1,721,207 research outputs found
A statistical method for idiographic analyses in biogeographical research
No full textIdiographic analyses (i.e. detailed analyses of single species ranges) can be criticized for subjective and speculative reasoning. Medoid partition is suggested here as a method to perform a statistically supported idiographic analysis. The medoid algorithms attempt to group objects into clusters by finding a set of representative objects called medoids. If areas are the objects that are clustered using species occurrences (0/1) as variables, each cluster will be characterized by a medoid area. The species that characterize each medoid are representative of the entire cluster to which the medoid belongs and can be regarded as (statistically supported) species `characteristic' of the main distributional patterns observed in the study system and can be used to draw idiographic observations. To illustrate the issues involved, the Coleoptera Tenebrionidae of the Aegean Islands (Greece) were analysed. Two species appeared to be characteristic of the Balkan cluster, while eight species were characteristic of the Anatolian one, and two species were equally distributed in both areas. Idiographic considerations based on these species outlined the importance of a Balkano-Anatolian discontinuity in the Aegean that prevented species dispersal between the two landmasses. This study illustrates that medoid analysis may help the researcher to find some representative patterns from a puzzling distribution. Traditional idiographic analyses can be biased by the fact that species are selected ad hoc. Thus, one cannot establish if results are truly objective or if the author intentionally selected, from a wider array of species, those that supported some preferred patterns. Medoid clustering uses the full array of species to find clusters of areas. After clusters are objectively defined, their medoids are examined to find species that mostly contributed to cluster definition, and the distribution patterns of these species are interpreted
Book review. Species Conservation. Lessons From Islands, edited by Jamieson A. Copsey, Simon A. Black, J. J. Groombridge and Carl G. Jones 2018. Cambridge University Press.
Full text linkA simple method to fit geometric series and broken stick models in community ecology and island biogeography
No full textSpecies abundance distributions are widely used in explaining natural communities. their natural evolution and the impacts of environmental disturbance. A commonly used approach is that of rank-abundance distributions. Favored, biologically founded models are the geometric series (GS) and the broken stick (BS) model. Comparing observed abundance distributions with those predicted by models is an extremely time-consuming task. Also, using goodness-of-fit tests for frequency distributions (like Chi-square or Kolmogorov-Smirnov tests) to compare observed with expected frequencies is problematic because the best way to calculate expected frequencies may be controversial. More important, the Chi-square test may prove if an observed distribution statistically differs from a model, but does not allow the investigator to choose among competing models from which the observed distribution does not differ. Both models can be easily tested by regression analysis. In GS, if a log scale is used for abundance, the species exactly fall along a straight line. The BS distribution shows tip as nearly linear when a log scale is used for the rank axis. Regression analysis is proposed here as a simpler and more efficient method to fit the GS and BS models. Also, regression analysis (1) does not suffer from assumptions related to Chi-square tests; (2) obviates the need to establish expected frequencies, and (3) offers the possibility to choose the best fit among competing models. A possible extension of abundance-rank analysis to species richness on islands is also proposed as a method to discriminate between relict and equilibrial models. Examples of application to field data are also presented. (c) 2005 Elsevier SAS. All rights reserved
Faunal patterns in tenebrionids (Coleoptera: Tenebrionidae) on the Tuscan Islands: The dominance of paleogeography over Recent geography
No full textThe tenebrionid fauna of the Tuscan Islands (Central Italy) is well known and is an ideal system for studying the role of current and historical factors in determining the biogeographical patterns in a complex archipelago. Cluster analyses, species-area relationships and Mantel tests were used to investigate the influence of current geography and Pleistocene connections with the mainland on the structure of insular communities. Current biogeographical similarity patterns fit both Pleistocene and Recent geography, but marked effects of Pleistocene geography appeared when the influence of Recent geography was removed. Thus, in contrast to more mobile insects, such as butterflies and chrysidids, tenebrionid colonization is likely to have occurred via land-bridges when the islands were connected to the mainland in the Pleistocene. The relict distributions of organisms with poor mobility should be of great concern to conservationists, because depletion of island populations cannot be balanced by new immigrations from mainland populations. The continued influence of man on the Tuscan Islands has adversely affected the natural environment, however, man made habitats may also be colonized and exploited by tenebrionids
Biogeography of tenebrionid beetles (Coleoptera: Tenebrionidae) in the circum-Sicilian islands (Italy, Sicily): Multiple biogeographical patterns require multiple explanations
