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Article

Microclimatic Fluctuation throughout the Day Influences Subtropical Fruit-Feeding Butterfly Assemblages between the Canopy and Understory

by
Aline Richter
1,2,*,
Milton de Souza Mendonça, Jr.
2,
Karine Gawlinski
2 and
Cristiano Agra Iserhard
1,*
1
Programa de Pós-Graduação em Biodiversidade Animal, Departamento de Ecologia, Zoologia e Genética, Universidade Federal de Pelotas, Pelotas 96.160-000, Rio Grande do Sul, Brazil
2
Programa de Pós-Graduação em Ecologia, Departamento de Ecologia, Universidade Federal do Rio Grande do Sul, Porto Alegre 91.509-900, Rio Grande do Sul, Brazil
*
Authors to whom correspondence should be addressed.
Diversity 2023, 15(4), 560; https://doi.org/10.3390/d15040560
Submission received: 10 March 2023 / Revised: 7 April 2023 / Accepted: 14 April 2023 / Published: 16 April 2023
(This article belongs to the Special Issue Biodiversity and Ecology of Butterflies)
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Abstract

:
Vertical stratification is a recognized pattern in tropical forests; however, biotic and abiotic factors driving this pattern are little explored. We investigated the influence of daily climatic variation in the vertical stratification of fruit-feeding butterfly assemblages sampled with bait traps in the understory and canopy of a subtropical Atlantic Forest. Overall, 1347 individuals belonging to 38 species of fruit-feeding butterflies were recorded. The canopy and understory are distinct concerning diurnal but not nocturnal microclimatic conditions, leading to different responses in community structure. Richness did not differ between strata, but we observed an effect of stratum in interaction with variation in microclimatic conditions, with the canopy increasing in abundance compared to the understory. Temperature homogenization at night can hinder vertical stratification in richness, while microclimatic variation influences species abundance. The species composition was affected by strata with high turnover in the understory, without an effect of microclimatic variables in beta diversity. In addition to the difference in composition, our study shows that the understory was represented mainly by species from Satyrinae, while the canopy presented species from different clades. This could be an artefact of habitat structure, and the species adapted to the closed forest have a dispersal limitation compared to in the canopy. These findings help us to better understand the mechanisms generating distinct patterns of vertical stratification of fruit-feeding butterflies in the Neotropics and provide new insights into the role of microclimatic conditions in the structure of insect assemblages.

1. Introduction

Tropical and subtropical forests support a high insect diversity [1,2], and a large portion of this diversity seems to be associated with the canopy [3]. Forest vertical stratification in distinct layers, such as the understory and canopy, leads to variations in microhabitat conditions at the local scale (e.g., light intensity, temperature, and wind speed, leading to differences in resource availability for different organisms) and, hence, can affect invertebrate distribution [3,4,5]. Subtropical forests, located at latitudes between 24° and 34° in the Northern and Southern hemispheres, are generally less structurally complex, have lower plant species richness, and have shorter canopy heights than tropical rainforests [3,6]. These characteristics could lead to less pronounced vertical stratification, causing a reduction in the alpha diversity of canopy-specialized organisms while maintaining a high disparity between strata (and, thus, potentially high beta diversity) [7,8,9,10]. Furthermore, other subtropical forest features could maintain a vertical stratification, such as daily climatic fluctuation [2,11], promoting relatively high differences in temperature during the day but homogenizing temperature at night [12]. In addition to the effects of climate and forest height, forests in elevated areas can exhibit further variations in temperature, light availability, and precipitation, consequently affecting the distribution of insects [13].
The Atlantic Forest is a heterogeneous and threatened Brazilian biome considered a diversity hotspot with high rates of endemism, including butterfly species [1,14,15]. The Araucaria Forest belongs to the Atlantic Forest domain and is viewed as a transitional zone between dense ombrophilous forest and seasonal semideciduous forest, forming a conspicuous environmental transition that leads to high species turnover [16]. The Araucaria forests extend across the south of Brazil between latitudes 20° S and 29° S and are strongly associated with highland plateaus (between 500 and 1200 m a.s.l.) [17]. Hence, this forest formation is subjected to a tropical climate in the northern part of their distribution and a subtropical climate in the southern part, with the latter consisting of four well-defined seasons [2]. Unlike tropical regions where the effects of microclimatic variation on insect assemblages are relatively well explored [18,19,20,21], this relationship is little known for subtropical forests.
Fruit-feeding butterflies are considered models for ecological studies and represent environmental quality and good predictors of diversity parameters, representing the diversity of other groups [1,22]. Their preference for a specific vegetational stratum along vertical gradients is relatively well described in the literature for the tropical zone worldwide [4,5,18,23,24,25]. These preferences are highly influenced by abiotic (temperature, humidity, luminosity, and wind speed) and biotic factors (vegetation architecture, resource availability, and presence of predators), as well as morphological traits related to flight performance [24,26,27]. Several studies indicate a clear segregation of strata leading to high beta diversity [25,28] and suggest species turnover as the main process that structures butterfly assemblages [18,29]. On the other hand, patterns in alpha diversity are inconsistent for fruit-feeding butterfly communities when comparing the understory and canopy. The most diverse stratum between these two strata depends on the region of the tropics considered (canopy for Central and South America butterflies [5,6,18,25,30] and understory for Afrotropical/Indo-Malaysian ones [4,31,32,33]).
This biogeographic incongruence highlights our lack of understanding of which factors are important in driving vertical stratification butterfly communities. It is known that canopies face more diel variation in conditions than the understory, thus having more stable conditions since the canopy itself would buffer the understory from insolation and air temperature changes throughout the day [34]. For ectothermic insects that respond to fine-scale abiotic factors, variation in microclimatic conditions can generate effects on species distribution comparable to the effect of the latitudinal gradient for other organisms [35]. Moreover, insect distributions may also be constrained at higher elevations as a result of reduced convective energy transfer and flight performance, and higher elevations may also lead to variation in adaptive strategies such as polymorphism and thermal tolerance [13,36], affecting the behavior and flight activity of butterflies [37]. However, it is unusual to find direct comparisons between butterfly diversity patterns and these potentially important proximal abiotic environmental factors, which would be the best prospect for solving our lack of knowledge on this topic.
Our study aims to evaluate how vertical stratification and microclimatic conditions affect the structure of fruit-feeding butterfly assemblages (alpha and beta diversity) in a subtropical Atlantic Forest region in southern Brazil. We aim to answer the following questions: (i) Is there an effect of temperature and humidity at different times of the day or night mediated by stratum on species richness and abundance? (ii) Is there a response of different components of beta diversity to environmental variation between strata? (iii) Can we find groups of species with preferences for one of the strata? We predict that the understory would show greater richness and abundance under warmer conditions, while the canopy would have greater diversity under wetter conditions. For beta diversity, we predict a difference in species composition between strata, in which canopy sites would have less replacement of individuals of different species from site to site because species in this stratum can tolerate open habitat conditions and move between sites more freely than understory species.

