An improved simulation of mesoscale dispersion of airborne cedar pollen using a flowering-time map

A model that simulates emission and dispersion of pollen of Japanese cedar (Cryptomeria japonica D. Don) was developed and tested for the Tohoku district of Japan. To take into account the effect of altitude and local climate on flowering time, a flowering-time map was tested. The observed variation in the number of pollen grains was high in Yamagata City and relatively small in the southern cities. Sakata, facing the Sea of Japan, shows an individual pattern with two large peaks. Simulation without a flowering-time map predicted unobserved large peaks at the beginning and end of the cedar pollen season and tended to overestimate peaks in general. Simulation with a flowering-time map closely reproduced the changes in the number of airborne pollen grains with time at the beginning and end of the season and simulated the general variation in airborne pollen number well.     

Phenology and productivity in a montane bird assemblage: Trends and responses to elevation and climate variation

Climate variation has been linked to historical and predicted future distributions and dynamics of wildlife populations. However, demographic mechanisms underlying these changes remain poorly understood. Here, we assessed variation and trends in climate (annual snowfall and spring temperature anomalies) and avian demographic variables from mist‐netting data (breeding phenology and productivity) at six sites along an elevation gradient spanning the montane zone of Yosemite National Park between 1993 and 2017. We implemented multi‐species hierarchical models to relate demographic responses to elevation and climate covariates. Annual variation in climate and avian demographic variables was high. Snowfall declined (10 mm/year at the highest site, 2 mm at the lowest site), while spring temperature increased (0.045°C/year) over the study period. Breeding phenology (mean first capture date of juvenile birds) advanced by 0.2 day/year (5 days); and productivity (probability of capturing a juvenile bird) increased by 0.8%/year. Breeding phenology was 12 days earlier at the lowest compared to highest site, 18 days earlier in years with lowest compared to highest snowfall anomalies, and 6 d earlier in relatively warm springs (after controlling for snowfall effects). Productivity was positively related to elevation. However, elevation–productivity responses varied among species; species with higher productivity at higher compared to lower elevations tended to be species with documented range retractions during the past century. Productivity tended to be negatively related to snowfall and was positively related to spring temperature. Overall, our results suggest that birds have tracked the variable climatic conditions in this system and have benefited from a trend toward warmer, drier springs. However, we caution that continued warming and multi‐year drought or extreme weather years may alter these relationships in the future. Multi‐species demographic modeling, such as implemented here, can provide an important tool for guiding conservation of species assemblages under global change.     

The start of frozen dates over northern permafrost regions with the changing climate

The soil freeze–thaw cycle in the permafrost regions has a significant impact on regional surface energy and water balance. Although increasing efforts have been made to understand the responses of spring thawing to climate change, the mechanisms controlling the global interannual variability of the start date of permafrost frozen (SOF) remain unclear. Using long-term SOF from the combinations of multiple satellite microwave sensors between 1979 and 2020, and analytical techniques, including partial correlation, ridge regression, path analysis, and machine learning, we explored the responses of SOF to multiple climate change factors, including warming (surface and air temperature), start date of permafrost thawing (SOT), soil properties (soil temperature and volume of water), and the snow depth water equivalent (SDWE). Overall, climate warming exhibited the maximum control on SOF, but SOT in spring was also an important driver of SOF variability; among the 65.9% significant SOT and SOF correlations, 79.3% were positive, indicating an overall earlier thawing would contribute to an earlier frozen in winter. The machine learning analysis also suggested that apart from warming, SOT ranked as the second most important determinant of SOF. Therefore, we identified the mechanism responsible for the SOT–SOF relationship using the SEM analysis, which revealed that soil temperature change exhibited the maximum effect on this relationship, irrespective of the permafrost type. Finally, we analyzed the temporal changes in these responses using the moving window approach and found increased effect of soil warming on SOF. In conclusion, these results provide important insights into understanding and predicting SOF variations with future climate change.     

