In a recent study published in the Journal of Animal Ecology, researchers reported the impact of energy landscapes on shaping elephant habitats. Energy landscapes are the energy expenditures of traveling across a particular landscape offset by resource gains.
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Introduction
The large size of elephants can hinder access to high-productive habitats. Thus, understanding the relationship between resource availability and locomotion costs could provide valuable insights into elephant habitat use.
Animal movement impacts biodiversity, ecosystems, and recovery from disturbances. Analyzing animal behavior and choices can guide conservation efforts. Megafauna (animals weighing ≥45 kg) play a crucial role in ecosystem functions such as nutrient and energy dispersal.
The African savanna elephant, the largest megaherbivore, now has fragmented populations. Wild elephant counts are declining due to human activities like poaching and increased land use. Thus, assessing their habitat requirements is crucial for conserving and restoring animal populations amid ongoing mass extinction.
Elephants bulk-feed, which increases metabolic costs and locomotion challenges due to size. Energy landscape evaluation can provide insights into elephants' habitat use and movement. Researchers often use elevation to predict habitat preferences; however, it may not directly influence movement. Other factors like water availability and vegetation structure may shape movement indirectly.
About the Study
In the present study, researchers reported the influence of landscape topography, particularly the cost of locomotion and vegetation productivity, on elephant movement and habitat preference.
The researchers analyzed the global positioning system (GPS) data of 157 elephants in the Samburu area of Northern Kenya (36–39° E, −0.36–2.81° N) using a step-selection function (SSF) approach.
Save The Elephants (STE), a nonprofit organization promoting elephant wellness and research, provided elephant data spanning 1998 to 2020. The team used the ENERSCAPE tool based on individual body mass and terrain inclination to estimate movement costs. The assumed body mass values were 6,029 kg for males and 2,744 kg for females.
In addition to elevation, the team considered the distance to human settlements and permanent water bodies as explanatory variables. They calculated the distances to human settlements and water bodies using remote sensing data tools such as the World Settlement Footprint and ESA WorldCover products. Digital elevation models (DEM) displayed the energy landscapes at a 30 × 30 m resolution.
The researchers determined the Normalized Difference Vegetation Index (NDVI), which measures the relative abundance of plant chlorophyll, as a proxy for vegetation productivity. They derived the monthly NDVI values from Sentinel-2 data obtained between June 2015 and February 2023.
Hidden Markov state-space models (HMM) defined movement patterns and states of individual elephants. To fit HMMs, the researchers calculated two movement parameters, the relocation step length (in meters) and the turning angle (in radians) from the GPS data.
From the fitted HMMs, they determined the most likely movement state at each GPS location using the Viterbi algorithm. Conditional logistic regressions enabled statistical analysis.
Results
The study showed that elephants generally avoid regions with high travel costs (n=148) and prefer those with high resource availability, as denoted by high NDVI values (n=146). In particular, one standard deviation increase in NDVI increases the odds of elephants moving a step further by 37%.
In contrast, one standard deviation increase in energy cost and distance from water bodies decreases the step-taking probabilities by 19% and 14%, respectively.
Water availability is crucial in determining habitat use; however, its effect varies among elephants, with some individuals preferring habitats avoided by others. In particular, 64 elephants avoided areas that were distant from water, whereas 13 preferred such habitats, and 80 did not show any preference.
The distance from water bodies strongly correlated with elevation for 19 elephants and distance to urban settlements for 39 individuals, indicating that these factors may influence movement preferences.
Elephants prefer high NDVI areas when moving faster, with 74% of individuals avoiding such sites while moving slowly. This preference increases to 87% during intermediate-speed motion and 93% at higher speeds. However, most elephants showed no preference regarding distance from water bodies.
The study suggests that elephants can adjust their behavior based on their locomotion state, avoiding costly areas while moving swiftly but showing weaker preferences during sluggish movements. In general, most elephants avoided high-cost areas in all movement states.
Implications and Future Directions
The study reveals that landscape topography influences elephant behavior and preferences, with elephants preferring areas with low transport costs and abundant resources. Energy landscapes could inform the planning of dispersal corridors, aiding in restoring the fragmented distributions of elephants.
Moreover, the elephants' increasing preference for reducing movement costs while traveling at higher speeds underscores the importance of energy landscapes during long-distance, strongly directional movements.
Further, changing climate conditions could alter ecological parameters, potentially increasing the metabolic costs of movement for large animals due to overheating. Thus, researchers must consider energy landscapes in future studies.
Future research could further explore the causal relationships between environmental factors and elephant landscape utilization, integrating energy costs and resource availability for a holistic understanding.
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