Dairy farm methane emissions using a dispersion model

There is a need to know whole-farm methane (CH(4)) emissions since confined animal facilities such as beef cattle feedlots and dairy farms are emission "hot spots" in the landscape. However, measurements of whole-farm CH(4) emissions can differ between farms because of differences in contributing sources such as manure handling, number of lactating and nonlactating cows, and diet. Such differences may limit the usefulness of whole-farm emissions for national inventories and mitigation purposes unless the variance between farms is taken into account or a large number of farms can be examined. Our study describes the application of a dispersion model used in conjunction with field measurements of CH(4) concentration and stability of the air to calculate whole-farm emissions of CH(4) from three dairy farms in Alberta, Canada, during three sequential campaigns conducted in November 2004 and May and July 2005. The dairy farms ranged in herd size from 208 to 351 cows (102 to 196 lactating cows) and had different manure handling operations. The results indicate that the average CH(4) emission per cow (mixture of lactating and nonlactating) from the three dairy farms was 336 g d(-1), which was reduced to 271 g d(-1) when the emission (estimated) from the manure storage was removed. Further separation of source strength yielded an average CH(4) (enteric) emission of 363 g d(-1) for a lactating cow. The estimated CH(4) emission intensities were approximately 15 g CH(4) kg(-1) dry matter intake and 16.7 L CH(4) L(-1) of milk produced. The approach of understanding the farm-to-farm differences in CH(4) emissions as affected by diet, animal type, and manure management is essential when utilizing whole-farm emission measurements for mitigation and inventory applications.     

Investigation of an Escherichia coli environmental benchmark for waterborne pathogens in agricultural watersheds in Canada

Canada's National Agri-Environmental Standards Initiative sought to develop an environmental benchmark for low-level waterborne pathogen occurrence in agricultural watersheds. A field study collected 902 water samples from 27 sites in four intensive agricultural watersheds across Canada from 2005 to 2007. Four of the sites were selected as reference sites away from livestock and human fecal pollution sources in each watershed. Water samples were analyzed for Campylobacter spp., Salmonella spp., Escherichia coli O157:H7, Cryptosporidium spp., Giardia spp., and the water quality indicator E. coli. The annual mean number of pathogen species was higher at agricultural sites (1.54 ± 0.07 species per water sample) than at reference sites (0.75 ± 0.14 species per water sample). The annual mean concentration of E. coli was also higher at agricultural sites (491 ± 96 colony-forming units [cfu] 100 mL(-1)) than at reference sites (53 ± 18 cfu 100 mL(-1)). The feasibility of adopting existing E. coli water quality guideline values as an environmental benchmark was assessed, but waterborne pathogens were detected at agricultural sites in 80% of water samples with low E. coli concentrations (<100 cfu 100 mL(-1)). Instead, an approach was developed based on using the natural background occurrence of pathogens at reference sites in agricultural watersheds to derive provisional environmental benchmarks for pathogens at agricultural sites. The environmental benchmarks that were derived were found to represent E. coli values lower than geometric mean values typically found in recreational water quality guidelines. Additional research is needed to investigate environmental benchmarks for waterborne pathogens within the context of the "One World, One Health" perspective for protecting human, domestic animal, and wildlife health.     

Identifying fecal sources in a selected catchment reach using multiple source-tracking tools

Given known limitations of current microbial source-tracking (MST) tools, emphasis on small, simple study areas may enhance interpretations of fecal contamination sources in streams. In this study, three MST tools-Escherichia coli repetitive element polymerase chain reaction (rep-PCR), coliphage typing, and Bacteroidales 16S rDNA host-associated markers-were evaluated in a selected reach of Plum Creek in south-central Nebraska. Water-quality samples were collected from six sites. One reach was selected for MST evaluation based on observed patterns of E. coli contamination. Despite high E. coli concentrations, coliphages were detected only once among water samples, precluding their use as a MST tool in this setting. Rep-PCR classification of E. coli isolates from both water and sediment samples supported the hypothesis that cattle and wildlife were dominant sources of fecal contamination, with minor contributions by horses and humans. Conversely, neither ruminant nor human sources were detected by Bacteroidales markers in most water samples. In bed sediment, ruminant- and human-associated Bacteroidales markers were detected throughout the interval from 0 to 0.3 m, with detections independent of E. coli concentrations in the sediment. Although results by E. coli-based and Bacteroidales-based MST methods led to similar interpretations, detection of Bacteroidales markers in sediment more commonly than in water indicates that different tools to track fecal contamination (in this case, tools based on Bacteroidales DNA and E. coli isolates) may have varying relevance to the more specific goal of tracking the sources of E. coli in watersheds. This is the first report of simultaneous, toolbox approach application of a library-based and marker-based MST analyses to flowing surface water.     