Global warming and the earlier start of the Japanese-cedar (Cryptomeria japonica) pollen season in Toyama, Japan

Atmospheric pollen surveys were conducted in Toyama City, Japan over a 21-year period (1983–2003). Airborne pollen was collected by two methods, the gravimetric method and the volumetric method. The gravimetric method indicated that the start of the Cryptomeria japonica pollen season, as indicated by pollen dispersion, has advanced from day 73 (from January 1) in 1983 to day 47 in 2003. Measurements taken using the volumetric method confirmed this trend. There was a significant correlation between the start dates obtained by both methods. Meteorological data indicated that the most noticeable elevation in temperature during the experimental period occurred in February – an increase of 2.1°C. Significant correlations existed between the mean temperatures and the start dates of the pollen season. These results support the steadily increasing number of reports indicating a global warming trend. The temperature change in February in affecting the start dates of the C. japonica pollen season is particularly relevant in the context of human health. Further studies will be needed to clarify the effects of the global warming trend on the pollen season and human health in more detail.     

Airborne pine (Pinus spp.) pollen in the atmosphere of Perugia (Central Italy): Behaviour of pollination in the two last decades

The phenology of many species, which grow intemperate climate, is principally regulated bythe temperature and the plants respond withvariations in the beginning, in the durationand in the intensity of the various phenophasestowards every climate change. We have analysedthe data of Pinus pollination in Perugia,Central Italy, during last 2 decades(1982–2001), in a period during which theannual mean temperature significantly increasedby about 0.8 °C.The pine pollination started, on average,between the end of March and mid-April andended in the last days of June, with a meanduration of 65 days. The start dates showed asignificant negative correlation with theaverage air temperature in March andsignificant trends towards an earlier beginningof pollination by 18 days (–0.9 day/year) and ashorter duration of the pollen season by 10days (–0.6 day/year) were found over thestudied period. Moreover, the trend of thedaily pollen counts showed, on average, analmost normal distribution, but the analysis ofeach yearly trend revealed significantdifferences correlated with the meantemperature during the pollen season. Theseobserved trends in pine pollination suggest theuse of aerobiological monitoring of thisairborne pollen as indicator of temperaturechange in Central Italy over a relatively longperiod.     

Prediction of the birch pollen season characteristics in Cracow, Poland using an 18-year data series

The aim of the study was to construct the model forecasting the birch pollen season characteristics in Cracow on the basis of an 18-year data series. The study was performed using the volumetric method (Lanzoni/Burkard trap). The 98/95 % method was used to calculate the pollen season. The Spearman’s correlation test was applied to find the relationship between the meteorological parameters and pollen season characteristics. To construct the predictive model, the backward stepwise multiple regression analysis was used including the multi-collinearity of variables. The predictive models best fitted the pollen season start and end, especially models containing two independent variables. The peak concentration value was predicted with the higher prediction error. Also the accuracy of the models predicting the pollen season characteristics in 2009 was higher in comparison with 2010. Both, the multi-variable model and one-variable model for the beginning of the pollen season included air temperature during the last 10 days of February, while the multi-variable model also included humidity at the beginning of April. The models forecasting the end of the pollen season were based on temperature in March–April, while the peak day was predicted using the temperature during the last 10 days of March.     

Antagonistic effects of growing season and autumn temperatures on the timing of leaf coloration in winter deciduous trees

Autumn phenology remains a relatively neglected aspect in climate change research, which hinders an accurate assessment of the global carbon cycle and its sensitivity to climate change. Leaf coloration, a key indicator of the growing season end, is thought to be triggered mainly by high or low temperature and drought. However, how the control of leaf coloration is split between temperature and drought is not known for many species. Moreover, whether growing season and autumn temperatures interact in influencing the timing of leaf coloration is not clear. Here, we revealed major climate drivers of leaf coloration dates and their interactions using 154 phenological datasets for four winter deciduous tree species at 89 stations, and the corresponding daily mean/minimum air temperature and precipitation data across China's temperate zone from 1981 to 2012. Results show that temperature is more decisive than drought in causing leaf coloration, and the growing season mean temperature plays a more important role than the autumn mean minimum temperature. Higher growing season temperature and lower autumn minimum temperature would induce earlier leaf coloration date. Moreover, the mean temperature over the growing season correlates positively with the autumn minimum temperature. This implies that growing season mean temperature may offset the requirement of autumn minimum temperature in triggering leaf coloration. Our findings deepen the understanding of leaf coloration mechanisms in winter deciduous trees and suggest that leaf life‐span control depended on growing season mean temperature and autumn low temperature control and their interaction are major environmental cues. In the context of climate change, whether leaf coloration date advances or is delayed may depend on intensity of the offset effect of growing season temperature on autumn low temperature.     

