Canadian Journal of Forest Research
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,Draft 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
Atlantic Rainforest, fine-scale spatial genetic structure, genetic diversity, Keyword: neighborhood size, seed collection
Is the invited manuscript for consideration in a Special N/A Issue? :
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1 Spatial genetic structure, population dynamics and spatial patterns in the distribution of
2 Ocotea catharinensis Mez. from southern Brazil: implications for conservation
3
4 Tiago Montagna1, Miguel Busarello Lauterjung2, Rafael Candido Ribeiro3ϯ, Juliano Zago
5 da Silva4, Marcia Patricia Hoeltgebaum5, Newton Clóvis Freitas da Costa6, Alison Paulo
6 Bernardi7, Maurício Sedrez dos Reis8.
7
8 Affiliation and address of all authors: Núcleo de Pesquisas em Florestas Tropicais, Pós
9 Graduação em Recursos Genéticos Vegetais, Centro de Ciências Agrárias, Universidade
10 Federal de Santa Catarina. Rodovia Admar Gonzaga, 1346. Florianópolis, Santa Catarina,
11 Brazil. Draft
12
13 E mail adresses of all authors: [email protected], [email protected],
14 [email protected], [email protected], [email protected],
15 [email protected], [email protected], [email protected]
16
17 Corresponding author: Tiago Montagna. Address: Rodovia Admar Gonzaga, 1346.
18 Florianópolis, Santa Catarina, Brazil. Telephone/Fax: +55 48 3721 5322. E mail:
19 [email protected]. ORCID: 0000 0002 7427 4237
ϯCurrent affiliation: Department of Forest and Conservation Sciences, University of British Columbia, Vancouver, BC, Canada. https://mc06.manuscriptcentral.com/cjfr-pubs Canadian Journal of Forest Research Page 2 of 44
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20 Abstract
21 In this study, we employ an integrated demographic/genetic approach with the aim of
22 informing efforts to conserve Ocotea catharinensis, an endangered tree species from the
23 Brazilian Atlantic Rainforest. After establishing two permanent plots (15 and 15.5 ha)
24 within Protected Areas in Santa Catarina state, Brazil, we evaluated demographic aspects
25 (density, recruitment, mortality and growth), spatial pattern, genetic diversity and spatial
26 genetic structure (SGS) in three categories of individuals (seedlings, juveniles and
27 reproductive) over two years. Studied populations presented low recruitment of individuals
28 and low rates of increment in diameter and height. Aggregation was the main spatial pattern
29 observed for both populations. High levels of genetic diversity were estimated for both
30 populations, but also high levels ofDraft fixation index, signaling the risk of losing genetic
31 diversity over generations. Significant SGS was found for both populations, reflecting
32 nonrandom distribution of the genotypes. Demographic and genetic surveys also allowed
33 the estimation of minimum viable areas for genetic conservation (> 170 ha), deme sizes
34 (around 10 ha) and distances for seed collection (at least 60 m). Effective population size is
35 restricted in studied populations, locally threatening the species perpetuation over
36 generations. Further research can clarify how this condition it will change in subsequent
37 years.
38
39 Keywords: Atlantic Rainforest, fine scale spatial genetic structure, genetic diversity,
40 neighborhood size, seed collection
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41 Introduction
42 Demographic and genetic studies are basic and powerful tools to understand
43 dynamic processes at the population level and their maintenance over time (Griffith et al.
44 2016, Lowe et al. 2017). Population structure can be described in terms of the ages, sizes,
45 and forms of the individuals that composes it, and population structure is susceptible to
46 environmental conditions and dynamic processes, such as recruitment, mortality and
47 growth rates, as well as intra and interspecific competition (Harper and White 1974).
48 Therefore, demographic studies can help us predict decline, stability or expansion in
49 populations (Paludo et al. 2016), predict impacts of management practices on the structure
50 of populations (Ribeiro et al. 2014), and unravel environmental and ecological aspects that
51 determine demographic parameters andDraft spatial patterns of distribution (Lara Romero et al.
52 2016).
53 Genetic structure, in turn, results from the spatial nonrandom distribution of
54 genotypes in space (Vekemans and Hardy 2004). At a more restricted scale (e.g., within a
55 population), genetic structure largely arises from the formation of local pedigrees caused by
56 limited gene flow (Vekemans and Hardy 2004). Life history traits, such as regeneration
57 mode (e.g., sprouting or non sprouting species), plus coarse and fine scale disturbances
58 (e.g., gaps, fires, landslides) and particular conditions for seedling establishment can also
59 lead to genetic structuring (Mathiasen and Premoli 2013). Genetic structure within a
60 population is commonly known as spatial genetic structure (SGS), or fine scale spatial
61 genetic structure. Studies of SGS and its causes have provided fundamental guidelines for
62 plant conservation and actions, e.g., minimum distances required for seed collections
63 (Tarazi et al. 2010), associations between habitat fragmentation and SGS (Santos et al.
64 2016), and estimates of neighborhood sizes (Buzatti et al. 2012). By using information
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65 gained from both demographic and genetic studies, we might be able to propose feasible
66 management and conservation strategies for plant species.
