Present Climate Change Scenarios Research Articles

Nitrogen Gradient Optimization with Kharif Legumes on Agronomic Parameters in Zero-till Rabi Maize

Background: With the SDG goals of using the generated output of one season on other season for managing the resource potential so to unlock the crop productivity is being the best alternative that need to be looked out in present climate change scenario. So, the present trial is focuses on the lines of residue management of legumes on maize sequence with nitrogen as the driving gradient in 2021-22 and 2022-23. Methods: The experiment is laid out in split-plot design with 18 treatments consisted of C1N1: groundnut100% RDN-maize, C1N2: groundnut75% RDN-maize, C2N1: soybean100% RDN-maize, C2N2: soybean75% RDN-maize, C3N1: greengram100% RDN-maize, C3N2: greengram75% RDN-maize as main-plots and 3 subplots viz.100% RDN, 125% RDN, 150% RDN (kharif and rabi respectively) during two years of study. Result: Among the different cropping systems, the preceding kharif greengram with 100% RDN on rabi zero-till maize showed higher growth parameters i.e. plant height, leaf area, leaf chlorophyll content (SPAD reading), dry matter at 30,60,90 DAS and at harvest and yields in both years. However, with respect to nitrogen levels, application of 150% RDN to rabi maize showed significantly higher growth and yields followed by 125% RDN and lowest was seen in 100% RDN in rabi respectively. On the other hand, the interaction effect was found significant at only 60 DAS in both years.

Distribution pattern of large old Ginkgo biloba in China under climate change scenarios.

Large old Ginkgo biloba trees (LOGTs), with profound ecological and cultural significance in China, face increasing threats from climate change and human activities. We employed the BIOCLIM and DOMAIN species distribution models to predict their spatial patterns under the present climate and doubled-CO2 climate change scenario in 2100. We collected 604 validated LOGT occurrence records and data on 19 bioclimate factors for the analysis. Our study yielded a LOGT geographic distribution pattern covering a wide latitudinal belt extending from south subtropical to temperate zones in central and eastern China, concentrating in low elevations and coastal regions. The principal component analysis identified the dominant bioclimatic factors shaping their distribution, namely annual precipitation and low winter temperatures. BIOCLIM and DOMAIN generated predicted suitable habitats that match the present distribution range well. However, under the future climate scenario, the models indicated habitat retentions mainly in the core distribution areas and habitat losses mainly in the southern edge of the present range and scattered pockets elsewhere. Some retained habitats, including excellent ones, will suffer from fragmentation. The predicted new habitats may permit some range expansion and migration but are beset by small patch size and large interpatch distance, bringing fragmentation and gene flow restrictions. The anticipated projected range decline highlights considerable threats climate change poses to the long-term survival of the precious natural-cum-cultural resource. Understanding the distribution patterns and underlying drivers and distillation of practical conservation measures can foster sustainable management vis-a-vis the looming global change.

Estimates of Genetic Variability, Association Studies and Per se Performance of Tomato Genotypes for Growth and Yield Parameters Under Drought Stress Conditions

Aims: Drought tolerance is a complex phenomenon, influenced by the coordinated activity of many genes. Breeding for drought tolerance is the need for contemporary research under the present climate change scenario. Further, the estimates of variability and degree of association among the traits would facilitate the selection for yield under drought conditions as it is highly influenced by environmental factors. This study aimed for the enhancement of selection capacity for drought stress tolerance in tomato based on the measures of genetic variability parameters and extent of association among traits which in turn used to identify drought tolerant genotypes. Methodology: The experiment was conducted with 39 tomato genotypes with 2 replications under normal and drought stress condition (15 days irrigation interval) following a Randomized Block Design during summer, 2020 at Department of Biotechnology and Crop Improvement, Kittur Rani Channamma College of Horticulture, Arabhavi. Results: High heritability along with moderate to high GAM was recorded for all the characters under study in both control and drought stress condition, indicating predominance of additive gene action for these traits. Yield per plant had positive and strong association with plant height, stem girth, number of primary branches, number of fruits per plant and average fruit weight. Further, path analysis revealed high desirable direct effect of average fruit weight and number of fruits per plant on yield per plant. Thus, there is ample of scope for improving these traits through selection. The genotypes viz., EC-634394, EC-638519 and Kashi Anupama shown superior performance for yield along with other yield attributing traits and also exhibited less percent reduction in these traits under drought condition.

