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Svalbard, located between 76°30'N and 80°50'N, is among the regions in the world with the most rapid temperature increase. We processed a cloud-free time-series of MODIS-NDVI for Svalbard. The dataset is interpolated to daily data during the 2000-2022 period with 232 m pixel resolution. The onset of growth, with a clear phenological definition, has been mapped each year. Then the integrated NDVI from the onset (O) of growth each year to the time of average (2000-2022) peak (P) of growth (OP NDVI) have been calculated. OP NDVI has previously shown high correlation with field-based tundra productivity. Daily mean temperature data from 11 meteorological stations are compared with the NDVI data. The OP NDVI values show very high and significant correlation with growing degree days computed from onset to time of peak of growth for all the meteorological stations used. On average for the entire Svalbard, the year 2016 first had the highest greening (OP NDVI values) recorded since the year 2000, then the greening in 2018 surpassed 2016, then 2020 surpassed 2018, and finally 2022 was the year with the overall highest greening by far for the whole 2000-2022 period. This shows a rapid recent greening of Svalbard very strongly linked to temperature increase, although there are regional differences: the eastern parts of Svalbard show the largest variability between years, most likely due to variability in the timing of sea-ice break-up in adjacent areas. Finally, we find that areas dominated by manured moss-tundra in the polar desert zone require new methodologies, as moss does not share the seasonal NDVI dynamics of tundra communities.

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The study explores the feasibility of adapting the EOStat crop monitoring system, originally designed for monitoring crop growth conditions in Poland, to fulfill the requirements of a similar system in Ukraine. The system utilizes satellite data and agrometeorological information provided by the Copernicus program, which offers these resources free of charge. To predict crop yields, the system uses several factors, such as vegetation condition indices obtained from Sentinel-3 Ocean and Land Color Instrument (OLCI) optical and Sea and Land Surface Temperature Radiometer (SLSTR). It also incorporates climate information, including air temperature, total precipitation, surface radiation, and soil moisture. To identify the best predictors for each administrative unit, the study utilizes a recursive feature elimination method and employs the Extreme Gradient Boosting regressor, a machine learning algorithm, to forecast crop yields. The analysis indicates a noticeable decrease in crop losses in 2022 in certain regions of Ukraine, compared to the previous year (2021) and the 5-year average (2017-2021), specifically for winter crops and maize. Considering the reduction in yield, it is estimated that the decline in production of winter crops in 2022 was up to 20%, while for maize, it was up to 50% compared to the decline in production.

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Global warming has been implicated in widespread demographic changes in Atlantic salmon Salmo salar populations, but projections of life-history responses to future climate change are lacking. Here, we first exploit multiple decades of climate and biological data from the Burrishoole catchment in the west of Ireland to model statistical relationships between atmospheric variables, water temperature, and freshwater growth of juvenile Atlantic salmon. We then use this information to project potential changes in juvenile growth and life-history scheduling under three shared socioeconomic pathway and representative concentration pathway scenarios from 1961 to 2100, based on an ensemble of five climate models. Historical water temperatures were well predicted with a recurrent neural network, using observation-based atmospheric forcing data. Length-at-age was in turn also well predicted by cumulative growing degree days calculated from these water temperatures. Most juveniles in the Burrishoole population migrated to sea as 2-year-old smolts, but our future projections indicate that the system should start producing a greater proportion of 1-year-old smolts, as increasingly more juveniles cross a size-based threshold in their first summer for smoltification the following spring. Those failing to cross the size-based threshold will instead become 2-year-old smolts, but at a larger length relative to 2-year-old smolts observed currently, owing to greater overall freshwater growth opportunity. These changes in age- and size-at-seaward migration could have cascading effects on age- and size-at-maturity and reproductive output. Consequently, the seemingly small changes that our results demonstrate have the potential to cause significant shifts in population dynamics over the full life cycle. This workflow is highly applicable across the range of the Atlantic salmon, as well as to other anadromous species, as it uses openly accessible climate data and a length-at-age model with minimal input requirements, fostering improved general understanding of phenotypic and demographic responses to climate change and management implications.

