draft - university of toronto t-space49 populations (paludo et al. 2016), predict impacts of...

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Spatial genetic structure, population dynamics and spatial

patterns in the distribution of Ocotea catharinensis Mez. from southern Brazil: implications for conservation

Journal: Canadian Journal of Forest Research

Manuscript ID cjfr-2017-0446.R1

Manuscript Type: Article

Date Submitted by the Author: 05-Feb-2018

Complete List of Authors: Montagna, Tiago; Universidade Federal de Santa Catarina, Fitotecnia Lauterjung, Miguel; Universidade Federal de Santa Catarina, Fitotecnia Candido-Ribeiro, Rafael; Universidade Federal de Santa Catarina, Fitotecnia Silva, Juliano; Universidade Federal de Santa Catarina, Fitotecnia Hoeltgebaum, Marcia; Universidade Federal de Santa Catarina, Fitotecnia Costa, Newton; Universidade Federal de Santa Catarina, Fitotecnia Bernardi, Alison; Universidade Federal de Santa Catarina, Fitotecnia Reis, Maurício; Universidade Federal de Santa Catarina, Fitotecnia

Keyword: Atlantic Rainforest, fine-scale spatial genetic structure, genetic diversity, neighborhood size, seed collection

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Canadian Journal of Forest Research

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1

ϯCurrent affiliation: Department of Forest and Conservation Sciences, University of British

Columbia, Vancouver, BC, Canada.

Spatial genetic structure, population dynamics and spatial patterns in the distribution of 1

Ocotea catharinensis Mez. from southern Brazil: implications for conservation 2

3

Tiago Montagna1, Miguel Busarello Lauterjung

2, Rafael Candido-Ribeiro

3ϯ, Juliano Zago 4

da Silva4, Marcia Patricia Hoeltgebaum

5, Newton Clóvis Freitas da Costa

6, Alison Paulo 5

Bernardi7, Maurício Sedrez dos Reis

8. 6

7

Affiliation and address of all authors: Núcleo de Pesquisas em Florestas Tropicais, Pós-8

Graduação em Recursos Genéticos Vegetais, Centro de Ciências Agrárias, Universidade 9

Federal de Santa Catarina. Rodovia Admar Gonzaga, 1346. Florianópolis, Santa Catarina, 10

Brazil. 11

12

E-mail adresses of all authors: [email protected],

[email protected], 13

[email protected],

[email protected],

[email protected], 14

[email protected],

[email protected],

[email protected] 15

16

Corresponding author: Tiago Montagna. Address: Rodovia Admar Gonzaga, 1346. 17

Florianópolis, Santa Catarina, Brazil. Telephone/Fax: +55 48 3721 5322. E-mail: 18

[email protected]. ORCID: 0000-0002-7427-4237 19

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Abstract 20

In this study, we employ an integrated demographic/genetic approach with the aim of 21

informing efforts to conserve Ocotea catharinensis, an endangered tree species from the 22

Brazilian Atlantic Rainforest. After establishing two permanent plots (15 and 15.5 ha) 23

within Protected Areas in Santa Catarina state, Brazil, we evaluated demographic aspects 24

(density, recruitment, mortality and growth), spatial pattern, genetic diversity and spatial 25

genetic structure (SGS) in three categories of individuals (seedlings, juveniles and 26

reproductive) over two years. Studied populations presented low recruitment of individuals 27

and low rates of increment in diameter and height. Aggregation was the main spatial pattern 28

observed for both populations. High levels of genetic diversity were estimated for both 29

populations, but also high levels of fixation index, signaling the risk of losing genetic 30

diversity over generations. Significant SGS was found for both populations, reflecting 31

nonrandom distribution of the genotypes. Demographic and genetic surveys also allowed 32

the estimation of minimum viable areas for genetic conservation (> 170 ha), deme sizes 33

(around 10 ha) and distances for seed collection (at least 60 m). Effective population size is 34

restricted in studied populations, locally threatening the species perpetuation over 35

generations. Further research can clarify how this condition it will change in subsequent 36

years. 37

38

Keywords: Atlantic Rainforest, fine-scale spatial genetic structure, genetic diversity, 39

neighborhood size, seed collection 40

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Introduction 41

Demographic and genetic studies are basic and powerful tools to understand 42

dynamic processes at the population level and their maintenance over time (Griffith et al. 43

2016, Lowe et al. 2017). Population structure can be described in terms of the ages, sizes, 44

and forms of the individuals that composes it, and population structure is susceptible to 45

environmental conditions and dynamic processes, such as recruitment, mortality and 46

growth rates, as well as intra- and interspecific competition (Harper and White 1974). 47

Therefore, demographic studies can help us predict decline, stability or expansion in 48

populations (Paludo et al. 2016), predict impacts of management practices on the structure 49

of populations (Ribeiro et al. 2014), and unravel environmental and ecological aspects that 50

determine demographic parameters and spatial patterns of distribution (Lara-Romero et al. 51

2016). 52

Genetic structure, in turn, results from the spatial nonrandom distribution of 53

genotypes in space (Vekemans and Hardy 2004). At a more restricted scale (e.g., within a 54

population), genetic structure largely arises from the formation of local pedigrees caused by 55

limited gene flow (Vekemans and Hardy 2004). Life history traits, such as regeneration 56

mode (e.g., sprouting or non-sprouting species), plus coarse- and fine-scale disturbances 57

(e.g., gaps, fires, landslides) and particular conditions for seedling establishment can also 58

lead to genetic structuring (Mathiasen and Premoli 2013). Genetic structure within a 59

population is commonly known as spatial genetic structure (SGS), or fine-scale spatial 60

genetic structure. Studies of SGS and its causes have provided fundamental guidelines for 61

plant conservation and actions, e.g., minimum distances required for seed collections 62

(Tarazi et al. 2010), associations between habitat fragmentation and SGS (Santos et al. 63

