AMB_2024v14n1

Animal Molecular Breeding 2024, Vol.14, No.1, 130-140 http://animalscipublisher.com/index.php/amb 139 Forester B., Landguth E., Hand B., and Balkenhol N., 2018, Landscape Genomics for Wildlife Research, In: Population Genomics: Wildlife, pp.1-40. https://doi.org/10.1007/13836_2018_56 He K., Bradley B., Cord A., Rocchini D., Tuanmu M., Schmidtlein S., Turner W., Wegmann M., and Pettorelli N., 2015, Will remote sensing shape the next generation of species distribution models, Remote Sensing in Ecology and Conservation, 1(1): 4-18. https://doi.org/10.1002/rse2.7 Hohenlohe P., Funk W., and Rajora O., 2020, Population genomics for wildlife conservation and management, Molecular Ecology, 30(1): 62-82. https://doi.org/10.1111/mec.15720 PMid:33145846 PMCid:PMC7894518 Hohenlohe P.A., and Rajora O.P., (eds.), 2021, Population Genomics: Wildlife, pp.41-55. https://doi.org/10.1007/978-3-030-63489-6 Johnson J., Altwegg R., Evans D., Ewen J., Gordon I., Pettorelli N., and Young J., 2016, Is there a future for genome‐editing technologies in conservation, Animal Conservation, 19: 97-101. https://doi.org/10.1111/acv.12273 Kerr J., and Ostrovsky M., 2003, From space to species: ecological applications for remote sensing, Trends in Ecology and Evolution, 18(6): 299-305. https://doi.org/10.1016/S0169-5347(03)00071-5 Marvin D., Koh L., Lynam A., Wich S., Davies A., Krishnamurthy R., Stokes E., Starkey R., and Asner G., 2016, Integrating technologies for scalable ecology and conservation, Global Ecology and Conservation, 7: 262-275. https://doi.org/10.1016/j.gecco.2016.07.002 Miao Z., Liu Z., Gaynor K., Palmer M., Yu S., and Getz W., 2021, Iterative human and automated identification of wildlife images, Nature Machine Intelligence, 3(10): 885-895. https://doi.org/10.1038/s42256-021-00393-0 Morota G., Ha D., and Chen J., 2022, 19 how can artificial intelligence accelerate phenotyping efforts in animal breeding, Journal of Animal Science, 100(Suppl 3): 11. https://doi.org/10.1093/jas/skac247.020 PMCid:PMC9493747 Ogden R., 2011, Unlocking the potential of genomic technologies for wildlife forensics, Molecular Ecology Resources, 11: 109-116. https://doi.org/10.1111/j.1755-0998.2010.02954.x PMid:21429167 Schmidt T., Thia J., and Hoffmann A., 2023, How can genomics help or hinder wildlife conservation, Annual Review of Animal Biosciences, 12(1): 45-68. https://doi.org/10.1146/annurev-animal-021022-051810 PMid:37788416 Shafer A., Northrup J., Wikelski M., Wittemyer G., and Wolf J., 2016, Forecasting ecological genomics: high-tech animal instrumentation meets high-throughput sequencing, PLoS Biology, 14(1): e1002350. https://doi.org/10.1371/journal.pbio.1002350 PMid:26745372 PMCid:PMC4712824 Steiner C., Putnam A., Hoeck P., and Ryder O., 2013, Conservation genomics of threatened animal species, Annual Review of Animal Biosciences, 1(1): 261-281. https://doi.org/10.1146/annurev-animal-031412-103636 PMid:25387020 Stephenson P., 2019, Integrating remote sensing into wildlife monitoring for conservation, Environmental Conservation, 46(3): 181-183. https://doi.org/10.1017/S0376892919000092 Storfer A., Kozakiewicz C., Beer M., and Savage A., 2020, Applications of population genomics for understanding and mitigating wildlife disease, In: Population Genomics: Wildlife, pp.357-383. https://doi.org/10.1007/13836_2020_73 Thackeray S., and Hampton S., 2020, The case for research integration, from genomics to remote sensing, to understand biodiversity change and functional dynamics in the world's lakes, Global Change Biology, 26(6): 3230-3240. https://doi.org/10.1111/gcb.15045 PMid:32077186 Thaden A., Nowak C., Tiesmeyer A., Reiners T., Alves P., Lyons L., Mattucci F., Randi E., Cragnolini M., Galián J., Hegyeli Z., Kitchener A., Lambinet C., Lucas J., Mölich T., Ramos L., Schockert V., and Cocchiararo B., 2020, Applying genomic data in wildlife monitoring: Development guidelines for genotyping degraded samples with reduced single nucleotide polymorphism panels, Molecular Ecology Resources, 20(3): 662-680. https://doi.org/10.1111/1755-0998.13136 PMid:31925943 PMCid:PMC7199164 Toro A.P., Bueno I.T., Werner J.P., Antunes J.F., Lamparelli R.A., Coutinho A.C., Esquerdo J.C., Magalhães P.S., and Figueiredo G. K., 2023, SAR and optical data applied to early-season mapping of integrated crop–livestock systems using deep and machine learning algorithms, Remote Sensing, 15(4): 1130. https://doi.org/10.3390/rs15041130

RkJQdWJsaXNoZXIy MjQ4ODY0NQ==