Evaluating the mitigation of greenhouse gas emissions and adaptation in dairy production.

USDA-ARS?s Scientific Manuscript database

Process-level modeling at the farm scale provides a tool for evaluating strategies for both mitigating greenhouse gas emissions and adapting to climate change. The Integrated Farm System Model (IFSM) simulates representative crop, beef or dairy farms over many years of weather to predict performance...

Simulating the Distribution of Individual Livestock Farms and Their Populations in the United States: An Example Using Domestic Swine (Sus scrofa domesticus) Farms

PubMed Central

Garza, Sarah J.; Miller, Ryan S.

2015-01-01

Livestock distribution in the United States (U.S.) can only be mapped at a county-level or worse resolution. We developed a spatial microsimulation model called the Farm Location and Agricultural Production Simulator (FLAPS) that simulated the distribution and populations of individual livestock farms throughout the conterminous U.S. Using domestic pigs (Sus scrofa domesticus) as an example species, we customized iterative proportional-fitting algorithms for the hierarchical structure of the U.S. Census of Agriculture and imputed unpublished state- or county-level livestock population totals that were redacted to ensure confidentiality. We used a weighted sampling design to collect data on the presence and absence of farms and used them to develop a national-scale distribution model that predicted the distribution of individual farms at a 100 m resolution. We implemented microsimulation algorithms that simulated the populations and locations of individual farms using output from our imputed Census of Agriculture dataset and distribution model. Approximately 19% of county-level pig population totals were unpublished in the 2012 Census of Agriculture and needed to be imputed. Using aerial photography, we confirmed the presence or absence of livestock farms at 10,238 locations and found livestock farms were correlated with open areas, cropland, and roads, and also areas with cooler temperatures and gentler topography. The distribution of swine farms was highly variable, but cross-validation of our distribution model produced an area under the receiver-operating characteristics curve value of 0.78, which indicated good predictive performance. Verification analyses showed FLAPS accurately imputed and simulated Census of Agriculture data based on absolute percent difference values of < 0.01% at the state-to-national scale, 3.26% for the county-to-state scale, and 0.03% for the individual farm-to-county scale. Our output data have many applications for risk management of agricultural systems including epidemiological studies, food safety, biosecurity issues, emergency-response planning, and conflicts between livestock and other natural resources. PMID:26571497

Simulating the Distribution of Individual Livestock Farms and Their Populations in the United States: An Example Using Domestic Swine (Sus scrofa domesticus) Farms.

PubMed

Burdett, Christopher L; Kraus, Brian R; Garza, Sarah J; Miller, Ryan S; Bjork, Kathe E

2015-01-01

Livestock distribution in the United States (U.S.) can only be mapped at a county-level or worse resolution. We developed a spatial microsimulation model called the Farm Location and Agricultural Production Simulator (FLAPS) that simulated the distribution and populations of individual livestock farms throughout the conterminous U.S. Using domestic pigs (Sus scrofa domesticus) as an example species, we customized iterative proportional-fitting algorithms for the hierarchical structure of the U.S. Census of Agriculture and imputed unpublished state- or county-level livestock population totals that were redacted to ensure confidentiality. We used a weighted sampling design to collect data on the presence and absence of farms and used them to develop a national-scale distribution model that predicted the distribution of individual farms at a 100 m resolution. We implemented microsimulation algorithms that simulated the populations and locations of individual farms using output from our imputed Census of Agriculture dataset and distribution model. Approximately 19% of county-level pig population totals were unpublished in the 2012 Census of Agriculture and needed to be imputed. Using aerial photography, we confirmed the presence or absence of livestock farms at 10,238 locations and found livestock farms were correlated with open areas, cropland, and roads, and also areas with cooler temperatures and gentler topography. The distribution of swine farms was highly variable, but cross-validation of our distribution model produced an area under the receiver-operating characteristics curve value of 0.78, which indicated good predictive performance. Verification analyses showed FLAPS accurately imputed and simulated Census of Agriculture data based on absolute percent difference values of < 0.01% at the state-to-national scale, 3.26% for the county-to-state scale, and 0.03% for the individual farm-to-county scale. Our output data have many applications for risk management of agricultural systems including epidemiological studies, food safety, biosecurity issues, emergency-response planning, and conflicts between livestock and other natural resources.

Measurement of unsteady loading and power output variability in a micro wind farm model in a wind tunnel

NASA Astrophysics Data System (ADS)

Bossuyt, Juliaan; Howland, Michael F.; Meneveau, Charles; Meyers, Johan

2017-01-01

Unsteady loading and spatiotemporal characteristics of power output are measured in a wind tunnel experiment of a microscale wind farm model with 100 porous disk models. The model wind farm is placed in a scaled turbulent boundary layer, and six different layouts, varied from aligned to staggered, are considered. The measurements are done by making use of a specially designed small-scale porous disk model, instrumented with strain gages. The frequency response of the measurements goes up to the natural frequency of the model, which corresponds to a reduced frequency of 0.6 when normalized by the diameter and the mean hub height velocity. The equivalent range of timescales, scaled to field-scale values, is 15 s and longer. The accuracy and limitations of the acquisition technique are documented and verified with hot-wire measurements. The spatiotemporal measurement capabilities of the experimental setup are used to study the cross-correlation in the power output of various porous disk models of wind turbines. A significant correlation is confirmed between streamwise aligned models, while staggered models show an anti-correlation.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Na, Ji Sung; Koo, Eunmo; Munoz-Esparza, Domingo

High-resolution large-eddy simulation of the flow over a large wind farm (64 wind turbines) is performed using the HIGRAD/FIRETEC-WindBlade model, which is a high-performance computing wind turbine–atmosphere interaction model that uses the Lagrangian actuator line method to represent rotating turbine blades. These high-resolution large-eddy simulation results are used to parameterize the thrust and power coefficients that contain information about turbine interference effects within the wind farm. Those coefficients are then incorporated into the WRF (Weather Research and Forecasting) model in order to evaluate interference effects in larger-scale models. In the high-resolution WindBlade wind farm simulation, insufficient distance between turbines createsmore » the interference between turbines, including significant vertical variations in momentum and turbulent intensity. The characteristics of the wake are further investigated by analyzing the distribution of the vorticity and turbulent intensity. Quadrant analysis in the turbine and post-turbine areas reveals that the ejection motion induced by the presence of the wind turbines is dominant compared to that in the other quadrants, indicating that the sweep motion is increased at the location where strong wake recovery occurs. Regional-scale WRF simulations reveal that although the turbulent mixing induced by the wind farm is partly diffused to the upper region, there is no significant change in the boundary layer depth. The velocity deficit does not appear to be very sensitive to the local distribution of turbine coefficients. However, differences of about 5% on parameterized turbulent kinetic energy were found depending on the turbine coefficient distribution. Furthermore, turbine coefficients that consider interference in the wind farm should be used in wind farm parameterization for larger-scale models to better describe sub-grid scale turbulent processes.« less

Modelling potential production of macroalgae farms in UK and Dutch coastal waters

NASA Astrophysics Data System (ADS)

van der Molen, Johan; Ruardij, Piet; Mooney, Karen; Kerrison, Philip; O'Connor, Nessa E.; Gorman, Emma; Timmermans, Klaas; Wright, Serena; Kelly, Maeve; Hughes, Adam D.; Capuzzo, Elisa

2018-02-01

There is increasing interest in macroalgae farming in European waters for a range of applications, including food, chemical extraction for biofuel production. This study uses a 3-D numerical model of hydrodynamics and biogeochemistry to investigate potential production and environmental effects of macroalgae farming in UK and Dutch coastal waters. The model included four experimental farms in different coastal settings in Strangford Lough (Northern Ireland), in Sound of Kerrera and Lynn of Lorne (north-west Scotland) and in the Rhine plume (the Netherlands), as well as a hypothetical large-scale farm off the UK north Norfolk coast. The model could not detect significant changes in biogeochemistry and plankton dynamics at any of the farm sites averaged over the farming season. The results showed a range of macroalgae growth behaviours in response to simulated environmental conditions. These were then compared with in situ observations where available, showing good correspondence for some farms and less good correspondence for others. At the most basic level, macroalgae production depended on prevailing nutrient concentrations and light conditions, with higher levels of both resulting in higher macroalgae production. It is shown that under non-elevated and interannually varying winter nutrient conditions, farming success was modulated by the timings of the onset of increasing nutrient concentrations in autumn and nutrient drawdown in spring. Macroalgae carbohydrate content also depended on nutrient concentrations, with higher nutrient concentrations leading to lower carbohydrate content at harvest. This will reduce the energy density of the crop and thus affect its suitability for conversion into biofuel. For the hypothetical large-scale macroalgae farm off the UK north Norfolk coast, the model suggested high, stable farm yields of macroalgae from year to year with substantial carbohydrate content and limited environmental effects.

The Interactive Effect of Diversification and Farming Scale on Productivity of Family Farm:Taking Rice Cultivation as An Example

NASA Astrophysics Data System (ADS)

Wei, Zhou

2017-05-01

Based on the diversification and cultivation scale, the rice cropping data of rural fixed observation points in 2011 were selected and the effect of diversification degree on rice productivity was analyzed by the Tobit model. The empirical results of the model show that diversification of sample farm will lead to loss of rice production efficiency. With the increase of rice planting scale, the loss of rice production efficiency will need to be further increased by diversification. Thus, we should stick to the family farm of specialized production operation. The transfer of land, the price and quantity of leasing, respecting the law of the market; the raising of funds can be considered non-subsidized capital market financing to help, while maintaining a certain degree of diversification, to avoid idle assets, low resource efficiency loss.

Factors associated with farm-level infection of porcine epidemic diarrhea during the early phase of the epidemic in Japan in 2013 and 2014.

PubMed

Toyomaki, Haruya; Sekiguchi, Satoshi; Sasaki, Yosuke; Sueyoshi, Masuo; Makita, Kohei

2018-02-01

The objective of this study was to investigate factors that caused rapid spread during the early phase of the porcine epidemic diarrhea (PED) epidemic in Japan in 2013 and 2014. Anonymized datasets from all pig farms were provided by Kagoshima (709 farms) and Miyazaki Prefectures (506 farms). Semi-parametric survival analysis was conducted using the first 180 days from the first case on December 3, 2013 in Kagoshima Prefecture. To compare the hazard between different farm management types, univariable survival analysis was conducted. As farm sizes varied among different farm types, bivariable survival analysis was conducted for farm size categories and farm density per km 2 for each management type. A case-control study using a postal questionnaire survey was conducted in September 2014, and risk factor analysis was performed using generalized linear models with binomial errors. The hazard was significantly higher in farrow-to-finish farms than fattening farms [hazard ratio (HR) = 1.6, p < 0.01], but was not significantly different between reproduction and fattening farms (HR = 1.3, p = 0.16). In separate bivariable survival analyses for each farm type, large- and middle-scale farms had higher hazard than small-scale farms in fattening (HR = 5.8 and 2.6, respectively, both p < 0.01) and reproduction farms (HR = 4.0 and 3.6, respectively, both p < 0.01). In farrow-to-finish farms, large-scale farms had higher hazard than small-scale farms (HR = 2.8, p < 0.01), and higher farm density per km 2 was also a risk factor (HR = 7.6, p < 0.01). In the case-control study, questionnaires were returned from 78 PED virus-infected and 91 non-infected farms. The overall response rate was 34%. Risk factors of the final model were occurrence of porcine reproductive and respiratory syndrome in the past 5 years [odds ratio (OR) = 1.97, 95% confidence interval (CI): 0.97-4.00, p = 0.054], use of a common compost station (OR = 2.51, 95%CI: 1.08-5.83, p = 0.03), and use of a pig excrement disposal service (OR = 2.64, 95%CI: 1.05-6.63, p = 0.04). High hazard in farrow-to-finish farms suggested transmission from slaughterhouses to susceptible suckling piglets. Hazard associated with large-scale farms and high density might be due to frequent vehicle entrance and transmission by roads. Improvement of farm hygiene management and avoidance of risky practices associated with contact with pig excrement were keys in preventing invasion of PED virus to a farm. Copyright © 2017 Elsevier B.V. All rights reserved.

Experimental study of the impact of large-scale wind farms on land-atmosphere exchanges

NASA Astrophysics Data System (ADS)

Zhang, wei; Markfort, Corey; Porté-Agel, Fernando

2013-04-01

Wind energy is one of the fastest growing sources of renewable energy world-wide, and it is expected that many more large-scale wind farms will be built and cover a significant portion of land and ocean surfaces. By extracting kinetic energy from the atmospheric boundary layer and converting it to electricity, wind farms may affect the transport of momentum, heat, moisture and trace gases (e.g. CO2) between the atmosphere and the land surface locally and globally. Understanding wind farm-atmosphere interactions and subsequent environmental impacts are complicated by the effects of turbine array configuration, wind farm size, land-surface characteristics and atmospheric thermal stability. In particular, surface scalar flux is influenced by wind farms and needs to be appropriately parameterized in meso-scale and/or high-resolution numerical models. Wind-tunnel experiments of model wind farms with perfectly aligned and staggered configurations, having the same turbine distribution density, were conducted in a neutral turbulent boundary layer with a surface heat source. Turbulent flow and fluxes over and through the wind farm were measured using a custom x-wire/cold-wire anemometer; and surface scalar flux was measured with an array of surface-mounted heat flux sensors within the quasi-developed flow regime. Although the overall surface heat flux change produced by the wind farms was found to be small, with a net reduction of 4% for the staggered wind farm and nearly zero for the aligned wind farm, the highly heterogeneous spatial distribution of the surface heat flux, dependent on wind farm layout, is significant. The difference between the minimum and maximum surface heat fluxes could be up to 12% and 7% in aligned and staggered wind farms, respectively. This finding is important for planning intensive agriculture practices and optimizing agricultural land use with regard to wind energy project development. The well-controlled wind-tunnel experiments presented here also provide a first comprehensive dataset on turbulent flow and scalar transport in wind farms, which can be further used to develop and validate new parameterizations for surface scalar fluxes in numerical models.

Whole-farm models to quantify greenhouse gas emissions and their potential use for linking climate change mitigation and adaptation in temperate grassland ruminant-based farming systems.

PubMed

Del Prado, A; Crosson, P; Olesen, J E; Rotz, C A

2013-06-01

The farm level is the most appropriate scale for evaluating options for mitigating greenhouse gas (GHG) emissions, because the farm represents the unit at which management decisions in livestock production are made. To date, a number of whole farm modelling approaches have been developed to quantify GHG emissions and explore climate change mitigation strategies for livestock systems. This paper analyses the limitations and strengths of the different existing approaches for modelling GHG mitigation by considering basic model structures, approaches for simulating GHG emissions from various farm components and the sensitivity of GHG outputs and mitigation measures to different approaches. Potential challenges for linking existing models with the simulation of impacts and adaptation measures under climate change are explored along with a brief discussion of the effects on other ecosystem services.

Studies of Sub-Synchronous Oscillations in Large-Scale Wind Farm Integrated System

NASA Astrophysics Data System (ADS)

Yue, Liu; Hang, Mend

2018-01-01

With the rapid development and construction of large-scale wind farms and grid-connected operation, the series compensation wind power AC transmission is gradually becoming the main way of power usage and improvement of wind power availability and grid stability, but the integration of wind farm will change the SSO (Sub-Synchronous oscillation) damping characteristics of synchronous generator system. Regarding the above SSO problem caused by integration of large-scale wind farms, this paper focusing on doubly fed induction generator (DFIG) based wind farms, aim to summarize the SSO mechanism in large-scale wind power integrated system with series compensation, which can be classified as three types: sub-synchronous control interaction (SSCI), sub-synchronous torsional interaction (SSTI), sub-synchronous resonance (SSR). Then, SSO modelling and analysis methods are categorized and compared by its applicable areas. Furthermore, this paper summarizes the suppression measures of actual SSO projects based on different control objectives. Finally, the research prospect on this field is explored.

Farms, Families, and Markets: New Evidence on Completeness of Markets in Agricultural Settings

PubMed Central

LaFave, Daniel; Thomas, Duncan

2016-01-01

The farm household model has played a central role in improving the understanding of small-scale agricultural households and non-farm enterprises. Under the assumptions that all current and future markets exist and that farmers treat all prices as given, the model simplifies households’ simultaneous production and consumption decisions into a recursive form in which production can be treated as independent of preferences of household members. These assumptions, which are the foundation of a large literature in labor and development, have been tested and not rejected in several important studies including Benjamin (1992). Using multiple waves of longitudinal survey data from Central Java, Indonesia, this paper tests a key prediction of the recursive model: demand for farm labor is unrelated to the demographic composition of the farm household. The prediction is unambiguously rejected. The rejection cannot be explained by contamination due to unobserved heterogeneity that is fixed at the farm level, local area shocks or farm-specific shocks that affect changes in household composition and farm labor demand. We conclude that the recursive form of the farm household model is not consistent with the data. Developing empirically tractable models of farm households when markets are incomplete remains an important challenge. PMID:27688430

Farms, pastures and woodlands: the fine-scale distribution of Palearctic Culicoides spp. biting midges along an agro-ecological gradient.

PubMed

Rigot, T; Drubbel, M Vercauteren; Delécolle, J-C; Gilbert, M

2013-03-01

The spatial epidemiology of Bluetongue virus (BTV) at the landscape level relates to the fine-scale distribution and dispersal capacities of its vectors, midges belonging to the genus Culicoides Latreille (Diptera: Ceratopogonidae). Although many previous researches have carried out Culicoides sampling on farms, little is known of the fine-scale distribution of Culicoides in the landscape immediately surrounding farms. The aim of this study was to gain a better understanding of Culicoides populations at increasing distances from typical dairy farms in north-west Europe, through the use of eight Onderstepoort-type black-light traps positioned along linear transects departing from farms, going through pastures and entering woodlands. A total of 16 902 Culicoides were collected in autumn 2008 and spring 2009. The majority were females, of which more than 97% were recognized as potential vectors. In pastures, we found decreasing numbers of female Culicoides as a function of the distance to the farm. This pattern was modelled by leptokurtic models, with parameters depending on season and species. By contrast, the low number of male Culicoides caught were homogeneously distributed along the transects. When transects entered woodlands, we found a higher abundance of Culicoides than expected considering the distance of the sampling sites to the farm, although this varied according to species. © 2012 The Authors. Medical and Veterinary Entomology © 2012 The Royal Entomological Society.

Turbulence and entrainment length scales in large wind farms.

PubMed

Andersen, Søren J; Sørensen, Jens N; Mikkelsen, Robert F

2017-04-13

A number of large wind farms are modelled using large eddy simulations to elucidate the entrainment process. A reference simulation without turbines and three farm simulations with different degrees of imposed atmospheric turbulence are presented. The entrainment process is assessed using proper orthogonal decomposition, which is employed to detect the largest and most energetic coherent turbulent structures. The dominant length scales responsible for the entrainment process are shown to grow further into the wind farm, but to be limited in extent by the streamwise turbine spacing, which could be taken into account when developing farm layouts. The self-organized motion or large coherent structures also yield high correlations between the power productions of consecutive turbines, which can be exploited through dynamic farm control.This article is part of the themed issue 'Wind energy in complex terrains'. © 2017 The Author(s).

Turbulence and entrainment length scales in large wind farms

PubMed Central

2017-01-01

A number of large wind farms are modelled using large eddy simulations to elucidate the entrainment process. A reference simulation without turbines and three farm simulations with different degrees of imposed atmospheric turbulence are presented. The entrainment process is assessed using proper orthogonal decomposition, which is employed to detect the largest and most energetic coherent turbulent structures. The dominant length scales responsible for the entrainment process are shown to grow further into the wind farm, but to be limited in extent by the streamwise turbine spacing, which could be taken into account when developing farm layouts. The self-organized motion or large coherent structures also yield high correlations between the power productions of consecutive turbines, which can be exploited through dynamic farm control. This article is part of the themed issue ‘Wind energy in complex terrains’. PMID:28265028

The Relationship of Dairy Farm Eco-Efficiency with Intensification and Self-Sufficiency. Evidence from the French Dairy Sector Using Life Cycle Analysis, Data Envelopment Analysis and Partial Least Squares Structural Equation Modelling.

PubMed

Soteriades, Andreas Diomedes; Stott, Alistair William; Moreau, Sindy; Charroin, Thierry; Blanchard, Melanie; Liu, Jiayi; Faverdin, Philippe

2016-01-01

We aimed at quantifying the extent to which agricultural management practices linked to animal production and land use affect environmental outcomes at a larger scale. Two practices closely linked to farm environmental performance at a larger scale are farming intensity, often resulting in greater off-farm environmental impacts (land, non-renewable energy use etc.) associated with the production of imported inputs (e.g. concentrates, fertilizer); and the degree of self-sufficiency, i.e. the farm's capacity to produce goods from its own resources, with higher control over nutrient recycling and thus minimization of losses to the environment, often resulting in greater on-farm impacts (eutrophication, acidification etc.). We explored the relationship of these practices with farm environmental performance for 185 French specialized dairy farms. We used Partial Least Squares Structural Equation Modelling to build, and relate, latent variables of environmental performance, intensification and self-sufficiency. Proxy indicators reflected the latent variables for intensification (milk yield/cow, use of maize silage etc.) and self-sufficiency (home-grown feed/total feed use, on-farm energy/total energy use etc.). Environmental performance was represented by an aggregate 'eco-efficiency' score per farm derived from a Data Envelopment Analysis model fed with LCA and farm output data. The dataset was split into two spatially heterogeneous (bio-physical conditions, production patterns) regions. For both regions, eco-efficiency was significantly negatively related with milk yield/cow and the use of maize silage and imported concentrates. However, these results might not necessarily hold for intensive yet more self-sufficient farms. This requires further investigation with latent variables for intensification and self-sufficiency that do not largely overlap- a modelling challenge that occurred here. We conclude that the environmental 'sustainability' of intensive dairy farming depends on particular farming systems and circumstances, although we note that more self-sufficient farms may be preferable when they may benefit from relatively low land prices and agri-environment schemes aimed at maintaining grasslands.

Reindeer habitat use in relation to two small wind farms, during preconstruction, construction, and operation.

PubMed

Skarin, Anna; Alam, Moudud

2017-06-01

Worldwide there is a rush toward wind power development and its associated infrastructure. In Fennoscandia, large-scale wind farms comprising several hundred windmills are currently built in important grazing ranges used for Sámi reindeer husbandry. In this study, reindeer habitat use was assessed using reindeer fecal pellet group counts in relation to two relatively small wind farms, with 8 and 10 turbines, respectively. In 2009, 1,315 15-m 2 plots were established and pellet groups were counted and cleaned from the plots. This was repeated once a year in May, during preconstruction, construction, and operation of the wind farms, covering 6 years (2009-2014) of reindeer habitat use in the area. We modeled the presence/absence of any pellets in a plot at both the local (wind farm site) and regional (reindeer calving to autumn range) scale with a hierarchical logistic regression, where spatial correlation was accounted for via random effects, using vegetation type, and the interaction between distance to wind turbine and time period as predictor variables. Our results revealed an absolute reduction in pellet groups by 66% and 86% around each wind farm, respectively, at local scale and by 61% at regional scale during the operation phase compared to the preconstruction phase. At the regional, scale habitat use declined close to the turbines in the same comparison. However, at the local scale, we observed increased habitat use close to the wind turbines at one of the wind farms during the operation phase. This may be explained by continued use of an important migration route close to the wind farm. The reduced use at the regional scale nevertheless suggests that there may be an overall avoidance of both wind farms during operation, but further studies of reindeer movement and behavior are needed to gain a better understanding of the mechanisms behind this suggested avoidance.

The Relationship of Dairy Farm Eco-Efficiency with Intensification and Self-Sufficiency. Evidence from the French Dairy Sector Using Life Cycle Analysis, Data Envelopment Analysis and Partial Least Squares Structural Equation Modelling

PubMed Central

Soteriades, Andreas Diomedes; Stott, Alistair William; Moreau, Sindy; Charroin, Thierry; Blanchard, Melanie; Liu, Jiayi; Faverdin, Philippe

2016-01-01

We aimed at quantifying the extent to which agricultural management practices linked to animal production and land use affect environmental outcomes at a larger scale. Two practices closely linked to farm environmental performance at a larger scale are farming intensity, often resulting in greater off-farm environmental impacts (land, non-renewable energy use etc.) associated with the production of imported inputs (e.g. concentrates, fertilizer); and the degree of self-sufficiency, i.e. the farm’s capacity to produce goods from its own resources, with higher control over nutrient recycling and thus minimization of losses to the environment, often resulting in greater on-farm impacts (eutrophication, acidification etc.). We explored the relationship of these practices with farm environmental performance for 185 French specialized dairy farms. We used Partial Least Squares Structural Equation Modelling to build, and relate, latent variables of environmental performance, intensification and self-sufficiency. Proxy indicators reflected the latent variables for intensification (milk yield/cow, use of maize silage etc.) and self-sufficiency (home-grown feed/total feed use, on-farm energy/total energy use etc.). Environmental performance was represented by an aggregate ‘eco-efficiency’ score per farm derived from a Data Envelopment Analysis model fed with LCA and farm output data. The dataset was split into two spatially heterogeneous (bio-physical conditions, production patterns) regions. For both regions, eco-efficiency was significantly negatively related with milk yield/cow and the use of maize silage and imported concentrates. However, these results might not necessarily hold for intensive yet more self-sufficient farms. This requires further investigation with latent variables for intensification and self-sufficiency that do not largely overlap- a modelling challenge that occurred here. We conclude that the environmental ‘sustainability’ of intensive dairy farming depends on particular farming systems and circumstances, although we note that more self-sufficient farms may be preferable when they may benefit from relatively low land prices and agri-environment schemes aimed at maintaining grasslands. PMID:27832199

Modeling velocity space-time correlations in wind farms

NASA Astrophysics Data System (ADS)

Lukassen, Laura J.; Stevens, Richard J. A. M.; Meneveau, Charles; Wilczek, Michael

2016-11-01

Turbulent fluctuations of wind velocities cause power-output fluctuations in wind farms. The statistics of velocity fluctuations can be described by velocity space-time correlations in the atmospheric boundary layer. In this context, it is important to derive simple physics-based models. The so-called Tennekes-Kraichnan random sweeping hypothesis states that small-scale velocity fluctuations are passively advected by large-scale velocity perturbations in a random fashion. In the present work, this hypothesis is used with an additional mean wind velocity to derive a model for the spatial and temporal decorrelation of velocities in wind farms. It turns out that in the framework of this model, space-time correlations are a convolution of the spatial correlation function with a temporal decorrelation kernel. In this presentation, first results on the comparison to large eddy simulations will be presented and the potential of the approach to characterize power output fluctuations of wind farms will be discussed. Acknowledgements: 'Fellowships for Young Energy Scientists' (YES!) of FOM, the US National Science Foundation Grant IIA 1243482, and support by the Max Planck Society.

Next generation data systems and knowledge products to support agricultural producers and science-based policy decision making.

PubMed

Capalbo, Susan M; Antle, John M; Seavert, Clark

2017-07-01

Research on next generation agricultural systems models shows that the most important current limitation is data, both for on-farm decision support and for research investment and policy decision making. One of the greatest data challenges is to obtain reliable data on farm management decision making, both for current conditions and under scenarios of changed bio-physical and socio-economic conditions. This paper presents a framework for the use of farm-level and landscape-scale models and data to provide analysis that could be used in NextGen knowledge products, such as mobile applications or personal computer data analysis and visualization software. We describe two analytical tools - AgBiz Logic and TOA-MD - that demonstrate the current capability of farmlevel and landscape-scale models. The use of these tools is explored with a case study of an oilseed crop, Camelina sativa , which could be used to produce jet aviation fuel. We conclude with a discussion of innovations needed to facilitate the use of farm and policy-level models to generate data and analysis for improved knowledge products.

Understanding sources of sea lice for salmon farms in Chile.

PubMed

Kristoffersen, A B; Rees, E E; Stryhn, H; Ibarra, R; Campisto, J-L; Revie, C W; St-Hilaire, S

2013-08-01

The decline of fisheries over recent decades and a growing human population has coincided with an increase in aquaculture production. As farmed fish densities increase, so have their rates of infectious diseases, as predicted by the theory of density-dependent disease transmission. One of the pathogen that has increased with the growth of salmon farming is sea lice. Effective management of this pathogen requires an understanding of the spatial scale of transmission. We used a two-part multi-scale model to account for the zero-inflated data observed in weekly sea lice abundance levels on rainbow trout and Atlantic salmon farms in Chile, and to assess internal (farm) and external (regional) sources of sea lice infection. We observed that the level of juvenile sea lice was higher on farms that were closer to processing plants with fish holding facilities. Further, evidence for sea lice exposure from the surrounding area was supported by a strong positive correlation between the level of juvenile sea lice on a farm and the number of gravid females on neighboring farms within 30 km two weeks prior. The relationship between external sources of sea lice from neighboring farms and juvenile sea lice on a farm was one of the strongest detected in our multivariable model. Our findings suggest that the management of sea lice should be coordinated between farms and should include all farms and processing plants with holding facilities within a relatively large geographic area. Understanding the contribution of pathogens on a farm from different sources is an important step in developing effective control strategies. Crown Copyright © 2013. Published by Elsevier B.V. All rights reserved.

Dispersive stresses in wind farms

NASA Astrophysics Data System (ADS)

Segalini, Antonio; Braunbehrens, Robert; Hyvarinen, Ann

2017-11-01

One of the most famous models of wind farms is provided by the assumption that the farm can be approximated as a horizontally-homogeneous forest canopy with vertically-varying force intensity. By means of this approximation, the flow-motion equations become drastically simpler, as many of the three-dimensional effects are gone. However, the application of the horizontal average operator to the RANS equations leads to the appearance of new transport terms (called dispersive stresses) originating from the horizontal (small-scale) variation of the mean velocity field. Since these terms are related to the individual turbine signature, they are expected to vanish outside the roughness sublayer, providing a definition for the latter. In the present work, an assessment of the dispersive stresses is performed by means of a wake-model approach and through the linearised code ORFEUS developed at KTH. Both approaches are very fast and enable the characterization of a large number of wind-farm layouts. The dispersive stress tensor and its effect on the turbulence closure models are investigated, providing guidelines for those simulations where it is impossible to resolve the farm at a turbine scale due to grid requirements (as, for instance, mesoscale simulations).

Simulation of Turbulent Flow Inside and Above Wind Farms: Model Validation and Layout Effects

NASA Astrophysics Data System (ADS)

Wu, Yu-Ting; Porté-Agel, Fernando

2013-02-01

A recently-developed large-eddy simulation framework is validated and used to investigate turbulent flow within and above wind farms under neutral conditions. Two different layouts are considered, consisting of thirty wind turbines occupying the same total area and arranged in aligned and staggered configurations, respectively. The subgrid-scale (SGS) turbulent stress is parametrized using a tuning-free Lagrangian scale-dependent dynamic SGS model. The turbine-induced forces are modelled using two types of actuator-disk models: (a) the `standard' actuator-disk model (ADM-NR), which calculates only the thrust force based on one-dimensional momentum theory and distributes it uniformly over the rotor area; and (b) the actuator-disk model with rotation (ADM-R), which uses blade-element momentum theory to calculate the lift and drag forces (that produce both thrust and rotation), and distributes them over the rotor disk based on the local blade and flow characteristics. Validation is performed by comparing simulation results with turbulence measurements collected with hot-wire anemometry inside and above an aligned model wind farm placed in a boundary-layer wind tunnel. In general, the ADM-R model yields improved predictions compared with the ADM-NR in the wakes of all the wind turbines, where including turbine-induced flow rotation and accounting for the non-uniformity of the turbine-induced forces in the ADM-R appear to be important. Another advantage of the ADM-R model is that, unlike the ADM-NR, it does not require a priori specification of the thrust coefficient (which varies within a wind farm). Finally, comparison of simulations of flow through both aligned and staggered wind farms shows important effects of farm layout on the flow structure and wind-turbine performance. For the limited-size wind farms considered in this study, the lateral interaction between cumulated wakes is stronger in the staggered case, which results in a farm wake that is more homogeneous in the spanwise direction, thus resembling more an internal boundary layer. Inside the staggered farm, the relatively longer separation between consecutive downwind turbines allows the wakes to recover more, exposing the turbines to higher local wind speeds (leading to higher turbine efficiency) and lower turbulence intensity levels (leading to lower fatigue loads), compared with the aligned farm. Above the wind farms, the area-averaged velocity profile is found to be logarithmic, with an effective wind-farm aerodynamic roughness that is larger for the staggered case.

Analysis of economic benefit of wind power based on system dynamics

NASA Astrophysics Data System (ADS)

Zhao, Weibo; Han, Yaru; Niu, Dongxiao

2018-04-01

The scale of renewable power generation, such as wind power, has increased gradually in recent years. Considering that the economic benefits of wind farms are affected by many dynamic factors. The dynamic simulation model of wind power economic benefit system is established based on the system dynamics method. By comparing the economic benefits of wind farms under different setting scenarios through this model, the impact of different factors on the economic benefits of wind farms can be reflected.

Modeling space-time correlations of velocity fluctuations in wind farms

NASA Astrophysics Data System (ADS)

Lukassen, Laura J.; Stevens, Richard J. A. M.; Meneveau, Charles; Wilczek, Michael

2018-07-01

An analytical model for the streamwise velocity space-time correlations in turbulent flows is derived and applied to the special case of velocity fluctuations in large wind farms. The model is based on the Kraichnan-Tennekes random sweeping hypothesis, capturing the decorrelation in time while including a mean wind velocity in the streamwise direction. In the resulting model, the streamwise velocity space-time correlation is expressed as a convolution of the pure space correlation with an analytical temporal decorrelation kernel. Hence, the spatio-temporal structure of velocity fluctuations in wind farms can be derived from the spatial correlations only. We then explore the applicability of the model to predict spatio-temporal correlations in turbulent flows in wind farms. Comparisons of the model with data from a large eddy simulation of flow in a large, spatially periodic wind farm are performed, where needed model parameters such as spatial and temporal integral scales and spatial correlations are determined from the large eddy simulation. Good agreement is obtained between the model and large eddy simulation data showing that spatial data may be used to model the full temporal structure of fluctuations in wind farms.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sanz Rodrigo, Javier; Chávez Arroyo, Roberto Aurelio; Moriarty, Patrick

The increasing size of wind turbines, with rotors already spanning more than 150 m diameter and hub heights above 100 m, requires proper modeling of the atmospheric boundary layer (ABL) from the surface to the free atmosphere. Furthermore, large wind farm arrays create their own boundary layer structure with unique physics. This poses significant challenges to traditional wind engineering models that rely on surface-layer theories and engineering wind farm models to simulate the flow in and around wind farms. However, adopting an ABL approach offers the opportunity to better integrate wind farm design tools and meteorological models. The challenge ismore » how to build the bridge between atmospheric and wind engineering model communities and how to establish a comprehensive evaluation process that identifies relevant physical phenomena for wind energy applications with modeling and experimental requirements. A framework for model verification, validation, and uncertainty quantification is established to guide this process by a systematic evaluation of the modeling system at increasing levels of complexity. In terms of atmospheric physics, 'building the bridge' means developing models for the so-called 'terra incognita,' a term used to designate the turbulent scales that transition from mesoscale to microscale. This range of scales within atmospheric research deals with the transition from parameterized to resolved turbulence and the improvement of surface boundary-layer parameterizations. The coupling of meteorological and wind engineering flow models and the definition of a formal model evaluation methodology, is a strong area of research for the next generation of wind conditions assessment and wind farm and wind turbine design tools. Some fundamental challenges are identified in order to guide future research in this area.« less

Towards uncovering the structure of power fluctuations of wind farms

NASA Astrophysics Data System (ADS)

Liu, Huiwen; Jin, Yaqing; Tobin, Nicolas; Chamorro, Leonardo P.

2017-12-01

The structure of the turbulence-driven power fluctuations in a wind farm is fundamentally described from basic concepts. A derived tuning-free model, supported with experiments, reveals the underlying spectral content of the power fluctuations of a wind farm. It contains two power-law trends and oscillations in the relatively low- and high-frequency ranges. The former is mostly due to the turbulent interaction between the flow and the turbine properties, whereas the latter is due to the advection between turbine pairs. The spectral wind-farm scale power fluctuations ΦP exhibit a power-law decay proportional to f-5 /3 -2 in the region corresponding to the turbulence inertial subrange and at relatively large scales, ΦP˜f-2 . Due to the advection and turbulent diffusion of large-scale structures, a spectral oscillation exists with the product of a sinusoidal behavior and an exponential decay in the frequency domain.

Towards uncovering the structure of power fluctuations of wind farms.

PubMed

Liu, Huiwen; Jin, Yaqing; Tobin, Nicolas; Chamorro, Leonardo P

2017-12-01

The structure of the turbulence-driven power fluctuations in a wind farm is fundamentally described from basic concepts. A derived tuning-free model, supported with experiments, reveals the underlying spectral content of the power fluctuations of a wind farm. It contains two power-law trends and oscillations in the relatively low- and high-frequency ranges. The former is mostly due to the turbulent interaction between the flow and the turbine properties, whereas the latter is due to the advection between turbine pairs. The spectral wind-farm scale power fluctuations Φ_{P} exhibit a power-law decay proportional to f^{-5/3-2} in the region corresponding to the turbulence inertial subrange and at relatively large scales, Φ_{P}∼f^{-2}. Due to the advection and turbulent diffusion of large-scale structures, a spectral oscillation exists with the product of a sinusoidal behavior and an exponential decay in the frequency domain.

Multiscale effects of management, environmental conditions, and land use on nitrate leaching in dairy farms.

PubMed

Oenema, Jouke; Burgers, Saskia; Verloop, Koos; Hooijboer, Arno; Boumans, Leo; ten Berge, Hein

2010-01-01

Nitrate leaching in intensive grassland- and silage maize-based dairy farming systems on sandy soil is a main environmental concern. Here, statistical relationships are presented between management practices and environmental conditions and nitrate concentration in shallow groundwater (0.8 m depth) at farm, field, and point scales in The Netherlands, based on data collected in a participatory approach over a 7-yr period at one experimental and eight pilot commercial dairy farms on sandy soil. Farm milk production ranged from 10 to 24 Mg ha(-1). Soil and hydrological characteristics were derived from surveys and weather conditions from meteorological stations. Statistical analyses were performed with multiple regression models. Mean nitrate concentration at farm scale decreased from 79 mg L(-1) in 1999 to 63 in 2006, with average nitrate concentration in groundwater decreasing under grassland but increasing under maize land over the monitoring period. The effects of management practices on nitrate concentration varied with spatial scale. At farm scale, nitrogen surplus, grazing intensity, and the relative areas of grassland and maize land significantly contributed to explaining the variance in nitrate concentration in groundwater. Mean nitrate concentration was negatively correlated to the concentration of dissolved organic carbon in the shallow groundwater. At field scale, management practices and soil, hydrological, and climatic conditions significantly contributed to explaining the variance in nitrate concentration in groundwater under grassland and maize land. We conclude that, on these intensive dairy farms, additional measures are needed to comply with the European Union water quality standard in groundwater of 50 mg nitrate L(-1). The most promising measures are omitting fertilization of catch crops and reducing fertilization levels of first-year maize in the rotation.

Wind Farm LES Simulations Using an Overset Methodology

NASA Astrophysics Data System (ADS)

Ananthan, Shreyas; Yellapantula, Shashank

2017-11-01

Accurate simulation of wind farm wakes under realistic atmospheric inflow conditions and complex terrain requires modeling a wide range of length and time scales. The computational domain can span several kilometers while requiring mesh resolutions in O(10-6) to adequately resolve the boundary layer on the blade surface. Overset mesh methodology offers an attractive option to address the disparate range of length scales; it allows embedding body-confirming meshes around turbine geomtries within nested wake capturing meshes of varying resolutions necessary to accurately model the inflow turbulence and the resulting wake structures. Dynamic overset hole-cutting algorithms permit relative mesh motion that allow this nested mesh structure to track unsteady inflow direction changes, turbine control changes (yaw and pitch), and wake propagation. An LES model with overset mesh for localized mesh refinement is used to analyze wind farm wakes and performance and compared with local mesh refinements using non-conformal (hanging node) unstructured meshes. Turbine structures will be modeled using both actuator line approaches and fully-resolved structures to test the efficacy of overset methods for wind farm applications. Exascale Computing Project (ECP), Project Number: 17-SC-20-SC, a collaborative effort of two DOE organizations - the Office of Science and the National Nuclear Security Administration.

Regional climate model simulations indicate limited climatic impacts by operational and planned European wind farms.

PubMed

Vautard, Robert; Thais, Françoise; Tobin, Isabelle; Bréon, François-Marie; Devezeaux de Lavergne, Jean-Guy; Colette, Augustin; Yiou, Pascal; Ruti, Paolo Michele

2014-01-01

The rapid development of wind energy has raised concerns about environmental impacts. Temperature changes are found in the vicinity of wind farms and previous simulations have suggested that large-scale wind farms could alter regional climate. However, assessments of the effects of realistic wind power development scenarios at the scale of a continent are missing. Here we simulate the impacts of current and near-future wind energy production according to European Union energy and climate policies. We use a regional climate model describing the interactions between turbines and the atmosphere, and find limited impacts. A statistically significant signal is only found in winter, with changes within ±0.3 °C and within 0-5% for precipitation. It results from the combination of local wind farm effects and changes due to a weak, but robust, anticyclonic-induced circulation over Europe. However, the impacts remain much weaker than the natural climate interannual variability and changes expected from greenhouse gas emissions.

Optimal management of on-farm resources in small-scale dairy systems of Central Mexico: model development and evaluation.

PubMed

Castelán-Ortega, Octavio Alonso; Martínez-García, Carlos Galdino; Mould, Fergus L; Dorward, Peter; Rehman, Tahir; Rayas-Amor, Adolfo Armando

2016-06-01

This study evaluates the available on-farm resources of five case studies typified as small-scale dairy systems in central Mexico. A comprehensive mixed-integer linear programming model was developed and applied to two case studies. The optimal plan suggested the following: (1) instruction and utilization of maize silage, (2) alfalfa hay making that added US$140/ha/cut to the total net income, (3) allocation of land to cultivated pastures in a ratio of 27:41(cultivated pastures/maize crop) rather than at the current 14:69, and dairy cattle should graze 12 h/day, (4) to avoid grazing of communal pastures because this activity represented an opportunity cost of family labor that reduced the farm net income, and (5) that the highest farm net income was obtained when liquid milk and yogurt sales were included in the optimal plan. In the context of small-scale dairy systems of central Mexico, the optimal plan would need to be implemented gradually to enable farmers to develop required skills and to change management strategies from reliance on forage and purchased concentrate to pasture-based and conserved forage systems.

Wind-tunnel experiments of scalar transport in aligned and staggered wind farms

NASA Astrophysics Data System (ADS)

Zhang, W.; Markfort, C. D.; Porté-Agel, F.

2012-04-01

Wind energy is the fastest growing renewable energy worldwide, and it is expected that many more large-scale wind farms will be built and will cover a significant portion of land and ocean surfaces. By extracting kinetic energy from the atmospheric boundary layer, wind farms may affect the exchange/transport of momentum, heat and moisture between the atmosphere and land surface. To ensure the long-term sustainability of wind energy, it is important to understand the influence of large-scale wind farms on land-atmosphere interaction. Knowledge of this impact will also be useful to improve parameterizations of wind farms in numerical prediction tools, such as large-scale weather models and large-eddy simulation. Here, we present wind-tunnel measurements of the surface scalar (heat) flux from model wind farms, consisting of more than 10 rows of wind turbines, in a turbulent boundary layer with a surface heat source. Spatially distributed surface heat flux was obtained in idealized aligned and staggered wind farm layouts, having the same turbine distribution density. Measurements, using surface-mounted heat flux sensors, were taken at the 11th out of 12 rows of wind turbines, where the mean flow achieves a quasi-equilibrium state. In the aligned farm, there exist two distinct regions of increased and decreased surface heat flux on either side of turbine columns. The regions are correlated with coherent wake rotation in the turbine-array. On the upwelling side there is decreased flux, while on the downwelling side cool air moves towards the surface causing increased flux. For the staggered farm, the surface heat flux exhibits a relatively uniform distribution and an overall reduction with respect to the boundary layer flow, except in the vicinity of the turbine tower. This observation is also supported by near-surface temperature and turbulent heat flux measured using a customized x-wire/cold-wire. The overall surface heat flux, relative to that of the boundary layer flow without wind turbines, is reduced by approximately 4% in the staggered wind farm and remains nearly the same in the aligned wind farm.

Improving Environmental Management on Small-scale Farms: Perspectives of Extension Educators and Horse Farm Operators

NASA Astrophysics Data System (ADS)

Rebecca, Perry-Hill; Linda, Prokopy

2015-01-01

Although the number of small-scale farms is increasing in North America and Europe, few studies have been conducted to better understand environmental management in this sector. We investigate this issue by examining environmental management on horse farms from both the perspective of the "expert" extension educator and horse farm operator. We conducted a Delphi survey and follow-up interviews with extension educators in Indiana and Kentucky. We also conducted interviews and farm assessments with 15 horse farm operators in the two states. Our results suggest a disconnection between the perceptions of extension educators and horse farm operators. Extension educators believed that operators of small horse farms are unfamiliar with conservation practices and their environmental benefits and they found it difficult to target outreach to this audience. In the interviews with horse farm operators, we found that the majority were somewhat familiar with conservation practices like rotational grazing, soil testing, heavy use area protection, and manure composting. It was not common, however, for practices to be implemented to generally recognized standards. The horse farm respondents perceived these practices as interrelated parts of a system of farm management that has developed over time to best deal with the physical features of the property, needs of the horses, and available resources. Because conservation practices must be incorporated into a complex farm management system, traditional models of extension (i.e., diffusion of innovations) may be inappropriate for promoting better environmental management on horse farms.

Improving environmental management on small-scale farms: perspectives of extension educators and horse farm operators.

PubMed

Rebecca, Perry-Hill; Linda, Prokopy

2015-01-01

Although the number of small-scale farms is increasing in North America and Europe, few studies have been conducted to better understand environmental management in this sector. We investigate this issue by examining environmental management on horse farms from both the perspective of the "expert" extension educator and horse farm operator. We conducted a Delphi survey and follow-up interviews with extension educators in Indiana and Kentucky. We also conducted interviews and farm assessments with 15 horse farm operators in the two states. Our results suggest a disconnection between the perceptions of extension educators and horse farm operators. Extension educators believed that operators of small horse farms are unfamiliar with conservation practices and their environmental benefits and they found it difficult to target outreach to this audience. In the interviews with horse farm operators, we found that the majority were somewhat familiar with conservation practices like rotational grazing, soil testing, heavy use area protection, and manure composting. It was not common, however, for practices to be implemented to generally recognized standards. The horse farm respondents perceived these practices as interrelated parts of a system of farm management that has developed over time to best deal with the physical features of the property, needs of the horses, and available resources. Because conservation practices must be incorporated into a complex farm management system, traditional models of extension (i.e., diffusion of innovations) may be inappropriate for promoting better environmental management on horse farms.

A Hybrid Wind-Farm Parametrization for Mesoscale and Climate Models

NASA Astrophysics Data System (ADS)

Pan, Yang; Archer, Cristina L.

2018-04-01

To better understand the potential impact of wind farms on weather and climate at the regional to global scales, a new hybrid wind-farm parametrization is proposed for mesoscale and climate models. The proposed parametrization is a hybrid model because it is not based on physical processes or conservation laws, but on the multiple linear regression of the results of large-eddy simulations (LES) with the geometric properties of the wind-farm layout (e.g., the blockage ratio and blockage distance). The innovative aspect is that each wind turbine is treated individually based on its position in the farm and on the wind direction by predicting the velocity upstream of each turbine. The turbine-induced forces and added turbulence kinetic energy (TKE) are first derived analytically and then implemented in the Weather Research and Forecasting model. Idealized simulations of the offshore Lillgrund wind farm are conducted. The wind-speed deficit and TKE predicted with the hybrid model are in excellent agreement with those from the LES results, while the wind-power production estimated with the hybrid model is within 10% of that observed. Three additional wind farms with larger inter-turbine spacing than at Lillgrund are also considered, and a similar agreement with LES results is found, proving that the hybrid parametrization works well with any wind farm regardless of the spacing between turbines. These results indicate the wind-turbine position, wind direction, and added TKE are essential in accounting for the wind-farm effects on the surroundings, for which the hybrid wind-farm parametrization is a promising tool.

Fishing Farmers or Farming Fishers? Fishing Typology of Inland Small-Scale Fishing Households and Fisheries Management in Singkarak Lake, West Sumatra, Indonesia

NASA Astrophysics Data System (ADS)

Yuerlita; Perret, Sylvain Roger; Shivakoti, Ganesh P.

2013-07-01

Technical and socio-economic characteristics are known to determine different types of fishers and their livelihood strategies. Faced with declining fish and water resources, small-scale fisheries engage into transformations in livelihood and fishing practices. The paper is an attempt to understand these changes and their socio-economic patterns, in the case of Singkarak Lake in West Sumatra, Indonesia. Based upon the hypothesis that riparian communities have diverse, complex yet structured and dynamic livelihood systems, the paper's main objective is to study, document and model the actual diversity in livelihood, practices and performance of inland small-scale fisheries along the Singkarak Lake, to picture how households are adapted to the situation, and propose an updated, workable model (typology) of those for policy. Principal component analysis and cluster analysis were used to develop a typology of fishing households. The results show that small-scale fishers can be classified into different types characterized by distinct livelihood strategies. Three household types are identified, namely "farming fishers" households (type I, 30 %), "fishing farmers" households (type II, 30 %), and "mainly fishers" households (type III, 40 %). There are significant differences among these groups in the number of boats owned, annual fishing income, agriculture income and farming experience. Type I consists of farming fishers, well equipped, with high fishing costs and income, yet with the lowest return on fishing assets. They are also landowners with farming income, showing the lowest return on land capital. Type II includes poor fishing farmers, landowners with higher farming income; they show the highest return on land asset. They have less fishing equipment, costs and income. Type III (mainly fishers) consists of poorer, younger fishers, with highest return on fishing assets and on fishing costs. They have little land, low farming income, and diversified livelihood sources. The nature of their livelihood strategies is discussed for each identified group. This helps to understand the complexity and diversity of small-scale fishers, particularly in the study area which is still poorly known. This paper concludes with policy implication and possible management initiatives for environmentally prudent policy aiming at improvement of fishers' livelihood.

Fishing farmers or farming fishers? Fishing typology of inland small-scale fishing households and fisheries management in singkarak lake, west sumatra, indonesia.

PubMed

Yuerlita; Perret, Sylvain Roger; Shivakoti, Ganesh P

2013-07-01

Technical and socio-economic characteristics are known to determine different types of fishers and their livelihood strategies. Faced with declining fish and water resources, small-scale fisheries engage into transformations in livelihood and fishing practices. The paper is an attempt to understand these changes and their socio-economic patterns, in the case of Singkarak Lake in West Sumatra, Indonesia. Based upon the hypothesis that riparian communities have diverse, complex yet structured and dynamic livelihood systems, the paper's main objective is to study, document and model the actual diversity in livelihood, practices and performance of inland small-scale fisheries along the Singkarak Lake, to picture how households are adapted to the situation, and propose an updated, workable model (typology) of those for policy. Principal component analysis and cluster analysis were used to develop a typology of fishing households. The results show that small-scale fishers can be classified into different types characterized by distinct livelihood strategies. Three household types are identified, namely "farming fishers" households (type I, 30 %), "fishing farmers" households (type II, 30 %), and "mainly fishers" households (type III, 40 %). There are significant differences among these groups in the number of boats owned, annual fishing income, agriculture income and farming experience. Type I consists of farming fishers, well equipped, with high fishing costs and income, yet with the lowest return on fishing assets. They are also landowners with farming income, showing the lowest return on land capital. Type II includes poor fishing farmers, landowners with higher farming income; they show the highest return on land asset. They have less fishing equipment, costs and income. Type III (mainly fishers) consists of poorer, younger fishers, with highest return on fishing assets and on fishing costs. They have little land, low farming income, and diversified livelihood sources. The nature of their livelihood strategies is discussed for each identified group. This helps to understand the complexity and diversity of small-scale fishers, particularly in the study area which is still poorly known. This paper concludes with policy implication and possible management initiatives for environmentally prudent policy aiming at improvement of fishers' livelihood.

Processor farming in two-level analysis of historical bridge

NASA Astrophysics Data System (ADS)

Krejčí, T.; Kruis, J.; Koudelka, T.; Šejnoha, M.

2017-11-01

This contribution presents a processor farming method in connection with a multi-scale analysis. In this method, each macro-scopic integration point or each finite element is connected with a certain meso-scopic problem represented by an appropriate representative volume element (RVE). The solution of a meso-scale problem provides then effective parameters needed on the macro-scale. Such an analysis is suitable for parallel computing because the meso-scale problems can be distributed among many processors. The application of the processor farming method to a real world masonry structure is illustrated by an analysis of Charles bridge in Prague. The three-dimensional numerical model simulates the coupled heat and moisture transfer of one half of arch No. 3. and it is a part of a complex hygro-thermo-mechanical analysis which has been developed to determine the influence of climatic loading on the current state of the bridge.

Comparing offshore wind farm wake observed from satellite SAR and wake model results

NASA Astrophysics Data System (ADS)

Bay Hasager, Charlotte

2014-05-01

Offshore winds can be observed from satellite synthetic aperture radar (SAR). In the FP7 EERA DTOC project, the European Energy Research Alliance project on Design Tools for Offshore Wind Farm Clusters, there is focus on mid- to far-field wind farm wakes. The more wind farms are constructed nearby other wind farms, the more is the potential loss in annual energy production in all neighboring wind farms due to wind farm cluster effects. It is of course dependent upon the prevailing wind directions and wind speed levels, the distance between the wind farms, the wind turbine sizes and spacing. Some knowledge is available within wind farm arrays and in the near-field from various investigations. There are 58 offshore wind farms in the Northern European seas grid connected and in operation. Several of those are spaced near each other. There are several twin wind farms in operation including Nysted-1 and Rødsand-2 in the Baltic Sea, and Horns Rev 1 and Horns Rev 2, Egmond aan Zee and Prinses Amalia, and Thompton 1 and Thompton 2 all in the North Sea. There are ambitious plans of constructing numerous wind farms - great clusters of offshore wind farms. Current investigation of offshore wind farms includes mapping from high-resolution satellite SAR of several of the offshore wind farms in operation in the North Sea. Around 20 images with wind farm wake cases have been retrieved and processed. The data are from the Canadian RADARSAT-1/-2 satellites. These observe in microwave C-band and have been used for ocean surface wind retrieval during several years. The satellite wind maps are valid at 10 m above sea level. The wakes are identified in the raw images as darker areas downwind of the wind farms. In the SAR-based wind maps the wake deficit is found as areas of lower winds downwind of the wind farms compared to parallel undisturbed flow in the flow direction. The wind direction is clearly visible from lee effects and wind streaks in the images. The wind farm wake cases are modeled by various types of wake models. In the EERA DTOC project the model suite consists of engineering models (Ainslie, DWM, GLC, PARK, WASP/NOJ), simplified CFD models (FUGA, FarmFlow), full CFD models (CRES-flowNS, RANS), mesoscale model (SKIRON, WRF) and coupled meso-scale and microscale models. The comparison analysis between the satellite wind wake and model results will be presented and discussed. It is first time a comprehensive analysis is performed on this subject. The topic gains increasing importance because there is a growing need to precisely model also mid- and far-field wind farms wakes for development and planning of offshore wind farm clusters.

Integrating watershed- and farm-scale modeling framework for targeting critical source areas while maintaining farm economic viability

USDA-ARS?s Scientific Manuscript database

Quantitative risk assessments of pollution and data related to the effectiveness of mitigating best management practices (BMPs) are important aspects of nonpoint source (NPS) pollution control efforts, particularly those driven by specific water quality objectives and by measurable improvement goals...

"Advances in Coupled Air Quality, Farm Management and Biogeochemistry to address bidirectional ammonia flux"

EPA Science Inventory

A cropland farm management modeling system for regional air quality and field-scale applications of bi-directional ammonia exchange was presented at ITM XXI. The goal of this research is to improve estimates of nitrogen deposition to terrestrial and aquatic ecosystems and ambien...

High-resolution computational algorithms for simulating offshore wind turbines and farms: Model development and validation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Calderer, Antoni; Yang, Xiaolei; Angelidis, Dionysios

2015-10-30

The present project involves the development of modeling and analysis design tools for assessing offshore wind turbine technologies. The computational tools developed herein are able to resolve the effects of the coupled interaction of atmospheric turbulence and ocean waves on aerodynamic performance and structural stability and reliability of offshore wind turbines and farms. Laboratory scale experiments have been carried out to derive data sets for validating the computational models.

Analysis of Control-Oriented Wake Modeling Tools Using Lidar Field Results

DOE PAGES

Annoni, Jennifer; Fleming, Paul; Scholbrock, Andrew; ...

2018-02-08

Wind turbines in a wind farm operate individually to maximize their own performance regardless of the impact of aerodynamic interactions on neighboring turbines. Wind farm controls can be used to increase power production or reduce overall structural loads by properly coordinating turbines. One wind farm control strategy that is addressed in literature is known as wake steering, wherein upstream turbines operate in yaw misaligned conditions to redirect their wakes away from downstream turbines. The National Renewable Energy Laboratory (NREL) in Golden, CO conducted a demonstration of wake steering on a single utility-scale turbine. In this study, the turbine was operatedmore » at various yaw misalignment setpoints while a lidar mounted on the nacelle scanned five downstream distances. The lidar measurements were combined with turbine data, as well as measurements of the inflow made by a highly instrumented meteorological mast upstream. The full-scale measurements are used to validate controls-oriented tools, including wind turbine wake models, used for wind farm controls and optimization. This paper presents a quantitative comparison of the lidar data and controls-oriented wake models under different atmospheric conditions and turbine operation. The results show good agreement between the lidar data and the models under these different conditions.« less

Analysis of Control-Oriented Wake Modeling Tools Using Lidar Field Results

DOE Office of Scientific and Technical Information (OSTI.GOV)

Annoni, Jennifer; Fleming, Paul; Scholbrock, Andrew

Wind turbines in a wind farm operate individually to maximize their own performance regardless of the impact of aerodynamic interactions on neighboring turbines. Wind farm controls can be used to increase power production or reduce overall structural loads by properly coordinating turbines. One wind farm control strategy that is addressed in literature is known as wake steering, wherein upstream turbines operate in yaw misaligned conditions to redirect their wakes away from downstream turbines. The National Renewable Energy Laboratory (NREL) in Golden, CO conducted a demonstration of wake steering on a single utility-scale turbine. In this study, the turbine was operatedmore » at various yaw misalignment setpoints while a lidar mounted on the nacelle scanned five downstream distances. The lidar measurements were combined with turbine data, as well as measurements of the inflow made by a highly instrumented meteorological mast upstream. The full-scale measurements are used to validate controls-oriented tools, including wind turbine wake models, used for wind farm controls and optimization. This paper presents a quantitative comparison of the lidar data and controls-oriented wake models under different atmospheric conditions and turbine operation. The results show good agreement between the lidar data and the models under these different conditions.« less

Evaluating expansion strategies for startup European Union dairy farm businesses.

PubMed

McDonald, R; Shalloo, L; Pierce, K M; Horan, B

2013-06-01

A stochastic whole-farm simulation model was used to examine alternative strategies for new entrant dairy farmers to grow and develop dairy farm businesses in the context of European Union (EU) milk quota abolition in 2015. Six alternative strategies were compared: remain static, natural growth expansion, waiting until after EU milk quota abolition to expand, a full-scale expansion strategy without milk quotas and not incurring super levy penalties, a full-scale expansion strategy with milk quotas and incurring super levy penalties, and once-a-day milking until EU milk quota abolition, followed by full-scale expansion. Each discrete whole farm investment strategy was evaluated over a 15-yr period (2013-2027) using multiple financial stability and risk indicators, including overall discounted farm business profitability, net worth change, return on investment, and financial risk. The results of this study indicate that, although associated with increased risk, dairy farm expansion will ensure the future profitability of the farm business. Within the context of EU milk quotas until 2015, the most attractive expansion strategy is to increase cow numbers while avoiding super levy fines using once-a-day milking techniques, increasing to the full capacity of the dairy farm once milk quotas are removed. In contrast, the results also indicate that dairy farms that remain static will experience a significant reduction in farm profitability in the coming year due to production cost inflation. Cash flow deficits were observed during the initial year of expansion and, therefore, rapidly expanding dairy farm businesses require a significant cash reserve to alleviate business risk during the initial year of expansion. The results of this analysis also indicate that dairy farm businesses that expand using lower cost capital investments and avoid milk quota super levy fines significantly reduce the financial risks associated with expansion. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Towards a deeper understanding of parenting on farms: A qualitative study.

PubMed

Elliot, Valerie; Cammer, Allison; Pickett, William; Marlenga, Barbara; Lawson, Joshua; Dosman, James; Hagel, Louise; Koehncke, Niels; Trask, Catherine

2018-01-01

Children living on farms experience exceptionally high risks for traumatic injury. There is a large body of epidemiological research documenting this phenomenon, yet few complementary studies that have explored the deep underlying reasons for such trends. Fundamental to this is understanding the decision-making processes of parents surrounding their choice to bring children, or not, into the farm worksite. To (1) document farm parent views of the risks and benefits of raising children on a family farm, and, (2) understand more deeply why children are brought into the farm worksite. Interviews were conducted as part of a larger cohort study, The Saskatchewan Farm Injury Cohort. Subsequent to an initial mail-out question focused on parental decision-making, 11 semi-structured telephone interviews were conducted with rural Saskatchewan farm parents. Interviews were digitally recorded and transcribed verbatim, then thematically analyzed using interpretive description methodology. This parental decision-making process on farms fundamentally involves weighing the risks vs. benefits of bringing children into the worksite, as if on a balance scale. One side of this scale holds potential risks such as exposure to physical and chemical farm hazards, in the absence of full supervision. The other side holds potential benefits such as meeting family needs for childcare, labour, and family time; building work ethic and pride; and the positive impacts of involvement and responsibility. Decision-making 'tips the scales', in part dependent upon parental perceptions of the risk-benefit trade-off. This 'perceptual lens' is influenced by factors such as: the agricultural way of life, parents' prior knowledge and past experience, characteristics of children, and safety norms. This novel qualitative study provides deep insight into how Saskatchewan farm parents approach a fundamental decision-making process associated with their parenting. The proposed model provides insight into the etiology of pediatric farm injuries as well as their prevention.

Towards a deeper understanding of parenting on farms: A qualitative study

PubMed Central

Elliot, Valerie; Cammer, Allison; Pickett, William; Marlenga, Barbara; Lawson, Joshua; Dosman, James; Hagel, Louise; Koehncke, Niels

2018-01-01

Background Children living on farms experience exceptionally high risks for traumatic injury. There is a large body of epidemiological research documenting this phenomenon, yet few complementary studies that have explored the deep underlying reasons for such trends. Fundamental to this is understanding the decision-making processes of parents surrounding their choice to bring children, or not, into the farm worksite. Objectives To (1) document farm parent views of the risks and benefits of raising children on a family farm, and, (2) understand more deeply why children are brought into the farm worksite. Methods Interviews were conducted as part of a larger cohort study, The Saskatchewan Farm Injury Cohort. Subsequent to an initial mail-out question focused on parental decision-making, 11 semi-structured telephone interviews were conducted with rural Saskatchewan farm parents. Interviews were digitally recorded and transcribed verbatim, then thematically analyzed using interpretive description methodology. Findings This parental decision-making process on farms fundamentally involves weighing the risks vs. benefits of bringing children into the worksite, as if on a balance scale. One side of this scale holds potential risks such as exposure to physical and chemical farm hazards, in the absence of full supervision. The other side holds potential benefits such as meeting family needs for childcare, labour, and family time; building work ethic and pride; and the positive impacts of involvement and responsibility. Decision-making 'tips the scales', in part dependent upon parental perceptions of the risk-benefit trade-off. This 'perceptual lens' is influenced by factors such as: the agricultural way of life, parents' prior knowledge and past experience, characteristics of children, and safety norms. Conclusions This novel qualitative study provides deep insight into how Saskatchewan farm parents approach a fundamental decision-making process associated with their parenting. The proposed model provides insight into the etiology of pediatric farm injuries as well as their prevention. PMID:29897960

Use of Bayesian networks in predicting contamination of drinking water with E. coli in rural Vietnam.

PubMed

Hall, David C; Le, Quynh B

2017-06-01

More than 70 million Vietnamese rely on small-scale farming for some form of household income. Water on many of those farms is contaminated with waste, including animal manure, partly due to non-sustainable waste management. This increases the risk of water-related zoonotic disease transmission. The purpose of this research was to examine the impact of various demographic and management factors on the likelihood of finding Escherichia coli in drinking water sourced from wells and rainwater on farms in Vietnam. A Bayesian Belief Network (BBN) was designed to describe association between various deterministic and probabilistic variables gathered from 600 small-scale integrated (SSI) farmers in Vietnam. The variables relate to E. coli content of their drinking water sourced on-farm from wells and rainwater, and stored in on-farm large vessels, including concrete water tanks. The BBN was developed using the Netica software tool; the model was calibrated and goodness of fit examined using concordance of predictability. Sensitivity analysis of the model revealed that choice variables, including engagement in mitigation of water contamination and livestock management activities, were particularly likely to influence endpoint values, reflecting the highly variable and impactful nature of preferences, attitudes and beliefs relating to mitigation strategies. Quantitative variables including numbers of livestock (particularly chickens) and income also had a high impact. The highest concordance (62%) was achieved with the BBN reported in this paper. This BBN model of SSI farming in Vietnam is helpful in understanding the complexity of small-scale agriculture and how various factors work in concert to influence contamination of on-farm drinking water as indicated by the presence of E. coli. The model will also be useful for identifying and estimating the impact of policy options such as improved delivery of clean water management training for rural areas, particularly where such analysis is combined with other analytical and policy tools. With appropriate knowledge translation, the model results will be particularly useful in helping SSI farmers understand their options for engaging in public health mitigation strategies addressing clean water that do not significantly disrupt their agriculture-based livelihoods. © The Author 2017. Published by Oxford University Press on behalf of Royal Society of Tropical Medicine and Hygiene. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

A regional assessment of the cost and effectiveness of mitigation measures for reducing nutrient losses to water and greenhouse gas emissions to air from pastoral farms.

PubMed

Vibart, Ronaldo; Vogeler, Iris; Dennis, Samuel; Kaye-Blake, William; Monaghan, Ross; Burggraaf, Vicki; Beautrais, Josef; Mackay, Alec

2015-06-01

Using a novel approach that links geospatial land resource information with individual farm-scale simulation, we conducted a regional assessment of nitrogen (N) and phosphorous (P) losses to water and greenhouse gas (GHG) emissions to air from the predominant mix of pastoral industries in Southland, New Zealand. An evaluation of the cost-effectiveness of several nutrient loss mitigation strategies applied at the farm-scale, set primarily for reducing N and P losses and grouped by capital cost and potential ease of adoption, followed an initial baseline assessment. Grouped nutrient loss mitigation strategies were applied on an additive basis on the assumption of full adoption, and were broadly identified as 'improved nutrient management' (M1), 'improved animal productivity' (M2), and 'restricted grazing' (M3). Estimated annual nitrate-N leaching losses occurring under representative baseline sheep and beef (cattle) farms, and representative baseline dairy farms for the region were 10 ± 2 and 32 ± 6 kg N/ha (mean ± standard deviation), respectively. Both sheep and beef and dairy farms were responsive to N leaching loss mitigation strategies in M1, at a low cost per kg N-loss mitigated. Only dairy farms were responsive to N leaching loss abatement from adopting M2, at no additional cost per kg N-loss mitigated. Dairy farms were also responsive to N leaching loss abatement from adopting M3, but this reduction came at a greater cost per kg N-loss mitigated. Only dairy farms were responsive to P-loss mitigation strategies, in particular by adopting M1. Only dairy farms were responsive to GHG abatement; greater abatement was achieved by the most intensified dairy farm system simulated. Overall, M1 provided for high levels of regional scale N- and P-loss abatement at a low cost per farm without affecting overall farm production, M2 provided additional N-loss abatement but only marginal P-loss abatement, whereas M3 provided the greatest N-loss abatement, but delivered no additional P abatement, and came at a large financial cost to farmers, sheep and beef farmers in particular. The modelling approach provides a farm-scale framework that can be extended to other regions to accommodate different farm production systems and performances, capturing the interactions between farm types, land use capabilities and production levels, as these influence nutrient losses and GHG emissions, and the effectiveness of mitigation strategies. Copyright © 2015 Elsevier Ltd. All rights reserved.

Effect of inter-annual variability in pasture growth and irrigation response on farm productivity and profitability based on biophysical and farm systems modelling.

PubMed

Vogeler, Iris; Mackay, Alec; Vibart, Ronaldo; Rendel, John; Beautrais, Josef; Dennis, Samuel

2016-09-15

Farm system and nutrient budget models are increasingly being used in analysis to inform on farm decision making and evaluate land use policy options at regional scales. These analyses are generally based on the use of average annual pasture yields. In New Zealand (NZ), like in many countries, there is considerable inter-annual variation in pasture growth rates, due to climate. In this study a modelling approach was used to (i) include inter-annual variability as an integral part of the analysis and (ii) test the approach in an economic analysis of irrigation in a case study within the Hawkes Bay Region of New Zealand. The Agricultural Production Systems Simulator (APSIM) was used to generate pasture dry matter yields (DMY) for 20 different years and under both dryland and irrigation. The generated DMY were linked to outputs from farm-scale modelling for both Sheep and Beef Systems (Farmaxx Pro) and Dairy Systems (Farmax® Dairy Pro) to calculate farm production over 20 different years. Variation in DMY and associated livestock production due to inter-annual variation in climate was large, with a coefficient of variations up to 20%. Irrigation decreased this inter-annual variation. On average irrigation, with unlimited available water, increased income by $831 to 1195/ha, but when irrigation was limited to 250mm/ha/year income only increased by $525 to 883/ha. Using pasture responses in individual years to capturing the inter-annual variation, rather than the pasture response averaged over 20years resulted in lower financial benefits. In the case study income from irrigation based on an average year were 10 to >20% higher compared with those obtained from individual years. Copyright © 2016 Elsevier B.V. All rights reserved.

High Performance Computing for Modeling Wind Farms and Their Impact

NASA Astrophysics Data System (ADS)

Mavriplis, D.; Naughton, J. W.; Stoellinger, M. K.

2016-12-01

As energy generated by wind penetrates further into our electrical system, modeling of power production, power distribution, and the economic impact of wind-generated electricity is growing in importance. The models used for this work can range in fidelity from simple codes that run on a single computer to those that require high performance computing capabilities. Over the past several years, high fidelity models have been developed and deployed on the NCAR-Wyoming Supercomputing Center's Yellowstone machine. One of the primary modeling efforts focuses on developing the capability to compute the behavior of a wind farm in complex terrain under realistic atmospheric conditions. Fully modeling this system requires the simulation of continental flows to modeling the flow over a wind turbine blade, including down to the blade boundary level, fully 10 orders of magnitude in scale. To accomplish this, the simulations are broken up by scale, with information from the larger scales being passed to the lower scale models. In the code being developed, four scale levels are included: the continental weather scale, the local atmospheric flow in complex terrain, the wind plant scale, and the turbine scale. The current state of the models in the latter three scales will be discussed. These simulations are based on a high-order accurate dynamic overset and adaptive mesh approach, which runs at large scale on the NWSC Yellowstone machine. A second effort on modeling the economic impact of new wind development as well as improvement in wind plant performance and enhancements to the transmission infrastructure will also be discussed.

ANEMOS: Development of a next generation wind power forecasting system for the large-scale integration of onshore and offshore wind farms.

NASA Astrophysics Data System (ADS)

Kariniotakis, G.; Anemos Team

2003-04-01

Objectives: Accurate forecasting of the wind energy production up to two days ahead is recognized as a major contribution for reliable large-scale wind power integration. Especially, in a liberalized electricity market, prediction tools enhance the position of wind energy compared to other forms of dispatchable generation. ANEMOS, is a new 3.5 years R&D project supported by the European Commission, that resembles research organizations and end-users with an important experience on the domain. The project aims to develop advanced forecasting models that will substantially outperform current methods. Emphasis is given to situations like complex terrain, extreme weather conditions, as well as to offshore prediction for which no specific tools currently exist. The prediction models will be implemented in a software platform and installed for online operation at onshore and offshore wind farms by the end-users participating in the project. Approach: The paper presents the methodology of the project. Initially, the prediction requirements are identified according to the profiles of the end-users. The project develops prediction models based on both a physical and an alternative statistical approach. Research on physical models gives emphasis to techniques for use in complex terrain and the development of prediction tools based on CFD techniques, advanced model output statistics or high-resolution meteorological information. Statistical models (i.e. based on artificial intelligence) are developed for downscaling, power curve representation, upscaling for prediction at regional or national level, etc. A benchmarking process is set-up to evaluate the performance of the developed models and to compare them with existing ones using a number of case studies. The synergy between statistical and physical approaches is examined to identify promising areas for further improvement of forecasting accuracy. Appropriate physical and statistical prediction models are also developed for offshore wind farms taking into account advances in marine meteorology (interaction between wind and waves, coastal effects). The benefits from the use of satellite radar images for modeling local weather patterns are investigated. A next generation forecasting software, ANEMOS, will be developed to integrate the various models. The tool is enhanced by advanced Information Communication Technology (ICT) functionality and can operate both in stand alone, or remote mode, or be interfaced with standard Energy or Distribution Management Systems (EMS/DMS) systems. Contribution: The project provides an advanced technology for wind resource forecasting applicable in a large scale: at a single wind farm, regional or national level and for both interconnected and island systems. A major milestone is the on-line operation of the developed software by the participating utilities for onshore and offshore wind farms and the demonstration of the economic benefits. The outcome of the ANEMOS project will help consistently the increase of wind integration in two levels; in an operational level due to better management of wind farms, but also, it will contribute to increasing the installed capacity of wind farms. This is because accurate prediction of the resource reduces the risk of wind farm developers, who are then more willing to undertake new wind farm installations especially in a liberalized electricity market environment.

Are large farms more efficient? Tenure security, farm size and farm efficiency: evidence from northeast China

NASA Astrophysics Data System (ADS)

Zhou, Yuepeng; Ma, Xianlei; Shi, Xiaoping

2017-04-01

How to increase production efficiency, guarantee grain security, and increase farmers' income using the limited farmland is a great challenge that China is facing. Although theory predicts that secure property rights and moderate scale management of farmland can increase land productivity, reduce farm-related costs, and raise farmer's income, empirical studies on the size and magnitude of these effects are scarce. A number of studies have examined the impacts of land tenure or farm size on productivity or efficiency, respectively. There are also a few studies linking farm size, land tenure and efficiency together. However, to our best knowledge, there are no studies considering tenure security and farm efficiency together for different farm scales in China. In addition, there is little study analyzing the profit frontier. In this study, we particularly focus on the impacts of land tenure security and farm size on farm profit efficiency, using farm level data collected from 23 villages, 811 households in Liaoning in 2015. 7 different farm scales have been identified to further represent small farms, median farms, moderate-scale farms, and large farms. Technical efficiency is analyzed with stochastic frontier production function. The profit efficiency is regressed on a set of explanatory variables which includes farm size dummies, land tenure security indexes, and household characteristics. We found that: 1) The technical efficiency scores for production efficiency (average score = 0.998) indicate that it is already very close to the production frontier, and thus there is little room to improve production efficiency. However, there is larger space to raise profit efficiency (average score = 0.768) by investing more on farm size expansion, seed, hired labor, pesticide, and irrigation. 2) Farms between 50-80 mu are most efficient from the viewpoint of profit efficiency. The so-called moderate-scale farms (100-150 mu) according to the governmental guideline show no advantage in efficiency. 3) Formal land certificates and farmer's participation in land rental market are found to be important determinants of the profit efficiency across different scale of farms. 4) Fertilizer use has been excessive in Liaoning and could lead to the decline of crop profit.

Environmental potentials of policy instruments to mitigate nutrient emissions in Chinese livestock production.

PubMed

Zheng, Chaohui; Liu, Yi; Bluemling, Bettina; Mol, Arthur P J; Chen, Jining

2015-01-01

To minimize negative environmental impact of livestock production, policy-makers face a challenge to design and implement more effective policy instruments for livestock farmers at different scales. This research builds an assessment framework on the basis of an agent-based model, named ANEM, to explore nutrient mitigation potentials of five policy instruments, using pig production in Zhongjiang county, southwest China, as the empirical filling. The effects of different policy scenarios are simulated and compared using four indicators and differentiating between small, medium and large scale pig farms. Technology standards, biogas subsidies and information provisioning prove to be the most effective policies, while pollution fees and manure markets fail to environmentally improve manure management in pig livestock farming. Medium-scale farms are the more relevant scale category for a more environmentally sound development of Chinese livestock production. A number of policy recommendations are formulated as conclusion, as well as some limitations and prospects of the simulations are discussed. Copyright © 2014 Elsevier B.V. All rights reserved.

Metrics and methods for characterizing dairy farm intensification using farm survey data.

PubMed

Gonzalez-Mejia, Alejandra; Styles, David; Wilson, Paul; Gibbons, James

2018-01-01

Evaluation of agricultural intensification requires comprehensive analysis of trends in farm performance across physical and socio-economic aspects, which may diverge across farm types. Typical reporting of economic indicators at sectorial or the "average farm" level does not represent farm diversity and provides limited insight into the sustainability of specific intensification pathways. Using farm business data from a total of 7281 farm survey observations of English and Welsh dairy farms over a 14-year period we calculate a time series of 16 key performance indicators (KPIs) pertinent to farm structure, environmental and socio-economic aspects of sustainability. We then apply principle component analysis and model-based clustering analysis to identify statistically the number of distinct dairy farm typologies for each year of study, and link these clusters through time using multidimensional scaling. Between 2001 and 2014, dairy farms have largely consolidated and specialized into two distinct clusters: more extensive farms relying predominantly on grass, with lower milk yields but higher labour intensity, and more intensive farms producing more milk per cow with more concentrate and more maize, but lower labour intensity. There is some indication that these clusters are converging as the extensive cluster is intensifying slightly faster than the intensive cluster, in terms of milk yield per cow and use of concentrate feed. In 2014, annual milk yields were 6,835 and 7,500 l/cow for extensive and intensive farm types, respectively, whilst annual concentrate feed use was 1.3 and 1.5 tonnes per cow. For several KPIs such as milk yield the mean trend across all farms differed substantially from the extensive and intensive typologies mean. The indicators and analysis methodology developed allows identification of distinct farm types and industry trends using readily available survey data. The identified groups allow the accurate evaluation of the consequences of the reduction in dairy farm numbers and intensification at national and international scales.

Full-Scale Field Test of Wake Steering

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fleming, Paul; Annoni, Jennifer; Scholbrock, Andrew

Wind farm control, in which turbine controllers are coordinated to improve farmwide performance, is an active field of research. One form of wind farm control is wake steering, in which a turbine is yawed to the inflow to redirect its wake away from downstream turbines. Wake steering has been studied in depth in simulations as well as in wind tunnels and scaled test facilities. This work performs a field test of wake steering on a full-scale turbine. In the campaign, the yaw controller of the turbine has been set to track different yaw misalignment set points while a nacelle-mounted lidarmore » scans the wake at several ranges downwind. The lidar measurements are combined with turbine data, as well as measurements of the inflow made by a highly instrumented meteorological mast. In conclusion, these measurements are then compared to the predictions of a wind farm control-oriented model of wakes.« less

Full-Scale Field Test of Wake Steering

DOE PAGES

Fleming, Paul; Annoni, Jennifer; Scholbrock, Andrew; ...

2017-06-13

Wind farm control, in which turbine controllers are coordinated to improve farmwide performance, is an active field of research. One form of wind farm control is wake steering, in which a turbine is yawed to the inflow to redirect its wake away from downstream turbines. Wake steering has been studied in depth in simulations as well as in wind tunnels and scaled test facilities. This work performs a field test of wake steering on a full-scale turbine. In the campaign, the yaw controller of the turbine has been set to track different yaw misalignment set points while a nacelle-mounted lidarmore » scans the wake at several ranges downwind. The lidar measurements are combined with turbine data, as well as measurements of the inflow made by a highly instrumented meteorological mast. In conclusion, these measurements are then compared to the predictions of a wind farm control-oriented model of wakes.« less

Modeling greenhouse gas emissions from dairy farms.

PubMed

Rotz, C Alan

2017-11-15

Dairy farms have been identified as an important source of greenhouse gas emissions. Within the farm, important emissions include enteric CH 4 from the animals, CH 4 and N 2 O from manure in housing facilities during long-term storage and during field application, and N 2 O from nitrification and denitrification processes in the soil used to produce feed crops and pasture. Models using a wide range in level of detail have been developed to represent or predict these emissions. They include constant emission factors, variable process-related emission factors, empirical or statistical models, mechanistic process simulations, and life cycle assessment. To fully represent farm emissions, models representing the various emission sources must be integrated to capture the combined effects and interactions of all important components. Farm models have been developed using relationships across the full scale of detail, from constant emission factors to detailed mechanistic simulations. Simpler models, based upon emission factors and empirical relationships, tend to provide better tools for decision support, whereas more complex farm simulations provide better tools for research and education. To look beyond the farm boundaries, life cycle assessment provides an environmental accounting tool for quantifying and evaluating emissions over the full cycle, from producing the resources used on the farm through processing, distribution, consumption, and waste handling of the milk and dairy products produced. Models are useful for improving our understanding of farm processes and their interacting effects on greenhouse gas emissions. Through better understanding, they assist in the development and evaluation of mitigation strategies for reducing emissions and improving overall sustainability of dairy farms. The Authors. Published by the Federation of Animal Science Societies and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

A high resolution WRF model for wind energy forecasting

NASA Astrophysics Data System (ADS)

Vincent, Claire Louise; Liu, Yubao

2010-05-01

The increasing penetration of wind energy into national electricity markets has increased the demand for accurate surface layer wind forecasts. There has recently been a focus on forecasting the wind at wind farm sites using both statistical models and numerical weather prediction (NWP) models. Recent advances in computing capacity and non-hydrostatic NWP models means that it is possible to nest mesoscale models down to Large Eddy Simulation (LES) scales over the spatial area of a typical wind farm. For example, the WRF model (Skamarock 2008) has been run at a resolution of 123 m over a wind farm site in complex terrain in Colorado (Liu et al. 2009). Although these modelling attempts indicate a great hope for applying such models for detailed wind forecasts over wind farms, one of the obvious challenges of running the model at this resolution is that while some boundary layer structures are expected to be modelled explicitly, boundary layer eddies into the inertial sub-range can only be partly captured. Therefore, the amount and nature of sub-grid-scale mixing that is required is uncertain. Analysis of Liu et al. (2009) modelling results in comparison to wind farm observations indicates that unrealistic wind speed fluctuations with a period of around 1 hour occasionally occurred during the two day modelling period. The problem was addressed by re-running the same modelling system with a) a modified diffusion constant and b) two-way nesting between the high resolution model and its parent domain. The model, which was run with horizontal grid spacing of 370 m, had dimensions of 505 grid points in the east-west direction and 490 points in the north-south direction. It received boundary conditions from a mesoscale model of resolution 1111 m. Both models had 37 levels in the vertical. The mesoscale model was run with a non-local-mixing planetary boundary layer scheme, while the 370 m model was run with no planetary boundary layer scheme. It was found that increasing the diffusion constant caused damping of the unrealistic fluctuations, but did not completely solve the problem. Using two-way nesting also mitigated the unrealistic fluctuations significantly. It can be concluded that for real case LES modelling of wind farm circulations, care should be taken to ensure the consistency between the mesoscale weather forcing and LES models to avoid exciting spurious noise along the forcing boundary. The development of algorithms that adequately model the sub-grid-scale mixing that cannot be resolved by LES models is an important area for further research. References Liu, Y. Y._W. Liu, W. Y.Y. Cheng, W. Wu, T. T. Warner and K. Parks, 2009: Simulating intra-farm wind variations with the WRF-RTFDDA-LES modeling system. 10th WRF Users' Workshop, Boulder, C, USA. June 23 - 26, 2009. Skamarock, W., J. Dudhia, D.O. Gill, D.M. Barker, M.G.Duda, X-Y. Huang, W. Wang and J.G. Powers, A Description of the Advanced Research WRF version 3, NCAR Technical Note TN-475+STR, NCAR, Boulder, Colorado, 2008.

Including spatial data in nutrient balance modelling on dairy farms

NASA Astrophysics Data System (ADS)

van Leeuwen, Maricke; van Middelaar, Corina; Stoof, Cathelijne; Oenema, Jouke; Stoorvogel, Jetse; de Boer, Imke

2017-04-01

The Annual Nutrient Cycle Assessment (ANCA) calculates the nitrogen (N) and phosphorus (P) balance at a dairy farm, while taking into account the subsequent nutrient cycles of the herd, manure, soil and crop components. Since January 2016, Dutch dairy farmers are required to use ANCA in order to increase understanding of nutrient flows and to minimize nutrient losses to the environment. A nutrient balance calculates the difference between nutrient inputs and outputs. Nutrients enter the farm via purchased feed, fertilizers, deposition and fixation by legumes (nitrogen), and leave the farm via milk, livestock, manure, and roughages. A positive balance indicates to which extent N and/or P are lost to the environment via gaseous emissions (N), leaching, run-off and accumulation in soil. A negative balance indicates that N and/or P are depleted from soil. ANCA was designed to calculate average nutrient flows on farm level (for the herd, manure, soil and crop components). ANCA was not designed to perform calculations of nutrient flows at the field level, as it uses averaged nutrient inputs and outputs across all fields, and it does not include field specific soil characteristics. Land management decisions, however, such as the level of N and P application, are typically taken at the field level given the specific crop and soil characteristics. Therefore the information that ANCA provides is likely not sufficient to support farmers' decisions on land management to minimize nutrient losses to the environment. This is particularly a problem when land management and soils vary between fields. For an accurate estimate of nutrient flows in a given farming system that can be used to optimize land management, the spatial scale of nutrient inputs and outputs (and thus the effect of land management and soil variation) could be essential. Our aim was to determine the effect of the spatial scale of nutrient inputs and outputs on modelled nutrient flows and nutrient use efficiencies at Dutch dairy farms. We selected two dairy farms located on cover sands in the Netherlands. One farm was located on relatively homogeneous soil type, and one on many different soil types within the sandy soils. A full year of data of N and P inputs and outputs on farm and field level were provided by the farmers, including field level yields, yield composition, manure composition, degree of grazing and degree of mowing. Soil heterogeneity was defined as the number of soil units within the farm corrected for surface area, and quantified from the Dutch 1:50.000 soil map. N and P balances at farm and field level were determined, as well as differences in nutrient use efficiency, leaching, and N emission. We will present the effect of the spatial scale on nutrient balance analysis and discuss to which degree any differences are caused by within-farm land management and soil variation. This study highlights to which extent within-farm land management and soil variation should be taken into account when modelling nutrient flows and nutrient use efficiencies at farm level, to contribute to field-based decision making for improved land management.

