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Disturbance history is a key driver of tree lifespan in temperate primary forests

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Aims We examined differences in lifespan among the dominant tree species (spruce (Picea abies (L.) H. Karst.), fir (Abies alba Mill.), beech (Fagus sylvatica L.), and maple (Acer pseudoplatanus L.)) across primary mountain forests of Europe. We ask how disturbance history, lifetime growth patterns, and environmental factors influence lifespan. Locations Balkan mountains, Carpathian mountains, Dinaric mountains. Methods Annual ring widths from 20,600 cores from primary forests were used to estimate tree life spans, growth trends, and disturbance history metrics. Mixed models were used to examine species-specific differences in lifespan (i.e. defined as species-specific 90th percentiles of age distributions), and how metrics of radial growth, disturbance parameters, and selected environmental factors influence lifespan. Results While only a few beech trees surpassed 500 years, individuals of all four species were older than 400 years. There were significant differences in lifespan among the four species (beech > fir > spruce > maple), indicating life history differentiation in lifespan. Trees were less likely to reach old age in areas affected by more severe disturbance events, whereas individuals that experienced periods of slow growth and multiple episodes of suppression and release were more likely to reach old age. Aside from a weak but significant negative effect of vegetation season temperature on fir and maple lifespan, no other environmental factors included in the analysis influenced lifespan. Conclusions Our results indicate species-specific biological differences in lifespan, which may play a role in facilitating tree species coexistence in mixed temperate forests. Finally, natural disturbances regimes were a key driver of lifespan, which could have implications for forest dynamics if regimes shift under global change.
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J Veg Sci. 2021;32:e13069.    
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https://doi.org/10.1111/jvs.13069
Journal of Vegetation Science
wileyonlinelibrary.com/journal/jvs
Received:5Januar y2021 
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Revised:12July2021 
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Accepted:20July2021
DOI : 10.1111/j vs.130 69
RESEARCH ARTICLE
Disturbance history is a key driver of tree life span in
temperate primary forests
Jakob Pavlin1| Thomas A. Nagel1,2 | Marek Svitok3,4| Joseph L. Pettit1|
KrešimirBegović1| Stjepan Mikac5| Abdulla Dikku6| Elvin Toromani7|
Momchil Panayotov8| Tzvetan Zlatanov9| Ovidiu Haruta10| Sorin Dorog10|
Oleh Chaskovskyy11| Martin Mikoláš1| Pavel Janda1|MichalFrankovič1|
Ruffy Rodrigo1|OndřejVostarek1| Michal Synek1| Martin Dušátko1|
TomášKníř1| Daniel Kozák1| Ondrej Kameniar1|RadekBače1|VojtěchČada1|
VolodymyrTrotsiuk1,12,13| Jonathan S. Schurman1| Mélanie Saulnier1,14|
Arne Buechling1| Miroslav Svoboda1
1Depar tment of Forest Ecology, Faculty of Forestr y and Wood S cience s, Czech University of Life Sciences Pra gue, Pr ague, C zech Republic
2Depar tment of Forest ry and Renewab le Fores t Resources, Biotechni cal Faculty, University of Ljubljana, Ljubljana , Slovenia
3Depar tment of Biolog y and Ge neral Ecology, Faculty of Ecology an d Environmental Sciences, Technical Universit y in Zvolen , Zvolen, Slovakia
4Depar tment of Ecosystem Biolo gy, Facult y of Scien ce, Universit y of South Bohemia, Ceske B udejovice, Czech Republic
5Depar tment of Forest Ecology a nd Silviculture, Facult y of Forestry, Universit y of Zagreb, Zagre b, Croatia
6PSEDA-ILIRIAOrganization,Tirana,Albania
7FacultyofForestrySciences,AgriculturalUniversityofTirana,Koder-Kamez,Albania
8Depar tment of Dendro logy, Universit y of Fores try S ofia, Sofia, Bu lgaria
9InstituteofBiodiversityandEcosystemResearch,BulgarianAcademyofSciences,Sofia,Bulgaria
10Fores try and Fores t Engine ering D epar tment , Univer sity of O radea, Oradea, Romania
11Institute of Forest Management, Ukrainian National Forestry University, Lviv, Ukraine
12Swiss Federal Ins titute for Forest, Snow and Landscape Resea rch WSL , Birme nsdor f, Switze rland
13Depar tmentofEnvironmentalSystemsScience,InstituteofAgriculturalSciences,ETHZurich,Zurich,Switzerland
14CentreNationaldelaRechercheScientifique/FrenchNationalCentreforScientificResearch,UMR5602LaboratoireGéode,Aix-MarseilleUniversit y,Aix-en-
Provence, France
©2021InternationalAssociationforVegetationScience
Correspondence
Jakob Pavlin, Departm ent of Forest
Ecology, Faculty of Forestr y and Wood
Science s, Czec h Univer sity of L ife
SciencesPrague,Kamýcka129,16521
Prague, Czech Republic.
Email: pavlinj@fld.c zu.cz
Funding information
This proj ect was suppor ted by th e
institutionalprojec t“EVA4.0”,No.
CZ.02.1.01/0.0/0.0/16 _019/0000803,
MSMT project LTT20016, Internal
GrantAgencyCULS(A_19_21;JP),and
Programme Integrated Infrastructure
(OPII)fundedbytheERDF(ITMS
313011T721;MSvi)
Abstract
Aims: Weexamineddifferencesinlifespanamongthedominanttreespecies(spruce,
Picea abies; fir, Abies alba; beech, Fagus sylvatica; and maple, Acer pseudoplatanus)
across primary mountain forests of Europe. We asked how disturbance history, life-
time growth patterns, and environmental factors influence life span.
Locations: Balkan Mountains, Carpathian Mountains, Dinaric Mountains.
Methods: Annual ring widths from 20,600 cores from primary forests were used
to estimate t ree life spans, growt h trends, and dist urbance histor y metrics. Mixed
models wereused to examine species-specific differences inlife span (i.e.,defined
asspecies-specific 90th percentiles ofagedistributions),and how metrics ofradial
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1 | INTRODUCTION
Tree life span plays an important role in the structure and function
offorestecosystems.Asakeylifehistorytrait,differencesinthelife
spanofcompetingspeciesmaycontributetotree coexistence in a
varietyof forestcommunities(Veblen,1986;Lertzman,1995;Lusk
&Smith,1998;Loehle,2000).Treelifespanalsohas importantim-
plications for carbon sequestration and residence time, particularly
within th e context of glob al change, whe reby faster grow th rates
andtreeturnovermayshortentreelifespan,therebyreducinglong-
term car bon storage in fore sts (Bugmann & B igler, 2011; Körner,
2017;Büntgenetal.,2019;Martin-Benitoetal.,2021).Finally,trees
thatapproachtheirmaximumlongevitydevelopuniquemorpholog-
icalcharacteristicsandmicrohabitats(VanPelt,2007),featuresthat
provide im portant hab itat for a variet y of forest-dwelling spe cies
(Fritz&Heilmann-Clausen,2010;Lindenmayer&Laurance,2017).
