differences in trait compositions between rocky natural and artificial habitats
TRANSCRIPT
Differences in trait compositions between rocky natural and
artificial habitats
Zdenka Lososova & Deana Lanıkova
AbstractQuestion: What are the differences in trait composi-tions that enable native plants to colonisecomparable natural and man-made habitats? Arethese traits independent of phylogenetic relation-ships between species?Location: Czech Republic.Methods: The relative importance of biological,ecological and distributional traits of native specieswas studied, using a dataset of 75 species growing inrock and wall habitats in the Czech Republic.Species preferences for individual habitats due toclimatic conditions and proportions of differentvegetation types in their surroundings were par-tialled out using partial canonical correspondenceanalysis. The pattern of plant traits along a gradientfrom natural rock habitats to secondary wall habi-tats was analysed using regression trees andgeneralized linear models with and without phylo-genetic correction.Results: The most common native species colonis-ing rock habitats are phanerophytes, mostly woodyjuveniles, with a CSR life strategy and most areadapted to epizoochory. Summer green leaves, an-nual life span, CR life strategy, reproduction mostlyby seeds and dispersal by ants are all traits positivelyassociated with the ability of species to colonise wallhabitats. These species are also characterised bytheir high demand for nutrients, temperature, base-rich substrates and light. Biological and ecologicaltraits are more important for colonising new habi-tats than traits related to species dispersal ability orphylogenetic relationships between species. Biologi-cal and ecological traits alone explained 29.3% of
variability in the species dataset, while dispersalcharacteristics and phylogeny alone explained 9.1%and 4.8%, respectively.Conclusions: We outline how the process of envir-onmental filtering determines native speciesassemblages and identify a set of species traits thatenable them to persist in particular habitats. Weconclude that although urbanisation generally re-sults in loss of natural habitats, there are new, man-made habitats potentially suitable for native species.
Keywords: BiolFlor; Czech Republic; Ellenberg in-dicator values; pCCA; Phylogeny; Regression treemodel; Rock; Wall.
Nomenclature: Kubat et al. (2002)
Introduction
Human activity has resulted in huge environ-mental changes in the Central European landscapeand in the creation of a great variety of new habitattypes (Brandes 1983; Kowarik 1990; Sukopp et al.1995; Wittig 2002; Godefroid & Koedam 2007).These habitats provide secondary niches for manyplant species in the urban environment. In general,urbanisation is a process that changes flora througha series of filters, which influence habitat avail-ability, the spatial arrangement of habitats, the poolof plant species and the evolutionary selection pres-sures on populations persisting in urbanised areas(Williams et al. 2009).
Urban areas provide various habitats for nat-ural vegetation (Ricotta et al. 2001; Kuhn et al.2004a; Celesti Grapow et al. 2006). Walls are acharacteristic habitat found in human settlementsand their surroundings. These habitats have a highlyheterogeneous flora composed partly of native spe-cies assembled from different habitats, e.g. rocks(Brandes 1992a; Ellenberg 1996; Larson et al. 2000;Wittig 2002), and partly of alien species (Woodell &Rossiter 1959; Holland 1972; Lisci & Pacini 1993;Simonova 2008; Lanıkova & Lososova 2009). Thisis why high floristic diversity is typical for wall ha-bitats (Brandes 1992b; Kolbek 1997; Lanıkova &Lososova 2009).
Lososova, Z. (corresponding author, lososova@
ped.muni.cz): Department of Biology, Faculty of Edu-
cation, Masaryk University, Porıcı 7, CZ-603 00 Brno,
Czech Republic
Lososova, Z. & Lanıkova, D.: Department of Botany
and Zoology, Faculty of Science, Masaryk University,
Kotlarska 2, CZ-611 37 Brno, Czech Republic
Lanıkova, D. ([email protected]): Institute of Bot-
any, Academy of Sciences of the Czech Republic,
Department of Vegetation Ecology, Porıcı 3b,
CZ-60300 Brno, Czech Republic.
Journal of Vegetation Science 21: 520–530, 2010DOI: 10.1111/j.1654-1103.2009.01160.x& 2010 International Association for Vegetation Science
Plant traits vary among species occupying simi-lar habitats. We present a trait-based approach thatprovides an understanding of the general processesthat cause variation in species diversity. There areseveral core frameworks for studying general pro-cesses that regulate the diversity of species traits in acommunity. The trait-based habitat filtering com-munity assembly theory suggests that two processesaffect the structure of trait values within commu-nities: competition and habitat filtering (see Palmer1994; Zobel 1997; Huston 1999; Wright 2002).Within a local community, competition leads toecological differentiation of coexisting species, whilehabitat filtering reduces the spread of trait values,reflecting shared ecological tolerances. Many recentstudies deal with the development of predictivemethods for detecting plant traits potentially sui-table for colonisation of new habitats. Such studieshave focused mainly on alien species (e.g. Pyseket al. 1995; Pysek & Richardson 2007; Kuster et al.2008; Simonova 2008) or have compared traits ofspecies of different man-made habitats (e.g. Loso-sova et al. 2006, 2008).
It is generally known that some plant traits arefavoured by urban environments, and this has beendocumented in some studies dealing with the com-parison of species traits of flora between urban andopen rural landscapes (Lososova et al. 2006; God-efroid & Koedam 2007; Knapp et al. 2008b;Thompson &McCarthy 2008). Knapp et al. (2008b)and Thompson &McCarthy (2008) showed that theprocess of urbanisation completely changed the traitstate composition of plant assemblages compared toflora of rural landscapes, and resulted in homo-genisation of flora with respect to trait statefrequency. Lososova et al. (2006) and Godefroid &Koedam (2007) demonstrated the importance of ahigh demands for nutrients and light in speciesgrowing in urban areas. Comparing annual weedand ruderal vegetation, Lososova et al. (2006) foundthat annual vegetation of ruderal habitats is com-posed in particular of competitors: wind-pollinatedspecies reproducing both vegetatively and by seedsand dispersed mainly by man or wind. However, it isdifficult to generalise such results because of thedifferent conceptual and methodological ap-proaches that have been employed. The majorityof these studies are based on floristic data, compar-ing areas with many habitats with differentenvironmental conditions, successional stages ordisturbance regimes (Pysek & Richardson 2007;Knapp et al. 2008a, b; Kuster et al. 2008).
