In New Zealand, nitrous oxide emissions from grazed hill pastures are estimated using different emission factors for urine and dung deposited on different slope classes. Allocation of urine and dung to each slope class needs to consider the distribution of slope classes within a landscape and animal behavior. The Nutrient Transfer (NT) model has recently been incorporated into the New Zealand Agricultural GHG Inventory Model to account for the allocation of excretal nitrogen (N) to each slope class. In this study, the predictive ability of the transfer function within the NT model was explored using urine deposition datasets collected with urine sensor and GPS tracker technology. Data were collected from three paddocks that had areas in low (<12°), medium (12–24°), and high slopes (>24°). The NT model showed a good overall predictive ability for two of the three datasets. However, if the urine emission factors (% of urine N emitted as N 2 O–N) were to be further disaggregated to assess emissions from all three slope classes or slope gradients, more precise data would be required to accurately represent the range of landscapes found on farms. We have identified the need for more geospatial data on urine deposition and animal location for farms that are topographically out of the range used to develop the model. These new datasets would provide livestock urine deposition on a more continuous basis across slopes (as opposed to broad ranges), a unique opportunity to improve the performance of the NT model.

Nitrous oxide emissions from grazed hill country grasslands are estimated using a spatial framework model that disaggregates excreta deposition according to slope class. A Nutrient Transfer Model has recently been incorporated to the New Zealand Agricultural GHG Inventory Model (AIM) for the allocation of excretal nitrogen (N) to each slope class. In our study, the predictive ability of the transfer function within the model is explored using three distinct urine deposition datasets. These datasets were collected using urine sensor and GPS tracker technology from paddocks that had areas in either low slope (LS; <12ᴏ), medium slope (MS; 12-24ᴏ) or high slope (HS; >24ᴏ) often outside of the range of slope class areas used to develop the model. Despite these differences, the model showed a good overall predictive ability for two of the three datasets. For all datasets there were differences (observed vs predicted) in urine deposition on MS vs HS areas. As the AIM uses the same emission factor (EF3) for MS and HS (i.e., slopes >12ᴏ), this disparity (observed vs predicted) has no effect on current nation-wide calculated N2O emissions. However, if EF3 were to be disaggregated by all slope classes, more accurate data would be required. Farm production regions with disproportionate areas in LS or HS (compared with those used to develop the model) are not well represented. We have identified the need for more geospatial data on urine deposition for farms that are topographically out of the range used to develop the model, ideally providing livestock urine deposition on a more continuum-type setting (as opposed to broad ranges) of areas in different slope classes. Under the current circumstances, there is insufficient evidence to suggest that a change in the Nutrient Transfer Model (in its current function and as applied at the national level), is required.

A urine sensor has been developed to measure the volume and nitrogen (N) concentration of individual urination events from female cattle in the field. The objective of this paper was to establish that the sensor's refractive index (RI) value could be used to accurately estimate urinary-N concentration. Individual urine samples (168 in total) were collected from 18 cows that were fed monocultures (ryegrass, clover or turnips) or from cattle that grazed conventional mixed pasture (ryegrass/white clover) in the field. Regression analysis of urine sensor RI values with either urinary-N or potassium (K) concentrations yielded strong linear relationships (P<0.001) for all feed types. However, individual regression lines varied between feed types, particularly for turnips. We conclude the use of RI in the sensor provides an accurate estimate of urinary-N but site-specific calibration of the sensor is warranted due to different feed types affecting urine K:N ratio and, by inference, other aspects of composition.

