Mapping from heterogeneous biodiversity monitoring data sources

Sardà-Palomera, F. and Brotons, L. and Villero, D. and Sierdsema, H. and Newson, S.E. and Jiguet, F. (2012) Mapping from heterogeneous biodiversity monitoring data sources. Biodiversity and Conservation, 21 (11). pp. 2927-2948.

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Abstract

Field monitoring can vary from simple volunteer opportunistic observations to professional standardised monitoring surveys, leading to a trade-off between data quality and data collection costs. Such variability in data quality may result in biased predictions obtained from species distribution models (SDMs). We aimed to identify the limitations of different monitoring data sources for developing species distribution maps and to evaluate their potential for spatial data integration in a conservation context. Using Maxent, SDMs were generated from three different bird data sources in Catalonia, which differ in the degree of standardisation and available sample size. In addition, an alternative approach for modelling species distributions was applied, which combined the three data sources at a large spatial scale, but then downscaling to the required resolution. Finally, SDM predictions were used to identify species richness and high quality areas (hotspots) from different treatments. Models were evaluated by using high quality Atlas information. We show that both sample size and survey methodology used to collect the data are important in delivering robust information on species distributions. Models based on standardized monitoring provided higher accuracy with a lower sample size, especially when modelling common species. Accuracy of models from opportunistic observations substantially increased when modelling uncommon species, giving similar accuracy to a more standardized survey. Although downscaling data through a SDM approach appears to be a useful tool in cases of data shortage or low data quality and heterogeneity, it will tend to overestimate species distributions. In order to identify distributions of species, data with different quality may be appropriate. However, to identify biodiversity hotspots high quality information is needed.

Item Type: Article
Author Affiliation: Centre Tecnològic Forestal de Catalunya, Solsona, Spain,Institut Català d’Ornitologia(ICO), Catalonia, Spain,European Bird Census Council,SOVON,The Netherlands British Trust for Ornithology, UK,
Subjects: Statistics and Experimentation
Crop Improvement
Divisions: UNSPECIFIED
Depositing User: Mr. SanatKumar Behera
Date Deposited: 13 Sep 2012 03:31
Last Modified: 13 Sep 2012 03:32
Official URL: http://dx.doi.org/10.1007/s10531-012-0347-6
URI: http://eprints.icrisat.ac.in/id/eprint/7865

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