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- Biogeographic patterns of Argentine cacti - 667

Journal of Vegetation Science 7: 667-680, 1996© IAVS; Opulus Press Uppsala. Printed in Sweden

Species richness of Argentine cacti:A test of biogeographic hypotheses

Mourelle, Cristina & Ezcurra, Exequiel

Centro de Ecología, UNAM, Apartado Postal 70-275, 04510 - Mexico, D.F., Mexico;Fax +52 5 6228995; E-mail [email protected]

Abstract. Patterns of species richness are described for 50columnar, 109 globose and 50 opuntioid cacti species in 318grid cells (1° × 1°) covering Argentina. Biological richnesshypotheses were tested by regressing 15 environmentaldescriptors against species richness in each group. We alsoincluded the collection effort (estimated as the logarithm ofthe number of herbarium specimens collected in each cell) toestimate the possible error induced by underrepresentation incertain cells. Log-linear regression models accounted for alarge portion of the variation in richness of columnar species,opuntioid species, globose species and all forms combined.Opuntioid and globose species richness was associated withpercentage summer rainfall. Columnar species richness wasassociated with the number of frost-free days. The distributionof columnar cacti seems to be limited by freezing tempera-tures. The results are consistent with the climate favourable-ness and climatic variation hypotheses, but do not support thehypothesis that energy flow limits regional species richness.

Altitudinal range (a measure of habitat heterogeneity) wasrelated to richness of globose cacti. A floristic affinity analysisbetween geographic provinces and the distribution of thedifferent growth forms confirmed the high degree of ende-mism of globose cacti and the cosmopolitanism of the opuntioidones. Two cells in the Prepuna and northern Monte Provincesshowed species richness values that were significantly higherthan those predicted by the log-linear model. This is inter-preted in terms of Quaternary historical events having affectedthe main South American biomes.

Keywords: Cactaceae; Growth form; Phytogeographic prov-ince; Plant-environment relationship.

Nomenclature: Hunt (1992) and Kiesling (in press).

Introduction

Members of the family Cactaceae exhibit a remark-able variety of growth forms (Gibson & Nobel 1986),possibly as a result of different environmental selectivepressures throughout the distributional range and theevolutionary history of the family. Within the Cactaceae,five main growth forms can be recognized: (a) columnarcacti, (b) globose cacti, (c) opuntioid cacti, (d) epiphytic

cacti and (e) pereskioid cacti. Columnar species havecolumn-like stems with ribs, formed by an arrangementof the areoles in longitudinal rows. These species haveparallel vascular bundles, separated by succulent paren-chyma, sometimes fusing towards a woody base in theadults. We broadly considered as columnar cacti:candelabriform arborescent species, unbranched erectstems (or solitary columnar arborescent cactus), branchedcacti, shrub-like forms with ascending or pendentbranches, and shorter barrel cacti.

Globose cacti are small, more or less spherical inshape and have a high density of areoles in their stems.Columnar and globose growth forms belong to the sub-family Cactoideae. Most of the columnar genera belongto the tribes Trichocereeae and Cereeae, while the gen-era of the globose species belong mostly to the TribeNotocacteae (Gibson & Nobel 1986). Opuntioid speciesdo not form ribs. Their vascular bundles are fused into anetlike, reticular structure. The stem consists of one ormore flat or cylindrical cladodes. Each cladode is anindependent unit with definite growth that may cloneinto a complete individual if detached from the motherplant. All opuntioid species belong to the subfamilyOpuntioideae. Epiphytic cacti are anatomically similarto the columnar species. Their growth habit, however, isquite different. They are mostly herbaceous plants(Gibson & Nobel 1986) with decumbent or prostrategrowth, and generally showing a few shallow ribs.

Most of the genera of the epiphytic cacti belong tothe Tribe Hylocereeae of the subfamily Cactoideae.The pereskioid cacti show many ancestral anatomicalcharacters of the family. They are leaf-bearing trees andshrubs with a woody, almost non-succulent stem, andbelong to the subfamily Pereskioideae. The adults ofthis group are C3 plants while the adults of the othergroups show CAM metabolism (Rayder & Ting 1981;Gibson & Nobel 1986; Nobel 1988).

As in other studies (e.g. Cody 1986, 1989; Brown1988; Major 1988; ) species richness is considered amain constituent of species diversity. Many historical,evolutionary and ecological hypotheses have been pro-posed to explain species richness patterns (e.g. Simpson

668 Mourelle, C. & Ezcurra, E.

1964; MacArthur 1965; Pianka 1966; Cook 1969; Schall& Pianka 1978; Shmida & Wilson 1985; Silvertown1985; Currie 1991) and geographic variation in growthforms (e.g. Raunkiaer 1934; Box 1981). Palmer (1994)identified at least 120 plausible hypotheses on speciesrichness patterns published in the literature. Attempts toclassify these hypotheses (Giller 1984; Brown 1988;Begon et al. 1990; Zobel 1992; Eriksson 1993; Palmer1994; van der Maarel et al. 1995) have not been verysuccessful as many are not mutually exclusive, and arefrequently based on the same theoretical mechanisms,such as the competitive exclusion principle (Palmer1994).

The aim of our work was to describe the patterns ofgeographic distribution of the main growth forms ofArgentine cactus species: how does the number of spe-cies in each growth form vary geographically, and whatis the relationship between environmental variables andthe richness of the different cactus growth forms. Wetested the following hypotheses: (1) environmental fa-vourableness, (2) temporal climatic variation, (3) habi-tat heterogeneity and (4) limited energy and productiv-ity. We did not explore other hypotheses, such asinterspecific interactions, due to the more local scale oftheir effect. Disturbances such as fire, and speciationand extinction processes were taken into account in theinterpretation of patterns but were not directly evalu-ated. We analyzed the different cactus growth formsseparately, as the species in each life form may corre-spond to different structural niches, and the overalldiversity of perennial plants is largely determined by thecoexistence of different growth forms (Cody 1986, 1989).

The environmental favourableness hypothesis statesthat extreme environmental conditions should supportfewer species than intermediate environments, as costlyadaptive mechanisms are needed (Brown 1988; Begonet al. 1990). Thus, this hypothesis examines the relation-ship between mean values of the environmental vari-ables (e.g. mean annual rainfall or temperature) anddiversity (Giller 1984). As a general rule, a heterogene-ous environment may offer more opportunities for theestablishment of species with different tolerances.

