An evaluation of the plant density estimator the point-centred quarter method (PCQM) using monte carlo simulation

PLoS ONE

Volumn 11, Issue 6, 2016, Pages

  Khan, Md Nabiul Islam ^a,b,c   Hijbeek, Renske ^d,e   Berger, Uta ^b   Koedam, Nico ^d   Grueters, Uwe ^b   Islam, S M Zahirul ^c   Hasan, Md Asadul ^c   Dahdouh Guebas, Farid ^a,d  

^a UNIVERSITÉ LIBRE DE BRUXELLES   (Belgium)

^b DRESDEN UNIVERSITY OF TECHNOLOGY   (Germany)

^c KHULNA UNIVERSITY   (Bangladesh)

^d VRIJE UNIVERSITEIT BRUSSEL   (Belgium)

^e WAGENINGEN UNIVERSITY   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

COMPETITION; GENETIC POLYMORPHISM; MONTE CARLO METHOD; PLANT DENSITY; SAMPLING; STATISTICAL MODEL; VEGETATION; ALGORITHM; COMPUTER SIMULATION; PLANT; POPULATION DENSITY;

ALGORITHMS; COMPUTER SIMULATION; MONTE CARLO METHOD; PLANTS; POPULATION DENSITY;

EID: 84976589544     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0157985     Document Type: Article

References (31)

