Research Aims - The extent of Madagascar’s grasslands prior to human colonization is unresolved. We used population genetic analyses of a broadly dominant C₄ fire-adapted grass, Loudetia simplex, as a proxy for estimating grassland change through time. We carefully examined the utility of target-enrichment data for population genetics to make recommendations for conservation genetics. We explored the potential of estimating individual ploidy levels from target-enrichment data and how assumptions about ploidy could affect analyses.

 

Methods - We developed a novel bioinformatic pipeline based to estimate ploidy and genotypes from target-enrichment data. We estimated standard population genetic summary statistics in addition to species trees and population structure. Extended Bayesian skyline plots provided estimates of population size through time for empirical and simulated data.

 

Key Result - All Malagasy Loudetia simplex individuals sampled in this study formed a clade and possibly indicated an ancestral high-altitude distribution. Demographic models suggested grassland expansions occurred prior to the Last Interglacial Period and supported extensive grasslands prior to human colonization. Though there are limitations to target-enrichment data for population genetic studies, we find that analyses of population structure are reliable.

 

Key Point - Genetic variation in Loudetia simplex supports widespread grasslands in Madagascar prior to the more recent periods of notable paleoclimatic change. However, the methods explored here could not differentiate between paleoclimatic change near the Last Glacial Maximum and anthropogenic effects. Target-enrichment data can be a valuable tool for analyses of population structure in the absence a reference genome.

 

 

Recognizing Loudetia dominated grasslands were widespread prior to human colonization highlights that open ecosystems were and continue to be an important component to Madagascar’s biodiversity. Urgently required are biodiversity inventories and risk assessments for unique grassland flora and fauna under present day environmental conditions to recognize and quantify modern human impacts within ecosystems historically regarded as wastelands. Substantial financial and logistic barriers exist to implementing conservation studies using contemporary genomic tools that we seek to ameliorate by developing computational resources to leverage a cost-effective data generation strategy that requires no prior genetic knowledge of the target species.