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Temporal Patterns in Rates of Community Change during Succession.Author(s): Kristina J. AndersonSource: The American Naturalist, Vol. 169, No. 6 (June 2007), pp. 780-793Published by: The University of Chicago Press for The American Society of NaturalistsStable URL: http://www.jstor.org/stable/10.1086/516653 .

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vol. 169, no. 6 the american naturalist june 2007 �

Temporal Patterns in Rates of Community

Change during Succession

Kristina J. Anderson*

Biology Department, University of New Mexico, Albuquerque,New Mexico 87131

Submitted May 22, 2006; Accepted December 13, 2006;Electronically published April 6, 2007

Online enhancements: appendix, data files.

abstract: While ecological dogma holds that rates of communitychange decrease over the course of succession, this idea has yet tobe tested systematically across a wide variety of successional se-quences. Here, I review and define several measures of communitychange rates for species presence-absence data and test for temporalpatterns therein using data acquired from 16 studies comprising 62successional sequences. Community types include plant secondaryand primary succession as well as succession of arthropods on de-faunated mangrove islands and carcasses. Rates of species gain gen-erally decline through time, whereas rates of species loss display nosystematic temporal trends. As a result, percent community turnovergenerally declines while species richness increases—both in a decel-erating manner. Although communities with relatively minor abioticand dispersal limitations (e.g., plant secondary successional com-munities) exhibit rapidly declining rates of change, limitations arisingfrom harsh abiotic conditions or spatial isolation of the communityappear to substantially alter temporal patterns in rates of successionalchange.

Keywords: colonization, extinction, turnover, primary succession,secondary succession, arthropods.

Succession—community development following a distur-bance or formation of a new habitat—is traditionallythought to embody increasing community stabilitythrough time (e.g., Odum 1969; Whittaker 1975); that is,rates of community change often decrease through timeduring succession (e.g., Drury and Nisbet 1973; Jassby andGoldman 1974; Bornkamm 1981; Schoenly and Reid 1987;Prach et al. 1993; Myster and Pickett 1994; Foster and

* E-mail: [email protected].

Am. Nat. 2007. Vol. 169, pp. 780–793. � 2007 by The University of Chicago.0003-0147/2007/16906-41849$15.00. All rights reserved.

Tilman 2000; Sheil et al. 2000). Meanwhile, species rich-ness usually increases initially (e.g., Odum 1969; Swaineand Hall 1983; Saldarriaga et al. 1988; Whittaker et al.1989) but then often declines (e.g., AuClair and Goff 1971;Schoenly and Reid 1987; Lichter 1998). However, a clearsynthesis regarding temporal patterns in rates of com-munity change during succession is currently lacking.Here, I (1) describe measures of species gain and loss ratesand how these combine to determine turnover rates andspecies richness, (2) examine the temporal patterns incommunity change rates during succession across a varietyof community types, and (3) discuss the mechanisms thatmay underlie predominant temporal patterns in speciescolonization rates and richness.

Species gain (colonization) rate. Gain rate (G; time�1) isthe rate at which previously absent species appear in thecommunity. In order to measure the magnitude of gainrelative to the existing community, gain rate may be ex-pressed as a proportion of the average number of speciespresent during the measurement period (Gp):

GG p . (1)p [ ](1/2) S(t ) � S(t )1 2

Here, S(t1) and S(t2) are species richness at the beginningand end of the sampling interval, respectively. The reap-pearance of previously present species that had disap-peared may be included (G and Gp) or excluded ( and′G

); exclusion assumes that absences are an artifact of′Gp

sampling and/or population stochasticity rather than a bi-ologically meaningful event.

Several major mechanisms may be expected to influencetemporal patterns in gain rate. First, gain rate will be con-strained by the number of species that can establish them-selves and simultaneously persist in the community (KS).Early in succession, when S is far below KS, G will belimited primarily by dispersal. As S approaches KS and theintensity of competition increases, gain rate will decrease(e.g., MacArthur and Wilson 1963; Tilman 2004) until, atKS, it is approximately balanced by loss rate (Goheen etal. 2005). Although clearly an oversimplification, this



Temporal Patterns in Succession Rate 781

Figure 1: Schematic diagram showing hypothesized effects of the number of species a community can potentially hold (KS; A–C) and dispersalrates (A, D, E) on species richness (S) and gain rate (G). A–C, Hypothesized effects of KS being constant (A), sigmoidal (B), or peaked (C) overtime. A, D, E, Consequences of dispersal rates being such that each time step witnesses the arrival of 90% (A), 50% (D), and 10% (E) of thepotential colonists that had not yet arrived. An implicit assumption is that when dispersal limitations do not interfere, S tracks KS.

