Mathematical modeling of plant community composition for urban greenery plans

Urban green space is critical for humans and other organisms living in cities. Researchers have noticed that urban green space planning has been focusing more on ornamental and public management purposes but less on its ecological purpose, which has a negative impact on eco-sustainability. We hypothesized that an urban greenery management plan with high eco-sustainability can be achieved by calculating the composition of a plant community through mathematical modeling. To test our hypothesis, we created a nonlinear programming function that generated a plant community composition aiming for high plant fitness, high biodiversity, and low managing cost. Green fields in a Beijing city park, comprising different combinations of plant species were used to optimize our model. Although the outputs of the optimized model do not match completely with the composition of testing fields, they illustrate possible patterns for plant community development. By applying this model, urban green space can be finely designed to become both ecologically and economically sustainable.