2. Materials and Methods

The Floresta Nacional de São Francisco de Paula (FLONA-SFP) is located in the municipality of the same name, in the northeastern region of Rio Grande do Sul (centered at 29°25′22″ S; 50°23′11″ W), the southernmost Brazilian state, in South America (Figure 1). FLONA-SFP is located at approximately 900 m a.s.l. and comprises 1615 ha of native mixed ombrophilous forest with Araucaria angustifolia (Bertol.) Kuntze, as well as patches of Pinus sp. and Eucalyptus sp. plantations [38]. The vegetation is composed of elements from the dense ombrophilous forest (Atlantic Forest stricto sensu) and seasonal semideciduous forest, also exhibiting a mosaic landscape with subtropical highland grasslands [39]. The climate is subtropical without a dry season, with a mean annual rainfall of about 2000 mm and a mean temperature of 14.5 °C [40].
Samples were carried out with Van Someren–Rydon bait traps [41] in two periods, the first between November 2016 and March 2017, and the second between October 2017 and March 2018, representing the best period for butterfly sampling in the subtropical Atlantic Forest [2]. In both periods, data were collected monthly, and the traps remained open for about 8 days. We used six transects in Araucaria Forest, distant, at least 600 m from each other, with ten bait traps in each transect, totaling 60 traps. In each transect, five traps were placed in the canopy (~15 m above the ground, inside canopy tree crowns), alternating with five in the understory (1.5 m above the ground), at a horizontal distance of 20 m from each other. Each set of five bait traps per stratum composed a sampling unit. The baits consisted of a mixture of mashed banana and sugarcane juice, fermented for 48 h before sampling [41]. Traps were checked every 48 h, with baits replaced, and captured butterflies were identified in the field, also determining sex, marking with sequential Arabian numbers with a permanent pen, and then releasing all individuals. This mark–release procedure avoids the recounting of individuals during each sampling occasion. Exceptions were cases of notably difficult species identification or the need for vouchers (three specimens per species), which were collected for posterior identification. The voucher species are deposited in the Lepidoptera Collection of Museu de Ciências Naturais Carlos Ritter, Instituto de Biologia at Universidade Federal de Pelotas (UFPel).
We measured the variation in air temperature and humidity between the canopy and understory using data loggers (Hobbo®) placed inside the traps in each stratum, in which the data loggers were exchanged among sampling units during the sampling occasions to cover all studied areas in FLONA-SFP. Measurements were carried out at 30 min intervals during all days within the sampling occasion. Months during which it was not possible to measure environmental variables were removed from the analysis, with seven out of 11 months of sampling remaining.
We consider each transect per stratum within a month as a sampling unit (2 stratum × 6 transects × 7 months = 84). Values for butterfly abundance, richness, mean temperature, and humidity represent the average values for each transect in each sampling month. We consider that transects sampled in the same month were not independent, adjusting for this in models for alpha and beta diversity.
We explored the variation in diversity profile between the canopy and understory using rarefaction and extrapolation curves based on Hill number and distinct q parameters [42,43]. These parameters measure the sensitivity to increments in abundance weight, where q = 0 is analogous to species richness, and q = 1 and q = 2 are analogous to the Shannon index (evenness) and Simpson index (dominance), respectively [43].
We investigated whether the mean and standard deviation of temperature and humidity affected the richness or abundance of fruit-feeding butterflies between strata and the period of the day (day or night). We considered day periods between 8:00 and 18:00, and night periods between 18:00 and 08:00, defined according to the predicted daily activity for fruit-feeding butterflies [44]. We employed a generalized mixed model to test the following hypothesis:
Si or Ni = αj(i) + β1i × Tmeanday + β2i × Tsdnight + β3i × Tmeanday: Strataund +β4i × Tsdnight: Strataund +β5i × Hmeanday:Stratacan +β6i × Hmeanday: Strataund +ε,
along with the following structure of the random effects for intercepts:
αj ~ Normal(μα, σα),
where S and N are the richness and abundance, respectively, for each transect in each sampling month, α is the intercept (canopy by default), β1 to β6 are the slopes, the index i indicates the sampling units, and j represents the random term associated with the sampling month that surveys were realized. Strata is a categorical variable with two levels (can = canopy or und = understory), Tmean and Tsd are the mean and standard deviation of temperature, and Hmean is the mean humidity, subscribed by the period of day (day or night). ε is the residual that we assumed to come from a Poisson distribution for S and a negative binomial distribution for N. We evaluated the collinearity among predictors by employing a variance inflator factor (VIF) [45], and the predictor variables were standardized (centered at zero and scaled).
To analyze butterfly assemblage species composition, we accessed the total beta diversity among sites (βtot) and decomposed it into the relativized species replacement component (βrep) and the richness differences component (βric). We generated the beta diversity components using abundance data and the Sørensen index of dissimilarity. These components were used in a permutational multivariate analysis of variance to evaluate the effects of environmental variables (stratum, mean temperature of the day, the standard deviation of temperature at night, and mean humidity of the day) over species composition. We also tested the homogeneity in group variation [46] and constraint permutation within the sampling month.
We also used indicator value analysis (IndVal) [47] to check whether species or groups of species could be considered indicators of canopy and understory habitats. This analysis uses the relationship between species abundances and environment specificity and fidelity. Values of specificity equal to 1 indicate that per species were present in all sites and sampling occasions, while values of fidelity equal to 1 indicate the probability of finding the same species in the same group of sites in all samplings [48].
All data analysis was performed in the R environment (v. 4.1.1) [49]. For estimates of sampling coverage and diversity profiles (function ChaoHill described in [50], we used package iNEXT (v. 2.0.20)) [51]. Mixed models were performed with the lme4 package (v. 1.1-27.1) [52], and the variance inflator factor was performed with the car package (v. 3.0-11) [53]. IndVal was assessed with the function multipatt of the indicspecies package (v. 1.7.9) [54]. For beta diversity analysis, we used the packages vegan (v. 2.5-7) [55] and BAT (v. 2.9.2) [56]. All graphics were generated with the package ggplot2 (v. 3.3.5) [57]. All code needed to perform the analysis used for this manuscript can be found at https://github.com/richterbine/Vertical_Stratification_bfly/tree/master, accessed on 3 April 2023.

