Nitrification is a key process in the global nitrogen cycle, indicative of both soil nitrogen availability and potential for nitrogen losses that cause environmental degradation. Heterotrophic soil microbes and plants compete with nitrifiers for ammonium, thereby influencing the fraction of mineralized nitrogen converted to nitrate. Microbially available carbon constrains heterotrophic nitrogen demand and therefore regulates the coupling of net nitrogen mineralization and nitrification rates. Whether soil carbon availability remains a central control on the coupling of these processes in disturbed ecosystems with reduced plant nitrogen demand remains relatively unexplored. Using a series of partially disturbed forests that vary in aboveground biomass and soil carbon availability, we test the relative influence of plant and heterotrophic nitrogen demand on the relationship between net nitrogen mineralization and nitrification. We analyzed differences between harvested and unharvested stands, changes over time since harvest, and the effects of legacy overstory trees within harvested stands. Higher levels of canopy disturbance consistently strengthened the positive relationship between net nitrogen mineralization and nitrification rates. However, reduced plant biomass, rather than microbially available carbon, mediated the coupling of these processes in partially disturbed forest stands. Our findings emphasize the importance of assessing both the effects of plant and heterotrophic nitrogen demand on the coupling of nitrogen mineralization and nitrification rates following forest disturbances. These results have important implications for understanding coupled nitrogen cycling processes in ecosystems globally, which are increasingly experiencing disturbances that partially reduce aboveground biomass, such as drought and species invasions.

Study area 

We conducted our work at Yale-Myers Forest, a mixed hardwood, second-growth forest in the northeastern USA (41° 57' N, 72°07’ W). Yale-Myers Forest is an actively managed research and demonstration forest with annual timber harvests that can be used to study changes over time since harvest through a chronosequence approach. We selected 15 oak-hardwood stands with similar silvicultural treatments that were harvested from 1994 through 2016 as well as five unharvested controls that had comparable characteristics to the harvested stands and hence were all eligible for the same silvicultural treatment. Each of the 15 harvested stands were managed to promote the regeneration of shade-intolerant tree species, such as oaks (Quercus spp.), through the creation of large canopy openings interspersed with legacy overstory trees at a spacing of 35 – 80 m.

Sampling design

To capture within-site variation in microbially available C and aboveground plant biomass, we stratified our sampling by 2 soil types, 9 harvest years, 4 topographic classes, and 2 distances relative to legacy overstory trees. This sampling design yielded 144 plots arrayed across the 15 harvested stands. The soil types included the Nipmuck-Brookfield complex, which consists of well-drained upland ablation tills derived from schist, granite, and gneiss, and the Paxton-Montauk and Woodbridge series, which are mesic, fertile basal tills of drumlins. For each of these soil types, we identified nine harvest years from 1994 to 2016. To stratify sampling by topography, we created four topographic classes with the most distinct features by running an unsupervised classification on slope, aspect, and elevation data using the “cluster” function in R with the CLARA K-medoids method. We then randomly located points ≥20 m from the harvest edge for each of these areas and established plots 2 m and 10 m from the nearest legacy overstory tree ≥20 cm diameter at breast height (DBH; 1.37 m) to stratify sampling by residual tree basal area. We used a similar design to locate plots within each of five unharvested stands (2 soil types ´ 3 time-since-thinning classes ´ 4 terrain classes ´ 2 tree distances), which yielded 48 plots in the unharvested stands. 

Vegetation and soil sampling

We sampled vegetation and soils in May through June 2019. We identified the species and measured DBH of all living trees and shrubs ≥5-cm DBH in a 5-m radius fixed area plot and ≥1-cm DBH in a nested 1-m radius plot and calculated total basal area (m² ha^-1). We chose to use 5-m radius plots to capture vegetation conditions in the immediate vicinity of the soil sampling location where overstory trees were most likely to influence N mineralization and nitrification rates. Within 1 m of each plot center, we collected and pooled eight 2-cm diameter, 10-cm deep soil cores. In sites with a thick Oa horizon and low bulk density soil, we collected an additional 1-4 cores to ensure we had sufficient sample mass for the laboratory assays. We kept field collected soils in coolers and stored them at 4°C for less than 4 weeks prior to analysis.

Laboratory assays

We used laboratory assays to estimate microbially available C and net N mineralization and nitrification rates using field-moist soil samples adjusted to 65% water holding capacity. We first homogenized each sample and passed it through a 4-mm sieve. We estimated water holding capacity by saturating field-moist samples with water and allowing them to drain freely for 2 h. We measured gravimetric water content by oven-drying the samples to constant mass at 105°C.

For microbially available C, we used 6 g equivalent dry mass of each sample to calculate cumulative C-CO₂ production rates over a 30-d incubation period. We integrated CO₂ efflux measurements sampled over 24-h periods with an Infra-Red Gas Analyzer (Li-COR model Li-7000, Li-Cor Biosciences, Lincoln, Nebraska, USA) at days 1, 4, 11, 24, and 30. During the incubation period, samples were maintained at 65% water holding capacity and 20°C under a humid atmosphere. For net potential N mineralization and nitrification rates, we estimated NH₄⁺ and NO₃^- production over a 30-d incubation period by calculating the difference between initial and incubated samples. For the incubated samples, we stored 6 g dry weight equivalent of each sample at 20°C and 65% water holding capacity for 30-d under a humid atmosphere. For the initial and incubated NH₄⁺ and NO₃^- extractions, we shook each sample vigorously for 30 s with 25 mL 2M KCl, refrigerated the samples for 12 h, and filtered the samples with Whatman Grade 42 filters. We analyzed NH₄⁺ and NO₃^- concentrations using a flow analyzer (Astoria 2, Astoria‐Pacific, Clackamas, Oregon, USA). Net potential nitrification was calculated as the difference in NO₃^- concentrations between the incubated and initial samples and net potential N mineralization as the difference between the initial and final sum of NH₄⁺ and NO₃^- concentrations over the 30-d incubation period.