Sequence-based source tracking of Escherichia coli based on genetic diversity of beta-glucuronidase

High levels of fecal bacteria are a concern for recreational waters; however, the source of contamination is often unknown. This study investigated whether direct sequencing of a bacterial gene could be utilized for detecting genetic differences between bacterial strains for microbial source tracking. A 525-nucleotide segment of the gene for beta-glucuronidase (uidA) was sequenced in 941 Escherichia coli isolates from the Clinton River-Lake St. Clair watershed, 182 E. coli isolates from human and animal feces, and 34 E. coli isolates from a combined sewer. Environmental isolates exhibited 114 alleles in 11 groups on a genetic tree. Frequency of strains from different genetic groups differed significantly (p < 0.03) between upstream reaches (Bear Creek-Red Run), downstream reaches, and Lake St. Clair beaches. Fecal E. coli uidA sequences exhibited 81 alleles that overlapped with the environmental set. An algorithm to assign alleles to different host sources averaged approximately 75% correct classification with the fecal data set. Using the same algorithm, the percent of environmental isolates assignable to humans decreased significantly between Bear Creek-Red Run (30 +/- 3%) and the beaches (17 +/- 2%) (p < 0.05). Birds accounted for approximately 50% of assignable environmental isolates. For combined sewer isolates, the same algorithm assigned 51% to humans. These experiments demonstrate differences in the frequency of different E. coli strains at different locations in a watershed, and provide a "proof in principle" that sequence-based data can be used for microbial source tracking.     

Efficacy of Bacteroides measurements for reducing the statistical uncertainty associated with hydrologic flow and fecal loads in a mixed use watershed

This paper presents an analysis of the occurrence and uncertainty of source-specific Bacteroides and Escherichia coli in a stream in a mixed land-use watershed with human, cattle, and wildlife fecal inputs located in a karstic geologic region during baseflow conditions. The objectives of the study were to evaluate the occurrence, hydrologic significance, and source of fecal mass in the stream using assays for total Bacteroides (AllBac) and bovine-specific Bacteroides (BoBac), and then to compare these measurements with E. coli densities and loads. Samples were collected during baseflow conditions over several months at seven different main channel sites in the Stock Creek watershed, a 49.3 km2 basin located in Knoxville, TN (USA). We determined instantaneous loads for total fecal loads, bovine fecal loads, and E. coli from measured flow rates and the representative Bacteroides fecal masses and/or E. coli densities. The study indicated a strong correlation between total fecal load (kg d(-1)), bovine fecal load (kg d(-1)), E. coli load rate (CFU d(-1)), 7-d antecedent precipitation, and turbidity. The various datasets were used to establish parameter correlations and spatial dependencies throughout the watershed. The data analysis demonstrated two prevalent patterns throughout the watershed: (i) a runoff-dominated transport and occurrence; and (ii) potential groundwater-dominated transport and occurrence.     

Manure collection and distribution on Wisconsin dairy farms

Manure management plans require knowing the amount of manure produced, collected, and available for land-spreading. Whereas much information is available to calculate manure production, little is known about the types and amounts of manure actually collected on typical dairy farms. This study of 54 representative Wisconsin dairy farms showed significant regional, housing, and herd size differences in collection of manure from lactating cows (Bos taurus), dry cows, and heifers. Significantly (P < 0.05) less manure is collected in the hilly southwest (56% of total annual herd production) than in the undulating south central (72%) or the flat northeast (68%) regions. Collection of lactating cow manure is significantly (P < 0.05) lower from stanchion (66% of total annual production) than free-stall (89%) housing, and significant (P < 0.05) positive relationships were found between the number of lactating cows a farm keeps and the percentage manure collected. Average annual manure N (range of 116-846 kg N ha(-1)) and P (range of 24-158 kg P ha(-1)) loading rates in areas where manure goes uncollected was highest in unvegetated barnyards followed by vegetated and partially vegetated outside areas. Once uncollected manure was accounted for, average annual loading rates on cereal cropland ranged from 128 to 337 kg ha(-1) of manure N, and from 45 to 139 kg ha(-1) of manure P. Compared with adjacent cropland, the accumulation of uncollected manure has vastly increased soil test P, K, and organic matter levels in outside areas. Manure management on Wisconsin dairy farms with small to medium herds might require assistance in managing manure in outside confinement areas to reduce the risk of impairing surface and ground water quality.     