Despite the fundamental importance of tree life span, determining
whether there are biological differences in the life span of competing
treespeciesin manyforestcommunitiesremainsachallenge.Forexam-
ple, among the common tree flora of the European temperate region, the
widelyacceptedliteratureindicatesthatbeech(Fagus sylvaticaL.)andfir
(Abies alba Mill.) are among the most long-livedspecies (e.g., 450 year
maximum age), while maple (Acer pseudoplatanus L.) and spruce (Picea
abies(L.)H.Karst.)areclassifiedasmoderatelylong-lived(e.g.,300years)
(Leuschner & Ellenberg, 2017; Leuschner & Meier, 2018). However,
a number of site-specific studies carried out in old-growth remnants
throughout temperate mountain forests in Europe often find individual
stemsthatexceedtheselongevities(Biondi,1992;Bigler&Veblen,2009;
Motta et al., 2011; Nagel et al., 2014; Di Filippo et al., 2015; Di Filippo
etal.,2017;Piovesanetal.,2019).
Inaddition to species-specificlife history,elucidating the driv-
ers of life span within and among tree species has also proved chal-
lenging.A relativelylargebody of treering research has examined
the longstanding hypothesized tradeoff between tree growth rates
andlife span(Schulman,1954).Across multiple treetaxaspanning
a range of shade tolerances, past work has generally documented
a consistent negative relationship between radial growth rates and
lifespanwithin speciesforbothlive(Blacket al.,2008;Johnson&
Abrams , 2009; Di Filip po et al., 2012; Cas tagneri et al ., 2013; Di
Filippo et al.,2015; Brienen et al.,2020) and dead trees (Bigler &
Veblen,2009;Röthelietal.,2012;Bigler,2016;Büntgenetal.,2019)
In particular, many studies highlight that m aximum tree ages are
reachedwhentreesexperiencealongperiodofsuppressedgrowth
during early life stages. Other studies, however, have not found sup-
portforatradeoffbetweenradialgrowthratesandlifespan(Ireland
etal.,2014;Cailleretetal.,2017).
Aspreviousauthorshave pointedout, it is not entirelyclearto
whatextent the relationshipbetween growthrates and life spanis
regulatedbyspecies-specificlifehistory,genetics,orenvironmental
constraints(Büntgenetal.,2019).Severalofthestudieshighlighted
above show substantial variation in growth rates and life span
among individual trees within a species at the same site, which likely
reflects the unique grow th history and resource availability of trees
ina given neighborhood ofcompetitors (Black etal., 2008; Bigler,
2016).Thegrowthhistoryofatreeislargelyafunctionoflocaldis-
turbance histor y, which controls the trajectory of canopy accession.
Thisisespeciallythecaseinmulti-agedforestswheregapscaleand
Co-ordinating Editor:KerryWoods
growth, disturbance parameters, and selected environmental factors influence life
span.
Results: While only a few beech trees surpassed 50 0 years, individuals of all four spe-
cies were older than 400 years. There were significant differences in life span among
thefourspecies(beech> fir > spruce >maple),indicatinglifehistorydifferentiation
in life span. Trees were less likely to reach old age in areas affected by more severe
disturbanceevents,whereasindividualsthatexperiencedperiodsofslowgrowthand
multipleepisodesofsuppressionandreleaseweremorelikelytoreacholdage.Aside
from a weak but significant negative effect of vegetation season temperature on fir
and maple life span, no other environmental factors included in the analysis influ-
enced life span.
Conclusions: Ourresultsindicatespecies-specificbiologicaldifferencesinlifespan,
whichmayplayaroleinfacilitatingtreespeciescoexistenceinmixedtemperatefor-
ests. Finally, natural disturbance regimes were a key driver of life span, which could
have implications for forest dynamics if regimes shift under global change.
KEYWORDS
Disturbance, European beech, grow th patterns, life span, longevity, Norway spruce, silver fir,
site conditions, sycamore maple
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periodic intermediate severity disturbances drive stand dynamics
(Frelich & Lorimer, 1991;Nagel etal., 2014). In such forests, trees
that avoid suppression, grow fast as juveniles and reach large canopy
stature quickly, may be more likely to die early because residing in
the canopy increases exposureto common disturbance agents (Di
Filippoetal.,2015;Bigler,2016).Whileitisgenerallyassumedthat
trees will reach old ages on less productive sites sheltered from dis-
turbance(Larson,2001;Lanner,2002;DiFilippoetal., 2015), few
studies have quantified the relationship between local disturbance
historyandtreelifespaninmulti-agedforests.
In addition to local constraints on growth regulated by stand dy-
namics,larger-scaleenvironmentalfactorsmayalsoplayaroleinin-
fluencing life span within a species, such as climate and topography.
Life span h as been positivel y associated with n orth-facing slo pes
(Bigler &Veblen, 2009; Bigler,2016),south-facing slopes on drier
sites (T herrell & Stahl e, 1998)s lope steepne ss (Bigler, 2016), and
elevation(Splechtnaetal., 2000;DiFilippoetal.,2007;Di Filippo
et al., 2012; Röt heli et al., 2012; D i Filippo et al. , 2015), whereby
harsher site conditions are thought to increase longevity via reduced
growth rates. The link between temperature and life span is less
clear; forbroad-leavedspeciesin the NorthernHemisphere, some
late-successionalshade-tolerantspecies(e.g.,Fagusspp.)havebeen
found to reach older ages in colder part s of their range, while this
relationshipwasweakforshade-intolerantspecies(DiFilippoetal.,
2015).
Previous work focusing on tree life span has of ten relied on
datafromtheInternationalTree-RingDataBank(Blacketal.,2008;
Johnson & Abrams, 2009; Di Filippo et al., 2015; Brienen et al.,
2020), inwhich the samplingobjectives and strategy are not pre-
served in the metadata; in many cases, tree cores may have been
subjectivelysampledfromlargetreesgrowingonextremesitecon-
ditions, or tree growth may have been influenced by past land use
histor y. Other st udies that have explicitly sampled live and dead
trees to ex amine life span w ithin specie s have often bee n limited
tolocalsites(Larson,2001)orregionalscales(Bigler,2016;Lorimer
& Frelich, 1989), and do not permit assessment of environmen-
tal drivers at large scales or variation in life span across a species’
range.Here,wetakeadvantageofanunprecedenteddataset,con-
sisting ofplot-levelforest structuraldataincludingrandomlycored
livetrees(N =20,600),sampledwithinextantprimary-forestland-
scapes across the Carpathian Mountains and Balkan peninsula. The
plot network covers the dominant mountain forest communities in
Europe,spanningfrombeechtomixedbeech–fir,toNorwayspruce
forest t ypes. The data set allows a unique assessment of life span
within and among tree species, across gradients of stand structure
and disturbance history, and from local to subcontinental scales.
