COMPETITIVE INTERACTIONS BETWEEN TREE SPECIES IN NEW ZEALAND'S OLD‐GROWTH INDIGENOUS FORESTS

By J. Leathwick, Michael P. Austin. 2001

248 citations recorded by the source corpus.

Subfields: Ecology, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/83f3668cfea3f92f184230d58e595047e9b24e26

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In Ecology

In Nature and Landscape Conservation

Citations in the corpus

Species Distribution Models: Ecological Explanation and Prediction Across Space and Time (2009, unknown): “SDMs are still regularly used for such purposes, particularly in quantitative ecological studies (Leathwick & Austin 2001) and evolutionary biology (Graham et al. 2004b).”
Species distribution models and ecological theory: A critical assessment and some possible new approaches (2007, methodology): “The different ecophysiological assumptions currently influencing selection of environmental predictors (Austin and Smith, 1989; Huntley et al., 1995; Leathwick and Whitehead, 2001; Huston, 2002) need to be justified in more detail, e.g. Bloom et al. (1985) and Rubio et al. (2003).”
Novel methods improve prediction of species' distributions from occurrence data (2006, unknown): “Modelling approaches which attempt to integrate such information include Bayesian approaches (Gelfand et al. 2006), investigation of competitors (Leathwick and Austin 2001, Anderson et al. 2002), and studies of connectivity (Ferrier et al. 2002a, Moilanen et al. 2005).”
Predicting reptile distributions at the mesoscale: relation to climate and topography (2003, background): “Sometimes, ecological 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 &…”
Error and uncertainty in habitat models (2006, background): “For example, the limit of distribution of a plant at some point in environmental space may be determined by physiological responses to environment, but these responses are likely to be influenced, perhaps strongly, by interactions with other species ( Leathwick & Austin 2001 ).”
Effects of restricting environmental range of data to project current and future species distributions (2004, background): “…is because modelled species’ realised niches capture many factors other than species limits of tolerance to environmental variables (e.g. competition and historical contingency, Araújo et al. 2001, Leathwick and Austin 2001) and these factors are not easily predictable (Loehle and LeBlanc 1996).”
Importance of abiotic stress as a range‐limit determinant for European plants: insights from species responses to climatic gradients (2009, background): “Hence, even though competitive exclusion arising from species-specific interactions is sometimes considered unimportant at large geographical scales (Pearson & Dawson, 2003; but see Leathwick & Austin, 2001), it may still play an important role when climate favours one life-form over another.”
Can biotic interactions cause allopatry? Niche models, competition, and distributions of South American mouse opossums (2014, background): “…Wiens 2009), causing extinctions (Mooney and Cleland 2001, Banks et al. 2008), and shaping both species ’ distributional ranges (Bullock et al. 2000, Leathwick and Austin 2001, Leathwick 2002, Arif et al. 2007, Wisz et al. 2008; but see Giff ord and Kozak 2012) and the composition of communities…”
Understanding co‐occurrence by modelling species simultaneously with a Joint Species Distribution Model (JSDM) (2014, background): “…interactions by restricting the predicted distribution of one species to that of another (Schweiger et al. 2012) or by adding the occurrence or abundance of other species as predictors alongside abiotic variables (Leathwick & Austin 2001; Leathwick 2002; Meier et al. 2010; Pellissier et al. 2010).”
How biotic interactions may alter future predictions of species distributions: future threats to the persistence of the arctic fox in Fennoscandia (2012, background): “It has already been shown that introducing species interactions in SDMs can considerably alter the output of such models (Leathwick & Austin, 2001; Anderson et al., 2002; Araújo & Luoto, 2007; Meier et al., 2011).”
Making better biogeographical predictions of species’ distributions (2006, background): “Such interactions can be addressed by adding one or more biotic predictors to the model formula alongside the environmental predictors (Leathwick & Austin 2001).”
A comprehensive evaluation of predictive performance of 33 species distribution models at species and community levels (2019, background): “…Article e01370; page 5 interspecific associations even in the context of singlespecies SDMs by using the occurrences of some species as predictors (Leathwick and Austin 2001, Meentemeyer et al. 2001, Stephens and MacCall 2004, Ara ujo and Luoto 2007, Pellissier et al. 2010, Meier et al. 2011,…”
Comparative performance of generalized additive models and multivariate adaptive regression splines for statistical modelling of species distributions (2006, methodology): “e c o l o g i c a l m o d e l l i n g 1 9 9 ( 2 0 0 6 ) 188–196 avai lab le at www.sc iencedi rec t .com journa l homepage: www.e lsev ier .com/ locate /eco lmodel Comparative performance of generalized additive models and multivariate adaptive regression splines for statistical modelling of species”