Journal of VegetationScience 10: 825-832, 1999
? IAVS;OpulusPress Uppsala. Printed in Sweden
825
Tree species richness and turnover throughout New Zealand forests
Bellingham, P.J.1, Stewart, G.H.2 & Allen, R.B.1
1Landcare Research, P.O. Box 69, Lincoln, New Zealand;
Plant
&
2Soil,
Ecological Sciences Division, Lincoln University, P.O. Box 84, Lincoln, New Zealand;
*Correspondingauthor;Fax +64 3 325 2418; E-mail bellinghamp@landcare.cri.nz
Abstract. Patternsof mortality,recruitment,andforestturnoverwereinvestigatedusingpermanentplotdatafromtemperate
forestsin 14 localitiesthroughoutNew Zealand.Treemortality
fromtaggedtrees> 10cm
rateswerecalculated
andrecruitment
diameterat 1.4 m on individual400 m2plots,andturnoverrates
rates.
andrecruitment
werecalculated
as themeanof mortality
Turnoverrates (1.4% per year) were very similar to those
recordedfortropicalforests(i.e. 1.5%peryear). As was shown
in tropicalforests, we also found significantrelationshipsbetween forest turnoverand species richness. In New Zealand
foreststherewas alsoa decreasein speciesrichnessandturnlatitude.Althoughspeciesrichnessis
overrateswithincreasing
well knownto declinewith latitude,our studyprovidessupport
fora possiblelinkbetweenseasonalityanddisturbancewithtree
andrecruitandspeciesdiversity.Whiletreemortality
turnover
in balanceatsomelocalities,in
mentrateswereapproximately
otherstherewereimbalancesbetweenmortalityandrecruitmentrates.
Keywords: Browsing mammal;Disturbance;Latitude;Mor-
forest.
Temperate
tality;Recruitment;
Nomenclature:Allan(1961);King(1990).
Introduction
In tropicalrainforests, diversity (as measuredby species
richness) was found by Phillips et al. (1994) to be posi-
tivelycorrelatedwithtreeturnoverrates,i.e. theaverageof
rates. Theyconsideredthat
treemortalityandrecruitment
forests with higher turnover, and higher diversity, were
those subject to more frequent fine-scale disturbance. It is
unknownwhetherthe relationshipbetweenspecies richness and turnoverrates found by Phillips et al. (1994)
applies in less species-rich temperate forests. If there is a
positive relationshipbetween turnoverrates and species
richness in temperate forests, we might also expect a
negative correlation between turnover rates and latitude,
since there is generally a decrease in species richness of
forests with increasing latitude (e.g. Currie& Paquin 1987).
of geographicpatternsin turnoverandspecies
Correlations
richnesswith those environmentalvariablesthat change
with latitudedo not providea mechanisticexplanationfor
observedpatterns(Huston1999). Recently,Givnish(1999)
proposedthattreeturnovershoulddecreasewith increas-
ing latitudedue to increasingseasonality;this produces
conditionsless favourableto abundanceof naturalplant
enemies, i.e. insects and fungi which, at low latitudes,
cause more frequent tree death. If such geographic, or
environmental,
patternsin turnoverexist, they mayrepresenta mechanisticlinkto speciesdiversitypatternsresulting fromdisturbance.
Tree mortalityand recruitmentare also influenced
by many forms of disturbance,both naturalandhumaninduced(Pickett& White 1985). Afterintensivedisturbance, forest development often includes periods of
self-thinning,in stands with high stem density and/or
basal area, where high mortalityrates and low recruitment rates are apparent(Waring& Schlesinger 1985).
Disparitiesbetweenmortalityandrecruitmentrates,as a
result of disturbance,can also be pronounced at an
individual species level (Harcombe1987). For example, duringsuccession after disturbancethere are often
high mortalityrates and low recruitmentrates of early
successional species and the converse for late successional species (Veblen 1992).
