A review of WTO and environmental issues

Multiple negotiating rounds of the General Agreement on Tariffs and Trade (GATT) and World Trade Organization (WTO) since 1947 have conferred economic benefits through liberalized international trade. A growing body of evidence also points to linkages between liberalized trade and damage to the global environment, ecology, and natural resource base. Ironically, the increased economic well-being conferred by trade liberalization ultimately provides the basis for improved environmental protection. It is the interim environmental damage due to trade liberalization that is controversial and needing amelioration. The proposition here is to promote further trade liberalization, but only as long as environmental ethics and sustainability issues are satisfactorily addressed. Trade liberalization should not be permitted at the expense of adequate environmental protection and sustainability. Future WTO rounds need to address both development benefits and environmental ethics issues in a net social welfare maximization setting.     

Conserving Slow-Growing, Long-Lived Tree Species: Input from the Demography of a Rare Understory Conifer, Taxus floridana

Abstract:  Although land preservation and promotion of successful regeneration are important conservation actions, their ability to increase population growth rates of slow-growing, long-lived trees is limited. We investigated the demography of Taxus floridana Nutt., a rare understory conifer, in three populations in different ravine forests spanning its entire geographic range along the Apalachicola River Bluffs in northern Florida (U.S.A.). We examined spatial and temporal patterns in demographic parameters and projected population growth rates by using four years of data on the recruitment and survival of seedlings and established stems, and on diameter growth from cross-sections of dead stems. All populations experienced a roughly 10-fold increase in seedling recruitment in 1996 compared with other years. The fates of seedlings and stems between 8 and 16 mm differed among populations. The fates of stems in two other size classes (the 2- to 4-mm class and the 4- to 8-mm class) differed among both populations and years. Individual stems in all populations exhibited similarly slow growth rates. Stochastic matrix models projected declines in all populations. Stochastic matrix analysis revealed the high elasticity of a measure of stochastic population growth rate to perturbations in the stasis of large reproductive stems for all populations. Additional analyses also indicated that occasional episodes of high recruitment do not greatly affect population growth rates. Conservation efforts directed at long-lived, slow-growing rare plants like Taxus floridana should both protect established reproductive individuals and further enhance survival of individuals in other life-history stages, such as juveniles, that often do not appear to contribute greatly to population growth rates.     

Empirical Bayes calculations of concordance between endpoints in environmental toxicity experiments

Hierarchical models are considered for estimating the probability of agreement between two outcomes or endpoints from an environmental toxicity experiment. Emphasis is placed on generalized regression models, under which the prior mean is related to a linear combination of explanatory variables via a monotone function. This function defines the scale over which the systematic effects are modelled as additive. Specific illustration is provided for the logistic link function. The hierarchical model employs a conjugate beta prior that leads to parametric empirical Bayes estimators of the individual agreement parameters. An example from environmental carcinogenesis illustrates the methods, with motivation derived from estimation of the concordance between two species carcinogenicity outcomes. Based on a large database of carcinogenicity studies, the inter-species concordance is seen to be reasonably informative, i.e. in the range 67–84%. Stratification into pertinent potency-related sub-groups via the logistic model is seen to improve concordance estimation: for environmental stimuli at the extremes of the potency spectrum, concordance can reach well above 90%.     

AGA法及其在非线性数学模型参数估计中的应用

介绍了在基因算法基础上改进的加速基因算法（ＡＧＡ），并通过环境非线性数学模型参数估计实例对该法与传统参数估计方法进行了比较。初步结果表明，ＡＧＡ法直观、简便、拟合精度高、通用性强，易为广大环境工程技术人员理解和使用。     

Island biogeographical theory: Can it be used to predict lotic recovery rates?

