AI Summary & Key Takeaways
AI InsightTo better understand the performance of (_ ^(α^*))D_MM , further studies should be generated using various types of real ecological data.
📌 3 Key Takeaways
Abstract
In the present study, a new estimator ((_ ^(α^*))D_MM ) is proposed to measure species richness. Its’ essential inputs are alfa (α) scale parameters of Margalef (D_MG ) and Menhinick (D_MN ) indices. To evaluate the performance of (_ ^(α^*))D_MM , both hypothetical and natural community datasets were used. The computations were performed using a spreadsheet program created for (_ ^(α^*))D_MM . The new proposed estimator is also integrated into the BİÇEB software. According to estimation results, (_ ^(α^*))D_MM seems to be a better form rather than D_MG and D_MN. Therefore it may be employed for comparing species richness of the natural communities. To better understand the performance of (_ ^(α^*))D_MM , further studies should be generated using various types of real ecological data.