1. Vegetation greenness, detected using digital photography, is useful for monitoring phenology of plant growth, carbon uptake and water loss at the ecosystem level. Assessing ecosystem phenology by greenness is especially useful in spatially extensive, water-limited ecosystems such as the grasslands of the western United States, where productivity is moisture dependent and may become increasingly vulnerable to future climate change.2. We used repeat photography and a novel means of quantifying greenness in digital photographs to assess how the individual and combined effects of warming and elevated CO 2 impact ecosystem phenology (greenness and plant cover) in a semi-arid grassland over an 8-year period.3. Climate variability within and among years was the proximate driver of ecosystem phenology. Individual and combined effects of warming and elevated CO 2 were significant at times, but mediated by variation in both intra-and interannual precipitation. Specifically, warming generally enhanced plant cover and greenness early in the growing season but often had a negative effect during the middle of the summer, offsetting the early season positive effects. The individual effects of elevated CO 2 on plant cover and greenness were generally neutral. 4.Opposing seasonal variations in the effects of warming and less so elevated CO 2 cancelled each other out over an entire growing season, leading to no net effect of treatments on annual accumulation of greenness. The main effect of elevated CO 2 dampened quickly, but warming continued to affect plant cover and plot greenness throughout the experiment. The combination of warming and elevated CO 2 had a generally positive effect on greenness, especially early in the growing season and in later years of the experiment, enhanced annual greenness accumulation. However, interannual precipitation variation had larger effect on greenness, with two to three times greater greenness in wet years than in dry years. 5.Synthesis. Seasonal variation in timing and amount of precipitation governs grassland phenology, greenness and the potential for carbon uptake. Our results indicate that concurrent changes in precipitation regimes mediate vegetation responses to warming and elevated atmospheric CO 2 in semi-arid grasslands. Even small changes in vegetation phenology and greenness in response to warming and rising atmospheric CO 2 concentrations, such as those we report here, can have large consequences for the future of grasslands.

We present an agent-based model of bicycle racing that incorporates both physiology and the types of multiplayer

In this paper we study the simultaneous problems of food waste and hunger in the context of food (waste) rescue and redistribution as a means for mitigating hunger. To this end, we develop an empirical model that can be used in Monte Carlo simulations to study the dynamics of the underlying problem. Our model's parameters are derived from a data set provided by a large food bank and food rescue organization in north central Colorado. We find that food supply is a non-parametric heavy-tailed process that is well modeled with an extreme value peaks over threshold model. Although the underlying process is stochastic, the basic approach of food rescue and redistribution to meet hunger demand appears to be feasible. The ultimate sustainability of this model is intimately tied to the rate at which food expires and hence the ability to preserve and quickly transport and redistribute food. The cost of the redistribution is related to the number and density of participating suppliers. The results show that costs can be reduced (and supply increased) simply by recruiting additional donors to participate. With sufficient funding and manpower, a significant amount of food can be rescued from the waste stream and used to feed the hungry.

Fostering an effective learning environment in large classes is a challenge: instructors and teaching assistants are stretched thin across many students, students often lack opportunities for personal interaction with course staff, and the size of the classes makes them seem impersonal. Furthermore, students in large classes can often find solutions to their labs and assignments online or copy them from other students, diminishing their impetus to learn and raising plagiarism concerns.This paper describes our experience and evaluation of an assessment method that resolves many of these problems and appears to scale to large classes of 600+ students. Using this method, students are evaluated via a combination of automatic grading mechanisms (or clear objective rubrics) and a 1-on-1 "grading interview". The grading interview serves to ensure the provenance of the student's work product and their depth of understanding. This change allows us to make more effective use of peer-instruction and pairprogramming in our courses. It also provides the ability to reuse assignments, the insurance of timely feedback to students, and the opportunity for individualized staff attention.This paper describes variations on this method across numerous classes over the past seven years, some of the goals of this method, modifications and adaptations of the method over time, and the student experience of using this method based on survey feedback.

Plants can have positive effects on each other in numerous ways, including protection from harsh environmental conditions. This phenomenon, known as facilitation, occurs in water-stressed environments when shade from larger shrubs protects smaller annuals from harsh sun, enabling them to exist on scarce water. The topic of this paper is a model of this phenomenon that allows search algorithms to find residential landscape designs that incorporate facilitation to conserve water. This model is based in botany; it captures the growth requirements of real plant species in a fitness function, but also includes a penalty term in that function that encourages facilitative interactions with other plants on the landscape. To evaluate the effectiveness of this approach, two search strategies--simulated annealing and agent-based search--were applied to models of different collections of simulated plant types and landscapes with different light distributions. These two search strategies produced landscape designs with different spatial distributions of the larger plants. All designs exhibited facilitation and lower water use than designs where facilitation was not included.