Search

The digitization of agriculture is widely discussed today. But despite proven benefits, its acceptance in agricultural practice remains low. In small-structured areas, this trend is even more pronounced. There are even known cases where farmers initially purchased and used technology, but then stopped using it due to lack of profitability or other reasons. Interestingly, despite extensive research on precision agriculture technologies (PATs), the processes of adoption and phase-out with their associated economic impacts have never been studied. This paper provides a methodological framework for evaluating the economics of PAT deployment, taking into account changes during the period of use; the framework provides decision rules for determining the appropriate time to phase out technology. Using a selected PAT, a farm model, and defined entry and exit scenarios, it was shown that farms with outdated technology and farms with retrofittable technology are at a significant economic disadvantage during implementation compared to farms already using technology suitable for site-specific fertilization or farms relying on the use of a contractor. And even in the event of a phase-out, the two disadvantaged starting conditions face significantly greater uncertainties and costs. Moreover, the decision to phase out in time is difficult, as making an informed and fact-based decision is not possible after the first year of use. Therefore, it is advisable that farmers are not only accompanied before and during phase-in, but also receive professional support during use. [ABSTRACT FROM AUTHOR]

The lives of rural households are predominantly based on agriculture and its allied activities. However, there are signs of an agricultural crisis resulting in dependence on alternative sources of income. This paper analyzes the factors that influence the decision of farm households to participate in non-farm activities for alternative income. The official data for two years on the Situation Assessment Survey of Agricultural Households are explored and a pooled probit regression model is run to examine the determinants of income diversification. Our findings reveal that farm income and irrigated land negatively influence diversification. However, diversification of those having lower access to farm holdings, socioeconomic deprivation, and improved access to education, informal credit, and crop insurance point out positive participation in non-farm enterprises. In addition, the population belonging to hilly and coastal plain regions and the age group 30–64 years are more likely to diversify. [ABSTRACT FROM AUTHOR]

Surface soil moisture (SSM) at high spatial resolution is an essential land parameter for agricultural applications like irrigation mapping, scheduling, crop water stress assessment, etc. However, available satellite derived soil moisture products are inadequate for meeting the requirements of agricultural applications due to coarse scale soil moisture (~10–40 km). In this article, we developed an operational framework for first of its kind sub-km (~500 m) operational soil moisture product over India by utilizing ISRO’s EOS-04 C-band synthetic aperture radar (SAR) data based on active-passive approach. The potential of EOS-04 SAR for sub-km scale is demonstrated and tested over major cropland sites covering highly heterogeneous and dynamic crop conditions in different agro-climatic regions over India which shows a good agreement with in situ datasets with mean ubRMSE, ranging from 0.051 to 0.078 m³ /m³. [ABSTRACT FROM AUTHOR]

In agrarian society, land is a critical resource. Not only does access to arable land increase food security and household income, it also provides resources to cope with any environmental stresses. In most cases, in the low-income developing regions land distribution is very heterogeneous. Based on empirical research in coastal Bangladesh, this article explores patterns in land ownership among the local farmers, discussing how gender, ethnicity, religion, and status relate to farm size, playing a critical role in shaping the heterogeneous distribution of land ownership. Historical patterns of inequality and marginality influence land distribution patterns as the historical 'Zamindar system' in the region reinforced elite control. Colonial and post-colonial expansion into climate-vulnerable regions fuelled land expropriation. Cultural constructions of gender create challenges for females owning land. These legacies impact current land ownership patterns. Land distribution informs who is struggling with limited resources and who needs financial subsidies or other forms of support in times of crisis. Even though this paper has a regional focus, it provides critical insights and caution about overlooked assumptions of resource distribution, poverty, and development that can be applied to other parts of the Global South facing similar social, economic and postcolonial legacies. [ABSTRACT FROM AUTHOR]

Species‐specific management strategies have been implemented to address persistently low continental populations of several duck species, including the northern pintail (Anas acuta). In the Canadian Prairie Pothole Region (PPR), addressing threats from spring‐seeded cereals on pintail productivity may provide sufficient gains to recover populations. Research on pintail duckling ecology has revealed that duckling survival may be greater in grassland‐dominated landscapes than in annual cropland‐dominated landscapes, possibly limiting the benefits of fall‐seeded cropping practices. Winter wheat crops increase nest success and may assist nesting pintail populations through provision of nesting refuges from spring tillage operations, earlier hatch, and greater nest densities compared to traditional spring‐seeded cereal crops. Yet inadequate duckling survival may reduce these benefits. Our principal objective was to examine if pintail reproductive success in winter wheat in cropland‐dominated landscapes was comparable to grassland‐dominated landscapes or, alternatively, if duckling survival rates in cropland‐dominated landscapes offset the gains of greater nesting success in winter wheat. We captured and radio‐marked 104 nesting female pintails in grasslands and croplands of southern Saskatchewan, during 2011–2012. We modeled cumulative survival to 30 days post hatch in relation to landscape composition and land cover type, specifically, the influence of nesting in fall‐seeded crops. Predicted 30‐day survival for ducklings hatched in perennial cover (40.8% [85% CI = 40.0–44.6%]) in grassland‐dominated landscapes and winter wheat (38.2% [32.0–44.4%]) in cropland‐dominated landscapes was more than double survival of ducklings hatched in spring‐seeded cropland (16.9% [12.6–21.6%]) in cropland‐dominated landscapes. Ducklings moving through local environments with more perennial cover and seasonal wetlands, but less wetland edge, had increased survival. The benefit of greater nest survival in winter wheat was not completely superseded by reduced duckling survival for broods raised in intensive agricultural landscapes. The retention of grassland landscapes and expansion and promotion of fall‐seeded crops in cropland‐dominated landscapes can benefit northern pintails across broad regions of the PPR. [ABSTRACT FROM AUTHOR]

Aim: As climate change increases the frequency and severity of droughts in many regions, conservation during drought is becoming a major challenge for ecologists. Droughts are multidimensional climate events whose impacts may be moderated by changes in temperature, water availability or food availability, or some combination of these. Simultaneously, other stressors such as extensive anthropogenic landscape modification may synergize with drought. Useful observational models for guiding conservation decision‐making during drought require multidimensional, dynamic representations to disentangle possible drought impacts, and consequently, they will require large, highly resolved data sets. In this paper, we develop a two‐stage predictive framework for assessing how drought impacts vary with species, habitats and climate pathways. Location: Central Valley, California, USA. Methods: We used a two‐stage counterfactual analysis combining predictive linear mixed models and N‐mixture models to characterize the multidimensional impacts of drought on 66 bird species. We analysed counts from the eBird participatory science data set between 2010 and 2019 and produced species‐ and habitat‐specific estimates of the impact of drought on relative abundance. Results: We found that while fewer than a quarter (16/66) of species experienced abundance declines during drought, nearly half of all species (27/66) changed their habitat associations during drought. Among species that shifted their habitat associations, the use of natural habitats declined during drought while use of developed habitat and perennial agricultural habitat increased. Main Conclusions: Our findings suggest that birds take advantage of agricultural and developed land with artificial irrigation and heat‐buffering microhabitat structure, such as in orchards or parks, to buffer drought impacts. A working lands approach that promotes biodiversity and mitigates stressors across a human‐induced water gradient will be critical for conserving birds during drought. [ABSTRACT FROM AUTHOR]