Impacts of climate change on the seasonal distribution of migratory caribou

Arctic ecosystems are especially vulnerable to global climate change as temperature and precipitation regimes are altered. An ecologically and socially highly important northern terrestrial species that may be impacted by climate change is the caribou, Rangifer tarandus . We predicted the current and potential future occurrence of two migratory herds of caribou [Rivière George herd (RG) and Rivière-aux-Feuilles (RAF) herd] under a Canadian General Circulation Model climate change scenario, across all seasons in the Québec–Labrador peninsula, using climatic and habitat predictor variables. Argos satellite-tracking collars have been deployed on 213 caribou between 1988 and 2003 with locations recorded every 4–5 days. In addition, we assembled a database of climate (temperature, precipitation, snowfall, timing and length of growing season) and habitat data obtained from the SPOT VEGETATION satellite sensor. Logistic regression models indicated that both climatic and physical habitat variables were significant predictors of current migratory caribou occurrence. Migratory caribou appeared to prefer regions with higher snowfall and lichen availability in the fall and winter. In the summer, caribou preferred cooler areas likely corresponding to a lower prevalence of insects, and they avoided disturbed and recently burnt areas. Climate change projections using climate data predicted an increased range for the RAF herd and decreased range for the RG herd during 2040–2069, limiting the herds to northeastern regions of the Québec–Labrador peninsula. Direct and indirect consequences of climate change on these migratory caribou herds possibly include alteration in habitat use, migration patterns, foraging behaviour, and demography, in addition to social and economic stress to arctic and subarctic native human populations.     

Temperature and snowfall trigger alpine vegetation green‐up on the world's roof

Rapid temperature increase and its impacts on alpine ecosystems in the Qinghai–Tibetan Plateau, the world's highest and largest plateau, are a matter of global concern. Satellite observations have revealed distinctly different trend changes and contradicting temperature responses of vegetation green‐up dates, leading to broad debate about the Plateau's spring phenology and its climatic attribution. Large uncertainties in remote‐sensing estimates of phenology significantly limit efforts to predict the impacts of climate change on vegetation growth and carbon balance in the Qinghai–Tibetan Plateau, which are further exacerbated by a lack of detailed ground observation calibration. Here, we revealed the spatiotemporal variations and climate drivers of ground‐based herbaceous plant green‐up dates using 72 green‐up datasets for 22 herbaceous plant species at 23 phenological stations, and corresponding daily mean air temperature and daily precipitation data from 19 climate stations across eastern and southern parts of the Qinghai–Tibetan Plateau from 1981 to 2011. Results show that neither the continuously advancing trend from 1982 to 2011, nor a turning point in the mid to late 1990s as reported by remote‐sensing studies can be verified by most of the green‐up time series, and no robust evidence for a warmer winter‐induced later green‐up dates can be detected. Thus, chilling requirements may not be an important driver influencing green‐up responses to spring warming. Moreover, temperature‐only control of green‐up dates appears mainly at stations with relatively scarce preseason snowfall and lower elevation, while coupled temperature and precipitation controls of green‐up dates occur mostly at stations with relatively abundant preseason snowfall and higher elevation. The diversified interactions between snowfall and temperature during late winter to early spring likely determine the spatiotemporal variations of green‐up dates. Therefore, prediction of vegetation growth and carbon balance responses to global climate change on the world's roof should integrate both temperature and snowfall variations.     

