tree population dynamics in kibale national park, uganda 1975–1998

Tree population dynamics in Kibale National Park,Uganda1975^1998

Jeremiah S. Lwanga1,ThomasM. Butynski2 andThomasT. Struhsaker31Makerere University Biological Field Station, Fort Portal, Uganda, 2Zoo Atlanta, Africa Biodiversity Conservation

Program, Nairobi, Kenya, 3Department of Biological Anthropology & Anatomy, Duke University, Durham, NC,

U.S.A.

Abstract

Changes in species composition, stem abundance, andbasal area of trees taller than or equal to10m in a med-ium altitude tropical rain forest at the Ngogo studyarea, Kibale National Park, Uganda are described forthe period between 1975 and 1998 (n�23 years). Twoenumeration episodes were conducted in 263 plots of5 m by 50m during1975^80 and1997^98. During thisperiod, species richness decreased by 3% (from 92 to89). Species diversity (H 0) also declined slightly from2.97 to 2.86. The number of trees recorded in the sam-ple plots decreased by 8% (from 2545 to 2329), whilebasal area decreased from 49.48m2 haÿ1 to 48.68m2

haÿ1. However, stem abundance and basal areaincreased for some species.

Keywords: plots, stand, dynamics, tropical, forest,Uganda

Resume

On decrit les changements survenus dans la composi-tion des espe© ces, l'abondance des jeunes pousses et lasurface a© la base d'arbres de 10m de haut ou plus, dansune foreª t tropicale de moyenne altitude de l'aire derecherches de Ngogo, au Parc National de Kibale, enOuganda, pour la periode qui va de1975 a© 1998 (n�23ans). On a mene deux series de releves dans 263 plots de5m sur 50m entre 1975 et 1980, et entre 1997 et 1998.Pour cette periode, la richesse en espe© ces avait baisse de3%, passant de 92 a© 89. La diversite speci¢que (H0) avaitaussi baisse lege© rement, de 2,97 a© 2,86. Le nombre

d'arbres rapportes dans les plots echantillons a baissede 8% (de 2545 a© 2329), alors que la surface de basepassait de 49,48m2/ha a© 48,68m2/ha. Cependant,l'abondance des jeunes pousses et la surface de baseavait augmente pour certaines espe© ces.

Introduction

Long-term monitoring of tree population dynamics iscrucial to forest management and conservation. Con-siderable expanses of tropical rain forests have beendegraded or lost in the recent past (Huguet, 1983;Struhsaker, 1987; Kangas, 1990;Van Schaik,Terbogh &Dugelby, 1997) and now there is a growing consensusamong conservationists that the remaining forestsshould be used sustainably. Success in this direction is,however, hampered by the paucity of information onthe dynamics of forest ecosystems. E¡orts towards gen-erating long-term information on forest dynamicsusing permanent sample plots were initiated in OmoForest Reserve, Nigeria in the 1920s (Okali & Ola-Adams,1987). In Uganda, permanent sample plots wereestablished in the Budongo Forest Reserve in the 1930sand 1940s (Eggeling, 1947; Swaine, Hall & Alexander,1987; Sheil, 1995), and in Mpanga Forest Reserve in1968 (Taylor et al.,1996).Repeat sampling of permanent sample plots has

proved useful in furthering our understanding of suc-cession and mortality patterns of tropical forest trees(Eggeling, 1947; Milton, Laca & Demment, 1994) andenabled the estimation of mortality and growth rates ofsome tropical forest trees through predictive modelling(Lieberman et al., 1985; Condit, Hubbell & Foster,

238 #2000 East AfricanWild Life Society, Afr. J. Ecol.,38, 238^247

Correspondence: Jeremiah S. Lwanga, Makerere University Biologi-cal Field Station, PO Box 409, Fort Portal, Uganda.