3. Results

After 2450 trap days of sampling effort, we captured 1347 individuals representing 38 species of fruit-feeding butterflies distributed in the four subfamilies of Nymphalidae (Table S1, supporting information). Canopy had 30 species and 563 individuals, whereas understory had 25 species and 784 individuals. Both strata exhibited 99% sampling coverage, indicating an adequate representation of butterfly assemblages. Seventeen species were shared between strata, 13 were exclusive to the canopy, and eight were exclusive to the understory. Satyrinae was the most represented subfamily with 22 species (83.7%), followed by Charaxinae with eight (12.4%), Biblidinae with seven (3.5%), and Nymphalinae with only one species (0.4%).
The rarefaction and extrapolation diversity curves (Supplementary Figure S1), as well as the diversity profiles (Figure 2), indicated an inversion of the most diverse strata according to the weight given to abundance. At q = 0 and q = 1, the strata did not differ in diversity, whereas, at q = 2, the understory had lower dominance than the canopy. This indicates that species abundance in the understory is more evenly distributed, mainly because the canopy exhibited a high dominance by a single species Carminda paeon (Godart, [1824]), which made up 53% of the total abundance of the stratum (Table S1, supporting information).

3.1. Environmental Effects on Richness and Abundance

The effect of environmental variables was only significant for abundance since, for richness, the model was worse than the null model (Table 1). The abundance of fruit-feeding butterflies increased with temperature and relative humidity of the day independently of the stratum (no interaction, Figure 3a,c), while the effect of variation in temperature at night was mediated by the strata (Table 2). The canopy showed a larger increase in predicted abundance when the variation in temperature increased (Figure 3b), whereas, for the understory, the increase in abundance was less pronounced.

3.2. Environmental Effects on Beta Diversity

The total beta diversity (βtot) in the subtropical Araucaria Forest was 0.885, driven by a small difference between the βrep and βric components (0.420, sd = 0.278 and 0.465, sd = 0.271, respectively). We observed that βtot was affected only by strata (Table 3), despite the lower R2 value (0.03), whereby the variation between understory sites was higher than the variation between canopy sites (Figure 4a,d). The beta components βrep and βric (Figure 4b,c) did not show effects of environmental variables evaluated or strata, although we observed that the stratum had a similar R2 value to that found in the model for βtot (Table 3). Moreover, IndVal generated two groups, with 11 out of the 38 species associated with one or the other stratum (Table 4). Five species belonging to the Satyrini tribe (Satyrinae), Charaxinae, Biblidinae, and Nymphalinae, can be considered canopy indicators, and six species corresponding to Satyrinae can be considered understory indicators.

4. Discussion

In this study, we report for the first time the response of fruit-feeding butterflies to environmental conditions across vertical strata in a subtropical region, highlighting the role of daily variation in microclimatic conditions on the structure of these assemblages. We emphasize the importance of the mean and deviation of temperature for abundance, not only for the period of butterfly activity but also for the nighttime, especially in canopy communities. In this stratum, fluctuation throughout the day is more pronounced than in the understory since, during the day, the canopy reaches higher average temperature values than the understory [58], whereas, at night, the temperature is homogenized between the strata [12], which was also confirmed by our data (Supplementary Figure S2). Although these organisms have a diurnal or crepuscular activity [44], they need adaptations to survive at night, especially in environments such as the Araucaria forests, which are associated with higher altitudes and where the observed minimum temperatures can reach below 10 °C in the summer period.
It is recognized that abiotic conditions, such as temperature, rainfall, and luminosity, affect the richness and abundance of fruit-feeding butterflies locally [18,19,21]. Thus, thermal variation in the microhabitat scale and the relationship with physiological and morphological components may be important for understanding how species and individuals are distributed along environmental gradients [35,59]. On the other hand, at a macroecological scale, these abiotic factors can determine the seasonal pattern in species occurrence in subtropical and temperate zones, limiting the growing season to the warmer months due to physiological constraints [59,60,61,62]. In temperate regions, climatic patterns are the most important factors influencing the distribution of species richness [19,61] and may override the effect of microclimatic variation. We observed that richness did not respond to daily variation or differ between strata. We suggest that the lack of stratification in richness in our study could have been an effect of macroclimatic conditions, which can determine the temperature homogenization at night, as well as influence the lower structural complexity of the forest (a relatively lower canopy height of about 10 to 25 m when compared with the Amazonian Forest, for example). Considering a microscale, the distribution of host plants can contribute to this lack of differentiation in richness, creating vertical connections between the understory and canopy using host plants in the immature stages [63], in which females of butterflies using the canopy may lay eggs in the low and middle understory. In this way, some canopy-dweller species can be caught in understory traps, thus inflating species richness.
We demonstrate that daily microclimatic variations are important in defining abundance, having distinct effects depending on the vertical stratum. Even though the canopy is warmer and drier than the understory (Supplementary Figure S2), an increase in mean temperature and humidity leads to an increase in abundance independently of strata despite the higher abundance of butterflies in the canopy. However, the vertical stratification on abundance was only observed when considering the variation of microclimatic conditions; an increase in the temperature variation had a positive effect on abundance for the canopy. This result highlights that the amplitude of variation in the temperature and humidity is important for species that inhabit the canopy layer. On the other hand, the butterflies that inhabit the understory have more stability concerning the microclimatic conditions. Unstable environments would allow individuals with different ecological requirements to be able to find the bait trap when the environment is within their optimal temperature range of activity [26]. This may be related to the difference in the intensity of the effect of environmental variation on the abundance in the canopy, corroborating the findings of Checa et al. [21] in warmer tropical forests.
The species composition is highly dissimilar between canopy and understory, as demonstrated in several studies regarding vertical stratification for fruit-feeding butterflies [6,18,21,25,30]. Our study corroborated this pattern and demonstrated that the understory has more dissimilarity among sites than the canopy. However, considering the components of beta diversity, the variables evaluated do not seem responsible for determining the processes of replacement and loss/gain of individuals within the community. The lack of effect of climatic conditions may be related to the scale of the study (microclimatic variations), and the greater dissimilarity of the understory may be due to the substitution in the number of individuals among the species. This variation is, possibly, associated with other characteristics across this gradient of vertical stratification, such as dispersal limitations of butterflies in the understory as a result of their specialization for inhabiting closed forests, or they may be determined by variables that act on a larger scale [64]. Furthermore, other facets of diversity, e.g., functional or phylogenetic, can influence the patterns of species distributions [64,65,66] and should be considered to better understand how assemblages are structured.
Through the analysis of indicator species, it is possible to define which species are more related to each stratum. Similar to other studies [18,25,26], we observed the strong association of Satyrinae with the understory, while the canopy encompassed species of the other subfamilies [18,25,26]. The association between Satyrinae and understory may result from a phylogenetic constraint [28] since the evolution of the group supposedly took place in closed forest environments [67]. The tribes Brassolini and Morphini have adaptations to use the understory of forests, such as larger body sizes and darker colors [26,35] and a short period of optimum adult activity during the year [62,68]. On the other hand, the more heterogenous canopy is defined by species with high mobility and the ability to tolerate greater environmental variations, such as many Charaxinae and Nymphalinae that are strongly associated with sunny habitats [18,26] and have fast thermoregulation with strong bodies and rapid flights [24,69]. This result may help us to understand the patterns observed for beta diversity. The highly mobile butterflies found in the canopy can lead to a homogenization of composition because they use the canopy as a corridor (or, more precisely, a sheet) to disperse between open patches perceiving this habitat as a green carpet [5,70].
From studies performed in the Neotropical region, diversity patterns of fruit-feeding butterflies’ distribution between canopy and understory may respond to several factors. Among them, the main one is the climate, which influences forest structure and seasonality, directly affecting fruit-feeding butterflies [60]. However, we demonstrate that microclimatic variation is very important to describe fruit-feeding butterfly assemblages’ local structure and abundance patterns. Our study can help to elucidate the distinct patterns found in this guild, mainly for alpha diversity in studies concerning vertical stratification. It seems that, for beta diversity, the pattern is more marked and consistent, with great convergence in all studies, indicating an intense selection pressure filtering the butterfly species between the canopy and understory. This study was the first to evaluate vertical stratification for fruit-feeding butterflies in a subtropical forest, helping to elucidate mechanisms and processes influencing these insect assemblages in the Neotropics. We hope that further studies strive to take microclimatic variation into account for short- and long-term evaluations to improve our knowledge of how assemblages are structured in subtropical areas worldwide.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/d15040560/s1: Figure S1: Rarefaction and extrapolation curves for fruit-feeding butterflies species diversity based on the Hill numbers for the canopy and the understory; Figure S2: Relationship between environmental variables and vertical stratum considering the day and night periods; Table S1: Species list of fruit-feeding butterflies in a mixed ombrophilous forest; Table S2: Relationship between environmental variables and vertical stratum considering the day and night periods.