Metrics and methods for characterizing dairy farm intensification using farm survey data

PubMed Central

Gonzalez-Mejia, Alejandra; Styles, David; Wilson, Paul

2018-01-01

Evaluation of agricultural intensification requires comprehensive analysis of trends in farm performance across physical and socio-economic aspects, which may diverge across farm types. Typical reporting of economic indicators at sectorial or the “average farm” level does not represent farm diversity and provides limited insight into the sustainability of specific intensification pathways. Using farm business data from a total of 7281 farm survey observations of English and Welsh dairy farms over a 14-year period we calculate a time series of 16 key performance indicators (KPIs) pertinent to farm structure, environmental and socio-economic aspects of sustainability. We then apply principle component analysis and model-based clustering analysis to identify statistically the number of distinct dairy farm typologies for each year of study, and link these clusters through time using multidimensional scaling. Between 2001 and 2014, dairy farms have largely consolidated and specialized into two distinct clusters: more extensive farms relying predominantly on grass, with lower milk yields but higher labour intensity, and more intensive farms producing more milk per cow with more concentrate and more maize, but lower labour intensity. There is some indication that these clusters are converging as the extensive cluster is intensifying slightly faster than the intensive cluster, in terms of milk yield per cow and use of concentrate feed. In 2014, annual milk yields were 6,835 and 7,500 l/cow for extensive and intensive farm types, respectively, whilst annual concentrate feed use was 1.3 and 1.5 tonnes per cow. For several KPIs such as milk yield the mean trend across all farms differed substantially from the extensive and intensive typologies mean. The indicators and analysis methodology developed allows identification of distinct farm types and industry trends using readily available survey data. The identified groups allow the accurate evaluation of the consequences of the reduction in dairy farm numbers and intensification at national and international scales. PMID:29742166

Using heterogeneity in the population structure of U.S. swine farms to compare transmission models for porcine epidemic diarrhoea

PubMed Central

O’Dea, Eamon B.; Snelson, Harry; Bansal, Shweta

2016-01-01

In 2013, U.S. swine producers were confronted with the disruptive emergence of porcine epidemic diarrhoea (PED). Movement of animals among farms is hypothesised to have played a role in the spread of PED among farms. Via this or other mechanisms, the rate of spread may also depend on the geographic density of farms and climate. To evaluate such effects on a large scale, we analyse state-level counts of outbreaks with variables describing the distribution of farm sizes and types, aggregate flows of animals among farms, and an index of climate. Our first main finding is that it is possible for a correlation analysis to be sensitive to transmission model parameters. This finding is based on a global sensitivity analysis of correlations on simulated data that included a biased and noisy observation model based on the available PED data. Our second main finding is that flows are significantly associated with the reports of PED outbreaks. This finding is based on correlations of pairwise relationships and regression modeling of total and weekly outbreak counts. These findings illustrate how variation in population structure may be employed along with observational data to improve understanding of disease spread. PMID:26947420

Spatiotemporal distribution of nitrogen dioxide within and around a large-scale wind farm - a numerical case study

NASA Astrophysics Data System (ADS)

Mo, Jingyue; Huang, Tao; Zhang, Xiaodong; Zhao, Yuan; Liu, Xiao; Li, Jixiang; Gao, Hong; Ma, Jianmin

2017-12-01

As a renewable and clean energy source, wind power has become the most rapidly growing energy resource worldwide in the past decades. Wind power has been thought not to exert any negative impacts on the environment. However, since a wind farm can alter the local meteorological conditions and increase the surface roughness lengths, it may affect air pollutants passing through and over the wind farm after released from their sources and delivered to the wind farm. In the present study, we simulated the nitrogen dioxide (NO2) air concentration within and around the world's largest wind farm (Jiuquan wind farm in Gansu Province, China) using a coupled meteorology and atmospheric chemistry model WRF-Chem. The results revealed an edge effect, which featured higher NO2 levels at the immediate upwind and border region of the wind farm and lower NO2 concentration within the wind farm and the immediate downwind transition area of the wind farm. A surface roughness length scheme and a wind turbine drag force scheme were employed to parameterize the wind farm in this model investigation. Modeling results show that both parameterization schemes yield higher concentration in the immediate upstream of the wind farm and lower concentration within the wind farm compared to the case without the wind farm. We infer this edge effect and the spatial distribution of air pollutants to be the result of the internal boundary layer induced by the changes in wind speed and turbulence intensity driven by the rotation of the wind turbine rotor blades and the enhancement of surface roughness length over the wind farm. The step change in the roughness length from the smooth to rough surfaces (overshooting) in the upstream of the wind farm decelerates the atmospheric transport of air pollutants, leading to their accumulation. The rough to the smooth surface (undershooting) in the downstream of the wind farm accelerates the atmospheric transport of air pollutants, resulting in lower concentration level.

Estimating Phosphorus Loss at the Whole-Farm Scale with User-Friendly Models

NASA Astrophysics Data System (ADS)

Vadas, P.; Powell, M.; Brink, G.; Busch, D.; Good, L.

2014-12-01

Phosphorus (P) loss from agricultural fields and delivery to surface waters persists as a water quality impairment issue. For dairy farms, P can be lost from cropland, pastures, barnyards, and open-air cattle lots; and all these sources must be evaluated to determine which ones are a priority for P loss remediation. We used interview surveys to document land use, cattle herd characteristics, and manure management for four grazing-based dairy farms in Wisconsin, USA. We then used the APLE and Snap-Plus models to estimate annual P loss from all areas on these farms and determine their relative contribution to whole-farm P loss. At the whole-farm level, average annual P loss (kg ha-1) from grazing-based dairy farms was low (0.6 to 1.8 kg ha-1), generally because a significant portion of land was in permanently vegetated pastures or hay and had low erosion. However, there were areas on the farms that represented sources of significant P loss. For cropland, the greatest P loss was from areas with exposed soil, typically for corn production, and especially on steeper sloping land. The farm areas with the greatest P loss had concentrated animal housing, including barnyards, and over-wintering and young-stock lots. These areas can represent from about 5% to almost 30% of total farm P loss, depending on lot management and P loss from other land uses. Our project builds on research to show that producer surveys can provide reliable management information to assess whole-farm P loss. It also shows that we can use models like RUSLE2, Snap-Plus, and APLE to rapidly, reliably, and quantitatively estimate P loss in runoff from all areas on a dairy farm and identify areas in greatest need of alternative management to reduce P loss.

Large Eddy Simulation of Vertical Axis Wind Turbines

NASA Astrophysics Data System (ADS)

Hezaveh, Seyed Hossein

Due to several design advantages and operational characteristics, particularly in offshore farms, vertical axis wind turbines (VAWTs) are being reconsidered as a complementary technology to horizontal axial turbines (HAWTs). However, considerable gaps remain in our understanding of VAWT performance since they have been significantly less studied than HAWTs. This thesis examines the performance of isolated VAWTs based on different design parameters and evaluates their characteristics in large wind farms. An actuator line model (ALM) is implemented in an atmospheric boundary layer large eddy simulation (LES) code, with offline coupling to a high-resolution blade-scale unsteady Reynolds-averaged Navier-Stokes (URANS) model. The LES captures the turbine-to-farm scale dynamics, while the URANS captures the blade-to-turbine scale flow. The simulation results are found to be in good agreement with existing experimental datasets. Subsequently, a parametric study of the flow over an isolated VAWT is carried out by varying solidities, height-to-diameter aspect ratios, and tip speed ratios. The analyses of the wake area and power deficits yield an improved understanding of the evolution of VAWT wakes, which in turn enables a more informed selection of turbine designs for wind farms. One of the most important advantages of VAWTs compared to HAWTs is their potential synergistic interactions that increase their performance when placed in close proximity. Field experiments have confirmed that unlike HAWTs, VAWTs can enhance and increase the total power production when placed near each other. Based on these experiments and using ALM-LES, we also present and test new approaches for VAWT farm configuration. We first design clusters with three turbines then configure farms consisting of clusters of VAWTs rather than individual turbines. The results confirm that by using a cluster design, the average power density of wind farms can be increased by as much as 60% relative to regular arrays. Finally, the thesis conducts an investigation of the influence of farm length (parallel to the wind) to assess the fetch needed for equilibrium to be reached, as well as the origin of the kinetic energy extracted by the turbines.

Impacts of drought on grape yields in Western Cape, South Africa

NASA Astrophysics Data System (ADS)

Araujo, Julio A.; Abiodun, Babatunde J.; Crespo, Olivier

2016-01-01

Droughts remain a threat to grape yields in South Africa. Previous studies on the impacts of climate on grape yield in the country have focussed on the impact of rainfall and temperature separately; meanwhile, grape yields are affected by drought, which is a combination of rainfall and temperature influences. The present study investigates the impacts of drought on grape yields in the Western Cape (South Africa) at district and farm scales. The study used a new drought index that is based on simple water balance (Standardized Precipitation Evapotranspiration Index; hereafter, SPEI) to identify drought events and used a correlation analysis to identify the relationship between drought and grape yields. A crop simulation model (Agricultural Production Systems sIMulator, APSIM) was applied at the farm scale to investigate the role of irrigation in mitigating the impacts of drought on grape yield. The model gives a realistic simulation of grape yields. The Western Cape has experienced a series of severe droughts in the past few decades. The severe droughts occurred when a decrease in rainfall occurred simultaneously with an increase in temperature. El Niño Southern Oscillation (ENSO) appears to be an important driver of drought severity in the Western Cape, because most of the severe droughts occurred in El Niño years. At the district scale, the correlation between drought index and grape yield is weak ( r≈-0.5), but at the farm scale, it is strong ( r≈-0.9). This suggests that many farmers are able to mitigate the impacts of drought on grape yields through irrigation management. At the farm scale, where the impact of drought on grape yields is high, poor yield years coincide with moderate or severe drought periods. The APSIM simulation, which gives a realistic simulation of grape yields at the farm scale, suggests that grape yields become more sensitive to spring and summer droughts in the absence of irrigation. Results of this study may guide decision-making on how to reduce the impacts of drought on food security in South Africa.

Farming for a Better Climate by Improving Nitrogen Use Efficiency and Reducing Greenhouse Gas Emissions (FarmClim)

NASA Astrophysics Data System (ADS)

Amon, Barbara; Winiwarter, Wilfried; Schröck, Andrea; Zechmeister-Boltenstern, Sophie; Kasper, Martina; Sigmund, Elisabeth; Schaller, Lena; Moser, Tobias; Baumgarten, Andreas; Dersch, Georg; Zethner, Gerhard; Anderl, Michael; Kitzler, Barbara

2014-05-01

The project FarmClim (Farming for a better climate) assesses impacts of agriculture on N and GHG fluxes in Austria and proposes measures for improving N efficiency and mitigating emissions, including their economic assessment. This paper focuses on animal husbandry and crop production measures, and on N2O emissions from soils. FarmClim applies national inventory reporting methods to assess Austrian NH3 and GHG fluxes in order to develop flux estimates with implementation of mitigation measures. Based on scientific literature and on the outcome of the Austrian working group agriculture and climate protection a list of potential mitigation measures has been produced: phase feeding, dairy cattle diet, biogas production. Data cover resulting production levels as well as GHG mitigation. In crop production, an optimisation potential remains with respect to N fertilization and nutrient uptake efficiency. Projected regional yield data and information on the N content of arable crops have been delivered from field experiments. These data complement official statistics and allow assessing the effect of increasing proportions of legume crops in crop rotations and reducing fertilizer input on a regional scale. Economic efficiency of measures is a crucial factor for their future implementation on commercial farms. The economic model evaluates investment costs as well as changes in direct costs, labour costs and economic yield. Biophysical modelling with Landscape DNDC allows establishing a framework to move from the current approach of applying the IPCC default emission factor for N2O emissions from soils. We select two Austrian model regions to calculate N fluxes taking into account region and management practices. Hot spots and hot moments as well as mitigation strategies are identified. Two test regions have been identified for soil emission modelling. The Marchfeld is an intensively used agricultural area in North-East Austria with very fertile soils and dry climate. The area of central Upper-Austria is characterized by heavy gley soils and higher annual precipitation (890mm). Based on site parameters, vegetation characteristics, management and meteorology, the model is able to predict C and N bio-geo-chemistry in agricultural ecosystems at site and regional scale. This is the basis for assessing further mitigation specifically focussing on the hot spots and hot moments of N emissions on a regional scale. The list of mitigation measures resulting from the project activities has been tailored to fit Austrian conditions in order to be attractive to stakeholders and farmers. Providing information on economic impacts to farms adds to the transparency of the approach taken. We expect that understanding the interest and the worries of farmers from the beginning supports creation of realistic output that can provide a strong incentive to urgently needed actions on improving farm N efficiencies.

Short-term Wind Forecasting at Wind Farms using WRF-LES and Actuator Disk Model

NASA Astrophysics Data System (ADS)

Kirkil, Gokhan

2017-04-01

Short-term wind forecasts are obtained for a wind farm on a mountainous terrain using WRF-LES. Multi-scale simulations are also performed using different PBL parameterizations. Turbines are parameterized using Actuator Disc Model. LES models improved the forecasts. Statistical error analysis is performed and ramp events are analyzed. Complex topography of the study area affects model performance, especially the accuracy of wind forecasts were poor for cross valley-mountain flows. By means of LES, we gain new knowledge about the sources of spatial and temporal variability of wind fluctuations such as the configuration of wind turbines.

A farm-level precision land management framework based on integer programming

PubMed Central

Li, Qi; Hu, Guiping; Jubery, Talukder Zaki; Ganapathysubramanian, Baskar

2017-01-01

Farmland management involves several planning and decision making tasks including seed selection and irrigation management. A farm-level precision farmland management model based on mixed integer linear programming is proposed in this study. Optimal decisions are designed for pre-season planning of crops and irrigation water allocation. The model captures the effect of size and shape of decision scale as well as special irrigation patterns. The authors illustrate the model with a case study on a farm in the state of California in the U.S. and show the model can capture the impact of precision farm management on profitability. The results show that threefold increase of annual net profit for farmers could be achieved by carefully choosing irrigation and seed selection. Although farmers could increase profits by applying precision management to seed or irrigation alone, profit increase is more significant if farmers apply precision management on seed and irrigation simultaneously. The proposed model can also serve as a risk analysis tool for farmers facing seasonal irrigation water limits as well as a quantitative tool to explore the impact of precision agriculture. PMID:28346499

Modelling pollination services across agricultural landscapes

PubMed Central

Lonsdorf, Eric; Kremen, Claire; Ricketts, Taylor; Winfree, Rachael; Williams, Neal; Greenleaf, Sarah

2009-01-01

Background and Aims Crop pollination by bees and other animals is an essential ecosystem service. Ensuring the maintenance of the service requires a full understanding of the contributions of landscape elements to pollinator populations and crop pollination. Here, the first quantitative model that predicts pollinator abundance on a landscape is described and tested. Methods Using information on pollinator nesting resources, floral resources and foraging distances, the model predicts the relative abundance of pollinators within nesting habitats. From these nesting areas, it then predicts relative abundances of pollinators on the farms requiring pollination services. Model outputs are compared with data from coffee in Costa Rica, watermelon and sunflower in California and watermelon in New Jersey–Pennsylvania (NJPA). Key Results Results from Costa Rica and California, comparing field estimates of pollinator abundance, richness or services with model estimates, are encouraging, explaining up to 80 % of variance among farms. However, the model did not predict observed pollinator abundances on NJPA, so continued model improvement and testing are necessary. The inability of the model to predict pollinator abundances in the NJPA landscape may be due to not accounting for fine-scale floral and nesting resources within the landscapes surrounding farms, rather than the logic of our model. Conclusions The importance of fine-scale resources for pollinator service delivery was supported by sensitivity analyses indicating that the model's predictions depend largely on estimates of nesting and floral resources within crops. Despite the need for more research at the finer-scale, the approach fills an important gap by providing quantitative and mechanistic model from which to evaluate policy decisions and develop land-use plans that promote pollination conservation and service delivery. PMID:19324897

Medium fidelity modelling of loads in wind farms under non-neutral ABL stability conditions - a full-scale validation study

NASA Astrophysics Data System (ADS)

Larsen, G. C.; Larsen, T. J.; Chougule, A.

2017-05-01

The aim of the present paper is to demonstrate the capability of medium fidelity modelling of wind turbine component fatigue loading, when the wind turbines are subjected to wake affected non-stationary flow fields under non-neutral atmospheric stability conditions. To accomplish this we combine the classical Dynamic Wake Meandering model with a fundamental conjecture stating: Atmospheric boundary layer stability affects primary wake meandering dynamics driven by large turbulent scales, whereas wake expansion in the meandering frame of reference is hardly affected. Inclusion of stability (i.e. buoyancy) in description of both large- and small scale atmospheric boundary layer turbulence is facilitated by a generalization of the classical Mann spectral tensor, which consistently includes buoyancy effects. With non-stationary wind turbine inflow fields modelled as described above, fatigue loads are obtained using the state-of-the art aeroelastic model HAWC2. The Lillgrund offshore wind farm (WF) constitute an interesting case study for wind farm model validation, because the WT interspacing is small, which in turn means that wake effects are significant. A huge data set, comprising 5 years of blade and tower load recordings, is available for model validation. For a multitude of wake situations this data set displays a considerable scatter, which to a large degree seems to be caused by atmospheric boundary layer stability effects. Notable is also that rotating wind turbine components predominantly experience high fatigue loading for stable stratification with significant shear, whereas high fatigue loading of non-rotating wind turbine components are associated with unstable atmospheric boundary layer stratification.

Pathways to sustainable intensification through crop water management

NASA Astrophysics Data System (ADS)

MacDonald, Graham K.; D'Odorico, Paolo; Seekell, David A.

2016-09-01

How much could farm water management interventions increase global crop production? This is the central question posed in a global modelling study by Jägermeyr et al (2016 Environ. Res. Lett. 11 025002). They define the biophysical realm of possibility for future gains in crop production related to agricultural water practices—enhancing water availability to crops and expanding irrigation by reducing non-productive water consumption. The findings of Jägermeyr et al offer crucial insight on the potential for crop water management to sustainably intensify agriculture, but they also provide a benchmark to consider the broader role of sustainable intensification targets in the global food system. Here, we reflect on how the global crop water management simulations of Jägermeyr et al could interact with: (1) farm size at more local scales, (2) downstream water users at the river basin scale, as well as (3) food trade and (4) demand-side food system strategies at the global scale. Incorporating such cross-scale linkages in future research could highlight the diverse pathways needed to harness the potential of farm-level crop water management for a more productive and sustainable global food system.

Assessing biodiversity on the farm scale as basis for ecosystem service payments.

PubMed

von Haaren, Christina; Kempa, Daniela; Vogel, Katrin; Rüter, Stefan

2012-12-30

Ecosystem services payments must be based on a standardised transparent assessment of the goods and services provided. This is especially relevant in the context of EU agri-environmental programs, but also for organic-food companies that foster environmental services on their contractor farms. Addressing the farm scale is important because land users/owners are major recipients of payments and they could be more involved in data generation and conservation management. A standardised system for measuring on-farm biodiversity does not yet exist that concentrates on performance indicators and includes farmers in generating information. A method is required that produces ordinal or metric scaled assessment results as well as management measures. Another requirement is the ease of application, which includes the ease of gathering input data and understandability. In order to respond to this need, we developed a method which is designed for automated application in an open source farm assessment system named MANUELA. The method produces an ordinal scale assessment of biodiversity that includes biotopes, species, biotope connectivity and the influence of land use. In addition, specific measures for biotope types are proposed. The open source geographical information system OpenJump is used for the implementation of MANUELA. The results of the trial applications and robustness tests show that the assessment can be implemented, for the most part, using existing information as well as data available from farmers or advisors. The results are more sensitive for showing on-farm achievements and changes than existing biotope-type classifications. Such a differentiated classification is needed as a basis for ecosystem service payments and for designing effective measures. The robustness of the results with respect to biotope connectivity is comparable to that of complex models, but it should be further improved. Interviews with the test farmers substantiate that the assessment methods can be implemented on farms and they are understood by farmers. Copyright © 2012 Elsevier Ltd. All rights reserved.

Seropositivity and risk factors for Brucella in dairy cows in urban and peri-urban small-scale farming in Tajikistan.

PubMed

Lindahl, Elisabeth; Sattorov, Nosirjon; Boqvist, Sofia; Sattori, Izzatullo; Magnusson, Ulf

2014-03-01

In this cross-sectional study, we assessed and mapped the seroprevalence of brucellosis in small-scale dairy farming in an urban and peri-urban area of Tajikistan and investigated factors associated with seropositivity. As urban and peri-urban farming is both an opportunity to improve the livelihood for small-scale farmers and a potential public health hazard, studies are warranted to reveal possible peculiarities in the epidemiology of brucellosis in this type of dairy farming. In total, 904 cows of breeding age belonging to 443 herds in 32 villages were serologically tested with indirect enzyme-linked immunosorbent assay (ELISA) and positive samples confirmed with competitive ELISA. Two logistic regression models were used to investigate an association between seropositivity and risk factors at herd and individual level. The herd and individual seroprevalences were 4.1 and 2.0 %, respectively. Herds with a history of abortions were found to be associated with seropositivity [odds ratio (OR) = 5.3; 95 % confidence interval (CI), 1.3-21.3]. Large herds with more than eight cattle were more likely to be seropositive compared to smaller herds with one to two cattle (OR = 13.9; 95 % CI, 1.6-119). The number of calves produced per cow (indicating age) was found to be associated with seropositivity. Younger cows with one to two produced calves were less likely to be seropositive compared to older cows with more than six produced calves (OR = 0.24; 95 % CI, 0.06-1.0). Neither introduction of new cattle to the herd nor communal grazing was associated with seropositivity. This study shows that infection with Brucella (1) is present in small-scale urban and peri-urban dairy farming in Tajikistan and (2) has significant negative effects on reproductive performance in this farming system and (3) that some previously known risk factors for seropositivity in rural farming system were absent here.

Large-Eddy Simulation of Waked Turbines in a Scaled Wind Farm Facility

NASA Astrophysics Data System (ADS)

Wang, J.; McLean, D.; Campagnolo, F.; Yu, T.; Bottasso, C. L.

2017-05-01

The aim of this paper is to present the numerical simulation of waked scaled wind turbines operating in a boundary layer wind tunnel. The simulation uses a LES-lifting-line numerical model. An immersed boundary method in conjunction with an adequate wall model is used to represent the effects of both the wind turbine nacelle and tower, which are shown to have a considerable effect on the wake behavior. Multi-airfoil data calibrated at different Reynolds numbers are used to account for the lift and drag characteristics at the low and varying Reynolds conditions encountered in the experiments. The present study focuses on low turbulence inflow conditions and inflow non-uniformity due to wind tunnel characteristics, while higher turbulence conditions are considered in a separate study. The numerical model is validated by using experimental data obtained during test campaigns conducted with the scaled wind farm facility. The simulation and experimental results are compared in terms of power capture, rotor thrust, downstream velocity profiles and turbulence intensity.

Benefit-Cost Analysis of Foot-and-Mouth Disease Vaccination at the Farm-Level in South Vietnam.

PubMed

Truong, Dinh Bao; Goutard, Flavie Luce; Bertagnoli, Stéphane; Delabouglise, Alexis; Grosbois, Vladimir; Peyre, Marisa

2018-01-01

This study aimed to analyze the financial impact of foot-and-mouth disease (FMD) outbreaks in cattle at the farm-level and the benefit-cost ratio (BCR) of biannual vaccination strategy to prevent and eradicate FMD for cattle in South Vietnam. Production data were collected from 49 small-scale dairy farms, 15 large-scale dairy farms, and 249 beef farms of Long An and Tay Ninh province using a questionaire. Financial data of FMD impacts were collected using participatory tools in 37 villages of Long An province. The net present value, i.e., the difference between the benefits (additional revenue and saved costs) and costs (additional costs and revenue foregone), of FMD vaccination in large-scale dairy farms was 2.8 times higher than in small-scale dairy farms and 20 times higher than in beef farms. The BCR of FMD vaccination over 1 year in large-scale dairy farms, small-scale dairy farms, and beef farms were 11.6 [95% confidence interval (95% CI) 6.42-16.45], 9.93 (95% CI 3.45-16.47), and 3.02 (95% CI 0.76-7.19), respectively. The sensitivity analysis showed that varying the vaccination cost had more effect on the BCR of cattle vaccination than varying the market price. This benefit-cost analysis of biannual vaccination strategy showed that investment in FMD prevention can be financially profitable, and therefore sustainable, for dairy farmers. For beef cattle, it is less certain that vaccination is profitable. Additional benefit-cost analysis study of vaccination strategies at the national-level would be required to evaluate and adapt the national strategy to achieve eradication of this disease in Vietnam.

Optimising reef-scale CO2 removal by seaweed to buffer ocean acidification

NASA Astrophysics Data System (ADS)

Mongin, Mathieu; Baird, Mark E.; Hadley, Scott; Lenton, Andrew

2016-03-01

The equilibration of rising atmospheric {{CO}}2 with the ocean is lowering {pH} in tropical waters by about 0.01 every decade. Coral reefs and the ecosystems they support are regarded as one of the most vulnerable ecosystems to ocean acidification, threatening their long-term viability. In response to this threat, different strategies for buffering the impact of ocean acidification have been proposed. As the {pH} experienced by individual corals on a natural reef system depends on many processes over different time scales, the efficacy of these buffering strategies remains largely unknown. Here we assess the feasibility and potential efficacy of a reef-scale (a few kilometers) carbon removal strategy, through the addition of seaweed (fleshy multicellular algae) farms within the Great Barrier Reef at the Heron Island reef. First, using diagnostic time-dependent age tracers in a hydrodynamic model, we determine the optimal location and size of the seaweed farm. Secondly, we analytically calculate the optimal density of the seaweed and harvesting strategy, finding, for the seaweed growth parameters used, a biomass of 42 g N m-2 with a harvesting rate of up 3.2 g N m-2 d-1 maximises the carbon sequestration and removal. Numerical experiments show that an optimally located 1.9 km2 farm and optimally harvested seaweed (removing biomass above 42 g N m-2 every 7 d) increased aragonite saturation by 0.1 over 24 km2 of the Heron Island reef. Thus, the most effective seaweed farm can only delay the impacts of global ocean acidification at the reef scale by 7-21 years, depending on future global carbon emissions. Our results highlight that only a kilometer-scale farm can partially mitigate global ocean acidification for a particular reef.

Supporting local diversity of habitats and species on farmland: a comparison of three wildlife-friendly schemes.

PubMed

Hardman, Chloe J; Harrison, Dominic P G; Shaw, Pete J; Nevard, Tim D; Hughes, Brin; Potts, Simon G; Norris, Ken

2016-02-01

Restoration and maintenance of habitat diversity have been suggested as conservation priorities in farmed landscapes, but how this should be achieved and at what scale are unclear. This study makes a novel comparison of the effectiveness of three wildlife-friendly farming schemes for supporting local habitat diversity and species richness on 12 farms in England.The schemes were: (i) Conservation Grade (Conservation Grade: a prescriptive, non-organic, biodiversity-focused scheme), (ii) organic agriculture and (iii) a baseline of Entry Level Stewardship (Entry Level Stewardship: a flexible widespread government scheme). Conservation Grade farms supported a quarter higher habitat diversity at the 100-m radius scale compared to Entry Level Stewardship farms. Conservation Grade and organic farms both supported a fifth higher habitat diversity at the 250-m radius scale compared to Entry Level Stewardship farms. Habitat diversity at the 100-m and 250-m scales significantly predicted species richness of butterflies and plants. Habitat diversity at the 100-m scale also significantly predicted species richness of birds in winter and solitary bees. There were no significant relationships between habitat diversity and species richness for bumblebees or birds in summer.Butterfly species richness was significantly higher on organic farms (50% higher) and marginally higher on Conservation Grade farms (20% higher), compared with farms in Entry Level Stewardship. Organic farms supported significantly more plant species than Entry Level Stewardship farms (70% higher) but Conservation Grade farms did not (10% higher). There were no significant differences between the three schemes for species richness of bumblebees, solitary bees or birds. Policy implications . The wildlife-friendly farming schemes which included compulsory changes in management, Conservation Grade and organic, were more effective at increasing local habitat diversity and species richness compared with the less prescriptive Entry Level Stewardship scheme. We recommend that wildlife-friendly farming schemes should aim to enhance and maintain high local habitat diversity, through mechanisms such as option packages, where farmers are required to deliver a combination of several habitats.

Prospective and participatory integrated assessment of agricultural systems from farm to regional scales: Comparison of three modeling approaches.

PubMed

Delmotte, Sylvestre; Lopez-Ridaura, Santiago; Barbier, Jean-Marc; Wery, Jacques

2013-11-15

Evaluating the impacts of the development of alternative agricultural systems, such as organic or low-input cropping systems, in the context of an agricultural region requires the use of specific tools and methodologies. They should allow a prospective (using scenarios), multi-scale (taking into account the field, farm and regional level), integrated (notably multicriteria) and participatory assessment, abbreviated PIAAS (for Participatory Integrated Assessment of Agricultural System). In this paper, we compare the possible contribution to PIAAS of three modeling approaches i.e. Bio-Economic Modeling (BEM), Agent-Based Modeling (ABM) and statistical Land-Use/Land Cover Change (LUCC) models. After a presentation of each approach, we analyze their advantages and drawbacks, and identify their possible complementarities for PIAAS. Statistical LUCC modeling is a suitable approach for multi-scale analysis of past changes and can be used to start discussion about the futures with stakeholders. BEM and ABM approaches have complementary features for scenarios assessment at different scales. While ABM has been widely used for participatory assessment, BEM has been rarely used satisfactorily in a participatory manner. On the basis of these results, we propose to combine these three approaches in a framework targeted to PIAAS. Copyright © 2013 Elsevier Ltd. All rights reserved.

Multi-time scale energy management of wind farms based on comprehensive evaluation technology

NASA Astrophysics Data System (ADS)

Xu, Y. P.; Huang, Y. H.; Liu, Z. J.; Wang, Y. F.; Li, Z. Y.; Guo, L.

2017-11-01

A novel energy management of wind farms is proposed in this paper. Firstly, a novel comprehensive evaluation system is proposed to quantify economic properties of each wind farm to make the energy management more economical and reasonable. Then, a combination of multi time-scale schedule method is proposed to develop a novel energy management. The day-ahead schedule optimizes unit commitment of thermal power generators. The intraday schedule is established to optimize power generation plan for all thermal power generating units, hydroelectric generating sets and wind power plants. At last, the power generation plan can be timely revised in the process of on-line schedule. The paper concludes with simulations conducted on a real provincial integrated energy system in northeast China. Simulation results have validated the proposed model and corresponding solving algorithms.

Unstructured grid modelling of offshore wind farm impacts on seasonally stratified shelf seas

NASA Astrophysics Data System (ADS)

Cazenave, Pierre William; Torres, Ricardo; Allen, J. Icarus

2016-06-01

Shelf seas comprise approximately 7% of the world's oceans and host enormous economic activity. Development of energy installations (e.g. Offshore Wind Farms (OWFs), tidal turbines) in response to increased demand for renewable energy requires a careful analysis of potential impacts. Recent remote sensing observations have identified kilometre-scale impacts from OWFs. Existing modelling evaluating monopile impacts has fallen into two camps: small-scale models with individually resolved turbines looking at local effects; and large-scale analyses but with sub-grid scale turbine parameterisations. This work straddles both scales through a 3D unstructured grid model (FVCOM): wind turbine monopiles in the eastern Irish Sea are explicitly described in the grid whilst the overall grid domain covers the south-western UK shelf. Localised regions of decreased velocity extend up to 250 times the monopile diameter away from the monopile. Shelf-wide, the amplitude of the M2 tidal constituent increases by up to 7%. The turbines enhance localised vertical mixing which decreases seasonal stratification. The spatial extent of this extends well beyond the turbines into the surrounding seas. With significant expansion of OWFs on continental shelves, this work highlights the importance of how OWFs may impact coastal (e.g. increased flooding risk) and offshore (e.g. stratification and nutrient cycling) areas.

Modeling the fate and transport of bacteria in agricultural and pasture lands using APEX

USDA-ARS?s Scientific Manuscript database

The Agricultural Policy/Environmental eXtender (APEX) model is a whole farm to small watershed scale continuous simulation model developed for evaluating various land management strategies. The current version, APEX0806, does not have the modeling capacity for fecal indicator bacteria fate and trans...

Long Island Solar Farm

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anders, R.

2013-05-01

The Long Island Solar Farm (LISF) is a remarkable success story, whereby very different interest groups found a way to capitalize on unusual circumstances to develop a mutually beneficial source of renewable energy. The uniqueness of the circumstances that were necessary to develop the Long Island Solar Farm make it very difficult to replicate. The project is, however, an unparalleled resource for solar energy research, which will greatly inform large-scale PV solar development in the East. Lastly, the LISF is a superb model for the process by which the project developed and the innovation and leadership shown by the differentmore » players.« less

Soil erosion measurements under organic and conventional land use treatments and different tillage systems using micro-scale runoff plots and a portable rainfall simulator

NASA Astrophysics Data System (ADS)

Seitz, Steffen; Goebes, Philipp; Song, Zhengshan; Wittwer, Raphaël; van der Heijden, Marcel; Scholten, Thomas

2015-04-01

Soil erosion is a major environmental problem of our time and negatively affects soil organic matter (SOM), aggregate stability or nutrient availability for instance. It is well known that agricultural practices have a severe influence on soil erosion by water. Several long-term field trials show that the use of low input strategies (e.g. organic farming) instead of conventional high-input farming systems leads to considerable changes of soil characteristics. Organic farming relies on crop rotation, absence of agrochemicals, green manure and weed control without herbicides. As a consequence, SOM content in the top soil layer is usually higher than on arable land under conventional use. Furthermore, the soil surface is better protected against particle detachment and overland flow due to a continuous vegetation cover and a well-developed root system increases soil stability. Likewise, tillage itself can cause soil erosion on arable land. In this respect, conservation and reduced tillage systems like No-Till or Ridge-Till provide a protecting cover from the previous year's residue and reduce soil disturbance. Many studies have been carried out on the effect of farming practices on soil erosion, but with contrasting results. To our knowledge, most of those studies rely on soil erosion models to calculate soil erosion rates and replicated experimental field measurement designs are rarely used. In this study, we performed direct field assessment on a farming system trial in Rümlang, Switzerland (FAST: Farming System and Tillage experiment Agroscope) to investigate the effect of organic farming practises and tillage systems on soil erosion. A portable single nozzle rainfall simulator and a light weight tent have been used with micro-scale runoff plots (0.4 m x 0.4 m). Four treatments (Conventional/Tillage, Conventional/No-Tillage, Organic/Tillage, Organic/Reduced-tillage) have been sampled with 8 replications each for a total of 32 runoff plots. All plots have been distributed randomly within the treatments. Linear mixed effect modelling was used to examine the effects of the treatments on sediment discharge and surface runoff. Results were compared with recent findings from erosion models and laboratory studies. Results show that sediment discharge is significantly higher (59 %, p=0.018) on conventional treatments (31.8 g/m2/h) than on organic treatments (20.0 g/m2/h). This finding supports results from several studies, which found soil erosion rates from 18 % to 184 % higher on conventional than on organic treatments. Under both farming systems, ploughed treatments show higher sediment discharge (conventional farming: 104 %, organic farming: 133 %, p=0.004) than treatments with reduced or no tillage. Runoff volume did not show significant effects in our treatments. An interaction between the farming practice and the tillage system could not be found, which strengthens the importance of both. With the help of a well-replicated micro-scale runoff plot design and a portable rainfall simulator we were able to gather reliable soil erosion data in situ in short term and without external parameterization. Our field assessment shows that organic farming and reduced tillage practices protect agricultural land best against soil erosion.

Impacts of an offshore wind farm on the lower marine atmosphere

NASA Astrophysics Data System (ADS)

Volker, P. J.; Huang, H.; Capps, S. B.; Badger, J.; Hahmann, A. N.; Hall, A. D.

2013-12-01

Due to a continuing increase in energy demand and heightened environmental consciousness, the State of California is seeking out more environmentally-friendly energy resources. Strong and persistent winds along California's coast can be harnessed effectively by current wind turbine technology, providing a promising source of alternative energy. Using an advanced wind farm parameterization implemented in the Weather Research & Forecast model, we investigate the potential impacts of a large offshore wind farm on the lower marine atmosphere. Located offshore of the Sonoma Coast in northern California, this theoretical wind farm includes 200-7 megawatt, 125 m hub height wind turbines which are able to provide a total of 1.4 TW of power for use in neighboring cities. The wind turbine model (i.e., the Explicit Wake Parameterization originally developed at the Danish Technical University) acts as a source of drag where the sub-grid scale velocity deficit expansion is explicitly described. A swath consisting of hub-height velocity deficits and temperature and moisture anomalies extends more than 100 km downstream of the wind farm location. The presence of the large modern wind farm also creates flow distortion upstream in conjunction with an enhanced vertical momentum and scalar transport.

Modelling farm vulnerability to flooding: A step toward vulnerability mitigation policies appraisal

NASA Astrophysics Data System (ADS)

Brémond, P.; Abrami, G.; Blanc, C.; Grelot, F.

2009-04-01

Recent catastrophic flood events such as Elbe in 2002 or Rhône in 2003 have shown limits of flood management policies relying on dykes protection: worsening of flood impacts downstream, increased damage by dykes rupture. Those events, among others, contributes to radical changes on the philosophy of flood prevention, with the promotion of new orientations for mitigating flood exposition. Two new trends may have a significant impact on rural areas: floodplain restoration and vulnerability mitigation. The Rhône River program, which is an contract of objectives signed between French Government and local collectivites, is highly illustrative of these new trends and their impact on agricultural sector. In this program, it appears that areas to be concerned by floodplain restoration are agricultural ones, because their supposed vulnerability to flood is expected to be less important to urban areas. As a consequence, agricultural sector is particularly concerned by planned actions on mitigation of assets vulnerability, an important part of the program (financial support of European Union of 7.5 Million euros). Mitigation of agricultural assets vulnerability reveals particularly interesting for two following reasons. Firstly, it is a way to maintain agricultural activities in floodplains yet existing, without promoting flood protection. Secondly, in case of floodplain restoration, vulnerability mitigation is a way for local authorities to compensate over-flooding impacts. In practice, local authorities may financially support farmers for implementing measures to mitigate their farm vulnerability. On the Rhône River, an important work has already been done to identify farm vulnerability to flooding, and propose measures to mitigate it. More than 3 000 farms exposed to flood risk have been identified representing 88 690 ha of agricultural areas which is estimated to generate damage between 400 and 800 Million euros depending on the season of occurrence for a catastrophic flood. In the case of farm activities, vulnerability mitigation consists in implementing measures which can be: physical (equipment or electric power system elevation), organizational (emergency or recovery plan) or financial (insurance). These measures aim at decreasing the total damage incurred by farmers in case of flooding. For instance, if equipment is elevated, it will not suffer direct damage such as degradation. As a consequence, equipment will be available to continue production or recovery tasks, thus, avoiding indirect damage such as delays, indebtedness… The effects of these policies on farms, in particular vulnerability mitigation cannot be appraised using current methodologies mainly because they do not consider farm as a whole and focus on direct damage at the land plot scale (loss of yield). Moreover, since vulnerability mitigation policies are quite recent, few examples of implementation exist and no feedback experience can be processed. Meanwhile, decision makers and financial actors require more justification of the efficiency of public fund by economic appraisal of the projects. On the Rhône River, decision makers asked for an economic evaluation of the program of farm vulnerability mitigation they plan to implement. This implies to identify the effects of the measures to mitigate farm vulnerability, and to classify them by comparing their efficacy (avoided damage) and their cost of implementation. In this presentation, we propose and discuss a conceptual model of vulnerability at the farm scale. The modelling, in Unified Modelling Language, enabled to represent the ties between spatial, organizational and temporal dimensions, which are central to understanding of farm vulnerability and resilience to flooding. Through this modelling, we encompass three goals: To improve the comprehension of farm vulnerability and create a framework that allow discussion with experts of different disciplines as well as with local farmers; To identify data which are needed to implement the model and to collect them, specifically using the focus group method; Based on the conceptual model, to program a mathematical model which will be used to simulate damage (direct and indirect) on farm due to flood. This last objective should enable us to appraise policy to mitigate vulnerability which is planned to be implemented on Rhône River at the individual and regional scale. Finally, we discuss the possibility to use the UML modelling to develop a multi-agent system approach which could be interesting to take into account ties between farmers (solidarity, loan of equipment) or systemic effects due to the damage incurred by economic partners (loss of market share). Keywords vulnerability, UML modelling, farming systems, flood, mitigation policy, economic valuation

Effects of agricultural conservation practices on N loads in the Mississippi-Atchafalya River Basin

USDA-ARS?s Scientific Manuscript database

A modeling framework consisting of a farm-scale model, Agricultural Policy Environmental Extender (APEX); a watershedscale model, Soil and Water Assessment Tool (SWAT); and databases was used in the Conservation Effects Assessment Project to quantify the environmental benefits of conservation practi...

Integrating Agent Models of Subsistence Farming With Dynamic Models of Water Distribution

NASA Astrophysics Data System (ADS)

Bithell, M.; Brasington, J.

2004-12-01

Subsistence farming communities are dependent on the landscape to provide the resource base upon which their societies can be built. A key component of this is the role of climate, and the feedback between rainfall, crop growth and land clearance, and their coupling to the hydrological cycle. Temporal fluctuations in rainfall on timescales from annual through to decadal and longer, and the associated changes in in the spatial distribution of water availability mediated by the soil-type, slope and landcover determine the locations within the landscape that can support agriculture, and control sustainability of farming practices. We seek to make an integrated modelling system to represent land use change by coupling an agent based model of subsistence farming, and the associated exploitation of natural resources, to a realistic representation of the hydrology at the catchment scale, using TOPMODEL to map the spatial distribution of crop water stress for given time-series of rainfall. In this way we can, for example, investigate how demographic changes and associated removal of forest cover influence the possibilities for field locations within the catchment, through changes in ground water availability. The framework for this modelling exercise will be presented and preliminary results from this system will be discussed.

CFD Study of the Performance of an Operational Wind Farm and its Impact on the Local Climate: CFD sensitivity to forestry modelling

NASA Astrophysics Data System (ADS)

Wylie, Scott; Watson, Simon

2013-04-01

Any past, current or projected future wind farm developments are highly dependent on localised climatic conditions. For example the mean wind speed, one of the main factors in assessing the economic feasibility of a wind farm, can vary significantly over length scales no greater than the size of a typical wind farm. Any additional heterogeneity at a potential site, such as forestry, can affect the wind resource further not accounting for the additional difficulty of installation. If a wind farm is sited in an environmentally sensitive area then the ability to predict the wind farm performance and possible impacts on the important localised climatic conditions are of increased importance. Siting of wind farms in environmentally sensitive areas is not uncommon, such as areas of peat-land as in this example. Areas of peat-land are important sinks for carbon in the atmosphere but their ability to sequester carbon is highly dependent on the local climatic conditions. An operational wind farm's impact on such an area was investigated using CFD. Validation of the model outputs were carried out using field measurements from three automatic weather stations (AWS) located throughout the site. The study focuses on validation of both wind speed and turbulence measurement, whilst also assessing the models ability to predict wind farm performance. The use of CFD to model the variation in wind speed over heterogeneous terrain, including wind turbines effects, is increasing in popularity. Encouraging results have increased confidence in the ability of CFD performance in complex terrain with features such as steep slopes and forests, which are not well modelled by the widely used linear models such as WAsP and MS-Micro. Using concurrent measurements from three stationary AWS across the wind farm will allow detailed validation of the model predicted flow characteristics, whilst aggregated power output information will allow an assessment of how accurate the model setup can predict wind farm performance. Given the dependence of the local climatic conditions influence on the peat-land's ability to sequester carbon, accurate predictions of the local wind and turbulence features will allow us to quantify any possible wind farm influences. This work was carried out using the commercially available Reynolds Averaged Navier-Stokes (RANS) CFD package ANSYS CFX. Utilising the Windmodeller add-on in CFX, a series of simulations were carried out to assess wind flow interactions through and around the wind farm, incorporating features such as terrain, forestry and rotor wake interactions. Particular attention was paid to forestry effects, as the AWS are located close to the vicinity of forestry. Different Leaf Area Densities (LAD) were tested to assess how sensitive the models output was to this change.

Wind tunnel measurements of the power output variability and unsteady loading in a micro wind farm model

NASA Astrophysics Data System (ADS)

Bossuyt, Juliaan; Howland, Michael; Meneveau, Charles; Meyers, Johan

2015-11-01

To optimize wind farm layouts for a maximum power output and wind turbine lifetime, mean power output measurements in wind tunnel studies are not sufficient. Instead, detailed temporal information about the power output and unsteady loading from every single wind turbine in the wind farm is needed. A very small porous disc model with a realistic thrust coefficient of 0.75 - 0.85, was designed. The model is instrumented with a strain gage, allowing measurements of the thrust force, incoming velocity and power output with a frequency response up to the natural frequency of the model. This is shown by reproducing the -5/3 spectrum from the incoming flow. Thanks to its small size and compact instrumentation, the model allows wind tunnel studies of large wind turbine arrays with detailed temporal information from every wind turbine. Translating to field conditions with a length-scale ratio of 1:3,000 the frequencies studied from the data reach from 10-4 Hz up to about 6 .10-2 Hz. The model's capabilities are demonstrated with a large wind farm measurement consisting of close to 100 instrumented models. A high correlation is found between the power outputs of stream wise aligned wind turbines, which is in good agreement with results from prior LES simulations. Work supported by ERC (ActiveWindFarms, grant no. 306471) and by NSF (grants CBET-113380 and IIA-1243482, the WINDINSPIRE project).

Occurrence of Eimeria Species Parasites on Small-Scale Commercial Chicken Farms in Africa and Indication of Economic Profitability

PubMed Central

Fornace, Kimberly M.; Clark, Emily L.; Macdonald, Sarah E.; Namangala, Boniface; Karimuribo, Esron; Awuni, Joseph A.; Thieme, Olaf; Blake, Damer P.; Rushton, Jonathan

2013-01-01

Small-scale commercial poultry production is emerging as an important form of livestock production in Africa, providing sources of income and animal protein to many poor households, yet the occurrence and impact of coccidiosis on this relatively new production system remains unknown. The primary objective of this study was to examine Eimeria parasite occurrence on small-scale commercial poultry farms in Ghana, Tanzania and Zambia. Additionally, farm economic viability was measured by calculating the farm gross margin and enterprise budget. Using these economic measures as global assessments of farm productivity, encompassing the diversity present in regional husbandry systems with a measure of fundamental local relevance, we investigated the detection of specific Eimeria species as indicators of farm profitability. Faecal samples and data on production parameters were collected from small-scale (less than 2,000 birds per batch) intensive broiler and layer farms in peri-urban Ghana, Tanzania and Zambia. All seven Eimeria species recognised to infect the chicken were detected in each country. Furthermore, two of the three genetic variants (operational taxonomic units) identified previously in Australia have been described outside of Australia for the first time. Detection of the most pathogenic Eimeria species associated with decreased farm profitability and may be considered as an indicator of likely farm performance. While a causal link remains to be demonstrated, the presence of highly pathogenic enteric parasites may pose a threat to profitable, sustainable small-scale poultry enterprises in Africa. PMID:24391923

Occurrence of Eimeria species parasites on small-scale commercial chicken farms in Africa and indication of economic profitability.

PubMed

Fornace, Kimberly M; Clark, Emily L; Macdonald, Sarah E; Namangala, Boniface; Karimuribo, Esron; Awuni, Joseph A; Thieme, Olaf; Blake, Damer P; Rushton, Jonathan

2013-01-01

Small-scale commercial poultry production is emerging as an important form of livestock production in Africa, providing sources of income and animal protein to many poor households, yet the occurrence and impact of coccidiosis on this relatively new production system remains unknown. The primary objective of this study was to examine Eimeria parasite occurrence on small-scale commercial poultry farms in Ghana, Tanzania and Zambia. Additionally, farm economic viability was measured by calculating the farm gross margin and enterprise budget. Using these economic measures as global assessments of farm productivity, encompassing the diversity present in regional husbandry systems with a measure of fundamental local relevance, we investigated the detection of specific Eimeria species as indicators of farm profitability. Faecal samples and data on production parameters were collected from small-scale (less than 2,000 birds per batch) intensive broiler and layer farms in peri-urban Ghana, Tanzania and Zambia. All seven Eimeria species recognised to infect the chicken were detected in each country. Furthermore, two of the three genetic variants (operational taxonomic units) identified previously in Australia have been described outside of Australia for the first time. Detection of the most pathogenic Eimeria species associated with decreased farm profitability and may be considered as an indicator of likely farm performance. While a causal link remains to be demonstrated, the presence of highly pathogenic enteric parasites may pose a threat to profitable, sustainable small-scale poultry enterprises in Africa.

Organic dairy production systems in Pennsylvania: a case study evaluation.

PubMed

Rotz, C A; Kamphuis, G H; Karsten, H D; Weaver, R D

2007-08-01

The current market demand and price for organic milk is encouraging dairy producers, particularly those on smaller farms, to consider organic production as a means for improving the economic viability of their operations. Organic production systems vary widely in scale, in practices, and across agroclimatic settings. Within this context, case studies of 4 actual organic dairy farms were used to characterize existing systems in Pennsylvania. Based on data from these farms, a whole-farm simulation model (Integrated Farm System Model) was used to compare 4 production systems representing organic grass, organic crop, conventional crop with grazing, and conventional confinement production. The performance of each of these systems was simulated over each year of 25 yr of central Pennsylvania weather data. Simulation results indicated that farm level accumulation of soil P and K may be a concern on organic farms that use poultry manure as a primary crop nutrient source, and that erosion and runoff loss of P may be of concern on organic farms producing annual crops because more tillage is required for weed control. Whole-farm budgets with prices that reflect recent conditions showed an economic advantage for organic over conventional production. A sensitivity analysis showed that this economic advantage depended on a higher milk price for producers of organic milk and was influenced by the difference in milk production maintained by herds using organic and conventional systems. Factors found to have little effect on the relative profitability of organic over conventional production included the differences between organic and conventional prices for seed, chemicals, forage, and animals and the overall costs or prices assumed for organic certification, machinery, pasture fencing, fuel, and labor. Thus, at the current organic milk price, relative to other prices, the case study organic production systems seem to provide an option for improving the economic viability of dairy operations of the scale considered in Pennsylvania. To motivate transition to organic systems, the economic advantage found requires the persistence of a substantial difference between conventional and organic raw milk prices.

Evaluating mountain goat dairy systems for conversion to the organic model, using a multicriteria method.

PubMed

Mena, Y; Nahed, J; Ruiz, F A; Sánchez-Muñoz, J B; Ruiz-Rojas, J L; Castel, J M

2012-04-01

Organic farming conserves natural resources, promotes biodiversity, guarantees animal welfare and obtains healthy products from raw materials through natural processes. In order to evaluate possibilities of increasing organic animal production, this study proposes a farm-scale multicriteria method for assessing the conversion of dairy goat systems to the organic model. In addition, a case study in the Northern Sierra of Seville, southern Spain, is analysed. A consensus of expert opinions and a field survey are used to validate a list of potential indicators and issues for assessing the conversion, which consider not only the European Community regulations for organic livestock farming, but also agroecological principles. As a result, the method includes 56 variables integrated in nine indicators: Nutritional management, Sustainable pasture management, Soil fertility and contamination, Weed and pest control, Disease prevention, Breeds and reproduction, Animal welfare, Food safety and Marketing and management. The nine indicators are finally integrated in a global index named OLPI (Organic Livestock Proximity Index). Application of the method to a case study with 24 goat farms reveals an OLPI value of 46.5% for dairy goat farms located in mountain areas of southern Spain. The aspects that differ most from the agroecological model include soil management, animal nutrition and product marketing. Results of the case study indicate that the proposed method is easy to implement and is useful for quantifying the approximation of conventional farms to an organic model.

Using wind tunnels to predict bird mortality in wind farms: the case of griffon vultures.

PubMed

de Lucas, Manuela; Ferrer, Miguel; Janss, Guyonne F E

2012-01-01

Wind farms have shown a spectacular growth during the last 15 years. Avian mortality through collision with moving rotor blades is well-known as one of the main adverse impacts of wind farms. In Spain, the griffon vulture incurs the highest mortality rates in wind farms. As far as we know, this study is the first attempt to predict flight trajectories of birds in order to foresee potentially dangerous areas for wind farm development. We analyse topography and wind flows in relation to flight paths of griffon vultures, using a scaled model of the wind farm area in an aerodynamic wind tunnel, and test the difference between the observed flight paths of griffon vultures and the predominant wind flows. Different wind currents for each wind direction in the aerodynamic model were observed. Simulations of wind flows in a wind tunnel were compared with observed flight paths of griffon vultures. No statistical differences were detected between the observed flight trajectories of griffon vultures and the wind passages observed in our wind tunnel model. A significant correlation was found between dead vultures predicted proportion of vultures crossing those cells according to the aerodynamic model. Griffon vulture flight routes matched the predominant wind flows in the area (i.e. they followed the routes where less flight effort was needed). We suggest using these kinds of simulations to predict flight paths over complex terrains can inform the location of wind turbines and thereby reduce soaring bird mortality.

Assessing manure management strategies through small-plot research and whole-farm modeling

USGS Publications Warehouse

Garcia, A.M.; Veith, T.L.; Kleinman, P.J.A.; Rotz, C.A.; Saporito, L.S.

2008-01-01

Plot-scale experimentation can provide valuable insight into the effects of manure management practices on phosphorus (P) runoff, but whole-farm evaluation is needed for complete assessment of potential trade offs. Artificially-applied rainfall experimentation on small field plots and event-based and long-term simulation modeling were used to compare P loss in runoff related to two dairy manure application methods (surface application with and without incorporation by tillage) on contrasting Pennsylvania soils previously under no-till management. Results of single-event rainfall experiments indicated that average dissolved reactive P losses in runoff from manured plots decreased by up to 90% with manure incorporation while total P losses did not change significantly. Longer-term whole farm simulation modeling indicated that average dissolved reactive P losses would decrease by 8% with manure incorporation while total P losses would increase by 77% due to greater erosion from fields previously under no-till. Differences in the two methods of inference point to the need for caution in extrapolating research findings. Single-event rainfall experiments conducted shortly after manure application simulate incidental transfers of dissolved P in manure to runoff, resulting in greater losses of dissolved reactive P. However, the transfer of dissolved P in applied manure diminishes with time. Over the annual time frame simulated by whole farm modeling, erosion processes become more important to runoff P losses. Results of this study highlight the need to consider the potential for increased erosion and total P losses caused by soil disturbance during incorporation. This study emphasizes the ability of modeling to estimate management practice effectiveness at the larger scales when experimental data is not available.

Spatial analysis and characteristics of pig farming in Thailand.

PubMed

Thanapongtharm, Weerapong; Linard, Catherine; Chinson, Pornpiroon; Kasemsuwan, Suwicha; Visser, Marjolein; Gaughan, Andrea E; Epprech, Michael; Robinson, Timothy P; Gilbert, Marius

2016-10-06

In Thailand, pig production intensified significantly during the last decade, with many economic, epidemiological and environmental implications. Strategies toward more sustainable future developments are currently investigated, and these could be informed by a detailed assessment of the main trends in the pig sector, and on how different production systems are geographically distributed. This study had two main objectives. First, we aimed to describe the main trends and geographic patterns of pig production systems in Thailand in terms of pig type (native, breeding, and fattening pigs), farm scales (smallholder and large-scale farming systems) and type of farming systems (farrow-to-finish, nursery, and finishing systems) based on a very detailed 2010 census. Second, we aimed to study the statistical spatial association between these different types of pig farming distribution and a set of spatial variables describing access to feed and markets. Over the last decades, pig population gradually increased, with a continuously increasing number of pigs per holder, suggesting a continuing intensification of the sector. The different pig-production systems showed very contrasted geographical distributions. The spatial distribution of large-scale pig farms corresponds with that of commercial pig breeds, and spatial analysis conducted using Random Forest distribution models indicated that these were concentrated in lowland urban or peri-urban areas, close to means of transportation, facilitating supply to major markets such as provincial capitals and the Bangkok Metropolitan region. Conversely the smallholders were distributed throughout the country, with higher densities located in highland, remote, and rural areas, where they supply local rural markets. A limitation of the study was that pig farming systems were defined from the number of animals per farm, resulting in their possible misclassification, but this should have a limited impact on the main patterns revealed by the analysis. The very contrasted distribution of different pig production systems present opportunities for future regionalization of pig production. More specifically, the detailed geographical analysis of the different production systems will be used to spatially-inform planning decisions for pig farming accounting for the specific health, environment and economical implications of the different pig production systems.

Reference Manual for the System Advisor Model's Wind Power Performance Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Freeman, J.; Jorgenson, J.; Gilman, P.

2014-08-01

This manual describes the National Renewable Energy Laboratory's System Advisor Model (SAM) wind power performance model. The model calculates the hourly electrical output of a single wind turbine or of a wind farm. The wind power performance model requires information about the wind resource, wind turbine specifications, wind farm layout (if applicable), and costs. In SAM, the performance model can be coupled to one of the financial models to calculate economic metrics for residential, commercial, or utility-scale wind projects. This manual describes the algorithms used by the wind power performance model, which is available in the SAM user interface andmore » as part of the SAM Simulation Core (SSC) library, and is intended to supplement the user documentation that comes with the software.« less

Modelling the interactions between C and N farm balances and GHG emissions from confinement dairy farms in northern Spain.

PubMed

Del Prado, A; Mas, K; Pardo, G; Gallejones, P

2013-11-01

There is world-wide concern for the contribution of dairy farming to global warming. However, there is still a need to improve the quantification of the C-footprint of dairy farming systems under different production systems and locations since most of the studies (e.g. at farm-scale or using LCA) have been carried out using too simplistic and generalised approaches. A modelling approach integrating existing and new sub-models has been developed and used to simulate the C and N flows and to predict the GHG burden of milk production (from the cradle to the farm gate) from 17 commercial confinement dairy farms in the Basque Country (northern Spain). We studied the relationship between their GHG emissions, and their management and economic performance. Additionally, we explored some of the effects on the GHG results of the modelling methodology choice. The GHG burden values resulting from this study (0.84-2.07 kg CO2-eq kg(-l) milk ECM), although variable, were within the range of values of existing studies. It was evidenced, however, that the methodology choice used for prediction had a large effect on the results. Methane from the rumen and manures, and N2O emissions from soils comprised most of the GHG emissions for milk production. Diet was the strongest factor explaining differences in GHG emissions from milk production. Moreover, the proportion of feed from the total cattle diet that could have directly been used to feed humans (e.g. cereals) was a good indicator to predict the C-footprint of milk. Not only were some other indicators, such as those in relation with farm N use efficiency, good proxies to estimate GHG emissions per ha or per kg milk ECM (C-footprint of milk) but they were also positively linked with farm economic performance. Copyright © 2013 Elsevier B.V. All rights reserved.

Analytical Model for Mean Flow and Fluxes of Momentum and Energy in Very Large Wind Farms

NASA Astrophysics Data System (ADS)

Markfort, Corey D.; Zhang, Wei; Porté-Agel, Fernando

2018-01-01

As wind-turbine arrays continue to be installed and the array size continues to grow, there is an increasing need to represent very large wind-turbine arrays in numerical weather prediction models, for wind-farm optimization, and for environmental assessment. We propose a simple analytical model for boundary-layer flow in fully-developed wind-turbine arrays, based on the concept of sparsely-obstructed shear flows. In describing the vertical distribution of the mean wind speed and shear stress within wind farms, our model estimates the mean kinetic energy harvested from the atmospheric boundary layer, and determines the partitioning between the wind power captured by the wind turbines and that absorbed by the underlying land or water. A length scale based on the turbine geometry, spacing, and performance characteristics, is able to estimate the asymptotic limit for the fully-developed flow through wind-turbine arrays, and thereby determine if the wind-farm flow is fully developed for very large turbine arrays. Our model is validated using data collected in controlled wind-tunnel experiments, and its usefulness for the prediction of wind-farm performance and optimization of turbine-array spacing are described. Our model may also be useful for assessing the extent to which the extraction of wind power affects the land-atmosphere coupling or air-water exchange of momentum, with implications for the transport of heat, moisture, trace gases such as carbon dioxide, methane, and nitrous oxide, and ecologically important oxygen.

Use of Chemical Pesticides in Ethiopia: A Cross-Sectional Comparative Study on Knowledge, Attitude and Practice of Farmers and Farm Workers in Three Farming Systems.

PubMed

Negatu, Beyene; Kromhout, Hans; Mekonnen, Yalemtshay; Vermeulen, Roel

2016-06-01

Chemical pesticides, regardless of their inherent hazard, are used intensively in the fast changing agricultural sector of Ethiopia. We conducted a cross-sectional pesticide Knowledge, Attitude and Practice (KAP) survey among 601 farmers and farm workers (applicators and re-entry workers) in three farming systems [large-scale closed greenhouses (LSGH), large-scale open farms (LSOF), and small-scale irrigated farms (SSIF)]. Main observations were that 85% of workers did not attain any pesticide-related training, 81% were not aware of modern alternatives for chemical pesticides, 10% used a full set of personal protective equipment, and 62% did not usually bath or shower after work. Among applicators pesticide training attendance was highest in LSGH (35%) and was lowest in SSIF (4%). None of the female re-entry farm workers had received pesticide-related training. Personal protective equipment use was twice as high among pesticide applicators as among re-entry workers (13 versus 7%), while none of the small-scale farm workers used personal protection equipment. Stockpiling and burial of empty pesticide containers and discarding empty pesticide containers in farming fields were reported in both LSOF and by 75% of the farm workers in SSIF. Considerable increment in chemical pesticide usage intensity, illegitimate usages of DDT and Endosulfan on food crops and direct import of pesticides without the formal Ethiopian registration process were also indicated. These results point out a general lack of training and knowledge regarding the safe use of pesticides in all farming systems but especially among small-scale farmers. This in combination with the increase in chemical pesticide usage in the past decade likely results in occupational and environmental health risks. Improved KAP that account for institutional difference among various farming systems and enforcement of regulatory measures including the available occupational and environmental proclamations in Ethiopia are urgently needed. © The Author 2016. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.

Benthic processes and coastal aquaculture: merging models and field data at a local scale

NASA Astrophysics Data System (ADS)

Brigolin, Daniele; Rabouille, Christophe; Bombled, Bruno; Colla, Silvia; Pastres, Roberto; Pranovi, Fabio

2016-04-01

Shellfish farming is regarded as an organic extractive aquaculture activity. However, the production of faeces and pseudofaeces, in fact, leads to a net transfer of organic matter from the water column to the surface sediment. This process, which is expected to locally affect the sediment biogeochemistry, may also cause relevant changes in coastal areas characterized by a high density of farms. In this paper, we present the result of a study recently carried out in the Gulf of Venice (northern Adriatic sea), combining mathematical modelling and field sampling efforts. The work aimed at using a longline mussel farm as an in-situ test-case for modelling the differences in soft sediments biogeochemical processes along a gradient of organic deposition. We used an existing integrated model, allowing to describe biogeochemical fluxes towards the mussel farm and to predict the extent of the deposition area underneath it. The model framework includes an individual-based population dynamic model of the Mediterranean mussel coupled with a Lagrangian deposition model and a 1D benthic model of early diagenesis. The work was articulated in 3 steps: 1) the integrated model allowed to simulate the downward fluxes of organic matter originated by the farm, and the extent of its deposition area; 2) based on the first model application, two stations were localized, at which sediment cores were collected during a field campaign, carried out in June 2015. Measurements included O2 and pH microprofiling, porosity and micro-porosity, Total Organic Carbon, and pore waters NH4, PO4, SO4, Alkalinity, and Dissolved Inorganic Carbon; 3) two distinct early diagenesis models were set-up, reproducing observed field data in the sampled cores. Observed oxygen microprofiles showed a different behavior underneath the farm with respect to the outside reference station. In particular, a remarkable decrease in the oxygen penetration depth, and an increase in the O2 influx calculated from the concentration gradients were observed. The integrated model described above allowed to extend the simulation over the entire farmed area, and to explore the response of the prediction to changes in water temperature.

Can tidal energy farms create temperature fronts in the coastal ocean?

NASA Astrophysics Data System (ADS)

Shapiro, G. I.

2012-04-01

Although an industrial scale tidal farm comprising a large set of submerged turbines has not been built yet, tidal power is considered to be one of potential sources of renewable energy in the future. For example, India plans to install a 50MW tidal farm in the Gulf of Kutch which could be further expanded to deliver more than 200MW. As tidal stream generators extract kinetic energy from the ocean currents, they change the circulation pattern and hence affect the marine environment. Recent research has shown ( Shapiro, 2011, Neill et al., 2009) that a tidal farm can modify currents and sediment transport outside the farm as far as up to a hundred kilometres. This paper studies the potential effect of a tidal farm on the temperature structure in a shallow sea using a 3D ocean model POLCOMS which was modified to include effects of kinetic energy extraction as detailed in (Shapiro, 2011). The model is set up in the Celtic Sea known for its high levels of tidal energy. The model is driven by 15 tidal constituents and the meteo forcing. Effects of tidal farms of varying sizes and power capacities (from 50 MW to 1500MW) have been studied during summer months. The simulated farms are placed in various locations north of the Cornish coast. It has been shown that even smaller farms can modify temperature distribution as far as a few tens of kilometres from the farm, and sometimes generate localised temperature fronts. This effect is particularly strong during the month of June when the fronts penetrate from surface to the seabed. The fronts are more pronounced during the spring tides, however they are still seen during the neaps. As the seasonal thermocline strengthens towards the end of summer, the fronts are mostly seen in the upper ocean layer, with warmer waters in the area of the farm and cooler waters outside the farm. The physical mechanism of front generation is linked to abrupt changes in the current patterns due to energy extraction from the ocean. The currents inside the farm become weaker, whilst the currents outside the farm ( at a scale comparable to the baroclinic Rossby radius) become stronger. Such stronger currents enhance the mixing of the water column outside the farm, and weaker currents inside the farm reduce turbulent mixing and facilitate formation of a stronger thermocline. The overall effect is generally similar to the formation of fronts between tidally mixed and stratified areas of a shallow sea (Simpson and Hunter, 1974). Effect of geometrically smaller farms is less pronounced as the water particles travel in and out the affected zone during the tidal cycle (over the length of the tidal excursion) and hence are influenced by the above mechanism only during a proportion of the tidal cycle. Reduced vertical mixing within the area of the farm and positive heat balance explains higher temperatures at the surface. In the beginning of summer when thermal stratification is relatively week, the thermocline is significantly altered and the fronts propagate to a greater depth. Development of a stronger thermocline towards the end of summer inhibits the effect of mixing and the fluctuations of the depth of the upper mixed layer due to energy extraction are suppressed .

Economic and financial viability of small-scale dairy systems in central Mexico: economic scenario 2010-2018.

PubMed

Posadas-Domínguez, R R; Callejas-Juárez, N; Arriaga-Jordán, C M; Martínez-Castañeda, F E

2016-12-01

A simulation Monte Carlo model was used to assess the economic and financial viability of 130 small-scale dairy farms in central Mexico, through a Representative Small-Scale Dairy Farm. Net yields were calculated for a 9-year planning horizon by means of simulated values for the distribution of input and product prices taking 2010 as base year and considering four scenarios which were compared against the scenario of actual production. The other scenarios were (1) total hiring in of needed labour; (2) external purchase of 100 % of inputs and (3) withdrawal of subsidies to production. A stochastic modelling approach was followed to determine the scenario with the highest economic and financial viability. Results show a viable economic and financial situation for the real production scenario, as well as the scenarios for total hiring of labour and of withdrawal of subsidies, but the scenario when 100 % of feed inputs for the herd are bought-in was not viable.

Spatial downscaling of soil prediction models based on weighted generalized additive models in smallholder farm settings.

PubMed

Xu, Yiming; Smith, Scot E; Grunwald, Sabine; Abd-Elrahman, Amr; Wani, Suhas P; Nair, Vimala D

2017-09-11

Digital soil mapping (DSM) is gaining momentum as a technique to help smallholder farmers secure soil security and food security in developing regions. However, communications of the digital soil mapping information between diverse audiences become problematic due to the inconsistent scale of DSM information. Spatial downscaling can make use of accessible soil information at relatively coarse spatial resolution to provide valuable soil information at relatively fine spatial resolution. The objective of this research was to disaggregate the coarse spatial resolution soil exchangeable potassium (K ex ) and soil total nitrogen (TN) base map into fine spatial resolution soil downscaled map using weighted generalized additive models (GAMs) in two smallholder villages in South India. By incorporating fine spatial resolution spectral indices in the downscaling process, the soil downscaled maps not only conserve the spatial information of coarse spatial resolution soil maps but also depict the spatial details of soil properties at fine spatial resolution. The results of this study demonstrated difference between the fine spatial resolution downscaled maps and fine spatial resolution base maps is smaller than the difference between coarse spatial resolution base maps and fine spatial resolution base maps. The appropriate and economical strategy to promote the DSM technique in smallholder farms is to develop the relatively coarse spatial resolution soil prediction maps or utilize available coarse spatial resolution soil maps at the regional scale and to disaggregate these maps to the fine spatial resolution downscaled soil maps at farm scale.

Experimental Study of Aligned and Staggered Wind Farms in a Convective Boundary Layer

NASA Astrophysics Data System (ADS)

Markfort, Corey; Zhang, Wei; Porte-Agel, Fernando

2011-11-01

Wind farm-atmosphere interaction is complicated by turbine configuration and thermal effects on momentum and kinetic energy fluxes. Wind farms of finite length have been modeled as increased surface roughness or as a sparse canopy; however it is not clear which approach is more appropriate. Experiments were conducted in a thermally controlled boundary layer wind tunnel, using a custom x-wire/cold wire and surface heat flux sensors, to understand the effect of aligned versus staggered turbine configurations on momentum absorption and flow adjustment in a convective boundary layer (CBL). Results for experiments of a large farm show the span-wise averaged flow statistics exhibit similar turbulent transport properties to that of canopy flows. The wake adjusts within and grows over the farm more quickly for a staggered compared to an aligned farm. Using canopy flow scaling, we show that the flow equilibrates faster and the overall momentum absorption is higher in a staggered compared to an aligned farm. Wake recovery behind a single turbine is facilitated by buoyancy in a CBL (Zhang et al. under review). We find a similar effect in wind farms resulting in reduced effective roughness and momentum absorption. We also find a reduction of surface heat flux for both wind farms, but greater for the staggered farm.

The economic efficiency of conservation measures for amphibians in organic farming--results from bio-economic modelling.

PubMed

Schuler, Johannes; Sattler, Claudia; Helmecke, Angela; Zander, Peter; Uthes, Sandra; Bachinger, Johann; Stein-Bachinger, Karin

2013-01-15

This paper presents a whole farm bio-economic modelling approach for the assessment and optimisation of amphibian conservation conditions applied at the example of a large scale organic farm in North-Eastern Germany. The assessment focuses mainly on the habitat quality as affected by conservation measures such as through specific adapted crop production activities (CPA) and in-field buffer strips for the European tree frog (Hyla arborea), considering also interrelations with other amphibian species (i.e. common spadefoot toad (Pelobates fuscus), fire-bellied toad (Bombina bombina)). The aim of the approach is to understand, analyse and optimize the relationships between the ecological and economic performance of an organic farming system, based on the expectation that amphibians are differently impacted by different CPAs. The modelling system consists of a set of different sub-models that generate a farm model on the basis of environmentally evaluated CPAs. A crop-rotation sub-model provides a set of agronomically sustainable crop rotations that ensures overall sufficient nitrogen supply and controls weed, pest and disease infestations. An economic sub-model calculates the gross margins for each possible CPA including costs of inputs such as labour and machinery. The conservation effects of the CPAs are assessed with an ecological sub-model evaluates the potential negative or positive effect that each work step of a CPA has on amphibians. A mathematical programming sub-model calculates the optimal farm organization taking into account the limited factors of the farm (e.g. labour, land) as well as ecological improvements. In sequential model runs, the habitat quality is to be improved by the model, while the highest possible gross margin is still to be achieved. The results indicate that the model can be used to show the scope of action that a farmer has to improve habitat quality by reducing damage to amphibian population on its land during agricultural activities. Thereby, depending on the level of habitat quality that is aimed at, different measures may provide the most efficient solution. Lower levels of conservation can be achieved with low-cost adapted CPAs, such as an increased cutting height, reduced sowing density and grubbing instead of ploughing. Higher levels of conservation require e.g. grassland-like managed buffer strips around ponds in sensible areas, which incur much higher on-farm conservation costs. Copyright © 2012 Elsevier Ltd. All rights reserved.

Fine-scale mapping of vector habitats using very high resolution satellite imagery: a liver fluke case-study.

PubMed

De Roeck, Els; Van Coillie, Frieke; De Wulf, Robert; Soenen, Karen; Charlier, Johannes; Vercruysse, Jozef; Hantson, Wouter; Ducheyne, Els; Hendrickx, Guy

2014-12-01

The visualization of vector occurrence in space and time is an important aspect of studying vector-borne diseases. Detailed maps of possible vector habitats provide valuable information for the prediction of infection risk zones but are currently lacking for most parts of the world. Nonetheless, monitoring vector habitats from the finest scales up to farm level is of key importance to refine currently existing broad-scale infection risk models. Using Fasciola hepatica, a parasite liver fluke, as a case in point, this study illustrates the potential of very high resolution (VHR) optical satellite imagery to efficiently and semi-automatically detect detailed vector habitats. A WorldView2 satellite image capable of <5m resolution was acquired in the spring of 2013 for the area around Bruges, Belgium, a region where dairy farms suffer from liver fluke infections transmitted by freshwater snails. The vector thrives in small water bodies (SWBs), such as ponds, ditches and other humid areas consisting of open water, aquatic vegetation and/or inundated grass. These water bodies can be as small as a few m2 and are most often not present on existing land cover maps because of their small size. We present a classification procedure based on object-based image analysis (OBIA) that proved valuable to detect SWBs at a fine scale in an operational and semi-automated way. The classification results were compared to field and other reference data such as existing broad-scale maps and expert knowledge. Overall, the SWB detection accuracy reached up to 87%. The resulting fine-scale SWB map can be used as input for spatial distribution modelling of the liver fluke snail vector to enable development of improved infection risk mapping and management advice adapted to specific, local farm situations.

White meat-Green farm: case study of Brinson Farms

USDA-ARS?s Scientific Manuscript database

Comprehensive on-farm resource utilization and renewable energy generation at the farm scale are not new concepts. However, truly encompassing implementation of these ideals is lacking. Brinson Farms operates 10 commercial broiler houses. The farm generates heat for its houses using biomass boile...

Characteristics of Nitrogen Balances of Large-scale Stock Farms and Reduction of Environmental Nitrogen Loads

NASA Astrophysics Data System (ADS)

Hattori, Toshihiro; Takamatsu, Rieko

We calculated nitrogen balances on farm gate and soil surface on large-scale stock farms and discussed methods for reducing environmental nitrogen loads. Four different types of public stock farms (organic beef, calf supply and daily cows) were surveyed in Aomori Prefecture. (1) Farm gate and soil surface nitrogen inflows were both larger than the respective outflows on all types of farms. Farm gate nitrogen balance for beef farms were worse than that for dairy farms. (2) Soil surface nitrogen outflows and soil nitrogen retention were in proportion to soil surface nitrogen inflows. (3) Reductions in soil surface nitrogen retention were influenced by soil surface nitrogen inflows. (4) In order to reduce farm gate nitrogen retention, inflows of formula feed and chemical fertilizer need to be reduced. (5) In order to reduce soil surface nitrogen retention, inflows of fertilizer need to be reduced and nitrogen balance needs to be controlled.

Spatial organization of agricultural landscape, farming activities and hydrological risk assessment

NASA Astrophysics Data System (ADS)

Viaud, V.; Merot, P.

2003-04-01

Agriculture intensification is considered as a major cause of water pollution since it has gone both with an increasing use of fertilisers and significant changes in land-use patterns. Among the prescriptions for pollution control, the management of buffer zones at the landscape scale is supported by the environmental policies, but often without consideration of the systems of human activities they are aimed at. Agricultural landscapes, with fields potentially source of pollution and buffer zones, are spatially organized and managed by farming activities. In a perspective of sustainable management, an integrating approach of environmental issues and farming activities is thus required. This approach was applied to bocage landscapes (landscapes with cultivated fields surrounded by hedgerow systems) in Brittany (Western France). Bocage landscapes are frequently encountered, especially in Europe, and many studies put forward their hydrological and hydrochemical buffer functions. Those results provide informations on the link between spatial organization of hedgerow systems and their environmental effectiveness. They enable to design models of functional bocage landscapes. The objective of this work was to pick out, among those theoretical models, the models compatible with the farming activities. The results will be presented and the additional constraints for the farming systems created by a functional landscape, from a hydrological and hydrochemical perspective, will be discussed.

Network analysis of swine shipments in Ontario, Canada, to support disease spread modelling and risk-based disease management.

PubMed

Dorjee, S; Revie, C W; Poljak, Z; McNab, W B; Sanchez, J

2013-10-01

Understanding contact networks are important for modelling and managing the spread and control of communicable diseases in populations. This study characterizes the swine shipment network of a multi-site production system in southwestern Ontario, Canada. Data were extracted from a company's database listing swine shipments among 251 swine farms, including 20 sow, 69 nursery and 162 finishing farms, for the 2-year period of 2006 to 2007. Several network metrics were generated. The number of shipments per week between pairs of farms ranged from 1 to 6. The medians (and ranges) of out-degree were: sow 6 (1-21), nursery 8 (0-25), and finishing 0 (0-4), over the entire 2-year study period. Corresponding estimates for in-degree of nursery and finishing farms were 3 (0-9) and 3 (0-12) respectively. Outgoing and incoming infection chains (OIC and IIC), were also measured. The medians (ranges) of the monthly OIC and IIC were 0 (0-8) and 0 (0-6), respectively, with very similar measures observed for 2-week intervals. Nursery farms exhibited high measures of centrality. This indicates that they pose greater risks of disease spread in the network. Therefore, they should be given a high priority for disease prevention and control measures affecting all age groups alike. The network demonstrated scale-free and small-world topologies as observed in other livestock shipment studies. This heterogeneity in contacts among farm types and network topologies should be incorporated in simulation models to improve their validity. In conclusion, this study provided useful epidemiological information and parameters for the control and modelling of disease spread among swine farms, for the first time from Ontario, Canada. Copyright © 2013 Elsevier B.V. All rights reserved.

Risk for highly pathogenic avian influenza H5N1 virus infection in chickens in small-scale commercial farms, in a high-risk area, Bangladesh, 2008.

PubMed

Biswas, P K; Rahman, M H; Das, A; Ahmed, S S U; Giasuddin, M; Christensen, J P

2011-12-01

Small-scale commercial chicken farms (FAO-defined system 3) with poor biosecurity predominate in developing countries including Bangladesh. By enroling fifteen highly pathogenic avian influenza (HPAI) cases occurring in such farms - (February - April 2008) and 45 control farms (March-May 2008) with similar set up, we conducted a case-control study to evaluate the risk factors associated with HPAI H5N1 virus infections in chickens reared in small-scale commercial farms in a spatially high-risk area in Bangladesh. Data collected by a questionnaire from the selected farms were analysed by univariable analysis and multivariable conditional logistic regression. The risk factors independently associated were 'dead crow seen at or near farm' [odds ratio (OR) 47.4, 95% confidence interval (CI) 4.7-480.3, P = 0.001], 'exchanging eggtrays with market vendors' (OR 20.4, 95% CI 1.9-225.5, P = 0.014) and 'mortality seen in backyard chicken reared nearby' (OR 19.4, 95% CI 2.8-131.9, P = 0.002). These observations suggest that improved biosecurity might reduce the occurrence of HPAI outbreaks in small-scale commercial farms in Bangladesh. © 2011 Blackwell Verlag GmbH.

Fact sheets and slides summarizing Soil and Water Assessment Tool (SWAT) and Integrated Farm Systems Model (IFSM)

USDA-ARS?s Scientific Manuscript database

Water quality models address nonpoint source pollution from agricultural land at a range of scales and complexities and involve a variety of input parameters. It is often difficult for conservationists and stakeholders to understand and reconcile water quality results from different models. However,...

Ute Mountain Ute Tribe Community-Scale Solar Feasibility Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rapp, Jim; Knight, Tawnie

2014-01-30

Parametrix Inc. conducted a feasibility study for the Ute Mountain Ute Tribe to determine whether or not a community-scale solar farm would be feasible for the community. The important part of the study was to find where the best fit for the solar farm could be. In the end, a 3MW community-scale solar farm was found best fit with the location of two hayfield sites.

Assessment of the sustainability of dual-purpose farms by the IDEA method in the subtropical area of central Mexico.

PubMed

Salas-Reyes, Isela Guadalupe; Arriaga-Jordán, Carlos Manuel; Rebollar-Rebollar, Samuel; García-Martínez, Anastacio; Albarrán-Portillo, Benito

2015-08-01

The objective of this study was to assess the sustainability of 10 dual-purpose cattle farms in a subtropical area of central Mexico. The IDEA method (Indicateurs de Durabilité des Exploitations Agricoles) was applied, which includes the agroecological, socio-territorial and economic scales (scores from 0 to 100 points per scale). A sample of 47 farms from a total of 91 registered in the local livestock growers association was analysed with principal component analysis and cluster analysis. From results, 10 farms were selected for the in-depth study herein reported, being the selection criterion continuous milk production throughout the year. Farms had a score of 88 and 86 points for the agroecological scale in the rainy and dry seasons. In the socio-territorial scale, scores were 73 points for both seasons, being the component of employment and services the strongest. Scores for the economic scale were 64 and 56 points for the rainy and dry seasons, respectively, when no economic cost for family labour is charged, which decreases to 59 and 45 points when an opportunity cost for family labour is considered. Dual-purpose farms in the subtropical area of central Mexico have a medium sustainability, with the economic scale being the limiting factor, and an area of opportunity.

Farm nitrogen balances in six European landscapes as an indicator for nitrogen losses and basis for improved management

NASA Astrophysics Data System (ADS)

Dalgaard, T.; Bienkowski, J. F.; Bleeker, A.; Dragosits, U.; Drouet, J. L.; Durand, P.; Frumau, A.; Hutchings, N. J.; Kedziora, A.; Magliulo, V.; Olesen, J. E.; Theobald, M. R.; Maury, O.; Akkal, N.; Cellier, P.

2012-12-01

Improved management of nitrogen (N) in agriculture is necessary to achieve a sustainable balance between the production of food and other biomass, and the unwanted effects of N on water pollution, greenhouse gas emissions, biodiversity deterioration and human health. To analyse farm N-losses and the complex interactions within farming systems, efficient methods for identifying emissions hotspots and evaluating mitigation measures are therefore needed. The present paper aims to fill this gap at the farm and landscape scales. Six agricultural landscapes in Poland (PL), the Netherlands (NL), France (FR), Italy (IT), Scotland (UK) and Denmark (DK) were studied, and a common method was developed for undertaking farm inventories and the derivation of farm N balances, N surpluses and for evaluating uncertainty for the 222 farms and 11 440 ha of farmland included in the study. In all landscapes, a large variation in the farm N surplus was found, and thereby a large potential for reductions. The highest average N surpluses were found in the most livestock-intensive landscapes of IT, FR, and NL; on average 202 ± 28, 179 ± 63 and 178 ± 20 kg N ha-1 yr-1, respectively. All landscapes showed hotspots, especially from livestock farms, including a special UK case with large-scale landless poultry farming. Overall, the average N surplus from the land-based UK farms dominated by extensive sheep and cattle grazing was only 31 ± 10 kg N ha-1 yr-1, but was similar to the N surplus of PL and DK (122 ± 20 and 146 ± 55 kg N ha-1 yr-1, respectively) when landless poultry farming was included. We found farm N balances to be a useful indicator for N losses and the potential for improving N management. Significant correlations to N surplus were found, both with ammonia air concentrations and nitrate concentrations in soils and groundwater, measured during the period of N management data collection in the landscapes from 2007-2009. This indicates that farm N surpluses may be used as an independent dataset for validation of measured and modelled N emissions in agricultural landscapes. No significant correlation was found with N measured in surface waters, probably because of spatial and temporal variations in groundwater buffering and biogeochemical reactions affecting N flows from farm to surface waters. A case study of the development in N surplus from the landscape in DK from 1998-2008 showed a 22% reduction related to measures targeted at N emissions from livestock farms. Based on the large differences in N surplus between average N management farms and the most modern and N-efficient farms, it was concluded that additional N-surplus reductions of 25-50%, as compared to the present level, were realistic in all landscapes. The implemented N-surplus method was thus effective for comparing and synthesizing results on farm N emissions and the potentials of mitigation options. It is recommended for use in combination with other methods for the assessment of landscape N emissions and farm N efficiency, including more detailed N source and N sink hotspot mapping, measurements and modelling.

Integrating watershed– and farm–scale models to target critical source areas while maintaining farm economic viability

USDA-ARS?s Scientific Manuscript database

Nonpoint source pollution from agriculture and the impacts of mitigating best management practices are commonly evaluated based on hydrologic boundaries using watershed models. However, management practice effectiveness is impacted by which of the feasible practices are actually selected, implemente...

Structural equation modeling of the relationships between pesticide poisoning, depressive symptoms and safety behaviors among Colorado farm residents.

PubMed

Beseler, Cheryl Lynn; Stallones, Lorann

2006-01-01

To use structural equation modeling (SEM) to test the theory that a past pesticide poisoning may act as a mediator in the relationship between depression and safety practices. Depression has been associated with pesticide poisoning and was more strongly associated with safety behaviors than workload, social support or health status of farm residents in a previously published report. A cross-sectional survey of farmers and their spouses was conducted in eight counties in northeastern Colorado. Depressive symptoms were assessed using the Center for Epidemiologic Studies-Depression (CES-D) scale. Exploratory and confirmatory factor analyses were used to identify symptoms most correlated with risk factors for depression and safety practices. SEM was used to examine theoretical causal models of the relationship between depression and poor health, financial difficulties, a history of pesticide poisoning, and safety practices. Exploratory factor analysis identified three factors in the CES-D scale. The SEM showed that poor health, financial difficulties and a history of pesticide poisoning significantly explained the depressive symptoms. Models with an excellent fit for the safety behaviors resulted when modeling the probability that the pesticide poisoning preceded depression, but no fit was possible when reversing the direction and modeling depression preceding pesticide poisoning. Specific depressive symptoms appeared to be significantly associated with primarily animal handling and farm machinery. The order of events, based on SEM results, was a pesticide poisoning preceding depressed mood in relation to safety behaviors.

