gelida and Apis mellifera specimens in a landscape perspective in southwest Brazil. Landscapes were considered in a multiscale approach with buffers of 250 m, 1 km, and 5 km around the point of collection.

2.2. Sampling design

Over twelve months, nineteen sampling points were established with a light trap each one (Figure 1, Supplementary Material Figure S1). We used a light trap (Luiz de Queiroz model), in which insects are attracted to a light source and guided through a collecting tube into a storage container filled with 5 L of 70% alcohol (Supplementary Material Figure S1). The traps automatically switched on at dusk and off at dawn. Sampling was conducted monthly from January to December 2016, and at each sampling event, the filled jars were replaced with empty ones. Collected material was sorted, and specimens identified belonging to A. gelida and A. mellifera were counted and separated for analysis (Supplementary Material Figure S2). The specimens were identified using identification keys and comparisons with literature images (Valverde et al., 2019; Somavilla and Carpenter, 2021). All individuals were deposited at the Department of Biodiversity, São Paulo State University “Júlio de Mesquita Filho”, Rio Claro, São Paulo, Brazil.

2.3. Wing morphometric analysis

For the morphometric analysis, 20 female individuals of each species per sampling point were selected, from which the right forewing was removed for analysis. Each wing was photographed using a Leica DMC 2900 digital camera attached to a Leica S8AP0 stereomicroscope at its lowest magnification, using the Leica Application Suite (LAS) Version 4.13.0 (Build:310) software. Fifteen Type I anatomical landmarks were selected for A. gelida and seventeen for A. mellifera (see result session). These landmarks were chosen based on vein junctions on the wings of the individuals (Adams et al., 2004; Rohlf, 2015). The anatomical landmarks were digitized by the same observer on different days. This procedure was performed using the TPSUtil32 and TPSDIG2w32 software (Rohlf, 2015).

Wing size was calculated using the software MorphoJ 1.08.02 (Klingenberg, 2016), based on the centroid size of the wings. The centroid represents the mean position of all anatomical points on the wing, and its size (which is related to wing size) is calculated as the square root of the sum of squared distances of each point to the centroid (Bookstein, 1997; Klingenberg, 2016). We also calculated the variance of centroid size as a measure of wing size variability within populations. A shape analysis of the wings was also used to support our results by applying a Procrustes Superimposition Analysis and then a Principal Component Analysis (PCA) to visualize the main axis of shape variation of wings in each of the landscapes analyzed using wireframe visualizations (Adams et al., 2004; Klingenberg, 2016; Klates et al., 2025).

2.4. Landscape analysis

Landscape structure explanatory variables were calculated using a multiscale approach with varying buffer sizes around the sampling points: 250 m, 1 km, and 5 km to check for responses in difference scales since social bees may reach wider foraging ranges (~5 km) than social wasps (~250 m) (Araújo et al., 2004; Couvillon et al., 2015; Detoni and Prezoto, 2020). When landscapes overlapped, they were merged and data were aggregated to minimize spatial autocorrelation, which generated non-circular buffers around the sampling points and resulted in different numbers of landscapes being analyzed at each spatial scale (Figure 1). The following landscape metrics were calculated: Forest loss associated :(1) forest cover (%): sum of the area of forest fragments divided by the total landscape area*100; Forest fragmentation associated: 2) edge density (m/ha): measured as the sum of the perimeter of forest fragments divided by the total area of the landscape*10000; 3) edge distance (m): measured as the distance from the sampling point to the nearest forest edge; (4) forest connectivity (%): cohesion index, which is used to assess whether patches of the same class are aggregated or rather isolated; and Spatial heterogeneity associated: (5) landscape spatial heterogeneity: Shannon–Wiener index applied to landscape classes. All these metrics are weighted by the area of landscape which allow us for comparison between landscapes of different sizes. To do this, we used the function sample_lsm() from the landscapemetrics package (Hesselbarth et al., 2019).

