UNIVERSITY OF FLORENCE Department of Agronomy and Land Management Current trends of agroclimatic indices applied to grapevine and olive tree in central Italy Simone Orlandini, Valentina Di Stefano, Annalena Puglisi simone.orlandini@unifi.it Symposium on Climate Change and Variability-Agro Meteorological Monitoring and Coping Strategies for Agriculture. Oscarsborg, Norway COST ACTION 734 ET - Climate Risks in Vulnerable Areas: Agrometeorological Monitoring and Coping Strategies (WMO)
Grapevine: high quality of production sensible to environmental change longer growing season phenological phases anticipated risk of decrease of productions Increase temperature Napa Valley (California): flowering anticipated of more then 20 days (51-97 ). Increasing of frozen Risk reduction of bud productivity (Nemani et al., 2001) Bordeaux: anticipated and shorter phenological phases, longer growing season (Jones and Davis, 2000) Veneto (Italia): anticipated Merlot flowering (Chiaudani et al., 2007) Oregon: increase elevation limit for vegetation of grapevine (from 180 to 300 m asl) (Sergo, 2007) Australia: quality changed in the last 50 years (Powley, 2007)
Olive is a bio-indicator for the Mediterranean climate high temperature bloom anticipated (data get from pollen bulletin) Max [pollen] anticipation= 8.5 days/1 C (Chuine et al., 98) Olive cultivated up to England (McCarthy, 2006; Coldiretti, 2007)
Aims 1 Homogenization of the historical series of temperature (data of Tuscany region, Italy) 2 Analysis of the trend of last 50 years 3 Analysis of the potential effects of change and variability on the grapevine and olive responses Result are homogeneous historical series
Material and methods IBIMET CNR data base 55-2002 38 agrometeorological stations analysed on the basis of > Number of years < % missing value Regional area covering 22 termometric stations Daily Tmax e Tmin
Station characteristics Name Lat UTM_X Long UTM_Y Elevation (m.s.l.m.) Arezzo Boscolungo Camaldoli Castel del Piano Castelnuovo Garf. Elba Calamita Firenzuola Grosseto Livorno Lucca Massa Massa Marittima Montepulciano Orbetello Peretola Pisa Pistoia Pontremoli San Miniato Siena Vallombrosa Volterra 730805 633977 727025 706920 613275 614306 689640 669415 606140 620990 591800 653850 726520 681025 676985 613017 653080 570117 647740 687630 706000 649965 4815384 4888891 4853030 4752060 4885305 4731893 4888022 4735216 4822595 4855580 4875450 4768500 4774950 4699970 4852101 4838671 4867535 4913436 4838630 4799185 4845450 4808235 249 1340 1110 596 280 380 454 5 9 25 38 362 575 1 38 3 88 247 132 346 972 465
Homogenization of the historical series original data Test of data quality Craddock test Homogenization { Tmax >= 42 C Tmin < - 15 C Δ >= 25 C Tmin o Tmax = for 5 or + days Tmin e Tmax = for 3 or + days Tmin > Tmax Reference stations: not only one but 10 stations Homogenization made by trigonometric fitting, reference period true up in the not homogeneity year Auer et al., 2005 Metadata Maugeri et al., 2004 (UNIMI) Brunetti et al., 2006 (CNR-ISAC)
Agroclimatic indices Durations of vegetative season (threshold: 10 C) Durations of vegetative season (threshold: 0 C) Degree day accumulation Mean of the maximum temperature Huglin index (grape) Mean of the minimum temperature Date of Bud-break (grape) Mean of the range of temperature Date of Flowering (grape) Frequency of frosts Date of growth (grape) Date of the last frost event Minimum temperature of the last frost event Date of the first autumnal frost Minimum temperature of the first autumnal frost September October mean temperature (olive) Chilling requirement (olive) Days with minimum temperature < 7 C (olive)
The historical series analysis slope (annual variation rate) Linear regression significativity p { 0.05 0.01 0.001 moving mean (5 year) Climate variability analysis standard deviations (5 years)
RESULTS
Craddock Test (Firenzuola, Tmax) before after
55-2002 Sub-periods analysis Craddock Test for the Tmin (Grosseto station). Annual trend
80-2002 Sub-periods analysis Craddock Test for the minimum temperature (Grosseto station). Annual trend.
AGROCLIMATIC INDICES
Duration of vegetative season threshold 0 C Peretola - DSV 0 C threshold 10 C Montepulciano - DSV 10 C y = 0.7903x + 153.2 y = 0.2187x + 166.52 R2 = 0.0081 R2 = 0.094 300 250 250 200 200 150 150 (Peretola station) (p<0.05) 00 97 20 94 (Montepulciano station) (p<0.05) 91 88 85 82 79 76 73 70 67 64 61 55 00 97 20 94 91 88 85 82 79 76 73 70 67 64 0 61 0 58 50 55 50 58 100 100
Maximum and minimum temperature Increase of temperature Minimum temperature trend period July-August-September (Massa station) (p<0.001). Maximum temperature trend period July-August-September (Livorno station) (p<0.01)
Maximum and minimum temperature ~~~~~~~~~~~~~~~~~~~~~~~~ 55-2002 April July August September Tmin ~ + ++ ~ Tmax ~ ~ /+ ++ ~
Grapevine phenology The sky-blue data are the ones with longer phenological phases. The red data are the stations in which the heat-need is not reach.
Frost and phenology 140 120 100 frost risks la u g rn io G 80 60 40 20 0 Tempo (anni) Lucca Montepulciano 120 100 80 Increase of frost risks la u g rn io G 60 40 20 0 Tempo (anni)
Flowering phase Trend of anticipation: 8 days during the study period Arezzo station (p<0.01).
Ripening period 21 days during the study period -21 Day! -21 giorni Grosseto (p<0.001).
Ripening period
Huglin index Values from 1884.4 to 2089.9 (+11%) quality IH High quality wine 1500-2000 Dessert wine 2000-2800 (t med 10) + (t max 10) IH = K 2 01 04 30 09
Huglin Index
Degree day accumulation Values from 1499.7-1675.0 C Elba Calamita station(p<0.001)
Degree day accumulation interannual variability Moving mean and standard deviations of the STA index (Montepulciano station). The mean (55-59) is about 59 C. The δ2 shows a significant trend (p<0.01).
Degree day accumulation
Chilling requirement (hours with T<7.2 C) Reduction: 1514 hours 1113 hours y = -8,5339x + 1522,7 R2 = 0,2091 Vernalizzazione - Massa M.ma 2000 1800 1200 1000 Tempo (anni) Massa Marittima station. (p<0.001). 00 20 97 94 91 88 85 82 79 76 73 70 67 64 61 58 55 800 600 400 Ore 1600 1400
September October mean temperature y = 0,0229x - 28,075 2 R = 0,0923 p<0,05 22.0 Temperatura ( C) 20.0 18.0 16.0 14.0 12.0 10.0 40 50 60 70 80 Tempo (anni) 90 2000 2010
Conclusions Better quality of the data thank to the homogenization Increase of Tmin, Tmax, degree day accumulation Tendency of the anticipation for the phenological phases > Risks (late frost) Fast growth rate < time for ripening Lengthening of growing season increase of Huglin index increase inter annual variability Shorten Affecting productions and quality Chilling period problems for the optimal threshold for the olive
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