Influence Of Climate Variability Research Articles

Economic losses caused by mastitis and the influence of climate variation on the occurrence of the disease in a dairy cattle farm in southern Brazil.

This study evaluated the economic impacts caused by mastitis in a small dairy farm with similar characteristics and production to most dairy farms in southern Brazil and investigated if climatic variations influenced mastitis occurrence in the region. A farm with, on average, 45 lactating Holstein cattle was monitored from November 2021 to October 2022, and data on mastitis cases, bulk tank milk somatic cell count, animal treatment costs, milk production, animal disposal costs, and production losses were collected. Monthly averages of temperature, relative humidity (RH), and rainfall in the region were obtained. The greatest loss was related to the drop in milk production, resulting in 63.8% of total losses, followed by animal disposal (29.5%), milk disposal (4.6%), and treating animals with mastitis (2.0%), totaling a 10.6% reduction in the annual gross income. There were negative correlations between the clinical mastitis rate and monthly RH and between subclinical mastitis and temperature; the occurrence of subclinical mastitis and average RH were positively correlated. Our findings showed that mastitis negatively impacted the economy and that climate influenced mastitis occurrence.

A Review on the Utilization of Herbarium Data in Phenological Research Addressing Climate Change Implications

In recent years, the profound impact of climate change on biodiversity has become increasingly evident, with significant consequences for critical life events in the natural world. It underscores the significant influence of climate variations on seasonal life events within the biotic environment of flora, such as blooming response, leaf growth, leaf senescence and fruit ripening. These phenological shifts, particularly in temperate and tropical ecosystems, serve as vital indicators of climatic changes. This review study delves into the intricate relationship of herbarium data for bridging the gap in plant phenological observation for the investigations on climatic change. This comprehensive literature review of 30 key research papers published in the past two decades, which focus on the utility of herbarium specimens as tools to document phenological changes, was critically analysed in this research study. Long-term observation of phenological data by various phenological observation networks has paved the way for advanced environmental analysis in climatic change studies. However, despite the importance of phenological data from field observation, its collection and long-term observation records, present challenges, emphasizing the need for spatiotemporal depth of phenological data. A noticeable gap in field data collection has hindered various studies reliant on plant phenological data. In response to these challenges, herbaria serve as invaluable repositories of plant specimens, boasting rich historical records spanning over a century, providing a deep spatiotemporal and taxonomic insight. Research findings indicate the fidelity of herbarium records to fill the gap in field observations, with no significant differences between the field observations and herbarium data, highlighting the reliability of herbarium data in capturing phenological information. Overcoming the challenges associated with extensive herbarium datasets, digitalization and the implementation of crowdsourcing platforms have emerged as effective strategies, granting researchers easy online access to these data. Moreover, it is evident that in Sri Lanka, there exists a research gap in utilizing herbarium data for phenological studies in climate change observation and the implementation of online accessibility for herbarium data, highlighting the need to address this gap in future research endeavours.
 
 Keywords: Climate change, Herbarium data, Biodiversity, Phenological data

Body size variation in a lineage of spur-thighed tortoises (Testudo graeca whitei) contrasts with that expected from the species level

Abstract Ectotherms exhibit varying geographic size patterns shaped by environmental and evolutionary factors. This variability is noticeable within taxonomic groups. For instance, certain testudinids follow Bergmann’s rule (body size increases with latitude) and Rensch’s rule (sexual size dimorphism correlates with body size), while others do not. Here we hypothesize that body size patterns can even vary within a monophyletic lineage. To address this, we evaluated the body size patterns of the spur-thighed tortoise Testudo graeca that globally follows Bergmann’s and Rensch’s rules. We specifically investigated the influence of climate variables, latitude and elevation within the subspecies T. g. whitei throughout its natural distribution in North Africa, and in a recently expanded range in SE Spain (20 kya old). We found that males were smaller than females in both regions. The tortoises from SE Spain were smaller than those from North Africa, which showcased the smallest sizes ever reported for the species. Latitude was the main variable to explain tortoise body size. In particular, body size decreased with latitude in both regions, which contrasts with Bergmann’s rule expectations based on species-level findings. Finally, to further contradict species-level expectations, we did not find any statistical correlation between sexual size dimorphism and body size across the two studied regions. Such contradictory outcomes reveal complex geographic size patterns within T. graeca and raise conservation questions about demographic viability at smaller-sized sites.

