Restricted accessResearch articleFirst published online 2017-5
Evidence of temperature and precipitation change over the past 100 years in a high-resolution pollen record from the boreal forest of Central European Russia
Near-annual pollen records for the last 100 years were obtained from a 65-cm peat monolith from a raised peat bog in the Central Forest State Natural Biosphere Reserve (southern part of the Valdai Hills, European Russia) and compared with the available long-term meteorological observations. An age–depth model for the peat monolith was constructed by 210Pb and 137Cs dating. Cross-correlation and the Granger causality analysis indicated a broad range of statistically significant correlations between the pollen accumulation rate (PAR) of the main forest-forming trees and shrubs (Picea, Pinus, Betula, Tilia, Quercus, Ulmus, Alnus, and Corylus) and the air temperature and precipitation during the previous 3 years. Results showed that high air temperatures during the growing season (May–September) in the year prior to the flowering led to an increase in pollen productivity of the main tree species. The statistically significant correlation between the PAR of trees and shrubs and winter precipitation of the current and previous years could reflect the influence of winter precipitation on soil water availability and as a result on tree growth and functioning in the spring.
ApplebyPG (2001) Chronostratigraphic techniques in recent sediments. In: LastWMSmolJP (eds) Tracking Environmental Change Using Lake Sediments. Dordrecht: Kluwer Academic Publishers, pp. 379–413.
2.
AutioJHicksS (2004) Annual variations in meteorological conditions and pollen deposition on the fell Aakenustunturi in northern Finland: Potential for using fossil pollen as a climate proxy. Grana43: 31–47.
3.
BarnekowLLoaderNJHicksS. (2007) Strong correlation between summer temperature and pollen accumulation rates for Pinus sylvestris, Picea abies and Betula spp. in a high-resolution record from northern Sweden. Journal of Quaternary Science22: 653–658.
4.
BennettKDHicksS (2005) Numerical analysis of surface and fossil pollen spectra from northern Fennoscandia. Journal of Biogeography32: 407–423.
5.
BeugH-J (2004) Leitfaden der Pollenbestimmung für Mitteleuropa und angrenzende Gebiete. Munich: Verlag Friedrich Pfeil.
6.
BinfordMW (1990) Calculation and uncertainty analysis of 210Pb dates for PIRLA project lake sediment cores. Journal of Paleolimnology3: 253–267.
7.
BroströmASugitaSGaillardM-J (2004) Pollen productivity estimates for the reconstruction of past vegetation cover in the cultural landscape of southern Sweden. The Holocene14: 368–381.
8.
BunnAGHughesMKKirdyanovAV. (2013) Comparing forest measurements from tree rings and a space-based index of vegetation activity in Siberia. Environmental Research Letters8: 035034.
9.
DavisMB (1967) Pollen accumulation rates at Rogers Lake, Connecticut, during late- and post-glacial time. Review of Palaeobotany and Palynology2: 219–230.
10.
DavisMBBrubakerLBWebbTIII (1973) Calibration of absolute pollen influx. In: BirksHJBWestRG (eds) Quaternary Plant Ecology. Oxford: Blackwell, pp. 9–25.
11.
DavisMBMoellerREFordJ (1984) Sediment focusing and pollen influx. In: HaworthEYLundJWG (eds) Lake Sediments and Environmental History. Leicester: University of Leicester Press, pp. 261–293.
12.
DesherevskayaOKurbatovaJOlchevAV (2010) Climatic conditions of the south part of Valday Hills, Russia, and their projected changes during the 21st century. The Open Geography Journal3: 73–79.
13.
EichlerM (2012) Causal inference in time series analysis. In: BerzuiniCDawidAPBernardinelliL (eds) Causality: Statistical Perspectives and Applications. Chichester: Wiley, pp. 327–352.
14.
EichlerM (2013) Causal inference with multiple time series: Principles and problems. Philosophical Transactions of the Royal Society A: Mathematical, Physical, and Engineering Sciences371: 20110612.
15.
GrangerCWJ (1969) Investigating causal relations by econometric models and cross-spectral methods. Econometrica37(3): 424–438.
16.
GrangerCWJ (1980) Testing for causality: A personal viewpoint. Journal of Economic Dynamics and Control2: 329–352.
17.
GrimmECA (1990) TILIA and TILIA*GRAPH.PC spreadsheet and graphics software for pollen data. INQUA Working Group on Data-Handling Methods. Newsletter4: 5–7.
18.
HicksS (2001) The use of annual arboreal pollen deposition values for delimiting tree-lines in the landscape and exploring models of pollen dispersal. Review of Palaeobotany and Palynology117: 1–29.
19.
HuuskoAHicksS (2009) Conifer pollen abundance provides a proxy for summer temperature: Evidence from the latitudinal forest limit in Finland. Journal of Quaternary Science24(5): 522–528.
20.
JensenCVorrenK-DMørkvedB (2007) Annual pollen accumulation rate (PAR) at the boreal and aline forest-line of north-western Norway, with special emphasis on Pinus sylvestris and Betula pubescens. Review of Palaeobotany and Palynology144: 337–361.
21.
KamenikCvan der KnaapWOvan LeeuwenJFN. (2009) Pollen/climate calibration based on a near-annual peat sequence from the Swiss Alps. Journal of Quaternary Science24: 529–546.
22.
KörnerC (1999) Alpine Plant Life. Berlin: Springer.
23.
