THE ROLE OF PONDS

Patterns in the organization of Cerrado pond biodiversityin Brazilian pasture landscapes

Paulo De Marco Jr. • Denis Silva Nogueira • Caroline Costa Correa •

Thiago Bernardi Vieira • Karina Dias Silva • Nelson Silva Pinto • David Bichsel •

Andrezza Sayuri Victoriano Hirota • Raısa Romenia Silva Vieira •

Fernanda Melo Carneiro • Arthur A. Bispo de Oliveira • Priscilla Carvalho •

Rogerio Pereira Bastos • Christiane Ilg • Beat Oertli

Received: 1 December 2012 / Accepted: 22 September 2013 / Published online: 18 October 2013

� Springer Science+Business Media Dordrecht 2013

Abstract There is a worldwide concern on the loss

of pond biodiversity in human dominated landscapes.

Nevertheless, agricultural activities appear to increase

pond number in the Brazilian Cerrado through dam-

ming streams for cattle raising. These man-made

ponds may represent important landscape features, but

their importance to regional biodiversity has not yet

been studied. Here, we evaluated differences in alpha

and beta diversity under a multi-taxonomic approach,

as well as tested pond size as the main driver of local

species richness. We also assessed the importance of

environmental heterogeneity through the analysis of

the regional species accumulation curves (SAC). The

overall result suggests that species turnover was the

major component of regional biodiversity for all

groups. Major physical and chemical water conditions

had no effects on algae, macrophytes, water bugs, and

birds species richness. Pond size had a significant

effect on Odonata and fish species richness, while

water beetles and amphibians were influenced by

trophic conditions. Results from regional SAC show

variations among different taxonomic groups regard-

ing landscape heterogeneity: only algae, fish, and birds

do not reached to an asymptote and had higher z-

values. Our results highlight the importance of ponds

for biodiversity conservation in increasingly agricul-

tural landscapes in central Brazil.

Keywords Additive partitioning �Heterogeneity � Metacommunity ecology �Species-accumulation curves � Species richness �Species–area relationship

Electronic supplementary material The online version ofthis article (doi:10.1007/s10750-013-1695-2) contains supple-mentary material, which is available to authorized users.

Guest editors: R. Cereghino, D. Boix, H.-M. Cauchie,

K. Martens & B. Oertli / Understanding the role of ponds in a

changing world

P. De Marco Jr. (&)

Laboratorio de Ecologia Teorica e Sıntese, ICB,

Universidade Federal de Goias, Goias, Brazil

e-mail: pdemarco@pq.cnpq.br; pdemarco@icb.ufg.br

D. S. Nogueira � C. C. Correa � T. B. Vieira �K. D. Silva � N. S. Pinto � A. S. V. Hirota �R. R. S. Vieira � A. A. B. de Oliveira �P. Carvalho � R. P. Bastos

ICB, Universidade Federal de Goias, Goias, Brazil

D. Bichsel � C. Ilg � B. Oertli

University of Applied Sciences of Western Switzerland,

Lullier-Geneva, Switzerland

F. M. Carneiro

Universidade Estadual de Goias, Goias, Brazil

123

Hydrobiologia (2014) 723:87–101

DOI 10.1007/s10750-013-1695-2

Introduction

There is an increasing concern regarding the loss of

ponds in agricultural landscapes, with the worst

possible consequences for its component biodiversity.

The recognition of this ongoing process supports the

need for a worldwide effort on pond conservation in

human dominated landscapes (Oertli et al., 2005;

Cereghino et al., 2008b). Nevertheless, a first glance at

pasture landscapes in central Brazil suggests that the

number of ponds is actually increasing due to the

stream damming for economic purposes (mostly

related to cattle raising). This may suggest a variable

pond persistence response in different world regions or

dominant land uses. For instance, since the current

economic activities in the Cerrado (e.g., soybean and

sugarcane production, cattle raising) have different

dependencies on water resources, they may also differ

on the economic pressure to increase pond number.

Ponds account for a substantial amount of the

biodiversity of a given landscape in comparison to

streams and rivers (Williams et al., 2004). The

differential response of pond species to environmental

factors may also lead to important differences in

community composition between these two systems

(Bilton et al., 2006; Bagella et al., 2010). Besides, the

lack of knowledge on organization of pond ecological

communities may hinder our ability to predict their

response to possible major threats (e.g., land use

changes, nitrogen uptake, and species invasion). In

order to assess the importance of ponds for pasture

landscape biodiversity, further knowledge on the

species composition and distribution in ponds is

crucial, as well as its contribution to regional biodi-

versity. For instance, information shortage on taxon-

omy and distribution of Neotropical species has been

suggested as a barrier that weakens the efforts for

species conservation (Brito, 2010; Diniz-Filho et al.,

2010).