67 Ocotea catharinensis Mez. is a tree species that occurs in the Brazilian Atlantic
68 Rainforest (AR) between latitudes 19°57' S (Saiter and Thomaz 2014) and 30°15' S
69 (Carvalho 1994). This species was considered the most abundant and dominant tree in the
70 upper stratum of Ombrophilous Dense Forest, a forest formation of the AR (Veloso and
71 Klein 1959, Klein 1980) in southern Brazil. However, the intensive exploitation of O.
72 catharinensis to produce timber, combined with the high fragmentation of AR (Ribeiro et
73 al. 2009, Vibrans et al. 2012), led to the placement of this species on the Brazilian List of
74 Endangered Plant Species (MMA 2014). The species is also classified as vulnerable by the
75 IUCN Red List (Varty and GuadagninDraft 1998).
76 Currently, the species occurs at an average density of 5.86 individuals/ha (diameter
77 at breast height – dbh > 10 cm) in remnants of Ombrophilous Dense Forest in Santa
78 Catarina state (SC) (Lingner et al. 2013). However, in the past, higher densities were
79 recorded, ranging from 23.9 individuals/ha (dbh > 12.7 cm) (Veloso and Klein 1959) up to
80 20 to 50 reproductive individuals/ha (Reitz et al. 1978). Densities of 200 up to 600
81 individuals/ha higher than 1 m were also reported for SC (Reitz et al. 1978). These major
82 differences between past and present densities call for studies to support conservation
83 efforts regarding O. catharinensis.
84 Indeed, studies reporting on the demographic aspects of O. catharinensis have
85 already been carried out (Veloso and Klein 1959, Tarazi et al. 2010, Lingner et al. 2013).
86 Nevertheless, such studies have neither covered seedling densities nor focused on
87 population dynamics (e.g., growth rates, mortality and recruitment). Ocotea catharinensis
88 presents an aggregated spatial pattern (Tarazi et al. 2010); however, not only is the extent
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89 of this aggregation unknown, but also possible variations in the extent and the intensity of
90 the spatial pattern between different categories of individuals (e.g., seedlings, juveniles or
91 reproductive). High levels of genetic diversity, low to moderate levels of fixation index,
92 and moderate genetic divergence are reported for O. catharinensis populations (Tarazi et al.
93 2010, Martins et al. 2015). Furthermore, significant SGS within the populations of O.
94 catharinensis have already been detected (Tarazi et al. 2010). So far, however, genetic
95 diversity and SGS within different categories of individuals are poorly understood.
96 In this study, we described the population dynamics, spatial pattern and SGS of
97 three categories of O. catharinensis individuals (seedlings, juveniles, and reproductive)
98 from two populations in SC, southern Brazil. We asked i) how the demographic structure
99 varies over the years, ii) how individualsDraft are spatially distributed, and iii) what is the
100 magnitude of SGS in those populations. This study aimed to provide useful knowledge for
101 O. catharinensis in situ conservation.
102
103 Material and methods
104 Study areas and plots
105 This study was conducted in two protected areas in SC: Parque Nacional da Serra
106 do Itajaí (Serra do Itajaí National Park: PNSI – 57,374 ha) and Floresta Nacional de
107 Ibirama (Ibirama National Forest: FNI – 570 ha) (Figure 1). Vegetation in the study areas
108 is classified as Ombrophilous Dense Forest (ODF), and the climate is described as
109 subtropical humid (Cfa), according to Köeppen’s classification. Although currently
110 protected, both areas have previously been subjected to anthropogenic activities at different
111 levels of intensity. For example, selective logging of O. catharinensis was reported for FNI
112 in the 1950s (MMA 2008) and until 1990 for PNSI (MMA 2009). Hunting and illegal
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113 exploitation of other key plant species were also reported for both areas (MMA 2008,
114 2009), and these activities remain a problem (personal observation).
115 In order to collect demographic and genetic data, two permanent plots were
116 established: a 15 ha plot (250 m x 600 m) in PNSI and a 15.5 ha plot (350 m x 430 m) in
117 FNI. Two smaller plots subdivided into 10 m x 10 m subplots were installed in the center of
118 the bigger plots (15 and 15.5 ha). These smaller plots comprised 1.9 ha in PNSI (100 m x
119 190 m) and 1.68 ha in FNI (120 m x 140 m) (Figure 1). The sampled area in PNSI has an
120 average elevation of 410 m, and vegetation varies from the middle stage of secondary
121 succession on hilltops to the advanced stage on hillsides (MMA 2009). The sampled area in
122 FNI has an average elevation of 350 m and vegetation in the advanced stage of secondary
123 succession (MMA 2008). Draft
124
125 Demographic characterization
126 For demographic characterization, Ocotea catharinensis individuals were classified
127 as i) seedlings, i.e., individuals without measurable diameter at breast height (dbh – 1.3 m);
128 ii) juveniles, i.e., individuals with measurable dbh at 1.3 m up to 20 cm dbh; and iii)
129 potentially reproductive (hereinafter, reproductive), i.e., individuals with dbh higher than
130 20 cm. We assessed seedling and juvenile individuals only in the smaller plots and the
131 reproductive individuals in both smaller and bigger plots. We measured the height of
132 seedlings and juveniles (up to 5 m) and the dbh of juveniles and reproductive individuals
133 over two years, 2015 and 2016 in PNSI and 2016 and 2017 in FNI. Additionally, we
134 evaluated individuals’ mortality, recruitment, density and increment (height and dbh).
