CSIRO PUBLISHING

Marine and Freshwater Research, 2008, 59, 418–428 www.publish.csiro.au/journals/mfr

Microinvertebrate and plant beta diversity in dry soilsof a semiarid agricultural wetland complex

David G. AngelerA,D, Olga ViedmaA, Santos CirujanoB,Miguel Alvarez-CobelasC and Salvador Sánchez-CarrilloC

AInstitute of Environmental Sciences, University of Castilla-La Mancha, Avda Carlos III s/n,E-45071 Toledo, Spain.

BRoyal Botanical Garden, Madrid (CSIC), Plaza de Murillo 2, E-28014 Madrid, Spain.CInstitute of Natural Resources (CSIC), Serrano 115 dpdo, E-28006 Madrid, Spain.DCorresponding author. Email: david.angeler@uclm.es

Abstract. The relationship between environmental features and the β diversity of the propagule bank of dry soils oftemporary wetlands has relevance to ecological theories of community structure and to the conservation of wetlandbiodiversity. The correlation of β diversity of microinvertebrates and macrophytes derived from propagules in dry soilswith wetland habitat characteristics, catchment land-use, and the distance between wetlands in a remnant pond complexin central Spain was assessed. Redundancy analyses showed that β diversity of both groups correlated with habitatcharacteristics, whereas associations with catchment agricultural practices were weaker. Nestedness analyses showedthat species-poor communities from degraded sites tended to form nested subsets of less degraded ponds with higherspecies richness. Distance between the ponds had no significant association with community similarity, suggesting thatfragmentation did not shape β diversity at the scale of our study area. To maintain high β diversity in this area, ponds withspecies-rich propagule banks should receive conservation priority. Given the functional dependence by much wildlifeon these propagule banks once these wetlands rewet, conservation of this hidden biodiversity is crucial for providingecosystem services to humans and wildlife.

Additional keywords: agricultural landscape, anthropogenic stress, conservation ecology, macrophytes, propagule banks,spatial species turnover.

Introduction

Ecologists are increasingly aware that scale issues are impor-tant to diversity conservation. Most studies have focussed ondiversity at the local scale (α diversity), but the β-component(turnover of species communities along spatial gradients), andconsequently its effect on regional (γ) diversity, often mediatedthrough the species–area relationship (e.g. Rosenzweig 1995;Horner-Devine et al. 2004), are less well known. Many studieson different organisms or ecosystems have addressed the role ofβ diversity for structuring spatial patterns (e.g. Nekola and White1999; MacNally et al. 2004; Beck and Khen 2007) and recog-nised the influence of complex processes (Koleff and Gaston2002; Ricklefs 2004; Legendre et al. 2005). These stronglydepend on the influence of environmental heterogeneity, bio-geographical conditions and species dispersal capacities withinmetacommunities (Cottenie et al. 2003; Leibold et al. 2004;Freestone and Inouye 2006).

Anthropogenic stress, such as agricultural activity, can influ-ence community assembly locally and/or regionally throughhabitat fragmentation (increased isolation and reduced dispersal)and habitat alteration (e.g. eutrophication), thereby affecting α-,β- and γ-components of diversity (Wagner et al. 2000; Fournierand Loreau 2001; Hendrickx et al. 2007). Does increased habitatfragmentation owing to wetland loss increase β diversity through

dispersal limitation? Is the impact of agricultural activity on localhabitat conditions context-specific and dependant on the propor-tion of land-use types in the catchments? How do these land-useimpacts vary with spatial scale? Are the effects of habitat frag-mentation or habitat alteration more important, and how do theyaffect species assemblages and their spatial turnover?

Temporary ponds are island-like systems surrounded by landand the constituent biota of their propagule banks has poor activeoverland dispersal capacities (Angeler and García 2005), eventhough they may be carried passively by biotic (birds) or abi-otic agents (winds) (Brendonck and Riddoch 1999; Figuerolaet al. 2005). Consequently a high degree of variability in bioticcommunities exists between ponds as a result of local ecologicalconstraints according to the species-sorting perspective in meta-community ecology (Leibold et al. 2004; Cottenie 2005). Basedon this rationale it is reasonable to assume a high β diversityof island-like aquatic ecosystems and this is supported by someempirical data (Colburn 2004; Robson and Clay 2005; Soininenet al. 2007). However, despite wetlands being recognised asbiodiversity hotspots (Mitsch and Gosselink 2000), only a fewstudies have addressed β diversity focusing either on organismswith distinct dispersal capacities in fragmented habitats withoutseeking underlying environmental correlates of patterns (Briedand Ervin 2005; Guadagnin et al. 2005; Robson and Clay 2005),

© CSIRO 2008 10.1071/MF07206 1323-1650/08/050418

Beta diversity in dry soils Marine and Freshwater Research 419

or, if environmental factors have been considered, informationis restricted to hydrologically interconnected floodplain or pondsystems (Cottenie et al. 2003; Freestone and Inouye 2006; Liuet al. 2006).

In the present study we focus on the latent diversity in drysoils of a remnant temporary wetland complex in an agricultur-ally heavily exploited landscape of semiarid Spain. Althoughdry temporary wetland soils seem virtually devoid of activeaquatic life, they accumulate a tremendous variety of dormantinvertebrate resting eggs, plant seeds and protist cysts (i.e. thepropagule bank) (Brendonck and De Meester 2003; Angelerand García 2005). Once ponds rewet, the propagule banks con-tribute to the formation of a diverse and functionally important‘plankton soup’ whereby the emerged organisms provide animportant food supply for later colonising amphibians, fish andbirds (Jenkins and Boulton 2007). Dry propagule banks are thusideal model systems for diversity research and have great poten-tial for evaluation of wetland ecological integrity and the effectsof anthropogenic stress (Angeler and García 2005). However,the low morphological diversity of propagules has traditionallyhampered diversity assessments. This problem can be overcomeby artificially rewetting dry soils under laboratory conditions(Vandekerkhove et al. 2005). This method has been shown toextract more species compared with sampling in the field, and itis often the only choice for assessing diversity if wetlands remaindry during the life time of a scientific project.

