An Analysis of Spatial Clustering and Implications for Wildlife Management: A Burrowing Owl Example

Analysis tools that combine large spatial and temporal scales are necessary for efficient management of wildlife species, such as the burrowing owl (Athene cunicularia). We assessed the ability of Ripley’s K-function analysis integrated into a geographic information system (GIS) to determine changes in burrowing owl nest clustering over two years at NASA Ames Research Center. Specifically, we used these tools to detect changes in spatial and temporal nest clustering before, during, and after conducting management by mowing to maintain low vegetation height at nest burrows. We found that the scale and timing of owl nest clustering matched the scale and timing of our conservation management actions over a short time frame. While this study could not determine a causal link between mowing and nest clustering, we did find that Ripley’s K and GIS were effective in detecting owl nest clustering and show promise for future conservation uses.     

Conservation or Preservation? A Qualitative Study of the Conceptual Foundations of Natural Resource Management

Few disputes in the annals of US environmentalism enjoy the pedigree of the conservation-preservation debate. Yet, although many scholars have written extensively on the meaning and history of conservation and preservation in American environmental thought and practice, the resonance of these concepts outside the academic literature has not been sufficiently examined. Given the significance of the ideals of conservation and preservation in the justification of environmental policy and management, however, we believe that a more detailed analysis of the real-world use and understanding of these ideas is needed. In this paper, we describe the results of a qualitative, semantic study of the concepts of conservation and preservation undertaken in the context of the Chattahoochee National Forest (CNF), located in northern Georgia (USA). Thirty in-depth interviews were conducted with scientists and north Georgia residents either interested or involved in the future management of the forest. Respondents were asked to define conservation and preservation in their own words and to indicate which approach they felt was more appropriate for the management of the CNF. Qualitative content analysis was used to elicit a set of recurring themes for each foundational concept. Taken together, these themes help to flesh out the meaning of conservation and preservation for citizens and scientists today, and illustrate the evolving nature of two of the more significant and venerable ideas animating US environmental policy and management.     

Predicting Opportunities for Greening and Patterns of Vegetation on Private Urban Lands

This paper examines predictors of vegetative cover on private lands in Baltimore, Maryland. Using high-resolution spatial data, we generated two measures: “possible stewardship,” which is the proportion of private land that does not have built structures on it and hence has the possibility of supporting vegetation, and “realized stewardship,” which is the proportion of possible stewardship land upon which vegetation is growing. These measures were calculated at the parcel level and averaged by US Census block group. Realized stewardship was further defined by proportion of tree canopy and grass. Expenditures on yard supplies and services, available by block group, were used to help understand where vegetation condition appears to be the result of current activity, past legacies, or abandonment. PRIZM™ market segmentation data were tested as categorical predictors of possible and realized stewardship and yard expenditures. PRIZM™ segmentations are hierarchically clustered into 5, 15, and 62 categories, which correspond to population density, social stratification (income and education), and lifestyle clusters, respectively. We found that PRIZM 15 best predicted variation in possible stewardship and PRIZM 62 best predicted variation in realized stewardship. These results were further analyzed by regressing each dependent variable against a set of continuous variables reflective of each of the three PRIZM groupings. Housing age, vacancy, and population density were found to be critical determinants of both stewardship metrics. A number of lifestyle factors, such as average family size, marriage rates, and percentage of single-family detached homes, were strongly related to realized stewardship. The percentage of African Americans by block group was positively related to realized stewardship but negatively related to yard expenditures.     

A framework for assessing the impact of land use policy on community exposure to air toxics

Our research focuses on the linkage between land use planning policy and the spatial pattern of exposure to air toxics emissions. Our objective is to develop a modeling framework for assessment of the community health risk implications of land use policy. The modeling framework is not intended to be a regulatory tool for small-scale land use decisions, but a long-range planning tool to assess the community health risk implications of alternative land use scenarios at a regional or subregional scale. This paper describes the development and application of an air toxic source model for generating aggregate emission factors for industrial and commercial zoning districts as a function of permitted uses. To address the uncertainty of estimating air toxics emission rates for planned general land use or zoning districts, the source model uses an emissions probability mass function that weights each incremental permitted land use activity by the likelihood of occurrence. We thus reduce the uncertainty involved in planning for development with no prior knowledge of the specific industries that may locate within the land use district. These air toxics emission factors can then be used to estimate pollutant atmospheric mass flux from land use zoning districts, which can then be input to air dispersion and human health risk assessment models to simulate the spatial pattern of air toxics exposure risk. The model database was constructed using the California Air Toxics Inventory, 1997 US Economic Census, and land assessment records from several California counties. The database contains information on more than 200 air toxics at the 2-digit Standard Industrial Classification (SIC) level. We present a case study to illustrate application of the model. LUAIRTOX, the interactive spreadsheet model that applies our methodology to the California data, is available at http://www2.bren.ucsb.edu/~mwillis/LUAIRTOX.htm.     

