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opencc-by-4.0Nov 2022View details →

Recent Interdisciplinary Studies in Agriculture, Forestry and Allied Sciences

International E- Conference on “One Day Multidisciplinary International e-Conference on “Recent Interdisciplinary Studies in Agriculture, Forestry and Allied Sciences” Jointly Organized by the Savitribai Phule Mahila Mahavidyalaya, Satara, Department of Geography & Internal Quality Assurance Cell (IQAC) In collaboration with Pangaea Geographical Association, India on Wednesday, 30th November 2022.

opencc-zeroJun 2023View details →

Data from: The fate of nitrogen during agricultural intensification in East Africa: nitrogen budgets in contrasting agroecosystems

The intensification of agricultural systems in sub-Saharan Africa (SSA) is necessary to reduce poverty and improve food security but requires increased nutrient applications to smallholder systems. To avoid the negative consequences of intensification that result from many large-scale agricultural systems (e.g., eutrophication), we must better understand how diverse soil systems in SSA will respond to increased fertilizer applications. We tracked nitrogen (N) inputs and outputs in fertilizer trials at two maize (Zea mays)-agroecological regions of contrasting soil type. We measured maize biomass, grain yields, N leaching, and N gaseous losses from a clayey soil in Yala, Kenya, and a sandy soil in Tumbi, Tanzania, with application rates of 0, 50, 75, 100, 150, and 200 kg N ha-1 yr‑1 over multiple years. Using measurements of NO, N2O, NO3-, biomass N, and an 15N enrichment experiment, we show that N budgets in Yala were nearly always negative, meaning more N was exported in yields or lost from the system than was added in fertilizer. In Tumbi, however, N budgets were negative at lower fertilizer levels (0 and 50 kg N ha-1), but positive at higher fertilizer levels (75 and 200 kg N ha-1). At both sites, most of the N was lost through maize biomass/grain removal and N leaching (over 96% of total losses). Gas losses were a minor component of N budgets. These results highlight the importance of tailoring fertilizer recommendations to a farm's specific soil and climatic conditions. However, on these two contrasting sites, fertilizer additions at or below 50 kg N ha-1 do not lead to major losses of N (via gaseous or leaching) and may be recommended at a range of sites across SSA soils in maize agroecosystems.

opencc-by-4.0Jun 2023View details →

Validating NISAR's cropland mapping approach and the USDA/NASS Cropland Data Layer against ground truth data in a fragmented urban agricultural region

Field data used in manuscript: 1 shapefile containing the ROI outline for which Sentinel-1 data was cropped 1 shapefile containing the 93 fields investigated with their names, types and sizes as attributes  8 annual csv data for active fields, consisting of 3 harvest dates and 5 planting dates. This list is after translating data from Farmlogic Report (not conducive to analysis in the format) and filtering for fields greater 1 acre. The study lateron further screened to use only fields greater than 2 acreas (0.81 hectares).

opencc-zeroJul 2023View details →

Flower strip effectiveness for pollinating insects in agricultural landscapes depends on established contrast in habitat quality: A meta-analysis

Flower strips have become a prevalent measure in agricultural landscapes to counteract biodiversity loss and especially promote pollinators. Although their benefits for pollinating insects have been frequently evaluated and reported, generalized conclusions about optimal settings for effective flower strips are still difficult. From the perspective of pollinators, flower strips vary distinctly in habitat quality, and the same applies for the control sites selected for scientific studies. In this study, we used a meta-analytic approach based on a systematic review of recent studies (2009-2020) to analyze the relationship between flower strip effectiveness for pollinators and the contrast in habitat quality between flower strips and control sites. We extracted 350 data entries from 29 out of 172 studies based on available data for richness or abundance of the pollinator taxa groups Apiformes, Lepidoptera and Syrphidae as response variables, for both flower strips and control treatments. All flower strips and control treatments were assigned a habitat quality score including information on spatial dimension, floral resources and management. Moreover, we included information on landscape complexity as measured by percent cover of semi-natural habitats in the studied landscape. In general, our results of meta-analytical models showed an increasing effect size of flower strips on pollinators for higher contrasts in habitat quality between flower strips and control treatments. This relationship was consistent across pollinator taxa and different levels of landscape complexity. Altogether, in terms of pollinator habitat quality, high-quality flower strips were more attractive than low-quality flower strips, and the reported effectiveness of flower strips decreased from low-quality to high-quality control treatments. We recommend that results of future studies evaluating flower strips for pollinators are always linked with the contrast in habitat quality between selected flower strips and control treatments.

opencc-by-4.0Feb 2023View details →

Meteorological variables for Agriculture: daily time series for the Italian Area (MADIA daily)