135 Spatial position of each individual was obtained by xy coordinate system in each of the
136 smaller plots and with GPS (Garmin GPSmap 76CSx) outside the smaller plots.
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137 To visualize the demographic structures in each population, histograms were
138 constructed. The density of individuals was compared between study sites with a
139 confidence interval (95%) constructed through bootstrapping 1,000 times the density of
140 each category of individuals in each subplot (10 m x 10 m). Confidence intervals (95%)
141 were also constructed for the increment averages of height and dbh (bootstrap – 1,000
142 times). The increment values were obtained through two evaluations in each study site. The
143 confidence intervals were constructed in R language (R Development Core Team 2015).
144
145 Spatial pattern and spatial independence analysis
146 Spatial pattern was estimated for all categories of individuals and evaluated years in
147 PNSI and FNI, applying the standardizedDraft Ripley’s K function L(r) (Ripley 1981), as
148 implemented in the “spatstat” package (Baddeley and Turner 2005) in R language (R
149 Development Core Team 2015). Spatial independence between seedlings and reproductive
150 individuals was tested using the bivariate extension of Ripley’s K L12(r) (Lotwick and
151 Silverman 1982), as implemented in the “splancs” package (Rowlingson and Diggle 2015)
152 in R language (R Development Core Team 2015). For both analyses, we used a radius (r) of
153 1 m to estimate L(r) and L12(r), and the spatial pattern was evaluated up to half the smaller
154 dimension of the plots, or up to 50 m and 60 m for smaller PNSI and FNI plots (seedlings
155 and juveniles), respectively, and up to 175.5 m and 125 m for bigger PNSI and FNI plots
156 (reproductive), respectively. Deviations from Complete Spatial Randomness were tested
157 through a confidence interval (95%) obtained from 1,000 Monte Carlo simulations of
158 completely random events.
159
160 Genetic data acquisition and analysis
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161 At both study sites, fresh leaves were collected from all O. catharinensis individuals
162 occurring in the smaller plots plus all reproductive individuals occurring in the bigger plots.
163 Furthermore, individuals that recruited into seedling category were also sampled by the
164 second demographic evaluation (2016 in PNSI and 2017 in FNI). Genetic characterization
165 was performed using allozyme markers, wich have been widely used for several studies
166 reporting on population genetics, including SGS (Vekemans and Hardy 2004, Tarazi et al.
167 2010, Quipildor et al. 2017). Enzymes were extracted by macerating the leaf tissue for 15
168 seconds with an automatic homogenizer (6500 rotations per minute).
169 The following enzymatic systems were resolved in starch gel (Penetrose 30 13%),
170 using a Tris Citrate pH 7.5 buffer (Tris 27 g.L 1 and citric acid 16.52 g.L 1) for
171 electrophoresis: aspartate transaminaseDraft (at, EC 2.6.1.1), diaphorase (dia, EC 1.8.1.4),
172 esterase (est – Enzyme Commission 3.1.1.1), glucose 6 phosphate dehydrogenase (g6pdh,
173 EC 1.1.1.49), glutamate dehydrogenase (gtdh, EC 1.4.1.2), isocitrate dehydrogenase (idh,
174 EC 1.1.1.42), malic enzyme (me, EC 1.1.1.40), malate dehydrogenase (mdh, EC 1.1.1.37)
175 and phosphoglucomutase (pgm, EC 5.4.2.2).
176 In order to characterize the genetic diversity of populations and their categories, we
177 estimated the following indexes: percentage of polymorphic loci ( ), total number of
178 alleles ( ), average number of alleles per locus ( ), average number of effective alleles per
179 locus ( = 1/(1 − )), observed ( ) and expected heterozygosity ( ) and fixation
180 index ( ). Effective population size ( – the size of an idealized population that would
181 have the same amount of inbreeding as the population under consideration – Kimura and
182 Crow (1963)) was estimated following the equation proposed by Li (1976): = /(1 +
183 ), where is the number of sampled individuals. Statistical significance (p < 0.05) for
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184 values was obtained through 1,000 permutations of alleles among individuals. All analyses
185 were carried out in FSTAT software, version 2.9.3.2 (Goudet 2002), except for and .
186 Based on the , we estimated the minimum viable areas ( ) for long term
187 genetic conservation, as follows: = ( )/( / . ), where ( ) is a reference
188 value of 1,000 individuals, which was proposed by Lynch (1996) as sufficient to mitigate
189 the effects of deleterious mutations, n is the sample size, and is the density of
190 reproductive individuals in each population. These estimates were made by taking into
191 account only reproductive individuals in the last year of evaluation in each population
192 (PNSI = 2016 and FNI = 2017).
193 Spatial genetic structure (SGS) for both populations and all categories was Draft 194 estimated by performing an autocorrelation analysis using the coancestry coefficient ( ),
195 as described in Loiselle et al. (1995). We established equal distance classes for both
196 populations (20 m) in order to facilitate comparisons, observing a minimum of 30 pairs of
197 observations in each class. To test the statistical significance of within each distance
198 class, a confidence interval (95%) was constructed by 10,000 permutations of individual
199 locations among all individuals. SGS analysis was performed using SPAGeDi software,
200 version 1.5 (Hardy and Vekemans 2002).
