References |
Alhajeri B.H., Fourcade Y. 2019. High correlation between species-level environmental data estimates extracted from IUCN expert range maps and from GBIF occurrence data. Journal of Biogeography 46(7): 1329–1341. DOI: 10.1111/jbi.13619 Arotolu T.E., Wang H.N., Lv J.N., Shi K., Huang L.Y., Wang X.L. 2023. Modeling the current and future distribution of Brucellosis under climate change scenarios in Qinghai Lake basin, China. Acta Veterinaria-Beograd 73(3): 325–345. DOI: 10.2478/acve-2023-0025 Baker D.J., Clarke R.H., McGeoch M.A. 2019. The power to detect regional declines in common bird populations using continental monitoring data. Ecological Applications 29(5): e01918. DOI: 10.1002/eap.1918 Beck J., Böller M., Erhardt A., Schwanghart W. 2014. Spatial bias in the GBIF database and its effect on modeling species' geographic distributions. Ecological Informatics 19: 10–15. DOI: 10.1016/j.ecoinf.2013.11.002 Bowler D.E., Callaghan C.T., Bhandari N., Henle K., Barth B.M., Koppitz C., Klenke R., Winter M., Jansen F., Bruelheide H., Bonn A. 2022. Temporal Trends in the Spatial Bias of Species Occurrence Records. Ecography 2022(8): e06219. DOI: 10.1111/ecog.06219 Boyd R.J., Aizen M.A., Barahona-Segovia R.M., Flores-Prado L., Fontúrbel F.E., Francoy T.M., Lopez-Aliste M., Martinez L., Morales C.L., Ollerton J., Pescott O.L., Powney G.D., Saraiva A.M., Schmucki R., Zattara E.E., Carvell C. 2022. Inferring trends in pollinator distributions across the Neotropics from publicly available data remains challenging despite mobilization efforts. Diversity and Distributions 28(7): 1404–1415. DOI: 10.1111/ddi.13551 Chadin I., Dalke I., Zakhozhiy I., Malyshev R., Madi E., Kuzivanova O., Kirillov D., Elsakov V. 2017. Distribution of the invasive plant species Heracleum sosnowskyi Manden. in the Komi Republic (Russia). Phytokeys 77: 71–80. DOI: 10.3897/phytokeys.77.11186 Chase M.W., Cameron K.M., Barrett R.L., Freudebstein J.V. 2003. DNA data and Orchidaceae systematics: A new phylogenetic classification. In: K.W. Dixon, S.P. Kell, R.L. Barrett, P.J. Cribb (Eds.): Orchid Conservation. Kota Kinabalu: Natural History Publications (Borneo). P. 69–89. Chevalier M., Zarzo-Arias A., Guélat J., Mateo R.G., Guisan A. 2022. Accounting for niche truncation to improve spatial and temporal predictions of species distributions. Frontiers in Ecology and Evolution 10: 944116. DOI: 10.3389/fevo.2022.944116 Christenhusz M.J.M., Byng J.W. 2016. The number of known plants species in the world and its annual increase. Phytotaxa 261(3): 201–217. DOI: 10.11646/phytotaxa.261.3.1 Cribb P.J., Kell S.P., Dixon K.W., Barrett R.L. 2003. Orchid conservation: A global perspective. In: K.W. Dixon, S.P. Kell, R.L. Barrett, P.J. Cribb (Eds.): Orchid Conservation. Kota Kinabalu: Natural History Publications (Borneo). P. 1–2. Czech Geological Survey. 1998. Geological map of the Czech Republic 1:500 000 (GEOCR500). Available from https://micka.geology.cz/en/record/basic/5f5b4530-a87c-4bf3-b45a-57d30a010852 Daba D., Kagnew B., Tefera B., Nemomissa S. 2023. Modelling the current and future distribution potential areas of Peperomia abyssinica Miq., and Helichrysum citrispinum Steud. ex A. Rich. in Ethiopia. BMC Ecology and Evolution 23(1): 71. DOI: 10.1186/s12862-023-02177-z Danihelka J., Chrtek J.J., Kaplan Z. 2012. Checklist of vascular plants of the Czech Republic. Preslia 84: 647–811. David O.A., Akomolafe G.F., Onwusiri K.C., Fabolude G.O. 2020. Predicting the distribution of the