Evaluating farm performance using agri-environmental indicators: recent experiences for nitrogen management in The Netherlands

Intensive agriculture, characterized by high inputs, has serious implications on the environment. Monitoring and evaluation of projects aiming at designing, testing and applying more sustainable practices require instruments to asses agronomic as well as environmental performance. Guidelines for Good Agricultural Practice (GAP) or Good Farming Practice (GFP) define sustainable practices but give limited insight into their environmental performance. Agri-environmental indicators (AEIs) provide information on environmental as well as agronomic performance, which allows them to serve as analytical instruments in research and provide thresholds for legislation purposes. Effective AEIs are quantifiable and scientifically sound, relevant, acceptable to target groups, easy to interpret and cost-effective. This paper discusses application of four AEIs for nitrogen (N) management in three Dutch research projects: 'De Marke', 'Cows and Opportunities' and 'Farming with a future'. 'De Marke' applied Nitrogen Surplus and Groundwater Nitrate Concentration in the design and testing of environmentally sound dairy systems. 'Cows and Opportunities', testing and disseminating dairy systems designed at 'De Marke', mainly applied Nitrogen Surplus, while 'Farming with a future' used Nitrogen Surplus, Groundwater Nitrate Concentration and Residual Mineral Soil Nitrogen to support arable farmers in complying with Dutch legislation (MINAS). Nitrogen Surplus is quantifiable, appealing and easy to interpret, but lacks scientific soundness or a good relationship with groundwater quality. Nitrogen Use Efficiency is sensitive to changes in management, while Residual Mineral Soil Nitrogen is appealing and cheap, but has difficulties in scaling. Groundwater Nitrate Concentration lacks clear rules for sampling, is labor consuming, expensive and mainly used in combination with other indicators. AEIs enhanced improvements in N management by facilitating (i) definition of project goals, (ii) design of desired systems, (iii) evaluation of applied systems and (iv) improving effective communication. AEI applications in other countries show a similar pattern as found in The Netherlands. Limitations to AEI application relate to inconsistencies between different indicators, heterogeneity of soil characteristics and linkages of N, carbon and water management. AEIs should be applied in an integrated evaluation, at a scale that reflects the farm's spatial variability. Simple AEIs like Nitrogen Surplus should be supported by other indicators and/or model calculations. The paper concludes that AEIs proved their value in design, implementation and testing of farming systems, but they should be used with care, always keeping in mind that indicators are simplifications of complex and variable processes.     

The integrated project AquaTerra of the EU sixth framework lays foundations for better understanding of river-sediment-soil-groundwater systems

The integrated project "AquaTerra" with the full title "integrated modeling of the river-sediment-soil-groundwater system; advanced tools for the management of catchment areas and river basins in the context of global change" is among the first environmental projects within the sixth Framework Program of the European Union. Commencing in June 2004, it brought together a multidisciplinary team of 45 partner organizations from 12 EU countries, Romania, Switzerland, Serbia and Montenegro. AquaTerra is an ambitious project with the primary objective of laying the foundations for a better understanding of the behavior of environmental pollutants and their fluxes in the soil-sediment-water system with respect to climate and land use changes. The project performs research as well as modeling on river-sediment-soil-groundwater systems through quantification of deposition, sorption and turnover rates and the development of numerical models to reveal fluxes and trends in soil and sediment functioning. Scales ranging from the laboratory to river basins are addressed with the potential to provide improved river basin management, enhanced soil and groundwater monitoring as well as the early identification and forecasting of impacts on water quantity and quality. Study areas are the catchments of the Ebro, Meuse, Elbe and Danube Rivers and the Brévilles Spring. Here we outline the general structure of the project and the activities conducted within eleven existing sub-projects of AquaTerra.     

CO2 storage capacity estimation: Methodology and gaps

Implementation of CO₂ capture and geological storage (CCGS) technology at the scale needed to achieve a significant and meaningful reduction in CO₂ emissions requires knowledge of the available CO₂ storage capacity. CO₂ storage capacity assessments may be conducted at various scales—in decreasing order of size and increasing order of resolution: country, basin, regional, local and site-specific. Estimation of the CO₂ storage capacity in depleted oil and gas reservoirs is straightforward and is based on recoverable reserves, reservoir properties and in situ CO₂ characteristics. In the case of CO₂-EOR, the CO₂ storage capacity can be roughly evaluated on the basis of worldwide field experience or more accurately through numerical simulations. Determination of the theoretical CO₂ storage capacity in coal beds is based on coal thickness and CO₂ adsorption isotherms, and recovery and completion factors. Evaluation of the CO₂ storage capacity in deep saline aquifers is very complex because four trapping mechanisms that act at different rates are involved and, at times, all mechanisms may be operating simultaneously. The level of detail and resolution required in the data make reliable and accurate estimation of CO₂ storage capacity in deep saline aquifers practical only at the local and site-specific scales. This paper follows a previous one on issues and development of standards for CO₂ storage capacity estimation, and provides a clear set of definitions and methodologies for the assessment of CO₂ storage capacity in geological media. Notwithstanding the defined methodologies suggested for estimating CO₂ storage capacity, major challenges lie ahead because of lack of data, particularly for coal beds and deep saline aquifers, lack of knowledge about the coefficients that reduce storage capacity from theoretical to effective and to practical, and lack of knowledge about the interplay between various trapping mechanisms at work in deep saline aquifers.     

