Shoot biomass of turfgrass cultivars grown on composted waste

Various cultivars of four cool-season grass types (tall fescue, fine fescue, perennial ryegrass, and Kentucky bluegrass) were seeded in 0.34-liter plastic pots containing either composted sewage sludge [Com-Til² (CT), Soil Magic² (SM)] or composted yard mulch (YM). Plants were grown in the greenhouse for four weeks prior to measuring shoot biomass. White most tall fescue cultivars showed more shoot growth on YM, perennial ryegrass cultivars generally grew better on SM. Cultivars of fine fescue and bluegrass grew about the same on YM or SM, and slightly less on CT. With very few exceptions, shoot biomass of individual cultivars was greater on either YM or SM than it was on CT. Within individual grass types, Pennlawn (fine fescue), Pennant (perennial ryegrass), and Victa (Kentucky bluegrass) averaged consistently better growth on all three composted media. For tall fescue, Aquara, Rebel II, and Monarch performed best on YM, SM, and CT, respectively. Bioaccumulation of heavy metals did not occur in selective samples of shoot tissues collected from the grass types used. This research was supported by National Science Foundation grant #8902053 to Buckeye Bluegrass Farms. The greenhouse studies described in this paper were performed in conjunction with field tests conducted at Buckeye Bluegrass Farms. Requests for information on field trials should be directed to H. F. Decker, Box 176, Ostrander, Ohio 43061, USA. Use of trade names is for the reader's information only and does not imply endorsement over similar products of like properties.     

An empirical study of spatial-temporal growth patterns of a voluntary residential green infrastructure program

Voluntary residential green infrastructure (GI) stormwater management retrofit programs can help cities comply with environmental regulations while also improving quality of life. Previous research has identified influential factors in residents’ willingness to adopt GI, but few have simultaneously studied the spatial and temporal dynamics of GI. I use a six-year record of participation in a voluntary residential GI program in Washington DC to explore how neighborhood characteristics and social influence affect GI adoption over time. Statistical regression and Monte Carlo permutation resampling techniques are used to explain the spatial-temporal patterns of growth of the program. I demonstrate empirical evidence that participation location is increasingly determined by the locations of previous participants. These findings suggest that past participants will increasingly influence spatial clustering of GI in the city.     

Maryland's Green Infrastructure—Using Landscape Assessment Tools to Identify a Regional Conservation Strategy

Maryland is growing at a very rapid pace. Compounding the problems associated with rapid growth is the scattered pattern of development that consumes an excessive amount of land and fragments the landscape. As land use changes, wildlife habitat and migration corridors are lost and normal ecosystem functions are disturbed or destroyed. While land use planners and developers are attempting to minimize such impacts, they do not always know where key natural lands and corridors are situated. The Green Infrastructure Assessment (GIA) provides this information and can be used to identify a greenway network that will protect the most critical lands in the state before they are gone foreover. Using GIS and principles of landscape ecology, the Maryland Department of Natural Resources is identifying an interconnected network of "hubs" and "corridors" that are now the focus of state and local agency deliberations and revisions. Elements of the network are being prioritized for conservation and restoration activities based on ecological parameters (e.g., sensitive species, important wetlands or riparian zones, etc.) and threat parameters (e.g., protection status, development pressure, etc.). The goal of GIA is to help identify an ecologically sound open space network, and ultimately, to incorporate the agreed upon network into state and local land conservation planning.     

WATERSHED WEIGHTING OF EXPORT COEFFICIENTS TO MAP CRITICAL PHOSPHOROUS LOADING AREAS1

ABSTRACT: The Export Coefficient model (ECM) is capable of generating reasonable estimates of annual phosphorous loading simply from a watershed's land cover data and export coefficient values (ECVs). In its current form, the ECM assumes that ECVs are homogeneous within each land cover type, yet basic nutrient runoff and hydrological theory suggests that runoff rates have spatial patterns controlled by loading and filtering along the flow paths from the upslope contributing area and downslope dispersal area. Using a geographic information system (GIS) raster, or pixel, modeling format, these contributing area and dispersal area (CADA) controls were derived from the perspective of each individual watershed pixel to weight the otherwise homogeneous ECVs for phosphorous. Although the CADA‐ECM predicts export coefficient spatial variation for a single land use type, the lumped basin load is unaffected by weighting. After CADA weighting, a map of the new ECVs addressed the three fundamental criteria for targeting critical pollutant loading areas: (1) the presence of the pollutant, (2) the likelihood for runoff to carry the pollutant offsite, and (3) the likelihood that buffers will trap nutrients prior to their runoff into the receiving water body. These spatially distributed maps of the most important pollutant management areas were used within New York's West Branch Delaware River watershed to demonstrate how the CADA‐ECM could be applied in targeting phosphorous critical loading areas.     

