Ecological restoration increases conservation of taxonomic and functional beta diversity of woody plants in a tropical fragmented landscape

Forest Ecology and Management 451 (2019) 117538

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Ecological restoration increases conservation of taxonomic and functional beta diversity of woody plants in a tropical fragmented landscape

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Débora Cristina Rothera,b, , Ana Paula Libonia,b, Luiz Fernando Silva Magnagoc, Anne Chaod, Robin L. Chazdone, Ricardo Ribeiro Rodriguesb a

Universidade Estadual de Campinas, Instituto de Biologia, Departamento de Biologia Vegetal, Campinas, São Paulo, Brazil Universidade de São Paulo, Escola Superior de Agricultura “Luiz de Queiroz”, Laboratório de Ecologia e Restauração Florestal, Piracicaba, São Paulo, Brazil c Universidade Federal do Sul da Bahia, Itabuna, Bahia, Brazil d National Tsing Hua University, Institute of Statistics, Hsin-Chu 30043, Taiwan e University of Connecticut, Department of Ecology and Evolutionary Biology, Storrs, CT, USA b

A R T I C LE I N FO

A B S T R A C T

Keywords: Diversity recovery Diversity metrics Large-scale restoration Seedling recruitment Taxonomic and functional beta diversity Tropical restoration Tropical forests

Ecological restoration can re-establish plant species populations, enhance forested habitats extension, improve landscape connectivity, and enable biodiversity persistence within a landscape. However, the potential benefits of ecological restoration on beta diversity have never been explored. Here we use field data to investigate, for the first time, if restoration plantings enhance the taxonomic and functional plant beta diversity in a fragmented landscape of the threatened Atlantic forest. Woody species were evaluated for 320 plots established in 18 forest fragments and 14 restoration plantings within a sugarcane production landscape with low forest cover, in southeastern Brazil. Diversity metrics were assessed using the multiple incidence-data version of Hill numbers and were compared among three sets of study sites: fragments, restoration plantings and the two combined. Fragments showed higher levels of alpha diversity and proportional abundance of non-pioneer and animaldispersed species than restoration plantings. Exotic, pioneer and non-zoochoric species were more abundant in restoration plantings, an expected result considering sites still be in the early or mid-successional stages of development. Taxonomic and functional beta diversity of trees was greatest when both areas were combined. For regenerating plants, however, beta diversity results varied according to species incidence-based frequencies. Although restoration plantings do not result in full recovery of alpha diversity, they can all together complement diversity of forest fragments at the landscape level. The findings indicate two key ecological implications for biodiversity conservation: the critical importance of forest fragments as biodiversity repositories and the positive effect of restoration efforts on landscape-scale diversity in degraded regions. These novel results highlight the importance of species selection for restoration initiatives toward species and functional attributes recognized as significantly reduced or locally rare. Overall, forest fragments and restoration plantings can act synergistically to promote recovery of plant diversity in heavily deforested agricultural landscapes.

1. Introduction Forest restoration plans are an important tool to conserve biodiversity (e.g., endangered species), and to enhance ecosystem services (Benayas et al., 2009). Restored forests play an essential role in conservation at the landscape scale, as they provide additional forest cover for threatened species, reconnect previously isolated biological populations of plants or animals (Brancalion et al., 2013; Rother et al., 2018) and provide important functional properties (e.g., food for fauna or wood production) (Garcia et al., 2015; Silva et al., 2015; MontoyaPfeiffer et al., 2018). Understanding the role of restored forests in

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mitigating the effects of fragmentation and habitat loss is crucial, as a large proportion of tropical forest biodiversity is restricted to small fragments embedded within an agricultural or pasture landscape matrix (Arroyo-Rodríguez et al., 2013). Forest habitat reduction and isolation can negatively affect taxonomic and functional dimensions of biodiversity (Arroyo-Rodríguez et al., 2013; Solar et al., 2015). Also, changes in forest cover and forest structure may lead to taxonomic and functional simplification and the homogenization of biota within regions (Arroyo-Rodríguez et al., 2013). Small and degraded forest fragments may hold missing important groups of species, such as large-seeded species (Oliveira et al.,

Corresponding author at: Universidade Estadual de Campinas, Instituto de Biologia, Departamento de Biologia Vegetal, Campinas, São Paulo, Brazil. E-mail address: [email protected] (D.C. Rother).

https://doi.org/10.1016/j.foreco.2019.117538 Received 6 June 2019; Received in revised form 9 August 2019; Accepted 10 August 2019 0378-1127/ © 2019 Elsevier B.V. All rights reserved.

