Probabilistic methods for seasonal forecasting in a changing climate: Cox-type regression models.

For climate risk management, cumulative distribution functions (CDFs) are an important source of information. They are ideally suited to compare probabilistic forecasts of primary (e.g. rainfall) or secondary data (e.g. crop yields). Summarised as CDFs, such forecasts allow an easy quantitative assessment of possible, alternative actions. Although the degree of uncertainty associated with CDF estimation could influence decisions, such information is rarely provided. Hence, we propose Cox-type regression models (CRMs) as a statistical framework for making inferences on CDFs in climate science. CRMs were designed for modelling probability distributions rather than just mean or median values. This makes the approach appealing for risk assessments where probabilities of extremes are often more informative than central tendency measures. CRMs are semi-parametric approaches originally designed for modelling risks arising from time-to-event data. Here we extend this original concept beyond time-dependent measures to other variables of interest. We also provide tools for estimating CDFs and surrounding uncertainty envelopes from empirical data. These statistical techniques intrinsically account for non-stationarities in time series that might be the result of climate change. This feature makes CRMs attractive candidates to investigate the feasibility of developing rigorous global circulation model (GCM)-CRM interfaces for provision of user-relevant forecasts. To demonstrate the applicability of CRMs, we present two examples for El Ni ? no/Southern Oscillation (ENSO)-based forecasts: the onset date of the wet season (Cairns, Australia) and total wet season rainfall (Quixeramobim, Brazil). This study emphasises the methodological aspects of CRMs rather than discussing merits or limitations of the ENSO-based predictors.

Local productive arrangements for biodiesel production in Brazil: Environmental assessment of small-holders integrated oleaginous crops management.

Sustainability assessments were carried out in small-holders? farms in four territories where productive arrangements have been organized for production of minor oleagi- nous crops under the Brazilian biodiesel program. The study aimed at checking local impacts of the biodiesel productive chains at the rural establishment scale, and pro- moting the environmental performance of the selected farms, henceforth proposed as sustainable management demonstration units. Assessments were carried out with the APOIA-NovoRural system, which integrates 62 objective and quantitative indicators re- lated to five sustainability dimensions: i) Landscape Ecology, ii) Environmental Quality (Atmosphere, Water and Soil), iii) Socio-cultural Values, iv) Economic Values and v) Management and Administration. The main results point out that, in general, the eco- logical dimensions of sustainability, that is, the Landscape Ecology and Atmosphere, Water, and Soil quality indicators, show adequate field conditions, seemingly not yet negatively affected by increases in chemical inputs and natural resources use predicted as important potential impacts of the agro-energy sector. The Economic Values indica- tors have been favorably influenced in the studied farms, due to a steadier demand and improved prices for the oleaginous crops. On the other hand, valuable positive conse- quences expected for favoring farmers? market insertion, such as improved Socio-cultural Values and Management & Administration indicators, are still opportunities to be ma-terialized. The Environmental Management Reports issued to the farmers, based on the presented sustainability assessment procedures, offer valuable documentation and com-munication means for consolidating the organizational influence of the local productive arrangements studied. These productive arrangements were shown to be determinant for the selection of crop associations and diversification, as well as for the provision of technical assistance and the stabilization of demand - conditions that promote value aggregation and income improvements, favoring small-holders? insertion in the market. More importantly, these locally organized productive arrangements have been shown to strongly influence the valorization of natural resources and environmental assets, which are fundamental if sustainable rural development is to take place under the emerging agro-energy scenario.