2016), and estimates of neighborhood sizes (Buzatti et al. 2012). By using information 64

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gained from both demographic and genetic studies, we might be able to propose feasible 65

management and conservation strategies for plant species. 66

Ocotea catharinensis Mez. is a tree species that occurs in the Brazilian Atlantic 67

Rainforest (AR) between latitudes 19°57' S (Saiter and Thomaz 2014) and 30°15' S 68

(Carvalho 1994). This species was considered the most abundant and dominant tree in the 69

upper stratum of Ombrophilous Dense Forest, a forest formation of the AR (Veloso and 70

Klein 1959, Klein 1980) in southern Brazil. However, the intensive exploitation of O. 71

catharinensis to produce timber, combined with the high fragmentation of AR (Ribeiro et 72

al. 2009, Vibrans et al. 2012), led to the placement of this species on the Brazilian List of 73

Endangered Plant Species (MMA 2014). The species is also classified as vulnerable by the 74

IUCN Red List (Varty and Guadagnin 1998). 75

Currently, the species occurs at an average density of 5.86 individuals/ha (diameter 76

at breast height – dbh > 10 cm) in remnants of Ombrophilous Dense Forest in Santa 77

Catarina state (SC) (Lingner et al. 2013). However, in the past, higher densities were 78

recorded, ranging from 23.9 individuals/ha (dbh > 12.7 cm) (Veloso and Klein 1959) up to 79

20 to 50 reproductive individuals/ha (Reitz et al. 1978). Densities of 200 up to 600 80

individuals/ha higher than 1 m were also reported for SC (Reitz et al. 1978). These major 81

differences between past and present densities call for studies to support conservation 82

efforts regarding O. catharinensis. 83

Indeed, studies reporting on the demographic aspects of O. catharinensis have 84

already been carried out (Veloso and Klein 1959, Tarazi et al. 2010, Lingner et al. 2013). 85

Nevertheless, such studies have neither covered seedling densities nor focused on 86

population dynamics (e.g., growth rates, mortality and recruitment). Ocotea catharinensis 87

presents an aggregated spatial pattern (Tarazi et al. 2010); however, not only is the extent 88

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of this aggregation unknown, but also possible variations in the extent and the intensity of 89

the spatial pattern between different categories of individuals (e.g., seedlings, juveniles or 90

reproductive). High levels of genetic diversity, low to moderate levels of fixation index, 91

and moderate genetic divergence are reported for O. catharinensis populations (Tarazi et al. 92

2010, Martins et al. 2015). Furthermore, significant SGS within the populations of O. 93

catharinensis have already been detected (Tarazi et al. 2010). So far, however, genetic 94

diversity and SGS within different categories of individuals are poorly understood. 95

In this study, we described the population dynamics, spatial pattern and SGS of 96

three categories of O. catharinensis individuals (seedlings, juveniles, and reproductive) 97

from two populations in SC, southern Brazil. We asked i) how the demographic structure 98

varies over the years, ii) how individuals are spatially distributed, and iii) what is the 99

magnitude of SGS in those populations. This study aimed to provide useful knowledge for 100

O. catharinensis in situ conservation. 101

102

Material and methods 103

Study areas and plots 104

This study was conducted in two protected areas in SC: Parque Nacional da Serra 105

do Itajaí (Serra do Itajaí National Park: PNSI – 57,374 ha) and Floresta Nacional de 106

Ibirama (Ibirama National Forest: FNI – 570 ha) (Figure 1). Vegetation in the study areas 107

is classified as Ombrophilous Dense Forest (ODF), and the climate is described as 108

subtropical humid (Cfa), according to Köeppen’s classification. Although currently 109

protected, both areas have previously been subjected to anthropogenic activities at different 110

levels of intensity. For example, selective logging of O. catharinensis was reported for FNI 111

in the 1950s (MMA 2008) and until 1990 for PNSI (MMA 2009). Hunting and illegal 112

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exploitation of other key plant species were also reported for both areas (MMA 2008, 113

2009), and these activities remain a problem (personal observation). 114

In order to collect demographic and genetic data, two permanent plots were 115

established: a 15 ha plot (250 m x 600 m) in PNSI and a 15.5 ha plot (350 m x 430 m) in 116

FNI. Two smaller plots subdivided into 10 m x 10 m subplots were installed in the center of 117

the bigger plots (15 and 15.5 ha). These smaller plots comprised 1.9 ha in PNSI (100 m x 118

190 m) and 1.68 ha in FNI (120 m x 140 m) (Figure 1). The sampled area in PNSI has an 119

average elevation of 410 m, and vegetation varies from the middle stage of secondary 120

succession on hilltops to the advanced stage on hillsides (MMA 2009). The sampled area in 121

FNI has an average elevation of 350 m and vegetation in the advanced stage of secondary 122

succession (MMA 2008). 123

124

Demographic characterization 125

For demographic characterization, Ocotea catharinensis individuals were classified 126

as i) seedlings, i.e., individuals without measurable diameter at breast height (dbh – 1.3 m); 127

ii) juveniles, i.e., individuals with measurable dbh at 1.3 m up to 20 cm dbh; and iii) 128

potentially reproductive (hereinafter, reproductive), i.e., individuals with dbh higher than 129

20 cm. We assessed seedling and juvenile individuals only in the smaller plots and the 130

reproductive individuals in both smaller and bigger plots. We measured the height of 131

seedlings and juveniles (up to 5 m) and the dbh of juveniles and reproductive individuals 132

over two years, 2015 and 2016 in PNSI and 2016 and 2017 in FNI. Additionally, we 133

evaluated individuals’ mortality, recruitment, density and increment (height and dbh). 134