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Fig. 1. Location of the woody plant communities studied in 18 forest fragments (black squares) and 14 restoration plantings (red circles) located in an Atlantic Forest-Cerrado ecotone in southeastern Brazil. A description of individual forest fragments and restoration plantings can be found in Table S1. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Some recent studies have examined restoration sites from different perspectives and for different biological taxa including invertebrates (Audino et al., 2017; Crouzeilles et al., 2017; Shuey et al., 2017), birds, mammals, amphibians, and plants (Crouzeilles et al., 2017). Although natural regeneration and active restoration have been evaluated at landscapes scales (Crouzeilles et al., 2017; Farah et al., 2017), several important questions remain poorly understood, mainly when tree composition and functional attributes used in active restoration projects were not known (the initial planted species is unknown). Here, we address two specific questions: (i) Can restoration plantings enhance beta diversity for species and functions at landscape scale compared to forest fragments? and (ii) How are functional attributes (e.g., wood density, seed length, dispersal syndromes and ecological strategy) distributed among forest fragments and restoration plantings? To answer these questions, we evaluated taxonomic and functional diversity at different levels, using metrics based on species richness and abundance data, in the Atlantic Forest of southeastern Brazil. This study presents and analyses the findings on diversity metrics at different scales and discuss the critical importance of remaining forests for plant diversity conservation and the effects of restoration efforts on landscape-scale diversity in tropical degraded regions.

2008), species pollinated and/or dispersed by vertebrates (Lopes et al., 2009) and understory and shade tolerant species (Tabarelli et al., 1999). In contrast, a number of disturbance-tolerant native species can become abundant in fragmented forests (Santos et al., 2012), contributing to increased levels of floristic homogenization at a range of spatial scales (Arroyo-Rodríguez et al., 2013). Within this scenario, even forest fragments and restored forests emerge as critically important sources of biodiversity, for supporting ecosystem functions and ecosystem services (Arroyo-Rodríguez et al., 2017), these two ecosystem types may differ in important ways about their biodiversity and the ecosystem functions they support. While forest fragments retain the remaining species after disturbances, restored forests (active restoration) emerge from active human management, such as mixed-species plantations from nursery-grown seedling (Rodrigues et al., 2009; Crouzeilles et al., 2017). In the Brazilian Atlantic forest, decision making on restoration strategies and their outcomes are particularly important due to the need to an effective compliance with the Native Vegetation Protection Law (Garcia et al., 2013). The compliance with the law is also essential since 90% of the native vegetation remaining in the biome is in private rural properties, rather than in protected areas (Soares-Filho et al., 2014; Brancalion et al., 2016). Agricultural companies and landowners, especially those devoted to sugarcane production, have initiated active restoration plantings in riparian corridors on their lands to comply with regulations and to obtain environmental certification for their products (Rodrigues et al., 2011; Brancalion et al., 2013, 2016). Most ecological restoration initiatives in such private properties are concentrated in riparian areas illegally cleared for agricultural use (Rodrigues et al., 2011). Tropical restoration efforts can have different aims and approaches. Increasing the likelihood of native species persistence in fragmented landscapes, targeting plant species exploited that have become rare in the region, and restoring habitats and ecosystem services are some approaches of how restoration can be used (Brancalion et al., 2010, 2013). In general, active restoration includes, among other methods, tree plantings with high native species diversity (e.g., about 80 tree species) composed of different functional groups (Rodrigues et al., 2009). It is important to highlight that the number of species used in the active restoration can vary according to environmental laws of each Brazilian state. Also, the restoration method to be applied depends on the aim of the project, local characteristics and landscape context.

2. Material and methods 2.1. Study region The study region is located in an ecotonal region between the Atlantic Forest and Cerrado domains (savanna) in northern Sao Paulo State, Brazil (Fig. 1). It is considered as the most threatened region in the country, as it presents high biodiversity, endemism and anthropic threats (Klink and Machado, 2005; Ribeiro et al., 2009). Since ecological restoration often has been implemented on private lands in compliance with the Native Vegetation Protection Law (Rodrigues et al., 2011; Sparovek et al., 2012), the region also comprises many restoration plantings (a total of 670.49 ha planted in 97 areas). Most of these projects are part of the “Environmental Planning Program of Farms” carried out from 2000 to 2010 by the Laboratório de Ecologia e Restauração Florestal, University of Sao Paulo (Rodrigues et al., 2011). The region is covered by about 10% of native vegetation (forest and wooded savanna), restricted to small fragments of secondary vegetation in different stages of succession (Kronka et al., 2005) (Fig. 1). The 2