Abstract The MADIA daily gridded dataset provides the series of the main agro-meteorological variables derived from ERA5 hourly surface data, with a spatial resolution of 0.25 degrees, across the Italian domain for the period 1981-2022. The dataset contains time series of minimum, average and maximum air temperature, minimum and maximum air relative humidity, wind speed, solar radiation, precipitation and reference evapotranspiration according to the FAO Penman-Monteith method. Data is provided at daily temporal resolution and in csv format (every cell is identified by the latitude/longitude coordinates of its centre). The dataset is annotated with discovery and description metadata. A vector file is included with the ERA5 cell polygons covering the Italian country for visualizing and mapping csv data. In order to facilitate the data reuse for computing statistics at Italian NUTS 2 and 3 levels, a complementary vector file which reports the cell weight in terms of fraction covered of each administrative unit considered, as well as its altitude, is provided in: <ul> <li>Parisse Barbara, Alilla Roberta, Pepe Antonio Gerardo, & De Natale Flora. (2022). Meteorological variables for Agriculture: a dataset for the Italian Area (MADIA) [Data set]. Zenodo. <a href="http://10.5281/zenodo.6868944">https://doi.org/10.5281/zenodo.6868944</a> </li> </ul> Further details on methods applied for data processing are available in: <ul> <li>Parisse B., Alilla R., Pepe A.G., De Natale F., MADIA - Meteorological variables for Agriculture: a Dataset for the Italian Area, Data in Brief, 46 (2023), 108843, <a href="https://doi.org/10.1016/j.dib.2022.108843">10.1016/j.dib.2022.108843</a>, (<a href="https://www.sciencedirect.com/science/article/pii/S2352340922010460">https://www.sciencedirect.com/science/article/pii/S2352340922010460</a>)</li> </ul> The MADIA daily dataset will be periodically updated. Attached content A ZIP archive composed by the following folders: <ol> <li>csv_data: daily time series for each year from 1981 to 2022 in csv format</li> <li>metadata: discovery and description metadata</li> <li>shp_data:  a complementary vector layer with the ERA5 cell polygons for Italy</li> </ol> Acknowledgments This work was supported by the Italian Ministry of Agricultural, Food and Forestry Policies (AgriDigit-Agromodelli, DM n. 36502 of 20/12/2018)

opencc-by-4.0Jul 2023View details →

Supplemental networks of cowords of the paper Measuring the impact of Big Data in the scientific research in Agriculture and allied fields

Supplemental networks of cowords of the paper Measuring the impact of Big Data in the scientific research in Agriculture and allied fields.

opencc-zeroJul 2023View details →

Sediment texture and nutrient data from: Bacterial assembly in agricultural streams

Agriculture is the most dominant land use globally and is projected to increase in the future to support a growing human population but also threatens ecosystem structure and services. Bacteria mediate numerous biogeochemical pathways within ecosystems. Therefore, identifying linkages between stressors associated with agricultural land use and responses of bacterial diversity is an important step in understanding and improving resource management. Here, we use the Mississippi Alluvial Plain (MAP) ecoregion, a highly modified agroecosystem, as a case study to better understand agriculturally-associated drivers of stream bacterial diversity and assembly mechanisms. In the MAP, we found that planktonic bacterial communities were strongly influenced by salinity. Tolerant taxa increased with increasing ion concentrations, likely driving homogenous selection which accounted for ~90% of assembly processes. Sediment bacterial phylogenetic diversity increased with increasing agricultural land use and was influenced by sediment particle size, with assembly mechanisms shifting from homogenous to variable selection as differences in median particle size increased. Within individual streams, sediment heterogeneity was correlated with bacterial diversity and a subsidy-stress relationship along the particle size gradient was observed. Planktonic and sediment communities within the same stream also diverged as sediment particle size decreased. Nutrients including carbon, nitrogen, and phosphorus, which tend to be elevated in agroecosystems, were also associated with detectable shifts in bacterial community structure. Collectively, our results establish that two understudied variables, salinity and sediment texture, are the primary drivers of bacterial diversity within the studied agroecosystem, while nutrients are secondary drivers. Although numerous macrobiological communities respond negatively, we observed increasing bacterial diversity in response to agricultural stressors including salinization and sedimentation. Elevated taxonomic and phylogenetic bacterial diversity likely increases the probability of detecting community responses to stressors. Thus, bacteria community responses may be more reliable for establishing water quality goals within highly modified agroecosystems that have experienced shifting baselines.

opencc-zeroJul 2023View details →

A secure future? Human urban and agricultural land use benefits a flightless island-endemic rail despite climate change

