Monthly Temperature Research Articles

Impact of seasonality on the reproductive physiology of diploid and tetraploid eastern oyster, Crassostrea virginica

Aquaculture production of triploid Eastern oyster, Crassostrea virginica, in the Gulf of Mexico (GoM) is reliant on naturally conditioned diploid females and tetraploid males. However, limited knowledge is available on their reproductive biology, including the gametogenic cycle. The aim was to quantify monthly changes in gametogenesis and gamete quality for triploid production in Eastern oyster in the GoM from June 2022 to July 2023. Monthly changes in temperature and salinity were recorded. Shell morphometrics and sex were determined. Sperm density, sperm activity, Spermatogenic Maturity Index (SMI), oocyte diameter, Oogenesis Maturity Index (OMI), and gonad coverage area were quantified. Mean monthly temperature ranged from 15.1 to 31.2 °C and salinity ranged from 12.5 to 27.6 PSU. Shell morphometrics increased over the annual cycle. When gametes were detectable, 48–80% of tetraploids and 45–70% of diploids were males. Hermaphrodites were identified in both ploidies in June; an additional tetraploid hermaphrodite was identified in March. Sperm density exhibited monthly fluctuations with high densities reported in June–July, September, and April–May. Sperm were motile when present, with high motility in June–July. High sperm velocity was also recorded in June–July and March–May. Tetraploids exhibited high SMI from June–September and April–May with increased variability in December–January. Mature sperm cells were predominant in tetraploids in June–July. Gonadal coverage was high from June–September and March–May. OMI was highest from June–September and March–May, while variability was high from August–March. Large oocyte diameters and gonad coverage areas were observed in June–July, September, and April–May. Together, these findings provide novel insights into reproductive dynamics for triploid production of Eastern oyster in GoM.

Interrelationships and Environmental Influences of Photosynthetic Capacity and Hydraulic Conductivity in Desert Species Populus pruinosa

An improved understanding of the mechanisms underlying plant adaptation to habitat heterogeneity can be achieved by clarifying the climate-driving factors of the hydraulic and photosynthetic traits of different populations. With a focus on Populus pruinosa Schrenk, which is the predominant tree species in the desert riparian forests of the Tarim Basin, Xinjiang, this study investigated the hydraulic and photosynthetic trait relationships and their interactions with environmental factors in 11 P. pruinosa populations using a Pearson correlation analysis, plant trait networks, a redundancy analysis, and a least squares linear regression analysis. The results showed that the degree of variation in the hydraulic traits was higher than that in the photosynthetic traits. The net photosynthetic rate (Pn) showed a significantly positive correlation with leaf-specific conductivity (Kl) and the Huber value (Hv). The Hv exhibited a significantly positive correlation with the water-use efficiency and Kl, and the branch–leaf mass ratio significantly affected the hydraulic traits. The groundwater depth (GD) in natural P. pruinosa forest habitats ranged from 3.4 to 7.9 m. With an increase in the annual average temperature, the hydraulic conductivity of the xylem significantly increased; with an increase in GD, Pn and Kl significantly decreased. The temperature annual range, temperature seasonality (standard deviation), min temperature of the coldest month, and GD were significantly correlated with the diameter and average path length of the overall trait network parameters, and these environmental factors affected the coordination of the functional traits of P. pruinosa.

Влияние основных показателей теплообеспеченности на сельское хозяйство Саратовской области

An analysis of changes in surface air temperature was carried out at stations in the Saratov region from 2002 to 2022. The study is based on the analysis of materials from longterm hydrometeorological observations carried out through the Roshydromet network, which reflects the reliability of the results obtained. The article presents a comparison of average monthly temperatures for a given period with temperature norms. A map of temperature changes was constructed. The duration of the growing season for plants was calculated and analyzed. With the help of agroclimatic zoning of the country according to D. I. Shashko there was established which zone the Saratov region belongs to and which agricultural crops are best cultivated in the region.

Interspecific interaction network of mites associated with mango trees.