201 Neighborhood size ( – the effective population number in an area from which the
202 parents may be assumed to be drawn at random – Wright (1940)) for reproductive
203 individuals within each studied population was estimated as = −(1 − )/
204 (Vekemans and Hardy 2004). In this formula, is the coancestry coefficient in the first
205 class of distance (0 – 20 m), and is the regression slope of the coancestry coefficient
206 value on the logarithm of spatial distance between individuals, but within plot distances, as
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207 follows: 0 up to 560 m in PNSI and 0 up to 480 m in FNI. was estimated using
208 SPAGeDi, version 1.5 (Hardy and Vekemans 2002). Deme sizes (ha) were estimated for
209 each studied population based on values, as in the following equation: =
210 / , where is the density of reproductive individuals in each population.
211
212 Results
213 Population structure and dynamics
214 The populations presented similar densities of juveniles and reproductive
215 individuals, but PNSI presented statistically higher density of seedlings (Table 1).
216 Recruitments in the seedling category were recorded for both populations (PNSI = 5
217 individuals; FNI = 1 individual), asDraft well as recruitment of seedlings into the juvenile
218 category (PNSI = 8 individuals; FNI = 11 individuals) (Table 1). Mortality was verified
219 only for seedlings from PNSI (9 individuals) (Table 1). Distribution of individuals per dbh
220 classes presented an inverted J shaped form for both populations; however, PNSI showed a
221 gap of individuals in the 10 cm to 20 cm and 20 cm to 30 cm dbh classes (Figure 2).
222 Increment averages in height and dbh were similar between populations and
223 categories, except for seedlings from FNI, which showed statistically higher height
224 increment when compared to seedlings from PNSI (Table 2). All increment averages
225 presented high associated standard deviations (S), evidencing the heterogeneity of these
226 features in the studied populations (Table 2).
227
228 Spatial pattern and spatial dependence
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229 Aggregation, with different intensities and at different distances, was the main
230 spatial pattern observed in both studied populations and their categories (Figure 3).
231 Seedling individuals from PNSI presented aggregation from 0 m up to 50 m in 2015 and
232 2016. Juveniles were aggregated from ≈5 up to 50 m in 2015 and 2016, and reproductive
233 individuals presented aggregation from ≈5 up to 125 m (2015 and 2016) (Figure 3). In FNI,
234 seedlings presented an aggregated spatial pattern from 0 m up to 60 m in 2016 and from ≈5
235 m up to ≈18 m in 2017. Juveniles presented no aggregation in 2016, but aggregation from 0
236 m up to ≈8 m was recorded in 2017. Reproductive individuals were aggregated from ≈2 m
237 up to ≈75 m (2016 and 2017) (Figure 3). Aggregation intensity (L(r)) was higher for
238 individuals from PNSI when compared to FNI (Figure 3). Seedlings and juveniles from
239 PNSI and FNI presented spatial distributionDraft independent of the spatial distribution of
240 reproductive individuals (Figure 4).
241
242 Genetic diversity
243 Between PNSI and FNI, 477 individuals were genotyped, and 21 different alleles
244 were recorded for both populations (Table 3). The number of individuals composing each
245 category followed the results of the demographic survey. For instance, seedlings that
246 recruited into the juvenile category (PNSI = 8 individuals; FNI = 11 individuals) were
247 analyzed as seedlings in the first year and as juveniles in the second year. Average number
248 of effective alleles per locus ( ) represented about 70% of for both populations,
249 indicating the occurrence of common alleles on the assessed loci. Diversity indexes were
250 quite similar between years, categories and populations (Table 3). Significant deviations
251 from Hardy–Weinberg equilibrium were detected for seedlings and reproductive
252 individuals from PNSI and FNI, indicating deficit of heterozygotes (Table 3). Effective
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253 population size was around 13% smaller than sample sizes, reflecting the estimates.
254 Minimum viable areas, taking a reference size of 1,000 individuals (Lynch 1996), were
255 equal to 176 ha and 205 ha for PNSI and FNI, respectively.
256
257 Spatial genetic structure
258 Significant SGS was found for both studied populations. Seedlings from PNSI
259 presented positive and significant coancestry ( ) values when separated by less than 40 m
260 in both evaluated years. Juveniles from PNSI did not show significant SGS, while
261 reproductive individuals from PNSI presented positive and significant values in the
first and third distance classes (0 – 20 m and 40 – 60 m) (Figure 5). For FNI, positive and 262 Draft 263 significant values were detected for seedlings (2016 and 2017) in the first distance class
264 (0 – 20 m). Juveniles also presented positive and significant values in the first distance
265 class (0 – 20 m), but only in 2017. For reproductive individuals, no significant SGS was
266 recorded (Figure 5). All significant and positive coancestry values ranged from 0.037
267 (PNSI seedlings in 2015) up to 0.073 (FNI seedlings in 2016). Negative and significant
268 values were verified for reproductive individuals in the distance class of 140 m to 160 m
269 and 180 m to 200 m in PNSI and FNI, respectively (Figure 5).
270 Neighborhood size estimates ( ) for reproductive individuals from PNSI and FNI
271 were equal to 44 and 48 individuals, respectively. Under the estimated densities of
272 reproductive individuals (Table 1), deme sizes were estimated to be 8.8 ha and 11.7 ha for
273 PNSI and FNI, correspondingly.
274
275 Discussion
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276 This is the first attempt to understand demographic and genetic aspects of O.
