Intermediary disturbance increases tree diversity in riverine forest of southern Brazil

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The material is for personal use onlycommercial use is not permitted

Unauthorized reproduction transfer andor usemay be a violation of criminal as well as civil law

ISSN 0960-3115 Volume 19 Number 8

ORI GIN AL PA PER

Intermediary disturbance increases tree diversityin riverine forest of southern Brazil

Jean Carlos Budke bull Joao Andre Jarenkow bull

Ary Teixeira de Oliveira-Filho

Received 9 August 2009 Accepted 31 March 2010 Published online 16 April 2010 Springer Science+Business Media BV 2010

Abstract Floods are frequently associated with disturbance in structuring riverine forests

and they lead to environmental heterogeneity over space and time We evaluated the

distribution of tree species ecological groups species richness and diversity from the point

bar to the slope of a riverside forest in southern Brazil (Lat 30010S Long 52470W) to

analyze the effects of flooding on soil properties and forest structure A plot of 50 9 200 m

divided in five contiguous transects of 10 9 200 m parallel to the river was installed

where we measured all the individual trees with pbh C 15 cm A detailed topographical

and soil survey was carried out across the plot and indicated significant differences in

organic matter and most mineral nutrients through the topographical gradient The 1229

surveyed individuals belonged to 72 species and 35 families We used Partial CCA and

Species Indicator Analysis to observe the spatial distribution of species Both analyses

showed that species distribution was strongly related to the flooding gradient soil prop-

erties and also by space and pure spatial structuring of species and environmental variables

(spatial autocorrelation) although a large part of variation remains unexplained The

ecological groups of forest stratification plant dispersal and requirements for germination

indicated slight differences among frequently occasional and non-flooded transects

Species richness and diversity were higher at intermediate elevations and were associated

to the increased spatialndashtemporal environmental heterogeneity Across the plot the direct

Electronic supplementary material The online version of this article (doi101007s10531-010-9845-6)contains supplementary material which is available to authorized users

J C Budke (amp)Departamento de Ciencias Biologicas Universidade Regional Integrada do Alto Uruguai e dasMissoesmdashURI Campus de Erechim Av Sete de Setembro 1621 Erechim RS 99700-000 Brazile-mail jeanuriceredubr

J A JarenkowDepartamento de Botanica Universidade Federal do Rio Grande do Sul Av Bento Goncalves 9500Porto Alegre RS 91501-970 Brazil

A T de Oliveira-FilhoDepartamento de Botanica Universidade Federal de Minas Gerais Av Antonio Carlos 6627Belo Horizonte MG 31270-901 Brazil

123

Biodivers Conserv (2010) 192371ndash2387DOI 101007s10531-010-9845-6

Authors personal copy

influence of flooding on tree species distribution created a vegetation zonation that is

determined by predicted ecological traits

Keywords Disturbance Ecological groups Flooding regime Partial CCA Soil properties Species richness and diversity

Introduction

Natural disturbances play an important role in structuring plant communities by leading to

environmental heterogeneity over space and time at different scales Several studies have

demonstrated that disturbance and abiotic stress affect diversity especially at local-scale

(Ferreira and Stohlgren 1999 Weiher 2003) In riparian ecosystems flooding events are

the key factor in shaping community features either by a positive or a negative effect on

the ecosystemrsquos function according to the timing frequency and magnitude of such events

(Neiff 1990) Long-lasting floods represent a major stress and may result in species-poor

plant communities due to restricted productivity in the aquatic phase and high mortality of

non-adapted species (Pollock et al 1998 Guilherme et al 2004 Wittmann et al 2004) On

the other hand periodic and short floods may contribute to the input of nutrients which

increase productivity and diversity (Desilets and Houle 2005)

Once magnitude and duration of flooding are directly associated with local relief (eg

relative elevation inclination) many studies have investigated the relationships among

topography and correlated variables (eg chemical and textural soil properties sedimen-

tation rates) on the distribution of plant species and patterns of richness and diversity

(Oliveira-Filho et al 1994 Ferreira 2000 Rosales et al 2001 Damasceno-Junior et al

2005 Budke et al 2007)

In riparian systems with regular or predicted (seasonal) flood events as Amazonian and

Pantanal floodplains in South America plant species show different strategies to survive

floods including morphological anatomical and physiological adaptations and also phe-

nological timing for both reproductive and vegetative phases Ferreira et al (2009) has

demonstrated that species living in low-lying areas may be ecotypes originated from

surrounding non-flooded forests In contrast riverine forests with unpredictable flooding

pulses are frequently colonized by species of early successional stages of wide geo-

graphical distribution (Walker et al 1995 Budke et al 2007) On this hand Budke et al

(2008) observed that in low order rivers where water column oscillated due to a local and

concentrated rainy period the species richness increased along a gradient from frequently

to occasionally flooded stands Furthermore Robertson (2006) showed that predictability

of species occurrence across different rivers in the south-eastern US Coastal Plain was

directly related to the geomorphic dynamics intermediate level of stream energy (eg

flooding magnitude) and non-altered hydrological regimes

This ubiquitous difference of showing or not a temporally synchronous and expected

disturbance is one of the most interesting in eco-hydrological studies On this way the

structured view of the dynamic-equilibrium model (Huston 1994) shows different patches

from different seral stages result from spatial variation of disturbance frequencies If

disturbance frequencies vary over time a landscape could also contain such patches

(Pollock et al 1998) Indeed as expected in the intermediate disturbance model richness

would be higher when disturbance is neither too rare nor too frequent (Connell 1978)

In this work we focused on species richness and diversity of tree species in a riverside

sequence from the point bar to the lateral slope in a river with an unpredictable flooding

2372 Biodivers Conserv (2010) 192371ndash2387

123


regime The inundation regime also varies according to the topographical position fol-

lowing to frequently flooded forests to well drained non-flooded forests Furthermore we

investigated the relationships among tree component structure species and functional

groups distribution and spatialndashenvironmental variables We hypothesized that (1) as

flooding may gradually affect environmental heterogeneity richness and diversity will be

higher at intermediate elevations and directly associated with increased environmental

heterogeneity and (2) both species and functional groups will reflect variations in elevation

andor soil texture and chemistry

Methods

Study area

The study area is a forest remnant of ca 20 ha situated in the riparian fringes of the

Botucaraı river near its confluence with the Jacuı river (Lat 30010S Long 52470W)

(Budke et al 2007) The headwaters of the river lie in the southernmost extent (ca 650 m

asl) of the high planes region locally known as Planalto Meridional which geologically

is part of the Serra Geral formation made up of Cretaceous basalts originated from giant

lava flows that covered the sedimentary lowlands of the Parana Basin (Leinz 1949)

Downstream at its mid-course the Botucaraı river reaches the lowlands (ca 100 m asl)

and the topography is dominated by recently flood-deposited sedimentsmdashmeanders and

point bars At its lower course near the study area flooding events are enhanced by the

confluence with the stronger adjoining stream flow of the Jacuı river therefore promoting

lateral overflow According to Budke et al (2007) soils in such areas reflect not only the

geomorphic features from the basin but they also reflect flooding dynamics which fre-

quently produces non-stratified layers of fine gravel wood debris litter and sediment As a

consequence different soil profiles occur from well structured planosols in the riverside

slopes to recent deposited layers of sediment in the lowlands

The regional climate is moist subtropical without a regular dry season mean tem-

peratures ranges from 249C (hottest month) to 142C (coldest month) with high tem-

perature variation (absolutes values ranges from 42C in the summer to -3C in the

winter) mean annual rainfall is 1594 mm year-1 respectively (IPAGRO 1982) The

predominant soil is a Hydromorphic Planosol with typical stratified layers of depositional

sediments (Streck et al 2002)

Floods in the area are highly unpredictable because there is no marked seasonal rainy

period and rainfall is relatively well distributed throughout the year As a consequence

floods occur at any time of the year with duration of overflow periods varying from some

days to a few weeks (Budke et al 2008)

Regional vegetation is an extent of the Atlantic Forest Domain (Oliveira-Filho et al

2006) and includes overlapping patches of Seasonal Semideciduous Forests and Araucaria

Rain Forests at the river headwaters at Serra Geral formation Seasonal Semideciduous

Forests shows several genera of deciduous Fabaceae trees as Apuleia leiocarpa Myro-carpus frondosus Enterolobium contortisiliquun Parapiptadenia rigida and Erythrinafalcata as well as perennial ones which include Myrtaceae Lauraceae Sapotaceae and

Rubiaceae among others Canopy and emergent tree species can reach 25 m high

although mean vegetation stature is near 12ndash15 m In the lowlands of the river basin

Seasonal Semideciduous Forests is gradually changed by grasslands of the Pampa Domain

Biodivers Conserv (2010) 192371ndash2387 2373

123


(Oliveira-Filho et al 2006) and the river basin play a typical role of forest corridor toward

south reaching the Uruguay pampas as forest enclaves or galleries (Budke et al 2006)

Data collection

We carried out a tree survey in a 1 ha plot installed in a toposequence in the lowland areas

from the river margin to the lateral slope and therefore liable to different flooding regimes

The plot was divided in five 10 9 200 m transects and each transect was subdivided in

sampling units of 10 9 10 m All individual living trees having at least one stem and with

perimeter at breast height (pbh) C15 cm were sampled Voucher specimens of the different

species were collected prepared and lodged in the Herbarium ICN of the Universidade

Federal do Rio Grande do Sul (UFRGS)

A detailed topographic survey of the transects was carried out using a 10 m long water-

filled levelling hose 38 in a tape measure and a compass according to Cardoso and

Schiavini (2002) The resulting grid of vertical transects was used to produce contour maps

and to obtain the relative elevation of each sampling unit rather to the river To estimate

flooding frequency in each sampling unit we overlap their relative elevation to the

hydrometer records of the Jacuı river station (data calibrated according to topography)

Through Pulse 111 software (Neiff and Neiff 2003) we estimated the mean number of

floods per year from 1981 to 2004 and we used this variable as a pulse disturbance estimate

to sampling units (hereafter named flooding)

We collected samples of the topsoil (0ndash20 cm depth) from 15 sites distributed in dif-

ferent positions in such a way that its overall topographic variation was encompassed The

soil samples were kept in polyethylene bags and taken to the UFRGS Soil Laboratory for

chemical and textural analyses The variables were pH in water suspension levels of

potassium (K) phosphorus (P) calcium (Ca) magnesium (Mg) and aluminium (Al)

potential acidity (Al H) bases saturation (V) sum of bases (S) cation exchange

capacity (CEC) organic matter (OM) and levels of clay sand and silt All procedures

followed EMBRAPA (1997) protocol In those plots without a soil subsample we

extrapolated real values by distance-proportional mean of the closest plots (ter Braak

