Understanding sheep baa-haviour: Investigating the relationship between pasture and animal grazing patterns

Background:Grasslands are the primary source of feed for grazing livestock,and as such,knowledge on how to best manage livestock and grasslands,through the use of spatiotemporal modelling,will assist in the long-term management of a valuable ecosystem resource.Methods:This study was conducted over 14 months between March and April 2017 in Orange,NSW,Australia.The study evaluated sheep behaviour in relation to the presence of pasture species,environment and paddock structures,using random forest modelling,to predict sheep location under continuous high(HSR,13 DSE ha−1)and low(LSR,7DSE ha−1)stocking rates.Results:In the LSR,significant drivers included water,shade and fence lines(p<0.01).In the HSR,only fence lines and available biomass were found to be significant(p<0.01).The presence of green legumes in both stocking rates often increased residency by sheep.Animals spent more time together in the LSR,suggesting that social behaviour played a larger role than pasture quantity and quality in driving grazing behaviours.Conclusions:Understanding how pasture type can influence grazing behaviours and also how animal behaviour affects pasture performance and utilisation is important in developing long-term sustainable management strategies on a paddock scale.

Assimilation of Total Lightning Data Using the Three-Dimensional Variational Method at Convection-Allowing Resolution

A large number of observational analyses have shown that lightning data can be used to indicate areas of deep convection. It is important to assimilate observed lightning data into numerical models, so that more small-scale information can be incorporated to improve the quality of the initial condition and the subsequent forecasts. In this study, the empirical relationship between flash rate, water vapor mixing ratio, and graupel mixing ratio was used to adjust the model relative humidity, which was then assimilated by using the three-dimensional variational data assimilation system of the Weather Research and Forecasting model in cycling mode at 10-min intervals. To find the appropriate assimilation time-window length that yielded significant improvement in both the initial conditions and subsequent forecasts, four experiments with different assimilation time-window lengths were conducted for a squall line case that occurred on 10 July 2007 in North China. It was found that 60 min was the appropriate assimilation time-window length for this case, and longer assimilation window length was unnecessary since no further improvement was present. Forecasts of 1-h accumulated precipitation during the assimilation period and the subsequent 3-h accumulated precipitation were significantly improved compared with the control experiment without lightning data assimilation. The simulated reflectivity was optimal after 30 min of the forecast, it remained optimal during the following 42 min, and the positive effect from lightning data assimilation began to diminish after 72 min of the forecast. Overall,the improvement from lightning data assimilation can be maintained for about 3 h.