Lognormality in ecological time series
Φόρτωση...
Ημερομηνία
Συγγραφείς
Halley, John
Inchausti, Pablo
Τίτλος Εφημερίδας
Περιοδικό ISSN
Τίτλος τόμου
Εκδότης
Munksgaard International Publishers
Περίληψη
Τύπος
Είδος δημοσίευσης σε συνέδριο
Είδος περιοδικού
peer reviewed
Είδος εκπαιδευτικού υλικού
Όνομα συνεδρίου
Όνομα περιοδικού
Oikos
Όνομα βιβλίου
Σειρά βιβλίου
Έκδοση βιβλίου
Συμπληρωματικός/δευτερεύων τίτλος
Περιγραφή
Among ecologists, it is often believed that population abundance is lognormally distributed. To test this hypothesis, we analysed and compared 544 annual time-series of population abundance longer than 30 years (nβ ₯30). Using Khamis" modified KS test we found one-half of the long-term datasets were lognormally distributed (p-value=0.05). Among those deviating from lognormality, the most consistent feature was that the skewness was less than that expected under the lognormal hypothesis, implying a shorter upper tail (i.e. fewer extremely high values) than expected. There was little evidence of systematic extreme heavy-tail behaviour characteristic of the LΓ©vy-stable distributions in long (nβ ₯50 years) time series. Both the standard KS test and the Akaike information criterion (AIC) were used to compare a number of alternative distributions for goodness of fit. Distributions symmetric in logarithmic scale (lognormal and log-sech) were found to fit the data best according to the KS test. However, by the AIC the gamma distribution was most often the best model. Numbers of significant departures from lognormality varied among taxa, with insects having the highest departure from lognormality. There were also trophic differences, with herbivores deviating from lognormality more than carnivores. We found no habitat or geographic dependencies in the incidence of lognormality. The poor fit of the lognormal to real data means that it is not a good substitute for specific population dynamic and distributional information. However, being a superior " universal" descriptor of population abundance than other two-parameter models, it may be useful in applications where such detailed information is unavailable.
Περιγραφή
Λέξεις-κλειδιά
Θεματική κατηγορία
Παραπομπή
Σύνδεσμος
http://dx.doi.org/10.1034/j.1600-0706.2002.11962.x
Γλώσσα
en
Εκδίδον τμήμα/τομέας
Όνομα επιβλέποντος
Εξεταστική επιτροπή
Γενική Περιγραφή / Σχόλια
Ίδρυμα και Σχολή/Τμήμα του υποβάλλοντος
Πανεπιστήμιο Ιωαννίνων. Σχολή Επιστημών και Τεχνολογιών. Τμήμα Βιολογικών Εφαρμογών και Τεχνολογιών