RESUMEN
Wildfires ravage lands in seasonally dry regions, imposing high costs on infrastructure maintenance and human habitation at the wildland-urban interface. Current fire mitigation approaches present upfront costs with uncertain long-term payoffs. We show that a new landscape intervention on human-managed wildlands-buffers of a low-flammability crop species such as banana irrigated using recycled water-can mitigate wildfires and produce food profitably. This new intervention can complement existing fire mitigation approaches. Recreating a recent, major fire in simulation, we find that a medium-sized (633 m) banana buffer decreases fireline intensity by 96%, similar to the combination of prescribed burns and mechanical thinning, and delays the fire by 316 min, enabling safer and more effective firefighting. We find that under climate change, despite worsened fires, banana buffers will still have a protective effect. We also find that banana buffers with average yield could produce a profit of $56k USD/hectare through fruit sales, in addition to fire mitigation.
RESUMEN
Agriculture is a designed system with the largest areal footprint of any human activity. In some cases, the designs within agriculture emerged over thousands of years, such as the use of rows for the spatial organization of crops. In other cases, designs were deliberately chosen and implemented over decades, as during the Green Revolution. Currently, much work in the agricultural sciences focuses on evaluating designs that could improve agriculture's sustainability. However, approaches to agricultural system design are diverse and fragmented, relying on individual intuition and discipline-specific methods to meet stakeholders' often semi-incompatible goals. This ad-hoc approach presents the risk that agricultural science will overlook nonobvious designs with large societal benefits. Here, we introduce a state space framework, a common approach from computer science, to address the problem of proposing and evaluating agricultural designs computationally. This approach overcomes limitations of current agricultural system design methods by enabling a general set of computational abstractions to explore and select from a very large agricultural design space, which can then be empirically tested.
RESUMEN
Type II topoisomerases are enzymes that change the topology of DNA by performing strand-passage. In particular, they unknot knotted DNA very efficiently. Motivated by this experimental observation, we investigate transition probabilities between knots. We use the BFACF algorithm to generate ensembles of polygons in Z(3) of fixed knot type. We introduce a novel strand-passage algorithm which generates a Markov chain in knot space. The entries of the corresponding transition probability matrix determine state-transitions in knot space and can track the evolution of different knots after repeated strand-passage events. We outline future applications of this work to DNA unknotting.