The land use and land cover map used in this step of the analysis was provided by the Mapbiomas project. The project provides annual land use and land cover classification maps for the entire national territory, at a scale of 1:5,000 using 30 m spatial resolution (Souza et al., 2020).

2.5. Statistics and modeling

To model the effect of the landscape metrics on abundance, wing size, and wing size variation of A. gelida and A. mellifera, we used Linear Models (LM) when data assumed normal or lognormal distribution with the lm() function from the stats package (R Core Team, 2026) and Generalized Linear Models (GLM) when data assumed negative-binomial distribution with the glm.nb() from the MASS package (Venables and Ripley, 2002). To avoid multicollinearity, we built separate models for each explanatory variable. In the same way, since each scale had different number of landscapes due to overlapping described in the previous session, we also built separate model to each scale. To explain our results, we only used models that showed a significant effect of landscape variables on our response variables (p-value < 0.05). All analyses and figures were produced using R version 4.5.2 (R Core Team, 2026).

3. Results

A total of 5,179 individuals of A. gelida and 5,755 individuals of A. mellifera were collected (Supplementary Material Table S1). At 250 m scale, forest cover ranged from 0% to 51% ($\overline{X}$ = 20%, SD = 16%), forest edge density from 0 m/ha to 146 m/ha ($\overline{X}$ = 57 m/ha, SD = 44 m/ha), forest connectivity from 0% to 97% ($\overline{X}$ = 73%, SD = 24%), and landscape spatial heterogeneity from 0.6 to 1.54 ($\overline{X}$ = 1.16, SD = 0.2). At 1 km scale, forest cover percentage ranged from 5% to 42% ($\overline{X}$ = 20%, SD = 9%), forest edge density from 20 m/ha to 100 m/ha ($\overline{X}$ = 54 m/ha, SD = 18 m/ha), forest connectivity from 84% to 98% ($\overline{X}$ = 91%, SD = 4%), and landscape spatial heterogeneity from 0.8 to 1.62 ($\overline{X}$ = 1.39, SD = 0.17). At 5 km scale, forest cover percentage ranged from 10% to 32% ($\overline{X}$ = 20%, SD = 6%), forest edge density from 30 m/ha to 54 m/ha ($\overline{X}$ = 46 m/ha, SD = 6 m/ha), forest connectivity from 86% to 98% ($\overline{X}$ = 94%, SD = 3%), and landscape spatial heterogeneity from 1.20 to 1.78 ($\overline{X}$ = 1.64, SD = 0.14). Finally, edge distance varied from -45 m inside the forest fragment to 313 m toward the matrix ($\overline{X}$ = 52.44 m, SD = 88.86 m).

The abundance of individuals was only significantly associated with forest edge distance for A. gelida, which decreased towards the anthropogenic matrix, which was also associated with smaller wings in this wasp (Figure 2, Table 1, Supplementary Material Table S2). The response of wing size of A. gelida also varied according to landscape scales, where smaller scales of 250 m and 1 km presented contrasting responses from analysis using 5 km buffers. In this sense, forest cover was positively associated with wing size at smaller scales while in the larger one the wing decreases with this variable (Figure 2, Table 1, Supplementary Material Table S2). This pattern was also found regarding forest edge density, and forest connectivity (Figure 2, Table 1, Supplementary Material Table S2). On the other hand, landscape spatial heterogeneity was only significant associated with wing size in 5 km scale landscapes, where it decreased wing size while increased wing size variation (Figure 2, Table 1, Supplementary Material Table S2).

Figure 2
Landscape effects on abundance and wing size of Apoica gelida. Only significant models are shown here.

Table 1
Simple linear models (LMs) and Generalized Linear Models (GLMs) output from the test of the effect of landscape on wing size and abundance of Apoica gelida and Apis mellifera. For non-significant models, see supplementary material.