The climatic variation hypothesis is based on thetemporal heterogeneity of the environment. More spe-cies may be expected to coexist in seasonal environ-ments (Brown 1988; Begon et al. 1990). Unpredictable,non-seasonal climatic variation is a form of disturbanceand species diversity may be highest at intermediatelevels (Hutchinson 1961; Connell 1978; Richerson &Lum 1980; Giller 1984).

The habitat heterogeneity hypothesis is based on thespatial variation of the environment. A heterogeneoushabitat may offer more by way of microhabitat differ-ences. Thus more niches may be available and more

species or growth forms may co-occur (Simpson 1964;Giller 1984; Auerbach & Shmida 1987; Aarsen 1992).

According to the limited energy hypothesis theamount of energy available will support a restrictednumber of species. Under certain conditions and at abiogeographic scale species richness is related to pri-mary productivity – a measure of energy flow – (e.g.Abramsky & Rosenzweig 1984; Rosenzweig 1984, 1992;O’Brien 1993). However, productivity is dependent onother factors such as climatic stability (Giller 1984) andat high levels of productivity diversity decreases again(e.g. Pausas 1994). A review of the complex relation-ship between productivity and species richness is foundin Rosenzweig (1995).

Methods

223 cactus species, known to occur in Argentina,were included – five low-frequency pereskioid species,some introduced species and species with either dubiousdistribution records or non-valid names were omitted(App. 1). Data on the distribution of the species weretaken from herbarium labels in eight Argentine herbaria(SI, LIL, LP, BA, BACP, BAB, BAF and MERL, acro-nyms as in Index Herbariorum) and supplemented byKiesling and Ferrari’s unpublished field data (Kieslingin press), and with various published sources (a list isavailable upon request). A total of 3395 records wereelaborated. For each species, we mapped the sites whereit had been collected; for this purpose the map of Argen-tina was divided into a grid of 318 cells of 1° latitude ×1° longitude. We superimposed the grid onto the mapswith the records for each species and digitized thespecies occurrences.

We also digitized climatic descriptors on a 1° × 1°scale; data were taken from published maps from theServicio Meteorológico Argentino and from Hoffman(1975). The Centro Biometeorológico Argentino pro-vided us with an unpublished map showing the propor-tion of annual rain falling in summer. Topographic datawere taken from Anon. (1981). We assigned to each cellvalues of mean annual temperature, mean annual pre-cipitation, mean minimum annual temperature, propor-tion of annual rain falling in summer, number of frost-free days, average annual water deficiency (defined asthe ratio of the net radiation to the heat energy requiredto evaporate the mean annual precipitation), mean an-nual potential evapotranspiration, mean July tempera-ture, mean December temperature, the difference be-tween the last two measures, and annual primary pro-ductivity calculated from Lieth’s model (Lieth 1975).Finally, we also recorded the cell’s latitude and threetopographic variables considered relevant to species


distribution: (a) altitudinal range, calculated as the dif-ference between the maximum and the minimum valuefrom nine systematically chosen elevations within eachcell; (b) topographic variation, measured as the standarddeviation of the same nine elevations per cell, and (c)mean elevation, obtained as the average of the nineelevations. Table 1 summarises the environmental vari-ables and the hypotheses put to test with each variable.

Species richness patterns and environmental variables

Statistical analyses were performed for the threedominant growth forms: columnar, globose and opuntioidcacti (n = 50, 109, and 50 species, respectively). Due tothe small number of epiphytic cacti (n = 14), species ofthis growth form were mapped, but not analyzed. Weused log-linear models in all cases, since species num-bers are frequencies (a discrete variable) which can beassumed to have a Poisson error distribution (Crawley1993). Standard regression models cannot be applied inthis case since (1) the variance of frequency counts isusually not constant, and (2) the error is frequently notnormally distributed, especially when the observed fre-quencies are low. Log-linear models ensure that thepredicted values are always positive; the assumption ofa Poisson error distribution takes into account the factthat the data include integer values and have variancesthat increase with the mean. For our log-linear modelswe used the GLIM package (Anon. 1986, Crawley1993), and evaluated the fit of the model by means of theG-statistic as a measure of goodness-of-fit (McCullagh& Nelder 1989). As in standard regression, we tested theresiduals of the model to evaluate their compliance withthe assumptions of the Poisson error distribution. Gen-eralized linear models are frequently used in biologicalsurveys (e.g. Nicholls 1989, Austin et al. 1990, Bojór-quez-Tapia et al. 1995), as their statistical approachallows the analysis of data that frequently do not con-form to the assumptions of standard regression andanalysis of variance.

Regression against latitudeFor each growth form, we counted the number of

species in each cell of the grid, and used this informationto map species richness. The relationship between spe-cies richness and latitude was determined by log-linearregression. Strictly speaking, latitude is not an environ-mental factor directly affecting the distribution of plants;rather, it is a variable related to a complex set of environ-mental factors that co-vary from the tropics to the tem-perate zones. By using latitude as an independent vari-able, we tried to evaluate its power as a single predictorof species richness.

Table 1. Environmental variables tested as predictors ofspecies richness, and the main hypothesis tested witheach variable.

Hypothesis Variable Symbol

Climate severity Number of frost-free days FFDor climate Average minimum annual temperature AMTfavourableness Mean annual temperature MAT

Mean annual precipitation MAPAverage annual water deficiency AWDMean July temperature MJTMean December temperature MDTMean elevation MELActual evapotranspiration AEV

Climatic variation Difference between the meanJuly and December temperatures DIFProportion of annual rain falling in summer PRSLatitude LAT

Habitat Altitudinal range ALRheterogeneity Topographic variation STD

Energy Actual evapotranspiration AEVPrimary productivity APP

History Residuals of the models

Disturbance Fires (discussed, but not included in the model)

Regression against environmental variablesIn a second regression model, we tried to identify

more precisely those variables that could be more di-rectly affecting plant distribution. For this purpose, wedetermined the relationship between species richness ineach growth form and the environmental variablesthrough an additive stepwise log-linear regression model.Because the data were collected from natural condi-tions, the multiple regression log-linear model did notfollow an orthogonal design for the independent vari-ables. Some of these predictors were significantly corre-lated between themselves (Table 2) and their explana-tory power, as indicated by the partial r2-value, maydepend on the order in which they were introduced intothe model. In the stepwise procedure we used, the mostsignificant predictor was introduced into the model ateach step and the resulting sequential r2-value wasregistered with that criterion.