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non-pioneer canopy, and non-pioneer understory) according to their light requirements and occurrence in forest strata (Barbosa et al., 2015), species growth form (Carvalho et al., 2010) and expert knowledge (Drs. Natália Ivanauskas, Vinícius Castro Souza and Ricardo Ribeiro Rodrigues). We considered as pioneers those species that develop in conditions of high light levels and usually do not regenerate in the understory; non-pioneer canopy species develop in intermediate shading conditions but do not remain in the understory (early secondary and emergent species); while non-pioneer understory species those develop exclusively in the shaded understory. Species without sufficient knowledge to classify them otherwise were called unclassified (6.7% of the established plant species and 8.2% of the regenerating plant species). We classified those species living outside their native distribution range and those species that occur exclusively in savanna formations as “exotic” (Oliveira-Filho, 2014). Due to the importance to understand how this factor is representative in the communities, exotic species was considered as a trait in the analysis to distinguish the contribution of each functional attribute. Data for wood density in dry weight (g/cm3) were obtained from The Global Wood Density (GWD) database in the subsection Tropical South America (Chave et al., 2009). For morphospecies only identified to the family or genus level, we used the average wood density of the taxonomic group; and for species not in the GWD database, we used the average wood density for the genus (following Flores and Coomes, 2011; Hawes et al., 2012; and Magnago et al., 2014). Species identified at morphospecies and genus levels represented 24% of the total species richness and 2.24% of the total abundance. These species were not included in the floristic diversity analysis but were included in the species richness analysis. Specimens identified to genus level were included in the functional diversity analysis. Analyses for taxonomic and functional beta diversities included only regional native species.

remaining patches are interspersed within a matrix dominated by sugarcane plantations (> 90%), with less extensive areas of commercial forestry (Eucalyptus spp. and Pinus spp.), fruit crops (Citrus spp.) and cattle pastures (SigRH, 2016). Climate in the region is a transition between Aw (tropical savanna climate, influenced by the altitude) and Cwa (humid subtropical climate, with wet summers and dry winters). The annual mean temperature is around 21 °C, January being the warmest (23.5 °C) and July the coldest month (17.5 °C) (Alvares et al., 2013). We conducted our study in 14 riparian restoration plantings from 3 to 7 years old and varying in size from 0.4 to 34.63 ha, covering a total of 146.14 ha. All restoration plantings present a closed canopy, received grass control treatments during the first two years and are in private sugarcane farms. Species selection for restoration plantings were based on their eco-physiological attributes such as fast- (called as cover species) and slow-growing species (called as diversity species). Seedlings were planted following a 3 × 2 m scheme resulting in 1666 individuals/ha. Species richness in the restoration plantings varied from 16 to 50 plant species. For the forest fragments we included only those fragments of semideciduous forests from the map of remaining vegetation of Sao Paulo State. That map included 526 of semideciduous forests, 32 lowland forests and 15 of wooded savanna (Kronka et al., 2005). Our data set resulted in 18 forest fragments from 2 ha to 120 ha in area, totaling 1240.68 ha. Species richness varied from 24 to 65 plant species per fragment. Both forest fragments and restoration plantings have elevation from 635 to 940 m. Details about each restoration planting and forest fragment are available in Appendix S1, S2, and S3: Table S3. Fragments included upland while restoration plantings included both, riparian (nine) and upland areas (five). The list of species produced in the nurseries and used in these restoration plantings was provided by floristic surveys made in both upland and riparian areas of the region. Seeds to produce seedlings in the nurseries were collected in those areas.

2.4. Data analysis 2.2. Woody plant sampling To describe the plant community in forest fragments and restoration plantings we constructed separate rank abundance curves for each stratum and plotted the abundance of each plant species in a bi-dimensional plane from the most to the least abundant (Magurran, 2004). We used the library “sads”, the “fitsads” function and the “poilog” distribution (Prado and Miranda, 2014). Analyses were performed in R software version 3.4.2 (R Development Core team, 2017). To distinguish the contribution of each functional attribute of each functional trait per forest type (i.e., forest fragments, restoration plantings or the two combined) and per plant strata we followed two steps. First, we calculated the Community-Level Weighted Means of each trait (CWM). Second, we evaluated generalized linear models (GLM) or generalized linear mixed models (GLMM), using CWM values as response variables and forest type (forest fragments and restoration plantings) as explanatory variables. We applied GLM with Gaussian family for CWM values of wood density and seed length. However, for the others CWM values of proportional abundance (seed dispersal type and ecological strategy), we used linear mixed model with binomial family. For these models we used “sites” as the random effect. This statistical approach was used to control the individual-level variance and this way, correcting the overdispersion problem (Harrison, 2015). The GLM models were built using the “glm” function from R base. To the GLMM we used the “glmer” function from the “lme4” package. All analyses were performed in R software version 3.4.2 (R Development Core team, 2017). For a given area type (fragment, restoration planting, or the two combined) and plant strata (established or regenerating), we can form two kinds of data: (1) species abundance data, and (2) multiple incidence data (the count of occurrences of each species among sites). We focused our analysis on multiple incidence data because such data are more robust to clustering/aggregation of individuals than abundance

