Impact of sedimentary processes on white-sand vegetation in an Amazonian megafan

12 Pages·2016·0.91 MB·English

JournalofTropicalEcology(2016)32:498–509.©CambridgeUniversityPress2016
doi:10.1017/S0266467416000493
Impact of sedimentary processes on white-sand vegetation
in an Amazonian megafan
∗ ∗ † ‡ ∗
CarlosL.O.Cordeiro ,DilceF.Rossetti ,Roge´rioGribel ,HannaTuomisto ,HiranZani ,
CarlosA.C.Ferreira# andLuizCoelho#
∗NationalInstituteforSpaceResearch(INPE),Sa˜oJose´dosCampos12227-010,Brazil
†JardimBotaˆnicodoRiodeJaneiro,RiodeJaneiro22460-030,Brazil
‡UniversityofTurku,Turku,FI-20014,Finland
#NationalInstituteforAmazonianResearch(INPA),Manaus,69067375,Brazil
(Received20January2016;revised1September2016;accepted2September2016)
Abstract: Amazonianwhite-sandvegetationhasuniquetreecommunitiestoleranttonutrient-poorsoilsofinterestfor
interpretingprocessesofadaptationinneotropicalforests.PartofthisphytophysionomyisconfinedtoLateQuaternary
megafanpalaeo-landforms,thuswepositthatsedimentarydisturbanceisthemainecologicalfactorcontrollingtree
distributionandstructuringinthisenvironment.Inthisstudy,wecharacterizethetopographictrendofonemegafan
palaeo-landformusingadigitalelevationmodelandverifyitsrelationshiptotheforestbymodellingthecanopyheight
withremotesensingdata.Wealsocomparethecompositionandstructure(i.e.canopyheightanddiameteratbreast
height)oftreegroupsfromtheouterandinnermegafanenvironmentsbasedontheintegrationofremotesensing
andfloristicdata.Thelatterconsistoffieldinventoriesoftrees(cid:2)10cmdbhusingsix(500×20m)plotsinva´rzea,
terrafirmeandigapo´ fromtheoutermegafanand20(50×20m)plotsinwoodlandsandforestsfromtheinner
megafan.Theunweightedpairgroupmethodwitharithmeticmean(UPGMA)andthenon-metricmultidimensional
scaling(NMDS)wereappliedforclusteringanddissimilarityanalyses,respectively.Themegafanisasand-dominated
triangular wetland with a topographic gradient of < 15 cm km−1, being more elevated along its axis. The outer
megafanhasahighernumberoftreespecies(367),tallercanopyheight(meanof14.1m)andhigherdiameterat
breastheight(meanof18.2cm)thanthewhite-sandforest.Thelatterrecords89treespecies,meancanopyheight
of8.4cmandmeandiameteratbreastheightof15.3cm.Treesincreaseinfrequencyclosertochannelsandtoward
themegafan’saxis.Thefloodedandnutrient-poorsandymegafansubstratefavouredtheestablishmentofwhite-sand
vegetation according to the overall megafan topography and morphological heterogeneities inherent to megafan
sub-environments.
KeyWords:Amazonian,megafan,openvegetation,sedimentarydynamics,white-sandvegetation
INTRODUCTION biologicalinteractions(Nakaetal.2006),particularlyfor
advancingtheknowledgeonhowlineagediversification
Studies focusing on Amazonian white-sand vegetation and community assembly occur in the tropical flora
areofecologicalinterest(Adeneyetal.2016,Anderson (Fine & Baraloto 2016). Despite this importance, the
1981, Higgins et al. 2011, Moulatlet et al. 2014, ter cause for the distribution of the white-sand vegetation
Steege et al. 2006, Tuomisto et al. 2003), because withinthevastnessoftheAmazonianlowlandsremains
of the high proportion of endemic species adapted largelyunknown,withthemainhypothesesincludingsoil
to these nutrient-poor sandy soils (Anderson 1978, properties (Anderson 1981), heritage from past glacial
1981; Lisboa 1975). The habitat endemism in white- dryclimates(Pessendaetal.2001)andburningbyman-
sand forests is a characteristic of great relevance for madefires(Lisboa1975).
TheNegro-BrancoRiverbasinshavethelargestareas
of white-sand vegetation in the Amazonian lowlands,
∗Correspondingauthor.Email:[email protected] which is in great part confined to triangular-shaped
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Impactofsedimentaryprocessesonwhite-sandvegetation 499
palaeo-landforms associated with Late Pleistocene- the south-central part of the State of Roraima, district
Holocene megafans (Rossetti et al. 2012a, b, 2014a, b; of Caracara´ı, northern Brazil (Figure1a, b), where it
Zani & Rossetti 2012). These features record fan-like encompasses (cid:3)1000 km2, with maximum length and
sedimentary deposits developed on large flat areas by width of 45 km and 25 km, respectively. Climate in
downstreambifurcatingdistributarydrainagenetworks this region is tropical, with monthly temperatures of
(Hartley et al. 2010), a drainage pattern no longer 26°C to 33°C (Radambrasil 1976), average annual
existinginAmazonianareas.Thebest-knownAmazonian rainfallof1800mm,awell-defineddryseasonbetween
megafan is the Virua´ megafan, which is represented by DecemberandMarch,andawetseasonbetweenJuneand
triangular-shapedresidualsandydepositslocatedatthe September.
