Search

Climate change is increasingly influencing the water cycle, hindering the effective management of water resources in various sectors. Lazio, central Italy, exhibits a wide range of climatic conditions, stretching from the Tyrrhenian coast to the Apennines. This study assessed a crucial aspect of climate change, focusing specifically on reference evapotranspiration (ETo) and its associated hydrological variables. The seasonal Mann–Kendall (MK) test was used to assess trends in gridded data. The K-means algorithm was then applied to divide Lazio into four homogeneous regions (clusters), each characterized by distinct trends in hydrological variables. The analysis revealed statistically significant increasing trends (p ≤ 0.01) in temperature, solar radiation, and ETo, with more marked effects observed in the coastal and hilly clusters. In contrast, statistically significant decreasing trends (p ≤ 0.01) were observed for relative humidity, while no statistically significant trends (p > 0.01) were observed for precipitation. This study's methodology, combining trend analysis and clustering, provides a comprehensive view of ETo dynamics in Lazio, aiding in pattern recognition and identifying regions with similar trends. [ABSTRACT FROM AUTHOR]

The 3rd International Electronic Conference on Agronomy (IECAG 2023) was held from October 15 to October 30, 2023. The conference brought together participants from various countries, including students, academics, scientists, and experts in agronomy and related fields. The conference focused on addressing current challenges, exploring innovative solutions, and promoting global collaboration within the agronomy community. The conference included presentations and discussions on a wide range of agronomy research topics, such as disease control, agro-ecology innovation, and digital farming. The conference also featured keynote speeches from distinguished scientists and was supported by various sponsors and media partners. [Extracted from the article]

Enhancing spatial data attributes is crucial for effective basin-scale environmental modelling and improving our understanding and management of precipitation patterns. In this study, we focused on reconstructing homogeneous areal precipitation data in the complex terrain of the Calore River Basin (CRB) in Southern Italy. Until 1869, weather observations in the region were inconsistent, unstandardised, and lacked coordination, but the establishment of meteorological observatories brought a more unified approach to weather monitoring. We relied on the rainfall data obtained from two of these historical observatories: Benevento (1869–present) and Montevergine (1884–present). We utilised a statistical regression framework that considered rainfall measurements and temporal properties from specific locations to reconstruct and visually analyse the evolution patterns of annual mean areal precipitation (MAP) in the CRB from 1869 to 2020. The analysis revealed that mean MAP decreased from 1153 mm yr−1 (1869–1951) to 998 mm yr−1 (1952–2020). This decrease was accompanied by a reduction in interannual variability (from 168 mm yr−1 to 147 mm yr−1 standard deviation), and the difference between the means was significant (p < 0.0001), suggesting a sudden shift in the time-series. These findings provide a basis for CRB water resource management and insights for modelling other complex Mediterranean basins. [ABSTRACT FROM AUTHOR]

Future climate change is expected to significantly alter the growth of vegetation in grassland systems, in terms of length of the growing season, forage production, and climate-altering gas emissions. The main objective of this work was, therefore, to simulate the future impacts of foreseen climate change in the context of two pastoral systems in the central Italian Apennines and test different adaptation strategies to cope with these changes. The PaSim simulation model was, therefore, used for this purpose. After calibration by comparison with observed data of aboveground biomass (AGB) and leaf area index (LAI), simulations were able to produce various future outputs, such as length of growing season, AGB, and greenhouse gas (GHG) emissions, for two time windows (i.e., 2011–2040 and 2041–2070) using 14 global climate models (GCMs) for the generation of future climate data, according to RCP (Representative Concentration Pathways) 4.5 and 8.5 scenarios under business-as-usual management (BaU). As a result of increasing temperatures, the fertilizing effect of CO2, and a similar trend in water content between present and future, simulations showed a lengthening of the season (i.e., mean increase: +8.5 and 14 days under RCP4.5 and RCP8.5, respectively, for the period 2011–2040, +19 and 31.5 days under RCP4.5 and RCP8.5, respectively, for the period 2041–2070) and a rise in forage production (i.e., mean biomass peak increase of the two test sites under BaU: +53.7% and 62.75% for RCP4.5. and RCP8.5, respectively, in the 2011–2040 period, +115.3% and 176.9% in RCP4.5 and RCP8.5 in 2041–2070, respectively,). Subsequently, three different alternative management strategies were tested: a 20% rise in animal stocking rate (+20 GI), a 15% increase in grazing length (+15 GL), and a combination of these two management factors (+20 GI × 15 GL). Simulation results on alternative management strategies suggest that the favorable conditions for forage production could support the increase in animal stocking rate and grazing length of alternative management strategies (i.e., +20 GI, +15 GL, +20 GI × 15 GL). Under future projections, net ecosystem exchange (NEE) and nitrogen oxide (N2O) emissions decreased, whereas methane (CH4) rose. The simulated GHG future changes varied in magnitude according to the different adaptation strategies tested. The development and assessment of adaptation strategies for extensive pastures of the Central Apennines provide a basis for appropriate agricultural policy and optimal land management in response to the ongoing climate change. [ABSTRACT FROM AUTHOR]

