Combined impact of climate change,cultivar shift,and sowing date on spring wheat phenology in Northern China

Distinct climate changes since the end of the 1980s have led to clear responses in crop phenology in many parts of the world. This study investigated the trends in the dates of spring wheat phenology in relation to mean temperature for different growth stages. It also analyzed the impacts of climate change, cultivar shift, and sowing date adjustments on phenological events/phases of spring wheat in northern China (NC). The results showed that significant changes have occurred in spring wheat phenology in NC due to climate warming in the past 30 years. Specifically, the dates of anthesis and maturity of spring wheat advanced on average by 1.8 and 1.7 day (10 yr)^?1. Moreover, while the vegetative growth period (VGP) shortened at most stations, the reproductive growth period (RGP) prolonged slightly at half of the investigated stations. As a result, the whole growth period (WGP) of spring wheat shortened at most stations. The findings from the Agricultural Production Systems Simulator (APSIM)-Wheat model simulated results for six representative stations further suggested that temperature rise generally shortened the spring wheat growth period in NC. Although the warming trend shortened the lengths of VGP, RGP, and WGP, the shift of new cultivars with high accumulated temperature requirements, to some extent, mitigated and adapted to the ongoing climate change. Furthermore, shifts in sowing date exerted significant impacts on the phenology of spring wheat. Generally, an advanced sowing date was able to lower the rise in mean temperature during the different growth stages (i.e., VGP, RGP, and WGP) of spring wheat. As a result, the lengths of the growth stages should be prolonged. Both measures (cultivar shift and sowing date adjustments) could be vital adaptation strategies of spring wheat to a warming climate, with potentially beneficial effects in terms of productivity.     

Combined Impact of Climate Change,Cultivar Shift,and Sowing Date on Spring Wheat Phenology in Northern China

Distinct climate changes since the end of the 1980 s have led to clear responses in crop phenology in many parts of the world. This study investigated the trends in the dates of spring wheat phenology in relation to mean temperature for different growth stages. It also analyzed the impacts of climate change, cultivar shift, and sowing date adjustments on phenological events/phases of spring wheat in northern China(NC).The results showed that significant changes have occurred in spring wheat phenology in NC due to climate warming in the past 30 years. Specifically, the dates of anthesis and maturity of spring wheat advanced on average by 1.8 and 1.7 day(10 yr)~(-1). Moreover, while the vegetative growth period(VGP) shortened at most stations, the reproductive growth period(RGP) prolonged slightly at half of the investigated stations. As a result, the whole growth period(WGP) of spring wheat shortened at most stations. The findings from the Agricultural Production Systems Simulator(APSIM)-Wheat model simulated results for six representative stations further suggested that temperature rise generally shortened the spring wheat growth period in NC.Although the warming trend shortened the lengths of VGP, RGP, and WGP, the shift of new cultivars with high accumulated temperature requirements, to some extent, mitigated and adapted to the ongoing climate change. Furthermore, shifts in sowing date exerted significant impacts on the phenology of spring wheat.Generally, an advanced sowing date was able to lower the rise in mean temperature during the different growth stages(i.e., VGP, RGP, and WGP) of spring wheat. As a result, the lengths of the growth stages should be prolonged. Both measures(cultivar shift and sowing date adjustments) could be vital adaptation strategies of spring wheat to a warming climate, with potentially beneficial effects in terms of productivity.     

Variations in cereal crop phenology in Spain over the last twenty-six years (1986–2012)

