Modeling the distribution of rare and interesting moss species of the family Orthotrichaceae (Bryophyta) in Tajikistan and Kyrgyzstan
Abstract
Keywords
Full Text:
PDFReferences
Blockeel TL, Bednarek-Ochyra H, Ochyra R, Cykowska B, Esquivel MG, Lebouvier M, et al. New national and regional bryophyte records, 21. J Bryol. 2013;31(2):132–139. https://doi.org/10.1179/174328209x431213
Ellis L, Akhoondi Darzikolaei S, Shirzadian S, Bakalin V, Bednarek-Ochyra H, Ochyra R, et al. New national and regional bryophyte records, 29. J Bryol. 2011;33(4):316–323. https://doi.org/10.1179/1743282011Y.0000000031
Ellis L, Alegro A, Bansal P, Nath V, Cykowska B, Bednarek-Ochyra H, et al. New national and regional bryophyte records, 32. J Bryol. 2012;34(3):231–246. https://doi.org/10.1179/1743282012y.0000000019
Ellis L, Bayliss J, Bruggeman-Nannenga M, Cykowska B, Ochyra R, Gremmen N, et al. New national and regional bryophyte records, 38. J Bryol. 2014;36(1):61–72. https://doi.org/10.1179/1743282013Y.0000000085
Ellis L, Afonina OM, Asthana A, Gupta R, Sahu V, Nath V, et al. New national and regional bryophyte records, 39. J Bryol. 2014;36(2):134–151. https://doi.org/10.1179/1743282014Y.0000000100
Ellis L, Aleffi M, Tacchi R, Alegro A, Alonso M, Asthana A, et al. New national and regional bryophyte records, 41. J Bryol. 2014;36(4):306–324. https://doi.org/10.1179/1743282014Y.0000000123
Ellis L, Aleffi M, Bakalin VA, Bednarek-Ochyra H, Bergamini A, Beveridge P, et al. New national and regional bryophyte records, 42. J Bryol. 2015;37(1):68–79. https://doi.org/10.1179/1743282014y.0000000132
Ellis L, Asthana A, Srivastava A, Bakalin VA, Bednarek-Ochyra H, Cano MJ, et al. New national and regional bryophyte records, 43. J Bryol. 2015;37(2):128–147. https://doi.org/10.1179/1743282015Y.0000000003
Ellis LT, Alegro A, Šegota V, Bakalin VA, Barone R, Borovichev EA, et al. New national and regional bryophyte records, 44. J Bryol. 2015;37(3):228–241. https://doi.org/10.1179/1743282015Y.0000000014
Plášek V, Sawicki J, Číhal L. Orthotrichum pamiricum (Bryophyta), a new epiphytic moss species from Pamir Mountains in Central Asia. Turk J Botany. 2014;38(4):754–762. https://doi.org/10.3906/bot-1312-23
Yu J, Ma YH, Guo SL. Modeling the geographic distribution of the epiphytic moss Macromitrium japonicum in China. Ann Bot Fenn. 2013;50(1–2):35–42. https://doi.org/10.5735/085.050.0105
Raxworthy CJ, Martinez-Meyer E, Horning N, Nussbaum RA, Schneider GE, Ortega-Huerta MA, et al. Predicting distributions of known and unknown reptile species in Madagascar. Nature. 2003;426(6968):837–841. https://doi.org/10.1038/nature02205
Bourg NA, McShea WJ, Gill DE. Putting a CART before the search: successful habitat prediction for a rare forest herb. Ecology. 2005;86(10):2793–2804. https://doi.org/10.1890/04-1666
Kruijer HJ, Raes N, Stech M. Modelling the distribution of the moss species Hypopterygium tamarisci (Hypopterygiaceae, Bryophyta) in Central and South America. Nova Hedwigia. 2010;91(3–4):399–420. https://doi.org/10.1127/0029-5035/2010/0091-0399
Sérgio C, Figueira R, Draper D, Menezes R, Sousa AJ. Modelling bryophyte distribution based on ecological information for extent of occurrence assessment. Biol Conserv. 2007;135(3):341–351. https://doi.org/10.1016/j.biocon.2006.10.018
