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Article

Temporal Shifts in Flower-Visiting Butterfly Communities and Their Floral Resources along a Vegetation Type Altered by Anthropogenic Factors

by
Karla López-Vázquez
1,
Carlos Lara
2,*,
Pablo Corcuera
3 and
Citlalli Castillo-Guevara
2
1
Doctorado en Ciencias Biológicas y de la Salud, Universidad Autónoma Metropolitana, Ciudad de México 09310, Mexico
2
Centro de Investigación en Ciencia Biológicas, Universidad Autónoma de Tlaxcala, Km 10.5 Autopista Tlaxcala-San Martín Texmelucan, San Felipe Ixtacuixtla 90120, Mexico
3
Departamento de Biología, Universidad Autónoma Metropolitana, Ciudad de México 09310, Mexico
*
Author to whom correspondence should be addressed.
Forests 2024, 15(9), 1668; https://doi.org/10.3390/f15091668
Submission received: 6 August 2024 / Revised: 12 September 2024 / Accepted: 20 September 2024 / Published: 23 September 2024
(This article belongs to the Special Issue Wildlife Ecology and Conservation in Forest Habitats)
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Abstract

:
Habitat disturbance driven by human activities poses a major threat to biodiversity and can disrupt ecological interactions. Butterfly–plant mutualisms represent an ideal model system to study such anthropogenic impacts, as butterflies exhibit intimate dependencies on larval host plants and adult nectar sources, rendering them highly sensitive to habitat changes affecting the availability of these floral resources. This study examined flower-visiting butterfly communities and their associations with flowering plants in a landscape altered by anthropogenic factors in central Mexico. The study area encompassed a mosaic of vegetation types, including native juniper forests, agricultural lands, and introduced eucalyptus plantations, representing different degrees of human-induced habitat modification. Monthly surveys were conducted over a single year, covering both rainy and dry seasons, to analyze butterfly and plant diversity, community composition, and interactions. Results showed the highest diversity in juniper forests, followed by eucalyptus and agricultural sites. Seasonal turnover was the primary driver of community changes, with habitat-based segregation persisting within seasons. Butterfly diversity strongly correlated with flower abundance, while plant richness played a secondary role. SIMPER and indicator species analyses identified key taxa contributing to compositional dissimilarities among habitats and associated with specific vegetation types and seasons. Our research provides insights into temporal dynamics structuring butterfly–plant interactions across this forest disturbance spectrum, highlighting how habitat changes and seasonality shape these mutualistic communities in changing landscapes.

1. Introduction

Anthropogenic activities such as urbanization, agricultural expansion, and resource extraction have resulted in widespread habitat loss and fragmentation and are recognized as the main drivers of biodiversity decline in ecosystems globally [1]. The disturbance and degradation of natural habitats can profoundly alter ecosystem functioning, community structure, and species interactions, with potential cascading effects across trophic levels [2].
Lepidopterans (butterflies and moths) represent a diverse and ecologically important group of insects in terrestrial ecosystems, acting as pollinators, herbivores, prey for higher trophic levels, and indicators of environmental change [3,4]. Their relatively short life cycles, sensitivity to environmental fluctuations, and well-studied relationships with host plants make them excellent indicators for assessing habitat quality, ecosystem integrity, and impacts of environmental stressors [1,5].
Butterflies exhibit associations with plants when hosting their larvae and when acting as nectar sources for adults, making them particularly vulnerable to habitat disturbances that disrupt the availability and spatial distribution of these essential resources [6,7]. Habitat fragmentation can lead to the isolation of butterfly populations, disrupting gene flow, reducing population sizes, and increasing the risk of local extinctions [8]. However, it can also have positive effects, such as increasing populations of species that prefer open habitats and sustaining some populations that might not survive in larger forests [8,9].
Understanding the responses of butterfly communities and their associated floral resources to varying degrees of habitat disturbance is crucial for developing effective conservation strategies and mitigating biodiversity loss [10]. While several studies have investigated the effects of habitat fragmentation on butterfly diversity, abundance, and community composition, e.g., [9,11,12,13], few have explicitly examined the concurrent impacts on butterfly community structure and their floral resources along a vegetation type altered by anthropogenic factors [14,15,16,17]. Furthermore, the potential influence of seasonality on these relationships remains understudied, despite well-documented seasonal fluctuations in butterfly and plant phenologies, e.g., [18,19].
In the central region of Tlaxcala, Mexico, landscapes encompass a range of habitat types altered by anthropogenic factors, providing an ideal opportunity to investigate the effects of habitat disturbance on butterfly communities and their floral resources. At both local and landscape scales, habitat disturbance can influence butterfly and flowering-plant communities [10]. Disturbance may lead to the loss of specialist species, while favoring generalist species better adapted to disturbed environments, e.g., [13,20]. Changes in environmental conditions, such as microclimate, light availability, and soil properties, can affect the relative abundances and phenologies of flowering plants. Additionally, human activities in the area and pollution can have significant effects on these environmental factors. These combined anthropogenic and environmental changes can potentially disrupt the temporal and spatial availability of resources for butterflies [21,22]. The spatial configuration of vegetation patches can influence butterfly movement and dispersal patterns, affecting gene flow, resource utilization, and metapopulation dynamics [23,24,25,26].
Moreover, the responses of butterfly and flowering-plant communities to habitat disturbance may vary across spatial and temporal scales, reflecting the inherent complexities of ecological processes and species-specific traits [10]. For instance, while habitat disturbance may negatively affect specialist species at the local scale during their active seasons, landscape-level factors such as habitat connectivity may be more influential in determining the persistence of wider-ranging generalist species during dispersal periods [27]. Seasonal variations in resource availability, climatic conditions, and life history traits of butterflies and plants may also modulate their responses to disturbance, highlighting the importance of considering temporal dynamics in ecological studies [28,29].
This study aims to elucidate the effects of habitat disturbance on adult butterfly communities and their interactions with flowering-plant resources along a vegetation type altered by anthropogenic factors in central Tlaxcala, Mexico. We addressed the following research questions: (1) How does the degree of habitat disturbance influence the diversity, abundance, and community composition of butterflies and flowering plants across seasons? (2) To what extent do plant richness and flower abundance explain the variation in butterfly community composition across the different vegetation types? (3) Which butterfly species show the highest degree of association with particular vegetation types and seasons, suggesting their potential role as indicator species?
By addressing these questions, our study contributes to a comprehensive understanding of the impacts of habitat disturbance on plant–insect communities in a region experiencing rapid land-use changes, while accounting for seasonal variations. The findings can inform conservation efforts aimed at preserving ecosystem integrity and promoting sustainable management practices.