The effect of collection intensityThe number of species detected in a given area is

non-linearly related to the number of herbarium speci-mens that have been collected (Soberón & Llorente1993). At first, new specimens will frequently incorpo-rate new species, but once the collection is large, mostnew specimens will belong to species that have alreadybeen collected. The incorporation of new species into acollection is a ‘diminishing returns function’ of thenumber of specimens (Fisher et al. 1943; Efron & Thisted1976). The mathematical equations that predict thisrelationship are often called ‘accumulation functions’.Soberón & Llorente (1993) have made a detailed review


Table 2. Correlations between environmental variables. Only the significant values (P ≤ 0.01) are shown. The symbols for eachvariable are given in Table 1. The variable productivity is not included in the matrix because it is a linear function of the actualevapotranspiration.

LAT ALR FFD PRS MAP MAT AMT STD MEL DIF MDT JUL AEV

ALR – 0.77 1FFD 0.21 - 1PRS – 0.71 0.52 - 1MAP – 0.38 0.41 - - 1MAT - - - - 0.49 1AMT - - - - – 0.20 – 0.22 1STD 0.58 - - – 0.63 - - - 1MEL - - – 0.93 - - - - - 1DIF – 0.42 0.49 - - - - 0.33 - - 1MDT - - - - - - 0.36 - - - 1JUL - - - - - - – 0.59 - - 0.33 – 0.68 1AEV - - - - - – 0.39 - – 0.19 - - - - 1AWD - - - - 0.05 0.33 – 0.21 - - - - - 0.48

critical normal deviate can be regarded as not fittingadequately to the model). Because the number of cellswas 318, we followed the Bonferroni criterion of usinga lower probability threshold (P ≤ 0.0002) in each indi-vidual test of residuals, in order to obtain a globalprobability of a type-I error of 0.05 (Cook & Weisberg1982; Miller 1965). We also followed Pearson’s rule forthe expected values, and did not analyse residuals incells where the frequencies predicted by the log-linearmodel were lower than five.

All cells with residuals departing significantly from themodel, and with predicted values higher than five, weremarked on the map in order to analyse the distribution ofsites where species richness was significantly higher thanwould be expected from the present environmental condi-tions. In this way, we could identify areas where thedifferences between the predictions of the model and theactual floristic richness could not be attributed to randomvariation. We also tested the standardized residuals forindependence, following Draper & Smith (1981).

Floristic affinities between regions

In order to analyse floristic affinities between regions,we chose three base cells of relatively high cactus rich-ness. Each base cell was located in the central part of oneof the three most cactus-rich phytogeographic provincesof Argentina: the Prepuna, Monte and Chaco Provinces(Cabrera & Willink 1980; Fig. 1). We then calculated, foreach cell on the map, the number of species shared withthe base cells. We then plotted maps of equiprobabilisticcontour lines showing the similarity of all cells with thechosen centre of comparison (i.e. the base cell). Thesecurves have been used to predict species barriers andcorridors for different taxa (Rapoport 1975, 1982; Rapo-port & Ezcurra 1979). This analysis was repeated for thethree main growth forms: opuntioid, columnar and glo-bose cacti.

of various accumulation functions. Their study, basedon theoretical models fitted to field data, has shown thatboth variables (specimens and species) should exhibitan approximately linear behaviour on a log-log scale(the functional relationship of logarithmic accumulationfunctions is not exactly linear since the number ofspecies eventually reaches an asymptote while thenumber of collected individuals can increase indefi-nitely with time (see Efron & Thisted 1976; Williams1995). Based on this property, we incorporated to ourlog-linear models the logarithm of the number of voucherspecimens registered per cell (we previously added oneto the number of specimens, to avoid the indetermina-tion of log-zero) as an additional predictor, with theobjective of evaluating the potential effect of under-collection in our study (we also tried the non-trans-formed data, but the log-transformed values were in allcases significantly better predictors). Thus, once thefinal model based on environmental predictors had beenfitted, we added the logarithm of the number of speci-mens (our estimation of collection intensity), in order toevaluate the proportion of the model’s error that couldbe attributed to spatial heterogeneity in the collectioneffort. Once this last effect had been fitted, we analysedthe residual χ2 deviance of the log-linear model (i.e. themodel’s error) for significance. If the residual variationwas significantly higher than could be expected bychance, we then proceeded to analyse the residuals ofthe model as explained in the next section.

Analysis of the residualsIn Poisson frequency data the standardized residuals

observed – expected expected( ) [ ] (1)

follow asymptotically a normal distribution (Everitt1977). Thus, for each cell the standardized residuals canbe used as a measure of the fit of that particular cell tothe complete model (any residual higher than a certain


The distribution of geographic ranges

The geographic range of each species was estimatedby adding the number of cells in which the species waspresent. The frequency distribution of species ranges ineach growth form was then calculated, together with themedian of the distribution. This procedure allows evalu-ation of the proportion of endemic species in eachgrowth form (i.e. the number of species below a givenlow number of cells). As predicted by previousbiogeographic research, the data were log-normally dis-tributed (Rapoport 1975, 1982). Thus, the mean and thestandard deviation of the distributions of ranges werecalculated on the log-transformed data, and these valueswere used to test for differences in the ranges of thethree growth forms.

Results

Species richness patterns

When the whole group was considered (Fig. 2),areas in the NW of the country showed the highestspecies richness: Prepuna Province, northern MonteDesert and Chaco dry forest. The number of species inthe peaks of the first two regions double that of therichest cells in the Chaco. The Andean-Patagonian andPampean provinces showed the lowest levels of cactusspecies richness. The columnar cacti (Fig. 3a) followeda pattern similar to that of the whole group. In bothcases, the number of species decreased from north tosouth, and from west to east. Both groups showed amarked decline above 34 - 36° S. The globose cacti (Fig.3c) did not fit this pattern, although their southern limitwas similar to that of the columnar group. They reachtheir highest species richness in the Prepuna Provinceand the Monte Desert, and in two isolated ranges: theSierras of Córdoba and San Luis, and the hills of EntreRíos. This growth form has a strikingly low speciesrichness in the Chaco dry forest compared to either thecolumnar growth form or the whole family. The opuntioidform (Fig. 3b), more widespread than the others, spanneda large altitudinal and latitudinal range. Although itsspecies richness decreased in regions such as Patagoniaand the high Andes, plants in this group reach colderhabitats than those generally tolerated by the other growthforms. In spite of the low number of species, the speciesrichness pattern of the epiphytic cacti (Fig. 3d) wasquite conspicuous. Two areas of high species richnessappeared, both in the most humid parts of Argentina: theYungas Province, a cloud forest in the NW, and theParana Province, a wet tropical forest in the NE linkedto the Brazilian Mata Atlántica (coastal cloud forests).