1993a,b). Such estimates are of great importance inproduction forestryand conservation.Although the importance of permanent sample

plots in forest ecological studies and management isobvious, they are time consuming to establish andmaintain. As a result, information obtained from moststudies using permanent sample plots cannot be gener-alized for whole forests because plots are usually smalland often not replicated (Condit, 1995; Sheil, 1995).Furthermore, many tropical forest tree species arerepresented by only one or a few individuals in mostsamples. This makes the establishment of clear changesin £oristic composition di¤cult (Swaine, Lieberman &Putz, 1987; Milton et al., 1994). Statistical con¢dence inpopulation changes, mortality rates, or growth ratesrequires a minimum of about 100 stems (Condit et al.,1993a; Condit, 1995). The need to gather informationon a large number (c.100 stems) of individuals of singlespecies inspired the establishment of a large (50 ha)permanent plot on the Barro Colorado Island, Panama(Hubbell & Foster, 1983, 1992; Condit et al., 1993a,b;Condit, 1995). Following the Barro Colorado example,50 ha plots were established at Pasoh, Malaysia Penin-sular and at Mudumalai, southern India (Condit, 1995).At Barro Colorado and Pasoh, 50% of the species wererepresented in the plot by at least 100 stems, while atMudumali, 25% of the species were represented by atleast100 stems (Condit,1995). Although the problem ofspecies representation can be overcome in single largeplots, the problem of lack of replicates remains un-solved. Therefore, information obtained in single 50 haplots may simply be a full evaluation of a sizeablefraction of one community but does not necessarilyrepresent the tremendous variation in the whole forest(Condit,1995).In this paper, we present data on tree population

dynamics from 263 (0.025 ha) plots distributedthroughout the Ngogo studyarea, Kibale National Park,western Uganda. The plots were established in1975^80to assess the abundance of food sources for study pri-mate species at Ngogo (Butynski, 1990;T.T. Struhsaker,unpublished data). Small plots such as these have atleast two advantages over large plots. First, because oftheir small size, samples can be replicated easily andsecond, much of the habitat variation that is typical oftropical rain forests is more likely to be represented inmany small plots scattered throughout the study areathan in one large plot equal in area. There is, however,

at least one disadvantage associated with small plots,the chances that an observer will consistently includeindividuals that ought to be excluded or vice versa aregreater for small plots than large ones (Greig-Smith,1983). However, strict following of guidelines for inclu-sion of trees in the sample (see Methods) can minimizeor eliminate the e¡ects of this problem completely.

Methods

The study area

The study was conducted at the Ngogo study area inKibale National Park, western Uganda. The park liesnear the eastern edge of the western rift valley approxi-mately 24 km east of the Rwenzori mountains. It is situ-ated just north of the equator and encompasses an areaof approximately 766 km2 within the following geogra-phical coordinates: 0�130 to 0�410 N and 30�190 to30�320 E. The vegetation in the park is a patchwork ofhabitat types, of which forest (57.9%) and grassland(14.6%) are the most extensive. Woodland occupies5.8% of the park's area while 2.2% of the park is com-prised of wetlands and lakes. Plantations of exotic trees,on hilltops formally occupied by grasslands derivedfrom past human activities (Wing & Buss, 1970; Struh-saker et al., 1989) cover 1.0% of the park's area. Othervegetation types in the park include abandoned farms(10.3%) and degraded forest (8.7%; largely representingsecondary forest associated with agriculturalencroachment). These degraded lands are concentratedmainly in the southern part of the park.Altitude within the park ranges from 1590m in the

north to 1110m in the south. Rainfall is heavy (annualmean rainfall is about1600mm) and fairly well distrib-uted throughout the year. However, March^May andSeptember^November are usually wetter than theother months while June^ July and December^Febru-ary are usually dry months (Struhsaker, 1997). Meanmonthly maximum temperatures are 23^24�C andmean monthly minimum temperature is about 16�C(Struhsaker,1997).When Kibale was ¢rst gazetted as a central forest

reserve in1948, Ngogowas set aside as a small (about 2km2) strict nature reserve. This area was never a¡ectedby the logging operations of the late 1960s and early1970s (Ghiglieri, 1984). The forest at Ngogo, like mostparts of the park, is punctuated with grasslands espe-

# 2000 East AfricanWild Life Society, Afr. J. Ecol.,38, 238^247

239Tree population dynamics

cially on high hill tops. Tree regeneration has beenslow in these grasslands due to frequent burning bypoachers. Apart from grassland and forest edge ¢resand occasional poaching, Ngogo has not su¡ered anymajor human intervention for at least 50 years. There-fore, any vegetation changes detected are probably dueto natural processes.