Our study area is situated in an agricultural landscape where∼70% of wetlands have been lost (conversion to croplands)and others have suffered from decade-long degradation throughovergrazing, waste water discharge, channelisation, ploughing,dumping, vehicle races and construction (Angeler, unpubl. data).As a result, the remnant wetland network is increasingly frag-mented and shows strong variability in local habitat qualityand regional land-use characteristics. These impacts can beintegrated in the ecological memory of the temporary pond’spropagule banks (Brendonck and De Meester 2003), and maybe manifest in a reduced diversity potential in severely degradedponds (Angeler and García 2005). Making use of this integrativememory, we focus on the hidden diversity potential of microin-vertebrates and macrophytes banked in dry pond soils to test thefollowing hypotheses:

(1) Because microinvertebrates and macrophytes are strictlyconfined to the local wetland habitat, their β diversity shouldbe associated with wetland habitat characteristics ratherthan land-use features in agricultural uplands. We usedmultivariate analysis to explore the strength of correlationbetween β diversity, wetland habitat features and land useacross four spatial scales (the 100-m buffer strip surroundingthe ponds and 1-km, 5-km, and 10-km catchment scales).

(2) Combinations of current distribution patterns of ponds andtheir degradation history rather than fragmentation alonecorrelates with the spatial community similarity in this rem-nant wetland complex. The few remaining wetlands in ourstudy area show spatially random variability in severe localhabitat degradation resulting from point sources of con-tamination (Angeler, unpubl. data). This could mask therelationship between community similarity and geographicdistance decay. By contrast, if degraded ponds would show

non-random clustering in the landscape this relationshipshould become significant.

(3) The revealed β diversity characteristics can help settingmanagement priorities for the remnant wetland complex.Using nestedness analyses, we test whether the speciesassemblages of degraded ponds are spatially nested subsetsfrom more diverse assemblages occurring in least-impactedponds. In such a case, conservation efforts can be more cost-effective, and β diversity maintained, by concentrating ona few focal ponds with high species richness rather thanemploying regionally based management schemes includingmany ponds that differ dramatically in species composition(Hecnar and M’Closkey 1997).

Material and methodsStudy areaThe Campo de Calatrava area is situated in central Spain(39◦00′N, 4◦25′W; 38◦30′N, 3◦23′W; Fig. 1). It covers 12 227 ha,and it formed in the late Pliocene and early Pleistocene fromhydromagmatic and Strombolian volcanic activity. It containedonce a unique, biologically rich and spatially discontinuouscomplex of more than 50 temporary ponds of different geo-morphic types (depressional, piedmont and volcanic craters)(García-Canseco 2000).

Agricultural activity in the second half of the nineteenth cen-tury caused massive land degradation and a more than 70%wetland loss (Angeler, unpubl. data). Many of the remnant wet-lands are degraded locally from cattle grazing, waste waterdischarge, dumping, and channel construction. The hydrolog-ical disturbance regime of all wetlands is dependent exclusivelyon rainfall and none of these wetlands is flooded artificially.Many ponds have altered hydroperiods as a result of road con-structions in their catchments that influence runoff processes.Although some wetlands may share the same catchment espe-cially at the 5-km and 10-km scale (Fig. 1) all ponds have aunique sub-catchment with no shared drainage under currentconditions. This is also reflected in the lack of hydrological sur-face connection between the ponds when they are inundated.Because many aquifers in the region have been severely over-exploited as a result of agricultural irrigation, no groundwaterconnection exists between ponds.

Despite degradation, a unique wetland fauna and flora canstill be found in this area (Velayos et al. 1989; Alonso 1996;Sánchez andAngeler 2007) highlighting the value of the remain-ing wetlands for regional biodiversity. For the present study,twelve wetlands were chosen that represented abiotic variabil-ity, landscape characteristics and anthropogenic stress conditionsamong wetlands in the region (García-Canseco 2000) (Table 1).

Sampling and experimental designBecause most wetlands were dry during our project because ofa prolonged supraseasonal drought period, we used an outdoormicrocosm design to study the propagule bank potential of drywetland soils of these wetlands and microinvertebrate fauna andmacrophyte flora that develop from them. Although the use ofmicrocosms is debated in the literature (Huston 1999), the com-position, structure and function of such systems approximatesthe organisation of larger systems, and the resulting interactions

420 Marine and Freshwater Research D. G. Angeler et al.

Almodovar

Alberquilla

Garbanzos

Saladilla

Cucharas

Cañada

Carrizosa

Caracuel

PosadillaPrado

Nava Grande Nava Enmedio

10

SPAIN

N

km

200

Pond � Buffer

1 km

5 km

10 km

Scales

N4335000

N4305000

N4275000

E360000 E405000 E450000

Fig. 1. Location of study ponds (UTM, Universal Transverse Mercator Coordinate System positions [northand east coordinates in zone 30]) in the Campo de Calatrava area (central Spain) showing their stratifiedlandscape surroundings.

