Frost Days Research Articles

Climate induced phenological shifts in pears – A crop of economic importance in the UK

Phenological advancements in flowering have been well documented in many food crop, ornamental, and native plant species. However, there is lack of information on how flowering times in crop species, especially fruit trees will react to future climate scenarios. This is important as changes in phenology could have significant implications for ecosystem services and function, biological interactions and agronomic outputs. Using 60 years of data from pear (Pyrus communis L.) orchards in two research organisations in Kent, UK we explored temporal changes in flowering phenology, identified the weather variables driving this change, and predicted how flowering times may be altered by 2080 with respect to future emissions scenarios. We show pear flowering (1990–2020) in the last 30 years has advanced 11.44 days compared to historical data (1960–1989). Furthermore, we highlight this advancement is apparent in all twelve pear cultivars and the four phenological stages analysed, including Conference, the most common UK pear cultivar. Our results indicate that this advancement in flowering began after 1982; that air temperature and frost days significantly impact pear flowering; and this change in flowering phenology is likely to continue under future climate scenarios. Four Representative Concentration Pathways from the UK Climate Projections 2018 report were used to model the impact of future climate, including low, medium, medium-high and high emission scenarios. Under all scenarios a phenological advancement in flowering time was predicted by 2080 with the greatest advancement in flowering time observed under the high emission scenario. Earlier flowering and budburst could result in phenological mismatches between plant and pollinators, alter agricultural spraying regimes, increase risk of frost exposure and exacerbate impacts of pest populations within an agroecosystem, thus it is vital to monitor advancements in flowering phenology.

IMPACT OF CLIMATE WARMING ON FLORISTIC DIVERSITY OF THE EAST EUROPEAN TUNDRA

IMPACT OF CLIMATE WARMING ON FLORISTIC DIVERSITY OF THE EAST EUROPEAN TUNDRA

Analysis of Extreme Temperature Variations on the Yunnan-Guizhou Plateau in Southwestern China over the Past 60 Years

Analysis of variations in 12 extreme temperature indices at 68 meteorological stations on the Yunnan-Guizhou Plateau (YGP) in southwestern China during 1960–2019 revealed widespread significant changes in all temperature indices. The temperature of the hottest days and coldest nights show significantly increasing trends, and the frequencies of the warm days and nights also present similar trends. The temperature of the coldest night has a significant and strong warming trend (0.38 °C/decade), whereas the frequency of frost days shows the fastest decrease (1.5 days/decade). Increases in the summer days are statistically significant, while a decreasing trend for the diurnal temperature range is not significant. Furthermore, there were significant differences in the changes of temperature indices between 1960–1989 and 1990–2019. Most parts of the YGP underwent significant warning, manifesting that the mountainous regions are relatively sensitive and vulnerable to climate change. The correlation coefficients between the temperature indices and various geographical factors (latitude, longitude, and height) reflect the complexity of regional temperature variability and indicate enhanced sensitivity of extreme temperatures to geographical factors on the YGP. It was also found that extreme temperatures generally had weaker correlations with the El Nino-Southern Oscillation, North Pacific Index, Southern Oscillation Index, North Atlantic Oscillation, and East Asian Summer Monsoon Index than with the South Asian summer monsoon index, Nino4 indices and Arctic Oscillation, and there were more insignificant correlations. Regional trends of the extreme temperature indices reflect the non-uniform temperature change over the YGP, which is due to the complex interaction between atmospheric circulation patterns and local topography. The results of this study have important practical significance for mitigating the adverse effects of extreme climatic changes, in particular for the YGP with its typical karst geomorphology and fragile ecological environment.

Evaluation of Walnut Tree Flowering and Frost Occurrence Probability During 1961-2012