Direct and indirect ecological interactions, environmental factors, and the phenology of host plants can shape the way mites interact. These relationships interfere with species occurrence and consequently alter the structure and stability of the intraplant community. As predatory mites act as regulators of herbivorous mites, we hypothesized that these mites may occupy a central position in a network of interactions among mite species associated with mango trees, and the occurrence of these species is mediated by environmental variables and the phenological stage of the host plant. We evaluated the global structure of the interaction network of mites associated with individual Mangifera indica plants and analyzed the interspecific relationships of the species using an undirected Bayesian network approach. Additionally, we observed a correlation between mite population density and plant phenological stage. Environmental variables, such as average monthly temperature, monthly precipitation, and average monthly relative humidity at different sampling date were used in the correlation analysis. The modularity at the mite-plant network level showed a low specialization index H2 = 0.073 (generalist) and high robustness (R = 0.93). Network analysis revealed that Amblyseius largoensis, Bdella ueckermanni, Parapronematus acaciae, and Tuckerella ornata occupied central positions in the assembly of mites occurring on mango trees. Environmental variables, average monthly temperature, and monthly precipitation were correlated with the occurrence of Brachytydeus formosa, Cisaberoptus kenyae, Oligonychus punicae, T. ornata, and Vilaia pamithus. We also observed a correlation between the plant phenological stage and population densities of Neoseiulus houstoni, O. punicae, P. acaciae, and V. pamithus.

Schistosomiasis transmission in Zimbabwe: Modelling based on machine learning

Zimbabwe, located in Southern Africa, faces a significant public health challenge due to schistosomiasis. We investigated this issue with emphasis on risk prediction of schistosomiasis for the entire population. To this end, we reviewed available data on schistosomiasis in Zimbabwe from a literature search covering the 1980-2022 period considering the potential impact of 26 environmental and socioeconomic variables obtained from public sources. We studied the population requiring praziquantel with regard to whether or not mass drug administration (MDA) had been regularly applied. Three machine-learning algorithms were tested for their ability to predict the prevalence of schistosomiasis in Zimbabwe based on the mean absolute error (MAE), the root mean squared error (RMSE) and the coefficient of determination (R2). The findings revealed different roles of the 26 factors with respect to transmission and there were particular variations between Schistosoma haematobium and S. mansoni infections. We found that the top-five correlation factors, such as the past (rather than current) time, unsettled MDA implementation, constrained economy, high rainfall during the warmest season, and high annual precipitation were closely associated with higher S. haematobium prevalence, while lower elevation, high rainfall during the warmest season, steeper slope, past (rather than current) time, and higher minimum temperature in the coldest month were rather related to higher S. mansoni prevalence. The random forest (RF) algorithm was considered as the formal best model construction method, with MAE = 0.108; RMSE = 0.143; and R2 = 0.517 for S. haematobium, and with the corresponding figures for S. mansoni being 0.053; 0.082; and 0.458. Based on this optimal model, the current total schistosomiasis prevalence in Zimbabwe under MDA implementation was 19.8%, with that of S. haematobium at 13.8% and that of S. mansoni at 7.1%, requiring annual MDA based on a population of 3,003,928. Without MDA, the current total schistosomiasis prevalence would be 23.2%, that of S. haematobium 17.1% and that of S. mansoni prevalence at 7.4%, requiring annual MDA based on a population of 3,521,466. The study reveals that MDA alone is insufficient for schistosomiasis elimination, especially that due to S. mansoni. This study predicts a moderate prevalence of schistosomiasis in Zimbabwe, with its elimination requiring comprehensive control measures beyond the currently used strategies, including health education, snail control, population surveillance and environmental management.

Analysis of a Plant’s Response to Climate Change Factors Through the Use of Herbarium Records: Collinsia violacea Nutt. (Plantaginaceae).

