193 research outputs found

    General Destabilizing Effects of Eutrophication on Grassland Productivity at Multiple Spatial Scales

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    Eutrophication is a widespread environmental change that usually reduces the stabilizing effect of plant diversity on productivity in local communities. Whether this effect is scale dependent remains to be elucidated. Here, we determine the relationship between plant diversity and temporal stability of productivity for 243 plant communities from 42 grasslands across the globe and quantify the effect of chronic fertilization on these relationships. Unfertilized local communities with more plant species exhibit greater asynchronous dynamics among species in response to natural environmental fluctuations, resulting in greater local stability (alpha stability). Moreover, neighborhood communities that have greater spatial variation in plant species composition within sites (higher beta diversity) have greater spatial asynchrony of productivity among communities, resulting in greater stability at the larger scale (gamma stability). Importantly, fertilization consistently weakens the contribution of plant diversity to both of these stabilizing mechanisms, thus diminishing the positive effect of biodiversity on stability at differing spatial scales. Our findings suggest that preserving grassland functional stability requires conservation of plant diversity within and among ecological communities

    Genome-Wide Association Study and Gene Expression Analysis Identifies CD84 as a Predictor of Response to Etanercept Therapy in Rheumatoid Arthritis

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    Anti-tumor necrosis factor alpha (anti-TNF) biologic therapy is a widely used treatment for rheumatoid arthritis (RA). It is unknown why some RA patients fail to respond adequately to anti-TNF therapy, which limits the development of clinical biomarkers to predict response or new drugs to target refractory cases. To understand the biological basis of response to anti-TNF therapy, we conducted a genome-wide association study (GWAS) meta-analysis of more than 2 million common variants in 2,706 RA patients from 13 different collections. Patients were treated with one of three anti-TNF medications: etanercept (n = 733), infliximab (n = 894), or adalimumab (n = 1,071). We identified a SNP (rs6427528) at the 1q23 locus that was associated with change in disease activity score (ΔDAS) in the etanercept subset of patients (P = 8×10-8), but not in the infliximab or adalimumab subsets (P>0.05). The SNP is predicted to disrupt transcription factor binding site motifs in the 3′ UTR of an immune-related gene, CD84, and the allele associated with better response to etanercept was associated with higher CD84 gene expression in peripheral blood mononuclear cells (P = 1×10-11 in 228 non-RA patients and P = 0.004 in 132 RA patients). Consistent with the genetic findings, higher CD84 gene expression correlated with lower cross-sectional DAS (P = 0.02, n = 210) and showed a non-significant trend for better ΔDAS in a subset of RA patients with gene expression data (n = 31, etanercept-treated). A small, multi-ethnic replication showed a non-significant trend towards an association among etanercept-treated RA patients of Portuguese ancestry (n = 139, P = 0.4), but no association among patients of Japanese ancestry (n = 151, P = 0.8). Our study demonstrates that an allele associated with response to etanercept therapy is also associated with CD84 gene expression, and further that CD84 expression correlates with disease activity. These findings support a model in which CD84 genotypes and/or expression may serve as a useful biomarker for response to etanercept treatment in RA patients of European ancestry. © 2013 Cui et al

    Linking changes in species composition and biomass in a globally distributed grassland experiment