Field methods

Tree enumeration was conducted in 1975^78 by T. T.Struhsaker (T.T.S.) and in 1980 by T. M. Butynski(T.M.B.) and in 1997^98 by J. S. Lwanga (J.S.L.). T.T.S.and T.M.B. described the locations of their sample plotsin detail; this enabled J.S.L. to sample exactly the sameplots 17^23 years later.We enumerated trees in plots of5 by 50m. The start and end points of plots establishedby T.T.S. were marked permanently with metalic tagsnailed on trees at 50-m intervals along the trail. Inaddition to the metalic tags, the beginning and end ofeach plot were also marked with red paint on nearbytrees. These marks were used by J.S.L. to locate the sam-ple plots. In case of missing tags in the second study per-iod, J.S.L. measured 50-m intervals from an existingtag. Plots established by T.M.B. were located in the sec-ond study period by measuring 50m from trail inter-sections and in the direction described byT.M.B.Plot length followed pre-existing trails that ran

north^south and east^west, and crossed one anotherat about 100-m intervals. All trees at least 10m high,with centres of their stems located within 2.5 m of themiddle of the trail were identi¢ed to species. In the1975^80 enumeration, T.M.B. recorded both stemabundance and diameter at breast height (d.b.h.) (1.4m). T.T.S. recorded stem abundance only. In the 1997^98 enumeration, both species and d.b.h. were recordedfor all trees. Plots sampled by T.T.S. (161 plots) weremostly adjoining and passed through various foresttypes, while plots sampled by T.M.B. (132) were chosenat random, started at trail intersections, and usuallyfell in one forest type.Thirty plots were fully or partiallyincluded in both subsamples. In such cases, data fromT.T.S. plots were excluded from the analysis. Conse-quently, 263 plots were used in analyses where datafrom T.T.S. and T.M.B. plots were combined. The twosubsamples were combined because they yielded simi-lar results whenanalysed separately.

Data analysis

The cumulative number of species was plotted againstsampling e¡ort (number of 0.025 ha plots) to examinewhether samples were representative of the speciesrichness of trees at least10m high at Ngogo.The irregu-lar manner inwhich additional species are found in tro-pical forests makes it di¤cult, if not impossible, todecide when to stop sampling by examining speciesaccumulation curves derived from raw data. Krebs's(1989) rarefaction algorithm was used to smooth thespecies accumulation curves. Because exactly the sameplots were sampled during both study periods, paired t-tests were used to examine for di¡erences in stem abun-dance and basal area between the two study periods.Stem abundance and basal area could have increasedor decreased in the second study period. The testhypotheses were stated such that the null hypothesescould be rejected if the test statistics fell in the area ofthe two tails of the normal distribution curve.The con¢-dence limit was 95%. Di¡erences were considered sig-ni¢cant if the calculated probabilities were less than orequal to 0.025. Changes in stem abundance were testedfor all species combined and for a few selected species.Changes in abundance for individual species weretested if (1) the species was represented by approxi-mately 100 stems or more in at least one of the enu-meration periods (Condit et al., 1993a; Condit, 1995), or(2) the species was an important food source for theKibale primates (Struhsaker, 1975, 1978; Ghiglieri,1984; Butynski, 1990). The second category should,however, be interpreted with caution because some ofthese analyses were based onas fewas two stems.

Results

Changes in stem abundance

The species accumulation curves (Fig.1) were almostasymptotic for both study periods, suggesting that mostspecies in the study area, except for the rarest ones,were represented in our samples. Species richnessdecreased by 3% (from 92 to 89), while species diversity(H0 calculated using logarithmic base e, Greig-Smith,1983) decreased from 2.97 to 2.86. Eleven species thatwere present in the 1975^80 sample were absent fromthe1997^98 sample (Table1). Eight species recorded in1997^98 were not recorded in the 1975^80 sample.

240 Jeremiah S. Lwanga et al.

#2000 East AfricanWild Life Society, Afr. J. Ecol.,38, 238^247

Consequently, species richness dropped by threebetween the ¢rst and second enumeration.The number of stems recorded in the 263 plots

(6.575 ha) decreased by 8% (from 2545 to 2329). Thisdecrease in stem abundance was statistically signi¢-cant. However, similar analyses for selected speciesindicate that not all species decreased in stem abun-dance. In fact some increased in stem abundance dur-ing the period between the ¢rst and secondenumeration (Table 2).With the exception of the smallproportion of individuals in the smallest size classrecorded in the1997^98 study period, the size class dis-tribution of stems (Fig. 2) in both study periods con-formed to the `inverse J'distribution curve, suggesting astable size and age class distribution (Swaine et al.,1987).

