Plant Ecology 147: 205–218, 2000.© 2000Kluwer Academic Publishers. Printed in the Netherlands.

205

Patterns of abundance of a narrow endemic species in a tropical andinfertile montane habitat

Katia T. Ribeiro∗ & G. Wilson FernandesEcologia Evolutiva de Herbivoros Tropicais, DBG/ICB/Universidade Federal de Minas Gerais, CP 486, BeloHorizonte MG 30161-970, Brazil; (∗Present adress: Ecologia Vegetal, Depto Ecologia, IB/CCS/UniversidadeFederal do Rio de Janeiro, CP 68020, Rio de Janeiro, RJ 21941-590, Brazil) (e-mail: ktorres@acd.ufrj.br)

Received 23 June 1998; accepted in revised form 8 October 1999

Key words: Aggregation patterns,Coccoloba cereifera, Fire, Geographic distribution, Habitat favorability,Soil specificity

Abstract

We examined the entire spatial distribution of a narrow endemic shrub (Coccoloba cereifera, Polygonaceae) inSerra do Cipó, Brazil. We tested the hypothesis that a narrow endemic species would show a gradual decline ineither size and density towards the edges of its distribution. The contribution of soil specificity and post-fire growthto C. cereiferaabundance and distribution were also investigated.C. cereiferashowed multimodal and highlyaggregated distribution pattern at several scales, from 25 m2 to 3000 m2 (blocked quadrat variance analyses). Thispattern seems to be strongly related to the predominance of clonal recruitment and to the close association ofthe species to sandfields, which have discrete distribution between gallery forests and rocky outcrops. Populationdensity did not decline towards the edge of the species distribution. Plants near the distribution boundaries hadslightly more leaves and more inflorescences per plant (p < 0.005), but there was no significant change in themean number of ramets per clone. The absence of large plants in some populations at the center of the speciesdistribution may be related to the higher frequency of fire in this region, killing aerial plant parts. Nearly allaggregations had inverse-J shaped size-distribution, suggesting effective recruitment of ramets, most frequentlyvia asexual reproduction. Similar patterns of plant abundance may be common in fire-prone habitats characterizedby infertile, and well-drained soils since these areas generally have high numbers of endemic plants, with strongsoil specificity. Possible mechanisms for the observed pattern are discussed considering current models concerningdistribution of abundance of species.

Nomenclature: Howard (1960).

Introduction

The distribution patterns of species are highly relevantin ecology, biogeography, and conservation biologybecause they strongly affect processes like predation,parasitism, competition, herbivory, pollination, spe-ciation, and local extinction (Huffaker 1958; Hassel& May 1974; Begon et al. 1986; Kareiva 1986;Simberloff & Cox 1987; Hanski 1994). There is a con-sistent spatial pattern emerging from several data sets:many bird, mammal, and plant species have higher

densities at the center of their distribution, with agradual decline towards the edges (Whittaker 1956;Rapoport 1982; Brown 1984). Whether changes arereally gradual or highly multimodal is a matter ofmuch debate, and possibly a question of scale (Taylor& Taylor 1977; Brown 1984; Lawton 1993).

Brown (1984) proposed a model to explain thegradual decline in density and the positive correla-tion between local abundance and distribution amongclosely related species. The model argues that habi-tat quality for a species is set by a combination of

206

many biotic and abiotic factors (see also Hutchinson1957), some of which are expected to be sufficientlyindependent from each other as to generate many envi-ronmental combinations in space. Furthermore, manyfactors are spatially autocorrelated, i.e. habitats withsimilar environmental conditions tend to be near eachother. Thus, favorable sites would be aggregated, withfavorability decreasing as a continuous function of dis-tance from the place where the best conditions arefound.

Some exceptions were already predicted in this pa-per. For example, species with a distribution largelylinked to a single environmental factor may haveabrupt changes in density, and situations where habi-tat similarity does not follow a continuous decreasingfunction of distance may produce multi-modal pat-terns of abundance. One assumption of the model isthat population densities reflect the habitat quality forthe species (but see Taylor & Taylor 1977; Pulliam1988; Brown 1995). There are obvious limitationsto this premise – for example, the intrinsic time-lagsin population responses. Nevertheless, Brown et al.(1995) reported a large constancy in abundance ranksof passerine birds in North America when differentsites are compared through time, what suggests at leastsome correspondence between abundance and habitatcharacteristics. However, this correspondence may beviolated by strong disturbances, mainly if they are un-predictable in time and space, and if the species havelarge time-lags in population responses (May 1975).Fire is an example of a high-intensity disturbance fac-tor with heterogeneous distribution in time and space.The mosaic of altered conditions with variable favora-bility created by a fire event is not readily reflected inspecies densities, and the time required for such a cor-respondence depends on the biology of each species.Time-lags in population responses vary according tothe type of response to fire (p. ex., resprouters, ob-ligate seeders), growth rate, and propagule avaiability,for instance (Zammit 1988; Pate 1993; Whelan 1995).Nevertheless, since fire intensity and frequency affectthese parameters, fire history is a characteristic of thehabitat, and should be included as an axis of the multi-dimensional habitat volume in the model proposed byBrown (1984).

A more general pattern seems to be the highclumping of individuals in a few sites and scarcityacross most of the species range, irrespective of therelative positions of high and low density sites. Brownet al. (1995) proposed a model to explain this pat-tern which is quite similar to the previous one, except

that environmental variables are not necessarily auto-correlated in space, thus embracing also multi-modaldistributions.