Table 1. Summary of characteristics and locations of the study wetlandsUTM, Universal Transverse Mercator coordinates

Wetland Geographic location Municipality Altitude Wetland Distance to nearest Geomorphic Trophic status(UTM coordinates) (m) size (ha) pond (km) type (total P; mg L−1)A

Alberquilla Z30, E410731, N4272899 Mestanza 833 6.5 16.98 Crater 0.14Almodovar Z30, E398387, N4285646 Almodóvar de Calatrava 640 22.6 5.49 Crater 10.05Cañada Z30, E409333, N4298926 Cañada de Calatrava 607 60.2 2.81 Piedmont 0.17Caracuel Z30, E407498, N4297226 Caracuel de Calatrava 627 61.4 2.82 Piedmont 0.18Carrizosa Z30, E392261, N4299942 Cabezarados 654 21.1 3.24 Piedmont 0.21Cucharas Z30, E399958, N4289407 Villamayor de Calatrava 609 106.8 2.95 Depression 0.22Garbanzos Z30, E389009, N4299957 Cabezarados 638 21.6 3.24 Depression 0.16Nava Enmedio Z30, E4214444, N4336323 Malagón 586 36.2 2.63 Piedmont 0.17Nava Grande Z30, E418069, N4337275 Malagón 578 110.2 2.63 Piedmont 0.12Posadilla Z30, E408938, N4310859 Ciudad Real 633 13.4 19.05 Crater 4.87Prado Z30, E427313, N4308263 Pozuelo de Calatrava 542 51.7 19.05 Depression 0.23Saladilla Z30, E399913, N4292226 Villamayor de Calatrava 609 39.3 2.95 Depression 1.56

AThese values represent the means of three replicate microcosms sampled in the present study. No field data were available.

observed in these experimental units should reflect at least asubset of biological and physical-chemical processes that occurin the field (Angeler and García 2005).

Dry sediments were collected in December 2005 when allwetlands were dry. Sediments were collected in 10 × 10 cm

squares at randomly chosen sites that covered three possible habi-tat types (wetland soils from emergent vegetation stands, soilsfrom non-helophyte vegetation areas, and uncovered sediments).These samples were composited so that the total amount of col-lected sediment within a wetland was proportional to its size.

Beta diversity in dry soils Marine and Freshwater Research 421

We took care during composition to take sediment volumes inproportion to the size of these three habitats within each wetland,which was estimated visually in the field. We made no attemptsto evaluate the relationship between wetland size and propaguletaxonomic structure across wetlands because species richness inpropagule banks is highly variable between and within wetlandtypes (Wissinger 1999; Cronk and Fennessy 2001).

The collected sediment was stored in the laboratory in thedark at room temperature for 2 months. Before use in the exper-iment, sediments were thoroughly mixed and coarse organicmatter was removed. For each wetland six microcosms (30-Lplastic aquaria) were used. These were designated to a ‘floodingtreatment (FT)’ and a ‘damp treatment (DT)’ with three repli-cates in each. Because artificial laboratory conditions can likelylimit the establishment of species from the egg banks (Angelerand García 2005), we placed the microcosms in the field wherenatural temperature and light cues should have favoured therecruitment of a range of species as would occur in ponds afterrewetting. The replicates were placed in a complete randomisedblocks design on outdoor benches at the Campus Tecnológicoof UCLM (Toledo) with one replicate from each treatment andwetland comprising one block. The meteorological conditions atthe Campus were very similar to those occurring in the Campode Calatrava during the experiment. On 6 February 2006, allmicrocosms received 4 L of sediment and the FT received 20 Lof tap water to induce microinvertebrate hatching and commu-nity dynamics. Previous studies have shown that tap water hadno influence on hatching and community dynamics comparedwith distilled water (Angeler et al. 2006). All microcosms werecovered with transparent plastic foils to avoid aerial contamina-tion with resting eggs. Air exchange with the atmosphere wasguaranteed by drilling holes (5 mm diameter) in the microcosmsthat were covered with 50-µm plankton net. DT received wateruntil soil saturation only.

Measurement of local variablesWater quality and microinvertebrates were sampled weekly in FTfrom 7 February 2006 to 18 April 2006, which reflected a periodwhen Mediterranean wetlands can be wet in nature. Macro-phyte development was monitored in FT and DT until autumn(September/October) 2006 when plant senescence began. Thecombined DT and FT treatments revealed the broad spectrum ofmacrophyte types and taxon richness, including submerged andamphibious species. Because of difficulties in measuring abun-dance of individual taxa, the plant community was evaluated onthe basis of incidence of taxa. The microcosms were inspectedhaphazardly and taxa were recorded when they occurred at anidentifiable stage.

Detailed protocols for water quality measurements (pH,electrical conductivity, dissolved oxygen concentration, Secchitransparency [in situ measurements], chlorophyll a [spectropho-tometrical analysis after methanol extraction], total phosphorus[APHA-methods] and total nitrogen [automated CN analyser])are given in Angeler et al. (2004). Six-L concentrated subsam-ples of water were used for microinvertebrate density evaluationand identification using sedimentation chambers and an invertedmicroscope as described in Angeler et al. (2006).

Measurement of landscape variablesData of topographic features and land-use percentage coverswere determined in a hierarchical design across four levels ofinfluence: a 100-m buffer strip surrounding the wetlands, andthree landscape scales (1 km, 5 km and 10 km). Topographicdata (slopes and altitudes) were calculated from a Digital TerrainModel with lines at 25-m intervals obtained from the SpanishNational Centre of Geographical Information (CNIG). Percent-age land use cover was extracted from revised CORINE 2000(EEA 2000) and divided into three broad classes: natural vegeta-tion (comprised of conifers and deciduous woodlands, dehesas,shrublands and grasslands), dry croplands (herbs, olives andvineyards) and irrigated croplands (also comprising herbs, olivesand vineyards categories). Wetland size was determined fromCORINE maps.