invasive species Hyptis suaveolens in Nigeria. European Journal of Environmental Sciences 10(2): 98–106. DOI: 10.14712/23361964.2020.11 De Araujo M.L., Quaresma A.C., Ramos F.N. 2022. GBIF information is not enough: national database improves the inventory completeness of Amazonian epiphytes. Biodiversity and Conservation 31(11): 2797–2815. DOI: 10.1007/s10531-022-02458-x Djordjević V., Tsiftsis S. 2022. The role of ecological factors in distribution and abundance of terrestrial orchids. In: J.M. Mérillon, H. Kodja (Eds.): Orchids Phytochemistry, Biology and Horticulture. Cham: Springer Nature. P. 1–71. DOI: 10.1007/978-3-030-11257-8_4-1 Dressler R.L. 1993. Phylogeny and Classification of the Orchid Family. Cambridge: Cambridge University Press. 301 p. El-Gabbas A., Dormann C.F. 2018. Wrong, but useful: regional species distribution models may not be improved by range-wide data under biased sampling. Ecology and Evolution 8(4): 2196–2206. DOI: 10.1002/ece3.3834 Elith J., Leathwick J. 2009. The contribution of species distribution modelling to conservation prioritization. In: A. Moilanen, A.K. Wilson, H.P. Possingham (Eds.): Spatial conservation prioritization. Quantitative methods and computational tools. New York: Oxford University Press Inc. P. 70–93. Elith J., Phillips S.J., Hastie T., Dudík M., Chee Y.E., Yates C.J. 2011. A statistical explanation of MaxEnt for ecologist. Diversity and Distributions 17(1): 43–57. DOI: 10.1111/j.1472-4642.2010.00725.x Fick S.E., Hijmans R.J. 2017. WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. International Journal of Climatology 37(12): 4302–4315. DOI: 10.1002/joc.5086 Graham C.H., Ferrier S., Huettman F., Moritz C., Peterson A.T. 2004. New developments in museum-based informatics and applications in biodiversity analysis. Trends in Ecology and Evolution 19(9): 497–503. DOI: 10.1016/j.tree.2004.07.006 Grulich V., Chobot K. 2017. Red list of threatened species of the Czech Republic vascular plants. Příroda 35: 1–178. Guedes T.B., Sawaya R.J., Zizka A., Laffan S., Faurby S., Pyron R.A., Bérnils R.S., Jansen M., Passos P., Prudente A.L.C., Cisneros-Heredia D.F., Braz H.B., Nogueira C.D., Antonelli A. 2018. Patterns, biases and prospects in the distribution and diversity of Neotropical snakes. Global Ecology and Biogeography 27(1): 14–21. DOI: 10.1111/geb.12679 Guisan A., Thuiller W. 2005. Predicting species distribution: Offering more than simple habitat models. Ecology Letters 8(9): 993–1009. DOI: 10.1111/j.1461-0248.2005.00792.x Halley J.M., Pimm S.L. 2023. The rate of species extinction in declining or fragmented ecological communities. PloS ONE 18(7): e0285945. DOI: 10.1371/journal.pone.0285945 Hernandez P.A., Graham C.H., Master L.L., Albert D.L. 2006. The effect of sample size and species characteristics on performance of different species distribution modeling methods. Ecography 29(5): 773–785. DOI: 10.1111/j.0906-7590.2006.04700.x Jiang Y., Purvis A. 2023. How land use affects biodiversity: an analysis of the differences in the effects recorded on different continents. European Journal of Environmental Sciences 13(1): 15–22. DOI: 10.14712/23361964.2023.2 Kistner E.J., Hatfield J.L. 2018. Potential geographic distribution of Palmer Amaranth under current and future climates. Agricultural and Environmental Letters 3(1): 170044. DOI: 10.2134/ael2017.12.0044 Krapf P. 2023. Contribution of the public to the modelling of the distributions of species: Occurrence and current and potential