PREDICTION IN COMPLEX COMMUNITIES: ANALYSIS OF EMPIRICALLY DERIVED MARKOV MODELS

By Timothy J Wootton. 2001

98 citations recorded by the source corpus.

Subfields: Ecology, Oceanography

View Paper: https://www.semanticscholar.org/paper/0464f0a104a0be624cabca39340da5d114d0d1a3

How researchers see this paper

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

In Ecology

1. M. Emmerson
2. P. C. Ruiter
3. J. M. Montoya
4. John Foster
5. Stephen P. Borgatti
6. Roman Dial
7. Alan J. McKane
8. Jeffrey C. Johnson

In Oceanography

1. John Foster
2. Stephen P. Borgatti
3. Jeffrey C. Johnson
4. Joseph J. Luczkovich
5. J. Timothy Wootton
6. Colin Brown
7. Tom A. B. Snijders
8. Owen L. Petchey

Citations in the corpus

• Interaction strengths in food webs: issues and opportunities (2004, background): “For example, if the goal is to predict community changes resulting from a species removal, statistical Markov models may be a useful approach even though they do not clearly shed light on the patterning of interaction strengths or the exact mechanisms of change (e.g. Wootton 2001).”
• Wetland drying and succession across the Kenai Peninsula Lowlands, south-central Alaska (2005, background): “Markov models rely on several assumptions: (1) spatial distribution is not influential (Wooton 2001); (2) transition probabilities are stationary and do not change with time (Hobbs 1983); and (3) transition to another state is depend-”
• Using social network analysis tools in ecology: Markov process transition models applied to the seasonal trophic network dynamics of the Chesapeake Bay. (2009, methodology): “Markov models have been used to study competitive networks of species (Buss and Jackson, 1979), diversity–stability relationships in ecosystems (Li and Charnov, 2001), and to model transition probabilities of species surviving in rocky intertidal communities (Wootton, 2001).”
• MEASUREMENT OF INTERACTION STRENGTH IN NATURE (2005, unknown): “F or p er so na l u se o nl y. 422 WOOTTON EMMERSON models (Wootton 2001).”
• Indirect effects in complex ecosystems: recent progress and future challenges (2002, background): “…on transition probabilities that defined spatial locations shift among different ecological states, where states are defined as the species or species combination occupying particular points in space (Horn, 1975; Saila and Erzini, 1987; Pastor et al., 1993; Tanner et al., 1994; Wootton, 2001).”
• Measuring resilience in energy systems: insights from a range of disciplines (2016, methodology): “Using transition probabilities derived from historical performance, simple Markov models have shown prediction accuracy for a limited number of parameters [15, 16].”