We aimed to determine the energy expenditure, oxygen uptake, and exercise intensity of 10 care farming activities performed by adults. The study had a crossover experimental design. Participants performed 10 care farming activities for 5 minutes, including four plant- and three animal-mediated activities, and three other activities. Each participant wore a portable telemetric calorimeter during the activities, and oxygen uptake, heart rate, and exercise intensity were measured. Twenty-one adults (aged 31.5 ± 10.2 years) participated in our study. Energy expenditure, oxygen uptake, and exercise intensity differed significantly for each activity. The 10 care farming activities were regarded as light- to moderate-intensity activities. The exercise intensity, energy expenditure, and oxygen uptake for organizing a garden plot were significantly higher than those for other care farming activities. Cooking using harvests, interacting with dogs, and feeding rabbits had the lowest exercise intensity, energy expenditure, and oxygen uptake. Other activities, such as transplanting plants, harvesting, creating art, maintaining a garden, walking with a dog, and cleaning the farm, had moderate exercise intensity, energy expenditure, and oxygen uptake. Energy expenditure, oxygen uptake, and exercise intensity data could be useful when developing a care farming program suitable for the physical condition of participants in care farming interventions. [ABSTRACT FROM AUTHOR]

We investigated how the presence of the highly range-restricted Agulhas Long-billed Lark Certhilauda brevirostris (ALBL) varies with vegetation type and landscape features. The lark's distribution is nearly completely outside formally protected areas and overlaps with a region where agriculture has transformed the landscape, with very little of the original vegetation type remaining. Establishing important habitat requirements is needed to better manage conservation efforts for the species. We conducted 10-minute point counts at 51 sites along small rural roads quarterly between October 2020 and January 2022, and recorded ALBL in 58% of the counts. A subset of 45 sites was used to model occupancy. According to a null constant parameter model, occupancy at sample sites was high (0.91) with a detection probability of 0.67 for each site where the species was present. Modelling of habitat features and vegetation type found that ALBL occupancy was best explained by the presence of renosterveld, the shrubby indigenous vegetation type. Occupancy increased at a site up to 25% renosterveld cover, after which there was no effect. Occupancy was also positively associated with renosterveld vegetation presence along fence lines and a combination of renosterveld and decreasing riverine vegetation cover. Presence was little modified by seasonal changes in agricultural land use. Overall, our results suggest that although the ALBL is locally abundant, certain habitat features need to be preserved to ensure the species' continued presence in this agricultural region. [ABSTRACT FROM AUTHOR]

The rice–crayfish co-culture system, a representative of Agri-aqua food systems, has emerged worldwide as an effective strategy for enhancing agricultural land use efficiency and boosting sustainability, particularly in China and Southeast Asia. Despite its widespread adoption in China's Jianghan Plain, the exact spatiotemporal dynamics and factors influencing this practice in this region are yet to be clarified. Therefore, understanding the spatiotemporal dynamics and influencing factors of the rice–crayfish fields (RCFs) is crucial for promoting the rice–crayfish co-culture system, and optimizing land use policies. In this study, we identified the spatial distribution of RCF using Sentinel-2 images and land use spatiotemporal data to analyze its spatiotemporal dynamics during the period of 2016–2020. Additionally, we used the Multiscale Geographically Weighted Regression model to explore the key factors influencing RCF's spatiotemporal changes. Our findings reveal that (1). the RCF area in Jianghan Plain expanded from 1216.04 km2 to 2429.76 km2 between 2016 and 2020, marking a 99.81% increase. (2). RCF in Jianghan Plain evolved toward a more contiguous and clustered spatial pattern, suggesting a clear industrial agglomeration in this area. (3). The expansion of the RCFs was majorly influenced by its landscape and local agricultural conditions. Significantly, the Aggregation and Landscape Shape Indexes positively impacted this expansion, whereas proximity to rural areas and towns had a negative impact. This study provides a solid foundation for promoting the rice–crayfish co-culture system and sustainably developing related industries. To ensure the sustainable development of rice–crayfish co-culture industries in Jianghan Plain, we recommend that local governments optimize the spatial layout of rural settlements, improve transportation infrastructure, and enhance regional agricultural water sources and irrigation system construction, all in line with the national strategy of rural revitalization and village planning. Additionally, promoting the concentration and contiguity of RCF through land consolidation can achieve efficient development of these industries. [ABSTRACT FROM AUTHOR]

Land Use and Land Cover (LULC) are the main components that indicate the coverage of land and its use. Kosova Plain, a flat and gentle plain with an altitude between 450-600 m, is one of the central plains in Kosova, where the human impact and environmental changes are very high. As a terrain with land with high-quality soils, it was one of the main areas of agricultural production in the past. With the industrialization of Kosova especially with coal surface mining, began an era of employment in other sectors rather than in agriculture, and its consequences were population migration inside Kosova, which is shown by the rising urban population and extension of artificial surfaces towards agricultural areas. Population migration inside Kosova is made mostly towards plain areas where most of the settlements are found, but also where high capability land is found. The article analyzes natural conditions of agricultural land in Kosova Plain and spatial and temporal changes in land cover as one of the consequences of pressure on the environment, especially in soil resources, where with GIS/RS analysis was made possible to use topographic maps and aerial images of different years, to analysis these changes. In 1990, the total area of artificial surfaces in Kosova Plain was 7,157 ha, while in 2020, it was increased to 15,881 hectares. There is an increase of artificial surfaces in urban fabric, mineral extraction sites, and road infrastructure, mostly done on agricultural land. Agriculture areas experienced a decrease of 8.76%. The extension of artificial surfaces was primarily made in an unplanned way. The results show that in the future, zoning of built-up areas is needed. [ABSTRACT FROM AUTHOR]

The present study, detailed a survey of the academic debate and scientific trends regarding generational succession in agriculture. Hence this study is categorized under quantitative and qualitative bibliometric research. For this research, the Scopus database was accessed to identify scientific articles from publications between the years 2010 and 2021. The search, which included keywords like "successors" and "farm*", resulted in 57 relevant articles. For the study, eleven thematic categories were selected, viz., Factors that influence generational succession; Gender issues in generational succession; Educational aspects in succession; Coping strategies in relation to the future of rural properties and utilization of agricultural land; Succession planning; Issues related to the dairy farming activity and the presence of successors; The role of rural youth in the succession; Socioeconomic effects on rural properties from the presence of successors; Agricultural transfers to "new" farmers; Emotional and belonging aspects in generational transfer; and Relationships and perceptions of non-successors with respect to rural property and succession. However, the factors that affect generational renewal and gender issues in generational succession are the themes that recur most often in the research. Europe is in the forefront in terms of research on succession, and reveals new research pathways and is on the frontline for the development of public policies on generational succession in agriculture. Finally, the other emerging themes were observed to be those which dealt with the relationship that exists between the emotional aspects and succession, as well as agricultural transfers to "new" farmers. [ABSTRACT FROM AUTHOR]