Over recent years, the Iberian Peninsula has witnessed an increase both in temperature and in rainfall intensity, especially in the Mediterranean climate area. Plant phenology is modulated by climate, and closely governed by water availability and air temperature. Over the period 1986–2012, the effects of climate change on phenology were analyzed in five crops at 26 sites growing in Spain (southern Europe): oats, wheat, rye, barley and maize. The phenophases studied were: sowing date, emergence, flag leaf sheath swollen, flowering, seed ripening and harvest. Trends in phenological response over time were detected using linear regression. Trends in air temperature and rainfall over the period prior to each phenophase were also charted. Correlations between phenological features, biogeographical area and weather trends were examined using a Generalized Lineal Mixed Model approach. A generalized advance in most winter-cereal phenophases was observed, mainly during the spring. Trend patterns differed between species and phenophases. The most noticeable advance in spring phenology was recorded for wheat and oats, the “Flag leaf sheath swollen” and “Flowering date” phenophases being brought forward by around 3 days/year and 1 day/year, respectively. Temperature changes during the period prior to phenophase onset were identified as the cause of these phenological trends. Climate changes are clearly prompting variations in cereal crop phenology; their consequences could be even more marked if climate change persists into the next century. Changes in phenology could in turn impact crop yield; fortunately, human intervention in crop systems is likely to minimize the negative impact.     

Effects of climate change on the phenology of <Emphasis Type="Italic">Osmia cornifrons</Emphasis>: implications for population management

The phenology of many ecological processes including pollination service is modulated by surface air temperature, making them potentially sensitive to climatic change. The Japanese hornfaced bee, Osmia cornifrons (Hymenoptera: Megachilidae), was introduced into the USA in the 1970s and has been used as a key pollinator of spring blooming fruit crops such as apple and blueberry. This study examined the effects of future climate change on three key phenological events of O. cornifrons: date for adult emergence (female and male) in spring, date for completion of egg and larval development, and duration for the development in the Eastern USA. We used daily temperature data obtained from 21 models in Coupled Model Intercomparison Project Phase 5 for 2006–2100 under the two future climate scenarios of Representative Concentration Pathways (RCPs 4.5 and 8.5). We estimated the Julian dates (JDs) of spring emergence and development of O. cornifrons using the phenological parameters derived from temperature-dependent biophysical models. The JDs for the bee emergence and development are projected to be significantly advanced in the Eastern USA under the RCP 4.5 and 8.5 scenarios. The number of days for bee development is projected to be longer in the southern region (+?0.57 days/decade) and shorter in the central (??0.27 days/decade) and northern (??0.65 days/decade) regions of the Eastern USA (all the p values <?0.01). The significantly longer duration of bee development under future climate change could pose a risk to the bee due to the longer period of being exposed to its pests. Implications for management of O. cornifrons population were discussed in this article.     

Impact of future climate change on wheat production in relation to plant-available water capacity in a semiaridenvironment

Conceptions encompassing climate change are irreversible rise of atmospheric carbon dioxide (CO₂) concentration, increased temperature, and changes in rainfall both in spatial- and temporal-scales worldwide. This will have a major impact on wheat production, particularly if crops are frequently exposed to a sequence, frequency, and intensity of specific weather events like high temperature during growth period. However, the process of wheat response to climate change is complex and compounded by interactions among atmospheric CO₂ concentration_, climate variables, soil, nutrition, and agronomic management. In this study, we use the Agricultural Production Systems sIMulator (APSIM)-wheat model, driven by statistically downscaled climate projections of 18 global circulation models (GCMs) under the 2007 Intergovernmental Panel on Climate Change (IPCC) Special Report on Emission Scenarios (SRES) A2 CO₂ emission scenario to examine impact on future wheat yields across key wheat growing regions considering different soil types in New South Wales (NSW) of Australia. The response of wheat yield, yield components, and phenology vary across sites and soil types, but yield is closely related to plant available water capacity (PAWC). Results show a decreasing yield trend during the period of 2021–2040 compared to the baseline period of 1961–1990. Across different wheat-growing regions in NSW, grain yield difference in the future period (2021–2040) over the baseline (1961–1990) varies from +3.4 to ?14.7 %, and in most sites, grain number is decreased, while grain size is increased in future climate. Reduction of wheat yield is mainly due to shorter growth duration, where average flowering and maturing time are advanced by an average of 11 and 12 days, respectively. In general, larger negative impacts of climate change are exhibited in those sites with higher PAWC. Current wheat cultivars with shorter growing season properties are viable in the future climate, but breading for early sowing wheat varieties with longer growing duration will be a desirable adaptation strategy for mitigating the impact of changing climate on wheat yield.     

