The Fallacy of Nuclear Primacy

"The United States is easily deterred by any nuclear armed state, even by the most primitive and diminutive of nuclear arsenals." Bruce G. Blair is the President of the World Security Institute. Chen Yali is the editor in chief of Washington Observer

The Oil Weapon: Myth of China's Vulnerability

The geopolitical canvass on which China plots its strategy for energy security displays a ubiquitous presence of one country: the United States. Chinese energy security planners must reckon with America's ravenous consumption of imported oil, its strategic alliances with other heavy importers of oil in Asia, its overseas military operations in the heart of the world's leading oil producing region, its naval dominion over the world's oil transportation routes, and the global domination of U.S. oil companies or multinational oil companies heavily capitalized by American investment. This is the context in which China pursues its energy security, sometimes blandly described as 'conservation and diversification of supply', which masks the nation's real struggle to satisfy its rapidly growing energy needs without exposing its energy lifelines to external forces that may, intentionally or not, betray China's interests

THE VALUE OF ENSO INFORMATION TO AGRICULTURE: CONSIDERATION OF EVENT STRENGTH AND TRADE

The agricultural value of El Nino-Southern Oscillation (ENSO) phase knowledge is measured in a value-of-information framework using economic models. We examine the value of considering the full distribution of ENSO phase strength effects as opposed to average ENSO phase strength effects, as well as the implications of considering ENSO impacts on the rest of the world (ROW). A stochastic U.S. agricultural sector model linked with a global trade model is used to assess the value of ENSO phase information. When the full distribution of ENSO phase strength is considered, the value of phase information increases twofold with respect to the average ENSO effects.Agribusiness,

Hurricanes and Possible Intensity Increases: Effects on and Reactions from U.S. Agriculture

Hurricanes have caused substantial damage in parts of the U.S. Damages are increasing, perhaps as part of a natural cycle or perhaps in part related to global warming. This paper examines the economic damages that hurricanes cause to U.S. agriculture, estimates the increased damage from an increase in hurricane frequency/intensity, and examines the way that sectoral reactions reduce damages. The simulation results show that hurricanes and associated adjustments cause widespread damage and redistribute agricultural welfare. We find that crop mix shifts of vulnerable crops from stricken to nonstricken regions significantly mitigate hurricane damages.crop mix, hurricane intensity, stochastic agricultural sector model, Agribusiness, Crop Production/Industries, Production Economics, Q24, Q54, R14,

Advancing Agricultural Production With Machine Learning Analytics: Yield Determinants for California's Almond Orchards.

Agricultural productivity is subject to various stressors, including abiotic and biotic threats, many of which are exacerbated by a changing climate, thereby affecting long-term sustainability. The productivity of tree crops such as almond orchards, is particularly complex. To understand and mitigate these threats requires a collection of multi-layer large data sets, and advanced analytics is also critical to integrate these highly heterogeneous datasets to generate insights about the key constraints on the yields at tree and field scales. Here we used a machine learning approach to investigate the determinants of almond yield variation in California's almond orchards, based on a unique 10-year dataset of field measurements of light interception and almond yield along with meteorological data. We found that overall the maximum almond yield was highly dependent on light interception, e.g., with each one percent increase in light interception resulting in an increase of 57.9 lbs/acre in the potential yield. Light interception was highest for mature sites with higher long term mean spring incoming solar radiation (SRAD), and lowest for younger orchards when March maximum temperature was lower than 19°C. However, at any given level of light interception, actual yield often falls significantly below full yield potential, driven mostly by tree age, temperature profiles in June and winter, summer mean daily maximum vapor pressure deficit (VPDmax), and SRAD. Utilizing a full random forest model, 82% (±1%) of yield variation could be explained when using a sixfold cross validation, with a RMSE of 480 ± 9 lbs/acre. When excluding light interception from the predictors, overall orchard characteristics (such as age, location, and tree density) and inclusive meteorological variables could still explain 78% of yield variation. The model analysis also showed that warmer winter conditions often limited mature orchards from reaching maximum yield potential and summer VPDmax beyond 40 hPa significantly limited the yield. Our findings through the machine learning approach improved our understanding of the complex interaction between climate, canopy light interception, and almond nut production, and demonstrated a relatively robust predictability of almond yield. This will ultimately benefit data-driven climate adaptation and orchard nutrient management approaches

Millennial slip rate of the Longitudinal Valley fault from river terraces: Implications for convergence across the active suture of eastern Taiwan

The Longitudinal Valley fault is a key element in the active tectonics of Taiwan. It is the principal structure accommodating convergence across one of the two active sutures of the Taiwan orogeny. To understand more precisely its role in the suturing process, we analyzed fluvial terraces along the Hsiukuluan River, which cuts across the Coastal Range in eastern Taiwan in the fault's hanging wall block. This allowed us to determine both its subsurface geometry and its long-term slip rate. The uplift pattern of the terraces is consistent with a fault-bend fold model. Our analysis yields a listric geometry, with dips decreasing downdip from about 50° to about 30° in the shallowest 2.5 km. The Holocene rate of dip slip of the fault is about 22.7 mm/yr. This rate is less than the 40 mm/yr rate of shortening across the Longitudinal Valley derived from GPS measurements. The discrepancy may reflect an actual difference in millennial and decadal rates of convergence. An alternative explanation is that the discrepancy is accommodated by a combination of slip on the Central Range fault and subsidence of the Longitudinal Valley floor. The shallow, listric geometry of the Longitudinal Valley fault at the Hsiukuluan River valley differs markedly from the deep listric geometry illuminated by earthquake hypocenters near Chihshang, 45 km to the south. We hypothesize that this fundamental along-strike difference in geometry of the fault is a manifestation of the northward maturation of the suturing of the Luzon volcanic arc to the Central Range continental sliver

Endangered by Sprawl: How Runaway Development Threatens America's Wildlife

Estimates the growth of land consumption in metropolitan areas over the next 25 years, investigates locally implemented strategies to protect natural lands from overdevelopment, and offers "smart growth" as an option for reducing suburban sprawl