It remains unclear how warming will affect resource flows during soil organic matter (SOM) decomposition, in part due to uncertainty in how exoenzymes produced by microbes and roots will function. Rising temperatures can enhance the activity of most exoenzymes, but soil pH can impose limitations on their catalytic efficiency. The effects of temperature and pH on enzyme activity are often examined in environmental samples, but purified enzyme kinetics reveal fundamental attributes of enzymes’ intrinsic temperature responses and how relative release of decay‐liberated resources (their flow ratios) can change with environmental conditions. In this paper, we illuminate the principle that fundamental, biochemical limitations on SOM release of C, N, and P during decay, and differential exoenzymes’ responses to the environment, can exert biosphere‐scale significance on the stoichiometry of bioavailable soil resources. To that end, we combined previously published intrinsic temperature sensitivities of two hydrolytic enzymes that release C and N during decay with a novel data set characterizing the kinetics of a P‐releasing enzyme (acid phosphatase) across an ecologically relevant pH gradient. We use these data to estimate potential change in the flow ratios derived from these three enzymes’ activities (C:N, C:P, and N:P) at the global scale by the end of the century, based on temperature projections and soil pH distribution. Our results highlight how the temperature sensitivity of these hydrolytic enzymes and the influence of pH on that sensitivity can govern the relative availability of bioavailable resources derived from these enzymes. The work illuminates the utility of weaving well‐defined kinetic constraints of microbes’ exoenzymes into models that incorporate changing SOM inputs and composition, nutrient availability, and microbial functioning into their efforts to project terrestrial ecosystem functioning in a changing climate.

The size and spatial distribution of soil structural macropores impact the infiltration, percolation, and retention of soil water. Despite the assumption often made in hydrologic flux equations that these macropores are rigid, highly structured soils can respond quickly to moisture variability‐induced shrink‐swell processes altering the size distribution of these pores. In this study, we use a high‐resolution (180 m) laser imaging technique to measure the average width of interpedal, planar macropores from intact cross sections and relate it to matrix water content. We also develop an expression for unsaturated hydraulic conductivity that accounts for dynamic macropore geometries and propose a method for partitioning sensor soil water content data into matrix and macropore water contents. The model was applied to a soil in northeastern Kansas where soil monoliths had been imaged to quantify macropore properties and continuous water content data were collected at three depths. Model‐predicted macropore width showed significant sensitivity to matrix water content resulting in changes of 15%–50% of maximum width over the 15‐month period of record. Transient saturated hydraulic conductivity predicted from the model compared favorably to a previously developed model accounting for moisture‐induced changes to structural unit porosity. Following periods of low soil moisture, infiltrating meteoric water filled highly conductive macropores increasing by several orders of magnitude which subsequently decreased as water was absorbed into the matrix and macropores drained. This model offers a means by which to combine measurable morphological data with soil moisture sensors to monitor dynamic hydraulic properties of soils susceptible to shrink‐swell processes.

Root distributions are typically based on root mass per soil volume. This plant‐focused approach masks the biogeochemical influence of fine roots, which weigh little. We assert that centimeter‐scale root presence‐absence data from soil profiles provide a more soil‐focused approach for probing depth distributions of root‐regolith interfaces, where microsite‐scale processes drive whole‐ecosystem functioning. In 75 soil pits across the continental USA, Puerto Rico, and the Alps, we quantified fine and coarse root presence as deep as 2 m. In 70 of these pits we estimated root mass and created standardized metrics of both data sets to compare their depth distributions. We addressed whether: (a) depth distributions of root presence‐absence data differ from root mass data, thus implying different degrees of root‐regolith interactions with depth; and (b) if root presence or any depth‐dependent differences between these data sets vary predictably with environmental conditions. Presence of fine roots exhibited diverse depth‐dependent patterns; root mass generally declined with depth. In B and C horizons, standardized root presence was greater than standardized root mass; random forest analyses suggest these discrepancies are greater in B horizons with increasing mean annual precipitation and in C horizons with increasing mean annual temperature. Our work suggests that deep in the subsurface, biogeochemical and reactive transport processes result from more numerous root‐regolith interfaces than mass data suggest. We present a new paradigm for discerning patterns in depth distributions of root‐regolith interfaces across multiple biomes and land uses that promotes understanding of the roles of those interfaces in driving key critical zone processes.