277 catharinensis over more than just one year. Nevertheless, it is important to keep in mind
278 that O. catharinensis is a long lived species, well distributed across the Ombrophilous
279 Dense Forest. Moreover, all the presented results and the following discussions are based
280 on a two year survey (genetic and demographic) in two populations. For that reasons, our
281 data and discussions should be interpreted considering the particularities mentioned.
282
283 Population structure and dynamics
284 Both studied populations presented densities of reproductive individuals (Table 1)
285 compatible with those of the most recent study. Ocotea catharinensis occurs at an average
286 density of 5.86 individuals/ha (dbh> Draft10 cm) in remnants of Ombrophilous Dense Forest in
287 SC (data from 197 sample units) (Lingner et al. 2013). Nevertheless, estimated densities for
288 both studied populations (Table 1) were found to be substantially lower than estimated
289 densities for O. catharinensis populations in the past. In SC, densities of 23.9
290 individuals/ha (dbh > 12.7 cm) were previously estimated in eight sample units (Veloso and
291 Klein 1959). Additionally, observations by Reitz et al. (1978) reported densities ranging
292 from 20 up to 50 reproductive individuals/ha and from 200 up to 600 individuals/ha higher
293 than 1 m. Such discrepancy between past (Veloso and Klein 1959, Reitz et al. 1978) and
294 present estimates (Tarazi et al. 2010, Lingner et al. 2013, Table 1) can be attributed to the
295 intensive exploitation of O. catharinensis for timber in the intervening years. Ocotea
296 catharinensis is considered one of the three most exploited timber species in the
297 Ombrophilous Dense Forest, supplying basically the national market (Reitz et al. 1978).
298 Recruitments into the seedling category occurred at lower intensity than mortality of
299 seedlings for the PNSI population, and for the FNI population, only one seedling individual
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300 was recruited (Table 1). Corroborating our results concerning increment rates (Table 2), O.
301 catharinensis is ranked as one of the three species with lowest growth rate among 100 tree
302 species from Brazil, as listed by Carvalho (1994). These results demonstrate that natural
303 reestablishment of past densities could be a slow process. For instance, at the estimated
304 average of dbh increment for juveniles from FNI (Table 2), an individual with dbh = 1 cm
305 could be expected to reach a dbh = 20 cm in about 126 years (95% confidence interval = 95
306 years – 211 years).
307 The distribution of individuals per dbh classes (Figure 2) presented an inverted J
308 shaped form for both populations, demonstrating that the studied populations still present
309 the potential for replacement of larger individuals, even with the low intensity of seedling
310 recruitment (Table 1). A gap of individualsDraft was observed in the 10 cm to 20 cm and 20 cm
311 to 30 cm dbh classes for the PNSI population (Figure 2), owing to logging activities
312 reported for PNSI until 1990 (MMA 2009). Therefore, theses gaps may be the result of past
313 exploitation processes, reducing the regeneration capacity of the population by the
314 withdrawal of reproductive individuals.
315
316 Spatial pattern and spatial independence
317 Aggregated distribution pattern is predominant for tropical tree species, resulting
318 from heterogeneous environments (Condit et al. 2000). This aggregated distribution pattern
319 was also recorded for O. catharinensis (Tarazi et al. 2010) and O. porosa (Canalez et al.
320 2006). The studied populations presented mostly aggregated distribution, with the
321 exception of juveniles from FNI (Figure 3). In general, aggregation intensity (L(r)) was
322 higher for individuals from PNSI, suggesting higher environmental heterogeneity in this
323 study site when compared to FNI (Figure 3). As mentioned, the stage of secondary
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324 succession in the PNSI plot varies according to the elevation: middle stage on hilltops and
325 advanced stage on hillsides (MMA 2009), while in the FNI plot, the vegetation only
326 presents the advanced stage of secondary succession (MMA 2008).
327 Comparing both studied populations, it is possible to observe that spatial
328 distribution of seedlings and juveniles was affected by mortality and recruitment. Seedlings
329 from PNSI presented a more intense aggregation in 2016 than in 2015; on the other hand,
330 seedlings from FNI were aggregated from 0 m up to 60 m in 2016 and from ≈5 m up to ≈18
331 m in 2017 (Figure 3). Recruitment of seedlings into the next category caused a slight
332 decrease in the aggregation intensity of juveniles in PNSI. Nevertheless, the opposite result
333 can be seen for FNI juveniles, which were not aggregated in 2016 and presented
334 aggregation from 0 m up to ≈8 m in 2017Draft (Figure 3).
335 Spatial distribution of seedlings was independent of the spatial distribution of
336 reproductive individuals (Figure 4). Therefore, spatial distribution of seedlings is unlikely
337 to be associated to the barochory reported for O. catharinensis (Moraes and Paoli 1995).
338 The better germination of seeds in conditions of higher soil humidity (Moraes and Paoli
339 1999), combined with high rates of deteriorated seeds found under seed trees (Moraes and
340 Paoli 1995, 1999), indicating density dependent recruitment, are factors that could better
341 explain the aggregation and spatial independence of seedlings. The action of fauna
342 dispersing seeds can also influence the spatial pattern and independence of seedlings. For
343 instance, Brachyteles arachnoides, one of the dispersers of O. catharinensis (Moraes and
344 Paoli 1995), presents two types of behavior when feeding on trees of Cryptocarya
345 moschata (Lauraceae): 1) feeding from only one seed tree, dispersing seeds in suitable
346 places for seedling recruitment (Moraes et al. 1999), which then favors aggregation and
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347 spatial independence and 2) feeding from several seed trees, dispersing seeds along the area
348 (Moraes et al. 1999), and then favoring random distribution.