The processes behind these patterns are controver-sial (e.g., Hanski 1982; Pulliam 1988), but the patternshold for many species. Nevertheless, their generalityawaits further field evaluation, since few data exist onthe abundance distributions of rare (sensuRabinowitzet al. 1986) species (Brown 1984; Brown et al. 1995).These species, either geographically restricted or withgenerally low abundance, constitute a large fraction ofspecies, especially when tropical plants and insects areconsidered (Gentry 1986; Lawton 1993).

The aim of this study is to verify if a range-restricted but locally abundant plant,Coccolobacereifera Schwn. (Polygonaceae), shows a gradualdecline in either density or size (number of leaves,number of ramets) towards the edges of its distrib-ution. The variation in density and plant size acrossthe distribution, and the degree of soil specificity wereinvestigated. Since fire is of common occurrence inthis region, we also looked at the effects of fire on thedistribution patterns ofC. cereifera.

Methods

Site and species descriptionThe study was conducted in the Serra do Cipó,

southeastern Brazil (43◦30′–40′W, 19◦10′–20′ S; Fig-ure 1). Serra do Cipó is at the southernmost portionof Espinhaço Mountains, a predominantly quartziticrange extending for 1100 km (10◦–20◦S) in centralBrazil (Rizzini 1979). Above 1000 m soils are shallow,acid, nutrient-poor, and has excessively drained sandsthat are highly erodable (Freitas & Silveira 1977).Quartzitic outcrops are common and in their crevicesa more humic soil may be found (Freitas & Silveira1977). The regions above 1000 m along the EspinhaçoMountains support a highly xerophytic vegetation withhigh plant species diversity and endemism (Rizzini1979; Giulietti et al. 1987). These areas, termed rupes-trian fields, have shrubby, tortuous and sclerophyllousvegetation or open grasslands (Rizzini 1979). Climateis characterized by dry winters and rainy summerswith an average annual rainfall of 1500 mm and meantemperature of 17.4–19.8◦C (Galvão & Nimer 1965).

Coccoloba cereifera, hereafter refered to asCoc-coloba, is a highly sclerophyllous shrub 2 m tall,and because of the unusual bluish-purple color of itsleaves, it is conspicuous against the open grassland

207

Figure 1. Distribution ofCoccoloba cereifera. (a) Serra do Cipo is located in the southernmost portion of the Espinhaço Mountains, in Brazil.(b) Serra do Cipo National Park.Coccoloba cereiferais found in the area within the square represented in the map. (c) Distribution ofCoccolobacereiferain further detail: dotted areas correspond to aggregations of the species.

of Serra do Cipó where it is endemic (Rizzini 1979;Giulietti et al. 1987).Coccolobais found in a sin-gle valley within an area of only 26 km2 (Ribeiro& Fernandes at press). Plants have branches growingfrom a lignotuber, a common structure amongcer-rado plants, found in more than 100 genera (Rizzini1979). After fire, aerial parts ofCoccolobadie back,but are not entirely carbonized due to a thick waxcover. Damaged plants resprout vigorously from tu-bers, forming very branched clones (K.T. Ribeiro,unpublished data). Each ramet has successive flower-ing periods and plants reproduce at any season, evenduring drought (April–September).

Sampling

Samples were taken across the entire distribution ofCoccoloba, using two perpendicular north-south/west-east transects which crossed at the geometric center ofthe species distribution (see Ribeiro & Fernandes; inpress). To determine variations in plant density and

size, and soil types, adjacent quadrats of 5× 5 mwere established along the transects. All ramets andclones within quadrats were counted. In this study,clones were defined as groups of ramets rising froma convergent point in the soil. Height, total num-ber of leaves and total number of inflorescences werecounted on all ramets. Both north and west transectswere 2500 m long and had 500 quadrats of 25 m2

each. The east transect was 3100 m long and had 620quadrats while the south transect was 3300 m longand had 660 quadrats. Overall, we sampled 5.7 ha in2280 quadrats and recorded 10 660 ramets and 4136clones, with an average of 4.7 ramets per clone. Sinceall analyses considering patterns in ramet or cloneabundance produced similar results, due to the strongcorrelation between number of ramets and number ofclones per quadrat (y = −3.16+ 0.97x; r2 = 0.95;F1,468 = 8016.0; p < 0.0001;n = 470), only theresults concerning the abundance of ramets will bereported, except when size-frequency distribution ofclones is considered.

208

Figure 2. Abundance frequency distribution of ramets ofCoccoloba cereiferain quadrats of 25 m2. Left figures (a–c): ranked abundance values(log). Right figures (b–d): abundance frequency distribution of quadrats. Bottom and top figures correspond to different groups of quadrats,each one composed of non-neighboring quadrats: adjacent quadrats were considered separately to avoid counting the same individual twice(see Brown et al. 1995).

Abundance throughout the distribution

As Coccolobashows a clear and highly aggregateddistribution (Figures 2 and 3a,c), problems in dataanalysis derived from the spatial autocorrelation ofvariables could emerge. To describe the scales of ag-gregation, the Hill’s (1973) two-term local quadratvariance method (TTLQV), designed for belt tran-sects, was used. Aggregated distribution was detectedon all scales of analysis, from 25 m2 to 3000 m2

(Figure 3b,d). Spatial autocorrelation analyses on theabundance of ramets and clones were carried out atvarious scales (1, 2, 5, 10 and 20 blocked adjacentquadrats), to identify at which scales these values werespatially independent. Only at the scale of 100 lin-ear meters (20 blocked adjacent quadrats) abundancevalues were not autocorrelated; therefore, all furtherregression analyses will be made at this scale.