1995) We compared the means of each soil property among transects by using one-way

ANOVA (Zar 1996)

Data analysis

Phytosociological parameters of density frequency and dominance (derived from tree

basal area) were calculated to describe tree community structure (Mueller-Dombois and

Ellenberg 1974) Frequency distributions into classes of diameter for each transect were

prepared and one-way ANOVA was used to compare transects Classes of exponentially

increasing range were used for diameters to make up for the accentuated decline in tree

frequency towards larger diameters (Oliveira-Filho et al 2001)

We applied rarefaction curves for each transect in order to analyse the range of species

richness within the toposequence The rarefaction curve technique generates expected

number of species based on the individualsrsquo density and then providing statistical

assumptions to this comparison (Gotelli and Colwell 2001) We also compared Shannon

diversity indices (H0) of each transect by bootstrap resampling tests with the software

Multiv (Pillar 2006) and depicted diversity and topography in a regression model

To verify topographical ranges of species we used an Indicator Species AnalysismdashISA

(Dufrene and Legendre 1997) which is a direct analysis of association between flooding


123


and species distribution As the aim of this analysis was to assess the association between

species and topographyflooding it was used a non-hierarchical clustering procedure kmeans to produce k groups from the mean elevation of the original sampling units and by

using the resulting groups as the clustering factor required in the ISA (Dufrene and

Legendre 1997 Budke et al 2008) The analysis was performed in the PC-Ord program

(McCune and Mefford 1997)

We partitioned the variance of species distribution over the toposequence accounted by

spatial and environmental variables by successive partial Correspondence Canonical

Analysis (Borcard et al 1992) This approach combines three different matrices to

decompose all species variation in four components pure effect of environment pure

effect of spatial pattern combined variation of environment and spatial pattern and finally

unexplained variation Species assemblages from a determined position are affected by

surrounding sites because of contagious biotic process and environmental variables used to

describe biological processes are also neither randomly or uniformly spatially distributed

(Legendre 1993) In such case it is necessary to incorporate the spatial structure in the

modelling because the independence of observations is not respected (Legendre 1993) The

first matrix or species matrix included the abundances of all species with density C10

individuals The environmental matrix included initially all chemical and granulometric

figures the topographic variable (average elevation) and an ordinal (ranking) variable

labeled lsquolsquoflooding frequencyrsquorsquo We obtained the last variable directly from the topographic

survey summarizing flood occurrences and their intensity in each plot (Budke et al 2008)

The third matrix or spatial matrix included all terms of a polynomial function of geo-

graphical coordinates ie centers of each sampling unit and it was made by adding all

terms of a cubic trend surface regression

f x yeth THORN frac14 x y xy x2 y2 x2y xy2 x3 y3

According to Borcard et al (1992) this ensures the detection of more complex spatial

features as gaps or patches which require the quadratic and cubic terms of the coordinates

and their interactions

The variance partitioning proceeded in two steps First we extracted from each

explanatory matrix (environmental variables and spatial variables) all non-significant

variables by forward stepwise regression using Monte Carlo permutations (999 permuta-

tions P 005) with CANOCO 40 (ter Braack and Smilauer 1998) and performed two

canonical ordinations that are redundant in terms of explained variation over the species

data due to spatial structuring (Borcard et al 1992) Then two partial canonical analyses

were carried out (lsquoenvironmentalrsquo and lsquospatialrsquo) each of them constrained by one of the

sets of explanatory variables to determine the relative contribution of environmental and

spatial variables in accounting for species variation Final partition is possible by using the

sum of all canonical eigenvalues of two canonical ordinations constrained by one set of

explanatory variables and of two partial canonical ordinations each of them constrained

by one set of explanatory variables while controlling for the effect of the others (covari-

ables) (Borcard et al 1992 Titeux et al 2004)

To search for ecological differences in the toposequence we classified the species in

ecological groups of regeneration vertical distribution and dispersal We defined regen-

eration based on the categories proposed by Swaine and Whitmore (1988) The two main

levels are (a) lsquopioneerrsquo which includes the species showing an entirely heliophilous life

cycle a seed bank but no bank of juveniles and (b) lsquolate successional speciesrsquo which are

those able to germinate and establish under some degree of shade to form a bank of


123


juveniles The later was divided into (b1) lsquoshade-tolerantrsquo and (b2) lsquolight-demanding late

successional speciesrsquo which are better seen as the two sides of a continuum of solar

radiation required by the trees to lsquoreleasersquo the bank of juveniles (Oliveira-Filho et al 1994)

We defined the vertical distribution based on the strata commonly reached by the adult

individuals (a) small tree species (b) medium tree species and (c) tall tree species (see

Oliveira-Filho et al 1994) The dispersal was (a) zoochorous species with animal-med-

iated dispersal syndrome (b) anemochorous and hydrochorous those with mechanisms to

facilitate wind-dispersal or flotation and (c) autochorous those dispersed by free fall or

ballistic mechanisms (Pijl 1982) The classification of each species into the ecological

groups was based on observations during fieldwork from 2004 to 2005 and on scientific

literature (Barroso et al 1999 Budke et al 2005 2008) We tested the distribution of trees

into frequency classes according to the ecological group by KruskalndashWallis tests (Zar

1996)

Results

River corridor along the studied area has a typical meandering system with well-defined

geomorphic features The lowest sector encompasses the levee and depression which

interacts directly with river floods Next to these sites we identified the lower-slope the

middle-slope and the ridge according to the relative elevation to the river channel

(Table 1) and these sectors corresponded to our installed transects The lower slope veg-

etation is a sharp transition between lowland and upland forests and only large inundation

floods this sector whereas upland sites present slight differences in vegetation structure

due to absence of flooding and allied effects Nevertheless there is a distinct gradient of

organic matter (OM) clay and cation exchange capacity (CEC) being higher toward upper

sites as also showed by potential acidity (Al H) (Table 1) By other hand sum of bases

(S) and phosphorus contents (P) showed a tendency of decreasing toward upper sites

(Table 1) Furthermore the variance of some soil variables was quite high and demon-

strated the high heterogeneity across transects

The field inventory yielded a total of 1229 individuals belonging to 72 species and 35

families from which Myrtaceae and Fabaceae were the richest families with 11 species

followed by Rubiaceae and Sapotaceae with four species (Table S1) Although Myrtaceae

and Fabaceae presented the highest richness both families appeared generally with low

density or basal area The stand showed a forest of low stature with most individuals

between 5 and 7 m tall and few emergent trees reaching up 15 m The diameter-class

distribution of trees revealed typical inverted-J distribution with most individuals situated

in the first two classes (Fig 1) Across the toposequence higher density was found near the

river (Levee) followed by lower density values in the depression and again an increased

density through lower and middle slope On the other hand the ridgetop transect presented

the lowest density but an increased basal area (Table 2) and several trees with diameter

[40 cm Vertical distribution of trees also showed the predominance of medium-sized

individuals followed by a decreased proportion of small and emergent trees (Fig 2A)

The proportion of light-demanding trees was higher towards the upper sites (Fig 2B)

Pioneer trees presented an opposite pattern being more abundant in low sites Shade-

tolerant trees also showed an increased density at upper sites where flooding is restrict or

absent Within the dispersal groups zoochorous trees presented higher proportion in all

transects Autochorous and hydrochorous trees decreased toward the ridgetop whereas

anemochorous trees followed the inverse pattern (Fig 2C) These structural patterns


123


Tab

le1

So

ilv

aria

ble

so

ffi

ve

tran

sect

so

fri

ver

ine

fore

sto

nth

eB

otu

cara

ıri

ver

so

uth

ern

Bra

zil

Soil

var

iable

sL

evee

Dep

ress

ion

L-s

lope

M-s

lope

Rid

ge

FP

Rel

ativ

eel

evat

ion

(m)

38

plusmn0

5a

54

plusmn0

7a

85

plusmn2

3b

11

8plusmn

35

bc

13

6plusmn

37

c8

03

0

00

1

pH

(H2O

)4

8plusmn

04

47

plusmn0

44

7plusmn

04

47

plusmn0

64

7plusmn

06

08

50

93

ns

Pmdash

Meh

lich

(mg

dm

-3)

71

plusmn2

17

1plusmn

23

63

plusmn1

66

plusmn1

75

7plusmn

14

22

30

07

ns

K(m

gd

m-

3)

76

1plusmn

12

57

96

plusmn1

64

89

plusmn2

62

94

3plusmn

34

87

8plusmn

24

14

36

03

5n

s

Ca

(cm

olc

dm

-3)

62

plusmn4

36

8plusmn

44

7plusmn

47

61

plusmn4

57

plusmn3

73

19

05

2n

s

Mg

(cm

olc

dm

-3)

15

plusmn0

71

6plusmn

07

15

plusmn0

71

5plusmn

06

14

plusmn0

50

36

09

8n

s

Al

H

(cm

olc

dm

-3)

66

plusmn3

1a

71

plusmn3

ab8

5plusmn

4ab

96

plusmn5

5ab

10

plusmn4

2b

97

60

04

S(c

mo

lcd

m-

3)

8plusmn

48

87

plusmn5

18

1plusmn

46

84

plusmn5

17

4plusmn

41

27

70

59

ns

CE

C(c

mo

lcd

m-

3)

15

2plusmn

48

16

2plusmn

38

17

1plusmn

33

17

9plusmn

43

17

3plusmn

34

14

50

22

ns

V(

)5

57

plusmn1

71

49

7plusmn

20

24

59

plusmn2

46

45

5plusmn

23

64

18

plusmn2

07

40

60

39

ns

OM

()

26

plusmn1

1a

28

plusmn1

a3

2plusmn

1ab

37

plusmn1

1b

38

plusmn0

8b

22

9

00

01

Cla

y(

)1

37

plusmn2

4a

15

4plusmn

33

ab1

58

plusmn2

8ab

16

plusmn2

1b

15

5plusmn

17

ab2

49

00

4

San

d(

)2

0plusmn

74

23

1plusmn

22

24

2plusmn

10

12

23

plusmn7

52

23

plusmn6

28

91

00

6n

s

Sil

t(

)6

42

plusmn1

09

60

4plusmn

14

59

8plusmn

12

96

2plusmn

91

62

plusmn7

24

91

02

9n

s

Val

ues

are

mea

ns

plusmnst

and

ard

dev

iati

on

sfr

om

0to

20

cmd

epth

top

soil

sam

ple

s(N

=2

0fo

rea

chtr

anse

ct)

