Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster (Nephrops norvegicus)

Summary

Here we present a protocol to individually track animals over a long period of time. It uses computer vision methods to identify a set of manually constructed tags by using a group of lobsters as case study, simultaneously providing information on how to house, manipulate, and mark the lobsters.

Abstract

We present a protocol related to a video-tracking technique based on the background subtraction and image thresholding that makes it possible to individually track cohoused animals. We tested the tracking routine with four cohoused Norway lobsters (Nephrops norvegicus) under light-darkness conditions for 5 days. The lobsters had been individually tagged. The experimental setup and the tracking techniques used are entirely based on the open source software. The comparison of the tracking output with a manual detection indicates that the lobsters were correctly detected 69% of the times. Among the correctly detected lobsters, their individual tags were correctly identified 89.5% of the times. Considering the frame rate used in the protocol and the movement rate of lobsters, the performance of the video tracking has a good quality, and the representative results support the validity of the protocol in producing valuable data for research needs (individual space occupancy or locomotor activity patterns). The protocol presented here can be easily customized and is, hence, transferable to other species where the individual tracking of specimens in a group can be valuable for answering research questions.

Introduction

In the last few years, automated image-based tracking has provided highly accurate datasets which can be used to explore basic questions in ecology and behavior disciplines¹. These datasets can be used for the quantitative analysis of animal behavior^2,3. However, each image methodology used for tracking animals and behavior evaluation has its strengths and limitations. In image-based tracking protocols that use spatial information from previous frames in a movie to track animals^4,5,6, errors ca....

Protocol

The species used in this study is not an endangered or protected species. Sampling and laboratory experiments followed the Spanish legislation and internal institutional (ICM-CSIC) regulations regarding animal welfare. Animal sampling was conducted with the permission of the local authority (Regional Government of Catalonia).

1. Animal Maintenance and Sampling

NOTE: The following protocol is based on the assumption that researchers can sample N. n.......

Discussion

The performance and representative results obtained with the video-tracking protocol confirmed its validity for applied research in the field of animal behavior, with a specific focus on social modulation and circadian rhythms of cohoused animals. The efficiency of animal detection (69%) and the accuracy of tag discrimination (89.5%) coupled with the behavioral characteristics (i.e., movement rate) of the target species used here suggest that this protocol is a perfect solution for long-term experimental trials (e.g., da.......

Materials

Name	Company	Catalog Number	Comments
Tripod 475	Manfrotto	A0673528	Discontinued
Articulated Arm 143	Manfrotto	D0057824	Discontinued
Camera USB 2.0 uEye LE	iDS	UI-1545LE-M	https://en.ids-imaging.com/store/products/cameras/usb-2-0-cameras/ueye-le.html
Fish Eye Len C-mount f=6mm/F1.4	Infaimon	Standard Optical	https://www.infaimon.com/es/estandar-6mm
Glass Fiber Tank 1500x700x300 mm
Black Felt Fabric
Wood Structure Tank			5 Wood Strips 50x50x250 mm
Wood Structure Felt Fabric			10 Wood Strips 25x25x250 mm
Stainless Steel Screws			As many as necessary for fix wood strips structures
PC			2-cores CPU, 4GB RAM, 1 GB Graphics, 500 GB HD
External Storage HDD			2 TB capacity desirable
iSPY Sotfware for Windows PC	iSPY		https://www.ispyconnect.com/download.aspx
Zoneminder Software Linux PC	Zoneminder		https://zoneminder.com/
OpenCV 2.4.13.6 Library	OpenCV		https://opencv.org/
Python 2.4	Python		https://www.python.org/
Camping Icebox
Plastic Tray
Cyanocrylate Gel			To glue tag’s
1 black PVC plastic sheet (1 mm thickness)			Tag's construction
1 white PVC plastic sheet (1 mm thickness)			Tag's construction
4 Tag’s Ø 40 mm			Maked with black & white PVC plastic sheet
3 m Blue Strid Led Ligts (480 nm)			Waterproof as desirable
3 m IR Strid Led Ligts (850 nm)			Waterproof as desirable
6m  Methacrylate Pipes Ø 15 mm			Enclosed Strid Led
4 PVC Elbow  45o Ø 63 mm			Burrow construction
3 m Flexible PVC Pipe Ø 63 mm			Burrow construction
4 PVC Screwcap Ø 63 mm			Burrow construction
4 O-ring Ø 63 mm			Burrow construction
4 Female PVC socket glue / thread Ø 63 mm			Burrow construction
10 m DC 12V Electric Cable			Light Control Mechanism
Ligt Power Supply DC 12V 300 w			Light Control Mechanism
MOSFET, RFD14N05L, N-Canal, 14 A, 50 V, 3-Pin, IPAK (TO-251)	RS Components	325-7580	Light Control Mechanism
Diode, 1N4004-E3/54, 1A, 400V, DO-204AL, 2-Pines	RS Components	628-9029	Light Control Mechanism
Fuse Holder	RS Components	336-7851	Light Control Mechanism
2 Way Power Terminal 3.81mm	RS Components	220-4658	Light Control Mechanism
Capacitor 220 µF 200 V	RS Components	440-6761	Light Control Mechanism
Resistance 2K2 7W	RS Components	485-3038	Light Control Mechanism
Fuse 6.3x32mm 3A	RS Components	413-210	Light Control Mechanism
Arduino Uno Atmel Atmega 328 MCU board	RS Components	715-4081	Light Control Mechanism
Prototipe Board CEM3,3 orific.,RE310S2	RS Components	728-8737	Light Control Mechanism
DC/DC converter,12Vin,+/-5Vout 100mA 1W	RS Components	689-5179	Light Control Mechanism
2 SERA T8 blue moonlight fluorescent bulb 36 watts	SERA		Discontinued / Light isolated facility