349 A comparison of PNSI and FNI based on differences in spatial distribution between
350 juveniles and reproductive individuals (Figure 3) can be viewed as a reflection of the stage
351 of secondary succession of each study site. In the case of reproductive individuals, spatial
352 distribution can also be influenced by past logging activities reported for both populations
353 (MMA 2008, 2009). Nevertheless, it is a difficult task to evaluate such influence,
354 essentially because evidence of exploited individuals, such as rotten logs, has, of course,
355 long since vanished.
356
357 Genetic diversity Draft
358 Tree species of the Lauraceae family apparently trend toward high levels of genetic
359 diversity (Chung et al. 2003, Tarazi et al. 2010, Reis et al. 2012, Martins et al. 2015). The
360 estimated genetic diversity ( ) for each population (PNSI = 0.222; FNI = 0.208) can also
361 be considered high when compared to average for long lived perennial woody species
362 (0.149) (Hamrick and Godt 1989). This is an important result for the conservation of O.
363 catharinensis, highlighting the role of protected areas in the conservation of genetic
364 diversity of several species and demonstrating that PNSI and FNI populations present the
365 real potential for conservation.
366 Significant and positive deviations from Hardy Weinberg equilibrium were also
367 recorded, on average, for other populations of O. catharinensis (Reis et al. 2012, Martins et
368 al. 2015) and for the congeneric species O. porosa and O. odorifera (Reis et al. 2012).
369 Nevertheless, significant excess of heterozygotes were also recorded for populations of O.
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370 catharinensis (Tarazi et al. 2010). Several factors can be influencing these divergences,
371 such as more or less intense historical exploitation of each evaluated fragment, SGS levels
372 in each population, which can affect genetic estimates (Jones and Hubbell 2006), biparental
373 inbreeding, and sampling strategies of each study. However, given a single reproduction
374 event under Hardy Weinberg equilibrium, the expected fixation index of seedlings should
375 be zero for an outcrossing species (Hartl and Clark 2007). Ocotea catharinensis is
376 presumably an outcrossing species, presenting apparent outcrossing rate of 1.0 (Tarazi et al.
377 2010); however, aspects of its reproductive biology, such as mating system and pollination
378 ecology, are still not fully understood. Future studies to elucidate the reproductive system
379 of the species can clarify this question.
380 Positive and significant fixationDraft indexes ( ) estimates were recorded for
381 reproductive individuals from both studied populations, and these estimates resulted in
382 effective sizes ( ) reductions (Table 3). Based on and taking a reference size of 1,000
383 individuals (Lynch 1996), minimum viable area estimates (176 ha for PNSI and 205 ha for
384 FNI) were smaller than the total areas at the study sites (PNSI = 57,374 ha; FNI = 570 ha).
385 Thus, both study sites are able to conserve large populations, even larger than 1,000
386 individuals. Populations lose genetic diversity in a rate of 1/2 , where is the number of
387 individuals (Wright 1931). Therefore, small populations will lose genetic diversity faster
388 than larger populations. This result demonstrates the potential importance of fragment size
389 in mitigating the effects of fixation indexes.
390
391 Spatial genetic structure
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392 Significant SGS has been reported for a number of tropical and neotropical tree
393 species (Hardy et al. 2006) and also for trees of the Lauraceae family, such as Cryptocarya
394 moschata (Moraes et al. 2004). Nevertheless, no significant SGS was observed for other
395 trees of Lauraceae, for instance, O. odorifera (Kageyama et al. 2003), and Cinnamomum
396 insularimontanum (Chung et al. 2003). These differences among species can be influenced
397 by environmental conditions, but also by aspects related to the reproductive biology and
398 gene flow of each species (Chung et al. 2003, Vekemans and Hardy 2004, Hardy et al.
399 2006).
400 Ocotea catharinensis presented significant SGS up to distances of 80 m (Tarazi et
401 al. 2010). Our SGS results for reproductive individuals differ from those found by Tarazi et
402 al. (2010). Reproductive individualsDraft from FNI lack SGS, while reproductive individuals
403 from PNSI present significant SGS up to 60 m, except in the distance class from 20 m up to
404 40 m (Figure 5). These differences can be explained in several ways, i) methodological
405 approaches: our reproductive category included only individuals with dbh > 20 cm, while
406 Tarazi et al. (2010) sampled individuals with dbh > 6.85 cm; ii) environmental conditions
407 of each study site: this could, for example, include the presence (or absence) and abundance
408 of seed dispersers; and iii) historical exploitation of each study site: both PNSI and FNI
409 have undergone adverse logging activities (MMA 2008, 2009). Selective logging may
410 reduce the distance of the SGS for reproductive individuals, such as that observed for
411 Hymenaea courbaril (Lacerda et al. 2008).
412 Significant SGS up to 40 m for PNSI and up to 20 m for FNI was estimated for
413 seedlings (Figure 5). As discussed, spatial distribution of seedlings is independent of the
414 spatial distribution of reproductive individuals for both populations (Figure 4). Therefore,
415 barochory cannot explain the SGS of seedlings. Brachyteles arachnoides, one of the
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416 dispersers of O. catharinensis (Moraes and Paoli 1995), presented two types behavior when
417 feeding on the Lauraceae tree Cryptocarya moschata, as previously mentioned. Hence, the
418 preference for germination in conditions of higher soil humidity (Moraes and Paoli 1999),
419 the high rates of deteriorated seeds found under seed trees (Moraes and Paoli 1995, 1999),
420 and the behavior of seed dispersers are all factors that can explain the SGS of seedlings,
421 apart from barochory.
