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Miniseminar: Successful Practice in the Era of Value-Based Purchasing
RESEARCH ARTICLE
Can pollination syndromes indicate ecological restoration success in tropical forests? Rafael Martins1 , Yasmine Antonini1,2 We evaluated the pollination syndromes of plant species occurring in revegetated patches of riparian Atlantic Forest in order to evaluate the success of restoration process. Between March 2013 and January 2014, the floral traits of all of the flowering plants found in, among four restoration sites of different ages and one reference site, were recorded and used to characterize pollination syndromes. Richness, abundance, and composition of pollination syndromes were related to season, age and width of the forest fragment, species richness and abundance of sampled plants, and also to the quality of the surrounding matrix. There were differences in the composition of syndromes among sampling units and among seasons. Richness and abundance of pollination syndromes varied among climatic periods, the highest values occurred at the end of the dry season and the start of the rainy season. Older, wider, and areas with more plants had higher values of richness and abundance of syndromes. The quality of the surrounding matrix influences only the richness of syndromes. It was concluded that floral traits are good indicators of ecological restoration of riparian forests and that the surrounding matrix contributes to the greater richness of syndromes. However, when planning for active restoration, attention should be given to the proper choice of plant species on the basis of pollination syndromes that should attract pollinators. Key words: floral syndromes, habitat complexity, landscape, pollinators, riparian forest
Implications for Practice • When planning for active restoration, attention should be given to the proper choice of plant species on the basis of pollination syndromes that should attract pollinators. • The presence of one or more forest fragments in the nearby matrix can increase pollination syndromes and enhance pollinator visits. • As composition and abundance of pollination syndromes are different among seasons, to warrant the use of pollination data for success assessment, the measurement of samples should occur within the same season or across seasons.
Introduction The ultimate goal of restoration is to create a self-supporting ecosystem that is resilient to perturbation without further assistance (Ruiz-Jaen & Aide 2005). But how do we know that we have reached that goal? According to Ruiz-Jaen and Aide (2005) the evaluation of diversity, vegetation structure, and ecological processes can reflect the recovery trajectory and self-maintenance of restored ecosystems. Therefore, in planning and evaluating restoration projects, a purely structural focus is inadequate. An alternative is to consider ecosystem functions, that is, what constituent species do rather than simply recording whether or not they are present (Ehrenfeld & Toth 1997; Petchey & Gaston 2006). Indeed, a direct functional comparison between restoration sites and target habitat is possible when considering ecological
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processes that should not vary between localities, such as pollination. Pollination is a ubiquitous interaction between plants and animals. Patterns in plant–pollinator interactions can be analyzed in many ways, including a complex system approaches and comparing pollination webs, or using the concept of pollination syndromes (or floral syndromes), which is based on the pollination system concept (Faegri & Van der Pijl 1979). Different species of plants share floral characteristics that place them in the same pollination syndrome. Plant reproductive processes are determinants of the composition and structure of communities (Bawa 1990; Oliveira & Gibbs 2000) and are susceptible to alterations and/or disturbance of the environment (Garcia et al. 2014). A diverse plant community is likely to include species that differ in resource partitioning and the proportion of niche space occupied (Loreau 1998). The way that ecosystem functions are influenced by species diversity is not exactly understood, but increased plant diversity often enhances ecosystem functioning (Nadrowski et al. 2010; Britain et al. 2013). Consequently, the diversity of plant Author contributions: RM, YA conceived and designed the research, performed the experiments, analyzed the data, wrote and edited the manuscript. 1 Laboratory of Biodiversity, Department of Biodiversity and Evolution, Federal University of Ouro Preto, Campus Morro do Cruzeiro, s/n, Ouro Preto, Minas Gerais CEP-35400-000, Brazil 2 Address correspondence to Y. Antonini, email [email protected]
© 2016 Society for Ecological Restoration doi: 10.1111/rec.12324 Supporting information at: http://onlinelibrary.wiley.com/doi/10.1111/rec.12324/suppinfo
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Table 1. Geographic location and characterization of sampling units by age, width, forest cover, and the surrounding matrix. Data of land use and cover were gathered evaluating a circular buffer of 3 km from the center of each sampling unit. *Reference site. Sampling Unit
Name
1 2 3 4 5
Nativa* Noboro Santa Bárbara Figueira Delta
Location (UTM)
Age (Years)
Width (m)
Matrix Forest Cover (%)
791531-7783262 798082-7775015 800294-7768027 205429-7786874 208838-7787209
30 20 10 20 10
400 30 30 100 100
27.3 18.3 88.00 74.5 80.0
phenological strategies is often positively influenced by species diversity (Vamosi et al. 2006). Although recovery of tree and shrub species in ecosystems being restored is often rapid, the colonization of growth forms such as epiphytes and climbers may be much slower (Garcia et al. 2014). Because different growth forms have dissimilar phenological patterns (Marques et al. 2004), monitoring seasonal phenology can help in the identification of resource bottlenecks and keystone species in locations undergoing restoration (Wallace & Painter 2002). In terms of self-sustainability of the forest, we expect that wider fragments would support a more lush vegetation with more plants (Davide & Reis 2007). A study of plant community structure by Davide and Reis (2007) showed that the number of species recruited and the total number of individuals regenerating was higher in the narrower units than in the wider ones. They attributed this result to the quality of the matrix surrounding each area, which has a strong influence on the recruitment of species. The aim of this study was to document differences in pollination syndromes among restoration sites with different characteristics such as age, forest fragment width, and amount of forest in the surrounding land cover, and a reference riparian secondary forest site, aiming to test whether richness, abundance, and composition of pollination syndromes are good indicators of forest recovery. Our specific predictions are: (1) composition of pollination syndromes vary between seasons and among restoration and reference sites; (2) the richness and abundance of pollination syndromes are progressively greater in wider and older riparian forest fragments; (3) Riparian forests with greater plant species richness and abundance have greater richness and abundance of pollination syndromes; and (4) richness and abundance of pollination syndromes will be different in fragments with different surrounding forest cover.
