Machine Learning Traces Toxic Algae Risks to Nickel and Nitrogen in Urban Ponds

Cyanobacteria are among the oldest life forms on Earth, having spent more than two and a half billion years oxygenating the atmosphere and stabilizing the planet’s carbon cycles. Yet in the Anthropocene, these ancient microbes are behaving in ways that have no analogue in the geological record, forming harmful algal blooms with increasing frequency across lakes, reservoirs and small engineered water bodies worldwide. A new study from eastern Ontario, Canada, suggests that in the constructed ponds and wetlands that pepper urban and agricultural landscapes, the drivers of cyanobacterial growth may be more surprising than the conventional story of nitrogen and phosphorus alone.

Researchers sampled thirty ponds monthly from June to September 2022, dividing them into four categories: agricultural reservoirs, biologically managed habitat ponds, natural ponds with little anthropogenic influence, and engineered urban stormwater ponds of the kind that now number more than 230 in the city of Ottawa alone. These impoundments are designed to capture runoff, trap sediments and shield downstream ecosystems from floods and pollutants, but they can also become nurseries for unwanted cyanobacteria and the cyanotoxins they produce. The team collected water for physical and chemical analysis, identified phytoplankton communities using FlowCam imaging systems, and quantified land use within a one-kilometer buffer around each pond using provincial land cover databases.

The chemical contrast between pond types was striking. Stormwater ponds had the highest specific conductivity, averaging roughly 1,045 microsiemens per centimeter and peaking above 3,000, a signature of road salt application across their largely impervious urban catchments. Agricultural ponds, by contrast, carried the heaviest nutrient loads, with total phosphorus averaging 0.119 milligrams per liter and total Kjeldahl nitrogen 1.876 milligrams per liter, both significantly higher than in any other pond type. Natural ponds remained consistently low in nutrients, salts and metals, buffered by surrounding soils and forest cover. A regression analysis revealed that roughly half the variation in overall water chemistry across all ponds could be explained simply by the percentage of impervious cover, such as roads and pavement, surrounding each pond.

When the researchers turned to the living communities, they found that phytoplankton assemblages were broadly similar across pond types, a reflection of broad ecological niches and effective dispersal among these small water bodies. But the details mattered. Agricultural and managed ponds hosted more chlorophyte green algae and larger cyanobacteria, while stormwater ponds were dominated by small picoplankton-sized cyanobacteria. Variance partitioning showed that environmental factors alone explained nearly 62 percent of the variation in community composition, with the full model accounting for about 70 percent, whereas land use independent of environment explained under 2 percent and season contributed nothing significant. In other words, it is the chemistry of the water, not the calendar or the map alone, that structures who lives in these ponds.

The study’s most provocative findings emerged from its machine learning analysis. Using classification and regression tree modeling, the team predicted cyanobacterial counts from dozens of chemical and land use variables. The first split in the entire dataset was not phosphorus, not temperature, but extractable nickel. Ponds with nickel concentrations above 0.0029 milligrams per liter harbored cyanobacterial densities nearly three times those of the rest, and these nickel-rich samples came almost exclusively from stormwater and agricultural ponds. Nitrate was the closest competing variable, and water temperature, conductivity and ammonia all ranked prominently in the model’s variable importance scores.

Even more striking was what did not matter. Total phosphorus and reactive phosphorus, long cast as the primary villains of cyanobacterial blooms, ranked only tenth or lower in importance, with importance scores of just 4.7 and 4.3. In these moderately disturbed, pre-bloom systems, the classical paradigm of phosphorus control appeared to loosen. Instead, the data pointed to a tight coupling between nickel and nitrogen metabolism. Cyanobacteria rely on the nickel-dependent enzyme urease to hydrolyze urea into ammonia and carbon dioxide, providing a bioavailable nitrogen source, and the co-occurrence of elevated nickel and ammonia in the CART hotspots is consistent with enhanced urease activity under urban contamination regimes.

The urban provenance of the nickel itself is well documented in the broader literature. Copper and zinc wash from vehicles, brake wear, tires, road surfaces and buildings, while nickel contamination traces to fossil fuel combustion, construction activity and waste disposal. Stormwater ponds, ringed by asphalt and receiving concentrated runoff, accumulate these metals readily, and the study found copper, zinc and nickel positively associated with cyanobacterial concentrations in urban ponds. At the moderate concentrations observed, nickel appears to act as a micronutrient rather than a toxin, though at higher levels it inhibits photosynthesis, promotes reactive oxygen species and can even stimulate toxin production in sensitive species.

Conductivity also emerged as a meaningful predictor, with cyanobacteria strongly associated with specific conductance above 1,184 microsiemens per centimeter, a threshold dominated by stormwater and managed ponds. While salts are generally treated as indirect indicators of landscape runoff rather than direct bloom drivers, the finding echoes earlier work showing that elevated ionic concentrations correlate with cyanobacterial and periphyton abundance in both natural and disturbed systems. Warm summer temperatures, peaking near 24 degrees Celsius in July, amplified the model’s predictive power, consistent with the widely observed synergy between warming and nutrient or contaminant loading.

The study confirmed that cyanobacteria fare disproportionately well in chemically and physically altered systems: the highest concentrations occurred in stormwater and agricultural ponds, while natural ponds, though biologically diverse, hosted the fewest. Although classical surface blooms were not observed during the sampling season, the team documented elevated numbers of potentially harmful taxa, including Microcystis and small coccoid cyanobacteria, in the modified ponds. This pre-bloom state is precisely where early-warning signals matter most, and the authors argue that nickel-mediated nitrogen processing could be an overlooked early driver of eutrophication before blooms become visible.

The practical implications are considerable. Managing cyanobacteria has long focused on curbing point-source phosphorus, capping nitrogen inputs and altering water flows, approaches that are often blunt and only partially effective against diffuse non-point pollution. This research suggests that in constructed ponds, the micronutrient dimension of contamination, and specifically the role of nickel in nitrogen cycling, deserves a place in monitoring and design strategies. As urbanization expands and climate change intensifies runoff, the humble stormwater pond may prove to be both a sentinel and a trigger in the global rise of harmful algal blooms, and the trace metals that trickle off our roads may be quietly shaping which microbes thrive in the waters we build.

Subject of Research: Anthropogenic and environmental factors driving plankton communities and cyanobacteria in constructed ponds and wetlands.

Article Title: Anthropogenic and environmental factors driving planktic community and Cyanobacteria selection in constructed ponds and wetlands

Article References: Schulz, N. A., Hamilton, P. B., Lapen, D., Sunohara, M., & Vermaire, J. C. (2026). Anthropogenic and environmental factors driving planktic community and Cyanobacteria selection in constructed ponds and wetlands. Environmental Advances, 25, Article 100752. https://doi.org/10.1016/j.envadv.2026.100752

Image Credits: AI Generated

DOI: 10.1016/j.envadv.2026.100752

Keywords: cyanobacteria, harmful algal blooms, stormwater ponds, nickel, nitrogen, phosphorus, phytoplankton, urease, urban runoff, water quality, machine learning, constructed wetlands