easternmarginoftheBrancoRiverinnorthernAmazonia Geologically, the Virua´ megafan is included in the
(Rossetti et al. 2012a, Zani & Rossetti 2012). The north-east of Solimo˜es Basin. The megafan deposits
Virua´ megafandepositsarehighlightedbyseveraltypes consist of moderately to well-sorted and very fine-
of white-sand vegetation (i.e. grasslands, shrublands to medium-grained quartzose sands, although coarse-
and forests) in sharp contact with the surrounding grained sands and silty or muddy deposits are locally
areas of rain forest (Cordeiro & Rossetti 2015). Recent present. Radiocarbon dating from superficial deposits
publications stated that the vegetation in the Virua´ recorded latest Pleistocene and Holocene ages ranging
megafan reflects soil propertiers (Damasco et al. 2013, from 36607–38161 cal y BP to 634–695 cal y BP
Mendonc¸a et al. 2014). This proposition neglects the (Rossetti et al. 2012a). Sediment sources are from
entire sedimentary history of the residual megafan neighbouringPrecambrianrocksoftheGuianaShield.
deposits preserved in this region, thereby offering only A remarkable characteristic of the Virua´ megafan is
apartialunderstandingofthefullprocessesthatmightbe the vast expanse of white-sand vegetation that is in
involvedintheoriginofthiswhite-sandvegetation. sharpcontrastwiththesurroundingforests.Thewhite-
Inthiswork,wecharacterizethephysicalenvironment sand vegetation varies from grasslands, shrublands,
of the Virua´ megafan by modelling its topography and woodlands to forests developed on poorly drained and
canopy height based on a digital elevation model. We poorly structured soils (Mendonc¸a et al. 2014). The
also compared the composition and structure of the surrounding forests consist of terra firme and alluvial
megafanwhite-sandforestwiththatoftheneighbouring forest (Cordeiro & Rossetti 2015) developed on well-
rainforestusingfieldinventoriesintegratedwithremote drained and well-structured Oxisols (Mendonc¸a et al.
sensing data. The aim was to determine how and to 2014).
whatextentthemegafanpalaeo-landforminfluencedthe
distribution of contemporaneous plant species in this
area. We considered if topographic gradients resulting METHODS
from the overall megafan morphology and variations
ofdepositionalsub-environmentsaffecttreecomposition The present study was based on botanical data
and structure. Associating the sedimentary processes from the outer and inner megafan, integrated with
responsible for the geomorphological evolution of the the characteristics of the physical environment. The
physicalenvironmentwithplantecologyanddistribution botanical data comprised field inventories along 26
in Amazonian areas is not novel (Damasco et al. 2013, transects,plottedusingapreviouslypublishedvegetation
Higgins et al. 2011, Tuomisto & Ruokolainen 1997), map(Cordeiro&Rossetti2015)tocomparethetreesof
but relating floristic dissimilarities to late Quaternary white-sandforestsanddenseforestsintheinnerandouter
sedimentary dynamics of megafan depositional systems Virua´ megafan,respectively(Figure1c).Fivevegetation
within this region is a novel hypothesis, tested here by typeswereconsidered:twotypes(woodlandsandforests)
the integration of topographic and floristic data. Thus, from the inner megafan and three types (va´rzea, terra
the hypothesis tested is that sedimentary disturbances firme and igapo´) from the outer megafan. Sampling in
imposedbythegeologicalevolutionoftheVirua´megafan the outer megafan comprised six 500 × 20-m (1ha)
isthemainecologicalfactorcontrollingthedistribution plots, each subdivided into a total of 20 subplots (25
andstructuringofwhite-sandplantcommunitiesinthis × 20 m). All vascular plants with a diameter at breast
environment. height (dbh) (cid:2) 10 cm at 1.30 m above ground were
inventoried, with 10 plots in the white-sand forest and
10plotsinthewoodland(Figure1).Eachplotmeasured
STUDYSITE 50 × 20 m (0.1 ha), totalling 1 ha for each vegetation
category. The plot sizes and dbh cut-off limits varied in
The Virua´ megafan consists of sedimentary deposits thefunctionsofthedifferentphysiognomies.Allvascular
having a conical geometry and a topographic gradient plants with dbh (cid:2) 5 cm were inventoried in the white-
averaging 26 cm km−1. This megafan is located in sandforest,whereasinthewoodland,thedbhlimitwas
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500 CARLOSL.O.CORDEIROETAL.
