snails and altitude south france

8/13/2019 Snails and Altitude South France

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O R I G I N A LA R T I C L E

Multi-scale altitudinal patterns in species

richness of land snail communities

in south-eastern France

Sebastien Aubry1*, Frederic Magnin2, Veronique Bonnet2 and Richard C.

Preece1

1Department of Zoology, University Museum of

Zoology, University of Cambridge, Cambridge,

UK and 2Institut Mediterraneen dEcologie

et de Paleoecologie, U.M.R. 6116 du CNRS,

Batiment Villemin, Europole de lArbois,

Aix-en-Provence Cedex, France

*Correspondence: Sebastien Aubry, Institut

Mediterraneen dEcologie et de Paleoecologie,

U.M.R. 6116 du CNRS, Batiment Villemin,

Europole de lArbois BP 80, F 13545

Aix-en-Provence Cedex 04, France.

E-mail: [email protected]

ABS T RACT

Aim Species richness is an important feature of communities that varies along

elevational gradients. Different patterns of distribution have been described in the

literature for various taxonomic groups. This study aims to distinguish between

species density and species richness and to describe, for land snails in south-

eastern France, the altitudinal patterns of both at different spatial scales.

Location The study was conducted on five calcareous mountains in south-

eastern France (Etoile, Sainte Baume, Sainte Victoire, Ventoux and Queyras).

Methods Stratified sampling according to vegetation and altitude wasundertaken on five mountains, forming a composite altitudinal gradient

ranging from 100 to 3100 m. Visual searching and analysis of turf samples

were undertaken to collect land snail species. Species density is defined as the

number of species found within quadrats of 25 m 2. Species richness is defined as

the number of species found within an elevation zone. Different methods

involving accumulation curves are used to describe the patterns in species

richness. Elevation zones of different sizes are studied.

Results Eighty-seven species of land snails were recovered from 209 samples

analysed during this study. Land snail species density, which can vary between

29 and 1 species per 25 m2, decreases logarithmically with increasing altitude

along the full gradient. However, on each mountain separately, only a linear

decrease is observable. The climatic altitudinal gradient can explain a large part

of this pattern, but the great variability suggests that other factors, such as

heterogeneity of ground cover, also exert an influence on species density. The

altitudinal pattern of species richness varies depending on the spatial resolution

of the study. At fine resolution (altitudinal zones of 100 m) land snail species

richness forms a plateau at altitudes below 1000 m, before decreasing with

increasing altitude. At coarse resolution (altitudinal zones of 500 and 1000 m)

the relationship becomes linear.

Main conclusions This study reveals that land snail species density and land

snail species richness form two different altitudinal patterns. Species density

exhibits strong variability between sites of comparable altitude. A large number of

samples seem necessary to study altitudinal patterns of species density. Speciesdensity decreases logarithmically with increasing altitude. Above a critical

altitudinal threshold, this decrease lessens below the rate seen in the first 1500 m.

Different methods exist to scale-up species density to species richness but these

often produce different patterns. In this study, the use of accumulation curves has

yielded a pattern of species richness showing a plateau at low altitude, whereas

simple plotting of known altitudinal ranges from single mountains would have

produced stronger mid-altitudinal peaks. This study shows that not only factors

Journal of Biogeography(J. Biogeogr.) (2005) 32, 985998

2005 Blackwell Publishing Ltd www.blackwellpublishing.com/jbi doi:10.1111/j.1365-2699.2005.01275.x 985


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INT RO DUCT IO N

Species richness, defined as the number of species, is the

simplest way to describe communities at local and regional

scales (Magurran, 1988). The study of patterns of species

richness is pervasive in ecology and biogeography and it is well

established in the literature that increased altitude generally

results in reduced species richness in both plants and animals

(MacArthur, 1972; McCoy, 1990). However, two main

patterns have been documented, a monotonic decrease in

species richness with increasing altitude and a hump-shapedrelationship with a peak in richness at intermediate altitude

(Rahbek, 1995). Both patterns have been observed for species

richness per quadrat, also called species density, as well as for

the richness of an entire elevational zone (Lomolino, 2001).

The shape of the relationship depends on the taxa studied, the

latitude and the ecological conditions of the investigated area

(Sfenthourakis, 1992) but it also depends on the sampling

strategy, which can also lead to a biased description of the

pattern (McCoy, 1990). Furthermore, despite a large number

of publications (Rahbek, 1995) and the suggestion of several

explanatory hypotheses for these patterns (MacArthur, 1972;

Terborgh, 1977; Lawton et al., 1987; McCoy, 1990; Stevens,

1992; OBrien, 1993, 1998; Colwell & Lees, 2000; Gaston, 2000;

Lomolino, 2001), the effect of altitude remains controversial

(Stevens, 1992; Rahbek, 1995). Data, collected with adapted

methods, from new communities and new regions at different

levels are needed if the distribution pattern of montane taxa is

to be properly understood (Lomolino, 2001; Li et al., 2003).