We ask if there are differences in life span among dominant
tree spe cies (i.e., spr uce, fir, beech, a nd maple). We first f ind evi-
dence that species-specific differencesinadult lifespan are partly
controlled by life history. We then ask how variation in life span
within species is influenced by a variety of different drivers, includ-
ing local disturbance history, lifetime radial growth patterns, and
environm ental fac tors availabl e in our data set ( i.e., slope, as pect,
temperature).Iflifespanisunderstrongenvironmentalcontrol,we
predict that older trees will be found on less productive sites, char-
acterizedby higherelevation,lowertemperature, and steepnorth-
facingslopes.Alternatively,iflocaldisturbancehistorycontrolslife
span, we predict that old trees will be found in areas with a history
oflow-intensitydisturbance (i.e.,gap dynamics)thatlack evidence
of more severe disturbance over the past few centuries. Individual
tree growth histories in such stands typically show long periods of
slow juvenile growth under the shaded understorey, followed by one
or several growth releases during canopy accession caused by the
deathofoverheadornearbyadulttrees(Nageletal.,2014).Finally,
weexamine howcommon exceptionallyold treesare withinthese
old-growthforestsites, whichhasimplications forconservation of
forest biodiversity.
2 | METHODS
2.1  |  Studyareaandsiteselection
This study was conducted in primar y temperate mount ain forests
of the Carpathian Mountains and the Balkan peninsula, spanning
frombeech-dominatedand mixedforests(hereafter referred to as
beech-dominated)atlowerelevationstospruce-dominatedforests
at higher elevations. These t wo regions contain the largest remnants
of primar y forests i n the temperate zon e of Europe (Janda e t al.,
2019;Mikolášetal., 2019;Nageletal.,2014;Sabatiniet al.,2018).
Primar y forests were characterized as unmanaged forests with natu-
ral stand composition, diverse horizontal, vertical, and age structure,
and a significant amount and diversity of downed and standing dead
trees in different stages of decomposition; most stands were typi-
cally inanold-growthstage of development,butearlyseralstages
developing after more severe natural disturbances were also present
intheseprimary-forestsites(Mikolášetal.,2019).Thedatasetused
forthisstudyisapartoftheREMOTEnetwork(formoredetailssee
www.remoteforests.org),whichisfocusedonsurveyingremaining
tractsofprimary-forestlandscapes inEurope andlong-term study
of their dynamics. The plot network has a hierarchical sampling
scheme, with plots located within stands, and multiple stands organ-
ized in larger landscapes. For the purposes of this study, we split
the data set into 11 landscapes, based on geographic location and
foresttype. Theyincludesevenbeech-dominatedlandscapes (i.e.,
Albania,Bulgaria,Croatia, CentralSlovakiabeech, EasternSlovakia
beech,NorthernRomaniabeech,andSouthernRomaniabeech)and
four spruce-dominated landscapes (i.e., Central Slovakia spruce,
Ukraine spruce, Northern Romania spruce, and Southern Romania
spruce). Th e landscape s comprise a tota l of 35 spruce-domin ated
stands,and33beech-dominatedstands(Figure1;AppendixS1.)
Norwaysprucecomprised99%ofalltreesinspruce-dominated
stand s, and was occasion ally mixed with fir, Pinus cembra L., and
Sorbus aucupariaL.Inbeech-dominate dstands,be echaccounte dfor
75%ofalltrees onaverage,followedbyfir(14%),spruce(7%),and
maple (2%);other lesscommonspecieswere sporadically present,
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such as Acer platanoides L., Acer obtusatumWaldst.&Kit.exWilld.,
Ulmus glabraHuds.,Fraxinus excelsior L., and Fraxinus ornus L.
2.2  |  Datacollection
Between 2010 and 2018, a net work of circular permanent sampling
plots wa s establis hed within ea ch primar y-fores t stand (A ppendix
S2). A strati fied rando m sampling de sign was used for p lot place-
ment, whereby plot s were randomly located within a regular grid
laid over each stand, with grid size depending on the size of stands.
In spruce l andscape s, a grid with eit her a 1- or 2-ha cell size wa s
used, and a circular plot of 1,000 m2(oroccasionally500m
2 in
recently disturbed areas where tree densities were high) was ran-
domlylocatedintheinteriorofeverycell(0.25or0.5ha).Inbeech-
dominatedlandscapes,a10-hagridwasused,andplotswereeither
1,500 or 2,000 m2.Arandompointwasgeneratedinthe0.5–3.4ha
interior of each grid cell, and a pair of plots was established 4 0 m
from either side of this point along the slope contour, such that plot
centers were separated by 80 m.
Thespeciesanddiameteratbreastheight(DBH)ofalllivetrees
≥10cmDBHwererecordedineachplot,aswellasthecrownpro-
jectionarea (neededfor the disturbance reconstruction described
below)of5–15treesperplot.Slope,aspect,andelevationwerealso
measured.Incrementcoreswereextractedfromrandomlyselected
non-suppressedtrees(i.e.,atleasthalfofthelivingcrownareaofthe
treewasexposedtodirectsunlight)ineachplottoobtaindataonlife
spans, lifetime growth patterns, and disturbance history. We took an
incrementcorefrom 15 (whensmaller plots were used)to30ran-
domlyselectedcanopytreesover10cmDBHoneveryplotinspruce
landscapes(forameanof24.1cores/plot).Inbeechlandscapes,we
cored all theliving trees≥20cmDBH and25%randomlyselected
treeswithDBHbetween10and20cmoneachplot(forameanof
33.9 cores/plot). Allcores were taken 1 m above the ground, and
perpendicular to the terrain slope direction to avoid reaction wood.
Datafrom13plotsaffectedbyrecent,stand-replacingdisturbances
wereexcludedfromfurtheranalyses.
2.3  |  Dataanalysis
In total, 20,60 0 increment cores were processed using standard den-
drochronological procedures. Each tree was represented by a single
core. Ring-width series were measured with a LintabTM sliding-
stage measuring system (Rinntech, Heidelberg, Germany; http://
www.rinntech.ds), cross-dated using marker years (Yamaguchi,
1991), and verifie d with COFECHA (Holmes , 1983) and CDe ndro
(Larsson,2003).Forsamplesthatdidnotintersectthepith,thenum-
berof missingringswasextrapolated from the curvature andaver-
agegrowthrates ofinnermost rings (Duncan, 1989). We excluded
all cores that had more than 20 estimated rings missing, or were of
poor quality and therefore did not allow tree rings to be measured
andcross-datedreliably.Intot al,3 ,50 0coreswe reomit tedfromfur-
theranalyses(320fir,74maple,2,790beech,and316sprucecores),
FIGURE1 Hierarchicaldesignand
spatial distribution of study plots. The
map shows the distribution of spruce
standsandbeech-dominatedstands
acrossthestudyregion(a),including
insetsofplotlocationswithin(b)spruce
and(c)beech-dominatedstands.The
numbers mark the forest landscapes: 1,
Albania;2,Bulgaria;3,Croatia;4,South
Romania beech; 5, North Romania beech;
6, East Slovakia; 7, Central Slovakia beech;
8, Central Slovakia spruce; 9, North
Romania spruce; 10, South Romania
spruce; and 11, Ukraine
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which resulted in a decrease in the overall mean diameter of cored
trees for eachspecies(from 31.4 cm to 28.0cmforfir,37.1cmto
34.4 cm for maple, 36.4 mm to 31.6 cm for beech, and 36.6 cm to
36.4cmforspruce).
