foraminifer communities and environmental change in marginal marine sequences (pliocene, tuscany,...

DOI 10.1111/j.1502-3931.2008.00099.x © 2008 The Authors, Journal compilation © 2008 The Lethaia Foundation

LETHAIA

Blackwell Publishing Ltd

Foraminifer communities and environmental change in marginal marine sequences (Pliocene, Tuscany, Italy)

STEFANO DOMINICI, CRISTINA CONTI AND MARCO BENVENUTI

Dominici, S., Conti, C. & Benvenuti, M. 2008: Foraminifer communities and envi-ronmental change in marginal marine sequences (Pliocene, Tuscany, Italy).

Lethaia

,Vol. 41, pp. 447–460

Fossil abundance data on foraminifer communities were collected in marginal marinesediments of the Pliocene Valdelsa succession, in Tuscany, Italy. This succession isorganized in a hierarchy of elementary and composite depositional sequences. Multi-variate techniques allowed to analyse the dataset and reconstruct gradients in speciesdistributions. Species-level data available on modern environmental distributions wereused to reconstruct Pliocene environmental gradients and to infer absolute palaeo-depths and palaeosalinities. Estimates were then compared with the sequence-stratigraphic interpretation to check for consistency. The high-resolution stratigraphicframework allowed us to test the stability of foraminifer communities against ecologicalvariations related to high-frequency glacio-eustatic cycles. The results confirm thatfossil distributions of foraminifer species can be used as a fine tool to detect environ-mental change and that multivariate techniques allow their interpretation in terms ofabsolute variations of controlling parameters. Salinity is the main contributor to thesum of depth-related factors that regulate foraminifer distributions in coastal facies. Inthe same setting, nutrient levels and the presence of a sea grass cover are responsiblefor secondary changes in shallow-water distributions. Below the wave base, however,depth-related parameters other than salinity explain the largest variations. This studyindicates that foraminifer communities are random associations of species that respondindividualistically to environmental change.

�

Community stability

,

foraminiferalpalaeoecology

,

gradient analysis

,

sequence stratigraphy

.

Stefano Dominici [[email protected]], Museo di Storia Naturale, SezioneGeologia e Paleontologia, Università di Firenze, Firenze, Via La Pira 4, 50121 Firenze,Italy; Cristina Conti [[email protected]] Agenzia Regionale Protezione AmbientaleToscana, Firenze, Italy; Marco Benvenuti [[email protected]] Dipartimento di Scienzedella Terra, Università di Firenze, Via La Pira 4, 50121 Firenze, Italy; manuscriptreceived 21/06/07; and manuscript accepted on 10/01/08.

The frequency with which a species appears in acommunity depends on its fundamental ecologicalniche, comprising a suite of combinations of envi-ronmental variables that permit establishment,survival and reproduction of individuals (Hutchinson1978). Some niche variables change continuouslyalong gradients, with populations responding in asimilar manner and producing biotic gradients offrequency distributions within assemblages. This hindersthe clear-cut subdivision of species groups into com-munities, suggesting that species distributions can bebetter expressed through coenoclines, or the gradualchange of community composition along an envi-ronmental gradient (Whittaker 1967; Gauch 1982).Species composition of fossil assemblages can thusbe an indirect measure of environmental gradientsin the geological past (Olszewski & Patzkowsky 2001;Hohenegger 2005). In marine environments, waterdepth is usually interpreted as the single mostimportant factor, summing up continuously chang-ing values of other parameters that directly affect thedistribution of benthic species, such as water energy,

substrate texture, seasonality and salinity. Previousstudies of gradients in fossil benthic assemblages,dealing mostly with brachiopods and molluscs,confirm that depth change directly explains the mainvariation of taxonomic composition between samples(Holland

et al

. 2001; Scarponi & Kowalewski 2004;Dominici & Kowalke 2007). When knowledge onthe environmental distributions of genus-level, extantrelatives was available, this evidence has been usedto infer absolute palaeodepths through taxonomicuniformitarianism and to augment sequence strati-graphic interpretation of sedimentary successions(Scarponi & Kowalewski 2004).

A similar approach at the species-level is appliedhere to foraminifer assemblages from a Pliocenealluvial and marine succession in Tuscany, Italy. Thisyields information on the factors regulating bioticcompositional variations and documents the distri-bution of fossil assemblages with respect to sequence–stratigraphic surfaces. Given appropriate outcropconditions, depositional sequences can be used as ahierarchic record of sea level- and climate-driven

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et al. LETHAIA 41 (2008)

environmental change as expressed by sequence-bounding unconformities (Scarponi & Kowalewski2004; Dominici & Kowalke 2007). The integration ofpalaeoecology with sequence stratigraphy can thusindirectly measure the degree of connectedness ofspecies within communities and the stability ofcommunities at times of environmental change(DiMichele

et al

. 2004; Scarponi & Kowalewski 2004;Dominici & Kowalke 2007). Foraminifer speciesseem particularly fit for these scopes because they areexcellent indicators of modern and past marginalmarine environments, widely used in palaeoecologyand environmental micropalaeontology (Sen Gupta2002; Murray 2006). Foraminifer distributions infossil assemblages from offshore settings confirmthat depth is the single most important factor(Hohenegger 2005), whereas salinity alone largelyexplains compositional variation in proximity ofterrestrial masses (Sen Gupta 2002).

