Stratigraphy,evolution, and volume of basalts in Mare Serenitatis

Abstract– Fourteen major basaltic units in Mare Serenitatis have been identified and mapped from differences in TiO₂ wt%. The ages of these units have been inferred from their crater densities and reference to isotopically dated Apollo samples. It has been found that FeO and TiO₂ wt% of the units do not show any apparent trend with time. However, the oldest units have much greater variation in FeO and TiO₂ wt% than younger ones. No lateral trend in the age of the basaltic units is apparent within the basin. A vertical profile of Mare Serenitatis has been produced based on the depth of basalt within impact craters. The minimum depth of basalt has been estimated where craters have not exposed underlying highland material. The profile has been used to estimate the minimum volume of basalt within the basin to be ≈500,000 km³.     

The last interglacial ocean

The final effort of the CLIMAP project was a study of the last interglaciation, a time of minimum ice volume some 122,000 yr ago coincident with the Substage 5e oxygen isotopic minimum. Based on detailed oxygen isotope analyses and biotic census counts in 52 cores across the world ocean, last interglacial sea-surface temperatures (SST) were compared with those today. There are small SST departures in the mid-latitude North Atlantic (warmer) and the Gulf of Mexico (cooler). The eastern boundary currents of the South Atlantic and Pacific oceans are marked by large SST anomalies in individual cores, but their interpretations are precluded by no-analog problems and by discordancies among estimates from different biotic groups. In general, the last interglacial ocean was not significantly different from the modern ocean. The relative sequencing of ice decay versus oceanic warming on the Stage 6/5 oxygen isotopic transition and of ice growth versus oceanic cooling on the Stage 5e/5d transition was also studied. In most of the Southern Hemisphere, the oceanic response marked by the biotic census counts preceded (led) the global ice-volume response marked by the oxygen-isotope signal by several thousand years. The reverse pattern is evident in the North Atlantic Ocean and the Gulf of Mexico, where the oceanic response lagged that of global ice volume by several thousand years. As a result, the very warm temperatures associated with the last interglaciation were regionally diachronous by several thousand years. These regional lead-lag relationships agree with those observed on other transitions and in long-term phase relationships; they cannot be explained simply as artifacts of bioturbational translations of the original signals.     

Dust provenance and its role as a potential fertilizing agent for the Okavango Delta,Botswana

Dust plays a globally important role in supplying biologically essential elements to landscapes underlain by nutrient-poor substrates. Here we show that dust may play a significant role in sustaining productivity in the vast wetlands of the Okavango Delta in southern Africa, one of the world's richest biodiversity hotspots. Dust accumulates preferentially on tree-covered islands in the seasonal swamps of the Delta, creating pockets of fine-grained, nutrient-rich material within the semi-arid landscape of the Kalahari Desert. Strontium and neodymium isotopes reveal that this dust likely originates predominantly from the Makgadikgadi salt pans, located 300 km away, and contributes 10–80% of the fine-grained material present in Okavango island soils. Surface material sourced from the Makgadikgadi Pans contains relatively high amounts of bioavailable phosphorus and iron, potentially influencing Okavango Delta biological productivity. We propose that long-term ecosystem productivity and nutrient availability in the Okavango may be strongly mediated by regional dust inputs. Understanding the influence of dust deposition on nutrient loads and biogeochemical cycling is thus critical for predicting the response of the Okavango Delta to future changes in climate. We suggest that dust inputs may play a significant role in the supply of nutrients to other large, global wetland systems located in dryland environments. © 2020 John Wiley & Sons, Ltd     

Sources of knowledge and ignorance in climate research

Ignorance is an inevitable component of climate change research, and yet it has not been specifically catered for in standard uncertainty guidance documents for climate assessments. Reports of ignorance in understanding require context to explain how such ignorance does and does not affect understanding more generally. The focus of this article is on dynamical sources of ignorance in regional climate change projections. A key source of ignorance in the projections is the resolution-limited treatment of dynamical instabilities in the ocean component of coupled climate models. A consequence of this limitation is that it is very difficult to quantify uncertainty in regional projections of climate variables that depend critically upon the details of the atmospheric flow. The standard methods for quantifying or reducing uncertainty in regional projections are predicated on the models capturing and representing the key dynamical instabilities, which is doubtful for present coupled models. This limitation does not apply to all regional projections, nor does it apply to the fundamental findings of greenhouse climate change. Much of what is known is not highly flow-dependent and follows from well grounded radiative physics and thermodynamic principles. The growing field of applications of regional climate projections would benefit from a more critical appraisal of ignorance in these projections.     