Delimitation of catchments was carried out using the digitalterrain model processed in the Geospatial Hydrologic Mod-elling Extension (HEC-GeoHMS) model ofArcView GIS (ESRI1999). Based on this method new catchment-specific mapswere created for each wetland at each spatial scale for furtherprocessing.

AnalysesTo standardise comparisons between macrophytes and micro-invertebrates, we used indices based on incidence (presence/absence) data, which are commonly used in studies of β diver-sity (Koleff et al. 2003). We initially explored the performanceof different indices including the Routledge (βr), Ochiai, Faith,Sørensen, and Russel and Rao indices (summarised in Legendreand Legendre 1998). Because no major differences were found,we present the results from the Sørensen index, which is regardedas one of the most effective incidence similarity measures(Southwood and Henderson 2000). We added a dummy vari-able ‘1’ to calculate the dissimilarity matrix for macrophyte datato avoid distortion of the ordination that would have arisen asa result of zero germinations in the Almodovar and Posadillaponds (Clarke et al. 2006). No dummy variable was necessaryto add for calculating the microinvertebrate dissimilarity matrixbecause all samples had at least one hatching species.

Our presence/absence data matrices of plants and inverte-brates were converted into dissimilarity matrices that presentedall possible combinations of pairwise comparisons betweenponds. The invertebrate and macrophyte dissimilarity matri-ces were used in separate non-metric multidimensional scalinganalyses (NMDS; PRIMER 6, Primer-E Ltd, Plymouth, UK) toordinate sites according to their faunal and floral dissimilarityrespectively. The spatial turnover in species composition wascaptured on three dimensions without losing too much of theoriginal data variability (3D stress values in macrophytes andmicroinvertebrate ordinations were 0.05 and 0.09 respectively).The dimension scores were then used as dependent variables forexploring the correlation of spatial turnover with wetland habitatfeatures and landscape characteristics at the four spatial scales inredundancy analyses (RDA). This multivariate technique allowsdecomposing the variance attributable to phenomena either at thelocal scale (i.e. habitat characteristics) or at each of the landscapescales (terBraak and Šmilauer 1998).

422 Marine and Freshwater Research D. G. Angeler et al.

Table 2. Summary of data on habitat and landscape characteristics ofthe studied wetlands (n = 12)

Mean s.e. Min. Max.

Wetland habitat characteristicsWetland size (ha) 45.92 9.86 6.52 110.21Dissolved O2 (mg L−1) 8.53 0.17 7.65 9.33Temperature (◦C) 10.24 0.06 9.80 10.40pH 8.35 0.14 7.82 9.34Electrical conductivity (µS cm−1) 1277.30 429.82 208.00 4560.00Secchi transparency (cm) 17.05 1.49 4.25 20.00Total P (mg L−1) 1.51 0.87 0.12 10.05Total N (mg L−1) 5.41 0.45 3.31 8.03Chlorophyll a (µg L−1) 0.96 0.26 0.07 2.58

Landscape characteristicsDistance between wetlands (km) 6.99 2.00 2.63 19.05

Buffer-scale featuresCatchment size (ha) 32.11 4.43 12.59 61.19Ratio catchment : wetland 0.94 0.14 0.39 1.93Altitude (m) 675.98 18.57 629.00 866.00Slopes 2.54 1.03 0.11 11.70Natural vegetation (% cover) 39.00 12.04 0.00 100.00Dry croplands (% cover) 49.16 10.13 0.00 100.00Irrigated croplands (% cover) 11.85 4.61 0.00 44.00

1-km scale featuresCatchment size (ha) 471.42 82.65 112.94 986.81Ratio catchment : wetland 16.65 4.25 1.61 45.55Altitude (m) 695.82 16.19 634.00 857.00Slopes 5.13 1.03 0.51 11.41Natural vegetation (% cover) 36.94 10.50 0.00 99.76Dry croplands (% cover) 47.07 8.25 0.24 81.28Irrigated croplands (% cover) 7.42 2.60 0.00 25.24

5-km scale featuresCatchment size (ha) 1225.70 188.76 36.26 2361.03Ratio catchment : wetland 57.68 18.80 0.34 232.89Altitude (m) 690.68 12.18 646.19 810.00Slopes 4.87 0.63 1.95 9.62Natural vegetation (% cover) 35.28 8.10 0.00 91.18Dry croplands (% cover) 50.94 6.27 8.82 88.74Irrigated croplands (% cover) 10.91 5.02 0.00 57.89

10-km scale featuresCatchment size (ha) 3139.42 350.23 2188.82 5434.96Ratio catchment : wetland 130.90 41.80 19.86 485.07Altitude (m) 680.06 9.26 627.04 753.00Slopes 4.30 0.60 1.68 9.28Natural vegetation (% cover) 34.90 6.32 10.46 89.89Dry croplands (% cover) 49.97 5.05 4.23 63.91Irrigated croplands (% cover) 11.33 2.62 0.00 28.84

We first used all habitat characteristics and landscapevariables (Table 2) as explanatory variables in a forward selec-tion in RDA to find a set of parsimonious explanatory vari-ables for partial redundancy analyses (pRDA). In Local andLocal + Landscape models, dissolved oxygen concentrations,wetland area and irrigated croplands (for microinvertebrates) andelectrical conductivity, total phosphorus, Secchi transparencyand the catchment : wetland size ratio (for macrophytes) werethe local and regional variables with significant conditionalcontributions. We then used these significant variables as mainlocal-landscape variables in pRDA.