Species	Landscape scale	Response variable	Explanatory variable	Estimate	Std. Error	t/z value	R square	p-value
Apoica gelida	250 m buffer	Wing size	Forest cover (%)	<0.001	<0.001	4.354	0.049	<0.001
			Forest total edge (m)	<0.001	<0.001	4.142	0.044	<0.001
			Forest connectivity (%)	<0.001	<0.001	3.221	0.027	0.001
	1 km buffer	Wing size	Forest cover (%)	<0.001	<0.001	4.354	0.049	<0.001
			Forest total edge (m)	<0.001	<0.001	4.142	0.044	<0.001
	5 km buffer	Wing size	Forest cover (%)	<0.001	<0.001	-3.088	0.025	0.002
			Forest edge density (m/ha)	<0.001	<0.001	-1.967	0.010	0.050
			Forest connectivity (%)	<0.001	<0.001	-3.187	0.027	0.002
			Landscape heterogeneity	-0.012	0.005	-2.362	0.015	0.019
		Wing size variation	Landscape heterogeneity	4970	2147	2.315	0.401	0.049
	Distance metric	Wing size	Forest edge distance	<0.001	<0.001	-3.31	0.029	0.001
		Abundance	Forest edge distance	-0.003	0.002	-1.978	0.227	0.048
Apis mellifera	1 km buffer	Wing size	Forest connectivity (%)	<0.001	<0.001	2.722	0.021	0.007
			Landscape heterogeneity	0.009	0.003	2.939	0.025	0.004
	5 km buffer	Wing size	Forest edge density (m/ha)	<0.001	<0.001	2.813	0.023	0.005
			Landscape heterogeneity	0.012	0.004	2.940	0.025	0.004

Additionally, the anatomical landmarks of A. gelida wings that showed the greatest variation were points 05, 06, 09, 10, 11, and 12 (Figure 3), located on the distal part of the wings (farthest from the body), resulting in wings with more tapered tips (Figure 3). Despite this general variation explained by PCA analysis (PC1: 13.62%), when comparing the mean shape from low to high landscape forest cover, the differences were less pronounced (Figure 3).

Figure 3
Geometric morphometric analysis of Apoica gelida wing shape. (a) Forewing image with landmarks for wing morphology analysis. (b) Mean wing shape (dark blue line) compared to the global wing mean shape (light blue line) for different levels of forest cover and landscape heterogeneity. (c) Global shape deformation of landmarks explained by principal component 1 (PC1).

In A. mellifera responses, wing size was only significant associated with larger scales of 1 km and 5 km. On one hand, forest cover did not affect wings at any spatial scale used. On the other hand, wing size was positively associated with forest connectivity and landscape spatial heterogeneity at 1 km scale (Figure 4, Table 1, Supplementary Material Table S3). At 5 km scale, wings increased in size in landscapes with higher spatial heterogeneity and forest edge density (Figure 4, Table 1, Supplementary Material Table S3). Wing size variation was not affected by any explanatory variable at any landscape scape (Supplementary Material Table S3).

Figure 4
Landscape effects on wing size of Apis mellifera. Only significant models are shown here.

Most anatomical landmarks of A. mellifera exhibited substantial variation along the first principal component (PC1 = 25.71%), with the observed deformation corresponding to a more tapered wing morphology (Figure 5). At the 250 m scale, individuals sampled in the most deforested landscape exhibited greater wing deformation than those from the most forested landscape (Figure 5).

Figure 5
Geometric morphometric analysis of Apis mellifera wing shape. (a) Forewing image with landmarks for wing morphology analysis. (b) Mean wing shape (dark blue line) compared to the global wing mean shape (light blue line) for different levels of forest cover and landscape heterogeneity. (c) Global shape deformation of landmarks explained by principal component 1 (PC1).