Using Wind Tunnels to Predict Bird Mortality in Wind Farms: The Case of Griffon Vultures

PubMed Central

de Lucas, Manuela; Ferrer, Miguel; Janss, Guyonne F. E.

2012-01-01

Background Wind farms have shown a spectacular growth during the last 15 years. Avian mortality through collision with moving rotor blades is well-known as one of the main adverse impacts of wind farms. In Spain, the griffon vulture incurs the highest mortality rates in wind farms. Methodology/Principal Findings As far as we know, this study is the first attempt to predict flight trajectories of birds in order to foresee potentially dangerous areas for wind farm development. We analyse topography and wind flows in relation to flight paths of griffon vultures, using a scaled model of the wind farm area in an aerodynamic wind tunnel, and test the difference between the observed flight paths of griffon vultures and the predominant wind flows. Different wind currents for each wind direction in the aerodynamic model were observed. Simulations of wind flows in a wind tunnel were compared with observed flight paths of griffon vultures. No statistical differences were detected between the observed flight trajectories of griffon vultures and the wind passages observed in our wind tunnel model. A significant correlation was found between dead vultures predicted proportion of vultures crossing those cells according to the aerodynamic model. Conclusions Griffon vulture flight routes matched the predominant wind flows in the area (i.e. they followed the routes where less flight effort was needed). We suggest using these kinds of simulations to predict flight paths over complex terrains can inform the location of wind turbines and thereby reduce soaring bird mortality. PMID:23152764

Assessing the production and economic benefits from preventing cows grazing on wet soils in New Zealand.

PubMed

Laurenson, Seth; Houlbrooke, David J; Beukes, Pierre C

2016-10-01

Intensive grazing by cattle on wet pasture can have a negative effect on soil physical quality and future pasture production. On a North Otago dairy farm in New Zealand, experimental plots were monitored for four years to assess whether preventing cow grazing of wet pastures during the milking season would improve soil structure and pasture production compared with unrestricted access to pastures. The DairyNZ Whole Farm Model was used to scale up results to a farm system level and ascertain the cost benefit of deferred grazing management. Soils under deferred grazing management had significantly higher total porosity, yet no significant improvement in macroporosity (values ranging between 0.112 and 0.146 m(3)  m(-3) ). Annual pasture production did not differ between the control and deferred grazing treatments, averaging 17.0 ± 3.8 and 17.9 ± 4.1 t DM ha(-1) year(-1) respectively (P > 0.05). Furthermore, whole farm modelling indicated that farm operating profit was reduced by NZ$1683 ha(-1) year(-1) (four-year average) under deferred grazing management. Deferring dairy cow grazing from wet Pallic soils in North Otago was effective in improving soil structure (measured as total soil porosity), yet did not lead to a significant increase in pasture production. Whole farm modelling indicated no economic benefit of removing cows from wet soils during the milking season. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Short-term wind speed prediction based on the wavelet transformation and Adaboost neural network

NASA Astrophysics Data System (ADS)

Hai, Zhou; Xiang, Zhu; Haijian, Shao; Ji, Wu

2018-03-01

The operation of the power grid will be affected inevitably with the increasing scale of wind farm due to the inherent randomness and uncertainty, so the accurate wind speed forecasting is critical for the stability of the grid operation. Typically, the traditional forecasting method does not take into account the frequency characteristics of wind speed, which cannot reflect the nature of the wind speed signal changes result from the low generality ability of the model structure. AdaBoost neural network in combination with the multi-resolution and multi-scale decomposition of wind speed is proposed to design the model structure in order to improve the forecasting accuracy and generality ability. The experimental evaluation using the data from a real wind farm in Jiangsu province is given to demonstrate the proposed strategy can improve the robust and accuracy of the forecasted variable.

Social environments, risk-taking and injury in farm adolescents

PubMed Central

Pickett, William; Berg, Richard L; Marlenga, Barbara

2017-01-01

Background Farm environments are especially hazardous for young people. While much is known about acute physical causes of traumatic farm injury, little is known about social factors that may underlie their aetiology. Objectives In a nationally representative sample of young Canadians aged 11–15 years, we described and compared farm and non-farm adolescents in terms of the qualities of their social environments, engagement in overt multiple risk-taking as well as how such exposures relate aetiologically to their reported injury experiences. Methods Cross-sectional analysis of survey reports from the 2014 (Cycle 7) Canadian Health Behaviour in School-Aged Children study was conducted. Children (n=2567; 2534 weighted) who reported living or working on farms were matched within schools in a 1:1 ratio with children not living or working on farms. Scales examining quality of social environments and overt risk-taking were compared between the two groups, stratified by gender. We then related the occurrence of any serious injury to these social exposures in direct and interactive models. Results Farm and non-farm children reported social environments that were quite similar, with the exception of overt multiple risk-taking, which was demonstrably higher in farm children of both genders. Engagement in overt risk-taking, but not the other social environmental factors, was strongly and consistently associated with risks for serious injury in farm as well as non-farm children, particularly among males. Conclusions Study findings highlight the strength of associations between overt multiple risk-taking and injury among farm children. This appears to be a normative aspect of adolescent farm culture. PMID:28137978

Simulations of an Offshore Wind Farm Using Large-Eddy Simulation and a Torque-Controlled Actuator Disc Model

NASA Astrophysics Data System (ADS)

Creech, Angus; Früh, Wolf-Gerrit; Maguire, A. Eoghan

2015-05-01

We present here a computational fluid dynamics (CFD) simulation of Lillgrund offshore wind farm, which is located in the Øresund Strait between Sweden and Denmark. The simulation combines a dynamic representation of wind turbines embedded within a large-eddy simulation CFD solver and uses hr-adaptive meshing to increase or decrease mesh resolution where required. This allows the resolution of both large-scale flow structures around the wind farm, and the local flow conditions at individual turbines; consequently, the response of each turbine to local conditions can be modelled, as well as the resulting evolution of the turbine wakes. This paper provides a detailed description of the turbine model which simulates the interaction between the wind, the turbine rotors, and the turbine generators by calculating the forces on the rotor, the body forces on the air, and instantaneous power output. This model was used to investigate a selection of key wind speeds and directions, investigating cases where a row of turbines would be fully aligned with the wind or at specific angles to the wind. Results shown here include presentations of the spin-up of turbines, the observation of eddies moving through the turbine array, meandering turbine wakes, and an extensive wind farm wake several kilometres in length. The key measurement available for cross-validation with operational wind farm data is the power output from the individual turbines, where the effect of unsteady turbine wakes on the performance of downstream turbines was a main point of interest. The results from the simulations were compared to the performance measurements from the real wind farm to provide a firm quantitative validation of this methodology. Having achieved good agreement between the model results and actual wind farm measurements, the potential of the methodology to provide a tool for further investigations of engineering and atmospheric science problems is outlined.

Measuring wind turbine wakes and unsteady loading in a micro wind farm model

NASA Astrophysics Data System (ADS)

Bossuyt, Juliaan; Meneveau, Charles; Meyers, Johan

2014-11-01

Very large wind farms, approximating the ``infinite'' asymptotic limit, are often studied with LES using periodic boundary conditions. In order to create an experimental realization of such large wind-turbine arrays in a wind tunnel experiment including over 100 turbines, a very small-scale turbine model based on a 3 cm diameter porous disk is designed. The porous disc matches a realistic thrust coefficient between 0.75--0.85, and the far wake flow characteristics of a rotating wind turbine. As a first step, we characterize the properties of a single model turbine. Hot-wire measurements are performed for uniform inflow conditions with different background turbulence intensity levels. Strain gage measurements are used to measure the mean value and power spectra of the thrust force, power output and wind velocity in front of the turbine. The dynamics of the wind turbine are modeled making it possible to measure force spectra at least up to the natural frequency of the model. This is shown by reproducing the -5/3 spectrum from the incoming flow and the vortex shedding signatures of an upstream obstruction. An array with a large number of these instrumented model turbines is placed in JHU's Corrsin wind tunnel, to study effects of farm layout on total power output and turbine loading. Work supported by ERC (ActiveWindFarms, Grant No: 306471), and by NSF (CBET-113380 and IIA-1243482).

Wake Dynamics in the Atmospheric Boundary Layer Over Complex Terrain

NASA Astrophysics Data System (ADS)

Markfort, Corey D.

The goal of this research is to advance our understanding of atmospheric boundary layer processes over heterogeneous landscapes and complex terrain. The atmospheric boundary layer (ABL) is a relatively thin (˜ 1 km) turbulent layer of air near the earth's surface, in which most human activities and engineered systems are concentrated. Its dynamics are crucially important for biosphere-atmosphere couplings and for global atmospheric dynamics, with significant implications on our ability to predict and mitigate adverse impacts of land use and climate change. In models of the ABL, land surface heterogeneity is typically represented, in the context of Monin-Obukhov similarity theory, as changes in aerodynamic roughness length and surface heat and moisture fluxes. However, many real landscapes are more complex, often leading to massive boundary layer separation and wake turbulence, for which standard models fail. Trees, building clusters, and steep topography produce extensive wake regions currently not accounted for in models of the ABL. Wind turbines and wind farms also generate wakes that combine in complex ways to modify the ABL. Wind farms are covering an increasingly significant area of the globe and the effects of large wind farms must be included in regional and global scale models. Research presented in this thesis demonstrates that wakes caused by landscape heterogeneity must be included in flux parameterizations for momentum, heat, and mass (water vapor and trace gases, e.g. CO2 and CH4) in ABL simulation and prediction models in order to accurately represent land-atmosphere interactions. Accurate representation of these processes is crucial for the predictions of weather, air quality, lake processes, and ecosystems response to climate change. Objectives of the research reported in this thesis are: 1) to investigate turbulent boundary layer adjustment, turbulent transport and scalar flux in wind farms of varying configurations and develop an improved modeling framework for wind farm - atmosphere interaction, 2) to determine how heterogeneous patches of forest affect the structure of the ABL and its interactions with clearings and water bodies, 3) to investigate how landscape heterogeneity, including wakes, may be parameterized in regional-scale weather and climate models to improve the representation of surface fluxes, e.g. from lakes/wetlands and forest clearings. To achieve these objectives, this research employs an interdisciplinary strategy, utilizing concepts and methods from fluid mechanics, micrometeorology, ecosystem ecology and environmental sciences, and combines laboratory and field experiments. In particular, a) wind tunnel experiments of flow through and over model wind farms and model forest canopies were used to improve our fundamental understanding of how wakes affect land-atmosphere coupling, including surface fluxes, after wind farm installation and for heterogeneous landscapes of canopies and clearings or lakes, and b) extensive field studies over lakes and wetlands were undertaken to study the effects of wakes downwind of forest canopies and the effect of wind sheltering on lake stratification dynamics and gas fluxes. These experiments were also used to improve and validate numerical simulation techniques for the atmospheric boundary layer, specifically the large eddy simulation technique, which is used to simulate flow in wind farms and flow over heterogeneous terrain.

Soil Carbon Storage in Christmas Tree Farms: Maximizing Ecosystem Management and Sustainability for Carbon Sequestration

NASA Astrophysics Data System (ADS)

Chapman, S. K.; Shaw, R.; Langley, A.

2008-12-01

Management of agroecosystems for the purpose of manipulating soil carbon stocks could be a viable approach for countering rising atmospheric carbon dioxide concentrations, while maximizing sustainability of the agroforestry industry. We investigated the carbon storage potential of Christmas tree farms in the southern Appalachian mountains as a potential model for the impacts of land management on soil carbon. We quantified soil carbon stocks across a gradient of cultivation duration and herbicide management. We compared soil carbon in farms to that in adjacent pastures and native forests that represent a control group to account for variability in other soil-forming factors. We partitioned tree farm soil carbon into fractions delineated by stability, an important determinant of long-term sequestration potential. Soil carbon stocks in the intermediate pool are significantly greater in the tree farms under cultivation for longer periods of time than in the younger tree farms. This pool can be quite large, yet has the ability to repond to biological environmental changes on the centennial time scale. Pasture soil carbon was significantly greater than both forest and tree farm soil carbon, which were not different from each other. These data can help inform land management and soil carbon sequestration strategies.

Cost analysis of immunisation against east coast fever on smallholder dairy farms in Kenya.

PubMed

Muraguri, G R; Mbogo, S K; McHardy, N; Kariuki, D P

1998-03-27

A spreadsheet model was developed and used to estimate the total cost of immunising cattle against East Coast fever (ECF) based on the infection-and-treatment method. Using data from an immunisation trial carried out on 102 calves and yearlings on 64 farms in the Githunguri division, Kiambu district, Kenya, a reference base scenario of a mean herd of five animals, a 10% rate of reaction to immunisation and a 2-day interval monitoring regimen (a total of 10 farm visits) was simulated. Under these conditions, the mean cost of immunisation per animal was US$16.48 (Ksh 955.78); this was equivalent to US$82.39 (Ksh 4778.90) per five-animal farm. A commonly reported reactor rate of 3% would decrease the cost of US$14.63 (Ksh 848.29) per animal. Reducing the number of farm monitoring visits from 10 to 7 would reduce the total cost by 10%, justified if farmers are trained to undertake some of the monitoring work. The fixed costs were 53% of the total cost of immunisation per farm. The cost of immunisation decreased with increasing number of animals per farm, showing economies of scale.

Drivers and risk factors for circulating African swine fever virus in Uganda, 2012-2013.

PubMed

Kabuuka, T; Kasaija, P D; Mulindwa, H; Shittu, A; Bastos, A D S; Fasina, F O

2014-10-01

We explored observed risk factors and drivers of infection possibly associated with African swine fever (ASF) epidemiology in Uganda. Representative sub-populations of pig farms and statistics were used in a case-control model. Indiscriminate disposal of pig viscera and waste materials after slaughter, including on open refuse dumps, farm-gate buyers collecting pigs and pig products from within a farm, and retention of survivor pigs were plausible risk factors. Wire mesh-protected windows in pig houses were found to be protective against ASF infection. Sighting engorged ticks on pigs, the presence of a lock for each pig pen and/or a gate at the farm entrance were significantly associated with infection/non-infection; possible explanations were offered. Strict adherence to planned within-farm and community-based biosecurity, and avoidance of identified risk factors is recommended to reduce infection. Training for small-scale and emerging farmers should involve multidimensional and multidisciplinary approaches to reduce human-related risky behaviours driving infection. Copyright © 2014. Published by Elsevier Ltd.

A large-eddy simulation based power estimation capability for wind farms over complex terrain

NASA Astrophysics Data System (ADS)

Senocak, I.; Sandusky, M.; Deleon, R.

2017-12-01

There has been an increasing interest in predicting wind fields over complex terrain at the micro-scale for resource assessment, turbine siting, and power forecasting. These capabilities are made possible by advancements in computational speed from a new generation of computing hardware, numerical methods and physics modelling. The micro-scale wind prediction model presented in this work is based on the large-eddy simulation paradigm with surface-stress parameterization. The complex terrain is represented using an immersed-boundary method that takes into account the parameterization of the surface stresses. Governing equations of incompressible fluid flow are solved using a projection method with second-order accurate schemes in space and time. We use actuator disk models with rotation to simulate the influence of turbines on the wind field. Data regarding power production from individual turbines are mostly restricted because of proprietary nature of the wind energy business. Most studies report percentage drop of power relative to power from the first row. There have been different approaches to predict power production. Some studies simply report available wind power in the upstream, some studies estimate power production using power curves available from turbine manufacturers, and some studies estimate power as torque multiplied by rotational speed. In the present work, we propose a black-box approach that considers a control volume around a turbine and estimate the power extracted from the turbine based on the conservation of energy principle. We applied our wind power prediction capability to wind farms over flat terrain such as the wind farm over Mower County, Minnesota and the Horns Rev offshore wind farm in Denmark. The results from these simulations are in good agreement with published data. We also estimate power production from a hypothetical wind farm in complex terrain region and identify potential zones suitable for wind power production.

Experimental Study on the Wake Meandering Within a Scale Model Wind Farm Subject to a Wind-Tunnel Flow Simulating an Atmospheric Boundary Layer

NASA Astrophysics Data System (ADS)

Coudou, Nicolas; Buckingham, Sophia; Bricteux, Laurent; van Beeck, Jeroen

2017-12-01

The phenomenon of meandering of the wind-turbine wake comprises the motion of the wake as a whole in both horizontal and vertical directions as it is advected downstream. The oscillatory motion of the wake is a crucial factor in wind farms, because it increases the fatigue loads, and, in particular, the yaw loads on downstream turbines. To address this phenomenon, experimental investigations are carried out in a wind-tunnel flow simulating an atmospheric boundary layer with the Coriolis effect neglected. A 3 × 3 scaled wind farm composed of three-bladed rotating wind-turbine models is subject to a neutral boundary layer over a slightly-rough surface, i.e. corresponding to offshore conditions. Particle-image-velocimetry measurements are performed in a horizontal plane at hub height in the wakes of the three wind turbines occupying the wind-farm centreline. These measurements allow determination of the wake centrelines, with spectral analysis indicating the characteristic wavelength of the wake-meandering phenomenon. In addition, measurements with hot-wire anemometry are performed along a vertical line in the wakes of the same wind turbines, with both techniques revealing the presence of wake meandering behind all three turbines. The spectral analysis performed with the spatial and temporal signals obtained from these two measurement techniques indicates a Strouhal number of ≈ 0.20 - 0.22 based on the characteristic wake-meandering frequency, the rotor diameter and the flow speed at hub height.

Experimental Study on the Wake Meandering Within a Scale Model Wind Farm Subject to a Wind-Tunnel Flow Simulating an Atmospheric Boundary Layer

NASA Astrophysics Data System (ADS)

Coudou, Nicolas; Buckingham, Sophia; Bricteux, Laurent; van Beeck, Jeroen

2018-04-01

The phenomenon of meandering of the wind-turbine wake comprises the motion of the wake as a whole in both horizontal and vertical directions as it is advected downstream. The oscillatory motion of the wake is a crucial factor in wind farms, because it increases the fatigue loads, and, in particular, the yaw loads on downstream turbines. To address this phenomenon, experimental investigations are carried out in a wind-tunnel flow simulating an atmospheric boundary layer with the Coriolis effect neglected. A 3 × 3 scaled wind farm composed of three-bladed rotating wind-turbine models is subject to a neutral boundary layer over a slightly-rough surface, i.e. corresponding to offshore conditions. Particle-image-velocimetry measurements are performed in a horizontal plane at hub height in the wakes of the three wind turbines occupying the wind-farm centreline. These measurements allow determination of the wake centrelines, with spectral analysis indicating the characteristic wavelength of the wake-meandering phenomenon. In addition, measurements with hot-wire anemometry are performed along a vertical line in the wakes of the same wind turbines, with both techniques revealing the presence of wake meandering behind all three turbines. The spectral analysis performed with the spatial and temporal signals obtained from these two measurement techniques indicates a Strouhal number of ≈ 0.20 - 0.22 based on the characteristic wake-meandering frequency, the rotor diameter and the flow speed at hub height.

Affect of dairy cow manure, urine, and slurry on N<2>O, CO<2>, and CH<4> emissions from Pasture

NASA Astrophysics Data System (ADS)

Dorich, C.; Varner, R. K.; Contosta, A.; Li, C.

2012-12-01

Agriculture is responsible for roughly 25% of total anthropogenic emission of greenhouse gases (GHG) globally. These agricultural emissions are primarily in the form of methane (CH<4>) and nitrous oxide (N<2>O) where they account for roughly 40 and 80 percent of anthropogenic emissions of their gas, respectively. Measuring and modeling of these gases has remained difficult however as management varies between farms and N<2>O fluxes have been difficult to link to climate and site conditions. Most of these N<2>O fluxes occur during soil freeze-thaw and wetting-drying cycles as well as fertilizer addition moments, all of which are difficult to measure and harder yet to model. Thus the N<2>O flux remains poorly understood and may be underestimated in literature. This provides a problem in agriculture emissions as N use efficiency has been suggested as a proxy for farm scale emissions. On a farm scale these large fluxes of N<2>O from soil "hot moments" can account for up to 60% of the total GHG emissions and thus it is essential to capture the full flux. At the University of New Hampshire Agriculture Experiment Station's (NHAES) organic dairy farm a manure fertilizer experiment was conducted. Manure, urine, and slurry from the UNH dairy farms were collected, analyzed, and applied to pasture plots in May 2012 in order to examine N<2>O flux hot moments. Sites were measured at least bi-weekly with manual static flux chambers taken with soil temperature and moisture along with measurements for soil inorganic N, soil C:N, plant biomass and C:N, and soil pH. Gas samples were analyzed for CO<2>, CH<4>, and N<2>O. Emissions were compared with other fluxes from the farm ecosystem including; corn silage, free stall bedding, composting and solid manure, and a manure slurry tank.

Fine-scale ecological and economic assessment of climate change on olive in the Mediterranean Basin reveals winners and losers

PubMed Central

Ponti, Luigi; Gutierrez, Andrew Paul; Ruti, Paolo Michele; Dell’Aquila, Alessandro

2014-01-01

The Mediterranean Basin is a climate and biodiversity hot spot, and climate change threatens agro-ecosystems such as olive, an ancient drought-tolerant crop of considerable ecological and socioeconomic importance. Climate change will impact the interactions of olive and the obligate olive fruit fly (Bactrocera oleae), and alter the economics of olive culture across the Basin. We estimate the effects of climate change on the dynamics and interaction of olive and the fly using physiologically based demographic models in a geographic information system context as driven by daily climate change scenario weather. A regional climate model that includes fine-scale representation of the effects of topography and the influence of the Mediterranean Sea on regional climate was used to scale the global climate data. The system model for olive/olive fly was used as the production function in our economic analysis, replacing the commonly used production-damage control function. Climate warming will affect olive yield and fly infestation levels across the Basin, resulting in economic winners and losers at the local and regional scales. At the local scale, profitability of small olive farms in many marginal areas of Europe and elsewhere in the Basin will decrease, leading to increased abandonment. These marginal farms are critical to conserving soil, maintaining biodiversity, and reducing fire risk in these areas. Our fine-scale bioeconomic approach provides a realistic prototype for assessing climate change impacts in other Mediterranean agro-ecosystems facing extant and new invasive pests. PMID:24706833

Fine-scale ecological and economic assessment of climate change on olive in the Mediterranean Basin reveals winners and losers.

PubMed

Ponti, Luigi; Gutierrez, Andrew Paul; Ruti, Paolo Michele; Dell'Aquila, Alessandro

2014-04-15

The Mediterranean Basin is a climate and biodiversity hot spot, and climate change threatens agro-ecosystems such as olive, an ancient drought-tolerant crop of considerable ecological and socioeconomic importance. Climate change will impact the interactions of olive and the obligate olive fruit fly (Bactrocera oleae), and alter the economics of olive culture across the Basin. We estimate the effects of climate change on the dynamics and interaction of olive and the fly using physiologically based demographic models in a geographic information system context as driven by daily climate change scenario weather. A regional climate model that includes fine-scale representation of the effects of topography and the influence of the Mediterranean Sea on regional climate was used to scale the global climate data. The system model for olive/olive fly was used as the production function in our economic analysis, replacing the commonly used production-damage control function. Climate warming will affect olive yield and fly infestation levels across the Basin, resulting in economic winners and losers at the local and regional scales. At the local scale, profitability of small olive farms in many marginal areas of Europe and elsewhere in the Basin will decrease, leading to increased abandonment. These marginal farms are critical to conserving soil, maintaining biodiversity, and reducing fire risk in these areas. Our fine-scale bioeconomic approach provides a realistic prototype for assessing climate change impacts in other Mediterranean agro-ecosystems facing extant and new invasive pests.

SIMS(DAIRY): a modelling framework to identify sustainable dairy farms in the UK. Framework description and test for organic systems and N fertiliser optimisation.

PubMed

Del Prado, A; Misselbrook, T; Chadwick, D; Hopkins, A; Dewhurst, R J; Davison, P; Butler, A; Schröder, J; Scholefield, D

2011-09-01

Multiple demands are placed on farming systems today. Society, national legislation and market forces seek what could be seen as conflicting outcomes from our agricultural systems, e.g. food quality, affordable prices, a healthy environmental, consideration of animal welfare, biodiversity etc., Many of these demands, or desirable outcomes, are interrelated, so reaching one goal may often compromise another and, importantly, pose a risk to the economic viability of the farm. SIMS(DAIRY), a farm-scale model, was used to explore this complexity for dairy farm systems. SIMS(DAIRY) integrates existing approaches to simulate the effect of interactions between farm management, climate and soil characteristics on losses of nitrogen, phosphorus and carbon. The effects on farm profitability and attributes of biodiversity, milk quality, soil quality and animal welfare are also included. SIMS(DAIRY) can also be used to optimise fertiliser N. In this paper we discuss some limitations and strengths of using SIMS(DAIRY) compared to other modelling approaches and propose some potential improvements. Using the model we evaluated the sustainability of organic dairy systems compared with conventional dairy farms under non-optimised and optimised fertiliser N use. Model outputs showed for example, that organic dairy systems based on grass-clover swards and maize silage resulted in much smaller total GHG emissions per l of milk and slightly smaller losses of NO(3) leaching and NO(x) emissions per l of milk compared with the grassland/maize-based conventional systems. These differences were essentially because the conventional systems rely on indirect energy use for 'fixing' N compared with biological N fixation for the organic systems. SIMS(DAIRY) runs also showed some other potential benefits from the organic systems compared with conventional systems in terms of financial performance and soil quality and biodiversity scores. Optimisation of fertiliser N timings and rates showed a considerable scope to reduce the (GHG emissions per l milk too). Copyright © 2011 Elsevier B.V. All rights reserved.

ATMOSPHERIC AMMONIA EMISSIONS FROM THE LIVESTOCK SECTOR: DEVELOPMENT AND EVALUATION OF A PROCESS-BASED MODELING APPROACH

EPA Science Inventory

We propose multi-faceted research to enhance our understanding of NH3 emissions from livestock feeding operations. A process-based emissions modeling approach will be used, and we will investigate ammonia emissions from the scale of the individual farm out to impacts on region...

Toward irrigation retrieval by combining multi-sensor remote sensing data into a land surface model over a semi-arid region

NASA Astrophysics Data System (ADS)

Malbéteau, Y.; Lopez, O.; Houborg, R.; McCabe, M.

2017-12-01

Agriculture places considerable pressure on water resources, with the relationship between water availability and food production being critical for sustaining population growth. Monitoring water resources is particularly important in arid and semi-arid regions, where irrigation can represent up to 80% of the consumptive uses of water. In this context, it is necessary to optimize on-farm irrigation management by adjusting irrigation to crop water requirements throughout the growing season. However, in situ point measurements are not routinely available over extended areas and may not be representative at the field scale. Remote sensing approaches present as a cost-effective technique for mapping and monitoring broad areas. By taking advantage of multi-sensor remote sensing methodologies, such as those provided by MODIS, Landsat, Sentinel and Cubesats, we propose a new method to estimate irrigation input at pivot-scale. Here we explore the development of crop-water use estimates via these remote sensing data and integrate them into a land surface modeling framework, using a farm in Saudi Arabia as a demonstration of what can be achieved at larger scales.

Potential Impacts of Offshore Wind Farms on North Sea Stratification

PubMed Central

Carpenter, Jeffrey R.; Merckelbach, Lucas; Callies, Ulrich; Clark, Suzanna; Gaslikova, Lidia; Baschek, Burkard

2016-01-01

Advances in offshore wind farm (OWF) technology have recently led to their construction in coastal waters that are deep enough to be seasonally stratified. As tidal currents move past the OWF foundation structures they generate a turbulent wake that will contribute to a mixing of the stratified water column. In this study we show that the mixing generated in this way may have a significant impact on the large-scale stratification of the German Bight region of the North Sea. This region is chosen as the focus of this study since the planning of OWFs is particularly widespread. Using a combination of idealised modelling and in situ measurements, we provide order-of-magnitude estimates of two important time scales that are key to understanding the impacts of OWFs: (i) a mixing time scale, describing how long a complete mixing of the stratification takes, and (ii) an advective time scale, quantifying for how long a water parcel is expected to undergo enhanced wind farm mixing. The results are especially sensitive to both the drag coefficient and type of foundation structure, as well as the evolution of the pycnocline under enhanced mixing conditions—both of which are not well known. With these limitations in mind, the results show that OWFs could impact the large-scale stratification, but only when they occupy extensive shelf regions. They are expected to have very little impact on large-scale stratification at the current capacity in the North Sea, but the impact could be significant in future large-scale development scenarios. PMID:27513754

Potential Impacts of Offshore Wind Farms on North Sea Stratification.

PubMed

Carpenter, Jeffrey R; Merckelbach, Lucas; Callies, Ulrich; Clark, Suzanna; Gaslikova, Lidia; Baschek, Burkard

2016-01-01

Advances in offshore wind farm (OWF) technology have recently led to their construction in coastal waters that are deep enough to be seasonally stratified. As tidal currents move past the OWF foundation structures they generate a turbulent wake that will contribute to a mixing of the stratified water column. In this study we show that the mixing generated in this way may have a significant impact on the large-scale stratification of the German Bight region of the North Sea. This region is chosen as the focus of this study since the planning of OWFs is particularly widespread. Using a combination of idealised modelling and in situ measurements, we provide order-of-magnitude estimates of two important time scales that are key to understanding the impacts of OWFs: (i) a mixing time scale, describing how long a complete mixing of the stratification takes, and (ii) an advective time scale, quantifying for how long a water parcel is expected to undergo enhanced wind farm mixing. The results are especially sensitive to both the drag coefficient and type of foundation structure, as well as the evolution of the pycnocline under enhanced mixing conditions-both of which are not well known. With these limitations in mind, the results show that OWFs could impact the large-scale stratification, but only when they occupy extensive shelf regions. They are expected to have very little impact on large-scale stratification at the current capacity in the North Sea, but the impact could be significant in future large-scale development scenarios.

Neurobehavioural symptoms and acute pesticide poisoning: a cross-sectional study among male pesticide applicators selected from three commercial farming systems in Ethiopia.

PubMed

Negatu, Beyene; Vermeulen, Roel; Mekonnen, Yalemtshay; Kromhout, Hans

2018-04-01

To estimate prevalence of acute pesticide poisoning (APP) and its association with neurobehavioural symptoms in Ethiopian pesticide applicators. We performed a cross-sectional survey among 256 pesticide applicators from small-scale irrigated farms, a large-scale open farm and large-scale greenhouses. APP was ascertained using a modified WHO case definition, and neurobehavioural symptoms were collected with a standardised questionnaire (Q16). Exposure to pesticides was estimated using detailed exposure algorithms specifically developed for Ethiopian farms. Multiple logistic regression models were used to estimate risk of APP and its association with neurobehavioural symptoms. Overall APP prevalence was 16%. Working as an applicator in greenhouses was strongly associated with APP (OR 3.00, 95% CI 1.38 to 6.54). Estimated annual pesticide exposure was also associated with APP (OR 1.14, 95% CI 1.00 to 1.20). Longer duration of employment appeared to be negatively associated with APP. Having had an APP was strongly associated with reporting more neurobehavioural symptoms (OR 2.15, 95% CI 1.01 to 4.58) independent of cumulative pesticide exposure. Cumulative exposure to pesticides appeared to be associated with neurobehavioural symptoms among applicators without and with APP. We showed a substantial prevalence of APP that differed between farming systems and was strongly associated with neurobehavioural symptoms. Intensity of exposure was also clearly associated with these symptoms. Reduction and control of occupational exposure to pesticides is urgently needed in Ethiopia. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Predicting nutrient responses to mitigation at catchment to national scale: the UK research platform (Invited)

NASA Astrophysics Data System (ADS)

Johnes, P.

2013-12-01

Nutrient enrichment of waters from land-based and atmospheric sources presents a significant management challenge, requiring effective stakeholder engagement and policy development, properly underpinned by robust scientific evidence. The challenge is complex, raising significant questions about the specific sources, apportionment and pathways that determine nutrient enrichment and the key priorities for effective management and policy intervention. This paper presents outputs from 4 major UK research programmes: the Defra Demonstration Test Catchments programme (DTC), the Environment Agency's Catchment Sensitive Farming monitoring and evaluation programme (CSF), Natural Resources Wales Welsh Catchment Initiative (WCI) and the NERC Environmental Virtual Observatory programme (EVOp). Funded to meet this challenge, they are delivering new understanding of the rates and sources of pollutant fluxes from land to water, their impacts on ecosystem goods and services, and likely trends under future climate and land use change from field to national scale. DTC, a 12m investment by the UK Government, has set up long-term, high resolution research platforms equipped with novel telemetered sensor networks to monitor stream ecosystem responses to on-farm mitigation measures at a representative scale for catchment management. Ecosystem structural and functional responses and bulk hydrochemistry are also being monitored using standard protocols. CSF has set up long-term, enhanced monitoring in 8 priority catchments, with monthly monitoring in a further 72 English catchments and 6 Welsh priority catchments, to identify shifts in pollutant flux to waters resulting from mitigation measures in priority areas and farming sectors. CSF and WCI have contributed to >50 million of targeted farm improvements to date, representing a significant shift in farming practice. Each programme has generated detailed evidence on stream ecosystem responses to targeted mitigation. However, to provide effective underpinning for policy the major challenge has been to upscale this knowledge beyond these data-rich systems and identify the dominant contributing areas and priorities for management intervention to control nutrient flux and ecological impacts in data-poor systems which are located downstream from existing monitoring infrastructure or are in unmonitored catchments in remote locations. EVOp has directly addressed this challenge, developing a cloud computing enabled National Biogeochemical Modelling Framework to support ensemble modelling, knowledge capture and transfer from DTC, CSF, WCI and data-rich research catchments. This platform provides opportunities for further development of national biogeochemical modelling capability, allowing upscaled predictions from plot to catchment and national scale, enabling knowledge transfer from data-rich to data-poor areas. This paper presents initial findings from these research platforms, identifying the key priorities for action emerging from our national scale scenario analysis, and future research directions to further improve understanding, prediction and management capability in nutrient enriched waters and their catchments under changing climate and land use.

Agricultural diversification as an important strategy for achieving food security in Africa.

PubMed

Waha, Katharina; van Wijk, Mark T; Fritz, Steffen; See, Linda; Thornton, Philip K; Wichern, Jannike; Herrero, Mario

2018-03-31

Farmers in Africa have long adapted to climatic and other risks by diversifying their farming activities. Using a multi-scale approach, we explore the relationship between farming diversity and food security and the diversification potential of African agriculture and its limits on the household and continental scale. On the household scale, we use agricultural surveys from more than 28,000 households located in 18 African countries. In a next step, we use the relationship between rainfall, rainfall variability, and farming diversity to determine the available diversification options for farmers on the continental scale. On the household scale, we show that households with greater farming diversity are more successful in meeting their consumption needs, but only up to a certain level of diversity per ha cropland and more often if food can be purchased from off-farm income or income from farm sales. More diverse farming systems can contribute to household food security; however, the relationship is influenced by other factors, for example, the market orientation of a household, livestock ownership, nonagricultural employment opportunities, and available land resources. On the continental scale, the greatest opportunities for diversification of food crops, cash crops, and livestock are located in areas with 500-1,000 mm annual rainfall and 17%-22% rainfall variability. Forty-three percent of the African cropland lacks these opportunities at present which may hamper the ability of agricultural systems to respond to climate change. While sustainable intensification practices that increase yields have received most attention to date, our study suggests that a shift in the research and policy paradigm toward agricultural diversification options may be necessary. © 2018 The Authors Global Change Biology Published by John Wiley & Sons Ltd.

Risk Preference of Farmer Beef Cattle Smallholder in West Java

NASA Astrophysics Data System (ADS)

Arief, H.; Fitriani, A.

2018-02-01

Beef cattle farm is an economic activity that its correlation relatively high with ecology condition, ever more its activity be dominated by smallholder with farm scale of 1—3 head beef cattle, so the capital of feeder cattle are component production costs relatively large. By doing so, lose one head of cattle means losing some of the capital that had been invested in its farm. This condition has implications for the behavior of farmers in managing its farm. The farmers in the decision-making act reluctant to risk so there is a bit of a program or package of new technologies to improve the performance of farm rejected. Therefore, this study analyzed the preferences of farmers against risks, and find out the socio-economic conditions that be the deciding factor on farmer preference for risk.The method used was a survey with multistage random sampling. The numbers of samples in this study were 150 people from three different areas, namely: District of Bandung, Subang, and Pangandaran (South Ciamis). Data analysis model used in relation to this research problem was the model’s utility function and Component Factor Analysis (CFA). The results showed that the overall breeders had a reluctant attitude to risk (risk averter). This is indicated by the value of x3, namely -63,692.693 < 0; and socio-economic factors that determine the preference of farmers against risk are age, education, and experience for farm management; while the business scale factor, number of dependents, and ownership determine the size of the gross margin.

Small-scale pig farmers' behavior, silent release of African swine fever virus and consequences for disease spread.

PubMed

Costard, Solenne; Zagmutt, Francisco J; Porphyre, Thibaud; Pfeiffer, Dirk Udo

2015-11-27

The expanding distribution of African swine fever (ASF) is threatening the pig industry worldwide. Most outbreaks occur in backyard and small-scale herds, where poor farmers often attempt to limit the disease's economic consequences by the emergency sale of their pigs. The risk of African swine fever virus (ASFV) release via this emergency sale was investigated. Simulation modeling was used to study ASFV transmission in backyard and small-scale farms as well as the emergency sale of pigs, and the potential impact of improving farmers and traders' clinical diagnosis ability-its timeliness and/or accuracy-was assessed. The risk of ASFV release was shown to be high, and improving farmers' clinical diagnosis ability does not appear sufficient to effectively reduce this risk. Estimates obtained also showed that the distribution of herd size within the backyard and small-scale sectors influences the relative contribution of these farms to the risk of release of infected pigs. These findings can inform surveillance and control programs.

Social environments, risk-taking and injury in farm adolescents.

PubMed

Pickett, William; Berg, Richard L; Marlenga, Barbara

2017-12-01

Farm environments are especially hazardous for young people. While much is known about acute physical causes of traumatic farm injury, little is known about social factors that may underlie their aetiology. In a nationally representative sample of young Canadians aged 11-15 years, we described and compared farm and non-farm adolescents in terms of the qualities of their social environments, engagement in overt multiple risk-taking as well as how such exposures relate aetiologically to their reported injury experiences. Cross-sectional analysis of survey reports from the 2014 (Cycle 7) Canadian Health Behaviour in School-Aged Children study was conducted. Children (n=2567; 2534 weighted) who reported living or working on farms were matched within schools in a 1:1 ratio with children not living or working on farms. Scales examining quality of social environments and overt risk-taking were compared between the two groups, stratified by gender. We then related the occurrence of any serious injury to these social exposures in direct and interactive models. Farm and non-farm children reported social environments that were quite similar, with the exception of overt multiple risk-taking, which was demonstrably higher in farm children of both genders. Engagement in overt risk-taking, but not the other social environmental factors, was strongly and consistently associated with risks for serious injury in farm as well as non-farm children, particularly among males. Study findings highlight the strength of associations between overt multiple risk-taking and injury among farm children. This appears to be a normative aspect of adolescent farm culture. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

A global synthesis of the effects of diversified farming systems on arthropod diversity within fields and across agricultural landscapes.

PubMed

Lichtenberg, Elinor M; Kennedy, Christina M; Kremen, Claire; Batáry, Péter; Berendse, Frank; Bommarco, Riccardo; Bosque-Pérez, Nilsa A; Carvalheiro, Luísa G; Snyder, William E; Williams, Neal M; Winfree, Rachael; Klatt, Björn K; Åström, Sandra; Benjamin, Faye; Brittain, Claire; Chaplin-Kramer, Rebecca; Clough, Yann; Danforth, Bryan; Diekötter, Tim; Eigenbrode, Sanford D; Ekroos, Johan; Elle, Elizabeth; Freitas, Breno M; Fukuda, Yuki; Gaines-Day, Hannah R; Grab, Heather; Gratton, Claudio; Holzschuh, Andrea; Isaacs, Rufus; Isaia, Marco; Jha, Shalene; Jonason, Dennis; Jones, Vincent P; Klein, Alexandra-Maria; Krauss, Jochen; Letourneau, Deborah K; Macfadyen, Sarina; Mallinger, Rachel E; Martin, Emily A; Martinez, Eliana; Memmott, Jane; Morandin, Lora; Neame, Lisa; Otieno, Mark; Park, Mia G; Pfiffner, Lukas; Pocock, Michael J O; Ponce, Carlos; Potts, Simon G; Poveda, Katja; Ramos, Mariangie; Rosenheim, Jay A; Rundlöf, Maj; Sardiñas, Hillary; Saunders, Manu E; Schon, Nicole L; Sciligo, Amber R; Sidhu, C Sheena; Steffan-Dewenter, Ingolf; Tscharntke, Teja; Veselý, Milan; Weisser, Wolfgang W; Wilson, Julianna K; Crowder, David W

2017-11-01

Agricultural intensification is a leading cause of global biodiversity loss, which can reduce the provisioning of ecosystem services in managed ecosystems. Organic farming and plant diversification are farm management schemes that may mitigate potential ecological harm by increasing species richness and boosting related ecosystem services to agroecosystems. What remains unclear is the extent to which farm management schemes affect biodiversity components other than species richness, and whether impacts differ across spatial scales and landscape contexts. Using a global metadataset, we quantified the effects of organic farming and plant diversification on abundance, local diversity (communities within fields), and regional diversity (communities across fields) of arthropod pollinators, predators, herbivores, and detritivores. Both organic farming and higher in-field plant diversity enhanced arthropod abundance, particularly for rare taxa. This resulted in increased richness but decreased evenness. While these responses were stronger at local relative to regional scales, richness and abundance increased at both scales, and richness on farms embedded in complex relative to simple landscapes. Overall, both organic farming and in-field plant diversification exerted the strongest effects on pollinators and predators, suggesting these management schemes can facilitate ecosystem service providers without augmenting herbivore (pest) populations. Our results suggest that organic farming and plant diversification promote diverse arthropod metacommunities that may provide temporal and spatial stability of ecosystem service provisioning. Conserving diverse plant and arthropod communities in farming systems therefore requires sustainable practices that operate both within fields and across landscapes. © 2017 John Wiley & Sons Ltd.

Impacts of Small-Scale Industrialized Swine Farming on Local Soil, Water and Crop Qualities in a Hilly Red Soil Region of Subtropical China

PubMed Central

Zhang, Di; Wang, Xingxiang; Zhou, Zhigao

2017-01-01

Industrialized small-scale pig farming has been rapidly developed in developing regions such as China and Southeast Asia, but the environmental problems accompanying pig farming have not been fully recognized. This study investigated 168 small-scale pig farms and 29 example pig farms in Yujiang County of China to examine current and potential impacts of pig wastes on soil, water and crop qualities in the hilly red soil region, China. The results indicated that the small-scale pig farms produced considerable annual yields of wastes, with medians of 216, 333 and 773 ton yr−1 per pig farm for manure, urine and washing wastewater, respectively, which has had significant impact on surface water quality. Taking NH4+-N, total nitrogen (TN) or total phosphorus (TP) as a criterion to judge water quality, the proportions of Class III and below Class III waters in the local surface waters were 66.2%, 78.7% and 72.5%. The well water (shallow groundwater) quality near these pig farms met the water quality standards by a wide margin. The annual output of pollutants from pig farms was the most important factor correlated with the nutrients and heavy metals in soils, and the relationship can be described by a linear equation. The impact on croplands was marked by the excessive accumulation of available phosphorus and heavy metals such as Cu and Zn. For crop safety, the over-limit ratio of Zn in vegetable samples reached 60%, other heavy metals in vegetable and rice samples tested met the food safety standard at present. PMID:29211053

Impacts of Small-Scale Industrialized Swine Farming on Local Soil, Water and Crop Qualities in a Hilly Red Soil Region of Subtropical China.

PubMed

Zhang, Di; Wang, Xingxiang; Zhou, Zhigao

2017-12-06

Industrialized small-scale pig farming has been rapidly developed in developing regions such as China and Southeast Asia, but the environmental problems accompanying pig farming have not been fully recognized. This study investigated 168 small-scale pig farms and 29 example pig farms in Yujiang County of China to examine current and potential impacts of pig wastes on soil, water and crop qualities in the hilly red soil region, China. The results indicated that the small-scale pig farms produced considerable annual yields of wastes, with medians of 216, 333 and 773 ton yr -1 per pig farm for manure, urine and washing wastewater, respectively, which has had significant impact on surface water quality. Taking NH₄⁺-N, total nitrogen (TN) or total phosphorus (TP) as a criterion to judge water quality, the proportions of Class III and below Class III waters in the local surface waters were 66.2%, 78.7% and 72.5%. The well water (shallow groundwater) quality near these pig farms met the water quality standards by a wide margin. The annual output of pollutants from pig farms was the most important factor correlated with the nutrients and heavy metals in soils, and the relationship can be described by a linear equation. The impact on croplands was marked by the excessive accumulation of available phosphorus and heavy metals such as Cu and Zn. For crop safety, the over-limit ratio of Zn in vegetable samples reached 60%, other heavy metals in vegetable and rice samples tested met the food safety standard at present.

Estimating landscape-scale impacts of agricultural management on soil carbon using measurements and models

NASA Astrophysics Data System (ADS)

Schipanski, M.; Rosenzweig, S. T.; Robertson, A. D.; Sherrod, L. A.; Ghimire, R.; McMaster, G. S.

2017-12-01

Agriculture covers 40% of Earth's ice-free land area and has broad impacts on global biogeochemical cycles. While some agricultural management changes are small in scale or impact, others have the potential to shift biogeochemical cycles at landscape and larger scales if widely adopted. Understanding which management practices have the potential to contribute to climate change adaptation and mitigation while maintaining productivity requires scaling up estimates spatially and temporally. We used on-farm, long-term, and landscape scale datasets to estimate how crop rotations impact soil organic carbon (SOC) accumulation rates under current and future climate scenarios across the semi-arid Central and Southern Great Plains. We used a stratified, landscape-scale soil sampling approach across 96 farm fields to evaluate crop rotation intensity effects on SOC pools and pesticide inputs. Replacing traditional wheat-fallow rotations with more diverse, continuously cropped rotations increased SOC by 17% and 12% in 0-10 cm and 0-20 cm depths, respectively, and reduced herbicide use by 50%. Using USDA Cropland Data Layer, we estimated soil C accumulation and pesticide reduction potentials of shifting to more intensive rotations. We also used a 30-year cropping systems experiment to calibrate and validate the Daycent model to evaluate rotation intensify effects under future climate change scenarios. The model estimated greater SOC accumulation rates under continuously cropped rotations, but SOC stocks peaked and then declined for all cropping systems beyond 2050 under future climate scenarios. Perennial grasslands were the only system estimated to maintain SOC levels in the future. In the Southern High Plains, soil C declined despite increasing input intensity under current weather while modest gains were simulated under future climate for sorghum-based cropping systems. Our findings highlight the potential vulnerability of semi-arid regions to climate change, which will be compounded by declining groundwater levels along the western edge of the High Plains Aquifer that increase reliance on dryland farming systems. Understanding these challenges provides opportunities to develop future transition and adaptation strategies in partnership with producers, policy makers, and rural communities.

Pollen-mediated gene flow and seed exchange in small-scale Zambian maize farming, implications for biosafety assessment

NASA Astrophysics Data System (ADS)

Bøhn, Thomas; Aheto, Denis W.; Mwangala, Felix S.; Fischer, Klara; Bones, Inger Louise; Simoloka, Christopher; Mbeule, Ireen; Schmidt, Gunther; Breckling, Broder

2016-10-01

Gene flow in agricultural crops is important for risk assessment of genetically modified (GM) crops, particularly in countries with a large informal agricultural sector of subsistence cultivation. We present a pollen flow model for maize (Zea mays), a major staple crop in Africa. We use spatial properties of fields (size, position) in three small-scale maize farming communities in Zambia and estimate rates of cross-fertilisation between fields sown with different maize varieties (e.g. conventional and transgene). As an additional factor contributing to gene flow, we present data on seed saving and sharing among farmers that live in the same communities. Our results show that: i) maize fields were small and located in immediate vicinity of neighboring fields; ii) a majority of farmers saved and shared seed; iii) modeled rates of pollen-mediated gene flow showed extensive mixing of germplasm between fields and farms and iv) as a result, segregation of GM and non-GM varieties is not likely to be an option in these systems. We conclude that the overall genetic composition of maize, in this and similar agricultural contexts, will be strongly influenced both by self-organised ecological factors (pollen flow), and by socially mediated intervention (seed recycling and sharing).

Pollen-mediated gene flow and seed exchange in small-scale Zambian maize farming, implications for biosafety assessment

PubMed Central

Bøhn, Thomas; Aheto, Denis W.; Mwangala, Felix S.; Fischer, Klara; Bones, Inger Louise; Simoloka, Christopher; Mbeule, Ireen; Schmidt, Gunther; Breckling, Broder

2016-01-01

Gene flow in agricultural crops is important for risk assessment of genetically modified (GM) crops, particularly in countries with a large informal agricultural sector of subsistence cultivation. We present a pollen flow model for maize (Zea mays), a major staple crop in Africa. We use spatial properties of fields (size, position) in three small-scale maize farming communities in Zambia and estimate rates of cross-fertilisation between fields sown with different maize varieties (e.g. conventional and transgene). As an additional factor contributing to gene flow, we present data on seed saving and sharing among farmers that live in the same communities. Our results show that: i) maize fields were small and located in immediate vicinity of neighboring fields; ii) a majority of farmers saved and shared seed; iii) modeled rates of pollen-mediated gene flow showed extensive mixing of germplasm between fields and farms and iv) as a result, segregation of GM and non-GM varieties is not likely to be an option in these systems. We conclude that the overall genetic composition of maize, in this and similar agricultural contexts, will be strongly influenced both by self-organised ecological factors (pollen flow), and by socially mediated intervention (seed recycling and sharing). PMID:27694819

Pollen-mediated gene flow and seed exchange in small-scale Zambian maize farming, implications for biosafety assessment.

PubMed

Bøhn, Thomas; Aheto, Denis W; Mwangala, Felix S; Fischer, Klara; Bones, Inger Louise; Simoloka, Christopher; Mbeule, Ireen; Schmidt, Gunther; Breckling, Broder

2016-10-03

Gene flow in agricultural crops is important for risk assessment of genetically modified (GM) crops, particularly in countries with a large informal agricultural sector of subsistence cultivation. We present a pollen flow model for maize (Zea mays), a major staple crop in Africa. We use spatial properties of fields (size, position) in three small-scale maize farming communities in Zambia and estimate rates of cross-fertilisation between fields sown with different maize varieties (e.g. conventional and transgene). As an additional factor contributing to gene flow, we present data on seed saving and sharing among farmers that live in the same communities. Our results show that: i) maize fields were small and located in immediate vicinity of neighboring fields; ii) a majority of farmers saved and shared seed; iii) modeled rates of pollen-mediated gene flow showed extensive mixing of germplasm between fields and farms and iv) as a result, segregation of GM and non-GM varieties is not likely to be an option in these systems. We conclude that the overall genetic composition of maize, in this and similar agricultural contexts, will be strongly influenced both by self-organised ecological factors (pollen flow), and by socially mediated intervention (seed recycling and sharing).

Broad-scale impacts of salmon farms on temperate macroalgal assemblages on rocky reefs.

PubMed

Oh, E S; Edgar, G J; Kirkpatrick, J B; Stuart-Smith, R D; Barrett, N S

2015-09-15

Intensive fish culture in open sea pens delivers large amounts of nutrients to coastal environments. Relative to particulate waste impacts, the ecological impacts of dissolved wastes are poorly known despite their potential to substantially affect nutrient-assimilating components of surrounding ecosystems. Broad-scale enrichment effects of salmonid farms on Tasmanian reef communities were assessed by comparing macroalgal cover at four fixed distances from active fish farm leases across 44 sites. Macroalgal assemblages differed significantly between sites immediately adjacent (100m) to fish farms and reference sites at 5km distance, while sites at 400m and 1km exhibited intermediate characteristics. Epiphyte cover varied consistently with fish farm impacts in both sheltered and exposed locations. The green algae Chaetomorpha spp. predominated near fish farms at swell-exposed sites, whereas filamentous green algae showed elevated densities near sheltered farms. Cover of canopy-forming perennial algae appeared unaffected by fish farm impacts. Copyright © 2015 Elsevier Ltd. All rights reserved.

Development and validation of a work stressor scale for Australian farming families.

PubMed

McShane, Connar J; Quirk, Frances; Swinbourne, Anne

2016-08-01

The aim of this research was to gain insight into the key stressors for Australian farming families. It is well established that the farming work environment consists of a number of unique stressors which arise from dependency on factors beyond an individual's control (e.g. climate conditions) as well as the overlap between work and family environments. Despite this, limited research has included family factors in the assessment of stress felt by farmers and their families. This research sought to develop a scale of stressors for farming families in an Australian sample. A survey design was used for validity and reliability studies. The validity study involved assessment of factor structure, concurrent validity and discriminant validity. The reliability study used a test-retest reliability design. Participants were recruited from across Australia (38% Queensland; 30% New South Wales) and multiple industries (43% beef; 27% broadacre cropping; 26% horticulture). The validity study involved 278 participants and the reliability study involved 53 participants. Development of a Farming Family Stressor scale. The generated Farming Family Stressor scale presented satisfactory levels of concurrent validity (e.g. r = .73 against the Farm Stress Survey total score), discriminant validity (e.g. r = -.42 to r = .53 against the Satisfaction with Life and Kessler-10 total scores, respectively), internal consistency (Cronbach's alpha >.90) and test-retest reliability (rho > .66). This research lends insight into the complexity of stressors for farming families and has implications for occupational health and mental health programs that seek to reduce stress and improve health outcomes for that group. © 2015 National Rural Health Alliance Inc.

The former Iron Curtain still drives biodiversity-profit trade-offs in German agriculture.

PubMed

Batáry, Péter; Gallé, Róbert; Riesch, Friederike; Fischer, Christina; Dormann, Carsten F; Mußhoff, Oliver; Császár, Péter; Fusaro, Silvia; Gayer, Christoph; Happe, Anne-Kathrin; Kurucz, Kornélia; Molnár, Dorottya; Rösch, Verena; Wietzke, Alexander; Tscharntke, Teja

2017-09-01

Agricultural intensification drives biodiversity loss and shapes farmers' profit, but the role of legacy effects and detailed quantification of ecological-economic trade-offs are largely unknown. In Europe during the 1950s, the Eastern communist bloc switched to large-scale farming by forced collectivization of small farms, while the West kept small-scale private farming. Here we show that large-scale agriculture in East Germany reduced biodiversity, which has been maintained in West Germany due to >70% longer field edges than those in the East. In contrast, profit per farmland area in the East was 50% higher than that in the West, despite similar yield levels. In both regions, switching from conventional to organic farming increased biodiversity and halved yield levels, but doubled farmers' profits. In conclusion, European Union policy should acknowledge the surprisingly high biodiversity benefits of small-scale agriculture, which are on a par with conversion to organic agriculture.

Water resource protection in Australia: Links between land use and river health with a focus on stubble farming systems

NASA Astrophysics Data System (ADS)

Bowmer, Kathleen H.

2011-06-01

SummaryStubble farming (conservation farming, minimum tillage, zero tillage) has increased in Australia over several decades with claims of improved productivity, landscape stability and environmental benefit including ecosystem services downstream, yet recent audits show a dramatic and general decline in river health. This review explores explanations for this apparent anomaly. Many confounding factors complicate interactions between land use and river condition and may disguise or over-ride the potential benefits of adoption of stubble systems or other improvements in agricultural land use practice. These factors include climate change and variability; land use changes including an increase in bushfires, growth of farm dams and afforestation; lag times between land use change and expression of benefits in river systems; use of inappropriate scale that disguises local benefit; variations in the extent of ecosystem resilience; impacts of river regulation; and impacts of introduced species. Additionally, the value of river condition and utility is complicated by different local or regional perceptions and by contrasting rural and urban outlooks. The use of indicators, risk frameworks and biophysical modelling may help elucidate the complex relationships between land use and downstream ecosystem impact. The strengthening of local, regional and catchment scale approaches is advocated. This includes the re-integration of land management and governance with water management and planning. It is encouraging that farmers are themselves developing systems to optimise trade-offs between on-farm activities and ecosystem service benefits. This approach needs to be supported and extended.

Monitoring, modeling and mitigating impacts of wind farms on local meteorology

NASA Astrophysics Data System (ADS)

Baidya Roy, Somnath; Traiteur, Justin; Kelley, Neil

2010-05-01

Wind power is one of the fastest growing sources of energy. Most of the growth is in the industrial sector comprising of large utility-scale wind farms. Recent modeling studies have suggested that such wind farms can significantly affect local and regional weather and climate. In this work, we present observational evidence of the impact of wind farms on near-surface air temperatures. Data from perhaps the only meteorological field campaign in an operational wind farm shows that downwind temperatures are lower during the daytime and higher at night compared to the upwind environment. Corresponding radiosonde profiles at the nearby Edwards Air Force Base WMO meteorological station show that the diurnal environment is unstable while the nocturnal environment is stable during the field campaign. This behavior is consistent with the hypothesis proposed by Baidya Roy et al. (JGR 2004) that states that turbulence generated in the wake of rotors enhance vertical mixing leading to a warming/cooling under positive/negative potential temperature lapse rates. We conducted a set of 306 simulations with the Regional Atmospheric Modeling System (RAMS) to test if regional climate models can capture the thermal effects of wind farms. We represented wind turbines with a subgrid parameterization that assumes rotors to be sinks of momentum and sources of turbulence. The simulated wind farms consistently generated a localized warming/cooling under positive/negative lapse rates as hypothesized. We found that these impacts are inversely correlated with background atmospheric boundary layer turbulence. Thus, if the background turbulence is high due to natural processes, the effects of additional turbulence generated by wind turbine rotors are likely to be small. We propose the following strategies to minimize impacts of wind farms: • Engineering solution: design rotors that generate less turbulence in their wakes. Sensitivity simulations show that these turbines also increase the productivity of wind farms and reduce damages to downwind rotors. • Siting solution: develop wind farms in regions where ABL turbulence is naturally high. Since, turbulence data is not widely recorded, we use surface KE dissipation rate as a proxy for ABL turbulence. Indeed, in our simulations, these 2 parameters are strongly positively correlated (P<0.99). Using the JRA25 dataset, comprising of 25-year long 6-hourly global meteorological data, we identify such regions in the world. These regions that include the Midwest and Great Plains as well as large parts of northern Europe and western China are appropriate sites for low-impact wind farms.

The Technical Efficiency of Specialised Milk Farms: A Regional View

PubMed Central

Špička, Jindřich; Smutka, Luboš

2014-01-01

The aim of the article is to evaluate production efficiency and its determinants of specialised dairy farming among the EU regions. In the most of European regions, there is a relatively high significance of small specialised farms including dairy farms. The DEAVRS method (data envelopment analysis with variable returns to scale) reveals efficient and inefficient regions including the scale efficiency. In the next step, the two-sample t-test determines differences of economic and structural indicators between efficient and inefficient regions. The research reveals that substitution of labour by capital/contract work explains the variability of the farm net value added per AWU (annual work unit) income indicator by more than 30%. The significant economic determinants of production efficiency in specialised dairy farming are farm size, herd size, crop output per hectare, productivity of energy, and capital (at α = 0.01). Specialised dairy farms in efficient regions have significantly higher farm net value added per AWU than inefficient regions. Agricultural enterprises in inefficient regions have a more extensive structure and produce more noncommodity output (public goods). Specialised dairy farms in efficient regions have a slightly higher milk yield, specific livestock costs of feed, bedding, and veterinary services per livestock unit. PMID:25050408

Integrating social and value dimensions into sustainability assessment of lignocellulosic biofuels

PubMed Central

Raman, Sujatha; Mohr, Alison; Helliwell, Richard; Ribeiro, Barbara; Shortall, Orla; Smith, Robert; Millar, Kate

2015-01-01

The paper clarifies the social and value dimensions for integrated sustainability assessments of lignocellulosic biofuels. We develop a responsible innovation approach, looking at technology impacts and implementation challenges, assumptions and value conflicts influencing how impacts are identified and assessed, and different visions for future development. We identify three distinct value-based visions. From a techno-economic perspective, lignocellulosic biofuels can contribute to energy security with improved GHG implications and fewer sustainability problems than fossil fuels and first-generation biofuels, especially when biomass is domestically sourced. From socio-economic and cultural-economic perspectives, there are concerns about the capacity to support UK-sourced feedstocks in a global agri-economy, difficulties monitoring large-scale supply chains and their potential for distributing impacts unfairly, and tensions between domestic sourcing and established legacies of farming. To respond to these concerns, we identify the potential for moving away from a one-size-fits-all biofuel/biorefinery model to regionally-tailored bioenergy configurations that might lower large-scale uses of land for meat, reduce monocultures and fossil-energy needs of farming and diversify business models. These configurations could explore ways of reconciling some conflicts between food, fuel and feed (by mixing feed crops with lignocellulosic material for fuel, combining livestock grazing with energy crops, or using crops such as miscanthus to manage land that is no longer arable); different bioenergy applications (with on-farm use of feedstocks for heat and power and for commercial biofuel production); and climate change objectives and pressures on farming. Findings are based on stakeholder interviews, literature synthesis and discussions with an expert advisory group. PMID:26664147

Integrating social and value dimensions into sustainability assessment of lignocellulosic biofuels.

PubMed

Raman, Sujatha; Mohr, Alison; Helliwell, Richard; Ribeiro, Barbara; Shortall, Orla; Smith, Robert; Millar, Kate

2015-11-01

The paper clarifies the social and value dimensions for integrated sustainability assessments of lignocellulosic biofuels. We develop a responsible innovation approach, looking at technology impacts and implementation challenges, assumptions and value conflicts influencing how impacts are identified and assessed, and different visions for future development. We identify three distinct value-based visions. From a techno-economic perspective, lignocellulosic biofuels can contribute to energy security with improved GHG implications and fewer sustainability problems than fossil fuels and first-generation biofuels, especially when biomass is domestically sourced. From socio-economic and cultural-economic perspectives, there are concerns about the capacity to support UK-sourced feedstocks in a global agri-economy, difficulties monitoring large-scale supply chains and their potential for distributing impacts unfairly, and tensions between domestic sourcing and established legacies of farming. To respond to these concerns, we identify the potential for moving away from a one-size-fits-all biofuel/biorefinery model to regionally-tailored bioenergy configurations that might lower large-scale uses of land for meat, reduce monocultures and fossil-energy needs of farming and diversify business models. These configurations could explore ways of reconciling some conflicts between food, fuel and feed (by mixing feed crops with lignocellulosic material for fuel, combining livestock grazing with energy crops, or using crops such as miscanthus to manage land that is no longer arable); different bioenergy applications (with on-farm use of feedstocks for heat and power and for commercial biofuel production); and climate change objectives and pressures on farming. Findings are based on stakeholder interviews, literature synthesis and discussions with an expert advisory group.

Experimental study on the wind-turbine wake meandering inside a scale model wind farm placed in an atmospheric-boundary-layer wind tunnel

NASA Astrophysics Data System (ADS)

Coudou, N.; Buckingham, S.; van Beeck, J.

2017-05-01

Increasing use of wind energy over the years results in more and larger clustered wind farms. It is therefore fundamental to have an in-depth knowledge of wind-turbine wakes, and especially a better understanding of the well-known but less understood wake-meandering phenomenon which causes the wake to move as a whole in both horizontal and vertical directions as it is convected downstream. This oscillatory motion of the wake is crucial for loading on downstream turbines because it increases fatigue loads and in particular yaw loads. In order to address this phenomenon, experimental investigations were carried out in an atmospheric-boundary-layer wind tunnel using a 3 × 3 scaled wind farm composed of three-bladed rotating wind-turbine models subject to a neutral atmospheric boundary layer (ABL) corresponding to a slightly rough terrain, i.e. to offshore conditions. Particle Image Velocimetry (PIV) measurements were performed in a horizontal plane, at hub height, in the wake of the three wind turbines in the wind-farm centreline. From the PIV velocity fields obtained, the wake-centrelines were determined and a spectral analysis was performed to obtain the characteristics of the wake-meandering phenomenon. In addition, Hot-Wire Anemometry (HWA) measurements were performed in the wakes of the same wind turbines to validate the PIV results. The spectral analysis performed with the spatial and temporal signals obtained from PIV and HWA measurements respectively, led to Strouhal numbers St = fD/Uhub ≃ 0.20 - 0.22.

Stories of Success and Struggle: California's Small Farms.

ERIC Educational Resources Information Center

Warnert, Jeannette; McCue, Susan

1999-01-01

Describes the University of California's Small Farms Program, which aims to support the sustainability of small farms by providing small-scale farmers with state-of-the-art information, research, support networks, and technical assistance in technology adoption and decision making. Profiles four successful small farms that grow strawberries,…

Field Scale Monitoring and Modeling of Water and Chemical Transfer in the Vadose Zone

USDA-ARS?s Scientific Manuscript database

Natural resource systems involve highly complex interactions of soil-plant-atmosphere-management components that are extremely difficult to quantitatively describe. Computer simulations for prediction and management of watersheds, water supply areas, and agricultural fields and farms have become inc...

"Advances in Coupled Air Quality, Farm Management and ...

EPA Pesticide Factsheets

A cropland farm management modeling system for regional air quality and field-scale applications of bi-directional ammonia exchange was presented at ITM XXI. The goal of this research is to improve estimates of nitrogen deposition to terrestrial and aquatic ecosystems and ambient ammonium aerosol particle concentrations injurious to human health. These concepts have been implemented and have been released as options in CMAQ 5.01. This presentation will summarize the integration of these two models and will present model performance results relative to wet deposition measurements, ambient ammonium aerosol and ambient ammonia observations. Results indicate a shift in the timing of current U.S. agricultural emission inventories and improved CMAQ model performance. Comparison to annual wet deposition observations suggests remaining bias may be attributable primarily to precipitation model errors. Preliminary results of CMAQ deposition and ambient ammonia response to interannual variability in farm management activities will also be presented. The USEPA Office of Air and Radiation is currently considering the recommendation of the coupled model for use in standard setting activities and applications are being developed in collaboration with USEPA Office of Water and Regional Offices. The National Exposure Research Laboratory (NERL) Atmospheric Modeling and Analysis Division (AMAD) conducts research in support of EPA mission to protect human health and the envi

Negative long term effects on harbour porpoises from a large scale offshore wind farm in the Baltic—evidence of slow recovery

NASA Astrophysics Data System (ADS)

Teilmann, Jonas; Carstensen, Jacob

2012-12-01

Offshore wind farms constitute a new and fast growing industry all over the world. This study investigates the long term impact on harbour porpoises, Phocoena phocoena, for more than 10 years (2001-12) from the first large scale offshore wind farm in the world, Nysted Offshore Wind Farm, in the Danish western Baltic Sea (72 × 2.3 MW turbines). The wind farm was brought into full operation in December 2003. At six stations, acoustic porpoise detectors (T-PODs) were placed inside the wind farm area and at a reference area 10 km to the east, to monitor porpoise echolocation activity as a proxy of porpoise presence. A modified statistical BACI design was applied to detect changes in porpoise presence before, during and after construction of the wind farm. The results show that the echolocation activity has significantly declined inside Nysted Offshore Wind Farm since the baseline in 2001-2 and has not fully recovered yet. The echolocation activity inside the wind farm has been gradually increasing (from 11% to 29% of the baseline level) since the construction of the wind farm, possibly due to habituation of the porpoises to the wind farm or enrichment of the environment due to reduced fishing and to artificial reef effects.

Statistical analysis of kinetic energy entrainment in a model wind turbine array boundary layer

NASA Astrophysics Data System (ADS)

Cal, Raul Bayoan; Hamilton, Nicholas; Kang, Hyung-Suk; Meneveau, Charles

2012-11-01

For large wind farms, kinetic energy must be entrained from the flow above the wind turbines to replenish wakes and enable power extraction in the array. Various statistical features of turbulence causing vertical entrainment of mean-flow kinetic energy are studied using hot-wire velocimetry data taken in a model wind farm in a scaled wind tunnel experiment. Conditional statistics and spectral decompositions are employed to characterize the most relevant turbulent flow structures and determine their length-scales. Sweep and ejection events are shown to be the largest contributors to the vertical kinetic energy flux, although their relative contribution depends upon the location in the wake. Sweeps are shown to be dominant in the region above the wind turbine array. A spectral analysis of the data shows that large scales of the flow, about the size of the rotor diameter in length or larger, dominate the vertical entrainment. The flow is more incoherent below the array, causing decreased vertical fluxes there. The results show that improving the rate of vertical kinetic energy entrainment into wind turbine arrays is a standing challenge and would require modifying the large-scale structures of the flow. This work was funded in part by the National Science Foundation (CBET-0730922, CBET-1133800 and CBET-0953053).

Reconstruction and Validation of a Genome-Scale Metabolic Model for the Filamentous Fungus Neurospora crassa Using FARM

PubMed Central

Hood, Heather M.; Ocasio, Linda R.; Sachs, Matthew S.; Galagan, James E.

2013-01-01

The filamentous fungus Neurospora crassa played a central role in the development of twentieth-century genetics, biochemistry and molecular biology, and continues to serve as a model organism for eukaryotic biology. Here, we have reconstructed a genome-scale model of its metabolism. This model consists of 836 metabolic genes, 257 pathways, 6 cellular compartments, and is supported by extensive manual curation of 491 literature citations. To aid our reconstruction, we developed three optimization-based algorithms, which together comprise Fast Automated Reconstruction of Metabolism (FARM). These algorithms are: LInear MEtabolite Dilution Flux Balance Analysis (limed-FBA), which predicts flux while linearly accounting for metabolite dilution; One-step functional Pruning (OnePrune), which removes blocked reactions with a single compact linear program; and Consistent Reproduction Of growth/no-growth Phenotype (CROP), which reconciles differences between in silico and experimental gene essentiality faster than previous approaches. Against an independent test set of more than 300 essential/non-essential genes that were not used to train the model, the model displays 93% sensitivity and specificity. We also used the model to simulate the biochemical genetics experiments originally performed on Neurospora by comprehensively predicting nutrient rescue of essential genes and synthetic lethal interactions, and we provide detailed pathway-based mechanistic explanations of our predictions. Our model provides a reliable computational framework for the integration and interpretation of ongoing experimental efforts in Neurospora, and we anticipate that our methods will substantially reduce the manual effort required to develop high-quality genome-scale metabolic models for other organisms. PMID:23935467

Numerical analysis of the wake of a 10kW HAWT

NASA Astrophysics Data System (ADS)

Gong, S. G.; Deng, Y. B.; Xie, G. L.; Zhang, J. P.

2017-01-01

With the rising of wind power industry and the ever-growing scale of wind farm, the research for the wake performance of wind turbine has an important guiding significance for the overall arrangement of wind turbines in the large wind farm. The wake simulation model of 10kW horizontal-axis wind turbine is presented on the basis of Averaged Navier-Stokes (RANS) equations and the RNG k-ε turbulence model for applying to the rotational fluid flow. The sliding mesh technique in ANSYS CFX software is used to solve the coupling equation of velocity and pressure. The characters of the average velocity in the wake zone under rated inlet wind speed and different rotor rotational speeds have been investigated. Based on the analysis results, it is proposed that the horizontal spacing between the wind turbines is less than two times radius of rotor, and its longitudinal spacing is less than five times of radius. And other results have also been obtained, which are of great importance for large wind farms.

Integrative modeling and novel particle swarm-based optimal design of wind farms

NASA Astrophysics Data System (ADS)

Chowdhury, Souma

To meet the energy needs of the future, while seeking to decrease our carbon footprint, a greater penetration of sustainable energy resources such as wind energy is necessary. However, a consistent growth of wind energy (especially in the wake of unfortunate policy changes and reported under-performance of existing projects) calls for a paradigm shift in wind power generation technologies. This dissertation develops a comprehensive methodology to explore, analyze and define the interactions between the key elements of wind farm development, and establish the foundation for designing high-performing wind farms. The primary contribution of this research is the effective quantification of the complex combined influence of wind turbine features, turbine placement, farm-land configuration, nameplate capacity, and wind resource variations on the energy output of the wind farm. A new Particle Swarm Optimization (PSO) algorithm, uniquely capable of preserving population diversity while addressing discrete variables, is also developed to provide powerful solutions towards optimizing wind farm configurations. In conventional wind farm design, the major elements that influence the farm performance are often addressed individually. The failure to fully capture the critical interactions among these factors introduces important inaccuracies in the projected farm performance and leads to suboptimal wind farm planning. In this dissertation, we develop the Unrestricted Wind Farm Layout Optimization (UWFLO) methodology to model and optimize the performance of wind farms. The UWFLO method obviates traditional assumptions regarding (i) turbine placement, (ii) turbine-wind flow interactions, (iii) variation of wind conditions, and (iv) types of turbines (single/multiple) to be installed. The allowance of multiple turbines, which demands complex modeling, is rare in the existing literature. The UWFLO method also significantly advances the state of the art in wind farm optimization by allowing simultaneous optimization of the type and the location of the turbines. Layout optimization (using UWFLO) of a hypothetical 25-turbine commercial-scale wind farm provides a remarkable 4.4% increase in capacity factor compared to a conventional array layout. A further 2% increase in capacity factor is accomplished when the types of turbines are also optimally selected. The scope of turbine selection and placement however depends on the land configuration and the nameplate capacity of the farm. Such dependencies are not clearly defined in the existing literature. We develop response surface-based models, which implicitly employ UWFLO, to quantify and analyze the roles of these other crucial design factors in optimal wind farm planning. The wind pattern at a site can vary significantly from year to year, which is not adequately captured by conventional wind distribution models. The resulting ill-predictability of the annual distribution of wind conditions introduces significant uncertainties in the estimated energy output of the wind farm. A new method is developed to characterize these wind resource uncertainties and model the propagation of these uncertainties into the estimated farm output. The overall wind pattern/regime also varies from one region to another, which demands turbines with capabilities uniquely suited for different wind regimes. Using the UWFLO method, we model the performance potential of currently available turbines for different wind regimes, and quantify their feature-based expected market suitability. Such models can initiate an understanding of the product variation that current turbine manufacturers should pursue, to adequately satisfy the needs of the naturally diverse wind energy market. The wind farm design problems formulated in this dissertation involve highly multimodal objective and constraint functions and a large number of continuous and discrete variables. An effective modification of the PSO algorithm is developed to address such challenging problems. Continuous search, as in conventional PSO, is implemented as the primary search strategy; discrete variables are then updated using a nearest-allowed-discrete-point criterion. Premature stagnation of particles due to loss of population diversity is one of the primary drawbacks of the basic PSO dynamics. A new measure of population diversity is formulated, which unlike existing metrics capture both the overall spread and the distribution of particles in the variable space. This diversity metric is then used to apply (i) an adaptive repulsion away from the best global solution in the case of continuous variables, and (ii) a stochastic update of the discrete variables. The new PSO algorithm provides competitive performance compared to a popular genetic algorithm, when applied to solve a comprehensive set of 98 mixed-integer nonlinear programming problems.

Empirical Analysis of Farm Credit Risk under the Structure Model

ERIC Educational Resources Information Center

Yan, Yan

2009-01-01

The study measures farm credit risk by using farm records collected by Farm Business Farm Management (FBFM) during the period 1995-2004. The study addresses the following questions: (1) whether farm's financial position is fully described by the structure model, (2) what are the determinants of farm capital structure under the structure model, (3)…

Prevalence and Risk Factors of Coxiella burnetii Antibodies in Bulk Milk from Cattle, Sheep, and Goats in Jordan.

PubMed

Obaidat, Mohammad M; Kersh, Gilbert J

2017-04-01

This large-scale cross-sectional study was conducted to determine the prevalence, geographical distribution, and risk factors for the presence of antibodies against Coxiella burnetii in bulk tank milk derived from dairy cattle, sheep, and goats in Jordan. Bulk milk samples were collected from 78 dairy cattle, 48 sheep, and 23 goat farms from various places in Jordan according to the density of these animal species in each region of the country. The samples were tested for C. burnetii antibodies using the CHEKIT Q-Fever Antibody ELISA kit. A standardized questionnaire was also used to collect data from each farm to identify and rank the risk factors for the presence of C. burnetii antibodies. The results revealed that 62.9% (95% confidence interval: 55.1 to 70.0%) of the tested ruminant farms were positive for C. burnetii antibodies. Positive results were obtained from 70.9% (60.6 to 79.5%) of dairy cattle farms, 52.1% (38.3 to 65.5%) of sheep farms, and 56.0% (37.1 to 73.3%) of goat farms. Six factors were associated with the presence of these antibodies on cattle farms, and five factors were associated with these antibodies on sheep and goat farms (chi-square test). The multivariate logistic regression model revealed that large dairy cattle farms, farms that add new animals to the herd, farms that infrequently clean the feeders, and farms in particular areas are 28.6, 19.9, 8.0, and 6.4 times more likely, respectively, to have animals with C. burnetii antibodies. Sheep and goat farms that mix their animals with those from other farms, graze more than 5 km, and infrequently sanitize the feeders were 8.0, 0.06, and 13.6 times more likely, respectively, to have animals with C. burnetii antibodies. These data reveal the widespread exposure of Jordanian ruminants to C. burnetii and suggest a high risk for public health.

Centimeter-scale surface deformation caused by the 2011 Mineral, Virginia, earthquake sequence at the Carter farm site—Subsidiary structures with a quaternary history

USGS Publications Warehouse

Harrison, Richard W.; Schindler, J. Stephen; Pavich, Milan J.; Horton, J. Wright; Carter, Mark W.

2016-08-25

Centimeter-scale ground-surface deformation was produced by the August 23, 2011, magnitude (M) 5.8 earthquake that occurred in Mineral, Virginia. Ground-surface deformation also resulted from the earthquake aftershock sequence. This deformation occurred along a linear northeast-trend near Pendleton, Virginia. It is approximately 10 kilometers (km) northeast of the M5.8 epicenter and near the northeastern periphery of the epicentral area as defined by aftershocks. The ground-surface deformation extends over a distance of approximately 1.4 km and consists of parallel, small-scale (a few centimeters (cm) in amplitude) linear ridges and swales. Individual ridge and swale features are discontinuous and vary in length across a zone that ranges from about 20 meters (m) to less than 5 m in width. At one location, three fence posts and adjoining rails were vertically misaligned. Approximately 5 cm of uplift on one post provides a maximum estimate of vertical change from pre-earthquake conditions along the ridge and swale features. There was no change in the alignment of fence posts, indicating that deformation was entirely vertical. A broad monoclinal flexure with approximately 1 m of relief was identified by transit survey across surface deformation at the Carter farm site. There, surface deformation overlies the Carter farm fault, which is a zone of brittle faulting and fracturing along quartz veins, striking N40°E and dipping approximately 75°SE. Brecciation and shearing along this fault is interpreted as Quaternary in age because it disrupts the modern B-soil horizon. However, deformation is confined to saprolitized schist of the Ordovician Quantico Formation and the lowermost portion of overlying residuum, and is absent in the uppermost residuum and colluvial layer at the ground surface. Because there is a lack of surface shearing and very low relief, landslide processes were not a causative mechanism for the surface deformation. Two possible tectonic models and one non-tectonic model are considered: (1) tectonic, monoclinal flexuring along the Carter farm fault, probably aseismic, (2) tectonic, monoclinal flexuring related to a shallow (1–3 km) cluster of aftershocks (M2 to M3) that occurred approximately 1 to 1.5 km to the east of Carter farm, and (3) non-tectonic, differential response to seismic shaking between more-rigid quartz veins and soft residuum-saprolite under vertical motions that were created by Rayleigh surface waves radiating away from the August 23, 2011, hypocenter and propagating along strike of the Carter farm fault. These processes are not considered mutually exclusive, and all three support brittle deformation on the Carter farm fault during the Quaternary. In addition, abandoned stream valleys and active stream piracy are consistent with long-term uplift in vicinity of the Carter farm fault.

Evaluation model of wind energy resources and utilization efficiency of wind farm

NASA Astrophysics Data System (ADS)

Ma, Jie

2018-04-01

Due to the large amount of abandoned winds in wind farms, the establishment of a wind farm evaluation model is particularly important for the future development of wind farms In this essay, consider the wind farm's wind energy situation, Wind Energy Resource Model (WERM) and Wind Energy Utilization Efficiency Model(WEUEM) are established to conduct a comprehensive assessment of the wind farm. Wind Energy Resource Model (WERM) contains average wind speed, average wind power density and turbulence intensity, which assessed wind energy resources together. Based on our model, combined with the actual measurement data of a wind farm, calculate the indicators using the model, and the results are in line with the actual situation. We can plan the future development of the wind farm based on this result. Thus, the proposed establishment approach of wind farm assessment model has application value.

Strategies for implementing Climate Smart Agriculture and creating marketable Greenhouse emission reduction credits, for small scale rice farmers in Asia

NASA Astrophysics Data System (ADS)

Ahuja, R.; Kritee, K.; Rudek, J.; Van Sanh, N.; Thu Ha, T.

2014-12-01

Industrial agriculture systems, mostly in developed and some emerging economies, are far different from the small holder farms that dot the landscapes in Asia and Africa. At Environmental Defense Fund, along with our partners from non-governmental, corporate, academic and government sectors and farmers, we have worked actively in India and Vietnam for the last four years to better understand how small scale farmers working on rice paddy (and other upland crops) cultivation can best deal with climate change. Some of the questions we have tried to answer are: What types of implementable best practices, both old and new, on small farm systems lend themselves to improved yields, farm incomes, climate resilience and mitigation? Can these practices be replicated everywhere or is the change more landscape and people driven? What are the institutional, cultural, financial and risk-perception related barriers that prevent scaling up of these practices? How do we innovate and overcome these barriers? The research community needs to work more closely together and leverage multiple scientific, economic and policy disciplines to fully answer these questions. In the case of small farm systems, we find that it helps to follow certain steps if the climate-smart (or low carbon) farming programs are to succeed and the greenhouse credits generated are to be marketed: Demographic data collection and plot demarcation Farmer networks and diaries Rigorous baseline determination via surveys Alternative practice determination via consultation with local universities/experts Measurements on representative plots for 3-4 years (including GHG emissions, yields, inputs, economic and environmental savings) to help calibrate biogeochemical models and/or calculate regional emission factors. Propagation of alternative practices across the landscape via local NGOs/governments Recording of parameters necessary to extrapolate representative plot GHG emission reductions to all farmers in a given landscape under several existing and new carbon offset methodologies. In this presentation, we will discuss our initial encouraging results on the basis of which our wider team now seeks to identify and recommend policies that the local governments to be able to scale up climate smart agriculture to larger jurisdictional levels.

Modeling nutrient removal using watershed-scale implementation of the two-stage ditch

USDA-ARS?s Scientific Manuscript database

Western Lake Erie Basin (WLEB) is the most intensively farmed region of the Great Lakes. Because of the flat topography and poorly-drained soils many farmers rely on drainage management practices (e.g., subsurface tile drainage, ditch channelization) to maintain productive agriculture. However, th...

Where is the ideal location for a US East Coast offshore grid?

NASA Astrophysics Data System (ADS)

Dvorak, Michael J.; Stoutenburg, Eric D.; Archer, Cristina L.; Kempton, Willett; Jacobson, Mark Z.

2012-03-01

This paper identifies the location of an “ideal” offshore wind energy (OWE) grid on the U.S. East Coast that would (1) provide the highest overall and peak-time summer capacity factor, (2) use bottom-mounted turbine foundations (depth ≤50 m), (3) connect regional transmissions grids from New England to the Mid-Atlantic, and (4) have a smoothed power output, reduced hourly ramp rates and hours of zero power. Hourly, high-resolution mesoscale weather model data from 2006-2010 were used to approximate wind farm output. The offshore grid was located in the waters from Long Island, New York to the Georges Bank, ≈450 km east. Twelve candidate 500 MW wind farms were located randomly throughout that region. Four wind farms (2000 MW total capacity) were selected for their synergistic meteorological characteristics that reduced offshore grid variability. Sites likely to have sea breezes helped increase the grid capacity factor during peak time in the spring and summer months. Sites far offshore, dominated by powerful synoptic-scale storms, were included for their generally higher but more variable power output. By interconnecting all 4 farms via an offshore grid versus 4 individual interconnections, power was smoothed, the no-power events were reduced from 9% to 4%, and the combined capacity factor was 48% (gross). By interconnecting offshore wind energy farms ≈450 km apart, in regions with offshore wind energy resources driven by both synoptic-scale storms and mesoscale sea breezes, substantial reductions in low/no-power hours and hourly ramp rates can be made.

Modeling livestock population structure: a geospatial database for Ontario swine farms.

PubMed

Khan, Salah Uddin; O'Sullivan, Terri L; Poljak, Zvonimir; Alsop, Janet; Greer, Amy L

2018-01-30

Infectious diseases in farmed animals have economic, social, and health consequences. Foreign animal diseases (FAD) of swine are of significant concern. Mathematical and simulation models are often used to simulate FAD outbreaks and best practices for control. However, simulation outcomes are sensitive to the population structure used. Within Canada, access to individual swine farm population data with which to parameterize models is a challenge because of privacy concerns. Our objective was to develop a methodology to model the farmed swine population in Ontario, Canada that could represent the existing population structure and improve the efficacy of simulation models. We developed a swine population model based on the factors such as facilities supporting farm infrastructure, land availability, zoning and local regulations, and natural geographic barriers that could affect swine farming in Ontario. Assigned farm locations were equal to the swine farm density described in the 2011 Canadian Census of Agriculture. Farms were then randomly assigned to farm types proportional to the existing swine herd types. We compared the swine population models with a known database of swine farm locations in Ontario and found that the modeled population was representative of farm locations with a high accuracy (AUC: 0.91, Standard deviation: 0.02) suggesting that our algorithm generated a reasonable approximation of farm locations in Ontario. In the absence of a readily accessible dataset providing details of the relative locations of swine farms in Ontario, development of a model livestock population that captures key characteristics of the true population structure while protecting privacy concerns is an important methodological advancement. This methodology will be useful for individuals interested in modeling the spread of pathogens between farms across a landscape and using these models to evaluate disease control strategies.

Development and application of incrementally complex tools for wind turbine aerodynamics

NASA Astrophysics Data System (ADS)

Gundling, Christopher H.

Advances and availability of computational resources have made wind farm design using simulation tools a reality. Wind farms are battling two issues, affecting the cost of energy, that will make or break many future investments in wind energy. The most significant issue is the power reduction of downstream turbines operating in the wake of upstream turbines. The loss of energy from wind turbine wakes is difficult to predict and the underestimation of energy losses due to wakes has been a common problem throughout the industry. The second issue is a shorter lifetime of blades and past failures of gearboxes due to increased fluctuations in the unsteady loading of waked turbines. The overall goal of this research is to address these problems by developing a platform for a multi-fidelity wind turbine aerodynamic performance and wake prediction tool. Full-scale experiments in the field have dramatically helped researchers understand the unique issues inside a large wind farm, but experimental methods can only be used to a limited extent due to the cost of such field studies and the size of wind farms. The uncertainty of the inflow is another inherent drawback of field experiments. Therefore, computational fluid dynamics (CFD) predictions, strategically validated using carefully performed wind farm field campaigns, are becoming a more standard design practice. The developed CFD models include a blade element model (BEM) code with a free-vortex wake, an actuator disk or line based method with large eddy simulations (LES) and a fully resolved rotor based method with detached eddy simulations (DES) and adaptive mesh refinement (AMR). To create more realistic simulations, performance of a one-way coupling between different mesoscale atmospheric boundary layer (ABL) models and the three microscale CFD solvers is tested. These methods are validated using data from incrementally complex test cases that include the NREL Phase VI wind tunnel test, the Sexbierum wind farm and the Lillgrund offshore wind farm. By cross-comparing the lowest complexity free-vortex method with the higher complexity methods, a fast and accurate simulation tool has been generated that can perform wind farm simulations in a few hours.