Species richness and environmental variables

Regression against latitude.The growth forms showed a significant negative

association between species richness and latitude (wholegroup: r2 = 0.46, P < 0.0001; opuntioid cacti: r2 = 0.27,P < 0.0001; globose cacti: r2 = 0.24, P < 0.0001; colum-nar cacti: r2 = 0.54, P < 0.0001). Species richness in-creased in all cases towards tropical, low latitude cells.However, in the opuntioid and globose growth forms, aswell as in the whole family, latitude was not the bestindividual predictor, as the specific environmental vari-ables were more significantly associated with speciesrichness. In contrast, in the columnar growth form lati-tude showed a higher association with species richnessthan any other single environmental variable (Fig. 4).

Regression against environmental variablesGlobally, the environmental variables selected by

the multiple regression procedure, together with the

Fig. 1. Phytogeographic provinces of Argentina, after Cabrera& Willink (1980). The main biome in each province is given inparentheses: Puna Province (high-altitude cold semidesert),Prepuna Province (sarcocaulescent scrub), Yungas Province(cloud forest), Chaco Province (dry subtropical forest), ParanaProvince (humid savannah), Monte Province (warm desert),Espinal Province (xerophyllous woodland), Pampas Province(temperate grassland), High-Andean Province (high-altitudecold grassland), Subantarctic Province (temperate humid for-est), Patagonia Province (steppe).


Fig. 3. Species richness for (a) columnar, (b) opuntioid, (c)globose, and (d) epiphytic cacti in Argentina.

Fig. 2. Species richness – numbers per 1° × 1° cell – for allcacti in Argentina (excluding Pereskioid species).

estimate of the collection effort, accounted for a largeproportion of the total variation in species richness forthe whole group, and for the individual growth forms(Table 3). For the whole group, the proportion of sum-mer rainfall was the strongest predictor (P < 0.0001; Fig.5a). The pooled set was also significantly associatedwith the number of frost-free days (P < 0.0001), thealtitudinal range (P < 0.0001) and the mean annualtemperature (P < 0.0001).

In the globose and opuntioid forms the best predictorof species richness was the proportion of annual rainfalling in summer (P < 0.0001 for both growth forms;Figs. 5c, 5d and Table 3). Additionally, in the globosecacti the mean minimum annual temperature and thealtitudinal range explained a significant (P < 0.0001),albeit lower, proportion of the residual variation. Inshort, the globose species tend to occur in regions whererain falls mainly in summer, but which are at the sametime relatively warm and topographically heterogene-ous. Besides the proportion of annual rain falling insummer, the species richness of the opuntioid group wasalso significantly (P < 0.0001) associated with the arid-ity index and with the mean annual temperature.

The number of frost-free days was the strongestpredictor for the columnar growth form (P < 0.0001;Fig. 5b). As the number of frost-free days increases, thespecies richness increases as well. This result seems toconfirm the high sensitivity to freezing temperatures of

the columnar growth form (Gibson & Nobel 1986). Thecolumnar species were also significantly associated withaltitudinal range (P < 0.0001), although the variationexplained by this second variable was lower.

The effect of collection intensityIn all growth forms the intensity of collection ex-

plained a highly significant (P < 0.0001) proportion ofthe residual variation of the models, although in no casewas it more important than the first environmental pre-dictor (Table 3).

Analysis of the residualsAs can be seen in Figs. 4 and 5, the dispersion of the

data increased with the mean values of species richness,and with the predicted values of the model. For exam-ple, for the whole cactus family it can be seen that in thelow-latitude regions the mean species richness is higher,but the dispersion of the data is also higher (Fig. 5a).This should be expected in frequency data, as a Poissonerror distribution predicts that the variance of randomly-varying frequency values should be equal to the mean


(i.e. the expected value). The standardized residualsfollowed the assumptions of the regression model(Poisson error and independence) in all growth formsseparately (G = 235.7, d.f. = 303 for the opuntioidspecies; G = 303.0, d.f. = 303 for the columnar species;G = 297.7, d.f. = 303 for the globose species), but thewhole group did show a significant residual variation (G= 407.0, d.f. = 302, P < 0.0001) that suggested non-random departures from the model in some cells.

When the residuals that departed significantly fromthe Poisson error distribution were analysed for thewhole group, it was found that a cell in the Prepuna andanother in the northernmost tip of the Monte Desertshowed significantly higher species richness than waspredicted by the regression model (Fig. 6). Three cellsalso appeared with significant negative residuals, show-ing areas where species richness is lower than could beexpected following the model’s predictions. These threecells corresponded to the three most collected grid cellsin Argentina. While on average the number of speci-mens per cell was 14.3 for the whole country and 25.2for the subtropical northern section, these three sites hadwell above 100 specimens each.

The effect of cell sizeAs the size of the cells used in this study co-

varies with latitude (the area of each cell decreases withlatitude), we could ask whether the area per se canexplain the observed latitudinal patterns of species rich-ness. In order to analyse the effect that decreasing cellsize may have on species richness, we followed Pres-ton’s species-area equation (s = k Az, where s is speciesrichness, A is the sampled area, z is the exponentialparameter, and k is a scale coefficient; see Preston 1960,Palmer & White 1994). For a more conservative analy-

Table 3. Proportion of the variation accounted by the bestpredictors of the linear regression models, excluding latitude.The sign of the coefficient explains the relationship betweenthe predictor and species richness.

Growth Variable r2 SignForm

Columnar and Number of frost-free days per year (FFD) 0.50 + barrel cacti Proportion of rain falling in summer (PRS) 0.17 +

Altitudinal range (ALR) 0.02 +Collection effort 0.15 +Total 0.74

Opuntioid cacti Proportion of rain falling in summer (PRS) 0.37 +Average annual water defficiency (AWD) 0.05 +Mean annual temperature (MAT) 0.03 +Collection effort 0.27 +Total 0.72

Globose cacti Proportion of rain falling in summer (PRS) 0.33 +Average minimum annual temperature (AMT) 0.07 +Altitudinal range (ALR) 0.03 +Collection effort 0.32 +Total 0.75

Whole group Proportion of rain falling in summer (PRS) 0.50 +Number of frost-free days per year (FFD) 0.07 +Altitudinal range (ALR) 0.05 +Mean annual temperature (MAT) 0.03 +Collection effort 0.21 +Total 0.86

Fig. 4. Relationship between species richness of the columnargrowth form and latitude.

sis, we set the z value to 0.4, much higher than Preston’s‘canonical’ value (z = 0.23). Preston’s model predictsthat a difference in cell area of 17% between northernArgentina and southern Patagonia may result in a reduc-tion in species richness not higher than 6%. As theobserved reduction in species number was almost 100%in all growth forms, only a minor part of this change inspecies richness can be attributed to the latitudinal re-duction of cell size. Another possible bias in cell areamay result from the fact that some cells are located on aseacoast, peninsula or in border areas. To analyse thesignificance of the effect of incomplete cells on speciesrichness, these cells were identified with a statisticalfactor (a dummy variable) in the regression analyses. Itwas found that the effect of incomplete cells was notsignificantly associated with species richness. Thus, theeffect of cell size on the observed patterns of cactusrichness can be safely ignored for all practical purposes.