2. Materials and Methods

2.1. Study Area

Butterfly and plant communities were studied in the municipality of Ixtacuixtla, which is located in the state of Tlaxcala in central Mexico (19°21′ N and 98°22′ W, with an altitude ranging from 2300 to 2350 m above sea level), from February 2023 to January 2024. While this timeframe allowed us to capture seasonal variations within a year, it is important to note that inter-annual variations were not assessed. The study was conducted in an area where the natural habitat of temperate forest (i.e., juniper–oak forest) has been altered by anthropogenic factors over the years, resulting in a mosaic of vegetation types. This landscape, covering an approximate area of 65 hectares, now includes the original juniper–oak forest alongside modified habitats such as agricultural lands and eucalyptus plantations. The study site is located 14.1 km west of the city of Tlaxcala. The original vegetation in the study sites consisted of juniper (Juniperus deppeana) and oak (Quercus spp.) forests, of which some relicts still remain. However, most of this vegetation was replaced by eucalyptus (Eucalyptus sp.) and/or modified to induced cultivation areas with rainfed agricultural areas with scattered trees around them. The climate is considered temperate sub-humid, exhibiting pronounced seasonal variations. The wet season extends from May to October and is characterized by a mean monthly precipitation of 123 mm and an average temperature of 17 °C. Conversely, the period from March to May constitutes the hottest and driest months, with a mean monthly precipitation of 10 mm and an average temperature of 13 °C [30] (Figure 1A).
The classification of vegetation types was established by conducting on-site visits to the locations, using a process known as ground truthing. This method allowed for the verification of land-use patterns through firsthand observations. Subsequently, these findings were further confirmed by examining satellite images of the surveyed areas [31]. In order to cover this landscape, three 100 m transects (with a distance between them of at least 100 m) were established in each vegetation type: Juniper forest (19°20′16.07″ N, 98°22′6.40″ W), where the vegetation is composed of relicts of original vegetation of Juniperus deppeana and some individuals of Quercus spp. species (Figure 1B,E), within a grassland dominated by native grasses and small shrubs such as Muhlenbergia implicata, Stipa ichu, and Aristida schiedeana, as well as Rhus standleyi. Eucalyptus forest (19°20′5.63″ N, 98°21′54.29″ W), an area where the original forest was replaced through induced plantations of Eucalyptus globulus trees as the dominant species (Figure 1C,F), and plant species such as Erythrina coralloides, Stevia elatior, and Dyssodia papposa are also present. Lastly, these forested zones are surrounded by agricultural lands (19°19′55.43″ N, 98°21′54.92″ W), used mainly for corn, wheat, and alfalfa crops (Figure 1D,G), and where human settlements are near.

2.2. Surveys of Plant–Butterfly Communities

While we acknowledge the importance of larval and host plant relationships, our research questions focus on the interactions between adult butterflies and flowering plants. Each month, the transects of a vegetation type were sampled (1 day per vegetation type until completing 3 continuous days), covering a schedule from 10:30 to 13:30 h, considering the peak activity times of butterflies. Two trained observers steadily walked the transects performing the censuses to ensure accuracy, data quality, and avoid observer bias, and to accomplish logistical feasibility. Throughout the study, exclusively during clear and sunny conditions, the censuses started from a different vegetation type transect and/or in a different direction to avoid order effects. Any butterfly visiting a flower within 10 m on either side of the transect or flying along it were counted, following the method of Pollard & Yates [32]. The term “flower visit” was used to describe the act of a butterfly species probing for nectar, which was recorded from the instant the proboscis was inserted into the corolla until it was withdrawn. We recorded all butterfly species observed during our surveys, including both sedentary and potentially migratory species. While we did not categorize species based on their mobility or migratory behavior in this study, we acknowledge that these traits may influence the observed patterns of butterfly–plant interactions. Butterfly identification was primarily conducted using Eagle Optics binoculars (Eagle Optics Co., Middleton, WI, USA). In cases where species identification was challenging through this method, individuals were carefully captured using a net and photographed with a Canon EOS Rebel T7 (Canon Inc., Tokyo, Japan). If the species could be identified from the photographs, the butterflies were immediately released. Only specimens that could not be identified in the field were collected and taken to the laboratory for further examination. These collected specimens were subsequently identified using taxonomic keys specific to butterflies, e.g., [33,34]. To ensure accuracy, all records were verified by José de Jesús García Díaz, a taxonomist specializing in butterflies, to corroborate their proper classification. After this process, these specimens were deposited in the Lepidoptera collection of the Centro de Investigación en Ciencias Biológicas at the Universidad Autónoma de Tlaxcala, Mexico. Additionally, samples of the plants that the butterflies interacted with were collected. These plant specimens were identified using specific taxonomic keys [35]. Finally, during each sampling month, all open flowers were quantified within each transect for at least 10 individuals of the plant species visited by butterflies.

2.3. Dynamics on the Richness and Diversity of the Plant–Butterfly Communities

To gain a comprehensive understanding of the ecological dynamics and interactions between butterflies and their flowering-plant communities on these habitat types, seasonal patterns were assessed and data were explored from both the dry and rainy seasons. The number of species found in each habitat type (i.e., combined across surveys over seasons) was used to express the richness of both butterflies and flowering plants. All interacting individuals as well as the flying butterflies recorded during the sampled surveys were included in the calculation of butterfly and flowering-plant richness.