Watershed vulnerability predictions for the Ozarks using landscape models

Forty-six broad-scale landscape metrics derived from commonly used landscape metrics were used to develop potential indicators of total phosphorus (TP) concentration, total ammonia (TA) concentration, and Escherichia coli bacteria count among 244 sub-watersheds of the Upper White River (Ozark Mountains, USA). Indicator models were developed by correlating field-based water quality measurements and contemporaneous remote-sensing-based ecological metrics using partial least squares (PLS) analyses. The TP PLS model resulted in one significant factor explaining 91% of the variability in surface water TP concentrations. Among the 18 contributing landscape model variables for the TP PLS model, the proportions of a sub-watershed that are barren and in human use were key indicators of water chemistry in the associated sub-watersheds. The increased presence and reduced fragmentation of forested areas are negatively correlated with TP concentrations in associated sub-watersheds, particularly within close proximity to rivers and streams. The TA PLS model resulted in one significant factor explaining 93% of the variability in surface water TA concentrations. The eight contributing landscape model variables for the TA PLS model were among the same forest and urban metrics for the TP model, with a similar spatial gradient trend in relationship to distance from streams and rivers within a sub-watershed. The E. coli PLS model resulted in two significant factors explaining 99.7% of the variability in E. coli cell count. The 17 contributing landscape model variables for the E. coli PLS model were similar to the TP and TA models. The integration of model results demonstrates that forest, riparian, and urban attributes of sub-watersheds affect all three models. The results provide watershed managers in the Ozark Mountains with a broad-scale vulnerability prediction tool, focusing on TP, TA, and E. coli, and are being used to prioritize and evaluate monitoring and restoration efforts in the vicinity of the White River, a major tributary to the Mississippi River and Gulf of Mexico.     

Effects of cattle grazing and haying on wildlife conservation at National Wildlife Refuges in the United States

The National Wildlife Refuge System is perhaps the most important system of federal lands for protecting wildlife in the United States. Only at refuges has wildlife conservation been legislated to have higher priority than either recreational or commercial activities. Presently, private ranchers and farmers graze cattle on 981,954 ha and harvest hay on 12,021 ha at 123 National Wildlife Refuges. US Fish and Wildlife Service policy is to permit these uses primarily when needed to benefit refuge wildlife. To evaluate the success of this policy, I surveyed grassland management practices at the 123 refuges. The survey results indicate that in fiscal year 1980 there were 374,849 animal unit months (AUMs) of cattle grazing, or 41% more than was reported by the Fish and Wildlife Service. According to managers' opinions, 86 species of wildlife are positively affected and 82 are negatively affected by refuge cattle grazing or haying. However, quantitative field studies of the effect of cattle grazing and haying on wildlife coupled with the survey data on how refuge programs are implemented suggest that these activities are impeding the goal of wildlife conservation. Particular management problems uncovered by the survey include overgrazing of riparian habitats, wildlife mortality due to collisions with cattle fences, and mowing of migratory bird habitat during the breeding season. Managers reported that they spend $919,740 administering cattle grazing and haying; thus refuge grazing and haying programs are also expensive. At any single refuge these uses occupy up to 50% of refuge funds and 55% of staff time. In light of these results, prescribed burning may be a better wildlife management option than is either cattle grazing or haying.     

