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There is widespread concern that fire exclusion has led to an unprecedented threat of uncharacteristically severe fires in ponderosa pine (Pinus ponderosa Dougl. ex. Laws) and mixed-conifer forests of western North America. These extensive montane forests are considered to be adapted to a low/moderate-severity fire regime that maintained stands of relatively old trees. However, there is increasing recognition from landscape-scale assessments that, prior to any significant effects of fire exclusion, fires and forest structure were more variable in these forests. Biota in these forests are also dependent on the resources made available by higher-severity fire. A better understanding of historical fire regimes in the ponderosa pine and mixed-conifer forests of western North America is therefore needed to define reference conditions and help maintain characteristic ecological diversity of these systems. We compiled landscape-scale evidence of historical fire severity patterns in the ponderosa pine and mixed-conifer forests from published literature sources and stand ages available from the Forest Inventory and Analysis program in the USA. The consensus from this evidence is that the traditional reference conditions of low-severity fire regimes are inaccurate for most forests of western North America. Instead, most forests appear to have been characterized by mixed-severity fire that included ecologically significant amounts of weather-driven, high-severity fire. Diverse forests in different stages of succession, with a high proportion in relatively young stages, occurred prior to fire exclusion. Over the past century, successional diversity created by fire decreased. Our findings suggest that ecological management goals that incorporate successional diversity created by fire may support characteristic biodiversity, whereas current attempts to “restore” forests to open, low-severity fire conditions may not align with historical reference conditions in most ponderosa pine and mixed-conifer forests of western North America.

Root-deposited photosynthate (rhizodeposition) is an important source of readily available carbon (C) for microbes in the vicinity of growing roots. Plant nutrient availability is controlled, to a large extent, by the cycling of this and other organic materials through the soil microbial community. Currently, our understanding of microbial community dynamics associated with rhizodeposition is limited. We used a 13 C pulse-chase labeling procedure to examine the incorporation of rhizodeposition into individual phospholipid fatty acids (PLFAs) in the bulk and rhizosphere soils of greenhouse-grown annual ryegrass (Lolium multiflorum Lam. var. Gulf). Labeling took place during a growth stage in transition between active root growth and rapid shoot growth on one set of plants (labeling period 1) and 9 days later during the rapid shoot growth stage on another set of plants (labeling period 2). Temporal differences in microbial community composition were more apparent than spatial differences, with a greater relative abundance of PLFAs from gram-positive organisms (i15:0 and a15:0) in the second labeling period. Although more abundant, gram-positive organisms appeared to be less actively utilizing rhizodeposited C in labeling period 2 than in labeling period 1. Gram-negative bacteria associated with the 16:15 PLFA were more active in utilizing 13 C-labeled rhizodeposits in the second labeling period than in the first labeling period. In both labeling periods, however, the fungal PLFA 18:26,9 was the most highly labeled. These results demonstrate the effectiveness of using 13 C labeling and PLFA analysis to examine the microbial dynamics associated with rhizosphere C cycling by focusing on the members actively involved.

Aim Wildfire is often considered more severe now than historically in dry forests of the western United States. Tree-ring reconstructions, which suggest that historical dry forests were park-like with large, old trees maintained by low-severity fires, are from small, scattered studies. To overcome this limitation, we developed spatially comprehensive reconstructions across 927,000 ha in four landscapes, using a new method based on land surveys from c. 1880.Location Dry forests of the western United States. MethodsWe reconstructed forest structure for four large dry-forest landscapes using forest descriptions and tree data from historical land surveys. Using multiple elements of historical forest structure from this study along with corroborating information from tree-ring studies, we were able to interpret past forest dynamics. Hypotheses concerning historical structure and dynamics were then tested.Results These reconstructions show that dry forests were structurally variable, containing from 20 to over 1000 trees ha -1 and some dense understoreys of shrubs and small trees. Park-like stands of large trees maintained by low-severity fire predominated only in parts of the study landscapes. Only 3, 12, 40 and 62% of the four landscapes fit a low-severity fire model; 38-97% had evidence of higherseverity (mixed-and high-severity) fire. Some large modern wildfires (e.g. Rodeo-Chediski), perceived as catastrophic, had fire severity congruent with historical variability.Main conclusions Spatially extensive reconstructions from the late 1800s show that these forests were structurally variable, including areas of dense forests and understorey trees and shrubs, and fires varied in severity, including 15-65% highseverity fire. A set of laws, policies and initiatives that aim to uniformly reduce fuels and fire severity is likely to move many of these forests outside their historical range of variability with adverse effects on biological diversity. Macroscale survey-based reconstructions and palaeoecological studies reveal that higher-severity fires were and are a part of the normal dynamics of dry forests.