Ecological factors and species interact at different scales in

space and time. At the same time, the scale of observation will

lead to the recognition of different factors and reveal different

patterns. These scales and factors therefore need to be integ-

rated into a theoretical hierarchical framework (Whittaker,

1960; Allen & Starr, 1982; Blondel, 1995; Willis & Whittaker,

2002). Willis & Whittaker (2002), while stressing the necessityof controlling area, highlighted the advantage of studying

diversity at different scales to reveal where in the continuum

particular factors have greatest relevance.

The distinction between species richness and species density

is rarely made in the literature although the shape of the

altitudinal pattern is strongly dependent on this difference

(Lomolino, 2001). The description of species density patterns

is relatively straightforward and usually results from the

measurements of species richness within plots along altitudinal

transects. However, by using only a few plots, this method

usually ignores the strong variability that exists between plots

at the same altitude (but see Lee et al., 2004). The description

of altitudinal patterns of species richness, supposedly inde-

pendent of the sampled area as well as of the actual area of the

elevation zone, is more complex. Indeed, species density is

often measured from only a few plots within a habitat type per

elevation zone and assumed to correspond to species richness

(e.g. McCoy, 1990). Classically, a second method, computing

species richness from the species elevation ranges, either

derived from the literature or from new sampling, is used to

scale-up to the richness of an entire elevation zone (e.g.Sanders, 2002; Bhattarai et al., 2004). Although the distribu-

tion of land snail species in France is relatively well known

(Kerney et al., 1999), the altitudinal distribution of most of

them has yet to be established, especially in the specific context

of the Mediterranean region. Furthermore, the use of such

species altitudinal ranges can produce spurious patterns of

richness (Zapata et al., 2003).

The main objective of the present study is to describe the

altitudinal patterns of both species density and species richness

of land snail species on the mountains of south-eastern France.

A large number of quadrats were sampled to take into account

the large variability of species density while controlling for

sampling effort and area (Whittaker et al., 2001; Lee et al.,

2004). In the present work, the relationship between land snail

species density and altitude is first studied at the restricted

scale of the quadrat (25 m2). At this scale, the influence of

habitat heterogeneity on the number of species is tested. An

attempt is then made to scale species richness up to the

landscape scale and to describe the patterns of the overall

number of species per elevation zones of different sizes.

M E T HO DS

Study area

This study was undertaken in south-eastern France, where

many of the mountains are not only composed of calcareous

bedrock, which supports thriving land snail communities, but

also cover an extensive altitudinal gradient from sea level to

elevations above 3000 m. Furthermore, the land snails of this

region are reasonably well known, in terms of distribution as

well as taxonomically, which provides a good foundation for

assessment of diversity, distribution and abundance. A samp-

ling strategy has been devised to cover the full altitudinal range

available in the region. This strategy produces a composite

such as temperatures and habitat heterogeneity, but also an ecotone effect, are

responsible for the observed patterns.

Keywords

Elevation gradient, France, land snails, Mediterranean mountains, rarefaction,

species accumulation curves, species density, species richness.

S. Aubry et al.

986 Journal of Biogeography32, 985998, 2005 Blackwell Publishing Ltd


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altitudinal gradient associating mountains with overlapping

altitudinal ranges. Five mountains were chosen from the

Etoile mountain range, bordering the Mediterranean, to the

Southern Alps region, 130 km inland (Fig. 1). Together, these

mountains cover an altitudinal gradient ranging from 100 to

3100 m a.s.l. and a southnorth distance of 200 km. Mean

annual temperatures range from 14 C at the base of the

southernmost mountain to below 4 C at the top of the

Queyras mountains (CNRS, 1970, 1972, 1975a,b). Similarly,

the number of cold months (T< 7 C) per year increases from

two to three at the base, to eleven at the summit, whereas the

number of dry months (P< 2T) decreases from three to none.

Consequently, altitudinal zones of vegetation range from plant

associations belonging to the Mediterranean vegetation zone

to those of the Alpine zone (Negre, 1950; Barberoet al., 1978;

Lavagne et al., 1984). Whereas the four southern mountains

are isolated and belong to the Mediterranean or Pre-alpine

biogeographical domain, the Queyras is situated within the

Alpine chain and belong to the Internal Alps biogeographical

domain (Ozenda, 1985).

