Displaying bias in sampling effort of data accessed from biodiversity databases using ignorance maps

Biodiversity Data Journal

Volumn 3, Issue 1, 2015, Pages

  Ruete, Alejandro ^a  

^a SWEDISH UNIVERSITY OF AGRICULTURAL SCIENCES   (Sweden)

Author keywords

Biodiversity database; Citizen science data; Presence only data; Sampling effort; Spatial bias; Species distribution model; Swedish Lifewatch

Indexed keywords

EID: 85018193953     PISSN: None     EISSN: 13142828     Source Type: Journal    
DOI: 10.3897/BDJ.3.e5361     Document Type: Article

References (23)

1. Argáez J, Andrés Christen J, Nakamura M, Soberón J (2005) Prediction of potential areas of species distributions based on presence-only data. Environmental and Ecological Statistics 12 (1): 27-44. DOI: 10.1007/s10651-005-6816-2
2. Barnes M, Szabo J, Morris W, Possingham H (2014) Evaluating protected area effectiveness using bird lists in the Australian Wet Tropics. Diversity and Distributions 21 (4): 368-378. DOI: 10.1111/ddi.12274
3. Elith J, Kearney M, Phillips S (2010) The art of modelling range-shifting species. Methods in Ecology and Evolution 1 (4): 330-342. DOI: 10.1111/ j.2041-210X.2010.00036.x
4. Franklin J (2010) Moving beyond static species distribution models in support of conservation biogeography. Diversity and Distributions 16 (3): 321-330. DOI: 10.1111/ j.1472-4642.2010.00641.x
5. Franklin J (2013) Species distribution models in conservation biogeography: developments and challenges. Diversity and Distributions 19 (10): 1217-1223. DOI: 10. 1111/ddi.12125
6. Gärdenfors U, Jönsson M, Obst M, Wremp AM, Kindvall O, Nilsson J (2014) Swedish LifeWatch-a biodiversity infrastructure integrating and reusing data from citizen science, monitoring and research. Human Computation 1 (2): 1. DOI: 10.15346/ hc.v1i2.6
7. Hertzog L, Besnard A, Jay-Robert P (2014) Field validation shows bias-corrected pseudo-absence selection is the best method for predictive species-distribution modelling. Diversity and Distributions 20 (12): 1403-1413. DOI: 10.1111/ddi.12249
8. Hill M (2012) Local frequency as a key to interpreting species occurrence data when recording effort is not known. Methods in Ecology and Evolution 3 (1): 195-205. DOI: 1 0.1111/j.2041-210X.2011.00146.x
9. Hortal J (2008) Uncertainty and the measurement of terrestrial biodiversity gradients. Journal of Biogeography 35 (8): 1335-1336. DOI: 10.1111/j.1365-2699.2008.01955.x
10. Hortal J, Lobo J, Jiménez-Valverde A (2007) Limitations of biodiversity databases: case study on seed-plant diversity in tenerife, canary islands. Conservation Biology 21 (3): 853-863. DOI: 10.1111/j.1523-1739.2007.00686.x
11. Hurlbert A, Jetz W (2007) Species richness, hotspots, and the scale dependence of range maps in ecology and conservation. Proceedings of the National Academy of Sciences 104 (33): 13384-13389. DOI: 10.1073/pnas.0704469104
12. Jeppsson T, Lindhe A, Gärdenfors U, Forslund P (2010) The use of historical collections to estimate population trends: A case study using Swedish longhorn beetles (Coleoptera: Cerambycidae). Biological Conservation 143 (9): 1940-1950. DOI: 10.101 6/j.biocon.2010.04.015
13. McCarthy M, Masters P (2005) Profiting from prior information in Bayesian analyses of ecological data. Journal of Applied Ecology 42 (6): 1012-1019. DOI: 10.1111/ j.1365-2664.2005.01101.x
14. Peterson AT, Soberón J (2012) Integrating fundamental concepts of ecology, biogeography, and sampling into effective ecological niche modeling and species distribution modeling. Plant Biosystems-An International Journal Dealing with all Aspects of Plant Biology 146 (4): 789-796. DOI: 10.1080/11263504.2012.740083
15. Phillips S, Dudík M, Elith J, Graham C, Lehmann A, Leathwick J, Ferrier S (2009) Sample selection bias and presence-only distribution models: implications for background and pseudo-absence data. Ecological Applications 19 (1): 181-197. DOI: 1 0.1890/07-2153.1
16. Ponder WF, Carter GA, Flemons P, Chapman RR (2001) Evaluation of museum collection data for use in biodiversity assessment. Conservation Biology 15 (3): 648-657. DOI: 10.1046/j.1523-1739.2001.015003648.x
17. Prendergast JR, Wood SN, Lawton JH, Eversham BC (1993) Correcting for variation in recording effort in analyses of diversity hotspots. Biodiversity Letters 1 (2): 39. DOI: 10. 2307/2999649
18. Rocchini D, Hortal J, Lengyel S, Lobo J, Jiménez-Valverde A, Ricotta C, Bacaro G, Chiarucci A (2011) Accounting for uncertainty when mapping species distributions: The need for maps of ignorance. Progress in Physical Geography 35 (2): 211-226. DOI: 10. 1177/0309133311399491
19. Schulman L, Toivonen T, Ruokolainen K (2007) Analysing botanical collecting effort in Amazonia and correcting for it in species range estimation. Journal of Biogeography 34 (8): 1388-1399. DOI: 10.1111/j.1365-2699.2007.01716.x
20. Snäll T, Kindvall O, Nilsson J, Pärt T (2011) Evaluating citizen-based presence data for bird monitoring. Biological Conservation 144 (2): 804-810. DOI: 10.1016/ j.biocon.2010.11.010
21. Stolar J, Nielsen S (2015) Accounting for spatially biased sampling effort in presenceonly species distribution modelling. Diversity and Distributions 21 (5): 595-608. DOI: 10. 1111/ddi.12279
22. Suarez A, Tsutsui N (2004) The value of museum collections for research and society. BioScience 54 (1): 66. DOI: 10.1641/0006-3568(2004)054[0066:TVOMCF]2.0.CO;2
23. Syfert M, Smith M, Coomes D (2013) The effects of sampling bias and model complexity on the predictive performance of Maxent species distribution models. PLoS ONE 8 (2): e55158. DOI: 10.1371/journal.pone.0055158