A Review on Bridging Molecular Biology and Ecological Dynamics through Integrative Approaches in Zoology

Deep Shikha *

Punjab Agricultural University, Ludhiana, 141004, India.

Gurrala Saivamsireddy

Department of Genetics and Plant Breeding, Kl College of Agriculture, Koneru Lakshmaih Educational Foundation, India.

M. Anbazhagan

Department of Environmental Science, Periyar University, Salem, India.

M. Veeraragavan

Department of Biochemistry, Mother Teresa College of Agriculture, Affiliated to Tamil Nadu Agricultural University, Coimbatore, Illuppur Road, Pudukkottai, Tamil Nadu, 622 102, India.

B. Rama Devi

Department of Agronomy, KL College of Agriculture, KL University, Andhra Pradesh, India.

Kavuri Kalpana

Department of Genetics and Plant Breeding, Kl College of Agriculture, Koneru Lakshmaiah Education Foundation, Kl Deemed To Be University, Vaddeswaram, Andhra Pradesh, India.

Chandan Kumar Panigrahi

Department of Entomology Faculty of Agricultural Sciences, Siksha 'O' Anusandhan, Deemed to be University, Bhubaneswar, 751003, Odisha, India.

*Author to whom correspondence should be addressed.


The integration of molecular biology with ecological dynamics has emerged as a transformative approach in zoology, enhancing our understanding of biodiversity, ecosystem health, and the adaptive responses of species to environmental changes. This review synthesizes key developments and methodological innovations at the intersection of molecular biology and ecological dynamics, highlighting the application of DNA barcoding, environmental DNA (eDNA) analyses, molecular phylogenetics, and advanced computational models in elucidating complex biological interactions and evolutionary patterns. Significant advancements include the use of high-throughput sequencing technologies and CRISPR-Cas systems that have expanded our ability to explore genetic diversity and manipulate genetic material for conservation purposes. The review discusses the predictive capabilities of integrative models that combine genetic with ecological data, offering insights into species resilience and ecosystem stability under varying environmental scenarios. Challenges in data integration, such as issues of scale, complexity, and the necessity for interdisciplinary cooperation, are critically examined. Technical limitations related to data management and ethical considerations in the use of genetic information are also explored. Looking forward, the review identifies emerging technologies and their potential impacts on ecological and conservation biology, emphasizing the need for policies that support sustainable management and conservation strategies. This review underscores the profound impact of integrating molecular biology with ecological dynamics, which not only enhances our scientific understanding but also provides practical frameworks for addressing global environmental challenges.

Keywords: Molecular biology, ecological dynamics, genomics, eDNA, phylogenetics

How to Cite

Shikha , D., Saivamsireddy , G., Anbazhagan , M., Veeraragavan , M., Devi , B. R., Kalpana , K., & Panigrahi , C. K. (2024). A Review on Bridging Molecular Biology and Ecological Dynamics through Integrative Approaches in Zoology. UTTAR PRADESH JOURNAL OF ZOOLOGY, 45(11), 157–167. https://doi.org/10.56557/upjoz/2024/v45i114082


Download data is not yet available.


Pauls SU, Alp M, Bálint M, Bernabò P, Čiampor Jr F, Čiamporová‐Zaťovičová Z, et al. Integrating molecular tools into freshwater ecology: developments and opportunities. Freshwater Biology. 2014;59 (8):1559-1576.

Moran P. Current conservation genetics: building an ecological approach to the synthesis of molecular and quantitative genetic methods. Ecology of Freshwater Fish. 2002;11(1):30-55.

Orsini L, Schwenk K, De Meester L, Colbourne JK, Pfrender ME, Weider LJ. The evolutionary time machine: using dormant propagules to forecast how populations can adapt to changing environments. Trends in Ecology & Evolution. 2013;28(5):274-282.

Sork VL. Genomic studies of local adaptation in natural plant populations. Journal of Heredity. 2018;109(1): 3-15.

DeAngelis DL. Dynamics of nutrient cycling and food webs Springer Science & Business Media. 2012;9.

Ruppert KM, Kline RJ, Rahman MS. Past, present, and future perspectives of environmental DNA (eDNA) metabarcoding: A systematic review in methods, monitoring, and applications of global eDNA. Global Ecology and Conservation. 2019;17:e00547.

