No abstract

No abstract

Range condition assessment procedures that rely on field—collected botanical data face major problems in nonequilibrium rangelands, which are spatially variable and extensively grazed. These problems include the difficulty of interpreting changes in plant species composition and the logistics of obtaining representative data for large areas. Consideration of ecosystem behavior through time and in space shows that certain spatial and temporal patterns exist that may be used to isolate the impact of grazing from other processes. The patterns also make it possible to distinguish between temporary changes and those that are more long term. All relevant patterns may be expressed in terms of total plant cover and may be monitored from remote sensing satellites. It is therefore possible to derive a set of range condition indicators that may be measured and monitored from space. These indicators use trends in average vegetation cover with distance from water at the end of very wet periods, trends in cover variance with distance from water, and the magnitude of observed vegetation response at individual points in the landscape compared with that which is expected when vegetation recovers fully from grazing. It is also possible to use spatial variability in the rate of cover depletion after rainfall to infer relative differences in the amount of forage present. When used in combination, the methods offer a realistic alternative to field—based assessment and are capable of detecting many types of rangeland degradation. They are also considerably cheaper to use.

No abstract

No abstract

No abstract

SUMMARYRegression equations with the form y =f(q), where y is a channel characteristic and q is a discharge of a particular frequency are widely used in fluvial geomorphology. They imply that channel geometry is related to a dominant discharge. For this to be so, the river must be 'in regime' i.e. its characteristics must fluctuate about a mean condition which is effectively stationary at the time scale considered. The static regression-dominant discharge approach does not fully describe the relationship between channel characteristics and discharge and an alternative model is proposed with the form y ( t ) = l ; h ( u ) . q ( t -u ) d u . This model states that channel form is a product of the whole series of discharges experienced by the channel. The dominant discharge-static regression approach provides a working approximation of the relationship between channel characteristics and discharge only when temporal variations in q are small or when y is insensitive to variations in q.

No abstract