scholarly journals Livin' on the edge: precision yield data shows evidence of ecosystem services from field boundaries.

2021 ◽  
Author(s):  
Samuel V. J. Robinson ◽  
Lan H. Nguyen ◽  
Paul Galpern
Keyword(s):  
Ecosystem Services ◽  
Crop Yield ◽  
Large Scale ◽  
Crop Yields ◽  
Spatial Scales ◽  
Beneficial Arthropods ◽  
Yield Data ◽  
Negative Edge ◽  
Field Boundaries ◽  
Monitor Data

Abstract Field boundaries can provide ecosystem services to crops by creating better abiotic conditions for crop growth, and can also act as habitat for beneficial arthropods. This suggests that crop boundaries may create an intermediate hump-shaped increase in crop yield, where negative edge effects are cancelled out by increased ecosystem services from the field boundary. However, there is little large-scale evidence showing this, largely because plot-scale crop yields are costly and time-consuming to measure. Precision yield data from combine yield monitors has huge potential in this respect, as the equipment is widespread and data is frequently recorded by growers. In this study, we used 252 field-years of yield monitor data from three common crops - wheat (Triticum aestivum), canola (Brassica napus), or peas (Pisum sativum) - recorded across Alberta, Canada, and examined how yield varied with distances from common crop boundary types. Average crop yield tended to increase with distance from crop boundaries before plateauing at about 50 m, and yield variation (SD) tended to decrease with distance. There was evidence of an intermediate increase in yield for wheat away from shelterbelts, and a weak increase in canola, but this was not seen for other crop types or boundary types. This study represents one of the first uses of precision yield data to measure ecosystem service provision at large spatial scales.

scholarly journals The impact of drought on the productivity of two rainfed crops in Spain

2019 ◽  
Author(s):  
Marina Peña-Gallardo ◽  
Sergio Martín Vicente-Serrano ◽  
Fernando Domínguez-Castro ◽  
Santiago Beguería
Keyword(s):  
Crop Yield ◽  
Crop Yields ◽  
Spatial Scales ◽  
Standardized Precipitation Index ◽  
Yield Response ◽  
Drought Indices ◽  
Economic Sectors ◽  
Yield Data ◽  
Agriculture Sector ◽  
The Impact

Abstract. Drought events are of great importance in most Mediterranean climate regions because of the diverse and costly impacts they have in various economic sectors and on the environment. The effects of this natural hazard on rainfed crops are particularly evident. In this study the impacts of drought on two representative rainfed crops in Spain (wheat and barley) were assessed. As the agriculture sector is vulnerable to climate, it is especially important to identify the most appropriate tools for monitoring the impact of the weather on crops, and particularly the impact of drought. Drought indices are the most effective tool for that purpose. Various drought indices have been used to assess the influence of drought on crop yields in Spain, including the standardized precipitation and evapotranspiration index (SPEI), the standardized precipitation index (SPI), the Palmer drought indices (PDSI, Z-Index, PHDI, PMDI), and the standardized Palmer drought index (SPDI). Two sets of crop yield data at different spatial scales and temporal periods were used in the analysis. The results showed that drought indices calculated at different time scales (SPI, SPEI) most closely correlated with crop yield. The results also suggested that different patterns of yield response to drought occurred depending on the region, period of the year, and the drought time scale. The differing responses across the country were related to season and the magnitude of various climate variables.

scholarly journals The impact of drought on the productivity of two rainfed crops in Spain

2019 ◽  
Vol 19 (6) ◽  
pp. 1215-1234 ◽  
Author(s):  
Marina Peña-Gallardo ◽  
Sergio Martín Vicente-Serrano ◽  
Fernando Domínguez-Castro ◽  
Santiago Beguería
Keyword(s):  
Crop Yield ◽  
Drought Index ◽  
Crop Yields ◽  
Spatial Scales ◽  
Standardized Precipitation Index ◽  
Yield Response ◽  
Drought Indices ◽  
Drought Severity ◽  
Yield Data ◽  
The Impact