Sampling strategy

Each mountain was sampled according to a stratified strategy

related to altitude and vegetation structure. When available, at

least three types of habitat (grassland, shrubland and wood-

land) were sampled per altitudinal zone of 100 m on each

mountain. In order to study and compare different sites, a

standardized sampling method was used. A standardized

sample of soil and litter, from an area of 25 m2, enables a

quantitative characterization of the malacological communities

from a variety of micro-habitats. Sampling undertaken

between March and November during three consecutive years

(1999, 2000 and 2001), led to the collection of 209 samples:

15 on Etoile, 30 on Sainte Baume, 49 on Sainte Victoire, 67 on

Mont Ventoux and 48 in the Queyras region. In order to

increase the number of samples, and therefore to have a better

image of the diversity at low altitude, samples collected during

an earlier study (Aubry, 2003) of the region of Auriol, a

lowland area between Sainte Baume, Sainte Victoire and Etoile

(Fig. 1), are included. During this earlier study, samples were

taken according to a systematic sampling strategy whereby

sampling sites were chosena priorion a location map. Twenty-

five samples aligned on a grid were taken between September

and October 1995. These sites covered an altitudinal gradient

between 220 and 750 m, and included all types of vegetation

from grassland to woodland. Eleven additional species were

recorded, leading to the recovery of a total of 98 species in thepresent work (Appendix S1).

Land snail sampling

Each sampling unit (hereafter referred to as a quadrat or site)

is a 5 5 m square taken from a habitat type for which the

Figure 1 Location map of southern France

showing sampling sites: Etoile, Sainte Baume,

Sainte Victoire, Ventoux and Queyras. One

other site from a previous unpublished study

is also included: Auriol. Land above 1000 m

a.s.l. shaded.

Multi-scale altitudinal patterns in land snail species richness

Journal of Biogeography32, 985998, 2005 Blackwell Publishing Ltd 987


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ground cover is described. Sampling of molluscan commu-

nities in each quadrat was performed in two ways. First, a

visual search involving the collection of all living, fresh or old

dead snails, was undertaken for 30 min over the entire 25 m2

area. This involved searching beneath fallen logs and stones,

investigating crevices and under the bark of trees. Methods

similar to those described by Evans (1972), Puissegur (1976),

Andre (1981, 1982) and Magnin (1991) were used to collect

shells < 5 mm diameter. Vegetation, litter and surface soil

covering an area of 25 25 cm and a depth of 5 cm (turves)

were collected at different points within the quadrat, bagged

and brought back to the laboratory. There, samples were

dried in an oven (4075 C), then immersed in water.

Floating material was collected in a 0.5 mm mesh sieve and

dried again. The sieved samples were separated into four

fractions using a set of graded soil sieves (10, 2, 1 and

0.5 mm). Shells were then separated from plant material,

using a binocular microscope for the smallest fractions.

Different numbers of turves per quadrat were collected for

each mountain, depending on the difficulty of sampling. Five

turves were taken for Sainte Baume, four for Etoile, four forSainte Victoire, four for Ventoux, two (four halves) for

Queyras. The snails collected were then identified in the

laboratory and counted. The results presented here consider

the snails collected during both the visual search and the

turves analysis. The difference in number of turves per

quadrats on different mountains has not led to a significant

bias because similar results were obtained when only the

individuals collected during the visual search were examined.

A similar method was used at Auriol where five turves were

also taken. However, these turves were collected within a

400 m2 area (quadrats of 20 20 m). This difference in size of

the sampling units implies that these results cannot be

included in the study of species density.

Environmental records

Variables covering the entire range highlighted by Menez

(2002) as being relevant for the description of habitat of

molluscan communities were recorded. As regards site des-

cription, the standard procedure proposed by Godron (1968)

was employed. The values of the environmental variables were

measured in the field, except for soil pH (varying between 5.5

and 8.6) and CaCO3, which were measured in the laboratory

from soil samples. These two variables showed no significant

effect on species density and are not included in the presentresults. This lack of significance is not surprising in the context

of the present study which deals essentially with limestone

mountains where calcium is always present in a form available

for organisms and is therefore rarely a limiting factor. Altitude

was measured with an altimeter calibrated with a topographic

map (1 : 25,000). Mean annual temperatures were attributed

to each site according to the four climatic maps covering the

area (CNRS, 1970, 1972, 1975a,b). The percentages of ground

cover of the different variables were assessed with the help of a

visual chart and a ruler.

The environmental heterogeneity was calculated with a

ShannonWiener index, first applied by MacArthur (1965) to

study the influence of the diversity of foliage height on bird

species richness. The ShannonWiener index is used as follows.