Radial growth pat terns of increment cores were analyzed for
evidence of past disturbance events within each plot. Quantitative
reconstructions of disturbance histories for different regions of the
largerdatasetusedherehavebeenpublishedpreviously(Standovár
&Kenderes,2003;Svobodaetal.,2014;Trotsiuketal.,2014;Janda
et al., 2017; Meigs et al., 2017; Nagel et al., 2017; Schurman et al.,
2018;Janda etal., 2019; Schurman, Babst,Björklund, etal., 2019;
Čada et al.,2020; Frankovičetal., 2020),andprovide detailedde-
scriptions of dendroecological methods. We therefore only briefly
summarize the methods used to reconstruct disturbance below. We
used theoriginalapproach of Lorimer and Frelich(1989),in which
each core is screened for (a)abrupt , sustained increases in radial
growth (i.e., releases) and (b) rapid early growth rates (i.e., gap-
recruitedtrees),bothofwhichprovideindirectevidenceofmortal-
ity of a former canopy tree. Following Lorimer and Frelich (1989),
we only included release events before trees reached a diameter
threshold, such that only mortality events that provided access to
the canopy were counted. The diameter threshold was based on
comparisons of diameters of currently suppressed vs released trees
in the plot data. Multiple releases were allowed as long as they oc-
curred before the diameter threshold. The severity of disturbance
was based on the relative canopy area removed on each plot cal-
culated from the current crown area of trees containing evidence
of past disturbance; this approach makes the assumption that the
sum of the current crown areas of such trees is representative of the
prop ortionof thepl otdisturbedinth epast(Lori mer&Frelich,198 9).
Disturbance history reconstruction and lifetime growth patterns
of trees were used to derive several variables that may influence lon-
gevity.Theseincludedthetimingandseverity(i.e.,percentplotcan-
opyareakilled) ofthereconstructedmaximum severitydisturbance
eve ntonea chplot(Meigsetal.,2017 )( hereafterreferredtoasdistu r-
banceseverityanddisturbanceyear),aswellasthenumberofrelease
events per core. To assess the influence of growth rates on longevity,
we used the average growth rate of the first 50 years following Bigler
(2016)(hereafter referredtoas earlygrowth).Assuch, weexcluded
all cores that had less than 50 rings measured or estimated. We also
included metrics of the minimum and maximum 10-year average
growthperiodsforeachtreeringseriesfollowingOrwigandAbrams
(1994)(hereafter referred to as minimumand maximum growth),as
well as the number of releases detected throughout the series.
Several different environmental variables were also compiled to
test their influence of longevity. We used raw values of slope steep-
ness for each plot, while values of slope aspect were transformed
into northness following the formula: northness =cosine[(as-
pect in degrees * π)/180] (J anda et al., 2019). To avoid problems
withmulticollinearity,weexcludedaltitudebecauseitwasstrongly
correlatedwithtemperature(r =−0.752).Meantemperatureofthe
vegetation season for each plot was calculated for the period from
the 1 May until 31 October, by downscaling the Worldclim gridded
data(Fick&Hijmans,2017)fortheperiod1970–2000;thiswasdone
by building a linear model of temperature vs the product of altitude,
longitude, andlatitude. Given that we use the 1970–2000 period,
whichislikelynotrepresentativeofthetemperaturesexperienced
during early life stages of old trees, our temperature variable is more
ofanindexofrelativetemperatureacrossthestudyregion.Finally,
thereare severalbroad-scaledifferences between the Balkanand
Carpathian study sites that may influence tree growth and longevity,
including higher annual precipitation and temperature in the Balkan
region, as w ell as differenc es in bedrock (Kozák et a l., 2018); we
thereforeincludedrawvaluesoflatitudeforeachplottofurtherex-
plore if there are dif ferences in life span across the region.
To estimate life span within a species, we simply use the 90th
percentile of age distributions for each species from pooled data
across th e entire study (N agel et al., 2014). To compare life span
amongspecies,weusedanegativebinomialgeneralizedlinearmixed
model(GLMM) with the agesoftrees≥thespecies-specific90th
percentile(hereafterreferredtoastheoldesttrees)astheresponse
variableandspeciesastheexplanatoryvariable.Weappliedafour-
levelrandom-effects structuretoaccount for the potential effects
of geograp hical variab ility: a plot n ested within a p air of plots (in
beech-dominatedregions),apairofplotsnestedwithinastand,and
a stand nested within a landscape. Wald tests were per formed to
assess statistical significance. We used Tukey pairwise comparisons
to test for differences among individual species.
To identify the most influential drivers of life span, a binomial
GLMM was fit for each species. To facilitate interpretation, we con-
verted the 90th percentile ages to a binary variable, such that the
agestatus of a given treeage waseither≥ species-specific 90th
percentile or <species-specific 90th percentile. Age status was
used as a response variable and disturbance history, growth rate,
andenvironmentalvariableswereincludedasfixedeffects.Inthe
spruceGLMM,foresttype(spruceorbeech-dominated)wasused
asanadditionalfixed factor thatmaycause potential differences
in longevit y of spruce growing in these two forest types. The mean
values and ranges of all the variables included in these models are
listedper speciesinAppendixS3.Inthemaple model,some vari-
ables wer e strongly corre lated (i.e., earl y growth with ma ximum
and minimum growth, latitude with the average temperature of the
vegetationseason,anddisturbanceyearwithdisturbanceseverity).
Toavoidmulticollinearityissues,weassembledasimplermodelex-
cluding disturbance year, early growth, number of releases, and lat-
itude from the model. None of the final models showed problems
associatedwithmulticollinearity(allvarianceinflationfactorswere
<3.00)( Zuuretal.,20 09).Weusedthesa merandom-ef fec tsstr uc-
ture as described above. We calculated marginal determination co-
efficients(R2
m)andconditionaldeterminationcoefficients(R2
c)for
eachGLMMtoassesstherelativecontributionoffixedeffectsand
alleffectsrespectively(Nakagawaetal.,2017).
All the analyses were performed inR language version 3.5.1(R
Core Team, 2019) using the following libraries: glmmTMB (Brooks
etal.,2017)torunthemodels,car(Fox&Weisberg,2019)foranalysis-
of-variance calculation, emmeans (R Core Team, R Foundation for
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Statistical Computing , Vienna, Austria) to perform Tukey pairwise
comparisons, DHARMa(R Core Team, R Foundation for Statistical
Computing,Vienna,Austria)toperformresidual diagnostics, perfor-
mance(RCoreTeam,RFoundationforStatisticalComputing,Vienna,
Austria)to calculate VIFvalues,MuMIn(RCore Team,RFoundation
forStatisticalComputing,Vienna,Austria)tocalculatethedetermina-
tion coefficients, and ggplot2(Wickham,2016)forplotting.
