Hemiparasitic plants increase alpine plant richness and evenness but reduce arbuscular mycorrhizal fungal colonization in dominant plant species

Hemiparasitic plants increase plant biodiversity by reducing the abundance of dominant plant species, allowing for the establishment of subordinate species. Hemiparasites reduce host resources by directly removing nutrients from hosts, competing for light and space, and may indirectly reduce host resources by disrupting plant associations with symbiotic root fungi, like arbuscular mycorrhizal fungi and dark-septate endophytes. Here, we explored how a generalist hemiparasite, Castilleja, influences plant richness, evenness, community composition, and mycorrhizal colonization patterns across a ∼1,000 m elevational gradient in the North American Rocky Mountains. We hypothesized that the presence of Castilleja would be associated with increased plant richness and evenness, shaping plant community composition, and would reduce mycorrhizal colonization within dominant plant taxa. However, the magnitude of the effects would be contingent upon climate contexts, that is, elevation. Overall, we found that the presence of Castilleja was associated with an 11% increase in plant richness and a 5% increase in plant evenness, regardless of elevation. However, we found that the presence of Castilleja influenced plant composition at only two of the five sites and at the remaining three of five sites, plot pairing was the only predictor that influenced composition. Additionally, we found that the presence of Castilleja reduced mycorrhizal fungal colonization within dominant plant species by ∼20%, regardless of elevation. Taken together, our results suggest that hemiparasites regulate plant diversity, evenness, and interactions with mycorrhizal fungi independent of abiotic and biotic contexts occurring at the site, although overall effect on community composition is likely driven by site-level factors

Root bacterial endophytes alter plant phenotype, but not physiology

Plant traits, such as root and leaf area, influence how plants interact with their environment and the diverse microbiota living within plants can influence plant morphology and physiology. Here, we explored how three bacterial strains isolated from the Populus root microbiome, influenced plant phenotype. We chose three bacterial strains that differed in predicted metabolic capabilities, plant hormone production and metabolism, and secondary metabolite synthesis. We inoculated each bacterial strain on a single genotype of Populus trichocarpa and measured the response of plant growth related traits (root:shoot, biomass production, root and leaf growth rates) and physiological traits (chlorophyll content, net photosynthesis, net photosynthesis at saturating light–Asat, and saturating CO2–Amax). Overall, we found that bacterial root endophyte infection increased root growth rate up to 184% and leaf growth rate up to 137% relative to non-inoculated control plants, evidence that plants respond to bacteria by modifying morphology. However, endophyte inoculation had no influence on total plant biomass and photosynthetic traits (net photosynthesis, chlorophyll content). In sum, bacterial inoculation did not significantly increase plant carbon fixation and biomass, but their presence altered where and how carbon was being allocated in the plant host

Root Bacterial Endophytes Alter Plant Phenotype, but not Physiology

Plant traits, such as root and leaf area, influence how plants interact with their environment and the diverse microbiota living within plants can influence plant morphology and physiology. Here, we explored how three bacterial strains isolated from the Populus root microbiome, influenced plant phenotype. We chose three bacterial strains that differed in predicted metabolic capabilities, plant hormone production and metabolism, and secondary metabolite synthesis. We inoculated each bacterial strain on a single genotype of Populus trichocarpa and measured the response of plant growth related traits (root:shoot, biomass production, root and leaf growth rates) and physiological traits (chlorophyll content, net photosynthesis, net photosynthesis at saturating light–Asat, and saturating CO2–Amax). Overall, we found that bacterial root endophyte infection increased root growth rate up to 184% and leaf growth rate up to 137% relative to non-inoculated control plants, evidence that plants respond to bacteria by modifying morphology. However, endophyte inoculation had no influence on total plant biomass and photosynthetic traits (net photosynthesis, chlorophyll content). In sum, bacterial inoculation did not significantly increase plant carbon fixation and biomass, but their presence altered where and how carbon was being allocated in the plant host

Adopting a multi-systems approach: examining the academic belongingness of first-generation college students with multiple stigmatized identities in STEM