Spatial position of each individual was obtained by xy coordinate system in each of the 135

smaller plots and with GPS (Garmin GPSmap 76CSx) outside the smaller plots. 136

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To visualize the demographic structures in each population, histograms were 137

constructed. The density of individuals was compared between study sites with a 138

confidence interval (95%) constructed through bootstrapping 1,000 times the density of 139

each category of individuals in each subplot (10 m x 10 m). Confidence intervals (95%) 140

were also constructed for the increment averages of height and dbh (bootstrap – 1,000 141

times). The increment values were obtained through two evaluations in each study site. The 142

confidence intervals were constructed in R language (R Development Core Team 2015). 143

144

Spatial pattern and spatial independence analysis 145

Spatial pattern was estimated for all categories of individuals and evaluated years in 146

PNSI and FNI, applying the standardized Ripley’s K function L(r) (Ripley 1981), as 147

implemented in the “spatstat” package (Baddeley and Turner 2005) in R language (R 148

Development Core Team 2015). Spatial independence between seedlings and reproductive 149

individuals was tested using the bivariate extension of Ripley’s K L12(r) (Lotwick and 150

Silverman 1982), as implemented in the “splancs” package (Rowlingson and Diggle 2015) 151

in R language (R Development Core Team 2015). For both analyses, we used a radius (r) of 152

1 m to estimate L(r) and L12(r), and the spatial pattern was evaluated up to half the smaller 153

dimension of the plots, or up to 50 m and 60 m for smaller PNSI and FNI plots (seedlings 154

and juveniles), respectively, and up to 175.5 m and 125 m for bigger PNSI and FNI plots 155

(reproductive), respectively. Deviations from Complete Spatial Randomness were tested 156

through a confidence interval (95%) obtained from 1,000 Monte Carlo simulations of 157

completely random events. 158

159

Genetic data acquisition and analysis 160

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At both study sites, fresh leaves were collected from all O. catharinensis individuals 161

occurring in the smaller plots plus all reproductive individuals occurring in the bigger plots. 162

Furthermore, individuals that recruited into seedling category were also sampled by the 163

second demographic evaluation (2016 in PNSI and 2017 in FNI). Genetic characterization 164

was performed using allozyme markers, wich have been widely used for several studies 165

reporting on population genetics, including SGS (Vekemans and Hardy 2004, Tarazi et al. 166

2010, Quipildor et al. 2017). Enzymes were extracted by macerating the leaf tissue for 15 167

seconds with an automatic homogenizer (6500 rotations per minute). 168

The following enzymatic systems were resolved in starch gel (Penetrose 30-13%), 169

using a Tris-Citrate pH 7.5 buffer (Tris 27 g.L-1 and citric acid 16.52 g.L-1) for 170

electrophoresis: aspartate transaminase (at, EC 2.6.1.1), diaphorase (dia, EC 1.8.1.4), 171

esterase (est – Enzyme Commission 3.1.1.1), glucose-6-phosphate dehydrogenase (g6pdh, 172

EC 1.1.1.49), glutamate dehydrogenase (gtdh, EC 1.4.1.2), isocitrate dehydrogenase (idh, 173

EC 1.1.1.42), malic enzyme (me, EC 1.1.1.40), malate dehydrogenase (mdh, EC 1.1.1.37) 174

and phosphoglucomutase (pgm, EC 5.4.2.2). 175

In order to characterize the genetic diversity of populations and their categories, we 176

estimated the following indexes: percentage of polymorphic loci (��), total number of 177

alleles (��), average number of alleles per locus (��), average number of effective alleles per 178

locus (�� = 1/(1 − � �)), observed (� �) and expected heterozygosity (� �) and fixation 179

index (��). Effective population size (� � – the size of an idealized population that would 180

have the same amount of inbreeding as the population under consideration – Kimura and 181

Crow (1963)) was estimated following the equation proposed by Li (1976): � � = �/(1 +182

��), where � is the number of sampled individuals. Statistical significance (p < 0.05) for �� 183

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values was obtained through 1,000 permutations of alleles among individuals. All analyses 184

were carried out in FSTAT software, version 2.9.3.2 (Goudet 2002), except for �� and � �. 185

Based on the � �, we estimated the minimum viable areas (��) for long-term 186

genetic conservation, as follows: �� = ��(��)/(� �/�. �), where ��(��) is a reference 187

value of 1,000 individuals, which was proposed by Lynch (1996) as sufficient to mitigate 188

the effects of deleterious mutations, n is the sample size, and � is the density of 189

reproductive individuals in each population. These estimates were made by taking into 190

account only reproductive individuals in the last year of evaluation in each population 191

(PNSI = 2016 and FNI = 2017). 192

Spatial genetic structure (SGS) for both populations and all categories was 193

estimated by performing an autocorrelation analysis using the coancestry coefficient (��), 194

as described in Loiselle et al. (1995). We established equal distance classes for both 195

populations (20 m) in order to facilitate comparisons, observing a minimum of 30 pairs of 196

observations in each class. To test the statistical significance of �� within each distance 197

class, a confidence interval (95%) was constructed by 10,000 permutations of individual 198

locations among all individuals. SGS analysis was performed using SPAGeDi software, 199

version 1.5 (Hardy and Vekemans 2002). 200

Neighborhood size (� – the effective population number in an area from which the 201

parents may be assumed to be drawn at random – Wright (1940)) for reproductive 202

individuals within each studied population was estimated as � = −(1 − �!)/"# 203

(Vekemans and Hardy 2004). In this formula, �! is the coancestry coefficient in the first 204

class of distance (0 – 20 m), and "# is the regression slope of the coancestry coefficient 205

value on the logarithm of spatial distance between individuals, but within plot distances, as 206

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follows: 0 up to 560 m in PNSI and 0 up to 480 m in FNI. � was estimated using 207

SPAGeDi, version 1.5 (Hardy and Vekemans 2002). Deme sizes (ha) were estimated for 208

each studied population based on � values, as in the following equation: �$�$%&'$ =209

� /�, where� is the density of reproductive individuals in each population. 210

211

Results 212

Population structure and dynamics 213

The populations presented similar densities of juveniles and reproductive 214

individuals, but PNSI presented statistically higher density of seedlings (Table 1). 215