Cross-Species Transferability of SSR Markers for Analyzing Genetic Diversity of Different Vicia species Collections

Legumes play an essential role in sustainable agriculture due to their ability to fix nitrogen and high protein content. Vicia is a relevant genus of the Fabaceae family that includes important crop species, such as V. faba and V. sativa, but also other species considered minor crops. They are mainly used as animal feed and usually cope resiliently with extreme conditions; therefore, they could play an essential role in sustainable agriculture under the present scenario of climate change and growing population. However, the scarcity of commercial cultivars limits their use. The Spanish National Plant Genetic Resources Center has collections of several species of the genus Vicia, including international landraces, which could be an essential source of biodiversity for breeding programs. These seed resources are underutilized due to the limited availability of characterization data, including the lack of molecular markers for these species. In this study, we analyzed the cross-transferability of SSR (simple sequence repeat) molecular markers from V. sativa and V. ervilia to distinct species of the genus Vicia. We also used heterologous validated markers for the genotypic characterization and genetic diversity analysis of almost 500 accessions of three undercharacterized Vicia collections: V. articulata (one-flower vetch), V. ervilia (bitter vetch), and V. narbonensis (narbon bean or French vetch). Subsequently, these molecular data were integrated with passport and agromorphological data to select representative varieties from these Vicia collections and establish core collections, with minimum loss of genetic diversity versus the Spanish total collections. The characterization of these legume collections is an essential step from an economic and ecological point of view to obtain selected Vicia varieties to be used in sustainable agriculture.

Chili: Breeding and Genomics

Chili or hot pepper is an important vegetable cum spice crop, which has huge commercial applications in food, nutrition, pharmaceutical and cosmetic industries. The Capsicum genus originated in Central America with about 35 species, of which five are domesticated for cultivation. Color and pungency-related components such as capsanthins, capsaicinoids and capsinoids are unique to Capsicum genus. There exists large variability in the genus and genetic resources have been explored for breeding varieties/ hybrids with resistance/ tolerance to biotic and abiotic stresses with enhanced fruit quality. In the present climate change scenario, there is an evolution of various pests and diseases, which requires continuous exploration of germplasm including related cultivated and wild species for novel genes/alleles. Conventional breeding has led to the development of improved lines/varieties/hybrids. Whole genome sequence information and the pan genome of chili are publicly available, which can help in the development of molecular markers associated with key traits of importance. Advancements in genomic resources and next-generation sequencing techniques can be employed to accelerate breeding programs.

Microplastics in groundwater: An overview of source, distribution, mobility constraints and potential health impacts during the anthropocene

Microplastics (MPs) have already been detected in various environmental matrices like soil, sediment, and surface water, and recently in groundwater also. The occurrence of MPs in groundwater depends up on the transportation through recharge and may controlled by source and local hydrogeology, and partly on the process of surface water-groundwater interaction (SW-GW). Based on the available studies, we intended to establish a hypothetical overview on the source and process-dependent occurrence of MPs in groundwater across terrestrial and coastal aquifers. Groundwater recharge from agricultural stagnant water, losing streams near dumping sites and agricultural fields, effluents from wastewater treatment plants, septic system failure etc. are the potential sources of MPs in groundwater. The factors like sea level rise and tidal pumping are among the major factors which may control the migration of MPs in coastal aquifer along with the physical and chemical properties of the aquifer media. These MPs have another ecological concern as they can adsorb persistent organic pollutants as well as heavy metals and transfer them to animal tissues through food chain. Studies are being conducted mainly focusing the MP contamination in surface water, marine environment and soil, and very limited studies are available to address the source of MPs in groundwater. However, no such study has been done on the existence, profusion, or environmental factors that contribute to MP pollution in the groundwater in relation to the present climate change scenario. Understanding the extent of MP contamination in groundwater systems is necessary for developing effective management strategies and minimizing their impact on the environment and human health. This study focusses on the source along with the controlling factors of the migration of MPs towards groundwater including the effect of climate change.