Phosphorus in fresh and dry dung of grazing dairy cattle, deer, and sheep: sequential fraction and phosphorus-31 nuclear magnetic resonance analyses

Knowledge of phosphorus (P) fractions in dung of animals (dairy cattle, deer, sheep) grazing pasture is important for soil fertility and the potential for P transport in runoff and subsequent surface water quality deterioration. We used sequential fractionation and 31P nuclear magnetic resonance (NMR) spectroscopy to determine P forms in fresh and air-dried (to simulate field conditions during grazing) dung. Sheep dung was richest in P (8 g kg(-1)), and cattle dung poorest (5.5 g kg(-1)). Data for sequential fractionation indicated that most P was extractable by water (15-36%) and bicarbonate (36-45%) in fresh dung, and shifted toward recalcitrant, HCl (12-28%), and residual P forms (15-31%) with drying. Organic P concentration in dung was poor (maximum of 15% of total P), probably due to the poor concentration of phytate in pasture. The 31P NMR spectra of NaOH-EDTA extracts supported this by detecting a low concentration of monoesters (9-19% of total P in extracts), of which phytate is a major component. The 31P NMR data also showed that changes in organic P concentration with drying could be due to the degradation of diesters. Data indicate the decreasing bioavailability of dairy cattle, deer, and sheep dung with drying and the need to consider this effect with respect to P returns for soil fertility and the potential for runoff.     

The relationship between milk production and farm-gate nitrogen surplus for the Waikato region, New Zealand

As the scope and scale of New Zealand (NZ) dairy farming increases, farmers and the industry are being challenged by Government and the New Zealand public to address growing environmental concerns. Dairying has come under increasing scrutiny from local authorities tasked with sustainable resource management. Despite recent efforts of farmers and industry to improve resource use efficiency, there is increasing likelihood of further regulatory constraints on water use and nutrient management. This study uses available data on farm-gate nitrogen (N) surpluses and milk production from the Waikato, New Zealand's largest dairying region, together with a farm scale modeling exercise, to provide a perspective on the current situation compared to dairy farms in Europe. It also aims to provide relevant guidelines for N surpluses and efficiencies under NZ conditions. Waikato dairy farms compare favorably with farms in Europe in terms of N use efficiency expressed as L milk/kg farm-gate N surplus. Achievable and realistic good practice objectives for Waikato dairy farmers could be 15,000 L milk/ha (1200 kg milk fat plus protein/ha) with a farm-gate N surplus of 100 kg/ha giving an eco-efficiency (L milk/kg N surplus) of 150, and long-term average nitrate leaching losses of approximately 25-30 kg/ha/yr. This can be achieved by increasing the N conversion efficiency through lower replacement rates (16 versus 22%), lower stocked (< 3 cows/ha) high genetic merit cows (30 L milk/day at peak) milked for longer (277 versus 240 days), feeding effluent-irrigated, home-grown, low-protein supplements to cows on high-protein, grass-clover pastures to dilute N concentration in the diet, removing some of the urinary N from the paddocks during critical times by standing cows on a loafing pad for part of the day, and through lower N fertilizer rates (50-70 kg/ha/yr compared to the norm of 170-200 kg/ha/yr) and using a nitrification inhibitor and gibberellins to boost pasture growth and the former to reduce N leaching.     

Locating Escherichia coli contamination in a rural South Carolina watershed

One of the problems associated with the use of ambient water quality standards in surface water regulation is the difficulty of identifying and regulating nonpoint source pollution, making such standards unenforceable, especially at the local level. We used the Escherichia coli indicator to locate the most contaminated reaches in rural South Carolina's Bush River watershed (297 km(2), 186 stream-km). We divided the watershed into 20 smaller reaches and sampled each reach multiple times, but restricted each sampling round to one day. We located four low order creek reaches, representing just nine stream-km, where we observed geometric mean E. coli densities of over 1250 E. coli/100 mL; in each case, the source of the contamination (riparian grazing of cattle) was easily identifiable. On the Bush River itself, we observed a step change in one reach where geometric means increased from 106 E. coli/100 mL to 565 E. coli/100 mL over the reach's 10 km length. In this case, the sources of contamination were not as obvious as in the lower order streams; in this case, more advanced Microbial Source Tracking techniques will be required to identify the sources. Nevertheless, this sampling protocol helped locate polluted reaches and provided decision-makers with reasonable justifications for concrete action in deciding where (or where not) to install conservation practices and where more sophisticated (and expensive) MST techniques were warranted.     