Recruitments in the seedling category were recorded for both populations (PNSI = 5 216

individuals; FNI = 1 individual), as well as recruitment of seedlings into the juvenile 217

category (PNSI = 8 individuals; FNI = 11 individuals) (Table 1). Mortality was verified 218

only for seedlings from PNSI (9 individuals) (Table 1). Distribution of individuals per dbh 219

classes presented an inverted J-shaped form for both populations; however, PNSI showed a 220

gap of individuals in the 10 cm to 20 cm and 20 cm to 30 cm dbh classes (Figure 2). 221

Increment averages in height and dbh were similar between populations and 222

categories, except for seedlings from FNI, which showed statistically higher height 223

increment when compared to seedlings from PNSI (Table 2). All increment averages 224

presented high associated standard deviations (S), evidencing the heterogeneity of these 225

features in the studied populations (Table 2). 226

227

Spatial pattern and spatial dependence 228

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Aggregation, with different intensities and at different distances, was the main 229

spatial pattern observed in both studied populations and their categories (Figure 3). 230

Seedling individuals from PNSI presented aggregation from 0 m up to 50 m in 2015 and 231

2016. Juveniles were aggregated from ≈5 up to 50 m in 2015 and 2016, and reproductive 232

individuals presented aggregation from ≈5 up to 125 m (2015 and 2016) (Figure 3). In FNI, 233

seedlings presented an aggregated spatial pattern from 0 m up to 60 m in 2016 and from ≈5 234

m up to ≈18 m in 2017. Juveniles presented no aggregation in 2016, but aggregation from 0 235

m up to ≈8 m was recorded in 2017. Reproductive individuals were aggregated from ≈2 m 236

up to ≈75 m (2016 and 2017) (Figure 3). Aggregation intensity (L(r)) was higher for 237

individuals from PNSI when compared to FNI (Figure 3). Seedlings and juveniles from 238

PNSI and FNI presented spatial distribution independent of the spatial distribution of 239

reproductive individuals (Figure 4). 240

241

Genetic diversity 242

Between PNSI and FNI, 477 individuals were genotyped, and 21 different alleles 243

were recorded for both populations (Table 3). The number of individuals composing each 244

category followed the results of the demographic survey. For instance, seedlings that 245

recruited into the juvenile category (PNSI = 8 individuals; FNI = 11 individuals) were 246

analyzed as seedlings in the first year and as juveniles in the second year. Average number 247

of effective alleles per locus (��) represented about 70% of �� for both populations, 248

indicating the occurrence of common alleles on the assessed loci. Diversity indexes were 249

quite similar between years, categories and populations (Table 3). Significant deviations 250

from Hardy–Weinberg equilibrium were detected for seedlings and reproductive 251

individuals from PNSI and FNI, indicating deficit of heterozygotes (Table 3). Effective 252

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population size was around 13% smaller than sample sizes, reflecting the �� estimates. 253

Minimum viable areas, taking a reference size of 1,000 individuals (Lynch 1996), were 254

equal to 176 ha and 205 ha for PNSI and FNI, respectively. 255

256

Spatial genetic structure 257

Significant SGS was found for both studied populations. Seedlings from PNSI 258

presented positive and significant coancestry (��) values when separated by less than 40 m 259

in both evaluated years. Juveniles from PNSI did not show significant SGS, while 260

reproductive individuals from PNSI presented positive and significant �� values in the 261

first and third distance classes (0 – 20 m and 40 – 60 m) (Figure 5). For FNI, positive and 262

significant �� values were detected for seedlings (2016 and 2017) in the first distance class 263

(0 – 20 m). Juveniles also presented positive and significant �� values in the first distance 264

class (0 – 20 m), but only in 2017. For reproductive individuals, no significant SGS was 265

recorded (Figure 5). All significant and positive coancestry values ranged from 0.037 266

(PNSI seedlings in 2015) up to 0.073 (FNI seedlings in 2016). Negative and significant �� 267

values were verified for reproductive individuals in the distance class of 140 m to 160 m 268

and 180 m to 200 m in PNSI and FNI, respectively (Figure 5). 269

Neighborhood size estimates (� ) for reproductive individuals from PNSI and FNI 270

were equal to 44 and 48 individuals, respectively. Under the estimated densities of 271

reproductive individuals (Table 1), deme sizes were estimated to be 8.8 ha and 11.7 ha for 272

PNSI and FNI, correspondingly. 273

274

Discussion 275

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This is the first attempt to understand demographic and genetic aspects of O. 276

catharinensis over more than just one year. Nevertheless, it is important to keep in mind 277

that O. catharinensis is a long-lived species, well distributed across the Ombrophilous 278

Dense Forest. Moreover, all the presented results and the following discussions are based 279

on a two-year survey (genetic and demographic) in two populations. For that reasons, our 280

data and discussions should be interpreted considering the particularities mentioned. 281

282

Population structure and dynamics 283

Both studied populations presented densities of reproductive individuals (Table 1) 284

compatible with those of the most recent study. Ocotea catharinensis occurs at an average 285

density of 5.86 individuals/ha (dbh> 10 cm) in remnants of Ombrophilous Dense Forest in 286

SC (data from 197 sample units) (Lingner et al. 2013). Nevertheless, estimated densities for 287

both studied populations (Table 1) were found to be substantially lower than estimated 288

densities for O. catharinensis populations in the past. In SC, densities of 23.9 289

individuals/ha (dbh > 12.7 cm) were previously estimated in eight sample units (Veloso and 290

Klein 1959). Additionally, observations by Reitz et al. (1978) reported densities ranging 291

from 20 up to 50 reproductive individuals/ha and from 200 up to 600 individuals/ha higher 292

than 1 m. Such discrepancy between past (Veloso and Klein 1959, Reitz et al. 1978) and 293

present estimates (Tarazi et al. 2010, Lingner et al. 2013, Table 1) can be attributed to the 294

intensive exploitation of O. catharinensis for timber in the intervening years. Ocotea 295

catharinensis is considered one of the three most exploited timber species in the 296

