Journal article
Nonparametric Threshold Model of Zero-Inflated Spatio-Temporal Data with Application to Shifts in Jellyfish Distribution
Journal of Agricultural, Biological, and Environmental Statistics, Vol.16(2), pp.185-201
06/2011
DOI: 10.1007/s13253-010-0044-4
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.
Details
- Title: Subtitle
- Nonparametric Threshold Model of Zero-Inflated Spatio-Temporal Data with Application to Shifts in Jellyfish Distribution
- Creators
- Hai Liu - Division of Biostatistics Indiana University School of Medicine Indianapolis IN 46202 USALorenzo Ciannelli - College of Oceanic and Atmospheric Sciences Oregon State University Corvallis OR 97331 USAMary Decker - Department of Ecology and Evolutionary Biology Yale University New Haven CT 06520 USACarol Ladd - Pacific Marine Environmental Laboratory NOAA Seattle WA 98115 USAKung-Sik Chan - Department of Statistics and Actuarial Science University of Iowa Iowa City IA 52242 USA
- Resource Type
- Journal article
- Publication Details
- Journal of Agricultural, Biological, and Environmental Statistics, Vol.16(2), pp.185-201
- Publisher
- Springer-Verlag; New York
- DOI
- 10.1007/s13253-010-0044-4
- ISSN
- 1085-7117
- eISSN
- 1537-2693
- Language
- English
- Date published
- 06/2011
- Academic Unit
- Statistics and Actuarial Science; Radiology
- Record Identifier
- 9983985938802771
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