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BACKGROUND AND AIMS: Changes in kelp abundances on regional scales have been highly variable over the past half-century owing to strong effects of local and regional drivers. Here, we assess patterns and dominant environmental variables causing spatial and interspecific variability in kelp persistence and resilience to change in Nova Scotia over the past 40 years. METHODS: We conducted a survey of macrophyte abundance at 251 sites spanning the Atlantic coast of Nova Scotia from 2019 to 2022. We use this dataset to describe spatial variability in kelp species abundances, compare species occurrences to surveys conducted in 1982 and assess changes in kelp abundance over the past 22 years. We then relate spatial and temporal patterns in abundance and resilience to environmental metrics. KEY RESULTS: Our results show losses of sea urchins and the cold-tolerant kelp species Alaria esculenta, Saccorhiza dermatodea and Agarum clathratum in Nova Scotia since 1982 in favour of the more warm-tolerant kelps Saccharina latissima and Laminaria digitata. Kelp abundances have increased slightly since 2000, and Saccharina latissima and L. digitata are widely abundant in the region today. The highest kelp cover occurs on wave-exposed shores and at sites where temperatures have remained below thresholds for growth (21 °C) and mortality (23 °C). Moreover, kelp has recovered from turf dominance following losses at some sites during a warm period from 2010 to 2012. CONCLUSIONS: Our results indicate that dramatic changes in kelp community composition and a loss of sea urchin herbivory as a dominant driver of change in the system have occurred in Nova Scotia over the past 40 years. However, a broad-scale shift to turf-dominance has not occurred, as predicted, and our results suggest that resilience and persistence are still a feature of kelp forests in the region despite rapid warming over the past several decades.

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Corn seedling emergence is a critical factor affecting crop yields. Accurately predicting emergence is crucial for precise crop growth and development simulation in process-based crop models. While various experimental studies have investigated the relationship between corn seedling emergence and temperature, there remains a scarcity of studies focused on newer corn hybrids. In the present study, statistical models (linear and quadratic functional relationships) are developed based on the seedling emergence of ten current corn hybrids, considering soil and air temperatures as influencing factors. The data used for model development are obtained from controlled soil plant atmospheric research chamber experiments focused on corn seedling emergence at five different temperatures. Upon evaluating the developed models, the quadratic model relating the air temperature with time to emergence was found more accurate for all corn hybrids (coefficient of determination (R2): 0.97, root mean square error (RMSE): 0.42 day) followed by the quadratic model based on soil temperature (R2: 0.96, RMSE: 1.42 days), linear model based on air (R2: 0.94, RMSE: 0.53 day) and soil temperature (R2: 0.94, RMSE: 0.70 day). A growing degree day (GDD)-based model was also developed for the newer hybrids. When comparing the developed GDD-based model with the existing GDD models (based on old hybrids), it was observed that the GDD required for emergence was 16% higher than the GDD used in the current models. This showed that the existing GDD-based models need to be revisited when adopted for newer hybrids and adapted to corn crop simulation models. The developed seedling emergence model, integrated into a process-based corn crop simulation model, can benefit farmers and researchers in corn crop management. It can aid in optimizing planting schedules, supporting management decisions, and predicting corn crop growth, development, and it yields more accurately.

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In recent years, the avocado has been one of the most dynamic fruits in the world market. In particular, cv. Hass stands out due to its productivity, nutritional quality, and acceptance. Under tropical conditions, weather elements, especially air temperature, and precipitation, affect the productivity and quality of cv. Hass. However, in tropical environments, many relationships between weather and phenological aspects of this cultivar are still unknown. Given this situation, our aim was to identify the variation and degree of association between the phenology of avocado cv. Hass and thermal time (TT) under low-latitude conditions. Eight commercial fields planted with cv. Hass grafted onto Antillean genotypes, located in an altitudinal transect between 1,700 and 2,500 m, were evaluated. The evaluation was carried out for three years and was focused on determining the differences in avocado phenological patterns associated with different environmental variables monitored by weather stations at each location. Air temperature data were used to calculate the base temperature (BT) using different methods for all phenological stages. Later the TT was determined for each stage and all locations. The results show that the duration of each phenological stage varies as a function of elevation (air temperature) and that the phenological stages overlap at the regional, crop field, and plant levels at different periods of the year, generating a high phenological variability but with specific patterns associated with temperature and precipitation. The BT for each phenological stage varied between 0.3 and 7.5 °C, and TT was found to vary depending on the method of calculation. Our work suggests that the generalization of a BT of 10 °C is not applicable for avocado cv. Hass crops under tropical conditions, specifically in the case of Colombia. Detailed studies of phenological relationships with respect to climatic variables will allow a better approximation of the productive behavior of avocado cv. Hass.