Redundancy analysis is a constrained principal compo-nent analysis that allows the extraction of patterns fromthe explained variation of environmental variables (i.e. directgradient analysis). This analysis is suitable for short lin-ear or monotonic responses and/or compositional gradients(<2 s.d.) (terBraak and Šmilauer 1998). When RDA includesco-variables (i.e. pRDA), the correlation of these co-variableswith the response of dependant variables is eliminated, andthe sum of canonical eigenvalues represents the varianceexplained apportioned to other environmental variables afteraccounting for the co-variables (ter Braak 1988). For exam-ple, autocorrelation may exist between local and landscapecharacteristics. If we were interested in the sole effects oflocal characteristics, landscape variables can be entered asco-variable in the analyses and the resulting inertia is thenexclusively apportioned to local variables. This is achievedmethodologically by replacing environmental variables bytheir residuals after regressing each environmental variable onco-variables and later fitting the residuals to the data matrix. Inall analyses, scaling was optimised for inter-sample distance andvariables were log-transformed [Y′ = log(Y + 1)] to lessen theeffect of skewed distributions.

Partial RDA allowed the decomposition of the variance intovarious components attributed to different sets of explanatoryvariables (ter Braak 1988). In the present study, we decomposedvariance attributable to explanatory variables following Cottenieet al. (2003):

(1) Local variation [L]: variation explained by wetland habi-tat conditions without eliminating autocorrelation withco-variables (landscape variables).

(2) Landscape variation [R]: variation explained by landscapeconditions. RDA models at buffer and landscape scales(1 km, 5 km and 10 km) without eliminating autocorrelationwith co-variables (wetland habitat variables).

(3) Pure local variation [L|R]: the fraction of species variationthat can be explained by local conditions after accountingfor autocorrelation with landscape condition (corresponds inthe univariate case to a partial linear regression procedure).

(4) Pure landscape variation [R|L]: the fraction of speciesvariation that can be explained by landscape conditionsindependently of any local characteristic.

(5) The variation explained by combined Local and Landscapevariables [L + R].

(6) The shared/confounded variation explained simultaneouslyby Local and Landscape conditions [L∩R] ([L∩R] = [L] −[L|R] = [R] − [R|L]).

(7) The total of unexplained variance (100 − [L + R]).

A stepwise selection method for entering variables wasapplied using a Monte Carlo permutation test (999 runs) inCANOCO software (terBraak and Šmilauer 1998) for signifi-cance testing. We used permutations under the reduced model(this permutes the raw data in the [L + R], [L], and [R] anal-yses, and the residuals from the co-variables in the [L|R] and[R|L] analyses) since this better maintains the Type I errorin small datasets (terBraak and Šmilauer 1998). The fractions[L∩R] and 100 − [L + R] were derived without significancetesting.

Beta diversity in dry soils Marine and Freshwater Research 423

Nava Enmedio

Cañada

Garbanzos CaracuelCucharas Almodovar

Alberquilla

PradoNava Grande

SaladillaPosadilla

Carrizosa

Cañada

AlberquillaCarrizosa

Nava GrandePosadilla

Saladilla

Prado Nava Enmedio

GarbanzosCucharas

Almodovar

Garbanzos

Caracuel

AlberquillaCarrizosa

Cañada

Nava GrandePosadilla

CucharasAlmodovar

Saladilla

PradoNava Enmedio

Saladilla

Prado Alberquilla

Carrizosa

Cañada

Nava Enmedio

GarbanzosCucharas

Caracuel

Nava Grande

Almodovar �Posadilla

Nava Grande

Cucharas

Prado

Saladilla

Carrizosa

Alberquilla

Garbanzos

Almodovar �Posadilla

Nava Enmedio

Cañada Caracuel

Alberquilla

Garbanzos

CarrizosaNava Enmedio

CañadaCucharas

PradoNava Grande

Saladilla

Almodovar �Posadilla

Caracuel

CaracuelNM

DS

2

NMDS 1 NMDS 1

Mic

roin

vert

ebra

tes

NMDS 2

Mac

roph

ytes

NM

DS

2

NMDS 1 NMDS 1 NMDS 2

NM

DS

3N

MD

S 3

NM

DS

3N

MD

S 3

Fig. 2. Non-metric, multidimensional scaling plots showing 3-D ordinations of ponds according to microinvertebrate and macrophyte communitydissimilarity. Note in the macrophyte ordination that Almodovar and Posadilla ponds had no macrophytes and these ponds are represented by the dummyvariable (see methods).

To test whether spatial species turnover is related to a non-random pattern in species distribution, patterns in assemblagecomposition of microinvertebrates and macrophytes were eval-uated by examining the incidence of nestedness in speciesdistributions using the software BINMATNEST (Rodríguez-Gironés and Santamaría 2006). A nested subset pattern occurswhen species-poor assemblages form subsets of species-richassemblages, such that rare species occur only in the richestassemblages and common species occur in assemblages with awide range of richness values (Patterson and Atmar 1986). Nest-edness was quantified using the temperature metric (T), whichmeasures the degree of disorder in the species presence/absencematrix and ranges from 0◦ for a perfectly nested matrix (max-imum order) to 100◦ for a totally random matrix (maximumdisorder). The program ‘packs’ the original matrix into a max-imal state of nestedness where the topmost site is judged tobe the most hospitable, and where the leftmost species is theone whose niche requirements are most common and prevalentacross sites (Atmar and Patterson 1993). The significance of thismaximally ordered (packed) matrix is tested against the mean Tvalue of matrices that are drawn at random. In the present study,the degree of nestedness of the packed species × pond islandmatrices (one for microinvertebrates and another one for macro-phytes) was tested against 2000 randomly drawn matrices usingthe most conservative null model (Model III) and the recom-mended parameter specifications of the genetic algorithm usedby BINMATNEST (population size = 30, number of individualsused for generations = 7, number of generations = 2000). Spear-man rank correlation was used to test for a relationship betweeneach pond’s nestedness rank and our environmental variables(Table 2).