3 | RESULTS
3.1  |  Interspecificdifferencesinlifespan
Theagesoftheoldesttreesdecreasedfrombeech(291–578years),
silver fir (218–456 years), spruce (218–449years), to maple (192–
412years)(Figure 2; AppendixS4).The GLMMshowed significant
differences in mean age of the oldest individuals among the four tree
species(χ2 = 280.41, p <0.001).Theoldestbeechtreesweresig-
nificantly older than all the other three species. The oldest fir trees
were significantly older than spruce trees, while the differences be-
tween the oldest maple and spruce trees, and maple and fir trees,
werenotstatisticallysignificant(AppendixS5).
3.2  |  Driversoftreelifespan
The influence of disturbance-related variables on reaching the
90th percentile ages varied among the four tree species (Table 1;
AppendicesS6,S7).Maximumseverityofplot-leveldisturbancehad
asignificantnegativeeffectonlifespan(i.e.,theplot-levelpresence
oftrees above the 90th percentile age thresholds) for spruce and
maple,while thecalendaryearofthismaximumseverityeventhad
asignificantnegativeinfluenceonbeechandspruce(i.e.,plotswith
more recent maximum severityevents had less trees reaching old
age(AppendicesS6, S7). Neither of the two disturbance variables
were significant in the fir model. The number of releases had a sig-
nificant positive effect on life span in all models.
Growth rate variables had strong and consistent effects
on life span a mong the specie s (Table 1; Appendixe s S8–S10).
Minimum ten-year average growth showed a significant neg-
ative influence for each species, while early growth rate had a
significant negative influence on life span for beech and fir, but
not spruce. Maximum growthwas not significantin anyof the
models.
The models did not show strong evidence of environmental
controlontreelifespans. Boththeplotlevel(northnessandslope)
FIGURE2 Agedistributionofthe
oldesttrees(≥species-specific90th
percentileofage)offourdominantspecies
pooledacrossallstudysites.Boxes
represent the interquartile range, with
the median age of the oldest trees given
byahorizontallinewithineachbox,and
notches showing 95% confidence inter vals
of the median. The lower whisker of each
boxextendstothespecies-specific90th
percentile of age, while upper whiskers
extend1.5timestheinterquartilerange,
and points show outliers. Numbers in the
upper right corners indicate the number
oftreesabovethespecies-specific90th
percentile, including the tot al numbers
of all trees per species in parentheses.
The letters in the upper left position of
each plot indicate significant differences
amongspecies(p <0.05)basedonTukey's
pairwise comparisons
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TAB LE 1  Summaryofgeneralizedlinearmixedmodels(GLMMs)examiningtheeffectofenvironmental,growth,anddisturbancefactorsontheageoftheoldestindividualsoffourtree
species
Parameter
Fagus sylvatica Picea abies Abies alba Acer pseudoplatanus
Est. SE zpEst. SE zpEst. SE zpEst. SE z p
(Intercept) −3.74 0.20 −19.14 <0,001 4.12 0.36 −11. 4 0 <0,0 01 −3.70 0.56 −6.66 <0,0 01 −22 . 36 6 .98 −3.20 0.001
Disturbance severity −0.11 0.09 −1. 22 0 .2 24 −0.70 0.09 −7. 6 0 <0,001 −0.06 0 .17 −0.33 0.738 −9.19 3.81 −2 .41 0.016
Disturbance year −0.39 0.08 −4.72 <0,001 0.29 0.06 −4.73 <0,001 0.25 0.16 1 .61 0 .108
Early growth −0.63 0.11 −5.73 <0,001 0.07 0.08 0.86 0.389 0.98 0.25 −3.90 <0,001
Maximumgrowth −0.05 0.07 −0.70 0.482 0.0 0 0.08 −0.04 0.967 0.06 0.17 0.36 0 .719 2.87 1.90 1. 51 0.131
Minimum growth −1.13 0 .14 −7.99 <0,001 −1 .9 9 0.10 −20.60 <0,001 −1. 11 0.32 −3.48 0.001 −13 .10 5.15 −2 .55 0.011
Number of release s 1.11 0.06 19.70 <0,001 0.58 0.04 14. 27 <0.001 1.08 0.15 7. 42 <0,001
Latitude −0.34 0.20 −1 .72 0.086 0.06 0.13 −0.45 0.650 0.01 0.45 −0.01 0.990
Northness −0.09 0.10 0.85 0.393 0.00 0.07 0.05 0.961 −0.28 0 .17 −1.6 2 0.106 −2.54 2 .47 −1 . 03 0.304
Slope 0.04 0.11 0.39 0.694 −0.03 0.08 −0.35 0.726 0.18 0.20 0.90 0.370 1.49 1.53 0.97 0.331
Mean T of veget ation
season
−0.20 0.16 −1 . 2 5 0.211 0 .13 0.10 1.27 0.204 −0.50 0.25 −2 .00 0.045 −6.45 3.17 −2.0 4 0.042
Forest t ype 0.29 0.37 0.79 0.432
τ00plot:(pairplot:(stand:landscape)) 0.57 0.47 0.00 464.87
τ00pairplot:(stand:landscape) 0.37 0. 57 0. 41 0.00
τ00 stand:landscape 0.69 0.34 1. 85 0.00
τ00 landscape 0.00 0.00 0.84 0.01
Rm
2[%] 48.03 54.56 42.65 40.93
Rc 2[%] 65.25 68.07 70.49 9 9. 59
Note:Resultsshowexplanatoryvariablesusedinthemodels,estimatesoftheregressioncoef ficients(Est.),standarderrors(SE),z-values(z),probabilities(p),variancesofallfourlevelsofrandomeffects
(τ00),marginaldeterminationcoefficients
R2
m
, and conditional determination coefficients
R2
c
. The significant model parameters are displayed in b old.
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andlarge-scaledrivers(latitudeandtemperatureofthevegetation
season) wereinsignificantfor mostspecies-level models. The only
exceptionswerethemodelsforfirandmaple,inwhichtemperature
of the vegetation season had a weak but significant negative effect
onlifespans(Table1,AppendixS11).
3.3  |  Commonnessofoldtrees
Thedensitiesoftheoldesttrees(≥species-specific90thpercentile
ofage)werehighlyvariableacrossthestandsandlandscapes,rang-
ingfrom0to48.8trees/ha(Figure3).Fifteenoutof68standshad
10–20 old tr ees/ha, and 11 stan ds had densities gr eater than 20
old trees/ha. We identified 893 trees that were at least 300 years
old, and 113 trees older than 400 years, of which two were maple
(0.084%ofallmapletrees),fourwerefir(0.29%ofallfirtrees),nine
werespruce(0.08%ofallsprucetrees),and98werebeech(1.32%of
allbeechtrees).Threebeechtreeswereolderthan500years(0.04%
ofallbeech trees).When calculated as a proportionofthecanopy
layer trees, the oldest trees made up from 0% to 23.9% of the can-
opyperstand(AppendixS12).