In this paper,we investigatewhetherthere are relationshipsbetween forest turnoverratesand tree species
richness in New Zealand's temperaterain forests. We
also test whetherforestturnover,ortree species richness
are related to latitude. These relationshipsare tested
using tree census data from permanentplots sampling
14 localities throughoutNew Zealand. Forests at some
localities includedin this study are subjectto 'dieback'
events (sensu Mueller-Domboiset al. 1983) resulting
from naturalor human-induceddisturbance(e.g. Grant
1963;Pekelharing& Reynolds 1983;Ogdenet al. 1993).
In these forests, we examine whetherthere are imbalancesbetweenmortalityandrecruitmentrates,andcompare the resulting turnoverrates with those of forests
without 'dieback' elsewhere. Although turnoverrates
among all species allow comparisonsamong compositionally and structurallydifferent forests, individual
species responses are needed to determinecoexistence
mechanismsandsuccessionalchanges(Kohyama1993;
Condit et al. 1995). Because many New Zealandtree
species are widespread(Meurk 1995), we are also able
to test whether there are imbalances in mortality vs.
recruitmentfor individualspecies at differentlocalities.
826
Bellingham,P.J. et al.
1 176?E
35?S
35?S
40?S
40?S
45?S
5
0
o100
200
kilometres
176?E
I
Fig. 1. 14 localitiesin New Zealandwithlong-term(> 8 yr)
censusdatafrompermanent
forestplots.
Methods
We determinedforestturnoverrateson plots from 14
localities covering more than 8? latitude(Fig. 1) and a
range of underlying lithology, soils, and forest types
(Table 1). Broad forest types were defined for each
locality accordingto the basalareadominance,acrossall
plots, in a locality of: conifers; angiospermtrees other
thanNothofagus('hardwoods');andNothofagusspecies,
which often dominatestands (Ogden et al. 1996). All
localitieshaveat least 8 yearsof censusdata(maximum=
27 yr), sampledwith variousnumbersof permanent20m
x 20 m plots located along compass lines (see Allen
1993). The origin of each line, in each locality, was
located along a stream course in a restrictedrandom
fashion. Plots were thenlocatedat 200 m intervalsalong
these compasslines, except in KokatahiandWhitcombe
where plots were located at regularaltitudinalintervals,
thus at each locality the plots can be used to portraythe
average dynamics of the forests. Within each plot, all
stems> 10 cm diameterat 1.4 m height(dbh)weretagged
at measurementheightat the earliestcensus,mortalityof
taggedstemsnotedat latercensuses,andingrowthstems
(i.e., stemsthatgrewto become> 10 cm dbh)weretagged
at latercensuses.
Summariesof numbersof stems for each plot at each
census were derivedfrom Hall (1994). We calculateda
mortalityratefor all species combinedin each plot as an
annualpercentageof the initialstemsusing a logarithmic
model (McCune& Cottam1985; Sheil et al. 1995), and
calculateda recruitmentrateabovethe minimumsize (10
cm dbh)for each plot as an annualpercentageaccording
to a similarlogarithmicmodel (modifiedfrom McCune
andCottam1985). Turnoverratesper plot were defined
as the mean of mortality and recruitmentrates (after
Phillips& Gentry1994). Speciesrichnesswas calculated
for each plot as the numberof species > 10 cm dbh/400
m2, after Phillips et al. (1994). We also computed a
Shannon-Wiener
indexfor eachplot using stems> 10 cm
dbh(H', a frequentlyusedmeasureof species diversityas
well as dominance;e.g. Magurran1988; Tilman et al.
1996). Stemdensityandbasalarea(all of stems2 10 cm
dbh at the most recentcensus) were calculatedfor each
plot as surrogatesfor standdevelopmentfollowing disturbance (Harper 1977). We examined relationships
between the three demographicrates (i.e. mortality,recruitmentand turnoverrates),latitude,species richness
and diversity,as well as stem density and basal area as
variablesfor each plot using generalisedlinear models
(GLMs, Crawley 1993), with variables nested within
localities. We also relatedthe mean of the demographic
ratesperlocalitywiththe meanaltitudeand meanannual
rainfallof the localities using Spearman'srankcorrelations. Demographicrateswerecomparedbetweenlocalities for four widespread common tree species, i.e.