Methods Site, Restoration Overview, and Study Design
The study was conducted in five patches of riparian forest (hereafter referred to as sampling units) in the region of the reservoir of the Volta Grande hydroelectric power plant (HPP) located on the Rio Grande river that forms the border between Minas Gerais and São Paulo States, Brazil (20∘ 01′ 54′′ S/48∘ 13′ 17′ W) (Table 1; Fig. S1, Supporting Information). According to Alvares et al. (2014), the region presents a Tropical AW
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Matrix Type
Cerrado Rubber Trees Sugarcane Sugarcane Sugarcane + households
Köppen climate (with a dry winter), whose annual average temperature ranges from 22 to 24∘ C with a well-defined dry season between May and October and a rainy season from November to April, with the average annual precipitation reaching 1,506 mm (Fig. 1). A complex mosaic of forest patches replaced most of the original riparian vegetation of the Volta Grande Reservoir, MG, Brazil, in different successional stages. Four of the sampling units were reforestations of different ages and widths, and a fifth sampling unit (Nativa) was a 30-year secondary forest considered as a reference site. The sampling units were classified by different land use (Table S1; Fig. S1). The sampling units were located in a very anthropogenic matrix formed mainly by grasslands and sugarcane plantations. After 30 years of recovery, the landscape naturally became a mosaic of environments that strongly influenced the restoration of the riparian forest fragments (Fig. S1), which are of different ages (time since the restoration began), different riparian strip widths, and also the proportion of different cover types in the surrounding matrix (Table 1). Data on land use and cover were recorded on a circular buffer of 3 km from the center of each sampling unit. Most of the original riparian vegetation of the study area were removed and/or flooded during the construction of the reservoir (Fig. 2). Thus, the geomorphology, hydrology, and vegetation had been altered. During the period between 1994 and 2004, about 35 tree species were planted in a single replanting event. Reforestation was carried out by planting nursery-grown seedlings of about 35 species, from seeds obtained in a nearby forest remnants. Seedlings were planted along the margins of the reservoir with a spacing of 3 × 2 m. At transplantation time, the seedlings were around 10-months-old. In each of the five sampling units, 12 plots of 100 m2 were used. Samples were drawn from 10 plots, which were randomly chosen from among the 12 plots in each sampling unit for a total of 50 plots. Sampling was performed between March 2013 and January 2014. Sampling events were separated into: the start of the dry season (DS: May–July), end of the dry season (DE: August–October), start of the rainy season (RS: November–January), and end of the rainy season (RE: February–April). The subdivisions of the rainy and dry seasons into start and end periods provided a more reliable scale for temporal analysis. In the plots, all trees with diameter at breast height or 1.30 m (dbh) ≥ 10 cm were sampled for vegetation analysis. Vouchers of the plants studied can be found in the herbarium OUPR,
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Figure 1. Average monthly rainfall between 2002 and 2012 for the study area. Source: HHP Porto Colômbia (Furnas Centrais Elétricas S/A). Dry season is from April to September and wet season from October to March. Bars are mean ± SE.
Figure 2. Volta Grande Reservoir, Brazil. A view of the evolution of the restoration process, reference site “Nativa.” Landscape before the restoration process (left) and 30 years after the process (right).
Ouro Preto, MG, Brazil. Among the plants with dbh < 10 cm, only flowering plants were recorded for identification of the pollination syndrome. For the classification of syndromes, all species of flowering plants that were not included in floristic studies were also recorded. These species (which were not included in the floristic studies—dbh < 10 cm) whose taxonomic identification were not determined were separated into morphotypes; however, these plants did not account for the total richness and abundance of plants. All flowering plants found in the plots were classified
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by their syndromes, following the study of Faegri and Van der Pijl (1979) including lianas, shrubs, and herbaceous plants. Analyses
As there were no reforested areas with similar restoration ages in the same landscape to act as ideal replicates, we considered sampling plots within each sampling unit as replicate of restoration age and size in our experimental design. Although we were aware of the issues associated with pseudoreplication,
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GLMs were also constructed to test which explanatory variables (age, width, percentage of surrounding forest cover, richness, and abundance of trees present in each sampling unit) influence the richness and abundance of pollination syndromes (response variables) in each sampling unit. In constructing the GLMs, the interactions between age and width of each fragment of riparian forest were studied (sampling unit) and between the variables, richness, and abundance of plants present in each fragment were also tested as explanatory variables. Contrast analyses were performed after the construction of the models. All statistical analyses were performed using R software (R Development Core Team 2013). The relative abundance of each pollination syndrome was calculated by dividing the abundance of the syndromes by the total number of flowering individuals × 100.
this sampling design has been successfully used in studies on restoration ecology done on a site-specific basis, where no replication across the landscape was feasible (Hurlburt 1984; Gilliam 2002; Sant’Anna et al. 2014). According to Sant’Anna et al. (2014), replication is impractical in many restoration treatments, given that replicate sites might simply not be present in a given area. Despite the known limitations of this design, the results obtained can be used as a good approach to better understand the recovery of pollination syndromes in restored areas, allowing crucial insights into long-term trends. Permutational analysis of variance (PERMANOVA) was used to test the hypothesis that the composition of pollination syndromes varies between seasons (dry and wet) and among sampling units. To test the composition of syndromes among seasons, the data were grouped into four categories (start and end of the dry season and the start and end of the wet season). To test the composition of syndromes among sampling units, the data were grouped into five categories according to the sampling units presented in Table 1. The measure of dissimilarity used was that of Bray–Curtis with 1,000 permutations, and to measure the dispersion of the data, multivariate analyses of permutation distance (PERMDISP) were performed. The graphical representation of the variation in the composition of pollination syndromes between seasons and among sampling units was shown by analysis of non-metric multidimensional scaling (NMDS). Mixed generalized linear models (MGLMs) were constructed to test the hypothesis that the months comprising the end of the dry season (September and October) have higher richness and abundance of pollination syndromes. The response variables were richness and the abundance of pollination syndromes and the explanatory variable were seasons. Generalized linear models (GLMs) were constructed in order to observe the difference in richness and abundance of pollination syndromes among sampling units. The response variables were richness and the abundance of pollination syndromes and the explanatory variable were sampling units.
