Spatial modelling of biodiversity at the community level

By Simon Ferrier, Antoine Guisan. 2006

759 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/adeb8eedcda76638cc953d8f21c9f627a3a1d15a

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

In Ecology

In Nature and Landscape Conservation

Citations in the corpus

Community ecology in the age of multivariate multiscale spatial analysis (2012, methodology): “…explicit methods have recently been developed and diversified (e.g., Borcard et al. 1992, Borcard and Legendre 2002, Wagner 2004, Dray et al. 2006, Ferrier and Guisan 2006, Lichstein 2007, Soininen et al. 2007, Blanchet et al. 2008a), we aim to highlight here how they can be used to address the…”
Species Distribution Models: Ecological Explanation and Prediction Across Space and Time (2009, neutral): “We include these, but exclude models that are mechanistic or process-based (see Kearney & Porter 2009 for a review), or that predict community-level features such as community composition and species turnover or richness (see Ferrier & Guisan 2006 for a review).”
Predicting spatial patterns of plant species richness: a comparison of direct macroecological and species stacking modelling approaches (2011, methodology): “As proposed by Guisan & Rahbek (2011) (see also Ferrier & Guisan, 2006; Fig.”
Testing species assemblage predictions from stacked and joint species distribution models (2019, background): “How we could predict local community richness and composition still remains a challenge even though different model‐ ling frameworks have been proposed (D'Amen et al., 2017; Ferrier & Guisan, 2006).”
A comprehensive evaluation of predictive performance of 33 species distribution models at species and community levels (2019, background): “…the 33 SDM variants as stacked species distribution models (SSDM; Dubuis et al. 2011, Guisan and Rahbek 2011), since they essentially model species individually and then stack the model predictions together to build up a compound prediction at the community level (Ferrier and Guisan 2006; Table 2).”
Phylogeography's past, present, and future: 10 years after Avise, 2000. (2010, background): “This approach will be useful for predicting how climate change will genetically, demographically, and spatially influence regional biodiversity (Ferrier and Guisan, 2006; Taberlet and Cheddadi, 2002; Williams et al., 2007).”
The impact of modelling choices in the predictive performance of richness maps derived from species‐distribution models: guidelines to build better diversity models (2013, methodology): “SDMs have also been used to predict species richness and composition based on the assemblage of single predicted species ranges, following the ‘predict first, assemble later’ principle proposed by Ferrier & Guisan (2006).”
Using generalized dissimilarity modelling to analyse and predict patterns of beta diversity in regional biodiversity assessment (2007, methodology): “To date, most predictions of distributional shifts expected to result from climate change have been based either on modelling of individual species or on modelling of discrete biomes or community types (Ferrier & Guisan, 2006).”
Species distribution models reveal apparent competitive and facilitative effects of a dominant species on the distribution of tundra plants (2010, background): “Community-based modelling approaches have been proposed to assess interactions between more than one species at a time (Ferrier and Guisan 2006), which could yield further insight about ecological processes underlying SDMs.”
Ecological genomics meets community-level modelling of biodiversity: mapping the genomic landscape of current and future environmental adaptation. (2015, background): “Simultaneous modelling of the entire site-by-species matrix confers several benefits (Ferrier & Guisan 2006), among which are an ability to: (1) rapidly analyse large numbers of species, (2) detect shared patterns of response to environmental gradients for rarely recorded species and (3) assess the…”
Multiscale effects of flow regime and habitat and their interaction on fish assemblage structure in eastern Australia (2007, background): “This multispecies approach increases our capacity to detect and synthesise complex biota–environment relationships (Ferrier and Guisan 2006; Olden et al. 2006a).”
The Diversity of Life in African Freshwaters: Under Water, Under Threat: An Analysis of the Status and Distribution of Freshwater Species throughout Mainland Africa (2011, background): “Using community-level surrogates (Ferrier and Guisan 2006) — especially if several community types can be combined — is desirable, because this may help account for unknown and under-surveyed species.”
Using k-nn and discriminant analyses to classify rain forest types in a Landsat TM image over northern Costa Rica (2008, background): “…composition or structural conditions on the ground, satellite images provide a low-cost source of data for distinguishing and mapping rain forest types, a prerequisite for conservation planning and sustainable forest management (Favrichon, 1998; Ferrier & Guisan, 2006; Margules & Pressey, 2000).”
Machine Learning Methods Without Tears: A Primer for Ecologists (2008, background): “Applications of ML methods in ecology are diverse, and range from testing biogeographical, ecological, and evolutionary hypotheses to modeling species distributions for conservation and management planning (e.g., Fielding 1999; Recknagel 2001, 2003; Cushing and Wilson 2005; Ferrier and Guisan 2006; ”
Climate change vulnerability assessment of species (2018, background): “Assemblages can be defined with reference to community types (Ferrier & Guisan, 2006), biomes (Midgley, Hannah, Millar, Thuiller, & Booth, 2003), or shared traits (Golicher, Cayuela, Alkemade, González-Espinosa, & Ramírez-Marcial, 2008; Vale & Brito, 2015) that are thought to mediate species'…”