Vermeulen, E. | Search bioRxiv

bioRxiv2023

Universal baleen whale microsatellite panel for individual identification and power to detect parentage

Highly polymorphic single tandem repeat loci (STR, also known as microsatellite loci) remain a familiar, cost efficient class of markers for genetic analyses in ecology, behavior and conservation. We characterize a new universal set of ten STR loci (from 28 potential candidate loci) in seven baleen whale species, which are optimized for PCR amplification in two multiplex reactions along with a Y chromosome marker for sex determination. The optimized, universal set of STR loci provides an ideal starting point for new studies in baleen whales aimed at individual-based and population genetic studies, and facilitates data sharing among research groups. Data from the new STR loci were combined with genotypes from other published STR loci to assess the power to assign parentage (paternity) using exclusion in four species: fin whales, humpback whales, blue whales and bowhead whales. We argue that parentage studies should present a power analysis to demonstrate that the specific data are sufficiently informative to assign parentage with statistical rigor.

genetics↗

bioRxiv2022

Wildlife and Marine Mammal Spatial Observatory: Observation and automated detection of Southern Right Whales in multispectral satellite imagery

The Wildlife and Marine Mammal Spatial Observatory is a joint research effort for the census of wildlife and particularly of marine mammals in satellite imagery. In that context, this paper illustrates the development of a high accuracy algorithm for the detection of right whales in sub-meter resolution multispectral satellite imagery with the constraint of a relatively small sample support of 580 southern right whale images. A significant space is devoted to exploratory data analysis to describe the statistical structure of right whale pixels and ocean surface pixels across multispectral bands. Observations of southern right whale in satellite imagery are divided into typical and atypical right whale forms and the first observations of right whale mother and calf pairs in satellite imagery are presented. Measurements of whales are furthermore automatically extracted from whale observations (major axis length, minor axis length, etc). A significant space is also devoted to statistical data exploration, a step frequently overlooked in machine learning solutions, that yet offers interesting insight into the structure of animal detection in satellite imagery. The extracted statistics can readily be used by researchers to develop detection solutions even with low sample support. The adopted solution for detection consists of feature extraction with a convolutional neural network followed by classification with a support vector machine. 20 different convolutional neural networks were tested for feature extraction. Biostatistics parameters (accuracy, sensitivity, specificity and precision) were measured for comparison. Most architectures generally achieved high performance with low false positive and false negative rates. 100% accuracy is achieved in the case of 2 convolutional neural networks, Nasnet Large and Inception V3, and only with a specific selection of multispectral bands. NB: This is a preprint that does not include satellite imagery due recent reviews

bioinformatics↗