Spatial variability of urban forest topsoil properties: towards representative and robust sampling design.

Background: Soil spatial variability is a major concern when deciding how to collect a representative topsoil sample for laboratory analysis. Sampling design to capture site-specific variability is documented in the agricultural literature, but poorly understood for urban forest soils where soils may be characterized by strong horizontal and vertical variability and large temporal anthropogenic disturbances. Methods: This paper evaluates the spatial variability of selected topsoil properties under urban trees to define a statistically robust sampling design that optimizes the number of samples to reliably characterize basal soil respiration (BSR), a property associated with soil health. To provide a reference on variability, two additional soil properties were measured, unrelated to BSR: electrical conductivity (EC) and bulk density (BD). Thirteen sampling sites comprising both park and street trees ( Acer rubrum) were selected in Cambridge, MA, USA. Results: Results indicate street tree topsoil had approximately twice as much variation, requiring more intensive sampling, as did park tree topsoil, even though street trees had smaller soil sampling zones, constricted by tree pits. The variability of BSR was nearly identical to that of EC, and BD results varied least. A large number of samples would be required for acceptable levels of statistical reliability (90% CI - 10% ER) of 44.4, 41.7, and 6.4 for BSR, EC, and BD, respectively, whereas by accepting a lower level of certainty (80% CI - 20% ER) the number of required soil samples was calculated as 6.8, 6.4, and 0.4 for BSR, EC, and BD, respectively. Conclusions: The use of EC testing as a baseline measure to determine spatial variation in the topsoil is proposed, to alleviate the financial implications of more expensive BSR testing. Factors of topsoil disturbance and soil access restrictions at sites with severe root-sidewalk conflicts and the overall generalizability of the results are also discussed.

The CINMa index: assessing the potential impact of GM crop management across a heterogeneous landscape.

While significant progress has been made on the modification of crops for the benefit of producers, the same cannot be said in regards to eliciting the potential impact that these crops may have on the wider landscape and the diversity of life therein. Management impacts can create difficulties when making policy, regulation and licensing decisions in those countries where agriculture has a significant social and ecological position in the landscape. To begin to gauge the potential impacts of the management of a selection of GM crops on an agricultural landscape, four key biodiversity stressors (Chemicals, Introgression, Nutrients and Management: CINMa) were identified and a grading system developed using published data. Upon application to five selected GM crops in a case study area, CINMa identifies areas in the wider landscape where biodiversity is likely to be negatively or positively impacted, as well as agricultural zones which may benefit from the land use change associated with the management of GM crops and their associated post market environmental monitoring.