African Savanna Research Articles

Substantial Insect Herbivory in a South African Savanna-Forest Mosaic: A Neglected Topic.

Insect herbivory plays a crucial role in shaping plant communities in many terrestrial ecosystems. However, in African savannas, insect herbivory has been relatively understudied compared to large mammalian herbivory. In this study, we examined the impact of insect herbivory, focusing on leaf chewers and miners, in a South African savanna-forest mosaic (including patches of forest, thicket and savanna) in Hluhluwe iMfolozi Park, South Africa. Our investigation spanned gradients of rainfall, fire frequency and mammal density. We surveyed a total of 864 woody plants from 48 plant species in 38 plots. Insects consumed 6% of leaf biomass, which is comparable to their impact in temperate broadleaf forests, but the extent of herbivory damage varied between vegetation types. Overall, leaf loss was 70% higher in forests and savanna than that in thicket. Plants in the forests experienced greater damage from chewing insects, whereas miners caused relatively more damage in savannas. Rates of insect herbivory also varied among plant species, declining with carbon and dry matter content but increasing with specific leaf area. Although no significant trade-off was detected between insect and mammal herbivory, plant species with limited physical defences against mammals tended to experience high levels of insect herbivory. Our findings highlight the intricate dynamics of insect herbivory in different vegetation types and suggest that insect leaf herbivory, alongside mammalian herbivory, could play a significant role in influencing plant community composition and overall savanna ecosystem functioning.

Exploring and closing the energy balance of eddy covariance measurements along a land use gradient in the West African Sudanian savanna

A good understanding of land-atmosphere exchange processes is essential for developing sustainable land management practices in Africa, in order to enhance food security and strengthen the resilience against climate change and extremes in this vulnerable region. In this study, we explore the energy balance closure (EBC) of three eddy covariance (EC) sites implemented along a land use gradient (pristine savanna forest, cropland, and degraded grassland) in the Sudanian savanna of West Africa. Our results show that the EBC strongly varies over the monsoon season and the EC sites. However, the best EBC is observed at the pristine site, which has the most homogenous vegetation. Thus, landscape heterogeneity seems to play an important role in the quality of the EC measurements. Moreover, we develop a novel post-closure method based on a quantile-mapping technique conditioned on monsoonal circulation patterns specifically determined for the West African Monsoon. This method is also compared to two well-established methods, the Bowen-ratio (BR) correction and a pure quantile-mapping using various bias measures. Our results show that the novel post-closure method outperforms the other methods and, therefore, leads to better elimination of the underestimation of the turbulent fluxes at the three savanna sites. In addition, specific characteristics of turbulent fluxes, like their strong diurnal cycle, are well represented by the new correction method.

Do elephants really never forget? What we know about elephant memory and a call for further investigation.

Despite popular culture's promotion of the elephant's ability to "never forget," there is remarkably limited empirical research on the memory capacities of any living elephant species (Asian, Elephas maximus; African savanna, Loxodonta africana; African forest, Loxodonta cyclotis). A growing body of literature on elephant cognition and behavioral ecology has provided insight into the elephant's ability to behave flexibly in changing physical and social environments, but little direct evidence of how memory might relate to this flexibility exists. In this paper, we review and discuss the potential relationships between what we know about elephant cognition and behavior and the elephants' memory for the world around them as they navigate their physical, social, and spatial environments. We also discuss future directions for investigating elephant memory and implications for such research on elephant conservation and human-elephant conflict mitigation.

Greenhouse gas emission from prescribed fires is influenced by vegetation types in West African Savannas

Greenhouse gas (GHG) emissions from prescribed fires are poorly investigated, resulting in a high uncertainty in GHG budgets. Using, a carbon mass balance approach and experimental prescribed fires in 80 plots, this study assessed carbon emissions and established emission factors (EFs) for carbon dioxides (CO2), carbon monoxide (CO), and methane (CH4) across climate zones and vegetation types. In grass and shrub savannas, fires could burn intensely due to the lower moisture content and continuous spatial distribution of biomass fuel, causing greater carbon emissions with 1.61 ± 0.13 t C ha−1 and 1.01 ± 0.13 t C ha−1, respectively. Despite their low carbon emissions, tree savannas (1658.17 ± 11.13 g kg−1) and woodlands (1629.94 ± 12.23 g kg−1) have the highest EFs, which can be attribute to the high carbon content of biomass fuel in these vegetation types. Vegetation types and their interaction with climate zones have a substantial impact on carbon emissions and carbon species EFs, and should therefore be considered in assessing GHG emissions from fires. The findings from this study provide a useful basis for improving the national measurement, reporting, and verification of GHG emissions and for improving the measurement of the global balance of GHG emissions from fires.

