eDNA metabarcoding reveals dietary niche overlap among herbivores in an Indian wildlife sanctuary

Abstract

As many ecosystems are under increasing pressure from invasive species, habitat degradation, overgrazing and overharvesting, pollution, and climate change, dietary niche monitoring is gaining importance. The Malai Mahadeshwara Wildlife Sanctuary (MMH) in southern India is home to several long-standing ethnic and tribal groups and supports a considerable number of domestic herbivores (cattle, goats and water buffalo) as well as a range of wildlife (including several species of deer, bonnet macaque, and Asian elephant). We reconstructed dietary niche partitioning of the herbivores occurring in MMH using eDNA metabarcoding to quantify diet richness, composition, and overlap. In total, we distinguish 134 diet items (molecular operational taxonomic units), covering 31 plant families. Overall, our results indicate 35% overlap in domestic and wild herbivore diet items. The greatest overlap is found for the dietary niches of cattle and sambar deer (Pianka's niche overlap index: 0.68), and the dietary niche of cattle also overlaps considerably with those of Indian hare (0.65) and Asian elephant (0.46). This suggests that these herbivores may compete for these food plants in the case of limited availability, which could lead to exclusion of some herbivore species. Particular concern should go to bonnet macaque and Asian elephant as their below average dietary richness could make them vulnerable to changes in their environment. With increasing pressures on local wildlife from a range of different factors, DNA metabarcoding of fecal samples is a non-invasive method for monitoring changes in animal diets, providing valuable information for the management of biodiversity in mosaic natural and anthropogenic landscapes.

Plant-animal interactions in the era of environmental DNA (eDNA) – a review

“…For herbivory, eDNA-based methods have been shown to detect large numbers of taxa more efficiently than other sampling methodologies (e.g., microscopic analysis of fecal sample, bulk DNA metabarcoding; Tournayre et al, 2021). In fact, eDNA metabarcoding has also been applied to understand the dietary overlap and competition among domestic and wild herbivores (ter Schure et al, 2021). Notably, sampling matter may be a restricted application to large organisms with detectable faecal deposits.…”

Reconciling livestock production and wild herbivore conservation: challenges and opportunities

“…Co-design of cost-benefit monitoring and impact evaluation programs Uncertainty relating to the costs and benefits associated with the interaction between domestic and wild herbivores is a major barrier to effective mitigation of conservation conflicts. While recent technical advances can contribute towards reducing this uncertainty, for example, by enabling close monitoring and quantification of livestock productivity [38] or reliable assessment of dietary niche overlap [61], the use of sophisticated approaches are often not available to, nor a priority for, most livestock producers. In many cases, it will also be necessary to look beyond traditional ecological and economic indicators of loss and gain, to acknowledging the intangible costs and benefits resulting from the interaction between livestock and wild herbivores [25].…”

Plant-animal interactions in the era of environmental DNA (eDNA) – a review

“…Importantly, eDNA-based methods have been shown to detect large numbers of taxa more efficiently than other sampling methodologies (e.g., microscopic analysis of fecal sample, bulk DNA metabarcoding; Tournayre et al, 2021). Environmental DNA metabarcoding has also been applied to understand the dietary overlap and competition among domestic and wild herbivores (ter Schure et al, 2021). Notably, sampling of fecal matter may be a restricted application to large organisms, yet the collection of eDNA can be acquired through the rinsing of water from leaf surfaces to identify smaller taxa (Valentin et al, 2020).…”

“…(V) The detection of niche partitioning using eDNA-based methods is only just beginning (ter Schure et al, 2021) and fine-scale partitioning (e.g, different herbivory behaviour on the same plant) is difficult with current eDNA analysis.…”