In the Pliocene succession sampled for this study,a repeated shift from alluvial to marine conditionsis recorded by frequent changes of lithofacies(Benvenuti

et al

. 2007). This seems particularly suit-able to understand the role of salinity amongdepth-related factors in shaping faunal gradients.The study is organized according to the followingscopes: (1) reconstructing gradients in species distri-butions through multivariate analyses of abundancedata, initially inferring the factors responsible ofcompositional variations among assemblages; (2)interpreting depositional sequences in terms ofabsolute depth and salinity, relying on species-leveldata from modern distributions; and (3) testing thestability of foraminifer communities in the face ofsea-level-induced environmental change as detectedfrom the sequence-stratigraphic architecture.

Geological setting

The Valdelsa Basin is a Neogene post-collisionalbasin filled with continental Miocene and Pliocenealluvial, coastal marine, and shelf sediments. The suc-cession can be subdivided into large-scale sequences,previously referred to as synthems, where boundingunconformities are produced during major pulses ofuplift of the Apennines (Benvenuti

et al

. 2007 andreferences). For the present study we address a250-m-thick Piacenzian succession of the Ponte aElsa and San Miniato sequences (Fig. 1). A subdivi-sion into four main lithofacies – based on geometry,sedimentary structures, grain size, and macrofaunalcontent – is used here as a simplified result of outcrop-based facies analysis (see Benvenuti

et al

. 2007). Thefour lithofacies are mudstones with no macrofauna,

mudstones and muddy sandstones with brackish-watermolluscs, sandstones with shoreface fossils, andmudstones with fossils indicative of open shelf con-ditions. Lithofacies are arranged in 5- to 30-m-thicksedimentary cycles broadly formed from the base by:(1) an erosional unconformity, (2) a fining-upward,cross-bedded sandstone interval, and (3) a coarsening-upward, bioturbated, mudstone-to-sandstone inter-val. Shell beds showing signs of time averaging arefrequent on top of the sandstone interval or in thelower half of the mudstone-to-sandstone interval.Some facies successions are arranged in alluvial toshallow-marine regressive–transgressive cycles,others have a more open marine character. Allcycles are interpreted by Benvenuti

et al.

(2007) ashigh-frequency elementary depositional sequences(EDS) and as representing the record of glacio-eustatic cycles driven by precessional orbital varia-tions (10

3

–10

4

-year frequency, see also Benvenuti &Dominici 1992). In particular, sequence boundaries(SB), transgressive surfaces (TS), maximum floodingintervals (MFS), and intervening systems tracts arerecognized from the analysis of facies and shell beds(Fig. 1; Benvenuti & Dominici 1992; Dominici 1994;Benvenuti

et al

. 2007). Usually four, and up to six,elementary sequences stacked to form a transgressive–regressive sedimentary cycle of lower frequency,referred to as a composite depositional sequence(CDS, in the sense of Mutti 1989, and Mutti

et al

.1994), were interpreted as the product of eccentricityorbital cycles. The sampled succession comprisesfour small-scale composite sequences of the Ponte aElsa large-scale sequence and two of the San Miniatosequence (Fig. 1). If small-scale composite sequencesare produced by eccentricity cycles of about 10

5

-yearduration, the whole succession would span 0.5–0.6my of the Piacenzian, according to available chrono-stratigraphic data (Benvenuti

et al

. 2007 and withadditional references).

Material and methods

Bulk sampling was designed to cover marine andtransitional mudstones and sandstones from com-posite sequences 1–5. Three hundred grams of eachsample was washed through sieves with sizes of 63,125 and 250

μ

m mesh in order to obtain reliableabundance data. The dried residue was split andspecimens were collected from sub-samples of eachsize fraction until approximately 300 foraminiferspecimens were retrieved; these were then countedand tallied at the species level. After discarding spe-cies occurring only in single samples, the final datasetcomprised 19,574 specimens belonging to 115

LETHAIA 41 (2008)

Foraminifer biofacies

449

species from 58 samples (Table S1). Twenty-eightsamples out of the 86 originally collected were devoidof foraminifers, some yielding ostracods and othermicrofossils diagnostic of terrestrial conditions.