Author Contributions

Conceptualization, A.R., M.d.S.M.J. and C.A.I.; methodology, A.R. and C.A.I.; validation, A.R., C.A.I. and M.d.S.M.J.; formal analysis, A.R.; investigation, A.R., K.G. and C.A.I.; resources, A.R., K.G. and C.A.I.; data curation, A.R., K.G. and C.A.I.; writing—original draft preparation, A.R.; writing—review and editing, A.R., M.d.S.M.J. and C.A.I.; supervision, C.A.I.; project administration, A.R., M.d.S.M.J., K.G. and C.A.I.; funding acquisition, A.R. and C.A.I. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) for graduate fellowships (financial code 001) to A.R. and K.G.; CNPq for a productivity scholarship (309616/2015-8) for M.M.J.; National Institutes for Science and Technology (INCT) in Ecology, Evolution, and Biodiversity Conservation, supported by MCTIC/CNPq (proc. 465610/2014-5) and FAPEG (proc. 201810267000023) for A.R. and C.A.I.

Institutional Review Board Statement

Not applicable.

Data Availability Statement

All code needed to perform the analysis used for this manuscript can be found at https://github.com/richterbine/Vertical_Stratification_bfly/tree/master (accessed in 3 April 2023) and in the Supplementary Materials.

Acknowledgments

The authors thank colleagues in the Laboratório de Ecologia de Lepidoptera and other friends that helped in field expeditions. The authors are grateful to the staff of Floresta Nacional de São Francisco de Paula for providing logistic assistance during the sampling periods, to Dra Karen Mustin for revision of the language of this manuscript, to the two anonymous reviewers for critically reviewing and valuable contributions to the manuscript, and to André Victor Lucci Freitas for help in the identification of some butterflies. Samples were procured under ICMBio permanent license number 45673-1 and research license numbers 54298-1 and 59568-1. This publication is part of the RedeLep ‘‘Rede Nacional de Pesquisa e Conservação de Lepidópteros’’ (National Network for Research and Conservation of Lepidoptera).