Figure1. Locationmapofthestudyareainthesouth-centralpartoftheStateofRoraima,northernAmazonia(a).LocationoftheVirua´megafan
inthecentralsouthernpartoftheStateofRoraima(b).VegetationmapoftheVirua´megafan(fromCordeiro&Rossetti2015)onanAdvanced
SpaceborneThermalEmissionandReflectionRadiometer(ASTER)image(band1),withlocationofthe26plotsusedforthefloristicinventories(c).
3cm.Thevegetationtypesintheinnerandoutermegafan methodtobetterordinatetheplantcommunityaccording
were compared using only trees with dbh (cid:2) 10 cm. tothenormalizeddifferencevegetationindex(NDVI)(cf.
Tree heights were visually estimated for all vegetation Rouse et al. 1973) or the digital elevation model (DEM)
categories. fromtheShuttleRadarTopographyMission(SRTM).The
The comparison of the floristic groups from the NDVIwasextractedfromadvancedspace-bornethermal
inner and outer megafan, important to demonstrate emissionandreflectionradiometer(ASTER)imageswith
the differences in vegetation types between these ahighprocessinglevel(L3),positionalaccuracyof±0.1
two environments, was achieved using two methods: pixelanddigitalnumbersexpressedinsurfacereflectance
the unweighted-pair group method with arithmetic and corrected for atmospheric influence. The DEM-
mean (UPGMA) for clustering analysis, based only SRTMcomprisedtheinterpolated30m-resolutionmodel
the floristic composition from field data; and the non- freely available in the TOPODATA database (Valeriano
metric multidimensional scaling (NMDS) method of the & Rossetti 2012). The DEM and NDVI values were
R-package ‘MASS’ (Venables & Ripley 2002), applied extractedfromeachsampledcommunityandplottedin
based on the combination of field and remote sensing twoseparateNMDSgraphics,togetherwiththefloristic
data. Compositional dissimilarities between sites were composition based on the presence and absence of tree
calculatedusingtheBray–Curtisdissimilarityindexbased speciesconsidering10woodlandplots,fiveinforest,two
onpresence-absencedata(Legendre&Legendre1998). inva´rzea,oneinigapo´andfourinterrafirme.Theseplots
ThedendrogramproducedbytheUPGMAwasanalysed accountedforthehighfrequencyofrarespecies,diluted
by three R-packages: ‘vegan’, ‘MASS’ and ‘cluster’. In usingonlyabundancedata,reflectingthepotentiallyhigh
addition to the UPGMA, we also applied the NMDS influenceofafewcommonspecies(Figueiredoetal.2014).
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Impactofsedimentaryprocessesonwhite-sandvegetation 501
TheKolmogorov–Smirnov(KS)testwasappliedtodetect canopyheightwas:
differences in the NDVI and DEM values among forest
y=β +β x
classes. 0 1
To analyse the influence of the megafan deposits on
thedistributionofplantcommunities,wecombinedthe where, y is the estimated canopy height; β0 is the
botanical data acquired in the field and modelled from interceptionpoint;β1isthelineslope;andxistheNDVI
remotesensingdatausingregionalmegafantopography. reflectancevalueand/orthetopographicDEMvalue.The
Thisprocedurewasbasedonthepreliminaryassumption resulting map selected 948 sample points, distributed
that topographic variation in this region results from regularlyineach1-kmintervalwithinthemegafan,and
sediment accumulation within an overall fan-shaped interpolated through the kriging (Hengl et al. 2007) in
morphology. These data were preprocessed to improve Arcgis10.0software.