Monitoring biogeographical response to climate change: The potential role of aeropalynology

To test models predicting biological reponse to future climate change, it is essential to find climatically-sensitive, easily monitored biological indicators that respond to climate change. Routine monitoring of airborne pollen, now undertaken on a near-global basis, could be adapted for this purpose. Analysis of spatial and seasonal variations in pollen levels in New Zealand suggests that the timing of onset and peak abundance of certain pollen taxa should be explored as possible bio-indicators of climate change. The onset of the airborne grass pollen season during the summer of 1988/89 varied consistently with latitude, and hence temperature, with the season in Southland commencing 8--9 days after Northland. However, these patterns were only apparent after sampling sites were separated into two groups reflecting predominantly urban or rural pollen sources. A less consistent north to south trend was apparent in the frequency of high (30 grains/m³) grass pollen levels, with high levels frequent in North Island localities in November, December and January and in southern localities during December and January. The successive onset of pollen seasons for the principal tree species during the spring-to-early summer warming interval may also be a useful bio-indicator of climate change. As well as assisting forecasts of the onset of the pollinosis season, these biogeographical patterns, reflecting climatic variation with latitude, suggest that routine aeropalynological monitoring might provide early signals of vegetation response to climate change. These conclusions are supported by recent investigations of long-term aeropalynological datasets in Europe that indicate earlier onset of pollen seasons in response to recent global warming.     

Amphibian breeding phenology trends under climate change: predicting the past to forecast the future

Global climate warming is predicted to hasten the onset of spring breeding by anuran amphibians in seasonal environments. Previous data had indicated that the breeding phenology of a population of Fowler's Toads (Anaxyrus fowleri) at their northern range limit had been progressively later in spring, contrary to generally observed trends in other species. Although these animals are known to respond to environmental temperature and the lunar cycle to commence breeding, the timing of breeding should also be influenced by the onset of overwintering animals’ prior upward movement through the soil column from beneath the frost line as winter becomes spring. I used recorded weather data to identify four factors of temperature, rainfall and snowfall in late winter and early spring that correlated with the toads’ eventual date of emergence aboveground. Estimated dates of spring emergence of the toads calculated using a predictive model based on these factors, as well as the illumination of the moon, were highly correlated with observed dates of emergence over 24 consecutive years. Using the model to estimate of past dates of spring breeding (i.e. retrodiction) indicated that even three decades of data were insufficient to discern any appreciable phenological trend in these toads. However, by employing weather data dating back to 1876, I detected a significant trend over 140 years towards earlier spring emergence by the toads by less than half a day/decade, while, over the same period of time, average annual air temperature and annual precipitation had both increased. Changes in the springtime breeding phenology for late‐breeding species, such as Fowler's Toads, therefore may conform to expectations of earlier breeding under global warming. Improved understanding of the environmental cues that bring organisms out of winter dormancy will enable better interpretation of long‐term phenological trends.     

Application of a numerical model to predict impacts of climate change on water temperatures in two deep, oligotrophic lakes in New Zealand

We applied a numerical hydrodynamic model (DYRESM) to two large, deep New Zealand lakes that are characterised by deep thermoclines and high wind forcing, to assess their sensitivity to changes in climate. Modifications to standard model parameters were necessary for the successful application of DYRESM. Predictions from downscaled global circulation models suggest an increase in mean air temperature, rainfall, and wind speeds. Modelling the hydrodynamics of the lakes suggests that increasing air temperatures would offset the cooling influences of increased rainfall and river flows, resulting in warmer overall lake temperatures, and an earlier, longer, and shallower thermal stratification. These physical changes could affect phytoplankton production as their light limitation would decrease in duration and intensity. However, deeper mixing caused by increases in wind speed would negate this reduction of thermocline depth. While warmer air temperatures appear to be the dominant driver of changes in thermal structure, changes in other meteorological factors, especially wind speed, are important in predicting future hydrodynamics. Compared to large, deep lakes in the Northern Hemisphere, the predicted warming rates in Lakes Wanaka and Wakatipu are slower, due partly to a lower predicted rate of atmospheric warming and the absence of winter ice cover in these lakes.     