4 | DISCUSSION
We found compelling evidence of biological differences in life span
amongthe four coexistingtreesspeciesacrossmountainregionsof
Europe, yet these dif ferences are not entirely consistent with pub-
lished literature on the ecology of European tree species. We also
foun dth atloc ald ist urb anc ehistory,r ath erthanpl ot-scal ean db roa d-
scale environmental fac tors, was a key driver of life span. The particu-
lar histor y of local disturbance likely contributes to the highly variable
density of the oldest trees that was documented across the study
region. Before we elaborate on these main findings, we highlight sev-
eral caveats that are impor tant for the discussion that follows.
The estimates of tree life span used in our study, in particular the
agesoftheoldestlivingstemsabovethespecies-specific90thper-
centiles, provide an indication of the longevity of a given individual,
but not actual longevity, or the number of years from seed germina-
tion to death of an adult tree. Because we cored trees at 1 m in height ,
we underestimate the number of years required to reach 1 m, which
could range from years to decades depending on light conditions,
particularly for shade-tolerant species (Wong & Lertzman, 2001;
Nageletal.,2006).Wealsoonlywor kedwithlivetrees,mainlydueto
the challenges of obtaining a large sample of recently dead trees with
intact wood for tree coring. The species sampled in our study, espe-
ciallythebroad-leavedspecies,haverelativelyfastdecayrates,such
thattreeringcountsofdeadanddecliningtreesareoftenextremely
difficult(DiFilippoetal.,2012). Finally,giventhatlargertreesoften
had boledecay, morelargerstems were excluded from the sample
compared to smaller stems, which is an additional reason why our
data set may underestimate life span. Despite these limitations, the
largepopulatio n-baseddatasetofr andomlysa mpledtree si nrem ain-
ing primary forests across a subcontinental scale should provide a
robust estimate of interspecific dif ferences in tree life span.
Beech, t he dominant broa d-leaved s pecies, was mar kedly older
than the other species, and fir was older than spruce, but there were
no significant dif ferences in life span between maple and the two
FIGURE3 Densitiesofoldesttrees(≥species-specific90thpercentileofage)byspecieswithineachstandacrossthestudyregion.The
numbersindicatetheforestlandscapenames:1,Albania;2,Bulgaria;3,Croatia;4,SouthRomaniabeech;5,NorthRomaniabeech;6,East
Slovakia; 7, Central Slovakia beech; 8, Central Slovakia spruce; 9, North Romania spruce; 10, South Romania spruce; 11, Ukraine
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coniferspecies.Aspreviousstudieshavepointedout,interspecificdif-
ferences in life history traits at both juvenile and adult life stages may
contributetotreecoexistence,wherebyadultlongevitymaycompen-
sateforlowercompetitivenessofjuvenilescomparedtoco-occurring
species(Veblen,1986;Lusk&Smith,1998).Intemperatemixedmoun-
tainforestsofEurope, beechis bothoneof the mostshade-tolerant
species as a juvenileandlong-livedasanadult, likelycontributingto
its dominance across the region. Compared to juveniles of beech and
fir, maple and spruce are less tolerant of shade, but grow more rap-
idlyinlargergapswithhigherlightlevels(StancioiuandO’hara,2006;
Petritanetal.,2007;Leuschner&Meier,2018).Forexample,inamixed
mountainforest intheDinaricregion, (Nageletal.,2010)foundthat
maplerequiredrelativelylargegaps(>40 0 m2)toaccessthecanopy,
while smaller gaps were captured by beech and fir, which were often
presentpriortogapformation.Althoughthelowershadetoleranceof
maple may beadisadvantage inforests that lackmoderate-severity
disturbance for long time periods, its relatively high longevit y likely
contributes to its persistence in the landscape. Indeed, there are likely
other interspecific trait differences associated with various life stages
thatmaycontributetothecoexistenceofthesespecies(Nakashizuka,
2001),suchaslong-distancedispersalofmapleseedsorthetallcan-
opystatureoffirandspruce.However,furtherresearchisrequiredto
better understand the life history traits and life stages that contribute
totreespeciescoexistenceintheseforests.
It is impor tant to point out that our findings are not consistent
with the classic literature on life span of European tree species. For
example , Korpel’ (1995) report ed life spans of 230 a nd 350 years
for beech and fir, respectively, which is in complete contrast to our
findings. Leuschner and Ellenberg(2017) report maximumages of
450 years for b oth beech and fir, and 300 year s for spruce and mapl e.
However,themaximumagesfoundinourdatasetareconsiderably
older than the median ages of trees above the 90th percentile ages;
thesemedianagesareabetterpredictorofexpectedtreelifespans
in forest s regulated by natural disturbance processes. We believe
that the range of life span estimates provided here may serve as an
important reference for future studies that must prescribe values for
them, such as simulation models of forest dynamics. Relying on esti-
mates from earlier work may lead to spurious conclusions regarding
long-termforestdynamics.Insupport ofourfindings,otherrecent
dendroecological studies that focused on local sites or other regions
inEuropehavereportedsimilarvaluesofmaximumlifespanforthe
fourspeciesstudiedhere(Bigler&Veblen,2009;Mottaetal.,2011;
Nagel et al., 2014; Di Filippo et al., 2015; Piovesan, Biondi, Baliva,
Dinella,etal.,2019).
In addition to life history differences, we also sought to iden-
tify drivers of longevity across the large gradient of environment al
conditions and disturbance histories present in the data set. The
analyses indicated significant links between disturbance metrics
andlongevity in threeofthe four species-levelmodels.There was
ahigherprobabilityoffindingoldtreesonplotswithalowermaxi-
mumseverityofplot-leveldisturbance,orwherethemaximumse-
verity event occurred further back in time. These findings are not
atall surprising given that both the beech-and spruce-dominated
primaryforestsstudiedhereexperienceadisturbanceregimechar-
acterized byrelatively frequent moderate-severity, partial canopy
disturbances that are likelytoremove susceptible individuals(i.e.,
large, old trees)inthecanopy layer (Nageletal.,2014;Čadaetal.,
2020;Frankovičetal.,2020).
Disturbance history is also intrinsically linked to lifetime growth
of trees in that it regulates canopy structure, and thereby the grow th
of understorey trees via changes in light. Depending on the size,
location, and timing of disturbance relative to a given understorey
tree, some individuals will gain access to the forest canopy quickly,
others will reach the canopy after multiple periods of suppression
and release, and yet others will die due to prolonged periods of sup-
pression.Acrossallfourofthespeciesstudiedhere,trees thatsur-
vived periods of very suppressed grow th were more likely to reach
oldage.Forexample,averageannual growthratesduringthemini-
mum10-yeargrowthperiodsforallthetreesolderthan 300years
was <0.62 mm/year, <0.36 mm/year for all the trees older than
400 years, and <0.17 mm/year for all the trees older than 500 years
(AppendixS1:FigureS6).Likewise,treesthathadslowearlygrowth
rates were a lso more likely to r each old age (A ppendix S1: Figur e
S5).Thesefindingsareconsistentwithpreviousliteratureforanum-
berofdifferentspecies(Larson,2001;DiFilippoetal.,2015;Bigler,
2016;Piovesan,Biondi,Baliva,Dinella,etal.,2019),includingbeech
(Piovesan etal.,2005;DiFilippoetal.,2012; Piovesanetal.,2019)
andspruce (Bigler&Veblen, 2009;Rötheli et al.,2012;Castagneri
et al., 2013). Finally, the results show a positive relationship be-
tween t he number of sup pression-rel ease period s experien ced by
atree and longevity (Appendix S1: Figure S7).Treeswith multiple
suppres sion-r elease perio ds persist in t he understo rey for a large
propor tion of their life span, while trees that access the canopy
quickly, such as those that establish in large gaps, spend a longer
propor tion of their life in the canopy. These results lend support to
the idea that time spent in the canopy, where there is higher risk of
disturbance, may have a stronger influence on longevity than other
factors, such as environmental constraints or genetics.