Projected Changes in Extreme High Temperature and Heat Stress in China

High temperature accompanied with high humidity may result in unbearable and oppressive weather. In this study, future changes of extreme high temperature and heat stress in mainland China are examined based on daily maximum temperature (T_x) and daily maximum wet-bulb globe temperature (T_w). T_w has integrated the effects of both temperature and humidity. Future climate projections are derived from the bias-corrected climate data of five general circulation models under the Representative Concentration Pathways (RCPs) 2.6 and 8.5 scenarios. Changes of hot days and heat waves in July and August in the future (particularly for 2020–50 and 2070–99), relative to the baseline period (1981–2010), are estimated and analyzed. The results show that the future T_x and T_w of entire China will increase by 1.5–5°C on average around 2085 under different RCPs. Future increases in T_x and T_w exhibit high spatial heterogeneity, ranging from 1.2 to 6°C across different regions and RCPs. By around 2085, the mean duration of heat waves will increase by 5 days per annum under RCP8.5. According to T_x, heat waves will mostly occur in Northwest and Southeast China, whereas based on T_w estimates, heat waves will mostly occur over Southeast China and the mean heat wave duration will be much longer than those from T_x. The total extreme hot days (T_x or T_w > 35°C) will increase by 10–30 days. Southeast China will experience the severest heat stress in the near future as extreme high temperature and heat waves will occur more often in this region, which is particularly true when heat waves are assessed based on T_w. In comparison to those purely temperature-based indices, the index T_w provides a new perspective for heat stress assessment in China.     

河南省稻麦类作物对气候变化的响应

小麦和水稻是世界最重要的粮食作物。利用河南省小麦和水稻的历史观测资料,结合DSSAT-CERES小麦和ORYZA2000水稻模拟模型,分析和模拟河南省稻麦类作物在历史气候变化条件下生育期和产量的变化。结果表明:冬小麦全生育期长度呈缩短趋势,但播种-越冬天数平均每10 a增加1.7 d,开花到乳熟天数平均每10 a增加2-4 d,返青后各生育期均表现出不同程度的提前;水稻各生育期均有不同程度的提前,尤其是拔节期以前,分蘖前的生育期间隔天数以缩短为主,拔节后以延长为主。雨养小麦模拟产量和水氮增产潜力均呈减少趋势;随着播种期的提前,水稻减产趋势逐渐减弱。     

Simulation of leaf blast infection in tropical rice agro-ecology under climate change scenario

Assessing disease risk has become an important component in the development of climate change adaptation strategies. Here, the infection ability of leaf blast (Magnaporthe oryzae) was modeled based on the epidemiological parameters of minimum (T _min), optimum (T _opt), and maximum (T _max) temperatures for sporulation and lesion development. An infection ability response curve was used to assess the impact of rising temperature on the disease. The simulated spatial pattern of the infection ability index (IAI) corresponded with observed leaf blast occurrence in Indo-Gangetic plains (IGP). The IAI for leaf blast is projected to increase during the winter season (December–March) in 2020 (2010–2039) and 2050 (2040–2069) climate scenarios due to temperature rise, particularly in lower latitudes. However, during monsoon season (July–October), the IAI is projected to remain unchanged or even reduce across the IGP. The results show that the response curve may be successfully used to assess the impact of climate change on leaf blast in rice. The model could be further extended with a crop model to assess yield loss.     

