Diplomová práce – Prostorová neurčitost geodat v ... - kvhem

ABSTRACTIn the first part of this Master thesis a literature review about uncertainty,taxonomy of uncertainty for ecology and uncertainty in species distribution modellingwas written.Secondly, the dependence of the long-eared owl (Asio otus) on five differentenvironmental variables (predictors), whose values were obtained from maps ofdifferent resolution, was investigated. The aim was to evaluate whether theresolution of maps affects values of the variables and therefore the results ofstudying dependence.In this study we have used perimeters and areas of forest and agriculturalpolygons and total length of their common boundary in the Czech Republic as thecore predictors of species presence. Data on species occurrence has been obtainedfrom the atlas Atlas hnízdního rozšíření ptáků v České republice (Šťastný & kol.,2006). Geodata with different resolutions were used; namely CORINE Land Cover1990 and 2000 with a scale of 1:100 000, DMÚ 25 which scale is 1:25 000 and LPISwith a scale of 1:10 000.To estimate the parameters of the individual predictors in establishedmodels, logistic regression was used as a method for explaining discrete dependentvariable (species presence/absence) according to continuous explanatory variables.The models were then compared by the resulting distribution functions and overlapsof confidence intervals of each parameter.Although the geodata had varying resolution, there were only smalldifferences in the values of the 3 predictors gained from these geodata.Dependence between long-eared owl occurrence and environmental parameterswere found for all geodata sets for 3 predictors - area and perimeter of agriculturalpolygons and area of forest, and in the case of DMÚ/LPIS for forest perimetermoreover.KEYWORDS:uncertainty, species distribution models, SDM, logistic regression, long-eared owl,Asio otus