Invasive plant species pose serious threats to biodiversity and stability of native ecosystems. Kudzu (Pueraria montana var. lobata) is an abundant and highly aggressive invasive plant in the Southeast United States. Herbicides, bioherbicides, and cultural practices are integral parts of integrated management of kudzu, yet few studies have evaluated the impact of kudzu management strategies on soils and their biological and chemical properties. To examine whether kudzu management options impact edaphic chemistry and/or soil microbial communities, we implemented a randomized complete block design (RCBD) with kudzu control treatments, which included synthetic, biological, and combined herbicide applications as well as mowing. Changes in edaphic chemistry, soil activity, and in bacterial and fungal communities were then measured across a single growing season. Treatments included the herbicides glyphosate and aminopyralid, the fungal bioherbicide Albifimbria verrucaria, mowing, as well as the combined treatments of aminopyralid and A. verrucaria, glyphosate and mowing, and two controls (untreated control and the surfactant used as a carrier for aminopyralid and A. verrucaria spores). Soils were collected at multiple points across the growing season between May and September. Soil enzymatic activity and edaphic chemistry were generally stable across treatments and time. Further, our community analyses indicates that the interaction between treatments and time structures fungal and bacterial soil communities, but only weakly. This study suggests that soil microbial communities are generally stable in response to different management strategies and had no discernable adverse non-target effects. We conclude that land managers likely can use any control strategies that are best suited for their circumstances without undue concern about how kudzu control strategies might impact soils.

The red snow algal taxon Sanguina nivaloides has a cosmopolitan distribution but detailed understanding of its functional capabilities, population structure, and evolutionary history has been hampered the current inability to culture this alga. Consequently, very little genetic information is available for this taxon and is limited to only a few loci. Similarly, functional investigations have been limited to community-wide metabolite and fatty acid analyses. Here, we develop an analytical framework to investigate uncultured taxa using a Pool-Seq genomic approach and use this to generate draft genomes of S. nivaloides. We use these data to expand our understanding of S. nivaloides by highlighting the functional potential of this alga via functional annotations and conducting population genomic investigations. We identify several putative functional pathways that this alga was previously not known to possess and demonstrate distinct population patterns between sampling locations. We extend our framework to discuss how such an approach can be applied to other taxa and other systems.

Snow algae blooms and associated microbial communities play large roles in snow ecosystem processes. Patterns and mechanisms underpinning snow algae bloom spatial distribution and associated microbial community assembly dynamics are poorly understood. Here we examine associations of microbial communities and environmental measures between/within snow algae blooms. Snows from the Cascade Mountains and the Rocky Mountains (USA) were collected from medial (M), peripheral (P), and adjacent (A) zones of red snow algae blooms. Medial snow shows increased levels of pollen, lower oxidation–reduction potential, decreased algal and increased bacterial richness, and increased levels of potassium when compared to A and P within the same bloom. Between the Cascade and Rocky Mountains, fungal communities are distinct but bacterial and algal communities show little differentiation. A weighted OTU co-expression analysis (WOCNA) explores OTU modules and their differential correlation with environmental features, suggesting certain subcommunities may be altered by ecological patterns. Individual OTU interaction networks (fungi and bacteria) show high levels of connectivity compared to networks based on the red snow alga Sanguina nivaloides , which underscores associative differences between algal dominated networks and other taxa.

The southern Appalachian Mountains in the United States are heavily forested with diverse forest types and vegetation structures and is generally considered a biodiversity hotspot. Fungal sporocarp investigations in this region are not new, but multi-year interseasonal investigations into sporocarp community patterns are rare. Using a 4-year (2014–2017) repeated monthly macrofungal sampling dataset (May–October) across an elevational gradient (associated with vegetation structure), we queried community, seasonal, and guild community ecological patterns. In doing so, we (1) demonstrate a temporal disconnect between saprobic and ectomycorrhizal taxa, (2) describe increased community variability across the growing season, and (3) explore individual taxa occurrences across seasons and examine co-occurrence patterns between taxa and guilds. Further, we explore congruence between sporocarp and metabarcoding fungal datasets and advocate the utility of both sampling schemes.

Millipedes are ubiquitous soil invertebrates that play major roles in physical and chemical processes in soil. Despite their importance to soil ecology and their presumed interactions with soil microorganisms, little is known about how millipedes influence and are influenced by soil microbes. Furthermore, it is not fully understood how these millipede-microbe interactions are influenced by available soil nitrogen, which is predicted to increase over the foreseeable future with increased anthropogenic production. Here, using the millipede Cherokia georgiana georgiana as a model and using a manipulative mesocosm and metabarcoding approach, we examine (1) the impacts of millipedes on soil microbial communities (fungi and bacteria) with varying nitrogen addition levels, and (2) the temporal impacts of nitrogen on millipede fecal communities (fungi and bacteria). This research demonstrates that millipede presence strongly alters soil communities and that alterations in nitrogen levels do not impact millipede gut communities. This work also provides the first evidence suggesting that millipede gut communities are predominantly derived from soils rather than leaf litter, though both contribute to gut composition. This work advances our current poor understanding of millipede-soil interactions and provides a framework for further investigations to disentangle the interactive effects of substrate, nitrogen, and time to better understand ecological impacts of these interactions.

