In Korea, urbanization has threatened the habitat of wild animals.To protect and manage them living in cities, it is significant to suggest strategies that considers the habitat suitability and the species distribution across the urban ecosystem. Since 1986, the government has investigated species, however, there were problems in that the number of data collected was not enough and the characteristics of the habitats in the urban areas were not reflected.To supplement these problems, citizen science data are being discussed. Despite the reliability of the data,the potentiality of citizen science data is high. In this research, we integrate expert survey data with citizen-science data(NATURING) and try to estimate the distribution of urban birds species. A total of 4 species of birds inhabiting Suwon-city, were selected.
Through the sampling method, 3 datasets are established: expert survey data, citizen-science data, and integrated data. In the method of integrating expert data and citizen science data, the combination ratio is changed, or the number of model simulations is increased. Afterwards, we estimate the species distribution and habitat probability through MaxENT. After comparing the covariance and deviation of each dataset's result, the model accuracy for each dataset is determined.
Results/Conclusions
The results of the species distribution estimation, which simulated the MaxENT model 5 times by combining 80% of expert survey data and 20% of citizen-science data, were compared with the results of expert survey and citizen-science data. As a result, the probability of inhabitation in urban areas for each bird species increased overall, and more actual species could be estimated. Also, there was a large deviation in the probability of habitation.The deviation of the habitat probability was different for each species, and the new species was identified at the point where the deviation of the habitat probability was large. It is expected that further progress will be needed toward reducing spatial uncertainty in the habitat probability. If a spatialized species distribution map is produced by integrating citizen-science data and expert survey data, it can help make policy decisions such as the selection of urban ecosystem priority management areas and can be used as a basis for conducting detailed species surveys in areas with high habitat probability.