Green, charismatic, microendemic, and threatened: breeding biology of the leaf frog Pithecopus rusticus (Anura: Hylidae: Phyllomedusinae)

ABSTRACT Pithecopus rusticus is a small and charismatic leaf frog species known only from the type locality, in the Brazilian Subtropical Highland Grasslands of the Atlantic Forest, southern Brazil. In this study, we describe aspects of the reproductive biology and populational size of P. rusticus, encompassing the characterization of breeding season, microhabitat use for vocalization and spawning, the variation in body size of males and females and operational sex ratio, as well as explore the influence of climate variables on the abundance of individuals. We collected information from 2015 to 2021, mainly in the breeding seasons of 2015/16 and 2017/18. We recorded 91 individuals of P. rusticus, with a recapture rate of 61% in the 2015/16 breeding season and 57% in the 2017/18 breeding season. The estimated population size was 28.9 individuals for the 2015/16 breeding season and 21 individuals for the 2017/18 breeding season. The temporal reproductive pattern was intermediate, being concentrated in spring to early summer months (October to January), and the male calling activity differed throughout the night, increasing from 9pm onwards. The abundance of P. rusticus was significantly related with relative air humidity. We found sexual size dimorphism, with females larger than males, and a male-skewed operational sex ratio. Males and females used Poaceae and Cyperaceae leaves located close to water. Spawns contained 43 ± 5 eggs, with a diameter of 3.26 ± 0.45 mm, and were deposited on leaves of Senecio (Asteraceae) and Eriocaulon (Eriocaulaceae). Information on natural history is essential to support the implementation and success of in situ and ex situ conservation strategies for this endangered species.

Assessing the influence of climate variability and land cover change on water resources in the Wami river catchment, Tanzania

Assessing the influence of climate variability and land cover change on water resources in the Wami river catchment, Tanzania

Rate of vegetation change in southeast China during the Holocene and its potential drivers

Understanding the factors behind past vegetation changes is instructive to anticipate how vegetation will react to future climate change and human activities. The factors that contribute to the changes in vegetation during the Holocene in the topographically diverse southeast China are still not well understood. This study presents a recently acquired subalpine pollen record and combines it with pollen records from low-lying areas and mountains in southeast China. We utilized a Rate of Change (RoC) analysis on the pollen sequences to detect shifts in vegetation composition. Our findings indicate a significant increase in vegetation rate of change in southeast China over the past 3000 years, comparable to or exceeding maximum levels seen during the early Holocene, a period characterized by greater climate variability. By analyzing available paleorecords of climate, fire, and human activity, it becomes clear that vegetation in southeast China was significantly affected by climate before c. 3 ka BP. However, after this time, human impacts began to play a prominent role, first in the lowlands and later in the mountains, in addition to the influence of climate variations. Our study emphasizes the significance of taking into account the rate of vegetation compositional change when examining the factors that influence long-term vegetation changes.

GloLakes: water storage dynamics for 27 000 lakes globally from 1984 to present derived from satellite altimetry and optical imaging

Abstract. Measuring the spatiotemporal dynamics of lake and reservoir water storage is fundamental for assessing the influence of climate variability and anthropogenic activities on water quantity and quality. Previous studies estimated relative water volume changes for lakes where both satellite-derived extent and radar altimetry data are available. This approach is limited to only a few hundred lakes worldwide and cannot estimate absolute (i.e. total volume) water storage. We increased the number of measured lakes by a factor of 300 by using high-resolution Landsat and Sentinel-2 optical remote sensing and ICESat-2 laser altimetry, in addition to radar altimetry from the Topex/Poseidon; Jason-1, Jason-2 and Jason-3; and Sentinel-3 and Sentinel-6 instruments. Historical time series (1984–2020) of water storage could be derived for more than 170 000 lakes globally with a surface area of at least 1 km2, representing 99 % of the total volume of all water stored in lakes and reservoirs globally. Specifically, absolute lake volumes are estimated based on topographic characteristics and lake properties that can be observed by remote sensing. In addition to that, we also generated relative lake volume changes solely based on satellite-derived heights and extents if both were available. Within this dataset, we investigated how many lakes can be measured in near real time (2020–current) in basins worldwide. We developed an automated workflow for near-real-time global lake monitoring of more than 27 000 lakes. The GloLakes historical and near-real-time lake storage dynamics data from 1984 to current are publicly available through https://doi.org/10.25914/K8ZF-6G46 (Hou et al., 2022c) and a web-based data explorer (http://www.globalwater.online, last access: 12 December 2023).

Land tenure, information sources and climate variability adaptation strategies: evidence from southern Ghana

ABSTRACT This article makes two central arguments to advance inconclusive literature in relevant extant research related to agriculture adaptation and climate change in the global south. First, it argues a relationship exists between land tenure and climate variability adaptation strategies. Second, it argues climate information sources influence climate variability adaptation strategies. Drawing on 150 smallholder farmers in southern Ghana, using a mixed methods paradigm, we answer two research questions: What is the relationship between land ownership and climate variability adaptation strategies? What are the sources of climate variability information that inform adaptation strategies? The findings show that land ownership positively correlates with mixed cropping, use of organic manure, and irrigation. Radio, agricultural extension agents, peer farmers, and families constitute major sources of climate information that influence climate variability adaptation strategies. Governments in sub-Saharan Africa (SSA) can implement land administration initiatives that ensures secured land tenure and engender long-term capital-intensive agricultural investments.

Influence of climatic variables on maize grain yield and its components by adjusting the sowing date.

Yield and its components are greatly affected by climate change. Adjusting the sowing date is an effective way to alleviate adverse effects and adapt to climate change. Aiming to determine the optimal sowing date of summer maize and clarify the contribution of climatic variables to grain yield and its components, a consecutive 4-year field experiment was conducted from 2016 to 2019 with four sowing dates at 10-day intervals from 5 June to 5 July. Analysis of historical meteorological data showed that more solar radiation (SR) was distributed from early June to mid-August, and the maximum temperature (Tmax) > 32°C appeared from early July to late August, which advanced and lasted longer in 1991-2020 relative to 1981-1990. Additionally, the precipitation was mainly distributed from early June to late July. The climate change in the growing season of summer maize resulted in optimal sowing dates ranging from 5 June to 15 June, with higher yields and yield stability, mainly because of the higher kernel number per ear and 1,000-grain weight. The average contribution of kernel number per ear to grain yield was 58.7%, higher than that of 1,000-grain weight (41.3%). Variance partitioning analysis showed that SR in 15 days pre-silking to 15 days post-silking (SS) and silking to harvest (SH) stages significantly contributed to grain yield by 63.1% and 86.4%. The extreme growing degree days (EDD) > 32°C, SR, precipitation, and diurnal temperature range (DTR) contributed 20.6%, 22.9%, 14.5%, and 42.0% to kernel number per ear in the SS stage, respectively. Therefore, we concluded that the early sowing dates could gain high yield and yield stability due to the higher SR in the growing season. Meanwhile, due to the decreasing trend in SR and increasing Tmax trend in this region, in the future, new maize varieties with high-temperature resistance, high light efficiency, shade tolerance, and medium-season traits need to be bred to adapt to climate change and increased grain yield.

Genotype × environment interaction and stability of high oleic sunflower (Helianthus annus L.) hybrids across temperature regimes

Sunflower cultivation in India faces challenges related to environmental variability, particularly in the choice of hybrid varieties for different regions and seasons. This study focuses on the development and stability evaluation of high-oleic sunflower hybrids, emphasizing oleic acid content, which is associated with health benefits. Thirty high-oleic hybrids along with four check hybrids were tested across multiple locations and seasons in Karnataka, India. Analysis of variance using the additive main effects and multiplicative interaction model revealed significant genotype × environment interactions, highlighting the variability in hybrid performance. Promising high-oleic hybrids were identified based on stability across locations and seasons. Interestingly, some hybrids exhibited high oleic acid content during the rabi/summer season but not during the rabi season, indicating sensitivity to temperature changes. Furthermore, the study explored the influence of climatic variables, confirming that temperature as key factor affecting the oleic acid content. The results emphasized the importance of the rabi/summer season for high-oleic sunflower cultivation in India. These findings provide valuable insights for sunflower breeding programs, enabling the development of stable and adaptable high-oleic sunflower hybrids that meet India’s agricultural and nutritional demands.

Multimodal deep learning water level forecasting model for multiscale drought alert in Feiyun River basin

Hydrological forecasting is an indispensable tool in intelligent water conservation for flood control and drought mitigation. Due to the influences of human activities and climate variability, accurate water level prediction poses a significant challenge. To address this, we develop a novel hybrid deep architecture, that is Dual-Stage Attention-based Multi-modal Deep Learning (DSAMDL), for reliable and interpretable multi-scale water level forecasting. Unlike previous techniques, multisource data is treated as different modalities in the proposed model. Firstly, we employ the one-dimensional Convolution to capture local trend features, followed by the Bidirectional Long Short-term Memory network to learn long-term dependencies. Subsequently, we design a dual-stage attention mechanism, which assigns contributions in a phased manner to different temporal and spatial. Finally, an adaptive fusion method is applied to enhance overall performance. To validate its accuracy and efficiency, short long-term drought water level forecasting and predictions under various events are implemented over six reservoir stations in the Feiyun River basin, Wenzhou City. Four evaluation metrics, namely RMSE, MAE, CORR, and NSE, are introduced for comprehensive assessment against the start-of-the-art baselines. The results well-document that the DSAMDL framework achieves satisfactory accuracy, with an average improvement of 22.4%, 27.8%, 29.7%, and 11.5% in these four metrics, showcasing the model’s effectiveness in handling complex multiscale drought water level forecasting.

Influence of climate variability on fire generation

This study evaluates the occurrence of dry and wet events and their relationship with fires in southern Pampas, Argentina. The intensity and magnitude of dry and wet events were determined based on the regional series of the Standardized Precipitation and Evapotranspiration Index (SPEI) for the 2000-2021 period. The data obtained were related to the El Niño Oceanic Index (ONI) to analyze the incidence of El Niño and La Niña events in generating them. Fires in the region were detected using remote sensing techniques, considering the number of events, their intensity, extent, and duration. The southern Pampas experiences marked rainfall variability, with 15 dry events, 11 wet years, and 2 standard years recorded for the period analyzed. Extreme dry years were, on average, more intense (SPEI = -2.14) and occurred mainly during the negative ONI phase. In contrast, extreme wet years exhibited lower intensity (SPEI = 1.98), and only the most intense ones were related to neutral ONI phases. We analyzed a representative extremely dry (ED) and an extremely wet events (EW) to interpret the relationship between climate variability and the spatiotemporal variability of fires in the region. It was observed that during the EW event (2014-2015, SPEI = 1.52, and El Niño event until 2015) the number of fires was higher compared to an ED event (2008-2009, SPEI = -2.22, and La Niña event during 2008), with 460 and 205 fires, respectively. The intensity was higher in the EW (302.6 and 31.5 MW), while the area presented considerable differences (1722 and 815.5 km2, respectively). Finally, the duration of the fires was shorter in ED than in EW (6 and 8 months, respectively). These results were related to vegetation health (NDVI = 0.29 and 0.41 and EVI = 0.15 and 0.21 in ED and EW, respectively) and changes in land covers. This study provides a solid database for future research efforts and sustainable land management plans.

Greater local cooling effects of trees across globally distributed urban green spaces

Urban green spaces (UGS) are an effective mitigation strategy for urban heat islands (UHIs) through their evapotranspiration and shading effects. Yet, the extent to which local UGS cooling effects vary across different background climates, plant characteristics and urban settings across global cities is not well understood. This study analysed 265 local air temperature (TA) measurements from 58 published studies across globally distributed sites to infer the potential influence of background climate, plant and urban variables among different UGS types (trees, grass, green roofs and walls). We show that trees were more effective at reducing local TA, with reductions 2–3 times greater than grass and green roofs and walls. We use a hierarchical linear mixed effects model to reveal that background climate (mean annual temperature) and plant characteristics (specific leaf area vegetation index) had the greatest influence on cooling effects across UGS types, while urban characteristics did not significantly influence the cooling effects of UGS. Notably, trees dominated the overall local cooling effects across global cities, indicating that greater tree growth in mild climates with lower mean annual temperatures has the greatest mitigation potential against UHIs. Our findings provide insights for urban heat mitigation using UGS interventions, particularly trees across cities worldwide with diverse climatic and environmental conditions and highlight the essential role of trees in creating healthy urban living environments for citizens under extreme weather conditions.

The role of climatic factor timing on grassland net primary productivity in Altay, Xinjiang

Grassland, as highly vulnerable ecosystem, requires a comprehensive understanding of its dynamics and response patterns to climate factors in response to climate change challenges. While previous research has primarily centered on the influence of interannual climate variability on grassland Net Primary Productivity (NPP), knowledge of the impacts of seasonal or monthly climate variations on annual net primary productivity (ANPP) remains limited. This study investigated the climatic drivers of grassland NPP dynamics in Xinjiang's Altay region from 2000 to 2022 using the Carnegie-Ames-Stanford approach (CASA) model and the random forest regression model. The study examined the significance and patterns of precipitation, solar radiation, temperature, soil moisture, and snowmelt water on NPP at three temporal scales. The results revealed the following key findings: (1) Grassland NPP declined significantly from 2000 to 2009 but showed a gradual increase from 2009 to 2022. Spatially, higher values were observed in the northern region and lower values were observed in the southern region. (2) Precipitation was the primary influential climate factor affecting grassland NPP, followed by solar radiation, temperature, soil moisture, and snowmelt water. In determining the significance of climate factor timing on ANPP, June played a critical role particularly for precipitation, temperature, and soil moisture, while August was essential for solar radiation. Moreover, the importance of snowmelt water had a bimodal distribution, with peaks in April and October. (3) Grassland NPP exhibited diverse nonlinear response dynamics and spatial heterogeneity to various climate factors at different temporal scales. These findings highlight the importance of considering both the magnitude and the local conditions, as well as the timing of climate variations when studying grassland dynamic responses to climate change and predicting future impacts. These insights enhance the comprehension of the intricate dynamics of grassland ecosystems and enhance predictions of their responses to future climate change.

Dynamic of Grassland Degradation and Its Driving Forces from Climate Variation and Human Activities in Central Asia

Central Asia is one of the most sensitive regions to climate changes in the world and the grassland degradation of this region has attracted considerable concern. Quantifying the driving force of grassland degradation is important for understanding the effects of climate variation and human activities on grassland. In this study, net primary productivity (NPP) was selected as an indicator to quantitatively evaluate the relative role of climate variation and human activities in Central Asia from 2000 to 2020. This study used the global NPP product MOD17A3 as actual NPP and estimated the potential NPP using the Thornthwaite memorial model. The potential NPP and the difference between the potential NPP and actual NPP were used to represent the influence of climate variation and human activities. The grassland degradation or restoration can be demonstrated by the slope of actual NPP (SA). A positive slope value (SA) suggested that restoration occurs, whereas a negative slope value suggested that degradation occurred. The results showed that 23.08% of the total grassland area experienced grassland degradation, whereas 2.51% of the whole grassland underwent grassland restoration. Furthermore, 53.8% of the degraded grassland areas were influenced by climate variation, and 14.5% were caused by human activities. By contrast, the relative roles of climate variation and human activities in grassland restoration were 25% and 47.9%, respectively. The NPP variation also could be calculated by assessing the effects of these factors and the results showed that 55.7% of the NPP decrease was caused by climate variation, whereas 9.6% was a result of human activities. On the contrary, climate variation and human activities resulted in 19.8% and 37.3% of grassland restoration, respectively. Therefore, climate variation was the dominant factor of grassland degradation, and human activities were the main driver of grassland restoration in Central Asia.

Climate variability, armed conflicts and child malnutrition in sub-saharan Africa: A spatial analysis in Ethiopia, Kenya and Nigeria

BackgroundSub-Saharan Africa (SSA) has one of the highest prevalence of malnutrition among children under 5 in the world. It is also the region most vulnerable to the adverse effect of climate change, and the one that records the most armed conflicts. The chains of causality suggested in the literature on the relationship between climate change, armed conflict, and malnutrition have rarely been supported by empirical evidence for SSA countries. MethodsThis study proposes to highlight, under the hypothesis of spatial non-stationarity, the influence of climatic variations and armed conflicts on malnutrition in children under 5 in Ethiopia, Kenya, and Nigeria. To do this, we use spatial analysis on data from Demographic and Health Surveys (DHS), Uppsala Conflict Data Program Georeferenced Event Dataset (UCDP GED), Climate Hazards center InfraRed Precipitation with Station data (CHIRPS) and Moderate Resolution Imaging Spectroradiometer (MODIS). ResultsThe results show that there is a spatial autocorrelation of malnutrition measured by the prevalence of underweight children in the three countries. Also, local geographically weighted analysis shows that armed conflict, temperature and rainfall are positively associated with the prevalence of underweight children in localities of Somali in Ethiopia, Mandera and Turkana of Wajir in Kenya, Borno and Yobe in Nigeria. ConclusionIn conclusion, the results of our spatial analysis support the implementation of conflict-sensitive climate change adaptation strategies.

Investigation of the consistency of changes in the wavelet phase characteristics of heliocosmic and climatic variables and changes in the components of the word water balance. Part 3

The relevance of research is due to the need to establish the true causes and patterns of changes in the hydrometric characteristics of the global water balance as a whole and its components, natural environments on Earth.
 Purpose of research: to establish patterns and causes of changes in the components of the global water balance on Earth: trends in the increase in water mass reserves, dynamics of the water balance of the South Seas of Europe, the Black Sea, dynamics of levels of the Indian Ocean, Western and Central Pacific Ocean, Eastern Pacific and Atlantic Oceans, level fluctuations of the World Ocean, changes in sea ice cover, river resources, reservoirs, variability of sea levels in the Arctic Ocean according to observations at coastal stations, changes in the balance of ice masses in glacial areas, changes in interseasonal thawing in the permafrost zones of the continent.
 Objects of research: time series of heliocosmic, climatic variables, hydrometric characteristics of the components of the global water balance.
 Methods of research: developed by the author, a method for interaction of observations of a variable or variables with groups of specified heliocosmic and climatic factors in the frequency and time domains, obtained using wavelet transformations of observations with the calculation of phase-frequency and phase-time characteristics in equal time intervals; comparative analysis of changes in the obtained phase characteristics of groups of variables with the calculation of their consistency matrices and the construction of graphs in the frequency and time domains.
 Main results of research: in the observed time intervals, in the trend of periodic changes in the reserves of water masses (glaciers, groundwater, lakes, reservoirs) in the frequency domain, significant negative unidirectional influences of changes in heliocosmic and multidirectional influences of climatic variables are observed; changes in the reserves of the World Ocean are more influenced by multidirectional changes in climatic factors compared to the unidirectional influences of heliocosmic factors; the frequency bands of changes in water mass reserves are less than the frequency bands of heliocosmic factors, due to the influence of climatic factors; The variability of water mass reserves on Earth is significantly and unidirectionally consistent with changes in evaporation, evaporation and precipitation on land, and in different directions with changes in cloudiness on the continents. Similar patterns are observed in changes in the water balance of the South Seas in Europe, the Black Sea, sea ice cover, river resources, reservoirs on land, ice mass balances in glacial areas, and interseasonal thawing in the permafrost zones of the continent. In the dynamics of the levels of the Indian, Western and Central Pacific, Eastern Pacific and Atlantic, fluctuations in the level of the World Ocean, significant multidirectional changes in levels in the frequency domain are observed on the effects of heliocosmic variables with the greatest influences of solar activity and long-term solar insolation, the Ap-index of geomagnetic activity, the parameter the ratio of plasma pressure to magnetic solar wind, changes in the ozone layer in the ionosphere, changes in the speed of rotation of the Earth, the influence of climate variables in the frequency domain with the greatest influences of solar radiation, precipitation, atmospheric processes, PTV is significant. The variability of sea levels in the Arctic Ocean, as observed at coastal stations, is characterized by significant multidirectional changes in the frequency domain due to the influence of heliocosmic and climatic factors, multidirectional mutual consistency of the component levels of the ocean seas, caused by anomalous changes in the Earths magnetic field in areas of the Northern Hemisphere. In changes in the phase-time characteristics of groups of factors, lattice structures of differently and unidirectional changes in variables are observed, characterizing the cyclical nature of climate change on Earth.