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The Rocky Mountain Biological Laboratory (RMBL; Colorado, USA) is the site for many research projects spanning decades, taxa, and research fields from ecology to evolutionary biology to hydrology and beyond. Climate is the focus of much of this work and provides important context for the rest. There are five major sources of data on climate in the RMBL vicinity, each with unique variables, formats, and temporal coverage. These data sources include (1) RMBL resident billy barr, (2) the National Oceanic and Atmospheric Administration (NOAA), (3) the United States Geological Survey (USGS), (4) the United States Department of Agriculture (USDA), and (5) Oregon State University's PRISM Climate Group. Both the NOAA and the USGS have automated meteorological stations in Crested Butte, CO, ~10 km from the RMBL, while the USDA has an automated meteorological station on Snodgrass Mountain, ~2.5 km from the RMBL. Each of these data sets has unique spatial and temporal coverage and formats. Despite the wealth of work on climate-related questions using data from the RMBL, previous researchers have each had to access and format their own climate records, make decisions about handling missing data, and recreate data summaries. Here we provide a single curated climate data set of daily observations covering the years 1975-2022 that blends information from all five sources and includes annotated scripts documenting decisions for handling data. These synthesized climate data will facilitate future research, reduce duplication of effort, and increase our ability to compare results across studies. The data set includes information on precipitation (water and snow), snowmelt date, temperature, wind speed, soil moisture and temperature, and stream flows, all publicly available from a combination of sources. In addition to the formatted raw data, we provide several new variables that are commonly used in ecological analyses, including growing degree days, growing season length, a cold severity index, hard frost days, an index of El Niño-Southern Oscillation, and aridity (standardized precipitation evapotranspiration index). These new variables are calculated from the daily weather records. As appropriate, data are also presented as minima, maxima, means, residuals, and cumulative measures for various time scales including days, months, seasons, and years. The RMBL is a global research hub. Scientists on site at the RMBL come from many countries and produce about 50 peer-reviewed publications each year. Researchers from around the world also routinely use data from the RMBL for synthetic work, and educators around the United States use data from the RMBL for teaching modules. This curated and combined data set will be useful to a wide audience. Along with the synthesized combined data set we include the raw data and the R code for cleaning the raw data and creating the monthly and yearly data sets, which facilitate adding additional years or data using the same standardized protocols. No copyright or proprietary restrictions are associated with using this data set; please cite this data paper when the data are used in publications or scientific events.

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Progressive warming of the grape growing regions has reduced the land capability for sustainable grapevine production and the geographical distribution of grapes. Bud burst, blooming, berry set, veraison, and harvest are the key phenological stages of grapevine, and are crucial for managing vineyard activities. The objective of this study was to evaluate the effect of seasonal temperature variability on the timing of key phenological stages of table grape cultivars in a new emerging viticulture region, i.e., the Pothwar region of Pakistan. Phenological stages of four table grape cultivars were recorded during two consecutive growing seasons at two locations. All phenological stages were attained earlier for the relatively warmer location, i.e., Chakwal. Similarly, the length of the growing season from bud burst to harvest was 15 to 21 days longer for the 2020 growing season than for the 2019 growing season, which corresponds to the inter-annual temperature variability. Moreover, the grapevine cultivars showed a distinct response for each growth phase; cv. Perlette matured earlier while cv. NARC Black was the last to ripen. Despite the large variability in the length of the active growing period from bud burst to harvest, accumulated growing degree days (GDD) varied only in a narrow range, i.e., 1510-1557 for cv. Perlette, 1641-1683 for cv. King's Ruby, 1744-1770 for cv. Sugraone, and 1869-1906 for cv. NARC Black. This implies that seasonal temperature variability using GDD is a better indicator for the phenology of table grape cultivars compared to regular time. It is clear from the results from this study that the variation in phenological responses of table grape cultivars due to temperature differences necessitates genotype and site-specific vineyard management.

