Regional trends for bud burst and flowering of woody plants in Norway as related to climate change

ORIGINAL PAPER

Regional trends for bud burst and flowering of woody plantsin Norway as related to climate change

Ø. Nordli & F. E. Wielgolaski & A. K. Bakken &

S. H. Hjeltnes & F. Måge & A. Sivle & O. Skre

Received: 9 February 2007 /Revised: 11 March 2008 /Accepted: 13 March 2008 /Published online: 17 April 2008# ISB 2008

Abstract Data series for bud burst, beginning of floweringand petal fall for 20 species of deciduous trees and conifersat four sites in different regions of southern Norway havebeen analysed and related to temperature series. Onaverage, the spring phenophases occurred 7 days earlierduring the period 1971–2005. The most significant lineartrends were observed for the earliest phases. The trends inthis period were compared with trends in other periods, thelongest one starting in 1927. Those starting in cold decadesand ending in 2005 were in most instances statistically

significant, whereas hardly any significant trend appearedfor series starting in warm decades. This fact showed thatthe results of trend studies are very sensitive to the choiceof starting year. There were significant decadal variations in40% of the series. The dates of occurrence of thephenophases, varying from the first days of May to thefirst days of June, correlated with seasonal temperatureseries, in most cases strongest to mean temperatures for theseasons March–May and April–May. The North AtlanticOscillation Index (NAOI) for January and Februaryappeared to have some predictive power for the date ofoccurrence of the recorded phases. The basis for this maybe that the oscillations described by the index are ofimportance for the fulfilment of physiological chillingrequirements needed to break bud dormancy. The samegenotypes of the trees were grown in region West Norwayand in Central Norwegian region; during the period 1965–2005 the trends towards earlier bud burst were morepronounced and steeper at the western site.

Keywords Phenology . Temperature . Climate change .

Norway . Trend

Introduction

Norway is a long and relatively narrow country, reachingfrom about 58°N to 71°N, with a total straight length ofabout 1,750 km. Many, often narrow, fjords cut far into thecountry, up to a maximum of 150 km from the coastal line.In many parts, steep mountains rise close to the fjords.Along the Atlantic coast the climate is oceanic, while it isrelatively continental in some inner fjord areas and east ofthe main north–south mountain chain. Due to high latitudesthe daylength varies considerably during the year.

Int J Biometeorol (2008) 52:625–639DOI 10.1007/s00484-008-0156-5

Ø. Nordli (*) :A. SivleNorwegian Meteorological Institute,Box 43, Blindern,0313 Oslo, Norwaye-mail: [email protected]

F. E. WielgolaskiDepartment of Biology, University of Oslo,Oslo, Norway

A. K. BakkenDivision Kvithamar,Norwegian Institute for Agricultural and Environmental Research,Stjørdal, Norway

S. H. HjeltnesDivision Njøs,Norwegian Institute for Agricultural and Environmental Research,Leikanger, Norway

F. MågeNorwegian University of Life Sciences,Ås, Norway

O. SkreDivision West Norway,Norwegian Forest and Landscape Institute,Bergen, Norway

The North Atlantic Oscillation Index (NAOI) seems toaccount for a large component of climate variability inEurope (e.g. Post and Stenseth 1999; Benestad 2001;Wanner et al. 2001; Sivle 2005). A positive NAOI in earlyspring during recent decades may be seen in the context ofa nearly Europe-wide lowland warming and earlier leafingof woody plants (Chmielewski and Rötzer 2001). A time-lagged effect of NAOI also seems to have influenced springflowering phenophases in Denmark (Gormsen et al. 2005).Klaveness and Wielgolaski (1996) reported that mostspecies in lowland areas in both southern and northernNorway flowered earlier in the mid-twentieth century thanabout 100 years earlier.

Generally, it is estimated that the annual temperature forthe Northern hemisphere has increased by 0.055°C perdecade in the period 1861–2000 (Jones and Moberg 2003).A similar overall trend for spring–summer temperature inthe same period was also estimated for western Norway(Nordli et al. 2003). Norwegian temperature series are to alarge extent dominated by "The Early 20th CenturyWarming" (e.g. BACC 2008)—a marked increase intemperature that culminated in the 1930s. This warmingwas followed by a minor cooling that culminated in the1960s, and then another warming lasting to the presenttime. Overland et al. (2004), using principal componentanalysis on individual station series, showed that thetwentieth century winter warming was present in the entiresector 0°–120°E, at high latitudes. The warming is alsopronounced in time series from Svalbard, Iceland, andGreenland (Førland et al. 2002).

Plants from various latitudes, altitudes and degrees ofcontinentality may have evolved different provenances,with different requirements for dormancy breaking and timeof bud burst (e.g. Myking 1999). In most parts of Norway,tree species and ecotypes (e.g. mountain birch) from alpineand Arctic areas are expected to have a lower optimumtemperature for development and growth than species (e.g.elm, maple) and ecotypes found in warmer parts of thecountry, as observed by Wielgolaski (1999) and Skre(1991). The threshold (=base) daily mean air temperaturesfor bud burst and flowering of native trees and fruit treesvary from below 0 to about 5°C (e.g. Heide 1993a).However, plant reactions such as physiological dormancyare complex, and results are not always consistent (Ovaskaet al. 2005).

Physiological dormancy in buds may influence the timeof bud burst in spring. Dormancy is initiated during latesummer and autumn, and is overcome by a chilling period.Approximately 1,000 h with temperatures between 4 and9°C during wintertime is normally needed to fulfill thechilling requirements (Heide and Prestrud 2005), whereaslittle physiological chilling is said to occur at temperaturesbelow 0°C (Powell 1986). In Norway, buds are normally

able to burst when temperatures start to rise in spring.However, in controlled climate studies, Heide (2003)observed that high temperatures in the pre-dormancy periodin the autumn delayed bud burst in spring.

In the present study, we searched for trends in the timingof spring phenological events and analysed whether theywere statistically related to corresponding trends in winterand spring temperatures. We also discuss the connectionbetween the winter NAOI and dates of bud burst andflowering, and how this may be understood by taking intoaccount the physiological chilling requirements of the plant.Our overall aim was to explore the relationship between airtemperatures and the rather complex chain of eventsleading to bud burst and flowering in deciduous trees.