Rumen flukes cause heavy economic losses in the ruminant industry worldwide, especially in tropical and subtropical countries. This study estimated the prevalence of rumen flukes in buffaloes, identified the species diversity, and determined risk factors associated with rumen fluke prevalence in Perak, Peninsular Malaysia. A cross-sectional study was conducted, and 321 faecal samples were collected from six buffalo farms. A structured questionnaire was developed, and farmers were interviewed to obtain information regarding risk factors associated with rumen fluke infection. The faecal samples were examined using sedimentation and Flukefinder® techniques. Genomic DNA was extracted from the fluke eggs recovered using the Flukefinder® method, and the internal transcribed spacer 2 (ITS2) fragment was amplified and sequenced to facilitate species identification. The results showed that the overall prevalence of rumen fluke across the sampled farms was 40.2% (129/321). Three rumen fluke species were identified, namely, Fischoederius elongatus, F. cobboldi, and Orthocoelium streptocoelium. Several management factors had a significant association (P < 0.05) with rumen fluke prevalence, including production type, cleaning of the stable, drinking water system, flooding around the farm, grazing system, pasture sharing with other livestock, and deworming program. This work constitutes the first attempt to understand the epidemiology of rumen fluke infection in the region and suggests that good farm management, pasture management, choosing appropriate drugs, and proper husbandry practices may improve buffalo health and production in areas where rumen flukes are prevalent. [ABSTRACT FROM AUTHOR]

Understanding and assessing the spatiotemporal patterns in crop-specific phosphorus (P) fertilizer management is crucial for promoting crop yield and mitigating environmental problems. The existing P fertilizer dataset, derived from sales data, depicts an average application rate on total cropland at the county level but overlooks cross-crop variations. Conversely, the survey-based dataset offers crop-specific application details at the state level yet lacks inter-state variability. By reconciling these two datasets, we developed long-term gridded maps to characterize crop-specific P fertilizer application rates, timing, and methods across the contiguous US at a resolution of 4 km × 4 km from 1850 to 2022. We found that P fertilizer application rate on fertilized area in the US increased from 0.9 g P m-2 yr-1 in 1940 to 1.9 g P m-2 yr-1 in 2022, with substantial variations among crops. However, approximately 40 % of cropland nationwide has remained unfertilized in the recent decade. The hotspots for P fertilizer use have shifted from the southeastern and eastern US to the Midwest and the Great Plains over the past century, reflecting changes in cropland area, crop choices, and P fertilizer use across different crops. Pre-planting (fall and spring) and broadcast application are prevalent among corn, soybean, and cotton in the Midwest and the Southeast, indicating a high P loss risk in these regions. In contrast, wheat and barley in the Great Plains receive the most intensive P fertilizer at planting and via non-broadcast application. The P fertilizer management dataset developed in this study can advance our comprehension in agricultural P budget and facilitate the refinement in P fertilizer best management practices to optimize crop yield and reduce P loss. Datasets are available at https://doi.org/10.5281/zenodo.10700822 (Cao et al., 2024). [ABSTRACT FROM AUTHOR]

Pesticide use in agricultural landscapes creates environmental contamination that is heterogenous in space and time. Mobile organisms, such as bees, are exposed to multiple contamination sources when visiting patches that vary in the amount, timing and toxicity of pesticides used. Yet, environmental risk assessments (ERA) typically fail to consider this heterogeneity, in part because of the complexities of estimating exposure to different pesticides, and subsequent risk at organism‐relevant scales.We use pesticide assays of 269 bee‐collected pollen samples to understand the spatiotemporal variability of risk across a network of 41 field sites in southern Sweden. Observed bee pesticide risk is calculated based on compound‐specific residue quantifications in pollen and standardized toxicity data. We then compare the ability of three classes of landscape‐scale variables to predict this risk: (1) landscape composition and configuration metrics, (2) landscape load based on national pesticide use data and (3) predictions from a newly developed bee pesticide exposure model.Based on use data, 10 crops account for 81% of the total risk. We detected 49 pesticide compounds in bee‐collected pollen. Although herbicides and fungicides constitute the bulk of detected pesticides, both in frequency and amount quantified, unsurprisingly, insecticides contribute the most to risk.Landscape composition and configuration metrics did not predict observed pesticide risk, and interactions with bee species indicate taxa‐dependency in predictions. Landscape load predicted observed risk consistently between taxa. Risk estimates from our exposure model were strongly predictive but only when considering realized risk (i.e., risk estimates based on prior pesticide use information).Synthesis and applications. Predicting pesticide risk based on landscape patterns could enable landscape‐scale ERA. However, simple metrics of landscape pattern, such as proportion of agricultural land, are not sufficient. We found that risk observed in bee‐collected pollen was best predicted when integrating spatialized pesticide use in the pesticide exposure model, underscoring the importance of such data for research, monitoring and mitigation. Further, we propose a guidance framework for future landscape ecotoxicological risk analyses that clarifies data needs relative to risk prediction goals. [ABSTRACT FROM AUTHOR]

Agriculture is vital for supporting human populations, but its intensification often leads to landscape homogenization and a decline in non‐provisioning ecosystem services. Ecological intensification and multifunctional landscapes are suggested as nature‐based alternatives to intensive agriculture, using ecological processes like natural pest regulation to maximize food production. Birds are recognized for their role in increasing crop yields by consuming invertebrate pests in several agroecosystems. However, the understanding of how bird species, their traits and agricultural land cover influence the structure of bird–pest interactions remains limited. We sampled bird–pest interactions monthly for 1 year, at four sites within a multifunctional landscape, following a gradient of increasing agricultural land cover. We analysed 2583 droppings of 55 bird species with DNA metabarcoding and detected 225 pest species in 1139 samples of 42 bird species. As expected, bird–pest interactions were highly variable across bird species. Dietary pest richness was lower in the fully agricultural site, while predation frequency remained consistent across the agricultural land cover gradient. Network analysis revealed a reduction in the complexity of bird–pest interactions as agricultural coverage increased. Bird species abundance affected the bird's contribution to the network structure more than any of the bird traits analysed (weight, phenology, invertebrate frequency in diet and foraging strata), with more common birds being more important to network structure. Overall, our results show that increasing agricultural land cover increases the homogenization of bird–pest interactions. This shows the importance of maintaining natural patches within agricultural landscapes for biodiversity conservation and enhanced biocontrol. [ABSTRACT FROM AUTHOR]

Introduction: As one of the agglomeration models targeting cluster-based rural development, cluster farming has been promoted in Ethiopia and it is already reported to have significant welfare implications, but participation rates are not as high as expected. This study examines the role of land as a constraint to the development of cluster-based development in Ethiopia both using extensive and intensive measures of cluster farming. The study further disaggregates farm households based on their farm size to better understand potential heterogeneities in the relationship between farm size and cluster farming. The paper also documents other household socio-economic and network characteristics that may matter in cluster farming. Methods: We use a large-scale farm household data from 3,969 households coupled with some expert insights on cluster farming in Ethiopia. Households in the study areas grow major staples such as maize, wheat, teff, malt barley, and sesame in four main regions of Ethiopia. We employ a double hurdle model to examine both the decision to participate and the extent to which households participate in cluster farming. By extent of participation, we refer to the amount of land and share of land farm households contribute to cluster farming. For robustness purposes, we also estimate the Tobit and Linear Probability Models. Results: We show a positive association between farm size and cluster farming both at the extensive and intensive margins. This relationship turns negative for large amounts of land. This shows that cluster farming increases with farm size up to a threshold beyond which it declines. We also find suggestive evidence that participation rates are lower for small-scale farms, but also declines for large-scale farms. In addition, we show that access to information and network characteristics also matter in enabling cluster farming. Conclusion: The findings of this study are relevant in the framework of plans to upscale the cluster-based development initiative in Ethiopia. Attention to landholding issues is key and may be an important area where policy action can be geared to boost cluster farming. Moreover, our results inform potential targeting plans that aim to increase the participation of small-scale farmers who are usually the intended targets of such programs. [ABSTRACT FROM AUTHOR]

