Trapping Elusive Cats: Using Intensive Camera Trapping to Estimate the Density of a Rare African Felid

Camera trapping studies have become increasingly popular to produce population estimates of individually recognisable mammals. Yet, monitoring techniques for rare species which occur at extremely low densities are lacking. Additionally, species which have unpredictable movements may make obtaining reliable population estimates challenging due to low detectability. Our study explores the effectiveness of intensive camera trapping for estimating cheetah (Acinonyx jubatus) numbers. Using both a more traditional, systematic grid approach and pre-determined, targeted sites for camera placement, the cheetah population of the Northern Tuli Game Reserve, Botswana was sampled between December 2012 and October 2013. Placement of cameras in a regular grid pattern yielded very few (n = 9) cheetah images and these were insufficient to estimate cheetah density. However, pre-selected cheetah scent-marking posts provided 53 images of seven adult cheetahs (0.61 ± 0.18 cheetahs/100km²). While increasing the length of the camera trapping survey from 90 to 130 days increased the total number of cheetah images obtained (from 53 to 200), no new individuals were recorded and the estimated population density remained stable. Thus, our study demonstrates that targeted camera placement (irrespective of survey duration) is necessary for reliably assessing cheetah densities where populations are naturally very low or dominated by transient individuals. Significantly our approach can easily be applied to other rare predator species.     

The strength of SMAD1/5 activity determines the mode of stem cell division in the developing spinal cord

The different modes of stem cell division are tightly regulated to balance growth and differentiation during organ development and homeostasis. However, the mechanisms controlling such events are not fully understood. We have developed markers that provide the single cell resolution necessary to identify the three modes of division occurring in a developing nervous system: self-expanding, self-renewing, and self-consuming. Characterizing these three modes of division during interneuron generation in the developing chick spinal cord, we demonstrated that they correlate to different levels of activity of the canonical bone morphogenetic protein effectors SMAD1/5. Functional in vivo experiments showed that the premature neuronal differentiation and changes in cell cycle parameters caused by SMAD1/5 inhibition were preceded by a reduction of self-expanding divisions in favor of self-consuming divisions. Conversely, SMAD1/5 gain of function promoted self-expanding divisions. Together, these results lead us to propose that the strength of SMAD1/5 activity dictates the mode of stem cell division during spinal interneuron generation.     

Phenotype Classification of Zebrafish Embryos by Supervised Learning

Zebrafish is increasingly used to assess biological properties of chemical substances and thus is becoming a specific tool for toxicological and pharmacological studies. The effects of chemical substances on embryo survival and development are generally evaluated manually through microscopic observation by an expert and documented by several typical photographs. Here, we present a methodology to automatically classify brightfield images of wildtype zebrafish embryos according to their defects by using an image analysis approach based on supervised machine learning. We show that, compared to manual classification, automatic classification results in 90 to 100% agreement with consensus voting of biological experts in nine out of eleven considered defects in 3 days old zebrafish larvae. Automation of the analysis and classification of zebrafish embryo pictures reduces the workload and time required for the biological expert and increases the reproducibility and objectivity of this classification.