Nonparametric Threshold Model of Zero-Inflated Spatio-Temporal Data with Application to Shifts in Jellyfish Distribution

Hai Liu, Lorenzo Ciannelli, Mary Beth Decker, Carol Ladd, Kung Sik Chan

Research output: Contribution to journalArticle

13 Scopus citations

Abstract

There is increasing scientific interest in studying the spatial distribution of species abundance in relation to environmental variability. Jellyfish in particular have received considerable attention in the literature and media due to regional population increases and abrupt changes in distribution. Jellyfish distribution and abundance data, like many biological datasets, are characterized by an excess of zero counts or nonstationary processes, which hampers their analyses by standard statistical methods. Here we further develop a recently proposed statistical framework, the constrained zero-inflated generalized additive model (COZIGAM), and apply it to a spatio-temporal dataset of jellyfish biomass in the Bering Sea. Our analyses indicate systematic spatial variation in the process that causes the zero inflation. Moreover, we show strong evidence of a range expansion of jellyfish from the southeastern to the northwestern portion of the survey area beginning in 1991. The proposed methodologies could be readily applied to ecological data in which zero inflation and spatio-temporal nonstationarity are suspected, such as data describing species distribution in relation to changes of climate-driven environmental variables. Some supplemental materials including an animation of jellyfish annual biomass and web appendices are available online.

Original languageEnglish (US)
Pages (from-to)185-201
Number of pages17
JournalJournal of Agricultural, Biological, and Environmental Statistics
Volume16
Issue number2
DOIs
StatePublished - Jun 9 2011

Keywords

  • Chrysaora melanaster
  • Constraint
  • Generalized additive model
  • Habitat expansion
  • Nonstationary
  • Splines

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Environmental Science(all)
  • Agricultural and Biological Sciences (miscellaneous)
  • Applied Mathematics
  • Statistics, Probability and Uncertainty
  • Statistics and Probability

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