Science Enabled by Specimen Data

Joshi, M. D., and C. Joshi. 2022. Areas of species diversity and endemicity of Nepal. Ecosphere 13.

In this study, we analyzed the distribution and the spatial pattern of species diversity of vascular plants in Nepal. The aim was to identify and evaluate the occurrence and status of species‐rich areas in Nepal using ecological and environmental drivers. We used 52,973 georeferenced herbarium specimen records, representing 2650 species collected from Nepal. Altogether, 41 environmental variables were used for model development and validation. We used MaxEnt to predict the distribution pattern. All the significant species distribution predictions were then used to develop a species richness and endemism pattern in Nepal. The High Mountain and Himalaya, particularly east and central Nepal, were found to be species diverse and endemically rich areas, whereas western Nepal had lower species richness. We observed that isothermality, slope, rugosity, potential evapotranspiration, precipitation of humid months, temperature annual range, mean diurnal range, and normalized difference in vegetation index of humid months were the most influential environmental and climatic variables. We observed that about 60% of the areas, which had highest richness and endemism values, are still not included in protected areas in Nepal. We quantitatively analyzed the species richness and endemicity patterns of Nepal and were able to identify 19 areas of high species diversity and endemicity, six of which are newly identified.

Briscoe Runquist, R. D., T. A. Lake, and D. A. Moeller. 2021. Improving predictions of range expansion for invasive species using joint species distribution models and surrogate co‐occurring species. Journal of Biogeography 48: 1693–1705.

Aims: Species distribution models (SDMs) are often used to forecast potential distributions of important invasive or rare species. However, situations where models could be the most valuable ecologically or economically, such as for predicting invasion risk, often pose the greatest challenges to SDM…