Some differences in trait state composition ofplant assemblages between two similar habitats can
be a result of the fact that some groups of phylo-genetically related species share the same traits dueto their common evolutionary history (Harvey &Pagel 1991; Losos 1996; Prinzing et al. 2001). Omit-ting phylogenetic information can lead to vagueinterpretations (Westoby et al. 1995; Valladareset al. 2008). Thus, discriminating between the effectof habitat filtering and the phylogenetic structure ofthe community gives us an opportunity to determinethe major ecological processes in community struc-turing and to estimate the relative effect ofphylogenetic relationships in community speciescomposition (Webb et al. 2002).
The present study focuses on habitats occurringboth in open landscapes and in urbanised areas. Ourgoal is to find traits of native species associated withsurvival either in open landscapes or in fragmentedurbanised areas. We have chosen two analogoushabitat types (walls and rocks) to compare patternsin the species traits of their native flora. We assumethat environmental conditions of secondary wallhabitats are different from natural rock habitats;therefore, they can act as different sets of filters, re-sulting in species assemblages characterised bysuitable trait combinations.
Material and Methods
Dataset compilation
We have compiled a dataset of vegetation plotsrecorded on walls and rocks occurring in the CzechRepublic. We have chosen only vegetation plots re-corded on vertical surfaces of walls and rocks; onlythose with slopes of above 751 were chosen. Thisdataset includes unpublished vegetation plots(mainly from D. Lanıkova) and also publishedplots, both of which are stored in the Czech Na-tional Phytosociological Database (Chytry &Rafajova 2003). All the plots were recorded between1967 and 2006. The dataset includes 1205 vegetationplots (381 plots on rocks and 824 plots on walls),with 581 species of vascular plants. For our study,we deleted all records of bryophytes and lichensfrom the dataset, because they were not consistentlyrecorded in all plots. Plot size ranged from 0.2 to100m2.
Using detrended correspondence analysis(DCA) in the CANOCO program (ter Braak &Smilauer 2002), we detected and removed two plotswith deviating floristic composition. Rare speciesoccurring in less than 1% of plots (i.e. o12plots) were excluded from the dataset. After these
Differences in traits of rocky natural and artificial habitats 521
procedures, the dataset consisted of 1205 plots with380 species of native plants.
We characterised each plot from the dataset bya set of environmental variables supposed to affectthe species composition of the studied vegetation(Lanıkova & Lososova 2009). Using a digital eleva-tion model and climatic maps based on Veseckyet al. (1958) in ArcGIS 8.3 program (http://www.esri.com), we obtained variables that were used forthe next analyses (Table 1). Other explanatory vari-ables were slope (1) and habitat type, with twocategories: walls and rocks. Original species covervalues were transformed to percentages and square-root transformed. To edit the dataset the softwareJUICE, version 7 (Tichy 2002), was used.
Biological, ecological and distributional traits ofspecies
For the next analysis, we chose traits that weexpected to respond to different site conditions inthe habitat types studied. Information about speciestraits was mostly adapted from the BiolFlor data-base (Klotz et al. 2002; Kuhn et al. 2004b). Data ondispersal of species were obtained from Frank &Klotz (1990). Data on seed mass were obtained fromthe BIOPOP database (Poschlod et al. 2003). Ellen-berg indicator values (Ellenberg et al. 1992) wereassigned to each species. Some species were assignedto more than one category of the same categoricaltrait (e.g. Cerastium arvense was treated as both in-sect- and self-pollinated). Each category of the sametrait was used as a separate trait in the analyses.Traits used are shown in Table 2.
Table 1. Set of environmental variables used for the char-acterisation of each plot in the Czech Republic. Theireffect on changes in species composition of the two com-pared vegetation types was later partialled out by pCCA.
Variable Min–max
Altitude 145-878mMean annual rainfall 450-1000mm/yearMean annual temperature 4-91CMean January temperature � 5-01CMean July temperature 12-171CPercentage cover of land-use categories in a
radius of 0.5 km from the sampling site(a) Arable land 0-100%(b) Ruderal areas – including mines,deposits and traffic infrastructure
0-100%
(c) Grasslands 0-100%(d) Forests – incl. coniferous, deciduousand mixed forests
0-100%
Distance from the closest settlement 0-6.5 km
Table 2. Traits used to explain the propensity of nativespecies to colonise either natural rock or secondary wallhabitat in the Czech Republic. Information on speciestraits was mostly adopted from the BiolFlor database(Klotz et al. 2002; Kuhn et al. 2004b). Data on dispersalof species were obtained from Frank &Klotz (1990). Dataon seed mass were obtained from the BIOPOP database(Poschlod et al. 2003). Ellenberg indicator values(Ellenberg et al. 1992) were assigned to each species.Categories of traits present in only five or less species werenot used in the analyses. Number of cases for each of thecategorical traits are given.