Dif

fere

nt

lett

ers

afte

rv

alu

esin

dic

ate

sign

ifica

nt

dif

fere

nce

sin

AN

OV

Ate

sts

(ns

=n

on

-sig

nifi

can

t)


123


shaped the physiognomic features of different sectors that varied according to the topo-

sequence and consequently in flooding regime The depression sector presented lower

density basal area and also low tree diameters whereas the levee portion presented high

density and basal area

Species distribution across the topographic gradient is presented in Table 3 according

to the Indicator Species Analysis Some species were clearly distributed from lowland to

medium sites as Eugenia uniflora Myrciaria tenella Eugenia uruguayensis whereas

others were restricted to upland areas as Chomelia obtusa and Cordia americana Many

species did not show a specific site distribution and occurred over a wide distribution range

as Gymnanthes concolor and Casearia sylvestris

The relative elevation of each transect reflects the pattern of flooding frequency and

duration in each site then spatial aggregation of trees may indicate preferences or

restriction on the establishment of some species Typical riverine species appeared near the

river margin as Pouteria gardneriana Guettarda uruguensis and others (Table 3) whereas

typical species of well-drained forests as Sorocea bonplandii Parapiptadenia rigida and

Cupania vernalis occurred frequently in the ridgetop transect Furthermore 13 species did

Fig 1 Diameter-class distributions of trees with pbh C 15 cm surveyed in five transects of riverine foreston the Botucaraı river southern Brazil Diameter-classes are used for increasing intervals (see lsquolsquoMethodsrsquorsquosection) Bars and ranges are means and 95 confidence intervals of 100 sampling units respectively

Table 2 Density (ind ha-1) dominance (m2 ha-1) mean height (m) and mean diameter (cm) for differenttransects of the riverside forest of the Botucaraı river southern Brazil

Transect AD ADo Height Diameter

Levee 1655 plusmn 467 a 3927 plusmn 268 a 62 plusmn 25 a 1761 plusmn 1697

Depression 1005 plusmn 369 b 198 plusmn 137 b 67 plusmn 21 b 161 plusmn 1194

L-slope 1120 plusmn 443 ab 229 plusmn 165 b 71 plusmn 26 b 1547 plusmn 1302

M-slope 1415 plusmn 438 a 274 plusmn 165 b 69 plusmn 25 b 1453 plusmn 98

Ridge 950 plusmn 294 b 282 plusmn 194 b 7 plusmn 24 b 1727 plusmn 1555

ANOVA F = 107 F = 129 F = 305 F = 35

Different letters after values indicate significant differences in t tests ( P 005 P 0001)

AD density ADo dominance


123


not present a topographic association due to wide distribution through the gradient On the

other hand the distinction among environmental and spatial effects showed that space

contributes significantly to the distribution of tree species (Fig 3) Environmental variables

selected by forward selection procedure (P 005) are summarized in Table 4 All geo-

graphical terms of the polynomial function were significant (P 005) during spatial CCA

and were add to the model The four CCA analyses provided the following results

1 CCA of the species matrix constrained by the environmental matrix sum of all

canonical eigenvalues = 0944 Monte Carlo tests for overall analysis F = 286

P 0001

2 CCA of the species matrix constrained by spatial matrix sum of all canonical

eigenvalues = 1017 Monte Carlo tests for overall analysis F = 359 P 0001

Fig 2 Ecological groups of vertical distribution (A) regeneration (B) and dispersal (C) in five transects ofriverine forest of Botucaraı river southern Brazil Pi pioneer Ld light-demanding St shade-tolerant Zoozoochorous Auto autochorous Ane anemochorous Hydro hydrochorous


123


3 Environmental partial CCA (after removing the effect of geographical matrix) sum of

all canonical eigenvalues = 0416 Monte Carlo tests for overall analysis F = 135

P 0001

Table 3 Indicator species analysis (ISA) performed for species with density C10 individuals sampled infive transects with 20 sampling units each Botucaraı river southern Brazil

Species Relative elevation IV exIV P

1 2 3 4 5

Lowland to medium sites

Eugenia uniflora 51 1 0 0 0 515 97 plusmn 37 0001

Myrciaria tenella 48 0 0 0 0 48 82 plusmn 35 0001

Eugenia uruguayensis 42 2 0 0 0 416 91 plusmn 37 0001

Sebastiania commersoniana 36 11 1 0 0 359 12 plusmn 41 0001

Guettarda uruguensis 30 15 1 1 5 303 149 plusmn 39 0001

Pouteria gardneriana 15 4 1 0 1 148 77 plusmn 33 003

Matayba elaeagnoides 9 2 27 0 0 266 102 plusmn 4 0001

Myrcia glabra 1 0 24 0 0 243 69 plusmn 35 0001

Eugenia ramboi 0 5 21 0 0 206 76 plusmn 35 0001

Myrsine lorentziana 0 1 18 4 0 176 71 plusmn 33 001

Apuleia leiocarpa 6 3 17 1 3 174 113 plusmn 37 006

Allophylus edulis 2 3 17 1 1 167 89 plusmn 35 004

Strychnos brasiliensis 1 2 16 1 0 161 81 plusmn 36 003

Faramea montevidensis 0 9 12 0 0 12 68 plusmn 32 008

Medium to upland sites

Chomelia obtusa 1 2 5 11 44 436 143 plusmn 38 0001

Cordia americana 2 1 1 21 38 381 149 plusmn 37 0001

Chrysophyllum marginatum 6 6 9 6 22 222 159 plusmn 35 005

Sorocea bonplandii 2 3 20 22 2 218 143 plusmn 38 004

Parapiptadenia rigida 1 1 0 7 17 173 92 plusmn 32 002

Cupania vernalis 0 0 1 14 4 14 72 plusmn 31 004

Celtis ehrenbergiana 0 0 1 12 5 122 72 plusmn 33 006

Without significant association

Gymnanthes concolor 15 5 21 5 14 207 177 plusmn 38 019

Casearia sylvestris 12 9 11 8 5 121 16 plusmn 35 090

Annona neosalicifolia 1 3 3 15 11 155 119 plusmn 36 014

Ruprechtia laxiflora 14 1 11 2 0 136 109 plusmn 36 019

Trichilia elegans 0 2 1 10 7 104 92 plusmn 36 027

Sebastiania brasiliensis 4 4 6 8 10 101 126 plusmn 36 077

Eugenia involucrata 0 1 10 10 0 10 79 plusmn 36 021

Luehea divaricata 2 1 8 2 6 85 87 plusmn 34 041

Machaerium paraguariense 2 1 0 5 8 82 79 plusmn 35 033

Ocotea pulchella 3 2 8 5 0 76 88 plusmn 35 054

Campomanesia xanthocarpa 0 1 8 1 4 76 73 plusmn 31 038

Myrocarpus frondosus 0 5 0 7 1 74 7 plusmn 35 035

Myrcianthes pungens 5 1 0 2 1 5 67 plusmn 33 064

IV = Observed Indicator Value exIV = Expected Indicator Value


123


4 Spatial CCA (after removing the effects of environmental matrix) sum of all


P 0001

The total variation in the species matrix (total inertia) was 4238 According to Borcard

et al (1992) the percentage of the total variation in the species matrix that accounted for

different steps (partition) is numbered as follows (a) non-spatial environmental variation

(0416 9 1004238 = 981) (b) spatially structured environmental variation [(0944ndash

0416) 9 1004238 or (1017ndash0489) 9 1004238 = 1246] (c) non-environmental

spatial variation (0489 9 1004238 = 1153) and (d) unexplained non-spatial variation

(100ndash338 = 662)

Biplots of environmental variables and species or environmental variables and sampling

units were depicted with the environmental partial analyses results (Fig 4) In this step

species distributions are purely based on speciesndashenvironment relationships The first two

axes accounted respectively for 268 (eigenvalue = 0112) and 181 (eigen-

value = 0075) of the speciesndashenvironment relationships and speciesndashenvironment corre-

lations for these axes were 0742 and 0649 (P 005) respectively The first four axes

accounted for 691 of speciesndashenvironment relationships Table 4 shows the intraset

correlations among variables and canonical coefficients with the first two axes The first

canonical axis was positively correlated with topography and several soil variables that are

Fig 3 Variation partitioning ofthe tree species matrix

Table 4 Intraset correlations among environmental variables selected for the model during lsquolsquoenviron-mentalrsquorsquo partial CCA of the species matrix and canonical coefficients of the first two axes

Topography Sand P K Al OM V CEC Flooding

Topography

Sand -002

P -008 0254

K 0588 -0003 0453

Al -0336 0368 -0023 -0552

OM 0625 0046 0226 0706 -0615

V 0304 0035 0323 0680 -0754 0769

CEC 0252 0159 0001 0322 -0315 0579 0574

Flooding -0804 -0042 0253 -0218 0040 -0422 0059 -0203

Axis 1 0700 0156 -008 0537 -0592 0814 0605 0632 -0678

Axis 2 0132 -0186 -0365 -0240 0361 -0185 -0618 0158 -0445

Environmental variables were selected by forward stepwise selection and included on the model if sig-nificant in Monte Carlo tests (P 005)


123


influenced by flooding events Percentages of organic matter saturation of bases and cation

exchange capacity where higher through upper sites whereas aluminium contents were

higher in lower areas Thus this environmental gradient may affect tree distribution pat-

terns by restricting or facilitating species establishment As related in the Indicator

Analysis (although not accounting for spatial patterns directly) typical species of flooding

areas occurred near the levee and depression and the zonation was sharp once frequent

species of well-drained areas occurred only in the middle slope and ridgetop Sampling

units (Fig 5) also appeared distributed according to the toposequence with some over-

lapping due to species distribution

Rarefaction curves of species revealed significant differences on the expected total

number of species in each transect with higher richness within the middle slope (Fig 6)

A regression model (Fig 6) fitted diversity in a second-order polynomial regression

(y = -00586x2 03594x 291 R2 = 077) that showed the same pattern

Discussion

Environmental and spatial patterns

Tree species distribution throughout the topographical gradient indicated that both envi-

ronmental and spatial features were particularly important in predicting species and

community patterns This agrees with the well-know influence of geomorphic features and

hydrological regimes on riparian forests over different temporal and spatial scales