2.4. Data Analysis

To assess the impact of land-use change on butterfly and flowering-plant diversity, we employed the unified framework of Hill numbers [36] to calculate species diversity using the interpolation and extrapolation approach developed by Chao et al. [37]. This method allows for the estimation of diversity at different orders (q), providing a comprehensive understanding of the effective number of species [38] and their relative abundances. We computed the zeroth-order (q = 0), first-order (q = 1), and second-order (q = 2) diversity, which correspond to species richness, the exponential of Shannon’s entropy index, and the inverse of Simpson’s concentration index, respectively [39]. These diversity measures quantify the number of equally abundant species required to produce the same value of a given diversity index [38] and reflect the degree of evenness in species abundances [40]. To compare the diversity indices across the habitat types, we constructed 95% confidence intervals using the iNEXT package version 3.0.0 [41]. Additionally, we visualized the species abundance distributions using rank-abundance curves to provide further insights into the community structure.
To assess the variability in species composition (beta diversity) among the butterfly and flowering-plant communities sampled across the three vegetation types, we calculated the Bray–Curtis dissimilarity index [42]. This index quantifies the differences in species composition between pairs of communities, considering both the presence and abundance of species. Subsequently, to visualize the patterns of community composition and identify potential clustering based on habitat types and climatic seasons (rainy and dry), we performed a non-metric multidimensional scaling (NMDS) ordination using the Bray–Curtis dissimilarity matrix. NMDS is a robust ordination technique that represents the compositional dissimilarities between communities in a reduced-dimensional space while minimizing the stress of the configuration [43]. The statistical significance of the observed community groupings was then evaluated using the Analysis of Similarities (ANOSIM), which is a non-parametric permutation test that assesses whether the compositional differences between a priori defined groups (in this case, habitat types and seasonality) are greater than expected by chance [44]. The NMDS and ANOSIM analyses were conducted using the vegan version 2.5-6 [45] and MASS version 7.3-61 [46] packages in R [47].
To determine the influence of flower abundance and plant species richness on butterfly community composition, we performed a redundancy analysis (RDA) using the “vegan” package in R [47]. The RDA was conducted on a matrix of butterfly species abundances across the three vegetation types, with flower abundance and plant species richness as explanatory variables. Flower abundance was quantified by counting the number of flowers along the transects at each site, while plant species richness was determined by identifying and counting the number of unique plant species within the same transects. The significance of the RDA axes was assessed using permutation tests with 999 permutations. Pearson’s correlation coefficients were calculated to examine the relationships between the RDA axes and the explanatory variables. The RDA ordination plot was generated to visualize the patterns of butterfly community composition in relation to the vegetation types and the explanatory variables.
The compositional dissimilarities between habitats for both butterflies and flowering plants were assessed through the percentage similarity test or SIMPER [48]. SIMPER identifies the species primarily contributing to the observed differences by decomposing the Bray–Curtis dissimilarity index into percentage contributions from each species [49]. In this analysis, a 90% cut-off for low contributions was employed, and the ‘simper’ function from the vegan package [45] in R was utilized. The test computes the overall sample dissimilarity as well as the dissimilarity contribution of individual species by considering their relative abundances and their dissimilarity across samples [48]. Consequently, SIMPER highlights the key species driving the compositional differences between habitats by accounting for both their abundance patterns and their distinctiveness across samples.
Lastly, to determine the flowering plant and butterfly species that could serve as indicators or representatives of each habitat type, an Indicator Species Analysis (IndVal) was conducted [50]. The IndVal approach combines information on the species’ abundance and their occurrence patterns across groups (e.g., habitats) to derive an indicator value for each species in each group [51]. This method identifies species that are both abundant and highly associated with particular groups, making them suitable indicators or representatives of those groups [50]. The analysis was performed using the indval function from the “labdsv” package [52] in the R-project software environment [47].

3. Results

3.1. Richness, Structure, and Seasonality

The composition and abundance of butterfly and flowering-plant communities exhibited pronounced differences across the three habitat types, as predicted. A total of 57 butterfly species (Table 1) and 34 flowering-plant species (Table 2) were recorded throughout the study. The observed number of butterfly species and plant species in the study seemed to reach an asymptote in relation to our sampling effort across the three sampled habitats (a total of 108 hours of evenly distributed observation efforts throughout the study). For butterfly species, we detected 99% sampling completeness for the juniper forest and the eucalyptus forest and 97% for agriculture sites according to the Chao2 estimator, after conducting 12 sampling events for each habitat type throughout the study. Likewise, we achieved 99% sampling completeness for flowering-plant species in the juniper forest, 99% in the eucalyptus forest, and 100% in the agriculture lands, based on the estimated species richness. The effective number of butterfly species varied considerably across both habitat types and seasons (Figure 2A). Butterfly species richness was consistently highest in the juniper forest, intermediate in the eucalyptus forest, and lowest in the agricultural sites. This pattern was maintained across both the rainy and dry seasons. However, the magnitude of the differences among habitats was more pronounced during the dry season compared to the rainy season. Butterfly richness also exhibited marked seasonal variation. Across all three habitat types, the number of butterfly species was highest during the rainy season and lowest during the dry season. The seasonal fluctuations were less pronounced than the differences among habitats. The flowering-plant community showed similar trends to the butterflies in terms of habitat differences (Figure 2B). The juniper forest had the highest effective number of flowering-plant species, followed by the eucalyptus forest, with the agricultural sites having the lowest flowering-plant richness. This pattern was consistent across both the rainy and dry seasons. Flowering-plant species richness was higher during the rainy season compared to the dry season in all habitats, but the magnitude of the seasonal difference varied among vegetation types. The largest seasonal difference in flowering-plant richness was observed in the agricultural sites, while the juniper forest showed a smaller difference between the rainy and dry seasons.
The rank-abundance distributions revealed markedly different butterfly community structures among the habitats (Figure 3A). The agricultural sites exhibited a relatively homogeneous abundance distribution, with few very abundant species and a long tail of rare species. In contrast, the forest habitats displayed a more heterogeneous structure, with abundances more evenly distributed among the species ranks (Table 3). This pattern suggests higher evenness and lower dominance in the forest butterfly communities compared to the disturbed agricultural areas.
The rank-abundance distributions for the flowering-plant communities (Figure 2B) showed similar patterns to those of the butterflies. The agricultural sites had a steeper rank-abundance curve, indicating a plant community with a few highly abundant species and many rare ones. The eucalyptus forest exhibited a slightly more even distribution of flowering-plant species abundances, while the juniper forest had the shallowest rank-abundance curve, suggesting a more balanced plant community with a greater number of species having intermediate abundances (Table 3). The species-accumulation curves for the butterflies (Figure 3A) further corroborated the lower diversity in agricultural sites, with shallower slopes indicating slower accumulation of new species compared to the juniper and eucalyptus forests. Similarly, the plant species-accumulation curves (Figure 3B) showed a slower rate of species accumulation in the agricultural sites compared to the forest habitats, reflecting lower plant diversity in the disturbed areas.
The Bray–Curtis similarity analysis indicated a considerable similarity in butterfly species composition between the juniper forests and eucalyptus forest (62%), as well as between juniper forest and agricultural areas (56%). The eucalyptus forest and agricultural sites also shared high similarity (65%). However, these similarities varied according to the climatic season. In contrast, the similarity in flowering-plant species composition was high between the juniper and eucalyptus forests (63%), but very low between these sites and agricultural areas (≤7%). These similarities also fluctuated according to the climatic season.

