Back

Optimising future rhino population management strategies using insights from genetic health assessments across India

Ghosh, T.; Kakati, P.; Sharma, A.; Mondol, S.

2024-08-09 genetics
10.1101/2024.08.09.607316 bioRxiv
Show abstract

Various species conservation paradigms are facing enormous challenges during the ongoing Anthropocene. While the widely-used reintroduction/translocation-based approaches have supported many endangered species population recoveries, they seldom use detailed genetic information during initial planning. The Indian greater one-horned rhino typifies such assisted migration-driven species recovery, but currently facing long-term survival concerns due to their mostly small, isolated populations reaching respective carrying capacities. We assessed nation-wide rhino genetic health, identified suitable source populations and provided future translocation scenarios for all extant and proposed rhino habitats. Analyses with 504 unique rhino genotypes across all seven Indian rhino-bearing parks revealed six genetically-isolated populations with overall moderately low genetic diversity. Our results showed that Kaziranga and Manas NPs (Assam) to have the best rhino genetic health, whereas Jaldapara and Gorumara NPs (West Bengal) undergoing strong genetic erosions. Forward genetic simulations suggested that annual supplementation efforts from only few Assam rhino populations (Kaziranga NP, Orang NP and Pobitora WLS) are best suited for genetic rescue of most of the extant populations. Overall, the genetic diversity and differentiation patterns mimics the complex evolutionary history and individual recovery histories. We suggest park-specific management solutions (ranging from protection measures, grassland restoration, livestock and conflict management, regular supplementation events etc.) to ensure the species long-term persistence and prevent the alarming loss of grassland habitats and its associate biodiversity. We insist on utilising such genetic health indices-driven population management solutions to identify targeted mitigative measures in other species.

Matching journals

The top 2 journals account for 50% of the predicted probability mass.

1
Conservation Genetics
15 papers in training set
Top 0.1%
38.2%
2
Global Ecology and Conservation
25 papers in training set
Top 0.1%
12.3%
50% of probability mass above
3
Evolutionary Applications
108 papers in training set
Top 0.2%
6.5%
4
Biological Conservation
46 papers in training set
Top 0.2%
6.1%
5
Diversity and Distributions
28 papers in training set
Top 0.1%
4.2%
6
PeerJ
308 papers in training set
Top 2%
3.9%
7
Heredity
64 papers in training set
Top 0.3%
3.1%
8
Ecology and Evolution
267 papers in training set
Top 3%
2.1%
9
BMC Ecology and Evolution
51 papers in training set
Top 0.5%
1.8%
10
PLOS ONE
5266 papers in training set
Top 47%
1.8%
11
Molecular Ecology
336 papers in training set
Top 3%
1.6%
12
Ecological Indicators
21 papers in training set
Top 0.3%
1.6%
13
Gene
46 papers in training set
Top 1%
1.3%
14
Biological Journal of the Linnean Society
24 papers in training set
Top 0.5%
1.3%
15
Peer Community Journal
281 papers in training set
Top 4%
1.3%
16
Primates
11 papers in training set
Top 0.2%
1.3%
17
Frontiers in Genetics
230 papers in training set
Top 4%
1.1%
18
G3: Genes, Genomes, Genetics
252 papers in training set
Top 4%
1.0%
19
Biological Invasions
14 papers in training set
Top 0.5%
1.0%
20
Molecular Ecology Resources
171 papers in training set
Top 2%
0.8%
21
Journal of Heredity
42 papers in training set
Top 1%
0.6%
22
Coral Reefs
21 papers in training set
Top 0.4%
0.6%