As the decrease in abundance towards the distri-bution boundaries is often related to a concomitantreduction in the number of occupied sites (ubiquity)

and in the mean density of individuals within occu-pied sites (mean local density) (see Brown 1984), weverified whether there was a decline in either ubiquityor mean local density ofCoccolobaramets accordingto distance from the center of distribution. Directionof the transects and arrangement of soil types wereincluded in the regression models. Furthermore, abun-dance ofCoccolobaramets (total number os rametsin all 20 adjacent quadrats) was regressed against thedistance to the center of the distribution, arrangementof soil types, ubiquity, and direction of each transect.All values were calculated for blocks of 20 adjacentquadrats (500 m2), for the reasons explained above.Arrangement of soil types was considered as the pro-portion of quadrats on sandy soils in detriment of othersoil types, sinceCoccolobawas strongly associatedwith sandy sites (see below). Ubiquity was consideredas the proportion of quadrats with plants. Values ofubiquity and proportion of quadrats on sands were arc-sin square-root transformed, and those of abundanceand mean local density were square-root transformed,

209

Figure 3. Abundance ofCoccoloba cereiferaramets along West-East (a) and North-South (c) transects, in groups of 20 adjacent quadrats(500 m2), and results of the two-term local quadrat variance TTLQV analyses for ramet abundance along West–East (b) and North–South (d)transects.

to meet normality. Direction of transects was a dummyvariable.

Plant size throughout the distribution

To verify whether there was a decline in plant sizeand flowering towards the edge of the species distri-bution, the mean number of ramets per clone, mean

number of leaves per clone, and mean number of inflo-rescences per clone in groups of 20 adjacent quadrats(500 m2) were individualy regressed against distancefrom the center of distribution. Each model also in-cluded the effects of the direction of each transect(dummy variable). Data on the mean number of leavesand mean number of ramets were log transformed,

210

and mean numbers of inflorescences were square-roottransformed.

Logistic regressions were performed to describethe relationship between plant size and probability offlowering, considering the size-frequency distributionof all sampled ramets and clones and the proportionof flowering plants in each size class. Ramets wereseparated into classes of 20 cm, while clones were sep-arated into classes of 25 leaves, according to their totalnumber of leaves. Total number of leaves was used asan indicator of clone size.

Aggregations of plants were distinguished alongthe transects to allow a description of the variationin size-frequency distribution of ramets and clonesand also in the proportion of flowering plants overCoccolobadistribution. Aggregations were arbitrarilydefined as groups of plants separated by at least 100 m(20 quadrats), a distance near the mean clump size ofCoccolobapatches.

Soil specificity

To quantify the association ofCoccolobawith soiltypes, each 25 m2 quadrat was classified according to

211

Figure 5. Size frequency distribution of ramets (black bars) in classes of 20 cm and proportion of flowering plants per height class (lineand open squares) within aggregations along each transect, from the center of distribution towards the edges. Each graph corresponds to oneaggregation. The extent of each aggregation is represented by the enlargements in the lines above each graph. The numbers above aggregationsindicate their number of ramets.

the following soil categories: sand, gravel, quartziticoutcrops, bogs, and clay. To verify the relation-ship between soil and vegetation type, each quadratwas also categorized according to physiognomically-defined vegetation type: sclerophyllous shrubland,grassland, gallery forest, and secondary forest. Wealso categorized the landscape according to its incli-nation: level;<15◦, 15◦–30◦, and>30◦. Soils whereCoccolobawas found most frequently, namely sand,gravel, and soil between rocky outcrops, were sampledfor chemical and granulometric analyses.

Frequency of occurrence (presence/absence data)of Coccolobaand the abundance of ramets in quadratson each soil category were used to test the associationof Coccolobato soil types using the G test (Sokal &Rohlf 1995). The association between soils, vegeta-tion, and slope inclination was analyzed using con-tingency tables, through a log-linear analysis (Sokal& Rohlf 1995). To reduce the number of empty cells,analyses included only quadrats on sands, gravels, androcky outcrops. Gallery and secondary forests weregrouped in the category named ‘others’, and quadratson terrain above 30◦ inclination were excluded dueto their small number and to the general absence ofCoccolobaon them.

Fire effects

Since we were interested in establishing the extent towhich habitat favorability may be masked by recentfires due to sudden changes in plant size and abun-dance, we asked the following questions: (a) are heightand leaf production rates similar between burned andunburnedCoccolobaplants?; (b) what is the requiredtime for a newly emerged ramet from a burned plant toflower after fire?; and (c) does the size-frequency dis-tribution of ramets from burned and unburned quadratsdiffer?

