Comparing multiple correspondence and principal component analyses with biomechanical signals. Example with turning the steering wheel

The purpose of this article is to compare Principal Component Analysis (PCA) and a much less used method, i.e. MCA (Multiple Correspondence Analysis) with data being first changed into membership values to fuzzy space windows. For such a comparison, data from an experimental study about turning the steering wheel is used. In a didactic perspective, this article only considers one multidimensional signal with 5 components: 3 linked to the steering wheel angle and hand positions and 2 to hand effort variables. A discussion weighs out the pros and the cons of both methods with criteria such as the possibility to show complex relational phenomena, the analysis/computing time or the information loss inherent to the averaging stage (in the perspective to analyze several hundreds of large multidimensional signals).     

Unbiased Estimation of Odds Ratio by Using Negative Binomial Plans

The use of the negative binomial distribution in both the numerator and denominator in prospective studies leads to an unbiased estimate of the odds ratio and an exact expression for its variance. Sample sizes that minimize the variance of odds ratio estimates are specified. The variance of the odds ratio estimate is shown to be close to the Cramér-Rao lower bound.     

Scale‐dependent biases in species counts in a grassland

Abstract. Numbers of plant species were recorded in species‐rich meadows in the Bílé Karpaty Mts., SE Czech Republic, with the aim to evaluate the sampling error made by well‐trained observers. Five observers recorded vascular plants in seven plots ranging from 9.8 cm² to 4 m² independently and were not time‐limited. In larger plots a discrepancy of 10–20% was found between individual estimates, in smaller plots discrepancy increased to 33%, on average. The gain in observed species richness by combining records of individual observers (in comparison with the mean numbers estimated by single observers) decreased from the smallest plot (27–82% for two to five observers) to the largest one (13–25%). However, after misidentified and suspicious records were eliminated, the gain was much lower and became scale‐independent; two observers added 12% species, on average, and the increase by combining species lists made by three or more observers was negligible (3% more on average). It is concluded that most discrepancies between individual observers were caused by misidentification of rare seedlings and young plants. We suggest that in species‐rich meadows plants should be recorded by at least three observers together and that they should consult all problematic plant specimens together in the field, to minimize errors.     

Atlas versus range maps: robustness of chorological relationships to distribution data types in European mammals

Aim Chorological relationships describe the patterns of distributional overlap among species. In addition to revealing biogeographical structure, the resulting clusters of species with similar geographical distributions can serve as natural units in conservation planning. Here, we assess the extent to which temporal, methodological and taxonomical differences in the source of species’ distribution data can affect the relationships that are found. Location Western Europe. Methods We used two data sets – the Atlas of European mammals and polygon range maps from the IUCN Global Mammal Assessment – both as presence–absence data for UTM 50 km × 50 km squares. We performed pairwise comparisons among 156 species for each data set to build matrices of the similarity in distribution across species, using both Jaccard’s and Baroni‐Urbani & Buser’s indices. We then compared these similarity matrices (chorological relationships), as well as the species richness and occurrence patterns from the two data sets. Results As expected, range maps increased both the mean prevalence per species and mean species richness per grid cell in comparison to atlas data, reflecting the general view that these data types respectively over‐ and underestimate species occurrence. However, species richness and occurrence patterns in atlas and range map data were positively associated and, most importantly, the chorological relationships underlying the two data sets were highly similar. Main conclusions Despite many methodological, temporal and taxonomical differences between atlas data and range maps, the chorological relationships encountered between species were similar for both data sets. Chorological analyses can thus be robust to the data source used and provide a solid basis for analytical biogeographical studies, even over broad spatial scales.     

Predicting the unexpected: using a qualitative model of a New Zealand dryland ecosystem to anticipate pest management outcomes

Pest management is expensive and there is often uncertainty about the benefits for the resources being protected. There can also be unintended consequences for other parts of the ecosystem, especially in complex food webs. In making decisions managers generally have to rely on qualitative information collected in a piecemeal fashion. A method to assist decision making is a qualitative modelling approach using fuzzy cognitive maps, a directed graphical model related to neural networks that can take account of interactions between pests and conservation assets in complex food webs. Using all available information on relationships between native and exotic resources and consumers, we generated hypotheses about potential consequences of single‐species and multi‐species pest control on the long‐term equilibrium abundances of other biotic components of an ecosystem. We applied the model to a dryland ecosystem in New Zealand because we had good information on its trophic structure, but the information on the strength of species interactions was imprecise. Our model suggested that pest control is unlikely to significantly boost native invertebrates and lizards in this ecosystem, suggesting that other forms of management may be required for these groups. Most of the pest control regimes tested resulted in greater abundances of at least one other pest species, which could potentially lead to other management problems. Some of the predictions were unexpected, such as more birds resulting from possum and mouse control. We also modelled the effects of an increase in invasive rabbits, which led to unexpected declines of stoats, weasels, mice and possums. These unexpected outcomes resulted from complex indirect pathways in the food web. Fuzzy cognitive maps allow rapid construction of prototype models of complex food webs using a wide range of data and expert opinion. Their utility lies in providing direction for future monitoring efforts and generating hypotheses that can be tested with field experiments.     

