Page 43 - IPCoSME 2021
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1  INTERNATIONAL POSTGRADUATE CONFERENCE ON SCIENCE AND MARINE ENVIRONMENT 2021
                  st
                                                                                             (IPCoSME 2021)
                                        “Environmental Sustainability Enhancement Through the Collaboration of Sciences”


                                                         RE-01



                   WHEN TO STOP SAMPLING? ESTIMATING FISH SPECIES RICHNESS IN
                                    TASIK KENYIR, PENINSULAR MALAYSIA


                         MOHAMAD AQMAL-NASER  AND AMIRRUDIN B AHMAD                         1, 2, *
                                                          1

                  1  Biological and Ecological Research Group, Universiti Malaysia Terengganu, 21030, Kuala
                                               Nerus, Terengganu, Malaysia
                    2  Terrestrial Biodiversity and Aquatic Research, Institute of Tropical Biodiversity and
                 Sustainable Management, Universiti Malaysia Terengganu, 21030, Kuala Nerus, Terengganu,
                                                        Malaysia


               *Corresponding author email: amirrudin@umt.edu.my

               Abstract: The information on species richness is critical especially for the conservation of

               biodiversity, but requires exhaustive sampling efforts and proper detection methods in order to
               get a reliable data. Hence, we explore the use of nine non-parametric estimators to estimate

               fish species richness at Tasik Kenyir, Terengganu, Peninsular Malaysia. The performances of
               each estimator were then evaluated to determine the precision, bias, and accuracy of each

               estimator.  The  species  richness  estimators  predicted  a  minimum  of  61.00  ±  10.51  and  a

               maximum of 79.18 fish species at Tasik Kenyir, an additional of three to 21.18 species. The
               predictions were closed to the 58 observed species, indicating the usefulness of those estimators

               for the well-collected data and species-rich ecosystem. The results were concurrent with the
               values  of  the  adjusted  estimated  range,  sampling  intensity,  percentage  of  inventory

               completeness,  and  inventory  completeness  index.  Chao1  estimator  was  chosen  as  the  best

               species  richness  estimator  for  Tasik  Kenyir  based  on  three  evaluation  criteria  used.  We
               conclude  that  the  application  of  species  richness  estimation  is  reliable,  and  essential  for

               biodiversity assessment in the reservoir systems.

               Keywords: accuracy, biodiversity, freshwater fishes, inventories, sampling effort, (how many)
















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