Coupled Information Diffusion–Pest Dynamics Models Predict Delayed Benefits of Farmer Cooperation in Pest Management Programs

Worldwide, the theory and practice of agricultural extension system have been dominated for almost half a century by Rogers' “diffusion of innovation theory”. In particular, the success of integrated pest management (IPM) extension programs depends on the effectiveness of IPM information diffusion from trained farmers to other farmers, an important assumption which underpins funding from development organizations. Here we developed an innovative approach through an agent-based model (ABM) combining social (diffusion theory) and biological (pest population dynamics) models to study the role of cooperation among small-scale farmers to share IPM information for controlling an invasive pest. The model was implemented with field data, including learning processes and control efficiency, from large scale surveys in the Ecuadorian Andes. Our results predict that although cooperation had short-term costs for individual farmers, it paid in the long run as it decreased pest infestation at the community scale. However, the slow learning process placed restrictions on the knowledge that could be generated within farmer communities over time, giving rise to natural lags in IPM diffusion and applications. We further showed that if individuals learn from others about the benefits of early prevention of new pests, then educational effort may have a sustainable long-run impact. Consistent with models of information diffusion theory, our results demonstrate how an integrated approach combining ecological and social systems would help better predict the success of IPM programs. This approach has potential beyond pest management as it could be applied to any resource management program seeking to spread innovations across populations

Impacts of climate change on plant diseases – opinions and trends

There has been a remarkable scientific output on the topic of how climate change is likely to affect plant diseases in the coming decades. This review addresses the need for review of this burgeoning literature by summarizing opinions of previous reviews and trends in recent studies on the impacts of climate change on plant health. Sudden Oak Death is used as an introductory case study: Californian forests could become even more susceptible to this emerging plant disease, if spring precipitations will be accompanied by warmer temperatures, although climate shifts may also affect the current synchronicity between host cambium activity and pathogen colonization rate. A summary of observed and predicted climate changes, as well as of direct effects of climate change on pathosystems, is provided. Prediction and management of climate change effects on plant health are complicated by indirect effects and the interactions with global change drivers. Uncertainty in models of plant disease development under climate change calls for a diversity of management strategies, from more participatory approaches to interdisciplinary science. Involvement of stakeholders and scientists from outside plant pathology shows the importance of trade-offs, for example in the land-sharing vs. sparing debate. Further research is needed on climate change and plant health in mountain, boreal, Mediterranean and tropical regions, with multiple climate change factors and scenarios (including our responses to it, e.g. the assisted migration of plants), in relation to endophytes, viruses and mycorrhiza, using long-term and large-scale datasets and considering various plant disease control methods

Low-cost automatic temperature monitoring system with alerts for laboratory rearing units

Monitoring accurately temperature is a key issue in biological studies involving living experimental material. It is especially true for insects which body temperature is mostly controlled by environmental temperature, with profound consequences of a few degrees variation on most physiological processes such as survival, development, fecundity, and mobility. If programmable rearing units can be purchased, it remains important to monitor and store temperature information acquired inside the rearing unit to ensure that observed phenomena are not the result of unintended and not scarily noticeable changes in temperature, and to account for the effect of temperature variation in statistical analysis. As most laboratories involved in insect rearing dispose of a large number of rearing units, the technical solution should meet the monitoring needs while being affordable and adaptable to various experimental designs. For that purpose, we designed a low cost (below 100(sic)) and open source automatic temperature monitoring system for rearing units in laboratory. Key features providing advantage over pre-existing methods include: Highly configurable temperature monitoring and life-time storage capacity Email alerts based on configurable user-defined threshold Automatic configurable reports in the form of dashboard

Eigenvalues and eigenvectors of a special class of band matrices

Scopo di questo lavoro è fornire autovalori ed autovettori esatti di una classe di particolari matrici, che possono essere usate come matrici test. Sono state considerate a tal fine dapprima matrici di Toeplitz tridiagonali, quindi matrici ottenute da queste con opportune correzioni ed infine alcune matrici di Haenkel, legate alle precedenti da una relazione di similitudine.The aim of this paper is to give exact eigenvalues and eigenvectors of a class of special matrices, to be used in testing algorithms. To this end, first Toeplitz tridiagonal matrices are considered, then matrices obtained from them by corrections and after a class of Haenkel matrices related to the privious by similarity transformations

The effect of diet Interacting with temperature on the development rate of a Noctuidae quinoa pest

The quinoa pest Copitarsia incommoda (Walker, Lepidoptera: Noctuidae) is a cause of significant damage, and it is thus critical for Andean countries to have access to phenological models to maintain production and food safety. These models are key components in pest control strategies in the context of global warming and in the development of sustainable production integrating agroecological concepts. Phenological models are mainly based on outlining the relationship between temperature and development rate. In this study, we investigated the combined effect of protein content within the diet (artificial diet; artificial diet with ?20% protein; artificial diet with +20% protein; natural quinoa diet) and temperature (12, 16.9, 19.5, 22.7, 24.6°C) as drivers of the development rate. Our study supports the literature, since temperature was found to be the main driver of the development rate. It highlights the significant role played by protein content and its interaction with temperature (significant effects of temperature, diet, and diet:temperature on development time using GLMs for all foraging life stages). We discuss the implications of such drivers of the development rate for implementing and applying phenological models that may benefit from including factors other than temperature. While performance curves such as development rate curves obtained from laboratory experiments are still a useful basis for phenological development, we also discuss the need to take into account the heterogeneity of the insect response to environmental factors. This is critical if pest control practices are to be deployed at the optimal time