Dealing with Uncertainty in Spatially Explicit Population Models

By T. Wiegand, E. Revilla, F. Knauer. Biodiversity and Conservation, 2004

150 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/a779971bb27e0699905a9a387980b75c7ba80cd4

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In Ecological Modeling

In Ecology

In Nature and Landscape Conservation

Citations in the corpus

Analyzing the effect of stepping stones on target patch colonisation in structured landscapes for Eurasian lynx (2011, methodology): “In particular, species of conservation concern often suffer from high mortality rates, are poor breeders, and/or occur at low numbers, e.g. after a reintroduction (Wiegand et al. 2004b; Hurford et al. 2006).”
The Role of Density Regulation in Extinction Processes and Population Viability Analysis (2004, methodology): “Also, testing the robustness of predictions from spatially explicit models to deviations from assumptions about individual behaviour (and landscape structure) is still in its infancy (Reed 1999, but see Wiegand et al. 2004 (this issue)).”
Lynx reintroductions in fragmented landscapes of Germany : Projects with a future or misunderstood wildlife conservation? (2005, background): “Despite a few drawbacks (Beissinger and Westphal, 1998; but see Wiegand et al., 2004), spatially explicit population simulation models are virtually the only means to answer certain specific questions of population development under different landscape and demographic scenarios (Brook et al., 2002)…”
Fragmented landscapes, road mortality and patch connectivity: modelling influences on the dispersal of Eurasian lynx (2004, unknown): “To assess the sensitivity of the model predictions to the remaining parameter uncertainty, we used linear regression of the accepted parameterizations (Wiegand et al. 2004).”
Competition among plants: Concepts, individual-based modelling approaches, and a proposal for a future research strategy (2008, methodology): “Pattern-oriented parameterization as employed by Wiegand et al. (2003, 2004), which can also be referred to as Monte-Carlo filtering, has been shown to be powerful for parameterizing grid- and individual-based models of plant and animal population dynamics.”
The state of plant population modelling in light of environmental change (2008, background): “So it is not surprising that pattern formation and its consequences is still an important topic in spatial plant population modelling (e.g. Jeltsch and Moloney, 2002; Rademacher et al., 2004; van de Koppel and Rietkerk, 2004; Wiegand et al., 2004a, b; Aitkenhead et al., 2004; Sherratt, 2005).”