3.2. Habitat and Seasonal Drivers of Community Composition

Non-metric multidimensional scaling ordinations based on community data clearly separated samples by season along the primary NMDS1 axis, both for the butterfly (Figure 4A) and flowering-plant (Figure 4B) communities. Their separation along this axis indicates a marked turnover in community composition between these two seasons in all three habitats. However, within each seasonal group, there was also evidence of clustering by habitat type, suggesting that compositional differences among habitats persisted across seasons. This habitat segregation was particularly pronounced for the butterfly communities (Figure 4A), with the three habitat types forming distinct clusters, especially during the dry season. The agricultural sites were the most differentiated, while the juniper and eucalyptus forests showed some overlap but still maintained distinct centroids.
For the flowering-plant communities (Figure 4B), the habitat segregation was less pronounced than for the butterflies but still evident. The agricultural sites were again the most distinct, particularly during the rainy season, indicating these disturbed areas hosted a plant community that differed markedly from the two forest habitats. The juniper and eucalyptus forests exhibited greater overlap in flowering-plant community composition, but their separation indicates persistent differences between these two forest types. Overall, the NMDS ordinations reveal that both butterfly and flowering-plant communities are structured by a combination of seasonal and habitat factors. The seasonal turnover is the primary driver of compositional change, but habitat-specific differences are maintained within each season, indicating that the human-altered vegetation types have a consistent impact on community structure across temporal scales.
The redundancy analysis (RDA) revealed that flower abundance and plant species richness significantly influenced butterfly community composition across the three studied vegetation types (Figure 5). The primary RDA axis (RDA1) accounted for 67.3% of the total variation in butterfly diversity and was strongly correlated with the flower abundance gradient (r = 0.92, p < 0.001). Along this axis, sites with higher flower abundance harbored greater butterfly diversity, as indicated by the diagonal distribution of data points.
The secondary RDA axis (RDA2), explaining an additional 18.5% of the variation, was associated with plant species richness (r = 0.78, p < 0.01). The eucalyptus forest site was positively correlated with this axis, reflecting its higher plant richness compared to the other vegetation types. The RDA ordination clearly separated the three vegetation types, suggesting distinct butterfly communities among habitats. Agricultural sites clustered at the lower end of the flower abundance gradient, indicating lower butterfly diversity due to reduced floral resources in these disturbed areas. Juniper forest sites exhibited intermediate levels of butterfly diversity, despite relatively low flower abundance, suggesting the influence of additional factors not included in this analysis.
In contrast, the eucalyptus forest site was associated with both high plant richness and moderately high flower abundance, potentially contributing to its relatively high butterfly diversity. Overall, the RDA results suggest that the drivers of adult butterfly community composition differ across the studied vegetation types, with flower abundance and plant richness playing varying roles in structuring these communities.

3.3. Key Indicator Species

The SIMPER analysis identified the butterfly and plant species contributing most to dissimilarity in community composition among the three vegetation types (Table 4) and between the rainy and dry seasons (Table 5). For butterflies (Table 4A), the species driving the greatest dissimilarity between vegetation types were Zerene cesonia cesonia (15.32% contribution), Battus philenor philenor (13.63%), and Dione incarnata incarnata (0.19%). Z. cesonia cesonia was overwhelmingly more abundant in the eucalyptus forest compared to the other habitats, while B. philenor philenor peaked in agricultural sites but was common across all vegetation types. D. incarnata incarnata exhibited highest abundance in the juniper forest.
Among flowering plants (Table 4B), the species contributing most to vegetation dissimilarity were Rhus integrifolia (37.86%), Loeselia mexicana (24.61%), and Mimosa aculeaticarpa (6.38%). R. integrifolia and L. mexicana showed very high flower abundance in the eucalyptus forest but were nearly absent from agricultural areas. M. aculeaticarpa occurred across all habitats but attained greatest abundance in the eucalyptus forest.
For seasonal dissimilarity in butterflies (Table 5A), B. philenor philenor (20.58%), Z. cesonia cesonia (10.87%), and Nathalis iole iole (6.68%) were the top contributors, being far more abundant during the rainy season compared to the dry season across vegetation types. The flowering-plant species accounting for most of the seasonal dissimilarity (Table 5B) were R. integrifolia (23.25%), L. mexicana (13.6%), and M. aculeaticarpa (13.47%). These species exhibited very low flower abundance or were absent during the rainy season but became highly abundant sources of floral resources in the dry season.
Based on the indicator species analysis (IndVal), several butterfly and flowering-plant species exhibited strong associations with particular vegetation types or seasons (Figure 6 and Figure 7). For butterflies (Figure 6A), Leptophobia aripa elodia emerged as a strong indicator of agricultural sites. Zerene cesonia cesonia and Battus philenor philenor were among the top indicators for the eucalyptus forest. Meanwhile, Dione incarnata incarnata was the strongest indicator species for the juniper forest vegetation type. Regarding seasonal indicators, butterflies like Battus philenor philenor, Dione juno, Phoebis sennae marcellina, and Danaus gilippus thersippus exhibited high indicator values for the rainy season across vegetation types. No butterfly species emerged as a particularly strong indicator of the dry season. Turning to flowering plants (Figure 6B), Raphanus sativus was a top indicator of agricultural areas during the rainy season. Rhus integrifolia and Loeselia mexicana were among the strongest indicators of the dry season across habitats. Mimosa aculeaticarpa also showed a high indicator value for this dry period. For associations with specific vegetation types, Rhus integrifolia and Loeselia mexicana again had the highest indicator values, pointing to their strong ties as indicator species for the eucalyptus forest habitat. Salvia polystachya emerged as an indicator species most associated with the juniper forest vegetation type.