Abstract. Drought events are of great importance in most Mediterranean climate regions because of the diverse and costly impacts they have in various economic sectors and on the environment. The effects of this natural hazard on rainfed crops are particularly evident. In this study the impacts of drought on two representative rainfed crops in Spain (wheat and barley) were assessed. As the agriculture sector is vulnerable to climate, it is especially important to identify the most appropriate tools for monitoring the impact of the weather on crops, and particularly the impact of drought. Drought indices are the most effective tool for that purpose. Various drought indices have been used to assess the influence of drought on crop yields in Spain, including the Standardized Precipitation Evapotranspiration Index (SPEI), the Standardized Precipitation Index (SPI), the Palmer drought indices (Palmer Drought Severity Index, PDSI; Palmer Z Index, Z Index; Palmer Hydrological Drought Index, PHDI; Palmer Modified Drought Index, PMDI), and the Standardized Palmer Drought Index (SPDI). Two sets of crop yield data at different spatial scales and temporal periods were used in the analysis. The results showed that drought indices calculated at different timescales (SPI, SPEI) most closely correlated with crop yield. The results also suggested that different patterns of yield response to drought occurred depending on the region, period of the year, and the drought timescale. The differing responses across the country were related to season and the magnitude of various climate variables.

scholarly journals The Use of Crop Yield Autocorrelation Data as a Sustainable Approach to Adjust Agronomic Inputs

2021 ◽  
Vol 13 (4) ◽  
pp. 2362
Author(s):  
Thomas M. Koutsos ◽  
Georgios C. Menexes ◽  
Andreas P. Mamolos
Keyword(s):  
Decision Making ◽  
Spatial Analysis ◽  
Crop Yield ◽  
Spatial Autocorrelation Analysis ◽  
Autocorrelation Analysis ◽  
Yield Data ◽  
Site Specific ◽  
Production Areas ◽  
Short Time ◽  
Monitor Data

Agricultural fields have natural within-field soil variations that can be extensive, are usually contiguous, and are not always traceable. As a result, in many cases, site-specific attention is required to adjust inputs and optimize crop performance. Researchers, such as agronomists, agricultural engineers, or economists and other scientists, have shown increased interest in performing yield monitor data analysis to improve farmers’ decision-making concerning the better management of the agronomic inputs in the fields, while following a much more sustainable approach. In this case, spatial analysis of crop yield data with the form of spatial autocorrelation analysis can be used as a practical sustainable approach to locate statistically significant low-production areas. The resulted insights can be used as prescription maps on the tractors to reduce overall inputs and farming costs. This aim of this work is to present the benefits of conducting spatial analysis of yield crop data as a sustainable approach. Current work proves that the implementation of this process is costless, easy to perform and provides a better understanding of the current agronomic needs for better decision-making within a short time, adopting a sustainable approach.

scholarly journals Geostatistical analysis of crop yield maps in a long term no tillage system

Bragantia ◽  
2010 ◽  
Vol 69 (suppl) ◽  
pp. 9-18 ◽  
Author(s):  
Osvaldo Guedes Filho ◽  
Sidney Rosa Vieira ◽  
Marcio Koiti Chiba ◽  
Célia Regina Grego
Keyword(s):  
Crop Yield ◽  
Crop Yields ◽  
Spherical Model ◽  
Exponential Model ◽  
Spatial And Temporal Variability ◽  
No Tillage ◽  
Yield Data ◽  
The North ◽  
Tillage System

It is known, for a long time, that crop yields are not uniform at the field. In some places, it is possible to distinguish sites with both low and high yields even within the same area. This work aimed to evaluate the spatial and temporal variability of some crop yields and to identify potential zones for site specific management in an area under no-tillage system for 23 years. Data were analyzed from a 3.42 ha long term experimental area at the Centro Experimental Central of the Instituto Agronômico, located in Campinas, Sao Paulo State, Brazil. The crop yield data evaluated included the following crops: soybean, maize, lablab and triticale, and all of them were cultivated since 1985 and sampled at a regular grid of 302 points. Data were normalized and analyzed using descriptive statistics and geostatistical tools in order to demonstrate and describe the structure of the spatial variability. All crop yields showed high variability. All of them also showed spatial dependence and were fitted to the spherical model, except for the yield of the maize in 1999 productivity which was fitted to the exponential model. The north part of the area presented repeated high values of productivity in some years. There was a positive cross correlation amongst the productivity values, especially for the maize crops.