4. Discussion

We observed that only the abundance of A. gelida was positively associated with distance from the forest edge toward the anthropogenic matrix. Regarding wing size, both eusocial hymenopteran species, A. gelida and A. mellifera, were significantly associated with landscape structure, with responses varying across spatial scales. Our results support our hypotheses, showing that variation in forest cover, edge density, edge proximity, forest connectivity, and landscape spatial heterogeneity is associated with morphological traits of these eusocial hymenopterans. However, these relationships differed according to spatial scale. For A. gelida, wing size at smaller scales (250 m and 1 km) was positively associated with forest cover, connectivity, and edge density, whereas the opposite was found for 5 km scale. Furthermore, individuals tended to exhibit smaller wings and greater intraspecific variation in wing size in more heterogeneous landscapes at larger spatial scales. In contrast, A. mellifera appeared to respond more strongly to landscape structure at larger scales (1 km and 5 km), exhibiting larger wings in landscapes characterized by greater forest connectivity, edge density, and spatial heterogeneity.

Despite A. gelida and A. mellifera sharing the biological characteristics of eusocial hymenopterans, they possess distinct natural history traits that may influence their responses to regional landscape variation. Because A. gelida has a more restricted foraging range and a nocturnal habit, which can constrain its ability to fly long distances depending on moon phase (Pickett and Wenzel, 2007; Somavilla et al., 2012), it is expected to respond more strongly to environmental changes at smaller spatial scales. In the genus Apoica, nests are composed of a single exposed comb of cells (Pickett and Wenzel, 2007), attached directly to the substrate without a pedicel, and are usually built on tree branches or herbaceous plants (Elisei et al., 2013). Consequently, A. gelida is expected to be closely associated with wooded environments (Carpenter and Marques, 2001; Ferreira et al., 2020). This may explain why its abundance was positively related to proximity to forest edges, which are likely to provide suitable nesting sites while also offering access to adjacent habitat types, such as crop matrices, where food resources may be abundant (Elisei et al., 2013). In contrast, A. mellifera forms large colonies with thousands of workers and exhibits a considerably larger foraging range, with individuals capable of flying 5 km or more from the nest (Couvillon et al., 2015). The large number of workers allows colonies to exploit resources over a broad area and buffer local and regional fluctuations in resource availability, potentially reducing the effects of landscape changes on colony abundance (Ulgezen et al., 2025). Such characteristics may explain why we did not detect a significant relationship between A. mellifera abundance and the landscape variables evaluated in this study.

Despite the restricted responses of abundance to landscape changing, individual’s performance in both A. gelida and A. mellifera may be under pressure due to morphological changes related to important structure drivers of fitness such as wings, as our results have shown. In hymenopterans, individual body size may be highly correlated to the amount of food available for the offspring (Rivera-Marchant et al., 2008; Nijhout and Grunert, 2010; Nijhout and Callier, 2015). The larger body size of A. gelida compared to A. mellifera may reflect a high requirement for food per individual, which in addition to their restricted foraging range and limited number of workers may explain why only wing size of A. gelida was significantly associated with forest edge distance, where the availability of food and shelter against predation for nests are more available (Almeida Locher et al., 2014; Caitano et al., 2020; Alves et al., 2024). In this context, these areas may reduce energetic costs of movement and select for individuals with larger wings, which may transport a greater volume of prey over time (Souza et al., 2012; Almeida Locher et al., 2014; Klein et al., 2015; Ferreira et al., 2020).

In addition to the availability of food resources, another factor that can significantly affect the development of eusocial wasps, such as A. gelida, is temperature (Gilbert and Raworth, 1996; Nadeau and Stamp, 2003). Forest-edge environments receive greater incidence of sunlight and, consequently, have higher temperatures compared to the interior of fragments (Murcia, 1995; Harper et al., 2005). Thus, wasp larvae located closer to the edge in landscapes with higher forest edge density at smaller scales (250 m and 1 km) are expected to exhibit accelerated growth and development rates, resulting in larger individuals compared to those in the forest fragment interior (Gilbert and Raworth, 1996). Moreover, these regional landscape effects on wing size in A. gelida may have a direct impact on its fitness, as larger individuals tend to exhibit greater longevity and higher body biomass, traits associated with nest provisioning, which increase reproductive efficiency (Schmidt-Nielsen, 1984; Wang et al., 2009).