Trait Category Number ofcases
Traits related with speciesregeneration ability afterdisturbancesLife span Annual 7
Biennial 4Perennial 68
Life form Chamaephyte 10Geophyte 9Hemicryptophyte 59Phanerophyte 6Therophyte 7
Life strategy Competitor 15Competitor/ruderal 5Competitor/stress tolerator 17Competitor/stress tolerator/
ruderal32
Ruderal 2Ruderal/stress tolerator 0Stress tolerator 0
Type of reproduction By seeds 39By seeds and vegetatively 33Vegetatively 2
Traits related withmicroclimatic and soil/productivitydifferences between studied habitatsLeaf persistence Spring green 0
Summer green 35Overwintering green 3Persistent green 34
Leaf anatomy Helomorphic 1Hygromorphic 16Mesomorphic 52Scleromorphic 30Succulent 4
Ellenberg indicatorvalues
LightTemperatureContinentalityMoistureSoil reactionNutrients
Traits related withspecies dispersal abilityPollination mode Anemogamy 22
Entomogamy 47Autogamy 31
Dispersal type Anemochory 62Hemerochory 1Myrmecochory 13Epizoochory 32Endozoochory 10Autochory 16
Seed massNumber ofgeographical zones
1-9 zones
522 Lososova, Z. & Lanıkova, D.
Ordination
We used DCA in the CANOCO program ver-sion 4.5 (ter Braak & Smilauer 2002) to characterisethe general pattern in variation of species composi-tion within the studied vegetation. The above-characterised environmental variables werepassively projected onto the ordination diagram.Their effect on changes in species composition in thedataset of vegetation plots was tested using canoni-cal correspondence analysis (CCA) with MonteCarlo permutation tests (999 permutations). In or-der to rank species according to their affinity tosecondary wall or natural rock habitats, we per-formed a partial canonical correspondence analysis(pCCA), with habitat type as the single environ-mental variable and all the other significantexplanatory variables used as co-variables. We ap-plied this method to partial out the effect of theimportant environmental variables and, conse-quently, to study the pure effect of habitat type onspecies composition.
Regression tree models
To identify which traits are the most importanteither for life in natural rock habitats or in urbanwall habitats, we used regression tree models (Brei-man et al. 1984) in the STATISTICA program,version 8 (http://www.statsoft.com). We related thespecies scores on the first axis of the pCCA as thedependent variable, and a set of biological, ecologi-cal and distributional traits as predictors. To reducenoise, we used only species whose fit on the firstpCCA axis was at least as high as the median. Insuch a way, only 75 native species were used fromthe initial list of 380 for further analyses, each ofthem being characterised by a set of biological, eco-logical and distributional traits (Table 2).
We used regression tree models because theyenabled us to find complex interactions betweenspecies traits as predictors. Regression tree modelsexplained the variation of the dependent variable(wall/rock affinity expressed as scores on the firstaxis of the pCCA) by hierarchical splitting of thedataset into more homogeneous groups (nodes)based on particular predictors (traits) and theirinteractions. In each split, the dataset was dividedinto two groups. At each node of the tree, besidesthe splitter predictor, surrogate variables were iden-tified. They were predictors that can separate casesin a similar way to the particular main splitter vari-able. In this study, only those variables whoseassociated value with respect to the splitter variable
was 40.3 were considered as surrogates of thesplitter variable.
To select optimal tree size, we applied a 10-foldcross-validation method with the SE5 0 rule(Breiman et al. 1984). The cross-validation proce-dure suggests the optimal tree that appears stableand valid. We calculated the total variance ex-plained by the best single regression tree as: R2 5 1� (resubstitution relative error). Each of the pre-dictors used in the model contributes to a differentextent to the explained variation in the dependentvariable. The influence of particular predictors canbe evaluated by the relative importance values, withthe best explanatory variable having a value of 100and the others being scored relative to the best vari-able on a scale from 0 to 100. The relativeimportance value reflects the contribution of eachvariable, stemming both from its role as a primarysplitter variable and as a surrogate across all bran-ches of the tree.
Only those categorical traits that occurred inmore than five species were used for the analyses (seeDataset compilation). Missing Ellenberg indicatorvalues for some species were replaced by the meanvalues for particular factors.
Phylogeny
We consider that the species data are not in-dependent (Harvey & Pagel 1991; Rohlf 2001), andassume that closely related species are often morealike and tend to be confined to the same habitatsdue to their common evolutionary history. There-fore we used the method of Desdevises et al. (2003)to separate variation in our dataset determined byphylogeny, and variation determined purely by spe-cies traits filtered by the environment.
Species phylogeny available in the BiolFlor da-tabase was used (Klotz et al. 2002; Kuhn et al.2004b). The patristic distance matrix among specieswas calculated with all branch lengths set as equalunits (Prinzing et al. 2001).
We subjected the patristic distance matrix toprincipal coordinate analysis (PCoA). We includedeight principal coordinates explaining more than85% of variability in the species dataset to multipleregressions to identify the part of the variation ex-plained strictly by traits, the part explained strictlyby phylogeny and the part explained by a combina-tion of the two. PCoA was performed within R(R Development Core Team 2004; see Appendix toLososova et al. 2008), regression models were cal-culated using STATISTICA version 8 (http://www.statsoft.com).
Differences in traits of rocky natural and artificial habitats 523
Results
The relationship between compared habitattypes, namely natural rocks and artificial walls, andenvironmental factors is depicted in a DCA ordina-tion diagram (Fig. 1). The first ordination axisexplains 3.7% of the total variation in species dataand is associated mainly with the studied habitattypes and particular categories of land use in theirsurroundings. Wall habitats sampled are situatedmainly in urbanised landscapes, unlike rocks, whichare located at some distance from settlements andsurrounded by natural or semi-natural vegetation.The second ordination axis explains 2.7% of thevariability and corresponds to the climatic factorsand altitudinal gradient. To eliminate the effect ofthe different locations of walls and rocks, and con-sequent diverse influence of environmental factors,we partialled out all these variables (Fig. 1) usingpartial CCA. As a result, we obtained the net effectassociated with the two habitat types.
The most typical native species occurring in thestudied habitats are shown in Table 3. To reveal thepattern of species traits in native flora colonisingsecondary wall habitats, regression tree analysis wasapplied. Sets of particular traits were used as pre-dictors in regression tree models and their relativeimportance values were counted (Table 4).