Mitochondria and chloroplasts are organelles with high iron demand that are particularly susceptible to iron-induced oxidative stress. Despite the necessity of strict iron regulation in these organelles, much remains unknown about mitochondrial and chloroplast iron transport in plants. Here, we propose that Arabidopsis ferroportin 3 (FPN3) is an iron exporter that is dual-targeted to mitochondria and chloroplasts. FPN3 is expressed in shoots, regardless of iron conditions, but its transcripts accumulate under iron deficiency in roots. fpn3 mutants cannot grow as well as the wild type under iron-deficient conditions and their shoot iron levels are lower compared with the wild type. Analyses of iron homeostasis gene expression in fpn3 mutants and inductively coupled plasma mass spectrometry (ICP-MS) measurements show that iron levels in the mitochondria and chloroplasts are increased relative to the wild type, consistent with the proposed role of FPN3 as a mitochondrial/plastid iron exporter. In iron-deficient fpn3 mutants, abnormal mitochondrial ultrastructure was observed, whereas chloroplast ultrastructure was not affected, implying that FPN3 plays a critical role in the mitochondria. Overall, our study suggests that FPN3 is essential for optimal iron homeostasis.

Snow microbial communities (algae, bacteria, and fungi) play major roles in snow ecosystem processes and are linked to snowmelt dynamics, but patterns and mechanisms underpinning their spatial distributions, community assembly, and maintenance dynamics are poorly understood. Here we examine nival microbial communities and physicochemical measures across a semi-continental scale and across categorical snow algae bloom zones to elucidate interrelation between communities and their environment. Evidence suggests that trophic partitioning may be a major driver of snow community sub-networks. Samples from snows from the Cascade Mountains (USA) and the Rocky Mountains (USA) were collected from active red snow algae blooms from the center of the bloom (medial), from the edge of the bloom (peripheral), and in adjacent ‘white’ snow. Medial sections of snow algae blooms show increased levels of anemophilous bisaccate pollen, lower oxidation-reduction potential, decreased algal and increased bacterial richness, and increased levels of potassium. Fungal communities between the Cascade and Rocky Mountains are distinct but bacterial and algal communities show little intracontinental differentiation. Ecological modules were identified using a weighted gene co-expression analysis (WGCNA), which shows that dominant microbial consortia correlate differentially to environmental parameters, suggesting complex subcommunities drive observed ecological patterns. Individual OTU networks (fungi and bacteria) show high levels of network connectivity compared to networks based on the snow algae Sanguina nivaloides, which underscores associative differences between algal dominated networks and other OTU networks, indicative of trophic partitioning.

AbstractIt has been previously suggested that snow algal species within the genus Sanguina (S. nivaloides and S. aurantia) show no population structure despite being found globally (S. nivaloides) or throughout the Northern Hemisphere (S. aurantia). However, systematic biogeographic research into global distributions is lacking due to few genetic and no genomic resources for these snow algae. Here, using all publicly available and previously unpublished Sanguina sequences of the Internal Transcribed Spacer 2 region, we investigated whether this purported lack of population structure within Sanguina species is supported by additional evidence. Using a minimum entropy decomposition (MED) approach to examine fine‐scale genetic population structure, we find that these snow algae populations are largely distinct regionally and have some interesting biogeographic structuring. This is in opposition to the currently accepted idea that Sanguina species lack any observable population structure across their vast ranges and highlights the utility of fine‐scale (sub‐OTU) analytical tools to delineate geographic and genetic population structure. This work extends the known range of S. aurantia and emphasizes the need for development of genetic and genomic tools for additional studies on snow algae biogeography.

ABSTRACT Gravity is a fundamental stimulus that affects plant growth and development. The gravity persistent signal (GPS) treatment uses a cold treatment to isolate the events of signal transduction. Plants are reoriented horizontally in the dark at 4°C for 1 hour and then returned to vertical at room temperature. A gene expression microarray was designed to identify genes that are regulated during the GPS treatment. Arabidopsis thaliana var. Columbia was grown to maturity with inflorescence stems of 8-10 cm. Total mRNA was collected from inflorescence stems at 2, 4, 10, and 30 min after reorientation in the cold. cDNA was synthesized from the mRNA and then probed against an Arabidopsis gene expression array with 4 replicates per time point. Analyses presented here focus on transcription factors because of their regulatory functions in response pathways. Five transcription factors ( AtAIB, WRKY18, WRKY26, WRKY33 , and BT2) were selected for further study based on their expression at 4 min. Quantitative real-time polymerase chain reaction ((PCR) RT-qPCR) was performed to confirm expression seen in the microarray data. Seeds of Arabidopsis lines containing T-DNA insertions in the genes were obtained, plants bred to homozygosity, and the mutants analyzed for GPS phenotype. Mutant analysis shows significant differences in curvature of inflorescence stems between mutants and wild type.