the information potential by application of the kriging
interpolation(from(cid:3)90mto(cid:3)30m).Aslightsmoothing
was used to reduce artefacts and distribute spatial RESULTS
randomness (Valeriano et al. 2006). The topography of
themegafanpalaeo-landformwasalsocharacterizedby Characterizationofthemegafantopography
surfacetrendanalysis(cf.Davis1986,Jonesetal.1986,
Swan&Sandilands1995),obtainedbytheapplicationof The Virua´ megafan encompasses an area of approxim-
polynomialregressionsusingtheMDE-SRTM.Amaskto ately 1016 km2 that is 45 km in length and 25 km
extractonlyimagefractionsofsoilandopenvegetation in width. This palaeo-landform (Figure1c) comprises a
(i.e. grassland and shrubland) was applied. Within this triangular morphology that is primarily flooded during
mask, we randomly selected 706 altimetric points to the greater part of the year. The topography of this
ensure sample spatial independence. Three polynomial area, based on the analysis of the topographic trend
equationsofthefirsttothethirddegreeusingArcgis10.1 surface, indicated the third-order polynomial model as
softwarewasperformedinthetrendsurfaceanalysis.The themostrepresentativeoftheVirua´megafantopography
statisticalsignificanceofthecomputedsurfaceswasbased (Figure2a). This model was selected because it showed
onthehighestcoefficientofdetermination(R²),withaP thehighestR2 (0.75)relativetotheothermodels,with
value<0.05. R2 = 0.61 and 0.72 for the first- and second-order
Theinfluenceoftheouterrainforestandofthechannels polynomial models, respectively. The P value for all
(modernandpast)onthedistributionofthewhite-sand modelswas<0.001.Thethird-orderpolynomialmodel
forest was realized by the extraction of all patches of indicatedthatthemegafansurfaceisextremelyflat,but
white-sand forest from the vegetation map shown in not horizontal, with trend surface isolines distributed
Figure1(seeCordeiro&Rossetti2015formoredetailson radially southwestward from the megafan axis to the
the mapping of these patches). The Euclidean distances fringe. The megafan slope is gentle, as indicated by a
betweenthepatchesofwhite-sandforestandthenearest topographic variation of less than 15 cm km−1, with
channels and between these patches and the nearest altitudes ranging from 53.8 to 40.0 m. The highest
rainforestwerecalculated.UsingtheKernelestimation topography was recorded to the north-east, i.e. toward
method,eachpatchwasconvertedintopointstoproduce the megafan axis, where the main feeding channel
density maps containing the number of patches and capturedsedimentsfromPrecambrianbasementrocksof
surfaceareas,whichwereusedtoidentifyhotspotswith theGuianaShield.Althoughthemegafanreliefissmooth,
a higher concentration of larger patches (cf. Silverman thisregioncontrolsthemoderndrainage,functioningas
1986). Several visual tests were conducted to select a aheadwaterformodernchannels.
radiusof1kmastheminimumsizetoincludeallofthe
mainpatchesofthewhite-sandvegetation.
The relationship between the white-sand forest and Foreststructure
megafan palaeo-landform was also investigated by
modelling the relationship of tree heights using NDVI, TheNDVIwasthemostvaluabledataformodellingthe
DEM,orboth,inR-softwarewithastatisticalsignificance canopy height in the Virua´ megafan. This explanatory
of P (cid:4) 0.05. This procedure followed the application variableappliedaloneprovidedR2=0.68andthelowest
of a mask for the rain forests from the outer megafan AIC values (134.10) among all models (Table2). The
and Preto Ridge (Figure1c). The best linear regression inclusion of DEM generated only a slight improvement
model was selected according to the highest coefficient (R2 = 0.69). In both instances, the P-test was <
of determination (R2) and lowest values of Akaike’s 0.0001. The use of only DEM in the model provided
information criterion (AIC) (Burnham et al. 2011). The the lowest correlation (R2 = 0.19, P = 0.03), probably
equation applied to produce the map of the estimated reflectingtheoccurrenceofwhite-sandforestatdifferent
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502 CARLOSL.O.CORDEIROETAL.
Figure2. TopographiccharacterizationoftheVirua´megafan,northernBrazil,basedonthethirdpolynomialmodelresultingfromthesurfacetrend
analysisofthedigitalelevationmodelderivedfromtheshuttleradartopographymission(DEM-SRTM)(a).Distributionoftheestimatedcanopy
height(m)alongtheVirua´megafanachievedfromalinearregressionmodelbasedonthenormalizeddifferencevegetationindex(NDVI)(b).The
rain-forestmaskshowninaandbcorrespondstorainforestcoveringbasementrocksofPrecambrianagewithinthemegafanthatweredisregarded
fromthesurfacetrendanalysisandalsofromtheanalysisoftheestimatedcanopyheight.
topographies within the megafan. The parameters for Chrysobalanaceae(12.7%),Fabaceae(7.2%),Clusiaceae
the linear model considering β = −12.9, β = 34.4 (6.1%), Annonaceae (5.8%) and Sapotaceae (4.9%).
0 1
andNDVIvaluesproducedamapwithestimatedcanopy Among these trees, the outer megafan recorded 3683
heights (Figure4a), plotting the highest vegetation individuals of 59 families, with the five most common
in the eastern/north-eastern part of the megafan. individuals including Fabaceae, Chrysobalanaceae,
The canopy height significantly decreased eastward Lecythidaceae, Annonaceae and Sapotaceae. A total of
and south-westward from the centre to the fringe 314treespecieswereidentifiedinthisenvironment,with
of the megafan, following the topographic gradient the five main species including Eschweilera atropetiolata
(Figure2b). Benth.,LicaniamicranthaMiq.,ProtiumapiculatumSwart,
The white-sand forest and rain forest were also Pterocarpus rohrii Vahl and Licania heteromorpha Benth.
differentiated,withdbhaveraging15.3cmand18.2cm, Theinnermegafanrecordedatotalof3683individuals
respectively.Thestatisticaltest-Dindicatedonlyaslight of 59 families, with the five most common individuals
difference in this parameter (D = 0.163; P (cid:4) 0.001). including Fabaceae, Chrysobalanaceae, Lecythidaceae,
Similarly,thecanopyheightaverageswere8.4minthe Annonaceae and Sapotaceae. A total of 89 tree species
white-sandforestand14.1mintherainforest(D=0.270; were recorded in this environment, with the five main
P(cid:4)0.001).Thus,thewhite-sandforestshowedtreeswith speciescomprisingRuizteraniaretusa(SpruceexWarm.)