Desamore A, Laenen B, Stech M, Papp B, Hedenäs L, Mateo RG, et al. How do temperate bryophytes face the challenge of a changing environment? Lessons from the past and predictions for the future. Glob Chang Biol. 2012;18(9):2915–2924. https://doi.org/10.1111/j.1365-2486.2012.02752.x
Yu J, Tang YX, Guo SL. Comparison of the geographical distribution of Racomitrium and Grimmia in China using ArcGis and MaxEnt software. Plant Sci J. 2012;30(5):443–458. https://doi.org/10.3724/sp.j.1142.2012.50443
Mateo RG, Vanderpoorten A, Muñoz J, Laenen B, Désamoré A. Modeling species distributions from heterogeneous data for the biogeographic regionalization of the European bryophyte flora. PLoS One. 2013;8(2):e55648. https://doi.org/10.1371/journal.pone.0055648
Poncet R, Hugonnot V, Vergne T. Modelling the distribution of the epiphytic moss Orthotrichum rogeri to assess target areas for protected status. Cryptogam Bryol. 2015;36(1):3–17. https://doi.org/10.7872/cryb.v36.iss1.2015.3
Pearson RG, Raxworthy CJ, Nakamura M, Townsend Peterson A. Predicting species distributions from small numbers of occurrence records: a test case using cryptic geckos in Madagascar. J Biogeogr. 2007;34(1):102–117. https://doi.org/10.1111/j.1365-2699.2006.01594.x
Shcheglovitova M, Anderson RP. Estimating optimal complexity for ecological niche models: a jackknife approach for species with small sample sizes. Ecol Modell. 2013;269:9–17. https://doi.org/10.1016/j.ecolmodel.2013.08.011
Anderson RP, Dudík M, Ferrier S, Guisan A, J Hijmans R, Huettmann F, et al. Novel methods improve prediction of species’ distributions from occurrence data. Ecography. 2006;29(2):129–151. https://doi.org/10.1111/j.2006.0906-7590.04596.x
Phillips S. A Brief tutorial on MaxEnt. Lessons in Conservation. 2006;3:108–135.
Phillips SJ, Dudík M. Modeling of species distributions with MaxEnt: new extensions and a comprehensive evaluation. Ecography. 2008;31(2):161–175. https://doi.org/10.1111/j.0906-7590.2008.5203.x
Elith J, Phillips SJ, Hastie T, Dudík M, Chee YE, Yates CJ. A statistical explanation of MaxEnt for ecologists. Divers Distrib. 2011;17(1):43–57. https://doi.org/10.1111/j.1472-4642.2010.00725.x
Halvorsen R. A strict maximum likelihood explanation of MaxEnt, and some implications for distribution modelling. Sommerfeltia. 2013;36:1–132. https://doi.org/10.2478/v10208-011-0016-2
Renner IW, Warton DI. Equivalence of MaxEnt and Poisson point process models for species distribution modeling in ecology. Biometrics. 2013;69(1):274–281. https://doi.org/10.1111/j.1541-0420.2012.01824.x
Halvorsen R, Mazzoni S, Bryn A, Bakkestuen V. Opportunities for improved distribution modelling practice via a strict maximum likelihood interpretation of MaxEnt. Ecography. 2015;38(2):172–183. https://doi.org/10.1111/ecog.00565
Anderson RP, Gonzalez I. Species-specific tuning increases robustness to sampling bias in models of species distributions: an implementation with MaxEnt. Ecol Modell. 2011;222(15):2796–2811. https://doi.org/10.1016/j.ecolmodel.2011.04.011
Kumar S, Stohlgren TJ. MaxEnt modeling for predicting suitable habitat for threatened and endangered tree Canacomyrica monticola in New Caledonia. Journal of Ecology and the Natural Environment. 2009;1(4):94–98.
Goffinet B, Buck WR, Wall MA. Orthotrichum freyanum (Orthotrichaceae), a new epiphytic moss from Chile. Nova Hedwigia 2007;131:1–11.