New Zealand dairy farmers are facing increasing pressure to reduce nutrient losses from grazing ruminants to the environment. Research suggests that the major source of nutrient loss is animal excreta which, for nitrogen (N), relates to cattle urine in particular. Most models used to describe N cycling and predict loss assume homogeneous distribution of urine patches across grazing areas. This study aims to provide baseline knowledge of the temporal and spatial distribution of N by monitoring the urination behaviour of individual dairy cows on a commercial farm using remote precision tools. The study took place on No 4 Dairy Farm, Massey University, Palmerston North, New Zealand during early autumn in March 2009. Thirty cows in late lactation, balanced for milking order and age, from a herd of 180 milking cows, were fitted with global positioning system collars and urine sensors for seven consecutive days. The herd was milked twice a day and rotationally grazed, without supplementation. Cows were rotated through 12 paddocks, each ~1.1 ha. The majority of urine (85 % of total) was deposited on pasture, while 10 % of total urine deposits were captured in the holding yard and milking shed. Kernel density estimates indicated that urine patch distribution was not homogeneous, thus there was aggregation of urine patches within particular areas of the paddocks. Moderate correlations between the time spent in a location and urine patch density provided evidence that the time spent in a particular location was a factor affecting the density of urine patches. Substantial variation in results between paddocks suggested that paddock characteristics did not play a major role in determining urine distribution patterns in this study.

BACKGROUND:The main source of nitrogen (N) leaching from grazed pastures is animal urine with a high N deposition rate (i.e. per urine patch), particularly between late summer and early winter. Salt is a potential mitigation option as a diuretic to induce greater drinking-water intake, increase urination frequency, decrease urine N concentration and urine N deposition rate, and thereby potentially decrease N leaching. This hypothesis was tested in three phases: a cattle metabolism stall study to examine effects of salt supplementation rate on water consumption, urination frequency and urine N concentration; a grazing trial to assess effects of salt (150 g per heifer per day) on urination frequency; and a lysimeter study on effects of urine N rate on N leaching.RESULTS:Salt supplementation increased cattle water intake. Urination frequency increased by up to 69%, with a similar decrease in urine N deposition rate and no change in individual urination volume. Under field grazing, sensors showed increased urination frequency by 17%. Lysimeter studies showed a proportionally greater decrease in N leaching with decreased urine N rate. Modelling revealed that this could decrease per-hectare N leaching by 10-22%.CONCLUSIONS:Salt supplementation increases cattle water intake and urination frequency, resulting in a lower urine N deposition rate and proportionally greater decrease in urine N leaching. Strategic salt supplementation in autumn/early winter with feed is a practical mitigation option to decrease N leaching in grazed pastures.

Geovisual analytics provides a framework for the development of decision support tools for landscape design, analysis and optimisation. An important application is modelling the spatial-temporal movements of ruminants and their grazing behaviour using global positioning system (GPS) collar units. This study describes the mapping and analysis of spatial distributions of animal waste products (which correlate with farm nitrogen [N] emissions) and also determination of animal feeding preferences (which correlate with animal welfare and production). Segmentation of local regions of animal N emissions provides support in meeting targets for local and international N leaching and greenhouse gas emissions. An agent-based model was used for pre-screening in order to gain insights into the clustering behaviour of sheep during feeding activities. Subsequent spatial analysis demonstrated that livestock excreta are not always randomly located, but concentrated around highly localised animal gathering points, separated by the nature of the excretion. In a separate study, the statistical significance of feeding choices was determined by testing a null hypothesis on animal boundary transitions between adjacent pastures using the binomial approximation. The analysis also included compensation for the precision of the GPS sensor, which produced a fuzzy decision boundary.

Urine of grazing livestock is the greatest contributor to leached nitrogen (N) in our environment. While many N cycling models have used average urine excretions as input data, concentration and volume of individual urination events can vary greatly. Stock camps receive large amounts of urine and pose a high risk of N leaching, especially when animals are set stocked over several days. A new urine sensor is described, along with the variation in urine characteristics of break-grazed cows. N leaching was modelled based on sensor data collection, and paddock-scale estimates were compared to those based on average urine data. There was a 10% difference in estimated N leached by two pumice soils, but both leached 10% less N when varying urine values were used compared to average urine values. The new data showed a frequency distribution pattern of urinary N concentration in urination events that differed to that estimated using earlier data. Thus, frequency distribution patterns have a large effect on modelled N leaching loss and need to be based on extensive data collection to increase the confidence in improving estimates of N leaching. Campsites, which occupy 5-15% of a hill country paddock, account for about half of all excreted urine; their locations can be predicted for the targeting of N-loss mitigation strategies using a simple topographic map of the farm. Keywords: nitrogen leaching, urine volume, environment, urinary nitrogen concentration