For each quadrat the percentage of cover of six variables was

recorded: bedrock, boulder, stones, vegetation, leaf-litter and

bare soil. The proportion of these variables (sum 1) were

calledp1, p2, p3,p4, p5 and p6, and the formula:

SCH X6

i1

pilnpi

was used to compute the soil cover heterogeneity (SCH). This

index varies between 0, when only one component is present

and covers the whole quadrat, and 1.792 when the six

components are present and evenly distributed. In no case

(all mountains together or separately) is SCH correlated with

altitude but it is noticeable that the most heterogeneous sites

on Sainte Baume are found along its ridge.

Analyses

The patterns in species density are observed by plotting thenumber of species collected in each quadrat according to the

altitude of that quadrat. The scaling-up, from species density

(each quadrat) to species richness (altitudinal zones), is

achieved by grouping all the samples from a same range of

altitude into one unit. Therefore, this method also merges

different types of habitat and creates a composite landscape at

the regional scale. Three different scales of observations

(altitudinal classes) have been chosen to describe altitudinal

patterns: every 100, 500 and 1000 m. Species richness was

calculated for each of them, with all the samples from the five

mountains taken together, plus those of Auriol.

Randomized species accumulation curves (sample-based

rarefaction curves) were calculated using the EstimateS v6.0 b1

software (Colwell, 2000) for each altitudinal band of the three

scales of observation. Repeated, averaged sample-based rare-

faction, allows standardization of sampling by producing

smooth curves for comparison (Gotelli & Colwell, 2001).

Species richness of a random selection of a set number of

samples per altitudinal segment was computed. After 500

iterations of this randomization, a mean richness per

altitudinal segment for a fixed number of samples is recorded.

Simultaneously, nine richness estimators are computed from

the observed richness and abundance (Colwell & Coddington,

1994; Gotelli & Colwell, 2001).

RE S ULT S

Eighty-seven species of land snails were recorded in the five

mountain ranges (Appendix S1). The total number of species

on each mountain varied between 39 on Queyras, 47 on Etoile

and Sainte Victoire, 56 on Sainte Baume and 55 on Ventoux.

These differences are difficult to interpret directly as the

sampling effort between altitudinal gradients was uneven. The

observation of the accumulation curves of the five mountains

(not shown here) suggests that more species would have been

S. Aubry et al.



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recovered if more samples had been taken. Indeed, when the

25 samples from Auriol are included, the number of species

increases to 98. However, the present study does not attempt

to obtain the complete list of species in the region but rather to

describe patterns using a sampling strategy with known

properties on the number of collected species. In the present

study, habitats such as riparian zones, human habitations, or

agricultural areas have been deliberately ignored, leading to an

under-representation of certain species. However, the results

concerning species density and the nature of the patterns

should nevertheless be of interest.

Species density

In the study area, species density ranges between 29 and 1

species per 25 m2. When all the individuals sampled in

quadrats (visual search and turves) from the five mountains

are pooled together the number of land snail species per

quadrat decreases with increasing altitude (Fig. 2). When a

regression curve is fitted to model the relationship between

altitude and species density, it appears that density doesnot decrease linearly but rather logarithmically (higher r2,

density )7.5 ln(altitude) + 63; r2 0.508; d.f. 207;

P< 0.0001).

When each mountain is examined individually (Appendix

S2), the relationships seem to be linear (Table 1). However,

this relationship is statistically significant only for Sainte

Victoire, Mont Ventoux and Queyras. The values of species

density correspond well between mountains. Species density

at the bottom of Mont Ventoux is comparable with that

occurring on the southernmost mountains at similar eleva-

tions. Similarly, species density from Queyras conforms well

to the trend observed for the four other mountains. However,

the logarithmic model is actually composed of two geo-

graphical components, Provence and Queyras. Species density

exhibits differences between these two regions; it decreases

linearly with altitude in both but has a much steeper slope in

Provence. On Mont Ventoux, the negative relationship

between species richness per quadrat and altitude is perfectly

linear whereas there is much more variability for SainteBaume and Sainte Victoire, where some quadrats at mid-

elevation yielded high species richness. In particular, species

density is surprisingly high on the ridges of Sainte Baume

and Sainte Victoire, at 900 and 600 m, respectively. Con-

versely, some quadrats are particularly species poor, inde-

pendent of altitude.

Mean annual temperature is strongly correlated with

altitude and can explain most of the relationship between

species richness and altitude (Fig. 3). Indeed, the mean species

richness per quadrat differs significantly between classes of

mean annual temperature (ANOVA, F5203 32:5, P< 0.0001).

The mean species density of a class of mean annual

temperature is always significantly different from that of the

second class of temperature next to it, and often significantly

different from that of the class next to it (LSD and Tukey HSD

post hoctests, Table 2).