To answer the first two questions, growth rates[height (cm) and number of leaves per ramet] andnumber of flowering branches of 120 randomly se-lected ramets were surveyed every two months fromJanuary 1996 to January 1997. From the 120 ramets,30 ramets were from a population burned in Septem-ber 1995, and 90 ramets from a population with noindication of fire. From the 90 ramets of the unburnedpopulation, 60 had not produced any inflorescenceswhile the other remaining 30 were flowering. This dis-tinction was necessary since flowering impairs growthuntil inflorescences become dry (K.T. Ribeiro, per-sonal observation). The initial height (mean± SE) ofplants in the burned population was 32.2± 15.6 cm,and the number of leaves was 7.4± 2.6. The cor-

212

Figure 6. Growth and phenology of ramets of burned and unburnedCoccoloba cereiferaplants. (a) Increase in height (open circles) andnumber of leaves (solid circles) for each plant group (mean and 95%confidence interval); (b) relationship between growth rate and initialplant size (height); (c) relationship between rate of increase in leafnumber and number of leaves per plant; (d) number of floweringramets (%) through time. Each group of plants is represented bydifferent symbols:• burned plants;◦ esterile ramets from unburnedplants;∗ flowered ramets from unburned plants.

responding data for non-flowering ramets in the un-burned population was 59.8± 30.2 cm and 10.5±6.5 leaves, while for flowering ramets was 133.9±43.3 cm and 29.7± 19.9 leaves. Growth rates (height)between groups were compared with an ANOVA.Growth rates (leaves per ramet) were compared withthe Kruskal–Wallis test, since data had normal dis-tribution but not homogeneous variances, even aftertransformations (Sokal & Rohlf 1995).

Size-frequency distribution of ramets from re-cently burned and for long unburned plants werecompared by Kolmogorov–Smirnov test. All quadratsalong the transects were classified as burned or un-burned whenever possible, and those with problematicclassification were excluded from analyses. Burnedsites are easily recognizable due to the presence ofblack, carbonized material on the stems ofCoccolobaas well as on other plants such asVellozia spp. andPaepalanthusspp. in the same plot.

Results

Abundance throughout the distribution

We found no trends forCoccolobaubiquity towardsthe center of distribution. Nevertheless, ubiquity waspositively related to the proportion of quadrats onsands (ubiquity= 0.18 + 0.51sands, r2 = 0.26,F1,112 = 39.05, p < 0.001). Mean local density ofCoccolobaramets was also positively influenced bysandy soils whereas it had no significant relationshipeither with distance from the center of distribution ordirection of the transects (mean local density= 1.48+0.37sands, r2 = 0.13, F1,111 = 17.20, p < 0.001).Although significant, these models explained a smallfraction of the observed variation; this may in part berelated to the proportion of quadrats without plantson all soil types (79.4%). Abundance ofCoccolobaramets was positively related to ubiquity (abundance= 0.63+ 0.81ubiquity, r2 = 0.65, F1,111 = 210.24,p < 0.001), but had no significant relationship witheither distance from the center of distribution, pre-dominance of sandy soil, or direction of the transects.There was an extreme value of abundance and meanlocal density at the end of the south transect thatlargely improved the two last regression models whenremoved.

Although the large number of quadrats withoutplants possibly obscured the influence of soil type onCoccolobaspatial pattern, a graphic display show-ing the proportion of quadrats with each soil type in

213

groups of 20 adjacent quadrats and the proportion ofthe quadrats withCoccolobamakes clear the relation-ship betweenCoccolobaand the distribution of sandysoils (Figure 4).

Plant size throughout the distribution

There was a slight increase in the number of leaves perclone towards the edges of distribution (mean numberof leaves= 8.48+ 0.28distance+ 0.21direction, r2 =0.16,F2,69 = 5.96,p < 0.05). Otherwise, we foundno trend in the mean number of ramets per clone.Conversely, clones tended to support more inflores-cences towards the edges of distribution, irrespectiveof transect direction (mean number of inflorescences= 0.10+ 0.461distance, r2 = 0.21, F1,70 = 18.91,p < 0.001).

Size-frequency distribution of all sampled rametspresented an inverse-J shaped curve. Size-frequencydistribution of clones had similar shape, but someintermediate classes were not represented. The prob-ability of flowering for either ramets or clones wasstrongly influenced by plant size (logistic regression,ramets:y = 2e−5.43+1.14x; r2 = 0.62;n = 20; clones:y = e−4.48+1.69x; r2 = 0.50; n = 20), althoughflowering plants were found in all size classes.

Twenty-two out of the 27 aggregations of plantsdefined along the transects had ramet size-frequencydistribution similar to the inverse-J shape curve. Thefirst size class (ramets up to 20 cm) was less repre-sented than the other classes in three aggregations.Four aggregations had no flowering ramets, whichseems to be due to the absence of large plants (Fig-ure 5). In spite of a large variation in ramet size, therewas some constancy in clone size because small clonesclearly prevail in all aggregations (data not shown).

Soil specificity

Sandy soils, gravelly soils, and rocky outcrops oc-cured at similar frequencies along the transects. Thesethree edaphic habitats represented 87.5% of the 2280quadrats of 25 m2. Only 6% of the quadrats were onclay soils, 2.1% on bogs and the remainder locatedabove streams (0.7%), roads (0.9%), or places wherethe classification into soil categories was dubious(2.8%).

Ramets ofCoccolobawere more abundant (G=5263.0; d.f. = 3; p < 0.0001) and more frequenton sandy soils (G= 271.7; d.f. = 3; p < 0.0001;

Table 1). Moreover, soil types, vegetation types, andground inclination were not independently distributed(log-linear analysis: model without interactions:χ2 =1785.93; d.f. = 20; p < 0.0001). The best-fit modelincluded the main effects and paired interactions be-tween the three variables (χ2 = 1785.93; d.f.= 20;p = 0.276). Sandy soils were frequently associatedwith flat terrain and open vegetation (grassland withshrubs likeCoccoloba) (Table 2). Soil types differedmainly in texture (Table 3).