The lamb industry in Victoria is a significant component of the state economy with annual exports in the vicinity of $1 billion. GPS and visualisation tools can be used to monitor grazing animal movements at the farm scale and observe interactions with the environment. Modelling the spatial-temporal movements of grazing animals in response to environmental conditions provides input for the design of paddocks with the aim of improving management procedures, animal performance and animal welfare. The term "biological shepherding" is associated with the re-design of environmental conditions and the analysis of responses from grazing animals. The combination of biological shepherding with geo-visual analytics (geo-spatial data analysis with visualisation) provides a framework for improving landscape design and supports research in grazing behaviour in variable landscapes, heat stress avoidance behaviour during summer months, and modelling excreta distributions (with respect to nitrogen emissions and nitrogen return for fertilising the paddock). Nitrogen losses due to excreta are mainly in the form of gaseous emissions to the atmosphere and leaching into the groundwater. In this study, background and context are provided in the case of biological shepherding and tracking animal movements. Examples are provided of recent applications in regional Australia and New Zealand. Based on experimental data and computer simulation, and using data visualisation and feature extraction, it was demonstrated that livestock excreta are not always randomly located, but concentrated around localised gathering points, sometimes separated by the nature of the excretion. Farmers require information on the nitrogen losses in order to reduce emissions to meet local and international nitrogen leaching and greenhouse gas targets and to improve the efficiency of nutrient management.

Nitrogen (N) leaching losses from grazing systems originate primarily from animal urine patches. The N load in urine patches has strong effects on N leaching and varies largely with variations in volume and N concentration of urination events. The effects of these variations in volume and N concentration of urination events on N leaching have not yet been explored. We present a framework for assessing N leaching losses from grazed pastures that incorporates variations of urination events. We found that, for the same amount of urinary N deposition, annual N leaching losses at paddock level increased logarithmically with increased mean urine volume or N concentration, though N leaching at urine patch level increased exponentially with N deposition rate. The estimates of N leaching losses using mean urine patches, derived from mean urine volume and N concentration, would be less than that estimated using variable urine patches as deposited by animals. Results for a case-study pasture on free-draining pumice soils indicate that, for the same number of urination events, depositing the same amount of urinary N within a year, N leaching would be underestimated by 5–8%, when using average urine patches as opposed to varying both volume and N concentration; and the underestimation would be bigger for pastures on soils of greater water holding capacity. Our results indicate the necessity of more accurate estimation of mean and variation patterns of urine volume and N concentration of urination events for improving estimates of N leaching risks. The results support the development of N leaching mitigation strategies by feeding animal diuretics, and are useful to recommend animal species and age class for areas of high N leaching risks.

Application of the nitrification inhibitor DCD is a promising technology for reducing N loss from grazed pastures, but its application over the whole farm may not be economically justified, especially on hills that require aerial application. Critical source areas (CSAs), such as stock camps, represent the areas of highest urinary-N deposition, highest N loss risk, and potential highest efficacy of DCD application in mitigating N loss. However, holding urinary N as ammonium for a period of time following DCD application may not reduce N leaching because the plants‟ potential to uptake N from CSA soils may have been exceeded. We used agro-ecosystem models, corroborated by available knowledge and experimental results, to assess efficacy of DCD applied to stock campsites to mitigate N leaching. Observation of GIS-tracked cattle grazing hill pastures indicates that 50% of urination events may be deposited on 6-16% of pasture areas (campsites). Our modelling showed that the intensity of urinary N aggregation within campsites will determine the soil mineral N status, N-leaching risk and the efficacy of DCD. With increasing urinary N aggregation, total N leached averaged over the whole pasture increased exponentially. DCD efficacy at reducing N leaching (kg N/ha, or %) was highest on campsites of „moderate urinary N aggregation‟, and the cost-effectiveness (reduction of N leached (kg N/ha/$ spent on DCD) was highest on campsites of high urinary-N aggregation. Our analyses suggest that applying DCD on campsites is a relatively cost-effective N mitigation strategy, but accurate evaluation of the efficiency using this framework is still challenging, requiring assessment of the urinary-N aggregation intensity and a more robust function describing the DCD effects.