Absolute abundances were standardized to per-centages and then square-root-transformed tominimize the weight of species with very highabundances; matrices of similarity were calculatedwith the Bray–Curtis coefficient, also known asCzekanowski coefficient or Sorenson distance,commonly used in ecological (Clarke & Warwick1994) and palaeoecological work (Holland &Patzkowsky 2004). Hierarchical agglomerative

clustering (CLUSTER), performed to see how speciestend to co-occur in samples and how samples can begrouped together because of similar taxonomic com-position, was achieved after group-average linking.The results are here expressed on a two-way diagram,showing at a glance both the species (R-mode) andthe sample clusters (Q-mode: Fig. 2). Whereby clustersreflect the vicinity of species in the multidimensionalspace (R-mode) and depict the types of communitythat can be reconstructed from fossil material (Q-mode), ordination methods are suited to understandthe structure of samples in terms of compositionalgradients (Olszewski & Patzkowsky 2001). Nonmetric

Fig. 1. Pliocene succession in the San Miniato area, with geographical locations shown in the inserts. The Ponte a Elsa and San Miniatolarge-scale depositional sequences are bounded by major unconformities of regional extension. Elementary and small-scale compositesequences are indicated by letters and numbers, respectively. The position of samples is noted on the left side of the sedimentary logs.

450

Dominici

et al. LETHAIA 41 (2008)

MDS was used as one of the best ordination tech-niques available (Kenkel & Orloci 1986; Clarke &Warwick 1994), together with detrended correspond-ence analysis (DCA: Hill & Gauch 1980). As a

method to use in conjunction with nonmetricordination, DCA of untransformed abundance datawas preferred to correspondence analysis (Kenkel &Orloci 1986; Olszewski & Patzkowsky 2001) based on

Fig. 2. Two-way cluster analysis (group-average linking). R-mode dendrogram based on the analysis of the 31 most important species(> 5% in at least one sample), Q-mode dendrogram based on the whole dataset. Biofacies: A = Ammonia beccarii; B = A. parkinsoniana;C = Trochammina ochracea; D = Quinqueloculina seminulum; E = Florilus boueanum.

LETHAIA 41 (2008)


451

consistent and effective results in previous palaeo-ecological studies (Holland

et al

. 2001; Holland &Patzkowsky 2004; Scarponi & Kowalewski 2004)and because the outputs were similar to the resultsof MDS.

Analysis of similarity (ANOSIM) allowed the measureof the degree of community stability by comparinggroups of samples based on their respective deposi-tional sequence – an

a priori

information, external tothe dataset. When differences of samples betweendepositional sequences are confronted with differenceswithin a depositional sequence, the null hypothesis(H

0

) is that there are no differences between sequences.The value of the Global test statistic R helps deter-mine whether H

0

is rejected or not. With R values> 0.75, groups are well separated; values > 0.5 indi-cate overlapping but clearly different groups; > 0.25strongly overlap groups; and < 0.25 barely separablegroups (Clarke & Warwick 1994). In our case, ifspecies show up in their communities with a recur-ring pattern of abundances, then samples of a givenbiofacies are expected be indistinguishable aftercycles of relative sea level variation, and Global Rshould be low; if Global R is high, species showindividualistic behaviour and communities are onlyrandom associations.

The software PRIMER designed for ecologicalresearch (Clarke & Warwick 1994) was used to per-form ANOSIM, MDS, and CLUSTER, whereas DCAwas carried out with the software PAST (Hammer

et al

. 2004).

A readily explainable clustering of species wasobtained with a restricted dataset of the 31 mostimportant species. Importance was determined byfrequencies of > 5% in at least one sample; percentagevalues were recalculated after discarding rare species.In contrast, the clustering of samples was based on thewhole dataset (Fig. 2). R-mode and Q-mode clusterswere then superimposed in MDS and DCA plots(Figs 3, 4). Ecological data on extant species were usedto interpret biofacies and gradients (Table 1), and toestimate mean values of water depths preferred by10 diagnostic species and salinities preferred by 11diagnostic species (Fig. 5). As foraminifer diversityincreases moving from brackish to marine waters(Sen Gupta 2002), species richness (S), the ShannonEvenness Index (H), and Simpson’s Equitability (E)were measured in order to check for inconsistencies(Fig. 4; Table S2).

Results

The R-mode cluster analysis shows that commonlyco-occurring species form five groups (clusters 1–5)at different similarity levels (~20% for cluster 1, other-wise ~45%), with four outlying taxa. The Q-modecluster analysis yielded five groups (clusters A–E)corresponding to biofacies or palaeocommunitytypes, with two outlying samples (Fig. 2). Biofaciescontain samples from different sequences, showinghabitat recurrence after cycles of sea-level change.