Lara F, Garilleti R, Mazimpaka V. A peculiar new Orthotrichum species (Orthotrichaceae, Bryopsida) from central Argentina. Bot J Linn Soc. 2007;155(4):477–482. https://doi.org/10.1111/j.1095-8339.2007.00720.x
Medina R, Lara F, Mazimpaka V, Garilleti R. Orthotrichum norrisii (Orthotrichaceae), a new epiphytic Californian moss. Bryologist. 2008;111(4):670–675. https://doi.org/10.1639/0007-2745-111.4.670
Lara F, Garilleti R, Mazimpaka V. Orthotrichum karoo (Orthotrichaceae), a new species with hyaline-awned leaves from southwestern Africa. Bryologist. 2009;112(1):194–201. https://doi.org/10.1639/0007-2745-112.1.194
Lara F, Garilleti R, Medina R, Mazimpaka V. A new key to the genus Orthotrichum Hedw. in Europe and the Mediterranean region. Cryptogam Bryol. 2009;30(1):129–142.
Plášek V, Sawicki J, Trávníčková V, Pasečná M. Orthotrichum moravicum (Orthotrichaceae), a new moss species from the Czech Republic. Bryologist. 2009;112(2):329–336. https://doi.org/10.1639/0007-2745-112.2.329
Fedosov V, Ignatova E. Orthotrichum dagestanicum sp. nov. (Orthotrichaceae, Musci) – a new species from Dagestan (Eastern Caucasus). Arctoa. 2010;19:69–74. https://doi.org/10.15298/arctoa.19.05
Garilleti R, Shevock JR, Norris DH, Lara F. Orthotrichum mazimpakanum sp. nov. and O. anodon (Orthotrichaceae), two similar species from California. Bryologist. 2011;114(2):346–355. https://doi.org/10.1639/0007-2745-114.2.346
Medina R, Lara F, Mazimpaka V, Shevock JR, Garilleti R. Orthotrichum pilosissimum (Orthotrichaceae), a new moss from arid areas of Nevada with unique axillary hairs. Bryologist. 2011;114(2):316–324. https://doi.org/10.1639/0007-2745.114.2.316
Medina R, Lara F, Goffinet B, Garilleti R, Mazimpaka V. Integrative taxonomy successfully resolves the pseudo-cryptic complex of the disjunct epiphytic moss Orthotrichum consimile s. l. (Orthotrichaceae). Taxon. 2012;61(6):1180–1198.
Sawicki J, Plášek V, Szczecińska M. Molecular studies resolve Nyholmiella (Orthotrichaceae) as a separate genus. J Syst Evol. 2010;48(3):183–194. https://doi.org/10.1111/j.1759-6831.2010.00076.x
Plášek V. Klíč pro determinaci zástupců rodů Orthotrichum a Nyholmiella v České republice. Bryonora. 2012;50:17–33.
Lewinsky J. A synopsis of the genus Orthotrichum Hedw. (Musci, Orthotrichaceae). Bryobrothera. 1993;2:1–59.
Rivas-Martínez S, Rivas-Sáenz S, Penas A. Worldwide bioclimatic classification system. Global Geobotany. 2011;1:1–634. https://doi.org/10.5616/gg110001
Peterson AT. Niches and geographic distributions. In: Peterson AT, Soberón J, Pearson RG, Anderson RP, Martínez-Meyer E, Nakamura M, et al., editors. Ecological niches and geographic distributions. Princeton, NJ: Princeton University Press; 2011. p. 23–46. (Monographs in Population Biology; vol 49). https://doi.org/10.1515/9781400840670.23
Guillera-Arroita G, Lahoz-Monfort JJ, Elith J, Gordon A, Kujala H, Lentini PE, et al. Is my species distribution model fit for purpose? Matching data and models to applications. Glob Ecol Biogeogr. 2015;24(3):276–292. https://doi.org/10.1111/geb.12268
Phillips SJ, Dudík M, Elith J, Graham CH, Lehmann A, Leathwick J, et al. Sample selection bias and presence-only distribution models: implications for background and pseudo-absence data. Ecol Appl. 2009;19(1):181–197. https://doi.org/10.1890/07-2153.1
Fourcade Y, Engler JO, Rödder D, Secondi J. Mapping species distributions with MaxEnt using a geographically biased sample of presence data: a performance assessment of methods for correcting sampling bias. PLoS One. 2014;9(5):e97122. https://doi.org/10.1371/journal.pone.0097122
QGIS Development Team. QGIS Geographic Information System [Internet]. 2016 [cited 2017 Apr 28]. Available from: http://www.qgis.org
Boria RA, Olson LE, Goodman SM, Anderson RP. Spatial filtering to reduce sampling bias can improve the performance of ecological niche models. Ecol Modell. 2014;275:73–77. https://doi.org/10.1016/j.ecolmodel.2013.12.012
Anderson RP, Raza A. The effect of the extent of the study region on GIS models of species geographic distributions and estimates of niche evolution: preliminary tests with montane rodents (genus Nephelomys) in Venezuela. J Biogeogr. 2010;37(7):1378–1393. https://doi.org/10.1111/j.1365-2699.2010.02290.x
Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A. Very high resolution interpolated climate surfaces for global land areas. Int J Climatol. 2005;25(15):1965–1978. https://doi.org/10.1002/joc.1276
Chang KT. Introduction to geographic information systems. Boston, MA: McGraw-Hill Higher Education; 2008.