KuoppamaaMGoslarTHicksS (2009) Pollen accumulation rates as a tool for detecting land-use changes in a sparsely settled boreal forest. Vegetation History and Archaeobotany18: 205–217.
24.
McCarrollDGagenMPawellekF. (2003) Multiproxy dendroclimatology: A pilot study in northern Finland. The Holocene13: 829–838.
25.
MatthiasIGieseckeT (2014) Insights into pollen source area, transport and deposition from modern pollen accumulation rates in lake sediments. Quaternary Science Reviews87: 12–23.
26.
MazierFNielsenABBroströmA. (2012) Signals of tree volume and temperature in a high-resolution record of pollen accumulation rates in northern Finland. Journal of Quaternary Science27(6): 564–574.
MyersJLWellAD (2003) Research Design and Statistical Analysis. 2nd Edition.Mahwah, NJ: Lawrence Erlbaum Associates, Inc.
29.
NakagawaTTarasovPKotobaN. (2002) Quantitative pollen-based climate reconstruction in Japan: Application to surface and late Quaternary spectra. Quaternary Science Reviews21(2): 2099–2113.
30.
NielsenABMøllerPFGieseckeT. (2010) The effect of climate conditions on inter-annual flowering variability monitored by pollen traps below the canopy in Draved Forest, Denmark. Vegetation History and Archaeobotany19: 309–323.
31.
NosovaMBSeverovaEEVolkovaOA (2013) Influence of extremely high summer temperatures on pollen accumulation rates in moderate climate zone of central European Russia. Bulletin of Moscow Society of Naturalists: Biological Series118(4): 55–63.
32.
NosovaMBSeverovaEEVolkovaOA. (2015) Representation of Picea pollen in modern and surface samples from Central European Russia. Vegetation History and Archaeobotany24(2): 319–330.
33.
NovenkoEYOlchevAV (2015) Early Holocene vegetation and climate dynamics in the central part of the East European Plain (Russia). Quaternary International388: 12–22.
34.
NovenkoEYOlchevAVDesherevskayaO. (2009a) Paleoclimatic reconstructions for the south of Valdai Hills (European Russia) as paleo-analogs of possible regional vegetation changes under global warming. Environmental Research Letters4: 045016.
35.
NovenkoEYVolkovaEMNosovaMB. (2009b) Late Glacial and Holocene landscape dynamics in the southern taiga zone of East European Plain according to pollen and macrofossil records from the Central Forest State Reserve (Valdai Hills, Russia). Quaternary International207: 93–103.
36.
OlchevAVIbromAPriessJ. (2008) Effects of land use changes on evapotranspiration of tropical rain forest margin area in Central Sulawesi (Indonesia): Modelling study with a regional SVAT model. Ecological Modelling212: 131–137.
37.
OlchevAVVolkovaEKarataevaT. (2013) Growing season variability of net ecosystem CO2 exchange and evapotranspiration of a sphagnum mire in the broad-leaved forest zone of European Russia. Environmental Research Letters8(3): 035051.
38.
OltchevACermakJGurtzJ. (2002) The response of the water fluxes of the boreal forest region at the Volga’s source area to climatic and land-use changes. Physics and Chemistry of the Earth27(9–10): 675–690.
39.
PayneRJMalyshevaETsyganovA. (2015) A multi-proxy record of Holocene environmental change, peatland development and carbon accumulation from Staroselsky Moch peatland, Russia. The Holocene26(2): 314–326.
40.
PrenticeIC (1986) Pollen percentages, tree abundances and the Fagerlind effect. Journal of Quaternary Science1(1): 35–43.
41.
ReilleM (1992) Pollen et spores d’Europe et d’Afrique du Nord. Marseille: Laboratoire de Botanique Historique et Palynologie.
42.
SeppäHAleniusTMuukkonenP. (2009) Calibrated pollen accumulation rates as a basis for quantitative tree biomass reconstructions. The Holocene19(2): 209–220.
43.
SeppäHBirksHJBOdlandA. (2004) A modern pollen–climate calibration set from northern Europe: Developing and testing a tool for palaeoclimatological reconstructions. Journal of Biogeography31: 251–267.
44.
SjögrenPKarlsenSRJensenC (2015) The use of quantitative models to assess long-term climate–vegetation dynamics – A case study from the northern Scandinavian Mountains. The Holocene25(7): 1124–1133.
45.
SjögrenPvan LeeuwenJFPvan der KnaapWO. (2006) The effect of climate variability on pollen productivity, AD 1975–2000, recorded in a Sphagnum peat hummock. The Holocene16(2): 277–286.
46.
SoepboerWSugitaSLotterAF. (2007) Pollen productivity estimates for quantitative reconstruction of vegetation cover on the Swiss Plateau. The Holocene17: 1–13.
47.
SpearmanC (1904) The proof and measurement of association between two things. American Journal of Psychology15: 72–101.
48.
StockmarrJ (1971) Tablets with spores used in absolute pollen analysis. Pollen et Spores1: 615–621.
49.
SugitaS (2007) Theory of quantitative reconstruction of vegetation. I: Pollen from large sites REVEALS regional vegetation. The Holocene17: 229–241.
50.
Van der KnaapWvan LeeuwenJSvitavska-SvobodovaH. (2010) Annual pollen traps reveal the complexity of climatic control on pollen productivity in Europe and the Caucasus. Vegetation History and Archaeobotany19: 285–307.