Altitude or mean annual temperature are good predictors of

species richness but the wide range of species densities for

comparable altitudes or temperatures, and the overlap between

these classes, indicates that other factors must be operating.

The highest species richness per quadrat is found at 400 m

but outlier samples with extreme values of species richness are

also observed. Indeed, there is a structural component to the

species richness per quadrat. On Sainte Baume, the sample

with the greatest richness at high altitude is a woodland, withrocks, litter and different vegetation strata in a small valley

facing north, whereas lower altitude sites are mainly covered

with leaf-litter and harbour fewer species. Similarly, on Sainte

Victoire a quadrat at 435 m yielded only five species. This

sample came from dry managed woodland ofQuercus ilexwith

only one vegetation stratum and a uniform leaf-litter. On the

contrary, the site with the greatest richness, occurring at

740 m, is a diverse woodland in a humid valley. In general,

species richness per quadrat increases with an increased

heterogeneity of the soil cover (SCH). Once the effect of

0

10

20

30

0 1000 2000 3000

Altitude (m)

Speciesdensity

Figure 2 Species density (per 25 m2) of land snails vs. altitude for

the five mountains. Quadrats are distinguished by regions. Circles

are for Provence and triangles for Queyras.

Table 1 Equations and significance of regression lines between

altitude (xin m) and species density (y) for each of the five

mountains

Mountains Relationships r2 n P

Etoile y 29.406 ) 0.018x 0.2064 15 0.0889

Ste Baume y 18.816 ) 0.003x 0.0175 30 0.4854

Ste Victoire y 18.307 ) 0.009x 0.1910 49 0.0017*

Ventoux y 19.945)

0.008x 0.5353 67 0.0000*Queyras y 7.644 ) 0.001x 0.0919 48 0.0362*

*Significant relationships.




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altitude has been taken into account, inspection of the

residuals of the regression can highlight this other factor.

The residuals of the logarithmic model of regression between

altitude and species richness per quadrat of the five mountains

together were calculated and plotted against the SCH of the

corresponding quadrat (Fig. 4). After removal of the effect of

altitude, the positive relationships between species richness and

SCH are all significant, except for Queyras (Fig. 4). The results

are the same when the residuals of the quadratic model are

taken into account. These residuals are not evenly distributed

between mountains. It is clear that quadrats from Etoile and

Sainte Baume have a higher richness than those of the other

mountains at comparable altitudes, as residuals are mainly > 0

for these two mountains. When the effect of altitude is not

accounted for, SCH is a significant first explanatory variable

only for Etoile and Ventoux (r2 0.52 and 0.07, respectively).

On Etoile, species density is therefore mainly influenced by the

heterogeneity of the soil cover. On the three other Provencal

mountains, it is the interaction of altitude and SCH that

governs species density. On Queyras, species density perquadrat is consistently low and independent of altitude or

SCH.

Species richness

Land snail species richness decreases with increasing altitude

for the three scales of observation (Fig. 5ac). However, for the

first two of these scales (Fig. 5a,b), species richness forms a

mid-altitudinal peak or plateau between 200 and 900 m, and

then decreases. There are 85 snail species present in the first

1000 m. The maximum species richness for an altitudinal band

of 100 m is 58 species and occurs between 100 and 200 m.

When only three altitudinal classes are chosen (every 1000 m),

species richness decreases linearly from 85 to 30 species with

increasing altitude. However, species richness is strongly linked

to the number of samples collected within each altitudinal

class, which is also maximal at mid-altitude.

Not surprisingly, the positive relationship between number

of samples taken in an altitudinal zone and its recorded species

richness (not shown here) is highly significant (r2 0.66,

n 29, P< 0.001). This certainly influences the observed

patterns in Fig. 5ac. This effect is particularly relevant in the

present study, where more samples have been collected at low

and mid-altitude than at higher altitude. It might therefore

account for the strong decrease in species richness with

increasing altitude, as well as for the plateau at mid-altitude.

However, in those zones where the sampling intensity is

comparable, the effect of altitude is nevertheless observable as

the high altitude zones invariably support fewer species.

In order to overcome the bias linked to the number of

samples, randomized species accumulation curves (sample-based rarefaction curves) have been calculated using the

EstimateS v6.0 b1 software (Colwell, 2000). After this process,

species richness appears to decrease linearly for all scales of

observation (Fig. 5d,f), as the low richness of the first 100 m

certainly results from the small number of samples (i.e. n 1).