Measurements of Heat Flux Differences Within a Large Wind Farm During the 2013 Crop/Wind-Energy Experiment (CWEX-13)

NASA Astrophysics Data System (ADS)

Rajewski, D. A.

2015-12-01

Wind farms are an important resource for electrical generation in the Central U.S., however with each installation there are many poorly documented interactions with the local and surrounding environment. The impact of wind farms on surface microclimate is largely understood conceptually using numerical or wind tunnel models or ex situ satellite-detected changes. Measurements suitable for calibration of numerical simulations are few and of limited applicability but are urgently needed to improve parameterization of wind farm aerodynamics influenced by the diurnal evolution of the boundary layer. Among large eddy simulations of wind farm wakes in thermally stable stratification, there are discrepancies on the influence of turbine-induced mixing on the surface heat flux. We provide measurements from seven surface flux stations, vertical profiling LiDARs located upwind and downwind of turbines, and SCADA measurements from turbines during the 2013 Crop Wind Energy Experiment (CWEX-13) as the best evidence for the variability of turbine induced heat flux within a large wind farm. Examination of ambient conditions (wind direction, wind veer, and thermal stratification) and on turbine operation factors (hub-height wind speed, normalized power) reveal conditions that lead to the largest modification of heat flux. Our results demonstrate the highest flux change from the reference station to be where the leading few lines of turbines influence the surface. Under stably stratified conditions turbine-scale turbulence is highly efficient at bringing warmer air aloft to the surface, leading to an increase in downward heat flux. Conversely we see that the combination of wakes from several lines of turbines reduces the flux contrast from the reference station. In this regime of deep wind-farm flow, wake turbulence is similar in scale and intensity to the reference conditions. These analysis tools can be extended to other turbine SCADA and microclimate variables (e.g. temperature) to improve basic understanding of turbine-turbine and total wind farm wake interactions. Forthcoming tall-tower measurements will provide additional opportunities for comparison of simulated wind and thermal profiles in non-wake, and waked flow conditions.

EFFECTS OF LARGE-SCALE POULTRY FARMS ON AQUATIC MICROBIAL COMMUNITIES: A MOLECULAR INVESTIGATION.

EPA Science Inventory

The effects of large-scale poultry production operations on water quality and human health are largely unknown. Poultry litter is frequently applied as fertilizer to agricultural lands adjacent to large poultry farms. Run-off from the land introduces a variety of stressors into t...

China’s new-age small farms and their vertical integration: agribusiness or co-ops?

PubMed

Huang, Philip C C

2011-01-01

The future of Chinese agriculture lies not with large mechanized farms but with small capital-labor dual intensifying family farms for livestock-poultry-fish raising and vegetable-fruit cultivation. Chinese food consumption patterns have been changing from the old 8:1:1 pattern of 8 parts grain, 1 part meat, and 1 part vegetables to a 4:3:3 pattern, with a corresponding transformation in agricultural structure. Small family-farming is better suited for the new-age agriculture, including organic farming, than large-scale mechanized farming, because of the intensive, incremental, and variegated hand labor involved, not readily open to economies of scale, though compatible with economies of scope. It is also better suited to the realities of severe population pressure on land. But it requires vertical integration from cultivation to processing to marketing, albeit without horizontal integration for farming. It is against such a background that co-ops have arisen spontaneously for integrating small farms with processing and marketing. The Chinese government, however, has been supporting aggressively capitalistic agribusinesses as the preferred mode of vertical integration. At present, Chinese agriculture is poised at a crossroads, with the future organizational mode for vertical integration as yet uncertain.

Field Scale Spatial Modelling of Surface Soil Quality Attributes in Controlled Traffic Farming

NASA Astrophysics Data System (ADS)

Guenette, Kris; Hernandez-Ramirez, Guillermo

2017-04-01

The employment of controlled traffic farming (CTF) can yield improvements to soil quality attributes through the confinement of equipment traffic to tramlines with the field. There is a need to quantify and explain the spatial heterogeneity of soil quality attributes affected by CTF to further improve our understanding and modelling ability of field scale soil dynamics. Soil properties such as available nitrogen (AN), pH, soil total nitrogen (STN), soil organic carbon (SOC), bulk density, macroporosity, soil quality S-Index, plant available water capacity (PAWC) and unsaturated hydraulic conductivity (Km) were analysed and compared among trafficked and un-trafficked areas. We contrasted standard geostatistical methods such as ordinary kriging (OK) and covariate kriging (COK) as well as the hybrid method of regression kriging (ROK) to predict the spatial distribution of soil properties across two annual cropland sites actively employing CTF in Alberta, Canada. Field scale variability was quantified more accurately through the inclusion of covariates; however, the use of ROK was shown to improve model accuracy despite the regression model composition limiting the robustness of the ROK method. The exclusion of traffic from the un-trafficked areas displayed significant improvements to bulk density, macroporosity and Km while subsequently enhancing AN, STN and SOC. The ability of the regression models and the ROK method to account for spatial trends led to the highest goodness-of-fit and lowest error achieved for the soil physical properties, as the rigid traffic regime of CTF altered their spatial distribution at the field scale. Conversely, the COK method produced the most optimal predictions for the soil nutrient properties and Km. The use of terrain covariates derived from light ranging and detection (LiDAR), such as of elevation and topographic position index (TPI), yielded the best models in the COK method at the field scale.

Landscape Level Carbon and Water Balances and Agricultural Production in Mountainous Terrain of the Haean Basin, South Korea

NASA Astrophysics Data System (ADS)

Lee, B.; Geyer, R.; Seo, B.; Lindner, S.; Walther, G.; Tenhunen, J. D.

2009-12-01

The process-based spatial simulation model PIXGRO was used to estimate gross primary production, ecosystem respiration, net ecosystem CO2 exchange and water use by forest and crop fields of Haean Basin, South Korea at landscape scale. Simulations are run for individual years from early spring to late fall, providing estimates for dry land crops and rice paddies with respect to carbon gain, biomass and leaf area development, allocation of photoproducts to the belowground ecosystem compartment, and harvest yields. In the case of deciduous oak forests, gas exchange is estimated, but spatial simulation of growth over the single annual cycles is not included. Spatial parameterization of the model is derived for forest LAI based on remote sensing, for forest and cropland fluxes via eddy covariance and chamber studies, for soil characteristics by generalization from spatial surveys, for climate drivers by generalizing observations at ca. 20 monitoring stations distributed throughout the basin and along the elevation gradient from 500 to 1000 m, and for incident radiation via modelling of the radiation components in complex terrain. Validation of the model is being carried out at point scale based on comparison of model output at selected locations with observations as well as with known trends in ecosystem response documented in the literature. The resulting modelling tool is useful for estimation of ecosystem services at landscape scale, first expressed as kg ha-1 crop yield, but via future cooperative studies also in terms of monetary gain to individual farms and farming cooperatives applying particular management strategies.

Farmers' contribution to landscape services in the Netherlands under different rural development scenarios.

PubMed

Pfeifer, Catherine; Sonneveld, Marthijn P W; Stoorvogel, Jetse J

2012-11-30

Landscape services represent the benefits human populations derive, directly or indirectly, from (agro-)ecosystem functions at the landscape scale. Many of these services are the result of farmers' decision making to allocate resources to other activities than food production and therefore are the result of farm the adoption of on-farm rural activities. With changing agricultural and rural policies, the future provision of landscape services to fulfill societal demands is not guaranteed. This study aims at mapping the spatial distribution of the adoption of on-farm rural activities under different explorative scenarios. For a Dutch landscape, storylines at the landscape scale were developed by combining global storylines, resulting from the Global Environmental Outlook, with local storylines resulting from key informant interviews. Subsequently these storylines were translated into quantitative scenarios that were implemented into a simulation procedure based on spatially explicit econometric models of farmer's decision making. Results show that further market liberalization leads to a decrease of landscape services in the study area. In our study, only increased cooperation between government, farmers and citizens appears to result in a general increase of all landscape services across the entire landscape. Copyright © 2012 Elsevier Ltd. All rights reserved.

Water temperature, body mass and fasting heat production of pacu (Piaractus mesopotamicus).

PubMed

Aguilar, Fredy A A; Cruz, Thaline M P DA; Mourão, Gerson B; Cyrino, José Eurico P

2017-01-01

Knowledge on fasting heat production (HEf) of fish is key to develop bioenergetics models thus improving feeding management of farmed species. The core of knowledge on HEf of farmed, neotropical fish is scarce. This study assessed the effect of body mass and water temperature on standard metabolism and fasting heat production of pacu, Piaractus mesopotamicus, an omnivore, Neotropical fresh water characin important for farming and fisheries industries all through South American continent. An automated, intermittent flow respirometry system was used to measure standard metabolic rate (SMR) of pacu (17 - 1,050 g) at five water temperatures: 19, 23, 26, 29 and 33 °C. Mass specific SMR increased with increasing water temperature but decreased as function of body mass. The allometric exponent for scaling HEf was 0.788, and lied in the range recorded for all studied warm-water fish. The recorded van't Hoff factor (Q10) for pacu (2.06) shows the species low response to temperature increases. The model HEf = 0.04643×W0.7882×T1.837 allows to predict HEf (kJ d-1) from body mass (W, kg) and water temperature (T, °C), and can be used in bioenergetical models for the species.

Collaborative Catchment-Scale Water Quality Management using Integrated Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Zia, Huma; Harris, Nick; Merrett, Geoff

2013-04-01

Electronics and Computer Science, University of Southampton, United Kingdom Summary The challenge of improving water quality (WQ) is a growing global concern [1]. Poor WQ is mainly attributed to poor water management and outdated agricultural activities. We propose that collaborative sensor networks spread across an entire catchment can allow cooperation among individual activities for integrated WQ monitoring and management. We show that sharing information on critical parameters among networks of water bodies and farms can enable identification and quantification of the contaminant sources, enabling better decision making for agricultural practices and thereby reducing contaminants fluxes. Motivation and results Nutrient losses from land to water have accelerated due to agricultural and urban pursuits [2]. In many cases, the application of fertiliser can be reduced by 30-50% without any loss of yield [3]. Thus information about nutrient levels and trends around the farm can improve agricultural practices and thereby reduce water contamination. The use of sensor networks for monitoring WQ in a catchment is in its infancy, but more applications are being tested [4]. However, these are focussed on local requirements and are mostly limited to water bodies. They have yet to explore the use of this technology for catchment-scale monitoring and management decisions, in an autonomous and dynamic manner. For effective and integrated WQ management, we propose a system that utilises local monitoring networks across a catchment, with provision for collaborative information sharing. This system of networks shares information about critical events, such as rain or flooding. Higher-level applications make use of this information to inform decisions about nutrient management, improving the quality of monitoring through the provision of richer datasets of catchment information to local networks. In the full paper, we present example scenarios and analyse how the benefits of collaborative information sharing can have a direct influence on agricultural practice. We apply a nutrient management scheme to a model of an example catchment with several individual networks. The networks are able to correlate catchment events to events within their zone of influence, allowing them to adapt their monitoring and control strategy in light of wider changes across the catchment. Results indicate that this can lead to significant reductions in nutrient losses (up to 50%) and better reutilization of nutrients amongst farms, having a positive impact on catchment scale water quality and fertilizer costs. 1. EC, E.C., Directive 2000/60/EC establishing a framework for Community action in the field of water policy, 2000. 2. Rivers, M., K. Smettem, and P. Davies. Estimating future scenarios for farm-watershed nutrient fluxes using dynamic simulation modelling-Can on-farm BMPs really do the job at the watershed scale? in Proc.29th Int.Conf System Dynamics Society, 2011. 2010. Washington 3. Liu, C., et al., On-farm evaluation of winter wheat yield response to residual soil nitrate-N in North China Plain. Agronomy Journal, 2008. 100(6): p. 1527-1534. 4. Kotamäki, N., et al., Wireless in-situ sensor network for agriculture and water monitoring on a river basin scale in Southern Finland: Evaluation from a data user's perspective. Sensors, 2009. 9(4): p. 2862-2883.

Quantitative microbial risk assessment for spray irrigation of dairy manure based on an empirical fate and transport model

USDA-ARS?s Scientific Manuscript database

Background: Spray irrigation for land-applying livestock manure is increasing in the United States as farms become larger and economies of scale make manure irrigation affordable. However, human health risks from exposure to zoonotic pathogens aerosolized during manure irrigation are not well-unders...

Not Your Family Farm

ERIC Educational Resources Information Center

Tenopir, Carol; Baker, Gayle; Grogg, Jill E.

2007-01-01

The information industry continues to consolidate, just as agribusiness has consolidated and now dominates farming. Both the family farm and the small information company still exist but are becoming rarer in an age of mergers, acquisitions, and increased economies of scale. Small companies distinguish themselves by high quality, special themes,…

Applying additive logistic regression to data derived from sensors monitoring behavioral and physiological characteristics of dairy cows to detect lameness.

PubMed

Kamphuis, C; Frank, E; Burke, J K; Verkerk, G A; Jago, J G

2013-01-01

The hypothesis was that sensors currently available on farm that monitor behavioral and physiological characteristics have potential for the detection of lameness in dairy cows. This was tested by applying additive logistic regression to variables derived from sensor data. Data were collected between November 2010 and June 2012 on 5 commercial pasture-based dairy farms. Sensor data from weigh scales (liveweight), pedometers (activity), and milk meters (milking order, unadjusted and adjusted milk yield in the first 2 min of milking, total milk yield, and milking duration) were collected at every milking from 4,904 cows. Lameness events were recorded by farmers who were trained in detecting lameness before the study commenced. A total of 318 lameness events affecting 292 cows were available for statistical analyses. For each lameness event, the lame cow's sensor data for a time period of 14 d before observation date were randomly matched by farm and date to 10 healthy cows (i.e., cows that were not lame and had no other health event recorded for the matched time period). Sensor data relating to the 14-d time periods were used for developing univariable (using one source of sensor data) and multivariable (using multiple sources of sensor data) models. Model development involved the use of additive logistic regression by applying the LogitBoost algorithm with a regression tree as base learner. The model's output was a probability estimate for lameness, given the sensor data collected during the 14-d time period. Models were validated using leave-one-farm-out cross-validation and, as a result of this validation, each cow in the data set (318 lame and 3,180 nonlame cows) received a probability estimate for lameness. Based on the area under the curve (AUC), results indicated that univariable models had low predictive potential, with the highest AUC values found for liveweight (AUC=0.66), activity (AUC=0.60), and milking order (AUC=0.65). Combining these 3 sensors improved AUC to 0.74. Detection performance of this combined model varied between farms but it consistently and significantly outperformed univariable models across farms at a fixed specificity of 80%. Still, detection performance was not high enough to be implemented in practice on large, pasture-based dairy farms. Future research may improve performance by developing variables based on sensor data of liveweight, activity, and milking order, but that better describe changes in sensor data patterns when cows go lame. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Three-dimensional modelling for assessment of far-field impact of tidal stream turbine: A case study at the Anglesey Coast, Wales, UK

NASA Astrophysics Data System (ADS)

Li, Xiaorong; Li, Ming; Wolf, Judith

2017-04-01

As a response to worldwide climate change, clean non-carbon renewable energy resources have been gaining significant attention. Among a range of renewable alternatives, tidal stream energy is considered very promising; due to its consistent predictability and availability. To investigate impacts of tidal stream devices on their surroundings, prototype experiments involving small scale laboratory studies have been implemented. Computational Flow Dynamics (CFD) modelling is also commonly applied to study turbine behaviours. However, these studies focus on impacts of the turbine in the near-field scale. As a result, in order to study and predict the far-field impacts caused by the operation of turbines, large scale 2D and 3D numerical oceanography models have been used, with routines added to reflect the impacts of turbines. In comparison to 2D models, 3D models are advantageous in providing complete prediction of vertical flow structures and hence mixing in the wake of a turbine. This research aims to deliver a thorough 3D tidal stream turbine simulation system, by considering major coastal processes, i.e. current, waves and sediment transport, based on a 3D wave-current-sediment fully coupled numerical oceanography model — the Unstructured Grid Finite Volume Community Ocean Model (FVCOM). The energy extraction of turbines is simulated by adding a body force to the momentum equations. Across the water depth, the coefficient related to the additional body force is given different values according to the turbine configuration and operation to reflect the vertical variation of the turbine's impacts on the passing flow. Three turbulence perturbation terms are added to the turbulence closure to simulate the turbine-induced turbulence generation, dissipation and interference for the turbulence length-scale. Impacts of turbine operation on surface waves are also considered by modification of wave energy flux across the device. A thorough validation study is carried out in which the developed model is tested; based on a combination of laboratory measured data and CFD simulated results. The developed turbine simulation system is then applied to the Anglesey coast, North Wales, UK for a case study. The validation study suggests that the developed turbine simulation system is able to accurately simulate both hydrodynamics and wave dynamics in the turbine wake. The case study with 18 turbines (diameter is 15 m) modelled individually in the waterway between the north-west Anglesey and the Skerries reveals impacts of the turbine farm on free surface elevation, flow field, turbulence kinetic energy (TKE), surface waves, bottom shear stress and suspended sediment transport. The wake is observable up to 4.5 km downstream of the device farm. Flow near the bed in the wake is accelerated, leading to enhanced bottom shear stress. The device farm has a strong influence on TKE and hence the vertical mixing of suspended sediment in the wake. Further, the eastwards directed residual sediment transport along the north coast of Anglesey is found to be weakened by the turbine farm.

Modelling Management Practices in Viticulture while Considering Resource Limitations: The Dhivine Model

PubMed Central

Martin-Clouaire, Roger; Rellier, Jean-Pierre; Paré, Nakié; Voltz, Marc; Biarnès, Anne

2016-01-01

Many farming-system studies have investigated the design and evaluation of crop-management practices with respect to economic performance and reduction in environmental impacts. In contrast, little research has been devoted to analysing these practices in terms of matching the recurrent context-dependent demand for resources (labour in particular) with those available on the farm. This paper presents Dhivine, a simulation model of operational management of grape production at the vineyard scale. Particular attention focuses on representing a flexible plan, which organises activities temporally, the resources available to the vineyard manager and the process of scheduling and executing the activities. The model relies on a generic production-system ontology used in several agricultural production domains. The types of investigations that the model supports are briefly illustrated. The enhanced realism of the production-management situations simulated makes it possible to examine and understand properties of resource-constrained work-organisation strategies and possibilities for improving them. PMID:26990089

What conservationists need to know about farming

PubMed Central

Balmford, Andrew; Green, Rhys; Phalan, Ben

2012-01-01

Farming is the basis of our civilization yet is more damaging to wild nature than any other sector of human activity. Here, we propose that in order to limit its impact into the future, conservation researchers and practitioners need to address several big topics—about the scale of future demand, about which crops and livestock to study, about whether low-yield or high-yield farming has the potential to be least harmful to nature, about the environmental performance of new and existing farming methods, and about the measures needed to enable promising approaches and techniques to deliver on their potential. Tackling these issues requires conservationists to explore the many consequences that decisions about agriculture have beyond the farm, to think broadly and imaginatively about the scale and scope of what is required to halt biodiversity loss, and to be brave enough to test and when necessary support counterintuitive measures. PMID:22535780

Diffusion of a Sustainable Farming Technique in Sri Lanka: An Agent-Based Modeling Approach

NASA Astrophysics Data System (ADS)

Jacobi, J. H.; Gilligan, J. M.; Carrico, A. R.; Truelove, H. B.; Hornberger, G.

2012-12-01

We live in a changing world - anthropogenic climate change is disrupting historic climate patterns and social structures are shifting as large scale population growth and massive migrations place unprecedented strain on natural and social resources. Agriculture in many countries is affected by these changes in the social and natural environments. In Sri Lanka, rice farmers in the Mahaweli River watershed have seen increases in temperature and decreases in precipitation. In addition, a government led resettlement project has altered the demographics and social practices in villages throughout the watershed. These changes have the potential to impact rice yields in a country where self-sufficiency in rice production is a point of national pride. Studies of the climate can elucidate physical effects on rice production, while research on social behaviors can illuminate the influence of community dynamics on agricultural practices. Only an integrated approach, however, can capture the combined and interactive impacts of these global changes on Sri Lankan agricultural. As part of an interdisciplinary team, we present an agent-based modeling (ABM) approach to studying the effects of physical and social changes on farmers in Sri Lanka. In our research, the diffusion of a sustainable farming technique, the system of rice intensification (SRI), throughout a farming community is modeled to identify factors that either inhibit or promote the spread of a more sustainable approach to rice farming. Inputs into the ABM are both physical and social and include temperature, precipitation, the Palmer Drought Severity Index (PDSI), community trust, and social networks. Outputs from the ABM demonstrate the importance of meteorology and social structure on the diffusion of SRI throughout a farming community.

Wind power prediction based on genetic neural network

NASA Astrophysics Data System (ADS)

Zhang, Suhan

2017-04-01

The scale of grid connected wind farms keeps increasing. To ensure the stability of power system operation, make a reasonable scheduling scheme and improve the competitiveness of wind farm in the electricity generation market, it's important to accurately forecast the short-term wind power. To reduce the influence of the nonlinear relationship between the disturbance factor and the wind power, the improved prediction model based on genetic algorithm and neural network method is established. To overcome the shortcomings of long training time of BP neural network and easy to fall into local minimum and improve the accuracy of the neural network, genetic algorithm is adopted to optimize the parameters and topology of neural network. The historical data is used as input to predict short-term wind power. The effectiveness and feasibility of the method is verified by the actual data of a certain wind farm as an example.

Managing farmed closed depressional areas using blind inlets to minimize phosphorus and nitrogen losses

USDA-ARS?s Scientific Manuscript database

Through watershed scale research in the St. Joseph River watershed in the United States, farmed potholes have been identified as contributing to nutrient loading of streams. Most farmed potholes are drained with tile risers, which are direct conduits for runoff water and associated contaminants dire...

Economic and phosphorus-related effects of precision feeding and forage management at a farm scale

USDA-ARS?s Scientific Manuscript database

A system-level redesign of farm management is needed to maintain economic viability of the farm while addressing phosphorous imbalance problems caused by many current practices. One innovative strategy, precision feed management (PFM), reduces soil-phosphorus build-up by limiting feed and fertilizer...

FARM WASTE TO ENERGY: A SUSTAINABLE SOLUTION FOR SMALL-SCALE FARMS

EPA Science Inventory

Through this project, it was determined that the utilization of anaerobic digestion on small farms for the purpose of managing varying waste streams and odor issues and decreasing fossil fuel consumption and cost was feasible. The feedstocks necessary to run the digester are r...

Ten Years of Plant Pathology Research at the Cook Agronomy Farm: What Have We Learned?

USDA-ARS?s Scientific Manuscript database

The Cook Agronomy Farm has provided important information for understanding root diseases under directseeded conditions in the higher rainfall annual cropping zones of the Palouse, at a landscape scale. This farm has served as an important outdoor laboratory to test disease management techniques suc...

Estimating the effect of mastitis on the profitability of Irish dairy farms.

PubMed

Geary, U; Lopez-Villalobos, N; Begley, N; McCoy, F; O'Brien, B; O'Grady, L; Shalloo, L

2012-07-01

The objective of this paper was to estimate the effect of the costs of mastitis on the profitability of Irish dairy farms as indicated by various ranges of bulk milk somatic cell count (BMSCC). Data were collected from 4 sources and included milk production losses, cases treated, and on-farm practices around mastitis management. The Moorepark Dairy Systems Model, which simulates dairying systems inside the farm gate, was used to carry out the analysis. The cost components of mastitis that affect farm profitability and that were included in the model were milk losses, culling, diagnostic testing, treatment, veterinary attention, discarded milk, and penalties. Farms were grouped by 5 BMSCC thresholds of ≤ 100,000, 100,001-200,000, 200,001-300,000, 300,001-400,000, and > 400,000 cells/mL. The ≤ 100,000 cells/mL threshold was taken as the baseline and the other 4 thresholds were compared relative to this baseline. For a 40-ha farm, the analysis found that as BMSCC increased, milk receipts decreased from €148,843 at a BMSCC <100,000 cells/mL to €138,573 at a BMSCC > 400,000 cells/mL. In addition, as BMSCC increased, livestock receipts increased by 17%, from €43,304 at a BMSCC <100,000 cells/mL to €50,519 at a BMSCC > 400,000 cells/mL. This reflected the higher replacement rates as BMSCC increased and the associated cull cow value. Total farm receipts decreased from €192,147 at the baseline (< 100,000 cells/mL) to €189,091 at a BMSCC > 400,000 cells/mL. Total farm costs increased as BMSCC increased, reflecting treatment, veterinary, diagnostic testing, and replacement heifer costs. At the baseline, total farm costs were €161,085, increasing to €177,343 at a BMSCC > 400,000 cells/mL. Net farm profit decreased as BMSCC increased, from €31,252/yr at the baseline to €11,748/yr at a BMSCC > 400,000 cells/mL. This analysis highlights the impact that mastitis has on the profitability of Irish dairy farms. The analysis presented here can be used to develop a "cost of mastitis" tool for use on Irish dairy farms to motivate farmers to acknowledge the scale of the problem, realize the value of improving mastitis control, and implement effective mastitis control practices. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Toward understanding the physical link between turbines and microclimate impacts from in situ measurements in a large wind farm

NASA Astrophysics Data System (ADS)

Rajewski, Daniel A.; Takle, Eugene S.; Prueger, John H.; Doorenbos, Russell K.

2016-11-01

Recent wind farm studies have revealed elevated nighttime surface temperatures but have not validated physical mechanisms that create the observed effects. We report measurements of concurrent differences in surface wind speed, temperature, fluxes, and turbulence upwind and downwind of two turbine lines at the windward edge of a utility-scale wind farm. On the basis of these measurements, we offer a conceptual model based on physical mechanisms of how wind farms affect their own microclimate. Periods of documented curtailment and zero-power production of the wind farm offer useful opportunities to rigorously evaluate the microclimate impact of both stationary and operating turbines. During an 80 min nighttime wind farm curtailment, we measured abrupt and large changes in turbulent fluxes of momentum and heat leeward of the turbines. At night, wind speed decreases in the near wake when turbines are off but abruptly increases when turbine operation is resumed. Our measurements are compared with Moderate Resolution Imaging Spectroradiometer Terra and Aqua satellite measurements reporting wind farms to have higher nighttime surface temperatures. We demonstrate that turbine wakes modify surface fluxes continuously through the night, with similar magnitudes during the Terra and Aqua transit periods. Cooling occurs in the near wake and warming in the far wake when turbines are on, but cooling is negligible when turbines are off. Wind speed and surface stratification have a regulating effect of enhancing or decreasing the impact on surface microclimate due to turbine wake effects.

Feeding strategies and manure management for cost-effective mitigation of greenhouse gas emissions from dairy farms in Wisconsin.

PubMed

Dutreuil, M; Wattiaux, M; Hardie, C A; Cabrera, V E

2014-09-01

Greenhouse gas (GHG) emissions from dairy farms are a major concern. Our objectives were to assess the effect of mitigation strategies on GHG emissions and net return to management on 3 distinct farm production systems of Wisconsin. A survey was conducted on 27 conventional farms, 30 grazing farms, and 69 organic farms. The data collected were used to characterize 3 feeding systems scaled to the average farm (85 cows and 127ha). The Integrated Farm System Model was used to simulate the economic and environmental impacts of altering feeding and manure management in those 3 farms. Results showed that incorporation of grazing practices for lactating cows in the conventional farm led to a 27.6% decrease in total GHG emissions [-0.16kg of CO2 equivalents (CO2eq)/kg of energy corrected milk (ECM)] and a 29.3% increase in net return to management (+$7,005/yr) when milk production was assumed constant. For the grazing and organic farms, decreasing the forage-to-concentrate ratio in the diet decreased GHG emissions when milk production was increased by 5 or 10%. The 5% increase in milk production was not sufficient to maintain the net return; however, the 10% increase in milk production increased net return in the organic farm but not on the grazing farm. A 13.7% decrease in GHG emissions (-0.08kg of CO2eq/kg of ECM) was observed on the conventional farm when incorporating manure the day of application and adding a 12-mo covered storage unit. However, those same changes led to a 6.1% (+0.04kg of CO2eq/kg of ECM) and a 6.9% (+0.06kg of CO2eq/kg of ECM) increase in GHG emissions in the grazing and the organic farms, respectively. For the 3 farms, manure management changes led to a decrease in net return to management. Simulation results suggested that the same feeding and manure management mitigation strategies led to different outcomes depending on the farm system, and furthermore, effective mitigation strategies were used to reduce GHG emissions while maintaining profitability within each farm. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

The greenhouse gas balance of European grasslands.

PubMed

Chang, Jinfeng; Ciais, Philippe; Viovy, Nicolas; Vuichard, Nicolas; Sultan, Benjamin; Soussana, Jean-François

2015-10-01

The greenhouse gas (GHG) balance of European grasslands (EU-28 plus Norway and Switzerland), including CO2 , CH4 and N2 O, is estimated using the new process-based biogeochemical model ORCHIDEE-GM over the period 1961-2010. The model includes the following: (1) a mechanistic representation of the spatial distribution of management practice; (2) management intensity, going from intensively to extensively managed; (3) gridded simulation of the carbon balance at ecosystem and farm scale; and (4) gridded simulation of N2 O and CH4 emissions by fertilized grassland soils and livestock. The external drivers of the model are changing animal numbers, nitrogen fertilization and deposition, land-use change, and variable CO2 and climate. The carbon balance of European grassland (NBP) is estimated to be a net sink of 15 ± 7 g C m(-2 ) year(-1) during 1961-2010, equivalent to a 50-year continental cumulative soil carbon sequestration of 1.0 ± 0.4 Pg C. At the farm scale, which includes both ecosystem CO2 fluxes and CO2 emissions from the digestion of harvested forage, the net C balance is roughly halved, down to a small sink, or nearly neutral flux of 8 g C m(-2 ) year(-1) . Adding CH4 and N2 O emissions to net ecosystem exchange to define the ecosystem-scale GHG balance, we found that grasslands remain a net GHG sink of 19 ± 10 g C-CO2 equiv. m(-2 ) year(-1) , because the CO2 sink offsets N2 O and grazing animal CH4 emissions. However, when considering the farm scale, the GHG balance (NGB) becomes a net GHG source of -50 g C-CO2 equiv. m(-2 ) year(-1) . ORCHIDEE-GM simulated an increase in European grassland NBP during the last five decades. This enhanced NBP reflects the combination of a positive trend of net primary production due to CO2 , climate and nitrogen fertilization and the diminishing requirement for grass forage due to the Europe-wide reduction in livestock numbers. © 2015 John Wiley & Sons Ltd.

Spatiotemporal structure of wind farm-atmospheric boundary layer interactions

NASA Astrophysics Data System (ADS)

Cervarich, Matthew; Baidya Roy, Somnath; Zhou, Liming

2013-04-01

Wind power is currently one of the fastest growing energy sources in the world. Most of the growth is in the utility sector consisting of large wind farms with numerous industrial-scale wind turbines. Wind turbines act as a sink of mean kinetic energy and a source of turbulent kinetic energy in the atmospheric boundary layer (ABL). In doing so, they modify the ABL profiles and land-atmosphere exchanges of energy, momentum, mass and moisture. This project explores theses interactions using remote sensing data and numerical model simulations. The domain is central Texas where 4 of the world's largest wind farms are located. A companion study of seasonally-averaged Land Surface Temperature data from the Moderate Resolution Imaging Spectroradiometer (MODIS) on TERRA and AQUA satellites shows a warming signal at night and a mixed cooling/warming signal during the daytime within the wind farms. In the present study, wind farm-ABL interactions are simulated with the Weather Research and Forecasting (WRF) model. The simulations show that the model is capable of replicating the observed signal in land surface temperature. Moreover, similar warming/cooling effect, up to 1C, was observed in seasonal mean 2m air temperature as well. Further analysis show that enhanced turbulent mixing in the rotor wakes is responsible for the impacts on 2m and surface air temperatures. The mixing is due to 2 reasons: (i) turbulent momentum transport to compensate the momentum deficit in the wakes of the turbines and (ii) turbulence generated due to motion of turbine rotors. Turbulent mixing also alters vertical profiles of moisture. Changes in land-atmosphere temperature and moisture gradient and increase in turbulent mixing leads to more than 10% change in seasonal mean surface sensible and latent heat flux. Given the current installed capacity and the projected installation across the world, wind farms are likely becoming a major driver of anthropogenic land use change on Earth. Hence, understanding WF-ABL interactions and its effects is of significant scientific and societal importance.

Within-farm transmission dynamics of foot and mouth disease as revealed by the 2001 epidemic in Great Britain.

PubMed

Chis Ster, Irina; Dodd, Peter J; Ferguson, Neil M

2012-08-01

This paper uses statistical and mathematical models to examine the potential impact of within-farm transmission dynamics on the spread of the 2001 foot and mouth disease (FMD) outbreak in Great Britain. We partly parameterize a simple within farm transmission model using data from experimental studies of FMD pathogenesis, embed this model within an existing between-farm transmission model, and then estimate unknown parameters (such as the species-specific within-farm reproduction number) from the 2001 epidemic case data using Markov Chain Monte-Carlo (MCMC) methods. If the probability of detecting an infected premises depends on farm size and species mix then the within-farm species specific basic reproduction ratios for baseline models are estimated to be 21 (16, 25) and 14 (10, 19) for cattle and sheep, respectively. Alternatively, if detection is independent of farm size, then the corresponding estimates are 49 (41, 61) and 10 (1.4, 21). Both model variants predict that the average fraction of total farm infectiousness accumulated prior to detection of infection on an IP is about 30-50% in cattle or mixed farms. The corresponding estimate for sheep farms depended more on the detection model, being 65-80% if detection was linked to the farms' characteristics, but only 25% if not. We highlighted evidence which reinforces the role of within-farm dynamics in contributing to the long tail of the 2001 epidemic. Copyright © 2012 Elsevier B.V. All rights reserved.

Plot-, farm-, and watershed-scale effects of coffee cultivation in runoff and sediment production in western Puerto Rico.

PubMed

Ramos-Scharrón, Carlos E; Figueroa-Sánchez, Yasiel

2017-11-01

The combination of a topographically abrupt wet-tropical setting with the high level of soil exposure that typifies many sun-grown coffee farms represents optimal conditions for high erosion rates. Although traditionally considered as a main cause for water resource degradation, limited empirical evidence has existed to document its true contribution. This study relies on plot-scale experimental results conducted in western Puerto Rico to assess the impact of cultivated surfaces and farm access roads on runoff and sediment production from the plot to the farm and watershed scales. Results show that unsurfaced and graveled road surfaces produce one- to two-orders of magnitude more per unit area runoff than cultivated lands. Similarly, erosion rates from unsurfaced roads are about 102 g m -2 per cm of rainfall and these are two-orders of magnitude greater than from actively cultivated surfaces. Mitigation practices such as uncompacting road surfaces by ripping and gravel application reduce onsite erosion rates to 0.6% and 8% of unsurfaced conditions, respectively. At the farm scale, coffee farms are estimated to produce sediment at a rate of 12-18 Mg ha -1 yr -1 , and roads are undoubtedly the dominant sediment source responsible for 59-95% of the total sediment produced. The costs associated to ameliorating erosion problems through road graveling are high. Therefore, a combined approach that treats road erosion onsite with one that traps sediment before it reaches river networks is the viable solution to this problem. Copyright © 2017 Elsevier Ltd. All rights reserved.

High Bee and Wasp Diversity in a Heterogeneous Tropical Farming System Compared to Protected Forest

PubMed Central

Schüepp, Christof; Rittiner, Sarah; Entling, Martin H.

2012-01-01

It is a globally important challenge to meet increasing demands for resources and, at the same time, protect biodiversity and ecosystem services. Farming is usually regarded as a major threat to biodiversity due to its expansion into natural areas. We compared biodiversity of bees and wasps between heterogeneous small-scale farming areas and protected forest in northern coastal Belize, Central America. Malaise traps operated for three months during the transition from wet to dry season. Farming areas consisted of a mosaic of mixed crop types, open habitat, secondary forest, and agroforestry. Mean species richness per site (alpha diversity), as well as spatial and temporal community variation (beta diversity) of bees and wasps were equal or higher in farming areas compared to protected forest. The higher species richness and community variation in farmland was due to additional species that did not occur in the forest, whereas most species trapped in forest were also found in farming areas. The overall regional species richness (gamma diversity) increased by 70% with the inclusion of farming areas. Our results suggest that small-scale farming systems adjacent to protected forest may not only conserve, but even favour, biodiversity of some taxonomic groups. We can, however, not exclude possible declines of bee and wasp diversity in more intensified farmland or in landscapes completely covered by heterogeneous farming systems. PMID:23300598

Assessing the Educational and Financial Needs of Small-Scale Dairy Farmers in Socopo, Venezuela. Summary of Research 64.

ERIC Educational Resources Information Center

Nieto, Ruben D.; Henderson, Janet L.

The process of transferring agricultural technology in many countries was studied to determine the perceived educational and financial needs of small-scale dairy farmers in Socopo, Venezuela. The following data were collected: (1) demographic characteristics--age, educational level, farm size, number of lactating cows, dairy farming experience,…

Fuel From Farms: A Guide to Small-Scale Ethanol Production.

ERIC Educational Resources Information Center

Solar Energy Research Inst., Golden, CO.

Ethanol and blends of ethanol and gasoline (such as gasohol) offer a near-term fuel alternative to oil. The focus of this handbook is upon the small-scale production of ethanol using farm crops as the source of raw materials. Provided are chapters on ethanol production procedures, feedstocks, plant design, and financial planning. Also presented…

Intensive grazing and maize silage to enhance the sustainability of small-scale dairy systems in the highlands of Mexico.

PubMed

Prospero-Bernal, Fernando; Martínez-García, Carlos Galdino; Olea-Pérez, Rafael; López-González, Felipe; Arriaga-Jordán, Carlos Manuel

2017-10-01

The effects of two innovative feeding strategies-intensive grazing (GR) and maize silage (MS)-on the sustainability of small-scale dairy systems (SSDS) were assessed in the highlands of central Mexico. On a total of 24 farms, four innovations were adopted between 2011 and 2014. Five farms continued their conventional feeding strategy (CC) of cut-and-carry pasture supplemented with commercial concentrate and ground corn grain, as well as straws (maize, oat, and wheat) in the dry season of feed scarcity; six farms implemented MS in the dry season; six farms GR of pastures; and seven farms implemented both GR and MS. Assessment in 2015 showed that farms which implemented both GR and MS had a higher local diversity score (P ≤ 0.001), higher scores for ethics and human development, and a higher score in economic independence (P ≤ 0.05) than farms that implemented only one of the innovations. The overall sustainability score (with range 0-100) was 46 for CC, 47 for MS, 52 for GR, and 55 for GR + MS. The innovations reduced feeding costs and enhanced sustainability, particularly when GR + MS were both implemented.

A comparative study on carbon footprint of rice production between household and aggregated farms from Jiangxi, China.

PubMed

Yan, Ming; Luo, Ting; Bian, Rongjun; Cheng, Kun; Pan, Genxing; Rees, Robert

2015-06-01

Quantifying the carbon footprint (CF) for crop production can help identify key options to mitigate greenhouse gas (GHG) emissions in agriculture. In the present study, both household and aggregated farm scales were surveyed to obtain the data of rice production and farming management practices in a typical rice cultivation area of Northern Jiangxi, China. The CFs of the different rice systems including early rice, late rice, and single rice under household and aggregated farm scale were calculated. In general, early rice had the lower CF in terms of land use and grain production being 4.54 ± 0.44 t CO2-eq./ha and 0.62 ± 0.1 t CO2-eq./t grain than single rice (6.84 ± 0.79 t CO2-eq./ha and 0.80 ± 0.13 t CO2-eq./t grain) and late rice (8.72 ± 0.54 t CO2-eq./ha and 1.1 ± 0.17 t CO2-eq./t grain). The emissions from nitrogen fertilizer use accounted for 33 % of the total CF on average and the direct CH4 emissions for 57 %. The results indicated that the CF of double rice cropping under aggregated farm being 0.86 ± 0.11 t CO2-eq./t grain was lower by 25 % than that being 1.14 ± 0.25 t CO2-eq./t grain under household farm, mainly due to high nitrogen use efficiency and low methane emissions. Therefore, developing the aggregated farm scale with efficient use of agro-chemicals and farming operation for greater profitability could offer a strategy for reducing GHG emissions in China's agriculture.

Whole farm quantification of GHG emissions within smallholder farms in developing countries

NASA Astrophysics Data System (ADS)

Seebauer, Matthias

2014-03-01

The IPCC has compiled the best available scientific methods into published guidelines for estimating greenhouse gas emissions and emission removals from the land-use sector. In order to evaluate existing GHG quantification tools to comprehensively quantify GHG emissions and removals in smallholder conditions, farm scale quantification was tested with farm data from Western Kenya. After conducting a cluster analysis to identify different farm typologies GHG quantification was exercised using the VCS SALM methodology complemented with IPCC livestock emission factors and the cool farm tool. The emission profiles of four farm clusters representing the baseline conditions in the year 2009 are compared with 2011 where farmers adopted sustainable land management practices (SALM). The results demonstrate the variation in both the magnitude of the estimated GHG emissions per ha between different smallholder farm typologies and the emissions estimated by applying two different accounting tools. The farm scale quantification further shows that the adoption of SALM has a significant impact on emission reduction and removals and the mitigation benefits range between 4 and 6.5 tCO2 ha-1 yr-1 with significantly different mitigation benefits depending on typologies of the crop-livestock systems, their different agricultural practices, as well as adoption rates of improved practices. However, the inherent uncertainty related to the emission factors applied by accounting tools has substantial implications for reported agricultural emissions. With regard to uncertainty related to activity data, the assessment confirms the high variability within different farm types as well as between different parameters surveyed to comprehensively quantify GHG emissions within smallholder farms.

Beta diversity at different spatial scales: plant communities in organic and conventional agriculture.

PubMed

Gabriel, Doreen; Roschewitz, Indra; Tscharntke, Teja; Thies, Carsten

2006-10-01

Biodiversity studies that guide agricultural subsidy policy have generally compared farming systems at a single spatial scale: the field. However, diversity patterns vary across spatial scales. Here, we examined the effects of farming system (organic vs. conventional) and position in the field (edge vs. center) on plant species richness in wheat fields at three spatial scales. We quantified alpha-, beta-, and gamma-diversity at the microscale in 800 plots, at the mesoscale in 40 fields, and at the macroscale in three regions using the additive partitioning approach, and evaluated the relative contribution of beta-diversity at each spatial scale to total observed species richness. We found that alpha-, beta-, and gamma-diversity were higher in organic than conventional fields and higher at the field edge than in the field center at all spatial scales. In both farming systems, beta-diversity at the meso- and macroscale explained most of the overall species richness (up to 37% and 25%, respectively), indicating considerable differences in community composition among fields and regions due to environmental heterogeneity. The spatial scale at which beta-diversity contributed the most to overall species richness differed between rare and common species. Total richness of rare species (present in < or = 5% of total samples) was mainly explained by differences in community composition at the meso- and macroscale (up to 27% and 48%, respectively), but only in organic fields. Total richness of common species (present in > or = 25% of total samples) was explained by differences in community composition at the micro- and mesoscale (up to 29% and 47%, respectively), i.e., among plots and fields, independent of farming system. Our results show that organic farming made the greatest contribution to total species richness at the meso (among fields) and macro (among regions) scale due to environmental heterogeneity. Hence, agri-environment schemes should exploit this large-scale contribution of beta-diversity by tailoring schemes at regional scales to maximize dissimilarity between conservation areas using geographic information systems rather than focusing entirely at the classical local-field scale, which is the current practice.

Study on the Measurement and Calculation of Environmental Pollution Bearing Index of China’s Pig Scale

NASA Astrophysics Data System (ADS)

Leng, Bi-Bin; Gong, Jian; Zhang, Wen-bo; Ji, Xue-Qiang

2017-11-01

According to the environmental pollution caused by large-scale pig breeding, the SPSS statistical software and factor analysis method were used to calculate the environmental pollution bearing index of China’s breeding scale from 2006 to 2015. The results showed that with the increase of scale the density of live pig farming and the amount of fertilizer application in agricultural production increased. However, due to the improvement of national environmental awareness, industrial waste water discharge is greatly reduced. China's hog farming environmental pollution load index is rising.

Antimicrobials in small-scale urban pig farming in a lower middle-income country - arbitrary use and high resistance levels.

PubMed

Ström, G; Boqvist, S; Albihn, A; Fernström, L-L; Andersson Djurfeldt, A; Sokerya, S; Sothyra, T; Magnusson, U

2018-01-01

Administration of antimicrobials to food-producing animals is regarded as a major contributor to the overall emergence of resistance in bacteria worldwide. However, few data are available on global antimicrobial use and resistance (AMR) in livestock, especially from low- and middle-income countries. We conducted a structured survey of 91 small-scale pig farms in the urban and peri-urban areas of Phnom Penh, Cambodia, to assess the farmers' knowledge, attitudes and practices related to antimicrobial use in their pig production. Commensal Escherichia coli was isolated from three healthy pigs from each farm ( n  = 261) and susceptibility testing was performed against 14 antimicrobials, using broth microdilution. Univariable logistic regression and generalized linear mixed models were used to investigate potential associations between farm characteristics, management factors and resistance to different types of antimicrobials. We found a widespread and arbitrary use of antimicrobials, often based on the farmer's own judgment. Around 66% of the farmers reported frequently self-adjusting treatment duration and dosage, and 45% had not heard about the term 'antimicrobial resistance'. The antimicrobials most commonly mentioned or kept by the farmers were amoxicillin, tylosin, gentamicin and colistin. Around 37% used a feed concentrate that contained antimicrobials, while antimicrobials for humans were used as a last-line treatment by 10% of the farmers. Commensal E. coli exhibited high prevalence of resistance to several antimicrobials considered to be of critical importance for human medicine, including ampicillin, ciprofloxacin and colistin, and multidrug-resistance was found in 79% of the samples. Higher prevalence of resistance was observed on farms that administered prophylactic antimicrobials and on farms that treated the entire group or herd in the event of disease. The widespread and arbitrary use of antimicrobials in pig farming in Cambodia is highly worrisome. Overall, farmers had a low awareness of the risks and consequences related to antimicrobial use and AMR. The results presented in this study confirm the hypothesis that non-rational use of antimicrobials results in higher prevalence of AMR and highlight the need for professional animal health systems that involve medically rational use of antimicrobials in emerging economies such as Cambodia.

Towards practical application of sensors for monitoring animal health; design and validation of a model to detect ketosis.

PubMed

Steensels, Machteld; Maltz, Ephraim; Bahr, Claudia; Berckmans, Daniel; Antler, Aharon; Halachmi, Ilan

2017-05-01

The objective of this study was to design and validate a mathematical model to detect post-calving ketosis. The validation was conducted in four commercial dairy farms in Israel, on a total of 706 multiparous Holstein dairy cows: 203 cows clinically diagnosed with ketosis and 503 healthy cows. A logistic binary regression model was developed, where the dependent variable is categorical (healthy/diseased) and a set of explanatory variables were measured with existing commercial sensors: rumination duration, activity and milk yield of each individual cow. In a first validation step (within-farm), the model was calibrated on the database of each farm separately. Two thirds of the sick cows and an equal number of healthy cows were randomly selected for model validation. The remaining one third of the cows, which did not participate in the model validation, were used for model calibration. In order to overcome the random selection effect, this procedure was repeated 100 times. In a second (between-farms) validation step, the model was calibrated on one farm and validated on another farm. Within-farm accuracy, ranging from 74 to 79%, was higher than between-farm accuracy, ranging from 49 to 72%, in all farms. The within-farm sensitivities ranged from 78 to 90%, and specificities ranged from 71 to 74%. The between-farms sensitivities ranged from 65 to 95%. The developed model can be improved in future research, by employing other variables that can be added; or by exploring other models to achieve greater sensitivity and specificity.

Economics of on-farm production and use of vegetable oils for fuel

DOE Office of Scientific and Technical Information (OSTI.GOV)

McIntosh, C.S.; Withers, R.V.; Smith, S.M.

1982-01-01

The technology of oilseed processing, on a small scale, is much simpler than that for ethanol production. This, coupled with the fact that most energy intensive farm operations use diesel powered equipment, has created substantial interest in vegetable oils as an alternative source of liquid fuel for agriculture. The purpose of this study was to estimate the impact on gross margins resulting from vegetable oil production and utilization in two case study areas, Latah and Power Counties, in Iadho. The results indicate that winter rape oil became a feasible alternative to diesel when the price of diesel reached $0.84 permore » liter in the Latah County model. A diesel price of $0.85 per liter was required in the Power County model before it became feasible to produce sunflower oil for fuel. 5 tables.« less

Fishermen's Energy Atlantic City Wind Farm

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wissemann, Chris

Fishermen's Energy Atlantic City Wind Farm final report under US DOE Advanced Technology Demonstration project documents achievements developing a demonstration scale offshore wind project off the coast of New Jersey.

Using a whole farm model to determine the impacts of mating management on the profitability of pasture-based dairy farms.

PubMed

Beukes, P C; Burke, C R; Levy, G; Tiddy, R M

2010-08-01

An approach to assessing likely impacts of altering reproductive performance on productivity and profitability in pasture-based dairy farms is described. The basis is the development of a whole farm model (WFM) that simulates the entire farm system and holistically links multiple physical performance factors to profitability. The WFM consists of a framework that links a mechanistic cow model, a pasture model, a crop model, management policies and climate. It simulates individual cows and paddocks, and runs on a day time-step. The WFM was upgraded to include reproductive modeling capability using reference tables and empirical equations describing published relationships between cow factors, physiology and mating management. It predicts reproductive status at any time point for individual cows within a modeled herd. The performance of six commercial pasture-based dairy farms was simulated for the period of 12 months beginning 1 June 2005 (05/06 year) to evaluate the accuracy of the model by comparison with actual outcomes. The model predicted most key performance indicators within an acceptable range of error (residual<10% of observed). The evaluated WFM was then used for the six farms to estimate the profitability of changes in farm "set-up" (farm conditions at the start of the farming year on 1 June) and mating management from 05/06 to 06/07 year. Among the six farms simulated, the 4-week calving rate emerged as an important set-up factor influencing profitability, while reproductive performance during natural bull mating was identified as an area with the greatest opportunity for improvement. The WFM presents utility to explore alternative management strategies to predict likely outcomes to proposed changes to a pasture-based farm system. Copyright (c) 2010 Elsevier B.V. All rights reserved.

Validation of Individual-Based Markov-Like Stochastic Process Model of Insect Behavior and a "Virtual Farm" Concept for Enhancement of Site-Specific IPM.

PubMed

Lux, Slawomir A; Wnuk, Andrzej; Vogt, Heidrun; Belien, Tim; Spornberger, Andreas; Studnicki, Marcin

2016-01-01

The paper reports application of a Markov-like stochastic process agent-based model and a "virtual farm" concept for enhancement of site-specific Integrated Pest Management. Conceptually, the model represents a "bottom-up ethological" approach and emulates behavior of the "primary IPM actors"-large cohorts of individual insects-within seasonally changing mosaics of spatiotemporally complex faming landscape, under the challenge of the local IPM actions. Algorithms of the proprietary PESTonFARM model were adjusted to reflect behavior and ecology of R. cerasi. Model parametrization was based on compiled published information about R. cerasi and the results of auxiliary on-farm experiments. The experiments were conducted on sweet cherry farms located in Austria, Germany, and Belgium. For each farm, a customized model-module was prepared, reflecting its spatiotemporal features. Historical data about pest monitoring, IPM treatments and fruit infestation were used to specify the model assumptions and calibrate it further. Finally, for each of the farms, virtual IPM experiments were simulated and the model-generated results were compared with the results of the real experiments conducted on the same farms. Implications of the findings for broader applicability of the model and the "virtual farm" approach-were discussed.

Farm-scale testing of soybean peroxidase and calcium peroxide for surficial swine manure treatment and mitigation of odorous VOCs, ammonia and hydrogen sulfide

USDA-ARS?s Scientific Manuscript database

The swine industry, regulatory agencies, and the public are interested in farm-tested methods for controlling gaseous emissions from swine barns. In earlier lab- and pilot-scale studies, a renewable catalyst consisting of soybean peroxidase (SBP) mixed with calcium peroxide was found to be effective...

The Spectrum of Wind Power Fluctuations

NASA Astrophysics Data System (ADS)

Bandi, Mahesh

2016-11-01

Wind is a variable energy source whose fluctuations threaten electrical grid stability and complicate dynamical load balancing. The power generated by a wind turbine fluctuates due to the variable wind speed that blows past the turbine. Indeed, the spectrum of wind power fluctuations is widely believed to reflect the Kolmogorov spectrum; both vary with frequency f as f - 5 / 3. This variability decreases when aggregate power fluctuations from geographically distributed wind farms are averaged at the grid via a mechanism known as geographic smoothing. Neither the f - 5 / 3 wind power fluctuation spectrum nor the mechanism of geographic smoothing are understood. In this work, we explain the wind power fluctuation spectrum from the turbine through grid scales. The f - 5 / 3 wind power fluctuation spectrum results from the largest length scales of atmospheric turbulence of order 200 km influencing the small scales where individual turbines operate. This long-range influence spatially couples geographically distributed wind farms and synchronizes farm outputs over a range of frequencies and decreases with increasing inter-farm distance. Consequently, aggregate grid-scale power fluctuations remain correlated, and are smoothed until they reach a limiting f - 7 / 3 spectrum. This work was funded by the Collective Interactions Unit, OIST Graduate University, Japan.

Experimental Investigation of Very Large Model Wind Turbine Arrays

NASA Astrophysics Data System (ADS)

Charmanski, Kyle; Wosnik, Martin

2013-11-01

The decrease in energy yield in large wind farms (array losses) and associated revenue losses can be significant. When arrays are sufficiently large they can reach what is known as a fully developed wind turbine array boundary layer, or fully developed wind farm condition. This occurs when the turbulence statistics and the structure of the turbulence, within and above a wind farm, as well as the performance of the turbines remain the same from one row to the next. The study of this condition and how it is affected by parameters such as turbine spacing, power extraction, tip speed ratio, etc. is important for the optimization of large wind farms. An experimental investigation of the fully developed wind farm condition was conducted using a large array of porous disks (upstream) and realistically scaled 3-bladed wind turbines with a diameter of 0.25m. The turbines and porous disks were placed inside a naturally grown turbulent boundary layer in the 6m × 2.5m × 72m test section of the UNH Flow Physics Facility which can achieve test section velocities of up to 14 m/s and Reynolds numbers δ+ = δuτ / ν ~ 20 , 000 . Power, rate of rotation and rotor thrust were measured for select turbines, and hot-wire anemometry was used for flow measurements.

Organic fields sustain weed metacommunity dynamics in farmland landscapes.

PubMed

Henckel, Laura; Börger, Luca; Meiss, Helmut; Gaba, Sabrina; Bretagnolle, Vincent

2015-06-07

Agro-ecosystems constitute essential habitat for many organisms. Agricultural intensification, however, has caused a strong decline of farmland biodiversity. Organic farming (OF) is often presented as a more biodiversity-friendly practice, but the generality of the beneficial effects of OF is debated as the effects appear often species- and context-dependent, and current research has highlighted the need to quantify the relative effects of local- and landscape-scale management on farmland biodiversity. Yet very few studies have investigated the landscape-level effects of OF; that is to say, how the biodiversity of a field is affected by the presence or density of organically farmed fields in the surrounding landscape. We addressed this issue using the metacommunity framework, with weed species richness in winter wheat within an intensively farmed landscape in France as model system. Controlling for the effects of local and landscape structure, we showed that OF leads to higher local weed diversity and that the presence of OF in the landscape is associated with higher local weed biodiversity also for conventionally farmed fields, and may reach a similar biodiversity level to organic fields in field margins. Based on these results, we derive indications for improving the sustainable management of farming systems. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

From cow to cheese: Novel phenotypes related to the sensory profile of model cheeses from individual cows.

PubMed

Cipolat-Gotet, C; Cecchinato, A; Drake, M A; Marangon, A; Martin, B; Bittante, G

2018-07-01

Milk samples were taken once from a total of 1,224 Brown Swiss cows from 83 herds, and 1,500 mL of raw full-fat milk from each cow was processed according to a laboratory-scale model-cheese-making procedure. A sensory panel was assembled and the members trained to evaluate the sensory profile of individual model cheeses. The protocol scorecard was composed of 7 main sensory descriptors related to smell intensity, flavor intensity, taste (salt and sour), and texture (elasticity, firmness, and moisture), and 40 sensory attributes describing smell and flavor profiles. Sensory data were analyzed using a mixed model that included random effects of herd, animal, and panelist, as well as fixed effects of dairy system, days in milk, parity, and order of cheese presentation, and covariates for cheese weight and fat:protein ratio. The sensory profile was not much affected by the dairy farming systems included in the trial, but it was affected by farm within dairy system: cheeses from traditional dairy farms had a greater wood/humus attribute of both smell and flavor than those from modern farm. Of the modern farms, cheeses from those using total mixed rations including silages had a more intense smell of sour milk and a firmer, less moist texture than those using total mixed rations without silages. Moreover, for all the sensory traits, we found less variance related to herd and animals than that related to the panelists and the residuals. Stage of lactation was found to be the most important, whereas parity was not relevant. In particular, cheese smell intensity (and some related attributes) exhibited a quadratic trend with lower values in mid-lactation, whereas flavor and salt descriptors were more intense in the last period of lactation. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Emergy evaluation and economic analysis of three wetland fish farming systems in Nansi Lake area, China.

PubMed

Zhang, L X; Ulgiati, S; Yang, Z F; Chen, B

2011-03-01

Emergy and economic methods were used to evaluate and compare three fish production models, i.e., cage fish farming system, pond intensive fish rearing system and semi-natural extensive pond fish rearing system, in Nansi Lake area in China in the year 2007. The goal of this study was to understand the benefits and driving forces of selected fish production models from ecological and economic points of view. The study considered input structure, production efficiency, environmental impacts, economic viability and sustainability. Results show that the main difference among the three production systems was the emergy cost for fish feed associated with their feeding system, i.e., feeding on natural biomass such as plankton and grass or on commercial feedstock. As indicated by EYR, ELR and ESI, it can be clearly shown that the intensive production model with commercial feed is not a sustainable pattern. However, the point is that more environmentally sound patterns do not seem able to provide a competitive net profit in the short run. The intensive pond fish farming system had a net profit of 2.57E+03 $/ha, much higher than 1.27E+03 $/ha for cage fish farming system and slightly higher than 2.37E+03 $/ha for semi-natural fish farming system. With regard to the drivers of local farmer's decisions, the accessibility of land for the required use and investment ability determine the farmer's choice of the production model and the scale of operation, while other factors seem to have little effect. Theoretically, the development of environmentally sustainable production patterns, namely water and land conservation measures, greener feed as well as low waste systems is urgently needed, to keep production activities within the carrying capacity of ecosystems. Coupled emergy and economic analyses can provide better insight into the environmental and economic benefits of fish production systems and help solve the problems encountered during policy making. Copyright © 2010 Elsevier Ltd. All rights reserved.

Off-farm applications of solar energy in agriculture

DOE Office of Scientific and Technical Information (OSTI.GOV)

Berry, R.E.

1980-01-01

Food processing applications make up almost all present off-farm studies of solar energy in agriculture. Research, development and demonstration projects on solar food processing have shown significant progress over the past 3 years. Projects have included computer simulation and mathematical models, hardware and process development for removing moisture from horticultural or animal products, integration of energy conservation with solar energy augmentation in conventional processes, and commercial scale demonstrations. The demonstration projects include solar heated air for drying prunes and raisins, soy beans and onions/garlic; and solar generated steam for orange juice pasteurization. Several new and planned projects hold considerable promisemore » for commerical exploitation in future food processes.« less

Living at the farm, innovative nursing home care for people with dementia - study protocol of an observational longitudinal study.

PubMed

de Boer, B; Hamers, J P H; Beerens, H C; Zwakhalen, S M G; Tan, F E S; Verbeek, H

2015-11-02

In nursing home care, new care environments directed towards small-scale and homelike environments are developing. The green care farm, which provides 24-h nursing home care for people with dementia, is one such new care environment. Knowledge is needed on the relation between environmental features of green care farms such as nature, domesticity and offering care in small groups and the influence on the daily lives of residents. The aim of this study is to explore (1) the daily lives of residents, (2) the quality of care and (3) the experiences of caregivers on green care farms compared with other nursing home care environments. An observational longitudinal study including a baseline and a six-month follow-up measurement is carried out. Four types of nursing home care environments are included: (1) large scale nursing home ward, (2) small scale living facility on the terrain of a larger nursing home (3) stand-alone small scale living facility and (4) green care farm. Quality of care is examined through structure, process and outcome indicators. The primary outcome measure is the daily life of residents, assessed by ecological momentary assessments. Aspects of daily life include (1) activity (activity performed by the resident, the engagement in this activity and the degree of physical effort); (2) physical environment (the location of the resident and the interaction with the physical environment); (3) social environment (the level and type of social interaction, and with whom this social interaction took place) and (4) psychological well-being (mood and agitation). In addition, social engagement, quality of life, behavioral symptoms and agitation are evaluated through questionnaires. Furthermore, demographics, cognitive impairment, functional dependence and the severity of dementia are assessed. Semi-structured interviews are performed with caregivers regarding their experiences with the different nursing home care environments. This is the first study investigating green care farms providing 24-h nursing home care for people with dementia. The study provides valuable insight into the daily lives of residents, the quality of care, and the experiences of caregivers at green care farms in comparison with other nursing home care environments including small-scale care environments and large scale nursing home wards.

Analysis of winter weather conditions and their potential impact on wind farm operations

NASA Astrophysics Data System (ADS)

Novakovskaia, E.; Treinish, L. A.; Praino, A.

2009-12-01

Severe weather conditions have two primary impacts on wind farm operations. The first relates to understanding potential damage to the turbines themselves and what actions are required to mitigate the effects. The second is recognizing what conditions may lead to a full or partial shutdown of the wind farm with sufficient lead time to determine the likely inability to meet energy generation committments. Ideally, wind forecasting suitable for wind farm operations should be of sufficient fidelity to resolve features within the boundary layer that lead to either damaging conditions or useful power generation. Given the complexity of the site-specific factors that effect the boundary layer at the scale of typical land-based wind farm locations such as topography, vegetation, land use, soil conditions, etc., which may vary with turbine design and layout within the farm, enabling reliable forecasts of too little or too much wind is challenging. A potential solution should involve continuous updates of alert triggering criteria through analysis of local wind patterns and probabilistic risk assessment for each location. To evaluate this idea, we utilize our operational mesoscale prediction system, dubbed “Deep Thunder”, developed at the IBM Thomas J. Watson Research Center. In particular, we analyze winter-time near-surface winds in upstate New York, where four similar winds farms are located. Each of these farms were built at roughly the same time and utilize similar turbines. Given the relative uncertainty associated with numerical weather prediction at this scale, and the difference in risk assessment due to the two primary impacts of severe weather, probabilistic forecasts are a prerequisite. Hence, we have employed ensembles of weather scenarios, which are based on the NCAR WRF-ARW modelling system. The set of ensemble members was composed with variations in the choices of physics and parameterization schemes, and source of background fields for initial conditions with horizontal grid resolutions in the one to two km range. In addition, the vertical grid structure was defined to ensure at least ten levels within the boundary layer and two from the bottom to the top of the turbine. This approach enables us to estimate the variability of winds at the farms and how it is distributed over the region. Further, we analyze the potential differences in structural risks at these farms during the 2009 winter season, and whether such differences in wind and weather patterns should be considered in choice of turbine design, installation and operations. We believe that this methodology can be extended to provide an estimate for mean annual energy production at a wind farm with the potential to improve the quality of siting and layout.

A Method for Semi-quantitative Assessment of Exposure to Pesticides of Applicators and Re-entry Workers: An Application in Three Farming Systems in Ethiopia.

PubMed

Negatu, Beyene; Vermeulen, Roel; Mekonnen, Yalemtshay; Kromhout, Hans

2016-07-01

To develop an inexpensive and easily adaptable semi-quantitative exposure assessment method to characterize exposure to pesticide in applicators and re-entry farmers and farm workers in Ethiopia. Two specific semi-quantitative exposure algorithms for pesticides applicators and re-entry workers were developed and applied to 601 farm workers employed in 3 distinctly different farming systems [small-scale irrigated, large-scale greenhouses (LSGH), and large-scale open (LSO)] in Ethiopia. The algorithm for applicators was based on exposure-modifying factors including application methods, farm layout (open or closed), pesticide mixing conditions, cleaning of spraying equipment, intensity of pesticide application per day, utilization of personal protective equipment (PPE), personal hygienic behavior, annual frequency of application, and duration of employment at the farm. The algorithm for re-entry work was based on an expert-based re-entry exposure intensity score, utilization of PPE, personal hygienic behavior, annual frequency of re-entry work, and duration of employment at the farm. The algorithms allowed estimation of daily, annual and cumulative lifetime exposure for applicators, and re-entry workers by farming system, by gender, and by age group. For all metrics, highest exposures occurred in LSGH for both applicators and female re-entry workers. For male re-entry workers, highest cumulative exposure occurred in LSO farms. Female re-entry workers appeared to be higher exposed on a daily or annual basis than male re-entry workers, but their cumulative exposures were similar due to the fact that on average males had longer tenure. Factors related to intensity of exposure (like application method and farm layout) were indicated as the main driving factors for estimated potential exposure. Use of personal protection, hygienic behavior, and duration of employment in surveyed farm workers contributed less to the contrast in exposure estimates. This study indicated that farmers' and farm workers' exposure to pesticides can be inexpensively characterized, ranked, and classified. Our method could be extended to assess exposure to specific active ingredients provided that detailed information on pesticides used is available. The resulting exposure estimates will consequently be used in occupational epidemiology studies in Ethiopia and other similar countries with few resources. © The Author 2016. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.

Predictive model for sustaining biodiversity in tropical countryside

PubMed Central

Mendenhall, Chase D.; Sekercioglu, Cagan H.; Brenes, Federico Oviedo; Ehrlich, Paul R.; Daily, Gretchen C.

2011-01-01

Growing demand for food, fuel, and fiber is driving the intensification and expansion of agricultural land through a corresponding displacement of native woodland, savanna, and shrubland. In the wake of this displacement, it is clear that farmland can support biodiversity through preservation of important ecosystem elements at a fine scale. However, how much biodiversity can be sustained and with what tradeoffs for production are open questions. Using a well-studied tropical ecosystem in Costa Rica, we develop an empirically based model for quantifying the “wildlife-friendliness” of farmland for native birds. Some 80% of the 166 mist-netted species depend on fine-scale countryside forest elements (≤60-m-wide clusters of trees, typically of variable length and width) that weave through farmland along hilltops, valleys, rivers, roads, and property borders. Our model predicts with ∼75% accuracy the bird community composition of any part of the landscape. We find conservation value in small (≤20 m wide) clusters of trees and somewhat larger (≤60 m wide) forest remnants to provide substantial support for biodiversity beyond the borders of tropical forest reserves. Within the study area, forest elements on farms nearly double the effective size of the local forest reserve, providing seminatural habitats for bird species typically associated with the forest. Our findings provide a basis for estimating and sustaining biodiversity in farming systems through managing fine-scale ecosystem elements and, more broadly, informing ecosystem service analyses, biodiversity action plans, and regional land use strategies. PMID:21911396

Predictive model for sustaining biodiversity in tropical countryside.

PubMed

Mendenhall, Chase D; Sekercioglu, Cagan H; Brenes, Federico Oviedo; Ehrlich, Paul R; Daily, Gretchen C

2011-09-27

Growing demand for food, fuel, and fiber is driving the intensification and expansion of agricultural land through a corresponding displacement of native woodland, savanna, and shrubland. In the wake of this displacement, it is clear that farmland can support biodiversity through preservation of important ecosystem elements at a fine scale. However, how much biodiversity can be sustained and with what tradeoffs for production are open questions. Using a well-studied tropical ecosystem in Costa Rica, we develop an empirically based model for quantifying the "wildlife-friendliness" of farmland for native birds. Some 80% of the 166 mist-netted species depend on fine-scale countryside forest elements (≤ 60-m-wide clusters of trees, typically of variable length and width) that weave through farmland along hilltops, valleys, rivers, roads, and property borders. Our model predicts with ∼75% accuracy the bird community composition of any part of the landscape. We find conservation value in small (≤ 20 m wide) clusters of trees and somewhat larger (≤ 60 m wide) forest remnants to provide substantial support for biodiversity beyond the borders of tropical forest reserves. Within the study area, forest elements on farms nearly double the effective size of the local forest reserve, providing seminatural habitats for bird species typically associated with the forest. Our findings provide a basis for estimating and sustaining biodiversity in farming systems through managing fine-scale ecosystem elements and, more broadly, informing ecosystem service analyses, biodiversity action plans, and regional land use strategies.

Metabolic Profile and Inflammatory Responses in Dairy Cows with Left Displaced Abomasum Kept under Small-Scaled Farm Conditions

PubMed Central

Klevenhusen, Fenja; Humer, Elke; Metzler-Zebeli, Barbara; Podstatzky-Lichtenstein, Leopold; Wittek, Thomas; Zebeli, Qendrim

2015-01-01

Simple Summary This research established an association between lactation number and milk production and metabolic and inflammatory responses in high-producing dairy cows affected by left abomasal displacement in small-scaled dairy farms. The study showed metabolic alterations, liver damage, and inflammation in the sick cows, which were further exacerbated with increasing lactation number and milk yield of the cows. Abstract Left displaced abomasum (LDA) is a severe metabolic disease of cattle with a strong negative impact on production efficiency of dairy farms. Metabolic and inflammatory alterations associated with this disease have been reported in earlier studies, conducted mostly in large dairy farms. This research aimed to: (1) evaluate metabolic and inflammatory responses in dairy cows affected by LDA in small-scaled dairy farms; and (2) establish an association between lactation number and milk production with the outcome of metabolic variables. The cows with LDA had lower serum calcium (Ca), but greater concentrations of non-esterified fatty acids (NEFA) and beta-hydroxy-butyrate (BHBA), in particular when lactation number was >2. Cows with LDA showed elevated levels of aspartate aminotransferase, glutamate dehydrogenase, and serum amyloid A (SAA), regardless of lactation number. In addition, this study revealed strong associations between milk yield and the alteration of metabolic profile but not with inflammation in the sick cows. Results indicate metabolic alterations, liver damage, and inflammation in LDA cows kept under small-scale farm conditions. Furthermore, the data suggest exacerbation of metabolic profile and Ca metabolism but not of inflammation and liver health with increasing lactation number and milk yield in cows affected by LDA. PMID:26479481

Influence of distances between places of residence and wind farms on the quality of life in nearby areas.

PubMed

Mroczek, Bożena; Kurpas, Donata; Karakiewicz, Beata

2012-01-01

The quality of life has three main characteristics: it always refers to the living conditions of an individual; it is measured both with subjective and objective indicators; and it is a multidimensional concept. To assess how the quality of life is affected by the close proximity of wind farms. The study group consisted of 1,277 Polish adults (703 women and 574 men), living in places located near wind farms. The mean age was 45.5 ± 16.10. Some 33.2% of participants lived more than 1,500 m from wind farms; 17% - below 700 m. The research tool consisted of the Norwegian version of the SF-36 General Health Questionnaire, the Visual Analogue Scale (VAS) for health assessment, and original questions. Regardless of the distance between a place of residence and a wind farm, the highest quality of life was noted within the physical functioning subscale (mean 76±27.97), and the lowest within the general health (mean 55.3±24.06). Within all scales, the quality of life was assessed highest by residents of areas located closest to wind farms, and the lowest by those living more than 1,500 m from wind farms. Close proximity of wind farms does not result in the worsening of the quality of life. Similar research should be conducted before any intended investment, and at least 6 months after construction of a wind farm.

Agricultural Incentives: Implications for Small-Scale and Subsistence Farming in the US Caribbean Islands

NASA Astrophysics Data System (ADS)

Alvarez-Berrios, N.; Parés-Ramos, I.; Gould, W. A.

2017-12-01

The effects of climate change threaten the world's most sensitive agroecosystems and our potential to reach agricultural productivity levels needed to feed a projected global population of 9.7 billion people by 2050. The US Caribbean agriculture is especially vulnerable to the effects of climate change, due to the region's frequent exposure to extreme weather events, its geographic and economic scale, shortage of labor force, and rapid urban expansion. Currently, agriculture contributes less than 1% of the island's GDP, and over 80% of the food consumed in the region is imported. Despite low production levels, there is widespread interest in reinvigorating the agricultural sector's contribution to the economy. Local and federal institutions play a major role strengthening the agricultural sector by providing access to incentives, loans, and education for best management practices. However, many of these efforts conform to agricultural systems of larger scale of production and temperate environments. In this study, we explore agricultural incentives programs and their implication for highly diverse, small-scale, and subsistence operations that characterize agricultural systems in Puerto Rico and the US Virgin Islands. We analyze records and maps from the USDA Farm Service Agency, to typify participating farms, and to track changes in land cover, farm size, crop diversity, practices, and production levels resulting from their enrollment in such programs. Preliminary results indicate that many incentives programs are not tailored to agricultural tropical systems and prescribe alternatives that exclude traditional farming methods employed in small-scale and subsistence farms (e.g. crop insurance that benefit monoculture over intercropped systems). Moreover, many of the incentives are contradictory in their recommendations (e.g., crop insurance benefit sun-grown coffee production, while best agricultural practices recommend agroforestry with shade-grown coffee). Understanding the characteristics that underlie the resilience of traditional agriculture is an urgent matter, as they can serve as the basis for the design of agricultural systems that mitigate projected climate changes.

Heart Rate and Heart Rate Variability in Dairy Cows with Different Temperament and Behavioural Reactivity to Humans

PubMed Central

Tőzsér, János; Szenci, Ottó; Póti, Péter; Pajor, Ferenc

2015-01-01

From the 1990s, extensive research was started on the physiological aspects of individual traits in animals. Previous research has established two extreme (proactive and reactive) coping styles in several animal species, but the means of reactivity with the autonomic nervous system (ANS) activity has not yet been investigated in cattle. The aim of this study was the characterization of cardiac autonomic activity under different conditions in cows with different individual characteristics. For this purpose, we investigated heart rate and ANS-related heart rate variability (HRV) parameters of dairy cows (N = 282) on smaller- and larger-scale farms grouped by (1) temperament and (2) behavioural reactivity to humans (BRH). Animals with high BRH scores were defined as impulsive, while animals with low BRH scores were defined as reserved. Cardiac parameters were calculated for undisturbed lying (baseline) and for milking bouts, the latter with the presence of an unfamiliar person (stressful situation). Sympathetic tone was higher, while vagal activity was lower in temperamental cows than in calm animals during rest both on smaller- and larger-scale farms. During milking, HRV parameters were indicative of a higher sympathetic and a lower vagal activity of temperamental cows as compared to calm ones in farms of both sizes. Basal heart rate did not differ between BRH groups either on smaller- or larger-scale farms. Differences between basal ANS activity of impulsive and reserved cows reflected a higher resting vagal and lower sympathetic activity of reserved animals compared to impulsive ones both on smaller- and larger-scale farms. There was no difference either in heart rate or in HRV parameters between groups during milking neither in smaller- nor in larger-scale farms. These two groupings allowed to draw possible parallels between personality and cardiac autonomic activity during both rest and milking in dairy cows. Heart rate and HRV seem to be useful for characterisation of physiological differences related to temperament and BRH. PMID:26291979

A case study of effects of atmospheric boundary layer turbulence, wind speed, and stability on wind farm induced temperature changes using observations from a field campaign

NASA Astrophysics Data System (ADS)

Xia, Geng; Zhou, Liming; Freedman, Jeffrey M.; Roy, Somnath Baidya; Harris, Ronald A.; Cervarich, Matthew Charles

2016-04-01

Recent studies using satellite observations show that operational wind farms in west-central Texas increase local nighttime land surface temperature (LST) by 0.31-0.70 °C, but no noticeable impact is detected during daytime, and that the diurnal and seasonal variations in the magnitude of this warming are likely determined by those in the magnitude of wind speed. This paper further explores these findings by using the data from a year-long field campaign and nearby radiosonde observations to investigate how thermodynamic profiles and surface-atmosphere exchange processes work in tandem with the presence of wind farms to affect the local climate. Combined with satellite data analyses, we find that wind farm impacts on LST are predominantly determined by the relative ratio of turbulence kinetic energy (TKE) induced by the wind turbines compared to the background TKE. This ratio explains not only the day-night contrast of the wind farm impact and the warming magnitude of nighttime LST over the wind farms, but also most of the seasonal variations in the nighttime LST changes. These results indicate that the diurnal and seasonal variations in the turbine-induced turbulence relative to the background TKE play an essential role in determining those in the magnitude of LST changes over the wind farms. In addition, atmospheric stability determines the sign and strength of the net downward heat transport as well as the magnitude of the background TKE. The study highlights the need for better understanding of atmospheric boundary layer and wind farm interactions, and for better parameterizations of sub-grid scale turbulent mixing in numerical weather prediction and climate models.

Water repellency: a whole-farm bio-economic perspective

NASA Astrophysics Data System (ADS)

Abadi Ghadim, A. K.

2000-05-01

A whole-farm bio-economic model was used to assess the profitability of innovations aimed at improving agricultural production on the non-wetting sands of wheatbelt farms of Western Australia. It was found that amelioration of water repellency might be an economical option for some farms in the northern wheatbelt of Western Australia. It was shown that a minimum of 30% increase in lupin yields and a 10% increase in wheat yields would be required before expenditure on innovations aimed at improving production on non-wetting soils could be justified. However, due to costs of amelioration of repellency much higher crop yield responses may be required for economical adoption of such innovations on most farms. The decision to ameliorate water repellency depends not only on the consideration of direct benefits and costs per hectare of ameliorated sand but also on other whole-farm factors. One such factor found to be important was the scale of relevance or the soil mix of the farm. It was found that farms with proportionately large areas of non-wetting sands were more likely to benefit from adoption of innovations aimed at amelioration of repellency. Another important factor in the decision to adopt innovations for amelioration of water repellency is availability of alternative enterprises on the non-wetting soils. In particular, whether or not sandplain lupins (lupinus cosentinii) and tagasaste (chamaecystisus proliferus) were options that a farmer could consider determined the profitability of taking remedial measures against water repellency. This study identified, through a series of sensitivity analyses, the magnitude of production responses that may be required for profitable amelioration of water repellency. Some gaps in our knowledge of biological and economic parameters related to costs and benefits of various innovations have also been highlighted and discussed.

Multi-scale measurements show limited soil greenhouse gas emissions in Kenyan smallholder coffee-dairy systems.

PubMed

Ortiz-Gonzalo, Daniel; de Neergaard, Andreas; Vaast, Philippe; Suárez-Villanueva, Víctor; Oelofse, Myles; Rosenstock, Todd S

2018-06-01

Efforts have been made in recent years to improve knowledge about soil greenhouse gas (GHG) fluxes from sub-Saharan Africa. However, data on soil GHG emissions from smallholder coffee-dairy systems have not hitherto been measured experimentally. This study aimed to quantify soil GHG emissions at different spatial and temporal scales in smallholder coffee-dairy farms in Murang'a County, Central Kenya. GHG measurements were carried out for one year, comprising two cropping seasons, using vented static chambers and gas chromatography. Sixty rectangular frames were installed on two farms comprising the three main cropping systems found in the area: 1) coffee (Coffea arabica L.); 2) Napier grass (Pennisetum purpureum); and 3) maize intercropped with beans (Zea mays and Phaseolus vulgaris). Within these fields, chambers were allocated on fertilised and unfertilised locations to capture spatial variability. Cumulative annual fluxes in coffee plots ranged from 1 to 1.9kgN 2 O-Nha -1 , 6.5 to 7.6MgCO 2 -Cha -1 and - 3.4 to -2.2kgCH 4 -Cha -1 , with 66% to 94% of annual GHG fluxes occurring during rainy seasons. Across the farm plots, coffee received most of the N inputs and had 56% to 89% higher emissions of N 2 O than Napier grass, maize and beans. Within farm plots, two to six times higher emissions were found in fertilised hotspots - around the perimeter of coffee trees or within planted maize rows - than in unfertilised locations between trees, rows and planting holes. Background and induced soil N 2 O emissions from fertiliser and manure applications in the three cropping systems were lower than hypothesized from previous studies and empirical models. This study supplements methods and underlying data for the quantification of GHG emissions at multiple spatial and temporal scales in tropical, smallholder farming systems. Advances towards overcoming the dearth of data will facilitate the understanding of synergies and tradeoffs of climate-smart approaches for low emissions development. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Reciprocal genomic evolution in the ant–fungus agricultural symbiosis

PubMed Central

Nygaard, Sanne; Hu, Haofu; Li, Cai; Schiøtt, Morten; Chen, Zhensheng; Yang, Zhikai; Xie, Qiaolin; Ma, Chunyu; Deng, Yuan; Dikow, Rebecca B.; Rabeling, Christian; Nash, David R.; Wcislo, William T.; Brady, Seán G.; Schultz, Ted R.; Zhang, Guojie; Boomsma, Jacobus J.

2016-01-01

The attine ant–fungus agricultural symbiosis evolved over tens of millions of years, producing complex societies with industrial-scale farming analogous to that of humans. Here we document reciprocal shifts in the genomes and transcriptomes of seven fungus-farming ant species and their fungal cultivars. We show that ant subsistence farming probably originated in the early Tertiary (55–60 MYA), followed by further transitions to the farming of fully domesticated cultivars and leaf-cutting, both arising earlier than previously estimated. Evolutionary modifications in the ants include unprecedented rates of genome-wide structural rearrangement, early loss of arginine biosynthesis and positive selection on chitinase pathways. Modifications of fungal cultivars include loss of a key ligninase domain, changes in chitin synthesis and a reduction in carbohydrate-degrading enzymes as the ants gradually transitioned to functional herbivory. In contrast to human farming, increasing dependence on a single cultivar lineage appears to have been essential to the origin of industrial-scale ant agriculture. PMID:27436133

Contributions of Local Farming to Urban Sustainability in the Northeast United States.

PubMed

Goldstein, Benjamin P; Hauschild, Michael Z; Fernández, John E; Birkved, Morten

2017-07-05

Food consumption is an important contributor to a city's environmental impacts (carbon emissions, land occupation, water use, etc.) Urban farming (UF) has been advocated as a means to increase urban sustainability by reducing food-related transport and tapping into local resources. Taking Boston as an illustrative Northeast U.S. city, we developed a novel method to estimate sub-urban, food-borne carbon and land footprints using multiregion-input-output modeling and nutritional surveys. Computer simulations utilizing primary data explored UF's ability to reduce these footprints using select farming technologies, building on previous city-scale UF assessments which have hitherto been dependent on proxy data for UF. We found that UF generated meagre food-related carbon footprint reductions (1.1-2.9% of baseline 2211 kg CO 2 equivalents/capita/annum) and land occupation increases (<1% of baseline 9000 m 2 land occupation/capita/annum) under optimal production scenarios, informing future evidence-based urban design and policy crafting in the region. Notwithstanding UF's marginal environmental gains, UF could help Boston meet national nutritional guidelines for vegetable intake, generate an estimated $160 million U.S. in revenue to growers and act as a pedagogical and community building tool, though these benefits would hinge on large-scale UF proliferation, likely undergirded by environmental remediation of marginal lands in the city.

Array Effects in Large Wind Farms. Cooperative Research and Development Final Report, CRADA Number CRD-09-343

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moriarty, Patrick

2016-02-23

The effects of wind turbine wakes within operating wind farms have a substantial impact on the overall energy production from the farm. The current generation of models drastically underpredicts the impact of these wakes leading to non-conservative estimates of energy capture and financial losses to wind farm operators and developers. To improve these models, detailed research of operating wind farms is necessary. Rebecca Barthelmie of Indiana University is a world leader of wind farm wakes effects and would like to partner with NREL to help improve wind farm modeling by gathering additional wind farm data, develop better models and increasemore » collaboration with European researchers working in the same area. This is currently an active area of research at NREL and the capabilities of both parties should mesh nicely.« less

Top Five Large-Scale Solar Myths | State, Local, and Tribal Governments |

Science.gov Websites

of large-scale photovoltaic (PV) facilities or solar farms tend to include a myriad of misperceptions technologies do use mirrors which can cause glare, most solar farms use PV modules to generate electricity. PV panels in order to convert solar energy into electricity. PV modules are generally less reflective than

Physical Model Study of the Fully Developed Wind Turbine Array Boundary Layer in the UNH Flow Physics Facility

NASA Astrophysics Data System (ADS)

Turner, John; Wosnik, Martin

2015-11-01

Results from an experimental study of an array of up to 100 model wind turbines with 0.25 m diameter are reported. The study was conducted in the UNH Flow Physics Facility (FPF), which has test section dimensions of 6.0 m wide, 2.7 m high and 72.0 m long. For a given configuration (spacing, initial conditions, etc.), the model wind farm reaches a ``fully developed'' condition, in which turbulence statistics remain the same from one row to the next within and above the wind turbine array. Of interest is the transport of kinetic energy within the wind turbine array boundary layer (WTABL). Model wind farms of up to 20 rows are possible in the FPF at the wind turbine scale used. The present studies in the FPF are able to achieve the fully developed WTABL condition, which can provide valuable insight to the optimization of wind farm energy production. The FPF can achieve a boundary layer height on the order of 1 m at the beginning of the wind turbine array. The wind turbine array was constructed of porous disks, which where drag (thrust) matched to wind turbines at typical operating conditions and therefore act as momentum sinks similar to wind turbines. The flow in the WTABL was measured with constant temperature anemometry using an X-wire.

Disease prevention versus data privacy: using landcover maps to inform spatial epidemic models.