distribution of the ant Manica rubida (Hymenoptera: Formicidae). European Journal of Entomology 120: 137–148. DOI: 10.14411/eje.2023.017 Liu C., Newell G., White M. 2016. On the selection of thresholds for predicting species occurrence with presence-only data. Ecology and Evolution 6(1): 337–348. DOI: 10.1002/ece3.1878 Maldonado C., Molina C.I., Zizka A., Persson C., Taylor C.M., Albán J., Chilquillo E., Rønsted N., Antonelli A. 2015. Estimating species diversity and distribution in the era of Big Data: to what extent can we trust public databases?. Global Ecology and Biogeography 24(8): 973–984. DOI: 10.1111/geb.12326 Mallen-Cooper M., Rodríguez-Caballero E., Eldridge D.J., Weber B., Büdel B., Höhne H., Cornwell W.K. 2023. Towards an understanding of future range shifts in lichens and mosses under climate change. Journal of Biogeography 50(2): 406–417. DOI: 10.1111/jbi.14542 Marcer A., Chapman A.D., Wieczorek J.R., Picó F.X., Uribe F., Waller J., Ariño A.H. 2022. Uncertainty matters: Ascertaining where specimens in natural history collections come from and its implications for predicting species distributions. Ecography 2022(9): e06025. DOI: 10.1111/ecog.06025 Martínez-Méndez N., Mejía O., Ortega J., Méndez-de la Cruz F. 2019. Climatic niche evolution in the viviparous Sceloporus torquatus group (Squamata: Phrynosomatidae). PeerJ 6: e6192. DOI: 10.7717/peerj.6192 Moudrý V., Devillers R. 2020. Quality and usability challenges of global marine biodiversity databases: An example for marine mammal data. Ecological Informatics 56: 101051. DOI: 10.1016/j.ecoinf.2020.101051 Namkhan M., Sukumal N., Savini T. 2022. Impact of climate change on Southeast Asian natural habitats, with focus on protected areas. Global Ecology and Conservation 39: e02293. DOI: 10.1016/j.gecco.2022.e02293 Newbold T. 2010. Applications and limitations of museum data for conservation and ecology, with particular attention to species distribution models. Progress in Physical Geography 34(1): 3–22. DOI: 10.1177/0309133309355630 Nunes L.A., Pearson R.G. 2017. A null biogeographical test for assessing ecological niche evolution. Journal of Biogeography 44(6): 1331–1343. DOI: 10.1111/jbi.12910 Palacký University Olomouc. 2020. Climatic Conditions of the Czech Republic. Available from https://geography.upol.cz/soubory/lide/smolova/GCZ/GCZ_Klima.pdf Phillips S.J., Dudík M. 2008. Modeling of species distributions with Maxent: New extensions and a comprehensive evaluation. Ecography 31(2): 161–175. DOI: 10.1111/j.0906-7590.2008.5203.x Phillips S.J., Anderson R.P., Schapire R.E. 2006. Maximum entropy modeling of species geographic distribution. Ecological Modelling 190(3–4): 231–259. DOI: 10.1016/j.ecolmodel.2005.03.026 Pillon Y., Chase M. 2007. Taxonomic exaggeration and its effects on orchid conservation. Conservation Biology 21(1): 263–265. DOI: 10.1111/j.1523-1739.2006.00573.x R Core Team. 2023. R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. Available from https://www.r-project.org/ Román-Palacios C., Wiens J.J. 2020. Recent responses to climate change reveal the drivers of species extinction and survival. Proceedings of the National Academy of Sciences of the United States of America 117(8): 4211–4217. DOI: 10.1073/pnas.1913007117 Salvà-Catarineu M., Romo A., Mazur M., Zielińska M., Minissale P., Dönmez A.A., Boratyńska K., Boratyński A. 2021. Past, present, and future geographic range of the relict Mediterranean and Macaronesian Juniperus phoenicea complex. Ecology and