Extinction trends of threatened invertebrates in peninsular Spain

Using information from two recently published atlases of threatened invertebrate species in peninsular Spain, we examined the climatic, land use and geographic characteristics of the 100 km2 UTM cells with most likelihood of suffering extinctions (extinction cells), as well as the attributes of the species prone to population extinctions. Extinction cells have had significantly (1) lower precipitation values, (2) higher temperatures, (3) higher percentages of anthropic land uses or (4) higher rates of anthropization during the last 20 years than the remaining cells. Nevertheless, probable extinctions may occur under a wide range of climatic and anthropization change rates and these variables can only explain a low proportion (~5 %) of variability in the occurrence or number of extinction cells. Aquatic species seem to suffer higher local extinction rates than terrestrial species. Interestingly, many invertebrate species with approximately 25 or less occurrence cells are on a clear trajectory towards extinction. These results outline the difficulties and uncertainties in relating probable population extinctions with climatic and land use changes in the case of invertebrate data. However, they also suggest that a third of the considered Spanish threatened species could have lost some of their populations, and that current conservation efforts are insufficient to reverse this tendency.

Evolution of the last koninckinids (Athyridida, Koninckinidae), a precursor signal of the early Toarcian mass extinction event in the Western Tethys

Koninckinids are a suitable group to shed light on the biotic crisis suffered by brachiopod fauna in the Early Jurassic. Koninckinid fauna recorded in the late Pliensbachian–early Toarcian from the easternmost Subbetic basin is analyzed and identified as a precursor signal for one of the most conspicuous mass extinction events of the Phylum Brachiopoda, a multi-phased interval with episodes of changing environmental conditions, whose onset can be detected from the Elisa–Mirabile subzones up to the early Toarcian extinction boundary in the lowermost Serpentinum Zone (T-OAE). The koninckinid fauna had a previously well-established migration pattern from the intra-Tethyan to the NW-European basins but a first phase with a progressive warming episode in the Pliensbachian–Toarcian transition triggered a koninckinid fauna exodus from the eastern/central Tethys toward the westernmost Mediterranean margins. A second stage shows an adaptive response to more adverse conditions in the westernmost Tethyan margins and finally, an escape and extinction phase is detected in the Atlantic areas from the mid-Polymorphum Zone onwards up to their global extinction in the lowermost Serpentinum Zone. This migration pattern is independent of the paleogeographic bioprovinciality and is unrelated to a facies-controlled pattern. The anoxic/suboxic environmental conditions should only be considered as a minor factor of partial control since well-oxygenated habitats are noted in the intra-Tethyan basins and this factor is noticeable only in the second westward migratory stage (with dwarf taxa and oligotypical assemblages). The analysis of cold-seep proxies in the Subbetic deposits suggests a radiation that is independent of methane releases in the Subbetic basin.

An adaptive algorithm for clustering cumulative probability distribution functions using the Kolmogorov–Smirnov two-sample test

This paper proposes an adaptive algorithm for clustering cumulative probability distribution functions (c.p.d.f.) of a continuous random variable, observed in different populations, into the minimum homogeneous clusters, making no parametric assumptions about the c.p.d.f.’s. The distance function for clustering c.p.d.f.’s that is proposed is based on the Kolmogorov–Smirnov two sample statistic. This test is able to detect differences in position, dispersion or shape of the c.p.d.f.’s. In our context, this statistic allows us to cluster the recorded data with a homogeneity criterion based on the whole distribution of each data set, and to decide whether it is necessary to add more clusters or not. In this sense, the proposed algorithm is adaptive as it automatically increases the number of clusters only as necessary; therefore, there is no need to fix in advance the number of clusters. The output of the algorithm are the common c.p.d.f. of all observed data in the cluster (the centroid) and, for each cluster, the Kolmogorov–Smirnov statistic between the centroid and the most distant c.p.d.f. The proposed algorithm has been used for a large data set of solar global irradiation spectra distributions. The results obtained enable to reduce all the information of more than 270,000 c.p.d.f.’s in only 6 different clusters that correspond to 6 different c.p.d.f.’s.

Cartels: the Probability of Getting Caught in the European Union. Bruges European Economic Research (BEER) Papers 12/March 2008

In 1991, Bryant and Eckard estimated the annual probability that a cartel would be detected by the US Federal authorities, conditional on being detected, to be at most between 13 % and 17 %. 15 years later, we estimated the same probability over a European sample and we found an annual probability that falls between 12.9 % and 13.3 %. We also develop a detection model to clarify this probability. Our estimate is based on detection durations, calculated from data reported for all the cartels convicted by the European Commission from 1969 to the present date, and a statistical birth and death process model describing the onset and detection of cartels.

Considering DPRK [North Korea] Regime Collapse: Its Probability and Possible Geopolitical and Security Consequences. Security Policy Brief No. 66, August 2015

Both the EU and its member states are in a period of rethinking security strategy to adapt to contemporary challenges both in the European region and beyond, including Northeast Asia. In this Security Policy Brief, Mason Richey discusses what difficulties and risks a North Korean regime collapse would pose, the likelihood that it will occur sooner rather than later, and how Europe will be affected by such a scenario.

RRREG: Stata module to estimate linear probability model for randomized response data

rrreg fits a linear probability model for randomized response data

Testing the validity of the lognormal probability model : computer analysis of carbon monoxide data from U.S. cities /

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