Strength and direction of the potential effect of climate change on walnuts is regionally specific (Gauthier and Jacobs, 2011) as climate change will probably affect the spatial distribution of the walnut. This paper evaluated the long-term phenological series (1961-2012) of the beginning of flowering, end of flowering and duration of flowering in walnut tree (Juglans regia) at two phenological stations located in different geographical locations of the Czech Republic but in the same climatic conditions (warm region). Phenological stages were analyzed in relation to growing degree days and to spring frosts occurrence. Onset of the beginning and end of flowering occurred earlier at VelkÊ Pavlovice station (-2.1 and -1.3 days), and conversely occurred later at Doksany station (+1.8 and +1.0). Period of flowering shortened at Doksany station (-0.8 day) and prolonged at VelkÊ Pavlovice station (+1.2 day). The occurrence of days with minimum air temperature < 0 °C during walnut tree flowering was more frequent at Doksany station (in total, 29 days) with absolute minimum value -5.5 °C. At VelkÊ Pavlovice station 5 days with minimum air temperature below 0 °C were found during examined period with absolute minimum value -3.8 °C. The negative trend in number of frost days occurrence during flowering period was found at both stations. Pearson correlation coefficient between phenophase onset (and flowering period) and sums of growing degree days was stronger at VelkÊ Pavlovice station, and the highest value was between period of flowering and temperature sums (0.782). The results confirmed our hypothesis of changes in phenophase onsets and duration of flowering including spring frosts occurrence according to west-east gradient (maritime climate-continental climate).

Optimal Strategy on Radiation Estimation for Calculating Universal Thermal Climate Index in Tourism Cities of China.

The Universal Thermal Climate Index (UTCI) is believed to be a very powerful tool for providing information on human thermal perception in the domain of public health, but the solar radiation as an input variable is difficult to access. Thus, this study aimed to explore the optimal strategy on estimation of solar radiation to increase the accuracy in UTCI calculation, and to identify the spatial and temporal variation in UTCI over China. With daily meteorological data collected in 35 tourism cities in China from 1961 to 2020, two sunshine-based Angstrom and Ogelman models, and two temperature-based Bristow and Hargreaves models, together with neural network and support vector machine-learning methods, were tested against radiation measurements. The results indicated that temperature-based models performed the worst with the lowest NSE and highest RMSE. The machine-learning methods performed better in calibration, but the predictive ability decreased significantly in validation due to big data requirements. In contrast, the sunshine-based Angstrom model performed best with high NSE (Nash–Sutcliffe Efficiency) of 0.84 and low RMSE (Root Mean Square Error) of 35.4 J/m2 s in validation, which resulted in a small RMSE of about 1.2 °C in UTCI calculation. Thus, Angstrom model was selected as the optimal strategy on radiation estimation for UTCI calculation over China. The spatial distribution of UTCI showed that days under no thermal stress were high in tourism cities in central China within a range from 135 to 225 days, while the largest values occurred in Kunming and Lijiang in southwest China. In addition, days under no thermal stress during a year have decreased in most tourism cities of China, which could be attributed to the asymmetric changes in significant decrease in frost days and slightly increase in hot days. However, days under no thermal stress in summer time have indeed decreased, accompanying with increasing days under strong stress, especially in the developed regions such as Yangze River Delta and Zhujiang River Delta. Based on the study, we conclude that UTCI can successfully depict the overall spatial distribution and temporal change of the thermal environments in the tourism cities over China, and can be recommend as an efficient index in the operational services for assessing and predicting thermal perception for public health. However, extreme cold and heat stress in the tourism cities of China were not revealed by UTCI due to mismatch of the daily UTCI with category at hourly scale, which makes it an urgent task to redefine category at daily scale in the next research work.

Long-term trends in daily extreme air temperature indices in Ireland from 1885 to 2018

Long-term instrumental series are crucial to analyse extreme air temperature indices and to examine modern climate warming within a historical context. This research provides the first assessment in Ireland of the frequency, duration, intensity and geographical distribution of the daily extreme air temperature indices recommended by the ETCCDI (Expert Team on Climate Change Detection and Indices) and based on long-term rescued, quality-controlled and homogenised data. Prior analysis of air temperature indices in Ireland had focused on the period since the second half of the 20th century, where digital data were readily available. Earlier estimations of long-term air temperature trends in Ireland focused on non-homogenised data from a small network of stations. For this research, 11 long-term (1885–2018) maximum and minimum air temperature series were analysed to assess seasonal and annual trends and construct extreme air temperature indices in Ireland. The non-parametric Mann-Kendall test was employed to test the statistical significance of the maximum and minimum air temperatures and indices trends (p < 0.05). Significant increasing trends were assessed in the seasonal and annual maximum and minimum air temperature series in Ireland, with greater increases in the spring and autumn seasons. Significant increasing trends were determined in the warm days (+6.8 days), warm nights (+7.5 nights), warm spell duration index (+3.9 days), growing season length (+22 days), coldest night (+2.7 °C) and coldest day (+1.5 °C) in the period 1885–2018 in Ireland. In the same period, significant decreasing trends were identified in the cold days (−9.3 days), cold nights (−7 nights), frost days (−13.7 days), cold spell duration index (−6.9 days) and diurnal air temperature range (−0.1 °C) in Ireland. The results follow global patterns presented in the Six Assessment Report of the Intergovernmental Panel on Climate Change. The findings of this research will be crucial to assist stakeholders and policymakers in defining climate action, adaptation and mitigation plans in response to shifting trends in air temperature extremes.