Prioritisation of farm scale remediation efforts for reducing losses of nutrients and faecal indicator organisms to waterways: a case study of New Zealand dairy farming

The international competitiveness of the New Zealand (NZ) dairy industry is built on low cost clover-based systems and a favourable temperate climate that enables cows to graze pastures mostly all year round. Whilst this grazed pasture farming system is very efficient at producing milk, it has also been identified as a significant source of nutrients (N and P) and faecal bacteria which have contributed to water quality degradation in some rivers and lakes. In response to these concerns, a tool-box of mitigation measures that farmers can apply on farm to reduce environmental emissions has been developed. Here we report the potential reduction in nutrient losses and costs to farm businesses arising from the implementation of individual best management practices (BMPs) within this tool-box. Modelling analysis was carried out for a range of BMPs targeting pollutant source reduction on case-study dairy farms, located in four contrasting catchments. Due to the contrasting physical resources and management systems present in the four dairy catchments evaluated, the effectiveness and costs of BMPs varied. Farm managements that optimised soil Olsen P levels or used nitrification inhibitors were observed to result in win-win outcomes whereby nutrient losses were consistently reduced and farm profitability was increased in three of the four case study farming systems. Other BMPs generally reduced nutrient and faecal bacteria losses but at a small cost to the farm business. Our analysis indicates that there are a range of technological measures that can deliver substantial reductions in nutrient losses to waterways from dairy farms, whilst not increasing or even reducing other environmental impacts (e.g. greenhouse gas emissions and energy use). Their implementation will first require clearly defined environmental goals for the catchment/water body that is to be protected. Secondly, given that the major sources of water pollutants often differed between catchments, it is important that BMPs are matched to the physical resources and management systems of the existing farm businesses.     

Cattle feedlot soil moisture and manure content: II. Impact on Escherichia coli O157

The moisture and manure contents of soils at cattle feedlot surfaces vary spatiotemporally and likely are important factors in the persistence of Escherichia coli O157 in these soils. The impacts of water content (0.11-1.50 g H2O g(-1) dry feedlot surface material [FSM]) and manure level (5, 25, and 75% dry manure in dry FSM) on E. coli O157:H7 in feedlot soils were evaluated. Generally, E. coli O157:H7 numbers either persisted or increased at all but the lowest moisture levels examined. Manure content modulated the effect of water on E. coli growth; for example, at water content of 0.43 g H2O g(-1) dry FSM and 25% manure, E. coli O157:H7 increased by 2 log10 colony forming units (CFU) g(-1) dry FSM in 3 d, while at 0.43 g H2O g(-1) dry FSM and 75% manure, populations remained stable over 14 d. Escherichia coli and coliform populations responded similarly. In a second study, the impacts of cycling moisture levels and different drying rates on naturally occurring E. coli O157 in feedlot soils were examined. Low initial levels of E. coli O157 were reduced to below enumerable levels by 21 d, but indigenous E. coli populations persisted at >2.50 log10 CFU g(-1) dry FSM up to 133 d. We conclude that E. coli O157 can persist and may even grow in feedlot soils, over a wide range of water and manure contents. Further investigations are needed to determine if these variables can be manipulated to reduce this pathogen in cattle and the feedlot environment.     

Waterfowl abundance does not predict the dominant avian source of beach Escherichia coli

The horizontal, fluorophore enhanced, rep-PCR (HFERP) DNA fingerprinting technique was used to identify potential sources of in water, nearshore sand, and sediment at two beaches in the Duluth-Superior Harbor, near Duluth, MN, and Superior, WI, during May, July, and September 2006. An animal or environmental source could be identified for 35, 29, and 30% of strains in water, sand, and sediments, respectively. Waterfowl, including Canada geese, ring-billed gulls, and mallard ducks, were the largest source of that could be identified in water (55-100%), sand (59-100%), and sediment (92-100%) at both beaches. Although ring-billed gulls were more abundant in this harbor, Canada geese were usually the dominant source of waterfowl found at these beaches. The percentage of identified from treated wastewater was always less than the percentage of originating from waterfowl. At both beaches, the percentage of in water contributed by treated wastewater was higher in May compared with July and September. The larger proportion of wastewater-derived seen in May probably reflected a smaller contribution of from geese when these birds were less abundant rather than an absolute increase in from treated wastewater. Microbial source analysis and bird census data both indicated that waterfowl were a major source of at beaches in the Duluth-Superior Harbor. These data also indicated it is risky to assume that the most abundant waterfowl species present in waterways will also be the largest source of avian-derived in water, nearshore sand, and sediments at beaches.     