Identifying environmental characteristics that limit species' distributions is important for contemporary conservation and inferring responses to future environmental change. The Tasmanian native hen is an island-endemic flightless rail and a survivor of a prehistoric extirpation event. Little is known about the regional-scale environmental characteristics influencing the distribution of native hens, or how their future distribution might be impacted by environmental shifts (e.g., climate change). Using a combination of local fieldwork and species distribution modelling, we assess environmental factors shaping the contemporary distribution of the native hen, and project future distribution changes under predicted climate change. We find 37.2% of Tasmania is currently suitable for the native hens, owing to low summer precipitation, low elevation, human-modified vegetation, and urban areas. Moreover, in unsuitable regions, urban areas can create 'oases' of habitat, able to support populations with high breeding activity by providing resources and buffering against environmental constraints. Under climate change predictions, native hens were predicted to lose only 5% of their occupied range by 2055. We conclude that the species is resilient to climate change and benefits overall from anthropogenic landscape modifications. As such, this constitutes a rare example of a flightless rail to have adapted to human activity.

openother-openAug 2023View details →

Agriculture Futures and Climate Data Set

This is the second release. The agriculturefuturedata.mat includes the realized volatility series of corn, cotton, palm, wheat, and soybean futures. The climatedata.mat includes the average air pollution variables, weighted average air pollution variables, weighted average weather variables, attention to climate change variables, and attention to extreme weather variables.

opencc-zeroAug 2023View details →

Data from: The contributions of flower strips to wild bee conservation in agricultural landscapes can be predicted using pollinator habitat suitability models

Sowing flower strips along field edges is a widely adopted method for conserving pollinating insects in agricultural landscapes. To maximize the effect of flower strips given limited resources, we need spatially explicit tools that can prioritize their placement, and for identifying plant species to include in seed mixtures. We sampled bees and plant species as well as their interactions in a semi-controlled field experiment with roadside/field edge pairs with/without a sown flower strip at 31 sites in Norway and used a regional spatial model of solitary bee species richness to test if the effect of flower strips on bee species richness was predictable from the modelled solitary bee species richness. We found that sites with flower strips were more bee species rich compared to sites without flower strips and that this effect was greatest in areas that the regional solitary bee species richness model had identified to be particularly important for bees. Spatial models revealed that even within small landscapes there were pronounced differences between field edges in the predicted effect of sowing flower strips. Of the plant species that attracted the most bee species, the majority mainly attracted bumblebees and only few species also attracted solitary bees. Considering both the taxonomic diversity of bees and the species richness of bees attracted by plants we suggest that seed mixes containing Hieracium spp. such as Hieracium umbellatum and Pilosella officinarum; Taraxacum spp; Trifolium repens; Lotus corniculatus; Stellaria graminea; and Achillea millefolium would provide resources for diverse bee communities in our region. Spatial prediction models of bee diversity can be used to identify locations where flower strips are likely to have the largest effect and can thereby provide managers with an important tool for prioritizing how funding for agri-environmental schemes such as flower strips should be allocated. Such flower strips should contain plant species that are attractive to both solitary and bumblebees, and do not need to be particularly plant species rich as long as the selected plants complement each other.

opencc-by-4.0Sep 2023View details →

Data for article Agricultural input shocks affect crop yields more in the high-yielding areas of the world

This repository contains the agricultural input data of 12 crops used in the article analysis. The agricultural inputs used are (unit in parentheses): <ul> <li>nitrogen (kg/ha)</li> <li>phosphorus (kg/ha)</li> <li>potassium (kg/ha)</li> <li>machinery (1000 metric horsepower cv)</li> <li>herbicides (original kg/ha, for analysis rescaled by dividing with 97.5th percentile)</li> <li>fungicides (original kg/ha, for analysis rescaled by dividing with 97.5th percentile)</li> <li>insecticides (original kg/ha, for analysis rescaled by dividing with 97.5th percentile)</li> <li>other pesticides (original kg/ha, for analysis rescaled by dividing with 97.5th percentile)</li> <li>soil organic carbon (t/ha)</li> <li>soil phosphorus (mg/kg(</li> <li>soil nitrogen (t/ha)</li> <li>non-mineral nitrogen (kg/ha)</li> <li>non-mineral phosphorus (kg/ha)</li> <li>irrigation (% of area under irrigation)</li> <li>agricultural workers (persons)</li> </ul> This repository also includes the analysis results of yields after agricultural input shocks. This data is in rasters named e.g. wheat_phosphorus_shock_75.tif, meaning that this file contains the yield data (t/ha) for wheat after a 75% shock in phosphorus input. Rasters are provided for the following: <ul> <li>yields after 25%, 50% or 75% nitrogen shock</li> <li>yields after 25%, 50% or 75% phosphorus shock</li> <li>yields after 25%, 50% or 75% potassium shock</li> <li>yields after 25%, 50% or 75% machinery shock</li> <li>yields after 25%, 50% or 75% pesticide shock</li> <li>yields after 25%, 50% or 75% shock in all fertilizers (fertilizer shock)</li> <li>yields after 25%, 50% or 75% shock in all inputs</li> </ul> In addition, the observed crop yield (t/ha) used to construct the model is provided. Other yield rasters are: <ul> <li>modelled baseline yield (t/ha), used to calculate the yield changes in shock scenarios</li> <li>modelled zero input yield (t/ha), calculated as a scenario with zero fertilizers, machinery and pesticide inputs</li> </ul> Please see the article for references on the datasets.

