Influence of palm trees on the richness and distribution of plant species on the murundus at a Caatinga/Cerrado ecotone

Abstract

Understand the role of the drivers in vegetation pattern is essential in ecology since diversity plays a major role in the stability and maintenance of plant communities. The murundus are small and scattered earthmounds with a differentiated flora of its surrounding. In our study site (Campo Maior, Piauí, Northeastern Brazil), we classified them in three categories: presence of carnaúba (PC), presence of tucum (PT), and with the absence of palm trees (AP). Here, our goals were (1) to explore alpha diversity using the richness estimator and abundance distribution rank, expecting that palm trees could influence the richness of plant species on murundus; (2) analyzing the species richness-area relationship in the murundus, following the assumptions that the largest one holds more species; (3) find the changes in the species composition (beta diversity) between the three categories of murundus, assuming which the presence of palm trees influence the species composition; and (4) investigate if the distance between murundus is a decisive factor in the species composition, where the closest murundus are the most similar in species composition. Ours results showed that palms trees do not influence the richness of the murundus, the largest murundus are the richest ones, and the turnover predominantly determines beta diversity in the different murundus categories. Furthermore, the distance between the murundus did not determine its floristic similarity. Overall, we demonstrated which the species of palm trees are not the main drive of the plant assemblage in the murundus, however its size comprises a major factor in the richness, with great species substitution, which explains the high plant diversity.

Key words
biogeography; dispersion; earthmounds; floristic; phytosociology

Resumo

Compreender o papel dos condutores nos padrões de diversidade é essencial na ecologia, uma vez que a diversidade desempenha um papel importante na estabilidade e manutenção das comunidades de plantas. Os murundus são montes de terra pequenos e dispersos com uma flora diferenciada em seu entorno. Em nosso local de estudo (Campo Maior, Piauí, Nordeste do Brasil), os classificamos nas categorias: presença de carnaúba (PC), presença de tucum (PT) e ausência de palmeiras (AP). Aqui, nossos objetivos foram (1) explorar a diversidade alfa usando o estimador de riqueza e a classificação de distribuição de abundância, uma vez que esperávamos que as palmeiras pudessem influenciar a riqueza de espécies de plantas em murundus; (2) explorar as relações de espécies-área no murundus, partindo do pressuposto de que o maior contém mais espécies; (3) encontrar as mudanças na composição de espécies (diversidade beta) entre as três categorias de murundus, supondo que a presença de palmeiras influencia na composição de espécies; e (4) investigar se a distância entre os murundus é um fator decisivo na composição das espécies, onde os murundus mais próximos são os mais semelhantes na composição das espécies. Nossos resultados demonstraram que as palmeiras não influenciam a riqueza dos murundus, os maiores murundus são os mais ricos, e o turnover determina predominantemente a diversidade beta nas diferentes categorias de murundus. Além disso, a distância entre os murundus não determinou sua similaridade florística. De maneira geral, demonstramos que as espécies de palmeiras não são o principal impulsionador da assembleia de plantas nos murundus, porém seu tamanho constitui um fator preponderante na riqueza, com grande substituição de espécies, o que explica a elevada diversidade vegetal.

Palavras-chave
biogeografia; dispersão; murundus; florística; fitossociologia

Introduction

The species-area relationship is well known for describing scale dependence on diversity components when measured by species richness (MacArthur & Wilson 1967; Zhang et al. 2015). In this context, the organization of species diversity across a region can be characterized by alpha, beta, and gamma diversity (Whittaker 1972; Magurran 2004). Alpha diversity constitutes the total number of species in one location, while beta diversity represents the change in species composition along an environmental gradient, and gamma diversity is defined as the total number of species observed in a region (Whittaker 1972; Nogueira et al. 2008; Baselga & Orme 2012; Zhang et al. 2015; Thukral 2017). Understanding the role of drivers in diversity patterns is a fundamental issue in ecology, since diversity plays a major role in the stability and maintenance of communities (Piroozi et al. 2018; Willis 2019). Thus, understanding the patterns of species distribution is useful in determining conservation strategies and policies (Budka et al. 2019; Li et al. 2019).

Alpha diversity is measured at the local level and is the most widely used component in community characterization, using indices based on species richness and equity of abundance (Gotelli & Colwell 2011; Magurran 2004; Willis 2019). On the other hand, beta diversity can be explained by two spatial components: turnover and nesting. Turnover implies the substitution of species between sites, while nesting occurs when sites with a smaller number of species represent a subset of species from species-rich sites (Baselga 2010). Thus, even at very fine scales, beta diversity increases rapidly with spatial growth due to the high variation in stochastic species distribution patterns between sampling units, which is a species response to habitat heterogeneity (Barton et al. 2013). Understanding, separating, and quantifying these two components of beta diversity can be useful in revealing ecological processes responsible for patterns, as well as planning conservation strategies (Koleff et al. 2003; Baselga 2010).