The optimization of energetic expenditure for resource acquisition may also be a limiting factor when selecting individuals with smaller wings in eusocial wasps at larger landscape scales. We observed that forest connectivity at 5 km was negatively associated with the wing size of A. gelida, which may be linked to a mechanism of energetic optimization (Dudley, 2002). Larger wings relative to body size are associated with more efficient long-distance flight, although they may also involve higher energetic costs and can be associated with environments with lower connectivity, whereas smaller wings may represent a response to environments with easier movement for individuals (Angelo and Slansky Júnior, 1984; Dudley, 2002; Berwaerts et al., 2002; Araújo et al., 2004; Gibb et al., 2006). Likewise, another potential explanation could be related to the competition with other hymenopteran species in heterogeneous landscapes. The greater availability of habitats, capable of maintaining higher species richness, increases the likelihood of species that share similar food requirements to co-occur in space (Ferreira et al., 2020; Montagnana et al., 2021). Such increased competition could reduce resource availability per individual, potentially leading to poorer offspring nutrition and consequently smaller wing sizes (Nijhout and Grunert, 2010; Nijhout and Callier, 2015). This mechanism may also explain the greater variability in wing size observed in more heterogeneous landscapes, where differences in resource acquisition among colonies or individuals could generate increased morphological variation.

Unlike A. gelida, the wing size of A. mellifera was more strongly associated with landscape changes at larger spatial scales (1 km and 5 km). Landscapes with greater forest connectivity, edge density, and spatial heterogeneity were associated with larger wing sizes. Honeybees are commonly found at forest edges, and their broad foraging ability in connected landscapes may enhance resource acquisition for the colony, potentially improving larval development and consequently increasing mean wing size (Caitano et al., 2020; Zhang et al., 2023). Furthermore, for bees, landscape spatial heterogeneity is considered one of the main landscape variables explaining their occurrence, development, and resource requirements (Montagnana et al., 2021; Coutinho et al., 2025). A greater amount and distribution of land-use classes may favor individuals with larger and more elongated wings, traits associated with longer flight distances and higher flight speeds, which increase efficiency in resource acquisition and predator avoidance (Berwaerts et al., 2002). Thus, the current landscape simplification, resulting from habitat fragmentation and loss, can reduce the quantity and quality of resources available to bees (Renauld et al., 2016).

Such as wasps, for A. mellifera compromised provisioning of food to the brood, may affect their development and, consequently, the body size of adult individuals (Williams and Kremen, 2007; Renauld et al., 2016). This reduction in body size may have direct consequences for the pollination process, as the amount of pollen transported by smaller workers may be significantly lower than that transported by larger workers (Renauld et al., 2016; Arteman et al., 2025). This may have important economic implications due to the use of A. mellifera for economic purposes, since despite this bee species has a wide distribution and is adapted to different environments, its populations may still be under environmental stress, mainly linked to fragmentation and the loss of forested areas in the Atlantic Forest (Klein et al., 2007; Donkersley et al., 2014; Giannini et al., 2017; Donkersley et al., 2014; Arteman et al., 2025). In the current context of fragmentation and environmental degradation, the quantity and quality of the diet provided may be a key factor (Chole et al., 2019). Bees depend on floral resources for their survival, and therefore, the spatiotemporal distribution of these resources is extremely important for their maintenance (Torné-Noguera et al., 2014). In this context, landscapes with greater forest connectivity and spatial heterogeneity may be richer in plant species, which can lead to a constant supply of food, increasing wing size as shown in our results (Torné-Noguera et al., 2014; Chole et al., 2019). Likewise, the forest edge often acts as a novel environment, increasing the number of pioneer plant species that can provide large amounts of food for bees, also contributing to increasing their average body size (Bailey et al., 2014; Chole et al., 2019; Alves et al., 2024).