opencc-by-4.0Sep 2023View details →

Pre-Aksumite and Aksumite agricultural economy at Ona Adi, Tigrai (Ethiopia): first look at a 1000-year history - Datasets

This repository contains the results datasets of the article Pre-Aksumite and Aksumite agricultural economy at Ona Adi, Tigrai (Ethiopia): first look at a 1000-year history submitted to the journal African Archaeological Review.

opencc-by-4.0Jul 2023View details →

Measurement Report: Exchange Fluxes of HONO over Agricultural Fields in the North China Plain

Raw data for Song et al. submitted to ACP.

Figure 8 in A Case Study of Wavelets and SVM Application in Coffee Agriculture: Detecting Cicadas Based on Their Acoustic and Image Patterns

Figure 8. Cross-oalidation algorithm.

Figure 6 in A Case Study of Wavelets and SVM Application in Coffee Agriculture: Detecting Cicadas Based on Their Acoustic and Image Patterns

Figure 6. The experimental setup for the proposed application two.

Figure 5 in A Case Study of Wavelets and SVM Application in Coffee Agriculture: Detecting Cicadas Based on Their Acoustic and Image Patterns

Figure 5. Examples of images used: high, low, and zero density, respectioely.

Figure 3 in A Case Study of Wavelets and SVM Application in Coffee Agriculture: Detecting Cicadas Based on Their Acoustic and Image Patterns

Figure 3. The experimental setup for the proposed application one.

opencc-zeroOct 2023View details →

Tillage agriculture and afforestation threaten tropical savanna plant communities across a broad rainfall gradient in India

The consequences of land-use change for savanna biodiversity remain undocumented in most regions of tropical Asia. One such region is western Maharashtra, India, where old-growth savannas occupy a broad rainfall gradient and are increasingly rare due to agricultural conversion and afforestation. To understand the consequences of land-use change, we sampled herbaceous plant communities of old-growth savannas and three alternative land-use types: tree plantations, tillage agriculture, and agricultural fallows (n=15 sites per type). Study sites spanned 457 to 1954 mm of mean annual precipitation—corresponding to the typical rainfall range of mesic savannas globally. Across the rainfall gradient, we found consistent declines in old-growth savanna plant communities due to land-use change. Local-scale native species richness dropped from a mean of 12 species/m2 in old-growth savannas to 8, 6, and 3 species/m2 in tree plantations, fallows, and tillage agriculture, respectively. Cover of native plants declined from a mean of 49% in old-growth savannas to 27% in both tree plantations and fallows, and 4% in tillage agriculture. Reductions in native cover coincided with increased cover of invasive species in tree plantations (18%), fallows (18%), and tillage agriculture (3%). In analyses of community composition, tillage agriculture was most dissimilar to old-growth savannas, while tree plantations and fallows showed intermediate dissimilarity. These compositional changes were driven partly by the loss of characteristic savanna species: 65 species recorded in old-growth savannas were absent in other land uses. Indicator analysis revealed 21 old-growth species, comprised mostly of native savanna specialists. Indicators of tree plantations (9 species) and fallows (13 species) were both invasive and native species, while the 2 indicators of tillage agriculture were invasive. As reflective of declines in savanna communities, mean native perennial graminoid cover of 27% in old-growth savannas dropped to 9%, 7%, and 0.1% in tree plantations, fallows, and tillage agriculture, respectively. Synthesis: Agricultural conversion and afforestation of old-growth savannas in India destroys and degrades herbaceous plant communities that do not spontaneously recover on fallowed land. Efforts to conserve India's native biodiversity should encompass the country's widespread savanna biome and seek to limit conversion of irreplaceable old-growth savannas.