天山北坡经济带棉花播期对气候变暖的响应

利用1971—2010年天山北坡经济带棉区11个代表站的气象资料,采用气候倾向率、t 检验和IDW插值方法,分析了棉区3月下旬至4月下旬各旬平均气温和≥12 ℃初日的时空变化对棉花播期的影响.结果表明： 研究期间,天山北坡经济带 3月下旬、4月上、中、下旬平均气温分别以0.8、0.5、0.1和0.5 ℃·(10 a)^-1的倾向率呈增加趋势,但是≥12 ℃初日却以-0.5 d·(10 a)^-1的倾向率呈提前趋势.各气象要素均在20世纪90年代发生突变,突变年后3月下旬、4月上、中、下旬平均气温依次增加2.5、1.9、1.1和1.5 ℃,分别达到7.2、10.0、13.2和15.6 ℃.3月下旬至4月下旬各旬平均气温的高值区普遍位于天山北坡东部棉花主产区的乌苏市、沙湾县和玛纳斯县站点周围,而低值区基本在东部的乌鲁木齐市附近.≥12 ℃初日的空间分布具有地区差异性,研究期间,初日日序较早的区域由精河县向西扩展到棉花主产区玛纳斯县周围,而日序较晚的区域从乌鲁木齐市以南的大部区域缩小至乌鲁木齐市周围.随着突变年后≥12 ℃初日逐年提前,大部县市棉花适宜播期在4月22—28日,采用地膜播种可使适宜播期提前至4月15—21日.     

The effect of the meteorological factors on the Alnus pollen season in Lublin (Poland)

Alder pollen seasons and the effect of meteorological conditions on daily average pollen counts in the air of Lublin (Poland) were analysed. Alnus pollen grains reach very high concentrations in the atmosphere of this city during the early spring period and the parameters of pollen seasons were very different in the particular years studied. The pollen season lasted on average one month. The highest variation was observed for the peak value and the Seasonal Pollen Index (SPI). The pollen seasons, which started later, had shorter duration. Peak daily average pollen counts and SPI value were higher during the shorter seasons. Similarities in the stages of pollen seasons designated by the percentage method depended on the start date of the pollen season. Season parameters were mainly correlated with thermal conditions at the beginning of the year. Regression analysis was used to predict certain characteristics of the alder pollen season. The highest level of explanation of the variation in Alnus pollen season start and peak dates was obtained in the model using mean temperature in February. The obtained regression models may predict 82% of the variation in the pollen season start date, 73% of the variation in the duration, and 62% in the peak date.     

内蒙古锡林河流域羊草草原净初级生产力及其对全球气候变化的响应

利用CENTURY模型对内蒙古锡林河流域羊草草原在未来气候变化以及大气CO₂浓度增高条件下的年地上净初级生产力(annual aboveground net primary productivity,ANPP)动态进行了模拟研究.结果表明：CENTURY模型可以较好地预测ANPP的变化.进一步的情景模拟发现,虽然全球气候变化所引起的温度和降水改变、以及大气CO₂浓度升高都会影响ANPP,但降水是关键的影响因子.多个全球气候模型(GCM) 预测该地区未来降水量会减少,故可能导致其ANPP降低,但在以下气候变化情景下研究区ANPP可能会升高：1)CO₂浓度倍增,温度升高2 ℃,降水保持不变或增加10%～20%;2)CO₂浓度保持不变,温度升高2 ℃,降水增加20%.气候变化将对内蒙古锡林河流域羊草草原产生显著影响.     

Study onPlatanus hispanica Miller pollen content in the air of Seville, southern Spain

The work was carried out using a Cour trap that sampled the air of the city for 8 consecutive years (1987–1994). The pollen ofPlatanus hispanica is the fourth most abundant in the air of Seville (a mean of 11.05% of the total pollen collected). The variation throughout the years in the sum of weekly concentrations ofPlatanus hispanica pollen presents a certain biennial rhythm, in which years of high and low collection of pollen alternate. The starting day of the main pollination period (MPP) is negatively related with the mean of the mean temperatures for February (r=0.73,r ²=0.53,P=0.0398) and is earlier (at the beginning of March) when the mean temperature for February is high, and vice versa. The pattern of pollen variation inPlatanus hispanica remains constant through the years—pollen appears abruptly in high weekly concentrations (> 150 grains/m³) in March (sporadically at the beginning of April), with a week of maximum pollen emission (WMPE) in which more than 50% of the annual pollen is collected (in 6 of the 8 years), and a main pollination period (MPP) of 2 or 3 weeks (except in 1989 when it was 5 weeks). In every year (except 1989), weekly mean temperatures increased during the MPP, the duration of which depends on mean temperature and mean rainfall: mean temperatures > 16°C and absence of rainfall shorten the MPP, while lower temperatures and presence of rainfall lengthen it. The meteorological conditions most often found during the WMPE are mean temperatures > 15°C and rainfall absent or almost so.     