Importantly, caution should be exercised when interpreting the results regarding A. mellifera in this study, since the light-trap design used here is traditionally intended for sampling nocturnal insects. Even so, the large number of individuals collected suggests that this method may still provide a useful estimate of local bee abundance patterns, as worker movement is not abruptly interrupted at sunset and residual activity may extend into crepuscular periods depending on environmental conditions and colony dynamics (Beer et al., 2016; Grodzicki and Caputa, 2012). Moreover, to our knowledge, there is no evidence demonstrating that workers incidentally captured by light traps differ systematically in wing morphology from the local worker population. Therefore, while we acknowledge that our sampling approach may introduce limitations, there is currently no empirical basis to conclude that the observed wing size patterns are artifacts of the sampling method itself.

In this study, we observed distinct responses depending on the species analyzed. A. gelida and A. mellifera and the landscape scale. Despite these species sharing some similarities in their lifestyles, the species differ in their resource-use strategies, which should be considered in management and conservation actions. The ecosystem services of regulation provided by wasps and provisioning rendered by bees are essential for maintaining natural ecosystems and for global economic development, both dependent on the flight-based foraging of these insects. Thus, this study contributes to a deeper understanding of how social insect populations respond to environmental variation, going beyond analyses based solely on species presence or absence and incorporating phenotypic effects that have a direct impact on fitness. Furthermore, our results provide valuable insights for better planning of multifunctional landscapes that reconcile the conservation of natural ecosystems with sustainable land use.

Supplementary Material

Supplementary material accompanies this paper.

Figure S1

Luiz de Queiroz light trap model adapted with a collecting tube and an insect storage container filled with 5 L of 70% alcohol. The traps turned on automatically at dusk and off at dawn.

Figure S2

Social hymenopteran species. a) Apoica gelida, and b) Apis mellifera.

Table S1

Raw data on the Apoica gelida and Apis mellifera abundance and landscape attributes collected in southwestern Brazil.

Table S2

Complete results from the linear model showing the effect of landscape changes on abundance and wing size of Apoica gelida. Significant models are shown in bold.

Table S3

Complete results from the linear model showing the effect of landscape changes on abundance and wing size of Apis mellifera. Significant models are shown in bold.

This material is available as part of the online article from https://doi.org/10.1590/1519-6984.303869

Acknowledgements

We would like to thank FAPESP (Fundação de Amparo à Pesquisa do Estado de São Paulo) for the grant to Cazemiro CS (process: 2024/01666-7). Deus JPA is supported by Conselho Nacional de Desenvolvimento Científico e Tecnológico - CNPQ (process: 385077/2025-4). We also thanks to the Sao Paulo Research Foundation - FAPESP (processes #2013/50421-2; #2020/01779-5; #2021/06668-0; #2021/08322-3; #2021/08534-0; #2021/10195-0; #2021/10639-5; #2022/10760-1) and National Council for Scientific and Technological Development - CNPq (processes #442147/2020-1; #402765/2021-4; #313016/2021-6; #440145/2022-8; 420094/2023-7; 446029/2024-6; 421464/2025-9), and Sao Paulo State University - UNESP for their financial support. This study is also part of the Center for Research on Biodiversity Dynamics and Climate Change (CBioClima), which is financed by the Sao Paulo Research Foundation - FAPESP.

Data Availability Statement

Most of the data generated or analyzed during this study are included in this published article and its supplementary information files. Files such as wing photography and raw data can be found with the corresponding author.

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Edited by

• Editor:
  Takako Matsumura Tundisi

Publication Dates

• Publication in this collection
  21 Sept 2026
• Date of issue
  2026

History

• Received
  17 Dec 2025
• Accepted
  09 July 2026