© 2006 Blackwell Publishing Ltd www.blackwellpublishing.com/geb DOI: 10.1111/j.1466-822x.2005.00193.x

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RESEARCHPAPER

Blackwell Publishing, Ltd.

Patterns of diversity in microscopic animals: are they comparable to those in protists or in larger animals?

Diego Fontaneto*, Gentile Francesco Ficetola, Roberto Ambrosini

and Claudia Ricci

ABSTRACT

Aim

General patterns of biodiversity, such as latitudinal gradients and species-arearelationships, are found consistently in a wide range of organisms, but recent resultsfor protist diversity suggest that organisms shorter than 2 mm do not display suchpatterns. We tested this prediction in bdelloid rotifers, pluricellular metazoanssmaller than 2 mm, but with size and ecology comparable to protists.

Location

A single valley in northern Italy was surveyed in detail and compared toall available faunistic data on bdelloids worldwide.

Methods

We analysed 171 local assemblages of bdelloid rotifers living in 5 systemsof dry mosses and submerged mosses in running water and in lakes. We comparedpatterns of alpha, beta, and gamma diversity, and nestedness of metacommunities,with those known from protists and larger organisms.

Results

Bdelloid rotifers showed low local species richness (alpha diversity), withstrong habitat selection, as observed in larger organisms. The number of species dif-fered among systems, with a higher number of species in dry than in aquatic mosses.There was no hierarchical structure or exclusion of species in the metacommunitypattern within each system. Local diversity for the entire valley was surprisingly highcompared with worldwide bdelloid diversity, similar to observed patterns in protists.

Main Conclusions

Bdelloid rotifers have some of the peculiarities of protistbiodiversity, although at slightly different spatial scales, thus confirming the idea ofa major change in biodiversity patterns among organisms shorter than 2 mm.However, bdelloids show stronger habitat selection than protists. We suggest twopossible explanations for the observed patterns: (1) dispersal is very rare, and not allbdelloid clones are arriving everywhere; and (2) dispersal is effective in displacingpropagules, but environmental heterogeneity is very high and prevents many speciesfrom colonizing a given patch of moss.

Keywords

Bdelloidea, biodiversity, community, metacommunity, rotifera, species richness.

*Correspondence: Diego Fontaneto, Dipartimento di Biologia, Università di Milano, via Celoria 26, I-20133 Milano, Italy. E-mail: diego.fontaneto@unimi.it

Dipartimento di Biologia, Università di Milano,

via Celoria 26, I-20133 Milano, Italy.

INTRODUCTION

General patterns of biodiversity are found consistently across a

wide range of organisms. Many such patterns have been described,

for example latitudinal and altitudinal gradients, species-area

relationships, and species-energy relationships (e.g. Rosenzweig,

1995; Lawton, 1999; Andrew

et al

., 2003; Brehm

et al

., 2003;

Bonn

et al

., 2004; Davies

et al

., 2004; Dimitrakopoulos & Schmid,

2004; Gaston

et al

., 2005; McAbendroth

et al

., 2005; Rahbek,

2005). In addition, many organisms experience historical

constraints on their distributions at different scales. For example,

onycophorans and marsupials are distributed almost exclusively

in the Southern Hemisphere (Monge-Najera & Hou, 2000;

Sanmartin & Ronquist, 2004), and the local distribution of many

species of plants and animals in the Northern Hemisphere can

be explained by the location of glacial refugia (Hausdorf &

Henning, 2004; Tribsch, 2004). Although debates continue on

the processes that cause these patterns, and on the exact nature

of patterns in different groups, the existence of gradients and

structure in species distributions is clear.

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One limitation of these studies for establishing general diver-

sity patterns is that they all considered organisms longer than

2 mm. Recent results for microscopic organisms indicate a major

change in biodiversity patterns among organisms less than 2 mm

in body length (Finlay, 2002). For example, Fenchel

et al

. (1997)

counted the number of ciliates in the sediment beneath a

few square centimetres in a pond and found around 50% of all

species recorded during comprehensive sampling of that pond,

corresponding to about 8% of all named freshwater ciliates.

