Neighborhood form and CO2 emission: evidence from 23 neighborhoods in Jinan, China

To understand the household C02 emission level in China, as well as how much the neighborhoods＇ socio-economic or design factors could influence the CO2 emission, 23 neighborhoods in Jinan were investigated in 2009 and 2010. These neighborhoods fall into four different types： superblock, enclave, grid and traditional. The household CO2 emission includes sources of both in- home energy use and passenger transportation. The average CO2 emission per household is 7.66 t.a^-1, including 6.87 t in-home operational emission and 792 kg transportation emission. The household CO2 emission by neighborhood categories is 10.97, 5.65, 6.49, 5.40 t-household-1. a-1 for superblock, enclave, grid and tradi- tional respectively. Superblock has the highest average emission and also the highest percent （more than 25%） of transportation emission among four different types of neighborhoods. The residential CO2 emission of superb- lock neighborhoods in Jinan has already reached the level in developed countries nearly ten years ago. It is predictable that more superblock neighborhoods would be built in China with the fast urbanization. How to avoid the rapid household CO2 emission growth in the future would be a systematic issue. The study also found that in addition to income and apartment area, household density, land use mix and accessibility to public transportation are three primary factors which have significant impacts on CO2 emission. High density, mixed land use and convenient accessibility to public transportation tend to reduce household CO2 emission.     

Estimating animal densities and home range in regions with irregular boundaries and holes: A lattice-based alternative to the kernel density estimator

Density estimates based on point processes are often restrained to regions with irregular boundaries or holes. We propose a density estimator, the lattice-based density estimator, which produces reasonable density estimates under these circumstances. The estimation process starts with overlaying the region with nodes, linking these together in a lattice and then computing the density of random walks of length k on the lattice. We use an approximation to the unbiased crossvalidation criterion to find the optimal walk length k. The technique is illustrated using walleye (Sander vitreus) radiotelemetry relocations in Lake Monroe, Indiana. We also use simulation to compare the technique to the traditional kernel density estimate in the situation where there are no significant boundary effects.     

Population dynamics models based on cumulative density dependent feedback: A link to the logistic growth curve and a test for symmetry using aphid data

Density dependent feedback, based on cumulative population size, has been advocated to explain and mathematically characterize “boom and bust” population dynamics. Such feedback results in a bell-shaped population trajectory of the population density. Here, we note that this trajectory is mathematically described by the logistic probability density function. Consequently, the cumulative population follows a time trajectory that has the same shape as the cumulative logistic function. Thus, the Pearl–Verhulst logistic equation, widely used as a phenomenological model for density dependent population growth, can be interpreted as a model for cumulative rather than instantaneous population. We extend the cumulative density dependent differential equation model to allow skew in the bell-shaped population trajectory and present a simple statistical test for skewness. Model properties are exemplified by fitting population trajectories of the soybean aphid, Aphis glycines. The linkage between the mechanistic underpinnings of the logistic probability density function and cumulative distribution function models could open up new avenues for analyzing population data.