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    Global change drivers, such as anthropogenic nutrient inputs, are increasing globally. Nutrient deposition simultaneously alters plant biodiversity, species composition and ecosystem processes like aboveground biomass production. These changes are underpinned by species extinction, colonisation and shifting relative abundance. Here, we use the Price equation to quantify and link the contributions of species that are lost, gained or that persist to change in aboveground biomass in 59 experimental grassland sites. Under ambient (control) conditions, compositional and biomass turnover was high, and losses (i.e. local extinctions) were balanced by gains (i.e. colonisation). Under fertilisation, the decline in species richness resulted from increased species loss and decreases in species gained. Biomass increase under fertilisation resulted mostly from species that persist and to a lesser extent from species gained. Drivers of ecological change can interact relatively independently with diversity, composition and ecosystem processes and functions such as aboveground biomass due to the individual contributions of species lost, gained or persisting.Fil: Ladouceur, Emma. Martin Luther University Halle-Wittenberg; Alemania. Universitat Leipzig; Alemania. German Centre for Integrative Biodiversity Research (iDiv) Leipzig-Halle-Jena; AlemaniaFil: Blowes, Shane A.. Martin Luther University Halle-Wittenberg; Alemania. German Centre for Integrative Biodiversity Research (iDiv) Leipzig-Halle-Jena; AlemaniaFil: Chase, Jonathan M.. German Centre for Integrative Biodiversity Research (iDiv) Leipzig-Halle-Jena; Alemania. Martin Luther University Halle-Wittenberg; AlemaniaFil: Clark, Adam T.. Martin Luther University Halle-Wittenberg; Alemania. German Centre for Integrative Biodiversity Research (iDiv) Leipzig-Halle-Jena; Alemania. University of Graz; AustriaFil: Garbowski, Magda. German Centre for Integrative Biodiversity Research (iDiv) Leipzig-Halle-Jena; Alemania. Universitat Leipzig; AlemaniaFil: Alberti, Juan. 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: Arnillas, Carlos Alberto. University of Toronto; CanadáFil: Bakker, Jonathan. University of Washington; Estados UnidosFil: Barrio, Isabel C.. Agricultural University of Iceland; IslandiaFil: Bharath, Siddharth. Atria University; IndiaFil: Borer, Elizabeth. University of Minnesota; Estados UnidosFil: Brudvig, Lars A.. Michigan State University; Estados UnidosFil: Cadotte, Marc W.. University of Toronto; CanadáFil: Chen, Qingqing. Peking University; ChinaFil: Collins, Scott L.. University of New Mexico; Estados UnidosFil: Dickman, Christopher R.. The University Of Sydney; AustraliaFil: Donohue, Ian. Trinity College Dublin; IrlandaFil: Du, Guozhen. Lanzhou University; ChinaFil: Ebeling, Anne. Universitat Jena; AlemaniaFil: Eisenhauer, Nico. Martin Luther University Halle—Wittenberg; Alemania. German Centre For Integrative Biodiversity Research (idiv) Halle-jena-leipzig; AlemaniaFil: Fay, Philip A.. USDA-ARS Grassland Soil and Water Research Lab; Estados UnidosFil: Hagenah, Nicole. University Of Pretoria; SudáfricaFil: Hautier, Yann. University of Utrecht; Países BajosFil: Jentsch, Anke. University of Bayreuth; AlemaniaFil: Jónsdóttir, Ingibjörg S.. University of Iceland; IslandiaFil: Komatsu, Kimberly J.. Smithsonian Environmental Research Center; Estados UnidosFil: MacDougall, Andrew. University of Guelph; CanadáFil: Martina, Jason P.. Texas State University; Estados UnidosFil: Moore, Joslin L.. Arthur Rylah Institute For Environmental Research; Australia. Monash University; AustraliaFil: Morgan, John W.. La Trobe University; AustraliaFil: Peri, Pablo Luis. Instituto Nacional de Tecnología Agropecuaria; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

    Opposing community assembly patterns for dominant and nondominant plant species in herbaceous ecosystems globally

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    Biotic and abiotic factors interact with dominant plants—the locally most frequent or with the largest coverage—and nondominant plants differently, partially because dominant plants modify the environment where nondominant plants grow. For instance, if dominant plants compete strongly, they will deplete most resources, forcing nondominant plants into a narrower niche space. Conversely, if dominant plants are constrained by the environment, they might not exhaust available resources but instead may ameliorate environmental stressors that usually limit nondominants. Hence, the nature of interactions among nondominant species could be modified by dominant species. Furthermore, these differences could translate into a disparity in the phylogenetic relatedness among dominants compared to the relatedness among nondominants. By estimating phylogenetic dispersion in 78 grasslands across five continents, we found that dominant species were clustered (e.g., co-dominant grasses), suggesting dominant species are likely organized by environmental filtering, and that nondominant species were either randomly assembled or overdispersed. Traits showed similar trends for those sites (\u3c50%) with sufficient trait data. Furthermore, several lineages scattered in the phylogeny had more nondominant species than expected at random, suggesting that traits common in nondominants are phylogenetically conserved and have evolved multiple times. We also explored environmental drivers of the dominant/nondominant disparity. We found different assembly patterns for dominants and nondominants, consistent with asymmetries in assembly mechanisms. Among the different postulated mechanisms, our results suggest two complementary hypotheses seldom explored: (1) Nondominant species include lineages adapted to thrive in the environment generated by dominant species. (2) Even when dominant species reduce resources to nondominant ones, dominant species could have a stronger positive effect on some nondominants by ameliorating environmental stressors affecting them, than by depleting resources and increasing the environmental stress to those nondominants. These results show that the dominant/nondominant asymmetry has ecological and evolutionary consequences fundamental to understand plant communities

