Svojstva podataka o raznolikosti vrsta prikupljenih ljudskim opažanjem iz baze Global Biodiversity Information Facility (GBIF)

master's thesis

• Title (english): Properties of species diversity Data Collected by Human Observation from the Global Biodiversity Information Facility (GBFI) Database
• Author: Ivan Šapina
• Mentor: Damjan Franjević (mentor)
• Mentor: Josip Skejo (komentor)
• Committee member: Sven Jelaska (predsjednik povjerenstva)
• Committee member: Ivana Maguire (član povjerenstva)
• Committee member: Zorica Petrinec (član povjerenstva)
• Committee member: Luka Valožić (član povjerenstva)
• Committee member: Darko Tibljaš (član povjerenstva)
• Granter: University of Zagreb; Faculty of Science; (Department of Biology); Zagreb
• Defense date and country: 2022-09-29, Croatia
• Scientific / art field, discipline and subdiscipline: NATURAL SCIENCES; Biology

Abstract

Ljudsko opažanje stvara velike količine podataka o raznolikosti vrsta. Tako prikupljeni podatci
sve češće se koriste u ekološkim istraživanjima. Poznate su mnoge pristranosti ovih podataka i
načini ispravljanja istih, ali do sada ljudsko opažanje nije istraženo kao metoda prikupljanja
podataka o raznolikosti svih dostupnih svojti. Cilj ovog rada je zaključiti svojstva ljudskog
opažanja kao metode uzorkovanja raznolikosti vrsta analiziranjem podataka koje stvara; pod
pretpostavkom kako pristranosti podataka bolje opisuju kolektivno ponašanje ljudi prilikom
opažanja nego samu raznolikost vrsta. Podatke sam preuzeo s javno dostupne mrežne baze
Global Biodiversity Information Facility za odabrane države u periodu od 22 godine. Podatke
sam analizirao pomoću mjere bogatstva vrsta, heterogenosti i prostorne raspodjele. Za sve
metode postoje teoretske vrijednosti i svojstva koje postižu u hipotetskim situacijama i time
sam usporedio dobivene rezultate. Rezultati su pokazali da podatci imaju logaritamski
normalnu raspodjelu vrsta i korisnika, broj vrsta ovisi o broju opažanja i kako ljudsko opažanje
vrsta nije nasumično. Također su podatci pokazali značajnu prostornu grupiranost. Zaključio
sam kako podatci koje ljudsko opažanje prikuplja najbolje opisuje interakciju ljudi s
organizmima za ona područja gdje čovjek obitava. Takvi podatci svoj najveći potencijal
ostvaruju pri opisivanju ljudskog ponašanja unutar okoliša.

Abstract (english)

Human observation is creating a large amount of species diversity data. Data collected in this
manner is being used more frequently in ecological research. Many biases are known for this
type of data and methods for correcting them, but still there is no research which investigates
human observation as a method for collecting species diversity data especially for all available
taxa. Goal of this thesis is to deduce features of human observation as a method for sampling
species diversity, by analyzing data which it generates; under the assumption that data bias
better describes collective human behavior while observing than diversity itself. Data was
downloaded from the open access internet database Global Biodiversity Information Facility
for selected states for a 22-year period. I have analyzed the data using species richness,
heterogeneity and spatial distribution. For all methods there are theoretical values and features
which can be achieved in hypothetical situations and using them I have compared given results.
Results show that data has a logarithmic normal distribution of species, that the number of
species depends on the number of observation and that human observation of species is not
random. Data also shows significant spatial grouping. I have deduced that human observation
data best describes the interaction between humans and organisms for areas that humans visit.
This kind of data achieves its fullest potential while describing human behavior in environment.

• Keywords: građanska znanost; raznolikost; ponašanje; raspodjela; akumulacija; rarefakcija
• Keywords (english): citizen science; diversity; behavior; distribution; accumulation; rarefaction
• Language: croatian
• URN:NBN: urn:nbn:hr:217:025890
• Study programme: Title: Enviromental Sciences; Study programme type: university; Study level: graduate; Academic / professional title: magistar/magistra struke znanosti o okolišu (magistar/magistra struke znanosti o okolišu)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Embargoed access; Embargo expiration date: 2024-09-29
• Created on: 2022-10-21 10:09:16