PubMed

Tildesley, Michael J; Ryan, Sadie J

2012-01-01

The availability of epidemiological data in the early stages of an outbreak of an infectious disease is vital for modelers to make accurate predictions regarding the likely spread of disease and preferred intervention strategies. However, in some countries, the necessary demographic data are only available at an aggregate scale. We investigated the ability of models of livestock infectious diseases to predict epidemic spread and obtain optimal control policies in the event of imperfect, aggregated data. Taking a geographic information approach, we used land cover data to predict UK farm locations and investigated the influence of using these synthetic location data sets upon epidemiological predictions in the event of an outbreak of foot-and-mouth disease. When broadly classified land cover data were used to create synthetic farm locations, model predictions deviated significantly from those simulated on true data. However, when more resolved subclass land use data were used, moderate to highly accurate predictions of epidemic size, duration and optimal vaccination and ring culling strategies were obtained. This suggests that a geographic information approach may be useful where individual farm-level data are not available, to allow predictive analyses to be carried out regarding the likely spread of disease. This method can also be used for contingency planning in collaboration with policy makers to determine preferred control strategies in the event of a future outbreak of infectious disease in livestock.

Disease Prevention versus Data Privacy: Using Landcover Maps to Inform Spatial Epidemic Models

PubMed Central

Tildesley, Michael J.; Ryan, Sadie J.

2012-01-01

The availability of epidemiological data in the early stages of an outbreak of an infectious disease is vital for modelers to make accurate predictions regarding the likely spread of disease and preferred intervention strategies. However, in some countries, the necessary demographic data are only available at an aggregate scale. We investigated the ability of models of livestock infectious diseases to predict epidemic spread and obtain optimal control policies in the event of imperfect, aggregated data. Taking a geographic information approach, we used land cover data to predict UK farm locations and investigated the influence of using these synthetic location data sets upon epidemiological predictions in the event of an outbreak of foot-and-mouth disease. When broadly classified land cover data were used to create synthetic farm locations, model predictions deviated significantly from those simulated on true data. However, when more resolved subclass land use data were used, moderate to highly accurate predictions of epidemic size, duration and optimal vaccination and ring culling strategies were obtained. This suggests that a geographic information approach may be useful where individual farm-level data are not available, to allow predictive analyses to be carried out regarding the likely spread of disease. This method can also be used for contingency planning in collaboration with policy makers to determine preferred control strategies in the event of a future outbreak of infectious disease in livestock. PMID:23133352

A comparison of methods for assessing power output in non-uniform onshore wind farms

DOE PAGES

Staid, Andrea; VerHulst, Claire; Guikema, Seth D.

2017-10-02

Wind resource assessments are used to estimate a wind farm's power production during the planning process. It is important that these estimates are accurate, as they can impact financing agreements, transmission planning, and environmental targets. Here, we analyze the challenges in wind power estimation for onshore farms. Turbine wake effects are a strong determinant of farm power production. With given input wind conditions, wake losses typically cause downstream turbines to produce significantly less power than upstream turbines. These losses have been modeled extensively and are well understood under certain conditions. Most notably, validation of different model types has favored offshoremore » farms. Models that capture the dynamics of offshore wind conditions do not necessarily perform equally as well for onshore wind farms. We analyze the capabilities of several different methods for estimating wind farm power production in 2 onshore farms with non-uniform layouts. We compare the Jensen model to a number of statistical models, to meteorological downscaling techniques, and to using no model at all. In conclusion, we show that the complexities of some onshore farms result in wind conditions that are not accurately modeled by the Jensen wake decay techniques and that statistical methods have some strong advantages in practice.« less

A comparison of methods for assessing power output in non-uniform onshore wind farms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Staid, Andrea; VerHulst, Claire; Guikema, Seth D.

Wind resource assessments are used to estimate a wind farm's power production during the planning process. It is important that these estimates are accurate, as they can impact financing agreements, transmission planning, and environmental targets. Here, we analyze the challenges in wind power estimation for onshore farms. Turbine wake effects are a strong determinant of farm power production. With given input wind conditions, wake losses typically cause downstream turbines to produce significantly less power than upstream turbines. These losses have been modeled extensively and are well understood under certain conditions. Most notably, validation of different model types has favored offshoremore » farms. Models that capture the dynamics of offshore wind conditions do not necessarily perform equally as well for onshore wind farms. We analyze the capabilities of several different methods for estimating wind farm power production in 2 onshore farms with non-uniform layouts. We compare the Jensen model to a number of statistical models, to meteorological downscaling techniques, and to using no model at all. In conclusion, we show that the complexities of some onshore farms result in wind conditions that are not accurately modeled by the Jensen wake decay techniques and that statistical methods have some strong advantages in practice.« less

COMPUTATIONAL FLUID DYNAMICS MODELING OF SCALED HANFORD DOUBLE SHELL TANK MIXING - CFD MODELING SENSITIVITY STUDY RESULTS

DOE Office of Scientific and Technical Information (OSTI.GOV)

JACKSON VL

2011-08-31

The primary purpose of the tank mixing and sampling demonstration program is to mitigate the technical risks associated with the ability of the Hanford tank farm delivery and celtification systems to measure and deliver a uniformly mixed high-level waste (HLW) feed to the Waste Treatment and Immobilization Plant (WTP) Uniform feed to the WTP is a requirement of 24590-WTP-ICD-MG-01-019, ICD-19 - Interface Control Document for Waste Feed, although the exact definition of uniform is evolving in this context. Computational Fluid Dynamics (CFD) modeling has been used to assist in evaluating scaleup issues, study operational parameters, and predict mixing performance atmore » full-scale.« less

Farm, household, and farmer characteristics associated with changes in management practices and technology adoption among dairy smallholders.

PubMed

Martínez-García, Carlos Galdino; Ugoretz, Sarah Janes; Arriaga-Jordán, Carlos Manuel; Wattiaux, Michel André

2015-02-01

This study explored whether technology adoption and changes in management practices were associated with farm structure, household, and farmer characteristics and to identify processes that may foster productivity and sustainability of small-scale dairy farming in the central highlands of Mexico. Factor analysis of survey data from 44 smallholders identified three factors-related to farm size, farmer's engagement, and household structure-that explained 70 % of cumulative variance. The subsequent hierarchical cluster analysis yielded three clusters. Cluster 1 included the most senior farmers with fewest years of education but greatest years of experience. Cluster 2 included farmers who reported access to extension, cooperative services, and more management changes. Cluster 2 obtained 25 and 35 % more milk than farmers in clusters 1 and 3, respectively. Cluster 3 included the youngest farmers, with most years of education and greatest availability of family labor. Access to a network and membership in a community of peers appeared as important contributors to success. Smallholders gravitated towards easy to implement technologies that have immediate benefits. Nonusers of high investment technologies found them unaffordable because of cost, insufficient farm size, and lack of knowledge or reliable electricity. Multivariate analysis may be a useful tool in planning extension activities and organizing channels of communication to effectively target farmers with varying needs, constraints, and motivations for change and in identifying farmers who may exemplify models of change for others who manage farms that are structurally similar but performing at a lower level.

Is Bhutan destined for 100% organic? Assessing the economy-wide effects of a large-scale conversion policy.

PubMed

Feuerbacher, Arndt; Luckmann, Jonas; Boysen, Ole; Zikeli, Sabine; Grethe, Harald

2018-01-01

Organic agriculture (OA) is considered a strategy to make agriculture more sustainable. Bhutan has embraced the ambitious goal of becoming the world's first 100% organic nation. By analysing recent on-farm data in Bhutan, we found organic crop yields on average to be 24% lower than conventional yields. Based on these yield gaps, we assess the effects of the 100% organic conversion policy by employing an economy-wide computable general equilibrium (CGE) model with detailed representation of Bhutan's agricultural sector incorporating agroecological zones, crop nutrients, and field operations. Despite a low dependency on agrochemicals from the onset of this initiative, we find a considerable reduction in Bhutan's GDP, substantial welfare losses, particularly for non-agricultural households, and adverse impacts on food security. The yield gap is the main driver for a strong decline in domestic agricultural production, which is largely compensated by increased food imports, resulting in a weakening of the country's cereal self-sufficiency. Current organic by default farming practices in Bhutan are still underdeveloped and do not apply the systems approach of organic farming as defined in the IFOAM organic farming standards. This is reflected in the strong decline of nitrogen (N) availability to crops in our simulation and bears potential for increased yields in OA. Improvement of soil-fertility practices, e.g., the adoption of N-fixing crops, improved animal husbandry systems with increased provision of animal manure and access to markets with price premium for organic products could help to lower the economic cost of the large-scale conversion.

Is Bhutan destined for 100% organic? Assessing the economy-wide effects of a large-scale conversion policy

PubMed Central

Luckmann, Jonas; Boysen, Ole; Zikeli, Sabine; Grethe, Harald

2018-01-01

Organic agriculture (OA) is considered a strategy to make agriculture more sustainable. Bhutan has embraced the ambitious goal of becoming the world’s first 100% organic nation. By analysing recent on-farm data in Bhutan, we found organic crop yields on average to be 24% lower than conventional yields. Based on these yield gaps, we assess the effects of the 100% organic conversion policy by employing an economy-wide computable general equilibrium (CGE) model with detailed representation of Bhutan’s agricultural sector incorporating agroecological zones, crop nutrients, and field operations. Despite a low dependency on agrochemicals from the onset of this initiative, we find a considerable reduction in Bhutan’s GDP, substantial welfare losses, particularly for non-agricultural households, and adverse impacts on food security. The yield gap is the main driver for a strong decline in domestic agricultural production, which is largely compensated by increased food imports, resulting in a weakening of the country’s cereal self-sufficiency. Current organic by default farming practices in Bhutan are still underdeveloped and do not apply the systems approach of organic farming as defined in the IFOAM organic farming standards. This is reflected in the strong decline of nitrogen (N) availability to crops in our simulation and bears potential for increased yields in OA. Improvement of soil-fertility practices, e.g., the adoption of N-fixing crops, improved animal husbandry systems with increased provision of animal manure and access to markets with price premium for organic products could help to lower the economic cost of the large-scale conversion. PMID:29897989

Wake flow control using a dynamically controlled wind turbine

NASA Astrophysics Data System (ADS)

Castillo, Ricardo; Wang, Yeqin; Pol, Suhas; Swift, Andy; Hussain, Fazle; Westergaard, Carsten; Texas Tech University Team

2016-11-01

A wind tunnel based "Hyper Accelerated Wind Farm Kinematic-Control Simulator" (HAWKS) is being built at Texas Tech University to emulate controlled wind turbine flow physics. The HAWKS model turbine has pitch, yaw and speed control which is operated in real model time, similar to that of an equivalent full scale turbine. Also, similar to that of a full scale wind turbine, the controls are developed in a Matlab Simulink environment. The current diagnostic system consists of power, rotor position, rotor speed measurements and PIV wake characterization with four cameras. The setup allows up to 7D downstream of the rotor to be mapped. The purpose of HAWKS is to simulate control strategies at turnaround times much faster than CFD and full scale testing. The fundamental building blocks of the simulator have been tested, and demonstrate wake steering for both static and dynamic turbine actuation. Parameters which have been studied are yaw, rotor speed and combinations hereof. The measured wake deflections for static yaw cases are in agreement with previously reported research implying general applicability of the HAWKS platform for the purpose of manipulating the wake. In this presentation the general results will be introduced followed by an analysis of the wake turbulence and coherent structures when comparing static and dynamic flow cases. The outcome of such studies could ultimately support effective wind farm wake flow control strategies. Texas Emerging Technology Fund (ETF).

Emergence of highly pathogenic porcine reproductive and respiratory syndrome (HP-PRRS) in medium-scale swine farms in southeastern Cambodia.

PubMed

Tornimbene, B; Frossard, J-P; Chhim, V; Sorn, S; Guitian, J; Drew, T W

2015-01-01

Since 2006, reports from China and Viet Nam have alerted of an emergent highly pathogenic variant of porcine reproductive and respiratory syndrome virus (HP-PRRSV) in that region. The frequent occurrence of outbreaks in these countries puts Cambodian pig farms at high risk of infection, but no study had been conducted to investigate the presence of HP-PRRS in Cambodian farms. We investigated the presence of HP-PRRS in medium-scale (semi-commercial) swine farms in the Cambodian southeastern region. Specifically, one province bordering Viet Nam (Takeo) was selected due to the concentration of most semi-commercial farms in that province. A cross-sectional study was carried out, between July and September 2010 to assess whether the prevalence of infection in these farms was indicative of recent spread of PPRSV and to identify risk factors for infection. The number of farms to be sampled was established using methods for Lot Quality Assurance Surveys (LQAS), in order to achieve a pre-established ability to discriminate between two different prevalence settings. The target population comprised all semi-commercial farms in Takeo province from which a random sample of 35 farms was selected. Selected farms were visited and questionnaires administered to gather information on farm characteristics and husbandry practices. Blood samples from individual pigs were collected in each of the study farms and tested for PRRSV, along with a number of other swine respiratory pathogens in order to investigate potential interactions. Our results showed that the virus was already present in Takeo semi-commercial pig population (LQAS herd prevalence ≥85%) at the time of sampling. The presence of sows in the farm and farm density were significantly associated (P<0.05) with the introduction and the presence of PRRS - but this was an unadjusted association as small sample size precluded multivariate analysis. Spatiotemporal description of the supposed pattern of infection revealed that the 1st farms infected were closely located to major national and provincial roads, connecting the Cambodian capital Phnom Penh to Viet Nam. Copyright © 2014 Elsevier B.V. All rights reserved.

Influence of grazing and land use on stream-channel characteristics among small dairy farms in the Eastern United States

USGS Publications Warehouse

Brand, Genevieve; Vondracek, Bruce C.; Jordan, Nicholas R.

2015-01-01

Rotational grazing (RG) is a livestock management practice that rotates grazing cattle on a scale of hours to days among small pastures termed paddocks. It may beneficially affect stream channels, relative to other livestock management practices. Such effects and other beneficial effects on hydrology are important to RG's potential to provide a highly multifunctional mode of livestock farming. Previous comparisons of effects of RG and confinement dairy (CD) on adjoining streams have been restricted in scale and scope. We examined 11 stream-channel characteristics on a representative sample of 37 small dairy farms that used either RG or CD production methods. Our objectives were: (1) to compare channel characteristics on RG and CD farms, as these production methods are implemented in practice, in New York, Pennsylvania and Wisconsin, USA; and (2) to examine land use on these farms that may affect stream-channel characteristics. To help interpret channel characteristic findings, we examined on-farm land use in riparian areas 50 m in width along both sides of stream reaches and whole-farm land use. In all states, stream-channel characteristics on RG and CD farms did not differ. Whole-farm land use differed significantly between farm types; CD farms allocated more land to annual row crops, whereas RG farms allocated more land to pasture and grassland. However, land cover in 50 m riparian areas was not different between farm types within states; in particular, many RG and CD farms had continuously grazed pastures in riparian areas, typically occupied by juvenile and non-lactating cows, which may have contributed sediment and nutrients to streams. This similarity in riparian management practices may explain the observed similarity of farm types with respect to stream-channel characteristics. To realize the potential benefits of RG on streams, best management practices that affect stream-channel characteristics, such as protection of riparian areas, may improve aggregate effects of RG on stream quality and also enhance other environment, economic and social benefits of RG.

A Field-Scale Sensor Network Data Set for Monitoring and Modeling the Spatial and Temporal Variation of Soil Water Content in a Dryland Agricultural Field

NASA Astrophysics Data System (ADS)

Gasch, C. K.; Brown, D. J.; Campbell, C. S.; Cobos, D. R.; Brooks, E. S.; Chahal, M.; Poggio, M.

2017-12-01

We describe a soil water content monitoring data set and auxiliary data collected at a 37 ha experimental no-till farm in the Northwestern United States. Water content measurements have been compiled hourly since 2007 by ECH2O-TE and 5TE sensors installed at 42 locations and five depths (0.3, 0.6, 0.9, 1.2, and 1.5 m, 210 sensors total) across the R.J. Cook Agronomy Farm, a Long-Term Agro-Ecosystem Research Site stationed on complex terrain in a Mediterranean climate. In addition to soil water content readings, the data set includes hourly and daily soil temperature readings, annual crop histories, a digital elevation model, Bt horizon maps, seasonal apparent electrical conductivity, soil texture, and soil bulk density. Meteorological records are also available for this location. We discuss the unique challenges of maintaining the network on an operating farm and demonstrate the nature and complexity of the soil water content data. This data set is accessible online through the National Agriculture Library, has been assigned a DOI, and will be maintained for the long term.

Staple Food Self-Sufficiency of Farmers Household Level in The Great Solo

NASA Astrophysics Data System (ADS)

Darsono

2017-04-01

Analysis of food security level of household is a novelty of measurement standards which usually includes regional and national levels. With household approach is expected to provide the basis of sharp food policy formulation. The purpose of this study are to identify the condition of self-sufficiency in staple foods, and to find the main factors affecting the dynamics of self-sufficiency in staple foods on farm household level in Great Solo. Using primary data from 50 farmers in the sample and secondary data in Great Solo (Surakarta city, Boyolali, Sukoharjo, Karanganyar, Wonogiri, Sragen and Klaten). Compiled panel data were analyzed with linear probability regression models to produce a good model. The results showed that farm households in Great Solo has a surplus of staple food (rice) with an average consumption rate of 96.8 kg/capita/year. This number is lower than the national rate of 136.7 kg/capita/year. The main factors affecting the level of food self-sufficiency in the farmer household level are: rice production, rice consumption, land tenure, and number of family members. Key recommendations from this study are; improvement scale of the land cultivation for rice farming and non-rice diversification consumption.

Biomass logistics analysis for large scale biofuel production: case study of loblolly pine and switchgrass.

PubMed

Lu, Xiaoming; Withers, Mitch R; Seifkar, Navid; Field, Randall P; Barrett, Steven R H; Herzog, Howard J

2015-05-01

The objective of this study was to assess the costs, energy consumption and greenhouse gas (GHG) emissions throughout the biomass supply chain for large scale biofuel production. Two types of energy crop were considered, switchgrass and loblolly pine, as representative of herbaceous and woody biomass. A biomass logistics model has been developed to estimate the feedstock supply system from biomass production through transportation. Biomass in the form of woodchip, bale and pellet was investigated with road, railway and waterway transportation options. Our analysis indicated that the farm or forest gate cost is lowest for loblolly pine whole tree woodchip at $39.7/dry tonne and highest for switchgrass round bale at $72.3/dry tonne. Switchgrass farm gate GHG emissions is approximately 146kgCO2e/dry tonne, about 4 times higher than loblolly pine. The optimum biomass transportation mode and delivered form are determined by the tradeoff between fixed and variable costs for feedstock shipment. Copyright © 2015 Elsevier Ltd. All rights reserved.

Extension Strategies for Poverty Alleviation: Lessons from China and India

ERIC Educational Resources Information Center

Swanson, Burton E.

2006-01-01

This paper discusses the transition from a national focus on food security during the last half of the 20th century to an emerging strategy on helping small-scale farm households increase farm income to reduce rural poverty. The basic proposition is that if extension is going to help increase farm incomes and rural employment, then it must shift…

Determining Performance Levels of Competencies for Job Entry Required of Beginning Farm Operators. Final Report.

ERIC Educational Resources Information Center

Avery, John H.

A sample of 145 people representing eighty farm operations and a statewide sample of 233 agricultural and agribusiness workers participated in a study to identify competencies, their importance (on a one to five rating scale), and the performance level required of a beginning farm operator in each of the following five cluster areas considered…

DairyWise, a whole-farm dairy model.

PubMed

Schils, R L M; de Haan, M H A; Hemmer, J G A; van den Pol-van Dasselaar, A; de Boer, J A; Evers, A G; Holshof, G; van Middelkoop, J C; Zom, R L G

2007-11-01

A whole-farm dairy model was developed and evaluated. The DairyWise model is an empirical model that simulated technical, environmental, and financial processes on a dairy farm. The central component is the FeedSupply model that balanced the herd requirements, as generated by the DairyHerd model, and the supply of homegrown feeds, as generated by the crop models for grassland and corn silage. The output of the FeedSupply model was used as input for several technical, environmental, and economic submodels. The submodels simulated a range of farm aspects such as nitrogen and phosphorus cycling, nitrate leaching, ammonia emissions, greenhouse gas emissions, energy use, and a financial farm budget. The final output was a farm plan describing all material and nutrient flows and the consequences on the environment and economy. Evaluation of DairyWise was performed with 2 data sets consisting of 29 dairy farms. The evaluation showed that DairyWise was able to simulate gross margin, concentrate intake, nitrogen surplus, nitrate concentration in ground water, and crop yields. The variance accounted for ranged from 37 to 84%, and the mean differences between modeled and observed values varied between -5 to +3% per set of farms. We conclude that DairyWise is a powerful tool for integrated scenario development and evaluation for scientists, policy makers, extension workers, teachers and farmers.

Comparison of bulk-tank standard plate count and somatic cell count for Wisconsin dairy farms in three size categories.

PubMed

Ingham, S C; Hu, Y; Ané, C

2011-08-01

The objective of this study was to evaluate possible claims by advocates of small-scale dairy farming that milk from smaller Wisconsin farms is of higher quality than milk from larger Wisconsin farms. Reported bulk tank standard plate count (SPC) and somatic cell count (SCC) test results for Wisconsin dairy farms were obtained for February to December, 2008. Farms were sorted into 3 size categories using available size-tracking criteria: small (≤118 cows; 12,866 farms), large (119-713 cattle; 1,565 farms), and confined animal feeding operations (≥714 cattle; 160 farms). Group means were calculated (group=farm size category) for the farms' minimum, median, mean, 90th percentile, and maximum SPC and SCC. Statistical analysis showed that group means for median, mean, 90th percentile, and maximum SPC and SCC were almost always significantly higher for the small farm category than for the large farm and confined animal feeding operations farm categories. With SPC and SCC as quality criteria and the 3 farm size categories of ≤118, 119 to 713, and ≥714 cattle, the claim of Wisconsin smaller farms producing higher quality milk than Wisconsin larger farms cannot be supported. Copyright © 2011 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

AgMIP Coordinated Global and Regional Assessments for 1.5°C and 2.0°C

NASA Astrophysics Data System (ADS)

Rosenzweig, C.

2017-12-01

The Agricultural Model Intercomparison and Improvement Project (AgMIP) has developed novel methods for Coordinated Global and Regional Assessments (CGRA) of agriculture and food security in a changing world. The present study performs a proof-of-concept of the CGRA to demonstrate advantages and challenges of the framework. This effort responds to the request by UNFCCC for the implications of limiting global temperature increases to 1.5°C and 2.0°C above pre-industrial conditions. The protocols for the 1.5°C/2.0°C assessment establish explicit and testable linkages across disciplines and scales, connecting outputs and inputs from the Shared Socio-economic Pathways (SSPs), Representative Agricultural Pathways (RAPs), HAPPI and CMIP5 ensemble scenarios, global gridded crop models, global agricultural economic models, site-based crop models, and within-country regional economic models. CGRA results show that at the global scale, mixed areas of positive and negative simulated yield changes, with declines in some breadbasket regions led to overall declines in productivity at both 1.5°C and 2.0°C. These projected global yield changes resulted in increases in prices of major commodities in a global economic model. Simulations for 1.5°C and 2.0°C using site-based crop models had mixed results depending on region and crop, but with more negative effects on productivity at 2.0°C than at 1.5°C for the most part. In conjunction with price changes from the global economics models, these productivity declines resulted generally in small positive effects on regional farm livelihoods, showing that farming systems should continue to be viable under high mitigation scenarios. CGRA protocols focus on how mitigation actions and effects differ across scales, with main mechanisms studied in the integrated assessment models being policies and technologies that reduce direct non-CO2 emissions from agriculture, reduce CO2 emissions from land use change and forest sink enhancement, and utilize biomass for energy production. At regional scales, increasing soil organic carbon (SOC) is of active interest.

IEA-Task 31 WAKEBENCH: Towards a protocol for wind farm flow model evaluation. Part 2: Wind farm wake models

NASA Astrophysics Data System (ADS)

Moriarty, Patrick; Sanz Rodrigo, Javier; Gancarski, Pawel; Chuchfield, Matthew; Naughton, Jonathan W.; Hansen, Kurt S.; Machefaux, Ewan; Maguire, Eoghan; Castellani, Francesco; Terzi, Ludovico; Breton, Simon-Philippe; Ueda, Yuko

2014-06-01

Researchers within the International Energy Agency (IEA) Task 31: Wakebench have created a framework for the evaluation of wind farm flow models operating at the microscale level. The framework consists of a model evaluation protocol integrated with a web-based portal for model benchmarking (www.windbench.net). This paper provides an overview of the building-block validation approach applied to wind farm wake models, including best practices for the benchmarking and data processing procedures for validation datasets from wind farm SCADA and meteorological databases. A hierarchy of test cases has been proposed for wake model evaluation, from similarity theory of the axisymmetric wake and idealized infinite wind farm, to single-wake wind tunnel (UMN-EPFL) and field experiments (Sexbierum), to wind farm arrays in offshore (Horns Rev, Lillgrund) and complex terrain conditions (San Gregorio). A summary of results from the axisymmetric wake, Sexbierum, Horns Rev and Lillgrund benchmarks are used to discuss the state-of-the-art of wake model validation and highlight the most relevant issues for future development.

Lessons Learned Developing an Extension-Based Training Program for Farm Labor Supervisors

ERIC Educational Resources Information Center

Roka, Fritz M.; Thissen, Carlene A.; Monaghan, Paul F.; Morera, Maria C.; Galindo-Gonzalez, Sebastian; Tovar-Aguilar, Jose Antonio

2017-01-01

This article outlines a four-step model for developing a training program for farm labor supervisors. The model draws on key lessons learned during the development of the University of Florida Institute of Food and Agricultural Sciences Farm Labor Supervisor Training program. The program is designed to educate farm supervisors on farm labor laws…

Topsoil N-budget model in orchard farming to evaluate groundwater nitrate contamination

NASA Astrophysics Data System (ADS)

Wijayanti, Yureana; Budihardjo, Kadarwati; Sakamoto, Yasushi; Setyandito, Oki

2017-12-01

A small scale field research was conducted in an orchard farming area in Kofu, Japan, where nitrate contamination was found in groundwater. The purpose of assessing the leaching of nitrate in this study is to understand the transformation and transport process of N-source in topsoil that leads to nitrate contamination of groundwater. In order to calculate N-budget in the soil, the model was utilized to predict the nitrogen leaching. In this res earch, the N-budget model was modified to evaluate influence of precipitation and application pattern of fertilizer and manure compost. The result shows that at the time before the addition of manure compost and fertilizer, about 75% of fertilizer leach from topsoil. Every month, the average remaining nitrate in soil from fertilizer and manure compost are 22% and 50%, respectively. The accumulation of this monthly manure compost nitrate, which stored in soil, should be carefully monitored. It could become the potential source of nitrate leaching to groundwater in the future.

Seaweed raft and farm design in the United States and China

DOE Office of Scientific and Technical Information (OSTI.GOV)

McKay, L.B.

1983-01-01

The following topics are discussed in this report: pilot-scale mariculture of seaweeds in Washington; experimental-scale raft culture of marine macroalgae in inland marine waters; macroalgal culture in California and China; land-based cultivation of seaweeds: an assessment of their potential yields for 'energy farming'; a design for energy-independent seaweed raft culture in tidal creeks and rivers; and the New York State marine biomass program.

Refinement of the nocturnal boundary layer budget method for quantifying agricultural greenhouse gas emissions

NASA Astrophysics Data System (ADS)

Wittebol, Laura A.

Measuring greenhouse gas (GHG) emissions directly at the farm scale is most relevant to the agricultural sector and has the potential to eliminate some of the uncertainty arising from scaling up from plot or field studies or down from regional or national levels. The stable nighttime atmosphere acts as a chamber within which sequentially-measured GHG concentration profiles determine the flux of GHGs. With the overall goal of refining the nocturnal boundary layer (NBL) budget method to obtain reliable flux estimates at a scale representative of the typical eastern Canadian farm (approximately 1 km2), fluxes of CO2, N2O, and CH4 were measured at two agricultural farms in Eastern Canada. Field sites in 1998 and 2002 were located on an experimental farm adjacent to a suburb southwest of the city of Ottawa, ON, a relatively flat area with corn, hay, and soy as the dominant crops. The field site in 2003 was located in the rural community of Coteau-du-Lac, QC, about 20 km southwest of the island of Montreal, a fairly flat area bordered by the St. Lawrence River to the south, consisting mainly of corn and hay with a mixture of soy and vegetable crops. A good agreement was obtained between the overall mean NBL budget-measured CO2 flux at both sites, near-in-time windy night eddy covariance data and previously published results. The mean NBL-measured N2O flux from all wind directions and farming management was of the same order of magnitude as, but slightly higher than, previously published baseline N2O emissions from agroecosystems. Methane fluxes results were judged to be invalid as they were extremely sensitive to wind direction change. Spatial sampling of CO 2, N2O, and CH4 around the two sites confirmed that [CH4] distribution was particularly sensitive to the nature of the emission source, field conditions, and wind direction. Optimal NBL conditions for measuring GHG fluxes, present approximately 60% of the time in this study, consisted of a very stable boundary layer in which GHG profiles converged at the top of the layer allowing a quick determination of the NBL flux integration height. For suboptimal NBL conditions consisting of intermittent turbulence where GHG profiles did not converge, a flux integration method was developed which yielded estimates similar to those obtained during optimal conditions. Eighty percent of the GHG flux in optimal NBL conditions corresponded to a footprint-modelled source area of approximately 2 km upwind, slightly beyond the typical length of a farm in Coteau-du-Lac. A large portion (50%) of the flux came from within 1 km upwind of the measurement site, showing the influence of local sources. 'Top-down' NBL-measured flux values were compared with aggregated field, literature and IPCC flux values for four footprint model-defined areas across both sites, with results indicating that in baseline climatic and farm management conditions, with no apparent intermittent NBL phenomena, the aggregated flux was a good approximation of the NBL-measured flux.

Modelling turbulent boundary layer flow over fractal-like multiscale terrain using large-eddy simulations and analytical tools.

PubMed

Yang, X I A; Meneveau, C

2017-04-13

In recent years, there has been growing interest in large-eddy simulation (LES) modelling of atmospheric boundary layers interacting with arrays of wind turbines on complex terrain. However, such terrain typically contains geometric features and roughness elements reaching down to small scales that typically cannot be resolved numerically. Thus subgrid-scale models for the unresolved features of the bottom roughness are needed for LES. Such knowledge is also required to model the effects of the ground surface 'underneath' a wind farm. Here we adapt a dynamic approach to determine subgrid-scale roughness parametrizations and apply it for the case of rough surfaces composed of cuboidal elements with broad size distributions, containing many scales. We first investigate the flow response to ground roughness of a few scales. LES with the dynamic roughness model which accounts for the drag of unresolved roughness is shown to provide resolution-independent results for the mean velocity distribution. Moreover, we develop an analytical roughness model that accounts for the sheltering effects of large-scale on small-scale roughness elements. Taking into account the shading effect, constraints from fundamental conservation laws, and assumptions of geometric self-similarity, the analytical roughness model is shown to provide analytical predictions that agree well with roughness parameters determined from LES.This article is part of the themed issue 'Wind energy in complex terrains'. © 2017 The Author(s).

Coxiella burnetii seropositivity and associated risk factors in goats in Ontario, Canada.

PubMed

Meadows, S; Jones-Bitton, A; McEwen, S; Jansen, J; Menzies, P

2015-10-01

Coxiella burnetii is a zoonotic bacterium, and infection in goats with this bacterium can result in abortion, stillbirth or birth of non-viable kids. A cross-sectional study was conducted to identify the seroprevalence and risk factors for C. burnetii exposure in Ontario goats. Sera were collected between August 2010 and February 2012, and tested for C. burnetii specific antibodies using an enzyme-linked immunosorbent assay (IDEXX). Overall, 63.2% (48/76, 95% CI=51.9-73.4) of farms had one or more seropositive goats. A higher farm-level seroprevalence of 78.6% (33/42) was found on dairy goat farms, compared to 44.1% (15/34) on meat goat farms (p<0.01). At the overall individual-animal level, 32.5% (714/2195, 95% CI=30.6-34.5) of goats were seropositive. Similarly, a higher individual-level seroprevalence was identified for dairy goats (43.7%, 633/1447) compared to meat goats (10.8%, 81/748) (p<0.001). A mixed multivariable logistic model that controlled for farm-level clustering identified risk factors associated with seropositivity (p<0.05). Increases in the female herd size (logarithmic scale) were associated with increased odds of seropositivity, while increases in male herd size had a negative association with seropositivity. If other sheep or goat farms were located in a 5-km radius, goats had 5.6 times (95% CI=1.01-30.8) times the odds of seropositivity compared to those that were not. Relative to goats from farms where all kidding pen hygiene was practiced (adding bedding, removing birth materials and disinfection after kidding), goats from farms which only added bedding and removed birth materials had a higher odds of seropositivity (OR=19.3, 95% CI=1.1-330.4), as did goats from farms which practiced none of these measures (OR=161.0, 95% CI=2.4-10822.2). An interaction term revealed kidding outdoors when there were no swine on farm had a protective effect on seropositivity compared to kidding indoors, or kidding outdoors with swine on the farm. These results can inform strategies to mitigate exposure to C. burnetii in Ontario. Copyright © 2015 Elsevier B.V. All rights reserved.

Assessment of gastrointestinal nematode infection, anthelmintic usage and husbandry practices on two small-scale goat farms in Malaysia.

PubMed

Wong, Flora; Sargison, Neil

2018-03-01

Haemonchosis is a common problem on goat farms in tropical countries such as Malaysia. Prevention of production losses generally depends on the use of anthelmintic drugs, but is threatened by the emergence of anthelmintic resistance. This study investigates anthelmintic efficacy on small-scale Malaysian goat farms and describes putative risk factors. Adult goats had moderate to high pre-treatment faecal trichostrongyle egg counts, despite being housed on slatted floors and fed on cut-and-carry forage, raising questions about the source of nematode infection. Our results show multiple resistance to benzimidazole and macrocyclic lactone anthelmintic drugs and allow us to discuss the genetic origins of resistance with reference to farm husbandry and management. We conclude that improvement in Malaysian goat production efficiency will require the development of sustainable helminth control strategies, underpinned by a better understanding of the origins and population genetics of anthelmintic resistance.

Farming for Ecosystem Services: An Ecological Approach to Production Agriculture.

PubMed

Philip Robertson, G; Gross, Katherine L; Hamilton, Stephen K; Landis, Douglas A; Schmidt, Thomas M; Snapp, Sieglinde S; Swinton, Scott M

2014-05-01

A balanced assessment of ecosystem services provided by agriculture requires a systems-level socioecological understanding of related management practices at local to landscape scales. The results from 25 years of observation and experimentation at the Kellogg Biological Station long-term ecological research site reveal services that could be provided by intensive row-crop ecosystems. In addition to high yields, farms could be readily managed to contribute clean water, biocontrol and other biodiversity benefits, climate stabilization, and long-term soil fertility, thereby helping meet society's need for agriculture that is economically and environmentally sustainable. Midwest farmers-especially those with large farms-appear willing to adopt practices that deliver these services in exchange for payments scaled to management complexity and farmstead benefit. Surveyed citizens appear willing to pay farmers for the delivery of specific services, such as cleaner lakes. A new farming for services paradigm in US agriculture seems feasible and could be environmentally significant.

Temporal and spatial water use on irrigated and nonirrigated pasture-based dairy farms.

PubMed

Higham, C D; Horne, D; Singh, R; Kuhn-Sherlock, B; Scarsbrook, M R

2017-08-01

Robust information for water use on pasture-based dairy farms is critical to farmers' attempts to use water more efficiently and the improved allocation of freshwater resources to dairy farmers. To quantify the water requirements of dairy farms across regions in a practicable manner, it will be necessary to develop predictive models. The objectives of this study were to compare water use on a group of irrigated and nonirrigated farms, validate existing water use models using the data measured on the group of nonirrigated farms, and modify the model so that it can be used to predict water use on irrigated dairy farms. Water use data were collected on a group of irrigated dairy farms located in the Canterbury, New Zealand, region with the largest area under irrigation. The nonirrigated farms were located in the Manawatu region. The amount of water used for irrigation was almost 52-fold greater than the amount of all other forms of water use combined. There were large differences in measured milking parlor water use, stock drinking water, and leakage rates between the irrigated and nonirrigated farms. As expected, stock drinking water was lower on irrigated dairy farms. Irrigation lowers the dry matter percentage of pasture, ensuring that the amount of water ingested from pasture remains high throughout the year, thereby reducing the demand for drinking water. Leakage rates were different between the 2 groups of farms; 47% of stock drinking water was lost as leakage on nonirrigated farms, whereas leakage on the irrigated farms equated to only 13% of stock drinking water. These differences in leakage were thought to be related to regional differences rather than differences in irrigated versus nonirrigated farms. Existing models developed to predict milking parlor, corrected stock drinking water, and total water use on nonirrigated pasture-based dairy farms in a previous related study were tested on the data measured in the present research. As expected, these models performed well for nonirrigated dairy farms but provided poor predictive power for irrigated farms. Partial least squares regression models were developed specifically to simulate corrected stock drinking water, milking parlor water, and total water use on irrigated dairy farms. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

An AgMIP framework for improved agricultural representation in integrated assessment models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ruane, Alex C.; Rosenzweig, Cynthia; Asseng, Senthold

Integrated assessment models (IAMs) hold great potential to assess how future agricultural systems will be shaped by socioeconomic development, technological innovation, and changing climate conditions. By coupling with climate and crop model emulators, IAMs have the potential to resolve important agricultural feedback loops and identify unintended consequences of socioeconomic development for agricultural systems. Here we propose a framework to develop robust representation of agricultural system responses within IAMs, linking downstream applications with model development and the coordinated evaluation of key climate responses from local to global scales. We survey the strengths and weaknesses of protocol-based assessments linked to the Agriculturalmore » Model Intercomparison and Improvement Project (AgMIP), each utilizing multiple sites and models to evaluate crop response to core climate changes including shifts in carbon dioxide concentration, temperature, and water availability, with some studies further exploring how climate responses are affected by nitrogen levels and adaptation in farm systems. Site-based studies with carefully calibrated models encompass the largest number of activities; however they are limited in their ability to capture the full range of global agricultural system diversity. Representative site networks provide more targeted response information than broadly-sampled networks, with limitations stemming from difficulties in covering the diversity of farming systems. Global gridded crop models provide comprehensive coverage, although with large challenges for calibration and quality control of inputs. Diversity in climate responses underscores that crop model emulators must distinguish between regions and farming system while recognizing model uncertainty. Finally, to bridge the gap between bottom-up and top-down approaches we recommend the deployment of a hybrid climate response system employing a representative network of sites to bias-correct comprehensive gridded simulations, opening the door to accelerated development and a broad range of applications.« less

An AgMIP framework for improved agricultural representation in integrated assessment models

NASA Astrophysics Data System (ADS)

Ruane, Alex C.; Rosenzweig, Cynthia; Asseng, Senthold; Boote, Kenneth J.; Elliott, Joshua; Ewert, Frank; Jones, James W.; Martre, Pierre; McDermid, Sonali P.; Müller, Christoph; Snyder, Abigail; Thorburn, Peter J.

2017-12-01

Integrated assessment models (IAMs) hold great potential to assess how future agricultural systems will be shaped by socioeconomic development, technological innovation, and changing climate conditions. By coupling with climate and crop model emulators, IAMs have the potential to resolve important agricultural feedback loops and identify unintended consequences of socioeconomic development for agricultural systems. Here we propose a framework to develop robust representation of agricultural system responses within IAMs, linking downstream applications with model development and the coordinated evaluation of key climate responses from local to global scales. We survey the strengths and weaknesses of protocol-based assessments linked to the Agricultural Model Intercomparison and Improvement Project (AgMIP), each utilizing multiple sites and models to evaluate crop response to core climate changes including shifts in carbon dioxide concentration, temperature, and water availability, with some studies further exploring how climate responses are affected by nitrogen levels and adaptation in farm systems. Site-based studies with carefully calibrated models encompass the largest number of activities; however they are limited in their ability to capture the full range of global agricultural system diversity. Representative site networks provide more targeted response information than broadly-sampled networks, with limitations stemming from difficulties in covering the diversity of farming systems. Global gridded crop models provide comprehensive coverage, although with large challenges for calibration and quality control of inputs. Diversity in climate responses underscores that crop model emulators must distinguish between regions and farming system while recognizing model uncertainty. Finally, to bridge the gap between bottom-up and top-down approaches we recommend the deployment of a hybrid climate response system employing a representative network of sites to bias-correct comprehensive gridded simulations, opening the door to accelerated development and a broad range of applications.

[Nitrogen balance in dairy farm: research progress].

PubMed

Lü, Chao; Qin, Wen-Xiao; Gao, Teng-Yun; Wang, Xiao-Xiao; Han, Zhi-Guo; Li, Jia

2013-01-01

Large dairy farm with intensive management has high stocking density, but generally does not have enough space and normative feces disposal system, resulting in the discharged nitrogen surpassed the environmental carrying capacity of unit area land. Dairy farm is one of the major emission sources of nitrogen discharges in agriculture, where the nitrogen balance has being aroused attention by the experts abroad. The research on the nitrogen flow and nitrogen balance in dairy farm is the basis of the dairy farm nitrogen cycling and management study, as well as the basis for the construction of environmental laws, regulations and policies. The most reliable indicators to evaluate the nitrogen flow and nitrogen balance in dairy farm are nitrogen surplus and nitrogen use efficiency. This paper introduced the concept of nitrogen balance on farm-scale and the nitrogen flow within farm, compared the application scope of nitrogen surplus and nitrogen use efficiency, analyzed the factors affecting the nitrogen balance in dairy farm, and summarized the effective strategies to reduce the nitrogen discharges from dairy farm, aimed to provide references for the nitrogen management of dairy farm in China.

Optimal crop selection and water allocation under limited water supply in irrigation

NASA Astrophysics Data System (ADS)

Stange, Peter; Grießbach, Ulrike; Schütze, Niels

2015-04-01

Due to climate change, extreme weather conditions such as droughts may have an increasing impact on irrigated agriculture. To cope with limited water resources in irrigation systems, a new decision support framework is developed which focuses on an integrated management of both irrigation water supply and demand at the same time. For modeling the regional water demand, local (and site-specific) water demand functions are used which are derived from optimized agronomic response on farms scale. To account for climate variability the agronomic response is represented by stochastic crop water production functions (SCWPF). These functions take into account different soil types, crops and stochastically generated climate scenarios. The SCWPF's are used to compute the water demand considering different conditions, e.g., variable and fixed costs. This generic approach enables the consideration of both multiple crops at farm scale as well as of the aggregated response to water pricing at a regional scale for full and deficit irrigation systems. Within the SAPHIR (SAxonian Platform for High Performance IRrigation) project a prototype of a decision support system is developed which helps to evaluate combined water supply and demand management policies.

Effects of urban sprawl on arthropod communities in peri-urban farmed landscape in Shenbei New District, Shenyang, Liaoning Province, China.

PubMed

Bian, Zhen-Xing; Wang, Shuai; Wang, Qiu-Bing; Yu, Miao; Qian, Feng-Kui

2018-01-08

Peri-urban farmland provides a diversity of ecological services. However, it is experiencing increasing pressures from urban sprawl. While the effects of land use associated with farming on arthropod assemblages has received increasing attention, most of this research has been conducted by comparing conventional and organic cropping systems. The present study identifies the effects of urban sprawl and the role of non-cropped habitat in defining arthropod diversity in peri-urban farmed landscapes. Multi-scale arthropod data from 30 sampling plots were used with linear-mixed models to elucidate the effects of distance from urban areas (0-13 km; 13-25 km and >25 km, zones I, II, and III, respectively) on arthropods. Results showed that urban sprawl, disturbed farm landscapes, and disturbance in non-cropped habitats had negative effects on arthropods, the latter requiring arthropods to re-establish annually from surrounding landscapes via dispersal. While arthropod species richness showed no obvious changes, arthropod abundance was lowest in zone II. Generally, patch density (PD), Shannon diversity index (SHDI), and aggregate index (AI) of non-cropped habitat were major drivers of changes in arthropod populations. This study contributes to identifying the effects of urban sprawl on arthropod diversity and documenting the multiple functions of farm landscapes in peri-urban regions.

Impacts of wind farms on surface air temperatures

PubMed Central

Baidya Roy, Somnath; Traiteur, Justin J.

2010-01-01

Utility-scale large wind farms are rapidly growing in size and numbers all over the world. Data from a meteorological field campaign show that such wind farms can significantly affect near-surface air temperatures. These effects result from enhanced vertical mixing due to turbulence generated by wind turbine rotors. The impacts of wind farms on local weather can be minimized by changing rotor design or by siting wind farms in regions with high natural turbulence. Using a 25-y-long climate dataset, we identified such regions in the world. Many of these regions, such as the Midwest and Great Plains in the United States, are also rich in wind resources, making them ideal candidates for low-impact wind farms. PMID:20921371

The effects of farm management practices on liver fluke prevalence and the current internal parasite control measures employed on Irish dairy farms.

PubMed

Selemetas, Nikolaos; Phelan, Paul; O'Kiely, Padraig; de Waal, Theo

2015-01-30

Fasciolosis caused by Fasciola hepatica is responsible for major production losses in cattle farms. The objectives of this study were to assess the effect of farm management practices on liver fluke prevalence on Irish dairy farms and to document the current control measures against parasitic diseases. In total, 369 dairy farms throughout Ireland were sampled from October to December 2013, each providing a single bulk tank milk (BTM) sample for liver fluke antibody-detection ELISA testing and completing a questionnaire on their farm management. The analysis of samples showed that cows on 78% (n=288) of dairy farms had been exposed to liver fluke. There was a difference (P<0.05) between farms where cows were positive or negative for liver fluke antibodies in (a) the total number of adult dairy cows in herds, (b) the number of adult dairy cows contributing to BTM samples, and (c) the size of the total area of grassland, with positive farms having larger numbers in each case. There was no difference (P>0.05) between positive and negative farms in (a) the grazing of dry cows together with replacement cows, (b) whether or not grazed grassland was mowed for conservation, (c) the type of drinking water provision system, (d) spreading of cattle manure on grassland or (e) for grazing season length (GSL; mean=262.5 days). Also, there were differences (P<0.001) between drainage statuses for GSL with farms on good drainage having longer GSL than moderately drained farms. The GSL for dairy cows on farms with good drainage was 11 days longer than for those with moderate drainage (P<0.001). The percentage of farmers that used an active ingredient during the non-lactating period against liver fluke, gastrointestinal nematodes, lungworm, and rumen fluke was 96%, 85%, 77% and 90%, respectively. Albendazole was the most frequently used active ingredient for treatment against gastrointestinal nematodes (57%), liver fluke (40%) and lungworm (47%), respectively. There was a difference (P<0.05) in the use of triclabendazole and albendazole between positive and negative farms, with triclabendazole use being more common in positive farms. This study highlighted differences in dairy management practices between Irish farms with dairy herds exposed or not exposed to liver fluke and stressed the need of fine-scale mapping of the disease patterns even at farm level to increase the accuracy of risk models. Also, comprehensive advice and professional support services to farmers on appropriate farm management practices are very important for an effective anthelmintic control strategy. Copyright © 2014 Elsevier B.V. All rights reserved.

Real time wind farm emulation using SimWindFarm toolbox

NASA Astrophysics Data System (ADS)

Topor, Marcel

2016-06-01

This paper presents a wind farm emulation solution using an open source Matlab/Simulink toolbox and the National Instruments cRIO platform. This work is based on the Aeolus SimWindFarm (SWF) toolbox models developed at Aalborg university, Denmark. Using the Matlab Simulink models developed in SWF, the modeling code can be exported to a real time model using the NI Veristand model framework and the resulting code is integrated as a hardware in the loop control on the NI 9068 platform.

Estimating nitrogen loading and far-field dispersal potential from background sources and coastal finfish aquaculture: A simple framework and case study in Atlantic Canada

NASA Astrophysics Data System (ADS)

McIver, R.; Milewski, I.; Loucks, R.; Smith, R.

2018-05-01

Far-field nutrient impacts associated with finfish aquaculture have been identified as a topic of concern for regulators, managers, scientists, and the public for over two decades but disentangling aquaculture impacts from those caused by other natural and anthropogenic sources has impeded the development of monitoring metrics and management plans. We apply a bulk, steady-state nitrogen loading model (NLM) framework to estimate the annual input of Total Dissolved Nitrogen (TDN) from point and non-point sources to the watershed surrounding Port Mouton Bay, Nova Scotia (Canada). We then use the results of the NLM together with estimates of dissolved inorganic nitrogen (DIN) loading from a sea-cage trout farm in the Bay and progressive vector diagrams to illustrate potential patterns of DIN dispersal from the trout farm. Our estimated anthropogenic nitrogen contribution to Port Mouton Bay from all terrestrial and atmospheric sources is ∼211,703 kg TDN/year with atmospheric deposition accounting for almost all (98.6%). At a stocking level of ∼400,000 rainbow trout, the Port Mouton Bay sea-cage farm increases the annual anthropogenic TDN loading to the bay by 14.4% or 30,400 kg. Depending on current flow rates, nitrogen flux from the trout farm can be more than double the background concentrations of TDN near the farm site. Although it is unlikely that nitrogen loading from this single fish farm is saturating the DIN requirements of the entire bay, progressive vector diagrams suggest that the dispersal potential may be insufficient to mitigate potential symptoms of eutrophication associated with nitrogen fluxes. We present an accessible and user-friendly tool for managers to estimate baseline nutrient loading in relation to aquaculture and our use of progressive vector diagrams illustrate a practical and simple method for characterizing potential nutrient dispersal based on local conditions and spatial scales. Our study joins numerous studies which have highlighted the need for more effective monitoring and assessment methods to improve the detection of aquaculture effects at far-field scales and to assess those effects in relation to other natural and anthropogenic factors impacting coastal habitats.

Multi-agent modeling and simulation of farmland use change in the farming-pastoral zone: A case study of Qianjingou Town in Inner Mongolia, China

NASA Astrophysics Data System (ADS)

Yan, H.

2015-12-01

Farmland is the most basic material conditions for guaranteeing rural livelihoods and national food security, and exploring management strategies that take both of the sustainable rural livelihoods and sustainable farmland use into account has vital significance of theory and practice. Farmland is a complex and self-adaptive system that couples human and natural systems together, and natural factors and social factors that are related to its changing process need to be considered when modeling farmland changing process. This paper takes Qianjingou Town in Inner Mongolia farming-pastoral zone as study area. From the perspective of the relationship between households' livelihoods and farmland use, this study builds the process mechanism of farmland use change based on questionnaires data, and constructs multi-agent simulation model of farmland use change with the help of Eclipse and Repast toolbox. Through simulating the relationship between natural factors (with geographical location) and households' behaviors, this paper systematically simulates households' renting and abandoning farmland behaviors, and truly describes dynamic interactions between households' livelihoods and factors related to farmland use change. These factors include natural factors (net primary productivity, road accessibility, slope and relief amplitude) and social factors (households' family structures, economic development and government policies). In the end, this study scientifically predicts farmland use change trend in the future 30 years. The simulation results show that, the number of abandoned and sublet farmland plots has a gradually increasing trend, the number of non-farm households and pure-outwork households has a remarkable increasing trend, and the number of part-farm households and pure-farm households shows a decreasing trend. Households' livelihoods sustainability in the study area is confronted with increasing pressure, and households' nonfarm employment has an increasing trend, while regional appropriate-scale agricultural management can be maintained. The research results establish the theory foundation and basic method for developing sustainable farmland use managements that can both meet households' willing and guarantee grain and ecology security.

Near real time wind energy forecasting incorporating wind tunnel modeling

NASA Astrophysics Data System (ADS)

Lubitz, William David

A series of experiments and investigations were carried out to inform the development of a day-ahead wind power forecasting system. An experimental near-real time wind power forecasting system was designed and constructed that operates on a desktop PC and forecasts 12--48 hours in advance. The system uses model output of the Eta regional scale forecast (RSF) to forecast the power production of a wind farm in the Altamont Pass, California, USA from 12 to 48 hours in advance. It is of modular construction and designed to also allow diagnostic forecasting using archived RSF data, thereby allowing different methods of completing each forecasting step to be tested and compared using the same input data. Wind-tunnel investigations of the effect of wind direction and hill geometry on wind speed-up above a hill were conducted. Field data from an Altamont Pass, California site was used to evaluate several speed-up prediction algorithms, both with and without wind direction adjustment. These algorithms were found to be of limited usefulness for the complex terrain case evaluated. Wind-tunnel and numerical simulation-based methods were developed for determining a wind farm power curve (the relation between meteorological conditions at a point in the wind farm and the power production of the wind farm). Both methods, as well as two methods based on fits to historical data, ultimately showed similar levels of accuracy: mean absolute errors predicting power production of 5 to 7 percent of the wind farm power capacity. The downscaling of RSF forecast data to the wind farm was found to be complicated by the presence of complex terrain. Poor results using the geostrophic drag law and regression methods motivated the development of a database search method that is capable of forecasting not only wind speeds but also power production with accuracy better than persistence.

"More drop per crop" when moving from gravitational to drip irrigated agriculture? Experiences from a North Moroccan case study

NASA Astrophysics Data System (ADS)

Feltz, N.; Gaspart, F.; Vanclooster, M.

2015-12-01

In order to save agricultural water, the famous FAO's "more crop per drop" has been taken literally in many arid or semi-arid places around the world and policies that aim improving "efficiencies" (irrigation efficiency…) have been implemented, often leading to the promotion of water saving technologies. In 1865, studying coal consumption, W.S. Jevons highlighted that improving coal use efficiency could, as a paradox, lead to higher global coal use. Many economists later extended this idea to resource saving technologies in general, showing that, due to the "rebound effect", the adoption of more efficient technologies, in terms of use of resources, could lead to a higher global consumption of this resource if this adoption didn't go with adjustment measures. Regarding these considerations, the emerging question is to which extent water saving technologies (i.e. that aim improving water related efficiencies) are appropriate to save water at large scale. Our study addresses this question through the analysis of the conversion from surface to drip irrigation in Triffa's irrigated perimeter (Morocco). We aim addressing this question using the detailed analysis of two data sets. First, available data were collected for every farm within the study area from the local administrations. Second, interviews were conducted with farmers to complete the dataset and to characterize their behavior. This allowed assessing water related efficiencies at farm scale. Subsequently, models were implemented to link efficiencies with general attributes and thereby identify the main drivers of water related efficiencies in the study area. Finally, these models were used to upscale farm-scale assessment to the perimeter scale. Our results show that, under current conditions, moving from surface to drip irrigation leads to higher global water withdrawal. However, the aforementioned "rebound effect" does not allow explaining the higher pressure because of contextual specificities. Deeper analysis suggests that economic but also social and psychological issues need to be considered in this transition process. To fully achieve the expected results from moving to drip irrigation, those issues must be dealt with and the transition to drip irrigation must go hand in hand with stewardship programs and appropriate farmers capacity building.

Antimicrobial Susceptibility Patterns of Clostridium difficile Isolates from Family Dairy Farms.

PubMed

Bandelj, P; Golob, M; Ocepek, M; Zdovc, I; Vengust, M

2017-05-01

A significant risk factor for developing Clostridium difficile infection (CDI) in humans and animals is associated with the antimicrobial use. It has often been hypothesized that farm animals could be the source for human infection with Clostridium difficile (CD). In the European Union, family-run dairy farms are the predominant farming model, which are more interlinked within the community compared to large-scale intensive dairy or beef farms. Therefore, it is important to investigate antimicrobial susceptibility patterns of CD in such environment. A total of 159 CD isolates from 20 family dairy farms were tested with a customized broth microdilution plate for their antimicrobial resistance. Seventeen antimicrobials were selected (amoxicillin, ceftriaxone, clindamycin, daptomycin, erythromycin, fusidic acid, imipenem, levofloxacin, linezolid, metronidazole, moxifloxacin, oxacillin, rifampicin, tetracycline, tigecycline, trimethoprim/sulfamethoxazole and vancomycin), which are commonly used for treatment of CDI in veterinary and human medicine, or were previously applied in CD epidemiological studies. Antimicrobials, which are used for treatment of CDI in humans (metronidazole, vancomycin, fusidic acid, tigecycline, linezolid) inhibited CD growth in vitro. Most CD isolates were resistant to erythromycin (93.1%), daptomycin (69.2%) and clindamycin (46.5%). High multiple-resistance was found in CD ribotype 012 (n = 5, 100%), some CD SLO 060 (n = 4, 25%) and one CD 033 (n = 1, 1.1%). High multiple-resistance in this study was linked with CD ribotypes and not with the origin of CD. The low prevalence of these ribotypes (6.3%; 10/159) indicates that family-run dairy farms are an unlikely source of CD with multiple-resistance to antimicrobials. © 2016 Blackwell Verlag GmbH.

Soil quality and soil degradation in agricultural loess soils in Central Europe - impacts of traditional small-scale and modernized large-scale agriculture

NASA Astrophysics Data System (ADS)

Schneider, Christian

2017-04-01

The study analyzes the impact of different farming systems on soil quality and soil degradation in European loess landscapes. The analyses are based on geo-chemical soil properties, landscape metrics and geomorphological indicators. The German Middle Saxonian Loess Region represents loess landscapes whose ecological functions were shaped by land consolidation measures resulting in large-scale high-input farming systems. The Polish Proszowice Plateau is still characterized by a traditional small-scale peasant agriculture. The research areas were analyzed on different scale levels combining GIS, field, and laboratory methods. A digital terrain classification was used to identify representative catchment basins for detailed pedological studies which were focused on soil properties that responded to soil management within several years, like pH-value, total carbon (TC), total nitrogen (TN), inorganic carbon (IC), soil organic carbon (TOC=TC-IC), hot-water extractable carbon (HWC), hot-water extractable nitrogen (HWN), total phosphorus, plant-available phosphorus (P), plant-available potassium (K) and the potential cation exchange capacity (CEC). The study has shown that significant differences in major soil properties can be observed because of different fertilizer inputs and partly because of different cultivation techniques. Also the traditional system increases soil heterogeneity. Contrary to expectations the study has shown that the small-scale peasant farming system resulted in similar mean soil organic carbon and phosphorus contents like the industrialized high-input farming system. A further study could include investigations of the effects of soil amendments like herbicides and pesticide on soil degradation.

Quantifying Human Appropriated Net Primary Productivity (HANPP) in a Ghanaian Cocoa System

NASA Astrophysics Data System (ADS)

Morel, A.; Adu-Bredu, S.; Adu Sasu, M.; Ashley Asare, R.; Boyd, E.; Hirons, M. A.; Malhi, Y.; Mason, J.; Norris, K.; Robinson, E. J. Z.; McDermott, C. L.

2015-12-01

Ghana is the second largest producer of cocoa (Theobroma cacoa), exporting approximately 18 percent of global volumes. These cocoa farms are predominantly small-scale, ranging in size from 2-4 hectares (ha). Traditionally, the model of cocoa expansion in Ghana relied on clearing new areas of forest and establishing a farm under remnant forest trees. This is increasingly less practical due to few unprotected forest areas remaining and management practices favoring close to full sun cocoa to maximize short-term yields. This study is part of a larger project, ECOLMITS, which is an interdisciplinary, ESPA-funded[1] initiative exploring the ecological limits of ecosystem system services (ESS) for alleviating poverty in small-scale agroforestry systems. The ecological study plots are situated within and around the Kakum National Forest, a well-protected, moist-evergreen forest of the Lower Guinea Forest region. Net primary productivity (NPP) is a measure of the rate at which carbon dioxide (CO2) is incorporated into plant tissues (e.g. canopy, stem and root). For this study, NPP was monitored in situ using methods developed by the Global Environmental Monitoring Network (GEM, http://gem.tropicalforests.ox.ac.uk/). By comparing NPP measured in intact forest and farms, the human appropriated NPP (HANPP) of this system can be estimated. The forest measures provide the "potential" NPP of the region, and then the reduction in NPP for farm plots is calculated for both land-cover change (HANPPLUC) and cocoa harvesting (HANPPHARV). The results presented are of the first year of NPP measurements across the cocoa landscape, including measurements from intact forest, logged forest and cocoa farms across a shade gradient and located at varying distances from the forest edge (e.g. 100 m, 500 m, 1 km and 5 km). These measures will have implications for carbon sequestration potential over the region and long-term sustainability of the Ghanaian cocoa sector. [1] Ecosystem Services for Poverty Alleviation grant program, http://www.espa.ac.uk/

Exploring expert opinion on the practicality and effectiveness of biosecurity measures on dairy farms in the United Kingdom using choice modeling.

PubMed

Shortall, Orla; Green, Martin; Brennan, Marnie; Wapenaar, Wendela; Kaler, Jasmeet

2017-03-01

Biosecurity, defined as a series of measures aiming to stop disease-causing agents entering or leaving an area where farm animals are present, is very important for the continuing economic viability of the United Kingdom dairy sector, and for animal welfare. This study gathered expert opinion from farmers, veterinarians, consultants, academics, and government and industry representatives on the practicality and effectiveness of different biosecurity measures on dairy farms. The study used best-worst scaling, a technique that allows for greater discrimination between choices and avoids the variability in interpretation associated with other methods, such as Likert scales and ranking methods. Keeping a closed herd was rated as the most effective measure overall, and maintaining regular contact with the veterinarian was the most practical measure. Measures relating to knowledge, planning, and veterinary involvement; buying-in practices; and quarantine and treatment scored highly for effectiveness overall. Measures relating to visitors, equipment, pest control, and hygiene scored much lower for effectiveness. Overall, measures relating to direct animal-to-animal contact scored much higher for effectiveness than measures relating to indirect disease transmission. Some of the most effective measures were also rated as the least practical, such as keeping a closed herd and avoiding nose-to-nose contact between contiguous animals, suggesting that real barriers exist for farmers when implementing biosecurity measures on dairy farms. We observed heterogeneity in expert opinion on biosecurity measures; for example, veterinarians rated the effectiveness of consulting the veterinarian on biosecurity significantly more highly than dairy farmers, suggesting a greater need for veterinarians to promote their services on-farm. Still, both groups rated it as a practical measure, suggesting that the farmer-veterinarian relationship holds some advantages for the promotion of biosecurity. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Wind Power Curve Modeling Using Statistical Models: An Investigation of Atmospheric Input Variables at a Flat and Complex Terrain Wind Farm

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wharton, S.; Bulaevskaya, V.; Irons, Z.

The goal of our FY15 project was to explore the use of statistical models and high-resolution atmospheric input data to develop more accurate prediction models for turbine power generation. We modeled power for two operational wind farms in two regions of the country. The first site is a 235 MW wind farm in Northern Oklahoma with 140 GE 1.68 turbines. Our second site is a 38 MW wind farm in the Altamont Pass Region of Northern California with 38 Mitsubishi 1 MW turbines. The farms are very different in topography, climatology, and turbine technology; however, both occupy high wind resourcemore » areas in the U.S. and are representative of typical wind farms found in their respective areas.« less

Comparing organic farming and land sparing: optimizing yield and butterfly populations at a landscape scale.

PubMed

Hodgson, Jenny A; Kunin, William E; Thomas, Chris D; Benton, Tim G; Gabriel, Doreen

2010-11-01

Organic farming aims to be wildlife-friendly, but it may not benefit wildlife overall if much greater areas are needed to produce a given quantity of food. We measured the density and species richness of butterflies on organic farms, conventional farms and grassland nature reserves in 16 landscapes. Organic farms supported a higher density of butterflies than conventional farms, but a lower density than reserves. Using our data, we predict the optimal land-use strategy to maintain yield whilst maximizing butterfly abundance under different scenarios. Farming conventionally and sparing land as nature reserves is better for butterflies when the organic yield per hectare falls below 87% of conventional yield. However, if the spared land is simply extra field margins, organic farming is optimal whenever organic yields are over 35% of conventional yields. The optimal balance of land sparing and wildlife-friendly farming to maintain production and biodiversity will differ between landscapes. © 2010 Blackwell Publishing Ltd/CNRS.

An experimental investigation on wind turbine aeromechanics and wake interferences among multiple wind turbines

NASA Astrophysics Data System (ADS)

Ozbay, Ahmet

A comprehensive experimental study was conducted to investigate wind turbine aeromechanics and wake interferences among multiple wind turbines sited in onshore and offshore wind farms. The experiments were carried out in a large-scale Aerodynamic/Atmospheric Boundary Layer (AABL) Wind Tunnel available at Iowa State University. An array of scaled three-blade Horizontal Axial Wind Turbine (HAWT) models were placed in atmospheric boundary layer winds with different mean and turbulence characteristics to simulate the situations in onshore and offshore wind farms. The effects of the important design parameters for wind farm layout optimization, which include the mean and turbulence characteristics of the oncoming surface winds, the yaw angles of the turbines with respect to the oncoming surface winds, the array spacing and layout pattern, and the terrain topology of wind farms on the turbine performances (i.e., both power output and dynamic wind loadings) and the wake interferences among multiple wind turbines, were assessed in detail. The aeromechanic performance and near wake characteristics of a novel dual-rotor wind turbine (DRWT) design with co-rotating or counter-rotating configuration were also investigated, in comparison to a conventional single rotor wind turbine (SRWT). During the experiments, in addition to measuring dynamic wind loads (both forces and moments) and the power outputs of the scaled turbine models, a high-resolution Particle Image Velocity (PIV) system was used to conduct detailed flow field measurements (i.e., both free-run and phase-locked flow fields measurements) to reveal the transient behavior of the unsteady wake vortices and turbulent flow structures behind wind turbines and to quantify the characteristics of the wake interferences among the wind turbines sited in non-homogenous surface winds. A miniature cobra anemometer was also used to provide high-temporal-resolution data at points of interest to supplement the full field PIV measurement results. The detailed flow field measurements are correlated with the dynamic wind loads and power output measurements to elucidate underlying physics in order to gain further insight into the characteristics of the power generation performance, dynamic wind loads and wake interferences of the wind turbines for higher total power yield and better durability of the wind turbines sited in atmospheric boundary layer (ABL) winds.

Can biosecurity and local network properties predict pathogen species richness in the salmonid industry?

PubMed

Yatabe, Tadaishi; More, Simon J; Geoghegan, Fiona; McManus, Catherine; Hill, Ashley E; Martínez-López, Beatriz

2018-01-01

Salmonid farming in Ireland is mostly organic, which implies limited disease treatment options. This highlights the importance of biosecurity for preventing the introduction and spread of infectious agents. Similarly, the effect of local network properties on infection spread processes has rarely been evaluated. In this paper, we characterized the biosecurity of salmonid farms in Ireland using a survey, and then developed a score for benchmarking the disease risk of salmonid farms. The usefulness and validity of this score, together with farm indegree (dichotomized as ≤ 1 or > 1), were assessed through generalized Poisson regression models, in which the modeled outcome was pathogen richness, defined here as the number of different diseases affecting a farm during a year. Seawater salmon (SW salmon) farms had the highest biosecurity scores with a median (interquartile range) of 82.3 (5.4), followed by freshwater salmon (FW salmon) with 75.2 (8.2), and freshwater trout (FW trout) farms with 74.8 (4.5). For FW salmon and trout farms, the top ranked model (in terms of leave-one-out information criteria, looic) was the null model (looic = 46.1). For SW salmon farms, the best ranking model was the full model with both predictors and their interaction (looic = 33.3). Farms with a higher biosecurity score were associated with lower pathogen richness, and farms with indegree > 1 (i.e. more than one fish supplier) were associated with increased pathogen richness. The effect of the interaction between these variables was also important, showing an antagonistic effect. This would indicate that biosecurity effectiveness is achieved through a broader perspective on the subject, which includes a minimization in the number of suppliers and hence in the possibilities for infection to enter a farm. The work presented here could be used to elaborate indicators of a farm's disease risk based on its biosecurity score and indegree, to inform risk-based disease surveillance and control strategies for private and public stakeholders.

Greenhouse gas balance of mountain dairy farms as affected by grassland carbon sequestration.

PubMed

Salvador, Sara; Corazzin, Mirco; Romanzin, Alberto; Bovolenta, Stefano

2017-07-01

Recent studies on milk production have often focused on environmental impacts analysed using the Life Cycle Assessment (LCA) approach. In grassland-based livestock systems, soil carbon sequestration might be a potential sink to mitigate greenhouse gas (GHG) balance. Nevertheless, there is no commonly shared methodology. In this work, the GHG emissions of small-scale mountain dairy farms were assessed using the LCA approach. Two functional units, kg of Fat and Protein Corrected Milk (FPCM) and Utilizable Agricultural Land (UAL), and two different emissions allocations methods, no allocation and physical allocation, which accounts for the co-product beef, were considered. Two groups of small-scale dairy farms were identified based on the Livestock Units (LU) reared: <30 LU (LLU) and >30 LU (HLU). Before considering soil carbon sequestration in LCA, performing no allocation methods, LLU farms tended to have higher GHG emission than HLU farms per kg of FPCM (1.94 vs. 1.59 kg CO 2 -eq/kg FPCM, P ≤ 0.10), whereas the situation was reversed upon considering the m 2 of UAL as a functional unit (0.29 vs. 0.89 kg CO 2 -eq/m 2 , P ≤ 0.05). Conversely, considering physical allocation, the difference between the two groups became less noticeable. When the contribution from soil carbon sequestration was included in the LCA and no allocation method was performed, LLU farms registered higher values of GHG emission per kg of FPCM than HLU farms (1.38 vs. 1.10 kg CO 2 -eq/kg FPCM, P ≤ 0.05), and the situation was likewise reversed in this case upon considering the m 2 of UAL as a functional unit (0.22 vs. 0.73 kg CO 2 -eq/m 2 , P ≤ 0.05). To highlight how the presence of grasslands is crucial for the carbon footprint of small-scale farms, this study also applied a simulation for increasing the forage self-sufficiency of farms to 100%. In this case, an average reduction of GHG emission per kg of FPCM of farms was estimated both with no allocation and with physical allocation, reaching 27.0% and 28.8%, respectively. Copyright © 2017 Elsevier Ltd. All rights reserved.

Antimicrobials usage assessments in commercial poultry and local birds in North-central Nigeria: Associated pathways and factors for resistance emergence and spread.

PubMed

Alhaji, N B; Haruna, A E; Muhammad, B; Lawan, M K; Isola, T O

2018-06-01

The World Health Organization's Global Action Plan on antimicrobial resistance (AMR) recommended monitoring of antimicrobial use (AMU) through surveillance and research to help mitigate AMR. This survey was aimed at assessing poultry owners' knowledge/awareness and practices regarding AMU, identified pathways for AMR emergence and spread in small-scale commercial poultry farms and free-range local bird flocks in North-central Nigeria. An interview questionnaire-based cross-sectional study was conducted on commercial poultry farmers and local bird flock keepers in 2017. Also, a Traffic Light system model was used assess risk status of AMU in farms and flocks. All the 384 recruited poultry farmers/keepers participated in the survey. Female respondents were the majority (67.2%). Low proportion of poultry farmers (46.4%, 89/192) and very low proportion of bird keepers (6.8%, 13/192) knew antimicrobials misuse to be when administered under dose. About 48% (93/192) of farmers and 93% (179/192) of keepers arbitrary determined antimicrobial dosage before administration. Respondents used antimicrobials for therapeutic, prophylactic, and growth promotion in birds. Also, participants significantly identified contaminated poultry products, infected poultry or contaminated formites, and discharged contaminated faeces into environment as pathways for transmission of antimicrobial resistant pathogens to humans. Traffic Light system model revealed 88.5% of small-scale commercial poultry farms to frequently used antimicrobials without veterinarians' consultations thereby attaining Class 1 (Red risk) status. The model showed that 92.1% of free-range local bird flocks rarely used antimicrobials thereby attaining Class 3 (Green risk) status. Improper antimicrobial dosage in poultry (OR: 7.23; 95% CI: 2.74, 19.21), non-enforcement of AMU regulating laws in poultry (OR: 4.12; 95% CI: 2.39, 7.10), weak financial status of poultry owners (OR: 3.00; 95% CI: 2.39, 7.10), and management system (OR: 8.94; 95% CI: 5.62, 14.24) were more likely to satisfactorily influenced antimicrobials misuse in poultry farms and local bird flocks. The survey revealed low knowledge level regarding AMU in the poultry. Antimicrobials were rarely used in local bird flocks, making them likely organic and safe from AMR. It is imperative to educate farmers on judicious AMU, enforce existing veterinary legislation on antimicrobials, establish antimicrobials surveillance system, and sensitize farmers on adequate biosecurity measures and routine vaccination of farms, so as to assure food safety, food security, and public health. Copyright © 2018 Elsevier B.V. All rights reserved.

Pest Control and Pollination Cost-Benefit Analysis of Hedgerow Restoration in a Simplified Agricultural Landscape.

PubMed

Morandin, L A; Long, R F; Kremen, C

2016-05-11

Field edge habitat in homogeneous agricultural landscapes can serve multiple purposes including enhanced biodiversity, water quality protection, and habitat for beneficial insects, such as native bees and natural enemies. Despite this ecosystem service value, adoption of field border plantings, such as hedgerows, on large-scale mono-cropped farms is minimal. With profits primarily driving agricultural production, a major challenge affecting hedgerow plantings is linked to establishment costs and the lack of clear economic benefits on the restoration investment. Our study documented that hedgerows are economically viable to growers by enhancing beneficial insects and natural pest control and pollination on farms. With pest control alone, our model shows that it would take 16 yr to break even from insecticide savings on the US$4,000 cost of a typical 300-m hedgerow field edge planting. By adding in pollination benefits by native bees, where honey bees (Apis mellifera L.) may be limiting, the return time is reduced to 7 yr. USDA cost share programs allow for a quicker return on a hedgerow investment. Our study shows that over time, small-scale restoration can be profitable, helping to overcome the barrier of cost associated with field edge habitat restoration on farms. Published by Oxford University Press on behalf of Entomological Society of America 2016. This work is written by US Government employees and is in the public domain in the United States.

Evaluation of the sustainability of contrasted pig farming systems: breeding programmes.

PubMed

Rydhmer, L; Gourdine, J L; de Greef, K; Bonneau, M

2014-12-01

The sustainability of breeding activities in 15 pig farming systems in five European countries was evaluated. One conventional and two differentiated systems per country were studied. The Conventional systems were the standard systems in their countries. The differentiated systems were of three categories: Adapted Conventional with focus on animal welfare, meat quality or environment (five systems); Traditional with local breeds in small-scale production (three systems) and Organic (two systems). Data were collected with a questionnaire from nine breeding organisations providing animals and semen to the studied farming systems and from, on average, five farmers per farming system. The sustainability assessment of breeding activities was performed in four dimensions. The first dimension described whether the market for the product was well defined, and whether the breeding goal reflected the farming system and the farmers' demands. The second dimension described recording and selection procedures, together with genetic change in traits that were important in the system. The third dimension described genetic variation, both within and between pig breeds. The fourth dimension described the management of the breeding organisation, including communication, transparency, and technical and human resources. The results show substantial differences in the sustainability of breeding activities, both between farming systems within the same category and between different categories of farming systems. The breeding activities are assessed to be more sustainable for conventional systems than for differentiated systems in three of the four dimensions. In most differentiated farming systems, breeding goals are not related to the system, as these systems use the same genetic material as conventional systems. The breeds used in Traditional farming systems are important for genetic biodiversity, but the small scale of these systems renders them vulnerable. It is hoped that, by reflecting on different aspects of sustainability, this study will encourage sustainable developments in pig production.

"An Equal Interest in the Soil": Creek Small-Scale Farming and the Work of Nationhood, 1866-1889

ERIC Educational Resources Information Center

Chang, David A.

2009-01-01

After the war in 1866, slaves became the owners of the lands they once farmed for their masters. The land they farmed became their own because of the nature of Creek citizenship and land tenure. The 1866 treaty of peace between the United States federal government and the Creek Nation (also known as the Muskogee Nation) declared that freed slaves…

The Development of a Model Design to Assess Instruction in Farm Management in Terms of Economic Returns and the Understanding of Economic Principles.

ERIC Educational Resources Information Center

Rolloff, John August

The records of 27 farm operators participating in farm business analysis programs in 5 Ohio schools were studied to develop and test a model for determining the influence of the farm business analysis phase of vocational agriculture instruction in farm management. Economic returns were measured as ratios between 1965 program inputs and outputs…

Do differences in food web structure between organic and conventional farms affect the ecosystem service of pest control?

PubMed

Macfadyen, Sarina; Gibson, Rachel; Polaszek, Andrew; Morris, Rebecca J; Craze, Paul G; Planqué, Robert; Symondson, William O C; Memmott, Jane

2009-03-01

While many studies have demonstrated that organic farms support greater levels of biodiversity, it is not known whether this translates into better provision of ecosystem services. Here we use a food-web approach to analyse the community structure and function at the whole-farm scale. Quantitative food webs from 10 replicate pairs of organic and conventional farms showed that organic farms have significantly more species at three trophic levels (plant, herbivore and parasitoid) and significantly different network structure. Herbivores on organic farms were attacked by more parasitoid species on organic farms than on conventional farms. However, differences in network structure did not translate into differences in robustness to simulated species loss and we found no difference in percentage parasitism (natural pest control) across a variety of host species. Furthermore, a manipulative field experiment demonstrated that the higher species richness of parasitoids on the organic farms did not increase mortality of a novel herbivore used to bioassay ecosystem service. The explanation for these differences is likely to include inherent differences in management strategies and landscape structure between the two farming systems.

The dairy industry: a brief description of production practices, trends, and farm characteristics around the world.

PubMed

Douphrate, David I; Hagevoort, G Robert; Nonnenmann, Matthew W; Lunner Kolstrup, Christina; Reynolds, Stephen J; Jakob, Martina; Kinsel, Mark

2013-01-01

The global dairy industry is composed of a multitude of countries with unique production practices and consumer markets. The global average number of cows per farm is about 1-2 cows; however, as a farm business model transitions from sustenance to market production, the average herd size, and subsequent labor force increases. Dairy production is unique as an agricultural commodity because milk is produced daily, for 365 days per year. With the introduction of new technology such as the milking parlor, the global industry trend is one of increasing farm sizes. The farm sizes are the largest in the United States; however, the European Union produces the most milk compared with other global producers. Dairy production is essential for economic development and sustainable communities in rural areas. However, the required capital investment and availability of local markets and labor are continued challenges. Due to farm expansion, international producers are faced with new challenges related to assuring food safety and a safe working environment for their workforce. These challenges exist in addition to the cultural and language barriers related to an increasing dependence on immigrant labor in many regions of the world. Continued success of the global dairy industry is vital. Therefore, research should continue to address the identification of occupational risk factors associated with injuries and illnesses, as well as develop cost-effective interventions and practices that lead to the minimization or elimination of these injuries and illnesses on a global scale, among our valuable population of dairy producers and workers.

Modelling the Wind-Borne Spread of Highly Pathogenic Avian Influenza Virus between Farms

PubMed Central

Ssematimba, Amos; Hagenaars, Thomas J.; de Jong, Mart C. M.

2012-01-01

A quantitative understanding of the spread of contaminated farm dust between locations is a prerequisite for obtaining much-needed insight into one of the possible mechanisms of disease spread between farms. Here, we develop a model to calculate the quantity of contaminated farm-dust particles deposited at various locations downwind of a source farm and apply the model to assess the possible contribution of the wind-borne route to the transmission of Highly Pathogenic Avian Influenza virus (HPAI) during the 2003 epidemic in the Netherlands. The model is obtained from a Gaussian Plume Model by incorporating the dust deposition process, pathogen decay, and a model for the infection process on exposed farms. Using poultry- and avian influenza-specific parameter values we calculate the distance-dependent probability of between-farm transmission by this route. A comparison between the transmission risk pattern predicted by the model and the pattern observed during the 2003 epidemic reveals that the wind-borne route alone is insufficient to explain the observations although it could contribute substantially to the spread over short distance ranges, for example, explaining 24% of the transmission over distances up to 25 km. PMID:22348042

Modelling the wind-borne spread of highly pathogenic avian influenza virus between farms.

PubMed

Ssematimba, Amos; Hagenaars, Thomas J; de Jong, Mart C M

2012-01-01

A quantitative understanding of the spread of contaminated farm dust between locations is a prerequisite for obtaining much-needed insight into one of the possible mechanisms of disease spread between farms. Here, we develop a model to calculate the quantity of contaminated farm-dust particles deposited at various locations downwind of a source farm and apply the model to assess the possible contribution of the wind-borne route to the transmission of Highly Pathogenic Avian Influenza virus (HPAI) during the 2003 epidemic in the Netherlands. The model is obtained from a Gaussian Plume Model by incorporating the dust deposition process, pathogen decay, and a model for the infection process on exposed farms. Using poultry- and avian influenza-specific parameter values we calculate the distance-dependent probability of between-farm transmission by this route. A comparison between the transmission risk pattern predicted by the model and the pattern observed during the 2003 epidemic reveals that the wind-borne route alone is insufficient to explain the observations although it could contribute substantially to the spread over short distance ranges, for example, explaining 24% of the transmission over distances up to 25 km.

Description and typology of intensive Chios dairy sheep farms in Greece.

PubMed

Gelasakis, A I; Valergakis, G E; Arsenos, G; Banos, G

2012-06-01

The aim was to assess the intensified dairy sheep farming systems of the Chios breed in Greece, establishing a typology that may properly describe and characterize them. The study included the total of the 66 farms of the Chios sheep breeders' cooperative Macedonia. Data were collected using a structured direct questionnaire for in-depth interviews, including questions properly selected to obtain a general description of farm characteristics and overall management practices. A multivariate statistical analysis was used on the data to obtain the most appropriate typology. Initially, principal component analysis was used to produce uncorrelated variables (principal components), which would be used for the consecutive cluster analysis. The number of clusters was decided using hierarchical cluster analysis, whereas, the farms were allocated in 4 clusters using k-means cluster analysis. The identified clusters were described and afterward compared using one-way ANOVA or a chi-squared test. The main differences were evident on land availability and use, facility and equipment availability and type, expansion rates, and application of preventive flock health programs. In general, cluster 1 included newly established, intensive, well-equipped, specialized farms and cluster 2 included well-established farms with balanced sheep and feed/crop production. In cluster 3 were assigned small flock farms focusing more on arable crops than on sheep farming with a tendency to evolve toward cluster 2, whereas cluster 4 included farms representing a rather conservative form of Chios sheep breeding with low/intermediate inputs and choosing not to focus on feed/crop production. In the studied set of farms, 4 different farmer attitudes were evident: 1) farming disrupts sheep breeding; feed should be purchased and economies of scale will decrease costs (mainly cluster 1), 2) only exercise/pasture land is necessary; at least part of the feed (pasture) must be home-grown to decrease costs (clusters 1 and 4), 3) providing pasture to sheep is essential; on-farm feed production decreases costs (mainly cluster 3), and 4) large-scale farming (feed production and cash crops) does not disrupt sheep breeding; all feed must be produced on-farm to decrease costs (mainly cluster 3). Conducting a profitability analysis among different clusters, exploring and discovering the most beneficial levels of intensified management and capital investment should now be considered. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Integrated Farm System Model Version 4.3 and Dairy Gas Emissions Model Version 3.3 Software development and distribution

USDA-ARS?s Scientific Manuscript database

Modeling routines of the Integrated Farm System Model (IFSM version 4.2) and Dairy Gas Emission Model (DairyGEM version 3.2), two whole-farm simulation models developed and maintained by USDA-ARS, were revised with new components for: (1) simulation of ammonia (NH3) and greenhouse gas emissions gene...

Data-driven modeling of hydroclimatic trends and soil moisture: Multi-scale data integration and decision support

NASA Astrophysics Data System (ADS)

Coopersmith, Evan Joseph

The techniques and information employed for decision-making vary with the spatial and temporal scope of the assessment required. In modern agriculture, the farm owner or manager makes decisions on a day-to-day or even hour-to-hour basis for dozens of fields scattered over as much as a fifty-mile radius from some central location. Following precipitation events, land begins to dry. Land-owners and managers often trace serpentine paths of 150+ miles every morning to inspect the conditions of their various parcels. His or her objective lies in appropriate resource usage -- is a given tract of land dry enough to be workable at this moment or would he or she be better served waiting patiently? Longer-term, these owners and managers decide upon which seeds will grow most effectively and which crops will make their operations profitable. At even longer temporal scales, decisions are made regarding which fields must be acquired and sold and what types of equipment will be necessary in future operations. This work develops and validates algorithms for these shorter-term decisions, along with models of national climate patterns and climate changes to enable longer-term operational planning. A test site at the University of Illinois South Farms (Urbana, IL, USA) served as the primary location to validate machine learning algorithms, employing public sources of precipitation and potential evapotranspiration to model the wetting/drying process. In expanding such local decision support tools to locations on a national scale, one must recognize the heterogeneity of hydroclimatic and soil characteristics throughout the United States. Machine learning algorithms modeling the wetting/drying process must address this variability, and yet it is wholly impractical to construct a separate algorithm for every conceivable location. For this reason, a national hydrological classification system is presented, allowing clusters of hydroclimatic similarity to emerge naturally from annual regime curve data and facilitate the development of cluster-specific algorithms. Given the desire to enable intelligent decision-making at any location, this classification system is developed in a manner that will allow for classification anywhere in the U.S., even in an ungauged basin. Daily time series data from 428 catchments in the MOPEX database are analyzed to produce an empirical classification tree, partitioning the United States into regions of hydroclimatic similarity. In constructing a classification tree based upon 55 years of data, it is important to recognize the non-stationary nature of climate data. The shifts in climatic regimes will cause certain locations to shift their ultimate position within the classification tree, requiring decision-makers to alter land usage, farming practices, and equipment needs, and algorithms to adjust accordingly. This work adapts the classification model to address the issue of regime shifts over larger temporal scales and suggests how land-usage and farming protocol may vary from hydroclimatic shifts in decades to come. Finally, the generalizability of the hydroclimatic classification system is tested with a physically-based soil moisture model calibrated at several locations throughout the continental United States. The soil moisture model is calibrated at a given site and then applied with the same parameters at other sites within and outside the same hydroclimatic class. The model's performance deteriorates minimally if the calibration and validation location are within the same hydroclimatic class, but deteriorates significantly if the calibration and validates sites are located in different hydroclimatic classes. These soil moisture estimates at the field scale are then further refined by the introduction of LiDAR elevation data, distinguishing faster-drying peaks and ridges from slower-drying valleys. The inclusion of LiDAR enabled multiple locations within the same field to be predicted accurately despite non-identical topography. This cross-application of parametric calibrations and LiDAR-driven disaggregation facilitates decision-support at locations without proximally-located soil moisture sensors.

Ammonia emission model for whole farm evaluation of dairy production systems.