The optimal regression tree calculated for nativespecies was divided into two nodes and explained
36.9% of variability in the dataset (Fig. 2). The da-taset of 75 native species was divided basically intotwo main groups based on ecological characteristicsof species. Native species with higher affinity forwall habitats are relatively more nutrient- andmoisture-demanding (split values 5.5 and 4). Withinthe regression tree analysis, relative importance va-lues of particular traits were counted (Table 4).Several biological traits seem to be important forspecies, differentiating between natural rocks andsecondary walls, especially: life span, type of leafpersistence and, to some extent, life strategy. Re-garding types of life strategy, secondary wallhabitats are colonised mainly by CR strategists (e.g.C. arvense, Stellaria media), while on natural rocks,plants with a CSR life strategy (e.g. Alliumsenescens, Asplenium cuneifolium, A. septentrionale,Biscutella laevigata) and also C strategists (e.g.woody juveniles – Acer platanoides, Betula pendula)occur more often. Species with annual life spansprevail on wall habitats. These species commonlyreproduce by seeds and most have relatively bigseeds that are dispersed by ants (e.g. Glechomahederacea).
0 12
10
–2
slope
altitude
temperature July
temperature January
precipitation
distance urban
0.5 km forest0.5 km grassland
0.5 km arable field
0.5 km ruderal stand
ROCKWALL
Fig. 1. Detrended correspondence analysis (DCA) of walland rock vegetation with passively projected environ-mental variables. Eigenvalues: first axis – 0.73, secondaxis – 0.52.
Table 3. Native species with the highest fit in the partialcanonical correspondence analysis (pCCA) and theirscores along the first ordination axis. The pCCA withhabitat type as the single environmental variable and allother significant explanatory variables (see Table 1) usedas co-variables was performed. Species with positivescores have high affinity to natural rock habitats, andspecies with the negative scores have high affinity tosecondary wall habitats.
Taxon Score Fit
Asplenium cuneifolium 2.56 0.019Jovibarba globifera subsp. globifera 2.52 0.023Festuca ovina 2.50 0.041Avenella flexuosa 2.40 0.021Allium senescens subsp. montanum 2.38 0.043Asplenium septentrionale 2.34 0.041Hieracium schmidtii 2.04 0.024Sesleria caerulea 2.02 0.036Seseli osseum 1.99 0.028Polypodium vulgare s. l. 1.88 0.037Rumex acetosella 1.86 0.022Bupleurum falcatum 1.84 0.020Vincetoxicum hirundinaria 1.69 0.020Festuca pallens 1.49 0.033Aurinia saxatilis subsp. arduini 1.29 0.023Taraxacum sect. Ruderalia � 0.65 0.035Elytrigia repens � 0.93 0.007Asplenium ruta-muraria � 1.06 0.028Urtica dioica � 1.32 0.021Epilobium montanum � 1.48 0.014Cystopteris fragilis � 1.59 0.029Glechoma hederacea � 1.72 0.012Anthriscus sylvestris � 1.81 0.012
524 Lososova, Z. & Lanıkova, D.
To characterise ecological requirements of spe-cies, Ellenberg indicator values were used. The mostimportant traits of native species colonising wallsare their relatively high demand for light, tempera-ture, and nutrient content. They are alsocharacterised by higher demand for moisture and
soil reaction compared to native species typical ofnatural rock habitats.
Some biological traits, especially pollinationmode and dispersal type, were strongly influencedby phylogeny (Table 4). However, these traits werenot as important for colonising the two habitats (but
Table 4. Biological, ecological and distributional traits of species used for regression tree models. The relative importance inregression tree models and the proportion of explained variability by phylogeny for each trait are given. The first columnincludes an abbreviation indicating the relationship between species trait and affinity to either rock (R) or wall (W) habitats.Numbers in the second column are values of relative importance, which are scaled from 0 to 100. These are related to theoptimal regression tree, in which species traits were used as predictors, and species scores on the first ordination axis inpCCA were used as dependent variables. The last column shows the percentage variation of each trait explained byphylogeny. A set of linear regressions was used. n.s., not significant.
Trait Category Rock/wallaffinity
Relativeimportance
Percentage variationexplained by phylogeny
Traits related to species regeneration ability after disturbancesLife span Annual W 28 9.8
Biennial – –Perennial R 9 4.2
Life form Chamaephyte R 8 17.4Geophyte R 4 n.s.Hemicryptophyte W 6 18Phanerophyte R 27 n.s.Therophyte W 22 6.8
Life strategy Competitor R 9 4Competitor/ruderal W 15 12Competitor/stress tolerator R 7 10.7Competitor/stress tolerator/ruderal R 14 6.1Ruderal – –Ruderal/stress tolerator – –Stress tolerator – –
Type of reproduction By seeds W 13 14.3By seeds and vegetatively R 4 7.7Vegetatively – –
Traits related to microclimatic and soil/productivity differences between the studied habitatsLeaf persistence Spring green – –
Summer green W 54 n.s.Overwintering green – –Persistent green R 1 n.s.
Leaf anatomy Helomorphic – –Hygromorphic W 1 6.1Mesomorphic W 5 11.9Scleromorphic R 2 n.s.Succulent – –
Ellenberg indicator values Light W 38 6.1Temperature W 39 6.7Continentality W 10 4.1Moisture W 28 10.4Soil reaction W 43 4.8Nutrients W 100 7
Traits related to species dispersal abilityPollination mode Anemogamy R 2 49.7
Entomogamy W 2 70.2Autogamy W 2 21.4
Dispersal type Anemochory R 2 14.7Hemerochory – –Myrmecochory W 51 21.2Epizoochory R 13 62Endozoochory W 0 22.7Autochory R 2 n.s.
Seed mass W 33 n.s.Number of geographic zones 1-9 zones W 2 n.s.Total variability explained 36.9%
Differences in traits of rocky natural and artificial habitats 525
see importance of myrmecochory for spread of spe-cies to wall habitats) as were ecological traits thatwere only poorly influenced by phylogeny.
Multiple regressions explained 72% of the totalvariation in our dataset (Fig. 3). The greatest part ofthis variation can be explained by a set of biologicaland ecological traits (29.3%). Only small parts ofthe total variation can be explained by distributionalcharacteristics or by phylogeny.