Fire effects

In the first year after fire, burned plants had sig-nificantly higher growth rates than unburned plants,either in terms of height (burned: 1.205%; no flow-ers: 0.087%; flowering: 0.056%;F2,102 = 35.312;p < 0.0001; planned comparison between burnedand unburned plants:F1,99 = 68.550; p < 0.0001)or in number of leaves (burned: 1.567%; no flowers:0.258%; flowering: 0.114%; Kruskal–Wallis (2,102)= 38.963;p < 0.0001; Figure 6a). This result doesnot seem to be an artifact due to differences in theinitial plant size between groups, since differences ingrowth rate between groups are evident when plantof similar size are compared (Figures 6b,c). Rametsfrom unburned plants may support flowers and fruitsthroughout the year, and some ramets from burnedplants were able to flower in the next year followingfire (Figure 6d).

High growth rates of burned plants allow rapid re-turn to original size structure, as is suggested by thesimilar size-frequency distribution of ramets in burnedand unburned quadrats along the 4 transects (664 ram-ets in 57 burned quadrats and 1236 ramets in 54unburned quadrats; Kolmogorov–Smirnov:p > 0.05;Figure 7).

Discussion

Abundance patterns

Few plant species have been thoroughly quantifiedwithin their entire range. From the few studies made,some showed a decline in the proportion of occupiedquadrats, but not in local densities (Carter & Prince1988), while Rapoport (1982) found a decline in bothdensity and ubiquity for the palmCopernica alba.The same pattern was reported by Brown (1984) forbreeding bird species in North America. In the case ofCoccoloba, there was no decline in abundance, mean

214

Table 1. Abundance and frequency ofCoccolobaon different soil types.

Soil types Number of quadrats (%) Number of Number of

ramets (%) clones (%)

Total Occupied

Sand 827 (36.3) 310 (37.5) 8907 (83.5) 3331 (80.5)

Gravel 562 (24.6) 83 (14.8) 843 (7.9) 397 (9.6)

Rocky outcrops 558 (24.5) 62 (11.1) 749 (7.0) 348 (8.4)

Clay 136 (6.0) 15 (11.0) 147 (1.5) 60 (1.5)

Bog 49 (2.1) 0 0 0

Other 148 (6.5) 0 0 0

Total 2280 470 (20.6) 10 660 4136

Table 2. Observed (O) and Expected (E) values for frequency of soil types, vegetation types,and slope inclination along transects. Expected values were based on a log-linear model con-sidering only the main effects (Sokal & Rohlf 1995). The best model included the main effectsand paired interactions between the three variables.

Categories Soil

Sand Gravel Rocky outcrop

Inclination Vegetation 0 E O E O E

Plain Grassland 490 241.2 113 160.9 45 169.2

Shrubland 0 59.97 0 40.01 46 42.07

Ohter 21 7.64 12 5.1 0 5.36

Up to 15◦ Grassland 288 244.2 221 162.9 60 171.3

Shrubland 3 60.71 0 40.51 152 42.59

Other 9 7.73 3 5.16 0 5.43

15◦ to 30◦ Grassland 29 174.3 210 116.3 102 122.3

Shrubland 0 43.33 0 28.91 183 30.4

Other 0 5.52 0 3.68 0 3.87

Table 3. Soil chemical and texture data for different soil types. Each soil type was represented by one sample consisting of 20 differentlocalities.

Soil type/analysis P K Al Ca Mg pH % C % m Gravel Coarse Thin Silt+sand sand clay

(mg dm−3) (c mol c.dm−3) (H2O)

Sand 2.0 21.0 2.0 0.1 0.1 4.4 1.24 92.16 0 13.0 73.0 14.0

Gravel 1.8 16.0 1.3 0.3 0.2 4.8 0.35 72.0 54.9 17.5 9.9 17.7

Rocky outcrops 3.0 36.0 3.0 0.2 0.01 4.2 2.82 90.63 0 6.0 74.0 20.0

215

local density or ubiquity from the center to the bound-aries of the distribution. Further, clones and ramets ofCoccolobawere not smaller at the edges of distribu-tion, as should be expected if these regions representworse habitat conditions for the species. Clones hadslightly more leaves and inflorescences towards theedges, and aggregations without flowering plants wereconcentrated in the center of the distribution.

Coccolobahad aggregated distribution at all con-sidered scales, from 25 to 3000 m2, with few sites har-boring a large fraction of the sampled plants. This ag-gregation seems to be strongly related to clonal growthand to scattered distribution of sandfields, but the re-sulting pattern (Figure 2) is reported for organismsshowing completely different bionomic characteris-tics, such as mammals, birds, plants, and parasites,sampled at contrasting scales (Brown 1995). Accord-ing to the model of Brown et al. (1995), this patternmay arise when several environmental factors that af-fect the species are relatively independent from eachother, and there are few sites where the best conditionsat each environmental axis are found together. Thesesame arguments, plus the assumed correspondence be-tween habitat favorability and population abundance,have been used to explain the gradual decline in den-sity towards the edges of a species range (Brown1984), a pattern not found forCoccoloba. Neverthe-less, the latter model considered that environmentalfactors are usually spatially autocorrelated, so thatsimilar sites tend to be near each other. One may com-bine both models to explainCoccolobapatterns: thestrong aggregation ofCoccolobaat few sites may bederived from the combination in space of many in-dependent environmental factors that rarely result inthe best conditions for the species, and an importantenvironmental factor, e.g., sandy soils, has discretedistribution, generating a multimodal pattern of abun-dance, as predicted by Brown (1984). Nevertheless,one must find a way to avoid tautological mechanisms,such as looking for environmental factors not spatiallyautocorrelated whenever a species shows multimodalpatterns of abundance. Further, all species have mul-timodal distributions depending on the chosen scale(Taylor & Taylor 1977; Lawton 1993)

