Individual identification and confirmation of nest site fidelity in Painted Stork (<em>Mycteria leucocephala</em>) using Deep Transfer Learning

Accurate individual identification is vital in field studies. Since traditional marking techniques, though effective, can be intrusive and potentially disrupt natural behaviours, identification using natural markings has gained popularity across various taxa as a non-invasive alternative. Here, we report on a Painted Stork (Mycteria leucocephala) with a distinctive neck injury mark, observed at the National Zoological Park (Delhi Zoo) over three consecutive breeding seasons (2022–2024). To verify its identity and assess nest-site fidelity, we employed a non-invasive approach combining morphometric measurements and Deep Transfer Learning-based image analysis. High-resolution photographs were used to extract linear measurements and assess repeatability, while a Deep Transfer Learning classifier further validated the individual’s identity with 98% accuracy. Image-based morphometric measurements were particularly reliable for longer morphological features, confirming that the scar-marked st..., 1.&nbsp;&nbsp;&nbsp;&nbsp; Morphological measurements of Ringo We used 82 photographs of Ringo from a collection of 100 that had proper orientation. The mean of the morphological variables of Ringo taken during 2024 was compared with randomly selected images of 2022 and 2023. With tps DIG we carefully measured morphological features in pixel units, namely (1) Upper mandible, (2) Lower mandible, (3) the distance between the mouth corner to the inside corner of the eye, (4) the distance between the inside corner of the eye to the top end of the right nostril, (5) The distance from the base of the pectoral wing to the tip of the wing covering black and white, (6) distance from the feather region to the tarsus and tibia junction. All the above morphological measurements are available in the Excel format. 2.&nbsp;&nbsp;&nbsp;&nbsp; Deep Transfer Learning Using the pre-trained model (ResNet-50), we fine-tuned our model with Ringo datasets collected during 2022, 2023, and 2024 to train, valida..., # Individual identification and confirmation of nest site fidelity in Painted Stork (Mycteria leucocephala) using Deep Transfer Learning Dataset DOI: [10.5061/dryad.c2fqz61p0](10.5061/dryad.c2fqz61p0) ## Description of the data and file structure #### File: Details_of_the_PsScarNet_Layers.txt **Description:** The layer details of the Deep Transfer Learning model which we have developed is available in text file. ##### Variables * It has 177 layers. #### File: PsScarNet_Code.m **Description:** The MATLAB code is provided to run the model. % This **PsScarNet_Code.m** MATLAB code classifies a new image using a pre-trained neural network model (**PsScarNet.mat**). % Ensure you have the following prerequisites before running the code: **% Prerequisites:** % 1. MATLAB installed with the Deep Learning Toolbox. % 2. The pre-trained neural network model (**PsScarNet.mat**) should be in MATLAB workspace. % 3. Extract the images from the **Sample_images_PS.zip** and the image you wa...,