Impacts of climate change on the distribution of venomous Conus (Gastropoda: Conidae) species in the Indo-Pacific region

Climate change is affecting the distribution of marine organisms worldwide, including venomous marine gastropods that offer risks to human health, but also potential pharmacological resources, such as Conus sp. Species Distribution Models (SDMs) are valuable tools for predicting species distribution under climate change. The objective of our study was to evaluate the potential distribution of Conus geographus and C. textile in the Indo-Pacific region under different climate change scenarios for 2050 and 2090. We constructed SDMs with MaxEnt for each species, using bioclimatic variables from Bio-ORACLE and NOAA, and occurrence data from GBIF. We projected the best-fit model for the present and different future climate change scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5). We obtained high accuracy SDMs for C. geographus and C. textile, with Temperature and Primary Productivity as the main explanatory variables. Our future projections reveal that both species may react differently to climate change. Southeast Asia and Micronesia will continue to provide a climatically appropriate environment for both species; however, they may become more suitable for C. geographus and less suitable for C. textile. This may lead to a higher risk of human envenomation by C. geographus, but a lower risk by C. textile. A decreased suitability for C. textile may also lead to the loss of potential pharmacological resources among its range. Our study emphasizes how SDMs can be used to assess the future distribution of species with human health implications, which can aid in the monitoring of venomous marine species.

Combined application of basic slag and methanotroph-formulation have good potential to mitigate greenhouse gases emissions in lowland rice ecology

Rice acts as a source of greenhouse gases (GHGs) and contributes about 47 and 58% of the world's agricultural emissions of methane (CH4) and nitrous oxide (N2O), respectively. So, mitigation of CH4 and N2O emissions from rice ecologies is an issue in present day climate change scenarios. Application of value-added soil amendment like basic slag (waste of steel industries) and use of efficient methanotroph formulation is an environmental and eco-friendly option to reduce GHGs emissions. However, those options were less exploited and documented. In our study, we imposed eight treatments viz., (i) control (recommended dose of fertilizer; RDF); (2) basic slag (BS; @ 1 t ha−1); (3) BS + methanotroph (root dip) [BS + MTH(R)]; (4) BS + Methanotroph (acacia-based formulation at 7 DAT) [BS + MTH(F)]; (5) BS + Methanotroph (root dip + acacia-based formulation at 28 DAT) [BS + MTH(R&F)]; (6) Methanotroph (R) [MTH(R)]; (7) methanotroph (F) [MTH(F)]; (8) methanotroph (R&F) [MTH(R&F)]. The CH4 reduction percentage was higher in BS + MTH(R&F) treatments (15.1 and 13.1% in wet and dry season, respectively) than in the control. Similarly, the N2O reduction percentage was also higher in BS + MTH(R&F) treatments (13.9 and 15.2% in wet and dry seasons, respectively) over control. The BS + MTH(R&F) treatment significantly reduced GWP by 14.9% and 14% in the wet and dry seasons, respectively. The average CH4/N2O emissions and GWP had a significant effect on RDF, BS, MTH and BS + MTH, however, no significant difference was observed between MTH and MTH + BS. Thus, the combination of basic slag and methanotrophs could be used simultaneously to reduce the GHGs emissions and climate change mitigation.

Evaluation of different fungicides against rice seedling rot incited by Sclerotium rolfsii Sacc.

Seedling rot disease in rice incited by Sclerotium rolfsii Sacc. in the rice nursery raised during December to January for summer rice cultivation is an emerging threat to rice cultivation in South Gujarat. In the present climate change scenario, rice crop is facing the challenges of new diseases which were otherwise not touching the economical threshold. Eight fungicides were evaluated under in vitro condition. Tebuconazole 50% + trifloxystrobin 25%, mancozeb 63%+ carbendazim 12%, azoxystrobin 18.2%+difenoconazole 11.4%SC, azoxystrobin 11.5% + mancozeb 30.0% and thiram 75 WS gave complete mycelial growth inhibition at 50 ppm concentration. Whereas azoxystrobin 23SC and tebuconazole 2% DS showed good mycelial growth inhibition ability with 83.30 and 90.74%, respectively. Most effective fungicides under in vitro were evaluated against seedling rot disease under field conditions during 2018 to 2020. Seed treatment with fungicides revealed that rice seeds treated with azoxystrobin 23SC @ 1ml /kg seed and soil application with Trichoderma harzianum (2×106 cfu/g) @ 1 g/m2 which was at par with seeds treated with azoxystrobin 23SC @ 1ml/kg seeds and azoxystrobin 18.2% + difenoconazole 11.4 %SC @ 1ml/kg seeds effectively managed seedling rot disease and given highest plant population with minimum seedling mortality, improved shoot and root length and good seedling vigor index.

