Predictive Model in tropical freshwater ecosystems: Dynamics of Planktonic Biota on the Tocantins-Araguaia Hydrographic Region - RHTA, Ecotonal region of the Brazilian Cerrado - Eastern Amazon

Study of the dynamics of planktonic biota in the Bico-do-Papagaio Study Area (AEBP), Tocantins-Araguaia Hydrographic Region, employing an integrative multidimensional statistical framework to decode complex ecosystem patterns. Was applied PERMANOVA, SIMPER, PCA, UMAP, Random Forest, RDA, and dbRDA methodologies, we identified the hydrological pulse (Flood versus Drought seasons) as the paramount driver of ecological organization, accounting for 62% of total variance in initial global PERMANOVA with 16 limnological parameters. Following rigorous Variance Inflation Factor assessment to eliminate multicollinearity artifacts, five redundant variables were excluded, ensuring all subsequent analyses leveraged 11 statistically robust predictors. SIMPER analysis pinpointed Silicon, Biochemical Oxygen Demand, and Euphotic Zone depth as primary determinants of dissimilarity between hydrological phases. The flood regime manifested as a turbid, nutrient-enriched environment with limited light penetration, whereas drought conditions exhibited transparent waters with enhanced photic zone depth and concentrated pollutants. Machine learning implementation via Random Forest algorithm identified Total Phosphorus, Ammonium, Euphotic Zone, and Nitrate as paramount non-linear predictors of environmental variance. Phytoplankton assemblages demonstrated marked functional succession: flood periods sustained elevated diversity dominated by MBFG-IV (mucilaginous colonies) and MBFG-V (turbulence-adapted diatoms), while drought intervals were characterized by MBFG-VII filamentous cyanobacteria proliferating to extreme densities of 3,198.40 ind mL⁻¹, signaling pronounced eutrophication pressure. Zooplankton communities responded concordantly, with r-selected rotifers and nauplii prevailing during floods versus K-selected copepods increasing during cyanobacteria-dominated droughts. dbRDA synthesized these relationships into a potent predictive model where seasonal forcing, nitrate availability, and spatial autocorrelation (PCNM1) collectively explained 52% of adjusted variance in plankton community structure. Nested PERMANOVA delineated anthropogenic impacts from urban effluents as statistically discernible but subsidiary to natural seasonal dynamics, contributing merely 8.8% to explained variance, though exhibiting marked intensification during drought-mediated dilution capacity reduction. This robust methodological triangulation validates the tropical flood pulse as the fundamental ecological architect, establishing a critically valuable predictive framework for monitoring and managing tropical freshwater ecosystems. The model's prognostic capacity regarding alternative stable states, turbid/nutritious/diverse versus clear/eutrophic/cyanobacteria-dominated, provides indispensable tools for adaptive management of tropical aquatic resources amid accelerating climate change and anthropogenic stress, highlighting crucial intervention windows during drought periods when ecosystem resilience is most compromised.