An approach for measuring methane emissions from whole farms

Estimates of enteric methane (CH4) emissions from ruminants are typically measured by confining animals in large chambers, using head hoods or masks, or by a ratiometric technique involving sampling respired air of the animal. These techniques are not appropriate to evaluate large-scale farm emissions and the variability between farms that may be partly attributed to different farm management. This study describes the application of an inverse-dispersion technique to calculate farm emissions in a controlled tracer-release experiment. Our study was conducted at a commercial dairy farm in southern Alberta, Canada (total of 321 cattle, including 152 lactating dairy cows). Sulfur hexafluoride (SF6) and CH4 were released from 10 outlet locations (barn and open pens) using mass-flow controllers. A Lagrangian stochastic (LS) dispersion model was then used to infer farm emissions from downwind gas concentrations. Concentrations of SF6 and CH4 were measured by gas chromatography analysis and open path lasers, respectively. Wind statistics were measured with a three-dimensional sonic anemometer. Comparing the inferred emissions with the known release rate showed we recovered 86% of the released CH4 and 100% of the released SF6. The location of the concentration observations downwind of the farm was critically important to the success of this technique.     

Escherichia coli loading at or near base flow in a mixed-use watershed

This study analyzed the occurrence of Escherichia coli in a mixed land-use watershed with human, cattle, and wildlife fecal inputs located in a karstic geologic region using synoptic monitoring (samples taken throughout the watershed system) during base-flow conditions. The objective of the study was to evaluate the occurrence of E. coli during base-flow conditions for several months at seven different main channel and nine different tributary sampling sites in the Stock Creek watershed, a 49.3-km(2) basin located in Knoxville, TN. Escherichia coli densities were measured using the Colilert (Defined Substrate Technology) method. The instantaneous loads for E. coli were determined from measured flow rates and E. coli densities, with the highest loading rates observed in the late fall. The study indicated a strong correlation between E. coli load rate (colony-forming units [CFU]/d), 7-d antecedent precipitation, and turbidity. Water quality data, however, also exhibited a spatial dependency; for example, the E. coli load rate was better correlated with turbidity in the slower draining basin tailwater sampling sites than in the faster draining upstream headwater sampling sites. In the headwater sites, the E. coli load rate was better correlated with 7-d antecedent precipitation than turbidity.     

Alcohol, volatile fatty acid, phenol, and methane emissions from dairy cows and fresh manure

There are approximately 2.5 million dairy cows in California. Emission inventories list dairy cows and their manure as the major source of regional air pollutants, but data on their actual emissions remain sparse, particularly for smog-forming volatile organic compounds (VOCs) and greenhouse gases (GHGs). We report measurements of alcohols, volatile fatty acids, phenols, and methane (CH4) emitted from nonlactating (dry) and lactating dairy cows and their manure under controlled conditions. The experiment was conducted in an environmental chamber that simulates commercial concrete-floored freestall cow housing conditions. The fluxes of methanol, ethanol, and CH4 were measured from cows and/or their fresh manure. The average estimated methanol and ethanol emissions were 0.33 and 0.51 g cow(-1) h(-1) from dry cows and manure and 0.7 and 1.27 g cow(-1) h(-1) from lactating cows and manure, respectively. Both alcohols increased over time, coinciding with increasing accumulation of manure on the chamber floor. Volatile fatty acids and phenols were emitted at concentrations close to their detection limit. Average estimated CH4 emissions were predominantly associated with enteric fermentation from cows rather than manure and were 12.35 and 18.23 g cow(-1) h(-1) for dry and lactating cows, respectively. Lactating cows produced considerably more gaseous VOCs and GHGs emissions than dry cows (P < 0.001). Dairy cows and fresh manure have the potential to emit considerable amounts of alcohols and CH4 and research is needed to determine effective mitigation.     

