Marja Niemi

Estimating and Mitigating Perinatal Mortality in the Endangered Saimaa Ringed Seal (Phoca hispida saimensis) in a Changing Climate

The ringed seal (Phoca hispida) is dependent on sufficient ice and snow cover for a breeding habitat. Therefore, climate change has a negative effect on pup survival. We developed methods to estimate perinatal mortality and to mitigate the effects of mild winters on the critically endangered subspecies (P. h. saimensis). Underwater surveys were used for collecting pup carcasses and placentas. Lanugo pup mortality was 13.5% and Brucella sp. was not found in the placentas. Camera traps showed sporadic human and medium-sized carnivore activity in the breeding habitat. Although carnivore activity was most intensive at lair sites, no penetration of the lairs was observed. We developed a method to mitigate the effects of poor snow cover by piling up snowdrifts (n = 117) at potential lair sites. Seals subsequently occupied 62% of these snow drifts. We suggest that the methods developed in this study should be implemented to conserve the Saimaa ringed seal.

Segmentation of Saimaa Ringed Seals for Identification Purposes

Wildlife photo-identification is a commonly used technique to identify and track individuals of wild animal populations over time. It has various applications in behavior and population demography studies. Nowadays, mostly due to large and labor-intensive image data sets, automated photo-identification is an emerging research topic. In this paper, the first steps towards automatic individual identification of the critically endangered Saimaa ringed seal (Phoca hispida saimensis) are taken. Ringed seals have a distinctive permanent pelage pattern that is unique to each individual making the image-based identification possible. We propose a superpixel classification based method for the segmentation of ringed seal in images to eliminate the background and to simplify the identification. The proposed segmentation method is shown to achieve a high segmentation accuracy with challenging image data. Furthermore, we show that using the obtained segmented images promising identification results can be obtained even with a simple texture feature based approach. The proposed method uses general texture classification techniques and can be applied also to other animal species with a unique fur or skin pattern.

Automatic individual identification of Saimaa ringed seals

In order to monitor an animal population and to track individual animals in a non-invasive way, identification of individual animals based on certain distinctive characteristics is necessary. In this study, automatic image-based individual identification of the endangered Saimaa ringed seal ( Phoca hispida saimensis ) is considered. Ringed seals have a distinctive permanent pelage pattern that is unique to each individual. This can be used as a basis for the identification process. The authors propose a framework that starts with segmentation of the seal from the background and proceeds to various post-processing steps to make the pelage pattern more visible and the identification easier. Finally, two existing species independent individual identification methods are compared with a challenging data set of Saimaa ringed seal images. The results show that the segmentation and proposed post-processing steps increase the identification performance.