(Tabacchi et al 1998 Turner et al 2004 Desilets and Houle 2005) even though dis-

tinctions between environmental and spatial effects remain poorly studied (Titeux et al

Fig 4 Ordination biplotdepicting the two axes of theenvironmental partial CCA ofsampling units in a riverine forestin southern Brazil Eachsampling unit was identified bydifferent symbols according tothe respective transectEnvironmental variables arerepresented by their acronyms(see Table S1)


123


2004) Here we employed a routine to partialling out the spatial effects on the analysis of

speciesndashenvironment relationships that also highlight the spatial component embedded in

such analysis (Legendre 1993) Once several biotic processes as growth mortality dis-

persal and predation influence the observed distributions of organisms (resulting in spatial

correlation) or if their distributions are dependent on explanatory variables which are

Fig 5 Ordination biplot depicting the two axes of the environmental partial CCA of species of a riverineforest in southern Brazil Species and environmental variables are represented by their acronyms (seeTable S1)

Fig 6 Rarefaction curves of tree species and Shannon diversity indices from five transects of riverine foreston the Botucaraı river southern Brazil Sampling units are representing different transects


123


themselves spatially structured (Legendre 1993 Titeux et al 2004) spatial structuring is

an intrinsic component of ecosystems In our analysis lsquopurersquo spatial trends were more

attributed to species distribution than to lsquopurersquo environmental effects which link conta-

gious biological processes as important to the tree species distribution Furthermore

species and environmental data have a reasonable proportion of similar spatial structuring

identified by the largest proportion on the species variation due to spatially structured

environmental variation (1246) According to Borcard et al (1992) species and envi-

ronmental variables have in this case the same response to some common underlying

causes as the topographicndashflooding gradient In fact several studies have demonstrated the

direct effect of wetting and desiccation processes on both mineralogy and microbial

ecology of the sediment including nutrient dynamics (Baldwin and Mitchell 2000)

Once sediment or soils are submerged the inundation leads to a decrease in oxygen

contents and then resulting in progressive anaerobic conditions Rapid cycling of litter may

occur due to an increase on microbial activity which generates pulses on nutrient contents

and finally result in highly productive systems (Baldwin and Mitchell 2000) However a

negative effect is the rapid oxygen consumption which quickly leads to soil hypoxia or

anoxia When flood ends the anaerobic zones of sediments are newly oxygenated and

microbiota is replaced gradually to a new phase

Other spatially structured variables are sediment deposition and litter displacement

which are not covered in our study As demonstrated in lsquovarzearsquo forests of Amazonia

(Wittmann et al 2004) sediment deposition decrease toward upper sites and species

colonizing such lower areas show specific adaptations to the new site conditions regarding

to adventitious roots that probably offer mechanical support (Parolin et al 2004 Wittmann

et al 2004) However litter removal or deposition including seed bank may affect

directly species distribution once flooding and allied effects reallocate litter and seeds

among sites (Johansson et al 1996) Moreover studies have showed that flooding timing

frequency and magnitude can be used as indicators of sapling zonation on floodplain

forests (Vreugdenhil et al 2006)

All these processes are included in the unmeasured variables or spatially structuring

processes that have been missed by the geographical terms (Titeux et al 2004) and

accounted to the far unexplained variation (662) As also stressed by these authors the

stochastic spacendashtime fluctuations of each population the lsquounsaturationrsquo pattern (some

species do not use all suitable habitats) and species recording in not appropriated spatial

scales contribute to this unexplained variation too Notwithstanding occurrence data or

species abundances are often noisy (ter Braak 1995) and widespread in ecological studies

(Borcard et al 1992 Titeux et al 2004)

Richness and diversity patterns

Significant transitions occurred from the levee and depression to the following lower slope

transect regarding to stand structure and ecological groups Inversions on the proportion of

pioneershade-tolerant trees and auto-hydrochorous to anemochorous trees occurred in that

small transition and affected not only ecological groups but also species occurrences As a

consequence this zonation transect may consist spatially as a boundary for tolerant and

intolerant trees with regarding to flooding In fact few species occurred over the entire

flooding gradient and the lower slope also appears as an edge for several species

In a temporal scale the lower slope area will probably present more heterogeneous

spans in flooding events and it may consist in the most heterogeneous temporalndashspatial

sector across the topographic gradient which agree with the findings of Pollock et al


123


(1998) from wetlands with different flooding regimes In the structured view of the

dynamic-equilibrium model (Huston 1994) different patches from different seral stages

result from spatial variation of disturbance frequencies If disturbance frequencies vary

over time a landscape could also contain patches of different seral stages (Pollock et al

1998) These authors used that assumption in a model with temporally synchronous dis-

turbance and found that at the community-scale level the results supported many pre-

dictions of the dynamic-equilibrium model especially regarding to species richness

In our study there are two major factors related to disturbance frequency First and

foremost is that once river floods are unpredictable due to a hydrological regime that varies

with occasional long-rainy periods temporal heterogeneity should be higher than in sea-

sonal predicted flood areas and second microtopography must create spatial heterogeneity

during floods events in the local area However well-drained upper sites are probably more

affected by inherent community processes as gap-phase dynamics and direct supply rates

of light (Stevens and Carson 2002) As related by Worbes et al (1992) and Parolin (2001)

hundreds of tree species with different phenological and other ecological traits grow in

seasonal flooded forests In such cases the cyclic alternation on floods and droughts drove

species to life history behavioral and morphological adaptations (Lytle and Poff 2004)

But in the case of unpredictable floods and droughts as assigned in our study bet-hedging

strategies might be evolved for example by persistent seed bank or asynchronous

reproductive phenologies (Brock 2003) although there are no conclusive studies related to

this theory (Lytle and Poff 2004)

Allowed by a transition in the ecological groups from the lower sites to the upper ones

species richness has a maximum at the lower slope transect probably due to higher het-

erogeneity in disturbance events (space and time) and correlated variables As reported by

Desilets and Houle (2005) the spatial gradient provides some evidences for stress toler-

ance and competition as factors structuring species distribution across the topographicndash

flooding gradient also boosted by an unpredictable pattern of floods that vary in frequency

timing and magnitude Lower sectors showed predicted ecological groups already

described for these areas (Budke et al 2007 2008 Junk et al 1989 Lytle and Poff 2004)

and expected structuring changes also occurred toward upper sites where the proportion of

shade-tolerant and small trees increased as well as anemochorous trees

In summary spatialndashtemporal and environmental variables are arranging tree species

distribution across the toposequence of our study site Furthermore predicted ecological

groups reflected the dynamics of disturbance in the topographicndashhydrological gradient

Species richness and diversity also reflected such pattern and were higher in the mid-sector

where occasional floods should prevent competitive exclusion and generate high envi-

ronmental heterogeneity

Acknowledgements We are grateful to the Programa de Pos-Graduacao em Botanica of the UniversidadeFederal do Rio Grande do SulmdashUFRGS for the opportunity to undertake this study and to CAPES Agencyfor the scholarship granted to the first author Our special thanks to Diogo lsquolsquoBagualrsquorsquo Lindenmaier forfieldwork assistance and to Ricardo Braga Eduardo Rossi and colleagues of the Laboratorio de Fitoeco-logiamdashUFRGS for critiques and suggestions We also appreciated the reviewing efforts of anonymouscontributors for providing useful comments to the manuscript

References

Baldwin DS Mitchell AM (2000) The effects of drying and re-flooding on the sediment and soil nutrientdynamics of lowland river-floodplain systems a synthesis Regul River 16457ndash467 doi1010021099-1646


123


Barroso GM Morim MP Peixoto AL Ichaso CLF (1999) Frutos e sementes morfologia aplicada a si-stematica de dicotiledoneas Editora UFV Vicosa

Borcard D Legendre P Drapeau P (1992) Partialling out the spatial component of ecological variationEcology 731045ndash1055 doi1010292006WR005044

Brock MA (2003) Drought and aquatic community resilience the role of eggs and seeds in sediments oftemporary wetlands Freshw Biol 481207ndash1218 doi101046j1365-2427200301083x

Budke JC Athayde EA Giehl ELH Zachia RA Eisinger SM (2005) Composicao florıstica e estrategias dedispersao de especies lenhosas em uma floresta ribeirinha arroio Passo das Tropas Santa Maria RSBrasil Iheringia Bot 6017ndash24

Budke JC Jarenkow JA Oliveira-Filho AT Lindenmaier DS (2006) Padroes de riqueza e diversidade emrios de pequeno porte In Mariath JEA Santos RP (eds) Os avancos da botanica no inıcio do seculoXXI SBB Porto Alegre

Budke JC Jarenkow JA Oliveira-Filho AT (2007) Relationships between tree component structuretopography and soils of a riverine forest Rio Botucaraı southern Brazil Plant Ecol 189187ndash200 doi101007s11258-006-9174-8

Budke JC Jarenkow JA Oliveira-Filho AT (2008) Tree community features of two stands of riverine forestunder different flooding regimes in southern Brazil Flora 203162ndash174 doi101016jflora200703001

Cardoso E Schiavini I (2002) Relacao entre distribuicao de especies arboreas e topografia em um gradienteflorestal na Estacao Ecologica do Panga (Uberlandia MG) Rev Bras Bot 25277ndash289

Connell JH (1978) Diversity in tropical rain forests and coral reefs Science 1991302ndash1310 doi101126science19943351302

Damasceno-Junior GA Semir J Santos FAM Leitao-Filho HF (2005) Structure distribution of species andinundation in a riparian forest of Rio Paraguai Pantanal Brazil Flora 200119ndash135 doi101016jflora200409002

Desilets P Houle G (2005) Effects of resource availability and heterogeneity on the slope of the species-areacurve along a floodplain-upland gradient J Veg Sci 16487ndash496 doi1016581100-9233

Dufrene M Legendre P (1997) Species assemblages and indicator species the need for a flexible asym-metrical approach Ecol Monogr 67345ndash366

EMBRAPA (1997) Manual de metodos de analises de solo Empresa Brasileira de Pesquisa Agropecuariaand Centro Nacional de Pesquisas de Solos Rio de Janeiro

Ferreira LV (2000) Effects of flooding duration on species richness floristic composition and forest structurein river margin habitat in Amazonian blackwater floodplain forests implications for future design ofprotected areas Biodivers Conserv 91ndash14 doi101023A1008989811637