Within each forest fragment and restoration planting, we located 10 4 × 25 m plots (total of 0.1 ha per site), oriented in north–south direction, at least 20 m distant from each other and excluding a 10 m edge buffer. We recorded all trees, palms and shrubs with diameter at breast height (DBH) > 3.18 cm in the plots (hereafter established plants). Within each plot, we established one 1 × 25 m subplot (total of 0.025 ha per site) to sample natural regeneration of woody plants higher than 0.5 m and with DBH ≤ 3.18 cm (we called regenerating plants). The total area sampled was 3.2 ha. Species not identified in the field were collected for subsequent identification (APG III, 2009) in the ESA Herbarium (University of Sao Paulo). 2.3. Functional traits We measured functional traits related to morphological and physical adaptations of woody species in their role as food resources, carbon storage and forest structure (Tabarelli and Peres, 2002; Bongers et al., 2009; Tabarelli et al., 2010; Magnago et al., 2014): seed dispersal type and seed size (reproductive traits), ecological strategy, and wood density. The dispersal type was categorized as zoochorous and nonzoochorous following Van der Pijl (1982). Species that could not be classified in these two groups were labelled “unclassified”. A zoochoric species produces diaspores surrounded by fleshy pulp, a fleshy appendage of the seed (aril) or has other features that are typically associated with dispersal by frugivorous animals, and a non-zoochoric species has characteristics that indicate dispersal by abiotic means, such as winged seeds, feathers, or a lack of features that indicate dispersal via methods other than gravity or explosive indehiscence (Magnago et al., 2014). Data for seed size was obtained through literature review. Species were classified into three ecological strategies (pioneer, 3

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data (Colwell et al., 2012). We treat each site as a sampling unit, record only species incidence (presence/absence) in each site, and pool species incidences to obtain the count of occurrences of each species among sites (“species incidence-based frequency/abundance”). We also treat the number of occurrences among multiple sites of each species as a proxy of its abundance (Chao et al., 2014). Taxonomic and functional metrics were used to: (i) identify beta diversity patterns at species level and (ii) indirectly understand the ecological processes and ecosystem functioning (e.g., plant-animal interactions; Galetti et al. (2013) and carbon stock; Brancalion et al. (2018)). We separately analyzed these metrics for the two vegetation strata. For restoration plantings, established woody plants reflect the initial planting, whereas woody regenerating strata reflect successional process as affected by species immigration or recruitment from fruiting planted trees. For forest fragments, established woody plants show the outcomes of initial colonization, while woody seedlings and saplings indicate the regenerating potential along the successional process in agricultural landscapes.

number of sites involved in computing beta diversity) in order to evaluate the hypothesis that taxonomic and functional beta diversity will increase when all sites are analyzed together. A statistical method for extrapolation of taxonomic and functional beta diversity is still not available. There are two major approaches to evaluate beta diversity: (i) the variance framework, derived from the total variance of species abundances (Legendre and De Cáceres, 2013), and (ii) diversity decomposition based on partitioning gamma diversity into alpha and beta components. Chao and Chiu (2016) recently bridged the above two major beta approaches by showing that both converge to the same classes of (dis)similarity measures. Based on species relative incidence probabilities, we considered the rarefaction for the two convergent dissimilarity measures, which are monotonic functions of beta diversities: (i) a class of Sørensen-type species-dissimilarity measures: 1-CqN (average proportion of non-shared species in a site), and (ii) a class of Jaccard-type species-dissimilarity measures: 1-UqN 1-UqN (effective proportion of non-shared species in the pooled site).

