How free-ranging ungulates with differing water dependencies cope with seasonal variation in temperature and aridity

Boyers, Melinda; Parrini, Francesca; Owen‐Smith, Norman; Erasmus, Barend; Hetem, Robyn S.

doi:10.1093/conphys/coz064

Cited by 22 publications

(25 citation statements)

References 39 publications

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“…For example, a reliance on water may favour the selection of highly efficient muscles to facilitate seasonal migration between regions with adequate forage and water 11 , thereby increasing behavioural flexibility. Despite these physiological and behavioural differences, our previous work showed that both wildebeest and gemsbok displayed similar body temperature profiles in a typical year 7 . Yet, the wildebeest population in the Kalahari region collapsed by 90% during the extreme 1982/3 drought when fences blocked their access to remaining sources of surface water 12 .…”

Section: Introductionmentioning

confidence: 86%

“…The Kalahari region of Botswana represents a semi-arid savanna with a lack of surface water, yet it supports an abundance and diversity of large mammalian herbivores. These ungulates appear to cope with seasonal extremes in temperature and aridity by seeking shade and reducing daytime activity 6 , 7 to reduce evaporative water losses. However, species may differ in their behavioural and physiological responses, as well as their resilience to aridity.…”

Section: Introductionmentioning

confidence: 99%

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Contrasting capabilities of two ungulate species to cope with extremes of aridity

Boyers

Parrini

Owen‐Smith

et al. 2021

Sci Rep

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Southern Africa is expected to experience increased frequency and intensity of droughts through climate change, which will adversely affect mammalian herbivores. Using bio-loggers, we tested the expectation that wildebeest (Connochaetes taurinus), a grazer with high water-dependence, would be more sensitive to drought conditions than the arid-adapted gemsbok (Oryx gazella gazella). The study, conducted in the Kalahari, encompassed two hot-dry seasons with similar ambient temperatures but differing rainfall patterns during the preceding wet season. In the drier year both ungulates selected similar cooler microclimates, but wildebeest travelled larger distances than gemsbok, presumably in search of water. Body temperatures in both species reached lower daily minimums and higher daily maximums in the drier season but daily fluctuations were wider in wildebeest than in gemsbok. Lower daily minimum body temperatures displayed by wildebeest suggest that wildebeest were under greater nutritional stress than gemsbok. Moving large distances when water is scarce may have compromised the energy balance of the water dependent wildebeest, a trade-off likely to be exacerbated with future climate change.

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Section: Introductionmentioning

confidence: 86%

Section: Introductionmentioning

confidence: 99%

Contrasting capabilities of two ungulate species to cope with extremes of aridity

Boyers

Parrini

Owen‐Smith

et al. 2021

Sci Rep

Self Cite

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show abstract

“…Fitting a model with smoothly varying parameters will be appropriate for situations where animals adopt a spectrum of different behaviours rather than switching between distinct, stereotyped behavioural modes. This would include movement behaviours that are driven by continuous variables such as temperature, vegetation quality, or water availability [ 61 ] that could either be included in the model as explicit covariates, or influence behaviour via seasonal or diurnal temporal patterns.…”

Section: Discussionmentioning

confidence: 99%

A hierarchical machine learning framework for the analysis of large scale animal movement data

2021

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Background In recent years the field of movement ecology has been revolutionized by our ability to collect high-accuracy, fine scale telemetry data from individual animals and groups. This growth in our data collection capacity has led to the development of statistical techniques that integrate telemetry data with random walk models to infer key parameters of the movement dynamics. While much progress has been made in the use of these models, several challenges remain. Notably robust and scalable methods are required for quantifying parameter uncertainty, coping with intermittent location fixes, and analysing the very large volumes of data being generated. Methods In this work we implement a novel approach to movement modelling through the use of multilevel Gaussian processes. The hierarchical structure of the method enables the inference of continuous latent behavioural states underlying movement processes. For efficient inference on large data sets, we approximate the full likelihood using trajectory segmentation and sample from posterior distributions using gradient-based Markov chain Monte Carlo methods. Results While formally equivalent to many continuous-time movement models, our Gaussian process approach provides flexible, powerful models that can detect multiscale patterns and trends in movement trajectory data. We illustrate a further advantage to our approach in that inference can be performed using highly efficient, GPU-accelerated machine learning libraries. Conclusions Multilevel Gaussian process models offer efficient inference for large-volume movement data sets, along with the fitting of complex flexible models. Applications of this approach include inferring the mean location of a migration route and quantifying significant changes, detecting diurnal activity patterns, or identifying the onset of directed persistent movements.

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“…Buffalo herds in Hwange National Park remained close to water through the dry season, and sometimes drank twice per day both in the early morning and at dusk (Valls-Fox et al 2018). At the other extreme, gemsbok in the Kalahari region fitted with GPS collars rarely visited places where water was available, except during an extremely dry year (Boyers 2019).…”

Section: What We Knowmentioning

confidence: 99%

“…Collared buffalos in Zimbabwe showed a similar activity pattern to the Kruger National Park animals (Valls‐Fox et al ). In the Schwelle region of Botswana, gemsbok Oryx gazella , but not wildebeest, became proportionately more active at night during the hot dry season than during the cooler months (Boyers ). These ungulates were all least mobile pre‐dawn, indicating that this is the time when large herbivores sleep.…”

Section: How Are Activities Scheduled Daily and Seasonally?mentioning

confidence: 99%

Movement ecology of large herbivores in African savannas: current knowledge and gaps

et al. 2020

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1. Nearly 90% of the world's large herbivore diversity occurs in Africa, yet there is a striking dearth of information on the movement ecology of these organisms compared to herbivores living in higher latitude ecosystems. 2. The environmental context for movements of large herbivores in African savanna ecosystems has several distinguishing features. African large herbivores move in landscapes with high spatiotemporal variability, low predictability, seasonal restrictions in surface water as well as food resources, and exposure to a diverse assemblage of competitors, predators, and pathogens. These features influence mobility, diel activity routines, home-range fidelity, and exposure to predation. 3. We review the knowledge that has been gained about the movements of African herbivores from Global Positioning System (GPS) telemetry and identify important gaps in knowledge that exist. Topics addressed include seasonal movement patterns, daily activity schedules, space utilisation, water dependency, responses to risks of predation, pathogen transmission, social affiliations, and local population density determination. 4. While the growing number of GPS telemetry studies has addressed a wide range of topics in Africa, they remain fragmentary in terms of places and species represented. Most research has been focussed on three species, and practices for data sharing and analysis should be improved. African landscapes are changing perhaps faster than any other region on Earth, with rapidly expanding human populations, massive infrastructure development projects, and changes in climatic regimes. There is a crucial need to establish relationships between herbivore movements and their changing environments, especially in Africa where most of the world's large herbivore diversity resides.

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How free-ranging ungulates with differing water dependencies cope with seasonal variation in temperature and aridity

Cited by 22 publications

References 39 publications

Contrasting capabilities of two ungulate species to cope with extremes of aridity

Contrasting capabilities of two ungulate species to cope with extremes of aridity

A hierarchical machine learning framework for the analysis of large scale animal movement data

Movement ecology of large herbivores in African savannas: current knowledge and gaps

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