Out of the frying pan into the fire: Predicted warming in alpine streams suggests hidden consequences for aquatic ectotherms.

Thermal regimes of aquatic ecosystems are predicted to change as climate warming progresses over the next century, with high-latitude and high-elevation regions predicted to be particularly impacted. Here, we have modelled alpine stream water temperatures from air temperature data and used future predicted air temperature trajectories (representative concentration pathway [rcp] 4.5 and 8.5) to predict future water temperatures. Modelled stream water temperatures have been used to calculate cumulative degree days (CDDs) under current and future climate conditions. These calculations show that degree days will accumulate more rapidly under the future climate scenarios, and with a stronger effect for higher CDD values (e.g., rcp 4.5: 18-28 days earlier [CDD = 500]; 42-55 days earlier [CDD = 2000]). Changes to the time to achieve specific CDDs may have profound and unexpected consequences for alpine ecosystems. Our calculations show that while the effect of increased CDDs may be relatively small for organisms that emerge in spring-summer, the effects for organisms emerging in late summer-autumn may be substantial. For these organisms, the air temperatures experienced upon emergence could reach 9°C (rcp 4.5) or 12°C (rcp 8.5) higher than under current climate conditions, likely impacting on the metabolism of adults, the availability of resources, including food and suitable oviposition habitat, and reproductive success. Given that the movement of aquatic fauna to the terrestrial environment represents an important flux of energy and nutrients, differential changes in the time periods to achieve CDDs for aquatic and terrestrial fauna may de-couple existing predator-prey interactions.

Loss, resilience and recovery of kelp forests in a region of rapid ocean warming.

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.

Estimates of Crop Yield Anomalies for 2022 in Ukraine Based on Copernicus Sentinel-1, Sentinel-3 Satellite Data, and ERA-5 Agrometeorological Indicators.

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.

Global warming is projected to lead to increased freshwater growth potential and changes in pace of life in Atlantic salmon Salmo salar.

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.

Dental DNA Mutations Occurring after Death: A Novel Method for Post-Mortem Interval (PMI) Estimation.

Post-mortem interval (PMI) estimation remains one of the major challenges in forensic practice, especially for late PMIs beyond 7-10 days after the death of the subject. In 2022, an innovative method to investigate the occurrence of mutations induced by the death of a subject in the DNA of post-mortem dental pulps at different PMIs was developed, applying a next-generation sequencing (NGS) analysis. The present study aims to apply the same method of analysis to a small sample of teeth belonging to the same subject and analyzed at different PMIs/accumulated degree days (ADDs), and of teeth extracted from different subjects but analyzed at the same PMI/ADD to verify the repeatability of the results obtained in relation to the time elapsed since death. A total of 10 teeth were collected from 6 patients (3 males and 3 females) with PMI varying from 8 to 35 days, and ADD from 157.4 to 753.8. We found 1754 mutations in 56 genes, with more than 700 mutations having a prevalence > 5% and more than 300 variants considered of interest for the purposes of the study. Mutations that were not present at lower PMIs but manifested in later PMIs in pulps belonging to the same subject demonstrate that they can only have been acquired by the subject after death and according to the time elapsed since death. In total, 67 somatic mutations in 29 out of the 56 genes of the used panel occurred in a fashion that allows an association with specific PMI/ADD ranges (within 8 days, between 17 and 28, and beyond 30 days after death). The results suggest that temperature and humidity could influence the rate of DNA degeneration in dental pulps, thus PMI should be estimated in ADD more than days. The preliminary validation supports the hypothesis that the innovative method could be a useful tool for estimating the post-mortem interval even beyond the first week after death, but further analyses are needed to customize a specific genetic panel for forensic investigations and verify the influence of degenerative processes of soft tissues surrounding dental elements on DNA degeneration of pulps.

Assessing temperature-based adaptation limits to climate change of temperate perennial fruit crops.

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.

Drivers of Odonata flight timing revealed by natural history collection data.