lowerheightsandsmallerdbhthantherainforest. Marc.-Berti, Licania heteromorpha Benth., Couma utilis
(Mart.) Muell. Arg., Sacoglottis guianensis Benth. and
Mezilaurus itauba (Meisn.) Taub. ex Mez. Table1 shows
Treecompositionintheinnerandoutermegafan theaverageheightsanddensitiesofthetreescomparing
the two megafan environments. Considering only trees
A total of 7357 tree individuals from 66 families and withdbh(cid:2)10cm,atotalof4353individualsfrom63
362specieswereidentified.Approximatelyhalf(50.2%) familiesand331specieswererecorded,with59families
of all trees belonged to six families: Rubiaceae (14.8%), and290speciesoccurringintheoutermloadegafanand
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Impactofsedimentaryprocessesonwhite-sandvegetation 503
Table1. Treedatafortheinnerandouterenvironmentsstudiedinthe supported UPGMA clustering, white-sand woodland
Virua´ megafanareacomparingtheaverageheight(Ah),numberof and forest vegetation from the inner megafan and
species and density (number of individuals ha−1) of the white-sand
the rain forest from the outer megafan. Interestingly,
forest(10plots),woodland(10plots)andrainforest(6plots).Thetrees
the NDVI provided the best separation among these
intheinnermegafangenerallyhadlowercanopy,lowernumberof
speciesandhighertreedensitythanthetreesintheoutermegafan.The classes (Figure4c), consistent with the more uniform
sizeofindividualplotsintheinnerandoutermegafanare0.1and1ha, distributionofreflectancevalueswithinindividualclasses
respectively. (circle sizes in Figure4a, b) relative to DEM. This
Megafan Ah No. Density uniformdistributionisevenmoreevidentcomparingthe
environment Plot (m) species (ind.ha−1) graphicrepresentation(Figure4c,d),whichincreasedthe
Inner P1F 7.84 18 2020 distancebetweenclassesusingNDVI.
P2F 8.92 23 1590
P3F 8.87 23 2390
P4F 3.92 15 490
P5F 7.52 23 2650 Patchesofwhite-sandforest
P6F 9.17 23 1810
P7F 8.29 25 2370 Atotalof1369patchesofwhite-sandforestweremapped
P8F 10.32 31 1540 in the Virua´ megafan (Figure5a). These patches have
P9F 9.07 23 1870
individual areas up to 640 ha (mean of 586 ha), with
P10F 8.08 23 2190
75% of the patches smaller than 4 ha and only (cid:3)10%
P1A 1.92 10 1160
P2A 2.06 11 1560 of the patches larger than 10 ha. The largest patches
P3A 1.96 12 1620 werelocatedinthenorth-east,atthemegafanapex.This
P4A 2.22 8 2850 area contained a feeding channel, serving as a conduit
P5A 1.81 14 1370
throughwhichsand,sourcedfromhighlandareasofthe
P6A 1.99 13 1660
Precambriancrystallinebasementrocks,wastransported
P7A 2.89 9 1760
P8A 2.03 4 2320 south-westwardtoformthemegafan.
P9A 1.95 10 990 The distribution of the patches of white-sand forest
P10A 1.67 14 1210 within the Virua´ megafan is parallel to channel
Outer P6I 13.89 69 1125
morphologies (compare Figures 5a). The densities of
P2TF – 86 647
these patches varied within the megafan (Figure5b,c),
P3V 12.51 56 530
P4TF 15.96 91 613 concentrating to the east/north-east. The central-
P1TF – 59 516 southernpartofthemegafan,withahigherconcentration
P5V 13.05 58 446 of intermittent and permanent active channels, also
showedahighdensityofthesepatches.Nearly90%ofthe
patcheswerelocatedlessthan300mfromthechannels,
Table2. Linearregressionmodelsforcanopyheightofthewhite-sand withhalfofthepatcheslessthan100mapartfromthese
forestintheVirua´megafan,indicatedbythecoefficientofdetermination features. A total of 50% of the patches were located up
R2obtainedwitheithernormalizeddifferencevegetationindex(NDVI)
to 98 m from the channels, while 75% of the patches
orthedigitalelevationmodeloftheshuttleradartopographymission
(DEM-SRTM), and both (P = P-test; AIC = Akaike’s information werelocated184mand90%ofthepatcheswerelocated
criterion). 333mfromthesefeatures(Figure5d).Atotalof50%of
Model R2 P AIC the patches of white-sand forest were located up to 2.7
CanopyHeight(cid:3)NDVI 0.68 <0.0001 134.10 kmfromthenearestrainforest,while75%ofthepatches
CanopyHeight(cid:3)NDVI+DEM 0.69 <0.0001 135.10 werelocatedupto5.2kmand90%ofthepatcheswere
CanopyHeight(cid:3)DEM 0.19 =0.03 156.52 locatedupto7.8kmfromthenearestrainforest.