Regarding agricultural landscapes, it is possible to

devise two main scales that affect biodiversity orga-

nization and may represent important ecological

processes. The pond scale may include short-distance

effects of nearby environmental conditions disturbed

by anthropogenic effects in addition to other common

local effects such as biotic interactions and environ-

mental filtering (Herwig & Schindler, 1996; Pierce &

Hinrichs, 1997; Studinski & Grubbs, 2006). Local

factors may directly determine the maximum number

of species that could be maintained in a given pond.

The landscape/regional scale is related to long-

distance interactions among ponds including dispersal

and constraints generated by the regional species pool.

The relative importance of local and regional pro-

cesses driving species richness are at the heart of

current debates on the importance of neutral or niche

processes shaping ecological communities (Cottenie

et al., 2003; Van de Meutter et al., 2007; Howeth &

Leibold, 2010).

As for local processes, it is expected that pond size

may shape several ecological patterns in aquatic lentic

systems (Oertli et al., 2002; Kadoya et al., 2004;

Bosiacka & Pienkowski, 2011). First, pond size

directly affects the amount of suitable areas available

for pond-dwelling species. Pond size is related to the

length and width of the littoral zone, which displays

the best ecological conditions of oxygen and temper-

ature for several species with a positive effect on their

abundance. Besides, the littoral zone provides favor-

able sites for both attachment and protection for

aquatic organisms. Secondly, small ponds may be

more intensely affected by any surrounding distur-

bance (e.g., nitrogen uptake from nearby human

activities or heavy rains), whereas the size of larger

ponds may confer them a relative environmental

stability by buffering the effects of eutrophication

(Menetrey et al., 2005). A possible relation between

pond size and general physical–chemical water vari-

ables may represent an important axis to understand

the organization of pond communities, such as aquatic

insects and amphibians (Oertli et al., 2002; Kadoya

et al., 2004). However, the species–area relationships

may not be so general when human impacts disrupt

natural ecological processes, namely as in intensively

managed ponds (e.g., fish ponds; cattle raising ponds).

Species are clearly not homogeneously distributed

in a landscape (Chandy et al., 2006; Simmering et al.,

2006). Different groups are expected to respond to

habitat heterogeneity according to their behavior

(Baguette & Van Dyck, 2007), dispersal capabilities

(Campagne et al., 2009), or other bionomic traits

usually related to habitat use (Burel & Baudry, 2005).

A logical consequence is that landscape and habitat

heterogeneity may be an important component to

explain species richness variation among ponds.

Kolasa et al. (2012) recently showed how species

accumulation curves (SAC) may help to understand

how broad-scale heterogeneity is important to

88 Hydrobiologia (2014) 723:87–101

123

determine species richness patterns in the regional

pools. They argue that the slope of these relations

increases with heterogeneity for a given set of species.

We argue further that if we compare different groups

in the same landscape, SAC may provide a useful

insight on how they respond differently to heteroge-

neity. Considering the large variety of body sizes and

ecological requirements of the species visiting and/or

inhabiting ponds (from tiny algal cells to birds), this

approach should be useful to analyze the component

assemblage of these systems.

Here, we provide a broad view of local and regional

patterns of species richness in the Cerrado ponds under

a multi-taxonomic approach. Following the analysis of

broad patterns of environmental conditions variation

among ponds, we explored the differences among

taxonomic groups through an additive partition of the

regional biodiversity into its alpha and beta diversity

components. Then, we tested the hypothesis that pond

size and pond trophic state are the main drivers of

species richness variation in each group. We also

evaluated the importance of the environmental heter-

ogeneity on the spatial organization of these commu-

nities by means of a regional species accumulation

curve analysis.

Materials and methods

Study area and study sites selection

The study area was located at 25 km from the borders

of Goiania (Capital of the Goias State, Brazil) to

assure that only landscapes dominated by agriculture

were sampled, avoiding urban areas (Fig. 1). Goiania

is localized in central position of Cerrado distribution,

with a variety of vegetational components that are a

characteristic of this biome. The total study area is

45 9 30 km2, bordered by a buffer of 10 km and a

core area with 35 9 20 km2, where the samplings take

place. All water bodies in the core area were identified

by visual interpretation of satellite images in Google

Earth. The shapes generated by this process were used

to calculate pond-size and the distance to the nearest

neighbor pond, which is used as a measure of isolation.

A total of 2,787 ponds were found in the core area,

reflecting a dense pond network in a relatively small

geographical extent.

Collinearity among explanatory variables is gener-

ally accepted as a factor that decreases our ability to

interpret existing relations of many ecological studies

(Graham, 2003). Our sampling design was planned to

Fig. 1 Study area in relation to Goiania, Goias state, Brazil. (A) A radius of 25 km (buffer) from the center of Goiania (B) together with

the buffer zone determine approximately the position of the core area of sampling. Urban areas in pink and forest remnants in green

Hydrobiologia (2014) 723:87–101 89

123

control collinearity among other variables such as

pond-size and isolation, which may also affect pond

biodiversity but are beyond of the scope of this study.