Classic island biogeographic theory predicts that equilibrium will be reached when immigration and extinction rates are equal. These rates are modified by number of species in source area, number of intermediate islands, distance to recipient island, and size of intermediate islands. This general model has been variously modified and proposed to be a stochastic process with minimal competitive interaction or heavily deterministic. Predictive models of recovery (regardless of the end point chosen) have been based on the appropriateness of the MacArthur-Wilson models. Because disturbance frequency, severity, and intensity vary in their effect on community dynamics, we propose that disturbance levels should first be defined before evaluating the applicability of island biogeographical theory. Thus, we suggest a classification system of four disturbance levels based on recovery patterns by primary and secondary succession and faunal organization by primary (invasion of vacant areas) and secondary (remnant of previous community remains) processes. Level 1A disturbances completely destroy communities with no upstream or downstream sources of colonizers, while some component of near surface interstitial or hyporheic flora and fauna survive level 1B disturbances. Recovery has been reported to take from five years to longer than 25 years, when most invading colonists do not have an aerial form. Level 2 disturbances destroy the communities but leave upstream and downstream colonization sources (level 2A) and, sometimes, a hyporheic pool of colonizers (level 2B). Recovery studies have indicated primary succession and faunal structuring patterns (2A) with recovery times of 90–400 days or secondary succession and faunal structuring patterns (2B) with recovery times of 40–250 days. Level 3 disturbances result in reduction in species abundance and diversity along a stream reach; level 4 disturbances result in reduction of abundance and diversity in discrete patches. Both disturbance types lead to secondary succession and secondary faunal organization. Recovery rates can be quite rapid, varying from less than 10 days to 100 or more days. We suggest that island biogeographical models seem appropriate to recovery by secondary processes after level 3 and 4 disturbances, where competition may be an important organizing factor, while models of numerical abundance and resource tracking are probably of better use where community development is by primary succession (levels 1 and 2). Development of predictive recovery models requires research that addresses a number of fundamental questions. These include the role of hydrologic patterns on colonization dynamics, the role of nonaerial colonizers in recovery from level 1 disturbances, and assessment of the impact of changes in the order of invasion by colonizers of varying energetic efficiencies. Finally, we must be able to assemble these data and determine whether information that guides community organization at one level of disturbance can provide insights into colonization dynamics at other levels.     

A SEMI-DISTRIBUTED ADAPTIVE MODEL FOR REAL-TIME FLOOD FORECASTING1

ABSTRACT: A semi-distributed deterministic model for real-time flood forecasting in large basins is proposed. Variability of rainfall and losses in space is preserved and the effective rainfall-direct runoff model segment based on the Clark procedure is incorporated. The distribution of losses in space is assumed proportional to rainfall intensity and their evolution in time is represented by the φ-index; furthermore, an initial period without production of effective rainfall is considered. The first estimation of losses and the associated forecasts of flow are performed at the time corresponding to the first rise observed in the hydrograph. Then the forecasts of flow are corrected at each subsequent time step through the updating of the φ-index. The model was tested by using rainfall-runoff events observed on two Italian basins and the predictions of flow for lead times up to six hours agree reasonably well with the observations in each event. For example, for the coefficient of persistence, which compares the model forecasts with those generated by the no-model assumption, appreciable positive values were computed. In particular, for the larger basin with an area of 4,147 km², the mean values were 0.4, 0.4 and 0.5 for forecast lead times of two hours, four hours and six hours, respectively. Good performance of the model is also shown by a comparison of its flow predictions with those derived from a unit hydrograph based model     

WATER FOR ENERGY: AN APPROACH TO COMPREHENSIVE IMPACT ASSESSMENT1

ABSTRACT: The effects of energy development on the water resources of the Colorado River and Great Basin regions is expected to be substantial. Complex physical, economic and institutional interactions may be expected. Most research on these impacts appears single purpose, fragmented, uncoordinated, and often inaccessible to potential users - particularly those with responsibility for energy/water policy and program decisions. A comprehensive, integrative framework for assessing alternative water allocation decisions is outlined, taking a heuristic decision making model for evaluating impacts on maximization of gross (or net) regional product, and regional social welfare, and for assessing the region's contribution to national objectives. The suggested model provides a structure for application and integration of data of various kinds to a range of situations arising from possible impacts from energy proposals. The focus is on water and energy relationships but the model may provide a framework for comprehensive analysis of a variety of environmental actions and resulting system perturbations and effects.     

PROBLEMS IN FORECASTING WATER REQUIREMENTS1

ABSTRACT. Methodological problems associated with forecasting water requirements by use of regression analysis are examined. Problems occurring when long-range forecasts are based on linear and nonlinear extrapolation of time series models include possible changes in socioeconomic conditions, water allocation system structure, and limits to growth. Problems arising in forecasting based on multiple regression models are likely to involve serially dependent errors, multicollinear explanatory variables, and difficulties inherent to the presence of explanatory variables that must themselves be predicted.