. Crimson Open Access Research Journals | Crimsonpublishers.com
Crimson Publishers Publish With Us Reprints e-Books Video articles

Abstract

Biodiversity Online J

Are Land Climatic Variables Good Predictors for the Distribution of Estuarine Microorganisms? A Study with the Microcrustacean Kalliapseudes Schubarti

  • Rômulo JR1,2* and Gustavo RL1,2,3

    1Instituto da Biodiversidade-IBIO, Brasil

    2Programa de Pós-graduação em Biologia Animal, Universidade Federal do Espírito Santo, Brasil

    3Unidade de Medicina Tropical, Universidade Federal do Espírito Santo, Brasil

    *Corresponding author:Rômulo José Ramos, Instituto da Biodiversidade-IBIO, Vila Velha, ES, Brasil.

Submission: December 06, 202; Published: June 10, 2022

Abstract

The estuarine organisms present limitations in their distribution due to tolerance factors as salinity, sediment type, water temperature, among others. Kalliapseudes schubarti is common in estuaries and slimy plains of the Brazilian south and southeast regions, where it plays an important role in the food chain. Recently, this species was found in areas where its distribution was unknown, as in the county of Guarapari, state of Espírito Santo (ES), Brazil. This occurrence may be suggesting that K. schubarti presents a wider distribution than the expected. Based in this found, by means of ecological niche modeling, we determine its potential distribution, using climatic variables. The first scenario, without ES data, showed that K. schubarti presents distribution from state of Rio Grande do Sul (RS) to the state of Rio de Janeiro. The second scenario, using the ES data, showed that its distribution ranges from RS to the south of state of Bahia (BA). We suggest the Brazilian coast temperatures are not a limitation factor for this species, which occurs in estuarine regions of soft bed rich in organic substance. This sediment, common in the some regions of ES and BA, should be the main factor for the K. schubarti occurrence.

Keywords:Estuaries; Geographical distribution; Bioclimatic parameters; Genetic algorithms; Brazillian coast

Get access to the full text of this article