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Being the apex predator of Sri Lanka’s forests, the endangered Sri Lankan leopard (Panthera pardus kotiya) plays a crucial role in maintaining the balance of natural ecosystems. In this study, we aimed to address the paucity of data related to one of the major leopard habitats of the country, Kumana National Park (KNP). This study investigates the spatial occupancy, population density, and activity patterns of the Sri Lankan leopard in KNP, Sri Lanka. Our findings reveal a higher concentration of leopards around water bodies and rocky areas, which provide shelter and support prey species such as wild buffalo and spotted deer. Using random encounter models (REM) and spatially explicit capture–recapture (SECR) analyses the population density of leopards was estimated. The study identified the eastern region of KNP as having one of the highest recorded leopard densities globally, with REM and SECR estimates showing statistically similar results of approximately 41 leopards per 100 km². This high density is attributed to the availability of prey and habitat variability that supports the ecological needs of leopards. The study underscores the importance of KNP as a stronghold of leopards in southern Sri Lanka and the necessity of preserving its natural habitats.

Ranking Sri Lanka among the World’s Top Mismanaged Waste Polluters: Does Model Data Change the Story?

By R. R. M. K. P. Ranatunga, Dilhara Wijetunge, W. V. P. H. Ranaweera, Chin-Chang Hung, Shang-Yin Vanson Liu, Qamar Schuyler, T. J. Lawson and Britta Denise Hardesty

Published in: Sustainability

The accumulation of Mismanaged Plastic Waste (MPW) in the environment is a global
concern. The amount of waste generated by countries is estimated using globally available data layers
and/or empirical surveys. Unlike globally available metadata, MPW estimates based on empirical
surveys allow for better visualization of amounts, potential pathways, and hotspots. A model study
conducted in 2015, based on global metadata, ranked Sri Lanka in fifth position among the world’s
worst mismanaged plastic offenders. However, there is significant uncertainty in the source data on
waste generation and the parameters used for model prediction, such as plastic usage (5.1 kg per
person per day), since Sri Lanka is predominantly a service-based country with limited plastic-based
manufacturing industries. The source data for plastic usage has been derived from a very limited
study, biased toward waste hotspots that have not been verified. Our empirical data has shown
that population density, one of the key parameters used for global ranking, is a weak predictor of
debris densities. Therefore, we argue that the given plastic leakage data and the ranking is an error.
Therefore, Sri Lanka’s position in the global ranking deserves reconsideration. Further, we propose
the need for model predictions that rely on global metadata to be backed by robust and unbiased
designed surveys that are based on empirical data and undergo intense baseline data verification to
generate more precise predictions on litter quantities.