Animal Molecular Breeding 2024, Vol.14, No.1, 130-140 http://animalscipublisher.com/index.php/amb 131 between these technologies can enhance our ability to predict and mitigate the impacts of environmental changes on wildlife, ultimately contributing to more informed and effective conservation strategies. This study will explore the current state of research on the integration of genomics and remote sensing technologies for wildlife monitoring. We will examine the methodologies, applications, and case studies that demonstrate the potential of these technologies to improve our understanding and management of wildlife populations. By highlighting the advancements and challenges in this field, we aim to provide a comprehensive overview of the prospects for integrating genomics and remote sensing in wildlife conservation. 1 Overview of Genomic Technologies Genomic technologies have revolutionized the field of wildlife monitoring and conservation, providing unprecedented insights into genetic diversity, population structure, and disease dynamics. These advancements are crucial for developing effective conservation strategies and managing wildlife populations in the face of environmental changes and anthropogenic pressures. 1.1 Key genomic tools and techniques The advent of next-generation sequencing (NGS) has been a game-changer in genomics, enabling the collection of genome-wide data across a broad range of taxa. Techniques such as reduced single nucleotide polymorphism (SNP) panels, microfluidic genotyping, and deep sequencing platforms have become essential tools in wildlife genomics (Ogden, 2011; Steiner et al., 2013; Thaden et al., 2020). These methods allow for the precise identification of genetic markers, which are critical for various applications, including individual identification, hybridization assessment, and population structure analysis (Ogden, 2011; Thaden et al., 2020). 1.2 Applications in genetic diversity and population structure analysis Genomic tools provide detailed insights into the genetic diversity and population structure of wildlife species, which are vital for conservation efforts. For instance, population genomics can estimate effective population size, inbreeding levels, and demographic history, all of which are crucial for understanding the evolutionary potential of populations (Steiner et al., 2013; Hohenlohe et al., 2020). These analyses help identify genetic loci responsible for adaptation to changing environments, thereby informing strategies to manage adaptive variation and enhance the resilience of wildlife populations (Steiner et al., 2013; Hohenlohe et al., 2020; Wambugu and Henry, 2022). 1.3 Implications for disease surveillance and management in wildlife Genomic methodologies are also pivotal in wildlife disease surveillance and management. They enable the detection and characterization of pathogens, uncover routes of disease transmission, and elucidate the interactions between hosts and pathogens (Blanchong et al., 2016). For example, genetic and genomic tools can identify loci associated with disease susceptibility and inbreeding depression, which are critical for predicting and mitigating the impacts of diseases on wildlife populations (Steiner et al., 2013; Blanchong et al., 2016). These insights are essential for developing targeted interventions to control wildlife diseases and protect both wildlife and human health (Blanchong et al., 2016). In summary, the integration of genomic technologies into wildlife monitoring provides a robust framework for understanding genetic diversity, population dynamics, and disease ecology. These advancements are instrumental in shaping effective conservation strategies and ensuring the long-term sustainability of wildlife populations. 2 Overview of Remote Sensing Technologies Remote sensing technologies have revolutionized wildlife monitoring by providing non-invasive, efficient, and comprehensive methods for tracking and studying wildlife populations and their habitats. These technologies encompass a wide range of tools and techniques that leverage satellite imagery, aerial photography, and ground-based sensors to collect data over large spatial and temporal scales. 2.1 Spectrum of remote sensing tools Remote sensing tools vary widely in their capabilities and applications. Satellite imagery and aerial photography are commonly used for large-scale habitat mapping and monitoring, while ground-based sensors, such as camera
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