Thus, we selected ponds using a stratified random

design according to size and isolation. The pond-sizes

were grouped into five size classes, with maximum

areas (in m2) of 190, 600, 1,900, 6,000, 10,000

(Table 1). As well, ponds with less than 100 m of

isolation were also excluded, leaving aside temporary

ponds and focusing only in permanent ones. Linear

distributed isolation classes were built after a visual

inspection of the overall frequency distribution in the

whole area. In each joint cell of pond-size and

isolation, the ponds were randomly chosen, summing

a total of 71 sampled ponds, excepting birds with 73

ponds (Table 1).

All physical and chemical water parameters except

transparency were measured in situ, and composed our

environmental data sets (chlorophyll, dissolved oxy-

gen, temperature, water transparency, pH, electrical

conductivity, ammonium, and chloride). The water

transparency was the first parameter that we measured,

using a modified Snellen method. In this method water

transparency is read in an alphabetic sequence inside

of a glass tube. For practical reasons, we adapt one

small piece of paper (with the alphabet sequence) in

one rule. When the letters disappear completely we

recorded the value of the profundity. The obtained

values follow closely the values obtained by the

Snellen method (Oertli, unpublished data). For pH,

chlorophyll, dissolved oxygen, chloride, ammonium,

and water temperature we used a 6820v2-1-C-S Multi-

Parameter water Quality Logger, at the beginning of

dry season (June–July 2012). The water sample for the

analyses was taken from the center of the pond at

30 cm deep. Readings of the Multi-Parameter water

Quality Logger was done only after the parameters

stabilized.

Sampling protocols

We sampled all ponds during the beginning of the dry

season, between June and September of 2012. For

macrophytes, odonates, water bugs, water beetles, and

fishes the protocols are adapted from the PLOCH

standardized method of pond sampling (Oertli et al.,

2005), both for interpretability and future comparison

with published results. The protocol aimed to allow

the most accurate description of pond species richness

by taking account of the size and the habitat hetero-

geneity of each pond. Thus, sub-samples within each

pond were located in the different microhabitats with a

number increasing according to the pond size. Orig-

inally the PLOCH protocol suggests an assignment of

number of samples using fixed categories (4 samples

in ponds less than 10 m2, 8 for ponds up to 100 m2, 16

for ponds up to 1,000 m2, and 32 for ponds larger than

10,000 m2). We developed an exponential interpola-

tion based on this distribution, which allow to a better

distribution of samples with a total sampling effort

similar to Oertli et al. (2002). Thus, the number of

samples in each pond is:

n ¼ 2log10 Sð Þþ1 ð1Þ

where n is the number of samples required for a pond

with area S. Observe that this equation produce the

exact number of sub-samples expected for the pond-

size classes described above in the original PLOCH

protocol.

We first made a visual inspection of the entire pond

identifying all types of substrates or microhabitats to

assure that samples conveniently represent environ-

mental heterogeneity. The samples were regularly

distributed on the major types of substrate available in

the littoral zone of each pond. The main habitat

categories observed are: emergent macrophyte,

swamp areas covered by Typha dominguensis Pers.,

floating macrophytes, submersed macrophytes near

littoral areas, marginal area covered by trees and

disturbed areas almost without marginal vegetation.

The identification of these habitat categories were only

made to assure that all important habitats present in

each pond were conveniently sampled. Clearly, larger

Table 1 Distribution of the sampled ponds in relation to pond-

size and isolation in the study area

Size (m2) Isolation (m)

300 500 700 900 [900

190 2 3 1 2 1

600 4 1 4 3 3

1,900 5 2 4 3 4

6,000 5 4 4 1 3

10,000 2 2 4 1 3

Pond isolation was measured as the linear distance to the

nearest neighbor pond

90 Hydrobiologia (2014) 723:87–101

123

ponds may have a more complete set of habitat

categories but these relations are beyond the objec-

tives of this study.

Phytoplankton

In each pond a sub-surface water sample was collected

with 100 ml amber bottles and fixed with acetic Lugol

(Vollenweider, 1974; Bicudo & Menezes, 2006). We

also made an algal sample using a 20 lm plankton net.

This sample was preserved in Transeau (6 part of

water: 3 parts of alcohol: 1 part of formaline 40%) in

1:1 proportion. The net sample was used for species

identification and the bottle sample to estimate species

density according to Utermohl (1958). The phyto-

plankton was identified to the species level or the

lowest taxonomic level possible according to Van den

Hoek et al. (1995).

Macrophytes

In each pond, the macrophytes were listed and all

species present were recorded. The macrophytes were

classified in 5 ecological groups (emergent, free

submersed, rooted submersed, free floating, and

rooted with floating leaves). The number of banks

sampled also follows the general relation with pond-

size. Samples of macrophyte were taken for identifi-

cation using relevant literature (Pott & Pott, 2000;

Amaral et al., 2008). Quantitative samples were taken

using quadrats of 0.25 m 9 0.25 m in transects 2 m

inside the pond and parallel to pond margin recording

the coverage of each species using the Dromin-Kajima

scale (0 = absent; 1 = 0–20% cover; 2 = 21–40%

cover; 3 = 41–60% cover; 4 = 61–80% cover;

5 = 81–100% cover). The distribution of the number

of samples follows the standardized protocol with

relation to pond size (Table 1).

Aquatic insects

Water bugs and beetles were sampled using a small

rectangular net of 14 9 10 cm2 with 0.5 mesh area as

in Oertli et al. (2002, 2005). Each sample was done in

the 2 m littoral margin of pond during 30 s in each

previous selected habitat. The samples were conserved

in alcohol and separated at lab for further identifica-

tion. The classification of water bugs adults at families

and genera level was done following Nieser & Melo

(1997) and Pereira & Melo (2007). Water beetles

adults were identified at families and genera levels

following Benetti et al. (2003) and Segura et al.

(2011).

Odonata

Odonata adults were sampled only between 10:00 and

15:00 h, always on air temperatures higher than 19�C

(De Marco & Resende, 2002). We use a modified scan

method with fixed areas (De Marco, 1998; Silva et al.,

2010) using 5 m segments distributed within the

previously selected microhabitats. All adults were

visually counted by an experienced collector and all

dubious individuals (especially the small species)

captured. Species determination was done with the

comparison with the material of the Odonate collec-

tion of UFG and relevant literature (Lencioni, 2005,

2006).

Fish

We use a passive sampling method based on a traps,

built using transparent PET bottles of 2 l during 24 h.

The traps were dispersed in the ponds following the

same habitats of the macroinvertebrate samples but

located at 5 m distance one to another, with their

opening being directed to pond margin. We choose

this sampling method because it is easily applicable,

but we acknowledge for the possible inherent bias

associated to this method. An active sampling, like a

net fishing or hand net fish, may also present some bias

or may be difficult to apply to some large ponds

(Table 1). Besides this, a large number of ponds are

fish farming and the owners impose restrictions for

active sampling. Although the abundance and the

richness are underestimated by the passive method, we

rely on the uniformity of this effect over ponds to

provide a comparison among them. However, com-

parisons with other work should be done cautiously.

Classification at order, families, and species follow the

current literature (Vari & Weitzman, 1991; Buckup,

1993).

Amphibians

Adult amphibians were sampled during the rainy

season, from October 2012 to February 2013, always

between 20:00 and 00:00 h. During 50 min, we

Hydrobiologia (2014) 723:87–101 91

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walked around the pond and registered all individuals

seen or heard according to the methods of visual

encounters surveys and audio strip transects (Zimmer-

man, 1994). Individuals heard in nearby ponds were

not included. Species identification followed Frost

(2013).

Birds

As bird species in ponds are well known, a direct

estimation of the absolute species richness by pond

was possible. All individuals at the shore area, floating

vegetation, or swamp vegetation were recorded visu-

ally (using 10 9 50 binoculars) and by song recogni-

tion during a complete walk around the pond at a

constant velocity.

Analytical methods

The dimension of water quality variables was reduced

using principal component analysis (PCA) according

to Legendre & Legendre (1998). Relations between

pond-size and water quality variables were investi-

gated by a linear regression of this variable and the first

axis of the PCA. Similarly, relations between both

pond-size and water quality (first PCA axis) and the

species richness were tested by linear regression.

Jackknife estimates of species richness was used for

groups having been sub-sampled: macrophytes, water

beetles, water bugs, Odonata adults, and fish; while,

for phytoplankton and birds we used observed species

richness. Jackknifed species richness has the advan-

tage both to corrected bias in observed species

richness and to provide variance estimates allowing

to further inferential tests (Colwell & Coddington,

1994). The analysis of estimated species richness

against our environmental predictors was done by

means of multiple linear regression (Zar, 1999).

Additive and multiplicative partitioning techniques

have been employed to decompose the total diversity

(c diversity) in the alpha and beta diversities from

ecological communities (Crist & Veech, 2006). Nev-

ertheless, diversity partitioning has aroused heated

discussions with a variety of suggested procedures

(Baselga, 2010; Jost, 2010; Veech & Crist, 2010a, b).

In this paper, we apply the additive diversity parti-

tioning developed by Crist et al. (2003), because it

measures the diversity at the different scales taking

into account the total number of species and the local

species richness as well, putting beta diversity in a

similar and comparable scale (see Chao et al., 2012).

Beta diversities for each group were calculated as the

difference among gamma and the average of alpha

using species richness, and were than compared to

random expectation by 999 Monte Carlo simulations

of individuals into any local samples (according to

Hypothesis testing 1 in Crist et al., 2003).

We also follow Kolasa et al. (2012) to use species

accumulation curves as indication of the relation of

species richness and habitat heterogeneity in the

landscape. Kolasa et al. (2012) show that the increase

of the exponent z of the species area relation is

indicative of an increase in heterogeneity at broader

spatial scale. We applied this concept here in a

different way since we try to compare the responses of

different groups to the same landscape and, thus, the

same variation on heterogeneity. We consider that the

increase in z is related to the way each group respond

to the existing heterogeneity gradients and its ability to

disperse in this landscape. Curves are fitted using

nonlinear estimation methods, but using number of

sites instead of cumulative area. All the computations

were performed with packages available in R program

(R Development Core Team, 2013) and the Statistica

7.1 (StatSoft, 2005).

Results

Limnological characterization

Water quality parameters of Cerrado ponds are

consistent with a medium trophic state with a relative

Table 2 General description of water quality parameters in

Cerrado ponds

Water parameter Mean 95% confidence interval

Lower limit Upper limit

Chlorophyll (lg/l) 5.1 3.2 7.0

Dissolved oxygen (%) 10.5 9.7 11.2

Temperature (�C) 23.4 23.0 23.7

Transparency (cm) 30.4 27.0 33.8

pH 7.1 7.0 7.2

Conductivity (ls/l) 76.3 64.9 87.7

Amonia (mg/l) 0.55 0.47 0.63

Chloride (mg/l) 5.7 4.6 6.8

92 Hydrobiologia (2014) 723:87–101

123

low level of oxygen (10.5%), with low variation

among ponds (1.5%). Transparency presents low

values (23.4 cm) and also a small inter-pond variation

(6.8 cm) (Table 2). Conductivity varied widely

among ponds (22.7 ls/l) and the ammonium is the

most stable variable, with only 0.16 mg/l of variation.

Chlorophyll had the third highest variation among

ponds followed by Chloride.

Water parameters collected in Cerrado ponds show

a medium level of collinearity (first three principal

components representing 61% of total variance). First

principal component is positively related to chloro-

phyll (log-transformed), ammonium, pH, and electric

conductivity and negatively related to transparency

(Fig. 2A). Thus, this axis represents mainly the trophic

state of the pond, well related to its littoral depth. No

groups of ponds could be easily identified (Fig. 2B),

except a distinct aggregation of ponds with high

chlorophyll.

Trophic state of the ponds (Factor 1) is negatively

related to pond-size (Fig. 3). This relation account

for a small fraction to total variance in Factor 1

(r2 = 0.124) but it represent a consistent relation

of pond-size with the decrease in chlorophyll-

a (r2 = 0.108; P \ 0.003; both variables log-

transformed).

Fig. 2 Loadings of variables (A) and scores of samples (B) of PCA of the water quality measures of the Cerrado ponds

Fig. 3 Water quality factor

1 as a function of pond-size.

A logarithmic regression

was done after analysis of

linear regression residuals

Hydrobiologia (2014) 723:87–101 93

123

It is important to note that 70.4% of the studied

ponds are the result of damming natural streams.

Ponds created by small dams are larger (3,360.3 m2;

SD = 2,872.9) than those not connected to streams

(634.3 m2; SD = 887.0) (t test for separate vari-

ances = 6.057, df = 65, P \ 0.001). Thus, the effect

of pond-size is not totally independent to the pond

connection to streams.

Regional biodiversity of ponds

We recorded 661 taxa (species and genera) distributed

in the seven studied taxonomic groups (Table 3; see

detailed lists in the supplementary material). Phyto-

plankton was the richer one with more than half of all

recorded taxa (346 species). However, we estimate

that about 234 species (67.6%) can still be found in

studied ponds (jackknife estimator). Macrophytes,

water beetles, water bugs, fish, and amphibians were

better represented in this study, with only about nine

species less than the estimated by jackknife (percent-

ages of possible not sampled species varying from

11.1 to 20.4%) (Table 3). Odonata and birds, present

highest percentages of not sampled species according

to jackknife estimator (28.6 and 53.3%, respectively).

The decomposition of regional pond biodiversity

enables us understanding the relative contribution of

alpha and beta diversity among the studied groups. The

percentage of singleton species varied from 13.9% (for

water beetles) to 68.5% (for phytoplankton). Despite

we were not interested in sampling effects we agree

that sampling biases can take a great amount on the

explication of true alpha and beta diversity in our

approach of regional diversity decomposition. In fact,

the greater number of singletons species for phyto-

plankton suggests that our protocol may highlight the

true potential sampled species diversity for this group.