To test whether geographical distance shapes faunal and flo-ral species turnover through potential effects of biogeographic

isolation we used a Mantel-type permutation test (10 000 runs,software by Jensen et al. 2005). We used different combinationsof log-transformed geographic distances or β-diversity measure-ments (community dissimilarity matrices derived from NMDS)which have been shown to be useful for determining the bestlinear fit of data (e.g. Nekola and White 1999; Condit et al.2002). We re-tested matrix correlations with a non-parametrictechnique that does not make any assumption on the linearity ofthe relationships (RELATE analysis, 10 000 runs; PRIMER 6).ArcView GIS software was used to calculate pairwise distancesbetween all possible sites, using Universal Transverse Mercator(UTM) projections of latitude and longitude data.

ResultsPatterns and environmental correlation of β diversityThe 3-D NMDS ordination of microinvertebrates shows anarrangement of most wetlands along dimension 2 in the cen-tre of the ordination space, whereas the Garbanzos pond and theCaracuel pond are situated towards the left and the right respec-tively (Fig. 2, upper left and middle panels). The reduced RDAmodel suggests that the community dissimilarity of microin-vertebrate species was influenced chiefly by habitat conditions[L] (Table 3), although the model was not very robust (34–41% of unexplained variance across spatial scales). Wetlandsize (r = 0.69, n = 12) and dissolved oxygen concentrations(r = 0.61, n = 12) correlated significantly with community dis-similarity in the constrained axes (P = 0.02). The lack of sig-nificant pure habitat [L|R] and landscape [R|L] associationsand the variable degree of shared variance between habitat andlandscape variables [L∩R] suggests that the wetland size andoxygen effects on community dissimilarity were a result of

424 Marine and Freshwater Research D. G. Angeler et al.

Table 3. Results from redundancy analyses (RDA) showing variance decomposition (variance explained [%]) and associated P levels (∗P < 0.05,∗∗P < 0.01) of spatial species turnover of microinvertebrates and macrophytes in ponds of the Campo de Calatrava area across four landacpe scalesThe components are: [L + R] total variation explained by combined local (wetland habitat) and landscape variables, [L] variation explained by wetland habitatfeatures, [R] variation explained by landscape variables, [L|R] pure variation owing to wetland habitat features, [R|L] pure landscape variation, [L∩R] thelandscape structuring in the species data that is shared by the wetland habitat data, and 100 − [L + R] unexplained variation. No significance values were

calculated for [L∩R] and 100 − [L + R]. ns, not significant

Microinvertebrates Macrophytes

Buffer 1 km 5 km 10 km Buffer 1 km 5 km 10 km

[L + R] 66ns 61ns 59ns 61∗ 97∗∗ 98∗∗ 97∗∗ 98∗∗[L] 48∗ 48∗ 48∗ 48∗ 83∗∗ 83∗∗ 83∗∗ 83∗∗[R] 52ns 41ns 37ns 42ns 53∗ 34ns 28ns 39∗[L|R] 29ns 16ns 20ns 29ns 39∗∗ 59∗∗ 64∗∗ 55∗∗[R|L] 33ns 8ns 9ns 23ns 9ns 10ns 8ns 11ns

[L∩R] 19 32 28 19 44 24 19 28100 − [L + R] 34 39 41 39 3 2 3 2

a co-variation with landscape effects (Table 3), but none ofthe landscape features were significant at the different spatialdomains.

The 3-D NMDS macrophyte ordination shows a clusteringof seven wetlands that are flanked by the remaining wetlands(Fig. 2, lower left and middle panels). The close arrangementof points in the cluster suggests that community dissimilaritybetween the sites composing this cluster is lower. By contrast,the communities of the sites that flank the cluster are more dis-similar, and the distance between the wetlands in the clusterand those that flank them suggests higher spatial communitydissimilarity.

The patterns of the reduced RDA models for macrophyteswere more robust with the amount of unexplained variance rang-ing only 2–3% across spatial domains (Table 3). Pure habitateffects [L|R], chiefly salinity concentrations (reflected in electri-cal conductivity [r = 0.43, n = 12]), total phosphorus concentra-tions (r = 0.73, n = 12), and turbidity levels (reflected by Secchitransparency [r = −0.92, n = 12]), were significantly correlatedwith the constrained axes across spatial scales (P < 0.002) withthe amount of variance ranging 39–64%. The only indicationsfor a correlation with landscape effects [R] were evident at thebuffer-zone and 10-km scale, although these effects are lost uponcorrecting for [L]. At the 10-km scale, the catchment : wetlandsize ratio explained this landscape correlations, whereas noneof our variables correlated with the [R] component at thebuffer-zone scale.

The influence of biogeographical isolationNone of the different combinations of untransformed and log-transformed community similarity and geographic distancerelationships was statistically significant in either the Man-tel test (Microinvertebrates: r2 = 0.036, P = 0.16; Macrophytes:r2 = 0.05, P = 0.1) or non-parametric test (RELATE: Micro-invertebrates: Spearman’s ρ = −0.106, P = 0.74; Macrophytes:ρ = 0.231, P = 0.1). This suggests that biogeographical condi-tions (distance between ponds) seem to be less important in theregulation of β diversity.

Nestedness patternsTwo thousand randomisations of the species-island matrixshowed microinvertebrate communities formed nested subsetsin the study area (T = 22.122◦, P < 0.0001). In accordance withRDA, Spearman rank correlation showed that the ponds inthe packed matrix were arranged with respect to environmen-tal variables. In contrast to the RDA model, wetland size wasnot a significant local correlate of pond ranking (P = 0.37).Ponds were ranked according to dissolved oxygen (Spear-man’s ρ = 0.727; n = 12; P = 0.004), phytoplankton biomass(Chlorophyll a; Spearman’s ρ = 0.517; n = 12; P = 0.042), andtotal phosphorus concentrations (Spearman’s ρ = 0.608; n = 12;P = 0.018) (Fig. 3). This suggests that species occurring ineutrophied ponds were drawn from predictable subsets of theassemblages occurring in less nutrient-enriched ponds.