ARTIFICIAL INTELLIGENCE AND ITS APPLICABILITY TO GEOGRAPHICAL PROBLEM SOLVING

Artificial Intelligence (AI) may be regarded as an attempt to understand the processes of perception and reasoning that underlie successful problem-solving and to incorporate the results of this research in effective computer programs. At present, AI is largely a collection of sophisticated programming techniques. Many of these techniques are based on the premise that the manner in which knowledge is acquired, organized, accessed and modified in both humans and machines provides the basis of “intelligent” decision-making. The techniques of AI are applicable to a wide variety of geographical problems, including the modeling of individual and aggregate decision-making, and the construction of expert systems and “intelligent” geographical information systems.     

Climate change stressors in the Sahel

The Sahel is prone to climate stressors such as droughts, winds and floods. This study employs a systematic review approach to track the frequency with which these stressors are reported in the scientific peer reviewed literature, examining publishing trends to identify which stressors are most reported, documenting the spatial distribution of these stressors from a country and regional perspective, and assessing the role played by climatic and non-climatic drivers in causing the stressors. A total of (n = 388) reports of stressors were documented in (n = 164) peer reviewed articles. From a country perspective, Southern Niger records the highest number of reports on all three stressors (15.97%), followed by Ethiopia (11.85%) and Senegal (10.56%). Regionally, West African Sahel recorded the highest number of reports on all stressors (49.97%) followed by East African Sahel (29.89%) and Central African Sahel (12.11%) respectively. Droughts are observed to be the most frequently reported stressor (n = 219), followed by floods (n = 123) and winds (n = 46). The decade 1975–1985 recorded the highest reports of stressors (n = 207), while the decade 1997–2007 recorded (n = 80) and the decade 1986–1996 recorded (n = 52). While climatic drivers are dominant (52%), there is however an increasing attribution of the drivers of the stressors to non-climatic drivers (47%). The main weakness of this study is that it uses peer reviewed papers dwelling on climate stressors as a proxy for climate stressors in the Sahel and a lot more studies could be hiding in non-peer reviewed studies, underscoring that this work provides a general and baseline overview of the climate stressors in the region.     

In situ pore‐pressure measurement in Mississippi delta front sediments

Abstract

A differential piezometer was used to monitor excess pore pressure in the soft clayey seafloor sediments of Block 28, South Pass, Mississippi delta, from September 1975 to March 1976. An ambient excess pore pressure of about 32 kPa was measured at a depth of 6.4 m below the mudline in a water depth of 19 m. Storm‐wave‐generated cyclic fluctuations of ± 4 kPa about the ambient were measured during Hurricane Eloise. Irregular, long‐period, small‐amplitude fluctuations in excess pore pressures persisted for 4 days following the storm. An effective stress analysis was made by using excess pore pressures; in situ field vane‐shear strength, t _fv, measurements; and laboratory wet unit weights measured by Lehigh and NOAA. The effective stress of the SEA‐SWAB site soil was calculated to be zero to a depth of about 6 m, below which it increased to 3.5 kPa at a depth of 15 m. Values of c´ = 4.6 kPa, ?´ = 56°, and T _FV/σ_vo(c/p) =0.1–0.2 were calculated, and it was concluded that these data do not represent the in situ condition of the soil because of the probability that the measured soil properties were affected by the presence of gas. However, it is clear that the soil is significantly underconsolidated.     

The adoption of agroecology and conventional farming techniques varies with socio-demographic characteristics of small-scale farmers in the Fako and Meme divisions of Cameroon

This study verifies how the adoption of agroecology and conventional farming techniques varies among different socio-economic characteristics. Data acquisition involved the administering of 200 questionnaires and the organization of two focus group discussions (FGDs). The data collected were analysed using: frequencies, means, probabilities, odds and odd ratios. The FGDs were analysed using context analysis. The analyses were performed in SPSS version 20 and Wordstat 7. The results reveal that older respondents tend to adopt conventional farming techniques more than other categories due mainly to inertia or the inability to adapt to changes and their limited propensity to adopt agroecology techniques. Farmers with fewer years of farming experience are more open to agroecology related techniques due to higher inertia while those with more years of farming experience converge with older farmers who tend to prefer conventional farming. The higher the level of income, the more frequent the use of agroecology techniques. Families with more members who live and work on the farm are more open to agroecology; however, there is a limit beyond which the more the number of family members who live and work on the farm, the less the probability of adopting agroecology techniques. The higher the level of education, the greater the propensity to adopt and experiment with agroecology.