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RESEARCH PRODUCT
Assessing sampling coverage of species distribution in biodiversity databases
Idoia BiurrunHelge BruelheideCorrado MarcenòGunnar SeidlerJonathan LenoirJürgen DenglerJürgen DenglerValentin GolubVigdis VandvikVigdis VandvikJesper Erenskjold MoeslundJohn-arvid GrytnesGunnar AustrheimUte JandtSolvita RūsiņaAaron Pérez-haaseEls De BieMiska LuotoJuan Antonio CamposErik WelkMilan ChytrýMaria SporbertJános CsikyAndraž ČArniAndraž ČArniMartin JiroušekMartin JiroušekKiril VassilevFlorian JansenAdrian IndreicaPetr Keilsubject
0106 biological sciencesChorological Database Halle (CDH)Range (biology)multi-scale[SDE.MCG]Environmental Sciences/Global Changesvegetation-plot databasesSpecies distributionPlant Science[SDV.BID]Life Sciences [q-bio]/Biodiversitycomputer.software_genre010603 evolutionary biology01 natural sciencesmacro-ecology333: Bodenwirtschaft und Ressourcen577: ÖkologieRealized niche widthMacroecologyEcological niche[SDV.EE]Life Sciences [q-bio]/Ecology environmentspatial scaleEcologyDatabaseNull modelvegetation plot databasesclimatic nichevascular plantSampling (statistics)species rangeVegetation15. Life on landDynamic Match Coefficient (DMC)sampling biasGeographyrealized niche1181 Ecology evolutionary biologymacroecology[SDE.BE]Environmental Sciences/Biodiversity and Ecologycomputer010606 plant biology & botanyEuropean Vegetation Archive (EVA)description
Abstract Aim Biodiversity databases are valuable resources for understanding plant species distributions and dynamics, but they may insufficiently represent the actual geographic distribution and climatic niches of species. Here we propose and test a method to assess sampling coverage of species distribution in biodiversity databases in geographic and climatic space. Location Europe. Methods Using a test selection of 808,794 vegetation plots from the European Vegetation Archive (EVA), we assessed the sampling coverage of 564 European vascular plant species across both their geographic ranges and realized climatic niches. Range maps from the Chorological Database Halle (CDH) were used as background reference data to capture species geographic ranges and to derive species climatic niches. To quantify sampling coverage, we developed a box-counting method, the Dynamic Match Coefficient (DMC), which quantifies how much a set of occurrences of a given species matches with its geographic range or climatic niche. DMC is the area under the curve measuring the match between occurrence data and background reference (geographic range or climatic niche) across grids with variable resolution. High DMC values indicate good sampling coverage. We applied null models to compare observed DMC values with expectations from random distributions across species ranges and niches. Results Comparisons with null models showed that, for most species, actual distributions within EVA are deviating from null model expectations and are more clumped than expected in both geographic and climatic space. Despite high interspecific variation, we found a positive relationship in DMC values between geographic and climatic space, but sampling coverage was in general more random across geographic space. Conclusion Because DMC values are species-specific and most biodiversity databases are clearly biased in terms of sampling coverage of species occurrences, we recommend using DMC values as covariates in macroecological models that use species as the observation unit. This article is protected by copyright. All rights reserved. Peer reviewed
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2019-07-01 |