Biogeography and Genetic Diversity of Pearl Millet (Pennisetum glaucum) from Sahelian Africa

Sahelian Africa makes up the native range of pearl millet and the impact of domestication on the genetic diversity of wild, intermediate, and cultivated subspecies is still poorly understood. Wild populations are known to spontaneously germinate throughout this range and hybridize with cultivated material. To investigate genetic structure, populations of pearl millet from several African countries were analyzed at the morphological and molecular levels for diversity. Results demonstrate how little differentiation there is between subspecies and populations. It appears that pearl millet throughout the Sahel remains a metapopulation with large hybrid zones. These results have important implications for conservation of pearl millet.     

Integrating landscape connectivity into the evaluation of ecosystem services for biodiversity conservation and its implications for landscape planning

This paper examines the integration of landscape connectivity and ecosystem services. It is based on the assumption that if a habitat within a landscape has a more significant role in connecting with other habitats, it would have a higher ecosystem services value for biodiversity conservation. The Shenzhen River watershed, a cross-border region shared by the city of Shenzhen and the Hong Kong Special Administrative Region in China, was used as a case study. An area-based functional connectivity index, known as the possibility of connectivity (PC), was implemented to examine the temporal and spatial dynamics of the value of ecosystem services for biodiversity conservation over the period from 1988 to 2008. To evaluate the effectiveness of the PC index, a comparison was made between the conventional assessment method for ecosystem services and the proposed method. Results suggest that our proposed method can identify significant reduction of ecosystem services that was not only due to the decrease of habitat size, but also caused by the damage of connectivity among habitat patches. Also, it can identify sites which should have a high priority in restoring the ecosystem services for biodiversity conservation. In conclusion, this study provides a way to consider landscape connectivity in the evaluation of ecosystem services which is essential for landscape planning and nature conservation.     

基于对象—事件—过程的时空数据模型及其应用

根据地理本体思想,提出和构建了基于对象—事件—过程的面向对象的时空数据模型.该模型基于3个基本地理实体类型:地理对象、地理事件和地理过程,三者基于地理本体的特性,本体化地表达和概括了地理现象和事物.该模型能有效地描述和表达复杂的地理动态现象和事物,能增强性的探讨和表征地理现象发生和发展的内在关联.甚者,鉴于描述和表达三者的侧重点不同,该模型可灵动性地整合或拆分成其它时空数据模型,不失为一种通用的时空数据模型.最后,以动态变化的海冰为例,验证了模型的可行性和有效性.     

Stochastic subspace identification for output‐only modal analysis: application to super high‐rise tower under abnormal loading condition

The objective of this paper is to develop an online system parameter estimation technique from the response measurements through using the recursive covariance‐driven stochastic subspace identification (SSI‐COV) approach. In developing the recursive SSI‐COV, to avoid time‐consumption of singular value decomposition in recursive SSI, the extended instrumental variable version of the projection approximation subspace tracking method is used in SSI‐COV. Besides, to reduce the effect of noise on the results of identification, the preprocessing of data using recursive singular spectrum analysis technique is also presented to remove the noise contaminant measurements to enhance the stability of data analysis. On the basis of the proposed method, both the ambient vibration and seismic response data of a tower (Canton Tower) are used to observe the time‐varying system natural frequencies of a tower from its operating condition. Results from using off‐line SSI‐COV method under normal operating condition are also presented. Comparison on the identified time‐varying dynamic characteristics of the tower under normal operating condition and earthquake response of distanced earthquake event is discussed. Copyright © 2012 John Wiley & Sons, Ltd.     

On topographic core-mantle coupling

Abstract

The purpose of this note is two-fold: to draw attention to a perplexing difficulty connected with topographic core-mantle coupling, and to suggest tentatively an explanation. The difficulty is an apparent conflict between the most comprehensive theory of the coupling so far attempted (Anufriev and Braginsky, 1975a, b, 1977a, b) and recent explicit calculations based on magnetic and seismic information (Speith et al., 1986). It is argued that asymmetric deviations from Anufriev and Braginsky's basically axisymmetric model of the underlying core flow are capable of resolving the difficulty.     

A parcel formulation of Hamiltonian layer models

Starting from the three-dimensional hydrostatic primitive equations, we derive Hamiltonian N-layer models with isentropic tropospheric and isentropic or isothermal stratospheric layers. Our construction employs a new parcel Hamiltonian formulation which describes the fluid as a continuum of Hamiltonian ordinary differential equations bound together by integral transport laws. In particular, we show that this parcel Hamiltonian structure is compatible with the stacking of layers under isentropic or isothermal constraints. The appeal of the parcel formulation is the simplification of various calculations, in particular the derivation of the continuum Poisson bracket and the proof of the Jacobi identity. A comparison and connection is made between the Hamiltonian dynamics of fluid parcels and the Hamiltonian system of partial differential equations. The parcel formulation can be seen as a precursor and tool for the study of Hamiltonian numerical schemes.     