Considering only the plots of white-sand forest using
floristic data, there was no significant relationship
23 families with only 52 species occurring in the inner between the number of tree species and the number of
megafan. channels(R2=0.001;P>0.9)ortheareaofindividual
The UPGMA analysis indicated that the tree species patches(R2=0.25;P>0.13).Inaddition,thenumberof
from the outer and inner megafans formed two major treespecieswasalsonotaffectedbytheproximitytothe
clusters (Figure3). The inner megafan presented two rainforestfromtheoutermegafan(R2=0.13;P>0.3).
sub-clusters that distinguished all of the plots from
forest and woodland, with only one forest plot (P1F)
classifiedaswoodland.Therain-forestvegetationshared DISCUSSION
a higher proportion of species, indicating a lower
floristic distance among the groups. NMDS analysis A comparison of the several tree data derived from the
usingeitherDEM(Figure4a)orNDVI(Figure4c)further innerandoutermegafanshowedthemaincontrolexerted
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504 CARLOSL.O.CORDEIROETAL.
Figure3. DendrogramwithclusteringofvegetationtypesintheVirua´megafanandsurroundingrainforestinnorthernBrazil.Thedendrograms
considerthetwenty0.1-haplotsonthewhite-sandvegetationfromtheinnermegafanandsix1-haplotsintherainforestfromtheoutermegafan.
Thisclassificationisbasedonunweighted-pairgroupmethodwitharithmeticmean(UPGMA)analysisusingBray–Curtisdissimilaritieswith
presence-absencedata(P1toP10=floristicplots;TF=terrafirme;V=va´rzea;I=igapo´;W=woodland;andF=white-sandforest).This
classificationformedtwomainclusters,onejoiningallparcelssampledintheoutermegafanandtheotherallparcelssampledintheinnermegafan.
Observealsothattheinnermegafangroupseparatesintotwosub-groups,onewiththeparcelsfromthewhite-sandforestandtheotherwith
theparcelsfromthewhite-sandwoodland.TheonlyexceptionistheparcelP1F,whichwasmisleadinglygroupedinthelattergroup,althoughit
correspondstoawhite-sandforestparcel.
bythislandformonthecontemporaneousvegetation.For result suggested that the clustering obtained for tree
instance, this is shown by the conspicuous separation speciesfromtheinnerandoutermegafandoesnotreflect
of tree species in the two major clusters obtained from sampling artefacts, but is associated with differences in
the UPGMA analysis, as well as the perfect match the forest structure with spectral responses. The two
of these clusters with the inner and outer megafan. plots of woodland superposed with forest (Figure4d)
The igapo´, va´rzea and terra firme have moderate reflect the fact that these areas contain tree species
similarityintreespeciescomposition,resultinginasingle withanomalouslyhigherdensitiesandheights(Table1)
cluster. However, these classes display a higher degree thanthosefromotherplotsofthissameclass.Similarly,
of dissimilarity with species from the inner megafan, the two outliers with the highest NDVI values from
resultingintheirgroupinginadistantcluster(Figure3). the white-sand forest have higher trees relative to the
Notably,thespeciesfromthisenvironmentshowedhigher remaining plots of this group. Contrasts in temporal
dissimilarity among white-sand forest and woodland as developmentreflectingdifferencesinsedimentarystages
indicated by two subclusters that separated all of the inherentfromthemegafanevolutionmightexplainthese
plots.Theonlyexception,representedbyplotP1Fwhich results.
ambiguously joined the woodland cluster (Figure3), Thedifferencesintreecompositioncomparingtheinner
reflects the low species diversity of this area, although and outer megafan environments are also remarkable
its structure is similar to that of the white-sand forest. and help in demonstrating the control exerted by
This plot might have been affected by fires, consistent this landform on the contemporaneous vegetation. The
with the observed local tree regrowth. Fire disturbance overalldominanceofR.retusa(107)andthehighnumber
could have facilitated the colonization of this plot by of S. guianensis and M. itauba in the white-sand forest
pioneerandwoodlandtreeslikelyrepresentinganinitial of the inner megafan and near absence of these species
stage in white-sand vegetation succession. The success in the outer megafan might reflect adaptation to areas
of the NMDS ordination diagrams based on the NDVI initially more exposed to sunlight, where competition
values (Figure4) in the confirmation of the UPGMA is likely lower than under the rain-forest environment.