Measuring the alpha and beta diversity components summarizes species diversity and allows for a better understanding of the processes that lead to species distribution patterns (Scofield et al. 2012; Baselga 2010). This approach has been used to infer the processes of species coexistence and helps interpret patterns of divergence and convergence in community composition and structure (Baselga 2010). Differentiating the turnover and nesting components of beta diversity is crucial to improving our understanding of ecological and conservation issues (Baselga 2010).

Therefore, analysis of beta diversity patterns and positive interactions between species are important in the formation of species composition, as well as the diversity and dynamics of the plant community (Callaway & Walker 1997; Stachowicz 2012), which enables the identification of processes involved in diversity patterns and species richness. In a transition zone between Cerrado and Caatinga in the state of Piauí, there is the murundus phytophysiognomy (earthmounds), which is characterized by the presence of microreliefs occupied by tree and shrub vegetation that are distributed along flood lands or swamps, acting as environmental filters (Marimon et al. 2015), with an herbaceous layer and some isolated woody trees, locally called capões (Farias & Castro 2004). These capões are phytophysiognomies similar to those found in the midwestern Cerrado and Pantanal, where they are called campos de murundus (earthmound fields) and whose many aspects have already been studied including the formation of microreliefs (Oliveira-Filho 1992; Silva et al. 2010), the floristic composition (Ponce & Cunha 1993; Marimon et al. 2012) and the species-area or volume relationships (Oliveira-Filho 1992; Resende et al. 2004; Marimon et al. 2012; Morais et al. 2014). However, the colonization process and the changes in species composition of these earthmounds still remains unclear.

In the state of Piauí, the ocurrence of murundus is common together with the presence of two species of Arecaceae, Copernicia prunifera (Mill.) H.E.Moore (carnaúba) and Astrocaryum vulgare Mart. (tucum). Some studies have demonstrated the importance of Arecaceae in structuring communities since they can influence the formation of a seed bank, nucleations (Pott & Pott 2002), seed rain and attract dispersers (Andreazzi et al. 2009; Torquarto 2015). Thus, we expected that C. prunifera and A. vulgare can act as natural perches and as nucleators (Santos & Pillar 2007; Dias et al. 2014; Reis et al. 2014). They can also facilitate ecological processes that encourage significant changes in resource conditions close to its stipe, promoting the abundance and richness of plant species (Montesinos 2015; Michalet & Pugnaire 2016). It is possible that in the murundus of the Campo Maior Vegetation Complex, the distribution and richness of tree species are more influenced by palm species than by the geographical distance between murundus. Thus, the beta diversity approach can help in understanding the patterns of diversity on a spatial scale (Gaston 2000; Leibold et al. 2004; Cottenie 2005), allowing to verify whether differences in species composition between murundus (beta diversity) is explained by nesting or turnover.

Therefore, we conducted a survey of tree and shrub vegetation in murundus with the presence of carnaúba (PC), presence of tucum (PT), and with the absence of palm trees (AP). First, we investigated the alpha diversity (species richness) using a richness estimator and abundance distribution rank, aiming to explore if palm trees can influence the richness species on murundus. Second, we expect an increase in species richness with an increase in the area of ​​murundus, following the well-known assumptions of the species-area relationship. Third, we hope to find divergence in species composition between the three categories of murundus, analyzing if the presence of palm trees could influence species composition. And, finally, if the distance between murundus is a decisive factor for species composition, where murundus that are closer have a similar composition. For this is expected that turnover is a predominant factor in determining beta diversity.

Material and Methods

Study area

The present study was carried out at Fazenda Pequizeiro (04°51’10”S and 42°12’07”W), in the municipality of Campo Maior, state of Piauí, Northeast Brazil. The studied murundus are located in the legal reserve area of the property a natural (Brasil 1965). According with local residents, the studied murundus have not been deforested in the past and have little evidence of fire, also the area is fenced to prevent entry of cattle, goats and horses.

The regional vegetation is characterized by a park and cerrado field with predominantly herbaceous vegetation, a phytophysiognomy similar to savannahs and a strong presence of carnaubais (stand of carnaúba trees) (Velloso et al. 2002; Sousa et al. 2009). It is located at 200 meters of altitude with an Aw climate (wet and dry tropical) (Kottek et al. 2006). The average temperature is 26.8 °C and the average annual rainfall is 1,360 mm, with well-defined seasonality between the months of June to November. The soil is red-yellow podzolic latosol associated with quartz (CEPRO 2000).

Data collection

We surveyed the trees and shrubs of 42 murundus, 15 with the presence of Copernicia prunifera, 12 with the presence of Astrocaryum vulgare, and 15 where both were absent. Geographic locations (UTM) of the murundus was obtained using GPS in order to make an Euclidean distance matrix. The length, width, and height of all trees and shrubs were sampled in each murundu. We used a tape measure to measure the length and width, where length was considered the largest extension of the murundu. The values ​​of length, width, and height were used to define the area and volume of the murundus. In order to calculate the area (m²) we used the equation: area = (ᴨ/4) × (length × width) (Oliveira-Filho 1992).