Phosphorus, sediment, and Escherichia coli loads in unfenced streams of the Georgia Piedmont, USA

Contamination of unfenced streams with P, sediments, and pathogenic bacteria from cattle (Bos taurus) activity may be affected by the availability of shade and alternative water sources. The objectives of this study were to evaluate water quality in two streams draining tall fescue (Festuca arundinacea Schreb.)-common bermudagrass (Cynodon dactylon L.) pastures with different shade distribution, and to quantify the effects of alternative water sources on stream water quality. For 3 yr, loads of dissolved reactive phosphorus (DRP), total phosphorus (TP), and total suspended solids (TSS) were measured during storm flow, and loads of DRP, TP, TSS, and Escherichia coli were measured every 14 d during base flow. We also used GPS collars to determine amount of time cattle spent in riparian areas. Our results showed that cattle-grazed pastures with unfenced streams contributed significant loads of DRP, TP, TSS, and E. coli to surface waters (p < 0.01). Time spent by cattle in riparian areas as well as storm flow loads of DRP, TP, and TSS were larger (p < 0.08) in the pasture with the smaller amount of nonriparian shade. Water trough availability decreased base flow loads of TSS and E. coli in both streams, and decreased time cattle spent in riparian areas in the pasture with the smaller amount of nonriparian shade (p < 0.08). Our results indicate that possible BMPs to reduce contamination from cattle-grazed pastures would be to develop or encourage nonriparian shade and to provide cattle with alternative water sources away from the stream.     

Use of Escherichia coli BOX-PCR fingerprints to identify sources of fecal contamination of water bodies in the State of São Paulo, Brazil

Repetitive element sequence-based polymerase chain reaction (rep-PCR) is one of the commonest methods used to identify sources of fecal contamination of water systems. In this work, BOX-A1R-based repetitive extragenic palindromic-PCR (BOX-PCR) was used to discriminate Escherichia coli strains originating from different animals and water sources, and the suitability of the technique for bacterial source tracking (BST) was evaluated. A total of 214 strains from humans, 150 strains from animals, 55 strains from sewage and 77 strains from water bodies were analyzed by the BOX-PCR technique. When maximum similarity between the fingerprints was used, a correct classification rate of 84% was achieved for strains from human and animal sources. Furthermore, 95% of the strains found in sewage were classified as being from human sources by at least one of the four classification tools used. Classification of the strains found in water bodies in the State of S?o Paulo was based on the fingerprints obtained for human and animal sources. Most of the sampling sites appeared to be affected by mixed sources of fecal contamination. The use of BOX-PCR for BST could be especially valuable in developing countries, where simplicity and cost are important considerations.     

Assessment of manure phosphorus export through turfgrass sod production in Erath County, Texas

A best management practice (BMP) for exporting manure phosphorus (P) in turfgrass sod from the North Bosque River (NBR) watershed in central Texas was assessed using a geographic information system (GIS). The NBR watershed has a mandate to reduce the total annual P load to the NBR by 50% as a result of total maximum daily load regulation. Since dairy waste applications to fields are identified as the major nonpoint source of P to the river, innovative BMPs, such as export of manure P in turfgrass, will be needed to achieve the 50% reduction. However, methods are needed to evaluate the feasibility of these innovative management practices prior to their implementation. A geospatial database of suitable turfgrass production sites was developed for Erath County using GIS. Erath County largely encompasses the upper portion of the NBR watershed. Information from field experiments, production practices, and ground-truthing was used to search, analyze, and verify a geospatial database developed from national and regional sources. The integration and analyses of large databases supports the search by turf producers for sites suitable for turfgrass sod production in Erath County. In addition, GIS enables researchers and regulators to estimate manure P exports and reduced P loading due to implementation of the manure export BMP on a county scale. Under optimal conditions 198,000 kg manure P yr(-1) could be used and 114,840 kg manure P yr(-1) exported from the NBR watershed through implementation of a system using dairy manure to produce turfgrass sod. This is the equivalent of the manure P applied from 10,032 dairy cows yr(-1) and exported from 5808 dairy cows yr(-1). Application of GIS to large-scale planning and decision-making transcends traditional field-scale applications in precision agriculture.