Fig. 3. Results of detrended correspondence analysis. �A. Ordination of species with frequencies > 5%, based on raw abundance data,groups based on R-mode clusters. �B. Ordination of samples subdivided into Q-mode clusters, or biofacies, the Ammonia beccariibiofacies showing important overlaps.

452

Dom

inici

et al.LET

HA

IA 41 (2008)

Table 1.

Ecological data from the present-day distribution of 19 extant species diagnostic of the Pliocene dataset. The order follows preferred depth, from upper marsh to open shelf. ColumnsA–E list the average frequency of each species in the three clusters where it occurs with the largest percentage.

Species

Mean frequency in clusters (%)Modern occurrence Environment DC1

Mean depth (m)

Mean salinity (‰)

Trophic level ReferencesA B C D E

Trochammina inflata

0.2 4.7 0.3 Worldwide Middle and upper marsh

−

0.7 0.3 12 Alve 1999; Cann

et al

. 2002; Hippensteel

et al

. 2000; Horton

et al

. 1999, 2003; Saffert & Thomas 1998; Serandrei

et al

. 2004

Cribrononion lagunensis

0.8 0.8 0.5 Mediterranean Lagoon Serandrei

et al

. 2004

Ammonia tepida

6.1 10.6 3.3 Worldwide Lower marsh, estuary, shallow shelf

0.65 –7 22 Alve & Murray 1994; Buzas-Stephens

et al

. 2003; Duleba & Debenay 2003; Horton

et al

. 2003; Pascual et al

. 2002; Samir et al . 2003; Serandrei

et al . 2004

Elphidium excavatum

0.3 0.8 0.3 Worldwide Lower marsh, shallow shelf

21 Alve & Murray 1994; Buzas-Stephens

et al

. 2003; Duleba & Debenay 2003; Saffert & Thomas 1998; Samir

et al

. 2003

Ammonia parkinsoniana

11.8 5.9 3.3 Mediterranean Lower marsh, tidal flat, lagoon, shallow shelf

–0.05 –1.2 19 High Buzas-Stephens

et al

. 2003; Duleba & Debenay 2003; Samir

et al

. 2003

Ammonia beccarii

63.9 66.6 29.1 Worldwide Lagoon, shoreface, shallow shelf

0.3 –42 30 Alve & Murray 1994; Saffert & Thomas 1998; Alve 1999; Moulfi-El-Houari

et al

. 1999; Donnici & Serandei Barbero 2002; Pascual

et al

. 2002; Serandrei

et al

. 2004

Quinqueloculina seminulum

4.9 10.1 1.7 Worldwide Lagoon, shoreface, shelf

1.55 –75 29 High Corner

et al

. 1996; Horton

et al

. 1999; Moulfi-El-Houari

et al

. 1999; Donnici & Serandei Barbero 2002; Pascual

et al

. 2002; Buzas-Stephens

et al

. 2003; Serandrei

et al

. 2004

Triloculina trigonula

0.2 2.4 0.8 Mediterranean Shelf 2.25 –104 36 Moulfi-El-Houari

et al

. 1999; Samir

et al

. 2003; Serandrei

et al

. 2004

LETH

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41 (2008)


453

Biofacies w

ere named after the single characteriz-

ing taxon, chosen because of its abundance or itsexclusivity to a given cluster of sam

ples (clusterA

=

Am

monia beccarii

; cluster B =

Am

monia parkin-

soniana

; cluster C = T

rochamm

ina ochracea

; clusterD

=

Quinqueloculina sem

inulum

; cluster E =

Florilusboueanum

). Sample diversities show

within-biofacies

consistency to a degree, the lowest diversities in

terms of richness, equitability and evenness being

associated with the

Am

monia beccarii

biofacies, thehighest values w

ith the

Quinqueloculina sem

inulum

and the

Florilus boueanum

biofacies (Fig. 4A).

Grouping taxa in ordination plots according to

R-m

ode clusters helped to visualize the relationshipsam

ong species. These show

a continuous distributionin the m

ultidimensional space, w

hereas clustersdisplay little overlap in both D

CA

(Fig. 3A) and

non-metric plots.