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Impactofsedimentaryprocessesonwhite-sandvegetation 505
Figure4. DiagramsoffloristicsimilaritiesfortheVirua´megafanandsurroundingrainforestinnorthernBrazilbasedonthenumberoftreespecies
andtheirrelationtoremotesensingdata.Ordinationdiagramsofthefirsttwonon-metricmultidimensionalscaling(NMDS)axes(a,b),withbasis
ontheirgreatestvariations(firstaxis=50.6%;secondaxis=27.2%)usingdigitalelevationmodel(DEM)(a)andnormalizeddifferencevegetation
index(NDVI)(b)values(circle=individualplot;circlesize=NDVIandDEMvalues;andcolouredcircle=unweighted-pairgroupmethodusing
arithmeticmean(UPGMA)classification(green=white-sandforest;darkblue=woodland;red=rainforest).DistributionofDEM(c)andNDVI
(d)valuesamongthethreeanalysedvegetationclasses(c,d).Observethattheplotswithalltreespeciesformedthreemainclustersusingeitherthe
DEMorNDVI,butthelatterincreasedthedistancebetweengroups,asbetterillustratedbythediagramd.
This interpretation is consistent with previous records areas. For example, Fabaceae are one of the 10 most
of this species on white-sand substrates from other important families in Amazonia (ter Steege et al. 2006)
Amazonian areas (Habermann & Bressan 2011, ter andChrysobalanaceaecomprisesupto10%ofthetrees
Steege & Zondervan 2000). However, L. heteromorpha, inthisregion(Hopkins2007).However,othercommon
thesecondmostabundantspeciesintheinnermegafan, familiesinthisregion,suchasLecythidaceae,withnearly
isalsocommonintheterrafirmeoftheoutermegafan. half of its species in Amazonia (Mori 1990), were not
This occurs because this species has the advantage observedintheinnermegafan.
of changing from shrub to tree in areas of open or Theinfluenceofthemegafanpalaeo-landformonthe
dense vegetation, respectively (Pereira 2013). Another distributionofthestudiedvegetationisfurthershownby
key point concerning the tree composition in the inner thecomparisonofdbhandcanopyheightoftreespecies
megafanistheoccurrenceofonlyoneorafewspeciesfrom from the outer megafan rain forest and the white-sand
alimitednumberoffamiliespresentintheoutermegafan, forest. Hence, the outer megafan contained tree species
primarily including Fabaceae and Chrysobalanaceae. that are more diversified and have a better-structured
Thesefamiliesaregenerallywellrepresentedintropical canopy than the inner megafan, as indicated by the
regions(Rundel1989),andareparticularlyabundantin higher number of species and higher dbh. These effects
SouthAmerica,withthehighestdiversityinAmazonian likelyreflectthegeologicalsettingthatprovidedahigher
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506 CARLOSL.O.CORDEIROETAL.
Figure5. Channelsandpatchesofwhite-sandforestintheVirua´megafan,northernBrazil.Hydrologicalmap(modifiedfromZani&Rossetti2012)
withthepatchesoverthechannelnetwork(modifiedfromCordeiro&Rossetti2015)(a).Mapofthedensityofpatchesbasedonthenumberof
patches(b)andareasofthepatches(c)basedontheKernelestimationmethod.Distributionofthepatchesofwhite-sandforestwithinarangeof
600mofdistancefromthechannelsshowingthatmostofthepatches(i.e.(cid:3)50%)arelocatedwithinarangeof100mfromthechannels,withthe
highestconcentrationonly10mdistantfromthesefeatures(d).
amount of nutrients favourable to the colonization of a thinner trees than the rain forest. The presence of
widertreespectrum.Severalcharacteristicsoftheouter this dissimilar vegetation in the study area is related
megafan environment might have contributed to this to several geological characteristics directly associated
scenario, including: (1) terrain comprising low-grade with the megafan evolution. First, the topographically
metamorphicrocksfromthePrecambrianGuianaShield low-lying terrain, caused by slow tectonic subsidence
or even the Plio-Pleistocene Ic¸a´ Formation, a context (Rossetti et al. 2014b), might have been more affected
that provided a long period for forest development; (2) byseasonalflooding.Second,theVirua´megafanconsists
varied lithological composition, which enhanced the ofawidespreadareacharacterizedbytheaccumulationof
potential for nutrients, reflecting the highest amount highvolumesofquartzosesandsbydistributarynetworks
of chemical constituents from a diversified mineralogy; thatremainedactiveuntiltheLatePleistocene-Holocene
and(3)developmentofwell-drainedandwell-structured (Rossettietal.2012a).Poorlydrained,poorlystructured
areas of Oxisols. In contrast, the inner megafan is and nutrient-poor soils developed in this terrain would
dominated by white-sand forest, which has lower and have constrained the colonization of rain-forest species,
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Impactofsedimentaryprocessesonwhite-sandvegetation 507
despitethegeographicproximitytothemegafanpalaeo- alignedparallelandclosetochannelsorpalaeochannels,
landform. suggestinganoriginassociatedwiththesemegafansub-
Inaddition,sandaccumulationproducedatriangular environments.Consideringthattheriseofgroundwater
palaeomorphology with a gentle slope, which further during rainy seasons creates anaerobic conditions in
constrained the white-sand vegetation to the megafan the soil that prevents root respiration (Pires & Prance
surface, consistent with reports of previous studies 1985),itislikelythatmicromorphologiesassociatedwith
(Rossetti et al. 2012a, Zani & Rossetti 2012). The sedimentation in various megafan sub-environments
progressive increment in canopy heights toward the would favour the development of the white-sand forest.
