Bridging the gap between movement data and connectivity analysis using the Time-Explicit Habitat Selection (TEHS) model

Denis Valle; Nina Attias; Joshua A Cullen; Mevin B Hooten; Aline Giroux; Luiz Gustavo R Oliveira-Santos; Arnaud L J Desbiez; Robert J Fletcher Jr

doi:10.1186/s40462-024-00461-1

Bridging the gap between movement data and connectivity analysis using the Time-Explicit Habitat Selection (TEHS) model

Mov Ecol. 2024 Mar 1;12(1):19. doi: 10.1186/s40462-024-00461-1.

Authors

Denis Valle^#¹, Nina Attias^#^{2

3}, Joshua A Cullen⁴, Mevin B Hooten⁵, Aline Giroux⁶, Luiz Gustavo R Oliveira-Santos⁶, Arnaud L J Desbiez^{3

7

8}, Robert J Fletcher Jr⁹

Affiliations

¹ School of Forest, Fisheries, and Geomatics Sciences, University of Florida, Gainesville, FL, USA. drvalle@ufl.edu.
² School of Forest, Fisheries, and Geomatics Sciences, University of Florida, Gainesville, FL, USA.
³ Instituto de Conservação de Animais Silvestres, Campo Grande, Mato Grosso do Sul, Brazil.
⁴ Department of Earth, Ocean, and Atmospheric Science, Florida State University, Tallahassee, FL, USA.
⁵ Department of Statistics and Data Sciences, University of Texas at Austin, Austin, TX, USA.
⁶ Ecology Department, Federal University of Mato Grosso do Sul, Campo Grande, Mato Grosso do Sul, Brazil.
⁷ Royal Zoological Society of Scotland, Murrayfield, Edinburgh, UK.
⁸ Instituto de Pesquisas Ecologicas, Nazare Paulista, Sao Paulo, Brazil.
⁹ Department of Wildlife Ecology and Conservation, University of Florida, P.O. Box 110410, Gainesville, FL, USA.

^# Contributed equally.

Abstract

Background: Understanding how to connect habitat remnants to facilitate the movement of species is a critical task in an increasingly fragmented world impacted by human activities. The identification of dispersal routes and corridors through connectivity analysis requires measures of landscape resistance but there has been no consensus on how to calculate resistance from habitat characteristics, potentially leading to very different connectivity outcomes.

Methods: We propose a new model, called the Time-Explicit Habitat Selection (TEHS) model, that can be directly used for connectivity analysis. The TEHS model decomposes the movement process in a principled approach into a time and a selection component, providing complementary information regarding space use by separately assessing the drivers of time to traverse the landscape and the drivers of habitat selection. These models are illustrated using GPS-tracking data from giant anteaters (Myrmecophaga tridactyla) in the Pantanal wetlands of Brazil.

Results: The time model revealed that the fastest movements tended to occur between 8 p.m. and 5 a.m., suggesting a crepuscular/nocturnal behavior. Giant anteaters moved faster over wetlands while moving much slower over forests and savannas, in comparison to grasslands. We also found that wetlands were consistently avoided whereas forest and savannas tended to be selected. Importantly, this model revealed that selection for forest increased with temperature, suggesting that forests may act as important thermal shelters when temperatures are high. Finally, using the spatial absorbing Markov chain framework, we show that the TEHS model results can be used to simulate movement and connectivity within a fragmented landscape, revealing that giant anteaters will often not use the shortest-distance path to the destination patch due to avoidance of certain habitats.

Conclusions: The proposed approach can be used to characterize how landscape features are perceived by individuals through the decomposition of movement patterns into a time and a habitat selection component. Additionally, this framework can help bridge the gap between movement-based models and connectivity analysis, enabling the generation of time-explicit connectivity results.

Keywords: Connectivity analysis; Giant anteater; Landscape resistance; Landscape use; Movement ecology; Step selection; Wildlife corridors.

Abstract

Grants and funding