Simulating the dynamics of plant species or types in grassland communities remains an open area of research for which the Community Simulation Model (CoSMo) offers novel approaches. The grassland model ModVege was first parameterised based on a functional vegetation typology, in which types "A" and "B" include fast-growing grass species with a phenology-dependent nutrient-capture strategy inherent to fertile grasslands, while the nutrient conservation strategy and late flowering characterise the other types as "b". ModVege was then coupled to the CoSMo rule set to dynamically simulate the relative abundance of plant functional types or individual species, assessed across fertilised and unfertilised, abandoned and mown conditions in a grassland site of the Massif Central of France. While for the simulation of aboveground biomass, model performance is not unambiguously linked to explicit consideration of plant diversity, the simulation of relative abundance for the whole community is satisfactory (relative root mean square error of ~13–25% when simulating functional types and ~28–52% when simulating species). This study extends previous studies by coupling CoSMo, for the first time, to a grassland-specific model and applying it to conditions (long-term observations, extended number of plant species, absence of fertilisation, frequent mowing and abandonment) never investigated before. [ABSTRACT FROM AUTHOR]

The Biology and Life Sciences Forum requires that all papers published in their conference proceedings undergo peer review by expert referees. The review process is single-blind, and submissions are managed through the Sciforum platform. Out of 234 submissions, 81 were accepted and 58 were published, resulting in an acceptance rate of 0.35. Each paper received an average of one review, with a total of 48 reviewers involved. The review process also included checks for compliance with MDPI standards on plagiarism. The author of the document declares no conflict of interest. [Extracted from the article]

There is increasing evidence that the impact of climate change on the productivity of grasslands will at least partly depend on their biodiversity. A high level of biodiversity may confer stability to grassland ecosystems against environmental change, but there are also direct effects of biodiversity on the quantity and quality of grassland productivity. To explain the manifold interactions, and to predict future climatic responses, models may be used. However, models designed for studying the interaction between biodiversity and productivity tend to be structurally different from models for studying the effects of climatic impacts. Here we review the literature on the impacts of climate change on biodiversity and productivity of grasslands. We first discuss the availability of data for model development. Then we analyse strengths and weaknesses of three types of model: ecological, process-based and integrated. We discuss the merits of this model diversity and the scope for merging different model types. [ABSTRACT FROM AUTHOR]

Associated with livestock farming, grasslands with a high diversity of plant species are at the core of low-input fodder production worldwide. However, this Special Issue does not fully consider climate-induced biodiversity change and the extent to which population growth, urbanisation, land-use change, consumption lifestyles and resource exploitation threaten grassland biodiversity as key factors directly or indirectly associated with climate change. For instance, innovative systems at the interface of grassland and cereal production hold promise for reconciling production objectives with the preservation of biodiversity and soil-water-air resources, and pave the way for a multifunctional, sustainable and more climate-resilient agriculture. [Extracted from the article]

This study performs a systematic analysis of the recent and future changes of dry spells (DS) in Croatia. DS are defined as consecutive sequences of days with daily precipitation less than 5 mm of the precipitation-per-day threshold (DS5). Daily precipitation data come from a dense national rain gauge network (covering seven regions) and span the period 1961–2015. The spatial and temporal changes of the observed mean (MDS5) and maximum (MxDS5) seasonal and annual dry spells were analysed by means of the Kendall tau method and the partial trend method. Future changes of DS5 were assessed by employing the three regional climate models (RegCM4, CCLM4 and RCA4) covering the EURO-CORDEX domain with a 12.5-km horizontal resolution, resulting in a realistic orography and land–sea border over Croatia. The models were forced at their boundaries by the four CMIP5 global climate models. For the reference period 1971–2000, the observed, as well as modelled, DS5 were analysed, and the systematic model errors were assessed. Finally, the projections and future changes of the DS5 statistics based on simulations under the high and medium greenhouse gases concentration scenarios (i.e., RCP8.5 and RCP4.5) with a focus on the climate change signal between 1971–2000 and two future periods, 2011–2040 and 2041–2070, were examined. A prevailing increasing trend of MDS5 was found in the warm part of the year, being significant in the mountainous littoral and North Adriatic coastal region. An increasing trend of MxDS5 was also found in the warm part of the year (both the spring and summer), and it was particularly pronounced along the Adriatic coast, while a coherent negative trend pattern was found in the autumn. By applying the partial trend methodology, an increase was found in the very long DS5 (above the 90th percentile) in the recent half of the analysed 55-year period in all seasons, except in the autumn when shortening in the DS5 was detected. The climate change signal during the two analysed future periods was positive for the summer in all regions, weakly negative for the winter and not conclusive for the spring, autumn and year. It was found that no RCM-GCM combination is the best in all cases, since the most successful model combinations depend on the season and location. [ABSTRACT FROM AUTHOR]

