Greater sexual reproduction contributes to differences in demography of invasive plants and their noninvasive relatives

An understanding of the demographic processes contributing to invasions would improve our mechanistic understanding of the invasion process and improve the efficiency of prevention and control efforts. However, field comparisons of the demography of invasive and noninvasive species have not previously been conducted. We compared the in situ demography of 17 introduced plant species in St. Louis, Missouri, USA, to contrast the demographic patterns of invasive species with their less invasive relatives across a broad sample of angiosperms. Using herbarium records to estimate spread rates, we found higher maximum spread rates in the landscape for species classified a priori as invasive than for noninvasive introduced species, suggesting that expert classifications are an accurate reflection of invasion rate. Across 17 species, projected population growth was not significantly greater in invasive than in noninvasive introduced species. Among five taxonomic pairs of close relatives, however, four of the invasive species had higher projected population growth rates compared with their noninvasive relative. A Life Table Response Experiment suggested that the greater projected population growth rate of some invasive species relative to their noninvasive relatives was primarily a result of sexual reproduction. The greater sexual reproduction of invasive species is consistent with invaders having a life history strategy more reliant on fecundity than survival and is consistent with a large role of propagule pressure in invasion. Sexual reproduction is a key demographic correlate of invasiveness, suggesting that local processes influencing sexual reproduction, such as enemy escape, might be of general importance. However, the weak correlation of projected population growth with spread rates in the landscape suggests that regional processes, such as dispersal, may be equally important in determining invasion rate

Standardized NEON organismal data for biodiversity research

Understanding patterns and drivers of species distribution and abundance, and thus biodiversity, is a core goal of ecology. Despite advances in recent decades, research into these patterns and processes is currently limited by a lack of standardized, high-quality, empirical data that span large spatial scales and long time periods. The NEON fills this gap by providing freely available observational data that are generated during robust and consistent organismal sampling of several sentinel taxonomic groups within 81 sites distributed across the United States and will be collected for at least 30 years. The breadth and scope of these data provide a unique resource for advancing biodiversity research. To maximize the potential of this opportunity, however, it is critical that NEON data be maximally accessible and easily integrated into investigators\u27 workflows and analyses. To facilitate its use for biodiversity research and synthesis, we created a workflow to process and format NEON organismal data into the ecocomDP (ecological community data design pattern) format that were available through the ecocomDP R package; we then provided the standardized data as an R data package (neonDivData). We briefly summarize sampling designs and data wrangling decisions for the major taxonomic groups included in this effort. Our workflows are open-source so the biodiversity community may: add additional taxonomic groups; modify the workflow to produce datasets appropriate for their own analytical needs; and regularly update the data packages as more observations become available. Finally, we provide two simple examples of how the standardized data may be used for biodiversity research. By providing a standardized data package, we hope to enhance the utility of NEON organismal data in advancing biodiversity research and encourage the use of the harmonized ecocomDP data design pattern for community ecology data from other ecological observatory networks

Harnessing the NEON data revolution to advance open environmental science with a diverse and data-capable community

It is a critical time to reflect on the National Ecological Observatory Network (NEON) science to date as well as envision what research can be done right now with NEON (and other) data and what training is needed to enable a diverse user community. NEON became fully operational in May 2019 and has pivoted from planning and construction to operation and maintenance. In this overview, the history of and foundational thinking around NEON are discussed. A framework of open science is described with a discussion of how NEON can be situated as part of a larger data constellation—across existing networks and different suites of ecological measurements and sensors. Next, a synthesis of early NEON science, based on >100 existing publications, funded proposal efforts, and emergent science at the very first NEON Science Summit (hosted by Earth Lab at the University of Colorado Boulder in October 2019) is provided. Key questions that the ecology community will address with NEON data in the next 10 yr are outlined, from understanding drivers of biodiversity across spatial and temporal scales to defining complex feedback mechanisms in human–environmental systems. Last, the essential elements needed to engage and support a diverse and inclusive NEON user community are highlighted: training resources and tools that are openly available, funding for broad community engagement initiatives, and a mechanism to share and advertise those opportunities. NEON users require both the skills to work with NEON data and the ecological or environmental science domain knowledge to understand and interpret them. This paper synthesizes early directions in the community’s use of NEON data, and opportunities for the next 10 yr of NEON operations in emergent science themes, open science best practices, education and training, and community building

Plant-microbial interactions are strong determinants of plant population and community dynamics

