US army land condition-trend analysis (LCTA) program

The US Army Land Condition-Trend Analysis (LCTA) program is a standardized method of data collection, analysis, and reporting designed to meet multiple goals and objectives. The method utilizes vascular plant inventories, permanent field plot data, and wildlife inventories. Vascular plant inventories are used for environmental documentation, training of personnel, species identification during LCTA implementation, and as a survey for state and federal endangered or threatened species. The permanent field plot data documents the vegetational, edaphic, topographic, and disturbance characteristics of the installation. Inventory plots are allocated in a stratified random fashion across the installation utilizing a geographic information system that integrates satellite imagery and soil survey information. Ground cover, canopy cover, woody plant density, slope length, slope gradient, soil information, and disturbance data are collected at each plot. Plot data are used to: (1) describe plant communities, (2) characterize wildlife and threatened and endangered species habitat, (3) document amount and kind of military and nonmilitary disturbance, (4) determine the impact of military training on vegetation and soil resources, (5) estimate soil erosion potential, (6) classify land as to the kind and amount of use it can support, (7) determine allowable use estimates for tracked vehicle training, (8) document concealment resources, (9) identify lands that require restoration and evaluate the effectiveness of restorative techniques, and (10) evaluate potential acquisition property. Wildlife inventories survey small and midsize mammals, birds, bats, amphibians, and reptiles. Data from these surveys can be used for environmental documentation, to identify state and federal endangered and threatened species, and to evaluate the impact of military activities on wildlife populations. Short- and long-term monitoring of permanent field plots is used to evaluate and adjust land management decisions.     

DEVELOPMENT AND TESTING OF A SNOWMELT-RUNOFF FORECASTING TECHNIQUE1

ABSTRACT: The snowmelt-runoff model (SRM) was used to produce accurate simulations of streamfiow during the snowmelt period (April-September) for ten years on the Rio Grande Basin (3419 km²) near Del Norte, Colorado, U.S.A. In order to use SRM in the forecast situation, it was necessary to develop a family of snow cover depletion curves for each elevation zone based on accumulated snow water equivalent on April 1. Selection of an appropriate curve for a particular year from snow course measurements allows input of the daily snow cover extent to SRM for forecast purposes. Data from three years (1980, 1981, and 1985) were used as a quasi-forecast test of the procedure. In these years forecasted snow cover extent data were input to SRM, but observed temperature and precipitation data were used. The resulting six-month hydrographs were very similar to the hydrographs in the ten simulation years previously tested based on comparisons of performance evaluation criteria. Based on this result, the Soil Conservation Service (SCS) requested SRM forecasts for 1987 on the Rio Grande. Using the same procedure but with SCS estimated temperature and precipi-tation data, SRM produced a forecast hydrograph that had a r²= 0.82 and difference in seasonal volume of 4.4 percent. To approximate actual operational conditions, SRM computed daily flows were updated every seven days with measured flows. The resulting forecast hydrograph had a R²= 0.90 and a difference in volume of 3.5 percent. The method developed needs to be refined and tested on additional years and basins, but the approach appears to be applicable to operational runoff forecasting using remote sensing data.     

Social-ecological resilience and social conflict: institutions and strategic adaptation in Swedish water management

Dealing with uncertainty and complexity in social-ecological systems is profoundly dependent on the ability of natural resource users to learn and adapt from ecological surprises and crises. This paper analyzes why and how learning processes are affected by strategic behavior among natural resource users and how social conflict is affected by social and ecological uncertainty. The claim is that social conflict among natural resource users seriously inhibits the possibilities of learning and adaptation in social-ecological systems. This is done combining insights from political science, experimental economics, and social-psychology and an analytical case study elaborating social conflict and institutional change in Swedish water management institutions. This paper also discusses the crucial role the institutional context plays in defining the outcome of learning processes in Swedish water management institutions and hence highlights previously poorly elaborated political aspects of learning processes and institutional change in social-ecological systems.     

Biodiversity Conservation in Traditional Coffee Systems of Mexico

In Mexico, coffee is cultivated on the coastal slopes of the central and southern parts of the country in areas where two or more types of vegetation make contact. Based on management level and vegetational and structural complexity, it is possible to distinguish five main coffee production systems in Mexico: two kinds of traditional shaded agroforests (with native trees), one commercially oriented polyspecific shaded system, and two modern systems (shaded and unshaded monocultures). Traditional shaded coffee is cultivated principally by small-scale, community-based growers, most of whom belong to some indigenous culture group. Through an exhaustive review of the literature, we found that traditional shaded coffee plantations are important repositories of biological richness for groups such as trees and epiphytes, mammals, birds, reptiles, amphibians, and arthropods. We evaluated the conservation role of these traditional shaded systems by estimating the percentage of the whole coffee area under traditional management, by reviewing the ecological and geographical distribution of coffee areas in Mexico, and by connecting the geographical distribution of these coffee areas with recognized centers of species richness and endemism. The assesment revealed that in Mexico, coffee fields are located in a biogeographically and ecologically strategic elevational belt that is an area of overlap between the tropical and temperate elements and of contact among the four main types of Mexican forests. We also found that between 60% and 70% of these coffee areas are under traditional management and that at least 14 of 155 priority regions selected by experts as having high numbers of species and endemics overlap with or are near traditional coffee-growing areas.     

HYDROLOGICAL UNDERSTANDING AND SOCIETAL ACTION1

ABSTRACT: Hydrology is both an applied practical science and a pure geophysical science. The goal of hydrology, as a geophysical science, is to achieve theories capable of explaining with satisfactory accuracy the phenomena of interest. Through the rapidly accelerating power and versatility of digital computing technology, theory development and application are immensely facilitated via increasingly sophisticated predictive modeling schemes, which are now the principal operating tools both for applied management hydrology and for basic geophysical hydrology. While this approach treats phenomena as classes or generalizations, social and behavioral scientists have long argued that human beings base their actions on percepts, i.e., on the concrete specifics of their experience. Thus, the commonly held ideal of basing policy, decisions, and public actions on the best possible science encounters a conflict in belief systems. A possible resolution of this dilemma lies in the use of observational components, which in concept-centered science serve as data to test or calibrate models. These components also serve as a great repository of natural experience that is closely attuned to the perceptual reality that propels societal action. Landscapes and sediments provide indices of real processes, whose occurrence can be expected by continuity to extend to present and future activity. More attention to research on such indices is warranted as a means of triggering perception-based action by responsible decision-makers. Grounded in reality, and tempered by their intrinsic fallibility, the scientifically powerful conceptual schemes (models) will then serve as guides to further action. The full societal benefit of hydrological science requires a balanced approach in which subdisciplines focused on environmental indices are afforded equal attention to those focused on conceptual idealization.     

Microwave treatment and struvite recovery potential of dairy manure

Microwave digestion of liquid dairy manure was tested for the release of nutrients, such as orthophosphates, ammonia-nitrogen, magnesium, calcium and potassium, both with and without the aid of an oxidizing agent (hydrogen peroxide). The orthophosphate to total phosphorus ratio of the manure increased from 21% to greater than 80% with 5 minutes of microwave treatment. More than 36% of total chemical oxygen demand (t-COD) of the manure was reduced when microwave digestion was assisted with peroxide addition. In addition, the volatile fatty acids (VFAs) distribution shifted to simpler chain acids (acetic acid in particular) with an increase in operating temperature. In the second part of the study, digested manure with increased soluble phosphate was tested for the recovery of struvite (magnesium ammonium phosphate) at different pH. It was found that up to 90% of orthophosphate can be removed from the solution. Overall, it was concluded that the oxidizing agent-assisted microwave digestion process can be used upstream of anaerobic digestion, following which the anaerobically digested manure can be used for struvite recovery. Thus, this microwave digestion process presents the potential for enhanced efficiencies in both manure digestion and struvite recovery.     

Cointegration and causality: considering Iberian economic activity sectors to test the environmental Kuznets curve hypothesis

Few studies have attempted to study the environmental Kuznets curve (EKC) hypothesis at the individual sector level using more than one sector at once. This paper investigates the existence of the EKC hypothesis in the Iberian countries (Portugal and Spain) using thirteen economic activity sectors for each, analyzing each individual sector’s cointegration and causality relationships considering carbon dioxide (CO2) emissions, sector gross value added and energy consumption. The findings of this paper using the autoregressive distributed lag (ARDL) approach only validate cointegration in six Portuguese sectors and in five of the Spanish sectors. Results confirm both short- and long-run bi-directional and unidirectional causality between economic growth, energy consumption and CO2 emissions, using the error correction model (ECM) and Toda and Yamamoto’s causality approaches. Moreover, results for Portuguese and Spanish sectors indicate an inverted U-shaped relationship only for one sector each. In some sectors there was evidence of a U-shaped relationship and in others the EKC hypothesis could be verified but no statistical significance was obtained. The study has significant contributions for sector policy, including implications to curtail energy pollutants by implementing environmental friendly regulations to sustain economic development at the sector level in the Iberian market. It also allows inferences to be made about the existence of different behaviors in comparative terms for the same economic activity sectors of the individual countries.     

Disarming the population bomb

This paper argues for a renewed international focus on managed population reduction as a key enabler of sustainable development. The paper presents development data that demonstrate why population reduction should be elevated to share top priority with poverty alleviation, as the two over-arching goals of international development strategy. The critical analysis put forth in this paper argues that the current ‘unsustainable’ approach to sustainable development stems from (1) ‘empty world’ economic growth theory applied to a ‘full world’, which is (2) supported and driven by socioeconomic incentives to expand population, (3) justified through flawed interpretation of demographic transition theory, (4) bolstered by the exaggerated efficacy of environmental economic theory applied in a resource-constrained world, (5) insulated from challenge by limitations of scientific knowledge and (6) perpetuated by herd behavior. This paper concludes that failure to reduce global population will inhibit attainment of poverty alleviation and worsen environmental degradation.