Olive and vine cultivations are two of the most important crops in Europe, yielding high quality and value food products. The climate change over the Balkans may elevate the agroecological pressure for the established crops and shift their cultivations areas. One of the widely-used agroclimatic indices is the growing degree days (GDD) which accumulates the necessary thermal units for the selected crops. Despite the advances on the agroclimatic research, there are few available methods for spatiotemporal estimation of this useful index. So, this research is focused on the construction of simple and reliable equations for the calculation and projection of olive and vine cultivations' GDD over the Balkans. The models' input parameters are the time, the altitude, the distance from the seashore, and the latitude. Its assembly is made by the extracted spatial data, combined with the Agri4Cast dataset for the period of 1980 to 2018 incorporating the regional climate change trend. The results indicate that the most influential parameter is the time, followed by the latitude, for both cultivations. According to the projections, as quantified by GDD, a vast sprawl of olive and vine cultivation areas will have been formed to the northern parts of the studied area. To be more precise, the viticulture could expand spatially by 28.8% (of the Balkans area) by 2040, and by 15.1% to 2060, when the olive cultivations' area could sprawl 23.9% by 2040 and 20.3% by 2060. [ABSTRACT FROM AUTHOR]

Semi-natural grasslands are particularly important in mountainous areas of Romania, being the only source of forage for many farmers. The aim of this study was to investigate the changes in forage quantity and quality as a result of Urea Ammonium nitrate (UAN) liquid fertilization. The experiment was carried out in the eastern part of Apuseni Mountains, Romania on a Festuca rubra L.-Agrostis capillaris L. grassland located at 1240 m altitude. Studies were made over three years of experimental trial (2014–2016) and covered four experimental plots in three replicates, as follows: V1–control plot, unfertilized; V2–plot fertilized with 50 kg UAN ha−1 year−1; V3–plot fertilized with 75 kg UAN ha−1 year−1, and V4–plot fertilized with 100 kg UAN ha−1 year−1. The experimental plots were harvested once per year and the botanical composition, dry matter yield and forage quality were assessed. Our results showed important changes in forage quantity, quality and diversity as a result of UAN fertilization. Starting from the second experimental year the dominance/co-dominance ratio changed favoring the species from Poaceae family. Dry matter increased as a result of UAN fertilization but forage quality was negatively affected by the higher percentage of participation of species from other botanical families which have higher crude fiber content and lower crude protein. Based on our results we recommend moderate fertilization with UAN up to 50 kg UAN ha−1 year−1 for semi-natural grasslands located in soil-climatic conditions similar to those in our experiment. [ABSTRACT FROM AUTHOR]

Regional studies on the erosive power of rainfall patterns are still limited and the actual impacts that may follow on erosional and sedimentation processes are poorly understood. Given the several interrelated challenges of environmental management, it is also not always unclear what is relevant for the development of adaptive and integrated approaches facilitating sustainable water resource management. This editorial introduces the Special Issue entitled "Rainfall Erosivity in Soil Erosion Processes", which offers options to fill some of these gaps. Three studies performed in China and Central Asia (by Duulatov et al., Water2019, 11, 897, Xu et al., 2019, 11, 2429, Gu et al. 2020, 12, 200) show that the erosion potential of rainfall is increasing in this region, driving social, economic, and environmental consequences. In the same region (the Weibei Plateau in China), Fu et al. (Water2019, 11, 1514) assessed the effect of raindrop energy on the splash distance and particle size distribution of aggregate splash erosion. In the Mediterranean, updated estimates of current and future rainfall erosivity for Greece are provided by Vantas et al. (Water2020, 12, 687), while Diodato and Bellocchi (Water2019, 11, 2306) reconstructed and investigated seasonal net erosion in an Italian catchment using parsimonious modelling. Then, this Special Issue includes two technologically oriented articles by Ricks at al. The first (Water2019, 11, 2386) evaluated a large-scale rainfall simulator design to simulate rainfall with characteristics similar to natural rainfall. The data provided contribute to the information that may be useful for the government's decision making when considering landscape changes caused by variations in the intensity of a rainfall event. The second article (Water2020, 12, 515) illustrated a laboratory-scale test of mulching methods to protect against the discharge of sediment-laden stormwater from active construction sites (e.g., highway construction projects). [ABSTRACT FROM AUTHOR]