Ferreira LV Stohlgren TJ (1999) Effects of river level fluctuation on plant species richness diversity anddistribution in a floodplain forest in Central Amazonia Oecologia 120582ndash587 doi101007s004420050893

Ferreira C Piedade MTF Franco AC Goncalves JFC Junk WJ (2009) Adaptive strategies to tolerateprolonged flooding in seedlings of floodplain and upland populations of Himatanthus sucuuba aCentral Amazon tree Aquat Bot 90246ndash252 doi101016jaquabot200810006

Gotelli NJ Colwell RK (2001) Quantifying biodiversity procedures and pitfalls in the measurement andcomparison of species richness Ecol Lett 4379ndash391 doi101046j1461-0248200100230x

Guilherme FAG Oliveira-Filho AT Appolinario V Bearzoti E (2004) Effects of flooding regime andwoody bamboos on tree community dynamics in a section of tropical semideciduous forest in south-eastern Brazil Plant Ecol 17419ndash36 doi101023BVEGE000004605197752cd

Huston M (1994) Biological diversity the coexistence of species in changing landscapes CambridgeUniversity Press Cambridge

IPAGRO (1982) Atlas agroclimatico do Rio Grande do Sul Pallotti Porto AlegreJohansson ME Nilsson C Nilsson E (1996) Do rivers function as corridors for plant dispersal J Veg Sci

7593ndash598Junk WJ Bayley PB Sparks RE (1989) The flood pulse concept in river-floodplain systems Can J Fish

Aquat Sci 106110ndash127Legendre P (1993) Spatial autocorrelationmdashtrouble or new paradigm Ecology 741659ndash1673Leinz V (1949) Contribuicao a geologia dos derrames basalticos do Rio Grande do Sul Bol Fac Filos Let

581ndash55Lytle DA Poff NL (2004) Adaptation to natural flow regimes Trends Ecol Evol 1994ndash100 doi

101016jtree200310002McCune B Mefford MJ (1997) PCndashORD Multivariate analysis of ecological data version 436 MjM

Software Design Glaneden BeachMueller-Dombois D Ellenberg H (1974) Aims and methods of vegetation ecology John Wiley New York


123


Neiff JJ (1990) Ideas para la interpretacion ecologica del Parana Interciencia 15424ndash441Neiff JJ Neiff M (2003) Pulso software para analisis de fenomenos recurrentes httpwwwneiffcom

Cited 25 May 2009Oliveira-Filho AT Vilela EA Gavilanes ML Carvalho DA (1994) Effect of flooding regime and understory

bamboos on the physiognomy and tree species composition of a tropical semideciduous forest in south-eastern Brazil Vegetatio 11399ndash124

Oliveira-Filho AT Curi N Vilela EA Carvalho DA (2001) Variation in tree community composition andstructure with changes in soil properties within a fragment of semideciduous forest in south-easternBrazil Edinb J Bot 58139ndash158 doi101017S0960428601000506

Oliveira-Filho AT Jarenkow JA Rodal MJN (2006) Floristic relationships of seasonally dry forests ofeastern South America based on tree species distribution patterns In Pennington RT Ratter JA LewisGP (eds) Neotropical savannas and dry forests plant diversity biogeography and conservation CRCPress Boca Raton

Parolin P (2001) Morphological and physiological adjustments to waterlogging and drought in seedlings ofAmazonian floodplain trees Oecologia 128326ndash335 doi101007s004420100660

Parolin P de Simone O Haase K Waldhoff D Rottenberger S Kuhn U Kesselmeier J Kleiss B SchmidtW Piedade MTF Junk WJ (2004) Central Amazonian floodplain forests tree adaptations in a pulsingsystem Bot Rev 70357ndash380 doi1016630006-8101(2004)070[0357CAFFTA]20CO2

Pijl L (1982) Principles of dispersal in higher plants Springer New YorkPillar VD (2006) Multivariate exploratory analysis randomization testing and bootstrap resampling version

2320 Departamento de Ecologia UFRGS Porto AlegrePollock MM Naiman RJ Hanley TA (1998) Plant species richness in riparian wetlandsmdasha test of biodi-

versity theory Ecology 7994ndash105Robertson KM (2006) Distributions of tree species along point bars of 10 rivers in the south-eastern US

Coastal Plain J Biogeogr 33121ndash132 doi101111j1365-2699200501371xRosales J Petts G Knab-Vispo C (2001) Ecological gradients within the riparian forests of the lower Caura

river Venezuela Plant Ecol 152101ndash118 doi101023A1011411020040Stevens MHH Carson WP (2002) Resource quantity not resource heterogeneity maintains plant diversity

Ecol Lett 5420ndash426 doi101046j1461-0248200200333xStreck EV Kampf N Dalmolin RSD Klamt E Nascimento PC Schneider P (2002) Solos do Rio Grande do

Sul EMATERRS and UFRGS Porto AlegreSwaine MD Whitmore TC (1988) On the definition of ecological species groups in tropical rain forests

Vegetatio 7581ndash86Tabacchi E Correll DL Hauer R Pinay G Planty-Tabacchi AM Wissmar R (1998) Development

maintenance and role of riparian vegetation in the river landscape Freshw Biol 40497ndash516 doi101046j1365-2427199800381x

ter Braack CJF Smilauer P (1998) Canoco reference manual and userrsquos guide to Canoco for Windowssoftware for canonical community ordination (version 40) Microcomputer Power Ithaca

ter Braak CJF (1995) Ordination In Jongman RHG ter Braak CJF van Togeren OFR (eds) Data analysis incommunity and landscape ecology Cambridge University Press New York

Titeux N Dufrene M Jacob JP Paquay M Defourny P (2004) Multivariate analysis of fine-scale breedingbird atlas using a geographical information system and partial canonical correspondence analysisenvironmental and spatial effects J Biogeogr 311841ndash1856 doi101111j1365-2699200401125x

Turner MG Gergel SE Dixon MD Miller JR (2004) Distribution and abundance of trees in floodplainforests of the Wisconsin river environmental influences at different scales J Veg Sci 15729ndash738

Vreugdenhil SJ Kramer K Pelsma T (2006) Effects of flooding duration frequency and depth on thepresence of saplings of six woody species in north-west Europe For Ecol Manage 23647ndash55 doi101016jforeco200608329

Walker KF Sheldon F Puckridge JT (1995) A perspective on dryland river ecosystems Regul River 1185ndash104 doi101002rrr3450110108

Weiher E (2003) Species richness along multiple gradients testing a general multivariate model in oaksavannas Oikos 101311ndash316 doi101034j1600-0706200312216x

Wittmann F Junk WJ Piedade MTF (2004) The varzea forests in Amazonia flooding and the highlydynamic geomorphology interact with natural forest succession For Ecol Manage 196199ndash212 doi101016jforeco200402060

Worbes M Klinge H Revilla JD Martius C (1992) On the dynamics floristic subdivision and geographicaldistribution of Varzea forests in Central Amazonia J Veg Sci 3553ndash564

Zar JH (1996) Biostatistical analysis Prentice-Hall New Jersey


123


ORI GIN AL PA PER

Intermediary disturbance increases tree diversityin riverine forest of southern Brazil

Jean Carlos Budke bull Joao Andre Jarenkow bull

Ary Teixeira de Oliveira-Filho

Received 9 August 2009 Accepted 31 March 2010 Published online 16 April 2010 Springer Science+Business Media BV 2010

Abstract Floods are frequently associated with disturbance in structuring riverine forests

and they lead to environmental heterogeneity over space and time We evaluated the

distribution of tree species ecological groups species richness and diversity from the point

bar to the slope of a riverside forest in southern Brazil (Lat 30010S Long 52470W) to

analyze the effects of flooding on soil properties and forest structure A plot of 50 9 200 m

divided in five contiguous transects of 10 9 200 m parallel to the river was installed

where we measured all the individual trees with pbh C 15 cm A detailed topographical

and soil survey was carried out across the plot and indicated significant differences in

organic matter and most mineral nutrients through the topographical gradient The 1229

surveyed individuals belonged to 72 species and 35 families We used Partial CCA and

Species Indicator Analysis to observe the spatial distribution of species Both analyses

showed that species distribution was strongly related to the flooding gradient soil prop-

erties and also by space and pure spatial structuring of species and environmental variables

(spatial autocorrelation) although a large part of variation remains unexplained The

ecological groups of forest stratification plant dispersal and requirements for germination

indicated slight differences among frequently occasional and non-flooded transects

Species richness and diversity were higher at intermediate elevations and were associated

to the increased spatialndashtemporal environmental heterogeneity Across the plot the direct

Electronic supplementary material The online version of this article (doi101007s10531-010-9845-6)contains supplementary material which is available to authorized users

J C Budke (amp)Departamento de Ciencias Biologicas Universidade Regional Integrada do Alto Uruguai e dasMissoesmdashURI Campus de Erechim Av Sete de Setembro 1621 Erechim RS 99700-000 Brazile-mail jeanuriceredubr

J A JarenkowDepartamento de Botanica Universidade Federal do Rio Grande do Sul Av Bento Goncalves 9500Porto Alegre RS 91501-970 Brazil

A T de Oliveira-FilhoDepartamento de Botanica Universidade Federal de Minas Gerais Av Antonio Carlos 6627Belo Horizonte MG 31270-901 Brazil

123

Biodivers Conserv (2010) 192371ndash2387DOI 101007s10531-010-9845-6





Introduction










































123










Methods

Study area


































123




Data collection



























ANOVA (Zar 1996)

Data analysis
















123

















































123














1996)

Results


































123


Tab

le1

So

ilv

aria

ble

so

ffi

ve

tran

sect

so

fri

ver

ine

fore

sto

nth

eB

otu

cara

ıri

ver

so

uth

ern

Bra

zil

Soil

var

iable

sL

evee

Dep

ress

ion

L-s

lope

M-s

lope

Rid

ge

FP

Rel

ativ

eel

evat

ion

(m)

38

plusmn0

5a

54

plusmn0

7a

85

plusmn2

3b

11

8plusmn

35

bc

13

6plusmn

37

c8

03

0

00

1

pH

(H2O

)4

8plusmn

04

47

plusmn0

44

7plusmn

04

47

plusmn0

64

7plusmn

06

08

50

93

ns

Pmdash

Meh

lich

(mg

dm

-3)

71

plusmn2

17

1plusmn

23

63

plusmn1

66

plusmn1

75

7plusmn

14

22

30

07

ns

K(m

gd

m-

3)