The significance of Q

-mode clusters w

as checkedon D

CA

and MD

S ordinations. Whereas clusters B

and E are largely separated, C scoring the low

est andE the highest along axis 1 of D

CA

(

Trocham

mina

ochracea

and

Florilus boueanum

biofacies), strongoverlap is show

n by samples of cluster A

(

Am

monia

beccarii

biofacies)

with

C,

and partially

with

D(

Quinqueloculina sem

inulum

biofacies, Fig. 3B). Abetter separation w

as obtained with non-m

etricordinations, together w

ith a distinct trend of increas-ing diversity along the direction of m

aximum

variation(Fig. 4A

). When lithofacies are show

n on the MD

Sdiagram

, a gross correlation proves the validity offield criteria for facies recognition, based on litho-facies and m

olluscs (Fig. 4B). In particular, offshorem

udstones are

often associated

with

a

Florilusboueanum

biofacies, mudstones from

coastal lagoonsand brackish w

ater environments are associated either

with a

Quinqueloculina sem

inulum

or a

Trochamm

inaochracea

biofacies, and mudstones w

ith no macro-

fauna invariably

contain an

Am

monia

beccarii

biofacies. The distribution of shoreface sandstones,

which m

ay contain remains from

all shallow-w

atercom

munities, is less m

eaningful. The

Am

monia

parkinsoniana

biofacies is usually associated with

shoreface environments.

The

Am

monia beccarii

biofacies (18 samples in

cluster A) groups sam

ples with abundant shallow

marine species (species cluster 4) and particularly

those where

A. beccarii

ranges from 40–90%

(average64%

). A strict interpretation based on the know

nm

odern distribution of

A. beccarii

would confine the

species to upper shoreface environments (H

ayward

et al

. 2004). The broad species concept for

A. beccarii

adopted here suggests that a wider range of coastal

environmental conditions could be responsible for

its abundance in all samples. O

ther species occupying

Cibicides lobatulus

1.3 0.2 0.2 Mediterranean, Atlantic, Arctic

Lower estuary, shelf

31 Low Alve 1999; Corner

et al

. 1996; Donnici & Serandei Barbero 2002; Moulfi-El-Houari

et al

. 1999; Pascual

et al

. 2002; Scott

et al

. 2003

Elphidium crispum

1.1 0.3 1.9 Worldwide Lower estuary, shelf

2.2 –104 35 Cann

et al


et al

. 1999; Pascual

et al

. 2002; Samir

et al

. 2003

Bulimina aculeata

0.1 0.2 1.9 Mediterranean Shelf 3.1 –168 36 Moulfi-El-Houari

et al

. 1999; Mendez

et al

. 2004

Asterigerinata mamilla

0.3 0.2 0.3 Mediterranean Estuary, shelf 38 Moulfi-El-Houari

et al

. 1999; Pascual

et al

. 2002

Bulimina elongata

0.2 0.8 Mediterranean, Atlantic

Shelf 2.7 –124 34 Corner

et al


et al

. 1999; Mendez

et al

. 2004

Cancris auriculus

0.9 1.0 1.8 Mediterranean, Atlantic

Shelf 36 High Altenbach

et al


et al. 1999Reussella spinulosa 0.6 2.2 Mediterranean Shelf 2.8 –60 Normal marine Low Moulfi-El-Houari et al. 1999;

Donnici & Serandei Barbero 2002Nonionella opima 0.5 Mediterranean Delta front, shelf Normal marine High Donnici & Serandei Barbero 2002Brizalina spathulata 0.1 Mediterranean Delta front, shelf Normal marine High Donnici & Serandei Barbero 2002;

Mendez et al. 2004Hanzawaya concentrica 0.6 Atlantic Inner shelf Normal marine Low Altenbach et al. 2003

Species

Mean frequency in clusters (%)Modern occurrence Environment DC1

Mean depth (m)

Mean salinity (‰)

Trophic level ReferencesA B C D E

454 Dominici et al. LETHAIA 41 (2008)

high ranks in samples are Cribroelphidium semistria-tum (6.3%), Ammonia tepida (6.1%), and Ammoniaperlucida (5.5%). The abundance of Ammonia tepida,a slightly euryhaline species typical of the lower

reaches of estuaries, the near absence of moreeuryhaline taxa (species cluster 2), and the very lowdiversity is consistent with either an upper shorefaceor a delta front depositional environment.

Fig. 4. Non-metric multidimensional scaling of the 58 samples. �A. Ordination subdivided according to Q-mode clusters, or biofacies,with values of species richness. Diversity increases from left to right, in the direction of interpreted increasing depths. �B. Same ordina-tion, with samples grouped according to lithofacies. Large overlaps show the difficulty to recognize subtle environmental variation basedsolely on facies analysis.

Fig. 5. Bivariate diagrams displaying variation along axis 1 of DCA. �A. Mean water depth estimated for 10 common species. �B. Meansalinity estimated for 11 species.

LETHAIA 41 (2008) Foraminifer biofacies 455

A second low-diversity biofacies is named afterTrochammina ochracea (eight samples, samplecluster C), characterized by Trochammina ochracea(up to 7.7%), T. inflata (up to 4.7%) and other eury-haline species (cluster 2). Ammonia beccarii (29%),A. perlucida (11.3%), A. tepida (10.6%), and themiliolids are locally important (Quinqueloculinaseminulum averages 4.9%). The lagoonal speciesCribrononion cf. lagunensis is also characteristic,albeit sparse (0.8%). Open marine species of cluster 5are nearly absent. This biofacies indicates a marsh orupper estuarine habitat, and generally weak connec-tions to the sea.