Raes J, Bork P. Molecular eco-systems biology: towards an understanding of community function. Nature Reviews Microbiology. 2008;6(9):693-699.

Manel S, Holderegger R. Ten years of landscape genetics. Trends in Ecology & Evolution. 2013;28(10):614-621.

Ouborg NJ, Vergeer P, Mix C. The rough edges of the conservation genetics paradigm for plants. Journal of Ecology. 2006;94(6):1233-1248.

Pickar-Oliver A, Gersbach CA. The next generation of CRISPR–Cas technologies and applications. Nature reviews Molecular cell biology. 2019;20(8):490-507.

Deng Y, Jiang YH, Yang Y, He Z, Luo F, Zhou J. Molecular ecological network analyses. BMC Bioinformatics. 2012;13:1-20.

MacEachren AM, Kraak MJ. Research challenges in geovisualization. Cartography and Geographic Information Science. 2001;28(1):3-12.

Bourlat SJ, Borja A, Gilbert J, Taylor MI, Davies N, Weisberg SB, et al. Genomics in marine monitoring: new opportunities for assessing marine health status. Marine Pollution Bulletin. 2013;74(1):19-31.

Pauls SU, Alp M, Bálint M, Bernabò P, Čiampor Jr F, Čiamporová‐Zaťovičová Z, et al. Integrating molecular tools into freshwater ecology: developments and opportunities. Freshwater Biology. 2014;59 (8):1559-1576.

Mullis KB. The polymerase chain reaction (Vol. 41, No. 5). Springer science & business media; 1994.

Pervez MT, Abbas SH, Moustafa MF, Aslam N, Shah SSM. A comprehensive review of performance of next-generation sequencing platforms. BioMed Research International. 2022.

Mushtaq M, Ahmad Dar A, Skalicky M, Tyagi A, Bhagat N, Basu U, et al. CRISPR-based genome editing tools: Insights into technological breakthroughs and future challenges. Genes. 2021;12(6):797.

Emanuelli F, Lorenzi S, Grzeskowiak L, Catalano V, Stefanini M, Troggio M, et al. Genetic diversity and population structure assessed by SSR and SNP markers in a large germplasm collection of grape. BMC Plant Biology. 2013;13:1-17.

Turchetto‐Zolet AC, Pinheiro F, Salgueiro F, Palma‐Silva C. Phylogeographical patterns shed light on evolutionary process in South America. Molecular Ecology. 2013;22(5):1193-1213.

Estoup A, Ravigné V, Hufbauer R, Vitalis R, Gautier M, Facon B. Is there a genetic paradox of biological invasion?. Annual Review of Ecology, Evolution and Systematics. 2016;47:51-72.

Caswell H. A general formula for the sensitivity of population growth rate to changes in life history parameters. Theoretical Population Biology. 1978;14(2) :215-230.

Gilpin ME. Enriched predator-prey systems: theoretical stability. Science. 1972;177(4052):902-904.

Kéfi S, Berlow EL, Wieters EA, Joppa LN, Wood SA, Brose U, et al. Network structure beyond food webs: mapping non‐trophic and trophic interactions on Chilean rocky shores. Ecology. 2015;96 (1):291-303.

DeAngelis DL. Dynamics of nutrient cycling and food webs. Springer Science & Business Media; 2012; 9.

Power ME, Tilman D, Estes JA, Menge BA, Bond WJ, Mills LS, et al. Challenges in the quest for keystones: identifying keystone species is difficult—but essential to understanding how loss of species will affect ecosystems. BioScience. 1996;46 (8):609-620.

Dada JO, Mendes P. Multi-scale modelling and simulation in systems biology. Integrative Biology. 2011;3(2):86-96.

Ingold T. The trouble with 'evolutionary biology'. Anthropology today. 2007;23(2): 13-17.

Manel S, Schwartz MK, Luikart G, Taberlet P. Landscape genetics: Combining landscape ecology and population genetics. Trends in Ecology & Evolution. 2003;18(4):189-197.