schema is useful for making first-order predictions re-garding temporal patterns in succession rate. For example,in the simple case where dispersal is not highly limitingand where KS remains relatively constant over the courseof succession—as may generally be the case in secondarysuccession—gain rate should start high and rapidly de-crease as S approaches KS and the intensity of competitionincreases (e.g., MacArthur and Wilson 1963; Bazzaz 1979;Walker and Chapin 1987; Tilman 2004). In the more com-plex case where KS changes substantially—perhaps as aresult of changing resource availability—gain rate will takethe form of the derivative of KS(t). Thus, for example, asigmoidal increase in KS over time—as may be the case inharsh environments where time and/or facilitation are re-quired to make resources available (e.g., Walker andChapin 1987)—would result in a peaked function of G(fig. 1B), whereas a peak in KS—as may be the case forsuccession on ephemeral resources such as corpses—would imply a roughly linear decrease in G (fig. 1C). Inboth cases, the maximum G would be lower than that ofa community that does not face such abiotic limitations(cf. fig. 1A–1C). Second, G will be controlled in large partby the rate at which propagules of new species arrive at

the site. If the rate at which propagules arrive remainsconstant through time, the rate at which new species arrivenecessarily decreases simply because many species are nolonger new. If, at each time step, a constant proportionof the species pool that is not yet represented arrives, G(t)will take an exponential form (fig. 1A, 1D, 1E). Sites thatreceive large numbers of propagules (e.g., 90% of unrep-resented species arrive at each time step) will have rapidlydecreasing G(t) and rapidly plateauing S(t) (fig. 1A). Thelower the rate of propagule arrival, the less rapid the de-crease in G(t), the lower the G(0), and the longer the timeuntil S reaches KS (cf. fig. 1A, 1D, 1E). As a result, suc-cessional communities facing strong dispersal limitationwill display relatively nondescript temporal patterns in G(fig. 1E). Note that, under this scenario, the size of theregional species pool should affect gain rate but not tem-poral patterns therein. Thus, gain rates should decreaseless dramatically in isolated locations (MacArthur and Wil-son 1963; Walker and del Moral 2003) and for commu-nities composed of poorly dispersing species than in suc-cessional communities with high dispersal rates. Third, Gmay be affected by herbivory or predation at any stage ofsuccession (e.g., Walker and Chapin 1987; Fraser and



782 The American Naturalist

Grime 1999; Howe and Brown 1999; Fagan and Bishop2000). Finally, G(t) may be influenced by loss rate (Barthaet al. 2003), especially in the later phases of successionwhen competition is more intense (e.g., MacArthur andWilson 1963; Bazzaz 1979; Lichter 2000). In combination,these four factors may affect G(t) in a variety of ways.Generally, G will decrease at any time that KS is not in-creasing, and the rate of this decrease will depend on dis-persal rates. An increase in KS will counteract this tendencyfor gain to decrease, sometimes causing it to increase.Conversely, a decrease in KS will force G to be less thanthe loss rate.

Species loss (extinction) rate. Loss rate (L; time�1) is therate at which species disappear from the community. Aswith gain rate, this may be expressed as a proportion ofthe species present over the measurement period (Lp):

LL p . (2)p [ ](1/2) S(t ) � S(t )1 2

This measure represents the probability that any givenspecies will be lost in one unit of time. Again, species thatdisappear and later reappear may be included (L and Lp)or excluded ( and ), depending on whether such tem-′ ′L Lp

porary absence is deemed to be biologically significant.Several mechanisms may act on temporal trends in loss

rate. For example, L should increase with the number ofspecies that may potentially be lost (S). Additionally, bothL and Lp may be expected to increase as the intensity ofcompetition increases (e.g., MacArthur and Wilson 1963;Bazzaz 1979; Lichter 2000). On the other hand, this maybe counteracted by a decreasing rate of invading speciesthat could potentially outcompete existing ones. Addi-tionally, if average body size increases significantly overthe course of succession, increasing life spans may resultin decreasing loss rates (Drury and Nisbet 1973). Thus, itis difficult to predict a priori how L and Lp will changeover successional time. The findings of previous studiesare likewise ambivalent, showing no relationship (Fosterand Tilman 2000), a positive relationship (Facelli et al.1987), or a peaked relationship (Lichter 1998) between Lp

and time. Species turnover rate and richness can be ex-pressed straightforwardly as functions of G and L.