High-resolution Projection Dataset of Agroclimatic Indicators over Central Asia

To understand the potential impacts of projected climate change on the vulnerable agriculture in Central Asia (CA), six agroclimatic indicators are calculated based on the 9-km-resolution dynamical downscaled results of three different global climate models from Phase 5 of the Coupled Model Intercomparison Project (CMIP5), and their changes in the near-term future (2031–50) are assessed relative to the reference period (1986–2005). The quantile mapping (QM) method is applied to correct the model data before calculating the indicators. Results show the QM method largely reduces the biases in all the indicators. Growing season length (GSL, day), summer days (SU, day), warm spell duration index (WSDI, day), and tropical nights (TR, day) are projected to significantly increase over CA, and frost days (FD, day) are projected to decrease. However, changes in biologically effective degree days (BEDD, °C) are spatially heterogeneous. The high-resolution projection dataset of agroclimatic indicators over CA can serve as a scientific basis for assessing the future risks to local agriculture from climate change and will be beneficial in planning adaption and mitigation actions for food security in this region.

Quantifying the Trends and Variations in the Frost-Free Period and the Number of Frost Days across China under Climate Change Using ERA5-Land Reanalysis Dataset

Understanding the spatio-temporal variations in the frost-free period (FFP) and the number of frost days (FD) is beneficial to reduce the harmful effects of climate change on agricultural production and enhancing agricultural adaptation. However, the spatio-temporal variations in FFP and FD and their response to climate change remain unclear across China. To investigate the impact of climate change on FFP and FD, the trends and variations in FFP and FD across China from 1950 to 2020 were quantified using ERA5-Land, a reanalysis dataset with high spatial and temporal resolution. The results showed that ERA5-Land has good applicability in quantifying the trends and variations in FFP and FD across China under climate change. The spatial distribution of multi-year average FFP and FD across China showed significant latitudinal zonality and altitude dependence, i.e., FFP decreased with increasing latitude and altitude, while FD increased with increasing latitude and altitude. As a result of climate warming across China, the FFP showed an increasing trend with an increase rate of 1.25 d/10a and the maximum increasing rate of FFP in the individual region was 6.2 d/10a, while the FD showed a decreasing trend with a decrease rate of 1.41 d/10a and the maximum decreasing rate of FD in the individual region was −6.7 d/10a. Among the five major climate zones in China, the subtropical monsoon climate zone (SUMZ) with the greatest increasing rate of 1.73 d/10a in FFP, while the temperate monsoon climate zone (TEMZ) with the greatest decreasing rate of −1.72 d/10a in FD. In addition, the coefficient of variation (Cv) of FFP showed greater variability at higher altitudes, while the Cv of FD showed greater variability at lower latitudes in southern China. Without considering the adaptation to temperature of crops, a general increase in FFP and a general decrease in FD were both beneficial to agricultural production in terms of FFP and FD promoting a longer growing period and reducing frost damage on crops. This study provides a comprehensive understanding of the trends and variations in FFP and FD under climate change, which is of great scientific significance for the adjustment of the agricultural production layout to adapt to climate change in China.

Multi-Model Ensemble Projections of Winter Extreme Temperature Events on the Chinese Mainland.

