Rising complexity and falling explanatory power in ecology

By É. Low‐Décarie, Corey J. Chivers, Monica Granados. 2014

89 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Ecological Modeling, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/79b7c88ff750e15d79a317e8325ed39c092079e8

How researchers see this paper

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

In Artificial Intelligence

1. David Hodgson
2. Maria Eugenia Correa-Cano
3. Beth S Robinson
4. Richard Inger
5. Lynda Donaldson
6. David N. Fisher
7. J. Evans
8. Cecily E. D. Goodwin

In Ecological Modeling

1. David Hodgson
2. Maria Eugenia Correa-Cano
3. Beth S Robinson
4. Richard Inger
5. Lynda Donaldson
6. David N. Fisher
7. J. Evans
8. Cecily E. D. Goodwin

In Nature and Landscape Conservation

1. Richard Inger
2. David Hodgson
3. Maria Eugenia Correa-Cano
4. Beth S Robinson
5. Lynda Donaldson
6. David N. Fisher
7. J. Evans
8. Cecily E. D. Goodwin

Citations in the corpus

• A brief introduction to mixed effects modelling and multi-model inference in ecology (2018, background): “In recent years, the suite of statistical tools available to biologists and the complexity of biological data analyses have grown in tandem (Low-Decarie et al 2014; Zuur & Ieno 2016; Kass et al 2016).”