河南省稻麦类作物对气候变化的响应

小麦和水稻是世界最重要的粮食作物。利用河南省小麦和水稻的历史观测资料,结合DSSAT-CERES 小麦和ORYZA2000水稻模拟模型,分析和模拟河南省稻麦类作物在历史气候变化条件下发育期和产量的变化。结果表明：冬小麦全育期长度呈缩短趋势,但播种-越冬天数平均每10年增加1.7天,开花到乳熟天数平均每10年增加2-4天,返青后各发育期均表现出不同程度的提前;水稻各发育期均有不同程度的提前,尤其是拔节期以前,分蘖前的发育期间隔天数以缩短为主,拔节后以延长为主。雨养小麦模拟产量和水氮增产潜力均呈减少趋势;随着播种期的提前,水稻减产趋势逐渐减弱。     

北方农牧交错带春小麦生育期对气候变化的响应——以内蒙古武川县为例

北方农牧交错带是气候变化的敏感地带,研究气候变化对农业生产的影响规律与农业生产的响应特征,对促进北方农牧交错带的农业可持续发展具有重要意义。以北方农牧交错带代表性站点--武川县为例,基于1960-2009年气象观测数据和1992-2010年春小麦农业气象观测数据,研究了气候变化与春小麦生育期变化之间的相互关系。结果表明,武川县1960-2009年年平均气温每10年升高0.43℃,春季稳定通过0℃的初日每10年提前0.98 d,当地满足春小麦播种温度的日期有提前的趋势,秋季稳定通过0℃的终日每10年推迟0.24 d,生长季具有延长趋势;1992-2010年作物生长季（4-8月）0～10 cm、10～20 cm土壤相对湿度有明显下降趋势,平均每10年分别下降18%和13%;播种期与0～10 cm和10～20 cm土壤相对湿度呈现显著负相关关系,表现为土壤相对湿度每降低1%,播种期分别推迟0.2 d和0.3 d;各生育期与播种期一样,受温度与水分综合作用的影响,不同生育期与二者之间关系不同,各生育期之间持续日数与二者呈正相关关系。研究得出,春小麦生育期的变化是各气侯因素综合作用的结果,在北方农牧交错带,水分对农作物生长发育具有较大影响,直接影响着春小麦的各个生育过程。     

A compact form for the analytic description of temperature dependence of saturation vapor pressure over plane surfaces of water and ice

A possibility is studied of extending the range of action of the simple three-parameter formula (ITS-90 scale) proposed in the previous work of the author [2] for the dependence of saturation vapor pressure E on temperature T within the range of 250 to 490 K. The results demonstrated that the dependence ln[E(T)/E(T _bas)] = (T - T _bas)[A - B(T - T _bas) + C(T - T _bas)²]/T with four sets of coefficients A, B, and C obtained using one base temperature Tbas equal to the temperature of triple point of water T _t = 273.16 K and two additional base values T _bas2 = 473.16 K and T _bas3 = 623.16 K makes it possible to approximate rather accurately the initial experimental and computed data in the temperature range from the point of homogeneous freezing of 235 K to the critical temperature of 647 K for liquid water and from 193 K to T _t for ice. A procedure used for obtaining the inverse function T(E) by solving the third-degree algebraic equation is validated. A hypothesis is proposed for the physical substantiation of additional base points in the form of “a noticeable appearance of dimers at the point T _bas2 and their 100% concentration at the temperature T _bas3.”     

Multivariate drought frequency estimation using copula method in Southwest China

This study reveals the impacts of climatic variable trends on drought severity in Xinjiang, China. Four drought indices, including the self-calibrating Palmer drought severity index (sc-PDSI), Erinç’s index (I _m), Sahin’s index (I _sh), and UNEP aridity index (AI), were used to compare drought severity. The ensemble empirical mode decomposition and the modified Mann-Kendall trend test were applied to analyze the nonlinear components and trends of the climatic variable and drought indices. Four and six climatic scenarios were generated in sc-PDSI, I _m, I _sh, and AI with different combinations of the observed and detrended climatic variables, respectively. In Xinjiang, generally increasing trends in minimal, average, and maximal air temperature (T _min, T _ave, T _max) and precipitation (P) were found, whereas a decreasing trend in wind speed at 2 m height (U ₂) was observed. There were significantly increasing trends in all of the four studied drought indices. Drought relief was more obvious in northern Xinjiang than in southern Xinjiang. The strong influences of increased P on drought relief and the weak influences of increased T _min, T _ave, and T _max on drought aggravation were shown by comparing four drought indices under different climate scenarios. Decreased U ₂ had a weak influence on drought, as shown by the AI in different climate scenarios. The weak influences of T and U ₂ were considered to be masked by the strong influences of P on droughts. Droughts were expected to be more severe if P did not increase, but were likely milder without an increase in air temperature and with a decrease in U ₂.     

