For 76 annual, biennial, and perennial species common in the grasslands of central Minnesota, USA, we determined the patterns of correlations among seven organ‐level traits (specific leaf area, leaf thickness, leaf tissue density, leaf angle, specific root length, average fine root diameter, and fine root tissue density) and their relationships with two traits relating to growth form (whether species existed for part of the growing season in basal, non‐caulescent form and whether species were rhizomatous or not). The first correlation of traits showed that grasses had thin, dense leaves and thin roots while forbs had thick, low‐density leaves and thick roots without any significant differences in growth form or life history. The second correlation of traits showed a gradient of species from those with high‐density roots and high‐density erect leaves to species with low‐density roots and low‐density leaves that were held parallel to the ground. High tissue density species were more likely to exist as a basal rosette for part of the season, were less likely to be rhizomatous, and less likely to be annuals. We examined the relationships between the two axes that represent the correlations of traits and previously collected data on the relative abundance of species across gradients of nitrogen addition and disturbance. Grasses were generally more abundant than forbs and the relative abundance of grasses and forbs did not change with increasing nitrogen addition or soil disturbance. High tissue density species became less common as fertility and disturbance increased.
Abstract Motivation Trait data are fundamental to quantitatively describe plant form and function. Although root traits capture key dimensions related to plant responses to changing environmental conditions and effects on ecosystem processes, they have rarely been included in large-scale comparative studies and global models. For instance, root traits remain absent from nearly all studies that define the global spectrum of plant form and function. Thus, to overcome conceptual and methodological roadblocks preventing a widespread integration of root trait data into large-scale analyses we created the Global Root Trait (GRooT) Database. GRooT provides ready-to-use data by combining the expertise of root ecologists with data mobilization and curation. Specifically, we (i) determined a set of core root traits relevant to the description of plant form and function based on an assessment by experts, (ii) maximized species coverage through data standardization within and among traits, and (iii) implemented data quality checks. Main types of variables contained GRooT contains 114,222 trait records on 38 continuous root traits. Spatial location and grain Global coverage with data from arid, continental, polar, temperate, and tropical biomes. Data on root traits derived from experimental studies and field studies. Time period and grain Data recorded between 1911 and 2019 Major taxa and level of measurement GRooT includes root trait data for which taxonomic information is available. Trait records vary in their taxonomic resolution, with sub-species or varieties being the highest and genera the lowest taxonomic resolution available. It contains information for 184 sub-species or varieties, 6,214 species, 1,967 genera and 254 families. Due to variation in data sources, trait records in the database include both individual observations and mean values. Software format GRooT includes two csv file. A GitHub repository contains the csv files and a script in R to query the database.
Abstract As freshwater algae respond strongly to environmental conditions, algal communities are routinely used as indicators of aquatic health. Algal bioassessments have historically relied upon microscopy‐based identifications that are typically slow, expensive, taxonomically restricted, and inconsistent across analysts and time. Metabarcoding of water column DNA (environmental DNA, or eDNA) can characterize assemblages more quickly, at lower cost, and with higher taxonomic precision than microscopy. As such, eDNA metabarcoding has the potential to improve bioassessments, but relationships between environmental conditions and eDNA‐derived algal assemblage composition need to be determined first. We performed metabarcoding of a plastid 23S rRNA gene region for 1230 freshwater eDNA samples collected from 51 lakes and 617 streams across the conterminous United States to test for assemblage‐wide patterns that may indicate ecological condition. Samples were collected by citizen, academic, and research scientists using a standardized commercial kit. This effort constitutes the largest published water column eDNA survey yet of algal diversity across freshwaters in the United States. We detected 14,943 algal exact sequence variants (ESVs) from 11 divisions. The richness and abundance of cyanobacteria was higher in lakes, while streams were dominated by diatoms. Nationwide, only 1% of variation in stream assemblages was explained by catchment integrity. The remaining, explicable 19% was associated with forest cover, stream order, elevation, and broad‐scale spatial variables. Nevertheless, select ESVs were candidate indicators of gradients in stream catchment integrity and possible eutrophication. Together, we show that algal eDNA metabarcoding has potential for measuring ecological condition relative to water quality. Yet, further sampling along anthropogenic gradients is needed before algal eDNA can be used for large‐scale biomonitoring in the United States. We also found that only 2% of algal ESVs could be assigned to U.S. morphospecies, highlighting the importance of building a more comprehensive reference sequence database to integrate existing morphospecies autecology with eDNA‐based bioassessments.