Species turnover rate. Turnover rate (T; time�1) is theaverage of gains and losses:

1( )T p G � L . (3)

2

Percent turnover has been defined in a variety of ways(Wilson and Shmida 1984; Koleff et al. 2003); I modify acommon measure of community turnover, Sørensen’s co-

efficient (CS; Sørensen 1948; Koleff et al. 2003), to expressthe rate of percent turnover (Tp):

C 1 � {2S /[S(t ) � S(t )]}S C 1 2T p pp t � t t � t2 1 2 1

G � L Tp p . (4)

[ ]S(t ) � S(t ) (1/2) S(t ) � S(t )1 2 1 2

Here, SC is the number of species present at both thebeginning and the end of the measurement period. Itshould be noted that, as opposed to narrow-sense mea-sures of turnover that focus on changes in species identity(e.g., Routledge 1977), this measure will also be stronglyinfluenced by changes in species richness (Koleff et al.2003). Note also that Tp is the average of Gp and Lp andrelates to T in the same way that G and L relate to Gp andLp (eqq. [1], [2], [4]). Just as with gain and loss, turnovermay include (T and Tp) or exclude ( and ) species′ ′T Tp

that disappear temporarily.Turnover rate, as the average of gain and loss rates, will

be driven by the mechanisms that drive them. As gaingenerally substantially exceeds loss during early succession,it is likely that T and Tp will decrease with time, if sucha trend exists for gain rate. Such a trend may be accen-tuated in communities where increasing size results inlengthening life cycles (Drury and Nisbet 1973; Foster andTilman 2000). As species richness increases, Tp will alsotend to decrease and possibly to increase toward the endof succession in communities using ephemeral resources(e.g., corpses). These patterns have been previously ob-served in both plant and animal communities (e.g., Born-kamm 1981; Schoenly 1992; Myster and Pickett 1994; Fos-ter and Tilman 2000; Chytry et al. 2001). However, itshould be noted that studies reporting a decrease in turn-over rate based on Shugart and Hett’s (1973) l do so inerror (Myster and Pickett 1994; Blatt et al. 2003). Thismeasure is flawed in that (1) while purporting to measureturnover, it actually considers only loss and (2) it is definedas the fraction of original species remaining (ln trans-formed) divided by the age of the community, resultingin a mathematically trivial relationship between rate andtime (i.e., vs. x) that is guaranteed to decrease in ay/xdecelerating manner.

Species richness. Species richness (S) is defined as thenumber of species present in a community and may ormay not exclude species that are temporarily absent (S and

, respectively); S(t) is the cumulative difference between′Sgains and losses:

t t

S p G(t) � L(t). (5)� �0 0




Thus, elucidation of temporal patterns in G and L willallow description of temporal patterns of S.

Here, I analyze temporal patterns in rates of species gain(G, Gp, , and ), loss (L, Lp, , and ), and turnover′ ′ ′ ′G G L Lp p

(T, Tp, , and ) over multiple successional sequences′ ′T Tp

in a variety of community types (table 1). Specifically, Iconsider plant secondary succession in worldwide loca-tions; plant primary succession on volcanic substrates, onsand dunes, and following a receding glacier; terrestrialarthropod succession on defaunated mangrove islands;and arthropod succession on corpses. Detailed descrip-tions of these successional seres are given in the appendixin the online edition of the American Naturalist. For eachrate measure–successional sequence combination, I con-sider several mathematical forms that may potentially de-scribe the community change rate, Y(t) (i.e., gain, loss, orturnover), as a function of time over the course of suc-cession. First, the null hypothesis is that Y(t) is constant:

Y(t) p Y . (6)0

Second, if a rate is driven by a process that changes linearlywith time, it may be described by a linear function:

Y(t) p Y � yt. (7)0

Third, a community change rate may display a power re-lationship with time:

aY(t) p Y � yt . (8)0

Fourth, if a change rate depends on the number of speciespresent in the community (e.g., MacArthur and Wilson1963), an exponential form is to be expected:

atY(t) p Y � ye . (9)0

Finally, in the event that a community becomes more con-ducive to community change as a linear function of time,the exponential form (eq. [9]) may be modified by addinga linear component of time:

atY(t) p Y � yte . (10)0

In equations (6)–(10), Y0 refers to an initial and/or a finalvalue of Y, y characterizes the magnitude of the rate’sresponse to time, and a is an exponent characterizing therate at which Y changes over time. While these mathe-matical forms are by no means the only ones that may beuseful in describing temporal patterns of communitychange rates, they are able to describe the range of pre-dicted temporal trends (fig. 1). For example, a negative,

decelerating function of community change rate with time(fig. 1A, 1D, 1E)—as may be expected for gain and turn-over rates—could be described by equations (8), (9), or(10), with a negative a, a positive y, and a Y0 representingbackground community change rates equal to those of anequivalent steady state community. A rate that peaks andsubsequently declines (fig. 1B)—as may be expected ifsuccession gets a slow start—can be described by equation(10) under the above conditions; the prominence of theinitial increase before the subsequent decline depends onthe value of a (as increases, the time at which Y0 peaksFaFdecreases).