PubMed

Rotz, C Alan; Montes, Felipe; Hafner, Sasha D; Heber, Albert J; Grant, Richard H

2014-07-01

Ammonia (NH) emissions vary considerably among farms as influenced by climate and management. Because emission measurement is difficult and expensive, process-based models provide an alternative for estimating whole farm emissions. A model that simulates the processes of NH formation, speciation, aqueous-gas partitioning, and mass transfer was developed and incorporated in a whole farm simulation model (the Integrated Farm System Model). Farm sources included manure on the floor of the housing facility, manure in storage (if used), field-applied manure, and deposits on pasture (if grazing is used). In a comprehensive evaluation of the model, simulated daily, seasonal, and annual emissions compared well with data measured over 2 yr for five free stall barns and two manure storages on dairy farms in the eastern United States. In a further comparison with published data, simulated and measured barn emissions were similar over differing barn designs, protein feeding levels, and seasons of the year. Simulated emissions from manure storage were also highly correlated with published emission data across locations, seasons, and different storage covers. For field applied manure, the range in simulated annual emissions normally bounded reported mean values for different manure dry matter contents and application methods. Emissions from pastures measured in northern Europe across seasons and fertilization levels were also represented well by the model. After this evaluation, simulations of a representative dairy farm in Pennsylvania illustrated the effects of animal housing and manure management on whole farm emissions and their interactions with greenhouse gas emissions, nitrate leaching, production costs, and farm profitability. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Modeling Commercial Freshwater Turtle Production on US Farms for Pet and Meat Markets

PubMed Central

Mali, Ivana; Wang, Hsiao-Hsuan; Grant, William E.; Feldman, Mark; Forstner, Michael R. J.

2015-01-01

Freshwater turtles are being exploited for meat, eggs, traditional medicine, and pet trade. As a response, turtle farming became a booming aquaculture industry in the past two decades, specifically in the southeastern states of the United States of America (US) and across Southeast Asia. However, US turtle farms are currently producing turtles only for the pet trade while commercial trappers remain focused on catching the largest individuals from the wild. In our analyses we have created a biological and economic model that describes farming operations on a representative turtle farm in Louisiana. We first modeled current production of hatchling and yearling red-eared slider turtles (Trachemys scripta elegans) (i.e., traditional farming) for foreign and domestic pet markets, respectively. We tested the possibility of harvesting adult turtles from the breeding stock for sale to meat markets to enable alternative markets for the farmers, while decreasing the continued pressures on wild populations (i.e., non-traditional farming). Our economic model required current profit requirements of ~$13/turtle or ~$20.31/kg of meat from non-traditional farming in order to acquire the same profit as traditional farming, a value which currently exceeds market values of red-eared sliders. However, increasing competition with Asian turtle farms and decreasing hatchling prices may force the shift in the US toward producing turtles for meat markets. In addition, our model can be modified and applied to more desirable species on the meat market once more knowledge is acquired about species life histories and space requirements under farmed conditions. PMID:26407157

Modeling Commercial Freshwater Turtle Production on US Farms for Pet and Meat Markets.

PubMed

Mali, Ivana; Wang, Hsiao-Hsuan; Grant, William E; Feldman, Mark; Forstner, Michael R J

2015-01-01

Freshwater turtles are being exploited for meat, eggs, traditional medicine, and pet trade. As a response, turtle farming became a booming aquaculture industry in the past two decades, specifically in the southeastern states of the United States of America (US) and across Southeast Asia. However, US turtle farms are currently producing turtles only for the pet trade while commercial trappers remain focused on catching the largest individuals from the wild. In our analyses we have created a biological and economic model that describes farming operations on a representative turtle farm in Louisiana. We first modeled current production of hatchling and yearling red-eared slider turtles (Trachemys scripta elegans) (i.e., traditional farming) for foreign and domestic pet markets, respectively. We tested the possibility of harvesting adult turtles from the breeding stock for sale to meat markets to enable alternative markets for the farmers, while decreasing the continued pressures on wild populations (i.e., non-traditional farming). Our economic model required current profit requirements of ~$13/turtle or ~$20.31/kg of meat from non-traditional farming in order to acquire the same profit as traditional farming, a value which currently exceeds market values of red-eared sliders. However, increasing competition with Asian turtle farms and decreasing hatchling prices may force the shift in the US toward producing turtles for meat markets. In addition, our model can be modified and applied to more desirable species on the meat market once more knowledge is acquired about species life histories and space requirements under farmed conditions.

The Farm Process Version 2 (FMP2) for MODFLOW-2005 - Modifications and Upgrades to FMP1

USGS Publications Warehouse

Schmid, Wolfgang; Hanson, R.T.

2009-01-01

The ability to dynamically simulate the integrated supply-and-demand components of irrigated agricultural is needed to thoroughly understand the interrelation between surface water and groundwater flow in areas where the water-use by vegetation is an important component of the water budget. To meet this need, the computer program Farm Process (FMP1) was updated and refined for use with the U.S. Geological Survey's MODFLOW-2005 groundwater-flow model, and is referred to as MF2005-FMP2. The updated program allows the simulation, analysis, and management of nearly all components of human and natural water use. MF2005-FMP2 represents a complete hydrologic model that fully links the movement and use of groundwater, surface water, and imported water for water consumption of irrigated agriculture, but also of urban use, and of natural vegetation. Supply and demand components of water use are analyzed under demand-driven and supply-constrained conditions. From large- to small-scale settings, the MF2005-FMP2 has the unique set of capabilities to simulate and analyze historical, present, and future conditions. MF2005-FMP2 facilitates the analysis of agricultural water use where little data is available for pumpage, land use, or agricultural information. The features presented in this new version of FMP2 along with the linkages to the Streamflow Routing (SFR), Multi-Node Well (MNW), and Unsaturated Zone Flow (UZF) Packages prevents mass loss to an open system and helps to account for 'all of the water everywhere and all of the time'. The first version, FMP1 for MODFLOW-2000, is limited to (a) transpiration uptake from unsaturated root zones, (b) on-farm efficiency defined solely by farm and not by crop type, (c) a simulation of water use and returnflows related only to irrigated agriculture and not also to non-irrigated vegetation, (d) a definition of consumptive use as potential crop evapotranspiration, (e) percolation being instantly recharged to the uppermost active aquifer, (f) automatic routing of returnflow from runoff either to reaches of tributary stream segments adjacent to a farm or to one reach nearest to the farm's lowest elevation, (g) farm-well pumping from cell locations regardless of whether an irrigation requirement from these cells exists or not, and (h) specified non-routed water transfers from an undefined source outside the model domain. All of these limitations are overcome in MF2005-FMP2. The new features include (a) simulation of transpiration uptake from variably saturated, fully saturated, or ponded root zones (for example, for crops like rice or riparian vegetation), (b) definition of on-farm efficiency not only by farm but also by crop, (c) simulation of water use and returnflow from non-irrigated vegetation (for example, rain-fed agriculture or native vegetation), (d) use of crop coefficients and reference evapotranspiration, (e) simulation of the delay between percolation from farms through the unsaturated zone and recharge into the uppermost active aquifer by linking FMP2 to the UZF Package, (f) an option to manually control the routing of returnflow from farm runoff to streams, (g) an option to limit pumping to wells located only in cells where an irrigation requirement exists, and (h) simulation of water transfers to farms from a series of well fields (for example, recovery well field of an aquifer-storage-and-recovery system, ASR). In addition to the output of an economic budget for each farm between irrigation demand and supply ('Farm Demand and Supply Budget' in FMP1), a new output option called 'Farm Budget' was created for FMP2, which allows the user to track all physical flows into and out of a water accounting unit at all times. Such a unit can represent individual farms, farming districts, natural areas, or urban areas. The example model demonstrates the application of MF2005-FMP2 with delayed recharge through an unsaturated zone, rejected infiltration in a riparian area, changes in de

Can biosecurity and local network properties predict pathogen species richness in the salmonid industry?

PubMed Central

More, Simon J.; Geoghegan, Fiona; McManus, Catherine; Hill, Ashley E.; Martínez-López, Beatriz

2018-01-01

Salmonid farming in Ireland is mostly organic, which implies limited disease treatment options. This highlights the importance of biosecurity for preventing the introduction and spread of infectious agents. Similarly, the effect of local network properties on infection spread processes has rarely been evaluated. In this paper, we characterized the biosecurity of salmonid farms in Ireland using a survey, and then developed a score for benchmarking the disease risk of salmonid farms. The usefulness and validity of this score, together with farm indegree (dichotomized as ≤ 1 or > 1), were assessed through generalized Poisson regression models, in which the modeled outcome was pathogen richness, defined here as the number of different diseases affecting a farm during a year. Seawater salmon (SW salmon) farms had the highest biosecurity scores with a median (interquartile range) of 82.3 (5.4), followed by freshwater salmon (FW salmon) with 75.2 (8.2), and freshwater trout (FW trout) farms with 74.8 (4.5). For FW salmon and trout farms, the top ranked model (in terms of leave-one-out information criteria, looic) was the null model (looic = 46.1). For SW salmon farms, the best ranking model was the full model with both predictors and their interaction (looic = 33.3). Farms with a higher biosecurity score were associated with lower pathogen richness, and farms with indegree > 1 (i.e. more than one fish supplier) were associated with increased pathogen richness. The effect of the interaction between these variables was also important, showing an antagonistic effect. This would indicate that biosecurity effectiveness is achieved through a broader perspective on the subject, which includes a minimization in the number of suppliers and hence in the possibilities for infection to enter a farm. The work presented here could be used to elaborate indicators of a farm’s disease risk based on its biosecurity score and indegree, to inform risk-based disease surveillance and control strategies for private and public stakeholders. PMID:29381760

Joint Offshore Wind Field Monitoring with Spaceborne SAR and Platform-Based Doppler LIDAR Measurements

NASA Astrophysics Data System (ADS)

Jacobsen, S.; Lehner, S.; Hieronimus, J.; Schneemann, J.; Kuhn, M.

2015-04-01

The increasing demand for renewable energy resources has promoted the construction of offshore wind farms e.g. in the North Sea. While the wind farm layout consists of an array of large turbines, the interrelation of wind turbine wakes with the remaining array is of substantial interest. The downstream spatial evolution of turbulent wind turbine wakes is very complex and depends on manifold parameters such as wind speed, wind direction and ambient atmospheric stability conditions. To complement and validate existing numerical models, corresponding observations are needed. While in-situ measurements with e.g. anemometers provide a time-series at the given location, the merits of ground-based and space- or airborne remote sensing techniques are indisputable in terms of spatial coverage. Active microwave devices, such as Scatterometer and Synthetic Aperture Radar (SAR), have proven their capabilities of providing sea surface wind measurements and particularly SAR images reveal wind variations at a high spatial resolution while retaining the large coverage area. Platform-based Doppler LiDAR can resolve wind fields with a high spatial coverage and repetition rates of seconds to minutes. In order to study the capabilities of both methods for the investigation of small scale wind field structures, we present a direct comparison of observations obtained by high resolution TerraSAR-X (TS-X) X-band SAR data and platform-based LiDAR devices at the North Sea wind farm alpha ventus. We furthermore compare the results with meteorological data from the COSMO-DE model run by the German Weather Service DWD. Our study indicates that the overall agreement between SAR and LiDAR wind fields is good and that under appropriate conditions small scale wind field variations compare significantly well.

Land Use Change on Coffee Farms in Southern Guatemala and its Environmental Consequences

NASA Astrophysics Data System (ADS)

Haggar, Jeremy; Medina, Byron; Aguilar, Rosa Maria; Munoz, Claudia

2013-04-01

Changes in commodity prices, such as the fall in coffee prices from 2000 to 2004, affect land use decisions on farms, and the environmental services they provide. A survey of 50 farms showed a 35 % loss in the area under coffee between 2000 and 2004 below 700 m with the majority of this area (64 %) being coffee agroforest systems that included native forest species. Loss of coffee only occurred on large and medium-scale farms; there was no change in area on cooperatives. Coffee productivity declined below 1,100 m altitude for sun and Inga shade coffee, but only below 700 m altitude for agroforest coffee. Coffee productivity was 37-53 % lower under agroforests than other systems. Increases in rubber and pasture were related to low altitude large-scale farms, and bananas and timber plantations to mid-altitude farms. Average aboveground carbon stocks for coffee agroforests of 39 t C ha-1 was similar to rubber plantations, but one-third to one half that of natural forest and timber plantations, respectively. Coffee agroforests had the highest native tree diversity of the productive systems (7-12 species ha-1) but lower than natural forest (31 species ha-1). Conversion of coffee agroforest to other land uses always led to a reduction in the quality of habitat for native biodiversity, especially avian, but was concentrated among certain farm types. Sustaining coffee agroforests for biodiversity conservation would require targeted interventions such as direct payments or market incentives specifically for biodiversity.

Land use change on coffee farms in southern Guatemala and its environmental consequences.

PubMed

Haggar, Jeremy; Medina, Byron; Aguilar, Rosa Maria; Munoz, Claudia

2013-04-01

Changes in commodity prices, such as the fall in coffee prices from 2000 to 2004, affect land use decisions on farms, and the environmental services they provide. A survey of 50 farms showed a 35% loss in the area under coffee between 2000 and 2004 below 700 m with the majority of this area (64 %) being coffee agroforest systems that included native forest species. Loss of coffee only occurred on large and medium-scale farms; there was no change in area on cooperatives. Coffee productivity declined below 1,100 m altitude for sun and Inga shade coffee, but only below 700 m altitude for agroforest coffee. Coffee productivity was 37-53% lower under agroforests than other systems. Increases in rubber and pasture were related to low altitude large-scale farms, and bananas and timber plantations to mid-altitude farms. Average aboveground carbon stocks for coffee agroforests of 39 t C ha(-1) was similar to rubber plantations, but one-third to one half that of natural forest and timber plantations, respectively. Coffee agroforests had the highest native tree diversity of the productive systems (7-12 species ha(-1)) but lower than natural forest (31 species ha(-1)). Conversion of coffee agroforest to other land uses always led to a reduction in the quality of habitat for native biodiversity, especially avian, but was concentrated among certain farm types. Sustaining coffee agroforests for biodiversity conservation would require targeted interventions such as direct payments or market incentives specifically for biodiversity.

LandCaRe DSS--an interactive decision support system for climate change impact assessment and the analysis of potential agricultural land use adaptation strategies.

PubMed

Wenkel, Karl-Otto; Berg, Michael; Mirschel, Wilfried; Wieland, Ralf; Nendel, Claas; Köstner, Barbara

2013-09-01

Decision support to develop viable climate change adaptation strategies for agriculture and regional land use management encompasses a wide range of options and issues. Up to now, only a few suitable tools and methods have existed for farmers and regional stakeholders that support the process of decision-making in this field. The interactive model-based spatial information and decision support system LandCaRe DSS attempts to close the existing methodical gap. This system supports interactive spatial scenario simulations, multi-ensemble and multi-model simulations at the regional scale, as well as the complex impact assessment of potential land use adaptation strategies at the local scale. The system is connected to a local geo-database and via the internet to a climate data server. LandCaRe DSS uses a multitude of scale-specific ecological impact models, which are linked in various ways. At the local scale (farm scale), biophysical models are directly coupled with a farm economy calculator. New or alternative simulation models can easily be added, thanks to the innovative architecture and design of the DSS. Scenario simulations can be conducted with a reasonable amount of effort. The interactive LandCaRe DSS prototype also offers a variety of data analysis and visualisation tools, a help system for users and a farmer information system for climate adaptation in agriculture. This paper presents the theoretical background, the conceptual framework, and the structure and methodology behind LandCaRe DSS. Scenario studies at the regional and local scale for the two Eastern German regions of Uckermark (dry lowlands, 2600 km(2)) and Weißeritz (humid mountain area, 400 km(2)) were conducted in close cooperation with stakeholders to test the functionality of the DSS prototype. The system is gradually being transformed into a web version (http://www.landcare-dss.de) to ensure the broadest possible distribution of LandCaRe DSS to the public. The system will be continuously developed, updated and used in different research projects and as a learning and knowledge-sharing tool for students. The main objective of LandCaRe DSS is to provide information on the complex long-term impacts of climate change and on potential management options for adaptation by answering "what-if" type questions. Copyright © 2013 Elsevier Ltd. All rights reserved.

Evaluating use of cattle winter feeding areas by elk and white-tailed deer: implications for managing bovine tuberculosis transmission risk from the ground up.

PubMed

Brook, Ryan K; Wal, Eric Vander; van Beest, Floris M; McLachlan, Stéphane M

2013-02-01

Transmission of bovine tuberculosis (Mycobacterium bovis) among wildlife and livestock has created important risks for conservation and agriculture. Management strategies aimed at controlling TB have typically been top-down, regionally focused, and government-led programs that were at best only partially successful. The purpose of this study was to quantify co-mingling of elk and white-tailed deer (WTD) with cattle at multiple spatial scales (i.e., the regional farm scale and winter cattle feeding area patch) in southwestern Manitoba, Canada, to assess the potential for bovine tuberculosis transmission and identify alternative management strategies. For each spatial scale we quantified use of cattle farms by elk and white-tailed deer. We mailed questionnaires to rural households and then conducted personal interviews with 86 cattle farmers to map the spatial distribution of their cattle winter feeding areas at a fine scale. We deployed Global Positioning System (GPS) collars on 48 wild elk and 16 wild white-tailed deer from 2003 to 2011. Elk were observed on farms by 66% of cattle producers, including 5% and 20% who observed direct and indirect contact, respectively, between elk and cattle. Cattle producers consistently (≈100%) observed white-tailed deer on their farms, including 11% and 47% whom observed direct and indirect contact, respectively, between white-tailed deer and cattle. A higher probability of white-tailed deer-cattle contact at the regional scale occurs on farms that (1) left crop residues specifically for wildlife, (2) had larger cattle herds, (3) used round bale feeders, and (4) were farther away from protected areas. None of the GPS-collared elk locations overlapped with cattle winter feeding areas. In contrast, 21% of GPS-collared white-tailed deer locations overlapped with winter cattle winter feeding areas (22% of these were from male WTD and 78% were from female WTD). White-tailed deer selected cattle winter feeding areas with higher (1) forage crop, (2) grassland/rangeland, and (3) forest cover around the cattle feeding area. Farmers overall expressed strongly negative attitudes toward eradicating the elk population or fencing the park to eradicate TB, but were generally supportive of less invasive and farm-based approaches. Our results suggested that management efforts to prevent TB transmission at the wildlife-agriculture interface can be effectively implemented using a 'bottom-up' approach that focuses on practical, farm-based mitigation strategies. This approach can be implemented by individual farm operators, is relatively low cost, and is generally well supported by farmers relative to other more extreme and controversial measures like wildlife eradication. Copyright © 2012. Published by Elsevier B.V.

Integrated Farm System Model Version 4.1 and Dairy Gas Emissions Model Version 3.1 software release and distribution

USDA-ARS?s Scientific Manuscript database

Animal facilities are significant contributors of gaseous emissions including ammonia (NH3) and nitrous oxide (N2O). Previous versions of the Integrated Farm System Model (IFSM version 4.0) and Dairy Gas Emissions Model (DairyGEM version 3.0), two whole-farm simulation models developed by USDA-ARS, ...

Relationship of trade patterns of the Danish swine industry animal movements network to potential disease spread.

PubMed

Bigras-Poulin, Michel; Barfod, Kristen; Mortensen, Sten; Greiner, Matthias

2007-07-16

The movements of animals were analysed under the conceptual framework of graph theory in mathematics. The swine production related premises of Denmark were considered to constitute the nodes of a network and the links were the animal movements. In this framework, each farm will have a network of other premises to which it will be linked. A premise was a farm (breeding, rearing or slaughter pig), an abattoir or a trade market. The overall network was divided in premise specific subnets that linked the other premises from and to which animals were moved. This approach allowed us to visualise and analyse the three levels of organization related to animal movements that existed in the Danish swine production registers: the movement of animals between two premises, the premise specific networks, and the industry network. The analyses of animal movements were done using these three levels of organisation. The movements of swine were studied for the period September 30, 2002 to May 22, 2003. For daily movements of swine between two slaughter pig premises, the median number of pigs moved was 130 pigs with a maximum of 3306. For movements between a slaughter pig premise and an abattoir, the median number of pigs was 24. The largest percentage of movements was from farm to abattoir (82.5%); the median number of pigs per movement was 24 and the maximum number was 2018. For the whole period the median and maximum Euclidean distances observed in farm-to-farm movements were 22 km and 289 km respectively, while in the farm-to-abattoir movements, they were 36.2 km and 285 km. The network related to one specific premise showed that the median number of premises was mainly away from slaughter pig farms (3) or breeder farms (26) and mainly to an abattoir (1535). The assumption that animal movements can be randomly generated on the basis of farm density of the surrounding area of any farm is not correct since the patterns of animal movements have the topology of a scale-free network with a large degree of heterogeneity. This supported the opinion that the disease spread software assuming homogeneity in farm-to-farm relationship should only be used for large-scale interpretation and for epidemic preparedness. The network approach, based on graph theory, can be used efficiently to express more precisely, on a local scale (premise), the heterogeneity of animal movements. This approach, by providing network knowledge to the local veterinarian in charge of controlling disease spread, should also be evaluated as a potential tool to manage epidemics during the crisis. Geographic information systems could also be linked in the approach to produce knowledge about local transmission of disease.

Organic farming enhances soil microbial abundance and activity—A meta-analysis and meta-regression

PubMed Central

Symnaczik, Sarah; Mäder, Paul; De Deyn, Gerlinde; Gattinger, Andreas

2017-01-01

Population growth and climate change challenge our food and farming systems and provide arguments for an increased intensification of agriculture. A promising option is eco-functional intensification through organic farming, an approach based on using and enhancing internal natural resources and processes to secure and improve agricultural productivity, while minimizing negative environmental impacts. In this concept an active soil microbiota plays an important role for various soil based ecosystem services such as nutrient cycling, erosion control and pest and disease regulation. Several studies have reported a positive effect of organic farming on soil health and quality including microbial community traits. However, so far no systematic quantification of whether organic farming systems comprise larger and more active soil microbial communities compared to conventional farming systems was performed on a global scale. Therefore, we conducted a meta-analysis on current literature to quantify possible differences in key indicators for soil microbial abundance and activity in organic and conventional cropping systems. All together we integrated data from 56 mainly peer-reviewed papers into our analysis, including 149 pairwise comparisons originating from different climatic zones and experimental duration ranging from 3 to more than 100 years. Overall, we found that organic systems had 32% to 84% greater microbial biomass carbon, microbial biomass nitrogen, total phospholipid fatty-acids, and dehydrogenase, urease and protease activities than conventional systems. Exclusively the metabolic quotient as an indicator for stresses on microbial communities remained unaffected by the farming systems. Categorical subgroup analysis revealed that crop rotation, the inclusion of legumes in the crop rotation and organic inputs are important farming practices affecting soil microbial community size and activity. Furthermore, we show that differences in microbial size and activity between organic and conventional farming systems vary as a function of land use (arable, orchards, and grassland), plant life cycle (annual and perennial) and climatic zone. In summary, this study shows that overall organic farming enhances total microbial abundance and activity in agricultural soils on a global scale. PMID:28700609

Assessing Impacts of Climate Change on Food Security Worldwide

NASA Technical Reports Server (NTRS)

Rosenzweig, Cynthia E.; Antle, John; Elliott, Joshua

2015-01-01

The combination of a warming Earth and an increasing population will likely strain the world's food systems in the coming decades. Experts involved with the Agricultural Model Intercomparison and Improvement Project (AgMIP) focus on quantifying the changes through time. AgMIP, a program begun in 2010, involves about 800 climate scientists, economists, nutritionists, information technology specialists, and crop and livestock experts. In mid-September 2015, the Aspen Global Change Institute convened an AgMIP workshop to draft plans and protocols for assessing global- and regional-scale modeling of crops, livestock, economics, and nutrition across major agricultural regions worldwide. The goal of this Coordinated Global and Regional Integrated Assessments (CGRA) project is to characterize climate effects on large- and small-scale farming systems.

Spatial Pattern Classification for More Accurate Forecasting of Variable Energy Resources

NASA Astrophysics Data System (ADS)

Novakovskaia, E.; Hayes, C.; Collier, C.

2014-12-01

The accuracy of solar and wind forecasts is becoming increasingly essential as grid operators continue to integrate additional renewable generation onto the electric grid. Forecast errors affect rate payers, grid operators, wind and solar plant maintenance crews and energy traders through increases in prices, project down time or lost revenue. While extensive and beneficial efforts were undertaken in recent years to improve physical weather models for a broad spectrum of applications these improvements have generally not been sufficient to meet the accuracy demands of system planners. For renewables, these models are often used in conjunction with additional statistical models utilizing both meteorological observations and the power generation data. Forecast accuracy can be dependent on specific weather regimes for a given location. To account for these dependencies it is important that parameterizations used in statistical models change as the regime changes. An automated tool, based on an artificial neural network model, has been developed to identify different weather regimes as they impact power output forecast accuracy at wind or solar farms. In this study, improvements in forecast accuracy were analyzed for varying time horizons for wind farms and utility-scale PV plants located in different geographical regions.

Facilitating smallholder tree farming in fragmented tropical landscapes: Challenges and potentials for sustainable land management.

PubMed

Rahman, Syed Ajijur; Sunderland, Terry; Roshetko, James M; Healey, John Robert

2017-08-01

Under changing land use in tropical Asia, there is evidence of forest product diversification through implementation of tree-based farming by smallholders. This paper assesses in two locations, West Java, Indonesia and eastern Bangladesh, current land use conditions from the perspective of smallholder farmers, the factors that facilitate their adoption of tree farming, and the potential of landscape-scale approaches to foster sustainable land management. Data were collected through rapid rural appraisals, focus group discussions, field observations, semi-structured interviews of farm households and key informant interviews of state agricultural officers. Land at both study sites is typically fragmented due to conversion of forest to agriculture and community settlement. Local land use challenges are associated with pressures of population increase, poverty, deforestation, shortage of forest products, lack of community-scale management, weak tenure, underdeveloped markets, government decision-making with insufficient involvement of local people, and poor extension services. Despite these challenges, smallholder tree farming is found to be successful from farmers' perspectives. However, constraints of local food crop cultivation traditions, insecure land tenure, lack of capital, lack of knowledge, lack of technical assistance, and perceived risk of investing in land due to local conflict (in Bangladesh) limit farmers' willingness to adopt this land use alternative. Overcoming these barriers to adoption will require management at a landscape scale, including elements of both segregation and integration of land uses, supported by competent government policies and local communities having sufficiently high social capital. Copyright © 2017 Elsevier Ltd. All rights reserved.

Development of FAST.Farm: A New Multiphysics Engineering Tool for Wind Farm Design and Analysis: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jonkman, Jason; Annoni, Jennifer; Hayman, Greg

2017-01-01

This paper presents the development of FAST.Farm, a new multiphysics tool applicable to engineering problems in research and industry involving wind farm performance and cost optimization that is needed to address the current underperformance, failures, and expenses plaguing the wind industry. Achieving wind cost-of-energy targets - which requires improvements in wind farm performance and reliability, together with reduced uncertainty and expenditures - has been eluded by the complicated nature of the wind farm design problem, especially the sophisticated interaction between atmospheric phenomena and wake dynamics and array effects. FAST.Farm aims to balance the need for accurate modeling of the relevantmore » physics for predicting power performance and loads while maintaining low computational cost to support a highly iterative and probabilistic design process and system-wide optimization. FAST.Farm makes use of FAST to model the aero-hydro-servo-elastics of distinct turbines in the wind farm, and it is based on some of the principles of the Dynamic Wake Meandering (DWM) model, but avoids many of the limitations of existing DWM implementations.« less

On-farm soil health evaluations: Challenges and opportunities

USDA-ARS?s Scientific Manuscript database

Interest in soil health (or soil quality) by producers, conservationists, environmentalists, agricultural scientists, policy makers and many other groups has increased exponentially during the past five years. Yet the question remains: Can soil health be measured at the field or farm scale and can t...

Certified safe farm: identifying and removing hazards on the farm.

PubMed

Rautiainen, R H; Grafft, L J; Kline, A K; Madsen, M D; Lange, J L; Donham, K J

2010-04-01

This article describes the development of the Certified Safe Farm (CSF) on-farm safety review tools, characterizes the safety improvements among participating farms during the study period, and evaluates differences in background variables between low and high scoring farms. Average farm review scores on 185 study farms improved from 82 to 96 during the five-year study (0-100 scale, 85 required for CSF certification). A total of 1292 safety improvements were reported at an estimated cost of $650 per farm. A wide range of improvements were made, including adding 9 rollover protective structures (ROPS), 59 power take-off (PTO) master shields, and 207 slow-moving vehicle (SMV) emblems; improving lighting on 72 machines: placing 171 warning decals on machinery; shielding 77 moving parts; locking up 17 chemical storage areas, adding 83 lockout/tagout improvements; and making general housekeeping upgrades in 62 farm buildings. The local, trained farm reviewers and the CSF review process overall were well received by participating farmers. In addition to our earlier findings where higher farm review scores were associated with lower self-reported health outcome costs, we found that those with higher farm work hours, younger age, pork production in confinement, beef production, poultry production, and reported exposure to agrichemicals had higher farm review scores than those who did not have these characteristics. Overall, the farm review process functioned as expected. encouraging physical improvements in the farm environment, and contributing to the multi-faceted CSF intervention program.

Nutrition mediates the expression of cultivar-farmer conflict in a fungus-growing ant.

PubMed

Shik, Jonathan Z; Gomez, Ernesto B; Kooij, Pepijn W; Santos, Juan C; Wcislo, William T; Boomsma, Jacobus J

2016-09-06

Attine ants evolved farming 55-60 My before humans. Although evolutionarily derived leafcutter ants achieved industrial-scale farming, extant species from basal attine genera continue to farm loosely domesticated fungal cultivars capable of pursuing independent reproductive interests. We used feeding experiments with the basal attine Mycocepurus smithii to test whether reproductive allocation conflicts between farmers and cultivars constrain crop yield, possibly explaining why their mutualism has remained limited in scale and productivity. Stoichiometric and geometric framework approaches showed that carbohydrate-rich substrates maximize growth of both edible hyphae and inedible mushrooms, but that modest protein provisioning can suppress mushroom formation. Worker foraging was consistent with maximizing long-term cultivar performance: ant farmers could neither increase carbohydrate provisioning without cultivars allocating the excess toward mushroom production, nor increase protein provisioning without compromising somatic cultivar growth. Our results confirm that phylogenetically basal attine farming has been very successful over evolutionary time, but that unresolved host-symbiont conflict may have precluded these wild-type symbioses from rising to ecological dominance. That status was achieved by the evolutionarily derived leafcutter ants following full domestication of a coevolving cultivar 30-35 Mya after the first attine ants committed to farming.

Nutrition mediates the expression of cultivar–farmer conflict in a fungus-growing ant

PubMed Central

Shik, Jonathan Z.; Gomez, Ernesto B.; Kooij, Pepijn W.; Santos, Juan C.; Wcislo, William T.; Boomsma, Jacobus J.

2016-01-01

Attine ants evolved farming 55–60 My before humans. Although evolutionarily derived leafcutter ants achieved industrial-scale farming, extant species from basal attine genera continue to farm loosely domesticated fungal cultivars capable of pursuing independent reproductive interests. We used feeding experiments with the basal attine Mycocepurus smithii to test whether reproductive allocation conflicts between farmers and cultivars constrain crop yield, possibly explaining why their mutualism has remained limited in scale and productivity. Stoichiometric and geometric framework approaches showed that carbohydrate-rich substrates maximize growth of both edible hyphae and inedible mushrooms, but that modest protein provisioning can suppress mushroom formation. Worker foraging was consistent with maximizing long-term cultivar performance: ant farmers could neither increase carbohydrate provisioning without cultivars allocating the excess toward mushroom production, nor increase protein provisioning without compromising somatic cultivar growth. Our results confirm that phylogenetically basal attine farming has been very successful over evolutionary time, but that unresolved host–symbiont conflict may have precluded these wild-type symbioses from rising to ecological dominance. That status was achieved by the evolutionarily derived leafcutter ants following full domestication of a coevolving cultivar 30–35 Mya after the first attine ants committed to farming. PMID:27551065

Brazilian Soybean Production: Emergy Analysis with an Expanded Scope

ERIC Educational Resources Information Center

Ortega, Enrique; Cavalett, Otavio; Bonifacio, Robert; Watanabe, Marcos

2005-01-01

This article offers the results of emergy analysis used to evaluate four different soybean production systems in Brazil that were divided into two main categories: biological models (organic and ecological farms) and industrial models (green-revolution chemical farms and herbicide with no-tillage farms). The biological models show better…

Volume sharing of reservoir water

NASA Astrophysics Data System (ADS)

Dudley, Norman J.

1988-05-01

Previous models optimize short-, intermediate-, and long-run irrigation decision making in a simplified river valley system characterized by highly variable water supplies and demands for a single decision maker controlling both reservoir releases and farm water use. A major problem in relaxing the assumption of one decision maker is communicating the stochastic nature of supplies and demands between reservoir and farm managers. In this paper, an optimizing model is used to develop release rules for reservoir management when all users share equally in releases, and computer simulation is used to generate an historical time sequence of announced releases. These announced releases become a state variable in a farm management model which optimizes farm area-to-irrigate decisions through time. Such modeling envisages the use of growing area climatic data by the reservoir authority to gauge water demand and the transfer of water supply data from reservoir to farm managers via computer data files. Alternative model forms, including allocating water on a priority basis, are discussed briefly. Results show lower mean aggregate farm income and lower variance of aggregate farm income than in the single decision-maker case. This short-run economic efficiency loss coupled with likely long-run economic efficiency losses due to the attenuated nature of property rights indicates the need for quite different ways of integrating reservoir and farm management.

Diversification and intensification of agricultural adaptation from global to local scales.

PubMed

Chen, Minjie; Wichmann, Bruno; Luckert, Marty; Winowiecki, Leigh; Förch, Wiebke; Läderach, Peter

2018-01-01

Smallholder farming systems are vulnerable to a number of challenges, including continued population growth, urbanization, income disparities, land degradation, decreasing farm size and productivity, all of which are compounded by uncertainty of climatic patterns. Understanding determinants of smallholder farming practices is critical for designing and implementing successful interventions, including climate change adaptation programs. We examine two dimensions wherein smallholder farmers may adapt agricultural practices; through intensification (i.e., adopt more practices) or diversification (i.e. adopt different practices). We use data on 5314 randomly sampled households located in 38 sites in 15 countries across four regions (East and West Africa, South Asia, and Central America). We estimate empirical models designed to assess determinants of both intensification and diversification of adaptation activities at global scales. Aspects of adaptive capacity that are found to increase intensification of adaptation globally include variables associated with access to information and human capital, financial considerations, assets, household infrastructure and experience. In contrast, there are few global drivers of adaptive diversification, with a notable exception being access to weather information, which also increases adaptive intensification. Investigating reasons for adaptation indicate that conditions present in underdeveloped markets provide the primary impetus for adaptation, even in the context of climate change. We also compare determinants across spatial scales, which reveals a variety of local avenues through which policy interventions can relax economic constraints and boost agricultural adaptation for both intensification and diversification. For example, access to weather information does not affect intensification adaptation in Africa, but is significant at several sites in Bangladesh and India. Moreover, this information leads to diversification of adaptive activities on some sites in South Asia and Central America, but increases specialization in West and East Africa.

Diversification and intensification of agricultural adaptation from global to local scales

PubMed Central

Chen, Minjie; Wichmann, Bruno; Luckert, Marty; Winowiecki, Leigh; Förch, Wiebke

2018-01-01

Smallholder farming systems are vulnerable to a number of challenges, including continued population growth, urbanization, income disparities, land degradation, decreasing farm size and productivity, all of which are compounded by uncertainty of climatic patterns. Understanding determinants of smallholder farming practices is critical for designing and implementing successful interventions, including climate change adaptation programs. We examine two dimensions wherein smallholder farmers may adapt agricultural practices; through intensification (i.e., adopt more practices) or diversification (i.e. adopt different practices). We use data on 5314 randomly sampled households located in 38 sites in 15 countries across four regions (East and West Africa, South Asia, and Central America). We estimate empirical models designed to assess determinants of both intensification and diversification of adaptation activities at global scales. Aspects of adaptive capacity that are found to increase intensification of adaptation globally include variables associated with access to information and human capital, financial considerations, assets, household infrastructure and experience. In contrast, there are few global drivers of adaptive diversification, with a notable exception being access to weather information, which also increases adaptive intensification. Investigating reasons for adaptation indicate that conditions present in underdeveloped markets provide the primary impetus for adaptation, even in the context of climate change. We also compare determinants across spatial scales, which reveals a variety of local avenues through which policy interventions can relax economic constraints and boost agricultural adaptation for both intensification and diversification. For example, access to weather information does not affect intensification adaptation in Africa, but is significant at several sites in Bangladesh and India. Moreover, this information leads to diversification of adaptive activities on some sites in South Asia and Central America, but increases specialization in West and East Africa. PMID:29727457

Green Care Farms as Innovative Nursing Homes, Promoting Activities and Social Interaction for People With Dementia.

PubMed

de Boer, Bram; Hamers, Jan P H; Zwakhalen, Sandra M G; Tan, Frans E S; Beerens, Hanneke C; Verbeek, Hilde

2017-01-01

Innovative care environments are developed for people with dementia to encourage person-centered care. This study aims to investigate whether residents of green care farms that provide 24-hour nursing care participate more in (physical) activities and social interaction compared with residents of other nursing homes. Longitudinal observation study. Nursing homes in the Netherlands (green care farms, traditional nursing homes, and regular small-scale living facilities). A total of 115 nursing home residents at baseline, 100 at follow-up. Ecological momentary assessments (n = 16,860) were conducted using the Maastricht Electronic Daily Life Observation Tool. Residents living at green care farms were compared with residents living in traditional nursing homes and regular small-scale living facilities. The following aspects were collected for this study: the activity performed by the participant or occurring in his or her vicinity, the engagement in the activity, the level of physical activity during the activity, the physical environment (location where the activity occurred), and the level of social interaction during the activity. In total, 9660 baseline observations and 7200 follow-up observations were conducted. Analyses showed that residents of green care farms significantly more often participated in domestic activities (P = .004, SE = 1.6) and outdoor/nature-related activities (P = .003, SE = 0.9), and significantly less often engaged in passive/purposeless activities (P < .001, SE = 1.7) compared with residents of traditional nursing homes. Furthermore, residents of green care farms had significantly more active engagement (P = .014, SE = 0.9), more social interaction (P = .006, SE = 1.1), and came outside significantly more (P = .010, SE = 1.1) than residents of traditional nursing homes. Residents of green care farms were significantly more physically active (P = .013, SE = 0.8) than were residents of regular small-scale living facilities. No other significant differences were found. Green care farms can be a valuable alternative to traditional nursing homes. They provide an attractive, homelike environment and activities that positively influence engagement and social interaction. Research is needed to study how successful elements of green care farms can be implemented in existing nursing homes. Copyright © 2016 AMDA – The Society for Post-Acute and Long-Term Care Medicine. Published by Elsevier Inc. All rights reserved.

Trade-offs between pasture production and farmland bird conservation: exploration of options using a dynamic farm model.

PubMed

Sabatier, R; Teillard, F; Rossing, W A H; Doyen, L; Tichit, M

2015-05-01

In European grassland landscapes, grazing and mowing play a key role for the maintenance of high-quality habitats that host important bird populations. As grasslands are also key resources for cattle feeding, there is a need to develop management strategies that achieve the double objective of production and biodiversity conservation. The objective of this study was to use a modelling approach to generate recognisable patterns of bird dynamics in farms composed of different land use proportions, and to compare their production and ecological dimensions. We developed a dynamic model, which linked grassland management to bird population dynamics at the field and farm levels. The model was parameterised for two types of suckling farms corresponding to contrasting levels of grassland intensification and for two bird species of high conservation value. A viability algorithm was used to define and assess viable management strategies for production and ecological performance so as to draw the shape of the relationship between both types of performances for the two types of farms. Our results indicated that, at the farm level, there was a farming system effect with a negative and non-linear relationship linking performance. Improving bird population maintenance was less costly in extensive farms compared with intensive farms. At the field level, the model predicted the timing and intensity of land use, maximising either production or ecological performance. The results suggested that multi-objective grassland management would benefit from public policies that consider levels of organisation higher than the field level, such as the farm or the landscape.

Using agricultural practices information for multiscale environmental assessment of phosphorus risk

NASA Astrophysics Data System (ADS)

Matos Moreira, Mariana; Lemercier, Blandine; Michot, Didier; Dupas, Rémi; Gascuel-Odoux, Chantal

2015-04-01

Phosphorus (P) is an essential nutrient for plant growth. In intensively farmed areas, excessive applications of animal manure and mineral P fertilizers to soils have raised both economic and ecological concerns. P accumulation in agricultural soils leads to increased P losses to surface waterbodies contributing to eutrophication. Increasing soil P content over time in agricultural soils is often correlated with agricultural practices; in Brittany (NW France), an intensive livestock farming region, soil P content is well correlated with animal density (Lemercier et al.,2008). Thus, a better understanding of the factors controlling P distribution is required to enable environmental assessment of P risk. The aim of this study was to understand spatial distribution of extractable (Olsen method) and total P contents and its controlling factors at the catchment scale in order to predict P contents at regional scale (Brittany). Data on soil morphology, soil tests (including P status, particles size, organic carbon…) for 198 punctual positions, crops succession since 20 years, agricultural systems, field and animal manure management were obtained on a well-characterized catchment (ORE Agrhys, 10 km²). A multivariate analysis with mixed quantitative variables and factors and a digital soil mapping approach were performed to identify variables playing a significant role in soil total and extractable P contents and distribution. Spatial analysis was performed by means of the Cubist model, a decision tree-based algorithm. Different scenarios were assessed, considering various panels of predictive variables: soil data, terrain attributes derived from digital elevation model, gamma-ray spectrometry (from airborne geophysical survey) and agricultural practices information. In the research catchment, mean extractable and total P content were 140.0 ± 63.4 mg/kg and 2862.7 ± 773.0 mg/kg, respectively. Organic and mineral P inputs, P balance, soil pH, and Al contents were positively correlated with soil P contents. Also land use, crop rotation and livestock production system influenced P contents. The highest mean values of P were found in croplands and close to pig farms. The lowest mean values of P were found in pastures and nearby dairy farms. The spatial analysis showed that sand content, geophysical parameters and P input by organic fertilization were the most significant variables for the linear predictive model of extractable P contents. For total P, geophysical parameters and P balance had the highest importance for the respective linear predictive model. This study revealed that agricultural practices information plays a significant role in soil P distribution. Once controlling factors of P spatial distribution were identified, relationships could be extrapolated at regional scale using the National Soil Test Database providing information on extractable P content and available information on agricultural practices in order to improve predictions of total P content at regional scale. Lemercier B., Gaudin, L., Walter C., Aurousseau P., Arrouays D., Schvartz C., Saby N., Follain S., Abrassart J., 2008. Soil phosphorus monitoring at the regional level by means of a soil test database. Soil Use and Management, 24, 131-138.

Poultry Farm Vulnerability and Risk of Avian Influenza Re-Emergence in Thailand

PubMed Central

Souris, Marc; Selenic, Dubravka; Khaklang, Supaluk; Ninphanomchai, Suwannapa; Minet, Guy; Gonzalez, Jean-Paul; Kittayapong, Pattamaporn

2014-01-01

Highly pathogenic avian influenza (HPAI) remains of concern as a major potential global threat. This article evaluates and discusses the level of vulnerability of medium and small-scale commercial poultry production systems in Thailand related to avian influenza virus re-emergence. We developed a survey on 173 farms in Nakhon Pathom province to identify the global level of vulnerability of farms, and to determine which type of farms appears to be more vulnerable. We used official regulations (the Good Agricultural Practices and Livestock Farm Standards regulations) as a reference to check whether these regulations are respected. The results show that numerous vulnerability factors subsist and could represent, in case of HPAI re-emergence, a significant risk for a large spread of the disease. Bio-security, farm management and agro-commercial practices are particularly significant on that matter: results show that these practices still need a thorough improvement on a majority of farms. Farms producing eggs (especially duck eggs) are more vulnerable than farms producing meat. Those results are consistent with the type of farms that were mostly affected during the 2004–2008 outbreaks in Thailand. PMID:24413705

Social capital on poultry farms in South Sulawesi, Indonesia

NASA Astrophysics Data System (ADS)

Sri Lestari, V.; Natsir; Patrick, I. W.; Ali, H. M.; Asya, M.; Sirajuddin, S. N.

2018-05-01

Social capital plays an important role in the development of poultry farms in South Sulawesi. Poultry farms consisted of laying hen and broiler farms. Most of laying hen farms were located in Sidrap Regency, while broiler farms were located in Maros regency. The aim of this research was to know social capital on beef cattle farms in South Sulawesi. Population of this research was 120 farmers which consisted of 6o were laying hen farmers and 60 were broiler farmers. Variable of social capital was mutual trust, reciprocity, shared norms and linkage. The data were collected from observation and depth interview by using questionnaire. There were 10 questions. The answer was scored by using Likert scale ranging from 1 refer to strongly agree; 2 refer to agree; 3 refer to not sure; 4 refer to disagree and 5 refer to strongly disagree. The data were analyzed descriptively using frequency distribution. The research revealed that mutual trust and shared norms members of the group in broiler farms have higher level than that on laying hen farms, on the other hand, linkage or net working members of the group among laying hen farmers has higher level than that on broiler farms.

Spatial modeling of personalized exposure dynamics: the case of pesticide use in small-scale agricultural production landscapes of the developing world.

PubMed

Leyk, Stefan; Binder, Claudia R; Nuckols, John R

2009-03-30

Pesticide poisoning is a global health issue with the largest impacts in the developing countries where residential and small-scale agricultural areas are often integrated and pesticides sprayed manually. To reduce health risks from pesticide exposure approaches for personalized exposure assessment (PEA) are needed. We present a conceptual framework to develop a spatial individual-based model (IBM) prototype for assessing potential exposure of farm-workers conducting small-scale agricultural production, which accounts for a considerable portion of global food crop production. Our approach accounts for dynamics in the contaminant distributions in the environment, as well as patterns of movement and activities performed on an individual level under different safety scenarios. We demonstrate a first prototype using data from a study area in a rural part of Colombia, South America. Different safety scenarios of PEA were run by including weighting schemes for activities performed under different safety conditions. We examined the sensitivity of individual exposure estimates to varying patterns of pesticide application and varying individual patterns of movement. This resulted in a considerable variation in estimates of magnitude, frequency and duration of exposure over the model runs for each individual as well as between individuals. These findings indicate the influence of patterns of pesticide application, individual spatial patterns of movement as well as safety conditions on personalized exposure in the agricultural production landscape that is the focus of our research. This approach represents a conceptual framework for developing individual based models to carry out PEA in small-scale agricultural settings in the developing world based on individual patterns of movement, safety conditions, and dynamic contaminant distributions. The results of our analysis indicate our prototype model is sufficiently sensitive to differentiate and quantify the influence of individual patterns of movement and decision-based pesticide management activities on potential exposure. This approach represents a framework for further understanding the contribution of agricultural pesticide use to exposure in the small-scale agricultural production landscape of many developing countries, and could be useful to evaluate public health intervention strategies to reduce risks to farm-workers and their families. Further research is needed to fully develop an operational version of the model.

Agricultural interventions for water saving and crop yield improvement, in a Mediterranean area - an experimental design

NASA Astrophysics Data System (ADS)

Morianou, Giasemi; Kourgialas, Nektarios; Psarras, George; Koubouris, George; Arampatzis, George; Karatzas, George; Pavlidou, Elisavet

2017-04-01

This work is a part of LIFE+ AGROCLIMAWATER project and the aim is to improve the water efficiency, increase the adaptive capacity of tree corps and save water, in a Mediterranean area, under different climatic conditions and agricultural practices. The experimental design as well as preliminary results at farm and river basin scales are presented in this work. Specifically, ten (10) pilot farms, both organic and conventional ones have been selected in the sub-basin of Platanias in western Crete - Greece. These ten pilot farms were selected representing the most typical crops in Platanias area (olive trees and citrus trees), as well as the typical soil, landscape and agricultural practices differentiation for each crop (field slope, water availability, soil type, management regime). From the ten pilot farms, eight were olive farms and the rest two citrus. This proportion correspond adequacy to the presentence of olive and citrus crops in the extended area of Platanias prefecture. Each of the ten pilot farm has been divided in two parts, the first one will be used as a control part, while the other one as the demonstration part where the interventions will be applied. The action plans for each selected farm are based on the following groups of possible interventions: a) reduction of water evaporation losses from soil surface, b) reduction of transpiration water losses through winter pruning and summer pruning, c) reduction of deep percolation water and nutrient losses, d) reduction of surface runoff, e) measures in order to maximize the efficiency of irrigation and f) rationalization of fertilizers and agrochemicals utilized. Preliminary results indicate that water saving and crop yield can be significantly improved based on the above innervations both at farm and river basin scale.

Cold chain food distribution from the Driftless Area : keys to attaining self-reliance in the circle city.

DOT National Transportation Integrated Search

2014-05-01

In recent years, small- to mid-scale farms have increasingly emphasized the importance of branding and establishing : the appropriate identity to enter the value-added market. Farms in the Driftless Area (mostly Southwest Wisconsin) are : slowly deve...

Adapting Certified Safe Farm to North Carolina Agriculture: An Implementation Study.

PubMed

Storm, Julia F; LePrevost, Catherine E; Tutor-Marcom, Robin; Cope, W Gregory

2016-01-01

Certified Safe Farm (CSF) is a multimodal safety and health program developed and assessed through multiple controlled intervention studies in Iowa. Although developed with the intent to be broadly applicable to agriculture, CSF has not been widely implemented outside the midwestern United States. This article describes the CSF implementation process in North Carolina (NC), as piloted on a large-scale in three agriculturally diverse and productive counties of NC, and reports its effectiveness using the Reach Effectiveness Adoption Implementation Maintenance (RE-AIM) framework. Implementation involved (1) capacity building through safety and health training, (2) adaptation of components of Iowa's CSF model to NC agriculture, (3) marketing and recruitment, and (4) formative evaluation, including an online survey and focus group discussion. From 2009 to 2012, 113 farms participated in at least one component of the CSF intervention, representing a NC farm participation rate of 3.1% in the study area. A major adaptation of NC implementation was the utilization of NC Cooperative Extension as the local driver of implementation in contrast to local AgriSafe clinics in Iowa. The most innovative adaptation to CSF components was the development of a defined economic incentive in the form of a cost-share program. The RE-AIM framework was found to be useful and relevant to the field of agricultural health and safety translational research. This study provides effectiveness measures and implementation alternatives useful for those considering implementing CSF. It informs current efforts to move CSF from research to practice through the National Sustainable Model CSF Program initiative.

Nutritional and ecological evaluation of dairy farming systems based on concentrate feeding regimes in semi-arid environments of Jordan

PubMed Central

Alqaisi, Othman; Hemme, Torsten; Hagemann, Martin; Susenbeth, Andreas

2013-01-01

The objective of this study was to evaluate the nutritional and ecological aspects of feeding systems practiced under semi-arid environments in Jordan. Nine dairy farms representing the different dairy farming systems were selected for this study. Feed samples (n = 58), fecal samples (n = 108), and milk samples (n = 78) were collected from the farms and analysed for chemical composition. Feed samples were also analysed for metabolisable energy (ME) contents and in vitro organic matter digestibility according to Hohenheim-Feed-Test. Furthermore, fecal nitrogen concentration was determined to estimate in vivo organic matter digestibility. ME and nutrient intakes were calculated based on the farmer’s estimate of dry matter intake and the analysed composition of the feed ingredients. ME and nutrient intakes were compared to recommended standard values for adequate supply of ME, utilizable crude protein, rumen undegradable crude protein (RUCP), phosphorus (P), and calcium (Ca). Technology Impact Policy Impact Calculation model complemented with a partial life cycle assessment model was used to estimate greenhouse gas emissions of milk production at farm gate. The model predicts CH4, N2O and CO2 gases emitted either directly or indirectly. Average daily energy corrected milk yield (ECM) was 19 kg and ranged between 11 and 27 kg. The mean of ME intake of all farms was 184 MJ/d with a range between 115 and 225 MJ/d. Intake of RUCP was lower than the standard requirements in six farms ranging between 19 and 137 g/d, was higher (32 and 93 g/d) in two farms, and matched the requirements in one farm. P intake was higher than the requirements in all farms (mean oversupply = 19 g/d) and ranged between 3 and 30 g/d. Ca intake was significantly below the requirements in small scale farms. Milk nitrogen efficiency N-eff (milk N/intake N) varied between 19% and 28% and was mainly driven by the level of milk yield. Total CO2 equivalent (CO2 equ) emission ranged between 0.90 and 1.88 kg CO2/kg ECM milk, where the enteric and manure CH4 contributed to 52% of the total CO2 equ emissions, followed by the indirect emissions of N2O and the direct emissions of CO2 gases which comprises 17% and 15%, respectively, from total CO2 equ emissions. Emissions per kg of milk were significantly driven by the level of milk production (r2 = 0.93) and of eDMI (r2 = 0.88), while the total emissions were not influenced by diet composition. A difference of 16 kg ECM/d in milk yield, 9% in N-eff and of 0.9 kg CO2 equ/kg in ECM milk observed between low and high yielding animals. To improve the nutritional status of the animals, protein requirements have to be met. Furthermore, low price by-products with a low carbon credit should be included in the diets to replace the high proportion of imported concentrate feeds and consequently improve the economic situation of dairy farms and mitigate CO2 equ emissions. PMID:24596499

Effects of stored feed cropping systems and farm size on the profitability of Maine organic dairy farm simulations.

PubMed

Hoshide, A K; Halloran, J M; Kersbergen, R J; Griffin, T S; DeFauw, S L; LaGasse, B J; Jain, S

2011-11-01

United States organic dairy production has increased to meet the growing demand for organic milk. Despite higher prices received for milk, organic dairy farmers have come under increasing financial stress due to increases in concentrated feed prices over the past few years, which can make up one-third of variable costs. Market demand for milk has also leveled in the last year, resulting in some downward pressure on prices paid to dairy farmers. Organic dairy farmers in the Northeast United States have experimented with growing different forage and grain crops to maximize on-farm production of protein and energy to improve profitability. Three representative organic feed systems were simulated using the integrated farm system model for farms with 30, 120, and 220 milk cows. Increasing intensity of equipment use was represented by organic dairy farms growing only perennial sod (low) to those with corn-based forage systems, which purchase supplemental grain (medium) or which produce and feed soybeans (high). The relative profitability of these 3 organic feed systems was strongly dependent on dairy farm size. From results, we suggest smaller organic dairy farms can be more profitable with perennial sod-based rather than corn-based forage systems due to lower fixed costs from using only equipment associated with perennial forage harvest and storage. The largest farm size was more profitable using a corn-based system due to greater economies of scale for growing soybeans, corn grain, winter cereals, and corn silages. At an intermediate farm size of 120 cows, corn-based forage systems were more profitable if perennial sod was not harvested at optimum quality, corn was grown on better soils, or if milk yield was 10% higher. Delayed harvest decreased the protein and energy content of perennial sod crops, requiring more purchased grain to balance the ration and resulting in lower profits. Corn-based systems were less affected by lower perennial forage quality, as corn silage is part of the forage base. Growing on better soils increased corn yields more than perennial forage yields. Large corn-based organic dairy farms that produced and fed soybeans minimized off-farm grain purchases and were the most profitable among large farms. Although perennial sod-based systems purchased more grain, these organic systems were more profitable under timely forage harvest, decreased soil quality, and relatively lower purchased energy prices and higher protein supplement prices. Copyright © 2011 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Effects of the construction of Scroby Sands offshore wind farm on the prey base of Little tern Sternula albifrons at its most important UK colony.

PubMed

Perrow, Martin R; Gilroy, James J; Skeate, Eleanor R; Tomlinson, Mark L

2011-08-01

Despite widespread interest in the impacts of wind farms upon birds, few researchers have examined the potential for indirect or trophic (predator-prey) effects. Using surface trawls, we monitored prey abundance before and after construction of a 30 turbine offshore wind farm sited close to an internationally important colony of Little terns. Observations confirmed that young-of-the-year clupeids dominated chick diet, which trawl samples suggested were mainly herring. Multivariate modelling indicated a significant reduction in herring abundance from 2004 onwards that could not be explained by environmental factors. Intensely noisy monopile installation during the winter spawning period was suggested to be responsible. Reduced prey abundance corresponded with a significant decline in Little tern foraging success. Unprecedented egg abandonment and lack of chick hatching tentatively suggested a colony-scale response in some years. We urge a precautionary approach to the timing and duration of pile-driving activity supported with long-term targeted monitoring of sensitive receptors. Copyright © 2011 Elsevier Ltd. All rights reserved.

Evaluation of new farming technologies in Ethiopia using the Integrated Decision Support System (IDSS).

PubMed

Clarke, Neville; Bizimana, Jean-Claude; Dile, Yihun; Worqlul, Abeyou; Osorio, Javier; Herbst, Brian; Richardson, James W; Srinivasan, Raghavan; Gerik, Thomas J; Williams, Jimmy; Jones, Charles A; Jeong, Jaehak

2017-01-31

This study investigates multi-dimensional impacts of adopting new technology in agriculture at the farm/village and watershed scale in sub-Saharan Africa using the Integrated Decision Support System (IDSS). Application of IDSS as an integrated modeling tool helps solve complex issues in agricultural systems by simultaneously assessing production, environmental, economic, and nutritional consequences of adopting agricultural technologies for sustainable increases in food production and use of scarce natural resources. The IDSS approach was applied to the Amhara region of Ethiopia, where the scarcity of resources and agro-environmental consequences are critical to agricultural productivity of small farm, to analyze the impacts of alternative agricultural technology interventions. Results show significant improvements in family income and nutrition, achieved through the adoption of irrigation technologies, proper use of fertilizer, and improved seed varieties while preserving environmental indicators in terms of soil erosion and sediment loadings. These pilot studies demonstrate the usefulness of the IDSS approach as a tool that can be used to predict and evaluate the economic and environmental consequences of adopting new agricultural technologies that aim to improve the livelihoods of subsistence farmers.

Observations of Near-Surface Relative Humidity in a Wind Turbine Array Boundary Layer Using an Instrumented Unmanned Aerial System

NASA Astrophysics Data System (ADS)

Adkins, K. A.; Sescu, A.

2016-12-01

Simulation and modeling have shown that wind farms have an impact on the near-surface atmospheric boundary layer (ABL) as turbulent wakes generated by the turbines enhance vertical mixing. These changes alter downstream atmospheric properties. With a large portion of wind farms hosted within an agricultural context, changes to the environment can potentially have secondary impacts such as to the productivity of crops. With the exception of a few observational data sets that focus on the impact to near-surface temperature, little to no observational evidence exists. These few studies also lack high spatial resolution due to their use of a limited number of meteorological towers or remote sensing techniques. This study utilizes an instrumented small unmanned aerial system (sUAS) to gather in-situ field measurements from two Midwest wind farms, focusing on the impact that large utility-scale wind turbines have on relative humidity. Wind turbines are found to differentially alter the relative humidity in the downstream, spanwise and vertical directions under a variety of atmospheric stability conditions.

Changes in human skull morphology across the agricultural transition are consistent with softer diets in preindustrial farming groups.

PubMed

Katz, David C; Grote, Mark N; Weaver, Timothy D

2017-08-22

Agricultural foods and technologies are thought to have eased the mechanical demands of diet-how often or how hard one had to chew-in human populations worldwide. Some evidence suggests correspondingly worldwide changes in skull shape and form across the agricultural transition, although these changes have proved difficult to characterize at a global scale. Here, adapting a quantitative genetics mixed model for complex phenotypes, we quantify the influence of diet on global human skull shape and form. We detect modest directional differences between foragers and farmers. The effects are consistent with softer diets in preindustrial farming groups and are most pronounced and reliably directional when the farming class is limited to dairying populations. Diet effect magnitudes are relatively small, affirming the primary role of neutral evolutionary processes-genetic drift, mutation, and gene flow structured by population history and migrations-in shaping diversity in the human skull. The results also bring an additional perspective to the paradox of why Homo sapiens , particularly agriculturalists, appear to be relatively well suited to efficient (high-leverage) chewing.

Hindcast of water availability in regional aquifer systems using MODFLOW Farm Process

USGS Publications Warehouse

Schmid, Wolfgang; Hanson, Randall T.; Faunt, Claudia C.; Phillips, Steven P.

2015-01-01

Coupled groundwater and surface-water components of the hydrologic cycle can be simulated by the Farm Process for MODFLOW (MF-FMP) in both irrigated and non-irrigated areas and aquifer-storage and recovery systems. MF-FMP is being applied to three productive agricultural regions of different scale in the State of California, USA, to assess the availability of water and the impacts of alternative management decisions. Hindcast simulations are conducted for similar periods from the 1960s to near recent times. Historical groundwater pumpage is mostly unknown in one region (Central Valley) and is estimated by MF-FMP. In another region (Pajaro Valley), recorded pumpage is used to calibrate model-estimated pumpage. Multiple types of observations are used to estimate uncertain parameters, such as hydraulic, land-use, and farm properties. MF-FMP simulates how climate variability and water-import availability affect water demand and supply. MF-FMP can be used to predict water availability based on anticipated changes in anthropogenic or natural water demands. Keywords groundwater; surface-water; irrigation; water availability; response to climate variability/change

Simulating Land-Use Change using an Agent-Based Land Transaction Model

NASA Astrophysics Data System (ADS)

Bakker, M. M.; van Dijk, J.; Alam, S. J.

2013-12-01

In the densely populated cultural landscapes of Europe, the vast majority of all land is owned by private parties, be it farmers (the majority), nature organizations, property developers, or citizens. Therewith, the vast majority of all land-use change arises from land transactions between different owner types: successful farms expand at the expense of less successful farms, and meanwhile property developers, individual citizens, and nature organizations also actively purchase land. These land transactions are driven by specific properties of the land, by governmental policies, and by the (economic) motives of both buyers and sellers. Climate/global change can affect these drivers at various scales: at the local scale changes in hydrology can make certain land less or more desirable; at the global scale the agricultural markets will affect motives of farmers to buy or sell land; while at intermediate (e.g. provincial) scales property developers and nature conservationists may be encouraged or discouraged to purchase land. The cumulative result of all these transactions becomes manifest in changing land-use patterns, and consequent environmental responses. Within the project Climate Adaptation for Rural Areas an agent-based land-use model was developed that explores the future response of individual land users to climate change, within the context of wider global change (i.e. policy and market change). It simulates the exchange of land among farmers and between farmers and nature organizations and property developers, for a specific case study area in the east of the Netherlands. Results show that local impacts of climate change can result in a relative stagnation in the land market in waterlogged areas. Furthermore, the increase in dairying at the expense of arable cultivation - as has been observed in the area in the past - is slowing down as arable produce shows a favourable trend in the agricultural world market. Furthermore, budgets for nature managers are obviously an important driver for nature expansion, but without a strict zoning plan imposed by a government, it is difficult to achieve a continuous, defragmented nature area. Lastly, the model suggests that with time the trend in ever-increasing farm sizes is gradually levelling out. The decision rules that determine the behaviours of the individual agents in the model (selling land, buying land, or none of the two) are calibrated on historical census records, using multi-nominal logistic regression. Because estimating who will sell and who will buy can only be done with a limited certainty, our model reproduces the volatility / uncertainty in who will do what and when. This makes that each specific future scenario can have numerous realizations of reality. Our stakeholders (including, besides policy makers, also local farmers and nature organizations) indicate that this aspect of the model strongly contributes to its credibility. Nevertheless, within different scenarios certain (spatial) trends are distinguishable, so that the model is -besides credible - also useful for exploring future trends.

Validation of the Dynamic Wake Meander model with focus on tower loads

NASA Astrophysics Data System (ADS)

Larsen, T. J.; Larsen, G. C.; Pedersen, M. M.; Enevoldsen, K.; Madsen, H. A.

2017-05-01

This paper presents a comparison between measured and simulated tower loads for the Danish offshore wind farm Nysted 2. Previously, only limited full scale experimental data containing tower load measurements have been published, and in many cases the measurements include only a limited range of wind speeds. In general, tower loads in wake conditions are very challenging to predict correctly in simulations. The Nysted project offers an improved insight to this field as six wind turbines located in the Nysted II wind farm have been instrumented to measure tower top and tower bottom moments. All recorded structural data have been organized in a database, which in addition contains relevant wind turbine SCADA data as well as relevant meteorological data - e.g. wind speed and wind direction - from an offshore mast located in the immediate vicinity of the wind farm. The database contains data from a period extending over a time span of more than 3 years. Based on the recorded data basic mechanisms driving the increased loading experienced by wind turbines operating in offshore wind farm conditions have been identified, characterized and modeled. The modeling is based on the Dynamic Wake Meandering (DWM) approach in combination with the state-of-the-art aeroelastic model HAWC2, and has previously as well as in this study shown good agreement with the measurements. The conclusions from the study have several parts. In general the tower bending and yaw loads show a good agreement between measurements and simulations. However, there are situations that are still difficult to match. One is tower loads of single-wake operation near rated ambient wind speed for single wake situations for spacing’s around 7-8D. A specific target of the study was to investigate whether the largest tower fatigue loads are associated with a certain downstream distance. This has been identified in both simulations and measurements, though a rather flat optimum is seen in the measurements.

Model Wind Turbines Tested at Full-Scale Similarity

NASA Astrophysics Data System (ADS)

Miller, M. A.; Kiefer, J.; Westergaard, C.; Hultmark, M.

2016-09-01

The enormous length scales associated with modern wind turbines complicate any efforts to predict their mechanical loads and performance. Both experiments and numerical simulations are constrained by the large Reynolds numbers governing the full- scale aerodynamics. The limited fundamental understanding of Reynolds number effects in combination with the lack of empirical data affects our ability to predict, model, and design improved turbines and wind farms. A new experimental approach is presented, which utilizes a highly pressurized wind tunnel (up to 220 bar). It allows exact matching of the Reynolds numbers (no matter how it is defined), tip speed ratios, and Mach numbers on a geometrically similar, small-scale model. The design of a measurement and instrumentation stack to control the turbine and measure the loads in the pressurized environment is discussed. Results are then presented in the form of power coefficients as a function of Reynolds number and Tip Speed Ratio. Due to gearbox power loss, a preliminary study has also been completed to find the gearbox efficiency and the resulting correction has been applied to the data set.

A simple rule based model for scheduling farm management operations in SWAT

NASA Astrophysics Data System (ADS)

Schürz, Christoph; Mehdi, Bano; Schulz, Karsten

2016-04-01

For many interdisciplinary questions at the watershed scale, the Soil and Water Assessment Tool (SWAT; Arnold et al., 1998) has become an accepted and widely used tool. Despite its flexibility, the model is highly demanding when it comes to input data. At SWAT's core the water balance and the modeled nutrient cycles are plant growth driven (implemented with the EPIC crop growth model). Therefore, land use and crop data with high spatial and thematic resolution, as well as detailed information on cultivation and farm management practices are required. For many applications of the model however, these data are unavailable. In order to meet these requirements, SWAT offers the option to trigger scheduled farm management operations by applying the Potential Heat Unit (PHU) concept. The PHU concept solely takes into account the accumulation of daily mean temperature for management scheduling. Hence, it contradicts several farming strategies that take place in reality; such as: i) Planting and harvesting dates are set much too early or too late, as the PHU concept is strongly sensitivity to inter-annual temperature fluctuations; ii) The timing of fertilizer application, in SWAT this often occurs simultaneously on the same date in in each field; iii) and can also coincide with precipitation events. Particularly, the latter two can lead to strong peaks in modeled nutrient loads. To cope with these shortcomings we propose a simple rule based model (RBM) to schedule management operations according to realistic farmer management practices in SWAT. The RBM involves simple strategies requiring only data that are input into the SWAT model initially, such as temperature and precipitation data. The user provides boundaries of time periods for operation schedules to take place for all crops in the model. These data are readily available from the literature or from crop variety trials. The RBM applies the dates by complying with the following rules: i) Operations scheduled in the spring planting season and fall harvesting season are temperature dependent. Warmer than usual conditions trigger the setting of respective operations earlier in spring and later in fall to prolong the cropping season. ii) Operations are randomized within a time span ± 5 days around the calculated dates and iii) are only set on days where no rainfall occurs. Advantages offered by the RBM framework are the implementation of farmers undertaking different farming strategies, such as conventional or conservative farming, and the consideration of the prevailing weather conditions on the planting periods, thus the shifting management operations due to climate change will also be considered over the long term. By applying these rules to the available data we were able to establish a simple framework developing more realistic crop management schedules for SWAT which are an improvement over the current PHU concept implemented in SWAT. The outlined framework is easily extendible and adaptable to many other applications in SWAT. Case studies have yet to demonstrate the applicability and the validity of the proposed RBM.

Scaling up food production in the Upper Mississippi river basin: modeling impacts on water quality and nutrient cycling

NASA Astrophysics Data System (ADS)

Bowen, E. E.; Martin, P. A.; Schuble, T. J.; Yan, E.; Demissie, Y.

2010-12-01

Agricultural production imposes significant environmental stress on the landscape, both in the intensity and extent of agricultural activities. Among the most significant impacts, agriculture dominates the natural reactive nitrogen cycle, with excess reactive nitrogen leading to the degraded quality of inland and coastal waters. In the U.S., policymakers and stakeholders nationwide continue to debate strategies for decreasing environmental degradation from agricultural lands. Such strategies aim to optimize the balance among competing demands for food, fuel and ecosystem services. One such strategy increasingly discussed in the national debate is that of localizing food production around urban areas, developing what some have recently called “foodsheds”. However, the environmental impacts of localizing food production around population centers are not well-understood given the hard-to-generalize variety seen in management practices currently employed among local farms marketing food crops directly to consumers. As a first, landscape level study of potential impacts from scaling up this type of agriculture, we use the USDA Soil and Water Assessment Tool (SWAT) model to quantify environmental impacts from developing foodsheds for all population centers in the Upper Mississippi river basin. Specifically, we focus on nutrient cycling and water quality impacts determining direct greenhouse gas emissions and changes to nutrient runoff from increased food production in this watershed. We investigate a variety of scenarios in which food production is scaled up to the regional level using different types of farm management practices, ranging from conventional production of fruits and vegetables, to production of these products from small-scale, diversified systems integrating conservation easements. In addition to impacts on nutrient cycling and water quality, we also characterize relative levels of productivity in conjunction with overall demand for food associated with population centers to address one aspect of socio-economic concern.

Assessing the impact of marine wind farms on birds through movement modelling.

PubMed

Masden, Elizabeth A; Reeve, Richard; Desholm, Mark; Fox, Anthony D; Furness, Robert W; Haydon, Daniel T

2012-09-07

Advances in technology and engineering, along with European Union renewable energy targets, have stimulated a rapid growth of the wind power sector. Wind farms contribute to carbon emission reductions, but there is a need to ensure that these structures do not adversely impact the populations that interact with them, particularly birds. We developed movement models based on observed avoidance responses of common eider Somateria mollissima to wind farms to predict, and identify potential measures to reduce, impacts. Flight trajectory data that were collected post-construction of the Danish Nysted offshore wind farm were used to parameterize competing models of bird movements around turbines. The model most closely fitting the observed data incorporated individual variation in the minimum distance at which birds responded to the turbines. We show how such models can contribute to the spatial planning of wind farms by assessing their extent, turbine spacing and configurations on the probability of birds passing between the turbines. Avian movement models can make new contributions to environmental assessments of wind farm developments, and provide insights into how to reduce impacts that can be identified at the planning stage.

Quality of care and quality of life of people with dementia living at green care farms: a cross-sectional study.

PubMed

de Boer, Bram; Hamers, Jan P H; Zwakhalen, Sandra M G; Tan, Frans E S; Verbeek, Hilde

2017-07-19

Many countries are introducing smaller, more home-like care facilities that represent a radically new approach to nursing home care for people with dementia. The green care farm is a new type of nursing home developed in the Netherlands. The goal of this study was to compare quality of care, quality of life and related outcomes in green care farms, regular small-scale living facilities and traditional nursing homes for people with dementia. A cross-sectional design was used. Three types of nursing homes were included: (1) green care farms; (2) regular small-scale living facilities; (3) traditional nursing homes. All participating nursing homes were non-profit, collectively funded nursing homes in the south of the Netherlands. One hundred and fifteen residents with a formal diagnosis of dementia were included in the study. Data on quality of care was gathered and consisted of outcome indicators (e.g. falling incidents, pressure ulcers), structure indicators (e.g. hours per resident per day), and process indicators (e.g. presence, accessibility and content of protocols on care delivery). Furthermore, questionnaires on cognition, dependence in activities of daily living, quality of life, social engagement, neuropsychiatric symptoms, agitation, and depression were used. Data showed that quality of care was comparable across settings. No large differences were found on clinical outcome measures, hours per resident per day, or process indicators. Higher quality of life scores were reported for residents of green care farms in comparison with residents of traditional nursing homes. They scored significantly higher on the Quality of Life - Alzheimer's disease Scale (p < 0.05, ES = 0.8) indicating a better quality of life. In addition, residents of green care farms scored higher on three quality of life domains of the Qualidem: positive affect, social relations and having something to do (p < 0.05, ES > 0.7). No differences with regular small-scale living facilities were found. Green care farms seem to be a valuable alternative to existing nursing homes. This is important as people with dementia are a heterogeneous group with varying needs. In order to provide tailored care there also is a need for a variety of living environments.

Targeting the impact of agri-environmental policy - Future scenarios in two less favoured areas in Portugal.

PubMed

Jones, Nadia; Fleskens, Luuk; Stroosnijder, Leo

2016-10-01

Targeting agri-environmental measures (AEM) improves their effectiveness in the delivery of public goods, provided the necessary coordination with other incentives. In less favoured areas (LFA) measures focusing on the conservation of extensive farming contribute to sustainable land management in these areas. In this paper we investigate the implementation of a possible AEM supporting the improvement of permanent pastures coordinated with the extensive livestock and single farm payments actually in place. Through applying a spatially-explicit mixed integer optimisation model we simulate future land use scenarios for two less favoured areas in Portugal (Centro and Alentejo) considering two policy scenarios: a 'targeted AEM', and a 'non-targeted AEM'. We then compare the results with a 'basic policy' option (reflecting a situation without AEM). This is done with regard to landscape-scale effects on the reduction of fire hazard and erosion risk, as well as effects on farm income. The results show that an AEM for permanent pastures would be more cost-effective for erosion and fire hazard mitigation if implemented within a spatially targeted framework. However when cost-effectiveness is assessed with other indicators (e.g. net farm income and share of grazing livestock) 'non-targeted AEM' implementation delivers the best outcome in Alentejo. In Centro the implementation of an AEM involves important losses of income compared to the 'basic policy'. 'Targeted AEM' tends to favour farms in very marginal conditions, i.e. targeting is demonstrated to perform best in landscapes where spatial heterogeneity is higher. The results also show the risk of farm abandonment in the two studied less favoured areas: in all three scenarios more than 30% of arable land is deemed to be abandoned. Copyright © 2016 Elsevier Ltd. All rights reserved.

Temporal consistency of spatial pattern in growth of the mussel, Mytilus edulis: Implications for predictive modelling

NASA Astrophysics Data System (ADS)

Bergström, Per; Lindegarth, Susanne; Lindegarth, Mats

2013-10-01

Human pressures on coastal seas are increasing and methods for sustainable management, including spatial planning and mitigative actions, are therefore needed. In coastal areas worldwide, the development of mussel farming as an economically and ecologically sustainable industry requires geographic information on the growth and potential production capacity. In practice this means that coherent maps of temporally stable spatial patterns of growth need to be available in the planning process and that maps need to be based on mechanistic or empirical models. Therefore, as a first step towards development of models of growth, we assessed empirically the fundamental requirement that there are temporally consistent spatial patterns of growth in the blue mussel, Mytilus edulis. Using a pilot study we designed and dimensioned a transplant experiment, where the spatial consistency in the growth of mussels was evaluated at two resolutions. We found strong temporal and scale-dependent spatial variability in growth but patterns suggested that spatial patterns were uncoupled between growth of shell and that of soft tissue. Spatial patterns of shell growth were complex and largely inconsistent among years. Importantly, however, the growth of soft tissue was qualitatively consistent among years at the scale of km. The results suggest that processes affecting the whole coastal area cause substantial differences in growth of soft tissue among years but that factors varying at the scale of km create strong and persistent spatial patterns of growth, with a potential doubling of productivity by identifying the most suitable locations. We conclude that the observed spatial consistency provides a basis for further development of predictive modelling and mapping of soft tissue growth in these coastal areas. Potential causes of observed patterns, consequences for mussel-farming as a tool for mitigating eutrophication, aspects of precision of modelling and sampling of mussel growth as well as ecological functions in general are discussed.

Local infestation or long-distance migration? The seasonal recolonization of dairy farms by Stomoxys calcitrans (Diptera: Muscidae) in south central Ontario, Canada.

PubMed

Beresford, D V; Sutcliffe, J F

2009-04-01

Stable fly (Diptera: Muscidae) populations in south central Ontario, Canada, first occur on dairy farms in late spring, grow exponentially throughout the summer, and are frozen back each autumn. We examined the extent of overwinter persistence on 22 dairy farms in a 55- by 60-km region north of Lake Ontario that spans four climatic zones. Our overwintering sampling of larval habitat identified three farms located in the southern section of the study region as potential overwintering refugia. Using sticky trap catches to identify the timing of first spring appearance at each farm, we then tested two models of how local farm populations are reestablished annually: 1) stable flies disperse from local climatic refuges and colonize neighboring farms (the local source model); and 2) stable flies are carried into the study region by frontal weather systems (the distant source model). The timing of when stable flies first occurred at these farms supported a local source of dispersing colonists from a small proportion of local refuge farms. We discuss our results in terms of how yearly fluctuation in climate would affect refuge farm density in the region and how this, in turn, would shift the recolonization dynamic. Implications for controlling stable flies also are discussed.

Transition to farming more likely for small, conservative groups with property rights, but increased productivity is not essential

PubMed Central

Gallagher, Elizabeth M.; Shennan, Stephen J.; Thomas, Mark G.

2015-01-01

Theories for the origins of agriculture are still debated, with a range of different explanations offered. Computational models can be used to test these theories and explore new hypotheses; Bowles and Choi [Bowles S, Choi J-K (2013) Proc Natl Acad Sci USA 110(22):8830–8835] have developed one such model. Their model shows the coevolution of farming and farming-friendly property rights, and by including climate variability, replicates the timings for the emergence of these events seen in the archaeological record. Because the processes modeled occurred a long time ago, it can be difficult to justify exact parameter values; hence, we propose a fitting to idealized outcomes (FIO) method to explore the model’s parameter space in more detail. We have replicated the model of Bowles and Choi, and used the FIO method to identify complexities and interactions of the model previously unidentified. Our results indicate that the key parameters for the emergence of farming are group structuring, group size, conservatism, and farming-friendly property rights (lending further support to Bowles and Choi’s original proposal). We also find that although advantageous, it is not essential that farming productivity be greater than foraging productivity for farming to emerge. In addition, we highlight how model behaviors can be missed when gauging parameter sensitivity via a fix-all-but-one variation approach. PMID:26578766

Antibiotic Resistance in Animal and Environmental Samples Associated with Small-Scale Poultry Farming in Northwestern Ecuador.

PubMed

Braykov, Nikolay P; Eisenberg, Joseph N S; Grossman, Marissa; Zhang, Lixin; Vasco, Karla; Cevallos, William; Muñoz, Diana; Acevedo, Andrés; Moser, Kara A; Marrs, Carl F; Foxman, Betsy; Trostle, James; Trueba, Gabriel; Levy, Karen

2016-01-01

The effects of animal agriculture on the spread of antibiotic resistance (AR) are cross-cutting and thus require a multidisciplinary perspective. Here we use ecological, epidemiological, and ethnographic methods to examine populations of Escherichia coli circulating in the production poultry farming environment versus the domestic environment in rural Ecuador, where small-scale poultry production employing nontherapeutic antibiotics is increasingly common. We sampled 262 "production birds" (commercially raised broiler chickens and laying hens) and 455 "household birds" (raised for domestic use) and household and coop environmental samples from 17 villages between 2010 and 2013. We analyzed data on zones of inhibition from Kirby-Bauer tests, rather than established clinical breakpoints for AR, to distinguish between populations of organisms. We saw significantly higher levels of AR in bacteria from production versus household birds; resistance to either amoxicillin-clavulanate, cephalothin, cefotaxime, and gentamicin was found in 52.8% of production bird isolates and 16% of household ones. A strain jointly resistant to the 4 drugs was exclusive to a subset of isolates from production birds (7.6%) and coop surfaces (6.5%) and was associated with a particular purchase site. The prevalence of AR in production birds declined with bird age (P < 0.01 for all antibiotics tested except tetracycline, sulfisoxazole, and trimethoprim-sulfamethoxazole). Farming status did not impact AR in domestic environments at the household or village level. Our results suggest that AR associated with small-scale poultry farming is present in the immediate production environment and likely originates from sources outside the study area. These outside sources might be a better place to target control efforts than local management practices. IMPORTANCE In developing countries, small-scale poultry farming employing antibiotics as growth promoters is being advanced as an inexpensive source of protein and income. Here, we present the results of a large ecoepidemiological study examining patterns of antibiotic resistance (AR) in E. coli isolates from small-scale poultry production environments versus domestic environments in rural Ecuador, where such backyard poultry operations have become established over the past decade. Our previous research in the region suggests that introduction of AR bacteria through travel and commerce may be an important source of AR in villages of this region. This report extends the prior analysis by examining small-scale production chicken farming as a potential source of resistant strains. Our results suggest that AR strains associated with poultry production likely originate from sources outside the study area and that these outside sources might be a better place to target control efforts than local management practices.

Spatially explicit modeling of animal tuberculosis at the wildlife-livestock interface in Ciudad Real province, Spain.

PubMed

LaHue, Nathaniel P; Baños, Joaquín Vicente; Acevedo, Pelayo; Gortázar, Christian; Martínez-López, Beatriz

2016-06-01

Eurasian wild boar (Sus scrofa) and red deer (Cervus elaphus) are the most important wildlife reservoirs for animal tuberculosis (TB) caused by the Mycobacterium tuberculosis complex (MTC), in Mediterranean Spain. These species are considered to play an important role in the transmission and persistence of MTC in cattle in some regions; however the factors contributing to the risk of transmission at the wildlife-livestock interface and the areas at highest risk for such transmission are largely unknown. This study sought to identify geographic areas where wildlife-livestock interactions are most likely to occur and to characterize the environmental and management factors at this interface contributing to persistence, incidence, and occurrence of TB on cattle farms, in one of the provinces with higher TB prevalence in Spain, Ciudad Real. We used spatially explicit, ecological niche models to evaluate the importance of factors such as wildlife demographics and hunting management, land use, climatic, and environmental variables as well as TB status in wildlife for TB breakdown (model 1), persistence (model 2) and new infection (model 3) on cattle farms and to generate high resolution maps of predicted TB occurrence to guide risk-based interventions. Models revealed that land use, particularly open area and woodland, high wild boar TB prevalence, and close proximity to fenced hunting estates were the most important factors associated with TB infection on cattle farms. This is the first time that local TB prevalence in wild boar for individual hunting estates has been significantly associated with TB occurrence on cattle farms at a local scale. Prediction maps identified two areas with high likelihood of TB occurrence in the southwest and northwest of the province where wildlife-livestock interactions and TB occurrence are highly likely and where TB preventative and mitigation strategies (e.g. targeted vaccination, increased biosecurity, etc.) should be prioritized. Methods and results of this study were aimed to inform the implementation of risk-based interventions to better prevent and control TB at the wildlife-livestock interface, a necessary step for the successful eradication of TB in cattle in Spain. Copyright © 2016 Elsevier B.V. All rights reserved.

Are local wind power resources well estimated?

NASA Astrophysics Data System (ADS)

Lundtang Petersen, Erik; Troen, Ib; Jørgensen, Hans E.; Mann, Jakob

2013-03-01

Planning and financing of wind power installations require very importantly accurate resource estimation in addition to a number of other considerations relating to environment and economy. Furthermore, individual wind energy installations cannot in general be seen in isolation. It is well known that the spacing of turbines in wind farms is critical for maximum power production. It is also well established that the collective effect of wind turbines in large wind farms or of several wind farms can limit the wind power extraction downwind. This has been documented by many years of production statistics. For the very large, regional sized wind farms, a number of numerical studies have pointed to additional adverse changes to the regional wind climate, most recently by the detailed studies of Adams and Keith [1]. They show that the geophysical limit to wind power production is likely to be lower than previously estimated. Although this problem is of far future concern, it has to be considered seriously. In their paper they estimate that a wind farm larger than 100 km2 is limited to about 1 W m-2. However, a 20 km2 off shore farm, Horns Rev 1, has in the last five years produced 3.98 W m-2 [5]. In that light it is highly unlikely that the effects pointed out by [1] will pose any immediate threat to wind energy in coming decades. Today a number of well-established mesoscale and microscale models exist for estimating wind resources and design parameters and in many cases they work well. This is especially true if good local data are available for calibrating the models or for their validation. The wind energy industry is still troubled by many projects showing considerable negative discrepancies between calculated and actually experienced production numbers and operating conditions. Therefore it has been decided on a European Union level to launch a project, 'The New European Wind Atlas', aiming at reducing overall uncertainties in determining wind conditions. The project is structured around three areas of work, to be implemented in parallel. Creation and publication of a European wind atlas in electronic form [2], which will include the underlying data and a new EU wind climate database which will as a minimum include: wind resources and their associated uncertainty; extreme wind and uncertainty; turbulence characteristics; adverse weather conditions such as heavy icing, electrical storms and so on together with the probability of occurrence; the level of predictability for short-term forecasting and assessment of uncertainties; guidelines and best practices for the use of data especially for micro-siting. Development of dynamical downscaling methodologies and open-source models validated through measurement campaigns, to enable the provision of accurate wind resource and external wind load climatology and short-term prediction at high spatial resolution and covering Europe. The developed downscaling methodologies and models will be fully documented and made publicly available and will be used to produce overview maps of wind resources and other relevant data at several heights and at high horizontal resolution. Measurement campaigns to validate the model chain used in the wind atlas. At least five coordinated measurement campaigns will be undertaken and will cover complex terrains (mountains and forests), offshore, large changes in surface characteristics (roughness change) and cold climates. One of the great challenges to the project is the application of mesoscale models for wind resource calculation, which is by no means a simple matter [3]. The project will use global reanalysis data as boundary conditions. These datasets, which are time series of the large-scale meteorological situation covering decades, have been created by assimilation of measurement data from around the globe in a dynamical consistent fashion using large-scale numerical models. For wind energy, the application of the reanalysis datasets is as a long record of the large-scale wind conditions. The large-scale reanalyses are performed in only a few global weather prediction centres using models that have been developed over many years, and which are still being developed and validated and are being used in operational services. Mesoscale models are more diverse, but nowadays quite a number have a proven track record in applications such as regional weather prediction and also wind resource assessment. There are still some issues, and use of model results without proper validation may lead to gross errors. For resource assessment it is necessary to include direct validation with in situ observed wind data over sufficiently long periods. In doing so, however, the mesoscale model output must be downscaled using some microscale physical or empirical/statistical model. That downscaling process is not straightforward, and the microscale models themselves tend to disagree in some terrain types as shown by recent blind tests [4]. All these 'technical' details and choices, not to mention the model formulation itself, the numerical schemes used, and the effective spatial and temporal resolution, can have a significant impact on the results. These problems, as well as the problem of how uncertainties are propagated through the model chain to the calculated wind resources, are central in the work with the New European Wind Atlas. The work of [1] shows that when wind energy has been implemented on a very massive scale, it will affect the power production from entire regions and that has to be taken into account. References [1] Adams A S and Keith D W 2013 Are global wind power resource estimates overstated? Environ. Res. Lett. 8 015021 [2] 2011 A New EU Wind Energy Atlas: Proposal for an ERANET+ Project (Produced by the TPWind Secretariat) Nov. [3] Petersen E L Troen I 2012 Wind conditions and resource assessment WIREs Energy Environ. 1 206-17 [4] Bechmann A, Sørensen N N, Berg J, Mann J Rethore P-E 2011 The Bolund experiment, part II: blind comparison of microscale flow models Boundary-Layer Meteorol. 141 245-71 [5] www.lorc.dk/offshore-wind-farms-map/horns-rev-1 www.ens.dk

Agent Based Model of Livestock Movements

NASA Astrophysics Data System (ADS)

Miron, D. J.; Emelyanova, I. V.; Donald, G. E.; Garner, G. M.