First-generation college students often experience greater social alienation and marginalization due to a mismatch of their cultural values compared to those of their university and often report lower academic satisfaction and sense of belonging. The effects on sense of belonging and satisfaction are intensified when first-generation college students have identities that intersect with other stigmatized social and cultural identities, like low socioeconomic status, Black or Latinx racial identities or religious identities, specifically for STEM majors. Students’ holistic health and well-being, including their sense of belonging, is highly correlated to their academic achievement, persistence, and overall student success, especially for underrepresented minority groups. However, there has been limited consideration for the nuanced experiences of first-generation college students with multiple stigmatized identities, and for how the academic STEM environment shapes student’s perceptions of inclusivity considering their social identities. To address these concerns, we used the Bioecological Systems theory to contextualize drivers of sense of belonging for students with stigmatized social and cultural identities by allowing space to explicitly consider institutional, departmental, classroom and societal-level phenomena that may operate to erode or fortify belonging for some individuals over others. Findings were organized contextually first, revealing how broader societal and familial values shaped their perceptions of their first-generation identity. Next, we reported how various forms of engagement and interactions with institutional agents impacted their perceptions of support at the institutional level. We then documented behavioral patterns within STEM departments that culminated to reveal how first-generation college students’ sense of belonging was impacted by perceived departmental culture. Last, we revealed interactions within STEM classrooms that signaled inclusivity through humanizing and intentional pedagogical practices. Infused throughout all findings are instances where student experiences were mediated through their multiple identities and were shaped by dual global pandemics of 2020, that being COVID-19 and the racial unrest resurfaced by the murder of George Floyd. Implications for this work have the potential to restructure how institutions provide support for first-generation college students given the salience of their intersecting stigmatized identities in shaping their institutional, disciplinary, and classroom belonging

Plant-soil interactions promote co-occurrence of three nonnative woody shrubs

Abstract. Ecosystems containing multiple nonnative plant species are common, but mechanisms promoting their co-occurrence are understudied. Plant-soil interactions contribute to the dominance of singleton species in nonnative ranges because many nonnatives experience stronger positive feedbacks relative to co-occurring natives. Plant-soil interactions could impede other nonnatives if an individual nonnative benefits from its soil community to a greater extent than its neighboring nonnatives, as is seen with natives. However, plant-soil interactions could promote nonnative co-occurrence if a nonnative accumulates beneficial soil mutualists that also assist other nonnatives. Here, we use greenhouse and field experiments to ask whether plant-soil interactions (1) promote the codominance of two common nonnative shrubs (Ligustrum sinense and Lonicera maackii ) and (2) facilitate the invasion of a lesscommon nonnative shrub (Rhamnus davurica) in deciduous forests of the southeastern United States. In the greenhouse, we found that two of the nonnatives, L. maackii and R. davurica, performed better in soils conditioned by nonnative shrubs compared to uninvaded forest soils, which suggests that positive feedbacks among co-occurring nonnative shrubs can promote continued invasion of a site. In both greenhouse and field experiments, we found consistent signals that the codominance of the nonnatives L. sinense and L. maackii may be at least partially explained by the increased growth of L. sinense in L. maackii soils. Overall, significant effects of plant-soil interactions on shrub performance indicate that plant-soil interactions can potentially structure the co-occurrence patterns of these nonnatives

Integrating natural gradients, experiments, and statistical modeling in a distributed network experiment: An example from the WaRM Network

A growing body of work examines the direct and indirect effects of climate change on ecosystems, typically by using manipulative experiments at a single site or performing meta-analyses across many independent experiments. However, results from single-site studies tend to have limited generality. Although meta-analytic approaches can help overcome this by exploring trends across sites, the inherent limitations in combining disparate datasets from independent approaches remain a major challenge. In this paper, we present a globally distributed experimental network that can be used to disentangle the direct and indirect effects of climate change. We discuss how natural gradients, experimental approaches, and statistical techniques can be combined to best inform predictions about responses to climate change, and we present a globally distributed experiment that utilizes natural environmental gradients to better understand long-term community and ecosystem responses to environmental change. The warming and (species) removal in mountains (WaRM) network employs experimental warming and plant species removals at high- and low-elevation sites in a factorial design to examine the combined and relative effects of climatic warming and the loss of dominant species on community structure and ecosystem function, both above- and belowground. The experimental design of the network allows for increasingly common statistical approaches to further elucidate the direct and indirect effects of warming. We argue that combining ecological observations and experiments along gradients is a powerful approach to make stronger predictions of how ecosystems will function in a warming world as species are lost, or gained, in local communities

Integrating natural gradients, experiments, and statistical modeling in a distributed network experiment: An example from the WaRM Network

A growing body of work examines the direct and indirect effects of climate change on ecosystems, typically by using manipulative experiments at a single site or performing meta-analyses across many independent experiments. However, results from single-site studies tend to have limited generality. Although meta-analytic approaches can help overcome this by exploring trends across sites, the inherent limitations in combining disparate datasets from independent approaches remain a major challenge. In this paper, we present a globally distributed experimental network that can be used to disentangle the direct and indirect effects of climate change. We discuss how natural gradients, experimental approaches, and statistical techniques can be combined to best inform predictions about responses to climate change, and we present a globally distributed experiment that utilizes natural environmental gradients to better understand long-term community and ecosystem responses to environmental change. The warming and (species) removal in mountains (WaRM) network employs experimental warming and plant species removals at high- and low-elevation sites in a factorial design to examine the combined and relative effects of climatic warming and the loss of dominant species on community structure and ecosystem function, both above- and belowground. The experimental design of the network allows for increasingly common statistical approaches to further elucidate the direct and indirect effects of warming. We argue that combining ecological observations and experiments along gradients is a powerful approach to make stronger predictions of how ecosystems will function in a warming world as species are lost, or gained, in local communities