Diameter at breast height and abundance of the`new' species are presented in Table 3. It should, how-ever, be noted that these species were not new in thestudy area. Possibly some of these trees were present inthe study plots in1975^80 but were under10m. Hence,they were not included in the sample at that time.

Changes in basal area

When all tree species are lumped, basal area in thestudy plots did not change signi¢cantly. However, ana-lyses for single selected species show that basal area

increased or decreased signi¢cantly for some species(Table 4). It should be pointed out that basal areachanges for Mimusops bagshawei and Randia urcellifor-mis need to be interpreted cautiously because they arebased on few stems (thirteen versus eleven) and (twoversus seven), respectively. The remaining species thatexhibited signi¢cant changes in basal area were repre-sented by more than 100 stems during both enumera-tion periods.Basal area extrapolated from the 132 plots for the

Ngogo forest decreased from 49.48m2 haÿ1 to 48.68m2 haÿ1 between 1975^80 and 1997^98, respectively.Both estimates were comparable to those for trees>10m in a mature forest at Kanyawara, 12^13 km north-west of Ngogo in a continuous forest (34^45m2 haÿ1;Butynski, 1990) and to mature lowland rain forestselsewhere in the tropics (36m2 haÿ1; Dawkins 1959,cited in Struhsaker,1997).

Discussion

The almost asymptotic shape of the species^areacurves suggests that our samples re£ect closely the treespecies richness in the study area. It should be empha-sized that our enumeration focused on trees that wereat least 10m high. Otherwise, if expressed as speciesper hectare, our data indicate that there were onlyabout fourteen species per hectare at Ngogo, suggestinga species-poor forest. The park is, however, not species-poor; 351 species of woody plants have been identi¢edin Kibale National Park (Lwanga, 1996). The represen-tation of nearly all tree species in the study area in only6.575 ha justi¢es the use of a large number of smallsample plots. In our sample only eight species wererepresented by at least 100 stems (Table1), the recom-mended minimum for statistical con¢dence in treepopulation changes (Condit et al., 1993a,b; Condit,1995). Therefore the results that are based on fewerstems should be interpreted with caution. It should benoted, however, that the low stem abundance of themajority of species in our samples was mainly the resultof excluding trees that were shorter than 10m. Poorrepresentation of tropical forest tree species is an una-voidable outcome of restricting sampling to larger sizeclasses (e.g. Lieberman & Lieberman,1987; Milton et al.,1994; Condit, 1995; Taylor et al., 1996; Chapman et al.,1997).

Fig1 Cumulative tree species as a function of sampling e¡ort in263 (0.025 ha) plots for the two enumeration episodes (1975^80and1997^98) at Ngogo, Kibale National Park, Uganda. Curveswere smoothed using rarefaction procedures.



Table1 Tree species encountered in 263 plots in Kibale National Park, Uganda, during the1975^80 and1997^98 enumeration periodsindicating stemabundance and change in abundance during the period

