Taxonomy and Species Richness of Amazonian Pimplinae and Rhyssinae (hymenoptera: ichneumonidae)

The Amazonian region, the biggest rain forest of our planet, is known for its extraordinary biodiversity. Most of this diversity is still unexplored and new species of different taxa are regularly found there. In this region, as in most areas of the world, insects are some of the most abundant organisms. Therefore, studying this group is important to promote the conservation of these highly biodiverse ecosystems of the planet. Among insects, parasitoid wasps are especially interesting because they have potential for use as biodiversity indicators and biological control agents in agriculture and forestry. The parasitoid wasp family Ichneumonidae is one of the most species rich groups among the kingdom Animalia. This group is still poorly known in many areas of the world; the Amazonian region is a clear example of this situation. Ichneumonids have been thought to be species poor in Amazonia and other tropical areas. However, recent studies are suggesting that parasitoid wasps may be quite abundant in Amazonia and possibly in most tropical areas of the world. The aim of my doctoral thesis is to study the species richness and taxonomy of two of the best known ichneumonid subfamilies in the Neotropical region, Pimplinae and Rhyssinae. To do this I conducted two extensive sampling programs in the Peruvian Amazonia. I examined also a large number of Neotropical ichneumonids deposited to different natural history museums. According to the results of my thesis, the species richness of these parasitoids in the Amazonian region is considerably higher than previously reported. In my research, I firstly further develop the taxonomy of these parasitoids by describing many new species and reporting several new faunistic records (I, II, III). In this first part I focus on two genera (Xanthopimpla and Epirhyssa) which were thought to be rather species poor. My thesis demonstrates that these groups are actually rather species rich in the Amazonian region. Secondly, I concentrate on the species richness of these parasitoids in a global comparison showing that the Neotropical region and especially the Peruvian Amazonia is one of the most species rich areas of Pimpliformes ichneumonids (V). Furthermore, I demonstrate that with the data available to date no clear latitudinal gradient in species richness is visible. Thirdly, increasing the macroecological knowledge of these parasitoids I show that some previously unreported ichneumonid subfamilies are present in the Amazonian region (IV). These new insights and the results of the global comparison of ichneumonid inventories suggest that the previous belief of low diversity in the tropics is most likely related to a lack of sampling effort in the region. Overall, my research increases the knowledge of Neotropical ichneumonids highlighting the importance of Peruvian Amazonia as one of the diversity hotspots of parasitoid wasps.

Evaluation of the spot urine sampling technique to assess urinary pseudouridine excretion in lactating dairy cows

Selostus: Mahdollisuus lyhytaikaisen virtsankeruun käyttöön lypsylehmien virtsan pseudouridiinin erityksen määrittämisessä

A simple device for sampling of volumetric forest soil cores

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Variation in soil organic carbon and thickness of soil horizons within a boreal forest stand - effect of trees and implications for sampling

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Cut-off importance sampling of bole volume

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Inventory of sparse forest populations using adaptive cluster sampling

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Comparison of randomized branch sampling with and without replacement at the first stage

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On Effort Estimation in Software Projects

Software engineering is criticized as not being engineering or 'well-developed' science at all. Software engineers seem not to know exactly how long their projects will last, what they will cost, and will the software work properly after release. Measurements have to be taken in software projects to improve this situation. It is of limited use to only collect metrics afterwards. The values of the relevant metrics have to be predicted, too. The predictions (i.e. estimates) form the basis for proper project management. One of the most painful problems in software projects is effort estimation. It has a clear and central effect on other project attributes like cost and schedule, and to product attributes like size and quality. Effort estimation can be used for several purposes. In this thesis only the effort estimation in software projects for project management purposes is discussed. There is a short introduction to the measurement issues, and some metrics relevantin estimation context are presented. Effort estimation methods are covered quite broadly. The main new contribution in this thesis is the new estimation model that has been created. It takes use of the basic concepts of Function Point Analysis, but avoids the problems and pitfalls found in the method. It is relativelyeasy to use and learn. Effort estimation accuracy has significantly improved after taking this model into use. A major innovation related to the new estimationmodel is the identified need for hierarchical software size measurement. The author of this thesis has developed a three level solution for the estimation model. All currently used size metrics are static in nature, but this new proposed metric is dynamic. It takes use of the increased understanding of the nature of the work as specification and design work proceeds. It thus 'grows up' along with software projects. The effort estimation model development is not possible without gathering and analyzing history data. However, there are many problems with data in software engineering. A major roadblock is the amount and quality of data available. This thesis shows some useful techniques that have been successful in gathering and analyzing the data needed. An estimation process is needed to ensure that methods are used in a proper way, estimates are stored, reported and analyzed properly, and they are used for project management activities. A higher mechanism called measurement framework is also introduced shortly. The purpose of the framework is to define and maintain a measurement or estimationprocess. Without a proper framework, the estimation capability of an organization declines. It requires effort even to maintain an achieved level of estimationaccuracy. Estimation results in several successive releases are analyzed. It isclearly seen that the new estimation model works and the estimation improvementactions have been successful. The calibration of the hierarchical model is a critical activity. An example is shown to shed more light on the calibration and the model itself. There are also remarks about the sensitivity of the model. Finally, an example of usage is shown.

Sampling in chemical analysis

The uncertainty of any analytical determination depends on analysis and sampling. Uncertainty arising from sampling is usually not controlled and methods for its evaluation are still little known. Pierre Gy’s sampling theory is currently the most complete theory about samplingwhich also takes the design of the sampling equipment into account. Guides dealing with the practical issues of sampling also exist, published by international organizations such as EURACHEM, IUPAC (International Union of Pure and Applied Chemistry) and ISO (International Organization for Standardization). In this work Gy’s sampling theory was applied to several cases, including the analysis of chromite concentration estimated on SEM (Scanning Electron Microscope) images and estimation of the total uncertainty of a drug dissolution procedure. The results clearly show that Gy’s sampling theory can be utilized in both of the above-mentioned cases and that the uncertainties achieved are reliable. Variographic experiments introduced in Gy’s sampling theory are beneficially applied in analyzing the uncertainty of auto-correlated data sets such as industrial process data and environmental discharges. The periodic behaviour of these kinds of processes can be observed by variographic analysis as well as with fast Fourier transformation and auto-correlation functions. With variographic analysis, the uncertainties are estimated as a function of the sampling interval. This is advantageous when environmental data or process data are analyzed as it can be easily estimated how the sampling interval is affecting the overall uncertainty. If the sampling frequency is too high, unnecessary resources will be used. On the other hand, if a frequency is too low, the uncertainty of the determination may be unacceptably high. Variographic methods can also be utilized to estimate the uncertainty of spectral data produced by modern instruments. Since spectral data are multivariate, methods such as Principal Component Analysis (PCA) are needed when the data are analyzed. Optimization of a sampling plan increases the reliability of the analytical process which might at the end have beneficial effects on the economics of chemical analysis,

Stratification of regional sampling by model-predicted changes of carbon stocks in Forested mineral soils

Selective papers of the workshop on "Development of models and forest soil surveys for monitoring of soil carbon", Koli, Finland, April 5-9 2006.