Results A total of 260 plants of 66 species, including trees, shrubs, herbs, and vines, were classified into the pollination syndromes. Vegetation structure and composition significantly differed across sampling units, particularly in tree species richness, tree height, dbh, and tree abundance. The reference site (Nativa) together with the oldest reforestation site had, in general, more plant species and higher abundance, besides taller trees. Although flowering plants were found throughout the study period, only those with the pollination syndromes of melittophily, myophily, and phalaenophily appeared throughout the study period (Table 2). Melittophily (the only syndrome encountered in all of the sampling units) and cantharophily were the most frequent syndromes presenting higher relative abundance; 31 and 20%, respectively, of the flowering plants (Table 2). Sapromyophily was the syndrome with the lowest relative abundance (0.77%) (Table 2). Among the flowers, 11 different pollination syndromes were identified (Table S2). The composition of pollination
Table 2. Richness, sites of records (sampling units), temporal distribution, abundance, and relative abundance (%) of the pollination syndromes recorded in the study area between the months of March 2013 and January 2014. DE, late dry season; DS, beginning of the dry season; RA, relative abundance; RE, the end of the rainy season; RS, the onset of the rainy season; x, syndromes record. Seasons Syndromes
Melittophily Cantharophily Myophily Thysanoptera Microhymenoptera Psychophily Phalaenophily Ornithophily Chiropterophily Sphingophily Sapromyophily Total individuals Richness
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Sites of Records
DS
DE
RS
RE
Abundance
RA (%)
1, 2, 3, 4, 5 1, 2, 3 1, 2, 3, 4 2, 4, 5 2, 3, 4, 5 1, 2, 4, 5 1, 2, 3 1, 4 1 1, 2, 3 2, 3
x
x x x
x x x x x x x x
x
x x 85 10
x
80 53 36 27 20 17 11 07 04 03 02 260
30.78 20.38 13.85 10.38 7.69 6.54 4.23 2.69 1.54 1.15 0.77
x x x x x x 60 07
x x x x 84 07
x x x
31 05
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plantations had a greater richness of syndromes than those surrounded by sugar cane fields and sugar cane fields with rural households. We also observed a positive linear correlation between the abundance of plants present in each sampling unit and the abundance (F = 6.3554, p < 0.001) and richness of syndromes (F = 10.715, p = 0.002). The richness of plants in each sampling unit did not influence the richness or abundance of pollination syndromes. Although some interactions between variables were tested, none were significant for richness or for total abundance of pollination syndromes.
(A)
Discussion (B)
Figure 3. Non-metric multidimensional scaling (NMDS) for sorting and graphical visualization of the PERMANOVA and PERMDISP analyses of pollination syndromes among the dry and rainy seasons (A), and among the sampling units (B). Seasons are beginning of the dry season (Ds), late dry season (De), onset of the rainy season (Rs), and at the end of the rainy season (Re). For sampling unit features, see Table 1.
syndromes varied among the four seasons (PERMANOVA, R2 = 0.22033, p = 0.003; PERMDISP, F = 8.8942, p < 0.001) (Fig. 3A) and among the sampling units (PERMANOVA, R2 = 0.37063, p = 0.001; PERMDISP, F = 54.402, p < 0.001) (Fig. 3B). Richness (X 2 = 18.869, p < 0.001) and total abundance (X 2 = 100.97, p < 0.001) of syndromes were greater at the end of the dry season and start of the rainy season (Fig. 4A). We found differences in both richness (F = 4.1339, p = 0.006) and in abundance (F = 9.1421, p < 0.001) of pollination syndromes among the sampling units (Fig. 4B). Age (F = 7.1183, p = 0.01, F = 29.018, p < 0.001) and width (F = 6.5165, p = 0.01, F = 10.184, p = 0.002) of riparian forest fragments influenced the richness and abundance of pollination syndromes (Fig. 4C & 4D). The older and reference areas had the greatest richness and higher abundance of pollination syndromes and did not differ from each other. The reference area, with 400 m, had the greatest total abundance of syndromes (Fig. 4D). However, the area with intermediate forest width (100 m) had a lower richness than areas of 400 and 30 m, which did not differ from each other (Fig. 4D). The type of matrix surrounding the fragments (F = 4.6147, p = 0.03) (Fig. 4E) influenced the richness of pollination syndromes but did not affect the abundance of syndromes. Considering the type of surrounding matrix, sampling units surrounded by Cerrado (Brazilian Savanna) and rubber tree
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Variation in the composition, richness, and abundance of pollination syndromes among seasons was expected because of the pronounced seasonality of the region with distinct dry and rainy seasons, having the greatest rainfall between November and April and least between May and October. Studies show that in tropical regions, there is not a single flowering event or season, but rather, plants which are flowering can be found throughout the year (Oliveira & Gibbs 2000), and although periods of intense flowering have been observed for specific periods of the year, this does not necessarily occur synchronously in different regions of an environment (Oliveira & Gibbs 2000). According to van Schaik et al. (1993), the timing of flowering in tropical forests occurs mainly during the dry season, or during the period of transition between the dry and rainy seasons (end of the dry season and the start of the rainy season). Thus, there is a tendency to encounter a greater number of trees during flowering when the amount of precipitation begins to decrease (van Schaik et al. 1993). According to Janzen (1967), flowering during the dry season is more advantageous because climatic conditions favor the activity of pollinating insects. Borchert (1983) also mentioned lower pollinator activity during the rainy season as a possible determining factor for the period of flowering of species in a dry forest in Costa Rica. The presence of fruits, whose seeds are dispersed by animals during the rainy season, ensures that they remain attractive for a longer period of time, thereby improving the chances of seed dispersal (Oliveira & Gibbs 2000). Thus, the seasonal pattern found in this study can be considered fairly common for tropical forests. The four sampling units presented a gradient of restoration success based on the vegetation structure. Older and larger areas presented a vegetation structure that was very similar to the reference site, and the results for pollination syndromes also followed this pattern. Thus, pollination syndromes can be a good information source for creating indicators of restoration success. The differences found in the richness and abundance of syndromes among the restoration sites and the reference site were expected because they presented differences in the structure of the vegetal community, time under restoration and the influence of surrounding landscape. Different areas may undergo different recovery processes after a major disturbance, such as the removal of vegetation for the construction of reservoirs for hydroelectric plants, which can result in different responses from plant communities. When
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Figure 4. Pollination syndrome richness and abundance by season (A), sampling units (B), age (C), width (D), and by percentage of habitat matrix (E) in riparian forest restoration sites of the Volta Grande reservoir of the Rio Grande River, Minas Gerais, Brazil. Seasons are beginning of the dry season (Ds), late dry season (De), onset of the rainy season (Rs), and at the end of the rainy season (Re). For sampling unit features, see Table 1. Bars are means ± SE.