Temporal rarity is a better predictor of local extinction risk than spatial rarity

Spatial rarity is often used to predict extinction risk, but rarity can also occur temporally. Perhaps more relevant in the context of global change is whether a species is core to a community (persistent) or transient (intermittently present), with transient species often susceptible to human activities that reduce niche space. Using 5–12 yr of data on 1,447 plant species from 49 grasslands on five continents, we show that local abundance and species persistence under ambient conditions are both effective predictors of local extinction risk following experimental exclusion of grazers or addition of nutrients; persistence was a more powerful predictor than local abundance. While perturbations increased the risk of exclusion for low persistence and abundance species, transient but abundant species were also highly likely to be excluded from a perturbed plot relative to ambient conditions. Moreover, low persistence and low abundance species that were not excluded from perturbed plots tended to have a modest increase in abundance following perturbance. Last, even core species with high abundances had large decreases in persistence and increased losses in perturbed plots, threatening the long-term stability of these grasslands. Our results demonstrate that expanding the concept of rarity to include temporal dynamics, in addition to local abundance, more effectively predicts extinction risk in response to environmental change than either rarity axis predicts alone.Fil: Wilfahrt, Peter A.. University of Minnesota; Estados UnidosFil: Asmus, Ashley L.. University of Minnesota; Estados UnidosFil: Seabloom, Eric. University of Minnesota; Estados UnidosFil: Henning, Jeremiah A.. University of Minnesota; Estados UnidosFil: Adler, Peter. State University of Utah; Estados UnidosFil: Arnillas, Carlos A.. University of Toronto Scarborough; CanadáFil: Bakker, Jonathan. University of Washington; Estados UnidosFil: Biederman, Lori. University of Iowa; Estados UnidosFil: Brudvig, Lars A.. Michigan State University; Estados UnidosFil: Cadotte, Marc W.. University of Toronto Scarborough; CanadáFil: Daleo, Pedro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Marinas y Costeras. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Marinas y Costeras; ArgentinaFil: Eskelinen, Anu. German Centre for Integrative Biodiversity Research; AlemaniaFil: Firn, Jennifer. University of Queensland; AustraliaFil: Harpole, W. Stanley. German Centre for Integrative Biodiversity Research; Alemania. Helmholtz Centre for Environmental Research; Alemania. Martin Luther University Halle-Wittenberg; AlemaniaFil: Hautier, Yann. Utrecht University; Países BajosFil: Kirkman, Kevin P.. University of KwaZulu-Natal; SudáfricaFil: Komatsu, Kimberly J.. Smithsonian Environmental Research Center; Estados UnidosFil: Laungani, Ramesh. Doane University; Estados UnidosFil: MacDougall, Andrew. University of Guelph; CanadáFil: McCulley, Rebecca L.. University of Kentucky; Estados UnidosFil: Moore, Joslin L.. Monash University; AustraliaFil: Morgan, John W.. La Trobe University; AustraliaFil: Mortensen, Brent. Benedictine College; Estados UnidosFil: Ochoa Hueso, Raul. Universidad de Cádiz; EspañaFil: Ohlert, Timothy. University of New Mexico; Estados UnidosFil: Power, Sally A.. University of Western Sydney; AustraliaFil: Price, Jodi. Charles Sturt University; AustraliaFil: Risch, Anita C.. Swiss Federal Institute for Forest, Snow and Landscape Research; SuizaFil: Schuetz, Martin. Swiss Federal Institute for Forest, Snow and Landscape Research; SuizaFil: Shoemaker, Lauren. University of Wyoming; Estados UnidosFil: Stevens, Carly. Lancaster University; Reino UnidoFil: Strauss, Alexander T.. University of Minnesota; Estados Unidos. University of Georgia; Estados UnidosFil: Tognetti, Pedro Maximiliano. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; ArgentinaFil: Virtanen, Risto. University of Oulu; FinlandiaFil: Borer, Elizabeth. University of Minnesota; Estados Unido

Dark sectors 2016 Workshop: community report

This report, based on the Dark Sectors workshop at SLAC in April 2016, summarizes the scientific importance of searches for dark sector dark matter and forces at masses beneath the weak-scale, the status of this broad international field, the important milestones motivating future exploration, and promising experimental opportunities to reach these milestones over the next 5-10 years

US Cosmic Visions: New Ideas in Dark Matter 2017: Community Report

This white paper summarizes the workshop "U.S. Cosmic Visions: New Ideas in Dark Matter" held at University of Maryland on March 23-25, 2017.Comment: 102 pages + reference