Comprehensive modeling of monthly mean soil temperature using multivariate adaptive regression splines and support vector machine

Soil temperature (T _s) and its thermal regime are the most important factors in plant growth, biological activities, and water movement in soil. Due to scarcity of the T _s data, estimation of soil temperature is an important issue in different fields of sciences. The main objective of the present study is to investigate the accuracy of multivariate adaptive regression splines (MARS) and support vector machine (SVM) methods for estimating the T _s. For this aim, the monthly mean data of the T _s (at depths of 5, 10, 50, and 100 cm) and meteorological parameters of 30 synoptic stations in Iran were utilized. To develop the MARS and SVM models, various combinations of minimum, maximum, and mean air temperatures (T _min, T _max, T); actual and maximum possible sunshine duration; sunshine duration ratio (n, N, n/N); actual, net, and extraterrestrial solar radiation data (R _s, R _n, R _a); precipitation (P); relative humidity (RH); wind speed at 2 m height (u ₂); and water vapor pressure (V_p) were used as input variables. Three error statistics including root-mean-square-error (RMSE), mean absolute error (MAE), and determination coefficient (R ²) were used to check the performance of MARS and SVM models. The results indicated that the MARS was superior to the SVM at different depths. In the test and validation phases, the most accurate estimations for the MARS were obtained at the depth of 10 cm for T _max, T _min, T inputs (RMSE = 0.71 °C, MAE = 0.54 °C, and R ² = 0.995) and for RH, V _p, P, and u ₂ inputs (RMSE = 0.80 °C, MAE = 0.61 °C, and R ² = 0.996), respectively.     

Drivers of the Severity of the Extreme Hot Summer of 2015 in Western China

Western China experienced an extreme hot summer in 2015, breaking a number of temperature records. The summer mean surface air temperature (SAT) anomaly was twice the interannual variability. The hottest daytime temperature (T_Xx) and warmest night-time temperature (T_Nx) were the highest in China since 1964. This extreme hot summer occurred in the context of steadily increasing temperatures in recent decades. We carried out a set of experiments to evaluate the extent to which the changes in sea surface temperature (SST)/sea ice extent (SIE) and anthropogenic forcing drove the severity of the extreme summer of 2015 in western China. Our results indicate that about 65%–72% of the observed changes in the seasonal mean SAT and the daily maximum (T_max) and daily minimum (T_min) temperatures over western China resulted from changes in boundary forcings, including the SST/SIE and anthropogenic forcing. For the relative role of individual forcing, the direct impact of changes in anthropogenic forcing explain about 42% of the SAT warming and 60% (40%) of the increase in T_Nx and Tmin (T_Xx and T_max) in the model response. The changes in SST/SIE contributed to the remaining surface warming and the increase in hot extremes, which are mainly the result of changes in the SST over the Pacific Ocean, where a super El Niño event occurred. Our study indicates a prominent role for the direct impact of anthropogenic forcing in the severity of the extreme hot summer in western China in 2015, although the changes in SST/SIE, as well as the internal variability of the atmosphere, also made a contribution.     