We sampled living individuals from the entire murundu with a PGH (Perimeter to Ground Height) > 10 cm to obtain the number of individuals and species for the tree and shrub community. Collection and herborization were conducted according to Fidalgo & Bononi (1984). Identification was carried out through consultation with specialized bibliographies and comparison with exsiccates from the TEPB Herbarium of the Universidade Federal do Piauí. The taxon distribution was conducted according to APG IV (2016), and synonyms were verified in the Flora do Brasil 2020 (continuously updated).

Data analysis

In order to compare the species richness among the three murundus categories (PC, PT and AP), sample-size-based rarefaction and extrapolation species accumulation curves (Gotelli & Colwell 2011) were constructed using the iNEXTfunction in the package iNEXT (Hsieh et al. 2016) and Hill numbers for interpolation and extrapolation (Chao et al. 2014).

Rank-abundance curves were made for the three categories of murundus (PC, PT and AP). In the graphical representation, the rankings of species’ abundances are presented along the horizontal axis in decreasing order of relative abundance, which facilitates community comparisons. The abundance rank is commonly used to infer which species abundance model best describes the community (Magurran 2004; Gotelli & Ellison 2011). Chi-square tests were used with the relative species abundance values to verify the best hypothetical model for the distribution of species abundances for each category of murundus. We selected four abundance distribution models (Log-series, geometric, Broken-stick, and Log-Normal) (Magurran 2004).

The influence of the murundus’ area on species richness and number of individuals from the tree and shrub community were assessed using linear regressions (Gotelli & Ellison 2011). A Mantel test was used to assess the effect of distance between murundus on species composition, and the significance was tested with a Monte Carlo test using 999 permutations (Legendre & Legendre 2012). The Mantel test assesses the correlation between two distance matrices, in this case a spatial distance matrix (Euclidean distance) and a floristic distance (Jaccard index) (Eisenlohr et al. 2015).

To assess whether species composition changes among the three categories of murundus, a PERMANOVA with 999 permutations was used (MacArdle & Anderson 2001). The comparison in species composition among the category of murundus was performed using the “pairwise.perm.amanova” function of the package “RVAideMemoire”. A Non-Parametric Multidimensional Scaling (NMDS) ordination was used to reduce the dimensionality of the data and gave a visual representation of the compared groups using PERMANOVA. We used a species presence and absence matrix, which was then used to calculate a distance matrix using the Jaccard index.

To check if the difference in species composition between murundus (beta diversity) is explained by nesting or turnover, we used the “beta.multi” and “parwise” functions of the betapart package (Baselga & Orme 2012). The beta.multi function was used to calculate the values ​​of the turnover and nesting components. The Sørensen index was used to obtain total dissimilarity. The beta.pair function calculates the same three dissimilarity metrics as the previous function. Instead of returning three unique values, as in the beta.multi function, beta.pair generates three dissimilarity matrices (total dissimilarity, turnover component, and nesting). The generated dissimilarity matrices can be used to construct a cluster, where the component that best explains beta diversity is selected (Baselga & Orme 2012; Maechler et al. 2005). All the analyzes were performed using R program (R Core Team 2020), and a value of p < 0.05 was used for all analyzes (Callegari-Jacques 2004).

Results

The species with the greatest abundance in the murundus were: Combretum leprosum Mart. (257ndividuals), Mouriri elliptica Mart. (195), Curatella americana L. (118), Ocotea brachybotrya (Meisn.) Mez. (115), Mimosa caesalpiniifolia Benth. (108), and Agonandra brasiliensis Miers ex Benth. & Hook. f. (88). Together, these species totaled 763 individuals (46.5%). For the three categories of murundus, we found that the six most abundant species added up to values greater than 50% of the community abundance (Tab. 1). For murundus with carnaúba, the six most abundant species totaled 330 individuals (61.57% of the relative abundance). For murundus with tucum, these six species totaled 371 individuals (58.99%). In murundus without palms, the six species constituted 308 individuals (64.84%). Species richness of murundus AP did not differ from murundus PC and PT, since we verified overlapping confidence intervals, and the rarefaction curves showed asymptotes (Fig. 1).

Figure 1
Rarefaction curve for tree and shrub species in murundus with carnaúba (PC), with tucum (PT), and absence of palms (AP), from the Complexo Vegetacional de Campo Maior, Piauí, Northeast Brazil.

Table 1
Families, species and number of individuals of tree-shrub species found in murundus with carnaúba (PC), with tucum (PT) and with the absence of Palms (AP), from the Vegetation Complex of Campo Maior, Piauí, Northeast Brazil. NT = total number of individuals; * = species with the greatest contribution to community abundance.

