The dietary patterns of water deer recently rediscovered in Northeast China exhibit remarkable similarities to those observed in other regions.

ABSTRACT: Climate change, human activities, and habitat fragmentation-or even loss-pose ongoing threats to the survival of wildlife. Understanding the dietary habits of endangered species is a critical component of their conservation. In this study, we investigated the diet of water deer (Hydropotes inermis) by integrating traditional fecal microhistological analysis with a deep learning algorithm. Fecal samples were collected from water deer in northeastern China, with microscopic slides prepared for both the warm season (203 samples) and cold season (451 samples). A deep learning model was trained and tested using labeled images of 130 known plant species, achieving an accuracy of 99.83%. The results revealed that water deer consume 110 plant species from 86 genera and 40 families annually. The di

SUBMITTER: Li Z 

PROVIDER: S-EPMC11920225 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature