Seasonal Climate Research Articles

Qualitative Production of Mixture Silage within a Sustainable Concept

Climate change and seasonality in forage production have caused alterations in animal feed. Thus, this study evaluated the composition of silages from soybean (Glycine max (L.) Merrill) mixed with tropical grasses. The experimental design was randomized blocks with four replications. Treatments were silage from soybeans, silage from soybeans with Aruana Guinea grass (Megathyrsus maximus cv. Aruana), and silage from soybeans with Congo grass (Urochloa ruziziensis cv. Comum). Silos were stored for 60 days in the laboratory at room temperature. The silage from soybeans with Aruana Guinea grass showed the highest contents of dry matter, crude fiber, neutral detergent fiber, insoluble nitrogen in neutral detergent fiber, and insoluble nitrogen in acid detergent fiber but the lowest levels of crude protein and ether extract. The highest content of mineral material and hemicellulose was observed in the silage from soybeans with Congo grass. The silages from soybeans and soybeans with Congo grass showed no significant differences for acid detergent fiber and lignin. In conclusion, the use of tropical grasses as a component to improve the quality of silage from soybeans is an alternative for forage conservation in ruminant production systems, especially at the dry season.

Multi-model ensembles for regional and national wheat yield forecasts in Argentina

Abstract While multi-model ensembles (MMEs) of seasonal climate models (SCMs) have been used for crop yield forecasting, there has not been a systematic attempt to select the most skillful SCMs to optimize the performance of a MME and improve in-season yield forecasts. Here, we propose a statistical model to forecast regional and national wheat yield variability from 1993–2016 over the main wheat production area in Argentina. Monthly mean temperature and precipitation from the four months (August–November) before harvest were used as features. The model was validated for end-of-season estimation in December using reanalysis data (ERA) from the European Centre for Medium-Range Weather Forecasts (ECMWF) as well as for in-season forecasts from June to November using a MME of three SCMs from 10 SCMs analyzed. A benchmark model for end-of-season yield estimation using ERA data achieved a R 2 of 0.33, a root-mean-square error (RMSE) of 9.8% and a receiver operating characteristic (ROC) score of 0.8 on national level. On regional level, the model demonstrated the best estimation accuracy in the northern sub-humid Pampas with a R 2 of 0.5, a RMSE of 12.6% and a ROC score of 0.9. Across all months of initialization, SCMs from the National Centers for Environmental Prediction, the National Center for Atmospheric Research and the Geophysical Fluid Dynamics Laboratory had the highest mean absolute error of forecasted features compared to ERA data. The most skillful in-season wheat yield forecasts were possible with a 3-member-MME, combining data from the SCMs of the ECMWF, the National Aeronautics and Space Administration and the French national meteorological service. This MME forecasted wheat yield on national level at the beginning of November, one month before harvest, with a R 2 of 0.32, a RMSE of 9.9% and a ROC score of 0.7. This approach can be applied to other crops and regions.

Seasonal sonic patterns reveal phenological phases (sonophases) associated with climate change in subarctic Alaska

Given that ecosystems are composed of sounds created by geophysical events (e.g., wind, rain), animal behaviors (e.g., dawn songbird chorus), and human activities (e.g., tourism) that depend on seasonal climate conditions, the phenological patterns of a soundscape could be coupled with long-term weather station data as a complimentary ecological indicator of climate change. We tested whether the seasonality of the soundscape coincided with common weather variables used to monitor climate. We recorded ambient sounds hourly for five minutes (01 January–30 June) over three years (2019–2021) near a weather station in a subarctic ecosystem in south-central Alaska. We quantified sonic information using the Acoustic Complexity Index (ACItf), coupled with weather data, and used machine learning (TreeNet) to identify sonic-climate relationships. We grouped ACItf according to time periods of prominent seasonal events (e.g., days with temperatures >0°C, no snow cover, green up, dawn biophony, and road-based tourism) and identified distinct sonic phenophases (sonophases) for groups with non-overlapping 95% confidence intervals. In general, sonic activity increased dramatically as winter transitioned to spring and summer. We identified two winter sonophases, a spring sonophase, and a summer sonophase, each coinciding with hours of daylight, temperature, precipitation, snow cover, and the prevalence of animal and human activities. We discuss how sonophases and weather data combined serve as a multi-dimensional, systems-based approach to understanding the ecological effects of climate change in subarctic environments.

Two‐way feedback between the Madden–Julian Oscillation and diurnal warm layers in a coupled ocean–atmosphere model

AbstractDiurnal warm layers develop in the upper ocean on sunny days with low surface wind speeds. They rectify intraseasonal sea‐surface temperatures (SSTs), potentially impacting intraseasonal weather patterns such as the Madden–Julian Oscillation (MJO). Here we analyse 15‐lead‐day forecast composites of coupled ocean–atmosphere and atmosphere‐only numerical weather prediction (NWP) models of the UK Met Office to reveal that the presence of diurnal warming of SST (dSST) leads to a faster MJO propagation in the coupled model compared with the atmosphere‐only model. To test the feedback between the MJO and the dSST, we designed a set of experiments with instantaneous vertical mixing over the top 5 or of the ocean component of the coupled model. Weaker dSST in the mixing experiments leads to a slower MJO over 15 lead days. The dSST produces a increase in the MJO phase speed between the coupled and the atmosphere‐only model. An additional increase is found for other coupling effects, unrelated to the dSST. A two‐way feedback manifests in the coupled model over the 15 lead days of the forecast between the MJO and the dSST. The MJO regime dictates the strength of the dSST and the dSST rectifies the intraseasonal anomalies of SST in the coupled model. Stronger dSST in the coupled model leads to stronger intraseasonal anomalies of SST. The MJO convection responds to these SSTs on a seven‐lead‐day timescale, and feeds back into the SST anomalies within the next three lead days. Overall, this study demonstrates the importance of high vertical resolution in the upper ocean for predicting the eastward propagation of the MJO in an NWP setting, which is potentially impactful for seasonal predictions and climate projections, should this feedback be unrepresented in the models.

A three-years survey of microbial contaminants in industrial hemp inflorescences from two Italian cultivation sites

BackgroundThe use of industrial Cannabis sativa L. for recreational, cosmeceutical, nutraceutical, and medicinal purposes has gained momentum due to its rich content of valuable phytochemicals, such as cannabidiol (CBD) and cannabigerol (CBG). However, there are concerns regarding the risk of microbial contamination in plants grown outside controlled environments. Microbes associated with hemp can be either epiphytes or endophytes and may pose a risk of infectious illness for humans.MethodsSeven Italian hemp genotypes, including Bernabeo, Carmagnola, Carmaleonte, Codimono, CS, Eletta Campana, and Fibranova, were cultivated in two distinct geographic locations, Catania and Rovigo, for three consecutive years from 2019 to 2021. Total aerobic microbes (TAMC), total combined yeasts/moulds (TYMC), the presence of bile-tolerant Gram-negative bacteria, and the absence of Escherichia coli and Salmonella spp. were evaluated and compared. The main phytocannabinoid content was measured and correlated with microbial contamination.ResultsMost samples analyzed in this study did not meet the European Pharmacopoeia microbiological limits. The detection of potential pathogens, such as E. coli and Salmonella spp., in the samples indicates that the use of inflorescences may represent a possible source of infection. Microbial contamination varied among harvesting seasons and production sites, with agroclimatic conditions influencing microbial load and composition. The presence of potentially pathogenic bacteria was less associated with seasonal climate variability and more likely affected by sporadic contamination from external sources. CBD concentration exhibited a negative correlation with bile-tolerant Gram-negative bacteria and total yeasts/moulds levels. Samples with lower CBD content were more contaminated than those with higher CBD levels, suggesting a potential protective effect of this phytochemical on the plant.ConclusionsThe threshing residues (inflorescences, floral bracts, and leaves) of industrial hemp varieties represent a valuable product and a source of beneficial phytochemicals that warrants further exploration. While post-harvest sterilization methods may reduce microbiological risks, they may also degrade heat- and light-sensitive bioactive phytochemicals. The most promising strategy involves implementing best agronomic practices to maintain healthy and uncontaminated cultures. Rigorous monitoring and quality certification protocols are essential to mitigate the microbiological risk associated with the consumption of hemp-derived products.

From leaves to whole plants: positive effects of shelter‐builders on arthropod communities are stronger in dry seasons

AbstractLeaf shelters function as microclimatic refuges, reducing arthropod exposure to climatic fluctuations of surrounding habitats. Although facilitation is expected to increase under stressful conditions, empirical studies investigating the patterns of variation and magnitude of effects of ecosystem engineering (EE) at different spatial and temporal scales are still scarce. In this study, we evaluated the facilitation consequences of leaf shelter created by gall‐inducers on arthropod communities of Miconia ligustroides (DC.) Naudin (Melastomataceae). We evaluated how such effects change at the leaf and plant levels in a habitat subject to strong climatic seasonality. The presence of leaf shelters on M. ligustroides increased arthropod diversity and biomass, modified the species composition at both the leaf and plant levels, during wet and dry seasons. However, the addition of artificial leaf shelters during the dry season showed greater abundance, richness, and biomass of arthropods when compared to shelters added during the wet season. Regarding the global effects of artificial leaf shelters on the diversity of arthropods associated with M. ligustroides, the dry season showed strong and positive effects, increasing the abundance, richness, and biomass of arthropods by an average of 65% for both years. Our study contributes to a better understanding of the patterns of variation and magnitude of EE at different spatial and temporal scales and provides new insights into the importance of shelters for aridity‐sensitive species.

Effects of blood metal(loid) concentrations on genomic damages in sharks

The use of effect biomarkers has contributed to the understanding of the sublethal effects of contaminants on different organisms. However, the analysis of genotoxic markers as an indicator of organism and environmental health in sharks is underexplored. Thus, the present study investigated the relationship between the genomic damage frequency in erythrocytes and metal(loid) concentrations in whole blood of three shark species (Galeocerdo cuvier, Negaprion brevirostris and Ginglymostoma cirratum), taking into account climatic seasonality. The results showed that G. cuvier, an apex predator, presented the highest total erythrocyte genomic damage frequencies together with the highest mean whole blood concentrations of Al, Cd, Cr, Fe, Mn, Ni, Pb and Zn. The shark N. brevirostris also presented high levels of metal(loid), indicating a greater susceptibility to these contaminants in species that preferentially feed on fish. In contrast, G. cirratum, a mesopredator, presented the lowest erythrocyte damage frequencies and whole blood metal(loid) concentrations. The presence of micronuclei was the most responsive biomarker, and Al, As and Zn had an important effect on the genomic damage frequencies for all species evaluated. Zn concentration influenced the binucleated cells frequencies and Al concentration had an effect on the total damage and micronuclei frequencies in G. cuvier and N. brevirostris. Binucleated cells and blebbed nuclei frequencies were affected by As concentration, especially in G. cirratum, while showing a strong and positive correlation with most of the metals analyzed. Nonetheless, baseline levels of metal(loid) blood concentrations and erythrocyte genomic damage frequencies in sharks have not yet been established. Therefore, minimum risk levels of blood contaminants concentrations on the health of these animals have also not been determined. However, the high genomic instability observed in sharks is of concern considering the current health status of these animals, as well as the quality of the environment studied.

Interactions between Hydrodynamic Forcing, Suspended Sediment Transport, and Morphology in a Microtidal Intermediate-Dissipative Beach

This study aims to investigate the hydrodynamic-morphological interactions on a microtidal intermediate-dissipative beach under low to moderate wave energy conditions using field measurements during two climatic seasons. The separate contributions of currents, sea-swell waves, and infragravity waves to high- and low-frequency sediment fluxes were analyzed. The infragravity wave energy was more relevant near the swash zone than in other areas. Although the currents are the primary suspended sediment transport mechanism, the results suggest that the waves are an important driver of sediment suspension from the seabed. The results indicate that Sea-Swell (SS) waves and cross-shore currents are the prevailing hydrodynamic factors in nearshore sediment transport, and the cross-shore suspended sediment transport rates are higher than those in alongshore transport. The submerged bar intensified during the wet season (1–4 November 2018) when the wave height intensities were lower, contrary to the dry season (24–25 March 2018). Significant accretion nearshore was identified (in the subaerial beach) during the wet season when the suspended sediments were greater, the SS-wave heights nearshore were lower, and sediment flux was directed onshore. A notorious erosion was distinguished during the dry season. The most representative volume changes occurred during the dry season (with high erosion), which is attributed to the high SS-wave energy.

Geochemical characteristics of the upper carboniferous source rocks in a terrestrial-marine transitional environment from the shuangjingzi area, Junggar Basin: Insights into palaeoenvironment, palaeoclimate, and palaeovegetation

The Upper Carboniferous organic-rich sediments record the depositional transition from terrestrial to marine environment across the Shiqiantan Formation-Batamayineishan Formation boundary. The geochemical characteristics of source rocks deposited in such terrestrial-marine transitional environments are not clear. The Late Carboniferous palaeovegetation, palaeoclimate and palaeoredox conditions are comprehensively reconstructed by combining organic petrology, molecular biomarkers, stable carbon isotopes and elemental composition. The molecular composition characteristics and stable carbon isotope compositions suggest a major terrestrial organic matter input with a lesser contribution of algae. Oxic to suboxic conditions for the Late Carboniferous sediments can be inferred from the elemental composition and biomarker proxies. A wet, cool, and seasonal dry climate during the Late Carboniferous can be deduced based on biomarkers, macerals, and spore and pollen records. The Late Carboniferous period is characterized by the enhanced burial of terrestrial organic carbon, coinciding approximately with the intensification of the Late Paleozoic Ice Age. The expansion of terrestrial floras in the Late Carboniferous is likely associated with the Late Paleozoic Ice Age.

How many animal-pollinated angiosperms are nectar-producing?

The diversity of plant-pollinator interactions is grounded in floral resources, with nectar considered one of the main floral rewards plants produce for pollinators. However, a global evaluation of the number of animal-pollinated nectar-producing angiosperms and their distribution world-wide remains elusive. We compiled a thorough database encompassing 7621 plant species from 322 families to estimate the number and proportion of nectar-producing angiosperms reliant on animal pollination. Through extensive sampling of plant communities, we also explored the interplay between nectar production, floral resource diversity, latitudinal and elevational gradients, contemporary climate, and environmental characteristics. Roughly 223 308 animal-pollinated angiosperms are nectar-producing, accounting for 74.4% of biotic-pollinated species. Global distribution patterns of nectar-producing plants reveal a distinct trend along latitudinal and altitudinal gradients, with increased proportions of plants producing nectar in high latitudes and altitudes. Conversely, tropical communities in warm and moist climates exhibit greater floral resource diversity and a lower proportion of nectar-producing plants. These findings suggest that ecological trends driven by climate have fostered the diversification of floral resources in warmer and less seasonal climates, reducing the proportion of solely nectar-producing plants. Our study provides a baseline for understanding plant-pollinator relationships, plant diversification, and the distribution of plant traits.

Temporal dynamics of parasite populations and communities of blue sea catfish Ariopsis guatemalensis (Günther, 1864), in a eutrophic coastal lagoon from Mexican Pacific

ABSTRACT The temporal dynamics of parasite populations and communities of blue sea catfish Ariopsis guatemalensis from a tropical eutrophic coastal lagoon was studied during an annual cycle. A total of 620 adult fishes were collected between January and December 2019. Eleven taxa of parasites were identified, three of monoxenous (single-host life cycle), and eight of heteroxenous (multi-host life cycle) parasites. The infection levels of two monoxenous (Neotetraonchus vegrandis and Ergasilus sp.) and five heteroxenous (Austrodiplostomum sp. Pseudoacanthostomum panamense, Pseudoleptorhynchoides lamothei, Contracaecum sp. and Hysterothylacium perezi) parasite species varied between sampling months and/or climatic seasons. The infection dynamics of these group of parasites were influenced by environmental changes generated by the dry/rainy cycle, which can affect the availability of intermediate host populations, and the feeding and reproductive behaviour of the host. Although the species composition of the parasite communities remains quite stable over time, its structure registers important changes mainly during the rainy season. Some host traits such as the feeding and reproductive behaviour, body size, physical condition, and sex of the host, as well as the temporal replacement of numerically dominant parasite species, were the main factors responsible for variations in the parasite community structure.

Historical and contemporary climate jointly determine angiosperm plant diversity patterns across east Eurasia

Mechanisms underlying large‐scale spatial patterns of species richness are one of the central issues in ecology. Although contemporary climate, evolutionary history, and historical climate change have been proposed as drivers of species richness patterns, variation in the relative importance of different factors remains a major challenge. Here, using newly compiled distribution data with a spatial resolution of 100 × 100 km for 43 023 angiosperms plant species in east Eurasia, we mapped species richness patterns for plants with different growth forms (i.e. woody versus herbaceous) and range sizes (i.e. wide‐ranged versus narrow‐ranged species), and compared the relative importance of the four hypotheses in explaining these patterns, i.e. freezing tolerance hypothesis, historical climate change hypothesis, Janzen's hypothesis (predicting that climate seasonality and topography determine species richness patterns), and diversification rate hypothesis. We found that species richness of all angiosperm plants presented a clear latitudinal gradient and was highest in southwestern China and Central Asian mountains. Notably, species richness patterns and their dominant drivers differed between species groups. Historical climate change was the dominant driver for richness patterns of all and herbaceous species. The freezing tolerance hypothesis dominated the drivers for all woody species, while Janzen's hypothesis dominated narrow‐ranged woody and herbaceous species. Our study suggests that different hypotheses contribute to large‐scale plant richness patterns via their effects on different plant groups. Our results did not support the diversification rate hypothesis, but demonstrated the high importance of historical climate change to plant diversity in east Eurasia, providing new perspectives on the mechanisms of plant diversity patterns in this continent.

Geographic patterns and climatic drivers of the mean genus age of liverworts in North America

Phylogenetic niche conservatism posits that species tend to retain ancestral ecological traits and distributions, which has been broadly tested for lineages originating in tropical climates but has been rarely tested for lineages that originated and diversified in temperate climates. Liverworts are thought to originate in temperate climates. Mean lineage age reflects evolutionary history of biological communities. Here, using regional liverwort floras across a long latitudinal gradient from tropical to arctic climates in North America, we test the age-component of the temperate niche conservatism hypothesis. Mean genus age (MGA) was estimated for each of 76 regional floras of liverworts. We related MGA to climatic variables for North America as a whole and for its eastern and western parts separately, and used variation partitioning analysis to assess the relative importance of temperature- versus precipitation-related variables and of climate extremes versus seasonality on MGA. We found that older genera of liverworts tend to concentrate in humid regions of intermediate temperatures in the range of 10 °C–20 °C, from which liverworts have adapted to and diversified into more arid, colder, and hotter regions, supporting the temperate niche conservatism hypothesis. We also found that across North America the MGA of liverwort assemblages is more strongly affected by precipitation-related variables than by temperature-related variables, and is more strongly affected by climate extremes than by climate seasonality. Geographic patterns of the MGA of liverworts are consistent with the temperate niche conservatism hypothesis, rather than the tropical niche conservatism hypothesis, the latter of which is broadly supported by angiosperms.

Edaphoclimatic variation and harvest seasonality as determining factors of multidimensional quality in avocado cv. hass grown in the tropics

The increase in cultivated areas in tropical zones such as Colombia for avocado cv. Hass and the lack of knowledge on edaphoclimatic relationships with factors associated with quality led to the present research. The aim of this research was to establish the relationship of soil, climatic, spatial factors (plot location), and harvest seasonality (principal and transitory) with the multidimensional quality of avocado cv. Hass planted under tropical conditions. This research was carried out on eight farms located in three producing subregions. Soil, environmental and harvest data were recorded for three years (2015–2017) in each plot. Avocado fruit samples were used to determine the parameters of macronutrient, fatty acids, minerals, and vitamin E. Descriptive, inferential statistics, multivariate analysis, effect size, second-order exponential model, and causal relationships were used to determine variables associated with soil, climate, harvest seasonality, and spatial location, and to determine quality parameters. The results established a relationship between nutritional quality and the origin region. Similarly, it was possible to identify parameters associated with differential quality with a robust statistical methodology to propose origin as a differentiating factor for quality. This study provided useful information for the value chain that selected the best areas for avocado crops according to market expectations and nutritional quality criteria.

Delivering and Evaluating Climate Services: The North Central U.S. Climate and Drought Webinar Series

Abstract Evaluation of near-term (sub)seasonal climate services’ impact is challenging but necessary for ensuring that society’s needs for actionable information are met. We use a descriptive study of the monthly North Central U.S. Climate and Drought Webinar Series at two time points (2014 and 2021) to examine societal impacts on capacity-building, sensemaking, fact-establishing, communication, decision-making, and social–ecological systems. The North Central U.S. Climate and Drought Webinar Series arose following a 2011 climate disaster and established itself over the next 10 years as a monthly resource for climate and impact information translation and interaction. Survey respondents indicated early benefits related to understanding how to find and use climate information and improved conceptual understanding of climate issues and problems. Many used webinar information to compare with other sources of data or to incorporate into their own communications, uses which can increase overall societal trust in climate information over time. Attendees’ self-reported capacity for using climate information in decision-making and actual use of information in specific decisions or management contexts increased as the webinar series approached the 10-yr mark. Most participants did not note financial or other social–ecological outcomes of their use of the webinars. We conclude by recommending that climate services be evaluated over sufficiently long time periods to capture evolving impacts and that evaluations incorporate impact rubrics that measure subtle yet important societal capacities and decision-making processes related to climate risk management.

A Framework for Joint Verification and Evaluation of Seasonal Climate Services across Socioeconomic Sectors

Abstract Assessing the information provided by coproduced climate services is a timely challenge, given the continuously evolving scientific knowledge and its increasing translation to address societal needs. Here, we propose a joint evaluation and verification framework to assess prototype services that provide seasonal forecast information based on the experience from the Horizon 2020 (H2020) Climate forecasts enabled knowledge services (CLARA) project. The quality and value of the forecasts generated by CLARA services were first assessed for five climate services utilizing the Copernicus Climate Change Service seasonal forecasts and responding to knowledge needs from the water resources management, agriculture, and energy production sectors. This joint forecast verification and service evaluation highlights various skills and values across physical variables, services, and sectors, as well as a need to bridge the gap between verification and user-oriented evaluation. We provide lessons learned based on the service developers’ and users’ experience and recommendations to consortia that may want to deploy such verification and evaluation exercises. Last, we formalize a framework for joint verification and evaluation in service development, following a transdisciplinary (from data purveyors to service users) and interdisciplinary chain (climate, hydrology, economics, and decision analysis).

Unraveling the dynamic interplay of microbial communities associated to Lupinus angustifolius in response to environmental and cultivation conditions

Microorganisms form dynamic communities with plants, providing benefits such as nutrient acquisition and stress resilience. Understanding how these microorganisms are affected by environmental factors such as growth conditions and soil characteristics are essential for harnessing these communities for sustainable agriculture practices and their response to climate change. The microbiome associated to Lupinus angustifolius, a legume native in Europe, with a high protein value and stress resilience was characterized for the first time. Using 16S rRNA gene and ITS amplicon sequencing, we characterized the compositional and temporal changes of the bacterial and fungal communities associated to the soil, rhizosphere, and plant compartments where Lupinus angustifolius grows naturally. Our results suggest that the main difference in the soil microbial communities is related to the edaphic properties, although environmental factors such as temperature, humidity or rainfall also influenced the composition of the soil microbial communities. We also characterized the bacterial communities associated with the rhizosphere, roots, nodules, and leaves of wild plants collected in the field and compared them against plants obtained under greenhouse conditions. In the plant compartments, the bacterial composition appeared to be more affected by the growing conditions (field vs greenhouse), than by soil characteristics or location. These results can be used to identify key taxa that may play crucial roles in the development and adaptation of the host plant and its associated microbiota to environmental changes and highlight the importance of characterizing the plant microbiomes in their natural habitats. Soil, influenced by climatic seasons, shapes the plant microbiome assembly. Lupinus recruits a core microbiome across rhizosphere, roots, nodules, and leaves, that is stable across locations. However, cultivation conditions may alter microbiome dynamics, impacting the adaptability of its components. Wild plants show a resilient and adaptable microbiome while germination and cultivation in greenhouse conditions alter its composition and vulnerability.