76

1plusmn

12

57

96

plusmn1

64

89

plusmn2

62

94

3plusmn

34

87

8plusmn

24

14

36

03

5n

s

Ca

(cm

olc

dm

-3)

62

plusmn4

36

8plusmn

44

7plusmn

47

61

plusmn4

57

plusmn3

73

19

05

2n

s

Mg

(cm

olc

dm

-3)

15

plusmn0

71

6plusmn

07

15

plusmn0

71

5plusmn

06

14

plusmn0

50

36

09

8n

s

Al

H

(cm

olc

dm

-3)

66

plusmn3

1a

71

plusmn3

ab8

5plusmn

4ab

96

plusmn5

5ab

10

plusmn4

2b

97

60

04

S(c

mo

lcd

m-

3)

8plusmn

48

87

plusmn5

18

1plusmn

46

84

plusmn5

17

4plusmn

41

27

70

59

ns

CE

C(c

mo

lcd

m-

3)

15

2plusmn

48

16

2plusmn

38

17

1plusmn

33

17

9plusmn

43

17

3plusmn

34

14

50

22

ns

V(

)5

57

plusmn1

71

49

7plusmn

20

24

59

plusmn2

46

45

5plusmn

23

64

18

plusmn2

07

40

60

39

ns

OM

()

26

plusmn1

1a

28

plusmn1

a3

2plusmn

1ab

37

plusmn1

1b

38

plusmn0

8b

22

9

00

01

Cla

y(

)1

37

plusmn2

4a

15

4plusmn

33

ab1

58

plusmn2

8ab

16

plusmn2

1b

15

5plusmn

17

ab2

49

00

4

San

d(

)2

0plusmn

74

23

1plusmn

22

24

2plusmn

10

12

23

plusmn7

52

23

plusmn6

28

91

00

6n

s

Sil

t(

)6

42

plusmn1

09

60

4plusmn

14

59

8plusmn

12

96

2plusmn

91

62

plusmn7

24

91

02

9n

s

Val

ues

are

mea

ns

plusmnst

and

ard

dev

iati

on

sfr

om

0to

20

cmd

epth

top

soil

sam

ple

s(N

=2

0fo

rea

chtr

anse

ct)

Dif

fere

nt

lett

ers

afte

rv

alu

esin

dic

ate

sign

ifica

nt

dif

fere

nce

sin

AN

OV

Ate

sts

(ns

=n

on

-sig

nifi

can

t)


123


























ANOVA F = 107 F = 129 F = 305 F = 35




123










P 0001





123




P 0001



1 2 3 4 5








































123




P 0001







(100ndash338 = 662)













Topography

Sand -002

P -008 0254

K 0588 -0003 0453

Al -0336 0368 -0023 -0552

OM 0625 0046 0226 0706 -0615

V 0304 0035 0323 0680 -0754 0769

CEC 0252 0159 0001 0322 -0315 0579 0574

Flooding -0804 -0042 0253 -0218 0040 -0422 0059 -0203

Axis 1 0700 0156 -008 0537 -0592 0814 0605 0632 -0678

Axis 2 0132 -0186 -0365 -0240 0361 -0185 -0618 0158 -0445



123















Discussion










123










123


















































123








































References



123




























123





























123





Introduction










































123










Methods

Study area


































123




Data collection



























ANOVA (Zar 1996)

Data analysis
















123

















































123














1996)

Results


































123


Tab

le1

So

ilv

aria

ble

so

ffi

ve

tran

sect

so

fri

ver

ine

fore

sto

nth

eB

otu

cara

ıri

ver

so

uth

ern

Bra

zil

Soil

var

iable

sL

evee

Dep

ress

ion

L-s

lope

M-s

lope

Rid

ge

FP

Rel

ativ

eel

evat

ion

(m)

38

plusmn0

5a

54

plusmn0

7a

85

plusmn2

3b

11

8plusmn

35

bc

13

6plusmn

37

c8

03

0

00

1

pH

(H2O

)4

8plusmn

04

47

plusmn0

44

7plusmn

04

47

plusmn0

64

7plusmn

06

08

50

93

ns

Pmdash

Meh

lich

(mg

dm

-3)

71

plusmn2

17

1plusmn

23

63

plusmn1

66

plusmn1

75

7plusmn

14

22

30

07

ns

K(m

gd

m-

3)

76

1plusmn

12

57

96

plusmn1

64

89

plusmn2

62

94

3plusmn

34

87

8plusmn

24

14

36

03

5n

s

Ca

(cm

olc

dm

-3)

62

plusmn4

36

8plusmn

44

7plusmn

47

61

plusmn4

57

plusmn3

73

19

05

2n

s

Mg

(cm

olc

dm

-3)

15

plusmn0

71

6plusmn

07

15

plusmn0

71

5plusmn

06

14

plusmn0

50

36

09

8n

s

Al

H

(cm

olc

dm

-3)

66

plusmn3

1a

71

plusmn3

ab8

5plusmn

4ab

96

plusmn5

5ab

10

plusmn4

2b

97

60

04

S(c

mo

lcd

m-

3)

8plusmn

48

87

plusmn5

18

1plusmn

46

84

plusmn5

17

4plusmn

41

27

70

59

ns

CE

C(c

mo

lcd

m-

3)

15

2plusmn

48

16

2plusmn

38

17

1plusmn

33

17

9plusmn

43

17

3plusmn

34

14

50

22

ns

V(

)5

57

plusmn1

71

49

7plusmn

20

24

59

plusmn2

46

45

5plusmn

23

64

18

plusmn2

07

40

60

39

ns

OM

()

26

plusmn1

1a

28

plusmn1

a3

2plusmn

1ab

37

plusmn1

1b

38

plusmn0

8b

22

9

00

01

Cla

y(

)1

37

plusmn2

4a

15

4plusmn

33

ab1

58

plusmn2

8ab

16

plusmn2

1b

15

5plusmn

17

ab2

49

00

4

San

d(

)2

0plusmn

74

23

1plusmn

22

24

2plusmn

10

12

23

plusmn7

52

23

plusmn6

28

91

00

6n

s

Sil

t(

)6

42

plusmn1

09

60

4plusmn

14

59

8plusmn

12

96

2plusmn

91

62

plusmn7

24

91

02

9n

s

Val

ues

are

mea

ns

plusmnst

and

ard

dev

iati

on

sfr

om

0to

20

cmd

epth

top

soil

sam

ple

s(N

=2

0fo

rea

chtr

anse

ct)

Dif

fere

nt

lett

ers

afte

rv

alu

esin

dic

ate

sign

ifica

nt

dif

fere

nce

sin

AN

OV

Ate

sts

(ns

=n

on

-sig

nifi

can

t)


123


























ANOVA F = 107 F = 129 F = 305 F = 35




123










P 0001





123




P 0001



1 2 3 4 5








































123




P 0001







(100ndash338 = 662)













Topography

Sand -002

P -008 0254

K 0588 -0003 0453

Al -0336 0368 -0023 -0552

OM 0625 0046 0226 0706 -0615

V 0304 0035 0323 0680 -0754 0769

CEC 0252 0159 0001 0322 -0315 0579 0574

Flooding -0804 -0042 0253 -0218 0040 -0422 0059 -0203

Axis 1 0700 0156 -008 0537 -0592 0814 0605 0632 -0678

Axis 2 0132 -0186 -0365 -0240 0361 -0185 -0618 0158 -0445



123















Discussion










123










123


















































123








































References



123




























123





























123










Methods

Study area


































123




Data collection



























ANOVA (Zar 1996)

Data analysis
















123

















































123














1996)

Results


































123


Tab

le1

So

ilv

aria

ble

so

ffi

ve

tran

sect

so

fri

ver

ine

fore

sto

nth

eB

otu

cara

ıri

ver

so

uth

ern

Bra

zil

Soil

var

iable

sL

evee

Dep

ress

ion

L-s

lope

M-s

lope

Rid

ge

FP

Rel

ativ

eel

evat

ion

(m)

38

plusmn0

5a

54

plusmn0

7a

85

plusmn2

3b

11

8plusmn

35

bc

13

6plusmn

37

c8

03

0

00

1

pH

(H2O

)4

8plusmn

04

47

plusmn0

44

7plusmn

04

47

plusmn0

64

7plusmn

06

08

50

93

ns

Pmdash

Meh

lich

(mg

dm

-3)

71

plusmn2

17

1plusmn

23

63

plusmn1

66

plusmn1

75

7plusmn

14

22

30

07

ns

K(m

gd

m-

3)

76

1plusmn

12

57

96

plusmn1

64

89

plusmn2

62

94

3plusmn

34

87

8plusmn

24

14

36

03

5n

s

Ca

(cm

olc

dm

-3)

62

plusmn4

36

8plusmn

44

7plusmn

47

61

plusmn4

57

plusmn3

73

19

05

2n

s

Mg

(cm

olc

dm

-3)

15

plusmn0

71

6plusmn

07

15

plusmn0

71

5plusmn

06

14

plusmn0

50

36

09

8n

s

Al

H

(cm

olc

dm

-3)

66

plusmn3

1a

71

plusmn3

ab8

5plusmn

4ab

96

plusmn5

5ab

10

plusmn4

2b

97

60

04

S(c

mo

lcd

m-

3)

8plusmn

48

87

plusmn5

18

1plusmn

46

84

plusmn5

17

4plusmn

41

27

70

59

ns

CE

C(c

mo

lcd

m-

3)

15

2plusmn

48

16

2plusmn

38

17

1plusmn

33

17

9plusmn

43

17

3plusmn

34

14

50

22

ns

V(

)5

57

plusmn1

71

49

7plusmn

20

24

59

plusmn2

46

45

5plusmn

23

64

18

plusmn2

07

40

60

39

ns

OM

()

26

plusmn1

1a

28

plusmn1

a3

2plusmn

1ab

37

plusmn1

1b

38

plusmn0

8b

22

9

00

01

Cla

y(

)1

37

plusmn2

4a

15

4plusmn

33

ab1

58

plusmn2

8ab

16

plusmn2

1b

15

5plusmn

17

ab2

49

00

4

San

d(

)2

0plusmn

74

23

1plusmn

22

24

2plusmn

10

12

23

plusmn7

52

23

plusmn6

28

91

00

6n

s

Sil

t(

)6

42

plusmn1

09

60

4plusmn

14

59

8plusmn

12

96

2plusmn

91

62

plusmn7

24

91

02

9n

s

Val

ues

are

mea

ns

plusmnst

and

ard

dev

iati

on

sfr

om

0to

20

cmd

epth

top

soil

sam

ple

s(N

=2

0fo

rea

chtr

anse

ct)