east/north-eastofthestudyareasupportstheinfluence Channelized systems, such as this one, display many
ofthemegafantopographyonthegrowthofthewhite- sub-environments (i.e. sand bars, levees, islands and
sand forest. The data presented also suggest that this crevasse splays) that constitute positive reliefs of a few
effect most likely reflects the topographic gradient of metresorevencentimetreshigherthanthesurrounding
15 cm km−1 from the megafan apex to the fringe, terrain. Additionally, sands that are exposed at the
based on the analysis of the trend surface. According megafan surface formed aeolian dunes that further
tothegeometrythattypifiesmegafansystems,proximal imposed topographic heterogeneities to this terrain.
areas are slightly higher (Fielding et al. 2012, Hartley Althoughsmooth,thesepositivemorphologies,abundant
et al. 2010, Nichols & Fisher 2007), reflecting the in megafans as a result of the unstable nature of
aggradation of larger sand volumes, which occurs theirdistributarydrainage(Slingerland&Smith2004),
because these areas are located closer to main feeding contributedtothemaintenanceofsomesitesfreefromthe
channelsresponsiblefortransportingsedimentintothese influenceofthewatertablelongerthroughouttheyear.
systems.Theproximalmegafanareasarealsogenerally Thus, tree colonization was preferentially concentrated
the first ones to be abandoned when sedimentation intheseareas,formingwhite-sandforestpatches.
ends. Thus, despite the overall similar sandy substrate Therefore, among all factors, hydrology controlled
throughout the Virua´ megafan, the higher topography by topographic gradients reflecting the evolution of
resulting from increased sediment aggradation, as the various depositional sub-environments of the Virua´
reflected by the longer abandonment time of proximal megafan is perhaps the most relevant factor explaining
depositional environments, might have generated more the highest concentration and greater heights of
suitableconditionsfortreecolonization.Thesedimentary trees in the proximal megafan areas, opposed to
dynamicsoftheproximalmegafanwouldhavelowered distal areas dominated by grass and shrub vegetation.
thewaterlevel,initiatingthepedogenicprocessesandthe Publicationshavepreviouslyhighlightedtheimportance
establishmentoftreeroots.White-sandforestsgenerally of hydrology on the stratification of the Virua´ white-
occurinareaswithgroundwaterlevelsthatare0.4to1.0 sandvegetation(Damascoetal.2013,Gribeletal.2009,
mbelowthesurface,enoughtopreventrhizospheresfrom Mendonc¸a et al. 2014). However, the realization that
total flooding (Mendonc¸a et al. 2014). In contrast, the thedistributionofvegetationtypesisdirectlydependent
megafanfringes,locatedfartherfromthemainsediment on the megafan morphology, as discussed herein, is
sources and at a lower elevation, had lower sediment an innovative model. A tenuous hydrological balance
aggradation rates and were abandoned at a later stage reflectingmicromorphologiesimposedbyenvironmental
during the megafan evolution. Thus, these areas have heterogeneitieswaskeytothedevelopmentofpatchesof
lowerelevationsrelativetoproximalmegafanareasand forestintheVirua´megafan.Theinfluenceofsedimentary
are,consequently,moreinfluencedbyseasonalflooding. dynamicsonthedistributionofvegetationpatternsalong
Such an environmental constraint could explain the the Virua´ megafan, as proposed here, is a useful model
preferred development of grass and shrub vegetation toalsoexplainthewhite-sandvegetationthattypifiesthe
towarddistalmegafanareas. Negro-Branco River basins in the northern Amazonian
The analysis of the numerous patches of white-sand lowland,assuchvegetationtypesinthisregionarealso
forest is in agreement with the proposed influence of associated with fan-shaped palaeo-landforms reflecting
themegafansedimentarydynamicsontreedistribution. megafan depositional systems similar to the Virua´
This analysis showed that there is no relationship megafan(Rossettietal.2012b,2014b).
between the number of tree species of these patches
and their areas, nor with their proximity to the
surrounding rain forest. However, although there is CONCLUSION
also only a moderate relationship between the number
of tree species and the number of channels, these Incontrasttopreviousstudiesemphasizingclimateasthe
features might be crucial for the development of the mainfactorinfluencingplantdissimilarityinAmazonia,
white-sand forest, as reflected by the fact that these the present survey consisting of field floristic invent-
patches are not randomly distributed, but are often ories and remote-sensing modelling, integrated with
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