Indeed, one of the more surprising findings was that we did not
identif y a consistent relationship bet ween life span and environmen-
tal factors, such as temperature and elevation, which has been docu-
mentedinpreviousstudiesofthesamespecies(Röthelietal.,2012;
DiFilippoetal.,2015;Bigler,2016).A sidefromt henegativecorrela-
tion between the mean temperature of the vegetation season and
longevit y for fir and maple, none of the other environmental factors
(i.e.,slope,northness,latitude)wererelatedtolongevityacrossthe
four species. The strong influence of disturbance and slow growth
rates on longevity documented here may simply override the influ-
ence of other environmental factors. In a study on mountain pine in
Switzerland,Bigler(2016)alsosuggestedthatalackofanexpected
temperature effect on the early growth of mountain pines was likely
due to superimposing effec ts of st and structure. Furthermore, past
studiesthathavedocumentedextremelyoldtrees for agivenspe-
cieswereoftenlocatedwithinextremesiteconditions(Larsonetal.,
2000),whereas our data set islikely to bemore representative of
site conditions found across mountain forests in the region.
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Anotabledrawbackofour studyis that we cannot teaseapart
how various drivers influence longevit y. Previous work has often
hypothesizedthat slow-growing treesinvest moreindefense, such
as chemicals or other wood properties that promote resistance to
decay (Loehle, 1987),or thatslow radial growth mayincur greater
mechanicalresistancetocanopydisturbance(Larson,2001).Forthe
species studied here, the literature does not provide clear evidence
on how slow grow th or other wood properties may increase longev-
ity. Previous research does not indicate a clear or consistent relation-
shipbetween radial growthand wooddensityfor beech(Bouriaud
etal.,2004;Diaconuetal.,2016),whilefasterradialgrowthhasbeen
found to decrease wooddensity in spruce (Piispanen et al., 2014).
Moreover, in a study of deadwood decay across temperate tree spe-
cies in Europe, wood density was positively correlated with decay
rates for beech, maple, and spruce, whereas chemicals such as phe-
nolicorganicextractiveswerenegativelycorrelatedwithdecayrate
(Kahletal.,2017).However,ifunderstoreytreesaregrowingslowly
due to light limitation, then presumably they have limited resources
toinvestinchemicaldefense(Herms&Mattson,1992).Finally,itis
important to note that we cannot rule out genetic control on intra-
specif ic variation in l ife span, or oth er trade-of fs betwe en growth
andlongevityrelatedtophysiology(Roskillyetal.,2019).
Afinalobjectiveofourstudywastoquantifythecommonness
of old tree s across the primar y-fores t landscapes s ampled in the
studyregion.Ingeneral,veryoldtreesareexceptionallyrare;outof
20,600coresdatedto≥50yearsofage,only115weredatedtomore
than400years.Althoughtheseexceptionally oldtreesarerare,26
out of the 68 stands had more than 10 trees ha−1 that reached the
species-specific90thpercentileage.Moreover,theremarkablevari-
ation in the density of these trees across the stands likely highlights
how tree longevity is strongly influenced by local disturbance his-
tories, which cover a gradient fromlow-intensitygap dynamics,to
partial canopy disturbance, to severe stand replacement in the study
region(Svobodaetal.,2014;Trotsiuketal.,2014;Jandaetal.,2017;
Schurm an et al., 2018; Čada et a l., 2020; Frankovič et a l., 2020).
Our results imply that disturbance and phenotypic plasticity play a
strongroleincontrollingtreelifespan.Asaconsequence,ifdistur-
bance regimes shift toward larger and more intense events under
globalchange(Seidletal.,2017),speedingupcanopyaccession,then
futureforestsmaysupportfewerlong-livedtrees.
ACKNOWLEDGEMENTS
We thank all who helped collect data in the field and who assisted in
the dendrochronology laboratory.
AUTHORSCONTRIBUTIONS
JP,TAN, andMSvo conceived theidea forthis study. JP,TAN,MSvi,
andJLPdesignedthestudy.SM,AD,ET,MP,TZ,OH,SD,OC,MM,and
MSvo located the study sites and dealt with acquiring permissions for
data collection.KB, MM,PJ,MF,RR, MSy,MD, TK,DK, OK,RB, VČ,
VT,MSvo,andMSacollectedthetreecoresandstructuraldata.JP,KB,
MM,PJ,MF,RR,MSy,MD,TK,DK,OK,RB,VČ,andVTprocessedand
analyzedthetree cores.MM, PJ,OV,RB, VČ, VT,MSvo, JSS,andAB
conceptualized and calculated the disturbance parameters. JP, MSvi,
andOVanalysedthe data.JPand TANwrote the draft of themanu-
script.Allauthorshaveapprovedthefinalversionofthemanuscript.
DATAAVAI L ABIL ITYSTATE MEN T
Data supporting the findings of this study are available at the Dr yad
DigitalRepository(https://doi.org/10.5061/dryad.1ns1rn8ts).
ORCID
Jakob Pavlin https://orcid.org/0000-0001-8514-3446
Thomas A. Nagel https://orcid.org/0000-0002-4207-9218
Ondřej Vostarek https://orcid.org/0000-0002-0657-0114
Radek Bače https://orcid.org/0000-0001-6872-1355
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SUPPORTINGINFORMATION
Additional supporting information may be found online in the
Supporting Information section.
How to cite this article:Pavlin,J.,Nagel,T.A .,Svitok,M.,
Pettit,J.L.,Begović,K.,Mikac,S.,etal(2021)Disturbance
history is a key driver of tree life span in temperate primary
forests. Journal of Vegetation Science, 32:e013069. ht t p s: //
doi .org /10.1111/j vs .13069
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... A root system weakened by pathogens might be more prone to wind disturbance. Finally, frequent and severe windstorms may not allow trees to grow to exceptional age [32]. ...