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Investigation of the reproductive phenology and spawning behaviour of imperilled species in relation to environmental variability is needed to understand a critical component of species life history. In this study, we used redside dace (Clinostomus elongatus), a freshwater leuciscid listed as Endangered under Canada's Species at Risk Act, to model spawning phenology and make predictions about spawning initiation using historical and climate change projected thermal cues (measured as cumulative growing degree days), and provide an ethological description of spawning behaviour. Logistic regression models applied to 4 years of average daily stream water temperature data and field behavioural observations of the onset of spawning activity indicated a 50% probability of spawning initiation when cumulative growing degree days reached 214°C days and a 95% probability of spawning initiation at 288°C days. Using two climate change scenarios (i.e., a mid-century 1.6°C increase and an end of century 3.6°C increase), spawning initiation was predicted to advance 3 days by the year 2050 and 7 days by the year 2100. Underwater video cameras placed at two sites within an urban stream captured 73 unique spawning events revealing that redside dace spawn in pairs as well as in dense, tightly packed groups (more than 20 individuals). Moreover, there is evidence of redside dace having a polygynandrous mating system, as female redside dace spawned with multiple males in 45.2% of the total spawning events recorded. Taken together, this study provides important insights into redside dace spawning initiation and behaviour, key life-history traits having conservation implications for future reproductive success and, ultimately, population dynamics.

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Cereal forages, such as triticale forage, progressively gain interest as alternative crop for maize. The main study objective was to investigate the variation in potential feeding value of triticale forage among maturity stage, growing season and genotype, using total plant and stem fractions. Therefore, near infrared spectroscopy (NIRS) was evaluated as fast screening tool. The prediction ability was good (ratio of prediction to deviation, RPD ≥3.0) for total plant residual moisture, starch, sugars and for stem crude ash (CAsh) and neutral detergent fibre (aNDFom); suitable for screening (2.0 ≤ RPD <3.0) for total plant CAsh, acid detergent fibre (ADFom), in vitro digestibility of organic matter (IVOMD), in vitro digestibility of neutral detergent fibre (IVNDFD) and for stem total lignin (TL) and IVNDFD; poor (1.5 ≤ RPD <2.0) for total plant crude protein, crude fat, aNDFom, lignin (sa) and for stem Klason lignin (KL); unreliable (RPD <1.5) for stem residual moisture and acid soluble lignin (ASL). The evolution in potential feeding value of 36 genotypes harvested at the medium and late milk to the early, soft and hard dough stage was followed. The most important changes occurred between the late milk and early dough stage, with little variation in quality after the soft dough stage. During 2 growing seasons, variation in feeding value of 120 genotypes harvested at the soft dough stage was demonstrated. Interestingly, variation in stem IVNDFD is almost twice as high as for the total plant (CV 12.4% versus 6.6%). Furthermore, Spearman correlations show no link between dry matter yield and digestibility of genotypes harvested at the soft dough stage. Based on linear regression models ADFom appears as main predictor of both plant IVOMD and plant IVNDFD. Stem IVNDFD is particularly determined by KL.

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Temperate perennial fruit and nut trees play varying roles in world food diversity-providing edible oils and micronutrient, energy, and protein dense foods. In addition, perennials reuse significant amounts of biomass each year providing a unique resilience. But they also have a unique sensitivity to seasonal temperatures, requiring a period of dormancy for successful growing season production. This paper takes a global view of five temperate tree fruit crops-apples, cherries, almonds, olives, and grapes-and assesses the effects of future temperature changes on thermal suitability. It uses climate data from five earth system models for two CMIP6 climate scenarios and temperature-related indices of stress to indicate potential future areas where crops cannot be grown and highlight potential new suitable regions. The loss of currently suitable areas and new additions in new locations varies by scenario. In the southern hemisphere (SH), end-century (2081-2100) suitable areas under the SSP 5-8.5 scenario decline by more than 40% compared to a recent historical period (1991-2010). In the northern hemisphere (NH) suitability increases by 20% to almost 60%. With SSP1-2.6, however, the changes are much smaller with SH area declining by about 25% and NH increasing by about 10%. The results suggest substantial restructuring of global production for these crops. Essentially, climate change shifts temperature-suitable locations toward higher latitudes. In the SH, most of the historically suitable areas were already at the southern end of the landmass limiting opportunities for adaptation. If breeding efforts can bring chilling requirements for the major cultivars closer to that currently seen in some cultivars, suitable areas at the end of the century are greater, but higher summer temperatures offset the extent. The high value of fruit crops provides adaptation opportunities such as cultivar selection, canopy cooling using sprinklers, shade netting, and precision irrigation.