scholarly journals A multi-model analysis of teleconnected crop yield variability in a range of cropping systems

2019 ◽  
Author(s):  
Matias Heino ◽  
Joseph H. A. Guillaume ◽  
Christoph Müller ◽  
Toshichika Iizumi ◽  
Matti Kummu
Keyword(s):  
Crop Yield ◽  
Crop Production ◽  
Food System ◽  
Crop Yields ◽  
Southern Oscillation ◽  
Yield Variability ◽  
Management Scenarios ◽  
Yield Data ◽  
Climate Oscillations ◽  
Crop Models

Abstract. Climate oscillations are periodically fluctuating oceanic and atmospheric phenomena, which are related to variations in weather patterns and crop yields worldwide. In terms of crop production, the most widespread impacts have been observed for the El Niño Southern Oscillation (ENSO), which has been found to impact crop yields in all continents that produce crops, while two other climate oscillations – the Indian Ocean Dipole (IOD) and the North Atlantic Oscillation (NAO) – have been shown to impact crop production especially in Australia and Europe, respectively. In this study, we analyse the impacts of ENSO, IOD and NAO on the growing conditions of maize, rice, soybean and wheat at the global scale, by utilizing crop yield data from an ensemble of global gridded crop models simulated for a range of crop management scenarios. Our results show that simulated crop yield variability is correlated to climate oscillations to a wide extent (up to almost half of all maize and wheat harvested areas for ENSO) and in several important crop producing areas, e.g. in North America (ENSO, wheat), Australia (IOD & ENSO, wheat) and northern South America (ENSO, soybean). Further, our analyses show that higher sensitivity to these oscillations can be observed for rainfed, and fully fertilized scenarios, while the sensitivity tends to be lower if crops are fully irrigated. Since, the development of ENSO, IOD and NAO can be reliably forecasted in advance, a better understanding about the relationship between crop production and these climate oscillations can improve the resilience of the global food system to climate related shocks.

scholarly journals Differential effects of soil-based agricultural diversification on arthropods and crop yield

2021 ◽  
Author(s):  
Elinor M. Lichtenberg ◽  
Ivan Milosavljević ◽  
Alistair J. Campbell ◽  
David Crowder
Keyword(s):  
Ecosystem Services ◽  
Functional Groups ◽  
Crop Yield ◽  
Crop Yields ◽  
Service Providers ◽  
Habitat Diversity ◽  
Landscape Scale ◽  
Policy Implications ◽  
No Tillage ◽  
Agricultural Diversification

Agricultural diversification often promotes biodiversity and ecosystem services by increasing habitat diversity. However, responses to agricultural diversification are context dependent, differentially impacting functional groups of service-providing organisms and crop yields. Conservation and no tillage are promoted as agricultural diversification practices that increase soil heterogeneity and habitat diversity. Here we investigated whether soil tillage practices in canola crop fields altered arthropod biodiversity or yield, and how effects of field-scale diversification compared to landscape-scale habitat context. We focused on effects of high, medium, or no tillage on five functional groups with unique diets and reproductive strategies: (i) herbivores, (ii) kleptoparasites, (iii) parasitoids, (iv) pollinators, and (v) predators. Effects of agricultural diversification on arthropod abundance and diversity varied across functional groups. Pollinators responded to on-farm soil diversification, benefiting from medium tillage. Predators and herbivores responded most strongly to landscape-scale habitat composition and were more abundant in landscapes with more semi-natural habitat. However, variation in arthropod communities had little effect on canola crop yield, which was lowest in fields with no tillage. Policy implications: Our results indicate that natural history differences among arthropod functional groups mediate how habitat availability affects biodiversity. Crop yields, however, showed no response to biodiversity of ecosystem service providers. Our research highlights the need to determine the contexts in which soil diversification practices meet a multi-faceted goal of simultaneously supporting natural biodiversity, ecosystem services, and crop yield.