In the Ammonia parkinsoniana biofacies (sixsamples, sample cluster B), Ammonia beccarii,although ranked first, has a much lower abundancethan in the preceding assemblages (31.4%), anddiversity is low or intermediate. Characterizing formsare A. parkinsoniana (11%) and Cribroelphidiumsemistriatum (8%). The slightly euryhaline Ammoniaparkinsoniana and the shallow shoreface Elphidiummacellum, reunited in species-cluster 2, suggest thatthis assembly lived in shallow marine environmentstransitional with estuaries, marshes and tidal flats.

In the Quinqueloculina seminulum biofacies (11samples, sample cluster D), Ammonia beccarii isabundant (28.3%), followed by Quinqueloculinaseminulum (10.1%) and Protelphidium granosum(8.8%). The miliolids of species-cluster 3 and othermarine species of cluster 5 are characteristic, indi-cating vegetated bottoms and marine salinities.Diversity is from intermediate to high.

The Florilus boueanum biofacies (14 samples,sample cluster E) is labelled after the most abundantspecies (25.3%), with Ammonia beccarii rankedsecond overall (16.7%). Stenohaline species of species-cluster 2 dominate (Cribroelphidium semistriatum,11.6%; Proelphidium granosum, 6.4%, Fursenkoinaacuta, 2.6%; Reussella spinulosa, 2.3%; Elphidiumcrispum, 1.9%; Cancris auriculus, 1.9%). Euryhalinespecies are very rare, miliolids are not abundant,planktonic forms score an overall frequency around1.3%, and other benthic forms common to deepershelfal settings are well represented (Bulimina elon-gata, Brizalina spathulata, Planorbulina mediterranea).Diversity is high, as would be expected in an openshelf environment.

Biotic gradients

Modern distributions of characterizing taxa allowus to interpret the outputs of multivariate analysesin terms of palaeoecological gradients (Tables 1, 2).In species ordinations, the direction connecting

supratidal/upper intertidal species of the genusTrochammina to open shelf Bulimina spp. suggests adepth-related gradient both between and within-species clusters 2, 4 and 5 along a direction parallelto the axis of main variation (DC1), the shallowestspecies occupying the left part of the ordination(Fig. 3A). Also, the slightly divergent directions con-necting clusters 2-1 and clusters 2-4-3 have a strongDC1 component. Two main onshore–offshore gradi-ents are evident in the sample ordination (Figs 3, 4),one connecting the Trochammina ochracea to theAmmonia parkinsoniana biofacies, the other theAmmonia beccarii to the Quinqueloculina biofacies,both merging in the Florilus boueanum biofaciestypical of open marine mudstones (Fig. 4B). Thesetwo gradients correspond in the species ordination tothe gradient 2-1-5, with high scores along axis 2(DC2), and the gradient 2-4-3, with low scores alongDC2. To interpret what factors underlie maximumvariation, the indirect gradient analysis resultingfrom ordination was confronted with direct gradientsby plotting DC1 scores against preferred depths andsalinities of selected species (Fig. 5). A good directrelationship is shown in both cases, with depthestimates being slightly better aligned (polynomialcurve; R2 = 0.9115 against R2 = 0.8581). The shape ofthe curves, however, suggests that salinity is the maincontroller in very shallow waters, other depth-relatedfactors controlling biotic distributions at depths below20–30 m, i.e., below wave base.

The direction perpendicular to the main axis of theDCA species ordination is more difficult to interpret.It may be explained in terms of substratum type, withforms adapted to muddy substrata (clusters 1 and 5)having the highest DC2 score, sandy bottom species(cluster 4) intermediate values, and epiphytic forms(cluster 3) the lowest score. However, a literaturesurvey (Alve & Murray 1994; Donnici & SerandeiBarbero 2002; Altenbach et al. 2003) shows thataxis 2 of the DCA ordination can also be interpretedin terms of sedimentation and nutrient levels:low-sedimentation rates in mud-dominated sett-ings for species having a high DC2 score, and

Table 2. Analysis of similarity of the five biofacies.