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BACKGROUND: In this study, the quality of land suitability for vine cultivation in south-western Iran was evaluated and a land suitability map for vine cultivation was developed using the fuzzy-analytic hierarchy process (AHP). The best harvest time of vines was determined based on the relationship between total soluble solids (TSS) and titratable acidity (TA) with fruit colour (red, green, and blue or RGB) in ten points and also the growing degree-days (GDD) maps from April to December. The relationship between GDD and effective parameters in vine cultivation was determined using principal component analysis (PCA) and Pearson correlation methods. RESULTS: The results illustrated that the maximum temperature and relative humidity (RH) have the greatest effect on vine cultivation and its yield (weight 0.24). The results of the land suitability map showed that central regions have better conditions for growing vines (32%). The measurements of TA and TSS depicted that vines of the northern parts have higher TA and lower TSS and there is a significant relationship between them and fruit colour. The results of GDD maps showed that the harvest time of ruby vine and Gezel-azm is July and August, respectively. Also, the temperature (Tmean , Tmax and Tmin ), wind speed, and GDD were the most important parameters to determine the best location for vine cultivation. CONCLUSION: Determining land suitability for cultivation, the best harvest time, the time of grape ripening, and following the exact time of export and import of vine has a vital role to increase its productivity and services. © 2022 Society of Chemical Industry.

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PREMISE: Phenological sensitivity, or the degree to which a species' phenology shifts in response to warming, is an important parameter for comparing and predicting species' responses to climate change. Phenological sensitivity is often measured using herbarium specimens or local studies in natural populations. These approaches differ widely in spatiotemporal scales, yet few studies explicitly consider effects of the geographic extent and resolution of climate data when comparing phenological sensitivities quantified from different data sets for a given species. METHODS: We compared sensitivity of flowering phenology to growing degree days of the alpine plant Silene acaulis using two data sets: herbarium specimens and a 6 yr observational study in four populations at Niwot Ridge, Colorado, USA. We investigated differences in phenological sensitivity obtained using variable spatial scales and climate data sources. RESULTS: Herbarium specimens underestimated phenological sensitivity compared to observational data, even when herbarium samples were limited geographically or to nearby weather station data. However, when observational data were paired with broader-scale climate data, as is typically used in herbarium data sets, estimates of phenological sensitivity were more similar. CONCLUSIONS: This study highlights the potential for variation in data source, geographic scale, and accuracy of macroclimate data to produce very different estimates of phenological responses to climate change. Accurately predicting phenological shifts would benefit from comparisons between methods that estimate climate variables and phenological sensitivity over a variety of spatial scales.

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Oviparous elasmobranch embryos (Chondrichthyes) have been the focus of several embryological studies; they are useful models for studying early ontogeny in vertebrates, as can help explore the existence of common developmental patterns among species. Skates (Rajiformes) are the most speciose order of oviparous elasmobranchs, however, few studies are focused on embryo development and only based on one skate family: Rajidae. Here, we extended the study of embryo development to other skate family, Arhynchobatidae, which represent about 1/3 of all skate species. Three adult female bignose fanskates (Sympterygia acuta) were held in captivity in order to provide the first complete embryonic development timeline for any species within the Arhynchobatidae family. Our results allowed further comparisons at the embryonic scale of different oviparous elasmobranch families, providing an updated cross-species overview of the early ontogeny. Incubation in S. acuta lasted 97 ± 1.4 days at 11-21.7 °C, and hatching size was 93.2 ± 0.2 mm in total length and 49.2 ± 0.3 mm in disc width. Early embryos of S. acuta were anatomically similar to other oviparous elasmobranch embryos, with several structures appearing at the same time, but late embryonic development was comparatively delayed. The late resorption of both the external yolk sac and the external gill filaments, and also the delay in the slit opening could indicate a low metabolic demand in S. acuta, which would probably be coupled with its seasonal reproductive cycle. Some structures such as external gill filaments and claspers appeared at a similar time in some species of Rajidae and also in Arhynchobatidae, but at different times in species of the same family, showing an inconsistency also found within shark families. Although the sequential scheme remained relatively constant, small heterochronies would be present within skates, within sharks, and also between skates and sharks.

