Seasonal Temperature Research Articles

Effects of mulching on plant growth, viral diseases, earliness and fruit yield attributes of round gourd under variable sowing dates in North Indian plains

Abstract Round gourd is sensitive to low temperature (March), high temperature (May–June), high humidity (July–August), and whitefly-transmitted begomovirus diseases (July–September), thereby restricting its fruit availability period in North-Western Indian Plains. Mulches extend the growing season by modifying soil temperature and reducing the incidence of viral diseases. Therefore, the present study was conducted to investigate the effects of sowing time, mulching and their interaction on performance of round gourd crop so as to identify the best mulch at different sowing times. The field trials were conducted in a split-plot design during 2021 and 2022. The main plot consisted of six sowing dates, i.e., the first week of March (DS1), April (DS2), May (DS3), June (DS4), July (DS5) and August (DS6). The sub-plot comprised bare soil (BS) and three mulching treatments, viz., silver-black plastic mulch (SBPM), black plastic mulch (BPM) and paddy straw mulch (6 t/ha) (PSM). The BPM and SBPM increased the seasonal soil temperature over BS by 3.1–4.1°C and 2.1–3.1°C, respectively, whereas the PSM reduced the seasonal soil temperature by 2.3–3.5°C. The SBPM produced the best crop performance, followed by BPM and PSM in all sowing dates except DS5 in which the PSM outperformed BPM. The DS1 and DS2 were the best sowing times, and the crop performance gradually declined with each successive sowing time, except that the crop performed better in DS6 compared with DS5. The SBPM or BPM in DS2 and DS1 were the best treatment combinations for round gourd cultivation in the study area.

Burn Period: A use-inspired metric to track wildfire risk across Arizona and New Mexico in the southwest U.S.

Abstract Numerous tools and indices exist for wildland fire managers to anticipate and track changes in wildfire risk driven by variability in weather and climate conditions at hourly to seasonal scales. However, in working closely with southwest U.S. managers, we learned of a simple meteorological metric being informally used, but not widely accessible in existing tools or information products, to gauge short-term changes in wildfire risk. This metric, termed ‘Burn Period’ (BP), is the local count of hours per day with relative humidity values equal to or less than 20%. Our collaboration led to the development of an experimental tool called the ‘Burn Period Tracker’ to ease access and promote use of BP values for planning and response. This study is a climatological analysis of BP values at 124 fire weather stations across Arizona and New Mexico for the period 2000-2022 to aid in interpretation and understanding of this use-inspired metric. BP values reflect the strong seasonality in temperature and moisture deficit-driven wildfire risk across the southwest U.S., with risk climbing through the arid spring season, peaking in June, and then falling rapidly with the onset of the summer monsoon in July. Regression analyses show that short-term variability in BP values are driven by variability in low level atmospheric moisture in all months with strongest relationships during the summer after the onset of the monsoon. This study highlights the utility of BP as a short-term wildfire planning tool as well as an example of collaborative weather and climate services development.

Current conservation status and potential distribution under climate change of Michelia lacei, a Plant Species with Extremely Small Populations in Yunnan, China

Abstract Michelia lacei W.W. Smith, a magnolia species categorized as Endangered on the IUCN Red List, is subject to severe disturbance. We carried out field surveys and a review of literature records to present a detailed description of the current status of M. lacei. We then predicted the potential distribution of M. lacei under different climatic scenarios based on 60 occurrence records (53 recorded during our field surveys and 7 earlier records) and 19 bioclimatic variables from the WorldClim database. We selected 18 locations and four bioclimatic variables for model training. Temperature seasonality and annual temperature range were the most influential variables for predicting the potential distribution of the species. We used MaxEnt to model distribution under current climate conditions and four Shared Socioeconomic Pathway scenarios in four future time periods to determine the effects of future climate change on the habitat suitable for the species. We predict areas of moderately and highly suitable habitat will gradually decrease over time. We recommend increased in situ and ex situ conservation efforts to mitigate this habitat decline and protect populations of M. lacei.

Changes in duration and intensity of waves of heat and cold on the territory of Belarus over the period from 1955 to 2021

The impact of modern climate warming on the characteristics of heat and cold waves on the territory of Belarus has been analysed. Since 1988, the number of heat waves and strong thaws has significantly increased (less than 15% of all registered heat waves and strong thaws occurred in the pre-warming period of 1955–1987), while the number of frost and summer cold waves has decreased. The average duration of frost and summer cold waves has decreased by 0.5–1.5 days, the average duration of strong thaws has increased by 1 day, while the changes in the duration of heat waves have been less significant. The greatest changes in temperature have been observed for strong thaws and frost waves (increase of up to 0.8°C). Heat waves are characterized by a decrease in the average duration by 1 day and the smallest temperature changes, because due to increase in average values, summer temperatures got closer to thresholds for a heat wave. Despite the effect of modern warming, frost waves remain the most intense type of extreme temperature episodes in Belarus. The spatial distribution of temperatures during heat and cold waves is either uniform or determined by seasonal temperature gradients.

Climate and ecology predict latitudinal trends in sexual selection inferred from avian mating systems.

Sexual selection, one of the central pillars of evolutionary theory, has powerful effects on organismal morphology, behaviour, and population dynamics. However, current knowledge about geographical variation in this evolutionary mechanism and its underlying drivers remains highly incomplete, in part because standardised data on the strength of sexual selection is sparse even for well-studied organisms. Here, we use information on mating systems-including the incidence of polygamy and extra-pair paternity-to estimate the intensity of sexual selection in 10,671 (>99.9%) bird species distributed worldwide. We show that avian sexual selection varies latitudinally, peaking at higher latitudes, although the gradient is reversed in the world's most sexually selected birds-specialist frugivores-which are strongly associated with tropical forests. Phylogenetic models further reveal that the strength of sexual selection is explained by temperature seasonality coupled with a suite of climate-associated factors, including migration, diet, and territoriality. Overall, these analyses suggest that climatic conditions leading to short, intense breeding seasons, or highly abundant and patchy food resources, increase the potential for polygamy in birds, driving latitudinal gradients in sexual selection. Our findings help to resolve longstanding debates about spatial variation in evolutionary mechanisms linked to reproductive biology and also provide a comprehensive species-level data set for further studies of selection and phenotypic evolution in the context of global climatic change.

Distinct Ecological Habits and Habitat Responses to Future Climate Change in Two Subspecies of Magnolia sieboldii K. Koch, a Tree Endemic to East Asia

Magnolia sieboldii, an important ornamental tree native to East Asia, comprises two subspecies in distinct regions, with wild populations facing suboptimal survival. This study aimed to understand the potential habitat distribution of these subspecies under future climate-change conditions to support climate-adaptive conservation. The maximum entropy (MaxEnt) model was used with occurrence and environmental data to simulate the current and future suitable habitats under various climate scenarios. Precipitation in the warmest quarter played a crucial role in shaping the potential habitats of both subspecies; however, they exhibited different sensitivities to temperature-related variables and altitude. Magnolia sieboldii subsp. sieboldii is more sensitive to temperature seasonality and annual mean temperature, whereas Magnolia sieboldii subsp. japonica is more affected by altitude, mean temperature in the driest quarter, and isothermality. Currently, the subsp. sieboldii is predicted to have larger, more contiguous suitable habitats across northeastern China, the Korean Peninsula, and Japan, whereas the subsp. japonica occupies smaller, more disjunct habitats scattered in central and western Japan and the southern Chinese mountains. These two subspecies will respond differently to future climate change. Potentially suitable habitats for subsp. sieboldii are expected to expand significantly northward over time, especially under the SSP585 scenario compared with the SSP126 scenario. In contrast, moderately and highly suitable habitats for the subsp. japonica are projected to contract southward significantly. Therefore, we recommend prioritizing the conservation of the subsp. japonica over that of the subsp. sieboldii. Strategies include in situ and ex situ protection, introduction and cultivation, regional hybridization, and international cooperation. Our study offers valuable insights for the development of targeted conservation strategies for both subspecies of M. sieboldii to counteract the effects of climate change.

Climate change alters the future of natural floristic regions of deep evolutionary origins

Biogeographic regions reflect the organization of biotas over long evolutionary timescales but face alterations from recent anthropogenic climate change. Here, we model species distributions for 189,269 vascular plant species of the world under present and future climates and use this data to generate biogeographic regions based on phylogenetic dissimilarity. Our analysis reveals declines in phylogenetic beta diversity for years 2040 to 2100, leading to a future homogenization of biogeographic regions. While some biogeographic boundaries will persist, climate change will alter boundaries separating biogeographic realms. Such boundary alterations will be determined by altitude variation, heterogeneity of temperature seasonality, and past climate velocity. Our findings suggest that human activities may now surpass the geological forces that shaped floristic regions over millions of years, calling for the mitigation of climate impacts to meet international biodiversity targets.

Predicting the Global Potential Suitable Areas of Sweet Osmanthus (Osmanthus fragrans) Under Current and Future Climate Scenarios.

Osmanthus fragrans is a valuable landscaping tree that is appreciated worldwide. However, the optimal environmental conditions for O. fragrans cultivation have yet to be studied in detail, which hinders the preservation of wild resources of this plant and its commercial exploitation. The maximum entropy model was applied to assess the significance of environment variables influencing O. fragrans distribution. Combining data from 629 global distribution points for O. fragrans, predictions were made on the potential effects of climate change on the geographical distribution of suitable habitats for this species in the present and the future. The results indicated that O. fragrans preferred a warm and humid growing environment. Under the current climatic conditions, the potential habitats for O. fragrans were mostly located in the eastern coastal areas of the continents at medium and low latitudes. The main environmental variables that affected its distribution were the precipitation during the warmest quarter, the temperature seasonality, and the mean temperature of the warmest quarter. The analysis indicated that the continuation of current trends in climate change will result in the further reduction of suitable habitats for O. fragrans growth, and the global centroid will shift to the southeast. These findings provided insight into the impact of climate change on O. fragrans habitats, as well as provide guidance for the conservation of wild resources of this species and the breeding of more climate change-resistant varieties for the future.

Discussion of “Effects of Traffic Loading on Seasonal Temperature Change-Induced Problems for Integral Bridge Approaches and Mitigation with Geosynthetic Reinforcement”

Discussion of “Effects of Traffic Loading on Seasonal Temperature Change-Induced Problems for Integral Bridge Approaches and Mitigation with Geosynthetic Reinforcement”

The Self‐Calibrating Tilt Accelerometer: A Method for Observing Tilt and Correcting Drift With a Triaxial Accelerometer

AbstractWe present observations from two field deployments of a calibrated tiltmeter that we name the Self‐Calibrating Tilt Accelerometer (SCTA). The tiltmeter is based upon a triaxial quartz crystal accelerometer; the horizontal channels measure tilt and are periodically rotated into the vertical to obtain a measurement of the acceleration of gravity. Changes in the measured total acceleration are ascribed to drift in the vertical channel and used as calibrations for removing that same drift from the tilt time series observed between calibrations. Changes in the span (sensitivity) of the accelerometer channels can also be measured by calibrating them pointing up and down. A 3‐year test on the seafloor at Axial Seamount show that the calibrations are consistent with a linear‐exponential model of drift to a RMS residual of ∼0.5 μg (μrad). The calibrated tilt time series was impacted by platform settling for the first 2 years, but after repositioning the tiltmeter, the calibrated observations were consistent for the final year with the tilt observed on a nearby LILY tiltmeter, within an assumed level of drift for the unconstrained LILY sensor. A separate 15‐month test in a stable vault at Piñon Flat Observatory was complicated by seasonal temperature variations of >5°C; the calibrations are consistent with a linear‐exponential model of drift to ∼2 μg RMS when temperature and temperature time‐derivative dependence is included. Similarly, the calibrated tilt time series was impacted by thermal deformation of the SCTA assembly. A future test in a thermally and tectonically stable borehole will be required to assess the accuracy of the SCTA.

Seasonal and Climatic Drivers of Wet Deposition Organic Matter at the Continental Scale

AbstractDissolved organic matter (DOM) concentrations and composition within wet deposition are rarely monitored despite contributing a large input of bioavailable dissolved organic carbon (DOC) and nitrogen (DON) to the Earth's surface. Lacking from the literature are spatially comprehensive assessments of simultaneous measurements of wet deposition DOC and DON chemistry and their dependencies on metrics of climate and environmental factors. Here, we use archived precipitation samples from the US National Atmospheric Deposition Program collected in 2017 to 2018 from 17 sites across six ecoregions to investigate variability in the concentration and composition of depositional DOM. We hypothesize metrics of DOM chemistry vary with ecoregion, season, large‐scale climate drivers, and precipitation geographic source. Findings indicate differences in DOC and DON concentrations and loads among ecoregions. The highest wet deposition concentrations are from sites in the Northern Forests and lowest concentrations from sites in Marine West Coast Forests. Summer and autumn samples contained the highest DOC concentrations and DON concentrations that were consistently above detection limit, corresponding with seasonality of peak air temperatures and the phenology of the growing season in the northern hemisphere. Compositional trends suggest lighter DOM molecules in autumn and winter and heavier molecules in spring and summer. Climate drivers explain 51% of variation in DOM chemistry, revealing differing drivers on the concentrations and loads of DOC versus DON in wet deposition. This study highlights the necessity of incorporating DOC and DON measurements into national deposition monitoring networks to understand spatial and temporal feedbacks between climate change, atmospheric chemistry and landscape biogeochemistry.

Using rare event algorithms to understand the statistics and dynamics of extreme heatwave seasons in South Asia

Abstract Computing the return times of extreme events and assessing the impact of climate change on such return times is fundamental to extreme event attribution studies. However, the rarity of such events in the observational record makes this task a challenging one, even more so for ‘record-shattering’ events that have not been previously observed at all. While climate models could be used to simulate such extremely rare events, such an approach entails a huge computational cost: gathering robust statistics for events with return time of centuries would require a few thousand years of simulation. In this study, we use an innovative tool, rare event algorithm, that allows us to sample numerous extremely rare events at a much lower cost than direct simulations. We employ the algorithm to sample extreme heatwave seasons, corresponding to large anomalies of the seasonal average temperature, in a heatwave hotspot of South Asia using the global climate model Plasim. We show that the algorithm estimates the return levels of extremely rare events with much greater precision than traditional statistical fits. It also enables the computation of various composite statistics, whose accuracy is demonstrated through comparison with a very long control run. In particular, our results reveal that extreme heatwave seasons are associated with an anticyclonic anomaly embedded within a large-scale hemispheric quasi-stationary wave-pattern. Additionally, the algorithm accurately represents the intensity-duration-frequency statistics of sub-seasonal heatwaves, offering insights into both seasonal and sub-seasonal aspects of extreme heatwave seasons. This innovative approach could be used in extreme event attribution studies to better constrain the changes in an event’s probability and intensity with global warming, particularly for events with return times spanning centuries or millennia.

Macro- and micro-geographic genetic variation in early fitness traits in populations of maritime pine (Pinus pinaster Ait.).

Assessing adaptive genetic variation and its spatial distribution is crucial to conserve forest genetic resources and manage species' adaptive potential. Macro-environmental gradients commonly exert divergent selective pressures that enhance adaptive genetic divergence among populations. Steep micro-environmental variation might also result in adaptive divergence at finer spatial scales, even under high gene flow, but it is unclear how often this is the case. Here, we assess genetic variation in early fitness traits among distant and nearby maritime pine (Pinus pinaster Ait.) populations, to investigate climatic factors associated with trait divergence, and to examine trait integration during seedling establishment. Open pollinated seeds were collected from seven population pairs across the European species distribution, with paired populations spatially close (between <1 km up to 21 km) but environmentally divergent. Seeds were sown in semi-natural conditions at three environmentally contrasting sites, where we monitored seedling emergence, growth and survival. At large spatial scales, we found significant genetic divergence among populations in all studied traits, with certain traits exhibiting association with temperature and precipitation gradients. Significant trait divergence was also detected between pairs of nearby populations. Besides, we found consistent trait correlations across experimental sites, notably heavier seeds and earlier seedling emergence were both associated with higher seedling survival and fitness over two years in all experimental conditions. We identified mean annual temperature and precipitation seasonality as potential drivers of P. pinaster population divergence in the studied early-life traits. Populations genetically diverge also at local spatial scales, potentially suggesting that divergent natural selection can override gene flow along local-scale ecological gradients. These results suggest the species exhibits substantial adaptive potential that has allowed it to survive and evolve under contrasting environmental conditions.

Seed ecology of the arid zone invasive thistle; Centaurea melitensis L.: A study of the effects of seasonal temperature, pH, salinity and moisture stress

AbstractCentaurea melitensis L., known commonly as Malta thistle, is an aggressive and invasive weed species native to the Mediterranean region. This species now occupies a diverse range of ecosystems and climate types across the globe, including the semi‐arid zone of New South Wales, Australia. This semi‐arid climate differs dramatically from its native Mediterranean climate, therefore, we aimed to identify if local adaptations in the seed ecology for C. melitensis have developed. Seeds were collected from mature C. melitensis at Nanya Station, located within the Scotia region of NSW, and then transported to Federation University Australia, Mt. Helen, Victoria. Under laboratory conditions, mature seeds were tested for their germination responses to temperature (17/7, 25/15, 30/20, 35/25°C), photoperiod (12 h light and 12 h dark [L/D], 24 h dark [D]), salinity (0, 25, 50, 100, 150, 200, and 250 mM), osmotic potential (0, −0.1, −0.2, −0.4, −0.6, and −0.8 MPa), and pH (5, 6, 6.2, 7, 8, 9, and 10). The seeds achieved 100% germination in the 17/7°C treatment, with light not being a limiting factor. The seeds exposed to the 25/15°C (D) and 30/20°C (D) treatments also maintained high germination percentage, whilst germination was significantly reduced in the 35/25°C (D) treatment. The L/D photoperiod maintained a 77.5% germination rate at 35/25°C. Whilst increased salinity reduced seed germination from 97.5% in the control to 6% at 250 mM, this species nevertheless demonstrated resistance to osmotic stress with 23% germination observed at 0.8 MPa. Germination exceeded 90% at all of the soil pH treatments, although mean germination time was significantly reduced when seeds were treated with a solution of pH 10. Our results demonstrate that the C. melitensis seeds collected in Australia's semi‐arid zone demonstrated high germination plasticity and are capable of competitive germination in warmer and drier conditions compared to its native Mediterranean climate. Therefore, management efforts that prioritise restricting the spread of C. melitensis seeds into new environments, for example through practising correct sanitation protocols, coupled with the early detection and control of emerging populations will be critical for C. melitensis management in Australia.

Non-adaptedness and vulnerability to climate change threaten Plathymenia trees (Fabaceae) from the Cerrado and Atlantic Forest

Climate change is increasing species extinction risk. The ability of a species to cope with climate change can be quantified by projecting distribution models and by estimating the risk of non-adaptedness using genomic data. The Cerrado and the Atlantic Forest in Tropical South America are increasingly threatened by habitat loss and anthropogenic climate change. This work aims to evaluate the ecological and genomic vulnerability of Plathymenia taxa and its lineages, P. reticulata, a Cerrado species, and P. foliolosa, an Atlantic Forest species, to determine their current and future habitat suitability and the mismatch between current local adaptation with the expected climate changes. The species distribution models predicted a high range loss for the Plathymenia lineages. The genotype-environment association analyses showed that the Plathymenia lineages have populations adapted to different precipitation and temperature seasonality regimes. The genomic offset analyses predict a mismatch between local adaptations and future climate for the Plathymenia indicating a high risk of non-adaptedness, especially in the pessimistic scenario. Our results show an elevated extinction risk of the species due to climate change. We suggest reevaluating the extinction risk and management of the Plathymenia species separately based on their differences in vulnerability to climate change.

Analysis of Macro- and Microphysical Characteristics of Ice Clouds over the Tibetan Plateau Using CloudSat/CALIPSO Data

Utilizing CloudSat/CALIPSO satellite data and ERA5 reanalysis data from 2007 to 2016, this study analyzed the distributions of optical and physical characteristics and change characteristics of ice clouds over the Tibetan Plateau (TP). The results show that the frequency of ice clouds in the cold season (November to March) on the plateau is over 80%, while in the warm season (May to September) it is around 60%. The average cloud base height of ice clouds in the warm season is 3–5 km, and mostly around 2 km in the cold season. The average cloud top height in the warm season is around 5–8 km, while in the cold season it is mainly around 4.5 km. The average thickness of ice clouds in both seasons is around 2 km. The statistical results of microphysical characteristics show that the ice water content is around 10−1 to 103 mg/m3, and the effective radius of ice clouds is mainly in the range of 10–90 μm. Both have their highest frequency in the west of the TP and lowest in the northeast. A comprehensive analysis of the change in temperature, water vapor, and ice cloud occurrence frequency shows that the rate of increase in water vapor in the warm season is greater than that in the cold season, while the rates of increase in both surface temperature and ice cloud occurrence are smaller than in the cold season. The rate of increase in temperature in the warm season is around 0.038 °C/yr, and that in the cold season is around 0.095 °C/yr. The growth rate of thin ice clouds in the warm season is around 0.15% per year, while that in the cold season is as high as 1% per year. The results suggest that the surface temperature change may be related to the occurrence frequency of thin ice clouds, with the notable increase in temperature during the cold season possibly being associated with a significant increase in the occurrence frequency of thin ice clouds.

Impact of ocean vertical-mixing parameterization on Arctic sea ice and upper-ocean properties using the NEMO-SI3 model

Abstract. We evaluate the vertical turbulent-kinetic-energy (TKE) mixing scheme of the NEMO-SI3 ocean–sea-ice model in sea-ice-covered regions of the Arctic Ocean. Specifically, we assess the parameters involved in TKE mixed-layer-penetration (MLP) parameterization. This ad hoc parameterization aims to capture processes that impact the ocean surface boundary layer, such as near-inertial oscillations, ocean swells, and waves, which are often not well represented in the default TKE scheme. We evaluate this parameterization for the first time in three regions of the Arctic Ocean: the Makarov, Eurasian, and Canada basins. We demonstrate the strong effect of the scaling parameter that accounts for the presence of sea ice. Our results confirm that TKE MLP must be scaled down below sea ice to avoid unrealistically deep mixed layers. The other parameters evaluated are the percentage of energy penetrating below the mixed layer and the length scale of its decay with depth. All these parameters affect mixed-layer depth and its seasonal cycle, surface temperature, and salinity, as well as underlying stratification. Shallow mixed layers are associated with stronger stratification and fresh surface anomalies, and deeper mixed layers correspond to weaker stratification and salty surface anomalies. Notably, we observe significant impacts on sea-ice thickness across the Arctic Ocean in two scenarios: when the scaling parameter due to sea ice is absent and when the TKE mixed-layer-penetration process vanishes. In the former case, we observe an increase of several meters in mixed-layer depth, along with a reduction in sea-ice thickness ranging from 30 to 40 cm, reflecting the impact of stronger mixing. Conversely, in the latter case, we notice that a shallower mixed layer is accompanied by a moderate increase in sea-ice thickness, ranging from 10 to 20 cm, as expected from weaker mixing. Additionally, interannual variability suggests that experiments incorporating a scaling parameter based on sea-ice concentration display an increased mixed-layer depth during periods of reduced sea ice, which is consistent with observed trends. These findings underscore the influence of enhanced ocean mixing, through specific parameterizations, on the physical properties of the upper ocean and sea ice.

Gastrointestinal morphology is an effective functional dietary proxy that predicts small mammal community structure.

The availability and quality of food resources can alter the intensity of competition and predation pressure within communities. Understanding species capacity to respond to global change-driven shifts in resource distribution is therefore crucial for biodiversity conservation. Small mammal communities are often structured by competition for food resources, but understanding and monitoring these processes are currently hindered by lack of functional dietary trait information in these hard-to-sample systems. In this study, we collected a comprehensive suite of gastrointestinal (GI) measurements from 26 small mammal species (including some never reported), compared them with more traditional craniodental traits in predicting dietary guild, and used them in a novel way to understand how diet structures 22 small mammal communities across the Appalachian Mountains of eastern North America. As predicted, we found GI traits to be effective dietary trait proxies; they were equally or more accurate than craniodental proportions in predicting the dietary guild of individual species. Furthermore, at the community level, we found that both the mean and functional dispersion of GI length were positively correlated with latitude and measures of temperature seasonality. Our results indicate that small mammal communities in more seasonal environments are filtered to include species with longer GI tracts (on average) as well as those that can partition food resources more finely, as expected based on the lower productivity of these regions. Conversely, communities in less seasonal environments display functional redundancy from the addition of species with short to intermediate GI lengths. Proportions of the GI tract represent novel dietary traits that can illuminate community assembly processes across regional environmental gradients and in the face of changing timing and availability of resources.

Statistical-empirical pavement temperature prediction models based on data from road weather stations in Estonia

Asphalt pavement properties are greatly affected by seasonal temperature variation. Binder grade selection needs to be aligned with forecasted operational pavement temperatures to maximise pavement longevity. Different widely adopted models for determining binder Superpave Performance Grading have been shown to provide inaccurate results for the Nordic-Baltic region, leading to under- or overestimation of operational pavement temperatures and erroneous selection of a suitable binder grade. This study proposes empirically formulated pavement temperature prediction models for Estonia based on temperature data collected from six different road weather stations in Estonia from 2019 to 2023. Models were derived using measurements from daily maximum and minimum air temperatures combined with pavement temperature profiles with depth.

Prediction of the potential distribution of a raspberry (Rubus idaeus) in China based on MaxEnt model

Rubus idaeus is a pivotal cultivated species of raspberry known for its attractive color, distinct flavor, and numerous health benefits. It can be used in pharmaceutical, cosmetics, agriculture and food industries not only as fresh but also as a processed product. Nowadays due to climatic changes, genetic diversity of cultivars has decreased dramatically. However, until now, the status of wild R. idaeus resources in China have not been exploited. In this study, we investigated the resources of wild R. idaeus in China to secure its future potential and sustainability. The MaxEnt model was used to predict R. idaeus suitable habitats and spatial distribution patterns for current and future climate scenarios, based on wild domestic geographic distribution data, current and future climate variables, and topographic variables. The results showed that, mean temperature of the coldest quarter (bio11), precipitation of the coldest quarter (bio19), precipitation of the warmest quarter (bio18), and temperature seasonality (bio4) were crucial factors affecting the distribution of R. idaeus. Presently, the suitable habitats were mainly distributed in the north of China including Xinjiang, Inner Mongolia, Gansu, Ningxia, Shaanxi, Shanxi, Hebei, Beijing, Liaoning, Jilin, Heilongjiang. According to our results, in 2050s, the total suitable habitat area of R. idaeus will increase under SSP1-2.6 and then will be decreased with climate change, while in the 2090s, the total suitable habitat area will continue to decrease. From the present to the 2090s, the centroid distribution of R. idaeus in China will shift towards the east and the species will always be present in Inner Mongolia. Our results provide wild resource information and theoretical reference for the protection and rational utilization of R. idaeus.