NothofagusmenziesiiandNothofagussolandrivar.cliffortioides (both Fagaceae), Podocarpus hallii (Podocarpaceae),andWeinmanniaracemosa(Cunoniaceae).Demographicrates were also comparedfor each species
with the mean proportioneach comprisedof total stem
densityandtotalbasalarea. Forindividualspeciesanalyses, the totalnumberof stemsof each species was aggregatedacrossall plots at a locality,anddemographicrates
computedacrossall plots.
All percentagedata were arcsine square-roottransformedfor analysis.Generalisedlinearmodelswere conductedin S-Plus version4.0 (Anon. 1997). Spearman's
rankcorrelations(rs) and ANOVA tests were conducted
using SYSTATversion7.0 (Wilkinson1997).
Results
All species combined
Across all plots, therewere significantnegativerelationshipsof latitudewith treemortality,recruitmentand
turnoverrates (GLMs, F14 659 = 1.84, 1.89 and 2.39
respectively,all P<0.05, Fig. 2). Mortality,recruitment
and turnoverrates were also significantly differentbetween the 14 localities (GLMs,F13673= 9.82,22.25 and
16.33 respectively,all P<0.01, Table 2).
- Tree species richness and turnover throughout New Zealand forests -
827
Table 1. Site details of forests in various localities in New Zealand.
Locality
Foresttype
Pirongia
Okataina
Pureora
Hardwood
37?59'S,175?02'E Basalt
Hardwood-conifer 38?08'S,176?27'E Recentvolcanictephras
Hardwood-conifer 38?23'S,175?35'E Ignimbrite
Mixed Nothofagus39?03'S,175?58'E Greywackeoverlain
hardwood
withvolcanicash
39?15'S,176?25'E Greywacke
Nothofagus
(mono-dominant)
Mixed Nothofagus41?00'S,175?13'E Greywacke/Argillite
hardwood
MixedNothofagus 41011'S,172?38'E Limestone
Hardwood-conifer 42?57'S,171?12'E Schist
Hardwood-conifer 43?05'S,171?01'E Schist
43?10'S,171?35'E Greywacke/Argillite
Nothofagus
(mono-dominant)
Mixed Nothofagus
44?52'S,168?13'E Greywacke/Argillite/
- conifer
Siltstones
Kaimanawa
Kaweka
Tararua
Mt. Arthur
Kokatahi
Whitcombe
Craigiebur
Caples
Greenstone
Murchison
MixedNothofagus
44?57'S,168?15'E
Mixed Nothofagus-
45?18'S,167?38'E
Mixed Nothofagus-
46?12'S,167?04'E
- hardwood
Waitutu
hardwood-conifer
Soils*
Latitude,Longitude Lithology
Dystrochrepts
Udorthents
Vitrichapludands
Vitrichapludandsand
vitrandricdystrochrepts
Vitrandric
dystrochrepts
Dystrochrepts
Elevation
mean(m), (range)
Rainfall
(mm)t
470 (200-760)
480 (320-800)
530 (350-850)
1600
2060
1770
860 (240-1210)
1530
1180 (920-1400)
720 (530-1080)
1580
2750
1160 (1080-1270)
2400
Endoaquepts
andendoaquepts 590 (320-780)
6000-8000
Humaquepts
andendoaquepts 560 (250-850)
8090
Humaquepts
1050(640-1420) 1400-2500
Dystrochrepts
Dystrochrepts
680 (290-1140)
2300
Greywacke/Argillite/ Dystrochrepts
Siltstones
Gneissandgranite
Dystrochrepts
750 (290-1140)
2300
690 (210-1090)
2400-4500
260(3-890)
1160
and
Sedimentaries
alluvium(glacial
outwashandmarine)
and
Haplorthods
dystrochrepts
* Soil classificationsfollow US Departmentof Agriculture(Anon.1998).
t Rainfallestimatesare from the nearestrainfallstation(Anon. 1973) for all localitiesexcept Kokatahi(estimatedfrom Griffiths& McSaveney1983),
Whitcombe(datafromGriffiths& McSaveney1983),Craigieburn
(datafromHarcombeet al. 1998)andMurchison(datafromtworainfallstationsin thestudy
area,W.G.Lee, pers.comm.).
Both species richness and species diversity (Shannon-WienerH) declinedwith latitude(GLMs,F14 659 =
5.75 and 4.67 respectively, both P < 0.01), and were
highly significantlydifferentbetweenlocalities (GLMs,
F13 673 = 133.55 and 149.96 respectively, both P<
0.001, Table 2). Species richnessanddiversitydeclined
with increasing mean altitude of localities (rs = -0.81
and -0.78 respectively, both P <0.002), but were not
significantly correlated with mean rainfall of localities
(rs = 0.02 and 0.01 respectively, both P >0.1).
Across all localities, there were positive relationships between tree mortality, recruitment and turnover
rates and species richness (GLMs, F14 659 = 2.30, 2.01
and 2.05 respectively, all P<0.025, Fig. 3), and species
diversity (H) (GLMs, F14 659 = 2.60, 2.32 and 2.56
respectively, all P < 0.01, Fig. 4).
Across all plots, tree mortality, recruitment and turnover rates of all species combined were highest when
total stem density was lowest (Table 2, GLMs, F14 659 =
3.09, 1.97 and 2.59 respectively, all P<0.025). Similarly, tree mortality, recruitment and turnover rates of all
species combined declined with increasing plot basal
area (Table 2, GLMs, F14 659 = 5.38, 3.41 and 6.95
respectively, all P< 0.01). Species richness increased
with increasing stem density and plot basal area (GLMs,
F14 659 = 5.45 and 2.39 respectively, both P< 0.01).
Likewise, species diversity (H) increased with increasing stem density and plot basal area (GLMs, F14 659 =
4.52 and 2.25 respectively, both P<0.025).
In most localities, mortality and recruitment rates
4 3.5 -
0
3Ca
I->.
0)
0
0
2.5-
0.
2-
a,
0q
1.5-
a1 -
0*
o
0o
0.50
0
0
a
0
0
000o 0
o
o
t
35
37
39
41
43
45
47
Latitude (degrees)
Fig. 2. Mean mortality rates ()) and recruitment rates (O) of
tree stems > 10 cm dbh in permanent forest plots in 14
localities in New Zealand vs latitude.
828
Bellingham,P.J. et al.
4 -
43.5-
3.5 -
0
a)
2.5-
(a
0
0
.
2-
a)
-
0
0
a)
0
3 -
3-
0
2.5-
a)
1.5 -
0
O
1-
0
0O
0.5-
u
0
0
I
a)
1.5-
0
.
0@
00
1 -
0
0
0
2 -
*
0O *
0
00
*
0
0
0
0.5
I
I
I
2
4
6
n
U
8
I
I
I
I
0
1
2
3
Species richness (number/400 m2)
Species diversity(H')
rates(0) of
Fig. 3. Meanmortalityrates(0) andrecruitment
treestems> 10 cm dbhvs meanspeciesrichness(numberof
forestplotsin 14localities
species> 10cmdbh)in permanent
in New Zealand.
rates(O)of
Fig. 4. Meanmortalityrates(0) andrecruitment
treestems> 10 cm dbhvs meanspeciesdiversity(ShannonWienerH', calculatedon stems> 10 cm dbhperspecies)in
forestplotsin 14 localitiesin New Zealand.
permanent
were similar,i.e. <0.5%/yr differencebetween the two
rates (Table 2). The greatestdifferencesbetween mortality and recruitmentrates were in Craigieburn(high
altitude mono-dominant Nothofagus solandri var.
cliffortioides forests), where mortality rates exceeded
recruitmentrates by 1.1%/yr, and in Pirongia (hardwood forests), where recruitmentrates exceeded mortality ratesby 1.3%/yr. Therewas no consistentpattern
of discrepancies (i.e. positive or negative differences
between mortalityand recruitmentrates)thatrelatedto
species richnessor diversity,latitude,altitudeor rainfall
of localities, or mean plot stem density or basal area(rs
all <0.38, all P>0.1).