北方冬小麦冬季冻害及播期延迟应对

全球变暖背景下, 我国北方冬麦区冬季冻害是否仍是主要气象灾害,冬小麦播期延迟是否能作为应对气候变化的措施,成为当前亟待解决的科学问题。研究表明:1981—2000年北方冬麦区偏北地区冬季冻害指数与冬小麦减产率相关系数为0.62(达到0.001显著性水平),即2000年前冬季冻害是冬小麦减产的主要气象灾害之一;2000年后冻害与冬小麦减产率相关不显著,即冬季冻害已不再是冬小麦减产的主要影响因子。2018—2021年的冬小麦分期播种试验分析表明:山东泰安和陕西咸阳主栽的冬小麦品种播期推迟,冬前积温和生长季积温明显减少,导致冬小麦植株高度、地上总干重和叶面积指数减小;播期推迟对产量结构造成不利影响,有效穗数、穗粒数和千粒重均分别减少,导致减产,播期推迟10 d平均减产22%,推迟20 d平均减产40%。因此,冬小麦推迟播期并未产生积极效应, 可能原因是当前冬小麦播期和主栽的冬小麦品种已适应当地气候变化。     

Interdisciplinary approaches: towards new statistical methods for phenological studies

The importance of global environmental questions has significantly advanced the impact of climate change phenology. Whilst spatial applications continue to be a core application of phenology; in recent years the temporal dimension has also been revisited, with studies showing that temporal changes, either with a natural or an anthropogenic origin, have significantly altered phenological rhythms and seasonal development—changes attributed now to an anthropogenically induced temperature increase. This paper explores and introduces recent and newly developing analytic methods in phenology; with a view to increasing an interdisciplinary perspective and dialogue. Of particular focus is how we can and best deal with nonlinearity of phenological change in time and with multiple location studies; rigorously model the inherent multivariate time series structures in climate-phenology data; further Bayesian and non-Bayesian methods, detect multiple change-points; map seasonality calendars; model de-synchronisation of species globally; invoke old fashioned, yet rarely used circular statistical methods; adapt new transitional state modelling of phenophases with respect to climate and progress a unified paradigm for meta analytic studies in phenology. The provision of uncertainty analysis is also still much needed in climate-related phenological research. Reaching consensus on design, method of data collection and comparable analytic methods is integral to advancing the generalisability of phenological results; as is a consensus on inclusion criterion for studies selected for phenological meta-analytic studies. A coherent nomenclature is critically required, but it is currently lacking in many areas of phenology.     

Potential Impacts of Climate Change on Tropical Asian Forests Through an Influence on Phenology

Changes in plant phenology will be one of the earliest responses to rapid global climate change and could potentially have serious consequences both for plants and for animals that depend on periodically available plant resources. Phenological patterns are most diverse and least understood in the tropics. In those parts of tropical Asia where low temperature or drought impose a seasonal rest period, regular annual cycles of growth and reproduction predominate at the individual, population, and community level. In aseasonal areas, individuals and populations show a range of sub- to supra-annual periodicities, with an overall supra-annual reproductive periodicity at the community level. There is no evidence for photoperiod control of phenology in the Asian tropics, and seasonal changes in temperature are a likely factor only near the northern margins. An opportunistic response to water availability is the simplest explanation for most observed patterns where water is seasonally limiting, while the great diversity of phenological patterns in the aseasonal tropics suggests an equal diversity of controls. The robustness of current phenological patterns to high interannual and spatial variability suggests that most plant species will not be seriously affected by the phenological consequences alone of climate change. However, some individual plant species may suffer, and the consequences of changes in plant phenology for flower- and fruit-dependent animals in fragmented forests could be serious.     

Vulnerability and adaptability of wheat production in different climatic zones of Pakistan under climate change scenarios