Another way to compare communities is to look at the

overall rarefaction curves. Inspection of these curves (Fig. 6,

Table 3) indicates more clearly a mid-altitudinal peak between

500 and 1000 m, as there is a strong overlap of curves when a

low number of samples is studied. Species richness is always

higher for the altitudinal belt between 100 and 200 m, but

richness at 600 m (500600 m) does not seem to have reached

its asymptote (Fig. 6a). When the curves are re-scaled for the

mean number of individuals per sample (Gotelli & Colwell,

2001), the picture changes radically (Fig. 6b) and this mid-

altitudinal peak is even more striking. For a comparable

number of individuals sampled, species richness becomes

higher in the 500600 m belt and that of the 100200 m

segment now falls into sixth position.

These interpolations allow a comparison of small samples

with the larger ones. An alternative approach is by extrapo-

lation via the statistical estimation of the real species richness

from the observed richness and abundance as described by

Colwell & Coddington (1994) and Gotelli & Colwell (2001).

These authors reviewed nine species richness estimators basedon the occurrence of rare species in collected samples. These

estimators had the advantage of reaching their asymptote

(estimated real richness) quicker than the accumulation curves

(maximal observed richness), therefore providing an expected

number of species with fewer samples. Despite this advanta-

geous property, the results are still dependent on the number

of samples taken into account. However, the plateau at low

altitude, or the hump-shaped curve with a peak at 600 m, were

more apparent (Fig. 7, Table 3), even with a small number of

samples for some estimators.

Mean annual temperature (C)

16

12

8

4

< 4 47 79 911 1112.5 12.514

Meanspeciesd

ensity

Figure 3 Mean species richness of land snails per quadrat foreach class of mean annual temperature (C) derived from regional

climatic maps. Error bars show 95% confidence intervals of mean

species richness per quadrat.

S. Aubry et al.



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DIS CUS S IO N

The Mediterranean Basin is one of the worlds major centres

for plant diversity, comprising 10% of the higher plants within

only 1.6% of its total surface (Medail & Quezel, 1997). It is also

a global hotspot for a large array of other taxa (Myers et al.,

2000). The region considered in this study does not belong to

one of the more local hotspots within the Mediterranean Basin,

defined by Medail & Quezel (1997, 1999). However, with 87

species of land snails recovered in 209 quadrats of 25 m2,

which increases to 98 species when the results of an earlier

study are included, this region is undoubtedly rich in species.This number is especially high when compared with the 279

species present in north-west Europe (area covered in Kerney

& Cameron, 1979). The high species richness of the

Mediterranean Basin is often explained by its Quaternary

history. The Mediterranean Basin is both a refuge and a place

of exchange and speciation (Medail & Quezel, 1999; Tzedakis

et al., 2002). The role of the Mediterranean peninsular regions

as refugia has long been recognized (Taberlet et al., 1998) but

during the last glacial stage, the whole basin (except moun-

tains), and the southern part of the present study area in

particular, was also free of ice and outside the zone of

permafrost (Van Vliet-Lanoe, 2000). This ensured that the area

remained favourable for many species. Indeed, not only have

land snails survived through the Quaternary in the surround-

ings of Marseille by shifting their altitudinal ranges accordingly

to climate, but there is also evidence that refugia for cold

intolerant snail species were also present in the area (Magnin,

1991; Pfenninger et al., 2003). Furthermore, this species

richness is explained by the variety of habitats encountered

in a small area due to the heterogeneity of the Mediterranean

landscapes and the elevational gradient.

Species density

The number of land snail species in a quadrat of 25 m2

decreases logarithmically with increasing altitude. This

decrease conforms to the general law observed for all kingdoms

in all environments (McCoy, 1990; Gaston, 2000). The linear

decrease in species richness per quadrat on each of the

mountains is consistent with the findings of Magnin (1991)