(a) Rarefaction/extrapolation for within-site alpha diversity

(c) Rarefaction for functional beta diversity

Hill numbers (effective number of species) are increasingly used for quantifying species diversity based on species relative abundances (Hsieh et al., 2016). Chao et al. (2014) formulated multiple incidencedata version of Hill numbers based on species relative incidence probabilities/rates; see Supporting Information for model formulation and mathematical formulas. The incidence-based Hill numbers are also parameterized by a diversity order q, which determines the measures’ sensitivity to species relative incidence probabilities. These incidencebased Hill numbers include three species diversity measures as special cases: Species richness (q = 0), Shannon diversity (q = 1) and Simpson diversity (q = 2); the latter two measures are computed from species relative incidence probabilities. In what follows, Hill numbers refer to the version based on multiple incidence data. Since each site is treated as a sampling unit, sample size refers to the number of sampling units (or sites). In assessing the species diversity patterns of the three types of areas (fragment, restoration planting, or all together), we first compared for each type of area Hill numbers (within-site alpha diversity) based on multiple incidence data. Chao et al. (2014) extended the conventional rarefaction/extrapolation methods for species richness to Hill numbers. We mainly focus on comparing equally large samples (i.e., standardizing the number of sites) because the two standardization methods yield generally similar patterns. For each type of area, we used the iNEXT software (Hsieh et al., 2016) separately for established and regenerating plants to obtain the sample-size-based rarefaction/extrapolation sampling curves along with 95% confidence intervals for q = 0, 1 and 2.

Based on species relative incidence probabilities and species pairwise Gower distance between calculated from species traits, Chiu and Chao (2014), and Chao et al. (2014) extended the above two classes of species dissimilarity measures to their functional version. These functional dissimilarity measures can be adapted to our multiple incidence data. As with taxonomic beta diversity, we consider rarefaction of the functional version of the Sørensen-type and Jaccard-type functional-dissimilarity measures based on four species traits described earlier. Both Jaccard and Sorensen-type dissimilarity measures for taxonomic and functional data revealed consistent patterns, so we present the Jaccard index in the main text and the Sørensen in Supporting Information (Appendix S5: Fig. S1 and Appendix S6: Fig. S2).

3. Results 3.1. Overview on plant species community Considering the 32 areas we recorded 5990 established woody plants belonging to 342 species (gamma diversity) across 3.2 ha (320 plots). Forest fragments and restoration plantings shared 83 species; 66 occurred exclusively in restoration plantings and 193 were found exclusively in fragments. For regenerating plants, we recorded a total of 14,468 individuals belonging to 389 species (gamma diversity) recorded in 0.8 ha (320 subplots). For the regenerating strata, forest fragments and restoration plantings shared 104 species, with 55 exclusives for restoration plantings and 230 for fragments. Alpha diversity for established plants varied from 24 to 65 species for fragments, and from 16 to 50 for restoration plantings. For regenerating plants, alpha diversity varied from 33 to 114 species for fragments and from 14 to 43 species for restoration plantings. Separate data for each condition and stratum is presented in Table 1 and diversity data for each area and stratum are available in Appendix S2: Table S2 and Appendix S3: Table S3.

(b) Rarefaction for among-site taxonomic beta diversity Like alpha diversity, beta diversity also depends on sample size. Beta diversity measures the extent of difference in species composition among sites. Thus, beta diversity depends on how many sites are involved in computing the differences. Using the same idea of rarefaction for alpha diversity, here we also rarefied the data (by standardizing the

Table 1 Descriptive data for woody plants from forest fragments and restoration plantings of an Atlantic Forest-Cerrado ecotone in southeastern Brazil. Area

Size-class

Total abundance

Total incidence

Observed species richness

Estimated species richness (Chao2)

Fragments

Established Regenerating Established Regenerating

3953 10,685 2037 3783

928 1306 476 411

276 334 149 159

388.891 457.836 212.390 244.224

Restoration plantings

4

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higher proportional abundance of understory non-pioneer species (z = −4.306; p = 0.0001) compared to established plants. However, non-pioneer canopy species reduced their proportional abundance in regenerating stratum (z = −5.508; p = 0.0001) (Fig. 4b). 3.4. Taxonomic beta diversity across sites and regional scales As we initially hypothesized, taxonomic beta diversity (and dissimilarity) was higher for all sites combined (forest fragments and restoration plantings) in comparison to only forest fragments or only restoration plantings (Fig. 5). For established plants, beta diversity values showed the following ordering: All > Fragments > Restoration plantings (Fig. 5a). For regenerating plants, if species incidence-based frequencies are considered (q = 1 and q = 2), beta diversity followed the order All > Restoration plantings > Fragments. For q = 0 (incidence-based frequencies are not considered) beta diversity was: All ~ Restoration plantings > Fragments (Fig. 5b). Species composition of seedlings and saplings varied more among restoration plantings than among fragments.