Floristic affinities between regions

PrepunaIn general, a remarkable level of endemism was

found in this region. Of all the opuntioid species presentin the Prepuna, only 40% are shared with a small part ofthe High-Andean province(Figs. 7a'). Less than 20% ofthe columnar and globose species present in the Prepunaoccur outside this province (Figs. 7a and 7a'').


Fig. 5. Relation between species richness per growth form and its best predictor: (a) all species; (b) columnar species; (c) opuntioidspecies; (d) globose species. Regression line indicates the log-linear function predicted by the stepwise regression analysis.

(Fig. 7c''). The existence of cells with a floristic similar-ity of 100% in these last provinces, as well as the generalpattern of isolines, suggest a biogeographic corridor forall globose species in the dry Chaco, allowing theirdispersion into the northern Monte and the Prepuna, andalso into the wet Chaco.

The distribution of geographic ranges

The globose group exhibited the highest number ofspecies with restricted distribution: 77.06% of the glo-bose species occupied five cells or less, compared to33.33% for the columnar species and 34% for theopuntioid form (Fig. 8). In increasing order, the medianrange of the globose group was the lowest (Me = 3.65),followed by the columnar and the opuntioid forms (Me= 9.33 and Me = 11.00 respectively). There were alsosignificant differences between the mean log-range ofglobose cacti (x = 1.86; S.E. = 0.11) with the opuntioidspecies (x = 3.35; S.E. = 0.21; P < 0.001) and with the

The Monte DesertWith the central Monte Desert as the base cell, a

strong southern barrier appeared in all three groups witha western barrier on the Andes. For the opuntioid growthform a corridor of high affinity running northwards wasobserved (Fig. 7b'). The columnar species in this regionshowed a high number of shared species with the north-ern Monte Desert and Prepuna, while the globose formspresented a corridor of shared species with the northernMonte Desert and the northern Espinal province (axerophyllous woodland; Figs. 7b and 7b'').

The Chaco dry forestMost opuntioid species present in the Chaco also

occur in the Prepuna and in the northern Monte Desert(Fig. 7c'). In the case of columnar cacti, this trend is lessmarked and only 60% of the species were found to beshared with the western arid zones (Fig. 7c). Most of theglobose cacti in the dry Chaco (more than 50%) are alsoshared by the Prepuna and northern Monte provinces


Discussion

The biodiversity patterns found for Argentine cactishowed significant variation between the different growthforms. Environmental factors operating at a regionalscale – mostly linked to climatic favourableness andclimatic variation – accounted for a large proportion ofthe geographic variation observed in the species rich-ness of all growth forms. Variables related to habitatheterogeneity or energy interception levels were poorerpredictors of species richness in general, although habi-tat heterogeneity was a significant predictor for theglobose growth form.

The columnar and globose growth forms, as well asthe combined group, showed the highest species rich-ness in the Prepuna and the northern Monte Desert. Theubiquity of the opuntioid form was noticeable in thehigh-diversity corridors found linking the Chaco withthe Prepuna and the northern Monte. The opuntioidcacti are the only group reaching the Patagonian steppein the southernmost province of Santa Cruz, a fact thatunderscores their wider climatic tolerances. The broadtolerances of opuntioid cacti may be related to themodular growth and the morphological plasticity of thisform, as suggested by Gibson & Nobel (1986) and

Fig. 6. Standardized residuals of the log-linear regressionmodels for the whole cactus group. Black squares correspondto significantly positive residuals (cells having significantlymore species than predicted by the Poisson error distribution),the grey squares correspond to significantly negative residuals.

Fig. 7. Floristic similarity centred in three selected cells representing different Provinces: (a-a'-a'') Prepuna; (b-b'-b'') Monte, and (c-c'-c'') Chaco. The shading represents the percentage floristic similarity from a central point of comparison (base cell representing a100% of species), marked by a cross. Maps to the left (a-b-c) correspond to columnar species, maps in the middle (a'-b'-c') toopuntioid species, maps to the right (a''-b''-c'') to the globose species.

columnar species (x = 3.29; se = 0.23; P < 0.001). Nosignificant difference was found between the mean loggeographic ranges of opuntioid and columnar cacti.Additionally, the globose form included a relativelyhigh number of strongly localized species: 10% of theglobose species were restricted to only one cell whilenone of the opuntioids and only 2 % of the columnarsdisplayed such highly restricted ranges.


Nobel (1982a, b, 1985). The adaptive advantage of theterminal orientation of the flat cladodes according to thelatitude and to specific environmental conditions, maybe the base of the higher success of opuntioid cacti inextreme environments. Gibson & Nobel (1986) havealso attributed the higher temperature tolerance ofopuntioid species to the shifting of the temperatureresponse for net nocturnal CO2 uptake as the environ-mental temperature changes. In spite of their widertolerances, the opuntioid species were statistically asso-ciated with the proportion of annual rain falling insummer, the aridity index and the mean annual tempera-ture. This group thus seems to be mainly associated withwarm areas with concentrated summer rains.

