The glutamate metabotropic receptor 5(GRM5)gene is associated with beef cattle home range and movement tortuosity

Background:The grazing behaviour of herbivores and their grazing personalities might in part be determined genetically,but there are few studies in beef cattle illustrating this.In this study,we investigated for first time the genetic variation within a candidate‘grazing gene',the glutamate metabotropic receptor 5 gene(GRM5),and tested associations between variation in that gene and variation in grazing personality behaviours(GP-behaviours)displayed by free-ranging cows during winter grazing in the steep and rugged rangelands of New Zealand.Mature beef cows(n=303,from 3 to 10 years of age)were tracked with global positioning system(GPS)and,with 5-minutes(min)relocation frequency,various GP-behaviours were calculated.These included horizontal and vertical distances travelled,mean elevation,elevation range,elevation gain,slope,home range and movement tortuosity,variously calculated using daily relocation trajectories with repeated measurements(i.e.,7 to 24 days(d))and satellite-derived digital elevation models(DEM).The different GP-behaviours were fitted into mixed models to ascertain their associations with variant sequences and genotypes of GRM5.Results:We discovered three GRM5 variants(A,B and C)and identified the six possible genotypes in the cattle studied.The mixed models revealed that A was significantly associated with elevation range,home range and movement tortuosity.Similarly,GRM5 genotypes were associated(P<0.05)to home range and movement tortuosity,while trends suggesting association(P<0.1)were also revealed for elevation range and horizontal distance travelled.Most GP-behaviour models were improved by correcting for cow age-class as a fixed factor.The analysis of GP-behaviours averaged per cow age-class suggests that grazing personality is fully established as beef cows reached 4 years of age.Home range and movement tortuosity were not only associated with GRM5 variation,but also negatively correlated with each other(r=-0.27,P<0.001).Conclusions:There seems to be a genetically determined trade-off between home range and movement tortuosity that may be useful in beef cattle breeding programmes aiming to improve the grazing distribution and utilisation of steep and rugged rangelands.

Analysis of forest structural complexity using airborne LiDAR data and aerial photography in a mixed conifer–broadleaf forest in northern Japan

Determining forest structural complexity,i.e.,a measure of the number of different attributes of a forest and the relative abundance of each attribute,is important for forest management and conservation.In this study,we examined the structural complexity of mixed conifer–broadleaf forests by integrating multiple forest structural attributes derived from airborne Li DAR data and aerial photography.We sampled 76 plots from an unmanaged mixed conifer–broadleaf forest reserve in northern Japan.Plot-level metrics were computed for all plots using both field and remote sensing data to assess their ability to capture the vertical and horizontal variations of forest structure.A multivariate set of forest structural attributes that included three Li DAR metrics(95 th percentile canopy height,canopy density and surface area ratio) and one image metric(proportion of broadleaf cover),was used to classify forest structure into structural complexity classes.Our results revealed significant correlation between field and remote sensing metrics,indicating that these two sets of measurements captured similar patterns of structure in mixed conifer–broadleaf forests.Further,cluster analysis identified six forest structural complexity classes includingtwo low-complexity classes and four high-complexity classes that were distributed in different elevation ranges.In this study,we could reliably analyze the structural complexity of mixed conifer–broadleaf forests using a simple and easy to calculate set of forest structural attributes derived from airborne Li DAR data and high-resolution aerial photography.This study provides a good example of the use of airborne Li DAR data sets for wider purposes in forest ecology as well as in forest management.