Species Family AuthorityStemabundance1975^80

Stemabundance1997^98 Change

Albizia coriaria Leguminoseae Welw. ex Oliv. 0 1 1Albizia glaberrima Leguminoseae (Schumach. & Thonn.) Benth. 8 4 ÿ4Albizia grandibracteata Leguminoseae Taub. 0 2 2Albizia gummifera Leguminoseae (J.F.Gmel.) C.A.Sm. 1 2 1Antiaris toxicaria Moraceae (Rumph. ex Pers.) Lesch. 1 1 0Anthocleista vogelii Loganiaceae Planch. 0 2 2Aphania senegalensis Sapindaceae (Juss. ex Poir.) Radlk. 22 19 ÿ3Apodytes dimidiata Icacinaceae Arn. 2 1 ÿ1Balanites wilsoniana Balanitaceae Dawe & Sprague 4 7 3Baphiopsis stuhlmanni Leguminoseae Taub. 2 0 ÿ2Bersama abyssinica Melianthaceae Fresen. 6 3 ÿ3Bersama sp. Melianthaceae 1 1 0Blighia unijugata Sapindaceae Bak. 7 6 ÿ1Bosquiea phoberos Moraceae Baill. 31 28 ÿ3Casearia engleri Flacourtiaceae Gilg 2 1 ÿ1Casearia sp. Flacourtiaceae 1 1 0Cassipourea ruwensorensis Rhizophoraceae (Engl.) Alston 13 8 ÿ5Celtis africana Ulmaceae Burm.f. 14 8 ÿ6Celtis durandii Ulmaceae Engl. 261 261 0Celtis mildbraedii Ulmaceae Engl. 4 4 0Chaetacme aristata Ulmaceae Planch. 25 21 ÿ4Chrysophyllum albidum Sapotaceae G.Don 234 260 26Cola gigantea Sterculiaceae A.Chev. 2 2 0Conophryngia holstii Apocynaceae (K.Schum) Stapf 123 68 ÿ55Cordia mellenii Boraginaceae Bak. 2 3 1Croton macrostachys Euphorbiaceae Hochst. ex A.Rich. 0 1 1Dictyandra arborescens Rubiaceae Welw. ex Benth. & Hook.f. 15 8 ÿ7Diospyros abyssinica Ebenaceae (Hiern) F.White 425 391 ÿ34Dombeya mukole Sterculiaceae Sprague 15 17 2Drypetes sp. Ephorbiaceae 1 1 0Ehretia cymosa Boraginaceae Thonn. 1 0 ÿ1Elaeodendron buchananii Celasteraceae (Leos.) Leos. 7 5 ÿ2Erythrina abyssinica Leguminosae Lam. ex DC. 5 3 ÿ2Erythrina excelsa Leguminosae Bak. 1 0 ÿ1Fagaropsis angolensis Rutaceae (Engl.) Dale 4 3 ÿ1Ficus brachylepis Moraceae Welw. ex Hiern 8 9 1Ficus capensis Moraceae Thunb. 3 3 0Ficus congensis Moraceae Engl. 0 2 2Ficus cyathistipula Moraceae Warb. 1 1 0Ficus dawei Moraceae Hutch. 1 1 0Ficus mucuso Moraceae Welw. ex Ficalho 1 1 0Ficus natalensis Moraceae Hochst. 5 5 0Ficus sp. Moraceae 1 1 0Ficus stipulifera Moraceae Hutch. 1 1 0Funtumia latifolia Apocynaceae (Stapf) Sclechter 174 212 38Grumelia megistostica Rubiaceae S.Moore 1 0 ÿ1Harrisonia abyssinica Simaroubaceaee Oliv 5 6 1Leptonichia mildbraedii Sterculiaceae Engl. 1 0 ÿ1Linociera johnsonii Oleaceae Baker 17 7 ÿ10