Assessment of soil carbon dioxide efflux from contrasting land uses in a semi-arid savannah ecosystem, northeastern Ghana (West Africa)

Soil respiration (SR) emits a vast amount of atmospheric carbon dioxide (CO2) and contributes largely to the global greenhouse gas budget. The study assessed the dynamics of SR rates in the Vea catchment in northeastern Ghana, a sparsely gauged semi-arid savannah ecosystem characterized by distinct patterns of soil CO2 efflux. Through field measurements using soil chambers, the study quantified soil CO2 efflux rates in different land use types (woodland, cropland and grazeland), and assessed the influence of soil moisture, temperature, and soil organic carbon stocks on SR variability. The highest soil CO2 fluxes (12.97 ± 0.89 Mg CO2C ha−1 yr−1) were recorded in woodland, followed by grazeland (9.10 ± 0.42 Mg CO2C ha−1 yr−1) with cropland having the lowest rate (5.61 ± 0.29 Mg CO2C ha−1 yr−1). We recorded mean annual soil CO2 flux of 9.23 ± 0.53 Mg CO2C ha−1 yr−1 across the land use types and also observed significant seasonal and spatial variations in SR rates. The highest SR rate (220 mg CO2C m−2h−1) was recorded in the wet months (Jul-Sept and Mar-May) and the lowest rate (30 mg CO2C m−2h−1) in the dry months (Nov-Jan). For the wet season, the mean weekly soil CO2 fluxes ranged between 140 and 160 mg CO2C m−2 hr−1 as opposed to 60–75 mg CO2C m−2 hr−1 for the dry season. Seasonal and spatial variations in SR rates were largely driven by land use type, soil moisture and the interaction of soil temperature and moisture. The results underscore the importance of understanding the emission patterns from various land uses in West African savanna ecosystems to harnessing their potential for climate change mitigation.

Do African Savanna Elephants (Loxodonta africana) Show Interspecific Social Long-Term Memory for Their Zoo Keepers?

"An elephant never forgets" is a popular phrase that refers not only to the elephant's extraordinary ability to remember migration routes but also to its pronounced social long-term memory (SLTM). Previous studies have shown intra- and interspecies SLTM performance, but the ability of elephants to have memories of individual humans has not yet been investigated. We tested this interspecific SLTM using auditory, olfactory, and visual stimuli, each from familiar and unfamiliar persons, in two African savanna elephant (Loxodonta africana) cows living in a zoo. The two-choice object tests revealed a higher interest in sensory stimuli from familiar keepers they had not seen for 13 years than in unfamiliar people. Statistically significant differences were found for olfactory stimuli. In addition, there was significantly more interest in visual stimuli from current keepers than in stimuli from unfamiliar people. Contrary to the results of a previous study with elephants, this was not observed for olfactory stimuli. Due to the small sample size and magnitude of the influencing factors, that is, outdoor experiment, only spatial separation of the animals, these results only represent indications of the possible interspecific SLTM. Nevertheless, we were able to provide the first empirical evidence that L. africana stores information about specific people over a long period of time. Further studies with larger sample sizes, cross-modal testing, and people disliked by the elephants could provide more insights.

Associations between Lantana camara L. (Verbenaceae) and common native species in an African savanna

Abstract Lantana camara L. (Verbenaceae) is recognised as a problematic invasive alien plant species in many parts of the world. To eradicate or control this global invader, we need to understand the drivers of its spread and impacts and the potential for native recovery after the invader has been removed. Here, we tested for species associations between L. camara and native plant species and large herbivores in Queen Elizabeth National Park, Uganda. We inventoried 40,100‐m2 nested plots spread over a 1 × 1‐km grid cell in the park's savanna landscape, with 11 plots located in uninvaded areas. Most of the plots (30 of 40) had been affected by fire. Lantana camara covered 29 (73%) plots, 11 (38%) of which were in open grassland. Of the large herbivores that frequented areas free of L. camara, the Ugandan kob Adenota kob thomasi Sclater tended to avoid the areas invaded. The floristic composition of invaded areas differed significantly from that of noninvaded areas, with several palatable species rare or absent from L. camara‐invaded areas. Practical implication: These observations indicate the presence of potential recovery constraints that will need to be overcome after L. camara has been removed. Sustained efforts will be needed to suppress the invader and subsequently enrich and bolster native recovery.