from Mont Ventoux. On a wider scale, the logarithmic shape

of the relationship between species richness per quadrat and

Table 2 LSD and Tukey HSD post hoc

tests (I) code

temperature

(J) code

temperature

Mean

difference (I ) J) SE

Significance,

Tukey HSD

Significance,

LSD

< 4 47 )1.9321 1.0627 0.459 0.072

79 )5.5095 1.0458 0.000* 0.000*

911 )7.9544 0.9091 0.000* 0.000*

1112.5 )11.0169 1.0627 0.000* 0.000*

12.514 )10.8919 1.5689 0.000* 0.000*

47 < 4 1.9231 1.0627 0.459 0.07279 )3.5864 1.0842 0.012* 0.001*

911 )6.0313 0.9531 0.000* 0.000*

1112.5 )9.0938 1.1005 0.000* 0.000*

12.514 )8.9688 1.5948 0.000* 0.000*

79 < 4 5.5095 1.0458 0.000* 0.000*

47 3.5864 1.0842 0.012* 0.001*

911 )2.4449 0.9342 0.093 0.010*

1112.5 )5.5074 1.0842 0.000* 0.000*

12.514 )5.3824 1.5836 0.009* 0.000*

911 < 4 7.9544 0.9091 0.000* 0.000*

47 6.0313 0.9531 0.000* 0.000*

79 2.4449 0.9342 0.093 0.010*

1112.5 )3.0625 0.9531 0.017* 0.002*

12.514 )2.9375 1.4969 0.364 0.051

1112.5 < 4 11.0169 1.0627 0.000* 0.000*

47 9.0938 1.1005 0.000* 0.000*

79 5.5074 1.0842 0.000* 0.000*

911 3.0625 0.9531 0.017* 0.002*

12.514 0.1250 1.5948 1.000 0.938

12.514 < 4 10.8919 1.5689 0.000* 0.000*

47 8.9688 1.5948 0.000* 0.000*

79 5.3824 1.5836 0.009* 0.001*

911 2.9375 1.4969 0.364 0.051

1112.5 )0.1250 1.5948 1.000 0.938

*Significant differences of species density between classes of temperature at the 0.05 level.




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altitude suggests that in this region, the 1500 m contour

constitutes a threshold above which species density declines

only slightly to the summit. However, it also seems that species

density behaves differently between two regions. In Provence,

the decrease is steep and linear with some variations depending

on the heterogeneity of the soil cover and on the number of

species present at any altitude. In Queyras, on the other hand,

the decrease is gentle and progressive. This difference is

thought to reflect a climatic threshold above which species

density remains relatively constant. Indeed, if Mont Ventoux

were a 1000 m higher, it is unlikely that no land snail species

would actually occur there. In fact, it is likely that the same few

species as those present from 1600 m would be found

continuously up to the summit. However, a biogeographical

pattern is also responsible for this regional difference, as alpine

species absent in Provence occur on Queyras along the entire

altitudinal gradient and contribute to the relative stability of

species density.

Etoile

Ventoux

SCH0.50 1.00 1.50

SCH

Residuals

Residuals

0.50 1.00 1.50

10.00

0.00

10.00

10.00

0.00

10.00

Queyras

Ste Baume Ste Victoire

Figure 4 Relationships between the hetero-geneity of the soil cover (SCH) and species

density of land snails represented by the

residuals of the logarithmic model of regres-

sion between species density and altitude.

Regression lines are fitted: Etoile (r2 0.45,

n 15, P< 0.01), Ste Baume (r2 0.21,

n 30, P< 0.05), Ste Victoire (r2 0.10,

n 49, P< 0.05), Ventoux (r2 0.12,

n 67, P< 0.01), Queyras (r2 0.05,

n 48, n.s.).

Figure 5 (ac) Species richness of land

snails per segment of altitude for three dif-

ferent scales of observation (100, 500 and

1000 m); (df) after random selection of

limited number of samples. Means for 5, 22

and 30 samples are chosen for classes of 100,

500 and 1000 m, respectively, when possible.

Circles are number of species and stars are

number of samples.

S. Aubry et al.



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sampling effort is likely to yield more rare species. Unfortu-

nately, these three components cannot be easily disentangled

and have to be considered together when studying the effect of

the number of samples.

The patterns obtained with a set number of samples also

refer to species density. Indeed, it is the species richness of five

samples taken randomly within each 100 m altitudinal zone

that decreases linearly with altitude. These results therefore

validate on a larger scale (five quadrats correspond to 125 m2)

the pattern obtained for quadrat of 25 m2. The intersection of

the accumulation curves indicates that the inspection of the

full curves is a better approach for comparing the species

richness from different elevational zones (Lande et al., 2000).

In that case a peak in species richness is suggested. On the

other hand, the rescaling of species richness per number of

individuals collected, recommended by Gotelli & Colwell

(2001) when comparing species richness, has two effects. First,

it transforms values of species density (number of species per

quadrat) into values of species richness (number of species

independent of the surface sampled). Secondly, by the same

process, it lowers the effect of number of soil samples perquadrat. In this case, species richness peaks, or at least forms a

plateau, at mid-altitude. The same is true for the estimators of

estimated real species richness.

The area of the altitudinal bands must also be taken into

account. The results obtained after rescaling per number of

individuals are dependent on the area of the altitudinal zone

where these snails were collected. In the broader sense these

results still refer to species density concept (Lomolino, 2001).