Spatial variation of soil phosphorus within a drainage ditch network

Agricultural drainage ditches serve as P transport pathways from fields to surface waters. Little is known about the spatial variation of P at the soil-water interface within ditch networks. We quantified the spatial variation of surficial (0-5 cm) soil P within vegetated agricultural ditches on a farm in Princess Anne, MD with an approximately 30-yr history of poultry litter application. Ditch soils from 10 ditches were sampled at 10-m intervals and analyzed for acid ammonium oxalate-extractable P, Fe, Al (P(ox), Fe(ox), Al(ox)), and pH. These variables were spatially autocorrelated. Oxalate-P (min = 135 mg kg(-1), max = 6919 mg kg(-1), mean = 700 mg kg(-1)) exhibited a high standard deviation across the study area (overall 580 mg kg(-1)) and within individual ditches (maximum 1383 mg kg(-1)). Several ditches contained distinct areas of high P(ox), which were associated with either point- or nonpoint-P sources. Phosphorus was correlated with Al(ox) or Fe(ox) within specific ditches. Across all ditches, Al(ox) (r = 0.80; p < 0.001) was better correlated with P(ox) than was Fe(ox) (r = 0.44; p < 0.001). The high level of spatial variation of soil P observed in this ditch network suggests that spatially distributed sampling may be necessary to target best management practices and to model P transport and fate in ditch networks.     

Lability of drinking water treatment residuals (WTR) immobilized phosphorus: aging and pH effects

Time constraints associated with conducting long-term (>20 yr) field experiments to test the stability of drinking water treatment residuals (WTR) sorbed phosphorus (P) inhibit improved understanding of the fate of sorbed P in soils when important soil properties (e.g., pH) change. We used artificially aged samples to evaluate aging and pH effects on lability of WTR-immobilized P. Artificial aging was achieved through incubation at elevated temperatures (46 or 70 degrees C) for 4.5 yr, and through repeated wetting and drying for 2 yr. Using a modified isotopic ((32)P) dilution technique, coupled with a stepwise acidification procedure, we monitored changes in labile P concentrations over time. This technique enabled evaluation of the effect of pH on the lability of WTR-immobilized P. Within the pH range of 4 to 7, WTR amendment, coupled with artificial aging, ultimately reduced labile P concentrations by > or = 75% relative to the control (no-WTR) samples. Soil samples with different physicochemical properties from two 7.5-yr-old, one-time WTR-amended field sites were utilized to validate the trends observed with the artificially aged samples. Despite the differences in physicochemical properties among the three (two field-aged and one artificially aged) soil samples, similar trends of aging and pH effects on lability of WTR-immobilized P were observed. Labile P concentrations of the WTR-amended field-aged samples of the two sites decreased 6 mo after WTR amendment and the reduction persisted for 7.5 yr, ultimately resulting in > or = 70% reduction, compared to the control plots. We conclude that WTR application is capable of reducing labile P concentration in P-impacted soils, doing so for a long time, and that within the commonly encountered range of pH values for agricultural soils WTR-immobilized P should be stable.     

Assessment of vegetation stress using reflectance or fluorescence measurements

Current methods for large-scale vegetation monitoring rely on multispectral remote sensing, which has serious limitation for the detection of vegetation stress. To contribute to the establishment of a generalized spectral approach for vegetation stress detection, this study compares the ability of high-spectral-resolution reflectance (R) and fluorescence (F) foliar measurements to detect vegetation changes associated with common environmental factors affecting plant growth and productivity. To obtain a spectral dataset from a broad range of species and stress conditions, plant material from three experiments was examined, including (i) corn, nitrogen (N) deficiency/excess; (ii) soybean, elevated carbon dioxide, and ozone levels; and (iii) red maple, augmented ultraviolet irradiation. Fluorescence and R spectra (400-800 nm) were measured on the same foliar samples in conjunction with photosynthetic pigments, carbon, and N content. For separation of a wide range of treatment levels, hyperspectral (5-10 nm) R indices were superior compared with F or broadband R indices, with the derivative parameters providing optimal results. For the detection of changes in vegetation physiology, hyperspectral indices can provide a significant improvement over broadband indices. The relationship of treatment levels to R was linear, whereas that to F was curvilinear. Using reflectance measurements, it was not possible to identify the unstressed vegetation condition, which was accomplished in all three experiments using F indices. Large-scale monitoring of vegetation condition and the detection of vegetation stress could be improved by using hyperspectral R and F information, a possible strategy for future remote sensing missions.