Herbivore regulation of savanna vegetation: Structural complexity, diversity, and the complexity–diversity relationship

AbstractLarge mammalian herbivores exert strong top‐down control on plants, which in turn influence most ecological processes. Accordingly, the decline, displacement, or extinction of wild large herbivores in African savannas is expected to alter the physical structure of vegetation, the diversity of plant communities, and downstream ecosystem functions. However, herbivore impacts on vegetation comprise both direct and indirect effects and often depend on herbivore body size and plant type. Understanding how herbivores affect savanna vegetation requires disaggregating the effects of different herbivores and the responses of different plants, as well as accounting for both the structural complexity and composition of plant assemblages. We combined high‐resolution Light Detection and Ranging (LiDAR) with field measurements from size‐selective herbivore exclosures in Kenya to determine how herbivores affect the diversity and physical structure of vegetation, how these impacts vary with body size and plant type, and whether there are predictable associations between plant diversity and structural complexity. Herbivores generally reduced the diversity and abundance of both overstory and understory plants, though the magnitude of these impacts varied substantially as a function of body size and plant type: only megaherbivores (elephants and giraffes) affected tree cover, whereas medium‐ and small‐bodied herbivores had stronger effects on herbaceous diversity and abundance. We also found evidence that herbivores altered the strength and direction of interactions between trees and herbaceous plants, with signatures of facilitation in the presence of herbivores and of competition in their absence. While megaherbivores uniquely affected tree structure, medium‐ and small‐bodied species had stronger (and complementary) effects on metrics of herbaceous vegetation structure. Plant structural responses to herbivore exclusion were species‐specific: of five dominant tree species, just three exhibited significant individual morphological variation across exclosure treatments, and the size class of herbivores responsible for these effects varied across species. Irrespective of exclosure treatment, more species‐rich plant communities were more structurally complex. We conclude that the diversity and architecture of savanna vegetation depend on consumptive and nonconsumptive plant–herbivore interactions; the roles of herbivore diversity, body size, and plant traits in mediating those interactions; and a positive feedback between plant diversity and structural complexity.

Seasonal variation of home range size and habitat selection of elephants in the Kabompo landscape of Zambia

BackgroundMovements of large herbivores and habitat utilization provide critical information for ecological monitoring and conservation. However, such geospatial information rarely exists, especially in sub-Saharan Africa. This study aims to provide insight on seasonal variation of home range size and habitat utilization by African savanna elephants (Loxodonta africana) in Zambia’s Kabompo Landscape.MethodsTwo male sub-adult elephants (estimated age 10–15 years) were collared and monitored between March 2018 and December 2021 using the Geographic Position System (GPS) tracking devices. We used Minimum Convex Polygon (MCP), which uses the outermost points, to arrive at the largest home range of a study subject and the Kernel Density Estimator (KDE), which captures the intensity use of various parts of the home range. Distance from the river, elevation, slope, land cover type, fire intensity and Normalized Difference Vegetation Index (NDVI) were assessed against habitat selection by elephants using multinomial logistic regression.ResultsThe findings showed that the movements of the elephants were largely confined within the West Lunga National Park. The wet season had the largest home range (1720.8 km2) dominated by grassland, while the cold dry season had the smallest area of 931.8 km2. Elevation and land cover types had significant (p-value < 0.05) influence on home range across all the seasons. Other factors also had positive and negative impacts on the home range selection depending on the season.ConclusionsThe insights from this study can be exemplary relevant to conservation planning through monitoring seasonal movement of elephants.

Resource selection at fine scale: what drives the decision of a generalist herbivore?