Species Family AuthorityStemabundance1975^80

Stemabundance1997^98 Change

Lovoa swynnertonii Meliaceae Bak.f. 29 21 ÿ8Macaranga schweinfurthi Euphorbiaceae Pax 0 1 1Markhamia platycalyx Bignoniaceaee (Bak.) Sprague 146 111 ÿ35Maytenus undata Celasteraceae (Thunb.) Blakelock 3 2 ÿ1Millettia dura Leguminosae Dunn 23 13 ÿ10Mimusops bagshawei Sapotaceae S.Moore 28 27 ÿ1Monodora myristica Annonaceae (Gaertn.) Dunal. 34 30 ÿ4Morus lactea Moraceae (Sim)Mildbr. 4 2 ÿ2Neoboutonia macrocalyx Euphorbiaceae Pax 4 5 1Newtonia buchananii Leguminosae (Baker) Gilb. & Bout. 5 0 ÿ5Ochnamembranacea Ochnaceae Oliv. 1 1 0Olea welwitschii Oleaceae (Knobl.) Gilg & Schellenb. 20 15 ÿ5Olinia sp. Oliniaceae 1 1 0Pancovia turbinata Sapindaceae Radlk. 1 0 ÿ1Parinari excelsa Rosaceae Sabine 6 6 0Parkia ¢licoidea Leguminosae Welw. ex Oliv. 1 1 0Phyllanthus discoidius Euphorbiaceae (Baill.) Muell. Arg. 0 1 1Piptadeniastrum africanum Leguminoseae (Hook.f.) Brenan 14 14 0Pleiocarpa pycnatha Apocynaceae (K.Schum.) Stapf 4 3 ÿ1Polyscias fulva Araliaceae (Hiern) Harms 0 1 1Premna angolensis Verbenaceae Guerke 25 23 ÿ2Pseudospondias microcarpa Anacardiaceae (A.Rich.) Engl. 16 17 1Pterygota mildbraedii Sterculiaceae Engl. 97 91 ÿ6Pygeum africana Rosaceae Hook.f. 2 6 4Randia lucidula Rubiaceae Hiern 2 2 0Randia urcelliformes Rubiaceae (Schweinf. ex Hiern) Eggeling 20 9 ÿ11Rauvol¢a oxyphylla Apocynaceae Stapf 5 7 2Rawsonia ugandensis Flacourtiaceae Dawe & Sprague 2 0 ÿ2Rinorea brachypetala Violaceae (Turcz.) Kuntze 1 0 ÿ1Sapium ellipticum Euphorbiaceae (Hochst. ex Krauss) Pax 5 4 ÿ1Schrebera arborea Oleaceae A.Chev. 7 7 0Spathodea campanulata Bignoniaceae P.Beauv. 20 20 0Strombosia sche¥eri Oleaceae Engl. 30 29 ÿ1Strychnos mitis Loganoniaceae S.Moore 3 3 0Teclea nobilis Rutaceae Del. 37 15 ÿ22Tetrapleura tetraptera Leguminosae (Schumach. & Thonn.) Taub. 1 1 0Treculia africana Moraceae Decne 3 3 0Trema guineensis Ulmaceae Ficalho 2 1 ÿ1Trichilia prieureana Meliaceae A.Juss. 1 1 0Trichilia splendida Meliaceae A.Chev. 1 0 ÿ1Turaeanthus sp. Meliaceae 1 1 0Turraea robusta Meliaceae Guarke 2 1 ÿ1Unident11 ? 1 1 0Unident15 ? 1 0 ÿ1Unident16 ? 1 1 0Uvariopsis congensis Annonaceae Robyns & Ghesquiere 455 425 ÿ30Vangueria apiculata Rubiaceae K.Schum. 7 1 ÿ6Vitex amboniensis Verbenaceae Guerke 4 2 ÿ2Warburgia ugandensis Canellaceae Sprague 2 5 3Xymalos monospora Monimiaceae (Harv.) Warb. 4 2 ÿ2Zanha golungensis Sapindaceae Hiern 4 4 0

Table1 Continued



Stem abundance at Ngogo decreased between 1975^80 and1997^98. Interestingly, at the Kanyawara studyarea, only 12 km NWof Ngogo in a continuous forest,Chapman et al. (1997) observed an increase in stemdensity in a mature forest block between the early1970s and 1992. Sampling procedures were similar atboth study areas and the Kanyawara plots were alsoestablished by T.T.S. (Struhsaker, 1975). Species such asCeltis durandii, Diospyros abyssinica, Markhamia platy-calyx and Uvariopsis congensis that, either declined ordid not change signi¢cantly at Ngogo were amongthose whose stem density increased at Kanyawara. Thestem density of the understorey tree U. congensis morethan doubled at Kanyawara. Although stem density ofFuntumia latifolia increased at both study areas, theincrease at Kanyawara was 180%, whereas at Ngogo it

increased by only 22%.These di¡erences are di¤cult toexplain because the two study areas are similar. Forexample, both areas were not seriously impacted byhuman activities prior to the early 1970s, or after,environmental variables such as temperature, rainfalland soils are also similar (Chapman et al., 1997). How-ever, Chapman and colleagues found that light pene-trating to the forest £oor was higher at Kanyawara thanNgogo. Perhaps this favoured the growth and/or estab-lishment of light demanding species at Kanyawara.Nonetheless, because Chapman and colleagues did notexplain exactly how they located the plots sampled byT.T.S. in the early 1970s 20 years later, the possibilitythat they sampled slightly di¡erent areas cannot beruled out.This also could have contributed the large dif-ferences between Ngogo and Kanyawara.

