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Null models reveal preferential sampling, spatial autocorrelation and overfitting in habitat suitability modelling
Merckx, B.; Steyaert, M.; Vanreusel, A.; Vincx, M.; Vanaverbeke, J. (2011). Null models reveal preferential sampling, spatial autocorrelation and overfitting in habitat suitability modelling. Ecol. Model. 222(3): 588-597.
In: Ecological Modelling. Elsevier: Amsterdam; Lausanne; New York; Oxford; Shannon; Tokyo. ISSN 0304-3800; e-ISSN 1872-7026, more
Peer reviewed article  

Available in  Authors 
    VLIZ: Open Repository 217488 [ OMA ]

    Analysis > Mathematical analysis > Statistical analysis > Correlation analysis > Autocorrelation
    Nematoda [WoRMS]
    ANE, Belgium [Marine Regions]; ANE, North Sea, Southern Bight [Marine Regions]
Author keywords
    MaxEnt; Null models; Preferential sampling; Spatial autocorrelation;Overfitting; Nematoda

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    Nowadays, species are driven to extinction at a high rate. To reduce this rate it is important to delineate suitable habitats for these species in such a way that these areas can be suggested as conservation areas. The use of habitat suitability models (HSMs) can be of great importance for the delineation of such areas. In this study MaxEnt, a presence-only modelling technique, is used to develop HSMs for 223 nematode species of the Southern Bight of the North Sea. However, it is essential that these models are beyond discussion and they should be checked for potential errors. In this study we focused on two categories (1) errors which can be attributed to the database such as preferential sampling and spatial autocorrelation and (2) errors induced by the modelling technique such as overfitting, In order to quantify these adverse effects thousands of nulls models were created. The effect of preferential sampling (i.e. some areas where visited more frequenty than others) was investigated by comparing model outcomes based from null models sampling the actual sampling stations and null models sampling the entire mapping area.

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