Leopard density and determinants of space use in a farming landscape in South Africa.

Protected areas are traditionally the foundation of conservation strategy, but land not formally protected is of particular importance for the conservation of large carnivores because of their typically wide-ranging nature. In South Africa, leopard (Panthera pardus) population decreases are thought to be occurring in areas of human development and intense negative interactions, but research is biased towards protected areas, with quantitative information on population sizes and trends in non-protected areas severely lacking. Using Spatially Explicit Capture-Recapture and occupancy techniques including 10 environmental and anthropogenic covariates, we analysed camera trap data from commercial farmland in South Africa where negative human-wildlife interactions are reported to be high. Our findings demonstrate that leopards persist at a moderate density (2.21 /100 km2) and exhibit signs of avoidance from areas where lethal control measures are implemented. This suggests leopards have the potential to navigate mixed mosaic landscapes effectively, enhancing their chances of long-term survival and coexistence with humans. Mixed mosaics of agriculture that include crops, game and livestock farming should be encouraged and, providing lethal control is not ubiquitous in the landscape, chains of safer spaces should permit vital landscape connectivity. However, continuing to promote non-lethal mitigation techniques remains vital.

A study on nickel application methods for optimizing soybean growth.

Fertilization with nickel (Ni) can positively affect plant development due to the role of this micronutrient in nitrogen (N) metabolism, namely, through urease and NiFe-hydrogenase. Although the application of Ni is an emerging practice in modern agriculture, its effectiveness strongly depends on the chosen application method, making further research in this area essential. The individual and combined effects of different Ni application methods-seed treatment, leaf spraying and/or soil fertilization-were investigated in soybean plants under different edaphoclimatic conditions (field and greenhouse). Beneficial effects of the Soil, Soil + Leaf and Seed + Leaf treatments were observed, with gains of 7 to 20% in biological nitrogen fixation, 1.5-fold in ureides, 14% in shoot dry weight and yield increases of up to 1161 kg ha-1. All the Ni application methods resulted in a 1.1-fold increase in the SPAD index, a 1.2-fold increase in photosynthesis, a 1.4-fold increase in nitrogenase, and a 3.9-fold increase in urease activity. Edaphoclimatic conditions exerted a significant influence on the treatments. The integrated approaches, namely, leaf application in conjunction with soil or seed fertilization, were more effective for enhancing yield in soybean cultivation systems. The determination of the ideal method is crucial for ensuring optimal absorption and utilization of this micronutrient and thus a feasible and sustainable management technology. Further research is warranted to establish official guidelines for the application of Ni in agricultural practices.

Restoring ecological complexity in a changing environment.

As land use leaves massive tracts of land vacant for recovery, restoration must undergo a substantial shift to incorporate a complexity perspective beyond the traditional community, biodiversity or functional views. With an interaction-function perspective, we may be able to achieve ecosystems with better chances to adapt to current environmental changes and, especially, to climate change. We explore combined approaches that include still unused and underexplored techniques that will soon go mainstream and produce massive amounts of information to address the complexity gap. As we understand how complexity reassembles after the end of agriculture, we will be able to design actions to restore or enhance it at unprecedented spatial scales while increasing its adaptability to environmental changes.

Restoring soil biodiversity.

Soil health is crucial for all terrestrial life, supporting, among other processes, food production, water purification and carbon sequestration. Soil biodiversity - the variety of life within soils - is key to these processes and thus key to soil restoration. Human activities that degrade ecosystems threaten soil biodiversity and associated ecosystem processes. Indeed, 75% of the world's soils are affected by degradation - a figure that could rise to 90% by 2050 if deforestation, overgrazing, urbanisation and other harmful practices persist. Restoring soil biodiversity is a prerequisite for planetary health, and it comes with many challenges and opportunities. Soil directly supports around 60% of all species on Earth, and land degradation poses a major problem for this biodiversity and the ecosystem services that sustain human populations. Indeed, 98% of human calories come from soil, and earthworms alone underpin 6.5% of the world's grain production. Moreover, the total carbon in terrestrial ecosystems is around 3,170 gigatons (1 gigaton (Gt) = 1 billion metric tons), of which approximately 80% (2,500 Gt) is found in soil. Therefore, restoring soil biodiversity is not just a human need but an ecological and Earth-system imperative. It is pivotal for maintaining ecosystem resilience, sustaining agricultural productivity and mitigating climate change impacts.