Similarly, Persson (2002) found roughly 25% of all known Swedish

sea-plankton dinoflagellates and diatoms in 100 ml of sediment.

Moreover, no latitudinal or species-area gradients in species

composition has ever been found. Hence, Fenchel & Finlay

(2004) concluded that, for microscopic organisms, ‘everything is

everywhere’ and that the protist species found in a given habitat

are a function only of habitat properties and not of historical

factors or restricted dispersal.

The degree of endemism is much higher in larger animals. For

example, in amphibians, even the richest countries, such as Brazil

and Colombia, possess only 8% and 6% of the global diversity

(Global Amphibian Assessment, 2005). Similarly, Europe has

17% of the species of ground beetles known worldwide (Audisio

& Vigna Taglianti, 2004) and each sampling locality presents less

than 0.1% of the global diversity (e.g. Allegro & Sciaky, 2003; Kotze

& O’Hara, 2003). This difference between organisms larger and

smaller than 2 mm seems to be related to size and not to environ-

ment, since many copepods, living in the same habitats as protists

but larger that 2 mm, share patterns of distribution with larger

animals (Jersabek

et al

., 2001; Suarez-Morales

et al

., 2004).

The difference in diversity patterns between small and large

organisms can be considered in terms of species-area curves. At

the local scale (alpha diversity), small organisms dominate in

species richness: many more species of small organisms than of

large ones can co-occur at finer scales. However, the species-area

curve increases less steeply among small organisms than among

large organisms. In macrofaunal groups, the curves increase

monotonically because larger areas contain different faunistic or

floristic domains and more endemic species are included. In

contrast, the worldwide richness (gamma diversity) of protists is

not much larger than local richness. No true endemism is known

in protists and most species are believed to have cosmopolitan

distributions (Finlay, 2002). For example, about 50% of all named

species of heterotrophic flagellates have been recorded in a small

Danish Bay (Fenchel & Finlay, 2004). Moreover, differences in

species composition among samples (beta diversity) appear to be

due to strong habitat differences and species preferences, and not

to biogeographical constraints to dispersal. For example, irrespective

of geographical location, moisture is the most important factor in

controlling the distribution of testate amoebae species (Mitchell

et al

., 1999). Of course unreliable taxonomy in protists could

mask true distributions (Coleman, 2002), but studies of closely

related forms from different areas demonstrate that isolates from

different areas can mate with each other, confirming true cosmo-

politism (Finlay & Fenchel, 2002).

The expectation for organisms smaller than 2 mm is therefore

to have very high local richness compared to a relatively low

worldwide richness, with differences among areas due only to

habitat heterogeneity. These expectations derive from studies on

small unicellular organisms, but do similar patterns apply to

small, multicellular organisms? We propose to test this hypothesis

using as a model microscopic but multicellular bdelloid rotifers

living in mosses. Bdelloid rotifers are a group of microscopic

animals (on average 200–600

µ

m in length) belonging to the so

called ‘meiofauna’. Meiofaunal organisms are the same size as

unicellular organisms, but they are true pluricellular animals, with

recognizable organs and apparatuses. Bdelloid rotifers, and other

terrestrial meiofaunal groups such as tardigrades, gastrotrichs

and some nematodes, share with protists size and other features:

(1) they live in the same aquatic interstitial habitats, where they

can be very abundant (Linhart

et al

., 2002; Wallace & Ricci,

2002); (2) they have amictic reproduction, allowing them to

increase rapidly in population size (Ricci, 2001); and (3) they are

able to resist drought or freezing by entering dormant stages,

which may also represent propagules for dispersal (Cáceres,

1997; Örstan, 1998). Do bdelloid rotifers share diversity features

with protists, because of their similar size, biology and ecology?

Or, if their distributions are similar to those of other larger

multicellular organisms, what might be the biological causes of

the differences from protist diversity? We are unaware of existing

studies on the community composition of a meiofaunal group in

continental habitats.

