Continuum theory revisited: what shape are species responses along ecological gradients?

By Jari Oksanen, P. Minchin. 2002

375 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Evolution, Behavior and Systematics, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/17f69526182790748e69ee680e7f04246b8eb5de

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Citations in the corpus

Distribution patterns of tropical woody species in response to climatic and edaphic gradients (2012, background): “Species response curves should differ in shape, amplitude, width and optimum (Huisman, Olff & Fresco 1993; Austin & Gaywood 1994; Jongman, ter Braak & van Tongeren 1995; Oksanen & Minchin 2002).”
Generalized models vs. classification tree analysis: Predicting spatial distributions of plant species at different scales (2003, methodology): “A strong feature is that GAM is non-parametric and can take any smooth shape (Oksanen & Minchin 2002).”
DIRECT MULTI‐SCALE ORDINATION WITH CANONICAL CORRESPONDENCE ANALYSIS (2004, methodology): “However, CA is not necessarily the best method for analyzing nonlinear relationships, as it has been shown that species response curves may often be asymmetric (Oksanen and Minchin 2002).”
Effects of restricting environmental range of data to project current and future species distributions (2004, background): “Since statistical models can fit extreme zeros reasonably, others authors argued that such restrictions are unnecessary and may lead to ecologically unrealistic response curves (Oksanen and Minchin 2002).”
Importance of abiotic stress as a range‐limit determinant for European plants: insights from species responses to climatic gradients (2009, methodology): “Generally, the largest fraction of the truncated responses consisted of continuously increasing curves (HOF II and III), while a smaller fraction was symmetric or skewed (Fig.”
Spatial prediction of species distribution: an interface between ecological theory and statistical modelling (2002, background): “See the papers by Oksanen (1997), Austin and Nicholls (1997), Oksanen and Minchin (2002) for a recent example of a debate over theory and data models concerning the shape of species response curves.”
A strict maximum likelihood explanation of MaxEnt, and some implications for distribution modelling (2013, methodology): “…curves (Oksanen & Minchin 2002, Rydgren et al. 2003), e.g., obtained by the HOF (Huisman-Olff-Fresco) modelling framework (Huisman et al. 1993, Oksanen & Minchin 2002), indicates that a function with four parameters (four degrees of freedom) is generally sufficient to capture generalisable…”
Changes to the elevational limits and extent of species ranges associated with climate change. (2005, methodology): “To test the validity of results based on unimodal logistic regression models, species elevational distributions were also fitted to Huisman–Olff–Fresco (HOF) models (Huisman et al. 1993; Oksanen & Minchin 2002).”
Predicting reptile distributions at the mesoscale: relation to climate and topography (2003, background): “…theories can even be suggested or evaluated from combining different models (e.g. on competition; Leathwick & Austin, 2001; Anderson et al., 2002; Austin, 2002), or an ecological hypothesis can be verified by testing the shape of the ecological response curves (e.g. Oksanen & Minchin, 2002).”
Techniques for cetacean-habitat modeling (2006, background): “Linear relationships, effectively representing simple direct or indirect resource selection along a habitat gradient, are considered rare or unlikely (Austin 2002, Oksanen & Minchin 2002).”
The effect of species response form on species distribution model prediction and inference (2009, background): “…Beta species response to an environmental variable can be modelled using the following function (Austin, 1976; Minchin, 1987; Austin et al., 1994; Oksanen and Minchin, 2002): H.betasmij = csm(gsmij − k1sm)˛sm (k2sm − gsmij) sm (3) where H.betasmij represents the Beta habitat suitability score of…”