Materials and methods

Data and site description

Analyses of temporal temperature variations during the latenineteenth and twentieth centuries reveal wide areas inwhich spatial differences are particularly small. Forsouthern Norway these define temperature regions (Fig. 1)

Fig. 1 Map showing the three temperature regions in southernNorway: regions East, West and Central Norway. Arrows Fourphenological observation sites, stars locations of two observationalsites for long-term temperature series

626 Int J Biometeorol (2008) 52:625–639

whose borders coincide mainly with the mountain rangethat divides south-eastern and western Norway (Hanssen-Bauer and Nordli 1998). The nearest temperature region tothe north of the mountain range includes the geographicalregion Trøndelag in Central Norway. The regions are namedEast, West, and Central Norway. The temperature data in thepresent paper comprises regional monthly means as well asmeans from local stations not exactly at the phenologicalobservation sites. For the study of long-term variations oftemperature, two well-homogenised reference climate sta-tions (RCS) were used: Kjøremsgrende (62°6′N, 9°3′ E) andUtsira (59°18′N, 4°53′E) (Fig. 1). All temperature data arefreely available to download from the home page of theNorwegian Meteorological Institute (http://www.met.no).

Observations of annual occurrences of tree phenophaseswere carried out within the three regions. The oldest seriesdates back to 1927 at the Njøs research station (61°11′N, 6°52′E, around 50 m a.s.l.), which is situated near a fjord inregion West (Fig. 1), whereas the oldest series from Ås inregion East dates back to 1947. At Ås, the fruit orchardbelongs to the Norwegian University of Life Science(UMB) (59° 40′N, 10°46′E, 90 m a.s.l.). From 1964onwards observations from the International PhenologicalGardens (IPG) (Chmielewski 1996; Chmielewski andRötzer 2001) at Kvithamar (63°30′N, 10°52′E, 70 m a.s.l)(Central Norway) and at Fana (60°16′N, 5°21′E, 50 m a.s.l)(oceanic West) are available. From about 1971 theobservational program was extended, making it feasible touse the last 35 years as a reference period for trend studies.

Every year since 1963, observations in the phenologicalgardens Fana and Kvithamar have been carried outaccording to the definition of phenophases given by theDeutscher Wetterdienst (DW) (1991). Their guidelines werelater adopted and revised in the Phenological ObservationGuide of the IPG (http://www.agrar.hu-berlin.de/pflanzenbau/agrarmet/observation%20guide.pdf). For simplicity, thephases in the present paper are specified solely according tothe BBCH system (Meier 1997). The phases comprise leafunfolding (=bud burst) for deciduous trees and bud opening(May shoot) for conifers. Leaf unfolding, coded as BBCH11, occurs when the first regular surfaces of leaves becomevisible in several places (3–4) on the observed plant, andthe first leaf has emerged up to its petiole from 50% of thebuds. May shoot for conifers—also coded as 11 on theBBCH scale—is defined as the phase when buds open andthe protecting involucres come off the bud edges. Theinvolucres either stick to the buds or fall down. The needlesare not yet expanded. The plants studied were vegetativelypropagated in Germany or, mainly, in lowland provenances(50–300 m elevation) in Central Europe, except the‘Nordic’ spruce, which originated from Scandinavia (alowland area east of the Oslo fjord, at about 60°N), andLarix, which originated from about 1,200 m elevation in the

Czech Sudetic mountains. For the Prunus and Maluscultivars in the two fruit research gardens, Njøs and Ås,the phenophases are all related to flowering and specifiedaccording to the BBCH scale. Growth stage 60 occurswhen the first flowers open, and stage 69 when floweringends and 80% of the petals have fallen.

For some series, a few missing observations were filledwith interpolated values. The interpolations were performedby comparisons with other species or cultivars. If there was atime lag between their phenophases, the heat sum (heredefined as accumulated degree days above 5°C) was alsotaken into account by regression between the time lag and theheat sum. However, in 1982, 1984, and 1985 no observationsweremade at Fana IPG, and in 1997 and 1998 no observationswere made at Kvithamar IPG. These gaps were filled solely byusing regression between phenophase occurrence and tem-perature. The total of interpolated data amounted to 6%.However, the original data without interpolations were alsopreserved. Whether the interpolations are included or not isspecified explicitly for each analysis as noted by “interpola-tions included” or “interpolations excluded”. Series with morethan one missing year at the end of the series were excludedfrom the trend analyses, although an exception was made for a75-year-long series for Prunus domestica at Njøs.

There are slightly different versions of the NAOI in use.However, in this paper the version used is based on thepressure difference between Iceland and Gibraltar, downloadedfrom the home page of the Climate Research Unit (CRU) at theUniversity of East Anglia: (http://www.cru.uea.ac.uk).

Statistical methods

For calculation of linear trends least-squares regression isused, with time (year) as the predictor and the day ofphenophase occurrence in Julian days (day number countedfrom 1 January) as the response variable. If the slopecoefficient is significantly different from zero, the trend issaid to be significant. Pearson correlation analyses wereperformed for ordinary correlation as well as for partialcorrelation. Partial correlations are used for correlationbetween two variables, A and B, removing the possibleeffect of a third variable C. This third variable, C, is said to bea control variable. The regression and correlation analyses,including tests of significance, were performed with theSPSS statistical package, ver 13: (http://www.spss.com).

Testing for trends in the datasets was also performedwith the non-parametric Mann-Kendall (M-K) test, whichmay be used without knowing the distribution of the timeseries as it is a rank test. Its test statistic, t, is defined by theequation

t ¼Xn

i¼1

ni ð1Þ

Int J Biometeorol (2008) 52:625–639 627

where n is the number of elements and ni is the number ofsmaller elements preceding element xi (i=1,2,.... n)(Sneyers 1990). Providing that n>10 the test statistic isvery nearly normally distributed under the hypothesis ofrandomness (the null hypothesis). Moreover, its expecta-tion, E(t), and variance, var t, are given by the equations

E tð Þ ¼ n n� 1ð Þ4

ð2Þ

var t ¼ n n� 1ð Þ 2nþ 5ð Þ72

ð3Þ

The standard distribution, u(t), of the test statistic is then

u tð Þ ¼ t � E tð Þffiffiffiffiffiffiffiffiffivar t

p ð4Þ

A percent table of the normal distribution function canbe used to decide whether the null hypothesis should berejected or not.

In order to examine the time evolution of the pheno-phases, the SiZer tool (significance of zero crossings of thederivative) was used (Chaudhuri et al. 2005). This tool

smooths the occurrences of the phenophases using a Kernalfunction (a low pass filter): the Gaussian distribution waschosen as the Kernal function. The purpose of using SiZerwas to smooth the series over different “bandwidths”,generating a whole family of smoothed curves. For eachsmoothed curve there might be local extremes (maxima andminima) defined by the zero-crossing in the derivative ofthe smooth; the statistical inference is based on thesederivatives. For every location on each smoothed curve, aconfidence interval for the derivative was constructed.When the confidence interval is completely above (below)zero, there is a significant increase (decrease) of thesmooth. A shift from a significant increase (decrease) to asignificant decrease (increase) is defined as a significantmaximum (minimum) value. The SiZer package is avail-able free online: (http://www.wagner.com/).

The smoothed values were calculated using the follow-ing formula:

Gj ¼Pn

i¼1wij � xi

Pn

i¼1wij

; where wij ¼ exp� i� jð Þ2

2s2ð5Þ

Table 1 Mean dates of occurrence, trends and results from correlationanalyses on spring phenophases identified according to the BBCHscale (Meier 1997) at the four sites Fana (Fa), Kvithamar (Kv), Njøs(Nj), and Ås. Linear trends (days/decade) were calculated from thestarting year up to the year 2005 (column 5) as well as for a fixed

period (1971–2005; column 6). For the normal period 1971–2000,mean dates of occurrence for each phenophase (with standarddeviations [SD]) are listed in column 7 and correlation coefficients(R) between the dates and seasonal mean temperature are in column8 (only the season of highest correlation is included)

1 2 3 4 5 6 7 8 RSpecies/cultivar BBCH

stageStart(year)

Start–2005Trend

1971–2005trend

Mean date ±SD Season

Fa Larix decidua 11 1971 −2.6* −2.6* 3 May ±8 TMarch/April −0.57Betula pubescens 11 1970 −4.3*** −4.3*** 5 May ±7 TMAM

a −0.71Fagus sylvatica ‘Har’ 11 1970 −3.7*** −3.9*** 11 May ±7 TApril −0.74Populus tremula 11 1969 −2.4* −2.4* 15 May ±9 TMAM −0.62Fagus sylvatica ‘Tri’ 11 1970 −0.6 −0.8 17 May ±6 TApril/May −0.55Picea abies ‘Early’ 11 1964 −2.2** −3.9*** 20 May ±8 TMAM −0.72Picea abies ‘Nordic’ 11 1964 −4.2*** −5.1*** 26 May ±8 TApril −0.70

Kv Larix decidua 11 1964 −0.8 −0.2 4 May ±8 TMarch/April −0.71Betula pubescens 11 1964 −1.9** −2.4* 13 May ±6 TMAM −0.78Fagus sylvatica ‘Har’ 11 1971 −1.6 −1.6 19 May ±6 TApril/May −0.65Populus tremula 11 1964 −0.3 −0.9 22 May ±7 TMAM −0.71Picea abies ‘Early’ 11 1964 23 May ±7 TMAM −0.62

Nj Prunus domestica ‘Victoria’ 60 1927 −1.08*** 13 May ±8 TMAM −0.74Pyrus communis ‘Moltke’ 60 1927 −0.3 −0.6 16 May ±7 TMAM −0.79Malus X domestica ‘Gravenstein’ 60 1927 −0.2 −1.5 20 May ±6 TMAM −0.76

Ås Prunus avium 60 1955 −2.9*** −2.8** 12 May ±7 TMAM −0.82Prunus domestica 60 1954 −2.6*** −2.2* 18 May ±7 TMAM −0.84Malus X domestica ‘Gravenstein’ 60 1947 −0.9* −1.9 22 May ±7 TApril/May −0.83Prunus avium 69 1955 −2.2*** −1.9* 25 May ±7 TApril/May −0.88Prunus domestica 69 1954 −2.6*** −1.8 25 May ±8 TApril/May −0.84Malus X domestica ‘Gravenstein’ 69 1947 −1.0* −1.3 1 June ±7 TApril/May −0.82

* P ≤ 0.1, ** P≤ 0.05, *** P≤ 0.01a TMarch/April/May = mean temperature for the season March-April-May


where Gj is the value of the smooth in year j, xi is the datapoint in year i, wj is the weight in year j, n is the number ofyears in the series, and s is the bandwidth (years), i.e. thestandard deviation in the Gaussian distribution. The degreeof smoothing is set by the value of the standard deviation inthe distribution, i.e. of the bandwidth in SiZer terminology.A bandwidth of 3 years corresponds to an approximately10-year moving average filter, and a bandwidth of 9 yearscorresponds to a 30-year filter. Gaussian filters arecommonly used for visualising meteorological time seriesand the significance of the variations on different timescales can be examined using the SiZer tool.

Results

The whole data set used in the study comprises series ofJulian dates for phenophase occurrence from four siteswithin three climate regions (Table 1, Fig. 1). Thecalculation of trends and testing for significance wasperformed for different time intervals defined by the datacoverage for each series as well as for the reference period1971–2005. The main result was that all series had trendstowards earlier occurrence of the phenophases, but the levelof significance was highly variable, from being significantat the 0.01 level to no significance even at the 0.1 level(Table 1, columns 5 and 6). Generally, there was goodagreement between the linear trend test and the M-K trendtest. For this reason the results of the M-K test are notshown.

Trends during the period 1971–2005 (Table 1, column 6;interpolations included)

At Ås (Fig. 1), the flowering date for Prunus aviumoccurred significantly earlier during the period 1971–2005, namely 10 days earlier, whereas for other series thesignificance was weaker. The latest phenophases (80%petal fall, BBCH=69) also had trends towards earlieroccurrences but these were not significant. At Njøs(Fig. 1) there were no significant changes in the timingof fruit tree phenophases. In the IPG at Fana (Fig. 1) budburst (BBCH 11) of Fagus sylvatica ‘Har’ was 14 daysearlier in 2005 than 35 years before, whereas the southernprovenance ‘Tri’ had no significant trend. Much earlieroccurrences were also seen for Betula pubescens and forthe Picea abies provenances ‘Early’ and ‘Nordic’; thelatter occurs 18 days earlier during this 35-year period. Forthe IPG Kvithamar in Central Norway no trend wassignificant according to the M-K test, whereas the trendfor Betula pubescens, whose bud burst occurred 8 daysearlier, was weakly significant according to the lineartrend test.

Trends during the whole length of the series (Table 1,column 5); interpolations included

Some of the fruit tree series started before 1971 and can beanalysed for trends over a considerably longer period thanthe last 35 years. The trends for Prunus avium and P.domestica at Ås were highly significant since the start ofthe series in the 1950s, showing a start of flowering up to14 days earlier. Also in this period, the trends of the 80%petal fall (BBCH 69) series were highly significant. For thelongest series in the whole data set, Pyrus communis andMalus x domestica at Njøs, the first flowering was only2 days earlier compared to the start of the series in 1927,which was not significant. For Prunus domestica, however,the trend since 1927 at the same site was significant even atthe 0.01 level. The phenophase occurred 9 days earlier in2005 than at the start of the series.

Comparison of phenophase occurrence for the same speciesin different regions; interpolations excluded

The establishment of the IPG at Fana in the oceanicWest and Kvithamar in Central Norway made it easy tocompare phenophase development, as the genotypespresent at the gardens are standardised. At the twogardens Larix decidua, Betula pubescens, Fagus sylvatica‘Har’ and Populus tremula have been growing at leastduring the period 1971–2005. Picea abies ‘Early’ wasgrowing in the two gardens with an overlapping windowfrom 1964 to 2000. The comparison was conducted bytaking the difference between the Julian dates of appear-ance of each phenophase for the same genotypes in thetwo regions. A linear trend test was performed on thedifferences.

All five species showed a development towards earlieroccurrences of each phenophase at Fana compared to thoseat Kvithamar. For Betula pubescens (1970–2005) andFagus sylvatica (1971–2005) the trends of the differencesthroughout the study period were significantly different atthe 0.05 level (Fig. 2, see also Fig. 5). For Picea abies,Larix decidua and Populus tremula the trends were notsignificantly different.

A similar comparison between Njøs (fjord district inregion West) and Ås (further from the sea in region East)was conducted, but none of the results were significant,even at the 0.1 level (not shown). The species available foranalyses were Malus x domestica ‘Gravenstein’ (analysedfor the periods 1971–2005 and 1947–2005) and Prunusdomestica (analysed for the period 1954–2005). For Prunusdomestica, particularly steep trends in relation to changes inphenophase dates were detected but this occurred at bothsites, resulting in no significant trend in the differencesbetween them.


Comparison with meteorological data; interpolationsexcluded

Temperature data were taken from the Norwegian Meteo-rological Institute’s data home page (http://www.met.no).As far as possible, homogenised data were chosen (Nordli1997). Monthly means for March, April, and May wereused both for local station series and for regional means(see data description). Seasonal means were calculated forMarch-April (TMarch-April), April-May (TApril-May), andMarch-April-May (TMAM).

Correlation analyses were performed for the normalperiod (1971–2000), comparing each phenophase serieswith the local temperature series (Table 1, column 8) aswell as with the regional series (not shown). All pheno-phase series had significant correlations with at least onemean monthly or seasonal temperature series. It waspresumed that the phenophase series would correlate betterwith the local station temperature series than with theregional series, but generally this was not true at the Fana,Njøs, and Kvithamar sites. The reason might be that thelocal series represent the climate at their own sites ratherthan at fruit gardens or at the IPGs, whereas regional seriesare not influenced by specific local conditions. For Ås,however, the correlations were better with local (r<−0.8)than with regional temperature (−0.8≤r<−0.7). This mightbe due to the fact that Ås is situated far from the centre ofthe region (Fig. 1).

The effect of temperature on the development of thephenophases was evident duringmore than 1month. Thus, thevalues TApril-May and TMAM most frequently correlated bestwith the phenophases. An exception was the Larix pheno-phase (BBCH 11), which correlated best with TMarch-April

(local data), apparently due to the early occurrence of thephenophase.

The temperature data for the seasons that exerted thestrongest influence on phenophase development (TApril/May

and TMAM) were also tested for trends in the period 1971–2005. For various local stations and regional data mosttrends amounted to 0.2–0.3°C per decade, or 1°C or lessduring the 35-year period (not shown). The temperature

trends of the well homogenised Utsira and Kjøremsgrendeseries (Fig. 1) were also within this interval. For the localstations near the Fana site (Flesland and Bergen) the trendswere weaker and not significant. This is not in agreementwith most of the phenophase series that had significanttrends (Table 1, column 6).

Variations within the period of observation; interpolationsincluded

The occurrences of the phenophases might also vary on asmaller time scale than the periods so far examined. Thesevariations were not detectable by the linear trend approachapplied above. The SiZer tool (see Materials and methods),however, allows variations to be visualised graphically(Fig. 3) and their significance to be examined for the 0.05level of significance. Out of 20 series, significant variationswere detected in 8 for some intervals of bandwidth(Table 2).

There was a concentration of significant bandwidthsaround 3 years that corresponds to variations on a decadaltime scale. Also, bandwidths up to 5 years were significantfor many of the series from Ås. For Malus x domestica‘Gravenstein’ variations on even longer time scales weresignificant. Thus, significant bandwidths of 10–15 yearscorresponding to time scales of roughly 30–50 years weredetected (Table 2) in those series. Both local maxima andminima on the smoothed curves were represented amongthe significant variations. Minima (early phenophases) werelocated in the early 1970s, whereas local maxima (latephenophases) were located in the 1960s or 1980s.

As most of the significant variations detected by theSiZer analyses occurred on a decadal time scale, decadalvariations were chosen for further analyses. For all 20series, the decadal variations (i.e. bandwidth=3 years) areshown by smoothed curves (Figs. 4, 5). The figures show amostly consistent pattern, with maxima and minima locatedin the same years, irrespectively of site, species, and meandate of occurrence for the phenophase. This was true notonly for the significant variations in the 1960s and 1970s,but also for variation during other decades.

20102000199019801970

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Diff

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ce (

days

)

a

20102000199019801970

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25

20

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bFig. 2 Differences between datesof bud burst: Kvithamar−Fana.a Betula pubescens (1970–2005).b Fagus sylvatica ‘Har’ (1971–2005). For both species asignificant, temporal increase inthe differences were detected,i.e. earlier occurrences of thephenophase at Fana relative toKvithamar


Phenophases occurred late in the late 1920s, early 1940s,and very pronounced in the late 1960s, around 1980, and inthe late 1990s, whereas phenophases occurred early in the1930s, around 1950, around 1960, in the 1970s, around1990, and at present (2005). For the longest series (fromNjøs) local maxima (late occurrences) were also seen in thelate 1950s. This is also seen for some species at Ås, forexample for the 80% petal fall (BBCH 69) phenophase ofMalus x domestica. The local minima (early occurrences) inthe 1970s were less pronounced for the late phenophasesboth at Fana and Kvithamar.

