Seasonality of mating and birth in wild black-and-white snub-nosed monkeys (Rhinopithecus bieti) at Xiaochangdu, Tibet

Data on mating and birth seasonality were recorded in wild black-and-white snub-nosed monkeys (Rhinopithecus bieti) at Xiaochangdu in the Honglaxueshan National Nature Reserve, Tibet. This represents one of the harshest habitats utilized by any nonhuman p

Reproductive seasonality and maturity of male Neophocaena phocaenoides asiaeorientalis in captivity: A case study based on the hormone evidence

To provide hormone evidence on reproductive seasonality and maturity of the Yangtze finless porpoise, the authors monitored the monthly variations of serum reproductive hormones of a male Yangtze finless porpoise in captivity via radioimmunoassay from 1997 to 2003. It was demonstrated that the immature animal had a serum T level of 28-101ngdL -1 (6552ngdL -1 ), reached puberty with the serum T concentration ranging between 250 and 590ngdL -1 (390130ngdL -1 ), and attained reproductive maturity when the serum T level went beyond 1120180ngdL -1 in the breeding season. The body length growth of the animal showed a pattern similar to the serum T variations during its adolescent period from the age of 4 to 6 years. Moreover, the serum T concentration of the male porpoise exhibited significant seasonal variations, indicating that its breeding season may start as early as March and end as late as September.

A non-linear perturbation model considering catchment wetness and its application in river flow forecasting

A non-linear perturbation model for river flow forecasting is developed, based on consideration of catchment wetness using an antecedent precipitation index (API). Catchment seasonality, of the form accounted for in the linear perturbation model (the LPM), and non-linear behaviour both in the runoff generation mechanism and in the flow routing processes are represented by a constrained nan-linear model, the NLPM-API. A total of ten catchments, across a range of climatic conditions and catchment area magnitudes, located in China and in other countries, were selected for testing daily rainfall-runoff forecasting with this model. It was found that the NLPM-API model was significantly more efficient than the original linear perturbation model (the LPM). However, restric tion of explicit nan-linearity to the runoff generation process, in the simpler LPM-API form of the model, did not produce a significantly lower value of the efficiency in flood forecasting, in terms of the model efficiency index R-2. (C) 1997 Elsevier Science B.V.

Characteristic rainfall for warning of debris flows

A characteristic rainfall is introduced to overcome the difficulties encountered in determining a critical rainfall value for triggering debris flow. The characteristic value is defined as the rainfall at which debris-flow occurrence probability shows a rapid increase, and can be used as a warning rainfall threshold for debris flows. Investigation of recorded debris flows and 24-hour rainfall data at Jiangjia basin, Yunnan Province, in southwestern China, demonstrates the existence of such a characteristic rainfall. It was found that the characteristic rainfall corresponds to the daily rainfall of 90% cumulative probability by analyzing the basin's daily rainfall histogram. The result provides a simple and useful method for estimating a debris-flow warning rainfall threshold from the daily rainfall distribution. It was applied to estimate the debris-flow warning rainfall threshold for the Subaohe basin, a watershed in the 2008 Wenchuan earthquake zone with many physical characteristics similar to those of the Jiangjia basin.

Adsorbed silica in stalagmite carbonate and its relationship to past rainfall

IEECAS SKLLQG

delta C-13 variation of C-3 and C-4 plants across an Asian monsoon rainfall gradient in arid northwestern China

IEECAS SKLLQG

Modeling of Hillslope Runoff and Soil Erosion at Rainfall Events Using Cellular Automata Approach

National Science Fund for Distinguished Young Scholars of China [40225004]; National Natural Science Foundation of China [40471048]