Dif

fere

nt

lett

ers

afte

rv

alu

esin

dic

ate

sign

ifica

nt

dif

fere

nce

sin

AN

OV

Ate

sts

(ns

=n

on

-sig

nifi

can

t)


123


























ANOVA F = 107 F = 129 F = 305 F = 35




123










P 0001





123




P 0001



1 2 3 4 5








































123




P 0001







(100ndash338 = 662)













Topography

Sand -002

P -008 0254

K 0588 -0003 0453

Al -0336 0368 -0023 -0552

OM 0625 0046 0226 0706 -0615

V 0304 0035 0323 0680 -0754 0769

CEC 0252 0159 0001 0322 -0315 0579 0574

Flooding -0804 -0042 0253 -0218 0040 -0422 0059 -0203

Axis 1 0700 0156 -008 0537 -0592 0814 0605 0632 -0678

Axis 2 0132 -0186 -0365 -0240 0361 -0185 -0618 0158 -0445



123















Discussion










123










123


















































123








































References



123




























123





























123




Data collection



























ANOVA (Zar 1996)

Data analysis
















123

















































123














1996)

Results


































123


Tab

le1

So

ilv

aria

ble

so

ffi

ve

tran

sect

so

fri

ver

ine

fore

sto

nth

eB

otu

cara

ıri

ver

so

uth

ern

Bra

zil

Soil

var

iable

sL

evee

Dep

ress

ion

L-s

lope

M-s

lope

Rid

ge

FP

Rel

ativ

eel

evat

ion

(m)

38

plusmn0

5a

54

plusmn0

7a

85

plusmn2

3b

11

8plusmn

35

bc

13

6plusmn

37

c8

03

0

00

1

pH

(H2O

)4

8plusmn

04

47

plusmn0

44

7plusmn

04

47

plusmn0

64

7plusmn

06

08

50

93

ns

Pmdash

Meh

lich

(mg

dm

-3)

71

plusmn2

17

1plusmn

23

63

plusmn1

66

plusmn1

75

7plusmn

14

22

30

07

ns

K(m

gd

m-

3)

76

1plusmn

12

57

96

plusmn1

64

89

plusmn2

62

94

3plusmn

34

87

8plusmn

24

14

36

03

5n

s

Ca

(cm

olc

dm

-3)

62

plusmn4

36

8plusmn

44

7plusmn

47

61

plusmn4

57

plusmn3

73

19

05

2n

s

Mg

(cm

olc

dm

-3)

15

plusmn0

71

6plusmn

07

15

plusmn0

71

5plusmn

06

14

plusmn0

50

36

09

8n

s

Al

H

(cm

olc

dm

-3)

66

plusmn3

1a

71

plusmn3

ab8

5plusmn

4ab

96

plusmn5

5ab

10

plusmn4

2b

97

60

04

S(c

mo

lcd

m-

3)

8plusmn

48

87

plusmn5

18

1plusmn

46

84

plusmn5

17

4plusmn

41

27

70

59

ns

CE

C(c

mo

lcd

m-

3)

15

2plusmn

48

16

2plusmn

38

17

1plusmn

33

17

9plusmn

43

17

3plusmn

34

14

50

22

ns

V(

)5

57

plusmn1

71

49

7plusmn

20

24

59

plusmn2

46

45

5plusmn

23

64

18

plusmn2

07

40

60

39

ns

OM

()

26

plusmn1

1a

28

plusmn1

a3

2plusmn

1ab

37

plusmn1

1b

38

plusmn0

8b

22

9

00

01

Cla

y(

)1

37

plusmn2

4a

15

4plusmn

33

ab1

58

plusmn2

8ab

16

plusmn2

1b

15

5plusmn

17

ab2

49

00

4

San

d(

)2

0plusmn

74

23

1plusmn

22

24

2plusmn

10

12

23

plusmn7

52

23

plusmn6

28

91

00

6n

s

Sil

t(

)6

42

plusmn1

09

60

4plusmn

14

59

8plusmn

12

96

2plusmn

91

62

plusmn7

24

91

02

9n

s

Val

ues

are

mea

ns

plusmnst

and

ard

dev

iati

on

sfr

om

0to

20

cmd

epth

top

soil

sam

ple

s(N

=2

0fo

rea

chtr

anse

ct)

Dif

fere

nt

lett

ers

afte

rv

alu

esin

dic

ate

sign

ifica

nt

dif

fere

nce

sin

AN

OV

Ate

sts

(ns

=n

on

-sig

nifi

can

t)


123


























ANOVA F = 107 F = 129 F = 305 F = 35




123










P 0001





123




P 0001



1 2 3 4 5








































123




P 0001







(100ndash338 = 662)













Topography

Sand -002

P -008 0254

K 0588 -0003 0453

Al -0336 0368 -0023 -0552

OM 0625 0046 0226 0706 -0615

V 0304 0035 0323 0680 -0754 0769

CEC 0252 0159 0001 0322 -0315 0579 0574

Flooding -0804 -0042 0253 -0218 0040 -0422 0059 -0203

Axis 1 0700 0156 -008 0537 -0592 0814 0605 0632 -0678

Axis 2 0132 -0186 -0365 -0240 0361 -0185 -0618 0158 -0445



123















Discussion










123










123


















































123








































References



123




























123





























123

















































123














1996)

Results


































123


Tab

le1

So

ilv

aria

ble

so

ffi

ve

tran

sect

so

fri

ver

ine

fore

sto

nth

eB

otu

cara

ıri

ver

so

uth

ern

Bra

zil

Soil

var

iable

sL

evee

Dep

ress

ion

L-s

lope

M-s

lope

Rid

ge

FP

Rel

ativ

eel

evat

ion

(m)

38

plusmn0

5a

54

plusmn0

7a

85

plusmn2

3b

11

8plusmn

35

bc

13

6plusmn

37

c8

03

0

00

1

pH

(H2O

)4

8plusmn

04

47

plusmn0

44

7plusmn

04

47

plusmn0

64

7plusmn

06

08

50

93

ns

Pmdash

Meh

lich

(mg

dm

-3)

71

plusmn2

17

1plusmn

23

63

plusmn1

66

plusmn1

75

7plusmn

14

22

30

07

ns

K(m

gd

m-

3)

76

1plusmn

12

57

96

plusmn1

64

89

plusmn2

62

94

3plusmn

34

87

8plusmn

24

14

36

03

5n

s

Ca

(cm

olc

dm

-3)

62

plusmn4

36

8plusmn

44

7plusmn

47

61

plusmn4

57

plusmn3

73

19

05

2n

s

Mg

(cm

olc

dm

-3)

15

plusmn0

71

6plusmn

07

15

plusmn0

71

5plusmn

06

14

plusmn0

50

36

09

8n

s

Al

H

(cm

olc

dm

-3)

66

plusmn3

1a

71

plusmn3

ab8

5plusmn

4ab

96

plusmn5

5ab

10

plusmn4

2b

97

60

04

S(c

mo

lcd

m-

3)

8plusmn

48

87

plusmn5

18

1plusmn

46

84

plusmn5

17

4plusmn

41

27

70

59

ns

CE

C(c

mo

lcd

m-

3)

15

2plusmn

48

16

2plusmn

38

17

1plusmn

33

17

9plusmn

43

17

3plusmn

34

14

50

22

ns

V(

)5

57

plusmn1

71

49

7plusmn

20

24

59

plusmn2

46

45

5plusmn

23

64

18

plusmn2

07

40

60

39

ns

OM

()

26

plusmn1

1a

28

plusmn1

a3

2plusmn

1ab

37

plusmn1

1b

38

plusmn0

8b

22

9

00

01

Cla

y(

)1

37

plusmn2

4a

15

4plusmn

33

ab1

58

plusmn2

8ab

16

plusmn2

1b

15

5plusmn

17

ab2

49

00

4

San

d(

)2

0plusmn

74

23

1plusmn

22

24

2plusmn

10

12

23

plusmn7

52

23

plusmn6

28

91

00

6n

s

Sil

t(

)6

42

plusmn1

09

60

4plusmn

14

59

8plusmn

12

96

2plusmn

91

62

plusmn7

24

91

02

9n

s

Val

ues

are

mea

ns

plusmnst

and

ard

dev

iati

on

sfr

om

0to

20

cmd

epth

top

soil

sam

ple

s(N

=2

0fo

rea

chtr

anse

ct)

Dif

fere

nt

lett

ers

afte

rv

alu

esin

dic

ate

sign

ifica

nt

dif

fere

nce

sin

AN

OV

Ate

sts

(ns

=n

on

-sig

nifi

can

t)


123


























ANOVA F = 107 F = 129 F = 305 F = 35




123










P 0001





123




P 0001



1 2 3 4 5








































123




P 0001







(100ndash338 = 662)













Topography

Sand -002

P -008 0254

K 0588 -0003 0453

Al -0336 0368 -0023 -0552

OM 0625 0046 0226 0706 -0615

V 0304 0035 0323 0680 -0754 0769

CEC 0252 0159 0001 0322 -0315 0579 0574

Flooding -0804 -0042 0253 -0218 0040 -0422 0059 -0203

Axis 1 0700 0156 -008 0537 -0592 0814 0605 0632 -0678

Axis 2 0132 -0186 -0365 -0240 0361 -0185 -0618 0158 -0445



123















Discussion










123










123


















































123








































References



123




























123





























123














1996)

Results


































123


Tab

le1

So

ilv

aria

ble

so

ffi

ve

tran

sect

so

fri

ver

ine

fore

sto

nth

eB

otu

cara

ıri

ver

so

uth

ern

Bra

zil

Soil

var

iable

sL

evee

Dep

ress

ion

L-s

lope

M-s

lope

Rid

ge

FP

Rel

ativ

eel

evat

ion

(m)

38

plusmn0

5a

54

plusmn0

7a

85

plusmn2

3b

11

8plusmn

35

bc

13

6plusmn

37

c8

03

0

00

1

pH

(H2O

)4

8plusmn

04

47

plusmn0

44

7plusmn

04

47

plusmn0

64

7plusmn

06

08

50

93

ns

Pmdash

Meh

lich

(mg

dm

-3)