All series were also examined more closely by M-K test.Starting with the last year (2005), years were added one byone backward in time, and for each year added the test wasapplied. In this way, a series of test results were generated,each with a different first year, but all of them ending in2005 (Fig. 6). The 0.05 level of significance is marked withlines in Fig. 6. Thus, if the test statistics does not cross anyof the lines, no significant trends in the series are detectedregardless of starting year. For most series, however, asignificant level was crossed several times. Starting in adecade where the phenophases appeared late, most series

Table 2 Significant local extremes detected by the SiZer tool, at the0.05 significance level, at the Fana (Fa), Kvithamar (Kv), Njøs (Nj)and Ås sites. Maxima (max.) and minima (min.) are marked in the table

by bandwidth (Bw1) and approximate position (Year) on the smoothedcurve. For some series a second significant extreme was detectedwhose bandwidth is denoted Bw2

Site Species/provenance Pheno-phase Start of series Bw1 Year Bw2 Year

Fa Picea abies ‘Early’ 11 1964 5 1974 min.Kv Larix decidua 11 1964 3 1973 min. 3 1980 max

Betula pubescens 11 1964 3 1972 min.Nj Prunus domestica 60 1927 3 1974 min.

Pyrus communis ‘Moltke’ 60 1927 3 1980 max.Ås Prunus avium 60 1955 3 1980 max.

Malus x domestica ‘Gravenstein’ 60 1947 3–5 1963 max. 15 1965 max.Malus x domestica ‘Gravenstein’ 69 1947 3 1961 max.

Prunus domestica 'Victoria' at Njøs

110

120

130

140

150

160

1920 1940 1960 1980 2000

Day

No.

for

BB

CH

60

Pyrus communis 'Moltke' at Njøs

120

125

130

135

140

145

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1920 1940 1960 1980 2000

Day

No.

for

BB

CH

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Malus X domestica 'Gravenstein' at Ås

120125130135140145150155160

1940 1950 1960 1970 1980 1990 2000 2010

Day

No.

for

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CH

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Betula pubescens at Kvithamar

110115120125130135140145150

1960 1970 1980 1990 2000 2010

Day

No.

for

BB

CH

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Larix decidua at Kvithamar

100105110115120125130135140

1960 1970 1980 1990 2000 2010

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No.

for

BB

CH

11

Picea abies 'Early' at Fana

115120125130135140145150155

1960 1970 1980 1990 2000 2010D

ay N

o. f

or B

BC

H11

Fig. 3 Families of smoothedcurves derived from the seriesof spring phenophases (days ofoccurrence) where significantbandwidths detected by theSiZer method are highlighted.For Prunus, Betula, Pyrus, andLarix the bandwidths of 3 years(time scale about 10 years) weresignificant (red), for Picea abandwidth of 5 years (blue) wassignificant. For Malus band-widths of 3 (red) and 15 (green)years were both significant. Forthe location on the time axis ofthe maxima and minima forsignificant bandwidths, seeTable 2


exhibited significant trends, but starting in a decade of earlyphenophases, significance was absent for most of the series.The situation for Picea abies ‘Nordic’ at Fana (Fig. 6),where the significance level was crossed already in the1990s and remained significant regardless of starting year,is unique not only for the 8 species or provenances shown,but also for the other 12 that were tested but not shown inthe figure.

Temporal variations and trends in temperature series

For comparison, the regional temperature series (March–May) were also analysed on a decadal time scale, lookingfor local maxima and minima (not shown). Using the SiZertool, the warm springs around 1990 were found to besignificant in the East, but not in other regions. However,the years of occurrence of maxima and minima differed nomore than by 2 years between the regions. The temperaturemaxima are located in the years 1936, 1948–1949, 1962,1974, and 1992, whereas the minima are located in theyears 1941, 1957, 1966–1968, 1979, and 1996–1997. Thismeans that the temperature maxima roughly correspond tothe phenophase minima (early occurrences) and vice versa,as would be expected as there is a negative correlationbetween temperature and occurrence of the phenophases.As the local maximum (late occurrences) on the pheno-phase curves in the 1960s is pronounced, so is thecorresponding minimum on the regional temperaturecurves.

As reliable long-term temperature series, the two wellhomogenised RCS series Kjøremsgrende and Utsira (seedata and site description) were chosen. Testing of signifi-cance was performed by the M-K test (Fig. 7) with a 0.05

level of significance. Both series exhibited a positive trend,i.e. a change towards warmer springs, but the significanceof the trends was again highly dependent on the startingyear. For long periods of the twentieth century, the timeevolution of M-K test statistics crossed the line ofsignificance, which means that the significance shifts asdifferent starting years were chosen. Thus, for the referenceperiod 1971–2005, the trend for Kjøremsgrende wassignificant, whereas that for Utsira was not. For 1964–2005 (the longest period of IPG data) the trends weresignificant for both series. However, for the periods 1947–2005 (start of the oldest data from Ås) as well as for 1927–2005 (oldest data from Njøs) no temperature trend wassignificant. For observations starting at the very beginningof the twentieth century or earlier, trends over the periods ofobservation were significant regardless of the decadalvariations that might be present.

Influence of the NAO circulation pattern; interpolationsexcluded

Correlation analyses were performed between the NAOIand the date of occurrence of the phenophases for threenon-overlapping periods (1927–1946, 1947–1970, and1971–2005) as well as for longer overlapping periods(1927–2005, 1947–2005). These periods were chosenpragmatically according to the start of the phenologicalseries (see above). A correlation analysis was alsoperformed between spring NAOI and spring regionaltemperatures.