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Currently, the multi-location testing of advanced hybrids in India is carried out at 25 centers under the All India Co-ordinated Research Project on Potato (AICRP-P), which is spread across the country. These centres have been chosen to represent different potato growing regions based on soil and agronomic features. However, the reliable deployment of the newly bred varieties in different regions requires a scientific delineation of potato growing zones with homogenous climates. The present study was undertaken to develop homogenous zones in the Indian sub-continent based on the environmental parameters of the potato growing season. A total of 1253 locations were identified across the country as having a plausible potato growing season of at least 70 days with suitable thermal limits. Six variables including five meteorological parameters including Physiological days (P days), Growing degree days (GDD), Mean daily temperature, Mean night temperature and Mean daily incident solar radiation, together with altitude as the sixth variable, were used for Agglomerative Hierarchical Clustering (AHC) and the Principal Component Analysis by Multidimensional Scaling (MDS) technique to derive identical classes. The thematic map of the classes was overlaid on potato growing districts of India using ArcGIS 9.1 software. The study clearly depicted that the clustering technique can effectively delineate the target population of environments (TPE) for potato genotypes performing well at different testing environments in India. The study also identifies target locations for future focus on breeding strategies, especially the high night temperature class having a large expanse in India. This is also vital in view of the impending climate change situation.

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The heterogeneity of the vineyard environment caused high variability in grape metabolites and flavor profiles, and the phenomenon was more prominent in recent years of climate change. Herein, distal leaf removal was applied in semi-arid Xinjiang to adjust the source to sink ratio of grapevines for three consecutive years (2018-2020). The grape-derived volatiles showed high correlations with specific climate factors such as temperature changes in the growth period. Results showed that distal leaf removal increased the solar radiation reaching the clusters in the first few days after applying LR treatments while not affecting the temperature. The improvement in fruity and floral aroma intensity by distal leaf removal was founded not only in grape metabolites but also in wines. Moderate cluster exposure brought by distal leaf removal was beneficial for the accumulation of isoprenoids, which therefore increased the fruity and floral intensity of wines. The carry-over effect did not show in consecutively defoliated vines among vintages regarding the wine aroma profile.

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Winter loss rates of honey bee colonies may fluctuate highly between years in temperate climates. The present study combined survey data of autumn and winter loss rates in Germany (2012-2021) with estimates of honey flow-assessed with automated hive scales as the start of honey flow in spring and its magnitude in summer-with the aim of understanding annual fluctuations in loss rates. Autumn colony loss rates were positively and significantly correlated with winter loss rates, whereas winter loss rates were inversely related to loss rates in autumn of the following year. An early start of net honey flow in spring predicted high loss rates in both autumn and winter, whereas high cumulative honey flow led to lower loss rates. The start of net honey flow was related to temperature sums in March. Combined, the results implied that the winter loss rate in one year was influenced by the loss rate of the preceding winter and shaped by honey flow dynamics during the following year. Hence, the rate of colony loss in winter can be viewed as a cumulative death process affected by the preceding one and a half years.