4. Discussion

This study elucidates how adult butterfly visitation patterns and flowering-plant community composition, abundance, and structure respond to anthropogenic habitat changes and seasonal fluctuations in the studied landscape. The findings reinforce the extensive literature documenting biodiversity losses and biotic homogenization in human-modified environments [1,53,54]. However, it also reveals nuanced responses across different intensities and types of disturbance, as well as to seasonal resource dynamics, underscoring the complexities of biodiversity’s responses to multiple interacting stressors.
The juniper forest sites, representing relatively undisturbed reference conditions, consistently harbored the highest plant and butterfly diversity levels. This accords with a wealth of studies globally reporting greater species richness and abundance in more intact, heterogeneous natural habitats [55,56]. In contrast, the less diverse communities observed in intensive agricultural areas reflect changes in the composition and abundance of flowering-plant species, as well as alterations in seasonal patterns. These changes in floral resources and phenology can significantly impact butterfly diversity and abundance. While our study primarily focused on these factors, it is worth noting that such changes in plant communities and seasonality are often consequences of broader landscape modifications, including habitat conversion and simplification [57,58,59]. These alterations can affect resource availability and quality for butterflies, potentially influencing their population dynamics and community structure [60,61,62].
The eucalyptus plantations occupied an intermediate position, corroborating studies across regions showing diminished biodiversity compared to intact native ecosystems, even for plantations of native tree species [63,64,65]. Beyond simplified vegetation structure and altered microclimate, factors like reduced food-plant diversity, intensive management practices, and temporal resource fluctuations appear to limit their value in sustaining diverse communities [66,67]. While representing an improvement over agricultural matrices, production forestry does not provide a substitute for preserving primary forests.
Our study revealed distinct associations between adult butterfly communities and floral resources across the different vegetation types, specifically in the context of flower visitation. In the eucalyptus plantations, butterflies were more closely associated with higher flower abundance, while in the juniper forests, they were more closely linked to higher plant richness. These findings suggest that the relative importance of resource quantity versus diversity in shaping butterfly communities may vary depending on the habitat context. Previous studies have also documented such context-dependent responses. For example, Valtonen et al. [68] found that butterfly species richness was more strongly correlated with nectar plant abundance in managed grasslands, while nectar plant diversity was a better predictor in semi-natural grasslands. Similarly, Pöyry et al. [69] reported that butterfly abundance was more sensitive to floral abundance in agricultural landscapes, whereas species richness was more responsive to floral diversity in forested landscapes. The weaker associations observed in the agricultural sites in our study likely reflect the overall resource scarcity and degraded conditions limiting both butterfly and plant communities, as seen in other intensively cultivated systems [70,71]. The species-level responses further underscore the importance of resource heterogeneity in supporting diverse butterfly assemblages, with different species linked to varying combinations of floral abundance and plant diversity. This aligns with the concept of niche complementarity, whereby a greater array of resources enables the coexistence of more species with different resource requirements [72,73]. Collectively, these nuanced patterns highlight the need to consider both the quantity and diversity of floral resources, as well as the habitat context, when assessing drivers of butterfly community structure across vegetation types altered by anthropogenic factors.
The tight positive correlation between plant richness and floral abundance matches well-established ecological theory. Floral resources are key drivers of pollinator diversity, abundance, and community composition patterns [74,75,76]. The scarcity of flowering plants in the most disturbed agricultural habitats likely contributed directly to the impoverished butterfly communities documented, mirroring patterns across degraded environments globally [77,78]. When resources are limited, competitive displacement by disturbance-adapted generalists overshadows rare specialists, driving homogenization of abundance distributions and diversity losses [13,27,79].
The pronounced seasonal turnover fits expectations of phenological resource tracking by multivoltine species in highly seasonal tropical/subtropical regions [80,81,82]. However, the distinct compositional clustering by habitat within each season reveals that local environmental filters remain paramount in structuring communities, as supported by other studies [16,67,83]. The agricultural matrices displayed the strongest habitat signature during the resource-flush rainy season, suggesting these areas become even more restrictive as ephemeral resources peak. Many forest species may be unable to effectively exploit these resources across the degraded agricultural landscape [17,84].
Our indicator species analysis revealed that certain butterfly species are strongly associated with particular vegetation types, serving as potential indicator species. In the agriculture sites, Colias eurytheme and Leptophobia aripa elodia were identified as the main indicator species. Previous studies have found that species in the genus Colias are often associated with open, disturbed habitats such as agricultural fields and pastures [70,85]. Similarly, species in the genus Leptophobia are known to occur in open, sunny areas and are often found in agricultural landscapes [86,87].
In the juniper forest, Anteos maerula and Fissicrambus sp. emerged as the primary indicator species. Butterflies in the genus Anteos, which belong to the family Pieridae, have been associated with woodland and forest habitats in previous studies [88,89]. Species in the genus Fissicrambus, which are geometrid moths, have been used as indicators of forest health and have been found to respond to changes in forest structure and composition [90,91].
In the eucalyptus forest, Ganyra josephina josepha was identified as the main indicator species. This species belongs to the family Pieridae, which has been shown to have strong associations with forest habitats in various studies [92,93]. Butterflies in the genus Ganyra have been identified as potential indicators of forest disturbance and have been found to respond to changes in forest management practices [94,95].
Furthermore, our analysis revealed that Danaus gilippus thersippus and Phoebis agarithe were the primary indicator species during the rainy season. Danaus gilippus belongs to the family Nymphalidae, and species in this genus have been widely used as indicators of environmental change and have been found to respond to seasonal variations in resource availability [93,96]. Phoebis agarithe, a member of the family Pieridae, has been associated with seasonal changes in tropical and subtropical regions [64,97]. These findings underscore the importance of considering both spatial and temporal factors when using butterfly species as ecological indicators. The presence and abundance of these indicator species can provide valuable insights into the ecological integrity, conservation value, and seasonal dynamics of different habitats [89,98].
A key strength was the integrated examination of both plant and pollinator communities, rare for local studies, providing a holistic biodiversity perspective. Furthermore, extending beyond simple diversity metrics to analyze composition, structure, and explicit incorporation of seasonality offers novel insights into multidimensional impacts of habitat modification, aligning with recent ecological frameworks [99,100,101]. Ongoing analyses identifying robust indicator taxa for each habitat disturbance–seasonality scenario will prove invaluable for monitoring, modeling biodiversity change, and informing conservation strategies and restoration efforts [102,103,104].
Lepidoptera behavioral diversity is crucial in interpreting our results. Species-specific behaviors, especially migratory patterns, may influence observed interactions. For example, the presence of migratory species like Vanessa cardui might reflect temporary resource use rather than habitat preference. Species mobility also affects responses to habitat changes and resource distribution. Future studies should categorize species based on behavioral traits to better understand how different Lepidoptera groups respond to habitat changes and interact with plant communities. This approach could help distinguish local habitat effects from broader landscape-level or seasonal factors influencing butterfly–plant interactions.
Our focus on adult butterfly–flower interactions provides valuable insights into one aspect of butterfly ecology, but it is important to consider these findings within the broader context of plant–lepidopteran relationships. The strong associations we observed between adult butterflies and floral resources may not necessarily reflect the overall habitat suitability for butterfly populations, as larval host-plant availability is also crucial. Future studies integrating both adult and larval resource requirements would provide a more comprehensive understanding of how habitat changes affect butterfly communities across their entire life cycle. Additionally, to gain a more complete picture of these ecological dynamics, multi-year studies are essential. Long-term research would allow us to account for inter-annual variations in climate, vegetation, and butterfly populations, providing a more robust context for understanding these complex interactions and their responses to anthropogenic changes over time.

5. Conclusions

Our findings reinforce the paramount importance of preserving intact forest ecosystems to sustain diverse ecological communities in the long-term. While plantations afford some habitat value versus intensive agriculture, they represent a markedly degraded state. Seasonal resource pulses can temporarily boost diversity but cannot compensate fully for chronic habitat degradation. Maintaining heterogeneous landscapes, promoting connectivity, and mitigating anthropogenic pressures like habitat conversion will be crucial for facilitating dispersal, enhancing community resilience, and conserving biodiversity amid accelerating global change [54,105,106]. This integrated investigation advances our understanding of biodiversity responses to different human disturbance regimes, while underscoring needs for additional targeted research developing robust mitigation strategies to sustain at-risk ecological communities in human-dominated environments.