Aquatic invertebrates provide important ecosystem services, including decomposition and nutrient cycling, and provide nutrition for birds, fish, amphibians, and bats. Thus, the effects of agricultural land management practices on aquatic invertebrates are relevant to farmers, wildlife biologists, and policymakers. Here, we used data on aquatic invertebrates (159 taxa, 73 to species, 75 to genus/family) collected in 40 wetlands in the Canadian prairies to test for direct and indirect relationships among land management types (perennial cover, organic, minimum tillage, conventional), landscape structure (cropland and wetland cover within the surrounding landscape), and water quality (total nutrient levels, turbidity) on species richness of invertebrates using structural equation modelling. Additionally, we assessed variation in community composition within and among wetlands in different land use management types using a direct gradient analysis and variance partitioning. The direct effects of land management type were not supported but we found strong supportive evidence that effects of land management on richness were significantly mediated through cropland cover, nutrient levels, and turbidity. After controlling for these indirect effects, aquatic invertebrate richness decreased along a gradient from the lowest to the highest farming intensity, i.e., richness decreased from perennial cover sites to organic to minimum tillage to conventional sites. Support was also found for negative effects of nutrient levels and turbidity on richness. We did not find significant support for differences in gamma diversity or a simple test (homogeneity of multivariate dispersions) of differences in turnover among land management types; however, land management had a significant effect in distance-based redundancy analysis. Taken together, these results suggest that focusing conservation efforts on reducing cropland erosion and nutrient inputs to wetlands and creating more permanent cover may be effective strategies for conserving richness of aquatic invertebrates in agricultural landscapes in this region. [ABSTRACT FROM AUTHOR]

Global Navigation Satellite Systems-Interferometric Reflectometry (GNSS-IR) is an emerging remote sensing technique studied and demonstrated for soil moisture retrieval over bare soil using multipath GNSS data. However, retrieval of soil moisture in the presence of vegetation/crops is still a very challenging task even becoming a more complex problem without using any ancillary datasets to compensate the vegetation effect for soil moisture retrievals in higher crop growth stages. This paper presents a novel multipath phase-based vegetation correction scheme for improved field-scale soil moisture retrieval using L-band data from Navigation with Indian Constellations (NavIC) based on GNSS-IR technique. The proposed three steps vegetation correction scheme categorized the crop as per growth stages for sensitivity analysis of NavIC derived multipath phase as GNSS-IR observables and significantly compensated vegetation effects on multipath phase for improved soil moisture retrievals. The proposed method utilized only multipath phase data as single SNR metrics without any ancillary data sets and validated during complete growth cycle of winter wheat crop (sowing to harvesting stages). It has been shown that the soil moisture retrieved using proposed vegetation correction scheme provides a Pearson correlation coefficient of 0.87 and ubRMSD of 0.0341 m3/m3 with in situ measured soil moisture, which is better than bare scheme with Pearson correlation coefficient of 0.71 and ubRMSD of 0.0480 m3/m3. Overall, proposed scheme has found highly effective for vegetation correction and has shown a good potential candidate for VSM retrievals over crop-covered soil using other GNSS constellations (GPS, GLONASS, Galileo and BeiDou etc.). [ABSTRACT FROM AUTHOR]

Based on historical documents, population data, published results, remote sensing data products, statistical data and survey data, this study reconstructed the cropland area and the spatial pattern changes at 28 time points from 1000 to 2020 in Northeast China. 1000 to 1600 corresponds to historical provincial-level administrative districts, while 1700 to 2020 corresponds to modern county-level administrative districts. The main findings are as follows: (1) The cropland in Northeast China exhibited phase changes of expansion-reduction-expansion over the past millennium. (2) The cropland area in Northeast China increased from 0.55 × 104 km2 in 1000 to 37.90 × 104 km2 in 2020 and the average cropland fraction increased from 0.37 % to 26.27 %; (3) From 1000 to 1200, the cropland area exhibited an increasing trend, peaking in 1200. The scope of land reclamation was comparable to modern times, but the overall cropland fraction remained low. The cropland area significantly decreased between 1300 and 1600, with the main land reclamation area was reduced southward into Liaoning Province. From 1700 to 1850, the cropland area increased slowly, and the agricultural reclamation gradually expanded northward. After 1850, there was almost exponential growth, with the cropland area continuously expanding to the whole study area, and the growth trend persists until 2020; (4) The dataset of changes in cropland of administrative districts in Northeast China, reconstructed based on improved historical cropland reconstruction methods, significantly enhances time resolution and reliability. Additionally, the dataset shows the changing characteristics of cropland in Northeast China over the past millennium, especially over the past 300 years, which can provide a refined data base for building a historical cropland gridded dataset. [ABSTRACT FROM AUTHOR]

Drained agricultural peatlands occupy only 1% of agricultural land but are estimated to be responsible for approximately one third of global cropland greenhouse gas emissions. However, recent studies show that greenhouse gases fluxes from agricultural peatlands can vary by orders of magnitude over time. The relationship between these hot moments (individual fluxes with disproportionate impact on annual budgets) of greenhouse gas emissions and individual chamber locations (i.e. hot spots with disproportionate observations of hot moments) is poorly understood, but may help elucidate patterns and drivers of high greenhouse gas emissions from agricultural peatland soils. We used continuous chamber-based flux measurements across three land uses (corn, alfalfa, and pasture) to quantify the spatiotemporal patterns of soil greenhouse gas emissions from temperate agricultural peatlands in the Sacramento-San Joaquin Delta of California. We found that the location of hot spots of emissions varied over time and were not consistent across annual timescales. Hot moments of nitrous oxide (N2O) and carbon dioxide (CO2) fluxes were more evenly distributed across space than methane (CH4). In the corn system, hot moments of CH4 flux were often isolated to a single location but locations were not consistent across years. Spatiotemporal variability in soil moisture, soil oxygen, and temperature helped explain patterns in N2O fluxes in the annual corn agroecosystem but were less informative for perennial alfalfa N2O fluxes or CH4 fluxes across ecosystems, potentially due to insufficient spatiotemporal resolution of the associated drivers. Overall, our results do not support the concept of persistent hot spots of soil CO2, CH4, and N2O emissions in these drained agricultural peatlands. Hot moments of high flux events generally varied in space and time and thus required high sample densities. Our results highlight the importance of constraining hot moments and their controls to better quantify ecosystem greenhouse gas budgets. [ABSTRACT FROM AUTHOR]

