JSEM: A Framework for Identifying and Evaluating Indicators

There are two issues in indicator development that have not been adequately addressed: (1) how to select an optimal combination of potentially redundant indicators that together best represent an endpoint, given cost constraints; (2) how to identify and evaluate indicators when the endpoint is unmeasured. This paper presents an approach to identifying and evaluating combinations of indicators when the mathematical relationships between the indicators and an endpoint may not be quantified, a limitation common to many ecological assessments. The approach uses the framework of Structural Equation Modeling (SEM), which combines path analysis withmeasurement models, to formalize available informationabout potential indicators and to evaluate their potential adequacy for representing an endpoint. Unlike traditional applications of SEM which require data on all variables, our approach – judgement-based SEM (JSEM) – can utilize expert judgement regarding the strengths and shapes of indicator-endpoint relationships. JSEM is applied in two stages. First, a conceptual model that relates variables in a network of direct and indirect linkages is developed, and is used to identify indicators relevant to an endpoint. Second, an index of indicator strength – i.e., the strength of the relationship between the endpoint and a set of indicators – is calculated from estimates of correlation between the modeled variables, and is used to compare alternative sets of indicators. The second stage is most appropriate for large, long-term assessments. Although JSEM is not a statistical technique, basing JSEM on SEM provides a structure for validating the conceptual model and for refining the index of indicator strength as data become available. Our main objective is to contribute to a rigorous and consistent selection of indicators even when knowledgeabout the ability of indicators to represent an endpoint is limited to expert judgement.     

On the Design of Computer-Based Models for Integrated Environmental Science

The current research agenda in environmental science is dominated by calls to integrate science and policy to better understand and manage links between social (human) and natural (nonhuman) processes. Freshwater resource management is one area where such calls can be heard. Designing computer-based models for integrated environmental science poses special challenges to the research community. At present it is not clear whether such tools, or their outputs, receive much practical policy or planning application. It is argued that this is a result of (1) a lack of appreciation within the research modeling community of the characteristics of different decision-making processes including policy, planning, and (2) participation, (3) a lack of appreciation of the characteristics of different decision-making contexts, (4) the technical difficulties in implementing the necessary support tool functionality, and (5) the socio-technical demands of designing tools to be of practical use. This article presents a critical synthesis of ideas from each of these areas and interprets them in terms of design requirements for computer-based models being developed to provide scientific information support for policy and planning. Illustrative examples are given from the field of freshwater resources management. Although computer-based diagramming and modeling tools can facilitate processes of dialogue, they lack adequate simulation capabilities. Component-based models and modeling frameworks provide such functionality and may be suited to supporting problematic or messy decision contexts. However, significant technical (implementation) and socio-technical (use) challenges need to be addressed before such ambition can be realized.     

Estimating the relevance of engineered carbonaceous nanoparticle facilitated transport of hydrophobic organic contaminants in porous media

Naturally occurring nanoparticles (NP) enhance the transport of hydrophobic organic contaminants (HOCs) in porous media. In addition, the debate on the environmental impact of engineered nanoparticles (ENP) has become increasingly important. HOC bind strongly to carbonaceous ENP. Thus, carbonaceous ENP may also act as carriers for contaminant transport and might be important when compared to existing transport processes. ENP bound transport is strongly linked to the sorption behavior, and other carbonaceous ENP-specific properties. In our analysis the HOC-ENP sorption mechanism, as well as ENP size and ENP residence time, was of major importance. Our results show that depending on ENP size, sorption kinetics and residence time in the system, the ENP bound transport can be estimated either as (1) negligible, (2) enhancing contaminant transport, or (3) should be assessed by reactive transport modeling. One major challenge to this field is the current lack of data for HOC-ENP desorption kinetics.     

Modeling community participation and other factors affecting biodiversity protection projects in China

A statistical model of community participation and investment in biodiversity protection projects was developed in order to understand patterns in the effectiveness of conservation actions in forest-edge communities in Gansu, China. Extensive questionnaires were used to validate the model. The effectiveness of biodiversity programs is strongly and positively influenced by the level of public participation and investment. Higher education improves the use of resources associated with conservation, such as reduced hunting, reduced use of forest products, and the use of fuels other than wood. Nevertheless, it will be important to balance the implementation of conservation programs with the rights of communities to earn or gather a livelihood. The CBI model will benefit from further development, but proves to be a valuable tool for evaluating the design and effectiveness of biodiversity protection programs. Readers should send their comments on this paper to: BhaskarNath@aol.com within 3 months of publication of this issue.     