Family	Species	PC	PT	AP	NT
Anacardiacae	Anacardium occidentale L.	4	9	7	20
Anacardiacae	Astronium fraxinifolium Schott	1			1
Apocynaceae	Aspidosperma cuspa (Kunth) S.F.Blake		1	2	3
Arecaceae	Astrocaryum vulgare Mart.		42*		42
Arecaceae	Bactris setosa Mart.	9			9
Arecaceae	Copernicia prunifera (Mill.) H.E.Moore	58*	3		61
Bignoniaceae	Handroanthus heptaphyllus (Vell.) Mattos	1			1
Bignoniaceae	Handroanthus serratifolius (Vahl) S.Grose			2	2
Bignoniaceae	Handroanthus vellosoi (Toledo) Mattos	1			1
Bignoniaceae	Jacaranda brasiliana (Lam.) Pers.	2			2
Bignoniaceae	Tabebuia aurea (Silva Manso) Benth. & Hook.f. ex S.Moore	15	14	21	50
Bixaceae	Cochlospermum regium (Mart. ex Schrank) Pilg.	7	3	3	13
Combretaceae	Combretum lanceolatum Pohl ex Eichler	1			1
Combretaceae	Combretum leprosum Mart.	36*	102*	119*	257
Combretaceae	Terminalia actinophylla Mart.	6		1	7
Dilleniaceae	Curatella americana L.	49*	41*	28*	118
Euphorbiaceae	Croton campestris A.St.-Hil.	3	2	2	7
Fabaceae	Amburana cearensis (Allem㯩 A.C. Sm.	3	3	10	16
Fabaceae	Andira cujabensis Benth.	5	20	13	38
Fabaceae	Bauhinia dubia G. Don		15	3	18
Fabaceae	Bauhinia ungulata L.	2			2
Fabaceae	Libidibia ferrea Mart.	3		1	4
Fabaceae	Hymenaea courbaril L.		4	7	11
Fabaceae	Luetzelburgia auriculata (Allem㯩 Ducke.	16	34	14	64
Fabaceae	Machaerium acutifolium Vogel.	1			1
Fabaceae	Mimosa caesalpiniifolia Benth.	39*	52*	17	108
Fabaceae	Mimosa arenosa (Willd.) Poir.	8		2	10
Fabaceae	Mimosa tenuiflora (Willd.) Poir.	1			1
Fabaceae	Mimosa sp.1		2		2
Fabaceae	Senna acuruensis (Benth.) H.S. Irwin & Barneby.	7	11	51*	69
Fabaceae	Tachigali aurea Tul.			1	1
Lamiaceae	Vitex cymosa Bertero ex Spreng.		1	2	3
Lauraceae	Ocotea brachybotrya (Meisn.) Mez.	17	64*	34*	115
Malpighiaceae	Byrsonima crassifolia (L.) Kunth			1	1
Malvaceae	Helicteres sacarolha A.St.-Hil., Juss. & Cambess.		1		1
Malvaceae	Sterculia striata A. St.-Hil. & Naudin	3		3	6
Melastomataceae	Mouriri elliptica Mart.	114*	33	48*	195
Moraceae	Ficus sp.1		1		1
Myrtaceae	Eugenia sp.1				0
Myrtaceae	Myrcia retorta Cambess.	4	17	1	22
Myrtaceae	Myrcia sp.1	9	3	3	15
Myrtaceae	Myrcia sp.2	11		6	17
Ochnaceae	Ouratea ceacearensis (Tiegh.) Sastre	4	5	2	11
Olacaceae	Ximenia americana L.	5	5		10
Opiliaceae	Agonandra brasiliensis Miers ex Benth. &Hook.f.	3	70*	15	88
Proteaceae	Roupala montana Aubl.	1			1
Rubiaceae	Alibertia edulis (Rich.) A.Rich.	9	6	3	18
Rubiaceae	Genipa americana L.	1			1
Rubiaceae	Randia armata (Sw.) DC.	10	11	5	26
Rubiaceae	Rudgea sp.1	4			4
Rubiaceae	Tocoyena formosa (Cham. & Schltdl.) K. Schum.	18	4	3	25
Sapotaceae	Pouteria ramiflora (Mart.) Radlk.		9	1	10
Simaroubaceae	Simarouba versicolor A.St.-Hil..		2	1	3
Vochysiaceae	Callisthene fasciculata Mart.	34*	8	3	45
Vochysiaceae	Chomelia obtusa Cham. & Schltdl.	2	1	1	4
Vochysiaceae	Qualea grandiflora Mart.	4	9	28*	41
Vochysiaceae	Qualea parviflora Mart.	4	21	11	36

A few abundant species were found for the three categories of murundus. The rank-abundance curves (Fig. 2) showed all categories of murundus presented the abundance curve adjusted to the Log Series model (PC: X2 = 17.2 and p = 0.9445; PR - X2 = 17.31 and p = 0.8353; AP - X2 = 19.5 and p = 0.7725).

Figure 2
Rank of relative abundances of tree and shrub species in murundus with carnaúba, tucum, and absence of palms, from the Complexo Vegetacional de Campo Maior, Piauí, Northeast Brazil.

