Modeling the distribution of four vegetation alliances using generalized linear models and classification trees with spatial dependence

By Jennifer A. Miller, Janet Franklin. 2002

275 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/947c944dbe3518c22e8a6cfea32cbf94d2a86d79

How researchers see this paper

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

In Ecological Modeling

1. Michael P. Austin
2. Ross K. Meentemeyer
3. Tomás Václavík
4. Raimundo Real
5. Jane Elith
6. Antoine Guisan
7. N. E. Zimmermann
8. J. Gégout

In Ecology

1. Michael P. Austin
2. Raimundo Real
3. Tomás Václavík
4. Ross K. Meentemeyer
5. P. Acevedo
6. N. E. Zimmermann
7. John A. Kupfer
8. Luis Cayuela

In Nature and Landscape Conservation

1. Michael P. Austin
2. Raimundo Real
3. Tomás Václavík
4. Ross K. Meentemeyer
5. Antoine Guisan
6. N. E. Zimmermann
7. John A. Kupfer
8. J. Gégout

Citations in the corpus

• Accounting for multi‐scale spatial autocorrelation improves performance of invasive species distribution modelling (iSDM) (2012, methodology): “…ranging from trend surface analysis (Lichstein et al., 2002) and autoregressive models (Santika & Hutchinson, 2009) to geostatistical methods (Miller & Franklin, 2002; Miller, 2005) and geographically weighted regression (Kupfer & Farris, 2007), have recently experienced a surge in…”
• Past, present and future of wild ungulates in relation to changes in land use (2010, methodology): “As spatially proximate objects are often more likely to exhibit similar attributes (Miller and Franklin 2002), we used a Markov and cellular automata (CA–Markov) approach to incorporate neighbouring states and improve model predictions of complex natural patterns (Deadman and Brown 1993).”
• Soil nutritional factors improve models of plant species distribution: an illustration with Acer campestre (L.) in France (2006, methodology): “In this study, indicator kriging was used on the observed presence/absence data from the evaluation set (see also Miller & Franklin, 2002; Marinoni, 2003; Bayliss et al., 2005).”
• Spatial interpolation of monthly climate data for Finland: comparing the performance of kriging and generalized additive models (2013, background): “Spatially and temporally continuous gridded datasets are important in many applications such as in agriculture, water resources, soil sciences, and ecological studies (Clifton and Neuman 1982; Robertson 1987; Goovaerts 1999; Miller and Franklin 2002; Liu et al. 2006).”
• Species distribution models and ecological theory: A critical assessment and some possible new approaches (2007, background): “…1995; Guisan and Zimmermann, 2000; Austin, 2002a; Huston, 2002), numerous methodological comparisons (e.g. Bio et al., 1998; Manel et al., 1999; Miller and Franklin, 2002; Moisen and Frescino, 2002; Munoz and Felicisimo, 2004; Thuiller, 2003; Segurado and Araujo, 2004) and several commentaries…”
• Agricultural land abandonment and natural forest re-growth in the Swiss mountains: A spatially explicit economic analysis (2007, methodology): “A logistic regression model that includes such a neighbourhood term is formally called an autologistic model ( Miller and Franklin, 2002 ).”
• Species Distribution Modeling in the Tropics: Problems, Potentialities, and the Role of Biological Data for Effective Species Conservation (2009, methodology): “This research was initiated in a working group at Managua, Nicaragua.”