Ombrophilous Dense Forest, supplying basically the national market (Reitz et al. 1978). 297

Recruitments into the seedling category occurred at lower intensity than mortality of 298

seedlings for the PNSI population, and for the FNI population, only one seedling individual 299

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was recruited (Table 1). Corroborating our results concerning increment rates (Table 2), O. 300

catharinensis is ranked as one of the three species with lowest growth rate among 100 tree 301

species from Brazil, as listed by Carvalho (1994). These results demonstrate that natural 302

reestablishment of past densities could be a slow process. For instance, at the estimated 303

average of dbh increment for juveniles from FNI (Table 2), an individual with dbh = 1 cm 304

could be expected to reach a dbh = 20 cm in about 126 years (95% confidence interval = 95 305

years – 211 years). 306

The distribution of individuals per dbh classes (Figure 2) presented an inverted J-307

shaped form for both populations, demonstrating that the studied populations still present 308

the potential for replacement of larger individuals, even with the low intensity of seedling 309

recruitment (Table 1). A gap of individuals was observed in the 10 cm to 20 cm and 20 cm 310

to 30 cm dbh classes for the PNSI population (Figure 2), owing to logging activities 311

reported for PNSI until 1990 (MMA 2009). Therefore, theses gaps may be the result of past 312

exploitation processes, reducing the regeneration capacity of the population by the 313

withdrawal of reproductive individuals. 314

315

Spatial pattern and spatial independence 316

Aggregated distribution pattern is predominant for tropical tree species, resulting 317

from heterogeneous environments (Condit et al. 2000). This aggregated distribution pattern 318

was also recorded for O. catharinensis (Tarazi et al. 2010) and O. porosa (Canalez et al. 319

2006). The studied populations presented mostly aggregated distribution, with the 320

exception of juveniles from FNI (Figure 3). In general, aggregation intensity (L(r)) was 321

higher for individuals from PNSI, suggesting higher environmental heterogeneity in this 322

study site when compared to FNI (Figure 3). As mentioned, the stage of secondary 323

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succession in the PNSI plot varies according to the elevation: middle stage on hilltops and 324

advanced stage on hillsides (MMA 2009), while in the FNI plot, the vegetation only 325

presents the advanced stage of secondary succession (MMA 2008). 326

Comparing both studied populations, it is possible to observe that spatial 327

distribution of seedlings and juveniles was affected by mortality and recruitment. Seedlings 328

from PNSI presented a more intense aggregation in 2016 than in 2015; on the other hand, 329

seedlings from FNI were aggregated from 0 m up to 60 m in 2016 and from ≈5 m up to ≈18 330

m in 2017 (Figure 3). Recruitment of seedlings into the next category caused a slight 331

decrease in the aggregation intensity of juveniles in PNSI. Nevertheless, the opposite result 332

can be seen for FNI juveniles, which were not aggregated in 2016 and presented 333

aggregation from 0 m up to ≈8 m in 2017 (Figure 3). 334

Spatial distribution of seedlings was independent of the spatial distribution of 335

reproductive individuals (Figure 4). Therefore, spatial distribution of seedlings is unlikely 336

to be associated to the barochory reported for O. catharinensis (Moraes and Paoli 1995). 337

The better germination of seeds in conditions of higher soil humidity (Moraes and Paoli 338

1999), combined with high rates of deteriorated seeds found under seed trees (Moraes and 339

Paoli 1995, 1999), indicating density-dependent recruitment, are factors that could better 340

explain the aggregation and spatial independence of seedlings. The action of fauna 341

dispersing seeds can also influence the spatial pattern and independence of seedlings. For 342

instance, Brachyteles arachnoides, one of the dispersers of O. catharinensis (Moraes and 343

Paoli 1995), presents two types of behavior when feeding on trees of Cryptocarya 344

moschata (Lauraceae): 1) feeding from only one seed tree, dispersing seeds in suitable 345

places for seedling recruitment (Moraes et al. 1999), which then favors aggregation and 346

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spatial independence and 2) feeding from several seed trees, dispersing seeds along the area 347

(Moraes et al. 1999), and then favoring random distribution. 348

A comparison of PNSI and FNI based on differences in spatial distribution between 349

juveniles and reproductive individuals (Figure 3) can be viewed as a reflection of the stage 350

of secondary succession of each study site. In the case of reproductive individuals, spatial 351

distribution can also be influenced by past logging activities reported for both populations 352

(MMA 2008, 2009). Nevertheless, it is a difficult task to evaluate such influence, 353

essentially because evidence of exploited individuals, such as rotten logs, has, of course, 354

long since vanished. 355

356

Genetic diversity 357

Tree species of the Lauraceae family apparently trend toward high levels of genetic 358

diversity (Chung et al. 2003, Tarazi et al. 2010, Reis et al. 2012, Martins et al. 2015). The 359

estimated genetic diversity (� �) for each population (PNSI = 0.222; FNI = 0.208) can also 360

be considered high when compared to average � � for long-lived perennial woody species 361

(0.149) (Hamrick and Godt 1989). This is an important result for the conservation of O. 362

catharinensis, highlighting the role of protected areas in the conservation of genetic 363

diversity of several species and demonstrating that PNSI and FNI populations present the 364

real potential for conservation. 365

Significant and positive deviations from Hardy-Weinberg equilibrium were also 366

recorded, on average, for other populations of O. catharinensis (Reis et al. 2012, Martins et 367

al. 2015) and for the congeneric species O. porosa and O. odorifera (Reis et al. 2012). 368

Nevertheless, significant excess of heterozygotes were also recorded for populations of O. 369