Discussion
Factors determining changes in species composition
As has been shown in several previous studies,the effect of land use filters the available regionalspecies pool to create the local species pool (Zobel1997; Roy et al. 1999; Ricotta et al. 2008; Williamset al. 2009). Processes of environmental filteringdetermine the composition of species that are able to
persist in particular habitats on the basis of theirtolerance to the abiotic and biotic factors. In ouranalysis, we eliminated the effect of climate and theinfluence of land use in the surroundings to obtainthe net effect of habitat types and, subsequently, toreveal the characteristic traits of native speciescolonising either natural rock or secondary wall ha-bitats. We have, in any case, to assume that manyother factors exist that also have a potential influ-ence on the floristic composition of the studiedhabitats (e.g. human impact, environmental pollu-tion, biotic interactions). Such factors are, however,very difficult to detect. In settlements, walls might beexposed to various human activities such as renova-tions and wall surface cleaning, or the intentionalplanting of some plants in these habitats. Moreover,different urban land-use types considerablyinfluence the selection of species assemblages(Godefroid & Koedam 2007); individual filters re-present selection pressures, which can lead todifferent distribution of plant traits and changes tothe phylogenetic distribution of species within dif-ferent types of built-up area. Generally, the selectivepressures affecting the species composition arestronger in the most densely urbanised areas (e.g.city centres) (Williams et al. 2009).
Analysing secondary wall habitats, we shouldalso consider that the wall flora is generally veryheterogeneous in its species composition and hashigh beta diversity (Kolbek 1997; Lanıkova &Lososova 2009). Nevertheless, many species occuron walls only accidentally and temporarily (Segal1969; Kolbek 1997; Duchoslav 2002; Prochazkova& Duchoslav 2004; Lanıkova & Lososova 2009). Asin natural habitats, characteristic combinations ofspecies could also be found under sets of similarconditions in man-made habitats (Sukopp 1990).Our study has revealed that the traits of native spe-cies able to occupy wall habitats are quite narrow.
Biological traits and ecological requirements of nativespecies
As previously shown, the shift of native speciesfrom their natural habitats to secondary habitats isconsiderably determined by local environmentalconditions in a newly colonised habitat, and onlypartially by traits associated with species dispersalability or phylogenetic relationships of species. Sev-eral distinct patterns in the species traits of nativespecies were revealed in the present study. Speciesdemanding a high input of nutrients, light, tem-perature and base-rich soils are successful colonisersof walls. This is not surprising, considering the
n = 75
n = 51 n = 24
≤ 5.5 nutrients requirement > 5.5
≤ 4 moisture requirement > 4
wall affinityrock affinity R = 36.9%
Fig. 2. Optimal regression tree model calculated for nativespecies. Species scores on the first ordination axis in pCCAare used as dependent variable. Biological and ecologicalspecies traits, and traits associated with dispersal ability ofspecies determining spread of species to secondary wallhabitats are used as predictors. Nodes are characterised bythe primary splitter variable and its split value (n5
number of species assigned to the node). The tree explains36.9% of the variability in the dataset.
29.3% 4.8%
9.1%
24% 0%
7.9%
0%
total explained 72% biological andecological traits
dispersal ability
phylogeny
Fig. 3. Explained variability based on a set of multiplelinear regressions with species score as dependent variableand biological and ecological traits, traits associated withdispersal ability of species and phylogenetic axes as pre-dictors.
526 Lososova, Z. & Lanıkova, D.
enrichment of wall habitats by nutrients from thesurrounding urbanised environments (nutrient-richdust, nitrogen and phosphorus in water and soil,and the activities of animals) into account. Con-versely, the generally low productivity of naturalrock habitats selects for species that are tolerant oflow resource supply (Larson et al. 2000), and rocksurfaces are colonised mainly by oligotrophic plantspecies. In comparison with rocks, walls (especiallytheir vertical surfaces) also seem to be relatively fa-vourable for plants in terms of moisture conditions.
Although the effect of climate was partialled outin the dataset, our results have shown that morethermophilous species are associated with walls.This may be due the fact that walls are locatedmainly in settlements, which act as heat islands inopen landscapes (Sukopp & Werner 1983; Sukopp& Wittig 1998; Wittig 2002) or due to the local con-ditions of individual walls and rocks.
Regarding the pH demands of species, calciphi-lous native species prevail on walls. A characteristicfeature of most of the studied walls is the presence ofcalcareous mortar. It is generally known that urbanareas favour plants adapted to base-rich soils(e.g. Chocholouskova & Pysek 2003; Godefroid &Koedam 2007; Thompson & McCarthy 2008) andthe local pool of these species can be important intheir spread in wall habitats. Compared to walls, onrocks there are specific species groups colonisingdifferent bedrock types that include species at bothextremes of the pH range.
Besides local ecological conditions, traits thatare necessary for regeneration after disturbancesduring the colonisation of secondary habitats play aless important role for native species. Our data areconsistent with other studies, which have concludedthat walls host many annual species (Segal 1969;Larson et al. 2000; Duchoslav 2002). Nevertheless,in total, only a small number of annual species waspresent in the analysed dataset. In terms of Grime’sCSR model of plant strategies (Grime 2001), wallsseem to represent mainly competitive or ruderal ha-bitats, while rocks are rather stressed habitats. Wallsare generally regarded as disturbed habitats, whichmight be expected to favour plants with a ruderalstrategy and low competitive ability. However, inour dataset, various kinds of wall differing in ecolo-gical conditions (e.g. Brandes 1992a; Lisci & Pacini1993; Duchoslav 2002; Simonova 2008; Lanıkova &Lososova 2009) were included. This fact con-siderably influences the representation of plant lifestrategies found in wall habitats. Retaining walls inparticular might have relatively constant and fa-vourable conditions with limited disturbances,
which allow the persistence of CR strategists, incomparison with the often drought-affected anddisturbed surrounding urban environment. Thesenative species are mainly common ruderal plants ofmesic habitats. In natural rock habitats, juvenileshrubs and trees and CSR strategists with an inter-mediate life strategy prevail among native species.On the rock surface the local conditions of each mi-crosite play a more important role than competitionwith other species; the competitive ability of speciesdecreases in this context (Larson et al. 2000).
