Elephant movement closely tracks precipitation-driven vegetation dynamics in a Kenyan forest-savanna landscape

Bohrer, Gil; Beck, Pieter S. A.; Ngene, Shadrack; Skidmore, Andrew K.; Douglas-Hamilton, I.

doi:10.1186/2051-3933-2-2

Cited by 103 publications

(96 citation statements)

References 70 publications

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“…; Bohrer et al . ). These findings highlight an important, yet unresolved, question of whether green‐wave surfing is a common behaviour among migrating ungulates.…”

Section: Introductionmentioning

confidence: 97%

The greenscape shapes surfing of resource waves in a large migratory herbivore

et al. 2017

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The Green Wave Hypothesis posits that herbivore migration manifests in response to waves of spring green-up (i.e. green-wave surfing). Nonetheless, empirical support for the Green Wave Hypothesis is mixed, and a framework for understanding variation in surfing is lacking. In a population of migratory mule deer (Odocoileus hemionus), 31% surfed plant phenology in spring as well as a theoretically perfect surfer, and 98% surfed better than random. Green-wave surfing varied among individuals and was unrelated to age or energetic state. Instead, the greenscape, which we define as the order, rate and duration of green-up along migratory routes, was the primary factor influencing surfing. Our results indicate that migratory routes are more than a link between seasonal ranges, and they provide an important, but often overlooked, foraging habitat. In addition, the spatiotemporal configuration of forage resources that propagate along migratory routes shape animal movement and presumably, energy gains during migration.

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“…; Bohrer et al . ). These findings highlight an important, yet unresolved, question of whether green‐wave surfing is a common behaviour among migrating ungulates.…”

Section: Introductionmentioning

confidence: 97%

The greenscape shapes surfing of resource waves in a large migratory herbivore

et al. 2017

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“…For instance, a powerful predictive migration model for the migratory zebra, Equus burchelli antiquorum, was developed using NDVI data to evaluate how their timing and pace of movement is affected by spatio-temporal changes in the environment (Bartlam-Brooks et al, 2013). Another example also showed that elephants tracked an intermediate value of NDVI in the Marsabit protected area in Kenya, corresponding to the "surfing the green wave" hypothesis (Bohrer et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Satellite- versus temperature-derived green wave indices for predicting the timing of spring migration of avian herbivores

Najafabadi

Darvishzadeh

Skidmore

et al. 2015

Ecological Indicators

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Keywords:GWI index GDD jerk index Barnacle geese Stopover site Breeding site Mixed effect linear regression a b s t r a c t According to the green wave hypothesis, herbivores follow the flush of spring growth of forage plants during their spring migration to northern breeding grounds. In this study we compared two green wave indices for predicting the timing of the spring migration of avian herbivores: the satellite-derived green wave index (GWI), and an index of the rate of acceleration in temperature (GDDjerk). The GWI was calculated from MODIS normalized difference vegetation index (NDVI) satellite imagery and GDDjerk from gridded temperature data using products from the global land data assimilation system (GLDAS). To predict the timing of arrival at stopover and breeding sites, we used four years (2008-2011) of tracking data from 12 GPS-tagged barnacle geese, a long-distance herbivorous migrant, wintering in the Netherlands, breeding in the Russian Arctic. The stopover and breeding sites for these birds were identified and the relations between date of arrival with the date of 50% GWI and date of peak GDDjerk at each site were analyzed using mixed effect linear regression. A cross-validation method was used to compare the predictive accuracy of the GWI and GDDjerk indices. Significant relationships were found between the arrival dates at the stopover and breeding sites for the dates of 50% GWI as well as the peak GDDjerk (p < 0.01). The goose arrival dates at both stopover and breeding sites were predicted more accurately using GWI (R 2 cv = 0.68, RMSD cv = 5.9 and R 2 cv = 0.71, RMSD cv = 3.9 for stopover and breeding sites, respectively) than GDDjerk. The GDDjerk returned a lower accuracy for prediction of goose arrival dates at stopover ( R 2 cv = 0.45, RMSD cv = 7.79) and breeding sites (R 2 cv = 0.55, RMSD cv = 4.93). The positive correlation between the absolute residual values of the GDDjerk model and distance to the breeding sites showed that this index is highly sensitive to latitude. This study demonstrates that the satellite-derived green wave index (GWI) can accurately predict the timing of goose migration, irrespective of latitude and therefore is suggested as a reliable green wave index for predicting the timing of avian herbivores spring migration.

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“…In order to implement effective conservation and management plans, a greater understanding is required about elephant movements across large areas and over long periods (Breuer et al, ; Loarie, Aarde, & Pimm, ). Both the distribution and movement patterns of African savannah elephants ( Loxodonta africana Blumenbach, 1797) have been related to land cover type (Loarie et al, ; Young, Ferreira, & van Aarde, ), weather (i.e., temperature and rainfall; Birkett, Vanak, Muggeo, Ferreira, & Slotow, ; Bohrer et al, ) and elevation, slope and the presence of water bodies (natural or artificial; Graham, Douglas‐Hamilton, Adams, & Lee, ). These natural features interact with human infrastructures such as fences or human settlements (Buij et al, ; Loarie et al, ), which shape elephant movement patterns.…”

Section: Introductionmentioning

confidence: 99%

Movement patterns of forest elephants (Loxodonta cyclotis Matschie, 1900) in the Odzala‐Kokoua National Park, Republic of Congo

et al. 2019

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African forest elephants (Loxodonta cyclotis Matschie, 1900) are ecological engineers that play a fundamental role in vegetation dynamics. The species is of immediate conservation concern, yet it is relatively understudied. To narrow this knowledge gap, we studied the drivers of daily movement patterns (linear displacements) of forest elephants—characterised by a set of geographical, meteorological and anthropogenic variables—in the Odzala‐Kokoua National Park, Republic of Congo. Explicitly, we used conditional random forest to model and disentangle the main environmental factors governing the displacements of six forest elephants, fitted with GPS collars and tracked over 16 months. Results indicated that females moved further distances than males, while the presence of roads or human settlements disrupted elephant behaviour resulting in faster displacements. Forest elephants moved faster along watercourses and through forest with understory dominated by Marantaceae forests and bais, but moved slower in savannahs. Finally, flood‐prone areas—described by elevation and accumulated precipitation—and higher temperatures prevented longer displacements. We expect these results to improve the knowledge on the species movements through different habitats, which would benefit its conservation management.

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Elephant movement closely tracks precipitation-driven vegetation dynamics in a Kenyan forest-savanna landscape

Cited by 103 publications

References 70 publications

The greenscape shapes surfing of resource waves in a large migratory herbivore

The greenscape shapes surfing of resource waves in a large migratory herbivore

Satellite- versus temperature-derived green wave indices for predicting the timing of spring migration of avian herbivores

Movement patterns of forest elephants (Loxodonta cyclotis Matschie, 1900) in the Odzala‐Kokoua National Park, Republic of Congo

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