Macrophytes did not show significant nestedness patterns(T = 31.78◦, P = 0.8). Despite the lack of significance, thearrangement of the ponds in the packed matrix was in goodagreement with the RDA solution. Ponds were arranged accord-ing to salinity (Spearman’s ρ = 0.758; n = 12; P = 0.011) andturbiditiy levels (Spearman’s ρ = 0.646; n = 12; P = 0.044)(Fig. 3).

Discussion

The present study shows that wetland habitat characteristicsrather than landscape features correlate with community dis-similarity of microinvertebrates and macrophytes in the studiedwetland complex. The similar RDA models of both groups interms of prevailing local influences on β diversity suggest thatlife-history traits of macrophytes and microinvertebrates may berelevant. In contrast to many terrestrial and actively dispersingaquatic species (birds, insects, amphibians) which can occupyhabitats on islands and their surrounding matrices (Herzog andKessler 2006; Lövei et al. 2006), obligate aquatic taxa are strictlyconfined to pond habitats, unless being dispersed passively byabiotic or biotic vectors.Although land-use conditions can affectdirectly the patterns of community dissimilarity of terrestrialand active aquatic dispersers (Bengtsson et al. 2005; Dauberet al. 2005; Hendrickx et al. 2007), obligate aquatic species are

Beta diversity in dry soils Marine and Freshwater Research 425

Eutrophication

(a) Microinvertebrates # Obs. spp. Pond rank37 Caracuel28 Garbanzos27 Cañada26 Nava Enmedio22 Alberquilla21 Carrizosa22 Prado22 Nava Grande19 Posadilla16 Saladilla13 Almodovar

9 Cucharas

Low

High

# Obs. spp. Pond rank12 Garbanzos10 Nava Enmedio12 Carrizosa9 Cañada

11 Cucharas8 Alberquilla6 Saladilla8 Caracuel7 Prado5 Nava Grande

(b) Macrophytes

Salinity, turbidity

Low

High

Fig. 3. Nested pattern of microinvertebrate andmacrophyte species occurrence in temporary pondsof the Campo de Calatrava area (central Spain).Each column in the matrix represents either amicroinvertebrate or macrophyte species and eachrow represents a temporary pond. The number ofobserved species for each pond is listed at the endof each row. The nested pattern for both groupsshows that assemblages of degraded ponds form anested subset of less degraded ponds.

spatially segregated from land use. This can make their spatialturnover potentially less sensitive to agricultural practices. How-ever, this is not to be confounded with the influence of landscapeprocesses on local diversity (α diversity). Indeed, many studieshave shown adverse land-use effects on local aquatic habitat,which can affect communities indirectly and reduce local diver-sity through the biogeochemical coupling of aquatic islands withtheir surrounding landscapes. In the present study, the lack of sig-nificant landscape correlations across most spatial scales (exceptthe 10-km scale for macrophytes), or the lack of land-use cate-gories to be associated with these effects when the scale effectswere significant, supports the idea that community dissimilar-ity of obligate temporary pond taxa is relatively buffered fromdirect effects of agricultural activity in the landscape.

Another explanation for the relatively low influence of landuse on β diversity is related to the strong local point contam-ination of many wetlands that is unrelated to land use. Manywetlands in the Campo de Calatrava area have traditionallyserved as natural waste water treatment areas, storage sitesfor solid wastes, have subsidised animal breeding or sufferedfrom other local practices that contributed to severe eutroph-ication. This was especially evident in some of the wetlandswhere total phosphorus concentrations were extremely high(Table 1). Although the mechanisms of degradation on commu-nities have not been studied, Angeler et al. (unpubl. data) haveshown that these local effects can override any adverse land-useeffect, thereby becoming the main contributor of degradationof ponds, and in the present context, also the main regulator ofβ diversity.

Despite wetland habitat features being most important forboth taxonomic groups, macrophyte β diversity differed frommicroinvertebrate spatial community dissimilarity by the corre-lation with landscape features (catchment : wetland size ratio)particularly at the 10-km scale. Alvarez-Cobelas et al. (2005)have shown that Mediterranean aquatic ecosystems are situatedin comparatively larger catchments than those in temperate areas,and our study suggests that this effect can directly influencewetland biodiversity. Although this size ratio is a quantitativemeasure that highlights a small patch size effect, it is difficult tointerpret how it correlates with qualitative measures that influ-ence β diversity. Further explorations including a broader setof variables related to landscape structure and habitat features,and how these may potentially correlate with biotic processesin the metacommunity (including passive seed transport bywater fowl) could help reveal the qualitative relevance of thecatchment : wetland size ratio.

Water quality is not only an important filter that triggersemergence of microinvertebrates and macrophytes banked inwetlands soils, but it influences also their posterior commu-nity development (Angeler and García 2005). Poor water qualityeliminates sensitive species from local communities and cancontribute to an increase of β diversity on a regional scale ifsome ponds remain relatively free from human impact. In fact,the ranking of ponds in our BINMATNEST analyses suggestthat microinvertebrate and macrophyte communities from pondswith poor water quality were nested subsets of communities fromless degraded sites, suggesting that species distribution patterns,and consequently β diversity, are driven by local degradation.