How Climate Change Impacts the Distribution of Lithocarpus hancei (Fagaceae), a Dominant Tree in East Asian Montane Cloud Forests

Subtropical montane moist evergreen broadleaf forests (MMEBFs) have a unique environmental envelope harboring a high percentage of endemic biota. This ecosystem is highly vulnerable, and little is known about its possible response to future climate change. In this study, we used Lithocarpus hancei (Fagaceae), a dominant tree in East Asian subtropical MMEBFs, as a proxy to investigate MMEBF distribution dynamics and key distribution restriction factors. In total, 607 L. hancei occurrence points were obtained after being gathered and filtered. The random forest model was selected as the best model. Eight environmental variables were selected to simulate the potential suitable areas of L. hancei under the Last Glacial Maximum (LGM), present, and future (2041–2060, 2061–2080, 2081–2100) climate change scenarios, including four shared socioeconomic pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5). Our results showed that precipitation of the warmest quarter, the precipitation of the driest month, the mean diurnal range, and temperature seasonality are the key factors affecting the spatial range of L. hancei with 11.2%, 10.9%, 8.1%, and 7.6% contributions, respectively. The current distribution of L. hancei is mainly within East and South China, with a scattered distribution in North Indo-China and the Southeast Himalayas. The highly suitable area only accounts for 9.7% of the total distribution area. The distribution area of the current suitability area is the smallest compared to that under LGM and future scenarios. In all the future climatic scenarios, the highly suitable areas of L. hancei would decrease or even disappear, whereas the medium- and low-suitability areas might increase with the centroid of the total suitable area northern. Its distribution in Central China, the Southern Himalayas, and Northern Indo-China will be lost in the future. Overall, our study predicted a prominent degradation of East Asian MMEBFs in the future. In situ and ex situ conservation on East Asian MMEBFs should be prioritized and enforced.

Functional vulnerability and biogeography of reef fish assemblages in the Galapagos Archipelago

The Galapagos archipelago's unique reef biodiversity and fish distribution patterns are well documented. However, reef ecosystem vulnerability to losing functional diversity and the biogeographical drivers of community functional diversity are undescribed. The functional diversity and vulnerability of coastal reef fish communities in the Galapagos were investigated using Baited Remote Underwater Stereo-Video systems (stereo-BRUVs). Relative abundance data for 41,594 individual fish belonging to 121 species was collected, 87 functional entities were identified, and functional diversity and vulnerability estimated based on five functional traits. The influence of spatial and environmental variability and human impact on functional entity composition and richness were also assessed.Galapagos reef fish communities have a high vulnerability to reduced functional diversity if species are lost due to the low redundancy and high sensitivity of reef fish functional entities. However, there may be some ecosystem resilience against species loss from species filling ecologically similar niches instead of redundant species filling the same niche. The functional trait structure and vulnerability of Galapagos reef fish assemblages reflect the known trophic structure of the marine food web. Most functional entities with resilience from redundancy include upper trophic level species with piscivorous diets. Most functional entities that are sensitive and represented by only one species include lower trophic level species. Spatial variables relating to marine environmental variation (from tropical to temperate reef ecosystems) and benthic habitat bottom incline were important predictors of reef fish functional entity distribution. Functional vulnerability may be a concern in marine ecosystems where functional diversity is low, including at higher southern latitudes and western longitudes, the cooler temperate regions and topographically simple marine habitats. Our study raises concerns about the long-term functioning of Galapagos marine ecosystems under present climate change and human management scenarios. We suggest grouping species by functional traits for consideration in the future marine management of Galapagos marine communities.

Temperature, Precipitation, and Agro-Hydro-Meteorological Indicator Based Scenarios for Decision Making in Ogallala Aquifer Region

The Ogallala Aquifer is one of the most productive agricultural regions and is referred to as the “breadbasket of the world”. It covers approximately 225,000 square miles beneath the Great Plains region spanning the states of Texas, New Mexico, Oklahoma, Kansas, Nebraska, South Dakota, Wyoming, and Colorado. The aquifer is a major water source for the region, with its use exceeding recharge. Previous studies have documented climate changes and their impacts in the region. However, this is the first study to document temperature and precipitation changes over the entire Ogallala region from 35 General Circulation Models participating in Phase 5 of the Climate Model Intercomparison Project (CMIP5). The main study objectives were (1) to provide estimates of present and future climate change scenarios for the High Plains Aquifer, (2) to translate the temperature and precipitation changes to agro-ecosystem indicator changes for Kansas using scenario funnels, and (3) to make recommendations for water resource and ecosystem managers to enable effective planning for the future availability of ecosystem services. The temperature change ranged from −4 °C to 8 °C, while the precipitation changes were between −50% to +50% over the region. This study improves the understanding of climate change on water resources and agro-ecosystems. This knowledge can be used to evaluate similar resources where the replenishment rate is slow.

