Natural Resource Use with Vague-Transferability in Property Right

The purpose of this paper is to study the impacts of the vagueness about the transfer of the harvest right on the use of a natural resource. We develop one-period non-cooperative game frameworks to examine whether the choice of the resource owner to be hazy about the transmission of the harvest contract is optimal. In the perfect information situation, we show that it is optimal for the resource owner to forbid the transfer of the harvest right instead of being hazy about it when the transfer fees are lesser than the collected net punishment fines of the monitoring costs even though the resource would be inefficiently used. In particular, we find in this case that the government’s announcement to forbid the transfer of the right should be public. We further show that there are subgame Nash equilibria in the perfect information context and a unique Nash equilibrium in the imperfect information setting. Specifically, we show that, when the transfer fees are greater or equal to the (net) punishment fines, there is a Nash equilibrium both in perfect and imperfect information situations, precisely when the owner chooses to allow the transfer of harvest title and the resource harvester transfers it.     

A Mathematical Model for the Effects of Fertilization on Nitrogen Concentrations in Unsaturated Soil on Blueberry Farms in Southern New Jersey

Nitrogen is commonly known as a food source for crops. However, the nitrogen compounds used in crop fertilizers, most commonly nitrate (NO₃) and ammonium (NH₄), are not widely understood. Blueberry plants do not take up these compounds as efficiently as organic nitrogen so varying amounts of leaching into the soil and groundwater will occur. A biogeochemical model consisting of ordinary and partial differential equations is implemented to computationally predict the concentrations of nitrate and ammonium in unsaturated soil of blueberry plants, specifically in the southern region of New Jersey. The model takes into account the type of soil of the region, the nitrate uptake of the plant, the water content in the roots region, the pressure heads in the soil pores, and the application rates of fertilizers containing nitrate, ammonium, and organic nitrogen. Computational simulations demonstrate that the model accounts for natural processes and, in addition, show that commonly used fertilizer application rates cause unnecessarily high concentrations of both nitrate and ammonium in the unsaturated soil level. Further, simulations show that decreasing nitrate fertilizer applications by 85.7% in annual and 91.8% in bi-annual schedules provides an optimal system for safe reapplication.     

GPU Accelerated Lattice Boltzmann Simulation of a Cyanide-Release Accident in the Danjiangkou Reservoir

A graphics processing unit (GPU) accelerated two-dimensional contamination transport model is developed using the lattice Boltzmann method (LBM). The intrinsic parallel features of LBM make it particularly suitable for implementation on GPUs. After validation with two benchmarks, the model was applied to a cyanide-release accident in the Danjiangkou Reservoir, using a numerical combination of hydrodynamics and solute transport. The results show good agreement with an Environmental Fluid Dynamics Code (EFDC) model. A single GPU workstation speedup reaches 1.58 times that of a central processing unit (CPU) calculation alone. This speedup provides the opportunity for applying the model as a pollution accident information and decision support system for the Middle Route of the South to North Water Diversion Project in China.     

Robust Regression with Data-Dependent Regularization Parameters and Autoregressive Temporal Correlations

We introduce robust procedures for analyzing water quality data collected over time. One challenging task in analyzing such data is how to achieve robustness in presence of outliers while maintaining high estimation efficiency so that we can draw valid conclusions and provide useful advices in water management. The robust approach requires specification of a loss function such as the Huber, Tukey’s bisquare and the exponential loss function, and an associated tuning parameter determining the extent of robustness needed. High robustness is at the cost of efficiency loss in parameter loss. To this end, we propose a data-driven method which leads to more efficient parameter estimation. This data-dependent approach allows us to choose a regularization (tuning) parameter that depends on the proportion of “outliers” in the data so that estimation efficiency is maximized. We illustrate the proposed methods using a study on ammonium nitrogen concentrations from two sites in the Huaihe River in China, where the interest is in quantifying the trend in the most recent years while accounting for possible temporal correlations and “irregular” observations in earlier years.     

The Impact of Succession Stage on Share and Traits of Clonal Plants in Abandoned <Emphasis Type="Italic">Molinion caeruleae</Emphasis> Meadows

The impact of succession stage on the share of clonal plants in the plant cover, seed rain and seedling pool has been studied in the years 2014 and 2015. The investigations were carried out in abandoned Molinion caeruleae meadows dominated by small-statured species (Patch I), tall growing large-tussock grasses (Patch II) and shrub-willows (Patch III). Although the clonal taxa dominated in the plant cover, seed rain and seedling pool, their share in subsequent study sites was quite different. The spectra of life-history traits relevant to clonality in the plant cover and seed rain were similar and did not vary significantly among subsequent locations, while they mostly differed as observed in the seedling pool. The various spectra observed in seedling pool in subsequent study sites might be due to fact that the seed germination and recruitment of offspring are strongly influenced by habitat conditions which varied remarkably in the successive Patches.     