Abstract Spatial patterns in topography and forage distribution significantly influence the movements and choices of large herbivores. However, understanding the foraging strategies of free-grazing herbivores at different temporal and spatial scales remains limited, as different behavioral decisions can apply at different hierarchical levels. This study investigates the fine-scale foraging strategies of the Plains Zebra (Equus quagga) in a South African savanna, with a specific focus on their selection of green vegetation at the plant and feeding patch levels. We used the Normalized Difference Vegetation Index as a proxy for vegetation productivity and quality. Our findings reveal that zebras adapted their foraging strategies according to scale and season. During the late-dry season and early-wet season, selection for greenness was at both the grass tuft and feeding site levels. In contrast, during the mid-dry season, selection was predominantly at the tuft level, focusing solely on greenness. These insights emphasize the importance of conducting multilevel studies when investigating factors influencing foraging decisions. Findings at 1 hierarchical level may not necessarily apply across other levels of investigation, highlighting the need for a nuanced and comprehensive approach to understanding the complex foraging behaviors of animals.

Evaluation of GEDI footprint level biomass models in Southern African Savannas using airborne LiDAR and field measurements

Savannas cover more than 20% of the Earth and account for the third largest stock of global aboveground biomass yet estimates of their above ground biomass density (AGBD) are very inaccurate. The Global Ecosystem Dynamic Investigation (GEDI) sensor provides near-global full-waveform LiDAR data with 25 m footprints, from which various structural metrics are derived that are used to predict footprint level AGBD. The current GEDI L4A AGBD product uses a comprehensive Forest Structure and Biomass Database (FSBD) to develop models for specific plant functional types and geographic regions, but southern African savannas have been underrepresented in the reference data. The objectives of this study were to (i) validate GEDI L4A AGBD in South African savannas using field measurements and ALS datasets and (ii) develop and evaluate local GEDI footprint-level AGBD estimates from multiple L2A and L2B metrics. The local GEDI AGBD models outperformed GEDI L4A AGBD (R2 = 0.42, RMSE = 12 Mg/ha, %RMSE = 79.5%) with higher R2 and smaller error measures. The local GEDI AGBD using a random forest model (RF) had the highest R2 of 0.71 and lowest %RMSE of 53.3%, while the generalized linear model (GLM) results provided the lowest Relative Mean Systematic Deviation (RMSD) of 9.2%, which was half that of RF model. L4A significantly underestimated AGBD with an RMSD up to −37%. This highlights the importance and benefits of local calibration of biomass models to unlock the full potential of GEDI metrics for estimating AGBD. The field and ALS data have subsequently been contributed to the GEDI FSBD and should be used in calibration of future versions of GEDI L4A AGBD product. This research paves the way for the integration of the local GEDI AGBD estimates with other sensors, notable the eminent NISAR mission, to derive regional to global gridded AGBD products that will enable the monitoring of savanna carbon stocks.

Eddy covariance measurements reveal a decreased carbon sequestration strength 2010-2022 in an African semiarid savanna.

Monitoring the changes of ecosystem functioning is pivotal for understanding the global carbon cycle. Despite its size and contribution to the global carbon cycle, Africa is largely understudied in regard to ongoing changes of its ecosystem functioning and their responses to climate change. One of the reasons is the lack of long-term insitu data. Here, we use eddy covariance to quantify the net ecosystem exchange (NEE) and its components-gross primary production (GPP) and ecosystem respiration (Reco) for years 2010-2022 for a Sahelian semiarid savanna to study trends in the fluxes. Significant negative trends were found for NEE (12.7 ± 2.8 g C m2 year-1), GPP (39.6 ± 7.9 g C m2 year-1), and Reco (32.2 ± 8.9 g C m2 year-1). We found that NEE decreased by 60% over the study period, and this decrease was mainly caused by stronger negative trends in rainy season GPP than in Reco. Additionally, we observed strong increasing trends in vapor pressure deficit, but no trends in rainfall or soil water content. Thus, a proposed explanation for the decrease in carbon sink strength is increasing atmospheric dryness. The warming climate in the Sahel, coupled with increasing evaporative demand, may thus lead to decreased GPP levels across this biome, and lowering its CO2 sequestration.

