Effects of tree size and spatial distribution on growth of ponderosa pine forests under alternative management scenarios

Forest ecosystems may be actively managed toward heterogeneous stand structures to provide both economic (e.g., wood production and carbon credits) and environmental benefits (e.g., invasive pest resistance). In order to facilitate wider adoption of possibly more sustainable forest stand structures, defining growth expectations among alternative management scenarios is crucial. To estimate the effect of tree size and spatial distributions on growth for forest structures commonly considered in uneven-aged forest stand management, large (0.2 ha+) plots were established in 14 uneven-aged ponderosa pine stands in eastern Montana. All study trees were stem-mapped and measured for diameter and 10-year sapwood and basal area increment. A generalized growth model was developed to predict both total and merchantable 10-year basal area increment for nine hypothetical stand structures [three diameter distributions (reverse-J, irregular, flat) × three spatial distributions (clumpy, partial clumpy, uniform)]. Results indicate that the size and spatial distributions of individual trees have a considerable effect on overall stand growth. The greatest total stand growth was in stands with reverse “J” shaped tree size distributions, while the greatest merchantable stand growth was in stands with “flat” diameter distributions and uniform spatial distributions. Through better comprehension of generalized uneven-aged stand growth dynamics, forest managers may better assess the effects of alternative stand structures on stand growth while providing forest stand structures that may be more resilient in a changing climate.     

Urbanization and its impact on groundwater: a remote sensing and GIS-based assessment approach

The perils of unplanned urbanization and increasing pressure of human activities on hydro-geomorphologic system often result in modification of the existing recharge mechanism, which leads to many environmental consequences. In the present research, an attempt has been made to investigate the applicability of remote sensing and geographical information system (GIS) in dealing with spatial and temporal variability of dynamic phenomena, like urbanization and its impact on groundwater. This paper covers primarily, quantitative and qualitative impacts of urban growth on the behavior of aquifer in Ajmer city (India). Urban growth of the Ajmer city in last 17 years has been estimated from the satellite images. Database related to urbanization and groundwater has been created in GIS. Groundwater recharge has been computed using a water balance approach known as Water Level Fluctuation Methodology. Recharge estimation methodology has been implemented in GIS to introduce the spatial variability of hydro-geological characteristics. Further, temporal and spatial variations in groundwater quality and quantity have been correlated with urban growth using overlay analysis in GIS. The study reveals a general decline in water table and quality with urbanization. Further, remote sensing and GIS technologies have been found useful in assessment of spatial and temporal phenomena of urbanization and its impact on groundwater system.     

Teachers' conceptions of nature and environment in 16 countries

By using an original framework involving complementary statistical approaches, we investigated the environmental attitudes of 6379 pre-service and in-service teachers in 16 countries of Europe and its neighbourhood. To test hypotheses about the nature of environmental attitudes, we examined the variation across groups of individuals (between-class analysis), investigated the independent effects of several candidate explanatory factors (orthogonal analysis), and finally inspected potential relationships between conceptions on a variety of topics (co-inertia analysis).     

Accretion of heavy metals in the catfish <Emphasis Type="Italic">Bagrus bayad</Emphasis> from Taylor Creek,southern Nigeria

Heavy metals in the aquatic environment have, to date, come essentially from naturally occurring geochemical resources. However, this has been enhanced by anthropogenic activities such as crude oil exploration and exploitation activities, resulting in pollution in the Taylor Creek aquatic ecosystem. The catfish species Bagrus bayad and other environmental segments were collected from five selected sites along Taylor Creek, southern Nigeria, and total metal concentration determined. The concentration levels of the metals in B. bayad were higher than the values reported in the literature for fresh fish and may lead to a higher risk of harmful effects. The bivariate regression models relating metals in B. bayad and metals in the surface waters were significant (R ² ≥ 0.9002). The log (bio-concentration factor; BCF) values of Cr and Zn in B. bayad were the highest, whereas the lowest was found for Ni. The ecological distribution of the log (BCF) values was, for all the heavy metals, moderately stable over the creek. All log-transformed bio-magnification factors (BMF) in the creek were positive, which indicates that the metal concentration was greater in B. bayad than in suspended particulate matter (SPM). The absolute log (BMF) values of heavy metals can, therefore, be ranked in order of decreasing magnitude: Cr (3.26) > Zn (2.99) > Cd (2.93) > Fe (2.76) > Pb (2.66) > Mn (2.36) > Ni (2.24). This sequence indicates that toxic metals such as Cd, Cr and Pb are undergoing significant bio-reduction from SPM to B. bayad. The degree of correlation between the metals was different in B. bayad, which suggests that the sources of the metals polluting Taylor Creek were diverse.     

An imprecise fuzzy risk approach for water quality management of a river system

Uncertainty plays an important role in water quality management problems. The major sources of uncertainty in a water quality management problem are the random nature of hydrologic variables and imprecision (fuzziness) associated with goals of the dischargers and pollution control agencies (PCA). Many Waste Load Allocation (WLA) problems are solved by considering these two sources of uncertainty. Apart from randomness and fuzziness, missing data in the time series of a hydrologic variable may result in additional uncertainty due to partial ignorance. These uncertainties render the input parameters as imprecise parameters in water quality decision making. In this paper an Imprecise Fuzzy Waste Load Allocation Model (IFWLAM) is developed for water quality management of a river system subject to uncertainty arising from partial ignorance. In a WLA problem, both randomness and imprecision can be addressed simultaneously by fuzzy risk of low water quality. A methodology is developed for the computation of imprecise fuzzy risk of low water quality, when the parameters are characterized by uncertainty due to partial ignorance. A Monte-Carlo simulation is performed to evaluate the imprecise fuzzy risk of low water quality by considering the input variables as imprecise. Fuzzy multiobjective optimization is used to formulate the multiobjective model. The model developed is based on a fuzzy multiobjective optimization problem with max–min as the operator. This usually does not result in a unique solution but gives multiple solutions. Two optimization models are developed to capture all the decision alternatives or multiple solutions. The objective of the two optimization models is to obtain a range of fractional removal levels for the dischargers, such that the resultant fuzzy risk will be within acceptable limits. Specification of a range for fractional removal levels enhances flexibility in decision making. The methodology is demonstrated with a case study of the Tunga–Bhadra river system in India.     