recovery strategies are implemented in areas in an asynchronous manner, and without preestablished type of restoration practices, great heterogeneity among restoration areas can result. This process can lead to patches in different successional stages that exhibit distinct patterns of richness and abundance of species (Rodrigues et al. 2009), such as was found in this study. As expected, the reference site (30 years of age) in our study showed the highest richness and abundance of pollination syndromes. This sampling unit also had the highest richness and abundance of plants presenting a more complex vegetation structure (MCTB Messias 2014, Federal University of Ouro Preto, personal communication). The sampling unit in a 20-year reforestation also had high values for richness and abundance
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of syndromes and did not differ from the reference site unit, which was also a secondary successional stand. This sampling unit within a fragment of riparian vegetation of intermediate age probably still contains species of the initial succession stage as well as intermediate and advanced stages, thus favoring the richness and abundance of syndromes. From this premise, it can be assumed that younger sampling units, up to 10 years since planting, are still dominated by a large number of pioneer species or species of initial successional stages, which would explain the low values of richness and abundance of pollination syndromes in these younger riparian forest fragments. The width of a sampling unit does not seem to contribute to an increase in syndrome richness, but it is an important factor
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in syndrome abundance. No differences were found between the reference site (400-m wide) and the sampling unit with 30-m width, and even the 100-m wide sampling unit showed lower syndrome richness than both units. The lower richness in wider areas was not expected because the edge effect should be more intense in narrower fragments, leading to an increase in mortality rates, that become greater than in wider fragments or non-fragmented areas, which could lead to a reduction in the abundance of syndromes (Laurance & Vasconcelos 2009). We found no relationship between richness and abundance of pollination syndromes and richness of plants in each sampling unit, this may be because of the lower richness of plant species. According to Faegri and Van der Pijl (1979), plants belonging to the same family can often share the same pollination syndrome, which may also explain the non-significant relationship. However, both richness and abundance of syndromes correlated positively with the total abundance of plants. This result was expected because the larger the number of plants, the greater the possibility of flowering plants and different types of flowers. It was expected that melittophily would be the most frequently recorded pollination syndrome throughout the sampling period and across all sampling units. This syndrome is more common in tropical environments, independent of the sampled ecosystem (Faegri & Van der Pijl 1979). Despite the importance of other syndromes, based on their high relative abundance and wide distribution, cantharophily is another syndrome that is representative of the study area, although in other tropical ecosystems, it is much less important (Gottsberger 1999) despite showing high diversity in tropical forests. Pollinating beetles are very specific to the groups of plants that they pollinate (Gottsberger 1999), which may help explain the high frequency of cantarophily in the study area as there is a high abundance of individuals of Xylopia aromatica, a species of Annonaceae that is only pollinated by beetles (Gottsberger 1999; Carvalho et al. 2012). The forest cover in the surrounding matrix may also explain the greater richness of pollination syndromes found in some of the sampling units, but it does not explain the greater abundance. Greater richness of syndromes was observed in areas surrounded by Cerrado (Brazilian Savanna) or rubber tree plantations. These results corroborate our hypothesis that the higher the incidence of a forest matrix, the greater the richness of pollination syndromes because the forest matrix can provide diaspores (natural forest) and also facilitate dispersal (both natural forest and tree monoculture) that could colonize those areas under recovery. The characteristics of the matrix are an important aspect in the context of the landscape because the matrix type that surround patches of habitat has significant effects over the biodiversity in different types of landscapes, spatial scales, and taxonomic groups. There is evidence that the type of matrix influences individual survival and reproduction as well as the structure and dynamics of communities, especially interspecific relationships (Prevedello & Vieira 2009). This study was the first to test, on a temporal and spatial scale, the influence of a set of abiotic and biotic variables on the richness and abundance of pollination syndromes in an area of
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riparian vegetation in the process of recovering from intensive anthropogenic degradation. The distribution of pollination syndromes in the study area has a seasonal pattern common for tropical forests (Bawa 1990). In addition to climatic conditions, the composition of syndromes is also influenced by factors intrinsic to the system itself, such as competition among plant species and plant–animal interactions and characteristic of each fragment of riparian vegetation studied (Britain et al. 2013). Patterns of richness and abundance of pollination syndromes throughout the year accompany periods of peak flowering in tropical forests, which occurs mainly during the dry season or the transition period between the dry and rainy seasons, when there is less precipitation and greater pollinator activity. Age, width, surrounding matrix, and abundance of plants showed a strong relationship with the richness of pollination syndromes. However, the results indicated that the patterns found are the result of the sum of the influence of some or many of the variables, and so it is not possible to think, in terms of the choice of priority areas for riparian vegetation for recuperation, of the variables dissociated from each other. We emphasized that although pollination syndromes are a good predictor of environmental quality, inferences about the restoration success based only on the richness of pollination syndromes can lead to an underestimation. Therefore, restored riparian forests could be important refuges for forest species and increase landscape permeability by allowing pollinators mobility between forest patches (Sant’Anna et al. 2014). Consequently, these areas potentially increase regional biodiversity and restore some of the most important ecosystem services provided by these organisms. We conclude that floral traits are good indicators of environmental restoration of riparian forests. However, when planning for active restoration, attention should be given to the proper choice of plant species on the basis of pollination syndromes that should attract pollinators. The presence of one or more forest fragments in the nearby matrix can increase pollination syndromes and enhance pollinator visits.
Acknowledgments CEMIG and FAPEMIG provided grants and scholarship to R.M. (CRA-APQ03055/11), staff of Volta Grande Station for the support during field work, UFOP for logistics, CNPq provided a scholarship to Y.A. M. C. Messias for help with plant community data. To J. M. Torezan for helpful suggestions in an earlier version of this manuscript.
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Britain C, Kremen C, Klein AM (2013) Biodiversity buffers pollination from changes in environmental conditions. Global Change Biology 19:540–547 Carvalho AT, Maia ACD, Ojima PY, Santos AA, Schlindwein C (2012) Nocturnal bees are attracted by widespread floral scents. Journal of Chemical Ecology 38:315–318 Davide AC, Reis DN (2007) Avaliação dos plantios de recomposição de matas ciliares às margens do reservatório de Volta Grande—Relatório Técnico Universidade Federal de Lavras, MG, Brasil. 75pp Ehrenfeld JG, Toth LA (1997) Restoration ecology and the ecosystem perspective. Restoration Ecology 5:307–317 Faegri K, Van der Pijl L (1979) The principles of pollination ecology. 3rd revised edition. Pergamon Press, Oxford, United Kingdom Garcia LC, Hobbs RJ, Maes dos Santos FA, Rodrigues RR (2014) Flower and fruit availability along a forest restoration gradient. Biotropica 46: 114–123 Gilliam FS (2002) Effects of harvesting on herbaceous layer diversity of a Central Appalachian Hardwood forest in West Virginia, U.S.A. Forest Ecology and Management 155:33–43 Gottsberger G (1999) Pollination and evolution in neotropical Annonaceae. Plant Species Biology 14:143–152 Hurlburt SH (1984) Pseudoreplication and the design of ecological field experiments. Ecological Monographs 54:187–211 Janzen DH (1967) Synchronization of sexual reproduction of trees within the dry season in Central America. Evolution 21:620–637 Laurance WF, Vasconcelos HL (2009) Consequências ecológicas da fragmentação florestal na Amazônia. Oecologia Brasiliensis 13:434–451 Loreau M (1998) Biodiversity and ecosystem functioning: a mechanistic model. Proceedings of the National Academy of Sciences of the United States of America 95:5632–5636 Marques MCM, Roper JJ, Salvalaggio APB (2004) Phenological patterns among plant life-forms in a subtropical forest in southern Brazil. Plant Ecology 173:203–213 Nadrowski K, With C, Scherer-Lorenzen M (2010) Is forest diversity driving ecosystem function and service? Current Opinion in Environmental Sustainability 2:75–79 Oliveira PE, Gibbs PE (2000) Reproductive biology of woody plants in a cerrado community of Central Brazil. Flora 195:311–329
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Supporting Information The following information may be found in the online version of this article: Figure S1. Volta Grande Reservoir, Brazil—landscape and study sites. Table S1. Pollination syndromes recorded in riparian vegetation in the Volta Grande Reservoir, Minas Gerais, Brazil (according to Faegri & Van der Pijl 1979 with modifications). Table S2. Pollination syndromes recorded in riparian vegetation in the Volta Grande Reservoir, Minas Gerais, Brazil (according to Faegri & Van der Pijl 1979 with modifications).