It is also interesting to note that the comparisonsof boundary characteristics of animal and plant distri-butions may be complicated by the fact that samplingschedules are often designed to gather mature or estab-lished individuals and, for plants, mature individualsare nearly always found in places where establishmentis or has been possible for the species, whereas adult

Figure 7. Size frequency distribution ofCoccoloba cereiferarametsfrom quadrats clearly not affected by recent fire events (gray bars;1236 ramets in 54 quadrats) and from quadrats with signs of fire, likecoal on plants (black bars; 664 ramets in 57 quadrats). There was nosignificant difference between groups (Kolmogorov–Smirnov test,p = ns).

animals may be sampled far away from sites favorablefor growth or, at least, for reproduction.

Soil specificity

The spatial distribution ofCoccolobawas largely re-lated to the arrangement of sandfields, frequentlyflat and covered with grasslands, which have dis-crete distribution between gallery forests and rockyoutcrops (see also Ribeiro & Fernandes, in press).Narrow endemism in plants is frequently related tosoil specificity, and many endemic plants are foundin patches of certain soils within a different soil ma-trix (Major 1988; Pate 1993). A distinct type of soilmay break the competitive dominance of widespreadspecies, allowing the establishment and evolution ofmore restricted species (Major 1988). This seems tobe more frequently observed in poor and exposed soilslike quartzitic or siliceous sands (Babbel & Selander1973; Kruckeberg & Rabinowitz 1985; Major 1988;Cowling et al. 1994; Schutte et al. 1995), such asthose found in Serra do Cipó (Freitas & Silveira 1977;Rizzini 1979). We argue that species of narrow rangeand clear association with soils of discrete distribu-tion should follow a similar pattern of abundance ofthe described forCoccoloba. It remains to be tested,however, whether this pattern is exclusive of range-restricted species, since at larger scales the gradualchanges in factors like climate, which affect popu-

216

lation parameters, may impose a gradual decline indensity independently of soil specificity.

This is basically the argument of Caughley et al.(1989), who, after describing the patterns of abun-dance of two species of kangaroo, proposed thatvariation in demographic parameters at the edge ofdistribution is not related to the number of factorsthat affect the species, but to the kind of factor thatfirst limits the species distribution. For instance, fac-tors related to climate usually vary gradually in spaceand probably determine gradual changes in intrinsicgrowth rates, population densities, and body condi-tion (considering animals). When the limiting factoris related to substrate, an abrupt limit in abundance isexpected, as well as in population parameters.

Fire effects

In Brazilian savannas (cerradovegetation), as in manyother fire-prone habitats, human interference in thelast 100 years has led to increased fire-frequency. Inpre-Columbian times, intervals between fire eventsin cerrados are estimated to have been of about 10years, and now fire frequency has dropped to 1–3 years(Coutinho 1990). This interval is insufficient for manyplants to regenerate and reproduce sexually and underthese conditions many species are possibly becominglocally extinct or remaining as sterile branches of re-duced size (Hoffmann 1998). There is some evidencethat under very frequent fires some resprouter speciesable to grow and set seeds in this interval would befavored (Hoffmann 1998), since lignotubers providea level of resilience to frequent disturbances not avail-able to obligate-seeders (Zammit 1988). Some of theseresprouter species spread laterally by clonal recruit-ment forming many small branches, and occasionallarge intervals without fire allow rapid growth andsexual reproduction (Hoffmann 1998).

Coccolobaramets are able to flower one year afterfire, therefore representing a species with exceptionalregeneration capacity in comparison to other studiedplants (Whelan 1995; Bond & van Wilgen 1996; Hoff-mann 1998). Nevertheless, 1–3 years of fire intervalmay not be enough for a seedling to reach a fire-resistant size, which remains to be investigated. Thecombination of lateral spread of established individu-als and difficulties in seed recruitment that precludesthe colonization of unoccupied sandfields may leadto increasing aggregation ofCoccoloba. It must benoted, however, that excessively frequent fires mayextinguish available buds for vegetative recruitment

impairing plant regeneration, as shown forBanksiaoblongifolia(Zammit 1988).

Season, intensity and frequency of fire are cru-cial environmental characteristics determining speciespersistence, coexistence, diversity and succession infire-prone habitats, and should not be consideredapart from other environmental variables (Bond & vanWilgen 1996). It may be misleading to look for factorsthat mask the correspondence between habitat favora-bility and density of a species, since there will alwaysbe some kind of disturbance in any habitat, and speciesrespond idiosyncratically to them, with variable time-lags. In the case of fire-prone habitats this observationis even more important, since fire is not simply acatastrophic event of external causes but is an impor-tant dimension of the habitat volume, both influencingand being influenced by the vegetation (Whelan 1995).The inclusion of fire in Brown’s models at this timemight be complex, but it certainly would benefit fromthe explicit incorporation of the ‘regeneration niche’of plants (Grubb 1977), since population abundancepatterns may be determined by the pattern and scalesof regeneration gaps (Anderson 1986).