Developing and applying a soil erosion model in a data-poor context to an island in the rural Philippines

Soil erosion in many parts of the developing world poses a threat to rural livelihoods, to the sustainbility of the agricultural sector, and to the environment. Most erosion prediction models are mechanistic and unsuited to quantify the severity of soil erosion in a data-limited developing world context. The model developed in this paper for Negros Island, in the central Philippines, is based on the Revised Universal Soil Loss Equation, but contains important innovations such as the movement of eroded soil over the landscape, simulating deposition on lower slopes and in waterways. It also includes a term describing farmer strategies to reduce soil erosion, which are typically ignored in erosion prediction models. A two-sample t-test found that model-predicted sediment loading values were not significantly different from field-measured sediment loading values when corrected for watershed size (P = 0.857). The model predicts an annual loss of 2.7 million cubic meters of sediment to waterways such that by 2050 more than 416,000 ha of agricultural land will be rendered unproductive due to erosion. Farmer behavior conserves soil, but on the steepest slopes soil conservation practices are not adequate to prevent erosion. Of two proposed strategies to control soil erosion in the rural Philippines, the model suggests that a complete switch to tree crops would conserve more soil than universal terrace adoption. However, even under these conservation scenarios, erosion threatens the areal extent of upland agriculture on Negros, and hence the sustainability of the island’s food supply.

Building future scenarios and uncovering persisting challenges of participatory forest management in Chilimo Forest, Central Ethiopia

We examined the changes in forest status and people's livelihoods through building future scenarios for Chilimo Forest in Central Ethiopia where participatory forest management (PFM) is being implemented. Participatory methods were employed to collect data, and a dynamic modeling technique was applied to explore trends over time. By integrating the more quantitative model outputs with qualitative insights, information on forests and livelihoods was summarized and returned to users, both to inform them and get feedback. A scenario of open access without PFM provides higher income benefits in the short term but not over the longer term, as compared to a scenario with PFM. Follow up meetings were organized with national decision makers to explore the possibility of new provisions in the national forest proclamation related to joint community-state ownership of forests. Project implementers must constantly work towards improving short term incentives from PFM, as these may be insufficient to garner support for PFM. Other necessary elements for PFM to succeed include: ensuring active participation of the communities in the process; and, clarifying and harmonizing the rules and regulations at different levels.     

A hybrid approach using ISM and fuzzy TOPSIS for the selection of reverse logistics provider

Return of used products is becoming an important logistics activity due to government legislation and increasing awareness among the people to protect the environment and reduce waste. For industries, the management of return flow usually requires a specialized infrastructure with special information systems for tracking and dedicated equipment for the processing of returns. Therefore, industries are turning to third-party reverse logistics providers (3PRLPs). In this study, a multi-criteria group decision-making (MCGDM) model in fuzzy environment is developed to guide the selection process of best 3PRLP. The interactions among the criteria are also analyzed before arriving at a decision for the selection of 3PRLP from among 15 alternatives. The analysis is done through Interpretive Structural Modeling (ISM) and fuzzy technique for order preference by similarity to ideal solution (TOPSIS). Finally the effectiveness of the model is illustrated using a case study on battery manufacturing industry in India.     

Modeling Residential Lawn Fertilization Practices: Integrating High Resolution Remote Sensing with Socioeconomic Data

This article investigates how remotely sensed lawn characteristics, such as parcel lawn area and parcel lawn greenness, combined with household characteristics, can be used to predict household lawn fertilization practices on private residential lands. This study involves two watersheds, Glyndon and Baisman’s Run, in Baltimore County, Maryland, USA. Parcel lawn area and lawn greenness were derived from high-resolution aerial imagery using an object-oriented classification approach. Four indicators of household characteristics, including lot size, square footage of the house, housing value, and housing age were obtained from a property database. Residential lawn care survey data combined with remotely sensed parcel lawn area and greenness data were used to estimate two measures of household lawn fertilization practices, household annual fertilizer nitrogen application amount (N_yr) and household annual fertilizer nitrogen application rate (N_ha_yr). Using multiple regression with multi-model inferential procedures, we found that a combination of parcel lawn area and parcel lawn greenness best predicts N_yr, whereas a combination of parcel lawn greenness and lot size best predicts variation in N_ha_yr. Our analyses show that household fertilization practices can be effectively predicted by remotely sensed lawn indices and household characteristics. This has significant implications for urban watershed managers and modelers.     

The opposing effects of bacterial activity and gas production on anaerobic TCE degradation in soil columns

This laboratory study explores the effect of growth substrate concentration on the anaerobic degradation of trichloroethylene (TCE) in sand packed columns. In all columns the growth substrate rapidly degraded to gas, that formed a separate phase. Biomass accumulated in the 0–4.8 cm section of the columns in proportion to the influent growth substrate concentration and biomass concentrations in the remaining sections of all columns were similar to the column receiving the lowest substrate concentration. Increases in growth substrate concentration up to 3030 mg-COD l⁻¹ promoted TCE degradation, but a further increase to 14 300 mg-COD l⁻¹ reduced the amount of TCE completely dechlorinated but did not affect the production of chlorinated TCE intermediates. The mathematical model developed here satisfactorily described the enhancement in TCE dehalogenation for substrate concentration up to 3030 mg-COD l⁻¹; reproducing TCE dehalogenation for 14 300 mg-COD l⁻¹ required that the moisture content used in simulation be lowered to 0.1. The study shows that volatilization of TCE can be significant and volatilization losses should be taken into account when anaerobic activity in in-situ bioremediation applications is stimulated via addition of growth substrates. An implication of the modeling simulations is that maintaining a lower, but uniform, substrate concentration over the contaminated region may lead to faster contaminant degradation.