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Increasing temperatures, heat waves, and reduction of annual precipitation are all the expressions of climate change (CC), strongly affecting bread wheat (Triticum aestivum L.) grain yield in Southern Europe. Being temperature the major driving force of plants' phenological development, these variations also have effects on wheat phenology, with possible consequences on grain quality, and gluten protein accumulation. Here, through a case study in the Bolognese Plain (North of Italy), we assessed the effects of CC in the area, the impacts on bread wheat phenological development, and the consequences on grain gluten quality. The increasing trend in mean annual air temperature in the area since 1952 was significant, with a breakpoint identified in 1989, rising from 12.7 to 14.1°C, accompanied by the signals of increasing aridity, i.e., increase in water table depth. Bread wheat phenological development was compared in two 15-year periods before and after the breakpoint, i.e., 1952-1966 (past period), and 2006-2020 (present period), the latest characterized by aridity and increased temperatures. A significant shortening of the chronological time necessary to reach the main phenological phases was observed for the present period compared to the past period, finally shortening the whole life cycle. This reduction, as well as the higher temperature regime, affected gluten accumulation during the grain-filling process, as emerged analyzing gluten composition in grain samples of the same variety harvested in the area both before and after the breakpoint in temperature. In particular, the proportion of gluten polymers (i.e., gliadins, high and low molecular weight glutenins, and their ratio) showed a strong and significant correlation with cumulative growing degree days (CGDDs) accumulated during the grain filling. Higher CGDD values during the period, typical of CC in Southern Europe, accounting for higher temperature and faster grain filling, correlated with gliadins, high molecular weight glutenins, and their proportion with low molecular weight glutenins. In summary, herein reported, data might contribute to assessing the effects of CC on wheat phenology and quality, representing a tool for both predictive purposes and decision supporting systems for farmers, as well as can guide future breeding choices for varietal innovation.

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It is essential to understand how climate change and varieties affect crop phenology and yields to adapt to future climate change. The aim of this study was to analyse the phenological development trends of three winter wheat cultivars (1990-2020) to identify the most critical meteorological-climatic factors influencing the development and yield of the cultivars and to investigate the heat requirements for each phenological phase to reveal the potential of the different cultivars to adapt to the warming climate. The observed dates of green-up, the beginning of stem elongation, and the grain development advanced significantly, but the timing of maturity changed insignificantly during the period of 1990-2020. The most marked change was related to the shortening of the period from sowing to green-up. The green-up dates were related to the mean temperature of the period after sowing. The occurrence of stem elongation and grain development dates were negatively correlated with the mean temperature in May. Significant correlations were found between temperature and duration from sowing to green-up and positive from stem elongation to grain development. The change of cultivar led to earlier green-up and grain development dates, but cultivar choise had no influence on sowing, stem elongation, and maturity dates from 1990 to 2020. The newer cultivar Skagen was more successful in exploiting increased thermal resources. The heat requirements remained almost unchanged during the vegetative development period, while the heat amount required during the reproductive period increased by about 15%. These findings demonstrate that the choice of crop cultivars with higher thermal requirements may be an appropriate adaptation mean to achieve higher yields in response to climate change, at least in the middle latitudes.

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China is the largest fruit producer and consumer market in the world. Understanding the growing conditions responses to climate change is the key to predict future site suitability of main cultivation areas for certain deciduous fruit trees. In this study, we used dynamic and growing degree day models driven by downscaled daily temperatures from 22 global climate models to project the effects of climate change on growing conditions for deciduous fruit trees under two representative concentration pathway (RCP) 4.5 and RCP8.5 scenarios over 2 future time periods (represented by central years 2050s and 2085s) in northern China. The results showed a general increase of available winter chill for all sites under RCP4.5 scenario, and the most dramatic increase in chill accumulation could reach up to 36.8% in northeast regions for RCP8.5. However, the forecasted chill will decrease by 6.4% in southeast stations under RCP8.5 by 2085s. Additionally, the increase rate of growing season heat showed spatially consistency, and the most pronounced increase was found in the RCP8.5 by 2085s. For the southwest station, median heat accumulation increased by 20.8% in the 2050s and 37.1% in the 2085s under RCP8.5. Similar increasing range could be found in the northeast station; the median growing season heat increased by 19.8% and 38.8% in the 2050s and 2085s under RCP8.5, respectively. Moreover, the date of last spring frost was expected to advance and the frequency of frost occurrences was projected to decline in the study area compared to the past. Overall, the present study improves understanding regarding site-specific characteristics of climatic suitability for deciduous fruit tree cultivation in main producing regions of northern China. The results could provide growers and decision-makers with theoretical evidence to take adaptive measure to ensure fruit production in future.

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