In the present era, the characteristics of agricultural development most exposed to the effects of global warming and irregular precipitation patterns remain scantily understood in the regions. The latest study aimed to identify the target regions with different degrees of variation in the average temperature, followed by their resource potential, conditions, strengthening, and production efficiency. Based on their groups through statistical studies, three groups of Russian regions attained partition (using a sample that included 77 Russian regions), with low (Group I - 20 regions), medium (Group II - 25 regions), and high (Group III - 32 regions) estimates of the linear temperature trend. In Group III, 72% of the regions appeared favorable for agriculture, according to the classification approved by the Russian Government. In Group I, 60% of the regions emerged as unfavorable. Based on the statistical indicators, these established that Group III has a considerable resource potential for agriculture, comprising 30% of agricultural lands, 36% of all crops, up to 50% of the area of fruit and berry plantations, 40% of milk production, and 69% of meat and meat products manufacture intended in this group of different regions. In Group III, conditions and intensification of production are developing more dynamically (the volume of subsidies allocated during the study period has increased almost five times), efficiency is higher (profit per 100 ha of agricultural land in Group I is 0.2 million rubles, whereas, in Group III, it equals 1 million rubles), with significant labor and human potential gathered there. This circumstance requires the development of a program for the adaptation of these regions to emerging climate changes. [ABSTRACT FROM AUTHOR]

Background and Aims: Understanding microbial compositions and functions in arable soils is crucial for effective agroecosystem management. While many studies have explored this topic, large-scale investigations are lacking, resulting in the absence of consistent and reliable patterns of communities and functions of soil microorganisms. Methods: To address this gap, we performed an integrated analysis of published sequencing data from the soils of three main arable fields: upland, paddy, and paddy-upland rotation. Results: Bacterial diversity (richness, Shannon) was highest in upland soils. Actinobacteria and Planctomycetes were enriched in upland soils, while Proteobacteria, Chloroflexi, and Nitrospirae preferred paddy and paddy-upland rotation soils. Bacteria in upland soils have a greater functional potential to decompose aromatic compounds, as well as for chitinolysis and ureolysis. Methanotrophy, methylotrophy, sulfur-related respiration, and most nitrogen metabolic processes were enriched in paddy fields. Bacteria in upland soils are characterized by increased dormancy potential and a faster response to resource input than those in paddy and paddy-upland rotation soils. Stochastic processes poorly contribute to the bacterial assembly in paddy soils, indicating strong environmental filtering due to anaerobic conditions. The spatial turnover in bacterial community composition was much faster than the functional potential, indicating high functional redundancy, especially in paddy soils. Edaphic factors were the major contributors to bacterial composition, whereas the cropland type influenced the predicted functions. Conclusions: Land use defines microbial composition, functional attributes, and ecological characteristics (e.g., dormancy potential, assembly processes, and functional redundancy). These findings deepen our knowledge of microbial biogeographic patterns in soils of agricultural ecosystems and provide new insights into sustainable cropland management. [ABSTRACT FROM AUTHOR]

When host nests are scarce, avian brood parasites would benefit from behaviours that increase the availability of suitable nests. Several studies reported ejection of host nestlings from nests by brood parasites; however, whether brood parasites do so to induce the host to re‐nest and thus increase opportunities for future parasitism (i.e. 'farming' behaviour) remains unclear. Here, we report observational evidence of farming behaviour by a common cuckoo Cuculus canorus female in a Daurian redstart Phoenicurus auroreus population: (1) the cuckoo destroyed a host nest by ejecting all nestlings, (2) the host then produced a new nest and (3) the cuckoo successfully parasitized the replacement nest. We suggest that farming behaviour may be more common, but often goes undetected because it requires intense nest monitoring. [ABSTRACT FROM AUTHOR]

The conversion of woodland ecosystems to agricultural landscapes has led to unprecedented losses of biodiversity and ecosystem functioning globally. Unsustainable agricultural practices have contributed to the degradation of soil's physical and biogeochemical properties. Ecological restoration of unproductive agricultural land is imperative for reversing land degradation and ameliorating the degrading effects of agriculture on biodiversity and ecosystem functions. However, it is unclear to what extent common restoration activities, such as tree planting, can facilitate the recovery of ecosystem condition and in particular, improve soil physical, biogeochemical and biotic components. Here, we investigated how the cessation of cropping, followed by tree planting, affected soil carbon concentrations and key biophysical soil functions. Data were collected across 10 sites a decade after the replanting of woody species on old fields in semi‐arid Western Australia. We applied a chronosequence approach and measured soil functions in fallow cropland (restoration starting point), 10‐year‐old planted old fields and intact woodland reference sites (restoration target point). We stratified sampling between open areas and patches under trees in planted old fields and reference woodlands to account for inherent biophysical differences. Soils under planted trees recovered to some extent, having reduced soil compaction and higher soil penetration depth in comparison with the fallow cropland. However, soils under trees in planted old fields did not reach woodland reference conditions for these properties. Moreover, recovery was not evident for other soil physical, biogeochemical and biotic components such as soil organic carbon, soil moisture, leaf litter and woody debris decomposition rates. Limited recovery of soil functions may be at least partly explained by time lags associated with slow growth rates of planted trees in dry ecosystems. Our study shows that the legacy of cropping can persist over long timeframes in semi‐arid regions, with modest signs of woodland recovery beginning to emerge 10 years after tree planting. [ABSTRACT FROM AUTHOR]

Lake Jošava (Croatia) is a shallow reservoir surrounded by agricultural land. In the present study, the trophic cascade was tested by examining the effects of stocking with common carp on plankton and periphytic microphytes. Before stocking, the phytoplankton community was dominated by the chrysophyte Synura uvella. In the epilithon and epiphyton, the predominant diatoms were prostrate, stalk-forming, and motile taxa representing an important food source for adult copepods. After stocking, phytoplankton biomass declined and the community shifted towards small centric diatoms, allowing the small-bodied zooplankton to exploit them. The lower biomass of adult copepods allowed rotifers to proliferate and exploit phytoplankton, while small cladocerans and nauplii fed primarily on epilithon. One month after stocking, phytoplankton was dominated by cryptophytes, small centric diatoms and chlorophytes, which were an important food for rotifers, while none of the zooplankton groups showed a significant relationship with the epilithic and epiphytic communities. By the end of the experiment, food was scarce due to reduced biomass of autotrophs, and zooplankton possibly began to feed on other sources. Our results add to the knowledge about the trophic cascade hypothesis in small shallow reservoirs. [ABSTRACT FROM AUTHOR]

The dissemination of antibiotic resistance genes (ARGs) in soil has become a global environmental issue. Vermicomposting is gaining prominence in agricultural practices as a soil amendment to improve soil quality. However, its impact on soil ARGs remains unclear when it occurs in farmland. We comprehensively explored the evolution and fate of ARGs and their hosts in the field soil profiles under vermicompost application for more than 3 years. Vermicompost application increased several ARG loads in soil environment but decreased the high-risk bla -ARGs (bla ampC , bla NDM , and bla GES-1) by log(0.04 – 0.43). ARGs in soil amended with vermicompost primarily occurred in topsoil (approximately 1.04-fold of unfertilized soil), but it is worth noting that their levels in the 40–60 cm soil layer were the same or even less than in the unfertilized soil. The microbial community structure changed in soil profiles after vermicompost application. Vermicompost application altered the microbial community structure in soil profiles, showing that the dominant bacteria (i.e., Proteobacteria, Actinobacteriota, Firmicutes) were decreased 2.62%–5.48% with the increase of soil depth. A network analysis further revealed that most of ARG dominant host bacteria did not migrate from surface soil to deep soil. In particular, those host bacteria harboring high-risk bla -ARGs were primarily concentrated in the surface soil. This study highlights a lower risk of the propagation of ARGs caused by vermicompost application and provides a novel approach to reduce and relieve the dissemination of ARGs derived from animals in agricultural production. [Display omitted] [ABSTRACT FROM AUTHOR]