The NAOI during spring correlated significantly withspring temperatures (not shown), particularly in March,where a positive correlation was seen for all regions (East,

Kvithamar

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Fig. 5 The occurrence of budburst at Kvithamar and Fanashown as smoothed curves rep-resenting decadal variations:black Picea abies, blue Populustremula, red Fagus sylvatica,green Betula pubescens, brownLarix decidua

Njos

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Fig. 4 The occurrence of fruittree phenophases at Njøs and Åsshown as smoothed curves rep-resenting decadal variations:black Malus domestica, bluePyrus communis, red Prunusdomestica, green Prunus avium


West, and Central) and all periods of investigation (1927–1946, 1947–1970, 1971–2005). In April, the NAOI andtemperature were still significantly positively correlated inthe earliest and the latest period, although the correlationwas weaker and less significant than in March. In May asignificant positive correlation was seen only in the earliestperiod; in other periods negative correlations occurred.

Since significant correlations were detected betweenspring temperature and spring NAOI, it was expected thatsignificant correlations would also occur between springNAOI and the occurrence of the phenophases, but this wasnot true. All phenophases were checked for correlation with

NAOI for the months March, April, and May, but almost nosignificant (P≤0.05) correlations were detected. The sameanalyses were also performed for the mean indices of allpossible combinations of those months, which also resultedin almost no significant correlations (not shown).

It is, however, the winter NAOI (mean value for themonths December–March) that governs the winter climateof the Scandinavia peninsula (e.g. Nordli et al. 2005). Thewinter NAOI might also influence the spring phenophases,for example due to an influence on physiological chilling ofthe plants, thus correlation analyses were performedbetween the spring phenophases and the winter NAOI.

Prunus domestica at Njos

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M. X dom. 'Gravenstein' at Ås

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Larix decidua at Fana

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Larix decidua at Kvithamar

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M. X dom. 'Gravenstein' at Njos

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Prunus avium at Ås

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Betula pubescens at Kvithamar

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Fig. 6 Time evolution of Mann-Kendall (M-K) test statistics fora selection of eight species orcultivars at the four sites Ås,Fana, Njøs, and Kvithamar. Thefollowing test procedure wasapplied: starting with the lastyear in each series (2005), yearswere added one by one back-wards in time, and for each yearadded the test was reapplied.The curves represent test resultsfor different starting years, allending in 2005. The lines markthe 0.05 level of significance


This resulted in significant correlations (P≤0.05) for themajority of the phenophases in the recent period (1971–2005).The correlations were further improved as the winter seasonwas narrowed to only January and February. The correlations,comprising all data from all four sites, varied from −0.25 to−0.74. Generally, the best correlations occurred at Ås andNjøs, whereas the weakest correlations occurred at Fana andKvithamar. The correlations were significant for two out ofseven series at Fana and for two out of five at Kvithamar,whereas for Njøs and Ås all correlations were significant.

For the periods 1927–1945 (data only for Njøs) and1947–1970 (data only from Njøs and Ås) no significantcorrelations were detected between the occurrences ofphenophases and the January–February NAOI (NAOIJF).However, for the overlapping periods, 1947–2005 and1927–2005, all correlations were significant (P≤0.05).

The correlation between the NAOIJF and the occurrenceof the phenophases might be caused solely by thepersistence of temperature during winter and spring. Thiswas our zero-hypothesis, which was tested by performing apartial correlation analysis with spring temperature (MAM)as controlling factor, i.e. the influence of spring temperaturewas removed from the correlation between the NAOIJF andthe phenophases (see Materials and methods). The resultwas that the correlations vanished for the IPGs at Fana andKvithamar, and the correlations were also reduced for thefruit trees at Ås and Njøs, but here most of the correlationsremained significant (P≤0.05; at Ås 4 out of 6 and at Njøs2 out of 3 remained significant). Thus, for Ås and Njøs thezero-hypothesis had to be rejected; i.e. the correlationscannot be accounted for by persistent temperature only.Thus, winter conditions might have had a direct influenceon phenophase occurrence.

Discussion

The general result of this study was that spring pheno-phases occur earlier in the present day climate than they did35–79 years ago. Approximately one-third of the seriesshowed significant negative trends, whereas no positivetrends were detected. If the series had been very noisy, i.e.had been strongly affected by non-climatological factors,both positive and negative trends should have beenexpected. Earlier occurrences of spring phenophases arealso in agreement with results from other European areas(e.g. Chmielewski and Rötzer 2001, 2002; Chmielewskiet al. 2004; Aasa et al. 2004; Gormsen et al. 2005; Menzelet al. 2005; Orlandi et al. 2005). The close relationship thathas been shown between spring temperature and date ofoccurrence of the phenophases in certain tree species andprovenances may therefore be used for climate reconstruc-tion purposes in areas where available meteorological seriesare shorter than phenological series (e.g. Nordli 2001).

The non-stable character of detected trends in short dataseries

The importance of the starting year for the significance oftrends was subjected to closer examination. The series weretested during periods with varying starting years, but aconstant ending year: 2005. If the starting year was locatedin a cold period the trends were significant, whereas startingin a warm period resulted in non-significant trends. Thesefindings have implications for the interpretation of trendstudies based on short observation series, e.g. for satellitedata, where the datasets do not cover more than about30 years. The results from such studies should therefore be

Kjoremsgrende

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KjoremsgrendeFig. 7 Time evolution of theMarch-May temperature (leftpanel) and M-K test statistics(right panel) for two locationswith long, well homogenisedtemperature series. The temper-ature is shown by smoothedcurves representing decadal var-iations. For the M-K test statis-tics, see the legend to Fig. 6


compared to longer time series before adequate conclusionscan be made concerning the effect of climate change onbiological events.

It is, however, possible to use an analogy with the long-term temperature series due to the correlation between theoccurrence of the phenophases and spring temperatures(Table 1). Of particular importance is "The Early 20thCentury Warming" (E20thCW), when an abrupt shiftoccurred in the northern European climate. The shift maybe identified and localised on the time axis by use of thenon-parametric Pettitt (1979) test. For southern Norway, themost likely year for the shift to occur was 1929 (notshown). The shift is less abrupt for the spring season thanfor annual values (Fig. 7). The significance of increasedsouthern Norwegian temperature seems to be stable forseries that start at least 20–30 years prior to the E20thCW.Thus, it is plausible that the occurrences of springphenophases for trees in southern Norway have changedsignificantly during the last 100 years. The temperaturetrends also remained significant for series starting in theeighteenth or nineteenth centuries (Nordli et al. 2003). It isthus also plausible that the spring phenophases appearearlier in the present day climate than they did 200–300 years ago.