71

plusmn2

17

1plusmn

23

63

plusmn1

66

plusmn1

75

7plusmn

14

22

30

07

ns

K(m

gd

m-

3)

76

1plusmn

12

57

96

plusmn1

64

89

plusmn2

62

94

3plusmn

34

87

8plusmn

24

14

36

03

5n

s

Ca

(cm

olc

dm

-3)

62

plusmn4

36

8plusmn

44

7plusmn

47

61

plusmn4

57

plusmn3

73

19

05

2n

s

Mg

(cm

olc

dm

-3)

15

plusmn0

71

6plusmn

07

15

plusmn0

71

5plusmn

06

14

plusmn0

50

36

09

8n

s

Al

H

(cm

olc

dm

-3)

66

plusmn3

1a

71

plusmn3

ab8

5plusmn

4ab

96

plusmn5

5ab

10

plusmn4

2b

97

60

04

S(c

mo

lcd

m-

3)

8plusmn

48

87

plusmn5

18

1plusmn

46

84

plusmn5

17

4plusmn

41

27

70

59

ns

CE

C(c

mo

lcd

m-

3)

15

2plusmn

48

16

2plusmn

38

17

1plusmn

33

17

9plusmn

43

17

3plusmn

34

14

50

22

ns

V(

)5

57

plusmn1

71

49

7plusmn

20

24

59

plusmn2

46

45

5plusmn

23

64

18

plusmn2

07

40

60

39

ns

OM

()

26

plusmn1

1a

28

plusmn1

a3

2plusmn

1ab

37

plusmn1

1b

38

plusmn0

8b

22

9

00

01

Cla

y(

)1

37

plusmn2

4a

15

4plusmn

33

ab1

58

plusmn2

8ab

16

plusmn2

1b

15

5plusmn

17

ab2

49

00

4

San

d(

)2

0plusmn

74

23

1plusmn

22

24

2plusmn

10

12

23

plusmn7

52

23

plusmn6

28

91

00

6n

s

Sil

t(

)6

42

plusmn1

09

60

4plusmn

14

59

8plusmn

12

96

2plusmn

91

62

plusmn7

24

91

02

9n

s

Val

ues

are

mea

ns

plusmnst

and

ard

dev

iati

on

sfr

om

0to

20

cmd

epth

top

soil

sam

ple

s(N

=2

0fo

rea

chtr

anse

ct)

Dif

fere

nt

lett

ers

afte

rv

alu

esin

dic

ate

sign

ifica

nt

dif

fere

nce

sin

AN

OV

Ate

sts

(ns

=n

on

-sig

nifi

can

t)


123


























ANOVA F = 107 F = 129 F = 305 F = 35




123










P 0001





123




P 0001



1 2 3 4 5








































123




P 0001







(100ndash338 = 662)













Topography

Sand -002

P -008 0254

K 0588 -0003 0453

Al -0336 0368 -0023 -0552

OM 0625 0046 0226 0706 -0615

V 0304 0035 0323 0680 -0754 0769

CEC 0252 0159 0001 0322 -0315 0579 0574

Flooding -0804 -0042 0253 -0218 0040 -0422 0059 -0203

Axis 1 0700 0156 -008 0537 -0592 0814 0605 0632 -0678

Axis 2 0132 -0186 -0365 -0240 0361 -0185 -0618 0158 -0445



123















Discussion










123










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123








































References



123




























123





























123


Tab

le1

So

ilv

aria

ble

so

ffi

ve

tran

sect

so

fri

ver

ine

fore

sto

nth

eB

otu

cara

ıri

ver

so

uth

ern

Bra

zil

Soil

var

iable

sL

evee

Dep

ress

ion

L-s

lope

M-s

lope

Rid

ge

FP

Rel

ativ

eel

evat

ion

(m)

38

plusmn0

5a

54

plusmn0

7a

85

plusmn2

3b

11

8plusmn

35

bc

13

6plusmn

37

c8

03

0

00

1

pH

(H2O

)4

8plusmn

04

47

plusmn0

44

7plusmn

04

47

plusmn0

64

7plusmn

06

08

50

93

ns

Pmdash

Meh

lich

(mg

dm

-3)

71

plusmn2

17

1plusmn

23

63

plusmn1

66

plusmn1

75

7plusmn

14

22

30

07

ns

K(m

gd

m-

3)

76

1plusmn

12

57

96

plusmn1

64

89

plusmn2

62

94

3plusmn

34

87

8plusmn

24

14

36

03

5n

s

Ca

(cm

olc

dm

-3)

62

plusmn4

36

8plusmn

44

7plusmn

47

61

plusmn4

57

plusmn3

73

19

05

2n

s

Mg

(cm

olc

dm

-3)

15

plusmn0

71

6plusmn

07

15

plusmn0

71

5plusmn

06

14

plusmn0

50

36

09

8n

s

Al

H

(cm

olc

dm

-3)

66

plusmn3

1a

71

plusmn3

ab8

5plusmn

4ab

96

plusmn5

5ab

10

plusmn4

2b

97

60

04

S(c

mo

lcd

m-

3)

8plusmn

48

87

plusmn5

18

1plusmn

46

84

plusmn5

17

4plusmn

41

27

70

59

ns

CE

C(c

mo

lcd

m-

3)

15

2plusmn

48

16

2plusmn

38

17

1plusmn

33

17

9plusmn

43

17

3plusmn

34

14

50

22

ns

V(

)5

57

plusmn1

71

49

7plusmn

20

24

59

plusmn2

46

45

5plusmn

23

64

18

plusmn2

07

40

60

39

ns

OM

()

26

plusmn1

1a

28

plusmn1

a3

2plusmn

1ab

37

plusmn1

1b

38

plusmn0

8b

22

9

00

01

Cla

y(

)1

37

plusmn2

4a

15

4plusmn

33

ab1

58

plusmn2

8ab

16

plusmn2

1b

15

5plusmn

17

ab2

49

00

4

San

d(

)2

0plusmn

74

23

1plusmn

22

24

2plusmn

10

12

23

plusmn7

52

23

plusmn6

28

91

00

6n

s

Sil

t(

)6

42

plusmn1

09

60

4plusmn

14

59

8plusmn

12

96

2plusmn

91

62

plusmn7

24

91

02

9n

s

Val

ues

are

mea

ns

plusmnst

and

ard

dev

iati

on

sfr

om

0to

20

cmd

epth

top

soil

sam

ple

s(N

=2

0fo

rea

chtr

anse

ct)

Dif

fere

nt

lett

ers

afte

rv

alu

esin

dic

ate

sign

ifica

nt

dif

fere

nce

sin

AN

OV

Ate

sts

(ns

=n

on

-sig

nifi

can

t)


123


























ANOVA F = 107 F = 129 F = 305 F = 35




123










P 0001





123




P 0001



1 2 3 4 5








































123




P 0001







(100ndash338 = 662)













Topography

Sand -002

P -008 0254

K 0588 -0003 0453

Al -0336 0368 -0023 -0552

OM 0625 0046 0226 0706 -0615

V 0304 0035 0323 0680 -0754 0769

CEC 0252 0159 0001 0322 -0315 0579 0574

Flooding -0804 -0042 0253 -0218 0040 -0422 0059 -0203

Axis 1 0700 0156 -008 0537 -0592 0814 0605 0632 -0678

Axis 2 0132 -0186 -0365 -0240 0361 -0185 -0618 0158 -0445



123















Discussion










123










123


















































123








































References



123




























123





























123


























ANOVA F = 107 F = 129 F = 305 F = 35




123










P 0001





123




P 0001



1 2 3 4 5








































123




P 0001







(100ndash338 = 662)













Topography

Sand -002

P -008 0254

K 0588 -0003 0453

Al -0336 0368 -0023 -0552

OM 0625 0046 0226 0706 -0615

V 0304 0035 0323 0680 -0754 0769

CEC 0252 0159 0001 0322 -0315 0579 0574

Flooding -0804 -0042 0253 -0218 0040 -0422 0059 -0203

Axis 1 0700 0156 -008 0537 -0592 0814 0605 0632 -0678

Axis 2 0132 -0186 -0365 -0240 0361 -0185 -0618 0158 -0445



123















Discussion










123










123


















































123








































References



123




























123





























123










P 0001





123




P 0001



1 2 3 4 5








































123




P 0001







(100ndash338 = 662)













Topography

Sand -002

P -008 0254

K 0588 -0003 0453

Al -0336 0368 -0023 -0552

OM 0625 0046 0226 0706 -0615

V 0304 0035 0323 0680 -0754 0769

CEC 0252 0159 0001 0322 -0315 0579 0574

Flooding -0804 -0042 0253 -0218 0040 -0422 0059 -0203

Axis 1 0700 0156 -008 0537 -0592 0814 0605 0632 -0678

Axis 2 0132 -0186 -0365 -0240 0361 -0185 -0618 0158 -0445



123















Discussion










123










123


















































123








































References



123




























123





























123




P 0001



1 2 3 4 5








































123




P 0001







(100ndash338 = 662)













Topography

Sand -002

P -008 0254

K 0588 -0003 0453

Al -0336 0368 -0023 -0552

OM 0625 0046 0226 0706 -0615

V 0304 0035 0323 0680 -0754 0769

CEC 0252 0159 0001 0322 -0315 0579 0574

Flooding -0804 -0042 0253 -0218 0040 -0422 0059 -0203

Axis 1 0700 0156 -008 0537 -0592 0814 0605 0632 -0678

Axis 2 0132 -0186 -0365 -0240 0361 -0185 -0618 0158 -0445



123















Discussion










123










123


















































123








































References



123




























123





























123




P 0001







(100ndash338 = 662)













Topography

Sand -002

P -008 0254

K 0588 -0003 0453

Al -0336 0368 -0023 -0552

OM 0625 0046 0226 0706 -0615

V 0304 0035 0323 0680 -0754 0769

CEC 0252 0159 0001 0322 -0315 0579 0574

Flooding -0804 -0042 0253 -0218 0040 -0422 0059 -0203

Axis 1 0700 0156 -008 0537 -0592 0814 0605 0632 -0678

Axis 2 0132 -0186 -0365 -0240 0361 -0185 -0618 0158 -0445



123















Discussion










123










123


















































123








































References



123




























123





























123















Discussion










123










123


















































123








































References



123




























123





























123










123


















































123








































References



123




























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123


















































123








































References



123




























123





























123








































References



123




























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123


Intermediary disturbance increases tree diversity in riverine forest of southern Brazil

Documents