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catharinensis (Tarazi et al. 2010). Several factors can be influencing these divergences, 370

such as more or less intense historical exploitation of each evaluated fragment, SGS levels 371

in each population, which can affect genetic estimates (Jones and Hubbell 2006), biparental 372

inbreeding, and sampling strategies of each study. However, given a single reproduction 373

event under Hardy-Weinberg equilibrium, the expected fixation index of seedlings should 374

be zero for an outcrossing species (Hartl and Clark 2007). Ocotea catharinensis is 375

presumably an outcrossing species, presenting apparent outcrossing rate of 1.0 (Tarazi et al. 376

2010); however, aspects of its reproductive biology, such as mating system and pollination 377

ecology, are still not fully understood. Future studies to elucidate the reproductive system 378

of the species can clarify this question. 379

Positive and significant fixation indexes (��) estimates were recorded for 380

reproductive individuals from both studied populations, and these estimates resulted in 381

effective sizes (� �) reductions (Table 3). Based on � � and taking a reference size of 1,000 382

individuals (Lynch 1996), minimum viable area estimates (176 ha for PNSI and 205 ha for 383

FNI) were smaller than the total areas at the study sites (PNSI = 57,374 ha; FNI = 570 ha). 384

Thus, both study sites are able to conserve large populations, even larger than 1,000 385

individuals. Populations lose genetic diversity in a rate of 1/2�, where � is the number of 386

individuals (Wright 1931). Therefore, small populations will lose genetic diversity faster 387

than larger populations. This result demonstrates the potential importance of fragment size 388

in mitigating the effects of fixation indexes. 389

390

Spatial genetic structure 391

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Significant SGS has been reported for a number of tropical and neotropical tree 392

species (Hardy et al. 2006) and also for trees of the Lauraceae family, such as Cryptocarya 393

moschata (Moraes et al. 2004). Nevertheless, no significant SGS was observed for other 394

trees of Lauraceae, for instance, O. odorifera (Kageyama et al. 2003), and Cinnamomum 395

insularimontanum (Chung et al. 2003). These differences among species can be influenced 396

by environmental conditions, but also by aspects related to the reproductive biology and 397

gene flow of each species (Chung et al. 2003, Vekemans and Hardy 2004, Hardy et al. 398

2006). 399

Ocotea catharinensis presented significant SGS up to distances of 80 m (Tarazi et 400

al. 2010). Our SGS results for reproductive individuals differ from those found by Tarazi et 401

al. (2010). Reproductive individuals from FNI lack SGS, while reproductive individuals 402

from PNSI present significant SGS up to 60 m, except in the distance class from 20 m up to 403

40 m (Figure 5). These differences can be explained in several ways, i) methodological 404

approaches: our reproductive category included only individuals with dbh > 20 cm, while 405

Tarazi et al. (2010) sampled individuals with dbh > 6.85 cm; ii) environmental conditions 406

of each study site: this could, for example, include the presence (or absence) and abundance 407

of seed dispersers; and iii) historical exploitation of each study site: both PNSI and FNI 408

have undergone adverse logging activities (MMA 2008, 2009). Selective logging may 409

reduce the distance of the SGS for reproductive individuals, such as that observed for 410

Hymenaea courbaril (Lacerda et al. 2008). 411

Significant SGS up to 40 m for PNSI and up to 20 m for FNI was estimated for 412

seedlings (Figure 5). As discussed, spatial distribution of seedlings is independent of the 413

spatial distribution of reproductive individuals for both populations (Figure 4). Therefore, 414

barochory cannot explain the SGS of seedlings. Brachyteles arachnoides, one of the 415

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dispersers of O. catharinensis (Moraes and Paoli 1995), presented two types behavior when 416

feeding on the Lauraceae tree Cryptocarya moschata, as previously mentioned. Hence, the 417

preference for germination in conditions of higher soil humidity (Moraes and Paoli 1999), 418

the high rates of deteriorated seeds found under seed trees (Moraes and Paoli 1995, 1999), 419

and the behavior of seed dispersers are all factors that can explain the SGS of seedlings, 420

apart from barochory. 421

The mortality and recruitment of seedlings and juveniles resulted in slight changes 422

in SGS pattern of these categories in FNI (Figure 5). The recruitment of 11 seedlings into 423

the juvenile category in 2017 (Table 1) led to the appearance of significant SGS in the first 424

distance class for juveniles (0 – 20 m) and the reduction of SGS level in the first distance 425

class for seedlings (0 – 20 m) (Figure 5). The same trend was not observed for seedlings 426

and juveniles from PNSI, possibly because seedling density in this population is larger than 427

that in the FNI population (Table 1). Consequently, the processes of recruitment and 428

mortality represent only a small portion of total density. Increase in SGS in older cohorts 429

relative to younger cohorts can result from several factors, such as bottlenecks or founder 430

effects, local adaptation owing to microhabitat selection, limited dispersal, and more 431

overlapping generations in older cohorts compared to younger cohorts (Jones and Hubbell 432

2006). 433

Neighborhood size estimates (� ) (PNSI = 44 individuals and FNI = 48 individuals) 434

can be considered intermediate when compared to other estimates for the species (25 to 83 435

individuals – Tarazi et al (2010). Nevertheless, under the estimated densities of 436

reproductive individuals (Table 1), estimates of deme size in the present study (PNSI = 8.8 437

ha and FNI = 11.7 ha) were greater than those of Tarazi et al. (2010) at 5 to 6 ha. These 438

estimates can be interpreted as a minimum required area for conservation of a deme. 439

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440

Implications for conservation 441

Estimated population densities by the present study and other recent studies (Tarazi 442

et al. 2010, Lingner et al. 2013) are considerably lower than historical densities (Veloso and 443

