Reading tea leaves worldwide: decoupled drivers of initial litter decomposition mass-loss rate and stabilisation

The breakdown of plant material fuels soil functioning and biodiversity. Currently, process understanding of global decomposition patterns and the drivers of such patterns are hampered by the lack of coherent large-scale datasets. We buried 36,000 individual litterbags (tea bags) worldwide and found an overall negative correlation between initial mass-loss rates and stabilization factors of plant-derived carbon, using the Tea Bag Index (TBI). The stabilization factor quantifies the degree to which easy-to-degrade components accumulate during early-stage decomposition (e.g. by environmental limitations). However, agriculture and an interaction between moisture and temperature led to a decoupling between initial mass-loss rates and stabilization, notably in colder locations. Using TBI improved mass-loss estimates of natural litter compared to models that ignored stabilization. Ignoring the transformation of dead plant material to more recalcitrant substances during early-stage decomposition, and the environmental control of this transformation, could overestimate carbon losses during early decomposition in carbon cycle models

Estimating brown hyaena occupancyusing baited camera traps

Conservation and management of brown hyaenas (Hyaena brunnea) is hampered by a lack ofinformation on abundance and distribution, which is difficult and labour-intensive to obtain.However, occupancy surveys offer a potentially efficient and robust means of assessingbrown hyaena populations. We evaluate the efficacy of camera trapping for estimatingbrown hyaena occupancy, and the effect of environmental variables and lures on detectionprobability. We estimated population density in Pilanesberg National Park, South Africa, at2.8/100 km2, occupancy at 1.0 and model-averaged detection probability at 0.1. Using a fishlure increased detection probability to 0.2 and significantly increased encounter rates. Wealso found that brown hyaenas are more likely to be detected in areas of scrub or woodlandrather than grassland. Our results suggest that 13 camera sites would be needed to achievean occupancy estimate with S.E. of 0.05, and a minimum of 16–34 sampling occasions (withand without the fish lure) should be used in comparable study areas. We conclude thatcamera trapping is a viable method of estimating brown hyaena occupancy at local andlandscape scales and capture–recapture analysis is also possible at a local scale