Effects of management practices on the ecosystem-service multifunctionality of temperate grasslands.

Human wellbeing depends on ecosystem services, highlighting the need for improving the ecosystem-service multifunctionality of food and feed production systems. We study Swiss agricultural grasslands to assess how employing and combining three widespread aspects of grassland management and their interactions can enhance 22 plot-level ecosystem service indicators, as well as ecosystem-service multifunctionality. The three management aspects we assess are i) organic production system, ii) an eco-scheme prescribing extensive management (without fertilization), and iii) harvest type (pasture vs. meadow). While organic production system and interactions between the three management aspects play a minor role, the main effects of eco-scheme and harvest type considerably shape single services. Moreover, the eco-scheme 'extensive management' and the harvest type 'pasture' enhance plot-scale ecosystem-service multifunctionality, mostly through facilitating cultural services at the expense of provisioning services. These changes in ecosystem-service supply occur mainly via changes in land-use intensity, i.e., reduced fertilizer input and harvest frequency. In conclusion, diversifying grassland management where this is currently homogeneous across farms and landscapes depicts an important first step to improve landscape-scale multifunctionality for sustainable grassland systems. To meet societal ecosystem services demand, the three studied management aspects can be systematically combined to increase ecosystem services that are in short supply.

Spatial and temporal distribution of optimal maize sowing dates in Nigeria.

Climate change and inter-annual variability cause variation in rainfall commencement and cessation which has consequences for the maize growing season length and thus impact yields. This study therefore sought to determine the spatially explicit optimum maize sowing dates to enable site specific recommendations in Nigeria. Gridded weather and soil data, crop management and cultivar were used to simulate maize yield from 1981-2019 at a scale of 0.5°. A total of 37 potential sowing dates between 1 March and 7 November at an interval of 7 days for each year were evaluated. The optimum sowing date was the date which maximizes yield at harvest, keeping all other management factors constant. The results show that optimum sowing dates significantly vary across the country with northern Nigeria having notably delayed sowing dates compared to southern Nigeria which has earlier planting dates. The long-term optimal sowing dates significantly (p<0.05), shifted between the 1980s (1981-1990), and current (2011-2019), for most of the country. The most optimum planting dates of southern Nigeria shifted to later sowing dates while most optimum sowing dates of central and northern Nigeria shifted to earlier sowing dates. There was more variation in optimum sowing dates in the wetter than the drier agro-ecologies. Changes in climate explain changes in sowing dates in wetter agro-ecologies compared to drier agro-ecologies. The study concludes that the optimum sowing dates derived from this study and the corresponding methodology used to generate them can be used to improve cropping calendars in maize farming in Nigeria.

Sward characteristics, herbage accumulation and nutritional value of elephantgrass based mixed with or without pinto peanut.

Elephantgrass stands out for its high potential for forage production in different tropical and subtropical regions. In most properties, it is cultivated intensively with high doses of mineral fertilizers, mainly nitrogen, which makes production expensive and less sustainable. In this context, the mixtures of elephantgrass with forage legumes can make the system more efficient and with less environmental impact. Thus, the objective is to evaluate elephantgrass-based grazing systems,with or without a legume in terms of sward characteristics, herbage accumulation and nutritional value of pastures during one, agricultural year. Two grazing systems (treatments) were analyzed: (i) elephantgrass-based (EG) with mixed spontaneous-growing species (SGE) in the warm-season and ryegrass (R) in the cool-season; and (ii) EG + SGE + R + pinto peanut. The standardization criterion between the systems was the level of nitrogen fertilization (120 kg N/ha/year). The presence of pinto peanut positively affected the botanical composition of the pasture, with a reduction in SGE and dead material, and in the morphology of elephantgrass, with a greater proportion of leaf blades, and less stem + sheath and senescent material. In themixture with pinto peanut, there was an increase in herbage accumulation and greater nutritional value of forage.

Responses of soil physico-chemical properties, structure of the microbial community and crop yields to different fertilization practices in Russia's conventional farming system.