It is important to note that temporal patterns in suc-cession rate will be influenced by the temporal and spatialscales of sampling. Regarding timescales, it is to be ex-pected that the relative influence of different mechanismswill change through time; for example, communities ini-tially limited by dispersal or abiotic conditions will almostinvariably eventually become more strongly shaped by bi-otic interactions (e.g., Walker and Chapin 1987; Lichter2000). As a result, temporal patterns in succession ratedepend on the rate of succession relative to the timescaleof measurement, and, therefore, the dynamics of speciesturnover during succession must always be viewed in lightof the frequency of sampling and the duration of the study.In terms of spatial scales, the species-area relationship (e.g.,Arrhenius 1921) implies that KS should scale with area. Incommunities limited by KS, this should result in higherpeak G and/or a more sustained period during which thereis a net accumulation of species in the community (i.e.,

). In dispersal-limited communities, an increase inG 1 LKS will result in stronger dispersal limitation, as a smallerproportion of KS would arrive at each time step.

Methods

A search of the literature yielded 62 successional sequenceswhose data were published or available from the re-searcher(s) (table 1; appendix). Studies selected used long-term monitoring rather than chronosequences becausestochastic spatial species turnover and failure of chrono-sequences to represent identical environmental conditionsmay result in artificially high community change rates.However, I included eight chronosequences for plant pri-mary succession, as the slow pace of this process precludeseffective long-term monitoring. Data for one primaryplant succession sequence (Surtsey, Iceland) were obtainedfrom long-term monitoring. Presence/absence datathrough time for all species detected (as opposed to onlydominants) were required. Alternatively, when a study re-ported one or more of the variables of interest (G, Gp,

, , L, Lp, , , T, Tp, , and/or ) without providing′ ′ ′ ′ ′ ′G G L L T Tp p p

a presence-absence matrix, I used the reported values di-



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rectly. No studies meeting the above criteria were excludedfrom this analysis.

For each successional sequence, I defined each time pe-riod (Dt; ) as the time from one survey to the next.t � t2 1

For each time step, I counted species richness (S) and thenumber of species gained and lost. Gain rate (G and ;′Gyear�1) and loss rate (L and ; year�1) were obtained by′Ldividing gains and losses by elapsed time (Dt). From thesevalues, I calculated Gp and (year�1; eq. [1]), Lp and′Gp

(year�1; eq. [2]), and T, Tp, , and (year�1; eqq.′ ′ ′L T Tp p

[3], [4]). Rates were calculated both including (G, Gp, L,Lp, T, and Tp) and excluding ( , , , , , and )′ ′ ′ ′ ′ ′G G L L T Tp p p

species that temporarily disappeared.Using Matlab 7.0.1, I used least squares regression to

fit equations (6)–(10) to each community change rate foreach successional sequence. To avoid unreasonable fits tothe data, I constrained a (eqq. [8]–[10]) between 2 and�2 for equation (8) and between and for equa-�100/t 5/ttion (9), where t is the time span of the entire successionalsequence. For equation (10), Y0 and y were constrainedto be positive, and a was constrained between and�100/t0. Calculated P values for equations (7)–(10) reflect theprobability that these explain more variation in the data(i.e., have a smaller standard deviation) than does a con-stant rate (eq. [6]).

Results

The summary statistics for all regressions, representing 192mathematical model–rate measure–community type com-binations, are given as both a Microsoft Excel file and atab-delimited ASCII file, available in the online edition ofthe American Naturalist. Here, I focus on rates calculatedunder the assumption that temporary absences of speciesfrom the successional community are an artifact of sam-pling (e.g., Whittaker et al. 1989) and/or population sto-chasticity rather than a biologically meaningful event (i.e.,

, , , , , and ). The results for rates calculated′ ′ ′ ′ ′ ′G G L L T Tp p p

under the assumption that such disappearances and reap-pearances are biologically meaningful (i.e., G, Gp, L, Lp, T,and Tp) are generally very similar (Excel data, tab-delim-ited ASCII data); I note any important differences. Itshould be noted that equations (8), (9), and sometimes(10) are usually approximately equally successful in de-scribing the observed patterns (table 2); statistically, itwould be unreasonable to favor one of these mathematicalforms over the other(s) (McGill 2003). It must be em-phasized that many of the successional sequences consid-ered here come from the same study (see table 1; appendix)and therefore are not statistically independent. While noneof the results presented here would differ qualitatively inthe absence of this pseudoreplication, it is important tobear in mind that quantitative values are influenced. I note

any cases in which pseudoreplication affects theconclusions.

Gain Rates

Rates of species gain consistently decline (negative slopewhen fitted with a linear function) over the course ofsuccession ( of 55 successional sequences), al-n p 54though this decline is sometimes preceded by an initialincrease ( of 55). In plant secondary successionaln p 10seres, is well described ( ) as a decelerating′ 2G (t) R ≥ 40%decrease (eqq. [8], [9], or [10], with a positive y and anegative a; fig. 2Ai) in all but the 1.8-year secondary forestsere in Venezuela (Uhl et al. 1981) and the two 3.7-yearseres in postfire chaparral (Guo 2001), in which cases thedecrease was essentially linear (Excel data, tab-delimitedASCII data). Generally, these fits are significant at a p