Received: 12 March, 2015; First decision: 22 April, 2015; Revised: 25 November, 2015; Accepted: 25 November, 2015; First published online: 20 January, 2016
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Can pollination syndromes indicate ecological restoration success in tropical forests? Rafael Martins1 , Yasmine Antonini1,2 We evaluated the pollination syndromes of plant species occurring in revegetated patches of riparian Atlantic Forest in order to evaluate the success of restoration process. Between March 2013 and January 2014, the floral traits of all of the flowering plants found in, among four restoration sites of different ages and one reference site, were recorded and used to characterize pollination syndromes. Richness, abundance, and composition of pollination syndromes were related to season, age and width of the forest fragment, species richness and abundance of sampled plants, and also to the quality of the surrounding matrix. There were differences in the composition of syndromes among sampling units and among seasons. Richness and abundance of pollination syndromes varied among climatic periods, the highest values occurred at the end of the dry season and the start of the rainy season. Older, wider, and areas with more plants had higher values of richness and abundance of syndromes. The quality of the surrounding matrix influences only the richness of syndromes. It was concluded that floral traits are good indicators of ecological restoration of riparian forests and that the surrounding matrix contributes to the greater richness of syndromes. However, when planning for active restoration, attention should be given to the proper choice of plant species on the basis of pollination syndromes that should attract pollinators. Key words: floral syndromes, habitat complexity, landscape, pollinators, riparian forest
Implications for Practice • When planning for active restoration, attention should be given to the proper choice of plant species on the basis of pollination syndromes that should attract pollinators. • The presence of one or more forest fragments in the nearby matrix can increase pollination syndromes and enhance pollinator visits. • As composition and abundance of pollination syndromes are different among seasons, to warrant the use of pollination data for success assessment, the measurement of samples should occur within the same season or across seasons.
Introduction The ultimate goal of restoration is to create a self-supporting ecosystem that is resilient to perturbation without further assistance (Ruiz-Jaen & Aide 2005). But how do we know that we have reached that goal? According to Ruiz-Jaen and Aide (2005) the evaluation of diversity, vegetation structure, and ecological processes can reflect the recovery trajectory and self-maintenance of restored ecosystems. Therefore, in planning and evaluating restoration projects, a purely structural focus is inadequate. An alternative is to consider ecosystem functions, that is, what constituent species do rather than simply recording whether or not they are present (Ehrenfeld & Toth 1997; Petchey & Gaston 2006). Indeed, a direct functional comparison between restoration sites and target habitat is possible when considering ecological
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processes that should not vary between localities, such as pollination. Pollination is a ubiquitous interaction between plants and animals. Patterns in plant–pollinator interactions can be analyzed in many ways, including a complex system approaches and comparing pollination webs, or using the concept of pollination syndromes (or floral syndromes), which is based on the pollination system concept (Faegri & Van der Pijl 1979). Different species of plants share floral characteristics that place them in the same pollination syndrome. Plant reproductive processes are determinants of the composition and structure of communities (Bawa 1990; Oliveira & Gibbs 2000) and are susceptible to alterations and/or disturbance of the environment (Garcia et al. 2014). A diverse plant community is likely to include species that differ in resource partitioning and the proportion of niche space occupied (Loreau 1998). The way that ecosystem functions are influenced by species diversity is not exactly understood, but increased plant diversity often enhances ecosystem functioning (Nadrowski et al. 2010; Britain et al. 2013). Consequently, the diversity of plant Author contributions: RM, YA conceived and designed the research, performed the experiments, analyzed the data, wrote and edited the manuscript. 1 Laboratory of Biodiversity, Department of Biodiversity and Evolution, Federal University of Ouro Preto, Campus Morro do Cruzeiro, s/n, Ouro Preto, Minas Gerais CEP-35400-000, Brazil 2 Address correspondence to Y. Antonini, email [email protected]
© 2016 Society for Ecological Restoration doi: 10.1111/rec.12324 Supporting information at: http://onlinelibrary.wiley.com/doi/10.1111/rec.12324/suppinfo
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Table 1. Geographic location and characterization of sampling units by age, width, forest cover, and the surrounding matrix. Data of land use and cover were gathered evaluating a circular buffer of 3 km from the center of each sampling unit. *Reference site. Sampling Unit
Name
1 2 3 4 5
Nativa* Noboro Santa Bárbara Figueira Delta
Location (UTM)
Age (Years)
Width (m)
Matrix Forest Cover (%)
791531-7783262 798082-7775015 800294-7768027 205429-7786874 208838-7787209
30 20 10 20 10
400 30 30 100 100
27.3 18.3 88.00 74.5 80.0
phenological strategies is often positively influenced by species diversity (Vamosi et al. 2006). Although recovery of tree and shrub species in ecosystems being restored is often rapid, the colonization of growth forms such as epiphytes and climbers may be much slower (Garcia et al. 2014). Because different growth forms have dissimilar phenological patterns (Marques et al. 2004), monitoring seasonal phenology can help in the identification of resource bottlenecks and keystone species in locations undergoing restoration (Wallace & Painter 2002). In terms of self-sustainability of the forest, we expect that wider fragments would support a more lush vegetation with more plants (Davide & Reis 2007). A study of plant community structure by Davide and Reis (2007) showed that the number of species recruited and the total number of individuals regenerating was higher in the narrower units than in the wider ones. They attributed this result to the quality of the matrix surrounding each area, which has a strong influence on the recruitment of species. The aim of this study was to document differences in pollination syndromes among restoration sites with different characteristics such as age, forest fragment width, and amount of forest in the surrounding land cover, and a reference riparian secondary forest site, aiming to test whether richness, abundance, and composition of pollination syndromes are good indicators of forest recovery. Our specific predictions are: (1) composition of pollination syndromes vary between seasons and among restoration and reference sites; (2) the richness and abundance of pollination syndromes are progressively greater in wider and older riparian forest fragments; (3) Riparian forests with greater plant species richness and abundance have greater richness and abundance of pollination syndromes; and (4) richness and abundance of pollination syndromes will be different in fragments with different surrounding forest cover.
