Habitat model
In ecology, a habitat model is a model representation of processes in a habitat . For this purpose, biotic and abiotic factors are taken into account in order to be able to draw conclusions about past or future developments in habitats.
aims
Habitat models are used to quantify the habitat requirements of a species. According to Morrison (1998), habitat models serve several purposes:
- Formation of hypotheses about individual species or systems,
- Understanding which factors influence the distribution and frequency of the species,
- a formalization of this understanding,
- a prediction of future distribution or frequency (scenarios).
Model choice
For the selection of a suitable, i. H. "Robust" model approach, parameters must be defined for the model. First, a scale level must be determined on which to model. This can range from individual microhabitats to global approaches - it can be a species or a coral reef several square kilometers in size. In the case of spatial approaches, the relevance of the environmental conditions of a landscape , a biome or a marine area (relief, watercourses, soil properties, etc.) is examined . The data collected and other available data must be checked to determine whether they are relevant for the model. Due to the mostly limited number of available data, interpolations have to be carried out. The level of interpolated data that goes into the model must therefore also be determined.
In order to be able to estimate the quality of the habitat model and to check the spatiotemporal transferability, an evaluation can be carried out. A solid practice is to use data sets that were not used to build the model. If these data agree with those derived from the model, a certain validity of the model can be assumed.
Species Distribution Models
A frequently used form of habitat models are the Species Distribution Models (SDM). With their help, conclusions can be drawn about the distribution possibilities of animal and plant species in space and time. They are used in ecological as well as evolutionary research.
Overview (based on Franklin 2009 ):
| Method Statistical basis |
description | reference | Application comment |
|---|---|---|---|
| Generalized Linear Models (GLM) | flexible, based on multiple regression | continuous, ordinal, binary (P / A) | effective method, especially for global models |
| Generalized Additive Models (GAM) | multiple regression combined with splines and other methods | continuous, ordinal, binary (P / A) | |
| Bayesian Modeling | Estimates the probability of (future) events | continuous, ordinal, binary (P / A) | is used but is not compatible with other SDM methods |
Web links
Publications
items
- Jane Elith & John R. Leathwick (2009): Species Distribution Models: Ecological Explanation and Prediction Across Space and Time Review in Annual Review of Ecology, Evolution, and Systematics. (doi 10.1146 / annurev.ecolsys.110308.120159)
- E. Penelope Holland, James N. Aegerter, Calvin Dytham, Graham C. Smith: Landscape as a Model: The Importance of Geometry. PLoS.
Books
- Atte Moilanen, Kerrie A. Wilson , Hugh Possingham (Eds.): Spatial Conservation Prioritization: Quantitative Methods and Computational Tools (= Oxford Biology ). Oxford University Press, Oxford, England 2009, ISBN 978-0-19-954777-7 (English).
- Lorenz Fahse, Andreas Huth: Modeling in Ecology: Creating, applying and analyzing ecological models . Springer, Berlin 2007, ISBN 978-3-540-37700-9 .
Individual evidence
- ↑ http://www.wildtierportal.bayern.de/mam/cms12/wildtiere_bayern/daten/schlussbericht-habitatmodell.pdf 2.3. Habitat models page 5-6
- ↑ Janet Franklin (2009): Mapping Species Distributions. Spatial Interference and Prediction. Cambridge.