and explain 190% of the variation (table 2). In plant.05primary successional seres, is generally well described′G (t)either as a decelerating decrease ( of 9) or as an p 4peaked function (eq. [10]; of 9; table 2; fig. 2Bi).n p 4With the exception of Surtsey Island, which displays nodetectable temporal pattern, at least 70% of the temporalvariation in could be described by equations (8), (9),′G (t)or (10). For arthropods on mangrove islands, tends′G (t)to peak (eq. [10]) or decrease in an accelerating manner(eqq. [8], [9], with negative y and positive a; fig. 2Ci),although no fits are statistically significant (table 2) andR2 tends to be low (averaging 15%–35%). For arthropodson carcasses, generally decreases in a roughly linear′G (t)fashion that is alternately best described as a peak (29%),a decelerating decline (18%), or an accelerating decline(12%; table 2; fig. 2Di). Again, most fits are not statisticallysignificant (table 2), and average R2 is less than 50%.

When expressed relative to the existing community( ), gain rate is well described as a decelerating decrease′Gp

(eqq. [8], [9], or [10]) for all plant secondary successionalcommunities, all arthropod-mangrove communities, 72%of arthropod-carrion communities, and 50% of plant pri-mary seres (table 2). The other 50% of plant primaryseres—the four highest-elevation sites on Mauna Loa, Ha-waii—are best described as peaked functions (eq. [10];table 2).

Loss Rates

With the exception of plant primary seres, where loss ratesoften peak (table 2; fig. 2Bi), there are no consistent tem-poral patterns in any of the measures of species loss rate(L, Lp, , and ); these measures tend to increase or′ ′L Lp

decrease with approximately equal frequency and are rarelysignificantly at (table 2); , however, displays an′P p .05 Lincreasing trend in all plant secondary and arthropod-



Tabl

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Figure 2: Representative temporal patterns in gain ( ; Ai, Bi, Ci, Di; black symbols, black lines), loss ( ; Ai, Bi, Ci, Di; gray symbols, gray lines),′ ′G Lpercent turnover ( ; Aii, Bii, Cii, Dii), and species richness ( ; Aii, Bii, Cii, Dii) for (A) plant secondary succession on an abandoned field in New′ ′T Sp

Jersey (Buell-Small succession study, field 4), (B) plant primary succession on Michigan sand dunes, (C) arthropod succession on mangrove islandE2 in Florida, and (D) arthropod succession on a rabbit carcass in Colorado (elevation 2,786 m). Temporal patterns in , , and are fitted with′ ′ ′G L Tp

power (eq. [8]; solid lines), exponential (eq. [9]; dashed lines), and (eq. [10]; dash-dotted lines) functions (statistics given in alinear # exponentialMicrosoft Excel data file or a tab-delimited ASCII data file, available in the online edition of the American Naturalist).

mangrove sequences ( , three significant atn p 16 P p), partially because this value artificially increases at the.05

end of the monitoring period when species that disappearhave decreasing time in which to reappear. Similar trends

are displayed by , with a slightly greater tendency toward′Lp

decreasing; L and Lp, which do not suffer from artificialincreases at the end of the sequence, increase or decreasewith approximately equal frequency.




Turnover Rates

Species turnover rates, as the average of gain and loss rates(eqq. [3], [4]), generally display temporal patterns similarto those of species gain rates (table 2) because gain tendsto dominate early successional change (fig. 2). Rates ofspecies turnover consistently decline (negative slope whenfitted with a linear function) over the course of succession( of 34 successional sequences), although this de-n p 31cline is sometimes best described as a peaked rate (n p

of 35). In plant secondary seres, is always well′8 T (t)described ( ) as a decelerating decrease (eqq. [8],2R ≥ 40%[9], or [10], with a positive y and a negative a; table 2)in all but one of the 3.7-year seres in postfire chaparral(Guo 2001), in which case the decrease is essentially linear(Excel data, tab-delimited ASCII data). These fits are sig-nificant at more than 75% of the time and explainP p .05more than 90% of the variation (table 2). In all plantprimary seres, more than 65% of the temporal variationin can be explained either as a decelerating decrease′T (t)(eqq. [8] or [9]; of 8) or as a peaked function (eq.n p 4[10]; of 8; table 2). For arthropods on mangroven p 4islands, increases and decreases with equal frequency′T (t)and is never well described by any of the mathematicalfunctions (eqq. [7]–[10]). For arthropods on carcasses,

is sometimes well described as a peaked function′T (t)( of 7); the remainder, which all decrease when fittedn p 3with a linear function, never have more than 40% of theirvariation explained by equations (7)–(10).

When expressed relative to the existing community( ), turnover rate is well described as a decelerating de-′Tp

crease (eqq. [8], [9], or [10]) for all plant secondary seres,all arthropod-mangrove seres, 72% of arthropod-carrionseres, and 50% of plant primary seres (table 2). The other50% of plant primary seres—the four highest-elevationsites on Mauna Loa, Hawaii—are best described as apeaked function (eq. [10]; table 2).