However, for most of studied taxonomic groups beta

diversity seems less biased by singletons species.

Alpha diversity was higher than expected only for

macrophytes. For all the others, beta diversity was

higher than expected (Table 4). The general pattern

suggests a high turnover of species compositions

among ponds for all the groups. Since sample bias may

affect those patters considering the high percentage of

singleton species, we also perform the analysis

excluding singletons. The general qualitative results

do not change, reinforcing the high beta diversity

among ponds in the area.

Main drivers: size and water quality parameters

We have found contrasting patterns for species

richness according to pond size and two first PCA

axes for water quality variables (Table 5). The species

richness of algae, macrophytes, and birds was not

influenced by our environmental predictors. Never-

theless, water beetles species richness were negatively

related to the first PCA axis (b = -0.32, P \ 0.05),

which described the increase of eutrophic conditions,

while Odonata (b = 0.43, P \ 0.05) and fish

(b = 0.35, P \ 0.05) were the groups witch best fit

for a pond size-species richness relation.

Species accumulation curves

All species accumulation curves showed high levels of

statistical fit to regional species–area relation (always

higher than 91% of total variance explained). The

slope of the curves varied widely among the groups

(Fig. 4, Table 6). Algae had the larger z-value (z-

value = 0.722) much higher than the second value

obtained for fishes (0.543). In both cases it is clear that

the sampled species richness do not represent the real

species richness in this landscape. Macrophyte, Odo-

nata, and birds had z-values between 0.260 and 0.352,

and represent an intermediate group. Amphibians,

water bugs, and water beetles showed the lowest z-

values, and reach to the asymptote for accumulation

curve. For these groups the studied ponds hold a

significant portion of the regional diversity, and have

Table 3 Summary of pond biodiversity showing the number

of studied sites, observed and estimated species richness (first

order jackknife) of all studied groups and total diversity

Taxonomic

group

Observed

species

richness

Jackknifed

species

richness

Difference of

observed and

estimated richness

Algae 346 580.46 *234 (67.6%)

Macrophytes 44 52.87 *9 (20.4%)

Water beetles 36 40.92 *5 (13.9%)

Water bugs 27 29.96 *3 (11.1%)

Odonata 56 71.77 *16 (28.6%)

Fish 15 22.85 *8 (53.3%)

Amphibians 33 38.91 *6 (18.2%)

Birds 137 174.49 *37 (27.0%)

The total number of ponds sampled was 71 except for birds,

which was 73

94 Hydrobiologia (2014) 723:87–101

123

the best representativeness, with only a few species

less than the total estimated richness.

Discussion

Since the Cerrado ponds are nearly all man-made, they

reflect the economic forces that surround them. In this

respect, we postulate that pond size is the main driver

of its environmental structure (which may reflect the

needs of the landowners). Large ponds are more stable

mostly because they can buffer the effects of heavy

rains. We showed that size influences the trophic state

of the ponds, with smaller waterbodies having a higher

probability to harbor higher levels of chlorophyll

concentration. Otherwise, the majority of the ponds

(70%) are made by dams on streams which may affect

directly its biotic component by changing the com-

munity composition and diversity. In addition, ponds

probably affect regional biodiversity by favoring

stepping stones dispersal (Cereghino et al., 2008a) or

even acting as ecological traps for species (Horvath

et al., 2007; Harabis & Dolny, 2011).

Regarding its origin, the Cerrado pond biodiversity

is partially composed by exogenous species that

colonize these ecosystems through migration from

nearby rivers and streams or other standing water

environments. Sometimes species are introduced by

man, such as fishes, or they are alien species favoured

by environmental change. Otherwise, as underlined by

new insight on pond ecology and management

(Cereghino et al., 2008a), our findings support the

claim that Cerrado ponds hold a high biodiversity,

despite their small sizes, with proportionally higher

contribution of beta diversity component. This result is

especially important, since we found about three

thousand ponds in an area of 686 km2 and sampled

Table 4 Additive partitioning of regional diversity for all the

studied groups, showing percentages of singletons species for

each group, observed versus expected values for alpha and beta

diversities (in terms of number of species) and percentages of

beta diversity component with and without singletons species

Algae Macrophytes Water

beetles

Water

bugs

Odonata Fish Amphibians Birds

% of singletons species 68.5 20.4 13.9 16.7 29.1 28.6 18.2 27.9

a-diversity with

singletons

10.2 (95.6) 4.5 (4.1) 5.8 (9.5) 5.3 (8.9) 7.4 (13.5) 1.9 (4.5) 6.94 (13.2) 8.9 (13.4)

b-diversity without

singletons

335.8 (250.3) 38.5 (38.9) 30.2 (26.5) 20.7 (17.1) 47.6 (41.5) 12.1 (9.5) 26.1 (19.8) 127.1 (122.6)

a-diversity without

singletons

6.63 (43.17) 4.35 (3.91) 5.73 (9.33) 5.21 (8.75) 7.16 (12.84) 1.83 (4.36) 6.85 (13.04) 8.34 (12.24)

b-diversity without

singletons

102.37 (65.80) 29.65 (30.09) 25.27 (21.67) 17.79 (14.25) 31.84 (26.16) 8.17 (5.64) 20.15 (13.96) 88.66 (84.76)

b-diversity with

singletons (%)