Assessing water use and quality through youth participatory research in a rural Andean watershed

Water availability, use and quality in a rural watershed of the Colombian Andes were investigated through participatory research involving local youth. Research included the quantification of disaggregated water use at the household level; comparison of water use with availability; monitoring water quality of streams, community water intakes and household faucets; and the determination of land use – water quality interactions. Youth were involved in all aspects of the research from design to implementation, dissemination of results and remediation options. Quantification of domestic and on-farm water use, and water availability indicated that water availability was sufficient during the study period, but that only an 8% decrease in dry season supply would result in shortages. Elevated conductivity levels in the headwaters were related to “natural” bank erosion, while downstream high conductivity and coliform levels were associated with discharges from livestock stalls and poorly maintained septic tanks in the stream buffer zone. Through the involvement of youth as co-investigators, the knowledge generated by the research was appropriated at the local level. Community workshops led by local youth promoted water conservation and water quality protection practices based on research, and resulted in broader community participation in water management. The approach involving youth in research stimulated improved management of both land and water resources, and could be applied in small rural watersheds in developed or developing countries.     

Predicted concentrations of biocides from antifouling paints in Visakhapatnam Harbour

The concentrations of biocides leached from antifouling coatings are monitored in most of the developed countries. However, in India and many other developing countries, there is very little data available on the concentrations of biocides in ports and harbours. The first step was to obtain the order of magnitude levels of concentrations of biocides in the marine environment of the Visakhapatnam Harbour, and the MAM-PEC (Marine Antifoulant Model to Predict Environmental Concentrations) model was used to predict these values. The Visakhapatnam Port lies on the eastern coast of India, roughly halfway between Chennai and Kolkata, and is the largest port in India. This port is a natural harbour; the long and narrow outlet to the open sea makes it a 'poorly flushed' harbour. Predicted concentrations of tributyltin (TBT), copper, dichlofluanid, seanine, irgarol, diuron, tolylfluanid, and zinc pyrithione were computed. The results of the computations indicate that the levels of these biocides are comparable to those in many western countries. This gives credence to the fact that persistence of TBT and some other biocides is a global problem that cannot be ignored.     

A Multilevel Model of the Impact of Farm‐Level Best Management Practices on Phosphorus Runoff1

Abstract: Multilevel or hierarchical models have been applied for a number of years in the social sciences but only relatively recently in the environmental sciences. These models can be developed in either a frequentist or Bayesian context and have similarities to other methods such as empirical Bayes analysis and random coefficients regression. In essence, multilevel models take advantage of the hierarchical structure that exists in many multivariate datasets; for example, water quality measurements may be taken from individual lakes, lakes are located in various climatic zones, lakes may be natural or man‐made, and so on. The groups, or levels, may effectively yield different responses or behaviors (e.g., nutrient load response in lakes) that often make retaining group membership more effective when developing a predictive model than when working with either all of the data together or working separately with the individuals. Here, we develop a multilevel model of the impact of farm level best management practices (BMPs) on phosphorus runoff. The result of this research is a model with parameters which vary with key practice categories and thus may be used to evaluate the effectiveness of these practices on phosphorus runoff. For example, it was found that the effect of fertilizer application rate on farm‐scale phosphorus loss is a function of the application method, the hydrologic soil group, and the land use (crop type). Further, results indicate that the most effective method for controlling fertilizer loss is through soil injection. In summary, the resultant multilevel model can be used to estimate phosphorus loss from farms and hence serve as a useful tool for BMP selection.     

Modeling Postfire Response and Recovery using the Hydrologic Engineering Center Hydrologic Modeling System (HEC‐HMS)1

Abstract: This paper investigates application of the Army Corps of Engineers’ Hydrologic Engineering Center Hydrologic Modeling System (HEC‐HMS) to a burned watershed in San Bernardino County, California. We evaluate the HEC‐HMS’ ability to simulate discharge in prefire and postfire conditions in a semi arid watershed and the necessary parameterizations for modeling hydrologic response during the immediate, and subsequent recovery, period after a wildfire. The model is applied to City Creek watershed, which was 90% burned during the Old Fire of October 2003. An optimal spatial resolution for the HEC‐HMS model was chosen based on an initial sensitivity analysis of subbasin configurations and related model performance. Five prefire storms were calibrated for the selected model resolution, defining a set of parameters that reasonably simulate prefire conditions. Six postfire storms, two from each of the following rainy (winter) seasons were then selected to simulate postfire response and evaluate relative changes in parameter values and model behavior. There were clear trends in the postfire parameters [initial abstractions (I_a), curve number (CN), and lag time] that reveal significant (and expected) changes in watershed behavior. CN returns to prefire (baseline) values by the end of Year 2, while I_a approaches baseline by the end of the third rainy season. However, lag time remains significantly lower than prefire values throughout the three‐year study period. Our results indicate that recovery of soil conditions and related runoff response is not entirely evidenced by the end of the study period (three rainy seasons postfire). Understanding the evolution of the land surface and related hydrologic properties during the highly dynamic postfire period, and accounting for these changes in model parameterizations, will allow for more accurate and reliable discharge simulations in both the immediate, and subsequent, rainy seasons following fire.