I am Prabhat Raj Dahal from Kathmandu, Nepal. I am an environmental engineer and an aspiring environmental scientist. I have a M.Sc. degree in Earth System Science from Universität Hohenheim, Germany and I will be starting my doctoral journey at La Sapienza and Birdlife International from late 2018. My broader research interests include application of geospatial tools like GIS and remote sensing in the domain of environmental sciences. My master’s thesis involved classification of different types of glaciers and glacial lakes in and around the Mt. Everest region using satellite imagery and construction of a time series for 23 years. Also, I have a keen interest in observing earth as a system and the interactions among the different components of this system. Recently I have been involved with IUCN-Nepal and Kathmandu Living Labs in mapping and modelling the habitat areas of 75 different mammalian species found in Nepal along with their respective life zones based on climatic data under the context of climate change. I am very fond of using open source tools for spatial data analysis and visualization. I strongly believe geospatial technology in combination with in situ methods has a great scope in conservation science. In my spare time I am mostly occupied with music, literature and wandering in the foothills of the Himalayas.
PhD project: Advancing quantitative analyses for IUCN Red List assessments of species’ risk of extinction
In the IUCN Red List, the relative extinction risk of a species is assessed against five criteria that take into account population size and decline (criteria A, C), geographic range size and decline (criterion B), very restricted range or population (criterion D), and/or quantitative analyses (criterion E). Several key parameters for the application of criteria can be estimated using common assumptions, baseline data and models across taxa, rather than assessed independently on individual species. Examples include estimates and projections of population decline based on recent trends or future scenarios, to apply to criteria A2 (past declines) A3 (past and future declines) and A4 (future declines), and robust estimations of other key parameters (e.g. generation length). Quantitative analyses are defined as "any form of analysis which estimates the extinction probability of a taxon based on known life history, habitat requirements, threats and specified management options" (IUCN 2012). These are a crucial concept in applying Criterion E, which is based on quantitative models of extinction risk.
This project will explore the degree to which Red List Assessments can be improved and made more rigorous and consistent by including more quantitative data, either directly through criterion E, or as parameters fed to criteria A-D, using mammals and birds to test different approaches. As an example of parameters to apply to criteria A-D that could be estimated, the project will aim to improve the methods used to develop maps of the Extent of Suitable Habitat (ESH) in order to reduce rates of commission (ie predicting the species to be present when it is actually absent) without increasing rates of omission (ie predicting a species to be absent when it is actually present). This will make use of the increasing volumes of citizen science data to independently assess rates of omission and commission, as a way of quantifying the extent to which different ways of reducing Extent Of Occurrence (EOO) maps to ESH maps improve accuracy. ESH maps in turn can be used to infer estimates of the upper bound of Area of Occupancy. The results of this project should demonstrate major scope of improvement of Red List assessments even for species for which little information is available, by making the best use of the other data to contextualise such information. Outputs of this project will be Extent of Suitable Habitat maps and estimates of generation lengths for thousands of vertebrate species that will be applicable to future iterations of the IUCN Red List of Threatened Species and which will be of critical utility for the identification of Key Biodiversity Areas.
Jung, M., Dahal, P.R., Butchart, S.H.M., Donald, P.F., De Lamo, X., Lesiv, M., Kapos, V., Rondinini, C., Visconti, P. (2020) A global map of terrestrial habitat types. Scientific Data 7, 256. https://doi.org/10.1038/s41597-020-00599-8 → Open Access Repository
- IUCN. (2012). IUCN Red List Categories and Criteria: Version 3.1. Second edition. Gland, Switzerland and Cambridge, UK: IUCN. iv + 32pp.
- Mace, GM, et al. (2008). Quantification of extinction risk: IUCN's system for classifying threatened species. Conservation Biology, 22(6), 1424-1442.
- Pacifici, M, et al. (2013) Generation length for mammals. Nature Conservation 5: 87-94.
- Rondinini, C, et al. (2011). Global habitat suitability models of terrestrial mammals. Philosophical Transactions of the Royal Society of London B: Biological Sciences 366.1578: 2633-2641.
- Tracewski, Ł., Butchart, S.H., Di Marco, M., Ficetola, G.F., Rondinini, C., Symes, A., Wheatley, H., Beresford, A.E. and Buchanan, G.M., 2016. Toward quantification of the impact of 21st‐century deforestation on the extinction risk of terrestrial vertebrates. Conservation Biology, 30(5), pp.1070-1079.