We focus on 171 local assemblages of bdelloid rotifers found in

moss cushions of similar size in a valley in northern Italy occupy-

ing three different habitats: terrestrial mosses, mosses in streams,

and mosses in lakes. The habitats differ in ecological features,

such as water availability and oxygenation, and also in the amount

of connectivity among moss patches: greater potential for dispersal

exists between local assemblages in a single stream than among

terrestrial moss patches separated by bare rock, or among lakes in

different hydrographical basins.

METHODS

Field procedures

All samples were collected haphazardly along a single valley in

northern Italy, Sesia Valley.

Each sample consisted of 5 cm

2

of mosses along with any

adhering soil particles. To avoid differences in growth stage

of mosses we collected our samples from the central, more

homogeneous part of each cushion. All moss cushions were

approximately 15–25 cm in diameter. Samples were taken directly

to the laboratory and bdelloids were isolated under a dissection

microscope. All the bdelloid rotifers present in the sample were

determined and counted. Species were identified under a

compound microscope at 100–1000x following Donner (1965).

We defined as a community the local assemblage of all species

encountered in each sample.

Almost no previous knowledge is available on bdelloid species

presence in different mosses, but there is no evidence of species-

specificity between bdelloids and moss or lichen species (Burger,

1948; Francez, 1980; Ricci, 1987). Therefore, as a measure of

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habitat we used a similar classification of moisture content in

mosses as used for protist studies (Jung, 1936; Meisterfeld, 1977),

rather than discriminating moss species. We categorized

three different kind of mosses: (1) completely dry terrestrial

mosses, called ‘dry’, (2) submerged mosses in stagnant water

from oligotrophic lakes, called ‘lentic’ and (3) submerged mosses

in running water, called ‘lotic’. These three habitats are at the

extremes of the scale of moisture: completely submerged or

completely dry.

Dry, terrestrial moss cushions

We collected 24 samples of moss along an altitudinal transect from

800 m (municipality of Campertogno, Sesia Valley, Piedmont,

northern Italy, approximate Gauss-Boaga coordinates 1424750 E,

5072400 N) to about 1800 m (Becco della Guardia Mount) in

spring 2002. All sampled mosses had a northern exposure.

Mosses were collected both on rocks (gneiss in all cases) and tree

trunks (at 20 cm from the base of different trees).

Lentic, alpine lakes

We sampled submerged mosses in 16 alpine lakes above 1700 m

in the Sesia Valley during the summers of 2001 and 2002 (see

Fontaneto & Melone, 2003 for details) and in Argnaccia Lake

(1100 m a.s.l.), in the municipality of Campertogno. Four different

mosses were haphazardly sampled in each lake, and the diversity of

each lake is the cumulative diversity of these 4 samples. All lakes

were on acidic substrates and had similar pH and temperature.

Lotic mosses in streams

We sampled submerged mosses in three different streams during

summer 2003. We sampled 15 bdelloid local assemblages, named

R1 to R15 from upstream to downstream, along Res Stream

(about 900 m a.s.l.), and 15 local assemblages, A1 to A15, along

Argnaccia Stream (about 900 m a.s.l.) (see Fontaneto

et al

.,

2004b). One hundred local assemblages, named V00 to V99,

were analysed along Valnava Stream (about 400 m a.s.l.) (see

Fontaneto

et al

., 2005 for details). Res and Argnaccia streams

are on acidic rock substrates, while Valnava is partially on

calcareous rocks.

This structure allows us to propose possible relationships with

(1) moisture of the moss, as mosses in lakes (lentic) and streams

(lotic) are aquatic, permanently submerged habitats, while dry

mosses are usually dry and became wet only during rain, and

(2) connectivity of the system, as mosses inside each stream are

connected by water flow while terrestrial mosses and alpine lakes

have no direct connection between patches.

Community analyses

We treat the local assemblage of bdelloid species in each moss

cushion as a potentially isolated community: although bdelloids

can creep on a substratum and swim in water, they cannot move

actively for long distances (Örstan, 1998).