No full textThe tenebrionid beetles on 25 circum-Sicilian islands were studied to determine the influence of island geographical and landscape features on three main intercorrelated biogeographical patterns: (1) species richness, studied using species-area and species environment relationships, (2) species assemblage composition, investigated using Canonical Correspondence Analysis (CCA), and (3) inter-site faunal similarity, investigated using Canonical Correlation Analysis (CANCOR) applied to multidimensional scaling of inter-island faunal dissimilarities. Species richness was mostly influenced by island area and landscape heterogeneity (expressed using various indices of diversity based on land cover categories). When species identities were considered in the CCA, no substantial effect of landscape was detected. Current island isolation did not have a strong influence on species richness, but has a distinct effect in determining species assortments on the remotest islands. Historical influences of Pleistocene landbridge connections were not detectable in species richness relationships using geographical variables in species richness analyses or in assemblage gradients in the CCA, but emerged distinctly from inter-island similarities in the CANCOR
Book Review Wildlife Habitat Conservation: Concepts, Challenges, and Solutions, Michael Morrison, Heather Mathewson (Eds.). Johns Hopkins University Press and The Wildlife Society (2015), ISBN: 978-1-4214-1610-6, 185 pp., $75.00 (hardcover)
No full textBook review. Biogeography: An ecological and evolutionary approach, eighth ed., C. Barry Cox, Peter D. Moore. John Wiley & Sons, Inc., Hoboken, NJ (2010). 498 pp., Paperback, Price £36.99/€44.40, ISBN: 978-0-470-63794-4
No full textTesting the latitudinal gradient: a narrow-scale analysis of tenebrionid richness (Coleoptera, Tenebrionidae) in the Aegean archipelago (Greece)
No full textThe latitudinal pattern of tenebrionid (Coleoptera Tenebrionidae) biodiversity on the Aegean Islands (Greece) was analysed. To remove the obvious influence of area on species richness, several species-area relationships, including power, exponential, negative exponential, logistic, Gompertz, Weibull, Lomolino, and He-Legendre functions, were applied. Residuals were retained as measures of species richness corrected for area. The power function model appeared to be the most convenient one. Species richness was not statistically related to latitude. However, when the confounding effect of area was removed, tenebrionid species richness and levels of endemism increased significantly at lower latitudes. This latitudinal pattern can be explained both as a consequence of increasing mean annual temperatures at lower latitudes (favouring thermophilic species) and as a reflection of the role in speciation played by southern areas during Tertiary land evolution and Pleistocene eco-geographic conditions
A multidimensional characterization of rarity applied to the Aegean tenebrionid beetles (Coleoptera Tenebrionidae)
No full textThis paper attempts to use museum collection data to estimate measures of species rarity and then to relate these measures to extinction risk. For this purpose, 170 taxa (138 species and 32 subspecies) of tenebrionid beetles from 32 Aegean Islands (Greece) were considered. For each taxon, rarity was evaluated as geographic distribution (mean incidence on islands in the archipelago), potential habitat exploitation (total area of the islands occupied on the total area of the study system) and contactability (number of decades of taxon's records on the total number of decades of assumed persistence from 1870 to 2000). All of these indices were correlated to each other. Whether expressed in terms of range size or habitat exploitation rarity was a major determinant of a species' risk of extinction (evaluated as extinction decade). Thus, the designation of rarity provides a good basis for identifying species that are most in need of conservation at a particular scale
Detecting biodiversity hotspots by species-area relationships: a case study of Mediterranean beetles
No full textAny method of identifying hotspots should take into account the effect of area on species richness. I examined the importance of the species-area relationship in determining tenebrionid (Coleoptera: Tenebrionidae) hotspots on the Aegean Islands (Greece). Thirty-two islands and 170 taxa (species and subspecies) were included in this study. I tested several species-area relationship models with linear and nonlinear regressions, including power exponential, negative exponential, logistic, Gompertz, Weibull, Lomolino, and He-Legendre functions. Islands with positive residuals were identified as hotspots. I also analyzed the values of the C parameter of the power function and the simple species-area ratios. Species richness was significantly correlated with island area for all models. The power function model was the most convenient one, Most functions, however, identified certain islands as hotspots. The importance of endemics in insular biotas should be evaluated carefully because they are of high conservation concern. The simple use of the species-area relationship can be problematic when areas with no endemics are included. Therefore the importance of endemics should be evaluated according to different methods, such as percentages, to take into account different levels of endemism and different kinds of ``endemics'' (e.g., endemic to single islands vs. endemic to the archipelago). Because the species-area relationship is a key pattern in ecology, my findings can be applied at broader scales
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