Ten wheat production sites of Pakistan were categorized into four climatic zones i.e. arid, semi-arid, sub-humid and humid to explore the vulnerability of wheat production in these zones to climate change using CSM-Cropsim-CERES-Wheat model. The analysis was based on multi-year (1971–2000) crop model simulation runs using daily weather series under scenarios of increased temperature and atmospheric carbon dioxide concentration (CO₂) along with two scenarios of water management. Apart from this, sowing date as an adaptation option to offset the likely impacts of climate change was also considered. Increase in temperature resulted in yield declines in arid, semi-arid and sub-humid zone. But the humid zone followed a positive trend of gain in yield with rise in temperature up to 4°C. Within a water regime, increase in CO₂ concentration from 375 to 550 and 700 ppm will exert positive effect on gain in wheat yield but this positive effect is significantly variable in different climatic zones under rainfed conditions than the full irrigation. The highest response was shown by arid zone followed by semi-arid, sub-humid and humid zones. But if the current baseline water regimes (i.e. full irrigation in arid and semi-arid zones and rainfed in sub-humid and humid zones) persist in future, the sub-humid zone will be most benefited in terms of significantly higher percent gain in yield by increasing CO₂ level, mainly because of its rainfed water regime. Within a CO₂ level the changes in water supply from rainfed to full irrigation shows an intense degree of responsiveness in terms of yield gain at 375 ppm CO₂ level compared to 550 and 700 ppm. Arid and semi-arid zones were more responsive compared to sub-humid and humid zones. Rise in temperature reduced the length of crop life cycle in all areas, though at an accelerated rate in the humid zone. These results revealed that the climatic zones have shown a variable intensity of vulnerability to different scenarios of climate change and water management due to their inherent specific and spatial climatic features. In order to cope with the negative effects of climate change, alteration in sowing date towards cooler months will be an appropriate response by the farmers.     

Trend analysis of Climatic Research Unit temperature dataset for Gangotri glacier,India

The absence of continuous long term meteorological dataset has led to limited knowledge of glaciers’ response to climate change over Himalayas. This study presents an open source long term temperature dataset Climatic Research Unit (CRU) available since 1901 to study trend analysis of temperature (T_max, T_min and T_mean) for Gangotri basin in Himalayas. The study first establishes close agreement between CRU time series data and observed temperature dataset available from National Institute of Hydrology (NIH), Roorkee for a period of 11 years from 2005 to 2015 using standard anomaly, Wilcoxon Signed-Rank (WSR) and correlation tests. The close agreement of CRU with NIH data validate the use of CRU time series to study variation in meteorological parameter for hilly terrain of Himalayas. The second part includes application of different statistical tests such as Mann-Kendall (MK), Sen’s slope and CUSUM technique on CRU data to detect existence of any possible trends and identification of change points in T_max, T_min and T_mean on long term scale. On annual scale, significant increasing trends for T_mean and T_min were observed with no significant trend for T_max. On seasonal and monthly scale, T_max showed significant decreasing trend for monsoon season and increasing trend for winters while T_min show significant increasing trend for all months (except May) and seasons. CUSUM technique identified 8 change points from 3 annual time series with 2 for T_mean (1974 and 1999), 3 each for T_max (1941, 1975 and 1999) and T_min (1941, 1965 and 1999) respectively. Overall, significant increase in T_min with no significant trend for T_max has been identified over the study area.     

Olive flowering phenology variation between different cultivars in Spain and Italy: modeling analysis

Phenology data are sensitive data to identify how plants are adapted to local climate and how they respond to climatic changes. Modeling flowering phenology allows us to identify the meteorological variables determining the reproductive cycle. Phenology of temperate of woody plants is assumed to be locally adapted to climate. Nevertheless, recent research shows that local adaptation may not be an important constraint in predicting phenological responses. We analyzed variations in flowering dates of Olea europaea L. at different sites of Spain and Italy, testing for a genetic differentiation of flowering phenology among olive varieties to estimate whether local modeling is necessary for olive or not. We build models for the onset and peak dates flowering in different sites of Andalusia and Puglia. Process-based phenological models using temperature as input variable and photoperiod as the threshold date to start temperature accumulation were developed to predict both dates. Our results confirm and update previous results that indicated an advance in olive onset dates. The results indicate that both internal and external validity were higher in the models that used the photoperiod as an indicator to start to cumulate temperature. The use of the unified model for modeling the start and peak dates in the different localities provides standardized results for the comparative study. The use of regional models grouping localities by varieties and climate similarities indicate that local adaptation would not be an important factor in predicting olive phenological responses face to the global temperature increase.