Klein 1959, Reitz et al. 1978), reflecting the intensive timber exploitation. Furthermore, 444

results of our demographic survey revealed a low recruitment of new individuals into 445

populations, as well as low rates of increment in dbh and height. Therefore, the negative 446

effects caused by exploitation on the demographic aspects of this species may require a 447

protracted period of recovery. In this sense, it is important to continue studying population 448

dynamics of O. catharinensis, especially in order to better understand the factors 449

influencing the low recruitment of seedlings. Supra-annual seed production limited to a few 450

seed trees was observed for O. catharinensis (Silva et al. 2000), and this can be a factor 451

influencing the regenerative potential of the species. It is also important to continue 452

restricting exploitation of O. catharinensis in order to avoid further reductions in 453

population sizes. 454

As part of our integrative approach, the genetic survey returned valuable 455

information regarding conservation of genetic diversity. Large areas are imperative for 456

long-term conservation of the species – ideally greater than 170 ha, according to the 457

minimum viable areas estimated. Selecting large areas to conserve O. catharinensis 458

populations might present other advantages, such as high probability of the presence of 459

fauna, an important vector of seed dispersal, and high occurrence of adequate microhabitats 460

for seed germination and seedling establishment. Nevertheless, deme sizes were estimated 461

to be around 10 ha for both PNSI and FNI, signaling that small fragments can also be 462

important in the genetic conservation of O. catharinensis. It should be noted that AR is 463

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currently highly fragmented (Ribeiro et al. 2009, Vibrans et al. 2012), and in this sense, 464

small fragments can harbor rare and exclusive alleles, and could also serve as binding 465

elements between larger fragments. 466

Regarding ex situ conservation, SGS analysis revealed two important distances to be 467

respected in order to avoid collection of seeds from closely related individuals. In order to 468

minimize the probability of sampling closely related individuals, it is recommended to 469

sample seeds of individuals separated by at least 60 m for PNSI and 40 m for FNI. The FNI 470

population did not present significant SGS, but a tendency toward structuration up to 40 m 471

was observed (Figure 5). In order to maximize the capture of genetic diversity, seeds should 472

be sampled from seed trees separated by 140 m to 160 m in PNSI and 180 m to 200 m in 473

FNI. These ranges represent the distance at which reproductive individuals presented 474

negative and significant estimates of coancestry (Figure 5). Therefore, these are also ranges 475

where individuals are more genetically distinct. 476

The major differences between present and past estimates of density and the high 477

levels of fixation indexes for seedlings are signaling major restrictions of effective 478

population size, caused by the intense timber exploitation. This condition summed up with 479

the low rates of growth and recruitment can imply in loss of genetic diversity and 480

population dynamism over generations, therefore locally threatening the species 481

perpetuation. Thus, it is important to continuously monitor and study O. catharinensis 482

populations to verify whether this condition is unique to the studied populations and how it 483

will change in subsequent years. 484

Finally, the conclusions above were made possible through the integration of 485

demographic and genetic data and the evaluation of demographic and genetic aspects of 486

two O. catharinensis stands over a two-year period, highlighting the importance of such 487

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integrative approach for studies of endangered tree species. Although O. catharinensis is a 488

longevous species, this is the first attempt to understand its demographic and genetic 489

aspects in more than one year. 490

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Acknowledgements 491

We thank the Instituto Chico Mendes de Conservação da Biodiversidade (ICMBio) 492

and the researchers of Núcleo de Pesquisas em Florestas Tropicais for their support with the 493

fieldwork. We also thank the Laboratório de Fisiologia do Desenvolvimento e Genética 494

Vegetal for providing the necessary infrastructure required for the genetic analysis 495

performed in this work. This study was funded by the Fundação de Amparo à Pesquisa e 496

Inovação do Estado de Santa Catarina (FAPESC) (grant numbers 11939/2009, 18868/2011-497

9 and TR2013-3558), the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior 498

(CAPES) to TM, APB, MBL, NCFC and JZS, and the Conselho Nacional de 499

Desenvolvimento Científico e Tecnológico (CNPq) to MSR (304724/2010-6), MPH 500

(140386/2013-0) and RCR (130894/2015-0). 501

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Table 1. Demographic estimates in two populations of Ocotea catharinensis Mez. from the 674

Atlantic Rainforest, Santa Catarina, Brazil. 675

PNSI

category

individuals density recr dead nf

2015 2016 2015 2016 2016 2016 2016

seedlings 217 198 114.2 (90.5/142.6) 104.2 (81/131.1) 5 9 7

juveniles 59 67 31.1 (22.6/39.5) 35.3 (26.3/45.2) 8 0 0

reproductive 75 75 5 (3.8/6.2) 5 (3.8/6.2) 0 0 0

FNI

category

individuals density recr dead nf

2016 2017 2016 2017 2017 2017 2017

seedlings 51 41 30.4 (19/42.3) 24.4 (16.1/32.7) 1 0 0

juveniles 52 63 31 (22/39.9) 37.5 (27.4/48.2) 11 0 0

reproductive 63 63 4.1 (3.3/5.2) 4.1 (3.3/5.2) 0 0 0

Note: PNSI, Parque Nacional da Serra do Itajaí; FNI, Floresta Nacional de Ibirama; 676

individuals, total number of individuals in each category; density, number of individuals 677

per hectare in each category; recr, number of recruitments; dead, number of dead 678

individuals; nf, number of not found individuals. Confidence intervals (95%) for density 679

averages are between parentheses. 680

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Table 2. Increment averages in height and diameter at breast height (dbh) in two 681

populations of Ocotea catharinensis Mez. from the Atlantic Rainforest, Santa Catarina, 682

Brazil. 683

PNSI

parameter category increment S

min max

n

height (m)

seedlings 0.07 (0.05/0.08) 0.10 0 0.64 170

juveniles 0.14 (0.09/0.2) 0.17 0 0.68 35

dbh (cm)

juveniles 0.12 (0.08/0.18) 0.20 0 0.80 56

reproductive 0.8 (0.58/1.02) 0.48 0 1.60 16

FNI

parameter category increment S min max n

height (m)

seedlings 0.13 (0.09/0.15) 0.11 0 0.55 44

juveniles 0.13 (0.07/0.19) 0.16 0 0.70 25

dbh (cm)

juveniles 0.15 (0.09/0.2) 0.18 0 0.60 45

reproductive 1.04 (0.76/1.33) 1.00 0 3.80 51

Note: PNSI, Parque Nacional da Serra do Itajaí; FNI, Floresta Nacional de Ibirama; S, 684

standard deviation; min, minimum; max, maximum; n, number of individuals. Confidence 685

intervals (95%) for increment averages are between parentheses. 686

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Table 3. Genetic estimates for two populations of Ocotea catharinensis Mez from the 687

