Dietary overlap of snow leopard and other carnivores in the Pamirs of Northwestern China

Information about competition between carnivore species for food within high altitude regions is limited.Data collected from the Taxkorgan Nature Reserve,China revealed important interactions between snow leopard(Panthera uncia),grey wolf(Canis lupus),red fox(Vulpes vulpes)and their prey species,including domestic livestock.Sixty-four line transects were conducted in order to identify field signs of habitat occupancy and collect scats for diet analysis.High dietary overlap was observed between all three carnivore species:snow leopard and red fox(Pianka’s index=0.96),red fox and grey wolf(Pianka’s index=0.90),snow leopard and grey wolf(Pianka’s index=0.87).Snow leopard and grey wolf showed significant predation on livestock(36.8%for snow leopard and 29.4%for grey wolf in diet composition).As a pioneering exploration of the endangered snow leopard and its relationship with other species within the alpine ecosystem under livestock grazing pressure,this study contributes a greater understanding of the relationship within carnivore guild in the Pamirs whilst providing implications for conservation planning and project implementation activities in China.     

Geopolitical risk and global financial cycle: Some forecasting experiments

In this study, we investigate the connection between geopolitical risk (GPR) and global financial cycle (GFCy) as well as whether the former has predictive value for the out-of-sample predictability of the latter. We utilize both the historical and recent GPR data and their variants, namely, GPR act covering all “acts” that constitute GPR such as war, nuclear invasion and terrorism, and GPR threat, which represents threats of these acts. We construct a predictive model that accommodates the salient features of the predicted and predictor series while the forecast evaluation is conducted for both in-sample and out-of-sample periods. Our findings reveal that a rise in GPR discourages investments in risky assets and by implication worsens GFCy. The impact is more severe after the global financial crisis (gfc), and the GPR threat exerts more adverse effect on GFCy compared with GPR act regardless of whether historical GPR or recent GPR is used. Meanwhile, the predictive model of GFCy that accommodates the GPR data outperforms the benchmark model that ignores it both in the in-sample and out-of-sample estimates albeit with improved forecast performance during the post-gfc period and at a longer forecast horizon. However, the recent GPR data, which are broader in scope, offer better forecast accuracy than the historical GPR data. Additional analyses involving the vulnerability of global economic conditions reveal similar outcomes as GFCy.     

The impact of seasonal constants on forecasting seasonally cointegrated time series

In this paper we focus on the effect of (i) deleting, (ii) restricting or (iii) not restricting seasonal intercept terms on forecasting sets of seasonally cointegrated macroeconomic time series for Austria, Germany and the UK. A first empirical result is that the number of cointegrating vectors as well as the relevant estimated parameter values vary across the three models. A second result is that the quality of out-of-sample forecasts critically depends on the way seasonal constants are treated. In most cases, predictive performance can be improved by restricting the effects of seasonal constants. However, we find that the relative advantages and disadvantages of each of the three methods vary across the data sets and may depend on sample-specific features. © 1998 John Wiley & Sons, Ltd.