scholarly journals Agricultural Beneficial Management Practices: A Synthesis of Co-benefits, Tradeoffs, and Co-costs between Crop Yield and Non-provisioning Ecosystem Services

2020 ◽  
Author(s):  
Andrew Nicholas Kadykalo ◽  
Kris Johnson ◽  
Scott McFatridge ◽  
C. Scott Findlay
Keyword(s):  
Ecosystem Services ◽  
Crop Yield ◽  
Cover Crops ◽  
Management Practices ◽  
Crop Yields ◽  
Crop Rotations ◽  
Agricultural Crop ◽  
Beneficial Management Practices ◽  
Provisioning Ecosystem Services ◽  
The Impact

Although agricultural “best (or beneficial) management practices” (BMPs) first emerged to mitigate agro-environmental resource challenges, they may also enhance ‘non-provisioning’ ecosystem services. The enthusiasm for adopting BMPs partially depends on evidence that doing so will lead to agro-environmental benefits while not substantially reducing crop productivity or farmer income. We survey and synthesize evidence in the existing literature to document the joint effects on agricultural crop yield and 12 ecosystem service (ES) associated with implementation of 5 agricultural BMPs (crop rotations, cover crops, nutrient management, perennial vegetated buffers, reduced or no tillage). We also analyze the prevalence of co-benefits (‘win-win’), tradeoffs, and co-costs (‘lose-lose’) outcomes. On the basis of a set of contextual variables we then develop empirical models that predict the likelihood of co-benefits relative to tradeoffs, and co-costs. We found thirty-six studies investigating 141 combinations of crop yields and non-provisioning ES outcomes (YESs) in the relevant literatures covering the period 1983-2016. The scope of the review is global, but included studies are geographically concentrated in the U.S. Corn Belt (Midwestern United States). In the literature sample, reporting of co-benefits (26%) was much more prevalent than reporting of co-costs (4%) between yields and ES. Tradeoffs most often resulted in a reduction in crop yields and an increase in ES (28%); this was marginally greater than studies reporting a neutral influence on crop yields and an increase in ES (26%). Other Y/ES combinations were uncommon. Mixed-effects models indicated reduced tillage and crop rotations had generally positive associations with YESs. Temporal scale was an informative predictor suggesting studies with longer time scales resulted in greater positive outcomes on YESs, on average. Our results are a step towards identifying those contexts where co-benefits or partial improvement outcomes of BMPs are more likely to be realized, as well as the impact of particular practices on specific ES.

scholarly journals Maximizing Ecosystem Services Provided to the New Oil Crop Brassica carinata Through Landscape and Arthropod Diversity

2019 ◽  
Author(s):  
Shane Stiles ◽  
Jon Lundgren ◽  
Charles Fenster ◽  
Henning Nottebrock
Keyword(s):  
Ecosystem Services ◽  
Crop Yield ◽  
Seed Treatment ◽  
Large Scale ◽  
Positive Relationship ◽  
Landscape Heterogeneity ◽  
Insect Diversity ◽  
Farming Practices ◽  
Pollinator Diversity ◽  
The Relationship

