IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Species Distribution Models (SDM) – A Strategic Tool for Predicting Suitable Habitats for Conserving the Target Species: GIS and Special Distribution Modelling (SDM)

Species Distribution Models (SDM) – A Strategic Tool for Predicting Suitable Habitats for Conserving the Target Species: GIS and Special Distribution Modelling (SDM)
View Sample PDF
Author(s): Balaguru Balakrishnan (Jamal Mohamed College, India), Nagamurugan Nandakumar (Government Arts College Melur, India), Soosairaj Sebastin (St. Joseph's College, Tiruchirappalli, India)and Khaleel Ahamed Abdul Kareem (Jamal Mohamed College, India)
Copyright: 2019
Pages: 14
Source title: Environmental Information Systems: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-5225-7033-2.ch023

Purchase


Abstract

Conservation of the species in their native landscapes required understanding patterns of spatial distribution of species and their ecological connectivity through Species Distribution Models (SDM) by generation and integration of spatial data from different sources using Geographical Information System (GIS) tools. SDM is an ecological/spatial model which combines datasets and maps of occurrence of target species and their geographical and environmental variables by linking various algorithms together, that has been applied to either identify or predict the regions fulfilling the set conditions. This article is focused on comprehensive review of spatial data requirements, statistical algorithms and softwares used to generate the SDMs. This chapter also includes a case study predicting the suitable habitat distribution of Gnetum ula, an endemic and vulnerable plant species using maximum entropy (MaxEnt) species distribution model for species occurrences with inputs from environmental variables such as bioclimate and elevation.

Related Content

Hendra Wijaya, Zaekhan Zaekhan, Lukman Junaidi, Ning Ima Arie Wardayanie, Yuliasri Ramadhani Meutia, Nona Widharosa, Tita Rosita. © 2023. 20 pages.
Sufiati Bintanah, Yuliana Noor Setiawati Ulvie, Hapsari Sulistya Kusuma, Firdananda Fikri Jauharany, Hersanti Sulistyaningrum. © 2023. 20 pages.
Diana Nur Afifah, Syafira Noor Pratiwi, Ahmad Ni'matullah Al-Baarri, Denny Nugroho Sugianto. © 2023. 21 pages.
Maria Belgis, Nur Fathonah Sadek, Ardiyan Dwi Masahid, Dian Purbasari, Dyah Ayu Savitri. © 2023. 18 pages.
Sri Mulyani, Yoyok Budi Pramono, Isti Handayani. © 2023. 22 pages.
Dessy Ariyanti, Aprilina Purbasari, Dina Lesdantina, Filicia Wicaksana, Wei Gao. © 2023. 15 pages.
Uyi Sulaeman, Ahmad Zuhairi Abdullah, Shu Yin. © 2023. 19 pages.
Body Bottom