Fig. 2. Dominance-diversity curve of woody species community sampled in 32 sites (18 fragments - green line, 14 restoration plantings – blue line, and 32 combined areas – magenta line) and two strata (established and regenerating plantings) in southeastern Brazil. The X-axis ranks each plant species in order from most to least abundant. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

3.5. Functional beta diversity change

3.2. Species dominance, richness, and alpha diversity

All functional dissimilarity patterns among sites were similar to those for species dissimilarity, with some differences in magnitude (Fig. 6). For established plants, functional beta diversity showed the following ordering: All > Fragments > Restoration plantings (Fig. 6a). For regenerating plants, if species incidence-based frequencies are considered (q = 1 and q = 2), functional beta diversity followed the order All > Restoration plantings > Fragments (Fig. 6b). However, for q = 0 (rare species are emphasized), we have ‘All sites combined’ showing similar functional beta diversity to Restoration plantings and these two conditions with higher functional beta diversity than the Fragments: All ~ Restoration plantings > Fragments (Fig. 6a and 6b). Functional traits of seedlings and saplings were more different among restoration plantings than among fragments.

Contrasting patterns of species richness are clearly displayed for the woody plant communities in the dominance-diversity curves for conditions and strata (Fig. 2). The dominance-diversity curve that represents the regenerating plants in the fragments covers a greater width, indicating a greater richness than the regenerating plants in restoration plantings and than the established plants both in fragments and restoration plantings. That difference is also noted by the difference in the length of the tails of each curve. The shape of the curves highlights differences in evenness amongst communities. Steep curves for established and regenerating plants in restoration plantings signify communities with high dominance of a few species (Fig. 2). The rarefaction/extrapolation sampling curves for multiple incidence-based frequency data for established plants and regenerating plants for species diversity for order q = 0 (Species richness), q = 1 (Shannon), and q = 2 (Simpson) are shown in Fig. 3. Standardizing for the number of sites, fragments and all areas combined show similar patterns of species diversity and significantly higher species diversity than the restoration plantings (Fig. 3a and 3b, respectively). These trends were consistent across all three Hill numbers.

4. Discussion Considering the current concerns about ecosystem resilience to large-scale anthropogenic impacts (Nimmo et al., 2015; ArroyoRodríguez et al., 2017), our study shows for the first time that restoration plantings can contribute to increase the conservation of taxonomic and functional beta diversity in highly fragmented landscapes. Results demonstrate the importance of establishing restoration plans that focus on planting a diversity of species selected from the region. For functional composition, some groups were significantly underrepresented among trees and shrub species used to restore areas (e.g., large-seeded, zoochoric and understory species) and this was consistent for the regenerating stratum. Although functional groups and species deficits are expected to be compensated throughout the process of natural regeneration, our sites are still at early stages of ecological succession. Small-seeded, non-animal dispersed and pioneer species were the most abundant groups occurring in restoration plantings, but non-pioneer species typically found in the understory had a considerable increment in the regenerating strata (Fig. 4a and b), maybe as a result of the seeds dispersed from both the surrounding forests and the local species already in reproductive age in the restoration plantings. Our results show the clear importance of restoration plantings for increasing plant beta diversity in fragmented landscapes via reintroduction of native species, but these plantings still lacked functional groups of threatened species (e.g., high wood density, large-seeded, animal dispersed and non-pioneer species), which can compromise the provision of ecosystem services (Brancalion et al., 2018). These findings reinforce, for example, the strong impact of species selection on genetic diversity (Zucchi et al., 2018), carbon stock (Brancalion et al., 2018) and plant-animal interactions (Galetti et al., 2013).

3.3. Functional traits The CWM revealed that all functional trait values varied significantly between fragments and restoration plantings for both established (Fig. 4a) and regenerating plants (Fig. 4b). For established plants we found that restoration plantings, when compared to fragments, showed a lower proportional abundance of species with higher wood density values (t = −2.146; p = 0.0401), seed length (t = −2.269; p = 0.0306), non-pioneer canopy (z = −5.725; p = 0.0001), understory non-pioneer (z = −7.926; p = 0.0001) and zoochoric species (z = −4.019; p = 0.0001). Restoration plantings showed higher mean values of exotic (z = 2.0868; p = 0.0001), pioneer (z = 10.07; p = 0.0001), and non-zoochoric (z = 4.008; p = 0.0001) species abundance (Fig. 4a). The regenerating strata show patterns similar to established species (Fig. 4b). Restoration plantings have lower wood density mean values (t = −3.267; p = 0.003), lower seed length (t = −3.386; p = 0.002) and lower incidence of zoochory (z = −3.610; p = 0.0001) compared to fragments. Also, the exotic (z = 2.218; p = 0.03), pioneer (z = 6.275; p = 0.0001) and non-zoochoric (z = 3.610; p = 0.0001) species increased their proportional abundance in restoration plantings compared to fragments. Comparing strata of restoration plantings, regenerating plants have 5