Generality of the pattern

The assessment of the generality of the pattern de-scribed forCoccolobais obscured by a large absenceof data on the distribution of other plant species. Fur-thermore, although highly geographically restrictedspecies, such asCoccoloba, are common in manyhabitats and floras (Drury 1980; Kruckeberg & Rabi-nowitz 1985; Gentry 1986; Major 1988; Baskauf &Eickmeier 1994; Schutte et al. 1995), the frequency ofthese species in tropical communities is not yet known(Gentry 1986). Despite this, some speculation may befruitful.

The rupestrian fields in Brazil, Mediterranean-type vegetation at Barrens in Australia, Cape FloristicProvince in South Africa, California Floristic Provincein United States, and sand-pine scrub in southeasternUnited States are examples of high diversity and en-demism habitats, characterized by poor sands and fre-quent fires (Giulietti et al. 1987; Cowling et al. 1994;McDonald et al. 1995; Schutte et al. 1995; Abraham-son & Abrahamson 1996), where multimodal patternsof abundance associated with soil specificity, and withfurther clumping due to fire effects, may be verycommon. These habitats are generally included in con-servation priorities, and management decisions maybe improved if the general pattern of spatial distrib-

217

ution of the species is known. From the available data,however, it seems that fire frequencies in thecerradoare higher than in any other fire-prone habitat (Bond& van Wilgen 1996). Thus, if fire frequency is animportant factor shaping abundance distributions, wemust be aware that the abundance patterns observed incerradovegetation may not be found in other kinds offire-prone habitats.

Acknowledgements

We would like to thank A. Paglia, R. P. Martins andF. A. M. Santos for helpful comments and discus-sion on earlier versions of the manuscript, and to twoanonymous reviewers whose observations have greatlyimproved the paper. This study was in partial fulfill-ment of K. T. Ribeiro MSc thesis at Ecologia, Conser-vação e Manejo da Vida Silvestre/Universidade Fed-eral de Minas Gerais and was conducted with supportfrom CNPq (52-1772/95-8, 133367/95-9), FAPEMIG(1950/95) and US Fish and Wildlife Service.

References

Abrahamson, W. G. & Abrahamson, C. R. 1996. Effects of fire onlong unburned Florida uplands. J. Veg. Sci. 7: 565–574.

Anderson, D.J. 1986. Ecological succession. Pp. 269–285. In:Kikkawa, J. & Anderson, D.J. (eds), Community ecology:pattern and process. Blackwell Scientific Publications, Oxford.

Babbel, G. R. & Selander, R. K. 1974. Genetic variability in edaph-ically restricted and widespread plant species. Evolution 28:619–630.

Baskauf, C. J. & Eickmeier, W. G. 1994. Comparative eco-physiology of a rare and a widespread species ofEchinacea(Asteraceae). Am. J. Bot. 81: 958–964.

Begon, M., Harper, J. L. & Townsend, C. R. 1986. Ecology:Individuals, populations and communities. Blackwell, Oxford.

Bond, W. J. & van Wilgen, B. W. 1996. Fire and plants. Populationand community biology series. Chapman & Hall, London.

Brown, J. H. 1984. On the relationship between abundance anddistribution of species. Am. Nat. 124: 255–279.

Brown, J. H. 1995. Macroecology. The University of Chicago Press,Chicago.

Brown, J. H., Mehlman, D. W. & Stevens, G. C. 1995. Spatialvariation in abundance. Ecology 76: 2028–2043.

Carter, R. N. & Prince, S. D. 1988. Distribution limits from a demo-graphic viewpoint. Pp. 59–82. In: Davy, A. J., Hutchings, M. J.& Watkinson, A. R. (eds), Plant Population Ecology. BlackwellScientific Publications, Oxford.

Caughley, G., Grice, D., Barker, R. & Brown, B. 1988. The edge ofthe range. J. Anim. Ecol. 57: 771–785.

Coutinho, L. M. 1990. Fire in the ecology of the Brazilian Cerrado.Pp. 82–105. In: Goldhammer, J.G. (ed.), Fire in the tropicalbiota. Springer-Verlag, Berlin.

Cowling, R. M., Witkowski, E. T. F., Milewski, A. V. & Newbey, K.R. 1994. Taxonomic, edaphic and biological aspects of narrow

plant endemism on matched sites in Mediterranean South Africaand Australia. J. Biog. 21: 651–664.

Drury, W. H. 1980. Rare species of plants. Rhodora 82: 3–48.Freitas, F. G. & C. O. Silveira 1977. Principais solos sob vege-

tação de cerrado e sua aptidão agrícola. Pp. 405. In: Ferri, M.G. (ed.), IV Simpósio sobre o Cerrado – Bases para UtilizaçãoAgropecuária. EDUSP/Itatiaia, São Paulo.

Galvão, M. V. & Nimer, E. 1965. Clima. Pp. 91–139. In: IBGE(ed.), Geografia do Brasil – Grande Região Leste, 5. IBGE, Riode Janeiro.

Gentry, A. H. 1986. Endemism in tropical versus temperate plantcommunities. Pp. 153–181. In: Soulé, M. E. (ed.), Conser-vation biology: the science of scarcity and diversity. Sinauer,Sunderland.