ABSTRACTPrairies, once spanning the Upper Midwest, have now largely been replaced by agriculture. The lack of resources available to pollinators in agricultural fields and practices commonly employed has led to a decline in insect diversity. To enhance sustainable practices, we must better understand how ecosystem services such as pest control and pollination services provided by a diverse insect and pollinator community scale to current farming practices as related to crop yield and how landscape features may positively contribute to insect and pollinator diversity. We examined how landscape heterogeneity relates to insect and pollinator diversity, as well as how insect and pollinator diversity relates to crop yield across common farming practices. We planted 35 single acre sites of Brassica carinata, a generalist flower possibly capable of supporting a diverse insect community. We randomly assigned each site with a combination of three common farming practices: tilling (yes/no), added honey bee hives (yes/no), and treatment with systemic neonicotinoids (yes/no). Insect and pollinator diversity and the surrounding landscape at multiple spatial scales were calculated. We observed a significant positive relationship between insect (and pollinator) diversity with yield in the absence of any farming practice. All farming practices will increase yield. However, farming practices alter the relationship between yield and diversity. The addition of seed treatment or tillage negates the relationship between insect (and pollinator) diversity with yield. Seed treatment alone results in a flat relationship between diversity and yield for all insects and a negative relationship for pollinators. Increased landscape heterogeneity results in a positive relationship between insect diversity at the 1000 m scale and pollinator diversity at the 3000 m scale, suggesting large-scale heterogeneity contributes to overall insect diversity. Our results show that increasing large-scale landscape heterogeneity increases diversity serving as a substitute for common farming practices such as application of pesticides, tilling, or bee hives. Increased heterogeneity could save farmers from the input cost of treatment or tillage, by way of increased insect diversity, while still providing similar yields.

scholarly journals Novel Approach for Forecasting Sugarcane Crop Yield: A Real-Time Prediction

2021 ◽  
Vol 11 (3) ◽  
Author(s):  
Ankit Kumar ◽  
Anil Kumar Kapil
Keyword(s):  
Data Mining ◽  
Crop Yield ◽  
Crop Yields ◽  
Yield Data ◽  
Sugarcane Crop ◽  
Use Of Data ◽  
Novel Approach ◽  
Technological Advances ◽  
Plant Area ◽  
Cultivation Technique

Agriculture is an environment in which there is considerable confusion. Crop development depends largely on several variables, including climate, temperature, genetics, politics and economics. In addition, a huge number of raw agriculture statistics are available, but study of those details for estimating crop yield is quite challenging. The most challenging job is therefore to include accurate details and awareness about the raw farm data. In order to evaluate cultivation yield, data mining could customize data expertise. The objective of this study was to predict crop yields through the use of data mining technological advances. Moreover, this paper compared various classification algorithms and it is expected that the results of the study may enhance the actual yields of sugarcane in a wide number of tropical fields. The specifications used in the forecast were plot (soil size, plant area, rain distance, previous year's plant yield), sugar-cane characteristics (cane class and sort), crop cultivation procedure (normal water resource size, cultivation technique, disease management process, sort / procedure of fertilizer) as well as rain quantity.

Climate change impacts on crop water productivity in Africa using a multi-model inter-comparison

2020 ◽  
Author(s):  
Imeshi Weerasinghe ◽  
Celray James Chawanda ◽  
Ann van Griensven
Keyword(s):  
Climate Change ◽  
Crop Yield ◽  
Crop Yields ◽  
Water Productivity ◽  
Baseline Scenario ◽  
Crop Water ◽  
Yield Data ◽  
Water Vapour Flux ◽  
Crop Models ◽  
Crop Water Productivity

<p>Evapotranspiration (ET) or the water vapour flux is an important component in the water cycle and is widely studied due to its implications in disciplines ranging from hydrology to agricultural and climate sciences. In the recent past, growing attention has been given to estimating ET fluxes at regional and global scales. However, estimation of ET at large scales has been a difficult task due to direct measurement of ET being possible only at point locations, for example using flux towers. For the African continent, only a limited number of flux tower data are openly available for use, which makes verification of regional and global ET products very difficult. Recent advances in satellite based products provide promising data to fill these observational gaps.</p><p>In this study we propose to investigate the Climate Change (CC) impact on crop water productivity across Africa using ET and crop yield predictions of different crop models for future climate scenarios. Different model outputs are evaluated including models from both the ISI-MIP 2a and 2b protocols. Considering the problem of direct observations of ET being difficult to obtain, especially over Africa, we use ET estimates from several remotely sensed derived products as a references to evaluate the crop models (maize) in terms of magnitude, spatial patterns and variations between models. The crop model results for crop yield are compared to FAO reported crop yields at country scale. The results show a very strong disagreement between the different crop models of the baseline scenario and when compared with ET and crop yield data.  Also, a very large uncertainty is obtained for the climate change predictions. It is hence recommended to improve the crop models for application in Africa.</p>

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