Why environmental scientists are becoming Bayesians

By James S. Clark. 2004

825 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Ecological Modeling

View Paper: https://www.semanticscholar.org/paper/392acf6c5fa509d2763fa96a39b582428726fb4f

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In Ecological Modeling

Citations in the corpus

Fine‐scale environmental variation in species distribution modelling: regression dilution, latent variables and neighbourly advice (2011, methodology): “Cabral & Schurr 2010) and biases introduced by imperfect measurement (Huston 2002; Clark 2005; Araújo & Rahbek 2006; Austin 2007).”
How to understand species’ niches and range dynamics: a demographic research agenda for biogeography (2012, methodology): “By describing processes in greater detail, they can also be linked to a wider range of empirical data (see next section), which should generally facilitate model estimation (Clark, 2005).”
Seven Shortfalls that Beset Large-Scale Knowledge of Biodiversity (2015, background): “…techniques allow researchers to incorporate covariates to account for measurement error, but an increasingly popular analytical strategy in ecological and evolutionary research is the switch from significance testing to probabilistic approaches and Bayesian analyses (Clark 2005, Beck et al. 2012).”
Traits of British alien and native urban plants (2008, methodology): “in a Bayesian framework (Clark 2005), the parameter estimates were”
Remotely sensed spectral heterogeneity as a proxy of species diversity: Recent advances and open challenges (2010, methodology): “Several new modeling techniques are now available which explicitly take into account uncertainty as an input to themodel and not only as an output statistic (e.g. Bayesian techniques, Ellison, 2004; Clark, 2005).”
Geneland: a computer package for landscape genetics (2005, background): “See (Gilks et al. 1996) for an introduction to Bayesian computations and (Clark 2005) for a recent introduction to their use in ecology.”
Capturing diversity and interspecific variability in allometries: A hierarchical approach (2008, methodology): “The model was fit making use of standard MCMC methods (Clark, 2007; Gelman et al., 1995).”
Lion hunting behaviour and vegetation structure in an African savanna (2013, neutral): “Bayesian statistics provide a powerful framework for building and estimating parameters from hierarchical models (Clark 2005; Clark & Gelfand 2006).”