Evolution 11(10): 5075–5095. DOI: 10.1002/ece3.7395 Smith V.S., Blagoderov V. 2012. Bringing collections out of the dark. ZooKeys 209: 1–6. DOI: 10.3897/zookeys.209.3699 Soberón J., Peterson T. 2004. Biodiversity informatics: managing and applying primary biodiversity data. Philosophical Transactions of the Royal Society B: Biological Sciences 359(1444): 689–698. DOI: 10.1098/rstb.2003.1439 Sokal R.R., Rohlf F.J. 2012. Biometry: The Principles and Practice of Statistics in biological Research, 4th ed. New York: W.H. Freeman and Company. 915 p. Spooner F.E.B., Pearson R.G., Freeman R. 2018. Rapid warming is associated with population decline among terrestrial birds and mammals globally. Global Change Biology 24(10): 4521–4531. DOI: 10.1111/gcb.14361 Steffelová M., Traxmandlová I., Štípková Z., Kindlmann P. 2023. Pollination strategies of deceptive orchids – a review. European Journal of Environmental Sciences 13(2): 110–116. DOI: 10.14712/23361964.2023.12 Štípková Z., Kindlmann P. 2015. Extent and reasons for meadows in South Bohemia becoming unsuitable for orchids. European Journal of Environmental Sciences 5(2): 142–147. DOI: 10.14712/23361964.2015.87 Štípková Z., Kosánová K., Romportl D., Kindlmann P. 2018. Determinants of orchid occurrence: a Czech example. In: B. Şen, O. Grillo (Eds.): Selected Studies in Biodiversity. London: InTechOpen. P. 133–155. DOI: 10.5772/intechopen.74851 Štípková Z., Romportl D., Kindlmann P. 2020a. Which environmental factors drive distribution of orchids? A case study from South Bohemia, Czech Republic. In: J.M. Mérillon, H. Kodja (Eds.): Orchids Phytochemistry, Biology and Horticulture. Cham: Springer Nature. P. 1–33. DOI: 10.1007/978-3-030-38392-3_27 Štípková Z., Tsiftsis S., Kindlmann P. 2020b. Pollination mechanisms are driving orchid distribution in space. Scientific Reports 10(1): 850. DOI: 10.1038/s41598-020-57871-5 Švecová M., Štípková Z., Traxmandlová I., Kindlmann P. 2023. Difficulties in determining distribution of population sizes within different orchid metapopulations. European Journal of Environmental Sciences 13(2): 96–109. DOI: 10.14712/23361964.2023.11 Štípková Z., Tsiftsis S., Kindlmann P. 2021. Distribution of orchids with different rooting systems in the Czech Republic. Plants 10(4): 632. DOI: 10.3390/plants10040632 Swarts N.D., Dixon K.W. 2009. Terrestrial orchid conservation in the age of extinction. Annals of Botany 104(3): 543–556. DOI: 10.1093/aob/mcp025 Tsiftsis S., Djordjević V. 2020. Modelling sexually deceptive orchid species distributions under future climates: the importance of plant-pollinator interactions. Scientific Reports 10(1): 10623. DOI: 10.1038/s41598-020-67491-8 Warren D.L., Glor R.E., Turelli M. 2008. Environmental niche equivalency versus conservatism: quantitative approaches to niche evolution. Evolution 62(11): 2868–2883. DOI: 10.1111/j.1558-5646.2008.00482.x Weterings R., Vetter K.C. 2018. Invasive house geckos (Hemidactylus spp.): their current, potential and future distribution. Current Zoology 64(5): 559–573. DOI: 10.1093/cz/zox052 Yi Y.J., Cheng X., Yang Z.F., Zhang S.H. 2016. Maxent modeling for predicting the potential distribution of endangered medicinal plant (H. riparia Lour) in Yunnan, China. Ecological Engineering 92: 260–269. DOI: 10.1016/j.ecoleng.2016.04.010 Zhang Z., Yan Y., Tian Y., Li J., He J.S., Tang Z. 2015. Distribution and conservation of orchid species richness in China. Biological Conservation 181: 64–72. DOI: 10.1016/j.biocon.2014.10.026 |