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Brown, K.S.; Freitas, A.V.L. Atlantic Forest Butterflies: Indicators for Landscape Conservation. Biotropica 2000, 32, 934–956. [Google Scholar] [CrossRef]
  2. Iserhard, C.A.; Romanowski, H.P.; Richter, A.; Mendonça, J.M.D.S. Monitoring Temporal Variation to Assess Changes in the Structure of Subtropical Atlantic Forest Butterfly Communities. Environ. Entomol. 2017, 46, 804–813. [Google Scholar] [CrossRef] [PubMed]
  3. Basset, Y.; Hammond, P.M.; Barrios, H.; Holloway, J.D.; Miller, S.E. Vertical Stratification of Arthropod Assemblages. In Arthropods of Tropical Forests: Spatio-Temporal Dynamics and Resource Use in the Canopy; Cambridge University Press: Cambridge, UK, 2003; pp. 17–27. [Google Scholar]
  4. Schulze, C.H.; Linsenmair, K.E.; Fiedler, K. Understorey versus Canopy: Patterns of Vertical Stratification and Diversity among Lepidoptera in a Bornean Rain Forest. Plant Ecol. 2001, 153, 133–152. [Google Scholar] [CrossRef]
  5. Devries, P.J. Stratification of Fruit-Feeding Nymphalid Butterflies in a Costa Rican Rainforest. J. Res. Lepid. 1988, 26, 98–108. [Google Scholar]
  6. Araujo, P.F.; Freitas, A.V.L.; De Souza, G.A.; Ribeiro, D.B. Studies on Neotropical Fauna and Environment Vertical Stratification on a Small Scale: The Distribution of Fruit-Feeding Butterflies in a Semi- Deciduous Atlantic Forest in Brazil. Stud. Neotrop. Fauna. Environ. 2020, 56, 10–39. [Google Scholar] [CrossRef]
  7. Hirao, T.; Murakami, M.; Kashizaki, A. Importance of the Understory Stratum to Entomofaunal Diversity in a Temperate Deciduous Forest. Ecol. Res. 2009, 24, 263–272. [Google Scholar] [CrossRef]
  8. Ulyshen, M.D. Arthropod Vertical Stratification in Temperate Deciduous Forests: Implications for Conservation-Oriented Management. Ecol. Manag. 2011, 261, 1479–1489. [Google Scholar] [CrossRef]
  9. Maguire, D.Y.; Robert, K.; Brochu, K.; Larrivée, M.; Buddle, C.M.; Wheeler, T.A. Vertical Stratification of Beetles (Coleoptera) and Flies (Diptera) in Temperate Forest Canopies. Environ. Entomol. 2014, 43, 9–17. [Google Scholar] [CrossRef]
  10. Ashton, L.A.; Nakamura, A.; Basset, Y.; Burwell, C.J.; Cao, M.; Eastwood, R.; Odell, E.; de Oliveira, E.G.; Hurley, K.; Katabuchi, M.; et al. Vertical Stratification of Moths across Elevation and Latitude. J. Biogeogr. 2016, 43, 59–69. [Google Scholar] [CrossRef]
  11. Danks, H.V. Winter Habitats and Ecological Adaptations for Winter Survival. Insects Low Temp. 1991, 1, 231–259. [Google Scholar] [CrossRef]
  12. Tal, O.; Freiberg, M.; Morawetz, W. Microclimate Variability in the Canopy of a Temperate Forest. Canopy Arthropod Res. Eur. 2008, 448, 49–59. [Google Scholar]
  13. Hodkinson, I.D. Terrestrial Insects along Elevation Gradients: Species and Community Responses to Altitude. Biol. Rev. Camb. Philos. Soc. 2005, 80, 489–513. [Google Scholar] [CrossRef] [PubMed]
  14. Brown, K.S. Conservation of Neotropical Environments: Insects as Indicators; The Royal Entomological Society of London: London, UK, 1991. [Google Scholar]
  15. Myers, N.; Mittermeier, R.A.; Mittermeier, C.G.; da Fonseca, G.A.B.; Kent, J. Biodiversity Hotspots for Conservation Priorities. Nature 2000, 403, 853–858. [Google Scholar] [CrossRef]
  16. Tabarelli, M.; Aguiar, A.V.; Ribeiro, M.C.; Metzger, J.P.; Peres, C.A. Prospects for Biodiversity Conservation in the Atlantic Forest: Lessons from Aging Human-Modified Landscapes. Biol. Conserv. 2010, 143, 2328–2340. [Google Scholar] [CrossRef]
  17. Hueck, K. As Florestas Da Ameérica Do Sul: Ecologia, Composição e Importancia Economica; Editora de Universidade de Brasilia: Brasilia, Brazil, 1972. [Google Scholar]
  18. dos Santos, J.P.; Iserhard, C.A.; Carreira, J.Y.O.; Freitas, A.V.L. Monitoring Fruit-Feeding Butterfly Assemblages in Two Vertical Strata in Seasonal Atlantic Forest: Temporal Species Turnover Is Lower in the Canopy. J. Trop. Ecol. 2017, 33, 345–355. [Google Scholar] [CrossRef]
  19. Checa, M.F.; Levy, E.; Rodriguez, J.; Willmott, K. Rainfall as a Significant Contributing Factor to Butterfly Seasonality along a Climatic Gradient in the Neotropics. BioRxiv 2019, 1, 1–32. [Google Scholar] [CrossRef]
  20. Checa, M.F.; Barragán, A.; Rodríguez, J.; Christman, M. Temporal Abundance Patterns of Butterfly Communities (Lepidoptera: Nymphalidae) in the Ecuadorian Amazonia and Their Relationship with Climate. Ann. Soc. Entomol. Fr. (N.S.) 2009, 45, 470–486. [Google Scholar] [CrossRef]
  21. Checa, M.F.; Rodriguez, J.; Willmott, K.R.; Liger, B. Microclimate Variability Significantly Affects the Composition, Abundance and Phenology of Butterfly Communities in a Highly Threatened Neotropical Dry Forest. Fla. Entomol. 2014, 97, 1–13. [Google Scholar] [CrossRef]
  22. Bonebrake, T.C.; Ponisio, L.C.; Boggs, C.L.; Ehrlich, P.R. More than Just Indicators: A Review of Tropical Butterfly Ecology and Conservation. Biol. Conserv. 2010, 143, 1831–1841. [Google Scholar] [CrossRef]
  23. Molleman, F.; Kop, A.; Brakefield, P.M.; DeVries, P.J.; Zwaan, B.J. Vertical and Temporal Patterns of Biodiversity of Fruit-Feeding Butterflies in a Tropical Forest in Uganda. Biodivers. Conserv. 2006, 15, 107–121. [Google Scholar] [CrossRef]
  24. Graça, M.B.; Pequeno, P.A.C.L.; Franklin, E.; Morais, J.W. Coevolution between Flight Morphology, Vertical Stratification and Sexual Dimorphism: What Can We Learn from Tropical Butterflies? J. Evol. Biol. 2017, 30, 1862–1871. [Google Scholar] [CrossRef] [PubMed]
  25. DeVries, P.J.; Alexander, L.G.; Chacon, I.A.; Fordyce, J.A. Similarity and Difference among Rainforest Fruit-Feeding Butterfly Communities in Central and South America. J. Anim. Ecol. 2012, 81, 472–482. [Google Scholar] [CrossRef]
  26. Mena, S.; Kozak, K.M.; Cárdenas, R.E.; Checa, M.F. Forest Stratification Shapes Allometry and Flight Morphology of Tropical Butterflies. Proc. R. Soc. B Biol. Sci. 2020, 287, 20201071. [Google Scholar] [CrossRef]
  27. DeVries, P.J.; Penz, C.M.; Hill, R.I. Vertical Distribution, Flight Behaviour and Evolution of Wing Morphology in Morpho Butterflies. J. Anim. Ecol. 2010, 79, 1077–1085. [Google Scholar] [CrossRef] [PubMed]
  28. Fordyce, J.A.; DeVries, P.J. A Tale of Two Communities: Neotropical Butterfly Assemblages Show Higher Beta Diversity in the Canopy Compared to the Understory. Oecologia 2016, 181, 235–243. [Google Scholar] [CrossRef] [PubMed]
  29. Lourenço, G.M.; Soares, G.R.; Santos, T.P.; Dáttilo, W.; Freitas, A.V.L.; Ribeiro, S.P. Equal but Different: Natural Ecotones Are Dissimilar to Anthropic Edges. PLoS ONE 2019, 14, e0213008. [Google Scholar] [CrossRef] [PubMed]
