Impact of integration time steps of rain drop size distribution on their structuring and their modelling: a case study in northern Benin

This paper focused on modelling rain drop size distributions (DSDs) of various integration time steps using unimodal DSD models (gamma and lognormal). Rain DSD data considered are those collected from 2005 to 2007 near Djougou city in the north-western region of Benin Republic. The efficiency of these models was characterized by statistical criteria, mainly Nash and KGE. These criteria are used to assess the level of fitting of rain DSD spectra. Superimposed rain DSDs were then parameterized with the rainfall rate, using the scaling law formalism. Results show that there is an improvement in the structuring of the rain DSDs according to their measurement duration. Analysis of the occurrence statistics of the structuring of the spectra reveals that the Spectra ill adjusted by a unimodal DSD model represents 5 to 15% of the population of 1 min rain DSDs. This population decreases according to the measurement duration of the spectra. The optimal measurement time is found to be 10 min. Furthermore, parameters of the shape functions (gamma and lognormal) increase or decrease markedly according to the measurement duration of the rain DSD spectra. For applications using the relationships deduced from the rain DSDs, results suggested that the measurement time scale must be taken into account when choosing appropriate relationships

Impact of integration time steps of rain drop size distribution on their structuring and their modelling: a case study in northern Benin

This paper focused on modelling rain drop size distributions (DSDs) of various integration time steps using unimodal DSD models (gamma and lognormal). Rain DSD data considered are those collected from 2005 to 2007 near Djougou city in the north-western region of Benin Republic. The efficiency of these models was characterized by statistical criteria, mainly Nash and KGE. These criteria are used to assess the level of fitting of rain DSD spectra. Superimposed rain DSDs were then parameterized with the rainfall rate, using the scaling law formalism. Results show that there is an improvement in the structuring of the rain DSDs according to their measurement duration. Analysis of the occurrence statistics of the structuring of the spectra reveals that the Spectra ill adjusted by a unimodal DSD model represents 5 to 15% of the population of 1 min rain DSDs. This population decreases according to the measurement duration of the spectra. The optimal measurement time is found to be 10 min. Furthermore, parameters of the shape functions (gamma and lognormal) increase or decrease markedly according to the measurement duration of the rain DSD spectra. For applications using the relationships deduced from the rain DSDs, results suggested that the measurement time scale must be taken into account when choosing appropriate relationships

Remote Sensing of Savannas and Woodlands

Savannas and woodlands are one of the most challenging targets for remote sensing. This book provides a current snapshot of the geographical focus and application of the latest sensors and sensor combinations in savannas and woodlands. It includes feature articles on terrestrial laser scanning and on the application of remote sensing to characterization of vegetation dynamics in the Mato Grosso, Cerrado and Caatinga of Brazil. It also contains studies focussed on savannas in Europe, North America, Africa and Australia. It should be important reading for environmental practitioners and scientists globally who are concerned with the sustainability of the global savanna and woodland biome

The Role of Europe in World-Wide Science and Technology: Monitoring and Evaluation in a Context of Global Competition

Noyons ECM, Buter RK, van Raan AFJ, Schwechheimer H, Winterhager M, Weingart P. The Role of Europe in World-Wide Science and Technology: Monitoring and Evaluation in a Context of Global Competition. Leiden: Universiteit Leiden; 2000

Climate variability and human anthropometric outcomes: Evidence from India

The World Meteorological Organisation defines Climate Variability as “variations in the mean state and other statistics of the climate on all temporal and spatial scales, beyond individual weather events”1. These variations can cause natural disasters, such as floods or prolonged droughts, which in turn may have numerous consequences for public health. While previous work has considered the health effects of extreme climate events, this thesis focuses on the full range of variability in precipitation and temperature as the exposure, and human health indicators, including attained or completed growth and nutritional status, as primary outcomes among both children and adults (Height-for-Age z-score (HAZ), Weight-for-Age z-score (WAZ) and Weight-for-Height z-score (WHZ) for children and height, weight and Body Mass Index (BMI) for adult women). Using this framework and utilising a large Demographic and Health Survey dataset, this thesis tested whether climate variability in India and more specifically in Uttar Pradesh, a large state that faces extreme fluctuations in weather patterns, is associated with short- and long-term effects on human health indicators, using a sample size of 32,498 children and 21,793 adult women. The investigation involved exploring the effect of climate exposure at the time of birth in children, the propagation of this effect to adulthood and its inter-generational persistence, using multiple linear regression models. Finally, the association of climate exposure at various times around birth with health outcomes was also explored. The outcomes of the analysis supported the hypotheses, indicating that the precipitation and temperature patterns in early life explain some of the variability in child HAZ, WAZ and WHZ, as well as in women’s adult height, weight and BMI. This can be assumed to reflect differential exposure to ecological factors associated with precipitation and temperature that affect early growth rate. Broadly the effects were negative, but at a more subtle level they had more complex components and also interacting associations, which are described later in detail. The associations were stronger mostly in the rural areas compared to urban areas and also the younger children were found to be more sensitive to climate variability than the older children. At the inter-generational level, the signal detected was positive but small and did not seem to denote biological significance. The investigation of the effect of climate exposure at various early life timings indicated that the effect varies between the different timings and the time of birth is not always the most sensitive one. Overall, the results suggest that there is no single association of climate with these human health indicators