The use of fertilizers affects not only the soil fertility and crop yield, but also significantly changes the taxonomic structure of the soil microbiocenosis. Here, based on stationary field experiment, we studied the influence of organo-mineral fertilizer (ОМF), modified by bacteria Bacillus subtilis, H-13 in comparison with different fertilizer systems (organic, mineral, organo-mineral) on (i) crop yield, (ii) physical and chemical properties, and (iii) alpha and beta diversity of the microbial community Albic Retisol (Loamic, Aric, Cutanic, Differentic, Ochric). The studies were carried out against the background of liming (рНКCl - 5.9) and without it (рНКCl - 5.1). The use of only one cattle farmyard manure was less effective than its co-application with mineral fertilizers in half doses. A similar effect was obtained when applying ОМF. In addition, the use of OMF contributes to a significant increase in the reserves of soil organic carbon in the soil layer 0-20 cm by 18%-32%. Using high-throughput sequencing of the 16S rRNA variable V4 gene sequence libraries, 10.759 taxa from 456 genera were identified, assigned to 34 fila (31 bacterial and 3 archaeotic. Unilateral application of mineral fertilizers leads to a significant decrease in the alpha diversity of the structure of soil microbial communities (OTE (other things equal) and Shannon index). A clear clustering of the microbiota was found in the variants with and without the introduction of сattle farmyard manure. It is revealed that the taxonomic structure of the microbiocenosis is formed under the influence of two main factors: crop rotation culture and applied fertilizers. The type of cultivated crop determines the dynamics of the microbiota at the level of larger taxa, such as domains, and fertilizers affect the structure of the microbial community at a lower taxonomic level (phyla, orders, bloodlines). On the basis of the Deseq analysis, marker taxa were identified, according to the share participation of which it is possible to determine the type of cultivated crop and fertilizers used in the experiment. Understanding the dynamics of taxa association and other influential factors can lead to the creation of universal systems of metagenomic indication, where tracking the dynamics of microbial communities will allow for a comprehensive assessment of the agroecological state of soils and timely decisions to prevent their degradation.

Digital Twins in Agriculture: Orchestration and Applications.

Digital Twins have emerged as an outstanding opportunity for precision farming, digitally replicating in real-time the functionalities of objects and plants. A virtual replica of the crop, including key agronomic development aspects such as irrigation, optimal fertilization strategies, and pest management, can support decision-making and a step change in farm management, increasing overall sustainability and direct water, fertilizer, and pesticide savings. In this review, Digital Twin technology is critically reviewed and framed in the context of recent advances in precision agriculture and Agriculture 4.0. The review is organized for each step of agricultural lifecycle, edaphic, phytotechnologic, postharvest, and farm infrastructure, with supporting case studies demonstrating direct benefits for agriculture production and supply chain considering both benefits and limitations of such an approach. Challenges and limitations are disclosed regarding the complexity of managing such an amount of data and a multitude of (often) simultaneous operations and supports.

Evidence of potential impacts of a nutrition-sensitive agroecology program in Andhra Pradesh, India, on dietary diversity, nutritional status, and child development.

INTRODUCTION: While a number of studies have examined the nutritional impacts of agroecological interventions, few have examined impacts on child development, maternal and child anemia, and men's dietary diversity. Moreover, there have been few such evaluations at scale. We evaluated the impact of a large-scale, multi-component food-based nutrition intervention involving homestead food production, nutrition counselling, cooking demonstrations, and crop planning exercises. METHODS: A cross-sectional assessment was conducted in 2021-2022 of 50 intervention villages where the nutrition-sensitive agroecology program had been implemented since 2018 and 79 control villages where only the agroecology program had been implemented. Data on self-reported dietary intake, caregiver-reported early child development, anthropometric measurements, and hemoglobin concentrations were collected using standardized procedures by trained Nutrition Farming Fellows, who were also responsible for implementing the program. RESULTS: A sample of 3,511 households (1,121 intervention and 2,390 control) participated in the survey. Dietary diversity scores (DDS) among women and men were mean (SD) 6.53 (±1.62) and 6.16 (±1.65), respectively, in intervention villages and 5.81 (±1.58) and 5.39 (±1.61), respectively, in control villages (p<0.01). DDS among children 6-24 months of age in intervention and control villages was 2.99 (±1.52) and 2.73 (±1.62), respectively (p<0.01). Children <2 years of age were less likely to be anemic in intervention versus control villages (59% versus 69%, p<0.01). Children 18-35 months age in intervention villages had higher child development scores than children in control villages (all p<0.05). CONCLUSION: Nutrition-sensitive agroecological programs may be effective in improving diets, nutrition, and child development in rural India.