Atlantic Rainforest, Santa Catarina, Brazil. 688

PSNI

category n � � ��

seedlings 2015 196 172 63.6 21 1.91 1.43 0.223 0.191 0.143*

seedlings 2016 193 168 63.6 21 1.91 1.43 0.223 0.190 0.148*

juveniles 2015 56 52 63.6 20 1.82 1.40 0.224 0.204 0.091

juveniles 2016 64 60 63.6 20 1.82 1.39 0.222 0.207 0.067

reproductive 15/16 68 60 63.6 20 1.82 1.34 0.196 0.171 0.131*

All 2015 320 279 63.6 21 1.91 1.42 0.221 0.189 0.147

All 2016 325 283 63.6 21 1.91 1.42 0.222 0.189 0.146

FNI

category n � � ��

seedlings 2016 51 44 63.6 20 1.82 1.37 0.206 0.177 0.139*

seedlings 2017 41 35 63.6 20 1.82 1.39 0.213 0.179 0.165*

juveniles 2016 52 47 72.7 21 1.91 1.39 0.214 0.193 0.099

juveniles 2017 63 58 72.7 21 1.91 1.37 0.208 0.191 0.084

reproductive 16/17 63 53 63.6 20 1.82 1.36 0.204 0.168 0.177*

All 2016 165 144 72.7 21 1.91 1.37 0.208 0.178 0.143

All 2017 166 146 72.7 21 1.91 1.37 0.208 0.179 0.141

Note: n, sample size; � �, effective size; ��, total number of alleles; ��, percentage of 689

polymorphic loci; ��, average number of alleles per locus; ��, average number of effective 690

alleles per locus; � �, genetic diversity; � �, observed heterozygosity; ��, fixation index; *, p 691

< 0.05. 692

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Figure 1. Map showing both study sites and details of permanent plots. 693

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Figure 2. Demographic structure in two populations of Ocotea catharinensis Mez. from the 694

Atlantic Rainforest, Santa Catarina, Brazil. PNSI: Parque Nacional da Serra do Itajaí; FNI: 695

Floresta Nacional de Ibirama. 696

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Figure 3. Standardized Ripley’s function (L(r)) for seedling, juvenile and reproductive 697

individuals plotted against radius distances (m) for Parque Nacional da Serra do Itajaí 698

(PNSI 2015/2016) and Floresta Nacional de Ibirama (FNI 2016/2017). Continuous lines 699

represent observed L(r), and dashed lines represent the upper and lower confidence 700

envelope (95%) expected under Complete Spatial Randomness. n represents the number of 701

individuals included in each graphic. 702

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Figure 4. Standardized bivariate Ripley’s function (L12(r)) for seedling vs. reproductive 703

individuals plotted against radius distances (m) for Parque Nacional da Serra do Itajaí 704

(PNSI 2015/2016) and Floresta Nacional de Ibirama (FNI 2016/2017). Continuous lines 705

represent observed L12(r), and dashed lines represent the upper and lower confidence 706

envelope (95%) expected under Complete Spatial Independence. n represents the number of 707

seedling individuals/reproductive individuals included in each graphic. 708

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Figure 5. Coancestry coefficient (��) plotted against distance classes (m) for seedling, 709

juvenile and reproductive individuals from Parque Nacional da Serra do Itajaí (PNSI 710

2015/2016) and Floresta Nacional de Ibirama (FNI 2016/2017). Continuous lines represent 711

observed ��, and dashed lines represent the upper and lower confidence envelope (95%). n 712

represents the number of individuals included in each graphic. 713

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Map showing both study sites and details of permanent plots.

210x148mm (300 x 300 DPI)

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Demographic structure in two populations of Ocotea catharinensis Mez. from the Atlantic Rainforest, Santa Catarina, Brazil. PNSI: Parque Nacional da Serra do Itajaí; FNI: Floresta Nacional de Ibirama.

73x29mm (300 x 300 DPI)

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Standardized Ripley’s function (L(r)) for seedling, juvenile and reproductive individuals plotted against radius distances (m) for Parque Nacional da Serra do Itajaí (PNSI 2015/2016) and Floresta Nacional de

Ibirama (FNI 2016/2017). Continuous lines represent observed L(r), and dashed lines represent the upper and lower confidence envelope (95%) expected under Complete Spatial Randomness. n represents the

number of individuals included in each graphic.

149x123mm (300 x 300 DPI)

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Standardized bivariate Ripley’s function (L12(r)) for seedling vs. reproductive individuals plotted against radius distances (m) for Parque Nacional da Serra do Itajaí (PNSI 2015/2016) and Floresta Nacional de

Ibirama (FNI 2016/2017). Continuous lines represent observed L12(r), and dashed lines represent the upper and lower confidence envelope (95%) expected under Complete Spatial Independence. n represents the

number of seedling individuals/reproductive individuals included in each graphic.

119x79mm (300 x 300 DPI)

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Coancestry coefficient (θxy) plotted against distance classes (m) for seedling, juvenile and reproductive individuals from Parque Nacional da Serra do Itajaí (PNSI 2015/2016) and Floresta Nacional de Ibirama (FNI

2016/2017). Continuous lines represent observed θxy, and dashed lines represent the upper and lower confidence envelope (95%). n represents the number of individuals included in each graphic.

149x123mm (300 x 300 DPI)

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draft - university of toronto t-space49 populations (paludo et al. 2016), predict impacts of...

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