Cereal crop (rice, wheat, maize etc.) residues mainly include the aboveground parts of plants that remain in an agricultural field after crop has been harvested. Nutritional value, organic matter content, and porous nature of cereal crop residues make them suitable for use on agricultural land to improve the soil physical, chemical, and biological properties. Application of crop residue into the soil needs proper strategies, which could sustain crop production as well as soil health. In this comprehensive review, efforts have been made to compile data on studies conducted the impact of residues on various soil health properties, current management practices and residue removing issues for a better understanding of soil health improvement strategies through cereal crop residue retention or incorporation. Further, the article discussed the relationship between cereal residue retention/incorporation and soil health properties by considering 113 peer-reviewed studies. We evaluated site-specific advantages and disadvantages involved on residue retention/incorporation. In addition, we found out the suitability of residue incorporation vs. retention, in respect to soil health improvement. This review found that residue retention or incorporation can positively influence soil physical, chemical, and biological characteristics associated with soil health. Significant influences of abiotic factors on residue management were observed in different locations. To our knowledge, this comprehensive review is the first one to present global view of current scenario of cereal crop residue management, their influence on soil health improvement, and residue removing issues with citing worldwide evidences. [ABSTRACT FROM AUTHOR]

The growth of the world population is leading to an increased demand for food production. Consequently, there is a need to update agricultural processes to enhance production. Smart farming has evolved as a farm management concept that leverages real-time, dependable, and site-specific agricultural information to ensure consistent and sustainable yields. This study focuses on soil nutrient analysis, specifically nitrogen (N), phosphorus (P), and potassium (K) for enhancing crop production. Maintaining an appropriate balance of NPK is crucial for the well-rounded nutrition of crops. Various environmental factors such as temperature, rainfall, humidity, and soil pH affect the NPK composition of agricultural land. The optimal usage of NPK levels can help to improve plant growth, increase crop yields, and enhance overall farm productivity. Hence, we have proposed a stack regressor learning algorithm comprising of two layers for accurate, reliable, and context-sensitive predictions of NPK levels. The proposed approach considers the combined impact of these environmental factors and predicts the optimal NPK requirements tailored to specific crops and agricultural land. The analysis of graphs demonstrates that the predictive accuracy of the proposed stacked regressor model far surpasses that of preexisting built-in machine learning models. This study helps farmers make informed decisions, leading to productivity and sustainability. [ABSTRACT FROM AUTHOR]

This study examines the influence of lag fertilization techniques on Pakistani wheat production, highlighting the need to understand and mitigate the environmental impacts of farming methods. The basic purpose of this study is to investigate the impact of CO2 emission from fertilization and other factors on wheat production in Pakistan, using a time series of data from 1990 to 2020. CO2 emission from fertilization (CO2EF) is estimated using the default values provided by the IPCC guidelines. The ARDL approach analyses the short-run and long-run effects of CO2EF, technology level, energy use, agricultural land, and agricultural labor on wheat production. The results show that all factors have significantly impacted wheat production in Pakistan at levels of 1% and 5% significance, both in the short and long run. These findings suggest that reducing CO2EF, technology level, energy use, agricultural land, and agricultural labor on wheat production can help to increase wheat production in Pakistan. The study also highlights the importance of adopting sustainable and efficient fertilization practices, exploring alternative fertilizers, and using crop rotation systems to mitigate the adverse effects of carbon emissions from nitrogen fertilization, energy use, and the use of technology. These measures can contribute to a more sustainable and climate-resilient agriculture sector in Pakistan. [ABSTRACT FROM AUTHOR]

Timely and accurate acquisition of spatial distribution and changes in cropland is of significant importance for food security and ecological preservation. Most studies that monitor long-term changes in cropland tend to overlook the rationality in the process of cropland evolution, and there are conflicts between the interannual cropland data, so they cannot be used to analyze land use change. This study focuses on the rationality of annual identification results for cropland, considering the long-term evolution and short-term variations influenced by natural environmental changes and human activities. An approach for annual monitoring of cropland based on long time series and deep learning is also proposed. We acquired imagery related to cropland's vegetation lush period (VLP) and vegetation differential period (VDP) from Landsat images on the Google Earth Engine (GEE) platform and used the ResUNet-a structural model for training. Finally, a long-time-series cropland correction algorithm based on LandTrendr is introduced, and interannual cropland maps of Guangdong Province from 1991 to 2020 were generated. Evaluating the cropland monitoring results in Guangdong Province every five years, we found an overall accuracy of 0.91–0.93 and a kappa coefficient of 0.80–0.83. Our results demonstrate good consistency with agricultural statistical data. Over the past 30 years, the total cropland area in Guangdong Province has undergone three phases: a decrease, significant decrease, and stabilization. Significant regional variations have also been observed. Our approach can be applied to long-time-series interannual cropland monitoring in the southern regions of China, providing valuable data support for the further implementation of cropland protection. [ABSTRACT FROM AUTHOR]

Agricultural land use alters nitrate (NO3–) uptake dynamics in streams, but the specific mechanisms linking individual agricultural stressors to benthic and hyporheic uptake remain unclear. Using stream-side mesocosms and 15N-nitrate additions, we examined the individual and combined effects of fine sediment (FS) and augmented light and phosphorus levels (L&P) on benthic and hyporheic NO3– uptake rates. In absence of FS, L&P stimulated uptake of autotrophic and heterotrophic biofilms, leading to a 12- and 7-fold increase in the benthic and hyporheic compartments, respectively. Under ambient light and nutrient conditions, FS reduced by 3-fold benthic uptake, but effects were not significant. Conversely, in the hyporheic compartment, FS induced anoxic conditions, likely stimulating denitrification and causing a 14-fold increase in hyporheic uptake. When these stressors were combined, they did not interact in the benthic compartment. Conversely, in the hyporheic compartment they interacted antagonistically, with L&P diminishing the increase in uptake induced by FS. Our results indicate that the previously observed increase of whole-stream NO3– uptake in agricultural streams is attributable to nutrients and light stimulating benthic uptake, while fine sediment effects and the role of the hyporheic compartment to total uptake are modest. Moreover, the finding that stressor interactions vary with ecosystem compartments calls for a consideration of all compartments and their contribution to whole-system functioning in multiple stressor studies. We are beginning to understand how multiple interacting stressors affect stream functioning, but more mechanistic evidence is needed to disentangle whether additive or non-additive effects prevail in human-altered ecosystems. [ABSTRACT FROM AUTHOR]

Successful farms—in the public imagination, agricultural policy, and more—tend to be highly profitable and operate at extremely large scales. Research has shown that women are less likely to operate these types of farms, possibly due to their preferences and lifestyle choices. There is evidence, however, that these gaps are additionally the result of differences in access to resources due to gender discrimination. Patterns of inequity in land inheritance and other resources limit women's farm size and choice of crops, and thus their opportunities to farm at larger, more profitable scales. Nonetheless, women farmers also employ creative strategies to make farming work for them. Our study uses 2017 Census of Agriculture data to compare women and men farmers at 7 different farm scales, revealing gendered strategies and comparing men and women farmers on equal footing. This presents a more nuanced picture of women's participation in farming at various scales. Overall, we find that within farm scales, women are often doing just as well as men—usually with fewer or different resources and approaches. Women's unbalanced representation at each farm scale, however, helps to explain why women are not always envisioned as "real farmers" in the popular conscience. [ABSTRACT FROM AUTHOR]