422 The mortality and recruitment of seedlings and juveniles resulted in slight changes
423 in SGS pattern of these categories in FNI (Figure 5). The recruitment of 11 seedlings into
424 the juvenile category in 2017 (Table 1) led to the appearance of significant SGS in the first
425 distance class for juveniles (0 – 20 m) and the reduction of SGS level in the first distance
426 class for seedlings (0 – 20 m) (FigureDraft 5). The same trend was not observed for seedlings
427 and juveniles from PNSI, possibly because seedling density in this population is larger than
428 that in the FNI population (Table 1). Consequently, the processes of recruitment and
429 mortality represent only a small portion of total density. Increase in SGS in older cohorts
430 relative to younger cohorts can result from several factors, such as bottlenecks or founder
431 effects, local adaptation owing to microhabitat selection, limited dispersal, and more
432 overlapping generations in older cohorts compared to younger cohorts (Jones and Hubbell
433 2006).
434 Neighborhood size estimates ( ) (PNSI = 44 individuals and FNI = 48 individuals)
435 can be considered intermediate when compared to other estimates for the species (25 to 83
436 individuals – Tarazi et al (2010). Nevertheless, under the estimated densities of
437 reproductive individuals (Table 1), estimates of deme size in the present study (PNSI = 8.8
438 ha and FNI = 11.7 ha) were greater than those of Tarazi et al. (2010) at 5 to 6 ha. These
439 estimates can be interpreted as a minimum required area for conservation of a deme.
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440
441 Implications for conservation
442 Estimated population densities by the present study and other recent studies (Tarazi
443 et al. 2010, Lingner et al. 2013) are considerably lower than historical densities (Veloso and
444 Klein 1959, Reitz et al. 1978), reflecting the intensive timber exploitation. Furthermore,
445 results of our demographic survey revealed a low recruitment of new individuals into
446 populations, as well as low rates of increment in dbh and height. Therefore, the negative
447 effects caused by exploitation on the demographic aspects of this species may require a
448 protracted period of recovery. In this sense, it is important to continue studying population
449 dynamics of O. catharinensis, especially in order to better understand the factors
450 influencing the low recruitment of seedlings.Draft Supra annual seed production limited to a few
451 seed trees was observed for O. catharinensis (Silva et al. 2000), and this can be a factor
452 influencing the regenerative potential of the species. It is also important to continue
453 restricting exploitation of O. catharinensis in order to avoid further reductions in
454 population sizes.
455 As part of our integrative approach, the genetic survey returned valuable
456 information regarding conservation of genetic diversity. Large areas are imperative for
457 long term conservation of the species – ideally greater than 170 ha, according to the
458 minimum viable areas estimated. Selecting large areas to conserve O. catharinensis
459 populations might present other advantages, such as high probability of the presence of
460 fauna, an important vector of seed dispersal, and high occurrence of adequate microhabitats
461 for seed germination and seedling establishment. Nevertheless, deme sizes were estimated
462 to be around 10 ha for both PNSI and FNI, signaling that small fragments can also be
463 important in the genetic conservation of O. catharinensis. It should be noted that AR is
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464 currently highly fragmented (Ribeiro et al. 2009, Vibrans et al. 2012), and in this sense,
465 small fragments can harbor rare and exclusive alleles, and could also serve as binding
466 elements between larger fragments.
467 Regarding ex situ conservation, SGS analysis revealed two important distances to be
468 respected in order to avoid collection of seeds from closely related individuals. In order to
469 minimize the probability of sampling closely related individuals, it is recommended to
470 sample seeds of individuals separated by at least 60 m for PNSI and 40 m for FNI. The FNI
471 population did not present significant SGS, but a tendency toward structuration up to 40 m
472 was observed (Figure 5). In order to maximize the capture of genetic diversity, seeds should
473 be sampled from seed trees separated by 140 m to 160 m in PNSI and 180 m to 200 m in
474 FNI. These ranges represent the distanceDraft at which reproductive individuals presented
475 negative and significant estimates of coancestry (Figure 5). Therefore, these are also ranges
476 where individuals are more genetically distinct.
477 The major differences between present and past estimates of density and the high
478 levels of fixation indexes for seedlings are signaling major restrictions of effective
479 population size, caused by the intense timber exploitation. This condition summed up with
480 the low rates of growth and recruitment can imply in loss of genetic diversity and
481 population dynamism over generations, therefore locally threatening the species
482 perpetuation. Thus, it is important to continuously monitor and study O. catharinensis
483 populations to verify whether this condition is unique to the studied populations and how it
484 will change in subsequent years.
485 Finally, the conclusions above were made possible through the integration of
486 demographic and genetic data and the evaluation of demographic and genetic aspects of
487 two O. catharinensis stands over a two year period, highlighting the importance of such
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488 integrative approach for studies of endangered tree species. Although O. catharinensis is a
489 longevous species, this is the first attempt to understand its demographic and genetic
490 aspects in more than one year.