The influence of biophysical characteristics on elephant space use in an African savanna

Understanding the influence of biophysical variables on spatial distribution and seasonal locations of elephants is valuable inter alia in understanding their movement patterns, and the carrying capacity to optimise the conservation of their habitats. Furthermore, understanding elephant distribution in time and space is beneficial for predicting locations for tourist viewing and determining potential areas of human–wildlife conflicts. In this study, we examined the environmental drivers of seasonal variations in elephant ranges and movement using telemetry data. Using the elephant tracking data and biophysical characteristics, the Adaptive-Local Convex Hull (a-LoCoH) and the Maximum Entropy Modelling (MaxEnt) algorithm were adopted to determine their potential locations and distribution in a protected area. The jackknife approach was used to assess the environmental factors influencing seasonal elephant movements based on collar data from ten individual elephants tracked between December 2015 and April 2018. The performance of the elephant distribution models for the two seasons was assessed using the area under the curve from the receiver operating characteristic based on a 30% test holdout data. Results showed that the core a-LoCoH home of elephants was larger in the dry than wet season (Wilcoxon signed-rank test; W = 3, Z = 2.4973, p < 0.012). However, no noticeable differences were observed (Wilcoxon signed-rank test; W = 10, Z = 1.7838, p < 0.07) between the dry and wet season for the total (90%) a-LoCoH ranges. The MaxEnt modelling results showed that distance to the artificial water holes was the most influential variable in predicting the potential elephant spatial distribution in both wet and dry seasons, while the normalised difference vegetation index, a proxy for forage availability, was more influential in the dry season in predicting elephant distribution. The study concludes that seasonal elephant space use is mostly influenced by water availability in both seasons, while forage availability and variability influence elephant distribution more strongly in the dry than wet season. The study provides valuable insight into the biophysical characteristics of elephant home ranges. This is useful for the sustainable management of elephants and their habitats.

Seasonal variation in the ranging behavior of elephants in the Laikipia-Samburu ecosystem.

African savanna elephants are a highly mobile species that ranges widely across the diversity of ecosystems they inhabit. In xeric environments, elephant movement patterns are largely dictated by the availability of water and suitable forage resources, which can drive strong seasonal changes in their movement behavior. In this study, we analyzed a unique movement dataset from 43 collared elephants, collected over a period of 10 years, to assess the degree to which seasonal changes influences home range size of elephants in the semi-arid, Laikipia-Samburu ecosystem of northern Kenya. Auto-correlated Kernel Density Estimation (AKDE) was used to estimate elephants' seasonal home range size. For each individual elephant, we also calculated seasonal home range shifts, as the distance between wet season home range centroids and dry season home range centroids. Core areas (50% AKDE isopleths) of all individual elephants ranged from 3 to 1743 km2 whereas total home range sizes (the 95% AKDE isopleths) ranged between 15 and 10,677 km2. Core areas and home range sizes were 67% and 61% larger, respectively, during the wet season than during the dry season. On average, the core area centroids for all elephants were 17 km away from the nearest river (range 0.2-150.3 km). Females had their core areas closer to the river than males (13.5 vs. 27.5 km). Females differed from males in their response to seasonal variation. Specifically, females tended to occupy areas farther from the river during the wet season, while males occupied areas further from the river during the dry season. Our study highlights how elephants adjust their space use seasonally, which can be incorporated into conservation area planning in the face of increased uncertainty in rainfall patterns due to climate change.

Spatio-Temporal Analysis of Wildfire Regimes in Miombo of the LevasFlor Forest Concession, Central Mozambique

Wildfires are an intrinsic and vital driving factor in the Miombo ecosystem. Understanding fire regimes in Miombo is crucial for its ecological sustainability. Miombo is dominant in Central Mozambique, having one of the highest fire incidences in the country. This study evaluated the spatio-temporal patterns of fire regimes (intensity, seasonality, frequency and fire return interval) in the LevasFlor Forest Concession (LFC), Central Mozambique using remotely sensed data from 2001 to 2022. We conducted hotspot spatial statistics using the Getis-Ord Gi* method to assess fire distribution and patterns. The results revealed that 88% of the study area was burnt at least once from 2001 to 2022, with an average burned area of 9733 ha/year (21% of LFC’s total area). Fires were more likely to occur (74.4%) in open and deciduous Miombo types. A total of 84% of the studied area, burned in a range of 4 to 22 years of fire return interval (FRI) over the 21 assessed. Only 16% of the area was affected by high to very high FRI (1 to 4 years), with an average FRI of 4.43 years. Generally, fires are more frequent and intense in September and October. These results highlight the usefulness of remote sensing in evaluating long-term spatiotemporal fire trends for effective fire management strategies and control measures in African savanna ecosystems.