Species richness

Local richness (alpha diversity) was treated as the number of

species in each moss patch. To detect differences in local species

richness among the 3 habitats, and then among the 3 streams, we

used analysis of variance (

), without transforming our

original count data because residuals were normally distributed.

Tukey Post-Hoc Honestly Significant Difference (Crawley, 2002)

was then used to recognize significantly different habitats.

Overall richness (gamma diversity) was obtained by counting

all species found across all habitats, dry, lentic or lotic. Richness in

each habitat was compared through rarefaction curves (Colwell

& Coddington, 1994), obtained by plotting the average number of

species in the cumulative number of analysed local assemblages,

through resampling techniques, using

EstimateS

7 (Colwell,

2004). We also estimated the diversity in each system and overall

according to ICE, the Incidence-based Coverage Estimator,

which estimates the overall number of species given the observed

number of species and how many species are found only once or

twice (Chazdon

et al

., 1998).

Species replacement in space (beta diversity)

First, we evaluated differences in species composition among the

three habitats (dry, lentic and lotic). We used reciprocal averaging

to ordinate the data matrix, using the first axis only, as proposed

by Leibold and Mikkelson (2002), so that sites with the most

similar species list are close together and species with the most

similar distribution are close together. Then we tested the signi-

ficance of the differences in species composition of local assem-

blages in the three different habitats.

We used Jaccard’s distances as a dissimilarity index for all the

pairwise comparisons and tested for significant differences using

analysis of similarities (

), based on 1000 permutations,

using the software R 2.0.1, package vegan (R Development Core

Team, 2004). We repeated the analysis to test for differences in

species composition among the local assemblages of the three

different streams.

To analyse species replacements within each habitat in detail, we

performed the analysis of metacommunity structure proposed

by Leibold and Mikkelson (2002). We defined as a metacommunity

all the local assemblages in each system, so we obtained 5 different

metacommunities, one from dry mosses, one from lentic mosses

and one from each lotic system. As these metacommunities came

from different habitats with different ecological features and

different connectivity of the patches, we tested whether there were

different rates of species replacement among local assemblages.

The probability of obtaining the observed spatial turnover was

calculated using a Monte Carlo simulation. For each metacommu-

nity, we generated 200 random matrices following a ‘random 0

Null Model’, subject only to the constraint that the matrices have

the same number of presences of the analysed metacommunity,

and that no row or column have only absences (Leibold &

Mikkelson, 2002). We tested the significance of differences

between the observed and the simulated matrices using a two-

tailed

z

-test. Low rates of spatial replacements (low turnover)

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represent nested structures, with hierarchical structures among

communities. Higher rates than expected provide evidence of

groups of species that exclude each other.

A high rate of species replacement, that is high spatial turnover of

species, is the opposite of nestedness; therefore, as a confirmation of

the results obtained by the previous procedure, we used Atmar

and Patterson’s (1995) nestedness calculator. This program uses

a thermodynamic model and measures the extent of order in a

matrix (T

°

) by Monte Carlo simulations (Atmar & Patterson, 1993).

The null-model normally used for this kind of analysis (Null Model

0) is known to overestimate the degree of nestedness; therefore, we

generated random matrices using the Null Model 1 proposed by

Fischer and Lindenmayer (2002). We generated random matrices

based on Null-model 1 using the program Random Matrix

Generator (P. Colombo, 2003), and subsequently we loaded them

into the nestedness calculator. The T

°

values for each matrix were

recorded; then we calculated the mean and standard deviation of

the resulting distribution of T

°

values. We calculated the associated

P

-values using a two-tailed

z

-test, performing 50 runs of Monte Carlo

simulation, as suggested by Fischer and Lindenmayer (2002).

RESULTS

Species richness

A total of 73 species was identified, 45 species in 24 terrestrial

mosses, 20 species in 17 alpine lakes, and 17, 15 and 8 species in

local assemblages from Res, Valnava and Argnaccia streams,

respectively (Fig. 1). Undetermined species, named ‘sp.’ followed

by a number, refer to morphotaxa that are recognizable but are

not previously described.