Based on the downscaling data of multi-model ensembles of 26 global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 6, this study calculated the extreme climate indices defined by the Expert Team on Climate Change Detection and Indices and the warm winter extreme grade indices to explore winter climate response on the Chinese mainland under different shared socioeconomic pathways (SSPs) and representative concentration pathways. The results showed that the temperature in winter increased overall, with the highest temperature increases of 0.31 °C/10a (Celsius per decade) (SSP245) and 0.51 °C/10a (SSP585) and the lowest temperature increases of 0.30 °C/10a (SSP245) and 0.49 °C/10a (SSP585). Warm-related extreme weather events such as warm days and warm spell duration indices showed an increasing trend, whereas cold-related extreme weather events such as cold spell duration indices, cold nights, ice days, and frost days showed a decreasing trend. On the regional scale, the maximum temperature increased by more than 2 °C/10a (SSP245) and 0.4 °C/10a (SSP585), except in South China, and the minimum temperature increased faster in Qinghai-Tibet and Northeast China compared to elsewhere on the Chinese mainland. Compared with that under SSP585, the frequency and intensity of warm winters in the latter half of the 21st century were lower under SSP245. At the end of the 21st century, under the SSP245 scenario, warm winter frequency in most regions will be reduced to below 60%, but under the SSP585 scenario, it will be more than 80%. Population exposures all showed a downward trend, mainly due to the reduction of warm winter events and the decline of the population under the SSP245 and SSP585 scenarios, respectively. If the greenhouse gas emission path is controlled in the SSP245 scenario, the population exposure risk in warm winters can be decreased by 25.87%. This study observed a consistent warming trend on the Chinese mainland under all SSPs in the 21st century and found that stricter emission reduction policies can effectively decrease the population exposure to warm winters.

Bias‐adjustment of high‐resolution temperature CORDEX data over the Carpathian region: Expected changes including the number of summer and frost days

AbstractClimate model simulations' outputs are prone to biases compared to observations; furthermore, climate projections can be very different in modelling future temperature characteristics. One possible solution for reducing uncertainty and eliminating possible systematic errors within climate projections is the bias‐adjustment of the raw climate model data. We used the quantile mapping method for bias‐adjustment of a mini ensemble consisting of 8‐member high‐resolution (0.11°) regional climate model simulations provided by the CORDEX community. As the method requires a reliable observational dataset serving as reference data, we used the quality controlled and homogenized observational dataset: CARPATCLIM. Quantile mapping bias‐adjustment technique was applied on the following variables: daily mean, minimum and maximum temperature. We analysed changes in mean temperature characteristics and of climate indices for future periods of 2021–2050 and 2070–2099 with respect to the reference period 1976–2005 for the Carpathian Region. The selected climate indices are based on minimum (frost days, FD) and maximum daily temperature data (summer days, SU). Our bias‐adjusted RCM results suggest a similar degree of mean temperature change as the raw RCMs' data. Bias‐adjusted and raw RCM data project a remarkable annual temperature increase on average under the RCP8.5 scenario (1.4°C and 3.9°C by 2021–2050 and 2070–2099, respectively). The highest temperature increase is likely to occur in summer: it is 4.3°C on average by the end of the 21st century. More pronounced differences were found for the projected changes of the number of summer and frost days based on the bias‐adjusted and the raw RCM data. Our results draw attention to the fact that bias‐adjusted RCM data are crucial for the provision of regional climate change impact and adaptation studies for the Carpathian Region.

50 years of estuarine cockles (Cerastoderma edule L.): Shifting cohorts, dwindling sizes and the impact of improved wastewater treatment

Bivalve populations are prone to change due to sudden or gradual alteration in the natural environment and anthropogenic interference. Fisheries and environmental managers are therefore interested in long-term trends and disentangling natural and human influences, assisting them in conservation efforts and the management of bivalve stocks. Here, 64 monitoring reports covering a 50-year period from 1958 to 2009 of cockles Cerastoderma edule (Linnaeus, 1758) in South Wales, UK, were scrutinised for data on recruitment, growth and mortality. Changes in these population parameters were related to the modernisation of wastewater treatment in 1997, weather and climate variables (temperature, sun hours, air frost days, NAO) and numbers of cockles in the estuary. Recruitment as well as mortalities were high during the first and last decade of the study, and variation was significantly linked to the total number of cockles in the population. Cockle sizes of all cohorts as well as overall biomass declined in the late 1990s. Modernisation of wastewater treatment was significantly related with the downward trend, suggesting that the changed nutrient regime in the estuary may have resulted in reduced food provision for cockles. The average size of newly settled cockles was related to their mortality: the smaller the recruits the higher their mortality. The study indicated a link between the change in wastewater treatment in 1997 and diminishing sizes of cockle recruits that shortened their life span. Survey methods were profoundly changed after 2009, and it is recommended to develop conversion factors between the pre- and post-2009 survey methods. This would allow an extension of the timeline and deeper insight into the long-term impact of the change in wastewater treatment and the recovery of the cockle population.