On the quest for chaotic attractors in hydrological processes

Abstract

In the last two decades, several researchers have claimed to have discovered low-dimensional determinism in hydrological processes, such as rainfall and runoff, using methods of chaotic analysis. However, such results have been criticized by others. In an attempt to offer additional insights into this discussion, it is shown here that, in some cases, merely the careful application of concepts of dynamical systems, without doing any calculation, provides strong indications that hydrological processes cannot be (low-dimensional) deterministic chaoti. Furthermore, it is shown that specific peculiarities of hydrological processes on fine time scales, such as asymmetric, J-shaped distribution functions, intermittency, and high autocorrelations, are synergistic factors that can lead to misleading conclusions regarding the presence of (low-dimensional) deterministic chaos. In addition, the recovery of a hypothetical attractor from a time series is put as a statistical estimation problem whose study allows, among others, quantification of the required sample size; this appears to be so huge that it prohibits any accurate estimation, even with the largest available hydrological records. All these arguments are demonstrated using appropriately synthesized theoretical examples. Finally, in light of the theoretical analyses and arguments, typical real-world hydrometeorological time series, such as relative humidity, rainfall, and runoff, are explored and none of them is found to indicate the presence of chaos.     

Soil moisture dynamics in coastal savanna soils in the tropics under different soil management practices

Abstract

Soil moisture is important for crop cultivation and its adequacy to meet crop-water requirements is determined by the degree of soil management practised and the quantity of water applied to the soil. This study investigates soil moisture dynamics on three plots: Bare (clean, weeds removed), Weedy (kept weedy), and Mulched (cleared of weeds and fully covered with grass mulch) during rainy and dry periods at the Teaching and Research Farm at the University of Cape Coast, in the coastal savanna zone of Ghana. Soil moisture dynamics under different levels of soil compaction were also studied. A Massey Ferguson tractor (MF265) was used to compact the soil at various levels by making 0, 1, 5, 9 and 13 passes. During both the rainy and the dry periods, moisture retention in the soil under bare, weedy and mulched plots increased with depth. During the rainy period, the mean soil moisture retention was in the order: Mulched > Weedy > Bare at both 0–20 cm and 20–40 cm depths. Within a 7–day period, soil moisture measurements from a day after heavy rainfall (intensity > 7 mm h^?1) gave mean moisture losses of 2.7, 4.1 and 3.9% for the Bare, Weedy and Mulched plots, respectively. During the dry period, however, the mean soil moisture retention was of the order: Mulched > Bare > Weedy at both 0–20 cm and 20–40 cm depths. Mean moisture loss during a 7–day dry period was 4.5, 2.9 and 3.4% for the Bare, Weedy and Mulched plots, respectively. Under different levels of soil compaction, the mean moisture retention in the soil increased from 8.3% at 0 pass to 17.8% at 13 passes within the 0–20 cm depth, whilst it decreased from 13.3 to 5.9% from 0 to 13 passes, respectively, within the 20–40 cm depth. It was realized that at less than two passes, the mean soil moisture retention within the 0–20 cm depth was less than the mean moisture retention within the 20–40 cm depth, but the converse happened for more than two passes. The study showed that mulching the soil surface helped to retain enough soil moisture during both the rainy and the dry seasons. Also, soil with high sand content required some sort of soil compaction in order to retain enough moisture at the crop rooting zone.     

Predicting Diel,Diurnal and Nocturnal Dynamics of Dissolved Oxygen and Chlorophyll‐a Using Regression Models and Neural Networks

Human‐induced and natural interruptions with continuous streams of observational data necessitate the development of gap‐filling and prediction strategies towards better understanding, monitoring and management of aquatic systems. This study quantified the efficacy of multiple non‐linear regression (MNLR) versus artificial neural network (ANN) models as well as the temporal partitioning of diurnal versus nocturnal data for the predictions of chlorophyll‐a (chl‐a) and dissolved oxygen (DO) dynamics. The temporal partitioning increased the predictive performances of the best MNLR models of diurnal DO by 45% and nocturnal DO by 4%, relative to the best diel MNLR model of diel DO ($r_{{\rm adj}}^{2} = 68.8\%$ ). The ANN‐based predictions had a higher predictive power than the MNLR‐based predictions for both chl‐a and DO except for diurnal DO dynamics. The best ANNs based on independent validations were multilayer perceptron (MLP) for diel chl‐a, generalized feedforward (GFF) for diurnal and nocturnal chl‐a, MLP for diel DO, GFF for diurnal DO, and MLP for nocturnal DO.     

Using a simulation analysis to evaluate the impact of crop mapping error on crop area estimation from stratified sampling

ABSTRACT

To analyze the efficiency of area estimations (i.e. estimation accuracy and variation of estimation) impacted by crop mapping error, we simulated error at eight levels for thematic maps using a stratified sampling estimation methodology. The results show that the estimation efficiency is influenced by the combination of the sample size and the error level. Evaluating the trade-offs between sample size and error level showed that reducing the crop mapping error level provides the most benefit (i.e. higher estimation efficiency). Further, sampling performance differed based on the heterogeneity of the crop area. The results demonstrated that the influence of increasing the error level on estimation efficiency is more detrimental in heterogeneous areas than in homogeneous ones. Therefore, to obtain higher estimation efficiency, a larger sample size and lower error level or both are needed, especially in heterogeneous areas. We suggest that existing land-cover maps should first be used to determine the heterogeneity of the area. The appropriate sample size for these areas then can be determined according to all three factors: heterogeneity, expected estimation efficiency, and sampling budget. Overall, extending our understanding of the impacts of crop mapping error is necessary for decision making to improve our ability to effectively estimate crop area.