Sturgeon farming is rapidly expanding in Europe, where Italy ranks first in farmed caviar production. A major threat to sturgeon health in captivity is infection with Acipenser European Iridovirus (AcIV-E), a viral disease definitively identified in 2016. Here we present data on the occurrence of AcIV-E in 482 sturgeons (age ≤ 12 months, species of the genus Acipenser and the species Huso huso) collected from sturgeon farms in northern Italy between January 2021 and December 2023. The health status of each specimen was determined by necroscopy and virological assay. Virological analysis was performed on gill samples and real-time PCR specific to the MCP gene of the iridovirus viral capsid. Molecular analysis revealed positivity to the virus in 204 samples (42.68% of the total), while anatomopathological examination of nearly all fish with positive real-time PCR disclosed swollen abdomen, hepatic steatosis, splenomegaly, and increased gill volume. Two challenges to timely diagnosis are the absence of pathognomonic symptoms and the inability to isolate the virus on cell monolayers. Continuous and widespread health monitoring is therefore crucial for disease management and to effectively control spread of the virus. [ABSTRACT FROM AUTHOR]

The Asian water plantain, Alisma orientale (Sam.) Juzep, is a traditional Chinese medicinal plant. The dried tubers of the Alisma orientale, commonly referred to as Alismatis rhizome (AR), have long been used in traditional Chinese medicine to treat a variety of diseases. Soil properties and the soil microbial composition are known to affect the quality and bioactivity of plants. Here, we sought to identify variations in soil fungal communities and soil properties to determine which would be optimal for cultivation of A. orietale. Soil properties, heavy metal content, and pesticide residues were determined from soils derived from four different agricultural regions around Shaowu City, Fujian, China, that had previously been cultivated with various crops, namely, Shui Dao Tu (SDT, rice), Guo Shu Tu (GST, pecan), Cha Shu Tu (CST, tea trees), and Sang Shen Tu (SST, mulberry). As fungi can either positively or negatively impact plant growth, the fungal communities in the different soils were characterized using long-read PacBio sequencing. Finally, we examined the quality of A. orientale grown in the different soils. Our results show that fungal community diversity of the GST soil was the highest with saprotrophs the main functional modes in these and SDT soils. Our data show that GST and SDT soils were most suitable for A. orientale growth, with the quality of the AR tubers harvested from GST soil being the highest. These data provide a systematic approach at soil properties of agricultural lands in need of replacement and/or rotating crops. Based on our findings, GST was identified as the optimal soil for planting A. orientale, providing a new resource for local farmers. [ABSTRACT FROM AUTHOR]

Cropland monitoring is important for ensuring food security in the context of global climate change and population growth. Freely available satellite data allow for the monitoring of large areas, while cloud-processing platforms enable a wide user community to apply remote sensing techniques. Remote sensing-based estimates of cropped area and crop types can thus assist sustainable land management in developing countries such as Ethiopia. In this study, we developed a method for cropland and crop type classification based on Sentinel-1 and Sentinel-2 time-series data using Google Earth Engine. Field data on 18 different crop types from three study areas in Ethiopia were available as reference for the years 2021 and 2022. First, a land use/land cover classification was performed to identify cropland areas. We then evaluated different input parameters derived from Sentinel-2 and Sentinel-1, and combinations thereof, for crop type classification. We assessed the accuracy and robustness of 33 supervised random forest models for classifying crop types for three study areas and two years. Our results showed that classification accuracies were highest when Sentinel-2 spectral bands were included. The addition of Sentinel-1 parameters only slightly improved the accuracy compared to Sentinel-2 parameters alone. The variant including S2 bands, EVI2, and NDRe2 from Sentinel-2 and VV, VH, and Diff from Sentinel-1 was finally applied for crop type classification. Investigation results of class-specific accuracies reinforced the importance of sufficient reference sample availability. The developed methods and classification results can assist regional experts in Ethiopia to support agricultural monitoring and land management. [ABSTRACT FROM AUTHOR]

Wasmannia auropunctata, the little fire ant, is an invasive pest threatening native biodiversity, agricultural and forestry production, and public health. In January 2022, wild populations of W. auropunctata were reported for the first time on the Chinese mainland. However, the stage and degree of W. auropunctata invasion in China are unclear. Therefore, assessing the risk of establishment and the potential impacts associated with this pest is crucial for preventing further spread. This study used the Bayesian additive regression trees (BARTs) model and global occurrence records to assess the potential distribution of W. auropunctata in southern China and the associated risk of invading urban, rural, agricultural, and forest lands. The results from our models indicate that: (1) coastal areas, southwest, and central areas are particularly suitable for W. auropunctata establishment; (2) temperature, clay content, mean normalized differential vegetation index (NDVI), and urban area are important factors in the distribution of W. auropunctata; (3) the agricultural lands in the coastal areas and the Yunnan–Guangxi border, the urban and rural lands in the coastal areas, and grasslands in the southwest should prepare for possible W. auropunctata invasion; and (4) forest lands have the highest area at risk of W. auropunctata invasion in southern China. These results provide valuable information for planning and implementing the monitoring and control strategies against W. auropunctata invasion in China. [ABSTRACT FROM AUTHOR]

Photosynthetically Active Radiation (PAR) is an important parameter in the plant photosynthesis process, which can relate to plant growth, crop water use, and leaf gas exchange. Previously, many researchers utilized commercially available sensors to monitor PAR. The high cost of the commercially available PAR sensors has limited researchers, agricultural professionals, and farmers to use and expand PAR monitoring in agricultural lands. Thus, this paper focuses on designing an affordable Internet of Things (IoT)-based PAR sensor monitoring system including 3D-printed enclosures (waterproof) for the sensors, performance evaluation of multiple light sensors, solar powering configuration, cloud setup, and cost analysis. Three sensors, including VTB8440BH photodiode, SI 1145, and LI-190R sensors, were evaluated. The 3D-printed waterproof enclosures were designed for the photodiode and SI 1145. Particle Boron was used for recording and sending the sensor data to the IoT webserver. Both the photodiode and SI 1145 were compared to LI-190R, which is the industry standard. In the calibration process, the R2 values of the photodiode and SI 1145 with LI-190R were 0.609 and 0.961, respectively. Field validation data shows that SI 1145 had a strong correlation with LI-190R. In addition, the performance evaluation data shows the photodiode had a weaker correlation with LI-190R than SI 1145. In conclusion, the study successfully developed and designed affordable and reliable IoT-based PAR sensor monitoring systems, including a 3D-printed housing, hardware, programming, and IoT website. SI 1145 with a glass filter is an alternative sensor to monitor PAR at a low cost and has the advantage of being connected to IoT microcontrollers. [ABSTRACT FROM AUTHOR]