GDAL – Geospatial Data Abstraction Library: Version 2.1.0 [Internet]. 2016 [cited 2017 Apr 28]. Available from: http://www.gdal.org
Warren DL, Glor RE, Turelli M. Environmental niche equivalency versus conservatism: quantitative approaches to niche evolution. Evolution. 2008;62(11):2868–2883. https://doi.org/10.1111/j.1558-5646.2008.00482.x
Warren DL, Glor RE, Turelli M. ENMTools: a toolbox for comparative studies of environmental niche models. Ecography. 2010;33(3):607–611. https://doi.org/10.1111/j.1600-0587.2009.06142.x
Mbatudde M, Mwanjololo M, Kakudidi EK, Dalitz H. Modelling the potential distribution of endangered Prunus africana (Hook. f.) Kalkm. in East Africa. Afr J Ecol. 2012;50(4):393–403. https://doi.org/10.1111/j.1365-2028.2012.01327.x
Pradhan P, Dutta A, Roy A, Basu S, Acharya K. Inventory and spatial ecology of macrofungi in the Shorea robusta forest ecosystem of lateritic region of West Bengal. Biodiversity. 2012;13(2):88–99. https://doi.org/10.1080/14888386.2012.690560
Pradhan P. Strengthening MaxEnt modelling through screening of redundant explanatory bioclimatic variables with variance inflation factor analysis. Researcher. 2016;8(5):29–34.
Chefaoui RM, Lobo JM. Assessing the effects of pseudo-absences on predictive distribution model performance. Ecol Modell. 2008;210(4):478–486. https://doi.org/10.1016/j.ecolmodel.2007.08.010
Barve N, Barve V, Jiménez-Valverde A, Lira-Noriega A, Maher SP, Peterson AT, et al. The crucial role of the accessible area in ecological niche modeling and species distribution modeling. Ecol Modell. 2011;222(11):1810–1819. https://doi.org/10.1016/j.ecolmodel.2011.02.011
Acevedo P, Jiménez‐Valverde A, Lobo JM, Real R. Delimiting the geographical background in species distribution modelling. J Biogeogr. 2012;39(8):1383–1390. https://doi.org/10.1111/j.1365-2699.2012.02713.x
Barbet-Massin M, Jiguet F, Albert CH, Thuiller W. Selecting pseudo-absences for species distribution models: how, where and how many? Methods Ecol Evol. 2012;3(2):327–338. https://doi.org/10.1111/j.2041-210x.2011.00172.x
VanDerWal J, Shoo LP, Graham C, Williams SE. Selecting pseudo-absence data for presence-only distribution modeling: how far should you stray from what you know? Ecol Modell. 2009;220(4):589–594. https://doi.org/10.1016/j.ecolmodel.2008.11.010
Longton R. Reproductive biology and life-history strategies. Advances in Bryology. 1997;6(65):101.
Wyatt R. Population ecology of bryophytes. Journal of the Hattori Botanical Laboratory. 1982;52:179–198.