Giulietti, A. M., Menezes, N. A, Pirani, J. R., Meguro, M. & Van-derley, M. G. L. 1987. Flora da Serra do Cipó: caracterização elista de espécies. Bol. Bot. 9: 1–151.

Grubb, P. J. 1977. The maintenance of species richness in plant com-munities: the importance of the regeneration niche. Biol. Rev. 52:107–145.

Hanski, I. 1994. A practical model of metapopulation dynamics. J.An. Ecol. 63: 151–162.

Hassel, M. P. & May, R. M. 1974. Aggregation of predators andinsect parasites and its effects on stability. J. An. Ecol. 43: 567–594.

Hill, M. O. 1973. The intensity of spatial pattern in plant communi-ties. J. Ecol. 61: 225–235.

Hoffman, W. A. 1998. Post-burn reproduction of woody plants ina neotropical savanna: the relative importance of sexual andvegetative reproduction. J. Appl. Ecol. 35: 422–433.

Howard, R. A. 1960. Studies in the genusCoccolobaIX. A critiqueof the South American species. J. Arn. Arb. 41: 213–258.

Huffaker, C. B. 1958. Experimental studies on predation: dispersionfactors and predator-prey oscillations. Hilgardia 27: 343–383.

Hutchinson, G. E. 1957. Concluding remarks. Quart. Rev. Biol. 22:415–427.

Kareiva, P. 1986. Patchiness, dispersal, and species interactions:consequences for communities of herbivorous insects. Pp. 192–206. In: Diamond, J. & Case, T. J. (eds), Community ecology.Harper & Row, New York.

Kruckeberg, A. R. & Rabinowitz, D. 1985. Biological aspects ofendemism in higher plants. Ann. Rev. Ecol. Syst. 16: 447–479.

Kunin, W. E. & Gaston, K. J. (eds.) 1997. The biology of rarity.Chapman & Hall, London.

Lawton, J. H. 1993. Range, population abundance and conservation.TREE 8: 409–413.

Ludwig, J. A. & Reynolds, J. F. 1988. Statistical ecology. Wiley,New York.

Major, J. 1988. Endemism: a botanical perspective. Pp. 117–146.In: Myers, A. A. & Giller, P. S. (eds), Analytical biogeogra-phy: an integrated approach to the study of animal and plantdistributions. Chapman & Hall, London.

May, R. M. 1975. Patterns of species abundance and diversity.Pp. 81–120. In: Cody, M. L. & Diamond, J. M. (eds), Ecol-ogy and evolution of communities. Harvard University Press,Cambridge.

McDonald, D. J., Juritz. J. M., Cowling, R. M. & Knottenbelt, W.J. 1995. Modeling the biological aspects of local endemism inSouth African fynbos. Pl. Syst. Evol. 195: 137–147.

Pate, J. S. 1993. Structural and functional responses to fire andnutrient stress: case studies from the sandplains of south-westAustralia. Pp. 189–205. In: Fowden, L., Mansfield, T. & Stod-dart, J. (eds), Plant adaptation to environmental stress. Chapman& Hall, London.

218

Prance, G. T. 1987. Biogeography of neotropical plants. Pp. 46–65. In: Whitmore, T. C. & Prance, G. T. (eds), Biogeography andquaternary history in tropical America. Clarendon Press, Oxford.

Pulliam, H. R. 1988. Sources, sinks, and population regulation. Am.Nat. 137: 550–60.

Rabinowitz, D., Cairns, S. & Dillon, T. 1986. Seven forms of rarityand their frequency in the flora of the British islands. Pp. 182–204. In: Soulé, M. E. (ed.), Conservation biology: the science ofscarcity and diversity. Sinauer, Sunderland.

Rapoport, E. H. 1982. Areography: Geographical strategies ofspecies. Pergamon Press, Oxford.

Ribeiro, K. T. & Fernandes, G. W. Geographic distribution ofCoc-coloba cereifera(Polygonaceae), a narrow endemic from Serrado Cipó, Brazil. Bios. (in press).

Rizzini, C. T. 1979. Tratado de fitogeografia do Brasil. Vol. 2.Hucitec/EDUSP, São Paulo.

Schutte, A. L., Vlok, J. H. J. & Van Wyk, B.- E. 1995. Fire-survivalstrategy – a character of taxonomic, ecological and evolutionaryimportance in fynbos legumes. Pl. Syst. Evol. 195: 243–259.

Simberloff, D. & Cox, J. 1987. Consequences and costs of conser-vation corridors. Cons. Biol. 1: 63–71.

Sokal, R. R. & Rohlf, F. J. 1995. Biometry. Freeman, New York.Taylor, R. A. J. & Taylor, L. R. 1977. A behavioral model for the

evolution of spatial dynamics. Pp. 1–27. In: Anderson, R. M.,B. D. Turner, B. D. & Taylor, L. R. (eds), Population dynamics.Blackwell, Oxford.

Whelan, R. J. 1995. The ecology of fire. Cambridge UniversityPress, Cambridge.

Whittaker, R. H. 1956. Vegetation of the Great Smoky Mountains.Ecol. Monogr. 22: 1–44.

Zammit, C. 1988. Dynamics of resprouting in the lignotuberousshrubBanksia oblongifolia. J. Ecol. 13: 311–320.