Joint Modeling of Climate Niches for Adult and Juvenile Trees

Souparno Ghosh (), Kai Zhu (), Alan E. Gelfand () and James S. Clark ()
Additional contact information
Souparno Ghosh: Texas Tech University
Kai Zhu: Duke University
Alan E. Gelfand: Duke University
James S. Clark: Duke University

Journal of Agricultural, Biological and Environmental Statistics, 2016, vol. 21, issue 1, No 7, 130 pages

Abstract: Abstract Typical ecological gradient analysis for plant species considers variation in the response along a gradient of covariate values, for example, temperature or precipitation. Response is customarily modeled through the presence/absence or a suitable measure of abundance or both. Such analysis enables the creation of a climate niche or range limits for the species using this covariate. Interest often extends to two climate covariates, thus seeking a climate niche in two-dimensional space. It also seeks to learn whether the niche changes over life stages of the species. For instance, is the niche for juveniles different from that for adults? Across the climate domain, where are seedlings relatively more or less abundant than adults? Adult abundance is measured through basal area, juvenile abundance through seedling counts. Our contribution is to describe a coherent modeling approach to address the foregoing objectives. We construct a hierarchical stochastic specification that jointly models juveniles and adults with regard to their two-dimensional climate niches. Joint modeling of the abundance response surfaces is proposed because seedlings and adults are living jointly, competitively and is justified through exploratory analysis. Joint modeling can be challenging when one response is counts and the other is area. We model adult abundance and then juvenile abundance driven by adult abundance. Due to excess zeroes over our study plots, we employ zero-inflated models for both adult and seedling abundance. We demonstrate the benefits of the joint modeling through out-of-sample predictive performance. Our abundance data come from the USDA Forest Service’s Forest Inventory and Analysis dataset. Our climate data come from the 800 m resolution Parameter-elevation Regressions on Independent Slopes Model dataset. In order to extract a response to climate, we aggregate FIA plots to ecological subsections. At plot scale, micro-scale covariates explain variation in abundance; at a larger spatial scale, climate covariates can explain variation in abundance.

Keywords: Abundance; Basal area; Hierarchical model; Mean annual precipitation; Mean winter temperature; Zero-inflated models (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s13253-015-0238-x Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:jagbes:v:21:y:2016:i:1:d:10.1007_s13253-015-0238-x

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/13253

DOI: 10.1007/s13253-015-0238-x

Access Statistics for this article

Journal of Agricultural, Biological and Environmental Statistics is currently edited by Stephen Buckland

More articles in Journal of Agricultural, Biological and Environmental Statistics from Springer, The International Biometric Society, American Statistical Association
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().