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Fig. 3. Sample-size-based rarefaction (solid line) and extrapolation (dotted line) for established plants (A) and regenerating plants (B) based on multiple incidence frequency data (the count of occurrences of each species among sites) for species diversity of q = 0 (species richness), q = 1 (Shannon diversity) and q = 2 (Simpson diversity) with 95% confidence intervals (shaded areas); Each X-axis denotes the number of sampling units (sites). All extrapolations are extended to double sample size.

and lack of seed supply and qualified labor (da Silva et al., 2017). Planning and executing ecological restoration actions in agricultural landscapes is a challenging task that requires improved policies and protocols to attend high-diversity forest ecosystem patterns (Rodrigues et al., 2009; Chaves et al., 2015; Costa et al., 2016; da Silva et al., 2017). For established plants, taxonomic and functional beta diversity were higher in fragments than in restoration plantings, but the opposite was observed for regenerating plants. This result reflects that establishment of restoration plantings using the same techniques and similar woody

Despite the legal instruments and efforts to ensure higher diversity in restoration plantings in Brazil, specifically in Sao Paulo state (Brancalion et al., 2010), species alpha diversity was consistently lower in restoration plantings than in forest fragments. Some studies have shown that alpha diversity of young restoration plantings (5 to 7 yearsold) is still much lower than that found in natural forests (Costa et al., 2016). This limitation may be due to the restricted availability of native species in seedling nurseries. The low potential of nurseries to provide a higher fraction of local tree flora can be attributed to the nurseries’ clustered distribution on the territory, underused production capacity, 6

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Fig. 4. Community-Level Weighted Means (CWM) of each functional trait for stratum (established (A) and regenerating plants (B)) and forest type (fragments and restoration plantings).

among fragments for the established stratum. Although age and local conditions (e.g., soil and light characteristics) have not been evaluated, the results for regenerating plants in restoration plantings suggest that those variables are important drivers of the compositional differentiation of woody plant assemblages, as previously observed for plant communities in grasslands (Stuble et al., 2017), and tropical forests (Meli et al., 2017; Suganuma et al., 2017). Variation in conditions across sites is reported as an important determinant of community assembly, producing a marked spatial and temporal variation in restoration outcomes (Stuble et al., 2017;

species composition, whereas natural regeneration showed more variable patterns in plant colonization. Forest fragments, in turn, are older and structurally more complex than restoration plantings, and still preserve some old long-lived species that became rare in the current fragmented agricultural landscapes, due to selective logging, deforestation and fires (Melo et al., 2013). Such species are expected to exhibit a time-lag in their biological responses to landscape changes due to their longevity (Metzger et al., 2009), and thus, rare large-seeded and non-pioneer individuals that persisted in the remaining forests after the disturbances may increase taxonomic and functional beta diversity 7

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Fig. 5. Rarefaction curves of the Jaccard-type species dissimilarity measure for a standardized number of sites based on multiple incidence frequencies data (the count of occurrences of each species among sites) for established (A) and regenerating plants (B). The X-axis denotes the number of sites.

landscapes in tropical regions is a challenge and will require a balance between conservation and production to encourage landowners. This encouragement could be possible by strengthening rural technical assistance agencies to assist landowners to comply with the local environmental laws, and by mechanisms to develop the productive chain of seeds and seedlings for the recovery of native vegetation (Brancalion et al., 2016).