For all categories of murundus, we found positive relationships (Fig. 3a-b) between area and species richness (PC: R² = 0.67 and p < 0.001; PT R² = 0.82 and p = 0.001; AP R² = 0.42 and p < 0.001; Fig. 3a), and between area and number of individuals (PC R2 = 0.73 and p = 0.01; PT R² = 0.87 and p < 0.001; AP R² = 0.85 and p = 0.008; Fig. 3b).

Figure 3
Relationship between area with number of species and number of individuals in murundus with carnaúba, tucum and absence of palms, from the Complexo Vegetacional de Campo Maior, Piauí, Northeast Brazil.

The distance between murundus showed no influence on tree and shrub species composition (Mantel test; r = 0.005; p = 0.44). On the other hand, the PERMANOVA showed that there is a difference in composition between the three types of murundus studied (p = 0.001). All categories of murundus present differences in species composition as shown by the a posteriori test (p < 0.001), and therefore, are distinct communities. The NMDS ordination showed the separation of three groups (Fig. 4), the first group without palms, the second with tucum, and lastly, murundus with the presence of carnaúba (stress = 0.223). The beta diversity analysis showed that the change in species composition was mainly influenced by turnover (0.89 or 89%), and there was little influence from nesting (0.11 or 11%). Figure 5 corroborates the NMDS analysis, reinforcing the hypothesis that the three categories of murundus have different tree and shrub communities and contribute to the increase in regional richness.

Figure 4
Ordination (NMDS) of tree and shrub species from murundus with carnaúba, tucum and absence of palms, of the Complexo Vegetacional de Campo Maior, Piauí, Piauí, Northeast Brazil.

Figure 5
Dendrogram generated using the turnover component dissimilarity matrix, for murundus with the absence of palms (AP), presence of carnaúba (PC), and presence of tucum (PT).

Discussion

The similarities in species richness and differences in species composition between the three categories of murundus (with carnaúba, with tucum and absence of palms) shows the importance of palm trees in the distribution of species in murundus. Palm trees can provide resources for fauna dispersers, reducing the dispersion limitations imposed by the swamps or flooded plains on murundus, thus, promoting species diversity.

The ranking of species’ abundances shows that the increase in community richness in the three categories of murundus was influenced by the equity of species abundances (Margurran 2004). The log-series model verified in the three murundus categories demonstrates the prevalence of rare species with the presence of a few high abundance species (Magurran 2004; Gotelli & Colwell 2011; Soares et al. 2020), which shows the importance of rare species in increasing local richness (alpha diversity) (Magurran 2004). The log-series model is also considered a niche partition model, and assumes that species occur randomly in a fraction of the niche as colonization by new species occurs (Magurran 2004). In this model, the dispersion capacity, environmental characteristics, and interspecific interactions will jointly determine community composition (Ferreira & Petrere-Jr 2008).

Our results show that the observed and estimated richness were close among the murundus categories, negating our hypothesis that palm trees favor local richness. On the other hand, the positive relationships found between murundus area and species richness and abundance support the hypothesis raised in this study and corroborate the assumption of the island biogeography theory (MacArthur & Wilson 1967). Our results also corroborate other studies that found a positive relationship between species-area in murundus (Oliveira-Filho 1992; Morais et al. 2014), and shows the importance of these microreliefs on local richness.

Our observations pointed that murundus with larger areas present more drained soils, allowing the occupation and establishment of woody vegetation, since water saturation during the rainy season is a limiting factor for the occupation of tree species (Furley 1986; Oliveira-Filho 1992). Studies conducted in murundu fields, showed that soil’s water saturation can cause differences in species distribution, as some individuals cannot tolerate hydromorphic soils, and therefore, vegetation is restricted to murundus (Resende et al. 2004; Barros & Castro 2006). In this way, the great size (1,000 m²) of the largest murundus and the well-drained soils also explain the high species richness in these ones.

On the other hand, we did not find a relationship between distance and species composition in murundus; thus, the hypothesis that the distance between murundus may determine species composition is negated. However, our hypothesis that murundus with palms have a different species composition than murundus without palms was confirmed. We believe that due to the distance between the murundus, species dispersed by the wind or by autochory are less successful in establishing themselves in murundus, and therefore, zoochory, is a more favorable type of dispersion mainly for those murundus that attract fauna.

Open areas, for example the murundu fields, have a low seed rain density due to low tree density, so the investment in dispersion strategies to attract fauna can guarantee seed dispersion to suitable places for germination (Fragoso et al. 2017), and the palms present in the murundus would be the attraction for dispersing fauna. Thus, from dispersion to the establishment of species, there are environmental filters that can eliminate many species and restrict occupation in certain habitats or reduce the community to a small number of species (Lambers et al. 2008), in our case, water is one of these environmental filters (Marinon et al. 2015).