Farmers have indicated that perennial pastures sown in the Lake Taupo catchment revert to low quality species within 8 to 10 years. These may be renewed with perennial pasture species following an autumn then spring cropping regime, or resown pasture-topasture by direct-drilling into glyphosate-sprayed turf or following full cultivation. Vegetation which is desiccated and/or ploughed-under before sowing will decay and release mineral nitrogen (N). The mineral N from these sources is available for newly sown plants but can also be leached. In a large, replicated, rotationally cattle-grazed trial near Lake Taupo, new pasture was established with the high sugar ryegrass (HSG) Aberdart in one treatment only by direct-drilling, following glyphosate application in late summer. Existing pasture remained in Control plots. Renovated pasture leached 63 kg nitrate-N ha-1 in the 8 months following establishment compared 8 kg nitrate-N ha-1 in Control (P

A replicated grazing study measuring nitrogen (N) leaching from cattle-, sheep- and deer-grazed pastures was conducted to investigate the impact of different animal species on N leaching in the Lake Taupo catchment in New Zealand. Leaching losses of nitrate N from intensively grazed pastures on a highly porous pumice soil in the catchment averaged 37, 26 and 25 kg N/ha.year for cattle-, sheep- and deer-grazed areas, respectively, over the 3-year study and were not significantly different (P > 0.05). Leaching losses of ammonium N were much lower (3 kg N/ha.year for all three species of grazer; P > 0.05). Amounts of dissolved organic N leached were significantly higher than that of mineral N (nitrate N + ammonium N), and over the 3-year study averaged 44, 43 and 39 kg N/ha.year for cattle-, sheep- and deer-grazed areas, respectively (P > 0.05). On a stock unit equivalence basis (1 stock unit is equivalent to 550 kg DM consumed/year), cattle-grazed areas leached significantly more mineral N than sheep- or deer-grazed areas (5.5, 2.9 and 3.4 g mineral N leached/24 h grazing by 1 stock unit, for cattle, sheep and deer, respectively) (P < 0.001). Likewise, based on the amount of N apparently consumed (estimated by difference in mass of herbage N pre- and post-grazing), cattle-grazed pastures leached more mineral N than sheep- or deer-grazed pastures (123, 75 and 75 g mineral N/kg N apparently consumed for cattle, sheep and deer, respectively) (P < 0.01). This study gives valuable information on mineral N leaching in a high-rainfall environment on this free-draining pumice soil, and provides new data to assist in developing strategies to mitigate mineral N leaching losses from grazed pastures using different animal species.

Precision nutrient management needs analytical tools that aid collection of site-specific data. Adequate soil phosphorus (P) and potassium (K) fertility is crucial for pasture production in New Zealand. This article explores (a) the relationship between 12 spectral indices from in situ canopy reflectance and pasture growth rate (PGR), and pasture P and K content in pastures, (b) the performance of the model in different seasons and (c) the relationship between sensed pasture P and K content and soil P (Olsen P) and K (exchangeable K) fertility. Hyperspectral data were collected from a small area of each of 30 legume-based pastures that varied in soil P (Olsen P 5-72 mg kg(-1)) and soil exchangeable K (0.20-1.32 cmol kg(-1)) in spring 2004 and again in summer 2006. Overall, the photochemical reflectance index (PRI) showed the best coefficients of determination (R 2) for most variables. In an exploratory analysis using all the spectral waveband data, normalized difference spectral indices (NDSIs) using the combination of reflectance at 523 and 583 nm of the pasture canopy gave the best prediction of soil P and exchangeable K status. The prediction of Olsen P from plant P (R-2 > 0.89) and soil K from plant K (R-2 > 0.73) was achieved through fitted logarithmic functions that linked plant P and K to soil P and K status, respectively. This pilot study has been broadened to examine other methodologies for interpreting the spectral data and extended to other pasture types and soil orders.