The distribution of columnar cacti appears to beseverely constrained by low temperatures. The north-ern, subtropical biogeographic regions showed littlefloristic similarity with the southern, more temperateregions, and the maps of floristic affinity suggest theexistence of a barrier south of the Chaco and PrepunaProvinces. Additionally, species richness decreasesabruptly above latitude 34 °S and above altitudes of3000 m. An exception is the genus Oreocereus (withtwo species in Argentina), which can be found at eleva-tions of 4000 m. Their stems are completely coveredwith white long spines and hairs, which seem to ther-mally insulate the plant from frost, supplying freezingresistance and mechanical protection in stressful habi-tats. The number of frost-free days was the best predic-tor for columnar species richness, explaining a signifi-cant proportion of the variation (50 %). It is necessary tonote here that all cells in Argentina have some level offrost danger in winter, ranging from fewer than fivefreezing days in the north to more than 250 days inPatagonia. This result confirms a trend described byBurgess & Shmida (1988): Cactoid vegetation does notoccur in areas where freezing occurs frequently. It hasalso been reported (Gibson & Nobel 1986) for the

saguaro (Carnegiea gigantea, a columnar species) inNorth America, that frost damage may cause a reductionin stem growth and often leads to substantial constric-tion in stem diameter. In short, columnar species seemto respond to the climate favourableness hypothesis.

Apart from their strong association with the amountof the precipitation falling in summer, the distribution ofthe globose species seems to be linked also to substratecharacteristics (e.g. microsites and soil rockiness), whichare basically independent of the large-scale variablesused in this study. In general they do not occur in areaslacking rocky substrates (e.g. the Chaco plains), whereother cactus groups are common. This substrate prefer-ence may explain the high species richness of the groupin the rocky Prepuna and the striking level of endemismthey show in the mountainous ranges of central Argen-tina (Córdoba and San Luis) and in the rocky hills ofEntre Ríos in the mesic northeast of the country. Ingeneral, the species richness pattern of this growth format our scale of study seems to follow the climatic varia-tion hypothesis, as the percentage of summer rainfallexplained a significant proportion of their variation inspecies numbers. For columnar and barrel cacti, it hasbeen shown that the key environmental factor affectingsurvival during the seedling stage is the availability ofwater, until the plant can reach a larger size and a lowersurface/volume relationship (Steenbergh & Lowe 1977).To survive an ensuing drought, the seedling must de-velop sufficient water storage tissue during the preced-ing wet season. More studies of seedling microhabitatsand requirements for germination and establishment(e.g. the length of the summer wet season) are neededfor opuntioid and globose cacti.

The altitudinal range of the cells explained a signifi-cant, but low, proportion of the variation in speciesnumbers for all groups with the exception of opuntioidcacti (r2 = 0.03, P < 0.0001 for the globose form; r2 =0.02, P < 0.0001 for the columnar species, and r2 = 0.05,P < 0.0001 for the whole group). Our results, unlikethose of Richerson & Lum (1980), are not completelyconsistent with the habitat heterogeneity hypothesis as amajor determinant of species richness; the analysedvariables only explained a small proportion of the ob-served variation.

Latitude, as an indirect environmental factor, wasthe single best predictor only for columnar species rich-ness, but it is difficult to use this relationship in order totest any specific hypothesis on the causes of speciesrichness. As it is strongly correlated to variables such asthe number of frost-free days and the proportion ofsummer rainfall, latitude can be interpreted as a com-posite indicator of both climatic favourableness andclimatic variation, and consequently it cannot be used todiscriminate between the two hypotheses.

Fig. 8. Geographic range of the different growth forms: (a)columnar; (b) opuntioid and (c) globose.


The species richness patterns of the whole group,and of the opuntioid and the globose growth forms,turned to be more consistent with the climatic variation(seasonality) hypothesis, with the proportion of summerrainfall appearing as the best predictor in all the regres-sion analyses. According to Burgess & Shmida (1988),cactoids preferentially thrive in warm semi-desert areaswhere rainfall ranges from 150 to 400 mm/yr. Whilecacti are not restricted to climates with summer rainfall,they are rarer where winter rain is common and summerrain lacking. A salient feature of the observed relation-ships between species richness and climatic variables isthat the mean values of the variables were not as stronglyrelated to species richness as seasonality indices or othermeasures of variation in climatic favourableness (i.e.number of frost-free days).

In agreement with other authors (Whittaker 1965;Richerson & Lum 1980) and at odds with the findings ofCurrie (1991) and Rosenzweig (1992), productivity wasnot related to species richness, nor did variables such asevapotranspiration, mean temperature and mean pre-cipitation (two main elements of productivity) showa strong relationship with species numbers. This mayresult from the fact that productivity obtained as afunction of evapotranspiration showed little variationwithin the distributional range of cacti in Argentina.Additionally, cacti are mainly found in low-productiv-ity environments, the exception being the epiphyteswhich were not included in the regression analyses.Potential productivity could also be measured fromestimates of incoming solar energy; it is possible that ifsuch an estimate of productivity was used it would moreclosely correlate with species richness.

Although we did not explicitly test the incidence offire as a predictor of cactus species richness, it has beenreported that cacti tolerate fire poorly (e.g. Thomas &Goodson 1992; McLaughlin & Bowers 1982). The cen-tral pampas, which are distributed along a moisture gradi-ent from a humid prairie in the east to an arid woodedgrassland in the west, have been for centuries the areaswith the highest fire intensity in Argentina. It is interest-ing to note that for all growth forms, these formationshave a relatively low number of species. Fire may bepartially responsible for these low-richness areas.

For all growth forms, the significant associationfound between collection intensity and the residual vari-ation of the models suggests that undercollection ispossibly biasing the observed distribution of speciespresences, as some cells are much better collected thanothers. This also suggests that, for the present intensityof botanical exploration in Argentine cacti, the use ofcells one degree in size is an adequate scale, as insmaller cells the error introduced by spatial gaps in thebotanical collection would be more important than the

variation associated with environmental factors.Remarkable differences were found between the

three growth forms in the area covered by their distribu-tional ranges. Globose species showed a striking levelof microendemism, consistent with the idea previouslydiscussed that factors operating at a more local scale,such as substrate type and topographic heterogeneity,are significantly associated with the distribution of thisgroup. The distribution of rocky soils and mountainousranges in central Argentina is highly discontinuous; thisin turn gives rise to a fragmented distribution of theglobose cacti, the group most associated to these typesof habitats. The distributional ranges of opuntioid andcolumnar cacti were significantly larger than those ofthe globose species, although they were not signifi-cantly different between themselves. In particular, manyopuntioid species do not only occupy large continuousgeographic areas (e.g. Opuntia quimilo, endemic to theChaco phytogeographic province or O. sulphurea, en-demic to the Monte province), but many of them (e.g. O.brasiliensis, O. monacantha, O. nigrispina, O. pent-landii and O. soehrensii) also inhabit more than onephytogeographic region.