Individualspecies
Across all localities present, the mean recruitment
rates of the conifer Podocarpus hallii ( x = 0.4 ?0.2%/
yr) were significantly lower than those of the three
angiospermspecies (Nothofagussolandri var. cliffortioides:0.9?0.1 %/yr;Nothofagusmenziesii:1.1?0.19%/
yr; Weinmanniaracemosa: 1.4 0.28%/yr; Table 3,
ANOVA, P=0.01). Mortalityand turnoverrates were
not differentamongthe four species (Table3, ANOVA,
P> 0.05). Mortality rates of W. racemosa exceeded
recruitmentratesby 4.8%/yrin Pureora,but in Pirongia
and Kaimanawarecruitmentrates of W. racemosa ex-
Table 2. Species diversityandrichnessas well as mortality,recruitmentandturnoverratesof trees > 10 cm dbhin forests at various
localitiesin New Zealand.
Locality
Pirongia
Okataina
Pureora
Kaimanawa
Kaweka
Tararua
Mt Arthur
Kokatahi
Whitcombe
Craigiebur
Caples
Greenstone
Murchison
Waitutu
No. of plots
and total
area(ha)
Trees/
400 m2
20 (0.80)
36 (1.44)
28 (1.12)
40(1.60)
30 (1.20)
10 (0.40)
34 (1.36)
22 (0.88)
23 (0.92)
250 (10.00)
20 (0.80)
29 (1.16)
38 (1.52)
107 (4.28)
29.1
46.3
27.1
16.0
31.0
45.8
47.3
35.6
44.6
41.8
20.7
27.0
29.5
32.0
Basal area Diversity
index
(m2/
400m2)
(H)
1.55
1.92
1.47
2.68
1.56
2.66
2.00
1.96
2.81
1.83
2.03
2.57
2.57
3.03
1.87
1.50
2.02
1.32
0.63
1.26
0.54
1.93
2.33
0.01
1.15
0.55
0.90
1.72
Species
richness
(species/
400 m2)
Time
(years)
Inventory
period
5.9
4.8
6.2
3.5
2.4
4.0
1.8
5.6
7.8
1.0
3.0
1.9
2.9
5.2
8
8.7
18.7
8.6
13.9
20.8
8.7
23.2
26.8
19.2
21
13
22.6
19.1
1979-1987
1983-1992
1975-1993
1979-1988
1981-1995
1975-1996
1978-1987
1972-1995
1972-1999
1974-1994
1976-1997
1976-1989
1976-1998
1978-1997
Mortality Recruitrate
ment rate
(%/yr)
(%/yr)
2.1
1.0
2.3
2.7
2.2
0.6
0.6
2.0
1.4
1.7
1.0
1.2
1.4
1.0
3.5
0.8
2.3
2.5
1.0
0.8
1.2
1.8
0.9
0.5
0.8
1.2
1.0
0.7
Turnover rate
(%/yr)
2.8
0.9
2.3
2.6
1.6
0.7
0.9
1.9
1.1
1.1
0.9
1.2
1.2
0.9
- Tree species richness and turnoverthroughoutNew Zealandforests -
829
Table 3. Demographicratesof trees> 10 cm dbhof four species in forestsat variouslocalities in New Zealand. P = meanpercentage
T = turnover
rate(%/yr);
rate(meanof mortality
rate(%/yr);R = recruitment
eachspeciesformsof totalstemsperplot;M= mortality
andrecruitment
rate,%/yr).
