Decomposition Rates and Nitrogen Release of Turf Grass Clippings

Decomposition rates and N release patterns of turfgrass clippings from lawns are not well understood. Litter bags containing clippings were inserted into the thatch layer of a coolseason turf. The experiment was arranged as a 2 × 4 factorial in a randomized complete block design with three replicates. Treatments included four rates of N fertilizer (0, 98, 196, and 392 kg N ha-1 yr-1) and two clipping treatments (returned vs. removed). Litter bags were removed periodically over the growing season and samples were analyzed for biomass, N and C concentrations, and C:N ratio on an ash-free basis. Percentage N loss from the clippings after 16 weeks ranged from 88% to 93% at the 0 and 392 kg N ha-1 rates, respectively, and from 86% to 94% when clippings were removed (CRM) or returned (CRT), respectively. Percentage C loss from the clippings ranged from 94% to 95% at the 0 and 392 kg N ha-1 rates, respectively, and from 92% to 96% with CRM and CRT, respectively. Cumulative N release was similar across N fertilization rates, (ranging from 131 g N kg-1 to 135 g N kg-1 tissue) but was higher for CRT (151 g N kg-1 tissue) than for CRM (128 g N kg-1 tissue). Grass clippings decomposed rapidly and released N quickly when returned to the turf thatch layer. This indicates the potential for reduced N fertilization when clippings are returned. Such rapid decomposition also suggests that the contribution of grass clippings to thatch development is negligible.

Extracting more out of relocation data: building movement models as mixtures of random walks

We present a framework for fitting multiple random walks to animal movement paths consisting of ordered sets of step lengths and turning angles. Each step and turn is assigned to one of a number of random walks, each characteristic of a different behavioral state. Behavioral state assignments may be inferred purely from movement data or may include the habitat type in which the animals are located. Switching between different behavioral states may be modeled explicitly using a state transition matrix estimated directly from data, or switching probabilities may take into account the proximity of animals to landscape features. Model fitting is undertaken within a Bayesian framework using the WinBUGS software. These methods allow for identification of different movement states using several properties of observed paths and lead naturally to the formulation of movement models. Analysis of relocation data from elk released in east-central Ontario, Canada, suggests a biphasic movement behavior: elk are either in an "encamped" state in which step lengths are small and turning angles are high, or in an "exploratory" state, in which daily step lengths are several kilometers and turning angles are small. Animals encamp in open habitat (agricultural fields and opened forest), but the exploratory state is not associated with any particular habitat type.