For the whole group, significantly low residualswere found in three cells that are the most collectedareas in Argentina. This result is quite likely an artefactof the model: as the number of species was positivelyassociated with the number of collected specimens, incells with an extraordinarily high number of specimensthe model will predict a very high number of species. Inpractice, however, most accumulation functions willtend to reach an asymptote at some level (Soberón &Llorente 1993; Williams 1995).

Similarly, significantly high residuals in the regres-sion model were observed in the Prepuna and the north-ern Monte Desert, indicating that these two cells havemore species than can be attributed to random change. Itcould be that the climatic maps used, which were ob-tained by smoothing data points from weather stations,failed to adequately represent the real environmentalconditions at these sites. We have found no reason for anartefact of this sort to occur in this region more thanothers, but the possibility cannot be completely ruledout. In some cases, high species richness areas havebeen associated with oversampling (Nelson et al. 1990),as plant collecting is subject to several sources of biases:(a) some regions are more accessible than others, andthe collection efforts may be heterogeneous and (b)many experts prefer rarities, and common species maybe poorly represented in collected samples. In our case,however, undercollection was controlled by includingour measure of collection effort into the model. Addi-tionally, the collection intensity in these two sites (82and 61 specimens) was well above the average. An


alternative explanation can be found in the environmen-tal history of these cells. Present environmental condi-tions may not explain the extraordinarily high speciesrichness of these sites because past events may be re-sponsible for the present species density. Possibly thePrepuna and northern Monte functioned as a refuge forcacti during Pleistocene glacial events; this may still bereflected in their present high species richness. It hasbeen suggested that the central Monte, as opposed to thePuna and the Chaco Provinces, experienced periods ofhigh humidity during the Quaternary (Axelrod 1958;Tricart 1970; Vuilleumier 1971; see further Markgraf1983, 1985, 1989 on South-American paleoclimates).

Acknowledgements. The authors acknowledge support fromRoberto Kiesling and Omar Ferrari during C. Mourelle’stravels in Argentina. This paper is part of the first author’sdoctoral research at UNAM, supported by a scholarship fromthe Noyes-Smith Sciences Foundation. Financial support wasreceived from the National Council of Science and Technol-ogy (CONACYT). Constructive comments by Michael Palmeron the first version of this paper are gratefully acknowledged.

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Received 7 June 1995;Revision received 6 January 1996;

Accepted 29 January 1996.


Pterocactus kuntzei K. SchumannPterocactus meglioli R. KieslingPterocactus pumilus Britton & RosePterocactus reticulatus R. KieslingPterocactus valentinii SpegazziniPuna clavarioides (Pfeiff.) KieslingPuna subterránea (R. E. Fries) R. KieslingTephrocactus alexanderi (Br. & Rose) Backbg.Tephrocactus aoracanthus (Lem.) Lem.Tephrocactus articulatus (Pfeiff.) Backbg.Tephrocactus articulatus (Pfeiff.) Backbg.Tephrocactus geometricus (Cast.) Backbg..Tephrocactus halophilus (Speg.) Backbg.Tephrocactus molinensis (Speg.) Backbg.Tephrocactus weberi (Speg.) Backbg.

GLOBOSE CACTIAcanthocalycium glaucum RitterAcanthocalycium thionathum (Speg.) Backbg.Acanthocalycium violaceum (Werd.) BackbgAustrocactus bertinii Britton et RoseAustrocactus dussenii Speg.Austrocactus patagonicus Hoss.Blossfeldia liliputana Werd.Echinopsis ancistrophora Speg.Echinopsis aurea Br. et RoseEchinopsis eyriesii (Turp.) Zucc.Echinopsis mamillosa GürkeEchinopsis obrepanda (S.-D.) K. SchumannEchinopsis silvestrii Speg.Echinopsis tubiflora (Pfeiff.) Zucc.Frailea castanea Backbg.Frailea cataphracta Britton et RoseFrailea grahliana Britton et RoseFrailea mammifera Buining et BrederooFrailea pygmaea Britton et RoseFrailea shilinzkyana (HGE. jr.) Britton et RoseGymnocalycium andreae KrainzGymnocalycium asterianum CastellanosGymnocalycium baldianum Speg.Gymnocalycium brucchii (Speg.) Hoss.Gymnocalycium brucchii Hoss.Gymnocalycium calochlorum (Bödek.) Y. ItoGymnocalycium capillaense (Schick) Backbg.Gymnocalycium capillensis Hoss.Gymnocalycium castellanosii Backbg.Gymnocalycium denudatum PazoutGymnocalycium ferrarii RauschGymnocalycium gibbosum Backbg.Gymnocalycium glaucum RitterGymnocalycium horridispinum FrankGymnocalycium huachinensis SchützGymnocalycium hybopleurum Backbg.Gymnocalycium kieslingii FerrariGymnocalycium marsoneri Y.ItoGymnocalycium mazanense Backbg.Gymnocalycium mesopotamicum R. KieslingGymnocalycium mihanovichii Britton et RoseGymnocalycium mostii Britton et RoseGymnocalycium multiflorum (Hook)Gymnocalycium nidulans Backbg.Gymnocalycium parvulum Speg.Gymnocalycium platense (Speg.) Britton et RoseGymnocalycium pugionacanthum Backbg.Gymnocalycium quehlianum Vaupel.Gymnocalycium ragonesei Castell.Gymnocalycium ritterianum RauschGymnocalycium saglionis Britton et RoseGymnocalycium sanguiniflorum Werderm.Gymnocalycium schickendantzii (Web.) Britton et RoseGymnocalycium schroederianum v. OstenGymnocalycium spegazzini Backbg.Gymnocalycium stuckertii Britton et RoseGymnocalycium tanigaensis Pilz.Gymnocalycium triacanthum Backbg.Gymnocalycium valnicekianum JajóGymnocalycium vatteri Buin.Gymnocalycium wessianum Backbg.Lobivia cachensis Britton et RoseLobivia chrysantha (Backbg.) RauschLobivia densispina WerdermannLobivia einsteinii M. FricLobivia famatimensis (Speg.) Britton et RoseLobivia haemathanta (Spegazzini) Britton et RoseLobivia iridiscens Backbg.Lobivia jajoiana Backbg.Lobivia kieslingii RauschLobivia pygmaea (R.E.Fr.) Backbg