The accuracy of methods for reconstructing parameters (e.g., tree density) of historical forest structure from General Land Office (GLO) survey data has not been thoroughly assessed. Past simulation and statistical assessments of plotless density estimators have focused on minimizing estimation error, but not congruent with the specific data available in the GLO surveys. Most GLO reconstruction studies do not reconstruct absolute measures of density, basal area, or diameter‐class distributions, key measures used for forest restoration. We tested the accuracy of a suite of plotless density estimators and other survey methods to accurately reconstruct forest attributes using both a field‐based modern calibration and a cross‐validation with tree‐ring reconstructions. In addition to the common distance estimators, we developed several Voronoi‐based plotless density estimators that can be used with GLO data. Estimators were assessed using modern survey and plot data collected in the same location and spatial arrangement as the original survey locations in three geographically distinct areas. Results showed that Voronoi‐based density estimators were superior to distance‐based estimators. Data need to be pooled across locations. Voronoi estimators yielded more accurate measures of density and basal area and can be used at smaller pooling levels without sacrificing much accuracy. At spatial extents of 260 and 520 ha (3‐ and 6‐corner pools), relative mean absolute error (RMAE) averaged 29% and 22%, respectively, for density estimates in all three study areas. To estimate basal area as accurately (i.e., 23%), data must be pooled to 780 ha (9‐corner pool). Composition and diameter‐class distributions also required larger pooling areas to achieve accurate results. In the cross‐validation, accuracy of density and basal area were both superior to accuracy in the modern calibration, and RMAE for density and basal area at all pooling levels averaged 16.6% and 15.7%, respectively. Composition and diameter‐class distribution estimates were lower in accuracy. Voronoi‐based methods can accurately estimate historical forest parameters across large landscapes and are accurate at finer scales (e.g., 260 ha, 3‐corner pool) than previously thought possible. GLO reconstructions complement tree‐ring reconstructions but can provide more spatially comprehensive estimates of the historical range of forest variability, facilitating landscape‐level restoration.

Belowground organisms play critical roles in maintaining multiple ecosystem processes, including plant productivity, decomposition, and nutrient cycling. Despite their importance, however, we have a limited understanding of how and why belowground biodiversity (bacteria, fungi, protists, and invertebrates) may change as soils develop over centuries to millennia (pedogenesis). Moreover, it is unclear whether belowground biodiversity changes during pedogenesis are similar to the patterns observed for aboveground plant diversity. Here we evaluated the roles of resource availability, nutrient stoichiometry, and soil abiotic factors in driving belowground biodiversity across 16 soil chronosequences (from centuries to millennia) spanning a wide range of globally distributed ecosystem types. Changes in belowground biodiversity during pedogenesis followed two main patterns. In lower-productivity ecosystems (i.e., drier and colder), increases in belowground biodiversity tracked increases in plant cover. In more productive ecosystems (i.e., wetter and warmer), increased acidification during pedogenesis was associated with declines in belowground biodiversity. Changes in the diversity of bacteria, fungi, protists, and invertebrates with pedogenesis were strongly and positively correlated worldwide, highlighting that belowground biodiversity shares similar ecological drivers as soils and ecosystems develop. In general, temporal changes in aboveground plant diversity and belowground biodiversity were not correlated, challenging the common perception that belowground biodiversity should follow similar patterns to those of plant diversity during ecosystem development. Taken together, our findings provide evidence that ecological patterns in belowground biodiversity are predictable across major globally distributed ecosystem types and suggest that shifts in plant cover and soil acidification during ecosystem development are associated with changes in belowground biodiversity over centuries to millennia.