BiofaciesGlobal R

Significance level of sample statistic

Number of permutations

Ammonia beccarii –0.030 54.2 999Quinqueloculina seminulum 0.538 0.8 999Trochammina ochracea 0.600 16.7 6Ammonia parkinsoniana 0.810 1.7 60Florilus boueanum 0.780 0.1 999


high-sedimentation rates in sand-dominated settingsfor species with a low DC2. The hypothesis of highsedimentation rates is consistent with the relativeposition of the Ammonia beccarii and Quinqueloculinaseminulum biofacies with respect to that of shallowmarine sandstones – off-centred towards the lowerpart in nonmetric ordination (Fig. 4B). Based onfacies analysis, these sandstones are interpreted asdistal, bioturbated delta front deposits (Benvenutiet al. 2007). During high-frequency transgressions,deltaic settings experienced lower sedimentationrates and high nutrient levels. The low DC2 score ofAmmonia beccarii, Quinqueloculina seminulum andall other miliolids allows their habitat to be inter-preted as an environment near the eutrophic end ofthe trophic continuum. This agrees with the highabundances of these species in the nutrient-rich beltof the modern Po delta front, Q. seminulum increas-ing distally (Donnici & Serandei Barbero 2002).Conversely, species of clusters 1, with the highestDC2, could indicate low-nutrient muddy bottoms(Cibicides lobatulus, Hanzawaia: Alve & Murray 1994),whereas species of cluster 5, promoted by the lowsedimentation rate under medium to high trophiclevels (Cancris auriculus: Altenbach et al. 2003), scoreintermediate DC2 values. The distribution of openshelf mudstones confirms this interpretation (Fig. 4B).

In summary, there is evidence of an onshore–offshore gradient in relatively eutrophic waters,under high rates of coarse-grained deposition, andanother, similar, gradient in meso- or oligotrophicwaters under lower net rates of deposition. Muddyoffshore bottoms are the common endpoint of bothgradients (Fig. 4), suggesting that the two differentregimes are recorded only at shallow depths, and thatthe nutrient regime in the Tuscan sea was controlledby terrestrial runoff.

Absolute depths and salinities

The relationships between the score along the axis ofmain variation of DCA, depth and salinity wereassessed by plotting preferred parameters for livingspecies with the DC1 score. The resulting bivariateplots illustrate the two most important environmen-tal gradients of foraminiferal species distributions(Fig. 5). The good results justify a comparison ofscore on axis 1 of sample DCA with sequence strati-graphic interpretations (Fig. 6), although some dis-tortion occurs at DC1 scores ≥ 4, where modern dataare insufficient to control the value of the calculatedpolynomial curves (Fig. 5). Estimated depths basedon DC1 are concordant in most cases with thesubdivision into systems tracts of the sequence

stratigraphic interpretation, even at elementarydepositional sequences. In fact, DC1 increases at eachtransgressive surface, and in particular at the passagebetween transgressive (TST) and maximum floodingsurface (MFS), across time-averaged and laterallytraceable shell beds. Accordingly, depth decreasesat the turn to highstand deposits (HST), with someexceptions (MFS-HST of sequences 4b and 4c). Theresults confirm the general palaeoenvironmentalreconstructions based on facies analysis (Benvenuti& Dominici 1992; Dominici 1994; Benvenuti et al.2007), for example the increasing depths recordedmoving from the Ponte a Elsa to the San Quintinosection, and the shallower depths of depositionrecorded in the San Miniato sequence with respect tothe Ponte a Elsa sequence (Benvenuti et al. 2007).Estimated depths for sequence 5 at the Poggio alLupo section would point to the existence of high-frequency, metre-thick regressive–transgressive cycles,unnoticed during early fieldwork (Benvenuti &Dominici 1992), but recognized during successiveanalyses (Benvenuti et al. 2007). However, in theintertidal to very-shallow subtidal settings repre-sented in the San Lorenzo and Catena sections,salinity alone could explain variations of DC1 score,invoking changes in river inputs or evaporation ratestied to land climate. This time interval is character-ized by major glacio-eustatic variations (Miller et al.2005). Accordingly, a mixed origin of DC1 variations,related to both eustasy and climate, most probablyexplain the observed patterns. Artefacts of the DC1-based calculations for samples with DC1 scores ≥ 4include decreased salinities recorded at open marinesettings (samples CNT67 and CAP7) and too-highdepth estimates for many samples of the Florilusboueanum biofacies (see Fig. 3B).

Community stability

Foraminifer assemblages are sensitive to palaeo-environmental parameters and can therefore be usedto test whether local communities of a given recurrentbiofacies are significantly different across boundariesof small-scale composite sequences. Thus, distur-bances related to sea-level lowstands with frequenciesin the order of 104 years might affect communitydynamics. To examine this, samples of each biofacieswere compared within and between sequences.Within-sequence comparisons of assemblages helpestimate small-scale variability within a givenenvironment, visualized by distances betweenassemblages collected in each composite sequence(Fig. 7). If samples of the same biofacies in differentsequences are more distant in MDS plots than