Methods Site, Restoration Overview, and Study Design
The study was conducted in five patches of riparian forest (hereafter referred to as sampling units) in the region of the reservoir of the Volta Grande hydroelectric power plant (HPP) located on the Rio Grande river that forms the border between Minas Gerais and São Paulo States, Brazil (20∘ 01′ 54′′ S/48∘ 13′ 17′ W) (Table 1; Fig. S1, Supporting Information). According to Alvares et al. (2014), the region presents a Tropical AW
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Matrix Type
Cerrado Rubber Trees Sugarcane Sugarcane Sugarcane + households
Köppen climate (with a dry winter), whose annual average temperature ranges from 22 to 24∘ C with a well-defined dry season between May and October and a rainy season from November to April, with the average annual precipitation reaching 1,506 mm (Fig. 1). A complex mosaic of forest patches replaced most of the original riparian vegetation of the Volta Grande Reservoir, MG, Brazil, in different successional stages. Four of the sampling units were reforestations of different ages and widths, and a fifth sampling unit (Nativa) was a 30-year secondary forest considered as a reference site. The sampling units were classified by different land use (Table S1; Fig. S1). The sampling units were located in a very anthropogenic matrix formed mainly by grasslands and sugarcane plantations. After 30 years of recovery, the landscape naturally became a mosaic of environments that strongly influenced the restoration of the riparian forest fragments (Fig. S1), which are of different ages (time since the restoration began), different riparian strip widths, and also the proportion of different cover types in the surrounding matrix (Table 1). Data on land use and cover were recorded on a circular buffer of 3 km from the center of each sampling unit. Most of the original riparian vegetation of the study area were removed and/or flooded during the construction of the reservoir (Fig. 2). Thus, the geomorphology, hydrology, and vegetation had been altered. During the period between 1994 and 2004, about 35 tree species were planted in a single replanting event. Reforestation was carried out by planting nursery-grown seedlings of about 35 species, from seeds obtained in a nearby forest remnants. Seedlings were planted along the margins of the reservoir with a spacing of 3 × 2 m. At transplantation time, the seedlings were around 10-months-old. In each of the five sampling units, 12 plots of 100 m2 were used. Samples were drawn from 10 plots, which were randomly chosen from among the 12 plots in each sampling unit for a total of 50 plots. Sampling was performed between March 2013 and January 2014. Sampling events were separated into: the start of the dry season (DS: May–July), end of the dry season (DE: August–October), start of the rainy season (RS: November–January), and end of the rainy season (RE: February–April). The subdivisions of the rainy and dry seasons into start and end periods provided a more reliable scale for temporal analysis. In the plots, all trees with diameter at breast height or 1.30 m (dbh) ≥ 10 cm were sampled for vegetation analysis. Vouchers of the plants studied can be found in the herbarium OUPR,
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Figure 1. Average monthly rainfall between 2002 and 2012 for the study area. Source: HHP Porto Colômbia (Furnas Centrais Elétricas S/A). Dry season is from April to September and wet season from October to March. Bars are mean ± SE.
Figure 2. Volta Grande Reservoir, Brazil. A view of the evolution of the restoration process, reference site “Nativa.” Landscape before the restoration process (left) and 30 years after the process (right).
Ouro Preto, MG, Brazil. Among the plants with dbh < 10 cm, only flowering plants were recorded for identification of the pollination syndrome. For the classification of syndromes, all species of flowering plants that were not included in floristic studies were also recorded. These species (which were not included in the floristic studies—dbh < 10 cm) whose taxonomic identification were not determined were separated into morphotypes; however, these plants did not account for the total richness and abundance of plants. All flowering plants found in the plots were classified
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by their syndromes, following the study of Faegri and Van der Pijl (1979) including lianas, shrubs, and herbaceous plants. Analyses
As there were no reforested areas with similar restoration ages in the same landscape to act as ideal replicates, we considered sampling plots within each sampling unit as replicate of restoration age and size in our experimental design. Although we were aware of the issues associated with pseudoreplication,
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GLMs were also constructed to test which explanatory variables (age, width, percentage of surrounding forest cover, richness, and abundance of trees present in each sampling unit) influence the richness and abundance of pollination syndromes (response variables) in each sampling unit. In constructing the GLMs, the interactions between age and width of each fragment of riparian forest were studied (sampling unit) and between the variables, richness, and abundance of plants present in each fragment were also tested as explanatory variables. Contrast analyses were performed after the construction of the models. All statistical analyses were performed using R software (R Development Core Team 2013). The relative abundance of each pollination syndrome was calculated by dividing the abundance of the syndromes by the total number of flowering individuals × 100.
this sampling design has been successfully used in studies on restoration ecology done on a site-specific basis, where no replication across the landscape was feasible (Hurlburt 1984; Gilliam 2002; Sant’Anna et al. 2014). According to Sant’Anna et al. (2014), replication is impractical in many restoration treatments, given that replicate sites might simply not be present in a given area. Despite the known limitations of this design, the results obtained can be used as a good approach to better understand the recovery of pollination syndromes in restored areas, allowing crucial insights into long-term trends. Permutational analysis of variance (PERMANOVA) was used to test the hypothesis that the composition of pollination syndromes varies between seasons (dry and wet) and among sampling units. To test the composition of syndromes among seasons, the data were grouped into four categories (start and end of the dry season and the start and end of the wet season). To test the composition of syndromes among sampling units, the data were grouped into five categories according to the sampling units presented in Table 1. The measure of dissimilarity used was that of Bray–Curtis with 1,000 permutations, and to measure the dispersion of the data, multivariate analyses of permutation distance (PERMDISP) were performed. The graphical representation of the variation in the composition of pollination syndromes between seasons and among sampling units was shown by analysis of non-metric multidimensional scaling (NMDS). Mixed generalized linear models (MGLMs) were constructed to test the hypothesis that the months comprising the end of the dry season (September and October) have higher richness and abundance of pollination syndromes. The response variables were richness and the abundance of pollination syndromes and the explanatory variable were seasons. Generalized linear models (GLMs) were constructed in order to observe the difference in richness and abundance of pollination syndromes among sampling units. The response variables were richness and the abundance of pollination syndromes and the explanatory variable were sampling units.