Hochachka WM, Fink D, Hutchinson RA, Sheldon D, Wong WK, Kelling S. Data-intensive science applied to broad-scale citizen science. Trends in Ecology & Evolution. 2012;27(2):130-137.

Kumar S, Tamura K, Nei M. MEGA3: integrated software for molecular evolutionary genetics analysis and sequence alignment. Briefings in Bioinformatics. 2004;5(2):150-1.

Peng GC, Alber M, Buganza Tepole A, Cannon WR, De S, Dura-Bernal S, et al. Multiscale modeling meets machine learning: What can we learn?. Archives of Computational Methods in Engineering. 2021;28:1017-1037.

Gunderson LH. Ecological resilience—in theory and application. Annual Review of Ecology and Systematics. 2000;31(1):425-439.

Cristescu ME. Genetic reconstructions of invasion history. In: Invasion Genetics: The Baker and Stebbins Legacy. 2016;267-282.

Whitehead A, Pilcher W, Champlin D, Nacci D. Common mechanism underlies repeated evolution of extreme pollution tolerance. Proceedings of the Royal Society B: Biological Sciences. 2012;279 (1728):427-433.

Taberlet P, Bonin A, Zinger L, Coissac E. Environmental DNA: For biodiversity research and monitoring. Oxford University Press; 2018.

Piergentili R, Del Rio A, Signore F, Umani Ronchi F, Marinelli E, Zaami S. CRISPR-Cas and its wide-ranging applications: From human genome editing to environmental implications, technical limitations, hazards and bioethical issues. Cells. 2021;10(5):969.

Scheffers BR, De Meester L, Bridge TC, Hoffmann AA, Pandolfi JM, Corlett RT, et al. The broad footprint of climate change from genes to biomes to people. Science. 2016;354(6313):aaf7671.

De Pace C, Ricciardi L, Kumar A, Pavan S, Lotti C, Dixit S, et al. Identification of traits, genes, and crops of the future. In: Genomics and Breeding for Climate-Resilient Crops: Concepts and Strategies. 2013;1:27-177.

Frankham R, Ballou JD, Ralls K, Eldridge M, Dudash MR, Fenster CB, et al. Genetic management of fragmented animal and plant populations. Oxford University Press; 2017.

Groombridge JJ, Raisin C, Bristol R, Richardson DS. Genetic consequences of reintroductions and insights from population history. In: Reintroduction biology: Integrating Science and Management. 2012;395-440.

Pauls SU, Nowak C, Bálint M, Pfenninger M. The impact of global climate change on genetic diversity within populations and species. Molecular Ecology. 2013;22(4): 925-946.

Walters C. Challenges in adaptive management of riparian and coastal ecosystems. Conservation Ecology. 1997; 1(2).

Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, et al. The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data. 2016;3(1):1-9.

Bergeron BP. Bioinformatics computing. Prentice Hall Professional; 2003.

Bridle H, Vrieling A, Cardillo M, Araya Y, Hinojosa L. Preparing for an interdisciplinary future: A perspective from early-career researchers. Futures. 2013; 53:22-32.

Clayton EW, Evans BJ, Hazel JW, Rothstein MA. The law of genetic privacy: applications, implications, and limitations. Journal of Law and the Biosciences. 2019;6(1):1-36.

Clare EL. Molecular detection of trophic interactions: emerging trends, distinct advantages, significant considerations and conservation applications. Evolutionary Applications. 2014;7(9):1144-1157.

Dlugosch KM, Parker IM. Founding events in species invasions: genetic variation, adaptive evolution, and the role of multiple introductions. Molecular Ecology. 2008;17 (1):431-449.

Frankham R. Challenges and opportunities of genetic approaches to biological conservation. Biological Conservation. 2010;143(9):1919-1927.

Munday PL, Warner RR, Monro K, Pandolfi JM, Marshall DJ. Predicting evolutionary responses to climate change in the sea. Ecology letters. 2013;16(12):1488-1500.

Newmark WD. The role and design of wildlife corridors with examples from Tanzania. Ambio. 1993;500-504.

Breed MF, Harrison PA, Blyth C, Byrne M, Gaget V, Gellie NJ, et al. The potential of genomics for restoring ecosystems and biodiversity. Nature Reviews Genetics. 2019;20(10):615-628.