A multi-method approach to delineate and validate migratory corridors

Bond, M. L., Bradley, C. M., Kiffner, C., Morrison, T. A. and Lee, D. E. (2017) A multi-method approach to delineate and validate migratory corridors. Landscape Ecology, 32(8), pp. 1705-1721. (doi: 10.1007/s10980-017-0537-4)

Abstract

Context: Managers are faced with numerous methods for delineating wildlife movement corridors, and often must make decisions with limited data. Delineated corridors should be robust to different data and models. Objectives: We present a multi-method approach for delineating and validating wildlife corridors using multiple data sources, which can be used conserve landscape connectivity. We used this approach to delineate and validate migration corridors for wildebeest (Connochaetes taurinus) in the Tarangire Ecosystem of northern Tanzania. Methods: We used two types of locational data (distance sampling detections and GPS collar locations), and three modeling methods (negative binomial regression, logistic regression, and Maxent), to generate resource selection functions (RSFs) and define resistance surfaces. We compared two corridor detection algorithms (cost-distance and circuit theory), to delineate corridors. We validated corridors by comparing random and wildebeest locations that fell within corridors, and cross-validated by data type. Results: Both data types produced similar RSFs. Wildebeest consistently selected migration habitat in flatter terrain farther from human settlements. Validation indicated three of the combinations of data type, modeling, and corridor detection algorithms (detection data with Maxent modeling, GPS collar data with logistic regression modeling, and GPS collar data with Maxent modeling, all using cost-distance) far outperformed the other seven. We merged the predictive corridors from these three data-method combinations to reveal habitat with highest probability of use. Conclusions: The use of multiple methods ensures that planning is able to prioritize conservation of migration corridors based on all available information.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Morrison, Dr Thomas
• Authors: Bond, M. L., Bradley, C. M., Kiffner, C., Morrison, T. A., and Lee, D. E.
• College/School: College of Medical Veterinary and Life Sciences > School of Biodiversity, One Health & Veterinary Medicine
• Journal Name: Landscape Ecology
• Publisher: Springer
• ISSN: 0921-2973
• ISSN (Online): 1572-9761
• Published Online: 26 May 2017
• Copyright Holders: Copyright © 2017 Springer Science+Business Media Dordrecht
• First Published: First published in Landscape Ecology 32(8):1705-1721
• Publisher Policy: Reproduced in accordance with the copyright policy of the publisher