Soil and atmospheric water deficits and the distribution of New Zealand's indigenous tree species

By J. Leathwick, D. Whitehead. 2001

84 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/3412dc3b4092c85c259ea89038d620b0541733c0

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atmospheric Science

1. Anthony Lehmann
2. J. Overton
3. Jane Elith
4. Antoine Guisan
5. N. E. Zimmermann
6. J. Leathwick

In Global and Planetary Change

1. Anthony Lehmann
2. Antoine Guisan
3. J. Overton
4. N. E. Zimmermann
5. Mark P. Robertson
6. A. R. Palmer
7. M. Villet
8. R. Maggini

In Nature and Landscape Conservation

1. Antoine Guisan
2. Jane Elith
3. J. Leathwick
4. Miguel B. Araújo
5. Wilfried Thuiller
6. N. E. Zimmermann
7. A. Townsend Peterson
8. Rune Halvorsen

Citations in the corpus

• Error and uncertainty in habitat models (2006, background): “models should be constrained to be congruent with ecological knowledge, with successive improvement in model specification that is driven by increasing knowledge of the ecology of the system ( Leathwick & Whitehead 2001 ).”
• Species Distribution Models: Ecological Explanation and Prediction Across Space and Time (2009, unknown): “Predictions show patterned residuals when variables are inadequate, and can be improved substantially by using more proximal predictors (Leathwick & Whitehead 2001), and small data sets and model selection difficulties mean that models can select irrelevant variables (Mac Nally 2000, Steyerberg et…”
• GRASP: generalized regression analysis and spatial prediction (2002, methodology): “Derived predictors more directly related to forest plant physiology and ecology were then calculated as described in Leathwick and Whitehead (2001) , Leathwick and Austin (2001)).”
• Improving generalized regression analysis for the spatial prediction of forest communities (2006, background): “Journal compilation ª 2006 Blackwell Publishing Ltd by Leathwick & Whitehead (2001), this predictor is a measure of water stress for trees, and hence represents an important limiting factor for their distribution and survival.”
• A fuzzy classification technique for predicting species’ distributions: applications using invasive alien plants and indigenous insects (2004, background): “Currently, the most popular of these appear to be Generalized Linear Models (GLM; Austin et al, 1984; McCullagh & Nelder, 1989; Austin et al ., 1990; Austin et al ., 1994; Ferrier & Watson, 1997; Guisan et al ., 1998; Pearce & Ferrier, 2000) and Generalized Additive Models (GAM; Austin & Meyers, 199”