Suganuma et al., 2017). The observed divergence in regeneration community of restoration plantings reinforce that direct species responses to local conditions can influence germination, emergence, establishment and survival (Classen et al., 2010). Moreover, indirect responses mediated by interspecific interactions can also be important drivers of site and age effects (Stuble et al., 2017). Effects of recent environmental changes on woody species are expected to be more evident in the community of the regenerating stratum (Rigueira et al., 2013; Benchimol et al., 2017), as seedlings and saplings are more sensitive to recent disturbances than established long-lived plants. The higher taxonomic and functional beta diversity for regenerating plants among restoration sites compared to forest fragments when rare species are emphasized could be driven by greater heterogeneity in understory environmental conditions among the restoration plantings and to differences in proximity to forest fragments. This result highlights the importance of each restoration planting of the surrounding landscape for the conservation and maintenance of the regional species pool and the need to include species that are missing from the landscape in the restoration plans. Restoration efforts may substantially contribute to improve the biodiversity at different scales and represents a great opportunity to reintroduce locally extinct species, and threatened populations with particular functional traits in agricultural regions, where forest cover has been severely reduced. However, the effective restoration in such

5. Conclusions We found higher beta diversity when restoration plantings were included in the landscape analysis if compared with diversity of forest fragments alone. This outcome highlights the positive effect of restoration initiatives on landscape woody plant diversity and functions in heavily agricultural regions with low native vegetation cover. At local scale, however, is not expected that restoration plantings will recover completely in terms of local diversity, but they can complement the diversity of forest fragments if (1) there is sufficient time for ecological succession, and (2) species selection for restoration plantings is well-planned in the beginning of the project. Based on our findings, there is an urgent need to maintain the complex network of biodiversity refuges, including the remaining forests, the regenerating forests, and the restoration plantings to conserve plant communities in humanmodified landscapes. As the compliance with Native Vegetation 8

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Fig. 6. Rarefaction curves of the Jaccard-type functional dissimilarity measure for a standardized number of sites based on multiple incidence frequency data (the count of occurrences of each species among sites) for established (A) and regenerating plants (B). The X-axis denotes the number of sites.

Brazil (CAPES) (#88881.064976/2014-01) to RLC and (#88882.305844/2018-01) to DCR. This project was part of a multidisciplinary study on tropical restoration coordinated by RRR (FAPESP #2013/50718-5).

Protection Law is the major driver of large-scale ecosystem restoration and conservation on privately owned lands in Brazil (Garcia et al., 2013), our study emphasizes the important role of agricultural landowners in maintaining and protecting natural vegetation, due to their irreplaceable value to conservation, in their lands and restoring areas illegally cleared in order to obtain concrete benefits for conservation in degraded landscapes. The characterization of diversity promoted by restoration plans implemented at different scales has important implications for the conservation in deeply degraded landscapes. The recovery of floristic and functional diversity is an essential indicator of restoration success and can be of great utility for future management plans aiming to conserve species populations, community, ecological processes and ecosystem functioning.

Appendix A. Supplementary material Supplementary data to this article can be found online at https:// doi.org/10.1016/j.foreco.2019.117538. References Alvares, C.A., Stape, J.L., Sentelhas, P.C., Gonçalves, J.L.M., Sparovek, G., 2013. Koppen’s climate classification map for Brazil. Meteorologische Zeitschrift 22, 711–728. https://doi.org/10.1127/0941-2948/2013/0507. APG III, 2009. An update of the Angiosperm Phylogeny Group classification for the orders and families of flowering plants: APG III. Bot. J. Linn. Soc. 161, 105–121. Arroyo-Rodríguez, V., Melo, F.P.L., Martínez-Ramos, M., Bongers, F., Chazdon, R.L., Meave, J.A., Norden, N., Santos, B.A., Leal, I.R., Tabarelli, M., 2017. Multiple successional pathways in human-modified tropical landscapes: new insights from forest succession, forest fragmentation and landscape ecology research. Biol. Rev. 92, 326–340. https://doi.org/10.1111/brv.12231/full. Arroyo-Rodríguez, V., Rös, M., Escobar, F., Melo, F.P.L., Santos, B.A., Tabarelli, M., Chazdon, R., 2013. Plant β-diversity in fragmented rain forests: testing floristic homogenization and differentiation hypotheses. J. Ecol. 101, 1449–1458. https:// doi.org/10.1111/1365-2745.12153. Audino, L.D., Murphy, S., Zambaldi, L., Louzada, J., Comita, L., 2017. Drivers of community assembly in tropical forest restoration sites: role of local environment,

Acknowledgements We are grateful to Ismael Ferreira Rodrigues and Marcos Trigo for data collection permission and logistical support. We also thank Evandro H. de Oliveira, Nathan R. Guedes, Reniê Michel Dutra and all laboratory colleagues for field assistance over the years. The authors received research grants and fellowships from the São Paulo Research Foundation (FAPESP) (#2012/24118-8) to DCR, from the National Council for Scientific and Technological Development to APL and from the Coordination for the Improvement of Higher Education Personnel of 9

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