Species richness of samples differed significantly among the 5

systems (

test:

F

4,166

= 16.75,

P

< 0.0001): species richness

in alpine lakes was lower than in all the other systems, and species

richness in Res stream higher than in the other aquatic systems

(Table 1). These differences, although highly significant, did not

relate to any simple difference of aquatic versus terrestrial habi-

tats or connected versus unconnected systems.

The curves of the cumulative number of species showed slopes

with sharp differences among systems (Fig. 2): systems of mosses

in running water soon reached an asymptotic value and the

observed number of species was very close to the estimated one

(Table 2). The systems of dry terrestrial mosses and of mosses in

lentic lakes were far from reaching an asymptotic behaviour and

the number of estimated species was much higher than the

observed one. In this case the differences could be related to our

prior predictions: mosses within each stream are connected and

therefore species assemblages more similar to one another.

Differences among communities

The three habitats were almost completely identifiable in the

ordered matrix (Fig. 1), showing strong habitat specificity in

bdelloid rotifers. Very few species were shared by lentic and lotic

systems, or by lotic and dry mosses. Even fewer were in common

between lentic and dry samples. Differences in species composition

of the local assemblages among the three habitats were significant

(

test:

R

= 0.904,

P

< 0.001), as were the differences

among the three streams (

test:

R

= 0.951,

P

< 0.001).

Each habitat could be clearly identified by its species and even

each stream could be recognized as different from the others.

Analysing each system by itself, a random distribution of

species was always found (Table 3). Using the nestedness calculator

with the correction of Fischer and Lindenmayer (2002), patterns

of species replacements were all random (Table 4), consistent

with the previous method. No hierarchical structure in species

distribution, nor exclusion of species, was found within any system

of local assemblages.

The only difference that can be seen among the matrices of the

five systems is that data sets from terrestrial mosses and alpine

lakes have a significantly lower percentage of occupied cells than

those originated from mosses in each stream (

test:

F

1,3

=

Table 1 Number of species in each community: n, number of communities in each analysed system of mosses; mean (stdev), average number of species and standard deviation; and P-values of the Tukey Post-Hoc test. Significant values are indicated by an asterisk (*); 0.000 means values < 0.001

System n Mean (stdev) Name Valnava Res Argnaccia Lakes

stream 1 100 5.71 (1.56) Valnava

stream 2 15 7.60 (1.18) Res 0.000*

stream 3 15 5.40 (0.91) Argnaccia 0.956 0.001*

lakes 17 3.24 (1.86) lakes 0.000* 0.000* 0.001*

terrestrial 24 6.38 (2.02) terrestrial 0.351 0.133 0.338 0.000*

Table 2 Number of species in each system, estimated number (ICE) and percentage of observed species

System ICE Observed %

overall 91.82 73 79.5

terrestrial 63.83 45 70.5

lakes 37.3 20 53.6

streams 25.34 25 98.7

Argnaccia 17 17 100.0

Res 8 8 100.0

Valnava 16.85 15 89.0

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29.34,

P

= 0.012 on arcsin-squareroot transformed data). This is

because average similarity between local assemblages is higher in

stream systems than in the other two systems.

DISCUSSION

The analysis of distribution of bdelloid species in mosses from

different habitats revealed: (1) few species in each single assemblage

(low alpha diversity); (2) significant differences among systems, but

not in relation to prior expectations relating to presumed connect-

edness or moisture content; (3) that the overall number of species

(gamma diversity) differed among systems, with a higher number

of species in dry than in aquatic mosses; (4) different species compo-

sition of local assemblages from different systems, indicating strong

habitat selection; and (5) no hierarchical structure or clear exclusion

of species in the metacommunity pattern within each system.

Figure 1 Matrix of the presence of species in all the analysed communities, ordered with reciprocal averaging. Habitat type: ( ) terrestrial, ( ) lakes, (�) streams.