采用地统计学方法对水曲柳人工纯林表层根量的估计

采用地统计学的变异函数分析方法定量研究了水曲柳纯林表层根量的空间异质性特征,利用地统计学的克里格内插法结合定积分,对水曲柳纯林表层(0～10 cm)各类型根量进行了估测。结果表明:1)水曲柳细根(<2 mm)、粗根(≥2 mm)、活根和土壤总根变异函数曲线的理论模型符合球状模型,其它植物活根符合指数模型,水曲柳及其它植物死根符合线性模型。水曲柳及其它植物死根的空间变异主要是由随机性因素引起;水曲柳细根、粗根、活根、其它植物活根和土壤总根的空间变异主要是由结构性因素引起,且空间自相关程度均属中等(空间结构比在2 5 %和75 %之间)。水曲柳粗根的空间变异尺度为13.2 m,水曲柳细根、水曲柳活根、土壤总根和其它植物活根的空间变异尺度均大于33.9m。根据理论模型的拟合参数估计,水曲柳细根、水曲柳活根和土壤总根的空间变异尺度为6 1m,其它植物活根为183m。(2 )平均值成对二样本t检验结果表明,变异函数分析结果基础上的克里格内插法适用于水曲柳样地各空间位置处各类型根量的估计。利用此估计值,拟合其与位置坐标值之间的多元回归关系均为二元十次余弦级数多项式。利用此多项式,通过定积分的方法(积分区间为整块样地的大小) ,估计出水曲柳纯林表层根量为1.5 92 6 t/ hm2 ,水曲柳细根为0 .6 86 5 t/     

Possibility Theory: A New Approach to Uncertainty Analysis? (3 pp)

Background, Aims and Scope The problem of the evaluation of practitioner's belief and belief-related uncertainties on LCA results obtained from different methodological choices has been addressed so far by scenario modeling, Cultural Theory perspectives and probabilistic simulation. The direct evaluation of belief and related uncertainties could be of interest, e.g. when the information available (resulting from classical uncertainty analysis or the application of the precautionary principle) do not allow one to choose between methodological alternatives leading to different LCA results and conclusions. The difficulty of modeling belief arises from the additive nature of classical measures, e.g. probabilities. Since the 1960s, non-additive measures (e.g. possibilities) have been developed and applied to model belief in real world problems. The aim of this paper is to discuss the application of possibility measures in LCA for uncertainty analysis in complement to classical approaches. Methods The nature and the meaning of possibilities are briefly introduced by comparison with probabilities (subjective or not) in order to enlighten strengths, drawbacks and complementarities. A tentative possibilistic approach based on the evaluation of a posteriori possibilities of final LCA results depending on a priori possibilities of the methodological choices behind the calculations is described, also by means of an application example. Results and Outlook. A new approach for the modeling of practitioner's belief and belief-related uncertainties in complement of classical methods of uncertainty analysis has been proposed for discussion. Uncertainty can be characterized by confidence intervals and indexes that could help practitioners in making methodological choices and could improve the interpretation and reliability of LCA results, still increasing its sophistication.     

Fuzzy-Sets Approach to Noise Impact Assessment (7 pp)

Background, Aims and Scope Noise impacts are rarely assessed in Life Cycle Assessment (LCA), probably due to lack of data, to the difficulty of setting up an appropriate assessment method including relevant uncertainties and vagueness and to their site-dependent nature. The evaluation, as well as for odour, cultural and aesthetic impacts, seems to be closely related to human judgements and perception based. Although fuzzy-sets have been developed for this purpose since the late '60s and their usefulness has been proven by successful applications, noise impact assessment approaches have been essentially crisp so far. The aim of this paper is to present a method for noise impact assessment based on fuzzy sets with an application to a simple example. Methods The fuzzy noise impact assessment involves: 1) the quality assessment of the site concerned by the noise impact before the occurrence of noise emissions; quality is expressed by a crisp (i.e. non-fuzzy) function depending on variables (the so-called 'primitives'), which are relevant for the evaluation (e.g. the population density, the type of land use,...); 2) the fuzzy representation of the primitives, e.g. their evaluation by means of linguistic variables (such as 'the population density is high') and by fuzzy numbers; 3) the fuzzy representation of the quality, by fuzzifying the crisp function defined in 1) and 4) the fuzzy representation of the noise impact. In the example, the noise impacts of three processes of coal mining and combustion are assessed. Results and Discussion The application example proved the operationability of the method. Primitives and noise impact assessment results are represented by fuzzy numbers and intervals that are more informative than crisp numbers for the interpretation of results The quality and impact assessment results obtained seem to be coherent with the nature of the processes involved and of the variables characterizing them. Conclusion and Outlook Fuzzy intervals and numbers could be more informative and closer to human judgements and perceptions than crisp numbers are, thus improving the pertinence and the interpretation of the results. Despite the increase in sophistication and the fact that the representation of the variables involved in calculations should be developed further (e.g. on the basis of consensus gained in an expert panel), the fuzzy approach seems to be promising for the assessment of noise impacts in LCA.     

NOTES ON THE BREEDING OF THE BOKMAKIRI

Counting Saddle-billed Storks in a study area the size of the Kruger National Park, at 2.2 million ha, is difficult because the birds are long-lived, sparse in the landscape and have large home ranges. Aerial surveys conducted to date provide an estimate with no measure of data dispersion, thence precision. The aim of this study was to estimate the population size within associated confidence limits using a modified mark–recapture field method. The vehicle survey, conducted shortly after rainfall in the area, did not produce results with known precision under these conditions. A repeat of this census in spring, after the peak breeding season and when surface water is confined to the larger rivers and dams, should yield different results. A photographic census technique yielded sufficient information to construct a population registration database. Individual identification profiles indicate that there are at least 40 adult Saddle-billed Storks in the southern part of the Kruger National Park. This is considered the minimum number of known-to-be-alive individuals in this area. In this paper, the Cormack–Jolly–Seber mark– recapture model was used to return an estimate of the population size for each capture occasion.