Our study shows that changes in species composition among the three categories of murundus are influenced by turnover, confirming our hypothesis, that the presence of palms can influence the composition and distribution of species. The main findings of the present study were that different types of communities (PC, PT and AP) within the same phytophysiognomy have different species composition.

The dispersion can be a determining factor for differences in species composition between murundus with and without palm trees, since palm trees are attractive to dispersing fauna, and thus, influence the colonization of these murundus by increasing the entry of diaspores and seeds. We believe that carnaúba and tucum can, not only act as artificial perches, but also exercise the function of natural perches because they attract dispersers by offering fruits and seeds. Additionally, their height makes them more attractive to birds, thus being able to cause an increase in seed rain (Reis et al. 2014; Fragoso et al. 2017).

The architectural differences between the two palm species can attract different types of dispersers, by the differences in the species composition between murundus with the presence of palms. Carnaúba presents a solitary stem without spines, reaching up to 15 m in height. The leaves are numerous and in the shape of a fan, a globose crown, with curved spines on the margins of the petiole, and fruits between 1.8 to 2.17 cm in length (Lorenzi et al. 2010). tucum has agglomerated stems, with stipe up to 20 m high, internodes are covered with thorns, numerous leaves, long sheath, and petiole covered with thorns, the fruits are globose with 3.5 to 5 cm in length, and 2.5 to 2.7 cm in diameter (Lorenzi et al 2010). Also, the architectural features of the plant can influence the availability of landing areas and reflects animal contributions in the seed rain (Fragoso et al. 2017). As they works as live perches, tall individuals are considered more effective and attractive to dispersers (Reis et al. 2014). Live perches with fruits can act as a feed, and thus, intensify the visitation of dispersers, this can be seen in the study area where the soil was upturned by mammals and rodents that were foraging for fruits deposited by carnaúba and tucum in the soil around the studied palm trees, as also verified by Torquato (2015) and Andreazzi et al. (2009). Seeds and fruits deposited in the soil can also stimulate secondary dispersion by rodents or other mammals (Hamäläinen et al. 2017).

Finally, in this study we found that carnaúba and tucum do not influence the richness (alpha diversity) in murundus, and that the species richness in the three murundus categories is influenced by less abundant species. Our results corroborate the theories that address the positive species-area relationship; however, distance between murundus did not determine similarity. The difference in species composition between the three categories of murundus is determined by species substitution, which shows that the presence of the studied palms influences the dispersion and colonization process. Thus, the three categories are comprised of distinct communities, which explains the high plant diversity of this phytophysiognomy.

Acknowledgements

To the State University of Piaui for the availability of the Botanical Laboratory.