As no speciesarea curves for each altitudinal belt (cf. Rahbek,

1997) can be calculated, the effect of area per se cannot be

factored out of the relationship between altitude and species

richness. Nevertheless, knowing that area decreases with

altitude and has a positive effect on richness, it can be

suggested that species richness at low altitude is actually lower

than that at higher altitude. In the region, area decreases

linearly between 0 and 800 m, with the area occupied by the

600800 m belt approximately being two-third of that occu-

pied by the one between 0 and 200 m. This enhances the

possibility that, once the effect of area is removed, species

richness at low altitude is lower than it appears, when

compared with the higher belt.

The mid-altitudinal peak in species richness reported in the

literature is usually more pronounced than the one described

here. The method used here can explain this difference as the

result of two factors. First, other works might explore speciesrichness along altitudinal gradient by using species altitudinal

ranges (e.g. Sanders, 2002; Bhattarai et al., 2004; McCain,

2004). These ranges are defined by upper and lower elevation

limits of species, which are assumed to occur everywhere

within this range. This assumption, and the use of these ranges

to calculate species richness at different elevations, leads to an

automatic, but spurious, inflation of species richness at mid-

altitude (Zapata et al., 2003). Secondly, the use of several

mountains to describe the species richness pattern over the

entire gradient (from sea level to 3100 m), results in a wide

plateau (sum of smaller peaks at different altitudes), instead of

a strong peak.

The patterns observed for species richness depend on the

scale of resolution. McCoy (1990) argued that most studies

that had not found a mid-altitudinal peak in species richness

had used an inappropriate sampling regime. Our results seem

to confirm this suggestion, showing that studies with a coarse

resolution will tend to demonstrate a linear decrease in species

richness with increasing altitude (e.g. Mylonas et al., 1995),

whereas a fine resolution covering the full altitudinal gradient

shows a mid-altitudinal peak in species richness (McCoy,

1990).

CO NCLUS IO NS

This baseline study on altitudinal patterns of land snail species

richness on five mountains in south-eastern France demon-

strates that species density decreases logarithmically with

altitude and that species richness peaks at mid-altitude. It also

shows the difficulty of determining precise patterns of richness.

Indeed, this study, the first large-scale analysis of land snailrichness patterns with elevation, aided by a large number of

samples, shows the strong variation in species richness between

sites, as well as the importance of the choice of methods used to

describe them. Despite these problems, it seems that land snail

species richness genuinely does peak at an altitude between 500

and 900 m in montane regions of south-eastern France.

The present study attempted to describe altitudinal patterns

of land snail species richness without providing an explanation

of them. Species richness is controlled by a wealth of factors,

operating at different scales on individual species. Each of the

observed global patterns of species richness, themselves

dependent on the scale of observation, can be explained by

different factors, but no consensus has emerged about the

mechanisms involved (Gaston, 2000). These effects, sometimes

similar and sometimes divergent, can all take place at the same

time and it appears that no factor can be singled out to explain

the general pattern (Lomolino, 2001). Indeed, in the present

study, mean annual temperature and area have been shown to

be potential explanations, but at the restricted scale of the

quadrat it has also been shown that environmental heterogen-

eity is a factor responsible for low densities at low altitude or

high densities at high altitude. This is further increased by what

can be called an ecotone effect or community overlap on the

ridges of the lower mountains, where faunas with different

ecologies can meet in a single quadrat. Certainly, otherinfluences, such as historical factors (Gutierrez, 1997), the

extension of Rapoports rule to elevational gradient (Stevens,

1992) or the geometric effect (Colwell & Lees, 2000) have to be

studied and might also provide partial explanation for these

patterns (Sanders, 2002; Bhattarai et al., 2004).

ACK NO W LE DGE M E NT S

The authors wish to thank Philip Roche and two anonymous

referees for their constructive comments on a previous version




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B I O S K E T C H E S

Dr Sebastien Aubry recently completed his PhD on the factors controlling the structure of land snail communities on limestone

mountains in south-eastern France at the Department of Zoology, University of Cambridge. He is now a post-doctorate researcher at

the Institut Mediterraneen dEcologie et de Paleoecologie. His main research interest is the ecology of land snails.

Dr Frederic Magninis a researcher at the Institut Mediterraneen dEcologie et de Paleoecologie (CNRS, Marseille) working on the

ecology of both Recent and Quaternary land snails within the Mediterranean Basin.

Dr Veronique Bonnetis a post-doctoral researcher at the Institut Mediterraneen dEcologie et de Paleoecologie. Her main interest

is community ecology, with a particular focus on the influence of perturbations.

Dr Richard C. Preece is the Watson Curator of Malacology at the University Museum of Zoology, Cambridge. His main research

interest is malacology in general, but especially the use of non-marine Mollusca in reconstructing environments and climates during

the Quaternary (and Tertiary).

Editor: Robert Whittaker

S. Aubry et al.


snails and altitude south france

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