  30. Ribeiro, D.B.; Freitas, A.V.L. The Effect of Reduced-Impact Logging on Fruit-Feeding Butterflies in Central Amazon, Brazil. J. Insect. Conserv. 2012, 16, 733–744. [Google Scholar] [CrossRef]
  31. Hill, J.; Hamer, K.; Tangah, J.; Dawood, M. Ecology of Tropical Butterflies in Rainforest Gaps. Oecologia 2001, 128, 294–302. [Google Scholar] [CrossRef] [PubMed]
  32. Fermon, H.; Waltert, M.; Vane-Wright, R.I.; Mühlenberg, M. Forest Use and Vertical Stratification in Fruit-Feeding Butterflies of Sulawesi, Indonesia: Impacts for Conservation. Biodivers. Conserv. 2005, 14, 333–350. [Google Scholar] [CrossRef]
  33. Roche, K.N.; Piorkowski, J.M.; Sanyaolu, R.A.; Cordeiro, N.J. Vertical Distribution of Fruit-Feeding Butterflies with Evidence of Sex-Specific Differences in a Tanzanian Forest. Afr. J. Ecol. 2015, 53, 480–486. [Google Scholar] [CrossRef]
  34. Shaw, D.C. Vertical Organization of Canopy Biota. In Forest Canopies; Lowman, M.D., Rinker, H.B., Eds.; Elsevier Academic Press Burlington: Burlington, MA, USA, 2004; pp. 73–101. [Google Scholar]
  35. Xing, S.; Bonebrake, T.C.; Tang, C.C.; Pickett, E.J.; Cheng, W.; Greenspan, S.E.; Williams, S.E.; Scheffers, B.R. Cool Habitats Support Darker and Bigger Butterflies in Australian Tropical Forests. Ecol. Evol. 2016, 6, 8062–8074. [Google Scholar] [CrossRef] [PubMed]
  36. García-Robledo, C.; Kuprewicz, E.K.; Staines, C.L.; Erwin, T.L.; Kress, W.J. Limited tolerance by insects to high temperatures across tropical elevational gradients and the implications of global warming for extinction. Proc. Natl. Acad. Sci. USA 2016, 113, 680–685. [Google Scholar] [CrossRef] [PubMed]
  37. Kingsolver, J.G.; Watt, W.B. Thermoregulatory Strategies in Colias Butterflies: Thermal Stress and the Limits to Adaptation in Temporally Varying Environments. Am. Nat. 1983, 121, 32–55. [Google Scholar] [CrossRef]
  38. ICMBio. Plano De Manejo Da Floresta Nacional De São Francisco De Paula; Technical Report; ICMBio: Brasília, Brazil, 2020; p. 54.
  39. Rambo, B. A Fisionomia Do Rio Grande Do Sul, 2nd ed.; Selbach: Porto Alegre, Brazil, 1956; ISBN 8585580119. [Google Scholar]
  40. Backes, A. Distribuição Geográfica Atual Da Floresta Com Araucária: Condicionamento Climático. In Floresta com Araucária: Ecologia, Conservação e Desenvolvimento Sustentável; Fonseca, C.R., Souza, A.F., Leal-Zanchet, A.M., Tânia, L., Dutra, A.B.G.G., Eds.; Holos: Ribeirão Preto, Brazil, 2009; p. 328. [Google Scholar]
  41. Freitas, A.V.L.; Iserhard, C.A.; dos Santos, J.P.; Carreira, J.Y.O.; Ribeiro, D.B.; Melo, D.H.A.; Rosa, A.H.; Marini-Filho, O.J.; Mattos Accacio, G.; Uehara-Prado, M. Studies with Butterfly Bait Traps: An Overview. Rev. Colomb. Entomol. 2014, 40, 203–212. [Google Scholar]
  42. Jost, L. Entropy and Diversity. Oikos 2006, 113, 363–375. [Google Scholar] [CrossRef]
  43. Chao, A.; Gotelli, N.J.; Hsieh, T.C.; Sande, E.L.; Ma, K.H.; Colwell, R.K.; Ellison, A.M. Rarefaction and Extrapolation with Hill Numbers: A Framework for Sampling and Estimation in Species Diversity Studies. Ecol. Monogr. 2014, 84, 45–67. [Google Scholar] [CrossRef]
  44. DeVries, P.J. The Butterflies of Costa Rica and Their Natural History: Papilionidae, Pieridae, Nymphalidae; The Butterflies of Costa Rica and Their Natural History; Princeton University Press: Princeton, NJ, USA, 1987; ISBN 9780691024035. [Google Scholar]
  45. Legendre, P.; Legendre, L. Numerical Ecology. In Developments in Environmental Modelling; Elsevier: Amsterdam, The Netherlands, 2012; Volume 24, p. 1006. [Google Scholar]
  46. Anderson, M.J.; Ellingsen, K.E.; McArdle, B.H. Multivariate Dispersion as a Measure of Beta Diversity. Ecol. Lett. 2006, 9, 683–693. [Google Scholar] [CrossRef] [PubMed]
  47. Dufrêne, M.; Legendre, P. Species Assemblages and Indicator Species: The Need for a Flexible Asymmetrical Approach. Ecol. Monogr. 1997, 67, 345–366. [Google Scholar] [CrossRef]
  48. De Cáceres, M. How to Use the Indicspecies Package (Ver. 1.7.1). Available online: https://cran.r-project.org/web/packages/indicspecies/vignettes/IndicatorSpeciesAnalysis.html (accessed on 3 April 2023).
  49. R Core Team. R: A Language and Environment for Statistical Computing 2021. Available online: https://www.R-project.org (accessed on 3 April 2023).
  50. Chao, A.; Jost, L. Estimating Diversity and Entropy Profiles via Discovery Rates of New Species. Methods Ecol. Evol. 2015, 6, 873–882. [Google Scholar] [CrossRef]
  51. Hsieh, T.C.; Ma, K.H.; Chao, A. INEXT: Interpolation and Extrapolation for Species Diversity. Methods in Ecology and Evolution 2020, 7, 1451–1456. [Google Scholar] [CrossRef]
  52. Bates, D.; Mächler, M.; Bolker, B.M.; Walker, S.C. Fitting Linear Mixed-Effects Models Using Lme4. J. Stat. Softw. 2015, 67, 48. [Google Scholar] [CrossRef]
  53. Fox, J.; Weisberg, S. An {R} Companion to Applied Regression, 3rd ed.; Sage: Thousand Oaks, CA, USA, 2019. [Google Scholar]
  54. De Caceres, M.; Legendre, P. Associations between Species and Groups of Sites: Indices and Statistical Inference. Ecology 2009, 90, 3566–3574. [Google Scholar] [CrossRef]
  55. Oksanen, J.; Blanchet, F.G.; Friendly, M.; Kindt, R.; Legendre, P.; McGlinn, D.; Minchin, P.R.; O’Hara, R.B.; Simpson, G.L.; Solymos, P.; et al. Vegan: Community Ecology Package. 2020. Available online: https://cran.r-project.org/web/packages/vegan/vegan.pdf (accessed on 3 April 2023).
  56. Cardoso, P.; Rigal, F.; Carvalho, J.C. BAT—Biodiversity Assessment Tools, an R Package for the Measurement and Estimation of Alpha and Beta Taxon, Phylogenetic and Functional Diversity. Methods Ecol. Evol. 2015, 6, 232–236. [Google Scholar] [CrossRef]
  57. Wickham, H. Ggplot2: Elegant Graphics for Data Analysis; Springer: New York, NY, USA, 2016; ISBN 978-3-319-24277-4. [Google Scholar]
  58. Madigosky, S.R. CHAPTER 2—Tropical Microclimatic Considerations. In Physiological Ecology; Lowman, M.D., Rinker, H.B.B.T.-F.C., Second, E., Eds.; Academic Press: San Diego, CA, USA, 2004; pp. 24–48. ISBN 978-0-12-457553-0. [Google Scholar]
  59. Wolda, H. Insect Seasonality: Why? Ann. Rev. Ecol. Sysi. 1988, 19, 1–18. [Google Scholar] [CrossRef]
  60. Menéndez, R.; González-Megías, A.; Collingham, Y.; Fox, R.; Roy, D.B.; Ohlemüller, R.; Thomas, C.D. Direct And Indirect Effects Of Climate And Habitat Factors On Butterfly Diversity. Ecology 2007, 88, 605–611. [Google Scholar] [CrossRef]
  61. Kingsolver, J.G.; Huey, R.B. Size, Temperature, and Fitness: Three Rules. Evol. Ecol. Res. 2008, 10, 251–268. [Google Scholar]