Distribution of polycyclic aromatic hydrocarbons in Datuo karst Tiankeng of South China

Levels of polycyclic aromatic hydrocarbons (PAHs) were measured in surface soils of Datuo karst Tiankeng (large sinkholes) in South China with the use of a gas chromatography-mass spectroscopy (GC-MS) system. This paper provides data on the levels and distribution of PAHs from the top to the bottom of the Datuo karst Tiankeng. The results showed that the sum of the 16 EPA priority PAHs from the sampled locations from top to bottom had a relative increment in PAHs concentration. summation operatorPAHs ranged from 16.93 ng/g to 68.07 ng/g with a mean concentration of 42.15 ng/g. The correlated results showed the bottom of the large sinkhole, which accounts for the higher concentrations, probably acts like a trap for the PAHs. Thus, the low evaporation rate at the bottom may play a key role in controlling the high concentration of PAHs at the bottom.     

Modeling the influence of precipitation and nitrogen deposition on forest understory fuel connectivity in Sierra Nevada mixed-conifer forest

Climate change models for California's Sierra Nevada predict greater inter-annual variability in precipitation over the next 50 years. These increases in precipitation variability coupled with increases in nitrogen deposition from fossil fuel consumption are likely to result in increased productivity levels and significant increases in forest understory fuel loads. Higher understory plant biomass contributes to fuel connectivity and may increase future fire size and severity in the Sierra Nevada. The objective of this research was to develop and test a model to determine how changing precipitation and nitrogen deposition levels affect shrub and herb biomass production, and to determine how often prescribed fire would be needed to counter increasing fuel loads. Model outputs indicate that under an increasing precipitation scenario significant increases in shrub and herb biomass occur that can be counteracted by decreasing the fire return interval to 10 years. Under a scenario with greater inter-annual variability in precipitation and increased nitrogen deposition, implementing fire treatments at an interval equivalent to the historical range of 15–30 years maintains understory vegetation fuel loads at levels comparable to the control.     

It takes more than a village: the challenges of co-management in Uganda's fishery and forestry sectors

Decentralisation policies in least developed countries have emerged in response to failed centralised natural resource governance programmes because high-value natural resources are distributed unequally, with central governments often reaping more than local-level users. Current natural resource governance institutions have been created to remedy the problems that central governments formerly posed. Here, we argue that Uganda's forestry and fishery resources are biologically diverse and thus amenable to current decentralised management programmes, provided that there is compromise between market values and local cultural and subsistence values and uses. We observe, however, Uganda's current institutional arrangement favours the former over the latter and determine that successful natural resource decentralisation requires strengthening local-level natural resource institutions with increased fiscal flow, enforcement, monitoring and judicial powers. A strong and reliable partnership between local-level resource users and the central government is necessary for this to occur.     

Combined effects of constant versus variable intensity simulated rainfall and reduced tillage management on cotton preemergence herbicide runoff

Pesticide runoff research relies heavily on rainfall simulation experiments. Most are conducted at a constant intensity, i.e., at a fixed rainfall rate; however, large differences in natural rainfall intensity is common. To assess implications we quantified runoff of two herbicides, fluometuron and pendimethalin, and applied preemergence after planting cotton on Tifton loamy sand. Rainfall at constant and variable intensity patterns representative of late spring thunderstorms in the Atlantic Coastal Plain region of Georgia (USA) were simulated on 6-m2 plots under strip- (ST) and conventional-tillage (CT) management. The variable pattern produced significantly higher runoff rates of both compounds from CT but not ST plots. However, on an event-basis, runoff totals (% applied) were not significantly different, with one exception: fluometuron runoff from CT plots. There was about 25% more fluometuron runoff with the variable versus the constant intensity pattern (P = 0.10). Study results suggest that conduct of simulations using variable intensity storm patterns may provide more representative rainfall simulation-based estimates of pesticide runoff and that the greatest impacts will be observed with CT. The study also found significantly more fluometuron in runoff from ST than CT plots. Further work is needed to determine whether this behavior may be generalized to other active ingredients with similar properties [low K(oc) (organic carbon partition coefficient) approximately 100 mL g(-1); high water solubility approximately 100 mg L(-1)]. If so, it should be considered when making tillage-specific herbicide recommendations to reduce runoff potential.