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Most information on the ecology of oak-dominated forests in Europe comes from forests altered for centuries because remnants of old-growth forests are rare. Disturbance and recruitment regimes in old-growth forests provide information on forest dynamics and their effects on long-term carbon storage. In an old-growth Quercus petraea forest in northwestern Spain, we inventoried three plots and extracted cores from 166 live and dead trees across canopy classes (DBH ≥ 5 cm). We reconstructed disturbance dynamics for the last 500 years from tree-ring widths. We also reconstructed past dynamics of above ground biomass (AGB) and recent AGB accumulation rates at stand level using allometric equations. From these data, we present a new tree-ring-based approach to estimate the age of carbon stored in AGB. The oldest tree was at least 568 years, making it the oldest known precisely-dated oak to date and one of the oldest broadleaved trees in the Northern Hemisphere. All plots contained trees over 400 years old. The disturbance regime was dominated by small, frequent releases with just a few more intense disturbances that affected ≤20% of trees. Oak recruitment was variable but rather continuous for 500 years. Carbon turnover times ranged between 153 and 229 years and mean carbon ages between 108 and 167 years. Over 50% of AGB (150 Mg·ha⁻¹) persisted ≥100 years and up to 21% of AGB (77 Mg·ha⁻¹) ≥300 years. Low disturbance rates and low productivity maintained current canopy oak dominance. Absence of management or stand-replacing disturbances over the last 500 years resulted in high forest stability, long carbon turnover times and long mean carbon ages. Observed dynamics and the absence of shade-tolerant species suggest that oak dominance could continue in the future. Our estimations of long-term carbon storage at centennial scales in unmanaged old-growth forests highlights the importance of management and natural disturbances for the global carbon cycle.
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Estimates of historical disturbance patterns are essential to guide forest management aimed at ensuring the sustainability of ecosystem functions and biodiversity. However, quantitative estimates of various disturbance characteristics required in management applications are rare in longer‐term historical studies. Thus, our objectives were to: (1) quantify past disturbance severity, patch size, and stand proportion disturbed, and (2) test for temporal and sub‐regional differences in these characteristics. We developed a comprehensive dendrochronological method to evaluate an approximately two‐century‐long disturbance record in the remaining Central and Eastern European primary mountain spruce forests, where wind and bark beetles are the predominant disturbance agents. We used an unprecedented large‐scale nested design dataset of 541 plots located within 44 stands and 6 sub‐regions. To quantify individual disturbance events, we used tree‐ring proxies, which were aggregated at plot and stand levels by smoothing and detecting peaks in their distributions. The spatial aggregation of disturbance events was used to estimate patch sizes. Data exhibited continuous gradients from low‐ to high‐severity and small‐ to large‐size disturbance events. In addition to the importance of small disturbance events, moderate‐scale (25‐75% of the stand disturbed, >10 ha patch size) and moderate‐severity (25‐75% of canopy disturbed) events were also common. Moderate disturbances represented more than 50% of the total disturbed area and their rotation periods ranged from one to several hundred years, which is within the lifespan of local tree species. Disturbance severities differed among sub‐regions, whereas the stand proportion disturbed varied significantly over time. This indicates partially independent variations among disturbance characteristics. Our quantitative estimates of disturbance severity, patch size, stand proportion disturbed, and associated rotation periods provide rigorous baseline data for future ecological research, decisions within biodiversity conservation, and silviculture intended to maintain native biodiversity and ecosystem functions. These results highlight a need for sufficiently large and adequately connected networks of strict reserves, more complex silvicultural treatments that emulate the natural disturbance spectrum in harvest rotation times, sizes, and intensities, and higher levels of tree and structural legacy retention.
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Given the global intensification of forest management and climate change, protecting and studying forests that develop free of direct human intervention-also known as primary forests-are becoming increasingly important. Yet, most countries still lack data regarding primary forest distribution. Previous studies have tested remote sensing approaches as a promising tool for identifying primary forests. However, their precision is highly dependent on data quality and resolution, which vary considerably. This has led to underestimation of primary forest abundance and distribution in some regions, such as the temperate zone of Europe. Field-based inventories of primary forests and methodologies to conduct these assessments are inconsistent; incomplete or inaccurate mapping increases the vulnerability of primary forest systems to continued loss from clearing and land-use change. We developed a comprehensive methodological approach for identifying primary forests, and tested it within one of Europe's hotspots of primary forest abundance: the Carpathian Mountains. From 2009 to 2015, we conducted the first national-scale primary forest census covering the entire 49,036 km 2 area of the Slovak Republic. We analyzed primary forest distribution patterns and the representativeness of potential vegetation types within primary forest remnants. We further evaluated the conservation status and extent of primary forest loss. Remaining primary forests are small, fragmented, and often do not represent the potential natural vegetation. We identified 261 primary forest localities. However, they represent only 0.47% of the total forested area, which is 0.21% of the country's land area. The spatial pattern of primary forests was clustered. Primary forests have tended to escape anthropogenic disturbance on sites with higher elevations, steeper slopes, rugged terrain, and greater distances from roads and settlements. Primary forest stands of montane mixed and subalpine spruce forests are more abundant compared to broadleaved forests. Notably, several habitat types are completely missing within primary forests (e.g., floodplain forests). More than 30% of the remaining primary forests are not strictly protected, and harvesting occurred at 32 primary forest localities within the study period. Almost all logging of primary forests was conducted inside of protected areas, underscoring the critical status of primary forest distribution in this part of Europe. Effective conservation strategies are urgently needed to stop the rapid loss and fragmentation of the remaining primary forests. Our approach based on precise, field-based surveys is widely applicable and transferrable to other fragmented forest landscapes.
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Climatic constraints on tree growth mediate an important link between terrestrial and atmospheric carbon pools. Tree rings provide valuable information on climate‐driven growth patterns, but existing data tend to be biased towards older trees on climatically extreme sites. Understanding climate change responses of biogeographic regions requires data that integrate spatial variability in growing conditions and forest structure. We analyzed both temporal (c. 1901‐2010) and spatial variation in radial growth patterns in 9 876 trees from fragments of primary Picea abies forests spanning the latitudinal and altitudinal extent of the Carpathian arc. Growth was positively correlated with summer temperatures and spring moisture availability throughout the entire region. However, important seasonal variation in climate responses occurred along geospatial gradients. At northern sites, winter precipitation and October temperatures of the year preceding ring formation were positively correlated with ring width. In contrast, trees at the southern extent of the Carpathians responded negatively to warm and dry conditions in autumn of the year preceding ring formation. An assessment of regional synchronization in radial growth variability showed temporal fluctuations throughout the 20th century linked to the onset of moisture limitation in southern landscapes. Since the beginning of the study period, differences between high and low elevations in the temperature sensitivity of tree growth generally declined, while moisture sensitivity increased at lower elevations. Growth trend analyses demonstrated changes in absolute tree growth rates linked to climatic change, with basal area increments in northern landscapes and lower altitudes responding positively to recent warming. Tree growth has predominantly increased with rising temperatures in the Carpathians, accompanied by early indicators that portions of the mountain range are transitioning from temperature to moisture limitation. Continued warming will alleviate large‐scale temperature constraints on tree growth, giving increasing weight to local drivers that are more challenging to predict. This article is protected by copyright. All rights reserved.