Much of the nitrogen (N) excreted by grazing animals is within highly concentrated urine patches. The N that is not used by plants is likely to be lost through leaching, emitted as N gases or added to the soil organic N pool. The present study used custom-made global positioning system (GPS) and urine sensors on 20 non-lactating ewes and 20 non-lactating beef heifers grazing steep hill country to determine potential critical source areas for N loss to the environment. Bite counters on four sheep and five heifers showed when and where animals were eating. Animals were monitored simultaneously on 0.5 ha adjacent paddocks over 8 days. Sheep and cows urinated a mean (±s.d.) of 21.2 ± 6.1 and 9.0 ± 3.0 times/day, respectively. Eating started soon after sunrise and increased during the day to reach a maximum in the hour before sunset, after which the eating activity of both species was near zero for most of the night, except for a short feeding period at around 0300 hours. The urination frequency of sheep increased as eating activity increased during the day, but this relationship was not seen in heifers. Land classified as easy hill country (≤12°) comprised 31% of the sheep paddock and contained 23% of the urination events. In contrast, although the easy hill country comprised 33% of the cattle paddock, 46% of the urine patches were in this area. Although aerial application of N mitigation products to whole paddocks or farms is uneconomic, the results of the present study suggest that mitigation products could possibly be cost-effectively targeted to easy contoured, cattle-grazed hill country areas accessible by farm vehicle.

Capturing urine and spreading it evenly across a paddock reduces the risk of nitrogen loss to the environment. This study investigated the effect of 16h/d removal from pasture on the capture of urination events, milk production, pasture intake, and animal welfare from cows grazing fresh pasture in early and late lactation. Forty-eight Holstein-Friesian cows in early [470+/-47kg of body weight (BW); 35+/-9 days in milk] and late (498+/-43kg of BW; 225+/-23 days in milk) lactation were allocated to 3 treatment groups. Cows had access to pasture for either 4h after each milking (2 x 4), for 8h between morning and afternoon milkings (1 x 8), or for 24h, excluding milking times (control). When not grazing, the 2 x 4 and 1 x 8 groups were confined to a plastic-lined loafing area with a woodchip surface. In early lactation, the proportion of urinations on pasture and laneways was reduced from 89% (control) to 51% (1 x 8) and 54% (2 x 4) of total urinations. The 1 x 8 cows ate less pasture [10.9kg of dry matter (DM)/cow per day] than the control (13.6kg of DM/cow per day) and 2 x 4 (13.0kg of DM/cow per day) cows, which did not differ from each other. The 1 x 8 and 2 x 4 cows produced less milk (21 and 22kg of milk/cow per day, respectively) compared with control cows (24kg of milk/cow per day). There were no differences in BW or body condition score (BCS) change across treatment groups, with all groups gaining BW and BCS during the experimental period. In late lactation, there was no difference in pasture intake (mean=8.8kg of DM/cow per day), milk production (mean=10kg of milk/cow per day), and BW or BCS change (mean=3.7kg and -0.2U/cow per week, respectively) between treatment groups. As in early lactation, urinations on pasture and laneways were reduced from 85% (control) to 56% (1 x 8) and 50% (2 x 4) of total urinations. These findings highlight an opportunity to maintain performance and welfare of grazing cows in early and late lactation while capturing additional urine. This can subsequently be spread evenly across pasture to minimize nitrogen loss to the environment.