The potential of durum wheat-chickpea intercropping to improve the soil available phosphorus status and biomass production in a subtropical climate.

The intercropping system is a promising approach to augmenting the soil nutrient status and promoting sustainable crop production. However, it is not known whether intercropping improves the soil phosphorus (P) status in alluvial soils with low P under subtropical climates. Over two growing seasons--2019-2020 and 2020-2021--two experimental fields were employed to explore the effect of durum wheat (Dw) and chickpea (Cp) cropping systems on the soil available P. A randomized complete block design was used in this experiment, with three blocks each divided into three plots. Each plot was used for one of the following three treatments with three replications: Dw monocrop (Dw-MC), Cp monocrop (Cp-MC), and Dw + Cp intercrop (CpDw-InC), with bulk soil (BS) used as a control. A reduction in the rhizosphere soil pH (-0.44 and -0.11 unit) was observed in the (Cp-MC) and (CpDw-InC) treatments over BS, occurring concomitantly with a significant increase in available P in the rhizosphere soil of around 28.45% for CpDw-InC and 24.9% for Cp-MC over BS. Conversely, the rhizosphere soil pH was significantly higher (+0.12 units) in the Dw-MC treatments. In addition, intercropping enhanced the soil microbial biomass P, with strong positive correlations observed between the biomass P and available P in the Cp-MC treatment, whereas this correlation was negative in the CpDw-InC and Dw-MC treatments. These findings suggested that Cp intercropped with Dw could be a viable approach in enhancing the available P through improved pH variation and biomass P when cultivated on alluvial soil under a subtropical climate.

The ecological and biodiversity conservation values of farm dams: A systematic review.

Biodiversity is in rapid decline globally with agriculture being one of the leading causes. Within agricultural landscapes, some features provide a benefit to biodiversity that is disproportionate to their spatial area. An interesting example is artificial ponds-or farm dams-which can support a large variety of taxa. Here, we present a global review of farm dam research related to biodiversity conservation objectives to provide an overview of the topics, key research insights, and the characteristics of current research. We used a three-stage process to screen literature and identified 104 relevant papers across 27 countries encompassing studies of 13 different taxa. Most of the studies were short-term (less than 5 years) with small sample sizes (less than 20 sites). Of the 104 papers, 88 were focussed primarily on ecological outcomes, such as species richness or abundance, and 15 on primary production outcomes, such as crop and livestock yield, despite addressing or measuring ecological metrics. Only one study measured both ecological and primary production outcomes. Studies frequently examined how the features of dams (79 studies) and attributes of the surrounding landscape (47 studies) impact particular species and communities. Terrestrial mammals (1 study) were under-represented in the literature with macrophytes (28 studies), macroinvertebrates (26 studies), and amphibians (19 studies) receiving the most attention. Our results reveal a growing trend towards recognizing farm dams as habitats for various taxa, including amphibians, beetles, dragonflies, and other macroinvertebrates within agricultural environments. Significant knowledge gaps exist in understanding how dam age, invasive species, and effective management practices impact the biodiversity conservation values of farm dams. Future research should emphasize enhancing biodiversity by collaborating with landholders to increase habitat through strategic vegetation planning, minimizing runoff and nutrient inflow, and restricting stock access.

The effect of education on safe use of pesticides based on the health belief model.

