Use evidence to support ecosystem cycling explanations.

Long before modern ecology emerged, scientists noticed that the same chemical elements appear again and again in soil, water, air, and living organisms. In the early nineteenth century, chemists began to wonder why carbon and nitrogen never seemed to run out despite being consumed constantly by life. This question — where do the atoms go, and how do they return? — launched centuries of investigation into biogeochemical cycles. Understanding these cycles requires more than a diagram on a textbook page; it demands real evidence from field measurements, isotope tracers, and long-term data sets. The history of ecosystem cycling science is, at its core, a story about learning to follow individual atoms through systems that span the entire planet.

Each milestone above shares a common thread: scientists needed quantitative evidence to move from speculation to understanding. Today, ecologists continue to ask the same fundamental question that Liebig and Vernadsky raised — how can we use measurable data to explain the movement and transformation of matter through ecosystems? This lesson teaches you to evaluate and construct such evidence-based explanations, connecting directly to NGSS Performance Expectation HS-LS2-4.

Matter cannot be created or destroyed — this principle from chemistry governs every ecosystem on Earth. When a deer eats grass, the carbon atoms in the grass do not vanish; they are reorganized into deer tissue, exhaled as CO₂, or excreted and recycled by decomposers. The same is true for nitrogen, phosphorus, water, and every other element essential to life. Ecosystem cycling refers to the continuous movement of matter through biotic (living) and abiotic (nonliving) components of an ecosystem. To explain these cycles scientifically, you must identify the reservoirs where matter is stored, the processes that move matter between reservoirs, and the evidence — data, measurements, or observations — that supports your claims.

The carbon cycle is the most frequently studied biogeochemical cycle because carbon is the backbone of all organic molecules. The diagram below shows the major reservoirs (boxes) and fluxes (arrows) of carbon in a terrestrial-aquatic ecosystem. Pay close attention to the direction and size of each arrow — they represent evidence-based estimates of how much carbon moves between compartments each year.

Several key patterns emerge from the diagram. First, photosynthesis and respiration form the dominant biological fluxes, each moving roughly 60–120 Gt of carbon per year between the atmosphere and producers. Second, the ocean is the largest active reservoir at approximately 38,000 Gt C, meaning it plays a critical role in buffering atmospheric CO₂. Third, fossil fuel combustion introduces about 9 Gt C per year into the atmosphere — a flux that did not exist before industrialization. This imbalance is the evidence scientists use to explain rising atmospheric CO₂ concentrations. When you construct a cycling explanation, you should trace the path of specific atoms through reservoirs and reference quantitative flux data like the values shown above.

Constructing an evidence-based explanation of ecosystem cycling requires a structured approach. Scientists use the Claim-Evidence-Reasoning (CER) framework to organize their arguments. A claim is a testable statement about how matter cycles. The evidence consists of specific data points, measurements, or observations that support the claim. The reasoning explains why the evidence supports the claim by connecting it to scientific principles such as conservation of matter, the laws of thermodynamics, or the biochemistry of photosynthesis and respiration.

The Claim-Evidence-Reasoning Framework Applied to Cycling

Suppose you observe the following data: atmospheric CO₂ at Mauna Loa drops by about 6 ppm each summer and rises by about 6 ppm each winter. You also know that the Northern Hemisphere has more land (and therefore more vegetation) than the Southern Hemisphere. From these observations, you can build a CER argument. Your claim: seasonal photosynthesis by Northern Hemisphere vegetation causes the annual oscillation in atmospheric CO₂. Your evidence: the Keeling Curve data showing the timing of peaks and troughs. Your reasoning: during Northern Hemisphere summer, increased photosynthesis removes CO₂ from the atmosphere faster than respiration and decomposition return it, creating a net drawdown.

Quantitative Flux Analysis

While high school biology does not typically require calculus, understanding the concept of a mass balance is essential. A mass balance states that the change in the amount of matter in a reservoir equals the total input minus the total output over a given time period.

This mass balance concept applies to any biogeochemical cycle — nitrogen, phosphorus, or water. The key skill is identifying all inputs and outputs for a given reservoir and then using data to determine whether the system is in steady state or experiencing a net gain or loss. When you cite flux values from research studies or field measurements, you are using evidence to support your cycling explanation.

The nitrogen cycle offers an excellent second example for practicing evidence-based explanations because it involves biological, chemical, and geological processes. Nitrogen makes up about 78% of Earth's atmosphere as N₂ gas, yet most organisms cannot use it in that form. Instead, specialized bacteria convert atmospheric N₂ into ammonium (NH₄⁺) through a process called nitrogen fixation. Other bacteria transform ammonium into nitrite (NO₂⁻) and nitrate (NO₃⁻) through nitrification, and still others return nitrogen to the atmosphere via denitrification. Plants absorb nitrate from the soil, consumers eat the plants, and decomposers release ammonium from dead organisms in a process called ammonification.

Scientists gather evidence for the nitrogen cycle using several techniques. Soil core analysis measures ammonium and nitrate concentrations at different depths, revealing where nitrification is most active. Stable isotope tracing uses ¹⁵N-labeled fertilizer to track how added nitrogen moves through plants, soil microbes, and groundwater over time. Atmospheric monitoring of nitrous oxide (N₂O), a potent greenhouse gas produced during denitrification, provides global-scale evidence of nitrogen cycling rates. Each type of evidence supports a different part of the cycle explanation. When constructing your own arguments, identify which reservoir or flux your data addresses and explain why the observed pattern is consistent with the mechanism you describe.

The following worked example walks through how to construct a complete evidence-based explanation of ecosystem cycling using real data from the Hubbard Brook Experimental Forest in New Hampshire.

Not all evidence is equally useful for every cycling question. The table below compares four common types of evidence used to support ecosystem cycling explanations, noting what each type does well and where it falls short.

At the introductory level, biogeochemical cycles are often presented as simple loops with arrows connecting reservoirs. Advanced ecology, however, treats ecosystems as complex adaptive systems with feedback loops, tipping points, and nonlinear responses. For example, increased atmospheric CO₂ can stimulate plant photosynthesis (a negative feedback that partially offsets the increase), but it also raises temperatures, which can accelerate decomposition and release more CO₂ from soil (a positive feedback that amplifies the increase). Understanding which feedback dominates requires sophisticated evidence — long-term flux tower measurements, eddy covariance data, and Earth system models.

As you progress in biology and environmental science, you will encounter these more sophisticated models. For now, the essential foundation is the same: every scientific explanation of cycling must be grounded in specific, relevant evidence connected to scientific principles through clear reasoning. The skills you develop constructing CER arguments about carbon and nitrogen cycling will serve you well when you encounter feedback loops, climate models, and systems ecology in college-level courses.