Author Contributions

Conceptualization, K.L.-V. and C.L.; methodology, K.L.-V., C.L. and P.C.; software, K.L.-V., C.L. and P.C.; validation, K.L.-V., C.L. and P.C.; formal analysis, K.L.-V., C.L., P.C. and C.C.-G.; investigation, K.L.-V. and C.L.; resources, K.L.-V. and C.L.; data curation, K.L.-V. and C.L.; writing—original draft preparation, K.L.-V. and C.L.; writing—review and editing, K.L.-V., C.L., P.C. and C.C.-G. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by CONAHCyT, Mexico through a doctoral scholarship to K.L.-V. (1003512).

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors on request.

Acknowledgments

We gratefully acknowledge Mauro Piedras, Deysi Muñoz and Mariana Cuautle for field assistance. This work constitutes partial fulfillment of Karla María López-Vázquez’s doctorate degree requirements at UAM. The authors thank José de Jesús García Díaz for their support with the butterfly species identification. We thank the Academic Editor and three anonymous reviewers for their invaluable feedback regarding the manuscript.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Study site and vegetation characteristics in Tlaxcala, Mexico. (A) Satellite image from Google Earth™ with colored overlays depicting juniper forest (yellow), eucalyptus forest (blue), and agricultural land (orange). Colored dots indicate survey transects. (B–D) Dry season and (E–G) rainy season images of the three vegetation types, demonstrating marked seasonal variation in vegetation cover and lushness.
Figure 1. Study site and vegetation characteristics in Tlaxcala, Mexico. (A) Satellite image from Google Earth™ with colored overlays depicting juniper forest (yellow), eucalyptus forest (blue), and agricultural land (orange). Colored dots indicate survey transects. (B–D) Dry season and (E–G) rainy season images of the three vegetation types, demonstrating marked seasonal variation in vegetation cover and lushness.
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Figure 2. Diversity of butterfly (A) and flowering-plant (B) species across three vegetation types during the rainy (solid lines) and dry (dashed lines) seasons. Three diversity orders are presented: q = 0 (richness), q = 1 (Shannon entropy), and q = 2 (inverse Simpson), with their 95% confidence intervals. The vegetation types include agricultural sites, juniper forest, and eucalyptus forest. Overlapping intervals suggest no significant differences, while non-overlapping intervals indicate significant differences (p < 0.05) in diversity indices.
Figure 2. Diversity of butterfly (A) and flowering-plant (B) species across three vegetation types during the rainy (solid lines) and dry (dashed lines) seasons. Three diversity orders are presented: q = 0 (richness), q = 1 (Shannon entropy), and q = 2 (inverse Simpson), with their 95% confidence intervals. The vegetation types include agricultural sites, juniper forest, and eucalyptus forest. Overlapping intervals suggest no significant differences, while non-overlapping intervals indicate significant differences (p < 0.05) in diversity indices.
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Figure 3. Species rank-abundance plots showing the log-scaled abundance of butterfly species (A) and flowering-plant species (B) across the three vegetation types monitored. Species are ranked on the x-axis from highest to lowest abundance, with rank 1 (leftmost) representing the most abundant species and increasing rank numbers (moving right) indicating progressively less abundant species. This ranking visualizes both species richness (total number of points) and evenness (slope of the line) for each vegetation type.
Figure 3. Species rank-abundance plots showing the log-scaled abundance of butterfly species (A) and flowering-plant species (B) across the three vegetation types monitored. Species are ranked on the x-axis from highest to lowest abundance, with rank 1 (leftmost) representing the most abundant species and increasing rank numbers (moving right) indicating progressively less abundant species. This ranking visualizes both species richness (total number of points) and evenness (slope of the line) for each vegetation type.
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Figure 4. Non-metric multidimensional scaling (NDMS) ordination with solid ellipses encircling vegetation types during rainy and dry seasons based on butterfly (A) and flowering-plant (B) community composition. One set of ellipses encloses all vegetation types in the rainy season, while another set encloses them in the dry season. Vegetation types are represented by symbols: agriculture sites (yellow circles), juniper forest (orange triangles), and eucalyptus forest (blue squares). The closer the symbols within each seasonal ellipse, the more similar the community composition across vegetation types for that season within each panel. The statistical significance of the differences observed between groups was assessed using ANOSIM (Analysis of Similarities). For butterflies, the global R statistic was R = 0.85 (p = 0.0001), indicating a strong separation between community compositions across the different vegetation types and seasons. For plants, the global R statistic was R = 0.32 (p = 0.0002), showing a moderate but significant separation in community composition.
Figure 4. Non-metric multidimensional scaling (NDMS) ordination with solid ellipses encircling vegetation types during rainy and dry seasons based on butterfly (A) and flowering-plant (B) community composition. One set of ellipses encloses all vegetation types in the rainy season, while another set encloses them in the dry season. Vegetation types are represented by symbols: agriculture sites (yellow circles), juniper forest (orange triangles), and eucalyptus forest (blue squares). The closer the symbols within each seasonal ellipse, the more similar the community composition across vegetation types for that season within each panel. The statistical significance of the differences observed between groups was assessed using ANOSIM (Analysis of Similarities). For butterflies, the global R statistic was R = 0.85 (p = 0.0001), indicating a strong separation between community compositions across the different vegetation types and seasons. For plants, the global R statistic was R = 0.32 (p = 0.0002), showing a moderate but significant separation in community composition.