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Comparing our results with what is known on protists, one

difference is straightforward: local species richness in bdelloids is

much lower. Fenchel

et al

. (1997) found 130 species of ciliates

beneath few cm

2

of sediment surface, while we never found more

than 10 bdelloid species from 5 cm

2

of moss. In that study many

protist species were obtained from the same sample by mani-

pulating environmental conditions (e.g. light, temperature,

redox gradients and food). A similar response is improbable for

bdelloids, as presence/absence of available water is the only

trigger known to reactivate bdelloid propagules (Cáceres, 1997;

Ricci, 2001). Hence, we are confident that all bdelloid species

present in our samples recovered after rehydratation, so that our

estimate of biodiversity is unbiased. However, if we think of local

richness as being the species present in one small geographical

area, and not only the species inside a single moss patch, then the

bdelloid local diversity is still a high fraction of the global diversity.

The 171 local assemblages in the Sesia Valley included 73 species,

which represents about 20% of all known bdelloid rotifers world-

wide. This is a very high percentage, keeping in mind that we did

not collect bdelloids from all their known habitats such as lichens,

Sphagnum

, soil or small bogs. In this way protists and bdelloids

have a similar pattern: local species richness is a fairly large

subsample of the worldwide species richness. Taxonomists working

on protists and bdelloids hoped to find weird and interesting new

organisms during the scientific expeditions in remote areas in the

world in the last two centuries, but most of the animals they

found could be ascribed to already known taxa. The saying

‘everything is everywhere’ Fenchel and Finlay (2004) used to

characterize protist distributions could be true also for bdelloids.

Due to the potential for dispersal in bdelloids provided by

their dormant propagules, the assumption of cosmopolitan

distributions is plausible. However, we still do not know if the

strictly morphological approach used in bdelloid identification is

discriminating real different lineages or whether there are many

more cryptic species awaiting discovery. Recent morphological

analyses of bdelloid species using scanning electron microscopy

have found detailed differences between similar animals from

different geographical areas (e.g. Ricci

et al

., 2003), but also

between animals collected within a few kilometres of one another

(e.g. Fontaneto

et al

., 2004a): the presence of sibling species is

likely underestimated, but it might not change greatly the pattern

of cosmopolitan distributions. The use of molecular barcoding

for species identification as proposed by Hebert

et al

. (2003)

would be invaluable to answer questions about the true distribu-

tion patterns in bdelloids. If morphospecies at least represent

monophyletic groups of lineages, the biogeographical patterning

is likely to still be valid, but at this stage of the knowledge, we

cannot confirm or deny this point. The first DNA data using

mitochondrial genes are showing a correlation between geograph-

ical distances and sequence divergences but with rapid dispersal:

Birky

et al

. (2005) suggested that bdelloid species could have

dispersed around the world many times since their divergence,

Figure 2 Average cumulative number of species with increasing number of communities in the 5 analysed systems. Average numbers of species were obtained through randomization (Colwell & Coddington, 1994).

Table 3 Probability of species replacements in analysed metacommunities of bdelloid rotifers following Leibold and Mikkelson (2002). P-values were obtained by comparing the observed number of replacements with a distribution of number of replacements obtained from 200 matrices generated by Monte Carlo simulations

sites*species species replacement

terrestrial mosses 24*45 random, P = 0.07

alpine lakes 17*19 random, P = 0.13

Res stream 15*17 random, P = 0.63

Argnaccia stream 15*8 random, P = 0.67

Valnava stream 10*15 random, P = 0.75

Table 4 Nestedness values following Atmar and Patterson (1993); µ and σ were obtained from 50 matrices randomly generated by Monte Carlo simulations following Null-model 1 (Fischer & Lindenmayer, 2002)

System Matrix fill %

Matrix

temperature T° µ σ P Pattern

terrestrial mosses 14.1 33.23 29.72 3.69 0.342 random

alpine lakes 16.7 17.59 25.54 5.20 0.127 random

Res stream 44.7 40.97 35.56 3.43 0.115 random

Argnaccia stream 62.8 26.89 22.52 6.14 0.477 random

Valnava stream 43.3 41.09 32.71 5.54 0.131 random

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consistent with cosmopolitan distributions. Monogonont

rotifers show a higher degree of geographical constraint than

previously thought (e.g. Segers, 2001; Gomez

et al

., 2002), but a

direct comparison with this taxon is not possible, as they repro-

duce by sex occasionally, and only hypotheses can be drawn on

the differences in speciation patterns without sex in bdelloids

(Barraclough

et al

., 2003).

