|Support type:||Scholarships in Brazil - Scientific Initiation|
|Effective date (Start):||January 01, 2021|
|Effective date (End):||December 31, 2021|
|Field of knowledge:||Agronomical Sciences - Forestry Resources and Forestry Engineering - Nature Conservation|
|Principal Investigator:||Lilian Casatti|
|Grantee:||Yoshiaki Nogueira Miyazaki|
|Home Institution:||Instituto de Biociências, Letras e Ciências Exatas (IBILCE). Universidade Estadual Paulista (UNESP). Campus de São José do Rio Preto. São José do Rio Preto , SP, Brazil|
Understanding the effects of land use changes have been recently gaining attention in freshwater ecology studies. It is noteworthy that, ecologists and ichthyologists have been increasingly used landscape variables to identify and comprehend the patterns of loss of fish biodiversity in aquatic systems. On the other hand, there is no standardization in the scales and methodologies applied for the acquisition of geographical information on land use and occupation. In general, two methodologies with two different spatial patterns have been used in stream ecology studies to obtain such information: 1. Circular (also known as radial); and 2. Riparian buffer (also known as continuous or linear) delimitations. The aim of this project is to evaluate the responses of stream fish assemblages to these two methods of obtaining information on land use and cover in streams. For this, circular (100, 500, and 100 m radius) and riparian (60 and 100 m) buffers will be traced from the georeferenced point in the ArcGis Software, based on the dataset from 75 streams sampled in the Machado River basin - RO. From these buffers, the proportion of native forest will be obtained and later used as the predictor variable. The response variables will be the richness and abundance of sensitive and tolerant fish species. The predictor and responses variables will be modeled using Generalized Mixed Additive Models. Thus, based on the Akaike criteria and R2 adj values, it will be possible to determine which buffer will have the greatest explanatory power on the fish assemblages structure indicators.