Global change may cause widespread phenological shifts. But knowledge of the extent and generality of these shifts is limited by the availability of phenological records with sufficiently large spatiotemporal extents. Using North American odonates (damselflies and dragonflies) as a model system, we show how a combination of natural history museum and community science collections, beginning in 1901 and extending through 2020, can be leveraged to better understand phenology. We begin with an analysis of odonate functional traits. Principal coordinate analysis is used to place odonate genera within a three-dimensional trait ordination. From this, we identify seven distinct functional groups and select a single odonate genus to represent each group. Next, we pair the odonate records with a list of environmental covariates, including air temperature and degree days, photoperiod, precipitation, latitude and elevation. An iterative subsampling process is then used to mitigate spatiotemporal sampling bias within the odonate dataset. Finally, we use path analysis to quantify the direct effects of degree days, photoperiod and precipitation on odonate emergence timing, while accounting for indirect effects of latitude, elevation and year. Path models showed that degree days, photoperiod and precipitation each have a significant influence on odonate emergence timing, but degree days have the largest overall effect. Notably, the effect that each covariate has on emergence timing varied among functional groups, with positive relationships observed for some group representatives and negative relationships observed for others. For instance, Calopteryx sp. emerged earlier as degree days increased, while Sympetrum sp. emerged later. Previous studies have linked odonate emergence timing to temperature, photoperiod or precipitation. By using natural history museum and community science data to simultaneously examine all three influences, we show that systems-level understanding of odonate phenology may now be possible.

Seasonal variability in the effect of temperature on key phenological stages of four table grapes cultivars.

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.

Reproductive phenology and behaviour of endangered redside dace (Clinostomus elongatus) in urban streams.

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.

Multi-criteria decision analysis integrated with GIS to determine land suitability for cultivation and best harvest time of vine.

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.

The heat stress during anthesis and the grain-filling period of spring maize in Northeast China is projected to increase toward the mid-21st century.

BACKGROUND: Against the background of global warming, heat stress has become more frequent, which adversely affects the growth and development of spring maize plants in Northeast China. To adapt the regional maize production to climate change, it is imperative to understand the spatio-temporal characteristics of heat stress. In the present study, we analyzed three of the indices for heat stress, including the number of heat stress days, heating degree days (HDD, the total heat degree-days during critical stages), and the percentage of stations with heat stress. RESULTS: From 1981 to 2019, the number of heat stress days varied greatly among the study years, ranging from 0 to 14 and 27 days, respectively. The average HDD was 7.8 and 5.0 °C day from 1981 to 2000, respectively, and the main hot-spots of heat stress occurred in the southwest regions. Moreover, compared with 1981-2000, the region of HDD during anthesis higher than 10 °C day in 2041-2060 under the SSP1-2.6 and SSP5-8.5 climate scenarios increased by 9.1-50.1% and 0.1-28.6%. The average HDD during the critical stages from 2041 to 2060 increased under the SSP5-8.5 climate scenario, being 1.5 times higher than that during 1981-2000. HDD during maize anthesis and the grain-filling period showed an overall increasing trend with years. About 19% and 58% of the study locations showed heat stress during the past 39 years, respectively. CONCLUSION: Heat stress during anthesis and the grain-filling period for spring maize in Northeast China is projected to increase toward the mid-21st century. © 2023 Society of Chemical Industry.

Phenotypic variation and genome-wide association studies of main culm panicle node number, maximum node production rate, and degree-days to heading in rice.

BACKGROUND: Grain yield is a complex trait that results from interaction between underlying phenotypic traits and climatic, edaphic, and biotic variables. In rice, main culm panicle node number (MCPNN; the node number on which the panicle is borne) and maximum node production rate (MNPR; the number of leaves that emerge per degree-day > 10°C) are primary phenotypic plant traits that have significant positive direct effects on yield-related traits. Degree-days to heading (DDTH), which has a significant positive effect on grain yield, is influenced by the interaction between MCPNN and MNPR. The objective of this research is to assess the phenotypic variation of MCPNN, MNPR, and DDTH in a panel of diverse rice accessions, determine regions in the rice genome associated with these traits using genome-wide association studies (GWAS), and identify putative candidate genes that control these traits. RESULTS: Considerable variation was observed for the three traits in a 220-genotype diverse rice population. MCPNN ranged from 8.1 to 20.9 nodes in 2018 and from 9.9 to 21.0 nodes in 2019. MNPR ranged from 0.0097 to 0.0214 nodes/degree day > 10°C in 2018 and from 0.0108 to 0.0193 nodes/degree-day > 10°C in 2019. DDTH ranged from 713 to 2,345 degree-days > 10°C in 2018 and from 778 to 2,404 degree-days > 10°C in 2019. Thirteen significant (P < 2.91 x 10-7) trait-single nucleotide polymorphism (SNP) associations were identified using the multilocus mixed linear model for GWAS. Significant associations between MCPNN and three SNPs in chromosome 2 (S02_12032235, S02_11971745, and S02_12030176) were detected with both the 2018 and best linear unbiased prediction (BLUP) datasets. Nine SNPs in chromosome 6 (S06_1970442, S06_2310856, S06_2550351, S06_1968653, S06_2296852, S06_1968680, S06_1968681, S06_1970597, and S06_1970602) were significantly associated with MNPR in the 2019 dataset. One SNP in chromosome 11 (S11_29358169) was significantly associated with the DDTH in the BLUP dataset. CONCLUSIONS: This study identifies SNP markers that are putatively associated with MCPNN, MNPR, and DDTH. Some of these SNPs were located within or near gene models, which identify possible candidate genes involved in these traits. Validation of the putative candidate genes through expression and gene editing analyses are necessary to confirm their roles in regulating MCPNN, MNPR, and DDTH. Identifying the underlying genetic basis for primary phenotypic traits MCPNN and MNPR could lead to the development of fast and efficient approaches for their estimation, such as marker-assisted selection and gene editing, which is essential in increasing breeding efficiency and enhancing grain yield in rice. On the other hand, DDTH is a resultant variable that is highly affected by nitrogen and water management, plant density, and several other factors.

Estimating phenological sensitivity in contemporary vs. historical data sets: Effects of climate resolution and spatial scale.

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.

Effects of climatic and cultivar changes on winter wheat phenology in central Lithuania.

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.

Climatic suitability projection for deciduous fruit tree cultivation in main producing regions of northern China under climate warming.

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.

Integration of GIS and remote sensing to derive spatially continuous thermal comfort and degree days across the populated areas in Jordan.

The widespread availability of high-resolution digital elevation data and high computational capabilities, along with GIS tools, has revolutionized big data processing, management, and interpolation. The present investigation generates high spatial resolution maps of thermal comfort levels, heating (HDD), and cooling (CDD) degree days across the populated areas in Jordan. Results show that areas having indoor apparent temperature (IAT) of 26 °C or above, which represents warm/hot conditions on this thermal index, cover a large portion of the study area during July and August. This thermal zone encompasses a large cluster of the major urban centers in the country. For instance, Amman, Zarqa, and Irbid, which host more than 80% of the population of the country, experience 13, 14, and 19 h of warm to very warm conditions during July and August, demonstrating that cooling needs are required to bring about thermal comfort for dwellings and office buildings. Heavy cooling loads, 1700-2000 CDDs, are restricted to the Jordan Rift Valley (JRV) and other small, low-level urban centers. With the exception of the JRV, the populated areas in the country experience cold to very cold conditions during the three coldest months, December through February. Very cold conditions in winter, IAT ≤ 8 °C, span more than 13-14 h of the diurnal cycle in most urban centers. The HDD range from values close to zero along the JRV to ⁓ 1900 in the southern mountains. Heating loads for dwellings and office buildings are very demanding and represent a pressing financial challenge to bring about thermal comfort to homes and public buildings during winter. The present procedure can be integrated with auxiliary data within a GIS environment to investigate numerous climatological, environmental, and site suitability issues. The present procedure can be used for operational purposes over territorial or regional scales for a wide range of applications.

Changes in spatio-temporal distribution of AgMERRA-derived agro-climatic indices and agro-climatic zones for wheat crops in the northeast Iran.

This study evaluates the potential of gridded AgMERRA (the Modern-Era Retrospective Analysis for Research and Applications) to estimate aridity index (AI), growing degree days (GDD), and temperature seasonality (TS) for six land stations across northeast Iran. The researcher investigated the spatiotemporal variation of the AgMERRA-derived agro-climatic indices for the entire period 1981-2010 and three 10-year sub-periods for the 347 wheat harvested grid cells (0.25° × 0.25°) and their utility for agro-climate zoning in northeast Iran. Results indicated a good agreement between AgMERRA daily solar radiation, maximum and minimum temperatures, and annual total precipitation with corresponding land observations for the six studied sites. AgMERRA-derived evapotranspiration (ETo), AI, GDD, and TS also exhibited good agreement (R2 and d > 0.7) with the land station-derived indices for most of the locations. Annual analysis of the AI indicated a negative trend for all of the wheat harvested grid cells, but the decrease was significant (p < 0.05) only for 14.70% of grid cells, which were located in the southwest part of the studied region. The magnitude of the significant decreasing trends in annual AI was (-)0.0011 per year. The increase in aridity was due to the concurrent occurrences of positive ETo trends and negative precipitation trends. All of the wheat harvested grid cells showed a significant increasing trend (p < 0.05) for GDD at the rate of 24.10 °C d year-1. The TS series demonstrated an apparent increasing trend for 99.2% of wheat harvested grid cells; however, only 16.9% of them had the significant positive trend (p < 0.05) with the average rate of 0.023 °C year-1. The wheat harvested grid cells with increasing trend for TS were mainly distributed in the arid mountainous southern part of the study area. The 10 years sub-periods revealed that the best conditions in terms of most of the studied agro-climatic indices were found in sub-period 1981-1990 and the north Khorasan had better conditions in all three sub-periods. Based on AI, GDD, and TS, 13 major gridded agro-climatic zones were recognized in northeast Iran.

Impact of climate change on Helicoverpa armigera voltinism in different Agro-Climatic Zones of India.

The Gram pod borer, Helicoverpa armigera (Noctuidae: Lepidoptera) is a cosmopolitan agricultural insect pest that prefers to feed on plant's protein biomolecules. Out of different density-independent factors, surface air temperature majorly affects the incidence and damage of the H. armigera on the crops. Early prediction of H. armigera generations (voltinism) in future climate years perhaps prevent additional damage in various crops and improve the farmers preparedness. In this study, future climate data that is temperature obtained for eleven Agro-Climatic Zones (ACZs) of India under four Representative Concentration Pathways (RCPs) scenarios in different climate years (2010, 2030, 2050, 2070, 2090) using weather file generator MarkSim web application. The accumulation of Growing Degree-days (GDD) by H. armigera at eleven ACZs in each climate year under different RCP scenarios was estimated using temperature data. The mean surface air temperature is predicted to 0.51 °C, 1.03 °C, 1.57 °C and 2.1 °C in climate years 2030, 2050, 2070 and 2090, which escalated annual H. armigera Gen. to 12.88, 13.33, 13.79 and 14.23, respectively over the baseline climate year 2010. Likewise, under RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5 scenarios H. armigera Gen. is predicted to 12.86, 13.29, 13.23 and 13.97 per annum with mean surface air temperatures 27.4 °C, 27.92 °C, 27.86 °C and 28.72 °C, respectively. The Eastern Coastal Plains and Hills Zone (ACZ 11) across climate years and RCPs has experienced a considerable increase in mean surface air temperature minimum (25.22 °C) and maximum (34.61 °C), which likely favor the GDD accumulation (6319.91) and the Genrations (14.97) in H. armigera. Therefore, the Eastern Coastal Plains and Hills Zone of India could be identified as H. armigera risk zone in near future. The present predictions in various ACZs of India may be significant in planning H. armigera management.

The influence of thermal cues on the reproductive phenology of Silver Shiner, Notropis photogenis.

Reproductive phenology and the length of the growing season vary in response to interannual environmental variability, with implications for population dynamics of freshwater fishes. Understanding the reproductive phenology of imperilled species in relation to environmental conditions is needed to better evaluate potential responses to changing environmental conditions, estimate future population dynamics and develop comprehensive recovery strategies. We examined Silver Shiner, a species listed as "Threatened" under Canada's Species at Risk Act, during spring 2018 and 2019 to better understand the reproductive phenology of the species at the northern edge of its range in Canada. The initiation of Silver Shiner spawning occurred on the descending limb of the hydrograph and was completed before the onset of the extended period of low summer flow. In addition, both the initiation and cessation of spawning occurred in response to a cumulative growing degree day base 5 (GDD5 ) cue, with logistic regression models indicating a 50% probability the population initiated and ceased spawning when GDD5 reached 68°C•days and 368°C•days, respectively. Logistic regression incorporating GDD5 effectively predicted spawning initiation and cessation, providing useful models for examining the impacts of alterations to the thermal regime on reproductive phenology and improving the ability to evaluate changes in the larval growth period. Furthermore, the models can facilitate the development of real-time estimates of spawning activity, and therefore ensure that disturbance to the species is minimized during the sensitive reproductive period.

Population-weighted degree-days: The global shift between heating and cooling.

Anthropogenic greenhouse gas emissions are driving global increases in temperature. This rise will likely lead to an increase in demand for cooling in the coming years. However, increasing temperatures are not the main explanatory factor for why the world is moving towards more cooling. This paper compares population and area-weighted cooling and heating degree-days derived using ERA5-Land reanalysis temperature, to show that population growth in warmer parts of the world drives cooling demand globally. The analysis shows that mean global area-weighted heating degree-days have fallen 8.46 °C days/year, whereas population-weighted heating degree-days have fallen by 12.5 °C days/year. At the same time, mean global area-weighted cooling degree-days have risen by 3.0 °C days/year, while population-weighted cooling degree-days have risen at 6.0 °C days/year. By using sub-country analysis, this paper shows that population-weighted degree-days can substantially differ from area-weighted degree-days. Finally, the findings highlight that the choice of heating and cooling degree-day base temperature is the most important parameter in the variability of degree-days and will need to be understood better in order to accurately account for future heating and cooling energy demand.