Plant-microbial interactions are ubiquitous and yet the consequences of these interactions on plant population and community dynamics are relatively unknown. Here, we used two different classes of plant-microbial interactions to examine their effects on key plant population and community characteristics such as commonness and rarity, competition and coexistence, as well as community stability. Vertically-transmitted endophytes had stage-dependent effects on the population growth of two grass species Poa sylvestris and Poa alsodes, and generally increased host population growth rates. However, it was the intrinsic demographic advantage of P. sylvestris that allowed its population to grow at a much faster rate compared to P. alsodes rather than endophyte benefits. In a greenhouse experiment, we showed that plant-soil microbial feedbacks were important in regulating the strength of self-limitation, or negative frequency dependence, of a strong competitor Bouteloua gracilis. These negative feedbacks increased the potential for its coexistence with Bouteloua eriopoda. In a field experiment, we showed that fungal-driven plant-soil feedbacks between B. gracilis and B. eriopoda may help explain long term patterns of spatial variation in temporal stability between these two species. Negative plant-soil feedbacks for B. gracilis could promote locally stable plant communities, and this effect was stronger when it was at low frequency in the community. Finally, next-generation sequencing of root-associated fungal communities from the two preceding studies revealed strong differences in composition among different growth conditions as well as cultivation periods. In addition, experimental inoculation methods in the greenhouse and field reliably altered the root-associated fungal communities of test plants

Minimal Effects of an Invasive Flowering Shrub on the Pollinator Community of Native Forbs

<div><p>Biological invasions can strongly influence species interactions such as pollination. Most of the documented effects of exotic plant species on plant-pollinator interactions have been observational studies using single pairs of native and exotic plants, and have focused on dominant exotic plant species. We know little about how exotic plants alter interactions in entire communities of plants and pollinators, especially at low to medium invader densities. In this study, we began to address these gaps by experimentally removing the flowers of a showy invasive shrub, <i>Rosa multiflora</i>, and evaluating its effects on the frequency, richness, and composition of bee visitors to co-flowering native plants. We found that while <i>R. multiflora</i> increased plot-level richness of bee visitors to co-flowering native plant species at some sites, its presence had no significant effects on bee visitation rate, visitor richness, bee community composition, or abundance overall. In addition, we found that compared to co-flowering natives, <i>R. multiflora</i> was a generalist plant that primarily received visits from generalist bee species shared with native plant species. Our results suggest that exotic plants such as <i>R. multiflora</i> may facilitate native plant pollination in a community context by attracting a more diverse assemblage of pollinators, but have limited and idiosyncratic effects on the resident plant-pollinator network in general.</p></div

Comparison of species community composition of bee visitors to native forbs across plots and sites.

<p>NMDS of all control and treatment plots. Control plots (<i>R. multiflora</i> flowers present) are filled, and treatment plots <i>(R. multiflora</i> flowers absent) are open; sites are represented by different symbols. Pollinator community composition was better predicted by experimental site, and the <i>R. multiflora</i> removal treatment did not systematically affect pollinator community composition in each plot.</p

Study plant species and their attributes.

<p>Study plant species and their attributes.</p

Bee visitation rate and visitor richness to <i>R. multiflora</i> and native forbs.

<p><b>A</b>) Visitation rate of bee visitors to <i>R. multiflora</i> and native plants across all sites. Errors indicate SE. Native plants in control and treatment plots were combined. All estimates of visitation rate significantly differed from each other (p<0.05) based on a randomization test. Sample sizes for each estimate are labeled at the bottom of each bar. <b>B</b>) Rarefied bee visitor richness to each plant species across all sites. Letters indicate groupings by 95% confidence intervals.</p

Comparison of bee visitation rate and visitor richness in control and treatment plots.

<p>Visualization of paired t-tests in <b>A</b>) bee visitation rate and <b>B</b>) bee visitor richness to native plants in paired plots at each site. The bee visitor richness trend at CulpB runs contrary to the other four sites.</p

Climate Disruption of Plant-Microbe Interactions

Interactions between plants and microbes have important influences on evolutionary processes, population dynamics, community structure, and ecosystem function. We review the literature to document how climate change may disrupt these ecological interactions and develop a conceptual framework to integrate the pathways of plant-microbe responses to climate over different scales in space and time. We then create a blueprint to aid generalization that categorizes climate effects into changes in the context dependency of plant-microbe pairs, temporal mismatches and altered feedbacks over time, or spatial mismatches that accompany species range shifts. We pair a new graphical model of how plant-microbe interactions influence resistance to climate change with a statistical approach to predictthe consequences of increasing variability in climate. Finally, we suggest pathways through which plant-microbe interactions can affect resilience during recovery from climate disruption. Throughout, we take a forward-looking perspective, highlighting knowledge gaps and directions for future research.Fil: Rudgers, Jennifer A.. University of New Mexico; Estados UnidosFil: Afkhami, Michelle E.. University of Miami; Estados UnidosFil: Bell Dereske, Lukas. Michigan State University; Estados UnidosFil: Chung, Y. Anny. University of Georgia; Estados UnidosFil: Crawford, Kerri M.. University Of Houston; Estados UnidosFil: Kivlin, Stephanie N.. University of Tennessee; Estados UnidosFil: Mann, Michael A.. University of New Mexico; Estados UnidosFil: Nuñez, Martin Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentin