Degree Days Research Articles

Remote Sensing Detection of Growing Season Freeze-Induced Defoliation of Montane Quaking Aspen (Populus tremuloides) in Southern Utah, USA

Growing season freeze events pose a threat to quaking aspen (Populus tremuloides Michx.), leading to canopy defoliation, reduced vigor, and increased mortality, especially for declining montane populations western North America. Detecting the spatial distribution and progression of this damage is challenging due to limited in situ observations in this region. This study represents the first attempt to comprehensively resolve the spatial extent of freeze-induced aspen canopy damage in southern Utah using multispectral remote sensing data. We developed an approach to detect the spatial and temporal dynamics of freeze-damaged aspen stands, focusing on a freeze event from 8–9 June 2020 in southern Utah. By integrating medium- (~250 to 500 m) and high-resolution (~10 m) satellite data, we employed the Normalized Difference Vegetation Index (NDVI) to compare post-freeze conditions with historical norms and pre-freeze conditions. Our analysis revealed NDVI reductions of 0.10 to 0.40 from pre-freeze values and a second flush recovery. We introduced a pixel-based method to evaluate freeze vulnerability, establishing a strong correlation (R values 0.78 to 0.82) between the onset of the first flush (NDVI > 0.50) and the accumulation of 100 growing degree days (GDD). These methods support the potential for retrospective assessments, proactive forest monitoring, and forecasting future risks.

Environmental Drivers of Palsa and Peat Plateau Occurrences: A Regional Comparison Across the Northern Hemisphere

ABSTRACTPalsas and peat plateaus occur in various environmental conditions, but their driving environmental factors have not been examined across the Northern Hemisphere with harmonized datasets. Such comparisons can deepen our understanding of these landforms and their response to climate change. We conducted a comparative study between four regions: Hudson Bay, Iceland, Northern Fennoscandia, and Western Siberia by integrating landform observations and geospatial data into a MaxEnt model. Climate and hydrological conditions were identified as primary, yet regionally divergent, factors affecting palsa and peat plateau occurrence. Suitable conditions for these landforms entail specific temperature ranges (500–1500 thawing degree days, 500–4000 freezing degree days), around 300 mm of rainfall, and high soil moisture accumulation potential. Iceland's conditions, in particular, differ due to higher precipitation, a narrower temperature range, and the significance of soil organic carbon content. The annual thermal balance is a critical factor in understanding the occurrence of permafrost peatlands and should be considered when comparing different regions. We conclude that palsas and peat plateaus share similar topographic conditions but occupy varying soil conditions and climatic niches across the Northern Hemisphere. These findings have implications for understanding the climatic sensitivity of permafrost peatlands and identifying potential greenhouse gas emitters.

Four decades in the vineyard: the impact of climate change on grapevine phenology and wine quality in northern Italy

The wine sector, among the most profitable agricultural segments, has been markedly affected by the ongoing climate change impacts, such as warmer climate conditions with higher frequency of extreme temperatures and a trend of decreasing precipitation. All this results in higher evaporative demand and therefore higher occurrence of water stress events leading to advancement of temperature-sensitive phenological stages (e.g., budburst and ripening). Such negative effects eventually affect berry development and quality, especially in historically valuable viticultural areas, forcing winegrowers to work within a compressed harvest period to maintain wine typicity. In this work we examined the relationship between environmental variables (air and soil temperature, relative humidity, precipitation, and solar radiation), phenology, berry, and wine quality for the two varieties (Chardonnay and Teroldego) in Trentino Alto-Adige/South Tyrol (Italy) over 36 years. Huglin Index (a bioclimatic heat index), growing degree days (measure of heat accumulation), and overall mean temperature showed linear increase (p < 0.001) in the last years, while no variations were recorded for precipitations. Despite no major effects being observed for phenological interval lengths, the onset of most of the phenological stages for both varieties had significantly (p < 0.001) advanced. However, i) early budburst pushed the budburst-flowering interphase by -1.2 days every two years toward putative colder periods with increased late frost probability and potential slower phenological progression towards flowering, and ii) early veraison shifted the veraison-ripening interphase by 0.25 day per year into warmer periods that oppositely impose faster phenological advancement. Hence, a substantial equilibrium in the seasonal growing length over years was maintained. Potential carry-over effects from the previous season were observed, particularly associated with heat requirements to unlock early phenological events, raising additional concerns on the additive effects of climate change to viticulture. Generally, white wine quality increased (p < 0.05) over the years, while red and sparkling wines remained unaffected. This was putatively related to accurate harvest date decision-making dictated by berry quality parameters: sugar-to-acidity ratio for Chardonnay and bunch sanitary status for Teroldego. Overall, this work provides evidence of the dynamics involved in climate change, and, to our knowledge, its overlooked effects on viticulture, thus providing new insights that can contribute to further developing adaptive strategies.

Optimizing ethephon application timing for ‘Meyer’ zoysiagrass seedhead suppression

AbstractZoysiagrass (Zoysia spp. Willd.) is a desirable, low‐input turfgrass species used on golf courses. However, prolific zoysiagrass seedhead production in the spring can increase golf course maintenance costs and reduce aesthetics. Previous research demonstrates that a single autumn ethephon application can suppress zoysiagrass seedhead production the following spring, but the optimum application timing is not well‐defined. The objective of this research was to determine the optimum window for an effective ethephon application for ‘Meyer’ zoysiagrass seedhead suppression. Small‐plot field research was conducted in Indiana, Kansas, Arkansas, and Tennessee. Seedheads were suppressed up to 99% depending on application timing. In Indiana, applications made on September 19 provided 99% seedhead suppression. In Kansas, applications between August 30 and September 18 yielded >64% seedhead suppression. In Arkansas, applications between October 3 and October 17 yielded >52% seedhead suppression. In Tennessee, applications between September 19 and October 23 provided >78% seedhead suppression. Applications made outside these windows resulted in more seedhead production at each respective location. Interestingly, optimum application timing was approximately 2 weeks later in Arkansas and Tennessee compared to Indiana and Kansas. Using growing degree days, a nonlinear Gaussian model was fit to predict the optimum ethephon application timing. In addition to data from this research, the proposed model accurately predicted observed zoysiagrass seedhead suppression in previously published research. This research better characterizes the optimum autumn application timing for Meyer zoysiagrass seedhead suppression across the transition zone.

Transient hypoxia drives soil microbial community dynamics and biogeochemistry during human decomposition.

Human decomposition in terrestrial ecosystems is a dynamic process creating localized hot spots of soil microbial activity. Longer-term (beyond a few months) impacts on decomposer microbial communities are poorly characterized and do not typically connect microbial communities to biogeochemistry, limiting our understanding of decomposer communities and their functions. We performed separate year-long human decomposition trials, one starting in spring, another in winter, integrating bacterial and fungal community structure and abundances with soil physicochemistry and biogeochemistry to identify key drivers of microbial community change. In both trials, soil acidification, elevated microbial respiration, and reduced soil oxygen concentrations occurred. Changes in soil oxygen concentrations were the primary driver of microbial succession and nitrogen transformation patterns, while fungal community diversity and abundance was related to soil pH. Relative abundance of facultative anaerobic taxa (Firmicutes and Saccharomycetes) increased during the period of reduced soil oxygen. The magnitude and timing of the decomposition responses were amplified during the spring trial relative to the winter, even when corrected for thermal inputs (accumulated degree days). Further, soil chemical parameters, microbial community structure, and fungal gene abundances remained altered at the end of 1 year, suggesting longer-term impacts on soil ecosystems beyond the initial pulse of decomposition products.

455 Evaluating the effect of a phenology-based timeline on the interpretation of enteric methane emission results

Abstract The methodology of analyzing methane emissions in cattle grazing native rangeland is imperative for producing reliable and repeatable estimations of total enteric emissions on an individual and herd basis. However, due to seasonal differences in climate from year to year, there are distinct differences in forage biomass availability and nutrient composition on extensive rangelands. Thus, our objective was to evaluate the differences in methane emissions using phenological forage phases compared with specific time periods. Yearling Angus steers (n = 127) were allocated to one of six pastures grazed from June to September (2023) at the South Dakota State University Cottonwood Field Station (Cottonwood, SD). Each pasture was equipped with a GreenFeed (C-Lock Inc., Rapid City, SD) pasture system to measure individual animal CH4 emissions. A subset of CH4 data from two cool-season-dominated pastures were aggregated from the overall study. We used two methods to segment CH4 by either 1) month (June, July, August) or 2) phenology (vegetative, reproductive, and senescence) to derive average CH4 (gּ animalּ -1ּ d-1) for each period. Western wheatgrass (WWG), a cool-season native, was used as a proxy for cool season grass development. On May 28th, 2023, the growing degree days (GDD) reached 632, representing the 3.5 leaf stage. WWG has been documented to reach maturity at approximately 1,100 GDD, which occurred on June 20th, 2023. Nutrient content of the forage (i.e., lignin) was used to approximate the start of senescence on August 11th. These developmental markers created estimates of the vegetative, reproductive, and senescence periods within our emissions data. Differences in enteric emissions for each approach were analyzed using a linear mixed effects model in R, and post-hoc contrast between methods was assessed using the lsmeans package. There were no statistical differences in CH4 by month (P > 0.05), and the means for June, July, and August were 217, 214, and 211 ± 4, respectively. By phenological phases, there was a difference (P < 0.05) between maturity and senescence, with means for vegetative, reproductive, and senescence as 214, 219, and 206 ± 4, respectively. Methane intensity (gּ animal-1ּ d-1) per period was then multiplied by the number of days in each month or phase to estimate total emissions for the entire grazing season (86 d). The monthly approach totaled 18,383 g CH4 per animal, while phenology totaled 18,504 g for the grazing season. This is a difference of 0.654% between the same data segmented by month or by phenology. Therefore, because of the dynamic nature of forage and cattle production, it is likely that accounting for phenology will provide greater clarity for GHG on rangeland systems rather than arbitrary periods of time and will require the use of dynamic models to handle the complexity of enteric emissions of grazing animals.

Compound extreme heat and drought stress alter the spatial gradients of protein and starch in wheat grains

The spatial gradients of protein and starch in wheat grains affected the grain milling characteristics and flour utilization. The increase in compound heat stress and drought stress (HDS) due to global climate change threatens wheat grain yield and quality parameters, but the impacts of extreme climate events on the gradients of protein and starch in wheat grains remain unclear. In this study, two-year, environment-controlled experiments with four heat stress levels (17/27, 21/31, 25/35, and 29/39°C) and three drought stress levels (30 %, 55 %, and 75 % field capacity) were conducted to investigate the effects of HDS on the gradients of protein and starch concentrations within the five grain layers. The results showed that HDS resulted in significantly greater protein concentrations, while resulting in lower starch concentrations in the wheat grain layers. Among the five layers, the endosperm layers exhibited the greatest increase in protein concentration under HDS, but the starch concentration under HDS decreased in the order of husk > aleurone > endosperm layer. HDS unevenly altered the protein and starch concentrations of the five grain layers. There was significant linear relationship between relative protein and starch concentration with accumulated heat degree days (AHDD). With a 1°C·d increase in AHDD, the protein concentration in the five grain layers increased by 1.17–2.19 %, while the starch concentration decreased by 0.62–0.90 %, depending on the drought stress levels. A significant linear relationship was also observed between the relative protein and starch concentrations and evapotranspiration (ET). A 1 mm increase in ET led to a protein concentration decrease of 0.58–0.76 % in P1-P5, with a corresponding starch concentration increase of 0.28–0.46 %, depending on cultivar and treatment stages. Our results indicate that HDS significantly impacts the grain quality parameters for the flour milling process and human diet and will provide important insights into adapting wheat quality to climate change.

Individual and combined effects of high-temperature stress at booting and flowering stages on rice grain quality.

High temperature stress (HTS) has become a serious threat to rice grain quality and few studies have examined the effects of HTS across multiple stages on rice grain quality. In the present study, we conducted 2 years of HTS treatments under three temperature regimes (32/22 °C, 40/30 °C and 44/34 °C) and HTS durations of 2 days and 4 days at three critical stages: booting, flowering, and a combination of booting and flowering. We employed the heat degree days (HDD) metric, which accounts for both the level and duration of HTS, to quantify the relationships between grain quality traits and HTS. The results revealed the diverse effects of HTS on rice grain quality at different stages, durations and temperature levels. HTS significantly (P < 0.05) reduced grain quality, with the highest sensitivities (reduction per 1 °C day-1 increase in HDD) observed at the flowering stage, followed by the combined and booting stages treatments under mild HTS treatment (40/30 °C). However, under extreme HTS treatments (44/34 °C) for 4 days, rice grains subjected to combined HTS treatment experienced complete mortality. Pre-exposed to HTS at the booting stage within a certain intensity can alleviate the adverse effects of post-flowering HTS on grain quality. This provides valuable insights for assessing the potential impact of multiple HTS events on the grain quality under future climate warming. © 2024 Society of Chemical Industry.

Climate change impact assessment of growing degree days and thermal growing period of cotton in north-west India

ABSTRACT Temperature is an indispensable necessity of plant growth, which explains the 95% variability in plant development. Accumulated temperature, i.e. growing degree day (GDD) is a useful agro-climatic indicator that translates raw climatic data into meaningful decisions. In this study, the GDD concept is used to analyze spatio-temporal variability of accumulated growing degree days (AGDD) and thermal growing period of cotton for the past and future climates in the three different zones (north-east, central and south-west) of Punjab. During the baseline period, higher AGDD were accumulated in the south-western (2,441 °C day), followed by central (2,276.8 °C day) and north-eastern (2,073.8 °C day) zones. During the end of mid-century, AGDD of the central zone was increased by 4–11%, 3–27% for north-eastern, and 3–7% for south-western zones in contrast to the baseline period. This increase in AGDD of cotton might decrease the thermal growing period by 6–14%, 8–25%, and 4–8% for central, north-east and south-western zones, clearly indicating the thermal stress over the cotton crop. This study provides quantitative information for crop breeders and cotton scientists to develop new genetically modified cultivars and improved agronomic practices to mitigate the adverse effect of climate change.

Identifying the key meteorological factors to marketable tuber rate of potato: A 5-year field experiment in North China

ContextPotato is one of the staple food crops in China. Optimized agronomic management could enhance potato yield, while the economic benefits of farmers depend on both the yield and marketable tuber rate (MTR) of potato. The key meteorological factors to the variation of MTR of potato and the relationship between potato yield and MTR remain unclear. ObjectiveThe study aims to explore the key meteorological factors to the variation of MTR of potato and the relationship between potato yield and MTR. MethodsA 5-year (20172021) rainfed field experiment with 3-planting date and 3-cultivar maturity of potato was conducted to investigate the optimum combination of planting date and cultivar maturity for both high yield and MTR under different year types and the relationship between potato yield and MTR. The meteorological factors during three growth stages including planting to 10 d before the tuberization, the tuber formation period (10 d before the tuberization to 10 d after the tuber bulking), 10 d after the tuber bulking to maturity were used to identify the key meteorological factors to yield and MTR of potato. ResultsThroughout the experimental period, there were large variations in the fresh tuber yield and MTR of potato ranging between 4.827 t ha−1 and 061 %, respectively. Early- to middle planting of middle maturing cultivars under warm-wet years resulted in higher MTR, yield, and economic benefit compared to other combinations. Under warm-dry years, while early planting of early- to middle-maturing cultivars could achieve higher yield and MTR, farmers still suffer economic losses under most combinations of planting date and cultivar maturity. On the whole, there was a synergistical enhancement between yield and MTR of potato (R2=0.86, P<0.01). The precipitation and growing degree day (GDD) during tuber formation period (TF), precipitation before TF, and the interaction of precipitation and mean air temperature after TF could account for 77 % of the variations in total tuber yield while marketable tuber rate could be determined by the precipitation from planting to 10 d after the tuber bulking, the HDD during TF, and the interaction of precipitation and mean air temperature before TF (R2=0.79). Conclusions:Total tuber yield and MTR of potato could be synergistically enhanced by optimizing planting date and cultivar maturity. Compared with total tuber yield, MTR influences economic benefit of potato more significantly. Implications:These findings could serve as a valuable reference for determining the optimal planting date and cultivar maturity of potato under different hydrothermal year types to enhance the MTR, yield, and economic benefit of rainfed potato planting and provide an important implication on potato model improvement.

Agrometeorological indices, physiological growth parameters and performance of finger millet as influenced by different cultivars under hot and sub humid region of Odisha

Present-day agriculture is under tremendous pressure due to various factors such as climate change, degradation of soil and water quality, and yield plateauing of major food crops. Under these scenarios, there is an urgent need to choose a climate-resilient and ecologically hardy crop which can perform under adverse conditions with low input requirements. In this regard, millets can be suitable crops for agricultural sustainability. Among various millets, finger millet (Eleusine coracana L. Gaertn) is cultivated mainly in India and Africa. However, most farmers grow finger millet with local cultivars, and improved ones can be replaced to enhance productivity. The present investigation conducted at the Post Graduate Research Farm of Centurion University of Technology and Management, Odisha, focused on evaluating suitable cultivars of finger millet. The study revealed that cultivars significantly influenced finger millet growth, productivity, and economics. The physiological growth parameters, namely, crop growth rate, relative growth rate, net assimilation rate and leaf area duration were significantly influenced by finger millet cultivars. The growing degree days (GDD), helio-thermal units (HTU) and photothermal units (PTU) of the finger millet showed a great variation among the cultivars. The Maximum total GDD (2169 °C day), HTU (18141 °C day hours) and PTU (24297 °C day hours) were recorded in the cultivar Hima(w) VR 936. The cultivars Indravathi VR 1101, Sri Chaitanya VR 847 (1.73) and Hima (W) VR 936 (1.60) were superior to other cultivars in expression of the grain yield and economics of finger millet. The study concluded that the cultivation of Indravathi and Sri Chaitanya could be considered as short-duration cultivars; however, Hima can be chosen as long duration crop for successful finger millet cultivation with higher net returns and benefit-cost ratio under hot and sub-humid regions of Odisha.

Mixed stands of black spruce (Picea mariana) and tamarack (Larix laricina) offer high secondary growth in eastern boreal forests of Canada

The Canadian boreal forest is still lacking investigation into compatible species mixtures that can lead to higher growth rates than monospecific or pure stands. The effect of species mixtures on stand productivity can vary with stem density, species proportion, site characteristics, and climate variation. We investigated mixed stands of black spruce (Picea mariana) and tamarack (Larix laricina) in eastern Canadian boreal forests. Using modern forest survey data, we analyzed stand basal area variation in 756 mature stands exclusively composed of these two species over a study area spanning 535,000 km². We generated a linear relationship between mixed stand basal area and stem density, and the residual of this relation was used as response variable named ‘residual basal area’. Positive and negative deviations of residual basal area were analysed with generalized additive models and quantile regressions with tamarack basal area, climate, and site characteristics as explanatory variables. The selected model included tamarack basal area, mean seasonal precipitation, degree days, mean annual temperature, stand age, latitude, longitude, and the type of surficial deposit. Tamarack exhibited a linear positive effect on predicted residual basal area. The most significant effect was observed from the interaction between tamarack basal area and stand age, predicting positive residual basal area of 16 m² ha−1 when stand aged was 150 years old and tamarack basal area was between 12 and 17 m² ha−1. Quantile regressions revealed that tamarack could enhance basal area while increasing black spruce stem size and density. Landscape managers may consider the establishment of mixed black spruce and tamarack stands to favor secondary growth in eastern Canadian boreal forests.

Game analysis of future rice yield changes in China based on explainable machine-learning and planting date optimization

ContextGlobal warming's escalating severity necessitates sophisticated approaches for predicting rice yield. Research QuestionCombining crop models with data-driven techniques, such as machine learning, can more effectively grasp the complex interplay of variables influencing crop growth. It remains a significant challenge to balance accuracy and interpretability in such hybrid models. MethodsThe research integrated the Decision Support System for Agrotechnology Transfer (DSSAT) with statistical and machine learning models respectively, to assess rice yield changes in China under four future Shared Socio-economic Pathway (SSP). SSPs are scenarios that integrate socioeconomic trends with greenhouse gas emissions and radiative forcing pathways, which affect the phenology and yield of rice. The Shapley Additive Explanation (SHAP) method was employed to interpret the model, effectively determining the interplay among variables influenced rice yields. Mitigated the negative impacts of climate change on rice yield through the planting date optimization. ResultsProjections indicate significant rice yield losses in China without CO2, worsening with increased radiative forcing (p < 0.001). Considering rising CO2, single-season rice yields are projected to increase by 0.1–3.6 %, early rice by 4.6–9.5 %, while late rice yields are still decrease by 2.3–8.8 %. The rising CO2 can offset yield losses for single and early rice but not for late rice. The hybrid approach which combined the Random Forest (RF) with the DSSAT performed best in predicting rice yield. Studies showed that rising temperatures caused rice yield losses in China, yet we found that Growing Degree Days (GDD) exerted a more negative impact (p < 0.001). In high-precipitation regions, deep soil moisture is more influential than shallow soil moisture, whereas the reverse was true in drier areas (p < 0.001). Advancing planting dates for early and single rice and delaying for late rice can increase yields (p < 0.001). Adjusting to optimal planting dates, single-season rice yields increased by 3.3–6.3 %, early rice increased by 9.7–18.3 %, while late rice still decreased by 1.0–4.7 %. ConclusionsWithout considering the impact of CO2, significant rice yield losses in China are projected. Even with the fertilization effect of CO2, rice yields remain negatively impacted by climate change. However, implementing appropriate measures, such as optimizing planting dates, can help Chinese rice production benefit under changing climate. ImplicationsThis study offers insights into balancing accuracy and interpretability in hybrid models and provides guidance for local policymakers to address future climate change.

The Fremont Frontier: Living at the Margins of Maize Farming

Abstract The Fremont provide an important case study to examine the resilience of ancient farmers to climatic downturns, because they lived at the far northern margin of intensive maize agriculture in the American West, where the constraints on maize production are made abundantly clear. Using a tree-ring and simulation-based reconstruction of average annual precipitation and maize growing degree days, along with cost-distance to perennial streams, we model spatial variability in Fremont site density in the eastern Great Basin. The results of our analysis have implications for defining the ecological envelope in which farming is a viable strategy across this arid region and can be used to predict where and why maize farming strategies might evolve and eventually collapse as climate changes over time.

Enhancing Sustainability through Weather Derivative Option Contracts: A Risk Management Tool in Greek Agriculture

This paper investigates the efficacy of weather derivatives as a risk management tool in the agricultural sector of Naousa, Greece, focusing on tree crops sensitive to temperature variations. The specific purpose is to assess how effectively weather derivative options can mitigate financial risks for farmers by providing strategic solutions. The study assesses the strategic application of Heating Degree Days (HDD) index options and their potential to alleviate economic vulnerabilities faced by farmers due to temperatures fluctuations. Employing different strike prices in Long Call and Straddle options strategies on the HDD index, the research offers tailored risk management solutions that cater to varying risk aversions among farmers. Moreover, the study applies the Value at Risk (VaR) methodology to quantify the financial security that weather derivatives can furnish, revealing a significantly reduced probability of severe financial losses in hedged scenarios compared to no-hedge conditions. Results show that all implemented strategies effectively enhance financial outcomes compared to scenarios without hedging, highlighting the exceptional utility of weather derivatives as risk management tools in the agricultural sector. Strategy 4, which exhibits the lowest VaR, emerges as the most effective, providing substantial protection against adverse weather conditions. This research supports the notion that weather derivatives can substantially contribute to the economic sustainability of rural economies, influencing policy decisions toward enhancing financial instruments for risk management in agriculture.

Accumulated thermal units method for predicting development stages, and potential seed yield of sunflower (Helianthus annuus) under Mediterranean conditions

The possibility of accurately assessing the emergence, anthesis and maturation dates of sunflower grown under Mediterranean conditions was investigated. Accumulated Thermal Units (TSUM) from sowing to emergence, from emergence to anthesis, and from anthesis to maturation were recorded in 14 experimental sunflower plantations, carried out in two sites with representative soils in the Thessaly Plain (central Greece) in the years 2012, 2013, 2014, 2015 and 2022. Various combinations of sowing date; irrigation and N-fertilization inputs were studied, and the corresponding phenological stages and seed yields were determined. It was found that the TSUM method is very effective for predicting the duration of the phenological stages of sunflower and thus the development rate and stages of this crop. Particularly accurate is the assessment of the emergence-anthesis period calculated at 817 degree days (°C-d) for base temperature (To) equal to 6 °C and optimum temperature (Topt) 28 °C, whereas for the anthesis-maturation period, the TSUM method needs to be adjusted for photoperiodism, using a photoperiod coefficient based on the daylength. In a simpler approach, the heat unit sum of 1213°C-d (To=0 °C) it can be used for the emergence-anthesis period (or 1418°C-d for the sowing-anthesis period), without much error, and an average period of 44 days for the anthesis-maturation period. Having determined the anthesis-maturation period, the potential seed yield of sunflower was successfully assessed, based on the global radiation prevailing during the grain filling period (i.e. last 37 days before capitulum ripening) for the treatments of optimum water and nitrogen applications. Knowledge of the seed yield potential of sunflower might be very important for land evaluation purposes and the introduction of this important crop in Thessaly more generally and many Mediterranean sites.

Local contribution of road traffic and residential biomass burning to black carbon aerosols – Modelling and validation

Black carbon (BC) is a harmful pollutant to human health and the environment. The aim of this paper is to evaluate the local contribution of road traffic and residential biomass burning to BC pollution levels at urban scale by implementing an integrated modelling approach with high spatial and temporal resolution. The traffic emission was extended to include BC emission factors considering road network as line emission sources. A new module to calculate emissions from residential biomass burning was developed based on the heating degree days methodology and local surveys. The modelling approach implemented in Coimbra, Portugal, was validated with observations collected during a six-month monitoring campaign at urban traffic and urban background stations using thermo-optical and optical methods. At the traffic station, modelling results showed that 86% of BC concentrations are related to traffic activity, which are mostly due to hot exhaust emissions (76%). Nevertheless, biomass burning has a significant contribution in the whole urban area during winter. The results of monthly average BC concentrations obtained from dispersion modelling revealed a contribution from local road traffic and residential biomass burning emissions of around 4 μg m−3 at both monitoring sites during the coldest period, but this contribution was two times higher for the hotspots identified within the urban area. Moreover, hourly values at hotspots obtained from the modelling may achieve 85 μg m−3, thus stressing the importance of spatial and temporal analysis with high resolution. The validation approach applied in this work highlight the need for more transparency in defining “black carbon” reported by modelling to ensure comparability with measurements obtained by different techniques.

Suitability of Residues from Seaweed and Fish Processing for Composting and as Fertilizer

There is a need to find novel sources of fertilizers to meet the increasing food demands of a growing human population and alternatives to mined and synthetic fertilizers for the certified organic sector. Composting is a common method for processing and stabilizing organic residues for use in horticulture. To that end, a small-scale composting experiment with six combinations of dried and ground rockweed (Ascophyllum nodosum), algae fiber from chemically processed rockweed, ground bones and fishmeal from cod (Gadus morhua), and ground blue mussels (Mytilus edulis) was conducted in Dewar flasks to assess whether these residues are suitable for composting and have potential for use as fertilizers. Expanded clay aggregates were used as a bulking material. Physicochemical analyses were performed on the residues and their mixtures before and after composting, and the temperature in the flasks was monitored for 92 days. Suitability was determined by evaluating the temperature dynamics, changes in physiochemical parameters, and nutrient profiles. All treatments generated heat, with reductions in C/N ratio, weight, and volume, demonstrating suitability for composting. The treatments with algae fiber had a higher mean temperature (34.5 vs. 29.0 °C) and more degree days above the thermophilic range (mean = 176- vs. 19-degree days), the greatest reduction in volume (mean = 35% vs. 27%), and the lowest C/N ratios at the end of active composting (18 vs. 24) compared to the treatments with dried and ground seaweed. In terms of fertilizer value, none of the finished composts were balanced for use as fertilizers alone and, in some cases, contained too much Na, but contained sufficient concentrations of K, S, Mg, and Ca and could be a valuable source of these nutrients and organic matter in combination with other N- and P-rich sources.

A Common Climate–Yield Relationship for Wheat and Barley in Japan and the United Kingdom

Wheat and barley yields in Japan are considerably lower than those in the UK, even where similar Climate Zones (CZs) of relatively cold and humid nature are shared. In order to understand this difference, it is first necessary to find out if any common climate–yield relationship exists between the two countries. The Climate Zonation Scheme (CZS) developed in the Global Yield Gap Atlas (GYGA) was used to analyse actual yield (Ya) with three climatic factors of the GYGA-CZS, i.e., growing degree days (GDD), aridity index (AI) and temperature seasonality (TS). A significant relationship was found between AI scores and Ya values across the two countries. Ya values decreased with an increase in AI scores; in other words, lower yields are associated with higher AI scores. In addition, the degree of yield reduction with the rise in AI scores was greater in Japan than in the UK. The present study also proposed a novel method to link CZs of the GYGA-CZS to regional classification units, especially for countries where statistical crop yield data are available only at a coarse scale.

A global analysis of ice phenology for 3702 lakes and 1028 reservoirs across the Northern Hemisphere using Sentinel-2 imagery

As existing global lake ice studies have predominantly focused on medium to large lakes, and reservoir ice studies have been limited to regional scales, very few studies of ice phenology have combined both lakes and reservoirs of different sizes. This study aims to characterize the freeze-up and break-up dates of 3702 lakes and 1028 reservoirs from 1 to 31,000 km2 across the Northern Hemisphere, and to analyze spatial patterns and relationships between ice phenological dates and driving factors. The freeze-up and break-up dates of these water bodies were retrieved from Sentinel-2 imagery using an ice detection algorithm through the Google Earth Engine platform from 2019 to 2023. The algorithm was verified by comparing phenology dates with an independent database based on observations from passive microwave sensors, with a mean absolute error of 18 days for both freeze-up and break-up dates. This newly established ice phenology database along with various geographic, morphometric, and climatic characteristics of the water bodies, was used to develop a random forest model for predicting ice phenology dates. While the predictive model performance is at a fair level (mean absolute error of 12 days for both freeze-up and break-up), challenges were encountered in certain high-elevation areas where cloudy conditions as well as black ice resulted in delayed freeze-up dates. Among the variables included in the random forest model, latitude and accumulation of freezing degree days were identified as the main drivers of ice phenology dates. Despite the challenges of applying a single, straightforward method on a global scale, this study has allowed the creation of a vast and comprehensive database of lake and reservoir freeze-up and break-up dates that can be used by the community to further analyze ice patterns.