The occurrence of hydrological extremes in the Amazon region and the associated sediment loss during rainfall events are key features in the global climate system. Climate extremes alter the sediment and carbon balance but the ecological consequences of such changes are poorly understood in this region. With the aim of examining the interactions between precipitation and landscape-scale controls of sediment export from the Amazon basin, we developed a parsimonious hydro-climatological model on a multi-year series (1997–2014) of sediment discharge data taken at the outlet of Óbidos (Brazil) watershed (the narrowest and swiftest part of the Amazon River). The calibrated model (correlation coefficient equal to 0.84) captured the sediment load variability of an independent dataset from a different watershed (the Magdalena River basin), and performed better than three alternative approaches. Our model captured the interdecadal variability and the long-term patterns of sediment export. In our reconstruction of yearly sediment discharge over 1859–2014, we observed that landscape erosion changes are mostly induced by single storm events, and result from coupled effects of droughts and storms over long time scales. By quantifying temporal variations in the sediment produced by weathering, this analysis enables a new understanding of the linkage between climate forcing and river response, which drives sediment dynamics in the Amazon basin. [ABSTRACT FROM AUTHOR]

Multi-species grasslands are reservoirs of biodiversity and provide multiple ecosystem services, including fodder production and carbon sequestration. The provision of these services depends on the control exerted on the biogeochemistry and plant diversity of the system by the interplay of biotic and abiotic factors, e.g., grazing or mowing intensity. Biogeochemical models incorporate a mechanistic view of the functioning of grasslands and provide a sound basis for studying the underlying processes. However, in these models, the simulation of biogeochemical cycles is generally not coupled to simulation of plant species dynamics, which leads to considerable uncertainty about the quality of predictions. Ecological models, on the other hand, do account for biodiversity with approaches adopted from plant demography, but without linking the dynamics of plant species to the biogeochemical processes occurring at the community level, and this hampers the models' capacity to assess resilience against abiotic stresses such as drought and nutrient limitation. While setting out the state-of-the-art developments of biogeochemical and ecological modelling, we explore and highlight the role of plant diversity in the regulation of the ecosystem processes underlying the ecosystems services provided by multi-species grasslands. An extensive literature and model survey was carried out with an emphasis on technically advanced models reconciling biogeochemistry and biodiversity, which are readily applicable to managed grasslands in temperate latitudes. We propose a roadmap of promising developments in modelling. [ABSTRACT FROM AUTHOR]

Knowledge on sustainable grassland management is available in the large body of literature. However, it is unclear where to look for it, and what is really relevant to the many interrelated challenges of sustainable grassland management. This special issue illustrates options to fill some of those gaps. This editorial introduces the Special Issue entitled "Grassland Management for Sustainable Agroecosystems". Two review articles deal with (i) concepts for monitoring grassland degradation (by Tiscornia et al. Agronomy2019, 9, 239) and (ii) impacts of alternative management practices and disturbances (by Wagle and Gowda et al. Agronomy2018, 8, 300). One paper (by Steiner et al. Agronomy2019, 9, 699). summarized a series of papers of the special issue. Other topics covered include four main aspects: (I) Landscape features (Ravetto Enri et al. Agronomy2019, 9, 333), two papers by Northup et al. Agronomy2019, 9, 329, Northup et al. Agronomy2019, 9, 281, and Ma et al. Agronomy2019, 9, 238; (II) climate (Zhou et al. Agronomy2019, 9, 219, Starks et al. Agronomy2019, 9, 235, and Moinet et al. Agronomy2019, 9, 124); (III) soil fertility (Franzluebbers et al. Agronomy2019, 9, 204, Poblete-Grant et al. Agronomy2019, 9, 191); and (IV) one on modeling (Puche et al. Agronomy2019, 9, 183). Two additional papers are from Andueza et al. Agronomy2019, 9, 273 (on the feed value of barn-dried hay) and Úbeda et al. Agronomy2019, 9, 340 (on the role of prescribed burns). [ABSTRACT FROM AUTHOR]