    Local Loss and Spatial Homogenization of Plant Diversity Reduce Ecosystem Multifunctionality

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    Biodiversity is declining in many local communities while also becoming increasingly homogenized across space. Experiments show that local plant species loss reduces ecosystem functioning and services, but the role of spatial homogenization of community composition and the potential interaction between diversity at different scales in maintaining ecosystem functioning remains unclear, especially when many functions are considered (ecosystem multifunctionality). We present an analysis of eight ecosystem functions measured in 65 grasslands worldwide. We find that more diverse grasslands—those with both species-rich local communities (α-diversity) and large compositional differences among localities (β-diversity)—had higher levels of multifunctionality. Moreover, α- and β-diversity synergistically affected multifunctionality, with higher levels of diversity at one scale amplifying the contribution to ecological functions at the other scale. The identity of species influencing ecosystem functioning differed among functions and across local communities, explaining why more diverse grasslands maintained greater functionality when more functions and localities were considered. These results were robust to variation in environmental drivers. Our findings reveal that plant diversity, at both local and landscape scales, contributes to the maintenance of multiple ecosystem services provided by grasslands. Preserving ecosystem functioning therefore requires conservation of biodiversity both within and among ecological communities

    Opposing community assembly patterns for dominant and jonnondominant plant species in herbaceous ecosystems globally

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    Biotic and abiotic factors interact with dominant plants—the locally most frequent or with the largest coverage—and nondominant plants differently, partially because dominant plants modify the environment where nondominant plants grow. For instance, if dominant plants compete strongly, they will deplete most resources, forcing nondominant plants into a narrower niche space. Conversely, if dominant plants are constrained by the environment, they might not exhaust available resources but instead may ameliorate environmental stressors that usually limit nondominants. Hence, the nature of interactions among nondominant species could be modified by dominant species. Furthermore, these differences could translate into a disparity in the phylogenetic relatedness among dominants compared to the relatedness among nondominants. By estimating phylogenetic dispersion in 78 grasslands across five continents, we found that dominant species were clustered (e.g., co-dominant grasses), suggesting dominant species are likely organized by environmental filtering, and that nondominant species were either randomly assembled or overdispersed. Traits showed similar trends for those sites (<50%) with sufficient trait data. Furthermore, several lineages scattered in the phylogeny had more nondominant species than expected at random, suggesting that traits common in nondominants are phylogenetically conserved and have evolved multiple times. We also explored environmental drivers of the dominant/nondominant disparity. We found different assembly patterns for dominants and nondominants, consistent with asymmetries in assembly mechanisms. Among the different postulated mechanisms, our results suggest two complementary hypotheses seldom explored: (1) Nondominant species include lineages adapted to thrive in the environment generated by dominant species. (2) Even when dominant species reduce resources to nondominant ones, dominant species could have a stronger positive effect on some nondominants by ameliorating environmental stressors affecting them, than by depleting resources and increasing the environmental stress to those nondominants. These results show that the dominant/nondominant asymmetry has ecological and evolutionary consequences fundamental to understand plant communities.Fil: Arnillas, Carlos Alberto. University of Toronto Scarborough; CanadáFil: Borer, Elizabeth. University of Minnesota; Estados UnidosFil: Seabloom, Eric. University of Minnesota; Estados UnidosFil: Alberti, Juan. 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: Baez, Selene. Escuela Politécnica Nacional; EcuadorFil: Bakker, Jonathan. University of Washington; Estados UnidosFil: Boughton, Elizabeth H.. Archbold Biological Station; Estados UnidosFil: Buckley, Yvonne M.. Trinity College Dublin; IrlandaFil: Bugalho, Miguel Nuno. Universidad de Lisboa; PortugalFil: Donohue, Ian. Trinity College Dublin; IrlandaFil: Dwyer, John. University of Queensland; AustraliaFil: Firn, Jennifer. The University of Queensland; AustraliaFil: Gridzak, Riley. Queens University; CanadáFil: Hagenah, Nicole. University of Pretoria; SudáfricaFil: Hautier, Yann. Utrecht University; Países BajosFil: Helm, Aveliina. University of Tartu; EstoniaFil: Jentsch, Anke. University of Bayreuth; AlemaniaFil: Knops, Johannes M. H.. Xi'an Jiaotong Liverpool University; China. University of Nebraska; Estados UnidosFil: Komatsu, Kimberly J.. Smithsonian Environmental Research Center; Estados UnidosFil: Laanisto, Lauri. Estonian University of Life Sciences; EstoniaFil: Laungani, Ramesh. Poly Prep Country Day School; Estados UnidosFil: McCulley, Rebecca. University of Kentucky; Estados UnidosFil: Moore, Joslin L.. Monash University; AustraliaFil: Morgan, John W.. La Trobe University; AustraliaFil: Peri, Pablo Luis. Universidad Nacional de la Patagonia Austral; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Patagonia Sur. Estación Experimental Agropecuaria Santa Cruz. Agencia de Extensión Rural Río Gallegos; ArgentinaFil: Power, Sally A.. University of Western Sydney; AustraliaFil: Price, Jodi. Charles Sturt University; AustraliaFil: Sankaran, Mahesh. National Centre for Biological Sciences; IndiaFil: Schamp, Brandon. Algoma University; CanadáFil: Speziale, Karina Lilian. 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; ArgentinaFil: Standish, Rachel. Murdoch University; AustraliaFil: Virtanen, Risto. University of Oulu; FinlandiaFil: Cadotte, Marc W.. University of Toronto Scarborough; Canadá. University of Toronto; Canad