In-depth field survey of a rockslide detachment surface to recognise the occurrence of gravity-induced cracking

This work describes field evidence of gravity-induced cracking that has been identified on the failure scar of a small rockslide (volume = 6–7 m3) that occurred in March 2004 in the Rosandra Valley near the town of Trieste (north-eastern Italy). This shallow rock slope failure involved a limestone slope that was re-profiled through blasting about 135 years ago for the construction of an old railway, which has now been reconverted into a cycle path. Field observations ascertained that the slope failure was characterised by a cascading rupture process in which adjacent blocks collapsed in rapid sequence as a result of the progressive breakage of a number of rock bridges (domino-like collapse), thus highlighting a progressive failure mechanism. The rock bridges were localised in eccentric positions on lateral and rear release planes and failed in tension as a result of combined tensile and bending loading conditions (tensile strength of intact rock = 5 ± 2 MPa). The rockslide was triggered by cyclic loading related to freeze-thaw (ice jacking) that occurred over some consecutive days of daily snowmelt and nocturnal frost. The recognition of newly formed fractures also proves the current progressive development of 3D rupture surfaces of some unstable blocks susceptible to failure. This study provides innovative content to detect gravity-induced cracking in the field, which is an important precursory sign relating to the progressive failure of rock slopes. Gravity-induced cracks can be distinguished from pre-existing discontinuities for their more irregular profile (zigzag pattern), rougher surface, lower persistence and potentially different orientation. This study also provides some new insights into the step-path failure process of steep rock slopes. The mechanical process of initiation, growing and coalescence of gravity-induced fractures is strongly time- and stress-dependent. In the absence of external changing factors that profoundly modify the acting stress state (for instance, engineering countermeasures), progressive failure is a dynamic and irreversible process. For excavated slopes, the creation of a new rock face may abruptly provide the kinematic freedom of potentially unstable blocks, thus determining a very quick stress redistribution. If the mechanical system is not able to redistribute the stress on resisting stiff parts without overcoming the intact rock strength, gravity-induced cracking initiates and propagates until reaching slope collapse within times that are much shorter (from hours to 100–200 years) compared to natural rock slopes subjected to long-lasting geological processes (from 1000 to 2000 up to 10,000–20,000 years).

Geo-Spatial Characteristics of 567 Places of Tick-Borne Encephalitis Infection in Southern Germany, 2018-2020.

Tick-borne encephalitis (TBE) is a growing public health problem with increasing incidence and expanding risk areas. Improved prevention requires better understanding of the spatial distribution and ecological determinants of TBE transmission. However, a TBE risk map at sub-district level is still missing for Germany. We investigated the distribution and geo-spatial characteristics of 567 self-reported places of probable TBE infection (POI) from 359 cases notified in 2018–2020 in the study area of Bavaria and Baden-Wuerttemberg, compared to 41 confirmed TBE foci and 1701 random comparator places. We built an ecological niche model to interpolate TBE risk to the entire study area. POI were distributed heterogeneously at sub-district level, as predicted probabilities varied markedly across regions (range 0–93%). POI were spatially associated with abiotic, biotic, and anthropogenic geo-spatial characteristics, including summer precipitation, population density, and annual frost days. The model performed with 69% sensitivity and 63% specificity at an optimised probability threshold (0.28) and an area under the curve of 0.73. We observed high predictive probabilities in small-scale areas, consistent with the known circulation of the TBE virus in spatially restricted microfoci. Supported by further field work, our findings may help identify new TBE foci. Our fine-grained risk map could supplement targeted prevention in risk areas.

Observed trends in extreme temperature events over northern part of the Korean Peninsula during 1960–2019 and a comparative overview

The aim of the study is to estimate the trend in extreme temperature events in the northern part of Korean Peninsula during 1960–2019, as well as to conduct a comparison experiment with the other representative results, all trends are examined based on quality-controlled daily maximum and minimum temperature data from 37 weather stations. Results are as follows. First, frost days (FD0) and ice days (ID0) showed a clear downward trend, whereas warm days (SU25) and warm nights (TR20) experienced an obvious uptrend, with SU25 exceeding TR20, while very hot days (TX35), extreme hot days (TX37) and very extreme hot days (TX39) showed abrupt increasing trends, especially twice in TX37 and six times in TX39, respectively. Both of cold nights (TN10) and cold days (TX10) decreased by about −0.7d/decade, hot nights (TN90) and hot days (TX90) increased by 0.6d and 1.0d/decade, respectively. Second, as compared with to representative results in global by the relevant reference and study period, all uptrends in TR20, SU25 and annual maximum of daily maximum temperature (TXx) were significantly higher than those in most regions in China, SU25 and TR20 were mostly greater than those in most regions, except for some regions in Europe. In particular, TR20 upward trend exceeded any other region's results. Meanwhile, TX10 and TNn experienced stronger downward and upward tendencies than those in whole China respectively. Especially, TNn experienced the strongest upward trend in comparing with the others. Overall, results revealed hot weather frequency and nighttime warm events over the study area have experienced a larger increasing trend than those in global land.