On walls, a high proportion of alien species isgenerally represented (Simonova 2008; Lanıkova2009; Lanıkova & Lososova 2009). Nevertheless,these species usually have only accidental occur-rences and colonise walls only temporarily, whileamong established species occurring on these habi-tats with high constancy, mainly native speciesprevail. In comparison with other man-made habi-tats (e.g. rubbish dumps and various ruderal sites insettlements), walls are relatively permanent second-ary habitats (Roy et al. 1999) and seem to beimportant sites for native flora in fragmented urba-nised areas.
Dispersal ability of native species
We showed that traits related to the dispersalability of native species are less important than eco-logical and biological traits. In spite of the fact thatwalls are situated mainly in settlements and are sur-rounded by other secondary habitats, we found nopreference for long-distance dispersal traits inspecies occurring on walls (Table 2). However,species occupying walls, similar to species in otherman-made habitats located in urban areas, might bepreferentially dispersed by human activities (Hod-kinson & Thompson 1997; Thompson & McCarthy2008; Williams et al. 2009), spreading either fromsurrounding habitats or being deliberately plantedon the wall tops (Simonova 2008; Lanıkova & Lo-sosova 2009). Nevertheless, one of the mostimportant roles in plant dispersal in wall habitats isplayed by myrmecochory. Many plant speciesgrowing in the vicinity of a wall (i.e. within a rangeof several metres) are dispersed by ants, which arealso able to disperse relatively heavy, large seeds di-rectly into wall fissures. In contrast to walls, rocksurfaces are colonised mainly by species with lightseeds. On the other hand, the two compared habitatsrepresent isolated habitat islands, being scarcelydistributed in the landscape, and are successfullyoccupied by wind-dispersed species (Lisci & Pacini1993; Larson et al. 2000; Duchoslav 2002). In our
Differences in traits of rocky natural and artificial habitats 527
dataset, 83% of species are wind dispersed and only17% prefer other dispersal modes. These findingsconfirm the results of Ozinga et al. (2009) andKnapp et al. (2009) that fragmented areas harbourmainly long-distance dispersed species. It is knownthat long-distance dispersal is an important trait forspecies colonising new habitats, e.g. for invasiveplants (e.g. Rejmanek & Richardson 1996; Pysek etal. 2002; Davis 2005; Gasso et al. 2009).
Effect of phylogeny
Our data suggest that traits determining plantaffinity to natural or man-made habitats are mainlyinfluenced by their adaptations to these habitats.However, some important traits are related to phy-logenetic relatedness among species. High demandsfor moisture and nutrients are determined by phylo-genetic relationships of species, while the influence ofsoil pH is more determined by habitat preference ofspecies, independent of phylogenetic relationships.
Conclusion
In conclusion, urbanisation generally results inloss of natural habitats on the one hand (McKinney2006; Williams et al. 2009), but on the other hand, increation of new habitats in urbanised areas that arepotentially suitable for native plants. By analysing na-tive plant trait distributions in comparable natural andman-made habitat types, we revealed traits that enableplants to persist in natural or man-made habitats.Species preferring secondary wall habitats are annualplants with summer-green leaves adapted to nutrient-rich, warm, sunny and base-rich habitats, and are dis-persed by ants. These findings contribute to a betterunderstanding of the process of synantropization ofnative flora and its adaptations to new environments.
Acknowledgements. We thank Jitka Klimesova for help
with dataset compilation and Milan Chytry for comments
on an earlier version of this manuscript. This work was
funded by the Long-term Research Plan MSM
0021622416 from the Ministry of Education of the Czech
Republic, and by grant IAA 601630803 from the Czech
Academy of Sciences.
References
Anon. (R Development Core Team) 2004. R: a language
and environment for statistical computing. R
Foundation for Statistical Computing.
Brandes, D. 1983. Stadtvegetation als Unterrichtsgegen-
stand. Praxis der Naturwissenschaften, Biologie 32:
35–55.
Brandes, D. 1992a. Asplenietea-Gesellschaften an
sekundaren Standorten in Mitteleuropa. Berichte der
Reinhold-Tuxen-Gesellschaft 4: 73–93.
Brandes, D. 1992b. Flora und Vegetation von
Stadtmauern. Tuexenia 12: 315–339.
Breiman, L., Friedman, J.H., Olshen, R.A. & Stone, C.G.
1984. Classification and regression trees. Wadsworth
International Group, Belmont, CA, US.
Celesti-Grapow, L., Pysek, P., Jarosık, V. & Blasi, C.
2006. Determinants of native and alien species richness
in the urban flora of Rome. Diversity and Distributions
12: 490–501.
Chocholouskova, Z. & Pysek, P. 2003. Changes in
composition and structure of urban flora over 120
years: a case study of the city Plzen. Flora 198:
366–376.
Chytry, M. & Rafajova, M. 2003. Czech National
Phytosociological Database: basic statistics of the
available vegetation-plot data. Preslia 75: 1–15.
Davis, M.A. 2005. Invasion biology. Oxford University
Press, Oxford, UK.
Desdevises, Y., Legendre, P., Azouzi, L. & Morand, S.
2003. Quantifying phylogenetically structured
environmental variations. Evolution 57: 2647–2652.
Duchoslav, M. 2002. Flora and vegetation of stony
walls in east Bohemia Czech Republic. Preslia 74:
1–25.
Ellenberg, H. 1996. Vegetation Mitteleuropas mit den
Alpen in okologischer, dynamischer und historischer
Sicht. 5th Ed. Verlag Eugen Ulmer, Stuttgart, DE.
Ellenberg, H., Weber, H.E., Dull, R., Wirth, W., Werner,
W. & Pauli�en, D. 1992. Zeigerwerte von Pflanzen
in Mitteleuropa. Ed. 2. Scripta Geobotanica 18:
1–258.