OBJECTIVE: In agricultural activities, pesticide use is critical, but poisoning issues are one of the most important occupational hazards for farmers. Training can help protect farmers' health from pesticide hazards. This study aimed to investigate the effect of education on farmers' behavior in the safe use of pesticides using the health belief model. METHODS: A quasi-experimental (pretest-post-test) study conducted on 84 farmers who were selected using the convenience sampling method. The data collection tool was a two-part questionnaire including demographic information and a questionnaire designed based on the constructs of the health belief model in using personal protective equipment while working with the pesticides. The instrument was completed before and two weeks after an educational intervention. Data analysis was performed using SPSS software version 26. RESULTS: The mean age of the participants was 48.94 ± 9.14 years and 69% were male. The study showed that with increasing age, the mean score of health belief model constructs in the safe use of pesticides decreased. Female and higher-educated farmers had higher scores. After the intervention, the mean scores of health belief model constructs in the safe use of pesticides increased significantly, except perceived barriers construct which decreased significantly. Also, the frequency of protective equipment uses while working with pesticides increased significantly after the intervention and safe behaviors increased, while unsafe behaviors decreased. CONCLUSION: The education as an effective intervention, improves farmers' safety attitudes and behaviors in pesticide use and it is recommended that educational programs be designed according to the characteristics of the audience.

Use of modelling tools to assess climate change impacts on smallholder oil seed yields in South Africa.

Oil seed crops are the second most important field crops after cereals in the agricultural economy globally. The use and demand for oilseed crops such as groundnut, soybean and sunflower have grown significantly, but climate change is expected to alter the agroecological conditions required for oilseed crop production. This study aims to present an approach that utilizes decision-making tools to assess the potential climate change impacts on groundnut, soybean and sunflower yields and the greenhouse gas emissions from the management of the crops. The Decision Support Tool for Agrotechnology Transfer (DSSAT v4.7), a dynamic crop model and the Cool Farm Tool, a GHG calculator, was used to simulate yields and estimate GHG emissions from these crops, respectively. Four representative concentration pathways (RCPs 2.6, 4.5, 6.0, and 8.5), three nitrogen (0, 75, and 150 kg/ha) and phosphorous (0, 30 and 60 P kg/ha) fertilizer rates at three sites in Limpopo, South Africa (Ofcolaco, Syferkuil and Punda Maria) were used in field trials for calibrating the models. The highest yield was achieved by sunflower across all crops, years and sites. Soybean yield is projected to decrease across all sites and scenarios by 2030 and 2050, except at Ofcolaco, where yield increases of at least 15.6% is projected under the RCP 4.5 scenario. Positive climate change impacts are predicted for groundnut at Ofcolaco and Syferkuil by 2030 and 2050, while negative impacts with losses of up to 50% are projected under RCP8.5 by 2050 at Punda Maria. Sunflower yield is projected to decrease across all sites and scenarios by 2030 and 2050. A comparison of the climate change impacts across sites shows that groundnut yield is projected to increase under climate change while notable yield losses are projected for sunflower and soybean. GHG emissions from the management of each crop showed that sunflower and groundnut production had the highest and lowest emissions across all sites respectively. With positive climate change impacts, a reduction of GHG emissions per ton per hectare was projected for groundnuts at Ofcolaco and Syferkuil and for sunflower in Ofcolaco in the future. However, the carbon footprint from groundnut is expected to increase by 40 to 107% in Punda Maria for the period up to 2030 and between 70-250% for 2050, with sunflower following a similar trend. We conclude that climate change will potentially reduce yield for oilseed crops while management will increase emissions. Therefore, in designing adaptation measures, there is a need to consider emission effects to gain a holistic understanding of how both climate change impacts on crops and mitigation efforts could be targeted.

A Systematic Review on Effects of Nitrogen Fertilizer Levels on Cabbage (Brassica oleracea var. capitata L.) Production in Ethiopia.