97.1 89.5 83.9 79.6 86.6 86.4 78.9 93.5

b-diversity without

singletons (%)

93.9 87.2 81.5 77.3 81.6 81.7 74.6 91.4

Expected values (between parenthesis) represent the average of 999 Monte Carlo simulations

For all simulations observed values were significant at an a-level of 0.05

Table 5 Multiple regression R2 adjusted and partial coeffi-

cients for multiple community parameters against pond size

and two first principal components

Taxonomic

group

Species richness** R2

adjustedPond

size

PCA1 PCA2

Algae -0.04 0.19 0.05 0.04

Macrophytes 0.26 -0.16 0.10 0.08

Water beetles 0.11 -0.39* -0.09 0.17*

Water bugs 0.28 0.09 0.11 0.01

Odonata 0.43* -0.15 0.10 0.20*

Fish 0.36* 0.22 -0.06 0.09*

Amphibians 0.04 -0.21 -0.34* 0.12*

Birds 0.00 -0.19 0.00 0.04

* Significant at an a-level of 0.05

** Species richness for algae and Birds are represented by

observed number of species, for all the other groups we used

estimated (jackknifed) species richness

Hydrobiologia (2014) 723:87–101 95

123

96 Hydrobiologia (2014) 723:87–101

123

only about 10% of this universe. However, this result

has to be interpreted with caution, because they are a

man-made modification of the Cerrado landscapes and

its effects on the original fauna was not properly

evaluated.

An important debate on current ecological theory is

related to Niche versus Neutral processes as the main

drivers of metacommunity organization (Chu et al.,

2007; Soininen et al., 2007; Juen & De Marco, 2011).

Neutral interpretations rely on dispersal process and

ecological drift to explain the variation on species

composition and diversity (Hubbell, 2001; Allouche &

Kadmon, 2009). Conversely, the importance of niche

processes is expected to increase when there is species

specific responses to habitat heterogeneity. Multi-

taxonomic studies are especially important to evaluate

whether different groups may respond to main

ecological drivers (such as pond size and pond trophic

state) in a similar way or differ according to broad

patterns of niche differentiation. Here, the responses

varied among the groups with support for an effect of

pond size only for Odonata and fish. At least for

Odonata, experimental (Siepielski et al., 2010) and

observational evidences (Juen & De Marco, 2011)

suggest that neutral community dynamics are more

important than trade-offs among species in aquatic

environments. On the other hand, for water beetles and

amphibians, which were affected by environmental

gradients, evidence supports that niche differentiation

(Leibold et al., 2004) may be important to determine

pond assemblage structure. A logical consequence of

the dominance of niche over neutral process at higher

taxa levels is that cross-taxa congruence is low since

there are group specific responses to the ecological

factors. Thus, it is not possible to order conservation

value of those ponds in a single dimension, such as

related to pond size, and this complexity should be

considered when practical measures for its conserva-

tion is discussed.

Pond size was positively important only for Odo-

nata and fish species richness. Typically, pond size is

taken as a direct measure of available habitat and may

support a simple neutral interpretation based on

Wright (1983) energy hypothesis: more area, more

individuals, and more species. A detailed study of the

interaction among groups needs to be made to evaluate

the importance of other ecological forces such as the

dependency of specific microhabitats, refuge from

predators, or interaction with competitors to determine

such patterns. For instance, current knowledge on

larval habitats of odonates suggests that the diversity

of aquatic macrophytes may be important both as

refuge against fish predators (McPeek, 1998, 2004)

and specific oviposition sites. On the other hand, water

beetles and amphibians were related to the environ-

mental gradients summarized by the first and second

PCA axes, respectively. Water beetles richness is

inversely related to the eutrophication level of the

ponds. As most of those species are visually oriented

predators, it is possible that water transparency plays

an important role in its habitat selection. However, as

eutrophic conditions were basically observed in fish

Table 6 Fitted species accumulation curves in ponds of agricultural landscape in Cerrado ponds, Brazil