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Figure 5. Redundancy analysis (RDA) ordination biplot with RDA1 and RDA2 axes relating butterfly community data to plant community variables (plant richness and flower abundance). Open circles represent individual butterfly species, and color-coded symbols represent the vegetation type. The arrows indicate the direction of increasing values for plant richness and flower abundance. Butterfly species in eucalyptus forests are more closely associated with higher flower abundance, while those in juniper forests are more closely associated with higher plant richness. Butterfly species in agriculture sites show a weaker association with both explanatory variables. The RDA model was statistically significant with a permutation test (F = 4.56, p = 0.001).
Figure 5. Redundancy analysis (RDA) ordination biplot with RDA1 and RDA2 axes relating butterfly community data to plant community variables (plant richness and flower abundance). Open circles represent individual butterfly species, and color-coded symbols represent the vegetation type. The arrows indicate the direction of increasing values for plant richness and flower abundance. Butterfly species in eucalyptus forests are more closely associated with higher flower abundance, while those in juniper forests are more closely associated with higher plant richness. Butterfly species in agriculture sites show a weaker association with both explanatory variables. The RDA model was statistically significant with a permutation test (F = 4.56, p = 0.001).
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Figure 6. Indicator values for butterfly species in each (A) vegetation type and (B) season. Taller bars indicate stronger association between a species and that vegetation type or season. The color gradient from yellow to purple represents increasing indicator values, with purple being the strongest indicators.
Figure 6. Indicator values for butterfly species in each (A) vegetation type and (B) season. Taller bars indicate stronger association between a species and that vegetation type or season. The color gradient from yellow to purple represents increasing indicator values, with purple being the strongest indicators.
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Figure 7. Indicator values displayed for plant species across (A) vegetation types and (B) seasons. Bar height corresponds to the strength of association between a given plant species and the specified vegetation type or season. Taller bars signify stronger indicator values. The color ramp transitions from yellow to purple, representing increasing indicator values.
Figure 7. Indicator values displayed for plant species across (A) vegetation types and (B) seasons. Bar height corresponds to the strength of association between a given plant species and the specified vegetation type or season. Taller bars signify stronger indicator values. The color ramp transitions from yellow to purple, representing increasing indicator values.
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Table 1. Butterfly species in each vegetation type recorded throughout the study.
Table 1. Butterfly species in each vegetation type recorded throughout the study.
FamilySpeciesAgriculture SitesJuniper ForestEucalyptus Forest
PapilionidaeBattus philenor philenor (Linnaeus, 1771)XX X
Mimoides thymbraeus (Boisduval, 1836)X
Pterourus garamas garamas (Geyer, Geyer, [1829]) X
Pterourus multicaudata multicaudata (Kirby, 1884)XX X
Heraclides pharnaces (Doubleday, 1846)XX
Papilio polyxenes asterius (Stoll, 1782) X
PieridaeAbaeis mexicana mexicana (Boisduval, 1836) X X
Anteos maerula (Fabricius, 1775) X
Archonias nimbice nimbice (Boisduval, 1836)XX X
Colias eurytheme (Boisduval, 1852)X
Abaeis salome jamapa (Reakirt, 1866) X
Ganyra josephina josepha (Godman & Salvin, 1868)XX X
Leptophobia aripa elodia (Boisduval, 1836)XX X
Nathalis iole iole (Boisduval, 1836)XX X
Phoebis agarithe agarithe (Boisduval, 1836)XX X
Phoebis argante argante (Fabricius, 1775) X X
Phoebis neocypris virgo (Butler, 1870)XX X
Phoebis philea philea (Linnaeus, 1763) X
Phoebis sennae marcellina (Cramer, 1777)XX X
Pieris rapae rapae (Linnaeus, 1758) X
Pontia protodice (Boisduval & Le Conte, [1830])X X
Zerene cesonia cesonia (Stoll, 1790)XX X
NymphalidaeAdelpha paroeca paroeca (Bates, 1864) X
Anartia fatima fatima (Fabricius, 1793)XX X
Anthanassa texana (Edwards, 1863)X
Chlosyne ehrenbergii (Geyer, [1833])X
Chlosyne marina (Geyer, 1837) X
Cyllopsis pyracmon pyracmon (Butler,1867) X
Danaus eresimus montezuma Talbot, 1943XX
Danaus gilippus thersippus (Bates, 1863)XXX
Danaus plexippus plexippus (Linnaeus, 1758)XXX
Dione juno huascuma (Reakirt, 1866)XXX
Dione moneta poeyii Bluter, 1873XXX
Dione incarnata incarnata (Riley, 1926)XXX
Euptoieta claudia claudia (Cramer, 1775)XXX
Euptoieta hegesia meridiania (Stichel, 1938)XXX
Phyciodes graphica graphica (Felder, 1869)X
Vanessa annabella (Field, 1971)XXX
Vanessa cardui (Linnaeus, 1758) X
LycaenidaeBrephidium exilis exilis (Boisduval, 1852) XX
Echinargus isola (Reakirt, 1867)XXX
Callophrys spinetorum millerorum (Clench, 1981) X
Leptotes cassius cassidula (Boisduval, 1870) X
Leptotes marina (Reakirt, 1868) XX
HesperiidaeAmblyscirtes fimbriata fimbriata (Plötz, 1882)XX
Atalopedes huron (Edwards, 1863) XX
Burnsius communis albescens (Plötz, 1884) X
Calpodes ethlius (Stoll, 1782)X
Cecropterus cincta (Plötz, 1882) X
Eantis pallida (Felder, 1869)XXX
Lerema accius (Smith, 1797) X
Oarisma edwardsii (Barnes, 1897)XX
Telegonus cellus (Boisduval & Le Conte, [1837])XX
ErebidaeApantesis proxima (Guérin-Méneville, 1831) X
Dysschema howardi (Edwards, 1886) X
CrambidaeFissicrambus sp. (Bleszynski, 1825) X
Pyrausta inornatalis (Fernald, 1885) X
Table 2. List of the plant species used by butterflies for nectar feeding and recorded in the three vegetation types throughout the study.
Table 2. List of the plant species used by butterflies for nectar feeding and recorded in the three vegetation types throughout the study.
FamilySpeciesAgriculture SitesJuniper ForestEucalyptus Forest
PhytolaccaceaePhytolacca icosandra L., 1753 X
PapaveraceaeArgemone platyceras Link & Otto, 1828X
BrassicaceaeRaphanus sativus L., 1753X
FabaceaeErythrina coralloides DC., 1825 X
Mimosa aculeaticarpa Ortega, 1798XX X
Senna multiglandulosa (Jacq.) H. S. Irwin & Barneby, 1982 X
AnacardiaceaeRhus integrifolia (Nutt.) Brebner ex W. H. Brewer & S.Watson, 1876 X X
OnagraceaeOenothera gaura Raf., 1836X
ConvolvulaceaeEvolvulus prostratus Rob., 1962 X
PolemoniaceaeLoeselia mexicana (Lam.) Brand, 1907 X X