Cabbage (Brassica oleracea var. capitata L.) holds significant agricultural and nutritional importance in Ethiopia; yet, its production faces challenges, including suboptimal nitrogen fertilizer management. The aim of this review was to review the possible effect of nitrogen fertilizer levels on the production of cabbage in Ethiopia. Nitrogen fertilization significantly influences cabbage yield and quality. Moderate to high levels of nitrogen application enhance plant growth, leaf area, head weight, and yield. However, excessive nitrogen levels can lead to adverse effects such as delayed maturity, increased susceptibility to pests and diseases, and reduced postharvest quality. In Ethiopia, small-scale farmers use different nitrogen levels for cabbage cultivation. In Ethiopia, NPSB or NPSBZN fertilizers are widely employed for the growing of various crops such as cabbage. 242 kg of NPS and 79 kg of urea are the blanket recommendation for the current production of cabbage in Ethiopia. The existing rate is not conducive for farmers. Therefore, small-scale farmers ought to utilize an optimal and cost-effective nitrogen rate to boost the cabbage yield. Furthermore, the effectiveness of nitrogen fertilization is influenced by various factors including the soil type, climate, cabbage variety, and agronomic practices. Integrated nutrient management approaches, combining nitrogen fertilizers with organic amendments or other nutrients, have shown promise in optimizing cabbage production while minimizing environmental impacts. The government ought to heed suggestions concerning soil characteristics such as the soil type, fertility, and additional factors such as the soil pH level and soil moisture contents.

Crop rotational diversity can mitigate climate-induced grain yield losses.

Diversified crop rotations have been suggested to reduce grain yield losses from the adverse climatic conditions increasingly common under climate change. Nevertheless, the potential for climate change adaptation of different crop rotational diversity (CRD) remains undetermined. We quantified how climatic conditions affect small grain and maize yields under different CRDs in 32 long-term (10-63 years) field experiments across Europe and North America. Species-diverse and functionally rich rotations more than compensated yield losses from anomalous warm conditions, long and warm dry spells, as well as from anomalous wet (for small grains) or dry (for maize) conditions. Adding a single functional group or crop species to monocultures counteracted yield losses from substantial changes in climatic conditions. The benefits of a further increase in CRD are comparable with those of improved climatic conditions. For instance, the maize yield benefits of adding three crop species to monocultures under detrimental climatic conditions exceeded the average yield of monocultures by up to 553 kg/ha under non-detrimental climatic conditions. Increased crop functional richness improved yields under high temperature, irrespective of precipitation. Conversely, yield benefits peaked at between two and four crop species in the rotation, depending on climatic conditions and crop, and declined at higher species diversity. Thus, crop species diversity could be adjusted to maximize yield benefits. Diversifying rotations with functionally distinct crops is an adaptation of cropping systems to global warming and changes in precipitation.

Cover crops support the climate change mitigation potential of agroecosystems.

Cover crops have the potential to mitigate climate change by reducing negative impacts of agriculture on ecosystems. This study is first to quantify the net climate change mitigation impact of cover crops including land-use effects. A systematic literature and data review was conducted to identify major drivers for climate benefits and costs of cover crops in maize (Zea maize L.) production systems. The results indicate that cover crops lead to a net climate change mitigation impact (NCCMI) of 3.30 Mg CO2e ha-1 a-1. We created four scenarios with different impact weights of the drivers and all of them showing a positive NCCMI. Carbon land benefit, the carbon opportunity costs based on maize yield gains following cover crops, is the major contributor to the NCCMI (34.5% of all benefits). Carbon sequestration is the second largest contributor (33.8%). The climate costs of cover crops are mainly dominated by emissions from their seed production and foregone benefits due to land use for cover crops seeds. However, these two costs account for only 15.8% of the benefits. Extrapolating these results, planting cover crops before all maize acreage in the EU results in a climate change mitigation of 49.80 million Mg CO2e a-1, which is equivalent to 13.0% of the EU's agricultural emissions. This study highlights the importance of incorporating cover crops into sustainable cropping systems to minimize the agricultural impact to climate change.

Assessment of land use and land cover change detection and prediction using deep learning techniques for the southwestern coastal region, Goa, India.