Fluctuations on different time scales; the questionof significance

In addition to long-term trends, phenological time seriesmight also contain variations on different time scales.These can be visualised by smoothing the series, as donehere by the SiZer tool. Since a series of random data willalso give an impression of variations on certain timescales, the significant variation is of particular interest. Inthe present dataset, significant decadal variations weredetected: late occurrences of the phenophases in the early1960s and early occurrences in the early 1970s (Table 2).These variations were seen at all observational sites, but foronly one series at Fana IPG. However, less frequentoccurrences of significant extremes at Fana might well bedue to this being a comparatively short dataset. Also, theminimum in the early 1970s can hardly be considered assignificant in the test as it occurs close to the start of theseries.

The late occurrences of the phenophases in the 1960sare also significant at time scales longer than decades, forexample at a time scale of up to 50 years. Thesignificance of these variations was seen in the phenolog-ical series from Ås. Taking a long perspective, the flow-ering date of the fruit trees became later from the start ofobservations in the 1940s to the 1960s when the lateoccurrences culminated, and a shift towards earlieroccurrences began.

Comparison of phenophase development for continentalversus oceanic and southern vs northern provenances

Studies of different provenances of a plant species trans-planted from various latitudes, altitudes and degree ofoceanity/continentality into the same climatic conditionshave often shown a high degree of variation in timing of thephenophases (e.g. Ovaska et al. 2005; Skre et al. 2008). Thegrowth of new shoots for the moderate oceanic ‘Nordic’provenance of Picea abies at Fana (60°N) started onaverage nearly a week later than that of the morecontinental German provenance. This is in accordance withthe results of Ovaska et al. (2005), who found that oceanicprovenances of birch are later in their phenophases thanmore continental provenances, often in contrast to thegenerally later development in southern compared withnorthern provenances (cf. Skre and Næss 1999; Myking1999). There is also the possibility of a delay in springgrowth at the oceanic Fana site because of higher lateautumn temperatures than at the place of origin, asobserved for many deciduous boreal tree species by Heide(2003).

Do early and late phenophases have different trends?

In all deciduous trees, the most significant linear trendstowards earlier occurrences of phenophases (first leaf budburst, first fruit flowering and fading) were found for plantsthat start development in early spring. This is in agreementwith the findings of Chmielewski et al. (2004) for severalcultivated species (fruit trees and crop plants) studied inGermany. In the three Norwegian regions, the steepest andmost significant temperature trends in the reference periodoccur in April, whereas the temperature did not increase inMay (not shown). One reason for the stronger influence onthe earliest phenophases might be that the most pronouncedtemperature change occurred early in the growing season.

Concerning fruit trees, the significant earlier flowering,but also flower fading, is most pronounced for stone fruitspecies, i.e. Prunus avium and P. domestica. These speciesflower 7–10 days earlier than pome fruits such as Pyruscommunis and Malus x domestica. The trend for earlyphenophases is steeper at Ås than at Njøs. This might be alocal effect (Wielgolaski 2003) due to the cold water bodyof Sognefjord, which remains cold even in warm springweather: increased temperatures in spring increase snowmelting in the surrounding mountains, but have little effecton the water surface temperature. Thus, at sites like Njøs(close to the Sognefjord), the long-term air temperaturetrend may be weaker than elsewhere in the region. Thetrend for later phenophases, such as petal fall of Malus xdomestica, recorded at Ås, and first flowering of thisspecies at Njøs, were not significant during the reference


period. This also indicates that temperature effects are mostpronounced for early phenophases. However, it is interest-ing to observe that even flower fading of the earlyflowering Prunus avium and P. domestica at Ås (Table 1,column 5) showed a significant negative linear trend duringthe longest period.

Why are there regional differences in the timingof phenophases for the same provenance or cultivar?

Physiological chilling in plants during the dormant period(Heide 1993a, b) may explain, in part, the regional differ-ences found in timing between phenophases, the mosteffective temperatures being between 4°C and 9°C (Murrayet al. 1989; Hänninen 1990; Myking and Heide 1995; Heideand Prestrud 2005), while temperatures below 0°C have beenregarded to be of limited importance for chilling (Powell1986). Temperatures in the previous autumn can influenceplant development even the following year (Heide 2003;Taulavouri et al. 2004), although these were not investigatedin the present study. During the period of observation therehas been an increase in the number of days when themaximum temperature in January–February has exceeded4°C for southern Norway, particularly after 1987 (Table 3).Physiological chilling early in the season might to someextent explain the trend in the differences between Fana andKvithamar (Fig. 2). A similar, but insignificant trend in thedifferences between Ås and Njøs (not shown) might also bereal. However, temperatures above a certain thresholdtemperature for growth in spring after dormancy breakingare also important for the timing of phenophases in different

species or cultivars. Increased night temperatures are foundto be of particular importance for early phenophases such asbud burst, due to internal plant physiological responses tohigher temperatures in the dark phase during periods of newplant development (Wielgolaski 1974).

Comparing the spring phenophase of the same speciesand provenances, a development towards a relatively earlieroccurrence was discovered at the oceanic site Fanacompared to Kvithamar (Fig. 2). The stronger trend towardearlier occurrence dates at Fana vs Kvithamar may beexplained by the lower mean annual temperature amplitudeat the most oceanic site, i.e. 12.6°C at Flesland (Fana) vs17.1°C at Værnes (Kvithamar) (Aune 1993), and by higherwinter and spring temperatures. Consequently, a certaintemperature increase in spring, e.g. +3°C, is expected tocause a stronger response in terms of fewer days after earlydormancy breaking to bud burst at the oceanic Fana sitethan at Kvithamar, where the physiological chilling re-quirement in winter may not be fully saturated in spring atthe time of expected bud burst. A similar difference may beexpected between Ås and Njøs as a result of a lowertemperature amplitude at Vangsnes compared to Rygge(14.6°C vs 20.0°C), but this may be opposed by theincrease in winter temperature within the range of impor-tance for physiological chilling in plants. This increase hasbeen pronounced since 1988, particularly at Ås (Table 3),and may have led to a stronger response in terms of earlierdormancy breaking at Ås than at Njøs. At Njøs, the chillingrequirements were often fulfilled before the temperaturechange as January normal temperature was −0.1°C atVangsnes vs −4.2°C at Rygge (Aune 1993).

