1/7 🌿 Where are greatest number of #PlantSpecies in #Mountains? 🏔️
Our recent study in #Forests explored elevational patterns of plant #SpeciesRichness in Western Himalayas.
🔗 https://doi.org/10.3390/f16101591
#Biodiversity #Biogeography #Ecology #ElevationalGradients #Himalayas #ProtectedAreas
3️⃣ What did we find?
While species richness often showed complex non-linear unimodal (hump-shaped) patterns, simple linear decreasing pattern was also observed.
Patterns vary with extent and position of #ElevationalGradients !
4️⃣ Is this just a random geometric effect?
We tested the Mid-Domain Effect (MDE) null model and found substantial deviations from its predictions.
This means plant distribution in the Himalayas is NOT a simple game of chance!
5️⃣ Influence of observed species?
As more species were added, elevational richness became more distinctly unimodal, converging toward the MDE predictions.
This effect also varies with extent and position of elevational gradients.
6️⃣ Conservation Takeaway
🔑 Mid-elevational zones for conservation priorities, where #SpeciesRichness is greatest.
🧭 Read the full #OpenAccess article for the detailed analyses:
🔗 https://www.mdpi.com/1999-4907/16/10/1591
7️⃣ Data and #RStats codes archived at #figshare :
🔗 https://doi.org/10.6084/m9.figshare.23828784.v3
A copy is maintained at GitHub:
🔗 https://github.com/kumar-a/richness-patterns
AbstractUnderstanding the patterns and drivers of species distribution has remained a central theme for biogeographical, conservation, and ecological research. This study aims to investigate the elevational patterns of plant species richness and compare the observed species richness with the predictions of the mid-domain effect (MDE) null model. By combining information from field observations and the published literature, we compiled a comprehensive database of the elevational distribution of plant species for three protected areas in the Western Himalayas. We used generalised linear model (GLM) and null model simulations to explore the elevational patterns of plant species richness. Our study revealed simple linear to complex non-linear patterns depending on the location and range of the elevational gradient. While non-linear unimodal patterns were common, a linear decreasing pattern was also observed. The observed species richness showed consistent deviations from the predictions of the mid-domain effect null model, suggesting that factors beyond the range constraints shape species richness patterns. These observations indicate that richness patterns are not solely generated by random processes, rather climatic gradients, ecological interactions, and topographic heterogeneity can shape these patterns. Understanding these factors can aid in predicting and managing the impacts of ongoing environmental changes on Himalayan biodiversity.How to useA comprehensive species checklist was compiled for each site by combining the information gathered from field surveys and literature surveys. The World Checklist of Vascular Plants (WCVP) was followed to standardise all the botanical names and their authorities. The README file provides a description of data files and directory structure. The "index.qmd" file presents a reproducible initial draft of the manuscript with all R codes used during the analysis.Fork or clone the linked github repository https://github.com/kumar-a/richness-patternsAlternatively, you can download all the files in the repository as .zipOpen the richness-patterns.Rproj file in RStudio and renderFeel free to reach out Abhishek Kumar, if scripts are not working or have any questions.CitationKumar, A., Patil, M., Kumar, P., & Singh, A. N. (2025). Elevational Patterns of Plant Species Richness: Insights from Western Himalayas. Forests, 16(10), 1591. https://doi.org/10.3390/f16101591
Abhishek Kumar