Effects of experimental nitrogen additions on plant diversity in an old-growth tropical forest

Response of plant biodiversity to increased availability of nitrogen (N) has been investigated in temperate and boreal forests, which are typically N-limited, but little is known in tropical forests. We examined the effects of artificial N additions on plant diversity (species richness, density and cover) of the understory layer in an N saturated old-growth tropical forest in southern China to test the following hypothesis: N additions decrease plant diversity in N saturated tropical forests primarily from N-mediated changes in soil properties. Experimental additions of N were administered at the following levels from July 2003 to July 2008: no addition (Control); 50 kg N ha−1 yr−1 (Low-N); 100 kg N ha−1 yr−1 (Medium-N), and 150 kg N ha−1 yr−1 (High-N). Results showed that no understory species exhibited positive growth response to any level of N addition during the study period. Although low-to-medium levels of N addition (≤100 kg N ha−1 yr−1) generally did not alter plant diversity through time, high levels of N addition significantly reduced species diversity. This decrease was most closely related to declines within tree seedling and fern functional groups, as well as to significant increases in soil acidity and Al mobility, and decreases in Ca availability and fine-root biomass. This mechanism for loss of biodiversity provides sharp contrast to competition-based mechanisms suggested in studies of understory communities in other forests. Our results suggest that high-N additions can decrease plant diversity in tropical forests, but that this response may vary with rate of N addition.

NONLINEAR TUBE-FITTING FOR THE ANALYSIS OF ANATOMICAL AND FUNCTIONAL STRUCTURES

We are concerned with the estimation of the exterior surface of tube-shaped anatomical structures. This interest is motivated by two distinct scientific goals, one dealing with the distribution of HIV microbicide in the colon and the other with measuring degradation in white-matter tracts in the brain. Our problem is posed as the estimation of the support of a distribution in three dimensions from a sample from that distribution, possibly measured with error. We propose a novel tube-fitting algorithm to construct such estimators. Further, we conduct a simulation study to aid in the choice of a key parameter of the algorithm, and we test our algorithm with validation study tailored to the motivating data sets. Finally, we apply the tube-fitting algorithm to a colon image produced by single photon emission computed tomography (SPECT)and to a white-matter tract image produced using diffusion tensor `imaging (DTI).