Response of fertilizer and planting time on yield and economics of Zucchini (Cucurbita pepo) in Assam condition

In the agricultural sector, the vitally important factors to achieve higher production in a crop are fertilizer management and planting time. To maintain healthy plant growth and to boost crop production and productivity, fertilizer application, and planting dates have a pivotal role in the present scenario of climate change. However, the effect of fertilizer and planting dates on zucchini in agro-climatic conditions of Assam has not been properly studied. So, during the year 2019-20, it was assessed in the Experimental Farm, Department of Horticulture, Assam Agricultural University, Jorhat. Four fertilizer treatments 45: 48: 48 kg NPK/ha, 60: 64: 64 kg NPK/ha, 75: 80: 80 kg NPK/ha and keeping one treatment as control with three planting dates 1st December, 15th December, 1st January was imposed in twelve treatment combinations. The zucchini seedlings were planted at a 60 cm x 60 cm distance in a plot size of 3.24 m2 in a split-plot design. During the growing period, the diameter of fruit, length of fruit, weight of fruit, number of days to opening of flower to harvest, number of days to first harvest, number of days to last harvest, number of harvests, number of fruits per plant and fruit yield per plant/ plot/ hectare were recorded. From this trial, it is concluded that early planting and maximum fertilizer dose were better in terms of the above physical and yield attributes. Therefore, based on the findings of the experiment, it is hereby inferred that planting of zucchini on the 15th of December with a fertilizer dose of 75: 80: 80 kg NPK/ha showed the best result with maximum yield (82.59 t) per hectare area with (3.46) B:C ratio in Assam growth condition.

Development of a Python-based algorithm for adaptive thermal comfort: Theoretical formulation and application cases

Adaptive thermal comfort has gained momentum within the scientific community as a cost effective and affordable way of maintaining acceptable levels of comfort in dwellings while abating energy expenditure. At the moment two international standards, namely the European EN16798-1 and the American ASHRAE55-2010 shape the understanding of adaptive comfort around the world. However, in recent years concerns have raised about whether they can accurately represent comfort conditions considering the cultural and societal background of different countries, and whether adaptive thermal comfort will be still feasible in future scenarios of climate change. Considering these challenges, this study presents an algorithm which can model different adaptive comfort models; additionally, it can be implemented into energy simulation engines and therefore used to predict energy consumption under different climates, building typologies, and dynamic comfort conditions. This contribution presents the development of the aforementioned algorithm, called ACCIS (Adaptive-Comfort-Control-Implementation Script), originally written in EnergyPlus Runtime Language (ERL) and later nested in a Python package called ACCIM (Adaptive-Comfort-Control-Implemented Model)”, its main characteristics, and also the implementation into two cases studies: The thermal comfort in social dwellings in Spain and Japan considering present and future climate change scenarios namely Representative Concentration Pathways (RCP) 2.6, 4.5 and 8.5 for years 2050, 2080 and 2100. The results show that the predicted energy consumption of low-income families is strongly influenced by the adaptive comfort model chosen to model their thermal routine and suggest that international standards should be put under revision to consider the local particularities of dwellers in subsidized housing projects. The results of this research can be useful to devise public policies aimed at abating energy cost for low-income dwellers that benefit from social housing programs, particularly in the light of the increment of energy costs for heating and cooling associated with climate change..

Effect of two water deficit regimes on phenolic composition of 15 recovered grapevine varieties in Castilla-La Mancha region (Spain): A comparison with national and international varieties

As a consequence of the climate change effects, the chemical composition of wine grapes is being altered, particularly the phenolic components. For this reason, the drought effect on the phenolic composition of an extensive group of white and red varieties grown under a semi-arid continental Mediterranean climate (La Mancha, Spain) was studied in the 2021 vintage. The study was based on the comparison of the phenolic compounds of minority varieties, using other widely cultivated varieties as a reference. The results obtained indicated that there are currently little-known varieties that can equal or even improve to other reference varieties in terms of phenolic composition. Such varieties may be a good alternative for maintaining wine quality in present and future climate change scenarios.