P
Pirongia
Okataina
Pureora
Kaimanawa
Kaweka
Tararua
Mt Arthur
Kokatahi
Whitcombe
Craigieburn
Caples
Greenstone
Murchison
Waitutu
Nothofagussolandri
var. cliffortioides
Nothofagus
menziesii
Locality
M
R
T
55.7
2.0
2.1
2.1
27.8
46.8
0.3
0.3
0.7
1.2
0.5
0.8
39.3
47.1
27.6
22.1
1.1
1.1
1.5
0.7
0.7
1.1
1.1
0.6
0.9
1.1
1.3
0.6
P
M
R
P
T
79.5
2.0
1.0
1.5
51.4
1.1
1.4
1.2
99.9
27.1
33.8
44.7
14.8
1.4
0.7
1.4
1.1
1.2
0.5
0.9
1.3
0.8
0.6
ceeded mortalityrates by 1.4%/yrand 1.1%/yr(Table
3). For the other six localities in which W. racemosa
was common,recruitmentandmortalityrateswere similar. MortalityandrecruitmentratesofN. menziesiiwere
generally similar at most localities, with the greatest
discrepancyat Mt Arthurwhere recruitmentrates exceeded mortality rates by 0.9%/yr (Table 3). While
recruitmentrates of N. solandri var. cliffortioideswere
similar to, or slightly exceeded, its mortality rates in
most localities (Table 3), mortalityrates of this species
greatly exceeded recruitmentrates in two montaneforests where it was mono-dominant (by 1.1%/yr in
Craigieburnand 1.0%/yrin Kaweka). Mortalityratesof
P. hallii, a minorcomponentof six forests, were higher
thanrecruitmentratesin four localities (Table 3). Most
notably, 3.1%/yrmortalityof this conifer in Kokatahi
over 23 yr contrastswith nil recruitmentover the same
period (Table 3), with a less extreme contrastbetween
0.4%/yr mortality and nil recruitmentover 21 yr in
Caples, and a disparitybetween 2.8%/yrmortalityand
0.9%/yrrecruitmentover 14 yr in Kaweka.
Mortalityandrecruitmentratesof W.racemosawere
greatestwhen total stem density was lowest (rs = -0.85
and-0.87 respectively,bothP<0.01). Mortalityratesof
N. menziesiiwere also greatestat least total stem density
(rs = -0.86, P< 0.05), although its recruitmentrates
were not significantlycorrelatedwith total stemdensity.
Mortality and recruitmentrates of N. solandri var.
cliffortioidesand P. hallii were not significantlycorrelated with total stem density (rs = 0.14 and-0.07 for N.
solandri var. cliffortioides and -0.14 and 0.29 for P.
hallii, all P > 0.1). For three species (N. menziesii, N.
solandri var. cliffortioidesand P. hallii) there were no
significantcorrelationsbetween demographicratesand
the proportioneach species formed of total stems in
Weinmannia
racemosa
Podocarpus
hallii
0.9
0.8
1.3
1.0
0.9
M
R
T
P
M
R
T
38.2
32.0
6.5
10.1
1.4
0.8
6.6
1.6
2.8
0.3
1.8
2.7
2.1
0.5
4.2
2.1
4.6
2.0
2.8
0.0
0.9
0.9
1.8
0.4
52.8
0.5
0.9
0.7
2.8
9.2
3.1
1.4
0.0
0.2
1.5
0.8
24.2
27.9
1.0
0.6
0.9
0.8
1.0
0.7
5.5
0.4
0.0
0.2
3.4
0.5
0.5
0.5
9.2
35.8
1.2
0.7
1.3
0.8
1.3
0.7
each locality (Spearman'scorrelations,all P>0.1). In
the case of W. racemosa, there was a weak correlation
between mortalityrate and the proportionof stems it
comprisedin a stand(rs = -0.67, P<0.1). Mortalityand
recruitmentrates of the four species were not significantly correlated with mean plot basal area in each
locality, or with the proportionthat each species comprisedof the basal areaof plots.
Discussion
The relationshipbetween turnoverand species richness found by Phillips et al. (1994) in tropicalforests
was also apparentin our analyses of datafrom throughout New Zealand's temperate forests. Within New
Zealand,it has long been noted thatthereis a decline in
tree species richness with latitude (Cockayne 1928;
Wardle 1991). Productivityis consideredby many to
decreasewith increasinglatitude(e.g. Adams & Woodward 1989), so the additional relationship we found
between turnover rates and latitude may in part be
relatedto increasingproductivitywith decreasinglatitude (Givnish 1999), and in our study this trend was
evident within some localities and thus may operatea
fine scale. However,others(e.g. Huston 1999) consider
that productivityincreases with increasinglatitude. If
this is the case, other explanationsfor decreasingturnover with latitudeareneeded. One possible explanation
for higher turnover rates in New Zealand forests at
lower latitudesmay be more frequentdisturbance.For
example, cyclones of tropical origins affect forests at
low latitudesmore frequentlythanthose at high latitude
(Shaw 1983). Such disturbancesmay cause more frequent mortality of canopy trees in forests at low lati-
830
Bellingham,P.J. et al.