Frank, D. &Klotz, S. 1990. Biologisch-okologische Daten
zur Flora der DDR. 2nd edition. Wissenschaftliche
Beitrage der Martin Luther Universitat Halle-
Wittenberg 41: 1–167.
Gasso, N., Sol, D., Pino, J., Dana, E.D., Lloret, F., Sanz-
Elorza, M., Sobrino, E. & Vila, M. 2009. Exploring
species attributes and site characteristics to assess
plant invasions in Spain. Diversity and Distributions
15: 50–58.
Godefroid, S. & Koedam, N. 2007. Urban plant species
patterns are highly driven by density and function of
built-up areas. Landscape Ecology 22: 1227–1239.
Grime, J.P. 2001. Plant strategies, vegetation processes,
and ecosystem properties. John Wiley & Sons,
Chichester, UK.
Harvey, P.H. & Pagel, M.D. 1991. The comparative
method in evolutionary biology. Oxford University
Press, Oxford, UK.
Hodkinson, D.J. & Thompson, K. 1997. Plant dispersal:
the role of man. Journal of Applied Ecology 34:
1484–1496.
528 Lososova, Z. & Lanıkova, D.
Holland, P.G. 1972. The pattern of species density of old
stone walls in western Ireland. Journal of Ecology 3:
799–805.
Huston, M.A. 1999. Local processes and regional
patterns: appropriate scales for understanding
variation in the diversity of plants and animals. Oikos
86: 393–401.
Klotz, S., Kuhn, I. & Durka, W. 2002. BIOLFLOR – Eine
Datenbank mit biologisch-okologischen Merkmalen
zur Flora von Deutschland. Schriftenreihe fur
Vegetationskunde 38: 1–334.
Knapp, S., Kuhn, I., Schweiger, O. & Klotz, S. 2008a.
Challenging urban species diversity: contrasting
phylogenetic patterns across plant functional groups
in Germany. Ecology Letters 11: 1054–1064.
Knapp, S., Kuhn, I., Wittig, R., Ozinga, W.A., Poschold,
P. & Klotz, S. 2008b. Urbanization causes shifts in
species’ trait state frequencies. Preslia 80: 375–388.
Knapp, S., Kuhn, I., Bakker, J.P., Kleyer, M., Klotz, S.,
Ozinga, W.A., Poschlod, P., Thompson, K., Thuiller,
W. & Rommermann, C. 2009. How species traits and
affinity to urban land use control large-scale species
frequency. Diversity and Distributions 15: 533–546.
Kolbek, J. 1997. Plant communities on walls in the Czech
Republic – preliminary notes. Zpravy Ceske Botanicke
Spoleenosti, Materialy 32: 61–67.
Kowarik, I. 1990. Some responses of flora and vegetation
to urbanization in Central Europe. In: Sukopp, H.,
Hejny, S. & Kowarik, I. (eds.) Urban ecology. pp. 45–
74. SPB Academic Publishing, The Hague, NL.
Kubat, K., Hrouda, L., Chrtek, J. Jr, Kaplan, Z.,
Kirschner, J. & Stıpanek, J. 2002. Klıe ke kvıtenı
Ceske republiky. [Key to the Flora of the Czech
Republic]. Academia, Praha, CZ (in Czech).
Kuhn, I., Brandl, R., May, R. &Klotz, S. 2004a. The flora
of German cities is naturally species rich. Evolutionary
Ecology Research 6: 749–764.
Kuhn, I., Durka, W. & Klotz, S. 2004b. BiolFlor – a new
plant-trait database as a tool for plant invasion
ecology. Diversity and Distributions 10: 363–365.
Kuster, E.C., Kuhn, I., Bruelheide, H. & Klotz, S.
2008. Trait interactions help explain plant invasion
success in the German flora. Journal of Ecology 96:
860–868.
Lanıkova, D. 2009. Neofyty na zdech v Ceske republice.
[Neophytes on walls in the Czech Republic]. Zpravy
Ceske Botanicke Spoleenosti 44: 113–123 (in Czech).
Lanıkova, D. & Lososova, Z. 2009. Rocks and walls:
natural versus secondary habitats. Folia Geobotanica
44: 263–280.
Larson, D.W., Matthes, U. & Kelly, P.E. 2000. Cliff
ecology: pattern and process in cliff ecosystems.
Cambridge University Press, Cambridge, UK.
Lisci, M. & Pacini, E. 1993. Plants growing on the walls
of Italian towns. 1. Sites and Distribution. Phyton 33:
15–26.
Losos, J.B. 1996. Phylogenetic perspectives on community
ecology. Ecology 77: 1344–1354.
Lososova, Z., Chytry, M., Kuhn, I., Hajek, O., Horakova,
V., Pysek, P. & Tichy, L. 2006. Patterns of plant traits
in annual vegetation of man-made habitats in Central
Europe. Perspectives in Plant Ecology, Evolution and
Systematics 8: 69–81.
Lososova, Z., Chytry, M. & Kuhn, I. 2008. Plant
attributes determining the regional abundance of
weeds on central European arable land. Journal of
Biogeography 35: 177–187.
McKinney, M. 2006. Urbanization as a major cause of
biotic homogenization. Biological Conservation 127:
247–260.
Ozinga, W.A., Romermann, Ch., Bekker, R.M., Prinzing,
A., Tamis, W.L.M., Schaminee, J.H.J., Hennekens,
S.M., Thompson, K., Poschlod, P., Kleyer, M.,
Bakker, J.P. & van Groenendael, J.M. 2009.
Dispersal failure contributes to plant losses in NW
Europe. Ecology Letters 12: 66–74.
Palmer, M.W. 1994. Variation in species richness: towards
a unification of hypotheses. Folia Geobotanica
Phytotaxonomica 29: 511–530.
Poschlod, P., Kleyer, M., Jackel, A.-K., Dannemann, A.
& Tackenberg, O. 2003. BIOPOP – A database of
plant traits and Internet application for nature
conservation. Folia Geobotanica 38: 263–271.