Temperature extremes and circulation types in the Czech Republic, 1961–2020

AbstractThis paper presents the characteristics of extreme temperatures in the Czech Republic, as calculated from homogenized series of daily maximum (TMAX) and daily minimum (TMIN) temperatures recorded by 133 climatological stations throughout the territory in the 1961–2020 period. In general, statistically significant increasing linear trends were recognized in series of absolute TMAX, absolute TMIN, numbers of summer days, tropical days, days with tropical nights, heat‐wave, and warm‐anomaly days. Significant decreasing linear trends appeared in series of numbers of frost days, ice days, cold‐wave, and cold‐anomaly days. Objective classification of circulation types demonstrated the importance of anticyclonic types (especially those with warm airflow from the southern quadrant) and an unclassified type in the development of summer hot extremes, while winter cold extremes were linked to cold (north‐)easterly advection. Significant changes in the frequency of certain circulation types emerged, as well as an increasing number of anticyclonic types conducive to hot extremes, a trend that contributed to their more frequent occurrence in recent decades. Existing trends in temperatures were complemented by spatiotemporal analysis of extreme temperatures, the characteristics of extremes and the circulation types in the two “normal” periods of 1961–1990 and 1991–2020. These exhibited significant differences in means and variances. The results obtained are also discussed in a broader context.

Climate change projections for Greece in the 21st century from high-resolution EURO-CORDEX RCM simulations

We present an updated assessment of projected climate change over Greece in the near future and at the end of the 21st century, focusing on near surface temperature, precipitation, and related heat (Hot Days and Tropical Nights), cold (Frost Days), and drought (Consecutive Dry Days) climate indices. The analysis is based on an ensemble of 11 high-resolution EURO-CORDEX regional climate model (RCM) simulations covering the historical period 1950–2005 and the future period 2006–2100 under the influence of a strong, a moderate, and a no mitigation Representative Concentration Pathway (RCP2.6, RCP4.5 and RCP8.5). The statistical robustness of climate change signal is also assessed. Our results strongly point towards a warmer future for Greece under all the examined RCPs. Under RCP8.5, annual near surface temperature is projected to increase on average by 1.6 °C in the near future and 4.3 °C at the end of the century. As a consequence of warming, the number of hot days and tropical nights in a year is projected to increase significantly and the number of frost days to decrease. In addition, the future will be possibly drier. Statistically robust results for precipitation changes are found only for the end-of-the-century period under RCP8.5. Precipitation is generally projected to decrease under RCP8.5 by −16% and the number of consecutive dry days in a year to increase by 15.4 days (30%) at the end of the century.

Impact of the dynamic vegetation on climate extremes during the wheat growing period over China

Extreme temperature and precipitation indices have important implications for the crop growing season. Whether a coupled regional model with carbon–nitrogen cycling (CN) and vegetation dynamics (DV) can better represent these indices during the growing season compared with a model without these modules remains unknown. This study evaluates the performance of extreme indices in three wheat planting regions (including northeast spring wheat, north winter wheat and south winter wheat regions) over China in the period of 1990–2009 using the Regional Climate Model (RegCM) coupled with the Community Land Model (CLM), which include CN and DV. The results show that relative to the RegCM-CLM, both the RegCM-CLM-CN and RegCM-CLM-CN-DV perform better in simulating summer days (SU), consecutive dry days (CDD), consecutive wet days (CWD), and the interannual variability in all the extreme indices in the three regions but produce larger biases on frost days (FD). The trends of extreme indices in the high-impact risk region of wheat are also better captured by the RegCM-CLM with CN or CN-DV compared with the model without these modules. In the northeast spring wheat and southern winter wheat regions, the greater cold bias of mean daily minimum temperature between RegCM-CLM-CN-DV and RegCM-CLM is consistent with the leaf area index (LAI) difference, which may increase evaporative cooling and thus increasing FD biases. Overestimation of the LAI may have a weaker effect than the surface albedo on the mean daily maximum temperature, leading to decreased SU biases in RegCM-CLM-CN-DV relative to RegCM-CLM.

