Apparent and real bias in numerical transfer functions in palaeolimnology

We present an evaluation of the procedure by which model prediction bias is examined in palaeolimnological transfer function inference models. We argue that most of the prediction biases commonly reported in the literature are, in fact, fallacious, and are the artificial consequence of the inappropriate manner in which residuals are traditionally examined. We show that the extent of the specious model bias is entirely predictable from first principles and is essentially determined by the strength of the predictive model. We suggest that the analysis of residuals should always be examined as a function of the model's predictions and we discuss the implications of the old and new approaches.     

Resprout characteristics of creosote bush (Larrea tridentata) when subjected to repeated vehicle damage

Studies were conducted in the central Mojave Desert to quantify how creosote bushes (Larrea tridentata) respond to physical damage during large-scale military training exercises. Creosote bush possesses a resilient growth form that recovers from repeated physical damage via resprouts arising from meristems in stem bark below severed or crushed canopy units. At high levels of disturbance by heavy vehicles, nearly all individuals showed measurable breakage, but without additional damage each plant can regain a full canopy within 5 years under arid field conditions. Resprouts exhibited more vigorous growth and doubled the biomass accumulation stimulated by high rainfall of 1998, an El Niño year, vs. a normal year. New shoots of resprouted individuals were markedly different in morphological traits than canopy old growth and had slightly higher predawn shoot water potentials. The natural ability of this evergreen species to recover from cutting and crushing bodes well for re-establishment of creosote bush desert scrub communities following episodes of severe damage by vehicles.