Table 2 Results of paired t-tests on number of stems per plot for selected tree species encountered in Kibale National Park, Uganda,during the1975^80 and1997^98 enumeration periods (n= 263 plots)

Mean no. of stems

Species 1997^98 1975^80 t-value2-tail signi¢canceP-value

All species1 9.0190 9.9011 ÿ5.06 0.000Celtis durandii1 0.9924 0.9924 0.00 1.000 NSChrysophyllum albidum1 0.9886 0.8897 �2.37 0.018Conophryngia holstii1 0.2586 0.4677 ÿ5.40 0.000Diospyros abyssinica1 1.4867 1.6160 ÿ1.89 0.060 NSFuntumia latifolia1 0.8061 0.6616 �3.20 0.002Markhamia platycalyx1 0.4221 0.5551 ÿ4.17 0.000Ptrygota mildbraedii1 0.3460 0.3688 �0.97 0.331 NSUvariopsis congensis1 1.6160 1.7300 ÿ1.74 0.083 NSAphania senegalensis2 0.0722 0.0837 ÿ1.00 0.318 NSBosquiea phoberos2 0.1065 0.1179 ÿ1.34 0.180 NSCeltis africana2 0.0304 0.0532 ÿ2.47 0.014Linociera johnsonii2 0.0266 0.0646 ÿ2.93 0.004Lovoa swynnertonii2 0.0798 0.1103 ÿ2.87 0.004Mimusops bagshawei2 0.1027 0.1065 ÿ0.38 0.706 NSMillettia dura2 0.0494 0.0875 ÿ1.97 0.050 NSMonodora myristica2 0.1141 0.1293 ÿ2.01 0.045 NSNewtonia buchananii2 0.0000 0.0190 ÿ2.25 0.025Olea welwitschii2 0.0570 0.0760 ÿ1.90 0.059 NSPremna angolensis2 0.0875 0.0951 ÿ0.58 0.565 NSPseudospondias microcarpa2 0.0646 0.0608 �1.00 0.318 NSRandia urcelliformis2 0.0760 0.0342 ÿ2.55 0.011Strombosia sche¡reli2 0.1103 0.1141 ÿ1.0 0.318 NSTeclea nobilis2 0.0570 0.1407 ÿ4.14 0.000

1Total number of stems was approximately equal to or greater than100 inat least one of the enumeration episodes.2Species was selected for analysis because it is an important food source for primates, but the total number of stems was less than100.



The overall decrease in stem abundance at Ngogowas not accompanied by a signi¢cant decrease in basalarea. This observation suggests that the majority oftrees that died were small and that the loss in basal areadue to such deaths was more or less compensated for bythe growth of the larger trees that survived. This idea isfurther strengthened by data presented in Fig. 2. Thesmallest size class exhibited the largest decline in stemabundance in the period between the two enumerationperiods. However, a combination of poor recruitment

and fast growth into larger size classes may also beresponsible for the decline in stem abundance of thesmallest size class exhibited in Fig. 2.

Only Chrysophyllum albidum and F. latifolia, exhib-ited signi¢cant increases in stem abundance. However,whereas the basal area of C. albidum also increased, thebasal area of F. latifolia did not. These observations areimportant in forest management and conservation,especially where tropical forests are managed for sus-tainable timber production. The fruits of C. albidum and

Fig 2 Frequencyof trees in increasingd.b.h. classes for the two enumerationperiods in132 (0.025 ha) plots at Ngogo,Kibale National Park, Uganda (1980 and1997).

Table 3 Abundance and diameters of eight species present in1997^98 thatwere not recorded in the1975^80 sample

Species No. of stems recorded Diameter at breast height (cm)

Albizia coriaria 1 17.8Albizia grandibracteata 2 13, 9.3Anthocleista vogelii 2 16, 19Crotonmacrostachys 1 20.1Ficus congensis1 2 ^Macaranga schweinfurthi2 1 69Phyllanthus discoidius 1 20Polyscias fulva 1 25.3

1The species is a strangler.Thus, d.b.h. was not measured.2Diameter was measured close to the ground because the tree hadmultiple stems.