Table 3 Minimum, maximum and percentiles of the number of days the daily maximum temperature exceeded 4°C during the months Januaryand February each year

Meteorological stationa Phenophase obs. Minimum 25% Median 75% Maximum

Reference periodRygge (1971–2005) Ås 0 3 17 24 53Flesland (1971–2005) Fana 6 20 30 40 56Vangsnes (1971–2005) Njøs 0 10 20 29 43Værnes (1971–2005) Kvithamar 0 13 21 28 43Other periodsRygge (1956–1987) Ås 0 0 6 16 21Rygge (1971–1987) Ås 0 1 5 19 21Rygge (1988–2005) Ås 1 16 24 30 53Flesland (1971–1987) Fana 6 15 23 35 54Flesland (1988–2005) Fana 16 27 37 44 56Vangsnes (1956–1987) Njøs 0 7 12 20 42Vangsnes (1971–1987) Njøs 0 8 10 24 42Vangsnes (1988–2005) Njøs 5 20 24 29 43Værnes (1971–1987) Kvithamar 0 8 13 24 36Værnes (1988–2005) Kvithamar 3 20 25 32 43

a The meteorological stations are all situated near a site of phenological observations


Possible causal relationships between winter NAOIand dates of flowering

Significant correlations between the occurrence of springphenophases and the winter NAOI (in particular theNAOIJF) were detected. This means that the NAOIJF has apredictive value for the timing of phenophases. Similarly,Gormsen et al. (2005) reported that NAOIJF could be usedto predict the spread of pollen from the genus Betula andthe first flowering of Prunus avium around Copenhagen. Astheir data period was 1977–1999 it covers most of our laterperiod of analysis (1971–2005). Aasa et al. (2004) foundthat the NAOIJFM correlated with spring phenophases ofTussilago farfara, Betula pendula, and Syringa vulgaris inthe period 1951–1998 for “The Baltic Sea region”including also a few northern and eastern sites like Kirillov(59.9°N, 39.2°E) but no Norwegian data. Including ourpresent work, the winter NAOI seems to correlate withseveral spring phenophases even at high latitudes (aroundlatitude 60°N) between longitudes 5–40°E.

The predictive ability of the winter NAOI should be usedwith some caution, as the stationarity of the correlation isquestionable. In our analysis, the correlations were notsignificant for the earlier periods (1927–1946 and 1947–1970). However, Post and Stenseth (1999) have shown foralmost the same time interval, 1928–1977, that significantcorrelations with winter NAO may occur. They used the socalled Printz and Lauscher data set (Lauscher and Lauscher1990) and correlated the NAOIDJFM, with the annual datesof spring phenophases of Hepatica nobilis (Anemonehepatica), A. nemorosa, Tussilago farfara, Caltha palustrisand Vaccinium myrtillus.

Furthermore, in two studies by Chmielewski and Rötzer(2001, 2002) the NAOIFMA was correlated with thebeginning of the growing season, as derived from datafrom the IPGs in the period 1969–1998. For the regionsinvolving Norwegian data, correlation coefficients of −0.57and −0.72 were detected (Chmielewski and Rötzer 2001).This seems to be in contrast with our results, as correlationswith the NAOIMAM lacked significance. However, thevariability of the index in February is larger than in Marchand April so the index used by Chmielewski and Rötzer isquite different from ours. For comparison we alsoperformed an analysis using the NAOIFMA. This resultedin significant correlations for Ås and also for Njøs, but notfor Fana or Kvithamar.

Correlation analyses do not explain the mechanism(s)underlying the correlations. Nonetheless, we hypothesisethat many of the correlations reported are due to thephysiological chilling requirements in plants. Thus, in someyears with low NAOIJF, the chilling requirements for thetrees may not have been fulfilled early in the year,particularly at Ås. At Ås, for example, there were 7 years

without a single day with maximum temperature above0 oC in January–February during the whole study period,whereas at Fana the maximum temperature was above thisthreshold for some time every year in those months.However, in years with high NAOIJF the chilling require-ments may have been fulfilled also at Ås and the buddormancy broken rather early. Thus, we find it plausiblethat the good predictive power at Ås is connected tophysiological chilling conditions. Conversely, at Fana thechilling requirements were fulfilled also in years with lowNAOIJF resulting in poor predictive power for that site.

Conclusions

For periods spanning 35 to 79 years, ending in 2005, springphenophases of several species of deciduous trees andconifers have shifted towards earlier occurrences at foursites representing three climatic regions in southern Nor-way. The trends for dates of bud burst were steeper thanthose for later phases such as flowering and petal fall.Regional differences in trends for the same genotypes werefound for Fagus sylvatica and Betula pubescens. At the siterepresenting Western Norway, the drift towards earlier budburst was far more pronounced than at the site located inCentral Norway during the period 1971–2005.

Significant decadal variations were detected for 40% ofthe phenophase series, with local extremes in the early1970s and in the early 1960s most often being significant.The extreme in the 1960s also appeared to be significant onlonger time scales of up to 50 years. Series starting in a colddecade tended to have significant trends in the period fromthe starting year to 2005, whereas series starting in a warmdecade tended to have insignificant trends. Thus, the resultsof trend studies are very sensitive to the choice of startingyear. Generally, trend analyses for shorter series shouldtherefore be compared with longer time series if used forclimate change detection.

The timing of all the phenological events studiedcorrelated well with seasonal temperature series, usuallymost strongly with mean temperatures for the seasonsMarch–May and April–May. Due to this close relationship,it was possible to draw an analogy between the shortphenological series and the long-term temperature series. Itis therefore plausible that phenological events occursignificantly earlier in the present day climate than theydid before the E20thCW.

The NAOI for January and February appeared to berelated to the dates of occurrence of the recorded phases. Attwo of the sites, at least, there were indications that theoscillations described by the index are of importance for thefulfilment of the physiological chilling requirements neededto break plant bud dormancy.


Acknowledgements Firstly, we have to thank the many observers atthe IPGs and at the fruit gardens. They are too many to be mentionedby name, but nevertheless each of them made important contributionsto the database available for this study. We also thank our twoanonymous reviewers for valuable suggestions and comments andlikewise we want to thank Dr. Olav Skarpaas (NINA, Norway) and Dr.Matt I. Daws (Royal Botanic Gardens, Kew, UK) for improving thelanguage. The present work was initiated by the European Coopera-tion on Phenology through COST-action 725.

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Regional trends for bud burst and flowering of woody plants in Norway as related to climate change

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