References

• Andreazzi CS, Pires AS & Fernandez FAS (2009) Mamíferos e palmeiras Neotropicais: interações em paisagens fragmentadas. Oecologia Brasiliensis 13: 554-574.
• APG IV - Angiosperm Phylogeny Group (2016) An update of the Angiosperm Phylogeny Group classification for the orders and families of flowering plants: APG IV. Botanical Journal of the Linnean Society 181: 1-20.
• Barros JS & Castro AAJF (2006) Compartimentação geoambiental no complexo regional de Campo Maior, PI: uma área de tensão ecológica. Revista Internacional de Desenvolvimento Local 8: 119-130.
• Barton PS, Cunningham SA, Manning AD, Gibb H, Lindenmayer DB & Dedham RK (2013) The spatial scaling of beta diversity. Global Ecology and Biogeography 22: 639-647.
• Baselga A & Orme CDL (2012) Betapart: an R package for the study of beta diversity. Methods in Ecology and Evolution 3: 808-812.
• Baselga A (2010) Partitioning the turnover and nestedness components of beta diversity. Global Ecology and Biogeography 19: 134-143.
• Brasil (1965) Lei 4771/1965. Código Florestal Brasileiro. Available at <https://www.planalto.gov.br/ccivil_03/LEIS/L4771impressao.htm>. Access in February 2021.
  » https://www.planalto.gov.br/ccivil_03/LEIS/L4771impressao.htm
• Budka M, Matyjasiak P, Typiak J, Okołowski M & Zagalska-Neubauer M (2019) Experienced males modify their behaviour during playback: the case of the chaffinch. Journal of Ornithology 160: 673-684.
• Callaway RM & Walker LR (1997) Competition and facilitation: a synthetic approach to Interactions in plant communities. Ecology 78: 1958-1965.
• Callegari-Jacques SM (2004) Bioestatística: princípios e aplicações. Artmed, Porto Alegre. 253p.
• CEPRO (2000) Diagnóstico socioeconômico: Campo maior, Piauí. Fundação CEPRO – Teresina. 420p.
• Chao A, Gotelli NJ, Hsieh TC, Sander EL, Ma KH, Colwell RK & Ellison AM (2014) Rarefaction and extrapolation with Hill numbers: a framework for sampling and estimation in species diversity studies. Ecological Monographs 84: 45-67.
• Cottenie K (2005) Integrating environmental and spatial processes in ecological community dynamics. Ecology Letters 8: 1175-1182.
• Dias CR, Umetsu F & Breier TB (2014) Contribuição dos poleiros artificiais na dispersão de sementes e sua aplicação na restauração florestal. Ciência Florestal 24: 501-507.
• Eisenlohr PV, Felfile JM, Melo MMRF, Andrade LA & Neto JAM (2015). Fitossociologia no Brasil - métodos e estudos de casos. Vol. II. Ed. UFV, Viçosa. 556p.
• Farias RRS & Castro AAJ (2004) Fitossociologia de trechos da vegetação do Complexo de Campo Maior, PI, Brasil. Acta Botanica Brasilica 18: 949-963.
• Ferreira FC & Petrere-Jr M (2008) Comments about some species abundance patterns: classic, neutral, and niche partitioning models. Brazilian Journal of Biology 68: 1003-1012.
• Fidalgo O & Bononi VL (1984) Técnicas de coleta, preservação e herborização de material botânico. Manual n. 4. Instituto de Botânica, São Paulo. 61p.
• Flora do Brasil 2020 (continuously updated) Jardim Botânico do Rio de Janeiro. Available at <http://floradobrasil.jbrj.gov.br/>. Access in February 2021.
  » http://floradobrasil.jbrj.gov.br/
• Fragoso RDO, Carpanezzi AA, Koehler HS & Zuffellatoribas KC (2017) Barreiras ao estabelecimento da regeneração natural em áreas de pastagens abandonadas. Ciência Florestal 27: 1451-1464.
• Furley PA (1986) Classification and distribution of mounds in the Cerrado of central Brazil. Journal of Biogeography 13: 265-268.
• Gaston KJ (2000) Global patterns in biodiversity. Nature 405: 220-227.
• Gotelli NJ & Colwell RK (2011) Estimating species richness. In: Magurran AE & McGill BJ (eds.) Biological diversity: frontiers in measurement and assessment. Oxford University Press, Oxford. Pp. 39-54.
• Gotelli NJ & Ellison AM (2011) Princípios de estatística em ecologia. Artmed, Porto alegre.532p.
• Hämäläinen A, Broadley K, Droghini A, Haines JA, Lamb CT, Boutin S & Gilbert S (2017) The ecological significance of secondary seed dispersal by carnivores. Ecosphere 80: 16-85.
• Hsieh TC, Ma KH & Chao A (2016) iNEXT: an R package for interpolation and extrapolation of species diversity (Hill numbers). To appear in Methods in Ecology and Evolution.
• Koleff P, Gaston KJ & Lennon JJ (2003) Measuring beta diversity for presence-absence data. Journal of Animal Ecology 72: 367-382.
• Kottek M, Grieser J, Beck C, Rudolf B & Rubel F (2006) World map of the Köppen-Geiger climate classification updated. Meteorologische Zeitschrift, 15: 259-263.
• Lambers H, Chapin III FS & Pons TL (2008) Plant physiological ecology. Springer Verlag, New York. 540p.
• Legendre P & Legendre L (2012) Numerical ecology. 3rd ed. Elsevier, Amsterdam. 990p.
• Leibold MA, Holyoak M, Mouquet N, Amarasekare P, Chase JM, Hoopes MF, Holt RD, Shurin JB, Law R, Tilman D, Loreau M & Gonzalez A (2004) The metacommunity concept: a framework for multi-scale community ecology. Ecology Letters 7: 601-613.
• Li N, Chu H, Qi Y, Li C, Ping X, Sun Y & Jiang Z (2019) Alpha and beta diversity of birds along elevational vegetation zones on the southern slope of Altai Mountains: implication for conservation. Global Ecology and Conservation 19: e006432.