In the low Mediterranean basin, late spring and autumn rainfall events have the potential to increase discharge and transport substantial amounts of sediment soil (that is, the net soil erosion from a watershed). For the Alento River Basin (ARB), located in the low Tyrrhenian coast of Italy, we estimated changes of net erosion as dependent on the seasonality of antecedent soil moisture and its control on rainfall-runoff and erosivity. Based on rainfall and runoff erosivity sub-models, we developed a simplified model to evaluate basin-wide sediment yields on a monthly basis by upscaling point rainfall input. For the period 1951–2018, the reconstruction of a time series of monthly net erosion data indicated a decreasing trend of the sediment yield after 1991. Revegetation and land abandonment that occurred in the last decades can explain such a decrease of net erosion, which occurred even when rainfall erosivity increased. This response, obtained at the basic scale, does not exclude that rapidly developing mesoscale convective systems, typically responsible for the heaviest and most destructive rainfall events in the ARB, can affect small catchments, which are the most vulnerable systems to storm-driven flash floods and soil erosion hazards during soil tilling in spring and at beginning of autumn. [ABSTRACT FROM AUTHOR]

Severity of drought in California (U.S.) varies from year-to-year and is highly influenced by precipitation in winter months, causing billion-dollar events in single drought years. Improved understanding of the variability of drought on decadal and longer timescales is essential to support regional water resources planning and management. This paper presents a soft-computing approach to forecast the Palmer Drought Severity Index (PDSI) in California. A time-series of yearly data covering more than two centuries (1801–2014) was used for the design of ensemble projections to understand and quantify the uncertainty associated with interannual-to-interdecadal predictability. With a predictable structure elaborated by exponential smoothing, the projections indicate for the horizon 2015–2054 a weak increase of drought, followed by almost the same pace as in previous decades, presenting remarkable wavelike variations with durations of more than one year. Results were compared with a linear transfer function model approach where Pacific Decadal Oscillation and El Niño Southern Oscillation indices were both used as input time series. The forecasted pattern shows that variations attributed to such internal climate modes may not provide more reliable predictions than the one provided by purely internal variability of drought persistence cycles, as present in the PDSI time series. [ABSTRACT FROM AUTHOR]

The prevalence of extreme drought and flooding is posing a threat to the food security of Sub-Saharan African countries. There are national and international calls for actions to investigate the level of resilience of existing crop cultivars to multiple abiotic stress conditions. A two-year study was carried out in South Africa to determine growth, development, yield, yield components, and physiological responses of two contrasting maize cultivars—PAN 413 (drought tolerant) and PAN 6Q-245 (drought intolerant) under drought and flooding. The drought effect on grain yield was more pronounced from mid-vegetative to tasselling stages, regardless of the cultivar with yields deviating from the control by 53–58% (2015/2016) and 34–42% (2016/2017). The effect of flooding on grain yield was pronounced at the early vegetative stage for both cultivars, with yield reductions ranging between 26–30% (2015/2016) and 15–21% (2016/2017). Results from the study indicated that existing maize cultivars (drought tolerant and drought intolerant) are both prone to likely extreme drought events experienced during the tasselling stage. Results also showed that both cultivars are prone to probable flooding events before the tasselling stage. It is recommended that plant breeders' efforts be directed to developing maize cultivars with multiple stress tolerances. [ABSTRACT FROM AUTHOR]

Highly dynamic hydro-geomorphic processes are known to drive exports of carbon (C) from river basins, but are not yet fully understood. Within this study, we simulated total organic carbon (TOC) exports at the outlet of Lake Simojärvi in the Gulf of Bothnia (Finland) with a parsimonious hydrological model. With thorough consideration of the dependence of erosion and sediment transport processes on seasonal precipitation rates, a satisfactory agreement was obtained between modelling and experimental observations (1962–2005). This provided confidence in the capability of the parsimonious model to represent temporal and spatial export dynamics. In the period 1860–2014, TOC export at the outlet of Lake Simojärvi was estimated to be highest on average (~5.5 Mg km−2·year−1) over 1974–2014 while the lowest TOC export (~2.5 Mg km−2·year−1) was estimated in 1860–1918 (with high levels of interannual-to-multidecadal variation). Regional simulations indicate that TOC increased in recent decades (on average, 4–5 Mg km−2·year−1 in 1974–2014 against ~3 Mg km−2·year−1 in 1940–1973) in northern Scandinavia and Finland. Warming-induced variability of TOC (which depends on precipitation patterns) may have altered the rates of C exchanges in aquatic ecosystems over recent years. TOC exports may continue to increase in boreal catchments with increasing temperatures as represented by future projections. [ABSTRACT FROM AUTHOR]