The modelling of livestock movements within Australia is of national importance for the purposes of the management and control of exotic disease spread, infrastructure development and the economic forecasting of livestock markets. In this paper an agent based model for the forecasting of livestock movements is presented. This models livestock movements from farm to farm through a saleyard. The decision of farmers to sell or buy cattle is often complex and involves many factors such as climate forecast, commodity prices, the type of farm enterprise, the number of animals available and associated off-shore effects. In this model the farm agent's intelligence is implemented using a fuzzy decision tree that utilises two of these factors. These two factors are the livestock price fetched at the last sale and the number of stock on the farm. On each iteration of the model farms choose either to buy, sell or abstain from the market thus creating an artificial supply and demand. The buyers and sellers then congregate at the saleyard where livestock are auctioned using a second price sealed bid. The price time series output by the model exhibits properties similar to those found in real livestock markets.

Phosphorus in agricultural soils: drivers of its distribution at the global scale

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ringeval, Bruno; Augusto, Laurent; Monod, Herve

Phosphorus (P) availability in soils limits crop yields in many regions of the world, while excess of soil P triggers aquatic eutrophication in other regions. Numerous processes drive the global spatial distribution of P in agricultural soils, but their relative roles remain unclear. Here, we combined several global datasets describing these drivers with a soil P dynamics model to simulate the distribution of P in agricultural soils and to assess the contributions of the different drivers at the global scale. We analyzed both the labile inorganic P (P ILAB), a proxy of the pool involved in plant nutrition and themore » total soil P (P TOT). We found that the soil biogeochemical background (BIOG) and farming practices (FARM) were the main drivers of the spatial variability in cropland soil P content but that their contribution varied between P TOT vs P ILAB. Indeed, 97% of the P TOT spatial variability could be explained by BIOG, while BIOG and FARM explained 41% and 58% of P ILAB spatial variability, respectively. Other drivers such as climate, soil erosion, atmospheric P deposition and soil buffering capacity made only very small contribution. Lastly, our study is a promising approach to investigate the potential effect of P as a limiting factor for agricultural ecosystems and for global food production. Additionally, we quantified the anthropogenic perturbation of P cycle and demonstrated how the different drivers are combined to explain the global distribution of agricultural soil P.« less

Estimating the sensitivity of passive surveillance for HPAI H5N1 in Bayelsa state, Nigeria.

PubMed

Ojimelukwe, Agatha E; Prakarnkamanant, Apisit; Rushton, Jonathan

2016-07-01

This study identified characteristics of poultry farming with a focus on practices that affect the detection of HPAI; and estimated the system sensitivity of passive surveillance for HPAI H5N1 in commercial and backyard chicken farms in Bayelsa-State, Nigeria. Field studies were carried out in Yenegoa and Ogbia local government areas in Bayelsa state. Willingness to report HPAI was highest in commercial poultry farms (13/13) than in Backyard farms (8/13). Poor means of dead bird disposal was common to both commercial and backyard farms. Administering some form of treatment to sick birds without prior consultation with a professional was higher in backyard farms (8/13) than in commercial farms (4/13). Consumption of sick birds was reported in 4/13 backyard farms and sale of dead birds was recorded in one commercial farm. The sensitivity of passive surveillance for HPAI was assessed using scenario tree modelling. A scenario tree model was developed and applied to estimate the sensitivity, i.e. the probability of detecting one or more infected chicken farms in Bayelsa state at different levels of disease prevalence. The model showed a median sensitivity of 100%, 67% and 23% for detecting HPAI by passive surveillance at a disease prevalence of 0.1%, a minimum of 10 and 3 infected poultry farms respectively. Passive surveillance system sensitivity at a design prevalence of 10 infected farms is increasable up to 86% when the disease detection in backyard chicken farms is enhanced. Copyright © 2016 Elsevier B.V. All rights reserved.

Validation of Individual-Based Markov-Like Stochastic Process Model of Insect Behavior and a “Virtual Farm” Concept for Enhancement of Site-Specific IPM

PubMed Central

Lux, Slawomir A.; Wnuk, Andrzej; Vogt, Heidrun; Belien, Tim; Spornberger, Andreas; Studnicki, Marcin

2016-01-01

The paper reports application of a Markov-like stochastic process agent-based model and a “virtual farm” concept for enhancement of site-specific Integrated Pest Management. Conceptually, the model represents a “bottom-up ethological” approach and emulates behavior of the “primary IPM actors”—large cohorts of individual insects—within seasonally changing mosaics of spatiotemporally complex faming landscape, under the challenge of the local IPM actions. Algorithms of the proprietary PESTonFARM model were adjusted to reflect behavior and ecology of R. cerasi. Model parametrization was based on compiled published information about R. cerasi and the results of auxiliary on-farm experiments. The experiments were conducted on sweet cherry farms located in Austria, Germany, and Belgium. For each farm, a customized model-module was prepared, reflecting its spatiotemporal features. Historical data about pest monitoring, IPM treatments and fruit infestation were used to specify the model assumptions and calibrate it further. Finally, for each of the farms, virtual IPM experiments were simulated and the model-generated results were compared with the results of the real experiments conducted on the same farms. Implications of the findings for broader applicability of the model and the “virtual farm” approach—were discussed. PMID:27602000

Evaluation in Appalachian pasture systems of the 1996 (update 2000) National Research Council model for weaning cattle.

PubMed

Whetsell, M S; Rayburn, E B; Osborne, P I

2006-05-01

This study was conducted to evaluate the accuracy of the National Research Council's (2000) Nutrient Requirements of Beef Cattle computer model when used to predict calf performance during on-farm pasture or dry-lot weaning and backgrounding. Calf performance was measured on 22 farms in 2002 and 8 farms in 2003 that participated in West Virginia Beef Quality Assurance Sale marketing pools. Calves were weaned on pasture (25 farms) or dry-lot (5 farms) and fed supplemental hay, haylage, ground shell corn, soybean hulls, or a commercial concentrate. Concentrates were fed at a rate of 0.0 to 1.5% of BW. The National Research Council (2000) model was used to predict ADG of each group of calves observed on each farm. The model error was measured by calculating residuals (the difference between predicted ADG minus observed ADG). Predicted animal performance was determined using level 1 of the model. Results show that, when using normal on-farm pasture sampling and forage analysis methods, the model error for ADG is high and did not accurately predict the performance of steers or heifers fed high-forage pasture-based diets; the predicted ADG was lower (P < 0.05) than the observed ADG. The estimated intake of low-producing animals was similar to the expected DMI, but for the greater-producing animals it was not. The NRC (2000) beef model may more accurately predict on-farm animal performance in pastured situations if feed analysis values reflect the energy value of the feed, account for selective grazing, and relate empty BW and shrunk BW to NDF.

A Framework for Statewide Analysis of Site Suitability, Energy Estimation, Life Cycle Costs, Financial Feasibility and Environmental Assessment of Wind Farms: A Case Study of Indiana

NASA Astrophysics Data System (ADS)

Kumar, Indraneel

In the last decade, Midwestern states including Indiana have experienced an unprecedented growth in utility scale wind energy farms. For example, by end of 2013, Indiana had 1.5 GW of wind turbines installed, which could provide electrical energy for as many as half-a-million homes. However, there is no statewide systematic framework available for the evaluation of wind farm impacts on endangered species, required necessary setbacks and proximity standards to infrastructure, and life cycle costs. This research is guided to fill that gap and it addresses the following questions. How much land is suitable for wind farm siting in Indiana given the constraints of environmental, ecological, cultural, settlement, physical infrastructure and wind resource parameters? How much wind energy can be obtained? What are the life cycle costs and economic and financial feasibility? Is wind energy production and development in a state an emission free undertaking? The framework developed in the study is applied to a case study of Indiana. A fuzzy logic based AHP (Analytic Hierarchy Process) spatial site suitability analysis for wind energy is formulated. The magnitude of wind energy that could be sited and installed comprises input for economic and financial feasibility analysis for 20-25 years life cycle of wind turbines in Indiana. Monte Carlo simulation is used to account for uncertainty and nonlinearity in various costs and price parameters. Impacts of incentives and cost variables such as production tax credits, costs of capital, and economies of scale are assessed. Further, an economic input-output (IO) based environmental assessment model is developed for wind energy, where costs from financial feasibility analysis constitute the final demand vectors. This customized model for Indiana is used to assess emissions for criteria air pollutants, hazardous air pollutants and greenhouse gases (GHG) across life cycle events of wind turbines. The findings of the case study include that, Indiana has adequate suitable land area available to locate wind farms with installed capacity between 11 and 51 GW if 100 meters high turbines are used. For a 1.5 MW standard wind turbine, financial feasibility analysis shows that production tax credits and property tax abatements are helpful for financial success in Indiana. Also, the wind energy is not entirely emission free if life cycle events of wind turbine manufacturing, production, installation, construction and decommissioning are considered. The research developed a replicable and integrated framework for statewide life cycle analysis of wind energy production accounting for uncertainty into the analyses. Considering the complexity of life cycle analysis and lack of state specific data on performance of wind turbines and wind farms, this study should be considered an intermediate step.

Agricultural depopulation in Croatia.

PubMed

Stambuk, M

1991-01-01

Trends in urban depopulation since 1945 in Yugoslavia and specifically in Croatia are analyzed. Two phases are identified: the first involved the eradication of the peasant farm under the Communist system, which resulted in a large-scale exodus from agricultural to urban-based activities. The second phase, which has lasted until the present, has two features: one is the tendency of those staying on family farms to have other employment off the farm; the other involves the likelihood of seeking employment abroad. (SUMMARY IN FRE AND GER)

Creating a model to detect dairy cattle farms with poor welfare using a national database.

PubMed

Krug, C; Haskell, M J; Nunes, T; Stilwell, G

2015-12-01

The objective of this study was to determine whether dairy farms with poor cow welfare could be identified using a national database for bovine identification and registration that monitors cattle deaths and movements. The welfare of dairy cattle was assessed using the Welfare Quality(®) protocol (WQ) on 24 Portuguese dairy farms and on 1930 animals. Five farms were classified as having poor welfare and the other 19 were classified as having good welfare. Fourteen million records from the national cattle database were analysed to identify potential welfare indicators for dairy farms. Fifteen potential national welfare indicators were calculated based on that database, and the link between the results on the WQ evaluation and the national cattle database was made using the identification code of each farm. Within the potential national welfare indicators, only two were significantly different between farms with good welfare and poor welfare, 'proportion of on-farm deaths' (p<0.01) and 'female/male birth ratio' (p<0.05). To determine whether the database welfare indicators could be used to distinguish farms with good welfare from farms with poor welfare, we created a model using the classifier J48 of Waikato Environment for Knowledge Analysis. The model was a decision tree based on two variables, 'proportion of on-farm deaths' and 'calving-to-calving interval', and it was able to correctly identify 70% and 79% of the farms classified as having poor and good welfare, respectively. The national cattle database analysis could be useful in helping official veterinary services in detecting farms that have poor welfare and also in determining which welfare indicators are poor on each particular farm. Copyright © 2015 Elsevier B.V. All rights reserved.

Dairy farming on permanent grassland: can it keep up?

PubMed

Kellermann, M; Salhofer, K

2014-10-01

Based on an extensive data set for southern Germany, we compared the productive performance of dairy farms that operate solely on permanent grassland and dairy farms using fodder crops from arable land. We allowed for heterogeneous production technologies and identified more intensive and extensive production systems for both types of farms, whereby we based our notion of intensive versus extensive dairy production on differences in stocking density and milk yield per cow and year. To be able to compare the productivity levels and productivity developments of the various groups of farms, we developed a group- and chain-linked multilateral productivity index. We also analyzed how technical change, technical efficiency change, and a scale change effect contribute to productivity growth between the years 2000 and 2008. Our results revealed that permanent grassland farms can generally keep up with fodder-crop farms, even in an intensive production setting. However, extensively operating farms, especially those on permanent grassland, significantly lag behind in productivity and productivity change and run the risk of losing ground. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Evaluation of average daily gain predictions by the integrated farm system model for forage-finished beef steers

USDA-ARS?s Scientific Manuscript database

Representing the performance of cattle finished on an all forage diet in process-based whole farm system models has presented a challenge. To address this challenge, a study was done to evaluate average daily gain (ADG) predictions of the Integrated Farm System Model (IFSM) for steers consuming all-...

Firm Efficiency and Returns-to-Scale in the Honey Bee Pollination Services Industry.

PubMed

Jones Ritten, Chian; Peck, Dannele; Ehmke, Mariah; Patalee, M A Buddhika

2018-04-03

While the demand for pollination services have been increasing, continued declines in honey bee, Apis mellifera L. (Hymenoptera: Apidae), colonies have put the cropping sector and the broader health of agro-ecosystems at risk. Economic factors may play a role in dwindling honey bee colony supply in the United States, but have not been extensively studied. Using data envelopment analysis (DEA), we measure technical efficiency, returns to scale, and factors influencing the efficiency of those apiaries in the northern Rocky Mountain region participating in the pollination services market. We find that, although over 25% of apiaries are technically efficient, many experience either increasing or decreasing returns to scale. Smaller apiaries (under 80 colonies) experience increasing returns to scale, but a lack of available financing may hinder them from achieving economically sustainable colony levels. Larger apiaries (over 1,000 colonies) experience decreasing returns to scale. Those beekeepers may have economic incentivizes to decrease colony numbers. Using a double bootstrap method, we find that apiary location and off-farm employment influence apiary technical efficiency. Apiaries in Wyoming are found to be more efficient than those in Utah or Montana. Further, engagement in off-farm employment increases an apiary's technical efficiency. The combined effects of efficiency gains through off-farm employment and diseconomies of scale may explain, in part, the historical decline in honey bee numbers.

A sample theory-based logic model to improve program development, implementation, and sustainability of Farm to School programs.

PubMed

Ratcliffe, Michelle M

2012-08-01

Farm to School programs hold promise to address childhood obesity. These programs may increase students’ access to healthier foods, increase students’ knowledge of and desire to eat these foods, and increase their consumption of them. Implementing Farm to School programs requires the involvement of multiple people, including nutrition services, educators, and food producers. Because these groups have not traditionally worked together and each has different goals, it is important to demonstrate how Farm to School programs that are designed to decrease childhood obesity may also address others’ objectives, such as academic achievement and economic development. A logic model is an effective tool to help articulate a shared vision for how Farm to School programs may work to accomplish multiple goals. Furthermore, there is evidence that programs based on theory are more likely to be effective at changing individuals’ behaviors. Logic models based on theory may help to explain how a program works, aid in efficient and sustained implementation, and support the development of a coherent evaluation plan. This article presents a sample theory-based logic model for Farm to School programs. The presented logic model is informed by the polytheoretical model for food and garden-based education in school settings (PMFGBE). The logic model has been applied to multiple settings, including Farm to School program development and evaluation in urban and rural school districts. This article also includes a brief discussion on the development of the PMFGBE, a detailed explanation of how Farm to School programs may enhance the curricular, physical, and social learning environments of schools, and suggestions for the applicability of the logic model for practitioners, researchers, and policy makers.

Field-scale soil moisture space-time geostatistical modeling for complex Palouse landscapes in the inland Pacific Northwest

NASA Astrophysics Data System (ADS)

Chahal, M. K.; Brown, D. J.; Brooks, E. S.; Campbell, C.; Cobos, D. R.; Vierling, L. A.

2012-12-01

Estimating soil moisture content continuously over space and time using geo-statistical techniques supports the refinement of process-based watershed hydrology models and the application of soil process models (e.g. biogeochemical models predicting greenhouse gas fluxes) to complex landscapes. In this study, we model soil profile volumetric moisture content for five agricultural fields with loess soils in the Palouse region of Eastern Washington and Northern Idaho. Using a combination of stratification and space-filling techniques, we selected 42 representative and distributed measurement locations in the Cook Agronomy Farm (Pullman, WA) and 12 locations each in four additional grower fields that span the precipitation gradient across the Palouse. At each measurement location, soil moisture was measured on an hourly basis at five different depths (30, 60, 90, 120, and 150 cm) using Decagon 5-TE/5-TM soil moisture sensors (Decagon Devices, Pullman, WA, USA). This data was collected over three years for the Cook Agronomy Farm and one year for each of the grower fields. In addition to ordinary kriging, we explored the correlation of volumetric water content with external, spatially exhaustive indices derived from terrain models, optical remote sensing imagery, and proximal soil sensing data (electromagnetic induction and VisNIR penetrometer)

Modeling Parasite Dynamics on Farmed Salmon for Precautionary Conservation Management of Wild Salmon

PubMed Central

Rogers, Luke A.; Peacock, Stephanie J.; McKenzie, Peter; DeDominicis, Sharon; Jones, Simon R. M.; Chandler, Peter; Foreman, Michael G. G.; Revie, Crawford W.; Krkošek, Martin

2013-01-01

Conservation management of wild fish may include fish health management in sympatric populations of domesticated fish in aquaculture. We developed a mathematical model for the population dynamics of parasitic sea lice (Lepeophtheirus salmonis) on domesticated populations of Atlantic salmon (Salmo salar) in the Broughton Archipelago region of British Columbia. The model was fit to a seven-year dataset of monthly sea louse counts on farms in the area to estimate population growth rates in relation to abiotic factors (temperature and salinity), local host density (measured as cohort surface area), and the use of a parasiticide, emamectin benzoate, on farms. We then used the model to evaluate management scenarios in relation to policy guidelines that seek to keep motile louse abundance below an average three per farmed salmon during the March–June juvenile wild Pacific salmon (Oncorhynchus spp.) migration. Abiotic factors mediated the duration of effectiveness of parasiticide treatments, and results suggest treatment of farmed salmon conducted in January or early February minimized average louse abundance per farmed salmon during the juvenile wild salmon migration. Adapting the management of parasites on farmed salmon according to migrations of wild salmon may therefore provide a precautionary approach to conserving wild salmon populations in salmon farming regions. PMID:23577082

Simulation of between-farm transmission of porcine reproductive and respiratory syndrome virus in Ontario, Canada using the North American Animal Disease Spread Model.

PubMed

Thakur, Krishna K; Revie, Crawford W; Hurnik, Daniel; Poljak, Zvonimir; Sanchez, Javier

2015-03-01

Porcine reproductive and respiratory syndrome (PRRS), a viral disease of swine, has major economic impacts on the swine industry. The North American Animal Disease Spread Model (NAADSM) is a spatial, stochastic, farm level state-transition modeling framework originally developed to simulate highly contagious and foreign livestock diseases. The objectives of this study were to develop a model to simulate between-farm spread of a homologous strain of PRRS virus in Ontario swine farms via direct (animal movement) and indirect (sharing of trucks between farms) contacts using the NAADSM and to compare the patterns and extent of outbreak under different simulated conditions. A total of 2552 swine farms in Ontario province were allocated to each census division of Ontario and geo-locations of the farms were randomly generated within the agriculture land of each Census Division. Contact rates among different production types were obtained using pig movement information from four regions in Canada. A total of 24 scenarios were developed involving various direct (movement of infected animals) and indirect (pig transportation trucks) contact parameters in combination with alternating the production type of the farm in which the infection was seeded. Outbreaks were simulated for one year with 1000 replications. The median number of farms infected, proportion of farms with multiple outbreaks and time to reach the peak epidemic were used to compare the size, progression and extent of outbreaks. Scenarios involving spread only by direct contact between farms resulted in outbreaks where the median percentage of infected farms ranged from 31.5 to 37% of all farms. In scenarios with both direct and indirect contact, the median percentage of infected farms increased to a range from 41.6 to 48.6%. Furthermore, scenarios with both direct and indirect contact resulted in a 44% increase in median epidemic size when compared to the direct contact scenarios. Incorporation of both animal movements and the sharing of trucks within the model indicated that the effect of direct and indirect contact may be nonlinear on outbreak progression. The increase of 44% in epidemic size when indirect contact, via sharing of trucks, was incorporated into the model highlights the importance of proper biosecurity measures in preventing transmission of the PRRS virus. Simulation of between-farm spread of the PRRS virus in swine farms has highlighted the relative importance of direct and indirect contact and provides important insights regarding the possible patterns and extent of spread of the PRRS virus in a completely susceptible population with herd demographics similar to those found in Ontario, Canada. Copyright © 2015 Elsevier B.V. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jonkman, Jason; Annoni, Jennifer; Hayman, Greg

This paper presents the development of FAST.Farm, a new multiphysics tool applicable to engineering problems in research and industry involving wind farm performance and cost optimization that is needed to address the current underperformance, failures, and expenses plaguing the wind industry. Achieving wind cost-of-energy targets - which requires improvements in wind farm performance and reliability, together with reduced uncertainty and expenditures - has been eluded by the complicated nature of the wind farm design problem, especially the sophisticated interaction between atmospheric phenomena and wake dynamics and array effects. FAST.Farm aims to balance the need for accurate modeling of the relevantmore » physics for predicting power performance and loads while maintaining low computational cost to support a highly iterative and probabilistic design process and system-wide optimization. FAST.Farm makes use of FAST to model the aero-hydro-servo-elastics of distinct turbines in the wind farm, and it is based on some of the principles of the Dynamic Wake Meandering (DWM) model, but avoids many of the limitations of existing DWM implementations.« less

Longitudinal study on the temporal and micro-spatial distribution of Galba truncatula in four farms in Belgium as a base for small-scale risk mapping of Fasciola hepatica.

PubMed

Charlier, Johannes; Soenen, Karen; De Roeck, Els; Hantson, Wouter; Ducheyne, Els; Van Coillie, Frieke; De Wulf, Robert; Hendrickx, Guy; Vercruysse, Jozef

2014-11-26

The trematode parasite Fasciola hepatica causes important economic losses in ruminants worldwide. Current spatial distribution models do not provide sufficient detail to support farm-specific control strategies. A technology to reliably assess the spatial distribution of intermediate host snail habitats on farms would be a major step forward to this respect. The aim of this study was to conduct a longitudinal field survey in Flanders (Belgium) to (i) characterise suitable small water bodies (SWB) for Galba truncatula and (ii) describe the population dynamics of G. truncatula. Four F. hepatica-infected farms from two distinct agricultural regions were examined for the abundance of G. truncatula from the beginning (April 2012) until the end (November 2012) of the grazing season. Per farm, 12 to 18 SWB were selected for monthly examination, using a 10 m transect analysis. Observations on G. truncatula abundance were coupled with meteorological and (micro-)environmental factors and the within-herd prevalence of F. hepatica using simple comparison or negative binomial regression models. A total of 54 examined SWB were classified as a pond, ditch, trench, furrow or moist area. G. truncatula abundance was significantly associated with SWB-type, region and total monthly precipitation, but not with monthly temperature. The clear differences in G. truncatula abundance between the 2 studied regions did not result in comparable differences in F. hepatica prevalence in the cattle. Exploration of the relationship of G. truncatula abundance with (micro)-environmental variables revealed a positive association with soil and water pH and the occurrence of Ranunculus sp. and a negative association with mowed pastures, water temperature and presence of reed-like plant species. Farm-level predictions of G. truncatula risk and subsequent risk for F. hepatica occurrence would require a rainfall, soil type (representing the agricultural region) and SWB layer in a geographic information system. While rainfall and soil type information is easily accessible, the recent advances in very high spatial resolution cameras carried on board of satellites, planes or drones should allow the delineation of SWBs in the future.

Species-specific patterns of aggregation of wild fish around fish farms

NASA Astrophysics Data System (ADS)

Dempster, T.; Sanchez-Jerez, P.; Uglem, I.; Bjørn, P.-A.

2010-01-01

Fish-farming structures are widespread in coastal waters and are highly attractive to wild fish. Several studies have estimated that tons to tens of tons of wild fish aggregate around fish farms. These estimates assumed that the majority of wild fish are concentrated immediately beneath farms, although this assumption has never been explicitly tested. We tested the hypothesis that abundances of wild fish would be greatest immediately beneath farms and progressively diminish with distance at 4 full-scale coastal salmon ( Salmo salar) farms in Norway. At each farm, fish were counted with a video-camera system at 5 different distances from the cages (farm = 0 m, 25, 50, 100 and 200 m) throughout the water column on three separate days. Combined across all locations and times, the total abundance of wild fish was 20 times greater at the farm than at the 200 m sampling distance. Saithe ( Pollachius virens) dominated assemblages at all 4 farms and were consistently significantly more abundant at the farm than at the 25-200 m distances. This 'tight aggregation' around farms corresponds to the reliance of saithe on waste feed when they school near farms. In contrast, patterns of distribution of both cod ( Gadus morhua) and poor cod ( Trisopterus minutus) varied among farms, with either highest abundances at the farm or a more even distribution of abundance across all 5 distances sampled. No specific pattern of aggregation was evident for the bottom-dwelling haddock ( Melanogrammus aeglefinus). Our results suggest that the present 100 m no-fishing zone around salmon farms protects the greatest proportion of farm-aggregated saithe and cod from fishing during the daytime. However, whether this reduces their overall susceptibility to fishing requires further research regarding nighttime distribution and movements.

Simulations for Making On-farm Decisions in Relation to ENSO in Semi-arid Areas, South Africa

NASA Astrophysics Data System (ADS)

Tesfuhuney, W. A.; Crespo, O. O.; Walker, S. S.; Steyn, S. A.

2017-12-01

The study was employed to investigate and improve on-farm decision making on planting dates and fertilization by relating simulated yield and seasonal outlook information. The Agricultural Production Systems SIMulator model (APSIM) was used to explore ENSO/SOI effects for small-scale farmers to represent weather conditions and soil forms of semi-arid areas of Bothaville, Bethlehem and Bloemfontein regions in South Africa. The relationships of rainfall and SOI anomalies indicate a positive correlation, signifies ENSO/SOI as seasonal outlooks for study areas. Model evaluation results showed higher degree of bias (RMSEs/RMSE value of 0.88-0.98). The D-index of agreement in the range 0.61-0.71 indicate the ability of the APSIM-Maize model is an adequate tool in evaluating relative changes in maize yield in relation to various management practices and seasonal variations. During rainy, La Niño years (SOI > +5), highest simulated yields were found for Bethlehem in November with addition of 100 - 150 kg ha-1 N fertilization and up to 50 kg ha-1 for both Bothaville and Bloemfontein. With respect to various levels of fertilization, the dry El Niño years (SOI < -5) had a range of 0.90-1.31, 3.03-3.54 and 1.11-1.26 t ha-1 yields and showed to increase during La Niña years with a range of 2.50-2.66, 3.36-4.79 and 2.24-2.38 t ha-1 at Bothaville, Bethlehem and Bloemfontein for November planting. During El Niño episodes planting earlier and using 50 kg ha-1 fertilizer with improved short maturing cultivar are effective adaptation measures to counteract poor soils and erratic rainfall of semi-arid environment, Under optimal soil conditions and/or when probability of La Niño episodes, optimal yields are obtained by maximizing fertilization. Effective rainfall and tactical on-farm management decisions in associate with seasonal rainfall out looks information is a useful mechanism in reducing risk for dryland farming in semi-arid regions. Key word: Semi-arid; APSIM; SOI; El Niño / La Niña; On-farm Decisions

Sensitivity of Caligus rogercresseyi (Boxshall and Bravo 2000) to pyrethroids and azamethiphos measured using bioassay tests-A large scale spatial study.

PubMed

Marín, S L; Ibarra, R; Medina, M H; Jansen, P A

2015-11-01

The variety of antiparasitics that can be used against caligid copepods is limited and efforts are needed to maintain their efficacies. The objective of this study was to monitor the sensitivity of Caligus rogercresseyi, populations towards antiparasitics based on deltamethrin, cypermethrin and azamethiphos within and across geographic regions. The bioassay design consisted of exposing parasites collected from 23 farms to the different chemotherapeutants at the concentration and exposure times recommended for field treatment, under laboratory conditions, and evaluating the number of dead and live parasites 48h after exposure. Parasites were collected from 23 farms distributed in four macrozones in the Los Lagos region and three macrozones in the Aysén region. Parasite sensitivity was evaluated using a Generalized Linear Mixed Model of the Binomial family (Logit) fit by the maximum likelihood, using the lme4 package in R. Parasite gender, macrozone, and antiparasitics were used as fixed factors and farm was the random factor. The model including all the factors proved to be a useful tool for predicting parasite sensitivity. This approach identified (i) those macrozones with a greater likelihood of finding parasite populations which are more or less sensitive to the three antiparasitics, (ii) cases in which parasite sensitivity to the different antiparasitics varied within a given macrozone, (iii) differences in sensitivity between females and males and (iv) an important random effect associated with farm. The results indicate a spatial variability of parasite sensitivity to antiparasitics which, added to the continuous treatments applied on farms, suggest it is necessary to regularly update the sensitivity status in the macrozones. This would allow managers to improve their decision making processes regarding the type of antiparasitic to be used in a given situation. The one-concentration type bioassay performed in this study allowed us to perform a large spatial study with replicated tests of the sensitivity of C. rogercresseyi to pyrethroids and azamethiphos. Further studies should focus on the farm effects, the relationship between the sensitivity of parasites and field efficacy, as well as parasite population structure and connectivity with regard to parasite transmission between farms. Copyright © 2015 Elsevier B.V. All rights reserved.

Could Crop Roughness Impact the Wind Resource at Agriculturally Productive Wind Farm Sites?

NASA Astrophysics Data System (ADS)

Vanderwende, B. J.; Lundquist, J. K.

2014-12-01

The high concentration of both large-scale agriculture and wind power production in the United States Midwest region raises new questions concerning the interaction of the two activities. For instance, it is known from internal boundary layer theory that changes in the roughness of the land-surface resulting from crop choices could modify the momentum field aloft. Upward propagation of such an effect might impact the properties of the winds encountered by modern turbines, which typically span a layer from about 40 to 120 meters above the surface. As direct observation of such interaction would require impractical interference in the planting schedules of farmers, we use numerical modeling to quantify the magnitude of crop-roughness effects. To simulate a collocated farm and turbine array, we use version 3.4.1 of the Weather Research and Forecasting model (WRF). The hypothetical farm is inserted near the real location of the 2013 Crop Wind Energy Experiment (CWEX). Reanalyses provide representative initial and boundary conditions. A month-long period spanning August 2013 is used to evaluate the differences in flows above corn (maize) and soybean crops at the mature, reproductive stage. Simulations are performed comparing the flow above each surface regime, both in the absence and presence of a wind farm, which consists of a parameterized 11x11 array of 1.8 MW Vestas V90 turbines. Appreciable differences in rotor-layer wind speeds emerge. The use of soybeans results in an increase in wind speeds and a corresponding reduction in rotor-layer shear when compared to corn. Despite the turbulent nature of flow within a wind farm, high stability reduces the impact of crop roughness on the flow aloft, particularly in the upper portion of the rotor disk. We use these results to estimate the economic impact of crop selection on wind power producers.

Developing COMET-Farm and the DayCent Model for California Specialty Crops

NASA Astrophysics Data System (ADS)

Steenwerth, K. L.; Barker, X. Z.; Carlson, M.; Killian, K.; Easter, M.; Swan, A.; Thompson, L.; Williams, S.; Paustian, K.

2016-12-01

Specialty crops are hugely important to the agricultural economy of California, which grows over 400 specialty crops and produces at least a third of the nations' vegetables and more than two thirds of its fruit and nut tree crops. Since the passage of AB32 Global Warming Solutions Act in 2006, the state has made strong investments in reducing greenhouse gas emissions and developing climate adaptation solutions. Most recently, Governor J. Brown (CA) has issued an executive order to establish reductions to 40% below 1990 levels. While agriculture in California is not regulated for greenhouse gas emissions under AB32, efforts are being made to develop tools to support practices that can enhance soil health and reduce greenhouse gas emissions. USDA-NRCS supports one such tool known as COMET-Farm, which is intended for future use with incentive programs and soil conservation plans managed by the agency. The underlying model that that simulates entity-scale greenhouse gas emissions in COMET-Farm is DayCent. Members of the California Climate Hub are collaborating with the Natural Resource Ecology Laboratory at Colorado State University in Fort Collins, CO to develop DayCent for 15 California specialty crops. These specialty crops include woody perennials like stone fruit like almonds and peaches, walnuts, citrus, wine grapes, raisins and table grapes. Annual specialty crops include cool season vegetables like lettuce and broccoli, tomatoes, and strawberries. DayCent has been parameterized for these crops using existing published and unpublished studies. Practice based information has also been gathered in consultation with growers. Aspects of the model have been developed for woody biomass production and competition between herbaceous vegetation and woody perennial crops. We will report on model performance for these crops and opportunities for model improvement.

Research in biomass production and utilization: Systems simulation and analysis

NASA Astrophysics Data System (ADS)

Bennett, Albert Stewart

There is considerable public interest in developing a sustainable biobased economy that favors support of family farms and rural communities and also promotes the development of biorenewable energy resources. This study focuses on a number of questions related to the development and exploration of new pathways that can potentially move us toward a more sustainable biobased economy. These include issues related to biomass fuels for drying grain, economies-of-scale, new biomass harvest systems, sugar-to-ethanol crop alternatives for the Upper Midwest U.S., biomass transportation, post-harvest biomass processing and double cropping production scenarios designed to maximize biomass feedstock production. The first section of this study considers post-harvest drying of shelled corn grain both at farm-scale and at larger community-scaled installations. Currently, drying of shelled corn requires large amounts of fossil fuel energy. To address future energy concerns, this study evaluates the potential use of combined heat and power systems that use the combustion of corn stover to produce steam for drying and to generate electricity for fans, augers, and control components. Because of the large capital requirements for solid fuel boilers and steam turbines/engines, both farm-scale and larger grain elevator-scaled systems benefit by sharing boiler and power infrastructure with other processes. The second and third sections evaluate sweet sorghum as a possible "sugarcane-like" crop that can be grown in the Upper Midwest. Various harvest systems are considered including a prototype mobile juice harvester, a hypothetical one-pass unit that separates grain heads from chopped stalks and traditional forage/silage harvesters. Also evaluated were post-harvest transportation, storage and processing costs and their influence on the possible use of sweet sorghum as a supplemental feedstock for existing dry-grind ethanol plants located in the Upper Midwest. Results show that the concept of a mobile juice harvester is not economically viable due to low sugar recovery. The addition of front-end stalk processing/pressing equipment into existing ethanol facilities was found to be economically viable when combined with the plants' use of residuals as a natural gas fuel replacement. Because of high loss of fermentable carbohydrates during ensilage, storage of sweet sorghum in bunkers was not found to be economically viable. The fourth section looks at double cropping winter triticale with late-planted summer corn and compares these scenarios to traditional single cropped corn. Double cropping systems show particular promise for co-production of grain and biomass feedstocks and potentially can allow for greater utilization of grain crop residues. However, additional costs and risks associated with producing two crops instead of one could make biomass-double crops less attractive for producers despite productivity advantages. Detailed evaluation and comparisons show double cropped triticale-corn to be at a significant economic disadvantage relative to single crop corn. The cost benefits associated with using less equipment combined with availability of risk mitigating crop insurance and government subsidies will likely limit farmer interest and clearly indicate that traditional single-crop corn will provide greater financial returns to management. To evaluate the various sweet sorghum, single crop corn and double cropped triticale-corn production scenarios, a detailed but generic model was developed. The primary goal of this generic approach was to develop a modeling foundation that can be rapidly adapted, by an experienced user, to describe new and existing biomass and crop production scenarios that may be of interest to researchers. The foundation model allows input of management practices, crop production characteristics and utilizes standardized machinery performance and cost information, including farm-owned machinery and implements, and machinery and farm production operations provided by custom operators. (Abstract shortened by UMI.)

Is the Production of Embryos in Small-Scale Farming an Economically Feasible Enterprise?

PubMed

Sánchez, Z; Lammoglia, M A; Alarcón, M A; Romero, J J; Galina, C S

2015-08-01

The present assay attempts to evaluate the feasibility of using embryo transfer in small community farmers by in vivo study and by modelling the results obtained. From the total of 59 donor cows, 62.7% responded to treatment, with a significant difference (p = 0.002) in the percentage of the response between breeds, being 90.5% (19/21) in Holstein and 47.4% (18/38) in Brahman. A total of 283 embryos were graded as transferable, while 141 as non-transferable, without difference in the percentage of transferable embryo by breed (p = 0.18). The mean of transferable embryos graded as class I and II was not different between Holstein and Brahman (p = 0.96 and p = 0.92, respectively); besides, no differences were observed in the other grades (non-transferable). The highest difference in costs, regardless of its quality by breed, was seen in the lower levels of probable fertility of the embryo transferred, even reaching several hundred dollars. When modelling the expected costs for embryo produced and transferred, values can reach nearly $2000.00 when the probable fertility is only 10%. However, when the probable fertility was 60%, embryo cost was close to $300.00. This technology seems to be viable on average or high-scale systems, having a superovulatory response between 60 and 80% with 4-6 transferrable embryos. Yet, in small-scale farming, due to the reduced number of donors and/or recipients, the costs surpass the economical feasibility of the technique. © 2015 Blackwell Verlag GmbH.

Farm-Level Effects of Soil Conservation and Commodity Policy Alternatives: Model and Data Documentation.

ERIC Educational Resources Information Center

Sutton, John D.

This report documents a profit-maximizing linear programming (LP) model of a farm typical of a major corn-soybean producing area in the Southern Michigan-Northern Indiana Drift Plain. Following an introduction, a complete description of the farm is provided. The next section presents the LP model, which is structured to help analyze after-tax…

Assessing the impact of marine wind farms on birds through movement modelling

PubMed Central

Masden, Elizabeth A.; Reeve, Richard; Desholm, Mark; Fox, Anthony D.; Furness, Robert W.; Haydon, Daniel T.

2012-01-01

Advances in technology and engineering, along with European Union renewable energy targets, have stimulated a rapid growth of the wind power sector. Wind farms contribute to carbon emission reductions, but there is a need to ensure that these structures do not adversely impact the populations that interact with them, particularly birds. We developed movement models based on observed avoidance responses of common eider Somateria mollissima to wind farms to predict, and identify potential measures to reduce, impacts. Flight trajectory data that were  collected post-construction of the Danish Nysted offshore wind farm were used to parameterize competing models of bird movements around turbines. The model most closely fitting the observed data incorporated individual variation in the minimum distance at which birds responded to the turbines. We show how such models can contribute to the spatial planning of wind farms by assessing their extent, turbine spacing and configurations on the probability of birds passing between the turbines. Avian movement models can make new contributions to environmental assessments of wind farm developments, and provide insights into how to reduce impacts that can be identified at the planning stage. PMID:22552921

Risk factors associated with bulk tank standard plate count, bulk tank coliform count, and the presence of Staphylococcus aureus on organic and conventional dairy farms in the United States.

PubMed

Cicconi-Hogan, K M; Gamroth, M; Richert, R; Ruegg, P L; Stiglbauer, K E; Schukken, Y H

2013-01-01

The purpose of this study was to assess the association of bulk tank milk standard plate counts, bulk tank coliform counts (CC), and the presence of Staphylococcus aureus in bulk tank milk with various management and farm characteristics on organic and conventional dairy farms throughout New York, Wisconsin, and Oregon. Data from size-matched organic farms (n=192), conventional nongrazing farms (n=64), and conventional grazing farms (n=36) were collected at a single visit for each farm. Of the 292 farms visited, 290 bulk tank milk samples were collected. Statistical models were created using data from all herds in the study, as well as exclusively for the organic subset of herds. Because of incomplete data, 267 of 290 herds were analyzed for total herd modeling, and 173 of 190 organic herds were analyzed for the organic herd modeling. Overall, more bulk tanks from organic farms had Staph. aureus cultured from them (62% of organic herds, 42% conventional nongrazing herds, and 43% of conventional grazing herds), whereas fewer organic herds had a high CC, defined as ≥50 cfu/mL, than conventional farms in the study. A high standard plate count (×1,000 cfu/mL) was associated with decreased body condition score of adult cows and decreased milk production in both models. Several variables were significant only in the model created using all herds or only in organic herds. The presence of Staph. aureus in the bulk tank milk was associated with fewer people treating mastitis, increased age of housing, and a higher percentage of cows with 3 or fewer teats in both the organic and total herd models. The Staph. aureus total herd model also showed a relationship with fewer first-lactation animals, higher hock scores, and less use of automatic takeoffs at milking. High bulk tank CC was related to feeding a total mixed ration and using natural service in nonlactating heifers in both models. Overall, attentive management and use of outside resources were useful with regard to CC on organic farms. In all models except the organic CC model, we observed an association with the average reported somatic cell count from 3 mo before the herd visit, indicating that many of the regularly tested milk quality parameters are interconnected. In conclusion, we found that conventional and organic farms are similar in regard to overall herd management, but each grazing system faces unique challenges when managing milk quality. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Residents' Perceptions toward Utility-Scale Wind Farm Development

ERIC Educational Resources Information Center

Campbell, Joseph; Romich, Eric

2015-01-01

Increased development of wind farms in the U.S. has fostered debates surrounding the siting and support for the projects. Prior research demonstrates the importance of understanding the attitudes and opinions of community members when developing projects. This article reviews a case study of an Ohio community that integrated a local survey to…

Solar energy use in U.S. agriculture. Overview and policy issues

USDA-ARS?s Scientific Manuscript database

Using solar energy on farms for livestock watering, electric fence charging, and building lighting is not new in the United States, but in the past five years, solar energy is now being used more for large scale irrigation, heating water in dairies, and running motors/appliances in farm houses and b...

Actual Condition of Paddy Field Levee Maintenance by Various Farm Households including Large-scale Farming in the Developed Land Renting Area

NASA Astrophysics Data System (ADS)

Sakata, Yasuyo

The survey of interview, resource acquisition, photographic operation, and questionnaire were carried out in the “n” Community in the “y” District in Hakusan City in Ishikawa Prefecture to investigate the actual condition of paddy field levee maintenance in the area where land-renting market was proceeding, large-scale farming was dominant, and the problems of geographically scattered farm-land existed. In the study zone, 1) an agricultural production legal person rent-cultivated some of the paddy fields and maintained the levees, 2) another agricultural production legal person rent-cultivated some of the soy bean fields for crop changeover and land owners maintained the levees. The results indicated that sufficient maintenance was executed on the levees of the paddy fields cultivated by the agricultural production legal person, the soy bean fields for crop changeover, and the paddy fields cultivated by the land owners. Each reason is considered to be the managerial strategy, the economic incentive, the mutual monitoring and cross-regulatory mechanism, etc.

Seroprevalence and risk factors for Toxoplasma gondii infection on pig farms in central China.

PubMed

Tao, Qing; Wang, Zhengsong; Feng, Huihui; Fang, Rui; Nie, Hao; Hu, Min; Zhou, Yanqin; Zhao, Junlong

2011-04-01

Toxoplasma gondii is a protozoan parasite that causes severe diseases in mammals, including humans, around the world. In China, pork is the main meat source; accordingly, T. gondii in pigs is considered an important source for human toxoplasmosis. Understanding the epidemiology of toxoplasmosis in pig farms is thus important for control of the disease in humans. The purpose of the present study was to investigate the epizootiology of T. gondii infections in pig farms in central China by assessing the seroprevalence and risk factors of this disease. In the present study, 3,558 sera samples were collected from pigs in 37 large-scale pig farms in this region and tested by AG-ELISA. The total seroprevalence was 24.5%, with the greatest prevalence in breeding pigs. The risk factors for toxoplasmosis suggest that high frequency of the contact of pigs with cats (P ≤ 0.01; IC 95%), high density of pig breeding (P ≤ 0.01; IC 95%), the presence of mosquitoes and flies (P ≤ 0.01; IC 95%), semi-patency pens (P ≤ 0.05; IC 95%), and low frequency of scavenging (P ≤ 0.01; IC 95%) were all associated with seroprevalence. In addition, the use of sulfonamides (P ≤ 0.01; IC 95%) significantly decreased seroprevalence. This is the first report of anti- T. gondii antibodies in pigs on large-scale pig farms in central China. The findings will provide useful information for designing control strategies of toxoplasmasis in pig farms.

Resource distributions among habitats determine solitary bee offspring production in a mosaic landscape.

PubMed

Williams, Neal M; Kremen, Claire

2007-04-01

Within mosaic landscapes, many organisms depend on attributes of the environment that operate over scales ranging from a single habitat patch to the entire landscape. One such attribute is resource distribution. Organisms' reliance on resources from within a local patch vs. those found among habitats throughout the landscape will depend on local habitat quality, patch quality, and landscape composition. The ability of individuals to move among complementary habitat types to obtain various resources may be a critical mechanism underlying the dynamics of animal populations and ultimately the level of biodiversity at different spatial scales. We examined the effects that local habitat type and landscape composition had on offspring production and survival of the solitary bee Osmia lignaria in an agri-natural landscape in California (U.S.A.). Female bees were placed on farms that did not use pesticides (organic farms), on farms that did use pesticides (conventional farms), or in seminatural riparian habitats. We identified pollens collected by bees nesting in different habitat types and matched these to pollens of flowering plants from throughout the landscape. These data enabled us to determine the importance of different plant species and habitat types in providing food for offspring, and how this importance changed with landscape and local nesting-site characteristics. We found that increasing isolation from natural habitat significantly decreased offspring production and survival for bees nesting at conventional farms, had weaker effects on bees in patches of seminatural habitat, and had little impact on those at organic farm sites. Pollen sampled from nests showed that females nesting in both farm and seminatural habitats relied on pollen from principally native plant species growing in seminatural habitat. Thus connectivity among habitats was critical for offspring production. Females nesting on organic farms were buffered to isolation effects by switching to floral resources growing at the farm site when seminatural areas were too distant. Overall local habitat conditions (farm management practices) can help bolster pollinators, but maintaining functional connectivity among habitats will likely be critical for persistence of pollinator populations as natural habitats are increasingly fragmented by human activities.

Modelling Infectious Hematopoietic Necrosis Virus Dispersion from Marine Salmon Farms in the Discovery Islands, British Columbia, Canada.

PubMed

Foreman, Michael G G; Guo, Ming; Garver, Kyle A; Stucchi, Dario; Chandler, Peter; Wan, Di; Morrison, John; Tuele, Darren

2015-01-01

Finite volume ocean circulation and particle tracking models are used to simulate water-borne transmission of infectious hematopoietic necrosis virus (IHNV) among Atlantic salmon (Salmo salar) farms in the Discovery Islands region of British Columbia, Canada. Historical simulations for April and July 2010 are carried out to demonstrate the seasonal impact of river discharge, wind, ultra-violet (UV) radiation, and heat flux conditions on near-surface currents, viral dispersion and survival. Numerical particles released from infected farm fish in accordance with IHNV shedding rates estimated through laboratory experiments are dispersed by model oceanic flows. Viral particles are inactivated by ambient UV radiation levels and by the natural microbial community at rates derived through laboratory studies. Viral concentration maps showing temporal and spatial changes are produced and combined with lab-determined minimum infectious dosages to estimate the infective connectivity among farms. Results demonstrate that neighbouring naïve farms can become exposed to IHNV via water-borne transport from an IHNV diseased farm, with a higher risk in April than July, and that many events in the sequence of farm outbreaks in 2001-2002 are consistent with higher risks in our farm connectivity matrix. Applications to other diseases, transfers between farmed and wild fish, and the effect of vaccinations are also discussed.

Modelling Infectious Hematopoietic Necrosis Virus Dispersion from Marine Salmon Farms in the Discovery Islands, British Columbia, Canada

PubMed Central

Foreman, Michael G. G.; Guo, Ming; Garver, Kyle A.; Stucchi, Dario; Chandler, Peter; Wan, Di; Morrison, John; Tuele, Darren

2015-01-01

Finite volume ocean circulation and particle tracking models are used to simulate water-borne transmission of infectious hematopoietic necrosis virus (IHNV) among Atlantic salmon (Salmo salar) farms in the Discovery Islands region of British Columbia, Canada. Historical simulations for April and July 2010 are carried out to demonstrate the seasonal impact of river discharge, wind, ultra-violet (UV) radiation, and heat flux conditions on near-surface currents, viral dispersion and survival. Numerical particles released from infected farm fish in accordance with IHNV shedding rates estimated through laboratory experiments are dispersed by model oceanic flows. Viral particles are inactivated by ambient UV radiation levels and by the natural microbial community at rates derived through laboratory studies. Viral concentration maps showing temporal and spatial changes are produced and combined with lab-determined minimum infectious dosages to estimate the infective connectivity among farms. Results demonstrate that neighbouring naïve farms can become exposed to IHNV via water-borne transport from an IHNV diseased farm, with a higher risk in April than July, and that many events in the sequence of farm outbreaks in 2001-2002 are consistent with higher risks in our farm connectivity matrix. Applications to other diseases, transfers between farmed and wild fish, and the effect of vaccinations are also discussed. PMID:26114643

Effects of pond draining on biodiversity and water quality of farm ponds.

PubMed

Usio, Nisikawa; Imada, Miho; Nakagawa, Megumi; Akasaka, Munemitsu; Takamura, Noriko

2013-12-01

Farm ponds have high conservation value because they contribute significantly to regional biodiversity and ecosystem services. In Japan pond draining is a traditional management method that is widely believed to improve water quality and eradicate invasive fish. In addition, fishing by means of pond draining has significant cultural value for local people, serving as a social event. However, there is a widespread belief that pond draining reduces freshwater biodiversity through the extirpation of aquatic animals, but scientific evaluation of the effectiveness of pond draining is lacking. We conducted a large-scale field study to evaluate the effects of pond draining on invasive animal control, water quality, and aquatic biodiversity relative to different pond-management practices, pond physicochemistry, and surrounding land use. The results of boosted regression-tree models and analyses of similarity showed that pond draining had little effect on invasive fish control, water quality, or aquatic biodiversity. Draining even facilitated the colonization of farm ponds by invasive red swamp crayfish (Procambarus clarkii), which in turn may have detrimental effects on the biodiversity and water quality of farm ponds. Our results highlight the need for reconsidering current pond management and developing management plans with respect to multifunctionality of such ponds. Efectos del Drenado de Estanques sobre la Biodiversidad y la Calidad del Agua en Estanques de Cultivo. © 2013 Society for Conservation Biology.

Biodegradation of endocrine disruptors in urban wastewater using Pleurotus ostreatus bioreactor.

PubMed

Křesinová, Zdena; Linhartová, Lucie; Filipová, Alena; Ezechiáš, Martin; Mašín, Pavel; Cajthaml, Tomáš

2018-07-25

The white rot fungus Pleurotus ostreatus HK 35, which is also an edible industrial mushroom commonly cultivated in farms, was tested in the degradation of typical representatives of endocrine disrupters (EDCs; bisphenol A, estrone, 17β-estradiol, estriol, 17α-ethinylestradiol, triclosan and 4-n-nonylphenol); its degradation efficiency under model laboratory conditions was greater than 90% within 12 days and better than that of another published strain P. ostreatus 3004. A spent mushroom substrate from a local farm was tested for its applicability in various batch and trickle-bed reactors in degrading EDCs in model fortified and real communal wastewater. The reactors were tested under various regimes including a pilot-scale trickle-bed reactor, which was finally tested at a wastewater treatment plant. The result revealed that the spent substrate is an efficient biodegradation agent, where the fungus was usually able to remove about 95% of EDCs together with suppression of the estrogenic activity of the sample. The results showed the fungus was able to operate in the presence of bacterial microflora in wastewater without any substantial negative effects on the degradation abilities. Finally, a pilot-scale trickle-bed reactor was installed in a wastewater treatment plant and successfully operated for 10days, where the bioreactor was able to remove more than 76% of EDCs present in the wastewater. Copyright © 2017 Elsevier B.V. All rights reserved.

Factors associated with small-scale agricultural machinery adoption in Bangladesh: Census findings.

PubMed

Mottaleb, Khondoker Abdul; Krupnik, Timothy J; Erenstein, Olaf

2016-08-01

There is strong advocacy for agricultural machinery appropriate for smallholder farmers in South Asia. Such 'scale-appropriate' machinery can increase returns to land and labour, although the still substantial capital investment required can preclude smallholder ownership. Increasing machinery demand has resulted in relatively well-developed markets for rental services for tillage, irrigation, and post-harvest operations. Many smallholders thereby access agricultural machinery that may have otherwise been cost prohibitive to purchase through fee-for-service arrangements, though opportunity for expansion remains. To more effectively facilitate the development and investment in scale-appropriate machinery, there is a need to better understand the factors associated with agricultural machinery purchases and service provision. This paper first reviews Bangladesh's historical policy environment that facilitated the development of agricultural machinery markets. It then uses recent Bangladesh census data from 814,058 farm households to identify variables associated with the adoption of the most common smallholder agricultural machinery - irrigation pumps, threshers, and power tillers (mainly driven by two-wheel tractors). Multinomial probit model results indicate that machinery ownership is positively associated with household assets, credit availability, electrification, and road density. These findings suggest that donors and policy makers should focus not only on short-term projects to boost machinery adoption. Rather, sustained emphasis on improving physical and civil infrastructure and services, as well as assuring credit availability, is also necessary to create an enabling environment in which the adoption of scale-appropriate farm machinery is most likely.

A process-based emission model of volatile organic compounds from silage sources on farms

NASA Astrophysics Data System (ADS)

Bonifacio, H. F.; Rotz, C. A.; Hafner, S. D.; Montes, F.; Cohen, M.; Mitloehner, F. M.

2017-03-01

Silage on dairy farms can emit large amounts of volatile organic compounds (VOCs), a precursor in the formation of tropospheric ozone. Because of the challenges associated with direct measurements, process-based modeling is another approach for estimating emissions of air pollutants from sources such as those from dairy farms. A process-based model for predicting VOC emissions from silage was developed and incorporated into the Integrated Farm System Model (IFSM, v. 4.3), a whole-farm simulation of crop, dairy, and beef production systems. The performance of the IFSM silage VOC emission model was evaluated using ethanol and methanol emissions measured from conventional silage piles (CSP), silage bags (SB), total mixed rations (TMR), and loose corn silage (LCS) at a commercial dairy farm in central California. With transport coefficients for ethanol refined using experimental data from our previous studies, the model performed well in simulating ethanol emission from CSP, TMR, and LCS; its lower performance for SB could be attributed to possible changes in face conditions of SB after silage removal that are not represented in the current model. For methanol emission, lack of experimental data for refinement likely caused the underprediction for CSP and SB whereas the overprediction observed for TMR can be explained as uncertainty in measurements. Despite these limitations, the model is a valuable tool for comparing silage management options and evaluating their relative effects on the overall performance, economics, and environmental impacts of farm production. As a component of IFSM, the silage VOC emission model was used to simulate a representative dairy farm in central California. The simulation showed most silage VOC emissions were from feed lying in feed lanes and not from the exposed face of silage storages. This suggests that mitigation efforts, particularly in areas prone to ozone non-attainment status, should focus on reducing emissions during feeding. For the simulated dairy farm, a reduction of around 30% was found if cows were housed and fed in a barn rather than in an open lot, and 23% if feeds were delivered as four feedings per day rather than as one. Reducing the exposed face of storage can also be useful. Simulated use of silage bags resulted in 90% and 18% reductions in emissions from the storage face and whole farm, respectively.

Impact of greenhouse gas metrics on the quantification of agricultural emissions and farm-scale mitigation strategies: a New Zealand case study

NASA Astrophysics Data System (ADS)

Reisinger, Andy; Ledgard, Stewart

2013-06-01

Agriculture emits a range of greenhouse gases. Greenhouse gas metrics allow emissions of different gases to be reported in a common unit called CO2-equivalent. This enables comparisons of the efficiency of different farms and production systems and of alternative mitigation strategies across all gases. The standard metric is the 100 year global warming potential (GWP), but alternative metrics have been proposed and could result in very different CO2-equivalent emissions, particularly for CH4. While significant effort has been made to reduce uncertainties in emissions estimates of individual gases, little effort has been spent on evaluating the implications of alternative metrics on overall agricultural emissions profiles and mitigation strategies. Here we assess, for a selection of New Zealand dairy farms, the effect of two alternative metrics (100 yr GWP and global temperature change potentials, GTP) on farm-scale emissions and apparent efficiency and cost effectiveness of alternative mitigation strategies. We find that alternative metrics significantly change the balance between CH4 and N2O; in some cases, alternative metrics even determine whether a specific management option would reduce or increase net farm-level emissions or emissions intensity. However, the relative ranking of different farms by profitability or emissions intensity, and the ranking of the most cost-effective mitigation options for each farm, are relatively unaffected by the metric. We conclude that alternative metrics would change the perceived significance of individual gases from agriculture and the overall cost to farmers if a price were applied to agricultural emissions, but the economically most effective response strategies are unaffected by the choice of metric.

Assessment of biosecurity level in small-scale broiler farms in the Western highlands of Cameroon (Central Africa).

PubMed

Kouam, Marc K; Jacouba, Manjeli; Nsangou, Inouss N; Teguia, Alexis

2018-04-23

The recent outbreak of avian influenza in the poultry sector of Cameroon has raised a concern about the level of implementation of biosecurity measures (BM) on poultry farms. Therefore, a study using a questionnaire on 102 randomly selected poultry farms was undertaken. Some measures with high adoption levels (> 90%) included "protection of airing openings of poultry barns by a wire mesh," "no external animal allowed to enter the farm," "respect of all-in all-out principle," "functional footbath," "rodent control," and "feedstuff protection from access to rodents." The least implemented measures (less than 20%) were "wearing of dedicated clothing (clean coveralls and boots) by workers," "disinfection of visitors," and "presence of storage room for dead animals." Only for "isolation" component of biosecurity, compliance with biosecurity measures was good, with more than 50% of farms having an adoption rate greater than 75%. The mean biosecurity score for the assessed farms was 19.29 ± 1.89 for a maximum score of 38 points. The score was significantly and positively correlated (p < 0.05) with the number of chicken and the geographic location of farms. The other results showed that the mean number of broiler per cycle was 550.82 ± 76 for a stocking density of 27.20 ± 6.64 birds per m 2 . In conclusion, broiler production in the Western highland is dominated by small-scale units with low level of biosecurity practices positively and significantly (p < 0.05) influenced by some production characteristics. To improve biosecurity practices in the area, efforts must focus on measures concerning "sanitation" and "traffic control" components of biosecurity.

Combining Restricted Grazing and Nitrification Inhibitors to Reduce Nitrogen Leaching on New Zealand Dairy Farms.

PubMed

Romera, Alvaro J; Cichota, Rogerio; Beukes, Pierre C; Gregorini, Pablo; Snow, Val O; Vogeler, Iris

2017-01-01

Intensification of pastoral dairy systems often means more nitrogen (N) leaching. A number of mitigation strategies have been proposed to reduce or reverse this trend. The main strategies focus on reducing the urinary N load onto pastures or reducing the rate of nitrification once the urine has been deposited. Restricted grazing is an example of the former and the use of nitrification inhibitors an example of the latter. A relevant concern is the cost effectiveness of these strategies, independently and jointly. To address this concern, we employed a modeling approach to estimate N leaching with and without the use of these mitigation options from a typical grazing dairy farm in New Zealand. Three restricted grazing options were modeled with and without a nitrification inhibitor (dicyandiamide, DCD) and the results were compared with a baseline farm (no restricted grazing, no inhibitor). Applying DCD twice a year, closely following the cows after an autumn and winter grazing round, has the potential to reduce annualized and farm-scale N leaching by ∼12%, whereas restricted grazing had leaching reductions ranging from 23 to 32%, depending on the timing of restricted grazing. Combining the two strategies resulted in leaching reductions of 31 to 40%. The abatement cost per kilogram of N leaching reduction was NZ$50 with DCD, NZ$32 to 37 for restricted grazing, and NZ$40 to 46 when the two were combined. For the range analyzed, all treatments indicated similar cost per percentage unit of mitigated N leaching, demonstrating that restricted grazing and nitrification inhibitors can be effective when used concurrently. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Climate-driven longitudinal trends in pasture-borne helminth infections of dairy cattle.

PubMed

Charlier, Johannes; Ghebretinsae, Aklilu H; Levecke, Bruno; Ducheyne, Els; Claerebout, Edwin; Vercruysse, Jozef

2016-12-01

Helminth parasites of grazing ruminants are highly prevalent globally and impact negatively on animal productivity and food security. There is a growing concern that climate change increases helminth disease frequency and intensity. In Europe, these concerns stem from case reports and theoretical life cycle models assessing the effects of climate change scenarios on helminth epidemiology. We believe this study is the first to investigate climate-driven trends in helminth infections of cattle on a cohort of randomly selected farms. One thousand, six hundred and eighty dairy farms were monitored over an 8year period for the two major helminth infections in temperate climate regions and climate-driven trends were investigated by multivariable linear mixed models. The general levels of exposure to Fasciola hepatica decreased over the study period while those to Ostertagia ostertagi increased, and this could at least be partially explained by meteorological factors (i.e. the number of rainy (precipitation >1mm) and warm days (average daily temperature >10°C) in a year). The longitudinal trends varied according to the altitude and the agricultural region of the farm. This study shows that longitudinal epidemiological data from sentinel farms combined with meteorological datasets can significantly contribute to understanding the effects of climate on infectious disease dynamics. When local environmental conditions are taken into account, the effects of climate change on disease dynamics can also be understood at more local scales. We recommend setting up a longitudinal sampling strategy across Europe in order to monitor climate-driven changes in helminth disease risk to inform adaptation strategies to promote animal health and productivity. Copyright © 2016 Australian Society for Parasitology. Published by Elsevier Ltd. All rights reserved.

Sustainable farming of the mealworm Tenebrio molitor for the production of food and feed.

PubMed

Grau, Thorben; Vilcinskas, Andreas; Joop, Gerrit

2017-09-26

The farming of edible insects is an alternative strategy for the production of protein-rich food and feed with a low ecological footprint. The industrial production of insect-derived protein is more cost-effective and energy-efficient than livestock farming or aquaculture. The mealworm Tenebrio molitor is economically among the most important species used for the large-scale conversion of plant biomass into protein. Here, we review the mass rearing of this species and its conversion into food and feed, focusing on challenges such as the contamination of food/feed products with bacteria from the insect gut and the risk of rapidly spreading pathogens and parasites. We propose solutions to prevent the outbreak of infections among farmed insects without reliance on antibiotics. Transgenerational immune priming and probiotic bacteria may provide alternative strategies for sustainable insect farming.

Efficiency of dairy farms participating and not participating in veterinary herd health management programs.

PubMed

Derks, Marjolein; Hogeveen, Henk; Kooistra, Sake R; van Werven, Tine; Tauer, Loren W

2014-12-01

This paper compares farm efficiencies between dairies who were participating in a veterinary herd health management (VHHM) program with dairies not participating in such a program, to determine whether participation has an association with farm efficiency. In 2011, 572 dairy farmers received a questionnaire concerning the participation and execution of a VHHM program on their farms. Data from the questionnaire were combined with farm accountancy data from 2008 through 2012 from farms that used calendar year accounting periods, and were analyzed using Stochastic Frontier Analysis (SFA). Two separate models were specified: model 1 was the basic stochastic frontier model (output: total revenue; input: feed costs, land costs, cattle costs, non-operational costs), without explanatory variables embedded into the efficiency component of the error term. Model 2 was an expansion of model 1 which included explanatory variables (number of FTE; total kg milk delivered; price of concentrate; milk per hectare; cows per FTE; nutritional yield per hectare) inserted into the efficiency component of the joint error term. Both models were estimated with the financial parameters expressed per 100 kg fat and protein corrected milk and per cow. Land costs, cattle costs, feed costs and non-operational costs were statistically significant and positive in all models (P<0.01). Frequency distributions of the efficiency scores for the VHHM dairies and the non-VHHM dairies were plotted in a kernel density plot, and differences were tested using the Kolmogorov-Smirnov two-sample test. VHHM dairies had higher total revenue per cow, but not per 100 kg milk. For all SFA models, the difference in distribution was not statistically different between VHHM dairies and non-VHHM dairies (P values 0.94, 0.35, 0.95 and 0.89 for the basic and complete model per 100 kg fat and protein corrected milk and per cow respectively). Therefore we conclude that with our data farm participation in VHHM is not related to overall farm efficiency. Copyright © 2014 Elsevier B.V. All rights reserved.

Low- and High-Pathogenic Avian Influenza H5 and H7 Spread Risk Assessment Within and Between Australian Commercial Chicken Farms

PubMed Central

Scott, Angela Bullanday; Toribio, Jenny-Ann L. M. L.; Singh, Mini; Groves, Peter; Barnes, Belinda; Glass, Kathryn; Moloney, Barbara; Black, Amanda; Hernandez-Jover, Marta

2018-01-01

This study quantified and compared the probability of avian influenza (AI) spread within and between Australian commercial chicken farms via specified spread pathways using scenario tree mathematical modeling. Input values for the models were sourced from scientific literature, expert opinion, and a farm survey conducted during 2015 and 2016 on Australian commercial chicken farms located in New South Wales (NSW) and Queensland. Outputs from the models indicate that the probability of no establishment of infection in a shed is the most likely end-point after exposure and infection of low-pathogenic avian influenza (LPAI) in one chicken for all farm types (non-free range meat chicken, free range meat chicken, cage layer, barn layer, and free range layer farms). If LPAI infection is established in a shed, LPAI is more likely to spread to other sheds and beyond the index farm due to a relatively low probability of detection and reporting during LPAI infection compared to high-pathogenic avian influenza (HPAI) infection. Among farm types, the median probability for HPAI spread between sheds and between farms is higher for layer farms (0.0019, 0.0016, and 0.0031 for cage, barn, and free range layer, respectively) than meat chicken farms (0.00025 and 0.00043 for barn and free range meat chicken, respectively) due to a higher probability of mutation in layer birds, which relates to their longer production cycle. The pathway of LPAI spread between sheds with the highest average median probability was spread via equipment (0.015; 5–95%, 0.0058–0.036) and for HPAI spread between farms, the pathway with the highest average median probability was spread via egg trays (3.70 × 10−5; 5–95%, 1.47 × 10−6–0.00034). As the spread model did not explicitly consider volume and frequency of the spread pathways, these results provide a comparison of spread probabilities per pathway. These findings highlight the importance of performing biosecurity practices to limit spread of the AI virus. The models can be updated as new information on the mechanisms of the AI virus and on the volume and frequency of movements shed-to-shed and of movements between commercial chicken farms becomes available. PMID:29686993

Low- and High-Pathogenic Avian Influenza H5 and H7 Spread Risk Assessment Within and Between Australian Commercial Chicken Farms.

PubMed

Scott, Angela Bullanday; Toribio, Jenny-Ann L M L; Singh, Mini; Groves, Peter; Barnes, Belinda; Glass, Kathryn; Moloney, Barbara; Black, Amanda; Hernandez-Jover, Marta

2018-01-01

This study quantified and compared the probability of avian influenza (AI) spread within and between Australian commercial chicken farms via specified spread pathways using scenario tree mathematical modeling. Input values for the models were sourced from scientific literature, expert opinion, and a farm survey conducted during 2015 and 2016 on Australian commercial chicken farms located in New South Wales (NSW) and Queensland. Outputs from the models indicate that the probability of no establishment of infection in a shed is the most likely end-point after exposure and infection of low-pathogenic avian influenza (LPAI) in one chicken for all farm types (non-free range meat chicken, free range meat chicken, cage layer, barn layer, and free range layer farms). If LPAI infection is established in a shed, LPAI is more likely to spread to other sheds and beyond the index farm due to a relatively low probability of detection and reporting during LPAI infection compared to high-pathogenic avian influenza (HPAI) infection. Among farm types, the median probability for HPAI spread between sheds and between farms is higher for layer farms (0.0019, 0.0016, and 0.0031 for cage, barn, and free range layer, respectively) than meat chicken farms (0.00025 and 0.00043 for barn and free range meat chicken, respectively) due to a higher probability of mutation in layer birds, which relates to their longer production cycle. The pathway of LPAI spread between sheds with the highest average median probability was spread via equipment (0.015; 5-95%, 0.0058-0.036) and for HPAI spread between farms, the pathway with the highest average median probability was spread via egg trays (3.70 × 10 -5 ; 5-95%, 1.47 × 10 -6 -0.00034). As the spread model did not explicitly consider volume and frequency of the spread pathways, these results provide a comparison of spread probabilities per pathway. These findings highlight the importance of performing biosecurity practices to limit spread of the AI virus. The models can be updated as new information on the mechanisms of the AI virus and on the volume and frequency of movements shed-to-shed and of movements between commercial chicken farms becomes available.

Environmental risk perception, environmental concern and propensity to participate in organic farming programmes.

PubMed

Toma, Luiza; Mathijs, Erik

2007-04-01

This paper aims to identify the factors underlying farmers' propensity to participate in organic farming programmes in a Romanian rural region that confronts non-point source pollution. For this, we employ structural equation modelling with latent variables using a specific data set collected through an agri-environmental farm survey in 2001. The model includes one 'behavioural intention' latent variable ('propensity to participate in organic farming programmes') and five 'attitude' and 'socio-economic' latent variables ('socio-demographic characteristics', 'economic characteristics', 'agri-environmental information access', 'environmental risk perception' and 'general environmental concern'). The results indicate that, overall, the model has an adequate fit to the data. All loadings are statistically significant, supporting the theoretical basis for assignment of indicators for each latent variable. The significance tests for the structural model parameters show 'environmental risk perception' as the strongest determinant of farmers' propensity to participate in organic farming programmes.

Field Scale Groundwater Nitrate Loading Model for the Central Valley, California, 1945-Current

NASA Astrophysics Data System (ADS)

Harter, T.; Dzurella, K.; Bell, A.; Kourakos, G.

2015-12-01

Anthropogenic groundwater nitrate contamination in the Central Valley aquifer system, California, is widespread, with over 40% of domestic wells in some counties exceeding drinking water standards. Sources of groundwater nitrate include leaky municipal wastewater systems, municipal wastewater recharge, onsite wastewater treatment (septic) systems, atmospheric nitrogen deposition, animal farming, application of organic waste materials (sludge, biosolids, animal manure) to agricultural lands, and synthetic fertilizer. At the site or field scale, nitrogen inputs to the landscape are balanced by plant nitrogen uptake and harvest, atmospheric nitrogen losses, surface runoff of nitrogen, soil nitrogen storage changes, and leaching to groundwater. Irrigated agriculture is a dominant player in the Central Valley nitrogen cycle: The largest nitrogen fluxes are synthetic fertilizer and animal manure applications to cropland, crop nitrogen uptake, and groundwater nitrogen losses. We construct a historic field/parcel scale groundwater nitrogen loading model distinguishing urban and residential areas, individual animal farming areas, leaky wastewater lagoons, and approximately 50 different categories of agricultural crops. For non-agricultural landuses, groundwater nitrate loading is based on reported leaching values, animal population, and human population. For cropland, groundwater nitrate loading is computed from mass balance, taking into account diverse and historically changing management practices between different crops. Groundwater nitrate loading is estimated for 1945 to current. Significant increases in groundwater nitrate loading are associated with the expansion of synthetic fertilizer use in the 1950s to 1970s. Nitrate loading from synthetic fertilizer use has stagnated over the past 20 years due to improvements in nutrient use efficiency. However, an unbroken 60 year exponential increase in dairy production until the late 2000s has significantly impacted the nitrogen imbalance and is a significant threat to future groundwater quality in the Central Valley system. The model provides the basis for evaluating future planning scenarios to develop and assess long-term solutions for sustainable groundwater quality management.Anthropogenic groundwater nitrate contamination in the Central Valley aquifer system, California, is widespread, with over 40% of domestic wells in some counties exceeding drinking water standards. Sources of groundwater nitrate include leaky municipal wastewater systems, municipal wastewater recharge, onsite wastewater treatment (septic) systems, atmospheric nitrogen deposition, animal farming, application of organic waste materials (sludge, biosolids, animal manure) to agricultural lands, and synthetic fertilizer. At the site or field scale, nitrogen inputs to the landscape are balanced by plant nitrogen uptake and harvest, atmospheric nitrogen losses, surface runoff of nitrogen, soil nitrogen storage changes, and leaching to groundwater. Irrigated agriculture is a dominant player in the Central Valley nitrogen cycle: The largest nitrogen fluxes are synthetic fertilizer and animal manure applications to cropland, crop nitrogen uptake, and groundwater nitrogen losses. We construct a historic field/parcel scale groundwater nitrogen loading model distringuishing urban and residential areas, individual animal farming areas, leaky wastewater lagoons, and approximately 50 different categories of agricultural crops. For non-agricultural landuses, groundwater nitrate loading is based on reported leaching values, animal population, and human population. For cropland, groundwater nitrate loading is computed from mass balance, taking into account diverse and historically changing management practices between different crops. Groundwater nitrate loading is estimated for 1945 to current. Significant increases in groundwater nitrate loading are associated with the expansion of synthetic fertilizer use in the 1950s to 1970s. Nitrate loading from synthetic fertilizer use has stagnated over the past 20 years due to improvements in nutrient use efficiency. However, an unbroken 60 year exponential increase in dairy production until the late 2000s has significantly impacted the nitrogen imbalance and is a significant threat to future groundwater quality in the Central Valley system. The model provides the basis for evaluating future planning scenarios to develop and assess long-term solutions for sustainable groundwater quality management.

Coping with climate variability and long-term climate trends for Nicaraguan maize-bean farmers (Invited)

NASA Astrophysics Data System (ADS)

Gourdji, S.; Zelaya Martinez, C.; Martinez Valle, A.; Mejia, O.; Laderach, P.; Lobell, D. B.

2013-12-01

Climate variability and change impact farmers at different timescales, but both are of concern for livelihoods and long-term viability of small farms in tropical, rain-fed agricultural systems. This study uses a historical dataset to analyze the impact of 40-year climate trends in Nicaragua on bean production, a staple crop that is an important source of calories and protein in the local diet, particularly in rural areas and in lower income classes. Bean yields are sensitive to rising temperatures, but also frequently limited by seasonal drought and low soil fertility. We use an empirical model to relate department-level yields to spatial variation and inter-annual fluctuations in historical precipitation, temperature and extreme rain events. We then use this model to quantify the impact on yields of long-term observed warming in day and night temperatures, increases in rainfall intensity, longer gaps between rain events, a shorter rainy season and overall drying in certain regions of the country. Preliminary results confirm the negative impacts of warming night temperatures, higher vapor pressure deficits, and longer gaps between rain events on bean yields, although some drying at harvest time has helped to reduce rotting. Across all bean-growing areas, these climate trends have led to a ~10% yield decline per decade relative to a stationary climate and production system, with this decline reaching up to ~20% in the dry northern highlands. In regions that have been particularly impacted by these trends, we look for evidence of farm abandonment, increases in off-farm employment, or on-farm adaptation solutions through crop diversification, use of drought or heat-tolerant seed, and adoption of rainwater harvesting. We will also repeat the modeling exercise for maize, another staple crop providing ~25% of daily calories at the national scale, but which is projected to be more resilient to climate trends.

Prevalence and potential risk factors for the occurrence of cefotaxime resistant Escherichia coli in German fattening pig farms--a cross-sectional study.

PubMed

Hering, Johanna; Hille, Katja; Frömke, Cornelia; von Münchhausen, Christiane; Hartmann, Maria; Schneider, Bettina; Friese, Anika; Roesler, Uwe; Merle, Roswitha; Kreienbrock, Lothar

2014-09-01

A cross-sectional study concerning farm prevalence and risk factors for the count of cefotaxime resistant Escherichia coli (E. coli) (CREC) positive samples per sampling group on German fattening pig farms was performed in 2011 and 2012. Altogether 48 farms in four agricultural regions in the whole of Germany were investigated. Faecal samples, boot swabs and dust samples from two sampling groups per farm were taken and supplemental data were collected using a questionnaire. On 85% of the farms, at least one sample contained cefotaxime resistant E. coli colonies. Positive samples were more frequent in faeces (61%) and boot swabs (54%) than in dust samples (11%). Relevant variables from the questionnaire were analysed in a univariable mixed effect Poisson regression model. Variables that were related to the number (risk) of positive samples per sampling group with a p-value <0.2 were entered in a multivariable model. This model was reduced to statistically significant variables via backward selection. Factors that increased the risk for positive samples involved farm management and hygienic aspects. Farms that had a separate pen for diseased pigs had a 2.8 higher mean count of positive samples (95%-CI [1.71; 4.58], p=0.001) than farms without an extra pen. The mean count was increased on farms with under-floor exhaust ventilation compared to farms with over floor ventilation (2.22 [1.43; 3.46], p=0.001) and more positive samples were observed on farms that controlled flies with toxin compared to farms that did not (1.86 [1.24; 2.78], p=0.003). It can be concluded, that CREC are wide spread on German fattening pig farms. In addition the explorative approach of the present study suggests an influence of management strategies on the occurrence of cefotaxime resistant E. coli. Copyright © 2014 Elsevier B.V. All rights reserved.

Optimal feeding systems for small-scale dairy herds in the North West Province, South Africa.

PubMed

Manzana, N Patience; McCrindle, Cheryl M E; Sebei, P Julius; Prozesky, Leon

2014-07-09

Land redistribution was legislated in 1994; it was designed to resolve historical imbalances inland ownership in South Africa. Between 2002 and 2006, a longitudinal observational studywas conducted with 15 purposively selected small-scale dairy farmers in a land redistributionproject in Central North West Province. Four farmers left the project over the period. For thepurposes of this study, a small-scale dairy farm was defined as a farm that produces less than500 L of milk a day, irrespective of the number of cows or size of the farm. The study wasconducted in three phases. In the first phase, situational analysis using participatory ruralappraisal (PRA) and observation was used to outline the extent of the constraints and designappropriate interventions. Feeds that were used were tested and evaluated. In the secondphase, three different feeding systems were designed from the data obtained from PRA. Thesewere: (1) A semi-intensive farm-based ration using available crops, pastures and crop residueswith minimal rations purchased. (2) An intensive, zero-grazing dairy system using a totalmixed ration. (3) A traditional, extensive or dual-purpose system, where the calf drank fromthe cow until weaning and milking was done only once a day. In the third phase, adoptionwas monitored. By July 2006, all remaining farmers had changed to commercially formulatedrations or licks and the body condition score of the cows had improved. It was concluded thatveterinary extension based on PRA and a holistic systems approach was a good option forsuch complex problems. Mentoring by commercial dairy farmers, veterinary and extensionservices appeared to be viable. Further research should be done to optimise the traditionalmodel of dairy farming, as this was relatively profitable, had a lower risk and was less labourintensive.

Potential benefits of farm scale measures versus landscape measures for reducing nitrate loads in a Danish catchment.

PubMed

Hashemi, Fatemeh; Olesen, Jørgen E; Børgesen, Christen D; Tornbjerg, Henrik; Thodsen, Hans; Dalgaard, Tommy

2018-05-08

To comply with the EU Water Framework Directive, Denmark must further reduce the nitrate (N)-load to marine ecosystems from agricultural areas. Under the anticipated future spatially targeted regulation, the required N-load reductions will differ between catchments, and these are expected to be mitigated by a combination of land and water management measures. Here, we explored how the expected N-load reduction target of 38% for a Danish catchment (River Odense) could be achieved through a combination of farm and landscape measures. These include: (a) N-leaching reduction through changing the crop rotation and applying cover crops, (b) enhancing N-reduction through (re)establishment of wetlands, and (c) reducing N-leaching through spatially targeting of set-aside to high N-load areas. Changes in crop rotations were effective in reducing N-leaching by growing crops with a longer growing season and by allowing a higher use of cover crops. A combination of wetlands and changes in crop rotations were needed for reaching the N-load reduction target without use of set-aside. However, not all combinations of wetlands and crop rotation changes achieved the required N-load reduction, resulting in a need for targeted set-aside, implying a need for balancing measures at farm and landscape scale to maximize N load reduction while minimizing loss of productive land. The effectiveness of farm scale measures is affected by farm and soil types as well as by N-reduction in groundwater, while the possibilities for using wetlands for decreasing the N-load depends on landscape features, allowing the establishment of wetlands connected to streams and rivers. Copyright © 2018 Elsevier B.V. All rights reserved.

Multiperiod planning tool for multisite pig production systems.

PubMed

Nadal-Roig, E; Plà, L M

2014-09-01

This paper presents a multiperiod planning tool for multisite pig production systems based on Linear Programming (LP). The aim of the model is to help pig managers of multisite systems in making short-term decisions (mainly related to pig transfers between farms and batch management in fattening units) and mid-term or long-term decisions (according to company targets and expansion strategy). The model skeleton follows the structure of a three-site system that can be adapted to any multisite system present in the modern pig industry. There are three basic phases, namely, piglet production, rearing pigs, and fattening. Each phase involves a different set of farms; therefore, transportation between farms and delivering of pigs to the abattoir are under consideration. The model maximizes the total gross margin calculated from the income of sales to the abattoir and the production costs over the time horizon considered. Production cost depends on each type of farm involved in the process. Parameters like number of farms per phase and distance, farm capacity, reproduction management policies, feeding and veterinary expenses, and transportation costs are taken into account. The model also provides a schedule of transfers between farms in terms of animals to be transported and number of trucks involved. The use of the model is illustrated with a case study based on a real instance of a company located in Catalonia (Spain).

Building a stakeholder's vision of an offshore wind-farm project: A group modeling approach.

PubMed

Château, Pierre-Alexandre; Chang, Yang-Chi; Chen, Hsin; Ko, Tsung-Ting

2012-03-15

This paper describes a Group Model Building (GMB) initiative that was designed to discuss the various potential effects that an offshore wind-farm may have on its local ecology and socioeconomic development. The representatives of various organizations in the study area, Lu-Kang, Taiwan, have held several meetings, and structured debates have been organized to promote the emergence of a consensual view on the main issues and their implications. A System Dynamics (SD) model has been built and corrected iteratively with the participants through the GMB process. The diverse interests within the group led the process toward the design of multifunctional wind-farms with different modalities. The scenario analyses, using the SD model under various policies, including no wind-farm policy, objectively articulates the vision of the local stakeholders. The results of the SD simulations show that the multifunctional wind-farms may have superior economic effects and the larger wind-farms with bird corridors could reduce ecological impact. However, the participants of the modeling process did not appreciate any type of offshore wind-farm development when considering all of the identified key factors of social acceptance. The insight gained from the study can provide valuable information to actualize feasible strategies for the green energy technique to meet local expectations. Copyright © 2012 Elsevier B.V. All rights reserved.

Wind Farms in Rural Areas: How Far Do Community Benefits from Wind Farms Represent a Local Economic Development Opportunity?

ERIC Educational Resources Information Center

Munday, Max; Bristow, Gill; Cowell, Richard

2011-01-01

Although the large-scale deployment of renewable technologies can bring significant, localised economic and environmental changes, there has been remarkably little empirical investigation of the rural development implications. This paper seeks to redress this through an analysis of the economic development opportunities surrounding wind energy…

Gender differences in use of hearing protection devices among farm operators.

PubMed

McCullagh, Marjorie C; Banerjee, Tanima; Yang, James J; Bernick, Janice; Duffy, Sonia; Redman, Richard

2016-01-01

Although farm operators have frequent exposure to hazardous noise and high rates of noise-induced hearing loss, they have low use of hearing protection devices (HPDs). Women represent about one-third of farm operators, and their numbers are climbing. However, among published studies examining use of HPDs in this worker group, none have examined gender-related differences. The purpose of this study was to examine gender-related differences in use of hearing protection and related predictors among farm operators. Data previously collected at farm shows and by telephone were analyzed using t-tests and generalized linear model with zero inflated negative binomial (ZINB) distribution. The difference in rate of hearing protector use between men and women farm operators was not significant. There was no difference between men and women in most hearing protector-related attitudes and beliefs. Although men and women farm operators had similar rates of use of hearing protectors when working in high-noise environments, attitudes about HPD use differed. Specifically, interpersonal role modeling was a predictor of HPD use among women, but not for men. This difference suggests that while farm operators of both genders may benefit from interventions designed to reduce barriers to HPD use (e.g., difficulty communicating with co-workers and hearing warning sounds), farm women have unique needs in relation to cognitive-perceptual factors that predict HPD use. Women farm operators may lack role models for use of HPDs (e.g., in peers and advertising), contributing to their less frequent use of protection.

Farming for Ecosystem Services: An Ecological Approach to Production Agriculture

PubMed Central

Philip Robertson, G.; Gross, Katherine L.; Hamilton, Stephen K.; Landis, Douglas A.; Schmidt, Thomas M.; Snapp, Sieglinde S.; Swinton, Scott M.

2014-01-01

A balanced assessment of ecosystem services provided by agriculture requires a systems-level socioecological understanding of related management practices at local to landscape scales. The results from 25 years of observation and experimentation at the Kellogg Biological Station long-term ecological research site reveal services that could be provided by intensive row-crop ecosystems. In addition to high yields, farms could be readily managed to contribute clean water, biocontrol and other biodiversity benefits, climate stabilization, and long-term soil fertility, thereby helping meet society's need for agriculture that is economically and environmentally sustainable. Midwest farmers—especially those with large farms—appear willing to adopt practices that deliver these services in exchange for payments scaled to management complexity and farmstead benefit. Surveyed citizens appear willing to pay farmers for the delivery of specific services, such as cleaner lakes. A new farming for services paradigm in US agriculture seems feasible and could be environmentally significant. PMID:26955069

Gradient-Based Optimization of Wind Farms with Different Turbine Heights: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stanley, Andrew P. J.; Thomas, Jared; Ning, Andrew

Turbine wakes reduce power production in a wind farm. Current wind farms are generally built with turbines that are all the same height, but if wind farms included turbines with different tower heights, the cost of energy (COE) may be reduced. We used gradient-based optimization to demonstrate a method to optimize wind farms with varied hub heights. Our study includes a modified version of the FLORIS wake model that accommodates three-dimensional wakes integrated with a tower structural model. Our purpose was to design a process to minimize the COE of a wind farm through layout optimization and varying turbine hubmore » heights. Results indicate that when a farm is optimized for layout and height with two separate height groups, COE can be lowered by as much as 5%-9%, compared to a similar layout and height optimization where all the towers are the same. The COE has the best improvement in farms with high turbine density and a low wind shear exponent.« less

Gradient-Based Optimization of Wind Farms with Different Turbine Heights

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stanley, Andrew P. J.; Thomas, Jared; Ning, Andrew

Turbine wakes reduce power production in a wind farm. Current wind farms are generally built with turbines that are all the same height, but if wind farms included turbines with different tower heights, the cost of energy (COE) may be reduced. We used gradient-based optimization to demonstrate a method to optimize wind farms with varied hub heights. Our study includes a modified version of the FLORIS wake model that accommodates three-dimensional wakes integrated with a tower structural model. Our purpose was to design a process to minimize the COE of a wind farm through layout optimization and varying turbine hubmore » heights. Results indicate that when a farm is optimized for layout and height with two separate height groups, COE can be lowered by as much as 5%-9%, compared to a similar layout and height optimization where all the towers are the same. The COE has the best improvement in farms with high turbine density and a low wind shear exponent.« less

Technical indicators of economic performance in dairy sheep farming.