• Lorenzi H, Kahn F, Noblick LR & Ferreira E (2010) Flora brasileira: Arecaceae (palmeiras). Instituto Plantarum de Estudos da Flora, Nova Odessa. 368p.
• MacArthur RH & Wilson EO (1967) The theory of island biogeography. Princeton University Press, Princeton. 224p.
• Maechler M, Rousseeuw P, Struyf A & Hubert M (2005) Cluster Analysis Basics and Extensions. R package. Available at <http://cran.r-project.org/>. Access in February 2021.
  » http://cran.r-project.org/
• Magurran AE (2004) Measuring biological diversity. Blackwell, Oxford. 272p.
• Marimon BS, Marimon-Junior BH, Mews HA, Jancoski HS, Franczak DD, Lima HS, Lenza E, Rossete AN & Moresco MC (2012) Florística dos campos de murundus do Pantanal do Araguaia, Mato Grosso, Brasil. Acta Botanica Brasilica 26: 181-196.
• Marimon BS, Colli GR, Marimon-Junior BH, Mews HA, Einselohr P, Feldpausch TR & Phillips O (2015) Ecology of Floodplain Campos de Murundus Savanna in Southern Amazonia. International Journal of Plant Sciences 176: 670-681.
• McArdle BH & Anderson MJ (2001) Fitting multivariate models to community data: a comment on distance based redundancy analysis. Ecology 82: 290-297.
• Michalet R & Pugnaire FI (2016) Facilitation in communities: underlying mechanisms, community and ecosystem implications. Functional Ecology 30: 3-9.
• Morais RF, Morais FF & Lima JF (2014) Composição e estrutura da comunidade arbórea e arbustiva em Murundus no Pantanal de Poconé, Mato Grosso. Revista Árvore 38: 443-451.
• Montesinos D (2015) Plant-plant interactions: from competition to facilitation. Web Ecology 15: 1-2.
• Nogueira EM, Fearnside PM, Nelson BW, Barbosa RI & Keizer EWH (2008) Estimates of forest biomass in the Brazilian Amazon: new allometric equations and adjustments to biomass from wood-volume inventories. Forest Ecology and Management 256: 18-53.
• Oliveira-Filho AT (1992) Floodplain ‘murundus’ of Central Brazil: evidence for the termite-origin hypothesis. Journal of Tropical Ecology 8: 1-19.
• Piroozi N, Kohandel A, Jafari M, Tavili A & Farizhendi GM (2018) Plant alpha and beta diversity in relation to spatial distribution patterns in different plant community types. Pakistan Journal of Botany 50: 2317-2323.
• Ponce VM & Cunha CN (1993) Vegetated earth mounds in tropical savannas of Central Brazil: a synthesis. Journal of Biogeography 20: 219-225.
• Pott A & Pott VJ (2002) Plantas nativas para recuperação de áreas degradadas e reposição da vegetação no Mato Grosso do Sul. Comunicado Técnico - EMBRAPA. n. 75. EMBRAPA Gado de Corte, Campo Grande. 6p.
• R Core Team (2020). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. Available at <http://www.R-project.org/>.
  » http://www.R-project.org/
• Reis A, Bechara FC, Tres DR & Trentin BE (2014) Nucleação: concepção biocêntrica para a restauração ecológica. Ciência Florestal 24: 509-518.
• Resende ILM, Araújo GM, Oliveira APA, Oliveira AP & Ávila-Júnior RM (2004) A comunidade vegetal e as características abióticas de um campo de murundu em Uberlândia, MG. Acta Botanica Brasilica 18: 9-17.
• Santos MMG & Pillar VP (2007) Influência de poleiros naturais e artificiais na expansão da floresta com Araucária sobre os campos, em São Francisco de Paula, RS. Revista Brasileira de Biociências 5: 594-596.
• Scofield DG, Smouse PE, Karubian J & Sork VL (2012) Use of alpha, beta, and gamma diversity measures to characterize seed dispersal by animals. The American Naturalist 180: 719-732.
• Silva LCR, Vale GD, Haidar RF & Sternberg LSL (2010) Deciphering earth mound origins in central Brazil. Plant & Soil 336: 3-14.
• Soares CJRS, Sampaio MB, Santos-Filho FS, Martins FR & Santos FAM (2020) Patterns of species diversity in different spatial scales and spatial heterogeneity on beta diversity. Acta Botanica Brasilica 34: 9-16.
• Sousa GM, Barros JS, Sousa SR & Castro AAJF (2009) Composição florítica e fitossociologica das Serras de Campo Maior, município de Campo Maior, Piauí, Brasil. Publicações Avulsas em Conservação de Ecossistemas 24: 1-20.
• Stachowicz JJ (2012) Niche expansion by positive interactions: realizing the fundamentals. A comment on Rodriguez-Cabal et al Ideas in Ecology and Evolution 5: 42-43.
• Thukral AK (2017) A review on measurement of alpha diversity in biology. Agriculture Research Journal 54: 1-10.
• Torquato JL (2015) Produção e consumo de frutos zoocóricos em dois fragmentos florestais do oeste do Rio Grande do Norte, Brasil. Dissertação de Mestrado. Universidade Federal Rural do Semi-Árido - UFERSA, Mossoró. 53p.
• Velloso AL, Sampaio EVSB & Pareyn FGC (2002) Ecorregiões: propostas para o bioma Caatinga. PNE Associação Plantas do Nordeste. Instituto de Conservação Ambiental, The Nature Conservancy Brasil, Recife. 75p.
• Whittaker RH (1972) Evolution and measurement of species diversity. Taxon 21: 213-251.
• Willis AD (2019) Rarefaction, alpha diversity, and statistics. Frontiers in Microbiology 10: 2407.
• Zhang Y, Ma K, Anand M, Ye W & Fu B (2015) Scale dependence of the beta diversity-scale relationship. Community Ecology 16: 39-47.

Edited by

Area Editor: Dra. Natalia Ivanauskas

Publication Dates

• Publication in this collection
  16 May 2022
• Date of issue
  2022

History

• Received
  28 Sept 2020
• Accepted
  26 May 2021