Simulating future land use changes can be an important tool to support decision-making, especially in areas that are experiencing rapid anthropogenic pressure, such as the Cerrado–Brazilian savanna. Here we used a spatially-explicit model to identify the main drivers of native vegetation loss in the Cerrado and then extrapolate this loss for 2050 and 2070. We also analyzed the role of property size in complex Brazilian environmental laws in determining different outcomes of these projections. Our results show that distance to rivers, roads, and cities, agricultural potential, permanent and annual crop agriculture, and cattle led to observed/historical loss of vegetation, while protected areas prevented such loss. Assuming full adoption of the current Forest Code, the Cerrado may lose 26.5 million ha (± 11.8 95% C.I.) of native vegetation by 2050 and 30.6 million ha (± 12.8 95% C.I.) by 2070, and this loss shall occur mainly within large properties. In terms of reconciling conservation and agricultural production, we recommend that public policies focus primarily on large farms, such as protecting 30% of the area of properties larger than 2500 ha, which would avoid a loss of more than 4.1 million hectares of native vegetation, corresponding to 13% of the predicted loss by 2070. [ABSTRACT FROM AUTHOR]

Simple Summary: Under field conditions, interactions occur between animals, parasites and the environment. Usually, only 30% of goats (over a dispersed distribution) display high gastrointestinal nematode (GIN) burdens. Hence, focusing on individual infection would allow better management of the impact of GINs. As acclaimed evolutionary biologist and natural historian S.J. Gould (1941–2002) once emphasized: "The Median Isn't the Message". The relationship between individual and herd GIN infection levels, nutritional and productive performance and anemia parameters in a tropical farm context were evaluated. Fifty-four female goats browsing the tropical forest (supplemented with balanced feed and chopped grass) were used. Measurements were obtained every 15 days (six samplings during the study); likewise, in each sampling time, the fecal samples were obtained in the morning [AM] and afternoon [PM] to assess the GIN burdens (eggs per gram of feces). The individual AM and PM values were similar and highly correlated at each sampling time. The nutritional and productive status fluctuated over time, although the median GIN burden of the flock was relatively constant. Nevertheless, the individual GIN burden differed when assessed at 30 d intervals; thus, these sampling points can be considered independent. Higher GIN burdens were associated with low body condition and low hematocrit. Moreover, the marked fluctuation of live weight should warn that nutrition is highly dynamic and could have a more important effect than GIN burden on the performance of goats under farm conditions in the tropics. We evaluated the relationship between individual and herd GIN infection level, nutrition, production performance and anemia parameters in a tropical farm context. Fifty-four female goats were monitored to assess their body condition score (BCS, nutritional status indicator), live weight (LW) and LW gain (LWG, both used as production level indicators), FAMACHA© and hematocrit (HT, both used as anemia indicators). Goats browsed for 4 h in a tropical forest and received balanced feed and chopped grass. The eggs per gram of feces (EPG) indicated the GIN burden, with fecal samples obtained at 7:00 (AM) and 15:00 h (PM.) from each goat at six sampling points during the study. The variables and their relationship with GIN burdens were analyzed using Kruskall–Wallis, ANOVA and Friedman tests and Spearman correlations. The fecal samples obtained in the AM and PM can be equally representative of parasitic burdens (similar and highly correlated). However, the EPG of individual goats from periods of 30 days apart can be considered independent. The BCS and LWG varied between sampling times (p < 0.05), whereas EPG, LW and HT did not (p > 0.05). The GIN burden was negatively correlated with HT and BCS (−0.21, p = 0.01 for each one). The individual pattern of infection demonstrates the true impact of GINs on their hosts. Additionally, feeding and nutritional status may present important variations influencing the performance of the goats more than the impact of GINs under the farm conditions of the present study. However, GIN infection contributed to the variation in goat health and productivity in this tropical farm. [ABSTRACT FROM AUTHOR]

Background: Two major factors that determine the efficiency of programs designed to mitigate greenhouse gases by encouraging voluntary changes in U.S. agricultural land management are the effect of land use changes on producers' profitability and the net sequestration those changes create. In this work, we investigate how the interaction of these factors produces spatial heterogeneity in the cost-efficiency of voluntary programs incentivizing tillage reduction and cover-cropping practices. We map county-level predicted rates of adoption for each practice with the greenhouse gas mitigation or carbon sequestration benefits expected from their use. Then, we use these bivariate maps to describe how the cost efficiency of agricultural mitigation efforts is likely to vary spatially in the United States. Results: Our results suggest the combination of high adoption rates and large reductions in net emissions make reduced tillage programs most cost efficient in the Chesapeake Bay watershed or the Upper Mississippi and Lower Missouri sub-basins of the Mississippi River. For programs aiming to reduce net emissions by incentivizing cover-cropping, we expect cost-efficiency to be greatest in the areas near the main stem of the Mississippi River within its Middle and Lower sections. Conclusions: Many voluntary agricultural conservation programs offer the same incentives across the United States. Yet spatial variation in profitability and efficacy of conservation practices suggest that these uniform approaches are not cost-effective. Spatial targeting of voluntary agricultural conservation programs has the potential to increase the cost-efficiency of these programs due to regional heterogeneity in the profitability and greenhouse gas mitigation benefits of agricultural land management practices across the continental United States. We illustrate how predicted rates of adoption and greenhouse gas sequestration might be used to target regions where efforts to incentivize cover-cropping and reductions in tillage are most likely to be cost -effective. [ABSTRACT FROM AUTHOR]

The farm scientists working in State Agricultural Universities (SAUs), strive to solve the problems of farmers from different agro-climatic zones of the country. Inventions of them are crucial for change. Therefore, the present study explores different dimensions that can be included to measure the inventive behaviour of farm scientists, especially in SAUs, as reflected in the model developed. Moreover, this study illustrates how the dimensions identified have implications for the inventive behaviour of farm scientists that helps to overcome the lacuna in this competitive, innovative research environment. [ABSTRACT FROM AUTHOR]

The European Green Deal aims to mitigate the environmental impact of food production while improving the income of primary producers and strengthening the EU's competitiveness. We examine how the degree of ecologisation affects farms' total factor productivity (TFP). Our analysis combines a random‐parameter stochastic production frontier model with a composite indicator and a dose–response function approach. Results show a monotonically decreasing relationship between ecologisation and expected TFP level. On average, a one‐step increase in the degree of ecologisation results in a 12% decrease in TFP. However, the results indicate a non‐linear relationship. Three regions of the dose–response function can be distinguished; associated with high, medium and low degrees of ecologisation. In a region with a low degree of ecologisation, farms can increase the degree of ecologisation without reducing TFP. Both efficiency and technological differences contribute to these differences, but the main reason is technological. With increasing ecologisation, farm technology becomes more 'land using'. Therefore, farms can increase their TFP and degree of ecologisation simultaneously by using land‐saving technologies or through sustainable intensification. [ABSTRACT FROM AUTHOR]

"Management" is routinely understood by agricultural historians as an exercise in rational expertise, targeted at driving ever more efficient, "businesslike" practices on the farm. However, insights from critical management studies suggest that farm management, as a body of theory and as a form of practice, may be grounded in something less savory than epistemological superiority or the ability to improve farming practice. This article explores how the meaning of farm management changed substantially over the course of the twentieth and early twenty-first centuries, from a pragmatic approach for empowering individual farmers to a more abstract set of theories offering a chimera of control. [ABSTRACT FROM AUTHOR]

The devastation of war cuts cultivated areas and crop yields, destroys infrastructure, and contaminates the soil and water. Assessment of these impacts on Ukraine's agricultural land helps to grasp the scale of the issue, develop recovery and risk management strategies, and informs decision-making. Regional differences in agricultural productivity are apparent but the fledgeling land market still operates, albeit hesitatingly. [ABSTRACT FROM AUTHOR]