Results A total of 260 plants of 66 species, including trees, shrubs, herbs, and vines, were classified into the pollination syndromes. Vegetation structure and composition significantly differed across sampling units, particularly in tree species richness, tree height, dbh, and tree abundance. The reference site (Nativa) together with the oldest reforestation site had, in general, more plant species and higher abundance, besides taller trees. Although flowering plants were found throughout the study period, only those with the pollination syndromes of melittophily, myophily, and phalaenophily appeared throughout the study period (Table 2). Melittophily (the only syndrome encountered in all of the sampling units) and cantharophily were the most frequent syndromes presenting higher relative abundance; 31 and 20%, respectively, of the flowering plants (Table 2). Sapromyophily was the syndrome with the lowest relative abundance (0.77%) (Table 2). Among the flowers, 11 different pollination syndromes were identified (Table S2). The composition of pollination
Table 2. Richness, sites of records (sampling units), temporal distribution, abundance, and relative abundance (%) of the pollination syndromes recorded in the study area between the months of March 2013 and January 2014. DE, late dry season; DS, beginning of the dry season; RA, relative abundance; RE, the end of the rainy season; RS, the onset of the rainy season; x, syndromes record. Seasons Syndromes
Melittophily Cantharophily Myophily Thysanoptera Microhymenoptera Psychophily Phalaenophily Ornithophily Chiropterophily Sphingophily Sapromyophily Total individuals Richness
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Sites of Records
DS
DE
RS
RE
Abundance
RA (%)
1, 2, 3, 4, 5 1, 2, 3 1, 2, 3, 4 2, 4, 5 2, 3, 4, 5 1, 2, 4, 5 1, 2, 3 1, 4 1 1, 2, 3 2, 3
x
x x x
x x x x x x x x
x
x x 85 10
x
80 53 36 27 20 17 11 07 04 03 02 260
30.78 20.38 13.85 10.38 7.69 6.54 4.23 2.69 1.54 1.15 0.77
x x x x x x 60 07
x x x x 84 07
x x x
31 05
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plantations had a greater richness of syndromes than those surrounded by sugar cane fields and sugar cane fields with rural households. We also observed a positive linear correlation between the abundance of plants present in each sampling unit and the abundance (F = 6.3554, p < 0.001) and richness of syndromes (F = 10.715, p = 0.002). The richness of plants in each sampling unit did not influence the richness or abundance of pollination syndromes. Although some interactions between variables were tested, none were significant for richness or for total abundance of pollination syndromes.
(A)
Discussion (B)
Figure 3. Non-metric multidimensional scaling (NMDS) for sorting and graphical visualization of the PERMANOVA and PERMDISP analyses of pollination syndromes among the dry and rainy seasons (A), and among the sampling units (B). Seasons are beginning of the dry season (Ds), late dry season (De), onset of the rainy season (Rs), and at the end of the rainy season (Re). For sampling unit features, see Table 1.
syndromes varied among the four seasons (PERMANOVA, R2 = 0.22033, p = 0.003; PERMDISP, F = 8.8942, p < 0.001) (Fig. 3A) and among the sampling units (PERMANOVA, R2 = 0.37063, p = 0.001; PERMDISP, F = 54.402, p < 0.001) (Fig. 3B). Richness (X 2 = 18.869, p < 0.001) and total abundance (X 2 = 100.97, p < 0.001) of syndromes were greater at the end of the dry season and start of the rainy season (Fig. 4A). We found differences in both richness (F = 4.1339, p = 0.006) and in abundance (F = 9.1421, p < 0.001) of pollination syndromes among the sampling units (Fig. 4B). Age (F = 7.1183, p = 0.01, F = 29.018, p < 0.001) and width (F = 6.5165, p = 0.01, F = 10.184, p = 0.002) of riparian forest fragments influenced the richness and abundance of pollination syndromes (Fig. 4C & 4D). The older and reference areas had the greatest richness and higher abundance of pollination syndromes and did not differ from each other. The reference area, with 400 m, had the greatest total abundance of syndromes (Fig. 4D). However, the area with intermediate forest width (100 m) had a lower richness than areas of 400 and 30 m, which did not differ from each other (Fig. 4D). The type of matrix surrounding the fragments (F = 4.6147, p = 0.03) (Fig. 4E) influenced the richness of pollination syndromes but did not affect the abundance of syndromes. Considering the type of surrounding matrix, sampling units surrounded by Cerrado (Brazilian Savanna) and rubber tree
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Variation in the composition, richness, and abundance of pollination syndromes among seasons was expected because of the pronounced seasonality of the region with distinct dry and rainy seasons, having the greatest rainfall between November and April and least between May and October. Studies show that in tropical regions, there is not a single flowering event or season, but rather, plants which are flowering can be found throughout the year (Oliveira & Gibbs 2000), and although periods of intense flowering have been observed for specific periods of the year, this does not necessarily occur synchronously in different regions of an environment (Oliveira & Gibbs 2000). According to van Schaik et al. (1993), the timing of flowering in tropical forests occurs mainly during the dry season, or during the period of transition between the dry and rainy seasons (end of the dry season and the start of the rainy season). Thus, there is a tendency to encounter a greater number of trees during flowering when the amount of precipitation begins to decrease (van Schaik et al. 1993). According to Janzen (1967), flowering during the dry season is more advantageous because climatic conditions favor the activity of pollinating insects. Borchert (1983) also mentioned lower pollinator activity during the rainy season as a possible determining factor for the period of flowering of species in a dry forest in Costa Rica. The presence of fruits, whose seeds are dispersed by animals during the rainy season, ensures that they remain attractive for a longer period of time, thereby improving the chances of seed dispersal (Oliveira & Gibbs 2000). Thus, the seasonal pattern found in this study can be considered fairly common for tropical forests. The four sampling units presented a gradient of restoration success based on the vegetation structure. Older and larger areas presented a vegetation structure that was very similar to the reference site, and the results for pollination syndromes also followed this pattern. Thus, pollination syndromes can be a good information source for creating indicators of restoration success. The differences found in the richness and abundance of syndromes among the restoration sites and the reference site were expected because they presented differences in the structure of the vegetal community, time under restoration and the influence of surrounding landscape. Different areas may undergo different recovery processes after a major disturbance, such as the removal of vegetation for the construction of reservoirs for hydroelectric plants, which can result in different responses from plant communities. When
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Figure 4. Pollination syndrome richness and abundance by season (A), sampling units (B), age (C), width (D), and by percentage of habitat matrix (E) in riparian forest restoration sites of the Volta Grande reservoir of the Rio Grande River, Minas Gerais, Brazil. Seasons are beginning of the dry season (Ds), late dry season (De), onset of the rainy season (Rs), and at the end of the rainy season (Re). For sampling unit features, see Table 1. Bars are means ± SE.