Draft
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491 Acknowledgements
492 We thank the Instituto Chico Mendes de Conservação da Biodiversidade (ICMBio)
493 and the researchers of Núcleo de Pesquisas em Florestas Tropicais for their support with the
494 fieldwork. We also thank the Laboratório de Fisiologia do Desenvolvimento e Genética
495 Vegetal for providing the necessary infrastructure required for the genetic analysis
496 performed in this work. This study was funded by the Fundação de Amparo à Pesquisa e
497 Inovação do Estado de Santa Catarina (FAPESC) (grant numbers 11939/2009, 18868/2011
498 9 and TR2013 3558), the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
499 (CAPES) to TM, APB, MBL, NCFC and JZS, and the Conselho Nacional de
500 Desenvolvimento Científico e Tecnológico (CNPq) to MSR (304724/2010 6), MPH
501 (140386/2013 0) and RCR (130894/2015 0).Draft
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674 Table 1. Demographic estimates in two populations of Ocotea catharinensis Mez. from the
675 Atlantic Rainforest, Santa Catarina, Brazil.
individuals density recr dead nf category 2015 2016 2015 2016 2016 2016 2016
PNSI 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
individuals density recr dead nf category 2016 2017 2016 2017 2017 2017 2017
FNI seedlings 51 41 30.4 (19/42.3) 24.4 (16.1/32.7) 1 0 0
juveniles 52 63 Draft 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
676 Note: PNSI, Parque Nacional da Serra do Itajaí; FNI, Floresta Nacional de Ibirama;
677 individuals, total number of individuals in each category; density, number of individuals
678 per hectare in each category; recr, number of recruitments; dead, number of dead
679 individuals; nf, number of not found individuals. Confidence intervals (95%) for density
680 averages are between parentheses.
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681 Table 2. Increment averages in height and diameter at breast height (dbh) in two
682 populations of Ocotea catharinensis Mez. from the Atlantic Rainforest, Santa Catarina,
683 Brazil.
parameter category increment S min max n
seedlings 0.07 (0.05/0.08) 0.10 0 0.64 170 height (m) PNSI juveniles 0.14 (0.09/0.2) 0.17 0 0.68 35
juveniles 0.12 (0.08/0.18) 0.20 0 0.80 56 dbh (cm) reproductive 0.8 (0.58/1.02) 0.48 0 1.60 16
parameter category increment S min max n
seedlings 0.13 (0.09/0.15) 0.11 0 0.55 44 height (m) FNI juveniles Draft 0.13 (0.07/0.19) 0.16 0 0.70 25
juveniles 0.15 (0.09/0.2) 0.18 0 0.60 45 dbh (cm) reproductive 1.04 (0.76/1.33) 1.00 0 3.80 51
684 Note: PNSI, Parque Nacional da Serra do Itajaí; FNI, Floresta Nacional de Ibirama; S,
685 standard deviation; min, minimum; max, maximum; n, number of individuals. Confidence
686 intervals (95%) for increment averages are between parentheses.
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687 Table 3. Genetic estimates for two populations of Ocotea catharinensis Mez from the
688 Atlantic Rainforest, Santa Catarina, Brazil.
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 PSNI 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
Draft 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 FNI 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
689 Note: n, sample size; , effective size; , total number of alleles; , percentage of
690 polymorphic loci; , average number of alleles per locus; , average number of effective
691 alleles per locus; , genetic diversity; , observed heterozygosity; , fixation index; *, p
692 < 0.05.
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693 Figure 1. Map showing both study sites and details of permanent plots.
Draft
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694 Figure 2. Demographic structure in two populations of Ocotea catharinensis Mez. from the
695 Atlantic Rainforest, Santa Catarina, Brazil. PNSI: Parque Nacional da Serra do Itajaí; FNI:
696 Floresta Nacional de Ibirama.
Draft
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697 Figure 3. Standardized Ripley’s function (L(r)) for seedling, juvenile and reproductive
698 individuals plotted against radius distances (m) for Parque Nacional da Serra do Itajaí
699 (PNSI 2015/2016) and Floresta Nacional de Ibirama (FNI 2016/2017). Continuous lines
700 represent observed L(r), and dashed lines represent the upper and lower confidence
701 envelope (95%) expected under Complete Spatial Randomness. n represents the number of
702 individuals included in each graphic.
Draft
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703 Figure 4. Standardized bivariate Ripley’s function (L12(r)) for seedling vs. reproductive
704 individuals plotted against radius distances (m) for Parque Nacional da Serra do Itajaí
705 (PNSI 2015/2016) and Floresta Nacional de Ibirama (FNI 2016/2017). Continuous lines
706 represent observed L12(r), and dashed lines represent the upper and lower confidence
707 envelope (95%) expected under Complete Spatial Independence. n represents the number of
708 seedling individuals/reproductive individuals included in each graphic.
Draft
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709 Figure 5. Coancestry coefficient ( ) plotted against distance classes (m) for seedling,
710 juvenile and reproductive individuals from Parque Nacional da Serra do Itajaí (PNSI
711 2015/2016) and Floresta Nacional de Ibirama (FNI 2016/2017). Continuous lines represent
712 observed , and dashed lines represent the upper and lower confidence envelope (95%). n
713 represents the number of individuals included in each graphic.
Draft
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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)
Draft
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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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