Environmental drivers of autumn migration departure decisions in midcontinental mallards

BackgroundThe timing of autumn migration in ducks is influenced by a range of environmental conditions that may elicit individual experiences and responses from individual birds, yet most studies have investigated relationships at the population level. We used data from individual satellite-tracked mallards (Anas platyrhynchos) to model the timing and environmental drivers of autumn migration movements at a continental scale.MethodsWe combined two sets of location records (2004–2007 and 2010–2011) from satellite-tracked mallards during autumn migration in the Mississippi Flyway, and identified records that indicated the start of long-range (≥ 30 km) southward movements during the migration period. We modeled selection of departure date by individual mallards using a discrete choice model accounting for heterogeneity in individual preferences. We developed candidate models to predict the departure date, conditional on daily mean environmental covariates (i.e. temperature, snow and ice cover, wind conditions, precipitation, cloud cover, and pressure) at a 32 × 32 km resolution. We ranked model performance with the Bayesian Information Criterion.ResultsDeparture was best predicted (60% accuracy) by a “winter conditions” model containing temperature, and depth and duration of snow cover. Models conditional on wind speed, precipitation, pressure variation, and cloud cover received lower support. Number of days of snow cover, recently experienced snow cover (snow days) and current snow cover had the strongest positive effect on departure likelihood, followed by number of experienced days of freezing temperature (frost days) and current low temperature. Distributions of dominant drivers and of correct vs incorrect prediction along the movement tracks indicate that these responses applied throughout the latitudinal range of migration. Among recorded departures, most were driven by snow days (65%) followed by current temperature (30%).ConclusionsOur results indicate that among the tested environmental parameters, the dominant environmental driver of departure decision in autumn-migrating mallards was the onset of snow conditions, and secondarily the onset of temperatures close to, or below, the freezing point. Mallards are likely to relocate southwards quickly when faced with snowy conditions, and could use declining temperatures as a more graduated early cue for departure. Our findings provide further insights into the functional response of mallards to weather factors during the migration period that ultimately determine seasonal distributions.

Using hybrid modelling to predict basal area and evaluate effects of climate change on growth of Norway spruce and Scots pine stands

ABSTRACT When modelling forest growth, capturing the effects of climate change is needed for reliable long-term predictions and management choices. This remains a challenge because commonly used mensurational forest growth and yield models, relying on inventory data, cannot account for climate change effects. We developed hybrid physiological/mensurational basal area growth and yield models, which combine physiological response to climatic conditions and empirical relations. We included climate and site effects by replacing time with light sums of photosynthetically active radiation and modifying the latter with monthly soil water, vapour pressure deficit, temperature, and frost days. When parameterised with permanent sample plot data for Scots pine and Norway spruce across Sweden, the hybrid models could reproduce observations well, although with no increase in precision compared with time-based mensurational models. When considering different climate scenarios, a significant impact on productivity from climate change emerged. For example, a 2 °C warming enhanced Scots pine production by up to 14% in regions where temperatures were originally cooler and soil water deficit was low (i.e. northwest Sweden), but depressed it, up to 9%, elsewhere. Hence, climate-sensitive models that take local variations into account are necessary for accurate predictions and sustainable forest management.

Occurrence of crop pests and diseases has largely increased in China since 1970.

Crop pests and diseases (CPDs) are emerging threats to global food security, but trends in the occurrence of pests and diseases remain largely unknown due to the lack of observations for major crop producers. Here, on the basis of a unique historical dataset with more than 5,500 statistical records, we found an increased occurrence of CPDs in every province of China, with the national average rate of CPD occurrence increasing by a factor of four (from 53% to 218%) during 1970-2016. Historical climate change is responsible for more than one-fifth of the observed increment of CPD occurrence (22% ± 17%), ranging from 2% to 79% in different provinces. Among the climatic factors considered, warmer nighttime temperatures contribute most to the increasing occurrence of CPDs (11% ± 9%). Projections of future CPDs show that at the end of this century, climate change will lead to an increase in CPD occurrence by 243% ± 110% under a low-emissions scenario (SSP126) and 460% ± 213% under a high-emissions scenario (SSP585), with the magnitude largely dependent on the impacts of warmer nighttime temperatures and decreasing frost days. This observation-based evidence highlights the urgent need to accurately account for the increasing risk of CPDs in mitigating the impacts of climate change on food production.