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Joint Modeling of Climate Niches for Adult and Juvenile Trees

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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.

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Notes

  1. A heavier than normal tail is needed which we capture through a t distribution with low d.f. We use d.f.=3 in the sequel but there is little sensitivity to this choice.

  2. More complex surfaces over climate space could be examined but, illustratively, we confine ourselves to quadratics here.

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Authors and Affiliations

  1. Department of Mathematics & Statistics, Texas Tech University, Lubbock, TX, USA

    Souparno Ghosh

  2.  Nicholas School of the Environment, Duke University, Durham, NC, USA

    Kai Zhu & James S. Clark

  3. Department of Global Ecology, Carnegie Institution for Science, Stanford, CA, USA

    Kai Zhu

  4. Department of Biology, Stanford University, Stanford, CA, USA

    Kai Zhu

  5.  Department of Statistical Science, Duke University, Durham, NC, USA

    Alan E. Gelfand

Authors
  1. Souparno Ghosh
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  2. Kai Zhu
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  3. Alan E. Gelfand
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  4. James S. Clark
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Corresponding author

Correspondence to Souparno Ghosh.

Appendix: RSMPEs for 25 Species

Appendix: RSMPEs for 25 Species

See Table 3.

Table 3 Root mean square predictive error associated with predicting seedling abundance for the joint model and the independence model.
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Ghosh, S., Zhu, K., Gelfand, A.E. et al. Joint Modeling of Climate Niches for Adult and Juvenile Trees. JABES 21, 111–130 (2016). https://doi.org/10.1007/s13253-015-0238-x

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  • DOI: https://doi.org/10.1007/s13253-015-0238-x

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