The impact of global warming on the potential suitable planting area of Pistacia chinensis is limited

Pistacia chinensis Bunge. is one of the main woody oil crops with a large artificial planting area in China and has important economic and ecological value. Here, based on 237 occurrence data and 22 environmental variables, we explored the potential planting area of P. chinensis in China in the present and future climate change scenarios by using a comprehensive model method. To fully consider the potential planting area of P. chinensis under specific climate change conditions and the limitations of soil conditions, we separately built two niche models to simulate the climate niche and soil demand niche, and then used the intersection of the two models as the result of the comprehensive habitat suitability model, finally, we used land-use data to filter the CHS model result. Our results showed, that under the baseline condition, the potential planting area of P. chinensis covers approximately 0.74 × 106 km2 in China. The future projection showed that the impact of global warming on the potentially suitable planting area of P. chinensis is limited, and most of the existing suitable habitats are not affected by climate change. With increasing temperature, the potential planting area will expand northward and slightly contract in the south margin, and its area will be slightly increased. Therefore, this species has great planting potential in China and should be given priority in the future afforestation plan.

Sapwood mycobiome varies across host, plant compartment and environments in Nothofagus forests from Northern Patagonia.

Global forests are increasingly being threatened by altered climatic conditions and increased attacks by pests and pathogens. The complex ecological interactions among pathogens, microbial communities, tree hosts and the environment are important drivers of forest dynamics. Little is known about the ecology of forest pathology and related microbial communities in temperate forests of the southern hemisphere. In this study, we used next-generation sequencing to characterize sapwood-inhabiting fungal communities in North Patagonian Nothofagus forests and assessed patterns of diversity of taxa and ecological guilds across climatic, site and host variables (health condition and compartment) as a contribution to Nothofagus autecology. The diversity patterns inferred through the metabarcoding analysis were similar to those obtained through culture-dependent approaches. However, we detected additional heterogeneity and greater richness with culture-free methods. Host species was the strongest driver of fungal community structure and composition, while host health status was the weakest. The relative impacts of site, season, plant compartment and health status were different for each tree species; these differences can be interpreted as a matter of water availability. For Nothofagus dombeyi, which is distributed across a wide range of climatic conditions, site was the strongest driver of community composition. The microbiome of N. pumilio varied more with season and temperature, a relevant factor for forest conservation in the present climate change scenario. Both species carry a number of potential fungal pathogens in their sapwood, whether they exhibit symptoms or not. Our results provide insight into the diversity of fungi associated with the complex pathobiome of the dominant Nothofagus species in southern South America.

Combining remote sensing analysis with machine learning to evaluate short-term coastal evolution trend in the shoreline of Venice

With increasing storminess and incessant sea-level rise, coastal erosion is becoming a primary issue along many littorals in the world. To cope with present and future climate change scenarios, it is important to map the shoreline position over years and assess the coastal erosion trends to select the best risk management solutions and guarantee a sustainable management of communities, structures, and ecosystems. However, this objective is particularly challenging on gentle-sloping sandy coasts, where also small sea-level changes trigger significant morphological evolutions.This study presents a multidisciplinary study combining satellite images with Machine Learning and GIS-based spatial tools to analyze short-term shoreline evolution trends and detect erosion hot-spots on the Venice coast over the period 2015–2019. Firstly, advanced image preprocessing, which is not frequently adopted in coastal erosion studies, was performed on satellite images downloaded within the same tidal range. Secondly, different Machine Learning classification methods were tested to accurately define shoreline position by recognizing the land-sea interface in each image. Finally, the application of the Digital Shoreline Analysis System tool was performed to evaluate and visualize coastal changes over the years.Overall, the case study littoral reveals to be stable or mainly subjected to accretion. This is probably due to the high presence of coastal protection structures that stabilize the beaches, enhancing deposition processes. In detail, with respect to the total length of the considered shoreline (about 83 km), 5 % of the coast is eroding, 36 % is stable, 52 % is accreting and 7 % is not evaluable. Despite a significant coastal erosion risk was not recognized within this region, well-delimited erosion hot-spots were mapped in correspondence of Caorle, Jesolo and Cavallino-Treporti municipalities. These areas deserve higher attention for territorial planning and prioritization of adaptation measures, facing climate change scenarios and sea-level rise emergencies in the context of Integrated Coastal Zone Management.

Maize/soybean strip intercropping produces higher crop yields and saves water under semi-arid conditions.