Investigating the oil curse in OECD and Non-OECD oil-exporting economies using green measures of income

Empirical studies investigating the natural resource curse theory mostly employ cross-country and panel regression techniques subject to endogeneity bias. Also, most of these studies employ GDP in its aggregate or per-capita terms as the outcome variable in their analyses. However, the use of GDP measures of income for resource curse investigations may not portray the true incomes of resource-intensive economies. Standard national accounts treat natural resource rents as a positive contribution to income without adjusting for the value of depleted natural resource stock. This treatment often leads to a positive bias in the national income computations of resource-rich economies. Unlike previous studies, we test the robustness of the curse in the predominantly used measures of national income, GDP, by investigating the theme in genuine income measures of economic output as well. Also, the paper deviates from most empirical studies in the literature by using the Arellano–Bond difference GMM method in investigating the oil curse in OECD and Non-OECD oil-exporting economies. Additionally, we employ two alternative measures of resource intensity in our explorations; the share of oil rents in GDP and per-capita oil reserves. Our results provide evidence of the curse in Non-OECD countries employing aggregate and per-capita measures of genuine income.     

Sustainability indicators in the swine industry of the Brazilian State of Santa Catarina

In recent decades, there has been a growing concern about measuring and evaluating the results of intensive production practices, such as the mode of integration practiced on a large scale by agro-industries. The present study discusses the application and the results of a Sustainability Indicators System in the context of the swine industry in the Brazilian State of Santa Catarina. These indicators, focused on the level of sustainability maturity, can be used as a way to diagnose and compare the efficiency of the industry from a broader perspective. The research findings indicate that most of the pig farms that have been studied can be classified as “in search of sustainability or sustainable.” Nevertheless, there are differences among the dimensions and between the most ranked farms and the others which must be considered for a better design and application of public policies and company strategies toward an effective and balanced social, economic and environmental sustainability.     

The personal,social and environmental sustainability of Jainism in light of Maharishi Vedic Science

The Jain tradition of ecological awareness and sustainability has been well documented over the last 25 years, although its roots lie deep in Indian history, specifically in texts such as the Tattvārtha Sūtra and ācārā?ga Sūtra. This traditional body of knowledge includes a long-standing theory and practice of personal, social and environmental sustainability, addressing such views as the interconnectedness of humans and the laws of nature, the interdependence of everything in the universe, the responsibility of humans to conserve and preserve natural resources, the avoidance of wanton and unnecessary waste generation, and a general aversion to mistreating or abusing the environment. These views encapsulate the lifestyles of some ten million people, including both mendicants and laity. Similarly, Maharishi Vedic Science, the systematic exploration and practical application of the Veda and Vedic Literature as taught by Maharishi Mahesh Yogi, makes a compelling case for establishing the unity of human life with nature and for promoting actions which guarantee both the protection of nature and protection by it. The purpose of this paper is to examine the relationship between the principles of sustainability in Jainism and the corresponding viewpoint of Maharishi Vedic Science, including supporting scientific evidence of its application, and to posit their contribution to a sustainable world future.     

Analyzing temporal–spatial characteristics of drought events in the northern part of Cyprus

Drought in the northern part of Cyprus has become a recurrent phenomenon. In the last few decades, Cyprus has experienced significantly severe drought events occurring periodically, and this trend is now continuing. With rainfall distribution varying considerably across the region and frequent drought conditions, the water resources, agriculture, economy and the environment have been adversely affected. This study aims to investigate spatial–temporal characteristic of drought using Standardized Precipitation Index (SPI) at multiple timescales (3, 6 and 12 months). Monthly time series of 36 years (1977–2013) rainfall data from nine weather stations are used to derive SPI values. Based on different drought categories, this study focuses on propagation of drought from one timescale to another and estimating critical rainfall values during moderate, severe and extreme drought conditions. The analysis revealed that there is a strong correlation among different timescales in detecting drought events. On average, 79 and 78% of 3-month timescale drought propagated into 6- and 12-month drought events, respectively, while 90% of 6-month timescale drought events propagated into 12-month drought events. The derived critical rainfall value for extreme droughts over a 12-month timescale was less than 255 mm/year in the town of Alsancak, while for Guzelyurt, a major citrus growing city, this figure was less than 135 mm/year. The results are validated through drought events detected at various regions of the Mediterranean basin and local flood occurrences during the wet periods and decline in water tables at drought seasons.