the seeds of F. latifolia are eaten by primates and otheranimals, but the trees are also sources of marketabletimber (Hamilton, 1981; Katende, Birnie & Tongna« s,1995). The lack of increment in basal area, in spite ofthe increase in stem abundance for F. latifolia indicatesthat recruitment exceeds the mortality of large trees.Funtumia latifolia is a fast growing species and starts toreproduce when still small (<30 cm d.b.h.). In princi-ple, this species can be harvested sustainably becausethe removal of large individuals is likely to mimic nat-ural mortality. Because fruit production starts at anearly age, the animals will not be deprived of food andregeneration will not be a¡ected. On the other hand, C.albidum may not be compatible with sustainable har-vesting, unless the o¡-take is exceedingly small. Chry-

sophyllum albidum is a long-lived species in which fruitis produced byonly large trees.Another species that is worth mentioning is Newto-

nia buchananii. At the Kanyawara study area, Struhsa-ker et al. (1989) observed a 100% mortality of the adultN. buchananii trees in1984; they cited proximity to pineplantations as the probable cause of the dieback.Although there are still some live trees of this species atNgogo, the death of all ¢ve trees in our plots (Table1)and presence of dead standing trees in the area indi-cates that the species is also experiencing a dieback atNgogo. It is important to note that pines are absent fromNgogo and that the trees are probably dying from othercauses. This observation calls for long-term monitoringof the surviving trees.

Table 4 Results of paired t-tests on basal area (m2) per plot for selected species encountered in Kibale National Park, Uganda, during the1975^80 and1997^98 enumeration periods (n= 132 plots)

Mean basal area

Species 1997^98 1975^80 t-value2-tail signi¢canceP-value

All species1 1.2370 1.2169 �0.37 0.712 NSCeltis durandii1 0.0856 0.0914 ÿ0.71 0.482 NSChrysophyllum albidum1 0.0730 0.0548 �3.46 0.001Conophryngia holstii1 0.0078 0.0098 ÿ1.46 0.146 NSDiospyros abyssinica1 0.0978 0.0833 �2.28 0.024Funtumia latifolia1 0.0575 0.0520 �1.42 0.159 NSMarkhamia platycalyx2 0.0177 0.0204 ÿ1.03 0.304 NSPtrygota mildbraedii2 0.2443 0.2556 ÿ0.38 0.701 NSUvariopsis congensis1 0.0481 0.0410 �2.99 0.003Aphania senegalensis2 0.0032 0.0028 ÿ2.08 0.039 NSBosquiea phoberos2 0.0098 0.0080 ÿ1.69 0.093 NSCeltis africana2 0.0040 0.0048 ÿ0.66 0.508 NSLinociera johnsonii2 0.0020 0.0023 ÿ0.29 0.77 NSLovoa swynnertonii2 0.0538 0.0435 �1.20 0.232 NSMimusops bagshawei2 0.0564 0.0490 �2.44 0.016Millettia dura2 0.0034 0.0073 ÿ1.46 0.145 NSMonodora myristica2 0.0231 0.0236 ÿ0.13 0.893 NSNewtonia buchananii2 0.0 0.0366 ÿ1.74 0.084 NSOlea welwitschii2 0.0096 0.0345 ÿ0.88 0.383 NSPremna angolensis2 0.0101 0.0066 �2.10 0.038 NSPseudospondias microcarpa2 0.0042 0.0034 �1.50 0.136 NSRandia urcelliformis2 0.0001 0.0005 ÿ2.30 0.023Strombosia sche¡reli2 0.0228 0.0226 �0.18 0.855 NSTeclea nobilis2 0.0031 0.0052 ÿ1.47 0.145 NS

1Total number of stems was approximately equal to or greater than100 in at least one of the enumeration periods. 2Species was selectedfor analysis because it is important food source for primates but total number of stems was less than100.



Acknowledgements

Fieldwork was sponsored by Makerere University Biolo-gical Field Station and Uganda Wildlife Authority. Weare thankful to C. Chapman and J. Lambert for theirconstructive comments on the manuscript. Researchduring1975^80 was supported by grants from the NewYork Zoological Society toT.M.B. andT.T.S.

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(Maunuscript accepted 23 October1999)



tree population dynamics in kibale national park, uganda 1975–1998

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