Effective management of introduced species requires the early identification of species that pose a significant threat of becoming invasive. To better understand the invasive ecology of species in New England, USA, we compiled a character data set with which to compare non‐native species that are known invaders to non‐native species that are not currently known to be invasive. In contrast to previous biological trait‐based models, we employed a Bayesian hierarchical analysis to identify sets of plant traits associated with invasiveness for each of three growth forms (vines, shrubs, and trees). The resulting models identify a suite of ‘invasive traits’ highlighting the ecology associated with invasiveness for each of three growth forms. The most effective predictors of invasiveness that emerged from our model were ‘invasive elsewhere’, ‘fast growth rate’, ‘native latitudinal range’, and ‘growth form’. The contrast among growth forms was pronounced. For example, ‘wind dispersal’ was positively correlated with invasiveness in trees, but negatively correlated in shrubs and vines. The predictive model was able to correctly classify invasive plants 67% of the time (22/33), and non‐invasive plants 95% of the time (204/215). A number of potential future invasive species in New England that deserve management consideration were identified.
Plant roots serve as conduits for water flow not only from soil to leaves but also from wetter to drier soil. This hydraulic redistribution through root systems occurs in soils worldwide and can enhance stomatal opening, transpiration, and plant carbon gain. For decades, upward hydraulic lift (HL) of deep water through roots into dry, litter-rich, surface soil also has been hypothesized to enhance nutrient availability to plants by stimulating microbially controlled nutrient cycling. This link has not been demonstrated in the field. Working in sagebrush-steppe, where water and nitrogen limit plant growth and reproduction and where HL occurs naturally during summer drought, we slightly augmented deep soil water availability to 14 HL+ treatment plants throughout the summer growing season. The HL+ sagebrush lifted greater amounts of water than control plants and had slightly less negative predawn and midday leaf water potentials. Soil respiration was also augmented under HL+ plants. At summer's end, application of a gasbased 15 N isotopic labeling technique revealed increased rates of nitrogen cycling in surface soil layers around HL+ plants and increased uptake of nitrogen into HL+ plants' inflorescences as sagebrush set seed. These treatment effects persisted even though unexpected monsoon rainstorms arrived during assays and increased surface soil moisture around all plants. Simulation models from ecosystem to global scales have just begun to include effects of hydraulic redistribution on water and surface energy fluxes. Results from this field study indicate that plants carrying out HL can also substantially enhance decomposition and nitrogen cycling in surface soils.rhizosphere | flowering | seed production
Summary Linking microbial activity with ecosystem function is a continuing goal among ecologists focusing their efforts below ground in terrestrial ecosystems. Genomic approaches, using DNA and RNA extracted from soil to characterize types of microbes present and genes expressed in soil, are promising, but, the required destructive harvest confounds spatial and temporal information. Microbiosensors offer a gene‐based way to examine microbial perception of, and response to, the soil environment non‐destructively, with high spatial and temporal resolution. In this mini‐review, we explore the promise, challenges and tradeoffs associated with the design and deployment of microbiosensors in soil, as well as the interpretation of information derived from them ‘live from the soil grain’. Both the promises and challenges are caused by the facts that: micro‐biosensors are living organisms with specific traits; they come from a phylogenetically diverse but restricted subsample of enormous soil microbial diversity; they are responsive to internal and external influences on multiple cellular processes (not just promoter induction); and they become part of food chains in non‐sterile soils. We examine each of these characteristics, and associated blessings and curses, in the context of using microbiosensors to explore microbial soil ecology.
Water availability and movement in soil are critical determinants of resource availability to, and interactions among, members of the soil community. However, it has been impossible to observe gradients in soil water potential empirically at millimetre spatial scales. Here we describe progress towards that goal using output from two microbial biosensors, Pantoea agglomerans BRT98/pPProGreen and Pseudomonas putida KT2442/pPProGreen, engineered with a reporter system based on the osmotically sensitive proU promoter from Escherichia coli. The proU-GFP construct in both microbiosensors produced green fluorescent protein (GFP) as a function total water potential in nonsterile soil. Controlled experiments in liquid culture showed that dramatically different microbiosensor growth rates (resulting from exposure to different salts as osmolytes) did not alter the GFP output as a function of water potential in either sensor, but P. agglomerans' GFP levels at a given water potential were strongly influenced by the type of carbon (energy) source available to the microbes. In non-sterile rhizosphere soil along Zea mays L. roots, though GFP expression was quite variable, microbiosensors reported statistically significantly more negative soil water potentials as a function of axial distance from root tips, reflecting the gradient in soil water potential hypothesized to develop during transpiration.
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