Understanding the connections between human activities and the natural environment depends heavily on information about land use and land cover (LULC) in the form of accurate LULC maps. Environmental monitoring using deep learning (DL) is rapidly growing to preserve a sustainable environment in the long term. For establishing effective policies, regulations, and implementation, DL can be a valuable tool for assessing environmental conditions and natural resources that will positively impact the ecosystem. This paper presents the assessment of land use and land cover change detection (LULCCD) and prediction using DL techniques for the southwestern coastal region, Goa, also known as the tourist destination of India. It consists of three components: (i) change detection (CD), (ii) quantification of LULC changes, and (iii) prediction. A new CD assessment framework, Spatio-Temporal Encoder-Decoder Self Attention Network (STEDSAN), is proposed for the LULCCD process. A dual branch encoder-decoder network is constructed using strided convolution with downsampling for the encoder and transpose convolution with upsampling for the decoder to assess the bitemporal images spatially. The self-attention (SA) mechanism captures the complex global spatial-temporal (ST) interactions between individual pixels over space-time to produce more distinct features. Each branch accepts the LULC map of 2 years as one of its inputs to determine binary and multiclass changes among the bitemporal images. The STEDSAN model determines the patterns, trends, and conversion from one LULC type to another for the assessment period from 2005 to 2018. The binary change maps were also compared with the existing state of the art (SOTA) CD methods, with STEDSAN having an overall accuracy of 94.93%. The prediction was made using an recurrent neural network (RNN) known as long short term memory network (LSTM) for the year 2025. Experiments were conducted to determine area-wise changes in several LULC classes, such as built-up (BU), crops (kharif crop (KC), rabi crop (RC), zaid crop (ZC), double/triple (D/T C)), current fallow (CF), plantation (PL), forests (evergreen forest (EF), deciduous forest (DF), degraded/scurb forest (D/SF) ), littoral swamp (LS), grassland (GL), wasteland (WL), waterbodies max (Wmx), and waterbodies min (Wmn). As per the analysis, over the period of 13 years, there has been a net increase in the amount of BU (1.25%), RC (1.17%), and D/TC( 2.42%) and a net decrease in DF (3.29%) and WL(1.44%) being the most dominant classes being changed. These findings will offer a thorough description of identifying trends in coastal areas that may incorporate methodological hints for future studies. This study will also promote handling the spatial and temporal complexity of remotely sensed data employed in categorizing the coastal LULC of a heterogeneous landscape.

Intercropping with maize and sorghum-induced saikosaponin accumulation in Bupleurum chinense DC. by liquid chromatography-mass spectrometry-based metabolomics.

Bupleuri Radix is an important medicinal plant, which has been used in China and other Asian countries for thousands of years. Cultivated Bupleurum chinense DC. (B. chinense) is the main commodity of Bupleuri Radix. The benefits of intercropping with various crops for B. chinense have been recognized; however, the influence of intercropping on the chemical composition of B. chinense is still unclear yet. In this study, intercropping with sorghum and maize exhibited little effect on the root length, root diameter, and single root mass of B. chinense. Only the intercropping with sorghum increased the root length of B. chinense slightly compared to the monocropping. In addition, 200 compounds were identified by UHPLC-Q-TOF-MS, and metabolomic combined with the Venn diagram and heatmap analysis showed apparent separation between the intercropped and monocropped B. chinense samples. Intercropping with sorghum and maize could both increase the saikosaponins, fatty acyls, and organic acids in B. chinense while decreasing the phospholipids. The influence of intercropping on the saikosaponin biosynthesis was probably related with the light intensity and hormone levels in B. chinense. Moreover, we found intercropping increased the anti-inflammatory activity of B. chinense. This study provides a scientific reference for the beneficial effect of intercropping mode of B. chinense.

Deer activity levels and patterns vary along gradients of food availability and anthropogenic development.

Animal activity reflects behavioral decisions that depend upon environmental context. Prior studies typically estimated activity distributions within few areas, which has limited quantitative assessment of activity changes across environmental gradients. We examined relationships between two response variables, activity level (fraction of each day spent active) and pattern (distribution of activity across a diel cycle) of white-tailed deer (Odocoileus virginianus), with four predictors-deer density, anthropogenic development, and food availability from woody twigs and agriculture. We estimated activity levels and patterns with cameras in 48 different 10.36-km2 landscapes across three larger regions. Activity levels increased with greater building density, likely due to heightened anthropogenic disturbance, but did not vary with food availability. In contrast, activity patterns responded to an interaction between twigs and agriculture, consistent with a functional response in habitat use. When agricultural land was limited, greater woody twig density was associated with reduced activity during night and evening. When agricultural land was plentiful, greater woody twig density was associated with more pronounced activity during night and evening. The region with the highest activity level also experienced the most deer-vehicle collisions. We highlight how studies of spatial variation in activity expand ecological insights on context-dependent constraints that affect wildlife behavior.