Lobivia saltensis (Spegazzini) Britton et RoseLobivia sanguiniflora Backbg.Lobivia schreiteri Castell.Lobivia shaferi Britton et RoseLobivia steinmannii (Solms-Laub.) Backbg.Lobivia stilowiana Backbg.Lobivia walteri R. KieslingNeowerdermania vorwerkii FricParodia auricentra Backbg.Parodia chrysacanthion (Schum.) Backbg.Parodia faustiana Backbg.Parodia linkii (Lehm.) R. KieslingParodia maasii (Heese) Berg.Parodia microsperma (Web.) Speg.Parodia nivosa Backbg.Parodia ottonis (Lehmann) N.P. TaylorParodia penicillata Fescher et Van der steegParodia schuetziana JajóParodia setifera Backbg.Parodia stuemeri (Werd.) Backbg.Parodia submammulosa R. KieslingParodia turecekianus R. KieslingPyrrhocactus andreanus (Backbg.) RitterPyrrhocactus atroviridis RitterPyrrhocactus bulbocalix (Werderm.) Backbg.Pyrrhocactus pachacoensis RauschPyrrhocactus sanjuanensis (Speg.) Backebg.Pyrrhocactus straussianus BergerPyrrhocactus villicumensis RauschRebutia calliantha BewerungeRebutia einstenii FricRebutia fiebrigii (Gürke) Britton et RoseRebutia margaretae RauschRebutia minuscula SchumannRebutia pseudominuscula SpegazziniSetiechinopsis miriabilis (Speg.) De HaasWeingartia neumanniana (Backbg.) Werd.Wigginsia tephracantha (Speg.) D.M.Porter

EPIPHYTIC CACTIEpiphyllum phyllantum (L.) HaworthPfeiffera ianthothele (Monv.) Web.Rhipsalis aculeata WeberRhipsalis baccifera (Mill.) StearnRhipsalis cereuscula HaworthRhipsalis cruciformis Vell.Rhipsalis houlletiana LemaireRhipsalis linearis SchumannRhipsalis lorentziana GrisebachRhipsalis lumbricoides (Lem.) Lem.Rhipsalis monacantha GrisebachRhipsalis shaferi (Britton et Rose)Rhipsalis tucumanensis WeberSelenicereus setaceus (S-D) Berger

PERESKIOID SPECIES (not included in the analyses)Pereskia aculeata MillerPereskia sacharosa Griseb.Pereskia nemorosa Rojas AcostaQuiabentia pflanzii (Vaup.) BergerQuiabentia chacoensis Backeberg

App. 1. List of Argentine cactus species included in this study.

COLUMNAR CACTICereus aethiops HaworthCereus argentinensis Br. et Rose (Britt. and Rose)Cereus chalybaeus Hauman (non Otto)Cereus dayami Speg.Cereus forbesii HaworthCereus hankeanus Web.Cereus stenogonus K. Sch.Cleistocactus baumannii (Lem.) LemaireCleistocactus ferrarii R. KieslingCleistocactus jujuyensis (Backbg.) Backbg.Cleistocactus smaragdiflorus (Web.) Britton et RoseDenmoza rhodacantha (SD) Britton et RoseEchinopsis leucantha (Gill.) Walp.Echinopsis rodotricha R. MeyHarrisia bonplandii (Parmentier) Britton et RoseHarrisia martinii (Labouret) Britton et RoseHarrisia pomanensis (Weber) Britton et RoseHarrisia tortuosa (Forbes) Britton et RoseLobivia chrysochete WerdermannLobivia ferox Britton et RoseLobivia formosa (Pfeiff.) Britton et RoseLobivia koretroides (Werd.) Backbg.Lobivia walteri R. KieslingMonvillea cavendishii (Monville) Britton et RoseMonvillea spegazzini (Weber) Britton et RoseNotocactus shumannianus BergerOreocereus celsianus (Lemaire) RiccobonoOreocereus trollii KuppPyrrhocactus umadeave (Werd.) Backbg.Stetsonia coryne (Salm-Dyck) Britton et RoseSoehrensia brucchi (Br. et Rose) Backbg.Trichocereus andalgalensis (Web.) HosseusTrichocereus angelesii R. KieslingTrichocereus cabrerae R. KieslingTrichocereus candicans (Gillies) Britton et RoseTrichocereus fabrisii R. KieslingTrichocereus huascha (Web.) Britton et RoseTrichocereus lamprochlorus (Lemaire) Britton et RoseTrichocereus pasacana (Web.) Britton et RoseTrichocereus pseudocandicans (Backbg.) ex R. KieslingTrichocereus rowleyi (Friedr.) R. KieslingTrichocereus schickendantzii (Web. ) Britton et RoseTrichocereus smirzianus (Backbg.) BackebergTrichocereus spachianus (Lem.) Ricc.Trichocereus strigosus (Salm-Dyck) Britton et RoseTrichocereus tarijensis (Vpl.) WerdermannTrichocereus terscheckii (Parm.) Britton et RoseTrichocereus thelegonoides (Speg.) Britton et RoseTrichocereus thelegonus (Web.) Britton et RoseTrichocereus vatteri Kiesling

OPUNTIOID CACTIAustrocylindropuntia shaferi (Britton et Rose)Austrocylindropuntia verschafeltii (Cels. & Web.) Backbg.Austrocylindropuntia vestita (Salm-Dyck) Backbg.Cylindropuntia tunicata (Lehm.) KnuthMaihueniopsis boliviana (S.-D.) R. KieslingMaihueniopsis darwinii (Hensl.) RitterMaihueniopsis minuta (Backbg.) R. KieslingMaihueniopsis nigrispina (K. Schum.)Maihueniopsis ovata (Pfeiff.) RitterMaihueniopsis pentlandii (S.-D.) R. KieslingOpuntia arechavaletai Speg.Opuntia aurantiaca Lindl.Opuntia brasiliensis (Will.) Haw.Opuntia brunescens Britt. et RoseOpuntia chakensis Speg.Opuntia cordobensis Speg.Opuntia corrugata Salm-DickOpuntia delaetiana Web.Opuntia discolor Britton & RoseOpuntia halophila Speg.Opuntia penicilligera Speg.Opuntia quimilo SchumannOpuntia retrorsa Speg.Opuntia salagria CastellanosOpuntia salmiana Parm. ex Pfeiff.Opuntia schickendantzii WeberOpuntia soehrensii Britton et RoseOpuntia subsphaerocarpa Speg.Opuntia sulphurea Salm-DickOpuntia wetmorei Britton et RosePterocactus araucanus CastellanosPterocactus australis (Weber) Backbg.Pterocactus fisherii Britton et RosePterocactus gonjianii R. KieslingPterocactus hickenii Britton et Rose

copyright noticecertain cells. log-linear regression models accounted for a large portion of the...

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