LamiaceaeClinopodium multiflorum (Romo & Delgadillo) B. L. Turner, 1994X
SolanaceaePhysalis philadelphica Lam., 1793X
Solanum carolinense L., 1753 X
RubiaceaeBouvardia ternifolia (Cav.) Schltdl., 1819XX X
AsteraceaeAmblyopappus pusillus Hooker & Arnott, 1835 X
Baccharis breviseta DC., 1836 X
Baccharis salicifolia (Ruiz & Pav.) Pers., 1807 X X
Barkleyanthus salicifolius (Kunth) H.Rob. & Brettell, 1974X
Bidens odorata Cav., 1794 X
Brickellia californica (Torr. & A.Gray) A. Gray, 1873X
Dahlia coccinea Cav., 1791XX X
Dyssodia papposa (Vent.) Hitchc., 1932 X
Eremosis corymbosa (DC.) Gleason, 1923 X
Garberia heterophylla (W.M.Wood) Merr. & F. Harper, 1909 X X
Heterotheca grandiflora Nutt., 1841X
Pseudognaphalium gaudichaudianum (DC.) Anderb., 2012X
Stevia elatior Kunth, 1818 X
Stevia serrata Cav., 1794 X
Tagetes lucida Cav., 1794 X
Tithonia tubiformis (Jacq.) Cass., 1825X X
Tridax procumbens L., 1753X X
AmaryllidaceaeZephyranthes brevipes (Engelm. ex Buckley) Ingram, 1940X
OrchidaceaeDichromanthus cinnabarinus (La Llave & Lex.) Garay, 1982X
PhytolaccaceaePhytolacca icosandra L., 1753 X
Table 3. Butterfly and flowering-plant diversity indicators, including the total number of sampled individuals (number of flowers in the case of plants), number of species, richness (q = 0), common species (q = 1), and dominant species (q = 2) across the three sampled vegetation types. Significant differences (p < 0.05), indicated by non-overlapping 95% confidence intervals among the three vegetation types, are marked with asterisks.
Table 3. Butterfly and flowering-plant diversity indicators, including the total number of sampled individuals (number of flowers in the case of plants), number of species, richness (q = 0), common species (q = 1), and dominant species (q = 2) across the three sampled vegetation types. Significant differences (p < 0.05), indicated by non-overlapping 95% confidence intervals among the three vegetation types, are marked with asterisks.
CommunityIndicatorAgriculture SitesJuniper ForestEucalyptus Forest
ButterflyIndividuals366434590
Species323146
q039.2033.11 *48.70
q112.4915.0620.95 *
q26.347.6112.85 *
PlantsFlowers966625,90837,279
Species181216
q018.112.1 *16.1
q15.206.173.97 *
q22.91 *4.433.19
Table 4. Results of the SIMPER analysis showing (A) butterfly and (B) flowering-plant species contributing most (in order of decreasing percentage) to dissimilarity between vegetation types. For plant species, mean abundance measures refer specifically to flowers. All dissimilarity values shown were statistically significant (p < 0.05).
Table 4. Results of the SIMPER analysis showing (A) butterfly and (B) flowering-plant species contributing most (in order of decreasing percentage) to dissimilarity between vegetation types. For plant species, mean abundance measures refer specifically to flowers. All dissimilarity values shown were statistically significant (p < 0.05).
(A) Butterfly SpeciesAgriculture Sites Mean AbundanceJuniper Forest Mean AbundanceEucalyptus Forest Mean Abundance% Contribution to Dissimilarity
Zerene cesonia cesonia11.726.350.715.32
Battus philenorphilenor43.331.347.313.63
Agraulisincarnata incarnata429.32.3310.19
Echinargus isola0.6674.3312.34.576
Leptophobia aripaelodia111.671.674.165
Nathalis ioleiole3.6713.38.334.081
Dione junohuascuma6910.33.902
Leptotes marina05.676.673.162
Fissicrambus sp.0.66783.673.059
Euptoieta claudiaclaudia17.674.672.894
Ganyra josephinajosepha0.3331.3372.488
Pterourus multicaudata multicaudata77.336.332.331
Colias eurytheme5.33002.303
(B) Plant Species
Rhus integrifolia01000466037.86
Loeselia mexicana04320595024.61
Mimosa aculeaticarpa1790264033506.384
Raphanus sativus1350005.706
Tithonia tubiformis91906.333.87
Eremosis corymbosa0010303.811
Salvia polystachya090903.215
Bouvardia ternifolia88416108232.84
Table 5. Results of the SIMPER analysis showing (A) butterfly and (B) flowering-plant species contributing most (in order of decreasing percentage) to dissimilarity between the rainy and dry seasons. For plant species, mean abundance measures refer specifically to flowers. All dissimilarity values shown were statistically significant (p < 0.05).
Table 5. Results of the SIMPER analysis showing (A) butterfly and (B) flowering-plant species contributing most (in order of decreasing percentage) to dissimilarity between the rainy and dry seasons. For plant species, mean abundance measures refer specifically to flowers. All dissimilarity values shown were statistically significant (p < 0.05).
(A) Butterfly SpeciesRainy Mean AbundanceDry Mean Abundance% Contribution to Dissimilarity
Battus philenorphilenor30.99.7820.58
Zerenecesonia cesonia14.42.7810.87
Nathalis ioleiole7.890.5566.678
Dione incarnata incarnata7.673.446.148
Dione junohuascuma7.1115.872
Pterorurus multicaudata multicaudata5.671.224.315
Dione monetapoeyyi40.3333.309
Phoebis sennae marcellina3.330.1113.154
Echinargus isola1.673.672.808
Danaus gilippusthersippus2.8902.761
Leptophobia aripaelodia2.781.782.718
Ganyra josephinajosepha2.780.1112.485
Leptotes marina2.561.562.197
(B) Plant species
Rhus integrifolia0303023.25
Loeselia mexicana142133013.6
Mimosa aculeaticarpa0140013.47
Raphanus sativus44915310.43
Bouvardia ternifolia23412.47.651
Salvia polystachya25105.187
Rhus integrifolia0303023.25
Loeselia mexicana142133013.6
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López-Vázquez, K.; Lara, C.; Corcuera, P.; Castillo-Guevara, C. Temporal Shifts in Flower-Visiting Butterfly Communities and Their Floral Resources along a Vegetation Type Altered by Anthropogenic Factors. Forests 2024, 15, 1668. https://doi.org/10.3390/f15091668

AMA Style

López-Vázquez K, Lara C, Corcuera P, Castillo-Guevara C. Temporal Shifts in Flower-Visiting Butterfly Communities and Their Floral Resources along a Vegetation Type Altered by Anthropogenic Factors. Forests. 2024; 15(9):1668. https://doi.org/10.3390/f15091668

Chicago/Turabian Style

López-Vázquez, Karla, Carlos Lara, Pablo Corcuera, and Citlalli Castillo-Guevara. 2024. "Temporal Shifts in Flower-Visiting Butterfly Communities and Their Floral Resources along a Vegetation Type Altered by Anthropogenic Factors" Forests 15, no. 9: 1668. https://doi.org/10.3390/f15091668

APA Style

López-Vázquez, K., Lara, C., Corcuera, P., & Castillo-Guevara, C. (2024). Temporal Shifts in Flower-Visiting Butterfly Communities and Their Floral Resources along a Vegetation Type Altered by Anthropogenic Factors. Forests, 15(9), 1668. https://doi.org/10.3390/f15091668

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