Climate change has resulted in various changes to the phenology of species, and some of these changes have been documented through the use of herbarium specimens. Understanding how plants react to changes in the environment can give scientists insight into how plants have been responding and will respond to the continuing consequences of climate change as well as how to approach biodiversity conservation. In this study, herbarium records of Collinsia violacea Nutt. ranging from 1895 to 2014 were utilized to show the trends of the first and peak flowering dates with regard to various geographic and climatic variables using regression analysis. The results from simple linear regression analyses showed a trend of the flowering times for first and peak flowering dates occurring earlier over the years; however, the relationship was not significant. The multiple linear regression full model for first flowering indicated increases in latitude, longitude, and mean monthly temperatures were associated with delayed flowering while increases in monthly minimum and maximum temperatures were associated with earlier flowering. The full model for peak flowering showed that peak flowering was delayed with increases in latitude, longitude, and maximum monthly temperature. The reduced models, with highly correlated variables removed, indicated significant delays in first flowering and peak flowering with increases in latitude, longitude, and mean monthly temperature, but no significant relationship between monthly precipitation and flowering time. Further research is needed to fully understand the implications of these changes.

Potential distribution prediction of Ceracris kiangsu Tsai in China

Ceracris kiangsu Tsai (C. kiangs) is a kind of forest pest, which can harm nearly 100 kinds of weeds and crops. In this study, based on 314 species distribution points of C. kiangsu which were obtained from Chinese herbaria, literatures and investigation, and data of three future climate scenarios presented by CMIP6, two niche models (Garp, Maxent) were used to predict the suitable area of C. kiangsu in China. The result shows that the main environmental factors affecting the distribution of C. kiangsu are precipitation of driest month (bio14) and min temperature of coldest month (bio6). No matter now and future, the potential distribution areas of C. kiangsu in China are mainly in the south of Qinling–Huaihe River. Under current scenarios, the areas of the total, highly, moderately and poorly suitable of C. kiangsu in China are 160.65 × 104 km2, 31.70 × 104 km2, 60.36 × 104 km2 and 68.59 × 104 km2 respectively. The southern Hubei, western Jiangxi and eastern Hunan are highly-suitable areas. Under SSP1-2.6 and SSP2-4.5 scenarios, both the total suitable area and the highly suitable show a decreasing tread in 2050s. Compared to the 2050s, the total suitable area will coninue to decease in 2090s under SSP1-2.6, while it will increase under SSP2-4.5. The highly suitable area will increase in both scenarios, and the increased percentage under SSP2-4.5 is greater than that under SSP1-2.6. Under SSP5-8.5 scenarios, the total suitable area will increase by 1.83% in the 2050s, and decrease by 1.17% in the 2090s. The highly suitable area in the 2050s and 2090s under this scenarios is larger than under current scenarios. No matter what the scenario, the southern part of Yunnan, the southeast of Sichuan and the southwest of Chongqing will become highly-suitable areas as the climate continues to warm and should be monitored more cosely.

Predicting the Impact of Climate Change on the Future Distribution of Paederus fuscipes Curtis, 1826, in China Based on the MaxEnt Model.

Paederus fuscipes Curtis, 1826, belongs to the Coleoptera order, Staphylinidae family, and Paederus genus (Fabricius, 1775). It has a wide distribution and strong invasive and environmental adaptation capabilities. As a predatory natural enemy of agricultural and forestry pests, understanding its suitable habitat is crucial for the control of other pests. This study, for the first time, uses the MaxEnt model and ArcGIS software, combining known distribution information of P. fuscipes and climate environmental factors to predict the current and future suitable habitat distribution of this insect. The key environmental variables affecting the distribution of P. fuscipes have been identified as mean diurnal range (mean of monthly (max temp-min temp)) (bio2), isothermality (Bio2/Bio7) (*100) (bio3), minimum temperature of the coldest month (bio6), temperature annual range (bio5-bio6) (bio7), mean temperature of the driest quarter (bio9), mean temperature of the coldest quarter (bio11), precipitation of the wettest month (bio13), precipitation of the driest month (bio14), and precipitation seasonality (coefficient of variation) (bio15). The highly suitable areas for P. fuscipes in China are mainly distributed in the hilly regions of Shandong, the North China Plain, and the middle and lower reaches of the Yangtze River Plain, with a total suitable area of 118.96 × 104 km2, accounting for 12.35% of China's total area. According to future climate change scenarios, it is predicted that the area of highly and lowly suitable regions will significantly decrease, while moderately suitable regions will increase (except for the 2090s, SSP2-4.5 scenario). These research findings provide important theoretical support for pest control and ecological conservation applications.

Distribution patterns of Phytoseiulus persimilis in response to climate change.

The biological control agent Phytoseiulus persimilis is a commercialized specialist predator of two agricultural pest mite species Tetranychus urticae and Tetranychus evansi. Biocontrol of these pest species by P. persimilis has achieved success in biological control in some areas. However, the lack of precise information about the influence of global climate change on the worldwide distribution of this biocontrol agent hampers international efforts to manage pest mites with P. persimilis. With 276 occurrence records and 19 bioclimatic variables, this study investigated the potential global distribution of P. persimilis. The results demonstrated that the Maximum Entropy (MaxEnt) model performed well, with the area under the curve being 0.956, indicating the high accuracy of this model. Two variables, the minimum temperature of the coldest month (Bio_6) and precipitation of the coldest quarter (Bio_19) were the most important environmental variables that influenced the distribution of P. persimilis, contributing more than 30% to the model, respectively. The suitable area currently occupies 21.67% of the world's land area, spanning latitudes between 60°S and 60°N. Under shared socio-economic pathway (SSP) 5-8.5 (high-carbon emissions), the low suitable area would increase by 1.31% until the 2050s. This study successfully identified that south-eastern China, parts of countries in the Mediterranean coastal regions, including Libya, Algeria, Portugal, Spain, and France, are climatically favorable regions for P. persimilis, providing valuable information about the potential areas where it can be effectively exploited as biocontrol agents in classical biological control programs to manage pest spider mites environmentally friendly. © 2024 Society of Chemical Industry.

Response of the functional traits of Schoenoplectus tabernaemontani to simulated warming in the Napahai wetland of northwestern Yunnan, China

The impact of climate warming on wetland ecosystems is a current focal point in ecological research. In this study, the Napahai wetland, a typical plateau wetland in northwest Yunnan Province, was selected as the study site to understand the growth and survival strategies of emergent plants in a plateau wetland under climate warming conditions. Open-top chambers (OTCs) were used to simulate warming in three treatments (i.e., control group, 2.0 ± 0.5°C, and 4.0 ± 0.5°C) in order to study the responses of the functional traits of the dominant emergent plant Schoenoplectus tabernaemontani to simulated warming. The results showed that simulated warming significantly reduced the photosynthetic carbon assimilation capacity and biomass accumulation of S. tabernaemontani, as well as its nitrogen content and vascular bundle density, while it significantly increased the vascular bundle size. The growing season accumulated temperature (AT) and the mean temperature of the hottest month (WT) were the main temperature factors influencing the functional traits of S. tabernaemontani. In summary, simulated warming significantly affected the functional traits of S. tabernaemontani, which demonstrated effective adaptation to warming conditions. As the temperature rises and the light and productivity decrease, S. tabernaemontani prioritizes the supply of limited resources to the underground part to ensure the biomass supply of the reproductive structure. This study provides a case for revealing the response patterns and ecological adaptation strategies of plateau wetland plants to climate warming.

Prediction of Potential Distribution of Carposina coreana in China under the Current and Future Climate Change.

Carposina coreana is an important pest of Cornus officinalis, distributed in China, Korea, and Japan. In recent years, its damage to C. officinalis has become increasingly serious, causing enormous economic losses in China. This study and prediction of current and future suitable habitats for C. coreana in China can provide an important reference for the monitoring, early warning, prevention, and control of the pest. In this study, the potential distributions of C. coreana in China under current climate and future climate models were predicted using the maximum entropy (MaxEnt) model with ArcGIS software. The distribution point data of C. coreana were screened using the buffer screening method. Nineteen environmental variables were screened using the knife-cut method and variable correlation analysis. The parameters of the MaxEnt model were optimized using the kuenm package in R software. The MaxEnt model, combined with key environmental variables, was used to predict the distribution range of the suitable area for C. coreana under the current (1971-2000) and four future scenarios. The buffer screening method screened data from 41 distribution points that could be used for modeling. The main factors affecting the distribution of C. coreana were precipitation in the driest month (Bio14), precipitation in the warmest quarter (Bio18), precipitation in the coldest quarter (Bio19), the standard deviation of seasonal variation of temperature (Bio4), minimum temperature in the coldest month (Bio6), and average temperature in the coldest quarter (Bio11). The feature class (FC) after the kuenm package optimization was a Q-quadratic T-threshold combination, and the regularization multiplier (RM) was 0.8. The suitable areas for C. coreana under the current climate model were mainly distributed in central China, and the highly suitable areas were distributed in southern Shaanxi, southwestern Henan, and northwestern Hubei. The lowest temperature in the coldest month (Bio6), the average temperature in the coldest quarter (Bio11), and the precipitation in the warmest quarter (Bio18) all had good predictive ability. In future climate scenarios, the boundary of the suitable area for C. coreana in China is expected to shift northward, and thus, most of the future climate scenarios would shift northward.

Ecological Niche Differentiation and Response to Climate Change of the African Endemic Family Myrothamnaceae.

Studying the ecological niches of species and their responses to climate change can provide better conservation strategies for these species. Myrothamnaceae is endemic to Africa, comprising only two species that belong to Myrothamnus (M. flabellifolius and M. moschatus). These closely related species exhibit allopatric distributions, positioning them as ideal materials for studying the species ecological adaptation. This study explores the ecological niche differentiation between M. flabellifolius and M. moschatus and their response capabilities to future climate change. The results indicate that M. flabellifolius and M. moschatus have undergone niche differentiation. The main drivers of niche differences are the minimum temperature of the coldest month (Bio6) for M. flabellifolius, precipitation of the driest month (Bio14), and precipitation of the coldest quarter (Bio19) for M. moschatus. M. flabellifolius demonstrated a stronger adaptation to environments characterized by lower precipitation, relatively lower temperatures, and greater annual temperature variations compared to M. moschatus. Under future climate scenarios (SSP5-8.5, 2081-2100 years), the results show that approximately 85% of the total suitable habitat for M. flabellifolius will be lost, with an 85% reduction in high-suitability areas and almost complete loss of the original mid-low suitability areas. Concurrently, about 29% of the total suitable habitat for M. moschatus will be lost, with a 34% reduction in high suitability areas and roughly 60% of the original mid-low suitability areas becoming unsuitable. This suggests that M. flabellifolius will face greater threats under future climate change. This study contributes novel insight into niche differentiation in Myrothamnaceae and provides useful information for the conservation of this distinctive African lineage.

Membraneless and membrane-bound organelles in an anhydrobiotic cell line are protected from desiccation-induced damage.

Anhydrobiotic species can survive virtually complete water loss by entering a reversible ametabolic glassy state that may persist for years in ambient conditions. The Pv11 cell line was derived from the egg mass of the anhydrobiotic midge, Polypedilum vanderplanki, and is currently the only available anhydrobiotic cell line. Our results demonstrate that the necessary preconditioning for Pv11 cells to enter anhydrobiosis causes autophagy and reduces mitochondrial respiration by over 70%. We speculate that reorganizing cellular bioenergetics to create and conserve energy stores may be valuable to successfully recover after rehydration. Furthermore, mitochondria in preconditioned cells lose their membrane potential during desiccation but rapidly restore it within 30min upon rehydration, demonstrating that the inner mitochondrial membrane integrity is well-preserved. Strikingly, the nucleolus remains visible immediately upon rehydration in preconditioned cells while absent in control cells. In contrast, a preconditioning-induced membraneless organelle reformed after rehydration, demonstrating that membraneless organelles in Pv11 cells can be either stabilized or recovered. Staining the endoplasmic reticulum and the Golgi apparatus revealed that these organelles fragment during preconditioning. We hypothesize that this process reduces sheering stress caused by rapid changes in cellular volume during desiccation and rehydration. Additionally, preconditioning was found to cause the filamentous-actin (F-actin) network to disassemble significantly and reduce the fusion of adjacent plasma membranes. This study offers several exciting avenues for future studies in the animal model and Pv11 cell line that will further our understanding of anhydrobiosis and may lead to advancements in storing sensitive biologics at ambient temperatures for months or years.

COMPONENT COMPOSITION OF ARTEMISIA SANTOLINIFOLIA TURCZ EX BESS. ESSENTIAL OIL

Purpose. To conduct a comparative analysis of the qualitative composition and quantitative content of components of essential oils isolated from different organs of Artemisia santolinofolia, and also to study the influence of weather conditions on the accumulation and composition of essential oils. Material and methods. The object of the study is the aerial part of A. santolinifolia, collected in the Okinsky district of the Republic of Buryatia during the flowering phase, in August 2016, 2017, 2019. Essential oils were isolated by hydrodistillation. The component composition was determined by chromatography-mass spectrometry with an Agilent Packard HP 6890 gas chromatograph with a quadrupole mass spectrometer (HP MSD 5973N). Results. The highest content of essential oils is in inflorescences (0.7%) and leaves (0.7%), less in the aerial parts (0.5%) and stems (0.4%). Monoterpenoids mainly accumulate in inflorescences, sesquiterpenoids are mostly found in leaves and stems. Dominant components characteristic of all parts of the plant: 1,8-cineole (1.5–9.1%), terpineol-4 (0.7–2.8%), bornyl-2-methylbutonoate (1.5–1.8), camphor (0.4–39.5%), borneol (0.7–6.4%), bornyl acetate (3.1–5.0%), davana ether (isomer 1) (1.9–5.3%), davana ester (isomer 2) (1.1–3.2%), davanone (0.6–12.4%), caryophiollene (0.5–2.0%), bicyclogermacrene ( 0.7–6.2%), spatulenol (0.8–19.9%). The hydrothermal coefficient (HTC) was calculated and a positive correlation between HTC and the content of essential oil in the raw material was shown. Conclusions. For the first time, the component composition of essential oils isolated from the inflorescences, leaves, and stems of Artemisia santolinofolia was studied; 60 compounds related to mono- and sesquiterpene compounds were identified. The dominant components of essential oils were identified. A study of the dynamics of accumulation showed that oils are contained in all organs of the plant, therefore the entire above-ground part of the plant is collected; the optimal period for collecting raw materials is the flowering phase. The content of essential oils depends more on the amount of precipitation than on the average monthly temperature.

Predicting global geographical distribution and latitudinal suitability gradient for light brown apple moth

Epiphyas postvittana, commonly known as the light brown apple moth (LBAM), is native to Australia and has a restricted global distribution. Its polyphagous nature and the recent surge in interceptions have emphasized the need for focused risk assessments to guide effective measures to curb the entry of this pest into new countries. This study aimed to perform a detailed global invasion risk assessment using an optimized MaxEnt model that incorporated 19 bioclimatic variables and elevation. The predictive outcomes underscored the significance of key variables, specifically the minimum temperature of the coldest month (bio6), precipitation of the driest month (bio14), and precipitation of the coldest quarter (bio19), in shaping the potential geographical distribution of LBAM. Regions beyond the existing range, including the southeastern United States, southern Brazil, eastern Argentina, Uruguay, southern Chile, and various Western European countries, were identified as susceptible to invasion and establishment by LBAM. An increase in suitability was observed above 45°N and 40°S under future climate scenario. With respect to climate change, LBAM would expand its potential range in Western Europe and the United States, especially under SSP5-8.5, in the 2050s. An upward trend in the latitudinal suitability gradient for LBAM in mid-high latitude areas implies that amid changing climate conditions, LBAM may find favorable habitats in these regions. For countries and regions with invasion risk, it is imperative to implement corresponding inspections and quarantine measures to thwart the introduction of LBAM, particularly in countries with established trade ties with invaded regions.

Bumble bee responses to climate and landscapes: Investigating habitat associations and species assemblages across geographic regions in the United States of America.

Bumble bees are integral pollinators of native and cultivated plant communities, but species are undergoing significant changes in range and abundance on a global scale. Climate change and land cover alteration are key drivers in pollinator declines; however, limited research has evaluated the cumulative effects of these factors on bumble bee assemblages. This study tests bumble bee assemblage (calculated as richness and abundance) responses to climate and land use by modeling species-specific habitat requirements, and assemblage-level responses across geographic regions. We integrated species richness, abundance, and distribution data for 18 bumble bee species with site-specific bioclimatic, landscape composition, and landscape configuration data to evaluate the effects of multiple environmental stressors on bumble bee assemblages throughout 433 agricultural fields in Florida, Indiana, Kansas, Kentucky, Maryland, South Carolina, Utah, Virginia, and West Virginia from 2018 to 2020. Distinct east versus west groupings emerged when evaluating species-specific habitat associations, prompting a detailed evaluation of bumble bee assemblages by geographic region. Maximum temperature of warmest month and precipitation of driest month had a positive impact on bumble bee assemblages in the Corn Belt/Appalachian/northeast, southeast, and northern plains regions, but a negative impact on the mountain region. Further, forest land cover surrounding agricultural fields was highlighted as supporting more rich and abundant bumble bee assemblages. Overall, climate and land use combine to drive bumble bee assemblages, but how those processes operate is idiosyncratic and spatially contingent across regions. From these findings, we suggested regionally specific management practices to best support rich and abundant bumble bee assemblages in agroecosystems. Results from this study contribute to a better understanding of climate and landscape factors affecting bumble bees and their habitats throughout the United States.

Identification of suitable habitats and priority conservation areas under climate change scenarios for the Chinese alligator (Alligator sinensis).

Amphibians and reptiles, especially the critically endangered Chinese alligators, are vulnerable to climate change. Historically, the decline in suitable habitats and fragmentation has restricted the distribution of Chinese alligators to a small area in southeast Anhui Province in China. However, the effects of climate change on range-restricted Chinese alligator habitats are largely unknown. We aimed to predict current and future (2050s and 2070s) Chinese alligator distribution and identify priority conservation areas under climate change. We employed species distribution models, barycenter migration analyses, and the Marxian model to assess current and future Chinese alligator distribution and identify priority conservation areas under climate change. The results showed that the lowest temperature and rainfall seasonality in the coldest month were the two most important factors affecting the distribution of Chinese alligators. Future predictions indicate a reduction (3.39%-98.41%) in suitable habitats and a westward shift in their distribution. Further, the study emphasizes that suitable habitats for Chinese alligators are threatened by climate change. Despite the impact of the Anhui Chinese Alligator National Nature Reserve, protection gaps persist, with 78.27% of the area lacking priority protected area. Our study provides crucial data for Chinese alligator adaptation to climate change and underscores the need for improved conservation strategies. Future research should refine conservation efforts, consider individual plasticity, and address identified limitations to enhance the resilience of Chinese alligator populations in the face of ongoing climate change.

The enduring nature of cranberry production in a changing climate: The interplay of extreme weather, knowledge networks, and adaptation