Taxonomic group R2 Estimated

z-value

Standard

error

Degrees of

freedom

t P level

Algae 0.999 0.722 0.005 63 141.435 \0.001

Macrophytes 0.981 0.260 0.009 64 29.427 \0.001

Water beetles 0.971 0.160 0.008 62 19.213 \0.001

Water bugs 0.981 0.165 0.006 66 28.918 \0.001

Odonata 0.993 0.304 0.004 65 86.486 \0.001

Fish 0.955 0.543 0.003 49 187.061 \0.001

Amphibians 0.988 0.166 0.003 64 47.432 \0.001

Birds 0.996 0.352 0.010 70 35.119 \0.001

Fig. 4 Species accumulation curve for algae (a), macrophytes

(b), water beetles (c), water bugs (d), Odonata (e), fish

(f) amphibians (g) and aquatic and semi-aquatic birds (h) in

Cerrado ponds. Fit to linear or nonlinear power functions were

selected based on residual analysis of regressions. Arrows

showed the species accumulation values for water beetle and

fish at the 30 sites sampled, which is close to the number

maximum sampled for the other groups

b

Hydrobiologia (2014) 723:87–101 97

123

ponds, special characteristic of this system (e.g., the

removal of aquatic macrophytes) provides a more

parsimonious explanation. In addition, studies on

ponds have found that environmental descriptors

reflecting vegetation complexity in farmland ponds

primarily predict the diversity of species in these

habitats (Oertli et al., 2002; Vasconcelos et al., 2009;

Honkanen et al., 2011; Silva et al., 2012). It is

important to note that the major aspects that create

heterogeneity among ponds are related to the marginal

vegetation, inside-pond macrophyte cover, and the

management of nearby landowners. As the entire

landscape is shaped by economic activities, especially

cattle raising, the marginal vegetation may be mostly

related to cattle presence.

A species accumulation curve is another way to

express how species of a given group respond to

environmental heterogeneity among ponds (Kolasa

et al., 2012). The use of this analytical tool showed a

large variation among the groups suggesting that they

respond very differently to the same degree of

heterogeneity in this landscape. For instance, algae

showed the highest z-values and steep regional SAC,

which seems to reflect the effect of their larger species

richness in the regional pool. In fact, algae assem-

blages showed a highly unsaturated behavior. While

birds and Odonata yielded intermediate z-values and

good fit to SAC, fishes had a poor fit despite having the

second highest z-values. Other groups, especially

amphibians, water beetles, and water bugs, reached

to the asymptote. All these results show that those

different groups have distinct regional species–area fit,

which may be related to distinct dispersal abilities. We

have shown that they react differently to our environ-

mental predictors and that the relationships with local

variables and the pond area may reflect the trophic

state of the ponds. Higher z-values describe less

dispersive groups in isolated ponds (e.g., algae and

fish), while groups with intermediate z-values species

are not restricted, but likely to respond to landscape

heterogeneity (e.g., Odonata, birds). Moreover, SAC

fits and the differences found between estimated and

observed regional diversity jointly give us a better

understanding about how many species remain to be

found in this poorly known ecosystem.

The Cerrado biome is now a battle field between the

forces that targets to increase grain production and

those devoted to the preservation of the biodiver-

sity and the natural remnants that can maintain its

ecological functionality. Land use changes may

directly affect the presence and distribution of both

streams and ponds in this system. A recent study

focused on terrestrial fauna proposes that, considering

landscape metrics, the pasture environment in the

Cerrado may maintain better conditions for the

biodiversity (Carvalho et al., 2009). Our study in this

pasture-dominated system suggests that the majority

of ponds result from stream damming, which may

represent a serious (but yet not specifically evaluated)

environmental impact. Impoundments, especially if

they have a large volume, can reduce the water quality

downstream (decreased oxygen content, increased

temperature), and reduce longitudinal connectivity

(e.g., for fishes). Nevertheless, for small-sized dams,

the longitudinal discontinuity seems to have only little

impact on the benthic invertebrate community

(Almeida et al., 2009). Furthermore, small dams are

ponds-like systems, enlarging the network of lentic

habitats, and they are colonized by a diverse flora and

fauna as demonstrated here. This was also evidenced

in other places of the world where small dams, if well-

vegetated and with a relatively constant water level,

are attractive to many dragonfly species (Clark &

Samways, 1996; Samways, 2008). Experimental

introduction of vegetation in ponds also shows the

same pattern of increase species richness (De Marco &

Resende, 2004). The real impact of small dams has

therefore still to be investigated in the streams network

from the Cerrado. Otherwise, the continuous march of

the soy and sugarcane agriculture over pasture areas in

the Cerrado (Fearnside, 2001), may pose a threat to

these ponds. We show that they maintain a large

biodiversity, with possible intricate relations which

need to be better understood in this scenario of land-

use changes.

Acknowledgements The work by P. De Marco has been

continuously supported by CNPq productivity fellowships. We

also thank the Swiss Agency for Development and Cooperation

for its financial support.

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