Remotely sensed agricultural modification improves prediction of suitable habitat for a threatened lizard. Issue 5 (4th May 2018)

• Record Type: Journal Article
• Authors: Wong, David T. Y.; Osborne, William S.; Sarre, Stephen D.; Gruber, Bernd
• Is Part Of: International journal of geographical information science. Volume 32:Issue 5(2018)
• Page Start: 1006
• Page End: 1025
• Publication Date: 2018-05-04
• Subjects: MaxEnt -- rare species -- species distribution model -- vegetation type -- human disturbance; Geography -- Data processing -- Periodicals; Information storage and retrieval systems -- Periodicals; Géomatique -- Périodiques; Systèmes d'information -- Périodiques; 910.285
• DOI: 10.1080/13658816.2018.1428747
• Languages: English
• ISSNs: 1365-8816

Abstract

ABSTRACT: The geographical distribution of a species is limited by factors such as climate, resources, disturbances and species interactions. Environmental niche models attempt to encapsulate these limits and represent them spatially but do not always incorporate disturbance factors. We constructed MaxEnt models derived from a remotely sensed vegetation classification with, and without, an agricultural modification variable. Including agricultural modification improved model performance and led to more sites with native vegetation and fewer sites with exotic or degraded native vegetation being predicted suitable for A. parapulchella . Analysis of a relatively well-surveyed sub-area indicated that including agricultural modification led to slightly higher omission rates but markedly fewer likely false positives. Expert assessment of the model based on mapped habitat also suggested that including agricultural modification improved predictions. We estimate that agricultural modification has led to the destruction or decline of approximately 30–35% of the most suitable habitat in the sub-area studied and approximately 20–25% of suitable habitat across the entire study area, located in the Australian Capital Territory, Australia. Environmental niche models for a range of species, particularly habitat specialists, are likely to benefit from incorporating agricultural modification. Our findings are therefore relevant to threatened species planning and management, particularly at finer spatial scales.