  62. Ribeiro, D.B.; Freitas, A.V.L. Large-Sized Insects Show Stronger Seasonality than Small-Sized Ones: A Case Study of Fruit-Feeding Butterflies. Biol. J. Linn. Soc. 2011, 104, 820–827. [Google Scholar] [CrossRef]
  63. Queiroz, J.M. Host Plant Use among Closely Related Anaea Butterfly Species (Lepidoptera, Nymphalidae, Charaxinae). Braz. J. Biol. 2002, 62, 657–663. [Google Scholar] [CrossRef] [PubMed]
  64. Perez Rocha, M.; Bini, L.M.; Domisch, S.; Tolonen, K.T.; Jyrkänkallio-Mikkola, J.; Soininen, J.; Hjort, J.; Heino, J. Local Environment and Space Drive Multiple Facets of Stream Macroinvertebrate Beta Diversity. J. Biogeogr. 2018, 45, 2744–2754. [Google Scholar] [CrossRef]
  65. McGill, B.J.; Enquist, B.J.; Weiher, E.; Westoby, M. Rebuilding Community Ecology from Functional Traits. Trends Ecol. Evol. 2006, 21, 178–185. [Google Scholar] [CrossRef]
  66. Cadotte, M.W.; Cavender-Bares, J.; Tilman, D.; Oakley, T.H. Using Phylogenetic, Functional and Trait Diversity to Understand Patterns of Plant Community Productivity. PLoS ONE 2009, 4, 1–9. [Google Scholar] [CrossRef] [PubMed]
  67. Peña, C.; Wahlberg, N. Prehistorical Climate Change Increased Diversification of a Group of Butterflies. Biol. Lett. 2008, 4, 274–278. [Google Scholar] [CrossRef] [PubMed]
  68. van Asch, M.; Visser, M.E. Phenology of Forest Caterpillars and Their Host Trees: The Importance of Synchrony. Annu. Rev. Entomol. 2007, 52, 37–55. [Google Scholar] [CrossRef]
  69. van Dyck, H.; Matthysen, E. Thermoregulatory Differences between Phenotypes in the Speckled Wood Butterfly: Hot Perchers and Cold Patrollers? Oecologia 1998, 114, 326–334. [Google Scholar] [CrossRef] [PubMed]
  70. Birnbaum, P. Canopy Surface Topography in a French Guiana Forest and the Folded Forest Theory. Plant Ecol. 2001, 153, 293–300. [Google Scholar] [CrossRef]
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Figure 1. Map showing the location of the study area in the Rio Grande do Sul State, southern Brazil.
Figure 1. Map showing the location of the study area in the Rio Grande do Sul State, southern Brazil.
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Figure 2. Empirical and proposed diversity profiles based on the q statistic for fruit-feeding butterfly assemblages for the canopy (red line) and understory (green line) sampled in mixed ombrophilous forest in southern Brazil during November 2016–March 2017 and October 2017–March 2018. Confidence intervals (95%) were constructed on the basis of bootstrap resampling (1000 iterations).
Figure 2. Empirical and proposed diversity profiles based on the q statistic for fruit-feeding butterfly assemblages for the canopy (red line) and understory (green line) sampled in mixed ombrophilous forest in southern Brazil during November 2016–March 2017 and October 2017–March 2018. Confidence intervals (95%) were constructed on the basis of bootstrap resampling (1000 iterations).
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Figure 3. Effects of environmental variables that explained the abundance patterns of fruit-feeding butterfly assemblages sampled in mixed ombrophilous forest in southern Brazil during November 2016–March 2017 and October 2017–March 2018. Red colors indicate sites and regression lines related to the canopy, while green colors indicate sites and regression lines related to the understory. (a) Effects of mean temperature at day, highlighting the lack of interaction with the stratum. (b) Effects of the standard deviation of temperature at night and their dependency on the stratum. (c) Effects of the mean humidity at day on abundance, showing the positive relationship with the canopy. The y-axis was square-root-transformed for better visualization of the patterns. The predictor variables were scaled before performing the analysis to have a mean equal to 0 and a standard deviation equal to 1.
Figure 3. Effects of environmental variables that explained the abundance patterns of fruit-feeding butterfly assemblages sampled in mixed ombrophilous forest in southern Brazil during November 2016–March 2017 and October 2017–March 2018. Red colors indicate sites and regression lines related to the canopy, while green colors indicate sites and regression lines related to the understory. (a) Effects of mean temperature at day, highlighting the lack of interaction with the stratum. (b) Effects of the standard deviation of temperature at night and their dependency on the stratum. (c) Effects of the mean humidity at day on abundance, showing the positive relationship with the canopy. The y-axis was square-root-transformed for better visualization of the patterns. The predictor variables were scaled before performing the analysis to have a mean equal to 0 and a standard deviation equal to 1.
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Figure 4. Beta diversity components and their relationship with environmental variables and the stratum of fruit-feeding butterfly assemblages sampled in mixed ombrophilous forest in southern Brazil during November 2016–March 2017 and October 2017–March 2018. (a–c) The dispersion of points related to strata for the component of total dissimilarity (βtot), the component of abundance replacement (βrep), and the component of abundance differences (βric), respectively. (d) Boxplot showing the effects of strata in βtot, indicating a larger dissimilarity among understory sites (UU, green color) than among canopy sites (CC, red color).
Figure 4. Beta diversity components and their relationship with environmental variables and the stratum of fruit-feeding butterfly assemblages sampled in mixed ombrophilous forest in southern Brazil during November 2016–March 2017 and October 2017–March 2018. (a–c) The dispersion of points related to strata for the component of total dissimilarity (βtot), the component of abundance replacement (βrep), and the component of abundance differences (βric), respectively. (d) Boxplot showing the effects of strata in βtot, indicating a larger dissimilarity among understory sites (UU, green color) than among canopy sites (CC, red color).
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Table
Table 1. Model selection table for models for richness and abundance of fruit-feeding butterfly assemblages sampled in mixed ombrophilous forest in southern Brazil during November 2016–March 2017 and October 2017–March 2018. In the null model, the response variables were modeled by 1, whereas, in the full model, they were modeled considering the environmental variables. We considered the best model to have the lowest AICc and a delta < 2. 1 Pseudo-R2 calculated using the trigamma method and considering both fixed and random effects (conditional).
