Climate change and crop diversity: farmers’ perceptions and adaptation on the Bolivian Altiplano

Crop diversity is central to traditional risk management practices on the Andean Altiplano and may find renewed importance in adapting to climate change. This study explored the role of crop diversity in farmers’ adaptation actions in eight Aymara communities on the northern Bolivian Altiplano. Using a combination of quantitative and qualitative methods, including multifactor analysis and a community resilience self-assessment, we investigated how farmers’ use of diversity in adaptation is related to their perceptions of crop and variety tolerances and other environmental, social, and economic factors. Few crops and varieties were perceived as tolerant to increasingly intense and unpredictable drought, frost, hail, and pest and disease outbreaks. Some local crops and varieties were perceived as vulnerable to emerging conditions (e.g. oca, papalisa, isaño), whereas bitter potatoes and wild relatives of quinoa and cañahua were perceived as highly stress tolerant and provide food in harsh periods. A total 19% of households surveyed (N = 193) had introduced new crops or varieties—often disease resistant or early maturing—as an adaptive action. Introduction of commercial crops was a common adaptation action, reflecting farmers’ response to warming temperatures and changing economic opportunities, but greater sensitivity of the introduced crops may cause maladaptation. Despite intensification of cropping systems, households continue to maintain a median four potato varieties with different tolerance traits, yet this risk management practice was not perceived as adaptation. Strengthening resilience will require a combination of actions, including maintaining and expanding crop portfolios and restoring soil and ecosystem health, using both traditional and innovative approaches.     

Effects of ammonia, nitrite and nitrate on hemoglobin content and oxygen consumption of freshwater fish, Cyprinus carpio (Linnaeus)

Lethal effects of nitrogenous compounds ammonia, nitrite and nitrate on freshwater fish Cyprinus carpio were studied and the static LC50 values obtained for these 3 toxicants for 24 hr were 0.80 ppb, 171.36 ppm; 1075.10 ppm and continuous flowthrough LC50 values for 24 hr were 0.72 ppb, 154.31 ppm; 967.63 ppm respectively. The fish were exposed to lethal concentrations to study the changes in hematological parameters and the rate of oxygen consumption. During the period of exposure general decline in the content of hemoglobin was observed. Methemoglobin content increased in case of nitrite exposure consequently the hemoglobin levels decreased drastically. It is also observed that rate of oxygen consumption decreased progressively with the increase of toxicant concentration and duration of the exposure.     

Nocturnal herbivore-induced plant volatiles attract the generalist predatory earwig <Emphasis Type="Italic">Doru luteipes</Emphasis> Scudder

Numerous studies have demonstrated that entomophagous arthropods use herbivore-induced plant volatile (HIPV) blends to search for their prey or host. However, no study has yet focused on the response of nocturnal predators to volatile blends emitted by prey damaged plants. We investigated the olfactory behavioral responses of the night-active generalist predatory earwig Doru luteipes Scudder (Dermaptera: Forficulidae) to diurnal and nocturnal volatile blends emitted by maize plants (Zea mays) attacked by either a stem borer (Diatraea saccharalis) or a leaf-chewing caterpillar (Spodoptera frugiperda), both suitable lepidopteran prey. Additionally, we examined whether the earwig preferred odors emitted from short- or long-term damaged maize. We first determined the earwig diel foraging rhythm and confirmed that D. luteipes is a nocturnal predator. Olfactometer assays showed that during the day, although the earwigs were walking actively, they did not discriminate the volatiles of undamaged maize plants from those of herbivore damaged maize plants. In contrast, at night, earwigs preferred volatiles emitted by maize plants attacked by D. saccharalis or S. frugiperda over undamaged plants and short- over long-term damaged maize. Our GC-MS analysis revealed that short-term damaged nocturnal plant volatile blends were comprised mainly of fatty acid derivatives (i.e., green leaf volatiles), while the long-term damaged plant volatile blend contained mostly terpenoids. We also observed distinct volatile blend composition emitted by maize damaged by the different caterpillars. Our results showed that D. luteipes innately uses nocturnal herbivore-induced plant volatiles to search for prey. Moreover, the attraction of the earwig to short-term damaged plants is likely mediated by fatty acid derivatives.     

A Comparison of Nonlinear Regression and Neural Network Models for Ground-Level Ozone Forecasting

ABSTRACT

A hybrid nonlinear regression (NLR) model and a neural network (NN) model, each designed to forecast next-day maximum 1-hr average ground-level O₃ concentrations in Louisville, KY, were compared for two O₃ seasons—1998 and 1999. The model predictions were compared for the forecast mode, using forecasted meteorological data as input, and for the hindcast mode, using observed meteorological data as input. The two models performed nearly the same in the forecast mode. For the two seasons combined, the mean absolute forecast error was 12.5 ppb for the NLR model and 12.3 ppb for the NN model. The detection rate of 120 ppb threshold exceedances was 42% for each model in the forecast mode. In the hindcast mode, the NLR model performed marginally better than the NN