1. Cottam G. Some Sampling Characteristics of a Population of Randomly Dispersed Individuals. Ecology. 1953; 34: 741-57.
2. Cottam G, Curtis J. The Use of Distance Measures in Phytosociological Sampling. Ecology. 1956: 451-60.
3. Engeman RM, Wildlife D, Aphis U, Box PO, Sugihara RT, Station HF, et al. A comparison of plotless density estimators using Monte Carlo simulation. Ecology. 1994; 75: 1769-79.
4. White N, Engeman RM, Sugihara RT, Krupa HW. A comparison of plotless density estimators using Monte Carlo simulation on totally enumerated field data sets. BMC Ecol. 2008; 8: 6. doi:10.1186/1472-6785-8-6PMID: 18416853.
5. Magnussen S, Kleinn C, Picard N. Two new density estimators for distance sampling. Eur J For Res. 2008; 127: 213-24. doi:10.1007/s10342-007-0197-z.
6. Dahdouh-Guebas F, Koedam N. Empirical estimate of the reliability of the use of the Point-Centred Quarter Method (PCQM): Solutions to ambiguous field situations and description of the PCQM+ protocol. For Ecol Manage. 2006; 228: 1-18. doi:10.1016/j.foreco.2005.10.076.
7. Kumarathunge DP, Thattil RO, Nissanka SP. Evaluation of the plotless sampling method to estimate aboveground biomass and other stand parameters in tropical rain forests. Appl Ecol Environ Res. 2011; 9(4): 425-31.
8. Cintrón G, Schaeffer-Novelli Y. Methods for studying mangrove structure. In: Snedaker S, Snedaker J, editors. The Mangrove Ecosystem: Research Methods. UNESCO, Paris, France 1984. p. 1-2.
9. Dahdouh-Guebas F, Van Pottelbergh I, Kairo J, Cannicci S, Koedam N. Human-impacted mangroves in Gazi (Kenya): predicting future vegetation based on retrospective remote sensing, social surveys, and tree distribution. Mar Ecol Prog Ser. 2004; 272: 77-92. doi:10.3354/meps272077.
10. Neukermans G, Kairo JG, Koedam N, Roosevelt AFD. Mangrove species and stand mapping in Gazi bay (Kenya) using Quickbird satellite imagery. Spatial Science. 2007; 52: 75-86.
11. Satyanarayana B, Idris IF, Mohamad A, Husain M-l, Shazili NAM, Dahdouh-guebas F. Mangrove species distribution and abundance in relation to local environmental settings: A case-study at Tumpat, Kelantan Delta, east coast of peninsular Malaysia. Bot Mar. 2010; 53: 79-88. doi:10.1515/BOT.2010.006.
12. Picard N, Kouyate M, Dessard H. Tree Density Estimations Using a Distance Method in Mali Savanna. For Sci. 2005; 51: 7-18.
13. Sheil D, Ducey M, Sidiyasa K, Samsoedin I. A new type of sample unit for the efficient assessment of diverse tree communities in complex forest landscapes. J Trop For Sci. 2003; 15: 117-35.
14. Magnussen S, Boyle TJB. Estimating sample size for inference about the Shannon-Weaver and the Simpson indices of species diversity. For Ecol Manage. 1995; 78: 71-84. doi:10.1016/0378-1127(95)03596-1.
15. Magnussen S. A new composite k- Tree estimator of stem density. Eur J For Res. 2012; 131: 1513-27. doi:10.1007/s10342-012-0619-4.
16. Pollard JH. On distance estimators of density in randomly distributed forests. Biometrics. 1971; 27: 991-1002.
17. Beasom SL, Haucke HH. A Comparison of Four Distance Sampling Techniques in South Texas Live Oak Mottes. Journal of Range Management. 1975; 28(2): 142-4.
18. Engeman RM, Nielson RM, Sugihara RT. Evaluation of optimized variable area transect sampling using totally enumerated field data sets. Environmetrics. 2005; 16: 767-72. doi:10.1002/env.736.
19. Engeman RM, Sugihara RT. Optimization of Variable Area Transect Sampling Using Monte Carlo Simulation. Ecology. 1998; 79: 1425. doi:10.2307/176753.
20. Nielson RM, Sugihara RT, Boardman TJ, Engeman RM. Optimization of ordered distance sampling. Environmetrics. 2004; 15: 119-28. doi:10.1002/env.627.
21. Hijbeek R, Koedam N, Khan MNI, Kairo JG, Schoukens J, Dahdouh-Guebas F. An Evaluation of Plotless Sampling Using Vegetation Simulations and Field Data from a Mangrove Forest. PLoS ONE. 2013; 8(6): E67201. doi:10.1371/journal.pone.0067201 PMID: 23826233.
22. Wilensky U. NetLogo. http://ccl.northwestern.edu/netlogo/. 1999.
23. Baddeley A, Turner R. Spatstat: An R package for analyzing spatial point patterns. Journal of Statistical Software. 2005; 12: 1-42.
24. R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria 2015. Available from: https://www.R-project.org/.
25. Clark PJ, Evans FC. Distance to Nearest Neighbor as a Measure of Spatial Relationships in Populations. Ecology. 1954; 35: 445-53. doi:10.2307/1931034.
26. Berger U, Wagner G, Wolff WF. Virtual biologists observe virtual grasshoppers: An assessment of different mobility parameters for the analysis of movement patterns. Ecol Model. 1999; 115: 119-27. doi:10.1016/S0304-3800(98)00187-2.
27. Zurell D, Berger U, Cabral JS, Jeltsch F, Meynard CN, Münkemüller T, et al. The virtual ecologist approach: simulating data and observers. Oikos. 2010; 119: 622-35. doi: 10.1111/j.1600-0706.2009. 18284.x.
28. Grimm V, Railsback S. Individual-based Modelling and Ecology. 2005.
29. Grimm V, Berger U, Bastiansen F, Eliassen S, Ginot V, Giske J, et al. A standard protocol for describing individual-based and agent-based models. Ecol Model. 2006; 198: 115-26. doi:10.1016/j.ecolmodel.2006.04.023.
30. Grimm V, Berger U, DeAngelis DL, Polhill JG, Giske J, Railsback SF. The ODD protocol: A review and first update. Ecol Model. 2010; 221: 2760-8. doi:10.1016/j.ecolmodel.2010.08.019.
31. Giraudoux P. pgirmess: Data analysis in ecology. R package version 1.5.6. 2012. Available from: http://CRAN.R-project.org/package=pgirmess.