Interactions between natural and anthropogenic impacts on the genetic diversity and population genetic structure of European beech forests

The accurate assessment of forest persistence under environmental change is dependent on the fundamental understanding of the genetic consequences of human intervention and its comparison to that of natural processes, as declines in genetic diversity and changes in its structuring can compromise the adaptive ability of a population. The European beech, Fagus sylvatica, has experienced prolonged human impact over its 14 million ha range with contemporary forests harbouring high ecological, economic, and cultural value. Historical traditional management practices, such as coppicing and pollarding, have impacted a large portion of Europe’s forests. This form of management encouraged vegetative regeneration, prolonging the longevity of individual trees. In several cases, the structure and function of managed trees and their associated ecosystems were significantly altered. Specifically, coppiced beech forests in Europe displayed significantly larger extents of spatial genetic structuring compared to their natural counterparts, revealing a change in the genetic composition of the population due to decades of management. Humans have also aided in the dispersal of beech within and outside of its natural range. In Great Britain, the putative native range retained signals of past colonisation dynamics. However, these signals were obscured by the wide-spread translocation of the species throughout the country. Evidence of post-glacial colonisation dynamics can be found in Sweden as well. In contrast to Britain, the structure of this natural leading range edge displays a gradual reduction in population size where isolation was found to have acted as an effective barrier to gene flow reducing the genetic diversity of populations

Nonparametric Stochastic Generation of Daily Precipitation and Other Weather Variables

Traditional stochastic approaches for synthetic generation of weather variables often assume a prior functional form for the stochastic process, are often not capable of reproducing the probabilistic structure present in the data, and may not be uniformly applicable across sites. In an attempt to find a general framework for stochastic generation of weather variables, this study marks a unique departure from the traditional approaches, and ushers in the use of data-driven nonparametric techniques and demonstrates their utility. Precipitation is one of the key variables that drive hydrologic systems and hence warrants more focus . In this regard, two major aspects of precipitation modeling were considered: (I) resampling traces under the assumption of stationarity in the process, or with some treatment of the seasonality, and (2) investigations into interannual and secular trends in precipitation and their likely implications. A nonparametric seasonal wet/dry spell model was developed for the generation of daily precipitation. In this the probability density functions of interest are estimated using non parametric kernel density estimators. In the course of development of this model, various nonparametric density estimators for discrete and continuous data were reviewed, tested, and documented, which resulted in the development of a nonparametric estimator for discrete probability estimation. Variations in seasonality of precipitation as a function of latitude and topographic factors were seen through the non parametric estimation of the time-varying occurrence frequency. Nonparametric spectral analysis, performed on monthly precipitation, revealed significant interannual frequencies and coherence with known atmospheric oscillations. Consequently, a non parametric, nonhomogeneous Markov chain for modeling daily precipitation was developed that obviated the need to divide the year into seasons. Multivariate nonparametric resampling technique from the nonparametrically fitted probability density functions, which can be likened to a smoothed bootstrap approach, was developed for the simulation of other weather variables (solar radiation, maximum and minimum temperature, average dew point temperature, and average wind speed). In this technique the vector of variables on a day is generated by conditioning on the vector of these variables on the preceding day and the precipitation amount on the current day generated from the wet/dry spell model

Conservation Genetics and Mark-Recapture Monitoring of the Rare Pigeon Mountain Salamander (Plethodon petraeus) within a Highly Restricted Range

Globally, amphibian species are experiencing declines at an alarming rate largely due to habitat loss, disease and climate change. Species with limited ranges are at an elevated risk of a significant decline in population numbers and extinction because of the inability to avoid and recover from these impacts. Long-term management plans are critical for conservation of species with small ranges; however, the knowledge required to develop effective plans is absent from the literature for many species. One such species is the Pigeon Mountain Salamander. The distribution of the Pigeon Mountain Salamander, Plethodon petraeus, is restricted to roughly 17 kilometers along the eastern flank of Pigeon Mountain in northwest Georgia. Consequently, P. petraeus is highly vulnerable to the impacts associated with amphibian declines, a fact that placed the salamander on the list of rare and protected species in Georgia. The distribution of P. petraeus is highly correlated with patchily distributed rocky outcrops, which provides an efficient management target. However, the development of an effective, long-term management plan requires an understanding of genetic population structure, gene flow, and habitat use patterns. Robust design mark-recapture methods and population genetics with cross- amplified microsatellites were used to further our knowledge of how this species is distributed. Mark recapture results indicated high site fidelity of recaptured salamanders and abundance estimates (average number of total salamander abundance in a single plot, 57.8) within two 25 x 25 meter study areas. Population genetic results revealed four distinct populations across the known range of P. petraeus and significant isolation by distance genetic structuring