Estimating tree growth from complex forest monitoring data.

Understanding tree growth as a function of tree size is important for a multitude of ecological and management applications. Determining what limits growth is of central interest, and forest inventory permanent plots are an abundant source of long-term information but are highly complex. Observation error and multiple sources of shared variation (spatial plot effects, temporal repeated measures, and a mosaic of sampling intervals) make these data challenging to use for growth estimation. We account for these complexities and incorporate potential limiting factors (tree size, competition, and resource supply) into a hierarchical state-space model. We estimate the diameter growth of white fir (Abies concolor) in the Sierra Nevada of California from forest inventory data, showing that estimating such a model is feasible in a Bayesian framework using readily available modeling tools. In this forest, white fir growth depends strongly on tree size, total plot basal area, and unexplained variation between individual trees. Plot-level resource supply variables (representing light, water, and nutrient availability) do not have a strong impact on inventory-size trees. This approach can be applied to other networks of permanent forest plots, leading to greater ecological insights on tree growth.

A review of vegetated buffers and a meta-analysis of their mitigation efficacy in reducing nonpoint source pollution.

Vegetated buffers are a well-studied and widely used agricultural management practice for reducing nonpoint-source pollution. A wealth of literature provides experimental data on their mitigation efficacy. This paper aggregated many of these results and performed a meta-analysis to quantify the relationships between pollutant removal efficacy and buffer width, buffer slope, soil type, and vegetation type. Theoretical models for removal efficacy (Y) vs. buffer width (w) were derived and tested against data from the surveyed literature using statistical analyses. A model of the form Y = K x (1-e(-bxw)), (0 < K < or = 100) successfully captured the relationship between buffer width and pollutant removal, where K reflects the maximum removal efficacy of the buffer and b reflects its probability to remove any single particle of pollutant in a unit distance. Buffer width alone explains 37, 60, 44, and 35% of the total variance in removal efficacy for sediment, pesticides, N, and P, respectively. Buffer slope was linearly associated with sediment removal efficacy either positively (when slope < or = 10%) or negatively (when slope > 10%). Buffers composed of trees have higher N and P removal efficacy than buffers composed of grasses or mixtures of grasses and trees. Soil drainage type did not show a significant effect on pollutant removal efficacy. Based on our analysis, a 30-m buffer under favorable slope conditions (approximately 10%) removes more than 85% of all the studied pollutants. These models predicting optimal buffer width/slope can be instrumental in the design, implementation, and modeling of vegetated buffers for treating agricultural runoff.