Discussion

Despite fundamental differences in the successional com-munities considered, some general trends emerge. First,the rate of species gain generally declines over the courseof succession (fig. 2; table 2; Swaine and Hall 1983; Facelliet al. 1987; Lichter 1998; Foster and Tilman 2000; Barthaet al. 2003). This is not surprising, given increasing com-petitive pressure and a decreasing pool of potential newcolonists (fig. 1; e.g., MacArthur and Wilson 1963). Mean-while, relative to gain rates, loss rates are generally lowand not strongly temporally patterned (fig. 2). Becausecolonization generally dominates early successional change(fig. 2; Sheil et al. 2000), turnover rates decline in a mannersimilar to gain rates (table 2). Generally, percent turnover

rate can be very well described as a decelerating decreaseover time (fig. 2; table 2), indicating that by far the greatestamount of relative change occurs early in succession. Ad-ditionally, species richness generally increases rapidly dur-ing early succession, plateaus when gain and loss ratesconverge, and subsequently decreases when (and if) gainrate drops below extinction rate (fig. 2). Thus, the resultsgenerally support the idea that community stability in-creases over the course of succession (e.g., Odum 1969).

These results can be used to address a couple of long-standing hypotheses regarding the nature of successionalcommunity assembly. First, my results universally contra-dict a strictly Clementsian notion of discrete communitiessequentially replacing one another during succession(Clements 1916), which would predict low turnover ratesinterspersed with spikes at each community transition.They are far more consistent with Gleason’s (1917) notionthat species appear and disappear as relatively independentunits. Second, gain is generally highest early in succes-sion—especially in plant communities (fig. 2), therebylending some support to the “initial floristics” hypothesisthat a large proportion of a community’s taxa arrives earlyin succession (Egler 1954; Drury and Nisbet 1973). How-ever, a strict interpretation of the initial floristics hypoth-esis would require that G be virtually absent after theearliest stages of succession, that the majority of subse-quent community change be in the form of species loss,and therefore that species richness start high and decline.My results are not consistent with these predictions (fig.2), indicating that the initial floristics hypothesis is notrealistic in any strict sense.

Differences in temporal patterns of community changerates between and within community types point to themechanisms that may underlie these patterns (fig. 1). Spe-cifically, my results suggest that three major factors drivingtemporal patterns in succession rate are competition, abi-otic limitations to the number of species a habitat cansupport, and dispersal limitations.

Competition

The majority of plant successional sequences display dra-matically decelerating decreases in colonization rates (eqq.[8], [9], or [10]; fig. 2Ai, 2Bi; table 2). Specifically, all butthe three shortest (!4 years) plant secondary successionalsequences display this pattern (fig. 2Ai; table 2; Swaineand Hall 1983). Somewhat surprisingly, some plant pri-mary seres exhibit the same patterns (table 2); specifically,rates of community change decrease in a decelerating man-ner for succession on Michigan sand dunes (fig. 2Bi, 2Bii),following a receding glacier, and at low elevations onMauna Loa (fig. 3A). These patterns match those predictedfor successional communities that are shaped largely by




Figure 3: Rates of primary succession, and temporal patterns therein, on the ′a′a lava flows of Mauna Loa, Hawaii, differ with elevation (A), temporalpatterns in the rate of new species gain ( ) at six elevations. Note that open and filled symbols are plotted on separate Y-axes that differ by an′Gorder of magnitude. B, Average rates of species gain ( ), loss ( ), and turnover ( ) over the first ∼3,400 years of succession at six elevations. All′ ′ ′G L Trates decrease significantly ( ) with increasing altitude.P ! .008

competition early in succession (fig. 1A). While this studydoes not directly test the idea that competition causes thisdecline in G(t), such a mechanism is likely in light of therecurring finding that G depends on the number of speciesalready present (e.g., MacArthur and Wilson 1963; Tilman2004; Fargione and Tilman 2005) or, in a broader sense,on the number of individuals and/or total biomass (e.g.Peart 1989; Bartha et al. 2003). Competition’s role in de-termining G is likewise supported by the fact that maturecommunities maintain relatively constant S through com-pensatory colonization and extinction (Goheen et al.2005). The suggestion that G(t) in successional plant com-munities is shaped primarily by competition does not con-flict with previous observations that early succession—especially in primary seres—is limited by factors such asdispersal, harsh abiotic conditions, and herbivory (e.g.,McClanahan 1986; Wood and del Moral 1987; Tsuyuzaki1991; Chapin et al. 1994; Fagan and Bishop 2000; Frid-riksson 2000; Lichter 2000). Rather, my model (fig. 1A)assumes that factors other than competition will determineinitial gain rates and that competition’s role in shapingG(t) will appear when S nears KS. While it may be sur-prising that secondary and primary seres display similarpatterns in G(t), it must be recalled that the timescales

differ dramatically (table 1). Thus, my findings do notimply that primary succession progresses at the same rateas secondary succession—only that relatively early primaryseres are often habitable to many species (e.g., Walker andChapin 1986; Chapin et al. 1994; Lichter 2000) and ac-commodate far higher rates of community change thando the later seres (fig. 2Bi, 2Bii). Thus, while direct testswill be required to decisively prove the role of competitionin shaping G(t), my results suggest that competition be-comes a strong influence on the assembly of plant com-munities at relatively early stages of succession.