tudes, hence more rapidturnover. The relationshipwe
show between declining tree turnoverwith increasing
latitude (Fig. 2) gives supportto the types of mechanisms proposedby Givnish (1999). His explanationfor
these phenomenaare that at high latitudes, conditions
are less favourablefor pathogensand insects thataccelerate rates of tree death, thus mortalityrates are lower
andhence thereis a lower tree species diversity. Lower
species diversity in some New Zealand forests is also
likely where they have been isolated for millions of
years and subjectedto repeatedlocal extinctionsduring
glacial periods (McGlone 1988, 1996). An ability to
also incorporatethese landscapestabilityprocesses, as
well as turnover,may allow us to explainnational-scale
diversity patterns more comprehensively (McGlone
1985; Huston 1999).
Contemporarydisturbanceinfluences on New Zealand's forests (e.g. drought,cyclones, vulcanism, and
earthquakes)are likely to have enduring effects on
forest dynamics (Wardle 1991). For example, natural
'diebacks' in high altitudemono-dominantNothofagus
solandri var. cliffortioidesforests have occurredin two
of the studylocalities (Wardle1983, Ogdenet al. 1993).
Mortalityrates exceeded recruitmentratesin these forests by 1.1%/yr in Craigiebur, and by 0.9%/yr in
Kaweka; such imbalances between mortality and recruitmentrates in forests, and among individual tree
species, areoften indicativeof adjustmentsto pastmajor
disturbances(Nakashizuka1991). In the case of the two
mono-dominantN. solandri var. cliffortioides forests,
we attributeobserved imbalances in mortalityand recruitment rates to past disturbance (wind and snow
storms and pathogens at Craigiebur, Harcombeet al
1988; drought and pathogens at Kaweka, Hosking &
Hutcheson1988). Followingwidespreaddeathof canopy
trees there is a lag between mortalityand recruitment
(Ogden et al. 1993; Harcombe et al. 1998), thus we
expect in the future,recruitmentrates will exceed mortality ratesin these two localities. The rangeof mortality, recruitmentand turnoverrates among the 14 New
Zealand forests were not different from those at low
latitudesin 65 tropicalrain forests (Phillips 1996; mortality: x = 1.5%/yrNew Zealand, 1.5%/yrtropics;recruitment:1.4%/yr,1.6%/yr;turnover:1.4%/yr,1.6%/
yr; unpairedt-tests, all P>0.2). While no attemptwas
made to remove forests thatare subjectto majordisturbances from the New Zealand dataset, this was attemptedin the case of the tropicalforestdatasets used in
Phillips's (1996) analysis.
New Zealandforests are also widely influenced by
the impacts of browsing mammalsintroducedlast century (Wardle 1991). Amongst the most widespread
introducedanimalsare brushtailpossums (Trichosurus
vulpecula),marsupialsnativeto Australia,introducedto
New Zealand in 1858 (Cowan 1990). Brushtailpossums selectively browse foliage of certaincanopy tree
species andhave caused treedeathin some species (e.g.
Meads 1976). Of the four individualspecies we examined in this study, Weinmanniaracemosa and Podocarpushallii areboth commonin brushtailpossumdiets
(Fitzgerald 1976; Coleman et al. 1985; Rogers &
Leathwick 1997), and the local mortalityof these two
species has been attributedto theirbrowsing (e.g. Rose
et al. 1992). In contrast,Nothofagusspecies, including
the two species considered in this study, are scarcely
representedin the diet of brushtailpossums (Wardle
1984; Owen & Norton 1995). We found no evidence
that forests where tree species palatable to brushtail
possums predominate, and where brushtail possums
havebeen presentfor severaldecades,have consistently
highermortalitythanforests dominatedby the unpalatable Nothofagusspecies.
