دانلود رایگان مقاله ارزیابی ریسک خشکسالی در چراگاه های مدیترانه

Abstract

Extensive grazing activities in the Mediterranean area will have to confront an increasing risk of drought. This threat poses a challenge to the long-term viability of these activities that play an important role in rural development and have traditionally shaped highly valued ecosystems such as the Dehesa landscape in the Iberian Peninsula. The aim of this research is to assess the economic impact of drought on this extensive livestock farming system and evaluate the potential of adaptation strategies such as reducing the stocking rate. A dynamic and stochastic bioeconomic model is developed to account for the complex climatic, ecologic and economic relationships at play during drought. We simulate the 1999–2010 weather time series to characterize seasonal patterns and evaluate the risk caused by drought spells. We assess the consequences of drought in terms of duration, frequency and intensity, finding that economic losses increase at an increasing rate with long lasting droughts. Our findings reveal different patterns between climate and economic risk variables. The risk of a climate shock concentrates in spring and the beginning of autumn while the risk of suffering economic losses occurs with a 3–4 weeks delay and lasts for a longer period of time. We integrate Monte Carlo routines in our simulation model to assess risk exposure and propose the use of Value-at-Risk to capture downside risk at different thresholds. Our simulation results show that the farmer may have to confront annual economic losses above 22.9% with a 5% probability in the current or baseline scenario. Finally, we use the model as a tool to evaluate the potential of adaptation strategies such as increasing or reducing the stocking rate. We find that the former has rather limited impact on average income as compared to the later but both show significant impacts on risk exposure, which may entail important economic consequences. In particular, we find that increasing the stocking rate by 20% decreases the probability of incurring moderate losses, from 45.0% to 40.6%. Furthermore, it also increases the probability of favourable outcomes, from 50.0% to 52.0%. However, this comes at the expense of a significant increase in the chance of experiencing severe economic impacts, from 5 to 6.9%. On the contrary, reducing the stocking rate by 20% reduces the chance of severe impacts from 5% to 3.7%, but also entails an increase in the probability of moderate losses and a significant drop in the probability of experiencing a favourable outcome

4. Conclusions

We presented a dynamic and stochastic bio-economic model to assess the economic risk of drought in grazing activities that sustain Dehesas, a highly valued silvo-pastoral ecosystem in the Southwestern part of the Iberian Peninsula. Field surveys, expert assessment and literature review were used to parameterize the model. Simulated pasture growth and economic model outcomes were validated by performing comparison against fieldwork and observed satellite NDVI data respectively. The model is based on a relatively limited amount of technical data and we claim that use of widely available satellite information for calibration and validation purposes may help to apply the model in other semi-arid areas. Our modelling framework contributes to the literature with several distinguished features. First, it allows for both inter-annual and intra-annual variability in order to better understand how climate risk translates into economic losses. Our results reveal complex patterns and show that, while climate risks concentrate at the beginning of spring and autumn, economic risk usually occurs later and lasts longer. These results are in line with previous research work that reports a delay between climate risk and its economic consequences (Freier et al., 2011; Wilhite and Glantz, 1985). We further characterized impacts and assessed episodes of drought in terms of duration, frequency and intensity revealing that the economic impact of a prolonged period of drought increase in a non-linear fashion. In addition, identifying critical factors and main sources of risk offers useful insights and may provide guidelines for the design of assistance, relief or other drought risk mitigation measures, such as insurance policy.