Abiotic Limitation

Some successional communities appear to be abioticallyconstrained by the development of favorable conditionsand/or accumulation of resources, which affects KS. Spe-cifically, many species may be unable to establish them-selves in a harsh environment before its modification bytime and/or facilitating species (e.g., Connell and Slatyer1977; McAuliffe 1988). These communities, which are ex-emplified by primary succession at Mauna Loa’s higherelevations, display temporally peaked rates of species gain(fig. 3A), turnover, and even loss (eq. [10]; table 2), as




predicted for successional communities whose capacity tosupport species (KS) develops relatively slowly (fig. 1B). Inthese seres, the resources necessary to support a full setof species are initially unavailable and appear with timeand/or facilitation, resulting in a temporally peaked rateof community change (eq. [10]; fig. 1B). Here, coloniza-tion rates appear to be inhibited during early succession,peak when KS is growing most rapidly, and decline againas competition becomes limiting. The idea that abioticconditions affect temporal patterns in succession rate inthis manner is supported by the fact that peak colonizationrates occur progressively later ( ) and have pro-P p .06gressively lower values ( ) at higher elevations onP p .02Mauna Loa (fig. 3A). Note that the average rate of suc-cession also decreases with increasing elevation (Aplet andVitousek 1994; Aplet et al. 1998), such that succession ratesat the highest elevation (2,434 m) are approximately anorder of magnitude less than those at the lowest elevation(1,219 m; fig. 3B). This gradient is likely related to cor-responding decreases in rates of biomass, nutrient, andsoil accumulation resulting from the colder and drier con-ditions at higher elevations (Vitousek et al. 1992; Apletand Vitousek 1994; Aplet et al. 1998). The Mauna Loagradient clearly exemplifies the principle that the temporalpattern observed is influenced by the rate of successionrelative to the timescale of measurement and hints thatsuccession rates at low elevations might likewise show apeak if measured on a finer timescale. Thus, in additionto slowing the overall rate of succession (e.g., Walker anddel Moral 2003), harsh abiotic conditions appear to delaypeak rates of community change (fig. 3).

Dispersal Limitation

A number of the successional seres considered here displaytemporal patterns expected for dispersal-limited com-munities (fig. 1D, 1E). First, in the secondary seres withthe shortest records (i.e., the secondary forest in Venezuelaand the postfire chaparral in California; table 1), de-′Gcreases in an approximately linear fashion (Excel data, tab-delimited ASCII data), indicating that the limiting effectsof KS are not yet strongly inhibiting the colonization ofnew species, as appears to be occurring in other plantsecondary successional seres. Another example of a suc-cession that is likely dispersal limited is that of SurtseyIsland (e.g., Fridriksson 2000), which is located 33 km offthe coast of Iceland. There, displays no significant tem-′Gporal patterns (Excel data, tab-delimited ASCII data), in-dicating that dispersal limitations may obscure temporalpatterns resulting from abiotic and/or competition-driventrends. As this successional sequence describes only thefirst 3 decades of primary succession, the fact that it failsto display temporal patterns similar to those of other pri-

mary seres is in line with the prediction that observedtemporal patterns and their underlying mechanisms willdepend on the timescale of measurement. Additionally,most insect successional sequences display relatively non-descript (high variance; Simberloff and Wilson 1969),roughly linear decreases in colonization rate over thecourse of succession (fig. 2Ci, 2Di; table 2) that may beindicative of dispersal limitation (fig. 1D, 1E). Such lim-itation is probable, as both mangrove islands and decom-posing carcasses are “islands” from the perspective of theirinhabitant species, and succession rates may therefore bedispersal limited. This possibility is supported by the factthat arthropod colonization rates on mangrove islandsclose to colonization sources tend to decline more rapidlythan do those of distant islands ( , ). Ad-n p 6 P p .20ditionally, gain rate decreases more slowly on large islands( , ), supporting the prediction that dispersaln p 6 P p .06limitation should be more pronounced on large islands(data from Simberloff and Wilson 1969; Wilson and Sim-berloff 1969; Excel data, tab-delimited ASCII data). In thecase of arthropod succession on carcasses, the oftenroughly linear decreases in gain rate may be explainedalternatively by dispersal limitation (fig. 1E) and/or as aresult of a temporally peaked pattern in resource avail-ability (KS; fig. 1C); a combination of the two is not un-likely. Thus, spatially isolated successional communitiesand/or those measured over a short timescale may displayless dramatic temporal patterns as a result of dispersallimitation. The idea that dispersal limits the rate of com-munity assembly agrees well with previous theory indi-cating (1) that succession rate depends on distance fromseed sources (e.g., McClanahan 1986) and (2) that an-thropogenic increases in propagule arrival in unsaturatedcommunities result in increased species diversity (e.g., Fos-ter 2001; Sax et al. 2002).

