Predicting Tachypleus gigas Spawning Distribution with Climate Change in Northeast Coast of India
Siddhartha Pati 1  
,   Salwa Shahimi 2  
,   Debabrata Nandi 3  
,   Tanmay Sarkar 4  
,   Satya Narayan Acharya 3  
,   Hassan I Sheikh 5  
,   Tanupriya Choudhury 6  
,   Akbar John 7  
,   Dipti Kanta Acharya 8  
,   Bryan R. Nelson 1  
,   Bisnu Prasad Dash 9  
,   Edinur Hisham Atan 10  
 
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1
Institute of Tropical Biodiversity and Sustainable Development, University Malaysia Terengganu, 21030 Kuala Nerus, Terengganu, Malaysia.
2
Faculty of Science and Marine Environment, Universiti Malaysia Terengganu, 21030 Kuala Nerus, Terengganu, Malaysia.
3
Department of Remote Sensing and GIS, North Orissa University, Takatpur, 757003, Odisha, India.
4
Malda Polytechnic, West Bengal State Council of Technical Education, 73210,West Bengal, India.
5
Faculty of Fisheries and Food Science, University Malaysia Terengganu, 21030, Kuala Nerus, Terengganu, Malaysia.
6
University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India.
7
INOCEM Research Station, Kulliyyah of Science, International Islamic University Malaysia, 25200 Kuantan, Pahang, Malaysia.
8
Association of Biodiversity Conservation and Research, Devine Colony, 756001 Balasore,Odisha, India.
9
Horseshoe Crab Research Unit, Department of Biosciences and Biotechnology, Fakir Mohan University, Balasore, India
10
Universiti Sains Malaysia, Health Campus, Kubang Kerian 16150, Kelantan, Malaysia
CORRESPONDING AUTHOR
Siddhartha Pati   

Institute of Tropical Biodiversity and Sustainable Development, University Malaysia Terengganu, 21030 Kuala Nerus, Terengganu, Malaysia.
 
 
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ABSTRACT
Species distribution models are used to predict ideal grounds, species range, and spatial shifts in an ecology over a span of time. With an aim to use Maximum entropy model (MaxEnt), presence records and pseudo-absence points are used to predict the Tachypleus gigas spawning activity for 2030 and 2050 in northeast India. The bearings of sixty T. gigas spawning grounds identified in 2018 were inserted into ArcGIS v.10.1. Meanwhile, 19 environment variables were inserted into MaxEnt v. 3.3.3, before the model performance was tested using receiver operational characteristics and area under curve (AUC). With an AUC of 0.978,85% was achieved for isothermality (bio3) and 74% for temperature (x̄= average) of the wettest quarter (bio8), all of which were inserted into ArcGIS to produce spatial maps. Although we learnt that T. gigas are still spawning in Odisha in 2030 and 2050, their distribution range is predicted to shrink due to the coastal morphology change. The climate conditions in Odisha revolve with the monsoon, summer and winter seasons from which, temperature variations do not only influence the annual absence/presence of spawning adults but also, the survival of juveniles in natal beaches. The use of MaxEnt offers novelty to predict population sustainability of arthropods characterized by oviparous spawning (horseshoe crabs, turtles, terrapins and crocodiles) through which, the government of India can take advantage of the present data to initiate the coastal rehabilitation measures to preserve their spawning grounds.