{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,3,31]],"date-time":"2022-03-31T02:10:52Z","timestamp":1648692652934},"reference-count":26,"publisher":"World Scientific Pub Co Pte Lt","issue":"07n08","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Advs. Complex Syst."],"published-print":{"date-parts":[[2015,11]]},"abstract":"<jats:p> Long range dependence or long memory is a feature of many processes in the natural world, which provides important insights on the underlying mechanisms that generate the observed data. The usual tools available to characterize the phenomenon are mostly based on second-order correlations. However, the long memory effects may not be evident at the level of second-order correlations and may require a deeper analysis of the nature of the stochastic processes. <\/jats:p><jats:p> After a short review of the notions and tools used to characterize long range dependence, we analyze data related to the abundance of exploited fish populations which provides an example of higher order long range dependence. In particular, we find that fish population time series were thought to have short term memory only because previous studies used averages over species instead of modeling each species individually. <\/jats:p>","DOI":"10.1142\/s0219525915500174","type":"journal-article","created":{"date-parts":[[2015,8,31]],"date-time":"2015-08-31T07:47:22Z","timestamp":1441007242000},"page":"1550017","source":"Crossref","is-referenced-by-count":1,"title":["LONG RANGE DEPENDENCE AND THE DYNAMICS OF EXPLOITED FISH POPULATIONS"],"prefix":"10.1142","volume":"18","author":[{"given":"HUGO C.","family":"MENDES","sequence":"first","affiliation":[{"name":"Instituto Portugu\u00eas do Mar e da Atmosfera, Avenida Bras\u00edlia, 1300-598 Lisboa, Portugal"}]},{"given":"ALBERTO","family":"MURTA","sequence":"additional","affiliation":[{"name":"Instituto Portugu\u00eas do Mar e da Atmosfera, Avenida Bras\u00edlia, 1300-598 Lisboa, Portugal"}]},{"given":"R. VILELA","family":"MENDES","sequence":"additional","affiliation":[{"name":"CMAF and IPFN, University Lisbon, Av. 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