Mapping off-road tracks and animal paths in protected areas using high-resolution GeoEye-1 panchromatic satellite imagery

ABSTRACT Off-road driving activities are common in many protected areas. This study aimed at applying a curvelet-based approach for the automatic extraction, mapping and separation of off-road tracks and animal paths in Masai Mara National Reserve, Kenya, using high-resolution GeoEye-1 panchromatic satellite imagery (50 cm). A novel hybrid remote sensing-GIS method comprising three main blocks is proposed: (1) extracting the high-contrast curvilinear feature from curvelet magnitudes derived from the finer scale of curvelet coefficient; (2) extracting the low-contrast curvilinear feature from coarser scale curvelets and refine the shape by deformable active contour (Snake), and (3) categorizing the extracted curvilinear feature into vehicle tracks and animal paths by a fuzzy logic inference system. Results from quantification of extraction and categorization performance of the trails were 77.5% for completeness, 89.2% for correctness, and 4.5% for redundancy, with an overall accuracy of 79.5%. Using grid matching, we find a high correlation between off-road vehicle tracks and animal paths in the area (r = 0.75, p < 0.05) indicating co-occurrence of these two types of trails. The proposed approach provides a basis for large-scale mapping and monitoring of off-road tracks and animal paths in the African savanna from space.

Integrating habitat suitability modeling with gene flow improves delineation of landscape connections among African savanna elephants

Integrating habitat suitability modeling with gene flow improves delineation of landscape connections among African savanna elephants

Rainfall, peak river flow and flow variability drive spatio‐temporal change in the extent of riparian woodland in an African protected area savanna

AbstractVerbal accounts, supported by limited ground‐based and satellite images, reveal decreasing riparian woodland and a loss of large trees along the rivers of the Kruger National Park (KNP, South Africa) over the last century. A multi‐decadal analysis was conducted to identify trends in extent and possible drivers of riparian woodland change. Aerial and satellite imagery (1936–2018) were used to quantify changes in the extent of riparian woodland at 18 sites on 14 rivers in KNP. These changes were compared in a multivariate time‐series with river flow and local rainfall. Particular attention was paid to cumulative flow effects, as well as the frequency and magnitude of large infrequent disturbances such as droughts and floods. Riparian tree cover fluctuated over the time period, and the trajectory of change varied between sites. Most (11) sites experienced a decrease in overall riparian tree cover over ~80 years, with these declines being significant at six sites. Peak flow and maximum rainfall events were strongly associated with these decreases, indicating that flood events are potentially the biggest driver of tree loss from the system. Indeed, the mega‐flood event of 2000 and subsequent large floods have resulted in substantial declines in riparian woodland extent in recent decades. Alternatively, flow variability and cumulative rainfall significantly influenced woodland expansion in isolated cases. With global change models predicting more erratic rainfall and an increased likelihood of large infrequent disturbances, together with increasing demands to abstract more water, the long‐term future of these dynamic habitats and their associated biota here is uncertain.

Grass layer limits tree seedling survival but not tree seedling growth in African and South American savannas

Grass layer limits tree seedling survival but not tree seedling growth in African and South American savannas

A metagenomic survey of the fecal microbiome of the African savanna elephant (Loxodonta africana).

The African savanna elephant (Loxodonta africana) is the largest terrestrial animal on Earth and is found primarily in Southern and Eastern Africa. It is a hindgut, colonic fermenter and subsists on a diet of raw plant materials found in its grazing area. In this study the bacterial, archaeal and fungal populations of seven African savanna elephant fecal metagenomes were first characterized using amplicon sequencing. On the genus level it was observed that the p-1088-a5 gut group in the bacteriome, Methanocorpusulum and Methanobrevibacter in the archaeome and Alternaria, Aurobasidium, Didymella and Preussia in the mycome, predominated. Subsequently, metagenomic shotgun sequencing was employed to identify possible functional pathways and carbohydrate-active enzymes (CAZymes). Carbohydrate catabolic pathways represented the main degradation pathways, and the fecal metagenome was enriched in the glycohydroside (GH) class of CAZymes. Additionally, the top GH families identified - GH43, GH2, GH13 and GH3 - are known to be associated with cellulytic, hemicellulytic and pectolytic activities. Finally, the CAZymes families identified in the African savanna elephant were compared with those found in the Asian elephant and it was demonstrated that there is a unique repository of CAZymes that could be leveraged in the biotechnological context such as the degradation of lignocellulose for the production of second-generation biofuels and energy.