426 Marine and Freshwater Research D. G. Angeler et al.

The complementary BINMATNEST and RDA models formacrophytes are in good agreement in terms of significantcorrelations with habitat variables, and although the nestednessanalysis was not significant, the combined results can be inter-preted straightforwardly. Most ponds that comprised the clusterin the 3-D NMDS ordination (Fig. 2) occupied higher ranks inthe nestedness analyses (Fig. 3), whereas the remaining pondswith lower ranks occurred outside this cluster. This suggests thatthe cluster in the ordination was composed of less degradedsites (lower salinity and turbidity) with higher species richness,flanked by species-poor, degraded sites (higher turbidity andsalinity). Thus the ordination captures with relative confidencethe contribution of each wetland to β diversity of macrophytetaxa.

These patterns were less clear for the microinvertebrates.RDA suggested wetland size rather than eutrophication (i.e. nest-edness analyses), as the main local correlate of species turnover.Even though the 3-D NMDS ordination captured relatively wellthe spatial turnover of microinvertebrate species richness (stressvalue 0.09), the resulting RDA analysis was not very robust, andits ecological meaning is difficult to interpret, based on variablesthat correlated with spatial community dissimilarity. Given thatthe results from the nestedness analysis were highly significant,we are confident that eutrophication was associated with speciesdistribution in the wetland complex.

From the purely spatial perspective, habitat fragmentation orbiogeographical isolation is known to have a major influence onspecies turnover through the similarity decay of ecological com-munities with increasing geographical distance (Soininen et al.2007).Although natural biogeographical isolation may have pos-itive effects on biodiversity through the promotion of β diversity(Fahrig 2003; Freestone and Inouye 2006; Marchant et al. 2006)the effects of habitat loss in human-fragmented systems may bemore complex and vary with environmental context. In the con-text of pure fragmentation effects our insignificant Mantel testresults for macrophytes and microinvertebrates would suggesta low dispersal limitation of both groups in the relatively smallstudy area (12 000 ha), a fact that has been recently demonstratedfor several taxa that have been otherwise believed to have pooroverland dispersal capacities (Charalambidou and Santamaría2005; Figuerola et al. 2005; Louette and De Meester 2005).However, we lack experimental evidence that could prove thatmicroinvertebrates and macrophytes are widely dispersed in ourstudy area.

Alternatively, our results suggest that fragmentation alonemay not be a strong environmental correlate of community dis-similarity in agricultural areas. Local degradation of ponds isspatially random within the Campo de Calatrava area (Angeler,unpubl. data), and this can substantially increase community dis-similarity between heavily degraded ponds and least-impactedsites that may otherwise be situated closely to each other. Thishigh community dissimilarity between close ponds may blur anypotential community similarity decay with increasing geograph-ical distance, independent of the biogeographical distribution ofponds, and lead to insignificant Mantel test results.

Management implicationsAlthough an increasing number of studies recognise the impor-tance of habitat permanence (hydroperiod) on wetland biota, we

could not include this variable in our study because of a pro-longed drought period spanning the duration of our project, andbecause of the lack of previous hydroperiod determinations ofthis ecologically poorly studied wetland complex. Although ourwetlands could potentially show a range of different hydroperi-ods, we expect these differences to be integrated in the ecologicalmemory of the dry propagule banks of each wetland. Becausethe propagule banks do not only integrate natural disturbancebut also anthropogenic stress (Angeler and García 2005), it isreaffirming that the degradation status of individual ponds is amajor determinant of species composition within, and spatialturnover between, ponds.

We acknowledge that the use of microcosms to representcommunities and local variables in the present study may onlyrepresent a subset of those that might occur in the field. However,prolonged droughts compromise research in temporary wetlandsand research using microcosms often becomes the only choice.Despite limitations, microcosm studies hold potential to reflectat least a subset of the composition, structure and function oflarger systems, and these experimental units should mimic bio-logical and physical-chemical processes that occur in the field.Although results from such an approach are conservative, theirtentative value lies in alerting management and providing abasis for future research, especially for wetlands that have beenpoorly studied previously (as the wetlands in the Campo deCalatrava).

Our analyses were able to identify patterns in changing levelsof β diversity in the agricultural temporary wetland complex ofthe Campo de Calatrava. We also identified high-diversity pondsand depauperate ponds in the nestedness analyses that allow forsetting management priorities for regional biodiversity conser-vation in this area. It is surprising that many apparently degradedsites (Garbanzos, Nava Enmedio and Cañada ponds) that sufferfrom different types of visual impact (cattle grazing, croplandencroachment, infrastructure construction) bear the most speciesrich communities in both their microinvertebrate resting eggand macrophyte seed bank. Although these results are encour-aging because they suggest that wetland propagule banks can beresilient to anthropogenic stress, they also highlight that currentmanagement and conservation practices, based on aesthetic val-ues of wetlands and selected target vertebrate and plant species,are suboptimal for integrative biodiversity conservation. Giventhat many wildlife species depend on the structural and func-tional properties of propagule banks (e.g. food supply, habitatprovision, mating, nesting and foraging ground) once wetlandsrewet, conservation of the hidden biodiversity of temporaryponds will not only be crucial for conserving regional diver-sity but also for providing ecosystem services to wildlife andhumans in agriculturally heavily exploited landscapes.

AcknowledgementsWe acknowledge the land holders for permitting access to their proper-ties, and B. Sánchez and M. Gutiérrez for help with field and laboratorywork. Andrew Boulton and two anonymous referees provided construc-tive criticisms that helped improve the final paper. The present study wasfunded jointly by Junta de Comunidades de Castilla – La Mancha andEuropean Community funds for regional development (FEDER) throughthe HUMACRO (PAI-05–020) project.

Beta diversity in dry soils Marine and Freshwater Research 427

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Manuscript received 31 October 2007, accepted 5 April 2008