Nitrogen (N) availability, defined here as the supply of N to terrestrial plants and soil microorganisms relative to their N demands, limits the productivity of many temperate zone forests and in part determines ecosystem carbon (C) content. Despite multidecadal monitoring of N in streams, the long-term record of N availability in forests of the northeastern United States is largely unknown. Therefore, although these forests have been receiving anthropogenic N deposition for the past few decades, it is still uncertain whether terrestrial N availability has changed during this time and, subsequently, whether forest ecosystems have responded to increased N deposition. Here, we used stable N isotopes in tree rings and lake sediments to demonstrate that N availability in a northeastern forest has declined over the past 75 years, likely because of ecosystem recovery from Euro-American land use. Forest N availability has only recently returned to levels forecast from presettlement trajectories, rendering the trajectory of future forest N cycling uncertain. Our results suggest that chronic disturbances caused by humans, especially logging and agriculture, are major drivers of terrestrial N cycling in forest ecosystems today, even a century after cessation.
Abstract Climatic warming is likely to exacerbate nutritional stress and reduce weight gain in large mammalian herbivores by reducing plant nutritional quality. Yet accurate predictions of the effects of climatic warming on herbivores are limited by a poor understanding of how herbivore diet varies along climate gradients. We utilized DNA metabarcoding to reconstruct seasonal variation in the diet of North American bison ( Bison bison ) in two grasslands that differ in mean annual temperature by 6 °C. Here, we show that associated with greater nutritional stress in warmer climates, bison consistently consumed fewer graminoids and more shrubs and forbs, i.e. eudicots. Bison in the warmer grassland consumed a lower proportion of C 3 grass, but not a greater proportion of C 4 grass. Instead, bison diet in the warmer grassland had a greater proportion of N 2 -fixing eudicots, regularly comprising >60% of their protein intake in spring and fall. Although bison have been considered strict grazers, as climatic warming reduces grass protein concentrations, bison may have to attempt to compensate by grazing less and browsing more. Promotion of high-protein, palatable eudicots or increasing the protein concentrations of grasses will be critical to minimizing warming-imposed nutritional stress for bison and perhaps other large mammalian herbivores.
Thermal analysis techniques can provide an important addition to our understanding of soil organic matter (SOM) composition and stability. Several recent studies have linked thermal and biological stability of SOM; however, contrasting results have been reported. The objective of this study was to characterize the relationships between thermal and biological SOM stability for a wide range of mineral soils. Soils were collected from 28 sites from across the United States and analyzed by thermogravimetry (TG) and differential scanning calorimetry (DSC) coupled with CO2 evolved gas analysis (CO2–EGA). We compared thermal analysis results to mean soil respiration rates during incubation at 20°C for 365 d (R20). For soils with <30 g C kg−1 (low C), R20 was negatively correlated with the temperature at which half of the DSC energy is released and the temperature at which half of the CO2–EGA is evolved. Conversely, for soils with >30 g C kg−1 (high C), R20 was positively correlated with CO2–EGA and DSC energy released between 345 and 460°C and to SOM energy density (in J mg−1 C). Differences between low-C and high-C soils indicate the relative importance of mineral association of SOM in low-C soils and the abundance of intact plant debris that is relatively energy dense and thermally resistant but relatively easy to decompose in high-C soils. Above all, thermal analysis proved to be a useful technique for interpreting SOM stability, but sample C concentration must be considered because it affects the dominant SOM stabilization mechanisms and thermal analysis results.
