Towards novel approaches to modelling biotic interactions in multispecies assemblages at large spatial extents

By Werner Kissling, Carsten F. Dormann, J. Groeneveld, Thomas Hickler, I. Kühn, Greg J. McInerny, J. M. Montoya, Christine Römermann, K. Schiffers, Frank M. Schurr and 4 more. 2012

442 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/2c1cbd81508c257902e596a286e93d06d666c1bf

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In Ecological Modeling

In Ecology, Evolution, Behavior and Systematics

In Nature and Landscape Conservation

Citations in the corpus

Will remote sensing shape the next generation of species distribution models? (2015, background): “Bradley et al. (2012) indeed caution that the use of NDVI metrics in plant models could create biases in cases where they measure properties of the target species directly.”
Mechanistic and Correlative Models of Ecological Niches (2015, background): “Such an ideal case has not, to our knowledge, been developed fully, although a few studies have linked multiple pieces of this complicated puzzle (Dormann et al. 2012; Kissling et al. 2012; Marion et al. 2012; Barve et al. 2014).”
Using joint species distribution models for evaluating how species‐to‐species associations depend on the environmental context (2017, background): “While there is a large body of statistical literature on how to predict species’ distributions based on abiotic variation (Elith & Leathwick 2009), the inclusion of interspecific interactions into species distribution modelling frameworks has been rather recent (Boulangeat, Gravel & Thuiller 2012; K”
Joint dynamic species distribution models: a tool for community ordination and spatio‐temporal monitoring (2016, background): “However, we envision the need for substantial dimen-sion reduction when estimating a species interaction matrix within a large community (Kissling et al ., 2012).”
Understanding co‐occurrence by modelling species simultaneously with a Joint Species Distribution Model (JSDM) (2014, methodology): “However, adding species as predictors assumes unidirectional interactions and induces multicollinearity within amodel when the distribution of a predictor species is governed by similar abiotic variables (Kissling et al. 2012).”