Mangrove ecosystems as fundamental habitats for fish from the Mexican Caribbean: An evaluation between a conserved and restoration zone

Mangrove ecosystems can function as a habitat for many juvenile marine fish species, with provisions of food and refuge. Seemingly, these ecosystems have been extensively reduced due to anthropogenic activity, as is widespread land use and road construction along the coastline. Nonetheless, much needed restoration efforts have increased tremendously over time. This study analyzes fish community, and the manner in which habitats in the mangrove ecosystem are used, comparing two mangrove zones, a conserved zone (healthier state) and one undergoing restoration. Hydrologically, no significant differences were registered (KW p>0.05). Of the 24 species registered, marine species were dominant in the conserved zone and estuarine species dominant in the restoration zone. Juvenile fishes were more abundant in the conserved mangrove zone, with a higher proportion of adults found in the restoration zone. According to Hutcheson’s t test, fish diversity showed significant statistical differences between sites combined with distinct climatic seasons. The Canonical Correspondence Analysis (CCA) indicated a relationship between secondary freshwater species Floridichthys polyommus and Cyprinodon artifrons and greater salinity and temperature, whereas marine species had a higher relationship with well oxygenated sites. A high number of marine fish species in juvenile stage in the conserved area may relate to mangroves functioning as nurseries. This can serve as a useful indicator by managers taking an integral approach to evaluate and monitor present and future mangrove restoration programs and pathways.

Comparative Analysis of Drought Effects on the Soil Moisture Level and Penetration Resistance in Conventional and Non-Conventional Tillage Systems in Maize Production

The period of extreme weather anomalies in recent years has challenged farmers, and this has encouraged greater adaptability in farming practices. In the last decade, conventional tillage systems have been complemented by more biologically based cropping systems. The research evaluated the impact of drought on soil physical parameters in maize production by testing different conventional and non-conventional tillage systems to ensure optimal soil physical parameters. In the analysis of the prevailing weather conditions, rainfall values were divided into two parts, the pre-growing season and the growing season. We studied different climatic seasons. In 2021, the soil moisture content in the upper shallow 15 cm soil layer during the sowing period in April in the case of conventional tillage was significantly lower than in reduced tillage, conservation tillage and strip tillage. The most significant difference was measured between conventional and conservation tillage, with a difference of 11.25 v/v%. The 2022 crop year was extremely dry. In June, the highest moisture value in the soil was measured in the case of strip tillage with a value of 21.64 v/v%, which was more than 60% higher than in the case of conventional and conservation tillage. In conventional tillage, a very pronounced compacted layer was observed in the lower part of the ploughed layer. This zone reached a compaction of 6.9 MPa between 28 and 34 cm, which is agronomically harmful. No compacted soil layer was found in the experiment site under conservation tillage. In the severe drought year of 2022, only the strip-till system provided the proper water management conditions for the maize stand.

Explainable El Niño predictability from climate mode interactions.

The El Niño-Southern Oscillation(ENSO) provides most of the global seasonal climate forecast skill1-3, yet, quantifying the sources of skilful predictions is a long-standing challenge4-7. Different sources of predictability affect ENSO evolution, leading to distinct global effects. Artificial intelligence forecasts offer promising advancements but linking their skill to specific physical processes is not yet possible8-10, limiting our understanding of the dynamics underpinning the advancements. Here we show that an extended nonlinear rechargeoscillator (XRO) model shows skilful ENSO forecasts at lead times up to 16-18 months, better than global climate models and comparable to the most skilful artificial intelligence forecasts. The XRO parsimoniously incorporates the core ENSO dynamics and ENSO's seasonally modulated interactions with other modes of variability in the global oceans. The intrinsic enhancement of ENSO's long-range forecast skill is traceable to the initial conditions of other climate modes by means of their memory and interactions with ENSO and is quantifiable in terms of these modes' contributions to ENSO amplitude. Reforecasts using the XRO trained on climate model output show that reduced biases in both model ENSO dynamics and in climate mode interactions can lead to more skilful ENSO forecasts. The XRO framework's holistic treatment of ENSO's global multi-timescale interactions highlights promising targets for improving ENSO simulations and forecasts.