Data availability constrains model complexity, generality, and utility: A response to Evans et al.

Trends in Ecology and Evolution

Volumn 29, Issue 6, 2014, Pages 301-302

  Lonergan, Mike ^a  

^a UNIVERSITY OF ST ANDREWS   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

BIOLOGICAL MODEL; ECOLOGY; ECOSYSTEM; PROCEDURES;

ECOLOGY; ECOSYSTEM; MODELS, BIOLOGICAL;

EID: 84901006964     PISSN: 01695347     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.tree.2014.03.005     Document Type: Letter

References (11)

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3. Johnson J.B., Omland K.S. Model selection in ecology and evolution. Trends Ecol. Evol. 2004, 19:101-108.
4. Patterson T.A., et al. State-space models of individual animal movement. Trends Ecol. Evol. 2008, 23:87-94.
5. Newman K.B., et al. Monte Carlo inference for state-space models of wild animal populations. Biometrics 2009, 65:572-583.
6. Uchmanski J., Grimm V. Individual-based modelling in ecology: what makes the difference?. Trends Ecol. Evol. 1996, 11:437-441.
7. Bolker B.M., et al. Individual-based modelling: what is the difference?. Trends Ecol. Evol. 1997, 12:111.
8. Uchmanski J., Grimm V. Individual-based modelling: what is the difference? Reply. Trends Ecol. Evol. 1997, 12:112.
9. Pike D.A., et al. Estimating survival rates of uncatchable animals: the myth of high juvenile mortality in reptiles. Ecology 2008, 89:607-611.
10. Clark F., et al. The theta-logistic is unreliable for modelling most census data. Methods Ecol. Evol. 2010, 1:253-262.
11. Lonergan M., et al. Rescaling of aerial survey data with information from small numbers of telemetry tags to estimate the size of a declining harbour seal population. Aquat. Conserv. Mar. Freshwater Ecosyst. 2013, 23:135-144.