Thus, it appears that competition, abiotic limitation,and dispersal are three major processes influencing tem-poral patterns in succession rate. No successional com-munity should be assumed to be free of the influence ofany of these; rather, it is likely that all influence successionand that their relative importance differs through time andwith community type. I propose that successional se-quences may be classified according to the relative influ-ence of these three processes and that temporal patternsin succession rate indicate which of these processes havethe greatest influence over the timescale of interest (fig.4). My classification of the successional communities an-alyzed in this study (fig. 4) is done according to the timeperiod for which data were available; it is to be expectedthat consideration of other timescales would indicate thatother mechanisms dominate over longer or shorter timeperiods; for example, all communities may be expected tomove toward competition limitation as S approaches KS—




Figure 4: Schematic diagram outlining three main controls on temporal patterns in succession rate: competition, dispersal, and abiotic conditions.Successional sequences considered in this study are placed in hypothesized locations according to their temporal patterns in succession rate, abioticconditions, and isolation. Note that these classifications are largely dependent on the timescale of interest.

as appears to be occurring with the plant secondary seres.While the triangular framework (fig. 4) is suggested by theresults of this study, further research will be necessary torigorously test it.

Two additional factors that probably affect temporalpatterns in succession rate cannot be addressed using thisdata set but may form additional axes of variation (fig.4). First, increasing body sizes may result in decreasingsuccession rates (e.g., Drury and Nisbet 1973) such thatthe magnitude of change in average body size may affectthe rapidity with which rates of community change declineduring succession. Second, trophic interactions undoubt-edly affect successional communities. The rate of speciesgain early in succession may be significantly reduced byprimary consumers (Howe and Brown 1999; Fagan andBishop 2000), and there is evidence that herbivores’ pref-erence for early successional plants (e.g., Coley 1983; God-fray 1985; Fagan et al. 2004) may accelerate the replace-ment of early successional species by later ones (e.g., Fraserand Grime 1999). Likewise, ant predation on sarcosa-

prophagous arthropods slows the rate at which carcassesdecay (Early and Goff 1986), thereby inevitably affectingsuccession. Thus, trophic interactions have the potentialto either hinder or accelerate community change at a va-riety of successional stages; accordingly, their impact ontemporal patterns in succession rate cannot be easily gen-eralized without further research.

It must be borne in mind that the appearance and dis-appearance of species from successional communities isonly one aspect of successional change. The numbers andsizes of individuals representing each species may poten-tially change dramatically, with little concurrent change inspecies occurrence. Thus, temporal patterns in rates ofcommunity change that consider relative abundance (e.g.,percent similarity/dissimilarity, detrended correspondenceanalysis) may differ from those observed here; a compar-ative analysis of temporal patterns in these rates would beinstructive.

In conclusion, there is a general tendency for rates ofcommunity change to decline in a decelerating manner




over the course of succession (fig. 2; table 2), a trend thatis consistent with the idea that the size of the existingcommunity affects species gain rates (e.g., MacArthur andWilson 1963; Bazzaz 1979; Peart 1989; Van der Putten etal. 2000; Bartha et al. 2003; Tilman 2004). However, thistendency may be modified by abiotic or dispersal limi-tations (fig. 4) such that temporal patterns in communitychange rates peak (figs. 1B, 3A) or decline in a more linearfashion (fig. 1E; fig. 2Ci, 2Di), respectively. While thisanalysis identifies some general trends in temporal patternsof succession rate and identifies some of the potentialmechanisms that may shape them, its more importantcontribution may be to provide baseline data and quan-titative methods for comparing successional communitiesthat differ in species composition, isolation, trophic struc-ture, and abiotic setting.

Acknowledgments

Special thanks to J. G. Anderson for Matlab programmingassistance and to J. H. Brown for helpful comments. I amgrateful to the Buell-Small succession study (National Sci-ence Foundation [NSF] Long-Term Research in Environ-mental Biology grant DEB-9726992) and to G. H. Apletfor providing data and to all researchers whose publisheddata were included in this analysis. Thanks also to S. Baez,S. L. Collins, J. P. DeLong, E. P. White, the Brown andMilne labs, and two anonymous reviewers for helpful com-ments. I was funded by an NSF biocomplexity grant (DEB-0083422).

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Associate Editor: Catherine A. PfisterEditor: Monica A. Geber



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