    Specificity of the STAT4 Genetic Association for Severe Disease Manifestations of Systemic Lupus Erythematosus

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    Systemic lupus erythematosus (SLE) is a genetically complex disease with heterogeneous clinical manifestations. A polymorphism in the STAT4 gene has recently been established as a risk factor for SLE, but the relationship with specific SLE subphenotypes has not been studied. We studied 137 SNPs in the STAT4 region genotyped in 4 independent SLE case series (total n = 1398) and 2560 healthy controls, along with clinical data for the cases. Using conditional testing, we confirmed the most significant STAT4 haplotype for SLE risk. We then studied a SNP marking this haplotype for association with specific SLE subphenotypes, including autoantibody production, nephritis, arthritis, mucocutaneous manifestations, and age at diagnosis. To prevent possible type-I errors from population stratification, we reanalyzed the data using a subset of subjects determined to be most homogeneous based on principal components analysis of genome-wide data. We confirmed that four SNPs in very high LD (r2 = 0.94 to 0.99) were most strongly associated with SLE, and there was no compelling evidence for additional SLE risk loci in the STAT4 region. SNP rs7574865 marking this haplotype had a minor allele frequency (MAF) = 31.1% in SLE cases compared with 22.5% in controls (OR = 1.56, p = 10−16). This SNP was more strongly associated with SLE characterized by double-stranded DNA autoantibodies (MAF = 35.1%, OR = 1.86, p<10−19), nephritis (MAF = 34.3%, OR = 1.80, p<10−11), and age at diagnosis<30 years (MAF = 33.8%, OR = 1.77, p<10−13). An association with severe nephritis was even more striking (MAF = 39.2%, OR = 2.35, p<10−4 in the homogeneous subset of subjects). In contrast, STAT4 was less strongly associated with oral ulcers, a manifestation associated with milder disease. We conclude that this common polymorphism of STAT4 contributes to the phenotypic heterogeneity of SLE, predisposing specifically to more severe disease

    Belowground biomass response to nutrient enrichment depends on light limitation across globally distributed grasslands

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    Anthropogenic activities are increasing nutrient inputs to ecosystems worldwide, with consequences for global carbon and nutrient cycles. Recent meta-analyses show that aboveground primary production is often co-limited by multiple nutrients; however, little is known about how root production responds to changes in nutrient availability. At twenty-nine grassland sites on four continents, we quantified shallow root biomass responses to nitrogen (N), phosphorus (P) and potassium plus micronutrient enrichment and compared below- and aboveground responses. We hypothesized that optimal allocation theory would predict context dependence in root biomass responses to nutrient enrichment, given variation among sites in the resources limiting to plant growth (specifically light versus nutrients). Consistent with the predictions of optimal allocation theory, the proportion of total biomass belowground declined with N or P addition, due to increased biomass aboveground (for N and P) and decreased biomass belowground (N, particularly in sites with low canopy light penetration). Absolute root biomass increased with N addition where light was abundant at the soil surface, but declined in sites where the grassland canopy intercepted a large proportion of incoming light. These results demonstrate that belowground responses to changes in resource supply can differ strongly from aboveground responses, which could significantly modify predictions of future rates of nutrient cycling and carbon sequestration. Our results also highlight how optimal allocation theory developed for individual plants may help predict belowground biomass responses to nutrient enrichment at the ecosystem scale across wide climatic and environmental gradients
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