Compensatoryrecruitmentof Weinmanniaracemosa
offset its mortalityin all localities in our study except
Pureora(Table 3). High turnoverof W. racemosa was
evident in stands of low total stem density. In the
Orongorongoforestsstudiedby Campbell(1990), where
therewas high mortalityof W.racemosa,it was a minor
componentof the forests. For the nine localities in our
study where W. racemosa was common there was a
weak negative relationshipbetween its mortalityrates
and the proportionof total stems contributedby this
species. Furtherdata from other localities are required
to determine whether there is a relationshipbetween
mortalityratesof this species and its abundance.While
turnoverrates across all species are approximatelyin
balancein forests dominatedby trees browsedby introduced mammals,those of individualpalatablespecies
may not be in balance. For example, whereasmortality
and recruitmentrates of W. racemosa were similar in
most localities in our study, this was often not the case
for Podocarpus hallii, especially in Kokatahi where
high mortality (3.1%/yr) and no recruitmentover 23
years suggests that it may become locally extinct as a
canopy species (cf. Wardle 1978).
Duringsuccessional changein New Zealandforests
whereNothofagusmenziesiico- occurswith N. solandri
var. cliffortioides, Wardle (1983) hypothesised N.
menziesiiwould progressivelydominatestandsas they
aged. This expectationwould be fulfilled at a locality
scale where N. menziesii recruitmentrates exceed its
mortalityand whereN. solandri var. cliffortioidesmortality rates exceed its recruitment. In this study, there
were threelocalities whereN. menziesiiandN. solandri
var. cliffortioideseach contributedsimilar proportions
of individuals,and in combination>70% of stems (Mt
Arthur,Caples and Greenstone,Table 3). At one locality, Mt Arthur,N. menziesiirecruitmentratesmarkedly
- Tree species richness and turnover throughout New Zealand forests -
exceeded mortalityrates, but we did not find the other
requirement of N. solandri var. cliffortioides mortality
rates exceeding recruitment.Therefore we found no
evidence fromlong-termcensus dataof gradualreplacement of N. solandri var. cliffortioides by N. menziesii in
mixed standsat a locality scale, and it is more likely to
be a process thatoperatesat a finer (plot) scale.
The networkof spatiallyextensive small permanent
forestplots in New Zealand(ca. 6500 nationally,mostly
establishedin the 1970s) gives opportunitiesfor understandinglong-term changes in forests, both nationally
andregionally,in relationto successionaltrends,withinspecies competitiveinteractions(Osawa & Allen 1993)
andeffects of introducedherbivores(Stewart& Burrows
1989). The potentialis being expandedandrealisedwith
the reportingrequirementsof internationalagreements
(e.g. Conventionon Biological Diversity). Forexample,
New Zealand's plot networkhas been used recentlyto
develop a 1990 estimateof carbonstoredin indigenous
forests, a requirementof the FrameworkConventionon
Climate Change (Hall et al. 1998). Phillips & Gentry
(1994) showed increasingturnoverratesin tropicalrain
forests with time, and they believed this was a likely
consequenceof increasedatmosphericCO2. New Zealand's nationalnetworkof permanentplots, in combination with similarnetworksof plotsin othercountries,will
be ableto help evaluationof whethersucha phenomenon
is true,and,if so, whetherit is widespread.
Acknowledgements. We acknowledgethe use of information
drawnfrom the NationalVegetationSurvey (NVS) database.
JohnWardlehada pivotalrolein thedesignandestablishmentof
plotsthatcontributedto this study. Earliestcensusesof theplots
and surveydesign were conductedby staff of the formerNew
ZealandForest Service and more recent censuses have been
conductedby the authorsandby staffof, andcontractorsto, the
Departmentof ConservationandtheWellingtonRegionalCouncil. We thank Bruce Kyle, Cathy Allan and Wayne Baxter
(Departmentof Conservation)for access to datacollectedfrom
Caples,MurchisonandWaitutu.DavidCoomesassistedin data
analysis. Trevor Webb provided soil classificationsfor the
localities. KirstyCullen draftedthe figures. We thankTohru
Nakashizukaand Bastow Wilson for helpfulcommentson the
manuscript.GHS receivedsupportfromthe JapaneseMinistry
of Education,Science and Cultureto attendthe workshopin
Kyoto. This study received financial supportfrom the New
ZealandFoundationforResearch,ScienceandTechnology(ContractNo. C09633).
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Received 14 April 1998;
Revision received 28 May 1999;
Final revision received 28 October1999;
Accepted 29 June 1999.