Exploring the influence of climatic variables on mycobiome composition and community diversity in lichens: insights from structural equation modeling analysis

BackgroundLichens are symbiotic organisms composed of a fungus and a photosynthetic partner, which are key ecological bioindicators due to their sensitivity to environmental changes. The endolichenic fungi (ELF) living inside lichen thalli, are an important but understudied component of playing crucial ecological roles such as nutrient cycling and protection against environmental stressors. Therefore ELF community investigation is vital for fostering sustainable ecosystems and leveraging their ecological benefits. Deciphering the intricate relationships between ELF and their lichen hosts, alongside the influence of environmental factors on these communities, presents a significant challenge in pinpointing the underlying drivers of community structure and diversity.ResultsOur research demonstrated that locational factors were the main drivers of the ELF community structure, rather than host haplotype. Several climatic factors affected the diversity of the ELF community and contributed to the prevalence of different types of fungal residents within the ELF community. A decrease in isothermality was associated with a greater prevalence of pathotrophic and saprotrophic fungi within the ELF community, resulting in an overall increase in community diversity. By conducting a structural equation modeling analysis, we identified a robust link between climatic variables, fungal trophic mode abundance, and the species diversity of the ELF community.ConclusionThis study’s discoveries emphasize the significance of examining climate-related factors when investigating ELF’s structure and function. The connection between fungi and climate is intricate and complex, and can be influenced by various other factors. Investigating the potential for ELF to adapt to changing climatic conditions, as well as the potential effects of changes in ELF communities on lichen function, would be valuable research areas. We anticipate that our research results will establish a basis for numerous future ELF research projects and have a significant impact on the field.

Physical, Sensorial, and Physicochemical Characteristics of Arabica Coffee Dried under Two Solar Brightness Conditions

The solar drying process is a critical postharvest stage for preserving coffee quality and is widely used in coffee-producing countries. A descriptive exploratory study was carried out in zones with different annual solar brightness to determine the climate variability influence on solar drying. Variables related to the evolution of drying, physical and sensory quality, and the physicochemical characteristics of the Castillo® coffee variety were analyzed. Coffee quality was assessed by means of SCA protocol. An automatic system was designed to record variables inside the dryers and mass loss. The drying rates were different by climatic zone above and below 0.52%∙h−1. Drying time was significantly longer in less solar brightness zones (Wilcoxon test). An inverse linear relationship between rewetting percentage and bean moisture was observed. Regarding coffee quality, the average scores were 81.37 and 80.93 SCA points for the climatic zones with the lowest and highest solar brightness, respectively. The bean color, water activity, acidity, and fat content did not vary between climatic zones. The coffee quality was not affected by solar drying in contrasting climatic conditions, despite the differences in drying time. Solar drying behaviors were identified that allow for the development of strategies for improving the process efficiency and management of coffee.

The Influence of Internal Climate Variability on Stratospheric Water Vapor Increases After Large‐Magnitude Explosive Tropical Volcanic Eruptions

AbstractSubstantial and prolonged enhancements in stratospheric water vapor (SWV) have occurred after large‐magnitude explosive tropical volcanic eruptions, with modified tropopause entry caused by aerosol‐absorptive heating. Here, we analyze the timing and longevity of heating‐driven post‐eruption SWV changes within CMIP6‐VolMIP short‐term climate‐response experiments with the UK Earth System Model (UKESM1). We find aerosol‐absorptive heating causes peak SWV increases of 17% (∼1 ppmv) and 10% (0.5 ppmv) at 100 and 50 hPa, at ∼18 and ∼23 months after a Pinatubo‐like eruption, respectively. We track the temperature response in the tropical lower stratosphere and identify the main SWV increase occurs only after the descending aerosol heating reaches the tropopause, suggesting a key role for aerosol microphysical processes (sedimentation rate). We explore how El Niño–Southern Oscillation variability modulates this effect. Post‐eruption SWV increases are ∼80% stronger for the La Nina phase compared to the ensemble mean. Tropical upwelling strongly mediates this effect.