Prinzing, A., Durka, W., Klotz, S. & Brandl, R. 2001. The
niche of higher plants: evidence for phylogenetic
conservatism. Proceedings of the Royal Society B –
Biological Sciences 268: 2383–2389.
Prochazkova, K. & Duchoslav, M. 2004. Vegetace
kamennych zdı na strednı Moravı. [Vegetation of
stony walls in central Moravia]. Biosoziologia 2:
34–48 (in Czech).
Pysek, P. & Richardson, D.M. 2007. Traits associated
with invasiveness in alien plants: where do we
stand? In: Nentwig, W. (ed.) Biological invasions. pp.
97–126. Ecological Studies, 193, Springer-Verlag,
Berlin, DE.
Pysek, P., Prach, K. & Smilauer, P. 1995. Relating
invasion success to plant traits: an analysis of the
Czech alien flora. In: Pysek, P., Prach, K., Rejmanek,
M. & Wade, M. (eds.) Plant invasions: general aspects
and special problems. pp. 39–60. SPB Academic
Publishing, Amsterdam, NL.
Pysek, P., Sadlo, J. &Mandak, B. 2002. Catalogue of alien
plants of the Czech Republic. Preslia 74: 97–186.
Rejmanek, M. & Richardson, D.M. 1996. What attributes
make some plant species more invasive? Ecology 77:
1655–1661.
Ricotta, C., Celesti-Grapow, L., Avena, G. & Blasi, C.
2001. Topological analysis of the spatial distribution
of plant species richness across the city of Rome (Italy)
with the echelon approach. Landscape and Urban
Planning 57: 69–76.
Ricotta, C., DiNepi, M., Guglietta, D. & Celesti Grapow,
L. 2008. Exploring taxonomic filtering in urban
environments. Journal of Vegetation Science 19:
229–238.
Differences in traits of rocky natural and artificial habitats 529
Rohlf, F.J. 2001. Comparative methods for the analysis of
continuous variables: geometric interpretations.
Evolution 55: 2143–2160.
Roy, D.B., Hill, M.O. & Rothery, P. 1999. Effects of
urban land cover on the local species pool in Britain.
Ecography 22: 507–515.
Segal, S. 1969. Ecological notes on wall vegetation. Junk
Publishers, The Hague, NL.
Simonova, D. 2008. Alien flora on walls in southern and
western Moravia (Czech Republic). In: Tokarska-
Guzik, B., Brock, J.H., Brundu, G., Child, L., Daehler,
C.C. & Pysek, P. (eds.) Plant invasions: human
perception, ecological impacts and management. pp.
317–332. Backhuys Publishers, Leiden, NL.
Sukopp, H. 1990. Urban ecology and its application in
Europe. In: Sukopp, H., Hejny, S. & Kowarik, I. (eds.)
Urban ecology: plants and plant communities in urban
environments. pp. 2–22. SPB Academic Publishing,
The Hague, NL.
Sukopp, H. & Werner, P. 1983. Urban environments and
vegetation. In: Holzner,W.,Werger,M.J.A. & Ikusima,
I. (eds.) Man’s impact on vegetation. pp. 247–260. Junk
Publishers, The Hague, NL.
Sukopp, H. & Wittig, R. 1998. Stadtokologie. Ein
Fachbuch fur Studium und Praxis. 2. Auflage. Gustav
Fischer Verlag, Stuttgart, DE.
Sukopp, H., Numata, M. & Huber, A. 1995. Urban
ecology as the basis of urban planning. SPB Academic
Publishing, Amsterdam, NL.
ter Braak, C.J.F. & Smilauer, P. 2002. CANOCO
reference manual and CanoDraw for Windows users
guide. Software for Canonical Community Ordination
(version 4.5). Biometris, Wageningen, NL.
Thompson, K. & McCarthy, M.A. 2008. Traits of British
alien and native urban plants. Journal of Ecology 96:
853–859.
Tichy, L. 2002. JUICE, software for vegetation classifi-
cation. Journal of Vegetation Science 13: 451–453.
Valladares, F., Tena, D., Matesanz, S., Bochet, E.,
Balaguer, L., Costa-Tenorio, M., Tormo, J. & Garcıa-
Fayos, P. 2008. Functional traits and phylogeny: what is
the main ecological process determining species
assemblage in roadside plant communities? Journal of
Vegetation Science 19: 381–392.
Vesecky, A., Petrovie, S., Briedon, V. & Karsky, V. 1958.
Atlas podnebı Ceskoslovenske republiky [Climate atlas
of the Czechoslovak Republic]. Ustrednı sprava
geodezie a kartografie, Praha, CZ (in Czech).
Webb, C., Ackerly, D.D., McPeek, M. & Donoghue, M.A.
2002. Phylogenies and community ecology. Annual
Review of Ecology and Systematics 33: 475–595.
Westoby, M., Leishman, L.R. & Lord, J. 1995. On
misinterpreting the phylogenetic correction. Journal
of Ecology 83: 531–534.
Williams, N.S.G., Schwartz, M.W., Vesk, P.A., McCarthy,
M.A., Hahs, A.K., Clemants, S.E., Corlett, R.T.,
Duncan, R.P., Norton, B.A., Thompson, K. &
McDonnell, M.J. 2009. A conceptual framework for
predicting the effects of urban environments on floras.
Journal of Ecology 97: 4–9.
Wittig, R. 2002. Siedlungsvegetation. Ulmer, Stuttgart, DE.
Woodell, S. & Rossiter, J. 1959. The flora of Durham
walls. Proceedings of the Botanical Society of the
British Isles 2: 257–273.
Wright, S.J. 2002. Plant diversity in tropical forest: a
review of mechanisms of species coexistence.
Oecologia 130: 1–14.
Zobel, M. 1997. The relative role of species pool in
determining plant species richness: as alternative
explanation of species coexistence? Trends in Ecology
and Evolution 12: 266–269.
Received 19 May 2009;
Accepted 26 November 2009.
Co-ordinating Editor: Dr. Ingolf Kuhn.
530 Lososova, Z. & Lanıkova, D.