Fig. 6. Depth and salinity estimates for selected tracts of the succession; calculations based on score along DC1 (see Fig. 3B). Depthsgenerally conform to the interpreted sequence stratigraphic architecture; values increase in an upward direction at each transgressiveinterval (TST), with greatest depths recorded at maximum flooding surfaces (MFS) or near major shell beds (see Fig. 1). Highstanddeposits (HST), however, are not always marked by a shallowing-up (e.g., sequences 4b, 4c). Salinity estimates suggest important andmeaningful fluctuations along composite sequence 5.


samples collected in the same sequence, then thedata could be interpreted to mean that foraminiferacommunities show little stability and low levels ofmembership of species within communities (seeDominici & Kowalke 2007). In MDS ordinations,wide overlaps are present only in the Ammoniabeccarii biofacies, consistent with the hypothesizedexistence of an Ammonia beccarii group formed bydifferent species that are indistinguishable based onmorphological characters. Possible diagenetic over-prints due to preferential dissolution of foraminifertests could also be invoked, explaining the very lowspecies richness of many Ammonia beccarii assem-blages and their frequent association with siltstonesdevoid of macrofauna (Fig. 4B). The other four bio-facies show that local communities significantly varywhen habitats are cyclically re-established after sealevel lowstands. This is particularly evident for theQuinqueloculina seminulum and the Florilus boueanumbiofacies, which have the largest number of samples(Fig. 7D, E), a situation evidenced also by the analysisof similarity (Table 2). Since the Valdelsa basin wasfilled under a strong subsidence of tectonic origin(producing a Neogene succession of about 2000 m inthe study area; references in Benvenuti & Dominici1992), large gaps between elementary and compositesequences are improbable. Models of habitat tracking,or the lateral migration of communities in responseto shifting environments, imply the relative continuity

of environmental belts parallel to the coast and themaintenance of community composition and guildstructure through time (Brett et al. 2007). The presentstudy suggests that community dynamics are inter-rupted at each major glacio-eustatic cycle and thatforaminifera tend to show a species-specific behav-iour when reassembling after each sea-level lowstand.Stability is evident at the hierarchic level above thatof communities, corresponding to the biofacies or thecommunity type of previous literature (Bennington& Bambach 1996), but communities are never exactlythe same.

Conclusions

Multivariate analysis of abundance data is a powerfultool to interpret complex environmental controls onbiofacies. The present study on Pliocene marginalmarine benthic communities confirms that palaeo-ecological patterns are overprinted by dynamicprocesses tied to cycles of relative sea level change.Moreover, it proves that the study of foraminiferalassemblages has a great explicatory power regardingfacies successions and key stratigraphic surfaces.Environmental inferences calibrated with knowledgeof extant species suggest that salinity alone canexplain most part of the compositional variationsrecorded in coastal communities of intertidal-

Fig. 7. Non-metric multidimensional scaling ordination of samples of each biofacies. Samples are grouped by small-scale compositesequence. All plots, except the Ammonia beccarii biofacies, suggest that between-sequence differences in sample composition are signifi-cantly larger than within-sequence differences.


shallow subtidal depth range. From around thefair-weather wave base towards deeper settings,depth-related factors other than salinity control mostcompositional variations of the benthic fauna. Ineither case, DC1 scores can be used as a fine proxyof climate-related sea level change, provided that acontrol exists based on data from modern distribu-tions. Transgressive pulses occur in coincidence withthe most important and laterally continuous shellbeds, confirming that these are produced by lowrates of sedimentation. Secondary variations, recordedalong axis 2 of ordination plots (DC2), can beexplained as changes in the nutrient levels and in thesedimentary regime. The comparison of assemblagesof each given biofacies within and between sequencessuggests that Mediterranean foraminifer biofaciesrecur after cycles of sea-level change, but that patternsof abundance of individual species are never exactlythe same. This echoes the conclusions of other high-resolution studies.

Acknowledgements. – The authors thank Marit-Solveig Seidenk-rantz, Johannes Hohenegger and the editors for their thoughtfulreviews and Martin Zuschin, Maria Holzmann and Adele Bertinifor helpful discussions during several phases of the study.

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Supplementary material

The following supplemental material is available forthis article:

Table S1. Raw abundance data for bulk samples from Pliocenesuccessions of Valdelsa, Italy.

Table S2. Diversity indexes for bulk samples from Pliocene suc-cessions of Valdelsa, Italy.

This material is available as part of the online articlefrom:http://www.blackwell-synergy.com/doi/full/10.1111/j.1502-3931.2008.00099.x(This link will take you to the article abstract).

Please note: Blackwell Publishing is not responsiblefor the content or functionality of any supplementarymaterials supplied by the authors. Any queries (otherthan missing material) should be directed to thecorresponding author for the article.

foraminifer communities and environmental change in marginal marine sequences (pliocene, tuscany,...

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