recovery strategies are implemented in areas in an asynchronous manner, and without preestablished type of restoration practices, great heterogeneity among restoration areas can result. This process can lead to patches in different successional stages that exhibit distinct patterns of richness and abundance of species (Rodrigues et al. 2009), such as was found in this study. As expected, the reference site (30 years of age) in our study showed the highest richness and abundance of pollination syndromes. This sampling unit also had the highest richness and abundance of plants presenting a more complex vegetation structure (MCTB Messias 2014, Federal University of Ouro Preto, personal communication). The sampling unit in a 20-year reforestation also had high values for richness and abundance
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of syndromes and did not differ from the reference site unit, which was also a secondary successional stand. This sampling unit within a fragment of riparian vegetation of intermediate age probably still contains species of the initial succession stage as well as intermediate and advanced stages, thus favoring the richness and abundance of syndromes. From this premise, it can be assumed that younger sampling units, up to 10 years since planting, are still dominated by a large number of pioneer species or species of initial successional stages, which would explain the low values of richness and abundance of pollination syndromes in these younger riparian forest fragments. The width of a sampling unit does not seem to contribute to an increase in syndrome richness, but it is an important factor
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in syndrome abundance. No differences were found between the reference site (400-m wide) and the sampling unit with 30-m width, and even the 100-m wide sampling unit showed lower syndrome richness than both units. The lower richness in wider areas was not expected because the edge effect should be more intense in narrower fragments, leading to an increase in mortality rates, that become greater than in wider fragments or non-fragmented areas, which could lead to a reduction in the abundance of syndromes (Laurance & Vasconcelos 2009). We found no relationship between richness and abundance of pollination syndromes and richness of plants in each sampling unit, this may be because of the lower richness of plant species. According to Faegri and Van der Pijl (1979), plants belonging to the same family can often share the same pollination syndrome, which may also explain the non-significant relationship. However, both richness and abundance of syndromes correlated positively with the total abundance of plants. This result was expected because the larger the number of plants, the greater the possibility of flowering plants and different types of flowers. It was expected that melittophily would be the most frequently recorded pollination syndrome throughout the sampling period and across all sampling units. This syndrome is more common in tropical environments, independent of the sampled ecosystem (Faegri & Van der Pijl 1979). Despite the importance of other syndromes, based on their high relative abundance and wide distribution, cantharophily is another syndrome that is representative of the study area, although in other tropical ecosystems, it is much less important (Gottsberger 1999) despite showing high diversity in tropical forests. Pollinating beetles are very specific to the groups of plants that they pollinate (Gottsberger 1999), which may help explain the high frequency of cantarophily in the study area as there is a high abundance of individuals of Xylopia aromatica, a species of Annonaceae that is only pollinated by beetles (Gottsberger 1999; Carvalho et al. 2012). The forest cover in the surrounding matrix may also explain the greater richness of pollination syndromes found in some of the sampling units, but it does not explain the greater abundance. Greater richness of syndromes was observed in areas surrounded by Cerrado (Brazilian Savanna) or rubber tree plantations. These results corroborate our hypothesis that the higher the incidence of a forest matrix, the greater the richness of pollination syndromes because the forest matrix can provide diaspores (natural forest) and also facilitate dispersal (both natural forest and tree monoculture) that could colonize those areas under recovery. The characteristics of the matrix are an important aspect in the context of the landscape because the matrix type that surround patches of habitat has significant effects over the biodiversity in different types of landscapes, spatial scales, and taxonomic groups. There is evidence that the type of matrix influences individual survival and reproduction as well as the structure and dynamics of communities, especially interspecific relationships (Prevedello & Vieira 2009). This study was the first to test, on a temporal and spatial scale, the influence of a set of abiotic and biotic variables on the richness and abundance of pollination syndromes in an area of
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riparian vegetation in the process of recovering from intensive anthropogenic degradation. The distribution of pollination syndromes in the study area has a seasonal pattern common for tropical forests (Bawa 1990). In addition to climatic conditions, the composition of syndromes is also influenced by factors intrinsic to the system itself, such as competition among plant species and plant–animal interactions and characteristic of each fragment of riparian vegetation studied (Britain et al. 2013). Patterns of richness and abundance of pollination syndromes throughout the year accompany periods of peak flowering in tropical forests, which occurs mainly during the dry season or the transition period between the dry and rainy seasons, when there is less precipitation and greater pollinator activity. Age, width, surrounding matrix, and abundance of plants showed a strong relationship with the richness of pollination syndromes. However, the results indicated that the patterns found are the result of the sum of the influence of some or many of the variables, and so it is not possible to think, in terms of the choice of priority areas for riparian vegetation for recuperation, of the variables dissociated from each other. We emphasized that although pollination syndromes are a good predictor of environmental quality, inferences about the restoration success based only on the richness of pollination syndromes can lead to an underestimation. Therefore, restored riparian forests could be important refuges for forest species and increase landscape permeability by allowing pollinators mobility between forest patches (Sant’Anna et al. 2014). Consequently, these areas potentially increase regional biodiversity and restore some of the most important ecosystem services provided by these organisms. We conclude that floral traits are good indicators of environmental restoration of riparian forests. However, when planning for active restoration, attention should be given to the proper choice of plant species on the basis of pollination syndromes that should attract pollinators. The presence of one or more forest fragments in the nearby matrix can increase pollination syndromes and enhance pollinator visits.
Acknowledgments CEMIG and FAPEMIG provided grants and scholarship to R.M. (CRA-APQ03055/11), staff of Volta Grande Station for the support during field work, UFOP for logistics, CNPq provided a scholarship to Y.A. M. C. Messias for help with plant community data. To J. M. Torezan for helpful suggestions in an earlier version of this manuscript.
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Supporting Information The following information may be found in the online version of this article: Figure S1. Volta Grande Reservoir, Brazil—landscape and study sites. Table S1. Pollination syndromes recorded in riparian vegetation in the Volta Grande Reservoir, Minas Gerais, Brazil (according to Faegri & Van der Pijl 1979 with modifications). Table S2. Pollination syndromes recorded in riparian vegetation in the Volta Grande Reservoir, Minas Gerais, Brazil (according to Faegri & Van der Pijl 1979 with modifications).
Received: 12 March, 2015; First decision: 22 April, 2015; Revised: 25 November, 2015; Accepted: 25 November, 2015; First published online: 20 January, 2016
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