Anthropogenic climate change is causing critical issues in agriculture, including cranberry production; however, in a previous study the majority of Massachusetts cranberry growers were less likely to see global warming as a threat than the general US population, and more still reported to be little worried about such warming. This research aims to determine the influence of weather and professional information disseminated to cranberry growers on their climate change adaptation. The authors used a mixed-methods, interdisciplinary approach, including content analysis of around 300 issues of UMass Extension’s Cranberry Station monthly newsletter—a widely trusted source of information in the cranberry grower “network of knowledge”—along with historical weather data from 1974 to 2020, and interview and survey data. Despite infrequent usage of direct communication on climate change and adaptation, UMass Extension’s communication on weather challenges in general showed a small but significant increase when monthly temperature anomalies increased. Meanwhile, anomalous monthly precipitation was negatively associated with total chemical mentions (linked to chemical use behavior). Climate impacts such as increased weeds, water issues (e.g., heavy rainfall, water scarcity), and heat waves ruining harvests were important to growers, leading to the adoption of both conventional (e.g., increased strategic flooding, barge sanding due to lack of ice) and emerging (e.g., smart irrigation, solar panel installations for added income) adaptive strategies. Growers demonstrate climate and technological optimism, believing that other growers are hit worse by climate change than themselves and that cranberry plant resilience, better weather forecasting, and improved irrigation technology will allow them to handle future weather challenges. The prioritization of immediate needs over the more abstract, long-term challenge of climate change by growers and the supporting system underscores the imperative to explore the socio-environmental dynamics that shape their climate responses in cranberry production.

From current to potential distribution: the case of Taxus baccata(Taxaceae, Pinales) on the island of Sardinia (Italy)

Taxus baccata is a relic-declining species, especially at the southern edge of its natural distribution. On the Island of Sardinia, we found 237 locations where yews grow, being indifferent to substrates, preferring moist sites with northern aspects and with an elevation range of 695–1,225 m a.s.l. We applied the Maximum Entropy algorithm (MaxEnt), using 202 field-based sites and 19 bioclimatic variables, to model the present potential distribution. Our model showed high levels of predictive performances with significant values of AUC (training, 0.962; test, 0.963). Annual precipitation, mean temperature of the warmest month and isothermality were the key drivers for the distribution of yew in Sardinia. The response curves showed that T. baccata prefers annual mean temperatures ranging from 8.65 to 12.55 °C and annual mean precipitation from 770 to 1,085 mm. Most potential suitable conditions were found in northern and central Sardinia. We also modelled future habitat suitability for T. baccata under two different scenarios (ssp245 and ssp585), highlighting a predicted drastic reduction, up to >95% in the worst scenario, of the habitat suitability for yews by the end of this century. This is related to climate change and poses increasing concerns about the future of yews in Sardinia.

Predicting the potential distribution of Dendrolimus punctatus and its host Pinus massoniana in China under climate change conditions

IntroductionDendrolimus punctatus, a major pest endemic to the native Pinus massoniana forests in China, displays major outbreak characteristics and causes severe destructiveness. In the context of global climate change, this study aims to investigate the effects of climatic variations on the distribution of D. punctatus and its host, P. massoniana. MethodsWe predict their potential suitable distribution areas in the future, thereby offering a theoretical basis for monitoring and controlling D. punctatus, as well as conserving P. massoniana forest resources. By utilizing existing distribution data on D. punctatus and P. massoniana, coupled with relevant climatic variables, this study employs an optimized maximum entropy (MaxEnt) model for predictions. With feature combinations set as linear and product (LP) and the regularization multiplier at 0.1, the model strikes an optimal balance between complexity and accuracy.ResultsThe results indicate that the primary climatic factors influencing the distribution of D. punctatus and P. massoniana include the minimum temperature of the coldest month, annual temperature range, and annual precipitation. Under the influence of climate change, the distribution areas of P. massoniana and its pests exhibit a high degree of similarity, primarily concentrated in the region south of the Qinling−Huaihe line in China. In various climate scenarios, the suitable habitat areas for these two species may expand to varying degrees, exhibiting a tendency to shift toward higher latitude regions. Particularly under the high emission scenario (SSP5-8.5), D. punctatus is projected to expand northwards at the fastest rate. DiscussionBy 2050, its migration direction is expected to closely align with that of P. massoniana, indicating that the pine forests will continue to be affected by the pest. These findings provide crucial empirical references for region-specific prevention of D. punctatus infestations and for the rational utilization and management of P. massoniana resources.