Apart from cosmopolitanism, bdelloid species seem to be very

specific in their choice of substratum: almost no species overlap

was evident among the three analysed habitats. This means that

not all bdelloid propagules arriving in a place can survive, but that

at least three groups of moss-dwelling species can be described,

those able to live in dry terrestrial mosses, in submerged mosses

from running water and in submerged mosses from alpine lakes.

However, even within the riverine habitat, the three streams were

different in species composition. The two most similar streams,

Argnaccia and Res, were at higher elevation and on more acidic

substratum than the other stream, but further replicates

from different streams would be needed to correlate differences

with elevation or pH. Local assemblages in lakes were different

among different lakes, although lakes had similar pH, temperature,

rocky substratum, and surrounding and submerged vegetation

(Fontaneto & Melone, 2003). This strong selection for the habitat

is in contrast with the patterns found in protists; the generalization

that ‘most microorganisms can be found at the local seashore or

lake or, for that matter, in a garden pond’ (Fenchel & Finlay,

2004) might be true for protists but not for bdelloids. The above

generalization does not fit all protists, as a recent study on testate

amoeba (Protozoa, Rhizopoda) found significant differences in

species composition of communities from mosses with different

moisture (Vincke

et al

., 2004). The habitat specificity of some

bdelloid species can be confirmed by comparison with other

faunistic surveys; the only available recent data are from riverine

ecosystems (e.g. Zullini & Ricci, 1980; Schmid-Araya, 1998), and

their species lists are very close to the communities of our streams.

This does argue for a habitat-type explanation for rotifers not

being found everywhere. However, this explanation of habitat

differences between the streams is a posteriori, and we do not

have repeated habitat measures or samples to show that it is

habitat characteristics, rather than particular sites just being

separate, that determines composition in species.

An alternative explanation could be that colonization of each

habitat is rare and random from the global pool; therefore, there

are good chances of getting significant differences in species

composition. Once an area is colonized, subsequent colonization

events are harder, hence the partitioning among different areas

we sampled. More generally, bdelloids might have globally

cosmopolitan distributions but dispersal is rare enough that they

still have patchy distributions at narrower scales, unrelated to

habitat characteristics. This hypothesis could explain why species

replacements among local assemblages within each single system

revealed a random pattern, and why we could not identify groups

or gradients of species.

We suggest two possible explanations for the observed patterns:

(1) dispersal is very rare, and not all propagules are arriving

everywhere, so a species potentially able to live in a local assemblage

can be absent because no individual of this species ever reached

that particular moss; and (2) dispersal is effective in displacing

propagules, but environmental heterogeneity is much higher

than we measured: what is defined as a homogeneous system in

our analysis can be not homogeneous for bdelloids. These two

hypotheses, the former linked to stochastic events, and the latter

to ecological features, are not mutually exclusive and can both

contribute to the observed diversity pattern. Both hypotheses on

the effect of dispersal are supported by studies on other freshwater

organisms (e.g. Bohonak & Jenkins, 2003; Cohen & Shurin, 2003).

We found no differences in species occurrence in lakes

analysed in two subsequent years (Fontaneto & Melone, 2003),

suggesting that communities could be stable through time. This

observation is not enough to discriminate between the two

hypotheses, as in the case of effective dispersal, we do not know

whether different populations of the same species are replacing

one another through time, or if populations are stable. Ricci

et al

.

(1988) suggested an existing temporal turnover of different

clones of one bdelloid species in mosses, while De Meester

et al

.

(2002) suggested a monopolization hypothesis, with priority

effect, for other freshwater organisms.

