Remote Sensing of Environmental Drivers Influencing the Movement Ecology of Sympatric Wild and Domestic Ungulates in Semi-Arid Savannas, a Review

Abstract

Interfaces between protected areas and their peripheries in southern Africa are subject to interactions between wildlife and livestock that vary in frequency and intensity. In these areas, the juxtaposition between production and conservation land uses in a context of increasing anthropisation can create issues associated with human-wildlife coexistence and raises concerns for biodiversity conservation, local development and livelihoods. This literature review aimed at addressing the need to consolidate and gather in one article current knowledge on potential uses of satellite remote sensing (SRS) products by movement ecologists to investigate the sympatry of wildlife/domestic ungulates in savanna interface environments. A keyword querying process of peer reviewed scientific paper, thesis and books has been implemented to identify references that (1) characterize the main environmental drivers impacting buffalo (Syncerus caffer caffer) and cattle (Bos taurus & Bos indicus) movements in southern Africa environments, (2) describe the SRS contribution to discriminate and characterize these drivers. In total, 327 references have been selected and analyzed. Surface water, precipitation, landcover and fire emerged as key drivers impacting the buffalo and cattle movements. These environmental drivers can be efficiently characterized by SRS, mainly through open-access SRS products and standard image processing methods. Applying SRS to better understand buffalo and cattle movements in semi-arid environments provides an operational framework that could be replicated in other type of interface where different wild and domestic species interact. There is, however, a need for animal movement ecologists to reinforce their knowledge of remote sensing and/or to increase pluridisciplinary collaborations.

Characterization of Buffalo/Cattle Interactions for Assessing Pathogen Transmission

“…Nonetheless, there is a need to further develop mechanistic animal movement, contact and interaction models that integrate independent and validated environmental SRS data enabling landscape-scale analysis of interspecies contact and interaction. Such models could benefit from the integration of especially characterized environmental SRS data while extending their application capacities to different environmental and ecological contexts (Neumann et al, 2015;Rumiano et al, 2020). Several SRS methodologies have already been developed to characterize spatial and temporal variations of environmental drivers, such as surface water (Naidoo et al, 2020) and vegetation (Zengeya et al, 2015), in relation to buffalo and cattle movements.…”

COMBINED USE OF REMOTE SENSING AND SPATIAL MODELLING: WHEN SURFACE WATER IMPACTS BUFFALO (SYNCERUS CAFFER CAFFER) MOVEMENTS IN SAVANNA ENVIRONMENTS

“…Monitoring more individuals and integrating this data in the calibration process should potentially strengthen the model's capacity to reproduce buffalo herd dynamics. Moreover, if surface water directly impacts buffalo movements in space and time (Chamaillé-Jammes et al, 2016), other environmental variables may be taken into account to accurately simulate buffalo movements at the landscape scale (Rumiano et al, 2020). Indeed, the temporal structuration of the model in two behavioural phases (cf.…”

“…However, dynamic animal movement models that combine SRS with GPS telemetry in order to specifically characterize speciesenvironment interactions in space and time at a landscape scale are lacking. Indeed, SRS derived environmental data are rarely used in combination with spatial modelling although the understanding of animal movement and their associated ecological mechanisms could benefit from such approaches (Neumann et al, 2015;Rumiano et al, 2020).…”

Methods for Implementing Integrated Step-Selection Functions with Incomplete Data

“…Thanks to recent advances in animal tracking (Cagnacci et al, 2010;Williams et al, 2019;Beardsworth et al, 2022) and remote sensing technologies (Toth & Jóźków, 2016;Rumiano et al, 2020), new opportunities and analytical tools have emerged for studying how animals move and interact with their environment (Tomkiewicz et al, 2010;Kays et al, 2015).…”

“…Understanding how animals move across the landscape, what habitats they prefer, and what resources they select are fundamental questions in movement ecology (Nathan, 2008). Thanks to recent advances in animal tracking (Cagnacci et al, 2010; Williams et al, 2019; Beardsworth et al, 2022) and remote sensing technologies (Toth & Jóźków, 2016; Rumiano et al, 2020), new opportunities and analytical tools have emerged for studying how animals move and interact with their environment (Tomkiewicz et al, 2010; Kays et al, 2015). Methods commonly used to analyze animal movement data, including step-selection analyses (Fortin et al, 2005; Thurfjell et al, 2014; Fieberg et al, 2021) and hidden Markov models (Michelot et al, 2016), require animal locations (terms in bold at first occurrence are defined in Table 1) that are collected at a constant sampling frequency, leading to data that are equally spaced in time.…”