A comparative study of different temperature accumulation methods for predicting the start of the Quercus pollen season in Cordoba (South West Spain)

The aim of the present paper is to study the influence of air temperature on the start of Quercus pollination in Córdoba (Andalusia, Spain). Sixteen years of pollen counts were used. The start date of the pollen season in this period varied between 26^th February and 7^th April. Chilling requirements and heat accumulation were taken into account although no significant correlation between chilling hours and the start date was observed. Five different predictive methods based on heat accumulation were compared in this paper: 1) Number of days over a threshold; 2) Heat Units (accumulated daily mean temperature after deducting a base temperature); 3) Growing Degrees Days (Snyder 1988), as a measure of physiological growing time; 4) Accumulated maximum temperatures; and 5) Mean maximum temperature. Results indicated that the optimum base temperature for heat accumulation was 11 C^o. This threshold was used in the first three methods mentioned above. Good statistical results were obtained with the five methods, yielding high levels of explanation (p～99%). Nevertheless, the most accurate method appeared to be the Growing Degree Days (GDD^o) method, which indicated that a mean of 127.3 GDD^o must be accumulated from the end of the chilling period up to the beginning of the Quercus pollen season in Córdoba (South West Spain). Results were tested for predicting start dates in 1999 and 2000. The predicted dates were only one day after the actual dates.     

Influence of air temperature on the first flowering date of Prunus yedoensis Matsum

Climate change is expected to have a significant effect on the first flowering date (FFD) in plants flowering in early spring. Prunus yedoensis Matsum is a good model plant for analyzing this effect. In this study, we used a degree day model to analyze the effect of air temperatures on the FFDs of P. yedoensis at Wuhan University from a long-time series from 1951 to 2012. First, the starting date (=7 February) is determined according to the lowest correlation coefficient between the FFD and the daily average accumulated degree days (ADD). Second, the base temperature (=−1.2°C) is determined according to the lowest root mean square error (RMSE) between the observed and predicted FFDs based on the mean of 62-year ADDs. Finally, based on this combination of starting date and base temperature, the daily average ADD of every year was calculated. Performing a linear fit of the daily average ADD to year, we find that there is an increasing trend that indicates climate warming from a biological climatic indicator. In addition, we find that the minimum annual temperature also has a significant effect on the FFD of P. yedoensis using the generalized additive model. This study provides a method for analyzing the climate change on the FFD in plants'' flowering in early spring.     

应用花粉分析预报板栗产量的研究

 1994～1996年河北省迁安县蔡园乡大气中板栗花粉散布特征研究表明,不同年份板栗花期有早有晚,大气中的花粉浓度变化悬殊;大气中板栗花粉浓度受花期气温和盛花末期前降水影响较大,受日照影响较小;盛花期花粉浓度与板栗产量的相关系数为0.998～0.999;根据两年相关关系建立的预报模式对第三年产量进行了预报,预报期比收获期提前2个月,预报结果最大误差5.7％,最小误差1.13％;多数误差均低于4％;运用花粉分析预报板栗和其它果品及农作物产量是一种投入少、预报期早、预报精度高的预测方法。     

Statistical downscaling of monthly mean air temperature to the beginning of flowering of Galanthus nivalis L. in Northern Germany

 We have examined the relationship between phenological data and concurrent large-scale meterological data. As phenological data we have chosen the beginning of the flowering of Galanthus nivalis L. (flowering date) in Northern Germany, and as large-scale meteorological data we use monthly mean near-surface air temperatures for January, February and March. By means of canonical correlation analysis (CCA), a strong linear correlation between both sets of variables is identified. Twenty years of observed data are used to build the statistical model. To validate the derived relationship, the flowering date is downscaled from air temperature observations of an independent period. The statistical model is found to reproduce the observed flowering dates well, both in terms of variability as well as amplitude. Air temperature data from a general circulation model of climate change are used to estimate the flowering date in the case of increasing atmospheric carbon dioxide concentration. We found that at a time of doubled CO₂ concentration (expected by about 2035) G. nivalis L. in Northern Germany will flower ∼2 weeks and at the time of tripled CO₂ concentration (expected by about 2085) ∼4 weeks earlier than presently. Received: 7 August 1996 / Accepted: 27 November 1996