PubMed

Theodoridis, A; Ragkos, A; Roustemis, D; Arsenos, G; Abas, Z; Sinapis, E

2014-01-01

In this study, the level of technical efficiency of 58 sheep farms rearing the Chios breed in Greece was measured through the application of the stochastic frontier analysis method. A Translog stochastic frontier production function was estimated using farm accounting data of Chios sheep farms and the impact of various socio-demographic and biophysical factors on the estimated efficiency of the farms was evaluated. The farms were classified into efficiency groups on the basis of the estimated level of efficiency and a technical and economic descriptive analysis was applied in order to illustrate an indicative picture of their structure and productivity. The results of the stochastic frontier model indicate that there are substantial production inefficiencies among the Chios sheep farms and that these farms could increase their production through the improvement of technical efficiency, whereas the results of the inefficiency effects model reveal that the farm-specific explanatory factors can partly explain the observed efficiency differentials. The measurement of technical inefficiency and the detection of its determinants can be used to form the basis of policy recommendations that could contribute to the development of the sector.

Using biological-physical modelling for informing sea lice dispersal in Loch Linnhe, Scotland.

PubMed

Salama, N K G; Dale, A C; Ivanov, V V; Cook, P F; Pert, C C; Collins, C M; Rabe, B

2018-06-01

Sea lice are a constraint on the sustainable growth of Scottish marine salmonid aquaculture. As part of an integrated pest management approach, farms coordinate procedures within spatial units. We present observations of copepodids being at relatively greater density than nauplii in upper waters, which informs the development of surface layer sea lice transmission modelling of Loch Linnhe, Scotland, for informing farm parasite management. A hydrodynamic model is coupled with a biological particle-tracking model, with characteristics of plankton sea lice. Simulations are undertaken for May and October 2011-2013, forced by local wind data collected for those periods. Particles are continually released from positions representing farm locations, weighted by relative farm counts, over a 2-week period and tracked for a further 5 days. A comparison is made between modelled relative concentrations against physical and biological surveys to provide confidence in model outputs. Connectivity between farm locations is determined in order to propose potential coordination areas. Generally, connectivity depends on flow patterns in the loch and decreases with increased farm separation. The connectivity indices are used to estimate the origins of the sea lice population composition at each site, which may influence medicinal regimens to avoid loss of efficacy. © 2017 John Wiley & Sons Ltd.

Antibiotic Resistance in Animal and Environmental Samples Associated with Small-Scale Poultry Farming in Northwestern Ecuador

PubMed Central

Braykov, Nikolay P.; Eisenberg, Joseph N. S.; Grossman, Marissa; Zhang, Lixin; Vasco, Karla; Cevallos, William; Muñoz, Diana; Acevedo, Andrés; Moser, Kara A.; Marrs, Carl F.; Trostle, James; Trueba, Gabriel

2016-01-01

ABSTRACT The effects of animal agriculture on the spread of antibiotic resistance (AR) are cross-cutting and thus require a multidisciplinary perspective. Here we use ecological, epidemiological, and ethnographic methods to examine populations of Escherichia coli circulating in the production poultry farming environment versus the domestic environment in rural Ecuador, where small-scale poultry production employing nontherapeutic antibiotics is increasingly common. We sampled 262 “production birds” (commercially raised broiler chickens and laying hens) and 455 “household birds” (raised for domestic use) and household and coop environmental samples from 17 villages between 2010 and 2013. We analyzed data on zones of inhibition from Kirby-Bauer tests, rather than established clinical breakpoints for AR, to distinguish between populations of organisms. We saw significantly higher levels of AR in bacteria from production versus household birds; resistance to either amoxicillin-clavulanate, cephalothin, cefotaxime, and gentamicin was found in 52.8% of production bird isolates and 16% of household ones. A strain jointly resistant to the 4 drugs was exclusive to a subset of isolates from production birds (7.6%) and coop surfaces (6.5%) and was associated with a particular purchase site. The prevalence of AR in production birds declined with bird age (P < 0.01 for all antibiotics tested except tetracycline, sulfisoxazole, and trimethoprim-sulfamethoxazole). Farming status did not impact AR in domestic environments at the household or village level. Our results suggest that AR associated with small-scale poultry farming is present in the immediate production environment and likely originates from sources outside the study area. These outside sources might be a better place to target control efforts than local management practices. IMPORTANCE In developing countries, small-scale poultry farming employing antibiotics as growth promoters is being advanced as an inexpensive source of protein and income. Here, we present the results of a large ecoepidemiological study examining patterns of antibiotic resistance (AR) in E. coli isolates from small-scale poultry production environments versus domestic environments in rural Ecuador, where such backyard poultry operations have become established over the past decade. Our previous research in the region suggests that introduction of AR bacteria through travel and commerce may be an important source of AR in villages of this region. This report extends the prior analysis by examining small-scale production chicken farming as a potential source of resistant strains. Our results suggest that AR strains associated with poultry production likely originate from sources outside the study area and that these outside sources might be a better place to target control efforts than local management practices. PMID:27303705

An R package for simulating growth and organic wastage in aquaculture farms in response to environmental conditions and husbandry practices

PubMed Central

Baldan, Damiano; Porporato, Erika Maria Diletta; Pastres, Roberto

2018-01-01

A new R software package, RAC, is presented. RAC allows to simulate the rearing cycle of 4 species, finfish and shellfish, highly important in terms of production in the Mediterranean Sea. The package works both at the scale of the individual and of the farmed population. Mathematical models included in RAC were all validated in previous works, and account for growth and metabolism, based on input data characterizing the forcing functions—water temperature, and food quality/quantity. The package provides a demo dataset of forcings for each species, as well as a typical set of husbandry parameters for Mediterranean conditions. The present work illustrates RAC main features, and its current capabilities/limitations. Three test cases are presented as a proof of concept of RAC applicability, and to demonstrate its potential for integrating different open products nowadays provided by remote sensing and operational oceanography. PMID:29723208

Analysis of near-surface relative humidity in a wind turbine array boundary layer using an instrumented unmanned aerial system and large-eddy simulation

NASA Astrophysics Data System (ADS)

Adkins, Kevin; Elfajri, Oumnia; Sescu, Adrian

2016-11-01

Simulation and modeling have shown that wind farms have an impact on the near-surface atmospheric boundary layer (ABL) as turbulent wakes generated by the turbines enhance vertical mixing. These changes alter downstream atmospheric properties. With a large portion of wind farms hosted within an agricultural context, changes to the environment can potentially have secondary impacts such as to the productivity of crops. With the exception of a few observational data sets that focus on the impact to near-surface temperature, little to no observational evidence exists. These few studies also lack high spatial resolution due to their use of a limited number of meteorological towers or remote sensing techniques. This study utilizes an instrumented small unmanned aerial system (sUAS) to gather in-situ field measurements from two Midwest wind farms, focusing on the impact that large utility-scale wind turbines have on relative humidity. Results are also compared to numerical experiments conducted using large eddy simulation (LES). Wind turbines are found to differentially alter the relative humidity in the downstream, spanwise and vertical directions under a variety of atmospheric stability conditions.

Environmentally sustainable production of food, feed and fuel from natural resources in the tropics.

PubMed

Preston, T Reg

2009-08-01

Responding to the challenges posed by global warming, peak oil and biofuels will require a paradigm shift in the practice of agriculture and in the role of live stock within the farming system. Farming systems should aim at maximizing plant biomass production from locally available diversified resources, processing of the biomass on farm to provide food, feed and energy and recycling of all waste materials. The approach that is the subject of this paper is that the generation of electricity can be a by-product of food/feed production. The concept is the fractionation of biomass into inedible cell wall material that can be converted to an inflammable gas by gasification, the gas in turn being the source of fuel for internal combustion engines driving electrical generators. The cell contents and related structures such as tree leaves are used as human food or animal feed. As well as providing food and feed the model is highly appropriate for decentralized small scale production of electricity in rural areas. It also offers opportunities for sequestration of carbon in the form of biochar the solid residue remaining after gasification of the biomass.

Towards a mature offshore wind energy technology - guidelines from the opti-OWECS project

NASA Astrophysics Data System (ADS)

Kühn, M.; Bierbooms, W. A. A. M.; van Bussel, G. J. W.; Cockerill, T. T.; Harrison, R.; Ferguson, M. C.; Göransson, B.; Harland, L. A.; Vugts, J. H.; Wiecherink, R.

1999-01-01

The article reviews the main results of the recent European research project Opti-OWECS (Structural and Economic Optimisation of Bottom-Mounted Offshore Wind Energy Converters'), which has significantly improved the understanding of the requirements for a large-scale utilization of offshore wind energy. An integrated design approach was demonstrated for a 300 MW offshore wind farm at a demanding North Sea site. Several viable solutions were obtained and one was elaborated to include the design of all major components. Simultaneous structural and economic optimization took place during the different design stages. An offshore wind energy converter founded on a soft-soft monopile was tailored with respect to the distinct characteristics of dynamic wind and wave loading. The operation and maintenance behaviour of the wind farm was analysed by Monte Carlo simulations. With an optimized maintenance strategy and suitable hardware a high availability was achieved. Based upon the experience from the structural design, cost models for offshore wind farms were developed and linked to a European database of the offshore wind energy potential. This enabled the first consistent estimate of cost of offshore wind energy for entire European regions.

Low Pathogenic Avian Influenza Exposure Risk Assessment in Australian Commercial Chicken Farms.

PubMed

Scott, Angela Bullanday; Toribio, Jenny-Ann; Singh, Mini; Groves, Peter; Barnes, Belinda; Glass, Kathryn; Moloney, Barbara; Black, Amanda; Hernandez-Jover, Marta

2018-01-01

This study investigated the pathways of exposure to low pathogenic avian influenza (LPAI) virus among Australian commercial chicken farms and estimated the likelihood of this exposure occurring using scenario trees and a stochastic modeling approach following the World Organization for Animal Health methodology for risk assessment. Input values for the models were sourced from scientific literature and an on-farm survey conducted during 2015 and 2016 among Australian commercial chicken farms located in New South Wales and Queensland. Outputs from the models revealed that the probability of a first LPAI virus exposure to a chicken in an Australian commercial chicken farms from one wild bird at any point in time is extremely low. A comparative assessment revealed that across the five farm types (non-free-range meat chicken, free-range meat chicken, cage layer, barn layer, and free range layer farms), free-range layer farms had the highest probability of exposure (7.5 × 10 -4 ; 5% and 95%, 5.7 × 10 -4 -0.001). The results indicate that the presence of a large number of wild birds on farm is required for exposure to occur across all farm types. The median probability of direct exposure was highest in free-range farm types (5.6 × 10 -4 and 1.6 × 10 -4 for free-range layer and free-range meat chicken farms, respectively) and indirect exposure was highest in non-free-range farm types (2.7 × 10 -4 , 2.0 × 10 -4 , and 1.9 × 10 -4 for non-free-range meat chicken, cage layer, and barn layer farms, respectively). The probability of exposure was found to be lowest in summer for all farm types. Sensitivity analysis revealed that the proportion of waterfowl among wild birds on the farm, the presence of waterfowl in the range and feed storage areas, and the prevalence of LPAI in wild birds are the most influential parameters for the probability of Australian commercial chicken farms being exposed to avian influenza (AI) virus. These results highlight the importance of ensuring good biosecurity on farms to minimize the risk of exposure to AI virus and the importance of continuous surveillance of LPAI prevalence including subtypes in wild bird populations.

Low Pathogenic Avian Influenza Exposure Risk Assessment in Australian Commercial Chicken Farms

PubMed Central

Scott, Angela Bullanday; Toribio, Jenny-Ann; Singh, Mini; Groves, Peter; Barnes, Belinda; Glass, Kathryn; Moloney, Barbara; Black, Amanda; Hernandez-Jover, Marta

2018-01-01

This study investigated the pathways of exposure to low pathogenic avian influenza (LPAI) virus among Australian commercial chicken farms and estimated the likelihood of this exposure occurring using scenario trees and a stochastic modeling approach following the World Organization for Animal Health methodology for risk assessment. Input values for the models were sourced from scientific literature and an on-farm survey conducted during 2015 and 2016 among Australian commercial chicken farms located in New South Wales and Queensland. Outputs from the models revealed that the probability of a first LPAI virus exposure to a chicken in an Australian commercial chicken farms from one wild bird at any point in time is extremely low. A comparative assessment revealed that across the five farm types (non-free-range meat chicken, free-range meat chicken, cage layer, barn layer, and free range layer farms), free-range layer farms had the highest probability of exposure (7.5 × 10−4; 5% and 95%, 5.7 × 10−4—0.001). The results indicate that the presence of a large number of wild birds on farm is required for exposure to occur across all farm types. The median probability of direct exposure was highest in free-range farm types (5.6 × 10−4 and 1.6 × 10−4 for free-range layer and free-range meat chicken farms, respectively) and indirect exposure was highest in non-free-range farm types (2.7 × 10−4, 2.0 × 10−4, and 1.9 × 10−4 for non-free-range meat chicken, cage layer, and barn layer farms, respectively). The probability of exposure was found to be lowest in summer for all farm types. Sensitivity analysis revealed that the proportion of waterfowl among wild birds on the farm, the presence of waterfowl in the range and feed storage areas, and the prevalence of LPAI in wild birds are the most influential parameters for the probability of Australian commercial chicken farms being exposed to avian influenza (AI) virus. These results highlight the importance of ensuring good biosecurity on farms to minimize the risk of exposure to AI virus and the importance of continuous surveillance of LPAI prevalence including subtypes in wild bird populations. PMID:29755987

Contamination in Ontario farmstead domestic wells and its association with agriculture:. 1. Results from drinking water wells

NASA Astrophysics Data System (ADS)

Goss, M. J.; Barry, D. A. J.; Rudolph, D. L.

1998-08-01

Groundwater provides about 30% of water requirements in Ontario, but farm families depend almost entirely on private wells. Major potential contaminants on farms are nitrate (NO 3-), pathogenic microorganisms, pesticides and petroleum derivatives. A survey of farm drinking-water wells was conducted throughout the Province of Ontario, Canada, in 1991 and 1992 and tested for these contaminants. The main objectives of the survey were to determine the quality and safety of drinking water for farm families, and determine the effect of agricultural management on groundwater quality at a provincial scale. Four farm wells were chosen in each township where >50% of the land area was used for agricultural production. Elsewhere one well per township was usually sampled. Within each township the types of farming activity and dominant soils were additional criteria for selection. The network comprised 1292 of the estimated 500,000 water-wells in Ontario, and the study conformed to a stratified random survey. A subset of 160 wells, chosen by farm type, soil, and the presence or absence of a fuel storage tank, was investigated for the presence of petroleum derivatives: benzene, toluene, ethyl benzene, and xylene. About 40% of farm wells tested contained one or more of the target contaminants above the maximum acceptable concentration; 34% of wells had more than the maximum acceptable number of coliform bacteria, 14% contained NO 3--N concentrations above 10 mg l -1 limit and about 7% were contaminated with both bacteria and NO 3-. Only six wells contained pesticide residues above the interim maximum acceptable concentration (IMAC), but pesticides were detected in 7% of wells in winter and in 11% in summer. No wells contained detectable petroleum derivatives. These results for NO 3- contamination were not significantly different from those reported for a survey of Ontario wells for the period 1950-1954, but the frequency of contamination by Escherichia coli was greater in the present study. None of the point sources investigated contributed significantly to the NO 3- contamination. The percentage of wells contaminated by coliform bacteria decreased significantly with increasing separation of the well from the feedlot or exercise yard on livestock farms. A full statistical model including the type of well construction, depth, age and soil hydrologic group was developed to describe the frequency of NO 3- contamination.

Review of Recent Development of Dynamic Wind Farm Equivalent Models Based on Big Data Mining

NASA Astrophysics Data System (ADS)

Wang, Chenggen; Zhou, Qian; Han, Mingzhe; Lv, Zhan’ao; Hou, Xiao; Zhao, Haoran; Bu, Jing

2018-04-01

Recently, the big data mining method has been applied in dynamic wind farm equivalent modeling. In this paper, its recent development with present research both domestic and overseas is reviewed. Firstly, the studies of wind speed prediction, equivalence and its distribution in the wind farm are concluded. Secondly, two typical approaches used in the big data mining method is introduced, respectively. For single wind turbine equivalent modeling, it focuses on how to choose and identify equivalent parameters. For multiple wind turbine equivalent modeling, the following three aspects are concentrated, i.e. aggregation of different wind turbine clusters, the parameters in the same cluster, and equivalence of collector system. Thirdly, an outlook on the development of dynamic wind farm equivalent models in the future is discussed.

Field Scale Optimization for Long-Term Sustainability of Best Management Practices in Watersheds

NASA Astrophysics Data System (ADS)

Samuels, A.; Babbar-Sebens, M.

2012-12-01

Agricultural and urban land use changes have led to disruption of natural hydrologic processes and impairment of streams and rivers. Multiple previous studies have evaluated Best Management Practices (BMPs) as means for restoring existing hydrologic conditions and reducing impairment of water resources. However, planning of these practices have relied on watershed scale hydrologic models for identifying locations and types of practices at scales much coarser than the actual field scale, where landowners have to plan, design and implement the practices. Field scale hydrologic modeling provides means for identifying relationships between BMP type, spatial location, and the interaction between BMPs at a finer farm/field scale that is usually more relevant to the decision maker (i.e. the landowner). This study focuses on development of a simulation-optimization approach for field-scale planning of BMPs in the School Branch stream system of Eagle Creek Watershed, Indiana, USA. The Agricultural Policy Environmental Extender (APEX) tool is used as the field scale hydrologic model, and a multi-objective optimization algorithm is used to search for optimal alternatives. Multiple climate scenarios downscaled to the watershed-scale are used to test the long term performance of these alternatives and under extreme weather conditions. The effectiveness of these BMPs under multiple weather conditions are included within the simulation-optimization approach as a criteria/goal to assist landowners in identifying sustainable design of practices. The results from these scenarios will further enable efficient BMP planning for current and future usage.

Preserving privacy whilst maintaining robust epidemiological predictions.

PubMed

Werkman, Marleen; Tildesley, Michael J; Brooks-Pollock, Ellen; Keeling, Matt J

2016-12-01

Mathematical models are invaluable tools for quantifying potential epidemics and devising optimal control strategies in case of an outbreak. State-of-the-art models increasingly require detailed individual farm-based and sensitive data, which may not be available due to either lack of capacity for data collection or privacy concerns. However, in many situations, aggregated data are available for use. In this study, we systematically investigate the accuracy of predictions made by mathematical models initialised with varying data aggregations, using the UK 2001 Foot-and-Mouth Disease Epidemic as a case study. We consider the scenario when the only data available are aggregated into spatial grid cells, and develop a metapopulation model where individual farms in a single subpopulation are assumed to behave uniformly and transmit randomly. We also adapt this standard metapopulation model to capture heterogeneity in farm size and composition, using farm census data. Our results show that homogeneous models based on aggregated data overestimate final epidemic size but can perform well for predicting spatial spread. Recognising heterogeneity in farm sizes improves predictions of the final epidemic size, identifying risk areas, determining the likelihood of epidemic take-off and identifying the optimal control strategy. In conclusion, in cases where individual farm-based data are not available, models can still generate meaningful predictions, although care must be taken in their interpretation and use. Copyright © 2016. Published by Elsevier B.V.

Modeling of In-stream Tidal Energy Development and its Potential Effects in Tacoma Narrows, Washington, USA

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Zhaoqing; Wang, Taiping; Copping, Andrea E.

Understanding and providing proactive information on the potential for tidal energy projects to cause changes to the physical system and to key water quality constituents in tidal waters is a necessary and cost-effective means to avoid costly regulatory involvement and late stage surprises in the permitting process. This paper presents a modeling study for evaluating the tidal energy extraction and its potential impacts on the marine environment in a real world site - Tacoma Narrows of Puget Sound, Washington State, USA. An unstructured-grid coastal ocean model, fitted with a module that simulates tidal energy devices, was applied to simulate themore » tidal energy extracted by different turbine array configurations and the potential effects of the extraction at local and system-wide scales in Tacoma Narrows and South Puget Sound. Model results demonstrated the advantage of an unstructured-grid model for simulating the far-field effects of tidal energy extraction in a large model domain, as well as assessing the near-field effect using a fine grid resolution near the tidal turbines. The outcome shows that a realistic near-term deployment scenario extracts a very small fraction of the total tidal energy in the system and that system wide environmental effects are not likely; however, near-field effects on the flow field and bed shear stress in the area of tidal turbine farm are more likely. Model results also indicate that from a practical standpoint, hydrodynamic or water quality effects are not likely to be the limiting factor for development of large commercial-scale tidal farms. Results indicate that very high numbers of turbines are required to significantly alter the tidal system; limitations on marine space or other environmental concerns are likely to be reached before reaching these deployment levels. These findings show that important information obtained from numerical modeling can be used to inform regulatory and policy processes for tidal energy development.« less

Impact of youth injuries on the uninsured farm family's economic viability.

PubMed

Zaloshnja, Eduard; Miller, Ted R

2012-01-01

The objective of this study is to estimate the impact of youth injuries on the uninsured farm family's economic viability. Using farm prototypes, we compared farm profits with costs of farm youth injuries. We built profit models for two types of farms, dairy and soybean farms. Then we estimated the cost impact of farm youth injuries of different levels of severity on a farm family with no health insurance. A severe child injury that requires at least 10 days of hospitalisation would cost almost equal to the operating profit of the average dairy farm with no health insurance and would turn the operating profit of the average soybean farm into a severe loss of $99,499. Prevention of child agricultural injuries would significantly improve the financial situation for farm families that lack health insurance.

Understanding Large Wind Farm Impacts on Regional Climate and Vegetation Growth from Observational and Modeling Perspectives

NASA Astrophysics Data System (ADS)

Xia, Geng

In the most recent decade, wind energy has experienced exponential growth worldwide and this rapid increase is expected to continue, particularly over farmlands in the United States. This poses an important question regarding whether the widespread deployment of wind turbines (WTs) will influence surface/near-surface microclimate and vegetation growth. In this dissertation, I investigate the potential wind farm (WF) impacts on regional climate and vegetation growth from both observational and modeling perspectives. High resolution satellite, radiosonde and field observations are used to determine the magnitude and variability of WF-induced changes on surface/near-surface temperatures while the Weather Research and Forecasting (WRF) model is used to simulate these changes in real-world WFs at regional scales and to uncover the physical processes behind the simulated temperature changes. First, the primary physical mechanisms controlling the seasonal and diurnal variations of WF impacts on land surface temperature (LST) are investigated by analyzing both satellite data and field observations. It is found that the turbine-induced turbulent kinetic energy (TKE) relative to the background TKE determines the magnitude and variability of such impacts. In addition, atmospheric stability also matters in determining the sign and strength of the net downward heat transport as well as the magnitude of the background TKE. Second, the WRF's ability in simulating the observed WF impacts on LST is examined by conducting real-world WF experiments driven by realistic initial and boundary conditions. Overall, the WRF model can moderately reproduce the observed spatiotemporal variations of the background LST but has difficulties in reproducing such variations for the turbine-induced LST change signals at pixel levels. However, the model is still able to reproduce the coherent and consistent responses of the observed WF-induced LST changes at regional scales. Third, the spatiotemporal characteristics of the simulated temperature changes as well as the relevant physical processes responsible for such changes are further investigated using the WRF model. It is found that (i) the WF-induced sensible heat flux change is the dominant surface forcing responsible for the simulated temperature changes; (ii) the WF-induced temperature changes are not only restricted at the surface but also can extend vertically to the hub-height level and horizontally spread 60 km in the downwind direction; (iii) the vertical divergence of heat flux from the planetary boundary layer scheme and the resolved temperature advection are the two most likely physical processes behind the simulated temperature changes. Finally, the possible WF impacts on vegetation growth are also investigated using high resolution ( 250m) satellite derived vegetation indices (VI) over two well-studied large WF regions. Results indicate that the WFs have insignificant or no detectable impacts on local vegetation growth. At the pixel level, the VI changes demonstrate a random nature and have no spatial coupling with the WF layout. At the regional level, there is no systematic shift in vegetation greenness between the pre- and post-turbine periods. At interannual and seasonal time scales, there are no confident vegetation changes over wind farm pixels relative to non-wind farm pixels. Most importantly, the majority of the VI changes are within the data uncertainty, suggesting that the WF impacts on vegetation, if any, cannot be separated confidently from the data noise.

A Multiscale Nested Modeling Framework to Simulate the Interaction of Surface Gravity Waves with Nonlinear Internal Gravity Waves

DTIC Science & Technology

2015-09-30

Meneveau, C., and L. Shen (2014), Large-eddy simulation of offshore wind farm , Physics of Fluids, 26, 025101. Zhang, Z., Fringer, O.B., and S.R...being centimeter scale, surface mixed layer processes arising from the combined actions of tides, winds and mesoscale currents. Issues related to...the internal wave field and how it impacts the surface waves. APPROACH We are focusing on the problem of modification of the wind -wave field

Numerical and Experimental Study of Wake Redirection Techniques in a Boundary Layer Wind Tunnel

NASA Astrophysics Data System (ADS)

Wang, J.; Foley, S.; Nanos, E. M.; Yu, T.; Campagnolo, F.; Bottasso, C. L.; Zanotti, A.; Croce, A.

2017-05-01

The aim of the present paper is to validate a wind farm LES framework in the context of two distinct wake redirection techniques: yaw misalignment and individual cyclic pitch control. A test campaign was conducted using scaled wind turbine models in a boundary layer wind tunnel, where both particle image velocimetry and hot-wire thermo anemometers were used to obtain high quality measurements of the downstream flow. A LiDAR system was also employed to determine the non-uniformity of the inflow velocity field. A high-fidelity large-eddy simulation lifting-line model was used to simulate the aerodynamic behavior of the system, including the geometry of the wind turbine nacelle and tower. A tuning-free Lagrangian scale-dependent dynamic approach was adopted to improve the sub-grid scale modeling. Comparisons with experimental measurements are used to systematically validate the simulations. The LES results are in good agreement with the PIV and hot-wire data in terms of time-averaged wake profiles, turbulence intensity and Reynolds shear stresses. Discrepancies are also highlighted, to guide future improvements.

Productivity, fertilizer responses and nutrient balances of farming systems in central Tigray, Ethiopia: a multi-perspective view in relation to degradation.

NASA Astrophysics Data System (ADS)

Kraaijvanger, Richard; Veldkamp, Tom; Nyssen, Jan

2014-05-01

In many rural livelihoods in sub-Saharan Africa, crop productivity plays an important role since it links with food insecurity, which again is a major constraining factor in livelihood development. Sustainable livelihood development and land degradation are closely connected: lacking sustainability often results in land degradation, whereas the incidence of land degradation frequently frustrates sustainable development. Important forms of land degradation are soil erosion and nutrient depletion, both often being attributed to exhaustive land use practices and both having a direct and major impact on crop productivity. Application of nutrients is an important way to increase productivity. In our study area, central Tigray, development agents recommend the application of fertilizers at high rates in order to boost productivity and to deal with nutrient depletion. In the discussion about the use of fertilizers different perspectives can be taken, in which especially responses and nutrient balances are important issues, linking respectively with socio-economic and agro-ecological livelihood aspects. Ethiopian soils for example are, based on large scale nutrient balances, considered to be depleted, at field scale fertilizer responses are frequently disappointing and achieving sustainable nutrient balances at farm level seems difficult. At a temporal scale however, agricultural systems remained almost unchanged for over 2500 years, suggesting at least some degree of sustainability. With respect to productivity data resulting from on-farm experimentation with natural and artificial fertilizers in 26 sites, we took four perspectives, different in ownership and scale, on nutrient related land degradation and its assumed impact on crop productivity. Taking a farmer perspective we found no significant difference between responses to recommended and current farmer based practices. Taking a more scientific perspective highlighted that, based on the positive correlation between response and soil-P, phosphorus was limiting. A relatively short term farm-level perspective made clear that closing nutrient balances to achieve sustainability is difficult, only the use of manure seemed somewhat satisfactory in this. In case a long term perspective is taken, apparent historical sustainability seems to relate to the combination of relatively low yield levels and mixed farming. Depending on the perspective taken different interventions can be forwarded, all four perspectives however indicate that strengthening the existing mixed farming system provides a promising alternative, allowing the improvement of agro-ecological as well as socio-economic sustainability of involved livelihoods.

Research on unit commitment with large-scale wind power connected power system

NASA Astrophysics Data System (ADS)

Jiao, Ran; Zhang, Baoqun; Chi, Zhongjun; Gong, Cheng; Ma, Longfei; Yang, Bing

2017-01-01

Large-scale integration of wind power generators into power grid brings severe challenges to power system economic dispatch due to its stochastic volatility. Unit commitment including wind farm is analyzed from the two parts of modeling and solving methods. The structures and characteristics can be summarized after classification has been done according to different objective function and constraints. Finally, the issues to be solved and possible directions of research and development in the future are discussed, which can adapt to the requirements of the electricity market, energy-saving power generation dispatching and smart grid, even providing reference for research and practice of researchers and workers in this field.

Aerodynamic design of the National Rotor Testbed.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kelley, Christopher Lee

2015-10-01

A new wind turbine blade has been designed for the National Rotor Testbed (NRT) project and for future experiments at the Scaled Wind Farm Technology (SWiFT) facility with a specific focus on scaled wakes. This report shows the aerodynamic design of new blades that can produce a wake that has similitude to utility scale blades despite the difference in size and location in the atmospheric boundary layer. Dimensionless quantities circulation, induction, thrust coefficient, and tip-speed-ratio were kept equal between rotor scales in region 2 of operation. The new NRT design matched the aerodynamic quantities of the most common wind turbinemore » in the United States, the GE 1.5sle turbine with 37c model blades. The NRT blade design is presented along with its performance subject to the winds at SWiFT. The design requirements determined by the SWiFT experimental test campaign are shown to be met.« less

Do Offshore Wind Farms Influence Marine Primary Production?

NASA Astrophysics Data System (ADS)

Tweddle, J. F.; Murray, R. B. O.; Gubbins, M.; Scott, B. E.

2016-02-01

Primary producers (phytoplankton) form the basis of marine food-webs, supporting production of higher trophic levels, and act as a sink of CO2. We considered the impact of proposed large scale offshore wind farms in moderately deep waters (> 45 m) off the east coast of Scotland on rates of primary production. A 2 stage modelling process was used, employing state-of-the-art 3-D hydrographic models with the ability to capture flow at the spatial resolution of 10 m combined with 1-D vertical modelling using 7 years of local forcing data. Through influencing the strength of stratification via changes in current flow, large (100 m) modelled wind turbine foundations had a significant effect on primary producers, consistently reducing total annual primary production, although within the range of natural interannual variability. The percentage reduction was largest over submarine banks less than 54 m in depth, and was outside the range of natural interannual variability. Smaller (10 m) turbine foundations had no discernible effect on total annual primary production. The results indicate that smaller foundations should be favored as a mitigation measure, in terms of effects on primary production, and this type of analysis should be considered within sectoral planning and licensing processes for future renewable energy developments.

Does tree harvesting in streamside management zones adversely affect stream turbidity? - preliminary observations from an Australian case study

Treesearch

Daniel G. Neary; Philip J. Smethurst; Brenda R. Baillie; Kevin C. Petrone; William E. Cotching; Craig C. Baillie

2010-01-01

In Australia, farmers and natural resource managers are striving to enhance environmental outcomes at farm and catchment scales by planting streamside management zones (SMZs) on farms with trees and other perennial vegetation. Lack of sound information on and funding for establishing and managing trees in SMZs is hindering widescale adoption of this practice....

Marine kelp: Energy resource in the coastal zone

NASA Astrophysics Data System (ADS)

Ritschard, R. L.; Haven, K. F.

1980-11-01

The relationship on the marine biomass concept and coastal zone management plans is discussed. An ocean farm system is described. The analysis of the ocean farm system includes a decription of the types of impacts that might occur if large scale operations become available, such as the production of environmental residuals, conflicts with the fishing and shipping industries and other legal/institutional impacts.

A mechanistic model for electricity consumption on dairy farms: definition, validation, and demonstration.

PubMed

Upton, J; Murphy, M; Shalloo, L; Groot Koerkamp, P W G; De Boer, I J M

2014-01-01

Our objective was to define and demonstrate a mechanistic model that enables dairy farmers to explore the impact of a technical or managerial innovation on electricity consumption, associated CO2 emissions, and electricity costs. We, therefore, (1) defined a model for electricity consumption on dairy farms (MECD) capable of simulating total electricity consumption along with related CO2 emissions and electricity costs on dairy farms on a monthly basis; (2) validated the MECD using empirical data of 1yr on commercial spring calving, grass-based dairy farms with 45, 88, and 195 milking cows; and (3) demonstrated the functionality of the model by applying 2 electricity tariffs to the electricity consumption data and examining the effect on total dairy farm electricity costs. The MECD was developed using a mechanistic modeling approach and required the key inputs of milk production, cow number, and details relating to the milk-cooling system, milking machine system, water-heating system, lighting systems, water pump systems, and the winter housing facilities as well as details relating to the management of the farm (e.g., season of calving). Model validation showed an overall relative prediction error (RPE) of less than 10% for total electricity consumption. More than 87% of the mean square prediction error of total electricity consumption was accounted for by random variation. The RPE values of the milk-cooling systems, water-heating systems, and milking machine systems were less than 20%. The RPE values for automatic scraper systems, lighting systems, and water pump systems varied from 18 to 113%, indicating a poor prediction for these metrics. However, automatic scrapers, lighting, and water pumps made up only 14% of total electricity consumption across all farms, reducing the overall impact of these poor predictions. Demonstration of the model showed that total farm electricity costs increased by between 29 and 38% by moving from a day and night tariff to a flat tariff. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Evaluating Job Demands and Control Measures for Use in Farm Worker Health Surveillance.

PubMed

Alterman, Toni; Gabbard, Susan; Grzywacz, Joseph G; Shen, Rui; Li, Jia; Nakamoto, Jorge; Carroll, Daniel J; Muntaner, Carles

2015-10-01

Workplace stress likely plays a role in health disparities; however, applying standard measures to studies of immigrants requires thoughtful consideration. The goal of this study was to determine the appropriateness of two measures of occupational stressors ('decision latitude' and 'job demands') for use with mostly immigrant Latino farm workers. Cross-sectional data from a pilot module containing a four-item measure of decision latitude and a two-item measure of job demands were obtained from a subsample (N = 409) of farm workers participating in the National Agricultural Workers Survey. Responses to items for both constructs were clustered toward the low end of the structured response-set. Percentages of responses of 'very often' and 'always' for each of the items were examined by educational attainment, birth country, dominant language spoken, task, and crop. Cronbach's α, when stratified by subgroups of workers, for the decision latitude items were (0.65-0.90), but were less robust for the job demands items (0.25-0.72). The four-item decision latitude scale can be applied to occupational stress research with immigrant farm workers, and potentially other immigrant Latino worker groups. The short job demands scale requires further investigation and evaluation before suggesting widespread use.

Livestock-associated methicillin-resistant Staphylococcus aureus ST9 in pigs and related personnel in Taiwan.

PubMed

Fang, Hsin-Wei; Chiang, Po-Hsing; Huang, Yhu-Chering

2014-01-01

A livestock-associated (LA) methicillin-resistant Staphylococcus aureus (MRSA) strain sequence type 398 (ST398) is found related to animals and humans in Europe and North America. To evaluate the nasal carriage of MRSA among pigs and related workers in Taiwan, we conducted this study. From June 25 to October 1 2012, a total of 641 and 100 nasal swabs were obtained from pigs and related workers, respectively, from 22 pig farms nationwide and 2 pig auction markets in Taiwan. All MRSA isolates were molecularly characterized. Overall, the nasal carriage rate of MRSA was 14.4% for pigs and 13% for humans. The carriage rate for pigs younger than 3 months was significantly higher than those older than 3 months (25.4% vs. 5.8%, p<.001). Percentage of MRSA-positive pig farms was 59.1% (13/22). The carriage rate for pigs in large-scale herds (≥ 10000 pigs) was significantly higher than that in small-scale (34.3% vs. 7.0%, p<.001) and that in auction markets (3.8%). The carriage rate was 19.2% (10/52) for pig farm workers, and the rate in large-scale farms was significantly higher than that in small-scale (36.8% vs. 9.1%, p = .014). Except for 3 isolates from humans, the other 99 isolates belonged to sequence type (ST) 9. 83 of 89 isolates from pigs shared a common pulsotype, which was also shared by 6 isolates from humans. More than 10% of pigs and related workers in Taiwan carried LA-MRSA ST9 in nares and cross-species transmission of LA-MRSA was documented by molecular methods.

Sea louse infection of juvenile sockeye salmon in relation to marine salmon farms on Canada's west coast.

PubMed

Price, Michael H H; Proboszcz, Stan L; Routledge, Rick D; Gottesfeld, Allen S; Orr, Craig; Reynolds, John D

2011-02-09

Pathogens are growing threats to wildlife. The rapid growth of marine salmon farms over the past two decades has increased host abundance for pathogenic sea lice in coastal waters, and wild juvenile salmon swimming past farms are frequently infected with lice. Here we report the first investigation of the potential role of salmon farms in transmitting sea lice to juvenile sockeye salmon (Oncorhynchus nerka). We used genetic analyses to determine the origin of sockeye from Canada's two most important salmon rivers, the Fraser and Skeena; Fraser sockeye migrate through a region with salmon farms, and Skeena sockeye do not. We compared lice levels between Fraser and Skeena juvenile sockeye, and within the salmon farm region we compared lice levels on wild fish either before or after migration past farms. We matched the latter data on wild juveniles with sea lice data concurrently gathered on farms. Fraser River sockeye migrating through a region with salmon farms hosted an order of magnitude more sea lice than Skeena River populations, where there are no farms. Lice abundances on juvenile sockeye in the salmon farm region were substantially higher downstream of farms than upstream of farms for the two common species of lice: Caligus clemensi and Lepeophtheirus salmonis, and changes in their proportions between two years matched changes on the fish farms. Mixed-effects models show that position relative to salmon farms best explained C. clemensi abundance on sockeye, while migration year combined with position relative to salmon farms and temperature was one of two top models to explain L. salmonis abundance. This is the first study to demonstrate a potential role of salmon farms in sea lice transmission to juvenile sockeye salmon during their critical early marine migration. Moreover, it demonstrates a major migration corridor past farms for sockeye that originated in the Fraser River, a complex of populations that are the subject of conservation concern.

Sea Louse Infection of Juvenile Sockeye Salmon in Relation to Marine Salmon Farms on Canada's West Coast

PubMed Central

Price, Michael H. H.; Proboszcz, Stan L.; Routledge, Rick D.; Gottesfeld, Allen S.; Orr, Craig; Reynolds, John D.

2011-01-01

Background Pathogens are growing threats to wildlife. The rapid growth of marine salmon farms over the past two decades has increased host abundance for pathogenic sea lice in coastal waters, and wild juvenile salmon swimming past farms are frequently infected with lice. Here we report the first investigation of the potential role of salmon farms in transmitting sea lice to juvenile sockeye salmon (Oncorhynchus nerka). Methodology/Principal Findings We used genetic analyses to determine the origin of sockeye from Canada's two most important salmon rivers, the Fraser and Skeena; Fraser sockeye migrate through a region with salmon farms, and Skeena sockeye do not. We compared lice levels between Fraser and Skeena juvenile sockeye, and within the salmon farm region we compared lice levels on wild fish either before or after migration past farms. We matched the latter data on wild juveniles with sea lice data concurrently gathered on farms. Fraser River sockeye migrating through a region with salmon farms hosted an order of magnitude more sea lice than Skeena River populations, where there are no farms. Lice abundances on juvenile sockeye in the salmon farm region were substantially higher downstream of farms than upstream of farms for the two common species of lice: Caligus clemensi and Lepeophtheirus salmonis, and changes in their proportions between two years matched changes on the fish farms. Mixed-effects models show that position relative to salmon farms best explained C. clemensi abundance on sockeye, while migration year combined with position relative to salmon farms and temperature was one of two top models to explain L. salmonis abundance. Conclusions/Significance This is the first study to demonstrate a potential role of salmon farms in sea lice transmission to juvenile sockeye salmon during their critical early marine migration. Moreover, it demonstrates a major migration corridor past farms for sockeye that originated in the Fraser River, a complex of populations that are the subject of conservation concern. PMID:21347456

Stackelberg Game Model of Wind Farm and Electric Vehicle Battery Switch Station

NASA Astrophysics Data System (ADS)

Jiang, Zhe; Li, Zhimin; Li, Wenbo; Wang, Mingqiang; Wang, Mengxia

2017-05-01

In this paper, a cooperation method between wind farm and Electric vehicle battery switch station (EVBSS) was proposed. In the pursuit of maximizing their own benefits, the cooperation between wind farm and EVBSS was formulated as a Stackelberg game model by treating them as decision makers in different status. As the leader, wind farm will determine the charging/discharging price to induce the charging and discharging behavior of EVBSS reasonably. Through peak load shifting, wind farm could increase its profits by selling more wind power to the power grid during time interval with a higher purchase price. As the follower, EVBSS will charge or discharge according to the price determined by wind farm. Through optimizing the charging /discharging strategy, EVBSS will try to charge with a lower price and discharge with a higher price in order to increase its profits. Since the possible charging /discharging strategy of EVBSS is known, the wind farm will take the strategy into consideration while deciding the charging /discharging price, and will adjust the price accordingly to increase its profits. The case study proved that the proposed cooperation method and model were feasible and effective.

Robustness of near-infrared calibration models for the prediction of milk constituents during the milking process.

PubMed

Melfsen, Andreas; Hartung, Eberhard; Haeussermann, Angelika

2013-02-01

The robustness of in-line raw milk analysis with near-infrared spectroscopy (NIRS) was tested with respect to the prediction of the raw milk contents fat, protein and lactose. Near-infrared (NIR) spectra of raw milk (n = 3119) were acquired on three different farms during the milking process of 354 milkings over a period of six months. Calibration models were calculated for: a random data set of each farm (fully random internal calibration); first two thirds of the visits per farm (internal calibration); whole datasets of two of the three farms (external calibration), and combinations of external and internal datasets. Validation was done either on the remaining data set per farm (internal validation) or on data of the remaining farms (external validation). Excellent calibration results were obtained when fully randomised internal calibration sets were used for milk analysis. In this case, RPD values of around ten, five and three for the prediction of fat, protein and lactose content, respectively, were achieved. Farm internal calibrations achieved much poorer prediction results especially for the prediction of protein and lactose with RPD values of around two and one respectively. The prediction accuracy improved when validation was done on spectra of an external farm, mainly due to the higher sample variation in external calibration sets in terms of feeding diets and individual cow effects. The results showed that further improvements were achieved when additional farm information was added to the calibration set. One of the main requirements towards a robust calibration model is the ability to predict milk constituents in unknown future milk samples. The robustness and quality of prediction increases with increasing variation of, e.g., feeding and cow individual milk composition in the calibration model.

Farm Management, Environment, and Weather Factors Jointly Affect the Probability of Spinach Contamination by Generic Escherichia coli at the Preharvest Stage

PubMed Central

Navratil, Sarah; Gregory, Ashley; Bauer, Arin; Srinath, Indumathi; Szonyi, Barbara; Nightingale, Kendra; Anciso, Juan; Jun, Mikyoung; Han, Daikwon; Lawhon, Sara; Ivanek, Renata

2014-01-01

The National Resources Information (NRI) databases provide underutilized information on the local farm conditions that may predict microbial contamination of leafy greens at preharvest. Our objective was to identify NRI weather and landscape factors affecting spinach contamination with generic Escherichia coli individually and jointly with farm management and environmental factors. For each of the 955 georeferenced spinach samples (including 63 positive samples) collected between 2010 and 2012 on 12 farms in Colorado and Texas, we extracted variables describing the local weather (ambient temperature, precipitation, and wind speed) and landscape (soil characteristics and proximity to roads and water bodies) from NRI databases. Variables describing farm management and environment were obtained from a survey of the enrolled farms. The variables were evaluated using a mixed-effect logistic regression model with random effects for farm and date. The model identified precipitation as a single NRI predictor of spinach contamination with generic E. coli, indicating that the contamination probability increases with an increasing mean amount of rain (mm) in the past 29 days (odds ratio [OR] = 3.5). The model also identified the farm's hygiene practices as a protective factor (OR = 0.06) and manure application (OR = 52.2) and state (OR = 108.1) as risk factors. In cross-validation, the model showed a solid predictive performance, with an area under the receiver operating characteristic (ROC) curve of 81%. Overall, the findings highlighted the utility of NRI precipitation data in predicting contamination and demonstrated that farm management, environment, and weather factors should be considered jointly in development of good agricultural practices and measures to reduce produce contamination. PMID:24509926

A Dynamic Spatio-Temporal Model to Investigate the Effect of Cattle Movements on the Spread of Bluetongue BTV-8 in Belgium

PubMed Central

Ensoy, Chellafe; Aerts, Marc; Welby, Sarah; Van der Stede, Yves; Faes, Christel

2013-01-01

When Bluetongue Virus Serotype 8 (BTV-8) was first detected in Northern Europe in 2006, several guidelines were immediately put into place with the goal to protect farms and stop the spreading of the disease. This however did not prevent further rapid spread of BTV-8 across Northern Europe. Using information on the 2006 Bluetongue outbreak in cattle farms in Belgium, a spatio-temporal transmission model was formulated. The model quantifies the local transmission of the disease between farms within a municipality, the short-distance transmission between farms across neighbouring municipalities and the transmission as a result of cattle movement. Different municipality-level covariates such as farm density, land composition variables, temperature and precipitation, were assessed as possibly influencing each component of the transmission process. Results showed a significant influence of the different covariates in each model component, particularly the significant effect of temperature and precipitation values in the number of infected farms. The model which allowed us to predict the dynamic spreading of BTV for different movement restriction scenarios, also affirmed the significant impact of cattle movement in the 2006 BTV outbreak pattern. Simulation results further showed the importance of considering the size of restriction zones in the formulation of guidelines for animal infectious diseases. PMID:24244324

A dynamic spatio-temporal model to investigate the effect of cattle movements on the spread of bluetongue BTV-8 in Belgium.

PubMed

Ensoy, Chellafe; Aerts, Marc; Welby, Sarah; Van der Stede, Yves; Faes, Christel

2013-01-01

When Bluetongue Virus Serotype 8 (BTV-8) was first detected in Northern Europe in 2006, several guidelines were immediately put into place with the goal to protect farms and stop the spreading of the disease. This however did not prevent further rapid spread of BTV-8 across Northern Europe. Using information on the 2006 Bluetongue outbreak in cattle farms in Belgium, a spatio-temporal transmission model was formulated. The model quantifies the local transmission of the disease between farms within a municipality, the short-distance transmission between farms across neighbouring municipalities and the transmission as a result of cattle movement. Different municipality-level covariates such as farm density, land composition variables, temperature and precipitation, were assessed as possibly influencing each component of the transmission process. Results showed a significant influence of the different covariates in each model component, particularly the significant effect of temperature and precipitation values in the number of infected farms. The model which allowed us to predict the dynamic spreading of BTV for different movement restriction scenarios, also affirmed the significant impact of cattle movement in the 2006 BTV outbreak pattern. Simulation results further showed the importance of considering the size of restriction zones in the formulation of guidelines for animal infectious diseases.

Estimating the scale of adverse animal welfare consequences of movement restriction and mitigation strategies in a classical swine fever outbreak.

PubMed

Yadav, Shankar; Weng, Hsin-Yi

2017-04-04

The study aim was to quantify the impact of movement restriction on the well-being of pigs and the associated mitigation responses during a classical swine fever (CSF) outbreak. We developed a stochastic risk assessment model and incorporated Indiana swine industry statistics to estimate the timing and number of swine premises that would encounter overcrowding or feed interruption resulting from movement restriction. Our model also quantified the amount of on-farm euthanasia and movement of pigs to slaughter plants required to alleviate those conditions. We simulated various single-site (i.e., an outbreak initiated from one location) and multiple-site (i.e., an outbreak initiated from more than one location) outbreak scenarios in Indiana to estimate outputs. The study estimated that 14% of the swine premises in Indiana would encounter overcrowding or feed interruption due to movement restriction implemented during a CSF outbreak. The number of premises that would experience animal welfare conditions was about 2.5 fold of the number of infected premises. On-farm euthanasia needed to be performed on 33% of those swine premises to alleviate adverse animal welfare conditions, and more than 90% of on-farm euthanasia had to be carried out within 2 weeks after the implementation of movement restriction. Conversely, movement of pigs to slaughter plants could alleviate 67% of adverse animal welfare conditions due to movement restriction, and only less than 1% of movement of pigs to slaughter plants had to be initiated in the first 2 weeks of movement restrictions. The risk of secondary outbreaks due to movement of pigs from movement restriction areas to slaughter plants was low and only seven pigs from each shipment needed to be tested for CSF infection to prevent a secondary outbreak. We found that the scale of adverse animal welfare consequences of movement restriction during a CSF outbreak in Indiana was substantial, and controlled movement of pigs to slaughter plants was an efficient and low-risk alternative mitigation response to on-farm euthanasia. The output estimates generated from this study provide empirical evidence for decision makers to properly incorporate required resources for mitigating adverse animal welfare conditions in CSF outbreak management strategic planning.

Unraveling the contact patterns and network structure of pig shipments in the United States and its association with porcine reproductive and respiratory syndrome virus (PRRSV) outbreaks.

PubMed

Lee, Kyuyoung; Polson, Dale; Lowe, Erin; Main, Rodger; Holtkamp, Derald; Martínez-López, Beatriz

2017-03-01

The analysis of the pork value chain is becoming key to understanding the risk of infectious disease dissemination in the swine industry. In this study, we used social network analysis to characterize the swine shipment network structure and properties in a typical multisite swine production system in the US. We also aimed to evaluate the association between network properties and porcine respiratory and reproductive syndrome virus (PRRSV) transmission between production sites. We analyzed the 109,868 swine shipments transporting over 93 million swine between more than 500 production sites from 2012 to 2014. A total of 248 PRRSV positive occurrences were reported from 79 production sites during those 3 years. The temporal dynamics of swine shipments was evaluated by computing network properties in one-month and three-month networks. The association of PRRS occurrence in sow farms with centrality properties from one-month and three-month networks was assessed by using the multilevel logistic regression. All monthly networks showed a scale-free network topology with positive degree assortativity. The regression model revealed that out-degree centrality had a negative association with PRRS occurrence in sow farms in both one-month and three-month networks [OR=0.79 (95% CI, 0.63-0.99) in one-month network and 0.56 (95% CI, 0.36, 0.88) in three-month network] and in-closeness centrality model was positively associated with PRRS occurrence in sow farms in the three-month network [OR=2.45 (95% CI, 1.14-5.26)]. We also describe how the occurrence of porcine epidemic diarrheac (PED) outbreaks severely affected the network structure as well as the PRRS occurrence reports and its association with centrality measures in sow farms. The structure of the swine shipment network and the connectivity between production sites influenced on the PRRSV transmission. The use of network topology and characteristics combining with spatial analysis based on fine scale geographical location of production sites will be useful to inform the design of more cost-efficient, risk-based surveillance and control measures for PRRSV as well as other diseases in the US swine industry. Copyright © 2017 Elsevier B.V. All rights reserved.

Participatory approach: from problem identification to setting strategies for increased productivity and sustainability in small scale irrigated agriculture

NASA Astrophysics Data System (ADS)

Habtu, Solomon; Ludi, Eva; Jamin, Jean Yves; Oates, Naomi; Fissahaye Yohannes, Degol

2014-05-01

Practicing various innovations pertinent to irrigated farming at local field scale is instrumental to increase productivity and yield for small holder farmers in Africa. However the translation of innovations from local scale to the scale of a jointly operated irrigation scheme is far from trivial. It requires insight on the drivers for adoption of local innovations within the wider farmer communities. Participatory methods are expected to improve not only the acceptance of locally developed innovations within the wider farmer communities, but to allow also an estimation to which extend changes will occur within the entire irrigation scheme. On such a base, more realistic scenarios of future water productivity within an irrigation scheme, which is operated by small holder farmers, can be estimated. Initial participatory problem and innovation appraisal was conducted in Gumselassa small scale irrigation scheme, Ethiopia, from Feb 27 to March 3, 2012 as part of the EAU4FOOD project funded by EC. The objective was to identify and appraise problems which hinder sustainable water management to enhance production and productivity and to identify future research strategies. Workshops were conducted both at local (Community of Practices) and regional (Learning Practice Alliance) level. At local levels, intensive collaboration with farmers using participatory methods produced problem trees and a "Photo Safari" documented a range of problems that negatively impact on productive irrigated farming. A range of participatory methods were also used to identify local innovations. At regional level a Learning Platform was established that includes a wide range of stakeholders (technical experts from various government ministries, policy makers, farmers, extension agents, researchers). This stakeholder group did a range of exercise as well to identify major problems related to irrigated smallholder farming and already identified innovations. Both groups identified similar problems to productive smallholder irrigation: soil nutrient depletion, salinization, disease and pest resulting from inefficient irrigation practices, infrastructure problems leading to a reduction of the size of the command area and decrease in reservoir volume. The major causes have been poor irrigation infrastructure, poor on-farm soil and water management, prevalence of various crop pests and diseases, lack of inputs and reservoir siltation. On-farm participatory research focusing on soil, crop and water management issues, including technical, institutional and managerial aspects, to identify best performing innovations while taking care of the environment was recommended. Currently, a range of interlinked activities are implemented a multiple scales, combining participatory and scientific approaches towards innovation development and up-scaling of promising technologies and institutional and managerial approaches from local to regional scales. ____________________________ Key words: Irrigation scheme, productivity, innovation, participatory method, Gumselassa, Ethiopia

Role of animal movement and indirect contact among farms in transmission of porcine epidemic diarrhea virus.

PubMed

VanderWaal, Kimberly; Perez, Andres; Torremorrell, Montse; Morrison, Robert M; Craft, Meggan

2018-04-12

Epidemiological models of the spread of pathogens in livestock populations primarily focus on direct contact between farms based on animal movement data, and in some cases, local spatial spread based on proximity between premises. The roles of other types of indirect contact among farms is rarely accounted for. In addition, data on animal movements is seldom available in the United States. However, the spread of porcine epidemic diarrhea virus (PEDv) in U.S. swine represents one of the best documented emergences of a highly infectious pathogen in the U.S. livestock industry, providing an opportunity to parameterize models of pathogen spread via direct and indirect transmission mechanisms in swine. Using observed data on pig movements during the initial phase of the PEDv epidemic, we developed a network-based and spatially explicit epidemiological model that simulates the spread of PEDv via both indirect and direct movement-related contact in order to answer unresolved questions concerning factors facilitating between-farm transmission. By modifying the likelihood of each transmission mechanism and fitting this model to observed epidemiological dynamics, our results suggest that between-farm transmission was primarily driven by direct mechanisms related to animal movement and indirect mechanisms related to local spatial spread based on geographic proximity. However, other forms of indirect transmission among farms, including contact via contaminated vehicles and feed, were responsible for high consequence transmission events resulting in the introduction of the virus into new geographic areas. This research is among the first reports of farm-level animal movements in the U.S. swine industry and, to our knowledge, represents the first epidemiological model of commercial U.S. swine using actual data on farm-level animal movement. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Prevalence of gastrointestinal helminths and anthelmintic resistance on small-scale farms in Gauteng Province, South Africa.

PubMed

Tsotetsi, Ana Mbokeleng; Njiro, Stephen; Katsande, Tendai Charles; Moyo, Gugulethu; Baloyi, Faculty; Mpofu, Jaison

2013-03-01

The present study was conducted to determine the prevalence and distribution of gastrointestinal helminths, to detect the presence of anthelmintic resistance in livestock from small-scale farms and to determine the level of helminthosis awareness among small-scale farmers in Gauteng Province, South Africa. Blood and faecal samples were collected from cattle (n = 314), sheep (n = 256) and goats (n = 311). Faecal egg counts and cultures were done, helminth genera identified and packed cell volume was assessed to detect anaemia. A faecal egg count reduction test was used to determine anthelmintic resistance against albendazole (7.5 mg/kg), levamisole (5 mg/kg) and ivermectin (0.2 mg/kg) on five small ruminant farms. A high prevalence of both nematodes and trematodes was observed; however, only 1 % of cattle had high nematode egg counts compared to goats (30 %) and sheep (32 %). Only 5 % of the animals were anaemic. Haemonchus and Calicophoron were the most dominant helminth genera in the studied ruminants. Anthelmintic resistance was detected against the three tested drugs on all the screened farms, except against albendazole and levamisole in sheep from Hammanskraal and Nigel, respectively. About 88 % of interviewed farmers were aware of veterinary helminthosis, 67 % treated against helminths and 83 % provided their livestock with nutritional supplements. This study showed that a high prevalence of helminthosis and anthelmintic resistance does occur in the study area, thus relevant strategic interventions are recommended.

A longitudinal survey of African swine fever in Uganda reveals high apparent disease incidence rates in domestic pigs, but absence of detectable persistent virus infections in blood and serum.

PubMed

Muhangi, Denis; Masembe, Charles; Emanuelson, Ulf; Boqvist, Sofia; Mayega, Lawrence; Ademun, Rose Okurut; Bishop, Richard P; Ocaido, Michael; Berg, Mikael; Ståhl, Karl

2015-05-13

African swine fever (ASF) is a fatal, haemorrhagic disease of domestic pigs, that poses a serious threat to pig farmers and is currently endemic in domestic pigs in most of sub-Saharan Africa. To obtain insight into the factors related to ASF outbreaks at the farm-level, a longitudinal study was performed in one of the major pig producing areas in central Uganda. Potential risk factors associated with outbreaks of ASF were investigated including the possible presence of apparently healthy ASF-virus (ASFV) infected pigs, which could act as long-term carriers of the virus. Blood and serum were sampled from 715 pigs (241 farms) and 649 pigs (233 farms) to investigate presence of ASFV and antibodies, during the periods of June-October 2010 and March-June 2011, respectively. To determine the potential contribution of different risks to ASF spread, a questionnaire-based survey was administered to farmers to assess the association between ASF outbreaks during the study period and the risk factors. Fifty-one (21 %) and 13 (5.6 %) farms reported an ASF outbreak on their farms in the previous one to two years and during the study period, respectively. The incidence rate for ASF prior to the study period was estimated at 14.1 per 100 pig farm-years and 5.6 per 100 pig farm-years during the study. Three pigs tested positive for ASFV using real-time PCR, but none tested positive for ASFV specific antibodies using two different commercial ELISA tests. There was no evidence for existence of pigs that were long-term carriers for the virus based on the analysis of blood and serum as there were no seropositive pigs and the only three ASFV DNA positive pigs were acutely infected and were linked to outbreaks reported by farmers during the study. Potential ASF risk factors were present on both small and medium-scale pig farms, although small scale farms exhibited a higher proportion with multiple potential risk factors (like borrowing boars for sows mating, buying replacement from neighboring farms without ascertaining health status, etc) and did not implement any biosecurity measures. However, no risk factors were significantly associated with ASF reports during the study.

Landscape-scale modelling of soil carbon dynamics under land use and climate change

NASA Astrophysics Data System (ADS)

Lacoste, Marine; Viaud, Valérie; Michot, Didier; Christian, Walter

2013-04-01

Soil organic carbon (SOC) sequestration is highly linked to soil use and farming practices, but also to soil redistributions, soil properties, and climate. In a global change context, landscape, farming practice and climate changes are expected; and they will most probably impact SOC dynamics. To assess their respective impacts, we modelled the SOC contents and stocks evolution at the scale of an agricultural landscape, by taking into account the soil redistribution by tillage and water processes. The simulations were conducted from 2010 to 2100 under different scenarios of landscape and climate. These scenarios combined different land uses associated to specific farming practices (mixed dairy with rotations of crops and grasslands, intensive cropping with only crops rotations or permanent grasslands), landscape managements (hedges planting or removal), and climates (business-as-usual climate and climate change, with temperature and precipitations increase). We used a spatially SOC dynamic model (adapted from RothC), coupled to a soil redistribution model (LandSoil). SOC dynamics were spatially modelled with a lateral resolution of 2-m and for soil organic layers up to 105 cm. Initial SOC stocks were described with a 2-m resolution map based on field data and produced with digital soil mapping methods. The major factor of change in SOC stocks was land use change, the second factor of importance was climate change, and finally landscape management: for the total SOC stocks (0-to-105 cm soil layer) the change of land use, climate and landscape management induced a respective mean absolute variation of 10 to 20 tC ha-1, 9 tC ha-1 and 0.4 tC ha-1. When considering the 0-to-105 cm soil layer, the different modelled landscapes showed the same sensitivity to climate change, with induced a mean decrease of 10 tC ha-1. However, the impact of climate change was found different according to the different modelled landscape when considering the 0-to-7.5 and 0-to-30 cm soil layers: the more sensitive landscapes were those of intensive cropping. This shows the importance of considering not only the plough layer, but also the vertical distribution of SOC stocks to assess the variation in SOC dynamics under land use, landscape management or climate change. Finally, rural hedgerow landscapes were proved to be quite well adapted for soil protection in a context of climate change, focusing on both carbon storage and soil erosion.

Flow adjustment inside large finite-size wind farms approaching the infinite wind farm regime

NASA Astrophysics Data System (ADS)

Wu, Ka Ling; Porté-Agel, Fernando

2017-04-01

Due to the increasing number and the growing size of wind farms, the distance among them continues to decrease. Thus, it is necessary to understand how these large finite-size wind farms and their wakes could interfere the atmospheric boundary layer (ABL) dynamics and adjacent wind farms. Fully-developed flow inside wind farms has been extensively studied through numerical simulations of infinite wind farms. The transportation of momentum and energy is only vertical and the advection of them is neglected in these infinite wind farms. However, less attention has been paid to examine the length of wind farms required to reach such asymptotic regime and the ABL dynamics in the leading and trailing edges of the large finite-size wind farms. Large eddy simulations are performed in this study to investigate the flow adjustment inside large finite-size wind farms in conventionally-neutral boundary layer with the effect of Coriolis force and free-atmosphere stratification from 1 to 5 K/km. For the large finite-size wind farms considered in the present work, when the potential temperature lapse rate is 5 K/km, the wind farms exceed the height of the ABL by two orders of magnitude for the incoming flow inside the farms to approach the fully-developed regime. An entrance fetch of approximately 40 times of the ABL height is also required for such flow adjustment. At the fully-developed flow regime of the large finite-size wind farms, the flow characteristics match those of infinite wind farms even though they have different adjustment length scales. The role of advection at the entrance and exit regions of the large finite-size wind farms is also examined. The interaction between the internal boundary layer developed above the large finite-size wind farms and the ABL under different potential temperature lapse rates are compared. It is shown that the potential temperature lapse rate plays a role in whether the flow inside the large finite-size wind farms adjusts to the fully-developed flow regime. The flow characteristics of the wake of these large finite-size wind farms are reported to forecast the effect of large finite-size wind farms on adjacent wind farms. A power deficit as large as 8% is found at a distance of 10 km downwind from the large finite-size wind farms.

GC13I-0857: Designing a Frost Forecasting Service for Small Scale Tea Farmers in East Africa

NASA Technical Reports Server (NTRS)

Adams, Emily C.; Wanjohi, James Nyaga; Ellenburg, Walter Lee; Limaye, Ashutosh S.; Mugo, Robinson M.; Flores Cordova, Africa Ixmucane; Irwin, Daniel; Case, Jonathan; Malaso, Susan; Sedah, Absae

2017-01-01

Kenya is the third largest tea exporter in the world, producing 10% of the world's black tea. Sixty percent of this production occurs largely by small scale tea holders, with an average farm size of 1.04 acres, and an annual net income of $1,075. According to a recent evaluation, a typical frost event in the tea growing region causes about $200 dollars in losses which can be catastrophic for a small holder farm. A 72-hour frost forecast would provide these small-scale tea farmers with enough notice to reduce losses by approximately 80 USD annually. With this knowledge, SERVIR, a joint NASA-USAID initiative that brings Earth observations for improved decision making in developing countries, sought to design a frost monitoring and forecasting service that would provide farmers with enough lead time to react to and protect against a forecasted frost occurrence on their farm. SERVIR Eastern and Southern Africa, through its implementing partner, the Regional Centre for Mapping of Resources for Development (RCMRD), designed a service that included multiple stakeholder engagement events whereby stakeholders from the tea industry value chain were invited to share their experiences so that the exact needs and flow of information could be identified. This unique event allowed enabled the design of a service that fit the specifications of the stakeholders. The monitoring service component uses the MODIS Land Surface Temperature product to identify frost occurrences in near-real time. The prediction component, currently under testing, uses the 2-m air temperature, relative humidity, and 10-m wind speed from a series of high-resolution Weather Research and Forecasting (WRF) numerical weather prediction model runs over eastern Kenya as inputs into a frost prediction algorithm. Accuracy and sensitivity of the algorithm is being assessed with observations collected from the farmers using a smart phone app developed specifically to report frost occurrences, and from data shared through our partner network developed at the stakeholder engagement meeting. This presentation will illustrate the efficacy of our frost forecasting algorithm, and a way forward for incorporating these forecasts in a meaningful way to the key decision makers - the small-scale farmers of East Africa.

Designing a Frost Forecasting Service for Small Scale Tea Farmers in East Africa

NASA Astrophysics Data System (ADS)

Adams, E. C.; Nyaga, J. W.; Ellenburg, W. L.; Limaye, A. S.; Mugo, R. M.; Flores Cordova, A. I.; Irwin, D.; Case, J.; Malaso, S.; Sedah, A.

2017-12-01

Kenya is the third largest tea exporter in the world, producing 10% of the world's black tea. Sixty percent of this production occurs largely by small scale tea holders, with an average farm size of 1.04 acres, and an annual net income of 1,075. According to a recent evaluation, a typical frost event in the tea growing region causes about 200 dollars in losses which can be catastrophic for a small holder farm. A 72-hour frost forecast would provide these small-scale tea farmers with enough notice to reduce losses by approximately $80 annually. With this knowledge, SERVIR, a joint NASA-USAID initiative that brings Earth observations for improved decision making in developing countries, sought to design a frost monitoring and forecasting service that would provide farmers with enough lead time to react to and protect against a forecasted frost occurrence on their farm. SERVIR Eastern and Southern Africa, through its implementing partner, the Regional Centre for Mapping of Resources for Development (RCMRD), designed a service that included multiple stakeholder engagement events whereby stakeholders from the tea industry value chain were invited to share their experiences so that the exact needs and flow of information could be identified. This unique event allowed enabled the design of a service that fit the specifications of the stakeholders. The monitoring service component uses the MODIS Land Surface Temperature product to identify frost occurrences in near-real time. The prediction component, currently under testing, uses the 2-m air temperature, relative humidity, and 10-m wind speed from a series of high-resolution Weather Research and Forecasting (WRF) numerical weather prediction model runs over eastern Kenya as inputs into a frost prediction algorithm. Accuracy and sensitivity of the algorithm is being assessed with observations collected from the farmers using a smart phone app developed specifically to report frost occurrences, and from data shared through our partner network developed at the stakeholder engagement meeting. This presentation will illustrate the efficacy of our frost forecasting algorithm, and a way forward for incorporating these forecasts in a meaningful way to the key decision makers - the small-scale farmers of East Africa.

Agricultural conservation planning framework: 3. Land use and field boundary database development and structure

USDA-ARS?s Scientific Manuscript database

Conservation planning information is important in identifying options for watershed water quality improvement, and can be developed for use at field, farm, and watershed scales. Translation across scales is a key issue impeding progress at watershed scales because watershed improvement goals must be...

78 FR 40940 - Lacey Act Implementation Plan; Definitions for Exempt and Regulated Articles

Federal Register 2010, 2011, 2012, 2013, 2014

2013-07-09

... plants. Many maricultural products are cultivated on a commercial scale on seaweed farms; however, some...'' definition to require that the plants be ``produced on a commercial scale'' instead. We have also made the... particular traits, through such means as breeding, cloning, or genetic modification. Commercial scale...

Modelling Farm Animal Welfare

PubMed Central

Collins, Lisa M.; Part, Chérie E.

2013-01-01

Simple Summary In this review paper we discuss the different modeling techniques that have been used in animal welfare research to date. We look at what questions they have been used to answer, the advantages and pitfalls of the methods, and how future research can best use these approaches to answer some of the most important upcoming questions in farm animal welfare. Abstract The use of models in the life sciences has greatly expanded in scope and advanced in technique in recent decades. However, the range, type and complexity of models used in farm animal welfare is comparatively poor, despite the great scope for use of modeling in this field of research. In this paper, we review the different modeling approaches used in farm animal welfare science to date, discussing the types of questions they have been used to answer, the merits and problems associated with the method, and possible future applications of each technique. We find that the most frequently published types of model used in farm animal welfare are conceptual and assessment models; two types of model that are frequently (though not exclusively) based on expert opinion. Simulation, optimization, scenario, and systems modeling approaches are rarer in animal welfare, despite being commonly used in other related fields. Finally, common issues such as a lack of quantitative data to parameterize models, and model selection and validation are discussed throughout the review, with possible solutions and alternative approaches suggested. PMID:26487411

Simulation of Intra- or transboundary surface-water-rights hierarchies using the farm process for MODFLOW-2000

USGS Publications Warehouse

Schmid, W.; Hanson, R.T.

2007-01-01

Water-rights driven surface-water allocations for irrigated agriculture can be simulated using the farm process for MODFLOW-2000. This paper describes and develops a model, which simulates routed surface-water deliveries to farms limited by streamflow, equal-appropriation allotments, or a ranked prior-appropriation system. Simulated diversions account for deliveries to all farms along a canal according to their water-rights ranking and for conveyance losses and gains. Simulated minimum streamflow requirements on diversions help guarantee supplies to senior farms located on downstream diverting canals. Prior appropriation can be applied to individual farms or to groups of farms modeled as "virtual farms" representing irrigation districts, irrigated regions in transboundary settings, or natural vegetation habitats. The integrated approach of jointly simulating canal diversions, surface-water deliveries subject to water-rights constraints, and groundwater allocations is verified on numerical experiments based on a realistic, but hypothetical, system of ranked virtual farms. Results are discussed in light of transboundary water appropriation and demonstrate the approach's suitability for simulating effects of water-rights hierarchies represented by international treaties, interstate stream compacts, intrastate water rights, or ecological requirements. ?? 2007 ASCE.

Multiregional input-output model for China's farm land and water use.

PubMed

Guo, Shan; Shen, Geoffrey Qiping

2015-01-06

Land and water are the two main drivers of agricultural production. Pressure on farm land and water resources is increasing in China due to rising food demand. Domestic trade affects China's regional farm land and water use by distributing resources associated with the production of goods and services. This study constructs a multiregional input-output model to simultaneously analyze China's farm land and water uses embodied in consumption and interregional trade. Results show a great similarity for both China's farm land and water endowments. Shandong, Henan, Guangdong, and Yunnan are the most important drivers of farm land and water consumption in China, even though they have relatively few land and water resource endowments. Significant net transfers of embodied farm land and water flows are identified from the central and western areas to the eastern area via interregional trade. Heilongjiang is the largest farm land and water supplier, in contrast to Shanghai as the largest receiver. The results help policy makers to comprehensively understand embodied farm land and water flows in a complex economy network. Improving resource utilization efficiency and reshaping the embodied resource trade nexus should be addressed by considering the transfer of regional responsibilities.

Lower Prevalence of Antibiotic-Resistant Enterococci on U.S. Conventional Poultry Farms that Transitioned to Organic Practices

PubMed Central

Hulet, R. Michael; Zhang, Guangyu; McDermott, Patrick; Kinney, Erinna L.; Schwab, Kellogg J.; Joseph, Sam W.

2011-01-01

Background: In U.S. conventional poultry production, antimicrobials are used for therapeutic, prophylactic, and nontherapeutic purposes. Researchers have shown that this can select for antibiotic-resistant commensal and pathogenic bacteria on poultry farms and in poultry-derived products. However, no U.S. studies have investigated on-farm changes in resistance as conventional poultry farms transition to organic practices and cease using antibiotics. Objective: We investigated the prevalence of antibiotic-resistant Enterococcus on U.S. conventional poultry farms that transitioned to organic practices. Methods: Poultry litter, feed, and water samples were collected from 10 conventional and 10 newly organic poultry houses in 2008 and tested for Enterococcus. Enterococcus (n = 259) was identified using the Vitek® 2 Compact System and tested for susceptibility to 17 antimicrobials using the Sensititre™ microbroth dilution system. Data were analyzed using SAS software (version 9.2), and statistical associations were derived based on generalized linear mixed models. Results: Litter, feed, and water samples were Enterococcus positive. The percentages of resistant Enterococcus faecalis and resistant Enterococcus faecium were significantly lower (p < 0.05) among isolates from newly organic versus conventional poultry houses for two (erythromycin and tylosin) and five (ciprofloxacin, gentamicin, nitrofurantoin, penicillin, and tetracycline) antimicrobials, respectively. Forty-two percent of E. faecalis isolates from conventional poultry houses were multidrug resistant (MDR; resistant to three or more antimicrobial classes), compared with 10% of isolates from newly organic poultry houses (p = 0.02); 84% of E. faecium isolates from conventional poultry houses were MDR, compared with 17% of isolates from newly organic poultry houses (p < 0.001). Conclusions: Our findings suggest that the voluntary removal of antibiotics from large-scale U.S. poultry farms that transition to organic practices is associated with a lower prevalence of antibiotic-resistant and MDR Enterococcus. PMID:21827979

Agricultural Conservation Planning Framework: 3. Land Use and Field Boundary Database Development and Structure.

PubMed

Tomer, Mark D; James, David E; Sandoval-Green, Claudette M J

2017-05-01

Conservation planning information is important for identifying options for watershed water quality improvement and can be developed for use at field, farm, and watershed scales. Translation across scales is a key issue impeding progress at watershed scales because watershed improvement goals must be connected with implementation of farm- and field-level conservation practices to demonstrate success. This is particularly true when examining alternatives for "trap and treat" practices implemented at agricultural-field edges to control (or influence) water flows through fields, landscapes, and riparian corridors within agricultural watersheds. We propose that database structures used in developing conservation planning information can achieve translation across conservation-planning scales, and we developed the Agricultural Conservation Planning Framework (ACPF) to enable practical planning applications. The ACPF comprises a planning concept, a database to facilitate field-level and watershed-scale analyses, and an ArcGIS toolbox with Python scripts to identify specific options for placement of conservation practices. This paper appends two prior publications and describes the structure of the ACPF database, which contains land use, crop history, and soils information and is available for download for 6091 HUC12 watersheds located across Iowa, Illinois, Minnesota, and parts of Kansas, Missouri, Nebraska, and Wisconsin and comprises information on 2.74 × 10 agricultural fields (available through /). Sample results examining land use trends across Iowa and Illinois are presented here to demonstrate potential uses of the database. While designed for use with the ACPF toolbox, users are welcome to use the ACPF watershed data in a variety of planning and modeling approaches. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Multiscale soil moisture estimates using static and roving cosmic-ray soil moisture sensors

NASA Astrophysics Data System (ADS)

McJannet, David; Hawdon, Aaron; Baker, Brett; Renzullo, Luigi; Searle, Ross

2017-12-01

Soil moisture plays a critical role in land surface processes and as such there has been a recent increase in the number and resolution of satellite soil moisture observations and the development of land surface process models with ever increasing resolution. Despite these developments, validation and calibration of these products has been limited because of a lack of observations on corresponding scales. A recently developed mobile soil moisture monitoring platform, known as the rover, offers opportunities to overcome this scale issue. This paper describes methods, results and testing of soil moisture estimates produced using rover surveys on a range of scales that are commensurate with model and satellite retrievals. Our investigation involved static cosmic-ray neutron sensors and rover surveys across both broad (36 × 36 km at 9 km resolution) and intensive (10 × 10 km at 1 km resolution) scales in a cropping district in the Mallee region of Victoria, Australia. We describe approaches for converting rover survey neutron counts to soil moisture and discuss the factors controlling soil moisture variability. We use independent gravimetric and modelled soil moisture estimates collected across both space and time to validate rover soil moisture products. Measurements revealed that temporal patterns in soil moisture were preserved through time and regression modelling approaches were utilised to produce time series of property-scale soil moisture which may also have applications in calibration and validation studies or local farm management. Intensive-scale rover surveys produced reliable soil moisture estimates at 1 km resolution while broad-scale surveys produced soil moisture estimates at 9 km resolution. We conclude that the multiscale soil moisture products produced in this study are well suited to future analysis of satellite soil moisture retrievals and finer-scale soil moisture models.

Outer layer effects in wind-farm boundary layers: Coriolis forces and boundary layer height

NASA Astrophysics Data System (ADS)

Allaerts, Dries; Meyers, Johan

2015-11-01

In LES studies of wind-farm boundary layers, scale separation between the inner and outer region of the atmospheric boundary layer (ABL) is frequently assumed, i.e., wind turbines are presumed to fall within the inner layer and are not affected by outer layer effects. However, modern wind turbine and wind farm design tends towards larger rotor diameters and farm sizes, which means that outer layer effects will become more important. In a prior study, it was already shown for fully-developed wind farms that the ABL height influences the power performance. In this study, we use the in-house LES code SP-Wind to investigate the importance of outer layer effects on wind-farm boundary layers. In a suite of LES cases, the ABL height is varied by imposing a capping inversion with varying inversion strengths. Results indicate the growth of an internal boundary layer (IBL), which is limited in cases with low inversion layers. We further find that flow deceleration combined with Coriolis effects causes a change in wind direction throughout the farm. This effect increases with decreasing boundary layer height, and can result in considerable turbine wake deflection near the end of the farm. The authors are supported by the ERC (ActiveWindFarms, grant no: 306471). Computations were performed on VSC infrastructiure (Flemish Supercomputer Center), funded by the Hercules Foundation and the Flemish Government-department EWI.

Differential Response of Fish Assemblages to Coral Reef-Based Seaweed Farming

PubMed Central

Hehre, E. James; Meeuwig, J. J.

2015-01-01

As the global demand for seaweed-derived products drives the expansion of seaweed farming onto shallow coral ecosystems, the effects of farms on fish assemblages remain largely unexplored. Shallow coral reefs provide food and shelter for highly diverse fish assemblages but are increasingly modified by anthropogenic activities. We hypothesized that the introduction of seaweed farms into degraded shallow coral reefs had potential to generate ecological benefits for fish by adding structural complexity and a possible food source. We conducted 210 transects at 14 locations, with sampling stratified across seaweed farms and sites adjacent to and distant from farms. At a seascape scale, locations were classified by their level of exposure to human disturbance. We compared sites where (1) marine protected areas (MPAs) were established, (2) neither MPAs nor blast fishing was present (hence “unprotected”), and (3) blast fishing occurred. We observed 80,186 fish representing 148 species from 38 families. The negative effects of seaweed farms on fish assemblages appeared stronger in the absence of blast fishing and were strongest when MPAs were present, likely reflecting the positive influence of the MPAs on fish within them. Species differentiating fish assemblages with respect to seaweed farming and disturbance were typically small but also included two key target species. The propensity for seaweed farms to increase fish diversity, abundance, and biomass is limited and may reduce MPA benefits. We suggest that careful consideration be given to the placement of seaweed farms relative to MPAs. PMID:25822342

Differential response of fish assemblages to coral reef-based seaweed farming.

PubMed

Hehre, E James; Meeuwig, J J

2015-01-01

As the global demand for seaweed-derived products drives the expansion of seaweed farming onto shallow coral ecosystems, the effects of farms on fish assemblages remain largely unexplored. Shallow coral reefs provide food and shelter for highly diverse fish assemblages but are increasingly modified by anthropogenic activities. We hypothesized that the introduction of seaweed farms into degraded shallow coral reefs had potential to generate ecological benefits for fish by adding structural complexity and a possible food source. We conducted 210 transects at 14 locations, with sampling stratified across seaweed farms and sites adjacent to and distant from farms. At a seascape scale, locations were classified by their level of exposure to human disturbance. We compared sites where (1) marine protected areas (MPAs) were established, (2) neither MPAs nor blast fishing was present (hence "unprotected"), and (3) blast fishing occurred. We observed 80,186 fish representing 148 species from 38 families. The negative effects of seaweed farms on fish assemblages appeared stronger in the absence of blast fishing and were strongest when MPAs were present, likely reflecting the positive influence of the MPAs on fish within them. Species differentiating fish assemblages with respect to seaweed farming and disturbance were typically small but also included two key target species. The propensity for seaweed farms to increase fish diversity, abundance, and biomass is limited and may reduce MPA benefits. We suggest that careful consideration be given to the placement of seaweed farms relative to MPAs.

Modeling wind energy potential in a data-poor region: A geographic information systems model for Iraq

NASA Astrophysics Data System (ADS)

Khayyat, Abdulkareem Hawta Abdullah Kak Ahmed

Scope and Method of Study: Most developing countries, including Iraq, have very poor wind data. Existing wind speed measurements of poor quality may therefore be a poor guide to where to look for the best wind resources. The main focus of this study is to examine how effectively a GIS spatial model estimates wind power potential in regions where high-quality wind data are very scarce, such as Iraq. The research used a mixture of monthly and hourly wind data from 39 meteorological stations. The study applied spatial analysis statistics and GIS techniques in modeling wind power potential. The model weighted important human, environmental and geographic factors that impact wind turbine siting, such as roughness length, land use⪉nd cover type, airport locations, road access, transmission lines, slope and aspect. Findings and Conclusions: The GIS model provided estimations for wind speed and wind power density and identified suitable areas for wind power projects. Using a high resolution (30*30m) digital elevation model DEM improved the GIS wind suitability model. The model identified areas suitable for wind farm development on different scales. The model showed that there are many locations available for large-scale wind turbines in the southern part of Iraq. Additionally, there are many places in central and northern parts (Kurdistan Region) for smaller scale wind turbine placement.

Linking bovine tuberculosis on cattle farms to white-tailed deer and environmental variables using Bayesian hierarchical analysis

USGS Publications Warehouse

Walter, W. David; Smith, Rick; Vanderklok, Mike; VerCauterren, Kurt C.

2014-01-01

Bovine tuberculosis is a bacterial disease caused by Mycobacterium bovis in livestock and wildlife with hosts that include Eurasian badgers (Meles meles), brushtail possum (Trichosurus vulpecula), and white-tailed deer (Odocoileus virginianus). Risk-assessment efforts in Michigan have been initiated on farms to minimize interactions of cattle with wildlife hosts but research onM. bovis on cattle farms has not investigated the spatial context of disease epidemiology. To incorporate spatially explicit data, initial likelihood of infection probabilities for cattle farms tested for M. bovis, prevalence of M. bovis in white-tailed deer, deer density, and environmental variables for each farm were modeled in a Bayesian hierarchical framework. We used geo-referenced locations of 762 cattle farms that have been tested for M. bovis, white-tailed deer prevalence, and several environmental variables that may lead to long-term survival and viability of M. bovis on farms and surrounding habitats (i.e., soil type, habitat type). Bayesian hierarchical analyses identified deer prevalence and proportion of sandy soil within our sampling grid as the most supported model. Analysis of cattle farms tested for M. bovisidentified that for every 1% increase in sandy soil resulted in an increase in odds of infection by 4%. Our analysis revealed that the influence of prevalence of M. bovis in white-tailed deer was still a concern even after considerable efforts to prevent cattle interactions with white-tailed deer through on-farm mitigation and reduction in the deer population. Cattle farms test positive for M. bovis annually in our study area suggesting that the potential for an environmental source either on farms or in the surrounding landscape may contributing to new or re-infections with M. bovis. Our research provides an initial assessment of potential environmental factors that could be incorporated into additional modeling efforts as more knowledge of deer herd factors and cattle farm prevalence is documented.

A control-oriented dynamic wind farm flow model: “WFSim”

NASA Astrophysics Data System (ADS)

Boersma, S.; Gebraad, P. M. O.; Vali, M.; Doekemeijer, B. M.; van Wingerden, J. W.

2016-09-01

In this paper, we present and extend the dynamic medium fidelity control-oriented Wind Farm Simulator (WFSim) model. WFSim resolves flow fields in wind farms in a horizontal, two dimensional plane. It is based on the spatially and temporally discretised two dimensional Navier-Stokes equations and the continuity equation and solves for a predefined grid and wind farm topology. The force on the flow field generated by turbines is modelled using actuator disk theory. Sparsity in system matrices is exploited in WFSim, which enables a relatively fast flow field computation. The extensions to WFSim we present in this paper are the inclusion of a wake redirection model, a turbulence model and a linearisation of the nonlinear WFSim model equations. The first is important because it allows us to carry out wake redirection control and simulate situations with an inflow that is misaligned with the rotor plane. The wake redirection model is validated against a theoretical wake centreline known from literature. The second extension makes WFSim more realistic because it accounts for wake recovery. The amount of recovery is validated using a high fidelity simulation model Simulator fOr Wind Farm Applications (SOWFA) for a two turbine test case. Finally, a linearisation is important since it allows the application of more standard analysis, observer and control techniques.

Risk analysis for U.S. offshore wind farms: the need for an integrated approach.

PubMed

Staid, Andrea; Guikema, Seth D

2015-04-01

Wind power is becoming an increasingly important part of the global energy portfolio, and there is growing interest in developing offshore wind farms in the United States to better utilize this resource. Wind farms have certain environmental benefits, notably near-zero emissions of greenhouse gases, particulates, and other contaminants of concern. However, there are significant challenges ahead in achieving large-scale integration of wind power in the United States, particularly offshore wind. Environmental impacts from wind farms are a concern, and these are subject to a number of on-going studies focused on risks to the environment. However, once a wind farm is built, the farm itself will face a number of risks from a variety of hazards, and managing these risks is critical to the ultimate achievement of long-term reductions in pollutant emissions from clean energy sources such as wind. No integrated framework currently exists for assessing risks to offshore wind farms in the United States, which poses a challenge for wind farm risk management. In this "Perspective", we provide an overview of the risks faced by an offshore wind farm, argue that an integrated framework is needed, and give a preliminary starting point for such a framework to illustrate what it might look like. This is not a final framework; substantial work remains. Our intention here is to highlight the research need in this area in the hope of spurring additional research about the risks to wind farms to complement the substantial amount of on-going research on the risks from wind farms. © 2015 Society for Risk Analysis.