Fenchel and Finlay (2004) argued that the composition and

diversity of a local biotic community in protists depend only on

the immigration and extinction of species populations, linked to

abiotic features, and not to interspecific interactions such as

competition and predation. This supports the general emphasis

given to dispersal and extinction as statistical phenomena more

important than species interactions in driving community

structure and diversity (Bell, 2001; Hubbell, 2001). The neutral

models apply only to guilds of species ecologically identical or

similar. This can be a reliable approximation for protists (Fenchel

& Finlay, 2004), and possibly for bdelloids, all being microfagous

filter-feeders or scrapers with very similar masticatory apparatuses

(Melone

et al

., 1998; Melone & Fontaneto, 2005). Moreover, the

random replacements of bdelloid species among local assem-

blages inside the same habitat could be easily explained by these

‘neutral’ models.

The differences in local species richness observed between

protists and bdelloids could be due to differences in reproductive

rates and therefore in effective population size: protists have

huge populations, and higher reproductive rates than bdelloids

(Ricci, 1983; Fenchel & Finlay, 2004). Therefore, a lower number

of individuals, and thus a lower number of propagules, can be

linked to low local richness, with higher differences among

patches, if each colonization event is less probable. Of course this

hypothesis has to be tested in further experiments.

In summary, it seems that bdelloid rotifers have some of the

peculiarities of protist biodiversity, but with much stronger

habitat selection. The most plausible explanation is that because

of their small size, bdelloids can be as easily dispersed as protists,

but then multicellular organisms are more complex in their

interactions with the environment and propagules cannot

survive everywhere.

Of course more work is needed in order to understand

meiofaunal biodiversity. No large data sets are available for other

small meiofaunal organisms. Data from mites, springtails and

D. Fontaneto

et al.

160

Global Ecology and Biogeography

,

15

, 153–162 © 2006 Blackwell Publishing Ltd

harpacticoid copepods indicate a higher degree of endemism and

historic biogeographical constraint (e.g. Jersabek

et al

., 2001;

Garrick

et al

., 2004; Niedbala, 2004), but these organisms,

although small, are larger than bdelloids and size matters for

dispersal mechanisms.

Regrettably, determining the global distribution of micro-

scopic organisms is a more difficult task than for large plants and

animals, because of undersampling in many parts of the world.

The vast majority of records of protists and meiofauna derive

from Europe and North America, with many fewer from most

other parts of the world. Intensive sampling is needed to clarify

biodiversity patterns of microscopic organisms. Even in the ‘well

known’ areas faunistic data are not available: only 54 bdelloid

species were known in Italy before this study (Braioni & Ricci,

1995; Fauna Europaea Service, 2004), and in our small valley we

found 73 species. Greater sampling and detailed molecular analyses

are needed to determine the true diversity of bdelloid rotifers.

Our results suggest that the geographical distribution of animals

and therefore biodiversity patterns may be strongly influenced

by animal size. This evidence of a gap between small and large

animals should be carefully taken into account in future studies

of biodiversity patterns.

ACKNOWLEDGEMENTS

We wish to thank Mathew A. Leibold for providing us the macro

for metacommunity analysis, P. Colombo for writing the

program Random Matrix Generator, Timothy G. Barraclough

for his suggestions on an earlier draft of the manuscript and for

revising the English text, and two anonymous reviewers for their

suggestions. Financial support came from a grant by the Italian

Space Agency.

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BIOSKETCHES

Diego Fontaneto has research interest in the fields of

systematics, phylogeny, and community ecology of

invertebrates, in particular of bdelloid rotifers.

G. Francesco Ficetola is interested in determinants of

biodiversity. He is currently researching conservation

biology and community ecology of amphibians and the

role of environmental factors at different scales.

Roberto Ambrosini is interested in behavioural ecology

and conservation biology of birds, in particular of the

barn swallow.

Claudia Ricci is a zoologist dealing with systematics and

ecology of bdelloid rotifers and thus with anhydrobiotic

responses, parthenogenetic reproduction and its

consequences on populations.