Table 1. Model selection table for models for richness and abundance of fruit-feeding butterfly assemblages sampled in mixed ombrophilous forest in southern Brazil during November 2016–March 2017 and October 2017–March 2018. In the null model, the response variables were modeled by 1, whereas, in the full model, they were modeled considering the environmental variables. We considered the best model to have the lowest AICc and a delta < 2. 1 Pseudo-R2 calculated using the trigamma method and considering both fixed and random effects (conditional).
dflogLikAICcDeltaWeightPseudo-R2
Model for richness
 Null (Poisson)2−163.125330.4000.0000.985
 Full model (Poisson)8−160.424338.8008.3700.0150.417 1
Model for abundance
 Full model (negative binomial)9−258.573537.6000.0000.9080.472 1
 Null (negative binomial)3−267.928542.2004.5800.092
Table
Table 2. Effect of environmental variables in the abundance of fruit-feeding butterfly assemblages of sampled in mixed ombrophilous forest in southern Brazil during November 2016–March 2017 and October 2017–March 2018, according to the model selection. The values of parameters estimated are in the log-link scale. SE—standard error. Bold values indicate the terms that were significant at an alpha threshold of 0.05.
Table 2. Effect of environmental variables in the abundance of fruit-feeding butterfly assemblages of sampled in mixed ombrophilous forest in southern Brazil during November 2016–March 2017 and October 2017–March 2018, according to the model selection. The values of parameters estimated are in the log-link scale. SE—standard error. Bold values indicate the terms that were significant at an alpha threshold of 0.05.
EstimateSEz-ValuePr(>|z|)
Intercept2.1200.3336.3720.000
Mean temperature (day)0.9130.4292.1270.033
Temperature variation (night)1.2210.4572.6740.007
Mean temperature (day): understory−0.1830.388−0.4710.638
Temperature variation (night): understory−0.9790.416−2.3520.019
Canopy: mean humidity (day)1.4000.4643.0160.003
Understory: mean humidity (day)0.5640.4201.3430.179
Table
Table 3. Effects of environmental variables on partitioning beta diversity dissimilarity in fruit-feeding butterfly assemblages sampled in mixed ombrophilous forest in southern Brazil during November 2016–March 2017 and October 2017–March 2018. βtot—component related to total dissimilarity among pairwise sites; βrep—component related to abundance replacement among sites; βric—component of abundance difference due to the gain/loss of individuals among sites.; df—degrees of freedom; SumOfSqs—sum of squares. Bold values indicate the significant terms at a p threshold of 0.05.
Table 3. Effects of environmental variables on partitioning beta diversity dissimilarity in fruit-feeding butterfly assemblages sampled in mixed ombrophilous forest in southern Brazil during November 2016–March 2017 and October 2017–March 2018. βtot—component related to total dissimilarity among pairwise sites; βrep—component related to abundance replacement among sites; βric—component of abundance difference due to the gain/loss of individuals among sites.; df—degrees of freedom; SumOfSqs—sum of squares. Bold values indicate the significant terms at a p threshold of 0.05.
DfSumOfSqsR2Fp
βtot
 Mean temperature (day)10.5620.0181.6250.081
 Temperature variation (night)10.3780.0121.0940.970
 Mean humidity (day)10.5610.0181.6230.161
 Strata11.1650.0373.3670.001
 Residual7325.2460.811
 Total7731.1441.000
βrep
 Mean temperature (day)1−0.493−0.050−4.2650.983
 Temperature variation (night)1−0.072−0.007−0.6190.999
 Mean humidity (day)10.0740.0080.6390.779
 Strata10.3390.0352.9370.060
 Residual738.4350.864
 Total779.7661.000
βric
 Mean temperature (day)11.0350.0938.3570.143
 Temperature variation (night)10.1430.0131.1560.214
 Mean humidity (day)10.1560.0141.2620.228
 Strata10.5580.0504.5090.485
 Residual739.0400.810
 Total7711.1551.000
Table
Table 4. Indicator species analysis (IndVal), showing the values of fidelity (A) and specificity (B) for fruit-feeding butterflies between the canopy and understory sampled in a mixed ombrophilous forest in southern Brazil, during November 2016–March 2017 and October 2017–March 2018. Names in the parentheses indicate the subfamily and tribe, respectively. Sat—Satyrinae, Cha—Charaxinae, Bib—Biblidinae, Nym—Nymphalinae. Only species with p values < 0.05 are shown.
Table 4. Indicator species analysis (IndVal), showing the values of fidelity (A) and specificity (B) for fruit-feeding butterflies between the canopy and understory sampled in a mixed ombrophilous forest in southern Brazil, during November 2016–March 2017 and October 2017–March 2018. Names in the parentheses indicate the subfamily and tribe, respectively. Sat—Satyrinae, Cha—Charaxinae, Bib—Biblidinae, Nym—Nymphalinae. Only species with p values < 0.05 are shown.
ABStatp
Canopy
 Carminda paeon (Sat, Satyrini)0.9060.6320.7560.001
 Zaretis strigosus (Cha, Anaeini)1.0000.3680.6070.001
 Epiphile orea (Bib, Epiphilini)0.9440.2900.5230.001
 Memphis moruus (Cha, Anaeini)1.0000.2630.5130.001
 Smyrna blomfildia (Nym, Coeini)1.0000.1050.3240.050
Understory
 Pseudodebis ypthima (Sat, Satyrini)1.0000.5750.7580.001
 Eryphanis reevesii (Sat, Brassolini)0.9850.5000.7020.001
 Forsterinaria quantius (Sat, Satyrini)0.9880.3250.5670.001
 Morpho epistrophus (Sat, Morphini)0.9790.2500.4950.003
 Opoptera fruhstorferi (Sat, Brassolini)1.0000.2250.4740.007
 Caligo martia (Sat, Brassolini)1.0000.1500.3870.023
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Richter, A.; de Souza Mendonça, M., Jr.; Gawlinski, K.; Iserhard, C.A. Microclimatic Fluctuation throughout the Day Influences Subtropical Fruit-Feeding Butterfly Assemblages between the Canopy and Understory. Diversity 2023, 15, 560. https://doi.org/10.3390/d15040560

AMA Style

Richter A, de Souza Mendonça M Jr., Gawlinski K, Iserhard CA. Microclimatic Fluctuation throughout the Day Influences Subtropical Fruit-Feeding Butterfly Assemblages between the Canopy and Understory. Diversity. 2023; 15(4):560. https://doi.org/10.3390/d15040560

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Richter, Aline, Milton de Souza Mendonça, Jr., Karine Gawlinski, and Cristiano Agra Iserhard. 2023. "Microclimatic Fluctuation throughout the Day Influences Subtropical Fruit-Feeding Butterfly Assemblages between the Canopy and Understory" Diversity 15, no. 4: 560. https://doi.org/10.3390/d15040560

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