Lönnell N, Hylander K, Jonsson BG, Sundberg S. The fate of the missing spores patterns of realized dispersal beyond the closest vicinity of a sporulating moss. PLoS One. 2012;7(7):e41987. https://doi.org/10.1371/journal.pone.0041987
Sundberg S. Spore rain in relation to regional sources and beyond. Ecography. 2013;36(3):364–373. https://doi.org/10.1111/j.1600-0587.2012.07664.x
Stoneburner A, Lane DM, Anderson LE. Spore dispersal distances in Atrichum angustatum (Polytrichaceae). Bryologist. 1992;95(3):324–328. https://doi.org/10.2307/3243491
Snäll T, Fogelqvist J, Ribeiro P, Lascoux M. Spatial genetic structure in two congeneric epiphytes with different dispersal strategies analysed by three different methods. Mol Ecol. 2004;13(8):2109–2119. https://doi.org/10.1111/j.1365-294x.2004.02217.x
Sundberg S. Larger capsules enhance short-range spore dispersal in Sphagnum, but what happens further away? Oikos. 2005;108(1):115–124. https://doi.org/10.1111/j.0030-1299.2005.12916.x
Miles C, Longton R. Deposition of moss spores in relation to distance from parent gametophytes. J Bryol. 1992;17(2):355–368. https://doi.org/10.1179/jbr.1992.17.2.355
Soro A, Sundberg S, Rydin H. Species diversity, niche metrics and species associations in harvested and undisturbed bogs. J Veg Sci. 1999;10(4):549–560. https://doi.org/10.2307/3237189
Miller NG, McDaniel SF. Bryophyte dispersal inferred from colonization of an introduced substratum on Whiteface Mountain, New York. Am J Bot. 2004;91(8):1173–1182. https://doi.org/10.3732/ajb.91.8.1173
Hutsemekers V, Dopagne C, Vanderpoorten A. How far and how fast do bryophytes travel at the landscape scale? Divers Distrib. 2008;14(3):483–492. https://doi.org/10.1111/j.1472-4642.2007.00454.x
Radosavljevic A, Anderson RP. Making better MaxEnt models of species distributions: complexity, overfitting and evaluation. J Biogeogr. 2014;41(4):629–643. https://doi.org/10.1111/jbi.12227
Zhang L, Cao B, Bai C, Li G, Mao M. Predicting suitable cultivation regions of medicinal plants with MaxEnt modeling and fuzzy logics: a case study of Scutellaria baicalensis in China. Environ Earth Sci. 2016;75(5):361. https://doi.org/10.1007/s12665-015-5133-9
Swets JA. Measuring the accuracy of diagnostic systems. Science. 1988;240(4857):1285–1293. https://doi.org/10.1126/science.3287615
Fielding AH, Bell JF. A review of methods for the assessment of prediction errors in conservation presence/absence models. Environ Conserv. 1997;24(1):38–49. https://doi.org/10.1017/s0376892997000088
Benítez Á, Prieto M, Aragón G. Large trees and dense canopies: key factors for maintaining high epiphytic diversity on trunk bases (bryophytes and lichens) in tropical montane forests. Forestry. 2015;88(5):521–527. https://doi.org/10.1093/forestry/cpv022
Glime JM. Bryophyte ecology. Vol 1. Physiological ecology. Ebook sponsored by Michigan Technological University and the International Association of Bryologists [Internet]. 2007 [cited 2017 May 12]. Available form: http://www.bryoecol.mtu.edu/
Bates J, Roy D, Preston C. Occurrence of epiphytic bryophytes in a tetrad transect across southern Britain. 2. Analysis and modelling of epiphyte-environment relationships. J Bryol. 2004;26(3):181–197. https://doi.org/10.1179/037366804x5288
Marini L, Nascimbene J, Nimis PL. Large-scale patterns of epiphytic lichen species richness: photobiont-dependent response to climate and forest structure. Sci Total Environ. 2011;409(20):4381–4386. https://doi.org/10.1016/j.scitotenv.2011.07.010
Sumarga E. A comparison of logistic regression, geostatistics and MaxEnt for distribution modeling of a forest endemic; a pilot study on lobel’s maple at Mt. Pizzalto, Italy [Master thesis]. Enschede: University of Twente; 2011.
DOI: https://doi.org/10.5586/asbp.3543
|
|
|