Sustainable increases in crop production require efficient use of resources, and intercropping can improve water use efficiency and land productivity at reduced inputs. Thus, in a three-year field experiment, the performance of maize/soybean strip intercropping system differing with maize plant density (6 maize plants m-2, low, D1; 8 maize plants m-2, medium, D2; and 10 maize plants m-2, high, D3) was evaluated in comparison with sole maize or soybean cropping system. Results revealed that among all intercropping treatments, D2 had a significantly higher total leaf area index (maize LAI + soybean LAI; 8.2), total dry matter production (maize dry matter + soybean dry matter; 361.5g plant-1), and total grain yield (maize grain yield + soybean grain yield; 10122.5kg ha-1) than D1 and D3, and also higher than sole maize (4.8, 338.7g plant-1, and 9553.7kg ha-1) and sole soybean (4.6, 64.8g plant-1, and 1559.5kg ha-1). The intercropped maize was more efficient in utilizing the radiation and water, with a radiation use efficiency of 3.5, 5.2, and 4.3g MJ-1 and water use efficiency of 14.3, 16.2, and 13.3kg ha-1 mm-1, while that of intercropped soybean was 2.5, 2.1, and 1.8g MJ-1 and 2.1, 1.9, and 1.5kg ha-1 mm-1 in D1, D2, and D3, respectively. In intercropping, the land and water equivalent ratios ranged from 1.22 to 1.55, demonstrating that it is a sustainable strategy to improve land and water use efficiencies; this maximization is likely associated with the species complementarities for radiation, water, and land in time and space, which resulted in part from competition avoidance responses that maximize the economic profit (e. g., 1300 US $ ha-1 in D2) over sole maize (798 US $ ha-1) or sole soybean (703 US $ ha-1). Overall, these results indicate that optimizing strip intercropping systems can save 20-50% of water and land, especially under the present scenario of limited resources and climate change. However, further research is required to fully understand the resource capture mechanisms of intercrops in intercropping.

Predicting the invasion risk of rugose spiraling whitefly, Aleurodicus rugioperculatus, in India based on CMIP6 projections by MaxEnt.

Rugose spiraling whitefly (RSW), Aleurodicus rugioperculatus Martin, is a highly polyphagous invasive pest native to Central America. The occurrence of A. rugioperculatus in the Oriental region was first reported from Pollachi, Tamil Nadu, India in 2017. This pest is widely distributed in India, causing severe economic damage to coconut and other horticultural crops. It is a recent invasion in India and information on its potential distribution is lacking. Thus, in the present study we used the latest Coupled Model Intercomparison Project phase 6 (CMIP6) dataset through Maximum Entropy species distribution modelling (version 3.4.1, MaxEnt) to determine the potential distribution of RSW in present and future climate change scenarios in 2050 and 2070 under Shared Socioeconomic Pathway (SSP) 126 and SSP585 emission scenarios. The performance of the model was evaluated using the area under the curve (AUC), true skill statistics (TSS) and the continuous Boyce index (CBI). The MaxEnt model performed well and predicted the potential distribution of A. rugioperculatus with high-accuracy AUC values of 0.991 and 0.989, TSS values of 0.891 and 0.842, and CBI values of 0.972 and 0.934 for training and testing, respectively. Jackknife analysis revealed that A. rugioperculatus distribution was mostly influenced by temperature-based bioclimatic variables contributing 62.1% of the suitability, with precipitation variables contributing the remainder. The most important bioclimatic variables for RSW distribution were annual mean temperature (Bio 1, 28.9%) followed by mean diurnal range (Bio 2, 19.5%) and annual precipitation (Bio 12, 19.1). Potential suitable areas for RSW establishment were mostly found in all coastal and southern states of India. A. rugioperculatus prefers a warm and humid climate, indicating that the tropics, subtropics and temperate regions are ideal for its spread and invasion. Our results highlighted that the suitable habitat area for A. rugioperculatus is predicted to increase and highest probability of invasion and spread in 2050 and 2070 under future climate change scenarios of SSP126 and SSP585 compared to present climatic conditions. This is the first study to use the latest CMIP6 models and it predicts the potential distribution of RSW in India under present and future climate change scenarios. The implementation of strict domestic quarantine measures may prevent the spread and damage of RSW to noncoastal regions of India. The results of the current study should help in timely monitoring and surveillance of RSW and to formulate integrated pest management strategies at the national level to restrict its spread, invasion and damage to new areas. © 2022 Society of Chemical Industry.